Predictive markers based on transcriptome modules for vinorelbine-based adjuvant chemotherapy for lung adenocarcinoma patients

Abstract

Microtubule inhibitors (MTIs) are widely used as anti-cancer drugs for various types of tumors. Vinorelbine, an MTI, is utilized in postoperative adjuvant chemotherapy, especially for lung adenocarcinoma. However, no molecular markers are able to identify patients for whom MTIs would be effective. In this study, we attempted to identify practical markers to predict the efficacy of MTI-based adjuvant chemotherapy. Materials and methods: We explored a novel combination of molecular marker candidates, based on gene expression network analysis constructed using an omics panel of 26 lung adenocarcinoma cell lines. We then applied the obtained classification method to predict the efficacy of MTI treatment in patients who received adjuvant chemotherapy. RNA sequencing (RNA-seq) analysis was conducted using surgical specimens from 24 Japanese lung adenocarcinoma patients treated postoperatively with vinorelbine. Results: We identified four modules within the network with module activities that were significantly associated with sensitivity to MTIs. Two modules were associated with high sensitivity to MTIs: genes with low differentiation or transdifferentiation of lung adenocarcinomas. On the other hand, MTI-low sensitivity modules were enriched in common epithelial genes and markers of well-differentiated lung adenocarcinomas. We also classified lung adenocarcinoma cases using the module activities associated with MTI efficacy and stratify the cases with MTI resistance. Conclusion:We demonstrate that the constructed classification method is useful for identifying patients with MTI resistance which results in a high risk of cancer relapse.

Prediction of Response to Radiotherapy by Characterizing the Transcriptomic Features in Clinical Tumor Samples across 15 Cancer Types

“…Their roles in cancer have been studied. For example, TRIM9 [ 29 ]and SCG3 [ 30 ] have been reported to promote the proliferation of cancer cell, and SNAP25 and TUBB4A were identified as potential prognostic biomarkers for prostate cancer [ 31 ] or lung adenocarcinoma [ 32 ] ( Figure 3 )…”

Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine

“…In our study, STAT3 expression was significantly lower in CS3 and CS4 [CS1: 159.11 (126.81, 199.74); CS2: 147.22 (129.03, 182.49); CS3: 129.68 (108.29, 167.60); CS4: 122.66 (98.27, 159.05); P < 0.001], which may be the main reason why these two subtypes are more sensitive to cisplatin and paclitaxel. On the other hand, class III β-tubulin (TUBB3) is a predictive marker of vinorelbine sensitivity in non-small cell lung cancer (52). Tumors with high levels of TUBB3 expression were more sensitive to vinorelbine.…”