Abstract 900P
Background
The efficacy of immune checkpoint inhibitors (ICIs) in neuroendocrine neoplasms (NEN) has not been fully explored, but recent clinical trials showed the effectiveness of ICIs in high-grade NEN. Despite the importance of tumor-infiltrating lymphocytes (TIL) and PD-L1 expression to ICI treatment outcomes, a comprehensive assessment of these biomarkers has not yet been conducted in NEN. We investigated PD-L1 expression and TIL distributions in NENs using an artificial intelligence (AI)-powered analyzer.
Methods
A total of 218 NEN cases were obtained from Ajou University Medical Center in Korea from 2020 to 2021. Primary sites include colorectum (N=158), small intestine (N=16), stomach (N=15), hepatopancreatobiliary (N=15), lung (N=7), and other organs (N=7). Low/intermediate grade NEN (neuroendocrine tumor [NET] G1/G2) and high grade NEN (NET G3 or neuroendocrine carcinoma) were 190 and 28, respectively. TIL distribution was derived from Lunit SCOPE IO, an AI-powered H&E analyzer, which was developed from 17,849 H&E WSI. Two pathologists interpreted the combined positive score (CPS) of PD-L1 22C3-stained slides.
Results
The proportion of intratumoral TIL high cases (upper than median TIL density) was higher in high grade NEN (75% vs 46%, P<0.01, Odds ratio 3.477 [IQR: 1.393 – 9.148]). Stromal TIL and combined (intratumoral and stromal) TIL densities showed insignificant differences between histologic groups. The proportion of PD-L1 CPS ≥ 1 cases was higher in high grade NEN (85% vs 33%, P < 0.0001, Odds ratio 12.1 [IQR: 4.169 – 33.15]). The PD-L1 CPS ≥ 1 group showed significantly higher intratumoral, stromal, and combined TIL densities compared to the CPS < 1 group (7.13 vs 2.95, P < 0.0001; 200.9 vs 120.5, P < 0.001; 86.7 vs 56.1, P<0.01). A significant correlation was observed between TIL density and PD-L1 CPS (r=0.37, P<0.0001 for intratumoral TIL; r=0.24, P<0.01 for stromal TIL and combined TIL).
Conclusions
AI-powered TIL analysis reveals that intra-tumoral TIL density is significantly higher in high grade NEN, and PD-L1 CPS has a positive correlation with TIL densities. Thus, AI-powered TIL analysis and PD-L1 CPS can be investigated as predictive biomarkers for ICI response in NEN.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Lunit Inc.
Funding
Lunit Inc.
Disclosure
H. Cho, W. Jung, S. Kim, G. Park, S. Song, S. Pereira, S. Park, M. Mostafavi, K. Paeng: Financial Interests, Personal, Full or part-time Employment: Lunit Inc. S.I. Cho: Financial Interests, Personal, Full or part-time Employment: Lunit Inc.; Financial Interests, Personal, Stocks/Shares: Lunit Inc. H. Song: Financial Interests, Personal, Ownership Interest: Lunit Inc. C. Ock: Financial Interests, Personal, Full or part-time Employment: Lunit Inc.; Financial Interests, Personal, Invited Speaker: Ybiologics; Financial Interests, Personal, Stocks/Shares: Lunit Inc., Ybiologics. All other authors have declared no conflicts of interest.