Molecular subtypes in cancers of the gastrointestinal tract

Transcriptomic subtyping of gastrointestinal malignancies

Gastrointestinal (GI) cancers are highly heterogeneous at multiple levels. Tumor heterogeneity can be captured by molecular profiling, such as genetic, epigenetic, proteomic, and transcriptomic classification. Transcriptomic subtyping has the advantage of combining genetic and epigenetic information, cancer cell-intrinsic properties, and the tumor microenvironment (TME). Unsupervised transcriptomic subtyping systems of different GI malignancies have gained interest because they reveal shared biological features across cancers and bear prognostic and predictive value. Importantly, transcriptomic subtypes accurately reflect complex phenotypic states varying not only per tumor region, but also throughout disease progression, with consequences for clinical management. Here, we discuss methodologies of transcriptomic subtyping, proposed taxonomies for GI malignancies, and the challenges posed to clinical implementation, highlighting opportunities for future transcriptomic profiling efforts to optimize clinical impact.

The biological function of demethylase ALKBH1 and its role in human diseases

AlkB homolog 1 (ALKBH1) is a member of the AlkB family of dioxygenases that are dependent on Fe(II) and α-ketoglutarate. Mounting evidence demonstrates that ALKBH1 exhibits enzymatic activity against various substrates, including N6-methyladenosine (m6A), N1-methyladenosine (m1A), N3-methylcytidine (m3C), 5-methylcytosine (m5C), N6-methyladenine (N6-mA, 6mA), and H2A, indicating its dual roles in different biological processes and involvement in human diseases. Up to the present, there is ongoing debate regarding ALKBH1's enzymatic activity. In this review, we present a comprehensive summary of recent research on ALKBH1, including its substrate diversity and pathological roles in a wide range of human disorders, the underlying mechanisms of its functions, and its dysregulation. We also explored the potential of ALKBH1 as a prognostic target.

Mechanisms and clinical landscape of N6-methyladenosine (m6A) RNA modification in gastrointestinal tract cancers

Epigenetics encompasses reversible and heritable chemical modifications of non-nuclear DNA sequences, including DNA and RNA methylation, histone modifications, non-coding RNA modifications, and chromatin rearrangements. In addition to well-studied DNA and histone methylation, RNA methylation has emerged as a hot topic in biological sciences over the past decade. N6-methyladenosine (m6A) is the most common and abundant modification in eukaryotic mRNA, affecting all RNA stages, including transcription, translation, and degradation. Advances in high-throughput sequencing technologies made it feasible to identify the chemical basis and biological functions of m6A RNA. Dysregulation of m6A levels and associated modifying proteins can both inhibit and promote cancer, highlighting the importance of the tumor microenvironment in diverse biological processes. Gastrointestinal tract cancers, including gastric, colorectal, and pancreatic cancers, are among the most common and deadly malignancies in humans. Growing evidence suggests a close association between m6A levels and the progression of gastrointestinal tumors. Global m6A modification levels are substantially modified in gastrointestinal tumor tissues and cell lines compared to healthy tissues and cells, possibly influencing various biological behaviors such as tumor cell proliferation, invasion, metastasis, and drug resistance. Exploring the diagnostic and therapeutic potential of m6A-related proteins is critical from a clinical standpoint. Developing more specific and effective m6A modulators offers new options for treating these tumors and deeper insights into gastrointestinal tract cancers.

Nutrient metabolism in regulating intestinal stem cell homeostasis

Intestinal stem cells (ISCs) are known for their remarkable proliferative capacity, making them one of the most active cell populations in the body. However, a high turnover rate of intestinal epithelium raises the likelihood of dysregulated homeostasis, which is known to cause various diseases, including cancer. Maintaining precise control over the homeostasis of ISCs is crucial to preserve the intestinal epithelium's integrity during homeostasis or stressed conditions. Recent research has indicated that nutrients and metabolic pathways can extensively modulate the fate of ISCs. This review will explore recent findings concerning the influence of various nutrients, including lipids, carbohydrates, and vitamin D, on the delicate balance between ISC proliferation and differentiation.

Potential clinical significance of ALDH3B1 in auxiliary diagnosis of gastric cancer

Objective: This research aimed to explore a diagnostic method based on serum ALDH3B1 and to evaluate the clinical diagnostic efficacy in gastric cancer (GC) by comparing it with the traditional GC diagnostic method, the carcinoembryonic protein (CEA) assay. Methods: Serum samples were collected from 70 healthy volunteers and various patients (GC: 76, benign gastric lesions: 20, postoperative: 37, recurrence: 56). The diagnostic efficacy of serum ALDH3B1, CEA and the co-diagnosis were evaluated by receiver operating characteristic curve. ALDH3B1 protein levels were evaluated by western blot. Results: The co-diagnosis of ALDH3B1 and CEA had the highest diagnostic efficacy (area under the curve = 0.841). Conclusion: Serum ALDH3B1 may be used as an auxiliary diagnostic biomarker for GC, and its co-diagnosis with CEA can improve diagnostic efficacy.

Emerging role of exosome-shuttled noncoding RNAs in gastrointestinal cancers: From intercellular crosstalk to clinical utility

Gastrointestinal cancer remains a significant global health burden. The pursuit of advancing the comprehension of tumorigenesis, along with the identification of reliable biomarkers and the development of precise therapeutic strategies, represents imperative objectives in this field. Exosomes, small membranous vesicles released by most cells, commonly carry functional biomolecules, including noncoding RNAs (ncRNAs), which are specifically sorted and encapsulated by exosomes. Exosome-mediated communication involves the release of exosomes from tumor or stromal cells and the uptake by nearby or remote recipient cells. The bioactive cargoes contained within these exosomes exert profound effects on the recipient cells, resulting in significant modifications in the tumor microenvironment (TME) and distinct alterations in gastrointestinal tumor behaviors. Due to the feasibility of isolating exosomes from various bodily fluids, exosomal ncRNAs have shown great potential as liquid biopsy-based indicators for different gastrointestinal cancers, using blood, ascites, saliva, or bile samples. Moreover, exosomes are increasingly recognized as natural delivery vehicles for ncRNA-based therapeutic interventions. In this review, we elucidate the processes of ncRNA-enriched exosome biogenesis and uptake, examine the regulatory and functional roles of exosomal ncRNA-mediated intercellular crosstalk in gastrointestinal TME and tumor behaviors, and explore their potential clinical utility in diagnostics, prognostics, and therapeutics.

Classification of Thyroid Tumors Based on DNA Methylation Patterns

Background: Alterations in DNA methylation are stable epigenetic events that can serve as clinical biomarkers. The aim of this study was to analyze methylation patterns among various follicular cell-derived thyroid neoplasms to identify disease subtypes and help understand and classify thyroid tumors. Methods: We employed an unsupervised machine learning method for class discovery to search for distinct methylation patterns among various thyroid neoplasms. Our algorithm was not provided with any clinical or pathological information, relying exclusively on DNA methylation data to classify samples. We analyzed 810 thyroid samples (n = 256 for discovery and n = 554 for validation), including benign and malignant tumors, as well as normal thyroid tissue. Results: Our unsupervised algorithm identified that samples could be classified into three subtypes based solely on their methylation profile. These methylation subtypes were strongly associated with histological diagnosis (p < 0.001) and were therefore named normal-like, follicular-like, and papillary thyroid carcinoma (PTC)-like. Follicular adenomas, follicular carcinomas, oncocytic adenomas, and oncocytic carcinomas clustered together forming the follicular-like methylation subtype. Conversely, classic papillary thyroid carcinomas (cPTC) and tall cell PTC clustered together forming the PTC-like subtype. These methylation subtypes were also strongly associated with genomic drivers: 98.7% BRAFV600E-driven cancers were PTC like, whereas 96.0% RAS-driven cancers had a follicular-like methylation pattern. Interestingly, unlike other diagnoses, follicular variant PTC (FVPTC) samples were split into two methylation clusters (follicular like and PTC like), indicating a heterogeneous group likely to be formed by two distinct diseases. FVPTC samples with a follicular-like methylation pattern were enriched for RAS mutations (36.4% vs. 8.0%; p < 0.001), whereas FVPTC- with PTC-like methylation patterns were enriched for BRAFV600E mutations (52.0% vs. 0%, Fisher exact p = 0.004) and RET fusions (16.0% vs. 0%, Fisher exact p = 0.003). Conclusions: Our data provide novel insights into the epigenetic alterations of thyroid tumors. Since our classification method relies on a fully unsupervised machine learning approach for subtype discovery, our results offer a robust background to support the classification of thyroid neoplasms based on methylation patterns.

Latent class analysis-derived classification improves the cancer-specific death stratification of molecular subtyping in colorectal cancer

The molecular subtypes of colorectal cancer (CRC) represent a comprehensive dissection of CRC heterogeneity. However, molecular feature-based classification systems have limitations in accurately prognosticating stratification due to the inability to distinguish cancer-specific deaths. This study aims to establish a classification system that bridges clinical characteristics, cause-specific deaths, and molecular features. We adopted latent class analysis (LCA) on 491,107 first primary CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database to reveal hidden profiles of CRC. The LCA-derived classification scheme was further applied to The Cancer Genome Atlas (TCGA) to assess its effectiveness in improving the accurate stratification of molecular-based subtypes of CRC. Four classes were identified based on latent class analysis integrating demographic and clinicopathological information of CRC patients. The LCA-derived Class 1 (LCAC1) and the LCAC2 showed a high risk of dying from non-CRC, while patients in LCAC3 had a risk of dying from CRC 1.41 times that of LCAC1 (95% confidence interval [CI] = 1.39-1.43). LCAC4 had the lowest probability to die from non-CRC (hazard ratio [HR] = 0.22, 95% CI = 0.21-0.24) compared with LCAC1. Since the LCA-derived classification can identify patients susceptible to CRC-specific death, adjusting for this classification allows molecular-based subtypes to achieve more accurate survival stratification. We provided a classification system capable of distinguish CRC-specific death, which will improve the accuracy of consensus molecular subtypes for CRC patients' survival stratification. Further studies are warranted to confirm the molecular features of LCA-derived classification to inform potential therapeutic strategies and treatment recommendations.

Construction and validation of a prognosis signature based on the immune microenvironment in gastric cancer

Background

Gastric cancer (GC) is an aggressive malignant tumor with a high degree of heterogeneity, and its immune microenvironment is closely associated with tumor growth, development and drug resistance. Therefore, a classification system of gastric cancer based explicitly on the immune microenvironment context might enrich the strategy for gastric cancer prognosis and therapy.

Methods

A total of 668 GC patients were collected from TCGA-STAD (n = 350), GSE15459 (n = 192), GSE57303 (n = 70) and GSE34942 (n = 56) datasets. Three immune-related subtypes (immunity-H, -M, and -L) were identified by hierarchical cluster analysis based on the ssGSEA score of 29 immune microenvironment-related gene sets. The immune microenvironment-related prognosis signature (IMPS) was constructed via univariate Cox regression, Lasso-Cox regression and multivariate Cox regression, and nomogram model combining IMPS and clinical variables was further constructed by the “rms” package. RT-PCR was applied to validate the expression of 7 IMPS genes between two human GC cell lines (AGS and MKN45) and one normal gastric epithelial cell line (GES-1).

Results

The patients classified as immunity-H subtype exhibited highly expressed immune checkpoint and HLA-related genes, with enriched naïve B cells, M1 macrophages and CD8 T cells. We further constructed and validated a 7-gene (CTLA4, CLDN6, EMB, GPR15, ENTPD2, VWF and AKR1B1) prognosis signature, termed as IMPS. The patients with higher IMPS expression were more likely to be associated with higher pathology grade, more advanced TNM stages, higher T and N stage, and higher ratio of death. In addition, the prediction values of the combined nomogram in predicting 1-year (AUC = 0.750), 3-year (AUC = 0.764) and 5-year (AUC = 0.802) OS was higher than IMPS and individual clinical characteristics.

Conclusions

The IMPS is a novel prognosis signature associated with the immune microenvironment and clinical characteristics. The IMPS and the combined nomogram model provide a relatively reliable predictive index for predicting the survival outcomes of gastric cancer.

The molecular biology of peritoneal metastatic disease

Peritoneal metastases are a common form of tumor cell dissemination in gastrointestinal malignancies. Peritoneal metastatic disease (PMD) is associated with severe morbidity and resistance to currently employed therapies. Given the distinct route of dissemination compared with distant organ metastases, and the unique microenvironment of the peritoneal cavity, specific tumor cell characteristics are needed for the development of PMD. In this review, we provide an overview of the known histopathological, genomic, and transcriptomic features of PMD. We find that cancers representing the mesenchymal subtype are strongly associated with PMD in various malignancies. Furthermore, we discuss the peritoneal niche in which the metastatic cancer cells reside, including the critical role of the peritoneal immune system. Altogether, we show that PMD should be regarded as a distinct disease entity, that requires tailored treatment strategies.

Poor-prognosis molecular subtypes in adenocarcinomas of pancreato-biliary and gynecological origin: A systematic review

Pancreato-biliary and gynecological adenocarcinomas need better tools to predict clinical outcome. Potential prognostic mesenchymal(-like) transcriptome-based subtypes have been identified in these cancers. In this systematic review, we include studies into molecular subtyping and summarize biological and clinical features of the subtypes within and across sites of origin, searching for suggestions to improve classification and prognostication. PubMed and Embase were searched for original research articles describing potential mesenchymal(-like) mRNA-based subtypes in pancreato-biliary or gynecological adenocarcinomas. Studies limited to supervised clustering were excluded. Fourty-four studies, discussing cholangiocarcinomas, gallbladder, ampullary, pancreatic, ovarian, and endometrial adenocarcinomas were included. There was overlap in molecular and clinical features in mesenchymal(-like) subtypes across all adenocarcinomas. Approaches including microdissection were more likely to identify prognosis-associating subtypes. To conclude, molecular subtypes in pancreato-biliary and gynecological adenocarcinomas share biological and clinical characteristics. Furthermore, separation of stromal and epithelial signals should be applied in future studies into biliary and gynecological adenocarcinomas.

Pancreatic Cancer in Chronic Pancreatitis: Pathogenesis and Diagnostic Approach

Chronic pancreatitis is one of the main risk factors for pancreatic cancer, but it is a rare event. Inflammation and oncogenes work hand in hand as key promoters of this disease. Tobacco is another co-factor. During alcoholic chronic pancreatitis, the cumulative risk of cancer is estimated at 4% after 15 to 20 years. This cumulative risk is higher in hereditary pancreatitis: 19 and 12% in the case of PRSS1 and SPINK1 mutations, respectively, at an age of 60 years. The diagnosis is difficult due to: (i) clinical symptoms of cancer shared with those of chronic pancreatitis; (ii) the parenchymal and ductal remodeling of chronic pancreatitis rendering imaging analysis difficult; and (iii) differential diagnoses, such as pseudo-tumorous chronic pancreatitis and paraduodenal pancreatitis. Nevertheless, the occurrence of cancer during chronic pancreatitis must be suspected in the case of back pain, weight loss, unbalanced diabetes, and jaundice, despite alcohol withdrawal. Imaging must be systematically reviewed. Endoscopic ultrasound-guided fine-needle biopsy can contribute by targeting suspicious tissue areas with the help of molecular biology (search for KRAS, TP53, CDKN2A, DPC4 mutations). Short-term follow-up of patients is necessary at the clinical and paraclinical levels to try to diagnose cancer at a surgically curable stage. Pancreatic surgery is sometimes necessary if there is any doubt.

Circulating exosomal microRNAs as potential prognostic biomarkers in gastrointestinal cancers: a systematic review and meta-analysis

BACKGROUND

Recent reports suggested that circulating exosomal microRNAs (exomiRs) may serve as non-invasive prediction biomarkers in gastrointestinal (GI) cancers, yet their clinicopathological and prognostic values need to be more clarified. Hence, the present meta-analysis was aimed to quantitatively assess the evidence regarding the association between circulating exomiRs and prognosis in GI cancer patients.

METHODS

A comprehensive search was carried out in prominent literature databases, including PubMed, ISI Web of Science, Scopus, and Embase. Odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs) were gathered to evaluate the strength of the association. The quality assessment was investigated through the Newcastle-Ottawa Scale (NOS) and publication bias via Eggers' test and funnel plots.

RESULTS

A total of 47 studies, comprising of 4881 patients, were considered eligible for this meta-analysis. Both up-regulated and down-regulated circulating exomiRs are significantly associated with differentiation (HR = 1.353, P = 0.015; HR = 1.504, P = 0.016), TNM stage (HR = 2.058, P < 0.001; HR = 2.745, P < 0.001), lymph node metastasis (HR = 1.527, P = 0.004; HR = 2.009, P = 0.002), distant metastasis (HR = 2.006, P < 0.001; HR = 2.799, P = 0.002), worse overall survival (OS) (HR = 2.053, P < 0.001; HR = 1.789, P = 0.001) and poorer disease/relapse/progression-free survival (DFS/RFS/PFS) (HR = 2.086, P < 0.001; HR = 1.607, P = 0.001) in GI cancer patients, respectively. In addition, subgroup analyses based on seven subcategories indicated the robustness of the association. The majority of findings were lack of publication bias except for the association between up-regulated exomiRs and OS or DFS/RFS/PFS and for the down-regulated exomiRs and TNM stage.

CONCLUSION

This study supports that up- and down-regulated circulating exomiRs are associated with poorer survival outcomes and could be served as potential prognostic biomarkers in GI cancers. Given the limitations of the current findings, such as significant heterogeneity, more investigations are needed to fully clarify the exomiRs prognostic role.

Gastrointestinal pan-cancer landscape of tumor matrix heterogeneity identifies biologically distinct matrix stiffness subtypes predicting prognosis and chemotherapy efficacy

Gastrointestinal (GI) cancers are a heterogeneous group of primary solid tumors, arising in GI tract from the esophagus to rectum. Matrix stiffness (MS) is a critical physical factor for cancer progression; however, its importance in tumor progression remains to be comprehensively recognized. Herein, we conducted a comprehensive pan-cancer analysis of MS subtypes across seven GI-cancer types. Using unsupervised clustering based on literature-derived MS-specific pathway signatures, the GI-tumor samples were divided into three MS subtypes, termed as the Soft, Mixed and Stiff. Then, distinct prognoses, biological features, tumor microenvironments and mutation landscapes among three MS subtypes were revealed. The Stiff tumor subtype was associated with the poorest prognosis, the most malignant biological behaviors, and the immunosuppressive tumor stromal microenvironment. Furthermore, multiple machine learning algorithms were used to develop an 11-gene MS-signature to identify the MS subtypes of GI-caner and predict chemotherapy sensitivity, which were further validated in two external GI-cancer cohorts. This novel MS-based classification on GI-cancers could enhance our understanding of the important role of MS in tumor progression, and may have implications for the optimization of individualized cancer management.

The tumor microenvironment in gastrointestinal adenocarcinomas revealed a prognostic and immunotherapeutic biomarker

Accumulated evidence has elucidated that the tumor microenvironment (TME) is great of clinical significance in predicting survival outcomes and therapeutic efficacy. Nonetheless, few studies have investigated the prognostic and immunotherapeutic signature correlated with TME phenotypes in gastrointestinal adenocarcinomas (GIAC). Here, by estimating the TME pattern of immune infiltration and expression in over 1,000 GIAC patients, we revealed three TME subgroups and identified six key differential genes. To predict the TME phenotypes, TMEscore was established and validated to be an independent prognostic factor, where the high TMEscore was characterized by immune activation and response to immunotherapy and accompanied with favorable prognosis in GIAC. Furthermore, TMEscore was confirmed to predict prognosis and immunotherapeutic response in six datasets. In summary, depicting TME landscape of GIAC patients may be beneficial for interpreting survival and immunotherapeutic response, and provide new strategies for clinical treatment of GIAC.

Identification and validation of a novel signature as a diagnostic and prognostic biomarker in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most common malignant neoplasms worldwide. Although marker genes associated with CRC have been identified previously, only a few have fulfilled the therapeutic demand. Therefore, based on differentially expressed genes (DEGs), this study aimed to establish a promising and valuable signature model to diagnose CRC and predict patient's prognosis.

METHODS

The key genes were screened from DEGs to establish a multiscale embedded gene co-expression network, protein-protein interaction network, and survival analysis. A support vector machine (SVM) diagnostic model was constructed by a supervised classification algorithm. Univariate Cox analysis was performed to construct two prognostic signatures for overall survival and disease-free survival by Kaplan-Meier analysis, respectively. Independent clinical prognostic indicators were identified, followed by univariable and multivariable Cox analysis. GSEA was used to evaluate the gene enrichment analysis and CIBERSORT was used to estimate the immune cell infiltration. Finally, key genes were validated by qPCR and IHC.

RESULTS

In this study, four key genes (DKC1, FLNA, CSE1L and NSUN5) were screened. The SVM diagnostic model, consisting of 4-gene signature, showed a good performance for the diagnostic (AUC = 0.9956). Meanwhile, the four-gene signature was also used to construct a risk score prognostic model for disease-free survival (DFS) and overall survival (OS), and the results indicated that the prognostic model performed best in predicting the DFS and OS of CRC patients. The risk score was validated as an independent prognostic factor to exhibit the accurate survival prediction for OS according to the independent prognostic value. Furthermore, immune cell infiltration analysis demonstrated that the high-risk group had a higher proportion of macrophages M0, and T cells CD4 memory resting was significantly higher in the low-risk group than in the high-risk group. In addition, functional analysis indicated that WNT and other four cancer-related signaling pathways were the most significantly enriched pathways in the high-risk group. Finally, qRT-PCR and IHC results demonstrated that the high expression of DKC1, CSE1L and NSUN5, and the low expression of FLNA were risk factors of CRC patients with a poor prognosis.

CONCLUSION

In this study, diagnosis and prognosis models were constructed based on the screened genes of DKC1, FLNA, CSE1L and NSUN5. The four-gene signature exhibited an excellent ability in CRC diagnosis and prognostic prediction. Our study supported and highlighted that the four-gene signature is conducive to better prognostic risk stratification and potential therapeutic targets for CRC patients.

Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge of the GC immune microenvironment. However, much uncertainty still exists about the relationship between the macroscopic and microscopic data in transcriptomics. In the current study, we made full use of scRNA-seq data from the Gene Expression Omnibus database (GSE134520) to identify 25 cell subsets, including 11 microenvironment-related cell types. The MIF signaling pathway network was obtained upon analysis of receptor–ligand pairs and cell–cell interactions. By comparing the gene expression in a wide variety of cells between intestinal metaplasia and early gastric cancer, we identified 64 differentially expressed genes annotated as immune response and cellular communication. Subsequently, we screened these genes for prognostic clinical value based on the patients’ follow-up data from The Cancer Genome Atlas. TMPRSS15, VIM, APOA1, and RNASE1 were then selected for the construction of LASSO risk scores, and a nomogram model incorporating another five clinical risk factors was successfully created. The effectiveness of least absolute shrinkage and selection operator risk scores was validated using gene set enrichment analysis and levels of immune cell infiltration. These findings will drive the development of prognostic evaluations affected by the immune tumor microenvironment in GC.

Site-Specific Hypermethylation of SST 1stExon as a Biomarker for Predicting the Risk of Gastrointestinal Tract Cancers

Background

DNA methylation is an important epigenetic modification in tumorigenesis, and similar epigenetic regulation mechanisms have been found in the gastrointestinal tract (GIT) cancers. Somatostatin (SST) has been confirmed to be expressed throughout the GIT. This study aimed to simultaneously explore the relationships between the SST methylation and the risks of three GIT cancers (esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC)) and to evaluate its diagnostic value.

Methods

Differentially methylated regions (DMRs) of the SST gene, including TSS200, 1stExon, and the gene body, were identified in GIT cancers by The Cancer Genome Atlas (TCGA) database analysis. Further analyses were conducted in tissue samples of EC (n = 50), GC (n = 99), and CRC (n = 80). The SST methylation was detected by bisulfite-sequencing PCR (BSP), and the SST expression was detected by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR).

Results

In GIT cancers, DMR-related CpG islands were mainly located in the 1stExon. The methylation status of the SST 1stExon in the tumor tissues was significantly higher than that in the adjacent noncancerous tissues, and the methylation rates of the specific CpG sites were correlated with clinical phenotypes. The average methylation rate (AMR) of the SST 1stExon was negatively correlated with the SST gene expression in GC and CRC (both P < 0.001). For the diagnosis of GIT cancers, the combined detection of methylation at CpG sites +18 and +129 showed the highest area under the curve (AUC 0.698), with a sensitivity of 59.3% and a specificity of 72.8%.

Conclusions

The site-specific hypermethylation of the SST 1stExon increases the risk of GIT cancers and might be a potential predictive marker for pan-GIT cancers.

Contribution of Epithelial and Gut Microbiome Inflammatory Biomarkers to the Improvement of Colorectal Cancer Patients’ Stratification

In order to ensure that primary endpoints of clinical studies are attained, the patients’ stratification is an important aspect. Selection criteria include age, gender, and also specific biomarkers, such as inflammation scores. These criteria are not sufficient to achieve a straightforward selection, however, in case of multifactorial diseases, with unknown or partially identified mechanisms, occasionally including host factors, and the microbiome. In these cases, the efficacy of interventions is difficult to predict, and as a result, the selection of subjects is often random. Colorectal cancer (CRC) is a highly heterogeneous disease, with variable clinical features, outcomes, and response to therapy; the CRC onset and progress involves multiple sequential steps with accumulation of genetic alterations, namely, mutations, gene amplification, and epigenetic changes. The gut microbes, either eubiotic or dysbiotic, could influence the CRC evolution through a complex and versatile crosstalk with the intestinal and immune cells, permanently changing the tumor microenvironment. There have been significant advances in the development of personalized approaches for CRC screening, treatment, and potential prevention. Advances in molecular techniques bring new criteria for patients’ stratification—mutational analysis at the time of diagnosis to guide treatment, for example. Gut microbiome has emerged as the main trigger of gut mucosal homeostasis. This may impact cancer susceptibility through maintenance of the epithelial/mucus barrier and production of protective metabolites, such as short-chain fatty acids (SCFAs) via interactions with the hosts’ diet and metabolism. Microbiome dysbiosis leads to the enrichment of cancer-promoting bacterial populations, loss of protective populations or maintaining an inflammatory chronic state, all of which contribute to the development and progression of CRC. Meanwhile, variations in patient responses to anti-cancer immuno- and chemotherapies were also linked to inter-individual differences in intestine microbiomes. The authors aim to highlight the contribution of epithelial and gut microbiome inflammatory biomarkers in the improvement of CRC patients’ stratification towards a personalized approach of early diagnosis and treatment.

The Role of Glucosinolates from Cruciferous Vegetables (Brassicaceae) in Gastrointestinal Cancers: From Prevention to Therapeutics

The gastrointestinal (GI) tract is composed of rapidly renewing cells, which increase the likelihood of cancer. Colorectal cancer is one of the most frequently diagnosed GI cancers and currently stands in second place regarding cancer-related mortality. Unfortunately, the treatment of GI is limited, and few developments have occurred in the field over the years. With this in mind, new therapeutic strategies involving biologically active phytocompounds are being evaluated as anti-cancer agents. Vegetables such as broccoli, brussels sprouts, cabbage, cauliflower, and radish, all belonging to the Brassicaceae family, are high in dietary fibre, minerals, vitamins, carotenoids, polyphenols, and glucosinolates. The latter compound is a secondary metabolite characteristic of this family and, when biologically active, has demonstrated anti-cancer properties. This article reviews the literature regarding the potential of Cruciferous vegetables in the prevention and/or treatment of GI cancers and the relevance of appropriate compound formulations for improving the stability and bioaccessibility of the major Cruciferous compounds, with a particular focus on glucosinolates.

LncRNA NR038975, A Serum-Based Biomarker, Promotes Gastric Tumorigenesis by Interacting With NF90/NF45 Complex

Gastric cancer (GC) is one of the deadliest cancers, and long noncoding RNAs (lncRNAs) have been reported to be the important regulators during the occurrence and development of GC. The present study identified a novel and functional lncRNA in GC, named NR038975, which was confirmed to be markedly upregulated in the Gene Expression Profiling Interactive Analysis (GEPIA) dataset and our independent cohort of GC tissues. We firstly characterized the full-length sequence and subcellular location of NR038975 in GC cells. Our data demonstrated that upregulated NR038975 expression was significantly related to lymph node metastasis and TNM stage. In addition, knockdown of NR038975 inhibited GC cell proliferation, migration, invasion, and clonogenicity and vice versa. Mechanistically, RNA pull-down and mass spectrometry assays identified the NR038975-binding proteins and NF90/NF45 complex, and the binding was also confirmed by RNA immunoprecipitation and confocal experiments. We further demonstrated that genetic deficiency of NR038975 abrogated the interaction between NF45 and NF90. Moreover, NF90 increased the stability of NR038975. Thus, NR038975-NF90/NF45 will be an important combinational target of GC. Finally, we detected NR038975 in serum exosomes and serum of GC patients. Our results indicated that NR038975 was a biomarker for gastric tumorigenesis. The current study demonstrated that NR038975 is a novel lncRNA that is clinically and functionally engaged in GC progression and might be a novel diagnostic marker and potential therapeutic target.

Preoperative serum ADAM12 levels as a stromal marker for overall survival and benefit of adjuvant therapy in patients with resected pancreatic and periampullary cancer

BACKGROUND

We evaluated the stroma marker A Disintegrin And Metalloprotease 12 (ADAM12) as a preoperative prognostic and treatment-predictive marker for overall survival (OS) in pancreatic ductal adenocarcinoma (PDAC) and periampullary cancers.

METHODS

Materials were derived from the prospective nationwide Dutch Pancreas Biobank (2015-2017). We included patients who underwent resection because of PDAC/periampullary cancer or non-invasive IPMN (control group) and had a preoperative serum sample available. ADAM12 levels were dichotomized using a pre-defined cut-off (316 pg/mL). Univariable and multivariable Cox regression analyses (backward selection) were performed.

RESULTS

Median ADAM12 levels were 161 (IQR 79-352) pg/mL in 215 PDAC and periampullary adenocarcinomas. High ADAM12 levels (>316 pg/mL) predicted poor OS in the total group of pancreatic and periampullary adenocarcinomas (P = 0.04), but not after adjustment. In distal cholangiocarcinoma (n = 33), high ADAM12 levels predicted poor OS in univariable analysis (P = 0.02), but not in PDAC (P = 0.63). PDAC patients (n = 135) with high ADAM12 levels benefited from adjuvant treatment (median OS 27 vs 14 months, P = 0.02), whereas those with low levels did not (21 vs 21 months, P = 0.87).

CONCLUSION

High circulating ADAM12 levels, as a proxy for activated stroma, predict survival benefit from adjuvant chemotherapy in PDAC, requiring validation in future studies.

Molecular subclassification of gastrointestinal cancers based on cancer stem cell traits

Human gastrointestinal malignancies are highly heterogeneous cancers. Clinically, heterogeneity largely contributes to tumor progression and resistance to therapy. Heterogeneity within gastrointestinal cancers is defined by molecular subtypes in genomic and transcriptomic analyses. Cancer stem cells (CSCs) have been demonstrated to be a major source of tumor heterogeneity; therefore, assessing tumor heterogeneity by CSC trait-guided classification of gastrointestinal cancers is essential for the development of effective therapies. CSCs share critical features with embryonic stem cells (ESCs). Molecular investigations have revealed that embryonic genes and developmental signaling pathways regulating the properties of ESCs or cell lineage differentiation are abnormally active and might be oncofetal drivers in certain tumor subtypes. Currently, multiple strategies allow comprehensive identification of tumor subtype-specific oncofetal signatures and evaluation of subtype-specific therapies. In this review, we summarize current knowledge concerning the molecular classification of gastrointestinal malignancies based on CSC features and elucidate their clinical relevance. We also outline strategies for molecular subtype identification and subtype-based therapies. Finally, we explore how clinical implementation of tumor classification by CSC subtype might facilitate the development of more effective personalized therapies for gastrointestinal cancers.

The immunology of sepsis

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to an infection. This recently implemented definition does not capture the heterogeneity or the underlying pathophysiology of the syndrome, which is characterized by concurrent unbalanced hyperinflammation and immune suppression. Here, we review current knowledge of aberrant immune responses during sepsis and recent initiatives to stratify patients with sepsis into subgroups that are more alike from a clinical and/or pathobiological perspective, which could be key for identification of patients who are more likely to benefit from specific immune interventions.

Dual Hyper-Graph Regularized Supervised NMF for Selecting Differentially Expressed Genes and Tumor Classification

Non-negative matrix factorization (NMF) is a dimensionality reduction technique based on high-dimensional mapping. It can learn part-based representations effectively. In this paper, we propose a method called Dual Hyper-graph Regularized Supervised Non-negative Matrix Factorization (HSNMF). To encode the geometric information of the data, the hyper-graph is introduced into the model as a regularization term. The advantage of hyper-graph learning is to find higher order data relationship to enhance data relevance. This method constructs the data hyper-graph and the feature hyper-graph to find the data manifold and the feature manifold simultaneously. The application of hyper-graph theory in cancer datasets can effectively find pathogenic genes. The discrimination information is further introduced into the objective function to obtain more information about the data. Supervised learning with label information greatly improves the classification effect. Furthermore, the real datasets of cancer usually contain sparse noise, so the L_2,1-norm is applied to enhance the robustness of HSNMF algorithm. Experiments under The Cancer Genome Atlas (TCGA) datasets verify the feasibility of the HSNMF method.

Pre-clinical Models of Metastasis in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a hostile solid malignancy coupled with an extremely high mortality rate. Metastatic disease is already found in most patients at the time of diagnosis, resulting in a 5-year survival rate below 5%. Improved comprehension of the mechanisms leading to metastasis is pivotal for the development of new targeted therapies. A key field to be improved are modeling strategies applied in assessing cancer progression, since traditional platforms fail in recapitulating the complexity of PDAC. Consequently, there is a compelling demand for new preclinical models that mirror tumor progression incorporating the pressure of the immune system, tumor microenvironment, as well as molecular aspects of PDAC. We suggest the incorporation of 3D organoids derived from genetically engineered mouse models or patients as promising new tools capable to transform PDAC pre-clinical modeling and access new frontiers in personalized medicine.

DNA methylation detection technology and plasma-based methylation biomarkers in screening of gastrointestinal carcinoma

DNA methylation is of paramount importance for the evolution of human cancers. Its high sensitivity and specificity make it a potential biomarker for early cancer screening in the context of an increasing global burden of gastrointestinal (GI) carcinoma. More DNA methylation biomarkers are emerging with the development of liquid biopsy and sensitive DNA methylation detection technology. This review provides an overview of DNA methylation, focusing on the presentation and comparison of 5-methylcytosine detection technologies, and introduces the promising plasma-based cell-free DNA (cfDNA) methylation biomarkers published in recent years for early screening of GI carcinoma. Finally, we summarize and discuss the future of plasma cfDNA methylation markers detection as a clinical tool for early screening of GI carcinoma.

Comparing immunotherapies to other frequently used treatments of gastric cancer

Introduction: Although standard doublet chemotherapy represents the upfront gold standard to increase survival and improve quality of life of gastric cancer patients, overall improvements in long-term outcomes are modest and novel treatments are urgently needed. Among these, immunotherapy is an increasingly attractive option.Areas covered: A number of clinical trials have shown that checkpoint inhibitors may be of value, but many unclear issues remain controversial and should be promptly untangled. In our short review, we offer the current available data regarding immunotherapies in gastric cancers, discuss potential limits of the reported trials, compare outcomes of checkpoints inhibitor to those of standard chemotherapy or other novel treatments, and present basic principles of immune surveillance and immune escape that may be embraced in the near future with novel drug combinations.Expert opinion: Gastric cancer patients may benefit from immunotherapy, both given alone in advanced lines and upfront in combination with chemotherapy. We believe that appropriate patients' and tumor's selection are crucial issues to maximize its potential efficacy. In addition, we think that assay standardization, biomarker agreement, and translational studies will improve the benefit-to-risk ratio of these agents in the clinical practice.

The recurring features of molecular subtypes in distinct gastrointestinal malignancies-A systematic review

In colorectal cancer (CRC), pancreatic ductal adenocarcinoma (PDAC) and gastric cancer (GC) multiple studies of inter-tumor heterogeneity have identified molecular subtypes, which correlate with clinical features. Our aim was to investigate the attributes of molecular subtypes across three different gastrointestinal cancer types. We performed a systematic search for publications on molecular subtypes or classifications in PDAC and GC and compared the described subtypes with the established consensus molecular subtypes of CRC. Examining the characteristics of subtypes across CRC, PDAC and GC resulted in four categories of subtypes. We describe uniting and distinguishing features within a mesenchymal, an epithelial, an immunogenic and a metabolic and digestive subtype category. We conclude that molecular subtypes of CRC, PDAC and GC display relevant overlap in molecular features and clinical outcomes. This finding encourages quantitative studies on subtypes across different cancer types and could lead to a paradigm shift in future treatment strategies.

Integrative omics analysis reveals effective stratification and potential prognosis markers of pan-gastrointestinal cancers

Gastrointestinal (GI) tract cancers are the most common malignant cancers with high mortality rate. Pan-cancer multi-omics data fusion provides a powerful strategy to examine commonalities and differences among various cancer types and benefits for the identification of pan-cancer drug targets. Herein, we conducted an integrative omics analysis on The Cancer Genome Atlas pan-GI samples including six carcinomas and stratified into 9 clusters, i.e. 5 single-type-dominant clusters and 4 mixed clusters, the clustering reveals the molecular features of different subtypes, other than the organ and cell-of-origin classifications. Especially the mixed clusters revealed the homogeneity of pan-GI cancers. We demonstrated that the prognosis differences among pan-GI subtypes based on multi-omics integration are more significant than clustering by single-omics. The potential prognostic markers for pan-GI stratification were identified by proportional hazards model, such as PSCA (for colorectal and stomach cancer) and PPP1CB (for liver and pancreatic cancer), which have prominent prognostic power supported by high concordance index.

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Pan-cancer multi-omics strategy reveals homogeneity and heterogeneity of pan-GI cancers

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Identify 9 iclusters with significantly different survival and molecular features

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Potential prognostic markers have prominent power supported by concordance index

Screening and identification of key biomarkers in alimentary tract cancers: A bioinformatic analysis

BACKGROUND

Alimentary tract cancers (ATCs) are the most malignant cancers in the world. Numerous studies have revealed the tumorigenesis, diagnosis and treatment of ATCs, but many mechanisms remain to be explored.

METHODS

To identify the key genes of ATCs, microarray datasets of oesophageal cancer, gastric cancer and colorectal cancer were obtained from the Gene Expression Omnibus (GEO) database. In total, 207 differentially expressed genes (DEGs) were screened. KEGG and GO function enrichment analyses were conducted, and a protein-protein interaction (PPI) network was generated and gene modules analysis was performed using STRING and Cytoscape.

RESULTS

Five hub genes were screened, and the associated biological processes indicated that these genes were mainly enriched in cellular processes, protein binding and metabolic processes. Clinical survival analysis showed that COL10A1 and KIF14 may be significantly associated with the tumorigenesis or pathology grade of ATCs. In addition, relative human ATC cell lines along with blood samples and tumour tissues of ATC patients were obtained. The data proved that high expression of COL10A1 and KIF14 was associated with tumorigenesis and could be detected in blood.

CONCLUSION

In conclusion, the identification of hub genes in the present study helped us to elucidate the molecular mechanisms of tumorigenesis and identify potential diagnostic indicators and targeted treatment for ATCs.

ITGA5 is a prognostic biomarker and correlated with immune infiltration in gastrointestinal tumors

BACKGROUND

Integrin Subunit Alpha 5 (ITGA5), belongs to the integrin alpha chain family, is vital for promoting cancer cell invasion, metastasis. However, the correlation between ITGA5 expression and immune infiltration in gastrointestinal tumors remain unclear.

METHODS

The expression level of ITGA5 was detected by Oncomine and Tumor Immune Estimation Resource (TIMER). The association between ITGA5 and prognosis of patients was identified by Kaplan-Meier plotter, Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and PrognoScan. We evaluated the correlation between ITGA5 expression and immune infiltrating level via TIMER. Besides, TIMER, immunohistochemistry (IHC) staining and western blot were used to explore correlations between ITGA5 expression and markers of immune infiltrates cells. Furthermore, we constructed protein-protein interaction (PPI) network and performed functional enrichment by GeneMANIA and Metascape.

RESULTS

ITGA5 was generally overexpressed and correlated with worse prognosis in multiple types of gastrointestinal tumors. In addition, ITGA5 expression level was significantly associated with tumor purity and immune infiltration levels of different immune cells in gastrointestinal tumors. Interestingly, immune markers for monocytes, tumor - associated macrophages (TAMs), macrophages 2 (M2) cells and T-helper 2 (Th2) cells were found to be significantly and positively correlated with ITGA5 expression levels in colon and gastric cancer. Results from IHC staining and western blot further proved that markers of Th2 and M2 cell were significantly increased in gastric cancer patients with high ITGA5 expression levels. Lastly, interaction network and function enrichment analysis revealed ITGA5 was mainly involved in "integrin mediated signaling pathway", "leukocyte migration", "cell-substrate adhesion".

CONCLUTIONS

Our study demonstrated that ITGA5 may act as an essential regulator of tumor immune cell infiltration and a valuable prognostic biomarker in gastrointestinal tumors. Additional work is needed to fully elucidate the underlying mechanisms behind these observations.

Identification of an Immune Gene-Associated Prognostic Signature and Its Association With a Poor Prognosis in Gastric Cancer Patients

The immune response plays a critical role in gastric cancer (GC) development, metastasis, and treatment. A better understanding of the tumor-immune system interactions in gastric cancer may provide promising diagnostic, prognostic, and therapeutic biomarkers for patients with this disease. In the present study, we aimed to identify a prognostic signature of GC through a comprehensive bioinformatics analysis on the tumor-immune interactions as well as the molecular characteristics. We firstly identified two immunophenotypes and immunological characteristics by employing multiple algorithms, such as the single sample Gene Sets Enrichment Analysis and Cell type Identification By Estimating Relative Subsets of RNA Transcripts. Next, we developed a six-immune-gene signature as a promising independent prognostic biomarker for GC using Lasso Cox regression and verified it via the external validation set and systematically correlated the immune signature with GC clinicopathologic features and genomic characteristics. Finally, a nomogram was successfully constructed based on the immune signature and clinical characteristics and showed a high potential for GC prognosis prediction. This study may shed light on the treatment strategies for GC patients from the perspective of immunology.

Transcriptome Based System Biology Exploration Reveals Homogeneous Tumorigenicity of Alimentary Tract Malignancy

Malignancies of alimentary tract include esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ). Despite of their similarities in cancer development and progression, there are numerous researches concentrating on single tumor but relatively little on their common mechanisms. Our study explored the transcriptomic data of digestive tract cancers from The Cancer Genome Atlas database, yielding their common differentially expressed genes including 1,700 mRNAs, 29 miRNAs, and 362 long non-coding RNAs (lncRNAs). There were 12 mRNAs, 5 miRNAs, and 16 lncRNAs in the core competitive endogenous RNAs network by RNA-RNA interactions, highlighting the prognostic nodes of SERPINE1, hsa-mir-145, and SNHG1. In addition, the weighted gene co-expression network analysis (WGCNA) illustrated 20 gene modules associated with clinical traits. By taking intersections of modules related to the same trait, we got 67 common genes shared by ESCA and READ and screened 5 hub genes, including ADCY6, CXCL3, NPBWR1, TAS2R38, and PTGDR2. In conclusion, the present study found that SERPINE1/has-mir-145/SNHG1 axis acted as promising targets and the hub genes reasoned the similarity between ESCA and READ, which revealed the homogeneous tumorigenicity of digestive tract cancers at the transcriptome level and led to further comprehension and therapeutics for digestive tract cancers.

Unsupervised Hierarchical Clustering Identifies Immune Gene Subtypes in Gastric Cancer

Objectives: The pathogenesis of heterogeneity in gastric cancer (GC) is not clear and presents as a significant obstacle in providing effective drug treatment. We aimed to identify subtypes of GC and explore the underlying pathogenesis. Methods: We collected two microarray datasets from GEO (GSE84433 and GSE84426), performed an unsupervised cluster analysis based on gene expression patterns, and identified related immune and stromal cells. Then, we explored the possible molecular mechanisms of each subtype by functional enrichment analysis and identified related hub genes. Results: First, we identified three clusters of GC by unsupervised hierarchical clustering, with average silhouette width of 0.96, and also identified their related representative genes and immune cells. We validated our findings using dataset GSE84426. Subtypes associated with the highest mortality (subtype 2 in the training group and subtype C in the validation group) showed high expression of SPARC, COL3A1, and CCN. Both subtypes also showed high infiltration of fibroblasts, endothelial cells, hematopoietic stem cells, and a high stromal score. Furthermore, subtypes with the best prognosis (subtype 3 in the training group and subtype A in the validation group) showed high expression of FGL2, DLGAP1-AS5, and so on. Both subtypes also showed high infiltration of CD4⁺ T cells, CD8⁺ T cells, NK cells, pDC, macrophages, and CD4⁺ T effector memory cells. Conclusion: We found that GC can be classified into three subtypes based on gene expression patterns and cell composition. Findings of this study help us better understand the tumor microenvironment and immune milieu associated with heterogeneity in GC and provide practical information to guide personalized treatment.

ANTXR1 Is a Prognostic Biomarker and Correlates With Stromal and Immune Cell Infiltration in Gastric Cancer

Gastric cancer (GC) is a complex and heterogeneous disease, making it difficult to ascertain the optimal therapeutic approach for individual GC patients. Stromal and immune cell infiltration in GC has a strong correlation with clinical outcomes; however, the underlying mechanisms that drive immunosuppression remain vastly undiscovered. Recent studies validated that anthrax toxin receptor 1 (ANTXR1) is aberrantly expressed in several cancers and holds promise as a new therapeutic target for cancer. However, its immunological roles in GC are still unclear. Here, we show that we identify the distinct stromal and immune cell infiltration in GC between the high and low ANTXR1 expression group by analyzing genomic data. Clinically, ANTXR1 is highly expressed in GC and correlates with adverse clinicopathological characteristics. Additionally, high ANTXR1 expression is linked to markedly poor clinical outcomes and resistance to chemotherapy, whereas the low ANTXR1 expression group is correlated with better outcomes and response to chemotherapy in GC patients. We further revealed the differential landscape of somatic tumor mutation burden (TMB) between the two groups and observed that patients with high ANTXR1 expression suffered from a lower TMB, potentially leading to less sensitivity to checkpoint therapy. Molecularly, results displayed that ANTXR1 is an immunosuppressive element, which may perform its function via promoting the secretion of immunosuppressive factors that play a significant role in modulating tumor-associated fibroblast transformation, M2 macrophage polarization, and T cell exhaustion. Gene set enrichment analysis revealed that cancer-related pathways including epithelial-to-mesenchymal transition, focal adhesion, and transforming growth factor-β (TGF-β) signaling pathways were enriched in high ANTXR1 expression tumors. Our work suggests that ANTXR1 could not only serve as a valuable prognostic biomarker in GC but also be deemed as a potential immunotherapeutic target and useful biomarker of sensitivity to chemotherapy.

Emerging roles of RNA methylation in gastrointestinal cancers

RNA methylation has emerged as a fundamental process in epigenetic regulation. Accumulating evidences indicate that RNA methylation is essential for many biological functions, and its dysregulation is associated with human cancer progression, particularly in gastrointestinal cancers. RNA methylation has a variety of biological properties, including N6-methyladenosine (m6A), 2-O-dimethyladenosine (m6Am), N1-methyladenosine (m1A), 5-methylcytosine (m5C) and 7-methyl guanosine (m7G). Dynamic and reversible methylation on RNA is mediated by RNA modifying proteins called "writers" (methyltransferases) and "erasers" (demethylases). "Readers" (modified RNA binding proteins) recognize and bind to RNA methylation sites, which influence the splicing, stability or translation of modified RNAs. Herein, we summarize the biological functions and mechanisms of these well-known RNA methylations, especially focusing on the roles of m6A in gastrointestinal cancer development.

Comprehensive Genomic Profiling of Gastroenteropancreatic Neuroendocrine Neoplasms (GEP-NENs)

PURPOSE

GEP-NENs are rare malignancies with increasing incidence. Their molecular characteristics are still undefined. We explored the underlying biology of GEP-NENs and the differences between gastrointestinal (GI) and pancreatic (PNEN), high-grade (HG), and low-grade (LG) tumors.

EXPERIMENTAL DESIGN

GEP-NENs were analyzed using next-generation sequencing (NGS; MiSeq on 47 genes, NextSeq on 592 genes), IHC, and in situ hybridization. Tumor mutational burden (TMB) was calculated on the basis of somatic nonsynonymous missense mutations, and microsatellite instability (MSI) was evaluated by NGS of known MSI loci.

RESULTS

In total, 724 GEP-NENs were examined: GI (N = 469), PNEN (N = 255), HG (N = 135), and LG (N = 335). Forty-nine percent were female, and median age was 59. Among LG tumors, the most frequently mutated genes were ATRX (13%), ARID1A (10%), and MEN1 (10%). HG tumors showed TP53 (51%), KRAS (30%), APC (27%), and ARID1A (23%). Immune-related biomarkers yielded a lower prevalence in LG tumors compared with HG [MSI-H 0% vs. 4% (P = 0.04), PD-L1 overexpression 1% vs. 6% (P = 0.03), TMB-high 1% vs. 7% (P = 0.05)]. Compared with LG, HG NENs showed a higher mutation rate in BRAF (5.4% vs. 0%, P < 0.0001), KRAS (29.4% vs. 2.6%, P < 0.0001), and PI3KCA (7% vs. 0.3%, P < 0.0001). When compared with GI, PNEN carried higher frequency of MEN1 (25.9% vs. 0.0%, P < 0.0001), FOXO3 (8.6% vs. 0.8%, P = 0.005), ATRX (20.6% vs. 2.0%, P = 0.007), and TSC2 (6.3% vs. 0.0%, P = 0.007), but lower frequency of mutations in APC (1.0% vs. 13.8%, P < 0.0001).

CONCLUSIONS

Significant molecular differences were observed in GEP-NENs by tumor location and grade, indicating differences in carcinogenic pathways and biology.

Predicting Peritoneal Dissemination of Gastric Cancer in the Era of Precision Medicine: Molecular Characterization and Biomarkers

Gastric cancer (GC) is a leading cause of worldwide cancer-related death. Being a highly heterogeneous disease, the current treatment of GC has been suboptimal due to the lack of subtype-dependent therapies. Peritoneal dissemination (PD) is a common pattern of GC metastasis associated with poor prognosis. Therefore, it is urgently necessary to identify patients at high risk of PD. PD is found to be associated with Lauren diffuse type GC. Molecular profiling of GC, especially diffuse type GC, has been utilized to identify molecular alterations and has given rise to various molecular classifications, shedding light on the underlying mechanism of PD and enabling identification of patients at higher PD risk. In addition, a series of diagnositc and prognostic biomarkers of PD from serum, peritoneal lavages and primary GCs have been reported. This comprehensive review summarizes findings on the multi-omic characteristics of diffuse type GC, the clinical significance of updating molecular classifications of GC in association with PD risk and research advances in PD-associated biomarkers.

Molecular classification and therapeutic targets in extrahepatic cholangiocarcinoma

BACKGROUND & AIMS

Cholangiocarcinoma (CCA), a deadly malignancy of the bile ducts, can be classified based on its anatomical location into either intrahepatic (iCCA) or extrahepatic (eCCA), each with different pathogenesis and clinical management. There is limited understanding of the molecular landscape of eCCA and no targeted therapy with clinical efficacy has been approved. We aimed to provide a molecular classification of eCCA and identify potential targets for molecular therapies.

METHODS

An integrative genomic analysis of an international multicenter cohort of 189 eCCA cases was conducted. Genomic analysis included whole-genome expression, targeted DNA-sequencing and immunohistochemistry. Molecular findings were validated in an external set of 181 biliary tract tumors from the ICGC.

RESULTS

KRAS (36.7%), TP53 (34.7%), ARID1A (14%) and SMAD4 (10.7%) were the most prevalent mutations, with ∼25% of tumors having a putative actionable genomic alteration according to OncoKB. Transcriptome-based unsupervised clustering helped us define 4 molecular classes of eCCA. Tumors classified within the Metabolic class (19%) showed a hepatocyte-like phenotype with activation of the transcription factor HNF4A and enrichment in gene signatures related to bile acid metabolism. The Proliferation class (23%), more common in patients with distal CCA, was characterized by enrichment of MYC targets, ERBB2 mutations/amplifications and activation of mTOR signaling. The Mesenchymal class (47%) was defined by signatures of epithelial-mesenchymal transition, aberrant TGFβ signaling and poor overall survival. Finally, tumors in the Immune class (11%) had a higher lymphocyte infiltration, overexpression of PD-1/PD-L1 and molecular features associated with a better response to immune checkpoint inhibitors.

CONCLUSION

An integrative molecular characterization identified distinct subclasses of eCCA. Genomic traits of each class provide the rationale for exploring patient stratification and novel therapeutic approaches.

LAY SUMMARY

Targeted therapies have not been approved for the treatment of extrahepatic cholangiocarcinoma. We performed a multi-platform molecular characterization of this tumor in a cohort of 189 patients. These analyses revealed 4 novel transcriptome-based molecular classes of extrahepatic cholangiocarcinoma and identified ∼25% of tumors with actionable genomic alterations, which has potential prognostic and therapeutic implications.

Exploring and modelling colon cancer inter-tumour heterogeneity: opportunities and challenges

Colon cancer inter-tumour heterogeneity is installed on multiple levels, ranging from (epi)genetic driver events to signalling pathway rewiring reflected by differential gene expression patterns. Although the existence of heterogeneity in colon cancer has been recognised for a longer period of time, it is sparingly incorporated as a determining factor in current clinical practice. Here we describe how unsupervised gene expression-based classification efforts, amongst which the consensus molecular subtypes (CMS), can stratify patients in biological subgroups associated with distinct disease outcome and responses to therapy. We will discuss what is needed to extend these subtyping efforts to the clinic and we will argue that preclinical models recapitulate CMS subtypes and can be of vital use to increase our understanding of treatment response and resistance and to discover novel targets for therapy.

Expression Patterns of Immune Genes Reveal Heterogeneous Subtypes of High-Risk Neuroblastoma

High risk neuroblastoma (HR-NB) remains difficult to treat, and its overall survival (OS) is still below 50%. Although HR-NB is a heterogeneous disease, HR-NB patients are currently treated in a similar fashion. Through unsupervised biclustering, we further stratified HR-NB patients into two reproducible and clinically distinct subtypes, including an ultra-high risk neuroblastoma (UHR-NB) and high risk neuroblastoma (HR-NB). The UHR-NB subtype consistently had the worst OS in multiple independent cohorts ( P < 0 . 008 ). Out of 283 neuroblastoma-specific immune genes that were used for stratification, 39 of them were differentiated in UHR-NB, including four upregulated and 35 downregulated, as compared to HR-NB. The four UHR-NB upregulated genes (ADAM22, GAL, KLHL13 and TWIST1) were all upregulated in MYCN amplified neuroblastoma in 5 additional cohorts. TWIST1 and ADAM22 were also positively correlated with cancer stage, while GAL was an independent OS predictor in addition to MYCN and age. Furthermore, we identified 26 commonly upregulated and 311 downregulated genes in UHR-NB from all 4723 immune-related genes. While 43 KEGG pathways with molecular functions were enriched in the downregulated immune-related genes, only the P53 signaling pathway was enriched in the upregulated ones, which suggested that UHR-NB was a TP53 related subtype with reduced immune activities.

Generation of 3D human gastrointestinal organoids: principle and applications

The stomach and intestine are important organs for food digestion, nutrient absorption, immune protection and hormone production. Gastrointestinal diseases such as cancer and ulcer are big threats to human health. Appropriate disease models are in sore need for mechanistic understanding and drug discovery. Organoids are three-dimensional in vitro cultured structures derived from tissues and pluripotent stem cells with multiple types of cells and mimicking in vivo tissues in major aspects. They have a great potential in regenerative medicine and personalized medicine. Here, we review the major signaling pathways regulating gastrointestinal epithelial homeostasis, summarize different methods to generate human gastrointestinal organoids and highlight their applications in biological research and medical practice.

The diagnostic value of extracellular protein kinase A (ECPKA) in serum for gastric and colorectal cancer

Background

For the biomarkers of cancer, many chromosomal and genetic alterations have been examined as possible. However, some tumors do not display a clear molecular and genetic signature. While there are some cellular processes regulated by second messenger intracellular pathways indeed involved in carcinogenesis. The first intracellular second messenger was described as cyclic adenosine 3',5'-monophosphate (cAMP), and cAMP-dependent protein kinase (PKA) play a crucial role in several biological processes; The dysregulation of PKA-mediated signaling in several types of cancer should be investigated. More interesting, the alpha catalytic subunit of PKA (PKACα) could be secreted into the conditioned medium by different types of cancer cells, and it also existed in the serum of some cancer patients, defined as extracellular protein kinase A (ECPKA).

Methods

The levels of serum PKACα from healthy people, gastric cancer and colon cancer patients were detected by ELISA kits. Western blotting was used to detect the expression of PKACα in cancer tissue and the adjacent mucosa. Mann-Whitney test was applied to analyze the patients’ characteristics and serum PKACα. ROC analyses were performed to further evaluate the utility of PKACα in cancer diagnosis. The correlation of serum PKACα and T stage, age, and tumor markers were analyzed by Spearman rank and Pearson correlation analysis, respectively.

Results

There were significant differences of PKACα in serum between the volunteers and the gastric cancers (P<0.01), but not the colorectal cancers (P>0.05). ROC analyses evaluated the utility of PKACα for gastric cancer with 61.90% sensitivities and 87.50% specificities. The serum PKACα was correlated with tumor marker CA50, while there was no significant difference of PKACα expression between the gastric/colorectal cancer tissue and the adjacent mucosa.

Conclusions

The above results implied that PKACα levels might be a potential biomarker for the early screening of gastric cancers. Moreover, further research is still needed to investigate the role of secreted PKACα and the regulatory mechanism in tumor progression.

Natural killer cell and stroma abundance are independently prognostic and predict gastric cancer chemotherapy benefit

BACKGROUNDSpecific features of the tumor microenvironment (TME) may provide useful prognostic information. We conducted a systematic investigation of the cellular composition and prognostic landscape of the TME in gastric cancer.METHODSWe evaluated the prognostic significance of major stromal and immune cells within the TME. We proposed a composite TME-based risk score and tested it in 6 independent cohorts of 1678 patients with gene expression or IHC measurements. Further, we devised a patient classification system based on TME characteristics.RESULTSWe identified NK cells, fibroblasts, and endothelial cells as the most robust prognostic markers. The TME risk score combining these cell types was an independent prognostic factor when adjusted for clinicopathologic variables (gene expression, HR [95% CI], 1.42 [1.22-1.66]; IHC, 1.34 [1.24-1.45], P < 0.0001). Higher TME risk scores consistently associated with worse survival within every pathologic stage (HR range, 2.18-3.11, P < 0.02) and among patients who received surgery only. The TME risk score provided additional prognostic value beyond stage, and combination of the two improved prognostication accuracy (likelihood-ratio test χ2 = 235.4 vs. 187.6, P < 0.0001; net reclassification index, 23%). The TME risk score can predict the survival benefit of adjuvant chemotherapy in nonmetastatic patients (stage I-III) (interaction test, P < 0.02). Patients were divided into 4 TME subtypes that demonstrated distinct genetic and molecular patterns and complemented established genomic and molecular subtypes.CONCLUSIONWe developed and validated a TME-based risk score as an independent prognostic and predictive factor, which has the potential to guide personalized management of gastric cancer.FUNDINGThis project is partially supported by NIH grant 1R01 CA222512.

Esophageal, gastric and colorectal cancers: Looking beyond classical serological biomarkers towards glycoproteomics-assisted precision oncology

Esophageal (OC), gastric (GC) and colorectal (CRC) cancers are amongst the digestive track tumors with higher incidence and mortality due to significant molecular heterogeneity. This constitutes a major challenge for patients' management at different levels, including non-invasive detection of the disease, prognostication, therapy selection, patient's follow-up and the introduction of improved and safer therapeutics. Nevertheless, important milestones have been accomplished pursuing the goal of molecular-based precision oncology. Over the past five years, high-throughput technologies have been used to interrogate tumors of distinct clinicopathological natures, generating large-scale biological datasets (e.g. genomics, transcriptomics, and proteomics). As a result, GC and CRC molecular subtypes have been established to assist patient stratification in the clinical settings. However, such molecular panels still require refinement and are yet to provide targetable biomarkers. In parallel, outstanding advances have been made regarding targeted therapeutics and immunotherapy, paving the way for improved patient care; nevertheless, important milestones towards treatment personalization and reduced off-target effects are also to be accomplished. Exploiting the cancer glycoproteome for unique molecular fingerprints generated by dramatic alterations in protein glycosylation may provide the necessary molecular rationale towards this end. Therefore, this review presents functional and clinical evidences supporting a reinvestigation of classical serological glycan biomarkers such as sialyl-Tn (STn) and sialyl-Lewis A (SLe^A) antigens from a tumor glycoproteomics perspective. We anticipate that these glycobiomarkers that have so far been employed in non-invasive cancer prognostication may hold unexplored value for patients' management in precision oncology settings.

Identification of TP53 mutation associated-immunotype and prediction of survival in patients with hepatocellular carcinoma

Background

Stratification of tumors is necessary to achieve better clinical outcomes. Hepatocellular carcinoma (HCC) is commonly associated with mutation of the TP53 gene and heterogeneity in immune cell content. However, TP53 mutation-associated immunotype of HCC has not been reported yet. This study aimed to identify the TP53 mutation-associated immunotype in HCC.

Methods

The mutation annotation format (MAF) document, mRNA expression data, and clinical data of HCC patients were downloaded from the publicly available The Cancer Genome Atlas (TCGA) data portal. Data from 332 HCC patients were analyzed in this study. Infiltrating immune cells were evaluated by the well-known CIBERSORT method. Additional mutation data of HCC patients were downloaded from the Catalogue of Somatic Mutations in Cancer (COSMIC) database.

Results

The TP53 gene harbored the highest frequency of mutations in HCC patients. Consequently, five lethal features, including TP53 mutations, were screened by least absolute shrinkage and selector operation (LASSO)-COX regression, according to TP53 mutations and 22 infiltrating immune cells. Two distinct subgroups of HCC were identified, namely, immunotypes A and B. Furthermore, the expression levels of co-inhibitory immune checkpoints were significantly upregulated, and the gene ontology (GO) terms or pathways to boost immune responses were found to be inhibited in the immunotype B subgroup compared to that in the immunotype A subgroup. Finally, we proved immunotype to be an independent adverse prognostic factor that contributed to improvement in the predictive accuracy of the immunotype-based model and helped in avoiding excessive medical treatment.

Conclusions

Two distinct immunotypes of HCC, in terms of prognosis, phenotype, and function, were identified and the traditional understanding of intratumoralCD8⁺ T cells was subverted. Moreover, the identified immunotypes contributed to improving the predictive accuracy of the immunotype-based model and helped in avoiding excessive medical treatment in some HCC patients.