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202 Spatial analysis of tumor-infiltrating lymphocytes in tumor microenvironment in non-small cell lung cancer patients who have resistance after EGFR tyrosine kinase inhibitors
  1. Yeong Hak Bang1,
  2. Chang Ho Ahn2,
  3. CheolYong Joe1,
  4. Sehhoon Park1,
  5. Hyun Ae Jung1,
  6. Yoon-La Choi1,
  7. Jin Seok Ahn1,
  8. Myung Ju Ahn1,
  9. Seunghwan Shin2,
  10. Chan-Young Ock2 and
  11. Se-Hoon Lee1
  1. 1Samsung Medical Center, Seoul, Republic of Korea
  2. 2Lunit Inc., Seoul, 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 Immune checkpoint inhibitors (ICI) were known to be of limited benefit for patients with non-small cell lung cancer (NSCLC) harboring EGFR mutations. Nevertheless, some of the patients showed response from ICI after acquiring resistance to EGFR tyrosine kinase inhibitors (TKI), and there is an unmet need for predictive biomarkers. Here, we assessed TILs using artificial intelligence (AI)-powered spatial analysis in EGFR-mutated NSCLC patients pre- and post-TKI treatment.

Methods A total of 76 patients who were treated with ICI post-progression after EGFR TKI at Samsumg Medical Center were included in the analysis. An AI-powered whole-slide image (WSI) analyzer (Lunit SCOPE IO, Lunit, Seoul, Korea) was used to segment tumor epithelium and stroma and identify intratumor TIL (iTIL) and stromal TIL (sTIL). Immune phenotypes (IP) were defined as follows: inflamed as high iTIL and sTIL; immune-excluded as low iTIL and high sTIL; immune-desert as low TIL overall. Among the study cohort, 52 patients were available to evaluate PD-L1 tumor proportion score (TPS), and 48 paired pre-TKI samples were available to investigate IP.

Results A total of 32 (42.1%) patients showed T790M mutation when performing the second biopsy, and 14 (18.4%) patients were administered cisplatin after TKI and prior to sample acquisition. Most patients (N=74, 97.3%) received ICI monotherapy as beyond 3rd line treatment. Among the 48 patients with paired pre- and post-TKI pathologic samples, IP of pre-TKI biopsy exhibited inflamed in 6 (12.5%), immune-excluded in 13 (27.1%), and immune-desert in 29 (60.4%). Among the 6 inflamed IP, 4 patients (66.7%) changed to other IP, and 4 of 29 immune-desert IP (13.8%) changed to inflamed IP after EGFR-TKI (figure 1A). Meanwhile, the TPS was increased after EGFR-TKI, showing patients with a TPS ≥50% increased from 4 (14.3%) to 7 (25.0%) after EGFR-TKI (figure 1B). With a median follow-up duration of 28.5 months, inflamed IP after TKI showed higher overall response (40.0% vs. 7.5%, P=0.023), and better progression-free survival (PFS; 4.1 vs. 1.4 months, HR=0.462 [95% CI, 0.226–0.944], P = 0.034) than other IP groups to ICI treatment, and this trend was prominent for patients with inflamed IP and TPS>50 (PFS; 12.2 vs. 1.4 months, HR=0.168 [95% CI, 0.040–0.704], P = 0.015) (figure 1C,D).

Conclusions Our findings suggest that EGFR-TKI affects immune landscape of EGFR-mutated NSCLC as higher PD-L1 expression and differential IPs. Inflamed IP after EGFR-TKI was significantly associated with favorable response to ICI as subsequent treatment.

Ethics Approval This study was approved by the Institutional Review Board (IRB) of Samsung Medical Center (IRB numbers SMC-2018–06-103) and conducted according to the Helsinki Declaration.

Consent This abstract does not contain sensitive or identifiable information.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See

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