Automated Quantitative CD8+ Tumor-Infiltrating Lymphocytes and Tumor Mutation Burden as Independent Biomarkers in Melanoma Patients Receiving Front-Line Anti-PD-1 Immunotherapy.

PD-1 PD-L1 TIL TMB/Mb biomarker immunotherapy melanoma metastatic tumor mutation burden

Journal

The oncologist
ISSN: 1549-490X
Titre abrégé: Oncologist
Pays: England
ID NLM: 9607837

Informations de publication

Date de publication:
24 Apr 2024
Historique:
received: 04 01 2024
accepted: 16 02 2024
medline: 24 4 2024
pubmed: 24 4 2024
entrez: 24 4 2024
Statut: aheadofprint

Résumé

CD8+ tumor-infiltrating lymphocyte (TIL) predicts response to anti-PD-(L)1 therapy. However, there remains no standardized method to assess CD8+ TIL in melanoma, and developing a specific, cost-effective, reproducible, and clinically actionable biomarker to anti-PD-(L)1 remains elusive. We report on the development of automatic CD8+ TIL density quantification via whole slide image (WSI) analysis in advanced melanoma patients treated with front-line anti-PD-1 blockade, and correlation immunotherapy response. Seventy-eight patients treated with PD-1 inhibitors in the front-line setting between January 2015 and May 2023 at the University of Pittsburgh Cancer Institute were included. CD8+ TIL density was quantified using an image analysis algorithm on digitized WSI. Targeted next-generation sequencing (NGS) was performed to determine tumor mutation burden (TMB) in a subset of 62 patients. ROC curves were used to determine biomarker cutoffs and response to therapy. Correlation between CD8+ TIL density and TMB cutoffs and response to therapy was studied. Higher CD8+ TIL density was significantly associated with improved response to front-line anti-PD-1 across all time points measured. CD8+ TIL density ≥222.9 cells/mm2 reliably segregated responders and non-responders to front-line anti-PD-1 therapy regardless of when response was measured. In a multivariate analysis, patients with CD8+ TIL density exceeding cutoff had significantly improved PFS with a trend toward improved OS. Similarly, increasing TMB was associated with improved response to anti-PD-1, and a cutoff of 14.70 Mut/Mb was associated with improved odds of response. The correlation between TMB and CD8+ TIL density was low, suggesting that each represented independent predictive biomarkers of response. An automatic digital analysis algorithm provides a standardized method to quantify CD8+ TIL density, which predicts response to front-line anti-PD-1 therapy. CD8+ TIL density and TMB are independent predictors of response to anti-PD-1 blockade.

Sections du résumé

BACKGROUND BACKGROUND
CD8+ tumor-infiltrating lymphocyte (TIL) predicts response to anti-PD-(L)1 therapy. However, there remains no standardized method to assess CD8+ TIL in melanoma, and developing a specific, cost-effective, reproducible, and clinically actionable biomarker to anti-PD-(L)1 remains elusive. We report on the development of automatic CD8+ TIL density quantification via whole slide image (WSI) analysis in advanced melanoma patients treated with front-line anti-PD-1 blockade, and correlation immunotherapy response.
METHODS METHODS
Seventy-eight patients treated with PD-1 inhibitors in the front-line setting between January 2015 and May 2023 at the University of Pittsburgh Cancer Institute were included. CD8+ TIL density was quantified using an image analysis algorithm on digitized WSI. Targeted next-generation sequencing (NGS) was performed to determine tumor mutation burden (TMB) in a subset of 62 patients. ROC curves were used to determine biomarker cutoffs and response to therapy. Correlation between CD8+ TIL density and TMB cutoffs and response to therapy was studied.
RESULTS RESULTS
Higher CD8+ TIL density was significantly associated with improved response to front-line anti-PD-1 across all time points measured. CD8+ TIL density ≥222.9 cells/mm2 reliably segregated responders and non-responders to front-line anti-PD-1 therapy regardless of when response was measured. In a multivariate analysis, patients with CD8+ TIL density exceeding cutoff had significantly improved PFS with a trend toward improved OS. Similarly, increasing TMB was associated with improved response to anti-PD-1, and a cutoff of 14.70 Mut/Mb was associated with improved odds of response. The correlation between TMB and CD8+ TIL density was low, suggesting that each represented independent predictive biomarkers of response.
CONCLUSIONS CONCLUSIONS
An automatic digital analysis algorithm provides a standardized method to quantify CD8+ TIL density, which predicts response to front-line anti-PD-1 therapy. CD8+ TIL density and TMB are independent predictors of response to anti-PD-1 blockade.

Identifiants

pubmed: 38655867
pii: 7657431
doi: 10.1093/oncolo/oyae054
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NCI NIH HHS
ID : P50 CA254865
Pays : United States

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press.

Auteurs

Dylan Fortman (D)

Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.

Arivarasan Karunamurthy (A)

Department of Dermatology, University of Pittsburgh and UPMC, Pittsburgh, PA, USA.
Department of Pathology, University of Pittsburgh and UPMC, Pittsburgh, PA, USA.

Douglas Hartman (D)

Department of Pathology, University of Pittsburgh and UPMC, Pittsburgh, PA, USA.

Hong Wang (H)

Department of Biostatistics, University of Pittsburgh and University of Pittsburgh Medical Center, Pittsburgh, PA, USA.

Lindsey Seigh (L)

Department of Pathology, University of Pittsburgh and UPMC, Pittsburgh, PA, USA.

Ibrahim Abukhiran (I)

Department of Pathology, University of Pittsburgh and UPMC, Pittsburgh, PA, USA.

Yana G Najjar (YG)

Division of Hematology-Oncology, Department of Medicine, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.

Liron Pantanowitz (L)

Department of Pathology, University of Michigan, Ann Arbor, MI, USA.

Hassane M Zarour (HM)

Division of Hematology-Oncology, Department of Medicine, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.

John M Kirkwood (JM)

Division of Hematology-Oncology, Department of Medicine, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.

Diwakar Davar (D)

Division of Hematology-Oncology, Department of Medicine, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.

Classifications MeSH