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Michor, Franziska

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Franziska

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Michor, Franziska
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    Breast Tumours Maintain a Reservoir of Subclonal Diversity During Expansion
    (Springer Science and Business Media LLC, 2021-03-24) Minussi, Darlan C.; Nicholson, Michael; Ye, Hanghui; Davis, Alexander; Wang, Kaile; Baker, Toby; Tarabichi, Maxime; Sei, Emi; Du, Haowei; Rabbani, Mashiat; Peng, Cheng; Hu, Min; Bai, Shanshan; Lin, Yu-wei; Schalck, Aislyn; Multani, Asha; Ma, Jin; McDonald, Thomas; Casasent, Anna; Barrera, Angelica; Chen, Hui; Lim, Bora; Arun, Banu; Meric-Bernstam, Funda; Van Loo, Peter; Michor, Franziska; Navin, Nicholas E.
    Our knowledge of copy number evolution during the expansion of primary breast tumors is limited. To investigate this process, we developed a single cell, single-molecule DNA sequencing method and performed copy number analysis of 16,178 single cells from 8 triple-negative breast cancers (TNBCs) and 4 cell lines. Our data shows that breast tumors and cell lines are comprised of a large milieu of subclones (7-22) that are organized into a few (3-5) major superclones. Evolutionary analysis suggests that after clonal TP53 mutations, multiple LOH events and genome doubling, there was a period of transient genomic instability followed by ongoing copy number evolution during the primary tumor expansion. By subcloning single daughter cells in culture, we show that tumor cells re-diversify their genomes and do not retain isogenic properties. These data show that TNBCs continue to evolve chromosome aberrations and maintain a reservoir of subclonal diversity during primary tumor growth.
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    Subclonal Cooperation Drives Metastasis by Modulating Local and Systemic Immune Microenvironments
    (Springer Science and Business Media LLC, 2019-07) Cristea, Simona; Kwak, Minsuk; Qin, Yuanbo; Laszewski, Tyler; Luoma, Adrienne; Marusyk, Andriy; Wagle, Nikhil; Fang, Rongxin; Polyak, Kornelia; Janiszewska, Michalina; Tabassum, Doris; Castaño, Zafira; Yamamoto, Kimiyo; Kingston, Natalie; Murphy, Katherine; Shu, Shaokun; Harper, Nicholas; Gil del Alcazar, Carlos; Alečković, Maša; Ekram, Muhammad; Cohen, Ofir; Wucherpfennig, Kai; Michor, Franziska; McAllister, Sandra
    Most human tumours are heterogeneous, composed of cellular clones with different properties present at variable frequencies. Highly heterogeneous tumours have poor clinical outcomes, yet the underlying mechanism remains poorly understood. Here, we show that minor subclones of breast cancer cells expressing IL11 and FIGF (VEGFD) cooperate to promote metastatic progression and generate polyclonal metastases composed of driver and neutral subclones. Expression profiling of the epithelial and stromal compartments of monoclonal and polyclonal primary and metastatic lesions revealed that this cooperation is indirect, mediated through the local and systemic microenvironments. We identified neutrophils as a leukocyte population stimulated by the IL11-expressing minor subclone and showed that the depletion of neutrophils prevents metastatic outgrowth. Single-cell RNA-seq of CD45+ cell populations from primary tumours, blood and lungs demonstrated that IL11 acts on bone-marrow-derived mesenchymal stromal cells, which induce pro-tumorigenic and pro-metastatic neutrophils. Our results indicate key roles for non-cell-autonomous drivers and minor subclones in metastasis.
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    Mathematical Modeling of Erythrocyte Chimerism Informs Genetic Intervention Strategies for Sickle Cell Disease
    (Wiley, 2016-07-14) Brendel, Christian; Renella, Raffaele; Michor, Franziska; Altrock, Philipp; Orkin, Stuart; Williams, David
    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 beta-globin gene. The developmental switch from fetal gamma-globin to adult beta-globin is governed in part by the transcription factor (TF) BCL11A. This TF has been proposed as a therapeutic target for reactivation of gamma-globin and concomitant reduction of beta-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.
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    Non-cell autonomous tumor-growth driving supports sub-clonal heterogeneity
    (2014) Marusyk, Andriy; Tabassum, Doris P.; Altrock, Philipp; Almendro, Vanessa; Michor, Franziska; Polyak, Kornelia
    SUMMARY Cancers arise through a process of somatic evolution that can result in substantial sub-clonal heterogeneity within tumors. 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 tumor phenotypes and the competitive expansion of individual clones. We found that tumor growth can be driven by a minor cell subpopulation, which enhances the proliferation of all cells within a tumor by overcoming environmental constraints and yet can be outcompeted by faster proliferating competitors, resulting in tumor collapse. We then developed a mathematical modeling framework to identify the rules underlying the generation of intratumor clonal heterogeneity. We found that non-cell autonomous driving, together with clonal interference, stabilizes sub-clonal heterogeneity, thereby enabling inter-clonal interactions that can lead to new phenotypic traits.
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    Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model
    (Public Library of Science, 2017) Zhao, Rui; Catalano, Paul; DeGruttola, Victor G.; Michor, Franziska
    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.
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    Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients
    (Public Library of Science, 2018) Stein, Shayna; Zhao, Rui; Haeno, Hiroshi; Vivanco, Igor; Michor, Franziska
    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.
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    In situ single cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2+ breast cancer
    (2015) Janiszewska, Michalina; Liu, Lin; Almendro, Vanessa; Kuang, Yanan; Paweletz, Cloud; Sakr, Rita A.; Weigelt, Britta; Hanker, Ariella B.; Chandarlapaty, Sarat; King, Tari A.; Reis-Filho, Jorge S.; Arteaga, Carlos L.; Park, So Yeon; Michor, Franziska; Polyak, Kornelia
    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+ breast cancer during neoadjuvant therapy. We found that the two genetic events are not always present within the same cell. Chemotherapy selects for PIK3CA mutant cells, a minor subpopulation in nearly all treatment-naïve samples, and modulates genetic diversity within tumors. Treatment-associated changes in spatial distribution of cellular genetic diversity correlated with poor long-term outcome following adjuvant trastuzumab therapy. 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.
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    Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells
    (Oxford University Press, 2017) Han, Lin; Wu, Hua-Jun; Zhu, Haiying; Kim, Kun-Yong; Marjani, Sadie L.; Riester, Markus; Euskirchen, Ghia; Zi, Xiaoyuan; Yang, Jennifer; Han, Jasper; Snyder, Michael; Park, In-Hyun; Irizarry, Rafael; Weissman, Sherman M.; Michor, Franziska; Fan, Rong; Pan, Xinghua
    Abstract 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.
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    Phase II study of ruxolitinib, a selective JAK1/2 inhibitor, in patients with metastatic triple-negative breast cancer
    (Nature Publishing Group UK, 2018) Stover, Daniel G.; Gil Del Alcazar, Carlos R.; Brock, Jane; Guo, Hao; Overmoyer, Beth; Balko, Justin; Xu, Qiong; Bardia, Aditya; Tolaney, Sara M.; Gelman, Rebecca; Lloyd, Maxwell; Wang, Yu; Xu, Yaomin; Michor, Franziska; Wang, Vivian; Winer, Eric P.; Polyak, Kornelia; Lin, Nancy U.
    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 (T-score >5) by central immunohistochemistry. pSTAT3 staining was available from 171 of 217 consented patients and pSTAT3 T-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 JAK2 amplification. Ruxolitinib, as a single agent, did not meet the primary efficacy endpoint in this refractory patient population despite evidence of on-target activity.
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    Histone Modifications Are Associated with Transcript Isoform Diversity in Normal and Cancer Cells
    (Public Library of Science, 2014) Podlaha, Ondrej; De, Subhajyoti; Gonen, Mithat; Michor, Franziska
    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.