Circulating Tumor Cell-Free DNA Genes as Prognostic Gene Signature for Platinum Resistant Ovarian Cancer Diagnosis.

Clinical management of gynecological cancer begins by optimal debulking with first-line platinum-based chemotherapy. However, in ~80% patients, ovarian cancer will recur and is lethal. Prognostic gene signature panel identifying platinum-resistance enables better patient stratification for precision therapy. Retrospectively collected serum from 11 "poor" (<6 months progression free interval [PFI]) and 22 "favorable" (>24 months PFI) prognosis patients, were evaluated using circulating cell-free DNA (cfDNA). DNA from both groups showed 50 to 10 000 bp fragments. Pairwise analysis of sequenced cfDNA from patients showed that gene dosages were higher for 29 genes and lower for 64 genes in poor than favorable prognosis patients. Gene ontology analysis of higher dose genes predominantly grouped into cytoskeletal proteins, while lower dose genes, as hydrolases and receptors. Higher dosage genes searched for cancer-relatedness in Reactome database indicated 15 genes were referenced with cancer. Among them 3 genes, TGFBR2, ZMIZ2, and NRG2, were interacting with more than 4 cancer-associated genes. Protein expression analysis of tumor samples indicated that TGFBR2 was downregulated and ZMIZ2 was upregulated in poor prognosis patients. Our results indicate that the cfDNA gene dosage combined with protein expression in tumor samples can serve as gene signature panel for prognosis determination amongst ovarian cancer patients.

Shifts in gut and vaginal microbiomes are associated with cancer recurrence time in women with ovarian cancer.

Many studies investigating the human microbiome-cancer interface have focused on the gut microbiome and gastrointestinal cancers. Outside of human papillomavirus driving cervical cancer, little is known about the relationship between the vaginal microbiome and other gynecological cancers, such as ovarian cancer. In this retrospective study, we investigated the relationship between ovarian cancer, platinum-free interval (PFI) length, and vaginal and gut microbiomes. We observed that Lactobacillus-dominated vaginal communities were less common in women with ovarian cancer, as compared to existing datasets of similarly aged women without cancer. Primary platinum-resistance (PPR) disease is strongly associated with survivability under one year, and we found over one-third of patients with PPR (PFI < 6 months, n = 17) to have a vaginal microbiome dominated by Escherichia (>20% relative abundance), while only one platinum super-sensitive (PFI > 24 months, n = 23) patient had an Escherichia-dominated microbiome. Additionally, L. iners was associated with little, or no, gross residual disease, while other Lactobacillus species were dominant in women with >1 cm gross residual disease. In the gut microbiome, we found patients with PPR disease to have lower phylogenetic diversity than platinum-sensitive patients. The trends we observe in women with ovarian cancer and PPR disease, such as the absence of Lactobacillus and presence of Escherichia in the vaginal microbiome as well as low gut microbiome phylogenetic diversity have all been linked to other diseases and/or pro-inflammatory states, including bacterial vaginosis and autoimmune disorders. Future prospective studies are necessary to explore the translational potential and underlying mechanisms driving these associations.

The presence of an endometrioid component does not alter the clinicopathologic profile or survival of patients with uterine serous cancer: A gynecologic oncology group (GOG/NRG) study of 934 women.

OBJECTIVE: While most cases of endometrial cancer can readily be classified as pure endometrioid, pure serous, or another type, others show an apparent mixture of serous and endometrioid components, or indeterminate serous versus endometrioid features. Since serous histology carries a worse prognosis than endometrioid, Gynecologic Oncology Group protocol GOG-8032 was established to examine whether the presence of a non-serous component is a favorable feature in an otherwise serous cancer. METHODS: 934 women with serous cancer were prospectively identified among a larger group enrolled in GOG-0210. Six expert gynecologic pathologists classified each case as pure serous (SER, n=663), mixed serous and endometrioid (SER-EM-M, n=138), or indeterminate serous v. endometrioid (SER-EM-I, n=133) by H&E morphology. Follow-up data from GOG-0210 were analyzed. RESULTS: The subgroups did not differ on BMI, race, ethnicity, lymphovascular invasion, cervical invasion, ovary involvement, peritoneal involvement, omental involvement, FIGO stage, or planned adjuvant treatment. SER-EM-M patients were younger (p=0.0001) and less likely to have nodal involvement (p=0.0287). SER patients were less likely to have myoinvasion (p=0.0002), and more likely to have adnexal involvement (p=0.0108). On univariate analysis, age, serous subtype, race, and components of FIGO staging predicted both progression-free and overall survival. On multiple regression, however, serous subtype (SER, SER-EM-M, or SER-EM-I) did not significantly predict survival. CONCLUSIONS: There were few clinicopathologic differences between cases classified as SER, SER-EM-M, and SER-EM-I. Cases with a mixture of serous and endometrioid morphology, as well as cases with morphology indeterminate for serous v. endometrioid type, had the same survival as pure serous cases. NCT#: NCT00340808.

Potential and mechanism of mebendazole for treatment and maintenance of ovarian cancer.

OBJECTIVE: Mebendazole and other anti-parasitic drugs are being used off-prescription based on social media and unofficial accounts of their anti-cancer activity. The purpose of this study was to conduct a controlled evaluation of mebendazole's therapeutic efficacy in cell culture and in vivo models of ovarian cancer. The majority of ovarian cancers harbor p53 null or missense mutations, therefore the effects of p53 mutations and a mutant p53 reactivator, PRIMA-1MET (APR246) on mebendazole activity were evaluated. METHODS: Mebendazole was evaluated in cisplatin-resistant high grade serous stage 3C ovarian cancer patient derived xenograft (PDX) models: PDX-0003 (p53 null) and PDX-0030 (p53 positive), and on ovarian cancer cell lines: MES-OV (p53 R282W), ES2 (p53 S241F), A2780 (p53 wild type), SKOV3 parental (p53 null) and isogenic sublines, SKOV3 R273H p53 and SKOV3 R248W p53. Drug synergy and mechanisms were evaluated in cell cultures using isobolograms, clonogenic assays and western blots. Prevention of tumor establishment was studied in a MES-OV orthotopic model. RESULTS: Mebendazole inhibited growth of ovarian cancer cell cultures at nanomolar concentrations and PDXs at doses up to 50 mg/kg, and reduced orthotopic tumor establishment at 50 mg/kg. The mechanism of mebendazole was associated with p53-independent induction of p21 and tubule depolymerization. PRIMA-1MET also inhibited tumor establishment and worked synergistically with mebendazole in cell culture to inhibit growth and induce intrinsic apoptosis through a p53- and tubule destabilization-independent mechanism. CONCLUSION: This work demonstrates the therapeutic potential of repurposing mebendazole and supports clinical development of mebendazole for ovarian cancer therapy and maintenance.

Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients.

BACKGROUND AND OBJECTIVE: In diagnosis of cervical cancer patients, lymph node (LN) metastasis is a highly important indicator for the following treatment management. Although CT/PET (i.e., computed tomography/positron emission tomography) examination is the most effective approach for this detection, it is limited by the high cost and low accessibility, especially for the rural areas in the U.S.A. or other developing countries. To address this challenge, this investigation aims to develop and test a novel radiomics-based CT image marker to detect lymph node metastasis for cervical cancer patients. METHODS: A total of 1,763 radiomics features were first computed from the segmented primary cervical tumor depicted on one CT image with the maximal tumor region. Next, a principal component analysis algorithm was applied on the initial feature pool to determine an optimal feature cluster. Then, based on this optimal cluster, the prediction models (i.e., logistic regression or support vector machine) were trained and optimized to generate an image marker to detect LN metastasis. In this study, a retrospective dataset containing 127 cervical cancer patients were established to build and test the model. The model was trained using a leave-one-case-out (LOCO) cross-validation strategy and image marker performance was evaluated using the area under receiver operation characteristic (ROC) curve (AUC). RESULTS: The results indicate that the SVM based imaging marker achieved an AUC value of 0.841 ± 0.035. When setting an operating threshold of 0.5 on model-generated prediction scores, the imaging marker yielded a positive and negative predictive value (PPV and NPV) of 0.762 and 0.765 respectively, while the total accuracy is 76.4%. CONCLUSIONS: This study initially verified the feasibility of utilizing CT image and radiomics technology to develop a low-cost image marker to detect LN metastasis for assisting stratification of cervical cancer patients.

Corrigendum to "Phase II evaluation of copanlisib, a selective inhibitor of Pi3kca, in patients with persistent or recurrent endometrial carcinoma harboring PIK3CA hotspot mutations: An NRG oncology study (NRG-GY008)" [Gynecol. Oncol. Rep. 31 (2020) 100532].

[This corrects the article DOI: 10.1016/j.gore.2019.100532.].

Randomized Phase II Trial of Nivolumab Versus Nivolumab and Ipilimumab for Recurrent or Persistent Ovarian Cancer: An NRG Oncology Study.

PURPOSE: Single-agent PD-1 blockade exhibits limited efficacy in epithelial ovarian cancer (EOC). We evaluated ipilimumab plus nivolumab compared with nivolumab alone in women with persistent or recurrent EOC. METHODS: Eligibility criteria included measurable disease, 1-3 prior regimens, and platinum-free interval (PFI) < 12 months. Participants were randomly allocated to intravenous nivolumab (every 2 weeks) or induction with nivolumab plus ipilimumab for 4 doses (every 3 weeks), followed by every-2-week maintenance nivolumab for a maximum of 42 doses. The primary null hypothesis was equal probability of objective response within 6 months of random allocation in each arm. RESULTS: One hundred patients were allocated to receive either nivolumab (n = 49), or nivolumab plus ipilimumab (n = 51), with PFI of < 6 months in 62%. Six (12.2%) responses occurred within 6 months in the nivolumab group and 16 (31.4%) in the nivolumab plus ipilimumab group (odds ratio, 3.28; 85% CI, 1.54 to infinity; P = .034). The median progression-free survival (PFS) was 2 and 3.9 months in the nivolumab and nivolumab plus ipilimumab groups, respectively, with a PFI-stratified hazard ratio of 0.53 (95% CI, 0.34 to 0.82); the respective hazard ratio for death was 0.79 (95% CI, 0.44 to 1.42). Grade ≥ 3 related adverse events occurred in 33% of patients in the nivolumab group and 49% in the combination group, with no treatment-related deaths. PD-L1 expression was not significantly associated with response in either treatment group. CONCLUSION: Compared with nivolumab alone, the combination of nivolumab and ipilimumab in EOC resulted in superior response rate and longer, albeit limited, PFS, with toxicity of the combination regimen comparable to prior reports. Additional combination studies to enhance durability of the dual regimen are warranted.

Phase II evaluation of copanlisib, a selective inhibitor of Pi3kca, in patients with persistent or recurrent endometrial carcinoma harboring PIK3CA hotspot mutations: An NRG Oncology study (NRG-GY008).

PURPOSE: NRG Oncology conducted a phase II trial to assess the antitumor activity and tolerability of copanlisib, a selective inhibitor of PIK3CA, in persistent or recurrent endometrial carcinoma harboring hotspot PIK3CA mutations. PATIENTS AND METHODS: Eligible patients had endometrial cancer with endometrioid, serous or mixed histology, a somatic PIK3CA gene mutation, measurable disease, and GOG performance status ≤2. Treatment consisted of IV copanlisib (60 mg weekly, day 1, 8 and 15 of 28-day cycle) until disease progression or prohibitive toxicity. The primary endpoints of the study were objective tumor response as assessed by RECIST 1.1 and to determine the nature and degree of toxicity of copanlisib as assessed by CTCAE version 4. The study used a 2-stage group sequential design. RESULTS: Eleven patients were enrolled onto stage I of the treatment trial. Five patients had endometrioid, four serous and two had a tumor of mixed histology. The most common PIK3CA mutation was Q546X (n = 3) in exon 9. The most common grade 3 or 4 AE was hyperglycemia. No grade 5 adverse events were reported. No clinical responses were detected. Six patients had a best overall response of stable disease. Of 11 who initiated treatment, 10 progressed on treatment. One patient with stable disease on copanlisib withdrew from treatment secondary to relocation. The median progression-free survival (PFS) was 2.8 months; at 6 months 27% were alive, progression-free. The median overall survival (OS) was 15.2 months. Due to the lack of CR/PR continuation of accrual to the second stage of accrual was not warranted. CONCLUSION: Copanlisib is well tolerated but has limited activity as a single agent in this population.

Intellectual Equipoise and Challenges: Accruing Patients With Advanced Cancer to a Trial Randomizing to Surgical or Nonsurgical Management (SWOG S1316).

BACKGROUND: Prospective, randomized trials are needed to determine optimal treatment approaches for palliative care problems such as malignant bowel obstruction (MBO). Randomization poses unique issues for such studies, especially with divergent treatment approaches and varying levels of equipoise. We report our experience accruing randomized patients to the Prospective Comparative Effectiveness Trial for Malignant Bowel Obstruction (SWOG S1316) study, comparing surgical and nonsurgical management of MBO. METHODS: Patients with MBO who were surgical candidates and had treatment equipoise were accrued and offered randomization to surgical or nonsurgical management. Patients choosing nonrandomization were offered prospective observation. Trial details are listed on www.clinicaltrials.gov (NCT #02270450). An accrual algorithm was developed to enhance enrollment. RESULTS: Accrual is ongoing with 176 patients enrolled. Most (89%) patients chose nonrandomization, opting for nonsurgical management. Of 25 sites that have accrued to this study, 6 enrolled patients on the randomization arm. Approximately 59% (20/34) of the randomization accrual goal has been achieved. Patient-related factors and clinician bias have been the most prevalent reasons for lack of randomization. An algorithm was developed from clinician experience to aid randomization. Using principles in this tool, repeated physician conversations discussing treatment options and goals of care, and a supportive team-approach has helped increase accrual. CONCLUSIONS: Experience gained from the S1316 study can aid future palliative care trials. Although difficult, it is possible to randomize patients to palliative studies by giving clinicians clear recommendations utilizing an algorithm of conversation, allotment of necessary time to discuss the trial, and encouragement to overcome internal bias.

Extending the platinum-free interval: The impact of omitting 2nd line platinum chemotherapy in intermediate platinum-sensitive ovarian cancer.

OBJECTIVES: Patients with epithelial ovarian cancer (EOC) recurring between 6 and 12 months after primary platinum chemotherapy have worse prognosis than those recurring in >12 months. Artificially prolonging the platinum-free interval (PFI) with cytotoxic chemotherapy was tested in MITO-8 with poor outcomes. This study aimed to determine the impact of using non-platinum or targeted therapy in 2nd line treatment of EOC patients recurring 6-12 months after completion of primary platinum-based chemotherapy. METHODS: A multi-institutional retrospective review of 177 patients with recurrent EOC and PFI of 6-12 months following primary chemotherapy was performed comparing platinum versus non-platinum chemotherapy or targeted therapy for 2nd line treatment. PFI1 was defined as the date of last chemotherapy to date of recurrence. PFS2/3 were defined as start of 2nd or 3rd line chemotherapy to start of subsequent line. RESULTS: Of 177 patients, the majority of patients were Caucasian, had serous histology, and underwent primary cytoreductive surgery. Median PFI1 was 8.2 months (95% CI 8-9 months). Second line platinum was omitted in 28% of patients. Bevacizumab was used in 2nd line in 16% of patients; 19% received other targeted therapies. Median PFS2 for platinum chemotherapy was longer than non-platinum (7.1 vs 3 months, p = 0.0114). Median PFS2 was significantly longer for platinum vs. targeted therapy (7.1 vs. 3 months p = 0.0431). Median OS for platinum in 2nd line vs. no platinum was 43.6 vs. 37.6 months (p = 0.0174). CONCLUSIONS: Use of non-platinum chemotherapy and even targeted therapy to prolong PFI in patients with EOC recurring between 6 and 12 months leads to worse survival.

A phase 1b dose escalation study of ipafricept (OMP54F28) in combination with paclitaxel and carboplatin in patients with recurrent platinum-sensitive ovarian cancer.

OBJECTIVES: The WNT pathway is an important oncologic driver of epithelial ovarian cancer (EOC). The first-in-class recombinant fusion protein ipafricept (IPA) blocks Wnt signaling through binding of Wnt ligands. This phase Ib trial was designed to determine the maximum tolerated dose (MTD) and recommended phase 2 dose (RPh2) for IPA in combination with taxane and platinum therapy (C/P). METHODS: Dose escalation started with a standard 3 + 3 design for IPA/C/P with q3w intravenous IPA on Day 1, in cycles 1 to 6 with C (AUC = 5 mg/ml·min) and P (175 mg/m2). For enhanced bone safety the trial was revised to 6-patient cohorts with a q3w regimen of IPA on Day 1 and C/P on Day 3 (IPA → C/P). RESULTS: 37 patients have been treated; 30 of whom were treated following protocol revision to q3w IPA(D1) → C/P(D3) (2 & 4 mg/kg). IPA-related TEAEs that occurred in ≥15% included: fatigue (40%); nausea (35%); diarrhea and decreased appetite (22%) each; dysgeusia (19%); and vomiting (16.2%). 22% reported ≥1 IPA related TEAE Grade ≥3 the most common of which was neutropenia at 16%. There were no DLTs; the MTD was not reached. The maximum administered dose based on bone safety was 6 mg/kg. The overall response rate (ORR) was 75.7%. Median PFS was 10.3 months (95% CI 8.5-14.2) and OS 33 months (95% CI 23.4-NR). CONCLUSIONS: IPA is well tolerated in combination with sequential C/P. ORR, PFS and OS are comparable to historical data but bone toxicity at efficacy doses of this particular Wnt inhibitor limit further development in EOC.

Update in the use and evaluation of poly (ADP-ribose) polymerase inhibitors in epithelial ovarian cancer: current and pending clinical research.

PURPOSE OF REVIEW: This review will provide an update of recently presented clinical data as well as discuss ongoing trials focused on the incorporation of poly (ADP-ribose) polymerase inhibitors (PARPi) into the treatment paradigm for ovarian cancer. RECENT FINDINGS: As of this publication, PARPi have indications in many parts of the globe as maintenance therapy following response to platinum-based chemotherapy in the setting of platinum-sensitive recurrence. In addition, in the United States, two PARPi have indications as monotherapy treatment for recurrent ovarian cancer in patients with a BRCA mutation and at least two prior lines of therapy. Exciting data was published in October 2018, demonstrating an unprecedented benefit to utilization of olaparib following response to front-line platinum-based chemotherapy among patients with a BRCA mutation and this data is expected to expand the indication for olaparib globally. SUMMARY: Ongoing studies will seek to expand the benefit of PARPi beyond the BRCA population in front-line therapy as well as to overcome inherent and acquired resistance to PARPi with studies of novel combinations with antiangiogenesis agents, immune-oncology agents and chemotherapy. These efforts may identify more settings and populations in which PARPi provide clinical benefit.

Prospective Evaluation of Multinational Association of Supportive Care in Cancer Risk Index Score for Gynecologic Oncology Patients With Febrile Neutropenia.

BACKGROUND: The Multinational Association of Supportive Care of Cancer (MASCC) risk-index score has been validated as a stratification tool for febrile neutropenia (FN) risk in a heterogeneous group of cancer patients; recently, it has been deemed a suitable tool in gynecologic oncology patients in a retrospective study. This is a prospective multi-institutional study wherein we sought to validate MASCC score for stratifying FN morbidity in gynecologic oncology patients. METHODS: IRB approval was obtained at 4 institutions for prospective data collection of gynecologic cancer patients admitted with FN from 3/1/2013 to 9/1/2014. Participating institutions have a policy of inpatient management of FN patients receiving chemotherapy. Deidentified data was compiled and processed at the leading institution. RESULTS: In total, 31 patients met inclusion criteria. Most had advanced stage disease (67%). 100% of patients were receiving chemotherapy (57% for primary, 43% for recurrent disease). 55% had a positive culture. Median MASCC score was 21 (range, 10 to 26); 58% of patients were considered low risk. High risk patients more often had one (11% vs. 38%, P=0.09) or multiple (6% vs. 23%, P=0.28) severe complications, ICU admission (0% vs. 15%, P=0.17), and delay in next chemotherapy cycle (33% vs. 54%, P=0.25). No patients died from FN during the study period. CONCLUSIONS: This pilot data suggests that MASCC score may be a promising tool for determining suitability of outpatient management of FN in gynecologic oncology patients. Larger studies are warranted to achieve statistically significant results, which may enable us to effectively utilize this risk stratification tool for cost containment and avoidance of nosocomial infections.

Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural Networks.

The tumor-stroma ratio (TSR) reflected on hematoxylin and eosin (H&E)-stained histological images is a potential prognostic factor for survival. Automatic image processing techniques that allow for high-throughput and precise discrimination of tumor epithelium and stroma are required to elevate the prognostic significance of the TSR. As a variant of deep learning techniques, transfer learning leverages nature-images features learned by deep convolutional neural networks (CNNs) to relieve the requirement of deep CNNs for immense sample size when handling biomedical classification problems. Herein we studied different transfer learning strategies for accurately distinguishing epithelial and stromal regions of H&E-stained histological images acquired from either breast or ovarian cancer tissue. We compared the performance of important deep CNNs as either a feature extractor or as an architecture for fine-tuning with target images. Moreover, we addressed the current contradictory issue about whether the higher-level features would generalize worse than lower-level ones because they are more specific to the source-image domain. Under our experimental setting, the transfer learning approach achieved an accuracy of 90.2 (vs. 91.1 for fine tuning) with GoogLeNet, suggesting the feasibility of using it in assisting pathology-based binary classification problems. Our results also show that the superiority of the lower-level or the higher-level features over the other ones was determined by the architecture of deep CNNs.

Prediction of chemotherapy response in ovarian cancer patients using a new clustered quantitative image marker.

This study aimed to investigate the feasibility of integrating image features computed from both spatial and frequency domain to better describe the tumor heterogeneity for precise prediction of tumor response to postsurgical chemotherapy in patients with advanced-stage ovarian cancer. A computer-aided scheme was applied to first compute 133 features from five categories namely, shape and density, fast Fourier transform, discrete cosine transform (DCT), wavelet, and gray level difference method. An optimal feature cluster was then determined by the scheme using the particle swarm optimization algorithm aiming to achieve an enhanced discrimination power that was unattainable with the single features. The scheme was tested using a balanced dataset (responders and non-responders defined using 6 month PFS) retrospectively collected from 120 ovarian cancer patients. By evaluating the performance of the individual features among the five categories, the DCT features achieved the highest predicting accuracy than the features in other groups. By comparison, a quantitative image marker generated from the optimal feature cluster yielded the area under ROC curve (AUC) of 0.86, while the top performing single feature only had an AUC of 0.74. Furthermore, it was observed that the features computed from the frequency domain were as important as those computed from the spatial domain. In conclusion, this study demonstrates the potential of our proposed new quantitative image marker fused with the features computed from both spatial and frequency domain for a reliable prediction of tumor response to postsurgical chemotherapy.

Consideration of older patients for enrollment in phase 1 clinical trials: Exploring treatment related toxicities and outcomes.

OBJECTIVES: Age imposes a disparity in the treatment of and outcomes with gynecologic cancer. Older patients are underrepresented in primary treatment trials, but little is known about their ability to withstand trial-based treatment for recurrent or refractory disease. This study sought to examine treatment-related toxicities and outcomes of older versus younger patients participating in phase 1 clinical trials. METHODS: A retrospective analysis of patients enrolled in phase 1 clinical trials for gynecologic malignancies from 2010 to 2016 was performed. Demographic and clinic-pathologic data was abstracted. Toxicities were defined as either grade III or IV by CTCAE criteria. Best response was calculated using RECIST criteria. Associations between categorical variables were determined using Fisher's exact test and continuous variables using Wilcoxon rank sum test. Survival was estimated using the Kaplan-Meier method. RESULTS: 237 patients were included with 22% (n=51) comprising the older cohort (≥70years). The vast majority (98%) were treated for recurrent disease. Older patients incurred similar grade III/IV hematologic (21% vs 16%, p=0.38) and non-hematologic toxicities (26% vs 29%, p=0.64). Older patients discontinued treatment due to toxicity only 8% of the time. Median survival was 13.0 and 10.3months in the <70 and ≥70 groups, respectively (p=0.35). 63% of patients ≥70 achieved clinical benefit. CONCLUSIONS: Although historically older patients have not been routinely considered for enrollment in phase 1 trials, our data demonstrates similar toxicity profiles to that of younger patients and 63% clinical benefit rate. Thus, with careful selection, patients ≥70 should be considered when facing recurrent or refractory gynecologic cancer.

A contemporary framework of health equity applied to gynecologic cancer care: A Society of Gynecologic Oncology evidenced-based review.

Health disparities are defined as the preventable difference in the burden of disease, injury, and violence, or opportunity to achieve optimal health that socially disadvantaged populations experience compared to the population as a whole. Disparities in incidence and cancer outcomes for women with gynecologic malignancies have been well described particularly for American women of Black race. The etiology of these disparities has been tied to socio-economics, cultural, educational and genetic factors. While access to high quality treatment has been primarily linked to survival from cervical and ovarian cancer, innate biologic distinctions have been principally cited as reasons for differences in incidence and mortality in cancers of the uterine corpus. This article will update the framework of disparities to incorporate a broader understanding of the social determinants of health and how they affect health equity by addressing the root causes of disparities within the health care system. Special populations are identified who are at risk for health inequities which include but are not limited to Black race, underserved racial and ethnic minorities (e.g. indigenous peoples, low English fluency), trans/gender nonconforming people and rural populations. Each of these populations at risk have unique structural barriers within the healthcare system impacting gynecologic cancer outcomes. The authors provide practical recommendations for practitioners aimed at eliminating cancer related outcome disparities.

Management of the toxicities of common targeted therapeutics for gynecologic cancers.

As precision medicine has become a focus in oncology in recent years, many targeted and biologic agents are being used along with or in place of traditional cytotoxic chemotherapy. As these drugs have been developed and some have received FDA approval, we have gained substantial data about the adverse event profiles. However, the management and approach to the toxicities incurred and subsequent complications are often not well understood, especially for physicians who have a varied clinical practice. The purpose of this review is to provide an overview of the frequency and types of adverse events and appropriate management steps when prescribing modern targeted therapies for gynecologic cancers in the classes of anti-angiogenic agents, poly-ADP-ribose polymerase (PARP) inhibitors, and immunotherapy drugs.

Factors influencing clinical trial enrollment among ovarian cancer patients.

OBJECTIVE: To characterize patients who did not enroll on a clinical trial and identify barriers that may limit enrollment among patients with advanced epithelial ovarian cancer (EOC) presenting for first-line chemotherapy. METHODS: We conducted a retrospective review of patients diagnosed with stage II-IV EOC from 10/2009-4/2013, a time period during which multiple trials were available to all EOC patients, including optimally debulked, suboptimally debulked, or undergoing neoadjuvant chemotherapy. Enrollment status, demographics, tumor characteristics, and treatment details were recorded. SAS version 9.3 was used for all analyses. RESULTS: 144 patients met study criteria; 67% were enrolled on a trial. Enrolled patients were significantly younger (median 61 vs 68years, p=0.002). Stage (p=0.30), race (p=0.75), and performance status (p=0.38) were similar between enrolled and non-enrolled patients. Distance did not impact enrollment, as nearly half of patients in both groups lived >50miles from the treatment center (39.0% vs 47.8%, p=0.36). Mode of chemotherapy administration significantly differed based on participation (all p<0.05). Despite similar residual disease status (p=1.00) and number of chemotherapy regimens received (p=0.59), patients treated on trial had a higher 3-year survival rate (70.7% vs 51.7%, p=0.031). The difference in median progression-free survival approached significance (20.2 vs 9.2months, p=0.091). CONCLUSION: In an institution where the culture is to offer clinical trials to all eligible patients, 33% of front-line EOC patients did not participate. Increasing age was associated with non-participation. Modifiable barriers must be overcome so that trial enrollment can better reflect true EOC demographics.

Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy.

RATIONALE AND OBJECTIVES: The study aimed to investigate the role of applying quantitative image features computed from computed tomography (CT) images for early prediction of tumor response to chemotherapy in the clinical trials for treating ovarian cancer patients. MATERIALS AND METHODS: A dataset involving 91 patients was retrospectively assembled. Each patient had two sets of pre- and post-therapy CT images. A computer-aided detection scheme was applied to segment metastatic tumors previously tracked by radiologists on CT images and computed image features. Two initial feature pools were built using image features computed from pre-therapy CT images only and image feature difference computed from both pre- and post-therapy images. A feature selection method was applied to select optimal features, and an equal-weighted fusion method was used to generate a new quantitative imaging marker from each pool to predict 6-month progression-free survival. The prediction accuracy between quantitative imaging markers and the Response Evaluation Criteria in Solid Tumors (RECIST) criteria was also compared. RESULTS: The highest areas under the receiver operating characteristic curve are 0.684 ± 0.056 and 0.771 ± 0.050 when using a single image feature computed from pre-therapy CT images and feature difference computed from pre- and post-therapy CT images, respectively. Using two corresponding fusion-based image markers, the areas under the receiver operating characteristic curve significantly increased to 0.810 ± 0.045 and 0.829 ± 0.043 (P < 0.05), respectively. Overall prediction accuracy levels are 71.4%, 80.2%, and 74.7% when using two imaging markers and RECIST, respectively. CONCLUSIONS: This study demonstrated the feasibility of predicting patients' response to chemotherapy using quantitative imaging markers computed from pre-therapy CT images. However, using image feature difference computed between pre- and post-therapy CT images yielded higher prediction accuracy.