Baseline and early changes in serum proteomic profiles predict anti-tumor activity in patients with advanced HPV-associated malignancies treated with novel combination immunotherapy

Abstract Background Patients with advanced human papillomavirus (HPV)–associated malignancies who do not respond to immune checkpoint blockade have limited treatment options. Combination immunotherapy consisting of an HPV16 therapeutic peptide cancer vaccine (PDS0101) to initiate an immune response, a tumor-targeting IL-12 immunocytokine (PDS01ADC) to potentiate that response, and a bifunctional agent providing dual blockade of programmed cell death ligand 1 (PD-L1) and transforming growth factor β (TGF-β) (bintrafusp alfa) to reduce immunosuppression has demonstrated promising clinical activity in a prior report of a clinical trial in patients with advanced HPV16 + –associated malignancies (NCT04287868). Here, we provide updated clinical results from that trial and identify immune correlates of clinical response. Methods We performed a comprehensive survey of the peripheral immunome from 38 patients with HPV16 + tumors, and built machine-learning models using a survey of serum proteomic data to predict which patients would derive clinical benefit and improved overall survival from treatment. Results Models incorporating baseline levels of IL- 6 and heme oxygenase 1, alone or with an early change in granzyme B, effectively predicted clinical benefit and duration of overall survival. We also identified a persistent skewing of increased peripheral CD8 + T cells to myeloid cell ratios in patients who benefit from treatment. Moreover, there was a positive association between monocyte and myeloid derived suppressor cell frequencies with serum concentrations of inhibitory biomarkers, providing biological rationale of the serum-based prediction models. Conclusions Although retrospective, these data demonstrate outcome prediction in patients with HPV-associated malignancies using readily quantifiable molecular correlates from minimally invasive sampling of peripheral blood prior to therapy or early in the regimen and thus provide the rationale for prospective validation in future clinical studies.

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Publication Details

Journal
Journal of Experimental & Clinical Cancer Research
Published
2026-10-21
DOI
https://doi.org/10.1186/s13046-026-03847-8
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
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article

Baseline and early changes in serum proteomic profiles predict anti-tumor activity in patients with advanced HPV-associated malignancies treated with novel combination immunotherapy

Megan T. Lynch, Jennifer L. Marté, Yo-Ting Tsai, Julius Strauss et al.
Journal of Experimental & Clinical Cancer Research
Cancer Immunotherapy and Biomarkers
article

Baseline and early changes in serum proteomic profiles predict anti-tumor activity in patients with advanced HPV-associated malignancies treated with novel combination immunotherapy

Megan T. Lynch, Jennifer L. Marté, Yo-Ting Tsai, Julius Strauss, Meghali Goswami, Charalampos S. Floudas, Renee Nicole Donahue, Jeffrey Schlom, James L. Gulley
article en

Abstract

Abstract Background Patients with advanced human papillomavirus (HPV)–associated malignancies who do not respond to immune checkpoint blockade have limited treatment options. Combination immunotherapy consisting of an HPV16 therapeutic peptide cancer vaccine (PDS0101) to initiate an immune response, a tumor-targeting IL-12 immunocytokine (PDS01ADC) to potentiate that response, and a bifunctional agent providing dual blockade of programmed cell death ligand 1 (PD-L1) and transforming growth factor β (TGF-β) (bintrafusp alfa) to reduce immunosuppression has demonstrated promising clinical activity in a prior report of a clinical trial in patients with advanced HPV16 + –associated malignancies (NCT04287868). Here, we provide updated clinical results from that trial and identify immune correlates of clinical response. Methods We performed a comprehensive survey of the peripheral immunome from 38 patients with HPV16 + tumors, and built machine-learning models using a survey of serum proteomic data to predict which patients would derive clinical benefit and improved overall survival from treatment. Results Models incorporating baseline levels of IL- 6 and heme oxygenase 1, alone or with an early change in granzyme B, effectively predicted clinical benefit and duration of overall survival. We also identified a persistent skewing of increased peripheral CD8 + T cells to myeloid cell ratios in patients who benefit from treatment. Moreover, there was a positive association between monocyte and myeloid derived suppressor cell frequencies with serum concentrations of inhibitory biomarkers, providing biological rationale of the serum-based prediction models. Conclusions Although retrospective, these data demonstrate outcome prediction in patients with HPV-associated malignancies using readily quantifiable molecular correlates from minimally invasive sampling of peripheral blood prior to therapy or early in the regimen and thus provide the rationale for prospective validation in future clinical studies.

Journal of Experimental & Clinical Cancer Research
Openalex Percentile: Top 17%
Cancer Immunotherapy and Biomarkers
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