Chemotherapy Response In Ovarian Cancer Research Articles

COPS5 inhibition targets nucleotide excision repair and homologous recombination to enhance platinum chemotherapy response in ovarian cancer

COPS5 inhibition targets nucleotide excision repair and homologous recombination to enhance platinum chemotherapy response in ovarian cancer

KDM1A/LSD1 inhibition enhances chemotherapy response in ovarian cancer.

Ovarian cancer (OCa) is the deadliest of all gynecological cancers. The standard treatment for OCa is platinum-based chemotherapy, such as carboplatin or cisplatin in combination with paclitaxel. Most patients are initially responsive to these treatments; however, nearly 90% will develop recurrence and inevitably succumb to chemotherapy-resistant disease. Recent studies have revealed that the epigenetic modifier lysine-specific histone demethylase 1A (KDM1A/LSD1) is highly overexpressed in OCa. However, the role of KDM1A in chemoresistance and whether its inhibition enhances chemotherapy response in OCa remains uncertain. Analysis of TCGA datasets revealed that KDM1A expression is high in patients who poorly respond to chemotherapy. Western blot analysis show that treatment with chemotherapy drugs cisplatin, carboplatin, and paclitaxel increased KDM1A expression in OCa cells. KDM1A knockdown (KD) or treatment with KDM1A inhibitors NCD38 and SP2509 sensitized established and patient-derived OCa cells to chemotherapy drugs in reducing cell viability and clonogenic survival and inducing apoptosis. Moreover, knockdown of KDM1A sensitized carboplatin-resistant A2780-CP70 cells to carboplatin treatment and paclitaxel-resistant SKOV3-TR cells to paclitaxel. RNA-seq analysis revealed that a combination of KDM1A-KD and cisplatin treatment resulted in the downregulation of genes related to epithelial-mesenchymal transition (EMT). Interestingly, cisplatin treatment increased a subset of NF-κB pathway genes, and KDM1A-KD or KDM1A inhibition reversed this effect. Importantly, KDM1A-KD, in combination with cisplatin, significantly reduced tumor growth compared to a single treatment in an orthotopic intrabursal OCa xenograft model. Collectively, these findings suggest that combination of KDM1A inhibitors with chemotherapy could be a promising therapeutic approach for the treatment of OCa.

Evaluating Ovarian Cancer Chemotherapy Response Using Gene Expression Data and Machine Learning.

Ovarian cancer (OC) is the most lethal gynecological cancer in the United States. Among the different types of OC, serous ovarian cancer (SOC) stands out as the most prevalent. Transcriptomics techniques generate extensive gene expression data, yet only a few of these genes are relevant to clinical diagnosis. Methods for feature selection (FS) address the challenges of high dimensionality in extensive datasets. This study proposes a computational framework that applies FS techniques to identify genes highly associated with platinum-based chemotherapy response on SOC patients. Using SOC datasets from the Gene Expression Omnibus (GEO) database, LASSO and varSelRF FS methods were employed. Machine learning classification algorithms such as random forest (RF) and support vector machine (SVM) were also used to evaluate the performance of the models. The proposed framework has identified biomarkers panels with 9 and 10 genes that are highly correlated with platinum-paclitaxel and platinum-only response in SOC patients, respectively. The predictive models have been trained using the identified gene signatures and accuracy of above 90% was achieved. In this study, we propose that applying multiple feature selection methods not only effectively reduces the number of identified biomarkers, enhancing their biological relevance, but also corroborates the efficacy of drug response prediction models in cancer treatment.

P27Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer.

The biological function of p27Kip1 largely depends on its subcellular localization and phosphorylation status. Different subcellular localizations and phosphorylation statuses of p27Kip1 may represent distinct clinical values, which are unclear in ovarian cancer. This study aimed to elucidate different subcellular localizations of p27Kip1 and pSer10p27 in predicting prognosis and chemotherapy response in ovarian cancer. Meta-analyses were executed to evaluate the association of p27Kip1 and phosphorylated p27Kip1 with the prognosis of ovarian cancer patients. The expression levels and patterns of p27Kip1 and pSer10p27 were evaluated by immunohistochemistry. The correlations between different p27Kip1 states, clinicopathological features, and prognosis were analyzed. p27Kip1 and pSer10p27 expression levels in cisplatin-sensitive and cisplatin-resistant ovarian cancer cell lines were detected using WB. KEGG analysis and WB were performed to evaluate the pathways in which p27Kip1 was involved. Meta-analyses showed that p27Kip1 was associated with significantly better overall survival (OS) in ovarian cancer (HR=2.14; 95% CI [1.71-2.68]) and pSer10p27 was associated with significantly poor OS in mixed solid tumors (HR=2.56; 95% CI [1.76-3.73]). In our cohort of ovarian cancer patients, low total p27Kip1 remained independent risk factors of OS (HR=2.097; 95% CI [1.121-3.922], P=0.021) and PFS (HR=2.483; 95% CI [1.364-4.518], P=0.003), while low cytoplasmic pSer10p27 had independent protective effects in terms of OS (HR=0.472; 95% CI [0.248-0.898], P=0.022) and PFS (HR=0.488; 95% CI [0.261-0.910], P=0.024). Patients with low total p27Kip1/pSer10p27 and low nuclear p27Kip1 had worse chemotherapy responses, while patients with low cytoplasmic pSer10p27 expression had better chemotherapy responses. The protein levels of p27Kip1 and pSer10p27 were significantly reduced in the cisplatin-resistant cell lines SKOV3-cDDP and A2780-cDDP, and the level of p27Kip1/pSer10p27 was subjective to Akt activation. The present study demonstrates that p27Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer.

Abstract 3237: KDM1A/LSD1 inhibition enhances chemotherapy response in ovarian cancer

Abstract Background: Ovarian cancer (OCa) is the deadliest of all gynecological cancers. The standard treatment for OCa is platinum-based chemotherapy, such as carboplatin or cisplatin in combination with paclitaxel. Most patients are initially responsive to these treatments; however, nearly 90% will develop recurrence and inevitably succumb to chemotherapy-resistant disease. Recent studies have revealed that the epigenetic modifier lysine-specific histone demethylase (KDM1A/LSD1) is highly overexpressed in OCa. However, whether KDM1A plays a role in chemoresistance and whether its inhibition enhances chemotherapy response in OCa is unknown. In this study, we explored the hypothesis that KDM1A inhibition will sensitize OCa cells to standard-of-care chemotherapy. Methods: Transduction of KDM1A-specific shRNA was used to generate KDM1A knockdown (KD) cells. Cell viability, colony formation, and apoptosis assays were used to determine the impact of KDM1A KD on sensitization of SKOV3, OVCAR8, and OVCAR5 OCa cells to cisplatin, carboplatin, and paclitaxel. The combination effect of KDM1A inhibitors (NCD38 and SP2509) and chemotherapy drugs was further determined. Mechanistic studies were conducted using RNA-sequencing, RT-qPCR, and Western blotting. In vivo efficacy ofKDM1A knockdown with or without chemotherapy was determined using OCa orthotopic xenograft models. Results: Analysis of TCGA datasets revealed that KDM1A expression is negatively correlated with OCa survival, and its expression is high in patients who do not respond to chemotherapy. Further, Western blotting results show that treatment with chemotherapy drugs cisplatin, carboplatin, and paclitaxel increased KDM1A expression in OCa cells. KDM1A-KD or KDM1A inhibition sensitized OCa cells to chemotherapy drugs in reducing cell viability, survival, and enhancing apoptosis. Moreover, knockdown of KDM1A sensitized carboplatin-resistantA2780-CP70 cells to carboplatin treatment. RNA-seq studies revealed that KDM1A-KD and cisplatin-regulated genes showed negative correction with epithelial-mesenchymal transition (EMT) and positive correlation with apoptosis-related pathways. Importantly, KDM1A KD in combination with cisplatin significantly reduced the tumor growth in the orthotopic OCa xenograft model. Conclusion: These results suggest that the combination of KDM1A inhibitors with chemotherapy is a viable therapeutic approach for the treatment of OCa Citation Format: Jessica D. Johnson, Yihong Chen, Sridharan Jayamohan, Yi He, Diksha Jamwal, Neetesh Pandey, Edward Kost, Ratna K. Vadlamudi, Gangadhara R. Sareddy. KDM1A/LSD1 inhibition enhances chemotherapy response in ovarian cancer [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 3237.

Abstract B098: Impact of dexamethasone on chemotherapy response in ovarian cancer

Abstract Background: Ovarian cancer ranks fifth in cancer deaths among women. The gold standard of care for advanced disease includes cytoreductive surgery along with adjuvant or neoadjuvant platinum/taxane-based chemotherapy. Although response to this treatment is high, chemotherapy-induced nausea and vomiting due to platinum agents and allergic reactions due to both agents are common. For nearly half a century, the glucocorticoid (GC) dexamethasone (DEX) has been administered as part of supportive care. However, there have periodically been questions about the possible deleterious effects of DEX on chemotherapy response, especially in solid tumors. Methods: Platinum-sensitive, glucocorticoid receptor (GRa) expressing ovarian cancer cells were exposed to DEX prior to chemotherapy and clonogenic survival was assessed. The effects of DEX on cell cycle and apoptosis were assessed by flow cytometry. Changes in the tumor cell transcriptome after acute DEX treatment were determined by RNA sequencing. Mice bearing orthotopic ovarian cancer patient-derived xenografts (PDXs) were treated with chemotherapy ± DEX to assess changes in chemotherapy response in vivo. Findings: DEX pre-treatment decreased platinum cytotoxicity in ovarian cancer cell lines in vitro and diminished platinum response in some PDXs analyzed for chemotherapy response ex vivo. RNA-seq analysis revealed changes in transcripts encoding proteins involved in platinum detoxification and TNFa pro-survival signaling. In ovarian cancer PDXs, DEX decreased platinum response in one model and had limited impact on both platinum and platinum/taxane chemotherapy in three distinct studies. Interpretation: DEX appears to modulate chemotherapy response in some settings in vitro and ex-vivo. The impact of DEX on chemotherapy response in vivo appears to be limited. However, further investigation of this question in vivo in non-immunosuppressed murine models appears warranted. Citation Format: Annapoorna Venkatachalam, Cristina Correia, Cordelia Mcgehee, Sarah Finstuen-Magro, Paula A. Schneider, Rachel Hurley, Kevin L. Peterson, Ethan Heinzen, Melissa C. Larson, Xiaonon Hou, Ann L. Oberg, Saravut Weroha, Scott H. Kaufmann. Impact of dexamethasone on chemotherapy response in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr B098.

Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer.

The leading cause of death related to gynecologic cancer is ovarian cancer, which typically has a poor prognosis. T cells are referred to as key mediators of immunosurveillance and tumor eradication, and unbalanced regulation or lack of T cells in tumors result in immunotherapy resistance. The identification of T cell related markers depended on single-cell RNA-seq analysis. Using data from multiple datasets, including TCGA, GSE14764, GSE26193, GSE26712, and GSE140082, we constructed a prognostic signature called TRS (T cell-related signature) using 10 different machine learning algorithms. The correlation between TRS and drug sensitivity were analyzed using the data from GSE91061 and IMvigor210 dataset. PlsRcox method based TRS was as a risk factor for the clinical outcome of ovarian cancer patients. In comparison with stage, grade and many prognostic signatures, the performance of our TRS in evaluating the clinical outcome was better in ovarian cancer. TRS-based risk score showed distinct association with the level of ESTIMATE score, immune-related function score and immune cells. Moreover, TRS could be used to predict the immunotherapy response and chemotherapy response in ovarian cancer. In conclusion, we constructed a powerful TRS in ovarian cancer, which could accurately predict the clinical outcome of patients and be used to predict the immunotherapy response and chemotherapy response.

148P Identification of potential predictive biomarkers for ovarian cancer chemotherapy response

148P Identification of potential predictive biomarkers for ovarian cancer chemotherapy response

RAD51 Foci as a Biomarker Predictive of Platinum Chemotherapy Response in Ovarian Cancer.

To determine the ability of RAD51 foci to predict platinum chemotherapy response in high-grade serous ovarian cancer (HGSOC) patient-derived samples. RAD51 and γH2AX nuclear foci were evaluated by immunofluorescence in HGSOC patient-derived cell lines (n = 5), organoids (n = 11), and formalin-fixed, paraffin-embedded tumor samples (discovery n = 31, validation n = 148). Samples were defined as RAD51-High if >10% of geminin-positive cells had ≥5 RAD51 foci. Associations between RAD51 scores, platinum chemotherapy response, and survival were evaluated. RAD51 scores correlated with in vitro response to platinum chemotherapy in established and primary ovarian cancer cell lines (Pearson r = 0.96, P = 0.01). Organoids from platinum-nonresponsive tumors had significantly higher RAD51 scores than those from platinum-responsive tumors (P < 0.001). In a discovery cohort, RAD51-Low tumors were more likely to have a pathologic complete response (RR, 5.28; P < 0.001) and to be platinum-sensitive (RR, ∞; P = 0.05). The RAD51 score was predictive of chemotherapy response score [AUC, 0.90; 95% confidence interval (CI), 0.78-1.0; P < 0.001). A novel automatic quantification system accurately reflected the manual assay (92%). In a validation cohort, RAD51-Low tumors were more likely to be platinum-sensitive (RR, ∞; P < 0.001) than RAD51-High tumors. Moreover, RAD51-Low status predicted platinum sensitivity with 100% positive predictive value and was associated with better progression-free (HR, 0.53; 95% CI, 0.33-0.85; P < 0.001) and overall survival (HR, 0.43; 95% CI, 0.25-0.75; P = 0.003) than RAD51-High status. RAD51 foci are a robust marker of platinum chemotherapy response and survival in ovarian cancer. The utility of RAD51 foci as a predictive biomarker for HGSOC should be tested in clinical trials.

Abstract 5058: Impact of dexamethasone on chemotherapy response in ovarian cancer

Abstract Background: Ovarian cancer ranks fifth in cancer deaths among women. The gold standard of care for advanced disease includes cytoreductive surgery along with adjuvant or neoadjuvant platinum/taxane-based chemotherapy. Although response to this treatment is high, chemotherapy-induced nausea and vomiting due to platinum agents and allergic reactions due to both agents are common. For nearly half a century, the glucocorticoid (GC) dexamethasone (DEX) has been administered as part of supportive care. However, there have periodically been questions about the possible deleterious effects of DEX on chemotherapy response, especially in solid tumors. Methods: Platinum-sensitive, glucocorticoid receptor (GRα) expressing ovarian cancer cells were exposed to DEX prior to chemotherapy and clonogenic survival was assessed. The effects of DEX on cell cycle and apoptosis were assessed by flow cytometry. Changes in the tumor cell transcriptome after acute DEX treatment were determined by RNA sequencing. Mice bearing orthotopic ovarian cancer patient-derived xenografts (PDXs) were treated with chemotherapy ± DEX to assess changes in chemotherapy response in vivo. Findings: DEX pre-treatment decreased platinum cytotoxicity in ovarian cancer cell lines in vitro and diminished platinum response in some PDXs analyzed for chemotherapy response ex vivo. RNA-seq analysis revealed changes in transcripts encoding proteins involved in platinum detoxification and TNFα pro-survival signaling. In ovarian cancer PDXs, DEX decreased platinum response in one model and had limited impact on both platinum and platinum/taxane chemotherapy in three distinct studies. Interpretation: DEX appears to modulate chemotherapy response in some settings in vitro and ex-vivo. The impact of DEX on chemotherapy response in vivo appears to be limited. However, further investigation of this question in vivo in non-immunosuppressed murine models appears warranted. Citation Format: Annapoorna Venkatachalam, Cristina Correia, Cordelia D. Mcgehee, Sarah Finstuen-Magro, Jamison VanBlaricom, Paula A. Schneider, Kevin L. Peterson, Ethan P. Heinzen, Melissa C. Larson, Xiaonon Hou, Ann L. Oberg, Saravut John Weroha, Scott H. Kaufmann. Impact of dexamethasone on chemotherapy response in 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 5058.

524MO Glucocorticoid receptor expression and activity in a phase II ovarian cancer trial of the glucocorticoid receptor modulator relacorilant in combination with nab-paclitaxel

Cortisol activity at the glucocorticoid receptor (GR) contributes to chemotherapy resistance by suppressing apoptotic pathways that taxanes utilize, and high tumor GR expression is associated with poor chemotherapy response in ovarian cancer. A phase 2 ovarian cancer study (NCT03776812) demonstrated the clinical benefit of adding relacorilant (RELA), a selective GR modulator, to nab-paclitaxel (NP) compared to NP alone. We present biomarker analyses from this study.

Comprehensive network analysis of dysregulated genes revealed MNX1-AS1/hsa-miR-4697-3p/HOXB13 axis in ovarian cancer chemotherapy response.

Poor chemotherapy response is the main obstacle of ovarian cancer (OC) treatment. Platinum‐refractory and ‐resistant patients are associated with a worse outcome than platinum‐sensitive and partially sensitive patients, but the comprehensive similarities and differences among them are not yet clear. In this study, we analyzed the data of patients with different chemotherapy response in The Cancer Genome Atlas. We found a minority of altered genes were overlapped in refractory and resistant groups, as did the enriched pathways and Gene Ontology terms. We noticed that the neural signaling and drug metabolism enzymes were more significantly enriched and the protein–protein interaction supported these results. The transcription analysis highlighted PDX1 as the common and central transcription factor in both refractory and resistant groups. The competing endogenous RNA (ceRNA) network shared no common ceRNA pairs, indicating a major difference in noncoding RNA post‐transcriptional regulation. In the end, we validated the expression, regulation, binding, and effect on chemotherapy response for selected MNX1‐AS1/hsa‐miR‐4697‐3p/HOXB13 in OC cell lines. Our study offered a novel and comprehensive insight into chemotherapy response, and potential targets for improving chemotherapy response in OC.

Expression of CD44+/CD24-, RAD6 and DDB2 on chemotherapy response in ovarian Cancer: A prospective flow cytometry study

BackgroundsOvarian cancer is the 8th deadliest common cancer in women around the world. Almost all ovarian cancer patients would experience chemoresistance, recurrence, and poor prognosis after cytoreductive surgery and platinum-based chemotherapy. Chemoresistant cancer cells have characteristic expressions of cancer stem cell proteins (CSCs) CD44+/CD24-, RAD6 and DDB2. The increased expression of CD44+/CD24-, RAD6, and decreased DDB2 are believed to be associated with chemoresistance, recurrence, and poor prognosis of the disease. Thus, this study’s objective is to analyze the correlation between the expression of CD44+/CD24-, RAD6 and DDB2 with ovarian cancer chemoresistance. Materials and methodsThis study was conducted with a prospective cohort of 64 patients who is divided into two groups (32 patients in each group) at the Obstetrics-gynecology and pathology department of Cipto Mangunkusumo, Tarakan, Dharmais, and Fatmawati Hospital. All suspected ovarian cancer patients underwent cytoreductive debulking and histopathological examination. Chemotherapy was given for six series followed by six months of observation. After the observation, we determined the therapy’s response with the RECIST Criteria (Response Criteria in Solid Tumors) and then classified the results into chemoresistant or chemosensitive groups. Flow cytometry blood tests were then performed to examine the expression of CD44+/CD24-, RAD6 and DDB2. ResultsThere was a significant relationship between increased levels of CD44+/CD24-, and RAD6 (p < 0.05) levels with the chemoresistance of ovarian cancer. The logistic regression test showed that the CD44+/CD24– was better marker. ConclusionsThese results indicate that CD44+/CD24 and RAD6 expressions are significantly associated with ovarian cancer chemoresistance, and CD44+/CD24- is the better marker to predict ovarian cancer chemoresistance.

Novel MicroRNA-Regulated Transcript Networks Are Associated with Chemotherapy Response in Ovarian Cancer.

High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecologic cancer, in part due to resistance to platinum-based chemotherapy reported among 20% of patients. This study aims to generate novel hypotheses of the biological mechanisms underlying chemotherapy resistance, which remain poorly understood. Differential expression analyses of mRNA- and microRNA-sequencing data from HGSOC patients of The Cancer Genome Atlas identified 21 microRNAs associated with angiogenesis and 196 mRNAs enriched for adaptive immunity and translation. Coexpression network analysis identified three microRNA networks associated with chemotherapy response enriched for lipoprotein transport and oncogenic pathways, as well as two mRNA networks enriched for ubiquitination and lipid metabolism. These network modules were replicated in two independent ovarian cancer cohorts. Moreover, integrative analyses of the mRNA/microRNA sequencing and single-nucleotide polymorphisms (SNPs) revealed potential regulation of significant mRNA transcripts by microRNAs and SNPs (expression quantitative trait loci). Thus, we report novel transcriptional networks and biological pathways associated with resistance to platinum-based chemotherapy in HGSOC patients. These results expand our understanding of the effector networks and regulators of chemotherapy response, which will help to improve the management of ovarian cancer.

Abstract 1708: Improving genotype specific chemotherapy response in ovarian cancer via cGAS-STING pathway activation

Abstract High grade serous ovarian carcinoma (HGSC) is the most lethal gynecologic malignancy with high rates of chemotherapy resistance and poor outcomes. Our previous studies have demonstrated the variable tumor immune microenvironment states that associate with platinum chemotherapy response. We further showed the significance of the interferon (IFN) induced chemokine CXCL10 as a key mediator of tumor infiltrating immune cell recruitment. Using the ID8-Trp53−/− murine model of HGSC, we demonstrated the potential of Stimulator of Interferon Genes (STING) pathway activation in enhancing response of HGSC tumors to carboplatin chemotherapy and sensitizing them to immune checkpoint blockade therapy through a heightened type 1 IFN (IFN1) response. CXCL10 production via IFN1 is also governed by genes that regulate cellular DNA damage repair pathways. Evolving evidence indicates a role of BRCA1 and PTEN genes in mediating cellular IFN1 responses. Losses in the function of these genes is widely prevalent in a large proportion of HGSC tumors, where tumors with BRCA1 mutations (~25% of HGSC cases) have higher CD8+ T cell infiltration in contrast to those with loss of PTEN (~10% of cases). We hypothesized that HGSC tumors with loss of PTEN expression can be rendered susceptible to immune mediated killing via activating the STING pathway. Tumors generated from ID8-Trp53−/−; Brca1−/− cells and those from ID8-Trp53−/−; Pten−/− cells in C57BL6 mice showed significant immunologic differences through local and systemic immune profiling. The addition of STING agonist treatment significantly increased chemosensitivity and improved overall response in mice implanted with ID8-Trp53−/−; Pten−/− cells compared to those treated with carboplatin alone, altering immune responses. This study is foundational to inform rational combinations of STING pathway activating therapies in HGSC, augmenting responses to existing chemotherapy regimens and prolonging survival rates in patients. Citation Format: Noor Shakfa, Elizabeth Lightbody, Deyang Li, Juliette Wilson-Sanchez, Gwenaelle Conseil, Afrakoma Afriyie-Asante, Stephen Chenard, Ali Hamade, Madhuri Koti. Improving genotype specific chemotherapy response in ovarian cancer via cGAS-STING pathway activation [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 1708.

Genomic, Transcriptomic, and Functional Alterations in DNA Damage Response Pathways as Putative Biomarkers of Chemotherapy Response in Ovarian Cancer.

Simple SummarySeveral chemotherapy drugs are approved for ovarian cancer treatment in the neo-adjuvant/adjuvant setting as well as following relapse. These include carboplatin, paclitaxel, doxorubicin, topotecan, PARP inhibitors (PARPi), and gemcitabine. However, except for PAPRi, there are no predictive biomarkers to guide the choice of drug. The majority of chemotherapeutic drugs function by inducing DNA damage or inhibiting its repair. However, the association of DNA damage repair (DDR) pathway alterations with therapy response remain unclear. In this study, using a panel of 14 ovarian cancer cell lines, 10 patient ascites-derived primary cultures and bioinformatic analysis of The Cancer Genome Atlas (TCGA) ovarian cancer dataset, we identified the role of genomic/transcriptomic and/or functional alterations in DDR pathways as determinants of therapy response.Defective DNA damage response (DDR) pathways are enabling characteristics of cancers that not only can be exploited to specifically target cancer cells but also can predict chemotherapy response. Defective Homologous Recombination Repair (HRR) function, e.g., due to BRCA1/2 loss, is a determinant of response to platinum agents and PARP inhibitors in ovarian cancers. Most chemotherapies function by either inducing DNA damage or impacting on its repair but are generally used in the clinic unselectively. The significance of HRR and other DDR pathways in determining response to several other chemotherapy drugs is not well understood. In this study, the genomic, transcriptomic and functional analysis of DDR pathways in a panel of 14 ovarian cancer cell lines identified that defects in DDR pathways could determine response to several chemotherapy drugs. Carboplatin, rucaparib, and topotecan sensitivity were associated with functional loss of HRR (validated in 10 patient-derived primary cultures) and mismatch repair. Two DDR gene expression clusters correlating with treatment response were identified, with PARP10 identified as a novel marker of platinum response, which was confirmed in The Cancer Genome Atlas (TCGA) ovarian cancer cohort. Reduced non-homologous end-joining function correlated with increased sensitivity to doxorubicin, while cells with high intrinsic oxidative stress showed sensitivity to gemcitabine. In this era of personalised medicine, molecular/functional characterisation of DDR pathways could guide chemotherapy choices in the clinic allowing specific targeting of ovarian cancers.

Identification and Analysis of An Epigenetically Regulated Five-lncRNA Signature Associated With Outcome and Chemotherapy Response in Ovarian Cancer.

The deregulation of long non-coding RNAs (lncRNAs) by epigenetic alterations has been implicated in cancer initiation and progression. However, the epigenetically regulated lncRNAs and their association with clinical outcome and therapeutic response in ovarian cancer (OV) remain poorly investigated. This study performed an integrative analysis of DNA methylation data and transcriptome data and identified 419 lncRNAs as potential epigenetically regulated lncRNAs. Using machine-learning and multivariate Cox regression analysis methods, we identified and developed an epigenetically regulated lncRNA expression signature (EpiLncRNASig) consisting of five lncRNAs from the list of 17 epigenetically regulated lncRNAs significantly associated with outcome. The EpiLncRNASig could stratify patients into high-risk groups and low-risk groups with significantly different survival and chemotherapy response in different patient cohorts. Multivariate Cox regression analyses, after adjusted by other clinical features and treatment response, demonstrated the independence of the DEpiLncSig in predicting survival. Functional analysis for relevant protein-coding genes of the DEpiLncSig indicated enrichment of known immune-related or cancer-related biological pathways. Taken together, our study not only provides a promising prognostic biomarker for predicting outcome and chemotherapy response but also will improve our understanding of lncRNA epigenetic regulation mechanisms in OV.

Role of BRCA Mutation and HE4 in Predicting Chemotherapy Response in Ovarian Cancer: A Retrospective Pilot Study.

Even though 80% of patients with High-Grade Serous Ovarian Cancer respond to standard first-line chemotherapy, a majority of them could relapse in the following five years due to a resistance to platinum. Human Epididymis protein 4 (HE4) is one of the most promising markers in predicting platinum therapy response. This pilot study aims to evaluate the potential role of HE4 value in predicting chemotherapy response in BRCA mutated patients and in BRCA wild-type (non-mutated) ones. We selected 69 patients, affected by High-Grade Serous Ovarian Cancer, and optimally debulked and submitted to standard chemotherapy protocols. HE4 was dosed during every chemotherapy course. Patients were classified as platinum-resistant and platinum-sensitive. According to BRCA mutation test, patients were further divided into BRCA wild-type (53 patients), and BRCA mutated (16 patients). 35 patients out of 69 (52%) were platinum-sensitive (recurrence > 12 months), while 33 patients (48%) were platinum-resistant (recurrence < 12 months). Thus, in the total population, HE4 performed as a marker of chemosensitivity with a sensibility of 79% and a specificity of 97%. In the BRCA WT group, 23 patients out of 53 (43%) were platinum-sensitive, while 30 patients out of 53 (57%) were platinum-resistant. In the BRCA WT group, HE4 performed as a predictive marker of chemosensitivity with a sensibility of 80% and a specificity of 100%. In the BRCA mutated group, 13 patients out of 16 (82%) were platinum-sensitive, while 3 patients (18%) were platinum-resistant. In the BRCA mutated group, HE4 performed as a predictive marker of chemosensitivity in all patients. The ability to detect platinum-resistant patients before tumor relapse probably could open new therapeutic scenarios.

Increased STAT1 Expression in High Grade Serous Ovarian Cancer Is Associated With a Better Outcome.

Recently it has been demonstrated that constitutively activated signal transducer and activator of transcription 1 (STAT1) gene expression may act as a biomarker of ovarian cancer chemotherapy response. In this study, our objective was to validate the use of STAT1 immunohistochemistry as a prognostic biomarker for disease outcome using a cohort derived from Latin America. We evaluated a cohort of Brazilian high-grade serous ovarian cancer, comprising 65 patients with outcome data covering more than 5 years to determine the prognostic and predictive value of STAT1 expression levels. High-grade serous ovarian cancer tumors were used to construct a tissue microarray. Exploratory analyses were conducted on clinical, histopathological, and STAT1 expression data that included descriptive statistics and Pearson correlative analyses. Survival curves for disease-free survival and overall survival were obtained by the Kaplan-Meier method, and the significance of homogeneity between the classes was assessed by log-rank statistics (Mantel-Cox). High expression of STAT1 in tumors was significantly associated with improved disease-free survival (P = 0.0256) and overall survival (P = 0.0193). Proportional hazards regression analysis showed STAT1 expression had an independent effect on both disease-free survival (P = 0.0358) and overall survival (P = 0.0469). These findings from a Brazilian cohort of patients with ovarian cancer reinforce the association of high STAT1 expression with better response to chemotherapy, providing additional validation of this protein as both a prognostic and predictive biomarker. Collectively, these results together with other recently published studies increase the feasibility of using the STAT1 pathway for the development of novel immunomodulator drugs that could enhance response to treatment.

Genomic markers of ovarian adenocarcinoma and its relevancy to the effectiveness of chemotherapy.

Ovarian cancer is the eighth most common cancer and the seventh highest cause of cancer-associated mortality in women worldwide. It is the second highest cause of mortality among female reproductive malignancies. The current standard first-line treatment for advanced ovarian cancer includes a combination of surgical debulking and standard systemic platinum-based chemotherapy with carboplatin and paclitaxel. Although a deeper understanding of this disease has been attained, relapse occurs in 70% of patients 18 months subsequent to the first-line treatment. Therefore, it is crucial to develop a novel drug that effectively affects ovarian cancer, particularly tumors that are resistant to current chemotherapy. The aim of the present study was to identify genes whose expression may be used to predict survival time or prognosis in ovarian cancer patients treated with chemotherapy. Gene or protein expression is an important issue in chemoresistance and survival prediction in ovarian cancer. In the present study, the research group consisted of patients treated at the Surgical Clinic of the Gynecology and Obstetrics Gynecological Clinical Hospital, Poznan University of Medical Sciences (Poznan, Poland) between May 2006 and November 2014. Additional eligibility criteria were a similar severity (International Federation of Gynecolgy and Obstetrics stage III) at the time of diagnosis, treatment undertaken in accordance with the same schedule, and an extremely good response to treatment or a lack of response to treatment. The performance of the OncoScan® assay was evaluated by running the assay on samples obtained from the four patients and by following the recommended protocol outlined in the OncoScan assay manual. The genomic screening using Affymetrix OncoScan Arrays resulted in the identification of large genomic rearrangements across all cancer tissues. In general, chromosome number changes were detected in all examined tissues. The OncoScan arrays enabled the identification of ~100 common somatic mutations. Chemotherapy response in ovarian cancer is extremely complex and challenging to study. The present study identified specific genetic alterations associated with ovarian cancer, but not with response for treatment.