AI Article Synopsis

  • - The study focuses on lung adenocarcinoma (LUAD) and introduces a miR-200 based RNA signature that helps predict survival rates beyond existing classification methods, especially as therapies are moving to earlier stages of the disease.
  • - Using RNA sequencing, researchers identified three different clusters of tumors based on their miR-200 signature, each associated with specific genetic mutations, and assessed various biological processes and immune responses connected to these clusters.
  • - The miR-200 signature effectively stratified patients into high- and low-risk groups, showing that those with a higher signature had longer disease-free survival, suggesting its potential for improving prognosis evaluations and guiding treatment plans in LUAD.

Article Abstract

Background: In Lung adenocarcinoma (LUAD), targeted therapies and immunotherapies have moved from metastatic to early stage and stratification of the relapse risk becomes mandatory. Here we identified a miR-200 based RNA signature that delineates Epithelial-to-mesenchymal transition (EMT) heterogeneity and predicts survival beyond current classification systems.

Methods: A miR-200 signature was identified using RNA sequencing. We scored the miR-200 signature by WISP (Weighted In Silico Pathology), used GSEA to identify pathway enrichments and MCP-counter to characterize immune cell infiltrates. We evaluate the clinical value of this signature in our series of LUAD and using TCGA and 7 published datasets.

Results: We identified 3 clusters based on supervised classification: I is miR-200-sign-down and enriched in TP53 mutations IIA and IIB are miR-200-sign-up: IIA is enriched in EGFR (p < 0.001), IIB is enriched in KRAS mutation (p < 0.001). WISP stratified patients into miR-200-sign-down (n = 65) and miR-200-sign-up (n = 42). Several biological processes were enriched in MiR-200-sign-down tumors, focal adhesion, actin cytoskeleton, cytokine/receptor interaction, TP53 signaling and cell cycle pathways. Fibroblast, immune cell infiltration and PDL1 expression were also significantly higher suggesting immune exhaustion. This signature stratified patients into high-vs low-risk groups, miR-200-sign-up had higher DFS, median not reached at 60 vs 41 months and within subpopulations with stage I, IA, IB, or II. Results were validated on TCGA data on 7 public datasets.

Conclusion: This EMT and miR-200-related prognostic signature refines prognosis evaluation independently of tumor stage and paves the way towards assessing the predictive value of this LUAD clustering to optimize perioperative treatment.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184345PMC
http://dx.doi.org/10.1186/s12967-023-04086-7DOI Listing

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