Identification and validation of Rab GTPases RAB13 as biomarkers for peritoneal metastasis and immune cell infiltration in colorectal cancer patients
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SUBMITTER: Lv F
PROVIDER: S-EPMC11347351 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Immunoscore can accurately predict the prognosis of patients with stage I-III colorectal cancer. However, whether it can be used to predict the prognosis of colorectal cancer peritoneal metastases (CRCPM) remains to be validated. We analyzed peritoneal and ovarian metastases in 68 patients with CRCPM. The immunoscore (IS) was based on the infiltration level of CD3+ and CD8+ T cells, whereas the TBM score was derived from the infiltration level of CD3+, CD8+, CD20+ and CD163+ cells to tumor microenvironment (TME). The predictive value of IS and TBM scores for relapse-free survival (RFS) and overall survival (OS) of patients with CRCPM was analyzed using Kaplan Meier curve and Cox multivariate models. Significant difference in the infiltration levels of different immune cell subtypes in primary lesions, peritoneal metastasis and ovarian metastasis were compared using t-test.CRCPM patients with high IS (>1), high TBM1 score (≥2) or high TBM2 score (≥2) had a significantly longer OS (IS: median OS, not reached vs 23 months, p = .0078; TBM1: not reached vs 21.5 months, p = .013; TBM2: 39.3 months vs 15.2 months, p = .001). On the other hand, patients with high IS had a trend of improved RFS (13.4 months vs 11.0 months, p = .067). However, TBM1 and TBM2 score has no predictive utility for RFS. Multivariate analysis revealed that IS, TBM1 and TBM2 can accurately predict OS, but not RFS. Finally, the infiltration level of CD3+ T cells, CD8+ T cells, CD20+ B cells, and CD68+ macrophage was significantly higher in peritoneal metastatic tissue and ovarian metastatic tissue, relative to primary tumor tissues.The IS and TBM score of peritoneal metastases could effectively predict OS of patients with CRCPM. Peritoneal metastasis of colorectal cancer decreased the infiltration level of T and B cells.
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Project description:PurposeSynchronous peritoneal metastasis (S-PM) is considered a poor prognostic factor for colorectal cancer (CRC) and there is no nomogram to predict the survival of these patients. In this study, we aimed to use a multicenter data to identify the factors associated with S-PM of CRC to construct a nomogram for predicting the overall survival (OS) of these patients.MethodsCRC patients with S-PM from two medical centers were enrolled between September 2007 and June 2017. Multivariate analysis was used to identify independent factors associated with OS for the nomogram to predict the 1-, 2-, and 3-year OS rates in the development group. The concordance index (C-index), calibration plot, relative operating characteristic (ROC) curve with area under the curve (AUC) were calculated to evaluate the performance of the nomogram in both the development and an external validation group.Results277 CRC patients with S-PM in the development group and 68 patients in the validation group were eligible for this study. In multivariate analysis of development group, age, carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), cytoreductive surgery (CRS), hyperthermic intraperitoneal chemotherapy (HIPEC), and chemotherapy were independent variables for OS, based on which the nomogram was built. The C-index of the nomogram in the development and validation group was 0.701 (95% Cl, 0.666-0.736) and 0.716 (95% Cl, 0.622-0.810); demonstrating good discriminative ability. The calibration plots showed satisfactory consistency between actual observation and nomogram-predicted OS probabilities in the development and external validation group. The nomogram showed good predictive accuracy for 1-, 2-, and 3-year OS rates in both groups with AUC >0.70. An online dynamic webserver was also developed for increasing the ease of the nomogram.ConclusionsWe developed and validated a predictive nomogram with good discriminative and high accuracy to predict the OS in CRC patients with S-PM.
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Project description:Diabetes mellitus (DM) can lead to diabetic ulcers (DUs), which are the most severe complications. Due to the need for more accurate patient classifications and diagnostic models, treatment and management strategies for DU patients still need improvement. The difficulty of diabetic wound healing is caused closely related to biological metabolism and immune chemotaxis reaction dysfunction. Therefore, the purpose of our study is to identify metabolic biomarkers in patients with DU and construct a molecular subtype-specific prognostic model that is highly accurate and robust. RNA-sequencing data for DU samples were obtained from the Gene Expression Omnibus (GEO) database. DU patients and normal individuals were compared regarding the expression of metabolism-related genes (MRGs). Then, a novel diagnostic model based on MRGs was constructed with the random forest algorithm, and classification performance was evaluated utilizing receiver operating characteristic (ROC) analysis. The biological functions of MRGs-based subtypes were investigated using consensus clustering analysis. A principal component analysis (PCA) was conducted to determine whether MRGs could distinguish between subtypes. We also examined the correlation between MRGs and immune infiltration. Lastly, qRT-PCR was utilized to validate the expression of the hub MRGs with clinical validations and animal experimentations. Firstly, 8 metabolism-related hub genes were obtained by random forest algorithm, which could distinguish the DUs from normal samples validated by the ROC curves. Secondly, DU samples could be consensus clustered into three molecular classifications by MRGs, verified by PCA analysis. Thirdly, associations between MRGs and immune infiltration were confirmed, with LYN and Type 1 helper cell significantly positively correlated; RHOH and TGF-β family remarkably negatively correlated. Finally, clinical validations and animal experiments of DU skin tissue samples showed that the expressions of metabolic hub genes in the DU groups were considerably upregulated, including GLDC, GALNT6, RHOH, XDH, MMP12, KLK6, LYN, and CFB. The current study proposed an auxiliary MRGs-based DUs model while proposing MRGs-based molecular clustering and confirmed the association with immune infiltration, facilitating the diagnosis and management of DU patients and designing individualized treatment plans.
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Project description:Immune-associated biomarkers can predict lung metastases from colorectal cancer. Differentially expressed genes (DEGs) were screened from sample data extracted from gene expression omnibus (GEO) database. The DEGs were screened from the lung metastasis (LM) and primary cancer (PC) groups of the Moffitt Cancer Center cohort dataset. Then, the tumor immune microenvironment and abundance of immune cell infiltration analyses were performed, and the immune-related DEGs were retrieved. In addition, the transcription factor (TF)-miRNA-mRNA network was constructed and enrichment analyses of the immune-related DEGs and upregulated and downregulated DEGs were carried out. Then, the protein-protein interaction (PPI) network was conducted and the drug-gene interaction was predicted. A total of 268 DEGs were screened. The Immune_Score of samples in the LM group was significantly higher compared with the PC group. The infiltration ratio of M0 macrophages and M2 macrophages of samples was higher than others. A total of 54 immune-related DEGs in M0 macrophages were screened. Moreover, the TF-miRNA-mRNA network was constructed among 8 miRNA-mRNA and 50 TF-mRNA, and the secreted phosphoprotein 1 was regulated by 12 TFs, and the oxidized low-density lipoprotein receptor 1 was regulated by 3 miRNAs and 3 TFs. The TF SAM pointed domain containing ETS TF was also a downregulated DEG. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the DEGs in the TF-miRNA-mRNA network were mainly involved in the interleukin-7 signaling pathway and cell adhesion molecules. In total, 23 protein interactions in this PPI network of M0 macrophage cells were involved in 27 mRNAs. There were 38 drug-gene interactions of immune-related DEGs of M0 macrophage cells predicted to contain 34 small molecule drugs and 8 mRNAs. Finally, the CON cohort dataset verified that the infiltration ratio of M0 and M2 macrophages of the samples was higher.
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