Interferon signaling promotes tolerance to chromosomal instability during metastatic evolution in renal cancer.

Molecular routes to metastatic dissemination are critical determinants of aggressive cancers. Through in vivo CRISPR-Cas9 genome editing, we generated somatic mosaic genetically engineered models that faithfully recapitulate metastatic renal tumors. Disruption of 9p21 locus is an evolutionary driver to systemic disease through the rapid acquisition of complex karyotypes in cancer cells. Cross-species analysis revealed that recurrent patterns of copy number variations, including 21q loss and dysregulation of the interferon pathway, are major drivers of metastatic potential. In vitro and in vivo genomic engineering, leveraging loss-of-function studies, along with a model of partial trisomy of chromosome 21q, demonstrated a dosage-dependent effect of the interferon receptor genes cluster as an adaptive mechanism to deleterious chromosomal instability in metastatic progression. This work provides critical knowledge on drivers of renal cell carcinoma progression and defines the primary role of interferon signaling in constraining the propagation of aneuploid clones in cancer evolution.

Loss of ARID1A Promotes Epithelial-Mesenchymal Transition and Sensitizes Pancreatic Tumors to Proteotoxic Stress.

Cellular dedifferentiation is a key mechanism driving cancer progression. Acquisition of mesenchymal features has been associated with drug resistance, poor prognosis, and disease relapse in many tumor types. Therefore, successful targeting of tumors harboring these characteristics is a priority in oncology practice. The SWItch/Sucrose non-fermentable (SWI/SNF) chromatin remodeling complex has also emerged as a critical player in tumor progression, leading to the identification of several SWI/SNF complex genes as potential disease biomarkers and targets of anticancer therapies. AT-rich interaction domain-containing protein 1A (ARID1A) is a component of SWI/SNF, and mutations in ARID1A represent one of the most frequent molecular alterations in human cancers. ARID1A mutations occur in approximately 10% of pancreatic ductal adenocarcinomas (PDAC), but whether these mutations confer a therapeutic opportunity remains unclear. Here, we demonstrate that loss of ARID1A promotes an epithelial-mesenchymal transition (EMT) phenotype and sensitizes PDAC cells to a clinical inhibitor of HSP90, NVP-AUY922, both in vitro and in vivo. Although loss of ARID1A alone did not significantly affect proliferative potential or rate of apoptosis, ARID1A-deficient cells were sensitized to HSP90 inhibition, potentially by promoting the degradation of intermediate filaments driving EMT, resulting in cell death. Our results describe a mechanistic link between ARID1A defects and a quasi-mesenchymal phenotype, suggesting that deleterious mutations in ARID1A associated with protein loss exhibit potential as a biomarker for patients with PDAC who may benefit by HSP90-targeting drugs treatment. SIGNIFICANCE: This study identifies ARID1A loss as a promising biomarker for the identification of PDAC tumors that are potentially responsive to treatment with proteotoxic agents.

Allosteric SHP2 Inhibitor, IACS-13909, Overcomes EGFR-Dependent and EGFR-Independent Resistance Mechanisms toward Osimertinib.

Src homology 2 domain-containing phosphatase (SHP2) is a phosphatase that mediates signaling downstream of multiple receptor tyrosine kinases (RTK) and is required for full activation of the MAPK pathway. SHP2 inhibition has demonstrated tumor growth inhibition in RTK-activated cancers in preclinical studies. The long-term effectiveness of tyrosine kinase inhibitors such as the EGFR inhibitor (EGFRi), osimertinib, in non-small cell lung cancer (NSCLC) is limited by acquired resistance. Multiple clinically identified mechanisms underlie resistance to osimertinib, including mutations in EGFR that preclude drug binding as well as EGFR-independent activation of the MAPK pathway through alternate RTK (RTK-bypass). It has also been noted that frequently a tumor from a single patient harbors more than one resistance mechanism, and the plasticity between multiple resistance mechanisms could restrict the effectiveness of therapies targeting a single node of the oncogenic signaling network. Here, we report the discovery of IACS-13909, a specific and potent allosteric inhibitor of SHP2, that suppresses signaling through the MAPK pathway. IACS-13909 potently impeded proliferation of tumors harboring a broad spectrum of activated RTKs as the oncogenic driver. In EGFR-mutant osimertinib-resistant NSCLC models with EGFR-dependent and EGFR-independent resistance mechanisms, IACS-13909, administered as a single agent or in combination with osimertinib, potently suppressed tumor cell proliferation in vitro and caused tumor regression in vivo. Together, our findings provide preclinical evidence for using a SHP2 inhibitor as a therapeutic strategy in acquired EGFRi-resistant NSCLC. SIGNIFICANCE: These findings highlight the discovery of IACS-13909 as a potent, selective inhibitor of SHP2 with drug-like properties, and targeting SHP2 may serve as a therapeutic strategy to overcome tumor resistance to osimertinib.

Predictive Signatures Inform the Effective Repurposing of Decitabine to Treat KRAS-Dependent Pancreatic Ductal Adenocarcinoma.

Mutated KRAS protein is a pivotal tumor driver in pancreatic cancer. However, despite comprehensive efforts, effective therapeutics that can target oncogenic KRAS are still under investigation or awaiting clinical approval. Using a specific KRAS-dependent gene signature, we implemented a computer-assisted inspection of a drug-gene network to in silico repurpose drugs that work like inhibitors of oncogenic KRAS. We identified and validated decitabine, an FDA-approved drug, as a potent inhibitor of growth in pancreatic cancer cells and patient-derived xenograft models that showed KRAS dependency. Mechanistically, decitabine efficacy was linked to KRAS-driven dependency on nucleotide metabolism and its ability to specifically impair pyrimidine biosynthesis in KRAS-dependent tumors cells. These findings also showed that gene signatures related to KRAS dependency might be prospectively used to inform on decitabine sensitivity in a selected subset of patients with KRAS-mutated pancreatic cancer. Overall, the repurposing of decitabine emerged as an intriguing option for treating pancreatic tumors that are addicted to mutant KRAS, thus offering opportunities for improving the arsenal of therapeutics for this extremely deadly disease. SIGNIFICANCE: Decitabine is a promising drug for cancer cells dependent on RAS signaling.

A Fast and Flexible Framework for Network-Assisted Genomic Association.

We present an accessible, fast, and customizable network propagation system for pathway boosting and interpretation of genome-wide association studies. This system-NAGA (Network Assisted Genomic Association)-taps the NDEx biological network resource to gain access to thousands of protein networks and select those most relevant and performative for a specific association study. The method works efficiently, completing genome-wide analysis in under 5 minutes on a modern laptop computer. We show that NAGA recovers many known disease genes from analysis of schizophrenia genetic data, and it substantially boosts associations with previously unappreciated genes such as amyloid beta precursor. On this and seven other gene-disease association tasks, NAGA outperforms conventional approaches in recovery of known disease genes and replicability of results. Protein interactions associated with disease are visualized and annotated in Cytoscape, which, in addition to standard programmatic interfaces, allows for downstream analysis.

A global transcriptional network connecting noncoding mutations to changes in tumor gene expression.

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer.

pyNBS: a Python implementation for network-based stratification of tumor mutations.

Summary: We present pyNBS: a modularized Python 2.7 implementation of the network-based stratification (NBS) algorithm for stratifying tumor somatic mutation profiles into molecularly and clinically relevant subtypes. In addition to release of the software, we benchmark its key parameters and provide a compact cancer reference network that increases the significance of tumor stratification using the NBS algorithm. The structure of the code exposes key steps of the algorithm to foster further collaborative development. Availability and implementation: The package, along with examples and data, can be downloaded and installed from the URL https://github.com/idekerlab/pyNBS.

Disruption of NSD1 in Head and Neck Cancer Promotes Favorable Chemotherapeutic Responses Linked to Hypomethylation.

Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) represents a distinct classification of cancer with worse expected outcomes. Of the 11 genes recurrently mutated in HNSCC, we identify a singular and substantial survival advantage for mutations in the gene encoding Nuclear Set Domain Containing Protein 1 (NSD1), a histone methyltransferase altered in approximately 10% of patients. This effect, a 55% decrease in risk of death in NSD1-mutated versus non-mutated patients, can be validated in an independent cohort. NSD1 alterations are strongly associated with widespread genome hypomethylation in the same tumors, to a degree not observed for any other mutated gene. To address whether NSD1 plays a causal role in these associations, we use CRISPR-Cas9 to disrupt NSD1 in HNSCC cell lines and find that this leads to substantial CpG hypomethylation and sensitivity to cisplatin, a standard chemotherapy in head and neck cancer, with a 40% to 50% decrease in the IC50 value. Such results are reinforced by a survey of 1,001 cancer cell lines, in which loss-of-function NSD1 mutations have an average 23% decrease in cisplatin IC50 value compared with cell lines with wild-type NSD1Significance: This study identifies a favorable subtype of HPV-negative HNSCC linked to NSD1 mutation, hypomethylation, and cisplatin sensitivity. Mol Cancer Ther; 17(7); 1585-94. ©2018 AACR.

Systematic Evaluation of Molecular Networks for Discovery of Disease Genes.

Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for particular applications. Here, we evaluate 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets identified through literature curation, gene expression profiling, or genome-wide association studies. While all networks have some ability to recover disease genes, we observe a wide range of performance with STRING, ConsensusPathDB, and GIANT networks having the best performance overall. A general tendency is that performance scales with network size, suggesting that new interaction discovery currently outweighs the detrimental effects of false positives. Correcting for size, we find that the DIP network provides the highest efficiency (value per interaction). Based on these results, we create a parsimonious composite network with both high efficiency and performance. This work provides a benchmark for selection of molecular networks in human disease research.

Genomic Landscape of Appendiceal Neoplasms.

PURPOSE: Appendiceal neoplasms are heterogeneous and are often treated with chemotherapy similarly to colorectal cancer (CRC). Genomic profiling was performed on 703 appendiceal cancer specimens to compare the mutation profiles of appendiceal subtypes to CRC and other cancers, with the ultimate aim to identify potential biomarkers and novel therapeutic targets. METHODS: Tumor specimens were submitted to a Clinical Laboratory Improvement Amendments-certified laboratory (Foundation Medicine, Cambridge, MA) for hybrid-capture-based sequencing of 3,769 exons from 315 cancer-related genes and 47 introns of 28 genes commonly rearranged in cancer. Interactions between genotype, histologic subtype, treatment, and overall survival (OS) were analyzed in a clinically annotated subset of 76 cases. RESULTS: There were five major histopathologic subtypes: mucinous adenocarcinomas (46%), adenocarcinomas (30%), goblet cell carcinoids (12%), pseudomyxoma peritonei (7.7%), and signet ring cell carcinomas (5.2%). KRAS (35% to 81%) and GNAS (8% to 72%) were the most frequent alterations in epithelial cancers; APC and TP53 mutations were significantly less frequent in appendiceal cancers relative to CRC. Low-grade and high-grade tumors were enriched for GNAS and TP53 mutations, respectively (both χ2 P < .001). GNAS and TP53 were mutually exclusive (Bonferroni corrected P < .001). Tumor grade and TP53 mutation status independently predicted OS. The mutation status of GNAS and TP53 strongly predicted OS (median, 37.1 months for TP53 mutant v 75.8 GNAS-TP53 wild type v 115.5 GNAS mutant; log-rank P = .0031) and performed as well as grade in risk stratifying patients. CONCLUSION: Epithelial appendiceal cancers and goblet cell carcinoids show differences in KRAS and GNAS mutation frequencies and have mutation profiles distinct from CRC. This study highlights the benefit of performing molecular profiling on rare tumors to identify prognostic and predictive biomarkers and new therapeutic targets.

ERCC1 and TS Expression as Prognostic and Predictive Biomarkers in Metastatic Colon Cancer.

In patients with metastatic colon cancer, response to first line chemotherapy is a strong predictor of overall survival (OS). Currently, oncologists lack diagnostic tests to determine which chemotherapy regimen offers the greatest chance for response in an individual patient. Here we present the results of gene expression analysis for two genes, ERCC1 and TS, measured with the commercially available ResponseDX: Colon assay (Response Genetics, Los Angeles, CA) in 41 patients with de novo metastatic colon cancer diagnosed between July 2008 and August 2013 at the University of California, San Diego. In addition ERCC1 and TS expression levels as determined by RNAseq and survival data for patients in TCGA were downloaded from the TCGA data portal. We found that patients with low expression of ERCC1 (n = 33) had significantly longer median OS (36.0 vs. 10.1 mo, HR 0.29, 95% CI .095 to .84, log-rank p = 9.0x10-6) and median time to treatment to failure (TTF) following first line chemotherapy (14.1 vs. 2.4 mo, HR 0.17, 95% CI 0.048 to 0.58, log-rank p = 5.3x10-4) relative to those with high expression (n = 4). After accounting for the covariates age, sex, tumor grade and ECOG performance status in a Cox proportional hazard model the association of low ERCC1 with longer OS (HR 0.18, 95% CI 0.14 to 0.26, p = 0.0448) and TTF (HR 0.16, 95% CI 0.14 to 0.21, p = 0.0053) remained significant. Patients with low TS expression (n = 29) had significantly longer median OS (36.0 vs. 14.8 mo, HR 0.25, 95% CI 0.074 to 0.82, log-rank p = 0.022) relative to those with high expression (n = 12). The combined low expression of ERCC1/TS was predictive of response in patients treated with FOLFOX (40% vs. 91%, RR 2.3, Fisher's exact test p = 0.03, n = 27), but not with FOLFIRI (71% vs. 71%, RR 1.0, Fisher's exact test p = 1, n = 14). Overall, these findings suggest that measurement of ERCC1 and TS expression has potential clinical utility in managing patients with metastatic colorectal cancer.