Identification of BGN positive fibroblasts as a driving factor for colorectal cancer and development of its related prognostic model combined with machine learning.

BACKGROUND: Numerous studies have indicated that cancer-associated fibroblasts (CAFs) play a crucial role in the progression of colorectal cancer (CRC). However, there are still many unknowns regarding the exact role of CAF subtypes in CRC. METHODS: The data for this study were obtained from bulk, single-cell, and spatial transcriptomic sequencing data. Bioinformatics analysis, in vitro experiments, and machine learning methods were employed to investigate the functional characteristics of CAF subtypes and construct prognostic models. RESULTS: Our study demonstrates that Biglycan (BGN) positive cancer-associated fibroblasts (BGN + Fib) serve as a driver in colorectal cancer (CRC). The proportion of BGN + Fib increases gradually with the progression of CRC, and high infiltration of BGN + Fib is associated with poor prognosis in terms of overall survival (OS) and recurrence-free survival (RFS) in CRC. Downregulation of BGN expression in cancer-associated fibroblasts (CAFs) significantly reduces migration and proliferation of CRC cells. Among 101 combinations of 10 machine learning algorithms, the StepCox[both] + plsRcox combination was utilized to develop a BGN + Fib derived risk signature (BGNFRS). BGNFRS was identified as an independent adverse prognostic factor for CRC OS and RFS, outperforming 92 previously published risk signatures. A Nomogram model constructed based on BGNFRS and clinical-pathological features proved to be a valuable tool for predicting CRC prognosis. CONCLUSION: In summary, our study identified BGN + Fib as drivers of CRC, and the derived BGNFRS was effective in predicting the OS and RFS of CRC patients.

A hypoxia-glycolysis-lactate-related gene signature for prognosis prediction in hepatocellular carcinoma.

BACKGROUND: Liver cancer ranks sixth in incidence and third in mortality globally and hepatocellular carcinoma (HCC) accounts for 90% of it. Hypoxia, glycolysis, and lactate metabolism have been found to regulate the progression of HCC separately. However, there is a lack of studies linking the above three to predict the prognosis of HCC. The present study aimed to identify a hypoxia-glycolysis-lactate-related gene signature for assessing the prognosis of HCC. METHODS: This study collected 510 hypoxia-glycolysis-lactate genes from Molecular Signatures Database (MSigDB) and then classified HCC patients from TCGA-LIHC by analyzing their hypoxia-glycolysis-lactate genes expression. Differentially expressed genes (DEGs) were screened out to construct a gene signature by LASSO-Cox analysis. Univariate and multivariate regression analyses were used to evaluate the independent prognostic value of the gene signature. Analyses of immune infiltration, somatic cell mutations, and correlation heatmap were conducted by "GSVA" R package. Single-cell analysis conducted by "SingleR", "celldex", "Seurat", and "CellCha" R packages revealed how signature genes participated in hypoxia/glycolysis/lactate metabolism and PPI network identified hub genes. RESULTS: We classified HCC patients from TCGA-LIHC into two clusters and screened out DEGs. An 18-genes prognostic signature including CDCA8, CBX2, PDE6A, MED8, DYNC1LI1, PSMD1, EIF5B, GNL2, SEPHS1, CCNJL, SOCS2, LDHA, G6PD, YBX1, RTN3, ADAMTS5, CLEC3B, and UCK2 was built to stratify the risk of HCC. The risk score of the hypoxia-glycolysis-lactate gene signature was further identified as a valuable independent factor for estimating the prognosis of HCC. Then we found that the features of clinical characteristics, immune infiltration, somatic cell mutations, and correlation analysis differed between the high-risk and low-risk groups. Furthermore, single-cell analysis indicated that the signature genes could interact with the ligand-receptors of hepatocytes/fibroblasts/plasma cells to participate in hypoxia/glycolysis/lactate metabolism and PPI network identified potential hub genes in this process: CDCA8, LDHA, YBX1. CONCLUSION: The hypoxia-glycolysis-lactate-related gene signature we built could provide prognostic value for HCC and suggest several hub genes for future HCC studies.

FBXO31 is upregulated by METTL3 to promote pancreatic cancer progression via regulating SIRT2 ubiquitination and degradation.

FBXO31, a member of F-box family to comprise of SCF complex, contributes to a pivotal role in cancer progression. However, the possible involvements of FBXO31 in PC are unelucidated. Here, we reported that FBXO31 was overexpressed in PC patients, which was negatively associated with survival in PC patients. Furthermore, FBXO31 significantly enhanced growth, migration and invasion of PC cells in vitro. Consistently, FBXO31 overexpression promoted tumor growth in nude mice. Mechanistically, SIRT2 was a target of FBXO31 and interacted with FBXO31. Protein half-life and ubiquitination analysis demonstrated that FBXO31 promoted proteasome-dependent degradation of SIRT2. In addition, FBXO31 binds to sirtuin-type domain of SIRT2. Moreover, SIRT2 is required for the oncogenic role of FBXO31 in PC progression. Impressively, METTL3 induced m6A modification of FBXO31 and up-regulated FBXO31 expression, subsequently leading to SIRT2 down-regulation in PC cells. The results showed that METTL3 enhanced FBXO31 mRNA translation in YTHDF1-dependent manner. Taken together, we suggest that METTL3-FBXO31-SIRT2 axis was involved in PC tumorigenesis, which could identify new targets for PC treatment.

Comprehensive Analysis of METTLs (METTL1/13/18/21A/23/25/2A/2B/5/6/9) and Associated mRNA Risk Signature in Hepatocellular Carcinoma.

Currently, 80%-90% of liver cancers are hepatocellular carcinomas (HCC). HCC patients develop insidiously and have an inferior prognosis. The methyltransferase-like (METTL) family principal members are strongly associated with epigenetic and tumor progression. The present study mainly analyzed the value of METTLs (METTL1/13/18/21A/23/25/2A/2B/5/6/9) and associated mRNA risk signature for HCC. METTLs expression is upregulated in HCC and is a poor prognostic factor in HCC. METTLs were upregulated in patients older than 60 and associated with grade. Except for METTL25, the remaining 10 genes were associated with the HCC stage, invasion depth (T). In addition, METTLs showed an overall alteration rate of 50%. Except for METTL13/2A/25/9, the expression of the other seven genes was significantly associated with overall survival, disease-specific survival, and progression-free survival. Multivariate studies have shown that METTL21A/6 can be an independent prognostic marker in HCC. A total of 664 mRNAs were selected based on Pearson correlation coefficient (R > 0.5), unsupervised consensus clustering, weighted coexpression network analysis, and univariate Cox analysis. These mRNAs were significantly associated with METTLs and were poor prognostic factors in HCC patients. The least absolute shrinkage and selection operator (lasso) was used to construct the best METTLs associated with mRNA risk signature. The mRNA risk signature was significantly associated with age, stage, and t grade. The mRNA high-risk group had higher TP53 and RB1 mutations. This study constructed a nomogram with the mRNA risk profile and clinicopathological features, which could better predict the OS of individuals with HCC. We also analyzed associations between METTLs and mRNA risk signatures in epithelial-mesenchymal transition, immune checkpoints, immune cell infiltration, tumor mutational burden, microsatellite instability, cancer stem cells, tumor pathways, and drug sensitivity. In addition, this study constructed a protein interaction network network including METTLs and mRNA risk signature genes related to tumor microenvironment remodeling based on single-cell sequencing. In conclusion, this study provides a theoretical basis for the mechanism, biomarker screening, and treatment of HCC.

ANGPTL2+cancer-associated fibroblasts and SPP1+macrophages are metastasis accelerators of colorectal cancer.

Background: Liver metastasis (LM) is a leading cause of cancer-related deaths in CRC patients, whereas the associated mechanisms have not yet been fully elucidated. Therefore, it is urgently needed to deeply explore novel metastasis accelerators and therapeutic targets of LM-CRC. Methods: The bulk RNA sequencing data and clinicopathological information of CRC patients were enrolled from the TCGA and GEO databases. The single-cell RNA sequencing (scRNA-seq) datasets of CRC were collected from and analyzed in the Tumor Immune Single-cell Hub (TISCH) database. The infiltration levels of cancer-associated fibroblasts (CAFs) and macrophages in CRC tissues were estimated by multiple immune deconvolution algorithms. The prognostic values of genes were identified by the Kaplan-Meier curve with a log-rank test. GSEA analysis was carried out to annotate the significantly enriched gene sets. The biological functions of cells were experimentally verified. Results: In the present study, hundreds of differentially expressed genes (DEGs) were selected in LM-CRC compared to primary CRC, and these DEGs were significantly associated with the regulation of endopeptidase activity, blood coagulation, and metabolic processes. Then, SPP1, CAV1, ANGPTL2, and COLEC11 were identified as the characteristic DEGs of LM-CRC, and higher expression levels of SPP1 and ANGPTL2 were significantly associated with worse clinical outcomes of CRC patients. In addition, ANGPTL2 and SPP1 mainly distributed in the tumor microenvironment (TME) of CRC tissues. Subsequent scRNA-seq analysis demonstrated that ANGPTL2 and SPP1 were markedly enriched in the CAFs and macrophages of CRC tissues, respectively. Moreover, we identified the significantly enriched gene sets in LM-CRC, especially those in the SPP1+macrophages and ANGPTL2+CAFs, such as the HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION and the HALLMARK_COMPLEMENT. Finally, our in vitro experiments proved that ANGPTL2+CAFs and SPP1+macrophages promote the metastasis of CRC cells. Conclusion: Our study selected four characteristic genes of LM-CRC and identified ANGPTL2+CAFs and SPP1+macrophages subtypes as metastasis accelerators of CRC which provided a potential therapeutic target for LM-CRC.

Integrated analysis of single cell and bulk RNA sequencing identifies CTHRC1+ INHBA+ CAF as drivers of colorectal cancer progression.

Cancer-associated fibroblasts (CAFs) are a key component of the tumor microenvironment and a critical factor in the progression of colorectal cancer (CRC). The aim of this study was to screen for CAFs specific genes that could serve as promising therapeutic targets for CRC patients. Our findings showed a significant increase in the proportion of fibroblasts in CRC tissues, and a high proportion of fibroblasts was associated with immune escape and poor prognosis in CRC. Collagen triple helix repeat containing 1 (CTHRC1) and inhibin subunit beta A (INHBA) were identified as key genes in the progression of CRC, primarily expressed in CAFs and significantly upregulated in CRC tissues. We defined CTHRC1 and INHBA as cancer-associated fibroblast-related genes (CAFRGs), which were associated with poor prognosis in CRC and macrophage polarization. CAFRGs promoted immune escape and metastasis in CRC and were good predictors of immune therapy response. Drug sensitivity analysis showed that the high expression group of CAFRGs was sensitive to 15 chemotherapy drugs, while the low expression group was sensitive to only 3. Clustering of fibroblasts in the tumor revealed that CTHRC1+ INHBA+ CAF was a poor prognostic factor in CRC and was associated with extracellular matrix remodeling and immune regulation. In conclusion, our study provides new theoretical basis for effective treatment strategies and therapeutic targets for CRC.

Comprehensive analysis of GSEC/miR-101-3p/SNX16/PAPOLG axis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies. A growing number of studies have shown that competitive endogenous RNA (ceRNA) regulatory networks might play important roles during HCC process. The present study aimed to identify a regulatory axis of the ceRNA network associated with the development of HCC. The roles of SNX16 and PAPOLG in HCC were comprehensively analyzed using bioinformatics tools. Subsequently, the "mRNA-miRNA-lncRNA" model was then used to predict the upstream miRNAs and lncRNAs of SNX16 and PAPOLG using the miRNet database, and the miRNAs with low expression and good prognosis in HCC and the lncRNAs with high expression and poor prognosis in HCC were screened by differential expression and survival analysis. Finally, the risk-prognosis models of ceRNA network axes were constructed by univariate and multifactorial Cox proportional risk analysis, and the immune correlations of ceRNA network axes were analyzed using the TIMER and GEPIA database. In this study, the relevant ceRNA network axis GSEC/miR-101-3p/SNX16/PAPOLG with HCC prognosis was constructed, in which GSEC, SNX16, and PAPOLG were highly expressed in HCC with poor prognosis, while miR-101-3p was lowly expressed in HCC with good prognosis. The risk-prognosis model predicted AUC of 0.691, 0.623, and 0.626 for patient survival at 1, 3, and 5 years, respectively. Immuno-infiltration analysis suggested that the GSEC/miR-101-3p/SNX16/PAPOLG axis might affect macrophage polarization. The GSEC/miR-101-3p/SNX16/PAPOLG axis of the ceRNA network axis might be an important factor associated with HCC prognosis and immune infiltration.

Effects and prognostic values of miR-30c-5p target genes in gastric cancer via a comprehensive analysis using bioinformatics.

Gastric cancer (GC) is a common cancer and the leading cause of cancer-related death worldwide. To improve the diagnosis and treatment of GC, it is necessary to identify new biomarkers by investigating the cellular and molecular mechanisms. In this study, miR-30c-5p expression was significantly down-regulated in GC tissues by comprehensive analysis using multiple databases. The target genes of miR-30c-5p with up-regulated expression level in GC were identified, including ADAM12 (a disintegrin and metalloproteinase12), EDNRA (the Endothelin receptor type A), STC1 (stanniocalcin 1), and CPNE8 (the calcium-dependent protein, copine 8). The expression level of ADAM12 was significantly related to depth of invasion (p = 0.036) in GC patients. The expression level of EDNRA was significantly related to grade (P = 0.003), depth of invasion (P = 0.019), and lymphatic metastasis (P = 0.001). The expression level of CPNE8 was significantly related to grade (P = 0.043) and TNM stage (P = 0.027).Gene set enrichment analysis showed that they might participate in GC progression through cancer-related pathways. CIBERSORT algorithm analysis showed that their expressions were related to a variety of tumor-infiltrating immune cells. The higher expression of those target genes might be the independent risk factor for poor survival of GC patients, and they might be potential prognostic markers in GC patients.

Identification of microRNA hsa-miR-30c-5p as an inhibitory factor in the progression of hepatocellular carcinoma and investigation of its regulatory network via comprehensive analysis.

Hepatocellular carcinoma (HCC) is a primary liver cancer with high morbidity and mortality. An increasing number of abnormal gene expressions were identified to be associated with the progression of HCC. Previous studies showed that the hsa-miR-30 c-5p (miR-30 c), one of the miR-30 family members, might play a role in suppressing tumor progression in a variety of tumors. The present study aims to examine miR-30 c effects in the development of HCC. The role of miR-30 c in HCC was comprehensively investigated by using bioinformatics and experiments in vitro. The multiple databases were combined to predict and screen the target genes and upstream lncRNAs of miR-30 c, and then constructed a competitive endogenous RNA (ceRNA) regulatory network with miR-30 c as the central miRNA. The miR-30 c-related ceRNA regulatory network was also initially validated in vitro. The results showed that miR-30 c over-expression could inhibit proliferation, migration, invasion, induce apoptosis, and increase G0/G1 phase ratio of HCC cells. Three miR-30 c upstream lncRNAs and 12 miR-30 c target genes were expressed in HCC cells with increased expression and poor prognosis, and a miR-30 C-related ceRNA regulatory network was constructed. This study verified miR-30 c as an inhibitory factor in the progression of HCC and performed analyses on the miR-30 c regulatory network, which might provide potential target information for HCC prognoses and therapies. However, further experiments in vivo and studies including clinical trials will be conducted to validate our results.

Glucoside xylosyltransferase 2 as a diagnostic and prognostic marker in gastric cancer via comprehensive analysis.

To investigate the potential role of GXYLT2 (glucoside xylosyltransferase 2) in gastric cancer (GC), the TCGA (The Cancer Genome Atlas) database and Gene Expression Omnibus (GEO) dataset were used to evaluate GXYLT2 mRNA expression, and the standardized mean difference and diagnostic value were comprehensively assessed. Survival analysis and univariate/multivariate cox regression analysis were performed to evaluate the prognostic value of GXYLT2 in GC patients. The correlation between GXYLT2 and tumor immune cells was identified by using the CIBERSORT algorithm. The results showed that GXYLT2 expression level was significantly increased in GC tissues. GXYLT2 expression was significantly correlated with the grade, stage, and invasion depth of gastric cancer. Overall survival was reduced in the high GXYLT2 expression group. Univariate and multivariate Cox regression analyses showed that GXYLT2 was a reliable prognostic factor. GSEA showed that GXYLT2 might participate in the development of GC through tumor-related pathways. The expression of GXYLT2 was positively correlated with 5 tumor-infiltrating immune cells (resting dendritic cells, m2 macrophages, monocytes, active NK cells and resting mast cells), and was negatively correlated with 6 tumor-infiltrating immune cells (plasma cells, activated memory CD4 T cells, resting NK cells, activated dendritic cells, and activated neutrophils and mast cells). Through cell experiment verification, GXYLT2 expression level in gastric cancer cells was found to be high, which verified the results from the bioinformatics analysis. Furthermore, immunohistochemical staining results also showed that GC tissues had positive GXYLT2 expression. In summary, GXYLT2 might be a potential diagnostic and prognostic biomarker for gastric cancer.

Bioinformatics Analysis of Differentially Expressed Rhythm Genes in Liver Hepatocellular Carcinoma.

Liver Hepatocellular Carcinoma (LIHC), a malignant tumor with high incidence and mortality, is one of the most common cancers in the world. Multiple studies have found that the aberrant expression of rhythm genes is closely related to the occurrence of LIHC. This study aimed to use bioinformatics analysis to identify differentially expressed rhythm genes (DERGs) in LIHC. A total of 563 DERGs were found in LIHC, including 265 downregulated genes and 298 upregulated genes. KEGG pathway enrichment and GO analyses showed that DERGs were significantly enriched in rhythmic and metabolic processes. Survival analysis revealed that high expression levels of CNK1D, CSNK1E, and NPAS2 were significantly associated with the low survival rate in LIHC patients. Through cell experiment verification, the mRNA expression levels of CSNK1D, CSNK1E, and NPAS2 were found to be strongly upregulated, which was consistent with the bioinformatics analysis of LIHC patient samples. A total of 23 nodes and 135 edges were involved in the protein-protein interaction network of CSNK1D, CSNK1E, and NPAS2 genes. Clinical correlation analyses revealed that CSNK1D, CSNK1E, and NPAS2 expression levels were high-risk factors and independently connected with the overall survival rate in LIHC patients. In conclusion, the identification of these DERGs contributes to the exploration of the molecular mechanisms of LIHC occurrence and development and may be used as diagnostic and prognostic biomarkers and molecular targets for chronotherapy in LIHC patients in the future.

Comprehensive analysis of the MIR4435-2HG/miR-1-3p/MMP9/miR-29-3p/DUXAP8 ceRNA network axis in hepatocellular carcinoma.

A growing number of studies have shown that competitive endogenous RNA (ceRNA) regulatory networks might play important roles during the process of hepatocellular carcinoma (HCC). This study assessed the role of the ceRNA network in immune cell infiltration in HCC. Immune-related gene sets were downloaded from Molecular Signatures Database, and differentially expressed genes were screened based on TCGA HCC transcriptome data. The corresponding miRNAs with low expression and good prognostic implications, and the corresponding lncRNAs with high expression and poor prognostic were identified to construct ceRNA networks. The networks were utilized for clinical correlation analysis and risk model construction, and the CIBERSORT algorithm was applied to assess immune cell infiltration. In this study, the mRNA-miRNA-lncRNA model was used to construct a ceRNA network in HCC using immune-related differentially expressed mRNAs. Assessment of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis in HCC showed that a high risk/poor prognosis was significantly correlated with tumor stage and invasion depth. MMP9 was positively correlated with resting M0 macrophages and NK cells and negatively correlated with activated mast cells, resting mast cells, monocytes and activated NK cells. DUXAP8 was positively correlated with M2 macrophages and negatively correlated with MIR4435-2HG, which was positively correlated with M2 macrophages and negatively correlated with activated mast cells, CD8 T cells and follicular helper T cells. The correlation of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis with immune cell infiltration provides further information on the mechanism of HCC development. The result might improve our understanding the interactions between immune related genes and non-coding RNAs in the occurrence and development of HCC, and the relevant RNAs might be used as diagnostic and prognostic biomarkers and molecular targets in HCC patients.