CBX2 Deletion Suppresses Growth and Metastasis of Colorectal Cancer by Mettl3-p38/ERK MAPK Signalling Pathway.

Colorectal cancer (CRC) seriously endangers human health owing to its high morbidity and mortality. Previous studies have suggested that high expression of CBX2 may be associated with poor prognosis in CRC patients. However, its functional role in CRC remains to be elucidated. Herein, we found that CBX2 overexpression in colorectal cancer tissue compared with adjacent tissues. Additionally, forest maps and the nomogram model indicated that elevated CBX2 expression was an independent prognostic factor in CRC. Moreover, we confirmed that the deletion of CBX2 markedly suppressed the proliferation and migration of CRC cells in vitro and in vivo. Furthermore, downregulation of CBX2 promotes CRC cell apoptosis and hinders the cell cycle. Mechanistically, our data demonstrated that deletion of CBX2 inhibited the MAPK signaling pathway by regulating the protein levels of Mettl3. In conclusion, our study demonstrated that CBX2 is a vital tumor suppressor in CRC and could be a promising anti-cancer therapeutic target.

Identification of novel T cell proliferation patterns, potential biomarkers and therapeutic drugs in colorectal cancer.

Background: T cells are crucial components of antitumor immunity. A list of genes associated with T cell proliferation was recently identified; however, the impact of T cell proliferation-related genes (TRGs) on the prognosis and therapeutic responses of patients with colorectal cancer (CRC) remains unclear. Methods: 33 TRG expression information and clinical information of patients with CRC gathered from multiple datasets were subjected to bioinformatic analysis. Consensus clustering was used to determine the molecular subtypes associated with T cell proliferation. Utilizing the Lasso-Cox regression, a predictive signature was created and verified in external cohorts. A tumor immune environment analysis was conducted, and potential biomarkers and therapeutic drugs were identified and confirmed via in vitro and in vivo studies. Results: CRC patients were separated into two TRG clusters, and differentially expressed genes (DEGs) were identified. Patient information was divided into three different gene clusters, and the determined molecular subtypes were linked to patient survival, immune cells, and immune functions. Prognosis-associated DEGs in the three gene clusters were used to evaluate the risk score, and a predictive signature was developed. The ability of the risk score to predict patient survival and treatment response has been successfully validated using multiple datasets. To discover more possible biomarkers for CRC, the weighted gene co-expression network analysis algorithm was utilized to screen key TRG variations between groups with high- and low-risk. CDK1, BATF, IL1RN, and ITM2A were screened out as key TRGs, and the expression of key TRGs was confirmed using real-time reverse transcription polymerase chain reaction. According to the key TRGs, 7,8-benzoflavone was identified as the most significant drug molecule, and MTT, colony formation, wound healing, transwell assays, and in vivo experiments indicated that 7,8-benzoflavone significantly suppressed the proliferation and migration of CRC cells. Conclusion: T cell proliferation-based molecular subtypes and predictive signatures can be utilized to anticipate patient results, immunological landscape, and treatment response in CRC. Novel biomarker candidates and potential therapeutic drugs for CRC were identified and verified using in vitro and in vivo tests.

Robust machine-learning based prognostic index using cytotoxic T lymphocyte evasion genes highlights potential therapeutic targets in colorectal cancer.

BACKGROUND: A minute fraction of patients stands to derive substantial benefits from immunotherapy, primarily attributable to immune evasion. Our objective was to formulate a predictive signature rooted in genes associated with cytotoxic T lymphocyte evasion (CERGs), with the aim of predicting outcomes and discerning immunotherapeutic response in colorectal cancer (CRC). METHODS: 101 machine learning algorithm combinations were applied to calculate the CERGs prognostic index (CERPI) under the cross-validation framework, and patients with CRC were separated into high- and low-CERPI groups. Relationship between immune cell infiltration levels, immune-related scores, malignant phenotypes and CERPI were further analyzed. Various machine learning methods were used to identify key genes related to both patient survival and immunotherapy benefits. Expression of HOXC6, G0S2, and MX2 was evaluated and the effects of HOXC6 and G0S2 on the viability and migration of a CRC cell line were in-vitro verified. RESULTS: The CERPI demonstrated robust prognostic efficacy in predicting the overall survival of CRC patients, establishing itself as an independent predictor of patient outcomes. The low-CERPI group exhibited elevated levels of immune cell infiltration and lower scores for tumor immune dysfunction and exclusion, indicative of a greater potential benefit from immunotherapy. Moreover, there was a positive correlation between CERPI levels and malignant tumor phenotypes, suggesting that heightened CERPI expression contributes to both the occurrence and progression of tumors. Thirteen key genes were identified, and their expression patterns were scrutinized through the analysis of single-cell datasets. Notably, HOXC6, G0S2, and MX2 exhibited upregulation in both CRC cell lines and tissues. Subsequent knockdown experiments targeting G0S2 and HOXC6 resulted in a significant suppression of CRC cell viability and migration. CONCLUSION: We developed the CERPI for effectively predicting survival and response to immunotherapy in patients, and these results may provide guidance for CRC diagnosis and precise treatment.

CTSG Suppresses Colorectal Cancer Progression through Negative Regulation of Akt/mTOR/Bcl2 Signaling Pathway.

Colorectal cancer (CRC) is the most common gastrointestinal tumor worldwide, which is a severe malignant disease that threatens mankind. Cathepsin G (CTSG) has been reported to be associated with tumorigenesis, whereas its role in CRC is still unclear. This investigation aims to determine the function of CTSG in CRC. Our results indicated that CTSG was inhibited in CRC tissues, and patients with CTSG low expression have poor overall survival. Functional experiments revealed that CTSG overexpression suppressed CRC cell progression in vitro and in vivo, whereas CTSG suppression supports CRC development cells in vitro and in vivo. Mechanistically, CTSG overexpression suppressed Akt/mTOR signaling mechanism and elevated apoptotic-associated markers, and CTSG silencing activated Akt/mTOR signaling mechanisms and inhibited apoptotic-associated markers. Furthermore, the Akt suppression signaling pathway by MK2206 abolishes CTSG-silenced expression-induced cell viability and Bcl2 up-regulation in vitro and in vivo. Altogether, these outcomes demonstrate that CTSG may act as a tumor suppressor gene via Akt/mTOR/Bcl2-mediated anti-apoptotic signaling inactivation, and CTSG represents a potential therapeutic target in CRC.

Identification of cuproptosis-based molecular subtypes, construction of prognostic signature and characterization of immune landscape in colon cancer.

Background: Cuproptosis is a newly discovered form of cell death induced by targeting lipoacylated proteins involved in the tricarboxylic acid cycle. However, the roles of cuproptosis-related genes (CRGs) in the clinical outcomes and immune landscape of colon cancer remain unknown. Methods: We performed bioinformatics analysis of the expression data of 13 CRGs identified from a previous study and clinical information of patients with colon cancer obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Colon cancer cases were divided into two CRG clusters and prognosis-related differentially expressed genes. Patient data were separated into three corresponding distinct gene clusters, and the relationships between the risk score, patient prognosis, and immune landscape were analyzed. The identified molecular subtypes correlated with patient survival, immune cells, and immune functions. A prognostic signature based on five genes was identified, and the patients were divided into high- and low-risk groups based on the calculated risk score. A nomogram model for predicting patient survival was developed based on the risk score and other clinical features. Results: The high-risk group showed a worse prognosis, and the risk score was related to immune cell abundance, microsatellite instability, cancer stem cell index, checkpoint expression, immune escape, and response to chemotherapeutic drugs and immunotherapy. Findings related to the risk score were validated in the imvigor210 cohort of patients with metastatic urothelial cancer treated with anti-programmed cell death ligand 1. Conclusion: We demonstrated the potential of cuproptosis-based molecular subtypes and prognostic signatures for predicting patient survival and the tumor microenvironment in colon cancer. Our findings may improve the understanding of the role of cuproptosis in colon cancer and lead to the development of more effective treatment strategies.

5-Fluorouracil Combined with Rutaecarpine Synergistically Suppresses the Growth of Colon Cancer Cells by Inhibiting STAT3.

Purpose: To evaluate the effect of 5-fluorouracil (5-FU) combined with rutaecarpine (RUT) on the antiproliferative, anti-migratory, and apoptosis-promoting ability of colorectal cancer (CRC) cells and explore the underlying mechanism. Methods: The antiproliferative effects of RUT and 5-FU on CRC cells were evaluated using MTT and colony formation assays. Anti-migration was assessed by cell scratch and transwell tests. The synergistic effect of RUT and 5-FU was assessed by isobologram and combination index analysis using CompuSyn software. The effects of RUT and 5-FU on cell apoptosis were detected by flow cytometry. Differences in protein expression levels with or without RUT and/or 5-FU treatment were assessed by Western blot. Moreover, a mouse xenograft model of CRC was established to investigate the antitumor effect of RUT and 5-FU in vivo, and Ki67 and cleaved caspase-3 expression was detected by immunofluorescence. Results: In this study, we found that 5-FU combined with RUT can inhibit the proliferative, migratory, and antiapoptotic abilities of CRC cells to a significantly greater extent than either RUT or 5-FU alone both in vivo and in vitro. Western blot analysis showed that the level of signal transducer and activator of transcription 3 (STAT3) phosphorylation in CRC cells was significantly reduced after combination therapy compared with that seen with the respective monotherapies. In addition, combination therapy influenced the STAT3 signaling pathway, namely, it inhibited the expression of c-Myc, CDK4, and Bcl-2 while enhancing that of the proapoptotic protein cleaved caspase-3. Immunofluorescence staining further showed that the expression of Ki67 and cleaved caspase-3 was significantly downregulated and upregulated, respectively, in tumor tissues of mice treated with combination therapy compared with that observed with 5-FU treatment alone. Conclusion: Combined therapy with 5-FU and RUT exerted a superior curative effect in CRC than treatment with either single drug alone and has potential as a novel therapeutic modality for the treatment of CRC.

A novel oxidative stress- and ferroptosis-related gene prognostic signature for distinguishing cold and hot tumors in colorectal cancer.

Oxidative stress and ferroptosis exhibit crosstalk in many types of human diseases, including malignant tumors. We aimed to develop an oxidative stress- and ferroptosis-related gene (OFRG) prognostic signature to predict the prognosis and therapeutic response in patients with colorectal cancer (CRC). Thirty-four insertion genes between oxidative stress-related genes and ferroptosis-related genes were identified as OFRGs. We then performed bioinformatics analysis of the expression profiles of 34 OFRGs and clinical information of patients obtained from multiple datasets. Patients with CRC were divided into three OFRG clusters, and differentially expressed genes (DEGs) between clusters were identified. OFRG clusters correlated with patient survival and immune cell infiltration. Prognosis-related DEGs in three clusters were used to calculate the risk score, and a prognostic signature was constructed according to the risk score. In this study, patients in the low-risk group had better prognosis, higher immune cell infiltration levels, and better responses to fluorouracil-based chemotherapy and immune checkpoint blockade therapy than high-risk patients; these results were successfully validated with multiple independent datasets. Thus, low-risk CRC could be defined as hot tumors and high-risk CRC could be defined as cold tumors. To further identify potential biomarkers for CRC, the expression levels of five signature genes in CRC and adjacent normal tissues were further verified via an in vitro experiment. In conclusion, we identified 34 OFRGs and constructed an OFRG-related prognostic signature, which showed excellent performance in predicting survival and therapeutic responses for patients with CRC. This could help to distinguish cold and hot tumors in CRC, and the results might be helpful for precise treatment protocols in clinical practice.

PANoptosis-based molecular clustering and prognostic signature predicts patient survival and immune landscape in colon cancer.

PANoptosis is a newly-discovered cell death pathway that involves crosstalk and co-ordination between pyroptosis, apoptosis, and necroptosis processes. However, the roles of PANoptosis-related genes (PRGs) in prognosis and immune landscape of colon cancer remain widely unknown. Here, we performed a bioinformatics analysis of expression data of nineteen PRGs identified from previous studies and clinical data of colon cancer patients obtained from TCGA and GEO databases. Colon cancer cases were divided into two PRG clusters, and prognosis-related differentially expressed genes (PRDEGs) were identified. The patient data were then separated into two corresponding distinct gene clusters, and the relationship between the risk score, patient prognosis, and immune landscape was analyzed. The identified PRGs and gene clusters correlated with patient survival and immune system and cancer-related biological processes and pathways. A prognosis signature based on seven genes was identified, and patients were divided into high-risk and low-risk groups based on the calculated risk score. A nomogram model for prediction of patient survival was also developed based on the risk score and other clinical features. Accordingly, the high-risk group showed worse prognosis, and the risk score was related to immune cell abundance, cancer stem cell (CSC) index, checkpoint expression, and response to immunotherapy and chemotherapeutic drugs. Results of quantitative real-time polymerase chain reaction (qRT-PCR) showed that LGR5 and VSIG4 were differentially expressed between normal and colon cancer samples. In conclusion, we demonstrated the potential of PANoptosis-based molecular clustering and prognostic signatures for prediction of patient survival and tumor microenvironment (TME) in colon cancer. Our findings may improve our understanding of the role of PANoptosis in colon cancer, and enable the development of more effective treatment strategies.

Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma.

Background: Cellular senescence is a typical irreversible form of life stagnation, and recent studies have suggested that long non-coding ribonucleic acids (lncRNA) regulate the occurrence and development of various tumors. In the present study, we attempted to construct a novel signature for predicting the survival of patients with hepatocellular carcinoma (HCC) and the associated immune landscape based on senescence-related (sr) lncRNAs. Method: Expression profiles of srlncRNAs in 424 patients with HCC were retrieved from The Cancer Genome Atlas database. Lasso and Cox regression analyses were performed to identify differentially expressed lncRNAs related to senescence. The prediction efficiency of the signature was checked using a receiver operating characteristic (ROC) curve, Kaplan-Meier analysis, Cox regression analyses, nomogram, and calibration. The risk groups of the gene set enrichment analysis, immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) were also analyzed. Quantitative real-time polymerase chain reaction (qPCR) was used to confirm the levels of AC026412.3, AL451069.3, and AL031985.3 in normal hepatic and HCC cell lines. Results: We identified 3 srlncRNAs (AC026412.3, AL451069.3, and AL031985.3) and constructed a new risk model. The results of the ROC curve and Kaplan-Meier analysis suggested that it was concordant with the prediction. Furthermore, a nomogram model was constructed to accurately predict patient prognosis. The risk score also correlated with immune cell infiltration status, immune checkpoint expression, and chemosensitivity. The results of qPCR revealed that AC026412.3 and AL451069.3 were significantly upregulated in hepatoma cell lines. Conclusion: The novel srlncRNA (AC026412.3, AL451069.3, and AL031985.3) signatures may provide insights into new therapies and prognosis predictions for patients with HCC.

Circ_002059 suppresses cell proliferation and migration of gastric cancer via miR-182/MTSS1 axis.

Circular RNAs (circRNAs) play either oncogenic or tumor suppressive roles in gastric cancer (GC). A previous study demonstrated that circ_002059, a typical circRNA, was downregulated in GC tissues. However, the role and mechanism of circ_002059 in GC development are still unknown. In this study, the levels of circ_002059, miR-182, and metastasis suppressor-1 (MTSS1) were examined by real-time quantitative polymerase chain reaction and western blot analysis. Cell proliferation and migration were evaluated by MTT assay and Transwell migration assay, respectively. The interactions between miR-182 and circ_002059 or MTSS1 were analyzed by dual-luciferase reporter assay. A GC xenograft model was established to validate the role of circ_002059 in GC progression in vivo. Overexpression of circ_002059 significantly inhibited, whereas knockdown of circ_002059 notably facilitated, cell proliferation and migration in GC cells. MTSS1 was found to be a direct target of miR-182 and circ_002059 upregulated MTSS1 expression by competitively sponging miR-182. Transfection with miR-182 mimic and MTSS1 silencing abated the inhibitory effect of circ_002059 on GC progression. Circ_002059 inhibited GC cell xenograft tumor growth by regulating miR-182 and MTSS1 expression. Collectively, Circ_002059 inhibited GC cell proliferation and migration in vitro and xenograft tumor growth in mice, by regulating the miR-182/MTSS1 axis.

LMNB2 is a prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma.

BACKGROUND: Previous studies have suggested Lamin B2 (LMNB2) as an oncogene in lung cancer. However, the role of LMNB2 in hepatocellular carcinoma (HCC) remains unclear. METHOD: The expression of LMNB2 was compared between HCC samples and non-tumor samples in multiple datasets. In addition, the prognostic value of LMNB2 in HCC was also investigated. Furthermore, the cBioPortal was utilized to analyze the genomic alternation of LMNB2 in HCC. Besides, co-expression genes and functional enrichment analysis were evaluated using LinkedOmics to determine the function of LMNB2. Finally, the correlation between LMNB2 and immune infiltration was assessed using Tumor Immune Estimation Resource (TIMER). RESULTS: Elevated LMNB2 expression level was identified in HCC patients in multiple datasets. Moreover, increased levels of LMNB2 were associated with poor overall survival (OS) and disease-free survival (DFS). The functional enrichment analysis revealed that LMNB2 plays an essential role via the cell cycle pathway, spliceosome, hippo-signaling pathway, and metabolic pathways. Besides, copy number variation (CNV) and methylation were significantly associated with LMNB2 expression. Additionally, increased levels of LMNB2 were significantly associated with B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. CONCLUSION: LMNB2 is a potential HCC prognostic and diagnostic biomarker.

Development and Validation of an Immune-Related lncRNA Signature for Predicting the Prognosis of Hepatocellular Carcinoma.

AIM: Immunotherapy is currently being explored as a potential treatment for hepatocellular carcinoma (HCC). This study investigated the prognostic value of immune-related long non-coding RNAs (lncRNAs) in patients with HCC. METHODS: The Wilcoxon test was used to compare differentially expressed lncRNAs between HCC tissue and non-tumor tissue. Moreover, co-expression analysis was used to determine immune-related lncRNA. Univariate cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression were used to identify immune-related prognostic lncRNA. The immune risk score was calculated by the sum of the product from each lncRNA expression and its coefficient. Furthermore, the prognostic significance of the lncRNA signature was determined in the training group, testing group, and the entire group. A prognostic nomogram was established by integrating immune risk score and clinicopathological features. RESULTS: PRRT3-AS1 and AL031985.3 were identified as immune-related prognostic lncRNAs in HCC patients. HCC patients were divided into high and low-risk groups based on the optimal cutoff value of risk score in the training group. The prognosis of HCC patients in the high-risk group was worse compared with the low-risk group. Besides, the immune-related lncRNA score was regarded as an independent risk factor for the prognosis of HCC patients. The predictive nomogram showed satisfactory discrimination and consistency. Gene enrichment analysis results indicated that the high-risk group was associated with immune-related signaling pathways. CONCLUSION: This study screened a 2-lncRNA signature and constructed a nomogram to predict the survival of HCC patients, thereby provided guidelines for undertaking medical decisions.

Diagnostic value of HOX transcript antisense RNA for cancer detection: a meta-analysis.

Aim: Numerous studies have investigated the diagnostic role of long noncoding RNA HOX transcript antisense RNA in cancers, but its diagnostic efficacy is inconsistent. Methods: The PubMed, Embase, Web of Science and Cochrane Library databases are used to retrieve relevant studies. The bivariate effect model was used to compute the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve. Results: A total of 13 studies were included in this meta-analysis. The combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve were: 0.77, 0.83, 4.7, 0.28, 17 and 0.87, respectively. Deeks' funnel plot test (p = 0.103) indicated no publication bias. Conclusion: Long noncoding RNA HOX transcript antisense RNA may be a useful biomarker for cancer detection.

Mean corpuscular hemoglobin concentration correlates with prognosis of resected hepatocellular carcinoma.

Aim: To evaluate the prognostic role of mean corpuscular hemoglobin concentration (MCHC) in hepatocellular carcinoma (HCC) after hepatectomy. Patients & methods: A total of 289 HCC patients were classified into two groups based on the cut-off value of MCHC. Significant prognostic factors were screened by univariate and multivariate analysis. Results: Low MCHC value was significantly associated with tumor diameter (p = 0.004) and vascular invasion (p = 0.038). Besides, Cox regression analysis showed that low MCHC was significantly associated with poor prognostic outcomes with HCC after hepatectomy (overall survival: hazard ratio: 0.372; 95% CI: 0.206-0.672; p = 0.001; recurrence-free survival: hazard ratio: 0.450; 95% confidence interval: 0.317-0.638; p < 0.001). Conclusion: Preoperative MCHC can predict prognosis for patients with HCC, and the lower MCHC value was associated with poor prognosis after hepatectomy.

Elevated platelet distribution width predicts poor prognosis in hepatocellular carcinoma.

BACKGROUND: Previous studies have demonstrated that platelets play an important role in growth, invasion, and angiogenesis of a variety of tumors. Nevertheless, the prognostic role of platelet indices in hepatocellular carcinoma (HCC) has not been explored. The aim of this study was to explore the association between platelet indices and prognosis in HCC. METHOD: A total of 260 patients with HCC between January 2009 and December 2015 were retrospectively analyzed. The optimal platelet distribution width (PDW) cutoff value is identified by the receiver operating characteristic curve (ROC) curve. The relationship between PDW and clinicopathological features was assessed. The prognostic effects of PDW were assessed by using the Kaplan-Meier method and Cox regression model. RESULT: Elevated PDW level was significantly associated with portal hypertension, vascular invasion, and Child-Pugh grade. In addition, survival curve indicates that patients with high PDW levels have a worse prognosis than patients with low PDW levels (P< 0.001). Multivariate Cox regression analysis identified PDW as an independent factor of prognosis in HCC patients (hazard ratio: 4.460, 95% confidence interval: 2.308-8.619, P< 0.001). CONCLUSION: Elevated PDW may be a novel marker for predicting the prognosis of HCC, but further research is needed to validate our conclusions.

Prognostic Value of Lactate Dehydrogenase in Patients with Hepatocellular Carcinoma: A Meta-Analysis.

BACKGROUND: Previous studies have shown the prognostic value of lactate dehydrogenase (LDH) in hepatocellular carcinoma (HCC), but the results are not persuasive. Therefore, the purpose of our study was to quantitatively explore the prognostic value of LDH in hepatocellular carcinoma. METHODS: We searched the Web of Science, Embase, PubMed, and the Cochrane Library for literature published before October 2018 on the prognostic value of LDH in patients with hepatocellular carcinoma. The combined hazard ratios (HRs) and 95% confidence intervals (CIs) were utilized to assess the prognostic value of LDH in overall survival (OS), recurrence-free survival (RFS), and progression-free survival (PFS) of HCC. Subgroup analysis, sensitivity analysis, and metaregression were used to explore the source of heterogeneity. Funnel plots with Begg's test and Egger's test were used to detect potential publication biases. Furthermore, combined odds ratios (ORs) were utilized to assess the correlation between LDH and clinicopathological features. RESULTS: A total of 10 nonrandomized controlled studies were included in this meta-analysis. The combined effects of LDH on HCC patients' OS, RFS/DFS, and PFS were HR = 2.07, 95% CI: 1.63-2.62, P < 0.001; HR = 1.62, 95% CI: 1.37-1.90, P < 0.001; and HR = 1.96, 95% CI: 1.14-3.36, P = 0.014, respectively. Subgroup analysis and sensitivity analysis showed that the outcome was stable, and the results of the metaregression also identified statistical models as an important source of heterogeneity. Potential publication bias was detected in the OS studies, so the trim-and-fill method was used to explore publication bias, and the results showed stability. Furthermore, the combined OR suggests that LDH was significantly correlated with gender, Child-Pugh grade, alpha-fetoprotein, vascular invasion, and tumor size. CONCLUSIONS: Preoperative LDH elevation is significantly associated with poor prognosis in patients with HCC, which may be a promising factor in assessing the prognosis of patients with HCC.