Clinical Data Analysis Identifies Prognostic Long Non-coding RNA Signatures in Lung Adenocarcinoma.
Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and remains associated with poor clinical outcomes due to pronounced molecular heterogeneity and limited prognostic biomarkers. Long non-coding RNAs (lncRNAs) have emerged as important regulators of cancer biology, yet their systematic association with disease progression and survival in LUAD remains incompletely defined. This study aimed to identify lncRNAs that robustly associate with LUAD progression and prognosis.
Pre-processed lncRNA expression data for 488 LUAD tumors and 58 normal lung tissues were obtained from The Cancer Genome Atlas (TCGA) via the TANRIC platform. Following expression filtering, stage-wise differential expression analysis was performed using Welch's t-test with false discovery rate correction. Kaplan-Meier survival analysis was used to evaluate prognostic relevance. Rank-based trend analyses using Spearman correlation were conducted to assess monotonic expression changes across tumor stage, lymph-node status, and tumor size.
We identified 68 lncRNAs consistently upregulated across all LUAD stages relative to normal lung tissue. Survival analysis revealed that higher expression of several lncRNAs was associated with poorer overall survival. Among these, FAM83A-AS1, CYTOR, and MIR4435-2HG emerged as prominent candidates, exhibiting consistent tumor-associated overexpression and adverse survival association. Importantly, these three lncRNAs also demonstrated significant monotonic trends across increasing lymph-node involvement and primary tumor size, indicating a close association with tumor burden and disease aggressiveness.
This integrative analysis identifies FAM83A-AS1, CYTOR, and MIR4435-2HG as robust poor-prognosis-associated lncRNAs in LUAD. Their coordinated behavior across expression, survival, nodal status, and tumor size highlights their potential utility as prognostic biomarkers and provides a framework for lncRNA-based risk stratification in lung adenocarcinoma.
Pre-processed lncRNA expression data for 488 LUAD tumors and 58 normal lung tissues were obtained from The Cancer Genome Atlas (TCGA) via the TANRIC platform. Following expression filtering, stage-wise differential expression analysis was performed using Welch's t-test with false discovery rate correction. Kaplan-Meier survival analysis was used to evaluate prognostic relevance. Rank-based trend analyses using Spearman correlation were conducted to assess monotonic expression changes across tumor stage, lymph-node status, and tumor size.
We identified 68 lncRNAs consistently upregulated across all LUAD stages relative to normal lung tissue. Survival analysis revealed that higher expression of several lncRNAs was associated with poorer overall survival. Among these, FAM83A-AS1, CYTOR, and MIR4435-2HG emerged as prominent candidates, exhibiting consistent tumor-associated overexpression and adverse survival association. Importantly, these three lncRNAs also demonstrated significant monotonic trends across increasing lymph-node involvement and primary tumor size, indicating a close association with tumor burden and disease aggressiveness.
This integrative analysis identifies FAM83A-AS1, CYTOR, and MIR4435-2HG as robust poor-prognosis-associated lncRNAs in LUAD. Their coordinated behavior across expression, survival, nodal status, and tumor size highlights their potential utility as prognostic biomarkers and provides a framework for lncRNA-based risk stratification in lung adenocarcinoma.
Authors
Sharma Sharma, Chourasia Chourasia, Priyanka Priyanka, Garg Garg, Nayak Nayak, Shah Shah, Dhar Dhar, Sarkar Sarkar, Nag Nag, Saxena Saxena
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