The Landscape of the Tumor-Infiltrating Immune Cell and Prognostic Nomogram in Colorectal Cancer

Developing and experimental validating a B cell exhaustion-related gene signature to assess prognosis and immunotherapeutic response in bladder cancer

BACKGROUND

B cell exhaustion (BEX) refers to the impairment of normal B cell functions and decreased proliferation capability. However, the prognostic value of BEX-related genes in bladder cancer (BLCA) remains unclear.

METHODS

BLCA cases from TCGA were used for training, while GSE5287, GSE13507, GSE31684, and GSE32894 cohorts from GEO were used for external validation. BEX-related genes were identified through literature retrieval, unsupervised clustering, and genomic difference detection. Gene pairing, LASSO, random forest, and Cox regression were employed to construct a predictive model. B cell samples from scRNAseqDB, GSE111636, and IMvigor210 were utilized to explore immunoprofiles and the predictive ability of the model in immunotherapeutic response. Additionally, 21 pairs of BLCA and paracarcinoma samples from Nanfang Hospital were used to re-confirm our findings through RT-qPCR, immunofluorescence, and flow cytometry.

RESULTS

39 BEX-related genes were identified. A 4-gene-pair signature was constructed and served as a reliable prognostic predictor across multiple datasets (pooled HR = 2.32; 95 % CI = 1.81-2.98). The signature reflected the BEX statuses of B cells (FDR < 0.05) and showed promise in evaluating immunotherapeutic sensitivity (P < 0.001). In the local cohort, CD52, TUBB6, and CAV1 were down-regulated in BLCA tissues, while TGFBI, UBE2L6, TINAGL1, and IL32 were up-regulated (all P < 0.05). Furthermore, the infiltration levels of CD19 + CD52 + and CD19 + TUBB6 + B cells in paracarcinoma samples were higher than those in BLCA samples (all P < 0.05).

CONCLUSION

A BEX-related gene signature was developed to predict prognosis and immunotherapeutic sensitivity in BLCA, providing valuable guidance for personalized treatment.

A Treg-related riskscore model may improve the prognosis evaluation of colorectal cancer

BACKGROUND

Colorectal cancer (CRC) poses a significant health challenge. This study aims to investigate the prognostic value of a regulatory T cell (Treg)-related gene signature in CRC.

METHODS

We extracted the gene expression and clinical data on CRC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The gene module related to Treg was identified by weighted gene co-expression network analysis (WGCNA). The genes in the significant module were filtered by univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. A riskscore model was established in terms of the key Treg-related genes. The reliability of this riskscore model was validated using the external GEO dataset. The association of riskscore with clinical features, mutation patterns and signaling pathways was explored.

RESULTS

Genes in the blue module showed the strongest association with Tregs. After a series of filtering cycles, seven Treg-related key genes, GDE1, GSR, HSPB1, AOC2, TBX19, TAMM41 and TIGD6, were selected to construct a riskscore model. This model performed well in evaluating the patients' survival in TCGA cohort, and was further affirmed by the GSE17536 validation cohort. For precise evaluation of the patients' survival, we established a nomogram in light of riskscore and clinical factors. Patients in different risk groups had distinct clinical features, mutation patterns and signaling pathway activities. The expression of five key genes was significantly associated with Treg infiltration in the CRC samples.

CONCLUSION

We established a useful riskscore model in light of seven Treg-related genes. This model may contribute to the prognosis evaluation, direct tailored treatment, and hopefully improve clinical outcomes of the CRC patients.

The construction of a novel ferroptosis-related lncRNA model to predict prognosis in colorectal cancer patients

Colorectal cancer (CRC) is the most common gastrointestinal tumor with poor prognosis. Ferroptosis is a pivotal form of programmed iron-dependent cell death different from autophagy and apoptosis, and long noncoding RNA (lncRNA) can influence the prognosis of CRC via regulating ferroptosis. To explore the role and prognostic value of the constructed ferroptosis-related lncRNA model in CRC, a prognostic model was constructed and validated by screening ferroptosis-related lncRNAs associated with prognosis based on the transcriptome data and survival data of CRC patients in The Cancer Genome Atlas database. Regarding the established prognostic models, differences in signaling pathways and immune infiltration, as well as differences in immune function, immune checkpoints, and N6-methyladenosine-related genes were also analyzed. A total of 6 prognostic ferroptosis-related lncRNAs were obtained, including AP003555.1, AC010973.2, LINC01857, AP001469.3, ITGB1-DT and AC129492.1. Univariate independent prognostic analysis, multivariate independent prognostic analysis and receiver operating characteristic curves showed that ferroptosis-related lncRNAs could be recognized as independent prognostic factors. The Kaplan-Meier survival curves and the risk curves showed that the survival time of the high-risk group was shorter. Gene set enrichment analysis enrichment analysis showed that ATP-binding cassette transporters, taste transduction and VEGF signaling pathway were more active in high-risk groups that than in low-risk groups. However, the citrate cycle tricarboxylic acid cycle, fatty acid metabolism and peroxisome were significantly more active in the low-risk group than in the high-risk group. In addition, there were also differences in immune infiltration in the high-low-risk groups based on different methods, including antigen-presenting cell co-stimulation, chemokine receptor, parainflammation, and Type II IFN Response. Further analysis of Immune checkpoints showed that most of the Immune checkpoints such as TNFRSF18, LGALS9 and CTLA4 in the high-risk group were significantly higher than those in the low-risk group, and the expressions of N6-methyladenosine related genes METTL3, YTHDH2 and YTHDC1 were also significantly different in the high-risk group. Ferroptosis-related lncRNAs are closely related to the survival of colorectal cancer patients, which can be used as new biomarkers and potential therapeutic targets for the prognosis of colorectal cancer.

Cuproptosis-Related genes in the prognosis of colorectal cancer and their correlation with the tumor microenvironment

Colorectal cancer (CRC) is a common tumor disease of the digestive system with high incidence and mortality. Cuproptosis has recently been found to be a new form of cell death. The clinical significance of cuproptosis-related genes (CRGs) in CRC is not clear. In this study, The Cancer Genome Atlas Colon and Rectal Cancer dataset was used to analyze the relationship between CRGs and clinical characteristics of CRC by differential expression analysis and Kaplan–Meier survival (K-M) analysis. Based on CRGs, prognosis model and risk score of CRC was constructed in COADREAD by multivariate Cox analysis. Receiver operating curves (ROC) analysis, K-M analysis and calibration analysis in GDC TCGA Colon Cancer dataset were applied to validating model. Subsequently, the relationship between risk score of CRC and immune microenvironment was analyzed by multiple immune score algorithms. Finally, we found that most CRGs were differentially expressed between tumors and normal tissues. Some CRGs were differentially expressed among different clinical characteristics. K-M analysis showed that the CRGs were related to overall survival (OS), disease-specific survival, and progression-free survival. Subsequently, DLAT and CDKN2A were identified as risk factors for OS in CRC by multivariate Cox analysis, and the risk score was established. K–M analysis showed that there was a significant difference in OS between the high-risk and low-risk groups, which were grouped by risk score median. ROC analysis showed that the risk score performs well in predicting the 1-year, 3-year and 5-year OS. Enrichment analysis showed that the differentially expressed genes between the high- and low-risk groups were enriched in immune-related signaling pathways. Further analysis showed that there were significant differences in the levels of immune cells and stromal cells between the high- and low-risk groups. The high-risk group had higher levels of immune cells and interstitial cells. At the same time, the high-risk group had a higher immune escape ability, and the predicted immune treatment response in the high-risk group was poor. In conclusion, CRGs can be used as prognostic factors in CRC and are closely related to the levels of immune cells and stromal cells in the tumor microenvironment.