The Ubiquitin Peptidase UCHL1 Induces G0/G1 Cell Cycle Arrest and Apoptosis Through Stabilizing p53 and Is Frequently Silenced in Breast Cancer

Background: Breast cancer (BrCa) is a complex disease driven by aberrant gene alterations and environmental factors. Recent studies reveal that abnormal epigenetic gene regulation also plays an important role in its pathogenesis. Ubiquitin carboxyl- terminal esterase L1 (UCHL1) is a tumor suppressor silenced by promoter methylation in multiple cancers, but its role and alterations in breast tumorigenesis remain unclear. Methodology/Principal Findings: We found that UCHL1 was frequently downregulated or silenced in breast cancer cell lines and tumor tissues, but readily expressed in normal breast tissues and mammary epithelial cells. Promoter methylation of UCHL1 was detected in 9 of 10 breast cancer cell lines (90%) and 53 of 66 (80%) primary tumors, but rarely in normal breast tissues, which was statistically correlated with advanced clinical stage and progesterone receptor status. Pharmacologic demethylation reactivated UCHL1 expression along with concomitant promoter demethylation. Ectopic expression of UCHL1 significantly suppressed the colony formation and proliferation of breast tumor cells, through inducing G0/G1 cell cycle arrest and apoptosis. Subcellular localization study showed that UCHL1 increased cytoplasmic abundance of p53. We further found that UCHL1 induced p53 accumulation and reduced MDM2 protein level, and subsequently upregulated the expression of p21, as well as cleavage of caspase3 and PARP, but not in catalytic mutant UCHL1 C90Sexpressed cells

Single Nucleotide Polymorphisms in the Wnt and BMP Pathways and Colorectal Cancer Risk in a Spanish Cohort

BACKGROUND: Colorectal cancer (CRC) is considered a complex disease, and thus the majority of the genetic susceptibility is thought to lie in the form of low-penetrance variants following a polygenic model of inheritance. Candidate-gene studies have so far been one of the basic approaches taken to identify these susceptibility variants. The consistent involvement of some signaling routes in carcinogenesis provided support for pathway-based studies as a natural strategy to select genes that could potentially harbour new susceptibility loci. METHODOLOGY/PRINCIPAL FINDINGS: We selected two main carcinogenesis-related pathways: Wnt and BMP, in order to screen the implicated genes for new risk variants. We then conducted a case-control association study in 933 CRC cases and 969 controls based on coding and regulatory SNPs. We also included rs4444235 and rs9929218, which did not fulfill our selection criteria but belonged to two genes in the BMP pathway and had consistently been linked to CRC in previous studies. Neither allelic, nor genotypic or haplotypic analyses showed any signs of association between the 37 screened variants and CRC risk. Adjustments for sex and age, and stratified analysis between sporadic and control groups did not yield any positive results either. CONCLUSIONS/SIGNIFICANCE: Despite the relevance of both pathways in the pathogenesis of the disease, and the fact that this is indeed the first study that considers these pathways as a candidate-gene selection approach, our study does not present any evidence of the presence of low-penetrance variants for the selected markers in any of the considered genes in our cohort

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

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

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

Artificial intelligence for diagnosis and Gleason grading of prostate cancer: The PANDA challenge

Through a community-driven competition, the PANDA challenge provides a curated diverse dataset and a catalog of models for prostate cancer pathology, and represents a blueprint for evaluating AI algorithms in digital pathology. Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge-the largest histopathology competition to date, joined by 1,290 developers-to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted kappa, 95% confidence interval (CI), 0.840-0.884) and 0.868 (95% CI, 0.835-0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.KWF Kankerbestrijding ; Netherlands Organization for Scientific Research (NWO) ; Swedish Research Council European Commission ; Swedish Cancer Society ; Swedish eScience Research Center ; Ake Wiberg Foundation ; Prostatacancerforbundet ; Academy of Finland ; Cancer Foundation Finland ; Google Incorporated ; MICCAI board challenge working group ; Verily Life Sciences ; EIT Health ; Karolinska Institutet ; MICCAI 2020 satellite event team ; ERAPerMe

Primary brain calcification: an international study reporting novel variants and associated phenotypes.

Primary familial brain calcification (PFBC) is a rare cerebral microvascular calcifying disorder with a wide spectrum of motor, cognitive, and neuropsychiatric symptoms. It is typically inherited as an autosomal-dominant trait with four causative genes identified so far: SLC20A2, PDGFRB, PDGFB, and XPR1. Our study aimed at screening the coding regions of these genes in a series of 177 unrelated probands that fulfilled the diagnostic criteria for primary brain calcification regardless of their family history. Sequence variants were classified as pathogenic, likely pathogenic, or of uncertain significance (VUS), based on the ACMG-AMP recommendations. We identified 45 probands (25.4%) carrying either pathogenic or likely pathogenic variants (n = 34, 19.2%) or VUS (n = 11, 6.2%). SLC20A2 provided the highest contribution (16.9%), followed by XPR1 and PDGFB (3.4% each), and PDGFRB (1.7%). A total of 81.5% of carriers were symptomatic and the most recurrent symptoms were parkinsonism, cognitive impairment, and psychiatric disturbances (52.3%, 40.9%, and 38.6% of symptomatic individuals, respectively), with a wide range of age at onset (from childhood to 81 years). While the pathogenic and likely pathogenic variants identified in this study can be used for genetic counseling, the VUS will require additional evidence, such as recurrence in unrelated patients, in order to be classified as pathogenic