Sarcopenia diagnosed with L3 SMI can be a negative predictor of postoperative and survival outcomes for non-metastatic CRC patients. Prospective studies with a uniform definition of sarcopenia are needed to update our findings.

Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer‐related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network. The module analysis was performed by the MCODE plug‐in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug‐in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.

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Colorectal cancer (CRC) ranks as one of the most commonly diagnosed malignancies worldwide. Although mortality rates have been decreasing, the prognosis of CRC patients is still highly dependent on the individual. Therefore, identifying and understanding novel biomarkers for CRC prognosis remains crucial. The gene expression profiles of five-gene expression omnibus (GEO) data sets of CRC were first downloaded. A total of 352 consistent differentially expressed genes (DEGs) were identified for CRC and paired with normal tissues. Functional analysis including gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment revealed that these DEGs were related to metabolic pathways, tight junctions, and the cell cycle. Ten hub DEGs were identified based on the search tool for the retrieval of interacting genes database and protein-protein interaction networks. By using univariate Cox proportional hazard regression analysis, we found 11 survival-related genes among these DEGs. We finally established a five-gene signature (kinesin family member 15, N-acetyltransferase 2, glutathione peroxidase 3, secretogranin II, and chloride channel accessory 1) with prognostic value in CRC by step multivariate Cox regression analysis. Based on this risk scoring system, patients in the high-risk group had significantly poorer survival results compared with those in the low-risk group (log-rank test, p < 0.0001). Finally, we validated our gene signature scoring system in two independent GEO cohorts (GSE17536 and GSE33113). We found all five of the signature genes to be DEGs in The Cancer Genome Atlas database. In conclusion, our findings suggest that our five DEG-based signature can provide a novel biomarker with useful applications in CRC prognosis.

Background: Many indicators of peripheral blood in routine blood test (BRT) results of colorectal cancer (CRC) patients are related to prognosis. Currently, indexes such as NLR (Neutrophil-to-Lymphocyte Ratio), PLR (Platelet-to-Lymphocyte Ratio) and LMR (Lymphocyte-to-Monocyte ratio) evaluate the survival risk of patients by assessing the inflammatory-immune status of CRCs. These indexes are more comprehensive and accurate than independent estimates. We hope to design more effective indexes through fully considering the correlation and significance between BRT indicators and prognosis, so as to play a guiding role in clinical malignant estimation of CRCs. Methods: 701 CRCs in training set and 256 CRCs in test set were included in the study samples, and their clinical data, tumor pathology results and peripheral blood routine results were collected. The prognosis, progression, and survival status of all patients were determined after follow-up. Above data were used for statistical analysis and designing new indexes. Results: It was found that high NE, MONO, RDW-CV/SD and PLT in peripheral blood indicated poor prognosis of DFS and OS. Conversely, CRCs with postoperative tumor progression or death had lower LY, EO, RBC, HGB, HCT, MCV, MCH, MCHC, PDW, and P-LCR. IRR, ARR and CRR related to infection, anemia and coagulation were designed respectively using the largest AUC indicators (P<0.05) selected by ROC curve. The formula: IRR= (NE*MONO)/(LY*EO); ARR= (HGB*MCHC)/RDW-CV; CRR=PLT/PDW. Results of Kaplan-Meier survival analysis and multivariate COX proportional hazard analysis adjusted for age, gender, TNM stage, infiltration, adhesion showed IRR, ARR, CRR were all able to be used as the evaluation standard of survival of CRC. The result was also authenticated in the test set. Conclusion: We designed three different prognostic indexes of colorectal cancer, IRR, ARR and CRR, which could be used as risk indicators of CRC prognosis, tumor progression and survival.

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