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Single-cell RNA sequencing for the identification of early-stage lung cancer biomarkers from circulating blood.

ABSTRACT: Lung cancer accounts for more than half of the new cancers diagnosed world-wide with poor survival rates. Despite the development of chemical, radiological, and immunotherapies, many patients do not benefit from these therapies, as recurrence is common. We performed single-cell RNA-sequencing (scRNA-seq) analysis using Fluidigm C1 systems to characterize human lung cancer transcriptomes at single-cell resolution. Validation of scRNA-seq differentially expressed genes (DEGs) through quantitative real time-polymerase chain reaction (qRT-PCR) found a positive correlation in fold-change values between C-X-C motif chemokine ligand 1 (CXCL1) and 2 (CXCL2) compared with bulk-cell level in 34 primary lung adenocarcinomas (LUADs) from Stage I patients. Furthermore, we discovered an inverse correlation between chemokine mRNAs, miR-532-5p, and miR-1266-3p in early-stage primary LUADs. Specially, miR-532-5p was quantifiable in plasma from the corresponding LUADs. Collectively, we identified markers of early-stage lung cancer that were validated in primary lung tumors and circulating blood.

SUBMITTER: Kim J

PROVIDER: S-EPMC8519939 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Single-cell RNA sequencing for the identification of early-stage lung cancer biomarkers from circulating blood.

Kim Jinhong J Xu Zhaolin Z Marignani Paola A PA

NPJ genomic medicine 20211015 1

Lung cancer accounts for more than half of the new cancers diagnosed world-wide with poor survival rates. Despite the development of chemical, radiological, and immunotherapies, many patients do not benefit from these therapies, as recurrence is common. We performed single-cell RNA-sequencing (scRNA-seq) analysis using Fluidigm C1 systems to characterize human lung cancer transcriptomes at single-cell resolution. Validation of scRNA-seq differentially expressed genes (DEGs) through quantitative ...[more]

PMID: 34654834

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Project description:BackgroundEarly diagnosis of nasopharyngeal carcinoma (NPC) is vital to improve the prognosis of these patients. However, early diagnosis of NPC is typically challenging. Therefore, we explored the pathogenetic roles and associated mechanisms of exosomes in plasma of patients with early-stage NPC.MethodsExosomes in plasma were extracted by ultra-high-speed centrifugation. Western blot and transmission electron microscopy (TEM) were used to verify the purity of exosomes. The sequencing data (6 plasma samples from healthy volunteers vs. 6 NPC plasma samples) were analyzed by principal component analysis (PCA), DESeq2, gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and TargetScan. The differentially expressed miRNAs (DEmiRNAs) were obtained from the dataset (GSE118720) downloaded from the Gene Expression Omnibus (GEO) repository. Additionally, the datasets downloaded from the GEO database (GSE12452, GSE13597, GSE53819, GSE64634) were used to predict the target genes and functions of hsa-miR-1301-3p. qPCR was applied to verify the differences in the expressions of hsa-miR-1301-3p between 10 normal plasma and 10 NPC plasma samples.ResultsWestern blot, TEM, and Nanoparticle Tracking Analysis showed adequate purity of the extracted exosomes. RNA-seq analysis revealed 21 upregulated miRNAs, and 10 downregulated miRNAs in plasma exosomes of early-stage NPC patients. GO analysis showed that the target genes of DEmiRNAs were mainly enriched in DNA synthesis and transcription regulation. KEGG analysis revealed that DEmiRNAs were mainly enriched in PI3K-Akt and MAPK signaling pathways. Moreover, the expression of hsa-mir-1301-3p was verified to be significantly upregulated in enlarged samples of plasma exosomes.ConclusionsWe identified several DEmiRNAs extracted from tumor-derived exosomes between normal plasma and early-stage NPC plasma. Bioinformatics analyses indicated that these DEmiRNAs may be related to NPC development. Our study may provide novel insights into underlying biomarkers and mechanisms of plasma exosomes in early-stage NPC.

Project description:BackgroundWith demographic shifts toward older populations, the number of people with dementia is steadily increasing. Alzheimer's disease (AD) is the most common cause of dementia, and no curative treatment is available. The current best strategy is to delay disease progression and to practice early intervention to reduce the number of patients that ultimately develop AD. Therefore, promising novel biomarkers for early diagnosis are urgently required.MethodsTo identify blood-based biomarkers for early diagnosis of AD, we performed RNA sequencing (RNA-seq) analysis of 610 blood samples, representing 271 patients with AD, 91 cognitively normal (CN) adults, and 248 subjects with mild cognitive impairment (MCI). We first estimated cell-type proportions among AD, MCI, and CN samples from the bulk RNA-seq data using CIBERSORT and then examined the differentially expressed genes (DEGs) between AD and CN samples. To gain further insight into the biological functions of the DEGs, we performed gene set enrichment analysis (GSEA) and network-based meta-analysis.ResultsIn the cell-type distribution analysis, we found a significant association between the proportion of neutrophils and AD prognosis at a false discovery rate (FDR) < 0.05. Furthermore, a similar trend emerged in the results of routine blood tests from a large number of samples (n = 3,099: AD, 1,605; MCI, 994; CN, 500). In addition, GSEA and network-based meta-analysis based on DEGs between AD and CN samples revealed functional modules and important hub genes associated with the pathogenesis of AD. The risk prediction model constructed by using the proportion of neutrophils and the most important hub genes (EEF2 and RPL7) achieved a high AUC of 0.878 in a validation cohort; when further applied to a prospective cohort, the model achieved a high accuracy of 0.727.ConclusionsOur model was demonstrated to be effective in prospective AD risk prediction. These findings indicate the discovery of potential biomarkers for early diagnosis of AD, and their further improvement may lead to future practical clinical use.

Dataset Information

Single-cell RNA sequencing for the identification of early-stage lung cancer biomarkers from circulating blood.

Publications

Single-cell RNA sequencing for the identification of early-stage lung cancer biomarkers from circulating blood.

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