Combinatorial blood platelets-derived circRNA and mRNA signature for early-stage lung cancer
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ABSTRACT:
PROVIDER: PRJNA937649 | ENA |
REPOSITORIES: ENA
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Project description:Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often 30 exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results 31 in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an Area Under the Curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 40 circRNA) enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.
2023-06-23 | GSE225787 | GEO
Project description:In platelets, splicing and translation occur in the absence of a nucleus. However, the integrity and stability of mRNAs derived from megakaryocyte progenitor cells remain poorly quantified on a transcriptome-wide level. As circular RNAs (circRNAs) are resistant to degradation by exonucleases, their abundance relative to linear RNAs can be used as a surrogate marker for mRNA stability in the absence of transcription. Here we show that circRNAs are enriched in human platelets 17-188 fold relative to nucleated tissues, and 14-26 fold relative to samples digested with RNAseR to selectively remove linear RNA. We compare RNAseq read depths inside and outside circRNAs to provide in silico evidence of transcript circularity, show that exons within circRNAs are enriched ~13X in platelets relative to nucleated tissues, and identify 3162 genes significantly enriched for circRNAs including some where all RNAs appear to be derived from circular molecules. We also confirm that this is a feature of other anucleate cells through transcriptome sequencing of mature erythrocytes, demonstrate that circRNAs are not enriched in megakaryocytes, and that linear RNAs decay more rapidly than circRNAs in platelet preparations. Collectively, these results suggest that circulating platelets have lost on aveage over 90% of their progenitor mRNAs, and that translation in platelets occurrs against the backdrop of a highly degraded transcriptome. Finally, we find that transcripts classified as products of reverse transcriptase template switching are both enriched in platelets and resistant to decay, countering the recent suggestion that up to 50% of rearranged RNAs are artefacts. A single rRNA depleted total RNA sample was sequenced. This together with 25 publicly available rRNA depleted total RNA samples (including 3 from platelets) were analysed using PTESFinder v 1 (http://sourceforge.net/projects/ptesfinder-v1/) to identify back-splice junctions, characteristic of circRNA transcripts. The contribution of circRNA producing exons was analysed on a gene by gene basis as follows: All circRNA transcripts identified in any sample were first pooled to define exons which can contribute to circRNA generation using custom scripts (available on request). For each sample, expression estimates (RPKMI) across all circRNA producing exons were computed for each locus using the total size of exons (in bp) and the read counts mapping to them. Similarly, total size and exonic read counts for exons for which no circRNA were detected in any sample were used to compute expression estimates (RPKME) for non-circRNA producing exons for each locus. Abundance ratios (RPKMI/RPKME and RPKMI/RPKMI+RPKME) were calculated and compared between Platelets and human tissues using Wilcoxon signed-rank test. Please note that the '25sample_info_accn_no.txt' contains the accession numbers and tissue/cell type information for 25 samples analyzed together.
2015-12-12 | E-GEOD-69192 | biostudies-arrayexpress
Project description:Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.
| S-EPMC10003255 | biostudies-literature
Project description:To determine the circRNA expression profile in early stage lung adenocarcinoma and matched non-tumor tissues, we used circRNA microArray analysis form Arraystar to examine the expression of circRNAs Lung adenocarcinoma, a form of NSCLC with high lethality at advanced stage, is becoming more popular in women, non- or never-smokers, and even young adult. However, there are no effective early diagnosis methods at present for patients to cure timely. Circular RNAs (circRNAs) as a special novel, stable, and conserved non-coding RNA in mammalian cells have been reported to be widely involved in the processes of cancer disease. Yet, it is still a puzzle which specific circRNAs are involved in the development of early stage lung adenocarcinoma. Here, tumour samples and paired adjacent normal tissues from 4 patients with early stage lung adenocarcinoma were selected for investigating the expression profile of circRNAs by using the high-throughput circRNA microarray. Bioinformatic analyses were conducted to screen those differentially expressed circRNAs. This work illustrates that clusters of circRNAs are aberrantly expressed in early stage lung adenocarcinoma, which might be able to provide potential targets for the early diagnosis of this disease and new genetic insights into lung cancer.
2019-06-26 | GSE101684 | GEO
Project description:Identify upregulated genes in platelets from patients with brain tumors. Platelets from 12 healty controls vs. 8 glioma patients where isolated from whole blood collected in purple-cap BD vacutainers containing EDTA as anti-cogulant.
2011-12-01 | E-GEOD-31095 | biostudies-arrayexpress
Project description:Identify upregulated genes in platelets from patients with brain tumors.
2011-12-01 | GSE31095 | GEO
Project description:Circulating circRNA signature in pregnancies with gestational diabetes mellitus
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Project description:We aimed to investigate the diagnostic potential of tumor educated platelets in ESCC. In this study, seventy-one ESCC patients and eighty healthy individuals were enrolled and divided into training cohort (23 patients and 27 healthy individuals) and validation cohort (48 patients and 53 healthy individuals). Next-generation RNA sequencing was performed on platelets isolated from peripheral blood of all participants and a support vector machine/leave-one-out cross validation (SVM/LOOCV) approach was used for binary classification. A diagnostic signature composed of ARID1A, GTF2H2 and PRKRIR discriminated ESCC patients from healthy individuals with 91.3% sensitivity and 85.2% specificity in the training cohort and 87.5% sensitivity and 81.1% specificity in the validation cohort. The AUC was 0.924 (95% CI, 0.845–0.956) and 0.893 (95% CI, 0.821–0.966), respectively, in the training cohort and validation cohort. This 3-gene platelet RNA signature could effectively discriminate ESCC from healthy control. Our data highlighted the potential of tumor educated platelets for the noninvasive diagnosis of ESCC. Moreover, we found keratin and collagen protein families, and ECM-related pathways might be involved in tumor progression and metastasis of ESCC, which might provide insights to understand ESCC pathobiology and advance novel therapeutics.
2022-06-01 | GSE197514 | GEO
Project description:Patients with systemic lupus erythematosus (SLE) have a markedly increased risk to develop cardiovascular disease, and traditional cardiovascular risk factors fail to account for this increased risk. We used microarray to probe the platelet transcriptome in individuals with SLE and healthy controls, and the gene and protein expression of a subset of differentially expressed genes was further investigated and correlated to platelet activation status. Real-time PCR was used to confirm a type I interferon (IFN) gene signature in patients with SLE, and the IFN-regulated proteins PRKRA, IFITM1 and CD69 (p<0.0001) were found to be up-regulated in platelets from SLE patients as compared to healthy volunteers. Notably, patients with a history of vascular disease had increased expression of type I IFN-regulated proteins as well as more activated platelets as compared with patients without vascular disease. We suggest that interferogenic immune complexes stimulate production of IFNα which up-regulates the megakaryocytic type I IFN-regulated genes and proteins. This could affect platelet activation and contribute to development of vascular disease in SLE. In addition, platelets with type I IFN signature could be a novel marker for vascular disease in SLE. Platelets were purified from SLE patients (n=10) and age and sex-matched healthy volunteers (n=10). cDNA was generated for each individual. For the microarray analysis, cDNA from the 10 SLE patients were pooled, as well as the cDNA from the 10 healthy volunteers to represent a mean mRNA expression level from 10 individuals.
2010-06-04 | E-GEOD-22132 | biostudies-arrayexpress
Project description:Early diagnosis of acute myeloid leukemia (AML) in the pre-leukemic stage remains a clinical challenge, as pre-leukemic patients show no symptoms, lacking any known morphological or numerical abnormalities in blood cells. Here, we demonstrate that platelets with structurally abnormal mitochondria emerge at the pre-leukemic phase of AML, preceding detectable changes in blood cell counts or detection of leukemic blasts in blood. We visualized frozen-hydrated platelets from mice at different time points during AML development in situ using electron cryo-tomography (cryo-ET) and identified intracellular organelles through an unbiased semi-automatic process followed by quantitative measurement. A large proportion of platelets exhibited changes in the overall shape and depletion of organelles in AML. Notably, 23% of platelets in pre-leukemic cells exhibit abnormal, round mitochondria with unfolded cristae, accompanied by a significant drop in ATP levels and altered expression of metabolism-related gene signatures. Our study demonstrates that detectable structural changes in pre-leukemic platelets may serve as a biomarker for the early diagnosis of AML.
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