Integrated case-control and somatic-germline interaction analyses of soft-tissue sarcoma

2020 ◽  
pp. jmedgenet-2019-106814
Author(s):  
Fulan Hu ◽  
Yao Yu ◽  
Jiun-Sheng Chen ◽  
Hao Hu ◽  
Paul Scheet ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Soft Tissue Sarcoma ◽  
Case Control ◽  
The Cancer Genome Atlas ◽  
Pathogenic Variants ◽  
Genome Wide ◽  
Whole Exome ◽  
Rare Genetic Variation ◽  
Cancer Genome Atlas ◽  
Cross Platform

PurposeThe contribution of rare genetic variation in the development of soft-tissue sarcoma (STS) remains underexplored. To address this gap, we conducted a whole-exome case-control and somatic-germline interaction study to identify and characterise STS susceptible genes.MethodsThe study involved 219 STS cases from The Cancer Genome Atlas and 3507 controls. All cases and controls were matched genetically onEuropean ancestry based on the 1000 Genomes project. Cross-platform technological stratification was performed with XPAT and gene-based association tests with VAAST 2.ResultsNF1 exhibited the strongest genome-wide signal across the six subtypes, with p=1×10−5. We also observed nominally significant association signals for three additional genes of interest, TP53 (p=0.0025), RB1 (p=0.0281), and MSH2 (p=0.0085). BAG1, which has not previously been implicated in STS, exhibited the strongest genome-wide signal after NF1, with p=6×10−5. The association signals for NF1 and MSH2 were driven primarily by truncating variants, with ORs of 39 (95% CI: 7.1 to 220) for NF1 and 33 (95% CI: 2.4 to 460) for MSH2. In contrast, the association signals for RB1 and BAG1 were driven primarily by predicted damaging missense variants, with estimated ORs of 12 (95% CI: 2.4 to 59) for RB1 and 20 (95% CI: 1.4 to 300) for BAG1.ConclusionsOur results confirm that pathogenic variants in NF1, RB1 and TP53 confer large increases in the risk of developing multiple STS subtypes, provide support for the role of MSH2 in STS susceptibility and identify BAG1 as a novel candidate STS risk gene.

Identification of Aneuploid Circulating Tumor Cells in Soft-Tissue Sarcoma Patients: A Pilot Study

Oncology ◽  
2020 ◽  
Vol 98 (12) ◽  
pp. 893-896
Author(s):  
Andrea Napolitano ◽  
Alessandro Minelli ◽  
Daniele Santini ◽  
Giuseppe Tonini ◽  
Bruno Vincenzi
Keyword(s):  
Overall Survival ◽  
Pilot Study ◽  
Soft Tissue ◽  
Soft Tissue Sarcoma ◽  
Tumor Cells ◽  
In Silico ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
First Time ◽  
Genome Atlas

<b><i>Background:</i></b> Circulating tumor cells (CTCs) have been identified and shown to have prognostic and predictive roles in several types of carcinoma. More recently, aneuploid CTCs have become subject of a growing interest, as aneuploidy is considered a hallmark of cancer often associated with poor prognosis. Here, we aimed to identify for the first time aneuploid CTCs in soft-tissue sarcoma (STS) patients and show supportive in silico evidence on the prognostic role of aneuploidy in mesenchymal cancers. <b><i>Methods:</i></b> In our pilot study, we collected blood from 4 metastatic STS patients and 4 age- and sex-matched healthy controls. After sample processing, cells were cyto-centrifuged onto glass slides and FISH was performed using 5 probes. The in silico analysis was performed using data from The Cancer Genome Atlas cohort of STS patients, using the validated Aneuploidy Score. We divided the patients in two populations (aneuploidy-high, Ane-Hi, and aneuploidy-low, Ane-Lo) using the median value of the Aneuploidy Score as a cutoff. Kaplan-Meier curves associated with log-rank test were used to compare progression-free and overall survival between groups. GraphPad Prism 8.0 (La Jolla, CA, USA) was used for statistical analyses. <b><i>Results:</i></b> Aneuploid CTCs were identified in all 4 STS patients and in none of the controls, with a median value of 4 (range 3–6) per 7 mL of blood. Ane-Hi patients showed a significantly worse progression-free and overall survival compared to Ane-Lo patients. The same trend was maintained when analyzing the data based on the different histologies. <b><i>Conclusions:</i></b> We identified for the first time aneuploid CTCs in STS patients using fluorescence in situ hybridization in a surface marker-independent way. We also showed that the Aneuploidy Score has a prognostic value both in terms of progression-free survival and overall survival in STS patients using The Cancer Genome Atlas data, regardless of the histology.

scholarly journals Predicted CD4+ T cell infiltration levels could indicate better overall survival in sarcoma patients

2021 ◽  
Vol 49 (1) ◽  
pp. 030006052098153
Author(s):  
Qing Bi ◽  
Yang Liu ◽  
Tao Yuan ◽  
Huizhen Wang ◽  
Bin Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
T Cell ◽  
Survival Data ◽  
Tumor Infiltrating Lymphocytes ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
T Cell Infiltration ◽  
Whole Exome ◽  
Cancer Genome Atlas ◽  
Infiltrating Lymphocytes

Objective The role of tumor-infiltrating lymphocytes (TILs) has not yet been characterized in sarcomas. The aim of this bioinformatics study was to explore the effect of TILs on sarcoma survival and genome alterations. Methods Whole-exome sequencing, transcriptome sequencing, and survival data of sarcoma were obtained from The Cancer Genome Atlas. Immune infiltration scores were calculated using the Tumor Immune Estimation Resource. Potential associations between abundance of infiltrating TILs and survival or genome alterations were examined. Results Levels of CD4+ T cell infiltration were associated with overall survival of patients with pan-sarcomas, and higher CD4+ T cell infiltration levels were associated with better survival. Somatic copy number alterations, rather than mutations, were found to correlate with CD4+ T cell infiltration levels. Conclusions This data mining study indicated that CD4+ T cell infiltration levels predicted from RNA sequencing could predict sarcoma prognosis, and higher levels of CD4+ T cells infiltration indicated a better chance of survival.

scholarly journals Promoter Methylation of PRKCB, ADAMTS12, and NAALAD2 Is Specific to Prostate Cancer and Predicts Biochemical Disease Recurrence

2021 ◽  
Vol 22 (11) ◽  
pp. 6091
Author(s):  
Kristina Daniunaite ◽  
Arnas Bakavicius ◽  
Kristina Zukauskaite ◽  
Ieva Rauluseviciute ◽  
Juozas Rimantas Lazutka ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Practice ◽  
Promoter Methylation ◽  
Disease Recurrence ◽  
The Cancer Genome Atlas ◽  
Cancer Dataset ◽  
Protein Coding ◽  
Diagnosis And Prognosis ◽  
Genome Wide ◽  
Cancer Genome Atlas

The molecular diversity of prostate cancer (PCa) has been demonstrated by recent genome-wide studies, proposing a significant number of different molecular markers. However, only a few of them have been transferred into clinical practice so far. The present study aimed to identify and validate novel DNA methylation biomarkers for PCa diagnosis and prognosis. Microarray-based methylome data of well-characterized cancerous and noncancerous prostate tissue (NPT) pairs was used for the initial screening. Ten protein-coding genes were selected for validation in a set of 151 PCa, 51 NPT, as well as 17 benign prostatic hyperplasia samples. The Prostate Cancer Dataset (PRAD) of The Cancer Genome Atlas (TCGA) was utilized for independent validation of our findings. Methylation frequencies of ADAMTS12, CCDC181, FILIP1L, NAALAD2, PRKCB, and ZMIZ1 were up to 91% in our study. PCa specific methylation of ADAMTS12, CCDC181, NAALAD2, and PRKCB was demonstrated by qualitative and quantitative means (all p < 0.05). In agreement with PRAD, promoter methylation of these four genes was associated with the transcript down-regulation in the Lithuanian cohort (all p < 0.05). Methylation of ADAMTS12, NAALAD2, and PRKCB was independently predictive for biochemical disease recurrence, while NAALAD2 and PRKCB increased the prognostic power of multivariate models (all p < 0.01). The present study identified methylation of ADAMTS12, NAALAD2, and PRKCB as novel diagnostic and prognostic PCa biomarkers that might guide treatment decisions in clinical practice.

scholarly journals Transposable element expression in tumors is associated with immune infiltration and increased antigenicity

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Yu Kong ◽  
Christopher M. Rose ◽  
Ashley A. Cass ◽  
Alexander G. Williams ◽  
Martine Darwish ◽  
...  
Keyword(s):  
Dna Methylation ◽  
De Novo ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Potential Consequence ◽  
Sequencing Data ◽  
Antiviral Responses ◽  
Genome Wide ◽  
Cancer Genome Atlas ◽  
Demethylation Agent

AbstractProfound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observe increased expression of over 400 TE subfamilies, of which 262 appear to result from a proximal loss of DNA methylation. The most recurrent TEs are among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent results in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing inflammation and the display of potentially immunogenic neoantigens.

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 IsoformSwitchAnalyzeR: analysis of changes in genome-wide patterns of alternative splicing and its functional consequences

2019 ◽  
Vol 35 (21) ◽  
pp. 4469-4471 ◽  
Author(s):  
Kristoffer Vitting-Seerup ◽  
Albin Sandelin
Keyword(s):  
Alternative Splicing ◽  
The Cancer Genome Atlas ◽  
Supplementary Information ◽  
Rna Seq ◽  
Genome Wide ◽  
Functional Consequences ◽  
Cancer Genome Atlas ◽  
Health And Disease ◽  
Splicing Patterns

Abstract Summary Alternative splicing is an important mechanism involved in health and disease. Recent work highlights the importance of investigating genome-wide changes in splicing patterns and the subsequent functional consequences. Current computational methods only support such analysis on a gene-by-gene basis. Therefore, we extended IsoformSwitchAnalyzeR R library to enable analysis of genome-wide changes in specific types of alternative splicing and predicted functional consequences of the resulting isoform switches. As a case study, we analyzed RNA-seq data from The Cancer Genome Atlas and found systematic changes in alternative splicing and the consequences of the associated isoform switches. Availability and implementation Windows, Linux and Mac OS: http://bioconductor.org/packages/IsoformSwitchAnalyzeR. Supplementary information Supplementary data are available at Bioinformatics online.

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