A pan-cancer analysis reveals CHD1L as a prognostic and immunological biomarker in several human cancers

Front Mol Biosci. 2023 Mar 23:10:1017148. doi: 10.3389/fmolb.2023.1017148. eCollection 2023.

Abstract

Introduction: Several recent studies pointed out that chromodomain-helicase-DNA-binding protein 1-like (CHD1L) is a putative oncogene in many human tumors. However, up to date, there is no pan-cancer analysis performed to study the different aspects of this gene expression and behavior in tumor tissues. Methods: Here, we applied several bioinformatics tools to make a comprehensive analysis for CHD1L. Firstly we assessed the expression of CHD1L in several types of human tumors and tried to correlate that with the stage and grade of the analyzed tumors. Following that, we performed a survival analysis to study the correlation between CHD1L upregulation in tumors and the clinical outcome. Additionally, we investigated the mutation forms, the correlation with several immune cell infiltration, and the potential molecular mechanisms of CHD1L in the tumor tissue. Result and discussion: The results demonstrated that CHD1L is a highly expressed gene across several types of tumors and that was correlated with a poor prognosis for most cancer patients. Moreover, it was found that CHD1L affects the tumor immune microenvironment by influencing the infiltration level of several immune cells. Collectively, the current study provides a comprehensive overview of the oncogenic roles of CHD1L where our results nominate CHD1L as a potential prognostic biomarker and target for antitumor therapy development.

Keywords: CHD1L; biomarker; differential expression; pan-cancer; prognosis; tumor immunotherapy.

Grants and funding

The Deanship of Scientific Research of King Khalid University in Abha, Saudi Arabia, entirely supported this research (Grant No. G.R.P.1-27-43). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2020R1I1A2066868), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A5A2019413), a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number : HF20C0038), and the innovation network support Program through the INNOPOLIS funded by Ministry of Science and ICT (2022-IT-RD-0205-01-101).