RNA expression profiling of peritoneal metastasis from pancreatic cancer treated with Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC)

Objectives

Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC) is an experimental treatment option in peritoneal metastasis from pancreatic cancer (PM-PC). Aims were to examine mRNA profile of fibrosis due to response after systemic chemotherapy and PIPAC (Regression) compared to treatment-naïve PM-PC and chronic cholecystitis-related peritoneal fibrosis (Controls).

Methods

Peritoneal biopsies (PBs) from PM-PC patients who had undergone systemic chemotherapy and PIPAC were evaluated with Peritoneal Regression Grading Score (PRGS). We extracted RNA from PBs with Regression (PRGS 1, n=11), treatment-naïve PM-PC (n=10), and Controls (n=10). Profiling of 800 mRNAs was performed (NanoString nCounter, PanCancer Immuno-Oncology 360 (IO-360) and 30 additional stroma-related mRNAs).

Results

Regression vs. PM-PC identified six up-regulated and 197 down-regulated mRNAs (FDR≤0.05), linked to TNF-α signaling via NF-kB, G2M checkpoint, epithelial-mesenchymal transition, estrogen response, and coagulation. Regression vs. Controls identified 43 significantly up-regulated mRNAs, linked to interferon-α response, and down-regulation of 99 mRNAs, linked to TNF-α signaling via NF-kB, inflammatory response, epithelial-mesenchymal transition, KRAS signaling, and hypoxia (FDR≤0.05).

Conclusions

In regressive fibrosis of PM-PC after systemic chemotherapy and PIPAC (Regression), downregulation of mRNAs related to key tumor biological pathways was identified. Regression also showed transcriptional differences from unspecific, benign fibrosis (Controls). Future studies should explore whether mRNA profiling of PBs with PM from PC or other primaries holds prognostic or predictive value.

Regional Immunotherapy for Peritoneal Carcinomatosis in Gastroesophageal Cancer: Emerging Strategies to Re-Condition a Maladaptive Tumor Environment

Peritoneal carcinomatosis originating from gastric/gastroesophageal junction cancer (GC-PC) occurs in a defined subset of gastric cancer patients with unique clinical, pathologic, molecular and immunologic characteristics that create significant obstacles to effective treatment with modern therapy. Although systemic chemo- and immuno- therapy have yielded disappointing results in GC-PC, recent advances in the characterization of GC-PC and peritoneal immune biology present new opportunities for targeted therapeutics. In this review article, we discuss the distinct properties of GC-PC and the peritoneal immune environment as they pertain to current and investigative treatment strategies. We discuss pre-clinical studies and clinical trials relevant to the modulation of the peritoneal environment as a therapeutic intervention in GC-PC. Finally, we present a road map for future combinatorial strategies based on the conception of the peritoneal cavity as a bioreactor. Within this isolated compartment, prevailing immunosuppressive conditions can be altered through regional interventions toward an adaptive phenotype that would support the effectiveness of regionally delivered cellular therapy products. It is hoped that novel combination strategies would promote efficacy not only in the sequestered peritoneal environment, but also via migration into the circulation of tumor-reactive lymphocytes to produce durable systemic disease control, thereby improving oncologic outcome and quality of life in patients with GC-PC.

Quantitative Analysis on Molecular Characteristics Evolution of Gastric Cancer Progression and Prognosis

The dynamic changes of key biological characteristics from gastric low-grade intraepithelial neoplasia (LGIN) to high-grade intraepithelial neoplasia (HGIN) to early gastric cancer (EGC) are still unclear, which greatly affect the accurate diagnosis and treatment of EGC and prognosis evaluation of gastric cancer (GC). In this study, bioinformatics methods/tools are applied to quantitatively analyze molecular characteristics evolution of GC progression, and a prognosis model is constructed. This study finds that some dysregulated differentially expressed mRNAs (DEmRNAs) in the LGIN stage may continue to promote the occurrence and development of EGC. Among the LGIN, HGIN, and EGC stages, there are differences and relevance in the transcription expression patterns of DEmRNAs, and the activation related to immune cells is very different. The biological functions continuously changed during the progression from LGIN to HGIN to EGC. The COX model constructed based on the three EGC-related DEmRNAs has GC prognostic risk prediction ability. The evolution of biological characteristics during the development of EGC mined by the authors provides new insight into understanding the molecular mechanism of EGC occurrence and development. The three-gene prognostic risk model provides a new method for assisting GC clinical treatment decisions.

A prediction model for prognosis of gastric adenocarcinoma based on six metabolism-related genes

Background

The study of tumor metabolism is of great value to elucidate the mechanism of tumorigenesis and predict the prognosis of patients. However, the prognostic role of metabolism-related genes (MRGs) in gastric adenocarcinoma (GAD) remains poorly understood.

Methods

We downloaded the gene chip dataset GSE79973 (n = 20) of GAD from the Gene Expression Omnibus (GEO) database to compare differentially expressed genes (DEGs) between normal and tumor tissues. We then extracted MRGs from these DEGs and systematically investigated the prognostic value of these differential MRGs for predicting patients' overall survival by univariable and multivariable Cox regression analysis. Six metabolic genes (ACOX3, APOE, DIO2, HSD17B4, NUAK1, and WHSC1L1) were identified as prognosis-associated hub genes, which were used to build a prognostic model in the training dataset GSE15459 (n = 200), and then validated in the dataset GSE62254 (n = 300).

Results

Patients were divided into high-risk and low-risk subgroups based on the model's risk score, and it was found that patients in the high-risk subgroup had shorter overall survival than those in the low-risk subgroup, both in the training and testing datasets. In addition, for the training and testing cohorts, the area under the ROC curve of the prognostic model for one-year survival prediction was 0.723 and 0.667, respectively, indicating that the model has good predictive performance. Furthermore, we established a nomogram based on tumor stage and risk score to effectively predict the overall survival (OS) of GAD patients. The expression of 6 MRGs at the protein level was confirmed by immunohistochemistry (IHC). Kaplan-Meier survival analysis further confirmed that their expression influenced OS in GAD patients.

Conclusion

Collectively, the 6 MRGs signature might be a reliable tool for assessing OS in GAD patients, with potential application value in clinical decision-making and individualized therapy.

Deterministic evolution and stringent selection during preneoplasia

The earliest events during human tumour initiation, although poorly characterized, may hold clues to malignancy detection and prevention1. Here we model occult preneoplasia by biallelic inactivation of TP53, a common early event in gastric cancer, in human gastric organoids. Causal relationships between this initiating genetic lesion and resulting phenotypes were established using experimental evolution in multiple clonally derived cultures over 2 years. TP53 loss elicited progressive aneuploidy, including copy number alterations and structural variants prevalent in gastric cancers, with evident preferred orders. Longitudinal single-cell sequencing of TP53-deficient gastric organoids similarly indicates progression towards malignant transcriptional programmes. Moreover, high-throughput lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programmes repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference and a marked degree of phenotypic convergence in premalignant epithelial organoids. These data imply predictability in the earliest stages of tumorigenesis and show evolutionary constraints and barriers to malignant transformation, with implications for earlier detection and interception of aggressive, genome-instable tumours.

FMO family may serve as novel marker and potential therapeutic target for the peritoneal metastasis in gastric cancer

Objective

To explore the relationship between flavin-containing monooxygenases (FMOs) and peritoneal metastasis (PM) in gastric cancer (GC).

Materials and methods

TIMER 2.0 was used to perform pan-cancer analysis and assess the correlation between the expression of FMOs and cancers. A dataset from The Cancer Genome Atlas (TCGA) was used to analyze the correlation between FMOs and clinicopathological features of GC. PM is well established as the most common mode of metastasis in GC. To further analyze the correlation between FMOs and PM of GC, a dataset was obtained from the National Center for Biotechnology Information Gene Expression Omnibus (GEO) database. The results were validated by immunohistochemistry. The relationship between FMOs and PM of GC was explored, and a novel PM risk signature was constructed by least absolute shrinkage and selection operator (LASSO) regression analysis. The regression model's validity was tested by multisampling. A nomogram was established based on the model for predicting PM in GC patients. The mechanism of FMOs in GC patients presenting with PM was assessed by conducting Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses in TCGA and GEO datasets. Finally, the potential relationship between FMOs and immunotherapy was analyzed.

Results

The pan-cancer analysis in TCGA and GEO datasets showed that FMO1 was upregulated, while FMO2 and FMO4 were downregulated in GC. Moreover, FMO1 and FMO2 correlated positively with the T and N stage of GC in the TCGA dataset. FMO1 and FMO2 expression was a risk factor for GC (hazard ratio: 1.112 and 1.185). The overexpression of FMO1 was significantly correlated with worse disease-free-survival (DFS) and overall survival (OS). However, no relationship was found between FMO2 expression in GC and DFS and OS. PM was highly prevalent among GC patients and typically associated with a worse prognosis. FMO1 was highly expressed in GC with PM. FMO1 and FMO2 were positively correlated with PM in GC. We identified a 12-gene panel for predicting the PM risk signature by LASSO (Area Under Curve (AUC) = 0.948, 95%CI: 0.896-1.000). A 10-gene panel for PM prediction was identified (AUC = 0.932, 95%CI: 0.874-0.990), comprising FMO1 and FMO2. To establish a model for clinical application, a 7-gene panel was established (AUC = 0.927, 95% CI: 0.877-0.977) and successfully validated by multisampling. (AUC = 0.892, 95% CI: 0.878-0.906). GO and KEGG analyses suggest that FMO1 and FMO2 regulate the extracellular matrix and cell adhesion. FMO1 and FMO2 were positively correlated with the immune score of GC, and their expression was associated with the infiltration of immune cells.

Conclusion

PM in GC is strongly correlated with FMOs. Overall, FMO1 and FMO2 have huge prospects for application as novel diagnostic and therapeutic targets.

Integrating multiple machine learning algorithms for prognostic prediction of gastric cancer based on immune-related lncRNAs

Background: Long non-coding RNAs (lncRNAs) play an important role in the immune regulation of gastric cancer (GC). However, the clinical application value of immune-related lncRNAs has not been fully developed. It is of great significance to overcome the challenges of prognostic prediction and classification of gastric cancer patients based on the current study.

Methods: In this study, the R package ImmLnc was used to obtain immune-related lncRNAs of The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) project, and univariate Cox regression analysis was performed to find prognostic immune-related lncRNAs. A total of 117 combinations based on 10 algorithms were integrated to determine the immune-related lncRNA prognostic model (ILPM). According to the ILPM, the least absolute shrinkage and selection operator (LASSO) regression was employed to find the major lncRNAs and develop the risk model. ssGSEA, CIBERSORT algorithm, the R package maftools, pRRophetic, and clusterProfiler were employed for measuring the proportion of immune cells among risk groups, genomic mutation difference, drug sensitivity analysis, and pathway enrichment score.

Results: A total of 321 immune-related lncRNAs were found, and there were 26 prognostic immune-related lncRNAs. According to the ILPM, 18 of 26 lncRNAs were selected and the risk score (RS) developed by the 18-lncRNA signature had good strength in the TCGA training set and Gene Expression Omnibus (GEO) validation datasets. Patients were divided into high- and low-risk groups according to the median RS, and the low-risk group had a better prognosis, tumor immune microenvironment, and tumor signature enrichment score and a higher metabolism, frequency of genomic mutations, proportion of immune cell infiltration, and antitumor drug resistance. Furthermore, 86 differentially expressed genes (DEGs) between high- and low-risk groups were mainly enriched in immune-related pathways.

Conclusion: The ILPM developed based on 26 prognostic immune-related lncRNAs can help in predicting the prognosis of patients suffering from gastric cancer. Precision medicine can be effectively carried out by dividing patients into high- and low-risk groups according to the RS.

NOTCH3 is a Prognostic Factor and Is Correlated With Immune Tolerance in Gastric Cancer

Introduction

Although traditional treatments confer survival benefits to patients with gastric cancer (GC), many patients experience relapse soon after postoperative adjuvant therapy. Immune-related mechanisms play an important role in GC, and immunotherapeutic strategies are considered to be a promising direction for the treatment of GC. Thus, our study aimed to investigate the expression and prognostic significance of immune-related genes in GC.

Methods

Formalin-fixed, paraffin-embedded samples were collected from 48 resectable GC patients. The transcriptome data of the tumor immune microenvironment were assessed using an immuno-oncology 395-gene panel RNA sequencing platform. The prognostic value of the 395 genes was analyzed and validated in the KM plotter and GEPIA databases. The data from The Cancer Genome Atlas (TCGA, downloaded from UCSC Xena repository) and Tumor IMmune Estimation Resource (TIMER) were used to evaluate the correlations between prognostic factors and immune signatures.

Results

Among the 395 genes, NOTCH3 was identified as a good prognostic factor for GC patients. Its prognostic value was also suggested in both our GC cohort from Zhongshan Hospital and the public databases (KM plotter and GEPIA database). Mechanistically, high NOTCH3 expression correlated with a lower infiltration of activated CD8⁺ T cells and a higher infiltration of immunosuppressive cells including Tregs and M2 macrophages in the tumor microenvironment. Moreover, high NOTCH3 expression was accompanied by the increased expression of a series of immune checkpoint inhibitors, resulting in a dampened immune response. Interestingly, NOTCH3 expression had a negative association with well-documented predictive biomarkers of immune checkpoint blockade (ICB) immunotherapy, including tumor mutation burden (TMB), gene expression profiling (GEP) score and innate anti-PD-1 resistance (IPRES) signature.

Conclusion

These findings uncovered a new mechanism by which NOTCH3 participates in the immune tolerance of GC, implying the potential of NOTCH3 as a therapeutic target or predictive marker for GC patients.

FNDC1 Promotes the Invasiveness of Gastric Cancer via Wnt/β-Catenin Signaling Pathway and Correlates With Peritoneal Metastasis and Prognosis

BACKGROUND

Gastric cancer (GC) has a high morbidity and mortality rate, with peritoneal metastasis (PM) identified as the main site of metastasis. Our previous study found that FNDC1 has a higher frequency of mutations in patients with PM by high-throughput sequencing assay, suggesting that it may be associated with GC invasion and PM, however the specific mechanism remains unclear.

METHODS

First, the correlation between FNDC1 and PM and prognosis of GC was clarified by bioinformatics and clinicopathological analysis. Next, the effect of FNDC1 expression on the invasion and metastasis ability of GC was investigated in vivo and in vitro. Finally, the signaling pathways involved in the regulation of FNDC1 were explored.

RESULTS

FNDC1 was highly expressed in GC and was associated with PM and poor prognosis. FNDC1 was also associated with epithelial-mesenchymal transition (EMT) in GC cells. Through in vivo and in vitro experiments, it was clarified that knockdown of FNDC1 could inhibit the proliferation, invasion, and migration of GC cells. In addition, it was elucidated that FNDC1 promotes EMT through the Wnt/β-catenin signaling pathway.

CONCLUSION

FNDC1 may be associated with the invasion of GC and PM after surgery. FNDC1 was highly expressed in GC tissues and cell lines, while significantly associated with poor DFS and OS in GC patients. Both univariate and multivariate analyses suggested that the expression of FNDC1 was an independent factor for GC. Knockdown of FNDC1 also significantly inhibited the proliferation, migration, and activity of GC cells. FNDC1 may promote EMT in GC cells through the regulation of Wnt/β-catenin signaling pathway. FNDC1 has the potential to be used as a predictor of PM and may also be studied in depth as a therapeutic target for GC, which has potential clinical utility and is worthy of further validation.

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.

Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients

Gastric cancer (GC) is the second leading cause of cancer mortality and remains the fourth common cancer worldwide. The effective and feasible methods for predicting the possible outcomes for GC patients are still lacking. While genetic profiling might be suitable in some way, the application of gene expression signatures has been show to be a robust tool. Here, by performing a comprehensive search in PubMed, we provided an up-to-date summary of 39 prognostic gene signatures for GC patients, and described the processing procedure of the selection, calculation and construction of gene signature. We also reviewed current web tools including PROGgene and SurvExpress that can be used to analyze the prognostic value of multiple genes for GC. This review will aid in comprehensive understanding of the current prognostic gene signatures to accurately predict the outcome of GC patients, and may guide the future clinical management when the reliability of these signatures is validated in clinics.

Evaluation of predictive role of carcinoembryonic antigen and salivary mRNA biomarkers in gastric cancer detection

We explored the potential of combining carcinoembryonic antigen (CEA) and salivary mRNAs for gastric cancer (GC) detection.This study included 2 phases of study: a biomarker discovery phase and an independent validation phase. In the discovery phase, we measured CEA levels in blood samples and expression level of messenger RNAs (SPINK7, PPL, SEMA4B, SMAD4) in saliva samples of 140 GC patients and 140 healthy controls. We evaluated the clinical performance of each biomarker and developed a predictive model using machine-learning algorithm to differentiate GC patients and healthy controls.Our biomarker panel successfully discriminated GC patients from healthy controls with both high sensitivity (0.94) and high specificity (0.91). We next applied our biomarker panel in the independent validation phase, in which we recruited a new patient cohort of 60 GC patients and 60 healthy controls. Using our biomarker panel, the GC patients were discriminated from healthy controls in the validation phase, with sensitivity of 0.92 and specificity of 0.87.A combination of blood CEA and salivary messenger RNA could be a promising approach to detect GC.

Dissecting expression profiles of gastric precancerous lesions and early gastric cancer to explore crucial molecules in intestinal-type gastric cancer tumorigenesis

Intestinal‐type gastric cancer (IGC) has a clear and multistep histological evolution. No studies have comprehensively explored gastric tumorigenesis from inflammation through low‐grade intraepithelial neoplasia (LGIN) and high‐grade intraepithelial neoplasia (HGIN) to early gastric cancer (EGC). We sought to investigate the characteristics participating in IGC tumorigenesis and identify related prognostic information within the process. RNA expression profiles of 94 gastroscopic biopsies from 47 patients, including gastric precancerous lesions (GPL: LGIN and HGIN), EGC, and paired controls, were detected by Agilent Microarray. During IGC tumorigenesis from LGIN through HGIN to EGC, the number of activity‐changed tumor hallmarks increased. LGIN and HGIN had similar expression profiles when compared to EGC. We observed an increase in the stemness of gastric epithelial cells in LGIN, HGIN, and EGC, and we found 27 consistent genes that might contribute to dedifferentiation, including five driver genes. Remarkably, we perceived that the immune microenvironment was more active in EGC than in GPL, especially in the infiltration of lymphocytes and macrophages. We identified a five‐gene signature from the gastric tumorigenesis process that could independently predict the overall survival and disease‐free survival of GC patients (log‐rank test: p < 0.0001), and the robustness was verified in an independent cohort (n > 300) and by comparing with two established prognostic signatures in GC. In conclusion, during IGC tumorigenesis, cancer‐like changes occur in LGIN and accumulate in HGIN and EGC. The immune microenvironment is more active in EGC than in LGIN and HGIN. The identified signature from the tumorigenesis process has robust prognostic significance for GC patients. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Integrated Analysis Identifies an Immune-Based Prognostic Signature for the Mesenchymal Identity in Gastric Cancer

Background

Gastric cancer (GC) has been divided into four molecular subtypes, of which the mesenchymal subtype has the poorest survival. Our goal is to develop a prognostic signature by integrating the immune system and molecular modalities involved in the mesenchymal subtype.

Methods

The gene expression profiles collected from 6 public datasets were applied to this study, including 1,221 samples totally. Network analysis was applied to integrate the mesenchymal modalities and immune signature to establish an immune-based prognostic signature for GC (IPSGC).

Results

We identified six immune genes as key factors of the mesenchymal subtype and established the IPSGC. The IPSGC can significantly divide patients into high- and low-risk groups in terms of overall survival (OS) and relapse-free survival (RFS) in discovery (OS: P < 0.001) and 5 independent validation sets (OS range: P = 0.05 to P < 0.001; RFS range: P = 0.03 to P < 0.001). Further, in multivariate analysis, the IPSGC remained an independent predictor of prognosis and performed better efficiency compared to clinical characteristics. Moreover, macrophage M2 was significantly enriched in the high-risk group, while plasma cells were enriched in the low-risk group.

Conclusions

We propose an immune-based signature identified by network analysis, which is a promising prognostic biomarker and help for the selection of GC patients who might benefit from more rigorous therapies. Further prospective studies are warranted to test and validate its efficiency for clinical application.

Identification of novel biomarkers, MUC5AC, MUC1, KRT7, GAPDH, CD44 for gastric cancer

Gastric cancer (GC) is one of the most common malignant tumors in the world, and it is also the third largest cause of cancer-related death in the world. As far as we know, no biomarker has been widely accepted for early diagnosis and prognosis prediction of gastric cancer. The purpose of this study is to find potential biomarkers to predict the prognosis of GC. The gene expression profiles of GSE2685 were downloaded from GEO database. Morpheus was used to calculate the differentially expressed genes (DEGs) between primary advanced gastric cancer tissues and noncancerous gastric tissues. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and protein-protein interaction (PPI) network of DEGs was constructed. Kaplan-Meier Plotter was used to determine the overall survival (OS) outcomes of UC5AC, MUC1, KRT7, GAPDH, CD44, and GEPIA was used to determine the Pearson correlation analysis. In total, 710 DEGs were identified in GC, including 396 upregulated genes and 314 downregulated genes. GO enrichment revealed that they were mainly enriched in binding, catalytic activity, cellular process and cell. KEGG pathway revealed that they were mainly enriched in metabolic pathways, pathways in cancer and PI3K-Akt signaling pathway. MUC5AC, MUC1, KRT7, GAPDH, CD44 were identified from the PPI network. MUC5AC, MUC1, KRT7, GAPDH, CD44 were demonstrated to have prognostic value for patients with GC. MUC5AC, MUC1 exhibited low expression levels in GC tissues, KRT7, GAPDH, CD44 presented high expression levels in GC tissues. In particular, KRT7 is hardly expressed in normal gastric tissues. MUC5AC and MUC1 were negatively correlated with GAPDH, CD44, respectively; and GAPDH was positively correlated with CD44 and KRT7, respectively. Moreover. MUC5AC, MUC1, KRT7, GAPDH, and CD44 are not only related to GC but also to apoptosis pathway. Results from the present study suggested that MUC5AC, MUC1, KRT7, GAPDH, CD44 may represent novel prognostic biomarkers for GC.

Prediction of gastric cancer prognosis in the next-generation sequencing era

Gastric cancer (GC) is one of the most commonly diagnosed malignancies worldwide, and is caused by complex interactions of multiple risk factors such as environmental (Helicobacter pylori and Epstein–Barr Virus), hereditary (genetic alterations and epigenetic modifications), as well as dietary and lifestyle factors. GC is usually detected at an advanced stage, with a dismal prognosis. Even for patients with similar clinical or pathologic stage receiving similar treatment, the outcomes are still uneven and unpredictable. To better incorporate genetic and epigenetic profiles into GC prognostic predication, gene expression signatures have been developed to predict GC outcomes. More recently, the advancement of high-throughput sequencing technology, also known as next-generation sequencing (NGS) technology, and analysis has provided the basis for accurate molecular classification of GC tumors. Here, we summarized and updated the literature related to NGS studies of GC, including whole-genome sequencing, whole-exome sequencing, RNA sequencing, and targeted sequencing, and discussed current progresses. NGS has facilitated the identification of genetic/epigenetic targets for screening as well as development of targeted agent therapy, thus enabling individualized patient management and treatment.

The ‘mitochondrial contact site and cristae organising system’ (MICOS) in health and human disease

The ‘mitochondrial contact site and cristae organising system’ (MICOS) is an essential protein complex that promotes the formation, maintenance and stability of mitochondrial cristae. As such, loss of core MICOS components disrupts cristae structure and impairs mitochondrial function. Aberrant mitochondrial cristae morphology and diminished mitochondrial function is a pathological hallmark observed across many human diseases such as neurodegenerative conditions, obesity and diabetes mellitus, cardiomyopathy, and in muscular dystrophies and myopathies. While mitochondrial abnormalities are often an associated secondary effect to the pathological disease process, a direct role for the MICOS in health and human disease is emerging. This review describes the role of MICOS in the maintenance of mitochondrial architecture and summarizes both the direct and associated roles of the MICOS in human disease.

Molecular Profiles and Metastasis Markers in Chinese Patients with Gastric Carcinoma

The goal of this work was to investigate the molecular profiles and metastasis markers in Chinese patients with gastric carcinoma (GC). In total, we performed whole exome sequencing (WES) on 74 GC patients with tumor and adjacent normal formalin-fixed, paraffin-embedded (FFPE) tissue samples. The mutation spectrum of these samples showed a high concordance with TCGA and other studies on GC. PTPRT is significantly associated with metastasis of GC, suggesting its predictive role in metastasis of GC. Patients carrying BRCA2 mutations tend not to metastasize, which may be related to their sensitivity to chemotherapy. Mutations in MACF1, CDC27, HMCN1, CDH1 and PDZD2 were moderately enriched in peritoneal metastasis (PM) samples. Furthermore, we found two genomic regions (1p36.21 and Xq26.3) were associated with PM of GC, and patients with amplification of 1p36.21 and Xq26.3 have a worse prognosis (P = 0.002, 0.01, respectively). Our analysis provides GC patients with potential markers for single and combination therapies.

An immune-related gene signature predicts prognosis of gastric cancer

BACKGROUND

Although the outcome of patients with gastric cancer (GC) has improved significantly with the recent implementation of annual screening programs. Reliable prognostic biomarkers are still needed due to the disease heterogeneity. Increasing pieces of evidence revealed an association between immune signature and GC prognosis. Thus, we aim to build an immune-related signature that can estimate prognosis for GC.

METHODS

For identification of a prognostic immune-related gene signature (IRGS), gene expression profiles and clinical information of patients with GC were collected from 3 public cohorts, divided into training cohort (n = 300) and 2 independent validation cohorts (n = 277 and 433 respectively).

RESULTS

Within 1811 immune genes, a prognostic IRGS consisting of 16 unique genes was constructed which was significantly associated with survival (hazard ratio [HR], 3.9 [2.78-5.47]; P < 1.0 × 10). In the validation cohorts, the IRGS significantly stratified patients into high- vs low-risk groups in terms of prognosis across (HR, 1.84 [1.47-2.30]; P = 6.59 × 10) and within subpopulations with stage I&II disease (HR, 1.96 [1.34-2.89]; P = 4.73 × 10) and was prognostic in univariate and multivariate analyses. Several biological processes, including TGF-β and EMT signaling pathways, were enriched in the high-risk group. T cells CD4 memory resting and Macrophage M2 were significantly higher in the high-risk risk group compared with the low-risk group.

CONCLUSION

In short, we developed a prognostic IRGS for estimating prognosis in GC, including stage I&II disease, providing new insights into the identification of patients with GC with a high risk of mortality.

Comprehensive Analysis of Somatic Mutations in Colorectal Cancer With Peritoneal Metastasis

BACKGROUND

To analyze for genetic mutations which may presage peritoneal metastasis by using targeted next-generation sequencing (NGS).

MATERIALS AND METHODS

Formalin-fixed, paraffin-embedded primary tumor specimens were obtained from 10 patients with small obstructing colorectal cancer and peritoneal metastasis (group A) and five with large non-obstructing colorectal cancer and no recurrence (group B). DNA was extracted for the sequencing of 409 cancer genes. The distribution of genetic mutations was compared between the two groups to find genetic mutations related to peritoneal metastasis.

RESULTS

When the samples were sorted based on similarity of gene expression by hierarchical clustering analysis, the samples were well divided between the two study groups. Mutations in AT-rich interactive domain-containing protein 1A (ARID1A), polycystic kidney and hepatic disease 1 (PKHD1), ubiquitin-protein ligase E3 component n-recognin 5 (UBR5), paired box 5 (PAX5), tumor protein p53 (TP53), additional sex combs like 1 (ASXL1) and androgen receptor (AR) genes were detected more frequently in group A.

CONCLUSION

A number of somatic mutations presumed to be relevant to colorectal cancer with peritoneal metastasis were identified in our study by NGS.

GeneExpressScore Signature: a robust prognostic and predictive classifier in gastric cancer

Although several prognostic signatures have been developed for gastric cancer (GC), the utility of these tools is limited in clinical practice due to lack of validation with large and multiple independent cohorts, or lack of a statistical test to determine the robustness of the predictive models. Here, a prognostic signature was constructed using a least absolute shrinkage and selection operator (LASSO) Cox regression model and a training dataset with 300 GC patients. The signature was verified in three independent datasets with a total of 658 tumors across multiplatforms. A nomogram based on the signature was built to predict disease-free survival (DFS). Based on the LASSO model, we created a GeneExpressScore signature (GES_GC ) classifier comprised of eight mRNA. With this classifier patients could be divided into two subgroups with distinctive prognoses [hazard ratio (HR) = 4.00, 95% confidence interval (CI) = 2.41-6.66, P < 0.0001]. The prognostic value was consistently validated in three independent datasets. Interestingly, the high-GES_GC group was associated with invasion, microsatellite stable/epithelial-mesenchymal transition (MSS/EMT), and genomically stable (GS) subtypes. The predictive accuracy of GES_GC also outperformed five previously published signatures. Finally, a well-performed nomogram integrating the GES_GC and four clinicopathological factors was generated to predict 3- and 5-year DFS. In summary, we describe an eight-mRNA-based signature, GES_GC , as a predictive model for disease progression in GC. The robustness of this signature was validated across patient series, populations, and multiplatform datasets.

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer “Big Data” has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of “hit” compounds.

Upregulation of brain-derived neurotrophic factor in advanced gastric cancer contributes to bone metastatic osteolysis by inducing long pentraxin 3

The brain-derived neurotrophic factor (BDNF) activates its receptor, tropomyosin receptor kinase B (TrkB; also called NTRK2) that has been shown to promote the malignant progression of several cancers. In this study, we investigated the clinical and biological significance of the BDNF/TrkB axis in the progression of human gastric cancer. The increased co-expression of the BDNF/TrkB axis was significantly correlated with bone metastatic properties in advanced gastric cancers. BDNF acting via TrkB receptors increased the levels of long pentraxin 3 (PTX3) that was related to bone metastatic status of gastric cancer by enhancing gastric cancer–osteoblastic niche interactions. In bone metastatic gastric cancer, PTX3 knockdown using small interfering RNA significantly inhibited BDNF-induced interactions of cancer cells with osteoblasts. Moreover, BDNF-derived PTX3 induction supported subsequent osteoclastogenesis, and this effect was significantly reversed by PTX3 silencing. These findings suggest that a functional interaction between BDNF/TrkB and PTX3 enhances the osteolysis of bone metastatic gastric cancer, thereby providing potential prognostic factors for the development of bone metastasis of gastric cancer.

Combination of TNM staging and pathway based risk score models in patients with gastric cancer

Due to the complexity and heterogeneity of gastric cancer (GC) in individual patient, current staging system is inadequate for predicting outcome of GC. Comprehensive computational and bioinformatics approach may triumph for the prediction. In this study, GC patients were devided according to stage and treatment: curative surgery plus chemoradiotherapy in stage II, curative surgery plus chemoradiotherapy in stages III, and IV, unresectable metastatic gastric cancer. The training sets were downloaded from GEO datasets (GSE26253 and GSE14208). Gene set enrichment analysis (GSEA) was performed to explore enriched difference between recurrence and nonrecurrence. The core enrichment genes of enriched pathways significantly associated with recurrence or progression were identified using Cox proportional hazards analysis. Thereafter, the risk score models were externally validated in independent datasets-GSE15081 and The Cancer Genome Atlas (TCGA). We generated respective risk score models of patients in different stages and treatment. A five-gene signature comprising FARP1, SGCE, SGCA, LAMA4, and COL9A2 was strongly associated with recurrence of patients with curative surgery plus chemoradiotherapy in stage II. A six-gene signature consisting of SHH, NF1, AP4B1, COMP, MATN3, and CCL8 was correlated with recurrence of patients with curative surgery plus chemoradiotherapy in stages III and IV. And a four-gene signature composing of ABCC2, AHNAK2, RNF43, and GSPT2 was highly related to progression of patients with unresectable metastatic GC. Taking into consideration TNM stage and gene signature reflecting recurrence or progression, the risk score models significantly improved the accuracy in predicting outcome of GC.

Peritoneal recurrence in gastric cancer following curative resection can be predicted by postoperative but not preoperative biomarkers: a single-institution study of 320 cases

To determine the risk factors for peritoneal recurrence in gastric cancer patients after curative resection, we included 320 patients with stage I-III primary gastric cancer between January 2008 and June 2012. Data on each patient's surgical and pathological information, preoperative and postoperative tumor markers were collected and analyzed retrospectively. The risk factors for peritoneal recurrence were investigated by univariate and multivariate analysis. In patients with peritoneal recurrence, advanced T or N stage, low differentiation, vascular/lymphatic invasion, perineural invasion, and elevated postoperative CEA/CA19-9 were more common than in patients without peritoneal recurrence. Patients with peritoneal recurrence showed a worse overall survival (OS) compared to those without peritoneal recurrence. In addition, patients with peritoneal recurrence within the first year had a worse OS compared to those with recurrence after 1 year. The univariate and multivariate analyses revealed that elevated number of metastatic lymph nodes and elevated postoperative CEA and CA19-9 were three independent risk factors for peritoneal recurrence in gastric cancer patients. For patients with N3 stage and high postoperative CEA and CA19-9, we found an initial steep slope within approximately 1 year and a subsequent gentle slope in the risk curve. Combined receiver operating characteristic curve analysis using the three independent risk factors for peritoneal recurrence yielded an area under the curve value of 0.73 with 73.7% sensitivity and 64.2% specificity. Therefore, the risk factors may be associated with peritoneal recurrence after curative resection in selected gastric cancer patients.

Prognostic value of a 25-gene assay in patients with gastric cancer after curative resection

This study aimed to develop and validate a practical, reliable assay for prognosis and chemotherapy benefit prediction compared with conventional staging in Gastric cancer (GC). Twenty-three candidate genes with significant correlation between quantitative hybridization and microarray results plus 2 reference genes were selected to form a 25-gene prognostic classifier, which can classify patients into 3 distinct groups of different risk of mortality obtained by analyzing microarray data from 78 frozen tumor specimens. The 25-gene assay was associated with overall survival in both training (P = 0.017) and testing cohort (P = 0.005) (462 formalin-fixed paraffin-embedded samples). The risk prediction in stages I + II is significantly better than that in stages III. Analysis demonstrated that this 25-gene signature is an independent prognostic predictor and show higher prognostic accuracy than conventional TNM staging in early stage patients. Moreover, only high-risk patients in stage I + II were found benefit from adjuvant chemotherapy (P = 0.043), while low-risk patients in stage III were not found benefit from adjuvant chemotherapy. In conclusion, our results suggest that this 25-gene assay can reliably identify patients with different risk for mortality after surgery, especially for stage I + II patients, and might be able to predict patients who benefit from chemotherapy.

TOP2A, GGH, and PECAM1 are associated with hematogenous, lymph node, and peritoneal recurrence in stage II/III gastric cancer patients enrolled in the ACTS-GC study

Background

To identify factors related to relapse sites, we carried out an exploratory biomarker analysis of data from the Adjuvant Chemotherapy Trial of TS-1 for Gastric Cancer study, which is a randomized, controlled trial comparing postoperative adjuvant S-1 therapy with surgery alone in 1,059 patients with stage II/III gastric cancer.

Patients and Methods

Surgical specimens from 829 patients were retrospectively examined, and 63 genes involved in a variety of biological processes were analyzed by quantitative real-time PCR. Gene expression normalized to reference genes was categorized as lower or higher than the median, and association with relapse sites was analyzed based on 5-year relapse-free survival.

Results

Hematogenous, lymph node, and peritoneal recurrence developed in 72, 105, and 138 of the 829 patients, respectively; hazard ratios were 0.79 (95% confidential interval: 0.54–1.16), 0.51 (0.31–0.82), and 0.60 (0.42–0.84), respectively. Expression of platelet/endothelial cell adhesion molecule 1 (PECAM1) and topoisomerase II alpha (TOP2A) was strongly correlated with hematogenous recurrence and peritoneal recurrence, respectively (false discovery rate = 7.7×10⁻⁵ and 0.002, respectively). Gamma-glutamyl hydrolase (GGH) expression was moderately correlated with lymph node recurrence (false discovery rate = 0.34). Relapse-free survival was worse in patients expressing high levels of PECAM1 (hazard ratio = 2.37, 1.65–3.41), TOP2A (hazard ratio = 2.35, 1.55–3.57), or GGH (hazard ratio = 1.87, 1.13–3.08), respectively. A multivariate analysis revealed that these were stronger independent risk factors than tumor histological type.

Conclusion

In patients with stage II/III gastric cancer, TOP2A, GGH, and PECAM1 levels in primary tumors are linked to high risk of hematogenous, lymph node, and peritoneal recurrence, respectively.

Molecular classification of gastric cancer

Gastric cancer (GC), a heterogeneous disease characterized by epidemiologic and histopathologic differences across countries, is a leading cause of cancer-related death. Treatment of GC patients is currently suboptimal due to patients being commonly treated in a uniform fashion irrespective of disease subtype. With the advent of next-generation sequencing and other genomic technologies, GCs are now being investigated in great detail at the molecular level. High-throughput technologies now allow a comprehensive study of genomic and epigenomic alterations associated with GC. Gene mutations, chromosomal aberrations, differential gene expression and epigenetic alterations are some of the genetic/epigenetic influences on GC pathogenesis. In addition, integrative analyses of molecular profiling data have led to the identification of key dysregulated pathways and importantly, the establishment of GC molecular classifiers. Recently, The Cancer Genome Atlas (TCGA) network proposed a four subtype classification scheme for GC based on the underlying tumor molecular biology of each subtype. This landmark study, together with other studies, has expanded our understanding on the characteristics of GC at the molecular level. Such knowledge may improve the medical management of GC in the future.

Seom guidelines for the treatment of gastric cancer 2015

Gastric cancer is the fourth cause of death by cancer in Spain and a significant medical problem. Molecular biology results evidence that gastroesophageal junction tumors and gastric cancer should be considered as two independent entities with a different prognosis and treatment approach. Endoscopic resection in very early tumors is feasible. Neoadjuvant and adjuvant therapy in locally advanced resectable tumor increase overall survival and should be considered standard treatments. In stage IV tumors, platinum–fluoropyrimidine-based schedule, with trastuzumab in HER2-overexpressed tumors, is the first-line treatment. Different therapies in second line have demonstrated in randomized studies their clear benefit in survival improvement.

Pin1 is overexpressed and correlates with poor prognosis in gastric cancer

The prolyl isomerase Pin1, which isomerizes the p-Ser/Thr-Pro peptide bonds and effects conformational and functional changes of the bound proteins, has been identified as a regulator of phosphorylation signaling in several diseases including cancer. The aim of this study is to determine the expression status of Pin1 in gastric cancer, its relationship between clinicopathologic features and patients' outcome. The mRNA levels of Pin1 in human normal and gastric cancer tissues were analyzed using the datasets from the publicly available Oncomine database ( www.oncomine.org ). Pin1 protein levels in human gastric cancer cells and tissues were analyzed by Western blot and immunohistochemistry staining, respectively. The Pin1 protein expression levels and its clinicopathologic correlations were investigated using tumor tissue microarray including 182 cases of human gastric cancer samples with survival information. Pin1 mRNA expression was found to be overexpressed in gastric cancer by using several datasets of Oncomine database analyzing. Pin1 protein expression is higher in 10 gastric cancer cell lines than that in normal gastric epithelial cell line GES-1. Pin1 positive expression was observed in 109 of 182 (59.9 %) gastric cancer samples and in 55 of 182 (30.2 %) normal gastric tissues (P < 0.001). Correlation analysis showed that high expression of Pin1 was significantly associated with pT (P = 0.017), pN (P = 0.043), TNM staging (P = 0.027), Lauren's classification (P < 0.001), as well as shorter overall survival in gastric cancer patients (29 mos vs. 47 mos. P = 0.048). Moreover, Pin1 expression, pT, and differentiation were independent prognostic factors of gastric cancer in Cox regression analysis. Pin1 is overexpressed in gastric cancer and correlates with clinicopathologic features, which might predict poor prognosis of gastric cancer patients.

Molecular classification and prediction in gastric cancer

Gastric cancer, a highly heterogeneous disease, is the second leading cause of cancer death and the fourth most common cancer globally, with East Asia accounting for more than half of cases annually. Alongside TNM staging, gastric cancer clinic has two well-recognized classification systems, the Lauren classification that subdivides gastric adenocarcinoma into intestinal and diffuse types and the alternative World Health Organization system that divides gastric cancer into papillary, tubular, mucinous (colloid), and poorly cohesive carcinomas. Both classification systems enable a better understanding of the histogenesis and the biology of gastric cancer yet have a limited clinical utility in guiding patient therapy due to the molecular heterogeneity of gastric cancer. Unprecedented whole-genome-scale data have been catalyzing and advancing the molecular subtyping approach. Here we cataloged and compared those published gene expression profiling signatures in gastric cancer. We summarized recent integrated genomic characterization of gastric cancer based on additional data of somatic mutation, chromosomal instability, EBV virus infection, and DNA methylation. We identified the consensus patterns across these signatures and identified the underlying molecular pathways and biological functions. The identification of molecular subtyping of gastric adenocarcinoma and the development of integrated genomics approaches for clinical applications such as prediction of clinical intervening emerge as an essential phase toward personalized medicine in treating gastric cancer.

Immunohistochemistry - microarray analysis of patients with peritoneal metastases of appendiceal or colorectal origin

BACKGROUND

The value of immunohistochemistry (IHC)-microarray analysis of pathological specimens in the management of patients is controversial, although preliminary data suggest potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM) and the feasibility of this technique in this population.

METHODS

We retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular Intelligence(™) testing. IHC, microarray, FISH, and mutational analysis were included and stratified by Peritoneal Carcinomatosis Index (PCI) score, histology, and treatment characteristics. Statistical analysis was performed using non-parametric tests.

RESULTS

Our study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65) years, with 11 (68%) female. The median PCI score of the patients was 17 (IQR 10-25). Hyperthermic intra-peritoneal chemoperfusion was performed in 4 (80%) patients with appendiceal primary tumors and 4 (36%) with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p = 0.06). IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n = 7) patients, which was not associated with previous use of chemotherapy (p > 0.20 for 5-FU/LV, Irinotecan and Oxaliplatin).

CONCLUSION

In a small sample of patients with PM, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.

Small GTPase RBJ mediates nuclear entrapment of MEK1/MEK2 in tumor progression

Ras-related small GTPases play important roles in cancer. However, the roles of RBJ, a representative of the sixth subfamily of Ras-related small GTPases, in tumorigenesis and tumor progression remain unknown. Here, we report that RBJ is dysregulated in human gastrointestinal cancers and can promote carcinogenesis and tumor progression via nuclear entrapment of mitogen-activated protein/extracellular signal-regulated kinase (ERK) kinase (MEK)1/MEK2 and activation of ERK1/ERK2. Nucleus-localized RBJ interacts with MEK/ERK and prolongs the duration of MEK/ERK activation. Rbj deficiency abrogates nuclear accumulation of MEK1/MEK2, attenuates ERK1/ERK2 activation, and impairs AOM/DSS-induced colonic carcinogenesis. Moreover, Rbj knockdown inhibits growth of established tumors. Our data suggest that RBJ may be an oncogenic Ras-related small GTPase mediating nuclear accumulation of active MEK1/MEK2 in tumor progression.

PATHOME: an algorithm for accurately detecting differentially expressed subpathways

The translation of high-throughput gene expression data into biologically meaningful information remains a bottleneck. We developed a novel computational algorithm, PATHOME, for detecting differentially expressed biological pathways. This algorithm employs straightforward statistical tests to evaluate the significance of differential expression patterns along subpathways. Applying it to gene expression data sets of gastric cancer (GC), we compared its performance with those of other leading programs. Based on a literature-driven reference set, PATHOME showed greater consistency in identifying known cancer-related pathways. For the WNT pathway uniquely identified by PATHOME, we validated its involvement in gastric carcinogenesis through experimental perturbation of both cell lines and animal models. We identified HNF4α-WNT5A regulation in the cross-talk between the AMPK metabolic pathway and the WNT signaling pathway, and further identified WNT5A as a potential therapeutic target for GC. We have demonstrated PATHOME to be a powerful tool, with improved sensitivity for identifying disease-related dysregulated pathways.

Up-regulation of CLDN1 in gastric cancer is correlated with reduced survival

Background

The genetic changes in gastric adenocarcinoma are extremely complex and reliable tumor markers have not yet been identified. There are also remarkable geographical differences in the distribution of this disease. Our aim was to identify the most differentially regulated genes in 20 gastric adenocarcinomas from a Norwegian selection, compared to matched normal mucosa, and we have related our findings to prognosis, survival and chronic Helicobacter pylori infection.

Methods

Biopsies from gastric adenocarcinomas and adjacent normal gastric mucosa were obtained from 20 patients immediately following surgical resection of the tumor. Whole genome, cDNA microarray analysis was performed on the RNA isolated from the sample pairs to compare the gene expression profiles between the tumor against matched mucosa. The samples were microscopically examined to classify gastritis. The presence of H. pylori was examined using microscopy and immunohistochemistry.

Results

130 genes showed differential regulation above a predefined cut-off level. Interleukin-8 (IL-8) and Claudin-1 (CLDN1) were the most consistently up-regulated genes in the tumors. Very high CLDN1 expression in the tumor was identified as an independent and significant predictor gene of reduced post-operative survival. There were distinctly different expression profiles between the tumor group and the control mucosa group, and the histological subsets of mixed type, diffuse type and intestinal type cancer demonstrated further sub-clustering. Up-regulated genes were mapped to cell-adhesion, collagen-related processes and angiogenesis, whereas normal intestinal functions such as digestion and excretion were associated with down-regulated genes. We relate the current findings to our previous study on the gene response of gastric epithelial cells to H. pylori infection.

Conclusions

CLDN1 was highly up-regulated in gastric cancer, and CLDN1 expression was independently associated with a poor post-operative prognosis, and may have important prognostic value. IL-8 and CLDN1 may represent central links between the gene response seen in acute H. pylori infection of gastric epithelial cells, and ultimately gastric cancer.

Gastric cancer-molecular and clinical dimensions

Gastric cancer imposes a considerable health burden around the globe despite its declining incidence. The disease is often diagnosed in advanced stages and is associated with a poor prognosis for patients. An in-depth understanding of the molecular underpinnings of gastric cancer has lagged behind many other cancers of similar incidence and morbidity, owing to our limited knowledge of germline susceptibility traits for risk and somatic drivers of progression (to identify novel therapeutic targets). A few germline (PLCE1) and somatic (ERBB2, ERBB3, PTEN, PI3K/AKT/mTOR, FGF, TP53, CDH1 and MET) alterations are emerging and some are being pursued clinically. Novel somatic gene targets (ARID1A, FAT4, MLL and KMT2C) have also been identified and are of interest. Variations in the therapeutic approaches dependent on geographical region are evident for localized gastric cancer-differences that are driven by preferences for the adjuvant strategies and the extent of surgery coupled with philosophical divides. However, greater uniformity in approach has been noted in the metastatic cancer setting, an incurable condition. Having realized only modest successes, momentum is building for carrying out more phase III comparative trials, with some using biomarker-based patient selection strategies. Overall, rapid progress in biotechnology is improving our molecular understanding and can help with new drug discovery. The future prospects are excellent for defining biomarker-based subsets of patients and application of specific therapeutics. However, many challenges remain to be tackled. Here, we review representative molecular and clinical dimensions of gastric cancer.

Gastric cancer-molecular and clinical dimensions

Gastric cancer imposes a considerable health burden around the globe despite its declining incidence. The disease is often diagnosed in advanced stages and is associated with a poor prognosis for patients. An in-depth understanding of the molecular underpinnings of gastric cancer has lagged behind many other cancers of similar incidence and morbidity, owing to our limited knowledge of germline susceptibility traits for risk and somatic drivers of progression (to identify novel therapeutic targets). A few germline (PLCE1) and somatic (ERBB2, ERBB3, PTEN, PI3K/AKT/mTOR, FGF, TP53, CDH1 and MET) alterations are emerging and some are being pursued clinically. Novel somatic gene targets (ARID1A, FAT4, MLL and KMT2C) have also been identified and are of interest. Variations in the therapeutic approaches dependent on geographical region are evident for localized gastric cancer-differences that are driven by preferences for the adjuvant strategies and the extent of surgery coupled with philosophical divides. However, greater uniformity in approach has been noted in the metastatic cancer setting, an incurable condition. Having realized only modest successes, momentum is building for carrying out more phase III comparative trials, with some using biomarker-based patient selection strategies. Overall, rapid progress in biotechnology is improving our molecular understanding and can help with new drug discovery. The future prospects are excellent for defining biomarker-based subsets of patients and application of specific therapeutics. However, many challenges remain to be tackled. Here, we review representative molecular and clinical dimensions of gastric cancer.

Failure patterns in resected pancreas adenocarcinoma: lack of predicted benefit to SMAD4 expression

OBJECTIVE

To determine whether SMAD4 expression is associated with recurrence pattern after resection for pancreatic ductal adenocarcinoma (PDA).

BACKGROUND

SMAD4 expression status has been reported to be associated with patterns of failure in PDA, but studies have not examined recurrence patterns after resection.

METHODS

A tissue microarray was constructed including 127 patients with resected PDA and either short-term (<12 months) or long-term (>30 months) survival. SMAD4 expression was evaluated by immunohistochemistry and categorized as present or lost in tumor cells. Conventional pathologic features (lymph node metastases, positive resection margin, poor grade, and tumor size) were recorded, and disease-specific outcomes (eg, recurrence pattern and early cancer-specific mortality) were determined.

RESULTS

Loss of SMAD4 expression in pancreatic adenocarcinoma was identified in 40 of 127 patients (32%). SMAD4 loss occurred in 27% of patients who experienced isolated local recurrence, 33% of patients with a distant recurrence, 33% of patients who experienced local and distant site recurrences, and 25% of patients who were without evidence of recurrence (Fisher exact, P = 0.9). In a multivariate analysis, the presence of regional lymph node metastases was the only factor associated with the development of distant metastases (odds ratio = 4.7, P = 0.02). SMAD4 was neither associated with recurrence pattern (odds ratio = 0.9, P = 0.9) nor associated with early death (odds ratio = 0.5, P = 0.15).

CONCLUSIONS

Primary tumor SMAD4 expression status was not a predictor of recurrence pattern in a large cohort of patients with resected PDA.

High levels of secreted frizzled-related protein 1 correlate with poor prognosis and promote tumourigenesis in gastric cancer

BACKGROUND

Secreted frizzled-related protein 1 (sFRP1), Wnt signalling regulator, can positively or negatively regulate tumourigenesis and progression. We sought to determine the clinical relevance and the role of sFRP1 in gastric cancer development and progression.

METHODS

We investigated the sFRP1 protein expression levels and its clinicopathological correlations using 85 cases of human gastric samples with survival information (JWCI cohort). mRNA levels of sFRP1 and coexpressed genes were analysed using 131-sample cDNA microarray data (Ruijin cohort). The effects of sFRP1 alteration were investigated using cell proliferation, colony formation, migration, and invasion and xenograft models.

RESULTS

We show that sFRP1 is overexpressed in some human cancers and is significantly associated with lymph node metastasis and decreased overall survival in gastric cancer patients. Using gastric cancer cell models, we demonstrate that sFRP1 overexpression is correlated with the activation of TGFβ (transforming growth factor-beta) signalling pathway and thereby induces cell proliferation, epithelial-mesenchymal transition (EMT), and invasion. Conversely, sFRP1 knockdown shows the opposite effects. Furthermore, sFRP1 overexpression promotes tumourigenesis and metastasis in a xenograft model.

CONCLUSION

Our studies demonstrate that sFRP1 is a biomarker for aggressive subgroups of human gastric cancer and a prognostic biomarker for patients with poor survival. Our data provide insight into a crosstalk between Wnt and TGFβ pathways which underlies gastric cancer development and progression.

Surgical second-look in high risk gastrointestinal stromal tumor of small intestine: A case report

INTRODUCTION

The peritoneum is one of the most common sites of distant gastrointestinal stromal tumor (GIST) metastases. In particular, GIST arising from the small intestine with resected minimal synchronous macroscopic peritoneal carcinomatosis or with primary tumor rupture has a higher risk of developing peritoneal recurrence. Current clinical practice does not envisage second-look surgery in GIST patients at high risk of developing peritoneal recurrence, and no literature data are available.

PRESENTATION OF CASE

We describe a 45-year-old woman who underwent emergency surgical resection of jejunal GIST presenting with spontaneous tumor rupture, synchronous ovarian and minimal macroscopic peritoneal involvement, and subsequent second-look surgery after 13 months of imatinib treatment.

DISCUSSION

Second-look surgery confirmed a 2.6cm lesion close to the mesenteric border of the fourth jejunal loop, and 11 peritoneal lesions with a macroscopic necrotic aspect related to treatment response. After conversion to an open procedure, a segmental jejunal resection was performed with removal of all peritoneal lesions and macroscopic radical cytoreduction.

CONCLUSION

Second-look surgery in selected GIST patients may be performed after at least 12 months of medical treatment with tyrosine-kinase inhibitors to identify those patients with limited peritoneal disease not disclosed by instrumental imaging who could undergo radical cytoreduction of peritoneal lesions.

Identification of differentially expressed genes in gastric cancer by high density cDNA microarray

The identification of molecular markers for diagnosis, treatment, and prognosis is a significant issue in the management of patients with gastric cancer. We compared the expression profiles of 23 gastric cancers and 22 normal gastric tissues using cDNA microarrays. We divided the samples into two sets, 11 pairs as a training set and 12 unpaired gastric cancer and 11 unpaired normal gastric tissues as a test set. We selected significant genes in the training set and validated the significance of the genes in the test set. We obtained 238 classifier genes that showed a maximum cross-validation probability and clear hierarchical clustering pattern in the training set, and showed excellent class prediction probability in the independent test set. The classifier genes consisted of known genes related to the biological features of cancer and 28% unknown genes. We obtained genome-wide molecular signatures of gastric cancer, which provides preliminary exploration data for the pathophysiology of gastric cancer.

Discovery and validation of prognostic markers in gastric cancer by genome-wide expression profiling

AIM: To develop a prognostic gene set that can predict patient overall survival status based on the whole genome expression analysis.

METHODS: Using Illumina HumanWG-6 BeadChip followed by semi-supervised analysis, we analyzed the expression of 47 296 transcripts in two batches of gastric cancer patients who underwent surgical resection. Thirty-nine samples in the first batch were used as the training set to discover candidate markers correlated to overall survival, and thirty-three samples in the second batch were used for validation.

RESULTS: A panel of ten genes were identified as prognostic marker in the first batch samples and classified patients into a low- and a high-risk group with significantly different survival times (P = 0.000047). This prognostic marker was then verified in an independent validation sample batch (P = 0.0009). By comparing with the traditional Tumor-node-metastasis (TNM) staging system, this ten-gene prognostic marker showed consistent prognosis results. It was the only independent prognostic value by multivariate Cox regression analysis (P = 0.007). Interestingly, six of these ten genes are ribosomal proteins, suggesting a possible association between the deregulation of ribosome related gene expression and the poor prognosis.

CONCLUSION: A ten-gene marker correlated with overall prognosis, including 6 ribosomal proteins, was identified and verified, which may complement the predictive value of TNM staging system.

Gene-expression signatures can distinguish gastric cancer grades and stages

Microarray gene-expression data of 54 paired gastric cancer and adjacent noncancerous gastric tissues were analyzed, with the aim to establish gene signatures for cancer grades (well-, moderately-, poorly- or un-differentiated) and stages (I, II, III and IV), which have been determined by pathologists. Our statistical analysis led to the identification of a number of gene combinations whose expression patterns serve well as signatures of different grades and different stages of gastric cancer. A 19-gene signature was found to have discerning power between high- and low-grade gastric cancers in general, with overall classification accuracy at 79.6%. An expanded 198-gene panel allows the stratification of cancers into four grades and control, giving rise to an overall classification agreement of 74.2% between each grade designated by the pathologists and our prediction. Two signatures for cancer staging, consisting of 10 genes and 9 genes, respectively, provide high classification accuracies at 90.0% and 84.0%, among early-, advanced-stage cancer and control. Functional and pathway analyses on these signature genes reveal the significant relevance of the derived signatures to cancer grades and progression. To the best of our knowledge, this represents the first study on identification of genes whose expression patterns can serve as markers for cancer grades and stages.