Fusion oncoproteins (FOs) arise from chromosomal translocations in ~17% of cancers and are often oncogenic drivers. Although some FOs can promote oncogenesis by undergoing liquid-liquid phase separation (LLPS) to form aberrant biomolecular condensates, the generality of this phenomenon is unknown. We explored this question by testing 166 FOs in HeLa cells and found that 58% formed condensates. The condensate-forming FOs displayed physicochemical features distinct from those of condensate-negative FOs and segregated into distinct feature-based groups that aligned with their sub-cellular localization and biological function. Using Machine Learning, we developed a predictor of FO condensation behavior, and discovered that 67% of ~3000 additional FOs likely form condensates, with 35% of those predicted to function by altering gene expression. 47% of the predicted condensate-negative FOs were associated with cell signaling functions, suggesting a functional dichotomy between condensate-positive and -negative FOs. Our Datasets and reagents are rich resources to interrogate FO condensation in the future.

A defective homologous recombination (HR) repair program increases tumor incidence as well as providing a survival advantage in patients with breast and ovarian cancers. Here we hypothesize that the tumor-promoting side of genome maintenance programs may be contributed by a self-renewal protein, nucleostemin (NS). To address this issue, we established its functional importance in mammary tumor progression in mice and showed that mammary tumor cells become highly susceptible to replicative DNA damage following NS depletion and are protected from hydroxyurea-induced damage by NS overexpression. Breast cancer cells with basal-like characters display more reliance on NS for genome maintenance than those with luminal characters. Mechanistically, NS-deficient cells demonstrate a significantly reduced HR repair activity. TCGA analyses of human breast cancers revealed that NS is co-enriched positively with HR repair proteins and that high NS expression correlates with low HR defects and predicts poor progression-free survival and resistance to knockdown of cell-cycle checkpoint genes in triple-negative/basal-like breast cancers. This work indicates that NS constitutes a tumor-promoting genome maintenance program required for mammary tumor progression.

We demonstrate that concurrent administration of poly(ADP-ribose) polymerase (PARP) and WEE1 inhibitors is effective in inhibiting tumor growth but poorly tolerated. Concurrent treatment with PARP and WEE1 inhibitors induces replication stress, DNA damage, and abrogates the G2 DNA damage checkpoint in both normal and malignant cells. Following cessation of monotherapy with PARP or WEE1 inhibitors, effects of these inhibitors persist suggesting that sequential administration of PARP and WEE1 inhibitors could maintain efficacy while ameliorating toxicity. Strikingly, while sequential administration mirrored concurrent therapy in cancer cells that have high basal replication stress, low basal replication stress in normal cells protected them from DNA damage and toxicity, thus improving tolerability while preserving efficacy in ovarian cancer xenograft and patient-derived xenograft models.

Despite rapid advancement in generation of large-scale microarray gene expression datasets, robust multigene expression signatures that are capable of guiding the use of specific therapies have not been routinely implemented into clinical care. We have developed an iterative resampling analysis to predict sensitivity algorithm to generate gene expression sensitivity profiles that predict patient responses to specific therapies. The resultant signatures have a robust capacity to accurately predict drug sensitivity as well as the identification of synergistic combinations. Here, we apply this approach to predict response to PARP inhibitors, and show it can greatly outperforms current clinical biomarkers, including BRCA1/2 mutation status, accurately identifying PARP inhibitor-sensitive cancer cell lines, primary patient-derived tumor cells, and patient-derived xenografts. These signatures were also capable of predicting patient response, as shown by applying a cisplatin sensitivity signature to ovarian cancer patients. We additionally demonstrate how these drug-sensitivity signatures can be applied to identify novel synergizing agents to improve drug efficacy. Tailoring therapeutic interventions to improve patient prognosis is of utmost importance, and our drug sensitivity prediction signatures may prove highly beneficial for patient management.

A non-immunogenic tumor microenvironment (TME) is a significant barrier to immune checkpoint blockade (ICB) response. The impact of Polybromo-1 (PBRM1) on TME and response to ICB in renal cell carcinoma (RCC) remains to be resolved. Here we show that PBRM1/Pbrm1 deficiency reduces the binding of brahma-related gene 1 (BRG1) to the IFNγ receptor 2 (Ifngr2) promoter, decreasing STAT1 phosphorylation and the subsequent expression of IFNγ target genes. An analysis of 3 independent patient cohorts and of murine pre-clinical models reveals that PBRM1 loss is associated with a less immunogenic TME and upregulated angiogenesis. Pbrm1 deficient Renca subcutaneous tumors in mice are more resistance to ICB, and a retrospective analysis of the IMmotion150 RCC study also suggests that PBRM1 mutation reduces benefit from ICB. Our study sheds light on the influence of PBRM1 mutations on IFNγ-STAT1 signaling and TME, and can inform additional preclinical and clinical studies in RCC.

Adoptive cell transfer (ACT) of tumor-infiltrating lymphocytes (TIL) yielded clinical benefit in patients with checkpoint blockade immunotherapy-refractory non-small cell lung cancer (NSCLC) prompting a renewed interest in TIL-ACT. This preclinical study explores the feasibility of producing a NSCLC TIL product with sufficient numbers and enhanced attributes using an improved culture method.

Adenoid cystic carcinoma (ACC) is a heterogeneous malignancy, and no effective systemic therapy exists for metastatic disease. We previously described two prognostic ACC molecular subtypes with distinct therapeutic vulnerabilities, ACC-I and ACC-II. In this study, we explored the ACC tumor microenvironment (TME) using RNA-sequencing and spatial biology to identify potential therapeutic targets.

Defects in homologous recombination DNA repair (HRD) both predispose to cancer development and produce therapeutic vulnerabilities, making it critical to define the spectrum of genetic events that cause HRD. However, we found that mutations in BRCA1/2 and other canonical HR genes only identified 10%-20% of tumors that display genomic evidence of HRD. Using a networks-based approach, we discovered that over half of putative genes causing HRD originated outside of canonical DNA damage response genes, with a particular enrichment for RNA-binding protein (RBP)-encoding genes. These putative drivers of HRD were experimentally validated, cross-validated in an independent cohort, and enriched in cancer-associated genome-wide association study loci. 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, with implications for basic biology, genetic screening, and therapy stratification.

Multipotent human mesenchymal stem cells (hMSCs) are uniquely suited for the growing field of regenerative medicine due to their ease of isolation, expansion, and transplantation. However, during ex vivo expansion necessary to obtain clinically relevant cell quantities, hMSCs undergo fundamental changes culminating in cellular senescence. The molecular changes as hMSCs transition into senescence have been well characterized, but few studies have focused on the mechanical properties that govern many processes necessary for therapeutic efficacy. We show that before detectable differences in classical senescence markers emerge, single-cell mechanical and cytoskeletal properties reveal a subpopulation of 'non-functioning' hMSCs that appears after even limited expansion. This subpopulation, characterized by a loss of dynamic cytoskeletal stiffening and morphological flexibility in response to chemotactic signals grows with extended culture resulting in overall decreased hMSC motility and ability to contract collagen gels. These changes were mitigated with cytoskeletal inhibition. Finally, a xenographic wound healing model was used to demonstrate that these in vitro differences correlate with decreased ability of hMSCs to aid in wound closure in vivo. These data illustrate the importance of analyzing not only the molecular markers, but also mechanical markers of hMSCs as they are investigated for potential therapeutics.

The outbreak the SARS-CoV-2 (CoV-2) virus has resulted in over 6.5 million cases of COVID19, greatly stressing global healthcare infrastructure. Lacking medical prophylactic measures to combat disease spread, many nations have adopted social distancing policies in order to mitigate transmission of CoV-2. While mathematical models have suggested the efficacy of social distancing to curb the spread of CoV-2, there is a lack of systematic studies to quantify the real-world efficacy of these approaches. Here, we first demonstrate that implementation of social distancing policies in US states corresponded with a reduction in COVID19 spread rates, and that the reduction in spread rate is proportional to the average change in mobility. We validate this observation on a worldwide scale by analyzing COVID19 spread rate in 134 nations with varying social distancing policies. Globally, we find that social distancing policies significantly reduced the COVID19 spread rate, with resulting in an estimated 65% reduction (95% CI = 39-80%) in new COVID19 cases over a two week time period. These data suggest that social distancing policies may be a powerful tool to prevent spread of COVID19 in real-world scenarios.

Somatic mutations are a major source of cancer development, and many driver mutations have been identified in protein coding regions. However, the function of mutations located in miRNA and their target binding sites throughout the human genome remains largely unknown. Here, we built detailed cancer-specific miRNA regulatory networks across 30 cancer types to systematically analyze the effect of mutations in miRNAs and their target sites in 3' untranslated region (3' UTR), coding sequence (CDS), and 5' UTR regions. A total of 3,518,261 mutations from 9,819 samples were mapped to miRNA-gene interactions (mGI). Mutations in miRNAs showed a mutually exclusive pattern with mutations in their target genes in almost all cancer types. A linear regression method identified 148 candidate driver mutations that can significantly perturb miRNA regulatory networks. Driver mutations in 3'UTRs played their roles by altering RNA binding energy and the expression of target genes. Finally, mutated driver gene targets in 3' UTRs were significantly downregulated in cancer and functioned as tumor suppressors during cancer progression, suggesting potential miRNA candidates with significant clinical implications. A user-friendly, open-access web portal (mGI-map) was developed to facilitate further use of this data resource. Together, these results will facilitate novel noncoding biomarker identification and therapeutic drug design targeting the miRNA regulatory networks.

Understanding the functional impact of cancer somatic mutations represents a critical knowledge gap for implementing precision oncology. It has been increasingly appreciated that the interaction profile mediated by a genomic mutation provides a fundamental link between genotype and phenotype. However, specific effects on biological signaling networks for the majority of mutations are largely unknown by experimental approaches. To resolve this challenge, we developed e-MutPath (edgetic Mutation-mediated Pathway perturbations), a network-based computational method to identify candidate 'edgetic' mutations that perturb functional pathways. e-MutPath identifies informative paths that could be used to distinguish disease risk factors from neutral elements and to stratify disease subtypes with clinical relevance. The predicted targets are enriched in cancer vulnerability genes, known drug targets but depleted for proteins associated with side effects, demonstrating the power of network-based strategies to investigate the functional impact and perturbation profiles of genomic mutations. Together, e-MutPath represents a robust computational tool to systematically assign functions to genetic mutations, especially in the context of their specific pathway perturbation effect.

Nucleotide excision repair (NER) resolves DNA adducts, such as those caused by ultraviolet light. Deficient NER (dNER) results in a higher mutation rate that can predispose to cancer development and premature ageing phenotypes. Here, we used isogenic dNER model cell lines to establish a gene expression signature that can accurately predict functional NER capacity in both cell lines and patient samples. Critically, none of the identified NER deficient cell lines harbored mutations in any NER genes, suggesting that the prevalence of NER defects may currently be underestimated. Identification of compounds that induce the dNER gene expression signature led to the discovery that NER can be functionally impaired by GSK3 inhibition, leading to synergy when combined with cisplatin treatment. Furthermore, we predicted and validated multiple novel drugs that are synthetically lethal with NER defects using the dNER gene signature as a drug discovery platform. Taken together, our work provides a dynamic predictor of NER function that may be applied for therapeutic stratification as well as development of novel biological insights in human tumors.

Immune checkpoint blockade (ICB) has revolutionized cancer treatment. However, ICB alone has demonstrated only benefit in a small subset of patients with breast cancer. Recent studies have shown that agents targeting DNA damage response improve the efficacy of ICB and promote cytosolic DNA accumulation. However, recent clinical trials have shown that these agents are associated with hematological toxicities. More effective therapeutic strategies are urgently needed.

Multiple cancers exhibit aberrant protein arginine methylation by both type I arginine methyltransferases, predominately protein arginine methyltransferase 1 (PRMT1) and to a lesser extent PRMT4, and by type II PRMTs, predominately PRMT5. Here, we perform targeted proteomics following inhibition of PRMT1, PRMT4, and PRMT5 across 12 cancer cell lines. We find that inhibition of type I and II PRMTs suppresses phosphorylated and total ATR in cancer cells. Loss of ATR from PRMT inhibition results in defective DNA replication stress response activation, including from PARP inhibitors. Inhibition of type I and II PRMTs is synergistic with PARP inhibition regardless of homologous recombination function, but type I PRMT inhibition is more toxic to non-malignant cells. Finally, we demonstrate that the combination of PARP and PRMT5 inhibition improves survival in both BRCA-mutant and wild-type patient-derived xenografts without toxicity. Taken together, these results demonstrate that PRMT5 inhibition may be a well-tolerated approach to sensitize tumors to PARP inhibition.

Mesenchymal stem cells (MSCs) are recruited to the tumor microenvironment and influence tumor progression; however, how MSCs induce the invasion of cancer cells is not completely understood. Here, we used a 3D coculture model to determine how MSCs affect the migration of invasive breast cancer cells. Coculture with MSCs increases the elongation, directional migration, and traction generation of breast cancer cells. MSC-induced directional migration directly correlates with traction generation and is mediated by transforming growth factor β (TGF-β) and the migratory proteins rho-associated kinase, focal adhesion kinase, and matrix metalloproteinases. Treatment with MSC conditioned media or recombinant TGF-β1 elicits a similar migration response to coculture. Taken together, this work suggests TGF-β is secreted by MSCs, leading to force-dependent directional migration of invasive breast cancer cells. These pathways may be potential targets for blocking cancer cell invasion and subsequent metastasis.

Chemorefractory ovarian cancer patients show extremely poor prognosis. Microtubule-stabilizing Taxol (paclitaxel) is a first-line treatment against ovarian cancer. Despite the close interplay between microtubules and cell adhesion, it remains unknown if chemoresistance alters the way cells adhere to their extracellular environment, a process critical for cancer metastasis. To investigate this, we isolated Taxol-resistant populations of OVCAR3 and SKOV3 ovarian cancer cell lines. Though Taxol-resistant cells neither effluxed more drug nor gained resistance to other chemotherapeutics, they did display increased microtubule dynamics. These changes in microtubule dynamics coincided with faster attachment rates and decreased adhesion strength, which correlated with increased surface β1-integrin expression and decreased focal adhesion formation, respectively. Adhesion strength correlated best with Taxol-sensitivity, and was found to be independent of microtubule polymerization but dependent on focal adhesion kinase (FAK), which was up-regulated in Taxol-resistant cells. FAK inhibition also decreased microtubule dynamics to equal levels in both populations, indicating alterations in adhesive signaling are up-stream of microtubule dynamics. Taken together, this work demonstrates that Taxol-resistance dramatically alters how ovarian cancer cells adhere to their extracellular environment causing down-stream increases in microtubule dynamics, providing a therapeutic target that may improve prognosis by not only recovering drug sensitivity, but also decreasing metastasis.

To realize the full potential of immunotherapy, it is critical to understand the drivers of tumor infiltration by immune cells. Previous studies have linked immune infiltration with tumor neoantigen levels, but the broad applicability of this concept remains unknown. Here, we find that while this observation is true across cancers characterized by recurrent mutations, it does not hold for cancers driven by recurrent copy number alterations, such as breast and pancreatic tumors. To understand immune invasion in these cancers, we developed an integrative multi-omics framework, identifying the DNA damage response protein ATM as a driver of cytokine production leading to increased immune infiltration. This prediction was validated in numerous orthogonal datasets, as well as experimentally in vitro and in vivo by cytokine release and immune cell migration. These findings demonstrate diverse drivers of immune cell infiltration across cancer lineages and may facilitate the clinical adaption of immunotherapies across diverse malignancies.

The wound healing process initiates after injury to a tissue and involves a series of orchestrated events to minimize the invasion of foreign matters such as bacteria and efficiently regenerate the damaged tissue. A variety of cells must be recruited to the tissue during wound healing. However, this process is severely disrupted in patients suffering from chronic illness, including diabetes, leading to impaired healing or non-healing wounds. Current avenues of treatment include negative-pressure therapy, wound debridement, growth factor replacement, and cell-based therapies. Among these therapies, mesenchymal stem cells (MSCs) delivery to the wound holds a very high promise due to the innate abilities of MSCs that include immunogenicity, plasticity, and self-renewal. Bone marrow derived MSCs have been shown to promote more rapid wound healing by increased cytokine production in diabetic mice. However, the lack of understanding of the mechanical and chemical interaction of the transplanted MSCs with the factors present in the regenerative niches limits their efficacy in the wound bed. In this study, we sought to understand how the changes in MSC biochemical and biophysical properties can affect their function in vitro and in vivo. We demonstrate that pretreatment of MSCs with the mechano-stimulatory soluble factor transforming growth factor (TGF-β1), which is highly expressed in injury sites, improves wound closure in a syngeneic murine wound model. This improved wound closure correlated with increased invasion into the wound bed. In vitro studies demonstrated that TGF-β1 pretreatment expedited wound closure by increasing adhesion, traction force, and migration even after removal of the stimulus. Furthermore, this response was mediated by the cytoskeletal protein focal adhesion kinase. Taken together, this study suggests that defined chemical stimuli can benefit site specific adaptability of MSCs to improve their function and therapeutic usefulness.

We previously demonstrated that altered activity of lysophosphatidic acid in murine mammary glands promotes tumorigenesis. We have now established and characterized a heterogeneous collection of mouse-derived syngeneic transplants (MDSTs) as preclinical platforms for the assessment of personalized pharmacological therapies. Detailed molecular and phenotypic analyses revealed that MDSTs are the most heterogeneous group of genetically engineered mouse models (GEMMs) of breast cancer yet observed. Response of MDSTs to trametinib, a mitogen-activated protein kinase (MAPK) kinase inhibitor, correlated with RAS/MAPK signaling activity, as expected from studies in xenografts and clinical trials providing validation of the utility of the model. Sensitivity of MDSTs to talazoparib, a poly(adenosine 5'-diphosphate-ribose) polymerase (PARP) inhibitor, was predicted by PARP1 protein levels and by a new PARP sensitivity predictor (PSP) score developed from integrated analysis of drug sensitivity data of human cell lines. PSP score-based classification of The Cancer Genome Atlas breast cancer suggested that a subset of patients with limited therapeutic options would be expected to benefit from PARP-targeted drugs. These results indicate that MDSTs are useful models for studies of targeted therapies, and propose novel potential biomarkers for identification of breast cancer patients likely to benefit from personalized pharmacological treatments.