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Prevalence of Claudin 18.2 Expression in Gastric and Gastroesophageal Junction Adenocarcinoma: A Systematic Review and Meta-Analysis.

BACKGROUND: Claudin 18 isoform 2 (CLDN18.2) has emerged as a clinically validated therapeutic target in gastric and gastroesophageal junction (GEJ) adenocarcinoma following the regulatory approval of zolbetuximab in combination with first-line chemotherapy. Accurate prevalence data at the clinically validated immunohistochemical threshold are essential for patient selection, healthcare resource planning, and treatment strategy. Reported prevalence estimates vary widely across studies due to differences in populations, methodologies, and immunohistochemical protocols. This systematic review and meta-analysis aimed to generate a robust pooled prevalence estimate of CLDN18.2 expression at the threshold used in pivotal phase III trials. METHODS: PubMed, Embase, and the Cochrane Library were searched from database inception through March 12th, 2026. Studies reporting CLDN18.2 expression in gastric or gastroesophageal junction adenocarcinoma using the ≥ 75% moderate-to-strong membranous staining threshold were included. Prevalence proportions were pooled using a random-effects model with logit transformation and restricted maximum-likelihood estimation of between-study variance. Heterogeneity was assessed using the I² statistic and Cochran's Q test, and a 95% prediction interval was calculated. Pre-specified subgroup analyses assessed antibody clone and geographic region, with additional exploratory analyses according to disease setting and specimen type. Sensitivity analyses were performed to assess the robustness of the pooled estimate. RESULTS: Twenty-two predominantly retrospective cohort studies comprising 12,173 patients were included. The pooled prevalence of CLDN18.2 positivity using a random-effects model was 33.99% (95% CI: 30.13%-38.07%; 95% prediction interval: approximately 18%-55%), with high between-study heterogeneity (I² = 92.4%). Subgroup analysis by antibody clone showed no statistically significant difference between studies using the 43-14 A clone (32.79%, 95% CI: 28.86%-36.97%) and those using other reported antibody clones (41.74%, 95% CI: 26.76%-58.42%; p = 0.281). One study with an unreported antibody clone was excluded from this subgroup analysis. Geographic subgroup analysis excluding the multinational Shitara et al. cohort demonstrated a non-significant trend toward higher prevalence in non-Asian populations (37.85%, 95% CI: 31.59%-44.54%) compared with Asian populations (32.10%, 95% CI: 27.28%-37.34%; p = 0.169). All three sensitivity analyses confirmed robustness of the pooled estimate. No significant evidence of publication bias was detected (Egger's test p = 0.56). CONCLUSIONS: Approximately one-third of patients with gastric and GEJ adenocarcinoma express CLDN18.2 at the clinically validated ≥ 75% threshold. However, because the included studies encompassed heterogeneous disease settings and were predominantly HER2-unselected, the pooled estimate should not be interpreted directly as the proportion of patients eligible for zolbetuximab. The estimate was robust across sensitivity analyses and provides an evidence base for understanding CLDN18.2 prevalence and biomarker-testing requirements. Standardisation of immunohistochemical assessment methods is warranted to reduce between-study heterogeneity in future research.

Humans

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74&#xb7;1 months (IQR 68&#xb7;3-75&#xb7;4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0&#xb7;84 [95% CI 0&#xb7;79-0&#xb7;88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11&#xb7;6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0&#xb7;41-0&#xb7;93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0&#xb7;36-0&#xb7;48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (&#x2265;70&#xb7;0%; mean absolute improvement 12&#xb7;1 percentage points [SD 2&#xb7;8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0&#xb7;010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans