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Site specificity of immunophenotypes a, UMAP plot of T and NK cell clusters profiled by scRNA-seq. Clusters are coloured and numbered to reference cluster labels in c. b, Pairwise comparisons of kernel density estimates in UMAP space. c, Left, heatmap of average T cell state module scores (left) and signalling pathway activity scores (right) across CD4⁺ T, CD8⁺ T, innate lymphoid cell (ILC), NK and cycling cell clusters. Right, dot plot showing site-specific enrichment of T and NK cell clusters based on GLM. The colour gradient indicates the log2-transformed odds ratio (red, enrichment; blue, depletion), and sizes indicate the Bonferroni-corrected –log10(P value). d, Intra-sample diversity of T and NK cell clusters estimated by Shannon entropy with samples grouped by site (patient and sample counts shown) and intra- and inter-patient dissimilarity of T and NK cell cluster composition for pairs of samples, estimated using the Bray–Curtis distance (patient and sample pair counts shown). Pairwise dissimilarity is shown for all heterotypic pairs of sites (adnexa versus non-adnexa, adnexa versus ascites, non-adnexa versus ascites). Violin plots show the median, top and bottom quartiles; whiskers correspond to 1.5× IQR. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. e, Top, diffusion maps of the subset of CD8⁺ T cells profiled by scRNA-seq, with cells coloured by CD8⁺ T cell cluster and pseudotime. Bottom, relative expression of genes marking CD8⁺ T cell clusters in diffusion space. DC, diffusion component. f, Scaled module scores with respect to pseudotime.
Source publication
High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability1–4 patterned by distinct mutational processes5,6, tumour heterogeneity7–9 and intraperitoneal spread7,8,10. Immunotherapies have had limited efficacy in HGSOC11–13, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour...
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Objective：Here, we explored the expression of SYNM by means of Gene Expression Omnibus (GEO) and investigated its prognostic significance as well as potential functions in gastric cancer (GC).
Methods：Toward this goal, differential gene expression analysis, univariate Cox regression, Lasso regression, best subset regression, Gene Set Enrichment Ana...
Citations
... Many HGSCs display rich tumor infiltration of CD8 + effector T lymphocytes, which is prognostically beneficial [4,5], but treatment with immune checkpoint inhibitors (ICI) has shown limited efficacy in this entity. The intratumoral T cells express inhibitory receptors resulting in impaired effector functions coupled to ICI resistance [6,7]. ...
... Kroeger et al. report a trend of TLS being more common in omental metastases than primary tumors in an investigation limited to 30 cases [8]. A single-cell RNA sequencing and multiplex immunofluorescence (mIF) mapping of different HGSC lesions has shown that immune cell densities vary between anatomical sites within patients, with higher lymphocyte and CD8 + TIL fractions observed in metastatic sites compared to the adnexae, and enrichment of dysfunctional T cells in adnexal sites [6]. ...
... Further, their results indicate that the scarcity of mTLS in HGSC is associated with an intratumoral CD8 + population which is dominated by an ICI-resistant TIM3 + PD-1 + phenotype, in contrast to TLS-rich non-small cell lung cancer, where the opposite is true [12]. In their elaborate characterization of the immune 8_PT 22_PT 27_PT 55_PT 64_PT 100_PT 111_PT 123_PT 145_PT 153_PT 8_pMet 13_pMet 53_pMet 55_pMet 60_pMet 64_pMet 70_pMet 74_pMet 96_pMet 113_pMet NA 8_PT 22_PT 27_PT 55_PT 64_PT 100_PT 111_PT 123_PT 145_PT 153_PT 8_pMet 13_pMet 53_pMet 55_pMet 60_pMet 64_pMet 70_pMet 74_pMet 96_pMet 113_pMet NA 8_PT 22_PT 27_PT 55_PT 64_PT 100_PT 111_PT 123_PT 145_PT 153_PT 8_pMet 13_pMet 53_pMet 55_pMet 60_pMet 64_pMet 70_pMet 74_pMet 96_pMet 113_pMet NA 8_PT 22_PT 27_PT 55_PT 64_PT 100_PT 111_PT 123_PT 145_PT 153_PT 8_pMet 13_pMet 53_pMet 55_pMet 60_pMet 64_pMet 70_pMet 74_pMet 96_pMet 113_pMet NA 8_PT 22_PT 27_PT 55_PT 64_PT 100_PT 111_PT 123_PT 145_PT 153_PT 8_pMet 13_pMet 53_pMet 55_pMet 60_pMet 64_pMet 70_pMet 74_pMet 96_pMet 113_pMet NA 8_PT 22_PT 27_PT 55_PT 64_PT 100_PT 111_PT 123_PT 145_PT 153_PT 8_pMet 13_pMet 53_pMet 55_pMet 60_pMet 64_pMet 70_pMet 74_pMet 96_pMet 113_pMet NA 8_PT 22_PT 27_PT 55_PT 64_PT 100_PT 111_PT 123_PT 145_PT 153_PT 8_pMet 13_pMet 53_pMet 55_pMet 60_pMet 64_pMet 70_pMet 74_pMet 96_pMet [6]. Our in-depth mapping of the cell composition and cell-cell interactions in PT and pMet TLS and LA revealed overall conformities between the sites and is consistent with descriptions of TLS characterized in other conditions and tissues [30,31]. ...
Tertiary lymphoid structures (TLS) in the tumor microenvironment are prognostically beneficial in many solid cancer types. Reports on TLS in high-grade serous tubo-ovarian carcinoma (HGSC) are few, and the prognostic impact is unclear. We investigated mature TLS (mTLS), immature TLS (iTLS) and lymphoid aggregates (LA) in primary adnexal tumors (PTs) and synchronous omental/peritoneal metastases (pMets) of HGSC. Whole H&E slides were scrutinized for mTLS and LA in a population-based cohort of 130 cases with stage III-IV HGSC. The immune cell tumor infiltration was evaluated with single chromogenic immunohistochemistry (IHC) on a tissue microarray (TMA) from the same cases. Selected whole slides (PT n = 11, pMet n = 10) of the cases most abundant in mTLS and LA were further investigated with multiplex IHC and immunofluorescence using digital image analysis (QuPath), to confirm TLS status and map the T and B lymphocyte subtypes. The results showed that mTLS were more common in pMets than in PTs but did not have an independent prognostic impact on overall or progression-free survival. The presence of mTLS correlated with intratumoral infiltration of CD8⁺ cytotoxic T cells, FOXP3⁺ regulatory T cells and PD-1⁺ lymphocytes in pMets only. Although overall mTLS cell composition was similar between PTs and pMets, the outer zones of mTLS in PTs were more immune cell-rich. In conclusion, our results indicate differences in TLS presence and cellular elements between primary adnexal tumors and synchronous peritoneal metastases, which are important to consider when conducting studies of the immune environment in HGSC.
... While initial reports had suggested limited effectiveness of immunotherapy, primarily due to the scarce presence of immune cells, recent years have witnessed a multitude of promising immunotherapy studies [6][7][8]. The capacity of cancer cells to evade the immune system poses a significant barrier to immunotherapeutic interventions [9]. The infiltrative migration of suppressive regulatory T cells into HGSOC tissue profoundly influences the prognosis of this malignancy [10]. ...
Immune checkpoint-based immunotherapy has shown limited efficacy in the treatment of ovarian cancer. In recent years, the emergence of immune checkpoint co-targeting therapies, led by the combination targeting of TIGIT and FAK, has shown promise in ovarian cancer treatment. Our preliminary research indicates that TIGIT is predominantly expressed in regulatory T cells during ovarian cancer. However, the therapeutic impact of TIGIT targeting based on regulatory T cells in ovarian cancer remains to be elucidated. We utilized ID8 cells to establish a mouse model of ovarian cancer. Through flow cytometry and co-culture methods, we validated the relationship between the functionality of regulatory T cells and tumor masses, and confirmed the crucial role of TIGIT in immune suppression in ovarian cancer. Furthermore, using Foxp3-diphtheria toxin receptor (DTR) mice, we substantiated that the combined TIGIT antibody treatment, based on targeting regulatory T cells, effectively slowed down the progression of ovarian cancer. Taken together, our results have demonstrated that dual targeting of regulatory T cells and TIGIT effectively retards tumor growth, laying the groundwork for the clinical application of immune checkpoint combination therapies. Future research in ovarian cancer immunotherapy is leaning towards a strategy that combines multiple targets, and specific cell-type immunotherapies.
Supplementary Information
The online version contains supplementary material available at 10.1186/s13048-024-01578-y.
... Tumorinfiltrating lymphocytes (TILs) can be detected in approximately half of ovarian cancer cases [12]. However, ovarian cancer is a highly heterogeneous malignant tumor, capable of evading immune surveillance during its spread and proliferation [13][14][15]. Due to the diversity of subtypes, the mechanisms of immune evasion also vary. In some patients, this is manifested by increased PD-L1 expression. ...
Ovarian cancer is the deadliest malignant tumor in the female reproductive system. Despite advancements in standard treatments such as tumor debulking surgery and platinum-based chemotherapy, the overall survival rate remains low. The emergence of targeted therapies, including Poly(ADP-ribose) polymerase (PARP) inhibitors and anti-angiogenic agents, has provided new avenues for treatment. However, drug resistance and disease heterogeneity continue to pose significant challenges. Immune checkpoint inhibitors (ICIs), as an emerging therapeutic approach, primarily target the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) pathways to restore anti-tumor immune responses. Although ICIs have shown significant efficacy in other malignancies, their effectiveness in ovarian cancer is limited, with a response rate of only 10–15% for monotherapy. Recent studies have focused on combining ICIs with chemotherapy, anti-angiogenic agents, or PARP inhibitors to enhance therapeutic outcomes. This article reviews the progress of ICIs in ovarian cancer, including monotherapy and combination treatment strategies, and explores emerging therapeutic targets and strategies aimed at improving patient prognosis and achieving personalized treatment. By gaining a deeper understanding of the tumor microenvironment and its immune evasion mechanisms, there is hope for developing more effective treatment options in the future, ultimately improving the survival rates and quality of life for ovarian cancer patients.
... Raw RNA sequencing data and clinical annotations for the ICON7 cohort (28) were downloaded from the EGA archive (EGAS00001003487). Single-cell RNA-seq data (29) were downloaded from the Gene Expression Omnibus (GEO) (GSE180661) as an annotated count matrix (anndata-object) in h5ad-format. Data files from the TOPACIO clinical trial (9) were retrieved from Synapse (https:// doi.org/10.7303/syn21569629). ...
Background
The efficacy of immunotherapies in high-grade serous ovarian cancer (HGSOC) is limited, but clinical trials investigating the potential of combination immunotherapy including poly-ADP-ribose polymerase inhibitors (PARPis) are ongoing. Homologous recombination repair deficiency or BRCAness and the composition of the tumor microenvironment appear to play a critical role in determining the therapeutic response.
Methods
We conducted comprehensive immunogenomic analyses of HGSOC using data from several patient cohorts. Machine learning methods were used to develop a classification model for BRCAness from gene expression data. Integrated analysis of bulk and single-cell RNA sequencing data was used to delineate the tumor immune microenvironment and was validated by immunohistochemistry. The impact of PARPi and BRCA1 mutations on the activation of immune-related pathways was studied using ovarian cancer cell lines, RNA sequencing, and immunofluorescence analysis.
Results
We identified a 24-gene signature that predicts BRCAness. Comprehensive immunogenomic analyses across patient cohorts identified samples with BRCAness and high immune infiltration. Further characterization of these samples revealed increased infiltration of immunosuppressive cells, including tumor-associated macrophages expressing TREM2, C1QA, and LILRB4, as specified by single-cell RNA sequencing data and gene expression analysis of samples from patients receiving combination therapy with PARPi and anti-PD-1. Our findings show also that genomic instability and PARPi activated the cGAS-STING signaling pathway in vitro and the downstream innate immune response in a similar manner to HGSOC patients with BRCAness status. Finally, we have developed a web application (https://ovrseq.icbi.at) and an associated R package OvRSeq, which allow for comprehensive characterization of ovarian cancer patient samples and assessment of a vulnerability score that enables stratification of patients to predict response to the combination immunotherapy.
Conclusions
Genomic instability in HGSOC affects the tumor immune environment, and TAMs play a crucial role in modulating the immune response. Based on various datasets, we have developed a diagnostic application that uses RNA sequencing data not only to comprehensively characterize HGSOC but also to predict vulnerability and response to combination immunotherapy.
... Most studies on immune cells in HGSOC focus on CD8 cells 2,9,10 with less information on the role of CD4 cells, especially after chemotherapy. Regulatory T cells (Tregs) represent 10-50% of the CD4 cells 11 in several human tumours. ...
... Previously published scRNA-seq data from HGSOC tumours were mainly obtained from treatment naïve patients 10,39,40 . The only study on chemotherapy-treated patient samples focused on stromal effects 41 . ...
Single-cell RNA sequencing (scRNAseq) of tumour-infiltrating immune cells in high-grade serous ovarian cancer (HGSOC) omental biopsies reveals potential targets that could enhance response to neo-adjuvant chemotherapy (NACT). Analysis of 64,097 cells identifies NACT-induced overexpression of stabilin-1 (clever-1) on macrophages and FOXP3 in Tregs that is confirmed at the protein level. STAB1 inhibition in vitro induces anti-tumour macrophages. FOXP3 anti-sense oligonucleotide (FOXP3-ASO), repolarises Tregs to an effector T cell phenotype. ScRNAseq on 69,781 cells from an HGSOC syngeneic mouse model recapitulates the patients’ data. Combining chemotherapy with anti-stabilin1 antibody and/or Foxp3-ASO significantly increases survival of mice with established peritoneal disease in two HGSOC syngeneic models and progression-free survival in a third model. Long-term survivors (300 days + ) are resistant to tumour rechallenge. Anti-stabilin1 antibody enriches the tumours with CXCL9+ macrophages and Foxp3-ASO increases TBET cell infiltration. Our results suggest that targeting these molecules in immune cells may improve chemotherapy response in patients.
... Lastly, to determine whether IL27 signaling is relevant in OvCa patients, we analyzed a recently published scRNA-seq dataset of tumors and ascites from patients with metastatic OvCa (Vázquez-García et al., 2022). In these tumors, IL27 and EBI3 were exclusively co-expressed in only monocytes/MΦs (Fig. S4, D and E), specifically in the "M2.CXCL10" subset ( Fig. 4, J and K). ...
... We obtained a scRNA-seq dataset deposited by Vázquez-García et al. from the National Center for Biotechnology Information Gene Expression Omnibus (GSE180661) (Vázquez-García et al., 2022). The dataset consisted of quality-filtered matrices of 929,686 cells. ...
Patients with metastatic ovarian cancer (OvCa) have a 5-year survival rate of <30% due to the persisting dissemination of chemoresistant cells in the peritoneal fluid and the immunosuppressive microenvironment in the peritoneal cavity. Here, we report that intraperitoneal administration of β-glucan and IFNγ (BI) induced robust tumor regression in clinically relevant models of metastatic OvCa. BI induced tumor regression by controlling fluid tumor burden and activating localized antitumor immunity. β-glucan alone cleared ascites and eliminated fluid tumor cells by inducing intraperitoneal clotting in the fluid and Dectin-1-Syk–dependent NETosis in the omentum. In omentum tumors, BI expanded a novel subset of immunostimulatory IL27+ macrophages and neutralizing IL27 impaired BI efficacy in vivo. Moreover, BI directly induced IL27 secretion in macrophages where single agent treatment did not. Finally, BI extended mouse survival in a chemoresistant model and significantly improved chemotherapy response in a chemo-sensitive model. In summary, we propose a new therapeutic strategy for the treatment of metastatic OvCa.
... The principal defining features of high-grade serous ovarian carcinoma (HGSOC), the most prevalent form of epithelial ovarian cancer, are copy number alterations and genomic rearrangements [27]. This makes genomic variants appealing as diagnostic or prognostic biomarkers, as well as for their easy detection [13]. ...
Background/Objectives: Aneuploidy is a prevalent cancer feature that occurs in many solid tumors. For example, high-grade serous ovarian cancer shows a high level of copy number alterations and genomic rearrangements. This makes genomic variants appealing as diagnostic or prognostic biomarkers, as well as for their easy detection. In this study, we focused on copy number (CN) losses shared by ovarian cancer stem cells (CSCs) to identify chromosomal regions that may be important for CSC features and, in turn, for patients’ prognosis. Methods: Array-CGH and bioinformatic analyses on three CSCs subpopulations were performed. Results: Pathway and gene ontology analyses on genes involved in copy number loss in all CSCs revealed a significant decrease in mRNA surveillance pathway, as well as miRNA-mediated gene silencing. Then, starting from these CN losses, we validated their potential prognostic relevance by analyzing the TCGA cohort. Notably, losses of 4q34.3-q35.2, 8p21.2-p21.1, and 18q12.2-q23 were linked to increased genomic instability. Loss of 18q12.2-q23 was also related to a higher tumor stage and poor prognosis. Finally, specific genes mapping in these regions, such as PPP2R2A and TPGS2A, emerged as potential biomarkers. Conclusions: Our findings highlight the importance of genomic alterations in ovarian cancer and their impact on tumor progression and patients’ prognosis, offering advance in understanding of the application of numerical aberrations as prognostic ovarian cancer biomarkers.
... Despite several studies aimed at identifying predictive markers for selecting the best candidates for upfront ovarian cancer (OC) surgery, relatively few have focused on identifying markers that can guide the selection of patients who are most suitable for interval cytoreductive surgery (ICS) following neoadjuvant chemotherapy (NACT) [31]. The evaluation of tumor response to chemotherapy has primarily relied on radiological assessments, particularly through CT scans. ...
Objectives: To analyze the role of PCI variation (Δ-PCI) before and after neoadjuvant chemotherapy (NACT) in an interval cytoreductive surgery (ICS) setting with the aim to propose a scoring model for predicting both complete cytoreduction and histopathologic response. Methods: A total of 50 consecutive patients who underwent ICS at our institution were prospectively collected between January-2020 and December-2023. PCI was assessed at exploratory surgery and at ICS. The clinical and histopathological response to NACT was determined by Δ-PCI and CRS. A cut-off value for Δ-PCI, to predict complete cytoreduction, histopathological response, and both together, was identified using a receiver operating characteristic (ROC) curve. The Kaplan–Meier test was used to define disease-free survival (DFS) based on the Δ-PCI cut-off value. Results: Complete cytoreduction was achieved in 82% of patients, with a median Δ-PCI score at ICS of 12 (range 7–29). The remaining 18% had a median Δ-PCI score at IDS of 8 (range 4–11). The best predictor of complete cytoreduction, histopathologic response CRS 3, and both was the Δ-PCI score, with an area under the curve (AUC) of 0.85 (0.73–0.96), 0.98 (0.94–1.00) and 0.88 (0.75–0.96), respectively; ROC curve analysis determined a Δ-PCI cut-off of 8, 17 and 15, respectively. Δ-PCI ≥ 15 as a predictor for both complete cytoreduction and histopathologic response CRS 3 with a median DFS of 26 months for Δ-PCI ≥ 15 versus 12 months for Δ-PCI < 15 (p = 0.02). Conclusions: Δ-PCI (cut-off ≥ 15) is a predictive model for complete cytoreduction, histological response CRS 3, and improved DFS.
... Using graph-based clustering, we first stratified them into 6 major cell populations: epithelial cells, endothelial cells, fibroblasts, T cells (including natural killer (NK) cells), B cells, and myeloid cells (including mast cells, macrophages, dendritic cells (DCs), and monocytes) (Fig. 3b). The composition and expression levels of key cell type markers confirmed the assignments for the cell clusters (PECAM1 and CDH5 for endothelial cells, EPCAM, KRT8 and CDH1 for epithelial cells, DCN, COL1A1, COL1A2 and PDGFRA for fibroblasts, CD3D and CD3E for T cells, CD79A, CD79B, CD19 and MS4A1 for B cells and LYZ, CD14, CD163 and CSF1R for myeloid cells) [26][27][28] (Fig. 3c, d). The labelling of the epithelial cell clusters was further supported by high copy number variation (CNV) scores (Fig. S3b). ...
Background
Epithelial ovarian cancer (EOC) represents the most lethal gynaecological malignancy, yet understanding the connections between its molecular subtypes and their therapeutic implications remains incomplete.
Methods
We conducted mass spectrometry-based proteomics analyses of 154 EOC tumour samples and 29 normal fallopian tubes, and single-cell RNA sequencing (scRNA-seq) analyses of an additional eight EOC tumours to classify proteomic subtypes and assess their cellular ecosystems and clinical significance. The efficacy of identified therapeutic targets was evaluated in patient-derived xenograft (PDX) and orthotopic mouse models.
Results
We identified four proteomic subtypes with distinct clinical relevance: malignant proliferative (C1), immune infiltrating (C2), Fallopian-like (C3) and differentiated (C4) subtypes. C2 subtype was characterized by lymphocyte infiltration, notably an increased presence of GZMK CD8+ T cells and phagocytosis-like MRC+ macrophages. Additionally, we identified CD40 as a specific prognostic factor for C2 subtype. The interaction between CD40+ phagocytosis-like macrophages and CD40RL+ IL17R CD4+ T cells was correlated with a favourable prognosis. Finally, we established a druggable landscape for non-immune EOC patients and verified a TYMP inhibitor as a promising therapeutic strategy.
Conclusions
Our study refines the current immune subtype for EOC, highlighting CD40 agonists as promising therapies for C2 subtype patients and targeting TYMP for non-immune patients.
... Specifically, we performed differential expression analysis using the "rank genes groups" function of Scanpy with a t-test to rank genes after grouping cells based on HoverNet labels. For the cell type analysis with marker genes, we first identified cell type marker genes with a reference single-cell dataset [47] from CellXGene. We selected only cells originating from the left and right ovary. ...
Advancing our understanding of tissue organization and its disruptions in disease remains a key focus in biomedical research. Histological slides stained with Hematoxylin and Eosin (H&E) provide an abundant source of morphological information, while Spatial Transcriptomics (ST) enables detailed, spatially-resolved gene expression (GE) analysis, though at a high cost and with limited clinical accessibility. Predicting GE directly from H&E images using ST as a reference has thus become an attractive objective; however, current patch-based approaches lack single-cell resolution. Here, we present sCellST, a multiple-instance learning model that predicts GE by leveraging cell morphology alone, achieving remarkable predictive accuracy. When tested on a pancreatic ductal adenocarcinoma dataset, sCellST outperformed traditional methods, underscoring the value of basing predictions on single-cell images rather than tissue patches. Additionally, we demonstrate that sCellST can detect subtle morphological differences among cell types by utilizing marker genes in ovarian cancer samples. Our findings suggest that this approach could enable single-cell level GE predictions across large cohorts of H&E-stained slides, providing an innovative means to valorize this abundant resource in biomedical research.
