A personalized probabilistic approach to ovarian cancer diagnostics.

Objective: The identification/development of a machine learning-based classifier that utilizes metabolic profiles of serum samples to accurately identify individuals with ovarian cancer.

Methods: Serum samples collected from 431 ovarian cancer patients and 133 normal women at four geographic locations were analyzed by mass spectrometry. Reliable metabolites were identified using recursive feature elimination coupled with repeated cross-validation and used to develop a consensus classifier able to distinguish cancer from non-cancer.

High throughput, label-free isolation of circulating tumor cell clusters in meshed microwells.

Extremely rare circulating tumor cell (CTC) clusters are both increasingly appreciated as highly metastatic precursors and virtually unexplored. Technologies are primarily designed to detect single CTCs and often fail to account for the fragility of clusters or to leverage cluster-specific markers for higher sensitivity. Meanwhile, the few technologies targeting CTC clusters lack scalability.

Label-free microfluidic enrichment of cancer cells from non-cancer cells in ascites.

The isolation of a patient's metastatic cancer cells is the first, enabling step toward treatment of that patient using modern personalized medicine techniques. Whereas traditional standard-of-care approaches select treatments for cancer patients based on the histological classification of cancerous tissue at the time of diagnosis, personalized medicine techniques leverage molecular and functional analysis of a patient's own cancer cells to select treatments with the highest likelihood of being effective. Unfortunately, the pure populations of cancer cells required for these analyses can be difficult to acquire, given that metastatic cancer cells typically reside in fluid containing many different cell populations.

A phase II randomized, double-blind trial of a polyvalent Vaccine-KLH conjugate (NSC 748933 IND# 14384) + OPT-821 versus OPT-821 in patients with epithelial ovarian, fallopian tube, or peritoneal cancer who are in second or third complete remission: An NRG Oncology/GOG study.

Objective: Early-phase data have demonstrated induction of antibody responses to a polyvalent vaccine conjugate (Globo-H, GM2, MUC1-TN, TF) with adjuvant OPT-821. We sought to determine if this combination decreases the hazard of progression or death compared to OPT-821 alone in patients with ovarian cancer in second/third clinical complete remission following chemotherapy. Secondary and translational objectives were overall survival (OS), safety, and immunogenicity.

Niraparib Maintenance Treatment Improves Time Without Symptoms or Toxicity (TWiST) Versus Routine Surveillance in Recurrent Ovarian Cancer: A TWiST Analysis of the ENGOT-OV16/NOVA Trial.

Purpose: This study estimated time without symptoms or toxicity (TWiST) with niraparib compared with routine surveillance (RS) in the maintenance treatment of patients with recurrent ovarian cancer.

Patients And Methods: Mean progression-free survival (PFS) was estimated for niraparib and RS by fitting parametric survival distributions to Kaplan-Meier data for 553 patients with recurrent ovarian cancer who were enrolled in the phase III ENGOT-OV16/NOVA trial. Patients were categorized according to the presence or absence of a germline mutation-gmut and non-gmut cohorts.

Niraparib Maintenance Therapy in Patients With Recurrent Ovarian Cancer After a Partial Response to the Last Platinum-Based Chemotherapy in the ENGOT-OV16/NOVA Trial.

Purpose: In the ENGOT-OV16/NOVA trial (ClinicalTrials.gov identifier: NCT01847274), maintenance therapy with niraparib, a poly(ADP-ribose) polymerase inhibitor, prolonged progression-free survival in patients with platinum-sensitive, recurrent ovarian cancer who had a response to their last platinum-based chemotherapy. The objective of the study was to assess the clinical benefit and patient-reported outcomes in patients who had a partial response (PR) and complete response (CR) to their last platinum-based therapy.

Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

Precision or personalized cancer medicine is a clinical approach that strives to customize therapies based upon the genomic profiles of individual patient tumors. Machine learning (ML) is a computational method particularly suited to the establishment of predictive models of drug response based on genomic profiles of targeted cells. We report here on the application of our previously established open-source support vector machine (SVM)-based algorithm to predict the responses of 175 individual cancer patients to a variety of standard-of-care chemotherapeutic drugs from the gene-expression profiles (RNA-seq or microarray) of individual patient tumors.

Quality of life in patients with recurrent ovarian cancer treated with niraparib versus placebo (ENGOT-OV16/NOVA): results from a double-blind, phase 3, randomised controlled trial.

Background: Quality of life (QOL) has become an important complementary endpoint in cancer clinical studies alongside more traditional assessments (eg, tumour response, progression-free survival, overall survival). Niraparib maintenance treatment has been shown to significantly improve progression-free survival in patients with recurrent ovarian cancer. We aimed to assess whether the benefits of extending progression-free survival are offset by treatment-associated toxic effects that affect QOL.

Evidence for the importance of post-transcriptional regulatory changes in ovarian cancer progression and the contribution of miRNAs.

High-throughput technologies have identified significant changes in patterns of mRNA expression over cancer development but the functional significance of these changes often rests upon the assumption that observed changes in levels of mRNA accurately reflect changes in levels of their encoded proteins. We systematically compared the expression of 4436 genes on the RNA and protein levels between discrete tumor samples collected from the ovary and from the omentum of the same OC patient. The overall correlation between global changes in levels of mRNA and their encoding proteins is low (r = 0.

Niraparib Maintenance Therapy in Platinum-Sensitive, Recurrent Ovarian Cancer.

Background: Niraparib is an oral poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP) 1/2 inhibitor that has shown clinical activity in patients with ovarian cancer. We sought to evaluate the efficacy of niraparib versus placebo as maintenance treatment for patients with platinum-sensitive, recurrent ovarian cancer.

Methods: In this randomized, double-blind, phase 3 trial, patients were categorized according to the presence or absence of a germline BRCA mutation (gBRCA cohort and non-gBRCA cohort) and the type of non-gBRCA mutation and were randomly assigned in a 2:1 ratio to receive niraparib (300 mg) or placebo once daily.

Highly-accurate metabolomic detection of early-stage ovarian cancer.

High performance mass spectrometry was employed to interrogate the serum metabolome of early-stage ovarian cancer (OC) patients and age-matched control women. The resulting spectral features were used to establish a linear support vector machine (SVM) model of sixteen diagnostic metabolites that are able to identify early-stage OC with 100% accuracy in our patient cohort. The results provide evidence for the importance of lipid and fatty acid metabolism in OC and serve as the foundation of a clinically significant diagnostic test.

Glycomic analysis of membrane glycoproteins with bisecting glycosylation from ovarian cancer tissues reveals novel structures and functions.

Biomarkers capable of detecting and targeting epithelial ovarian cancer cells for diagnostics and therapeutics would be extremely valuable. Ovarian cancer is the deadliest reproductive malignancy among women in the U.S.

Ectopic over-expression of miR-429 induces mesenchymal-to-epithelial transition (MET) and increased drug sensitivity in metastasizing ovarian cancer cells.

Objective: We recently determined that the ectopic over-expression of miR-429 and other members of the miR-200 family of microRNAs in ovarian cancer (OC) mesenchymal-like cell lines induces mesenchymal-to-epithelial transition (MET) with a concomitant increase in sensitivity to platinum drugs. We sought to determine if metastasizing OC cells isolated from an OC patient could also be induced by miR-429 to undergo MET and become sensitized to established first-line platinum-based therapies.

Methods: We established and characterized a new primary cell line (OCI-984) from free-floating OC cells isolated from the ascites fluid of an advanced stage OC patient.

Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression.

Background: Documented changes in levels of microRNAs (miRNA) in a variety of diseases including cancer are leading to their development as early indicators of disease, and as a potential new class of therapeutic agents. A significant hurdle to the rational application of miRNAs as therapeutics is our current inability to reliably predict the range of molecular and cellular consequences of perturbations in the levels of specific miRNAs on targeted cells. While the direct gene (mRNA) targets of individual miRNAs can be computationally predicted with reasonable degrees of accuracy, reliable predictions of the indirect molecular effects of perturbations in miRNA levels remain a major challenge in molecular systems biology.

p66Shc longevity protein regulates the proliferation of human ovarian cancer cells.

p66Shc functions as a longevity protein in murine and exhibits oxidase activity in regulating diverse biological activities. In this study, we investigated the role of p66Shc protein in regulating ovarian cancer (OCa) cell proliferation. Among three cell lines examined, the slowest growing OVCAR-3 cells have the lowest level of p66Shc protein.

High-dose chemotherapy with autologous stem cell support as salvage therapy in recurrent gestational trophoblastic disease.

Background: Gestational trophoblastic disease usually follows a molar pregnancy but can occur also after an abortion or a term pregnancy. In only 10% of cases will treatment be required; and usually, single-agent chemotherapy will suffice. In high-risk disease, the multiagent regimen EMA-CO is usually used; and if that fails, most oncologists will use the EMA-EP regimen.

Molecular profiling supports the role of epithelial-to-mesenchymal transition (EMT) in ovarian cancer metastasis.

Background: While metastasis ranks among the most lethal of all cancer-associated processes, on the molecular level, it remains one of the least well understood. One model that has gained credibility in recent years is that metastasizing cells at least partially recapitulate the developmental process of epithelial-to-mesenchymal transition (EMT) in their transit from primary to metastatic sites. While experimentally supported by cell culture and animal model studies, the lack of unambiguous confirmatory evidence in cancer patients has led to persistent challenges to the model's relevance in humans.

Molecular profiling predicts the existence of two functionally distinct classes of ovarian cancer stroma.

Although stromal cell signaling has been shown to play a significant role in the progression of many cancers, relatively little is known about its importance in modulating ovarian cancer development. The purpose of this study was to investigate the process of stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues. RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133 Plus 2.

Evidence for the complexity of microRNA-mediated regulation in ovarian cancer: a systems approach.

MicroRNAs (miRNAs) are short (∼22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. Previous studies have shown that miRNAs inhibit the translation and facilitate the degradation of their targeted messenger RNAs (mRNAs) making them attractive candidates for use in cancer therapy. However, the potential clinical utility of miRNAs in cancer therapy rests heavily upon our ability to understand and accurately predict the consequences of fluctuations in levels of miRNAs within the context of complex tumor cells.

Rapid mass spectrometric metabolic profiling of blood sera detects ovarian cancer with high accuracy.

Background: Ovarian cancer diagnosis is problematic because the disease is typically asymptomatic, especially at the early stages of progression and/or recurrence. We report here the integration of a new mass spectrometric technology with a novel support vector machine computational method for use in cancer diagnostics, and describe the application of the method to ovarian cancer.

Methods: We coupled a high-throughput ambient ionization technique for mass spectrometry (direct analysis in real-time mass spectrometry) to profile relative metabolite levels in sera from 44 women diagnosed with serous papillary ovarian cancer (stages I-IV) and 50 healthy women or women with benign conditions.

Gene expression profiling supports the hypothesis that human ovarian surface epithelia are multipotent and capable of serving as ovarian cancer initiating cells.

Background: Accumulating evidence suggests that somatic stem cells undergo mutagenic transformation into cancer initiating cells. The serous subtype of ovarian adenocarcinoma in humans has been hypothesized to arise from at least two possible classes of progenitor cells: the ovarian surface epithelia (OSE) and/or an as yet undefined class of progenitor cells residing in the distal end of the fallopian tube.

Methods: Comparative gene expression profiling analyses were carried out on OSE removed from the surface of normal human ovaries and ovarian cancer epithelial cells (CEPI) isolated by laser capture micro-dissection (LCM) from human serous papillary ovarian adenocarcinomas.

Selective removal of ovarian cancer cells from human ascites fluid using magnetic nanoparticles.

Unlabelled: A majority of ovarian cancer metastases result from the shedding of malignant cells from the primary tumor into the abdominal cavity. Free-floating cancer cells in serous effusions of late-stage ovarian cancer patients may spread to internal organs, making effective treatment extremely difficult. Selective removal of ovarian cancer cells from serous fluids may abate metastasis and improve long-term prognoses.

Identification of candidate biomarkers with cancer-specific glycosylation in the tissue and serum of endometrioid ovarian cancer patients by glycoproteomic analysis.

Epithelial ovarian cancer is diagnosed less than 25% of the time when the cancer is confined to the ovary, leading to 5-year survival rates of less than 30%. Therefore, there is an urgent need for early diagnostics for ovarian cancer. Our study using glycotranscriptome comparative analysis of endometrioid ovarian cancer tissue and normal ovarian tissue led to the identification of distinct differences in the transcripts of a restricted set of glycosyltransferases involved in N-linked glycosylation.

Comparison of a novel surgical approach for radical hysterectomy: robotic assistance versus open surgery.

To report the learning curve and perioperative outcomes for robotic radical hysterectomy using a unilateral surgical approach transferred directly from one surgeon's open radical hysterectomy experience, thirty-two consecutive robotic radical hysterectomy cases (10/2006-1/2009) were contrasted to a cohort of 20 consecutive open radical hysterectomies (2/2005-2/2008). Perioperative characteristics compared included operative time, number of nodes, estimated blood loss, length of hospital stay, and complications. Robotic operative times were significantly longer than for open (122.