The therapeutic options for first-line gastroesophageal adenocarcinomas (GEAs) are improving, underscoring the need for biomarker testing to guide treatment selection for our patients. 2021 was a transformative year, with two Food and Drug Administration approvals of immune checkpoint inhibitor-based combinations in the first-line setting for both human epidermal growth factor receptor 2 (HER2)-negative (nivolumab, 5-fluorouracil, platinum) and HER2-positive (pembrolizumab, trastuzumab, 5-fluorouracil, platinum) patients.1,2 More recently, the randomized phase II FIGHT trial examining first-line 5-fluororacil/platinum with or without the anti-FGFR2b (anti-fibroblast growth factor receptor 2b) antibody bemarituzumab demonstrated promising results in FGFR2b+ patients.3 Finally, in November 2022, Astellas announced positive top-line results of the randomized phase III SPOTLIGHT trial in which the addition of the claudin18.2 (CLDN18.2) antibody zolbetuximab to standard frontline FOLFOX improved progression-free survival and overall survival versus FOLFOX + placebo in CLDN18.2+ patients. Currently, biomarker testing for first-line GEA management is anchored on HER2, microsatellite instability, and programmed death-ligand 1 (PD-L1); however, the emergence of anti-CLDN18.2 and possibly future anti-FGFR2b are an entrée to new treatment paradigms and questions, particularly around biomarkers.
In the current issue of ESMO Open Kubota and colleagues4 provide important data to understand CLDN18.2 prevalence, biomarker overlap, and prognostic implications in advanced GEA. The authors leverage a large, well-annotated, clinical cohort (n = 408, ∼87% gastric) which is representative of the known clinicopathologic features and molecular subtypes of GEA. To define the prevalence of CLDN18.2+ they used the same antibody (clone 43-14A, Roche Ventana) and immunohistochemical (IHC) cut-off (moderate-strong expression in ≥75% of tumor cells) that are being used in the ongoing phase III trials of zolbetuximab. With this definition, the prevalence of CLDN18.2+ GEA was 24% in this Japanese cohort (Table 1). In a somewhat more heterogeneous cohort of Western patients (n = 350) using the same antibody and CLDN18.2+ definition, the prevalence of CLDN18.2+ was reported at 33%.5,6 Taken together, these data along with data from the phase II FAST trial suggest an overall prevalence of CLDN18.2+ in the 25%-40% range across GEA.7 Using lower cut points to define CLDN18.2+ the prevalence increases, with ∼50% defined as CLDN18.2+ at a cut-off of moderate-strong expression in ≥40% of tumor cells.6
Table 1.
Gastroesophageal adenocarcinoma biomarker prevalence stratified by CLDN18.2 status in published series
| Feature/Biomarker | Kubota et al.4 |
Pellino et al.5 |
Jia et al.6 |
|||
|---|---|---|---|---|---|---|
| CLDN18.2+ (n = 98) n (%) | CLDN18.2− (n = 310) n (%) | CLDN18.2+ (n = 117) n (%) | CLDN18.2− (n = 233) n (%) | CLDN18.2+ (n = 42) n (%) | CLDN18.2− (n = 38) n (%) | |
| HER2− | 83 (85) | 267 (85) | 100 (85) | 198 (85) | 33 (79) | 25 (66) |
| HER2+ | 15 (15) | 43 (14) | 17 (15) | 35 (15) | 9 (21) | 13 (34) |
| FGFR2b+ | N/A | N/A | N/A | N/A | N/A | N/A |
| FGFR2b− | N/A | N/A | N/A | N/A | N/A | N/A |
| pMMR/MSS | 93 (96) | 291 (94) | 102 (87) | 194 (83) | 36 (86) | 33 (87) |
| dMMR/MSI | 5 (5) | 19 (6) | 15 (13) | 39 (17) | 6 (14) | 5 (13) |
| EBV+ | 4 (4) | 11 (4) | 7 (6) | 1 (0.4) | 8 (19) | 2 (5) |
| EBV− | 94 (96) | 299 (96) | 110 (94) | 232 (99.5) | 34 (81) | 36 (95) |
| PD-L1− (CPS <1) | 24 (26) | 68 (23) | 87 (74) | 165 (71) | 9 (21) | 8 (21) |
| PD-L1+ (CPS ≥1) | 69 (74) | 225 (77) | 30 (26) | 68 (29) | 33 (79) | 30 (79) |
| PD-L1+ (CPS ≥5) | 39 (42) | 293 (52) | 21 (18) | 50 (21) | N/A | N/A |
| PD-L1+ (CPS ≥10) | N/A | N/A | N/A | N/A | 19 (45) | 17 (45) |
| Diffuse type | 47 (48) | 137 (44) | 47 (40) | 70 (30) | 12 (29) | 22 (58) |
| Intestinal type | 51 (52) | 173 (56) | 54 (46) | 132 (57) | 16 (38) | 6 (16) |
CPS, combined positive score; dMMR, MMR deficient; EBV, Epstein-Barr Virus; FGFR2b, fibroblast growth factor receptor 2b; MMR, mismatch repair; MSI, microsatellite instability; N/A, not available; PD-L1, programmed death-ligand 1; pMMR, MMR proficient.
aKubota et al.4 and Pellino et al.5 defined CLDN18.2+ as ≥75% tumor cells with 2+/3+ membrane staining, IHC Ab = Roche, clone 43-14A for Pellino et al. and Kubota et al.
bJia et al.6 defined CLDN18.2+ as ≥40% tumor cells with 2+ or higher membrane staining, IHC Ab = Abcam ab222512.
Having explored the prevalence of CLDN18.2+ in their cohort, the authors examined biomarker overlap in CLDN18.2+ and CLDN18.2− patients. The majority of CLD18.2+ tumors are HER2 negative and mismatch repair (MMR) proficient, potentially carving out a unique therapeutic niche for metastatic GEA patients. However, there were no clear differences in the prevalence of current biomarkers, including HER2, PD-L1, and MMR, between CLDN18.2+ and CLDN18.2− patients (Table 1). When placing the Kubota et al. data in the context of other CLDN18.2 datasets, similar trends are seen. There was a numerically lower rate of PD-L1 combined positive score (CPS) ≥5 among CLDN18.2+ patients, but this was nonsignificant. Notably, there is substantial variation in the rates of higher PD-L1 CPSs (CPS ≥5) between this Japanese cohort and a previously published Western cohort, which is not completely explained and is likely multifactorial (assay used, timing of sample, etc.).
It is important to understand the prognostic impact of our biomarkers, particularly when interpreting the control arms of biomarker-enriched trial designs. Previously, the prognostic impact of CLDN18.2 expression was unknown. To address this gap, Kubota et al. asked whether CLDN18.2+ versus CLDN18.2− patients had differential outcomes with standard first-line 5-fluorouracil/platinum doublet chemotherapy. There was no difference in objective response rate (43% versus 49%), median progression-free survival (8.6 months versus 7.1 months), or median overall survival (18.4 months versus 20.1 months) between CLDN18.2+ and CLDN18.2− patients. When PD-L1 CPS strata (using the SP142 assay) were overlayed on the CLDN18.2 status, there was similarly no difference in outcomes. The authors extended their findings to second-line chemotherapy and again saw no impact of CLDN18.2 status on outcomes. Given the widespread adoption of anti-PD-1 (programmed cell death protein 1) agents in GEA and the interest in combining CLDN18.2 antibodies with anti-PD-1 agents, the authors explored outcomes with anti-PD-1 in CLDN18.2+ and CLDN18.2− patients. There was no difference in outcomes between CLDN18.2+ and CLDN18.2− patients treated with anti-PD-1 agents. Although entirely retrospective, these data suggest that CLDN18.2 is not an independent prognostic factor in advanced GEAs.
As we continue to understand determinants of response to targeted and immunotherapeutic approaches in GEA, a clear role for the tumor immune microenvironment (TIME) has emerged.8,9 The baseline immune context and the ability of therapies to remodel the TIME are both prognostic and predictive. In an exploratory subset of 149 patients the authors looked broadly at TIME composition by IHC for canonical cell types. In comparing CLDN18.2+ versus CLDN18.2− tumors they noted lower CD16 (pan-NK marker) and higher CD68 (pan-macrophage marker) among CLDN18.2+ patients. There are substantial limitations to their TIME analysis and these findings do not align with findings from a Chinese study showing higher CD8+ T-cell, higher neutrophil, and no macrophage enrichment in CLDN18.2+ patients using a lower CLDN18.2 cut-off (≥40% positive tumor cells). Whether these findings are early clues to a CLDN18.2-associated biology remain unknown. In addition, future work examining paired pre/post samples from patients treated with CLDN18.2-directed agents are needed to understand true TIME changes and effects on CLDN18.2 expression.
We commend the authors for a timely addition to the GEA biomarker literature. Over the next several years, the treatment landscape will likely include additional targeted therapies and deeply understanding outcomes in patient subgroups from our trial data will be essential. For example, what would be the optimal management of a CLDN18.2+ patient with a PD-L1 CPS of 2? What if the PD-L1 CPS were 7? What about a CLDN18.2+ and FGFR2b+ patient? Of equal importance is accurate implementation and standardization of biomarker testing. While massive-parallel sequencing from plasma and/or tissue is a substantial advance, the diagnostic assays for MMR, PD-L1, FGFR2b, HER2, and CLDN18.2 rely on IHC testing (Figure 1). In tumor types like GEA, where diagnostic tissue samples can be limited, discussions with pathology colleagues and future consideration for multiplexed assays will be increasingly important. While these represent challenges for our field, these advances bring new hope for the individualized treatment of gastroesophageal cancers.10
Figure 1.
Potential future biomarker testing in advanced gastroesophageal adenocarcinomas. Current approaches rely on individual immunohistochemical tests for MMR assessment, HER2 testing, and PD-L1 CPS testing. CLDN18.2 and FGFR2b are emerging biomarkers utilizing IHC platforms. Molecular alterations detectable by tissue and/or plasma-based next-generation sequencing are shown on the right.
amp, amplification; CPS, combined positive score; EGFR, epidermal growth factor receptor; ERBB2, Erb-B2 Receptor Tyrosine Kinase; FGFR2b, fibroblast growth factor receptor 2b; HER2, human epidermal growth factor receptor 2; IHC, immunohistochemistry; MET, MET proto-oncogene, receptor tyrosine kinase; MMR, mismatch repair; MSI, microsatellite instability; NTRK, neurotrophic receptor tyrosine kinase; PD-L1, programmed death-ligand 1; TMB, tumor mutation burden.
Acknowledgments
Funding
None declared.
Disclosure
SJK reports consulting/advisory role in Eli Lilly, Merck, BMS, Novartis, Astellas, AstraZeneca, Daiichi-Sankyo, Novartis, Sanofi-Aventis, Natera, Exact Sciences, and Mersana; stock/equity in Turning Point Therapeutics and Nuvalent. YYJ reports consulting/advisory role in AmerisourceBergen Corporation, Arcus Biosciences, Inc., AstraZeneca, Axis Medical Education, Basilea Pharmaceutica International Ltd., Bristol-Myers Squibb, Clinical Care Options, Creative Educational Concepts, Inc., Daiichi Sankyo, Eli Lilly and Company, Geneos Therapeutics, Inc., GlaxoSmithKline, Imedex, Inc., Lynx Health LLC, Merck & Co Inc., Michael J. Hennessy Associates, PeerView Institute for Medical Education (PVI), Prova Education, Inc., Research to Practice, Rgenix (Ownership/Equity Interests), and Silverback Therapeutics, Inc. ZAW reports consulting for Amgen, Arcus, Astra Zeneca, Daiichi, Bayer, BMS, Merck, Ipsen, Lilly, Gilead, Arcus, Astellas, and Molecular Templates; and research grants from Arcus, BMS, and Plexxikon.
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