Michor Lab Publications
All Publications
2019
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2019. KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance. Cancer cell. 35(2):330-332. Pubmed: 30753830 DOI:S1535-6108(19)30046-7 Hinohara K, Wu HJ, Sébastien Vigneau, McDonald TO, Igarashi KJ, Yamamoto KN, Madsen T, Fassl A, Egri SB, Papanastasiou M, Ding L, Peluffo G, Cohen O, Kales SC, Lal-Nag M, Rai G, Maloney DJ, Jadhav A, Simeonov A, Wagle N, Brown M, Meissner A, Sicinski P, Jaffe JD, Jeselsohn R, Gimelbrant AA, Michor F, Polyak K. 2019. KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance. Cancer cell. 35(2):330-332. Pubmed: 30753830 DOI:S1535-6108(19)30046-7 -
Ferlic J, Shi J, McDonald TO, Michor F. 2019. DIFFpop: a stochastic computational approach to simulate differentiation hierarchies with single cell barcoding. Bioinformatics (Oxford, England). 35(19):3849-3851. Pubmed: 30816920 DOI:10.1093/bioinformatics/btz074 Ferlic J, Shi J, McDonald TO, Michor F. 2019. DIFFpop: a stochastic computational approach to simulate differentiation hierarchies with single cell barcoding. Bioinformatics (Oxford, England). 35(19):3849-3851. Pubmed: 30816920 DOI:10.1093/bioinformatics/btz074 Array© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. -
Yamamoto KN, Liu LL, Nakamura A, Haeno H, Michor F. 2019. Stochastic Evolution of Pancreatic Cancer Metastases During Logistic Clonal Expansion. JCO clinical cancer informatics. 3:1-11. Pubmed: 30901235 DOI:10.1200/CCI.18.00079 Yamamoto KN, Liu LL, Nakamura A, Haeno H, Michor F. 2019. Stochastic Evolution of Pancreatic Cancer Metastases During Logistic Clonal Expansion. JCO clinical cancer informatics. 3:1-11. Pubmed: 30901235 DOI:10.1200/CCI.18.00079 Despite recent progress in diagnostic and multimodal treatment approaches, most cancer deaths are still caused by metastatic spread and the subsequent growth of tumor cells in sites distant from the primary organ. So far, few quantitative studies are available that allow for the estimation of metastatic parameters and the evaluation of alternative treatment strategies. Most computational studies have focused on situations in which the tumor cell population expands exponentially over time; however, tumors may eventually be subject to resource and space limitations so that their growth patterns deviate from exponential growth to adhere to density-dependent growth models. In this study, we developed a stochastic evolutionary model of cancer progression that considers alterations in metastasis-related genes and intercellular growth competition leading to density effects described by logistic growth. Using this stochastic model, we derived analytical approximations for the time between the initiation of tumorigenesis and diagnosis, the expected number of metastatic sites, the total number of metastatic cells, the size of the primary tumor, and survival. Furthermore, we investigated the effects of drug administration and surgical resection on these quantities and predicted outcomes for different treatment regimens. Parameter values used in the analysis were estimated from data obtained from a pancreatic cancer rapid autopsy program. Our theoretical approach allows for flexible modeling of metastatic progression dynamics. -
Yamamoto KN, Nakamura A, Liu LL, Stein S, Tramontano AC, Kartoun U, Shimizu T, Inoue Y, Asakuma M, Haeno H, Kong CY, Uchiyama K, Gonen M, Hur C, Michor F. 2019. Computational modeling of pancreatic cancer patients receiving FOLFIRINOX and gemcitabine-based therapies identifies optimum intervention strategies. PloS one. 14(4):e0215409. Pubmed: 31026288 DOI:10.1371/journal.pone.0215409 Yamamoto KN, Nakamura A, Liu LL, Stein S, Tramontano AC, Kartoun U, Shimizu T, Inoue Y, Asakuma M, Haeno H, Kong CY, Uchiyama K, Gonen M, Hur C, Michor F. 2019. Computational modeling of pancreatic cancer patients receiving FOLFIRINOX and gemcitabine-based therapies identifies optimum intervention strategies. PloS one. 14(4):e0215409. Pubmed: 31026288 DOI:10.1371/journal.pone.0215409 Pancreatic ductal adenocarcinoma (PDAC) exhibits a variety of phenotypes with regard to disease progression and treatment response. This variability complicates clinical decision-making despite the improvement of survival due to the recent introduction of FOLFIRINOX (FFX) and nab-paclitaxel. Questions remain as to the timing and sequence of therapies and the role of radiotherapy for unresectable PDAC. Here we developed a computational analysis platform to investigate the dynamics of growth, metastasis and treatment response to FFX, gemcitabine (GEM), and GEM+nab-paclitaxel. Our approach was informed using data of 1,089 patients treated at the Massachusetts General Hospital and validated using an independent cohort from Osaka Medical College. Our framework establishes a logistic growth pattern of PDAC and defines the Local Advancement Index (LAI), which determines the eventual primary tumor size and predicts the number of metastases. We found that a smaller LAI leads to a larger metastatic burden. Furthermore, our analyses ascertain that i) radiotherapy after induction chemotherapy improves survival in cases receiving induction FFX or with larger LAI, ii) neoadjuvant chemotherapy improves survival in cases with resectable PDAC, and iii) temporary cessations of chemotherapies do not impact overall survival, which supports the feasibility of treatment holidays for patients with FFX-associated adverse effects. Our findings inform clinical decision-making for PDAC patients and allow for the rational design of clinical strategies using FFX, GEM, GEM+nab-paclitaxel, neoadjuvant chemotherapy, and radiation. 2018
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McDonald TO, Chakrabarti S, Michor F. 2018. Currently available bulk sequencing data do not necessarily support a model of neutral tumor evolution. Nature genetics. 50(12):1620-1623. Pubmed: 30374067 DOI:10.1038/s41588-018-0217-6 McDonald TO, Chakrabarti S, Michor F. 2018. Currently available bulk sequencing data do not necessarily support a model of neutral tumor evolution. Nature genetics. 50(12):1620-1623. Pubmed: 30374067 DOI:10.1038/s41588-018-0217-6 -
Altrock PM, Ferlic J, Galla T, Tomasson MH, Michor F. 2018. Computational Model of Progression to Multiple Myeloma Identifies Optimum Screening Strategies. JCO clinical cancer informatics. 2:1-12. Pubmed: 30652561 DOI:10.1200/CCI.17.00131 Altrock PM, Ferlic J, Galla T, Tomasson MH, Michor F. 2018. Computational Model of Progression to Multiple Myeloma Identifies Optimum Screening Strategies. JCO clinical cancer informatics. 2:1-12. Pubmed: 30652561 DOI:10.1200/CCI.17.00131 Array -
Hinohara K, Wu HJ, Vigneau S, McDonald TO, Igarashi KJ, Yamamoto KN, Madsen T, Fassl A, Egri SB, Papanastasiou M, Ding L, Peluffo G, Cohen O, Kales SC, Lal-Nag M, Rai G, Maloney DJ, Jadhav A, Simeonov A, Wagle N, Brown M, Meissner A, Sicinski P, Jaffe JD, Jeselsohn R, Gimelbrant AA, Michor F, Polyak K. 2018. KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance. Cancer cell. 34(6):939-953.e9. Pubmed: 30472020 DOI:S1535-6108(18)30480-X Hinohara K, Wu HJ, Vigneau S, McDonald TO, Igarashi KJ, Yamamoto KN, Madsen T, Fassl A, Egri SB, Papanastasiou M, Ding L, Peluffo G, Cohen O, Kales SC, Lal-Nag M, Rai G, Maloney DJ, Jadhav A, Simeonov A, Wagle N, Brown M, Meissner A, Sicinski P, Jaffe JD, Jeselsohn R, Gimelbrant AA, Michor F, Polyak K. 2018. KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance. Cancer cell. 34(6):939-953.e9. Pubmed: 30472020 DOI:S1535-6108(18)30480-X Members of the KDM5 histone H3 lysine 4 demethylase family are associated with therapeutic resistance, including endocrine resistance in breast cancer, but the underlying mechanism is poorly defined. Here we show that genetic deletion of KDM5A/B or inhibition of KDM5 activity increases sensitivity to anti-estrogens by modulating estrogen receptor (ER) signaling and by decreasing cellular transcriptomic heterogeneity. Higher KDM5B expression levels are associated with higher transcriptomic heterogeneity and poor prognosis in ER breast tumors. Single-cell RNA sequencing, cellular barcoding, and mathematical modeling demonstrate that endocrine resistance is due to selection for pre-existing genetically distinct cells, while KDM5 inhibitor resistance is acquired. Our findings highlight the importance of cellular phenotypic heterogeneity in therapeutic resistance and identify KDM5A/B as key regulators of this process.Copyright © 2018 Elsevier Inc. All rights reserved. -
Van Egeren D, Madsen T, Michor F. 2018. Fitness variation in isogenic populations leads to a novel evolutionary mechanism for crossing fitness valleys. Communications biology. 1:151. Pubmed: 30272027 DOI:10.1038/s42003-018-0160-1 Van Egeren D, Madsen T, Michor F. 2018. Fitness variation in isogenic populations leads to a novel evolutionary mechanism for crossing fitness valleys. Communications biology. 1:151. Pubmed: 30272027 DOI:10.1038/s42003-018-0160-1 Individuals in a population often have different fitnesses even when they have identical genotypes, but the effect of this variation on the evolution of a population through complicated fitness landscapes is unknown. Here, we investigate how populations with non-genetic fitness variation cross fitness valleys, common barriers to adaptation in rugged fitness landscapes in which a population must pass through a deleterious intermediate to arrive at a final advantageous stage. We develop a stochastic computational model describing the dynamics of an asexually reproducing population crossing a fitness valley, in which individuals of the same evolutionary stage can have variable fitnesses. We find that fitness variation that persists over multiple generations increases the rate of valley crossing through a novel evolutionary mechanism different from previously characterized mechanisms such as stochastic tunneling. By reducing the strength of selection against deleterious intermediates, persistent fitness variation allows for faster adaptation through rugged fitness landscapes. -
Jun HJ, Appleman VA, Wu HJ, Rose CM, Pineda JJ, Yeo AT, Delcuze B, Lee C, Gyuris A, Zhu H, Woolfenden S, Bronisz A, Nakano I, Chiocca EA, Bronson RT, Ligon KL, Sarkaria JN, Gygi SP, Michor F, Mitchison TJ, Charest A. 2018. A PDGFRα-driven mouse model of glioblastoma reveals a stathmin1-mediated mechanism of sensitivity to vinblastine. Nature communications. 9(1):3116. Pubmed: 30082792 DOI:10.1038/s41467-018-05036-4 Jun HJ, Appleman VA, Wu HJ, Rose CM, Pineda JJ, Yeo AT, Delcuze B, Lee C, Gyuris A, Zhu H, Woolfenden S, Bronisz A, Nakano I, Chiocca EA, Bronson RT, Ligon KL, Sarkaria JN, Gygi SP, Michor F, Mitchison TJ, Charest A. 2018. A PDGFRα-driven mouse model of glioblastoma reveals a stathmin1-mediated mechanism of sensitivity to vinblastine. Nature communications. 9(1):3116. Pubmed: 30082792 DOI:10.1038/s41467-018-05036-4 Glioblastoma multiforme (GBM) is an aggressive primary brain cancer that includes focal amplification of PDGFRα and for which there are no effective therapies. Herein, we report the development of a genetically engineered mouse model of GBM based on autocrine, chronic stimulation of overexpressed PDGFRα, and the analysis of GBM signaling pathways using proteomics. We discover the tubulin-binding protein Stathmin1 (STMN1) as a PDGFRα phospho-regulated target, and that this mis-regulation confers sensitivity to vinblastine (VB) cytotoxicity. Treatment of PDGFRα-positive mouse and a patient-derived xenograft (PDX) GBMs with VB in mice prolongs survival and is dependent on STMN1. Our work reveals a previously unconsidered link between PDGFRα activity and STMN1, and highlight an STMN1-dependent cytotoxic effect of VB in GBM. -
Stover DG, Gil Del Alcazar CR, Brock J, Guo H, Overmoyer B, Balko J, Xu Q, Bardia A, Tolaney SM, Gelman R, Lloyd M, Wang Y, Xu Y, Michor F, Wang V, Winer EP, Polyak K, Lin NU. 2018. Phase II study of ruxolitinib, a selective JAK1/2 inhibitor, in patients with metastatic triple-negative breast cancer. NPJ breast cancer. 4:10. Pubmed: 29761158 DOI:10.1038/s41523-018-0060-z Stover DG, Gil Del Alcazar CR, Brock J, Guo H, Overmoyer B, Balko J, Xu Q, Bardia A, Tolaney SM, Gelman R, Lloyd M, Wang Y, Xu Y, Michor F, Wang V, Winer EP, Polyak K, Lin NU. 2018. Phase II study of ruxolitinib, a selective JAK1/2 inhibitor, in patients with metastatic triple-negative breast cancer. NPJ breast cancer. 4:10. Pubmed: 29761158 DOI:10.1038/s41523-018-0060-z Preclinical data support a role for the IL-6/JAK2/STAT3 signaling pathway in breast cancer. Ruxolitinib is an orally bioavailable receptor tyrosine inhibitor targeting JAK1 and JAK2. We evaluated the safety and efficacy of ruxolitinib in patients with metastatic breast cancer. This was a non-randomized phase II study enrolling patients with refractory, metastatic triple-negative breast cancer. The primary endpoint was objective response by RECIST 1.1. The study was designed to enroll patients whose archival tumor tissue was pSTAT3-positive (-score >5) by central immunohistochemistry. pSTAT3 staining was available from 171 of 217 consented patients and pSTAT3 -score was positive in 67/171 (39.2%) tumors, suggesting that JAK-STAT activation is frequent. Twenty-three patients including one patient with inflammatory breast cancer were enrolled. Ruxolitinib was well-tolerated with infrequent grade 3 or higher toxicities with fatigue as the most common toxicity. Among 21 patients who received at least one dose of protocol therapy, no objective responses were observed and the study was closed to further accrual. Pharmacodynamic analyses of baseline vs. cycle 2 biopsies suggest on-target activity, including a significant decrease in the proportion of pSTAT3 cells in three patients with paired biopsies and downregulation of JAK-STAT target genes and signatures via transcriptional analyses of 11 total baseline and four metastatic biopsies. Immuno-FISH analyses demonstrate intratumoral heterogeneity of pSTAT3 and amplification. Ruxolitinib, as a single agent, did not meet the primary efficacy endpoint in this refractory patient population despite evidence of on-target activity. -
Karaayvaz M, Cristea S, Gillespie SM, Patel AP, Mylvaganam R, Luo CC, Specht MC, Bernstein BE, Michor F, Ellisen LW. 2018. Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq. Nature communications. 9(1):3588. Pubmed: 30181541 DOI:10.1038/s41467-018-06052-0 Karaayvaz M, Cristea S, Gillespie SM, Patel AP, Mylvaganam R, Luo CC, Specht MC, Bernstein BE, Michor F, Ellisen LW. 2018. Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq. Nature communications. 9(1):3588. Pubmed: 30181541 DOI:10.1038/s41467-018-06052-0 Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conducted single-cell RNA-sequencing (scRNA-seq) of >1500 cells from six primary TNBC. Here, we show that intercellular heterogeneity of gene expression programs within each tumor is variable and largely correlates with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of individual subpopulations. Clustering of gene expression profiles identified distinct subgroups of malignant cells shared by multiple tumors, including a single subpopulation associated with multiple signatures of treatment resistance and metastasis, and characterized functionally by activation of glycosphingolipid metabolism and associated innate immunity pathways. A novel signature defining this subpopulation predicts long-term outcomes for TNBC patients in a large cohort. Collectively, this analysis reveals the functional heterogeneity and its association with genomic evolution in TNBC, and uncovers unanticipated biological principles dictating poor outcomes in this disease. -
Stein S, Zhao R, Haeno H, Vivanco I, Michor F. 2018. Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients. PLoS computational biology. 14(1):e1005924. Pubmed: 29293494 DOI:10.1371/journal.pcbi.1005924 Stein S, Zhao R, Haeno H, Vivanco I, Michor F. 2018. Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients. PLoS computational biology. 14(1):e1005924. Pubmed: 29293494 DOI:10.1371/journal.pcbi.1005924 Human primary glioblastomas (GBM) often harbor mutations within the epidermal growth factor receptor (EGFR). Treatment of EGFR-mutant GBM cell lines with the EGFR/HER2 tyrosine kinase inhibitor lapatinib can effectively induce cell death in these models. However, EGFR inhibitors have shown little efficacy in the clinic, partly because of inappropriate dosing. Here, we developed a computational approach to model the in vitro cellular dynamics of the EGFR-mutant cell line SF268 in response to different lapatinib concentrations and dosing schedules. We then used this approach to identify an effective treatment strategy within the clinical toxicity limits of lapatinib, and developed a partial differential equation modeling approach to study the in vivo GBM treatment response by taking into account the heterogeneous and diffusive nature of the disease. Despite the inability of lapatinib to induce tumor regressions with a continuous daily schedule, our modeling approach consistently predicts that continuous dosing remains the best clinically feasible strategy for slowing down tumor growth and lowering overall tumor burden, compared to pulsatile schedules currently known to be tolerated, even when considering drug resistance, reduced lapatinib tumor concentrations due to the blood brain barrier, and the phenotypic switch from proliferative to migratory cell phenotypes that occurs in hypoxic microenvironments. Our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment schedules in search for optimal dosing strategies for glioblastoma and other cancer types. -
Riester M, Xu Q, Moreira A, Zheng J, Michor F, Downey RJ. 2018. The Warburg effect: persistence of stem-cell metabolism in cancers as a failure of differentiation. Annals of oncology : official journal of the European Society for Medical Oncology. 29(1):264-270. Pubmed: 29045536 DOI:10.1093/annonc/mdx645 Riester M, Xu Q, Moreira A, Zheng J, Michor F, Downey RJ. 2018. The Warburg effect: persistence of stem-cell metabolism in cancers as a failure of differentiation. Annals of oncology : official journal of the European Society for Medical Oncology. 29(1):264-270. Pubmed: 29045536 DOI:10.1093/annonc/mdx645 Array© The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For Permissions, please email: journals.permissions@oup.com. -
Chakrabarti S, Paek AL, Reyes J, Lasick KA, Lahav G, Michor F. 2018. Hidden heterogeneity and circadian-controlled cell fate inferred from single cell lineages. Nature communications. 9(1):5372. Pubmed: 30560953 DOI:10.1038/s41467-018-07788-5 Chakrabarti S, Paek AL, Reyes J, Lasick KA, Lahav G, Michor F. 2018. Hidden heterogeneity and circadian-controlled cell fate inferred from single cell lineages. Nature communications. 9(1):5372. Pubmed: 30560953 DOI:10.1038/s41467-018-07788-5 The origin of lineage correlations among single cells and the extent of heterogeneity in their intermitotic times (IMT) and apoptosis times (AT) remain incompletely understood. Here we developed single cell lineage-tracking experiments and computational algorithms to uncover correlations and heterogeneity in the IMT and AT of a colon cancer cell line before and during cisplatin treatment. These correlations could not be explained using simple protein production/degradation models. Sister cell fates were similar regardless of whether they divided before or after cisplatin administration and did not arise from proximity-related factors, suggesting fate determination early in a cell's lifetime. Based on these findings, we developed a theoretical model explaining how the observed correlation structure can arise from oscillatory mechanisms underlying cell fate control. Our model recapitulated the data only with very specific oscillation periods that fit measured circadian rhythms, thereby suggesting an important role of the circadian clock in controlling cellular fates. -
Cimino PJ, Kim Y, Wu HJ, Alexander J, Wirsching HG, Szulzewsky F, Pitter K, Ozawa T, Wang J, Vazquez J, Arora S, Rabadan R, Levine R, Michor F, Holland EC. 2018. Increased expression provides a selective advantage for gain of whole chromosome 7 in IDH wild-type glioblastoma. Genes & development. 32(7-8):512-523. Pubmed: 29632085 DOI:10.1101/gad.312157.118 Cimino PJ, Kim Y, Wu HJ, Alexander J, Wirsching HG, Szulzewsky F, Pitter K, Ozawa T, Wang J, Vazquez J, Arora S, Rabadan R, Levine R, Michor F, Holland EC. 2018. Increased expression provides a selective advantage for gain of whole chromosome 7 in IDH wild-type glioblastoma. Genes & development. 32(7-8):512-523. Pubmed: 29632085 DOI:10.1101/gad.312157.118 Glioblastoma is the most frequently occurring and invariably fatal primary brain tumor in adults. The vast majority of glioblastomas is characterized by chromosomal copy number alterations, including gain of whole chromosome 7 and loss of whole chromosome 10. Gain of whole chromosome 7 is an early event in gliomagenesis that occurs in proneural-like precursor cells, which give rise to all isocitrate dehydrogenase (IDH) wild-type glioblastoma transcriptional subtypes. () is one gene on chromosome 7 known to drive gliomagenesis, but, given its location near the end of 7p, there are likely several other genes located along chromosome 7 that select for its increased whole-chromosome copy number within glioblastoma cells. To identify other potential genes that could select for gain of whole chromosome 7, we developed an unbiased bioinformatics approach that identified () as a gene whose expression correlated with gain of chromosome 7 and a more aggressive phenotype of the resulting glioma. High expression of in glioblastoma was associated with a proneural gene expression pattern and decreased overall survival in both human proneural and PDGF-driven mouse glioblastoma. Furthermore, overexpression promoted cellular proliferation and potentiated radioresistance. We also found enrichment of expression in recurrent human and mouse glioblastoma at first recurrence after radiotherapy. Overall, this study implicates as a chromosome 7-associated gene-level locus that promotes selection for gain of whole chromosome 7 and an aggressive phenotype in glioblastoma.© 2018 Cimino et al.; Published by Cold Spring Harbor Laboratory Press. 2017
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Smith KS, Liu LL, Ganesan S, Michor F, De S. 2017. Nuclear topology modulates the mutational landscapes of cancer genomes. Nature structural & molecular biology. 24(11):1000-1006. Pubmed: 28967881 DOI:10.1038/nsmb.3474 Smith KS, Liu LL, Ganesan S, Michor F, De S. 2017. Nuclear topology modulates the mutational landscapes of cancer genomes. Nature structural & molecular biology. 24(11):1000-1006. Pubmed: 28967881 DOI:10.1038/nsmb.3474 Nuclear organization of genomic DNA affects processes of DNA damage and repair, yet its effects on mutational landscapes in cancer genomes remain unclear. Here we analyzed genome-wide somatic mutations from 366 samples of six cancer types. We found that lamina-associated regions, which are typically localized at the nuclear periphery, displayed higher somatic mutation frequencies than did the interlamina regions at the nuclear core. This effect was observed even after adjustment for features such as GC percentage, chromatin, and replication timing. Furthermore, mutational signatures differed between the nuclear core and periphery, thus indicating differences in the patterns of DNA-damage or DNA-repair processes. For instance, smoking and UV-related signatures, as well as substitutions at certain motifs, were more enriched in the nuclear periphery. Thus, the nuclear architecture may influence mutational landscapes in cancer genomes beyond the previously described effects of chromatin structure and replication timing. -
Mishima Y, Paiva B, Shi J, Park J, Manier S, Takagi S, Massoud M, Perilla-Glen A, Aljawai Y, Huynh D, Roccaro AM, Sacco A, Capelletti M, Detappe A, Alignani D, Anderson KC, Munshi NC, Prosper F, Lohr JG, Ha G, Freeman SS, Van Allen EM, Adalsteinsson VA, Michor F, San Miguel JF, Ghobrial IM. 2017. The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma. Cell reports. 19(1):218-224. Pubmed: 28380360 DOI:S2211-1247(17)30357-1 Mishima Y, Paiva B, Shi J, Park J, Manier S, Takagi S, Massoud M, Perilla-Glen A, Aljawai Y, Huynh D, Roccaro AM, Sacco A, Capelletti M, Detappe A, Alignani D, Anderson KC, Munshi NC, Prosper F, Lohr JG, Ha G, Freeman SS, Van Allen EM, Adalsteinsson VA, Michor F, San Miguel JF, Ghobrial IM. 2017. The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma. Cell reports. 19(1):218-224. Pubmed: 28380360 DOI:S2211-1247(17)30357-1 The development of sensitive and non-invasive "liquid biopsies" presents new opportunities for longitudinal monitoring of tumor dissemination and clonal evolution. The number of circulating tumor cells (CTCs) is prognostic in multiple myeloma (MM), but there is little information on their genetic features. Here, we have analyzed the genomic landscape of CTCs from 29 MM patients, including eight cases with matched/paired bone marrow (BM) tumor cells. Our results show that 100% of clonal mutations in patient BM were detected in CTCs and that 99% of clonal mutations in CTCs were present in BM MM. These include typical driver mutations in MM such as in KRAS, NRAS, or BRAF. These data suggest that BM and CTC samples have similar clonal structures, as discordances between the two were restricted to subclonal mutations. Accordingly, our results pave the way for potentially less invasive mutation screening of MM patients through characterization of CTCs.Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved. -
Temko D, Cheng YK, Polyak K, Michor F. 2017. Mathematical Modeling Links Pregnancy-Associated Changes and Breast Cancer Risk. Cancer research. 77(11):2800-2809. Pubmed: 28360138 DOI:10.1158/0008-5472.CAN-16-2504 Temko D, Cheng YK, Polyak K, Michor F. 2017. Mathematical Modeling Links Pregnancy-Associated Changes and Breast Cancer Risk. Cancer research. 77(11):2800-2809. Pubmed: 28360138 DOI:10.1158/0008-5472.CAN-16-2504 Recent debate has concentrated on the contribution of bad luck to cancer development. The tight correlation between the number of tissue-specific stem cell divisions and cancer risk of the same tissue suggests that bad luck has an important role to play in tumor development, but the full extent of this contribution remains an open question. Improved understanding of the interplay between extrinsic and intrinsic factors at the molecular level is one promising route to identifying the limits on extrinsic control of tumor initiation, which is highly relevant to cancer prevention. Here, we use a simple mathematical model to show that recent data on the variation in numbers of breast epithelial cells with progenitor features due to pregnancy are sufficient to explain the known protective effect of full-term pregnancy in early adulthood for estrogen receptor-positive (ER) breast cancer later in life. Our work provides a mechanism for this previously ill-understood effect and illuminates the complex influence of extrinsic factors at the molecular level in breast cancer. These findings represent an important contribution to the ongoing research into the role of bad luck in human tumorigenesis. .©2017 American Association for Cancer Research. -
Riester M, Wu HJ, Zehir A, Gönen M, Moreira AL, Downey RJ, Michor F. 2017. Distance in cancer gene expression from stem cells predicts patient survival. PloS one. 12(3):e0173589. Pubmed: 28333954 DOI:10.1371/journal.pone.0173589 Riester M, Wu HJ, Zehir A, Gönen M, Moreira AL, Downey RJ, Michor F. 2017. Distance in cancer gene expression from stem cells predicts patient survival. PloS one. 12(3):e0173589. Pubmed: 28333954 DOI:10.1371/journal.pone.0173589 The degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis. Here we utilized mRNA expression data from 4,413 patient samples with 7 diverse cancer histologies to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors. We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells orients cancers in a clinically coherent fashion. For all histologies analyzed (including carcinomas, sarcomas, and hematologic malignancies), patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. We also found that the genes in all undifferentiated cancers of diverse histologies that were most differentially expressed were associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes. Thus, a stem cell-oriented phylogeny of cancers allows for the derivation of a novel cancer gene expression signature found in all undifferentiated forms of diverse cancer histologies, that is competitive in predicting overall survival in cancer patients compared to previously published prediction models, and is coherent in that gene expression was associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes associated with regulation of the multicellular state. -
Yu HA, Sima C, Feldman D, Liu LL, Vaitheesvaran B, Cross J, Rudin CM, Kris MG, Pao W, Michor F, Riely GJ. 2017. Phase 1 study of twice weekly pulse dose and daily low-dose erlotinib as initial treatment for patients with EGFR-mutant lung cancers. Annals of oncology : official journal of the European Society for Medical Oncology. 28(2):278-284. Pubmed: 28073786 DOI:10.1093/annonc/mdw556 Yu HA, Sima C, Feldman D, Liu LL, Vaitheesvaran B, Cross J, Rudin CM, Kris MG, Pao W, Michor F, Riely GJ. 2017. Phase 1 study of twice weekly pulse dose and daily low-dose erlotinib as initial treatment for patients with EGFR-mutant lung cancers. Annals of oncology : official journal of the European Society for Medical Oncology. 28(2):278-284. Pubmed: 28073786 DOI:10.1093/annonc/mdw556 Array© The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For Permissions, please email: journals.permissions@oup.com. -
Campbell PT, Rebbeck TR, Nishihara R, Beck AH, Begg CB, Bogdanov AA, Cao Y, Coleman HG, Freeman GJ, Heng YJ, Huttenhower C, Irizarry RA, Kip NS, Michor F, Nevo D, Peters U, Phipps AI, Poole EM, Qian ZR, Quackenbush J, Robins H, Rogan PK, Slattery ML, Smith-Warner SA, Song M, VanderWeele TJ, Xia D, Zabor EC, Zhang X, Wang M, Ogino S. 2017. Proceedings of the third international molecular pathological epidemiology (MPE) meeting. Cancer causes & control : CCC. 28(2):167-176. Pubmed: 28097472 DOI:10.1007/s10552-016-0845-z Campbell PT, Rebbeck TR, Nishihara R, Beck AH, Begg CB, Bogdanov AA, Cao Y, Coleman HG, Freeman GJ, Heng YJ, Huttenhower C, Irizarry RA, Kip NS, Michor F, Nevo D, Peters U, Phipps AI, Poole EM, Qian ZR, Quackenbush J, Robins H, Rogan PK, Slattery ML, Smith-Warner SA, Song M, VanderWeele TJ, Xia D, Zabor EC, Zhang X, Wang M, Ogino S. 2017. Proceedings of the third international molecular pathological epidemiology (MPE) meeting. Cancer causes & control : CCC. 28(2):167-176. Pubmed: 28097472 DOI:10.1007/s10552-016-0845-z Molecular pathological epidemiology (MPE) is a transdisciplinary and relatively new scientific discipline that integrates theory, methods, and resources from epidemiology, pathology, biostatistics, bioinformatics, and computational biology. The underlying objective of MPE research is to better understand the etiology and progression of complex and heterogeneous human diseases with the goal of informing prevention and treatment efforts in population health and clinical medicine. Although MPE research has been commonly applied to investigating breast, lung, and colorectal cancers, its methodology can be used to study most diseases. Recent successes in MPE studies include: (1) the development of new statistical methods to address etiologic heterogeneity; (2) the enhancement of causal inference; (3) the identification of previously unknown exposure-subtype disease associations; and (4) better understanding of the role of lifestyle/behavioral factors on modifying prognosis according to disease subtype. Central challenges to MPE include the relative lack of transdisciplinary experts, educational programs, and forums to discuss issues related to the advancement of the field. To address these challenges, highlight recent successes in the field, and identify new opportunities, a series of MPE meetings have been held at the Dana-Farber Cancer Institute in Boston, MA. Herein, we share the proceedings of the Third International MPE Meeting, held in May 2016 and attended by 150 scientists from 17 countries. Special topics included integration of MPE with immunology and health disparity research. This meeting series will continue to provide an impetus to foster further transdisciplinary integration of divergent scientific fields. -
Gibson CJ, Lindsley RC, Tchekmedyian V, Mar BG, Shi J, Jaiswal S, Bosworth A, Francisco L, He J, Bansal A, Morgan EA, Lacasce AS, Freedman AS, Fisher DC, Jacobsen E, Armand P, Alyea EP, Koreth J, Ho V, Soiffer RJ, Antin JH, Ritz J, Nikiforow S, Forman SJ, Michor F, Neuberg D, Bhatia R, Bhatia S, Ebert BL. 2017. Clonal Hematopoiesis Associated With Adverse Outcomes After Autologous Stem-Cell Transplantation for Lymphoma. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 35(14):1598-1605. Pubmed: 28068180 DOI:10.1200/JCO.2016.71.6712 Gibson CJ, Lindsley RC, Tchekmedyian V, Mar BG, Shi J, Jaiswal S, Bosworth A, Francisco L, He J, Bansal A, Morgan EA, Lacasce AS, Freedman AS, Fisher DC, Jacobsen E, Armand P, Alyea EP, Koreth J, Ho V, Soiffer RJ, Antin JH, Ritz J, Nikiforow S, Forman SJ, Michor F, Neuberg D, Bhatia R, Bhatia S, Ebert BL. 2017. Clonal Hematopoiesis Associated With Adverse Outcomes After Autologous Stem-Cell Transplantation for Lymphoma. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 35(14):1598-1605. Pubmed: 28068180 DOI:10.1200/JCO.2016.71.6712 Purpose Clonal hematopoiesis of indeterminate potential (CHIP) is an age-related condition characterized by somatic mutations in the blood of otherwise healthy adults. We hypothesized that in patients undergoing autologous stem-cell transplantation (ASCT) for lymphoma, CHIP at the time of ASCT would be associated with an increased risk of myelodysplastic syndrome and acute myeloid leukemia, collectively termed therapy-related myeloid neoplasm (TMN), and other adverse outcomes. Methods We performed whole-exome sequencing on pre- and post-ASCT samples from 12 patients who developed TMN after autologous transplantation for Hodgkin lymphoma or non-Hodgkin lymphoma and targeted sequencing on cryopreserved aliquots of autologous stem-cell products from 401 patients who underwent ASCT for non-Hodgkin lymphoma between 2003 and 2010. We assessed the effect of CHIP at the time of ASCT on subsequent outcomes, including TMN, cause-specific mortality, and overall survival. Results For six of 12 patients in the exome sequencing cohort, mutations found in the TMN specimen were also detectable in the pre-ASCT specimen. In the targeted sequencing cohort, 120 patients (29.9%) had CHIP at the time of ASCT, which was associated with an increased rate of TMN (10-year cumulative incidence, 14.1% v 4.3% for those with and without CHIP, respectively; P = .002). Patients with CHIP had significantly inferior overall survival compared with those without CHIP (10-year overall survival, 30.4% v 60.9%, respectively; P < .001), including increased risk of death from TMN and cardiovascular disease. Conclusion In patients undergoing ASCT for lymphoma, CHIP at the time of transplantation is associated with inferior survival and increased risk of TMN. -
Malone CF, Emerson C, Ingraham R, Barbosa W, Guerra S, Yoon H, Liu LL, Michor F, Haigis M, Macleod KF, Maertens O, Cichowski K. 2017. mTOR and HDAC Inhibitors Converge on the TXNIP/Thioredoxin Pathway to Cause Catastrophic Oxidative Stress and Regression of RAS-Driven Tumors. Cancer discovery. 7(12):1450-1463. Pubmed: 28963352 DOI:10.1158/2159-8290.CD-17-0177 Malone CF, Emerson C, Ingraham R, Barbosa W, Guerra S, Yoon H, Liu LL, Michor F, Haigis M, Macleod KF, Maertens O, Cichowski K. 2017. mTOR and HDAC Inhibitors Converge on the TXNIP/Thioredoxin Pathway to Cause Catastrophic Oxidative Stress and Regression of RAS-Driven Tumors. Cancer discovery. 7(12):1450-1463. Pubmed: 28963352 DOI:10.1158/2159-8290.CD-17-0177 Although agents that inhibit specific oncogenic kinases have been successful in a subset of cancers, there are currently few treatment options for malignancies that lack a targetable oncogenic driver. Nevertheless, during tumor evolution cancers engage a variety of protective pathways, which may provide alternative actionable dependencies. Here, we identify a promising combination therapy that kills -mutant tumors by triggering catastrophic oxidative stress. Specifically, we show that mTOR and HDAC inhibitors kill aggressive nervous system malignancies and shrink tumors by converging on the TXNIP/thioredoxin antioxidant pathway, through cooperative effects on chromatin and transcription. Accordingly, TXNIP triggers cell death by inhibiting thioredoxin and activating apoptosis signal-regulating kinase 1 (ASK1). Moreover, this drug combination also kills -mutant and -mutant non-small cell lung cancers. Together, these studies identify a promising therapeutic combination for several currently untreatable malignancies and reveal a protective nodal point of convergence between these important epigenetic and oncogenic enzymes. There are no effective therapies for - or -mutant cancers. We show that combined mTOR/HDAC inhibitors kill these RAS-driven tumors by causing catastrophic oxidative stress. This study identifies a promising therapeutic combination and demonstrates that selective enhancement of oxidative stress may be more broadly exploited for developing cancer therapies. .©2017 American Association for Cancer Research. -
Smith ZD, Shi J, Gu H, Donaghey J, Clement K, Cacchiarelli D, Gnirke A, Michor F, Meissner A. 2017. Epigenetic restriction of extraembryonic lineages mirrors the somatic transition to cancer. Nature. 549(7673):543-547. Pubmed: 28959968 DOI:10.1038/nature23891 Smith ZD, Shi J, Gu H, Donaghey J, Clement K, Cacchiarelli D, Gnirke A, Michor F, Meissner A. 2017. Epigenetic restriction of extraembryonic lineages mirrors the somatic transition to cancer. Nature. 549(7673):543-547. Pubmed: 28959968 DOI:10.1038/nature23891 In mammals, the canonical somatic DNA methylation landscape is established upon specification of the embryo proper and subsequently disrupted within many cancer types. However, the underlying mechanisms that direct this genome-scale transformation remain elusive, with no clear model for its systematic acquisition or potential developmental utility. Here, we analysed global remethylation from the mouse preimplantation embryo into the early epiblast and extraembryonic ectoderm. We show that these two states acquire highly divergent genomic distributions with substantial disruption of bimodal, CpG density-dependent methylation in the placental progenitor. The extraembryonic epigenome includes specific de novo methylation at hundreds of embryonically protected CpG island promoters, particularly those that are associated with key developmental regulators and are orthologously methylated across most human cancer types. Our data suggest that the evolutionary innovation of extraembryonic tissues may have required co-option of DNA methylation-based suppression as an alternative to regulation by Polycomb-group proteins, which coordinate embryonic germ-layer formation in response to extraembryonic cues. Moreover, we establish that this decision is made deterministically, downstream of promiscuously used-and frequently oncogenic-signalling pathways, via a novel combination of epigenetic cofactors. Methylation of developmental gene promoters during tumorigenesis may therefore reflect the misappropriation of an innate trajectory and the spontaneous reacquisition of a latent, developmentally encoded epigenetic landscape. -
Maruvka YE, Mouw KW, Karlic R, Parasuraman P, Kamburov A, Polak P, Haradhvala NJ, Hess JM, Rheinbay E, Brody Y, Koren A, Braunstein LZ, D'Andrea A, Lawrence MS, Bass A, Bernards A, Michor F, Getz G. 2017. Analysis of somatic microsatellite indels identifies driver events in human tumors. Nature biotechnology. 35(10):951-959. Pubmed: 28892075 DOI:10.1038/nbt.3966 Maruvka YE, Mouw KW, Karlic R, Parasuraman P, Kamburov A, Polak P, Haradhvala NJ, Hess JM, Rheinbay E, Brody Y, Koren A, Braunstein LZ, D'Andrea A, Lawrence MS, Bass A, Bernards A, Michor F, Getz G. 2017. Analysis of somatic microsatellite indels identifies driver events in human tumors. Nature biotechnology. 35(10):951-959. Pubmed: 28892075 DOI:10.1038/nbt.3966 Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3). -
Zhao R, Catalano P, DeGruttola VG, Michor F. 2017. Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model. PloS one. 12(7):e0180756. Pubmed: 28723910 DOI:10.1371/journal.pone.0180756 Zhao R, Catalano P, DeGruttola VG, Michor F. 2017. Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model. PloS one. 12(7):e0180756. Pubmed: 28723910 DOI:10.1371/journal.pone.0180756 The dynamics of tumor burden, secreted proteins or other biomarkers over time, is often used to evaluate the effectiveness of therapy and to predict outcomes for patients. Many methods have been proposed to investigate longitudinal trends to better characterize patients and to understand disease progression. However, most approaches assume a homogeneous patient population and a uniform response trajectory over time and across patients. Here, we present a mixture piecewise linear Bayesian hierarchical model, which takes into account both population heterogeneity and nonlinear relationships between biomarkers and time. Simulation results show that our method was able to classify subjects according to their patterns of treatment response with greater than 80% accuracy in the three scenarios tested. We then applied our model to a large randomized controlled phase III clinical trial of multiple myeloma patients. Analysis results suggest that the longitudinal tumor burden trajectories in multiple myeloma patients are heterogeneous and nonlinear, even among patients assigned to the same treatment cohort. In addition, between cohorts, there are distinct differences in terms of the regression parameters and the distributions among categories in the mixture. Those results imply that longitudinal data from clinical trials may harbor unobserved subgroups and nonlinear relationships; accounting for both may be important for analyzing longitudinal data. -
McDonald TO, Michor F. 2017. SIApopr: a computational method to simulate evolutionary branching trees for analysis of tumor clonal evolution. Bioinformatics (Oxford, England). 33(14):2221-2223. Pubmed: 28334409 DOI:10.1093/bioinformatics/btx146 McDonald TO, Michor F. 2017. SIApopr: a computational method to simulate evolutionary branching trees for analysis of tumor clonal evolution. Bioinformatics (Oxford, England). 33(14):2221-2223. Pubmed: 28334409 DOI:10.1093/bioinformatics/btx146 Array© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com -
Gil Del Alcazar CR, Huh SJ, Ekram MB, Trinh A, Liu LL, Beca F, Zi X, Kwak M, Bergholtz H, Su Y, Ding L, Russnes HG, Richardson AL, Babski K, Min Hui Kim E, McDonnell CH, Wagner J, Rowberry R, Freeman GJ, Dillon D, Sorlie T, Coussens LM, Garber JE, Fan R, Bobolis K, Allred DC, Jeong J, Park SY, Michor F, Polyak K. 2017. Immune Escape in Breast Cancer During to Invasive Carcinoma Transition. Cancer discovery. 7(10):1098-1115. Pubmed: 28652380 DOI:10.1158/2159-8290.CD-17-0222 Gil Del Alcazar CR, Huh SJ, Ekram MB, Trinh A, Liu LL, Beca F, Zi X, Kwak M, Bergholtz H, Su Y, Ding L, Russnes HG, Richardson AL, Babski K, Min Hui Kim E, McDonnell CH, Wagner J, Rowberry R, Freeman GJ, Dillon D, Sorlie T, Coussens LM, Garber JE, Fan R, Bobolis K, Allred DC, Jeong J, Park SY, Michor F, Polyak K. 2017. Immune Escape in Breast Cancer During to Invasive Carcinoma Transition. Cancer discovery. 7(10):1098-1115. Pubmed: 28652380 DOI:10.1158/2159-8290.CD-17-0222 To investigate immune escape during breast tumor progression, we analyzed the composition of leukocytes in normal breast tissues, ductal carcinoma (DCIS), and invasive ductal carcinomas (IDC). We found significant tissue and tumor subtype-specific differences in multiple cell types including T cells and neutrophils. Gene expression profiling of CD45CD3 T cells demonstrated a decrease in CD8 signatures in IDCs. Immunofluorescence analysis showed fewer activated GZMBCD8 T cells in IDC than in DCIS, including in matched DCIS and recurrent IDC. T-cell receptor clonotype diversity was significantly higher in DCIS than in IDCs. Immune checkpoint protein TIGIT-expressing T cells were more frequent in DCIS, whereas high PD-L1 expression and amplification of (encoding PD-L1) was only detected in triple-negative IDCs. Coamplification of a 17q12 chemokine cluster with subdivided HER2 breast tumors into immunologically and clinically distinct subtypes. Our results show coevolution of cancer cells and the immune microenvironment during tumor progression. The design of effective cancer immunotherapies requires the understanding of mechanisms underlying immune escape during tumor progression. Here we demonstrate a switch to a less active tumor immune environment during the to invasive breast carcinoma transition, and identify immune regulators and genomic alterations that shape tumor evolution. .©2017 American Association for Cancer Research. -
Han L, Wu HJ, Zhu H, Kim KY, Marjani SL, Riester M, Euskirchen G, Zi X, Yang J, Han J, Snyder M, Park IH, Irizarry R, Weissman SM, Michor F, Fan R, Pan X. 2017. Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells. Nucleic acids research. 45(10):e77. Pubmed: 28126923 DOI:10.1093/nar/gkx026 Han L, Wu HJ, Zhu H, Kim KY, Marjani SL, Riester M, Euskirchen G, Zi X, Yang J, Han J, Snyder M, Park IH, Irizarry R, Weissman SM, Michor F, Fan R, Pan X. 2017. Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells. Nucleic acids research. 45(10):e77. Pubmed: 28126923 DOI:10.1093/nar/gkx026 Conventional DNA bisulfite sequencing has been extended to single cell level, but the coverage consistency is insufficient for parallel comparison. Here we report a novel method for genome-wide CpG island (CGI) methylation sequencing for single cells (scCGI-seq), combining methylation-sensitive restriction enzyme digestion and multiple displacement amplification for selective detection of methylated CGIs. We applied this method to analyzing single cells from two types of hematopoietic cells, K562 and GM12878 and small populations of fibroblasts and induced pluripotent stem cells. The method detected 21 798 CGIs (76% of all CGIs) per cell, and the number of CGIs consistently detected from all 16 profiled single cells was 20 864 (72.7%), with 12 961 promoters covered. This coverage represents a substantial improvement over results obtained using single cell reduced representation bisulfite sequencing, with a 66-fold increase in the fraction of consistently profiled CGIs across individual cells. Single cells of the same type were more similar to each other than to other types, but also displayed epigenetic heterogeneity. The method was further validated by comparing the CpG methylation pattern, methylation profile of CGIs/promoters and repeat regions and 41 classes of known regulatory markers to the ENCODE data. Although not every minor methylation differences between cells are detectable, scCGI-seq provides a solid tool for unsupervised stratification of a heterogeneous cell population.© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. -
Chakrabarti S, Michor F. 2017. Pharmacokinetics and Drug Interactions Determine Optimum Combination Strategies in Computational Models of Cancer Evolution. Cancer research. 77(14):3908-3921. Pubmed: 28566331 DOI:10.1158/0008-5472.CAN-16-2871 Chakrabarti S, Michor F. 2017. Pharmacokinetics and Drug Interactions Determine Optimum Combination Strategies in Computational Models of Cancer Evolution. Cancer research. 77(14):3908-3921. Pubmed: 28566331 DOI:10.1158/0008-5472.CAN-16-2871 The identification of optimal drug administration schedules to battle the emergence of resistance is a major challenge in cancer research. The existence of a multitude of resistance mechanisms necessitates administering drugs in combination, significantly complicating the endeavor of predicting the evolutionary dynamics of cancers and optimal intervention strategies. A thorough understanding of the important determinants of cancer evolution under combination therapies is therefore crucial for correctly predicting treatment outcomes. Here we developed the first computational strategy to explore pharmacokinetic and drug interaction effects in evolutionary models of cancer progression, a crucial step towards making clinically relevant predictions. We found that incorporating these phenomena into our multiscale stochastic modeling framework significantly changes the optimum drug administration schedules identified, often predicting nonintuitive strategies for combination therapies. We applied our approach to an ongoing phase Ib clinical trial (TATTON) administering AZD9291 and selumetinib to EGFR-mutant lung cancer patients. Our results suggest that the schedules used in the three trial arms have almost identical efficacies, but slight modifications in the dosing frequencies of the two drugs can significantly increase tumor cell eradication. Interestingly, we also predict that drug concentrations lower than the MTD are as efficacious, suggesting that lowering the total amount of drug administered could lower toxicities while not compromising on the effectiveness of the drugs. Our approach highlights the fact that quantitative knowledge of pharmacokinetic, drug interaction, and evolutionary processes is essential for identifying best intervention strategies. Our method is applicable to diverse cancer and treatment types and allows for a rational design of clinical trials. .©2017 American Association for Cancer Research. 2016
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Wu HJ, Michor F. 2016. A computational strategy to adjust for copy number in tumor Hi-C data. Bioinformatics (Oxford, England). 32(24):3695-3701. Pubmed: 27531101 Wu HJ, Michor F. 2016. A computational strategy to adjust for copy number in tumor Hi-C data. Bioinformatics (Oxford, England). 32(24):3695-3701. Pubmed: 27531101 Array© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com. -
Liu LL, Brumbaugh J, Bar-Nur O, Smith Z, Stadtfeld M, Meissner A, Hochedlinger K, Michor F. 2016. Probabilistic Modeling of Reprogramming to Induced Pluripotent Stem Cells. Cell reports. 17(12):3395-3406. Pubmed: 28009305 DOI:S2211-1247(16)31654-0 Liu LL, Brumbaugh J, Bar-Nur O, Smith Z, Stadtfeld M, Meissner A, Hochedlinger K, Michor F. 2016. Probabilistic Modeling of Reprogramming to Induced Pluripotent Stem Cells. Cell reports. 17(12):3395-3406. Pubmed: 28009305 DOI:S2211-1247(16)31654-0 Reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) is typically an inefficient and asynchronous process. A variety of technological efforts have been made to accelerate and/or synchronize this process. To define a unified framework to study and compare the dynamics of reprogramming under different conditions, we developed an in silico analysis platform based on mathematical modeling. Our approach takes into account the variability in experimental results stemming from probabilistic growth and death of cells and potentially heterogeneous reprogramming rates. We suggest that reprogramming driven by the Yamanaka factors alone is a more heterogeneous process, possibly due to cell-specific reprogramming rates, which could be homogenized by the addition of additional factors. We validated our approach using publicly available reprogramming datasets, including data on early reprogramming dynamics as well as cell count data, and thus we demonstrated the general utility and predictive power of our methodology for investigating reprogramming and other cell fate change systems.Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved. -
Gao R, Davis A, McDonald TO, Sei E, Shi X, Wang Y, Tsai PC, Casasent A, Waters J, Zhang H, Meric-Bernstam F, Michor F, Navin NE. 2016. Punctuated copy number evolution and clonal stasis in triple-negative breast cancer. Nature genetics. 48(10):1119-30. Pubmed: 27526321 DOI:10.1038/ng.3641 Gao R, Davis A, McDonald TO, Sei E, Shi X, Wang Y, Tsai PC, Casasent A, Waters J, Zhang H, Meric-Bernstam F, Michor F, Navin NE. 2016. Punctuated copy number evolution and clonal stasis in triple-negative breast cancer. Nature genetics. 48(10):1119-30. Pubmed: 27526321 DOI:10.1038/ng.3641 Aneuploidy is a hallmark of breast cancer; however, knowledge of how these complex genomic rearrangements evolve during tumorigenesis is limited. In this study, we developed a highly multiplexed single-nucleus sequencing method to investigate copy number evolution in patients with triple-negative breast cancer. We sequenced 1,000 single cells from tumors in 12 patients and identified 1-3 major clonal subpopulations in each tumor that shared a common evolutionary lineage. For each tumor, we also identified a minor subpopulation of non-clonal cells that were classified as metastable, pseudodiploid or chromazemic. Phylogenetic analysis and mathematical modeling suggest that these data are unlikely to be explained by the gradual accumulation of copy number events over time. In contrast, our data challenge the paradigm of gradual evolution, showing that the majority of copy number aberrations are acquired at the earliest stages of tumor evolution, in short punctuated bursts, followed by stable clonal expansions that form the tumor mass. -
Wee B, Pietras A, Ozawa T, Bazzoli E, Podlaha O, Antczak C, Westermark B, Nelander S, Uhrbom L, Forsberg-Nilsson K, Djaballah H, Michor F, Holland EC. 2016. ABCG2 regulates self-renewal and stem cell marker expression but not tumorigenicity or radiation resistance of glioma cells. Scientific reports. 6:25956. Pubmed: 27456282 DOI:10.1038/srep25956 Wee B, Pietras A, Ozawa T, Bazzoli E, Podlaha O, Antczak C, Westermark B, Nelander S, Uhrbom L, Forsberg-Nilsson K, Djaballah H, Michor F, Holland EC. 2016. ABCG2 regulates self-renewal and stem cell marker expression but not tumorigenicity or radiation resistance of glioma cells. Scientific reports. 6:25956. Pubmed: 27456282 DOI:10.1038/srep25956 Glioma cells with stem cell traits are thought to be responsible for tumor maintenance and therapeutic failure. Such cells can be enriched based on their inherent drug efflux capability mediated by the ABC transporter ABCG2 using the side population assay, and their characteristics include increased self-renewal, high stem cell marker expression and high tumorigenic capacity in vivo. Here, we show that ABCG2 can actively drive expression of stem cell markers and self-renewal in glioma cells. Stem cell markers and self-renewal was enriched in cells with high ABCG2 activity, and could be specifically inhibited by pharmacological and genetic ABCG2 inhibition. Importantly, despite regulating these key characteristics of stem-like tumor cells, ABCG2 activity did not affect radiation resistance or tumorigenicity in vivo. ABCG2 effects were Notch-independent and mediated by diverse mechanisms including the transcription factor Mef. Our data demonstrate that characteristics of tumor stem cells are separable, and highlight ABCG2 as a potential driver of glioma stemness. -
Badri H, Pitter K, Holland EC, Michor F, Leder K. 2016. Optimization of radiation dosing schedules for proneural glioblastoma. Journal of mathematical biology. 72(5):1301-36. Pubmed: 26094055 DOI:10.1007/s00285-015-0908-x Badri H, Pitter K, Holland EC, Michor F, Leder K. 2016. Optimization of radiation dosing schedules for proneural glioblastoma. Journal of mathematical biology. 72(5):1301-36. Pubmed: 26094055 DOI:10.1007/s00285-015-0908-x Glioblastomas are the most aggressive primary brain tumor. Despite treatment with surgery, radiation and chemotherapy, these tumors remain uncurable and few significant increases in survival have been observed over the last half-century. We recently employed a combined theoretical and experimental approach to predict the effectiveness of radiation administration schedules, identifying two schedules that led to superior survival in a mouse model of the disease (Leder et al., Cell 156(3):603-616, 2014). Here we extended this approach to consider fractionated schedules to best minimize toxicity arising in early- and late-responding tissues. To this end, we decomposed the problem into two separate solvable optimization tasks: (i) optimization of the amount of radiation per dose, and (ii) optimization of the amount of time that passes between radiation doses. To ensure clinical applicability, we then considered the impact of clinical operating hours by incorporating time constraints consistent with operational schedules of the radiology clinic. We found that there was no significant loss incurred by restricting dosage to an 8:00 a.m. to 5:00 p.m. window. Our flexible approach is also applicable to other tumor types treated with radiotherapy. -
Altrock PM, Brendel C, Renella R, Orkin SH, Williams DA, Michor F. 2016. Mathematical modeling of erythrocyte chimerism informs genetic intervention strategies for sickle cell disease. American journal of hematology. 91(9):931-7. Pubmed: 27299299 DOI:10.1002/ajh.24449 Altrock PM, Brendel C, Renella R, Orkin SH, Williams DA, Michor F. 2016. Mathematical modeling of erythrocyte chimerism informs genetic intervention strategies for sickle cell disease. American journal of hematology. 91(9):931-7. Pubmed: 27299299 DOI:10.1002/ajh.24449 Recent advances in gene therapy and genome-engineering technologies offer the opportunity to correct sickle cell disease (SCD), a heritable disorder caused by a point mutation in the β-globin gene. The developmental switch from fetal γ-globin to adult β-globin is governed in part by the transcription factor (TF) BCL11A. This TF has been proposed as a therapeutic target for reactivation of γ-globin and concomitant reduction of β-sickle globin. In this and other approaches, genetic alteration of a portion of the hematopoietic stem cell (HSC) compartment leads to a mixture of sickling and corrected red blood cells (RBCs) in periphery. To reverse the sickling phenotype, a certain proportion of corrected RBCs is necessary; the degree of HSC alteration required to achieve a desired fraction of corrected RBCs remains unknown. To address this issue, we developed a mathematical model describing aging and survival of sickle-susceptible and normal RBCs; the former can have a selective survival advantage leading to their overrepresentation. We identified the level of bone marrow chimerism required for successful stem cell-based gene therapies in SCD. Our findings were further informed using an experimental mouse model, where we transplanted mixtures of Berkeley SCD and normal murine bone marrow cells to establish chimeric grafts in murine hosts. Our integrative theoretical and experimental approach identifies the target frequency of HSC alterations required for effective treatment of sickling syndromes in humans. Our work replaces episodic observations of such target frequencies with a mathematical modeling framework that covers a large and continuous spectrum of chimerism conditions. Am. J. Hematol. 91:931-937, 2016. © 2016 Wiley Periodicals, Inc.© 2016 Wiley Periodicals, Inc. -
Tang M, Zhao R, van de Velde H, Tross JG, Mitsiades C, Viselli S, Neuwirth R, Esseltine DL, Anderson K, Ghobrial IM, San Miguel JF, Richardson PG, Tomasson MH, Michor F. 2016. Myeloma Cell Dynamics in Response to Treatment Supports a Model of Hierarchical Differentiation and Clonal Evolution. Clinical cancer research : an official journal of the American Association for Cancer Research. 22(16):4206-4214. Pubmed: 27006493 DOI:10.1158/1078-0432.CCR-15-2793 Tang M, Zhao R, van de Velde H, Tross JG, Mitsiades C, Viselli S, Neuwirth R, Esseltine DL, Anderson K, Ghobrial IM, San Miguel JF, Richardson PG, Tomasson MH, Michor F. 2016. Myeloma Cell Dynamics in Response to Treatment Supports a Model of Hierarchical Differentiation and Clonal Evolution. Clinical cancer research : an official journal of the American Association for Cancer Research. 22(16):4206-4214. Pubmed: 27006493 DOI:10.1158/1078-0432.CCR-15-2793 Array©2016 American Association for Cancer Research. 2015
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Mumenthaler SM, Foo J, Choi NC, Heise N, Leder K, Agus DB, Pao W, Michor F, Mallick P. 2015. The Impact of Microenvironmental Heterogeneity on the Evolution of Drug Resistance in Cancer Cells. Cancer informatics. 14(Suppl 4):19-31. Pubmed: 26244007 DOI:10.4137/CIN.S19338 Mumenthaler SM, Foo J, Choi NC, Heise N, Leder K, Agus DB, Pao W, Michor F, Mallick P. 2015. The Impact of Microenvironmental Heterogeneity on the Evolution of Drug Resistance in Cancer Cells. Cancer informatics. 14(Suppl 4):19-31. Pubmed: 26244007 DOI:10.4137/CIN.S19338 Therapeutic resistance arises as a result of evolutionary processes driven by dynamic feedback between a heterogeneous cell population and environmental selective pressures. Previous studies have suggested that mutations conferring resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) in non-small-cell lung cancer (NSCLC) cells lower the fitness of resistant cells relative to drug-sensitive cells in a drug-free environment. Here, we hypothesize that the local tumor microenvironment could influence the magnitude and directionality of the selective effect, both in the presence and absence of a drug. Using a combined experimental and computational approach, we developed a mathematical model of preexisting drug resistance describing multiple cellular compartments, each representing a specific tumor environmental niche. This model was parameterized using a novel experimental dataset derived from the HCC827 erlotinib-sensitive and -resistant NSCLC cell lines. We found that, in contrast to in the drug-free environment, resistant cells may hold a fitness advantage compared to parental cells in microenvironments deficient in oxygen and nutrients. We then utilized the model to predict the impact of drug and nutrient gradients on tumor composition and recurrence times, demonstrating that these endpoints are strongly dependent on the microenvironment. Our interdisciplinary approach provides a model system to quantitatively investigate the impact of microenvironmental effects on the evolutionary dynamics of tumor cells. -
Bhang HE, Ruddy DA, Krishnamurthy Radhakrishna V, Caushi JX, Zhao R, Hims MM, Singh AP, Kao I, Rakiec D, Shaw P, Balak M, Raza A, Ackley E, Keen N, Schlabach MR, Palmer M, Leary RJ, Chiang DY, Sellers WR, Michor F, Cooke VG, Korn JM, Stegmeier F. 2015. Studying clonal dynamics in response to cancer therapy using high-complexity barcoding. Nature medicine. 21(5):440-8. Pubmed: 25849130 DOI:10.1038/nm.3841 Bhang HE, Ruddy DA, Krishnamurthy Radhakrishna V, Caushi JX, Zhao R, Hims MM, Singh AP, Kao I, Rakiec D, Shaw P, Balak M, Raza A, Ackley E, Keen N, Schlabach MR, Palmer M, Leary RJ, Chiang DY, Sellers WR, Michor F, Cooke VG, Korn JM, Stegmeier F. 2015. Studying clonal dynamics in response to cancer therapy using high-complexity barcoding. Nature medicine. 21(5):440-8. Pubmed: 25849130 DOI:10.1038/nm.3841 Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer. -
Selmecki AM, Maruvka YE, Richmond PA, Guillet M, Shoresh N, Sorenson AL, De S, Kishony R, Michor F, Dowell R, Pellman D. 2015. Polyploidy can drive rapid adaptation in yeast. Nature. 519(7543):349-52. Pubmed: 25731168 DOI:10.1038/nature14187 Selmecki AM, Maruvka YE, Richmond PA, Guillet M, Shoresh N, Sorenson AL, De S, Kishony R, Michor F, Dowell R, Pellman D. 2015. Polyploidy can drive rapid adaptation in yeast. Nature. 519(7543):349-52. Pubmed: 25731168 DOI:10.1038/nature14187 Polyploidy is observed across the tree of life, yet its influence on evolution remains incompletely understood. Polyploidy, usually whole-genome duplication, is proposed to alter the rate of evolutionary adaptation. This could occur through complex effects on the frequency or fitness of beneficial mutations. For example, in diverse cell types and organisms, immediately after a whole-genome duplication, newly formed polyploids missegregate chromosomes and undergo genetic instability. The instability following whole-genome duplications is thought to provide adaptive mutations in microorganisms and can promote tumorigenesis in mammalian cells. Polyploidy may also affect adaptation independently of beneficial mutations through ploidy-specific changes in cell physiology. Here we perform in vitro evolution experiments to test directly whether polyploidy can accelerate evolutionary adaptation. Compared with haploids and diploids, tetraploids undergo significantly faster adaptation. Mathematical modelling suggests that rapid adaptation of tetraploids is driven by higher rates of beneficial mutations with stronger fitness effects, which is supported by whole-genome sequencing and phenotypic analyses of evolved clones. Chromosome aneuploidy, concerted chromosome loss, and point mutations all provide large fitness gains. We identify several mutations whose beneficial effects are manifest specifically in the tetraploid strains. Together, these results provide direct quantitative evidence that in some environments polyploidy can accelerate evolutionary adaptation. -
Roccaro AM, Mishima Y, Sacco A, Moschetta M, Tai YT, Shi J, Zhang Y, Reagan MR, Huynh D, Kawano Y, Sahin I, Chiarini M, Manier S, Cea M, Aljawai Y, Glavey S, Morgan E, Pan C, Michor F, Cardarelli P, Kuhne M, Ghobrial IM. 2015. CXCR4 Regulates Extra-Medullary Myeloma through Epithelial-Mesenchymal-Transition-like Transcriptional Activation. Cell reports. 12(4):622-35. Pubmed: 26190113 DOI:S2211-1247(15)00685-3 Roccaro AM, Mishima Y, Sacco A, Moschetta M, Tai YT, Shi J, Zhang Y, Reagan MR, Huynh D, Kawano Y, Sahin I, Chiarini M, Manier S, Cea M, Aljawai Y, Glavey S, Morgan E, Pan C, Michor F, Cardarelli P, Kuhne M, Ghobrial IM. 2015. CXCR4 Regulates Extra-Medullary Myeloma through Epithelial-Mesenchymal-Transition-like Transcriptional Activation. Cell reports. 12(4):622-35. Pubmed: 26190113 DOI:S2211-1247(15)00685-3 Extra-medullary disease (EMD) in multiple myeloma (MM) is associated with poor prognosis and resistance to chemotherapy. However, molecular alterations that lead to EMD have not been well defined. We developed bone marrow (BM)- and EMD-prone MM syngeneic cell lines; identified that epithelial-to-mesenchymal transition (EMT) transcriptional patterns were significantly enriched in both clones compared to parental cells, together with higher levels of CXCR4 protein; and demonstrated that CXCR4 enhanced the acquisition of an EMT-like phenotype in MM cells with a phenotypic conversion for invasion, leading to higher bone metastasis and EMD dissemination in vivo. In contrast, CXCR4 silencing led to inhibited tumor growth and reduced survival. Ulocuplumab, a monoclonal anti-CXCR4 antibody, inhibited MM cell dissemination, supported by suppression of the CXCR4-driven EMT-like phenotype. These results suggest that targeting CXCR4 may act as a regulator of EMD through EMT-like transcriptional modulation, thus representing a potential therapeutic strategy to prevent MM disease progression.Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved. -
Bambury RM, Bhatt AS, Riester M, Pedamallu CS, Duke F, Bellmunt J, Stack EC, Werner L, Park R, Iyer G, Loda M, Kantoff PW, Michor F, Meyerson M, Rosenberg JE. 2015. DNA copy number analysis of metastatic urothelial carcinoma with comparison to primary tumors. BMC cancer. 15:242. Pubmed: 25886454 DOI:10.1186/s12885-015-1192-2 Bambury RM, Bhatt AS, Riester M, Pedamallu CS, Duke F, Bellmunt J, Stack EC, Werner L, Park R, Iyer G, Loda M, Kantoff PW, Michor F, Meyerson M, Rosenberg JE. 2015. DNA copy number analysis of metastatic urothelial carcinoma with comparison to primary tumors. BMC cancer. 15:242. Pubmed: 25886454 DOI:10.1186/s12885-015-1192-2 Array -
Ashcroft P, Michor F, Galla T. 2015. Stochastic tunneling and metastable states during the somatic evolution of cancer. Genetics. 199(4):1213-28. Pubmed: 25624316 DOI:10.1534/genetics.114.171553 Ashcroft P, Michor F, Galla T. 2015. Stochastic tunneling and metastable states during the somatic evolution of cancer. Genetics. 199(4):1213-28. Pubmed: 25624316 DOI:10.1534/genetics.114.171553 Tumors initiate when a population of proliferating cells accumulates a certain number and type of genetic and/or epigenetic alterations. The population dynamics of such sequential acquisition of (epi)genetic alterations has been the topic of much investigation. The phenomenon of stochastic tunneling, where an intermediate mutant in a sequence does not reach fixation in a population before generating a double mutant, has been studied using a variety of computational and mathematical methods. However, the field still lacks a comprehensive analytical description since theoretical predictions of fixation times are available only for cases in which the second mutant is advantageous. Here, we study stochastic tunneling in a Moran model. Analyzing the deterministic dynamics of large populations we systematically identify the parameter regimes captured by existing approaches. Our analysis also reveals fitness landscapes and mutation rates for which finite populations are found in long-lived metastable states. These are landscapes in which the final mutant is not the most advantageous in the sequence, and resulting metastable states are a consequence of a mutation-selection balance. The escape from these states is driven by intrinsic noise, and their location affects the probability of tunneling. Existing methods no longer apply. In these regimes it is the escape from the metastable states that is the key bottleneck; fixation is no longer limited by the emergence of a successful mutant lineage. We used the so-called Wentzel-Kramers-Brillouin method to compute fixation times in these parameter regimes, successfully validated by stochastic simulations. Our work fills a gap left by previous approaches and provides a more comprehensive description of the acquisition of multiple mutations in populations of somatic cells.Copyright © 2015 by the Genetics Society of America. -
Janiszewska M, Liu L, Almendro V, Kuang Y, Paweletz C, Sakr RA, Weigelt B, Hanker AB, Chandarlapaty S, King TA, Reis-Filho JS, Arteaga CL, Park SY, Michor F, Polyak K. 2015. In situ single-cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2-positive breast cancer. Nature genetics. 47(10):1212-9. Pubmed: 26301495 DOI:10.1038/ng.3391 Janiszewska M, Liu L, Almendro V, Kuang Y, Paweletz C, Sakr RA, Weigelt B, Hanker AB, Chandarlapaty S, King TA, Reis-Filho JS, Arteaga CL, Park SY, Michor F, Polyak K. 2015. In situ single-cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2-positive breast cancer. Nature genetics. 47(10):1212-9. Pubmed: 26301495 DOI:10.1038/ng.3391 Detection of minor, genetically distinct subpopulations within tumors is a key challenge in cancer genomics. Here we report STAR-FISH (specific-to-allele PCR-FISH), a novel method for the combined detection of single-nucleotide and copy number alterations in single cells in intact archived tissues. Using this method, we assessed the clinical impact of changes in the frequency and topology of PIK3CA mutation and HER2 (ERBB2) amplification within HER2-positive breast cancer during neoadjuvant therapy. We found that these two genetic events are not always present in the same cells. Chemotherapy selects for PIK3CA-mutant cells, a minor subpopulation in nearly all treatment-naive samples, and modulates genetic diversity within tumors. Treatment-associated changes in the spatial distribution of cellular genetic diversity correlated with poor long-term outcome following adjuvant therapy with trastuzumab. Our findings support the use of in situ single cell-based methods in cancer genomics and imply that chemotherapy before HER2-targeted therapy may promote treatment resistance. -
Altrock PM, Liu LL, Michor F. 2015. The mathematics of cancer: integrating quantitative models. Nature reviews. Cancer. 15(12):730-45. Pubmed: 26597528 DOI:10.1038/nrc4029 Altrock PM, Liu LL, Michor F. 2015. The mathematics of cancer: integrating quantitative models. Nature reviews. Cancer. 15(12):730-45. Pubmed: 26597528 DOI:10.1038/nrc4029 Mathematical modelling approaches have become increasingly abundant in cancer research. The complexity of cancer is well suited to quantitative approaches as it provides challenges and opportunities for new developments. In turn, mathematical modelling contributes to cancer research by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. The recent expansion of quantitative models addresses many questions regarding tumour initiation, progression and metastases as well as intra-tumour heterogeneity, treatment responses and resistance. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving tumorigenesis and shape future research in cancer biology. -
Michor F, Beal K. 2015. Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort. Cell. 163(5):1059-1063. Pubmed: 26590416 DOI:S0092-8674(15)01482-8 Michor F, Beal K. 2015. Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort. Cell. 163(5):1059-1063. Pubmed: 26590416 DOI:S0092-8674(15)01482-8 Drug delivery schedules are key factors in the efficacy of cancer therapies, and mathematical modeling of population dynamics and treatment responses can be applied to identify better drug administration regimes as well as provide mechanistic insights. To capitalize on the promise of this approach, the cancer field must meet the challenges of moving this type of work into clinics.Copyright © 2015 Elsevier Inc. All rights reserved. -
Liu LL, Li F, Pao W, Michor F. 2015. Dose-Dependent Mutation Rates Determine Optimum Erlotinib Dosing Strategies for EGFR Mutant Non-Small Cell Lung Cancer Patients. PloS one. 10(11):e0141665. Pubmed: 26536620 DOI:10.1371/journal.pone.0141665 Liu LL, Li F, Pao W, Michor F. 2015. Dose-Dependent Mutation Rates Determine Optimum Erlotinib Dosing Strategies for EGFR Mutant Non-Small Cell Lung Cancer Patients. PloS one. 10(11):e0141665. Pubmed: 26536620 DOI:10.1371/journal.pone.0141665 Array -
Foo J, Liu LL, Leder K, Riester M, Iwasa Y, Lengauer C, Michor F. 2015. An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. PLoS computational biology. 11(9):e1004350. Pubmed: 26379039 DOI:10.1371/journal.pcbi.1004350 Foo J, Liu LL, Leder K, Riester M, Iwasa Y, Lengauer C, Michor F. 2015. An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer. PLoS computational biology. 11(9):e1004350. Pubmed: 26379039 DOI:10.1371/journal.pcbi.1004350 The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such "driver" mutations from innocuous "passenger" events is critical for prioritizing the validation of candidate mutations in disease-relevant models. We design a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set, and apply it to a mutational data set in colorectal cancer. Our methodology is based upon a population dynamics model of mutation accumulation and selection in colorectal tissue prior to cancer initiation as well as during tumorigenesis. This methodology can be used to aid in the prioritization of candidate mutations for functional validation and contributes to the process of drug discovery. -
Kleppe M, Kwak M, Koppikar P, Riester M, Keller M, Bastian L, Hricik T, Bhagwat N, McKenney AS, Papalexi E, Abdel-Wahab O, Rampal R, Marubayashi S, Chen JJ, Romanet V, Fridman JS, Bromberg J, Teruya-Feldstein J, Murakami M, Radimerski T, Michor F, Fan R, Levine RL. 2015. JAK-STAT pathway activation in malignant and nonmalignant cells contributes to MPN pathogenesis and therapeutic response. Cancer discovery. 5(3):316-31. Pubmed: 25572172 DOI:10.1158/2159-8290.CD-14-0736 Kleppe M, Kwak M, Koppikar P, Riester M, Keller M, Bastian L, Hricik T, Bhagwat N, McKenney AS, Papalexi E, Abdel-Wahab O, Rampal R, Marubayashi S, Chen JJ, Romanet V, Fridman JS, Bromberg J, Teruya-Feldstein J, Murakami M, Radimerski T, Michor F, Fan R, Levine RL. 2015. JAK-STAT pathway activation in malignant and nonmalignant cells contributes to MPN pathogenesis and therapeutic response. Cancer discovery. 5(3):316-31. Pubmed: 25572172 DOI:10.1158/2159-8290.CD-14-0736 Array©2015 American Association for Cancer Research. 2014
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Riester M, Werner L, Bellmunt J, Selvarajah S, Guancial EA, Weir BA, Stack EC, Park RS, O'Brien R, Schutz FA, Choueiri TK, Signoretti S, Lloreta J, Marchionni L, Gallardo E, Rojo F, Garcia DI, Chekaluk Y, Kwiatkowski DJ, Bochner BH, Hahn WC, Ligon AH, Barletta JA, Loda M, Berman DM, Kantoff PW, Michor F, Rosenberg JE. 2014. Integrative analysis of 1q23.3 copy-number gain in metastatic urothelial carcinoma. Clinical cancer research : an official journal of the American Association for Cancer Research. 20(7):1873-83. Pubmed: 24486590 DOI:10.1158/1078-0432.CCR-13-0759 Riester M, Werner L, Bellmunt J, Selvarajah S, Guancial EA, Weir BA, Stack EC, Park RS, O'Brien R, Schutz FA, Choueiri TK, Signoretti S, Lloreta J, Marchionni L, Gallardo E, Rojo F, Garcia DI, Chekaluk Y, Kwiatkowski DJ, Bochner BH, Hahn WC, Ligon AH, Barletta JA, Loda M, Berman DM, Kantoff PW, Michor F, Rosenberg JE. 2014. Integrative analysis of 1q23.3 copy-number gain in metastatic urothelial carcinoma. Clinical cancer research : an official journal of the American Association for Cancer Research. 20(7):1873-83. Pubmed: 24486590 DOI:10.1158/1078-0432.CCR-13-0759 Array©2014 AACR. -
Leder K, Pitter K, LaPlant Q, Hambardzumyan D, Ross BD, Chan TA, Holland EC, Michor F. 2014. Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules. Cell. 156(3):603-616. Pubmed: 24485463 DOI:10.1016/j.cell.2013.12.029 Leder K, Pitter K, LaPlant Q, Hambardzumyan D, Ross BD, Chan TA, Holland EC, Michor F. 2014. Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules. Cell. 156(3):603-616. Pubmed: 24485463 DOI:10.1016/j.cell.2013.12.029 Glioblastomas (GBMs) are the most common and malignant primary brain tumors and are aggressively treated with surgery, chemotherapy, and radiotherapy. Despite this treatment, recurrence is inevitable and survival has improved minimally over the last 50 years. Recent studies have suggested that GBMs exhibit both heterogeneity and instability of differentiation states and varying sensitivities of these states to radiation. Here, we employed an iterative combined theoretical and experimental strategy that takes into account tumor cellular heterogeneity and dynamically acquired radioresistance to predict the effectiveness of different radiation schedules. Using this model, we identified two delivery schedules predicted to significantly improve efficacy by taking advantage of the dynamic instability of radioresistance. These schedules led to superior survival in mice. Our interdisciplinary approach may also be applicable to other human cancer types treated with radiotherapy and, hence, may lay the foundation for significantly increasing the effectiveness of a mainstay of oncologic therapy. PAPERCLIP:Copyright © 2014 Elsevier Inc. All rights reserved. -
Almendro V, Cheng YK, Randles A, Itzkovitz S, Marusyk A, Ametller E, Gonzalez-Farre X, Muñoz M, Russnes HG, Helland A, Rye IH, Borresen-Dale AL, Maruyama R, van Oudenaarden A, Dowsett M, Jones RL, Reis-Filho J, Gascon P, Gönen M, Michor F, Polyak K. 2014. Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. Cell reports. 6(3):514-27. Pubmed: 24462293 DOI:S2211-1247(13)00799-7 Almendro V, Cheng YK, Randles A, Itzkovitz S, Marusyk A, Ametller E, Gonzalez-Farre X, Muñoz M, Russnes HG, Helland A, Rye IH, Borresen-Dale AL, Maruyama R, van Oudenaarden A, Dowsett M, Jones RL, Reis-Filho J, Gascon P, Gönen M, Michor F, Polyak K. 2014. Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. Cell reports. 6(3):514-27. Pubmed: 24462293 DOI:S2211-1247(13)00799-7 Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved. -
Almendro V, Kim HJ, Cheng YK, Gönen M, Itzkovitz S, Argani P, van Oudenaarden A, Sukumar S, Michor F, Polyak K. 2014. Genetic and phenotypic diversity in breast tumor metastases. Cancer research. 74(5):1338-48. Pubmed: 24448237 DOI:10.1158/0008-5472.CAN-13-2357-T Almendro V, Kim HJ, Cheng YK, Gönen M, Itzkovitz S, Argani P, van Oudenaarden A, Sukumar S, Michor F, Polyak K. 2014. Genetic and phenotypic diversity in breast tumor metastases. Cancer research. 74(5):1338-48. Pubmed: 24448237 DOI:10.1158/0008-5472.CAN-13-2357-T Metastatic disease is the main cause of cancer-related mortality due to almost universal therapeutic resistance. Despite its high clinical relevance, our knowledge of how cancer cell populations change during metastatic progression is limited. Here, we investigated intratumor genetic and phenotypic heterogeneity during metastatic progression of breast cancer. We analyzed cellular genotypes and phenotypes at the single cell level by performing immunoFISH in intact tissue sections of distant metastatic tumors from rapid autopsy cases and from primary tumors and matched lymph node metastases collected before systemic therapy. We calculated the Shannon index of intratumor diversity in all cancer cells and within phenotypically distinct cell populations. We found that the extent of intratumor genetic diversity was similar regardless of the chromosomal region analyzed, implying that it may reflect an inherent property of the tumors. We observed that genetic diversity was highest in distant metastases and was generally concordant across lesions within the same patient, whereas treatment-naïve primary tumors and matched lymph node metastases were frequently genetically more divergent. In contrast, cellular phenotypes were more discordant between distant metastases than primary tumors and matched lymph node metastases. Diversity for 8q24 was consistently higher in HER2(+) tumors compared with other subtypes and in metastases of triple-negative tumors relative to primary sites. We conclude that our integrative method that couples ecologic models with experimental data in human tissue samples could be used for the improved prognostication of patients with cancer and for the design of more effective therapies for progressive disease.©2014 AACR -
Chambwe N, Kormaksson M, Geng H, De S, Michor F, Johnson NA, Morin RD, Scott DW, Godley LA, Gascoyne RD, Melnick A, Campagne F, Shaknovich R. 2014. Variability in DNA methylation defines novel epigenetic subgroups of DLBCL associated with different clinical outcomes. Blood. 123(11):1699-708. Pubmed: 24385541 DOI:10.1182/blood-2013-07-509885 Chambwe N, Kormaksson M, Geng H, De S, Michor F, Johnson NA, Morin RD, Scott DW, Godley LA, Gascoyne RD, Melnick A, Campagne F, Shaknovich R. 2014. Variability in DNA methylation defines novel epigenetic subgroups of DLBCL associated with different clinical outcomes. Blood. 123(11):1699-708. Pubmed: 24385541 DOI:10.1182/blood-2013-07-509885 Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive form of non-Hodgkin lymphoma with variable biology and clinical behavior. The current classification does not fully explain the biological and clinical heterogeneity of DLBCLs. In this study, we carried out genomewide DNA methylation profiling of 140 DLBCL samples and 10 normal germinal center B cells using the HpaII tiny fragment enrichment by ligation-mediated polymerase chain reaction assay and hybridization to a custom Roche NimbleGen promoter array. We defined methylation disruption as a main epigenetic event in DLBCLs and designed a method for measuring the methylation variability of individual cases. We then used a novel approach for unsupervised hierarchical clustering based on the extent of DNA methylation variability. This approach identified 6 clusters (A-F). The extent of methylation variability was associated with survival outcomes, with significant differences in overall and progression-free survival. The novel clusters are characterized by disruption of specific biological pathways such as cytokine-mediated signaling, ephrin signaling, and pathways associated with apoptosis and cell-cycle regulation. In a subset of patients, we profiled gene expression and genomic variation to investigate their interplay with methylation changes. This study is the first to identify novel epigenetic clusters of DLBCLs and their aberrantly methylated genes, molecular associations, and survival. -
Shaknovich R, De S, Michor F. 2014. Epigenetic diversity in hematopoietic neoplasms. Biochimica et biophysica acta. 1846(2):477-84. Pubmed: 25240947 DOI:S0304-419X(14)00085-7 Shaknovich R, De S, Michor F. 2014. Epigenetic diversity in hematopoietic neoplasms. Biochimica et biophysica acta. 1846(2):477-84. Pubmed: 25240947 DOI:S0304-419X(14)00085-7 Tumor cell populations display a remarkable extent of variability in non-genetic characteristics such as DNA methylation, histone modification patterns, and differentiation levels of individual cells. It remains to be elucidated whether non-genetic heterogeneity is simply a byproduct of tumor evolution or instead a manifestation of a higher-order tissue organization that is maintained within the neoplasm to establish a differentiation hierarchy, a favorable microenvironment, or a buffer against changing selection pressures during tumorigenesis. Here, we review recent findings on epigenetic diversity, particularly heterogeneity in DNA methylation patterns in hematologic malignancies. We also address the implications of epigenetic heterogeneity for the clonal evolution of tumors and discuss its effects on gene expression and other genome functions in cancer.Copyright © 2014. Published by Elsevier B.V. -
Olshen A, Tang M, Cortes J, Gonen M, Hughes T, Branford S, Quintás-Cardama A, Michor F. 2014. Dynamics of chronic myeloid leukemia response to dasatinib, nilotinib, and high-dose imatinib. Haematologica. 99(11):1701-9. Pubmed: 25216683 DOI:10.3324/haematol.2013.085977 Olshen A, Tang M, Cortes J, Gonen M, Hughes T, Branford S, Quintás-Cardama A, Michor F. 2014. Dynamics of chronic myeloid leukemia response to dasatinib, nilotinib, and high-dose imatinib. Haematologica. 99(11):1701-9. Pubmed: 25216683 DOI:10.3324/haematol.2013.085977 Treatment with the tyrosine kinase inhibitor imatinib is the standard of care for newly diagnosed patients with chronic myeloid leukemia. In recent years, several second-generation inhibitors - such as dasatinib and nilotinib - have become available: these promise to overcome some of the mutations associated with acquired resistance to imatinib. Despite eliciting similar clinical responses, the molecular effects of these agents on different subpopulations of leukemic cells remain incompletely understood. Furthermore, the consequences of using high-dose imatinib therapy have not been investigated in detail. Here we utilized clinical data from patients treated with dasatinib, nilotinib, or high-dose imatinib, together with a statistical data analysis and mathematical modeling approach, to investigate the molecular treatment response of leukemic cells to these agents. We found that these drugs elicit very similar responses if administered front-line. However, patients display significantly different kinetics when treated second-line, both in terms of differences between front-line and second-line treatment for the same drug, and among agents when used as second-line. We then utilized a mathematical framework describing the behavior of four differentiation levels of leukemic cells during therapy to predict the treatment response kinetics for the different cohorts of patients. The dynamics of BCR-ABL1 clearance observed in our study suggest that the use of standard or high-dose imatinib or a second-generation tyrosine kinase inhibitor such as nilotinib or dasatinib elicits similar responses when administered as front-line therapy for patients with chronic myeloid leukemia in chronic phase.Copyright© Ferrata Storti Foundation. -
Wang Y, Waters J, Leung ML, Unruh A, Roh W, Shi X, Chen K, Scheet P, Vattathil S, Liang H, Multani A, Zhang H, Zhao R, Michor F, Meric-Bernstam F, Navin NE. 2014. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature. 512(7513):155-60. Pubmed: 25079324 DOI:10.1038/nature13600 Wang Y, Waters J, Leung ML, Unruh A, Roh W, Shi X, Chen K, Scheet P, Vattathil S, Liang H, Multani A, Zhang H, Zhao R, Michor F, Meric-Bernstam F, Navin NE. 2014. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature. 512(7513):155-60. Pubmed: 25079324 DOI:10.1038/nature13600 Sequencing studies of breast tumour cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumours. Here we developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumour nuclei from an oestrogen-receptor-positive (ER(+)) breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Using targeted single-molecule sequencing, many of the diverse mutations were shown to occur at low frequencies (<10%) in the tumour mass. Using mathematical modelling we found that the triple-negative tumour cells had an increased mutation rate (13.3×), whereas the ER(+) tumour cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer. -
Marusyk A, Tabassum DP, Altrock PM, Almendro V, Michor F, Polyak K. 2014. Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature. 514(7520):54-8. Pubmed: 25079331 DOI:10.1038/nature13556 Marusyk A, Tabassum DP, Altrock PM, Almendro V, Michor F, Polyak K. 2014. Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature. 514(7520):54-8. Pubmed: 25079331 DOI:10.1038/nature13556 Cancers arise through a process of somatic evolution that can result in substantial sub-clonal heterogeneity within tumours. The mechanisms responsible for the coexistence of distinct sub-clones and the biological consequences of this coexistence remain poorly understood. Here we used a mouse xenograft model to investigate the impact of sub-clonal heterogeneity on tumour phenotypes and the competitive expansion of individual clones. We found that tumour growth can be driven by a minor cell subpopulation, which enhances the proliferation of all cells within a tumour by overcoming environmental constraints and yet can be outcompeted by faster proliferating competitors, resulting in tumour collapse. We developed a mathematical modelling framework to identify the rules underlying the generation of intra-tumour clonal heterogeneity. We found that non-cell-autonomous driving of tumour growth, together with clonal interference, stabilizes sub-clonal heterogeneity, thereby enabling inter-clonal interactions that can lead to new phenotypic traits. -
Maruvka YE, Tang M, Michor F. 2014. On the validity of using increases in 5-year survival rates to measure success in the fight against cancer. PloS one. 9(7):e83100. Pubmed: 25054541 DOI:10.1371/journal.pone.0083100 Maruvka YE, Tang M, Michor F. 2014. On the validity of using increases in 5-year survival rates to measure success in the fight against cancer. PloS one. 9(7):e83100. Pubmed: 25054541 DOI:10.1371/journal.pone.0083100 Array -
Podlaha O, De S, Gonen M, Michor F. 2014. Histone modifications are associated with transcript isoform diversity in normal and cancer cells. PLoS computational biology. 10(6):e1003611. Pubmed: 24901363 DOI:10.1371/journal.pcbi.1003611 Podlaha O, De S, Gonen M, Michor F. 2014. Histone modifications are associated with transcript isoform diversity in normal and cancer cells. PLoS computational biology. 10(6):e1003611. Pubmed: 24901363 DOI:10.1371/journal.pcbi.1003611 Mechanisms that generate transcript diversity are of fundamental importance in eukaryotes. Although a large fraction of human protein-coding genes and lincRNAs produce more than one mRNA isoform each, the regulation of this phenomenon is still incompletely understood. Much progress has been made in deciphering the role of sequence-specific features as well as DNA-and RNA-binding proteins in alternative splicing. Recently, however, several experimental studies of individual genes have revealed a direct involvement of epigenetic factors in alternative splicing and transcription initiation. While histone modifications are generally correlated with overall gene expression levels, it remains unclear how histone modification enrichment affects relative isoform abundance. Therefore, we sought to investigate the associations between histone modifications and transcript diversity levels measured by the rates of transcription start-site switching and alternative splicing on a genome-wide scale across protein-coding genes and lincRNAs. We found that the relationship between enrichment levels of epigenetic marks and transcription start-site switching is similar for protein-coding genes and lincRNAs. Furthermore, we found associations between splicing rates and enrichment levels of H2az, H3K4me1, H3K4me2, H3K4me3, H3K9ac, H3K9me3, H3K27ac, H3K27me3, H3K36me3, H3K79me2, and H4K20me, marks traditionally associated with enhancers, transcription initiation, transcriptional repression, and others. These patterns were observed in both normal and cancer cell lines. Additionally, we developed a novel computational method that identified 840 epigenetically regulated candidate genes and predicted transcription start-site switching and alternative exon splicing with up to 92% accuracy based on epigenetic patterning alone. Our results suggest that the epigenetic regulation of transcript isoform diversity may be a relatively common genome-wide phenomenon representing an avenue of deregulation in tumor development. -
Guancial EA, Werner L, Bellmunt J, Bamias A, Choueiri TK, Ross R, Schutz FA, Park RS, O'Brien RJ, Hirsch MS, Barletta JA, Berman DM, Lis R, Loda M, Stack EC, Garraway LA, Riester M, Michor F, Kantoff PW, Rosenberg JE. 2014. FGFR3 expression in primary and metastatic urothelial carcinoma of the bladder. Cancer medicine. 3(4):835-44. Pubmed: 24846059 DOI:10.1002/cam4.262 Guancial EA, Werner L, Bellmunt J, Bamias A, Choueiri TK, Ross R, Schutz FA, Park RS, O'Brien RJ, Hirsch MS, Barletta JA, Berman DM, Lis R, Loda M, Stack EC, Garraway LA, Riester M, Michor F, Kantoff PW, Rosenberg JE. 2014. FGFR3 expression in primary and metastatic urothelial carcinoma of the bladder. Cancer medicine. 3(4):835-44. Pubmed: 24846059 DOI:10.1002/cam4.262 While fibroblast growth factor receptor 3 (FGFR3) is frequently mutated or overexpressed in nonmuscle-invasive urothelial carcinoma (UC), the prevalence of FGFR3 protein expression and mutation remains unknown in muscle-invasive disease. FGFR3 protein and mRNA expression, mutational status, and copy number variation were retrospectively analyzed in 231 patients with formalin-fixed paraffin-embedded primary UCs, 33 metastases, and 14 paired primary and metastatic tumors using the following methods: immunohistochemistry, NanoString nCounterTM, OncoMap or Affymetrix OncoScanTM array, and Gain and Loss of Analysis of DNA and Genomic Identification of Significant Targets in Cancer software. FGFR3 immunohistochemistry staining was present in 29% of primary UCs and 49% of metastases and did not impact overall survival (P = 0.89, primary tumors; P = 0.78, metastases). FGFR3 mutations were observed in 2% of primary tumors and 9% of metastases. Mutant tumors expressed higher levels of FGFR3 mRNA than wild-type tumors (P < 0.001). FGFR3 copy number gain and loss were rare events in primary and metastatic tumors (0.8% each; 3.0% and 12.3%, respectively). FGFR3 immunohistochemistry staining is present in one third of primary muscle-invasive UCs and half of metastases, while FGFR3 mutations and copy number changes are relatively uncommon.© 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. -
Riester M, Wei W, Waldron L, Culhane AC, Trippa L, Oliva E, Kim SH, Michor F, Huttenhower C, Parmigiani G, Birrer MJ. 2014. Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples. Journal of the National Cancer Institute. 106(5). Pubmed: 24700803 DOI:10.1093/jnci/dju048 Riester M, Wei W, Waldron L, Culhane AC, Trippa L, Oliva E, Kim SH, Michor F, Huttenhower C, Parmigiani G, Birrer MJ. 2014. Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples. Journal of the National Cancer Institute. 106(5). Pubmed: 24700803 DOI:10.1093/jnci/dju048 Array© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com. -
Foo J, Michor F. 2014. Evolution of acquired resistance to anti-cancer therapy. Journal of theoretical biology. 355:10-20. Pubmed: 24681298 DOI:S0022-5193(14)00100-3 Foo J, Michor F. 2014. Evolution of acquired resistance to anti-cancer therapy. Journal of theoretical biology. 355:10-20. Pubmed: 24681298 DOI:S0022-5193(14)00100-3 Acquired drug resistance is a major limitation for the successful treatment of cancer. Resistance can emerge due to a variety of reasons including host environmental factors as well as genetic or epigenetic alterations in the cancer cells. Evolutionary theory has contributed to the understanding of the dynamics of resistance mutations in a cancer cell population, the risk of resistance pre-existing before the initiation of therapy, the composition of drug cocktails necessary to prevent the emergence of resistance, and optimum drug administration schedules for patient populations at risk of evolving acquired resistance. Here we review recent advances towards elucidating the evolutionary dynamics of acquired drug resistance and outline how evolutionary thinking can contribute to outstanding questions in the field.Published by Elsevier Ltd. -
Ozawa T, Riester M, Cheng YK, Huse JT, Squatrito M, Helmy K, Charles N, Michor F, Holland EC. 2014. Most human non-GCIMP glioblastoma subtypes evolve from a common proneural-like precursor glioma. Cancer cell. 26(2):288-300. Pubmed: 25117714 DOI:S1535-6108(14)00265-7 Ozawa T, Riester M, Cheng YK, Huse JT, Squatrito M, Helmy K, Charles N, Michor F, Holland EC. 2014. Most human non-GCIMP glioblastoma subtypes evolve from a common proneural-like precursor glioma. Cancer cell. 26(2):288-300. Pubmed: 25117714 DOI:S1535-6108(14)00265-7 To understand the relationships between the non-GCIMP glioblastoma (GBM) subgroups, we performed mathematical modeling to predict the temporal sequence of driver events during tumorigenesis. The most common order of evolutionary events is 1) chromosome (chr) 7 gain and chr10 loss, followed by 2) CDKN2A loss and/or TP53 mutation, and 3) alterations canonical for specific subtypes. We then developed a computational methodology to identify drivers of broad copy number changes, identifying PDGFA (chr7) and PTEN (chr10) as driving initial nondisjunction events. These predictions were validated using mouse modeling, showing that PDGFA is sufficient to induce proneural-like gliomas and that additional NF1 loss converts proneural to the mesenchymal subtype. Our findings suggest that most non-GCIMP mesenchymal GBMs arise as, and evolve from, a proneural-like precursor.Copyright © 2014 Elsevier Inc. All rights reserved. -
Michor F, Weaver VM. 2014. Understanding tissue context influences on intratumour heterogeneity. Nature cell biology. 16(4):301-2. Pubmed: 24691256 DOI:10.1038/ncb2942 Michor F, Weaver VM. 2014. Understanding tissue context influences on intratumour heterogeneity. Nature cell biology. 16(4):301-2. Pubmed: 24691256 DOI:10.1038/ncb2942 Although human cancers exhibit intratumour heterogeneity, the influence of the tumour environment on this property is unclear. Single basal-like mammary epithelial cells are now shown to engage a dynamic TGFBR3-JUND signalling circuit in an extracellular-matrix-dependent manner. Cell transition between the distinct gene expression states underlying this circuit alters their properties and may modulate their propensity to malignancy. 2013
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Gallipoli P, Stobo J, Heaney N, Nicolini FE, Clark R, Wilson G, Tighe J, McLintock L, Hughes T, Michor F, Paul J, Drummond M, Holyoake TL. 2013. Safety and efficacy of pulsed imatinib with or without G-CSF versus continuous imatinib in chronic phase chronic myeloid leukaemia patients at 5 years follow-up. British journal of haematology. 163(5):674-6. Pubmed: 24032404 DOI:10.1111/bjh.12532 Gallipoli P, Stobo J, Heaney N, Nicolini FE, Clark R, Wilson G, Tighe J, McLintock L, Hughes T, Michor F, Paul J, Drummond M, Holyoake TL. 2013. Safety and efficacy of pulsed imatinib with or without G-CSF versus continuous imatinib in chronic phase chronic myeloid leukaemia patients at 5 years follow-up. British journal of haematology. 163(5):674-6. Pubmed: 24032404 DOI:10.1111/bjh.12532