RNA Binding Protein-Based Model for Prognostic Prediction of Colorectal Cancer

Li, Ting; Hui, Wenjia; Halike, Halina; Gao, Feng

doi:10.1177/15330338211019504

Cited by 14 publications

(9 citation statements)

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“…PLEKHA8P1 expression has been associated with the development and progression of many malignancies in humans, such as CRC and renal cancer [ 33 ]; moreover, research has shown that its dysregulated expression affects 5-Fluorouracil-induced chemoresistance in the human hepatocellular carcinoma cell line FT3-7 [ 34 ]. Prior studies found ZC3H12A has links with immune homeostasis and post-transcriptional regulation which can stimulate tumor progression in lung and colon cancer [ 35 – 37 ]. LPO can collaborate with activated Wnt signaling to induce intestinal neoplasia [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction

et al. 2022

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Background Previous studies have reported that the tumor heterogeneity and complex oncogenic mechanisms of proximal and distal colon cancer (CRC) are divergent. Therefore, we aim to analyze the differences between left-sided CRC (L_cancer) and right-sided CRC (R_cancer), as well as constructing respective nomograms. Methods We enrolled 335 colon cancer patients (146 L_cancer patients and 189 R_cancer patients) from The Cancer Genome Atlas (TCGA) data sets, and 102 pairs of color cancer tissue and adjacent normal tissue (51 L_cancer patients and 51 R_cancer patients) from our hospital. Firstly, we analyzed the differences between the L_cancer patients and R_cancer patients, and then established the L_cancer and R_cancer prognostic models using LASSO Cox. Results R_cancer patients had lower survival than L_cancer patients. R_cancer patients had higher ESTIMATE and immune scores and lower tumor purity. These patterns of expression of immune checkpoint-related genes and TMB level were higher in R_cancer than in L_cancer patients. Finally, we using Lasso Cox regression analyses established a prognostic model for L_cancer patients and a prognostic model for R_cancer patients. The AUC values of the risk score for OS in L_cancer were 0.862 in the training set and 0.914 in the testing set, while those in R_cancer were 0.835 in the training set and 0.857 in the testing set. The AUC values in fivefold cross-validation were between 0.727 and 0.978, proving that the two prognostic models have great stability. The nomogram of L_cancer included prognostic genes, age, pathological M, pathological stage, and gender, the AUC values of which were 0.800 in the training set and 0.905 in the testing set. Meanwhile, the nomogram of R_cancer comprised prognostic genes, pathological N, pathological T, and age, the AUC values of which were 0.836 in the training set and 0.850 in the testing set. In the R_cancer patients, high-risk patients had a lower proportion of ‘B cells memory’, ‘Dendritic cells resting’, immune score, ESTIMATE score, immune checkpoint-related genes, and HLA-family genes, and a higher proportion of ‘T cells follicular helper’, ‘Dendritic cells activated’, and ‘Mast cells activated’. Conclusions We found significant differences between L_cancer and R_cancer patients and established a clinical predictive nomogram for L_cancer patients and a nomogram for R_cancer patients. Additionally, R_cancer patients in low-risk groups may be more beneficial from immunotherapy.

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Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction

et al. 2022

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“…Kaplan–Meier survival plots, receiver operating characteristic (ROC), C-index and DCA curves, visualized by R package“survival”, “timeROC”,“ggDCA” and “survminer”, were used to evaluate prognostic value of risk model in colon cancer. The constructed model in this study was also compared with known models in predicting the prognosis of colon patients ( Huang et al, 2018 ; Li et al, 2021 ; Liang et al, 2021 ). Univariate and multifactor analyses were performed to determine the independent prognostic value of the risk model.…”

Section: Materials Methodsmentioning

confidence: 99%

m7G-Related DNA Damage Repair Genes are Potential Biomarkers for Predicting Prognosis and Immunotherapy Effectiveness in Colon Cancer Patients

Chen

Dong²,

Li³

et al. 2022

Front. Genet.

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Objective: m7G is a post-transcriptional modification modality, however, limited research has been conducted on its role in colon cancer. DNA damage repair (DDR) is an important factor that contributes to colon cancer development, growth and chemoresistance. This study aimed to explore whether m7G-related DNA damage repair genes may be used as biomarkers to predict the prognosis of colon cancer patients.Methods: We use non-negative matrix factorization (NMF) to type CRC patients into. Risk models were constructed using different expression genes in two clusters. We assessed the reliability of risk models with DCA curves, and a Nomogram. Meanwhile, The receiver operating characteristic and C-index curves were used to compare the predictive significance of the constructed risk models with other studies. In additional, we examined the significance of risk models on patients’ immunity microenvironment and response to immune therapy. Finally, we used a series of cellular experiments to validate the effect of model genes on the malignant progression of CRC cells.Results: Twenty-eight m7G genes were obtained from the GSEA database. Multivariate Cox and LASSO Cox regression analysis was performed and eleven m7G-related DDR genes were identified for constructing the risk model. Survival and stage of CRC patients were worser in the high-risk group than in the low-risk group for both the training and test sets. Additionally, the different immune microenvironment status of patients in the high- and low-risk groups, suggesting that patients in the low-risk group may be more sensitive to immunotherapy, particularly immune checkpoint inhibitors. Finally, we found that depletion of ATP2A1, one of the risk genes in our model, influence the biologic behaviour of CRC cells significantly.Conclusion: The m7G-related DDR genes can be used as important markers for predicting patient prognosis and immunotherapy response. Our data suggest that ATP2A1 may promote the proliferation of colon cancer cells. These findings may provide new therapeutic targets for the treatment of colon cancer.

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“…Apart from this study, colorectal cancer is the most studied malignancy in relation to the CELF4 expression level and mutations. In this context, CELF4 has been identified as one of the reproducible prognostic RBPs in multiple investigations; however, the results are controversial [100][101][102][103]. CELF4 downregulation in colorectal cancer samples is detected through analysis of the Cancer Genome Atlas database (TCGA).…”

Section: Other Celf Membersmentioning

confidence: 99%

“…This gene, along with other RBP genes, has created a survival-related network with remarkable prognostic value [100][101][102]. On the other hand, the predictive study of the characteristics of RBPs in colorectal cancer highlights the significant role of CELF4 as an overexpressed transcript in highly metastatic SW620 cell lines [103].…”

Section: Other Celf Membersmentioning

confidence: 99%

CELF Family Proteins in Cancer: Highlights on the RNA-Binding Protein/Noncoding RNA Regulatory Axis

Aghdam

Jave‐Suárez

2021

IJMS

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Post-transcriptional modifications to coding and non-coding RNAs are unquestionably a pivotal way in which human mRNA and protein diversity can influence the different phases of a transcript’s life cycle. CELF (CUGBP Elav-like family) proteins are RBPs (RNA-binding proteins) with pleiotropic capabilities in RNA processing. Their responsibilities extend from alternative splicing and transcript editing in the nucleus to mRNA stability, and translation into the cytoplasm. In this way, CELF family members have been connected to global alterations in cancer proliferation and invasion, leading to their identification as potential tumor suppressors or even oncogenes. Notably, genetic variants, alternative splicing, phosphorylation, acetylation, subcellular distribution, competition with other RBPs, and ultimately lncRNAs, miRNAs, and circRNAs all impact CELF regulation. Discoveries have emerged about the control of CELF functions, particularly via noncoding RNAs, and CELF proteins have been identified as competing, antagonizing, and regulating agents of noncoding RNA biogenesis. On the other hand, CELFs are an intriguing example through which to broaden our understanding of the RBP/noncoding RNA regulatory axis. Balancing these complex pathways in cancer is undeniably pivotal and deserves further research. This review outlines some mechanisms of CELF protein regulation and their functional consequences in cancer physiology.

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RNA Binding Protein-Based Model for Prognostic Prediction of Colorectal Cancer

Cited by 14 publications

References 50 publications

Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction

Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction

m7G-Related DNA Damage Repair Genes are Potential Biomarkers for Predicting Prognosis and Immunotherapy Effectiveness in Colon Cancer Patients

CELF Family Proteins in Cancer: Highlights on the RNA-Binding Protein/Noncoding RNA Regulatory Axis

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