Biology subjects

Winslow, M. M.

Publications and source records attributed to Winslow, M. M..

23 records · Page 2Linked to original sources

bioRxiv2021

LKB1 inactivation modulates chromatin accessibility to drive metastatic progression

Metastasis is the leading cause of cancer-related deaths, enabling cancer cells to expand to secondary sites and compromise organ function1. Given that primary tumors and metastases often share the same constellation of driver mutations2-4, the mechanisms driving their distinct phenotypes are unclear. Here, we show that inactivation of the frequently mutated tumor suppressor gene, liver kinase B1 (LKB1), has evolving effects throughout lung cancer progression, leading to the differential epigenetic re-programming of early-stage primary tumors compared to late-stage metastases. By integrating genome-scale CRISPR/Cas9 screening with bulk and single-cell multi-omic analyses, we unexpectedly identify LKB1 as a master regulator of chromatin accessibility in lung adenocarcinoma primary tumors. Using an in vivo model of metastatic progression, we further reveal that loss of LKB1 activates the early endoderm transcription factor SOX17 in metastases and a metastatic-like sub-population of cancer cells within primary tumors. SOX17 expression is necessary and sufficient to drive a second wave of epigenetic changes in LKB1-deficient cells that enhances metastatic ability. Overall, our study demonstrates how the downstream effects of an individual driver mutation can appear to change throughout cancer development, with implications for stage-specific therapeutic resistance mechanisms and the gene regulatory underpinnings of metastatic evolution.

cancer biology↗

bioRxiv2020

miR-200 deficiency promotes lung cancer metastasis by activating cancer-associated fibroblasts

Lung adenocarcinoma, the most prevalent lung cancer subtype, is characterized by its high propensity to metastasize. Despite the importance of metastasis in lung cancer mortality, its underlying cellular and molecular mechanisms remain largely elusive. Here, we identified miR-200 miRNAs as potent suppressors for lung adenocarcinoma metastasis. miR-200 expression is specifically repressed in mouse metastatic lung adenocarcinomas, and miR-200 decrease strongly correlates with poor patient survival. Consistently, deletion of mir-200c/141 in the KrasLSL-G12D/+; Trp53flox/flox lung adenocarcinoma mouse model significantly promoted metastasis, generating a desmoplastic tumor stroma highly reminiscent of metastatic human lung cancer. miR-200 deficiency in lung cancer cells promotes the proliferation and activation of adjacent cancer-associated fibroblasts (CAFs), which in turn elevates the metastatic potential of cancer cells. miR-200 regulates the functional interaction between cancer cells and CAFs, at least in part, by targeting Notch ligand Jagged1 and Jagged2 in cancer cells and inducing Notch activation in adjacent CAFs. Hence, the interaction between cancer cells and CAFs constitutes an essential mechanism to promote metastatic potential.

cancer biology↗

bioRxiv2020

Genetic determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo

Cancer genome sequencing has uncovered substantial complexity in the mutational landscape of tumors. Given this complexity, experimental approaches are necessary to establish the impact of combinations of genetic alterations on tumor biology and to uncover genotype-dependent effects on drug sensitivity. In lung adenocarcinoma, EGFR mutations co-occur with many putative tumor suppressor gene alterations, however the extent to which these alterations contribute to tumor growth and their response to therapy in vivo has not been explored experimentally. By integrating a novel mouse model of oncogenic EGFR-driven Trp53-deficient lung adenocarcinoma with multiplexed CRISPR-Cas9-mediated genome editing and tumor barcode sequencing, we quantified the effects of inactivation of ten putative tumor suppressor genes. Inactivation of Apc, Rb1, or Rbm10 most strongly promoted tumor growth. Unexpectedly, inactivation of Lkb1 or Setd2 - which are the strongest drivers of tumor growth in an oncogenic Kras-driven model - reduced EGFR-driven tumor growth. These results are consistent with the relative frequency of these tumor suppressor gene alterations in human EGFR- and KRAS-driven lung adenocarcinomas. Furthermore, Keap1 inactivation reduces the sensitivity of EGFR-driven Trp53-deficient tumors to the EGFR inhibitor osimertinib. Importantly, in human EGFR/TP53 mutant lung adenocarcinomas, mutations in the KEAP1 pathway correlated with decreased time on tyrosine kinase inhibitor treatment. Our study highlights how genetic alterations can have dramatically different biological consequences depending on the oncogenic context and that the fitness landscape can shift upon drug treatment.

cancer biology↗

bioRxiv2020

G-baToN: a versatile cell-cell interaction reporter system.

Cell-cell interactions influence all aspects of development, homeostasis, and disease. In cancer, interactions between cancer cells and stromal cells play a major role in nearly every step of carcinogenesis. Thus, the ability to record cell-cell interactions would facilitate mechanistic delineation of the role of cancer microenvironment. Here, we describe GFP-based Touching Nexus (G-baToN) which relies upon nanobody-directed fluorescent protein transfer to enable sensitive and specific labeling of cells after cell-cell interactions. G-baToN is a generalizable system that enables physical contact-based labeling between various cell types, including diverse cancer-stromal cell pairs. A suite of orthogonal baToN tools enables reciprocal cell-cell labeling, interaction-dependent cargo transfer, and the identification of higher-order cell-cell interactions across a wide range of cell types. The ability to track physically interacting cells with these simple and sensitive systems will greatly accelerate our understanding of the outputs of cell-cell interactions in cancer as well as across many biological processes.

bioengineering↗

bioRxiv2020

Quantitative in vivo analyses reveal a complex pharmacogenomic landscape in lung adenocarcinoma

AbstractThe lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most important gaps in enabling the effective use of cancer therapies. Here, we couple a multiplexed and quantitative platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses in vivo. We uncover a surprisingly complex map of genotype-specific therapeutic responses, with over 20% of possible interactions showing significant resistance or sensitivity. We validate one of these interactions - the resistance of Keap1 mutant tumors to platinum therapy - using a large patient response dataset. Our results highlight the importance of understanding the genetic determinants of treatment responses in the development of precision therapies and define a strategy to identify such determinants.

cancer biology↗