Epigenetics in ovarian cancer: premise, properties, and perspectives.

Malignant ovarian tumors bear the highest mortality rate among all gynecological cancers. Both late tumor diagnosis and tolerance to available chemical therapy increase patient mortality. Therefore, it is both urgent and important to identify biomarkers facilitating early identification and novel agents preventing recurrence. Accumulating evidence demonstrates that epigenetic aberrations (particularly histone modifications) are crucial in tumor initiation and development. Histone acetylation and methylation are respectively regulated by acetyltransferases-deacetylases and methyltransferases-demethylases, both of which are implicated in ovarian cancer pathogenesis. In this review, we summarize the most recent discoveries pertaining to ovarian cancer development arising from the imbalance of histone acetylation and methylation, and provide insight into novel therapeutic interventions for the treatment of ovarian carcinoma

Infrequent expression of the cancer-testis antigen, PASD1, in ovarian cancer

Ovarian cancer is very treatable in the early stages of disease; however, it is usually detected in the later stages, at which time, treatment is no longer as effective. If discovered early (Stage I), there is a 90% chance of five-year survival. Therefore, it is imperative that early-stage biomarkers are identified to enhance the early detection of ovarian cancer. Cancer-testis antigens (CTAs), such as Per ARNT SIM (PAS) domain containing 1 (PASD1), are unique in that their expression is restricted to immunologically restricted sites, such as the testis and placenta, which do not express MHC class I, and cancer, making them ideally positioned to act as targets for immunotherapy as well as potential biomarkers for cancer detection where expressed. We examined the expression of PASD1a and b in a number of cell lines, as well as eight healthy ovary samples, eight normal adjacent ovarian tissues, and 191 ovarian cancer tissues, which were predominantly stage I (n = 164) and stage II (n = 14) disease. We found that despite the positive staining of skin cancer, only one stage Ic ovarian cancer patient tissue expressed PASD1a and b at detectable levels. This may reflect the predominantly stage I ovarian cancer samples examined. To examine the restriction of PASD1 expression, we examined endometrial tissue arrays and found no expression in 30 malignant tumor tissues, 23 cases of hyperplasia, or 16 normal endometrial tissues. Our study suggests that the search for a single cancer-testes antigen/biomarker that can detect early ovarian cancer must continue

Programmed cell death 6 interacting protein (PDCD6IP) and Rabenosyn-5 (ZFYVE20) are potential urinary biomarkers for upper gastrointestinal cancer

PURPOSE: Cancer of the upper digestive tract (uGI) is a major contributor to cancer-related death worldwide. Due to a rise in occurrence, together with poor survival rates and a lack of diagnostic or prognostic clinical assays, there is a clear need to establish molecular biomarkers. EXPERIMENTAL DESIGN: Initial assessment was performed on urine samples from 60 control and 60 uGI cancer patients using MS to establish a peak pattern or fingerprint model, which was validated by a further set of 59 samples. RESULTS: We detected 86 cluster peaks by MS above frequency and detection thresholds. Statistical testing and model building resulted in a peak profiling model of five relevant peaks with 88% overall sensitivity and 91% specificity, and overall correctness of 90%. High-resolution MS of 40 samples in the 2-10 kDa range resulted in 646 identified proteins, and pattern matching identified four of the five model peaks within significant parameters, namely programmed cell death 6 interacting protein (PDCD6IP/Alix/AIP1), Rabenosyn-5 (ZFYVE20), protein S100A8, and protein S100A9, of which the first two were validated by Western blotting. CONCLUSIONS AND CLINICAL RELEVANCE: We demonstrate that MS analysis of human urine can identify lead biomarker candidates in uGI cancers, which makes this technique potentially useful in defining and consolidating biomarker patterns for uGI cancer screening

microRNA. Diagnostic Perspective

Biomarkers are biological measures of a biological state. An ideal marker should be safe and easy to measure, cost efficient, modifiable with treatment, and consistent across gender and ethnic groups. To date, none of the available biomarkers satisfy all of these criteria. In addition, the major limitations of these markers are low specificity, sensitivity, and false positive results. Recently identified, microRNAs (miRNAs) are endogenous, evolutionarily conserved small non-coding RNA (about 22-25 nt long), also known as micro-coordinators of gene expression, which have been shown to be an effective tools to study the biology of diseases and to have great potential as novel diagnostic and prognostic biomarkers with high specificity and sensitivity. In fact, it has been demonstrated that miRNAs play a pivotal role in the regulation of a wide range of developmental and physiological processes and their deficiencies have been related to a number of disease. In addition, miRNAs are stable and can be easily isolated and measured from tissues and body fluids. In this review, we provide a perspective on emerging concepts and potential usefulness of miRNAs as diagnostic markers, emphasizing the involvement of specific miRNAs in particular tumor types, subtypes, cardiovascular diseases, diabetes, infectious diseases, and forensic test

MicroRNA-551b expression profile in low and high-grade cervical intraepithelial neoplasia

OBJECTIVE: To evaluate the expression of microRNA (miR)-551b in patients with low and high grade cervical intraepithelial neoplasia (CIN) and to find an association with high-risk Human Papillomavirus (HR-HPV) infection-related prognostic biomarkers. PATIENTS AND METHODS: The expression level of miR-551b was determined in 50 paraffin-embedded cervical specimens (10 normal squamous epithelium, 18 condylomas, 8 CIN1, and 14 CIN2-3) using quantitative Real-time polymerase chain reaction (qRT-PCR). χ2-test compared miR-551b expression in different diagnosis groups. An Ordered Logistic Regression and a Probit correlation were made to correlate miR-551b expression levels with the cervical tissue histological findings. The immunohistochemical distribution of p16 and Ki-67 according to histopathological findings was also assessed. RESULTS: The distribution of the miR-551b expression profile was significantly lower in CIN1-3 samples compared to other histological diagnosis groups (condyloma and negative). The expression levels were inversely correlated to the cervical pathological grade, from negative to CIN2-3. A 1% increase in miR-551b expression level produced an increase of 19% to the probability of a minor histological grade diagnosis in a range from negative to CIN2-3 and an increase of 13% to the probability of a negative histological grade diagnosis. Among the cases with miR-551b expression < 0.02 (considered as cut-off value) a significant statistical correlation was found between p16 and Ki-67 expression and the diagnosis of CIN2-3. CONCLUSIONS: O ur d ata s howed a s ignificant inverse correlation between miR-551b expression and the histological grading of the lesions, suggesting a tumor suppressive function in the different stages of cervical dysplasia

HE4 in the differential diagnosis of ovarian masses

Ovarian masses, a common finding among pre- and post-menopausal women, can be benign or malignant. Ovarian cancer is the leading cause of death from gynecologic malignancy among women living in industrialized countries. According to the current guidelines, measurement of CA125 tumor marker remains the gold standard in the management of ovarian cancer. Recently, HE4 has been proposed as emerging biomarker in the differential diagnosis of adnexal masses and in the early diagnosis of ovarian cancer. Discrimination of benign and malignant ovarian tumors is very important for correct patient referral to institutions specializing in care and management of ovarian cancer. Tumor markers CA125 and HE4 are currently incorporated into the Risk of Ovarian Malignancy Algorithm” (ROMA) with menopausal status for discerning malignant from benign pelvic masses. The availability of a good biomarker such as HE4, closely associated with the differential and early diagnosis of ovarian cancer, could reduce medical costs related to more expensive diagnostic procedures. Finally, it is important to note that HE4 identifies platinum non-responders thus enabling a switch to second line chemotherapy and improved survival

Urinary CE-MS peptide marker pattern for detection of solid tumors

Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features

MicroRNA applications for prostate, ovarian and breast cancer in the era of precision medicine.

The high degree of conservation in microRNA from Caenorhabditiselegans to humans has enabled relatively rapid implementation of findings in model systems to the clinic. The convergence of the capacity for genomic screening being implemented in the prevailing precision medicine initiative and the capabilities of microRNA to address these changes holds significant promise. However, prostate, ovarian and breast cancers are heterogeneous and face issues of evolving therapeutic resistance. The transforming growth factor-beta (TGFβ) signaling axis plays an important role in the progression of these cancers by regulating microRNAs. Reciprocally, microRNAs regulate TGFβ actions during cancer progression. One must consider the expression of miRNA in the tumor microenvironment a source of biomarkers of disease progression and a viable target for therapeutic targeting. The differential expression pattern of microRNAs in health and disease, therapeutic response and resistance has resulted in its application as robust biomarkers. With two microRNA mimetics in ongoing restorative clinical trials, the paradigm for future clinical studies rests on the current observational trials to validate microRNA markers of disease progression. Some of today's biomarkers can be translated to the next generation of microRNA-based therapies

Quantification and expert evaluation of evidence for chemopredictive biomarkers to personalize cancer treatment.

Predictive biomarkers have the potential to facilitate cancer precision medicine by guiding the optimal choice of therapies for patients. However, clinicians are faced with an enormous volume of often-contradictory evidence regarding the therapeutic context of chemopredictive biomarkers.We extensively surveyed public literature to systematically review the predictive effect of 7 biomarkers claimed to predict response to various chemotherapy drugs: ERCC1-platinums, RRM1-gemcitabine, TYMS-5-fluorouracil/Capecitabine, TUBB3-taxanes, MGMT-temozolomide, TOP1-irinotecan/topotecan, and TOP2A-anthracyclines. We focused on studies that investigated changes in gene or protein expression as predictors of drug sensitivity or resistance. We considered an evidence framework that ranked studies from high level I evidence for randomized controlled trials to low level IV evidence for pre-clinical studies and patient case studies.We found that further in-depth analysis will be required to explore methodological issues, inconsistencies between studies, and tumor specific effects present even within high evidence level studies. Some of these nuances will lend themselves to automation, others will require manual curation. However, the comprehensive cataloging and analysis of dispersed public data utilizing an evidence framework provides a high level perspective on clinical actionability of these protein biomarkers. This framework and perspective will ultimately facilitate clinical trial design as well as therapeutic decision-making for individual patients