Gastric cancer and genomics: review of literature

VEGFA locus amplification potentially predicts a favorable prognosis in gastric adenocarcinoma

Gastric adenocarcinoma harbors a range of genetic and epigenetic alterations, including alterations in DNA copy number. However, the key genes that promote the development and progression of gastric adenocarcinoma remain unknown. To identify the key genes amplified in gastric adenocarcinoma, we performed array comparative genomic hybridization on formalin-fixed paraffin-embedded samples of surgically resected gastric adenocarcinoma. We detected a relatively wide genomic region of gain containing the vascular endothelial growth factor A (VEGFA) gene locus on chromosome 6p. VEGFA locus amplification in gastric adenocarcinoma was validated by fluorescence in situ hybridization. To assess the frequency of VEGFA locus amplification in gastric adenocarcinoma, we conducted multiplex ligation-dependent probe amplification (MLPA) assays using homemade probes designed to target the VEGFA gene locus. Eleven of 54 (20 %) gastric adenocarcinomas with MLPA values above 1.3 were defined as having VEGFA locus amplification. Next, we investigated the effect of VEGFA locus amplification on the clinicopathological characteristics of gastric adenocarcinomas and patient survival. VEGFA locus amplification demonstrated a significantly close relationship with pathological intestinal type and lower rates of venous invasion Furthermore, a Kaplan-Meier analysis showed that patients with VEGFA locus amplification had significantly better overall survival than those without amplification (p = 0.038), particularly in the long-term follow-up period. In conclusion, VEGFA locus amplification can predict modest aggressiveness and good outcomes, suggesting the possibility that it may predict a favorable prognosis in patients with gastric adenocarcinoma.

Novel prognostic alternative splicing events in colorectal Cancer: Impact on immune infiltration and therapy response

OBJECTIVE

This study aims to comprehensively analyze alternative splicing (AS) features in colorectal cancer (CRC) using integrative multi-omics and to elucidate their relationship with the CRC immune microenvironment.

METHODS

Transcriptomic data, clinical information, and Percent Spliced In (PSI) values of AS events for CRC patients were obtained from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq databases. Differentially expressed AS events were identified. Univariate Cox analysis was used to pinpoint prognosis-related AS events. A prognostic risk model was developed and validated using multivariate Cox analysis, patient survival analysis, and the area under the receiver operating characteristic (ROC) curve (AUC). Gene Set Enrichment Analysis (GSEA), immune infiltration, immunotherapy, chemotherapy sensitivity analyses, and regulatory relationships between AS events and splicing factors (SFs) were conducted. Single-cell sequencing was used to study the distribution of key factors. siRNA and overexpression vectors were utilized to silence/overexpress BCAS1 in CRC cells and evaluate their effects on cell growth, migration, and invasion. Furthermore, the interaction between BCAS1 and ANO7 pre-mRNA was investigated using RIP-PCR.

RESULTS

82 prognosis-related AS events were identified in CRC patients. A 15-AS prognostic model was constructed, which correlated with immune cell infiltration and showed differences in immunotherapy and chemotherapy sensitivity. BCAS1 was identified as a potential regulator of the ANO7|58341|AT splicing event in CRC. Single-cell sequencing analysis revealed the distribution of BCAS1 and ANO7 in cancer stem cells. In vitro experiments demonstrated that overexpression of BCAS1 and silencing of ANO7 inhibit the proliferation, migration, and invasion of CRC cells. Moreover, BCAS1 suppresses the progression of CRC by modulating ANO7 alternative splicing.

CONCLUSION

This study provides new insights into the role of alternative splicing in colorectal cancer, particularly the potential regulatory action of BCAS1 on the ANO7|58341|AT splicing event. It also identifies the impact of alternative splicing on the tumor microenvironment and potential implications for immunotherapy, highlighting its relevance for the in-depth study and treatment of CRC.

Discovering cancer stem-like molecule, nuclear factor I X, using spatial transcriptome in gastric cancer

Gastric cancer (GC) is characterized by significant intratumoral heterogeneity, and stem cells are promising therapeutic targets. Despite advancements in spatial transcriptome analyses, unexplored targets for addressing cancer stemness remain unknown. This study aimed to identify Nuclear Factor IX (NFIX) as a critical regulator of cancer stemness in GC and evaluate its clinicopathological significance and function. Spatial transcriptome analysis of GC was conducted. The correlation between NFIX expression, clinicopathological factors, and prognosis was assessed using immunostaining in 127 GC cases. Functional analyses of cancer cell lines validated these findings. Spatial transcriptome analysis stratified GC tissues based on genetic profiles, identified CSC-like cells, and further refined the classification to identify and highlight the significance of NFIX, as validated by Monocle 3 and CytoTRACE analyses. Knockdown experiments in cancer cell lines have demonstrated the involvement of NFIX in cancer cell proliferation and kinase activity. This study underscores the role of spatial transcriptome analysis in refining GC tissue classification and identifying therapeutic targets, highlighting NFIX as a pivotal factor. NFIX expression is correlated with poor prognosis and drives GC progression, suggesting its potential as a novel therapeutic target for personalized GC therapies.

Deep-GenMut: Automated genetic mutation classification in oncology: A deep learning comparative study

Early cancer detection and treatment depend on the discovery of specific genes that cause cancer. The classification of genetic mutations was initially done manually. However, this process relies on pathologists and can be a time-consuming task. Therefore, to improve the precision of clinical interpretation, researchers have developed computational algorithms that leverage next-generation sequencing technologies for automated mutation analysis. This paper utilized four deep learning classification models with training collections of biomedical texts. These models comprise bidirectional encoder representations from transformers for Biomedical text mining (BioBERT), a specialized language model implemented for biological contexts. Impressive results in multiple tasks, including text classification, language inference, and question answering, can be obtained by simply adding an extra layer to the BioBERT model. Moreover, bidirectional encoder representations from transformers (BERT), long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) have been leveraged to produce very good results in categorizing genetic mutations based on textual evidence. The dataset used in the work was created by Memorial Sloan Kettering Cancer Center (MSKCC), which contains several mutations. Furthermore, this dataset poses a major classification challenge in the Kaggle research prediction competitions. In carrying out the work, three challenges were identified: enormous text length, biased representation of the data, and repeated data instances. Based on the commonly used evaluation metrics, the experimental results show that the BioBERT model outperforms other models with an F1 score of 0.87 and 0.850 MCC, which can be considered as improved performance compared to similar results in the literature that have an F1 score of 0.70 achieved with the BERT model.

Clinical application of targeted tumour sequencing tests for detecting ERBB2 amplification and optimizing anti-HER2 therapy in gastric cancer

BACKGROUND

Evaluation of human epidermal growth factor receptor 2 (HER2) overexpression caused by erb-b2 receptor tyrosine kinase 2 (ERBB2) amplification (AMP) by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) is essential for treating unresectable metastatic gastric cancer (GC). A targeted tumour sequencing test enables comprehensive assessment of alterations in cancer-related genes, including ERBB2. This study aimed to evaluate the concordance between the targeted tumour sequencing test and IHC/FISH for detecting HER2-positive GC and to clarify the significance of ERBB2 AMP and concomitant genetic alterations in HER2 downstream pathways (DPs) in anti-HER2 therapy for unresectable metastatic GC patients.

METHODS

ERBB2 copy number alteration (CNA) was examined via a targeted tumour sequencing test in 152 formalin-fixed paraffin-embedded (FFPE) GC tissues. ERBB2 CNA was compared to HER2 status evaluated by IHC/FISH in FFPE block sections, which were identical to those subjected to the targeted tumour sequencing test. Treatment outcomes of anti-HER2 therapy in 11 patients with unresectable metastatic GC was evaluated.

RESULTS

ERBB2 AMP (≥ 2.5-fold change) was detected by the targeted tumour sequencing test in 15 patients (9.9%), and HER2 positivity (IHC 3 + or IHC 2+/FISH positive) was detected in 21 patients (13.8%). The overall percent agreement, positive percent agreement, negative percent agreement and Cohen's kappa between ERBB2 CNA and HER2 status were 94.7%, 66.7%, 99.2% and 0.75, respectively. Progression-free survival for trastuzumab therapy in patients with ERBB2 AMP was significantly longer than that in patients with no ERBB2 AMP detected by the targeted tumour sequencing test (median 14 months vs. 4 months, P = 0.007). Treatment response to trastuzumab therapy was reduced in patients with ERBB2 AMP and concomitant CNAs of genes in HER2 DPs. One patient with ERBB2 AMP and concomitant CNAs of genes in HER2 DPs achieved a durable response to trastuzumab deruxtecan as fourth-line therapy.

CONCLUSIONS

A targeted tumour sequencing test is a reliable modality for identifying HER2-positive GC. ERBB2 AMP and concomitant genetic alterations detected through the targeted tumour sequencing test are potential indicators of treatment response to trastuzumab therapy. The targeted tumour sequencing test has emerged as a plausible candidate for companion diagnostics to determine indications for anti-HER2 therapy in the era of precision medicine for GC.

Multi-dimensional cell-free DNA-based liquid biopsy for sensitive early detection of gastric cancer

BACKGROUND

Gastric cancer is the fifth most common cancer type. Most patients are diagnosed at advanced stages with poor prognosis. A non-invasive assay for the detection of early-stage gastric cancer is highly desirable for reducing associated mortality.

METHODS

We collected a prospective study cohort of 110 stage I-II gastric cancer patients and 139 non-cancer individuals. We performed whole-genome sequencing with plasma samples and profiled four types of cell-free DNA (cfDNA) characteristics, fragment size pattern, copy number variation, nucleosome coverage pattern, and single nucleotide substitution. With these differential profiles, we developed an ensemble model to detect gastric cancer signals. Further, we validated the assay in an in-house first validation cohort of 73 gastric cancer patients and 94 non-cancer individuals and an independent second validation cohort of 47 gastric cancer patients and 49 non-cancer individuals. Additionally, we evaluated the assay in a hypothetical 100,000 screening population by Monte Carlo simulation.

RESULTS

Our cfDNA-based assay could distinguish early-stage gastric cancer from non-cancer at an AUROC of 0.962 (95% CI: 0.942-0.982) in the study cohort, 0.972 (95% CI: 0.953-0.992) in the first validation cohort and 0.937 (95% CI: 0.890-0.983) in the second validation cohort. The model reached a specificity of 92.1% (128/139) and a sensitivity of 88.2% (97/110) in the study cohort. In the first validation cohort, 91.5% (86/94) of non-cancer individuals and 91.8% (67/73) of gastric cancer patients were correctly identified. In the second validation cohort, 89.8% (44/49) of non-cancer individuals and 87.2% (41/47) of gastric cancer patients were accurately classified.

CONCLUSIONS

We introduced a liquid biopsy assay using multiple dimensions of cfDNA characteristics that could accurately identify early-stage gastric cancer from non-cancerous conditions. As a cost-effective non-invasive approach, it may provide population-wide benefits for the early detection of gastric cancer.

TRIAL REGISTRATION

This study was registered on ClinicalTrials.gov under the identifier NCT05269056 on March 7, 2022.

Exploring the anti-gastric cancer mechanism of action of Bidentis Bipinnatae Herba based on network pharmacology, molecular docking, and cellular experimental validation

The purpose of this study is to explore the potential molecular mechanism of Bidentis Bipinnatae Herba against gastric cancer by using network pharmacology methods, molecular docking, and cellular experimental validation. Medicinal plants related to gastric cancer were queried through TCMSP, SymMap, and Herb databases. The TCSMP database (drug-likeness ≥ 0.18) was used to retrieve the bioactive constituents. TCSMP, SwissTargetPrediction, and Herb databases were used to retrieve the target genes, and Cytoscape software was used to construct the "active ingredient-target" network. After protein interaction analysis using String 11.0 platform, the hub genes were screened using CytoHubba. The obtained hub genes were uploaded to the cBioPortal for pathway enrichment. The genes involved in gastric cancer-related RTK-RAS pathway were molecularly docked and experimentally validated. Bidentis Bipinnatae Herba was common to TCMSP, SymMap, and Herb databases. A total of nine active ingredients were obtained in Bidentis Bipinnatae Herba, acting on 192 targets. Seven hub genes were obtained from these target genes and enriched in the RTK-RAS pathway in gastric cancer. MAPK1 and EGFR had good molecular docking results with their corresponding chemicals. Cellular experiments showed that the treatment of luteolin, quercetin, and Okanin reduced the expression of EGFR in AGS cells; the treatment of luteolin and quercetin could reduce the expression of MAPK1. Bidentis Bipinnatae Herba contained active components, which may be anti-gastric cancer in a multi-target (MAPK1 and EGFR) manner.

Leveraging the fundamentals of heat transfer and fluid mechanics in microscale geometries for automated next-generation sequencing library preparation

Next-generation sequencing (NGS) is emerging as a powerful tool for molecular diagnostics but remains limited by cumbersome and inefficient sample preparation. We present an innovative automated NGS library preparation system with a simplified mechanical design that exploits both macro- and microfluidic properties for optimizing heat transfer, reaction kinetics, mass transfer, fluid mechanics, adsorption-desorption rates, and molecular thermodynamics. Our approach introduces a unique two-cannula cylindrical capillary system connected to a programmable syringe pump and a Peltier heating element able to execute all steps with high efficiency. Automatic reagent movement, mixing, and magnetic bead-based washing with capillary-based thermal cycling (capillary-PCR) are completely integrated into a single platform. The manual 3-h library preparation process is reduced to less than 15 min of hands-on time via optimally pre-plated reagent plates, followed by less than 6 h of instrument run time during which no user interaction is required. We applied this method to two library preparation assays with different DNA fragmentation requirements (mechanical vs. enzymatic fragmentation), sufficiently limiting consumable use to one cartridge and one 384 well-plate per run. Our platform successfully prepared eight libraries in parallel, generating sequencing data for both human and Escherichia coli DNA libraries with negligible coverage bias compared to positive controls. All sequencing data from our libraries attained Phred (Q) scores > 30, mapping to reference genomes at 99% confidence. The method achieved final library concentrations and size distributions comparable with the conventional manual approach, demonstrating compatibility with downstream sequencing and subsequent data analysis. Our engineering design offers repeatability and consistency in the quality of sequence-able libraries, asserting the importance of mechanical design considerations that employ and optimize fundamental fluid mechanics and heat transfer properties. Furthermore in this work, we provide unique insights into the mechanisms of sample loss within NGS library preparation assays compared with automated adaptations and pinpoint areas in which the principles of thermodynamics, fluid mechanics, and heat transfer can improve future mechanical design iterations.

Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review)

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

TGF-β-driven LIF expression influences neutrophil extracellular traps (NETs) and contributes to peritoneal metastasis in gastric cancer

Gastric cancer (GC), notorious for its poor prognosis, often advances to peritoneal dissemination, a crucial determinant of detrimental outcomes. This study intricately explores the role of the TGFβ-Smad-LIF axis within the tumor microenvironment in propagating peritoneal metastasis, with a specific emphasis on its molecular mechanism in instigating Neutrophil Extracellular Traps (NETs) formation and encouraging GC cellular functions. Through a blend of bioinformatics analyses, utilizing TCGA and GEO databases, and meticulous in vivo and in vitro experiments, LIF was identified as pivotally associated with GC metastasis, notably, enhancing the NETs formation through neutrophil stimulation. Mechanistically, TGF-β was substantiated to elevate LIF expression via the activation of the Smad2/3 complex, culminating in NETs formation and consequently, propelling peritoneal metastasis of GC. This revelation uncovers a novel potential therapeutic target, promising a new avenue in managing GC and mitigating its metastatic propensities.

Determining the Mechanism of Banxia Xiexin Decoction for Gastric Cancer Treatment through Network Analysis and Experimental Validation

Gastric cancer (GC) is a widespread malignancy. Banxia Xiexin decoction (BXD) has been used for GC treatment, but the specific mechanisms underlying its therapeutic effects remain controversial. This study used a comprehensive approach to network pharmacology combined with experimental validation to elucidate the mechanism of BXD's anti-GC effects. Initially, we used the UHPLC-LTQ-Orbitrap-MS/MS technology to identify the main chemical constituents of BXD, as well as potential targets associated with these constituents. Then, we employed the Genecard and Online Mendelian Inheritance in Man (OMIM) to determine the targets specifically related to GC. We employed a combination of Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes pathway, and protein-protein interaction analysis to predict the crucial targets of BXD and uncover the pathways involved in its therapeutic effects against GC. The results were subsequently verified through cell experiments. The analysis revealed 174 common targets shared by BXD and GC. GO enrichment analysis highlighted biological processes, such as autophagy, protein kinase activity, and apoptosis. Moreover, the enrichment analysis revealed several significant pathways that serve as the primary mechanisms by which BXD exerts its effects. Notably, these pathways include PI3K-Akt, HIF-1, and Pathways in cancer. Subsequent in vitro experiments demonstrated that BXD effectively hindered GC cell proliferation, stimulated autophagy, and facilitated apoptosis by PI3K-Akt-mTOR signaling pathway regulation. These findings reveal the effectiveness of BXD against GC through diverse components, targets, and pathways, indicating that BXD holds potential therapeutic value in GC treatment. This study uncovers the intricate biological mechanisms that underlie BXD's efficacy in treating GC through the integration of network pharmacology analysis and rigorous in vitro experiments.

Precision-based tertiary care improves nutritional status and quality of life in patients undergoing adjuvant chemotherapy after radical gastrectomy for gastric cancer

OBJECTIVE

To assess the impact of a precision-based tertiary care protocol, including participatory dietary care, on the nutritional status, immune function, and quality of life in gastric cancer patients after radical gastrectomy.

METHODS

The clinical and laboratory data of 124 patients diagnosed with gastric cancer at the Second People's Hospital of Lanzhou City from June 2020 to May 2022 were collected and retrospectively analyzed. The patients were grouped into a control group of 54 patients who received standard care and a study group of 70 patients who additionally received detailed tertiary care and bundled nutritional interventions. The clinical data (age, gender, surgical method, clinical staging, chemotherapy regimen, histories of diabetes, hypertension, smoking, alcohol consumption, time to first flatus and bowel movement, time to first liquid intake, length of hospital stay, complications at discharge, PG-SGA score, and QLQ-C30 score) and lab indices (serum albumin (ALB), prealbumin (PA), transferrin (TRF), hemoglobin (Hb), immunoglobulin A (IgA), M (IgM), and G (IgG)) were compared between the two groups.

RESULTS

Study group had significantly higher levels of ALB, PA, TRF, Hb, IgA, IgM, and IgG compared to the control group after intervention (all P<0.001). QLQ-C30 score was higher while PG-SGA score was lower in the study group (both P<0.01). Postoperative digestive system recovery was faster in the study group, as evidenced by a shorter time to first anal defecation, bowel movement, liquid food intake, and hospital stay (P<0.001). Complication rate was significantly lower in the study group (P<0.05). Cox regression analysis showed age (P=0.021) and clinical stage (P=0.039) as independent prognostic factors, while treatment regimen was not (P>0.05).

CONCLUSION

Precision-based tertiary care protocol can improve nutritional status, enhance immune function, and facilitate faster postoperative recovery for gastric cancer patients following gastrectomy, thus greatly improving the quality of life of the patient. However, age and clinical staging, rather than the care protocol, are independent prognostic factors for patients' 1-year survival.

Discovery of a novel lipid metabolism-related gene signature to predict outcomes and the tumor immune microenvironment in gastric cancer by integrated analysis of single-cell and bulk RNA sequencing

Gastric cancer (GC) is a pressing global clinical issue, with few treatment options and a poor prognosis. The onset and spread of stomach cancer are significantly influenced by changes in lipid metabolism-related pathways. This study aimed to discover a predictive signature for GC using lipid metabolism-related genes (LMRGs) and examine its correlation with the tumor immune microenvironment (TIME). Transcriptome data and clinical information from patients with GC were collected from the TCGA and GEO databases. Data from GC samples were analyzed using both bulk RNA-seq and single-cell sequencing of RNA (scRNA-seq). To identify survival-related differentially expressed LMRGs (DE-LMRGs), differential expression and prognosis studies were carried out. We built a predictive signature using LASSO regression and tested it on the TCGA and GSE84437 datasets. In addition, the correlation of the prognostic signature with the TIME was comprehensively analyzed. In this study, we identified 258 DE-LMRGs in GC and further screened seven survival-related DE-LMRGs. The results of scRNA-seq identified 688 differentially expressed genes (DEGs) between the three branches. Two critical genes (GPX3 and NNMT) were identified using the above two gene groups. In addition, a predictive risk score that relies on GPX3 and NNMT was developed. Survival studies in both the TCGA and GEO datasets revealed that patients categorized to be at low danger had a significantly greater prognosis than those identified to be at high danger. Additionally, by employing calibration plots based on TCGA data, the study demonstrated the substantial predictive capacity of a prognostic nomogram, which incorporated a risk score along with various clinical factors. Within the high-risk group, there was a noticeable abundance of active natural killer (NK) cells, quiescent monocytes, macrophages, mast cells, and activated CD4 + T cells. In summary, a two-gene signature and a predictive nomogram have been developed, offering accurate prognostic predictions for general survival in GC patients. These findings have the potential to assist healthcare professionals in making informed medical decisions and providing personalized treatment approaches.

Host Transcriptional Regulatory Genes and Microbiome Networks Crosstalk through Immune Receptors Establishing Normal and Tumor Multiomics Metafirm of the Oral-Gut-Lung Axis

The microbiome has shown a correlation with the diet and lifestyle of each population in health and disease, the ability to communicate at the cellular level with the host through innate and adaptative immune receptors, and therefore an important role in modulating inflammatory process related to the establishment and progression of cancer. The oral cavity is one of the most important interaction windows between the human body and the environment, allowing the entry of an important number of microorganisms and their passage across the gastrointestinal tract and lungs. In this review, the contribution of the microbiome network to the establishment of systemic diseases like cancer is analyzed through their synergistic interactions and bidirectional crosstalk in the oral-gut-lung axis as well as its communication with the host cells. Moreover, the impact of the characteristic microbiota of each population in the formation of the multiomics molecular metafirm of the oral-gut-lung axis is also analyzed through state-of-the-art sequencing techniques, which allow a global study of the molecular processes involved of the flow of the microbiota environmental signals through cancer-related cells and its relationship with the establishment of the transcription factor network responsible for the control of regulatory processes involved with tumorigenesis.

Construction and validation of a novel senescence-related risk score can help predict the prognosis and tumor microenvironment of gastric cancer patients and determine that STK40 can affect the ROS accumulation and proliferation ability of gastric cancer cells

Background

In recent years, significant molecules have been found in gastric cancer research. However, their precise roles in the disease's development and progression remain unclear. Given gastric cancer's heterogeneity, prognosis prediction is challenging. This study aims to assess patient prognosis and immune therapy efficacy using multiple key molecules.

Method

The WGCNA algorithm was employed to identify modules of genes closely related to immunity. A prognostic model was established using the Lasso-Cox method to predict patients' prognosis. Single-sample gene set enrichment analysis (ssGSEA) was conducted to quantify the relative abundance of 16 immune cell types and 13 immune functions. The relationship between risk score and TMB, MSI, immune checkpoints, and DNA repair genes was examined to predict the effectiveness of immune therapy. GO and KEGG analyses were performed to explore potential pathways and mechanisms associated with the genes of interest. Single-cell RNA sequencing was utilized to investigate the expression patterns of key genes in different cell types.

Results

Through the WGCNA algorithm and Lasso-Cox algorithm selected KL, SERPINE1, and STK40 as key genes for constructing the prognostic model. The SSGSEA algorithm was employed to evaluate the infiltration of immune cells and immune functions in different patients, and their association with the risk score was investigated. The high-risk group exhibited lower TMB and MSI compared to the low-risk group. MMR and immune checkpoint analysis revealed a significant correlation between the risk score and multiple molecules. Finally, we also believe that STK40 is the most critical senescence-related gene affecting the progression of gastric cancer. In vitro experiments showed that ROS accumulation and cell proliferation ability of gastric cancer cells were impaired when STK40 was knocked down.

Conclusion

In summary, we've constructed a prognostic model utilizing key genes for gastric cancer prognosis, while also showcasing its efficacy in predicting patient response to immunotherapy.

The epigenetic modifier lysine methyltransferase 2C is frequently mutated in gastric remnant carcinoma

Gastric remnant carcinoma (GRC), which occurs in the stomach after partial gastrectomy, is a rare and aggressive form of gastric adenocarcinoma (GAC). Comprehensive profiling of genomic mutations in GRC could provide the basis for elucidating the origin and characteristics of this cancer. Herein, whole-exome sequencing (WES) was performed on 36 matched tumor-normal samples from patients with GRC and identified recurrent mutations in epigenetic modifiers, notably KMT2C, ARID1A, NSD1, and KMT2D, in 61.11% of cases. Mutational signature analysis revealed a low frequency of microsatellite instability (MSI) in GRC, which was further identified by MSIsensor, MSI-polymerase chain reaction, and immunohistochemistry analysis. Comparative analysis demonstrated that GRC had a distinct mutation spectrum compared to that of GAC in The Cancer Genome Atlas samples, with a significantly higher mutation rate of KMT2C. Targeted deep sequencing (Target-seq) of an additional 25 paired tumor-normal samples verified the high mutation frequency (48%) of KMT2C in GRC. KMT2C mutations correlated with poor overall survival in both WES and Target-seq cohorts and were independent prognosticators in GRC. In addition, KMT2C mutations were positively correlated with favorable outcomes in immune checkpoint inhibitor-treated pan-cancer patients and associated with higher intratumoral CD3+ , CD8+ tumor-infiltrating lymphocyte counts, and PD-L1 expression in GRC samples (p = 0.018, 0.092, 0.047, 0.010, and 0.034, respectively). Our dataset provides a platform for information and knowledge mining of the genomic characteristics of GRC and helps to frame new therapeutic approaches for this disease.

Novel Biomarkers of Gastric Cancer: Current Research and Future Perspectives

Gastric cancer is a heterogeneous disease with diverse histological and genomic subtypes, making it difficult to demonstrate treatment efficacy in clinical trials. However, recent efforts have been made to identify molecular biomarkers with prognostic and predictive implications to better understand the broad heterogeneity of gastric cancer and develop effective targeted therapies for it. HER2 overexpression, HER2/neu amplification, MSI-H, and PD-L1+ are predictive biomarkers in gastric cancer, and a growing number of clinical trials based on novel biomarkers have demonstrated the efficacy of targeted therapies alone or in combination with conventional chemotherapy. Enrichment design clinical trials of targeted therapies against FGFR2b and claudin 18.2 have demonstrated efficacy in unresectable advanced gastric cancer. Nonetheless, it is essential to continuously validate promising molecular biomarkers and introduce them into clinical practice to optimize treatment selection and improve patient outcomes. In this review, we focused on established (PD-L1, HER2, MSI) and emerging biomarkers (FGFR2, CLDN18.2) in gastric cancer, their clinical significance, detection methods, limitations, and molecular agents that target these biomarkers.

Antibody-drug conjugates: the clinical development in gastric cancer

Gastric cancer (GC) is a prevalent malignant tumor of the digestive system worldwide, ranking among the top five in terms of incidence and mortality. However, the clinical efficacy of conventional treatments for gastric cancer remains limited, with a median overall survival of approximately eight months for advanced cases. In recent years, researchers have increasingly focused on antibody-drug conjugates (ADCs) as a promising approach. ADCs are potent chemical drugs that selectively target cancer cells by binding to specific cell surface receptors with antibodies. Notably, ADCs have demonstrated promising results in clinical studies and have made significant strides in the treatment of gastric cancer. Currently, several ADCs are under investigation in clinical trials for gastric cancer patients, targeting various receptors such as EGFR, HER-2, HER-3, CLDN18.2, Mucin 1, among others. This review offers a comprehensive exploration of ADC drug characteristics and provides an overview of the research progress in ADC-based therapies for gastric cancer.

Prognostic significance of JAM 3 in gastric cancer: An observational study from TCGA and GEO

Junctional adhesion molecule 3 (JAM3) can be used as a prognostic marker in multiple cancer types. However, the potential prognostic role of JAM3 in gastric cancer (GC) remains unclear. The purpose of this research was to gauge JAM3 expression and methylation as potential biomarkers for GC patient survival. Through bioinformatics research, we analyzed JAM3 expression, methylation, prognosis, and immune cell infiltrations. JAM3 methylation acts as a negative regulator of JAM3, leading to reduced expression of JAM3 in GC tissues relative to normal tissues. Patients with GC who expressed little JAM3 have a better chance of living a long time free of the disease, according to the Cancer Genome Atlas (TCGA) database. Through univariate and multivariate Cox regression analysis, inadequate JAM3 expression was labeled as an isolated indicator for overall survival (OS). The GSE84437 dataset was also used to confirm JAM3 prognostic role in GC, with consistent findings. A meta-analysis also found that low levels of JAM3 expression were significantly associated with longer OS. Finally, there was a strong correlation between JAM3 expression and a subset of immune cells. According to the TCGA database, low JAM3 expression could predict favorable OS and progression-free-survival (PFS) in GC patients (P < .05). The univariate and multivariate Cox regression demonstrated that low JAM3 expression was independent biomarker for OS (P < .05). Moreover, GSE84437 dataset was utilized to verify the prognostic role of JAM3 in GC, and the similar results were reached (P < .05). A meta-analysis revealed that low JAM3 expression was closely relevant to better OS. Finally, JAM3 expression exhibited a close correlation with some immune cells (P < .05). JAM3 might be a viable predictive biomarker and likely plays a crucial part in immune cell infiltration in individuals with GC.

Identification of mitochondrial respiratory chain signature for predicting prognosis and immunotherapy response in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is the third leading cause of cancer-related deaths and the fifth most prevalent malignancy worldwide. Mitochondrial respiratory chain complexes play a crucial role in STAD pathogenesis. However, how mitochondrial respiratory chain complex genes (MRCCGs) affect the prognosis and tumor microenvironment in STAD remains unclear. In this study, we systematically analyzed genetic alterations and copy number variations of different expression densities of MRCCGs, based on 806 samples from two independent STAD cohorts. Then we employed the unsupervised clustering method to classify the samples into three expression patterns based on the prognostic MRCCG expressions, and found that they were involved in different biological pathways and correlated with the clinicopathological characteristics, immune cell infiltration, and prognosis of STAD. Subsequently, we conducted a univariate Cox regression analysis to identify the prognostic value of 1175 subtype-related differentially expressed genes (DEGs) and screened out 555 prognostic-related genes. Principal component analysis was performed and developed the MG score system to quantify MRCCG patterns of STAD. The prognostic significance of MG Score was validated in three cohorts. The low MG score group, characterized by increased microsatellite instability-high (MSI-H), tumor mutation burden (TMB), PD-L1 expression, had a better prognosis. Interestingly, we demonstrated MRCCG patterns score could predict the sensitivity to ferroptosis inducing therapy. Our comprehensive analysis of MRCCGs in STAD demonstrated their potential roles in the tumor-immune-stromal microenvironment, clinicopathological features, and prognosis. Our findings highlight that MRCCGs may provide a new understanding of immunotherapy strategies for gastric cancer and provide a new perspective on the development of personalized immune therapeutic strategies for patients with STAD.

Robotic gastrectomy for gastric cancer: systematic review and future directions

BACKGROUND

Robotic gastrectomy (RG) using the da Vinci Surgical System for gastric cancer was approved for national medical insurance coverage in Japan in April 2018, and its number has been rapidly increasing since then.

AIM

We reviewed and compared current evidence on RG and conventional laparoscopic gastrectomy (LG) to identify the differences in surgical outcomes.

METHODS

Three independent reviewers systematically reviewed the data collected from a comprehensive literature search by an independent organization, focusing on the following nine endpoints: mortality, morbidity, operative time, estimated blood loss volume, length of postoperative hospital stay, long-term oncologic outcome, quality of life, learning curve, and cost.

RESULTS

Compared to LG, RG has lower intraoperative blood loss volume, shorter length of hospital stay, and shorter learning curve, but both procedures have similar mortality. Contrarily, its disadvantages include longer procedural time and higher costs. Although the morbidity rate and long-term outcomes are almost comparable, RG showed superior potentials. Currently, the outcomes of RG are considered comparable to or better than LG.

CONCLUSION

RG might be applicable to all gastric cancer patients who fulfill the indication of LG at institutions that meet specific criteria and are approved to claim the National Health Insurance costs for the use of the surgical robot in Japan.

Overview of Chemotherapy for Gastric Cancer

Gastric cancer (GC) is one of the most clinically challenging cancers worldwide. Over the past few years, new molecular-targeted agents and immunotherapy have markedly improved GC prognosis. Human epidermal growth factor receptor 2 (HER2) expression is a key biomarker in first-line chemotherapy for unresectable advanced GC. Further, the addition of trastuzumab to cytotoxic chemotherapy has extended the overall survival of patients with HER2-positive advanced GC. In HER2-negative GC, the combination of nivolumab, an immune checkpoint inhibitor, and a cytotoxic agent has been demonstrated to prolong the overall survival of GC patients. Ramucirumab and trifluridine/tipiracil, which are second- and third-line treatments for GC, and trastuzumab deruxtecan, an antibody-drug conjugate for HER2-positive GC, have been introduced in clinics. New promising molecular-targeted agents are also being developed, and combination therapy comprising immunotherapy and molecular-targeted agents is expected. As the number of available drugs increases, it is important to understand the target biomarkers and drug characteristics and select the optimal therapy for each patient. For resectable disease, differences in the extent of standard lymphadenectomy between Eastern and Western countries have led to different standard treatments: perioperative (neoadjuvant) and adjuvant therapy. This review aimed to summarize recent advances in chemotherapy for advanced GC.

Exosomes: A potential tool for immunotherapy of ovarian cancer

Ovarian cancer is a malignant tumor of the female reproductive system, with a very poor prognosis and high mortality rates. Chemotherapy and radiotherapy are the most common treatments for ovarian cancer, with unsatisfactory results. Exosomes are a subpopulation of extracellular vesicles, which have a diameter of approximately 30-100 nm and are secreted by many different types of cells in various body fluids. Exosomes are highly stable and are effective carriers of immunotherapeutic drugs. Recent studies have shown that exosomes are involved in various cellular responses in the tumor microenvironment, influencing the development and therapeutic efficacy of ovarian cancer, and exhibiting dual roles in inhibiting and promoting tumor development. Exosomes also contain a variety of genes related to ovarian cancer immunotherapy that could be potential biomarkers for ovarian cancer diagnosis and prognosis. Undoubtedly, exosomes have great therapeutic potential in the field of ovarian cancer immunotherapy. However, translation of this idea to the clinic has not occurred. Therefore, it is important to understand how exosomes could be used in ovarian cancer immunotherapy to regulate tumor progression. In this review, we summarize the biomarkers of exosomes in different body fluids related to immunotherapy in ovarian cancer and the potential mechanisms by which exosomes influence immunotherapeutic response. We also discuss the prospects for clinical application of exosome-based immunotherapy in ovarian cancer.

The Impact of Palliative Radiation Therapy on Patients With Advanced Gastric Cancer: Results of a Retrospective Cohort Study

Aim In advanced gastric cancer, symptoms such as loss of appetite, stomach tightness, occasional pain, vomiting blood, and melena may occur. Palliative radiation therapy may be indicated in such cases. This study aimed to investigate the clinical outcomes of palliative radiotherapy in patients with advanced-stage gastric carcinoma. Methods From April 2018 to October 2022, consecutive patients with non-resected advanced gastric cancer who received radiation therapy for palliation of symptoms were included. Results A total of 23 patients with advanced-stage gastric carcinoma were analyzed in this study. Twelve male and 11 female patients were included. The median overall survival period was 3.9 months (95% confidence interval: 1.0-8.7 months). Sixteen patients required erythrocyte transfusion before radiotherapy; for 13 patients (83%), the required units of erythrocyte transfusion decreased after palliative radiotherapy. The mean erythrocyte transfusion units significantly decreased from 4.2 (standard deviation [SD]: 4.3) to 1.7 (SD: 3.6) (p = 0.02). No adverse events of grade ≥3 were observed in this study population. Conclusion Palliative radiation therapy for advanced gastric cancer yielded a good response rate and can be a useful treatment option.