Artificial <scp>intelligence‐powered</scp> spatial analysis of <scp>tumor‐infiltrating</scp> lymphocytes as a predictive biomarker for axitinib in adenoid cystic carcinoma-Reference-Cited by-同舟云学术

Artificial intelligence‐powered spatial analysis of tumor‐infiltrating lymphocytes as a predictive biomarker for axitinib in adenoid cystic carcinoma

Published:2023-10-13 Issue:12 Volume:45 Page:3086-3095
ISSN:1043-3074
Container-title:Head & Neck
language:en
Short-container-title:Head & Neck

Author:

Kim Dong Hyun¹^ORCID,Lim Yoojoo²,Ock Chan‐Young²,Park Gahee²,Park Seonwook²,Song Heon²,Ma Minuk²,Mostafavi Mohammad²,Kang Eun Joo³^ORCID,Ahn Myung‐Ju⁴,Lee Keun‐Wook⁵,Kwon Jung Hye⁶,Yang Yaewon⁷,Choi Yoon Hee⁸,Kim Min Kyoung⁹,Ji Jun Ho¹⁰,Yun Tak¹¹,Kim Sung‐Bae¹²,Keam Bhumsuk¹¹³^ORCID

Affiliation:

1. Department of Internal Medicine Seoul National University Hospital Seoul South Korea

2. Lunit Seoul South Korea

3. Department of Internal Medicine, Korea University Guro Hospital Korea University College of Medicine Seoul South Korea

4. Department of Medicine, Samsung Medical Center Sungkyunkwan University School of Medicine Seoul South Korea

5. Department of Internal Medicine, Seoul National University College of Medicine Seoul National University Bundang Hospital Seongnam South Korea

6. Department of Internal Medicine Chungnam National University College of Medicine Daejeon South Korea

7. Department of Internal Medicine Chungbuk National University Hospital Cheongju South Korea

8. Department of Internal Medicine Dongnam Institute of Radiological and Medical Sciences Busan South Korea

9. Division of Hematology‐Oncology, Department of Internal Medicine, Yeungnam University Hospital Yeungnam University College of Medicine Daegu South Korea

10. Department of Internal Medicine, Samsung Changwon Hospital Sungkyunkwan University School of Medicine Changwon South Korea

11. Rare Cancers Clinic, Center for Specific Organs Cancer National Cancer Center Goyang South Korea

12. Department of Oncology, Asan Medical Center University of Ulsan College of Medicine Seoul South Korea

13. Cancer Research Institute Seoul National University College of Medicine Seoul South Korea

Abstract

AbstractBackgroundThis study analyzed the predictive value of artificial intelligence (AI)‐powered tumor‐infiltrating lymphocyte (TIL) analysis in recurrent or metastatic (R/M) adenoid cystic carcinoma (ACC) treated with axitinib.MethodsPatients from a multicenter, prospective phase II trial evaluating axitinib efficacy in R/M ACC were included in this study. H&E whole‐side images of archival tumor tissues were analyzed by Lunit SCOPE IO, an AI‐powered spatial TIL analyzer.ResultsTwenty‐seven patients were included in the analysis. The best response was stable disease, and the median progression‐free survival (PFS) was 11.1 months (95% CI, 9.2–13.7 months). Median TIL densities in the cancer and surrounding stroma were 25.8/mm2 (IQR, 8.3–73.0) and 180.4/mm2 (IQR, 69.6–342.8), respectively. Patients with stromal TIL density >342.5/mm2 exhibited longer PFS (p = 0.012).ConclusionsCancer and stromal area TIL infiltration were generally low in R/M ACC. Higher stromal TIL infiltration was associated with a longer PFS with axitinib treatment.

Funder

AstraZeneca

MSD

Ono Pharmaceutical

Publisher

Wiley

Subject

Otorhinolaryngology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hed.27537

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