Molecular classification of human papillomavirus-positive cervical cancers based on immune signature enrichment

BackgroundHuman papillomavirus-positive (HPV+) cervical cancers are highly heterogeneous in clinical and molecular characteristics. Thus, an investigation into their heterogeneous immunological profiles is meaningful in providing both biological and clinical insights into this disease.MethodsBased on the enrichment of 29 immune signatures, we discovered immune subtypes of HPV+ cervical cancers by hierarchical clustering. To explore whether this subtyping method is reproducible, we analyzed three bulk and one single cell transcriptomic datasets. We also compared clinical and molecular characteristics between the immune subtypes.ResultsClustering analysis identified two immune subtypes of HPV+ cervical cancers: Immunity-H and Immunity-L, consistent in the four datasets. In comparisons with Immunity-L, Immunity-H displayed stronger immunity, more stromal contents, lower tumor purity, proliferation potential, intratumor heterogeneity and stemness, higher tumor mutation burden, more neoantigens, lower levels of copy number alterations, lower DNA repair activity, as well as better overall survival prognosis. Certain genes, such as MUC17, PCLO, and GOLGB1, showed significantly higher mutation rates in Immunity-L than in Immunity-H. 16 proteins were significantly upregulated in Immunity-H vs. Immunity-L, including Caspase-7, PREX1, Lck, C-Raf, PI3K-p85, Syk, 14-3-3_epsilon, STAT5-α, GATA3, Src_pY416, NDRG1_pT346, Notch1, PDK1_pS241, Bim, NF-kB-p65_pS536, and p53. Pathway analysis identified numerous immune-related pathways more highly enriched in Immunity-H vs. Immunity-L, including cytokine-cytokine receptor interaction, natural killer cell-mediated cytotoxicity, antigen processing and presentation, T/B cell receptor signaling, chemokine signaling, supporting the stronger antitumor immunity in Immunity-H vs. Immunity-L.ConclusionHPV+ cervical cancers are divided into two subgroups based on their immune signatures' enrichment. Both subgroups have markedly different tumor immunity, progression phenotypes, genomic features, and clinical outcomes. Our data offer novel perception in the tumor biology as well as clinical implications for HPV+ cervical cancer..

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Frontiers in Public Health - 10(2022)

Sprache:

Englisch

Beteiligte Personen:

Guanghui Song [VerfasserIn]
Jiangti Luo [VerfasserIn]
Jiangti Luo [VerfasserIn]
Jiangti Luo [VerfasserIn]
Shaohan Zou [VerfasserIn]
Fang Lou [VerfasserIn]
Tianfang Zhang [VerfasserIn]
Xiaojun Zhu [VerfasserIn]
Jianhua Yang [VerfasserIn]
Xiaosheng Wang [VerfasserIn]
Xiaosheng Wang [VerfasserIn]
Xiaosheng Wang [VerfasserIn]

Links:

doi.org [kostenfrei]
doaj.org [kostenfrei]
www.frontiersin.org [kostenfrei]
Journal toc [kostenfrei]

Themen:

Human papillomavirus-positive cervical cancer
Immunological classification
Immunotherapy
Machine learning
Multi-omics analysis
Public aspects of medicine

doi:

10.3389/fpubh.2022.979933

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

DOAJ023441410