Tumor-educated platelet RNA for the detection and (pseudo)progression monitoring of glioblastoma
Ontology highlight
ABSTRACT: We report RNA-sequencing data of 805 blood platelet samples, including 240 tumor-educated platelet (TEP) samples collected from patients with glioblastoma and 126 TEP samples collected from patients with brain metastases. In addition, we report RNA-sequencing data of blood platelets isolated from 353 asymptomatic controls and 86 individuals with multiple sclerosis. This dataset highlights the ability of TEP RNA-based 'liquid biopsy' diagnostics for the detection and (pseudo)progression monitoring of glioblastoma.
Project description:We report RNA-sequencing data of 283 blood platelet samples, including 228 tumor-educated platelet (TEP) samples collected from patients with six different malignant tumors (non-small cell lung cancer, colorectal cancer, pancreatic cancer, glioblastoma, breast cancer and hepatobiliary carcinomas). In addition, we report RNA-sequencing data of blood platelets isolated from 55 healthy individuals. This dataset highlights the ability of TEP RNA-based 'liquid biopsies' in patients with several types with cancer, including the ability for pan-cancer, multiclass cancer and companion diagnostics.
Project description:We report RNA-sequencing data of 779 blood platelet samples, including 402 tumor-educated platelet (TEP) samples collected from patients with non-small cell lung cancer (NSCLC). In addition, we report RNA-sequencing data of blood platelets isolated from 377 individuals without reported cancer, but not excluding individuals with inflammatory conditions. This dataset highlights the ability of TEP RNA-based 'liquid biopsy' diagnostics in patients with NSCLC.
Project description:We report RNA-sequencing data of 283 blood platelet samples, including 228 tumor-educated platelet (TEP) samples collected from patients with six different malignant tumors (non-small cell lung cancer, colorectal cancer, pancreatic cancer, glioblastoma, breast cancer and hepatobiliary carcinomas). In addition, we report RNA-sequencing data of blood platelets isolated from 55 healthy individuals. This dataset highlights the ability of TEP RNA-based 'liquid biopsies' in patients with several types with cancer, including the ability for pan-cancer, multiclass cancer and companion diagnostics. Blood platelets were isolated from whole blood in purple-cap BD Vacutainers containing EDTA anti-coagulant by standard centrifugation. Total RNA was extracted from the platelet pellet, subjected to cDNA synthesis and SMARTer amplification, fragmented by Covaris shearing, and prepared for sequencing using the Truseq Nano DNA Sample Preparation Kit. Subsequently, pooled sample libraries were sequenced on the Illumina Hiseq 2500 platform. All steps were quality-controlled using Bioanalyzer 2100 with RNA 6000 Picochip, DNA 7500 and DNA High Sensitivity chips measurements. For further downstream analyses, reads were quality-controlled using Trimmomatic, mapped to the human reference genome using STAR, and intron-spanning reads were summarized using HTseq. The processed data includes 285 samples (columns) and 57736 ensemble gene ids (rows). The supplementary data file (TEP_data_matrix.txt) contains the intron-spanning read counts, after data summarization by HTseq.
Project description:Tumor-educated platelets (TEPs) are a potential method of liquid biopsy for the diagnosis and monitoring of cancer. However, the mechanism underlying tumor education of platelets is not known, and transcripts associated with TEPs are often not tumor-associated transcripts. We demonstrate that direct tumor transfer of transcripts to circulating platelets is an unlikely source of the TEP signal. We use CDSeq, a latent Dirichlet allocation algorithm, to deconvolute the TEP signal in blood samples from patients with glioblastoma. We demonstrate that a significant proportion of transcripts in the platelet transcriptome are derived from non-platelet cells, and the use of this algorithm allows the removal of contaminant transcripts. Furthermore, we used the results of this algorithm to demonstrate that TEPs represent a subset of more activated platelets, which also contain transcripts normally associated with non-platelet inflammatory cells, suggesting that these inflammatory cells, possibly in the tumor microenvironment, transfer transcripts to platelets that are then found in circulation. Our analysis suggests a useful and efficient method of processing TEP transcriptomic data to enable the isolation of a unique TEP signal associated with specific tumors.
Project description:Tumor-educated platelets (TEPs) are a potential method of liquid biopsy for the diagnosis and monitoring of cancer. However, the mechanism underlying tumor education of platelets is not known, and transcripts associated with TEPs are often not tumor-associated transcripts. We demonstrate that direct tumor transfer of transcripts to circulating platelets is an unlikely source of the TEP signal. We use CDSeq, a latent Dirichlet allocation algorithm, to deconvolute the TEP signal in blood samples from patients with glioblastoma. We demonstrate that a significant proportion of transcripts in the platelet transcriptome are derived from non-platelet cells, and the use of this algorithm allows the removal of contaminant transcripts. Furthermore, we used the results of this algorithm to demonstrate that TEPs represent a subset of more activated platelets, which also contain transcripts normally associated with non-platelet inflammatory cells, suggesting that these inflammatory cells, possibly in the tumor microenvironment, transfer transcripts to platelets that are then found in circulation. Our analysis suggests a useful and efficient method of processing TEP transcriptomic data to enable the isolation of a unique TEP signal associated with specific tumors.
Project description:We report RNA-seq data of 766 blood platelet samples, including 399 Non-Small Cell Lung Cancer (NSCLC) patients from different stages (I-IV) and 367 asymptomatic individuals (Controls). Our data explains how tumor-educated platelet (TEP)-derived spliced RNA can serve as a biomarker for minimally-invasive clinical blood tests on assisting the detection and management of lung cancer patients.
Project description:We report RNA-sequencing data of 80 tumor-educated blood platelet (TEP) samples isolated from 39 patients with lower-grade glioma (LGG) and 41 healthy donors (HD). This dataset can be employed as input for the thromboSeq source code (available via GitHub: https://github.com/MyronBest/) to reproduce the thromboSeq drylab pipeline.
Project description:We report RNA-sequencing data of 2351 blood platelet samples, including 1628 patients with stage I-IV cancer (of which 18 different tumor types), 390 asymptomatic controls and 333 symptomatic controls. This dataset highlights the ability of TEP RNA-based 'liquid biopsy' diagnostics for the detection and localization of early- and late-stage cancers.