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53 Predictors of response to immune checkpoint inhibitor therapy in metastatic solid tumors: real world evidence
  1. Aasems Jacob,
  2. Jianrong Wu,
  3. Jill Kolesar,
  4. Eric Durbin,
  5. Aju Mathew,
  6. Susanne Arnold and
  7. Aman Chauhan
  1. University of Kentucky, Lexington, KY, USA


Background Immune checkpoint inhibitor (ICI) therapy is increasingly being used in oncology and novel predictive biomarker for efficacy and side effects are an unmet need.1 2 The study aims to do a comprehensive analysis of factors affecting outcome from ICI therapy with real-world data and identify potential predictive biomarkers in diverse populations.

Methods We performed a retrospective analysis of patients with metastatic solid tumors who received ICI and underwent molecular profiling with FoundationOne® CDx panel between 2016 and 2020 at Markey Cancer Center, Lexington KY. Progression-free survival (PFS), radiological response, and autoimmune side effects were analyzed and compared with various molecular biomarkers (figure 1). Logistic regression, Fisher’s exact test, Kaplan-Meier method, log-rank test, and Cox regression were used to analyze clinical features and efficacy outcomes.

Abstract 53 Figure 1

Mutational analysis of patients receiving immunotherapy grouped based on radiologic response, in the order of mutational load and frequency of mutations

Abstract 53 Figure 2

Kaplan-Meier graphs depicting progression free survival in patients based on tumor samples showing (a) High TMB and low/intermediate TMB; (b) PDL1 expression; (c) Presence of IRAEs; (d) Presence of PIK3 mutation; (e) Presence of FGFR mutation; (f) Presence of BRAF mutation

Abstract 53 Table 1

Baseline characteristics of the study population

Abstract 53 Table 2

Treatment and biomarker characteristics of study population

Abstract 53 Table 3

ORR based on various factors with odds ratio calculated using logistic regression model

Abstract 53 Table 4

Identified PIK3 mutations in tumor samples, with their chromosomal position and protein changes

Results 69 patients were included in the study (tables 1 and 2). A statistically significant improvement in PFS was observed in the PIK3 mutated cohort (median 123 vs. 23 weeks. HR=2.51. 95%CI 1.23, 5.14; table 3 and figure 2). This was independent of tumor mutational burden (TMB) status or PDL1 expression status (HR 3.24, p=0.016). PIK3 mutants had a higher overall response rate (ORR) than the wild type (69.6% vs. 43.5%, OR 0.34; p=0.045; tables 3 and 4). PIK3 mutants had a higher risk of developing immune-related adverse events (IRAEs) (73.9% vs. 37%, p=0.004). PIK3 mutation did not associate with TMB, PDL1 expression or microsatellite stability status. Median PFS was higher in the high TMB cohort compared to the low-intermediate group and reached statistical significance (median not reached vs. 26 weeks; HR=0.37. 95%CI 0.13, 1.05). PDL1 expression had no significant effect on the radiologic response, but PFS improvement in patients with tumors expressing PDL1 trended towards statistical significance (median 18 vs. 40 weeks. HR=1.43. 95%CI 0.93, 4.46). BRAF mutation conferred shorter PFS (median 17 vs. 39 weeks. HR=0.35. 95%CI 0.14, 0.91) (figure 2).

Conclusions High tumor mutational burden and PIK3 mutation conferred better progression-free survival with immunotherapy across cancer types. The improvement in PFS in PIK3 mutated patients was independent of PDL1 status or TMB. The results should prompt further evaluation of these potential biomarkers and more widespread real-world data publications to help determine biomarkers that could benefit specific populations.

Ethics Approval The study was approved by University of Kentucky Institutional Review Board, approval number 49450


  1. Topalian SL, Hodi FS, Brahmer JR, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012;366(26):2443–2454.

  2. Spencer KR, Wang J, Silk AW, Ganesan S, Kaufman HL, Mehnert JM. Biomarkers for Immunotherapy: Current Developments and Challenges. Am Soc Clin Oncol Educ Book. 2016; 35:e493–503.

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