胃癌诊疗的瓶颈与破局：迈向精准化与智能化融合的新纪元

doi:10.19723/j.issn.1671-167X.2026.02.001

摘要/Abstract

摘要：

胃癌是全球高负担的恶性肿瘤，胃癌诊疗正处于从传统经验模式向精准化与智能化深度融合的关键阶段，目前，诊疗的核心瓶颈已从技术缺乏转变为精准决策能力不足。近年来，诊断领域在人工智能(artificial intelligence, AI)辅助内镜、影像组学、分子分型及液体活检等精准化与智能化技术方面进步显著；在治疗领域，早期胃癌的功能保留、局部进展期胃癌的围术期综合策略，以及晚期胃癌基于生物标志物的精准分层治疗均取得了重要进展。然而，早期诊断率低、分期不精准、治疗个体化选择困难，以及疗效评估滞后等问题依然突出。未来的发展关键在于将精准医学与人工智能技术有机结合，即通过多组学等精准化工具刻画肿瘤本质，并运用智能技术覆盖疾病筛查、诊断、治疗决策与随访全流程，从而构建更高效的诊疗体系，最终提升患者生存预后。

关键词: 胃肿瘤, 精准治疗, 人工智能

Abstract:

Gastric cancer constitutes a significant global health burden, and its clinical management is undergoing a critical transition from a traditional experience-driven paradigm toward the deep integration of precision medicine and artificial intelligence (AI). At present, the main bottleneck has shifted from a lack of therapeutic options to insufficient capacity for precise clinical decision-making. In recent years, diagnostic approaches have seen marked advances through the application of AI-augmented endoscopy, radiomics, molecular subtyping, and liquid biopsy, reflecting progress in both precision and intelligence. Therapeutically, notable strides have been made in function-preserving strategies for early-stage disease, multimodal perioperative management for locally advanced cancer, and biomarker-guided stratified therapy for advanced gastric cancer. However, challenges persist, including low early-detection rates, inaccurate staging, difficulties in treatment personalization, and delayed assessment of therapeutic response. The future of gastric cancer care lies in the synergistic combination of precision medicine and AI technologies: leveraging multi-omics and other precision tools to delineate tumor biology, while deploying intelligent systems across the entire continuum from screening and diagnosis to treatment selection and follow-up. This integrated approach is key to establishing a more efficient clinical framework and ultimately improving patient survival outcomes.

Key words: Stomach neoplasms, Precision medicine, Artificial intelligence

中图分类号:

R735.2

季加孚, 韦静涛, 季科, 步召德. 胃癌诊疗的瓶颈与破局：迈向精准化与智能化融合的新纪元[J]. 北京大学学报（医学版）, 2026, 58(2): 231-238.

Jiafu JI, Jingtao WEI, Ke JI, Zhaode BU. Bottlenecks and breakthroughs in gastric cancer diagnosis and treatment: Towards a new era of precision and intelligent integration[J]. Journal of Peking University (Health Sciences), 2026, 58(2): 231-238.

参考文献 52

1	Yoshida N , Doyama H , Yano T , et al. Early gastric cancer detection in high-risk patients: A multicentre randomised controlled trial on the effect of second-generation narrow band imaging[J]. Gut, 2021, 70 (1): 67- 75. doi: 10.1136/gutjnl-2019-319631
2	Horiuchi Y , Hirasawa T , Fujisaki J . Application of artificial intelligence for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging[J]. Clin Endosc, 2024, 57 (1): 11- 17. doi: 10.5946/ce.2023.173
3	Wu L , He X , Liu M , et al. Evaluation of the effects of an artificial intelligence system on endoscopy quality and preliminary testing of its performance in detecting early gastric cancer: A randomized controlled trial[J]. Endoscopy, 2021, 53 (12): 1199- 1207. doi: 10.1055/a-1350-5583
4	Tang D , Wang L , Ling T , et al. Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study[J]. eBioMedicine, 2020, 62, 103146. doi: 10.1016/j.ebiom.2020.103146
5	Matsubayashi CO , Cheng S , Hulchafo I , et al. Artificial intelligence for gastric cancer in endoscopy: From diagnostic reasoning to market[J]. Dig Liver Dis, 2024, 56 (7): 1156- 1163. doi: 10.1016/j.dld.2024.04.019
6	Hu C , Xia Y , Zheng Z , et al. AI-based large-scale screening of gastric cancer from noncontrast CT imaging[J]. Nat Med, 2025, 31 (9): 3011- 3019. doi: 10.1038/s41591-025-03785-6
7	Sun Z , Jiang Y , Chen C , et al. Radiomics signature based on computed tomography images for the preoperative prediction of lymph node metastasis at individual stations in gastric cancer: A multicenter study[J]. Radiother Oncol, 2021, 165, 179- 190. doi: 10.1016/j.radonc.2021.11.003
8	Dong D , Fang MJ , Tang L , et al. Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: An international multicenter study[J]. Ann Oncol, 2020, 31 (7): 912- 920. doi: 10.1016/j.annonc.2020.04.003
9	Dong D , Tang L , Li ZY , et al. Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer[J]. Ann Oncol, 2019, 30 (3): 431- 438. doi: 10.1093/annonc/mdz001
10	Gao P , Xiao Q , Tan H , et al. Interpretable multi-modal artificial intelligence model for predicting gastric cancer response to neoadjuvant chemotherapy[J]. Cell Rep Med, 2024, 5 (12): 101848. doi: 10.1016/j.xcrm.2024.101848
11	Jiang Y , Zhou K , Sun Z , et al. Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics[J]. Cell Rep Med, 2023, 4 (8): 101146. doi: 10.1016/j.xcrm.2023.101146
12	Huang W , Zhang Y , Chen S , et al. Personalized immune subtypes based on machine learning predict response to checkpoint blockade in gastric cancer[J]. Brief Bioinform, 2023, 24, bbac554. doi: 10.1093/bib/bbac554
13	Wu Z , Wang T , Lan J , et al. Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features[J]. J Transl Med, 2025, 23 (1): 13. doi: 10.1186/s12967-024-06034-5
14	Cancer Genome Atlas Research N . Comprehensive molecular characterization of gastric adenocarcinoma[J]. Nature, 2014, 513 (7517): 202- 209. doi: 10.1038/nature13480
15	Lei Z , Tan IB , Das K , et al. Identification of molecular subtypes of gastric cancer with different responses to PI3-kinase inhibitors and 5-fluorouracil[J]. Gastroenterology, 2013, 145 (3): 554- 565. doi: 10.1053/j.gastro.2013.05.010
16	Cristescu R , Lee J , Nebozhyn M , et al. Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes[J]. Nat Med, 2015, 21 (5): 449- 456. doi: 10.1038/nm.3850
17	Chen Y , Cheng WY , Shi H , et al. Classifying gastric cancer using FLORA reveals clinically relevant molecular subtypes and highlights LINC01614 as a biomarker for patient prognosis[J]. Oncogene, 2021, 40 (16): 2898- 2909. doi: 10.1038/s41388-021-01743-3
18	Zhang M , Hu S , Min M , et al. Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing[J]. Gut, 2021, 70 (3): 464- 475. doi: 10.1136/gutjnl-2019-320368
19	Weng S , Li M , Deng J , et al. Epigenetically regulated gene expression profiles decipher four molecular subtypes with prognostic and therapeutic implications in gastric cancer[J]. Clin Epigenet, 2023, 15 (1): 64. doi: 10.1186/s13148-023-01478-w
20	Sato Y , Wada I , Odaira K , et al. Integrative immunogenomic analysis of gastric cancer dictates novel immunological classification and the functional status of tumor-infiltrating cells[J]. Clin and Trans Imm, 2020, 9 (10): e1194. doi: 10.1002/cti2.1194
21	Ma H , Srivastava S , Ho SWT , et al. Spatially resolved tumor ecosystems and cell states in gastric adenocarcinoma progression and evolution[J]. Cancer Discov, 2025, 15 (4): 767- 792. doi: 10.1158/2159-8290.CD-24-0605
22	Ma S , Zhou M , Xu Y , et al. Clinical application and detection techniques of liquid biopsy in gastric cancer[J]. Mol Cancer, 2023, 22 (1): 7. doi: 10.1186/s12943-023-01715-z
23	Zhang Z , Wu H , Chong W , et al. Liquid biopsy in gastric cancer: Predictive and prognostic biomarkers[J]. Cell Death Dis, 2022, 13 (10): 903. doi: 10.1038/s41419-022-05350-2
24	Díaz del Arco C , Fernández Aceñero MJ , Ortega Medina L . Liquid biopsy for gastric cancer: Techniques, applications, and future directions[J]. World J Gastroenterol, 2024, 30 (12): 1680- 1705. doi: 10.3748/wjg.v30.i12.1680
25	Japanese Gastric Cancer Association . Japanese gastric cancer treatment guidelines 2010 (ver. 3)[J]. Gastric Cancer, 2011, 14 (2): 113- 123. doi: 10.1007/s10120-011-0042-4
26	Japanese Gastric Cancer Association . Japanese gastric cancer treatment guidelines 2014 (ver. 4)[J]. Gastric Cancer, 2017, 20 (1): 1- 19.
27	Hasuike N , Ono H , Boku N , et al. A non-randomized confirmatory trial of an expanded indication for endoscopic submucosal dissection for intestinal-type gastric cancer (cT1a): The Japan Clinical Oncology Group study (JCOG0607)[J]. Gastric Cancer, 2018, 21 (1): 114- 123. doi: 10.1007/s10120-017-0704-y
28	庞博然, 朱正伦, 李琛, 等. 早期低分化胃癌淋巴结转移危险因素分析[J]. 中华胃肠外科杂志, 2019, 22 (5): 446- 450.
29	Takizawa K , Ono H , Hasuike N , et al. A nonrandomized, single-arm confirmatory trial of expanded endoscopic submucosal dissection indication for undifferentiated early gastric cancer: Japan Clinical Oncology Group study (JCOG1009/1010)[J]. Gastric Cancer, 2021, 24 (2): 479- 491. doi: 10.1007/s10120-020-01134-9
30	Association Japanese Gastric Cancer . Japanese gastric cancer treatment guidelines 2021 (6th edition)[J]. Gastric Cancer, 2023, 26 (1): 1331.
31	Wang FH , Zhang XT , Li YF , et al. The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021[J]. Cancer Commun, 2021, 41 (8): 747- 795. doi: 10.1002/cac2.12193
32	Kim YW , Min JS , Yoon HM , et al. Laparoscopic sentinel node navigation surgery for stomach preservation in patients with early gastric cancer: A randomized clinical trial[J]. J Clin Oncol, 2022, 40 (21): 2342- 2351. doi: 10.1200/JCO.21.02242
33	Eom BW , Yoon HM , Kim YW , et al. Quality of life and nutritional outcomes of stomach-preserving surgery for early gastric cancer: A secondary analysis of the SENORITA randomized clinical trial[J]. JAMA Surg, 2024, 159 (8): 900. doi: 10.1001/jamasurg.2024.1210
34	Hur H , Lee YJ , Kim YW , et al. Clinical efficacy of laparoscopic sentinel node navigation surgery for stomach preservation in patients with early gastric cancer: 5-year results of the SENORITA trial[J]. Ann Surg, 2025, 281 (2): 296- 303. doi: 10.1097/SLA.0000000000006219
35	陈龙奇, 胡建昆, 季加孚, 等. 食管胃结合部腺癌外科治疗中国专家共识(2018年版)[J]. 中华胃肠外科杂志, 2018, 21 (9): 961- 975.
36	Japanese Gastric Cancer Association . Japanese gastric cancer treatment guidelines 2018 (5th edition)[J]. Gastric Cancer, 2021, 24 (1): 1- 21. doi: 10.1007/s10120-020-01042-y
37	中国抗癌协会胃癌专业委员会, 徐泽宽, 梁寒, 等. 近端胃切除消化道重建中国专家共识(2024版)[J]. 消化肿瘤杂志, 2025, 17 (2): 105- 114.
38	Al-Batran SE , Homann N , Pauligk C , et al. Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): A randomised, phase 2/3 trial[J]. Lancet, 2019, 393 (10184): 1948- 1957. doi: 10.1016/S0140-6736(18)32557-1
39	Kang YK , Yook JH , Park YK , et al. PRODIGY: A phase Ⅲ study of neoadjuvant docetaxel, oxaliplatin, and S-1 plus surgery and adjuvant S-1 versus surgery and adjuvant S-1 for resectable advanced gastric cancer[J]. J Clin Oncol, 2021, 39 (26): 2903- 2913. doi: 10.1200/JCO.20.02914
40	Zhang X , Liang H , Li Z , et al. Perioperative or postoperative adjuvant oxaliplatin with S-1 versus adjuvant oxaliplatin with capecitabine in patients with locally advanced gastric or gastro-oesophageal junction adenocarcinoma undergoing D2 gastrectomy (RESOLVE): Final report of a randomised, open-label, phase 3 trial[J]. Lancet Oncol, 2025, 26 (3): 312- 319. doi: 10.1016/S1470-2045(24)00676-4
41	Shitara K , Bang YJ , Wyrwicz LS , et al. Neoadjuvant/adjuvant pembrolizumab (pembro)+chemotherapy (chemo) vs placebo (pbo)+chemo for gastric/gastroesophageal junction (G/GEJ) adenocarcinoma: Major pathologic response (mPR) in KEYNOTE-585[J]. J Clin Oncol, 2024, 42 (Suppl 16): 4073.
42	André T , Tougeron D , Piessen G , et al. Neoadjuvant nivolumab plus ipilimumab and adjuvant nivolumab in localized deficient mismatch repair/microsatellite instability-high gastric or esophagogastric junction adenocarcinoma: The GERCOR NEONIPIGA phase Ⅱ study[J]. J Clin Oncol, 2023, 41 (2): 255- 265. doi: 10.1200/JCO.22.00686
43	Tabernero J , Al-Batran SE , Wainberg ZAA , et al. LBA81 final overall survival (OS) and the association of pathological outcomes with event-free survival (EFS) in MATTERHORN: A randomised, phase Ⅲ study of durvalumab (D) plus 5-fluorouracil, leucovorin, oxaliplatin and docetaxel (FLOT) in resectable gastric/gastroesophageal junction (G/GEJ) adenocarcinoma[J]. Ann Oncol, 2025, 36, S1623- S1624. doi: 10.1016/j.annonc.2025.09.096
44	Peng Z , Zhang X , Liang H , et al. Atezolizumab and trastuzumab plus chemotherapy in patients with HER2+ locally advanced resectable gastric cancer or adenocarcinoma of the gastroesophageal junction: A multicenter, randomized, open-label phase Ⅱ study[J]. J Clin Oncol, 2024, 42 ((Suppl 3): 312.
45	Li C , Tian Y , Zheng Y , et al. Pathologic response of phase Ⅲ study: Perioperative camrelizumab plus rivoceranib and chemotherapy versus chemotherapy for locally advanced gastric cancer (DRAGON Ⅳ/CAP 05)[J]. J Clin Oncol, 2025, 43 (4): 464- 474. doi: 10.1200/JCO.24.00795
46	Leong T , Smithers BM , Michael M , et al. Preoperative chemoradiotherapy for resectable gastric cancer[J]. N Engl J Med, 2024, 391 (19): 1810- 1821. doi: 10.1056/NEJMoa2405195
47	Janjigian YY , Kawazoe A , Bai Y , et al. 1400O Final overall survival for the phase Ⅲ, KEYNOTE-811 study of pembrolizumab plus trastuzumab and chemotherapy for HER2⁺ advanced, unresectable or metastatic G/GEJ adenocarcinoma[J]. Ann Oncol, 2024, 35, S877- S878. doi: 10.1016/j.annonc.2024.08.1466
48	Elimova E , Shitara K , Moehler MH , et al. Nivolumab (NIVO)+chemotherapy (chemo) vs chemo as first-line (1L) treatment for advanced gastric cancer/gastroesophageal junction cancer/esophageal adenocarcinoma (GC/GEJC/EAC): 4-year follow-up of CheckMate 649[J]. J Clin Oncol, 2024, 42 (Suppl 16): 4040.
49	Shen L , Zhang Y , Li Z , et al. First-line cadonilimab plus chemotherapy in HER2-negative advanced gastric or gastroesophageal junction adenocarcinoma: A randomized, double-blind, phase 3 trial[J]. Nat Med, 2025, 31 (4): 1163- 1170. doi: 10.1038/s41591-024-03450-4
50	Shitara K , Lordick F , Bang YJ , 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[J]. Lancet, 2023, 401 (10389): 1655- 1668. doi: 10.1016/S0140-6736(23)00620-7
51	Shitara K , Bang YJ , Iwasa S , et al. Trastuzumab deruxtecan in HER2-positive advanced gastric cancer: Exploratory biomarker analysis of the randomized, phase 2 DESTINY-Gastric01 trial[J]. Nat Med, 2024, 30 (7): 1933- 1942. doi: 10.1038/s41591-024-02992-x
52	Qi C , Liu C , Gong J , et al. Claudin18.2-specific CAR T cells in gastrointestinal cancers: Phase 1 trial final results[J]. Nat Med, 2024, 30 (8): 2224- 2234. doi: 10.1038/s41591-024-03037-z

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

[1]	高加勒, 张忠涛. 局部进展期直肠癌精准治疗现状与展望[J]. 北京大学学报（医学版）, 2026, 58(2): 247-250.
[2]	王海, 江一舟. 靶向血管治疗在乳腺癌精准治疗中的分子机制与临床应用[J]. 北京大学学报（医学版）, 2026, 58(2): 251-256.
[3]	杜文, 章文博, 于尧, 刘硕, 苏惠裕, 胡耒豪, 唐祖南, 吴彬彰, 陈震, 李家琦, 王昊, 彭歆. 口腔颌面部肿瘤"数智化外科"诊疗流程探索与临床应用[J]. 北京大学学报（医学版）, 2026, 58(2): 278-284.
[4]	刘友东, 吕亚军, 陈杰, 臧明德, 潘宏达, 刘晓文, 陆俊, 刘凤林. 全腹腔镜保留贲门胃底胃次全切除术治疗中上部胃癌的疗效及安全性[J]. 北京大学学报（医学版）, 2026, 58(2): 301-306.
[5]	李嘉临, 陈力侨, 唐家天, 吴艳, 王安强. 胃肝样腺癌转化治疗1例[J]. 北京大学学报（医学版）, 2026, 58(2): 399-404.
[6]	李斌, 梁寒. 机器人胃癌根治术：研究进展与实践挑战[J]. 北京大学学报（医学版）, 2026, 58(2): 416-422.
[7]	邓旭亮, 徐明明, 杜宸临. 人工智能驱动口腔医学：临床、科研、教学与管理的创新探索[J]. 北京大学学报（医学版）, 2025, 57(5): 821-826.
[8]	李浙民, 季加孚, 李国新, 李子禹, 步召德, 高翔宇, 董迪, 唐磊, 邢晓芳, 贾淑芹, 郭婷, 张连海, 陕飞, 季鑫, 王安强. 胃癌精准诊疗技术的创建与推广[J]. 北京大学学报（医学版）, 2025, 57(5): 864-867.
[9]	许克新,丁泽华. 人工智能在功能泌尿外科的应用[J]. 北京大学学报（医学版）, 2023, 55(5): 771-774.
[10]	刘想,谢辉辉,许玉峰,张晓东,陶晓峰,柳林,王霄英. 人工智能对提高放射科住院医生诊断胸部肋骨骨折一致性的价值[J]. 北京大学学报（医学版）, 2023, 55(4): 670-675.
[11]	侯卫华,宋书杰,石中月,金木兰. 幽门螺杆菌阴性早期胃癌的临床病理特征[J]. 北京大学学报（医学版）, 2023, 55(2): 292-298.
[12]	孙玉春,郭雨晴,陈虎,邓珂慧,李伟伟. 口腔精准仿生修复技术的自主创新研发与转化[J]. 北京大学学报（医学版）, 2022, 54(1): 7-12.
[13]	武颖超,蔡云龙,戎龙,张继新,刘金,汪欣. 早期胃癌淋巴结转移规律及内镜黏膜下剥离术治疗早期胃癌的疗效评价[J]. 北京大学学报（医学版）, 2020, 52(6): 1093-1097.
[14]	杨阳,刘毅强,王晓红,季科,李忠武,白健,杨爱蓉,胡颖,韩海勃,李子禹,步召德,吴晓江,张连海,季加孚. 单中心大样本Epstein-Barr病毒相关性胃癌亚型的临床病理及分子特征分析[J]. 北京大学学报（医学版）, 2019, 51(3): 451-458.
[15]	高翔，陈香梅，张婷，张静，陈茉，郭正阳，石岩岩，鲁凤民，丁士刚. 巨噬细胞加帽蛋白与胃癌细胞增殖及迁移能力的关系[J]. 北京大学学报(医学版), 2017, 49(3): 489-494.