Gastric Cancer Genetics and Its Implications for Diagnosis, Prognosis, and Treatment of the Disease

José Pedro Santos; Joana Figueiredo; José Carlos Machado

doi:10.7704/kjhugr.2024.0018

Korean J Helicobacter Up Gastrointest Res > Volume 24(2); 2024 > Article

Santos, Figueiredo, and Machado: Gastric Cancer Genetics and Its Implications for Diagnosis, Prognosis, and Treatment of the Disease

Review

The Korean Journal of Helicobacter and Upper Gastrointestinal Research 2024;24(2):103-112.

Published online: June 10, 2024

DOI: https://doi.org/10.7704/kjhugr.2024.0018

Gastric Cancer Genetics and Its Implications for Diagnosis, Prognosis, and Treatment of the Disease

José Pedro Santos^1,^2,³

, Joana Figueiredo^1,^2,³

, José Carlos Machado^1,^2,³

¹i3S - Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal

²Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), Porto, Portugal

³Medical Faculty of the University of Porto, Porto, Portugal

Corresponding author José Carlos Machado, PhD Instituto de Investigação e Inovação em Saúde, University of Porto, Rua Alfredo Allen, 208 | 4200-135 Porto, Portugal E-mail: josem@ipatimup.pt

Received March 26, 2024; Revised April 17, 2024; Accepted April 17, 2024;

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Gastric cancer (GC) is an aggressive disease and the fifth most common cancer worldwide with a variable geographical distribution. GC has a very low survival rate, mainly because of its heterogeneous presentation, multifactorial etiology, and late diagnosis. It is well established that various risk factors contribute to the development of the disease, including salty diet, smoking, and excessive alcohol consumption. Importantly, interactions between genetic and environmental traits trigger the activation of key signaling pathways, influencing gastric cell behavior towards neoplastic transformation and progression. Despite important advances in our understanding of GC, it remains a major health burden owing to epidemiological and therapeutic limitations. This study aimed to provide a comprehensive overview of the genetic landscape of GC phenotypes and molecular biomarkers for diagnosis and prognosis. In particular, we discuss the advances in genomic knowledge and technology that have yielded comprehensive information on the genetics of GC and classified it from a histological to a molecular perspective. Therefore, targeted and immune-based therapies have been developed, highlighting the challenges associated with intratumoral and interpatient heterogeneity. Finally, we explored potential research avenues on the intricacies of GC and identified accurate biomarkers for improved cancer screening and stratification. The development of innovative approaches to tackle relevant molecules is needed for GC management.

Key words: Gastric cancer; Cancer genetics; Molecular profile; Diagnostic

INTRODUCTION

Gastric cancer (GC) is an aggressive disease and the fifth most common malignancy worldwide. Despite extensive research and recent breakthroughs in medicine, GC has a very low survival rate, making it the fourth leading cause of cancer-related death worldwide [1,2]. The incidence of GC differs globally, with a higher prevalence in Eastern Europe, South America, and Eastern Asia than in North European and East African countries [3,4]. Men are more prone to gastric carcinogenesis than women [1,2].

According to the histological pattern, GC has been classified into intestinal, diffuse, and indeterminate subtypes based on the Lauren’s classification [5]. The intestinal type is characterized by well-differentiated glandular structures and accounts for approximately 50%–60% of cases. This subtype exhibits aneuploidy or frequent genetic alterations that affect mitotic and relevant oncogenic signaling pathways. In contrast, the diffuse type is rarer (30%–40%) and displays an undifferentiated pattern of poorly cohesive cells, often with a signet ring cell morphology. A mixture of intestinal-and diffuse-type components is observed in a small proportion of GC cases, which are classified as the indeterminate type. A different classification system was proposed by the World Health Organization in 2010 and updated in 2019. This complex scheme recognizes four major histological patterns, tubular, papillary, mucinous, and poorly cohesive, followed by several subdivisions in each category [6].

To some extent, the heterogeneous presentation of GC is associated with its multifactorial etiology. It is well established that various risk factors contribute to disease development[7]. For instance, salty diet, smoking, and excessive alcohol consumption are regarded as modulators of gastric cell behavior that can promote genetic alterations and subsequent neoplastic transformations [7,8].

Among environmental factors, Helicobacter pylori is recognized as type 1 carcinogenic being associated with approximately 80% of all GC cases worldwide [9,10]. This pathogen promotes chronic gastritis and increases the pH of the stomach, enabling the colonization of the gastric epithelium by opportunistic microbes [11]. The preferential binding of H. pylori to the gastric mucosa is mediated by the bacterial blood group antigen-binding adhesin (BabA), sialic acid-binding adhesin (SabA), and Lewis antigen-binding adhesin present in the gastric cell membrane [12-14]. This initiates a gradual process of histological alteration, known as the Correa cascade, from chronic to atrophic gastritis, intestinal metaplasia, dysplasia, and eventually to invasive carcinoma [15,16]. Progression to GC is strongly associated with bacterial virulence factors and genetic polymorphisms in the host [17,18]. Among these, cytotoxin-associated gene A (CagA) and vacuolating cytotoxic gene A (VacA) genotypes are correlated with severe clinical outcomes and increased incidence in Western countries [19,20].

The Epstein-Barr virus (EBV) has also been associated with gastric adenocarcinoma, although only a small proportion of infected individuals progress to GC [21,22]. EBV-positive tumors are distinguishable from EBV-negative tumors based on genetic alterations and evident clinicopathological features, including the formation of lumps or ulcers accompanied by lymphocyte infiltration [23]. Interestingly, other environmental factors, such as eating salty or spicy foods, cigarette smoking, excessive coffee consumption, and drinking high-temperature beverages, are also considered risk factors for developing EBV-positive GC, corroborating the relevance of repeated tissue injury in the disease [24,25].

Although most cases of GC are sporadic, genetic predisposition plays an important role in its development. Accordingly, germline mutations in tumor suppressor genes may trigger familial aggregation of GC and early onset manifestations [26,27].

Herein, we aimed to provide a comprehensive overview of the genetics underlying GC phenotypes and how this knowledge can aid in the diagnosis and overall patient management. We outlined the challenges associated with the heterogeneity of the disease and explored potential research avenues to advance our understanding of the etiology of GC and development of alternative therapeutics.

GENETICS OF GASTRIC CANCER

In recent years, improved genomic knowledge and technology have yielded a large amount of information on the genetics of tumors, challenging the classification paradigm from a histological to a molecular perspective. This has not only revealed the molecular mechanism of cancer but has also contributed to innovative biomarkers and targeted therapeutics. In 2014, The Cancer Genome Atlas Research Network proposed the molecular classification of GC into four distinct subtypes: EBV-positive, microsatellite instability (MSI), chromosomal instability (CIN), and genomically stable (GS) (Fig. 1) [28].

EBV-positive gastric carcinomas are mostly located in the gastric fundus and more prevalent in male patients. These tumors are characterized by an extensive mutation burden, including recurrent mutations in genes involved in the phosphatidylinositol 3-kinase (PIK3CA) pathway or gene amplification of Janus-associated kinase 2 (JAK2) and HER2 receptor tyrosine kinase 2 (ERBB2) [28]. In addition, these malignancies typically present mutations in chromatin remodeling genes, such as AT-rich interactive domain-containing protein 1A (ARID1A) and B-cell lymphoma 6 corepressor (BCOR), and overexpression of programmed death ligand-1/2 (PD-L1/2) [28,29]. Extensive DNA methylation and the subsequent silencing of cyclin-dependent kinase inhibitor 2A gene (CDKN2A) has also been reported in EBV-positive tumors [28,30].

MSI subtype tumors are typically found in the distal stomach of older patients and are associated with H. pylori infection and intestinal metaplasia. These tumors display a hypermutation profile resulting from promoter methylation and transcriptional silencing of the DNA mismatch repair gene MLH1 [30,31]. Dysfunction of the mismatch repair system leads to high mutation rates and inactivation of tumor suppressor genes or oncogenes. The most frequently mutated genes are PIK3CA and epithelial growth factor receptor (EGFR). To escape immunosurveillance triggered by the mutation burden, these tumors express high levels of PD-L1/2 with concomitant low levels of major histocompatibility complex class I (MHC1) [32,33]. Importantly, both MSI and EBV-positive gastric carcinomas exhibit intestinal-type histology and CpG island methylator phenotype (CIMP) [32,34].

In contrast to EBV-positive and MSI subtypes, GS tumors are characterized by lower rates of somatic mutations, earlier onset, and diffuse histology. Mutations usually affect the CDH1 and RHOA genes, decreasing cell-cell adhesion and promoting cell motility [35]. Genomic rearrangements, such as the CLDN18::ARHGAP26 fusion, can also be detected and are strongly associated with RHOA inhibition and loss of epithelial integrity [28,36].

CIN carcinomas exhibit intestinal histology and are often located in the gastroesophageal junction or cardia of the stomach. These gastric tumors exhibit severe chromosomal abnormalities that can result from four distinct mechanisms: inaccurate chromosome segregation during mitosis, cell cycle checkpoint defects, oncogene-induced mitotic stress, and replication stress [37]. CIN tumors exhibit high aneuploidy rates and are characterized by tumor protein 53 (TP53) mutations, the most recurrent genetic alterations, which impair cell division/death control. Genomic amplification of receptor tyrosine kinases (EGFR, RAS, FGFR, ERBB2, and MET), VEGFA (VEGFR2 ligand), and cell cycle mediators (CCNE1, CCND1, and CDK6) are also described in the CIN subtype [28,29].

In addition to sporadic cases, 10% of GC cases arise in familial settings. GC is the primary clinical manifestation of hereditary diffuse gastric cancer (HDGC), gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS), and familial intestinal gastric cancer (FIGC) syndromes (Fig. 2) [38].

HDGC is an autosomal-dominant syndrome characterized by a significant lifetime risk of diffuse gastric and lobular breast cancers, although congenital malformations such as cleft lip/palate have also been described as part of the disease spectrum [39,40]. In this setting, GC is highly aggressive, with neoplastic cells diffusely infiltrating the gastric wall and spreading into the peritoneal cavity and distant sites [41]. To date, pathogenic germline mutations of CDH1 and CTNNA1 genes are the only proven cause of HDGC [42,43]. CDH1 encodes E-cadherin, a transmembrane protein responsible for homophilic binding between adjacent cells, whereas CTNNA1 codifies for α-catenin, a pivotal molecule for linkage between E-cadherin and cytoskeleton [44,45]. Thus, it is clear that the loss of either of these proteins affects intercellular junction and maintenance of epithelial structure and function. CDH1 and CTNNA1 germline variants are evenly distributed throughout the gene, and no definite genotype-phenotype correlations can be established [42]. Because mutations are inherited from one parent, every cell from the progeny carries a functional and a defective copy of the gene. Complete gene inactivation occurs upon somatic loss of the second allele (Knudson’s two-hit hypothesis) through hypermethylation, mutation, or deletion [46,47].

GAPPS was first recognized in 2012; it is characterized by fundic gland polyposis with focal dysplasia and intestinal or mixed-type adenocarcinoma [48]. For diagnosis, >100 gastric polyps should be detected, and polyposis elsewhere in the gastrointestinal tract, namely colorectal or duodenal, should be excluded. Syndrome etiology is attributed to germline single nucleotide mutations in the promoter region 1B of the tumor suppressor gene APC, which lead to decreased APC expression [49,50]. Second-hit events encompass truncating mutations or loss of the wild-type allele, resulting in biallelic inactivation of APC gene [49,50].

In contrast to HDGC and GAPPS, the pathogenesis of FIGC remains largely unknown, possibly because of the broad categories of cancer that can arise in this setting [51]. In addition to an increased risk of intestinal-type GC, colorectal, and breast carcinomas, 15 other cancer phenotypes were observed in family members with FIGC. These comprise lung, laryngotracheal, hepatobiliary and liver cancers, as well as leukemia, among other malignancies [49,51]. Moreover, studies addressing the genetic factors underlying FIGC are scarce, and suggest a polygenic cause. For instance, heterozygous mutations in the immune response-related gene IL12RB1 were reported in a Dutch family in which several members were affected by the intestinal-type GC [52]. The implementation of next-generation sequencing approaches identified TP53 as a potential susceptibility gene for FIGC, while MSI was detected in 38% of cases [51].

GC may also develop in the context of other hereditary cancer syndromes, albeit at a lower frequency. These include Li-Fraumeni syndrome, familial adenomatous polyposis, Peutz-Jeghers syndrome, Lynch syndrome, hereditary breast/ovarian cancer syndrome, MUTYH-associated adenomatous polyposis, juvenile polyposis syndrome, and Cowden syndrome [53].

DIAGNOSTIC APPROACHES

During its initial stages, GC often presents with no noticeable symptoms. As the disease progresses, common symptoms may include difficulty in swallowing (dysphagia), asthenia, indigestion, vomiting, weight loss, early satiety, and iron deficiency anemia [2,54]. However, these symptoms are not specific, and there is little urgency in determining their causes. Consequently, approximately 60% of individuals with GC are ineligible for curative treatment due to late diagnosis or underlying health conditions [54,55].

Traditionally, GC diagnosis relies on endoscopic examination and subsequent histological analysis of gastric biopsies [56]. Examination of tissue features includes not only the epithelial component but also elements of the tumor microenvironment, namely infiltrating lymphocytes and the surrounding extracellular matrix [57,58]. Recently, deep learning methods have emerged as promising complementary tools for improving the detection of cancer cell traits, which can promptly affect screening and therapeutic strategies. For instance, deep learning was able to effectively predict the MSI status directly from H&E-stained histology slides [59]. The classification of gastric and colon biopsy specimens has also been achieved using convolutional neural networks, supporting routine histopathological diagnoses [60,61]. Likewise, the implementation of multiplexed immunofluorescence imaging approaches provides a framework for the quantitative analysis of spatial interactions and immune phenotypes in gastric biopsies and resection specimens [62,63].

Contrary to tissue biopsies, which can be expensive, carry potential risks for patients, and only provide information on a small portion of the tumor, liquid biopsies offer a non-invasive approach and a broader overview of the heterogeneity and complexity of the disease [64,65]. Several tumor-derived components have been detected in the bloodstream of patients with cancer, including circulating tumor DNA (ctDNA), circulating tumor cells (CTC), and exosomes. While CTCs and exosome content can provide relevant molecular and functional data, ctDNA is easy to isolate, more sensitive, and constitutes a superior source of genetic information [64,65]. In particular, ctDNA has been proposed for the identification of HER2 amplification, whose detection rates within tumor tissues are hampered by GC heterogeneity [66,67].

MOLECULAR BIOMARKERS

The challenges associated with the management of GC are intratumoral and intertumoral heterogeneity. Therefore, remarkable efforts have been made to identify effective molecular markers for diagnosis and prognosis.

Currently, biomarkers such as carcinoembryonic antigen (CEA) and carbohydrate antigens CA19-9 and CA72-4 are used in clinical pipelines to predict GC recurrence. Nonetheless, these methods lack specificity and sensitivity and are often used in combination with other tumor markers [68,69].

The tyrosine-kinase membrane receptor HER2 has predictive value for treatment of advanced gastric carcinoma with HER2 inhibitors. This protein, encoded by the ERBB2 gene located on chromosome 17, belongs to the EGFR family and can activate survival and proliferative signaling pathways without the need for a binding ligand [70,71]. The activation mechanism of this oncogene occurs primarily upon amplification or, in rare cases, by gene fusion. HER2 amplification occurs in 6%–23% of patients, predominantly in the CIN molecular subtype, encompassing the intestinal type and well-differentiated tumors [72].

HER2 status is usually evaluated by immunohistochemistry and its expression is scored from 0 (no presence of HER2 amplification) to 3 (HER2 overexpression). In cases where HER2 staining status remains unclear, in situ hybridization with directed probes should be performed [73]. HER2-amplified GC is associated with an aggressive phenotype and poor outcome; therefore, this marker is considered a negative prognostic factor [74-76].

Another emerging biomarker is PD-L1, a binding ligand for the membrane programmed death 1 (PD-1) protein, which is expressed in immune cells. The interaction between PD-L1 and PD-1 impairs the immune response and induces the apoptosis of cytotoxic T cells, thereby allowing tumor progression [77]. Thus, this molecule has become valuable for the prognosis and assessment of potential sensitivity to PD-1/PD-L1 inhibitors in various cancers. In GC, PD-L1 is differentially expressed across distinct subtypes, exhibiting higher levels in MSI and EBV-positive tumors [78,79]. Similar to HER2 evaluation, PD-L1 is assessed by immunohistochemistry in gastric biopsies and tumors, where PD-L1 overexpression is associated with an increased ability to evade the immune system and, consequently, poor survival rates [80].

Approximately 15%–30% of gastric tumors display MSI. Microsatellites are short tandem repeats (1–6 nucleotides) scattered throughout the genome, including non-coding and coding DNA sequences. These regions are prone to high mutation rates by the insertion or deletion of repeat units, leading to genomic instability and susceptibility to tumor development [81]. Tumors exhibiting 10%–29% unstable microsatellite regions are categorized as MSI-low, whereas tumors with ≥30% unstable microsatellite regions fall into the MSI-high group. MSI is primarily caused by promoter hypermethylation and epigenetic silencing of MLH1 gene [82]. A comprehensive analysis conducted in South Korea revealed that over 63% of MSI-high GC cases harbored mutations in genes, such as TGFBR2, CEP164, MIS18BP1, RNPC3, KIAA2018, CNOT1, and CCDC150 [83]. MSI is detected through immunohistochemistry or polymerase chain reaction (PCR) in gastric biopsies or by PCR/next-generation sequencing molecular analysis in plasma-derived cellfree ctDNA. Interestingly, MSI-high tumors show a better prognosis than those presenting MSI-low phenotypes, which is attributed to increased levels of tumor-infiltrating lymphocytes and consequently higher immunogenicity [84,85].

Fibroblast growth factor receptor 2 (FGFR2) has been suggested as a biomarker for predicting long-term recurrence and lower overall survival, given its involvement in several cancer hallmarks, namely mitogenesis, differentiation, cell proliferation, migration, and angiogenesis [86]. FGFR2 is systematically amplified in metastatic GC [87], and its overexpression (31%) is more common than that of EGFR (24%), HER2 (12%), and MET (25%) [88].

More recently, claudin 18.2 has arisen as a selective molecular marker of diffuse-type GC. In normal gastric mucosa, the expression of this protein is limited to tight junctions, which become exposed and overexpressed in gastric adenocarcinoma cells following the disruption of cell-cell adhesion [89]. Claudin 18.2 overexpression is related to a higher probability of tumor invasion limited to the mucosa and submucosa; hence, it is regarded as a predictive biomarker in resectable GC. Corroborating these data, low claudin 18.2 levels were described in more aggressive and invasive tumors [90,91].

Ultimately, knowledge gathered regarding the identification of accurate biomarkers and their biological significance is essential for cancer screening and stratification as well as for devising innovative therapeutic interventions.

TREATMENT STRATEGIES

Despite the important developments in our understanding of GC, very little has been translated into successful therapeutics. For patients with early stage GC, surgery remains the primary line of treatment, whereas patients with advanced GC rely on chemotherapy alone or combined with targeted and immunotherapies. Standard chemotherapy involves a platinum-fluoropyrimidine doublet, usually involving oxaliplatin or cisplatin and fluoropyrimidines administered as an infusion (5-FU) or orally (capecitabine or tegafur-gimeracil-oteracil [S-1]) [54]. Conventional treatment results in a median overall survival of approximately 12 months, reflecting high toxicity and drug resistance [92]. In a phase 3 randomized trial, a triplet of docetaxel, cisplatin, and S-1 was evaluated, which yielded a debatable benefit and increased toxicity [93].

The past decade has witnessed remarkable progress in cancer treatment using immunotherapy and targeted therapy regimens. For instance, patient stratification based on the HER2 status revealed the possibility of combining chemotherapy with trastuzumab, with increased response rates and overall survival up to 16 months [94]. Trastuzumab is a monoclonal antibody that binds specifically to the extracellular domain of the receptor, blocking downstream survival and proliferative signaling pathways such as PI3K/AKT [94]. Approval of this antibody for unresectable or metastatic GC represented a paradigm shift in the management of HER2-positive tumors. Notably, the role of anti-HER2 targeted therapy in the perioperative setting remains under investigation, although current guidelines do not recommend its administration, given the extensive adverse effects and absence of significant improvement in patient well-being [95,96].

Immune checkpoint blockade using the anti-PD-1 monoclonal antibody nivolumab, in addition to chemotherapy, resulted in significant improvements in overall survival and progression-free survival [97]. In addition to PD-L1 expression, high MSI and tumor mutation burden are also indicative of immunotherapy response. Increased mutation rates can induce the formation of immunogenic neoantigens that are easily recognized by effector immune cells [98,99]. Furthermore, EBV-positive tumors exhibit an excess of CD8+ tumor-infiltrating lymphocytes, supporting the use of immune-based therapies [78,98]. PD-1 inhibitors, such as nivolumab and pembrolizumab, have been evaluated as the first- or second-line treatment, either as monotherapy or in combination with other agents. In particular, the potential benefits of immune checkpoint inhibitors along with anti-HER2 therapies have been observed in patients with HER2-sensitive GC [97,100].

Anti-angiogenic therapies using vascular endothelial growth factor receptor 2 (VEGFR2) antibodies following the first-line chemotherapy have also been investigated. VEGFR2 is a tyrosine kinase receptor involved in angiogenesis, autocrine survival, and migration signaling [101]. Upon binding to its ligand VEGF, it stimulates neighboring neovascularization, increasing the availability of oxygen and nutrients to malignant cells [102]. According to the REGARD trial, the anti-VEGFR2 ramucirumab improved overall survival compared with the best supportive care [103], whereas in the RAINBOW study, the combination of ramucirumab and paclitaxel improved survival compared with paclitaxel alone [104]. However, anti-VEGFR2 therapeutics did not provide benefits when combined with platinum- or fluoropyrimidine-based chemotherapy [105]. In addition, it is well established that the angiogenic factor VEGF and its downstream signaling pathways yield an anti-inflammatory phenotype and immune evasion. Therefore, a synergistic mechanism involving anti-VEGFR2 and immunotherapy has been proposed to enhance antitumor immunity [106,107].

Innovative therapies targeting relevant biomarkers remain in demand for GC management. In particular, claudin 18.2 and FGFR2 have gained attention for the design of novel regimens, either alone or in combination with other agents. Anti-claudin and anti-FGFR2 antibodies are already available and currently being tested in combination with chemotherapy in trials for gastric or gastro-esophageal junction adenocarcinomas [108,109].

CONCLUSION

GC remains a major health burden due to the epidemiological and therapeutic challenges associated with late diagnosis. Future research should focus on the implementation of endoscopic screening programs, as well as on community literacy to ameliorate the associated risk. Moreover, efforts should be made to develop less invasive tools for early disease detection.

The main barrier in the near future is to overcome the intratumoral and interpatient heterogeneity for patient stratification and drug development. Advances in the molecular landscape of GC highlight the need for a more rigorous selection of patients for a given treatment while revealing the remarkable capacity of tumors to overcome therapeutic assault. Understanding the biological intricacies of GC will certainly reveal unforeseen susceptibilities that must be addressed for the benefit of patients.

Notes

Availability of Data and Material

Data sharing not applicable to this article as no datasets were generated or analyzed during the study.

Conflicts of Interest

The authors have no financial conflicts of interest.

Funding Statement

This work was financed by FEDER funds through the Operational Programme for Competitiveness Factors (COMPETE 2020), Programa Operacional de Competitividade e Internacionalização (POCI), and Programa Operacional Regional do Norte (Norte 2020); and by National Funds through the Portuguese Foundation for Science and Technology (FCT projects EXPL/MED-ONC/0386/2021 and 2022.02665.PTDC). JF received funding by the FCT Scientific Employment Stimulus – Institutional Call (CEECINST/00056/2021). We acknowledge the American Association of Patients with Hereditary Gastric Cancer “No Stomach for Cancer” for funding the research by JF and the project “P.CCC: Centro Compreensivo de Cancro do Porto” - NORTE-01-0145-FEDER-072678, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF).

Authors’ Contribution

Conceptualization: José Carlos Machado. Funding acquisition: José Carlos Machado, Joana Figueiredo. Investigation: all authors. Writing—original draft: José Pedro Santos. Writing—review & editing: José Carlos Machado, Joana Figueiredo. Approval of final manuscript: all authors.

Acknowledgements

None

Fig. 1.

Molecular classification of gastric cancer. Key features of different gastric cancer subtypes, including localization, histology, genetic alterations, and expression markers. Dashed lines represent different anatomical divisions of the stomach. TP53, tumor protein 53; CDKN2A, cyclin-dependent kinase inhibitor 2A gene; PIK3CA, phosphatidylinositol 3-kinase; ARID1A, AT-rich interactive domain-containing protein 1A; JAK2, Janus-associated kinase 2; ERBB2, HER2 receptor tyrosine kinase 2; PD-L1/2, programmed death ligand-1/2; CIMP, CpG island methylator phenotype.

Fig. 2.

Cellular mechanisms associated with gastric cancer development in familial settings. Cancer syndromes in which gastric cancer is the primary clinical manifestation include hereditary diffuse gastric cancer (HDGC) and gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS). In a small proportion of cases, gastric cancer also occurs as part of the tumor spectrum of Li-Fraumeni syndrome, familial adenomatous polyposis (FAP), and Lynch syndrome. Genes involved in each syndrome are presented as colored.

REFERENCES

1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021;71:209–249.

2. Smyth EC, Nilsson M, Grabsch HI, van Grieken NC, Lordick F. Gastric cancer. Lancet 2020;396:635–648.

3. Ang TL, Fock KM. Clinical epidemiology of gastric cancer. Singapore Med J 2014;55:621–628.

4. Arnold M, Park JY, Camargo MC, Lunet N, Forman D, Soerjomataram I. Is gastric cancer becoming a rare disease? A global assessment of predicted incidence trends to 2035. Gut 2020;69:823–829.

5. Lauren P. The two histological main types of gastric carcinoma: diffuse and so‐called intestinal‐type carcinoma. An attempt at a histoclinical classification. Acta Pathol Microbiol Scand 1965;64:31–49.

6. Nagtegaal ID, Odze RD, Klimstra D, et al. The 2019 WHO classification of tumours of the digestive system. Histopathology 2020;76:182–188.

7. Machlowska J, Baj J, Sitarz M, Maciejewski R, Sitarz R. Gastric cancer: epidemiology, risk factors, classification, genomic characteristics and treatment strategies. Int J Mol Sci 2020;21:4012.

8. Kim J, Cho YA, Choi WJ, Jeong SH. Gene-diet interactions in gastric cancer risk: a systematic review. World J Gastroenterol 2014;20:9600–9610.

9. Shirani M, Pakzad R, Haddadi MH, et al. The global prevalence of gastric cancer in Helicobacter pylori-infected individuals: a systematic review and meta-analysis. BMC Infect Dis 2023;23:543.

10. Moss SF. The clinical evidence linking Helicobacter pylori to gastric cancer. Cell Mol Gastroenterol Hepatol 2017;3:183–191.

11. Ferreira RM, Pereira-Marques J, Pinto-Ribeiro I, et al. Gastric microbial community profiling reveals a dysbiotic cancer-associated microbiota. Gut 2018;67:226–236.

12. Doohan D, Rezkitha YAA, Waskito LA, Yamaoka Y, Miftahussurur M. Helicobacter pylori BabA-SabA key roles in the adherence phase: the synergic mechanism for successful colonization and disease development. Toxins (Basel) 2021;13:485.

13. Ilver D, Arnqvist A, Ogren J, et al. Helicobacter pylori adhesin binding fucosylated histo-blood group antigens revealed by retagging. Science 1998;279:373–377.

14. Mahdavi J, Sondén B, Hurtig M, et al. Helicobacter pylori SabA adhesin in persistent infection and chronic inflammation. Science 2002;297:573–578.

15. Correa P, Haenszel W, Cuello C, Tannenbaum S, Archer M. A model for gastric cancer epidemiology. Lancet 1975;2:58–60.

16. Correa P, Piazuelo MB. The gastric precancerous cascade. J Dig Dis 2012;13:2–9.

17. Ferreira RM, Machado JC, Figueiredo C. Clinical relevance of Helicobacter pylori vacA and cagA genotypes in gastric carcinoma. Best Pract Res Clin Gastroenterol 2014;28:1003–1015.

18. Machado JC, Pharoah P, Sousa S, et al. Interleukin 1B and interleukin 1RN polymorphisms are associated with increased risk of gastric carcinoma. Gastroenterology 2001;121:823–829.

19. González CA, Figueiredo C, Lic CB, et al. Helicobacter pylori cagA and vacA genotypes as predictors of progression of gastric preneoplastic lesions: a long-term follow-up in a high-risk area in Spain. Am J Gastroenterol 2011;106:867–874.

20. Ferreira RM, Figueiredo C, Bonet C, et al. Helicobacter pylori vacA intermediate region genotyping and progression of gastric preneoplastic lesions. Am J Gastroenterol 2012;107:145–146.

21. Burke AP, Yen TS, Shekitka KM, Sobin LH. Lymphoepithelial carcinoma of the stomach with Epstein-Barr virus demonstrated by polymerase chain reaction. Mod Pathol 1990;3:377–380.

22. Lee JH, Kim SH, Han SH, An JS, Lee ES, Kim YS. Clinicopathological and molecular characteristics of Epstein-Barr virus-associated gastric carcinoma: a meta-analysis. J Gastroenterol Hepatol 2009;24:354–365.

23. van Beek J, zur Hausen A, Klein Kranenbarg E, et al. EBV-positive gastric adenocarcinomas: a distinct clinicopathologic entity with a low frequency of lymph node involvement. J Clin Oncol 2004;22:664–670.

24. Camargo MC, Koriyama C, Matsuo K, et al. Case-case comparison of smoking and alcohol risk associations with Epstein-Barr viruspositive gastric cancer. Int J Cancer 2014;134:948–953.

25. Koriyama C, Akiba S, Minakami Y, Eizuru Y. Environmental factors related to Epstein-Barr virus-associated gastric cancer in Japan. J Exp Clin Cancer Res 2005;24:547–553.

26. Choi IJ, Kim CG, Lee JY, et al. Family history of gastric cancer and Helicobacter pylori treatment. N Engl J Med 2020;382:427–436.

27. Oliveira C, Pinheiro H, Figueiredo J, Seruca R, Carneiro F. Familial gastric cancer: genetic susceptibility, pathology, and implications for management. Lancet Oncol 2015;16:e60. –e70.

28. Cancer Genome Atlas Research Network. Comprehensive molecular characterization of gastric adenocarcinoma. Nature 2014;513:202–209.

29. Wang Q, Liu G, Hu C. Molecular classification of gastric adenocarcinoma. Gastroenterology Res 2019;12:275–282.

30. Usui G, Matsusaka K, Mano Y, et al. DNA methylation and genetic aberrations in gastric cancer. Digestion 2021;102:25–32.

31. Leung SY, Yuen ST, Chung LP, Chu KM, Chan AS, Ho JC. hMLH1 promoter methylation and lack of hMLH1 expression in sporadic gastric carcinomas with high-frequency microsatellite instability. Cancer Res 1999;59:159–164.

32. Puliga E, Corso S, Pietrantonio F, Giordano S. Microsatellite instability in gastric cancer: between lights and shadows. Cancer Treat Rev 2021;95:102175.

33. Kim ST, Cristescu R, Bass AJ, et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat Med 2018;24:1449–1458.

34. Tahara T, Arisawa T. DNA methylation as a molecular biomarker in gastric cancer. Epigenomics 2015;7:475–486.

35. Ling Y, Watanabe Y, Nagahashi M, et al. Genetic profiling for diffuse type and genomically stable subtypes in gastric cancer. Comput Struct Biotechnol J 2020;18:3301–3308.

36. Yao F, Kausalya JP, Sia YY, et al. Recurrent fusion genes in gastric cancer: CLDN18-ARHGAP26 induces loss of epithelial integrity. Cell Rep 2015;12:272–285.

37. Maleki SS, Röcken C. Chromosomal instability in gastric cancer biology. Neoplasia 2017;19:412–420.

38. Gullo I, van der Post RS, Carneiro F. Recent advances in the pathology of heritable gastric cancer syndromes. Histopathology 2021;78:125–147.

39. Blair VR, McLeod M, Carneiro F, et al. Hereditary diffuse gastric cancer: updated clinical practice guidelines. Lancet Oncol 2020;21:e386–e397.

40. Figueiredo J, Melo S, Carneiro P, et al. Clinical spectrum and pleiotropic nature of CDH1 germline mutations. J Med Genet 2019;56:199–208.

41. Decourtye-Espiard L, Guilford P. Hereditary diffuse gastric cancer. Gastroenterology 2023;164:719–735.

42. Hansford S, Kaurah P, Li-Chang H, et al. Hereditary diffuse gastric cancer syndrome: CDH1 mutations and beyond. JAMA Oncol 2015;1:23–32.

43. Majewski IJ, Kluijt I, Cats A, et al. An α-E-catenin (CTNNA1) mutation in hereditary diffuse gastric cancer. J Pathol 2013;229:621–629.

44. Lecuit T, Yap AS. E-cadherin junctions as active mechanical integrators in tissue dynamics. Nat Cell Biol 2015;17:533–539.

45. Bajpai S, Correia J, Feng Y, et al. α-catenin mediates initial E-cadherin-dependent cell-cell recognition and subsequent bond strengthening. Proc Natl Acad Sci U S A 2008;105:18331–18336.

46. Grady WM, Willis J, Guilford PJ, et al. Methylation of the CDH1 promoter as the second genetic hit in hereditary diffuse gastric cancer. Nat Genet 2000;26:16–17.

47. Oliveira C, Sousa S, Pinheiro H, et al. Quantification of epigenetic and genetic 2nd hits in CDH1 during hereditary diffuse gastric cancer syndrome progression. Gastroenterology 2009;136:2137–2148.

48. Worthley DL, Phillips KD, Wayte N, et al. Gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS): a new autosomal dominant syndrome. Gut 2012;61:774–779.

49. Carneiro F. Familial and hereditary gastric cancer, an overview. Best Pract Res Clin Gastroenterol 2022;58-59:101800.

50. Li J, Woods SL, Healey S, et al. Point mutations in exon 1B of APC reveal gastric adenocarcinoma and proximal polyposis of the stomach as a familial adenomatous polyposis variant. Am J Hum Genet 2016;98:830–842.

51. Carvalho J, Oliveira P, Senz J, et al. Redefinition of familial intestinal gastric cancer: clinical and genetic perspectives. J Med Genet 2021;58:1–11.

52. Vogelaar IP, van der Post RS, van de Vosse E, et al. Gastric cancer in three relatives of a patient with a biallelic IL12RB1 mutation. Fam Cancer 2015;14:89–94.

53. van der Post RS, Oliveira C, Guilford P, Carneiro F. Hereditary gastric cancer: what’s new? Update 2013-2018. Fam Cancer 2019;18:363–367.

54. Lordick F, Carneiro F, Cascinu S, et al. Gastric cancer: ESMO clinical practice guideline for diagnosis, treatment and follow-up. Ann Oncol 2022;33:1005–1020.

55. Allum W, Lordick F, Alsina M, et al. ECCO essential requirements for quality cancer care: oesophageal and gastric cancer. Crit Rev Oncol Hematol 2018;122:179–193.

56. Aziz S, Rasheed F, Zahra R, König S. Gastric cancer pre-stage detection and early diagnosis of gastritis using serum protein signatures. Molecules 2022;27:2857.

57. Aoyama T, Hutchins G, Arai T, et al. Identification of a high-risk subtype of intestinal-type Japanese gastric cancer by quantitative measurement of the luminal tumor proportion. Cancer Med 2018;7:4914–4923.

58. Lee D, Ham IH, Son SY, Han SU, Kim YB, Hur H. Intratumor stromal proportion predicts aggressive phenotype of gastric signet ring cell carcinomas. Gastric Cancer 2017;20:591–601.

59. Kather JN, Pearson AT, Halama N, et al. Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer. Nat Med 2019;25:1054–1056.

60. Iizuka O, Kanavati F, Kato K, Rambeau M, Arihiro K, Tsuneki M. Deep learning models for histopathological classification of gastric and colonic epithelial tumours. Sci Rep 2020;10:1504.

61. Yoshida H, Shimazu T, Kiyuna T, et al. Automated histological classification of whole-slide images of gastric biopsy specimens. Gastric Cancer 2018;21:249–257.

62. Ying L, Yan F, Meng Q, et al. Understanding immune phenotypes in human gastric disease tissues by multiplexed immunohistochemistry. J Transl Med 2017;15:206.

63. Huang YK, Wang M, Sun Y, et al. Macrophage spatial heterogeneity in gastric cancer defined by multiplex immunohistochemistry. Nat Commun 2019;10:3928.

64. Lone SN, Nisar S, Masoodi T, et al. Liquid biopsy: a step closer to transform diagnosis, prognosis and future of cancer treatments. Mol Cancer 2022;21:79.

65. Lengyel CG, Hussain S, Trapani D, et al. The emerging role of liquid biopsy in gastric cancer. J Clin Med 2021;10:2108.

66. Pectasides E, Stachler MD, Derks S, et al. Genomic heterogeneity as a barrier to precision medicine in gastroesophageal adenocarcinoma. Cancer Discov 2018;8:37–48.

67. Li Y, Zhang X, Liu D, et al. Evolutionary expression of HER2 conferred by chromosome aneuploidy on circulating gastric cancer cells contributes to developing targeted and chemotherapeutic resistance. Clin Cancer Res 2018;24:5261–5271.

68. Shimada H, Noie T, Ohashi M, Oba K, Takahashi Y. Clinical significance of serum tumor markers for gastric cancer: a systematic review of literature by the Task Force of the Japanese Gastric Cancer Association. Gastric Cancer 2014;17:26–33.

69. Matsuoka T, Yashiro M. Biomarkers of gastric cancer: current topics and future perspective. World J Gastroenterol 2018;24:2818–2832.

70. Sato Y, Okamoto K, Kawano Y, et al. Novel biomarkers of gastric cancer: current research and future perspectives. J Clin Med 2023;12:4646.

71. Arienti C, Pignatta S, Tesei A. Epidermal growth factor receptor family and its role in gastric cancer. Front Oncol 2019;9:1308.

72. Boku N. HER2-positive gastric cancer. Gastric Cancer 2014;17:1–12.

73. Rüschoff J, Hanna W, Bilous M, et al. HER2 testing in gastric cancer: a practical approach. Mod Pathol 2012;25:637–650.

74. Abrahao-Machado LF, Scapulatempo-Neto C. HER2 testing in gastric cancer: an update. World J Gastroenterol 2016;22:4619–4625.

75. Dang HZ, Yu Y, Jiao SC. Prognosis of HER2 over-expressing gastric cancer patients with liver metastasis. World J Gastroenterol 2012;18:2402–2407.

76. Tanner M, Hollmén M, Junttila TT, et al. Amplification of HER-2 in gastric carcinoma: association with Topoisomerase IIα gene amplification, intestinal type, poor prognosis and sensitivity to trastuzumab. Ann Oncol 2005;16:273–278.

77. Han Y, Liu D, Li L. PD-1/PD-L1 pathway: current researches in cancer. Am J Cancer Res 2020;10:727–742.

78. Derks S, Liao X, Chiaravalli AM, et al. Abundant PD-L1 expression in Epstein-Barr virus-infected gastric cancers. Oncotarget 2016;7:32925–32932.

79. Ma C, Patel K, Singhi AD, et al. Programmed death-ligand 1 expression is common in gastric cancer associated with Epstein-Barr virus or microsatellite instability. Am J Surg Pathol 2016;40:1496–1506.

80. Gu L, Chen M, Guo D, et al. PD-L1 and gastric cancer prognosis: a systematic review and meta-analysis. PLoS One 2017;12:e0182692.

81. Aaltonen LA, Peltomäki P, Leach FS, et al. Clues to the pathogenesis of familial colorectal cancer. Science 1993;260:812–816.

82. Pinto M, Oliveira C, Machado JC, et al. MSI-L gastric carcinomas share the hMLH1 methylation status of MSI-H carcinomas but not their clinicopathological profile. Lab Invest 2000;80:1915–1923.

83. Yoon K, Lee S, Han TS, et al. Comprehensive genome- and transcriptome-wide analyses of mutations associated with microsatellite instability in Korean gastric cancers. Genome Res 2013;23:1109–1117.

84. dos Santos NR, Seruca R, Constância M, Seixas M, Sobrinho-Simões M. Microsatellite instability at multiple loci in gastric carcinoma: clinicopathologic implications and prognosis. Gastroenterology 1996;110:38–44.

85. Pötzsch M, Berg E, Hummel M, et al. Better prognosis of gastric cancer patients with high levels of tumor infiltrating lymphocytes is counteracted by PD-1 expression. Oncoimmunology 2020;9:1824632.

86. Yashiro M, Matsuoka T. Fibroblast growth factor receptor signaling as therapeutic targets in gastric cancer. World J Gastroenterol 2016;22:2415–2423.

87. Schrumpf T, Behrens HM, Haag J, Krüger S, Röcken C. FGFR2 overexpression and compromised survival in diffuse-type gastric cancer in a large central European cohort. PLoS One 2022;17:e0264011.

88. Nagatsuma AK, Aizawa M, Kuwata T, et al. Expression profiles of HER2, EGFR, MET and FGFR2 in a large cohort of patients with gastric adenocarcinoma. Gastric Cancer 2015;18:227–238.

89. Kim HD, Choi E, Shin J, et al. Clinicopathologic features and prognostic value of claudin 18.2 overexpression in patients with resectable gastric cancer. Sci Rep 2023;13:20047.

90. Shah MA, Shitara K, Ajani JA, et al. Zolbetuximab plus CAPOX in CLDN18.2-positive gastric or gastroesophageal junction adenocarcinoma: the randomized, phase 3 GLOW trial. Nat Med 2023;29:2133–2141.

91. Cao W, Xing H, Li Y, et al. Claudin18.2 is a novel molecular biomarker for tumor-targeted immunotherapy. Biomark Res 2022;10:38.

92. Wagner AD, Syn NL, Moehler M, et al. Chemotherapy for advanced gastric cancer. Cochrane Database Syst Rev 2017;8:CD004064.

93. Yamada Y, Boku N, Mizusawa J, et al. Docetaxel plus cisplatin and S-1 versus cisplatin and S-1 in patients with advanced gastric cancer (JCOG1013): an open-label, phase 3, randomised controlled trial. Lancet Gastroenterol Hepatol 2019;4:501–510.

94. Bang YJ, Van Cutsem E, Feyereislova A, et al. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet 2010;376:687–697.

95. Tabernero J, Hoff PM, Shen L, et al. Pertuzumab, trastuzumab, and chemotherapy in HER2-positive gastric/gastroesophageal junction cancer: end-of-study analysis of the JACOB phase III randomized clinical trial. Gastric Cancer 2023;26:123–131.

96. Tabernero J, Hoff PM, Shen L, et al. Pertuzumab plus trastuzumab and chemotherapy for HER2-positive metastatic gastric or gastrooesophageal junction cancer (JACOB): final analysis of a doubleblind, randomised, placebo-controlled phase 3 study. Lancet Oncol 2018;19:1372–1384.

97. Janjigian YY, Shitara K, Moehler M, et al. First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric, gastro-oesophageal junction, and oesophageal adenocarcinoma (CheckMate 649): a randomised, open-label, phase 3 trial. Lancet 2021;398:27–40.

98. Kono K. Advances in cancer immunotherapy for gastroenterological malignancy. Ann Gastroenterol Surg 2018;2:244–245.

99. Yarchoan M, Hopkins A, Jaffee EM. Tumor mutational burden and response rate to PD-1 inhibition. N Engl J Med 2017;377:2500–2501.

100. Stein A, Paschold L, Tintelnot J, et al. Efficacy of ipilimumab vs FOLFOX in combination with nivolumab and trastuzumab in patients with previously untreated ERBB2-positive esophagogastric adenocarcinoma: the AIO INTEGA randomized clinical trial. JAMA Oncol 2022;8:1150–1158.

101. Refolo MG, Lotesoriere C, Lolli IR, Messa C, D’Alessandro R. Molecular mechanisms of synergistic action of ramucirumab and paclitaxel in gastric cancers cell lines. Sci Rep 2020;10:7162.

102. Simons M, Gordon E, Claesson-Welsh L. Mechanisms and regulation of endothelial VEGF receptor signalling. Nat Rev Mol Cell Biol 2016;17:611–625.

103. Fuchs CS, Tomasek J, Yong CJ, et al. Ramucirumab monotherapy for previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (REGARD): an international, randomised, multicentre, placebo-controlled, phase 3 trial. Lancet 2014;383:31–39.

104. Wilke H, Muro K, Van Cutsem E, et al. Ramucirumab plus paclitaxel versus placebo plus paclitaxel in patients with previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (RAINBOW): a double-blind, randomised phase 3 trial. Lancet Oncol 2014;15:1224–1235.

105. Fuchs CS, Shitara K, Di Bartolomeo M, et al. Ramucirumab with cisplatin and fluoropyrimidine as first-line therapy in patients with metastatic gastric or junctional adenocarcinoma (RAINFALL): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Oncol 2019;20:420–435.

106. Khan KA, Kerbel RS. Improving immunotherapy outcomes with anti-angiogenic treatments and vice versa. Nat Rev Clin Oncol 2018;15:310–324.

107. Tada Y, Togashi Y, Kotani D, et al. Targeting VEGFR2 with ramucirumab strongly impacts effector/activated regulatory T cells and CD8+ T cells in the tumor microenvironment. J Immunother Cancer 2018;6:106.

108. Sahin U, Türeci Ö, Manikhas G, et al. FAST: a randomised phase II study of zolbetuximab (IMAB362) plus EOX versus EOX alone for first-line treatment of advanced CLDN18.2-positive gastric and gastro-oesophageal adenocarcinoma. Ann Oncol 2021;32:609–619.

109. Wainberg ZA, Kang YK, Lee KW, et al. Bemarituzumab as firstline treatment for locally advanced or metastatic gastric/gastroesophageal junction adenocarcinoma: final analysis of the randomized phase 2 FIGHT trial. Gastric Cancer 2024;27:558–570.