961 Tumor-infiltrating lymphocytes in tumor microenvironment assessed by artificial intelligence powered H&E image analyzer is correlated with immunomodulatory subtype of triple-negative breast cancer

• Published in: Journal for immunotherapy of cancer Vol. 11; no. Suppl 1; p. A1068
• Main Authors: Moon, Jimin, Ahn, Chang Ho, Shin, Seunghwan, Kim, Seulki, Lee, Taebum, Cho, Soo Ick, Lim, Yoojoo, Kang, Mingu, Song, Heon, Yoo, Donggeun, Nesmith, Ken, Ali, Siraj, Ock, Chan-Young, Kim, Seokhwi
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd 02-11-2023; BMJ Publishing Group LTD
• Subjects: Artificial intelligence; Biomarkers; Breast cancer; Immunotherapy; Mutation; Regular and Young Investigator Award Abstracts
• ISSN: 2051-1426
• DOI: 10.1136/jitc-2023-SITC2023.0961

BackgroundTumor-infiltrating lymphocytes (TILs) serve as both prognostic and predictive biomarker in triple-negative breast cancer (TNBC). TNBC exhibits six distinct molecular subtypes —basal-like 1, basal-like 2, mesenchymal, mesenchymal stem-like, immunomodulatory (IM), and luminal androgen receptor— which have clinical implications in terms of treatment response.1 2 In this study, we investigated the TIL distribution in the subtypes of TNBC, along with their association with driver mutations.MethodsThe Cancer Genome Atlas breast cancer dataset was analyzed using Lunit SCOPE IO, an artificial intelligence (AI)-powered H&E whole-slide image analyzer, which identifies TIL and distinguishes cancer and stromal area. TNBC was defined based on the bimodal distribution of ER, PR and HER2 gene expression, and the molecular subtype was determined based on the transcriptomic data.1 2 The presence of genomic alteration was obtained from cBioportal. The percentage of the area occupied by TIL among the total stromal, intratumoral and total tumoral area was defined as stromal (sTIL), intratumoral (iTIL) and total TIL (tTIL) scores, respectively. TIL area was computationally measured using area inflation method based on TIL coordinates detected by Lunit SCOPE IO.ResultsOverall, the median and interquartile range of iTIL, sTIL, and tTIL score in tumor microenvironment were 1.4% (0.7–3.3%), 14.8% (6.7–31.9%), and 7.6% (3.4–16.6%) in total TNBC samples (N = 180), respectively. Among 6 subtypes of TNBC, the mean iTIL (4.1% vs. 1.2%, p < 0.001), sTIL (36.7% vs. 12.5%, p < 0.001) and tTIL score (18.2% vs. 6.0%, p < 0.001) was significantly higher in the IM subtype than other 5 TNBC subtypes (figure 1A-C). The results of the receiver-operating-characteristic curve (ROC) analysis exhibited the optimal tTIL cut-off values at 10.0% (area under the ROC: 0.775; sensitivity 75.0% and specificity 68.1%) to distinguish IM subtype from the others (figure 2). Additionally, across all TNBC samples, those with PIK3CA mutation/amplification or PTEN loss (median 9.6% vs 6.6%, p=0.03), and BRCA1 or BRCA2 mutation (median 12.7% vs 7.1%, p=0.045) each showed higher tTIL score compared to those without mutation.ConclusionsOur findings reveal an enriched TIL distribution in the IM subtype compared to the others, while enrichment of total TIL was also associated with genomic alterations including BRCA mutations. The differential distribution of TIL highlights its potential as a valuable biomarker guiding optimal immuno-oncology treatment strategies.ReferencesLehmann BD, Bauer JA, Chen X, Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest. 2011;121(7):2750–67. doi: 10.1172/jci45014.Lehmann BD, Jovanovi B, Chen X, Refinement of Triple-Negative Breast Cancer Molecular Subtypes: Implications for Neoadjuvant Chemotherapy Selection. PLoS One. 2016;11(6):e0157368. doi: 10.1371/journal.pone.0157368.Abstract 961 Figure 1Abstract 961 Figure 2