TNFRSF10C methylation is a new epigenetic biomarker for colorectal cancer

Machine learning-based integration develops a multiple programmed cell death signature for predicting the clinical outcome and drug sensitivity in colorectal cancer

Tumorigenesis and treatment are closely associated with various programmed cell death (PCD) patterns. However, the coregulatory role of multiple PCD patterns in colorectal cancer (CRC) remains unknown. In this study, we developed a multiple PCD index (MPCDI) based on 19 PCD patterns using two machine learning algorithms for risk stratification, prognostic prediction, construction of nomograms, immune cell infiltration analysis, and chemotherapeutic drug sensitivity analysis. As a result, in the TCGA-COAD, GSE17536, and GSE29621 cohorts, the MPCDI can effectively distinguished survival outcomes in CRC patients and served as an independent factor for CRC patients. We then explored the immune infiltration landscape in two groups using the nine algorithms and found more overall immune infiltration in the high-MPCDI group. TIDE scores suggested that the increased immune evasion potential and immune checkpoint inhibition therapy may be less effective in the high-MPCDI group. Immunophenoscores indicated that anti-PD1, anti-cytotoxic T-lymphocyte associated antigen 4 (anti-CTLA4), and anti-PD1-CTLA4 combination therapies are less effective in the high-MPCDI group. In addition, the high-MPCDI group was more sensitive to AZD1332, Foretinib, and IGF1R_3801, and insensitive to AZD3759, AZD5438, AZD6482, Erlotinib, GSK591, IAP_5620, and Picolinici-acid, which suggests that the MPCDI can guide drug selection for CRC patients. As a new clinical classifier, the MPCDI can more accurately distinguish CRC patients who benefit from immunotherapy and develop personalized treatment strategies for CRC patients.

MLH1 gene promoter methylation status partially overlaps with CpG methylator phenotype (CIMP) in colorectal adenocarcinoma

BACKGROUND

RAS/BRAF mutations, mismatch DNA repair complex deficiency (MMRd)/microsatellite instability (MSI), and CpG methylator phenotype (CIMP) are key molecular actors in colorectal carcinogenesis. To date, conflicting evidence about the correlations between these molecular features has been reported.

MATERIALS AND METHODS

A retrospectively selected cohort of 123 CRCs was divided into 3 groups based on the molecular characteristics: MMR proficient (MMRp)/BRAF p.V600E mutated (BRAFmut), MMRd/BRAFmut, and MMRd/BRAF wild type (BRAFwt). MLH1 promoter (pMLH1) methylation status was assessed by pyrosequencing. For 82 samples the CIMP phenotype was evaluated using the EpiTect® MethyLight kit.

RESULTS

The MMRd/BRAFmut group showed a higher pMLH1 methylation rate compared to both the MMRd/BRAFwt and the MMRp/BRAFmut groups. Overall, the two MMRd groups had a higher methylation rate compared to the MMRp cases independently from the mutational status of BRAF (p-value <0.0001). The MMRd/BRAFmut group was characterized by a 90.0 % of CIMP high (CIMP-H) tumors of which 97.2 % were pMLH1 methylated. Instead, the MMRd/BRAFwt group presented 50.0 % of CIMP-H adenocarcinomas.

CONCLUSIONS

Our study demonstrates that pMLH1 hypermethylation, MMRd, BRAFmut and CIMP phenotype do not completely overlap in CRC. These findings further refine the knowledge on the molecular landscape of CRC and may have critical implications also for the clinical management of the disease.

Investigation of risk signatures associated with anoikis in thyroid cancer through integrated transcriptome and Mendelian randomization analysis

Background

Anoikis is intricately associated with the malignant progression of cancer. Thyroid cancer (THCA) is the most common endocrine tumor, metastasis is closely related to treatment response and prognosis of THCA. Hence, it is imperative to comprehensively identify predictive prognostic genes and novel molecular targets for effective THCA therapy.

Methods

Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were utilized to mine differentially expressed anoikis-related (DE-ARGs). Then, the prognostic genes were identified and a risk signature was constructed for THCA using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) method. Furthermore, the associations between risk signature and immune infiltration, immunotherapy, as well as potential mechanisms of action were determined using multiple R packages and Wilcoxon test. Finally, Mendelian randomized (MR) analysis was conducted to investigate the causal relationship between the prognostic genes and THCA.

Results

In total, six prognostic genes (LRRC75A, METTL7B, ADRA1B, TPD52L1, TNFRSF10C, and CXCL8) related to anoikis were identified, and the corresponding risk signature were constructed to assess the survival time of THCA patients. Immunocorrelation analysis demonstrated the anoikis-relevant risk signature could be used to evaluate immunotherapy effects in THCA patients, and the infiltration of immune cells was correlated with the degree of risk in THCA patients. According to two-sample MR analysis, there was the significant causal relationship between CXCL8 and THCA (odds ratio [OR] > 1 & p< 0.05), and the increase of its gene expression would lead to an increased risk of THCA. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) confirmed the upregulated expression patterns of these prognostic genes in THCA tissues.

Conclusion

In conclusion, we constructed the risk signature related to anoikis for THCA, which might have important clinical significance for improving the quality of life and treatment effect of THCA patients.

Copy Number Alterations as Novel Biomarkers and Therapeutic Targets in Colorectal Cancer

In colorectal cancer, somatic mutations have played an important role as prognostic and predictive biomarkers, with some also functioning as therapeutic targets. Another genetic aberration that has shown significance in colorectal cancer is copy number alterations (CNAs). CNAs occur when a change to the DNA structure propagates gain/amplification or loss/deletion in sections of DNA, which can often lead to changes in protein expression. Multiple techniques have been developed to detect CNAs, including comparative genomic hybridization with microarray, low pass whole genome sequencing, and digital droplet PCR. In this review, we summarize key findings in the literature regarding the role of CNAs in the pathogenesis of colorectal cancer, from adenoma to carcinoma to distant metastasis, and discuss the roles of CNAs as prognostic and predictive biomarkers in colorectal cancer.

A Genome-Wide Investigation of Effects of Aberrant DNA Methylation on the Usage of Alternative Promoters in Hepatocellular Carcinoma

BACKGROUND

The alternative usage of promoters provides a way to regulate gene expression, has a significant influence on the transcriptome, and contributes to the cellular transformation of cancer. However, the function of alternative promoters (APs) in hepatocellular carcinoma (HCC) has not been systematically studied yet. In addition, the potential mechanism of regulation to the usage of APs remains unclear. DNA methylation, one of the most aberrant epigenetic modifications in cancers, is known to regulate transcriptional activity. Whether DNA methylation regulates the usage of APs needs to be explored. Here, we aim to investigate the effects of DNA methylation on usage of APs in HCC.

METHODS

Promoter activities were calculated based on RNA-seq data. Functional enrichment analysis was implemented to conduct GO terms. Correlation tests were used to detect the correlation between promoter activity and methylation status. The LASSO regression model was used to generate a diagnostic model. Kaplan-Meier analysis was used to compare the overall survival between high and low methylation groups. RNA-seq and whole-genome bisulfite sequencing (WGBS) in HCC samples were performed to validate the correlation of promoter activity and methylation.

RESULTS

We identified 855 APs in total, which could be well used to distinguish cancer from normal samples. The correlation of promoter activity and DNA methylation in APs was observed, and the APs with negative correlation were defined as methylation-regulated APs (mrAPs). Six mrAPs were identified to generate a diagnostic model with good performance (AUC = 0.97). Notably, the majority of mrAPs had CpG sites that could be used to predict clinical outcomes by methylation status. Finally, we verified 85.6% of promoter activity variation and 92.3% of methylation changes in our paired RNA-seq and WGBS samples, respectively. The negative correlation between promoter activity and methylation status was further confirmed in our HCC samples.

CONCLUSION

The aberrant methylation status plays a critical role in the precision usage of APs in HCC, which sheds light on the mechanism of cancer development and provides a new insight into cancer screening and treatment.

Identification of the Key Immune-Related Genes in Chronic Obstructive Pulmonary Disease Based on Immune Infiltration Analysis

Purpose

Chronic obstructive pulmonary disease (COPD) is a major cause of death and morbidity worldwide. A better understanding of new biomarkers for COPD patients and their complex mechanisms in the progression of COPD are needed.

Methods

An algorithm was conducted to reveal the proportions of 22 subsets of immune cells in COPD samples. Differentially expressed immune-related genes (DE-IRGs) were obtained based on the differentially expressed genes (DEGs) of the GSE57148 dataset, and 1509 immune-related genes (IRGs) were downloaded from the ImmPort database. Functional enrichment analyses of DE-IRGs were conducted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and Ingenuity Pathway Analysis (IPA). We defined the DE-IRGs that had correlations with immune cells as hub genes. The potential interactions among the hub genes were explored by a protein-protein interaction (PPI) network.

Results

The CIBERSORT results showed that lung tissue of COPD patients contained a greater number of resting NK cells, activated dendritic cells, and neutrophils than normal samples. However, the fractions of follicular helper T cells and resting dendritic cells were relatively lower. Thirty-eight DE-IRGs were obtained for further analysis. Functional enrichment analysis revealed that these DE-IRGs were significantly enriched in several immune-related biological processes and pathways. Notably, we also observed that DE-IRGs were associated with the coronavirus disease COVID-19 in the progression of COPD. After correlation analysis, six DE-IRGs associated with immune cells were considered hub genes, including AHNAK, SLIT2 TNFRRSF10C, CXCR1, CXCR2, and FCGR3B.

Conclusion

In the present study, we investigated immune-related genes as novel diagnostic biomarkers and explored the potential mechanism for COPD based on CIBERSORT analysis, providing a new understanding for COPD treatment.

Development and Validation of a TNF Family-Based Signature for Predicting Prognosis, Tumor Immune Characteristics, and Immunotherapy Response in Colorectal Cancer Patients

In this study, a comprehensive analysis of TNF family members in colorectal cancer (CRC) was conducted and a TNF family-based signature (TFS) was generated to predict prognosis and immunotherapy response. Using the expression data of 516 CRC patients from The Cancer Genome Atlas (TCGA) database, TNF family members were screened to construct a TFS by using the univariate Cox proportional hazards regression and the least absolute shrinkage and selection operator- (LASSO-) Cox proportional hazards regression method. The TFS was then validated in a meta-Gene Expression Omnibus (GEO) cohort (n = 1162) from the GEO database. Additionally, the tumor immune characteristics and predicted responses to immune checkpoint blockade in TFS-based risk subgroups were analyzed. Eight genes (TNFRSF11A, TNFRSF10C, TNFRSF10B, TNFSF11, TNFRSF25, TNFRSF19, LTBR, and NGFR) were used to construct the TFS. Compared to the high-risk patients, the low-risk patients had better overall survival, which was verified by the GEO data. In addition, a high TFS risk score was associated with high infiltration of regulatory T cells (Tregs), nonactivated macrophages (M0), natural killer cells, immune escape phenotypes, poor immunotherapy response, and tumorigenic and metastasis-related pathways. Conversely, a low TFS risk score was related to high infiltration of resting CD4 memory T cells and resting dendritic cells, few immune escape phenotypes, and high sensitivity to immunotherapy. Thus, the eight gene-based TFS is a promising index to predict the prognosis, immune characteristics, and immunotherapy response in CRC, and our results also provide new understanding of the role of the TNF family members in the prognosis and treatment of CRC.

CNV Analysis of the Correlation between Preoperative Lymph Node Metastasis and Prognosis of Early Tongue Cancer

Objective: To investigate the relationship between preoperative concealed lymph node metastasis (LNM) and prognosis in patients with early tongue cancer.

Methods: According to preoperative lymph node dissection, 41 patients with tongue cancer were divided into the LNM group (n=19) and the non-LNM group (n=22). Analysis of single nucleotide variation (SNV), tumor mutation burden (TMB), mutant allele tumor heterogeneity (MATH), aneuploidy and copy number variation (CNV) was performed to identify differentially expressed genes (DEGs) related to LNM. While KEGG analysis was conducted to reveal the CNV differentially expressed genes and main enriched pathways, the correlation between pathways and genes was analyzed by hierarchical clustering. The clinical information of LNM and data on overall survival (OS) rate were obtained from The Cancer Genome Atlas (TCGA), and survival analysis was performed based on combined LNM information.

Results: We observed significant correlations for the mTOR signaling pathway, Hippo signaling pathway and Wnt signaling pathway with the LNM group, while leukocyte transendothelial migration and cytokine-cytokine receptor interaction were markedly correlated with the non-LNM group. Moreover, TNFRSF10C was identified as the main DEG in the leukocyte transendothelial migration pathway. TCGA-based validation revealed that the disease-free survival (DFS) of the non-LNM group was significantly higher than that of the LNM group (P<0.005) when TNFRSF10C CNV was set to a log2 ratio>-0.163.

Conclusion: The differential expression of TNFRSF10C in leukocyte transendothelial migration, an immune-related pathway, is associated with LNM and DFS. The TNFRSF10C CNV log2 ratio could potentially serve as an indicator of good prognosis for tongue cancer patients with non-LNM after neck dissection.

Whole-exome sequencing of 79 xenografts as a potential approach for the identification of genetic variants associated with sensitivity to cytotoxic anticancer drugs

Chemotherapy response remains unpredictable in most patients with cancer. In this study, we performed whole-exome sequencing of 79 cancer xenografts derived from human cancer tissues to identify genetic predictors of chemosensitivity to nine cytotoxic anticancer drugs. Xenografts were harvested from 12 organs with cancer and implanted into nude mice. The mice were exposed to one of nine cytotoxic anticancer drugs (5-fluorouracil, nimustine, adriamycin, cyclophosphamide, cisplatin, mitomycin C, methotrexate, vincristine, and vinblastine) to assess the correlation between chemosensitivity response and variant allele frequency. We found 162 candidate variants that were possibly associated with chemosensitivity to one or more of the nine anticancer drugs (P < 0.01). In a subgroup analysis of breast and gastric cancer xenografts, 78 and 67 variants, respectively, were possibly associated with chemosensitivity. This approach may help to contribute to the development of personalized treatments that may allow for the prescription of optimal chemotherapy regimens among patients with cancer.

Association between GPX3 promoter methylation and malignant tumors: A meta-analysis

Glutathione peroxidase 3 (GPX3) has an important function of scavenging hydrogen peroxide and preventing cancer. The purpose of this meta-analysis was to analyze the relationship between GPX3 gene methylation and cancer and to further evaluate its diagnostic value for cancer. We screened eligible literatures from the PubMed, Embase, CNKI and Wanfang databases. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to measure the association of GPX3 methylation with cancer. Summary receiver operating characteristics (SROC) analysis was used to assess the diagnostic value of GPX3 methylation for cancer. A total of 17 eligible articles were included in the meta-analysis involving a total of 960 tumor samples and 445 non-tumor samples. The results showed that GPX3 hypermethylation was significantly associated with cancer (OR = 17.32, 95% CI = 8.22-36.51, P <  0.00001). Compared with cancer patients without lymph node metastasis, cancer patients with lymph node metastasis were more associated with GPX3 hypermethylation (OR = 2.97, 95% CI = 1.53-5.76, P =  0.001). SROC analysis showed for GPX3 methylation was a promising biomarker for cancer risk (AUC = 0.89, pooled sensitivity = 0.93, pooled specificity = 0.54, NLR = 0.15, PLR = 2.05, DOR = 17.32). TCGA database bioinformatics analysis of 696 pairs of tumor and non-tumor tissues further validate the association of GPX3 methylation with the risk of cancer [cg21504918: 0.10 (0.08, 0.15) vs. 0.09 (0.08, 0.11), P = 5.8E-28; cg26638444: 0.05 (0.04, 011) vs. 0.04 (0.03, 0.06), P = 8.7E-29]. In summary, our study indicates that GPX3 methylation is associated with cancer and has the potential to become a broad-spectrum tumor screening marker and has a value in predicting tumor lymph node metastasis.