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112 Circulating and molecular markers of inflammation: impact on treatment response and survival among older patients with cancer treated with immune checkpoint inhibitors
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  1. Khalil Choucair1,
  2. Caroline Nebhan2,
  3. Alessio Cortellini3,
  4. Stijn Hentzen4,
  5. Yinghong Wang5,
  6. April Salama6,
  7. Andrew Elliott7,
  8. Matthew Oberley7,
  9. Phillip Walker7,
  10. Raza Bokhari5,
  11. Raffaele Giusti8,
  12. Marco Filetti9,
  13. Paolo Ascierto10,
  14. Vito Vannella11,
  15. Domenico Galetta12,
  16. Annamaria Catino12,
  17. Pamela Pizzutilo12,
  18. Carlo Genova13,
  19. Melissa Bersanelli14,
  20. Sebastiano Buti14,
  21. Azhaar Saeed15,
  22. Wafik El-Deiry16,
  23. Himisha Beltran17,
  24. Chadi Nabhan7,
  25. Douglas Johnson2,
  26. Claudia Fulgenzi18,
  27. David Pinato18,
  28. Maluki Radford4,
  29. Stephen Liu19,
  30. Chul Kim19,
  31. Rafeh Naqash20 and
  32. Anwaar Saeed21
  1. 1Karmanos Cancer Institute/Wayne State University, Detroit, MI, USA
  2. 2Vanderbilt-Ingram Cancer Center, Nashville, TN, USA
  3. 3Hammersmith Hospital, Imperial College London; Fondazione Policlinico Campus Bio-Medico, London, UK
  4. 4Kansas University Medical Center, Kansas City, KS, USA
  5. 5UT MD Anderson Cancer Center, Houston, TX, USA
  6. 6Duke Cancer Institute, Durham, NC, USA
  7. 7Caris Life Sciences, Phoenix, AZ, USA
  8. 8Azienda Ospedaliero Universitaria Sant’Andrea, Rome, Italy
  9. 9Fondazione Policlinico Universitario Agostino Gemelli, IRCC, Rome, Italy
  10. 10Istituto Nazionale Tumori-Fondazione Pascale, Milan, Italy
  11. 11Istituto Nazionale Tumori IRCCS Fondazione Pascale, Napoli, Italy
  12. 12IRCCS Istituto Tumori Giovanni Paolo II, Bari, Italy
  13. 13UOC Clinica di Oncologia Medica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
  14. 14University Hospital of Parma, Parma, Italy
  15. 15University of Minnesota, Minneapolis, MN, USA
  16. 16Cancer Center at Brown University, Providence, RI, USA
  17. 17Dana Farber Cancer Institute, Boston, MA, USA
  18. 18Hammersmith Hospital Campus, Imperial College London, London, UK
  19. 19Georgetown University, Washington, DC, USA
  20. 20University of Oklahoma/Stephenson Cancer Center, Oklahoma, OK, USA
  21. 21Kansas University Cancer Center, Fairway, KS, USA

Abstract

Background Age-associated pro-inflammatory states may result in decreased response to immune checkpoint inhibitors (ICI) in older patients (pts) with cancer. We explored the association of circulating inflammatory markers with response to ICIs, and investigate potential differences in transcriptional and TME signatures of pts ≥80-years (yr) of age and younger.

Methods We built a multicenter, international database of pts with different tumors treated with ICIs monotherapy between 2011 and 2021 from 11 academic centers in the US and Europe. Retrospective analysis of 885 pts compared objective response rates (ORR; iRECIST), median progression-free survival (mPFS) and overall survival (mOS) between pts ≥80-yr and <80-yr, and stratified them across serum pre-treatment levels of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII=PxN/L). Optimal cut-off values for high (H) vs. low (L) levels were determined using receiver operating characteristic curves.

DNA (592-gene panel/whole exome) and RNA (whole transcriptome) next-generation sequencing, immunohistochemistry (IHC) and TME analysis (MCP-counter) were performed on 24,123 independent samples of non-small cell lung cancer (NSCLC), melanoma (MEL) and renal cell carcinoma (RCC) submitted to a CLIA-certified laboratory (Caris Life Sciences, Phoenix, AZ). Results were compared between pts ≥80-yr and <80-yr.

Results Table 1 summarizes pts baseline characteristics. Pts <80-yr had better ORR (P<0.01), but comparable mOS and mPFS to ≥80-yr (table 2). In pts ≥80-yr, NLR-L and SII-L were associated with higher ORR (P<0.01 and P<0.05; figure 1). All pts with NLR-L, MLR-L and SII-L, had longer mOS (P<0.01; figure 2). All PLR-L and SII-L pts had significantly longer mPFS (P<0.01; figure 3).

Compared to pts <80-yr, NSCLC ≥80-yr had increased abundance of fibroblasts, dendritic cells and macrophages (P<0.01) in their TME and lower TMB-H (P<0.001). MEL ≥80-yr pts had fewer TME infiltrating T-lymphocytes (P=0.02), a1.24-fold increased expression of IL-6. RCC ≥80-yr pts had 0.56-fold decreased expression of GZMB, and lower PD-L1 (IHC-SP142, ≥2+|5%) expression (P<0.05; figure 4). Additional correlative biomarkers will be reported in the poster.

Conclusions Lower levels of circulating inflammatory markers associated with significantly longer survival and better response rates to ICIs. SII-L and NLR-L specifically are potential biomarkers of response to ICI in pts ≥80-yr. This is the first study to evaluate the role of serum markers of inflammation as potential biomarkers of response to ICI in older pts with cancer, along with molecular correlate. Circulating inflammatory markers, and associated gene expression and TME composition suggest potential unique, cancer-specific biomarkers of response to ICIs in this population.

Ethics Approval The study was approved by the institutional review board at each participating institution. Written informed consent was waived, given the retrospective nature of the study and the de-identified status of collected data.

Abstract 112 Table 1

Baseline characteristics of patients

Abstract 112 Table 2

Treatment response and survival

Abstract 112 Figure 1

Objective response rates (ORR)Objective response rates (ORR) in patients < 80 vs. ≥ 80 years, stratified by pre-treatment levels of inflammatory markers: ICI: immune checkpoint inhibitory; NLR: neutrophil-to-lymphocyte ratio; H: high; L: low

Abstract 112 Figure 2A

Kaplan-Meier plot of overall survival by NLR levelKaplan-Meier plot of overall survival (OS) from ICI initiation, for patients < 80 and ≥ 80 years, stratified according to pre-treatment NLR levels: ICI: immune checkpoint inhibitor; NLR: neutrophil-to-lymphocyte ratio; H: high; L: low; 95%CI: 95% confidence interval

Abstract 112 Figure 2B

Kaplan-Meier plot of overall survival by MLR levelKaplan-Meier plot of overall survival (OS) from ICI initiation, for patients < 80 and ≥ 80 years, stratified according to pre-treatment MLR levels: ICI: immune checkpoint inhibitor; MLR: monocyte-to-lymphocyte ratio; H: high; L: low; 95%CI: 95% confidence interval

Abstract 112 Figure 2C

Kaplan-Meier plot of overall survival by SII levelKaplan-Meier plot of overall survival (OS) from ICI initiation, for patients < 80 and ≥ 80 years, stratified according to pre-treatment SII levels: ICI: immune checkpoint inhibitor; SII: Systemic immune-inflammatory index; H: high; L: low; 95%CI: 95% confidence interval

Abstract 112 Figure 3A

Kaplan-Meier plot of PFS by PLR levelKaplan-Meier plot of progression-free survival (PFS) from ICI initiation, for patients < 80 and ≥ 80 years, stratified according to pre-treatment PLR levels: ICI: immune checkpoint inhibitor; PLR: platelets-to-lymphocyte ratio; H: high; L: low; 95%CI: 95% confidence interval

Abstract 112 Figure 3B

Kaplan-Meier plot of PFS by SII levelKaplan-Meier plot of progression-free survival (PFS) from ICI initiation, for patients < 80 and ≥ 80 years, stratified according to pre-treatment SII levels: ICI: immune checkpoint inhibitor; SII: systemic immune-inflammation index; H: high; L: low; 95%CI: 95% confidence interval

Abstract 112 Figure 4

ICI-related biomarkers (A) and (B)TME compositionICI-related biomarkers (A) and composition of the TME (B) in patients ≥ 80 and < 80 years: Fold-changes represent the median value of patients ≥ 80 years compared to those < 80 years. ICI: immune checkpoint inhibitor; TME: tumor microenvironment; TMB-H: high tumor mutation burden; NSCLC: non-small cell lung cancer; MEL: melanoma; PD-L1: programmed-death ligand-1; RCC: renal cell carcinoma

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