Endoscopic Response Reduces the Risk of Subsequent Pouchitis in Patients With Crohn's Disease-Like Pouch Inflammation.

INTRODUCTION: The aim of this study was to report the frequency and impact of endoscopic response and remission on the risk of subsequent pouchitis in patients with Crohn's disease-like pouch inflammation (CDLPI) on therapy. METHODS: This was a single-center retrospective study of patients older than 18 years with CDLPI on therapy. RESULTS: Among 110 included patients with CDLPI in clinical remission, endoscopic remission was not significantly associated with a reduced risk of subsequent pouchitis when compared with endoscopic response. DISCUSSION: Endoscopic response, not remission, is sufficient to reduce the risk of subsequent pouchitis in patients with CDLPI.

Association between echocardiographic features, troponin levels, and survival time in hospitalized COVID-19 patients with cardiovascular events.

Introduction: This study aims to explore the predictive roles of echocardiographic parameters and biomarkers in determining outcomes among hospitalized COVID-19 patients experiencing cardiovascular events. Methods: A retrospective cohort study was conducted involving 49 COVID-19 patients who encountered cardiovascular events during hospitalization and underwent echocardiography. Our findings revealed notable associations between echocardiographic parameters and survival time. Results: A decrease in left ventricular ejection fraction (LVEF) of 10% was linked to a 20% reduction in survival time (TR: 0.80, 95% CI: 0.67 - 0.96, p = .017). Similarly, an increase in left ventricular (LV) volume by 10 mL was associated with a 9% decrease in survival time (TR: 0.91, 95% CI: 0.84 - 0.98, p = .011). Moreover, an increase in left atrial (LA) volume by 10 mL corresponded to an 8% decrease in survival time (TR: 0.92, 95% CI: 0.86 - 0.99, p = .026). Additionally, each 1 cm increase in right ventricular (RV) diameter was linked to a 22% reduction in survival time (TR: 0.78, 95% CI: 0.61 - 0.99, p = .043). Furthermore, a 10 mL increase in right atrial (RA) volume was associated with a 12% decrease in survival time (TR: 0.88, 95% CI: 0.78 - 0.98, p = .017). Notably, a tenfold rise in troponin levels was linked to a 33% decrease in survival time (TR: 0.67, 95% CI: 0.48 - 0.93, p = .014). Conclusions: Our study emphasizes the significant associations between various echocardiographic parameters and troponin levels with reduced survival time among COVID-19 patients experiencing cardiovascular events. These findings highlight the potential utility of echocardiography and troponin assessment in predicting outcomes and guiding management strategies in this patient population.

Detection of COVID-19 by quantitative analysis of carbonyl compounds in exhaled breath.

COVID-19 has caused a worldwide pandemic, creating an urgent need for early detection methods. Breath analysis has shown great potential as a non-invasive and rapid means for COVID-19 detection. The objective of this study is to detect patients infected with SARS-CoV-2 and even the possibility to screen between different SARS-CoV-2 variants by analysis of carbonyl compounds in breath. Carbonyl compounds in exhaled breath are metabolites related to inflammation and oxidative stress induced by diseases. This study included a cohort of COVID-19 positive and negative subjects confirmed by reverse transcription polymerase chain reaction between March and December 2021. Carbonyl compounds in exhaled breath were captured using a microfabricated silicon microreactor and analyzed by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). A total of 321 subjects were enrolled in this study. Of these, 141 (85 males, 60.3%) (mean ± SD age: 52 ± 15 years) were COVID-19 (55 during the alpha wave and 86 during the delta wave) positive and 180 (90 males, 50%) (mean ± SD age: 45 ± 15 years) were negative. Panels of a total of 34 ketones and aldehydes in all breath samples were identified for detection of COVID-19 positive patients. Logistic regression models indicated high accuracy/sensitivity/specificity for alpha wave (98.4%/96.4%/100%), for delta wave (88.3%/93.0%/84.6%) and for all COVID-19 positive patients (94.7%/90.1%/98.3%). The results indicate that COVID-19 positive patients can be detected by analysis of carbonyl compounds in exhaled breath. The technology for analysis of carbonyl compounds in exhaled breath has great potential for rapid screening and detection of COVID-19 and for other infectious respiratory diseases in future pandemics.

A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds.

BACKGROUND: The COVID-19 pandemic had profound global impacts on daily lives, economic stability, and healthcare systems. Diagnosis of COVID-19 infection via RT-PCR was crucial in reducing spread of disease and informing treatment management. While RT-PCR is a key diagnostic test, there is room for improvement in the development of diagnostic criteria. Identification of volatile organic compounds (VOCs) in exhaled breath provides a fast, reliable, and economically favorable alternative for disease detection. METHODS: This meta-analysis analyzed the diagnostic performance of VOC-based breath analysis in detection of COVID-19 infection. A systematic review of twenty-nine papers using the grading criteria from Newcastle-Ottawa Scale (NOS) and PRISMA guidelines was conducted. RESULTS: The cumulative results showed a sensitivity of 0.92 (95 % CI, 90 %-95 %) and a specificity of 0.90 (95 % CI 87 %-93 %). Subgroup analysis by variant demonstrated strong sensitivity to the original strain compared to the Omicron and Delta variant in detection of SARS-CoV-2 infection. An additional subgroup analysis of detection methods showed eNose technology had the highest sensitivity when compared to GC-MS, GC-IMS, and high sensitivity-MS. CONCLUSION: Overall, these results support the use of breath analysis as a new detection method of COVID-19 infection.

Different clinical characteristics and outcomes of adult hospitalized SARS-CoV-2 pneumonia patients complicated by cardiovascular events during the first, delta and omicron waves of COVID-19.

Background: The effects of SARS-CoV-2 have varied between significant waves of hospitalization. Research question: Are cardiovascular complications different among the first, delta and omicron waves of hospitalized COVID-19 pneumonia patients? Study design and methods: This was a multi-centre retrospective study of patients hospitalized with SARS-CoV-2 pneumonia: 632 were hospitalized during the first wave (March-July 2020), 1013 during the delta wave (September 2020-March 2021), and 323 during the omicron wave (January 2022-July 2022). Patients were stratified by wave and occurrence of cardiovascular events. Results: Among all hospitalized patients with cardiovascular events, patients in the omicron wave were younger (62.4 ± 14 years) than patients in the first wave (67.4 ± 7.8 years) and the delta wave (66.9 ± 12.6 years) and had a higher proportion of non-Hispanic White people than in the first wave (78.6% vs. 61.7%). For COVID-19 patients who suffered from cardiovascular events, the omicron wave patients had significantly higher neutrophil/lymphocyte ratio, white blood cell and platelet counts when compared to the first wave. Omicron wave patients had significantly lower albumin and B-type natriuretic peptide levels (only 5.8% of the first wave and 14.6% of the delta wave) when compared to either the first wave or delta wave patients. In COVID-19 patients who suffered cardiovascular events during hospitalization, mortality rate in the omicron wave (26.8%) was significantly lower than the first wave (48.3%), time to mortality for non-survivors of COVID-19 patients who suffered cardiovascular events was significantly longer in the omicron wave (median 16 days) than in the first wave (median 10 days). Conclusions: Younger and white patients were affected with cardiovascular complications more often by the omicron variant. Despite higher neutrophil/lymphocyte ratio and WBC counts, the omicron patients with cardiovascular events showed lower heart injuries, lower mortality and longer time to mortality for non-survivors when compared to the first and delta waves.

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.

The cost of anti-Asian racism during the COVID-19 pandemic.

Anti-Chinese sentiment increased during the COVID-19 pandemic, presenting as a considerable spike in overt violence and hatred directed at Asian American individuals. However, it is less clear how subtle patterns of consumer discrimination, which are difficult to directly observe yet greatly impact Asian American livelihoods, changed through the pandemic. Here we examine this in the context of restaurants-ubiquitous small businesses that sell goods that are closely entwined with ethnicity. Using a series of surveys, online search trends and consumer traffic data, we find that Asian restaurants experienced an 18.4% decrease in traffic (estimated US$7.42 billion lost revenue in 2020) relative to comparable non-Asian restaurants, with greater decreases in areas with higher levels of support for Donald Trump. Our findings are consistent with the roles of collective blame, out-group homogeneity and ethnic misidentification in explaining how anti-China rhetoric can harm the Asian American community, underlining the importance of avoiding racism and stigmatization in political and public health communications.

Leveraging weak supervision to perform named entity recognition in electronic health records progress notes to identify the ophthalmology exam.

OBJECTIVE: To develop deep learning models to recognize ophthalmic examination components from clinical notes in electronic health records (EHR) using a weak supervision approach. METHODS: A corpus of 39,099 ophthalmology notes weakly labeled for 24 examination entities was assembled from the EHR of one academic center. Four pre-trained transformer-based language models (DistilBert, BioBert, BlueBert, and ClinicalBert) were fine-tuned to this named entity recognition task and compared to a baseline regular expression model. Models were evaluated on the weakly labeled test dataset, a human-labeled sample of that set, and a human-labeled independent dataset. RESULTS: On the weakly labeled test set, all transformer-based models had recall > 0.93, with precision varying from 0.815 to 0.843. The baseline model had lower recall (0.769) and precision (0.682). On the human-annotated sample, the baseline model had high recall (0.962, 95 % CI 0.955-0.067) with variable precision across entities (0.081-0.999). Bert models had recall ranging from 0.771 to 0.831, and precision >=0.973. On the independent dataset, precision was 0.926 and recall 0.458 for BlueBert. The baseline model had better recall (0.708, 95 % CI 0.674-0.738) but worse precision (0.399, 95 % CI -0.352-0.451). CONCLUSION: We developed the first deep learning system to recognize eye examination components from clinical notes, leveraging a novel opportunity for weak supervision. Transformer-based models had high precision on human-annotated labels, whereas the baseline model had poor precision but higher recall. This system may be used to improve cohort and feature identification using free-text notes.Our weakly supervised approach may help amass large datasets of domain-specific entities from EHRs in many fields.

Age-dependent cognitive impairment, hydrocephalus and leukocyte infiltration in transgenic mice with endothelial expression of human EPHX2.

Soluble epoxide hydrolase (sEH) is upregulated in microvascular endothelium of human brain with vascular cognitive impairment (VCI). Transgenic endothelial expression of human sEH in mice (Tie2hsEH) induces endothelial dysfunction (ED), a pathogenetic mechanism of VCI. We sought to determine if endothelial upregulation of sEH is sufficient to cause cognitive impairment, and if cognitive impairment due to chronic hypoperfusion induced by unilateral common carotid artery occlusion (CCAO) is exacerbated in Tie2hsEH mice. Behavioral performance was assessed by the open field, rotarod, novel object, Morris water maze and fear conditioning tests. Cerebral blood flow and brain morphology were evaluated by MRI, and inflammatory changes investigated using immunohistochemistry and flow cytometry. We demonstrate that transgenic endothelial expression of sEH is sufficient to induce cognitive impairment, associated with leukocyte infiltration, brain atrophy and accelerated, age-dependent ventriculomegaly, identifying ED and sEH upregulation as potential underlying mechanisms and therapeutic targets for VCI.

Ruxolitinib reverses checkpoint inhibition by reducing programmed cell death ligand-1 (PD-L1) expression and increases anti-tumour effects of T cells in multiple myeloma.

Multiple myeloma (MM) tumour cells evade host immunity through a variety of mechanisms, which may potentially include the programmed cell death ligand-1 (PD-L1):programmed cell death protein-1 (PD-1) axis. This interaction contributes to the immunosuppressive bone marrow (BM) microenvironment, ultimately leading to reduced effector cell function. PD-L1 is overexpressed in MMBM and is associated with the resistance to immune-based approaches for treating MM. Ruxolitinib (RUX), an inhibitor of the Janus kinase (JAK) family of protein tyrosine kinases, is approved for myeloproliferative diseases. We investigated the effects of RUX alone or in combination with anti-MM agents on the expression of PD-L1 and T-cell cytotoxicity in MM. We showed that the expression of the PD-L1 gene was markedly increased in BM mononuclear cells from patients with MM with progressive disease versus those in complete remission. Furthermore, RUX treatment resulted in a concentration-dependent reduction of PD-L1 gene expression in the MM tumour cells cultured alone or co-cultured with stromal cells compared with untreated cells. The results also demonstrated that RUX increased MM cell apoptosis in the presence of interleukin-2-stimulated T cells to a similar degree as the treatment with anti-PD-1 or anti-PD-L1 antibodies. In summary, these results indicate that RUX can block PD-L1 expression resulting in augmentation of anti-MM effects of T cells.

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.

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on in silico estimation of MHC binding affinity and are limited by low predictive value for actual peptide presentation, inadequate support for rare MHC alleles, and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method that predicts peptide-MHC binding. MHCnuggets can predict binding for common or rare alleles of MHC class I or II with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is faster than other methods. When compared with methods that integrate binding affinity and MHC-bound peptide (HLAp) data from mass spectrometry, MHCnuggets yields a 4-fold increase in positive predictive value on independent HLAp data. We applied MHCnuggets to 26 cancer types in The Cancer Genome Atlas, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique predicted immunogenic missense mutations (IMM). Predicted IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted IMM load was significantly associated with increased immune cell infiltration (P < 2 × 10-16), including CD8+ T cells. Only 0.16% of predicted IMMs were observed in more than 2 patients, with 61.7% of these derived from driver mutations. Thus, we describe a method for neoantigen prediction and its performance characteristics and demonstrate its utility in data sets representing multiple human cancers.

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.

BDNF Val66Met polymorphism and clinical response to antipsychotic treatment in schizophrenia and schizoaffective disorder patients: a meta-analysis.

Brain-derived neurotrophic factor (BDNF) plays an important role in dopaminergic and serotonergic neurotransmission by modulating dopaminergic neuron differentiation and establishment. Multiple studies have analyzed the functional BDNF Val66Met variant in relation to antipsychotic response in schizophrenia (SCZ) patients, yielding mixed results. A meta-analysis was thus performed to examine the relationship between this variant and symptom improvement during antipsychotic treatment. Searches using PubMed, Web of Science, and PsycInfo until October 2017 yielded 11 studies that met inclusion criteria (total n = 3774). These studies investigated the BDNF Val66Met variant and antipsychotic response in patients with SCZ or schizoaffective disorder. Responders to antipsychotics were defined using the original criteria applied in each study. Effect sizes were computed using odds ratios, which were pooled according to the Mantel-Haenszel method. The BDNF Val66Met variant was not associated with the total number of responders and non-responders (p > 0.05) under dominant, recessive, or allelic models. Secondary analyses stratifying for individuals of each ethnicity and drug type also revealed no significant associations. Our findings suggest that the BDNF Val66Met variant is not associated with response to antipsychotics in individuals with SCZ. However, considering the current sample size, small effects cannot be ruled out. Moreover, recent studies have suggested that Val66Met forms haplotypes with other BDNF variants. Future studies should examine the Val66Met variant in conjunction with these other variants in relation to antipsychotic response. Moreover, since illness duration appears to influence BDNF levels in SCZ patients, future studies should aim to control for this potential confounding factor in response analyses.

Typing tumors using pathways selected by somatic evolution.

Many recent efforts to analyze cancer genomes involve aggregation of mutations within reference maps of molecular pathways and protein networks. Here, we find these pathway studies are impeded by molecular interactions that are functionally irrelevant to cancer or the patient's tumor type, as these interactions diminish the contrast of driver pathways relative to individual frequently mutated genes. This problem can be addressed by creating stringent tumor-specific networks of biophysical protein interactions, identified by signatures of epistatic selection during tumor evolution. Using such an evolutionarily selected pathway (ESP) map, we analyze the major cancer genome atlases to derive a hierarchical classification of tumor subtypes linked to characteristic mutated pathways. These pathways are clinically prognostic and predictive, including the TP53-AXIN-ARHGEF17 combination in liver and CYLC2-STK11-STK11IP in lung cancer, which we validate in independent cohorts. This ESP framework substantially improves the definition of cancer pathways and subtypes from tumor genome data.

Association of blood IgG with tumor necrosis factor-alpha and clinical course of chronic lymphocytic leukemia.

The intrinsic humoral immunodeficiency of chronic lymphocytic leukemia (CLL) is often managed with immunoglobulin replacement therapy (IgRT) to maintain IgG levels in the low-normal range (6-8 g/L) but optimal targets for IgG and timing to commence IgRT are unclear. IgG levels fell near 6 g/L at rates of -0.85±0.14 g/L/year in 51 patients who required treatment for CLL within 4.5±0.4 years from initial diagnosis and - 0.27±0.04 g/L/year in 40 patients with progressive disease who remained untreated after 8.5±0.5 years. In contrast, endogenous IgG levels remained above 8 g/L in patients with highly indolent disease (n = 25) and TNFα and beta-2-microglobulin (ß2M) in blood decreased when IgRT was used to increase IgG levels over 9 g/L. At 15 g/L but not 5 g/L, the IgRT product Hizentra® inhibited B cell receptor (BCR)-activation, TNFα production, and survival in vitro, particularly of CLL cells that spontaneously made little TNFα. These findings suggest deterioration of the humoral immune system is associated with progressive CLL and altering the dosing of IgRT to achieve higher than conventional IgG target levels may have therapeutic activity.

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.

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.