Biology subjects

Winslow, M. M.

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

At least 19 recordsLinked to original sources

bioRxiv2026

Targeted cancer ablation via programmable sensing of amplified oncogenic RNA

Selectively eliminating cancer cells based on their oncogenic drivers holds great promise but remains challenging for targeted cancer therapy. Here, we present ORCA (Oncogenic RNA-triggered Cancer Ablation), a programmable and modular platform that couples RADAR-based detection of oncogenic RNA with conditional expression of therapeutic payloads in cancer cells. We identify RADAR sensors targeting the transcripts of endogenously amplified oncogenes, including MYC, FGFR2 and wild-type KRAS in colorectal and gastric cancer cells. Focusing on colorectal cancer (CRC) driven by extrachromosomal DNA-amplified MYC, we demonstrate targeted ablation of high-MYC cancer cells using two orthogonal strategies: anti-CD19 CAR-T therapy and enzyme-prodrug therapy. In vivo delivery of ORCA using adeno-associated virus (AAV) suppresses tumor growth in a subcutaneous xenograft model and prolongs survival in a CRC liver metastasis model. ORCA establishes oncogenic RNAs as actionable inputs for targeted cancer therapy via programmable RNA sensing, thus offering a strategy to target tumors through the transcripts of otherwise difficult-to-drug oncogenes such as MYC.

synthetic biology↗

bioRxiv2026

Transcriptional Response to Tumor Mutational Burden Is Consistent Across Cancer Types

Tumor mutational burden (TMB) shapes tumor transcriptional state, but studies typically describe this response as an average effect pooled across cancer types. Whether that average reflects a consistent response present within individual cancer types, or is an artifact of merging heterogeneous, tissue-specific responses, remains unresolved. Here we analyze ~9,100 tumors across 32 TCGA cancer types to test whether the transcriptional response to TMB is genuinely consistent across tissues. We construct a TMB axis score from TMB-associated genes upregulated with increasing TMB, yielding a sample-level measure of response strength, and subsequently decompose it at the component and pathway/complex levels. The pooled transcriptional response to TMB stays largely consistent within each cancer type, and no single cancer is driving the pooled signal. This consistency was also observed at the component and pathway/complex levels. These findings support TMB as a promising tissue-agnostic signature, with implications for tissue-agnostic therapeutic targeting.

cancer biology↗

bioRxiv2026

CXCL-CXCR2 signaling drives cancer-endothelium interactions in SCLC metastatic seeding

Small cell lung cancer (SCLC) is a highly metastatic malignancy with tropism to the liver, yet the signals that enable organ-specific metastatic colonization remain largely undefined. During metastasis, disseminated cancer cells first encounter endothelial cells (ECs) at the vascular-tissue interface, positioning cancer-endothelium crosstalk as a key determinant of metastatic success. Defining the signaling pathways underlying this reciprocal communication may uncover actionable vulnerabilities for preventing and treating this lethal disease. Here, we uncover an EC-derived CXCL chemokine program that activates cancer-intrinsic CXCR2-RAC1 signaling as a critical mediator of SCLC liver metastasis. By integrating in vitro and in vivo models, we show that SCLC cells induce robust CXCL chemokine expression from liver ECs, which in turn enhances SCLC migration and reinforces cancer cell-EC interactions. We applied highly quantitative metastatic colony barcode sequencing coupled with individual gene inactivation to demonstrate that CXCR2 is essential for SCLC migration and liver metastatic seeding. Mechanistically, CXCL-CXCR2 signaling activates RAC1-dependent F-actin assembling to drive SCLC motility during CXCL-induced metastatic seeding. Pharmacologic inhibition of CXCR2 or RAC1 suppresses SCLC migration and prevents SCLC liver metastasis. Together, our research defined a chemokine-driven signaling circuit that governs cancer-endothelium communication during the metastatic cascade and nominate the CXCL-CXCR2-RAC1 axis as a promising therapeutic vulnerability for preventing and treating metastatic SCLC.

cancer biology↗

bioRxiv2025

Tumor suppressor genotype influences the extent and mode of immunosurveillance in lung cancer

The impact of cancer driving mutations in regulating immunosurveillance throughout tumor development remains poorly understood. To better understand the contribution of tumor genotype to immunosurveillance, we generated and validated lentiviral vectors that create an epi-allelic series of increasingly immunogenic neoantigens. This vector system is compatible with autochthonous Cre-regulated cancer models, CRISPR/Cas9-mediated somatic genome editing, and tumor barcoding. Here, we show that in the context of KRAS-driven lung cancer and strong neoantigen expression, tumor suppressor genotype dictates the degree of immune cell recruitment, positive selection of tumors with neoantigen silencing, and tumor outgrowth. By quantifying the impact of 11 commonly inactivated tumor suppressor genes on tumor growth across neoantigenic contexts, we show that the growth promoting effects of tumor suppressor gene inactivation correlate with increasing sensitivity to immunosurveillance. Importantly, specific genotypes dramatically increase or decrease sensitivity to immunosurveillance independently of their growth promoting effects. We propose a model of immunoediting in which tumor suppressor gene inactivation works in tandem with neoantigen expression to shape tumor immunosurveillance and immunoediting such that the same neoantigens uniquely modulate tumor immunoediting depending on the genetic context. One Sentence SummaryHere we uncover an under-appreciated role for tumor suppressor gene inactivation in shaping immunoediting upon neoantigen expression.

cancer biology↗

bioRxiv2024

A STAG2-PAXIP1/PAGR1 axis suppresses lung tumorigenesis

The cohesin complex is a critical regulator of gene expression. STAG2 is the most frequently mutated cohesin subunit across several cancer types and is a key tumor suppressor in lung cancer. Here, we coupled somatic CRISPR-Cas9 genome editing and tumor barcoding with an autochthonous oncogenic KRAS-driven lung cancer model and show that STAG2 is uniquely tumor suppressive among all core and auxiliary cohesin components. The heterodimeric complex components PAXIP1 and PAGR1 have highly correlated effects with STAG2 in human lung cancer cell lines, are tumor suppressors in vivo, and are epistatic to STAG2 in oncogenic KRAS-driven lung tumorigenesis in vivo. STAG2 inactivation elicits changes in gene expression, chromatin accessibility and 3D genome conformation that impact cancer cell state. Gene expression and chromatin accessibility similarities between STAG2- and PAXIP1-deficient neoplastic cells further relates STAG2-cohesin to PAXIP1/PAGR1. These findings reveal a STAG2-PAXIP1/PAGR1 tumor-suppressive axis and uncover novel PAXIP1-dependent and PAXIP1-independent STAG2-cohesin mediated mechanisms of lung tumor suppression. SUMMARYSTAG2 is a frequently mutated cohesin subunit across several cancers and one of the most important functional suppressors of lung adenocarcinoma. Our findings underscore important roles of STAG2 in suppressing lung tumorigenesis and highlight a STAG2-PAXIP1/PAGR1 tumor-suppressive program that may transcend cancer type.

cancer biology↗

bioRxiv2024

Integrative multiomic approaches reveal ZMAT3 and p21 as conserved hubs in the p53 tumor suppression network

TP53, the most frequently mutated gene in human cancer, encodes a transcriptional activator that induces myriad downstream target genes. Despite the importance of p53 in tumor suppression, the specific p53 target genes important for tumor suppression remain unclear. Recent studies have identified the p53-inducible gene Zmat3 as a critical effector of tumor suppression, but many questions remain regarding its p53-dependence, activity across contexts, and mechanism of tumor suppression alone and in cooperation with other p53-inducible genes. To address these questions, we used Tuba-seqUltra somatic genome editing and tumor barcoding in a mouse lung adenocarcinoma model, combinatorial in vivo CRISPR/Cas9 screens, meta-analyses of gene expression and Cancer Dependency Map data, and integrative RNA-sequencing and shotgun proteomic analyses. We established Zmat3 as a core component of p53-mediated tumor suppression and identified Cdkn1a as the most potent cooperating p53-induced gene in tumor suppression. We discovered that ZMAT3/CDKN1A serve as near-universal effectors of p53-mediated tumor suppression that regulate cell division, migration, and extracellular matrix organization. Accordingly, combined Zmat3-Cdkn1a inactivation dramatically enhanced cell proliferation and migration compared to controls, akin to p53 inactivation. Together, our findings place ZMAT3 and CDKN1A as hubs of a p53-induced gene program that opposes tumorigenesis across various cellular and genetic contexts.

cancer biology↗

bioRxiv2024

EML4-ALK variant-specific genetic interactions shape lung tumorigenesis

Oncogenic fusions of EML4 and ALK occur in [~]5% of lung adenocarcinomas. More than 15 EML4-ALK variants with distinct breakpoints within EML4 have been identified, but the functional differences between these variants remain poorly understood. Here we use CRISPR/Cas9 somatic genome editing to generate autochthonous mouse models of the two most common EML4-ALK variants, V1 and V3, and show that V3 is more oncogenic than V1. By integrating these models with multiplexed genome editing, we quantify the effects of 29 putative tumor suppressor genes on V1- and V3-driven lung cancer growth in vivo and show that many tumor suppressor genes have dramatically variant-specific effects on tumorigenesis. Analysis of a novel dataset representing the largest human EML4-ALK lung cancer cohort to date identified alterations in the genomic landscape depending on the EML4-ALK variant. These findings demonstrate functional heterogeneity among EML4-ALK variants, suggesting that EML4-ALK variants behave more like distinct oncogenes than a uniform entity. More broadly, these findings highlight the dramatic impact of oncogenic fusions partner proteins on tumor biology.

cancer biology↗

bioRxiv2024

Functional mapping of epigenetic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes

Epigenetic dysregulation is widespread in cancer. However, the specific epigenetic regulators and the processes they control to drive cancer phenotypes are poorly understood. Here, we employed a novel, scalable and high-throughput in vivo method to perform iterative functional screens of over 250 epigenetic regulatory genes within autochthonous oncogenic KRAS-driven lung tumors. We identified multiple novel epigenetic tumor suppressor and tumor dependency genes. We show that a specific HBO1 complex and the MLL1 complex are among the most impactful tumor suppressive epigenetic regulators in lung. The histone modifications generated by the HBO1 complex are frequently absent or reduced in human lung adenocarcinomas. The HBO1 and MLL1 complexes regulate chromatin accessibility of shared genomic regions, lineage fidelity and the expression of canonical tumor suppressor genes. The HBO1 and MLL1 complexes are epistatic during lung tumorigenesis, and their functional correlation is conserved in human cancer cell lines. Together, these results demonstrate the value of quantitative methods to generate a phenotypic roadmap of epigenetic regulatory genes in tumorigenesis in vivo.

cancer biology↗

bioRxiv2024

Aging represses lung tumorigenesis and alters tumor suppression

Most cancers are diagnosed in persons over the age of sixty, but little is known about how age impacts tumorigenesis. While aging is accompanied by mutation accumulation -- widely understood to contribute to cancer risk -- it is also associated with numerous other cellular and molecular changes likely to impact tumorigenesis. Moreover, cancer incidence decreases in the oldest part of the population, suggesting that very old age may reduce carcinogenesis. Here we show that aging represses tumor initiation and growth in genetically engineered mouse models of human lung cancer. Moreover, aging dampens the impact of inactivating many, but not all, tumor suppressor genes with the impact of inactivating PTEN, a negative regulator of the PI3K/AKT pathway, weakened to a disproportionate extent. Single-cell transcriptomic analysis revealed that neoplastic cells from tumors in old mice retain many age-related transcriptomic changes, showing that age has an enduring impact that persists through oncogenic transformation. Furthermore, the consequences of PTEN inactivation were strikingly age-dependent, with PTEN deficiency reducing signatures of aging in cancer cells and the tumor microenvironment. Our findings suggest that the relationship between age and lung cancer incidence may reflect an integration of the competing effects of driver mutation accumulation and tumor suppressive effects of aging.

cancer biology↗

bioRxiv2024

Modeling the genomic complexity of human cancer using Cas12a mice

Somatic genome editing in mouse models has increased our understanding of the in vivo effects of genetic alterations in areas ranging from neuroscience to cancer biology and beyond. However, existing models are limited in their ability to create multiple targeted edits. Thus, our understanding of the complex genetic interactions that underlie development, homeostasis, and disease remains incomplete. Cas12a is an RNA-guided endonuclease with unique attributes that enable simple targeting of multiple genes with crRNA arrays containing tandem guides. To accelerate and expand the generation of complex genotypes in somatic cells, we generated transgenic mice with Cre-regulated and constitutive expression of enhanced Acidaminococcus sp. Cas12a (enAsCas12a). In these mice, enAsCas12a-mediated somatic genome editing robustly generated compound genotypes, as exemplified by the initiation of diverse cancer types driven by homozygous inactivation of trios of tumor suppressor genes. We further integrated these modular crRNA arrays with clonal barcoding to quantify the size and number of tumors with each array, as well as the efficiency of each crRNA. These Cas12a alleles will enable the rapid generation of disease models and broadly facilitate the high-throughput investigation of coincident genomic alterations in somatic cells in vivo.

cancer biology↗

bioRxiv2024

Combinatorial in vivo genome editing identifies widespread epistasis during lung tumorigenesis

Lung adenocarcinoma, the most common subtype of lung cancer, is genomically complex, with tumors containing tens to hundreds of non-synonymous mutations. However, little is understood about how genes interact with each other to enable tumorigenesis in vivo, largely due to a lack of methods for investigating genetic interactions in a high-throughput and multiplexed manner. Here, we employed a novel platform to generate tumors with all pairwise inactivation of ten tumor suppressor genes within an autochthonous mouse model of oncogenic KRAS-driven lung cancer. By quantifying the fitness of tumors with every single and double mutant genotype, we show that most tumor suppressor genetic interactions exhibited negative epistasis, with diminishing returns on tumor fitness. In contrast, Apc inactivation showed positive epistasis with the inactivation of several other genes, including dramatically synergistic effects on tumor fitness in combination with Lkb1 or Nf1 inactivation. This approach has the potential to expand the scope of genetic interactions that may be functionally characterized in vivo, which could lead to a better understanding of how complex tumor genotypes impact each step of carcinogenesis.

cancer biology↗

bioRxiv2024

A Lung Cancer Mouse Model Database

Lung cancer, the leading cause of cancer mortality, exhibits diverse histological subtypes and genetic complexities. Numerous preclinical mouse models have been developed to study lung cancer, but data from these models are disparate, siloed, and difficult to compare in a centralized fashion. Here we established the Lung Cancer Mouse Model Database (LCMMDB), an extensive repository of 1,354 samples from 77 transcriptomic datasets covering 974 samples from genetically engineered mouse models (GEMMs), 368 samples from carcinogen-induced models, and 12 samples from a spontaneous model. Meticulous curation and collaboration with data depositors have produced a robust and comprehensive database, enhancing the fidelity of the genetic landscape it depicts. The LCMMDB aligns 859 tumors from GEMMs with human lung cancer mutations, enabling comparative analysis and revealing a pressing need to broaden the diversity of genetic aberrations modeled in GEMMs. Accompanying this resource, we developed a web application that offers researchers intuitive tools for in-depth gene expression analysis. With standardized reprocessing of gene expression data, the LCMMDB serves as a powerful platform for cross-study comparison and lays the groundwork for future research, aiming to bridge the gap between mouse models and human lung cancer for improved translational relevance.

cancer biology↗

bioRxiv2023

Fully accessible fitness landscape of oncogene-negative lung adenocarcinoma

Cancer genomes are almost invariably complex with genomic alterations cooperating during each step of carcinogenesis. In cancers that lack a single dominant oncogene mutation, cooperation between the inactivation of multiple tumor suppressor genes can drive tumor initiation and growth. Here, we shed light on how the sequential acquisition of genomic alterations generates oncogene-negative lung tumors. We couple tumor barcoding with combinatorial and multiplexed somatic genome editing to characterize the fitness landscapes of three tumor suppressor genes NF1, RASA1, and PTEN, the inactivation of which jointly drives oncogene-negative lung adenocarcinoma initiation and growth. The fitness landscape was surprisingly accessible, with each additional mutation leading to growth advantage. Furthermore, the fitness landscapes remained fully accessible across backgrounds with additional tumor suppressor mutations. These results suggest that while predicting cancer evolution will be challenging, acquiring the multiple alterations required for the growth of oncogene-negative tumors can be facilitated by the lack of constraints on mutational order.

cancer biology↗

bioRxiv2022

Oncogenic context shapes the fitness landscape of tumor suppression

Tumors acquire alterations in oncogenes and tumor suppressor genes in an adaptive walk through the fitness landscape of tumorigenesis. However, the features of this landscape remain poorly understood and cannot be revealed by human cancer genotyping alone. Here, we use a multiplexed, autochthonous mouse platform to model and quantify the initiation and growth of more than one hundred genotypes of lung tumors across four oncogenic contexts: KRAS G12D, KRAS G12C, BRAF V600E, and EGFR L858R. The resulting fitness landscape is rugged (the effect of tumor suppressor inactivation often switches between beneficial and deleterious depending on the oncogenic context), shows no evidence of diminishing-returns epistasis within variants of the same oncogene, and is inconsistent with expectations of a simple linear signaling relationship among these three oncogenes. Our findings suggest that tumor suppressor effects are strongly context-specific, which limits the set of evolutionary paths that can be taken through the fitness landscape.

cancer biology↗

bioRxiv2022

A multiplexed in vivo approach to identify driver genes in small cell lung cancer

Small cell lung cancer (SCLC) is a highly lethal form of lung cancer. The high mutation burden in SCLC cells makes it challenging to predict key drivers of SCLC from genome sequencing data, thereby hindering the identification of possible therapeutic targets. Here we develop a quantitative multiplexed approach based on lentiviral barcoding with somatic CRISPR/Cas9-mediated genome editing to functionally investigate candidate regulators of tumor initiation and growth in genetically engineered mouse models of SCLC. Lentiviral vector-mediated SCLC initiation was greatly enhanced by naphthalene pre-treatment, enabling high multiplicity of tumor clones for analysis through high-throughput sequencing methods. Based on a meta-analysis across multiple human SCLC genomic datasets, we quantified the impact of inactivating 39 genes across many candidate pathways and captured both positive and detrimental effects on SCLC initiation and progression upon gene inactivation. This analysis and subsequent validation in human SCLC cells identified TSC1 in the PI3K-AKT-mTOR pathway as a robust tumor suppressor in SCLC. This new approach should illuminate novel drivers of SCLC, facilitate the development of precision therapies for defined SCLC genotypes, and identify new therapeutic targets.

cancer biology↗

bioRxiv2021

Combinatorial tumor suppressor inactivation efficiently initiates lung adenocarcinoma with therapeutic vulnerabilities

Lung cancer is the leading cause of cancer death worldwide, with lung adenocarcinoma being the most common subtype. Many oncogenes and tumor suppressor genes are altered in this cancer type and the discovery of oncogene mutations has led to the development of targeted therapies that have improved clinical outcomes. However, a large fraction of lung adenocarcinomas lacks mutations in known oncogenes, and the genesis and treatment of these oncogene-negative tumors remain enigmatic. Here, we perform iterative in vivo functional screens using quantitative autochthonous mouse model systems to uncover the genetic and biochemical changes that enable efficient lung tumor initiation in the absence of oncogene alterations. Through the generation of hundreds of diverse combinations of tumor suppressor alterations, we demonstrate that the inactivation of suppressors of the RAS and PI3K pathways drive the development of oncogene-negative lung adenocarcinoma. Human genomic data and histology identified RAS/MAPK and PI3K pathway activation as a common event in oncogene- negative human lung adenocarcinomas. We demonstrate that these Onc-negativeRAS/PI3K tumors and related cell lines are vulnerable to pharmacological inhibition of these signaling axes. These results transform our understanding of this prevalent yet understudied subtype of lung adenocarcinoma.

cancer biology↗

bioRxiv2021

Neuronal mimicry generates an ecosystem critical for brain metastatic growth of SCLC

Brain metastasis is a major cause of morbidity and mortality in cancer patients. Here we investigated mechanisms allowing small-cell lung cancer (SCLC) cells to grow in the brain. We show that SCLC cells undergo a cell state transition towards neuronal differentiation during tumor progression and metastasis, and that this neuronal mimicry is critical for SCLC growth in the brain. Mechanistically, SCLC cells re-activate astrocytes, which in turn promote SCLC growth by secreting neuronal pro-survival factors such as SERPINE1. We further identify Reelin, a molecule important in brain development, as a factor secreted by SCLC cells to recruit astrocytes to brain metastases in mice. This recruitment of astrocytes by SCLC was recapitulated in assembloids between SCLC aggregates and human cortical spheroids. Thus, SCLC brain metastases grow by co-opting mechanisms involved in reciprocal neuron-astrocyte interactions during development. Targeting such developmental programs activated in this cancer ecosystem may help treat brain metastases.

cancer biology↗

bioRxiv2021

Multiplexed identification of RAS paralog imbalance as a driver of lung cancer growth

Oncogenic KRAS mutations occur in approximately 30% of lung adenocarcinoma. Despite several decades of effort, oncogenic KRAS-driven lung cancer remains difficult to treat, and our understanding of the positive and negative regulators of RAS signaling is incomplete. To uncover the functional impact of diverse KRAS-interacting proteins on lung cancer growth in vivo, we used multiplexed somatic CRISPR/Cas9-based genome editing in genetically engineered mouse models with tumor barcoding and high-throughput barcode sequencing. Through a series of CRISPR/Cas9 screens in autochthonous lung tumors, we identified HRAS and NRAS as key suppressors of KRASG12D-driven tumor growth in vivo and confirmed these effects in oncogenic KRAS-driven human lung cancer cell lines. Mechanistically, RAS paralogs interact with oncogenic KRAS, suppress KRAS-KRAS interactions, and reduce downstream ERK signaling. HRAS mutations identified in KRAS-driven human tumors partially abolished this effect. Comparison of the tumor-suppressive effects of HRAS and NRAS in KRAS- and BRAF-driven lung cancer models confirmed that RAS paralogs are specific suppressors of oncogenic KRAS-driven lung cancer in vivo. Our study outlines a technological avenue to uncover positive and negative regulators of oncogenic KRAS-driven cancer in a multiplexed manner in vivo and highlights the role of RAS paralog imbalance in oncogenic KRAS-driven lung cancer.

cancer biology↗