Abstract
BackgroundColorectal cancer (CRC) is one of the most common malignant tumors with a poor prognosis. At present, the pathogenesis is not completely clear. Therefore, finding reliable prognostic indicators for CRC is of important clinical significance. In this study, bioinformatics methods were used to screen the prognostic immune-related lncRNAs of CRC, and a prognostic risk scoring model based on immune-related lncRNAs signatures were constructed to provide a basis for prognostic evaluation and immunotherapy of CRC patients.MethodsThe clinical information and RNA-seq data of CRC patients were obtained from The Cancer Genome Atlas (TCGA) database. The information of immune-related lncRNA was downloaded from the immunology database and analysis portal. The differentially expressed immune-related lncRNAs (IRLs) were screened by the edgeR package of R software. The prognostic value of IRLs was studied. Based on Cox regression analysis, a prognostic index (IRLPI) based on IRLs was established, and the relationship between the risk score and the clinicopathological characteristics of CRC was analyzed to determine the effectiveness of the risk score model as an independent prognostic factor.ResultsA total of 240 differentially expressed IRLs were identified between normal colorectal cancer tissues and normal colorectal cancer tissues, in which 8 were significantly associated with the survival of CRC patients (P < 0.05), including LINC00461, LINC01055, ELFN1-AS1, LMO7-AS1, CYP4A22-AS1, AC079612.1, LINC01351, and MIR31HG. And most of the lncRNAs related to survival were risk factors for the prognosis of CRC. The index established based on the 7 survival-related IRLs found to be highly accurate in monitoring CRC prognosis. Besides, IRLPI was significantly correlated with a variety of pathological factors and immune cell infiltration.ConclusionEight immune-related lncRNAs closely related to the prognosis of CRC patients were identified from the TCGA database. At the same time, an independent IRLPI was constructed, which may be helpful for clinicians to assess the prognosis of patients with CRC and to formulate individualized treatment plans.
Highlights
Colorectal cancer (CRC) is the third most common malignant tumor in the world (Arnold et al, 2017)
The RNA-sequencing data of CRC samples were downloaded from The Cancer Genome Atlas (TCGA) data portal (Tomczak et al, 2015), and the clinical information was obtained by Perl script
With the immune-related lncRNAs (IRLs) list, 240 differentially expressed IRLs were extracted from all DElncRNAs (Figure 1C), including 100 up-regulated IRLs and 140 down-regulated IRLs
Summary
Colorectal cancer (CRC) is the third most common malignant tumor in the world (Arnold et al, 2017). Chemotherapy, radiotherapy, and targeted therapy could extend the median survival of patients appropriately, CRC is still the fourth leading cause of cancer-related deaths with a poor prognosis (Miller et al, 2019). Tumor-induced immune escape is common, and many problems need to be solved in immunotherapy, especially in the field of identifying immunotherapy biomarkers and new effective therapeutic targets. It is urgent to explore effective prognostic biomarkers and predictive models for facilitating and evaluating the diagnosis, the molecular mechanism, the immune microenvironment and treatment of CRC. Colorectal cancer (CRC) is one of the most common malignant tumors with a poor prognosis. Bioinformatics methods were used to screen the prognostic immune-related lncRNAs of CRC, and a prognostic risk scoring model based on immune-related lncRNAs signatures were constructed to provide a basis for prognostic evaluation and immunotherapy of CRC patients
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