scholarly journals Accurate diagnosis of prostate cancer using logistic regression

Open Medicine ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 459-463
Author(s):  
Arash Hooshmand
Keyword(s):  
Prostate Cancer ◽  
Logistic Regression ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data ◽  
Cancer Genome Atlas ◽  
High Level

Abstract A new logistic regression-based method to distinguish between cancerous and noncancerous RNA genomic data is developed and tested with 100% precision on 595 healthy and cancerous prostate samples. A logistic regression system is developed and trained using whole-exome sequencing data at a high-level, i.e., normalized quantification of RNAs obtained from 495 prostate cancer samples from The Cancer Genome Atlas and 100 healthy samples from the Genotype-Tissue Expression project. We could show that both sensitivity and specificity of the method in the classification of cancerous and noncancerous cells are perfectly 100%.

scholarly journals Interfocal heterogeneity challenges the clinical usefulness of molecular classification of primary prostate cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kristina Totland Carm ◽  
Andreas M. Hoff ◽  
Anne Cathrine Bakken ◽  
Ulrika Axcrona ◽  
Karol Axcrona ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Classification ◽  
Primary Diagnosis ◽  
The Cancer Genome Atlas ◽  
Clinical Usefulness ◽  
Whole Exome ◽  
Primary Prostate Cancer ◽  
Cancer Genome Atlas ◽  
Prostate Cancers

Abstract Prostate cancer is a highly heterogeneous disease and typically multiple distinct cancer foci are present at primary diagnosis. Molecular classification of prostate cancer can potentially aid the precision of diagnosis and treatment. A promising genomic classifier was published by The Cancer Genome Atlas (TCGA), successfully classifying 74% of primary prostate cancers into seven groups based on one cancer sample per patient. Here, we explore the clinical usefulness of this classification by testing the classifier’s performance in a multifocal context. We analyzed 106 cancer samples from 85 distinct cancer foci within 39 patients. By somatic mutation data from whole-exome sequencing and targeted qualitative and quantitative gene expression assays, 31% of the patients were uniquely classified into one of the seven TCGA classes. Further, different samples from the same focus had conflicting classification in 12% of the foci. In conclusion, the level of both intra- and interfocal heterogeneity is extensive and must be taken into consideration in the development of clinically useful molecular classification of primary prostate cancer.

scholarly journals Bisphenol S Promotes the Progression of Prostate Cancer by Regulating the Expression of COL1A1 and COL1A2.

2021 ◽  
Author(s):  
Kai Fang ◽  
Yang Li ◽  
Yuqing Zhang ◽  
Shengjie Liang ◽  
Simin Li ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Cell Counting ◽  
Lncap Cells ◽  
Bisphenol S ◽  
Treatment And Prevention ◽  
Prostate Cells ◽  
Cancer Genome Atlas

Abstract In recent decades, Bisphenol S (BPS), which have been considered as alternatives for Bisphenol A (BPA), have become widely used in personal care products, paper products and food. Clarifying the relationship between bisphenol and tumors is of great significance for the treatment and prevention of diseases. In this work, we discovered a new method to predict the correlation between bisphenol interactive genes and tumors. The transcriptome profile and interactive genes of bisphenol were obtained from the Cancer Genome Atlas and Genotype-Tissue Expression, Comparative Toxicology Genomics and PharmMapper database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that interactive genes were mainly enriched in prostate cancer. Gene targetd prediction and gene set variation analysis proved that bisphenol exert potential effects on prostate cancer. The operating characteristic curves and survival analysis showed that role of COL1A1 and COL1A2 in predicting the prognosis of prostate cancer. Cell counting kit-8 assay demonstrated that the cells with BPS-treated could remarkably promote the cell proliferation ability in both PC-3 and LNCap cells. Wound healing assay and the transwell assay demonstrated that the cells with BPS-treated could significantly promote the cell invasion capacity of prostate cells. Two key genes, COL1A1 and COL1A2, were significantly upregulated with BPS-treated in the PC-3 and LNCap cells.

scholarly journals CloneSig can jointly infer intra-tumor heterogeneity and mutational signature activity in bulk tumor sequencing data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Judith Abécassis ◽  
Fabien Reyal ◽  
Jean-Philippe Vert
Keyword(s):  
Tumor Heterogeneity ◽  
Cancer Genomics ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Cancer Dataset ◽  
Whole Exome Sequencing Data ◽  
Cancer Genome Atlas ◽  
Pan Cancer ◽  
Mutational Processes

AbstractSystematic DNA sequencing of cancer samples has highlighted the importance of two aspects of cancer genomics: intra-tumor heterogeneity (ITH) and mutational processes. These two aspects may not always be independent, as different mutational processes could be involved in different stages or regions of the tumor, but existing computational approaches to study them largely ignore this potential dependency. Here, we present CloneSig, a computational method to jointly infer ITH and mutational processes in a tumor from bulk-sequencing data. Extensive simulations show that CloneSig outperforms current methods for ITH inference and detection of mutational processes when the distribution of mutational signatures changes between clones. Applied to a large cohort of 8,951 tumors with whole-exome sequencing data from The Cancer Genome Atlas, and on a pan-cancer dataset of 2,632 whole-genome sequencing tumor samples from the Pan-Cancer Analysis of Whole Genomes initiative, CloneSig obtains results overall coherent with previous studies.

scholarly journals Alternative polyadenylation drives oncogenic gene expression in pancreatic ductal adenocarcinoma

2019 ◽  
Author(s):  
Swati Venkat ◽  
Arwen A. Tisdale ◽  
Johann R. Schwarz ◽  
Abdulrahman A. Alahmari ◽  
H. Carlo Maurer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alternative Polyadenylation ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Ductal Adenocarcinoma ◽  
Tumor Type ◽  
Mirna Regulation ◽  
Sequencing Data ◽  
Altered Expression ◽  
Cancer Genome Atlas

ABSTRACTAlternative polyadenylation (APA) is a gene regulatory process that dictates mRNA 3’-UTR length, resulting in changes in mRNA stability and localization. APA is frequently disrupted in cancer and promotes tumorigenesis through altered expression of oncogenes and tumor suppressors. Pan-cancer analyses have revealed common APA events across the tumor landscape; however, little is known about tumor type-specific alterations that may uncover novel events and vulnerabilities. Here we integrate RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Atlas (TCGA) to comprehensively analyze APA events in 148 pancreatic ductal adenocarcinomas (PDAs). We report widespread, recurrent and functionally relevant 3’-UTR alterations associated with gene expression changes of known and newly identified PDA growth-promoting genes and experimentally validate the effects of these APA events on expression. We find enrichment for APA events in genes associated with known PDA pathways, loss of tumor-suppressive miRNA binding sites, and increased heterogeneity in 3’-UTR forms of metabolic genes. Survival analyses reveal a subset of 3’-UTR alterations that independently characterize a poor prognostic cohort among PDA patients. Finally, we identify and validate the casein kinase CK1α as an APA-regulated therapeutic target in PDA. Knockdown or pharmacological inhibition of CK1α attenuates PDA cell proliferation and clonogenic growth. Our single-cancer analysis reveals APA as an underappreciated driver of pro-tumorigenic gene expression in PDA via the loss of miRNA regulation.

scholarly journals Enabling cross-study analysis of RNA-Sequencing data

2017 ◽  
Author(s):  
Qingguo Wang ◽  
Joshua Armenia ◽  
Chao Zhang ◽  
Alexander V. Penson ◽  
Ed Reznik ◽  
...  
Keyword(s):  
Large Scale ◽  
Tissue Expression ◽  
Underlying Disease ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Sequencing Data ◽  
Whole Transcriptome Sequencing ◽  
Cancer Genome Atlas ◽  
Next Generation Sequencing Ngs ◽  
Different Sources

AbstractDriven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data. While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources poses a great challenge, due to differences in sample and data processing. Here, we present a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment and gene expression quantification as well as batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA) and have successfully corrected for study-specific biases, enabling comparative analysis across studies. The normalized data are available for download via GitHub (at https://github.com/mskcc/RNAseqDB).

Integrated genomic profiling and modelling for risk stratification in patients with advanced oesophagogastric adenocarcinoma

Gut ◽  
2020 ◽  
pp. gutjnl-2020-322707
Author(s):  
Dapeng Hao ◽  
Siyuan He ◽  
Kazuto Harada ◽  
Melissa Pool Pizzi ◽  
Yang Lu ◽  
...  
Keyword(s):  
Prognostic Model ◽  
Integrated Model ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Molecular Features ◽  
Whole Exome ◽  
Molecular Determinants ◽  
Cancer Genome Atlas ◽  
High Level ◽  
Druggable Targets

ObjectivePrognosis of patients with advanced oesophagogastric adenocarcinoma (mEGAC) is poor and molecular determinants of shorter or longer overall survivors are lacking. Our objective was to identify molecular features and develop a prognostic model by profiling the genomic features of patients with mEGAC with widely varying outcomes.DesignWe profiled 40 untreated mEGACs (20 shorter survivors <13 months and 20 longer survivors >36 months) with whole-exome sequencing (WES) and RNA sequencing and performed an integrated analysis of exome, transcriptome, immune profile and pathological phenotypes to identify the molecular determinants, developing an integrated model for prognosis and comparison with The Cancer Genome Atlas (TCGA) cohorts.ResultsKMT2C alterations were exclusively observed in shorter survivors together with high level of intratumour heterogeneity and complex clonal architectures, whereas the APOBEC mutational signatures were significantly enriched in longer survivors. Notably, the loss of heterozygosity in chromosome 4 (Chr4) was associated with shorter survival and ‘cold’ immune phenotype characterised by decreased B, CD8, natural killer cells and interferon-gamma responses. Unsupervised transcriptomic clustering revealed a shorter survivor subtype with distinct expression features (eg, upregulated druggable targets JAK2, MAP3K13 and MECOM). An integrated model was then built based on clinical variables and the identified molecular determinants, which significantly segregated shorter and longer survivors. All the above features and the integrated model have been validated independently in multiple TCGA cohorts.ConclusionThis study discovered novel molecular features prognosticating overall survival in patients with mEGAC and identified potential novel targets in shorter survivors.

scholarly journals Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthew H. Bailey ◽  
◽  
William U. Meyerson ◽  
Lewis Jonathan Dursi ◽  
Liang-Bo Wang ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Gc Content ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Exome ◽  
Cancer Genome Atlas

AbstractThe Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

scholarly journals Automatic Classification of Prostate Cancer Gleason Scores from Digitized Whole Slide Tissue Biopsies

2018 ◽  
Author(s):  
Hongming Xu ◽  
Sunho Park ◽  
Tae Hyun Hwang
Keyword(s):  
Prostate Cancer ◽  
Texture Features ◽  
The Cancer Genome Atlas ◽  
Support Vector ◽  
Pixel Intensity ◽  
Gleason Grading ◽  
Slide Image ◽  
Cancer Genome Atlas ◽  
Automatic Technique

AbstractHistological Gleason grading of tumor patterns is one of the most powerful prognostic predictors in prostate cancer. However, manual analysis and grading performed by pathologists are typically subjective and time-consuming. In this paper, we propose an automatic technique for Gleason grading of prostate cancer from H&E stained whole slide biopsy images using a set of novel completed and statistical local bi-nary pattern (CSLBP) descriptors. First the technique divides the whole slide image into a set of small image tiles, where salient tumor tiles with high nuclei densities are selected for analysis. The CSLBP texture features that encode pixel intensity variations from circularly surrounding neighborhoods are then extracted from salient image tiles to characterize different Gleason patterns. Finally, CSLBP texture features computed from all tiles are integrated and utilized by the multi-class support vector machine (SVM) that assigns patient biopsy with different Gleason score of 6, 7 or ≥8. Experiments have been performed on 312 different patient cases selected from the cancer genome atlas (TCGA) and have achieved more than 79% classification accuracies, which is superior to state-of-the-art textural descriptors for prostate cancer Gleason grading.

scholarly journals The contribution of CACNA1A, ATP1A2 and SCN1A mutations in hemiplegic migraine: A clinical and genetic study in Finnish migraine families

Cephalalgia ◽  
2018 ◽  
Vol 38 (12) ◽  
pp. 1849-1863 ◽  
Author(s):  
Marjo Eveliina Hiekkala ◽  
Pietari Vuola ◽  
Ville Artto ◽  
Paavo Häppölä ◽  
Elisa Häppölä ◽  
...  
Keyword(s):  
Migraine With Aura ◽  
Genetic Factors ◽  
Severe Headache ◽  
Headache Disorders ◽  
Sequencing Data ◽  
Hemiplegic Migraine ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

Objective To study the position of hemiplegic migraine in the clinical spectrum of migraine with aura and to reveal the importance of CACNA1A, ATP1A2 and SCN1A in the development of hemiplegic migraine in Finnish migraine families. Methods The International Classification of Headache Disorders 3rd edition criteria were used to determine clinical characteristics and occurrence of hemiplegic migraine, based on detailed questionnaires, in a Finnish migraine family collection consisting of 9087 subjects. Involvement of CACNA1A, ATP1A2 and SCN1A was studied using whole exome sequencing data from 293 patients with hemiplegic migraine. Results Overall, hemiplegic migraine patients reported clinically more severe headache and aura episodes than non-hemiplegic migraine with aura patients. We identified two mutations, c.1816G>A (p.Ala606Thr) and c.1148G>A (p.Arg383His), in ATP1A2 and one mutation, c.1994C>T (p.Thr665Met) in CACNA1A. Conclusions The results highlight hemiplegic migraine as a clinically and genetically heterogeneous disease. Hemiplegic migraine patients do not form a clearly separate group with distinct symptoms, but rather have an extreme phenotype in the migraine with aura continuum. We have shown that mutations in CACNA1A, ATP1A2 and SCN1A are not the major cause of the disease in Finnish hemiplegic migraine patients, suggesting that there are additional genetic factors contributing to the phenotype.

scholarly journals Upgrading the Repertoire of miRNAs in Gastric Adenocarcinoma to Provide a New Resource for Biomarker Discovery

2019 ◽  
Vol 20 (22) ◽  
pp. 5697 ◽  
Author(s):  
Michelle E. Pewarchuk ◽  
Mateus C. Barros-Filho ◽  
Brenda C. Minatel ◽  
David E. Cohn ◽  
Florian Guisier ◽  
...  
Keyword(s):  
Gastric Adenocarcinoma ◽  
Biomarker Discovery ◽  
The Cancer Genome Atlas ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Specific Expression ◽  
Novel Mirna ◽  
Cancer Genome Atlas ◽  
Context Specific ◽  
Independent Cohort

Recent studies have uncovered microRNAs (miRNAs) that have been overlooked in early genomic explorations, which show remarkable tissue- and context-specific expression. Here, we aim to identify and characterize previously unannotated miRNAs expressed in gastric adenocarcinoma (GA). Raw small RNA-sequencing data were analyzed using the miRMaster platform to predict and quantify previously unannotated miRNAs. A discovery cohort of 475 gastric samples (434 GA and 41 adjacent nonmalignant samples), collected by The Cancer Genome Atlas (TCGA), were evaluated. Candidate miRNAs were similarly assessed in an independent cohort of 25 gastric samples. We discovered 170 previously unannotated miRNA candidates expressed in gastric tissues. The expression of these novel miRNAs was highly specific to the gastric samples, 143 of which were significantly deregulated between tumor and nonmalignant contexts (p-adjusted < 0.05; fold change > 1.5). Multivariate survival analyses showed that the combined expression of one previously annotated miRNA and two novel miRNA candidates was significantly predictive of patient outcome. Further, the expression of these three miRNAs was able to stratify patients into three distinct prognostic groups (p = 0.00003). These novel miRNAs were also present in the independent cohort (43 sequences detected in both cohorts). Our findings uncover novel miRNA transcripts in gastric tissues that may have implications in the biology and management of gastric adenocarcinoma.

Sign in / Sign up

Export Citation Format

Share Document