Epigenomic biomarkers for prognostication and diagnosis of gastrointestinal cancers

Epigenetic regulation of major histocompatibility complexes in gastrointestinal malignancies and the potential for clinical interception

BACKGROUND

Gastrointestinal malignancies encompass a diverse group of cancers that pose significant challenges to global health. The major histocompatibility complex (MHC) plays a pivotal role in immune surveillance, orchestrating the recognition and elimination of tumor cells by the immune system. However, the intricate regulation of MHC gene expression is susceptible to dynamic epigenetic modification, which can influence functionality and pathological outcomes.

MAIN BODY

By understanding the epigenetic alterations that drive MHC downregulation, insights are gained into the molecular mechanisms underlying immune escape, tumor progression, and immunotherapy resistance. This systematic review examines the current literature on epigenetic mechanisms that contribute to MHC deregulation in esophageal, gastric, pancreatic, hepatic and colorectal malignancies. Potential clinical implications are discussed of targeting aberrant epigenetic modifications to restore MHC expression and 0 the effectiveness of immunotherapeutic interventions.

CONCLUSION

The integration of epigenetic-targeted therapies with immunotherapies holds great potential for improving clinical outcomes in patients with gastrointestinal malignancies and represents a compelling avenue for future research and therapeutic development.

Integrated multi-omics analyses reveal the TM4SF family genes with prognostic and therapeutic relevance in hepatocellular carcinoma

TM4SF family members (TM4SFs) have been shown to be aberrantly expressed in multiple types of cancer. However, a comprehensive investigation of the TM4SFs has yet to be performed in LIHC. The study comprehensively investigated the expression and prognostic value of TM4SFs. Then, a TM4SFs-based risk model and nomogram were constructed for prognostic prediction. Finally, functional loss of TM4SFs was performed to verify the potential role of TM4SFs in LIHC. We found that TM4SFs were significantly up-regulated in LIHC. High expression and hypomethylation of TM4SFs were associated with poor prognosis of LIHC patients. Then, a TM4SFs-based risk model was constructed that could effectively classify LIHC patients into high and low-risk groups. In addition, we constructed a prognostic nomogram that could predict the long-term survival of LIHC patients. Based on immune infiltration analysis, high-risk patients had a relatively higher immune status than low-risk patients. Moreover, the prediction module could predict patient responses to immunotherapy and chemotherapy. Finally, loss-of-function studies showed that TM4SF4 knockdown could substantially suppress the growth, migratory, and invasive abilities of LIHC cells. Targeting TM4SFs will contribute to effective immunotherapy strategies and improve the prognosis of liver cancer patients.

A sensitive and robust plasma-based DNA methylation panel for early detection of target gastrointestinal cancers

BACKGROUND

Target gastrointestinal cancers (GICs), encompassing esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC), originate within a single readily accessible luminal organ system and are diagnosable using endoscopy. However, endoscopy is an invasive procedure with low compliance and no plasma-based DNA methylation assay for the early detection of GICs.

METHODS

Nine potential DNA methylation markers were identified and evaluated in tissue (n=60) and plasma (n=155) cohorts to select the most suitable markers. A training cohort (n=244) and a validation cohort (n=199), including GICs patients, benign tumors, gastrointestinal polyps, and controls, were enrolled to develop and validate a DNA methylation panel. An independent prospective cohort (n=158) was used to validate the panel's performance and compare it with blood protein tumor markers.

RESULTS

Six out of nine candidate methylation markers with excellent discrimination abilities in both tissue and plasma cohorts were selected for the DNA methylation panel. The panel demonstrated high AUC values of 0.937 (EC), 0.968 (GC), and 0.987 (CRC) in training cohort, and achieved AUC values of 0.921 (EC), 0.921 (GC), and 0.959 (CRC) in validation cohort. Notably, it achieved impressive AUC values of 0.971 and 0.843 for identifying stage I GICs in the training and validation cohorts, respectively. In the prospective cohort, the six-marker panel showed comparable AUC values to CEA, AFP, and CA19-9 (0.935, 0.769, 0.663, and 0.668, respectively).

CONCLUSION

This study successfully developed and validated a novel, robust, sensitive, and specific plasma-based DNA methylation panel, offering a promising strategy for the early detection of GICs.

Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment

Research into the potential benefits of artificial intelligence for comprehending the intricate biology of cancer has grown as a result of the widespread use of deep learning and machine learning in the healthcare sector and the availability of highly specialized cancer datasets. Here, we review new artificial intelligence approaches and how they are being used in oncology. We describe how artificial intelligence might be used in the detection, prognosis, and administration of cancer treatments and introduce the use of the latest large language models such as ChatGPT in oncology clinics. We highlight artificial intelligence applications for omics data types, and we offer perspectives on how the various data types might be combined to create decision-support tools. We also evaluate the present constraints and challenges to applying artificial intelligence in precision oncology. Finally, we discuss how current challenges may be surmounted to make artificial intelligence useful in clinical settings in the future.

Identification of HnRNP Family as Prognostic Biomarkers in Five Major Types of Gastrointestinal Cancer

BACKGROUND

Heterogeneous nuclear ribonucleoproteins (hnRNPs), a large family of RNAbinding proteins, have been implicated in tumor progression in multiple cancer types. However, the expression pattern and prognostic value of hnRNPs in five gastrointestinal (GI) cancers, including gastric, colorectal, esophageal, liver, and pancreatic cancer, remain to be investigated.

OBJECTIVE

The current research aimed to identify prognostic biomarkers of the hnRNP family in five major types of gastrointestinal cancer.

METHODS

Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), and Kaplan-Meier Plotter were used to explore the hnRNPs expression levels concerning clinicopathological parameters and prognostic values. The protein level of hnRNPU was validated by immunohistochemistry (IHC) in human tissue specimens. Genetic alterations of hnRNPs were analyzed using cBioportal, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to illustrate the biological functions of co-expressed genes of hnRNPs.

RESULTS

The vast majority of hnRNPs were highly expressed in five types of GI cancer tissues compared to their adjacent normal tissues, and mRNA levels of hnRNPA2B1, D, Q, R, and U were significantly different in various GI cancer types at different stages. In addition, Kaplan-Meier analysis revealed that the increased hnRNPs expression levels were correlated with better prognosis in gastric and rectal cancer patients (log-rank p < 0.05). In contrast, patients with high levels of hnRNPs exhibited a worse prognosis in esophageal and liver cancer (log-rank p < 0.05). Using immunohistochemistry, we further confirmed that hnRNPU was overexpressed in gastric, rectal, and liver cancers. In addition, hnRNPs genes were altered in patients with GI cancers, and RNA-related processing was correlated with hnRNPs alterations.

CONCLUSION

We identified differentially expressed genes of hnRNPs in tumor tissues versus adjacent normal tissues, which might contribute to predicting tumor types, early diagnosis, and targeted therapies in five major types of GI cancer.

Tumor DNA Methylation Profiles Enable Diagnosis, Prognosis Prediction, and Screening for Cervical Cancer

Background

DNA-methylation-based machine learning algorithms have demonstrated powerful diagnostic capabilities, and these tools are currently emerging in many fields of tumor diagnosis and patient prognosis prediction. This work aimed to identify novel DNA methylation diagnostic biomarkers for differentiating cervical cancer (CC) from normal tissues, as well as a prognostic prediction model to predict survival of CC patients.

Methods

The methylation profiles with the available clinical characteristics were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) program. We first screened out the differential methylation sites in CC and normal tissues and performed multiple statistical analyses to discover DNA methylation diagnostic markers that are used to distinguish CC and normal control. Then, we developed a methylation-based survival model to improve risk stratification.

Results

A diagnostic prediction panel consists of five CpG markers that could predict cervical cancer versus normal tissue with highly correct rate of 100%, and cg16428251, cg22341310, and cg23316360 which in diagnostic prediction panel all could yield high sensitivity and specificity for detection of CC and normal in six cohorts (area under curve [AUC] > 0.8), in addition to excellent performance in discriminating between CC and normal sample. The diagnostic marker panel also effectively predicted the CIN3 versus normal tissue with high accuracy in two datasets (AUC = 0.80, 0.789, respectively). Furthermore, a prognostic prediction model aggregated two CpG markers that effectively stratified the prognosis of high-risk and low-risk groups (training cohort: hazard ratio [HR] 4, 95% CI: 1.7–9.6, P = 0.0021; testing cohort: hazard ratio [HR] 1.9, 95% CI: 1.2–3.1, P = 0.0072).

Conclusion

The findings of our study showed that DNA methylation markers are of great value in the diagnosis and prognosis of CC.

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

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

DNA methylation-mediated down-regulation of TMEM130 promotes cell migration in breast cancer

BACKGROUND

Breast cancer is the most common female cancer worldwide. DNA methylation is a common modification in epigenetics and affects the prognosis of breast cancer by changing gene expression. In the present study, we aim to investigate the role of DNA methylation in TMEM130 gene expression, and the function of TMEM130 in breast cancer cell migration.

METHODS

The transcriptional expression of TMEM130 was detected by qRT-PCR in breast cancer cell lines and tissues. Bisulfite sequencing PCR (BSP) was used to confirm the methylation status of TMEM130 promoter. Then, TMEM130 was transfected in breast cancer cell lines and to explore its role in cell migration by Transwell and western blot.

RESULTS

TMEM130 mRNA expression was decreased in breast cancer cell lines and tissues, and consistent with the data in The Cancer Genome Atlas (TCGA). The promoter of TMEM130 was hypermethylated in breast cancer and the expression of TMEM130 could be restored by the methyltransferase inhibitor. Overexpression of TMEM130 could inhibit cell migration ability in breast cancer cell lines.

CONCLUSION

Taken together, these results indicate TMEM130 downregulation and hypermethylation might contribute to breast cancer migration and TMEM130 might be a promising biomarker for breast cancer.

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.

Prognostic role of SIRT6 in gastrointestinal cancers: a meta-analysis

Sirtuin 6 (SIRT6) plays a critical role in the progression and development of gastrointestinal cancers. However, the association between SIRT6 expression and clinicopathological parameters and prognosis in gastrointestinal cancer patients remains inconclusive. Consequently, we conducted this meta-analysis to evaluate the importance of SIRT6 expression in various types of gastrointestinal cancers. PubMed, EMBASE, and Web of Science databases were systematically searched to screen the relevant literature. The reported or estimated hazard ratio (HR) and odds ratio (OR) and their corresponding 95% confidence interval (CI) were pooled to assess the strength of the association. Nine studies involving 867 patients were included in the meta-analysis. Overall analysis showed that high SIRT6 expression was related to better overall survival in gastrointestinal cancers (HR = 0.62, 95% CI = 0.47–0.82). High SIRT6 expression was also related to a favorable tumor node metastasis (TNM) stage (OR = 0.44, 95% CI = 0.28–0.70) among gastrointestinal cancer patients. Our meta-analysis revealed that high SIRT6 expression might be a potential biomarker predicting better prognosis in gastrointestinal cancers, which may offer options for gastrointestinal cancer treatment.

Epigenetic silencing of ZIC4 contributes to cancer progression in hepatocellular carcinoma

Inactivation of tumor suppressor gene played critical roles in the development and progression of human hepatocellular carcinoma (HCC). Zic family member 4 (ZIC4) is transcription factor and plays an important role in the developmental process. However, the expression and biological role of ZIC4 in HCC is poorly understood. Here, bioinformatics analysis based on The Cancer Genome Atlas (TCGA) database revealed an aberrant hypermethylation of ZIC4 in HCC. ZIC4 is frequently hypermethylated in promoter region and down expressed in HCC cells and tissues. Functionally, ZIC4 inhibition facilitated the proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in vitro and in vivo. Conversely, ZIC4 overexpression reduced proliferation and invasiveness of HCC cells. In addition, ZIC4 inhibition rescued the antitumor effect induced by enhancer of zeste homolog 2 (EZH2) knockdown or EZH2 inhibitor. Mechanistically, EZH2 knockdown or EZH2 inhibitor reduced the enrichment of EZH2 and H3K27me3 in ZIC4 promoter region and leading to the upregulation of ZIC4. Altogether, these data indicate that epigenetic silencing of ZIC4 by EZH2 mediated H3K27me3 is an important mechanism in HCC and provide a new therapeutic target for the treatment of hepatocellular carcinoma disease.

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.

Promoter aberrant methylation status of ADRA1A is associated with hepatocellular carcinoma

The aim of our study was to explore the relationship between the methylation status of the alpha-1A adrenergic receptor (ADRA1A) gene and hepatocellular carcinoma (HCC). We combined our in-house data-set with the Cancer Genome Atlas (TCGA) data-set to screen and identify the methylation status and expression of adrenergic receptor (AR) genes in HCC. Immunohistochemistry and western blot were performed to assess the expression of ADRA1A in HCC cell lines and tissues. We further evaluated the methylation levels of the ADRA1A promoter region in 160 HCC patients using the Sequenom MassARRAY® platform and investigated the association between methylation of ADRA1A and clinical characteristics. The expression levels of ADRA1A mRNA and protein were significantly decreased in HCC tissues. Compared with that in paired normal tissues, the mean methylation level of the ADRA1A promoter region was significantly increased in tumour tissues from 160 HCC patients (25.2% vs. 17.0%, P < 0.0001). We found that a DNA methyltransferase inhibitor (decitabine) could increase the expression of ADRA1A mRNA in HCC cell lines. Moreover, hypermethylation of the ADRA1A gene in HCC samples was associated with clinical characteristics, including alcohol intake (P = 0.0097) and alpha-fetoprotein (P = 0.0411). Receiver operator characteristic (ROC) curve analysis demonstrated that the mean methylation levels of ADRA1A could discriminate between HCC tissues and adjacent non-cancerous tissues (AUC = 0.700, P < 0.0001). mRNA sequencing indicated that the main enriched pathways were pathways in cancer, cytokine-cytokine receptor interaction and metabolic pathways (P < 0.01). ADRA1A gene hypermethylation might contribute to HCC initiation and is a promising biomarker for the diagnosis of HCC.

Combined Analysis of the Aberrant Epigenetic Alteration of Pancreatic Ductal Adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most fatal malignancies due to its high morbidity and mortality. DNA methylation exerts a vital part in the development of PDAC. However, a mechanistic role of mutual interactions between DNA methylation and mRNA as epigenetic regulators on transcriptomic alterations and its correlation with clinical outcomes such as survival have remained largely uncovered in cancer. Therefore, elucidation of aberrant epigenetic alteration in the development of PDAC is an urgent problem to be solved. In this work, we conduct an integrative epigenetic analysis of PDAC to identify aberrant DNA methylation-driven cancer genes during the occurrence of cancer.

METHODS

DNA methylation matrix and mRNA profile were obtained from the TCGA database. The integration of methylation and gene expression datasets was analyzed using an R package MethylMix. The genes with hypomethylation/hypermethylation were further validated in the Kaplan-Meier analysis. The correlation analysis of gene expression and aberrant DNA methylation was also conducted. We performed a pathway analysis on aberrant DNG methylation genes identified by MethylMix criteria using ConsensusPathDB.

RESULTS

188 patients with both methylation data and mRNA data were considered eligible. A mixture model was constructed, and differential methylation genes in normal and tumor groups using the Wilcoxon rank test was performed. With the inclusion criteria, 95 differential methylation genes were detected. Among these genes, 74 hypermethylation and 21 hypomethylation genes were found. The pathway analysis revealed an increase in hypermethylation of genes involved in ATP-sensitive potassium channels, Robo4, and VEGF signaling pathways crosstalk, and generic transcription pathway.

CONCLUSION

Integrated analysis of the aberrant epigenetic alteration in pancreatic ductal adenocarcinoma indicated that differentially methylated genes could play a vital role in the occurrence of PDAC by bioinformatics analysis. The present work can help clinicians to elaborate on the function of differentially methylated expressed genes and pathways in PDAC. CDO1, GJD2, ID4, NOL4, PAX6, TRIM58, and ZNF382 might act as aberrantly DNA-methylated biomarkers for early screening and therapy of PDAC in the future.

High pretreatment plasma D-dimer levels predict poor prognosis in gastrointestinal cancers: A meta-analysis

BACKGROUND

High pretreatment plasma D-dimer levels can predict poor prognosis in various types of gastrointestinal carcinomas. Our meta-analysis explored the correlation between plasma D-dimer levels and prognosis in gastrointestinal malignancies.

METHODS

Two independent reviewers conducted a comprehensive search from PubMed, ScienceDirect, Embase, Web of Science and the Cochrane Library. All articles evaluating the correlation between pretreatment plasma D-dimer levels and prognosis in gastrointestinal malignancies were searched. We chose overall survival (OS) as the primary survival outcome measure and progression-free survival (PFS), disease-free survival (DFS) and cancer-specific survival (CSS) as the secondary survival outcome measures. We extracted hazard ratios (HRs) and 95% confidence intervals (CIs) from the eligible publications.

RESULTS

We included 30 studies involving 5928 gastrointestinal cancer patients. There was an obvious correlation between high D-dimer levels and poor OS (HR = 2.01, 95% CI = 1.72-2.36, P < .01). High plasma D-dimer levels were correlated with shorter PFS (HR = 1.34, 95% CI = 1.05-1.70, P = .32), DFS (HR =  1.67, 95% CI = 1.12-2.50, P < .01) and CSS rates (HR = 1.93, 95% CI = 1.49-2.49, P = .66).

CONCLUSIONS

Elevated pretreatment plasma D-dimer levels might help predict poor prognosis in patients with gastrointestinal malignancies.