Classification Of Gastric Cancer Research Articles

Expression of nicotinamide-N-methyltransferase in gastric cancer and its biological and clinicopathological significance

To investigate the expression of nicotinamide-N-methyltransferase (NNMT) in gastric cancer (GC) and explore its biological and clinicopathological significance. We screened the candidate genes associated with the classification and prognosis of gastric cancer by analyzing GEO, Oncomine and TCGA datasets. The molecular pathways and protein interaction network involving these candidate genes were analyzed using STRING, GSEA, David and Cytoscape software. The expressions of the candidate genes in 28 pairs of gastric cancer and adjacent tissues were detected with qRTPCR, and CCK-8 assay, clone formation assay, wound healing assay and Transwell assay were carried out to analyze the effects of modulation of NNMT expression on proliferation, invasion and migration of different gastric cancer cell lines. NNMT was highly expressed in gastric cancer tissues and was negatively correlated with the prognosis of patients with gastric cancer. Pathway analysis showed that the high expression of NNMT was associated with adhesion-related pathway molecules such as extracellular matrix receptors, cell adhesion molecules, and cytokine receptors, while its low expression was associated with base mismatch repair and riboflavin metabolism. Protein interaction analysis showed that NNMT interacted with 16 differentially expressed proteins such as AURKA and was co-expressed with TAGLN, PTRF, AKAP12 and IGF2BP2. In clinical tissue specimens, qRT-PCR results showed that the expression of NNMT mRNA was significantly higher in gastric cancer tissues than in the adjacent tissues (P < 0.05). In gastric cancer cell lines, overexpression of NNMT was found to significantly promote cell proliferation, invasion and migration, while NNMT knockdown produced obvious inhibitory effects on cell proliferation, invasion and migration. NNMT is highly expressed in gastric cancer and negatively correlated with the prognosis of gastric cancer patients. The high expression of NNMT promotes the proliferation, invasion and metastasis of gastric cancer cells, suggesting the potential of NNMT as prognostic marker of gastric cancer.

A Signature-Based Classification of Gastric Cancer That Stratifies Tumor Immunity and Predicts Responses to PD-1 Inhibitors.

Gastric cancer is a leading cause of cancer-related deaths with considerable heterogeneity among patients. Appropriate classifications are essential for prognosis prediction and individualized treatment. Although immunotherapy showed potential efficacy in a portion of patients with gastric cancer, few studies have tried to classify gastric cancer specifically based on immune signatures. In this study, we established a 3-subtype cluster with low (CLIM), medium (CMIM), and high (CHIM) enrichment of immune signatures based on immunogenomic profiling. We validated the classification in multiple independent datasets. The CHIM subtype exhibited a relatively better prognosis and showed features of “hot tumors”, including low tumor purity, high stromal components, overexpression of immune checkpoint molecules, and enriched tumor-infiltrated immune cells (activated T cells and macrophages). In addition, CHIM tumors were also characterized by frequent ARID1A mutation, rare TP53 mutation, hypermethylation status, and altered protein expression (HER2, β-catenin, Cyclin E1, PREX1, LCK, PD-L1, Transglutaminase, and cleaved Caspase 7). By Gene Set Variation Analysis, “TGFβ signaling pathway” and “GAP junction” were enriched in CLIM tumors and inversely correlated with CD8+ and CD4+ T cell infiltration. Of note, the CHIM patients showed a higher response rate to immunotherapy (44.4% vs. 11.1% and 16.7%) and a more prolonged progression-free survival (4.83 vs. 1.86 and 2.75 months) than CMIM and CLIM patients in a microsatellite-independent manner. In conclusion, the new immune signature-based subtypes have potential therapeutic and prognostic implications for gastric cancer management, especially immunotherapy.

Identification of gastric cancer subtypes based on pathway clustering

Gastric cancer (GC) is highly heterogeneous in the stromal and immune microenvironment, genome instability (GI), and oncogenic signatures. However, a classification of GC by combining these features remains lacking. Using the consensus clustering algorithm, we clustered GCs based on the activities of 15 pathways associated with immune, DNA repair, oncogenic, and stromal signatures in three GC datasets. We identified three GC subtypes: immunity-deprived (ImD), stroma-enriched (StE), and immunity-enriched (ImE). ImD showed low immune infiltration, high DNA damage repair activity, high tumor aneuploidy level, high intratumor heterogeneity (ITH), and frequent TP53 mutations. StE displayed high stromal signatures, low DNA damage repair activity, genomic stability, low ITH, and poor prognosis. ImE had strong immune infiltration, high DNA damage repair activity, high tumor mutation burden, prevalence of microsatellite instability, frequent ARID1A mutations, elevated PD-L1 expression, and favorable prognosis. Based on the expression levels of four genes (TAP2, SERPINB5, LTBP1, and LAMC1) in immune, DNA repair, oncogenic, and stromal pathways, we developed a prognostic model (IDOScore). The IDOScore was an adverse prognostic factor and correlated inversely with immunotherapy response in cancer. Our identification of new GC subtypes provides novel insights into tumor biology and has potential clinical implications for the management of GCs.

SURGICAL AND PROGNOSTIC IMPLICATIONS IN GASTRIC ADENOCARCINOMA BY THE INTEGRATION OF PROTEOMIC MOLECULAR ANALYSIS

Abstract INTRODUCTION Despite a steady decline in the incidence of gastric cancer (GC) over recent decades, the prognosis remains poor with 5-year survival rates of 21.9% in Europe. The AJCC Cancer Staging Manual (8th Edition) establishes the necessity to evaluate personalized survival models. These models would help in the decision-making process. Proteomic and genomic molecular analyses have provided a more in-depth knowledge of GC. MATERIAL AND METHODS 19 patients affected by 21 tumors operated between 2012-2014 were prospectively included. Healthy tissue and tumor samples were taken from each case and deposited in a tissue biobank for subsequent proteomic analysis by Proteomics Department. RESULTS The following histopathological types were identified: (73.69%) intestinal, (10.52%) diffuse, and (15.78%) undetermined, poorly differentiated, and mixed neuroendocrine of the classification WHO. According to the size and extent of tumor invasion, the percentages of the sample were T1 or T2 (26.31%) and T3 or T4 (73.68%). Furthermore, 57.89% of the patients were found to have lymph-node metastases (N 1, 2, 3 +). After the differences in protein intensities in healthy tissue and tumor tissue were analyzed, it was found that in the healthy tissue, EGFR1, MAPK1 and MAPK3 were predictive variables of overall survival when the tumor stage was T3 or T4 CONCLUSIONS It would be convenient to redefine the classification and treatment plan in gastric cancer by integrating the study at a molecular level.

Eight-gene prognostic signature associated with hypoxia and ferroptosis for gastric cancer with general applicability.

Aims: To investigate the prognostic significance of hypoxia- and ferroptosis-related genes for gastric cancer (GC). Materials & methods: We extracted data on 259 hypoxia- and ferroptosis-related genes from The Cancer Genome Atlas and identified the differentially expressed genes between normal (n=32) and tumor (n=375) tissues. A risk score was established by univariate Cox regression analysis and LASSO penalized Cox regression analysis. Results: The risk score contained eight genes showed good performance in predicting overall survival and relapse-free survival in GC patients in both the training cohort (The Cancer Genome Atlas, n=350) and the testing cohorts (GSE84437, n=431; GSE62254, n=300; GSE15459, n=191; GSE26253, n=432). Conclusion: The eight-gene signature may help to the improve the prognostic risk classification of GC.

Histopathological Analysis of Gastric Cancers in University of Ilorin Teaching Hospital: A 20-Year Review

Gastric cancer is a relatively common malignancy in Nigeria. Gastric cancer varies from region, being 4th to 20th in proportion to other malignancies. The symptom and signs are often non-specific with the early stages of the disease. This may be responsible for late presentation and poor prognosis. This is a 20-year retrospective analysis of 107 histopathologically confirmed gastric cancers in the department of pathology. This study aimed to analyze the Histopathological patterns of all the gastric cancer cases diagnosed in U.I.T.H Ilorin, over a twenty-year period. Gastric cancers were classified according to WHO 2010 and Lauren classification of gastric cancers. A total of 107 cases of gastric cancers diagnosed, that met the inclusion criteria, were analyzed with male: female ratio of 1.3:1 out of which epithelial malignancy accounted for 93.5% with tubular adenocarcinoma representing the commonest epithelial subtype. Epithelial malignancy is the commonest histological type in this area. Therefore, it is recommended that patients above 40 years with dyspepsia and other alarm features should undergo routine endoscopic screening.

Topography and Morphology of Gastric Cancer in Nigeria: A Dual Institution Review of 622 Upper Gastrointestinal Endoscopies.

IntroductionGastric cancer is a leading cause of cancer mortality worldwide. The burden of this disease is highest in developing countries of East Asia, Eastern Europe, and parts of Central and Southern America. Africa, despite having a similar high profile of Helicobacter pylori infection with East Asia, has a reported low prevalence of gastric cancer. There is a paucity of data on the natural history and endoscopic presentation of gastric cancer in West Africa.AimTo study the topography and morphology of gastric cancer from two institutions in Southern Nigeria.MethodsA cross-sectional retrospective study of 622 consecutive cases of upper gastrointestinal (GI) endoscopy performed in two referral endoscopy facilities in Port Harcourt, Rivers State, Nigeria from February 2012 to January 2021. Variables collated from centre records included age, sex, ethnicity, symptoms, site, endoscopic classification, and histology of gastric cancers. Statistical analysis was performed using IBM SPSS version 20 (IBM Corp., Armonk, NY).ResultsThere were 17 (2.7%) cases of histologically confirmed gastric cancer. The age range of patients was from 34 years to 99 years (mean 60.7 ± 14.6 years). There were nine males and eight females (M:F ratio of 1.1:1). Antrum and cardia were predominantly affected in 10 (60.0%) and seven (6.7%) cases, respectively. Borrmann type 1 advanced gastric tumor was seen in seven (53.8%) and adenocarcinoma, the predominant histology, in 14 (82.4%) cases. Helicobacter pylori was detected in a sole case of gastric cancer.ConclusionGastric cancer is uncommon in our environment and with a delayed presentation. A predominance of gastric antrum topography and exophytic growth morphology is the pattern.

Expression profiles of gastric cancer molecular subtypes in remnant tumors.

BACKGROUNDRemnant gastric cancer (RGC) is a carcinoma arising in the stomach remnant after previous gastric resection. It is frequently reported as a tumor with a poor prognosis and distinct biological features from primary gastric cancer (PGC). However, as it is less frequent, its profile regarding the current molecular classifications of gastric cancer has not been evaluated.AIMTo evaluate a cohort of RGC according to molecular subtypes of GC using a panel of immunohistochemistry and in situ hybridization to determine whether the expression profile is different between PGC and RGC.METHODSConsecutive RGC patients who underwent gastrectomy between 2009 and 2019 were assessed using seven GC panels: Epstein-Barr virus in situ hybridization, immunohistochemistry for mismatch repair proteins (MutL homolog 1, MutS homolog 2, MutS homolog 6, and PMS1 homolog 2), p53 protein, and E-cadherin expression. Clinicopathological characteristics and survival of these patients were compared to 284 PGC patients.RESULTSA total of 40 RGC patients were enrolled in this study. Compared to PGC, older age (P < 0.001), male (P < 0.001), lower body mass index (P = 0.010), and lower hemoglobin level (P < 0.001) were associated with RGC patients. No difference was observed regarding Lauren’s type and pathologic Tumor Node Metastasis stage between the groups. Regarding the profiles evaluated, EBV-positive tumors were higher in RGC compared to PGC (P = 0.039). The frequency of microsatellite instability, aberrant p53 immunostaining, and loss of E-cadherin expression were similar between RGC and PGC. Higher rates of simultaneous alterations in two or more profiles were observed in RGC compared to PGC (P < 0.001). According to the molecular classification, the subtypes were defined as EBV in nine (22.5%) cases, microsatellite instability in nine (22.5%) cases, genomically stable in one (2.5%) case, and chromosomal instability in 21 (52.5%) cases. There was no significant difference in survival between molecular subtypes in RGC patients.CONCLUSIONRGC was associated with EBV positivity and higher rates of co-altered expression profiles compared to PGC. According to the molecular classification, there was no significant difference in survival between the subtypes of RGC.

Classifying gastric cancer using FLORA reveals clinically relevant molecular subtypes and highlights LINC01614 as a biomarker for patient prognosis

Molecular-based classifications of gastric cancer (GC) were recently proposed, but few of them robustly predict clinical outcomes. While mutation and expression signature of protein-coding genes were used in previous molecular subtyping methods, the noncoding genome in GC remains largely unexplored. Here, we developed the fast long-noncoding RNA analysis (FLORA) method to study RNA sequencing data of GC cases, and prioritized tumor-specific long-noncoding RNAs (lncRNAs) by integrating clinical and multi-omic data. We uncovered 1235 tumor-specific lncRNAs, based on which three subtypes were identified. The lncRNA-based subtype 3 (L3) represented a subgroup of intestinal GC with worse survival, characterized by prevalent TP53 mutations, chromatin instability, hypomethylation, and over-expression of oncogenic lncRNAs. In contrast, the lncRNA-based subtype 1 (L1) has the best survival outcome, while LINC01614 expression further segregated a subgroup of L1 cases with worse survival and increased chance of developing distal metastasis. We demonstrated that LINC01614 over-expression is an independent prognostic factor in L1 and network-based functional prediction implicated its relevance to cell migration. Over-expression and CRISPR-Cas9-guided knockout experiments further validated the functions of LINC01614 in promoting GC cell growth and migration. Altogether, we proposed a lncRNA-based molecular subtype of GC that robustly predicts patient survival and validated LINC01614 as an oncogenic lncRNA that promotes GC proliferation and migration.

Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network

Deep learning is an emerging tool, which is regularly used for disease diagnosis in the medical field. A new research direction has been developed for the detection of early-stage gastric cancer. The computer-aided diagnosis (CAD) systems reduce the mortality rate due to their effectiveness. In this study, we proposed a new method for feature extraction using a stacked sparse autoencoder to extract the discriminative features from the unlabeled data of breath samples. A Softmax classifier was then integrated to the proposed method of feature extraction, to classify gastric cancer from the breath samples. Precisely, we identified fifty peaks in each spectrum to distinguish the EGC, AGC, and healthy persons. This CAD system reduces the distance between the input and output by learning the features and preserve the structure of the input data set of breath samples. The features were extracted from the unlabeled data of the breath samples. After the completion of unsupervised training, autoencoders with Softmax classifier were cascaded to develop a deep stacked sparse autoencoder neural network. In last, fine-tuning of the developed neural network was carried out with labeled training data to make the model more reliable and repeatable. The proposed deep stacked sparse autoencoder neural network architecture exhibits excellent results, with an overall accuracy of 98.7% for advanced gastric cancer classification and 97.3% for early gastric cancer detection using breath analysis. Moreover, the developed model produces an excellent result for recall, precision, and f score value, making it suitable for clinical application.

Current treatment and recent progress in gastric cancer.

Gastric cancer is not a top-10 malignancy in the United States but represents one of the most common causes of cancer death worldwide. Biological differences between tumors from Eastern and Western countries add to the complexity of identifying standard-of-care therapy based on international trials. Systemic chemotherapy, radiotherapy, surgery, immunotherapy, and targeted therapy all have proven efficacy in gastric adenocarcinoma; therefore, multidisciplinary treatment is paramount to treatment selection. Triplet chemotherapy for resectable gastric cancer is now accepted and could represent a plateau of standard cytotoxic chemotherapy for localized disease. Classification of gastric cancer based on molecular subtypes is providing an opportunity for personalized therapy. Biomarkers, in particular microsatellite instability (MSI), programmed cell death ligand 1 (PD-L1), human epidermal growth factor receptor 2 (HER2), tumor mutation burden, and Epstein-Barr virus, are increasingly driving systemic therapy approaches and allowing for the identification of populations most likely to benefit from immunotherapy and targeted therapy. Significant research opportunities remain for the less differentiated histologic subtypes of gastric adenocarcinoma and those without markers of immunotherapy activity.

Zinc Finger Protein CTCF Regulates Extracellular Matrix (ECM)-Related Gene Expression Associated With the Wnt Signaling Pathway in Gastric Cancer.

Gastric cancer (GC), a leading cause of cancer-related death, is a heterogeneous disease. We aim to describe clinically relevant molecular classifications of GC that incorporate heterogeneity and provide useful clinical information. We combined different gene expression datasets and filtered a 7-gene signature related to the extracellular matrix (ECM), which also exhibited significant prognostic value in GC patients. Interestingly, putative CCCTC-binding factor (CTCF) regulatory elements were identified within the promoters of these ECM-related genes and were confirmed by chromatin immunoprecipitation sequencing (ChIP-Seq). CTCF binding sites also overlapped with histone activation markers, indicating direct regulation. In addition, CTCF was also correlated with the Wnt signaling pathway. A comparison of human GC cell lines with high or low expression of ECM-related genes revealed different levels of tumor aggressiveness, suggesting the cancer development-promoting functions of ECM-related genes. Furthermore, CTCF regulated COL1A1 and COLA31 expression in vitro. Silencing CTCF or COL1A1/COL1A3 markedly inhibited cell growth and migration in the metastatic GC cell line BGC823. Collectively, this ECM-related 7-gene signature provides a novel insight for survival prediction among GC patients. The zinc finger protein CTCF regulates ECM-related genes, thereby promoting GC cell growth and migration.

The Analysis of Human Epidermal Growth Receptor-2 (HER-2) in Gastric Cancer in a Tertiary Hospital in Sub-Saharan Africa.

In Ghana, gastric cancer contributes significantly to cancer morbidity and mortality. However, the recent usage of HER-2 monoclonal antibody in combination with chemotherapy has greatly improved the overall survival of patients. This study, therefore, aims at evaluating the pattern of HER-2 over expression in gastric carcinomas in Kumasi, Ghana. Demographic data and histological diagnosis were retrieved from the surgical daybook of the Department of Pathology, Komfo Anokye Teaching Hospital, Kumasi. The slides were retrieved and reviewed to confirm the diagnosis, grading and classification of gastric cancer and immunohistochemistry was done with anti-HER-2 antibody to confirm HER-2 over-expression. Results: Of the 99 cases of gastric cancer seen over the 8 years, there were 57 males and 42 females. There were 91 adenocarcinomas, 5 GIST and 3 Non-Hodgkin Lymphoma. The age range of the study population was 8-90 years with a modal age group in the 6th decade. Of the adenocarcinomas, 45 were poorly differentiated, 38 moderately differentiated and 8 well differentiated. The diffuse type was most common with 47 cases followed by intestinal-type with 41cases and mixed type with 3 cases. Three of the 4 patients under the age of 30 years had lymphoma. HER-2 over expression was seen in 14 out of the 47 tested and all were intestinal type. HER -2 over-expression was seen in 30% of patients with gastric carcinoma especially those with intestinal-type.

A phase II study of perioperative capecitabine plus oxaliplatin for clinical SS/SE N1-3 M0 gastric cancer (OGSG1601).

203 Background: D2 gastrectomy followed by adjuvant S-1 is one of the standard therapy for the patients (pts) with stage III gastric cancer (GC) in Japan; however, the outcome is not satisfactory. We examined the efficacy of perioperative capecitabine and oxaliplatin (CapeOx) in pts with clinical SS/SE N1-3 M0 GC. Methods: The eligibility criteria included histopathologically confirmed clinical T3(SS)/T4a(SE) N1-3 M0 GC according to the Japanese Classification of GC (JCGC; 3rd English Edition). Three cycles of neoadjuvant CapeOx (NAC; capecitabine, 2,000 mg/m2 for 14 days; oxaliplatin, 130 mg/m2 on day 1, every 3 weeks) were administered, followed by five cycles of adjuvant CapeOx after D2 gastrectomy. The primary endpoint was the pathological response rate (pRR) according to JCGC ( ≥Grade 1b). Results: Thirty-seven pts were enrolled from April 2016 to May 2017, and fully evaluated for efficacy and toxicity. Thirty-three pts (89.2%) completed the planned three cycles of NAC and underwent gastrectomy, with an R0 resection rate of 78.4% (n = 29) and a pRR of 54.1% (n = 20, p = .058; 90% confidence interval [CI], 39.4–68.2) were demonstrated. The relative dose intensity (RDI) of capecitabine and oxaliplatin were 90.5% and 91.9%, respectively. Among 27 pts who initiated AC, 21 (63.6%) completed the treatment, and the RDI of capecitabine and oxaliplatin were 80.9% and 65.1%, respectively. Grade 3–4 toxicities during NAC included neutropenia (8%), thrombocytopenia (8%), and anorexia (8%) and during AC included neutropenia (37%), diarrhea (4%), and anorexia (4%), but no treatment-related death was reported. The overall survival (OS) rate and relapse free survival (RFS) rate at 3 years was 83.8% (95% CI, 72.7-96.5%) and 73.0% (95% CI, 60.0-88.8%), respectively. Subgroup analyses according to residual tumor after surgery (R status) showed a 3-year OS and RFS rate of 86.2% (95% CI, 74.5-99.7%) and 75.7% (95% CI, 63.0-90.8%) for R0. Conclusions: Perioperative CapeOx showed good feasibility and favorable prognosis with sufficient pathological response, although statistical significance at .058 did not reach the commonly accepted cutoff of .05. The data obtained using this novel approach warrant further investigations. Clinical trial information: 000021641.

Prognostic significance of serum inflammation indexes in different Lauren classification of gastric cancer.

BackgroundInflammatory indexes are considered to be potential prognostic biomarkers for patients with gastric cancer (GC). However, little evidence has defined the prognostic significance of inflammatory indexes for GC with different Lauren classification.MethodsA total of 852 patients with GC were randomly selected consecutively into intestinal type and diffuse/mixed type groups. Group bias was reduced by propensity score matching. The cutoff values of inflammatory indexes were analyzed by receiver operating characteristic curve. The Kaplan–Meier method and log‐rank test were used to analyze the overall survival (OS). The chi‐square test was used to analyze the association between inflammatory indexes and clinical characteristics. The independent risk factor for prognosis in each group was analyzed by univariate and multivariate analyses based on logistic regression. The nomogram models were constructed by R studio.ResultsIntestinal type GC patients (p < 0.05) had a lower percentage of neutrophils in stage I, higher percentage of neutrophils and higher platelet count in stage Ⅲ (p < 0.05). Systemic immune‐inflammation index (SII) (p < 0.001), pTNM stage (p < 0.001), and postoperative chemotherapy (p = 0.002) were independent risk factors for prognosis in the intestinal type group. Platelet–lymphocyte ratio (PLR) (p < 0.001) and pTNM stage (p = 0.001) were independent risk factors for prognosis in the diffuse/mixed type group. The area under the curve of the nomogram model in predicting 5‐year prognosis in the intestinal type group and diffuse/mixed type group were 0.807 and 0.788, respectively.ConclusionSII combined with postoperative chemotherapy and pTNM stage were used to construct a nomogram model to predict the prognosis of intestinal type GC. PLR combined with pTNM stage can be used to construct a nomogram model for diffuse/mixed type GC patients.

A Novel Approach for Increased Convolutional Neural Network Performance in Gastric-Cancer Classification Using Endoscopic Images

Gastric cancer is the third-most-common cause of cancer-related deaths in the world. Fortunately, it can be detected using endoscopy equipment. Computer-aided diagnosis (CADx) systems can help clinicians identify cancer from gastric diseases more accurately. In this paper, we present a CADx system that distinguishes and classifies gastric cancer from pre-cancerous conditions, such as gastric polyps, gastric ulcers, gastritis, and bleeding. The system uses a deep-learning model, Xception, which involves depth-wise separable convolutions, to classify cancer and non-cancers. The proposed method consists of two steps: Google’s AutoAugment for augmentation and the simple linear iterative clustering (SLIC) superpixel and fast and robust fuzzy C-means (FRFCM) algorithm for image segmentation during preprocessing. These approaches produce a feasible method of distinguishing and classifying cancers from other gastric diseases. Based on biopsy-supported ground truth, the performance metrics of the area under the receiver operating characteristic curve (i.e. Az) are measured on the test sets. Based on the classification results, the Az of the proposed classification model is 0.96, which is 0.06 up from 0.90 which is the Az of the original data. Our methods are fully automated without the manual specification of region-of-interests for the test and with a random selection of images for model training. This methodology may play a crucial role in selecting effective treatment options without the need for a surgical biopsy.

Tumor-Infiltrating Neutrophils and Non-Classical Monocytes May Be Potential Therapeutic Targets for HER2negative Gastric Cancer.

Gastric cancer (GC) is the fourth most common cause of cancer-related death globally. The classification of advanced GC (AGC) according to molecular features has recently led to effective personalized cancer therapy for some patients. Specifically, AGC patients whose tumor cells express high levels of human epidermal growth factor receptor 2 (HER2) can now benefit from trastuzumab, a humanized monoclonal Ab that targets HER2. However, patients with HER2negative AGC receive limited clinical benefit from this treatment. To identify potential immune therapeutic targets in HER2negative AGC, we obtained 40 fresh AGC specimens immediately after surgical resections and subjected the CD45+ immune cells in the tumor microenvironment to multi-channel/multi-panel flow cytometry analysis. Here, we report that HER2 negativity associated with reduced overall survival (OS) and greater tumor infiltration with neutrophils and non-classical monocytes. The potential pro-tumoral activities of these cell types were confirmed by the fact that high expression of neutrophil or non-classical monocyte signature genes in the gastrointestinal tumors in The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases associated with worse OS on Kaplan-Meir plots relative to tumors with low expression of these signature genes. Moreover, advanced stage disease in the AGCs of our patients associated with greater tumor frequencies of neutrophils and non-classical monocytes than early stage disease. Thus, our study suggests that these 2 myeloid populations may serve as novel therapeutic targets for HER2negative AGC.

Circ-sirt1 inhibits growth and invasion of gastric cancer by sponging miR-132-3p/miR-212-3p and upregulating sirt1 expression.

circRNAs have been considered as a rising factor in cancers. However, the roles and mechanisms of circ-sirt1 in gastric cancer (GC) remain largely unknown. In this study, we found that the expressions of sirt1 and circ-sirt1 are decreased in tissues or serums of GC patients by real-time quantitative PCR (RT-qPCR). The expressions of miR-132-3p/miR-212-3p showed an opposite tendency in these samples. The co-transfection of miR-132-3p/miR-212-3p mimics counteracted the enhancement of sirt1 expression induced by circ-sirt1. The results of cell colony-formation assay and transwell assays demonstrated that the proliferation, migration, and invasion activities of BGC-823 cells were inhibited by circ-sirt1 overexpression or miR-132-3p/miR-212-3p knockdown, respectively. The xenograft tumor model result indicated that the circ-sirt1 overexpression suppressed the tumor growth of BGC-823 cells. The regulation of miR-132-3p/miR-212-3p between circ-sirt1 and sirt1 was verified in the mice tumor tissues. Thus, circ-sirt1 inhibited tumor growth and invasion probably by sponging miR-132-3p/miR-212-3p and upregulating sirt1 expression in GC. These findings may provide a theoretical basis for the classification of GC and a novel therapeutic target for GC patients.

Gastric Adenocarcinomas and Signet-Ring Cell Carcinoma: Unraveling Gastric Cancer Complexity through Microbiome Analysis-Deepening Heterogeneity for a Personalized Therapy.

Gastric cancer (GC) is the fifth most prevalent cancer worldwide and the third leading cause of global cancer mortality. With the advances of the omic studies, a heterogeneous GC landscape has been revealed, with significant molecular diversity. Given the multifaceted nature of GC, identification of different patient subsets with prognostic and/or predictive outcomes is a key aspect to allow tailoring of specific treatments. Recently, the involvement of the microbiota in gastric carcinogenesis has been described. To deepen this aspect, we compared microbiota composition in signet-ring cell carcinoma (SRCC) and adenocarcinoma (ADC), two distinct GC subtypes. To this purpose, 10 ADC and 10 SRCC and their paired non-tumor (PNT) counterparts were evaluated for microbiota composition through 16S rRNA analysis. Weighted and unweighted UniFrac and Bray–Curtis dissimilarity showed significant community-level separation between ADC and SRCC. Through the LEfSe (linear discriminant analysis coupled with effect size) tool, we identified potential microbial biomarkers associated with GC subtypes. In particular, SRCCs were significantly enriched in the phyla Fusobacteria, Bacteroidetes, Patescibacteria, whereas in the ADC type, Proteobacteria and Acidobacteria phyla were found. Overall, our data add new insights into GC heterogeneity and may contribute to deepening the GC classification.

Perioperative CRP: A novel inflammation-based classification in gastric cancer for recurrence and chemotherapy benefit.

BackgroundPerioperative C‐reactive protein (CRP) levels have effects on the prognosis of cancer patients. We intended to determine the prognostic value of combining the two for gastric cancer (GC).MethodsData were extracted from a clinical trial. By calculating the area under the curve (AUC) and the C‐index, the predictive value of CRPs among different time points, including preoperative (pre‐CRP), postoperative days 1, 3, and 5 (post‐CRPs), and postoperative maximum CRP (post‐CRPmax), was derived. Multivariate analysis was performed to further explore the independent variates for recurrence‐free survival (RFS).ResultsFinally, 401 patients were available in the present study. For RFS, higher AUC (0.692) and concordance index (0.678) of pre‐CRP were observed when compared with those of post‐CRPs. Further, among post‐CRPs, post‐CRPmax had the highest predictive values (AUC: 0.591; concordance index: 0.585) among the other post‐CRPs. The threshold values in predicting RFS for pre‐CRP and post‐CRPmax were 3.1 mg/L and 77.1 mg/L. Multivariate analysis showed both pre‐CRP≥3.1 mg/L (high‐pre‐CRP) and post‐CRPmax≥77.1 mg/L (high‐post‐CRPmax) were risk factors for RFS. Postoperative chemotherapy benefit was further analyzed for patients with stage II/III GC and indicated that patients with pre‐CRP<3.1 mg/L had better prognosis without benefit from postoperative adjuvant chemotherapy (ACT), p = 0.557. In high‐pre‐CRP patients, only patients with post‐CRPmax≥77.1 mg/L but not post‐CRPmax<77.1 mg/L benefited from postoperative ACT (RFS: 33.2% vs 49.9% for non‐chemotherapy group and chemotherapy group, respectively, p = 0.037). Analyses for overall survival obtained the similar outcomes.ConclusionsBoth high‐pre‐CRP and high‐post‐CRPmax are associated with worse prognosis in GC. ACT seems to only improve the prognosis for stage II/III GC with pre‐CRP≥3.1 mg/L and post‐CRPmax≥77.1 mg/L after radical gastrectomy. Further studies are needed to confirm these findings and explore the potential mechanism.