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Although Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) have been approved in multiple diseases, including BRCA1/2 mutant breast cancer, responses are usually transient requiring the deployment of combination therapies for optimal efficacy. Here we thus explore mechanisms underlying sensitivity and resistance to PARPi using two intrinsically PARPi sensitive (T22) and resistant (T127) syngeneic murine breast cancer models in female mice. We demonstrate that tumor associated macrophages (TAM) potentially contribute to the differential sensitivity to PARPi. By single-cell RNA-sequencing, we identify a TAM_C3 cluster, expressing genes implicated in antiinflammatory activity, that is enriched in PARPi resistant T127 tumors and markedly decreased by PARPi in T22 tumors. Rps19/C5aR1 signaling is selectively elevated in TAM_C3. C5aR1 inhibition or transferring C5aR1hi cells increases and decreases PARPi sensitivity, respectively. High C5aR1 levels in human breast cancers are associated with poor responses to immune checkpoint blockade. Thus, targeting C5aR1 may selectively deplete pro-tumoral macrophages and engender sensitivity to PARPi and potentially other therapies. [ABSTRACT FROM AUTHOR]

Cyclic Immunofluorescence (CyCIF) can quantify multiple biomarkers, but panel capacity is limited by technical challenges. We propose a computational panel reduction approach that can impute the information content from 25 markers using only 9 markers, learning co-expression and morphological patterns while concurrently increasing speed and panel content and decreasing cost. We demonstrate strong correlations in predictions and generalizability across breast and colorectal cancer, illustrating applicability of our approach to diverse tissue types. This study proposes a computational panel reduction method for CyCIF, leveraging 9 markers to impute information from 25, enhancing speed, content, and reducing costs. [ABSTRACT FROM AUTHOR]

Several alterations in fibroblast growth factor receptor (FGFR) genes have been found in breast cancer; however, they have not been well characterized as therapeutic targets. Futibatinib (TAS-120; Taiho) is a novel, selective, pan-FGFR inhibitor that inhibits FGFR1-4 at nanomolar concentrations. We sought to determine futibatinib's efficacy in breast cancer models. Nine breast cancer patient–derived xenografts (PDXs) with various FGFR1-4 alterations and expression levels were treated with futibatinib. Antitumor efficacy was evaluated by change in tumor volume and time to tumor doubling. Alterations indicating sensitization to futibatinib in vivo were further characterized in vitro. FGFR gene expression between patient tumors and matching PDXs was significantly correlated; however, overall PDXs had higher FGFR3-4 expression. Futibatinib inhibited tumor growth in 3 of 9 PDXs, with tumor stabilization in an FGFR2-amplified model and prolonged regression (> 110 days) in an FGFR2 Y375C mutant/amplified model. FGFR2 overexpression and, to a greater extent, FGFR2 Y375C expression in MCF10A cells enhanced cell growth and sensitivity to futibatinib. Per institutional and public databases, FGFR2 mutations and amplifications had a population frequency of 1.1%–2.6% and 1.5%–2.5%, respectively, in breast cancer patients. FGFR2 alterations in breast cancer may represent infrequent but highly promising targets for futibatinib. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) have been shown as key mediators of extracellular small RNA transport. However, carriers of cell-free messenger RNA (cf-mRNA) in human biofluids and their association with cancer remain poorly understood. Here, we performed a transcriptomic analysis of size-fractionated plasma from lung cancer, liver cancer, multiple myeloma, and healthy donors. Morphology and size distribution analysis showed the successful separation of large and medium particles from other soluble plasma protein fractions. We developed a strategy to purify and sequence ultra-low amounts of cf-mRNA from particle and protein enriched subpopulations with the implementation of RNA spike-ins to control for technical variability and to normalize for intrinsic drastic differences in cf-mRNA amount carried in each plasma fraction. We found that the majority of cf-mRNA was enriched and protected in EVs with remarkable stability in RNase-rich environments. We observed specific enrichment patterns of cancer-associated cf-mRNA in each particle and protein enriched subpopulation. The EV-enriched differentiating genes were associated with specific biological pathways, such as immune systems, liver function, and toxic substance regulation in lung cancer, liver cancer, and multiple myeloma, respectively. Our results suggest that dissecting the complexity of EV subpopulations illuminates their biological significance and offers a promising liquid biopsy approach. Fractionation and characterization of cell-free mRNA carriers - mostly EVs - from various human plasma samples leads to identification of cancer-specific EV enrichment patterns [ABSTRACT FROM AUTHOR]

Genomically-informed therapy requires consideration of the functional impact of genomic alterations on protein expression and/or function. However, a substantial number of variants are of unknown significance (VUS). The MD Anderson Precision Oncology Decision Support (PODS) team developed an actionability classification scheme that categorizes VUS as either "Unknown" or "Potentially" actionable based on their location within functional domains and/or proximity to known oncogenic variants. We then compared PODS VUS actionability classification with results from a functional genomics platform consisting of mutant generation and cell viability assays. 106 (24%) of 438 VUS in 20 actionable genes were classified as oncogenic in functional assays. Variants categorized by PODS as Potentially actionable (N = 204) were more likely to be oncogenic than those categorized as Unknown (N = 230) (37% vs 13%, p = 4.08e-09). Our results demonstrate that rule-based actionability classification of VUS can identify patients more likely to have actionable variants for consideration with genomically-matched therapy. [ABSTRACT FROM AUTHOR]

Most ovarian high-grade serous carcinomas (HGSC) arise from Serous Tubal Intraepithelial Carcinoma (STIC) lesions in the distal end of the fallopian tube (FT). Formation of STIC lesions from FT secretory cells leads to seeding of the ovarian surface, with rapid tumor dissemination to other abdominal structures thereafter. It remains unclear how nascent malignant cells leave the FT to colonize the ovary. This report provides evidence that the L1 cell adhesion molecule (L1CAM) contributes to the ability of transformed FT secretory cells (FTSEC) to detach from the tube, survive under anchorage-independent conditions, and seed the ovarian surface. L1CAM was highly expressed on the apical cells of STIC lesions and contributed to ovarian colonization by upregulating integrins and fibronectin in malignant cells and activating the AKT and ERK pathways. These changes increased cell survival under ultra-low attachment conditions that mimic transit from the FT to the ovary. To study dissemination to the ovary, we developed a tumor-ovary co-culture model. We showed that L1CAM expression was important for FT cells to invade the ovary as a cohesive group. Our results indicate that in the early stages of HGSC development, transformed FTSECs disseminate from the FT to the ovary in a L1CAM-dependent manner. L1CAM is implicated as an important factor that enables early fallopian tube cancer precursors to seed the ovary by promoting cell survival through extracellular matrix signaling, thereby facilitating ovarian cancer growth. [ABSTRACT FROM AUTHOR]

Systematically identifying synergistic combinations of targeted agents and immunotherapies for cancer treatments remains difficult. In this study, we integrated high-throughput and high-content techniques—an implantable microdevice to administer multiple drugs into different sites in tumors at nanodoses and multiplexed imaging of tumor microenvironmental states—to investigate the tumor cell and immunological response signatures to different treatment regimens. Using a mouse model of breast cancer, we identified effective combinations from among numerous agents within days. In vivo studies in three immunocompetent mammary carcinoma models demonstrated that the predicted combinations synergistically increased therapeutic efficacy. We identified at least five promising treatment strategies, of which the panobinostat, venetoclax and anti-CD40 triple therapy was the most effective in inducing complete tumor remission across models. Successful drug combinations increased spatial association of cancer stem cells with dendritic cells during immunogenic cell death, suggesting this as an important mechanism of action in long-term breast cancer control. Testing of combinations of cancer immunotherapies and conventional drugs yields promising leads. [ABSTRACT FROM AUTHOR]

Primary liver cancer is a heterogeneous disease in terms of its etiology, histology, and therapeutic response. Concurrent proteomic and genomic characterization of a large set of clinical liver cancer samples can help elucidate the molecular basis of heterogeneity and thus serve as a valuable resource for personalized liver cancer treatment. In this study, we perform proteomic profiling of ~300 proteins on 259 primary liver cancer tissues with reverse-phase protein arrays, mutational analysis using whole genome sequencing and transcriptional analysis with RNA-Seq. Patients are of Japanese ethnic background and mainly HBV or HCV positive, providing insight into this important liver cancer subtype. Unsupervised classification of tumors based on protein expression profiles reveal three proteomic subclasses R1, R2, and R3. The R1 subclass is immunologically hot and demonstrated a good prognosis. R2 contains advanced proliferative tumor with TP53 mutations, high expression of VEGF receptor 2 and the worst prognosis. R3 is enriched with CTNNB1 mutations and elevated mTOR signaling pathway activity. Twenty-two proteins, including CDK1 and CDKN2A, are identified as potential prognostic markers. The proteomic classification presented in this study can help guide therapeutic decision making for liver cancer treatment. The molecular heterogeneity of primary liver cancer remains to be characterised. Here, the authors perform multi-omics analysis of 259 primary liver cancer tissues and identify three distinct molecular subtypes. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) targeting PD-L1 and PD-1 have improved survival in a subset of patients with advanced non-small cell lung cancer (NSCLC). However, only a minority of NSCLC patients respond to ICIs, highlighting the need for superior immunotherapy. Herein, we report on a nanoparticle-based immunotherapy termed ARAC (Antigen Release Agent and Checkpoint Inhibitor) designed to enhance the efficacy of PD-L1 inhibitor. ARAC is a nanoparticle co-delivering PLK1 inhibitor (volasertib) and PD-L1 antibody. PLK1 is a key mitotic kinase that is overexpressed in various cancers including NSCLC and drives cancer growth. Inhibition of PLK1 selectively kills cancer cells and upregulates PD-L1 expression in surviving cancer cells thereby providing opportunity for ARAC targeted delivery in a feedforward manner. ARAC reduces effective doses of volasertib and PD-L1 antibody by 5-fold in a metastatic lung tumor model (LLC-JSP) and the effect is mainly mediated by CD8+ T cells. ARAC also shows efficacy in another lung tumor model (KLN-205), which does not respond to CTLA-4 and PD-1 inhibitor combination. This study highlights a rational combination strategy to augment existing therapies by utilizing our nanoparticle platform that can load multiple cargo types at once. Only a minority of patients with non-small cell lung cancer (NSCLC) respond to immune checkpoint inhibitors. Here the authors design a nanosystem for the co-delivery of a PLK1 inhibitor and PD-L1 antibody, showing anti-tumor immune responses in preclinical lung cancer models. [ABSTRACT FROM AUTHOR]

The lack of tumor infiltration by CD8+ T cells is associated with poor patient response to anti-PD-1 therapy. Understanding how tumor infiltration is regulated is key to improving treatment efficacy. Here, we report that phosphorylation of HRS, a pivotal component of the ESCRT complex involved in exosome biogenesis, restricts tumor infiltration of cytolytic CD8+ T cells. Following ERK-mediated phosphorylation, HRS interacts with and mediates the selective loading of PD-L1 to exosomes, which inhibits the migration of CD8+ T cells into tumors. In tissue samples from patients with melanoma, CD8+ T cells are excluded from the regions where tumor cells contain high levels of phosphorylated HRS. In murine tumor models, overexpression of phosphorylated HRS increases resistance to anti-PD-1 treatment, whereas inhibition of HRS phosphorylation enhances treatment efficacy. Our study reveals a mechanism by which phosphorylation of HRS in tumor cells regulates anti-tumor immunity by inducing PD-L1+ immunosuppressive exosomes, and suggests HRS phosphorylation blockade as a potential strategy to improve the efficacy of cancer immunotherapy. Lack of CD8+ T-cell infiltration into solid tumors is associated with poor responsiveness to immune checkpoint therapy (ICT). Here, the authors show that blocking the phosphorylation of HRS to reduce the induction of immunosuppressive exosomes promotes CD8+ T-cell infiltration into tumors and enhances the efficacy of ICT in mouse melanoma models. [ABSTRACT FROM AUTHOR]

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. Here 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 and recent extensions of VAE architectures and intensity measurements by enhancing phenotypic differences between cells and by improving correlations to other analytic modalities. Better feature extraction and image analysis methods enabled by the ME-VAE will advance our understanding of complex cell biology and enable discoveries previously hidden behind image complexity ultimately improving medical outcomes and drug discovery. The Multi-Encoder Variational AutoEncoder (ME-VAE) is a computational model that can control for multiple transformational features in single-cell imaging data, enabling researchers to extract meaningful single-cell information and better separate heterogeneous cell types. [ABSTRACT FROM AUTHOR]

Precision treatment for breast cancers has made several notable advances in recent decades, but challenges of tumor heterogeneity, drug resistance, and aggressive recurrence and metastases remain. To meet and overcome these challenges, we must refine our understanding of breast subtypes and treatment biomarkers according to the knowledge afforded across the spectrum of 'omics assays. A critical aspect of harnessing this knowledge into actionable biomarkers for treatment decision relies on our ability to integrate knowledge across data types and leverage our insight in evidence-based clinical trials. We review recent advances in cutting-edge clinical trials for precision treatment of breast cancer, including chemotherapies, targeted therapies, immunotherapies, and combination therapies. We comment on promising future areas of development for this exciting point in precision breast cancer research. [ABSTRACT FROM AUTHOR]

Background: Circulating tumour DNA (ctDNA) is known as a tumour-specific personalised biomarker, but the mutation-selection criteria from heterogeneous tumours remain a challenge.Methods: We conducted multiregional sequencing of 42 specimens from 14 colorectal tumours of 12 patients, including two double-cancer cases, to identify mutational heterogeneity to develop personalised ctDNA assays using 175 plasma samples.Results: "Founder" mutations, defined as a mutation that is present in all regions of the tumour in a binary manner (i.e., present or absent), were identified in 12/14 tumours. In contrast, "truncal" mutations, which are the first mutation that occurs prior to the divergence of branches in the phylogenetic tree using variant allele frequency (VAF) as continuous variables, were identified in 12/14 tumours. Two tumours without founder and truncal mutations were hypermutators. Most founder and truncal mutations exhibited higher VAFs than "non-founder" and "branch" mutations, resulting in a high chance to be detected in ctDNA. In post-operative long-term observation for 10/12 patients, early relapse prediction, treatment efficacy and non-relapse corroboration were achievable from frequent ctDNA monitoring.Conclusions: A single biopsy is sufficient to develop custom dPCR probes for monitoring tumour burden in most CRC patients. However, it may not be effective for those with hypermutated tumours. [ABSTRACT FROM AUTHOR]

Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance. Dysregulated phosphorylation is well-known in cancers, but it has largely been studied in isolation from mutations. Here the authors introduce HotPho, a tool that can discover spatial interactions between phosphosites and mutations, which are associated with activating mutation and genetic dependencies in cancer. [ABSTRACT FROM AUTHOR]

Molecular heterogeneity in metastatic breast cancer presents multiple clinical challenges in accurately characterizing and treating the disease. Current diagnostic approaches offer limited ability to assess heterogeneity that exists among multiple metastatic lesions throughout the treatment course. We developed a precision oncology platform that combines serial biopsies, multi-omic analysis, longitudinal patient monitoring, and molecular tumor boards, with the goal of improving cancer management through enhanced understanding of the entire cancer ecosystem within each patient. We describe this integrative approach using comprehensive analytics generated from serial-biopsied lesions in a metastatic breast cancer patient. The serial biopsies identified remarkable heterogeneity among metastatic lesions that presented clinically as discordance in receptor status and genomic alterations with mixed treatment response. Based on our study, we highlight clinical scenarios, such as rapid progression or mixed response, that indicate consideration for repeat biopsies to evaluate intermetastatic heterogeneity (IMH), with the objective of refining targeted therapy. We present a framework for understanding the clinical significance of heterogeneity in breast cancer between metastatic lesions utilizing multi-omic analyses of serial biopsies and its implication for effective personalized treatment. [ABSTRACT FROM AUTHOR]

Ovarian cancer (OVCA) inevitably acquires resistance to platinum chemotherapy and PARP inhibitors (PARPi). We show that acquisition of PARPi-resistance is accompanied by increased ATR-CHK1 activity and sensitivity to ATR inhibition (ATRi). However, PARPi-resistant cells are remarkably more sensitive to ATRi when combined with PARPi (PARPi-ATRi). Sensitivity to PARPi-ATRi in diverse PARPi and platinum-resistant models, including BRCA1/2 reversion and CCNE1-amplified models, correlate with synergistic increases in replication fork stalling, double-strand breaks, and apoptosis. Surprisingly, BRCA reversion mutations and an ability to form RAD51 foci are frequently not observed in models of acquired PARPi-resistance, suggesting the existence of alternative resistance mechanisms. However, regardless of the mechanisms of resistance, complete and durable therapeutic responses to PARPi-ATRi that significantly increase survival are observed in clinically relevant platinum and acquired PARPi-resistant patient-derived xenografts (PDXs) models. These findings indicate that PARPi-ATRi is a highly promising strategy for OVCAs that acquire resistance to PARPi and platinum. Patients with ovarium cancer frequently develop resistance to platinum chemotherapy and PARP inhibitors (PARPi). Here, the authors show that the combination of PARP and ATR inhibitors increases the therapeutic response in PARPi and platinum resistant ovarium cancer PDX models. [ABSTRACT FROM AUTHOR]

PIK3R2 encodes the p85β regulatory subunit of phosphatidylinositol 3-kinase and is frequently amplified in cancers. The signaling mechanism and therapeutic implication of p85β are poorly understood. Here we report that p85β upregulates the protein level of the receptor tyrosine kinase AXL to induce oncogenic signaling in ovarian cancer. p85β activates p110 activity and AKT-independent PDK1/SGK3 signaling to promote tumorigenic phenotypes, which are all abolished upon inhibition of AXL. At the molecular level, p85β alters the phosphorylation of TRIM2 (an E3 ligase) and optineurin (an autophagy receptor), which mediate the selective regulation of AXL by p85β, thereby disrupting the autophagic degradation of the AXL protein. Therapeutically, p85β expression renders ovarian cancer cells vulnerable to inhibitors of AXL, p110, or PDK1. Conversely, p85β-depleted cells are less sensitive to these inhibitors. Together, our findings provide a rationale for pharmacological blockade of the AXL signaling axis in PIK3R2-amplified ovarian cancer. p85β (PIK3R2), a regulatory subunit of PI3K, has oncogenic properties. Here the authors show that p85β promotes AXL protein stability, which in turn activates p110 to induce PDK1/SGK3 signaling, and therapeutically, p85β-expressing ovarian cancer cells are sensitive to AXL inhibition. [ABSTRACT FROM AUTHOR]

Immune checkpoint blockade therapies have extended patient survival across multiple cancer lineages, but there is a heated debate on whether cancer immunotherapy efficacy is different between male and female patients. We summarize the existing meta-analysis to show inconsistent conclusions for whether gender is associated with the immunotherapy response. We analyze molecular profiling from ICB-treated patients to identify molecular differences for immunotherapy responsiveness. We perform comprehensive analyses for patients from The Cancer Genome Atlas (TCGA) and reveal divergent patterns for sex bias in immune features across multiple cancer types. We further validate our observations in multiple independent data sets. Considering that the majority of clinical trials are in melanoma and lung cancer, meta-analyses that pool multiple cancer types have limitations to discern whether cancer immunotherapy efficacy is different between male and female patients. Future studies should include omics profiling to investigate sex-associated molecular differences in immunotherapy. Immunotherapy has tremendous potential to treat many patients with cancer. In this study, the authors investigate the impact of gender on the response to therapy, highlighting the importance to include omics profiling in clinical studies. [ABSTRACT FROM AUTHOR]

Background: In endometrioid endometrial cancer (EEC), current clinical algorithms do not accurately predict patients with lymph node metastasis (LNM), leading to both under- and over-treatment. We aimed to develop models that integrate protein data with clinical information to identify patients requiring more aggressive surgery, including lymphadenectomy.Methods: Protein expression profiles were generated for 399 patients using reverse-phase protein array. Three generalised linear models were built on proteins and clinical information (model 1), also with magnetic resonance imaging included (model 2), and on proteins only (model 3), using a training set, and tested in independent sets. Gene expression data from the tumours were used for confirmatory testing.Results: LNM was predicted with area under the curve 0.72-0.89 and cyclin D1; fibronectin and grade were identified as important markers. High levels of fibronectin and cyclin D1 were associated with poor survival (p = 0.018), and with markers of tumour aggressiveness. Upregulation of both FN1 and CCND1 messenger RNA was related to cancer invasion and mesenchymal phenotype.Conclusions: We demonstrate that data-driven prediction models, adding protein markers to clinical information, have potential to significantly improve preoperative identification of patients with LNM in EEC. [ABSTRACT FROM AUTHOR]

Limited clinical activity has been seen in osteosarcoma (OS) patients treated with immune checkpoint inhibitors (ICI). To gain insights into the immunogenic potential of these tumors, we conducted whole genome, RNA, and T-cell receptor sequencing, immunohistochemistry and reverse phase protein array profiling (RPPA) on OS specimens from 48 pediatric and adult patients with primary, relapsed, and metastatic OS. Median immune infiltrate level was lower than in other tumor types where ICI are effective, with concomitant low T-cell receptor clonalities. Neoantigen expression in OS was lacking and significantly associated with high levels of nonsense-mediated decay (NMD). Samples with low immune infiltrate had higher number of deleted genes while those with high immune infiltrate expressed higher levels of adaptive resistance pathways. PARP2 expression levels were significantly negatively associated with the immune infiltrate. Together, these data reveal multiple immunosuppressive features of OS and suggest immunotherapeutic opportunities in OS patients. The efficacy of immune checkpoint inhibitors (ICI) in osteosarcoma has been limited. Here, the authors investigate the immunogenomic landscape of osteosarcoma, and integrated analyses highlight features related to a suppressed immune microenvironment. [ABSTRACT FROM AUTHOR]

Glioblastoma is a universally lethal form of brain cancer that exhibits an array of pathophysiological phenotypes, many of which are mediated by interactions with the neuronal microenvironment1,2. Recent studies have shown that increases in neuronal activity have an important role in the proliferation and progression of glioblastoma3,4. Whether there is reciprocal crosstalk between glioblastoma and neurons remains poorly defined, as the mechanisms that underlie how these tumours remodel the neuronal milieu towards increased activity are unknown. Here, using a native mouse model of glioblastoma, we develop a high-throughput in vivo screening platform and discover several driver variants of PIK3CA. We show that tumours driven by these variants have divergent molecular properties that manifest in selective initiation of brain hyperexcitability and remodelling of the synaptic constituency. Furthermore, secreted members of the glypican (GPC) family are selectively expressed in these tumours, and GPC3 drives gliomagenesis and hyperexcitability. Together, our studies illustrate the importance of functionally interrogating diverse tumour phenotypes driven by individual, yet related, variants and reveal how glioblastoma alters the neuronal microenvironment. Glioblastoma tumours expressing oncogenic PIK3CA variants secrete the glycan GPC3, which promotes the formation of neural synapses, brain synaptic hyperexcitability and gliomagenesis. [ABSTRACT FROM AUTHOR]

Background: Mutation of TP53 is the most frequent genetic alteration in high-grade serous ovarian cancer (HGSOC). The impact of hotspot mutations of TP53 and protein levels on patient outcomes in HGSOC has not been fully elucidated.Methods: The study population (n = 791) comprised of HGSOC samples with TP53 mutation from TCGA and other publicly available data. Univariate and multivariate cox proportional hazards regression analyses were used to select variables that were correlated with patient survival.Results: We assessed the effects of TP53 mutations based on type and individual hotspot mutations on patient outcomes in HGSOC. Only hotspot mutations were associated with outcomes. Three hotspot mutations: G266, Y163C, and R282, in aggregate were associated with a worsened overall and recurrence-free survival compared with other hotspot mutations (p < 0.0001 and p = 0.001), other non-hotspot missense mutations (p < 0.0001 and p = 0.008), truncated mutations (p < 0.0001 and p = 0.001), and all other mutations (p < 0.0001 and p = 0.001). Specific hotspot mutations were associated with different protein expression patterns consistent with different functions.Conclusions: This study provides evidence that individual TP53 hotspot mutations have different impact on HGSOC patient outcomes and potentially TP53 function. Thus the status of particular TP53 aberrations could influence response to therapy and selection of therapeutic agents. [ABSTRACT FROM AUTHOR]

Purpose: Limited knowledge exists on the detection of breast cancer stem cell (BCSC)-related mutations in circulating free DNA (cfDNA) from patients with advanced cancers. Identification of new cancer biomarkers may allow for earlier detection of disease progression and treatment strategy modifications. Methods: We conducted a prospective study to determine the feasibility and prognostic utility of droplet digital polymerase chain reaction (ddPCR)-based BCSC gene mutation analysis of cfDNA in patients with breast cancer. Results: Detection of quantitative BCSC gene mutation in cfDNA by ddPCR mirrors disease progression and thus may represent a valuable and cost-effective measure of tumor burden. We have previously shown that hematological and neurological expressed 1-like (HN1L), ribosomal protein L39 (RPL39), and myeloid leukemia factor 2 (MLF2) are novel targets for BCSC self-renewal, and targeting these genetic alterations could be useful for personalized genomic-based therapy. Conclusion: BCSC mutation detection in cfDNA may have important implications for diagnosis, prognosis, and serial monitoring. [ABSTRACT FROM AUTHOR]

Genetic aberrations driving pro-oncogenic and pro-metastatic activity remain an elusive target in the quest of precision oncology. To identify such drivers, we use an animal model of KRAS-mutant lung adenocarcinoma to perform an in vivo functional screen of 217 genetic aberrations selected from lung cancer genomics datasets. We identify 28 genes whose expression promoted tumor metastasis to the lung in mice. We employ two tools for examining the KRAS-dependence of genes identified from our screen: 1) a human lung cell model containing a regulatable mutant KRAS allele and 2) a lentiviral system permitting co-expression of DNA-barcoded cDNAs with Cre recombinase to activate a mutant KRAS allele in the lungs of mice. Mechanistic evaluation of one gene, GATAD2B, illuminates its role as a dual activity gene, promoting both pro-tumorigenic and pro-metastatic activities in KRAS-mutant lung cancer through interaction with c-MYC and hyperactivation of the c-MYC pathway. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: The directed study of the functional proteome in colorectal cancer (CRC) has identified critical protein markers and signaling pathways; however, the prognostic relevance of many of these proteins remains unclear. Methods: We determined the prognostic implications of the functional proteome in 263 CRC tumor samples from patients treated at MD Anderson Cancer Center (MDACC) and 462 patients from The Cancer Genome Atlas (TCGA) to identify patterns of protein expression that drive tumorigenesis. A total of 163 validated proteins were analyzed by reverse phase protein array (RPPA). Unsupervised hierarchical clustering of the tumor proteins from the MDACC cohort was performed, and clustering was validated using RPPA data from TCGA CRC. Cox regression was used to identify predictors of tumor recurrence. Results: Clustering revealed dichotomization, with subtype A notable for a high epithelial-mesenchymal transition (EMT) protein signature, while subtype B was notable for high Akt/TSC/mTOR pathway components. Survival data were only available for the MDACC cohort and were used to evaluate prognostic relevance of these protein signatures. Group B demonstrated worse relapse-free survival (hazard ratio 2.11, 95% confidence interval 1.04-4.27, p = 0.039), although there was no difference in known genomic drivers between the two proteomic groups. Proteomic grouping and stage were significant predictors of recurrence on multivariate analysis. Eight proteins were found to be significant predictors of tumor recurrence on multivariate analysis: Collagen VI, FOXO3a, INPP4B, LcK, phospho-PEA15, phospho-PRAS40, Rad51, phospho-S6. Conclusion: CRC can be classified into distinct subtypes by proteomic features independent of common oncogenic driver mutations. Proteomic analysis has identified key biomarkers with prognostic importance, however these findings require further validation in an independent cohort. [ABSTRACT FROM AUTHOR]

Recent evidence has established a role for the small GTPase RAB25, as well as related effector proteins, in enacting both pro-oncogenic and anti-oncogenic phenotypes in specific cellular contexts. Here we report the development of all-hydrocarbon stabilized peptides derived from the RAB-binding FIP-family of proteins to target RAB25. Relative to unmodified peptides, optimized stapled peptides exhibit increased structural stability, binding affinity, cell permeability, and inhibition of RAB25:FIP complex formation. Treatment of cancer cell lines in which RAB25 is pro-oncogenic with an optimized stapled peptide, RFP14, inhibits migration, and proliferation in a RAB25-dependent manner. In contrast, RFP14 treatment augments these phenotypes in breast cancer cells in which RAB25 is tumor suppressive. Transcriptional profiling identified significantly altered transcripts in response to RAB25 expression, and treatment with RFP14 opposes this expression profile. These data validate the first cell-active chemical probes targeting RAB-family proteins and support the role of RAB25 in regulating context-specific oncogenic phenotypes. [ABSTRACT FROM AUTHOR]

The lack of effective chemotherapies for high-grade serous ovarian cancers (HGS-OvCa) has motivated a search for alternative treatment strategies. Here, we present an unbiased systems-approach to interrogate a panel of 14 well-annotated HGS-OvCa patient-derived xenografts for sensitivity to PI3K and PI3K/mTOR inhibitors and uncover cell death vulnerabilities. Proteomic analysis reveals that PI3K/mTOR inhibition in HGS-OvCa patient-derived xenografts induces both pro-apoptotic and anti-apoptotic signaling responses that limit cell killing, but also primes cells for inhibitors of anti-apoptotic proteins. In-depth quantitative analysis of BCL-2 family proteins and other apoptotic regulators, together with computational modeling and selective anti-apoptotic protein inhibitors, uncovers new mechanistic details about apoptotic regulators that are predictive of drug sensitivity (BIM, caspase-3, BCL-XL) and resistance (MCL-1, XIAP). Our systems-approach presents a strategy for systematic analysis of the mechanisms that limit effective tumor cell killing and the identification of apoptotic vulnerabilities to overcome drug resistance in ovarian and other cancers. [ABSTRACT FROM AUTHOR]

Estrogen receptor (ER)-negative cancers have a poor prognosis, and few targeted therapies are available for their treatment. Our previous analyses have identified potential kinase targets critical for the growth of ER-negative, progesterone receptor (PR)-negative and HER2-negative, or 'triple-negative' breast cancer (TNBC). Because phosphatases regulate the function of kinase signaling pathways, in this study, we investigated whether phosphatases are also differentially expressed in ER-negative compared to those in ER-positive breast cancers. We compared RNA expression in 98 human breast cancers (56 ER-positive and 42 ER-negative) to identify phosphatases differentially expressed in ER-negative compared to those in ER-positive breast cancers. We then examined the effects of one selected phosphatase, dual specificity phosphatase 4 (DUSP4), on proliferation, cell growth, migration and invasion, and on signaling pathways using protein microarray analyses of 172 proteins, including phosphoproteins. We identified 48 phosphatase genes are significantly differentially expressed in ER-negative compared to those in ER-positive breast tumors. We discovered that 31 phosphatases were more highly expressed, while 11 were underexpressed specifically in ER-negative breast cancers. The DUSP4 gene is underexpressed in ER-negative breast cancer and is deleted in approximately 50 % of breast cancers. Induced DUSP4 expression suppresses both in vitro and in vivo growths of breast cancer cells. Our studies show that induced DUSP4 expression blocks the cell cycle at the G1/S checkpoint; inhibits ERK1/2, p38, JNK1, RB, and NFkB p65 phosphorylation; and inhibits invasiveness of TNBC cells. These results suggest that that DUSP4 is a critical regulator of the growth and invasion of triple-negative breast cancer cells. [ABSTRACT FROM AUTHOR]

Protein-protein interactions (PPIs) are useful for understanding signaling cascades, predicting protein function, associating proteins with disease and fathoming drug mechanism of action. Currently, only ∼10% of human PPIs may be known, and about one-third of human proteins have no known interactions. We introduce FpClass, a data mining-based method for proteome-wide PPI prediction. At an estimated false discovery rate of 60%, we predicted 250,498 PPIs among 10,531 human proteins; 10,647 PPIs involved 1,089 proteins without known interactions. We experimentally tested 233 high- and medium-confidence predictions and validated 137 interactions, including seven novel putative interactors of the tumor suppressor p53. Compared to previous PPI prediction methods, FpClass achieved better agreement with experimentally detected PPIs. We provide an online database of annotated PPI predictions (http://ophid.utoronto.ca/fpclass/) and the prediction software (http://www.cs.utoronto.ca/~juris/data/fpclass/). [ABSTRACT FROM AUTHOR]

Obesity-related hormones and cytokines alter PI3 K-AKT-mTOR pathway activation in breast tumors contributing to poorer disease-free survival (DFS) and decreased responsiveness to tamoxifen and trastuzumab. We hypothesized that single nucleotide polymorphisms (SNPs) in candidate genes in the PI3 K-AKT-mTOR signaling pathway may act as genetic modifiers of breast cancer DFS. We analyzed the association of 106 tagging SNPs in 13 genes ( ADIPOQ, IGF1, INS, IRS1, LEP, LEPR, LEPROT, PIK3CA, PIK3R5, PTEN, TSC1, TSC2, and AKT1) in the P13K-AKT-mTOR pathway with DFS in a sample of 1,019 women with stage I-II breast cancer. SNPs significantly associated with DFS in any genetic model (additive, dominant, or recessive) after correcting for false discovery rate (FDR = 0.10) were included in Cox proportional hazards multivariable analyses. After adjusting for race/ethnicity, age at diagnosis, tumor stage, and treatment, rs1063539 in ADIPOQ, rs11585329 in LEPR, and rs2519757 in TSC1 were associated with improved DFS, and rs1520220 in IGF1 and rs2677760 in PIK3CA were associated with worse DFS. The associations were not significantly modified by the type of systemic treatment received or body mass index. The SNPs were not associated with tumor characteristics such as tumor size, lymph node status, nuclear grade, or hormone receptor status. In this study, germline SNPs in the PI3 K-AKT-mTOR pathway were associated with breast cancer DFS and may be potential prognostic markers. Future studies are needed to replicate our results and to evaluate the relationship between these polymorphisms and activation of the PI3 K-AKT-mTOR pathway in breast tumors. [ABSTRACT FROM AUTHOR]

Molecular profiling of tumors promises to advance the clinical management of cancer, but the benefits of integrating molecular data with traditional clinical variables have not been systematically studied. Here we retrospectively predict patient survival using diverse molecular data (somatic copy-number alteration, DNA methylation and mRNA, microRNA and protein expression) from 953 samples of four cancer types from The Cancer Genome Atlas project. We find that incorporating molecular data with clinical variables yields statistically significantly improved predictions (FDR < 0.05) for three cancers but those quantitative gains were limited (2.2-23.9%). Additional analyses revealed little predictive power across tumor types except for one case. In clinically relevant genes, we identified 10,281 somatic alterations across 12 cancer types in 2,928 of 3,277 patients (89.4%), many of which would not be revealed in single-tumor analyses. Our study provides a starting point and resources, including an open-access model evaluation platform, for building reliable prognostic and therapeutic strategies that incorporate molecular data. [ABSTRACT FROM AUTHOR]

The aim of this study is to identify and validate copy number aberrations in early-stage primary breast tumors associated with bone or non-bone metastasis. Whole-genome molecular inversion probe arrays were used to evaluate copy number imbalances (CNIs) in breast tumors from 960 early-stage patients with information about site of metastasis. The CoxBoost algorithm was used to select metastasis site-related CNIs and to fit a Cox proportional hazards model. Gains at 1q41 and 1q42.12 and losses at 1p13.3, 8p22, and Xp11.3 were significantly associated with bone metastasis. Gains at 2p11.2, 3q21.3-22.2, 3q27.1, 10q23.1, and 14q13.2-3 and loss at 7q21.11 were associated with non-bone metastasis. To examine the joint effect of CNIs and clinical predictors, patients were stratified into three risk groups (low, intermediate, and high) based on the sum of predicted linear hazard ratios. For bone metastasis, the hazard (95 % confidence interval) for the low-risk group was 0.32 (0.11-0.92) compared to the intermediate-risk group and 2.99 (1.74-5.11) for the high-risk group. For non-bone metastasis, the hazard for the low-risk group was 0.34 (0.17-0.66) and 2.33 (1.59-3.43) for the high-risk group. The prognostic value of loss at 8p22 for bone metastasis and gains at 10q23.1 for non-bone metastasis, and gain at 11q13.5 for both bone and non-bone metastases were externally validated in 335 breast tumors pooled from four independent cohorts. Distinct CNIs are independently associated with bone and non-bone metastasis for early-stage breast cancer patients across cohorts. These data warrant consideration for tailoring surveillance and management of metastasis risk. [ABSTRACT FROM AUTHOR]

We conducted a phase II feasibility study of a 6-month behavioral weight loss intervention in postmenopausal overweight and obese women at increased risk for breast cancer and the effects of weight loss on anthropomorphic, blood, and benign breast tissue biomarkers. 67 women were screened by random peri-areolar fine-needle aspiration, 27 were registered and 24 participated in the interventional phase. The 24 biomarker evaluable women had a median baseline BMI of 34.2 kg/m and lost a median of 11 % of their initial weight. Significant tissue biomarker modulation after the 6-month intervention was noted for Ki-67 (if restricted to the 15 women with any Ki-67 at baseline, p = 0.041), adiponectin to leptin ratio ( p = 0.003); and cyclin B1 ( p = 0.001), phosphorylated retinoblastoma ( p = 0.005), and ribosomal S6 ( p = 0.004) proteins. Favorable modulation for serum markers was observed for sex hormone-binding globulin ( p < 0.001), bioavailable estradiol ( p < 0.001), bioavailable testosterone ( p = 0.033), insulin ( p = 0.018), adiponectin ( p = 0.001), leptin ( p < 0.001), the adiponectin to leptin ratio ( p < 0.001), C-reactive protein ( p = 0.002), and hepatocyte growth factor ( p = 0.011). When subdivided by <10 or >10 % weight loss, change in percent total body and android (visceral) fat, physical activity, and the majority of the serum and tissue biomarkers were significantly modulated only for women with >10 % weight loss from baseline. Some factors such as serum PAI-1 and breast tissue pS2 (estrogen-inducible gene) mRNA were not significantly modulated overall but were when considering only those with >10 % weight loss. In conclusion, a median weight loss of 11 % over 6 months resulted in favorable modulation of a number of anthropomorphic, breast tissue and serum risk and mechanistic markers. Weight loss of 10 % or more should likely be the goal for breast cancer risk reduction studies in obese women. [ABSTRACT FROM AUTHOR]

Stearoyl-CoA desaturase 1 (SCD1) is an essential regulator of fatty acid synthesis. We have previously shown that overexpression of SCD1 increases the growth of breast cancer cell lines. The purpose of this study was to determine the relationship between SCD1 expression level and clinical-pathologic characteristics and survival of patients with breast cancer. Fine-needle aspirates were collected from the primary tumors of 250 patients with stage I-III breast cancer. Demographic and clinical characteristics including patient age, ethnicity, and menopausal status and tumor clinical stage, grade, and subtype were reviewed. SCD1 expression was analyzed using reverse-phase protein arrays. Samples were divided into high or low SCD1 expression levels based on a cut-off determined from martingale residual plots and regression tree analysis. SCD1 levels were significantly higher in tumors from patients >50-years old compared to patients ≤50-years old and were lower in triple-negative (estrogen/progesterone receptor-negative and human epidermal growth factor receptor-2-negative) breast cancers than other tumor subtypes. After adjusting for patient age, tumor subtype, tumor grade, and clinical stage, we found that patients with primary breast cancers expressing high SCD1 levels had significantly shorter relapse-free survival (RFS) ( P = 0.0140) and overall survival (OS) ( P = 0.039) in multivariable analysis. We conclude that SCD1 expression varies by breast cancer subtype and that high levels of SCD1 expression are associated with significantly shorter RFS and OS in multivariable analysis. Future studies are needed to define the role of SCD1 in the malignant phenotype of breast cancer and to evaluate the potential for SCD1 as a therapeutic target. [ABSTRACT FROM AUTHOR]

Neoadjuvant chemotherapy (NAC) induces a pathological complete response (pCR) in ?30% of patients with breast cancer. However, many patients have residual cancer after chemotherapy, which correlates with a higher risk of metastatic recurrence and poorer outcome than those who achieve a pCR. We hypothesized that molecular profiling of tumors after NAC would identify genes associated with drug resistance. Digital transcript counting was used to profile surgically resected breast cancers after NAC. Low concentrations of dual specificity protein phosphatase 4 (DUSP4), an ERK phosphatase, correlated with high post-NAC tumor cell proliferation and with basal-like breast cancer (BLBC) status. BLBC had higher DUSP4 promoter methylation and gene expression patterns of Ras-ERK pathway activation relative to other breast cancer subtypes. DUSP4 overexpression increased chemotherapy-induced apoptosis, whereas DUSP4 depletion dampened the response to chemotherapy. Reduced DUSP4 expression in primary tumors after NAC was associated with treatment-refractory high Ki-67 scores and shorter recurrence-free survival. Finally, inhibition of mitogen-activated protein kinase kinase (MEK) synergized with docetaxel treatment in BLBC xenografts. Thus, DUSP4 downregulation activates the Ras-ERK pathway in BLBC, resulting in an attenuated response to anti-cancer chemotherapy. [ABSTRACT FROM AUTHOR]

Purpose: The phosphatidylinositol 3-kinase (PI3K)/PTEN/AKT/mTOR and Ras/Raf/MEK/ERK pathways have been implicated in endometrial tumorigenesis. In this candidate pathway analysis, we investigated associations between genetic variations in these two pathways and both risk and clinical outcomes of endometrial cancer. Methods: We genotyped a total of 48 potentially functional SNPs in 11 key genes ( AKT1, AKT2, AKT3, BRAF, FRAP1, KRAS, PDPK1, PIK3CA, PIK3CB, PIK3R1, and PTEN) with the Sequenom genotyping platform in 115 endometrial cancer patients and 230 cancer-free women to evaluate their associations with risk, survival, and recurrence of endometrial cancer. Results: We found the following: (1) PIK3CA rs6443624 and rs9838411 variants either borderline or significantly decreased risk of endometrial cancer in a dominant model (adjusted odds ratio [OR], 0.62; 95% CI, 0.39-1.00 and 0.59; 95% CI, 0.36-0.95, respectively). Furthermore, there was a statistically significant multiplicative interaction ( P = 0.036) between these two loci in risk of endometrial cancer. In contrast, the AKT1 rs2498801 genotype significantly increased risk of endometrial cancer (adjusted OR, 1.94; 95% CI, 1.02-3.67 in a recessive model). (2) In Cox regression analyses, three SNPs ( PIK3R1 rs1862162, AKT2 rs892119, and PIK3CA rs2699887) showed significant associations with survival of endometrial cancer patients. (3) KRAS rs7312175 and PIK3CA rs6443624 had significant effects on recurrence of endometrial cancer individually and combined in a locus-dosage manner (adjusted P = 0.003). Conclusion: These results suggest that common genetic variations in these pathways may modulate risk and clinical outcomes of endometrial cancer. Further replication and functional studies are needed to confirm these findings. [ABSTRACT FROM AUTHOR]