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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
  1. Jimin Moon1,
  2. Chang Ho Ahn1,
  3. Seunghwan Shin1,
  4. Seulki Kim1,
  5. Taebum Lee1,
  6. Soo Ick Cho1,
  7. Yoojoo Lim1,
  8. Mingu Kang1,
  9. Heon Song1,
  10. Donggeun Yoo1,
  11. Ken Nesmith1,
  12. Siraj Ali1,
  13. Chan-Young Ock1 and
  14. Seokhwi Kim2
  1. 1Lunit Inc., Seoul, Republic of Korea
  2. 2Ajou University School of Medicine, Suwon, Republic of Korea
  • Journal for ImmunoTherapy of Cancer (JITC) preprint. The copyright holder for this preprint are the authors/funders, who have granted JITC permission to display the preprint. All rights reserved. No reuse allowed without permission.


Background Tumor-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.

Methods The 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.

Results Overall, 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.

Conclusions Our 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.


  1. Lehmann 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.

  2. Lehmann BD, Jovanovi&cacute; 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.

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