Angelica polysaccharides relieve blood glucose levels in diabetic KKAy mice possibly by modulating gut microbiota: an integrated gut microbiota and metabolism analysis.

BACKGROUND: Angelica polysaccharides (AP) have numerous benefits in relieving type 2 diabetes (T2D). However, the underlying mechanisms have yet to be fully understood. Recent many reports have suggested that altering gut microbiota can have adverse effects on the host metabolism and contribute to the development of T2D. Here, we successfully established the T2D model using the male KKAy mice with high-fat and high-sugar feed. Meanwhile, the male C57BL/6 mice were fed with a normal feed. T2D KKAy mice were fed either with or without AP supplementation. In each group, we measured the mice's fasting blood glucose, weight, and fasting serum insulin levels. We collected the cecum content of mice, the gut microbiota was analyzed by targeted full-length 16S rRNA metagenomic sequencing and metabolites were analyzed by untargeted-metabolomics. RESULTS: We found AP effectively alleviated glycemic disorders of T2D KKAy mice, with the changes in gut microbiota composition and function. Many bacteria species and metabolites were markedly changed in T2D KKAy mice and reversed by AP. Additionally, 16 altered metabolic pathways affected by AP were figured out by combining metagenomic pathway enrichment analysis and metabolic pathway enrichment analysis. The key metabolites in 16 metabolic pathways were significantly associated with the gut microbial alteration. Together, our findings showed that AP supplementation could attenuate the diabetic phenotype. Significant gut microbiota and gut metabolite changes were observed in the T2D KKAy mice and AP intervention. CONCLUSIONS: Administration of AP has been shown to improve the composition of intestinal microbiota in T2D KKAy mice, thus providing further evidence for the potential therapeutic application of AP in the treatment of T2D.

Copper in cancer: from limiting nutrient to therapeutic target.

As an essential nutrient, copper's redox properties are both beneficial and toxic to cells. Therefore, leveraging the characteristics of copper-dependent diseases or using copper toxicity to treat copper-sensitive diseases may offer new strategies for specific disease treatments. In particular, copper concentration is typically higher in cancer cells, making copper a critical limiting nutrient for cancer cell growth and proliferation. Hence, intervening in copper metabolism specific to cancer cells may become a potential tumor treatment strategy, directly impacting tumor growth and metastasis. In this review, we discuss the metabolism of copper in the body and summarize research progress on the role of copper in promoting tumor cell growth or inducing programmed cell death in tumor cells. Additionally, we elucidate the role of copper-related drugs in cancer treatment, intending to provide new perspectives for cancer treatment.

Single-cell RNA-seq and bulk RNA-seq explore the prognostic value of exhausted T cells in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains a worldwide health problem. Mounting evidence indicates that exhausted T cells play a critical role in the progress and treatment of HCC. Therefore, a detailed characterisation of exhausted T cells and their clinical significance warrants further investigation in HCC. Based on the GSE146115, we presented a comprehensive single-cell Atlas in HCC. Pseudo-time analysis revealed that tumour heterogeneity progressively increased, and the exhausted T cells gradually appeared during tumour progression. Functional enrichment analysis revealed that the evolutionary process of exhausted T cells mainly contained the pathway of cadherin binding, proteasome, cell cycle, and T cell receptor regulation of apoptosis. In the International Cancer Genome Consortium database, we divided patients into three clusters with the T cell evolution-associated genes. We found that the exhausted T cells are significantly related to poor outcomes through immunity and survival analysis. In The Cancer Genome Atlas database, the authors enrolled weighted gene co-expression network analysis, univariate Cox analysis, and Lasso Cox analysis, then screened the 19 core genes in T cells evolution and built a robust prognostic model. This study offers a fresh view on evaluating the patients' outcomes from an exhausted T cells perspective and might help clinicians develop therapeutic systems.

Prognostic and Immunological Significance of the Molecular Subtypes and Risk Signatures Based on Cuproptosis in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) remains a challenging medical problem. Cuproptosis is a novel form of cell death that plays a crucial role in tumorigenesis, angiogenesis, and metastasis. However, it remains unclear whether cuproptosis-related genes (CRGs) influence the outcomes and immune microenvironment of HCC patients. Method: From The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, we obtained the mRNA expression file and related clinical information of HCC patients. We selected 19 CRGs as candidate genes for this study according to previous literature. We performed a differential expression analysis of the 19 CRGs between malignant and precancerous tissue. Based on the 19 CRGs, we enrolled cluster analysis to identify cuproptosis-related subtypes of HCC patients. A prognostic risk signature was created utilizing univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. We employed independent and stratification survival analyses to investigate the predictive value of this model. The functional enrichment features, mutation signatures, immune profile, and response to immunotherapy of HCC patients were also investigated according to the two molecular subtypes and the prognostic signature. Results: We found that 17 CRGs significantly differed in HCC versus normal samples. Cluster analysis showed two distinct molecular subtypes of cuproptosis. Cluster 1 is preferentially related to poor prognosis, high activity of immune response signaling, high mutant frequency of TP53, and distinct immune cell infiltration versus cluster 2. Through univariate and LASSO Cox regression analyses, we created a cuproptosis-related prognostic risk signature containing LIPT1, DLAT, MTF1, GLS, and CDKN2A. High-risk HCC patients were shown to have a worse prognosis. The risk signature was proved to be an independent predictor of prognosis in both the TCGA and ICGC datasets, according to multivariate analysis. The signature also performed well in different stratification of clinical features. The immune cells, which included regulatory T cells (Treg), B cells, macrophages, mast cells, NK cells, and aDCs, as well as immune functions containing cytolytic activity, MHC class I, and type II IFN response, were remarkably distinct between the high-risk and low-risk groups. The tumor immune dysfunction and exclusion (TIDE) score suggested that high-risk patients had a higher response rate to immune checkpoint inhibitors than low-risk patients. Conclusion: This research discovered the potential prognostic and immunological significance of cuproptosis in HCC, improved the understanding of cuproptosis, and may deliver new directions for developing more efficacious therapeutic techniques for HCC patients.

Construction and Validation of a Protein-associated Prognostic Model for Gastrointestinal Cancer.

Background Gastrointestinal cancer (GIC) is a prevalent and lethal malignant tumor. It is obligatory to investigate innovative biomarkers for the diagnosis and prognosis. Proteins play a crucial role in regulating the occurrence and progression of GIC. However, the prognostic value of proteins is unclear in GIC. OBJECTIVE: This paper aims to identify the hub prognosis-related proteins (PAPs) and construct a prognosis model for GIC patients for clinical application. METHODS: Protein expression data of GIC was obtained from The Cancer Proteome Atlas (TCPA) and downloaded the clinicopathological data from The Cancer Genome Atlas database (TCGA). Besides, hub proteins were filtrated via univariate and multivariate Cox regression analysis. Moreover, survival analysis and nomogram were used to predict overall survival (OS). We used the calibration curves to assess the consistency of predictive and actual survival rates. The consistency index (C-index) was used to evaluate the prognostic ability of the predictive model. Furthermore, functional enrichment analysis and protein co-expression of PAPs were used to explore their roles in GIC. RESULTS: Finally, a prognosis model was conducted based on ten PAPs (CYCLIND1, DVL3, NCADHERIN, SYK, ANNEXIN VII, CD20, CMET, RB, TFRC, and PREX1). The risk score calculated by the model was an independent prognostic predictor. Compared with the high-risk subgroup, the low-risk subgroup had better OS. In the TCGA cohort, the area under the curve value of the receiver operating characteristic curve of the prognostic model was 0.692. The expression of proteins and risk score had a significant association with the clinicopathological characteristics of GIC. Besides, a nomogram based on GIC clinicopathological features and risk scores could properly predict the OS of individual GIC patients. The C-index is 0.71 in the TCGA cohort and 0.73 in the GEO cohort. CONCLUSION: The results indicate that the risk score is an independent prognostic biomarker and is related to the malignant clinical features of GIC patients. Besides, several PAPs associated with the survival and clinicopathological characteristics of GIC might be potential biomarkers for GIC diagnosis and treatment.

Role of gasdermin family proteins in the occurrence and progression of hepatocellular carcinoma.

Primary liver cancer is the sixth most common cancer and the third leading cause of cancer mortality worldwide, hepatocellular carcinoma (HCC) is the most common type of liver cancer, accounting for 75%-85% of cases. The occurrence and progression of HCC involve multiple events. Pyroptosis is a gasdermins mediated programmed cell death and is intricately associated with cancerogenesis, including HCC. This review mainly concerns the recent research advances of the gasdermin family members in HCC. The biological roles and specific expression patterns of the family members are discussed, especially those that are involved in the regulatory pathways in the occurrence and progression of HCC. We provide the latest progress into the distinct molecular mechanisms of gasdermin family members involved in the occurrence and development of HCC.

Prognostic role of expression of angiogenesis markers in hepatocellular carcinoma: A bioinformatics analysis.

The expression of angiopoietin (ANGPT) 1, ANGPT2, vascular endothelial growth factor (VEGF) A, VEGFB, VEGFC, VEGFD, and placental growth factor (PGF) is significantly higher in tumor tissues than in normal tissues in both unpaired and paired hepatocellular carcinoma (HCC) samples. ANGPT2, VEGFB, VEGFC, and PGF are primarily involved in regulating the activation of the epithelial-mesenchymal transition pathway; ANGPT1 is primarily involved in regulating the activation of the RAS/mitogen-activated protein kinase and receptor tyrosine kinase (RTK) pathways; VEGFA is engaged in regulating the RTK activation pathway; and VEGFD is mainly involved in regulating the activation of the tuberous sclerosis protein/mammalian target of rapamycin pathway. There is a significant difference in overall survival between HCC patients with high and low expression of ANGPT2, PGF, VEGFA, and VEGFD. Disease free survival (DFS) is significantly shorter in HCC patients with high ANGPT2, PGF, and VEGFA expression than in those with low ANGPT2, PGF, and VEGFA expression.

Prevention of late complications of endoscopic resection of colorectal lesions with a coverage agent: Current status of gastrointestinal endoscopy.

Endoscopic ectomy of large nonpedunculated colorectal lesions (≥ 20 mm) might cause significant adverse incidents, such as delayed perforation and delayed bleeding, despite the closure of mucosal lesions with clips. The conventional utilization of prophylactic clipping has not decreased the risk of postprocedural delayed adverse events, and additional outcomes and cost-effectiveness research is needed for patients with proximal lesions ≥ 20 mm, in whom prophylactic clipping might be useful. Coverage of the wound after endoscopic excision offers shield protection against delayed concomitant diseases.

Construction and validation of m6 A RNA methylation regulators associated prognostic model for gastrointestinal cancer.

N6-methyladenosine (m6 A) RNA methylation is correlated with carcinogenesis and dynamically possessed through the m6 A RNA methylation regulators. This paper aimed to explore 13 m6 A RNA methylation regulators' role in gastrointestinal cancer (GIC) and determine the risk model and prognosis value of m6 A RNA methylation regulators in GIC. We used several bioinformatics methods to identify the differential expression of m6 A RNA methylation regulators in GIC, constructed a prognostic model, and carried out functional enrichment analysis. Eleven of 13 m6 A RNA methylation regulators were differentially expressed in different clinicopathological characteristics of GIC, and m6 A RNA methylation regulators were nearly associated with GIC. We constructed a risk model based on five m6 A RNA methylation regulators (METTL3, FTO, YTHDF1, ZC3H13, and WTAP); the risk score is an independent prognosis biomarker. Moreover, the five m6 A RNA methylation regulators can also forecast the 1-, 3- and 5-year overall survival through a nomogram. Furthermore, four hallmarks of oxidative phosphorylation, glycolysis, fatty acid metabolism, and cholesterol homoeostasis gene sets were significantly enriched in GIC. m6 A RNA methylation regulators were related to the malignant clinicopathological characteristics of GIC and may be used for prognostic stratification and development of therapeutic strategies.

Comment on "Outcomes of curative liver resection for hepatocellular carcinoma in patients with cirrhosis".

The present letter to the editor is in response to the research "Outcomes of curative liver resection for hepatocellular carcinoma in patients with cirrhosis" by Elshaarawy et al in World J Gastroenterol 2021; 13(5): 424-439. The preoperative assessment of the liver reserve function in hepatocellular carcinoma (HCC) patients with cirrhosis is crucial, and there is no universal consensus on how to assess it. Based on a retrospective study, Elshaarawy et al investigated the impact of various classical clinical indicators on liver failure and the prognosis after hepatectomy in HCC patients with cirrhosis. We recommend that we should strive to explore new appraisal indicators, such as the indocyanine green retention rate at 15 min.

Prognostic implications of ferroptosis-associated gene signature in colon adenocarcinoma.

BACKGROUND: Colon adenocarcinoma (COAD) is one of the most common and fatal malignant tumors, which increases the difficulty of prognostic predictions. Thus, new biomarkers for the diagnosis and prognosis of COAD should be explored. Ferroptosis is a recently identified programmed cell death process that has the characteristics of iron-dependent lipid peroxide accumulation. However, the predictive value of ferroptosis-related genes (FRGs) for COAD still needs to be further clarified. AIM: To identify some critical FRGs and construct a COAD patient prognostic signature for clinical utilization. METHODS: The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus databases were the data sources for mRNA expression and corresponding COAD patient clinical information. Differentially expressed FRGs were recognized using R and Perl software. We constructed a multi-FRG signature of the TCGA-COAD cohort by performing a univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis. COAD patients from the Gene Expression Omnibus cohort were utilized for verification. RESULTS: Our research showed that most of the FRGs (85%) were differentially expressed between the corresponding adjacent normal tissues and cancer tissues in the TCGA-COAD cohort. Seven FRGs were related to overall survival (OS) in the univariate Cox analysis (all P < 0.05). A model with five FRGs (AKR1C1, AKR1C3, ALOX12, CRYAB, and FDFT1) was constructed to divide patients into high- and low-risk groups. The OS of patients in the high-risk group was significantly lower than that of the low-risk group (all P < 0.01 in the TCGA and Gene Expression Omnibus cohorts). The risk score was an independent prognosticator of OS in the multivariate Cox analysis (hazard ratio > 1, P < 0.01). The predictive capacity of the model was verified by a receiver operating characteristic curve analysis. In addition, a nomogram based on the expression of five hub FRGs and risk score can precisely predict the OS of individual COAD cancer patients. Immune correlation analysis and functional enrichment analysis results revealed that immunology-related pathways were abundant, and the immune states of the high-risk group and the low-risk group were different. CONCLUSION: In conclusion, a novel five FRG model can be utilized for predicting prognosis in COAD. Targeting ferroptosis may be a treatment option for COAD.

Identification of Mutator-Derived lncRNA Signatures of Genomic Instability for Promoting the Clinical Outcome in Hepatocellular Carcinoma.

BACKGROUND: Accumulating evidence proves that long noncoding RNA (lncRNA) plays a crucial role in maintaining genomic instability. However, it is significantly absent from exploring genomic instability-associated lncRNAs and discovering their clinical significance. OBJECTIVE: To identify crucial mutator-derived lncRNAs and construct a predictive model for prognosis and genomic instability in hepatocellular carcinoma. METHODS: First, we constructed a mutator hypothesis-derived calculative framework through uniting the lncRNA expression level and somatic mutation number to screen for genomic instability-associated lncRNA in hepatocellular carcinoma. We then selected mutator-derived lncRNA from the genome instability-associated lncRNA by univariate Cox analysis and Lasso regression analysis. Next, we created a prognosis model with the mutator-derived lncRNA signature. Furthermore, we verified the vital role of the model in the prognosis and genomic instability of hepatocellular carcinoma patients. Finally, we examined the potential relationship between the model and the mutation status of TP53. RESULTS: In this study, we screened 88 genome instability-associated lncRNAs and built a prognosis model with four mutator-derived lncRNAs. Moreover, the model was an independent predictor of prognosis and an accurate indicator of genomic instability in hepatocellular carcinoma. Finally, the model could catch the TP53 mutation status, and the model was a more effective indicator than the mutation status of TP53 for hepatocellular carcinoma patients. CONCLUSION: This research adopted a reliable method to analyze the role of lncRNA in genomic instability. Besides, the prognostic model with four mutator-derived lncRNAs is an excellent new indicator of prognosis and genomic instability in hepatocellular carcinoma. In addition, this finding may help clinicians develop therapeutic systems.

Metabolism-associated genes in occurrence and development of gastrointestinal cancer: Latest progress and future prospect.

Gastrointestinal (GI) cancer remains one of the most prevalent cancers in the world. The occurrence and progression of GI cancer involve multiple events. Metabolic reprogramming is one of the hallmarks of cancer and is intricately related to tumorigenesis. Many metabolic genes are involved in the occurrence and development of GI cancer. Research approaches combining tumor genomics and metabolomics are more likely to provide deeper insights into this field. In this paper, we review the roles of metabolism-associated genes, especially those involved in the regulation pathways, in the occurrence and progression of GI cancer. We provide the latest progress and future prospect into the different molecular mechanisms of metabolism-associated genes involved in the occurrence and development of GI cancer.

Construction and validation of an RNA-binding protein-associated prognostic model for colorectal cancer.

Colorectal cancer (CRC) is one of the most prevalent and fatal malignancies, and novel biomarkers for the diagnosis and prognosis of CRC must be identified. RNA-binding proteins (RBPs) are essential modulators of transcription and translation. They are frequently dysregulated in various cancers and are related to tumorigenesis and development. The mechanisms by which RBPs regulate CRC progression are poorly understood and no clinical prognostic model using RBPs has been reported in CRC. We sought to identify the hub prognosis-related RBPs and to construct a prognostic model for clinical use. mRNA sequencing and clinical data for CRC were obtained from The Cancer Genome Atlas database (TCGA). Gene expression profiles were analyzed to identify differentially expressed RBPs using R and Perl software. Hub RBPs were filtered out using univariate Cox and multivariate Cox regression analysis. We used functional enrichment analysis, including Gene Ontology and Gene Set Enrichment Analysis, to perform the function and mechanisms of the identified RBPs. The nomogram predicted overall survival (OS). Calibration curves were used to evaluate the consistency between the predicted and actual survival rate, the consistency index (c-index) was calculated, and the prognostic effect of the model was evaluated. Finally, we identified 178 differently expressed RBPs, including 121 up-regulated and 57 down-regulated proteins. Our prognostic model was based on nine RBPs (PNLDC1, RRS1, HEXIM1, PPARGC1A, PPARGC1B, BRCA1, CELF4, AEN and NOVA1). Survival analysis showed that patients in the high-risk subgroup had a worse OS than those in the low-risk subgroup. The area under the curve value of the receiver operating characteristic curve of the prognostic model is 0.712 in the TCGA cohort and 0.638 in the GEO cohort. These results show that the model has a moderate diagnostic ability. The c-index of the nomogram is 0.77 in the TCGA cohort and 0.73 in the GEO cohort. We showed that the risk score is an independent prognostic biomarker and that some RBPs may be potential biomarkers for the diagnosis and prognosis of CRC.

A pan-cancer analysis of the HER family gene and their association with prognosis, tumor microenvironment, and therapeutic targets.

AIMS: The human epidermal growth factor receptor (HER) family gene is involved in a wide range of biological functions in human cancers. Nevertheless, there is little research that comprehensively analysis the correlation between HER family members and prognosis, tumor microenvironment (TME) in different cancers. MATERIALS AND METHODS: Based on updated public databases and integrated several bioinformatics analysis methods, we evaluated expression level, prognostic values of HER family gene and explore the association between expression of HER family gene and TME, Stemness score, immune subtype, drug sensitivity in pan-cancer. KEY FINDINGS: EGFR, ERBB2, ERBB3, and ERBB4 were higher expressed in four cancers, five cancers, ten cancers, and two cancers, respectively. HER family gene expression is related to the prognosis in several cancers from TCGA and has a significant correlation with stromal and immune scores in pan-cancer also has a significant correlation with RNA stemness score and DNA stemness score in pan-cancer. Expression level of HER family gene is associated with immune subtype in head and neck squamous cell carcinoma and kidney renal clear cell carcinoma. EGFR expression was negatively associated with drug sensitivity of Pipamperone, Tamoxifen, Bafetinib and positively related to drug sensitivity of Dasatinib and Staurosporine. ERBB2 expression was negatively related to drug sensitivity of Ifosfamide, Imexon, and Oxaliplatin. ERBB4 expression was positively related to drug sensitivity of E-7820. SIGNIFICANCE: These findings may elucidate the roles played by HER family gene in cancer progression and providing insights for further investigation of the HER family gene as potential targets in pan-cancer.

Microarray analysis to explore the effect of CXCL12 isoforms in a pancreatic pre-tumor cell model.

CXCL12 expression was significantly lower in tumor samples than in corresponding normal samples. CXCL12 expression was significantly positively related to the infiltration levels of T cells, dendritic cells (DCs), immature DCs, cytotoxic cells, Tfh cells, mast cells, B cells, Th1 cells, natural killer (NK) cells, pDCs, neutrophils, and T helper cells (Spearman correlation coefficient > 0.5, P < 0.001) and negatively correlated with the infiltration level of NK CD56bright cells. In addition, pancreatic hTERT-HPNE cells treated with three diverse CXCL12 isoforms exhibited changes mainly in the regulation of the epithelial-mesenchymal transition activation pathway.

Identification prognosis-associated immune genes in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is one of the most prevalent malignant tumors worldwide. Immune genes (IGs) have a considerable correlation with tumor initiation and prognosis. The present paper aims to identify the prognosis value of IGs in COAD and conduct a prognosis model for clinical utility. Gene expression data of COAD were downloaded from The Cancer Genome Atlas (TCGA), screening and analyzing differentially expressed IGs by bioinformatics. Core genes were screened by univariate and multivariate Cox regression analyses. Survival analysis was appraised by the Kaplan-Meier method and the log-rank test. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis (GSEA) were used to identify IGs' relevant signal pathways. We predicted the overall survival (OS) by nomogram. Finally, a prognosis model was conducted based on 12 IGs (SLC10A2, CXCL3, NOX4, FABP4, ADIPOQ, IGKV1-33, IGLV6-57, INHBA, UCN, VIP, NGFR, and TRDC). The risk score was an independent prognostic factor, and a nomogram could accurately predict the OS of individual COAD patients. These results were validated in GSE39582, GSE12945, and GSE103479 cohorts. Functional enrichment analysis demonstrated that these IGs are mainly enriched in hormone secretion, hormone transport, lipid transport, cytokine-cytokine receptor interaction, and peroxisome proliferators-activated receptor signaling pathway. In summary, the risk score is an independent prognostic biomarker. We also excavated several IGs related to COAD's survival and maybe potential biomarkers for COAD diagnosis and treatment.

Construction prognosis model based on autophagy-related gene signatures in hepatocellular carcinoma.

Aim: To develop robust and accurate prognostic biomarkers to help clinicians optimize therapeutic strategies. Materials & methods: Differentially prognosis-related autophagy genes were identified by bioinformatics analysis method. Results: Seven prognosis-related autophagy genes were more significantly related to the prognosis of hepatocellular carcinoma (HCC). Functional enrichment analysis demonstrated that these genes were mainly enriched in the autophagy pathway. BIRC5, HSPB8 and TMEM74 exhibited significant prognostic value for HCC. Besides, the risk score and BIRC5 have significant significance with clinicopathological significance of HCC. Conclusion: The research has identified a number of prognosis-related autophagy genes that associated with the survival and clinical stage of HCC. In addition, the prognostic model can be used to calculate the patient's risk score and these prognosis-related autophagy genes might serve as therapeutic targets.

Prognostic value and immunological role of PDCD1 gene in pan-cancer.

OBJECTIVE: Identify the prognostic value and investigate the association between programmed cell death 1 (PDCD1) gene expression and immune infiltration in pan-cancer. METHODS: We used a series of bioinformatics methods to comprehensively analyze the relationship between PDCD1 gene and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), immune cell infiltration of various cancers from the existing public database, and try to find the potential prognostic value of PDCD1 for in pan-cancer. RESULTS: High expression of PDCD1 was closely related to better overall survival (OS) and disease-specific survival (DSS) in breast invasive carcinoma, head and neck squamous cell carcinoma, skin cutaneous melanoma, and uterine corpus endometrial carcinoma; have a better disease-free interval (DFI) and progression-free interval (PFI) in several cancer types. Meanwhile, the high level of PDCD1 gene expression was associated with poorer OS, DSS, and PFI in brain lower grade glioma and uveal melanoma; poorer OS in acute myeloid leukemia and kidney renal papillary cell carcinoma; poorer OS and DSS in glioblastoma multiforme; poorer DSS in kidney renal clear cell carcinoma, by Kaplan-Meier and Cox survival analysis. PDCD1 gene expression was significantly correlated with TMB and MSI in 14 and 12 cancer types, respectively, and infiltrating levels of immune cells, especially Macrophages M0, M1, CD4-T-cells, CD8-T-cells, and T cells follicular helper, in most of eight cancer types. CONCLUSION: PDCD1 can be used as a prognostic marker in multiple cancers, owing to it is closely associated with TMB, MSI, and immune cells infiltration.

Identification of prognosis-associated immune genes and exploration of immune cell infiltration in colorectal cancer.

Aim: To identify prognosis-related immune genes (PRIGs) and construct a prognosis model of colorectal cancer (CRC) patients for clinical use. Materials & methods: Expression profiles were obtained from The Cancer Genome Atlas database and identified differentially expressed PRIGs of CRC. Results: A prognostic model was conducted based on nine PRIGs. The risk score, based on prognosis model, was an independent prognostic predictor. Five PRIGs and risk score were significantly associated with the clinical stage of CRC and five immune cells related to the risk score. Conclusion: The risk score was an independent prognostic biomarker for CRC patients. The research excavated immune genes that were associated with survival and that could be potential biomarkers for prognosis and treatment for CRC patients.