BackgroundCAN-003 was a randomized, open-label, Phase 2 trial evaluating the safety, efficacy and immune outcomes of CVac, a mucin 1 targeted-dendritic cell (DC) treatment as a maintenance therapy to patients with epithelial ovarian cancer (EOC).MethodsPatients (n = 56) in first (CR1) or second clinical remission (CR2) were randomized (1:1) to standard of care (SOC) observation or CVac maintenance treatment. Ten doses were administered over 56 weeks. Both groups were followed for progression-free survival (PFS) and overall survival (OS).ResultsFifty-six patients were randomized: 27 to SOC and 29 to CVac. Therapy was safe with only seven patients with Grade 3–4 treatment-emergent adverse events. A variable but measurable mucin 1 T cell-specific response was induced in all CVac-treated and some standard of care (SOC) patients. Progression free survival (PFS) was not significantly longer in the treated group compared to SOC group (13 vs. 9 months, p = 0.36, hazard ratio [HR] = 0.73). Analysis by remission status showed in the CR1 subgroup a median PFS of 18 months (SOC) vs. 13 months (CVac); p = 0.69 (HR = 1.18; CI 0.52–2.71). However CR2 patients showed a longer median PFS in the CVac-treated group (median PFS not yet reached, >13 vs. 5 months; p = 0.04, HR = 0.32 CI). OS for CR2 patients at 42 months of follow-up showed a difference of 26 months for SOC vs. > 42 months for CVac-treated (as median OS had not been reached; HR = 0.17 (CI 0.02–1.4) with a p = 0.07).ConclusionsCVac, a mucin 1-dendritic cell maintenance treatment was safe and well tolerated in ovarian cancer patients. A variable but observed CVac-derived, mucin 1-specific T cell response was measured. Notably, CR2 patients showed an improved PFS and lengthened OS. Further studies in CR2 ovarian cancer patients are warranted (NCT01068509).Trial registrationNCT01068509. Study Initiation Date (first patient screened): 20 July 2010. Study Completion Date (last patient observation): 20 August 2013, the last patient observation for progression-free survival; 29 April 2015, the last patient was documented regarding overall survival.

The competitive endogenous RNA (ceRNA) hypothesis suggests that a long noncoding RNA (lncRNA) can function as sinks for pools of microRNAs (miRNAs); thereby, in the presence of ceRNA, messenger RNAs (mRNAs) targeted by specific miRNAs can liberate and translate to protein. Maternally expressed gene 3 (MEG3) is a lncRNA, which its expression has been detected in various normal tissues, while it is lost or downregulated in human tumors. The MEG3 is an imprinted gene which, is methylated and suppressed by DNA methyltransferases (DNMTs) family. Also, miRNAs are involved in the regulation of MEG3 gene expression. Interestingly, the lncRNA MEG3 (lnc-MEG3), as a ceRNA affects various cell processes such as proliferation, apoptosis, and angiogenesis by sponging miRNAs. These miRNAs, in turn, regulate different mRNAs in different pathways. This review focuses on the interaction between lnc-MEG3 and experimentally validated miRNAs. In addition, the discussion supplemented by some data obtained from mirPath (v.3) and TarBase (v.8) databanks to provide more details about the pathways affected by this ceRNA.

Background: The expression of MMP genes has been demonstrated to be associated with tumor invasion, metastasis and survival rate for a variety of cancers. The functional promoter polymorphism MMP-2 C-735T is associated with decreased expression of the MMP-2 gene. The aim of present study was to detect any association between MMP-2 C-735T and susceptibility to breast cancer. Materials and Methods: The MMP-2 C-735T polymorphism was studied in 233 women (98 with breast cancer and 135 healthy controls). All studied women were from Kermanshah and Ilam provinces of Western Iran. The MMP-2 C-735T polymorphism was detected using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Results: The frequencies of MMP-2 CC, CT and TT genotypes in healthy individuals were 59.3, 38.5 and 2.2%, respectively. However, in breast cancer patients, only CC (71.4%) and CT (28.6%) genotypes were observed (p=0.077). controls (78.5 %, p=0.048). The presence of C allele of MMP-2 increased the risk of breast cancer by 1.64-fold family history of cancer (67.3%, p=0.31). Conclusions: polymorphism is associated with increased risk of breast cancer. Also, the MMP-2 C allele might increase the risk of young onset breast cancer in our population.

This paper identifies prognosis factors for survival in patients with acute myeloid leukemia (AML) using machine learning techniques. We have integrated machine learning with feature selection methods and have compared their performances to identify the most suitable factors in assessing the survival of AML patients. Here, six data mining algorithms including Decision Tree, Random Forrest, Logistic Regression, Naive Bayes, W-Bayes Net, and Gradient Boosted Tree (GBT) are employed for the detection model and implemented using the common data mining tool RapidMiner and open-source R package. To improve the predictive ability of our model, a set of features were selected by employing multiple feature selection methods. The accuracy of classification was obtained using 10-fold cross-validation for the various combinations of the feature selection methods and machine learning algorithms. The performance of the models was assessed by various measurement indexes including accuracy, kappa, sensitivity, specificity, positive predictive value, negative predictive value, and area under the ROC curve (AUC). Our results showed that GBT with an accuracy of 85.17%, AUC of 0.930, and the feature selection via the Relief algorithm has the best performance in predicting the survival rate of AML patients.

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