Variant Interpretation for Cancer (VIC): a computational tool for assessing clinical impacts of somatic variants.

BACKGROUND: Clinical laboratories implement a variety of measures to classify somatic sequence variants and identify clinically significant variants to facilitate the implementation of precision medicine. To standardize the interpretation process, the Association for Molecular Pathology (AMP), American Society of Clinical Oncology (ASCO), and College of American Pathologists (CAP) published guidelines for the interpretation and reporting of sequence variants in cancer in 2017. These guidelines classify somatic variants using a four-tiered system with ten criteria. Even with the standardized guidelines, assessing clinical impacts of somatic variants remains to be tedious. Additionally, manual implementation of the guidelines may vary among professionals and may lack reproducibility when the supporting evidence is not documented in a consistent manner. RESULTS: We developed a semi-automated tool called "Variant Interpretation for Cancer" (VIC) to accelerate the interpretation process and minimize individual biases. VIC takes pre-annotated files and automatically classifies sequence variants based on several criteria, with the ability for users to integrate additional evidence to optimize the interpretation on clinical impacts. We evaluated VIC using several publicly available databases and compared with several predictive software programs. We found that VIC is time-efficient and conservative in classifying somatic variants under default settings, especially for variants with strong and/or potential clinical significance. Additionally, we also tested VIC on two cancer-panel sequencing datasets to show its effectiveness in facilitating manual interpretation of somatic variants. CONCLUSIONS: Although VIC cannot replace human reviewers, it will accelerate the interpretation process on somatic variants. VIC can also be customized by clinical laboratories to fit into their analytical pipelines to facilitate the laborious process of somatic variant interpretation. VIC is freely available at https://github.com/HGLab/VIC/ .

Tumoral expression of drug and xenobiotic metabolizing enzymes in breast cancer patients of different ethnicities with implications to personalized medicine.

Drug and xenobiotic metabolizing enzymes (DXME) play important roles in drug responses and carcinogenesis. Recent studies have found that expression of DXME in cancer cells significantly affects drug clearance and the onset of drug resistance. In this study we compared the expression of DXME in breast tumor tissue samples from patients representing three ethnic groups: Caucasian Americans (CA), African Americans (AA), and Asian Americans (AS). We further combined DXME gene expression data with eQTL data from the GTEx project and with allele frequency data from the 1000 Genomes project to identify SNPs that may be associated with differential expression of DXME genes. We identified substantial differences among CA, AA, and AS populations in the expression of DXME genes and in activation of pathways involved in drug metabolism, including those involved in metabolizing chemotherapy drugs that are commonly used in the treatment of breast cancer. These data suggest that differential expression of DXME may associate with health disparities in breast cancer outcomes observed among these three ethnic groups. Our study suggests that development of personalized treatment strategies for breast cancer patients could be improved by considering both germline genotypes and tumor specific mutations and expression profiles related to DXME genes.

Integrative Comparison of mRNA Expression Patterns in Breast Cancers from Caucasian and Asian Americans with Implications for Precision Medicine.

Asian Americans (AS) have significantly lower incidence and mortality rates of breast cancer than Caucasian Americans (CA). Although this racial disparity has been documented, the underlying pathogenetic factors explaining it are obscure. We addressed this issue by an integrative genomics approach to compare mRNA expression between AS and CA cases of breast cancer. RNA-seq data from the Cancer Genome Atlas showed that mRNA expression revealed significant differences at gene and pathway levels. Increased susceptibility and severity in CA patients were likely the result of synergistic environmental and genetic risk factors, with arachidonic acid metabolism and PPAR signaling pathways implicated in linking environmental and genetic factors. An analysis that also added eQTL data from the Genotype-Tissue Expression Project and SNP data from the 1,000 Genomes Project identified several SNPs associated with differentially expressed genes. Overall, the associations we identified may enable a more focused study of genotypic differences that may help explain the disparity in breast cancer incidence and mortality rates in CA and AS populations and inform precision medicine. Cancer Res; 77(2); 423-33. ©2016 AACR.

Performing Concomitant Tricuspid Valve Repair at the Time of Mitral Valve Operations Is Not Associated With Increased Operative Mortality.

BACKGROUND: The performance of concomitant tricuspid valve repair (TVr) at the time of mitral valve repair or replacement (MVRR) has previously been associated with elevated short-term risk. Outcomes were assessed at incremental grades of tricuspid regurgitation (TR) to quantify the contemporary risk of concomitant TVr. METHODS: Between July 2011 and June 2014, 88,473 patients undergoing MVRR were examined using The Society of Thoracic Surgeons database. Outcomes with or without TVr, after isolated MVRR (n = 62,118) and MVRR with coronary artery bypass graft surgery (CABG [n = 26,355]), were independently analyzed at three levels of TR: none-mild, moderate, and severe. Risk-adjusted morbidity and mortality associated with the performance of concomitant TVr were evaluated using multivariable logistic regression. RESULTS: The TR was graded as none-mild in 74.3% of patients (65,769 of 88,473), moderate in 17.2% (15,222 of 88,473), and severe in 8.5% (7,482 of 88,473). The rate of TVr by TR grade was 3.5% (2,308 of 65,769) for none-mild, 30.6% (4,661 of 15,222) for moderate, and 75.6% (5,654 of 7,482) for severe. Overall risk-adjusted occurrence of any morbidity associated with performance of TVr was increased in both groups (MVRR odds ratio [OR] 1.36, 95% confidence interval [CI]: 1.24 to 1.48; and MVRR plus CABG OR 1.33, 95% CI: 1.19 to 1.49). However, at all grades of TR, TVr was not associated with increased risk-adjusted mortality (MVRR OR 0.99, 95% CI: 0.84 to 1.17; and MVRR plus CABG OR 1.04, 95% CI: 0.85 to 1.27). CONCLUSIONS: In contemporary patients, concomitant TVr is not associated with a risk-adjusted increase in mortality, regardless of TR severity. A more liberal approach to TVr at the time of MVRR may be justified when long-term benefits are thought to outweigh incremental short-term morbidity risk. Further investigation of longitudinal TVr outcomes is warranted.

Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records.

BACKGROUND: It is unclear whether and how whole-genome sequencing (WGS) data can be used to implement genomic medicine. Our objective is to retrospectively evaluate whether WGS can facilitate improving prevention and care for patients with susceptibility to cancer syndromes. METHODS AND FINDINGS: We analyzed genetic mutations in 60 autosomal dominant cancer-predisposition genes in 300 deceased patients with WGS data and nearly complete long-term (over 30 years) medical records. To infer biological insights from massive amounts of WGS data and comprehensive clinical data in a short period of time, we developed an in-house analysis pipeline within the SeqHBase software framework to quickly identify pathogenic or likely pathogenic variants. The clinical data of the patients who carried pathogenic and/or likely pathogenic variants were further reviewed to assess their clinical conditions using their lifetime EHRs. Among the 300 participants, 5 (1.7%) carried pathogenic or likely pathogenic variants in 5 cancer-predisposing genes: one in APC, BRCA1, BRCA2, NF1, and TP53 each. When assessing the clinical data, each of the 5 patients had one or more different types of cancers, fully consistent with their genetic profiles. Among these 5 patients, 2 died due to cancer while the others had multiple disorders later in their lifetimes; however, they may have benefited from early diagnosis and treatment for healthier lives, had the patients had genetic testing in their earlier lifetimes. CONCLUSIONS: We demonstrated a case study where the discovery of pathogenic or likely pathogenic germline mutations from population-wide WGS correlates with clinical outcome. The use of WGS may have clinical impacts to improve healthcare delivery.

SparkText: Biomedical Text Mining on Big Data Framework.

BACKGROUND: Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. RESULTS: In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. CONCLUSIONS: This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records.

IMPORTANCE: Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants. OBJECTIVE: To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014. EXPOSURES: One or more variants designated as pathogenic in SCN5A or KCNH2. MAIN OUTCOMES AND MEASURES: Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review. RESULTS: Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, -10 milliseconds; 95% CI, -16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds. CONCLUSIONS AND RELEVANCE: Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.

Evaluation of The Society of Thoracic Surgeons Online Risk Calculator for Assessment of Risk in Patients Presenting for Aortic Valve Replacement After Prior Coronary Artery Bypass Graft: An Analysis Using the STS Adult Cardiac Surgery Database.

BACKGROUND: Accurate risk assessment in patients presenting for aortic valve replacement (AVR) after prior coronary artery bypass grafting (CABG) is essential for appropriate selection of surgical versus percutaneous therapy. METHODS: We included 6,534 patients in The Society for Thoracic Surgeons (STS) Adult Cardiac Surgery Database (October 2009 through December 2013) who underwent elective, isolated reoperative AVR for aortic stenosis after prior CABG. Case-specific PROM was calculated and observed-to-expected ratios were inspected across the spectrum of risk. A cohort-specific recalibration equation was derived using logistic regression: = expit(-0.6453+0.6147*logit(PROM) -0.0709*logit(PROM)(ˆ)2), where PROM is the predicted risk of mortality. The proportion of patients reclassified as low (PROM < 4%), intermediate (4% to < 8%), high (8% to < 12%), and very high risk (≥ 12%) was calculated using the recalibration equation. The performance of the cohort-specific recalibration equation was then compared with the generic recalibration for quarterly STS reports. RESULTS: The STS online risk calculator overestimates risk for low, intermediate, and high risk categories. Using the recalibrated risk equation, a substantial proportion of patients were reclassified as the following: 25.5% from intermediate to low risk; 39.7% from high to intermediate risk; and 41.5% from very high to high risk. Comparison of the cohort-specific recalibration equation to the generic quarterly STS recalibration demonstrated very similar results. CONCLUSIONS: In patients presenting for AVR after prior CABG, the STS online risk calculator overestimates risk for all but the highest risk patients. Using a cohort-specific recalibration equation, a substantial proportion of patients would be downgraded to lower risk categories. The cohort-specific recalibration correlates well with the existing generic quarterly STS recalibration. The findings of this study support recommendations for periodic recalibration of the online risk calculator in order to facilitate clinical decision making in real time.

Epidemiology and outcomes after in-hospital cardiac arrest after pediatric cardiac surgery.

BACKGROUND: Multicenter data regarding cardiac arrest in children undergoing heart operations are limited. We describe epidemiology and outcomes associated with postoperative cardiac arrest in a large multiinstitutional cohort. METHODS: Patients younger than 18 years in the Society of Thoracic Surgeons Congenital Heart Surgery Database (2007 through 2012) were included. Patient factors, operative characteristics, and outcomes were described for patients with and without postoperative cardiac arrest. Multivariable models were used to evaluate the association of center volume with cardiac arrest rate and mortality after cardiac arrest, adjusting for patient and procedural factors. RESULTS: Of 70,270 patients (97 centers), 1,843 (2.6%) had postoperative cardiac arrest. Younger age, lower weight, and presence of preoperative morbidities (all p < 0.0001) were associated with cardiac arrest. Arrest rate increased with procedural complexity across common benchmark operations, ranging from 0.7% (ventricular septal defect repair) to 12.7% (Norwood operation). Cardiac arrest was associated with significant mortality risk across procedures, ranging from 15.4% to 62.3% (all p < 0.0001). In multivariable analysis, arrest rate was not associated with center volume (odds ratio, 1.06; 95% confidence interval, 0.71 to 1.57 in low- versus high-volume centers). However, mortality after cardiac arrest was higher in low-volume centers (odds ratio, 2.00; 95% confidence interval, 1.52 to 2.63). This association was present for both high- and low-complexity operations. CONCLUSIONS: Cardiac arrest carries a significant mortality risk across the stratum of procedural complexity. Although arrest rates are not associated with center volume, lower-volume centers have increased mortality after cardiac arrest. Further study of mechanisms to prevent cardiac arrest and to reduce mortality in those with an arrest is warranted.

The expanding role of mitral valve repair in triple valve operations: contemporary North American outcomes in 8,021 patients.

BACKGROUND: Although the operative risk of multivalve operations has historically been high, current outcomes are poorly understood. We sought to evaluate factors influencing contemporary results of triple-valve operations using The Society of Thoracic Surgeons Adult Cardiac Surgery Database. METHODS: Among patients undergoing combined mitral, aortic, and tricuspid valve (triple- valve) operations between 1993 and 2011, aortic valve repair patients were excluded and those having aortic valve replacement were analyzed according to whether they underwent repair vs replacement of the mitral valve (MV) and tricuspid valve (TV). Temporal trends in operative death and clinical outcomes were examined using unadjusted and adjusted analyses. RESULTS: A total of 8,021 triple-valve patients were studied. The median (25th percentile, 75th percentile) age was 67 years (59, 77 years), 4,809 (60%) were women, 4,488 (56%) had New York Heart Association class III to IV symptoms, and the mean (25th percentile, 75th percentile) ejection fraction was 50% (40%, 60%). MV repair was performed in 2,728 (34%) patients overall and increased over time from 13% (1993 to 1997) to 41% (2008 to 2011). TV repair was performed in 7,512 (94%) patients overall and increased over time from 86% (1993 to 1997) to 96% (2008 to 2011). Unadjusted operative mortality decreased from 17% in 1993 to 9% in 2011. Adjusted odds ratios (95% confidence intervals) of operative mortality were lower in those having MV repair (0.72 [0.61 to 0.85]), TV repair (0.64 [0.50 to 0.83]), and MV+TV repair (0.46 [0.34 to 0.63]) compared with those having replacements. Unadjusted and adjusted odds of stroke were similar between groups and not significant for all. CONCLUSIONS: This large series demonstrates that surgical results of triple-valve operations have continued to improve during the past 18 years. MV and TV repair were associated with improvements in early survival. Although further study is required to understand late outcomes, these data suggest that broader efforts to perform MV repair instead of replacement in this high-risk patient population appear warranted.

LncRNA profile study reveals a three-lncRNA signature associated with the survival of patients with oesophageal squamous cell carcinoma.

BACKGROUND: Oesophageal cancer is one of the most deadly forms of cancer worldwide. Long non-coding RNAs (lncRNAs) are often found to have important regulatory roles. OBJECTIVE: To assess the lncRNA expression profile of oesophageal squamous cell carcinoma (OSCC) and identify prognosis-related lncRNAs. METHOD: LncRNA expression profiles were studied by microarray in paired tumour and normal tissues from 119 patients with OSCC and validated by qRT-PCR. The 119 patients were divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random Forest supervised classification algorithm and a nearest shrunken centroid algorithm, then validated in a test group and further, in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by multivariable Cox regression analysis. RESULTS: LncRNAs showed significantly altered expression in OSCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885.1, XLOC_013014 and ENST00000547963.1) which classified the patients into two groups with significantly different overall survival (median survival 19.2 months vs >60 months, p<0.0001). The signature was applied to the test group (median survival 21.5 months vs >60 months, p=0.0030) and independent cohort (median survival 25.8 months vs >48 months, p=0.0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for patients with OSCC. Stratified analysis suggested that the signature was prognostic within clinical stages. CONCLUSIONS: Our results suggest that the three-lncRNA signature is a new biomarker for the prognosis of patients with OSCC, enabling more accurate prediction of survival.

Isocitrate dehydrogenase 1 is a novel plasma biomarker for the diagnosis of non-small cell lung cancer.

PURPOSE: Effective biomarkers for the diagnosis of non-small cell lung cancer (NSCLC) are needed. We previously showed that isocitrate dehydrogenase 1 (IDH1) is significantly increased in NSCLC tumors. This study aimed to examine the plasma levels of IDH1 in a large patient population to evaluate its effectiveness in NSCLC diagnosis. EXPERIMENTAL DESIGN: The plasma levels of IDH1, CA125, Cyfra21-1, and CEA were assayed by ELISA. Blood samples were obtained from 1,422 participants (943 patients with NSCLC and 479 healthy controls). The samples were randomly divided into a training set and a test set. Receiver operating characteristic and binary logistic regression analyses were applied to evaluate diagnostic efficacy and establish diagnostic mathematical models. RESULTS: Plasma IDH1 levels were significantly higher in patients with NSCLCs than in healthy controls (P < 0.001). The diagnostic use of IDH1 in lung adenocarcinoma [area under curve (AUC): 0.858 and 0.810; sensitivity: 77.1% and 76.2%; specificity: 82.9% and 76.6%; in the training set and test set, respectively] was significantly greater than that of CA125, Cyfra21-1, or CEA (P < 0.001). The model combining IDH1 with CEA, CA125, and Cyfra21-1 was more effective for lung adenocarcinoma diagnosis than IDH1 alone (sensitivity and specificity in the training set: 75.8%, 89.6%; test set: 86.3%, 70.7%). In addition, the plasma levels of IDH1 could contribute to the diagnostic model of lung squamous cell carcinoma. CONCLUSIONS: IDH1 can be used as a plasma biomarker for the diagnosis of NSCLCs, particularly lung adenocarcinoma, with relatively high sensitivity and specificity.

Prediction of incident heart failure in general practice: the Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: A simple and effective heart failure (HF) risk score would facilitate the primary prevention and early diagnosis of HF in general practice. We examined the external validity of existing HF risk scores, optimized a 10-year HF risk function, and examined the incremental value of several biomarkers, including N-terminal pro-brain natriuretic peptide. METHODS AND RESULTS: During 15.5 years (210 102 person-years of follow-up), 1487 HF events were recorded among 13 555 members of the biethnic Atherosclerosis Risk in Communities (ARIC) Study cohort. The area under curve from the Framingham-published, Framingham-recalibrated, Health ABC HF recalibrated, and ARIC risk scores were 0.610, 0.762, 0.783, and 0.797, respectively. On addition of N-terminal pro-brain natriuretic peptide, the optimism-corrected area under curve of the ARIC HF risk score increased from 0.773 (95% CI, 0.753-0.787) to 0.805 (95% CI, 0.792-0.820). Inclusion of N-terminal pro-brain natriuretic peptide improved the overall classification of recalibrated Framingham, recalibrated Health ABC, and ARIC risk scores by 18%, 12%, and 13%, respectively. In contrast, cystatin C or high-sensitivity C-reactive protein did not add toward incremental risk prediction. CONCLUSIONS: The ARIC HF risk score is more parsimonious yet performs slightly better than the extant risk scores in predicting 10-year risk of incident HF. The inclusion of N-terminal pro-brain natriuretic peptide markedly improves HF risk prediction. A simplified risk score restricted to a patient's age, race, sex, and N-terminal pro-brain natriuretic peptide performs comparably to the full score (area under curve, 0.745) and is suitable for automated reporting from laboratory panels and electronic medical records.

Association of circulating matrix metalloproteinases with carotid artery characteristics: the Atherosclerosis Risk in Communities Carotid MRI Study.

OBJECTIVE: To examine the relationship of plasma levels of matrix metalloproteinases (MMPs) and tissue inhibitor of metalloproteinase 1 (TIMP-1) with carotid artery characteristics measured by MRI in a cross-sectional investigation among Atherosclerosis Risk in Communities Carotid MRI Study participants. METHODS AND RESULTS: A stratified random sample was recruited based on intima-media thickness from a previous ultrasonographic examination. A high-resolution gadolinium-enhanced MRI examination of the carotid artery was performed from 2004 to 2005 on 1901 Atherosclerosis Risk in Communities cohort participants. Multiple carotid wall characteristics, including wall thickness, lumen area, calcium area, lipid core, and fibrous cap measures, were evaluated for associations with plasma MMPs 1, 2, 3, 7, 8, and 9 and TIMP-1. Plasma MMPs 1, 3, and 7 were significantly higher among participants in the high intima-media thickness group compared with those in the low intima-media thickness group. The normalized wall index was independently associated with MMPs 3 and 7 and TIMP-1. MMP-7 was positively associated with carotid calcification. The mean fibrous cap thickness was significantly higher in individuals with elevated TIMP-1 levels. In addition, TIMP-1 was positively associated with measures of lipid core. CONCLUSION: Circulating levels of specific MMPs and TIMP-1 were associated with carotid wall remodeling and structural changes related to plaque burden in elderly participants.