Advanced Stage High-grade Serous Ovarian Cancer Research Articles

Abstract 1070: Overcoming deficiencies in the early detection of high grade serous ovarian cancer: Evaluating exosomal proteins as novel biomarkers of disease

Abstract Introduction: High-grade serous ovarian cancer (HGSOC) accounts for over 75% of all epithelial ovarian cancer and has a high mortality rate due to a lack of early detection methods. Many biomarkers have been proposed; however, none have been shown to improve detection at an early stage in this patient population. The purpose of this study is to assess whether there are unique extracellular vesicle (EV) protein signatures of early-stage HGSOC that could serve as early detection biomarkers. Methods: 250 serum samples were obtained from a multi-institutional retrospective cohort of patients with all stages of HGSOC and healthy controls. LC-MS/MS and PEA of serum samples from patients with early-stage HGSOC identified differentially expressed EVs proteins in HGSOC versus controls. Tob candidate proteins are validated by ELISA. Results: We have identified the top 10 EVs candidate proteins based on their fold change and statistical significance. When comparing early-stage HGSOC and controls using ELISA, CFH, PCP, and CCNE1 exhibited the highest Area Under the Curve (AUC) values of 0.94, 0.91, and 0.83, respectively. In contrast, MUC16 (also known as CA-125) exhibited an AUC of only 0.42 in whole serum. Furthermore, MUC16 distinguished between controls and both early and advanced-stage HGSOC in EVs, while in whole serum, it was only differentially expressed between controls and advanced-stage disease. Our results demonstrate that the predictive performance of the combined biomarkers surpasses that of any individual biomarker. Further, we integrated the ten aforementioned biomarkers, deriving the optimal combination biomarker by maximizing the corresponding Sum of Harmonic Means (SHUM) function by utilizing data from all 70 patients, results showed the optimal coefficients of the biomarkers, which maximize the diagnostic accuracy for early-stage HGSOC. The overall true positive rate (TPR) of 0.943, false positive rate (FPR) of 0.000, and Mathew's correlation coefficient (MCC) were presented for both the combined biomarker approach and individual biomarkers. The results demonstrated that the predictive performance of the combined biomarkers surpassed that of any individual biomarker. Conclusion: Expression of EV-based protein biomarkers is significantly different in early-stage HGSOC compared to both control and late-stage HGSOC. This work can be readily translated to clinical use and potentially improve the early detection of HGSOC substantially. Citation Format: Michelle Lightfoot, Kalpana Deepa Priya Dorayappan, Lianbo Yu, Colin Hisey, Takahiko Sakaue, Muralidharan Anbalagan, Casey M. Cosgrove, Larry G. Maxwell, Premal Thaker, Beth Y. Karlan, David O’Malley, Raphael E. Pollock, David E. Cohn, Rajan Gogna, Selvendiran Karuppaiyah. Overcoming deficiencies in the early detection of high grade serous ovarian cancer: Evaluating exosomal proteins as novel biomarkers of disease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1070.

P53 and TLR4 expression are prognostic markers informing progression free survival of advanced stage high grade serous ovarian cancer

ObjectiveNew prognostic biomarkers, and bio-signatures, are urgently needed to facilitate a precision medicine-based approach to more effectively treat patients with high-grade serous ovarian cancer (HGSC). In this study, we analysed the expression patterns of a series of candidate protein biomarkers. MethodsThe panel of markers which included MyD88, TLR4, MAD2, PR, OR, WT1, p53, p16, CD10 and Ki67 was assessed using immunohistochemistry in a tissue microarray (TMA) cohort of n = 80 patients, composed of stage 3–4 HGSCs. Each marker was analysed for their potential to predict both overall survival (OS) and progression-free survival (PFS). ResultsTLR4 and p53 were found to be individually predictive of poorer PFS (Log Rank, p = 0.017, p = 0.030 respectively). Cox regression analysis also identified high p53 and TLR4 expression as prognostic factors for reduced PFS (p53; HR=1.785, CI=1.036–3.074, p = 0.037 and TLR4; HR=2.175, CI=1.112–4.253, p = 0.023). Multivariate forward conditional Cox regression analysis, examining all markers, identified a combined signature composed of p53 and TLR4 as prognostic for reduced PFS (p = 0.023). ConclusionCombined p53 and TLR4 marker assessment may help to aid treatment stratification for patients diagnosed with advanced-stage HGSC.

Understanding Long-Term Survival of Patients with Ovarian Cancer—The Tumor Microenvironment Comes to the Forefront

High-grade serous ovarian cancer (HGSOC) is the deadliest subtype of ovarian cancer, and most patients do not survive more than 5 years after diagnosis. Yet, for reasons that are often elusive, approximately 15% of women with advanced-stage HGSOC will survive longer than 10 years. An understanding of the biological basis of long-term survival with HGSOC may elucidate novel prognostic factors and targets for treatment. Past analyses of the clinicopathologic features of these women and genetic profiles of their tumors have not revealed a unifying explanation for their increased longevity. In this issue of Cancer Research, Ferri-Borgogno and colleagues investigate the tumor microenvironment (TME) in samples from both long- and short-term survivors using spatial transcriptomics and single-cell RNA sequencing. They found that, in metastatic tumors, various populations of cancer-associated fibroblasts (CAF) in the TME play different roles in supporting the malignant phenotype of ovarian cancer cells. Higher density of CAFs, particularly αSMA+VIM+PDGFRβ+ CAFs, was associated with lower tumor immune infiltration and short-term survival. There was also marked expression of periostin and CD36 in spatially resolved CAFs, as well as a prevalence of the APOE-LRP5 ligand-receptor pair at the tumor-stromal interface in tissue from short-term survivors. These findings suggest that, in short-term survivors, CAFs are able to more effectively promote tumorigenicity, stemness, and chemoresistance in the nearby tumor. See related article by Ferri-Borgogno et al., p. 1503.

Abstract 2865: IL4I1, IDO1 and other amino acid-metabolizing enzymes in high-grade serous ovarian cancer

Abstract Ovarian cancer is among the most lethal malignancies in women, and breakthrough immunotherapies including anti-PD-1/PD-L1 and anti-CTLA4 have thus far not been able to significantly ameliorate patient outcomes. In various tumor types, amino acid-metabolizing enzymes such as indoleamine 2,3-dioxygenase 1 (IDO1) and arginase 1 (ARG1) have been found to be among the culprits responsible for generation of an immunosuppressive tumor microenvironment. More recently, interleukin 4 induced 1 (IL4I1) was put forward as a promising anticancer drug target, whereas its expression may also contribute to resistance against IDO1 inhibition. Similar to IDO1, IL4I1 can metabolize tryptophan (Trp) resulting in the formation of AhR agonists, although phenylalanine (Phe) and tyrosine (Tyr) are also major substrates of IL4I1. Plasma and ascites (i.e., peritoneal fluid buildup) were collected from advanced-stage high-grade serous ovarian cancer (HGSOC) patients to determine whether aberrant metabolism by amino acid-metabolizing enzymes occurs in these patients and to evaluate ascites as a potential source of biomarkers related to these enzymes. Activity of the enzymes was indirectly determined through measurement of relevant amino acids and metabolites by targeted metabolomics using LC-MS/MS, while levels of secreted IL4I1 were determined by ELISA. Amino acid, metabolite and enzyme concentrations were compared to healthy control subjects and were examined for correlations with clinicopathological characteristics and clinical outcomes. Pleural effusions from non-small cell lung cancer patients were included to evaluate whether the results could be extended towards another type of cancer-related fluid buildup. Metabolism of Trp was significantly elevated in HGSOC patients compared to control subjects, likely attributable to increased IDO1 expression. Kynurenine (Kyn) levels and Kyn/Trp ratios were higher in ascites compared to plasma samples, demonstrating the value of utilizing this fluid for biomarker detection. Whereas elevated metabolism of Trp by IL4I1 could not be detected in the patients, high levels of Phe- and Tyr-derived metabolites associated with IL4I1 activity were found in their ascites. Levels of these metabolites significantly correlated with the concentration of IL4I1. Moreover, enhanced metabolism of Phe and Tyr correlated with disease stage, suggesting a role for IL4I1 in HGSOC progression. Elevated levels of IL4I1-associated metabolites were also found in the pleural effusions of a subset of non-small cell lung cancer patients, demonstrating that enhanced IL4I1 activity is not limited to ovarian cancer ascites. In conclusion, our results suggest that IL4I1 may be involved in HGSOC progression, indicating this enzyme as a potential therapeutic target. The levels of IL4I1- and IDO1-generated metabolites in ascites may additionally serve as valuable diagnostic or predictive biomarkers. Citation Format: Yvonne Grobben, Judith E. den Ouden, Cristina Aguado, Anne M. van Altena, Aletta D. Kraneveld, Guido J. Zaman. IL4I1, IDO1 and other amino acid-metabolizing enzymes in high-grade serous ovarian cancer [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 2865.

Stratification of Length of Stay Prediction following Surgical Cytoreduction in Advanced High-Grade Serous Ovarian Cancer Patients Using Artificial Intelligence; the Leeds L-AI-OS Score

(1) Background: Length of stay (LOS) has been suggested as a marker of the effectiveness of short-term care. Artificial Intelligence (AI) technologies could help monitor hospital stays. We developed an AI-based novel predictive LOS score for advanced-stage high-grade serous ovarian cancer (HGSOC) patients following cytoreductive surgery and refined factors significantly affecting LOS. (2) Methods: Machine learning and deep learning methods using artificial neural networks (ANN) were used together with conventional logistic regression to predict continuous and binary LOS outcomes for HGSOC patients. The models were evaluated in a post-hoc internal validation set and a Graphical User Interface (GUI) was developed to demonstrate the clinical feasibility of sophisticated LOS predictions. (3) Results: For binary LOS predictions at differential time points, the accuracy ranged between 70-98%. Feature selection identified surgical complexity, pre-surgery albumin, blood loss, operative time, bowel resection with stoma formation, and severe postoperative complications (CD3-5) as independent LOS predictors. For the GUI numerical LOS score, the ANN model was a good estimator for the standard deviation of the LOS distribution by ± two days. (4) Conclusions: We demonstrated the development and application of both quantitative and qualitative AI models to predict LOS in advanced-stage EOC patients following their cytoreduction. Accurate identification of potentially modifiable factors delaying hospital discharge can further inform services performing root cause analysis of LOS.

Lifestyle and personal factors associated with having macroscopic residual disease after ovarian cancer primary cytoreductive surgery

ObjectiveThe presence of macroscopic residual disease after primary cytoreductive surgery (PCS) is an important factor influencing survival for patients with high-grade serous ovarian cancer (HGSC). More research is needed to identify factors associated with having macroscopic residual disease. We analyzed 12 lifestyle and personal exposures known to be related to ovarian cancer risk or inflammation to identify those associated with having residual disease after surgery. MethodsThis analysis used data on 2054 patients with advanced stage HGSC from the Ovarian Cancer Association Consortium. The exposures were body mass index, breastfeeding, oral contraceptive use, depot-medroxyprogesterone acetate use, endometriosis, first-degree family history of ovarian cancer, incomplete pregnancy, menopausal hormone therapy use, menopausal status, parity, smoking, and tubal ligation. Logistic regression models were fit to assess the association between these exposures and having residual disease following PCS. ResultsMenopausal estrogen-only therapy (ET) use was associated with 33% lower odds of having macroscopic residual disease compared to never use (OR = 0.67, 95%CI 0.46–0.97, p = 0.033). Compared to nulliparous women, parous women who did not breastfeed had 36% lower odds of having residual disease (OR = 0.64, 95%CI 0.43–0.94, p = 0.022), while there was no association among parous women who breastfed (OR = 0.90, 95%CI 0.65–1.25, p = 0.53). ConclusionsThe association between ET and having no macroscopic residual disease is plausible given a strong underlying biologic hypothesis between this exposure and diagnosis with HGSC. If this or the parity finding is replicated, these factors could be included in risk stratification models to determine whether HGSC patients should receive PCS or neoadjuvant chemotherapy.

Machine Learning-Based Risk Prediction of Critical Care Unit Admission for Advanced Stage High Grade Serous Ovarian Cancer Patients Undergoing Cytoreductive Surgery: The Leeds-Natal Score.

Achieving complete surgical cytoreduction in advanced stage high grade serous ovarian cancer (HGSOC) patients warrants an availability of Critical Care Unit (CCU) beds. Machine Learning (ML) could be helpful in monitoring CCU admissions to improve standards of care. We aimed to improve the accuracy of predicting CCU admission in HGSOC patients by ML algorithms and developed an ML-based predictive score. A cohort of 291 advanced stage HGSOC patients with fully curated data was selected. Several linear and non-linear distances, and quadratic discriminant ML methods, were employed to derive prediction information for CCU admission. When all the variables were included in the model, the prediction accuracies were higher for linear discriminant (0.90) and quadratic discriminant (0.93) methods compared with conventional logistic regression (0.84). Feature selection identified pre-treatment albumin, surgical complexity score, estimated blood loss, operative time, and bowel resection with stoma as the most significant prediction features. The real-time prediction accuracy of the Graphical User Interface CCU calculator reached 95%. Limited, potentially modifiable, mostly intra-operative factors contributing to CCU admission were identified and suggest areas for targeted interventions. The accurate quantification of CCU admission patterns is critical information when counseling patients about peri-operative risks related to their cytoreductive surgery.

Prognostic Significance of SLFN11 Methylation in Plasma Cell-Free DNA in Advanced High-Grade Serous Ovarian Cancer.

Simple SummaryIn the present study, we examined the methylation status of six gene promoters (BRCA1, CST6, MGMT, RASSF10, SLFN11 and USP44) in high-grade serous ovarian cancer (HGSOC). We evaluated the prognostic significance of DNA methylation of these six gene promoters in primary tumors (FFPEs) and plasma cfDNA samples from patients with early, advanced and metastatic HGSOC. We report for the first time that the DNA methylation of SLFN11 in plasma cfDNA was significantly correlated with worse PFS (p = 0.045) in advanced stage HGSOC. Our results strongly indicate that SLFN11 epigenetic inactivation could serve as a potential prognostic DNA methylation biomarker and a predictor of resistance to platinum-based chemotherapy in ovarian cancer.Background: Epigenetic alterations in ctDNA are highly promising as a source of novel potential liquid biopsy biomarkers and comprise a very promising liquid biopsy approach in ovarian cancer, for early diagnosis, prognosis and response to treatment. Methods: In the present study, we examined the methylation status of six gene promoters (BRCA1, CST6, MGMT, RASSF10, SLFN11 and USP44) in high-grade serous ovarian cancer (HGSOC). We evaluated the prognostic significance of DNA methylation of these six gene promoters in primary tumors (FFPEs) and plasma cfDNA samples from patients with early, advanced and metastatic HGSOC. Results: We report for the first time that the DNA methylation of SLFN11 in plasma cfDNA was significantly correlated with worse PFS (p = 0.045) in advanced stage HGSOC. Conclusions: Our results strongly indicate that SLFN11 epigenetic inactivation could be a predictor of resistance to platinum drugs in ovarian cancer. Our results should be further validated in studies based on a larger cohort of patients, in order to further explore whether the DNA methylation of SLFN11 promoter could serve as a potential prognostic DNA methylation biomarker and a predictor of resistance to platinum-based chemotherapy in ovarian cancer.

The prognostic factor for recurrence in advanced-stage high-grade serous ovarian cancer after complete clinical remission: a nested case-control study

BackgroundWomen with advanced-stage high-grade serous ovarian cancer (HGSOC) are likely to have a bad prognosis. Relapses are common in patients even with no evidence of disease after primary treatment. We aimed to identify the prognostic factors for disease recurrence in these patients.MethodsA nested case-control study was conducted in a large medical center in Southwest China. The primary outcome was recurrence of disease within 3 years after clinical remission (CR). Cox regression was used to calculate the time to event analysis in different groups.ResultsNinety-seven patients were finally included. Fifty-seven patients (58.8%) relapsed within 3 years after CR. Among all the variables, the difference in posttreatment CA-125 level was statistically significant (P <0.05) between the recurrent group and the progression-free group in both univariate and multivariable analysis. A cutoff value was set at the median level in the recurrent group (10 U/ml) to categorize patients into two arms. In Cox regression, the posttreatment CA-125 level was identified as a prognostic factor for recurrence with an OR of 1.05 (95% CI: 1.02–1.10, P = 0.033). The median time (from initiation of treatment) until relapse was 25 months for patients whose posttreatment CA-125 levels were higher than 10 U/ml, while it was undefined for patients whose posttreatment CA-125 level were ≤ 10 U/ml. Patients with a higher posttreatment CA-125 level showed an increased risk for OC relapse compared to those with a lower posttreatment CA-125 level. Furthermore, as shown in line graphs recording serum CA-125 levels during follow-up in each recurrent case, the increments of serum CA-125 levels were delayed in recurrent OC patients who had a posttreatment CA125 level ≤ 10 U/ml compared with those with a higher CA-125 level.ConclusionA low serum CA-125 level after primary treatment was a potential prognostic factor in women with advanced HGSOC.

Survival Is Related to Estrogen Signal Transduction Pathway Activity in Postmenopausal Women Diagnosed with High-Grade Serous Ovarian Carcinoma.

Simple SummaryAll cells have a complex internal network of ‘communication chains’ called signal transduction pathways (STPs). Through interaction of different proteins in STPs, they are partly responsible for the behavior of a cell. In our study, we investigated the activity of six STPs in 85 women with advanced stage high-grade serous ovarian cancer (HGSC). To investigate the relation between and differences in survival and STP activity, women with a short disease-free survival (below 12 months) and a long disease-free survival (above 24 months) were included. We found no differences in mean STP activity between short-term survivors (52 women) and long-term survivors (33 women). However, when we analyzed postmenopausal women, we found that both disease-free and overall survival were related to estrogen receptor (ER) pathway signaling. This indicates that a better survival outcome was related to a more active ER pathway in this subgroup.High-grade serous ovarian carcinoma (HGSC), the most common subtype of ovarian cancer, has a high mortality rate. Although there are some factors associated with survival, such as stage of disease, there are remarkable differences in survival among women diagnosed with advanced stage disease. In this study, we investigate possible relations between survival and signal transduction pathway (STP) activity. We assessed the functional activity of the androgen receptor (AR), estrogen receptor (ER), phosphoinositide-3-kinase (PI3K), Hedgehog (HH), transforming growth factor beta (TGF-β) and canonical wingless-type MMTV integration site (Wnt) pathway in 85 primary tumor samples of patients with FIGO stage IIIC to IVB HGSC and disease-free survival (DFS) below 12 (n = 52) or over 24 months (n = 33). There were no significant differences in median pathway activity between patients with a short and long DFS. In univariate Cox proportional hazards analysis, ER pathway activity was related to a favorable DFS and overall survival (OS) in postmenopausal women (p = 0.033 and p = 0.041, respectively), but not in premenopausal women. We divided the postmenopausal group into subgroups based on ER pathway activity quartiles. Survival analysis revealed that postmenopausal women in the lowest ER quartile had a shorter DFS and OS (log-rank p = 0.006 and p < 0.001, respectively). Furthermore, we were able to form subgroups of patients based on an inverse relation between ER and PI3K pathway activity. In conclusion, in postmenopausal patients with advanced stage HGSC, a poorer survival outcome was associated with low functional ER pathway activity.

Abstract 1440: Novel imipridone ONC206 suppresses ovarian cancer progression through modulating immune cell response

Abstract Advanced ovarian cancer (stages III and IV) is the most lethal gynecologic malignancy in the United States. Survival of this cancer has not improved to a major extent over the past decade. High-grade serous ovarian cancer (HGSC), in particular, is notable for its initial sensitivity to chemotherapy using platinum and taxane combination following debulking surgery. However, the vast majority of these cancers (&amp;gt;75-80%) recur within 12-24 months after diagnosis, and patients die of progressively chemotherapy-resistant disease. The identification of prognostic or predictive markers, for ovarian cancer is crucial to the development of therapeutic targets and thus improvement of survival. ONC201 is the first clinical bitopic antagonist of dopamine receptor D2 (DRD2), that is well tolerated and currently being investigated in several clinical trials for oncology. ONC206 is a chemical derivative of ONC201 with the same impridone core structure, which is also a DRD2 antagonist that exhibits distinct receptor pharmacology and nanomolar potency in various preclinical cancer models. However, the effects of ONC206 on HGSC progression and the mechanism of action have not been thoroughly explored. Preliminary data demonstrated that overexpression of DRD2 is associated with poor overall survival rates in patients with advanced stage HGSC. ONC206-treated HGSC cells demonstrated significantly lower growth rates and higher percentage of apoptotic cells than ONC201-treated cells did in vitro. Besides, intraperitoneal injection of ONC206 (100 mg/kg) twice a week into HGSC-bearing immunocompetent mice demonstrated decreased tumor volume in vivo. In addition, by using suspension mass cytometry with a panel of 28 antibodies, fresh tumor tissues from ONC206-treated mice showed markedly increase in intratumoral NK cells and activated CD8+ T cells densities. These data suggest that ONC206 is more potent than ONC201 in suppressing HGSC growth directly. In addition, ONC206 may also suppresses HGSC growth through activating immune cell response in tumor tissues. Further studies that define the molecular mechanism by which DRD2 modulates the tumor suppressive effect of ONC206 on HGSC cells by suppressing HGSC directly or enhancing anti-tumor immune cell activity will be perform to establish ONC206 as a novel therapeutic agent in treatment of HGSC patients. Citation Format: Chi Lam Au Yeung, Wen Hu, Sammy Ferri-Borgogno, Rohinton S. Tarapore, Joshua E. Allen, Karen H. Lu, Samuel C. Mok. Novel imipridone ONC206 suppresses ovarian cancer progression through modulating immune cell response [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 1440.

Patterns of BRD4 protein expression in advanced stage high-grade serous ovarian cancers

Objective: Previous results have associated elevated bromodomain and extraterminal 4 (BRD4) expression with poor overall survival in ovarian cancer. However, patterns of BRD4 expression in advanced-stage high-grade serous ovarian cancer (HGSOC) are not well characterized. The aim of this study was to evaluate BRD4 protein expression in primary and metastatic tumors of advanced-stage HGSOC.

SOX2 is a promising predictor of relapse and death in advanced stage high-grade serous ovarian cancer patients with residual disease after debulking surgery

ABSTRACT The transcription factor SOX2 is a well-established and important stem cell marker. Its role in cancer biology remains unclear, but it has been proposed to also be a marker of cancer stem cells. We investigated the role of SOX2 protein expression in women with high-grade serous ovarian cancer (HGSOC) to determine its potential prognostic and treatment predictive value. We constructed a tissue microarray of 130 advanced stage HGSOC tumors with an average of 6 cores each, stained for SOX2 protein expression and evaluated survival outcomes. We also treated two HGSOC cell lines with carboplatin and paclitaxel and measured SOX2 expression by RT-PCR and immunoblotting at different doses and time-points. Among patients with non-radical debulking surgery overall and progression-free survival were shorter for patients with SOX2 positive tumors (mean 26 vs. 39 months, log-rank test: p = .0076, and mean 14 vs. 19 months, p = .055, respectively). Knockdown of SOX2 in cell lines did not affect growth inhibition following chemotherapy treatment. Our results show that SOX2 has a strong prognostic potential among HGSOC patients with residual tumor tissue after debulking surgery and suggest that SOX2 expressing cells remaining after non-radical debulking surgery may constitute a subpopulation of cancer stem cells with greater tumor-initiating potential.

Abstract 2941: Functional proteomic aberrations post-chemotherapy with paclitaxel and carboplatin in patients with advanced ovarian cancer

Abstract Background: High-grade serous ovarian cancer (HGSOC) remains the leading cause of death from gynecologic malignancies. Here, we examined tumoral proteome changes following neoadjuvant chemotherapy (NACT) to identify potential predictive and prognostic biomarkers of response to primary chemotherapy. Methods: A total of 65 tissue specimens from 10 patients with advanced-stage HGSOC were collected from matched pre- and post-NACT (3 cycles of dose-dense paclitaxel and carboplatin). Protein expression was assessed using reverse-phase protein arrays (RPPA). All relative protein levels using 297 antibodies were normalized by the expression level of pre-treatment samples, and then protein expression alterations and functional analyses were performed by Reactome pathway analysis followed by statistical analysis. Results: The protein expression patterns of samples tended to cluster according to the time point (pre- and post-treatment) by a non-supervised clustering analysis using all the proteins assessed in the RPPA panel. Five differentially expressed proteins among 239 proteins (adj. p&amp;lt;0.1, log2FC≥1) were identified by RPPA. We identified XBP1, MYH11, and S100A4 as being upregulated and CCNB1 and TFRC were down-regulated post-treatment compared to pre-treatment. We also observed significant enrichment of specific functional and signaling pathways by pathway analysis; these included PI3K/AKT signaling, necrosis and programmed cell death (upregulated, p&amp;lt;0.05, FDR&amp;lt;1), and cell cycle and homology-directed repair (HDR) through homologous recombination repair and G2/M checkpoints (down-regulated, p&amp;lt;0.02, FDR&amp;lt;0.5) in post-treatment compared to pre-treatment. Interestingly, cell cycle, DNA damage, and G2 checkpoint pathways at post-treatment exhibited significantly lower pathway scores than pre-treatment. Conclusion: Our findings identified significant proteomic alterations following NACT, and could provide insights into interval proteomic alterations following induction chemotherapy in advanced-stage ovarian cancer patients. These data present information to optimize future clinical trial designs for patients with ovarian cancer. Citation Format: Sanghoon Lee, Li Zhao, Joseph Celestino, Kelly M. Rangel, Richard A. Hajek, Mark S. Kim, Sara E. Sharafi, Jinsong Liu, Nicole D. Fleming, Karen H. Lu, Jianhua Zhang, P. Andrew Futreal, Gordon B. Mills, Shannon N. Westin, Anil K. Sood, Amir A. Jazaeri, Robert L. Coleman. Functional proteomic aberrations post-chemotherapy with paclitaxel and carboplatin in patients with advanced ovarian cancer [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 2941.

Preoperative neutrophil-to-lymphocyte ratio predicts 30 day postoperative morbidity and survival after primary surgery for ovarian cancer

ObjectiveThe preoperative neutrophil-to-lymphocyte ratio has been found to be an independent prognostic indicator for perioperative complications and survival outcomes in patients undergoing oncologic surgery for several malignancies. The objective of...

Role of M1-polarized tumor-associated macrophages in the prognosis of advanced ovarian cancer patients

The identification of prognostic and predictive markers is crucial for choosing the most appropriate management method for ovarian cancer patients. We aimed to assess the prognostic role of tumor-associated macrophage (TAM) polarization in advanced ovarian cancer patients. We carried out a prospective observational study that included 140 consecutive patients with advanced-stage high-grade serous ovarian cancer as well as patients with other histotypes of ovarian cancer and patients with ovarian metastasis from other sites between June 2013 and December 2018. Patients were enrolled at the time of laparoscopic surgery before receiving any antineoplastic treatment. We found that patients with high-grade serous papillary ovarian cancers had a prevalence of M1 TAMs, a higher M1/M2 ratio, and a longer overall survival (OS) and progression-free survival (PFS) than other patients. Regression analysis confirmed that there was a significant positive association between the M1/M2 ratio and an improved OS, PFS and platinum-free interval (PFI), both in the entire population and in patients stratified according to tumor type and initial surgery. Kaplan-Meier analysis was performed after the patients were divided into 2 groups according to the median M1/M2 ratio and revealed that patients with a high M1/M2 ratio had a higher OS, PFS and PFI than those with a low M1/M2 ratio. In conclusion, the prognostic and predictive role of TAM polarization in the tumor microenvironment could be of great clinical relevance and may allow the early identification of patients who are likely to respond to therapy. Further studies in a larger prospective sample are warranted.

Prediction of Platinum-based Chemotherapy Response in Advanced High-grade Serous Ovarian Cancer: ADC Histogram Analysis of Primary Tumors

To investigate the feasibility of apparent diffusion coefficient (ADC) histogram analysis of primary advanced high-grade serous ovarian cancer (HGSOC) to predict patient response to platinum-based chemotherapy. A total of 70 patients with 102 advanced stage HGSOCs (International Federation of Gynecology and Obstetrics (FIGO) stages III-IV) who received standard treatment of primary debulking surgery followed by the first line of platinum-based chemotherapy were retrospectively enrolled. Patients were grouped as platinum-resistant and platinum-sensitive according to whether relapse occurred within 6 months. Clinical characteristics, including age, pretherapy CA125 level, International Federation of Gynecology and Obstetrics stage, residual tumor, and histogram parameters derived from whole tumor and solid component such as ADCmean; 10th, 20th, 25th, 30th, 40th, 50th, 60th, 70th, 75th, 80th, 90th percentiles; skewness and kurtosis, were compared between platinum-resistant and platinum-sensitive groups. No significantly different clinical characteristics were observed between platinum-sensitive and platinum-resistant patients. There were no significant differences in any whole-tumor histogram-derived parameters between the two groups. Significantly higher ADCmean and percentiles and significantly lower skewness and kurtosis from the solid-component histogram parameters were observed in the platinum-sensitive group when compared with the platinum-resistant group. ADCmean, skewness and kurtosis showed moderate prediction performances, with areas under the curve of 0.667, 0.733 and 0.616, respectively. Skewness was an independent risk factor for platinum resistance. Pretreatment ADC histogram analysis of primary tumors has the potential to allow prediction of response to platinum-based chemotherapy in patients with advanced HGSOC.

Abstract TMIM-067: EXPRESSION OF LNCRNAS IN OVARIAN CANCER-ASSOCIATED FIBROBLASTS IS ASSOCIATED WITH PATIENT SURVIVAL

Abstract BACKGROUND: Ovarian cancer is the most lethal gynecological malignancy in women, with high-grade serous ovarian cancer (HGSOC) the most common and aggressive subtype. The tumor microenvironment is acknowledged to play a vital role in the growth and metastasis of many solid tumors, including ovarian cancer, and as such represents an attractive new therapeutic target. In ovarian cancer, patients with a higher proportion of desmoplasia have a poorer survival. Cancer-associated fibroblasts (CAFs) represent the most abundant cell type in the tumor stroma and are responsible for producing the desmoplastic reaction that is a poor prognostic factor in HGSOC. Genetic aberrations in ovarian CAFs are extremely rare, raising the possibility of alternative mechanisms that regulate gene expression in CAFs, such as regulation by long non-coding RNAs (lncRNAs). LncRNAs are transcripts that do not encode for protein, but have been shown to play important roles in several diseases, including cancer. However, very little is known about the role of lncRNAs in the tumor microenvironment. OBJECTIVES: To identify lncRNAs whose expression levels in CAFs are associated with patient survival and use computational approaches to predict their function. METHODS: CAFs were laser capture microdissected from 67 advanced stage HGSOCs. RNA was extracted from the microdissected samples and expression analyzed using Affymetrix U133 Plus 2.0 Arrays. Probes identified as lncRNAs were used in this analysis. Samples were normalized and background corrected using the robust multiarray average (RMA) method and expression values were log2 transformed. Expression levels of each lncRNA were clustered into low and high expression groups. Kaplan Meier /log-rank analysis was used to assess the association between expression levels of each lncRNA and the patients' overall survival. Multivariate cox regression analysis was used to determine if differential expression of lncRNAs were independent predictors of survival. A network based ‘guilt-by-association' approach was used to predict the function of lncRNAs associated with patient survival. RESULTS: Increased expression of 9 lncRNAs including DANCR, MALAT1 and NEAT1 and decreased expression of 1 lncRNA in ovarian CAFs were found to be associated with poorer overall survival by the log-rank test. Expression profiles of 5 lncRNAs as well as response to chemotherapy and debulking status were significant predictors of survival by univariate cox proportional hazards analysis. To adjust for existing collinearity of the 10 lncRNAs, the first principal component of these lncRNAs (capturing 98% of variations), as well as response to chemotherapy and debulking status were incorporated into a multivariate model. The first principal component (HR=0.74, P=0.0001163) and response to chemotherapy (HR=0.22, P=0.000168) were found to be independent predictors of survival. Functional enrichment analysis revealed these lncRNAs are likely to play a role in metabolism, autophagy or immune response. CONCLUSIONS: We have identified several lncRNAs whose expression levels in CAFs are associated with survival of HGSOC patients, raising the likelihood that they play an important role in the tumor-promoting functions of CAFs. A further understanding of the role of lncRNAs in CAFs may be useful when designing novel therapies that target the tumor microenvironment. Citation Format: Emily K. Colvin, Viive M. Howell, Samuel C. Mok, Goli Samimi and Fatemeh Vafaee. EXPRESSION OF LNCRNAS IN OVARIAN CANCER-ASSOCIATED FIBROBLASTS IS ASSOCIATED WITH PATIENT SURVIVAL [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 TMIM-067.

Engineered Adoptive T-cell Therapy Prolongs Survival in a Preclinical Model of Advanced-Stage Ovarian Cancer.

Adoptive T-cell therapy using high-affinity T-cell receptors (TCR) to target tumor antigens has potential for improving outcomes in high-grade serous ovarian cancer (HGSOC) patients. Ovarian tumors develop a hostile, multicomponent tumor microenvironment containing suppressive cells, inhibitory ligands, and soluble factors that facilitate evasion of antitumor immune responses. Developing and validating an immunocompetent mouse model of metastatic ovarian cancer that shares antigenic and immunosuppressive qualities of human disease would facilitate establishing effective T-cell therapies. We used deep transcriptome profiling and IHC analysis of human HGSOC tumors and disseminated mouse ID8VEGF tumors to compare immunologic features. We then evaluated the ability of CD8 T cells engineered to express a high-affinity TCR specific for mesothelin, an ovarian cancer antigen, to infiltrate advanced ID8VEGF murine ovarian tumors and control tumor growth. Human CD8 T cells engineered to target mesothelin were also evaluated for ability to kill HLA-A2+ HGSOC lines. IHC and gene-expression profiling revealed striking similarities between tumors of both species, including processing/presentation of a leading candidate target antigen, suppressive immune cell infiltration, and expression of molecules that inhibit T-cell function. Engineered T cells targeting mesothelin infiltrated mouse tumors but became progressively dysfunctional and failed to persist. Treatment with repeated doses of T cells maintained functional activity, significantly prolonging survival of mice harboring late-stage disease at treatment onset. Human CD8 T cells engineered to target mesothelin were tumoricidal for three HGSOC lines. Treatment with engineered T cells may have clinical applicability in patients with advanced-stage HGSOC.

Prediction of optimal surgical outcomes with radiologic images using deep learning artificial intelligence

Objective: At present, there is no universally accepted objective method for predicting which patients will reach optimal cytoreduction after primary debulking surgery for high-grade serous ovarian cancer (HGSC). Our objective was to predict which patients will obtain optimal surgical outcomes in advanced-stage HGSC using preoperative radiologic images processed with convolutional neural networks and artificial intelligence.