Abstract
Abstract Background: Gastric cancer (GC) is the third leading cause of death from malignant neoplasms in Japan, and unresectable advanced GC has a poor prognosis, so further therapeutic development is needed. However, genomic medicine has its limitations, and it is imperative to establish precision medicine based on a new concept to match the dynamic changes in cancer. Focusing on phosphorylation signaling in cancer cells, we have been developing deep phosphoproteome analysis from minute endoscopic biopsy specimens frozen within 20 seconds of collection. This is to enable phosphorylation signal profiling that reflects the phosphorylation signal state in the patient's body as much as possible. Methods: We collected endoscopic biopsy specimens from 85 patients with gastric cancer. Post-treatment specimens from nine gastric cancer patients were obtained two months later after the initiation of drug therapy. In a single endoscopic procedure, three tumor specimens and three normal gastric mucosa specimens were collected concomitantly from each patient. Each specimen was separately put in a screw-cap tube and immediately snap-frozen in liquid nitrogen within 20 s after collection. Frozen specimens were stored at -80 °C until further sample preparation. Proteome and phosphoproteome analysis were performed by multiplex analysis using Tandem Mass Tag reagent. Genomic analysis was performed by using a targeted high-multiplex PCR-based NGS panel (OncoMine Comprehensive Assay). Results: Using this system, we obtained phosphorylation profiles of 340 specimens from 85 untreated gastric cancer patients. Ultrasensitive mass spectrometry-based proteomics quantified an average of 21000 phosphorylation sites and divided gastric cancer patients into subtype 1 (CDK active, 35%), subtype 2 (EMT, 15%), and subtype 3. (Others, 50%). The association with the four subtypes defined by TCGA was low. Furthermore, EMT type increased to 67% after chemotherapy. These results strongly suggest that gastric cancer undergoes dynamic transformation with treatment. The kinase activity profile of each subtype is useful information to provide therapeutic options for each subtype. Furthermore, our method of quantifying phosphorylation signals in cancer using biopsy specimens is expected to be a powerful driver of signaling-based precision medicine, not only for determining subtypes, but also for selecting treatment options and measuring drug efficacy. Conclusions: We succeeded in developing the ultra-sensitive phosphorylation analysis system, which can quantify phosphorylation at more than 20,000 sites from endoscopic biopsy specimens, and propose a molecular classification dividing gastric cancer into three subtypes. Citation Format: Jun Adachi, Masahiko Aoki, Hidekazu Hirano, Yuichi Abe, Ryohei Narumi, Kazufumi Honda, Takeshi Tomonaga, Kenji Mizuguchi, Takaki Yoshikawa, Narikazu Boku. Phosphoproteomic subtyping of gastric cancer reveals dynamic transformation with chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1060.
Published Version
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