A six‐gene prognostic and predictive radiotherapy‐based signature for early and locally advanced stages in non‐small‐cell lung cancer Journal Article
| Authors: | Peinado‐Serrano, J.; Quintanal‐Villalonga, Á; Muñoz‐Galvan, S.; Verdugo‐Sivianes, E. M.; Mateos, J. C.; Ortiz‐Gordillo, M. J.; Carnero, A. |
| Article Title: | A six‐gene prognostic and predictive radiotherapy‐based signature for early and locally advanced stages in non‐small‐cell lung cancer |
| Abstract: | Non‐small‐cell lung cancer (NSCLC) is the leading cause of cancer death worldwide, gener-ating an enormous economic and social impact that has not stopped growing in recent years. Cancer treatment for this neoplasm usually includes surgery, chemotherapy, molecular targeted treatments, and ionizing radiation. The prognosis in terms of overall survival (OS) and the disparate therapeutic responses among patients can be explained, to a great extent, by the existence of widely heterogeneous molecular profiles. The main objective of this study was to identify prognostic and predictive gene signatures of response to cancer treatment involving radiotherapy, which could help in making therapeutic decisions in patients with NSCLC. To achieve this, we took as a reference the differential gene expression pattern among commercial cell lines, differentiated by their response profile to ionizing radiation (radiosensitive versus radioresistant lines), and extrapolated these results to a cohort of 107 patients with NSCLC who had received radiotherapy (among other therapies). We obtained a six‐gene signature (APOBEC3B, GOLM1, FAM117A, KCNQ1OT1, PCDHB2, and USP43) with the ability to predict overall survival and progression‐free survival (PFS), which could translate into a prediction of the response to the cancer treatment received. Patients who had an unfavorable prognostic signature had a median OS of 24.13 months versus 71.47 months for those with a favorable signature, and the median PFS was 12.65 months versus 47.11 months, respectively. We also carried out a univariate analysis of multiple clinical and pathological variables and a bivariate analysis by Cox regression without any factors that substantially modified the HR value of the proposed gene signature. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
| Keywords: | biomarkers; radiation oncology; nsclc; prognosis; predictive signature |
| Journal Title: | Cancers |
| Volume: | 14 |
| Issue: | 9 |
| ISSN: | 2072-6694 |
| Publisher: | MDPI |
| Date Published: | 2022-05-01 |
| Start Page: | 2054 |
| Language: | English |
| DOI: | 10.3390/cancers14092054 |
| PROVIDER: | scopus |
| PMCID: | PMC9099638 |
| PUBMED: | 35565183 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 2 May 2022 -- Source: Scopus |
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