[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
JGC is now indexed in MEDLINE!
Open Access, Peer-reviewed
pISSN 2093-582X
eISSN 2093-5641
    J Gastric Cancer. 2025 Jan;25(1):192-209. English.
    Published online Dec 23, 2024.
    https://doi.org/10.5230/jgc.2025.25.e3
    Copyright © 2025. Korean Gastric Cancer Association
    Review

    Spatial and Temporal Tumor Heterogeneity in Gastric Cancer: Discordance of Predictive Biomarkers

    Hye Seung Lee
      • Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
    • Correspondence to Hye Seung Lee. Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul 03080, Korea. Email: hye2@snu.ac.kr
    Received November 13, 2024; Accepted December 09, 2024.

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

    Abstract

    Gastric cancer (GC) is a highly heterogeneous disease that varies in both histological presentation and genetic characteristics. Recent advances in the treatment of metastatic and unresectable GC have made several biomarker tests essential for patient management. Predictive biomarkers such as human epidermal growth factor receptor 2 (HER2), programmed death-ligand 1 (PD-L1), mismatch-repair (MMR) proteins, claudin 18.2, and fibroblast growth factor receptor 2b (FGFR2b) are commonly evaluated using immunohistochemistry. However, the expression levels of these biomarkers may vary across different tumor areas, and the accuracy of biomarker diagnosis can be affected by sample quantity, sample location, and collection method. Therefore, tumor heterogeneity presents substantial challenges for accurate biomarker-based diagnosis and prediction of therapeutic responses. Tumor heterogeneity can be categorized into spatial heterogeneity, which refers to variations within the primary tumor (intra-tumoral) or between primary and metastatic sites, and temporal heterogeneity, which encompasses changes over time. This review addresses the tumor heterogeneity in predictive biomarker expression in GC, focusing on HER2, PD-L1, MMR, the Epstein–Barr virus, claudin 18.2, and FGFR2b.

    Keywords
    Gastric cancer; Tumor heterogeneity; Biomarker

    INTRODUCTION

    Intra-and inter-tumoral heterogeneity are frequently observed in the histology of gastric cancer (GC), and histological type is typically determined based on the dominant histological component within the largest tumor area [1]. Mixed adenocarcinoma, for example, is characterized by a combination of distinct glandular and poorly cohesive histological components [1, 2]. In addition to histological variability, recent studies have highlighted considerable heterogeneity in biomarker expression in GC.

    Tumor heterogeneity can be categorized into spatial and temporal heterogeneity [3, 4]. Spatial heterogeneity is further divided as follows: 1) intra-tumoral heterogeneity, which occurs within the same tumor; 2) differences between the primary tumor and its metastases; and 3) heterogeneity among metastatic sites (Fig. 1A). Human cancers comprise genetically and phenotypically distinct subclones that arise throughout tumor progression [5]. These subclones lead to genetic and phenotypic variability within the same tumor or between multiple sites via diverse mechanisms. Genomic instability, triggered by exogenous or endogenous carcinogenic factors, is suggested to be one of the main drivers of tumor heterogeneity [4, 6]. This instability can evoke genetic diversity at the single-nucleotide, long-sequence, or chromosomal level, although other promoting factors in addition to genomic instability are necessary to generate clonal diversity [7].

    Fig. 1
    Spatial and temporal heterogeneity. (A) Spatial heterogeneity refers to heterogeneous positivity within the primary tumor, discordance between the primary and matched metastatic tumors, or discordance among metastatic sites. (B) Temporal heterogeneity refers to changes in genetic features over time, either due to the natural progression of the tumor or response to treatment.

    In contrast, temporal heterogeneity refers to changes over time, either owing to the natural progression of the tumor or as a response to treatment (Fig. 1B). Longitudinal tissue sampling has demonstrated clonal evolution and genetic alterations in response to treatment [8, 9]. Temporal heterogeneity is believed to stem from the survival and proliferation of pre-existing treatment-resistant subclones or emergence of drug-tolerant cells [4]. This type of heterogeneity is a major cause of resistance to targeted drugs and affects treatment decisions as the genetic profile of the tumor evolves.

    Tumor heterogeneity poses considerable challenges for accurate biomarker assessment from small biopsy samples, which may not represent the entire primary tumor or overall tumor burden in the patient. Clinically, heterogeneity complicates biomarker-based diagnoses and contributes to resistance to targeted therapies and immunotherapies [4, 10].

    Trastuzumab, which targets human epidermal growth factor receptor 2 (HER2), has been approved for use in combination with chemotherapy as a first-line treatment for metastatic or unresectable GC, based on the success of the Trastuzumab for GAstric cancer (ToGA) trial [11]. Recently, immunotherapies that target the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis, such as nivolumab and pembrolizumab, have also been approved for use alongside chemotherapy and/or trastuzumab [12, 13, 14]. Therefore, testing for HER2 and PD-L1 expression using immunohistochemistry (IHC) is critical for guiding initial treatment decisions in patients with GC. Additionally, assessing microsatellite instability (MSI)/mismatch-repair (MMR) status and Epstein–Barr virus (EBV) infection via in situ hybridization (ISH) may be essential in determining second-line or subsequent treatment [15]. New biomarkers of GC have recently emerged from clinical trials. Phase-3 trials have shown promising results for zolbetuximab targeting claudin 18.2 (CLDN18.2) in patients with CLDN18.2-positive GC [16, 17]. Consequently, CLDN18.2 has become a critical biomarker in GC treatment. A phase-2 study similarly demonstrated the efficacy of an anti-fibroblast growth factor receptor 2b (FGFR2b) monoclonal antibody in patients with FGFR2b-positive GC [18].

    This review discusses tumor heterogeneity in relation to predictive biomarkers, including HER2, PD-L1, MSI/MMR, EBV, CLDN18.2, and FGFR2b, focusing on spatial and temporal heterogeneity. The clinical implications of tumor heterogeneity for biomarker-based diagnosis and therapeutic selection are also addressed.

    HER2 HETEROGENEITY

    Intra-tumoral heterogeneity

    In the trastuzumab-based first-line treatment of metastatic or unresectable GC, HER2 positivity is defined as either strong membranous staining on IHC (3+) or weak-to-moderate staining (2+) with HER2 amplification [1]. A HER2-positive area is defined as positivity in ≥10% of tumor cells in a resected specimen or as a cluster of ≥5 HER2-positive tumor cells in a biopsy sample [1]. HER2 positivity has been observed in approximately 9.8%–23.0% of patients in Asian populations [19]. Initial studies reported controversial results regarding the spatial heterogeneity of HER2 positivity (Table 1). For example, one study described discordance rates of 1.5% and 5.1% between primary tumors and matched metastases when assessed using HER2 gene fluorescence ISH (FISH) and HER2 IHC, respectively [22]. Another study identified intra-tumoral heterogeneity in 2.5% of cases using HER2 FISH and 14.5% using IHC in a cohort of 325 individuals [20]. Both studies indicated that 80–90% of GC cases were HER2-negative, suggesting a homogeneous expression pattern; however, HER2 heterogeneity was likely underestimated given that it was calculated across all GC cases.

    Table 1
    Published results for tumor heterogeneity in HER2 expression

    Subsequent studies focused on heterogeneity only among HER2-positive GC cases and demonstrated substantial heterogeneity in HER2 positivity, although their definitions of heterogeneity varied (Table 1, Fig. 2). In our previous study, intra-tumoral heterogeneity was defined as HER2 overexpression or gene amplification in 5%–50% of the tumor area, which we identified in 74.0% (54) and 41.1% (30) of cases using IHC and FISH, respectively, among 73 cases with IHC scores of 2+ or 3+ [27]. These results are consistent with those of other studies. For instance, in tissue microarray (TMA) analyses, HER2 heterogeneity between different tissue cores was observed in 70.6% (36/51 cases) of GCs with IHC scores of 2+ and 3+ in one study [26] and 33.3% (21/63) in another [21]. Additionally, intra-tumoral heterogeneity was detected in 50.0% of patients when defined as 2+ or 3+ HER2 staining in some but not all tumor cells [32]. Regional heterogeneity in HER2 IHC expression—defined as 10%–70% positive cells—was found in 42.9% (79/184) of IHC 3+ and 70.5% (31/44) of IHC 2+ cases [30]. Finally, when characterized as HER2 positivity in 10–66% of tumor cells, heterogeneity was present in 50% of HER2-positive GC cases [31].

    Fig. 2
    Intra-tumoral HER2 heterogeneity. (A) A HER2-positive case had a score of 3+ in the poorly differentiated adenocarcinoma area, whereas the poorly cohesive and mucinous adenocarcinoma area was negative. (B) A HER2-positive case had a 3+ score in areas of lower-grade histology, whereas the high-grade areas were negative. (C) HER2 positivity was identified in one of four biopsy fragments, with HER2 gene amplification observed in the pictured fragment.
    HER2 = human epidermal growth factor receptor 2.

    HER2 gene amplification has also been investigated, with a study reporting heterogeneity (amplification in <50% of tumor cells) in 41.2% (21/51) of HER2-amplified tumors [28]. Additionally, amplification heterogeneity between different TMA cores was observed in 47.3% (9/19) of HER2-amplified cases [29].

    Comparison between biopsy and surgical resection

    In patients with initially metastatic GC, endoscopic biopsy specimens are usually the only tissues available for HER2 testing. However, owing to the considerable heterogeneity in HER2 expression in GC, discrepancies between biopsy and surgical specimens can pose substantial challenges in HER2-targeted therapies. In a study that examined matched biopsy and resection specimens from 128 patients with GC, 5 of the 18 HER2-positive cases (27.8%) had discordant results: two cases were positive only on biopsy and three only on resection [23]. Another study that compared HER2 status between biopsy and resection specimens in a larger cohort of 702 patients with GC identified 86 discrepant cases (12.3% of all cases and 54.1% of 159 HER2-positive cases), with 57 cases positive on biopsy and 29 on resection [24].

    Therefore, several studies have sought to identify the optimal number of biopsy fragments required to reduce the amount of false-negative and -positive results. Ahn et al. [24] recommended the use of at least four biopsy fragments containing tumor cells to accurately determine HER2 status in GC, whereas another study suggested a minimum of five fragments for reliable assessment [33]. Additionally, some researchers have proposed that the use six to eight viable fragments is optimal [34]. Based on these findings, the guidelines of the College of American Pathologists, American Society for Clinical Pathology, and American Society of Clinical Oncology recommend obtaining a minimum of five biopsy specimens (ideally six to eight) to ensure sufficient tumor sampling for accurate diagnosis and biomarker testing [35].

    Discordance between primary and metastatic tumors

    In addition to intra-tumoral heterogeneity, discordance in HER2 positivity between primary and metastatic GCs has been observed, with reported rates ranging from 1% to 14% [15]. Fassan et al. [25] identified a high concordance rate between the HER2 statuses of primary tumors and matched lymph-node metastases, reporting only a 2.1% discordance. Another study found a 14.3% discordance in HER2 status between primary tumors and synchronous metastases (22/154 cases) [26]. Notably, when HER2-negative and 1+ cases were excluded, the discordance rate increased to 62.9% (22/35), with six cases showing positive conversion (negativity in primary tumor but positivity in lymph-node metastasis) and sixteen exhibiting negative conversion [26]. In another study, discordance between primary tumors and paired metastatic lymph nodes was observed in 11.3% of cases assessed using HER2 IHC and 7.2% via silver ISH [21]. These discordance rates increased considerably to 50.0% and 38.9%, respectively, when calculated only for cases with HER2 IHC scores of 2+ or 3+ or those with HER2 amplification [21].

    Kim et al. [20] suggested that these discrepancies between primary and metastatic tumors may originate from heterogeneity within the primary tumor. Additionally, genetic drift or clonal selection during tumor progression might contribute to these differences [36]. Given the spatial heterogeneity observed within primary tumors and between primary and metastatic lesions, incorporating additional HER2 testing of both site types could enhance diagnostic accuracy and reliability.

    Clinical significance of HER2 heterogeneity

    GC with intra-tumoral HER2 heterogeneity tends to exhibit diffuse or mixed histological types according to the Lauren classification, and generally has low levels of HER2 expression (IHC 2+) or HER2 gene amplification [27, 30]. HER2 is a key oncogenic driver associated with aggressive disease. Although some studies have found correlations between HER2 positivity and poor outcomes in GC, others have failed to confirm its prognostic value [19, 21]. Therefore, the predictive significance of HER2 positivity in GC remains unclear. Furthermore, whether patients with heterogeneous HER2-positive GC experience better or worse outcomes than those with homogeneous HER2-positive GC is still unknown [27, 37].

    In contrast, heterogeneous HER2 positivity in patients with GC that received trastuzumab with chemotherapy as the first-line treatment has been linked to limited clinical benefits, including reduced response and shorter survival times [38]. The median progression-free (PFS) and overall survival (OS) were notably longer in patients with homogeneous HER2-positive GC than in those with heterogeneous HER2-positive GC, and multivariate analyses indicated significant associations between HER2 heterogeneity and poor PFS and OS [32, 39, 40]. Regarding treatment response rate, one study identified no significant difference between homogeneous and heterogeneous HER2-positive disease [32]; however, other studies have reported greater responses in patients with homogeneous HER2 positivity [39, 40]. Therefore, HER2 heterogeneity potentially contributes to trastuzumab resistance.

    In the GASTric cancer HER2 re-assessment study 1 (GASTHER1), “rescued” HER2 positivity was identified in 16 of 183 (8.7%) and 10 of 175 (5.7%) patients with initial HER2 negativity via repeated endoscopic biopsy and re-assessment of metastatic or recurrent lesions, respectively [41]. Compared with patients that were HER2-positive on the initial testing of primary tumors, those with rescued HER2 positivity achieved similar overall responses to trastuzumab-based first-line chemotherapy and comparable PFS [41]. However, a subsequent study that included a larger cohort and longer follow-up reported significantly worse PFS and OS in patients with rescued HER2 positivity than in those with initial positivity, likely due to HER2 heterogeneity in the rescued group [42].

    Circulating tumor DNA tests using digital polymerase chain reaction (PCR) or next-generation sequencing have been explored as alternative HER2 assessment methods, and the sensitivity of digital PCR ranged from 37.5% to 76.5% in previous studies [43, 44, 45]. Despite their potential as alternative HER2 tests, these techniques are not used in standard practice because of their relatively low sensitivity and high costs. Recently, antibody-drug conjugates such as trastuzumab-deruxtecan have been introduced to treat GC [46]. These drugs may improve responses in HER2-heterogenous GC by utilizing a bystander effect, in which HER2-targeted agents affect HER2-negative cells adjacent to positive cells [47]. In addition, pembrolizumab-based immunotherapy has been approved as a first-line treatment for HER2-positive GC, and a PD-L1 combined positive score (CPS) ≥1 was observed in 85% of patients with HER2-positive GC that underwent this treatment in the phase-3 KEYNOTE-811 trial [13]. As new treatment regimens continue to emerge for patients with HER2-positive GC, the relevance of HER2 heterogeneity is expected to grow.

    Temporal heterogeneity

    Trastuzumab targets and kills HER2-positive cancer cells, allowing for the proliferation of HER2-negative cells, which may contribute to the acquired resistance to trastuzumab-based treatments [15]. In a study that compared IHC results from the pre-treatment biopsies and post-treatment surgical samples of individuals with HER2-positive GC, HER2-negative conversion following trastuzumab-based chemotherapy was reported in three of the seven patients (42.9%) [48]. However, since pre- and post-treatment samples were obtained from biopsies and resections, respectively, the observed loss of HER2 expression in this study reflects either treatment effects or pre-existing heterogeneity [48].

    Several studies have investigated the loss of HER2 positivity by examining pre- and post-treatment biopsies following tumor progression. In one study, 31.6% (6/19) of patients lost HER2 positivity after trastuzumab-based first-line chemotherapy, and this loss was more frequent in initial IHC 2+ than in IHC 3+ cases (80.0% vs. 14.3%, respectively) [49]. Similarly, in the GASTHER3 study, 14 of 48 (29.2%) patients lost HER2 positivity according to post-progression biopsies, and the median H-score for these samples was significantly lower than that for pre-treatment biopsies [50]. Another research group reported an even higher rate of HER2 positivity loss, with 60.6% (20/33) of patients with refractory disease having exhibited decreased HER2 expression after treatment [51].

    The GASTHER3 study further highlights the clinical impact of HER2 loss, having observed that although the reduction was not significantly associated with patient outcomes, individuals with reduced HER2 positivity in post-progression samples had no objective response to second-line treatment with trastuzumab emtansine [50]. Therefore, trastuzumab-induced changes in HER2 expression in GC may not only contribute to drug resistance, but also influence the choice of second-line treatment. Consequently, re-assessment of HER2 status prior to the initiation of second-line or subsequent HER2-targeted therapy is recommended if post-progression samples are available [52].

    PD-L1

    PD-L1 expression is highly heterogeneous within tumors in patients with GC (Fig. 3). According to the guidelines for PD-L1 IHC interpretation, the CPS should be averaged across the entire tumor area to determine the final score [53]. Therefore, the consideration of tumor heterogeneity is crucial when diagnosing PD-L1 positivity and making immunotherapy decisions for patients with GC.

    Fig. 3
    Intra-tumoral PD-L1 heterogeneity was observed in gastric cancer, with PD-L1 combined positive scores ≥10 (A) and ≥1 and <5 (B and C).
    PD-L1 = programmed death-ligand 1.

    Previous studies have reported higher PD-L1 positivity rates in surgically resected samples than in biopsies, with false negatives being more common in biopsy samples. In a study that compared PD-L1 expression between 112 gastric biopsy samples and matched gastrectomy specimens, CPS ≥1 was observed in 32.1% of biopsies versus 47.3% of gastrectomy samples, with biopsy sensitivity and specificity of 62% and 73%, respectively, in predicting PD-L1 expression in the gastrectomy specimens [54]. Similarly, in 99 patients with advanced GC, biopsy and gastrectomy pairs exhibited 86% concordance in PD-L1 CPS ≥1 when assessed using the 22C3 pharmDx assay, with 13 false-negative and no false-positive cases [55]. Another study reported PD-L1 positivity in 46.6% of biopsies and 70.1% of resected samples, with false-negative and -positive biopsy rates of 29.8% and 5.8%, respectively [56].

    To improve the accuracy of PD-L1 testing, an adequate number of viable endoscopic biopsies is necessary. This is because the concordance between biopsy and resected specimens is reportedly lower in cases with single-fragment biopsy (48.8%) than in those with multiple fragments (68.9%) [56]. In TMA analyses, combining the CPS for four TMA cores (1.2-mm diameter) yielded results closely aligned with those for resected samples, although the inclusion of fewer cores reduced sensitivity and increased the number of false negatives [57]. In another study that assessed six TMA cores from each gastrectomy specimen, the consistency of PD-L1 positivity between cores and resected samples improved as the number of cores increased, with five identified as being optimal for representational accuracy [58]. These findings suggest that at least four to five biopsy fragments are required to reliably assess PD-L1 expression in GC [59].

    Discordance of PD-L1 expression between primary and metastatic tumors is also evident. In paired baseline primary and metastatic tumors, concordance in PD-L1 CPS ≥1 and ≥10 was observed in 61.3% (38/62) and 83.9% of cases, respectively [60]. Another study identified a PD-L1 CPS ≥ 1 in 52.2% of primary tumors (12/23) but only 4.3% of distant metastases (1/23); however, this analysis was limited by the small sample size and inclusion of metachronous metastasis [61]. Interestingly, the PD-L1 expression in tumor-infiltrating immune cells was higher in lymph-node metastases (54.4%) than in primary tumors (41.6%) [62], with a similar trend reported in another study (60.5% vs. 41.9%, respectively) [63].

    Temporal heterogeneity, or post-chemotherapeutic variation in PD-L1 expression, has also been observed in GC. In one study, the PD-L1 immunoreactivity scores (IRS) decreased following chemotherapy; positivity (IRS ≥2) was reduced from 58.3% (42/76) in pre-treatment samples to 41.7% (30/72) in post-treatment samples, with a 50% concordance rate between pre-and post-treatment samples [64]. Another study revealed that the PD-L1 status (CPS ≥1) of pre-treatment primary tumors was concordant with those of post-treatment primary or metastatic samples in 62.7% (52/83) of cases, with an increased rate of 74.7% (62/83) for CPS ≥10 [60]. The concordance rates were not affected by the chemotherapeutic regimens used. PD-L1 positivity with a cutoff of CPS = 1 was identified in 54.2% of pre- and 53.0% of post-treatment samples in this study [60].

    Therefore, the spatial and temporal heterogeneity in PD-L1 expression should be carefully considered in clinical practice. The re-evaluation of PD-L1 IHC in recurrent or metastatic tumors may be helpful for accurate PD-L1 assessment in patients with GC.

    MSI/MMR

    In daily practice, MSI testing is performed using PCR with five microsatellite markers [65]. For molecular testing, DNA is typically extracted from tumor cells after macro-dissection of the entire tumor area, with a sensitivity or limit of detection of approximately 10% for MSI analysis [66]. Therefore, PCR-based MSI analysis is restricted in detecting intra-tumoral heterogeneity. In contrast, MMR status can be assessed using IHC in four MMR proteins—mutL homolog 1 (MLH1), mutS homologs 2 (MSH2) and 6 (MSH6), and post-meiotic segregation increased 2 (PMS2)—allowing the estimation of heterogeneity in MMR protein expression. The IHC analysis of MMR proteins is advantageous due to its cost-effectiveness and availability; however, it also has limitations, including indeterminate diagnoses due to ambiguous staining [67]. Thus, the heterogeneity in MMR expression identified on IHC may be underestimated.

    A previous study reported no intra-tumoral heterogeneity in the MMR status between the tumor front and center in 415 GC cases [68]. Another study described a high level of instability (MSI-H) detected using PCR in 187 of the 3,723 cases (5.1%) and heterogeneous MMR protein expression within the primary GC area in 11 cases (0.3%) [69]. Additionally, a single instance of heterogeneous MSH2 expression loss in 452 GC cases (0.2%) was reported, corresponding to 2.9% of 34 MSI-H GC cases [70]. In our previous study, we observed subclonal loss of MLH1 expression in 0.4% of all GC cases (24/5676) and 4.3% of 549 MSI-H cases [67]. In contrast, Kim et al. [71] conducted multi-regional sampling of 79 deficient MMR (dMMR) or MSI-H tumors from patients with advanced GC and revealed a heterogeneous MSI status in 8.9%, suggesting that a subset of MSI-H or dMMR tumors exhibits significant heterogeneity. Interestingly, one of six patients with MSI-H GC showed no response in a small phase-2 trial of single-agent pembrolizumab treatment, which was associated with the heterogeneous loss of MLH1 expression [71]. Overall, intra-tumoral heterogeneity in MSI/MMR is rare in GC, occurring in less than 1% of all cases; however, among MSI-H cases, its incidence may be as high as 8.9%.

    A few studies have examined the MSI/MMR concordance between primary and metastatic tumors (Fig. 4). Recently, a discordant case with MSS in the primary tumor and MSI-H in an ovarian metastasis was identified [69]. Another study documented a GC case with dMMR at the primary site and proficient MMR in synchronous skin metastases; overall, dMMR was more common in primary (8.7%, 2/23) than in paired metastatic GC (4.3%, 1/23) [61]. However, full concordance in MSI/MMR status was observed in a study that analyzed 269 primary GCs with matched metastatic lymph nodes and 98 with matched distant metastases [68]. Although rare, discordance between primary and metastatic tumors should not be overlooked.

    Fig. 4
    Tumor heterogeneity in MLH1 expression. A focal area with MLH1 loss was identified (A and B), whereas MLH1 expression was retained in the lymph-node metastasis of the same patient (C). In another patient, MLH1 expression was lost in an endoscopic biopsy sample (D) but present in a metastatic tumor (supraclavicular lymph node) (E).
    MLH1 = mutL homolog 1.

    EBV

    ISH for EBV-encoded RNA (EBER) is considered the gold standard for detecting and localizing latent EBV in GC tissue samples. Typically, EBER ISH exhibits diffuse nuclear positivity in EBV-associated GC, supporting the hypotheses that EBV infection may influence GC carcinogenesis and that EBV-associated GC is a monoclonal proliferation originating from a single cell persistently infected with EBV [72]. Further substantiating these hypotheses, consistent EBV status was observed between the tumor front and center in 415 cases [68]. Additionally, the EBV status of primary tumors was preserved in metastatic lymph nodes (n=284) and distant metastases (n=103), although only 11 cases were EBV-positive [68].

    In contrast, rare instances of heterogeneous EBER positivity have been reported. In one study, heterogeneous EBV positivity was identified in four cases, representing 0.8% of 484 GC cases and 18.2% of 22 EBV-positive cases; moreover, heterogeneity was also observed in paired lymph-node metastases [73]. In a more recent study, heterogeneous EBV positivity was identified in four GC cases, accounting for 0.1% of 3,499 consecutive surgical cases and 1.9% of 214 EBV-positive cases [74]. Among these four cases, three exhibited two histologically distinct regions, with the EBV-positive area being poorly differentiated and displaying lymphocytic infiltration [74]. Therefore, although heterogeneous EBV positivity in GC is rarely observed in clinical practice, it raises questions about whether this phenomenon reflects a genuine loss of EBV infection, reduced EBV transcription, or a mix of EBV-positive and -negative tumor populations [73].

    CLDN18.2

    Positivity rates for CLDN18.2 in GC have been reported to vary widely, ranging from 14% to 88% depending on the testing protocols and positivity criteria applied [75]. Currently, CLDN18.2 positivity is defined as ≥75% of tumor cells showing moderate-to-strong membranous staining with the 43-14A antibody on IHC, as established in the SPOTLIGHT and GLOW clinical trials [75]. CLDN18.2 expression in the GC tumor area varies considerably: 27% of cases in clinical trials had no expression, 22% had low expression (≥1% and <40%), 13% had moderate expression (≥40% and <75%), and 38% had high expression (≥75%) [76], indicating substantial heterogeneity in CLDN18.2 expression within a single tumor (Fig. 5).

    Fig. 5
    Intra-tumoral CLDN18.2 heterogeneity. (A) Homogeneous expression of CLDN18.2. (B) A CLDN18.2-positive case with a heterogeneous expression pattern. (C) A CLDN18.2-negative case with a heterogeneous expression pattern.
    CLDN18.2 = claudin 18.2.

    Defining intra-tumoral CLDN18.2 heterogeneity is challenging because of its positivity threshold of 75%, which is stricter than those for other biomarkers. In comparison, the respective definitions of HER2 heterogeneity in previous studies were positivity in 10%–50%, 33%–66%, or 10%–90% of the tumor area. In a recent study, 299 stage I–III GC cases were analyzed, 46.5% (139 cases) of which were positive for CLDN18.2 [77]. Of the 139 CLDN18.2-positive cases, 31.0% (43) had heterogeneous expression (75%–90% positivity), with most (40) exhibiting a random expression pattern [77]. In a study on gastrectomy samples, intra-tumoral CLDN18.2 heterogeneity (again defined as 75%–90% positivity) was identified in 38.5% of 32 CLDN18.2-positive samples [78]. When comparing biopsy and surgical specimens, the concordance rate of CLDN18.2 positivity was 81.3%, with a tendency for increased positivity in superficial areas than in the invasive front [79].

    In our recent study, we constructed TMA blocks with four 2-mm diameter cores for each case and compared CLDN18.2 positivity across these four cores [80]. Heterogeneous intra-tumoral CLDN18.2 expression among the cores was identified in 68 cases, representing 23.8% of 286 total GC cases and 61.3% of 111 cases with CLDN18.2 positivity in at least one core. However, when we compared CLDN18.2 positivity between whole-tissue sections and the combined results for all four TMA cores, discordance was observed in only 2.4% (2/85) of cases. These findings suggest that while CLDN18.2 expression is heterogeneous throughout GC tumors, a combined analysis of four TMA cores may provide a representative assessment for each case.

    CLDN18.2 expression differences between primary and metastatic sites have also been examined. The concordance rate between primary tumors and peritoneal metastases was 75.0%, with higher positivity rates in primary tumors than in peritoneal metastases (28.6% [24/84] vs. 20.2% [17/84], respectively) [79]. The concordance across various metastatic sites (peritoneum, liver, lung, bone, and distant lymph nodes) was 74.8% (101/135), with peritoneal metastases showing the highest CLDN18.2 positivity (44.3%) and liver metastases the lowest (17.9%) [78].

    Standardized protocols and interpretation guidelines for CLDN18.2 IHC testing were introduced recently, leaving CLDN18.2 heterogeneity in GC yet to be fully elucidated. Further studies are needed to clarify these patterns according to the prescribed guidelines.

    FGFR2b

    Bemarituzumab, a fucosylated, humanized immunoglobulin G1 anti-FGFR2b monoclonal antibody, was combined with chemotherapy in patients with HER2-negative GC and FGFR2b overexpression, detected via IHC and/or FGFR2 gene amplification assessed using a circulating tumor DNA assay [18, 81, 82]. This phase-2 study reported clinically significant outcomes. Although protocols and interpretation guidelines for FGFR2b IHC or FGFR2 gene testing in routine practice have not yet been standardized, the heterogeneity in FGFR2b expression and FGFR2 amplification have been explored in a few studies. An earlier study identified FGFR2b overexpression via IHC in 2.5% (9/362) of GC cases, with intra-tumoral heterogeneity—defined as discordance among three TMA cores—observed in five of nine FGFR2b-positive cases (55.5%) [83]. Additionally, discordant FGFR2b expression between primary tumors and paired lymph-node metastases was identified in four of nine cases (44.4%), comprising three cases of negative conversion (positive in primary tumors but negative in lymph-node metastases) and one of positive conversion [83]. In an independent study, FGFR2b overexpression was detected in 8.0% (7/88) of cases, with a higher prevalence in metastatic lymph nodes than in primary tumors (8.0% vs. 3.4%, respectively) [84]. Further, a translational study that used cell lines and patient-derived xenograft models demonstrated durable responses only in tumors with high-level clonal FGFR2 amplification; conversely, patients with subclonal heterogeneous FGFR2 amplification did not respond to treatment [85].

    CONCLUSION

    Biomarker expression is not consistent throughout the entire tumor burden, including primary tumors and metastatic sites, and can change after treatment. Spatial and temporal heterogeneity in the expression of key biomarkers is frequently observed in patients with GC. Among these biomarkers, heterogeneity in HER2 is the most extensively studied, with reports estimating intra-tumoral heterogeneity rates of 2.5%–14.5% across all GC cases [20, 21, 23, 24] and 22.6%–74.0% in those with HER2 positivity or gene amplification [21, 26, 27, 28, 30, 31, 32]. Negative conversion of HER2 expression has been observed in post-progression biopsies from 29.2%–60.6% of patients with GC that received trastuzumab-based therapies [48, 49, 50, 51]. Intra-tumoral heterogeneity in MSI/MMR is less common than HER2 heterogeneity in GC; however, patients with MSI heterogeneity have experienced rapid disease progression following immunotherapy [71]. Additionally, heterogeneity has been studied in emerging biomarkers such as CLDN18.2 and FGFR2b. This variability in biomarker expression may lead to diagnostic inaccuracies and limit biomarker-based treatment efficacy. Therefore, tumor heterogeneity should be carefully considered in the management of patients with metastatic or unresectable GC, particularly in the establishment of standardized guidelines for biomarker testing and interpretation.

    Notes

    Funding:This study was supported by the Korea-US Collaborative Cancer R&D Program, funded by the Ministry of Health and Welfare, Republic of Korea (RS-2024-00442017).

    Conflict of Interest:No potential conflict of interest relevant to this article was reported.

    References

      1. Park YS, Kook MC, Kim BH, Lee HS, Kang DW, Gu MJ, et al. A standardized pathology report for gastric cancer: 2nd edition. J Pathol Transl Med 2023;57:1–27.
      1. Joo M, Kim KM. Histologic discrepancy between gastric biopsy and resection specimen in the era of endoscopic treatment for early gastric cancer. Korean J Gastroenterol 2014;64:256–259.
      1. Kuwata T. Molecular classification and intratumoral heterogeneity of gastric adenocarcinoma. Pathol Int 2024;74:301–316.
      1. Dagogo-Jack I, Shaw AT. Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol 2018;15:81–94.
      1. Marusyk A, Almendro V, Polyak K. Intra-tumour heterogeneity: a looking glass for cancer? Nat Rev Cancer 2012;12:323–334.
      1. McGranahan N, Swanton C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell 2015;27:15–26.
      1. Anderson AR, Weaver AM, Cummings PT, Quaranta V. Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment. Cell 2006;127:905–915.
      1. Sequist LV, Waltman BA, Dias-Santagata D, Digumarthy S, Turke AB, Fidias P, et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med 2011;3:75ra26
      1. Hata A, Katakami N, Yoshioka H, Kaji R, Masago K, Fujita S, et al. Spatiotemporal T790M heterogeneity in individual patients with EGFR-mutant non-small-cell lung cancer after acquired resistance to EGFR-TKI. J Thorac Oncol 2015;10:1553–1559.
      1. Bedard PL, Hansen AR, Ratain MJ, Siu LL. Tumour heterogeneity in the clinic. Nature 2013;501:355–364.
      1. Bang YJ, Van Cutsem E, Feyereislova A, Chung HC, Shen L, Sawaki 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.
      1. Janjigian YY, Shitara K, Moehler M, Garrido M, Salman P, Shen L, 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.
      1. Janjigian YY, Kawazoe A, Bai Y, Xu J, Lonardi S, Metges JP, et al. Pembrolizumab plus trastuzumab and chemotherapy for HER2-positive gastric or gastro-oesophageal junction adenocarcinoma: interim analyses from the phase 3 KEYNOTE-811 randomised placebo-controlled trial. Lancet 2023;402:2197–2208.
      1. Rha SY, Oh DY, Yañez P, Bai Y, Ryu MH, Lee J, et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for HER2-negative advanced gastric cancer (KEYNOTE-859): a multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol 2023;24:1181–1195.
      1. Nakamura Y, Kawazoe A, Lordick F, Janjigian YY, Shitara K. Biomarker-targeted therapies for advanced-stage gastric and gastro-oesophageal junction cancers: an emerging paradigm. Nat Rev Clin Oncol 2021;18:473–487.
      1. Shitara K, Lordick F, Bang YJ, Enzinger P, Ilson D, Shah MA, et al. Zolbetuximab plus mFOLFOX6 in patients with CLDN18.2-positive, HER2-negative, untreated, locally advanced unresectable or metastatic gastric or gastro-oesophageal junction adenocarcinoma (SPOTLIGHT): a multicentre, randomised, double-blind, phase 3 trial. Lancet 2023;401:1655–1668.
      1. Shah MA, Shitara K, Ajani JA, Bang YJ, Enzinger P, Ilson D, 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.
      1. Wainberg ZA, Enzinger PC, Kang YK, Qin S, Yamaguchi K, Kim IH, et al. Bemarituzumab in patients with FGFR2b-selected gastric or gastro-oesophageal junction adenocarcinoma (FIGHT): a randomised, double-blind, placebo-controlled, phase 2 study. Lancet Oncol 2022;23:1430–1440.
      1. Kim KM, Bilous M, Chu KM, Kim BS, Kim WH, Park YS, et al. Human epidermal growth factor receptor 2 testing in gastric cancer: recommendations of an Asia-Pacific task force. Asia Pac J Clin Oncol 2014;10:297–307.
      1. Kim MA, Lee HJ, Yang HK, Bang YJ, Kim WH. Heterogeneous amplification of ERBB2 in primary lesions is responsible for the discordant ERBB2 status of primary and metastatic lesions in gastric carcinoma. Histopathology 2011;59:822–831.
      1. Cho EY, Park K, Do I, Cho J, Kim J, Lee J, et al. Heterogeneity of ERBB2 in gastric carcinomas: a study of tissue microarray and matched primary and metastatic carcinomas. Mod Pathol 2013;26:677–684.
      1. Bozzetti C, Negri FV, Lagrasta CA, Crafa P, Bassano C, Tamagnini I, et al. Comparison of HER2 status in primary and paired metastatic sites of gastric carcinoma. Br J Cancer 2011;104:1372–1376.
      1. Wang T, Hsieh ET, Henry P, Hanna W, Streutker CJ, Grin A. Matched biopsy and resection specimens of gastric and gastroesophageal adenocarcinoma show high concordance in HER2 status. Hum Pathol 2014;45:970–975.
      1. Ahn S, Ahn S, Van Vrancken M, Lee M, Ha SY, Lee H, et al. Ideal number of biopsy tumor fragments for predicting HER2 status in gastric carcinoma resection specimens. Oncotarget 2015;6:38372–38380.
      1. Fassan M, Ludwig K, Pizzi M, Castoro C, Guzzardo V, Balistreri M, et al. Human epithelial growth factor receptor 2 (HER2) status in primary and metastatic esophagogastric junction adenocarcinomas. Hum Pathol 2012;43:1206–1212.
      1. Fusco N, Rocco EG, Del Conte C, Pellegrini C, Bulfamante G, Di Nuovo F, et al. HER2 in gastric cancer: a digital image analysis in pre-neoplastic, primary and metastatic lesions. Mod Pathol 2013;26:816–824.
      1. Lee HE, Park KU, Yoo SB, Nam SK, Park DJ, Kim HH, et al. Clinical significance of intratumoral HER2 heterogeneity in gastric cancer. Eur J Cancer 2013;49:1448–1457.
      1. Tajiri R, Ooi A, Fujimura T, Dobashi Y, Oyama T, Nakamura R, et al. Intratumoral heterogeneous amplification of ERBB2 and subclonal genetic diversity in gastric cancers revealed by multiple ligation-dependent probe amplification and fluorescence in situ hybridization. Hum Pathol 2014;45:725–734.
      1. Stahl P, Seeschaaf C, Lebok P, Kutup A, Bockhorn M, Izbicki JR, et al. Heterogeneity of amplification of HER2, EGFR, CCND1 and MYC in gastric cancer. BMC Gastroenterol 2015;15:7.
      1. Cho J, Jeong J, Sung J, Sung CO, Kim KM, Park CK, et al. A large cohort of consecutive patients confirmed frequent HER2 positivity in gastric carcinomas with advanced stages. Ann Surg Oncol 2013;20 Suppl 3:S477–S484.
      1. Lee S, de Boer WB, Fermoyle S, Platten M, Kumarasinghe MP. Human epidermal growth factor receptor 2 testing in gastric carcinoma: issues related to heterogeneity in biopsies and resections. Histopathology 2011;59:832–840.
      1. Wakatsuki T, Yamamoto N, Sano T, Chin K, Kawachi H, Takahari D, et al. Clinical impact of intratumoral HER2 heterogeneity on trastuzumab efficacy in patients with HER2-positive gastric cancer. J Gastroenterol 2018;53:1186–1195.
      1. Gullo I, Grillo F, Molinaro L, Fassan M, De Silvestri A, Tinelli C, et al. Minimum biopsy set for HER2 evaluation in gastric and gastro-esophageal junction cancer. Endosc Int Open 2015;3:E165–E170.
      1. Rüschoff J, Hanna W, Bilous M, Hofmann M, Osamura RY, Penault-Llorca F, et al. HER2 testing in gastric cancer: a practical approach. Mod Pathol 2012;25:637–650.
      1. Bartley AN, Washington MK, Colasacco C, Ventura CB, Ismaila N, Benson AB 3rd, et al. HER2 testing and clinical decision making in gastroesophageal adenocarcinoma: Guideline from the College of American Pathologists, American Society for Clinical Pathology, and the American Society of Clinical Oncology. J Clin Oncol 2017;35:446–464.
      1. Grillo F, Fassan M, Sarocchi F, Fiocca R, Mastracci L. HER2 heterogeneity in gastric/gastroesophageal cancers: from benchside to practice. World J Gastroenterol 2016;22:5879–5887.
      1. Yoon HH, Shi Q, Sukov WR, Lewis MA, Sattler CA, Wiktor AE, et al. Adverse prognostic impact of intratumor heterogeneous HER2 gene amplification in patients with esophageal adenocarcinoma. J Clin Oncol 2012;30:3932–3938.
      1. Haffner I, Schierle K, Raimúndez E, Geier B, Maier D, Hasenauer J, et al. HER2 expression, test deviations, and their impact on survival in metastatic gastric cancer: results from the prospective multicenter VARIANZ study. J Clin Oncol 2021;39:1468–1478.
      1. Yagi S, Wakatsuki T, Yamamoto N, Chin K, Takahari D, Ogura M, et al. Clinical significance of intratumoral HER2 heterogeneity on trastuzumab efficacy using endoscopic biopsy specimens in patients with advanced HER2 positive gastric cancer. Gastric Cancer 2019;22:518–525.
      1. Kaito A, Kuwata T, Tokunaga M, Shitara K, Sato R, Akimoto T, et al. HER2 heterogeneity is a poor prognosticator for HER2-positive gastric cancer. World J Clin Cases 2019;7:1964–1977.
      1. Park SR, Park YS, Ryu MH, Ryoo BY, Woo CG, Jung HY, et al. Extra-gain of HER2-positive cases through HER2 reassessment in primary and metastatic sites in advanced gastric cancer with initially HER2-negative primary tumours: results of GASTric cancer HER2 reassessment study 1 (GASTHER1). Eur J Cancer 2016;53:42–50.
      1. Bang K, Cheon J, Park YS, Kim HD, Ryu MH, Park Y, et al. Association between HER2 heterogeneity and clinical outcomes of HER2-positive gastric cancer patients treated with trastuzumab. Gastric Cancer 2022;25:794–803.
      1. Kim B, Nam SK, Seo SH, Park KU, Ahn SH, Park DJ, et al. Comparative analysis of HER2 copy number between plasma and tissue samples in gastric cancer using droplet digital PCR. Sci Rep 2020;10:4177.
      1. Shoda K, Ichikawa D, Fujita Y, Masuda K, Hiramoto H, Hamada J, et al. Monitoring the HER2 copy number status in circulating tumor DNA by droplet digital PCR in patients with gastric cancer. Gastric Cancer 2017;20:126–135.
      1. Liu Y, Yang M, Jiang T, Lan C, Yuan H, Li G, et al. Quantitative analysis of HER2 amplification by droplet digital PCR in the follow-up of gastric cancer patients being treated with trastuzumab after surgery. Gastroenterol Res Pract 2019;2019:1750329
      1. Shitara K, Bang YJ, Iwasa S, Sugimoto N, Ryu MH, Sakai D, et al. Trastuzumab deruxtecan in previously treated HER2-positive gastric cancer. N Engl J Med 2020;382:2419–2430.
      1. Suzuki M, Yagishita S, Sugihara K, Ogitani Y, Nishikawa T, Ohuchi M, et al. Visualization of intratumor pharmacokinetics of [fam-] trastuzumab deruxtecan (DS-8201a) in HER2 heterogeneous model using phosphor-integrated dots imaging analysis. Clin Cancer Res 2021;27:3970–3979.
      1. Kijima T, Arigami T, Uenosono Y, Hiraki T, Yanagita S, Matsushita D, et al. Comparison of HER2 status before and after trastuzumab-based chemotherapy in patients with advanced gastric cancer. Anticancer Res 2020;40:75–80.
      1. Pietrantonio F, Caporale M, Morano F, Scartozzi M, Gloghini A, De Vita F, et al. HER2 loss in HER2-positive gastric or gastroesophageal cancer after trastuzumab therapy: Implication for further clinical research. Int J Cancer 2016;139:2859–2864.
      1. Seo S, Ryu MH, Park YS, Ahn JY, Park Y, Park SR, et al. Loss of HER2 positivity after anti-HER2 chemotherapy in HER2-positive gastric cancer patients: results of the GASTric cancer HER2 reassessment study 3 (GASTHER3). Gastric Cancer 2019;22:527–535.
      1. Saeki H, Oki E, Kashiwada T, Arigami T, Makiyama A, Iwatsuki M, et al. Re-evaluation of HER2 status in patients with HER2-positive advanced or recurrent gastric cancer refractory to trastuzumab (KSCC1604). Eur J Cancer 2018;105:41–49.
      1. Ma C, Wang X, Guo J, Yang B, Li Y. Challenges and future of HER2-positive gastric cancer therapy. Front Oncol 2023;13:1080990
      1. Angerilli V, Fassan M, Parente P, Gullo I, Campora M, Rossi C, et al. A practical approach for PD-L1 evaluation in gastroesophageal cancer. Pathologica 2023;115:57–70.
      1. Heo YJ, Kim B, Kim H, Kim S, Jang MS, Kim KM. PD-L1 expression in paired biopsies and surgical specimens in gastric adenocarcinoma: a digital image analysis study. Pathol Res Pract 2021;218:153338
      1. Kim SW, Jeong G, Ryu MH, Park YS. Comparison of PD-L1 immunohistochemical assays in advanced gastric adenocarcinomas using endoscopic biopsy and paired resected specimens. Pathology 2021;53:586–594.
      1. Yamashita K, Iwatsuki M, Harada K, Koga Y, Kiyozumi Y, Eto K, et al. Can PD-L1 expression evaluated by biopsy sample accurately reflect its expression in the whole tumour in gastric cancer? Br J Cancer 2019;121:278–280.
      1. Schoemig-Markiefka B, Eschbach J, Scheel AH, Pamuk A, Rueschoff J, Zander T, et al. Optimized PD-L1 scoring of gastric cancer. Gastric Cancer 2021;24:1115–1122.
      1. Ye M, Huang D, Zhang Q, Weng W, Tan C, Qin G, et al. Heterogeneous programmed death-ligand 1 expression in gastric cancer: comparison of tissue microarrays and whole sections. Cancer Cell Int 2020;20:186.
      1. Peixoto RD, Mathias-Machado MC, Jácome A, Gil M, Fogacci J, Sodré B, et al. PD-L1 testing in advanced gastric cancer-what physicians who treat this disease must know-a literature review. J Gastrointest Oncol 2023;14:1560–1575.
      1. Zhou KI, Peterson B, Serritella A, Thomas J, Reizine N, Moya S, et al. Spatial and temporal heterogeneity of PD-L1 expression and tumor mutational burden in gastroesophageal adenocarcinoma at baseline diagnosis and after chemotherapy. Clin Cancer Res 2020;26:6453–6463.
      1. Son SM, Woo CG, Kim DH, Yun HY, Kim H, Kim HK, et al. Distinct tumor immune microenvironments in primary and metastatic lesions in gastric cancer patients. Sci Rep 2020;10:14293.
      1. Svensson MC, Borg D, Zhang C, Hedner C, Nodin B, Uhlén M, et al. Expression of PD-L1 and PD-1 in chemoradiotherapy-naïve esophageal and gastric adenocarcinoma: relationship with mismatch repair status and survival. Front Oncol 2019;9:136.
      1. Erdogdu IH. MHC class 1 and PDL-1 status of primary tumor and lymph node metastatic tumor tissue in gastric cancers. Gastroenterol Res Pract 2019;2019:4785098
      1. Yang JH, Kim H, Roh SY, Lee MA, Park JM, Lee HH, et al. Discordancy and changes in the pattern of programmed death ligand 1 expression before and after platinum-based chemotherapy in metastatic gastric cancer. Gastric Cancer 2019;22:147–154.
      1. Park YS, Kook MC, Kim BH, Lee HS, Kang DW, Gu MJ, et al. A standardized pathology report for gastric cancer: 2nd edition. J Gastric Cancer 2023;23:107–145.
      1. Lee HS, Kim WH, Kwak Y, Koh J, Bae JM, Kim KM, et al. Molecular testing for gastrointestinal cancer. J Pathol Transl Med 2017;51:103–121.
      1. Park Y, Nam SK, Seo SH, Park KU, Oh HJ, Park YS, et al. Comprehensive study of microsatellite instability testing and its comparison with immunohistochemistry in gastric cancers. J Gastric Cancer 2023;23:264–274.
      1. Dislich B, Blaser N, Berger MD, Gloor B, Langer R. Preservation of Epstein-Barr virus status and mismatch repair protein status along the metastatic course of gastric cancer. Histopathology 2020;76:740–747.
      1. Wang X, Jiang K, Hu Y, Zhao X, Yin L, Diao X, et al. An exploration of gastric cancer with heterogeneous mismatch repair status. Virchows Arch 2023;482:517–523.
      1. Mathiak M, Warneke VS, Behrens HM, Haag J, Böger C, Krüger S, et al. Clinicopathologic characteristics of microsatellite instable gastric carcinomas revisited: urgent need for standardization. Appl Immunohistochem Mol Morphol 2017;25:12–24.
      1. Kim ST, Cristescu R, Bass AJ, Kim KM, Odegaard JI, Kim K, et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat Med 2018;24:1449–1458.
      1. Chen JN, He D, Tang F, Shao CK. Epstein-Barr virus-associated gastric carcinoma: a newly defined entity. J Clin Gastroenterol 2012;46:262–271.
      1. Böger C, Krüger S, Behrens HM, Bock S, Haag J, Kalthoff H, et al. Epstein-Barr virus-associated gastric cancer reveals intratumoral heterogeneity of PIK3CA mutations. Ann Oncol 2017;28:1005–1014.
      1. Kim HN, Ahn S, Kim KM. Gastric cancer with Epstein-Barr virus heterogeneity: evaluation of the frequency, clinicopathologic features, and genomic profiles. Pathol Res Pract 2022;238:154108
      1. Kwak Y, Kim TY, Nam SK, Hwang HJ, Han D, Oh HJ, et al. Clinicopathologic and molecular characterization of stages II-IV gastric cancer with Claudin 18.2 expression. Oncologist. 2024
        Forthcoming.
      1. Nakayama I, Qi C, Chen Y, Nakamura Y, Shen L, Shitara K. Claudin 18.2 as a novel therapeutic target. Nat Rev Clin Oncol 2024;21:354–369.
      1. Kim HD, Choi E, Shin J, Lee IS, Ko CS, Ryu MH, et al. Clinicopathologic features and prognostic value of claudin 18.2 overexpression in patients with resectable gastric cancer. Sci Rep 2023;13:20047.
      1. Choi E, Shin J, Ryu MH, Kim HD, Park YS. Heterogeneity of claudin 18.2 expression in metastatic gastric cancer. Sci Rep 2024;14:17648.
      1. Ogawa H, Abe H, Yagi K, Seto Y, Ushiku T. Claudin-18 status and its correlation with HER2 and PD-L1 expression in gastric cancer with peritoneal dissemination. Gastric Cancer 2024;27:802–810.
      1. Kim TY, Kwak Y, Nam SK, Han D, Oh DY, Im SA, et al. Clinicopathological analysis of claudin 18.2 focusing on intratumoral heterogeneity and survival in patients with metastatic or unresectable gastric cancer. ESMO Open 2024;9:104000
      1. Kang YK, Qin S, Lee KW, Oh SC, Kim IH, Kim JG, et al. Bemarituzumab plus mFOLFOX6 as first-line treatment in East Asian patients with FGFR2b-overexpressing locally advanced or metastatic gastric/gastroesophageal junction cancer: subgroup of FIGHT final analysis. Gastric Cancer 2024;27:1046–1057.
      1. Wainberg ZA, Kang YK, Lee KW, Qin S, Yamaguchi K, Kim IH, et al. Bemarituzumab as first-line 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.
      1. Han N, Kim MA, Lee HS, Kim WH. Evaluation of fibroblast growth factor receptor 2 expression, heterogeneity and clinical significance in gastric cancer. Pathobiology 2015;82:269–279.
      1. Ahn S, Lee J, Hong M, Kim ST, Park SH, Choi MG, et al. FGFR2 in gastric cancer: protein overexpression predicts gene amplification and high H-index predicts poor survival. Mod Pathol 2016;29:1095–1103.
      1. Pearson A, Smyth E, Babina IS, Herrera-Abreu MT, Tarazona N, Peckitt C, et al. High-level clonal FGFR amplification and response to FGFR inhibition in a translational clinical trial. Cancer Discov 2016;6:838–851.
    Publication Types
    Review
    MeSH Terms
    Biomarkers
    Biomarkers*
    Claudins
    Diagnosis
    ErbB Receptors
    Humans
    Immunohistochemistry
    Receptor, Fibroblast Growth Factor, Type 2
    Stomach Neoplasms*
    Substance
    ERBB2 protein, human
    Metrics
    Share
    Figures
    slide
    slide
    slide
    slide
    slide

    1 / 5

    Tables
    slide

    1 / 1

    ORCID IDs
    Funding Information
    PERMALINK