Biology subjects

Mills, G. B.

Publications and source records attributed to Mills, G. B..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Longitudinal and multimodal auditing of tumor adaptation to CDK4/6 inhibitors in HR+ metastatic breast cancers

CDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To improve understanding of how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets suggests a diverse set of tumor adaptations to CDK4/6i therapy. Malignant cells may adapt to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression during therapy. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to better understand HR+ breast cancer tumor therapeutic adaptations to CDK4/6i therapy.

cancer biology↗

bioRxiv2023

Systematic Pan-cancer Functional Inference and Validation of Hyper, Hypo and Neomorphic Mutations

While the functional effects of many recurrent cancer mutations have been characterized, the TCGA repository comprises more than 10M non-recurrent events, whose function is unknown. We propose that the context specific activity of transcription factor (TF) proteins--as measured by expression of their transcriptional targets--provides a sensitive and accurate reporter assay to assess the functional role of oncoprotein mutations. Analysis of differentially active TFs in samples harboring mutations of unknown significance--compared to established gain (GOF/hypermorph) or loss (LOF/hypomorph) of function--helped functionally characterize 577,866 individual mutational events across TCGA cohorts, including identification of mutations that are either neomorphic (gain of novel function) or phenocopy other mutations (mutational mimicry). Validation using mutation knock-in assays confirmed 15 out of 15 predicted gain and loss of function mutations and 15 of 20 predicted neomorphic mutations. This could help determine targeted therapy in patients with mutations of unknown significance in established oncoproteins.

systems biology↗

bioRxiv2023

Supervised learning of high-confidence phenotypic subpopulations from single-cell data

Accurately identifying phenotype-relevant cell subsets from heterogeneous cell populations is crucial for delineating the underlying mechanisms driving biological or clinical phenotypes. Here, by deploying a learning with rejection strategy, we developed a novel supervised learning framework called PENCIL to identify subpopulations associated with categorical or continuous phenotypes from single-cell data. By embedding a feature selection function into this flexible framework, for the first time, we were able to select informative features and identify cell subpopulations simultaneously, which enables the accurate identification of phenotypic subpopulations otherwise missed by methods incapable of concurrent gene selection. Furthermore, the regression mode of PENCIL presents a novel ability for supervised phenotypic trajectory learning of subpopulations from single-cell data. We conducted comprehensive simulations to evaluate PENCILs versatility in simultaneous gene selection, subpopulation identification and phenotypic trajectory prediction. PENCIL is fast and scalable to analyze 1 million cells within 1 hour. Using the classification mode, PENCIL detected T-cell subpopulations associated with melanoma immunotherapy outcomes. Moreover, when applied to scRNA-seq of a mantle cell lymphoma patient with drug treatment across multiple time points, the regression mode of PENCIL revealed a transcriptional treatment response trajectory. Collectively, our work introduces a scalable and flexible infrastructure to accurately identify phenotype-associated subpopulations from single-cell data.

bioinformatics↗

bioRxiv2022

A Novel Mouse Model that Recapitulates the Heterogeneity of Human Triple Negative Breast Cancer

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new targeted therapies, but few TNBC mouse models exist. Here, we developed a novel TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl murine model develops TN mammary tumors that display histological and molecular features commonly found in human TNBC. We performed deep omic analyses on Myc;Ptenfl tumors including machine learning for morphologic features, bulk and single-cell RNA-sequencing, multiplex immunohistochemistry and single-cell phenotyping. Through comparison with human TNBC, we demonstrated that this new genetic mouse model develops mammary tumors with differential survival that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC; providing a unique pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response. Statement of significanceThe development of cancer models that mimic triple-negative breast cancer (TNBC) microenvironment complexities is critical to develop effective drugs and enhance disease understanding. This study addresses a critical need in the field by identifying a murine model that faithfully mimics human TNBC heterogeneity and establishing a foundation for translating preclinical findings into effective human clinical trials.

cancer biology↗

bioRxiv2022

Beyond BRCA: Discovery of novel causes and consequences of homologous recombination deficiencies

Since the discovery of BRCA1 and BRCA2 mutations as cancer risk factors, we have gained substantial insight into their role in maintaining genomic stability through homologous recombination (HR) DNA repair. However, upon pan-cancer analysis of tumors from The Cancer Genome Atlas (TCGA), we found that mutations in BRCA1/2 and other classical HR genes only identified 10-20% of tumors that display genomic evidence of HR deficiency (HRD), suggesting that the cause of the vast majority of HR defects in tumors is unknown. As HRD both predisposes individuals to cancer development and leads to therapeutic vulnerabilities, it is critical to define the spectrum of genetic events that drive HRD. Here, we employed a network-based approach leveraging the abundance of molecular characterization data from TCGA to identify novel drivers of HRD. We discovered that over half of putative genes driving HRD originated outside of canonical DNA damage response genes, with a particular enrichment for RNA binding protein (RBP)-encoding genes. These novel drivers of HRD were cross-validated using an independent ICGC cohort, and were enriched in GWAS loci associated with cancer risk. Experimental approaches validated over 90% of our predictions in a panel of 50 genes tested by siRNA and 31 additional engineered mutations identified from TCGA patient tumors. Moreover, genetic suppression of identified RBPs or pharmacological inhibition of RBPs induced PARP inhibition. Further mechanistic studies indicate that some RBPs are recruited to sites of DNA damage to facilitate repair, whereas others control the expression of canonical HR genes. Overall, this study greatly expands the repertoire of known drivers of HRD and their contributions to DNA damage repair, which has implications for not only future mechanistic studies, but also for genetic screening and therapy stratification. HIGHLIGHTSO_LIThe majority of HR deficiencies detected cannot be directly attributed to aberrations in canonical HR genes. C_LIO_LIIntegrated network analysis identifies RNA binding proteins (RBPs) as a novel driver of HR deficiency in patient tumors. C_LIO_LIRBP dysfunction can produce HR deficiencies through both dysregulation of canonical HR genes and action at sites of DNA damage. C_LI

systems biology↗

bioRxiv2022

Ongoing Replication Stress Response and New Clonal T Cell Development Discriminate Between Liver and Lung Recurrence Sites and Patient Outcomes in Pancreatic Ductal Adenocarcinoma

Background and AimsMetastatic pancreatic adenocarcinoma (mPDAC) is lethal, yet a subset of patients who have metastatic disease that spreads only to the lung have better outcomes. We identified unique transcriptomic and immune features that distinguish patients who develop metastases in the liver (liver cohort) versus those with lung-avid but liver-averse mPDAC (lung cohort). MethodsWe used clinical data from the Oregon Pancreas Tissue Registry to identify PDAC patients with liver and/or lung metastases. Gene expression and genomic alteration data from 290 PDAC tumors were used to identify features unique to patients from the liver and lung cohorts. In parallel, T cell receptor sequencing data from 289 patients were used to identify immune features unique to patients in the lung cohort. ResultsLung cohort patients had better survival outcomes than liver cohort patients. Primary tumors from patients in the liver cohort expressed a novel gene signature associated with ongoing replication stress (RS) response predictive of poor patient outcome independent from known subtypes. In contrast, patients with tumors lacking the RS response signature survived longer, especially if their tumors had alterations in DNA damage repair genes. A subset of patients in the lung cohort demonstrated new T cell clonal development in their primary and metastatic tumors leading to diverse peripheral blood TCR repertoires. ConclusionLiver-avid metastatic PDAC is associated with an ongoing RS response, whereas tumors lacking the RS response with ongoing T cell clonal responses may have unique vulnerabilities allowing long-term survival in patients with lung-avid, liver-averse metastatic PDAC.

cancer biology↗

bioRxiv2021

Multiplex spatial systems analysis of local nanodose drug responses predicts effective treatment combinations of immunotherapies and targeted agents in mammary carcinoma

Better methods are needed to identify effective combinations of immunotherapies with chemotherapies and targeted anti-cancer agents. Here we present a Multiplex Implantable Microdevice Assay (MIMA) system for rapid in vivo assessment of the effects of multiple, spatially separate anticancer drugs directly in the complex tumor microenvironment. In prototypic experiments, olaparib, lenvatinib, palbociclib, venetoclax, panobinostat, doxorubicin, and paclitaxel and combinations thereof were administered simultaneously to murine mammary tumor models. Quantitative multiplex immunohistochemistry and spatial systems analyses of each local drug response defined cellular relations of fibroblasts, endothelial cells, immune lineages, immunogenic cell death, tumor proliferation and/or cancer stem cells that were used to predict effective drug combinations. A predicted combination of panobinostat, venetoclax and anti-CD40 showed long-term anti-tumor efficacy in multiple mouse models with no observable toxicity when administered systemically. Future MIMA use promises to design effective drug combinations for tumor cell control and immune activation on a personalized basis.

cancer biology↗

bioRxiv2021

A LINCS microenvironment perturbation resource for integrative assessment of ligand-mediated molecular and phenotypic responses

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes.

systems biology↗

bioRxiv2021

Mechanical stress in pancreatic cancer: Signaling pathway adaptation activates cytoskeletal remodeling and enhances cell migration

New treatments for patients with advanced or metastatic pancreatic cancers are urgently needed due to their resistance to all current therapies. Current studies focus on alternative treatment approaches that target or normalize the abnormal microenvironment of pancreatic tumors, which among others, is responsible for elevated mechanical stress in the tumor interior. Nevertheless, the underlying mechanisms by which mechanical stress regulates pancreatic cancer metastatic potential remain elusive. Herein, we used a large-scale proteomic assay to profile mechanical stress-induced signaling cascades that drive the motility of pancreatic cancer cells. Proteomic analysis, together with selective protein inhibition and siRNA treatments, revealed that mechanical stress enhances cell migration through activation of the p38 MAPK/HSP27 and JNK/c-Jun signaling axes, and activation of the actin cytoskeleton remodelers: Rac1, cdc42, and Myosin II. Our results highlight targeting aberrant signaling in cancer cells that are adapted to the mechanical tumor microenvironment as a novel approach to effectively limit pancreatic cancer cell migration.

cancer biology↗

bioRxiv2021

ME-VAE: Multi-Encoder Variational AutoEncoder for Controlling Multiple Transformational Features in Single Cell Image Analysis

Image-based cell phenotyping relies on quantitative measurements as encoded representations of cells; however, defining suitable representations that capture complex imaging features is challenged by the lack of robust methods to segment cells, identify subcellular compartments, and extract relevant features. Variational autoencoder (VAE) approaches produce encouraging results by mapping an image to a representative descriptor, and outperform classical hand-crafted features for morphology, intensity, and texture at differentiating data. Although VAEs show promising results for capturing morphological and organizational features in tissue, single cell image analyses based on VAEs often fail to identify biologically informative features due to uninformative technical variation. Herein, we propose a multi-encoder VAE (ME-VAE) in single cell image analysis using transformed images as a self-supervised signal to extract transform-invariant biologically meaningful features, including emergent features not obvious from prior knowledge. We show that the proposed architecture improves analysis by making distinct cell populations more separable compared to traditional VAEs and intensity measurements by enhancing phenotypic differences between cells and by improving correlations to other analytic modalities.

bioinformatics↗

bioRxiv2021

Targeting Adaptation to Cancer Treatment by Drug Combinations

Adaptation of tumors to therapeutic interventions contributes to dismal long-term patient outcomes. Adaptation to therapy involves co-action of functionally related proteins that together activate cell survival programs and compensate for the therapeutic impact. Oncogenic dependencies to such adaptive events, however, can generate new therapeutic vulnerabilities that can be targeted with drug combinations. The precision medicine approaches in which targeted drugs are matched to pre-existing genomic aberrations fail to address the adaptive responses and resulting vulnerabilities. Here, we provide the mathematical formulation, implementation and validation of the TargetScore method. The TargetScore identifies collective adaptive responses to targeted interventions as concurrent changes of phospho-proteins that are connected within a signaling network. Based on the adaptive responses, the method predicts drug-induced vulnerabilities. Using TargetScore, we inferred the adaptive responses with short-term (i.e., days) stress and long-term (i.e., months) acquired resistance to inhibitors of anti-apoptotic mediators, MCL1 and BCL2. With experiments guided by the predictions, we identified synergistic interactions between inhibitors of PARP, SHP2, and MCL1 in breast cancer cells. TargetScore is readily applicable to existing precision oncology efforts by matching targeted drug combinations to emerging molecular signatures under therapeutic stress.

systems biology↗

bioRxiv2021

Selective abrogation of S6K2 maps lipid homeostasis as a survival vulnerability in MAPKi-resistant NRASmut melanoma

Although oncogenic NRAS activates MAPK signaling, inhibition of the MAPK pathway is not therapeutically efficacious in NRAS-mutant tumors. Here we report that silencing the ribosomal protein S6 kinase 2 (S6K2), while preserving the activity of S6K1, perturbs lipid metabolism, enhances fatty acid unsaturation, and triggers lethal lipid peroxidation selectively in NRAS-mutant melanoma cells that are resistant to MAPK inhibition. S6K2 depletion induces ER stress, and PPAR activation, triggering cell death selectively in MAPKi-resistant melanoma. We show that combining PPAR agonists and polyunsaturated fatty acids phenocopies the effects of S6K2 abrogation, blocking tumor growth in PDX and immunocompetent mouse pre-clinical models. Collectively, our study establishes S6K2 and its effector subnetwork as promising targets for NRAS-mutant melanoma that are resistant to global MAPK pathway inhibitors. One Sentence SummaryS6K2 is a vulnerability in MAPK inhibitor-resistant NRAS-mutant melanoma

cancer biology↗

bioRxiv2021

BCL-XL blockage in TNBC models confers vulnerability to inhibition of specific cell cycle regulators

Cell cycle regulators are frequently altered in Triple-Negative Breast Cancer (TNBC). Emerging agents targeting these signals offer the possibility to design new combinatorial therapies. However, preclinical models that recapitulate TNBC primary resistance and heterogeneity are essential to evaluate the potency of these combined treatments. MethodsBioinformatic processing of human breast cancer datasets was used to analyse correlations between expression levels of cell cycle regulators and patient survival outcome. The MMTV-R26Met mouse model of TNBC resistance and heterogeneity was employed to analyse expression and targeting vulnerability of cell cycle regulators in the presence of BCL-XL blockage. Robustness of outcomes and selectivity was further explored using a panel of human breast cancer cells. Alterations of protein expression, phosphorylation, and/or cellular localisation were analysed by western blots, reverse phase protein array, and immunocytochemistry. Bioinformatics was performed to highlight drugs mechanisms of action. ResultsWe report that high expression levels of BCL-XL and specific cell cycle regulators correlate with poor survival outcomes of TNBC patients. Blockage of BCL-XL confers vulnerability to drugs targeting CDK1/2/4, but not FOXM1, CDK4/6, Aurora A and Aurora B, to all MMTV-R26Met and human TNBC cell lines tested. Mechanistically, we show that, co-targeting of BCL-XL and CDK1/2/4 synergistically inhibited cell growth by combinatorial depletion of survival and RTK/AKT signals, and concomitantly restoring FOXO3a tumour suppression actions. This was accompanied by an accumulation of DNA damage and consequently apoptosis. ConclusionsOur studies illustrate the possibility to exploit the vulnerability of TNBC cells to CDK1/2/4 inhibition by targeting BCL-XL. Moreover, they underline that specificity matters in targeting cell cycle regulators for combinatorial anticancer therapies.

cancer biology↗

bioRxiv2021

Relevance of Circulating Hybrid Cells as a Non-Invasive Biomarker for Myriad Solid Tumors

AbstractMetastatic progression defines the final stages of tumor evolution and underlies the majority of cancer-related deaths. The heterogeneity in disseminated tumor cell populations capable of seeding and growing in distant organ sites contributes to the development of treatment resistant disease. We recently reported the identification of a novel tumor-derived cell population, circulating hybrid cells (CHCs), harboring attributes from both macrophages and neoplastic cells, including functional characteristics important to metastatic spread. These disseminated hybrids outnumber conventionally defined circulating tumor cells (CTCs) in cancer patients. It is unknown if CHCs represent a generalized cancer mechanism for cell dissemination, or if this population is relevant to the metastatic cascade. Herein, we detect CHCs in the peripheral blood of patients with cancer in myriad disease sites encompassing epithelial and non-epithelial malignancies. Further, we demonstrate that in vivo-derived hybrid cells harbor tumor-initiating capacity in murine cancer models and that CHCs from human breast cancer patients express stem cell antigens, features consistent with the ability to seed and grow at metastatic sites. Finally, we reveal heterogeneity of CHC phenotypes reflect key tumor features, including oncogenic mutations and functional protein expression. Importantly, this novel population of disseminated neoplastic cells opens a new area in cancer biology and renewed opportunity for battling metastatic disease. Simple SummaryThere is an incomplete understanding of circulating neoplastic cell populations and the fundamental mechanisms that drive dissemination, immune evasion, and growth --all critical information to more effectively prevent and treat cancer progression. A novel disseminated tumor cell population, circulating hybrid cells, are detected across many cancer types and carry functional tumor-initiating properties. Additionally, circulating hybrid cells are found at significantly higher levels than conventionally defined circulating tumor cells. Our study demonstrates that neoplastic hybrid cells harbor phenotypic and genetic characteristics of tumor and immune cells, display stem features, and are a generalizable phenomenon in solid tumors. Circulating hybrid cells therefore have relevance as a novel biomarker and open a new field of study in malignancy.

cancer biology↗

bioRxiv2020

An Integrated Clinical, Omic, and Image Atlas of an Evolving Metastatic Breast Cancer

Mechanisms of therapeutic resistance manifest in metastatic cancers as tumor cell intrinsic alterations and extrinsic microenvironmental influences that can change during treatment. To support the development of methods for the identification of these mechanisms in individual patients, we present here an Omic and Multidimensional Spatial (OMS) Atlas generated from four serial biopsies of a metastatic breast cancer patient during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata including treatment times and doses, anatomic imaging, and blood-based response measurements to exploratory analytics including comprehensive DNA, RNA, and protein profiles, images of multiplexed immunostaining, and 2- and 3-dimensional scanning electron micrographs. These data reveal aspects of therapy-associated heterogeneity and evolution of the cancers genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples showing how integrative analyses of these data provide insights into potential mechanisms of response and resistance, and suggest novel therapeutic vulnerabilities.

cancer biology↗

bioRxiv2020

Targeting uncoupling of copy number and gene expression in cancers

The high degree of aneuploidy in cancer is likely tolerated via extensive uncoupling of copy number (CN) and mRNA expression (UCNE) of deleterious genes located in copy number aberrations (CNAs). To test the extent and role of UCNE in cancer, we performed integrative analysis of multiomics data across The Cancer Genome Atlas (TCGA), encompassing [~] 5000 individual tumors. We found many genes having UCNE, the degree of which are associated with increased oncogenic signaling, proliferation and immune-suppression. The occurrence of UCNE appears to be orchestrated by complex epigenetic and regulatory changes, with transcription factors (TFs) playing a prominent role. To further dissect the regulatory mechanisms, we developed a systems-biological approach to identify candidate TFs, which upon perturbation can offset UCNE and reduce tumor fitness. Applying our approach on TCGA data, we identified 20 putative targets, 45% of which were validated by independent sources. Among them are IRF1, which plays a prominent role in anti-tumor immunity and response to immune checkpoint therapy, ETS1, TRIM21 and GATA3, which are associated with anti-tumor immunity, tumor proliferation and metastasis. Together, our study indicates that UCNE is likely an important mechanism in cancer development that can be exploited therapeutically.

cancer biology↗

bioRxiv2020

Modeling heterogeneity of Triple-Negative Breast Cancer highlights potency of WEE1 and BCL-XL targeting

Triple-negative breast cancer (TNBC) is a highly aggressive breast cancer subtype characterized by a remarkable molecular heterogeneity. Currently, there are no effective druggable targets and advanced preclinical models of the human disease. Here, we generated a unique mouse model (MMTV-R26Met mice) of mammary tumors driven by a subtle increase in the expression of the wild-type MET receptor. MMTV-R26Met mice develop spontaneous, exclusive TNBC tumors, recapitulating primary resistance to treatment of patients. Proteomic profiling of MMTV-R26Met tumors and machine learning approach showed that the model faithfully recapitulates inter-tumoral heterogeneity of human TNBC. Further signaling network analysis highlighted potential druggable targets, of which co-targeting of WEE1 and BCL-XL synergistically killed TNBC cells and efficiently induced tumor regression. Mechanistically, BCL-XL inhibition exacerbates the dependency of TNBC cells on WEE1 function, leading to Histone H3 and phosphoS33RPA32 upregulation, RRM2 downregulation, cell cycle perturbation, mitotic catastrophe and apoptosis. Our study introduces a unique, powerful mouse model for studying TNBC formation and evolution, its heterogeneity, and for identifying efficient therapeutic targets.

cancer biology↗

bioRxiv2020

Transient Commensal Clonal Interactions Can Drive Tumor Metastasis

To interrogate functional heterogeneity and crosstalk between tumor cells, we generated clonal populations from a patient-derived ovarian clear cell carcinoma model which forms malignant ascites and solid peritoneal tumors upon intraperitoneal transplantation in mice. The clonal populations were engineered with secreted Gaussia luciferase to monitor tumor growth dynamics and tagged with a unique DNA barcode to track their fate in multiclonal mixtures during tumor progression. Only one clone, CL31, grew robustly, generating exclusively malignant ascites. However, multiclonal mixtures formed large solid peritoneal metastases, populated almost entirely by CL31, suggesting that transient cooperative interclonal interactions were sufficient to promote metastasis of CL31. CL31 uniquely harbored ERBB2 amplification, and its acquired metastatic trait was dependent on transient exposure to amphiregulin, which was exclusively secreted by non-tumorigenic clones. Amphiregulin enhanced CL31 mesothelial clearance, a prerequisite for metastasis. These findings demonstrate that transient, ostensibly innocuous tumor subpopulations can promote metastases via "hit- and-run" commensal interactions.

cancer biology↗