14-3-3τ Regulates Beclin 1 and Is Required for Autophagy

Beclin 1 plays an essential role in autophagy; however, the regulation of Beclin 1 expression remains largely unexplored. An earlier ChIP-on-chip study suggested Beclin 1 could be an E2F target. Previously, we also reported that 14-3-3tau regulates E2F1 stability, and is required for the expression of several E2F1 target genes. 14-3-3 proteins mediate many cellular signaling processes, but its role in autophagy has not been investigated. We hypothesize that 14-3-3tau could regulate Beclin 1 expression through E2F1 and thus regulate autophagy.Using the RNAi technique we demonstrate a novel role for one of 14-3-3 isoforms, 14-3-3tau, in the regulation of Beclin 1 expression and autophagy. Depletion of 14-3-3tau inhibits the expression of Beclin 1 in many different cell lines; whereas, upregulation of 14-3-3tau induces Beclin 1. The regulation is physiologically relevant as an extracellular matrix protein tenascin-C, a known 14-3-3tau inducer, can induce Beclin 1 through 14-3-3tau. Moreover, rapamycin-induced, serum free-induced and amino acid starvation-induced autophagy depends on 14-3-3tau. We also show the expression of Beclin 1 depends on E2F, and E2F can transactivate the Beclin 1 promoter in a promoter reporter assay. Upregulation of Beclin 1 by 14-3-3tau requires E2F1. Depletion of E2F1, like 14-3-3tau, also inhibits autophagy.Taken together, this study uncovers a role for 14-3-3tau in Beclin 1 and autophagy regulation probably through regulation of E2F1

Medication adherence, its associated factors and implication on glycaemic control in patients with type 2 diabetes mellitus: A cross-sectional study in a Malaysian primary care clinic

Introduction: Medication adherence and metabolic control remain suboptimal among patients with diabetes mellitus in Malaysia despite the clear benefits of reduced vascular complications and mortality risk. This study examined the factors associated with medication adherence and glycaemic control in patients with type 2 diabetes mellitus in a primary care clinic. Methods: This cross-sectional study was conducted in a public health clinic in Pagoh, Johor, among 386 patients recruited via systematic random sampling. Data were obtained using a validated 7-item structured questionnaire, glycated haemoglobin (HbA1c) test and medical record review. Logistic regression analysis was performed to determine the factors associated with medication adherence. Results: The mean patient age was 60.04±10.75 years, and the mean HbA1c level was 8.3±2.0%. Approximately 60.3% of the participants were adherent to their medication, and an increasing age was significantly associated with medication nonadherence (adjusted odds ratio [OR]: 0.959; confidence interval [CI]: 0.934–0.985). Medication adherence (adjusted OR: 2.688; CI: 1.534–4.708) and use of combined oral medications (adjusted OR: 5.604; CI: 3.078–10.203), combined oral medications with insulin (adjusted OR: 23.466; CI: 8.208–67.085) and insulin only (adjusted OR: 6.528; CI: 1.876–22.717) were associated with good glycaemic control. Older age (adjusted OR: 0.954; CI: 0.923–0.986) and Malay ethnicity (adjusted OR: 0.284; CI: 0.101–0.794) were associated with poor glycaemic control. Conclusion: Suboptimal medication adherence and glycaemic control are prevalent in primary care settings, especially among elderly patients. Counselling should be targeted to patients and their caretakers to improve medication adherence and optimise metabolic control

A pan-cancer proteomic perspective on The Cancer Genome Atlas.

Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyse 3,467 patient samples from 11 TCGA 'Pan-Cancer' diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome

A Pan-cancer analysis reveals high-frequency genetic alterations in mediators of signaling by the tgf-β superfamily

We present an integromic analysis of gene alterations that modulate transforming growth factor β (TGF-β)-Smad-mediated signaling in 9,125 tumor samples across 33 cancer types in The Cancer Genome Atlas (TCGA). Focusing on genes that encode mediators and regulators of TGF-β signaling, we found at least one genomic alteration (mutation, homozygous deletion, or amplification) in 39% of samples, with highest frequencies in gastrointestinal cancers. We identified mutation hotspots in genes that encode TGF-β ligands (BMP5), receptors (TGFBR2, AVCR2A, and BMPR2), and Smads (SMAD2 and SMAD4). Alterations in the TGF-β superfamily correlated positively with expression of metastasis-associated genes and with decreased survival. Correlation analyses showed the contributions of mutation, amplification, deletion, DNA methylation, and miRNA expression to transcriptional activity of TGF-β signaling in each cancer type. This study provides a broad molecular perspective relevant for future functional and therapeutic studies of the diverse cancer pathways mediated by the TGF-β superfamily

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Molecular Characterization of Uterine Carcinosarcoma

SummaryWe performed genomic, epigenomic, transcriptomic, and proteomic characterizations of uterine carcinosarcomas (UCSs). Cohort samples had extensive copy-number alterations and highly recurrent somatic mutations. Frequent mutations were found in TP53, PTEN, PIK3CA, PPP2R1A, FBXW7, and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong epithelial-to-mesenchymal transition (EMT) gene signature in a subset of cases that was attributable to epigenetic alterations at microRNA promoters. The range of EMT scores in UCS was the largest among all tumor types studied via The Cancer Genome Atlas. UCSs shared proteomic features with gynecologic carcinomas and sarcomas with intermediate EMT features. Multiple somatic mutations and copy-number alterations in genes that are therapeutic targets were identified