Epigenetic profiling and mRNA expression reveal candidate genes as biomarkers for colorectal cancer

Diverse functions of SOX9 in liver development and homeostasis and hepatobiliary diseases

The liver is the central organ for digestion and detoxification and has unique metabolic and regenerative capacities. The hepatobiliary system originates from the foregut endoderm, in which cells undergo multiple events of cell proliferation, migration, and differentiation to form the liver parenchyma and ductal system under the hierarchical regulation of transcription factors. Studies on liver development and diseases have revealed that SRY-related high-mobility group box 9 (SOX9) plays an important role in liver embryogenesis and the progression of hepatobiliary diseases. SOX9 is not only a master regulator of cell fate determination and tissue morphogenesis, but also regulates various biological features of cancer, including cancer stemness, invasion, and drug resistance, making SOX9 a potential biomarker for tumor prognosis and progression. This review systematically summarizes the latest findings of SOX9 in hepatobiliary development, homeostasis, and disease. We also highlight the value of SOX9 as a novel biomarker and potential target for the clinical treatment of major liver diseases.

Prognostic Biomarkers of Cell Proliferation in Colorectal Cancer (CRC): From Immunohistochemistry to Molecular Biology Techniques

Colorectal cancer (CRC) is one of the most common and severe malignancies worldwide. Recent advances in diagnostic methods allow for more accurate identification and detection of several molecular biomarkers associated with this cancer. Nonetheless, non-invasive and effective prognostic and predictive testing in CRC patients remains challenging. Classical prognostic genetic markers comprise mutations in several genes (e.g., APC, KRAS/BRAF, TGF-β, and TP53). Furthermore, CIN and MSI serve as chromosomal markers, while epigenetic markers include CIMP and many other candidates such as SERP, p14, p16, LINE-1, and RASSF1A. The number of proliferation-related long non-coding RNAs (e.g., SNHG1, SNHG6, MALAT-1, CRNDE) and microRNAs (e.g., miR-20a, miR-21, miR-143, miR-145, miR-181a/b) that could serve as potential CRC markers has also steadily increased in recent years. Among the immunohistochemical (IHC) proliferative markers, the prognostic value regarding the patients' overall survival (OS) or disease-free survival (DFS) has been confirmed for thymidylate synthase (TS), cyclin B1, cyclin D1, proliferating cell nuclear antigen (PCNA), and Ki-67. In most cases, the overexpression of these markers in tissues was related to worse OS and DFS. However, slowly proliferating cells should also be considered in CRC therapy (especially radiotherapy) as they could represent a reservoir from which cells are recruited to replenish the rapidly proliferating population in response to cell-damaging factors. Considering the above, the aim of this article is to review the most common proliferative markers assessed using various methods including IHC and selected molecular biology techniques (e.g., qRT-PCR, in situ hybridization, RNA/DNA sequencing, next-generation sequencing) as prognostic and predictive markers in CRC.

An artificial intelligence prediction model based on extracellular matrix proteins for the prognostic prediction and immunotherapeutic evaluation of ovarian serous adenocarcinoma

Background: Ovarian Serous Adenocarcinoma is a malignant tumor originating from epithelial cells and one of the most common causes of death from gynecological cancers. The objective of this study was to develop a prediction model based on extracellular matrix proteins, using artificial intelligence techniques. The model aimed to aid healthcare professionals to predict the overall survival of patients with ovarian cancer (OC) and determine the efficacy of immunotherapy. Methods: The Cancer Genome Atlas Ovarian Cancer (TCGA-OV) data collection was used as the study dataset, whereas the TCGA-Pancancer dataset was used for validation. The prognostic importance of 1068 known extracellular matrix proteins for OC were determined by the Random Forest algorithm and the Lasso algorithm establishing the ECM risk score. Based on the gene expression data, the differences in mRNA abundance, tumour mutation burden (TMB) and tumour microenvironment (TME) between the high- and low-risk groups were assessed. Results: Combining multiple artificial intelligence algorithms we were able to identify 15 key extracellular matrix genes, namely, AMBN, CXCL11, PI3, CSPG5, TGFBI, TLL1, HMCN2, ESM1, IL12A, MMP17, CLEC5A, FREM2, ANGPTL4, PRSS1, FGF23, and confirm the validity of this ECM risk score for overall survival prediction. Several other parameters were identified as independent prognostic factors for OC by multivariate COX analysis. The analysis showed that thyroglobulin (TG) targeted immunotherapy was more effective in the high ECM risk score group, while the low ECM risk score group was more sensitive to the RYR2 gene-related immunotherapy. Additionally, the patients with low ECM risk scores had higher immune checkpoint gene expression and immunophenoscore levels and responded better to immunotherapy. Conclusion: The ECM risk score is an accurate tool to assess the patient's sensitivity to immunotherapy and forecast OC prognosis.

Identification of potential biomarkers for colorectal cancer by clinical database analysis and Kaplan-Meier curves analysis

This study aimed to explore critical genes as potential biomarkers for the diagnosis and prognosis of colorectal cancer (CRC) for clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, and GSE32323 from the GEO database identified differentially expressed genes (DEGs), and performed a functional enrichment analysis. A protein-protein interaction network was constructed, and correlated module analysis was performed using STRING and Cytoscape. The Kaplan-Meier survival curve shows the survival of the hub genes. The expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), and PCNA in tissues and changes in tumor grade were analyzed. A total of 329 DEGs were identified, including 264 upregulated and 65 downregulated genes. The functions and pathways of DEGs include the mitotic cell cycle, poly(A) RNA binding replication, ATP binding, DNA replication, ribosome biogenesis in eukaryotes, and RNA transport. Forty-seven Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in cell cycle and DNA replication. Patients with mutations in CDK1, PCNA, and CCNB1 had poorer survival rates. CDK1, PCNA, and CCNB1 were significantly overexpressed in the tumor tissues. The expression of CDK1 and CCNB1 gradually decreased with increasing tumor grade. CDK1, CCNB1, and PCNA can be used as potential markers for the diagnosis and prognosis of CRC. These genes are overexpressed in colon cancer tissues and are associated with low survival rates in CRC patients.

Pan-Cancer Analysis of the Associations of TGFBI Expression With Prognosis and Immune Characteristics

Transforming growth factor-beta-induced (TGFBI) protein has important roles in tumor growth, metastasis, and immunity. However, there is currently no pan-cancer evidence regarding TGFBI. In this study, we conducted a pan-cancer analysis of TGFBI mRNA and protein expression and prognoses of various cancer types using public databases. We also investigated the associations of TGFBI expression with tumor microenvironment (TME) components, immune cell infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI), along with the TGFBI genetic alteration types. The results showed that TGFBI expression varied among different cancer types, and it was positively or negatively related to prognosis in various cancers. TGFBI expression was also significantly correlated with TME components, TMB, MSI, immune cell infiltration, and immunoinhibitory and immunostimulatory gene subsets. These findings indicate that TGFBI participates in various immune responses and it may function as a prognostic marker in various cancers. The findings may be useful for developing immunotherapies that target TGFBI.

Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma

BACKGROUND

The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients.

METHODS

The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson's correlation coefficient less than - 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual's OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student's t-test.

RESULTS

In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage.

CONCLUSION

We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients.

The role of the extracellular matrix protein TGFBI in cancer

The secreted extracellular protein, transforming growth factor beta induced (TGFBI or βIGH3), has roles in regulating numerous biological functions, including cell adhesion and bone formation, both during embryonic development and during the pathogenesis of human disease. TGFBI has been most studied in the context of hereditary corneal dystrophies, where mutations in TGFBI result in accumulation of TGFBI in the cornea. In cancer, early studies focused on TGFBI as a tumor suppressor, in part by promoting chemotherapy sensitivity. However, in established tumors, TGFBI largely has a role in promoting tumor progression, with elevated levels correlating to poorer clinical outcomes. As an important regulator of cancer progression, TGFBI expression and function is tightly regulated by numerous mechanisms including epigenetic silencing through promoter methylation and microRNAs. Mechanisms to target TGFBI have potential clinical utility in treating advanced cancers, while assessing TGFBI levels could be a biomarker for chemotherapy resistance and tumor progression.

Hypermethylation of heparanase 2 promotes colorectal cancer proliferation and is associated with poor prognosis

BACKGROUND

The epigenetic abnormality of tumor-associated genes contributes to the pathogenesis of colorectal carcinoma (CRC). However, methylation in colorectal cancer is still poorly characterized.

METHOD

By integration of DNA methylation data from the GEO database and gene expression data from The Cancer Genome Atlas database, the aberrantly methylated genes involved in CRC tumorigenesis were identified. Subsequent in vitro experiments further validated their role in CRC.

RESULTS

We performed integrative genomic analysis and identified HPSE2, a novel tumor suppressor gene that is frequently inactivated through promoter methylation in CRC. K-M survival analysis showed that hypermethylation-low expression of heparanase 2 (HPSE2) was related to poor patient prognosis. Overexpression of HPSE2 reduced cell proliferation in vivo and in vitro. HPSE2 could regulate the p53 signaling pathway to block the cell cycle in G1 phase.

CONCLUSION

HPSE2, a novel tumor suppressor gene that is frequently inactivated through promoter methylation in CRC. HPSE2 performs a tumor suppressive function by activating the p53/ p21 signaling cascade. The promoter hypermethylation of HPSE2 is a potential therapeutic target in patients with CRC, especially those with late-stage CRC.

Identification of MTHFD2 as a novel prognosis biomarker in esophageal carcinoma patients based on transcriptomic data and methylation profiling

DNA methylation is an important epigenetic regulatory mechanism in esophageal carcinoma (EC) and is associated with genomic instability and carcinogenesis. In the present study, we aimed to identify tumor biomarkers for predicting prognosis of EC patients.We downloaded mRNA expression profiles and DNA methylation profiles associated with EC from the Gene Expression Omnibus database. Differentially expressed and differentially methylated genes between tumor tissues and adjacent normal tissue samples were identified. Functional enrichment analyses were performed, followed by the construction of protein-protein interaction networks. Data were validated based on methylation profiles from The Cancer Genome Atlas. Candidate genes were further verified according to survival analysis and Cox regression analysis.We uncovered multiple genes with differential expression or methylation in tumor samples compared with normal samples. After taking the intersection of 3 differential gene sets, we obtained a total of 232 overlapping genes. Functional enrichment analysis revealed that these genes are related to pathways such as "glutathione metabolism," "p53 signaling pathway," and "focal adhesion." Furthermore, 8 hub genes with inversed expression and methylation correlation were identified as candidate genes. The abnormal expression levels of MSN, PELI1, and MTHFD2 were correlated with overall survival times in EC patients (P < .05). Only MTHFD2 was significantly associated with a pathologic stage according to univariate analysis (P = .037) and multivariate analysis (P = .043).Our study identified several novel EC biomarkers with prognostic value by integrated analysis of transcriptomic data and methylation profiles. MTHFD2 could serve as an independent biomarker for predicting prognosis and pathological stages of EC.

High expression of TCN1 is a negative prognostic biomarker and can predict neoadjuvant chemosensitivity of colon cancer

Transcobalamin (TCN1) is a vitamin B12 (cobalamin)-binding protein that regulates cobalamin homeostasis. Recent studies and bioinformatic analyses have found that TCN1 is highly expressed in cancer tissues and is associated with tumour aggressiveness and poor prognosis. The present study aimed to detect TCN1 as a novel biomarker for prognosis and chemosensitivity of colon cancer. Next-generation sequencing showed that TCN1 was one of several upregulated mRNAs in colon cancer, which was verified by further bioinformatics analyses. Western blotting (n = 9) and quantitative real time polymerase chain reaction (qRT-PCR, n = 30) revealed that TCN1 was highly expressed in colon cancer tissues at both the protein and mRNA level. A total of 194 cases of colon cancer were examined by immunohistochemistry and revealed that TCN1 expression level was related to advanced stages (P < 0.005). Kaplan-Meier analysis verified that patients with lower TCN1 expression usually had longer overall survival (P = 0.008). In addition, TCN1 was highly expressed in pulmonary metastatic tumour tissues (n = 37, P = 0.025) and exhibited higher levels in right-sided colon cancer than in left-sided colon cancer (P = 0.029). TCN1 expression in specimens that had received neoadjuvant chemotherapy decreased compared with that in colonoscopy biopsy tissues (n = 42, P = 0.009). Further bioinformatics analyses verified that apoptosis pathways might have a role in high TCN1 expression. All the studies revealed that TCN1 expression in colon cancer was significantly associated with malignant biological behaviour. Therefore, TCN1 could be used as a novel biomarker for colon cancer aggressiveness and prognosis and might also be a potential biomarker for predicting neoadjuvant chemosensitivity.

A novel epigenetic signature to predict recurrence-free survival in patients with colon cancer

BACKGROUND

DNA methylation plays an important role in the initiation and progression of colon cancer. The aim of the present study was to perform a comprehensive analysis of DNA methylation and gene expression profiles in order to develop a signature to predict recurrence-free survival (RFS) of colon cancer.

METHODS

DNA methylation and mRNA expression data were obtained from TCGA database, and were analyzed using an R package MethylMix. Functional enrichment analysis was performed on statistically significant genes identified by MethylMix criteria. The epigenetic signature and nomogram associated with the RFS of colon cancer were established by the Least Absolute Shrinkage and Selection Operator (LASSO) Cox model. Additionally, a joint survival analysis of gene expression and methylation was performed to identify potential prognostic factors for patients with colon cancer.

RESULTS

A total of 179 differentially methylated genes were obtained using MethylMix algorithm. An epigenetic signature for RFS was developed using LASSO. Patients with high-risk had significantly worse RFS than those with low-risk. The signature is independent of clinicopathological variables and indicated better predictive power than other clinicopathological variables in patients with colon cancer. Moreover, joint survival analysis of gene expression and methylation revealed that seven methylated genes could be independent prognostic factors for RFS in colon cancer.

CONCLUSIONS

Our proposed epigenetic signature presents potential prognostic significance in assessing recurrence risk stratification for patients with colon cancer.

DNA-methylated gene markers for colorectal cancer in TCGA database

Colorectal cancer (CRC) is characterized by the accumulation of genetic and epigenetic alterations in neoplastic processes. DNA methylation, as an important epigenetic process, contributes to the development of CRC. In the present study, the epigenetic landscape of genes in CRC was characterized by analyzing the dataset from The Cancer Genome Atlas database and 177 DNA-methylated genes were screened based on the criterion of the Pearson correlation (R) between expression and methylation levels being >0.4. Pathway enrichment analysis revealed prominent pathways, including transcription and metabolism, further implying their significant role in tumorigenesis. Among the methylated genes, only zinc finger protein (ZNF)726 with aberrant expression was determined to affect overall survival (OS) as well as disease-free survival of patients with CRC. In addition, ZNF726 was identified as an independent prognostic risk factor for OS in patients with CRC. The methylation-based regulation of ZNF726 expression in CRC cells was further assessed using the Cancer Cell Line Encyclopedia database. Finally, the CpG island methylation of the ZNF726 promoter was evaluated to further elucidate its role in the development of CRC. In conclusion, the epigenetic landscape of genes in terms of promoter methylation in CRC was characterized, revealing that aberrant expression of ZNF726 may be an independent prognostic risk factor for OS in patients with CRC.

SOX9: The master regulator of cell fate in breast cancer

SRY-related high-mobility group box 9 (SOX9) is an indispensable transcription factor that regulates multiple developmental pathways related to stemness, differentiation, and progenitor development. Previous studies have demonstrated that the SOX9 protein directs pathways involved in tumor initiation, proliferation, migration, chemoresistance, and stem cell maintenance, thereby regulating tumorigenesis as an oncogene. SOX9 overexpression is a frequent event in breast cancer (BC) subtypes. Of note, the molecular mechanisms and functional regulation underlying SOX9 upregulation during BC progression are still being uncovered. The focus of this review is to appraise recent advances regarding the involvement of SOX9 in BC pathogenesis. First, we provide a general overview of SOX9 structure and function, as well as its involvement in various kinds of cancer. Next, we discuss pathways of SOX9 regulation, particularly its miRNA-mediated regulation, in BC. Finally, we describe the involvement of SOX9 in BC pathogenesis via its regulation of pathways involved in regulating cancer hallmarks, as well as its clinical and therapeutic importance. In general, this review article aims to serve as an ample source of knowledge on the involvement of SOX9 in BC progression. Targeting SOX9 activity may improve therapeutic strategies to treat BC, but precisely inhibiting SOX9 using drugs and/or small peptides remains a huge challenge for forthcoming cancer research.

A gas chromatography-mass spectrometry (GC-MS) metabolomic approach in human colorectal cancer (CRC): the emerging role of monosaccharides and amino acids

Background

Colorectal cancer (CRC) has been confirmed to be the third most commonly diagnosed cancer in males and the second in females. We investigated the blood plasma metabolome in CRC patients and in healthy adults to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways as prognostic factors in patients with CRC.

Methods

Fifteen patients with CRC and nine healthy adults were enrolled in the study and their blood plasma samples analyzed by gas chromatography-mass spectrometry (GC-MS). Univariate Student's t-test, multivariate principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were conducted on MetaboAnalyst 4.0. The analysis of metabolic profiles was carried out by the web-based extension Metabolite Sets Enrichment Analysis (MSEA).

Results

Overall, 125 metabolites were identified in plasma samples by GC-MS. In CRC patient samples, nine metabolites, including D-mannose and fructose, were significantly more abundant than in controls; conversely, eleven amino derivatives were less abundant, including methionine, valine, lysine, and proline. Methionine was significantly less abundant in died patients compared with survivors. The most significantly altered metabolic pathways in CRC patients are those involving monosaccharides (primarily the catabolic pathway of fructose and D-mannose), and amino acids (primarily methionine, valine, leucine, and isoleucine).

Conclusions

The abundance of D-mannose in CRC patient samples contributes to inhibiting the growth of cancer cells, while the abundance of fructose may be consistent either with low consumption of fructose by aerobic glycolysis within cancer cells or with a high bioavailability of fructose from diet. The reduction in methionine concentration may be related to increased activity of the threonine and methionine catabolic pathways, confirmed by high levels of α-hydroxybutyrate.

Identification of key genes involved in the development and progression of early-onset colorectal cancer by co-expression network analysis

A number of studies have revealed that there is an increasing incidence of early-onset colorectal cancer (CRC) in young adults (before the age of 50 years) and a progressive decline in CRC among older patients, after the age of 50 years (late-onset CRC). However, the etiology of early-onset CRC is not fully understood. The aim of the present study was to identify key genes associated with the development of early-onset CRC through weighted gene co-expression network analysis (WGCNA). The GSE39582 dataset was downloaded from the Gene Expression Omnibus database, and the data profiles of tissues from patients diagnosed before the age of 50 years were selected. The top 10,000 genes with the highest variability were used to construct the WGCNA. Hub genes were identified from the modules associated with clinical traits using gene significance >0.2 and module membership >0.8 as the cut-off criteria. Gene Ontology and pathway analyses were subsequently performed on the hub genes and a protein-protein interaction network (PPI) was constructed. The diagnostic value of module hub genes with a degree score >5 in the PPI network was verified in samples from patients with CRC diagnosed before the age of 50 years obtained from The Cancer Genome Atlas. Eight co-expressed gene modules were identified in the WGCNA and two modules (blue and turquoise) were associated with the tumor-node-metastasis stage. A total of 140 module hub genes were identified and found to be enriched in 'mitochondrial large ribosomal subunit', 'structural constituent of ribosome', 'poly (A) RNA binding', 'collagen binding', 'protein ubiquitination' and 'ribosome pathway'. Twenty-six module hub genes were found to have a degree score >5 in the PPI network, seven of which [secreted protein acidic and cysteine rich (SPARC), decorin (DCN), fibrillin 1 (FBN1), WW domain containing transcription regulator 1 (WWTR1), transgelin (TAGLN), DEAD-box helicase 28 (DDX28) and cold shock domain containing C2 (CSDC2)], had good prognostic values for patients with early-onset CRC, but not late-onset CRC. Therefore, SPARC, DCN, FBN1, WWTR1, TAGLN, DDX28 and CSDC2 may contribute to the development of early-onset CRC and may serve as potential diagnostic biomarkers.

Multiplexed real-time polymerase chain reaction cell-free DNA assay as a potential method to monitor stage IV colorectal cancer

BACKGROUND

Liquid biopsy is a new area in cancer diagnostics that measures cell-free DNA in plasma from tumor that may serve as a monitoring tool in colorectal cancer patients.

METHODS

Multiplexed real-time polymerase chain reaction based on multicopy retro-transposable elements (targeting 80 base pair and 265 base pair sequences and an internal-positive-control) was used to evaluate the ability of cell-free DNA concentration and DNA Integrity Index to discriminate cancer from healthy patients. A cohort of 40 healthy controls and 39 stage IV colorectal patient's plasma were interrogated. The potency of each biomarker was measured by using receiver operating characteristic curves and derived area under the curve measures.

RESULTS

Significant differences in cell-free DNA concentration and DNA integrity index were observed between controls and stage IV patients with a limit of detection <0.1 pg/μL. Investigation of the ability of both biomarker candidates to differentiate cancer from healthy patients showed an area under the curve of 0.9891 and 0.9859 for 80 base pair and 265 amplicons respectively and 0.8603 for DNA integrity index-265/80.

CONCLUSIONS

After establishing differences in cell-free DNA levels between healthy and treated and untreated stage IV patients, the multiplexed real-time polymerase chain reaction measurements of retro-transposable elements in cancer patient plasma potentially possess the ability to monitor therapy responsiveness in near real time.