Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and transcriptional activities of ECs in CC

Genetic dependencies associated with transcription factor activities in human cancer cell lines

Transcription factors (TFs) are important mediators of aberrant transcriptional programs in cancer cells. In this study, we focus on TF activity (TFa) as a biomarker for cell-line-selective anti-proliferative effects, in that high TFa predicts sensitivity to loss of function of a given gene (i.e., genetic dependencies [GDs]). Our linear-regression-based framework identifies 3,047 pan-cancer and 3,952 cancer-type-specific candidate TFa-GD associations from cell line data, which are then cross-examined for impact on survival in patient cohorts. One of the most prominent biomarkers is TEAD1 activity, whose associations with its predicted GDs are validated through experimental evidence as proof of concept. Overall, these TFa-GD associations represent an attractive resource for identifying innovative, biomarker-driven hypotheses for drug discovery programs in oncology.

Three-dimensional chromatin analysis reveals Sp1 as a mediator to program and reprogram HPV-host epigenetic architecture in cervical cancer

Human papillomavirus (HPV) is predominantly associated with HPV-related cancers, however, the precise mechanisms underlying the HPV-host epigenetic architectures in HPV carcinogenesis remain elusive. Here, we employed high-throughput chromosome conformation capture (Hi-C) to comprehensively map HPV16/18-host chromatin interactions. Our study identified the transcription factor Sp1 as a pivotal mediator in programming HPV-host interactions. By targeting Sp1, the active histone modifications (H3K27ac, H3K4me1, and H3K4me3) and the HPV-host chromatin interactions are reprogrammed, which leads to the downregulation of oncogenes located near the integration sites in both HPV (E6/E7) and the host genome (KLF5/MYC). Additionally, Sp1 inhibition led to the upregulation of immune checkpoint genes by reprogramming histone modifications in host cells. Notably, humanized patient-derived xenograft (PDX-HuHSC-NSG) models demonstrated that Sp1 inhibition promoted anti-PD-1 immunotherapy via remodeling the tumor immune microenvironment in cervical cancer. Moreover, single-cell transcriptomic analysis validated the enrichment of transcription factor Sp1 in epithelial cells of cervical cancer. In summary, our findings elucidate Sp1 as a key mediator involved in the programming and reprogramming of HPV-host epigenetic architecture. Inhibiting Sp1 with plicamycin may represent a promising therapeutic option for HPV-related carcinoma.

Tertiary lymphoid structures associated with enhanced anti-tumor immunity and favorable prognosis in cervical squamous carcinoma

BACKGROUND

Cervical squamous carcinoma (CESC) is the main subtype of cervical cancer. Unfortunately, there are presently no effective treatment options for advanced and recurrent CESC. Tertiary lymphoid structures (TLSs) are clusters of lymphoid cells that resemble secondary lymphoid organs; nevertheless, there is no summary of the clinical importance of TLS in CESC.

METHODS

A large set of transcriptomic and single-cell RNA-sequencing (scRNA-seq) datasets were used to analyze the pattern of TLS and its immuno-correlations in CESC. Additionally, an independent in-house cohort was collected to validate the correlation between TLS and TME features.

RESULTS

In the current study, we found that the presence of TLS could predict better prognosis in CESC and was correlated with the activation of immunological signaling pathways and enrichment of immune cell subpopulations. In addition, TLS was associated with reduced proliferation activity in tumor cells, indicating the negative correlation between TLS and the degree of malignancy. Last but not least, in two independent immunotherapy cohorts, tumors with the presence of TLS were more sensitive to immunotherapy.

CONCLUSION

Overall, TLS is related to an inflamed TME and identified immune-hot tumors, which could be an indicator for the identification of immunological features in CESC.

Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses

Background

Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated.

Methods

We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes.

Results

Through our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator-the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines.

Conclusion

This study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.

Single-cell RNA sequencing of cervical exfoliated cells reveals potential biomarkers and cellular pathogenesis in cervical carcinogenesis

Cervical cancer (CC) is a common gynecological malignancy. Despite the current screening methods have been proved effectively and significantly decreased CC morbidity and mortality, deficiencies still exist. Single-cell RNA sequencing (scRNA-seq) approach can identify the complex and rare cell populations at single-cell resolution. By scRNA-seq, the heterogeneity of tumor microenvironment across cervical carcinogenesis has been mapped and described. Whether these alterations could be detected and applied to CC screening is unclear. Herein, we performed scRNA-seq of 56,173 cervical exfoliated cells from 15 samples, including normal cervix, low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL), and malignancy. The present study delineated the alteration of immune and epithelial cells derived during the cervical lesion progression. A subset of lipid-associated macrophage was identified as a tumor-promoting element and could serve as a biomarker for predicting the progression of LSIL into HSIL, which was then verified by immunofluorescence. Furthermore, cell-cell communication analysis indicated the SPP1-CD44 axis might exhibit a protumor interaction between epithelial cell and macrophage. In this study, we investigated the cervical multicellular ecosystem in cervical carcinogenesis and identified potential biomarkers for early detection.

Exploring the tumor micro-environment in primary and metastatic tumors of different ovarian cancer histotypes

Ovarian cancer is a highly heterogeneous disease consisting of at least five different histological subtypes with varying clinical features, cells of origin, molecular composition, risk factors, and treatments. While most single-cell studies have focused on High grade serous ovarian cancer, a comprehensive landscape of the constituent cell types and their interactions within the tumor microenvironment are yet to be established in the different ovarian cancer histotypes. Further characterization of tumor progression, metastasis, and various histotypes are also needed to connect molecular signatures to pathological grading for personalized diagnosis and tailored treatment. In this study, we leveraged high-resolution single-cell RNA sequencing technology to elucidate the cellular compositions on 21 solid tumor samples collected from 12 patients with six ovarian cancer histotypes and both primary (ovaries) and metastatic (omentum, rectum) sites. The diverse collection allowed us to deconstruct the histotypes and tumor site-specific expression patterns of cells in the tumor, and identify key marker genes and ligand-receptor pairs that are active in the ovarian tumor microenvironment. Our findings can be used in improving precision disease stratification and optimizing treatment options.

An integrated study to decipher immunosuppressive cellular communication in the PDAC environment

Pancreatic ductal adenocarcinoma (PDAC) is one the most aggressive cancers and characterized by a highly rigid and immunosuppressive tumor microenvironment (TME). The extensive cellular interactions are known to play key roles in the immune evasion, chemoresistance, and poor prognosis. Here, we used the spatial transcriptomics, scRNA-seq, and bulk RNA-seq datasets to enhance the insights obtained from each to decipher the cellular communication in the TME. The complex crosstalk in PDAC samples was revealed by the single-cell and spatial transcriptomics profiles of the samples. We show that tumor-associated macrophages (TAMs) are the central cell types in the regulation of microenvironment in PDAC. They colocalize with the cancer cells and tumor-suppressor immune cells and take roles to provide an immunosuppressive environment. LGALS9 gene which is upregulated in PDAC tumor samples in comparison to healthy samples was also found to be upregulated in TAMs compared to tumor-suppressor immune cells in cancer samples. Additionally, LGALS9 was found to be the primary component in the crosstalk between TAMs and the other cells. The widespread expression of P4HB gene and its interaction with LGALS9 was also notable. Our findings point to a profound role of TAMs via LGALS9 and its interaction with P4HB that should be considered for further elucidation as target in the combinatory immunotherapies for PDAC.

Disfunction of communication among immune cells in minimal-deviation adenocarcinoma of the cervix as an immunotherapeutic opportunity

Minimal deviation adenocarcinoma (MDA) of the uterine cervix, also referred to as malignant adenoma, is a rare subtype of cervical adenocarcinoma that exhibits histological characteristics resembling those of benign tumors, resulting in a low diagnostic rate and a lack of effective treatment options. The transcriptomic features of MDA at the single-cell resolution and within the tumor microenvironment (TME) remain unclear. In this study, we conducted single-cell transcriptomic analyses of MDA samples (Ca) and adjacent normal tissues (PCa). The present study reveals the prevalence of dendritic cells (DCs) and T cells in the carcinoma (Ca) of mammary ductal adenocarcinoma (MDA), with DCs undergoing significant metabolic reprogramming and immune stress. Additionally, our findings demonstrate the crucial involvement of DCs and T cells in the pathogenesis and metastatic progression of MDA, as evidenced by single-cell transcriptomic profiling of MDA and HPV samples. This resource provides a more profound understanding of the indolent nature of MDA and may prove useful in the development of MDA immunotherapy.

Understanding cervical cancer at single-cell resolution

Cervical cancer is now the fourth most prevalent malignancy in women worldwide, representing a tremendous burden of cancer. The heterogeneity of complex tumor ecosystem impacts tumorigenesis, malignant progression, and response to treatment; thus, a thorough understanding of the tumor ecosystem is vital for enhancing the prognosis of patients with cervical cancer. The rapid development and widespread use of single-cell sequencing have generated a new paradigm of cancer research, providing a comprehensive and in-depth understanding of cancers. In this review, we give an overview of the recent advances made by leveraging single-cell sequencing studies in the dissection of cervical cancer ecosystem heterogeneity. We highlight the evolution of the cervical cancer ecosystem during tumor initiation, progression, and treatment. High-resolution dissection of cervical cancer at the single-cell level has the potential to drive the development of targeted therapies and enable the realization of personalized medicine.

Characterization of tumor microenvironment and tumor immunology based on the double-stranded RNA-binding protein related genes in cervical cancer

BACKGROUND

Cervical cancer is one of the most common gynecological cancers threatening women's health worldwide. Double-stranded RNA-binding proteins (dsRBPs) regulate innate immunity and are therefore believed to be involved in virus-related malignancies, however, their role in cervical cancer is not well known.

METHODS

We performed RNA-seq of tumor samples from cervical cancer patients in local cohort and also assessed the RNA-seq and clinical data derived from public datasets. By using single sample Gene Set Enrichment Analysis (ssGSEA) and univariate Cox analysis, patients were stratified into distinct dsRBP clusters. Stepwise Cox and CoxBoost were performed to construct a risk model based on optimal dsRBPs clusters-related differentially expressed genes (DEGs), and GSE44001 and CGCI-HTMCP-CC were employed as two external validation cohorts. Single cell RNA sequencing data from GSE168652 and Scissor algorithm were applied to evaluated the signature-related cell population.

RESULTS

The expression of dsRBP features was found to be associated with HPV infection and carcinogenesis in CESC. However, only Adenosine deaminases acting on RNA (ADAR) and Dicer, Drosha, and Argonautes (DDR) exhibited significant correlations with the overall survival (OS) of CESC patients. Based on these findings, CESC patients were divided into three dsRBP clusters. Cluster 3 showed superior OS but lower levels of ADAR and DDR. Additionally, Cluster 3 demonstrated enhanced innate immunity, with significantly higher activity in cancer immunity cycles, immune scores, and levels of tumor-infiltrating immune cells, particularly CD8+ T cells. Furthermore, a risk model based on nine dsRBP cluster-related DEGs was established. The accuracy of survival prediction for 1 to 5 years was consistently above 0.78, and this model's robust predictive capacity was confirmed by two external validation sets. The low-risk group exhibited significantly higher levels of immune checkpoints, such as PDCD1 and CTLA4, as well as a higher abundance of CD8+ T cells. Analysis of single-cell sequencing data revealed a significant association between the dsRBP signature and glycolysis. Importantly, low-risk patients showed improved OS and a higher response rate to immunotherapy, along with enduring clinical benefits from concurrent chemoradiotherapy.

CONCLUSIONS

dsRBP played a crucial role in the regulation of prognosis and tumor immunology in cervical cancer, and its prognostic signature provides a strategy for risk stratification and immunotherapy evaluation.

Single-Nucleus Transcriptome Profiling of Locally Advanced Cervical Squamous Cell Cancer Identifies Neural-Like Progenitor Program Associated with the Efficacy of Radiotherapy

Radiotherapy is the first-line treatment for locally advanced cervical squamous cell cancer (CSCC). However, ≈50% of patients fail to respond to therapy and, in some cases, tumors progress after radical radiotherapy. Here, single-nucleus RNA-seq is performed to construct high-resolution molecular landscapes of various cell types in CSCC before and during radiotherapy, to better understand radiotherapy related molecular responses within tumor microenvironment. The results show that expression levels of a neural-like progenitor (NRP) program in tumor cells are significantly higher after radiotherapy and these are enriched in the tumors of nonresponding patients. The enrichment of the NRP program in malignant cells from the tumors of nonresponders in an independent cohort analyzed by bulk RNA-seq is validated. In addition, an analysis of The Cancer Genome Atlas dataset shows that NRP expression is associated with poor prognosis in CSCC patients. In vitro experiments on the CSCC cell line demonstrate that downregulation of neuregulin 1 (NRG1), a key gene from NRP program, is associated with decreased cell growth and increased sensitivity to radiation. Immunohistochemistry staining in cohort 3 validated key genes, NRG1 and immediate early response 3 from immunomodulatory program, as radiosensitivity regulators. The findings reveal that the expression of NRP in CSCC can be used to predict the efficacy of radiotherapy.

Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis

Human Papillomaviruses (HPVs) are associated with around 5-10% of human cancer, notably nearly 99% of cervical cancer. The mechanisms HPV interacts with stratified epithelium (differentiated layers) during the viral life cycle, and oncogenesis remain unclear. In this study, we used single-cell transcriptome analysis to study viral gene and host cell differentiation-associated heterogeneity of HPV-positive cervical cancer tissue. We examined the HPV16 genes - E1, E6, and E7, and found they expressed differently across nine epithelial clusters. We found that three epithelial clusters had the highest proportion of HPV-positive cells (33.6%, 37.5%, and 32.4%, respectively), while two exhibited the lowest proportions (7.21% and 5.63%, respectively). Notably, the cluster with the most HPV-positive cells deviated significantly from normal epithelial layer markers, exhibiting functional heterogeneity and altered epithelial structuring, indicating that significant molecular heterogeneity existed in cancer tissues and that these cells exhibited unique/different gene signatures compared with normal epithelial cells. These HPV-positive cells, compared to HPV-negative, showed different gene expressions related to the extracellular matrix, cell adhesion, proliferation, and apoptosis. Further, the viral oncogenes E6 and E7 appeared to modify epithelial function via distinct pathways, thus contributing to cervical cancer progression. We investigated the HPV and host transcripts from a novel viewpoint focusing on layer heterogeneity. Our results indicated varied HPV expression across epithelial clusters and epithelial heterogeneity associated with viral oncogenes, contributing biological insights to this critical field of study.

Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis

Human Papillomaviruses (HPVs) are associated with around 5%-10% of human cancer, notably nearly 99% of cervical cancer. The mechanisms HPV interacts with stratified epithelium (differentiated layers) during the viral life cycle, and oncogenesis remain unclear. In this study, we used single-cell transcriptome analysis to study viral gene and host cell differentiation-associated heterogeneity of HPV-positive cervical cancer tissue. We examined the HPV16 genes-E1, E6, and E7, and found they expressed differently across nine epithelial clusters. We found that three epithelial clusters had the highest proportion of HPV-positive cells (33.6%, 37.5%, and 32.4%, respectively), while two exhibited the lowest proportions (7.21% and 5.63%, respectively). Notably, the cluster with the most HPV-positive cells deviated significantly from normal epithelial layer markers, exhibiting functional heterogeneity and altered epithelial structuring, indicating that significant molecular heterogeneity existed in cancer tissues and that these cells exhibited unique/different gene signatures compared with normal epithelial cells. These HPV-positive cells, compared to HPV-negative, showed different gene expressions related to the extracellular matrix, cell adhesion, proliferation, and apoptosis. Further, the viral oncogenes E6 and E7 appeared to modify epithelial function via distinct pathways, thus contributing to cervical cancer progression. We investigated the HPV and host transcripts from a novel viewpoint focusing on layer heterogeneity. Our results indicated varied HPV expression across epithelial clusters and epithelial heterogeneity associated with viral oncogenes, contributing biological insights to this critical field of study.

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

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.

Cervical cancer immune infiltration microenvironment identification, construction of immune scores, assisting patient prognosis and immunotherapy

Background

The immune microenvironment is of great significance in cervical cancer. However, there is still a lack of systematic research on the immune infiltration environment of cervical cancer.

Methods

We obtained cervical cancer transcriptome data and clinical information from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, evaluated the immune microenvironment of cervical cancer, determined immune subsets, constructed an immune cell infiltration scoring system, screened key immune-related genes, and performed single-cell data analysis and cell function analysis of key genes.

Results

We combined the TCGA and GEO data sets and obtained three different immune cell populations. We obtained two gene clusters, extracted 119 differential genes, and established an immune cell infiltration (ICI) scoring system. Finally, three key genes, IL1B, CST7, and ITGA5, were identified, and single-cell sequencing data were mined to distribute these key genes in different cell types. By up-regulating CST7 and down-regulating IL1B and ITGA5, cervical cancer cells’ proliferation ability and invasion ability were successfully reduced.

Conclusion

We conducted a comprehensive assessment of the state of the tumor immune microenvironment in cervical cancer, constructed the ICI scoring system, and identified the ICI scoring system as a potential indicator of susceptibility to immunotherapy for cervical cancer, identifying key genes suggesting that IL1B, CST7, and ITGA5 play an essential role in cervical cancer.

Spatiotemporally deciphering the mysterious mechanism of persistent HPV-induced malignant transition and immune remodelling from HPV-infected normal cervix, precancer to cervical cancer: Integrating single-cell RNA-sequencing and spatial transcriptome

BACKGROUND

The mechanism underlying cervical carcinogenesis that is mediated by persistent human papillomavirus (HPV) infection remains elusive.

AIMS

Here, for the first time, we deciphered both the temporal transition and spatial distribution of cellular subsets during disease progression from normal cervix tissues to precursor lesions to cervical cancer.

MATERIALS & METHODS

We generated scRNA-seq profiles and spatial transcriptomics data from nine patient samples, including two HPV-negative normal, two HPV-positive normal, two HPV-positive HSIL and three HPV-positive cancer samples.

RESULTS

We not only identified three 'HPV-related epithelial clusters' that are unique to normal, high-grade squamous intraepithelial lesions (HSIL) and cervical cancer tissues but also discovered node genes that potentially regulate disease progression. Moreover, we observed the gradual transition of multiple immune cells that exhibited positive immune responses, followed by dysregulation and exhaustion, and ultimately established an immune-suppressive microenvironment during the malignant program. In addition, analysis of cellular interactions further verified that a 'homeostasis-balance-malignancy' change occurred within the cervical microenvironment during disease progression.

DISCUSSION

We for the first time presented a spatiotemporal atlas that systematically described the cellular heterogeneity and spatial map along the four developmental steps of HPV-related cervical oncogenesis, including normal, HPV-positive normal, HSIL and cancer. We identified three unique HPV-related clusters, discovered critical node genes that determined the cell fate and uncovered the immune remodeling during disease escalation.

CONCLUSION

Together, these findings provided novel possibilities for accurate diagnosis, precise treatment and prognosis evaluation of patients with precancer and cervical cancer.

Characterization of the microenvironment in different immune-metabolism subtypes of cervical cancer with prognostic significance

Introduction: Immune cell infiltration and metabolic reprogramming may have great impact on the tumorigenesis and progression of malignancies. The interaction between these two factors in cervical cancer remains to be clarified. Here we constructed a gene set containing immune and metabolism related genes and we applied this gene set to molecular subtyping of cervical cancer. Methods: Bulk sequencing and single-cell sequencing data were downloaded from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database respectively. Immune and metabolism related genes were collected from Immport and Kyoto encyclopedia of genes and genomes (KEGG) database respectively. Unsupervised consensus clustering was performed to identify the molecular subtypes. Cibersort was applied to evaluate the immune cells infiltration status. Differential expression analysis and Gene set enrichment analysis (GSEA) were performed to characterize the molecular pattern of different subtypes. Multivariate Cox regression analysis was used for prognosis prediction model construction and receiver operating characteristic (ROC) curve was used for performance evaluation. The hub genes in the model were verified in single-cell sequencing dataset and clinical specimens. In vitro experiments were performed to validate the findings in our research. Results: Three subtypes were identified with prognostic implications. C1 subgroup was in an immunosuppressive state with activation of mitochondrial cytochrome P450 metabolism, C2 had poor immune cells infiltration and was characterized by tRNA anabolism, and the C3 subgroup was in an inflammatory state with activation of aromatic amino acid synthesis. The area under the ROC curve of the constructed model was 0.8, which showed better performance than clinical features. IMPDH1 was found to be significantly upregulated in tumor tissue and it was demonstrated that IMPDH1 could be a novel therapeutic target in vitro. Discussion: In summary, our findings suggested novel molecular subtypes of cervical cancer with distinct immunometabolic profiles and uncovered a novel therapeutic target.

Single-cell transcriptomics dissects epithelial heterogeneity in HPV+ cervical adenocarcinoma

The intra- and intertumoral heterogeneity of epithelial cells in human papillomavirus (HPV⁺ ) cervical adenocarcinoma (CEAD) remains largely unknown. To investigate this issue, we performed single-cell RNA sequencing on 19 229 epithelial cells sorted from three tumor samples of three patients with HPV⁺ CEAD. Six epithelial subclusters (Epi1-Epi6) were identified that showed distinct gene expression. Among these, Epi1 and Epi4 had apparent tumor hallmarks and metabolic activities. Epi1 was highly enriched in hallmarks of hypoxia, IL2/STAT5 signaling, retinol metabolism, glycolysis, and arachidonic acid metabolism, while Epi4 was highly enriched in hallmarks of G2M checkpoint, E2F targets, DNA repair, PI3K/AKT/MTOR signaling, glycolysis, fatty acid degradation, TCA cycle, and glutathione metabolism. We also investigated intertumoral epithelial heterogeneity and found that Patient 1 was highly enriched for KRAS signaling and angiogenesis, while Patient 2 was highly enriched for epithelial-mesenchymal transition and TGF-β signaling, and Patient 3 was highly enriched for hypoxia, DNA repair, G2M checkpoint, and E2F targets. Using single-cell RNA sequencing, we revealed the intra- and intertumoral heterogeneity of epithelial cells in HPV⁺ CEAD, providing insights into the importance of personalized treatment for patients with HPV⁺ CEAD.

Single-cell dissection of cellular and molecular features underlying human cervical squamous cell carcinoma initiation and progression

Cervical squamous cell carcinoma (CESC) is a prototypical human cancer with well-characterized pathological stages of initiation and progression. However, high-resolution knowledge of the transcriptional programs underlying each stage of CESC is lacking, and important questions remain. We performed single-cell RNA sequencing of 76,911 individual cells from 13 samples of human cervical tissues at various stages of malignancy, illuminating the transcriptional tumorigenic trajectory of cervical epithelial cells and revealing key factors involved in CESC initiation and progression. In addition, we found significant correlations between the abundance of specific myeloid, lymphoid, and endothelial cell populations and the progression of CESC, which were also associated with patients' prognosis. Last, we demonstrated the tumor-promoting function of matrix cancer-associated fibroblasts via the NRG1-ERBB3 pathway in CESC. This study provides a valuable resource and deeper insights into CESC initiation and progression, which is helpful in refining CESC diagnosis and for the design of optimal treatment strategies.

Single-nucleus RNA sequencing and deep tissue proteomics reveal distinct tumour microenvironment in stage-I and II cervical cancer

BACKGROUND

Cervical cancer (CC) is the 3rd most common cancer in women and the 4th leading cause of deaths in gynaecological malignancies, yet the exact progression of CC is inconclusive, mainly due to the high complexity of the changing tumour microenvironment (TME) at different stages of tumorigenesis. Importantly, a detailed comparative single-nucleus transcriptomic analysis of tumour microenvironment (TME) of CC patients at different stages is lacking.

METHODS

In this study, a total of 42,928 and 29,200 nuclei isolated from the tumour tissues of stage-I and II CC patients and subjected to single-nucleus RNA sequencing (snRNA-seq) analysis. The cell heterogeneity and functions were comparatively investigated using bioinformatic tools. In addition, label-free quantitative mass spectrometry based proteomic analysis was carried out. The proteome profiles of stage-I and II CC patients were compared, and an integrative analysis with the snRNA-seq was performed.

RESULTS

Compared with the stage-I CC (CCI) patients, the immune response relevant signalling pathways were largely suppressed in various immune cells of the stage-II CC (CCII) patients, yet the signalling associated with cell and tissue development was enriched, as well as metabolism for energy production suggested by the upregulation of genes associated with mitochondria. This was consistent with the quantitative proteomic analysis that showed the dominance of proteins promoting cell growth and intercellular matrix development in the TME of CCII group. The interferon-α and γ responses appeared the most activated pathways in many cell populations of the CCI patients. Several collagens, such as COL12A1, COL5A1, COL4A1 and COL4A2, were found significantly upregulated in the CCII group, suggesting their roles in diagnosing CC progression. A novel transcript AC244205.1 was detected as the most upregulated gene in CCII patients, and its possible mechanistic role in CC may be investigated further.

CONCLUSIONS

Our study provides important resources for decoding the progression of CC and set the foundation for developing novel approaches for diagnosing CC and tackling the immunosuppressive TME.

Angiogenesis-related gene signatures reveal the prognosis of cervical cancer based on single cell sequencing and co-expression network analysis

Cervical cancer ranks first in female reproductive tract tumors in terms of morbidity and mortality. Yet the curative effect of patients with persistent, recurrent or metastatic cervical cancer remains unsatisfactory. Although antitumor angiogenic drugs have been recommended as the first-line treatment options for cervical cancer, there are no comprehensive prognostic indicators for cervical cancer based on angiogenic signature genes. In this study, we aimed to develop a model to assess the prognosis of cervical cancer based on angiogenesis-related (AG) signature genes, and to provide some reference for the comprehensive treatment of cervical cancer in the clinical setting. First we screened the AG gene set from GeneCard website, and then performed angiogenesis-related scores (AGS) per cell from single cell sequencing dataset GSE168652, followed by performing weighted gene co-expression network analysis (WGCNA) for cervical cancer patients according to angiogenesis phenotype. Thus, we established a prognostic model based on AGS by taking the intersection of WGCNA angiogenic module gene and differential gene (DEGs) of GSE168652. The GSE44001 was selected as an external validation set, followed by performing ROC curve analysis to assess its accuracy. The results showed that we successfully constructed a prognostic model related to the AG genes. Patients in the high-AGS group in both the train, test and the validation sets had a worse prognosis than those in the low-AGS group, had lower expression of most immune checkpoint-associated genes and lower tumor mutational burden as well. Patients in the low-AGS group were more sensitive to AMG.706, Bosutinib, and Lenalidomide while Imatinib, Pazopanib, and Sorafenib were more recommended to patients in the high-AGS group. Finally, TXNDC12 and ZC3H13, which have high hazard ratio and poor prognosis in the model, were highly expressed in cervical cancer cell lines and tissue. Meanwhile, the results showed that TXNDC12 promoted the migration of cervical cancer cells and the tubule-forming ability of endothelial cells. In conclusion, our model based on genes with AG features can effectively assess the prognosis of cervical cancer, and can also provide reference for clinicians to choose immune-related treatments.

Multi-region sequencing depicts intratumor heterogeneity and clonal evolution in cervical cancer

Cervical cancer is a heterogeneous malignancy mainly caused by human papillomavirus (HPV). While a few studies have revealed heterogeneity of cervical cancer in chromosome levels, the correlation between genetic heterogeneity and HPV integration in cervical cancer remains unknown. Here, we applied multi-region whole-exome sequencing and HPV integration analysis to explore intratumor heterogeneity in cervical cancer. We sequenced 20 tumor regions and 5 adjacent normal tissues from 5 cervical cancer patients, analysis based on somatic mutations and somatic copy number alterations (SCNAs) levels were performed. Variable heterogeneity was observed between the five patients with different tumor stages and HPV infection statuses. We found HPV integration has a positive effect on somatic mutation burden, but the relation to SCNAs remains unclear. Frequently mutated genes in cervical cancer were identified as trunk events, such as FBXW7, PIK3CA, FAT1 in somatic mutations and TP63, MECOM, PIK3CA, TBL1XR1 in SCNAs. New potential driver genes in cervical cancer were summarized including POU2F2, TCF7 and UBE2A. The SCNAs level has potential relation with tumor stage, and Signature 3 related to homologous recombination deficiency may be the appropriate biomarker in advanced cervical cancer. Mutation signature analysis also revealed a potential pattern that APOBEC-associated signature occurs in early stage and signatures associated with DNA damage repair arise at the later stage of cervical cancer evolution. In a conclusion, our study provides insights into the potential relationship between HPV infection and tumor heterogeneity. Those results enhanced our understanding of tumorigenesis and progression in cervical cancer.

Single-cell transcriptomic analysis of the role of HPV16-positive macrophages in cervical cancer prognosis

Almost all cases of cervical cancer (CC) can be attributed to high-risk human papillomavirus (HPVs) infections in keratinocytes. However, it is unknown whether HPV invades immune cells such as macrophages and T cells. We analyzed the single-cell transcriptome of the CC and its adjacent tissues and found that HPV16 genes, including E1, E6, and E7, expressed in the macrophages and CD8⁺ T cells in addition to the malignant cells. HPV16⁺ macrophages highly expressed the genes that promote cell adhesion and the favorable genes such as WAS, IQCB1, MYO1F, and PDZD11 in CC prognosis. The transcription factor KLF5 potentially accounted for the induction of these protective genes and thus facilitated the infiltration of the immune cells in tumor tissues. Our single-cell transcriptome analysis suggests the potential value of the HPV16⁺ macrophage in CC prognosis. However, extensive experimental studies investigating the characteristics and functions of the HPV⁺ immune cells are still required.

A risk prediction model mediated by genes of APOD/APOC1/SQLE associates with prognosis in cervical cancer

Cervical cancer is one of the most common gynecological malignancies. Due to the high heterogeneity of cervical cancer accelerating cancer progression, it is necessary to identify new prognostic markers and treatment regimens for cervical cancer to improve patients' survival rates. We purpose to construct and verify a risk prediction model for cervical cancer patients. Based on the analysis of data from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA), differences of genes in normal and cancer samples were analyzed and then used analysis of WGCNA along with consistent clustering to construct single-factor + multi-factor risk models. After regression analysis, the target genes were obtained as prognostic genes and prognostic risk models were constructed, and the validity of the risk model was confirmed using the receiver operating characteristic curve (ROC) and Kaplan-Meier curve. Subsequently, the above model was verified on the GSE44001 data validation followed by independent prognostic analysis. Enrichment analysis was conducted by grouping the high and low risks of the model. In addition, differences in immune analysis (immune infiltration, immunotherapy), drug sensitivity, and other levels were counted by the high and low risks groups. In our study, three prognostic genes including APOD, APOC1, and SQLE were obtained, and a risk model was constructed along with validation based on the above-mentioned analysis. According to the model, immune correlation and immunotherapy analyses were carried out, which will provide a theoretical basis and reference value for the exploration and treatment of cervical cancer.

Activation of OSM-STAT3 Epigenetically Regulates Tumor-Promoting Transcriptional Programs in Cervical Cancer

Despite improvements in preventative strategies, such as regular screenings with Pap tests and human papillomavirus (HPV) tests as well as HPV vaccinations, effective treatment for advanced cervical cancer remains poor. Deregulation of STAT3 is an oncogenic factor that promotes tumorigenesis and epithelial-to-mesenchymal transition (EMT) in various cancers. Oncostatin M (OSM), a pleiotropic cytokine, induces STAT3 activation, exacerbating cervical cancer. However, the mechanism by which the OSM-STAT3 axis epigenetically regulates tumor-progression-related genes in cervical cancer is not well understood. Here, we show that OSM-mediated STAT3 activation promotes pro-tumorigenic gene expression programs, with chromatin remodeling in cervical cancer. Reanalysis of scRNA-seq data performed in cervical cancer uncovered an interaction between the oncostatin M receptor (OSMR) on tumor cells and OSM induced by tumor-associated macrophages (TAMs). Our gene expression profiling (bulk RNA-seq) shows that OSM-induced genes were involved in hypoxia, wound healing, and angiogenesis, which were significantly inhibited by SD-36, a STAT3-selective degrader. Additionally, ATAC-seq experiments revealed that STAT3 binding motifs were preferentially enriched in open chromatin regions of the OSM-STAT3-regulated genes. Among the 50 candidate genes that were regulated epigenetically through the OSM-STAT3 axis, we found that the expression levels of NDRG1, HK2, PLOD2, and NPC1 were significantly correlated with those of OSMR and STAT3 in three independent cervical cancer cohorts. Also, higher expression levels of these genes are significantly associated with poor prognosis in cervical cancer patients. Collectively, our findings demonstrate that the OSM-STAT3 signaling pathway regulates crucial transcriptomic programs through epigenetic changes and that selective inhibition of STAT3 may be a novel therapeutic strategy for patients with advanced cervical cancer.

Integrated single-cell transcriptome analysis of the tumor ecosystems underlying cervical cancer metastasis

Cervical cancer (CC) is one of the most frequent female malignancies worldwide. However, the molecular mechanism of lymph node metastasis in CC remains unclear. In this study, we investigated the transcriptome profile of 51,507 single cells from primary tumors, positive lymph nodes (P-LN), and negative lymph nodes (N-LN) using single-cell sequencing. Validation experiments were performed using bulk transcriptomic datasets and immunohistochemical assays. Our results indicated that epithelial cells in metastatic LN were associated with cell- cycle-related signaling pathways, such as E2F targets, and mitotic spindle, and immune response-related signaling pathways, such as allograft rejection, IL2_STAT5_signaling, and inflammatory response. However, epithelial cells in primary tumors exhibited high enrichment of epithelial-mesenchymal translation (EMT), oxidative phosphorylation, and interferon alpha response. Our analysis then indicated that metastasis LN exhibited an early activated tumor microenvironment (TME) characterized by the decrease of naive T cells and an increase of cytotoxicity CD8 T cells, NK cells, FOXP3+ Treg cells compared with normal LN. By comparing the differently expressed gene of macrophages between tumor and metastatic LN, we discovered that C1QA+ MRC1^low macrophages were enriched in a tumor, whereas C1QA+ MRC1^high macrophages were enriched in metastatic LN. Finally, we demonstrated that cancer-associated fibroblasts (CAFs) in P-LN were associated with immune regulation, while CAFs in tumor underwent EMT. Our findings offered novel insights into the mechanisms of research, diagnosis, and therapy of CC metastasis.

Single-cell RNA-sequencing dissects cellular heterogeneity and identifies two tumor-suppressing immune cell subclusters in HPV-related cervical adenosquamous carcinoma

The intratumor heterogeneity of human papillomavirus (HPV)-related cervical cancer remains poorly defined. We performed single-cell RNA sequencing on 18 046 individual cells derived from two HPV-related cervical adenosquamous carcinoma samples to analyze the transcriptional heterogeneity of both epithelial and immune constituents, identifying seven epithelial (Epi1-7) and 11 immune subclusters. Based on expression of known cervical cancer markers, Epi1-2 primarily displayed features of adenocarcinoma, whereas Epi3-6 were instead characterized by features of squamous carcinoma. Our analyses also revealed that hypoxia and Kirsten rat sarcoma viral oncogene signaling were highly represented within Epi1; metabolic pathways mediating glycolysis and oxidative phosphorylation were enriched in Epi2-4; while Epi5 was enriched in p53 pathway components and features of epithelial-mesenchymal transition. Moreover, CD8⁺ FGFBP2⁺ T cells and FGFBP2⁺ natural killer cells were found to display high levels of cytotoxic effectors (GZMA, GZMB, GNLY, and PRF1) and low levels of inhibitory markers (PDCD1, TIGIT, and CTLA4), such that tumor infiltration by these populations was positively associated with survival in a cohort of n = 165 patients with HPV-related cervical cancer from The Cancer Genome Atlas database (p = 0.017 and 0.014, respectively). These results shed new light on the intratumor heterogeneity of HPV-related cervical adenosquamous carcinoma, which will help to refine diagnostic and treatment approaches.

Cervical cancer heterogeneity: a constant battle against viruses and drugs

Cervical cancer is the first identified human papillomavirus (HPV) associated cancer and the most promising malignancy to be eliminated. However, the ever-changing virus subtypes and acquired multiple drug resistance continue to induce failure of tumor prevention and treatment. The exploration of cervical cancer heterogeneity is the crucial way to achieve effective prevention and precise treatment. Tumor heterogeneity exists in various aspects including the immune clearance of viruses, tumorigenesis, neoplasm recurrence, metastasis and drug resistance. Tumor development and drug resistance are often driven by potential gene amplification and deletion, not only somatic genomic alterations, but also copy number amplifications, histone modification and DNA methylation. Genomic rearrangements may occur by selection effects from chemotherapy or radiotherapy which exhibits genetic intra-tumor heterogeneity in advanced cervical cancers. The combined application of cervical cancer therapeutic vaccine and immune checkpoint inhibitors has become an effective strategy to address the heterogeneity of treatment. In this review, we will integrate classic and recently updated epidemiological data on vaccination rates, screening rates, incidence and mortality of cervical cancer patients worldwide aiming to understand the current situation of disease prevention and control and identify the direction of urgent efforts. Additionally, we will focus on the tumor environment to summarize the conditions of immune clearance and gene integration after different HPV infections and to explore the genomic factors of tumor heterogeneity. Finally, we will make a thorough inquiry into completed and ongoing phase III clinical trials in cervical cancer and summarize molecular mechanisms of drug resistance among chemotherapy, radiotherapy, biotherapy, and immunotherapy.

Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer

Cervical cancer (CC) is the most common gynecological malignancy, whose cellular heterogeneity has not been fully understood. Here, we performed single-cell RNA sequencing (scRNA-seq) to survey the transcriptomes of 57,669 cells derived from three CC tumors with paired normal adjacent non-tumor (NAT) samples. Single-cell transcriptomics analysis revealed extensive heterogeneity in malignant cells of human CCs, wherein epithelial subpopulation exhibited different genomic and transcriptomic signatures. We also identified cancer-associated fibroblasts (CAFs) that may promote tumor progression of CC, and further distinguished inflammatory CAF (iCAF) and myofibroblastic CAF (myCAF). CD8+ T cell diversity revealed both proliferative (MKI67+) and non-cycling exhausted (PDCD1+) subpopulations at the end of the trajectory path. We used the epithelial signature genes derived from scRNA-seq to deconvolute bulk RNA-seq data of CC, identifying four different CC subtypes, namely hypoxia (S-H subtype), proliferation (S-P subtype), differentiation (S-D subtype), and immunoactive (S-I subtype) subtype. The S-H subtype showed the worst prognosis, while CC patients of the S-I subtype had the longest overall survival time. Our results lay the foundation for precision prognostic and therapeutic stratification of CC.

LncRNA TP53TG1 plays an anti-oncogenic role in cervical cancer by synthetically regulating transcriptome profile in HeLa cells

Long non-coding RNAs (lncRNAs) have been extensively studied as important regulators of tumor development in various cancers. Tumor protein 53 target gene 1 (TP53TG1) is a newly identified lncRNA in recent years, and several studies have shown that TP53TG1 may play oncogenic or anti-oncogenic roles in different cancers. Nevertheless, the role of TP53TG1 in the development of cervical cancer is unclear. In our study, pan-cancer analysis showed that high expression of TP53TG1 was significantly associated with a better prognosis. We then constructed a TP53TG1 overexpression model in HeLa cell line to explore its functions and molecular targets. We found that TP53TG1 overexpression significantly inhibited cell proliferation and induced apoptosis, demonstrating that TP53TG1 may be a novel anti-oncogenic factor in cervical cancer. Furthermore, overexpression of TP53TG1 could activate type I interferon signaling pathways and inhibit the expression of genes involved in DNA damage responses. Meanwhile, TP53TG1 could affect alternative splicing of genes involved in cell proliferation or apoptosis by regulating the expression of many RNA-binding protein genes. Competing endogenous RNA (ceRNA) network analysis demonstrated that TP53TG1 could act as the sponge of several miRNAs to regulate the expression level of target genes. In conclusion, our study highlights the essential role of lncRNA TP53TG1 in the development of cervical cancer and suggests the potential regulatory mechanisms.

Single-Nucleus RNA Sequencing and Spatial Transcriptomics Reveal the Immunological Microenvironment of Cervical Squamous Cell Carcinoma

The effective treatment of advanced cervical cancer remains challenging. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial enhanced resolution omics-sequencing (Stereo-seq) are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC). The expression levels of most immune suppressive genes in the tumor and inflammation areas of CSCC are not significantly higher than those in the non-cancer samples, except for LGALS9 and IDO1. Stronger signals of CD56+ NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, whereas more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of pro-tumorigenic cancer-associated myofibroblasts (myCAFs) are identified. The myCAFs may support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling of the tumor extracellular matrix. Furthermore, these myCAFs are associated with poorer survival probability in patients with CSCC, predict resistance to immunotherapy, and might be present in a small fraction (< 30%) of patients with advanced cancer. Immunohistochemistry and multiplex immunofluorescence staining are conducted to validate the spatial distribution and potential function of myCAFs. Collectively, these findings enhance the understanding of the immunological microenvironment of CSCC and shed light on the treatment of advanced CSCC.

Comparative profiling of single-cell transcriptome reveals heterogeneity of tumor microenvironment between solid and acinar lung adenocarcinoma

BACKGROUND

The diversity of histologic composition reflects the inter- and intra-tumor heterogeneity of lung adenocarcinomas (LUADs) macroscopically. Insights into the oncological characteristics and tumor microenvironment (TME) of different histologic subtypes of LUAD at the single-cell level can help identify potential therapeutic vulnerabilities and combinational approaches to improve the survival of LUAD patients.

METHODS

Through comparative profiling of cell communities defined by scRNA-seq data, we characterized the TME of LUAD samples of distinct histologic subtypes, with relevant results further confirmed in multiple bulk transcriptomic, proteomic datasets and an independent immunohistochemical validation cohort.

RESULTS

We find that the hypoxic and acidic situation is the worst in the TME of solid LUADs compared to other histologic subtypes. Besides, the tumor metabolic preferences vary across histologic subtypes and may correspondingly impinge on the metabolism and function of immune cells. Remarkably, tumor cells from solid LUADs upregulate energy and substance metabolic activities, particularly the folate-mediated one-carbon metabolism and the key gene MTHFD2, which could serve as a potential therapeutic target. Additionally, ubiquitination modifications may also be involved in the progression of histologic patterns. Immunologically, solid LUADs are characterized by a predominance of exhausted T cells and immunosuppressive myeloid cells, where the hypoxic, acidified and nutrient-deprived TME has a non-negligible impact. Discrepancies in stromal cell function, evidenced by varying degrees of stromal remodeling and fibrosis, may also contribute to the specific immune phenotype of solid LUADs.

CONCLUSIONS

Overall, our research proposes several potential entry points to improve the immunosuppressive TME of solid LUADs, thereby synergistically potentiating their immunotherapeutic efficacy, and may provide precise therapeutic strategies for LUAD patients of distinct histologic subtype constitution.

Metabolic Reprogramming in Tumor Endothelial Cells

The dynamic crosstalk between the different components of the tumor microenvironment is critical to determine cancer progression, metastatic dissemination, tumor immunity, and therapeutic responses. Angiogenesis is critical for tumor growth, and abnormal blood vessels contribute to hypoxia and acidosis in the tumor microenvironment. In this hostile environment, cancer and stromal cells have the ability to alter their metabolism in order to support the high energetic demands and favor rapid tumor proliferation. Recent advances have shown that tumor endothelial cell metabolism is reprogrammed, and that targeting endothelial metabolic pathways impacts developmental and pathological vessel sprouting. Therefore, the use of metabolic antiangiogenic therapies to normalize the blood vasculature, in combination with immunotherapies, offers a clinical niche to treat cancer.

A novel prognostic biomarker CD3G that correlates with the tumor microenvironment in cervical cancer

Cervical cancer (CESC) is the fourth most common and death-causing gynecological cancer, mostly induced by infection of human papillomavirus (HPV). Multiple components of the tumor microenvironment (TME), such as tumor infiltrating immune cells, could be targets of immunotherapy for HPV-related CESC. However, little is known about the TME of CESC until now. Here, we aimed to uncover the pathogenesis as well as to identify novel biomarkers to predict prognosis and immunotherapy efficacy for CESC. Combining the transcriptomic data and clinical characteristics, we identified differentially expressed genes in CESC samples from TCGA database by comparing the two groups with different ImmuneScore and StromalScore. Next, we detected ten key genes based on the PPI network and survival analyses with the univariate Cox regression model. Thereafter, we focused on CD3G, the only gene exhibiting increased RNA and protein expression in tumors by multiple analyses. Higher CD3G expression was associated with better survival; and it was also significantly associated with immune-related pathways through GSEA analysis. Furthermore, we found that CD3G expression was correlated with 16 types of TICs. Single cell RNA-sequencing data of CD3G in lymphocytes subgroup indicated its possible role in HPV defense. Hence, CD3G might be a novel biomarker in prognosis and immunotherapy for CESC patients.

BNIP3 Upregulation Characterizes Cancer Cell Subpopulation With Increased Fitness and Proliferation

BNIP3 is a BH3-only protein with both pro-apoptotic and pro-survival roles depending on the cellular context. It remains unclear how BNIP3 RNA level dictates cell fate decisions of cancer cells. Here, we undertook a quantitative analysis of BNIP3 expression and functions in single-cell datasets of various epithelial malignancies. Our results demonstrated that BNIP3 upregulation characterizes cancer cell subpopulations with increased fitness and proliferation. We further validated the upregulation of BNIP3 in liver cancer 3D organoid cultures compared with 2D culture. Taken together, the combination of in silico perturbations using public single-cell datasets and experimental cancer modeling using organoids ushered in a new approach to address cancer heterogeneity.

Deciphering cell-cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing

A tumor's heterogeneity has important implications in terms of its clonal origin, progression, stemness, and drug resistance. Therefore, because of its significance in treatment, it is important to understand the gene expression pattern of a single cell, track gene expression or mutation in heterogeneous cells, evaluate the clonal origin of cancer cells, and determine the selective evolution of different subpopulations of cancer cells. Researchers are able to trace a cell's mutation and identify different types of tumor cells by measuring the whole transcriptome with single-cell sequencing (scRNA-seq). This technology provides a better understanding of the molecular mechanisms driving tumor growth than that offered by traditional RNA sequencing methods. In addition, it has revealed changes in the mutations and functions of somatic cells as a tumor evolves; it has also clarified immune cell infiltration and activation. Research on scRNA-seq technology has recently advanced significantly, suggesting new strategies for the treatment of cancer. In short, cancer researchers have become increasingly dependent on scRNA-seq. This paper reviews the development, detection principles, and processes of scRNA-seq technology and their application in tumor research. It also considers potential clinical applications.

Dissecting the Single-Cell Transcriptome Network of Immune Environment Underlying Cervical Premalignant Lesion, Cervical Cancer and Metastatic Lymph Nodes

Cervical cancer (CC) is one of the most common malignancy in women worldwide. It is characterized by a natural continuous phenomenon, that is, it is in the initial stage of HPV infection, progresses to intraepithelial neoplasia, and then develops into invasion and metastasis. Determining the complexity of tumor microenvironment (TME) can deepen our understanding of lesion progression and provide novel therapeutic strategies for CC. We performed the single-cell RNA sequencing on the normal cervix, intraepithelial neoplasia, primary tumor and metastatic lymph node tissues to describe the composition, lineage, and functional status of immune cells and mesenchymal cells at different stages of CC progression. A total of 59913 single cells were obtained and divided into 9 cellular clusters, including immune cells (T/NK cells, macrophages, B cells, plasma cells, mast cells and neutrophils) and mesenchymal cells (endothelial cells, smooth muscle cells and fibroblasts). Our results showed that there were distinct cell subpopulations in different stages of CC. High-stage intraepithelial neoplasia (HSIL) tissue exhibited a low, recently activated TME, and it was characterized by high infiltration of tissue-resident CD8 T cell, effector NK cells, Treg, DC1, pDC, and M1-like macrophages. Tumor tissue displayed high enrichment of exhausted CD8 T cells, resident NK cells and M2-like macrophages, suggesting immunosuppressive TME. Metastatic lymph node consisted of naive T cell, central memory T cell, circling NK cells, cytotoxic CD8+ T cells and effector memory CD8 T cells, suggesting an early activated phase of immune response. This study is the first to delineate the transcriptome profile of immune cells during CC progression using single-cell RNA sequencing. Our results indicated that HSIL exhibited a low, recently activated TME, tumor displayed immunosuppressive statue, and metastatic lymph node showed early activated phase of immune response. Our study enhanced the understanding of dynamic change of TME during CC progression and has implications for the development of novel treatments to inhibit the initiation and progression of CC.

Integration of scRNA-Seq and TCGA RNA-Seq to Analyze the Heterogeneity of HPV+ and HPV- Cervical Cancer Immune Cells and Establish Molecular Risk Models

Background

Numerous studies support that Human papillomavirus (HPV) can cause cervical cancer. However, few studies have surveyed the heterogeneity of HPV infected or uninfected (HPV+ and HPV-) cervical cancer (CESC) patients. Integration of scRNA-seq and TCGA data to analyze the heterogeneity of HPV+ and HPV- cervical cancer patients on a single-cell level could improve understanding of the cellular mechanisms during HPV-induced cervical cancer.

Methods

CESC scRNA-seq data obtained from the Gene Expression Omnibus (GEO) database and the Seurat, Monocle3 package were used for scRNA-seq data analysis. The ESTIMATE package was used for single-sample gene immune score, CIBERSORT package was used to identify immune scores of cells, and the “WGCNA” package for the weighted correlation network analysis. Univariate Cox and LASSO regression were performed to establish survival and relapse signatures. KEGG and GO analyses were performed for the signature gene. Gene Expression Profiling Interactive Analysis was used for Pan-cancer analysis.

Results

In the HPV+ CESC group, CD8+ T cells and B cells were down-regulated, whereas T reg cells, CD4+ T cells, and epithelial cells were up-regulated according to scRNA-seq data. Survival analysis of TCGA-CESC revealed that increased expression of naive B cells or CD8+ T cells favors the survival probability of CESC patients. WGCNA, univariate Cox, and LASSO Cox regression established a 9-genes survival signature and a 7-gene relapse model. Pan-cancer analysis identified IKZF3, FOXP3, and JAK3 had a similar distribution and effects in HPV-associated HNSC.

Conclusion

Analysis of scRNA-seq and bulk RNA-seq of HPV+ and HPV- CESC samples revealed heterogeneity from transcriptional state to immune infiltration. Survival and relapse models were adjusted according to the heterogeneity of HPV+ and HPV- CESC immune cells to assess the prognostic risk accurately. Hub genes represent similar protection in HPV- associated HNSC while showing irrelevant to other potential HPV-related cancers.

Use of Single Cell Transcriptomic Techniques to Study the Role of High-Risk Human Papillomavirus Infection in Cervical Cancer

High-risk human papillomavirus (hrHPV) infection has been associated with a higher probability of progression to cervical cancer. However, several extensive studies have reported that the presence of hrHPV can lead to a better prognosis, but the mechanism of how this occurs is unclear. In this study, microbiological analysis was used to identify HPV infection as a factor for the prognosis of patients with cervical squamous cell carcinoma (CSCC). Comparing the interactions of HPV⁺ and HPV^- malignant cells with immune cells as well as the trajectory of malignant cells either with or without HPV, we found that most of the HPV⁺ cells are well differentiated while HPV^- cells appear to be hypo-fractionated. Using transcriptomic and immunostaining data, we validated a set of unfavourable molecules in the HPV^- CSCC cells, including KRT16, ITGB1, CXCR1, VEGFA, CRCT1 and TNFRSF10B/DR5. This study provides a basis for the development of a rational post-operative follow-up programme and the development of an appropriate treatment plan for patients with cervical cancer.

Single-Cell Sequencing: Current Applications in Precision Onco-Genomics and Cancer Therapeutics

Simple Summary

Single-cell sequencing technologies are growing, advancing, and supporting new opportunities to better understand cancer. A variety of technologies are available that analyze the human transcriptome, genome, epigenome, and proteome, enabling integrated datasets. As a result, these integrated datasets contribute to new mechanistic insights and areas with therapeutic potential. This review summarizes the various single-cell sequencing techniques and provides examples of recent high-impact findings from the utilization of these technologies. Additionally, the translational relevance of these technologies and their use in clinical trials is described, along with the future potential for novel findings using these innovative methods.

Abstract

Single-cell sequencing encompasses a variety of technologies that evaluate cells at the genomic, transcriptomic, epigenomic, and proteomic levels. Each of these levels can be split into additional techniques that enable specific and optimized sequencing for a specialized purpose. At the transcriptomic level, single-cell sequencing has been used to understand immune-malignant cell networks, as well as differences between primary versus metastatic tumors. At the genomic and epigenomic levels, single-cell sequencing technology has been used to study genetic mutations involved in tumor evolution or the reprogramming of regulatory elements present in metastasized disease, respectively. Lastly, at the proteomic level, single-cell sequencing has been used to identify biomarkers important for predicting patient prognosis, as well as biomarkers essential for evaluating optimal treatment strategies. Integrated databases and atlases, as a result of large sequencing experiments, provide a vast array of information that can be applied to various studies and accessed by researchers to further answer scientific questions. This review summarizes recent, high-impact literature covering these aspects, as well as single-cell sequencing in the translational setting. Specifically, we review the potential that single-cell sequencing has in the clinic and its implementation in current clinical studies.

Functional New Transcription Factors (TFs) Associated with Cervical Cancer

The goal of this research was to find noval transcription factors (TFs) that are involved in cervical carcinogenesis. The Gene Expression Omnibus (GEO) database was utilized to analyze ten cervical cancer datasets using the Robust Rank Aggregation (RRA) technique. Survival and differential expression were validated using GEPIA (Gene Expression Profiling Interactive Analysis). The transcriptional regulatory network and putative targets were built using Cytoscape. A real-time PCR (quantitative real-time polymerase chain reaction) experiment was used to confirm the mRNA expression. Using public cervical cancer single-cell RNA-sequencing (scRNA-seq), bulk TCGA-CESC RNA-seq, and microarray datasets, coexpression correlations between putative targets and TFs were confirmed. After combining the results of 10 datasets, 8 TFs, including EMX2 (Empty Spiracles Homeobox 2), were chosen among 385 robust DEGs. In the normal female reproductive tract, EMX2 is extensively expressed, but it is reduced in cervical cancer. Overexpression EMX2 suppresses the proliferation of HeLa cells. 12 potential targets of EMX2 were selected. Our research has revealed evidence that EMX2 acted as a tumor suppressor in cervical cancer and PDZRN3 might be possible target of EMX2 in cervical cancer. It might be a therapeutic target in the future.

Angiogenesis goes computational – The future way forward to discover new angiogenic targets?

Multi-omics technologies are being increasingly utilized in angiogenesis research. Yet, computational methods have not been widely used for angiogenic target discovery and prioritization in this field, partly because (wet-lab) vascular biologists are insufficiently familiar with computational biology tools and the opportunities they may offer. With this review, written for vascular biologists who lack expertise in computational methods, we aspire to break boundaries between both fields and to illustrate the potential of these tools for future angiogenic target discovery. We provide a comprehensive survey of currently available computational approaches that may be useful in prioritizing candidate genes, predicting associated mechanisms, and identifying their specificity to endothelial cell subtypes. We specifically highlight tools that use flexible, machine learning frameworks for large-scale data integration and gene prioritization. For each purpose-oriented category of tools, we describe underlying conceptual principles, highlight interesting applications and discuss limitations. Finally, we will discuss challenges and recommend some guidelines which can help to optimize the process of accurate target discovery.

A New Antitumor Direction: Tumor-Specific Endothelial Cells

Targeting tumor blood vessels is an important strategy for tumor therapies. At present, antiangiogenic drugs are known to have significant clinical effects, but severe drug resistance and side effects also occur. Therefore, new specific targets for tumor and new treatment methods must be developed. Tumor-specific endothelial cells (TECs) are the main targets of antiangiogenic therapy. This review summarizes the differences between TECs and normal endothelial cells, assesses the heterogeneity of TECs, compares tumorigenesis and development between TECs and normal endothelial cells, and explains the interaction between TECs and the tumor microenvironment. A full and in-depth understanding of TECs may provide new insights for specific antitumor angiogenesis therapies.

Single-Cell RNA Sequencing Reveals Multiple Pathways and the Tumor Microenvironment Could Lead to Chemotherapy Resistance in Cervical Cancer

Background

Cervical cancer is one of the most common gynecological cancers worldwide. The tumor microenvironment significantly influences the therapeutic response and clinical outcome. However, the complex tumor microenvironment of cervical cancer and the molecular mechanisms underlying chemotherapy resistance are not well studied. This study aimed to comprehensively analyze cells from pretreated and chemoresistant cervical cancer tissues to generate a molecular census of cell populations.

Methods

Biopsy tissues collected from patients with cervical squamous cell carcinoma, cervical adenocarcinoma, and chronic cervicitis were subjected to single-cell RNA sequencing using the 10× Genomics platform. Unsupervised clustering analysis of cells was performed to identify the main cell types, and important cell clusters were reclustered into subpopulations. Gene expression profiles and functional enrichment analysis were used to explore gene expression and functional differences between cell subpopulations in cervicitis and cervical cancer samples and between chemoresistant and chemosensitive samples.

Results

A total of 24,371 cells were clustered into nine separate cell types, including immune and non-immune cells. Differentially expressed genes between chemoresistant and chemosensitive patients enriched in the phosphoinositide 3-kinase (PI3K)/AKT pathway were involved in tumor development, progression, and apoptosis, which might lead to chemotherapy resistance.

Conclusions

Our study provides a comprehensive overview of the cancer microenvironment landscape and characterizes its gene expression and functional difference in chemotherapy resistance. Consequently, our study deepens the insights into cervical cancer biology through the identification of gene markers for diagnosis, prognosis, and therapy.