Identifying potential DNA methylation markers in early-stage colorectal Cancer

Early detection and diagnosis of cancer with interpretable machine learning to uncover cancer-specific DNA methylation patterns

Cancer, a collection of more than two hundred different diseases, remains a leading cause of morbidity and mortality worldwide. Usually detected at the advanced stages of disease, metastatic cancer accounts for 90% of cancer-associated deaths. Therefore, the early detection of cancer, combined with current therapies, would have a significant impact on survival and treatment of various cancer types. Epigenetic changes such as DNA methylation are some of the early events underlying carcinogenesis. Here, we report on an interpretable machine learning model that can classify 13 cancer types as well as non-cancer tissue samples using only DNA methylome data, with 98.2% accuracy. We utilize the features identified by this model to develop EMethylNET, a robust model consisting of an XGBoost model that provides information to a deep neural network that can generalize to independent data sets. We also demonstrate that the methylation-associated genomic loci detected by the classifier are associated with genes, pathways and networks involved in cancer, providing insights into the epigenomic regulation of carcinogenesis.

Precision medicine in colorectal cancer: Leveraging multi-omics, spatial omics, and artificial intelligence

Colorectal cancer (CRC) is a leading cause of cancer-related deaths. Recent advancements in genomic technologies and analytical approaches have revolutionized CRC research, enabling precision medicine. This review highlights the integration of multi-omics, spatial omics, and artificial intelligence (AI) in advancing precision medicine for CRC. Multi-omics approaches have uncovered molecular mechanisms driving CRC progression, while spatial omics have provided insights into the spatial heterogeneity of gene expression in CRC tissues. AI techniques have been utilized to analyze complex datasets, identify new treatment targets, and enhance diagnosis and prognosis. Despite the tumor's heterogeneity and genetic and epigenetic complexity, the fusion of multi-omics, spatial omics, and AI shows the potential to overcome these challenges and advance precision medicine in CRC. The future lies in integrating these technologies to provide deeper insights and enable personalized therapies for CRC patients.

DNA methylation modulates epigenetic regulation in colorectal cancer diagnosis, prognosis and precision medicine

Colorectal cancer (CRC) is a multifaceted disease influenced by the interplay of genetic and environmental factors. The clinical heterogeneity of CRC cannot be attributed exclusively to genetic diversity and environmental exposures, and epigenetic markers, especially DNA methylation, play a critical role as key molecular markers of cancer. This review compiles a comprehensive body of evidence underscoring the significant involvement of DNA methylation modifications in the pathogenesis of CRC. Moreover, this review explores the potential utility of DNA methylation in cancer diagnosis, prognostics, assessment of disease activity, and prediction of drug responses. Recognizing the impact of DNA methylation will enhance the ability to identify distinct CRC subtypes, paving the way for personalized treatment strategies and advancing precision medicine in the management of CRC.

YAP1 expression is associated with survival and immunosuppression in small cell lung cancer

Immunotherapy is considered a major breakthrough in the treatment of small cell lung cancer (SCLC), although its anti-tumor efficacy is limited. With a high degree of malignancy and high heterogeneity, SCLC is difficult to treat in the clinic. A new combination strategy is urgently needed to further improve the efficacy of immunotherapy in patients with SCLC. By immunofluorescence, 100 SCLC patients in a local cohort were classified into the SCLC-A (high ASCL1 expression; n = 36), SCLC-N (high NEUROD1 expression; n = 32), SCLC-P (high POU2F3 expression; n = 14), and SCLC-Y (high YAP1 expression; n = 18) subtypes. Each SCLC molecular subtype represented different prognoses, tumor microenvironment traits, and immunotherapy sensitivities. Analysis of both the local and public cohorts suggested that the SCLC-Y subtype exhibited the worst clinical outcome (p < 0.05) when compared with other subtypes. SCLC with high YAP1 expression was characterized by high PD-L1 expression, high stromal score, T-cell functional impairment, and a close relationship with immune-related pathways. YAP1 upregulated PD-L1 expression and suppressed T cell activation, thus leading to immune evasion. In in vitro experiments, blockade of YAP1 promoted cancer cell apoptosis, immune cell proliferation, T-cell activation, and cytotoxic T-cell infiltration, thus further potentiating the efficacy of immunotherapy in patients with the SCLC-Y subtype.

FAM72 family proteins as poor prognostic markers in clear cell renal carcinoma

Purpose

This study aimed to investigate the prognostic significance of the Family with Sequence Similarity 72 member (FAM72) gene family in clear cell renal carcinoma (ccRCC) using a bioinformatic approach.

Patients and methods

To investigate the association between FAM72 and ccRCC, we utilized various databases and analysis tools, including TCGA, GEPIA, Metscape, cBioPortal, and MethSurv. We conducted an analysis of FAM72 expression levels in ccRCC tissues compared to normal kidney tissues and performed univariate and multivariate Cox analysis to determine the relationship between FAM72 expression and patient prognosis. Furthermore, we carried out Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) to identify enriched biological processes associated with FAM72 expression. Additionally, we analyzed immune cell infiltration and the level of methylation in ccRCC patients. Our bioinformatic analysis revealed that FAM72 expression levels were significantly higher in ccRCC tissues than in normal kidney tissues. High expression of FAM72 was associated with poor prognosis in ccRCC patients and was found to be an independent prognostic factor for ccRCC. GO and GSEA analyses indicated that FAM72 was enriched in biological processes related to mitosis, cell cycle, and DNA metabolism. Moreover, we found a significant correlation between FAM72 and immune cell infiltration and the level of methylation in ccRCC patients.

Conclusion

Our findings suggest that FAM72 could serve as an unfavorable prognostic molecular marker for ccRCC. A comprehensive understanding of FAM72 could provide crucial insights into tumor progression and prognosis.

Construction of a prediction model for prognosis of bladder cancer based on the expression of ion channel-related genes

OBJECTIVES

To construct a prediction model for the prognosis of bladder cancer patients based on the expression of ion channel-related genes (ICRGs).

METHODS

ICRGs were obtained from the existing researches. The clinical information and the expression of ICRGs mRNA in breast cancer patients were obtained from the Cancer Genome Atlas database. Cox regression analysis, minimum absolute shrinkage and selection operator regression analysis were used to screen breast cancer prognosis related genes, which were verified by immunohistochemistry and qRT-PCR. The risk scoring equation for predicting the prognosis of patients with bladder cancer was constructed, and the patients were divided into high-risk group and low-risk group according to the median risk score. Immune cell infiltration was compared between the two groups. Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to evaluate the accuracy and clinical application value of the risk scoring equation. The factors related to the prognosis of bladder cancer patients were analyzed by univariate and multivariate Cox regression, and a nomogram for predicting the prognosis of bladder cancer patients was constructed.

RESULTS

By comparing the expression levels of ICRGs in bladder cancer tissues and normal bladder tissues, 73 differentially expressed ICRGs were dentified, of which 11 were related to the prognosis of bladder cancer patients. Kaplan-Meier survival curve suggested that the risk score based on these 11 genes was negatively correlated with the prognosis of patients. The area under the ROC curve of the risk score for predicting the prognosis of patients at 1, 3 and 5 year was 0.634, 0.665 and 0.712, respectively. Stratified analysis showed that the ICRGs-based risk score performed well in predicting the prognosis of patients with American Joint Committee on Cancer (AJCC) stage Ⅲ-Ⅳ bladder cancer (P<0.05), while it had a poor value in predicting the prognosis of patients with AJCC stage Ⅰ-Ⅱ (P>0.05). There were significant differences in the infiltration of plasma cells, activated natural killer cells, resting mast cells and M2 macrophages between the high-risk group and the low-risk group. Cox regression analysis showed that risk score, smoking, age and AJCC stage were independently associated with the prognosis of patients with bladder cancer (P<0.05). The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1, 3 and 5 year overall survival rate of bladder cancer patients.

CONCLUSIONS

The study shows the potential value of ICRGs in the prognostic risk assessment of bladder cancer patients. The constructed prognostic nomogram based on ICRGs risk score has high accuracy in predicting the prognosis of bladder cancer patients.

Identification of genes critical for inducing ulcerative colitis and exploring their tumorigenic potential in human colorectal carcinoma

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease leading to continuous mucosal inflammation in the rectum extending proximally towards the colon. Chronic and/or recurrent UC is one of the critical predisposing mediators of the oncogenesis of human colorectal carcinoma (CRC). Perturbations of the differential expression of the UC-critical genes exert an intense impact on the neoplastic transformation of the affected tissue(s). Herein, a comprehensive exploration of the UC-critical genes from the transcriptomic profiles of UC patients was conducted to study the differential expression, functional enrichment, genomic alterations, signal transduction pathways, and immune infiltration level encountered by these genes concerning the oncogenesis of CRC. The study reveals that WFDC2, TTLL12, THRA, and EPHB3 play crucial roles as UC-CRC critical genes and are positively correlated with the molecular transformation of UC to CRC. Taken together, these genes can be used as potential biomarkers and therapeutic targets for combating UC-induced human CRC.

Recurrence risk assessment for stage III colorectal cancer based on five methylation biomarkers in plasma cell-free DNA

For stage III colorectal cancer (CRC) patients with a high risk of recurrence, intensified adjuvant chemotherapy can improve overall survival. We aimed to develop a circulating tumor DNA (ctDNA) methylation marker model for predicting the relapse risk of stage III CRC patients. Differentially methylated markers identified between 53 normal mucosa samples and 165 CRC tissue samples, as well as between plasma samples from 75 stage I/II (early-stage) CRC patients and 55 stage IV (late-stage) CRC patients, were analyzed using Student's t-tests. The overlapping methylation markers shared by plasma and tissue samples were used to establish a methylation marker model to evaluate the tumor burden in the peripheral blood of CRC patients using the random forest method. This model was verified in the validation cohort (n = 44) and then applied to predict recurrence risk in 50 stage III CRC patients and monitor the clinical disease course in serial samples from four CRC patients. We built a five-marker-based ctDNA methylation model that had high sensitivity (84.21%) and specificity (84%) in identifying late-stage CRC in a validation cohort containing 24 stage I/II CRC patients and 20 stage IV CRC patients. The model achieved high sensitivity (87.5%) and specificity (94.12%) in predicting tumor relapse in an independent cohort of 50 stage III CRC patients and could be an independent recurrence risk factor for stage III patients [Hazard ratio (HR), 60.4; 95% confidence interval (CI): 7.68-397; p = 9.73e-5]. Analysis of serial blood samples of CRC showed that the model could monitor disease relapse earlier than imaging examination and serum carcinoembryonic antigen (CEA) and so may provide an opportunity for the early adjustment of therapeutic strategies. Moreover, the model could potentially monitor the clinical course and treatment response dynamically. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Aberrant circulating tumor DNA methylation and exosomal microRNA biomarkers for early detection of colorectal cancer

INTRODUCTION

Colorectal cancer (CRC) became the third most commonly diagnosed malignancy and the second leading cause of cancer death in 2020. However, the rates of early screening and early diagnosis for CRC remain unsatisfactory. Thus, it is essential to explore the initiating factors of CRC and strategies for its early diagnosis. Research progress in liquid biopsy has led to the finding that circulating tumor-derived DNA (ctDNA) and exosomes play vital roles in early detection of CRC. THE APPLICATIONS OF LIQUID BIOPSY FOR EARLY DETECTION OF COLORECTAL CANCER: Moreover, the increased understanding of epigenetics has highlighted the role of ctDNA methylation in CRC carcinogenesis, and the detection of aberrant ctDNA methylation markers is a feasible strategy for diagnosis of early-stage CRC. Among exosomal markers, microRNAs (miRNAs) are abundant and are the most researched. Upregulated or downregulated expression of exosome-derived miRNAs can indicate the occurrence of early-stage CRC.

FUTURE PERSPECTIVE

The current research progress on aberrant ctDNA methylation and tumor exosomal miRNA biomarkers in early detection of CRC is summarized in this review, and the advantages and shortcomings of the methods are discussed.

A novel DNA methylation marker to identify lymph node metastasis of colorectal cancer

Lymph node metastasis (LNM) of colorectal cancer (CRC) is an important factor for both prognosis and treatment. Given the deficiencies of conventional tests, we aim to discover novel DNA methylation markers to efficiently identify LNM status of CRC. In this study, genome-wide methylation sequencing was performed in a cohort (n=30) using fresh CRC tissue to discover differentially methylated markers. These markers were subsequently validated with fluorescence quantitative PCR in a cohort (n=221), and the optimal marker was compared to conventional diagnostic methods. Meanwhile, immunohistochemistry was used to verify the effectiveness of the antibody corresponding to this marker in a cohort (n=56). LBX2 achieved an AUC of 0.87, specificity of 87.3%, sensitivity of 75.7%, and accuracy of 81.9%, which outperformed conventional methods including imaging (CT, PET-CT) with an AUC of 0.52, CA199 with an AUC of 0.58, CEA with an AUC of 0.56. LBX2 was also superior to clinicopathological indicators including the depth of tumor invasion and lymphatic invasion with an AUC of 0.61and 0.63 respectively. Moreover, the AUC of LBX2 antibody was 0.84, which was also better than these conventional methods. In conclusion, A novel methylation marker LBX2 could be used as a simple, cost-effective, and reliable diagnostic method for LNM of CRC.

Lymph Node Metastasis-Related Gene ITGA4 Promotes the Proliferation, Migration, and Invasion of Gastric Cancer Cells by Regulating Tumor Immune Microenvironment

The Integrin Subunit Alpha 4 (ITGA4) plays important roles in cancers pathogenesis. However, the expression and association with clinicopathological and survival probability have not been previously assessed in gastric cancer (GC). Protein expression of ITGA4 was assessed in TMA using immunohistochemistry and correlated with clinicopathological factors and survival. The mRNA expression of ITGA4 was also assessed in the HMU-GC cohort. Bioinformatics function analysis was conducted through GSEA. The “CIBERSORT” package was used for immune infiltration analysis. “SvyNom” package is used to construct prognosis model. ITGA4 knock down using shRNA. The evaluation of cell function was performed by CCK-8 and Transwell invasion and migration experiments. ITGA4 was significantly associated with N classification ( $P=0.031$ ), tumor location ( $P=0.033$ ), WHO classification ( $P=0.007$ ), and poor prognosis in mRNA level. GSEA analysis of the validation cohort suggested that ITGA4 was associated with macrophage infiltration. Immunohistochemistry showed that ITGA4 was associated with poor prognosis. Multivariate Cox regression analysis found that ITGA4 ( $P=0.045$ ) and lymph node metastasis rate ( $P=0.026$ ) were independent prognostic factors and could construct a prognosis model. ITGA4 knockdown cell line significantly reduced the ability of proliferation, invasion, and metastasis. ITGA4 is associated with patient survival in GC and may be an important prognostic biomarker.

Construction of Prognostic Risk Model of Patients with Skin Cutaneous Melanoma Based on TCGA-SKCM Methylation Cohort

Skin cutaneous melanoma (SKCM) is a common malignant skin cancer. Early diagnosis could effectively reduce SKCM patient's mortality to a large extent. We managed to construct a model to examine the prognosis of SKCM patients. The methylation-related data and clinical data of The Cancer Gene Atlas- (TCGA-) SKCM were downloaded from TCGA database. After preprocessing the methylation data, 21,861 prognosis-related methylated sites potentially associated with prognosis were obtained using the univariate Cox regression analysis and multivariate Cox regression analysis. Afterward, unsupervised clustering was used to divide the patients into 4 clusters, and weighted correlation network analysis (WGCNA) was applied to construct coexpression modules. By overlapping the CpG sites between the clusters and turquoise model, a prognostic model was established by LASSO Cox regression and multivariate Cox regression. It was found that 9 methylated sites included cg01447831, cg14845689, cg20895058, cg06506470, cg09558315, cg06373660, cg17737409, cg21577036, and cg22337438. After constructing the prognostic model, the performance of the model was validated by survival analysis and receiver operating characteristic (ROC) curve, and the independence of the model was verified by univariate and multivariate regression. It was represented that the prognostic model was reliable, and riskscore could be used as an independent prognostic factor in SKCM patients. At last, we combined clinical data and patient's riskscore to establish and testify the nomogram that could determine patient's prognosis. The results found that the reliability of the nomogram was relatively good. All in all, we constructed a prognostic model that could determine the prognosis of SKCM patients and screened 9 key methylated sites through analyzing data in TCGA-SKCM dataset. Finally, a prognostic nomogram was established combined with clinical diagnosed information and riskscore. The results are significant for improving the prognosis of SKCM patients in the future.

Diagnostic and prognostic biomarkers in colorectal cancer and the potential role of exosomes in drug delivery

Colorectal cancer (CRC) is third most common cancer with second most common cause of death worldwide. One fourth to one fifth of the CRC cases are detected at advance stage. Early detection of colorectal cancer might help in decreasing mortality and morbidity worldwide. CRC being a heterogeneous disease, new non-invasive approaches are needed to complement and improve the screening and management of CRC. Reliable and early detectable biomarkers would improve diagnosis, prognosis, therapeutic responses, and will enable the prediction of drug response and recurrence risk. Over the past decades molecular research has demonstrated the potentials of CTCs, ctDNAs, circulating mRNA, ncRNAs, and exosomes as tumor biomarkers. Non-invasive screening approaches using fecal samples for identification of altered gut microbes in CRC is also gaining attention. Exosomes can be potential candidates that can be employed in the drug delivery system. Further, the integration of in vitro, in vivo and in silico models that involve CRC biomarkers will help to understand the interactions occurring at the cellular level. This review summarizes recent update on CRC biomarkers and their application along with the nanoparticles followed by the application of organoid culture in CRC.

A Novel Stool Methylation Test for the Non-Invasive Screening of Gastric and Colorectal Cancer

Background

Because of poor compliance or low sensitivity, existing diagnostic approaches are unable to provide an efficient diagnosis of patients with gastric and colorectal cancer. Here, we developed the ColoCaller test, which simultaneously detects the methylation status of the SDC2, TFPI2, WIF1, and NDRG4 genes in stool DNA, to optimize the screening of gastric and colorectal cancer in high-risk populations.

Methods

A total of 217 stool samples from patients with gastrointestinal cancer and from patients with negative endoscopy were prospectively collected, complete with preoperative and postoperative clinical data from patients. The methylation of these samples was detected using ColoCaller, which was designed by selecting CpGs with a two-step screening strategy, and was interpreted using a prediction model built using libSVM to evaluate its clinical value for gastric and colorectal cancer screening.

Results

Compared to pathological diagnosis, the sensitivity and specificity of the ColoCaller test in 217 stool DNA samples were 95.56% and 91.86%, respectively, for colorectal cancer, and 67.5% and 97.81%, respectively, for gastric cancer. The detection limit was as low as 1% in 8 ng of DNA.

Conclusion

In this study, we developed and established a new test, ColoCaller, which can be used as a screening tool or as an auxiliary diagnostic approach in high-risk populations with gastric and colorectal cancer to promote timely diagnosis and treatment.

DNA Methylation of PI3K/AKT Pathway-Related Genes Predicts Outcome in Patients with Pancreatic Cancer: A Comprehensive Bioinformatics-Based Study

Simple Summary

Pancreatic cancer is a highly lethal malignancy. Dysregulation of epigenetic mechanisms leads to abnormal patterns of gene expression contributing to the development and progression of cancer. We explored the ability of DNA methylation of PI3K-related genes to differentiate between malignant and healthy pancreatic tissue using distinct pancreatic cancer cohorts, and found that the methylation levels of the ITGA4, SFN, ITGA2, and PIK3R1 genes are altered in tumour samples since the early stages of malignant transformation and could serve as new diagnostic tools. We also demonstrate that these alterations correlate with overall survival and recurrence-free survival of the patients suggesting that its assessment can serve as independent prognostic indicators of patients’ survival with higher sensitivity and specificity than the currently implemented biomarkers. Therefore, the methylation profile of genes involved in this pathway may be an alternative method for predicting cell malignancy and help doctors’ decisions on patient care.

Abstract

Pancreatic cancer (PCA) is one of the most lethal malignancies worldwide with a 5-year survival rate of 9%. Despite the advances in the field, the need for an earlier detection and effective therapies is paramount. PCA high heterogeneity suggests that epigenetic alterations play a key role in tumour development. However, only few epigenetic biomarkers or therapeutic targets have been identified so far. Here we explored the potential of distinct DNA methylation signatures as biomarkers for early detection and prognosis of PCA. PI3K/AKT-related genes differentially expressed in PCA were identified using the Pancreatic Expression Database (n = 153). Methylation data from PCA patients was obtained from The Cancer Genome Atlas (n = 183), crossed with clinical data to evaluate the biomarker potential of the epigenetic signatures identified and validated in independent cohorts. The majority of selected genes presented higher expression and hypomethylation in tumour tissue. The methylation signatures of specific genes in the PI3K/AKT pathway could distinguish normal from malignant tissue at initial disease stages with AUC > 0.8, revealing their potential as PCA diagnostic tools. ITGA4, SFN, ITGA2, and PIK3R1 methylation levels could be independent prognostic indicators of patients’ survival. Methylation status of SFN and PIK3R1 were also associated with disease recurrence. Our study reveals that the methylation levels of PIK3/AKT genes involved in PCA could be used to diagnose and predict patients’ clinical outcome with high sensitivity and specificity. These results provide new evidence of the potential of epigenetic alterations as biomarkers for disease screening and management and highlight possible therapeutic targets.

Chitosan oligosaccharides packaged into rat adipose mesenchymal stem cells-derived extracellular vesicles facilitating cartilage injury repair and alleviating osteoarthritis

Objectives

This study aimed to investigate the roles of adipose mesenchymal stem cell (AMSC)-derived extracellular vesicles (EVs) binding with chitosan oligosaccharides (COS) in cartilage injury, as well as the related mechanisms.

Results

IL-1β treatment significantly inhibited the viability and migration of chondrocytes and enhanced cell apoptosis (P < 0.05), while chitosan oligosaccharides and extracellular vesicles-chitosan oligosaccharide conjugates (EVs-COS/EVs-COS conjugates) reversed the changes induced by IL-1β (P < 0.05), and the effects of extracellular vesicles-chitosan oligosaccharide conjugates were better than those of chitosan oligosaccharides (P < 0.05). After cartilage damage, IL-1β, OPN, and p53 were significantly upregulated, COL1A1, COL2A1, OCN, RUNX2, p-Akt/Akt, PI3K, c-Myc, and Bcl2 were markedly downregulated, and extracellular vesicles-chitosan oligosaccharide conjugates reversed the expression induced by cartilage injury. Through sequencing, 760 differentially expressed genes (DEGs) clustered into four expression patterns were associated with negative regulation of the canonical Wnt, PI3K-Akt, AMPK, and MAPK signaling pathways.

Conclusion

Extracellular vesicles-chitosan oligosaccharide conjugates may serve as a new cell-free biomaterial to facilitate cartilage injury repair and improve osteoarthritis.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-021-01086-x.

Identification and Prognostic Value Exploration of Radiotherapy Sensitivity-Associated Genes in Non-Small-Cell Lung Cancer

Background

Non-small-cell lung cancer (NSCLC) is a prevalent malignancy with high mortality and poor prognosis. The radiotherapy is one of the most common treatments of NSCLC, and the radiotherapy sensitivity of patients could affect the individual prognosis of NSCLC. However, the prognostic signatures related to radiotherapy response still remain limited. Here, we explored the radiosensitivity-associated genes and constructed the prognostically predictive model of NSCLC cases.

Methods

The NSCLC samples with radiotherapy records were obtained from The Cancer Genome Atlas database, and the mRNA expression profiles of NSCLC patients from the GSE30219 and GSE31210 datasets were obtained from the Gene Expression Omnibus database. The Weighted Gene Coexpression Network Analysis (WGCNA), univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and nomogram were conducted to identify and validate the radiotherapy sensitivity-related signature.

Results

WGCNA revealed that 365 genes were significantly correlated with radiotherapy response. LASSO Cox regression analysis identified 8 genes, including FOLR3, SLC6A11, ALPP, IGFN1, KCNJ12, RPS4XP22, HIST1H2BH, and BLACAT1. The overall survival (OS) of the low-risk group was better than that of the high-risk group separated by the Risk Score based on these 8 genes for the NSCLC patients. Furthermore, the immune infiltration analysis showed that monocytes and activated memory CD4 T cells had different relative proportions in the low-risk group compared with the high-risk group. The Risk Score was correlated with immune checkpoints, including CTLA4, PDL1, LAG3, and TIGIT.

Conclusion

We identified 365 genes potentially correlated with the radiotherapy response of NSCLC patients. The Risk Score model based on the identified 8 genes can predict the prognosis of NSCLC patients.

Comprehensive Characterization of Integrin Subunit Genes in Human Cancers

Although integrin subunit genes (ITGs) have been reported to be associated with some human cancer types, a systematic assessment of ITGs across human cancers is lacking. Hence, we performed comprehensive analyses to investigate mRNA expression, copy number variation (CNV), DNA methylation, mutation, and clinical landscapes of ITGs in more than 8000 cancer patients from The Cancer Genome Atlas (TCGA) dataset. Landscapes of ITGs were established across 20 human cancer types. We observed that ITGs are extensively dysregulated with heterogeneity in different system cancer types, part of which are driven by CNV, DNA hypomethylation or mutation. Furthermore, dysregulated prognosis-related ITGs were systematically identified in each cancer type, including ITGA11 in stomach adenocarcinoma (STAD). The models based on dysregulated ITGs with clinical relevance and TNM staging indexes are good indicators in STAD and head and neck squamous cell carcinoma. Finally, ITGA11 is overexpressed and associated with poor survival in STAD cases from the TCGA and additionally Gene Expression Omnibus cohorts. Functionally, ITGA11 knockdown inhibits malignant phenotypes in STAD cell lines AGS and MKN45, demonstrating the oncogenic role of ITGA11 in STAD. Together, this study highlights the important roles of ITGs in tumorigenesis as potential prognostic biomarkers, and provide an effective resource that identifies cancer-related genes of ITGs in human cancers.

Sensitive detection of colorectal cancer in peripheral blood by a novel methylation assay

BACKGROUND

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Early detection of CRC can significantly reduce its mortality rate. Current method of CRC diagnosis relies on the invasive endoscopy. Non-invasive assays including fecal occult blood testing (FOBT) and fecal immunological test (FIT) are compromised by low sensitivity and specificity, especially at early stages. Thus, a non-invasive and accurate approach for CRC screening would be highly desirable.

RESULTS

A new qPCR-based assay combining the simultaneous detection of the DNA methylation status of ten candidate genes was used to examine plasma samples from 56 normal controls, 6 hyperplastic polys, 9 non-advanced adenomas (NAAs), 22 advanced adenomas (AAs) and 175 CRC patients, using 10 ng of cfDNA. We further built a logistic regression model for CRC diagnosis. We tested ten candidate methylation markers including twist1, vav3-as1, fbn1, c9orf50, sfmbt2, kcnq5, fam72c, itga4, kcnj12 and znf132. All markers showed moderate diagnostic performance with AUCs ranging from 0.726 to 0.815. Moreover, a 4-marker model, comprised of two previously reported markers (c9orf50 and twist1) and two novel ones (kcnj12 and znf132), demonstrated high performance for detecting colorectal cancer in an independent validation set (N = 69) with an overall AUC of 0.911 [95% confidence interval (CI) 0.834-0.988], sensitivity of 0.800 [95% CI 0.667-0.933] and specificity of 0.971 [95% CI 0.914-1.000]. The stage-stratified sensitivity of the model was 0.455 [95% CI 0.227-0.682], 0.667 [95% CI 0.289-1.000], 0.800 [95% CI 0.449-1.000], 0.800 [95% CI 0.449-1.000] and 0.842 [95% CI 0.678-1.000] for advanced adenoma and CRC stage I-IV, respectively.

CONCLUSION

kcnj12 and znf132 are two novel methylation biomarkers for CRC diagnosis. The 4-marker methylation model provides a new non-invasive choice for CRC screening and interception.