Single‐Cell Landscape Highlights Heterogenous Microenvironment, Novel Immune Reaction Patterns, Potential Biomarkers and Unique Therapeutic Strategies of Cervical Squamous Carcinoma, Human Papillomavirus‐Associated (HPVA) and Non‐HPVA Adenocarcinoma

Abstract

Cervical adenocarcinomas (ADCs), including human papillomavirus (HPV)-associated (HPVA) and non-HPVA (NHPVA), though exhibiting a more malignant phenotype and poorer prognosis, are treated identically to squamous cell carcinoma (SCC). This clinical dilemma requires a deeper investigation into their differences. Herein a transcriptomic atlas of SCC, HPVA, and NHPVA-ADC using single-cell RNA (scRNA) and T-cell receptor sequencing (TCR-seq) is presented. Regarding structural cells, the malignancy origin of epithelial cells, angiogenic tip cells and two subtypes of fibroblasts is revealed. The promalignant properties of the structural cells using organoids are further confirmed. Regarding immune cells, myeloid cells with multiple functions other than antigen presentation and exhausted T lymphocytes contribute to immunosuppression. From the perspective of HPV infection, not only is HPV-dependent and independent cervical cancer oncogenesis proposed but also three immune reaction patterns mediated by T cells (coordinated/inactive/imbalanced) are identified. Strikingly, diagnostic biomarkers to distinguish ADC from SCC are discovered and prognostic biomarkers with marker genes for malignant epithelial cells, tip cells, and SPP1/C1QC macrophages are generated. Importantly, the efficacy of anti-CD96 and anti-TIGIT, not inferior to anti-PD1, in animal experiments is confirmed and targeted therapies specifically for HPV-positive SCC, HPVA and NHPVA-ADC, providing essential clues for further clinical trials, are proposed.

Single-cell profiling reveals the intratumor heterogeneity and immunosuppressive microenvironment in cervical adenocarcinoma

“…For instance, Cao et al compared 5 cases of SCC tumor tissues with paired adjacent normal tissues and described the immune landscape in which specific clusters of T and B cells exhibited immune-exhausting or activating processes (Cao et al, 2023). Another study conducted by Qiu et al aimed to elucidate the distinct molecular patterns of immune reactions between ADC and SCC in the context of different HPV infection status at the single-cell level (Qiu et al, 2023). However, due to limited samples tested in these studies, our knowledge on the TIME in CC is yet inadequate.…”

“…The cell typing was conducted and annotated according to the selected gene markers via CellMarker database and publications (C. Li et al, 2022; Qiu et al, 2023; Xue et al, 2022). The expression of differential expressed genes (DEGs) was used to determine each cell type following the rules: Log 2 Foldchange should be > 0.2 and adjusted- P values should be < 0.05.…”

CCNA2 and NEK2 regulate glioblastoma progression by targeting the cell cycle

“…To differentiate between cell types in the GBM microenvironment, immune and non-immune clusters were classified based on marker genes identified in previous studies (41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58). Genes such as C1QB (41), CD68 (42), CSF1R (43), PTPRC (44), C1QC (45), P2RY12 (46), CX3CR1 (47), CD163 (48), PTGS2 (49) and CD86 (50) were used to identify immune clusters; whereas genes AQP4 (51), PTPRZ1 (52), CLDN5 (53), CD34 (54), GFAP (55), FDGFRA (56), OLIG2 (57) and PLP1 (58) were used to identify non-immune clusters. Clusters 0, 2, 6, 14 and 15 were identified as immune cells, whereas clusters 1, 3, 4, 5, 7, 8, 9, 10, 11, 12 and 13 were identified as non-immune cells based on the average expression of PTPRC, as demonstrated in Fig.…”

Interactions of Indoleamine 2,3‐dioxygenase‐expressing LAMP3+ dendritic cells with CD4+ regulatory T cells and CD8+ exhausted T cells: synergistically remodeling of the immunosuppressive microenvironment in cervical cancer and therapeutic implications

“…To acquire transcriptomic profiles during the malignant transition of the cervix, we obtained 10x Genomics scRNAseq data from 17 cervical tissue samples that were previously generated by our group (Gene Expression Omnibus accession number: GSE197461 [14] and GSE208653 [15]. S1.…”