Artificial intelligence–powered tumor-infiltrating lymphocytes analyzer to reveal distinct immune landscapes in breast cancer by molecular subtype and HER2 score.

Authors

null

Seunghwan Shin

Oncology, Lunit, Seoul, Korea, Republic of (South)

Seunghwan Shin , Soo Youn Cho , Eun Yoon Cho , So-Woon Kim , Minsun Jung , Seung-Geun Song , Yoojoo Lim , Soo Ick Cho , Sukjun Kim , Gahee Park , Heon Song , Minuk Ma , Donggeun Yoo , Chan-Young Ock

Organizations

Oncology, Lunit, Seoul, Korea, Republic of (South), Department of Pathology and Translational Genomics, Samsung Medical Center, Seoul, South Korea, Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea, Department of Pathology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, South Korea, Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea, Department of Pathology, Seoul National University College of Medicine, Seoul, South Korea, Oncology, Lunit, Seoul, South Korea, Lunit Inc., Seoul, Korea, Republic of (South)

Research Funding

No funding received
None.

Background: Tumor-infiltrating lymphocytes (TIL) reflect an ongoing anti-tumor immune response in the tumor microenvironment (TME) and have been studied as a predictive as well as prognostic biomarker in breast cancer (BC). The immune profile differs depending on BC molecular subtypes, with triple-negative BC (TNBC) and HER2-positive BC more frequently infiltrated by higher numbers of TIL than hormone receptor (HR)-positive tumors. In this study, we analyze TIL and immune phenotype by molecular subtype in BC and explore differences based on HER2 scores using an AI-powered TIL analyzer. Methods: A total of 1,973 cases of BC with molecular subtype, HER2 immunohistochemistry (IHC) or in situ hybridization (ISH) results, and TIL analysis from H&E slides from TCGA (n=1021), Samsung Medical Center (SMC, n=663), and KyungHee Medical Center (KHMC, n=289) were included in the analysis. The density of TIL were spatially analyzed from H&E WSI, and the immune phenotype (IP) was analyzed for each 1 mm2-sized patch. Tumor microenvironment (TME) was categorized into three types: inflamed (TIL distributed intratumorally), Immune-excluded (TIL excluded, out of cancer stroma), immune-desert (scant TIL in TME), and the score for each IP was calculated as the percentage of the total patches in WSI. Results: TNBC showed the highest TIL density in both cancer epithelium (214.5 ± 299.7/mm2) and stroma (1133.3 ± 1245.9/mm2), and a high percentage of inflamed IP (35.7%), IS (28.4 ± 28.1) than other subtypes (inflamed IP: 17.5%, IS 16.2±20.2, both p<0.001). HER2-positive BCs showed higher sTIL density (904.0 ± 901.7/mm2) compared to HR- positive BC (616.7 ± 794.1/mm2) but were associated with a higher percentage of immune-excluded IP (71.2%) and IES (57.6 ± 24.6). HR-positive BC had a high percentage of immune-desert IP (30.4%). In both HR-positive and negative BCs, higher IES was observed as the HER2 score increased. HER2-positive BC significantly showed a higher proportion of cancer stroma in the cancer region from WSI (Stromal ratio, 0.682 ± 0.149 vs. 0.578 ± 0.176, p<0.001). Conclusions: Different TIL densities and IP were seen in BC for each molecular subtype, pointing to a distinct immune landscape. HER2 score was associated with immune-excluded IP despite having higher TIL density, which should be considered for immunotherapy in BC.

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Abstract Details

Meeting

2023 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Breast Cancer—Metastatic

Track

Breast Cancer

Sub Track

HER2-Positive

Citation

J Clin Oncol 41, 2023 (suppl 16; abstr 1049)

DOI

10.1200/JCO.2023.41.16_suppl.1049

Abstract #

1049

Poster Bd #

270

Abstract Disclosures

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