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. 2019 Jun;21(6):591-601.
doi: 10.1016/j.neo.2019.04.003. Epub 2019 May 2.

Immune Signature-Based Subtypes of Cervical Squamous Cell Carcinoma Tightly Associated with Human Papillomavirus Type 16 Expression, Molecular Features, and Clinical Outcome

Xiaofan Lu  1 , Liyun Jiang  1 , Liya Zhang  1 , Yue Zhu  1 , Wenjun Hu  1 , Jiashuo Wang  1 , Xinjia Ruan  1 , Zhengbao Xu  1 , Xiaowei Meng  1 , Jun Gao  1 , Xiaoping Su  2 , Fangrong Yan  3
Affiliations

Immune Signature-Based Subtypes of Cervical Squamous Cell Carcinoma Tightly Associated with Human Papillomavirus Type 16 Expression, Molecular Features, and Clinical Outcome

Xiaofan Lu et al. Neoplasia. 2019 Jun.

Abstract

Substantial heterogeneity exists within cervical cancer that is generally infected by human papillomavirus (HPV). However, the most common histological subtype of cervical cancer, cervical squamous cell carcinoma (CSCC), is poorly characterized regarding the association between its heterogeneity and HPV oncoprotein expression. We filtered out 138 CSCC samples with infection of HPV16 only as the first step; then we compressed HPV16 E6/E7 expression as HPVpca and correlated HPVpca with the immunological profiling of CSCC based on supervised clustering to discover subtypes and to characterize the differences between subgroups in terms of the HPVpca level, pathway activity, epigenetic dysregulation, somatic mutation frequencies, and likelihood of responding to chemo/immunotherapies. Supervised clustering of immune signatures revealed two HPV16 subtypes (namely, HPV16-IMM and HPV16-KRT) that correlated with HPVpca and clinical outcomes. HPV16-KRT is characterized by elevated expression of genes in keratinization, biological oxidation, and Wnt signaling, whereas HPV16-IMM has a strong immune response and mesenchymal features. HPV16-IMM exhibited much more epigenetic silencing and significant mutation at FBXW7, while MUC4 and PIK3CA were mutated frequently for HPV16-KRT. We also imputed that HPV16-IMM is much more sensitive to chemo/immunotherapy than is HPV16-KRT. Our characterization tightly links the expression of HPV16 E6/E7 with biological and clinical outcomes of CSCC, providing valuable molecular-level information that points to decoding heterogeneity. Together, these results shed light on stratifications of CSCC infected by HPV16 and shall help to guide personalized management and treatment of patients.

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Figures

Figure 1
Figure 1
Overview of sample selection. (A) Pie chart of the distribution of the detected HPV type and (B) histological type. The 138 selected samples were those diagnosed with CSCC and infected by HPV16.
Figure 2
Figure 2
Highly correlated oncoproteins E6 and E7 were associated with clinical outcome. (A) The forest plot shows only that HPV16 E6/E7 expression affects the patient overall survival. (B) Pearson correlation coefficient of pairwise HPV16 oncoproteins. (C) High level of HPVpca presented a favorable prognosis.
Figure 3
Figure 3
Immune signatures based on supervised clustering revealed two HPV16 subtypes that correlated with clinical outcomes. (A) Heatmap of 20 immune signatures across 138 CSCC samples distinguished two immunological patterns between the subtypes. The box plot shows different enrichment levels between the subtypes in (B) adaptive immunity signatures, (C) innate immunity signatures, and (D) other immunity components. E6 activity calculated by E6-repressed and -induced genes was compared and presented in (E) and (F). Kaplan-Meier curve showing the difference in (G) overall survival and (H) progression-free survival between the subtypes.
Figure 4
Figure 4
Differentially regulated genes and pathways between the HPV16 subtypes. (A) Heatmap of significant differentially expressed genes between the subtypes with different enrichment in the predicted epithelial-mesenchymal transition status. (B) The volcano plot shows representative genes within interested pathways. (C) Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that the immune-related pathway and TNF signaling were enriched in the HPV16-IMM subtype, whereas the Wnt signaling was enriched in the HPV16-KRT subtype. (E) Heatmap of the enrichment level calculated by single-sample gene set enrichment analysis for interested pathways derived from GSEA and their corresponding GSEA plots in (F).
Figure 5
Figure 5
Epigenetic and genetic alteration between the HPV16 subtypes in terms of (A) the methylation-based immune infiltration score, (B) tumor mutation burden, and (C) predicted number of neoantigens. (D) Oncoprint shows the somatic mutation landscape of MutSigCV-detected SMGs and other differentially mutated genes between the subtypes.
Figure 6
Figure 6
Differential putative chemotherapeutic and immunotherapeutic response. The box plots of the estimated IC50 for cisplatin and gemcitabine are shown in (A) for HPVpca-based HPV-H and HPV-L and (B) for HPV16-IMM and HPV16-KRT. (C) Submap analysis manifested that HPV16-IMM could be more sensitive to the programmed cell death protein 1 inhibitor (Bonferroni-corrected P = .008).
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