HPV-Positive and -Negative Cervical Cancers Are Immunologically Distinct

Abstract

Although infection with human papillomavirus (HPV) is associated with nearly all cervical cancers (CC), a small proportion are HPV-negative. Recently, it has become clear that HPV-negative CC represent a distinct disease phenotype compared to HPV-positive disease and exhibit increased mortality. In addition, variations between different HPV types associated with CC have been linked to altered molecular pathology and prognosis. We compared the immune microenvironments of CC caused by HPV α9 species (HPV16-like), HPV α7 species (HPV18-like) and HPV-negative disease. HPV-negative CC appeared distinct from other subtypes, with greatly reduced levels of lymphocyte infiltration compared to either HPV α9 or α7 CC. Besides reduced levels of markers indicative of B, T, and NK lymphocytes, the expression of T-cell effector molecules, activation/exhaustion markers, and T-cell receptor diversity were also significantly lower in HPV-negative CC. Interestingly, HPV-negative CC expressed much higher levels of potential neoantigens than HPV-positive CC. These results identify profound differences between the immune landscape of HPV-positive and HPV-negative CC as well as modest differences between HPV α9 and α7 CC. These differences may contribute to altered patient outcomes between HPV-negative and HPV-positive CC and potentially between CC associated with different HPV types.

Keywords: T-cell function; TCGA; TCR repertoire; cervical cancer; gene expression; human papillomavirus; immune exhaustion; immune landscape; neoantigens; tumor immunology.

Figure 1

Analysis of tumor infiltrating lymphocytes and subsets in HPV-positive (HPV α9 and HPV α7) and HPV-negative (HPV-) cervical cancer. (A) Comparison of Lymphocyte Infiltration Signature Score between HPV α9, HPV α7, and HPV-negative cervical cancers. Values were extracted from Thorsson et al. [26] and HPV status annotated manually; (B–F) expression of marker genes related to B-cell (CD19, IL21R) and T-cell (CD3D, CD3E, CD3G) infiltration. Numbers in brackets refer to the number of samples included in each analysis. *** p ≤ 0.001, ** p ≤ 0.01, * p ≤ 0.05, ns (not significant).

Figure 2

Transcript levels of NK cell marker genes in HPV-positive (HPV α9 and HPV α7) and HPV-negative (HPV-) cervical cancer. Normalized RNA-seq data was extracted from The Cancer Genome Atlas (TCGA) database for cervical cancer cohort. Numbers in brackets refer to the number of samples included in each analysis. **** p ≤ 0.0001, *** p ≤ 0.001, ** p ≤ 0.01, * p = 0.05, ns (not significant).

Figure 3

Analysis of T-cell populations in HPV-positive and HPV-negative cervical cancers. (A–C) Expression of marker genes related to CD4⁺ helper (CD4), CD8⁺ cytotoxic (CD8A), and Treg (FOXP3) cells; (D) expression of CD137 (TNFRSF9/4-1BB), an activation-induced costimulatory molecule present primarily on CD8⁺ T cells. (E,F) Comparison of CD4⁺ helper Th1 and Th2 Signature Score between HPV α9, HPV α7, and HPV-negative (HPV-) cervical cancers. Numbers in brackets refer to the number of samples included in each analysis. **** p ≤ 0.0001, ** p ≤ 0.01, * p ≤ 0.05, ns (not significant).

Figure 4

Transcript levels of lymphocyte effector molecules in HPV-positive (HPV α9 and HPV α7) and HPV-negative (HPV-) cervical cancers. (A–F) Expression of marker genes related to activated cytotoxic CD8⁺ T cells, including IFN-γ (IFNG), TNF-α (TNF), granzyme A (GZMA), granzyme B (GZMB), granzyme K (GZMK), and perforin (PRF1). Numbers in brackets refer to the number of samples included in each analysis. ** p ≤ 0.01, * p ≤ 0.05, ns (not significant).

Figure 5

Transcript levels of tumor-derived interferon-responsive immunomodulatory genes in cervical cancer. Normalized RNA-seq data for genes associated with tumor cell mediated immunomodulation, including (A) PDL1 (CD274), (B) IDO1, and (C) its negative regulator BIN1, were compared between HPV-positive (HPV α9 and HPV α7) and HPV-negative (HPV-) cervical cancers. Numbers in brackets refer to the number of samples included in each analysis. **** p ≤ 0.0001, *** p ≤ 0.001, ** p ≤ 0.01, * p ≤ 0.05, ns (not significant).

Figure 6

Analysis of immune checkpoint markers in HPV-positive (HPV α9 and HPV α7) and HPV-negative (HPV-) cervical cancers. (A–F) Expression of marker genes related to T-cell exhaustion markers, including CD96, CTLA4, LAG3, PD1 (PDCD1), TIGIT, and TIM3 (HAVCR2). (G,H) Expression of marker genes related to immunosuppressive purinergic signals including CD39 (ENTPD1) and CD73 (NT5E). Numbers in brackets refer to the number of samples included in each analysis. **** p ≤ 0.0001, *** p ≤ 0.001, ** p ≤ 0.01, * p ≤ 0.05, ns (not significant).

Figure 7

Correlation of immune checkpoint markers with patient mortality in HPV-positive (HPV α9 and HPV α7) cervical cancer. Hazard ratios (HR) and 95% confidence intervals (CI) related to immune checkpoint/T-cell exhaustion marker expression for CD96, CTLA4, LAG3, PD1 (PDCD1), TIGIT, TIM3 (HAVCR2), and genes related to immunosuppressive purinergic signals, including CD39 (ENTPD1) and CD73 (NT5E), were calculated. Numbers indicated in red are statistically significant.

Figure 8

Comparison of the T-cell receptor (TCR) repertoire between HPV-positive (HPV α9 and HPV α7) and HPV-negative (HPV-) cervical cancers. (A) Comparison of unique TCR sequences in the TCR repertoire (richness); (B) comparison of clonal diversity weighted by the abundance of each complementarity-determining region 3 (Shannon entropy); (C) comparison of the distribution spectrum of TCR sequences, reflecting the relative abundance of individual T-cell clones (evenness). Numbers in brackets refer to the number of samples included in each analysis. ** p ≤ 0.01, * p ≤ 0.05, ns (not significant).

Figure 9

Comparison of the levels of potential neoantigens in HPV-positive (HPV α9 and HPV α7) and HPV-negative (HPV-) cervical cancers. Predicted levels of (A) single-nucleotide variant (SNV) neoantigens; (B) insertion–deletion (indel) neoantigens; (C) cancer testis antigen (CTA) score; and (D) non-silent mutations. Numbers in brackets refer to the number of samples included in each analysis. **** p ≤ 0.0001, *** p ≤ 0.001, ** p ≤ 0.01, * p ≤ 0.05, ns (not significant).