2013 — 2014 |
Winslow, Monte Meier |
R00Activity Code Description: To support the second phase of a Career/Research Transition award program that provides 1 -3 years of independent research support (R00) contingent on securing an independent research position. Award recipients will be expected to compete successfully for independent R01 support from the NIH during the R00 research transition award period. |
Functional Characterization of Hmga2 in Lung Cancer Progression
DESCRIPTION: Metastasis leads to most cancer-related deaths, yet many of the molecular determinants and their mechanisms of action remain unknown. This proposal details a career development plan and research objectives to further the training of Dr. Monte Winslow during his studies on cancer metastasis. While supervised by Dr. Tyler Jacks during the mentored phase of the K99, program the applicant will devote his time to the major objective of transitioning his gene-discovery work into functional validation. The Jacks laboratory and the Koch Institute for Integrative Cancer Research at the Massachusetts Institute of Technology are the ideal environment in which to conduct these studies, as they will provide all equipment, facilities and intellectual stimulation required for success. The applicant's ultimate goal is to direct an academic research laboratory addressing questions regarding the biology and mechanistic details that control metastasis, with the hope that this knowledge may, in time, impact human health. The proposed research builds heavily on preliminary data that uncovered down-regulation of the homeobox transcription factor Nkx2-1 as an important regulator of lung tumor progression and metastasis. Interrogation of Nkx2-1 regulated genes and analysis of tumors at defined stages of development indicate that Nkx2-1 may constrain tumors by repressing embryonically-restricted transcriptional regulators and components of the extracellular matrix. The proposed experiments will address the role of these factors in regulating metastasis-associated phenotype in vitro and tumor progression and metastasis in an autochthonous lung adenocarcinoma model in vivo. These experiments will contribute to our understanding of the molecular underpinning of lung adenocarcinoma progression towards malignancy consistent with the mission of the National Cancer Institute. The Specific Aims of this proposal are to: (1) Determine the relevance of Nkx2-1 and Nkx2-1-regulated genes to lung adenocarcinoma progression; (2) Interrogate the function of candidate genes in an autochthonous lung adenocarcinoma mouse model; (3) Determine the effect of Hmga2 loss on tumor progression and metastasis.
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1 |
2013 — 2017 |
Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Molecular Dissection of Lung Cancer Progression and Metastasis
DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer deaths in both men and women in the United States, with over 155,000 patients dying each year in this country alone. Several factors contribute to the poor outcome of lung cancer patients, but, as in most solid tumors, the ability of cancer cells to leave the primary tumor and establish inoperable metastases is a major impediment to successful therapy. Metastasis thus represents a major clinical challenge that is driven by as yet poorly understood cell state alterations. This proposal uses novel methods to uncover the molecular and cellular changes that underlie lung cancer progression and each step of the metastatic cascade. We will use a genetically-engineered lung adenocarcinoma mouse model that recapitulates the genetic alterations and histological progression of human lung adenocarcinoma. In Aim1, we will functionally interrogate lung cancer metastasis-promoting and -inhibiting genes in vivo, by using a lentiviral vector system to directly express rational candidate regulators of lung cancer metastasis in developing tumors in vivo. We will combine these tools with a genetically-engineered mouse model of lung adenocarcinoma which incorporates fluorescent marking of cancer cells to allow quantification of each step of the metastatic cascade. In Aim2, we will isolate lung adenocarcinoma cells from primary tumors and metastases by fluorescence activated cell-sorting to uncover gene expression profiles that define each stage of malignant progression. Gene expression changes that direct metastatic ability will help define potential biomarkers of the malignant disease state and reveal the relationship of global gene expression in primary tumors and their related metastases in different organs. In Aim3, we will analyze and functionally dissect gene function during human lung adenocarcinoma progression, through the correlation of candidate gene expression in human lung adenocarcinoma with clinical outcome and use of a defined lung epithelial cell transformation system to assess gene function both in cell culture and in vivo. Given the immense clinical impact of metastatic cancer and the current gap in understanding the molecular underpinnings of this disease state, both clinical practice and patient outcome would be greatly impacted by any new therapies that might result from the fundamental knowledge gained from our proposed analyses. By combining quantitative methods and powerful in vivo methods, we hope to uncover general principles that govern tumor progression and metastatic spread and ultimately uncover novel therapeutic targets across the continuum of cancer progression.
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1 |
2014 — 2015 |
Bogyo, Matthew (co-PI) [⬀] Winslow, Monte Meier |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Multiplexed in Vivo Drug Screening: Inhibitors of Metastatic Seeding
DESCRIPTION (provided by applicant): Pancreatic ductal adenocarcinoma (PDAC) is a prevalent and almost uniformly fatal malignancy. Several factors contribute to the poor outcome of PDAC patients, but the ability of cancer cells to leave the primary tumors and establish inoperable metastases remains a major impediment to successful therapy. Metastasis is a complex multistep process that is poorly understood at the molecular level. In particular, the molecular events that are required for a cancer cell to leave the blood and enter a secondary organ, a process called metastatic seeding, have remained elusive. The identification of tool compounds that inhibit metastatic seeding would not only illuminate the fundamental mechanisms that enable this process but also be directly translated into therapeutics to inhibit metastatic spread. While large in vitro compound screens have been used to address a variety of biological questions, it has remained difficult to use this approach for complex in vivo processes like metastasis, as it remains unclear which cell-based assays and readouts accurately reflect the in vivo process. High content in vivo chemical screens have historically been challenging due to the high cost of performing these assays in parallel. Our multi-disciplinary proposal will establish a novel method for in vivo multiplexed screening of covalent inhibitors to allow a chemical genetic dissection of the metastatic seeding process. To identify compounds that inhibit the initial steps of metastatic seeding we will screen a library of ~1,500 small molecule covalent inhibitors of hydrolytic enzymes. Importantly, these compounds contain electrophilic traps that irreversibly bind their targets, enabling sustained inhibition after in viro pretreatment of the cells without the need for continued dosing. To permit a multiplexed in vivo screening, we generated 96 variants of a metastasis-derived PDAC cell line in which each variant cell line contains a unique 6-nucleotide barcode (PDACBC). We will pretreat each PDACBC cell line in vitro with one irreversible inhibitor, then pool the 96 pretreated PDACBC cell lines. Barcode representation in the pre-injection and post-metastatic seeding cells will be determined using IlluminaTM sequencing of the barcode region. Barcodes that are underrepresented the post-seeding population will identify candidate inhibitors of metastatic seeding. To validate top candidates PDAC cells will be pretreated with top candidate compounds and assessed for their ability to seed metastases and form macro-metastasis. To identify the targets of these inhibitors we will generate tagged analogs of hit compounds to enable the purification of drug-target complexes followed by mass spectrometry-based protein identification. shRNA knockdown of these targets followed by intravenous injection will also be used to confirm the effect of the target on metastatic seeding. Our study will identify not only novel drug targets but also lead compounds potent enough to elicit a reduction in metastatic ability in vivo. Our study will advance our understanding of PDAC metastasis and provide insight into common mechanisms used by other cancer types.
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2015 — 2016 |
Winslow, Monte Meier |
R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Somatic Engineering-Based Models of Pancreatic Cancer
? DESCRIPTION (provided by applicant): Pancreatic ductal adenocarcinoma (PDAC) is an almost uniformly fatal malignancy that often presents clinically as late stage invasive and metastatic disease. Both cancer cell intrinsic and extrinsic factors contribute to pancreatic cancer initiation and progression but most steps remain poorly understood at the molecular level. Genetically engineered mouse models of human PDAC have been important tools to understand the early stages of pancreatic cancer development, many aspects of basic cancer biology, and evaluate new treatment strategies. Assessing gene function using conventional mouse models of pancreatic cancer is expensive, labor intensive, and slow with only minor efforts towards generating more accurate, rapid, and flexible alternatives. Furthermore, despite the clear importance of altering genes of interest within established pancreatic cancer this remains a major largely unanswered challenge. In this high-risk high-reward proposal, we document preliminary data and outline systems that will allow rapid functional interrogation of candidate genes in vivo at any stage of pancreatic cancer progression. We will generate flexible virus-based autochthonous mouse models of pancreatic cancer using a method of tumor induction based on retrograde pancreatic duct injection of viral Cre-expressing vectors. This will allow the rapid interrogation of gene function during pancreatic cancer development in vivo. Incorporation of lentiviral vectors containing a cDNA or shRNA targeting a gene of interest will enable genetic manipulation of PDAC in vivo no more difficult than altering a cell line in culture. To allow streamlined genomic alterations in mouse models of human pancreatic cancer we have also generated a mouse with Cre-regulatable Cas9 expression. In combination with the conventional conditional KrasG12D and tumor suppressor alleles this will allow lentiviral vectors carrying Cre and a guideRNA to induce CRISPR- mediated genome engineering in pancreatic cancer. Finally, we will combine viral-FLP induced pancreatic cancer initiation with secondary viral-Cre infection to enable temporally separated genetic and genomic alterations. These methods will greatly simplify and accelerate investigation of gene function in vivo and provide a path towards multiplexed combinatory genetic manipulations as well as pooled gain- and loss-of- function screens in pancreatic cancer in vivo. We have extensive expertise using genetic-engineering approaches to generate disease models, a growing effort in PDAC, considerable experience using other viral induced tumors models, and are well integrated within the Stanford pancreatic cancer basic science and clinical research community. PDAC patients have a 5 year survival rate of ~5% underscoring the need for truly novel approaches to accelerate the molecular characterization of this disease. With growing interest in the interaction of pancreatic cancer cells with the immune system and other stromal components during each step of carcinogenesis as well as the relative void of mechanistic knowledge related to metastatic progression, our high-risk project has the potential to benefit many pancreatic cancer investigators.
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2016 — 2018 |
Petrov, Dmitri (co-PI) [⬀] Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
A Quantitative Multiplexed Platform For the Pharmacogenomic Analysis of Lung Cancer
PROJECT SUMMARY Lung cancer is a major health burden, leading to more deaths than the next four major cancer types combined. Despite advances in clinical cancer genome sequencing and the development of many targeted therapies, understanding the relationship of tumor genotype to therapeutic response remains a major obstacle to translating existing drugs into effective cancer treatments in the clinic. Pharmacogenomic analysis of tumor response is often extrapolated from the analysis of patients' tumor responses or modeled using in vitro cultured cell line systems, but investigating the effect of tumor genotype on drug response in cell lines, patient-derived xenograft models, or patients themselves all have severe limitations. Genetically-engineered mouse models have emerged as particularly rigorous in vivo systems with which to test early stage oncology therapies and represent tractable models with which to investigate the impact of tumor genotype on therapy response. Current genetically-engineered mouse models are time-consuming, cost-intensive, and have unavoidable technical and experimental variability that has limited their use in translational studies. We have established a novel multiplexed somatic genome-editing approach that will allow the quantification of genotype-specific drug responses. This in vivo approach will increase in precision and scope of translational cancer pharmacogenomics studies. To quantify the effect of tumor suppressor gene inactivation on lung cancer growth, we established a system that combines somatic Cas9-mediated gene inactivation with existing genetically-engineered mouse models to generate ~30 different lung tumor genotypes. To quantify the exact size of each tumor and determine the size distribution of each tumor genotype, we induce tumors with barcoded vectors and use high-throughput sequencing and statistical approaches to determine the number of cancer cells in each tumor. We will combine our quantitative pooled genome-editing approach with pre-clinical treatments to uncover genotype-specific therapy responses. We will quantify the responses of ~30 different genotypes of tumors to several therapies that have been shown to have genotype-specific effects in lung adenocarcinoma models. This will extend our understanding of the genomic modifiers of treatment responses and define the experimental and statistical parameters to enable the most efficient use of these models for translational studies. Finally, by performing pre-clinical/co-clinical trials for targeted therapies across >30 tumor genotypes in parallel we will generate a pharmacogenomic map connecting lung adenocarcinoma genotype to targeted therapy response. Our ongoing clinical interactions will allow validation of our pharmacogenomic predictions in lung adenocarcinoma patients. This flexible system can incorporate additional tumor suppressors, allows for the investigation of genotype-specific responses to other therapies including immunotherapies, and be adapted to other cancer types. The techniques described in this proposal are ideally positioned to become a mainstay of pre-clinical/co-clinical trial design.
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2016 — 2020 |
Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Molecular Dissection of An Arntl2 Induced Pro-Metastatic Secretome
? DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer deaths in both men and women in the United States, with over 155,000 patients dying each year in this country alone. Several factors contribute to the poor outcome of lung cancer patients, but, as in most solid tumors, the ability of cancer cells to leave the primary tumor and establish inoperable metastases is a major impediment to successful therapy. Metastasis thus represents a major clinical challenge that is driven by as yet poorly understood cell state alterations. By integratin gene expression analyses on murine models of metastatic lung adenocarcinoma and human lung adenocarcinomas we identified the transcription factor Arntl2 as a key driver of lung adenocarcinoma metastatic ability. Arntl2 appears to drive metastatic fitness by controlling the expression of a complex pro-metastatic secretome that has the ability to greatly increase clonal growth potential. In Aim1, we will functionally interrogate Arntl2 function in human and mouse lung adenocarcinoma cell lines. We will perform gain- and loss-of-function experiments and fully assess the cellular phenotypes driven by Arntl2. Transplantation assays and quantification of initial adhesion, proliferation, and cell death within the metastatic site in vivo will elucidate te cellular consequence of high Arntl2 expression. In Aim2, we will investigate which Arntl2-regulated secreted factors cooperate to drive clonal growth and metastatic ability. We will integrate screening of recombinant proteins in cell culture, gain- and loss-of-function experiments in cell culture and in vivo, and therapeutically target pathways downstream of key pro-metastatic secreted proteins to better understand the importance of autocrine metastatic niche factors. In Aim3, we will use novel methods for CRISPR/Cas9-mediated genome editing and lentiviral-mediated cDNA expression to test the requirement and sufficiency of Arntl2 and Arntl2- regulated genes to promote step of the metastatic cascade in autochthonous mouse models of human lung cancer. Given the immense clinical impact of metastatic cancer and the current gap in understanding the molecular underpinnings of this disease state, both clinical practice and patient outcome would be greatly impacted by any new therapies that might result from the fundamental knowledge gained from our proposed analyses. By combining quantitative methods and powerful in vivo methods, we hope to uncover general principles that govern tumor progression and metastatic spread and ultimately reveal novel therapeutic targets across the continuum of cancer progression.
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1 |
2018 — 2021 |
Petrov, Dmitri (co-PI) [⬀] Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
(Pq4) Quantitative and Multiplexed Analysis of Gene Function in Cancer in Vivo
PROJECT SUMMARY Genome sequencing has catalogued the somatic alterations in human cancers and identified many putative driver genes. However, human cancers generally evolve through the sequential acquisition of multiple genomic alterations and simply identifying recurrent genomic alterations does not necessarily reveal their functional importance to cancer growth. Genetically engineered mouse models have become a mainstay for the analysis of gene function in cancer in vivo, however the breadth of their utility is limited by the fact that they are neither readily scalable nor sufficiently quantitative. To increase the scope and precision of in vivo cancer modeling, we previously integrated conventional genetically-engineered mouse models, CRISPR/Cas9-based somatic genome engineering, and quantitative genomics with mathematical approaches. We developed methods to inactivate multiple genes in parallel in mouse models of lung cancer using pools of barcoded sgRNA- containing lentiviral vectors. This tumor barcoding with sequencing (Tuba-seq) approach uncovers the size of each tumor, enables the parallel investigation of multiple tumor genotypes in individual mice, and allows the generation of large-scale maps of gene function within autochthonous cancer models. Our preliminary data and novel genetic systems, as well as our dedicated and collaborative team of investigators with expertise in cancer genetics, mouse models, genome-editing, clinical cancer care, and quantitative modeling make us uniquely positioned to conduct these studies. In this proposal, we will extend Tuba-seq to quantify the effect of combinatorial genetic alterations through the development and validation of a platform for the rapid and quantitative analysis of interactions between genetic alterations on tumor growth in vivo. To enable multiplexed and quantitative analysis of the impact of temporally controlled genomic alterations on cancer cell growth in vivo, we will also develop a system for inducible genome editing in established lung tumors. Finally, we will develop novel in vivo approaches to comprehensively and broadly uncover the gene expression programs in cancer cells of different genotypes in parallel. Through multiplexed in vivo genetic alterations, the effect of putative cancer drivers can be uncovered at an unprecedented scale and resolution. The results of this proposal will be significant because innovative methods for the cost-effective, quantitative, and multiplexed analysis of the genetic determinants of cancer pathogenesis will illuminate novel aspects of tumorigenesis and accelerate our ability to understand cancer evolution, drug responses, and therapy resistance.
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2018 — 2021 |
Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Molecular Dissection of Lkb1-Mediated Tumor Suppression
! PROJECT SUMMARY Lung cancer is the leading cause of cancer deaths in both men and women in the United States, with over 155,000 patients dying each year in this country alone. Cancer genome sequencing has begun to uncover the compendium of mutations within human lung adenocarcinoma, but despite these advances we still have a very limited understanding of the molecular and cellular mechanisms by which even the most frequently mutated genes drive cancer growth. In particular, the molecular and cellular consequences of tumor suppressor gene function have been difficult to understand, slowing our understanding of these pathways and stalling personalized oncology approaches aimed at tailoring therapies based on tumor suppressor genotypes. In this proposal, we will employ several innovative methods to uncover the mechanisms by which the Lkb1 tumor suppression constrains lung cancer growth. This will enable a detailed understanding of the tumor suppressive function of Lkb1. While current tools have led to important insights into tumor biology, the inability to restore tumor-suppressor genes of interest at will in established tumors in vivo, has hampered our understanding of their molecular and cellular functions. We have generated mice with a conditionally-inactivable and conditionally-restorable genetic system which allows Lkb1 inactivation and subsequent restoration in autochthonous tumors. To characterize Lkb1-mediated tumor suppression, we will use this allele system to restore Lkb1 expression in lung tumors in vivo. Cellular and molecular analysis both in cell culture and in vivo will extend preliminary findings which linkLkb1 to changes in chromatin accessibility. To further understand the impact of the chromatin landscape on Lkb1-mediated tumor suppression, we will perform cell culture and in vivo experiments focused on the epistatic relationship between Lkb1 and epigenetic modifying enzymes identified in a genome-scale screen for suppressors of Lkb1-mediated growth suppression. Finally, we will investigate the relative importance of the Sik family of kinases which we have found to be tumor suppressive Lkb1-substrates. Our overall goals are to understand the molecular and cellular responses of lung tumors to Lkb1/Sik-mediated tumor suppression as well as to uncover how this response is related to changes in chromatin state. Our preliminary data, novel genetic systems, and strong collaborative team make us uniquely positioned to conduct these studies. Our proposed research is significant because it will increase our fundamental understanding of how Lkb1 limits lung tumor growth, illuminate the connection between Lkb1 and chromatin state dynamics, and potentially uncover novel and therapeutically targetable pro-tumorigenic pathways. !
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2019 — 2021 |
Petrov, Dmitri (co-PI) [⬀] Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Unraveling Mechanisms of Tumor Suppression in Lung Cancer
PROJECT SUMMARY Genome sequencing has catalogued the somatic alterations in human cancers and identified many putative tumor suppressor genes. However, human cancers generally evolve through the sequential acquisition of multiple genomic alterations and simply identifying recurrent genomic alterations does not necessarily reveal their functional importance to cancer growth. Genetically engineered mouse models uniquely enable the introduction of defined genetic alterations into normal adult cells, which results in the initiation and growth of tumors entirely within their natural in vivo setting. However, the breadth of their utility is limited by the fact that they are neither readily scalable nor sufficiently quantitative. To increase the scope and precision of in vivo cancer modeling, we previously integrated conventional genetically engineered mouse models, CRISPR/Cas9-based somatic genome engineering, and quantitative genomics with mathematical approaches. Tumor barcoding coupled with CRISPR/Cas9-mediated gene inactivation and high-throughput barcode sequencing (Tuba-seq) enables the parallel investigation of multiple tumor genotypes in individual mice and allows the large-scale analysis of pairwise tumor suppressor alterations. In Aim 1, we will employ our multiplexed and quantitative Tuba-seq approach to quantify the impact of inactivating many uncharacterized putative tumor suppressor genes on tumor growth in vivo and across time. This analysis will broaden our understanding of the driving forces of tumorigenesis and uncover the potential clinical meaning of these genomic alterations. In Aim 2, we will uncover epistatic genetic interactions between tumor suppressor genes by generating de novo tumors with pairwise combination of tumor suppressor alterations. We will generate the first broad-scale functional understanding of the combinatorial effects of genomic alterations within an autochthonous cancer model. We will uncover the epistatic interactions of these genes and pathways, illuminating novel aspects of tumorigenesis, and potentially highlighting therapeutic vulnerabilities. In Aim 3, we will uncover the molecular programs in cancer cells of different genotypes. To gain insight into how the molecular outputs of single genomic alterations relate to the effects of pairwise alteration, we will also characterize tumors with combined inactivation of cooperative tumor suppressors. This will provide a molecular framework to understand the effects of novel tumor suppressors and uncover the molecular logic that drives the pattern of genomic alterations in human cancer. Our preliminary data, novel genetic systems, and strong collaborative team make us uniquely positioned to conduct these studies. The results of this proposal will be significant because these innovative, multidisciplinary, and highly quantitative approaches will accelerate our understanding of the determinants of cancer growth and will begin the systematic deconvolution of gene function during lung cancer growth in vivo.
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2021 |
Winslow, Monte Meier |
U01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Dissecting the Interplay Between Aging, Genotype and the Microenvironment in Lung Cancer
PROJECT SUMMARY Cancer is primarily a disease of the old. While this is due in part to the sequential acquisition of genomic alterations, aging is also associated with a constellation of changes that could impact tumor initiation and growth. These ?hallmarks of aging? involve diverse pathways that impinge on carcinogenesis and lead to systemic changes. However, despite the very close association between aging and cancer, or perhaps because of it, very little is known about how cancer cell-intrinsic, microenvironmental, and systemic age-related changes impact cancer initiation and growth. Genetically engineered mouse models uniquely enable the introduction of defined genetic alterations into normal adult cells with defined temporal control. Human lung cancer has been modeled using genetically engineered mouse models, and these tumors recapitulate many features of early-stage human lung adenocarcinoma. To increase the scope and precision of in vivo cancer modeling, we integrated conventional genetically engineered mouse models, CRISPR/Cas9-based somatic genome engineering, and quantitative genomics with statistical approaches. Tumor barcoding coupled with CRISPR/Cas9-mediated gene inactivation and high-throughput barcode sequencing (Tuba-seq) enables quantitative analysis of the effects of large panels of genes on tumor initiation and various facets of autochthonous tumor growth. These models can thus distinguish the effects of aging from mutational events while affording a level of precision that allows us to detect differences in tumor suppressor function across age contexts. In Aim 1, we will quantify the interaction between age and tumor suppressor gene function. Our in vivo experiments will define whether aging increases or decreases the absolute efficiency of tumor initiation and uncover the impact of aging on the importance of diverse tumor suppressor genes on tumor initiation and growth. In Aim 2. we will determine how the lung tumor microenvironment and lung cancer cells themselves change with age. We will elucidate the impact of tumor genotype on the microenvironment across age and determine whether age-dependent changes in growth are accompanied by dramatic differences in cancer cell state. In Aim 3, we will disentangle cell-autonomous differences in tumors developing in young and aged mice from effects on tumor suppressor function driven specifically by aging of the local tissue and systemic host environments. These experiments will provide insight into whether age-dependent genotype-specific effects are largely cancer cell-intrinsic or driven by the shifts in the microenvironment or whole organism environment. By permuting cancer cell age and genotype, as well as microenvironment and host age, we will gain an unprecedented understanding of the contribution of these factors to multiple aspects of lung carcinogenesis. Ultimately, these findings could have important implication for cancer prevention, detection, and treatment.
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2021 |
Politi, Katerina Abigail [⬀] Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Genetic Determits of Tumor Growth and Drug Sensitivity in Egfr Mutant Lung Cancer
PROJECT SUMMARY The discovery of mutations in EGFR that drive lung cancer growth and confer sensitivity to tyrosine kinase inhibitors (TKIs) has transformed the treatment of lung cancer. However, responses to TKIs are variable and resistance ultimately develops. Thus, EGFR-driven lung cancers still cause ~20,000 deaths annually in the US. These tumors have frequent alterations in diverse tumor suppressor genes (TSGs), however which of these alterations co-operate to drive tumor growth, how they impact cancer cell state, and whether they are key determinants of responses to therapy remains largely unknown. Current methods to uncover relationships between EGFR and TSGs largely rely on correlative human genomic studies and cell line-based models. However, genomic studies are often statistically underpowered to uncover genetic interactions and do not provide information on TSG function. Conversely, cell line studies do not recapitulate the in vivo environment and the limited cell lines that exist represent only a subset of EGFR mutant tumors. To overcome these limitations and better understand the genomic drivers of lung cancer growth and drug responses in vivo, we recently integrated a novel autochthonous mouse model of oncogenic EGFR-driven lung cancer with CRISPR/Cas9- mediated somatic genome editing and high-throughput tumor barcode sequencing. Using this multiplexed in vivo model, we uncovered the splicing factor RBM10 as a poorly characterized suppressor of tumor growth and unexpectedly found that inactivation of the ?tumor suppressor? Lkb1 is synthetic lethal with oncogenic EGFR. Here, we will investigate how genotype controls the biology of oncogenic EGFR-driven lung cancer. Specifically, we will establish the cellular and molecular consequences of Rbm10 inactivation and elucidate the mechanism that underlies the synthetic lethality between EGFR and Lkb1. Moreover, understanding how tumor genotype influences treatment responses could reveal genotype-specific therapeutic vulnerabilities. Thus, we will leverage our multiplexed in vivo gene editing platform to determine the impact of additional TSGs on EGFR mutant lung cancer growth and uncover genomic drivers of responses to therapy. This work will increase our fundamental understanding of the genomic determinants of EGFR mutant lung cancer growth and reveal novel and therapeutically targetable pro-tumorigenic pathways. These findings could ultimately inform precision treatments for patients with oncogenic EGFR-driven lung cancer.
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0.97 |
2021 |
Winslow, Monte Meier |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Genetic Dissection of Oncogenic Kras Signaling
ABSTRACT Lung cancer is a prevalent cancer type that leads to more deaths than the next four major cancer types combined. KRAS is one of the most frequent oncogenes in human lung cancer. Despite more than 30 years of biochemical and cell culture studies, as well as correlative studies on human tumors and clinical trials, therapeutic options for patients with oncogenic KRAS-driven tumors are just beginning to emerge. KRAS is often mutated at codons 12 and 13, but these mutations are diverse and these different mutant forms of KRAS have dramatically different biochemical features. By integrating conventional genetically-engineered mouse models and CRISPR/Cas9-based somatic genome engineering with quantitative genomics and mathematical modeling, we recently established CRISPR/Cas9-based approaches that enable the generation and quantitative analysis of multiple tumor genotypes in parallel in vivo. By employing homology directed repair in somatic cells, we induce a panel of oncogenic Kras variants, and uncovered an unexpectedly dramatic difference in oncogenic potential of different Kras variants in vivo. In addition to the diversity of different oncogenic KRAS variants, the compendium of important pathways downstream of oncogenic KRAS remains relatively poorly understood. The goals of this proposal are 1) to use genomic and pharmacological methods to generate a quantitative understanding of different signaling requirements in cancers driven by different Kras variants and 2) to uncover novel functional regulators of Kras-driven carcinogenesis. To understand the basis for the differential oncogenic potential of different oncogenic Kras variants, we will use our multiplexed genetic approaches to quantify the impact of increasing either overall Kras signaling or discrete downstream pathways on the in vivo tumorigenic potential of diverse oncogenic Kras variants. We will also use therapeutic treatments to uncover the requirement for sustained PI3K and Raf/Mek/Erk signaling in established lung tumors driven by diverse Kras variants. Finally, to expand our understanding of Kras-driven tumorigenesis beyond the canonical effect pathways, we will directly analyze the function of novel Kras-interacting proteins on lung tumor growth in vivo. By performing multiplexed genomic and pharmacologic analyses of oncogenic Kras signaling in cancer, we will uncover the molecular mechanisms that contribute to tumor growth driven by different variants of KRAS. We will define specific therapeutic sensitivities of lung tumors driven by diverse oncogenic mutations. Our proposed research is significant because it will uncover interesting new areas of biology, motivate genotype-directed clinical trials, and facilitate precision cancer therapy for lung cancer patients with KRAS- mutant tumors.
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