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Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review.

ABSTRACT: Lung cancer represent the leading cause of cancer mortality, so several efforts have been focused on the development of a screening program. To address the issue of high overdiagnosis and false positive rates associated to LDCT-based screening, there is a need for new diagnostic biomarkers, with liquid biopsy ncRNAs detection emerging as a promising approach. In this scenario, this work provides an updated summary of the literature evidence about the role of non-coding RNAs in lung cancer screening. A literature search on PubMed was performed including studies which investigated liquid biopsy non-coding RNAs biomarker lung cancer patients and a control cohort. Micro RNAs were the most widely studied biomarkers in this setting but some preliminary evidence was found also for other non-coding RNAs, suggesting that a multi-biomarker based liquid biopsy approach could enhance their efficacy in the screening context. However, further studies are needed in order to optimize detection techniques as well as diagnostic accuracy before introducing novel biomarkers in the early diagnosis setting.

SUBMITTER: Garbo E

PROVIDER: S-EPMC10571819 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review.

Garbo Edoardo E Del Rio Benedetta B Ferrari Giorgia G Cani Massimiliano M Napoli Valerio Maria VM Bertaglia Valentina V Capelletto Enrica E Rolfo Christian C Novello Silvia S Passiglia Francesco F

Cancers 20230928 19

Lung cancer represent the leading cause of cancer mortality, so several efforts have been focused on the development of a screening program. To address the issue of high overdiagnosis and false positive rates associated to LDCT-based screening, there is a need for new diagnostic biomarkers, with liquid biopsy ncRNAs detection emerging as a promising approach. In this scenario, this work provides an updated summary of the literature evidence about the role of non-coding RNAs in lung cancer screen ...[more]

PMID: 37835468

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Project description:BackgroundDespite the availability of advanced technology to detect and treat esophageal squamous cell carcinoma (ESCC), the 5-year survival rate of ESCC patients is still meager. Recently, long non-coding RNAs (lncRNAs) have emerged as essential players in the diagnosis and prognosis of various cancers.ObjectiveThis pilot study focused on identifying circulating lncRNAs as liquid biopsy markers for the ESCC.MethodologyWe performed next-generation sequencing (NGS) to profile circulating lncRNAs in ESCC and healthy individuals' blood samples. The expression of the top five upregulated and top five downregulated lncRNAs were validated through quantitative real-time PCR (qRT-PCR), including samples used for the NGS. Later, we explored the diagnostic/prognostic potential of lncRNAs and their impact on the clinicopathological parameters of patients. To unravel the molecular target and pathways of identified lncRNAs, we utilized various bioinformatics tools such as lncRnome, RAID v2.0, Starbase, miRDB, TargetScan, Gene Ontology, and KEGG pathways.ResultsThrough NGS profiling, we obtained 159 upregulated, 137 downregulated, and 188 neutral lncRNAs in ESCC blood samples compared to healthy individuals. Among dysregulated lncRNAs, we observed LINC00324 significantly upregulated (2.11-fold; p-value = 0.0032) and LOC100507053 significantly downregulated (2.22-fold; p-value = 0.0001) in ESCC patients. Furthermore, we found LINC00324 and LOC100507053 could discriminate ESCC cancer patients' from non-cancer individuals with higher accuracy of Area Under the ROC Curve (AUC) = 0.627 and 0.668, respectively. The Kaplan-Meier and log-rank analysis revealed higher expression levels of LINC00324 and lower expression levels of LOC100507053 well correlated with the poor prognosis of ESCC patients with a Hazard ratio of LINC00324 = 2.48 (95% CI: 1.055 to 5.835) and Hazard ratio of LOC100507053 = 4.75 (95% CI: 2.098 to 10.76)]. Moreover, we also observed lncRNAs expression well correlated with the age (>50 years), gender (Female), alcohol, tobacco, and hot beverages consumers. Using bioinformatics tools, we saw miR-493-5p as the direct molecular target of LINC00324 and interacted with the MAPK signaling pathway in ESCC pathogenesis.ConclusionThis pilot study suggests that circulating LINC00324 and LOC100507053 can be used as a liquid biopsy marker of ESCC; however, multicentric studies are still warranted.

Project description:BackgroundAlzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone.MethodsThis nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed.ResultsThe study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD.ConclusionsThe AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

Dataset Information

Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review.

Publications

Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review.

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