Probabilistic pathway-based multimodal factor analysis.

MOTIVATION: Multimodal profiling strategies promise to produce more informative insights into biomedical cohorts via the integration of the information each modality contributes. To perform this integration, however, the development of novel analytical strategies is needed. Multimodal profiling strategies often come at the expense of lower sample numbers, which can challenge methods to uncover shared signals across a cohort. Thus, factor analysis approaches are commonly used for the analysis of high-dimensional data in molecular biology, however, they typically do not yield representations that are directly interpretable, whereas many research questions often center around the analysis of pathways associated with specific observations. RESULTS: We develop PathFA, a novel approach for multimodal factor analysis over the space of pathways. PathFA produces integrative and interpretable views across multimodal profiling technologies, which allow for the derivation of concrete hypotheses. PathFA combines a pathway-learning approach with integrative multimodal capability under a Bayesian procedure that is efficient, hyper-parameter free, and able to automatically infer observation noise from the data. We demonstrate strong performance on small sample sizes within our simulation framework and on matched proteomics and transcriptomics profiles from real tumor samples taken from the Swiss Tumor Profiler consortium. On a subcohort of melanoma patients, PathFA recovers pathway activity that has been independently associated with poor outcome. We further demonstrate the ability of this approach to identify pathways associated with the presence of specific cell-types as well as tumor heterogeneity. Our results show that we capture known biology, making it well suited for analyzing multimodal sample cohorts. AVAILABILITY AND IMPLEMENTATION: The tool is implemented in python and available at https://github.com/ratschlab/path-fa.

Diagnosing and staging epithelial ovarian cancer by serum glycoproteomic profiling.

BACKGROUND: There is a need for diagnostic tests for screening, triaging and staging of epithelial ovarian cancer (EOC). Glycoproteomics of blood samples has shown promise for biomarker discovery. METHODS: We applied glycoproteomics to serum of people with EOC or benign pelvic masses and healthy controls. A total of 653 analytes were quantified and assessed in multivariable models, which were tested in an independent cohort. Additionally, we analyzed glycosylation patterns in serum markers and in tissues. RESULTS: We identified a biomarker panel that distinguished benign lesions from EOC with sensitivity and specificity of 83.5% and 90.1% in the training set, and of 86.7 and 86.7% in the test set, respectively. ROC analysis demonstrated strong performance across a range of cutoffs. Fucosylated multi-antennary glycopeptide markers were higher in late-stage than in early-stage EOC. A comparable pattern was found in late-stage EOC tissues. CONCLUSIONS: Blood glycopeptide biomarkers have the potential to distinguish benign from malignant pelvic masses, and early- from late-stage EOC. Glycosylation of circulating and tumor tissue proteins may be related. This study supports the hypothesis that blood glycoproteomic profiling can be used for EOC diagnosis and staging and it warrants further clinical evaluation.

Highly Sensitive Spatial Glycomics at Near-Cellular Resolution by On-Slide Derivatization and Mass Spectrometry Imaging.

Glycans on proteins and lipids play important roles in maturation and cellular interactions, contributing to a variety of biological processes. Aberrant glycosylation has been associated with various human diseases including cancer; however, elucidating the distribution and heterogeneity of glycans in complex tissue samples remains a major challenge. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is routinely used to analyze the spatial distribution of a variety of molecules including N-glycans directly from tissue surfaces. Sialic acids are nine carbon acidic sugars that often exist as the terminal sugars of glycans and are inherently difficult to analyze using MALDI-MSI due to their instability prone to in- and postsource decay. Here, we report on a rapid and robust method for stabilizing sialic acid on N-glycans in FFPE tissue sections. The established method derivatizes and identifies the spatial distribution of α2,3- and α2,6-linked sialic acids through complete methylamidation using methylamine and PyAOP ((7-azabenzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate). Our in situ approach increases the glycans detected and enhances the coverage of sialylated species. Using this streamlined, sensitive, and robust workflow, we rapidly characterize and spatially localize N-glycans in human tumor tissue sections. Additionally, we demonstrate this method's applicability in imaging mammalian cell suspensions directly on slides, achieving cellular resolution with minimal sample processing and cell numbers. This workflow reveals the cellular locations of distinct N-glycan species, shedding light on the biological and clinical significance of these biomolecules in human diseases.

Identification of potential classes of glycoligands mediating dynamic endothelial adhesion of human tumor cells.

One critical step of metastasis formation is the extravasation of circulating tumor cells from the bloodstream. This process requires the dynamic interaction of cell adhesion molecules like E-selectin on endothelial cells with carbohydrate ligands on tumor cells. To characterize these glycans in a comprehensible approach, the rolling, tethering, and firm adhesion of nine human tumor cell lines on human umbilical vein endothelial cells was analyzed using laminar flow adhesion assays. The tumor cell lines were grouped into three subsets by their canonical E-selectin ligand status (sialyl-Lewis A and X +/+, -/+, -/-) and their adhesiveness was compared after enzymatic, pharmacologic, chemical treatment or antibody blockade of the tumor cells or endothelial cells, respectively. Tumor cells were also screened regarding their glycosyltransferase expression profile. We found that although E-selectin and terminal α2,3-sialic acid largely determined firm adhesion, adhesive events did not exclusively depend on the presence of sialyl-Lewis A and/or sialyl-Lewis X. Nevertheless, two of the three sialyl-Lewis A/X-/- tumor cells additionally or fully depended on vascular cell adhesion molecule-1 for firm adhesion. The significance of O-GalNAc- and N-glycans for adhesion varied remarkably among the tumor cells. The sialyl-Lewis A/X+/+ subset showed glycoprotein-independent adhesion, suggesting a role of glycolipids as well. All sialyl-Lewis A/X-/- tumor cells lacked FUT3 and FUT7 expression as opposed to sialyl-Lewis A/X+/+ or -/+ cell lines. In summary, the glycans on tumor cells mediating endothelial adhesion are not as much restricted to sialyl-Lewis A /X as previously assumed. The present study specifically suggests α2,3-linked sialic acid, O-GalNAc glycans, glycosphingolipids, and FUT3/FUT7 products as promising targets for future studies.

Mucins and Truncated O-Glycans Unveil Phenotypic Discrepancies between Serous Ovarian Cancer Cell Lines and Primary Tumours.

Optimal research results rely on the selection of cellular models capable of recapitulating the characteristics of primary tumours from which they originate. The expression of mucins (MUC16 and MUC1) and truncated O-glycans (Tn, STn and T) represents a characteristic footprint of serous ovarian carcinomas (SOCs). Therefore, selecting ovarian cancer (OVCA) cell lines that reflect this phenotype is crucial to explore the putative biological role of these biomarkers in the SOC setting. Here, we investigated a panel of OVCA cell lines commonly used as SOC models, and tested whether, when cultured in 2D and 3D conditions, these recapitulate the mucin and O-glycan expression profiles of SOCs. We further explored the role of truncating the O-glycosylation capacity in OVCAR3 cells through knockout of the COSMC chaperone, using in vitro and in vivo assays. We found that the majority of OVCA cell lines of serous origin do not share the mucin and truncated O-glycan footprint of SOCs, although 3D cultures showed a higher resemblance. We also found that genetic truncation of the O-glycosylation capacity of OVCAR3 cells did not enhance oncogenic features either in vitro or in vivo. This study underscores the importance of well-characterized cellular models to study specific features of ovarian cancer.

MELK expression in ovarian cancer correlates with poor outcome and its inhibition by OTSSP167 abrogates proliferation and viability of ovarian cancer cells.

OBJECTIVE: Maternal embryonic leucine-zipper kinase (MELK) shows oncogenic properties in basal-like breast cancer, a cancer subtype sharing common molecular features with high-grade serous ovarian cancer. We examined the potential of MELK as a molecular and pharmacological target for treatment of epithelial ovarian cancer (EOC). METHODS/MATERIALS: Bioinformatic analysis was performed on nine OC transcriptomic data sets totaling 1241 patients. Effects of MELK depletion by shRNA or inhibition by OTSSP167 in cell lines were assessed by colony formation and MTT (proliferation) assays, Western blotting (apoptosis), and flow cytometry (cell cycle analysis). RESULTS: Elevated MELK expression was correlated with histological grading (n=6 data sets, p<0.05) and progression-free survival (HR 5.73, p<0.01) in OC patients and elevated MELK expression in other cancers with disease-free survival (n=3495, HR 1.071, p<0.001). Inhibition or depletion of MELK reduced cell proliferation and anchorage-dependent and -independent growth in various OC cell lines through a G2/M cell cycle arrest, eventually resulting in apoptosis. OTSSP167 retained its cytotoxicity in Cisplatin- and Paclitaxel-resistant IGROV1 and TYK-nu OC cells and sensitized OVCAR8 cells to Carboplatin but not Paclitaxel. CONCLUSION: MELK inhibition by OTSSP167 may thus present a strategy to treat patients with aggressive, progressive, and recurrent ovarian cancer.

Specific glycosylation of membrane proteins in epithelial ovarian cancer cell lines: glycan structures reflect gene expression and DNA methylation status.

Epithelial ovarian cancer is the fifth most common cause of cancer in women worldwide bearing the highest mortality rate among all gynecological cancers. Cell membrane glycans mediate various cellular processes such as cell signaling and become altered during carcinogenesis. The extent to which glycosylation changes are influenced by aberrant regulation of gene expression is nearly unknown for ovarian cancer and remains crucial in understanding the development and progression of this disease. To address this effect, we analyzed the membrane glycosylation of non-cancerous ovarian surface epithelial (HOSE 6.3 and HOSE 17.1) and serous ovarian cancer cell lines (SKOV 3, IGROV1, A2780, and OVCAR 3), the most common histotype among epithelial ovarian cancers. N-glycans were released from membrane glycoproteins by PNGase F and analyzed using nano-liquid chromatography on porous graphitized carbon and negative-ion electrospray ionization mass spectrometry (ESI-MS). Glycan structures were characterized based on their molecular masses and tandem MS fragmentation patterns. We identified characteristic glycan features that were unique to the ovarian cancer membrane proteins, namely the "bisecting N-acetyl-glucosamine" type N-glycans, increased levels of α 2-6 sialylated N-glycans and "N,N'-diacetyl-lactosamine" type N-glycans. These N-glycan changes were verified by examining gene transcript levels of the enzymes specific for their synthesis (MGAT3, ST6GAL1, and B4GALNT3) using qRT-PCR. We further evaluated the potential epigenetic influence on MGAT3 expression by treating the cell lines with 5-azacytidine, a DNA methylation inhibitor. For the first time, we provide evidence that MGAT3 expression may be epigenetically regulated by DNA hypomethylation, leading to the synthesis of the unique "bisecting GlcNAc" type N-glycans on the membrane proteins of ovarian cancer cells. Linking the observation of specific N-glycan substructures and their complex association with epigenetic programming of their associated synthetic enzymes in ovarian cancer could potentially be used for the development of novel anti-glycan drug targets and clinical diagnostic tools.

Glucosylceramide synthase inhibitors differentially affect expression of glycosphingolipids.

Glucosylceramide synthase (GCS) catalyzes the first committed step in the biosynthesis of glucosylceramide (GlcCer)-related glycosphingolipids (GSLs). Although inhibitors of GCS, PPMP and PDMP have been widely used to elucidate their biological function and relevance, our comprehensive literature review revealed that the available data are ambiguous. We therefore investigated whether and to what extent GCS inhibitors affect the expression of lactosylceramide (LacCer), neolacto (nLc4 and P1), ganglio (GM1 and GD3) and globo (Gb3 and SSEA3) series GSLs in a panel of human cancer cell lines using flow cytometry, a commonly applied method investigating cell-surface GSLs after GCS inhibition. Their cell-surface GSL expression considerably varied among cell lines and more importantly, sublethal concentrations (IC10) of both inhibitors preferentially and significantly reduced the expression of Gb3 in the cancer cell lines IGROV1, BG1, HT29 and T47D, whereas SSEA3 was only reduced in BG1. Unexpectedly, the neolacto and ganglio series was not affected. LacCer, the precursor of all GlcCer-related GSL, was significantly reduced only in BG1 cells treated with PPMP. Future research questions addressing particular GSLs require careful consideration; our results indicate that the extent to which there is a decrease in the expression of one or more particular GSLs is dependent on the cell line under investigation, the type of GCS inhibitor and exposure duration.

A platform for the structural characterization of glycans enzymatically released from glycosphingolipids extracted from tissue and cells.

RATIONALE: Glycosphingolipids (GSLs) constitute a highly diverse class of glyco-conjugates which are involved in many aspects of cell membrane function and disease. The isolation, detection and structural characterization of the carbohydrate (glycan) component of GSLs are particularly challenging given their structural heterogeneity and thus rely on the development of sensitive, analytical technologies. METHODS: Neutral and acidic GSL standards were immobilized onto polyvinylidene difluoride (PVDF) membranes and glycans were enzymatically released using endoglycoceramidase II (EGCase II), separated by porous graphitized carbon (PGC) liquid chromatography and structurally characterized by negative ion mode electrospray ionization tandem mass spectrometry (PGC-LC/ESI-MS/MS). This approach was then employed for GSLs isolated from 100 mg of serous and endometrioid cancer tissue and from cell line (10(7) cells) samples. RESULTS: Glycans were released from GSL standards comprising of ganglio-, asialo-ganglio- and the relatively resistant globo-series glycans, using as little as 1 mU of enzyme and 2 µg of GSL. The platform of analysis was then applied to GSLs isolated from tissue and cell line samples and the released isomeric and isobaric glycan structures were chromatographically resolved on PGC and characterized by comparison with the MS(2) fragment ion spectra of the glycan standards and by application of known structural MS(2) fragment ions. This approach identified several (neo-)lacto-, globo- and ganglio-series glycans and facilitated the discrimination of isomeric structures containing Lewis A, H type 1 and type 2 blood group antigens and sialyl-tetraosylceramides. CONCLUSION: We describe a relatively simple, detergent-free, enzymatic release of glycans from PVDF-immobilized GSLs, followed by the detailed structural analysis afforded by PGC-LC-ESI-MS/MS, to offer a versatile method for the analysis of tumour and cell-derived GSL-glycans. The method uses the potential of MS(2) fragmentation in negative ion ESI mode to characterize, in detail, the biologically relevant glycan structures derived from GSLs.

Expression of GBGT1 is epigenetically regulated by DNA methylation in ovarian cancer cells.

BACKGROUND: The GBGT1 gene encodes the globoside alpha-1,3-N-acetylgalactosaminyltransferase 1. This enzyme catalyzes the last step in the multi-step biosynthesis of the Forssman (Fs) antigen, a pentaglycosyl ceramide of the globo series glycosphingolipids. While differential GBGT1 mRNA expression has been observed in a variety of human tissues being highest in placenta and ovary, the expression of GBGT1 and the genes encoding the glycosyltransferases and glycosidases involved in the biosynthesis of Fs as well as the possible involvement of DNA methylation in transcriptional regulation of GBGT1 expression have not yet been investigated. RESULTS: RT-qPCR profiling showed high GBGT1 expression in normal ovary surface epithelial (HOSE) cell lines and low GBGT1 expression in all (e.g. A2780, SKOV3) except one (OVCAR3) investigated ovarian cancer cell lines, a finding that was confirmed by Western blot analysis. Hierarchical cluster analysis showed that GBGT1 was even the most variably expressed gene of Fs biosynthesis-relevant glycogenes and among the investigated cell lines, whereas NAGA which encodes the alpha-N-acetylgalactosaminidase hydrolyzing Fs was not differentially expressed. Bisulfite- and COBRA-analysis of the CpG island methylation status in the GBGT1 promoter region demonstrated high or intermediate levels of GBGT1 DNA methylation in all ovarian cancer cell lines (except for OVCAR3) but marginal levels of DNA methylation in the two HOSE cell lines. The extent of DNA methylation inversely correlated with GBGT1 mRNA and protein expression. Bioinformatic analysis of GBGT1 in The Cancer Genome Atlas ovarian cancer dataset demonstrated that this inverse correlation was also found in primary ovarian cancer tissue samples confirming our cell line-based findings. Restoration of GBGT1 mRNA and protein expression in low GBGT1-expressing A2780 cells was achieved by 5-aza-2'-deoxycytidine treatment and these treated cells exhibited increased helix pomatia agglutinin-staining, reflecting the elevated presence of Fs disaccharide on these cells. CONCLUSIONS: GBGT1 expression is epigenetically silenced through promoter hypermethylation in ovarian cancer. Our findings not only suggest an involvement of DNA methylation in the synthesis of Fs antigen but may also explain earlier studies showing differential GBGT1 expression in various human tissue samples and disease stages.

De novo detection of somatic variants in long-read single-cell RNA sequencing data.

In cancer, genetic and transcriptomic variations generate clonal heterogeneity, possibly leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging LR scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), copy-number alterations (CNAs), and gene fusions to reconstruct the tumor clonal heterogeneity. For SNV calling, LongSom distinguishes somatic SNVs from germline polymorphisms by reannotating marker gene expression-based cell types using called variants and applying strict filters. Applying LongSom to ovarian cancer samples, we detected clinically relevant somatic SNVs that were validated against single-cell and bulk panel DNA-seq data and could not be detected with short-read (SR) scRNA-seq. Leveraging somatic SNVs and fusions, LongSom found subclones with different predicted treatment outcomes. In summary, LongSom enables de novo SNVs, CNAs, and fusions detection, thus enabling the study of cancer evolution, clonal heterogeneity, and treatment resistance.

Protocol for quantifying drug sensitivity in 3D patient-derived ovarian cancer models.

Three-dimensional (3D) ex vivo cultures allow the study of cancer progression and drug resistance mechanisms. Here, we present a protocol for measuring on-target drug sensitivity in a scaffold-free 3D culture system through quantification of apoptotic tumor cells. We provide detailed steps for sample processing, immunofluorescence staining, semi-high-throughput confocal imaging, and imaged-based quantification of 3D cultures. This protocol is versatile and can be applied in principle to any patient-derived material.

Nuclear and cytosolic fractions of SOX2 synergize as transcriptional and translational co-regulators of cell fate.

Stemness and pluripotency are mediated by transcriptional master regulators that promote self-renewal and repress cell differentiation, among which is the high-mobility group (HMG) box transcription factor SOX2. Dysregulated SOX2 expression, by contrast, leads to transcriptional aberrations relevant to oncogenic transformation, cancer progression, metastasis, therapy resistance, and relapse. Here, we report a post-transcriptional mechanism by which the cytosolic pool of SOX2 contributes to these events in an unsuspected manner. Specifically, a low-complexity region within SOX2's C-terminal segment connects to the ribosome to modulate the expression of cognate downstream factors. Independent of nuclear structures or DNA, this C-terminal functionality alone changes metabolic properties and induces non-adhesive growth when expressed in the cytosol of SOX2 knockout cells. We thus propose a revised model of SOX2 action where nuclear and cytosolic fractions cooperate to impose cell fate decisions via both transcriptional and translational mechanisms.

Chemotherapy drives tertiary lymphoid structures that correlate with ICI-responsive TCF1+CD8+ T cells in metastatic ovarian cancer.

PURPOSE: Patients with high-grade serous ovarian carcinoma (HGSOC) are virtually insensitive to immune checkpoint inhibitors (ICIs) employed as standalone therapeutics, at least in part reflecting microenvironmental immunosuppression. Thus, conventional chemotherapeutics and targeted anticancer agents that not only mediate cytotoxic effects but also promote the recruitment of immune effector cells to the HGSOC microenvironment stand out as promising combinatorial partners for ICIs in this oncological indication. EXPERIMENTAL DESIGN: We harnessed a variety of transcriptomic, spatial and functional assays to characterize the differential impact of neo-adjuvant paclitaxel-carboplatin on the immunological configuration of paired primary and metastatic HGSOC biopsies as compared to NACT-naïve HGSOC samples from 5 independent patient cohorts. RESULTS: We found neo-adjuvant chemotherapy (NACT)-driven endoplasmic reticulum stress and calreticulin exposure in metastatic HGSOC lesions culminates with the establishment of a dense immune infiltrate including follicular T cells (TFH cells), a prerequisite for mature tertiary lymphoid structure (TLS) formation. In this context, TLS maturation was associated with an increased intratumoral density of ICI-sensitive TCF1+PD-1+ CD8+ T cells over their ICI-insensitive TIM-3+PD-1+ counterparts. Consistent with this notion, chemotherapy coupled with a PD-1-targeting ICI provided a significant survival benefit over either therapeutic approach in syngeneic models of HGSOC bearing high (but not low) tumor mutational burden. CONCLUSION: Altogether, our findings suggest that NACT promotes TLS formation and maturation in HGSOC lesions, de facto preserving an intratumoral ICI-sensitive T-cell phenotype. These observations emphasize the role of rational design, especially relative to the administration schedule, for clinical trials testing chemotherapy plus ICIs in patients with HGSOC.

Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer.

Intratumoral tertiary lymphoid structures (TLSs) have been associated with improved outcome in various cohorts of patients with cancer, reflecting their contribution to the development of tumor-targeting immunity. Here, we demonstrate that high-grade serous ovarian carcinoma (HGSOC) contains distinct immune aggregates with varying degrees of organization and maturation. Specifically, mature TLSs (mTLS) as forming only in 16% of HGSOCs with relatively elevated tumor mutational burden (TMB) are associated with an increased intratumoral density of CD8+ effector T (TEFF) cells and TIM3+PD1+, hence poorly immune checkpoint inhibitor (ICI)-sensitive, CD8+ T cells. Conversely, CD8+ T cells from immunologically hot tumors like non-small cell lung carcinoma (NSCLC) are enriched in ICI-responsive TCF1+ PD1+ T cells. Spatial B-cell profiling identifies patterns of in situ maturation and differentiation associated with mTLSs. Moreover, B-cell depletion promotes signs of a dysfunctional CD8+ T cell compartment among tumor-infiltrating lymphocytes from freshly isolated HGSOC and NSCLC biopsies. Taken together, our data demonstrate that - at odds with NSCLC - HGSOC is associated with a low density of follicular helper T cells and thus develops a limited number of mTLS that might be insufficient to preserve a ICI-sensitive TCF1+PD1+ CD8+ T cell phenotype. These findings point to key quantitative and qualitative differences between mTLSs in ICI-responsive vs ICI-irresponsive neoplasms that may guide the development of alternative immunotherapies for patients with HGSOC.

Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia.

Deep single-cell multi-omic profiling offers a promising approach to understand and overcome drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML). Here, we combine single-cell ex vivo drug profiling (pharmacoscopy) with single-cell and bulk DNA, RNA, and protein analyses, alongside clinical data from 21 rrAML patients. Unsupervised data integration reveals reduced ex vivo response to the Bcl-2 inhibitor venetoclax (VEN) in patients treated with both a hypomethylating agent (HMA) and VEN, compared to those pre-exposed to chemotherapy or HMA alone. Integrative analysis identifies both known and unreported mechanisms of innate and treatment-related VEN resistance and suggests alternative treatments, like targeting increased proliferation with the PLK inhibitor volasertib. Additionally, high CD36 expression in VEN-resistant blasts associates with sensitivity to CD36-targeted antibody treatment ex vivo. This study demonstrates how single-cell multi-omic profiling can uncover drug resistance mechanisms and treatment vulnerabilities, providing a valuable resource for future AML research.

Generation of endogenously tagged E-cadherin cells using gene editing via non-homologous end joining.

We provide a protocol using non-homologous end joining to integrate an oligonucleotide sequence of a fluorescence protein at the CDH1 locus encoding for the epithelial glycoprotein E-cadherin. We describe steps for implementing the CRISPR-Cas9-mediated knock-in procedure by transfecting a cancer cell line with a pool of plasmids. The EGFP-tagged cells are traced by fluorescence-activated cell sorting and validated on DNA and protein levels. The protocol is flexible and can be applied in principle to any protein expressed in a cell line. For complete details on the use and execution of this protocol, please refer to Cumin et al. (2022).1.

Low grade serous ovarian cancer - A rare disease with increasing therapeutic options.

High-grade serous ovarian cancers (HGSOCs) most commonly arise from the fimbrial end of the fallopian tube and harbor TP53 gene mutations. In contrast, low-grade serous ovarian cancers (LGSOCs) appear to have different pathological, epidemiological, and clinical features and should be seen as a distinct serous epithelial ovarian cancer subtype. Our current understanding of LGSOC is limited, and treatment has generally been derived from the more common HGSOCs due to a lack of separate trial data. LGSOCs are characterized by slow tumor growth and are assumed to develop from serous borderline ovarian tumors as precursors. These cancers are often estrogen-receptor positive and show an activated mitogen-activated protein kinase pathway together with KRAS and BRAF mutations and, rarely, TP53 mutations. These characteristics are now commonly used to guide therapeutical decision making and, consequently, a substantial part of treatment consists of maintenance with endocrine treatment, thus balancing disease stabilization and mild toxicity. Additionally, new trials are ongoing that examine the role of targeted therapies such as MEK inhibitors in combination with endocrine treatments. The purpose of this work is to summarize current knowledge and present ongoing trial efforts for LGSOCs.

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer.

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-ß/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

A 3D multi-cellular tissue model of the human omentum to study the formation of ovarian cancer metastasis.

Reliable and predictive experimental models are urgently needed to study metastatic mechanisms of ovarian cancer cells in the omentum. Although models for ovarian cancer cell adhesion and invasion were previously investigated, the lack of certain omental cell types, which influence the metastatic behavior of cancer cells, limits the application of these tissue models. Here, we describe a 3D multi-cellular human omentum tissue model, which considers the spatial arrangement of five omental cell types. Reproducible tissue models were fabricated combining permeable cell culture inserts and bioprinting technology to mimic metastatic processes of immortalized and patient-derived ovarian cancer cells. The implementation of an endothelial barrier further allowed studying the interaction between cancer and endothelial cells during hematogenous dissemination and the impact of chemotherapeutic drugs. This proof-of-concept study may serve as a platform for patient-specific investigations in personalized oncology in the future.