A new oxidative stress-related lncRNA signature predicts the prognosis of colorectal cancer patients

Figures

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  Fig. 1. GO and KEGG analyses of OS-related DEGs in cancer and adjacent tissues. A Volcano plot of 104 OS-related genes in CRC. Red and blue dots represent up-regulated and down-regulated genes, respectively. B Heat map of OS-related DEGs. C KEGG analysis of OS-related DEGs. D GO analysis of OS-related DEGs. GO, Gene Ontology; KEGG, Kyoto Encyclopaedia of Genes and Genomes; DEGs, differentially expressed genes; FC, fold change; FDR, false discovery rate; BP, biological process; CC, cellular components; MF, molecular function

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  Fig. 2. Expression and lncRNA–mRNA network of four OS-related lncRNAs in the predictive signature. A Expression of four OS-related lncRNAs in CRC and normal tissues. B The co-expression network of prognostic OS-related lncRNAs. C Sankey diagram of prognostic OS-based lncRNAs. lncRNA, long non-coding RNAs; N, normal; T, tumor

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  Fig. 3. Correlation between the predictive signature and prognosis of patients with CRC. A Kaplan–Meier analysis of the overall survival rate of patients with CRC in the high-risk and low-risk groups. B The distribution of risk score among patients with CRC. C The number of dead and alive patients with different risk scores. Blue and yellow represent the numbers of survivors and deaths, respectively. D Forest plot for univariate Cox regression analysis. E Forest plot for multivariate Cox regression analysis. F The ROC curve of the risk score and clinicopathological variables. G ROC curve and AUCs at 13- and 5-year survival for the predictive signature. CRC, colorectal carcinoma; ROC, receiver operating characteristic; AUC, area under the curve; T, tumor; N, lymph node

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  Fig. 4. Construction and verification of the nomogram. A Nomogram combining clinicopathological variables and risk scores to predict overall survival at 1, 2, 3, and 5 years of patients with CRC. B–E The calibration curves test the agreement of actual overall survival rates with predicted survival at 1, 2, 3, and 5 years

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  Fig. 5. Kaplan–Meier survival curves of high-risk and low-risk groups were classified according to different clinicopathological variables

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  Fig. 6. Internal validation of total survival prediction features based on the entire TCGA dataset. A Kaplan–Meier survival curve of the training cohort. B Kaplan–Meier survival curve of the test cohort. C ROC curves and AUC values for the training cohort’s 1-year, 3-year, and 5-year survival. D ROC curves and AUC values for the test cohort’s 1 -, 3 -, and 5-year survival. TCGA, Cancer Genome Atlas; ROC, receiver operating characteristics; AUC, area under the curve

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  Fig. 7. Patients in the high-risk and low-risk groups were divided into high-risk and low-risk groups with different immune statuses, immune infiltrating cells, and immune-related function scores. A Genome-wide distribution of patients. B OS-related gene set. C OS-related lncRNAs. D 4-lncRNA prognostic characteristics of OS. E Infiltration levels of 16 immune cells in high-risk and low-risk groups using the ssGSEA algorithm. F Correlation of predicted features with 13 immune-related functions. G Expression of immune checkpoints among high and low-risk groups. OS, oxidative stress; lncRNA, long non-coding RNA; ssGSEA, single sample gene set enrichment analysis; aDCs, activated dendritic cells; iDCs, immature dendritic cells; NK, natural killer; pDCs, plasmacytoid dendritic cells; Tfh, T follicular helper cells; Th1, type 1 helper T cells; TIL, tumor-infiltrating lymphocytes; Treg, regulatory T cells; APC, antigen-presenting cell; CCR, cytokine—cytokine receptor interaction; HLA, Human leukocyte antigen; MHC, major histocompatibility complex; IFN, interferon. *p < 0.05; **p < 0.01; ***p < 0.001; ns, not significant

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  Fig. 8. Comparison of sensitivity to treating drugs across high- and low-risk groups. A ABT.263. B AZD.0530. C BMS.509744. D CEP.701. E IGefitinib. F Imatinib. G PAC.1. H ISorafenib. I Shikonin

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  Fig. 9. Expression analysis and clinical relevance of four selected lncRNAs in tumor tissues. A Box plots showing the expression levels (log₂ TPM + 1) of four lncRNAs (AL161729.4, AL513550.1, LINC02474, and SNHG16) in tumor (red) versus normal (blue) tissues based on TCGA datasets. Expression differences were analyzed using a two-tailed t-test. B qRT-PCR validation of lncRNA expression in paired tumor (T, red) and adjacent normal (N, blue) tissues. Data are presented as mean ± SD. Statistical significance is indicated as: ***P < 0.001; **P < 0.01; ****P < 0.0001. C Line graph showing the correlation between tumor size (mm) and the relative expression levels of the four lncRNAs. Expression levels increase with tumor size, particularly after 40 mm. D Spline regression curves showing the relationship between lncRNA expression and TNM stage. The expression patterns of the lncRNAs vary across TNM stages, indicating potential involvement in tumor progression