2ⁿᵈ Edition of the Cancer R&D World Conference 2026

Abstract

Background: Lung tumor is the highest cancer-related mortality worldwide, leading to approximately 1.8 million death events annualy. The most prevalent subtype of lung cancer is non-small lung cancer (NSLC), representing almost 85% of all lung cancer cases, including lung adenocarcinoma, squamous cell carcinoma, and large cell carcinoma subtypes. Notwithstanding, the continuous development in diagnostic tools and the discovery of novel therapeutic agents, lung cancer has only 28.1% of 5-years survival rate. Underlying explanations include late-stage diagnosis, treatment selection, unopposed resistance mechanisms in cancer cells, and high heterogeneity. MicroRNAs (miRNAs) are small, non-coding RNAs that consist of 18-25 nucleotides and regulate gene expression and post-transcriptional modifications, eventually interfering with major cancer hallmarks. The miR-100 is a tumor suppressor miRNA that has been explored in many solid tumors. The mechanism of miR-100’s tumor-suppressive activity remains incompletely elucidated. Our aim is to understand the role of miR-100 in lung tumor biology, and to detect related therapeutic effect by modulating miR-100 expression in lung cancer cell lines.

Methods: We recruited bioinformatics tools, then augmented with biological experiments. Our in-silicon analyses were done by accessing TCGA database using XENA broswer and TCGA packages for R sutdio (Version 3.6.0). The kaplan meier plot was done to understand the survival rate of miR-100 and the investigated genes by using KM-Plotter database. Genes of interest were selected based on association with miR-100, Investigated target for miR-100, survival benefits for lung cancer patients and differential expressed in normal compared to cancerous tissues. Baseline expressions were done for miR-100 and the investigated genes using UALCAN database. Linkedomics database was accessed to explore the correlated mRNA expression with miR-100. KEGG and Reactome were utilized to explore the investigated gene’s pathways. TargetScan is the tool of choice to calculate the miR-100 preferred targeted genes. iLINCS was used to propose disease signature and eventually chemical perturbation agens for drug repurposing. MiR-100 expressoin were modulated using RNAiMAX lipofectaime reagents including mimic and inhibtors. The baseline expression of miR-100 and investigated genes was done using qPCR in A549 BEAS-2B cell lines. P-value of 0.05 was the selected threshold for statistical significance.

Results: A total of 706 lung cancer patients were accessed. The high expression of miR-100 was leading to better overall survival for those patients (HR= 0.85 (0.74 – 0.99) logRankP= 0.033). Out of those patients, 491 patients were included in the baseline expression analysis. The miR-100 expression was signifcantly downregulted in tumor tissues compared to adjacent normal tissues from the same samples. ST6GALNAC4 is the most associated gene with miR-100 and shows differnatial expression, survival rate benefits, and a predicted target of miR-100. ST6GALNAC4 is predicted to be regulatd by another genes which is TXNDC11. Both of these two genes contribute to metabolism and anti-oxidative stress. The baselines expression of miR-100 in A549 was 2 times lower than the normal cell lines BEAS-2B which confirm the in-silico findings. Moreimportantly, transfection the cancer cells with miR-100 mimic and inhibitor led to dysregulate these two genes which another confirmatory findings for the in-silico. As inhibiting miR-100 led to downexpression of TXNDC11 and overexpression of ST6GALNAC4. For drug repurposing, we created disease siganture by including the previous discussed genes and link it to chemical perturbations, Voirinostat is the most predicated drug that can reverse the disease siganture for lung cancer.

Conclusion: Our findings confirm the role of miR-100 as tumor supporessor miRNA. Glycosylation is well investigated and linked to develop tumorgnesis and immunce response dysregulation. Our findings create overlapping regulation between ST6GALNAC4 and miR-100. Despite the survival rate of lung cancer patients was better with ST6GALNAC4 overexpression in the accessed data, the introduction of miR-100 inhibitor in A549 cell line led to overexpresson compared to control cells which may explains the role of this gene in lung cancer glycosylation pathway. Moreover, the transfected cells with miR-100 inhibitor show significant reduction of TXNDC11 which supports in antioxidative stress mechanisms. Voirinostat is predicated to reverse these genes to normal levels in lung cancer patients. We report our findings are the first to link the association between miR-100, ST6GALNAC4, and TXNDC11 in lung cancer.