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The Molecular Landscape of Gastric Cancers for Novel Targeted Therapies from Real-World Genomic Profiling

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Abstract

Background

Panel-based comprehensive genomic profiling is used in clinical practice worldwide; however, large real-world datasets of patients with advanced gastric cancer are not well known.

Objective

We investigated what differences exist in clinically relevant alterations for molecularly defined or age-stratified subgroups.

Methods

This was a collaborative biomarker study of a real-world dataset from comprehensive genomic profiling testing (Foundation Medicine, Inc.). Hybrid capture was carried out on at least 324 cancer-related genes and select introns from 31 genes frequently rearranged in cancer. Overall, 4634 patients were available for analyses and were stratified by age (≥ 40/< 40 years), microsatellite instability status, tumor mutational burden status (high 10 ≥ /low < 10 Muts/Mb), Epstein–Barr virus status, and select gene alterations. We analyzed the frequency of alterations with a chi-square test with Yate’s correction.

Results

Genes with frequent alterations included TP53 (60.1%), ARID1A (19.6%), CDKN2A (18.2%), KRAS (16.6%), and CDH1 (15.8%). Differences in comprehensive genomic profiling were observed according to molecularly defined or age-stratified subgroups. Druggable genomic alterations were detected in 31.4% of patients; ATM (4.4%), BRAF V600E (0.4%), BRCA1 (1.5%), BRCA2 (2.9%), ERBB2 amplification (9.2%), IDH1 (0.2%), KRAS G12C (0.7%), microsatellite instability-high (4.8%), NTRK1/2/3 fusion (0.13%), PIK3CA mutation (11.4%), and tumor mutational burden-high (9.4%). CDH1 alterations and MET amplification were significantly more frequent in patients aged < 40 years (27.7 and 6.2%) than in those aged ≥ 40 years (14.7 and 4.0%).

Conclusions

Real-world datasets from clinical panel testing revealed the genomic landscape in gastric cancer by subgroup. These findings provide insights for the current therapeutic strategies and future development of treatments in gastric cancer.

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Authors and Affiliations

  1. Department of Bioinformatics, St. Marianna University Graduate School of Medicine, 2-16-1 Sugao, Miyamae-ku, Kawasaki, Kanagawa, 216-8511, Japan

    Hiroyuki Yamamoto

  2. Department of Gastroenterology, St. Marianna University School of Medicine, Kawasaki, Japan

    Hiroyuki Yamamoto & Ritsuko Oikawa

  3. Department of Clinical Oncology, St. Marianna University School of Medicine, Kawasaki, Japan

    Hiroyuki Arai, Kumiko Umemoto, Hiroyuki Takeda, Takuro Mizukami, Yohei Kubota, Ayako Doi, Yoshiki Horie, Takashi Ogura, Naoki Izawa & Yu Sunakawa

  4. Cancer Genomics Research, Foundation Medicine, Inc., Cambridge, MA, USA

    Jay A. Moore & Ethan S. Sokol

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  1. Hiroyuki Yamamoto
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Corresponding author

Correspondence to Hiroyuki Yamamoto.

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Funding

No external funding was used in the preparation of this article.

Conflict of interest

Kumiko Umemoto has received honoraria from Chugai Pharmaceutical. Naoki Izawa has recived honoraria form Chugai Pharmaceutical. Jay A. Moore and Ethan S. Sokol are employees of Foundation Medicine, Inc. and shareholders in Roche. Yu Sunakawa has recived honoraria and research funding from Chugai Pharmaceutical. Hiroyuki Yamamoto, Hiroyuki Arai, Ritsuko Oikawa, Hiroyuki Takeda, Takuro Mizukami, Yohei Kubota, Ayako Doi, Yoshiki Horie, Takashi Ogura, and Naoki Izawa have no conflicts of interest that are directly relevant to the content of this article.

Ethics approval

Approval for this study, including a waiver of informed consent and a Health Insurance Portability and Accountability Act waiver of authorization, was obtained from the Western Institutional Review Board (protocol #20152817). This study was also approved by the Ethics Committee of St. Marianna University School of Medicine.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and material

The sequencing data generated in this study are derived from clinical samples. The data supporting the findings of this study are provided within the paper and its supplementary files. All supplementary information accompanying the different analyses and figures presented in this study are provided in the ESM. Because of Health Insurance Portability and Accountability Act requirements, we are not consented to share individualized patient genomic data that contain potentially identifying or sensitive patient information. Foundation Medicine, Inc. is committed to collaborative data analysis, and we have well-established and widely utilized mechanisms by which investigators can query our core genomic database of > 600,000 de-identified sequenced cancers to obtain aggregated datasets. Requests for collaborative datashares can be made by contacting the corresponding author(s) and completing a study review committee form. Once approved, investigators are required to sign a data transfer agreement. Written proposals are considered at monthly meetings and data transfer agreements expire 18 months from execution of the agreement.

Code availability

Not applicable.

Author contributions

HY designed the study, performed the analyses, and interpreted the data. RO performed the analyses and interpreted the data. YS designed the study and interpreted the data. JM and ES collected the data, performed the analyses, and interpreted the data. All authors contributed to the writing and approved the final manuscript.

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Yamamoto, H., Arai, H., Oikawa, R. et al. The Molecular Landscape of Gastric Cancers for Novel Targeted Therapies from Real-World Genomic Profiling. Targ Oncol (2024). https://doi.org/10.1007/s11523-024-01052-1

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  • DOI: https://doi.org/10.1007/s11523-024-01052-1

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