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.

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.

Genome-wide quantification of copy-number aberration impact on gene expression in ovarian high-grade serous carcinoma

Copy-number alterations (CNAs) are a hallmark of cancer and can regulate cancer cell states via altered gene expression values. Herein, we have developed a copy-number impact (CNI) analysis method that quantifies the degree to which a gene expression value is impacted by CNAs and leveraged this analysis at the pathway level. Our results show that a high CNA is not necessarily reflected at the gene expression level, and our method is capable of detecting genes and pathways whose activity is strongly influenced by CNAs. Furthermore, the CNI analysis enables unbiased categorization of CNA categories, such as deletions and amplifications. We identified six CNI-driven pathways associated with poor treatment response in ovarian high-grade serous carcinoma (HGSC), which we found to be the most CNA-driven cancer across 14 cancer types. The key driver in most of these pathways was amplified wild-type KRAS, which we validated functionally using CRISPR modulation. Our results suggest that wild-type KRAS amplification is a driver of chemotherapy resistance in HGSC and may serve as a potential treatment target.

Extensive mutational ctDNA profiles reflect High-grade serous cancer tumors and reveal emerging mutations at recurrence

OBJECTIVE

Circulating tumor DNA (ctDNA) offers a minimally-invasive alternative to study genomic changes in recurrent malignancies. With a high recurrence rate, the overall survival in high-grade serous ovarian carcinoma (HGSC) has remained low. Our objectives were to determine whether ctDNA from plasma adequately represents HGSC, and to find mutational changes at relapse suggesting therapy options that could alter patient outcome.

METHODS

We collected 152 longitudinal plasma and 92 fresh tissue samples from 29 HGSC patients, sequencing and detecting mutations with a gene panel of more than 700 cancer-related genes. Tumor content was measured using TP53 VAF. We analyzed the concordance between the mutations in tissue and plasma samples and calculated correlations to patient outcomes. We also searched for novel mutations appearing at relapse.

RESULTS

The concordance rate between mutations in plasma compared to tumor tissue was 83 % at diagnosis and 90 % at relapse. CtDNA was released similarly from the tubo-ovarian tumors, intra-abdominal metastases and ascites. CtDNA release was high when CA-125 level was elevated. The TP53 VAF in ctDNA from plasma samples before the third cycle of primary chemotherapy showed a negative correlation to patient outcome. At relapse, 19 novel, pathogenic DNA mutations appeared, suggesting possible actionable alterations and biological mechanisms related to chemoresistance.

CONCLUSION

Relapse ctDNA samples reflect tissue samples well and longitudinal sampling provides a timely source for mutational profiling. The emerging genetic mutations at recurrence propose that ctDNA accurately represents the widespread disease and provides possibilities for personalized therapy options.

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.

Functional Homologous Recombination Assay on FFPE Specimens of Advanced High-Grade Serous Ovarian Cancer Predicts Clinical Outcomes

PURPOSE

Deficiency in homologous recombination (HR) repair of DNA damage is characteristic of many high-grade serous ovarian cancers (HGSC). It is imperative to identify patients with homologous recombination-deficient (HRD) tumors as they are most likely to benefit from platinum-based chemotherapy and PARP inhibitors (PARPi). Existing methods measure historical, not necessarily current HRD and/or require high tumor cell content, which is not achievable for many patients. We set out to develop a clinically feasible assay for identifying functionally HRD tumors that can predict clinical outcomes.

EXPERIMENTAL DESIGN

We quantified RAD51, a key HR protein, in immunostained formalin-fixed, paraffin-embedded (FFPE) tumor samples obtained from chemotherapy-naïve and neoadjuvant chemotherapy (NACT)-treated HGSC patients. We defined cutoffs for functional HRD separately for these sample types, classified the patients accordingly as HRD or HR-proficient, and analyzed correlations with clinical outcomes. From the same specimens, genomics-based HRD estimates (HR gene mutations, genomic signatures, and genomic scars) were also determined, and compared with functional HR (fHR) status.

RESULTS

fHR status significantly predicted several clinical outcomes, including progression-free survival (PFS) and overall survival (OS), when determined from chemo-naïve (PFS, P < 0.0001; OS, P < 0.0001) as well as NACT-treated (PFS, P < 0.0001; OS, P = 0.0033) tumor specimens. The fHR test also identified as HRD those PARPi-at-recurrence-treated patients with longer OS (P = 0.0188).

CONCLUSIONS

We developed an fHR assay performed on routine FFPE specimens, obtained from either chemo-naïve or NACT-treated HGSC patients, that can significantly predict real-world platinum-based chemotherapy and PARPi response. See related commentary by Garg and Oza, p. 2957.

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

Ovarian high-grade serous carcinoma (HGSC) is typically diagnosed at an advanced stage, with multiple genetically heterogeneous clones existing in the tumors long before therapeutic intervention. Herein we integrate clonal composition and topology using whole-genome sequencing data from 510 samples of 148 patients with HGSC in the prospective, longitudinal, multiregion DECIDER study. Our results reveal three evolutionary states, which have distinct features in genomics, pathways, and morphological phenotypes, and significant association with treatment response. Nested pathway analysis suggests two evolutionary trajectories between the states. Experiments with five tumor organoids and three PI3K inhibitors support targeting tumors with enriched PI3K/AKT pathway with alpelisib. Heterogeneity analysis of samples from multiple anatomical sites shows that site-of-origin samples have 70% more unique clones than metastatic tumors or ascites. In conclusion, these analysis and visualization methods enable integrative tumor evolution analysis to identify patient subtypes using data from longitudinal, multiregion cohorts.

A platform for efficient establishment and drug-response profiling of high-grade serous ovarian cancer organoids

The broad research use of organoids from high-grade serous ovarian cancer (HGSC) has been hampered by low culture success rates and limited availability of fresh tumor material. Here, we describe a method for generation and long-term expansion of HGSC organoids with efficacy markedly improved over previous reports (53% vs. 23%-38%). We established organoids from cryopreserved material, demonstrating the feasibility of using viably biobanked tissue for HGSC organoid derivation. Genomic, histologic, and single-cell transcriptomic analyses revealed that organoids recapitulated genetic and phenotypic features of original tumors. Organoid drug responses correlated with clinical treatment outcomes, although in a culture conditions-dependent manner and only in organoids maintained in human plasma-like medium (HPLM). Organoids from consenting patients are available to the research community through a public biobank and organoid genomic data are explorable through an interactive online tool. Taken together, this resource facilitates the application of HGSC organoids in basic and translational ovarian cancer research.

Abstract 5779: A platform utilizing high-grade serous ovarian cancer organoids for prospective patient stratification in functional precision medicine

High-grade serous ovarian cancer (HGSC) is the most prevalent and lethal ovarian cancer type. While HGSC usually responds well to primary treatment, most cases eventually relapse. Functional precision medicine - tailoring individualized treatments based on functional in vitro assays on patient-derived cells - has been recently employed in cancer clinical trials. Cancer organoids - three-dimensional, self-organizing, self-renewing cell cultures that recapitulate original tissue structure and function - have been applied as cellular models in these trials. However, in case of HGSC, organoid derivation has proven time consuming and inefficient, hindering their application in functional precision medicine due to a short time window, in which therapy for each patient needs to be selected.

To address this problem, we aimed to establish whether drug vulnerabilities at HGSC relapse could be predicted using organoids derived from the primary disease cells. We derived sequential organoid models from material sampled during primary treatment and at relapse. Then, for organoid pairs (primary-relapse), we performed large-scale drug response profiling of a library of 370 compounds (approved drugs or drugs in clinical development), in 384-well microplate format, alone or in combination with a standard HGSC chemotherapeutic agent carboplatin. First, we found that HGSC organoid responses to standard chemotherapeutics retrospectively correlated to observed clinical treatment outcomes. But further, for each patient we identified compounds with pronounced cytotoxicity both in the primary and in the relapsed model, amounting to 66% of all hits (7% were primary-specific and 27% relapse-specific). We then focused on identifying patient-specific hits rather than compounds displaying general toxicity in all patient models. Based on a potential clinical applicability, for three patients we selected compounds for validation in organoid outgrowth assay, with prolonged (&gt;1 month) drug-free period post-treatment. In two patients, AZD4573, a selective CDK9 inhibitor in clinical development for hematological malignancies, at nanomolar concentrations caused eradication of organoids when combined with carboplatin. Organoids from the third patient were vulnerable to nitazoxanide, an approved anti-helminthic agent and an inhibitor of mitochondrial oxidative phosphorylation. Importantly, the selected final hits were identified solely based on screening in organoid models from primary disease.

In summary, we here demonstrate that HGSC organoids derived from primary disease material predict a majority of patient-specific drug vulnerabilities of organoids derived from the relapsed HGSC lesions. This indicates that patient stratification in functional precision medicine for treatment of HGSC relapse could be prospectively performed at the primary disease stage.

Citation Format: Wojciech Senkowski, Laura Gall-Mas, Matias M. Falco, Yilin Li, Kari Lavikka, Mette C. Kriegbaum, Jaana Oikkonen, Daria Bulanova, Elin J. Pietras, Karolin Voßgröne, Yan-Jun Chen, Erdogan P. Erkan, Mia K. Høg, Ida M. Larsen, Tarja Lamminen, Katja Kaipio, Jutta Huvila, Anni Virtanen, Lars H. Engelholm, Pernille Christiansen, Eric Santoni Rugiu, Kaisa Huhtinen, Olli Carpén, Johanna Hynninen, Sampsa Hautaniemi, Anna Vähärautio, Krister Wennerberg. A platform utilizing high-grade serous ovarian cancer organoids for prospective patient stratification in functional precision medicine. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5779.

Abstract 2135: Multi-omics characterization of chemo-refractory HGSC patients

Neoadjuvant chemotherapy (NACT) is the preferred treatment strategy for high-grade serous (ovarian) cancer (HGSC) patients, if optimal cytoreduction is estimated unachievable at the time of the diagnosis. In such cases, intrinsic sensitivity to standard-of-care (platinum and taxane combination therapy) is a major determinant of the disease progression.

The DECIDER project is an international effort to overcome the mechanisms of chemo-resistance by integration of clinical, imaging and multi-omics data layers from a prospective cohort of &gt;300 HGSC patients. In the DECIDER cohort, NACT was chosen as the treatment for 46% of the patients, of whom 31 had intrinsically chemo-refractory disease, defined as progressive or stable disease (SD/PD) at the end of the primary therapy and progression-free interval (PFI) shorter than 45 days. A reference group comprised 60 patients with partial or complete response (PR/CR) after primary therapy and PFI longer than six months. The rest of the NACT-treated patients had at least partial relapse but PFI between one to six months.

Herein, we tested the enrichment of clinicopathological and molecular features in the refractory and reference groups. Furthermore, we studied all NACT-treated patients, using a three-state survival model with primary progression and death as events of interest, and characterized survival associations with Cox regression. RNA sequencing data were used to identify cellular states and pathway activities, with the goal of revealing molecular level differences that drive early resistance to chemotherapy. Whole genome sequencing data were integrated to the gene expression-based results, to identify causal genetic aberrations. Additionally, the molecular features were tested against clinicopathological features and known HGSC driver mutations.

Our results suggest that the resistance to primary therapy predicts decreased survival, so that the mean time to death was 13.6 months for patients with SD/PD and about 5 months longer for patients with at least partial response. As expected, a higher pathological chemotherapy response score (CRS) predicted increased time to progression and a longer time from primary progression to death. However, there was only marginal difference in the distribution of the CRS between the chemo-refractory and responsive groups. In a multivariable model, mutation signature-based homologous recombination (HR) deficiency was associated with a longer time to primary progression, whereas the time from progression to death was associated only with loss-of-function mutations in HR genes. Interestingly, tumor mutation burden, whole genome duplication, or the level of tumor cell proliferation were not associated with chemo-resistance or patient survival. Immune cell infiltration in solid tissue samples was very low, except for one responsive patient, and was not associated with chemo-response.

Citation Format: Taru A. Muranen, Anna Rajavuori, Daria Afenteva, Kaisa Huhtinen, Veli-Matti Isoviita, Sanaz Jamalzadeh, Alexandra Lahtinen, Kari Lavikka, Yilin Li, Giovanni Marchi, Jaana Oikkonen, Kaiyang Zhang, Anni Virtanen, Johanna Hynninen, Sampsa Hautaniemi. Multi-omics characterization of chemo-refractory HGSC patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2135.

Abstract 6002: Characterizing dynamic landscape of DNA methylation in ovarian high-grade serous carcinoma

Dysregulated DNA methylation (DNAm) is a hallmark of all cancer types, though the precise role of these aberrations in tumor progression and treatment response remains elusive. Advances in whole-genome bisulfite sequencing (WGBS) have enabled profiling methylomes at full resolution and stimulated interest to explore dynamics of DNAm across tumor sites and cancer treatment. A major challenge in the analysis of patient data is that a surgically removed tumor sample represents a mixture of cancer cells and microenvironment, and that the insights on DNAm changes are intertwined due to mixed effects from patient epigenomic background, tissue context, and treatment pressure. By using a computational approach, these effects can be decomposed into patient background, tissue site, and treatment phase specific changes, and controlled for natural microenvironment variation. retion, and action, as well as in several oncogenic signaling cascades. The analysis of the tissue profiles indicated that the progression of HGSC from the tissues-of-origin to the metastatic deposits is accompanied by drastic changes in DNAm profiles. Thus, when comparing ovaries and peritoneum, intra-abdominal tissues mesentery and omentum featured prominent change of promoter DNAm: loss in 10% and gain in 20% of genes. Interestingly, the genes with aberrant DNAm included ABC transporters implicated in pumping drugs across the cell membrane, as well as the members of MAPK and PI3K signaling cascades. The joint analysis of both treatment and tissue contributions suggests that the overall modest effect of NACT is further reduced in metastases, mediated via DNAm changes in genes involved in multidrug resistance.

Citation Format: Alexandra Lahtinen, Giovanni Marchi, Daria Afenteva, Susanna Holmström, Kaisa Huhtinen, Anni Virtanen, Johanna Hynninen, Antti Häkkinen, Sampsa Hautaniemi. Characterizing dynamic landscape of DNA methylation in ovarian high-grade serous carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6002.

Aberrant glycosylation of α3 integrins as diagnostic markers in epithelial ovarian cancer

BACKGROUND

Glycans are strongly involved in stability and function of integrins (ITG) and tetraspanin protein CD63 and their respective interaction partners as they are dysregulated in the tumorigenic processes. Glycosylation changes is a universal phenomenon of cancer cells. In this study, glycosylation changes in epithelial ovarian cancer (EOC) are explored using tetraspanin and integrin molecules.

METHODS

ITG and CD63 were immobilized from 10 EOC and 5 benign ovarian cyst fluid on microtiter wells and traced with 3 glycan binding proteins (STn, WGA, UEA) conjugated on europium nanoparticles. Total protein measurements (ITG & CD63 immunoassays) were also performed. The most promising glycovariant candidates identified were then clinically evaluated on the whole cohort of 77 ovarian cyst fluids. Additional testing was performed in ascites fluid samples of liver cirrhosis (n=2) and EOC (n=4).

RESULTS

Sialylated Tn antibody based glycovariants of ITGα3 (ITGα3^STn) and CD63 (CD63^STn) performed better than corresponding protein epitope-based immunoassays, ITGα3^IA and CD63^IA respectively. Combined ITGα3 based assays (ITGα3^IA + ITGα3^STn) detected 49 out of 55 malignant & borderline cases without detecting any of the 22 benign and healthy cysts.

CONCLUSION

Our findings indicate the potential diagnostic application of ITGα3^STn along with total ITGα3^IA, which could help reduce the unnecessary surgeries. The results encourage studying further the potential use of these novel assays to detect EOC at earlier clinical stages.

Toxicity and therapy outcome associations in LIG3, SLCO1B3, ABCB1, OPRM1, and GSTP1 in high-grade serous ovarian cancer

Adverse effects are the major limiting factor in combinatorial chemotherapies. To identify genetic associations in ovarian cancer chemotherapy-induced toxicities and therapy outcomes, we examined a cohort of 101 patients receiving carboplatin-paclitaxel treatment with advanced high-grade serous ovarian cancers. Based on literature and database searches, we selected 19 candidate polymorphisms, designed a multiplex single nucleotide polymorphism-genotyping assay, and applied Cox regression analysis, case-control association statistics, and the log-rank Mantel-Cox test. In the Cox regression analysis, the SLCO1B3 rs1052536 AA-genotype was associated with a reduced risk of any severe toxicity (hazard ratio = 0.35, p=0.023). In chi-square allelic test, the LIG3 rs1052536 T-allele was associated with an increased risk of neuropathy (odds ratio (OR) = 2.79, p=0.031) and GSTP1 rs1695 G-allele with a poorer response in the first-line chemotherapy (OR=2.65, p=0.026). In Kaplan-Meier survival analysis, ABCB1 rs2032582 TT-genotype was associated with shorter overall survival (uncorrected p=0.025), and OPRM1 rs544093 GG and GT genotypes with shorter platinum-free interval (uncorrected p=0.027) and progression-free survival (uncorrected p=0.012). Results suggest that SLCO1B3 and LIG3 variants are associated with the risk of adverse effects in patients receiving carboplatin-paclitaxel treatment, the GSTP1 variant may affect the treatment response, and ABCB1 and OPRM1 variants may influence the prognosis.

Effects of Wee1 inhibitor adavosertib on patient-derived high-grade serous ovarian cancer cells are multiple and independent of homologous recombination status

Objective

A major challenge in the treatment of platinum-resistant high-grade serous ovarian cancer (HGSOC) is lack of effective therapies. Much of ongoing research on drug candidates relies on HGSOC cell lines that are poorly documented. The goal of this study was to screen for effective, state-of-the-art drug candidates using primary HGSOC cells. In addition, our aim was to dissect the inhibitory activities of Wee1 inhibitor adavosertib on primary and conventional HGSOC cell lines.

Methods

A comprehensive drug sensitivity and resistance testing (DSRT) on 306 drug compounds was performed on three patient-derived genetically unique HGSOC cell lines and two commonly used ovarian cancer cell lines. The effect of adavosertib on the cell lines was tested in several assays, including cell-cycle analysis, apoptosis induction, proliferation, wound healing, DNA damage, and effect on nuclear integrity.

Results

Several compounds exerted cytotoxic activity toward all cell lines, when tested in both adherent and spheroid conditions. In further cytotoxicity tests, adavosertib exerted the most consistent cytotoxic activity. Adavosertib affected cell-cycle control in patient-derived and conventional HGSOC cells, inducing G2/M accumulation and reducing cyclin B1 levels. It induced apoptosis and inhibited proliferation and migration in all cell lines. Furthermore, the DNA damage marker γH2AX and the number of abnormal cell nuclei were clearly increased following adavosertib treatment. Based on the homologous recombination (HR) signature and functional HR assays of the cell lines, the effects of adavosertib were independent of the cells' HR status.

Conclusion

Our study indicates that Wee1 inhibitor adavosertib affects several critical functions related to proliferation, cell cycle and division, apoptosis, and invasion. Importantly, the effects are consistent in all tested cell lines, including primary HGSOC cells, and independent of the HR status of the cells. Wee1 inhibition may thus provide treatment opportunities especially for patients, whose cancer has acquired resistance to platinum-based chemotherapy or PARP inhibitors.

Ovarian Cancers with Low CIP2A Tumor Expression Constitute an APR-246-Sensitive Disease Subtype

Identification of ovarian cancer patient subpopulations with increased sensitivity to targeted therapies could offer significant clinical benefit. We report that 22% of the high-grade ovarian cancer tumors at diagnosis express CIP2A oncoprotein at low levels. Furthermore, regardless of their significantly lower likelihood of disease relapse after standard chemotherapy, a portion of relapsed tumors retain their CIP2A-deficient phenotype. Through a screen for therapeutics that would preferentially kill CIP2A-deficient ovarian cancer cells, we identified reactive oxygen species inducer APR-246, tested previously in ovarian cancer clinical trials. Consistent with CIP2A-deficient ovarian cancer subtype in humans, CIP2A is dispensable for development of MISIIR-Tag-driven mouse ovarian cancer tumors. Nevertheless, CIP2A-null ovarian cancer tumor cells from MISIIR-Tag mice displayed APR-246 hypersensitivity both in vitro and in vivo. Mechanistically, the lack of CIP2A expression hypersensitizes the ovarian cancer cells to APR-246 by inhibition of NF-κB activity. Accordingly, combination of APR-246 and NF-κB inhibitor compounds strongly synergized in killing of CIP2A-positive ovarian cancer cells. Collectively, the results warrant consideration of clinical testing of APR-246 for CIP2A-deficient ovarian cancer tumor subtype patients. Results also reveal CIP2A as a candidate APR-246 combination therapy target for ovarian cancer.

Abstract 3069: Efficient establishment and utilization of a high-grade serous ovarian cancer organoid biobank

Extensive utilization of organoids from high-grade serous ovarian carcinoma (HGSOC), the most common and lethal ovarian cancer, has been hampered by low success rates of long-term culture and scarcity of fresh tumor material. Here we present the development of a novel method for efficient generation, expansion and use of HGSOC organoids from cryopreserved tumor material.

First, we assessed commonly used organoid media components and found that supplements such as FGF-2, R-Spondin1, Wnt or Noggin had negative impact on the HGSOC organoid derivation. But further, we found that supplementation with FGF-4, which has not been used in cancer organoid culture before, is beneficial for HGSOC organoid growth. Through extensive testing of various supplements and their combinations, we designed two novel HGSOC organoid media formulations - Medium 1 (M1) and Medium 2 (M2). Using M1 and M2 enabled generation and long-term expansion of living HGSOC organoid biobank with markedly improved success rate than in previous reports (55% vs. 23-38%). The organoids were established from cryopreserved tumor material, demonstrating the feasibility of using frozen tissue biobanks for HGSOC organoid derivation. Overall, we generated a collection of 18 expandable HGSOC organoid lines from 11 patients, encompassing samples from different tissue sites and disease progression stages.

We validated the organoids using whole-genome sequencing, immunohistochemistry and single-cell RNA sequencing and demonstrated that they are genetically and phenotypically representative of original patient samples over long-term culture. Based on available patient consents, we deposited 3 organoid lines in a publicly accessible biobank. Finally, we investigated whether organoid drug responses correlate to those observed earlier in the clinic in the corresponding patients. Organoid-based drug-response profiling of clinically used HGSOC drug collection was performed in 384-well microplate format. To explore whether growth conditions impact correlation between organoid drug responses and clinical response, we compared the organoid drug responses in the nutrient-rich M1/M2 growth media to the ones observed in human plasma-like medium (HPLM), supplemented with relevant niche factors from M1/M2. Organoid drug responses correlated with clinical treatment outcomes, but only for organoids maintained in HPLM (Spearman r = 0.987, p=0.007 in HPLM vs 0.607, p=0.167 in growth medium, n=7), highlighting the importance of culture conditions in organoid-based functional assays. Taken together, we introduce a resource for efficient development and use of HGSOC organoids from cryopreserved material in ovarian cancer research.

Citation Format: Wojciech Senkowski, Laura Gall Mas, Matias M. Falco, Yilin Li, Kari Lavikka, Mette C. Kriegbaum, Jaana Oikkonen, Daria Bulanova, Elin J. Pietras, Karolin Voßgröne, Erdogan P. Erkan, Terese K. Høj, Mia K. Høg, Tarja Lamminen, Katja Kaipio, Anni Virtanen, Lars H. Engelholm, Pernille Christiansen, Eric Santoni-Rugiu, Kaisa Huhtinen, Olli Carpén, Johanna Hynninen, Sampsa Hautaniemi, Anna Vähärautio, Krister Wennerberg. Efficient establishment and utilization of a high-grade serous ovarian cancer organoid biobank [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3069.

Abstract 192: Ex vivo screening and analysis of novel effective treatments for ovarian cancer

Purpose: Ovarian cancer is the most lethal gynecological cancer. Histologically, about 90% of the ovarian cancers have epithelial origin and more than 75% are characterized as high-grade serous ovarian cancer (HGSOC). Despite having a good primary response to the standard platinum-taxane based chemotherapy, almost all HGSOC patients experience a relapsed disease. The 5-year survival rate of ovarian cancer is only 38% globally, indicating need for the development of novel efficient treatments to fight the resistance. Here we have established a personalized drug screening and evaluation platform using HGSOC patient samples and medicines approved for treatment of different types of cancers.

Methods: Tissues collected from ovarian cancer patients were grown as 3-dimensional (3D) ex vivo long-term tumor organoid cultures. Seven HGSOC cell lines were additionally grown as spheroids or as xenograft tumors to establish them as 3D tumor organoid cultures for drug efficiency evaluation. Cancer stemness and further classification of samples were determined via immunofluorescent staining with relevant antibodies (pax8, Ki67, acetylated tubulin, p53, cytokeratin-8) and consequent high-throughput imaging using the ImageXpress Micro Confocal microscope (Molecular Devices). The images were analyzed and quantified using MetaXpress software. Organoid growth and response to tested treatments was validated via invasive growth and survival assays. Both assays were used to monitor resistance of organoids towards cisplatin and carboplatin treatment and towards suggested potential new treatments. Cancer drugs were selected according to suggestions based on RNA seq, DNA and/or drug screenings done in cancer cell lines. A preclinical mouse model (in immunodeficient NOD/Shi-scid/IL-2Rγnull (NOG) mice) was set up to be used for in vivo validation by monitoring the tumor growth in response to the treatment.

Results: Currently, 20 patient tumor samples received from Turku University Hospital, Finland (KH, JH) have been cultured in 4 different culture media to obtain highest possible survival rates for each sample. Organoids from ovarian cancer cell lines are characterized for their resistance to increasing concentrations of platinum treatment. Notably, organoid analysis protocols and screening conditions have been setup for the high-throughput microscopy. These include organoid growth, survival, and invasiveness/aggressiveness. We are currently set up for screening organoids with the first drugs suggested by bioinformatics-based genetic pathway analysis and drug screening studies in cancer cell lines. The results of the screen will be presented. This study is a part of a large EU-funded ovarian cancer project DECIDER (https://www.deciderproject.eu/).

Citation Format: Aikaterini Skorda, Kaisa Huhtinen, Wojciech Senkowski, Krister Wennerberg, Sampsa Hautaniemi, Johanna Hynninen, Tuula Kallunki. Ex vivo screening and analysis of novel effective treatments for ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 192.

Abstract 2707: Factoring expression data of high-grade serous ovarian cancer tumors for unbiased longitudinal analysis

We address challenges in longitudinal RNA-seq analysis of patient tumors, which can reveal powerful insights on cancer evolution at personalized level, proposing methods for unbiased analysis and integration

Experimental procedures:

214 whole-genome bulk RNA-seq samples from 61 high-grade serous ovarian cancer (HGSC) patients were collected before and after chemotherapy, along with single-cell RNA-seq data from &gt;93,000 cells in 11 patients. 308 TCGA treatment-naive bulk RNA-seq samples from HGSC, 474 from melanoma (SKCM), and 581 from endometrial carcinoma (UCEC) were used for validation.

Results:

We show that in a longitudinal analysis, cancer progression and chemotherapy exert both microenvironmental and phenotypic changes. We developed PRISM [1] to factor the expression data at individual bulk level, and show the adjustment improves the association between expression profiles and patient survival. Our findings extend to pathway and expression-derived tumor subtype levels in HGSC and SKCM.

Technical batch effects pose challenges for multi-institute or long-running sample collections. Unbiased correction requires replicates, which are typically unavailable for patient data. We developed POIBM [submitted] to simultaneously infer a suitable reference and factor out the batch effects. We show that POIBM effectively discovers true replicates, batch effects plague many cancer types in TCGA data, and batch correction allows more meaningful expression subtyping in UCEC.

Distinct genomic backgrounds of the patients hinders stratification and discovering shared functional states. We developed PRIMUS [submitted] to simultaneously factor the patient background (or other confounders) and a sample clustering, which is necessary when the underlying stratification is uneven or shared by patient subsets. Among the commonly aberrant cell states, such as EMT, PRIMUS analysis on HGSC scRNA identified a novel stress signature, enriched by chemotherapy and indicating poor survival, which were validated in PRISM-factored TCGA bulk ovarian data.

Conclusions:

Our methodology facilitates unbiased longitudinal expression analysis and integration. The more accurate phenotypic changes at gene, pathway, and expression subtype level may confer sensitivity/resistance chemotherapy, and, as shown, allow enhance patient survival prediction and discovery of novel chemotherapy related subtypes. Consequently, our work aids ranking putative intervention strategies for overcoming ovarian cancer chemoresistance for future validation experiments.

[1]: Hakkinen et al., Bioinformatics 37: 2882 (2021)

Citation Format: Antti Häkkinen, Kaiyang Zhang, Susanna Holmström, Sanaz Jamaldazeh, Johanna Hynninen, Sakari Hietanen, Kaisa Huhtinen, Sampsa Hautaniemi. Factoring expression data of high-grade serous ovarian cancer tumors for unbiased longitudinal analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2707.

Abstract A010: Integration of clonal composition and tumor heterogeneity reveals novel evolutionary states and intervention targets in ovarian cancer

This abstract is being presented as a short talk in the scientific program. A full abstract is available in the Proffered Abstracts section (PR003) of the Conference Proceedings.

Citation Format: Alexandra Lahtinen, Kari Lavikka, Yilin Li, Sanaz Jamalzadeh, Anni Virtanen, Rainer Lehtonen, Olli Carpén, Sakari Hietanen, Kaisa Huhtinen, Antti Häkkinen, Johanna Hynninen, Jaana Oikkonen, Sampsa Hautaniemi. Integration of clonal composition and tumor heterogeneity reveals novel evolutionary states and intervention targets in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A010.

Abstract PR003: Integration of clonal composition and tumor heterogeneity reveals novel evolutionary states and intervention targets in ovarian cancer

High-grade serous ovarian cancer (HGSC) is the most common form of epithelial ovarian cancer, typically diagnosed at advanced stage with five-year survival of only 38%. Herein, we used 149 treatment-naïve and 65 after-treatment samples subjected to whole-genome sequencing from 55 HGSC patients to reconstruct evolutionary histories, characterize clonal compositions and intra- and inter-tumor heterogeneity, in order to identify mechanisms that drive treatment failure. Using clonal information from the phylogenetic trees we quantified intra- and intertumor heterogeneity and identified three types of clonal compositions corresponding to three evolutionary states (“adaptive”, “maintaining” and “evolving”) of treatment-naïve HGSC tumors. The branch depths from phylogenetic trees were used to quantify “clonal age” for each state. The “adaptive” state showed the highest clonal age, followed by the “maintaining” state, and the “evolving” being the youngest, least evolved tumor state. The three states have significantly different survival association, “evolving” the longest and “maintaining” the shortest (p = 0.029). Pathway analysis of genes harboring branch mutations revealed that the three states are characterized by unique signaling cascades, with MAPK, PI3K/AKT, and NOTCH signaling significantly enriched at “evolving”, “maintaining”, and “adaptive” states, respectively. Furthermore, we suggest two evolutionary trajectories originating from “evolving” state towards “maintaining” via PI3K/AKT activation and extensive cytokine signaling or towards “adaptive” state via RAS/RAF/MAP cascade. Overall, altered PI3K/AKT signaling was found in half of the patients, followed by alterations in NOTCH signaling enriched in 20% of patients. To explore the effect of treatment on evolutionary states we investigated clonal compositions and enriched pathways in the after-treatment samples. Interestingly, 62% of the neoadjuvant chemotherapy treated (three cycles of platinum & paclitaxel) samples remained in the same evolutionary state as compared to the treatment-naïve samples from the same patients, indicating that the neoadjuvant therapy does not significantly alter tumor composition. Analysis of relapse samples revealed that signal transduction via PI3K/AKT and NOTCH was enriched after the full course of treatment (including platinum-taxane chemotherapy, surgery, possible maintenance therapy with PARP inhibitors or angiogenesis inhibitors), which testifies for their central role in treatment failure. Taken together, our results show that integrating clonal composition and heterogeneity at diagnosis allows allocation of HGSC tumors into three states with different prognosis. Aberrations in PI3K/AKT or NOTCH signaling, distinctive for higher evolved “maintaining” and “adaptive” states, are key pathways to the development of chemoresistant clones. As the herein identified pathways can be targeted by several clinically approved drugs, our results provide a means to identify effective, combinatorial personalized treatments for HGSC patients at the relapse setting.

Citation Format: Alexandra Lahtinen, Kari Lavikka, Yilin Li, Sanaz Jamalzadeh, Anni Virtanen, Rainer Lehtonen, Olli Carpén, Sakari Hietanen, Kaisa Huhtinen, Antti Häkkinen, Johanna Hynninen, Jaana Oikkonen, Sampsa Hautaniemi. Integration of clonal composition and tumor heterogeneity reveals novel evolutionary states and intervention targets in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR003.

Diagnostic potential of nanoparticle aided assays for MUC16 and MUC1 glycovariants in ovarian cancer

Our study reports the discovery and evaluation of nanoparticle aided sensitive assays for glycovariants of MUC16 and MUC1 in a unique collection of paired ovarian cyst fluids and serum samples obtained at or prior to surgery for ovarian carcinoma suspicion. Selected glycovariants and the immunoassays for CA125, CA15‐3 and HE4 were compared and validated in 347 cyst fluid and serum samples. Whereas CA125 and CA15‐3 performed poorly in cyst fluid to separate carcinoma and controls, four glycovariants including MUC16^MGL, MUC16^STn, MUC1^STn and MUC1^Tn provided highly improved separations. In serum, the two STn glycovariants outperformed conventional CA125, CA15‐3 and HE4 assays in all subcategories analyzed with main benefits obtained at high specificities and at postmenopausal and early‐stage disease. Serum MUC16^STn performed best at high specificity (90%‐99%), but sensitivity was also improved by the other glycovariants and CA15‐3. The highly improved specificity, excellent analytical sensitivity and robustness of the nanoparticle assisted glycovariant assays carry great promise for improved identification and early detection of ovarian carcinoma in routine differential diagnostics.

Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer

Chemotherapy resistance is a critical contributor to cancer mortality and thus an urgent unmet challenge in oncology. To characterize chemotherapy resistance processes in high-grade serous ovarian cancer, we prospectively collected tissue samples before and after chemotherapy and analyzed their transcriptomic profiles at a single-cell resolution. After removing patient-specific signals by a novel analysis approach, PRIMUS, we found a consistent increase in stress-associated cell state during chemotherapy, which was validated by RNA in situ hybridization and bulk RNA sequencing. The stress-associated state exists before chemotherapy, is subclonally enriched during the treatment, and associates with poor progression-free survival. Co-occurrence with an inflammatory cancer-associated fibroblast subtype in tumors implies that chemotherapy is associated with stress response in both cancer cells and stroma, driving a paracrine feed-forward loop. In summary, we have found a resistant state that integrates stromal signaling and subclonal evolution and offers targets to overcome chemotherapy resistance.

Dubious effects of methadone as an "anticancer" drug on ovarian cancer cell-lines and patient-derived tumor-spheroids

BACKGROUND

The opioid agonist D,L-methadone exerts analgesic effects via the mu opioid receptor, encoded by OPRM1 and therefore plays a role in chronic pain management. In preclinical tumor-models D,L-methadone shows apoptotic and chemo-sensitizing effects and was therefore hyped as an off-label "anticancer" drug without substantiation from clinical trials. Its effects in ovarian cancer (OC) are completely unexplored.

METHODS

We analyzed OPRM1-mRNA expression in six cisplatin-sensitive, two cisplatin-resistant OC cell-lines, 170 OC tissue samples and 12 non-neoplastic control tissues. Pro-angiogenetic, cytotoxic and apoptotic effects of D,L-methadone were evaluated in OC cell-lines and four patient-derived tumor-spheroid models.

RESULTS

OPRM1 was transcriptionally expressed in 69% of OC-tissues and in three of eight OC cell-lines. D,L-methadone exposure significantly reduced cell-viability in five OC cell-lines irrespective of OPRM1 expression. D,L-methadone, applied alone or combined with cisplatin, showed no significant effects on apoptosis or VEGF secretion in cell-lines. Notably, in two of the four spheroid models, treatment with D,L-methadone significantly enhanced cell growth (by up to 121%), especially after long-term exposure. This is consistent with the observed attenuation of the inhibitory effects of cisplatin in three spheroid models when adding D,L-methadone. The effect of methadone treatment on VEGF secretion in tumor-spheroids was inconclusive.

CONCLUSIONS

Our study demonstrates that certain OC samples express OPRM1, which, however, is not a prerequisite for D,L-methadone function. As such, D,L-methadone may exert also detrimental effects by stimulating the growth of certain OC-cells and abrogating cisplatin's therapeutic effect.

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer

Each patient's cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.

Targeting DNA Homologous Repair Proficiency With Concomitant Topoisomerase II and c-Abl Inhibition

Critical DNA repair pathways become deranged during cancer development. This vulnerability may be exploited with DNA-targeting chemotherapy. Topoisomerase II inhibitors induce double-strand breaks which, if not repaired, are detrimental to the cell. This repair process requires high-fidelity functional homologous recombination (HR) or error-prone non-homologous end joining (NHEJ). If either of these pathways is defective, a compensatory pathway may rescue the cells and induce treatment resistance. Consistently, HR proficiency, either inherent or acquired during the course of the disease, enables tumor cells competent to repair the DNA damage, which is a major problem for chemotherapy in general. In this context, c-Abl is a protein tyrosine kinase that is involved in DNA damage-induced stress. We used a low-dose topoisomerase II inhibitor mitoxantrone to induce DNA damage which caused a transient cell cycle delay but allowed eventual passage through this checkpoint in most cells. We show that the percentage of HR and NHEJ efficient HeLa cells decreased more than 50% by combining c-Abl inhibitor imatinib with mitoxantrone. This inhibition of DNA repair caused more than 87% of cells in G2/M arrest and a significant increase in apoptosis. To validate the effect of the combination treatment, we tested it on commercial and patient-derived cell lines in high-grade serous ovarian cancer (HGSOC), where chemotherapy resistance correlates with HR proficiency and is a major clinical problem. Results obtained with HR-proficient and deficient HGSOC cell lines show a 50–85% increase of sensitivity by the combination treatment. Our data raise the possibility of successful targeting of treatment-resistant HR-proficient cancers.

Abstract 947: Effects of methadone on ovarian cancer cell-lines and patient-derived tumor-spheroids

Background: D,L-Methadone exerts analgesic effects via the mu opioid receptor, encoded by OPRM1 and therefore plays a role in chronic pain management. Although the use of this opioid-receptor agonist as an anti-cancer drug is deemed controversial, this drug is gaining popularity in Europe as an “off-label” therapy despite insufficient research to support its benefits. In preclinical glioblastoma and leukaemia cell culture models D,L-methadone showed apoptotic and chemo-sensitizing effects. Its effects in ovarian cancer (OC) are completely unexplored.

Methods: We analysed the OPRM mRNA expression in six cisplatin-sensitive, two cisplatin-resistant OC cell-lines, 192 OC samples and 12 non-neoplastic control tissues. Pro-angiogenetic, cytotoxic and apoptotic effects of D,L-methadone were evaluated in OC cell-lines and four patient-derived tumor-spheroid models.

Results: OPRM1 was transcriptionally expressed in 69% of OC-tissues and in five of eight OC cell-lines. D,L-methadone exposure significantly reduced cell-viability in five OC cell-lines irrespective of OPRM1 expression. D,L-methadone, applied alone or combined with cisplatin, showed no significant effects on apoptosis or VEGF secretion in cell-lines. Notably, in two of the four spheroid models, treatment with D,L-methadone resulted in significantly enhanced cell growth (by up to 121%), especially after long-term exposure. This is consistent with the observed attenuation of the inhibitory effects of cisplatin in three spheroid models when adding D,L-methadone. The effect of methadone treatment on VEGF secretion in tumor-spheroids was inconclusive.

Conclusions: Our study demonstrates that certain OC samples express OPRM1, which, however, is not a prerequisite for D,L-methadone function. As such, D,L-methadone may exert detrimental effects by stimulating the growth of certain OC-cells and abrogating cisplatin's therapeutic effect.

Citation Format: Heidelinde Fiegl, Judith Hagenbuchner, Michael J. Ausserlechner, Christiana Kyvelidou, Beata Seeber, Sieghart Sopper, Irina Tsibulak, Verena Wieser, Julia Roessler, Elisabeth Reiser, Kaisa Huhtinen, Olli Carpén, Walther Parson, Christian Marth, Alain G. Zeimet. Effects of methadone on ovarian cancer cell-lines and patient-derived tumor-spheroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 947.

Exploratory Analysis of CA125-MGL and -STn Glycoforms in the Differential Diagnostics of Pelvic Masses

BACKGROUND

The cancer antigen 125 (CA125) immunoassay (IA) does not distinguish epithelial ovarian cancer (EOC) from benign disease with the sensitivity needed in clinical practice. In recent studies, glycoforms of CA125 have shown potential as biomarkers in EOC. Here, we assessed the diagnostic abilities of two recently developed CA125 glycoform assays for patients with a pelvic mass. Detailed analysis was further conducted for postmenopausal patients with marginally elevated conventionally measured CA125 levels, as this subgroup presents a diagnostic challenge in the clinical setting.

METHODS

Our study population contained 549 patients diagnosed with EOC, benign ovarian tumors, and endometriosis. Of these, 288 patients were postmenopausal, and 98 of them presented with marginally elevated serum levels of conventionally measured CA125 at diagnosis. Preoperative serum levels of conventionally measured CA125 and its glycoforms (CA125-MGL and CA125-STn) were determined.

RESULTS

The CA125-STn assay identified EOC significantly better than the conventional CA125-IA in postmenopausal patients (85% vs. 74% sensitivity at a fixed specificity of 90%, P = 0.0009). Further, both glycoform assays had superior AUCs compared to the conventional CA125-IA in postmenopausal patients with marginally elevated CA125. Importantly, the glycoform assays reduced the false positive rate of the conventional CA125-IA.

CONCLUSIONS

The results indicate that the CA125 glycoform assays markedly improve the performance of the conventional CA125-IA in the differential diagnosis of pelvic masses. This result is especially valuable when CA125 is marginally elevated.

Aggressive and recurrent ovarian cancers upregulate ephrinA5, a non-canonical effector of EphA2 signaling duality

Erythropoietin producing hepatocellular (Eph) receptors and their membrane-bound ligands ephrins are variably expressed in epithelial cancers, with context-dependent implications to both tumor-promoting and -suppressive processes in ways that remain incompletely understood. Using ovarian cancer tissue microarrays and longitudinally collected patient cells, we show here that ephrinA5/EFNA5 is specifically overexpressed in the most aggressive high-grade serous carcinoma (HGSC) subtype, and increased in the HGSC cells upon disease progression. Among all the eight ephrin genes, high EFNA5 expression was most strongly associated with poor overall survival in HGSC patients from multiple independent datasets. In contrast, high EFNA3 predicted improved overall and progression-free survival in The Cancer Genome Atlas HGSC dataset, as expected for a canonical inducer of tumor-suppressive Eph receptor tyrosine kinase signaling. While depletion of either EFNA5 or the more extensively studied, canonically acting EFNA1 in HGSC cells increased the oncogenic EphA2-S897 phosphorylation, EFNA5 depletion left unaltered, or even increased the ligand-dependent EphA2-Y588 phosphorylation. Moreover, treatment with recombinant ephrinA5 led to limited EphA2 tyrosine phosphorylation, internalization and degradation compared to ephrinA1. Altogether, our results suggest a unique function for ephrinA5 in Eph-ephrin signaling and highlight the clinical potential of ephrinA5 as a cell surface biomarker in the most aggressive HGSCs.

FUNGI: Fusion Gene Integration Toolset

Motivation

Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules.

Results

We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance.

Availabilityand implementation

FUNGI and its documentation are available at https://bitbucket.org/alejandra_cervera/fungi as standalone or from Anduril at https://www.anduril.org.

Supplementary information

Supplementary data are available at Bioinformatics online.

PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples

MOTIVATION

A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample composition changes systematically due to chemotherapy and between the anatomical sites, preventing direct comparison of treatment-naive and treated samples.

RESULTS

To overcome this, we developed PRISM, a latent statistical framework to simultaneously extract the sample composition and cell-type-specific whole-transcriptome profiles adapted to each individual sample. Our results indicate that the PRISM-derived composition-free transcriptomic profiles and signatures derived from them predict the patient response better than the composite raw bulk data. We validated our findings in independent ovarian cancer and melanoma cohorts, and verified that PRISM accurately estimates the composition and cell-type-specific expression through whole-genome sequencing and RNA in situ hybridization experiments.

AVAILABILITYAND IMPLEMENTATION

https://bitbucket.org/anthakki/prism.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

HE4 in the evaluation of tumor load and prognostic stratification of high grade serous ovarian carcinoma

OBJECTIVE

Human epididymis protein 4 (HE4) is a validated, complementary biomarker to cancer antigen 125 (CA125) for high grade serous ovarian carcinoma (HGSC). Currently, there are insufficient data on the utility of longitudinal HE4 measurement during HGSC treatment and follow up. We set to provide a comprehensive analysis on the kinetics and prognostic performance of HE4 with serial measurements during HGSC treatment and follow up.

METHODS

This prospective study included 143 patients with advanced HGSC (ClinicalTrials.gov identifier: NCT01276574). Serum CA125 and HE4 were measured at baseline, before each cycle of chemotherapy and during follow up until first progression. Baseline biomarker values were compared to the tumor load assessed during surgery and to residual disease. Biomarker nadir values and concentrations at progression were correlated to survival.

RESULTS

The baseline HE4 concentration distinguished patients with a high tumor load from patients with a low tumor load assessed during surgery (p<.0001). The baseline CA125 level was not associated with tumor load to a similar extent (p=.067). At progression, the HE4 level was an independent predictor of worse survival in the multivariate analysis (p=.002). All patients that were alive 3 years post-progression had a serum HE4 concentration below 199.20 pmol/l at the 1st recurrence.

CONCLUSION

HE4 is a feasible biomarker in the treatment monitoring and prognostic stratification of patients with HGSC. Specifically, the serum level of HE4 at first relapse was associated with the survival of patients and it may be a useful complementary tool in the selection of second line treatments. This is to the best of our knowledge the first time this finding has been reported.

Genetically Defined Syngeneic Mouse Models of Ovarian Cancer as Tools for the Discovery of Combination Immunotherapy

Despite advances in immuno-oncology, the relationship between tumor genotypes and response to immunotherapy remains poorly understood, particularly in high-grade serous tubo-ovarian carcinomas (HGSC). We developed a series of mouse models that carry genotypes of human HGSCs and grow in syngeneic immunocompetent hosts to address this gap. We transformed murine-fallopian tube epithelial cells to phenocopy homologous recombination-deficient tumors through a combined loss of Trp53, Brca1, Pten, and Nf1 and overexpression of Myc and Trp53 ^R172H, which was contrasted with an identical model carrying wild-type Brca1. For homologous recombination-proficient tumors, we constructed genotypes combining loss of Trp53 and overexpression of Ccne1, Akt2, and Trp53 ^R172H, and driven by KRAS ^G12V or Brd4 or Smarca4 overexpression. These lines form tumors recapitulating human disease, including genotype-driven responses to treatment, and enabled us to identify follistatin as a driver of resistance to checkpoint inhibitors. These data provide proof of concept that our models can identify new immunotherapy targets in HGSC. SIGNIFICANCE: We engineered a panel of murine fallopian tube epithelial cells bearing mutations typical of HGSC and capable of forming tumors in syngeneic immunocompetent hosts. These models recapitulate tumor microenvironments and drug responses characteristic of human disease. In a Ccne1-overexpressing model, immune-checkpoint resistance was driven by follistatin.This article is highlighted in the In This Issue feature, p. 211.

A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions

Endometriosis is a common inflammatory estrogen-dependent gynecological disorder, associated with pelvic pain and reduced fertility in women. Several aspects of this disorder and its cellular and molecular etiology remain unresolved. We have analyzed the global gene expression patterns in the endometrium, peritoneum and in endometriosis lesions of endometriosis patients and in the endometrium and peritoneum of healthy women. In this report, we present the EndometDB, an interactive web-based user interface for browsing the gene expression database of collected samples without the need for computational skills. The EndometDB incorporates the expression data from 115 patients and 53 controls, with over 24000 genes and clinical features, such as their age, disease stages, hormonal medication, menstrual cycle phase, and the different endometriosis lesion types. Using the web-tool, the end-user can easily generate various plot outputs and projections, including boxplots, and heatmaps and the generated outputs can be downloaded in pdf-format.

Availability and implementationThe web-based user interface is implemented using HTML5, JavaScript, CSS, Plotly and R. It is freely available from https://endometdb.utu.fi/.

Measurement(s)	RNA • differential expression analysis data • endometriosis
Technology Type(s)	Microarray Analysis • digital curation
Factor Type(s)	age • disease stage • menstrual cycle phase • hormonal medication • endometriosis lesion type • endometrium
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12800642

Glycovariant-based lateral flow immunoassay to detect ovarian cancer-associated serum CA125

Cancer antigen 125 (CA125) is a widely used biomarker in monitoring of epithelial ovarian cancer (EOC). Due to insufficient cancer specificity of CA125, its diagnostic use is severely compromised. Abnormal glycosylation of CA125 is a unique feature of ovarian cancer cells and could improve differential diagnosis of the disease. Here we describe the development of a quantitative lateral flow immunoassay (LFIA) of aberrantly glycosylated CA125 which is widely superior to the conventional CA125 immunoassay (CA125IA). With a 30 min read-out time, the LFIA showed 72% sensitivity, at 98% specificity using diagnostically challenging samples with marginally elevated CA125 (35–200 U/mL), in comparison to 16% sensitivity with the CA125IA. We envision the clinical use of the developed LFIA to be based on the substantially enhanced disease specificity against the many benign conditions confounding the diagnostic evaluation and against other cancers.

Sherif Bayoumy et al. report a lateral flow immunoassay (LFIA) to quantify aberrantly glycosylated CA125 to diagnose epithelial ovarian cancer. Their method has a 30-minute read-out time, high sensitivity and specificity, and can distinguish ovarian cancer from benign endometriosis and other cancers.

Abstract 4383: Inferring transcription activity changes from copy-number and expression data of longitudinally sampled high-grade serous ovarian cancer tumors

To predict patient response and optimal treatment strategies, we present models for integrating copy-number and expression data sampled longitudinally in high-grade serous ovarian cancer.

Experimental procedures:

We analyzed 91 prospectively collected samples from 60 high-serous ovarian cancer patients, collected before and after chemotherapy. Whole-genome and/or whole-transcriptome sequencing was performed on each sample, in order to quantify copy-number profiles and the transcriptomic activity. Additionally, 235 ovarian cancer samples containing both whole-genome and whole-transcriptome data from primary tumors of the The Cancer Genome Atlas (TCGA) cohort were used for validation.

Results:

Chemotherapy exerts both microenvironmental and phenotypic changes on the patient tumors, which manifest in systematic variation in the sequenced profiles. Copy-numbers are often adjusted for a normal population, whereas transcriptomes are not. We report here a novel computational method to adjust the expression data and show that this improves the association between expression profiles and patient survival.

Using the adjusted expression data, we constructed co-expression modules for 473 transcription factors (TFs), whose DNA recognition motif is enriched in the upstream sequences of their coexpressed genes, and used a network inference procedure to predict the latent TF activity by modeling the relationships between copy-number and expression data, and the latent TF activity. Compared to expression data, the advantage is that the model integrates information from the (regulatory-wise) neighboring copy-number alterations and expression data.

With the above analysis, we identified various TFs whose predicted activity significantly differs between patient groups, such as good/poor treatment response and between the treatment naive and relapsed samples. Several TFs, such as PPAR-alpha, EPAS-1, ELF-1, and GATA-3 were validated to have a similar, significant association between their predicted activity and patient survival in the TCGA cohort.

Conclusions:

Our methodology allows quantitative estimation of pathway and TF activity in individual patient samples, which facilitates analysis and comparison of patient tumor evolution during the treatment. The identified TFs might confer sensitivity/resistance chemotherapy, and, as shown, allow better predicting patient survival. Consequently, our results allow ranking putative intervention strategies for overcoming ovarian cancer chemoresistance in future validation experiments.

Citation Format: Antti Häkkinen, Kaiyang Zhang, Johanna Hynninen, Sakari Hietanen, Kaisa Huhtinen, Olli Carpén, Rainer Lehtonen, Sampsa Hautaniemi. Inferring transcription activity changes from copy-number and expression data of longitudinally sampled high-grade serous ovarian cancer tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4383.

Abstract A60: Phylogenetic analyses reveal variable patterns of tumor evolution in HGSOC

High-grade serous ovarian cancer (HGSOC) is the most common and difficult to treat ovarian cancer subtype. HGSOC is diagnosed typically at late stage when it has already metastasized to many tissues in peritoneal cavity. In order to gain understanding of ovarian cancer evolution and reasons for chemoresistance, patients’ sequencing and clinical data were extensively analyzed.

We studied 124 cancerous samples from 30 HGSOC patients and sequenced whole genomes from multiple tissues collected at diagnosis (N=92), interval debulking surgery (N=17), and relapse (N=15), and in addition deep sequencing data (600 genes) from seven patients with longitudinal circulating tumor DNA (ctDNA). Subclones were identified using somatic mutations and copy number variants (CNV). Patients were divided into three primary therapy response groups (poor, intermediate, and good) using platinum free interval (PFI), primary therapy outcome, and residual tumor size after surgery. The poor response group consisted of patients having progressive disease. Phylogenetic analysis revealed clearly distinct evolutionary models in HGSOC. Briefly, patients can be first divided into two main groups based on genetic diversity between tissues at diagnosis and secondly into three subgroups by comparing them to patients’ relapse samples affected by chemotherapy. In our study 70% of patients fall into the model displaying high genetic diversity between tissues. Although genetic diversity did not correlate with clinical outcome, the number of subclones differed significantly between primary therapy response groups (ANOVA, p=0.013): good outcome patients had more subclones. Relapse or interval stage samples were available from ten patients. Four of them displayed static pattern, continuing the low genetic diversity detected at diagnosis. In this evolution model, subclonal composition is very similar in all the samples regardless of tissue or treatment stage. In the six other patients, we identified models with a) complete subclonal turnover (N=2), b) accumulation of novel mutations (N=2), or c) mixed pattern (N=2). Accumulation of novel mutations in the two patients (PFI 6.0 and 2.7 months) may result from the defective homologous recombination machinery identified by relapse-specific mutational signature (COSMIC signature SBS3). As a common feature of metastasis, evidence of polyclonal seeding was detected in almost all the patients. HGSOC tumors exhibit multiple distinct models of evolution. The most patients are highly genetically different. However, in a quarter of the patients tumors were quite static at diagnosis and half of them remained static even after chemotherapy despite obvious selection pressure. In the majority of cases, the largest number of changes were detected once influenced to chemotherapy. Because of inter-tissue heterogeneity and diverging nature of HGSOC on-time samples, for example through ctDNA, are needed to find optimal drug combinations for this moving target.

Citation Format: Jaana Oikkonen, Nil Campamà Sanz, Antti Häkkinen, Yilin Li, Ingrid Schulman, Mikko Kivikoski, Kaisa Huhtinen, Sakari Hietanen, Seija E. Grénman, Johanna Hynninen, Rainer Lehtonen, Sampsa Hautaniemi. Phylogenetic analyses reveal variable patterns of tumor evolution in HGSOC [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A60.

Abstract A40: Singling out tumor heterogeneity and chemoresistance in high-grade serous ovarian cancer

Tumor heterogeneity in high-grade serous ovarian cancer (HGSOC) stems from highly variable copy number changes that lack shared actionable drug targets and contribute to inevitable recurrence and death. To unveil the vast heterogeneity in HGSOC, and understand the molecular changes that occur during chemotherapy, we analyzed single-cell transcriptomes of 49 dissociated HGSOC tumor or ascites specimens, along with six normal postmenopausal fimbria/tuba specimens as controls. This set contains 13 pairs of samples from patients who underwent neoadjuvant chemotherapy, taken before treatment (primary), and after three cycles of standard carboplatin-paclitaxel chemotherapy (interval). Clustering single-cell transcriptomes based on acknowledged cell type markers revealed epithelial cancer cells, as well as diverse stromal and immune cell types. The cell type proportions displayed high variability across HGSOC tumors, intriguingly with lowest tumor purity in patients with short platinum-free interval. To identify the impact of chemotherapy on transcriptional programs, we extracted shared transcriptomic differences in the cancer cells of seven primary-interval pairs. Regardless of the clinical response, three cycles of chemotherapy induced an oxidative stress response program that inhibits apoptosis, while inducing genes involved in MHC II antigen presentation to T helper cells. Next, to study how cell states change during chemotherapy, we ordered the cells in pseudotime based on their transcriptomic similarity, revealing a mixture of primary and interval cells in all but two primary-interval pairs. Furthermore, based on inferred copy number analysis, we estimate that genomic differences contribute variably, between &lt;1% to &gt;20%, to the overall transcriptomic differences between the primary and interval pairs. These results suggest that pre- and post-chemotherapy states are not completely separate and that genomic evolution has a highly variable effect on the state differences, providing support for an intrinsic chemoresistance model with genomic and nongenomic components. To further the understanding of intrinsic resistance, we next focused on patients’ clinical response mechanisms in HGSOC cancer cells. Genes encoding well-known serum markers of HGSOC, WFDC2 and MUC16, were expressed at higher levels in primary specimens of patients with incomplete response, whereas patients with complete response displayed higher expression of genes related to chromatin repression/heterochromatin. Finally, we focused on tumor resectability to understand the transcriptomic patterns underlying HGSOC metastasis. Already prior to chemotherapy, patients with residual disease showed induced FOXO3-driven regulon linked to quiescence, stress resistance, and stemness, whereas patients with no residual disease express increased level of E2F1/DP1-driven regulon linked to BRCAness, high proliferation, and high metabolic rate.

Citation Format: Erdogan Pekcan Erkan, Jun Dai, Kaiyang Zhang, Katja Kaipio, Tarja Lamminen, Naziha Mansuri, Lasse Suominen, Amjad Alkodsi, Kaisa Huhtinen, Sakari Hietanen, Johanna Hynninen, Seija Grénman, Olli Carpén, Sampsa Hautaniemi, Anna Vähärautio. Singling out tumor heterogeneity and chemoresistance in high-grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A40.

Abstract A59: RNA-seq analysis of high-grade serous ovarian cancer patients before and after chemotherapy reveals chemoresistance-associated genes and pathways

Introduction: To identify genes and pathways that drive platinum-taxane resistance in high-grade serous ovarian cancer (HGSOC), we analyzed 108 samples subjected to RNA-seq before and after chemotherapy.

Experimental Procedure: We collected prospectively 108 tissue samples from various anatomic locations (omentum, ovary, mesothelium, peritoneum) for 53 HGSOC patients with high enough tumor purity (&gt;25%) and follow-up information to calculate platinum free interval (PFI). These samples were subjected to RNA-seq to obtain gene expression data for known protein coding genes. Additionally, data from 16,826 samples (cells) with single-cell RNA-seq were used in the decomposition analysis to overcome cell heterogeneity in the samples. For validation we used 306 The Cancer Genome Atlas (TCGA) HGSOC samples that were analyzed with the decompose algorithm. Differential expressions for selected resistance associated genes were validated with immunohistochemistry (IHC).

Results: We examined firstly whether gene expressions values are systematically influenced by anatomic location of the samples and chemotherapy. Our results show that bias due to anatomic locations can be controlled by relatively simple computational adjusting. However, chemotherapy-treated samples have significantly lower tumor purity than treatment-naive samples and samples have varying cell compositions. We developed a computational decomposition method to correct these biases. Secondly, we compared gene expression values of cancer cells between 1) well and poor responding patients, and 2) before and after chemotherapy followed by pathway analysis. We identified several genes that were significantly upregulated in the poor-responder group, such as FOXK1 and FBXO32, which also had significant survival association in the TCGA cohort. Our results highlight genes whose expression values are significantly enriched after chemotherapy, such as BTG2, CITED2, CTGF, FOS, DUSP1, and EGR1, which have been shown to promote resistance to platinum or paclitaxel in HGSOC or other cancers. In addition to these known chemoresistant-associated genes, we identified several hitherto unknown genes and validated them with IHC. Pathway analysis revealed actionable targets in the B-cell receptor and MAPK signaling pathways, which were the most significant enriched signaling pathways after chemotherapy.

Conclusions: We have shown that successful comparison of gene expression values before and after chemotherapy requires heavy computational correction of the strong and systematic bias caused by chemotherapy and tumor heterogeneity. To overcome these biases, we have developed a novel decomposition algorithm. This method allows to obtain reliable data for the subsequent analyses. The gene expression analyses herein identified several genes and pathways that play central roles in chemoresistance and are rational targets for overcoming platinum-taxane resistance in HGSOC.

Citation Format: Sanaz Jamalzadeh, Kaiyang Zhang, Antti Häkkinen, Kaisa Huhtinen, Johanna Hynninen, Noora Andersson, Naziha Mansuri, Olli Carpén, Erkan Erdogan, Jun Dai, Anna Vähärautio, Sakari Hietanen, Jaana Oikkonen, Rainer Lehtonen, Sampsa Hautaniemi. RNA-seq analysis of high-grade serous ovarian cancer patients before and after chemotherapy reveals chemoresistance-associated genes and pathways [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A59.

A longitudinal analysis of CA125 glycoforms in the monitoring and follow up of high grade serous ovarian cancer

OBJECTIVE

Cancer antigen 125 (CA125) is generally considered the gold standard of biomarkers in the diagnosis and monitoring of high grade serous ovarian carcinoma (HGSC). We recently reported, that two CA125 glycoforms (CA125-STn and CA125-MGL) have a high specificity to HGSC and further hypothesized, that these cancer specific glycoforms are feasible candidates as biomarkers in HGSC treatment and follow up.

METHODS

Our cohort consisted of 122 patients diagnosed with HGSC. Serum samples were collected longitudinally at the time of diagnosis, during treatment and follow up. Serum levels of CA125, CA125-STn and CA125-MGL were determined and compared or correlated with different end points (tumor load assessed intraoperatively, residual disease, treatment response, progression free survival).

RESULTS

Serum CA125-STn levels at diagnosis differentiated patients with low tumor load and high tumor load (p = 0,030), indicating a favorable detection of tumor volume. Similarly, the CA125-STn levels at diagnosis were significantly lower in patients with subsequent complete cytoreduction than in patients with suboptimal cytoreduction (p = 0,025). Conventional CA125 did not differentiate these patients (p = 0,363 and p = 0,154). The CA125-STn nadir value predicted the progression free survival of patients. The detection of disease relapse was improved with CA125-STn, which presented higher fold increase in 80,0% of patients and earlier increase in 37,0% of patients.

CONCLUSIONS

CA125-STn showed promise as a useful biomarker in the monitoring and follow up of patients with HGSC utilizing a robust and affordable technique. Our findings are topical as a suitable indicator of tumor load facilitates patient selection in an era of new targeted therapies.

ALDH1A1-related stemness in high-grade serous ovarian cancer is a negative prognostic indicator but potentially targetable by EGFR/mTOR-PI3K/aurora kinase inhibitors

Poor chemotherapy response remains a major treatment challenge for high-grade serous ovarian cancer (HGSC). Cancer stem cells are the major contributors to relapse and treatment failure as they can survive conventional therapy. Our objectives were to characterise stemness features in primary patient-derived cell lines, correlate stemness markers with clinical outcome and test the response of our cells to both conventional and exploratory drugs. Tissue and ascites samples, treatment-naive and/or after neoadjuvant chemotherapy, were prospectively collected. Primary cancer cells, cultured under conditions favouring either adherent or spheroid growth, were tested for stemness markers; the same markers were analysed in tissue and correlated with chemotherapy response and survival. Drug sensitivity and resistance testing was performed with 306 oncology compounds. Spheroid growth condition HGSC cells showed increased stemness marker expression (including aldehyde dehydrogenase isoform I; ALDH1A1) as compared with adherent growth condition cells, and increased resistance to platinum and taxane. A set of eight stemness markers separated treatment-naive tumours into two clusters and identified a distinct subgroup of HGSC with enriched stemness features. Expression of ALDH1A1, but not most other stemness markers, was increased after neoadjuvant chemotherapy and its expression in treatment-naive tumours correlated with chemoresistance and reduced survival. In drug sensitivity and resistance testing, five compounds, including two PI3K-mTOR inhibitors, demonstrated significant activity in both cell culture conditions. Thirteen compounds, including EGFR, PI3K-mTOR and aurora kinase inhibitors, were more toxic to spheroid cells than adherent cells. Our results identify stemness markers in HGSC that are associated with a decreased response to conventional chemotherapy and reduced survival if expressed by treatment-naive tumours. EGFR, mTOR-PI3K and aurora kinase inhibitors are candidates for targeting this cell population. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Abstract GMM-043: CTDNA PROFILING TO PREDICT PROGNOSIS AND OPTIMIZE TREATMENT IN HIGH-GRADE SEROUS OVARIAN CANCER

Tumor cells leak their DNA into the blood stream, which allows detection of tumor mutations and copy number variants from circulating tumor DNA (ctDNA) from plasma samples. These variants offer a dynamic “molecular snapshot” to the changing landscape of genomic events occurring during tumor treatment and progression. Our aim is to translate ctDNA profiling into clinical benefit in patients with high-grade serous ovarian cancer (HGSOC).

We used a comprehensive cancer-specific sequencing panel of over 500 genes to identify mutations and copy-number alterations (CNA) in ctDNA from plasma. We collected 78 plasma samples in 12 patients: at pre-treatment, primary treatment, follow-up and possible progression. For each patient, we also collected tissue and ascites samples (from 1-4 different time points per patient, totally 21 samples) and a white blood cell sample for germline variant detection. From variation detected in ctDNA, we identified clinically relevant information to predict prognosis and detect actionable genomic alterations that could be used to target treatment.

After extensive filtering of non-somatic mutations, we detected high concordance between ctDNA and tumor tissue samples: 77% of the mutations detected in ctDNA were also detected in tumor tissue samples. Mean correlation between CNAs detected in plasma versus tissue was also high, 0.7.

We identified several actionable mutations and CNAs. For example, we identified ERBB2 amplification in pre-treatment ctDNA in a poor-responding patient (platinum free interval (PFI) 5 months). The HER2 over-expression was validated in interval tumor tissue sample with immunohistochemistry and in-situ hybridization. Based on these results, the patient was treated with trastuzumab combined with reduce-dose carboplatin and dose-dense paclitaxel during disease progression, which yielded promising clinical response. In two other patients, mTOR pathway activation was predicted based on mutations detected in ctDNA. In both patients, the activation was validated with immunohistochemistry. These patients could benefit from mTOR inhibitors in case of disease progression. These identified clinically relevant variants illustrate the clinical value of ctDNA in the treatment of HGSOC patients.

Overall, patients with longer PFIs showed fast response to chemotherapy: ctDNA level was considerably reduced and mutational composition changed after first cycles of chemotherapy. Contrary, the poor-responding patients with PFI less than 12 months showed failure to drop ctDNA level after start of chemotherapy, smaller changes in mutational composition during primary treatment and higher number of detected mutations.

The early prognosis prediction in combination with identification of clinically relevant variants can allow window of opportunity to treat poor-prognosis patients even before relapse. Additionally, ctDNA allows detection of changes in mutational composition during treatment that can reveal subclonal selection which cannot be covered by single biopsies.

Citation Format: Jaana Oikkonen, Kaiyang Zhang, Liina Salminen, Kaisa Huhtinen, Ingrid Schulman, Noora Andersson, Olli Carpén, Sakari Hietanen, Seija Grénman, Rainer Lehtonen, Johanna Hynninen, Anniina Färkkilä, Sampsa Hautaniemi. CTDNA PROFILING TO PREDICT PROGNOSIS AND OPTIMIZE TREATMENT IN HIGH-GRADE SEROUS OVARIAN CANCER [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr GMM-043.

Prospective Longitudinal ctDNA Workflow Reveals Clinically Actionable Alterations in Ovarian Cancer

PURPOSE

Circulating tumor DNA (ctDNA) detection is a minimally invasive technique that offers dynamic molecular snapshots of genomic alterations in cancer. Although ctDNA markers can be used for early detection of cancers or for monitoring treatment efficacy, the value of ctDNA in guiding treatment decisions in solid cancers is controversial. Here, we monitored ctDNA to detect clinically actionable alterations during treatment of high-grade serous ovarian cancer, the most common and aggressive form of epithelial ovarian cancer with a 5-year survival rate of 43%.

PATIENTS AND METHODS

We implemented a clinical ctDNA workflow to detect clinically actionable alterations in more than 500 cancer-related genes. We applied the workflow to a prospective cohort consisting of 78 ctDNA samples from 12 patients with high-grade serous ovarian cancer before, during, and after treatment. These longitudinal data sets were analyzed using our open-access ctDNA-tailored bioinformatics analysis pipeline and in-house Translational Oncology Knowledgebase to detect clinically actionable genomic alterations. The alterations were ranked according to the European Society for Medical Oncology scale for clinical actionability of molecular targets.

RESULTS

Our results show good concordance of mutations and copy number alterations in ctDNA and tumor samples, and alterations associated with clinically available drugs were detected in seven patients (58%). Treatment of one chemoresistant patient was changed on the basis of detection of ERBB2 amplification, and this ctDNA-guided decision was followed by significant tumor shrinkage and complete normalization of the cancer antigen 125 tumor marker.

CONCLUSION

Our results demonstrate a proof of concept for using ctDNA to guide clinical decisions. Furthermore, our results show that longitudinal ctDNA samples can be used to identify poor-responding patients after first cycles of chemotherapy. We provide what we believe to be the first comprehensive, open-source ctDNA workflow for detecting clinically actionable alterations in solid cancers.

Secreted frizzled-related protein 2 (SFRP2) expression promotes lesion proliferation via canonical WNT signaling and indicates lesion borders in extraovarian endometriosis

STUDY QUESTION

What is the role of SFRP2 in endometriosis?

SUMMARY ANSWER

SFRP2 acts as a canonical WNT/CTNNB1 signaling agonist in endometriosis, regulating endometriosis lesion growth and indicating endometriosis lesion borders together with CTNNB1 (also known as beta catenin).

WHAT IS KNOWN ALREADY

Endometriosis is a common, chronic disease that affects women of reproductive age, causing pain and infertility, and has significant economic impact on national health systems. Despite extensive research, the pathogenesis of endometriosis is poorly understood, and targeted medical treatments are lacking. WNT signaling is dysregulated in various human diseases, but its role in extraovarian endometriosis has not been fully elucidated.

STUDY DESIGN, SIZE, DURATION

We evaluated the significance of WNT signaling, and especially secreted frizzled-related protein 2 (SFRP2), in extraovarian endometriosis, including peritoneal and deep lesions. The study design was based on a cohort of clinical samples collected by laparoscopy or curettage and questionnaire data from healthy controls and endometriosis patients.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Global gene expression analysis in human endometrium (n = 104) and endometriosis (n = 177) specimens from 47 healthy controls and 103 endometriosis patients was followed by bioinformatics and supportive qPCR analyses. Immunohistochemistry, Western blotting, primary cell culture and siRNA knockdown approaches were used to validate the findings.

MAIN RESULTS AND THE ROLE OF CHANCE

Among the 220 WNT signaling and CTNNB1 target genes analysed, 184 genes showed differential expression in extraovarian endometriosis (P < 0.05) compared with endometrium tissue, including SFRP2 and CTNNB1. Menstrual cycle-dependent regulation of WNT genes observed in the endometrium was lost in endometriosis lesions, as shown by hierarchical clustering. Immunohistochemical analysis indicated that SFRP2 and CTNNB1 are novel endometriosis lesion border markers, complementing immunostaining for the known marker CD10 (also known as MME). SFRP2 and CTNNB1 localized similarly in both the epithelium and stroma of extraovarian endometriosis tissue, and interestingly, both also indicated an additional distant lesion border, suggesting that WNT signaling is altered in the endometriosis stroma beyond the primary border indicated by the known marker CD10. SFRP2 expression was positively associated with pain symptoms experienced by patients (P < 0.05), and functional loss of SFRP2 in extraovarian endometriosis primary cell cultures resulted in decreased cell proliferation (P < 0.05) associated with reduced CTNNB1 protein expression (P = 0.05).

LIMITATIONS REASONS FOR CAUTION

SFRP2 and CTNNB1 improved extraovarian endometriosis lesion border detection in a relatively small cohort (n = 20), although larger studies with different endometriosis subtypes in variable cycle phases and under hormonal medication are required.

WIDER IMPLICATIONS OF THE FINDINGS

The highly expressed SFRP2 and CTNNB1 improve endometriosis lesion border detection, which can have clinical implications for better visualization of endometriosis lesions over CD10. Furthermore, SFRP2 acts as a canonical WNT/CTNNB1 signaling agonist in endometriosis and positively regulates endometriosis lesion growth, suggesting that the WNT pathway may be an important therapeutic target for endometriosis.

STUDY FUNDING/COMPETING INTEREST(S)

This study was funded by the Academy of Finland and by Tekes: Finnish Funding Agency for Innovation. The authors have no conflict of interest to declare.

Abstract B40: High-throughput screening of new potential targets for high-grade serous ovarian cancer treatment

High-grade serous ovarian cancer (HGSOC) is the most common cause of gynecologic-cancer-associated death. Although HGSOC is initially extremely sensitive to platinum-based chemotherapy, relapse and progression to chemotherapy resistance are frequently seen, resulting in the low 5-year survival rate of this disease. Therefore, we aim to establish a feasible methodology that combines genome editing and single-cell RNA-seq to high-throughput screen new potential targets that could be utilized alone or combined with platinum for HGSOC treatment. Firstly, we constructed several inducible Cas9-expressed HGSOC cell lines, including both platinum-sensitive and -resistant cells. Secondly, we transduced these cell lines with a pooled sgRNA lentivirus consisting of 105 non-target scrambled sgRNAs and sgRNAs against 188 genes (10 sgRNAs per gene) that are currently targets of FDA/EMA approved drugs or drugs undergoing clinical trials in ovarian cancer treatment. Our analysis of multiple HGSOC dissociated tumors by single-cell RNA-seq has revealed intertumoral heterogeneity in expression of these drug targets in vivo. The majority of these 188 genes, approximately two thirds, are expressed in low level in most epithelial ovarian cancer (EOC) cells. Only 4 genes (AKT1, IL6, C1QA, INHBA) show relatively high expression, and only in a small subset of EOC cells. Also, the remaining drug target genes that are expressed show intertumoral heterogeneity, e.g., high expression of PARP-1 in tumors that are potentially deficient in homologous recombination repair. To elucidate the functionality of these drug targets, we will next analyze the transcriptomic effects of specific gene CRISPR/Cas9 knockouts in these HGSOC cell lines by droplet-based single-cell RNA-seq. From the data, we will compare the differences between platinum-sensitive and -resistant cell lines after the gene knockouts to identify the correlations between specific genetic perturbations and platinum resistance. As a future perspective, we will continue optimizing our platform for screening other potential targets. Overall, this study provides a comprehensive and unbiased approach for potential HGSOC target screening.

Note: This abstract was not presented at the conference.

Citation Format: Jun Dai, Erdogan Pekcan Erkan, Kaiyang Zhang, Katja Kaipio, Tarja Lamminen, Kaisa Huhtinen, Johanna Hynninen, Seija Grenman, Olli Mikael Carpen, Sampsa Hautaniemi, Anna Vähärautio. High-throughput screening of new potential targets for high-grade serous ovarian cancer treatment. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr B40.