Histo- and immunohistochemistry-based estimation of the TCGA and ACRG molecular subtypes for gastric carcinoma and their prognostic significance: A single-institution study

Autoři: Ju-Yoon Yoon aff001;  Keiyan Sy aff002;  Christine Brezden-Masley aff003;  Catherine J. Streutker aff001
Působiště autorů: Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada aff001;  Department of Pathology, St. Michael’s Hospital, Toronto, Ontario, Canada aff002;  Department of Hematology/Oncology, St. Michael’s Hospital, Toronto, Ontario, Canada aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0224812


Gastric cancers comprise molecularly heterogeneous diseases; four molecular subtypes were identified in the cancer genome atlas (TCGA) study, with implications in patient management. In our efforts to devise a clinically feasible means of subtyping, we devised an algorithm based on histology and five stains available in most academic pathology laboratories. This algorithm was used to subtype our cohort of 107 gastric cancer patients from a single institution (St. Michael’s Hospital, Toronto, Canada), which was divided into 3 cases of EBV-positive, 23 of MSI, 27 of GS and 54 of CIN tumours. 87% of the tumours with diffuse histology were classified as GS subtype, which was notable for younger age. Examining for characteristic molecular features, aberrant p53 immunostaining was seen most frequently in the CIN subtype (43% in CIN vs. 6% in others), whereas ARID1A loss was rarely seen (6% vs. 35% in others). HER2 overexpression was seen exclusively in CIN tumours (17% of CIN tumours). PD-L1 positivity was seen predominantly in the EBV and MSI tumours. As with the TCGA study, no survival differences were seen between the subtypes. A similar strategy was employed to approximate the Asian Cancer Research Group (ACRG) molecular subtyping, with the addition of p53 IHC to the algorithm. We observed rates of ARID1A loss and HER2 overexpression that were comparable to the ACRG study. In summary, our algorithm allowed for clinically feasible means of subtyping gastric carcinoma that recapitulated the key molecular features reported in the large scale studies.

Klíčová slova:

Adenocarcinomas – Cancer detection and diagnosis – Cancer treatment – Gastric cancer – Histology – Immunohistochemistry techniques – Immunostaining – Surgical pathology


1. The Cancer Genome Atlas Research N. Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 2014;513(7517):202–9. http://www.nature.com/nature/journal/v513/n7517/abs/nature13480.html#supplementary-information 25079317

2. Lei Z, Tan IB, Das K, Deng N, Zouridis H, Pattison S, et al. Identification of Molecular Subtypes of Gastric Cancer With Different Responses to PI3-Kinase Inhibitors and 5-Fluorouracil. Gastroenterology. 2013;145(3):554–65 http://doi.org/10.1053/j.gastro.2013.05.010 23684942

3. Cristescu R, Lee J, Nebozhyn M, Kim K-M, Ting JC, Wong SS, et al. Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes. Nat Med. 2015;21(5):449–56. http://www.nature.com/nm/journal/v21/n5/abs/nm.3850.html#supplementary-information 25894828

4. Kim HS, Shin S-J, Beom S-H, Jung M, Choi YY, Son T, et al. Comprehensive expression profiles of gastric cancer molecular subtypes by immunohistochemistry: implications for individualized therapy. Oncotarget. 2016;7(28):44608–20. doi: 10.18632/oncotarget.10115 27331626

5. Wiegand KC, Sy K, Kalloger SE, Li-Chang H, Woods R, Kumar A, et al. ARID1A/BAF250a as a prognostic marker for gastric carcinoma: a study of 2 cohorts. Hum Pathol. 2014;45(6):1258–68. Epub 2014/04/29. doi: 10.1016/j.humpath.2014.02.006 24767857.

6. Bartley AN, Washington MK, Ventura CB, Ismaila N, Colasacco C, Benson AB 3rd, et al. HER2 Testing and Clinical Decision Making in Gastroesophageal Adenocarcinoma: Guideline From the College of American Pathologists, American Society for Clinical Pathology, and American Society of Clinical Oncology. Arch Pathol Lab Med. 2016;140(12):1345–63. Epub 2016/11/15. doi: 10.5858/arpa.2016-0331-CP 27841667.

7. Shia J. Immunohistochemistry versus Microsatellite Instability Testing For Screening Colorectal Cancer Patients at Risk For Hereditary Nonpolyposis Colorectal Cancer Syndrome: Part I. The Utility of Immunohistochemistry. The Journal of Molecular Diagnostics: JMD. 2008;10(4):293–300. doi: 10.2353/jmoldx.2008.080031 18556767

8. Bae YS, Kim H, Noh SH, Kim H. Usefulness of Immunohistochemistry for Microsatellite Instability Screening in Gastric Cancer. Gut and Liver. 2015;9(5):629–35. doi: 10.5009/gnl15133 26343070

9. Camargo MC, Kim W-H, Chiaravalli AM, Kim K-M, Corvalan AH, Matsuo K, et al. Improved survival of gastric cancer with tumour Epstein–Barr virus positivity: an international pooled analysis. Gut. 2014;63(2):236–43. doi: 10.1136/gutjnl-2013-304531 23580779

10. Wang K, Kan J, Yuen ST, Shi ST, Chu KM, Law S, et al. Exome sequencing identifies frequent mutation of ARID1A in molecular subtypes of gastric cancer. Nat Genet. 2011;43(12):1219–23. http://www.nature.com/ng/journal/v43/n12/abs/ng.982.html#supplementary-information 22037554

11. Liu L, Wang ZW, Ji J, Zhang JN, Yan M, Zhang J, et al. A cohort study and meta-analysis between histopathological classification and prognosis of gastric carcinoma. Anti-cancer agents in medicinal chemistry. 2013;13(2):227–34. Epub 2012/09/01. doi: 10.2174/1871520611313020007 22934699.

12. Petrelli F, Berenato R, Turati L, Mennitto A, Steccanella F, Caporale M, et al. Prognostic value of diffuse versus intestinal histotype in patients with gastric cancer: a systematic review and meta-analysis. Journal of gastrointestinal oncology. 2017;8(1):148–63. Epub 2017/03/11. doi: 10.21037/jgo.2017.01.10 28280619.

13. Wang HH, Wu MS, Shun CT, Wang HP, Lin CC, Lin JT. Lymphoepithelioma-like carcinoma of the stomach: a subset of gastric carcinoma with distinct clinicopathological features and high prevalence of Epstein-Barr virus infection. Hepato-gastroenterology. 1999;46(26):1214–9. Epub 1999/06/17. 10370694.

14. Setia N, Agoston AT, Han HS, Mullen JT, Duda DG, Clark JW, et al. A protein and mRNA expression-based classification of gastric cancer. Mod Pathol. 29(7):772–84. Epub 2016/04/02. doi: 10.1038/modpathol.2016.55 27032689.

15. Ahn S, Lee SJ, Kim Y, Kim A, Shin N, Choi KU, et al. High-throughput Protein and mRNA Expression-based Classification of Gastric Cancers Can Identify Clinically Distinct Subtypes, Concordant With Recent Molecular Classifications. The American journal of surgical pathology. 41(1):106–15. Epub 2016/11/08. doi: 10.1097/PAS.0000000000000756 27819872.

16. Zhu LIN, Li ZHI, Wang YAN, Zhang C, Liu Y, Qu X. Microsatellite instability and survival in gastric cancer: A systematic review and meta-analysis. Molecular and Clinical Oncology. 2015;3(3):699–705. doi: 10.3892/mco.2015.506 26137290

17. Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. New England Journal of Medicine. 2015;372(26):2509–20. doi: 10.1056/NEJMoa1500596 26028255.

18. Gonzalez RS, Messing S, Tu X, McMahon LA, Whitney-Miller CL. Immunohistochemistry as a surrogate for molecular subtyping of gastric adenocarcinoma. Hum Pathol. 2016;56:16–21. Epub 2016/06/28. doi: 10.1016/j.humpath.2016.06.003 27342907.

19. Mathiak M, Warneke VS, Behrens H-M, Haag J, Böger C, Krüger S, et al. Clinicopathologic Characteristics of Microsatellite Instable Gastric Carcinomas Revisited: Urgent Need for Standardization. Applied Immunohistochemistry & Molecular Morphology. 2017;25(1):12–24. doi: 10.1097/pai.0000000000000264 26371427

20. Birkman E-M, Mansuri N, Kurki S, Ålgars A, Lintunen M, Ristamäki R, et al. Gastric cancer: immunohistochemical classification of molecular subtypes and their association with clinicopathological characteristics. Vichows Archiv A Pathol Anat. 2018;472(3):369–82. doi: 10.1007/s00428-017-2240-x 29046940

21. Kulangara K, Hanks DA, Waldroup S, Peltz L, Shah S, Roach C, et al. Development of the combined positive score (CPS) for the evaluation of PD-L1 in solid tumors with the immunohistochemistry assay PD-L1 IHC 22C3 pharmDx. Journal of Clinical Oncology. 2017;35(15_suppl):e14589–e. doi: 10.1200/JCO.2017.35.15_suppl.e14589

22. Parra ER, Villalobos P, Mino B, Rodriguez-Canales J. Comparison of Different Antibody Clones for Immunohistochemistry Detection of Programmed Cell Death Ligand 1 (PD-L1) on Non-Small Cell Lung Carcinoma. Applied immunohistochemistry & molecular morphology: AIMM. 2018;26(2):83–93. Epub 2017/07/19. 28719380.

23. Giunchi F, Degiovanni A, Daddi N, Trisolini R, Dell’Amore A, Agostinelli C, et al. Fading With Time of PD-L1 Immunoreactivity in Non-Small Cells Lung Cancer Tissues: A Methodological Study. Applied immunohistochemistry & molecular morphology: AIMM. 2018;26(7):489–94. Epub 2016/11/02. doi: 10.1097/pai.0000000000000458 27801735.

24. Truong CD, Feng W, Li W, Khoury T, Li Q, Alrawi S, et al. Characteristics of Epstein-Barr virus-associated gastric cancer: a study of 235 cases at a comprehensive cancer center in U.S.A. Journal of experimental & clinical cancer research: CR. 2009;28:14. Epub 2009/02/05. doi: 10.1186/1756-9966-28-14 19192297.

25. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA: a cancer journal for clinicians. 2018;68(1):7–30. doi: 10.3322/caac.21442 29313949

Článek vyšel v časopise


2019 Číslo 12
Nejčtenější tento týden