Development and validation of a combined hypoxia and immune prognostic classifier for head and neck cancer

Jill M. Brooks, Albert N. Menezes, Maha Ibrahim, Lucinda Archer, Neeraj Lal, Christopher J. Bagnall, Sandra V. Von Zeidler, Helen R. Valentine, Rachel J. Spruce, Nikolaos Batis, Jennifer L. Bryant, Margaret Hartley, Baksho Kaul, Gordon B. Ryan, Riyue Bao, Arun Khattri, Steven P. Lee, Kalu U.E. Ogbureke, Gary Middleton, Daniel A. TennantAndrew D. Beggs, Jonathan Deeks, Catharine M.L. West, Jean Baptiste Cazier, Benjamin E. Willcox, Tanguy Y. Seiwert, Hisham Mehanna

Research output: Contribution to journalArticle

Abstract

Purpose: Intratumoral hypoxia and immunity have been correlated with patient outcome in various tumor settings. However, these factors are not currently considered for treatment selection in head and neck cancer (HNC) due to lack of validated biomarkers. Here we sought to develop a hypoxiaimmune classifier with potential application in patient prognostication and prediction of response to targeted therapy. Experimental Design: A 54-gene hypoxia-immune signature was constructed on the basis of literature review. Gene expression was analyzed in silico using the The Cancer Genome Atlas (TCGA) HNC dataset (n = 275) and validated using two independent cohorts (n = 130 and 123). IHC was used to investigate the utility of a simplified protein signature. The spatial distribution of hypoxia and immune markers was examined using multiplex immunofluorescence staining. Results: Unsupervised hierarchical clustering of TCGA dataset (development cohort) identified three patient subgroups with distinct hypoxia-immune phenotypes and survival profiles: hypoxialow/immunehigh, hypoxiahigh/immunelow, and mixed, with 5-year overall survival (OS) rates of 71%, 51%, and 49%, respectively (P = 0.0015). The prognostic relevance of the hypoxia-immune gene signature was replicated in two independent validation cohorts. Only PDL1 and intratumoral CD3 protein expression were associated with improved OS on multivariate analysis. Hypoxialow/ immunehigh and hypoxiahigh/immunelow tumors were overrepresented in "inflamed" and "immune-desert" microenvironmental profiles, respectively. Multiplex staining demonstrated an inverse correlation between CA-IX expression and prevalence of intratumoral CD3+ T cells (r = -0.5464; P = 0.0377), further corroborating the transcription-based classification. Conclusions: We developed and validated a hypoxiaimmune prognostic transcriptional classifier, which may have clinical application to guide the use of hypoxia modification and targeted immunotherapies for the treatment of HNC.

Original languageEnglish (US)
Pages (from-to)5315-5328
Number of pages14
JournalClinical Cancer Research
Volume25
Issue number17
DOIs
StatePublished - Sep 1 2019
Externally publishedYes

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Head and Neck Neoplasms
Atlases
Neoplasms
Biomarkers
Genome
Staining and Labeling
Survival
Computer Simulation
Immunotherapy
Genes
Fluorescent Antibody Technique
Cluster Analysis
Hypoxia
Immunity
Proteins
Research Design
Therapeutics
Multivariate Analysis
Survival Rate
T-Lymphocytes

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Brooks, J. M., Menezes, A. N., Ibrahim, M., Archer, L., Lal, N., Bagnall, C. J., ... Mehanna, H. (2019). Development and validation of a combined hypoxia and immune prognostic classifier for head and neck cancer. Clinical Cancer Research, 25(17), 5315-5328. https://doi.org/10.1158/1078-0432.CCR-18-3314

Development and validation of a combined hypoxia and immune prognostic classifier for head and neck cancer. / Brooks, Jill M.; Menezes, Albert N.; Ibrahim, Maha; Archer, Lucinda; Lal, Neeraj; Bagnall, Christopher J.; Von Zeidler, Sandra V.; Valentine, Helen R.; Spruce, Rachel J.; Batis, Nikolaos; Bryant, Jennifer L.; Hartley, Margaret; Kaul, Baksho; Ryan, Gordon B.; Bao, Riyue; Khattri, Arun; Lee, Steven P.; Ogbureke, Kalu U.E.; Middleton, Gary; Tennant, Daniel A.; Beggs, Andrew D.; Deeks, Jonathan; West, Catharine M.L.; Cazier, Jean Baptiste; Willcox, Benjamin E.; Seiwert, Tanguy Y.; Mehanna, Hisham.

In: Clinical Cancer Research, Vol. 25, No. 17, 01.09.2019, p. 5315-5328.

Research output: Contribution to journalArticle

Brooks, JM, Menezes, AN, Ibrahim, M, Archer, L, Lal, N, Bagnall, CJ, Von Zeidler, SV, Valentine, HR, Spruce, RJ, Batis, N, Bryant, JL, Hartley, M, Kaul, B, Ryan, GB, Bao, R, Khattri, A, Lee, SP, Ogbureke, KUE, Middleton, G, Tennant, DA, Beggs, AD, Deeks, J, West, CML, Cazier, JB, Willcox, BE, Seiwert, TY & Mehanna, H 2019, 'Development and validation of a combined hypoxia and immune prognostic classifier for head and neck cancer', Clinical Cancer Research, vol. 25, no. 17, pp. 5315-5328. https://doi.org/10.1158/1078-0432.CCR-18-3314
Brooks, Jill M. ; Menezes, Albert N. ; Ibrahim, Maha ; Archer, Lucinda ; Lal, Neeraj ; Bagnall, Christopher J. ; Von Zeidler, Sandra V. ; Valentine, Helen R. ; Spruce, Rachel J. ; Batis, Nikolaos ; Bryant, Jennifer L. ; Hartley, Margaret ; Kaul, Baksho ; Ryan, Gordon B. ; Bao, Riyue ; Khattri, Arun ; Lee, Steven P. ; Ogbureke, Kalu U.E. ; Middleton, Gary ; Tennant, Daniel A. ; Beggs, Andrew D. ; Deeks, Jonathan ; West, Catharine M.L. ; Cazier, Jean Baptiste ; Willcox, Benjamin E. ; Seiwert, Tanguy Y. ; Mehanna, Hisham. / Development and validation of a combined hypoxia and immune prognostic classifier for head and neck cancer. In: Clinical Cancer Research. 2019 ; Vol. 25, No. 17. pp. 5315-5328.
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T1 - Development and validation of a combined hypoxia and immune prognostic classifier for head and neck cancer

AU - Brooks, Jill M.

AU - Menezes, Albert N.

AU - Ibrahim, Maha

AU - Archer, Lucinda

AU - Lal, Neeraj

AU - Bagnall, Christopher J.

AU - Von Zeidler, Sandra V.

AU - Valentine, Helen R.

AU - Spruce, Rachel J.

AU - Batis, Nikolaos

AU - Bryant, Jennifer L.

AU - Hartley, Margaret

AU - Kaul, Baksho

AU - Ryan, Gordon B.

AU - Bao, Riyue

AU - Khattri, Arun

AU - Lee, Steven P.

AU - Ogbureke, Kalu U.E.

AU - Middleton, Gary

AU - Tennant, Daniel A.

AU - Beggs, Andrew D.

AU - Deeks, Jonathan

AU - West, Catharine M.L.

AU - Cazier, Jean Baptiste

AU - Willcox, Benjamin E.

AU - Seiwert, Tanguy Y.

AU - Mehanna, Hisham

PY - 2019/9/1

Y1 - 2019/9/1

N2 - Purpose: Intratumoral hypoxia and immunity have been correlated with patient outcome in various tumor settings. However, these factors are not currently considered for treatment selection in head and neck cancer (HNC) due to lack of validated biomarkers. Here we sought to develop a hypoxiaimmune classifier with potential application in patient prognostication and prediction of response to targeted therapy. Experimental Design: A 54-gene hypoxia-immune signature was constructed on the basis of literature review. Gene expression was analyzed in silico using the The Cancer Genome Atlas (TCGA) HNC dataset (n = 275) and validated using two independent cohorts (n = 130 and 123). IHC was used to investigate the utility of a simplified protein signature. The spatial distribution of hypoxia and immune markers was examined using multiplex immunofluorescence staining. Results: Unsupervised hierarchical clustering of TCGA dataset (development cohort) identified three patient subgroups with distinct hypoxia-immune phenotypes and survival profiles: hypoxialow/immunehigh, hypoxiahigh/immunelow, and mixed, with 5-year overall survival (OS) rates of 71%, 51%, and 49%, respectively (P = 0.0015). The prognostic relevance of the hypoxia-immune gene signature was replicated in two independent validation cohorts. Only PDL1 and intratumoral CD3 protein expression were associated with improved OS on multivariate analysis. Hypoxialow/ immunehigh and hypoxiahigh/immunelow tumors were overrepresented in "inflamed" and "immune-desert" microenvironmental profiles, respectively. Multiplex staining demonstrated an inverse correlation between CA-IX expression and prevalence of intratumoral CD3+ T cells (r = -0.5464; P = 0.0377), further corroborating the transcription-based classification. Conclusions: We developed and validated a hypoxiaimmune prognostic transcriptional classifier, which may have clinical application to guide the use of hypoxia modification and targeted immunotherapies for the treatment of HNC.

AB - Purpose: Intratumoral hypoxia and immunity have been correlated with patient outcome in various tumor settings. However, these factors are not currently considered for treatment selection in head and neck cancer (HNC) due to lack of validated biomarkers. Here we sought to develop a hypoxiaimmune classifier with potential application in patient prognostication and prediction of response to targeted therapy. Experimental Design: A 54-gene hypoxia-immune signature was constructed on the basis of literature review. Gene expression was analyzed in silico using the The Cancer Genome Atlas (TCGA) HNC dataset (n = 275) and validated using two independent cohorts (n = 130 and 123). IHC was used to investigate the utility of a simplified protein signature. The spatial distribution of hypoxia and immune markers was examined using multiplex immunofluorescence staining. Results: Unsupervised hierarchical clustering of TCGA dataset (development cohort) identified three patient subgroups with distinct hypoxia-immune phenotypes and survival profiles: hypoxialow/immunehigh, hypoxiahigh/immunelow, and mixed, with 5-year overall survival (OS) rates of 71%, 51%, and 49%, respectively (P = 0.0015). The prognostic relevance of the hypoxia-immune gene signature was replicated in two independent validation cohorts. Only PDL1 and intratumoral CD3 protein expression were associated with improved OS on multivariate analysis. Hypoxialow/ immunehigh and hypoxiahigh/immunelow tumors were overrepresented in "inflamed" and "immune-desert" microenvironmental profiles, respectively. Multiplex staining demonstrated an inverse correlation between CA-IX expression and prevalence of intratumoral CD3+ T cells (r = -0.5464; P = 0.0377), further corroborating the transcription-based classification. Conclusions: We developed and validated a hypoxiaimmune prognostic transcriptional classifier, which may have clinical application to guide the use of hypoxia modification and targeted immunotherapies for the treatment of HNC.

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