Evolutionary states and trajectories characterized by distinct pathways stratify patients with ovarian high grade serous carcinoma

DiffInvex identifies evolutionary shifts in driver gene repertoires during tumorigenesis and chemotherapy

Somatic cells can transform into tumors due to mutations, and the tumors further evolve towards increased aggressiveness and therapy resistance. We develop DiffInvex, a framework for identifying changes in selection acting on individual genes in somatic genomes, drawing on an empirical mutation rate baseline derived from non-coding DNA that accounts for shifts in neutral mutagenesis during cancer evolution. We apply DiffInvex to >11,000 somatic whole-genome sequences from ~30 cancer types or healthy tissues, identifying genes where point mutations are under conditional positive or negative selection during exposure to specific chemotherapeutics, suggesting drug resistance mechanisms occurring via point mutation. DiffInvex identifies 11 genes exhibiting treatment-associated selection for different classes of chemotherapies, linking selected mutations in PIK3CA, APC, MAP2K4, SMAD4, STK11 and MAP3K1 with drug exposure. Various gene-chemotherapy associations are further supported by differential functional impact of mutations pre- versus post-therapy, and are also replicated in independent studies. In addition to nominating drug resistance genes, we contrast the genomes of healthy versus cancerous cells of matched human tissues. We identify noncancerous expansion-specific drivers, including NOTCH1 and ARID1A. DiffInvex can also be applied to diverse analyses in cancer evolution to identify changes in driver gene repertoires across time or space.

Uptake of lipids from ascites drives NK cell metabolic dysfunction in ovarian cancer

High-grade serous ovarian cancer (HGSOC) remains an urgent unmet clinical need, with more than 70% of patients presenting with metastatic disease. Many patients develop large volumes of ascites, which promotes metastasis and is associated with poor therapeutic response and survival. Immunotherapy trials have shown limited success, highlighting the need to better understand HGSOC immunology. Here, we analyzed cytotoxic lymphocytes [natural killer (NK), T, and innate T cells] from patients with HGSOC and observed widespread dysfunction across primary and metastatic sites. Although nutrient rich, ascites was immunosuppressive for all lymphocyte subsets. NK cell dysfunction was driven by uptake of polar lipids, with associated dysregulation in lipid storage. Phosphatidylcholine was a key immunosuppressive metabolite, disrupting NK cell membrane order and cytotoxicity. Blocking lipid uptake through SR-B1 protected NK cell antitumor functions in ascites. These findings offer insights into immune suppression in HGSOC and have important implications for the design of future immunotherapies.

Blocking copper transporter protein-dependent drug efflux with albumin-encapsulated Pt(IV) for synergistically enhanced chemo-immunotherapy

Non-small cell lung cancer (NSCLC) represents the most prevalent form of lung cancer, exerting a substantial impact on global health. Cisplatin-based chemotherapy is the standard treatment for NSCLC, but resistance and severe side effects present significant clinical challenges. Recently, novel tetravalent platinum compounds have attracted significant interest. While numerous studies concentrate on their functional modifications and targeted delivery, tumor-induced platinum resistance is frequently overlooked. Previous tetravalent platinum compound demonstrated antitumor activity, yet proved ineffective against cells exhibiting resistance to cisplatin. In order to enhance the efficacy and potential applications of tetravalent platinum in NSCLC, a glutathione (GSH)-responsive albumin nanoquadrivalent platinum (HSA@Pt) have been constructed. In light of previous research into drug conjugation, this study was to develop a combined chemo-immunotherapy approach. The HSA@Pt demonstrated high efficacy and low toxicity, with targeted tumor accumulation. Furthermore, Ammonium Tetrathiomolybdate (TM) has been demonstrated to exert a synergistic inhibitory effect on ATPase Copper Transporting Beta (ATP7B) and Programmed Death Ligand 1 (PD-L1), impede platinum efflux, induce cellular stress, and activate antitumor immunity. The findings suggest HSA@Pt's potential for clinical use and a novel chemo-immunotherapy strategy for NSCLC, enhancing the utility of established drugs through synergistic sensitization.

Jellyfish: integrative visualization of spatio-temporal tumor evolution and clonal dynamics

SUMMARY

Spatial and temporal intra-tumor heterogeneity drives tumor evolution and therapy resistance. Existing visualization tools often fail to capture both dimensions simultaneously. To address this, we developed Jellyfish, a tool that integrates phylogenetic and sample trees into a single plot, providing a holistic view of tumor evolution and capturing both spatial and temporal evolution. Available as a JavaScript library and R package, Jellyfish generates interactive visualizations from tumor phylogeny and clonal composition data. We demonstrate its ability to visualize complex subclonal dynamics using data from ovarian high-grade serous carcinoma.

AVAILABILITY AND IMPLEMENTATION

Jellyfish is freely available with MIT license at https://github.com/HautaniemiLab/jellyfish (JavaScript library) and https://github.com/HautaniemiLab/jellyfisher (R package).

A multiplex single-cell RNA-Seq pharmacotranscriptomics pipeline for drug discovery

The gene-regulatory dynamics governing drug responses in cancer are yet to be fully understood. Here, we report a pipeline capable of producing high-throughput pharmacotranscriptomic profiling through live-cell barcoding using antibody-oligonucleotide conjugates. This pipeline combines drug screening with 96-plex single-cell RNA sequencing. We show the potential of this approach by exploring the heterogeneous transcriptional landscape of primary high-grade serous ovarian cancer (HGSOC) cells after treatment with 45 drugs, with 13 distinct classes of mechanisms of action. A subset of phosphatidylinositol 3-OH kinase (PI3K), protein kinase B (AKT) and mammalian target of rapamycin (mTOR) inhibitors induced the activation of receptor tyrosine kinases, such as the epithelial growth factor receptor (EGFR), and this was mediated by the upregulation of caveolin 1 (CAV1). This drug resistance feedback loop could be mitigated by the synergistic action of agents targeting PI3K-AKT-mTOR and EGFR for HGSOC with CAV1 and EGFR expression. Using this workflow could enable the personalized testing of patient-derived tumor samples at single-cell resolution.

Molecular and functional profiling of primary normal ovarian cells defines insights into cancer development and drug responses

Patients with ovarian cancer, especially the high-grade serous ovarian cancer (HGSOC) subtype, face poor prognosis due to late diagnosis and treatment resistance. Owing to the high heterogeneity of HGSOC, identifying the origin of the disease and optimal treatments is difficult. Here, we characterized two primary immortalized human ovarian cell lines, human ovarian surface epithelium (HOSE)1C and HOSE2C, comparing their molecular profiling with representative HGSOC cells. We identified molecular features associated with normal and malignant phenotype of ovarian cells by applying single-cell transcriptomics, high-content image-based cell painting, and high-throughput drug testing. Our findings reveal distinct transcriptomic and morphological profiles for the two HOSEs, with a stromal phenotype. Moreover, their responses to the tumor microenvironment differ, exemplified by STAT1 and GREM1 upregulation in HOSE1C and HOSE2C, respectively. We identified selective activation of ERK/MEK targeted inhibitors in cancer cells compared to HOSEs. This study offers insights into the normal and malignant ovarian cells, shedding light on cancer development and drug responses.

Immune-molecular interactions in high-grade serous ovarian cancer distinguish long-term survivors

The approach and efficacy of treatments for high-grade serous carcinoma (HGSC) of the ovary have changed little in decades. Although numerous studies demonstrated immune infiltration as frequent and prognostically beneficial, clinical trials of immunotherapies have generated benefit in fewer than 15% of patients. In this issue of the JCI, Nelson and colleagues compiled 1,233 HGSC samples from patients across four continents and compared the molecular and immunologic features that associate with long-term survival (greater than 10 years). Diversity among HGSC tumors is well defined, but this study explored the combined influence of immunologic and molecular features. Long-term survivors harbored tumors with high epithelial content and overrepresentation of the C4/differentiated molecular signature, with cytotoxic T and B cells infiltrating to the tumor epithelium and stroma, respectively. These findings highlight features that might underly poor responsiveness to existing immunotherapies of most HGSC tumors and considerations for the design of future, more precise treatments for HGSC.

Chemotherapy induces myeloid-driven spatially confined T cell exhaustion in ovarian cancer

Anti-tumor immunity is crucial for high-grade serous ovarian cancer (HGSC) prognosis, yet its adaptation upon standard chemotherapy remains poorly understood. Here, we conduct spatial and molecular characterization of 117 HGSC samples collected before and after chemotherapy. Our single-cell and spatial analyses reveal increasingly versatile immune cell states forming spatiotemporally dynamic microcommunities. We describe Myelonets, networks of interconnected myeloid cells that contribute to CD8+ T cell exhaustion post-chemotherapy and show that M1/M2 polarization at the tumor-stroma interface is associated with CD8+ T cell exhaustion and exclusion, correlating with poor chemoresponse. Single-cell and spatial transcriptomics reveal prominent myeloid-T cell interactions via NECTIN2-TIGIT induced by chemotherapy. Targeting these interactions using a functional patient-derived immuno-oncology platform demonstrates that high NECTIN2-TIGIT signaling in matched tumors predicts responses to immune checkpoint blockade. Our discovery of clinically relevant myeloid-driven spatial T cell exhaustion unlocks immunotherapeutic strategies to unleash CD8+ T cell-mediated anti-tumor immunity in HGSC.

Patient-Representative Cell Line Models in a Heterogeneous Disease: Comparison of Signaling Transduction Pathway Activity Between Ovarian Cancer Cell Lines and Ovarian Cancer

Background/Objectives: Advances in treatment options have barely improved the prognosis of ovarian carcinoma (OC) in recent decades. The inherent heterogeneity of OC underlies challenges in treatment (development) and patient stratification. One hurdle for effective drug development is the lack of patient-representative disease models available for preclinical drug research. Based on quantitative measurement of signal transduction pathway (STP) activity in cell lines, we aimed to identify cell line models that better mirror the different clinical subtypes of OC. Methods: The activity of seven oncogenic STPs (signal transduction pathways) was determined by previously described STP technology using transcriptome data from untreated OC cell lines available in the GEO database. Hierarchal clustering of cell lines was performed based on STP profiles. Associations between cell line histology (original tumor), cluster, and STP profiles were analyzed. Subsequently, STP profiles of clinical OC tissue samples were matched with OC cell lines. Results: Cell line search resulted in 80 cell line transcriptome data from 23 GEO datasets, with 51 unique cell lines. These cell lines were derived from eight different histological OC subtypes (as determined for the primary tumor). Clustering revealed seven clusters with unique STP profiles. When borderline tumors (n = 6), high-grade serous (n = 51) and low-grade (n = 31) OC were matched with cell lines, twelve different cell lines were identified as potentially patient-representative OC cell line models. Conclusions: Based on STP activity, we identified twelve different cell lines that were the most representative of the common subtypes of OC. These findings are important to improve drug development for OC.

Exploration of organoids in ovarian cancer: From basic research to clinical translation

Ovarian cancer is a highly heterogeneous tumor with a poor prognosis. The lack of reliable and efficient research models that can accurately mimic heterogeneity has impeded in-depth investigations and hindered the clinical translation of research findings in ovarian cancer. Organoid models have emerged as a promising in vitro approach, demonstrating remarkable fidelity to the histological, molecular, genomic, and transcriptomic features of their tissues of origin. In recent years, organoids have contributed to advancing our understanding of ovarian cancer initiation, metastasis, and drug resistance mechanisms, as well as facilitating clinical screening of effective therapeutic agents. The establishment of high-throughput organoid culture systems, coupled with cutting-edge technologies such as organ-on-a-chip, genetic engineering, and 3D printing, has tremendous potential for accelerating ovarian cancer research translation. In this review, we present a comprehensive overview of the latest exploration of organoids in basic ovarian cancer research and clinical translation. Furthermore, we discuss the prospects and challenges associated with the use of organoids and related novel technologies in the context of ovarian cancer. This review provides insights into the application of organoids in ovarian cancer.

Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones

Intratumoral cellular heterogeneity necessitates multi-targeting therapies for improved clinical benefits in advanced malignancies. However, systematic identification of patient-specific treatments that selectively co-inhibit cancerous cell populations poses a combinatorial challenge, since the number of possible drug-dose combinations vastly exceeds what could be tested in patient cells. Here, we describe a machine learning approach, scTherapy, which leverages single-cell transcriptomic profiles to prioritize multi-targeting treatment options for individual patients with hematological cancers or solid tumors. Patient-specific treatments reveal a wide spectrum of co-inhibitors of multiple biological pathways predicted for primary cells from heterogenous cohorts of patients with acute myeloid leukemia and high-grade serous ovarian carcinoma, each with unique resistance patterns and synergy mechanisms. Experimental validations confirm that 96% of the multi-targeting treatments exhibit selective efficacy or synergy, and 83% demonstrate low toxicity to normal cells, highlighting their potential for therapeutic efficacy and safety. In a pan-cancer analysis across five cancer types, 25% of the predicted treatments are shared among the patients of the same tumor type, while 19% of the treatments are patient-specific. Our approach provides a widely-applicable strategy to identify personalized treatment regimens that selectively co-inhibit malignant cells and avoid inhibition of non-cancerous cells, thereby increasing their likelihood for clinical success.

Exploring evolutionary trajectories in ovarian cancer patients by longitudinal analysis of ctDNA

OBJECTIVES

We analysed whether temporal heterogeneity of ctDNA encodes evolutionary patterns in ovarian cancer.

METHODS

Targeted sequencing of 275 cancer-associated genes was performed in a primary tumor biopsy and in ctDNA of six longitudinal plasma samples from 15 patients, using the Illumina platform.

RESULTS

While there was low overall concordance between the mutational spectrum of the primary tumor biopsies vs. ctDNA, TP53 variants were the most commonly shared somatic alterations. Up to three variant clusters were detected in each tumor biopsy, likely representing predominant clones of the primary tumor, most of them harbouring a TP53 variant. By tracing these clusters in ctDNA, we propose that liquid biopsy may allow to assess the contribution of ancestral clones of the tumor to relapsed abdominal masses, revealing two evolutionary patterns. In pattern#1, clusters detected in the primary tumor biopsy were likely relapse seeding clones, as they contributed a major share to ctDNA at relapse. In pattern#2, similar clusters were present in tumors and ctDNA; however, they were entirely cleared from liquid biopsy after chemotherapy and were undetectable at relapse. ctDNA private variants were present among both patterns, with some of them mirroring subclonal expansions after chemotherapy.

CONCLUSIONS

We demonstrate that tracing the temporal heterogeneity of ctDNA, even below exome scale resolution, deciphers evolutionary trajectories in ovarian cancer. Furthermore, we describe two evolutionary patterns that may help to identify relapse seeding clones for targeted therapy.

Autophagy unrelated transcriptional mechanisms of hydroxychloroquine resistance revealed by integrated multi-omics of evolved cancer cells

Hydroxychloroquine (HCQ) and chloroquine are repurposed drugs known to disrupt autophagy, a molecular recycling pathway essential for tumor cell survival, chemotherapeutic resistance, and stemness. We pursued a multi-omic strategy in OVCAR3 ovarian cancer and CCL218 colorectal cancer cells. Two genome-scale screens were performed. In the forward genetic screen, cell populations were passaged for 15 drug pulse-chases with HCQ or vehicle control. Evolved cells were collected and processed for bulk RNA-seq, exome-seq, and single-cell RNA-seq (scRNA-seq). In the reverse genetic screen, a pooled CRISPR-Cas9 library was used in cells over three pulse-chases of HCQ or vehicle control treatments. HCQ evolved cells displayed remarkably few mutational differences, but substantial transcriptional differences. Transcriptomes revealed multiple pathways associated with resistance to HCQ, including upregulation of glycolysis, exocytosis, and chromosome condensation/segregation, or downregulation of translation and apoptosis. The Cas9 screen identified only one autophagy gene. Chromosome condensation and segregation were confirmed to be disrupted by HCQ in live cells and organelle-free in vitro extracts. Transcriptional plasticity was the primary mechanism by which cells evolved resistance to HCQ. Neither autophagy nor the lysosome were substantive hits. Our analysis may serve as a model for how to better position repurposed drugs in oncology.

Single-cell RNA sequencing reveals the change in cytotoxic NK/T cells, epithelial cells and myeloid cells of the tumor microenvironment of high-grade serous ovarian carcinoma

BACKGROUND

The heterogeneity of high-grade serous ovarian carcinoma (HGSOC) has hindered the clinical treatment, and our current study aims to characterize the change in tumor microenvironment (TME) with the progression of HGSOC via single cell RNA sequencing (scRNA-seq).

METHODS

The single-cell landscape in HGSOC was downloaded from the dataset GSE184880, which included 7 HGSOC and 5 normal samples and then applied for the filtering and annotation of cell clusters. The differentially expressed marker genes in these clusters were analyzed via "FindAllMarker" function in Seurat package and the functional enrichment analyses were implemented using clusterProflier package. Finally, the CellChat package was applied for the cell-cell communication analysis. Cellular experimental were determined Real-time Reverse Transcription Polymerase Chain Reaction (RT-qPCR).

RESULTS

45,448 single cells were categorized into 10 cell clusters. The proportion of NK/T cells (49.5%), epithelial cells (15.3%) and myeloid cells (14%) was higher in the HGSOC samples. The heterogeneity and different enriched pathways of epithelial cells have been revealed with the progression of HGSOC from early to late stage, concurrent with the reduced activity of cytotoxic NK/T cells and the decreased capabilities of recruiting immune cells and presenting antigens in macrophages. Besides, the cell-cell communication analysis has revealed a strong communication of CXCL and CCL signal between M1 macrophages and cytotoxic NK/T cells in early stage of HGSOC. Moreover, RT-qPCR indicated that CCL4/5 and CCR1/5 levels were upregulated in tumor cell SK-OV-3.

CONCLUSION

The investigation using scRNA-seq has depicted the change in cytotoxic NK/T cells, epithelial cells and myeloid cells of the TME of HGSOC, which may provide another insight into the specific mechanisms underlying the progression of HGSOC.

Exploring the Potential of Natural Killer Cell-Based Immunotherapy in Targeting High-Grade Serous Ovarian Carcinomas

High-grade serous ovarian cancers (HGSOCs) likely consist of poorly differentiated stem-like cells (PDSLCs) and differentiated tumor cells. Conventional therapeutics are incapable of completely eradicating PDSLCs, contributing to disease progression and tumor relapse. Primary NK cells are known to effectively lyse PDSLCs, but they exhibit low or minimal cytotoxic potential against well-differentiated tumors. We have introduced and discussed the characteristics of super-charged NK (sNK) cells in this review. sNK cells, in comparison to primary NK cells, exhibit a significantly higher capability for the direct killing of both PDSLCs and well-differentiated tumors. In addition, sNK cells secrete significantly higher levels of cytokines, especially those known to induce the differentiation of tumors. In addition, we propose that a combination of sNK and chemotherapy could be one of the most effective strategies to eliminate the heterogeneous population of ovarian tumors; sNK cells can lyse both PDSLCs and well-differentiated tumors, induce the differentiation of PDSLCs, and could be used in combination with chemotherapy to target both well-differentiated and NK-induced differentiated tumors.

PIK3R1 fusion drives chemoresistance in ovarian cancer by activating ERK1/2 and inducing rod and ring-like structures

Gene fusions are common in high-grade serous ovarian cancer (HGSC). Such genetic lesions may promote tumorigenesis, but the pathogenic mechanisms are currently poorly understood. Here, we investigated the role of a PIK3R1-CCDC178 fusion identified from a patient with advanced HGSC. We show that the fusion induces HGSC cell migration by regulating ERK1/2 and increases resistance to platinum treatment. Platinum resistance was associated with rod and ring-like cellular structure formation. These structures contained, in addition to the fusion protein, CIN85, a key regulator of PI3K-AKT-mTOR signaling. Our data suggest that the fusion-driven structure formation induces a previously unrecognized cell survival and resistance mechanism, which depends on ERK1/2-activation.

Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

To uncover the intricate, chemotherapy-induced spatiotemporal remodeling of the tumor microenvironment, we conducted integrative spatial and molecular characterization of 97 high-grade serous ovarian cancer (HGSC) samples collected before and after chemotherapy. Using single-cell and spatial analyses, we identify increasingly versatile immune cell states, which form spatiotemporally dynamic microcommunities at the tumor-stroma interface. We demonstrate that chemotherapy triggers spatial redistribution and exhaustion of CD8+ T cells due to prolonged antigen presentation by macrophages, both within interconnected myeloid networks termed "Myelonets" and at the tumor stroma interface. Single-cell and spatial transcriptomics identifies prominent TIGIT-NECTIN2 ligand-receptor interactions induced by chemotherapy. Using a functional patient-derived immuno-oncology platform, we show that CD8+T-cell activity can be boosted by combining immune checkpoint blockade with chemotherapy. Our discovery of chemotherapy-induced myeloid-driven spatial T-cell exhaustion paves the way for novel immunotherapeutic strategies to unleash CD8+ T-cell-mediated anti-tumor immunity in HGSC.

Locus-specific LINE-1 expression in clinical ovarian cancer specimens at the single-cell level

Long interspersed nuclear elements (LINE-1s/L1s) are a group of retrotransposons that can copy themselves within a genome. In humans, it is the most successful transposon in nucleotide content. L1 expression is generally mild in normal human tissues, but the activity has been shown to increase significantly in many cancers. Few studies have examined L1 expression at single-cell resolution, thus it is undetermined whether L1 reactivation occurs solely in malignant cells within tumors. One of the cancer types with frequent L1 activity is high-grade serous ovarian carcinoma (HGSOC). Here, we identified locus-specific L1 expression with 3' single-cell RNA sequencing in pre- and post-chemotherapy HGSOC sample pairs from 11 patients, and in fallopian tube samples from five healthy women. Although L1 expression quantification with the chosen technique was challenging due to the repetitive nature of the element, we found evidence of L1 expression primarily in cancer cells, but also in other cell types, e.g. cancer-associated fibroblasts. The expression levels were similar in samples taken before and after neoadjuvant chemotherapy, indicating that L1 transcriptional activity was unaffected by clinical platinum-taxane treatment. Furthermore, L1 activity was negatively associated with the expression of MYC target genes, a finding that supports earlier literature of MYC being an L1 suppressor.

Evolutionary mode and timing of dissemination of high-grade serous carcinomas

Dissemination within the peritoneal cavity is a main determinant of poor patient outcomes from high-grade serous carcinomas (HGSCs). The dissemination process is poorly understood from a cancer evolutionary perspective. We reconstructed the evolutionary trajectories across a median of 5 tumor sites and regions from each of 23 patients based on deep whole-exome sequencing. Polyclonal cancer origin was detected in 1 patient. Ovarian tumors had more complex subclonal architectures than other intraperitoneal tumors in each patient, which indicated that tumors developed earlier in the ovaries. Three common modes of dissemination were identified, including monoclonal or polyclonal dissemination of monophyletic (linear) or polyphyletic (branched) subclones. Mutation profiles of initial or disseminated clones varied greatly among cancers, but recurrent mutations were found in 7 cancer-critical genes, including TP53, BRCA1, BRCA2, and DNMT3A, and in the PI3K/AKT1 pathway. Disseminated clones developed late in the evolutionary trajectory models of most cancers, in particular in cancers with DNA damage repair deficiency. Polyclonal dissemination was predicted to occur predominantly as a single and rapid wave, but chemotherapy exposure was associated with higher genomic diversity of disseminated clones. In conclusion, we described three common evolutionary dissemination modes across HGSCs and proposed factors associated with dissemination diversity.

HRD related signature 3 predicts clinical outcome in advanced tubo-ovarian high-grade serous carcinoma

OBJECTIVES

We evaluated usability of single base substitution signature 3 (Sig3) as a biomarker for homologous recombination deficiency (HRD) in tubo-ovarian high-grade serous carcinoma (HGSC).

MATERIALS AND METHODS

This prospective observational trial includes 165 patients with advanced HGSC. Fresh tissue samples (n = 456) from multiple intra-abdominal areas at diagnosis and after neoadjuvant chemotherapy (NACT) were collected for whole-genome sequencing. Sig3 was assessed by fitting samples independently with COSMIC v3.2 reference signatures. An HR scar assay was applied for comparison. Progression-free survival (PFS) and overall survival (OS) were studied using Kaplan-Meier and Cox regression analysis.

RESULTS

Sig3 has a bimodal distribution, eliminating the need for an arbitrary cutoff typical in HR scar tests. Sig3 could be assessed from samples with low (10%) cancer cell proportion and was consistent between multiple samples and stable during NACT. At diagnosis, 74 (45%) patients were HRD (Sig3+), while 91 (55%) were HR proficient (HRP, Sig3-). Sig3+ patients had longer PFS and OS than Sig3- patients (22 vs. 13 months and 51 vs. 34 months respectively, both p < 0.001). Sig3 successfully distinguished the poor prognostic HRP group among BRCAwt patients (PFS 19 months for Sig3+ and 13 months for Sig3- patients, p < 0.001). However, Sig3 at diagnosis did not predict chemoresponse anymore in the first relapse. The patient-level concordance between Sig3 and HR scar assay was 87%, and patients with HRD according to both tests had the longest median PFS.

CONCLUSIONS

Sig3 is a prognostic marker in advanced HGSC and useful tool in patient stratification for HRD.

Quantification of cell death and proliferation of patient-derived ovarian cancer organoids through 3D imaging and image analysis

Patient-derived organoids (PDOs) are ideal ex vivo model systems to study cancer progression and drug resistance mechanisms. Here, we present a protocol for measuring drug efficacy in three-dimensional (3D) high-grade serous ovarian cancer PDO cultures through quantification of cytotoxicity using propidium iodide incorporation in dead cells. We also provide detailed steps to analyze proliferation of PDOs using the Ki67 biomarker. We describe steps for sample processing, immunofluorescent staining, high-throughput confocal imaging, and image-based quantification for 3D cultures. For complete details on the use and execution of this protocol, please refer to Lahtinen et al. (2023).1.

Circulating tumor DNA-based copy-number profiles enable monitoring treatment effects during therapy in high-grade serous carcinoma

Circulating tumor DNA (ctDNA) analysis has emerged as a promising tool for detecting and profiling longitudinal genomics changes in cancer. While copy-number alterations (CNAs) play a major role in cancers, treatment effect monitoring using copy-number profiles has received limited attention as compared to mutations. A major reason for this is the insensitivity of CNA analysis for the real-life tumor-fraction ctDNA samples. We performed copy-number analysis on 152 plasma samples obtained from 29 patients with high-grade serous ovarian cancer (HGSC) using a sequencing panel targeting over 500 genes. Twenty-one patients had temporally matched tissue and plasma sample pairs, which enabled assessing concordance with tissues sequenced with the same panel or whole-genome sequencing and to evaluate sensitivity. Our approach could detect concordant CNA profiles in most plasma samples with as low as 5% tumor content and highly amplified regions in samples with ∼1% of tumor content. Longitudinal profiles showed changes in the CNA profiles in seven out of 11 patients with high tumor-content plasma samples at relapse. These changes included focal acquired or lost copy-numbers, even though most of the genome remained stable. Two patients displayed major copy-number profile changes during therapy. Our analysis revealed ctDNA-detectable subclonal selection resulting from both surgical operations and chemotherapy. Overall, longitudinal ctDNA data showed acquired and diminished CNAs at relapse when compared to pre-treatment samples. These results highlight the importance of genomic profiling during treatment as well as underline the usability of ctDNA.

Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers

Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.

H&E image analysis pipeline for quantifying morphological features

Detecting cell types from histopathological images is essential for various digital pathology applications. However, large number of cells in whole-slide images (WSIs) necessitates automated analysis pipelines for efficient cell type detection. Herein, we present hematoxylin and eosin (H&E) Image Processing pipeline (HEIP) for automatied analysis of scanned H&E-stained slides. HEIP is a flexible and modular open-source software that performs preprocessing, instance segmentation, and nuclei feature extraction. To evaluate the performance of HEIP, we applied it to extract cell types from ovarian high-grade serous carcinoma (HGSC) patient WSIs. HEIP showed high precision in instance segmentation, particularly for neoplastic and epithelial cells. We also show that there is a significant correlation between genomic ploidy values and morphological features, such as major axis of the nucleus.

ROR1-STAT3 signaling contributes to ovarian cancer intra-tumor heterogeneity

Wnt pathway dysregulation through genetic and non-genetic alterations occurs in multiple cancers, including ovarian cancer (OC). The aberrant expression of the non-canonical Wnt signaling receptor ROR1 is thought to contribute to OC progression and drug resistance. However, the key molecular events mediated by ROR1 that are involved in OC tumorigenesis are not fully understood. Here, we show that ROR1 expression is enhanced by neoadjuvant chemotherapy, and Wnt5a binding to ROR1 can induce oncogenic signaling via AKT/ERK/STAT3 activation in OC cells. Proteomics analysis of isogenic ROR1-knockdown OC cells identified STAT3 as a downstream effector of ROR1 signaling. Transcriptomics analysis of clinical samples (n = 125) revealed that ROR1 and STAT3 are expressed at higher levels in stromal cells than in epithelial cancer cells of OC tumors, and these findings were corroborated by multiplex immunohistochemistry (mIHC) analysis of an independent OC cohort (n = 11). Our results show that ROR1 and its downstream STAT3 are co-expressed in epithelial as well as stromal cells of OC tumors, including cancer-associated fibroblasts or CAFs. Our data provides the framework to expand the clinical utility of ROR1 as a therapeutic target to overcome OC progression.

Decoding evolutionary trajectories of ovarian cancer metastasis

The genetic changes during high-grade serous ovarian cancer metastasis have largely remained a mystery. Lahtinen et al. show that ovarian cancer metastasizes along three different evolutionary states that have distinct mutations and signaling pathways, potentially allowing the identification of targeted treatments.