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Liu, Lin

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Liu, Lin

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2013 - 20175

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Author's Publications: search.filters.isAuthorOfPublication.404c2e32-4139-437a-ba7f-39a24f548fb1

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Now showing 1 - 5 of 5
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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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    DNA replication timing and higher-order nuclear organization determine single nucleotide substitution patterns in cancer genomes
    (2013) Liu, Lin; De, Subhajyoti; Michor, Franziska
    Single nucleotide substitutions (SNS) are a defining characteristic of cancer genomes. Many SNS in cancer genomes arise due to errors in DNA replication, which is spatio-temporally stratified. Here we propose that DNA replication patterns help shape the mutational landscapes of normal and cancer genomes. Using data on five fully sequenced cancer types and two personal genomes, we determined that the frequency of intergenic SNS is significantly higher in late DNA replication timing regions, even after controlling for a number of genomic features. Furthermore, some substitution signatures are more frequent in certain DNA replication timing zones. Finally, integrating data on higher-order nuclear organization, we found that genomic regions in close spatial proximity to late replicating domains display similar mutation spectra as the late replicating regions themselves. These data suggest that DNA replication timing together with higher-order genomic organization contribute to the patterns of SNS in normal and cancer genomes.
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    An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer
    (Public Library of Science, 2015) Foo, Jasmine; Liu, Lin; Leder, Kevin; Riester, Markus; Iwasa, Yoh; Lengauer, Christoph; Michor, Franziska
    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.
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    Dose-Dependent Mutation Rates Determine Optimum Erlotinib Dosing Strategies for EGFR Mutant Non-Small Cell Lung Cancer Patients
    (Public Library of Science, 2015) Liu, Lin; Li, Fei; Pao, William; Michor, Franziska
    Background: The advent of targeted therapy for cancer treatment has brought about a paradigm shift in the clinical management of human malignancies. Agents such as erlotinib used for EGFR-mutant non-small cell lung cancer or imatinib for chronic myeloid leukemia, for instance, lead to rapid tumor responses. Unfortunately, however, resistance often emerges and renders these agents ineffective after a variable amount of time. The FDA-approved dosing schedules for these drugs were not designed to optimally prevent the emergence of resistance. To this end, we have previously utilized evolutionary mathematical modeling of treatment responses to elucidate the dosing schedules best able to prevent or delay the onset of resistance. Here we expand on our approaches by taking into account dose-dependent mutation rates at which resistant cells emerge. The relationship between the serum drug concentration and the rate at which resistance mutations arise can lead to non-intuitive results about the best dose administration strategies to prevent or delay the emergence of resistance. Methods: We used mathematical modeling, available clinical trial data, and different considerations of the relationship between mutation rate and drug concentration to predict the effectiveness of different dosing strategies. Results: We designed several distinct measures to interrogate the effects of different treatment dosing strategies and found that a low-dose continuous strategy coupled with high-dose pulses leads to the maximal delay until clinically observable resistance. Furthermore, the response to treatment is robust against different assumptions of the mutation rate as a function of drug concentration. Conclusions: For new and existing targeted drugs, our methodology can be employed to compare the effectiveness of different dose administration schedules and investigate the influence of changing mutation rates on outcomes.
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    Nuclear topology modulates the mutational landscapes of cancer genomes
    (2017) Smith, Kyle S.; Liu, Lin; Ganesan, Shridar; Michor, Franziska; De, Subhajyoti
    Nuclear organization of genomic DNA affects DNA damage and repair processes, and yet its impact on mutational landscapes in cancer genomes remains unclear. Here we analyzed genome-wide somatic mutations from 366 samples of 6 cancer types. We found that lamina-associated regions, which are typically localized at the nuclear periphery, displayed higher somatic mutation frequencies compared to the inter-lamina regions at the nuclear core. This effect remained even after adjusting for features such as GC%, chromatin, and replication timing. Furthermore, mutational signatures differed between the nuclear core and periphery, indicating differences in the patterns of DNA damage and/or DNA repair processes. For instance, smoking and UV-related signatures were more enriched in the nuclear periphery. Substitutions at certain motifs were also more common in the nuclear periphery. Taken together, we found that the nuclear architecture influences mutational landscapes in cancer genomes beyond the effects already captured by chromatin and replication timing.