Abstract
BackgroundLimited treatment strategies are available for squamous-cell lung cancer (SQLC) patients. Few studies have addressed whether immune-related genes (IRGs) or the tumor immune microenvironment can predict the prognosis for SQLC patients. Our study aimed to construct a signature predict prognosis for SQLC patients based on IRGs.MethodsWe constructed and validated a signature from SQLC patients in The Cancer Genome Atlas (TCGA) using bioinformatics analysis. The underlying mechanisms of the signature were also explored with immune cells and mutation profiles.ResultsA total of 464 eligible SQLC patients from TCGA dataset were enrolled and were randomly divided into the training cohort (n = 232) and the testing cohort (n = 232). Eight differentially expressed IRGs were identified and applied to construct the immune signature in the training cohort. The signature showed a significant difference in overall survival (OS) between low-risk and high-risk cohorts (P < 0.001), with an area under the curve of 0.76. The predictive capability was verified with the testing and total cohorts. Multivariate analysis revealed that the 8-IRG signature served as an independent prognostic factor for OS in SQLC patients. Naive B cells, resting memory CD4 T cells, follicular helper T cells, and M2 macrophages were found to significantly associate with OS. There was no statistical difference in terms of tumor mutational burden between the high-risk and low-risk cohorts.ConclusionOur study constructed and validated an 8-IRG signature prognostic model that predicts clinical outcomes for SQLC patients. However, this signature model needs further validation with a larger number of patients.
Highlights
Lung cancer is the most commonly diagnosed cancer and the first leading cause of cancer-related mortality worldwide, making it a major public health concern [1]
A total of 502 squamous-cell lung cancer (SQLC) patients were identified in the The Cancer Genome Atlas (TCGA) cohort
In order to reduce the effect of follow-up time on short term, patients with follow-up time less than 30 days were not included in our study
Summary
Lung cancer is the most commonly diagnosed cancer and the first leading cause of cancer-related mortality worldwide, making it a major public health concern [1]. Standard treatments, including chemotherapy, radiotherapy, and surgical resection, have improved the prognosis of early stage squamous-cell lung cancer (SQLC) [2]. Most novel drugs, including pemetrexed and bevacizumab, have been approved in the treatment for lung cancer but not for squamous-cell subtype because of the adverse events [8, 9]. There are limited treatment strategies available for SQLC patients. Due to the remarkable response, pembrolizumab was approved as the first-line treatment for recurrent or metastatic SQLC by the United States Food and Drug Administration and National Medical Products Administration of China [12]. Limited treatment strategies are available for squamous-cell lung cancer (SQLC) patients. Few studies have addressed whether immune-related genes (IRGs) or the tumor immune microenvironment can predict the prognosis for SQLC patients. Our study aimed to construct a signature predict prognosis for SQLC patients based on IRGs
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
