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

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

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

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

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.

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.

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 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.

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.

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.

Abstract 2059: AI - optimized genomic homologous recombination deficiency test (HRDScar) to predict platinum and PARP inhibitor responses in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSC) is the most common and most lethal subtype of ovarian cancer. More than half of the HGSCs are defective in Homologous Recombination DNA repair (HRD), and sensitive to Poly-ADP Ribose Polymerase (PARP) inhibitors. Recently, a genomic HRD test based on three types of genomic scarring events (Large scale transitions; LST, Telomeric Allelic Imbalance TAI, Loss of Heterozygosity LOH) was shown to predict which patients benefit the most from PARP inhibitors. The HRD test, however, was originally designed and optimized in breast cancer, and therefore the details of genomic scarring events occurring in ovarian cancers are unknown.

To characterize the genomic scarring events and define an optimal cut-off for HRDScar biomarker in ovarian cancer, we are using large publicly available dataset from the TCGA. We selected 103 HRD samples based on somatic and germline mutations, gene deletions or hypermethylation in the BRCA1/2 and RAD51 paralog genes, and 34 HR proficient (HRP) samples without any mutation, deletion or hypermethylation of the HR genes. To identify the detailed features of LOH, LST and TAI scarring events, we employed state-of-the-art machine-learning algorithm and statistics to optimally separate the HRD-samples from HRP in the TCGA SNP array dataset. Our new optimized genomic footprints and cut-offs showed improved accuracy to separate HRD from HRP compared to the previous algorithm (accuracy of 0.89 vs 0.79). The optimized HRDScar showed reliable performance in NGS-derived data and correlated with mutational signature 3 (p=2.2e-16, r2=0.5). Interestingly, the HRDScar levels also positively correlated with an HRD score derived from an ex-vivo RAD51-based functional assay for HRD performed in the prospective HERCULES samples (n=72). Using two independent validation cohorts (PCAWG, HERCULES), our optimized HRDScar more accurately predicted progression-free survival (PFS) and overall survival (OS) when compared to previous algorithms. Importantly, improved prediction of PFS was detected especially in patients without BRCA1/2 alterations (p= 1.9e-04, HR=0.70). We are in the process of analyzing HRDScar from a clinical trial involving PARP inhibitor Niraparib (TOPACIO/Keynote-162 (NCT02657889)) enabling direct association of the HRDScar to clinical outcomes. In conclusion, HRDScar shows promise as a fully optimized algorithm that can be used for improved selection of patients for PARP inhibitor therapies in HGSC.

Citation Format: Fernando Perez-Villatoro, Jaana Oikkonen, Manuela Tumiati, Julia Casado, Sakari Hietanen, Johanna Hynninen, Elizabeth P. Garcia, Panagiotis Konstantinopoulos, Sampsa Hautaniemi, Liisa Kauppi, Anniina Färkkilä. AI - optimized genomic homologous recombination deficiency test (HRDScar) to predict platinum and PARP inhibitor responses in high-grade serous ovarian cancer [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 2059.

Heterogeneity and Clonal Evolution of Acquired PARP Inhibitor Resistance in TP53- and BRCA1-Deficient Cells

Homologous recombination (HR)-deficient cancers are sensitive to poly-ADP ribose polymerase inhibitors (PARPi), which have shown clinical efficacy in the treatment of high-grade serous cancers (HGSC). However, the majority of patients will relapse, and acquired PARPi resistance is emerging as a pressing clinical problem. Here we generated seven single-cell clones with acquired PARPi resistance derived from a PARPi-sensitive TP53 ^-/- and BRCA1 ^-/- epithelial cell line generated using CRISPR/Cas9. These clones showed diverse resistance mechanisms, and some clones presented with multiple mechanisms of resistance at the same time. Genomic analysis of the clones revealed unique transcriptional and mutational profiles and increased genomic instability in comparison with a PARPi-sensitive cell line. Clonal evolutionary analyses suggested that acquired PARPi resistance arose via clonal selection from an intrinsically unstable and heterogenous cell population in the sensitive cell line, which contained preexisting drug-tolerant cells. Similarly, clonal and spatial heterogeneity in tumor biopsies from a clinical patient with BRCA1-mutant HGSC with acquired PARPi resistance was observed. In an imaging-based drug screening, the clones showed heterogenous responses to targeted therapeutic agents, indicating that not all PARPi-resistant clones can be targeted with just one therapy. Furthermore, PARPi-resistant clones showed mechanism-dependent vulnerabilities to the selected agents, demonstrating that a deeper understanding on the mechanisms of resistance could lead to improved targeting and biomarkers for HGSC with acquired PARPi resistance. SIGNIFICANCE: This study shows that BRCA1-deficient cells can give rise to multiple genomically and functionally heterogenous PARPi-resistant clones, which are associated with various vulnerabilities that can be targeted in a mechanism-specific manner.

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.

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 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.

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.

Abstract PR08: Longitudinal sampling of ctDNA reveals actionable mutations to optimize treatment of patients with high-grade serous ovarian cancer

Tumor cells leak their DNA into the blood stream, which allows us to use plasma sample from a patient to measure biomarker levels. In particular, circulating tumor DNA (ctDNA) sampling together with next-generation sequencing technologies provide a rapid and noninvasive test for quantifying tumor response to a treatment as well as finding potentially actionable mutations. The main objective of our study was to use ctDNA to establish a therapeutic window for targeting potentially actionable mutations to optimize the treatment of high-grade serous ovarian cancer (HGSOC) patients.

We employed a targeted sequencing panel of 508 clinically annotated cancer genes to screen for actionable copy-number variations (CNV) and single-nucleotide variants (SNV) in 56 plasma and 20 fresh tumor samples from 13 patients with stage IIB-IVB HGSOC treated at the Turku University Hospital, Finland. All patients were surgically debulked and had received standard first-line carboplatin and paclitaxel chemotherapy. We analyzed longitudinal samples (from 3-6 time points per patient) from 11 patients during primary therapy, and from two patients with multiple (two and three samples per patient) relapsed disease. DNA isolated from tumor tissue and plasma was analyzed for genetic alterations by targeted deep-sequencing. White blood cell DNA was used as germline controls. Pathogenic germline mutations in 14 known ovarian cancer susceptibility genes were evaluated with CADD annotation framework and ClinVar database. Minimum requirements for passed somatic SNVs were CADD phred score 10, sequencing depth 100 (ctDNA) or 30 reads (tumor and blood), variant read count 4 or frequency 0.001. Variants detected in blood with &gt; 2 reads were excluded. Additionally, a variant that passed filtering in at least one sample of a patient was included, regardless of threshold, if present in any other specimen. Thresholds of &lt; 0.7 and &gt; 4 copies were used as functionally relevant losses and gains, respectively.

Clinically relevant germline pathogenic mutations in BRCA2, ATR, APC, and RB1 genes were identified from blood samples of five (38%) patients. The preoperative samples were also characterized by the highest somatic mutation burden, with a median total variant allele frequency (VAF) of 0.16 (range 0.02-0.77). Importantly, clinically relevant CNVs were detected in preoperative ctDNA of 6 (46%) patients, in potentially targetable driver genes such as ERBB2, PIK3CA, and CDK12.

In six patients undergoing neoadjuvant chemotherapy (NACT), we noted a significant decrease in total ctDNA mutation burden during treatment, consistent with a drop in CA-125 levels. Interestingly, the levels of CNV counts increased in ctDNA during NACT in two patients, which associated with improved response to chemotherapy. During adjuvant treatment after debulking surgery, potentially actionable mutations were detected in all patients, with median total VAF of 0.03 (range 0.006-0.43). Importantly, in patients with no macroscopic residual disease, we detected a median of 2.5 (range 1-21) mutations in adjuvant treatment samples, indicating a molecularly persistent disease. Further, a subset of these alterations in, e.g., FANCA and PRCKB persisted during adjuvant treatment, revealing a potential therapeutic window for targeted treatments. Finally, two patients with progressive disease were characterized by predominantly either ctDNA gains or losses. Further, potentially actionable mutations in, e.g., TNXRD1, which sensitizes to AKT inhibitors, could be identified and tracked during disease progression.

Taken together, longitudinal analysis of a panel-based ctDNA targeted sequencing can reliably detect very low VAF alterations, which can be used to identify and track actionable genomic alterations. Thus, ctDNA analysis can open a therapeutic window to target molecular residual disease in patients with newly diagnosed and advanced HGSOC.

This abstract is also being presented as Poster B06.

Citation Format: Kaiyang Zhang, Liina Salminen, Jaana Oikkonen, Kaisa Huhtinen, Johanna Hynninen, Seija Grénman, Sakari Hietanen, Rainer Lehtonen, Anniina Färkkilä, Sampsa Hautaniemi. Longitudinal sampling of ctDNA reveals actionable mutations to optimize treatment of patients with high-grade serous ovarian cancer. [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 PR08.

Abstract 5344: Phylogenetic and signature analyses predict treatment response in high-grade serous ovarian cancer

Background. High-grade serous ovarian cancer (HGSOC) is a heterogeneous cancer where majority of the patients will eventually relapse. Phylogenetic analysis of longitudinal samples can reveal mechanisms leading to chemoresistance in different subclones. Companied with signature analysis timing of major mutations can be estimated. These methods can reveal the origin of the resistance mechanisms and bring knowledge about the heterogeneity in the surviving subclones.

Methods. We employed whole genome sequencing in 48 tumor tissue samples from 9 patients with stage IIB -IVB HGSOC treated at the Turku University Hospital, Finland. DNA from 3-7 tumor tissues at diagnosis (debulking surgery or laparoscopy) and interval debulking surgery (NACT treated patients) and/or relapse from each patient was sequenced with coverage of 30-100x. The mutations were detected with MuTect2 and HaplotypeCaller and copy number alterations with Ascat, excluding germline variation using a blood control. The subclonal structures were identified with PyClone and ClonEvol using maximum of 3000 mutations in each patient. Phylogenetic trees explaining largest proportion of the variations were used. Signatures were fitted with the 30 consensus signatures from COSMIC for each tumor sample as well as for major subclones.

Results. Each patient was characterized with 7-15 variant clusters (subclones). Largest divergence was detected in ovaries (11-49% of the mutations were ovary spesific) and lymph nodes compared to other tissues. Even left and right ovary can be very different from each other and ovaries exhibit earlier spreading than other sampled sites. Other tissues were spread from clones detected in the ovaries. Constant mutation rate or higher mutation rate during the treatment could not be explained by the detected number of variants between time points.

Early clonal BRCA (COSMIC signature 3) with high contribution predicted better response to chemotherapy. Signature 3 has been associated with homologous recombination deficiency and sensitivity to platinum-based chemotherapy. High APOBEC (signature 2 and 13) associates with higher level of diversification of related branches. Patient level heterogeneity does not seem to predict outcome contrary to within sample heterogeneity which was higher in the patients with shorter survival times. Relapses contained late or early branching clones. In one poor outcome case a clone which was enriched in relapses dominated in the patient derived cell line indicating superior viability and cause of chemoresistance.

Conclusions. Cancer evolution trees improved mutation signature analyses and relieved clinically relevant differences between HGSOC patients. Early BRCA signature as well as similar signatures between subclones predicted good clinical outcomes.

Citation Format: Jaana Oikkonen, Yilin Li, Amjad Alkodsi, Olli Carpen, Kaisa Huhtinen, Sakari Hietanen, Seija E. Grenman, Rainer Lehtonen, Sampsa Hautaniemi. Phylogenetic and signature analyses predict treatment response in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5344.

Convergent evidence for the molecular basis of musical traits

To obtain aggregate evidence for the molecular basis of musical abilities and the effects of music, we integrated gene-level data from 105 published studies across multiple species including humans, songbirds and several other animals and used a convergent evidence method to prioritize the top candidate genes. Several of the identified top candidate genes like EGR1, FOS, ARC, BDNF and DUSP1 are known to be activity-dependent immediate early genes that respond to sensory and motor stimuli in the brain. Several other top candidate genes like MAPK10, SNCA, ARHGAP24, TET2, UBE2D3, FAM13A and NUDT9 are located on chromosome 4q21-q24, on the candidate genomic region for music abilities in humans. Functional annotation analyses showed the enrichment of genes involved in functions like cognition, learning, memory, neuronal excitation and apoptosis, long-term potentiation and CDK5 signaling pathway. Interestingly, all these biological functions are known to be essential processes underlying learning and memory that are also fundamental for musical abilities including recognition and production of sound. In summary, our study prioritized top candidate genes related to musical traits.

Creative Activities in Music--A Genome-Wide Linkage Analysis

Creative activities in music represent a complex cognitive function of the human brain, whose biological basis is largely unknown. In order to elucidate the biological background of creative activities in music we performed genome-wide linkage and linkage disequilibrium (LD) scans in musically experienced individuals characterised for self-reported composing, arranging and non-music related creativity. The participants consisted of 474 individuals from 79 families, and 103 sporadic individuals. We found promising evidence for linkage at 16p12.1-q12.1 for arranging (LOD 2.75, 120 cases), 4q22.1 for composing (LOD 2.15, 103 cases) and Xp11.23 for non-music related creativity (LOD 2.50, 259 cases). Surprisingly, statistically significant evidence for linkage was found for the opposite phenotype of creative activity in music (neither composing nor arranging; NCNA) at 18q21 (LOD 3.09, 149 cases), which contains cadherin genes like CDH7 and CDH19. The locus at 4q22.1 overlaps the previously identified region of musical aptitude, music perception and performance giving further support for this region as a candidate region for broad range of music-related traits. The other regions at 18q21 and 16p12.1-q12.1 are also adjacent to the previously identified loci with musical aptitude. Pathway analysis of the genes suggestively associated with composing suggested an overrepresentation of the cerebellar long-term depression pathway (LTD), which is a cellular model for synaptic plasticity. The LTD also includes cadherins and AMPA receptors, whose component GSG1L was linked to arranging. These results suggest that molecular pathways linked to memory and learning via LTD affect music-related creative behaviour. Musical creativity is a complex phenotype where a common background with musicality and intelligence has been proposed. Here, we implicate genetic regions affecting music-related creative behaviour, which also include genes with neuropsychiatric associations. We also propose a common genetic background for music-related creative behaviour and musical abilities at chromosome 4.

Association and Promoter Analysis of AVPR1A in Finnish Autism Families

The arginine vasopressin receptor 1A gene (AVPR1A) is known to affect social communication and has been reported to associate with autism in several studies. Given that the microsatellite RS1 and a few SNPs in the promoter region of the AVPR1A have repeatedly associated with several traits, including autism it is rather surprising that the molecular explanation for these associations has remained unknown, although it has been reported that the allele length of the AVPR1A microsatellites might affect disease risk. Here we carried out an extended association analysis of three microsatellites and 12 tag single nucleotide polymorphisms (SNPs) in and around the AVPR1A gene in 205 Finnish families followed by promoter analysis. FBAT version v2.0.3 was used for family-based genetic association analyses of AVPR1A microsatellites and SNPs. The nearby microsatellite RS1 was found to harbor the best association. Interestingly, there are two potentially relevant transcription factor (TF) binding sites at RS1: for MEF2C and PBX, predicted with the Match algorithm in the TRANSFAC database. Sequence variations changing the affinity of these TFs might partly explain the AVPR1A promoter region associations shown in autism.

A genome-wide linkage and association study of musical aptitude identifies loci containing genes related to inner ear development and neurocognitive functions

Humans have developed the perception, production and processing of sounds into the art of music. A genetic contribution to these skills of musical aptitude has long been suggested. We performed a genome-wide scan in 76 pedigrees (767 individuals) characterized for the ability to discriminate pitch (SP), duration (ST) and sound patterns (KMT), which are primary capacities for music perception. Using the Bayesian linkage and association approach implemented in program package KELVIN, especially designed for complex pedigrees, several single nucleotide polymorphisms (SNPs) near genes affecting the functions of the auditory pathway and neurocognitive processes were identified. The strongest association was found at 3q21.3 (rs9854612) with combined SP, ST and KMT test scores (COMB). This region is located a few dozen kilobases upstream of the GATA binding protein 2 (GATA2) gene. GATA2 regulates the development of cochlear hair cells and the inferior colliculus (IC), which are important in tonotopic mapping. The highest probability of linkage was obtained for phenotype SP at 4p14, located next to the region harboring the protocadherin 7 gene, PCDH7. Two SNPs rs13146789 and rs13109270 of PCDH7 showed strong association. PCDH7 has been suggested to play a role in cochlear and amygdaloid complexes. Functional class analysis showed that inner ear and schizophrenia-related genes were enriched inside the linked regions. This study is the first to show the importance of auditory pathway genes in musical aptitude.

Correlation between components of newly diagnosed exudative age-related macular degeneration lesion and focal retinal sensitivity

PURPOSE

To analyse lesion components determining retinal sensitivity in microperimetry in eyes with newly diagnosed exudative age-related macular degeneration (AMD).

METHODS

Visual acuity, contrast sensitivity, microperimetry, optical coherence tomography (OCT), and fluorescein (FA) and indocyanine green (ICGA) angiographies of 23 eyes of 23 patients were analysed. Central microperimetry grids with 28 test stimulus sites were automatically aligned with three-dimensional OCTs and manually aligned with angiographies. Thicknesses of the neuroretina, neuroepithelial detachment (NED), retinal pigment epithelial (RPE) elevation and subretinal tissue were measured under the 644 microperimetry stimulus sites. Areas of classic and occult choroidal neovascularizations (CNVs), subretinal and intraretinal haemorrhage, and late hyperfluorescence in ICGA were identified. The impact of the lesion components on retinal sensitivity was evaluated with correlation analysis and multivariate modelling.

RESULTS

Decreased retinal sensitivity correlated significantly with the presence of CNV, haemorrhage, subretinal tissue and RPE elevation. Out of the OCT parameters, the most important determinant of sensitivity was the thickness of RPE elevation (Spearman's rho, r = -0.202, p < 0.0001). The thicknesses of subretinal tissue (r = -0.168, p < 0.0001) and NED had weaker effects (r = -0.147, p < 0.0001), and the neuroretinal thickness remained nonsignificant. In multivariate modelling, RPE elevation and subretinal tissue in OCT, CNV membranes in angiographies and haemorrhage had the strongest impacts on retinal sensitivity.

CONCLUSION

The most important lesion components affecting retinal function were RPE elevation and subretinal tissue in OCT as well as neovascular membranes and haemorrhage in angiographies. NED and neuroretinal thickening remained less significant.

The genome-wide landscape of copy number variations in the MUSGEN study provides evidence for a founder effect in the isolated Finnish population

Here we characterized the genome-wide architecture of copy number variations (CNVs) in 286 healthy, unrelated Finnish individuals belonging to the MUSGEN study, where molecular background underlying musical aptitude and related traits are studied. By using Illumina HumanOmniExpress-12v.1.0 beadchip, we identified 5493 CNVs that were spread across 467 different cytogenetic regions, spanning a total size of 287.83 Mb (∼9.6% of the human genome). Merging the overlapping CNVs across samples resulted in 999 discrete copy number variable regions (CNVRs), of which ∼6.9% were putatively novel. The average number of CNVs per person was 20, whereas the average size of CNV per locus was 52.39 kb. Large CNVs (>1 Mb) were present in 4% of the samples. The proportion of homozygous deletions in this data set (∼12.4%) seemed to be higher when compared with three other populations. Interestingly, several CNVRs were significantly enriched in this sample set, whereas several others were totally depleted. For example, a CNVR at chr2p22.1 intersecting GALM was more common in this population (P=3.3706 × 10(-44)) than in African and other European populations. The enriched CNVRs, however, showed no significant association with music-related phenotypes. Moreover, the most common CNV locations in world's normal population cohorts (6q14.1, 11q11) were overrepresented in this population. Thus, the genome-wide CNV investigation in this Finnish sample set demonstrated features that are characteristic to isolated populations. Novel CNVRs and the functional implications of CNVs revealed in this study elucidate structural variation present in this population isolate, and may also serve as candidate gene loci for music-related traits.

Genome-wide copy number variation analysis in extended families and unrelated individuals characterized for musical aptitude and creativity in music

Music perception and practice represent complex cognitive functions of the human brain. Recently, evidence for the molecular genetic background of music related phenotypes has been obtained. In order to further elucidate the molecular background of musical phenotypes we analyzed genome wide copy number variations (CNVs) in five extended pedigrees and in 172 unrelated subjects characterized for musical aptitude and creative functions in music. Musical aptitude was defined by combination of the scores of three music tests (COMB scores): auditory structuring ability, Seashores test for pitch and for time. Data on creativity in music (herein composing, improvising and/or arranging music) was surveyed using a web-based questionnaire.

Several CNVRs containing genes that affect neurodevelopment, learning and memory were detected. A deletion at 5q31.1 covering the protocadherin-α gene cluster (Pcdha 1-9) was found co-segregating with low music test scores (COMB) in both sample sets. Pcdha is involved in neural migration, differentiation and synaptogenesis. Creativity in music was found to co-segregate with a duplication covering glucose mutarotase gene (GALM) at 2p22. GALM has influence on serotonin release and membrane trafficking of the human serotonin transporter. Interestingly, genes related to serotonergic systems have been shown to associate not only with psychiatric disorders but also with creativity and music perception. Both, Pcdha and GALM, are related to the serotonergic systems influencing cognitive and motor functions, important for music perception and practice. Finally, a 1.3 Mb duplication was identified in a subject with low COMB scores in the region previously linked with absolute pitch (AP) at 8q24. No differences in the CNV burden was detected among the high/low music test scores or creative/non-creative groups. In summary, CNVs and genes found in this study are related to cognitive functions. Our result suggests new candidate genes for music perception related traits and supports the previous results from AP study.

Association of the arginine vasopressin receptor 1A (AVPR1A) haplotypes with listening to music

Music is listened in all cultures. We hypothesize that willingness to produce and perceive sound and music is social communication that needs musical aptitude. Here, listening to music was surveyed using a web-based questionnaire and musical aptitude using the auditory structuring ability test (Karma Music test) and Carl Seashores tests for pitch and for time. Three highly polymorphic microsatellite markers (RS3, RS1 and AVR) of the arginine vasopressin receptor 1A (AVPR1A) gene, previously associated with social communication and attachment, were genotyped and analyzed in 31 Finnish families (n=437 members) using family-based association analysis. A positive association between the AVPR1A haplotype (RS1 and AVR) and active current listening to music (permuted P=0.0019) was observed. Other AVPR1A haplotype (RS3 and AVR) showed association with lifelong active listening to music (permuted P=0.0022). In addition to AVPR1A, two polymorphisms (5-HTTLPR and variable number of tandem repeat) of human serotonin transporter gene (SLC6A4), a candidate gene for many neuropsychiatric disorders and previously associated with emotional processing, were analyzed. No association between listening to music and the polymorphisms of SLC6A4 were detected. The results suggest that willingness to listen to music is related to neurobiological pathways affecting social affiliation and communication.