Comparative Analysis of Clinical Practice Guidelines for the Pharmacological Treatment of Type 2 Diabetes Mellitus in Latin America.

PURPOSE OF REVIEW: Type 2 diabetes mellitus (T2DM) is one of the leading causes of death and disability in the world. The majority of diabetes deaths (> 80%) occur in low- and middle-income countries, which are predominant in Latin America. Therefore, the purpose of this article is to compare the clinical practice guideline (CPG) for the pharmacological management of T2DM in Latin America (LA) with international reference guidelines. RECENT FINDINGS: Several LA countries have recently developed CPGs. However, the quality of these guidelines is unknown according to the AGREE II tool and taking as reference three CPGs of international impact: American Diabetes Association (ADA), European Diabetes Association (EASD), and Latin American Diabetes Association (ALAD). Ten CPGs were selected for analysis. The ADA scored > 80% on the AGREE II domains and was selected as the main comparator. Eighty percent of LA CPGs were developed before 2018. Only one was not recommended (all domains < 60%). The CPGs in LA have good quality but are outdated. They have significant gaps compared to the reference. There is a need for improvement, as proposing updates every three years to maintain the best available clinical evidence in all guidelines.

Unannotated small RNA clusters associated with circulating extracellular vesicles detect early stage liver cancer.

OBJECTIVE: Surveillance tools for early cancer detection are suboptimal, including hepatocellular carcinoma (HCC), and biomarkers are urgently needed. Extracellular vesicles (EVs) have gained increasing scientific interest due to their involvement in tumour initiation and metastasis; however, most extracellular RNA (exRNA) blood-based biomarker studies are limited to annotated genomic regions. DESIGN: EVs were isolated with differential ultracentrifugation and integrated nanoscale deterministic lateral displacement arrays (nanoDLD) and quality assessed by electron microscopy, immunoblotting, nanoparticle tracking and deconvolution analysis. Genome-wide sequencing of the largely unexplored small exRNA landscape, including unannotated transcripts, identified and reproducibly quantified small RNA clusters (smRCs). Their key genomic features were delineated across biospecimens and EV isolation techniques in prostate cancer and HCC. Three independent exRNA cancer datasets with a total of 479 samples from 375 patients, including longitudinal samples, were used for this study. RESULTS: ExRNA smRCs were dominated by uncharacterised, unannotated small RNA with a consensus sequence of 20 nt. An unannotated 3-smRC signature was significantly overexpressed in plasma exRNA of patients with HCC (p<0.01, n=157). An independent validation in a phase 2 biomarker case-control study revealed 86% sensitivity and 91% specificity for the detection of early HCC from controls at risk (n=209) (area under the receiver operating curve (AUC): 0.87). The 3-smRC signature was independent of alpha-fetoprotein (p<0.0001) and a composite model yielded an increased AUC of 0.93. CONCLUSION: These findings directly lead to the prospect of a minimally invasive, blood-only, operator-independent clinical tool for HCC surveillance, thus highlighting the potential of unannotated smRCs for biomarker research in cancer.

RNA2DNAlign: nucleotide resolution allele asymmetries through quantitative assessment of RNA and DNA paired sequencing data.

We introduce RNA2DNAlign, a computational framework for quantitative assessment of allele counts across paired RNA and DNA sequencing datasets. RNA2DNAlign is based on quantitation of the relative abundance of variant and reference read counts, followed by binomial tests for genotype and allelic status at SNV positions between compatible sequences. RNA2DNAlign detects positions with differential allele distribution, suggesting asymmetries due to regulatory/structural events. Based on the type of asymmetry, RNA2DNAlign outlines positions likely to be implicated in RNA editing, allele-specific expression or loss, somatic mutagenesis or loss-of-heterozygosity (the first three also in a tumor-specific setting). We applied RNA2DNAlign on 360 matching normal and tumor exomes and transcriptomes from 90 breast cancer patients from TCGA. Under high-confidence settings, RNA2DNAlign identified 2038 distinct SNV sites associated with one of the aforementioned asymetries, the majority of which have not been linked to functionality before. The performance assessment shows very high specificity and sensitivity, due to the corroboration of signals across multiple matching datasets. RNA2DNAlign is freely available from http://github.com/HorvathLab/NGS as a self-contained binary package for 64-bit Linux systems.

Quantification of three chlorinated dialkyl phosphates, diphenyl phosphate, 2,3,4,5-tetrabromobenzoic acid, and four other organophosphates in human urine by solid phase extraction-high performance liquid chromatography-tandem mass spectrometry.

Polybrominated diphenyl ethers (PBDEs), produced as flame retardants worldwide, have been phased-out in many countries, and chlorinated and non-chlorinated organophosphates and non-PBDE brominated formulations (e.g., Firemaster 550 (FM550)) have entered the consumers' market. Recent studies show that components of organophosphate esters and FM550 are frequently detected in many products common to human environments. Therefore, urinary metabolites of these compounds can be used as human exposure biomarkers. We developed a method to quantify nine compounds in 0.4 mL urine: diphenyl phosphate (DPhP), bis(1,3-dichloro-2-propyl) phosphate (BDCPP), bis-(1-chloro-2-propyl) phosphate, bis-2-chloroethyl phosphate, di-p-cresylphosphate, di-o-cresylphosphate (DoCP), di-n-butyl phosphate, dibenzyl phosphate (DBzP), and 2,3,4,5-tetrabromobenzoic acid. The method relies on an enzymatic hydrolysis of urinary conjugates of the target analytes, automated off-line solid phase extraction, reversed phase high performance liquid chromatography separation, and isotope dilution-electrospray ionization tandem mass spectrometry detection. The method is high-throughput (96 samples/day) with detection limits ranging from 0.05 to 0.16 ng mL-1. Spiked recoveries were 90-113 %, and interday imprecision was 2-8 %. We assessed the suitability of the method by analyzing urine samples collected from a convenience sample of adults (n = 76) and from a group of firefighters (n = 146). DPhP (median, 0.89; range, 0.26-5.6 ng mL-1) and BDCPP (median, 0.69; range, 0.31-6.8 ng mL-1) were detected in all of the non-occupationally exposed adult samples and all of the firefighter samples (DPhP [median, 2.9; range, 0.24-28 ng mL-1], BDCPP [median, 3.4; range, 0.30-44 ng mL-1]); DBzP and DoCP were not detected in any samples.

Improving deep vein thrombosis prophylaxis with mechanical modalities in surgical intensive care unit.

Deep vein thrombosis remains a source of adverse outcomes in surgical patients. Deep vein thrombosis is preventable with prophylactic intervention. The success of noninvasive mechanical modalities for prophylaxis relies on compliance with correct application. The goals of this project were to create a guideline that reflected current evidence and expert thinking about mechanical modalities use, assess compliance with mechanical modalities, and develop strategies to disseminate an evidence-based guideline for deep vein thrombosis prophylaxis.

A temporal classifier predicts histopathology state and parses acute-chronic phasing in inflammatory bowel disease patients.

Previous studies have conducted time course characterization of murine colitis models through transcriptional profiling of differential expression. We characterize the transcriptional landscape of acute and chronic models of dextran sodium sulfate (DSS) and adoptive transfer (AT) colitis to derive temporal gene expression and splicing signatures in blood and colonic tissue in order to capture dynamics of colitis remission and relapse. We identify sub networks of patient-derived causal networks that are enriched in these temporal signatures to distinguish acute and chronic disease components within the broader molecular landscape of IBD. The interaction between the DSS phenotype and chronological time-point naturally defines parsimonious temporal gene expression and splicing signatures associated with acute and chronic phases disease (as opposed to ordinary time-specific differential expression/splicing). We show these expression and splicing signatures are largely orthogonal, i.e. affect different genetic bodies, and that using machine learning, signatures are predictive of histopathological measures from both blood and intestinal data in murine colitis models as well as an independent cohort of IBD patients. Through access to longitudinal multi-scale profiling from disease tissue in IBD patient cohorts, we can apply this machine learning pipeline to generation of direct patient temporal multimodal regulatory signatures for prediction of histopathological outcomes.

Triple MAPK inhibition salvaged a relapsed post-BCMA CAR-T cell therapy multiple myeloma patient with a BRAF V600E subclonal mutation.

BACKGROUND: Multiple Myeloma (MM) is a progressive plasma cell neoplasm characterized by heterogeneous clonal expansion. Despite promising response rates achieved with anti-BCMA CAR-T cell therapy, patients may still relapse and there are currently no clear therapeutic options in post-CAR-T settings. In this report, we present a case of a post-BCMA CAR-T relapsed/refractory (RR) MM patient with skin extramedullary disease (EMD) in which a novel MAPK inhibition combinatorial strategy was implemented based on next-generation sequencing and in vitro experiments. CASE PRESENTATION: A 61-year-old male with penta-refractory MM penta- (IgA lambda), ISS stage 3 with hyperdiploidy, gain of 1q21 and del13 was treated with anti-BCMA CAR-T cell therapy, achieving a best response of VGPR. He progressed after 6 months and was salvaged for a short period with autologous stem cell transplantation. Eventually, he progressed with extramedullary disease manifested as subcutaneous nodules. Based on whole-exome sequencing, we identified a BRAF (V600E) dominant subclone in both bone marrow and cutaneous plasmacytoma. Following in vitro experiments, and according to our previous studies, we implemented a triple MAPK inhibition strategy under which the patient achieved a very good partial response for 110 days, which allowed to bridge him to subsequent clinical trials and eventually achieve a stringent complete response (sCR). CONCLUSION: Here, we show the applicability, effectiveness, and tolerability the triple MAPK inhibition strategy in the context of post-BCMA CAR-T failure in specific subset of patients. The triple therapy could bridge our hospice bound RRMM patient with BRAF (V600E) to further therapeutic options where sCR was achieved. We will further evaluate triple MAPK inhibition in patients with BRAF V600E in a precision medicine clinical trial launching soon.

A Three-Gene Signature Predicts Response to Selinexor in Multiple Myeloma.

PURPOSE: Selinexor is the first selective inhibitor of nuclear export to be approved for the treatment of relapsed or refractory multiple myeloma (MM). Currently, there are no known genomic biomarkers or assays to help select MM patients at higher likelihood of response to selinexor. Here, we aimed to characterize the transcriptomic correlates of response to selinexor-based therapy. METHODS: We performed RNA sequencing on CD138+ cells from the bone marrow of 100 patients with MM who participated in the BOSTON study, followed by differential gene expression and pathway analysis. Using the differentially expressed genes, we used cox proportional hazard models to identify a gene signature predictive of response to selinexor, followed by validation in external cohorts. RESULTS: The three-gene signature predicts response to selinexor-based therapy in patients with MM in the BOSTON cohort. Then, we validated this gene signature in 64 patients from the STORM cohort of triple-class refractory MM and additionally in an external cohort of 35 patients treated in a real-world setting outside of clinical trials. We found that the signature tracks with both depth and duration of response, and it also validates in a different tumor type using a cohort of pretreatment tumors from patients with recurrent glioblastoma. Furthermore, the genes involved in the signature, WNT10A, DUSP1, and ETV7, reveal a potential mechanism through upregulated interferon-mediated apoptotic signaling that may prime tumors to respond to selinexor-based therapy. CONCLUSION: In this study, we present a present a novel, three-gene expression signature that predicts selinexor response in MM. This signature has important clinical relevance as it could identify patients with cancer who are most likely to benefit from treatment with selinexor-based therapy.

Patient similarity network of newly diagnosed multiple myeloma identifies patient subgroups with distinct genetic features and clinical implications.

The remarkable genetic heterogeneity of multiple myeloma poses a substantial challenge for proper prognostication and clinical management of patients. Here, we introduce MM-PSN, the first multiomics patient similarity network of myeloma. MM-PSN enabled accurate dissection of the genetic and molecular landscape of the disease and determined 12 distinct subgroups defined by five data types generated from genomic and transcriptomic profiling of 655 patients. MM-PSN identified patient subgroups not previously described defined by specific patterns of alterations, enriched for specific gene vulnerabilities, and associated with potential therapeutic options. Our analysis revealed that co-occurrence of t(4;14) and 1q gain identified patients at significantly higher risk of relapse and shorter survival as compared to t(4;14) as a single lesion. Furthermore, our results show that 1q gain is the most important single lesion conferring high risk of relapse and that it can improve on the current International Staging Systems (ISS and R-ISS).

GeTallele: A Method for Analysis of DNA and RNA Allele Frequency Distributions.

Variant allele frequencies (VAF) are an important measure of genetic variation that can be estimated at single-nucleotide variant (SNV) sites. RNA and DNA VAFs are used as indicators of a wide-range of biological traits, including tumor purity and ploidy changes, allele-specific expression and gene-dosage transcriptional response. Here we present a novel methodology to assess gene and chromosomal allele asymmetries and to aid in identifying genomic alterations in RNA and DNA datasets. Our approach is based on analysis of the VAF distributions in chromosomal segments (continuous multi-SNV genomic regions). In each segment we estimate variant probability, a parameter of a random process that can generate synthetic VAF samples that closely resemble the observed data. We show that variant probability is a biologically interpretable quantitative descriptor of the VAF distribution in chromosomal segments which is consistent with other approaches. To this end, we apply the proposed methodology on data from 72 samples obtained from patients with breast invasive carcinoma (BRCA) from The Cancer Genome Atlas (TCGA). We compare DNA and RNA VAF distributions from matched RNA and whole exome sequencing (WES) datasets and find that both genomic signals give very similar segmentation and estimated variant probability profiles. We also find a correlation between variant probability with copy number alterations (CNA). Finally, to demonstrate a practical application of variant probabilities, we use them to estimate tumor purity. Tumor purity estimates based on variant probabilities demonstrate good concordance with other approaches (Pearson's correlation between 0.44 and 0.76). Our evaluation suggests that variant probabilities can serve as a dependable descriptor of VAF distribution, further enabling the statistical comparison of matched DNA and RNA datasets. Finally, they provide conceptual and mechanistic insights into relations between structure of VAF distributions and genetic events. The methodology is implemented in a Matlab toolbox that provides a suite of functions for analysis, statistical assessment and visualization of Genome and Transcriptome allele frequencies distributions. GeTallele is available at: https://github.com/SlowinskiPiotr/GeTallele.

Tumoral and immune heterogeneity in an anti-PD-1-responsive glioblastoma: a case study.

Clinical benefit of immune checkpoint blockade in glioblastoma (GBM) is rare, and we hypothesize that tumor clonal evolution and the immune microenvironment are key determinants of response. Here, we present a detailed molecular characterization of the intratumoral and immune heterogeneity in an IDH wild-type, MGMT-negative GBM patient who plausibly benefited from anti-PD-1 therapy with an unusually long 25-mo overall survival time. We leveraged multiplex immunohistochemistry, RNA-seq, and whole-exome data from the primary tumor and three resected regions of recurrent disease to survey regional tumor-immune interactions, genomic instability, mutation burden, and expression profiles. We found significant regional heterogeneity in the neoantigenic and immune landscape, with a differential T-cell signature among recurrent sectors, a uniform loss of focal amplifications in EGFR, and a novel subclonal EGFR mutation. Comparisons with recently reported correlates of checkpoint blockade in GBM and with TCGA-GBM revealed appreciable intratumoral heterogeneity that may have contributed to a differential PD-1 blockade response.

Intratumoral heterogeneity and clonal evolution in liver cancer.

Clonal evolution of a tumor ecosystem depends on different selection pressures that are principally immune and treatment mediated. We integrate RNA-seq, DNA sequencing, TCR-seq and SNP array data across multiple regions of liver cancer specimens to map spatio-temporal interactions between cancer and immune cells. We investigate how these interactions reflect intra-tumor heterogeneity (ITH) by correlating regional neo-epitope and viral antigen burden with the regional adaptive immune response. Regional expression of passenger mutations dominantly recruits adaptive responses as opposed to hepatitis B virus and cancer-testis antigens. We detect different clonal expansion of the adaptive immune system in distant regions of the same tumor. An ITH-based gene signature improves single-biopsy patient survival predictions and an expression survey of 38,553 single cells across 7 regions of 2 patients further reveals heterogeneity in liver cancer. These data quantify transcriptomic ITH and how the different components of the HCC ecosystem interact during cancer evolution.

Urinary paranitrophenol, a metabolite of methyl parathion, in Thai farmer and child populations.

Human exposure to methyl parathion can be assessed by measuring the concentration of its metabolite paranitrophenol (PNP) in urine. Our biologic monitoring study in Chiang Mai, Thailand, measured PNP and dialkylphosphate metabolites (i.e., dimethylphosphate [DMP] and dimethylthiophosphate [DMTP]) of methyl parathion in urine samples collected from 136 farmers (age 20 to 65 years) and 306 school children (age 10 to 15 years) in 2006. Participants came from two topographically different areas: one was colder and mountainous, whereas the other was alluvial with climate fluctuations depending on the monsoon season. Both children and farmers were recruited from each area. Despite methyl parathion's prohibited use in agriculture in 2004, we detected PNP in >90% of all samples analyzed. We applied a nonparametric correlation test (PNP vs. DMP and DMTP) to determine whether the PNP found in most of the samples tested resulted from exposures to methyl parathion. DMP (Spearman's rho = 0.601 [p = 0.001] for farmers and Spearman's rho = 0.263 [p <0.001] for children) and DMTP (Spearman's rho = 0.296 [p = 0.003] for farmers and Spearman's rho = 0.304 [p<0.001] for children) were positively correlated with PNP, suggesting a common source for the three analytes, presumably methyl parathion or related environmental degradates. Although we found a modest correlation between the metabolites, our findings suggest that despite the prohibition, at least a portion (approximately 25% to 60%) of the PNP detected among farmers and children in Thailand may be attributed to exposure from continued methyl parathion use.

Quantification of 16 urinary biomarkers of exposure to flame retardants, plasticizers, and organophosphate insecticides for biomonitoring studies.

Chlorinated alkyl and non-chlorinated aryl organophosphate flame retardants (OPFRs) and some brominated flame retardants (FR) were introduced as replacements for polybrominated diphenyl ethers (PBDEs) after PBDEs phase-out in 2004 and 2013. Organophosphorous (OP) insecticides are mainly used in agricultural settings since the Food Quality Protection Act of 1996 phased-out most residential uses of OP insecticides in the United States. Urinary metabolites of FRs and OPs are known exposure biomarkers to FRs and OP insecticides, respectively. For large population-based studies, concurrent quantification of these metabolites using a small urine volume is desirable, but until now was not possible. We developed an analytical approach to quantify in 0.2 mL urine 10 FRs and six OP insecticide metabolites: diphenyl phosphate, bis(1,3-dichloro-2-propyl) phosphate, bis(1-chloro-2-propyl) phosphate, bis(2-chloroethyl) phosphate, dicresyl phosphates, dibutyl phosphate, dibenzyl phosphate, 2,3,4,5-tetrabromobenzoic acid, 2-((isopropyl)phenyl)phenyl phosphate, 4-((tert-butyl)phenyl)phenyl phosphate, dimethyl phosphate, diethyl phosphate, dimethyl thiophosphate, dimethyl dithiophosphate, diethyl thiophosphate, and diethyl dithiophosphate. The method relies on enzymatic deconjugation, automated off-line solid phase extraction, high-performance liquid chromatography, and isotope dilution tandem mass spectrometry. Detection limits ranged from 0.05 to 0.5 ng mL-1, accuracy from 89 to 118%, and imprecision was <10%. . This method is the first to quantify simultaneously trace levels of 16 biomarkers of FRs and OP insecticides in only four drops of urine. We confirmed the method suitability for use in large epidemiological studies to assess background and occupational exposures to these classes of environmental pollutants by analyzing 303 samples collected from the general population and a group of firefighters. FR metabolite and DAPs concentrations in the general population group were lower than in the firefighters group, and within the ranges reported in the U.S. general population and other non-occupationally exposed populations.

Burden of Disease Attributable to Obesity and Overweight in Colombia.

OBJECTIVES: To estimate the burden of disease attributable to obesity and overweight conditions using disability-adjusted life-years (DALYs) in Colombia. METHODS: The burden of disease was estimated following an adapted methodology published by the World Health Organization. A selection of diseases was performed in which overweight and obesity are risk factors. DALYs were calculated by obtaining the proportion of cases and deaths of every disease that can be attributable to obesity and overweight conditions. The economic impact of obesity was calculated by multiplying the cost of care per patient for each comorbidity by the number of cases attributable exclusively to obesity. RESULTS: A total of 997 371 DALYs were estimated, 45% of which corresponded to men; 81% of DALYs corresponded to years lived with disability. Conditions with greater attributable DALYs are, in order, hypertension (31.6% of the total DALYs), type 2 diabetes mellitus (28.0%), cardiac ischemic disease (14.6%), and lower back pain (11.2%). An estimation of 20.5 DALYs per 1000 inhabitants was made. The economic impact of care for comorbidities associated with obesity could amount to $2158 million. CONCLUSIONS: Obesity and overweight conditions are related to higher mortality and disability than previously estimated; effective interventions aimed at prevention and treatment will have a high impact on quality of life.

Exposure to organophosphate flame retardant chemicals in the U.S. general population: Data from the 2013-2014 National Health and Nutrition Examination Survey.

BACKGROUND: Use of organophosphate flame retardants (OPFRs) including tris(1,3-dichloro-2-propyl) phosphate, triphenyl phosphate, tris(1-chloro-2-propyl) phosphate, and tris-2-chloroethyl phosphate, in consumer products is on the rise because of the recent phase out of polybrominated diphenyl ether (PBDE) flame retardants. Some of these chemicals are also used as plasticizers or lubricants in many consumer products. OBJECTIVES: To assess human exposure to these chlorinated and non-chlorinated organophosphates, and non-PBDE brominated chemicals in a representative sample of the U.S. general population 6years and older from the 2013-2014 National Health and Nutrition Examination Survey (NHANES). METHODS: We used solid-phase extraction coupled to isotope dilution high-performance liquid chromatography-tandem mass spectrometry after enzymatic hydrolysis of conjugates to analyze 2666 NHANES urine samples for nine biomarkers: diphenyl phosphate (DPHP), bis(1,3-dichloro-2-propyl) phosphate (BDCIPP), bis-(1-chloro-2-propyl) phosphate (BCIPP), bis-2-chloroethyl phosphate (BCEP), di-n-butyl phosphate (DNBP), di-p-cresylphosphate (DpCP), di-o-cresylphosphate (DoCP), dibenzyl phosphate (DBzP), and 2,3,4,5-tetrabromobenzoic acid (TBBA). We calculated the geometric mean (GM) and distribution percentiles for the urinary concentrations (both in micrograms per liter [µg/L] and in micrograms per gram of creatinine). We only calculated GMs for analytes with an overall weighted frequency of detection >60%. For those analytes, we also a) determined weighted Pearson correlations among the log10-transformed concentrations, and b) used regression models to evaluate associations of various demographic parameters with urinary concentrations of these biomarkers. RESULTS: We detected BDCIPP and DPHP in approximately 92% of study participants, BCEP in 89%, DNBP in 81%, and BCIPP in 61%. By contrast, we detected the other biomarkers much less frequently: DpCP (13%), DoCP (0.1%), TBBA (5%), and did not detect DBzP in any of the participants. Concentration ranges were highest for DPHP (<0.16-193µg/L), BDCIPP (<0.11-169µg/L), and BCEP (<0.08-110µg/L). Regardless of race/ethnicity, 6-11year old children had significantly higher BCEP adjusted GMs than other age groups. Females had significantly higher DPHP and BDCIPP adjusted GM than males, and were more likely than males to have DPHP concentrations above the 95th percentile (odds ratio=3.61; 95% confidence interval, 2.01-6.48). CONCLUSIONS: Our results confirm findings from previous studies suggesting human exposure to OPFRs, and demonstrate, for the first time, widespread exposure to several OPFRs among a representative sample of the U.S. general population 6years of age and older. The observed differences in concentrations of certain OPFRs biomarkers by race/ethnicity, in children compared to other age groups, and in females compared to males may reflect differences in lifestyle and exposure patterns. These NHANES data can be used to stablish a nationally representative baseline of exposures to OPFRs and when combined with future 2-year survey data, to evaluate exposure trends.

Systematic pan-cancer analysis of somatic allele frequency.

Imbalanced expression of somatic alleles in cancer can suggest functional and selective features, and can therefore indicate possible driving potential of the underlying genetic variants. To explore the correlation between allele frequency of somatic variants and total gene expression of their harboring gene, we used the unique data set of matched tumor and normal RNA and DNA sequencing data of 5523 distinct single nucleotide variants in 381 individuals across 10 cancer types obtained from The Cancer Genome Atlas (TCGA). We analyzed the allele frequency in the context of the variant and gene functional features and linked it with changes in the total gene expression. We documented higher allele frequency of somatic variants in cancer-implicated genes (Cancer Gene Census, CGC). Furthermore, somatic alleles bearing premature terminating variants (PTVs), when positioned in CGC genes, appeared to be less frequently degraded via nonsense-mediated mRNA decay, indicating possible favoring of truncated proteins by the tumor transcriptome. Among the genes with multiple PTVs with high allele frequency, ARID1, TP53 and NSD1 were known key cancer genes. All together, our analyses suggest that high allele frequency of tumor somatic variants can indicate driving functionality and can serve to identify potential cancer-implicated genes.

Overexpressed somatic alleles are enriched in functional elements in Breast Cancer.

Asymmetric allele content in the transcriptome can be indicative of functional and selective features of the underlying genetic variants. Yet, imbalanced alleles, especially from diploid genome regions, are poorly explored in cancer. Here we systematically quantify and integrate the variant allele fraction from corresponding RNA and DNA sequence data from patients with breast cancer acquired through The Cancer Genome Atlas (TCGA). We test for correlation between allele prevalence and functionality in known cancer-implicated genes from the Cancer Gene Census (CGC). We document significant allele-preferential expression of functional variants in CGC genes and across the entire dataset. Notably, we find frequent allele-specific overexpression of variants in tumor-suppressor genes. We also report a list of over-expressed variants from non-CGC genes. Overall, our analysis presents an integrated set of features of somatic allele expression and points to the vast information content of the asymmetric alleles in the cancer transcriptome.