E-cadherin deregulation in breast cancer.

E-cadherin protein (CDH1 gene) integrity is fundamental to the process of epithelial polarization and differentiation. Deregulation of the E-cadherin function plays a crucial role in breast cancer metastases, with worse prognosis and shorter overall survival. In this narrative review, we describe the inactivating mechanisms underlying CDH1 gene activity and its possible translation to clinical practice as a prognostic biomarker and as a potential targeted therapy.

Meta-analysis of diagnostic performance of serological tests for SARS-CoV-2 antibodies up to 25 April 2020 and public health implications.

We reviewed the diagnostic accuracy of SARS-CoV-2 serological tests. Random-effects models yielded a summary sensitivity of 82% for IgM, and 85% for IgG and total antibodies. For specificity, the pooled estimate were 98% for IgM and 99% for IgG and total antibodies. In populations with ≤ 5% of seroconverted individuals, unless the assays have perfect (i.e. 100%) specificity, the positive predictive value would be ≤ 88%. Serological tests should be used for prevalence surveys only in hard-hit areas.

Exogenous sex hormones, menstrual and reproductive history, and risk of non-melanoma skin cancer among women: a systematic literature review and meta-analysis.

Non-melanoma skin cancers (NMSC) are more frequent among men, but women (especially those aged < 40 years) have experienced steeper growth in their incidence rates in recent years. Hormonal factors were hypothesized to be playing a role in modulating NMSC risk, but the studies published to date provided conflicting results. We systematically reviewed and meta-analysed the studies focusing on the association between hormone-related characteristics (use of exogenous sex hormones, and aspects of menstrual and reproductive history) and the risk of NMSC among women. We included observational and experimental studies published in PubMed and EMBASE until February 2020. We calculated summary relative risk (SRR) and 95% confidence intervals (CI) by applying random effects models with maximum likelihood estimation, and used the I2 statistics to quantify the degree of heterogeneity of risk estimates across studies. Eleven independent studies encompassing a total of over 30,000 NMSC cases were included in quantitative analyses. No evidence of an increased NMSC risk emerged among ever vs. never users of oral contraceptives (SRR 1.13, 95% CI 0.88-1.45) or hormones for menopause (SRR 1.09, 95% CI 0.87-1.37). Likewise, age at menarche or at menopause and parity were not associated with NMSC risk. Heterogeneity across studies was low, and pooled results were comparable between NMSC subtypes. We found no evidence that hormonal factors play a role in the pathogenesis of NMSC among women.

Ethnicity as modifier of risk for Vitamin D receptors polymorphisms: Comprehensive meta-analysis of all cancer sites.

Vitamin D receptors polymorphisms are found to be associated with several cancers. Since their prevalence vary across ethnicities and ethnicity itself seems to influence the cancer risk, a comprehensive meta-analysis was performed to investigate the role of VDR Fok1, Bsm1, Taq1, Apa1, Cdx2 and cancer risk at specific organ sites. Odds ratios, calculated with random-effects models, summarized one-hundred-ninety-two independent studies for twenty-two cancer sites. Evidence was provided that Fok1, Bsm1, Cdx2, Apa1 and Taq1 are linked to cancer susceptibility for colorectal, lung, ovarian, skin, multiple myeloma and brain cancer. Stratifying by ethnicity, some differences were found, partially explained by minor allele frequency (MAF), for colorectal cancer, ovarian and prostate cancer in Caucasian and prostate cancer in Asian populations. In summary, ethnicity may be a modifier of cancer risk, in particular for hormone dependent cancers and it should be considered evaluating the effect of VDR on cancer risk.

Circulating tumour DNA and melanoma survival: A systematic literature review and meta-analysis.

We reviewed and meta-analysed the available evidence (until December 2019) about circulating tumour DNA (ctDNA) levels and melanoma patients survival. We included twenty-six studies (>2000 patients overall), which included mostly stage III-IV cutaneous melanoma patients and differed widely in terms of systemic therapy received and somatic mutations that were searched. Patients with detectable ctDNA before treatment had worse progression-free survival (PFS) (summary hazard ratio (SHR) 2.47, 95 % confidence intervals (CI) 1.85-3.29) and overall survival (OS) (SHR 2.98, 95 % CI 2.26-3.92), with no difference by tumour stage. ctDNA detectability during follow-up was associated with poorer PFS (SHR 4.27, 95 %CI 2.75-6.63) and OS (SHR 3.91, 95 %CI 1.97-7.78); in the latter case, the association was stronger (p = 0.01) for stage IV vs. III melanomas. Between-estimates heterogeneity was low for all pooled estimates. ctDNA is a strong prognostic biomarker for advanced-stage melanoma patients, robust across tumour (e.g. genomic profile) and patients (e.g. systemic therapy) characteristics.

The Challenge of Choosing the Best Classification Method in Radiomic Analyses: Recommendations and Applications to Lung Cancer CT Images.

Radiomics uses high-dimensional sets of imaging features to predict biological characteristics of tumors and clinical outcomes. The choice of the algorithm used to analyze radiomic features and perform predictions has a high impact on the results, thus the identification of adequate machine learning methods for radiomic applications is crucial. In this study we aim to identify suitable approaches of analysis for radiomic-based binary predictions, according to sample size, outcome balancing and the features-outcome association strength. Simulated data were obtained reproducing the correlation structure among 168 radiomic features extracted from Computed Tomography images of 270 Non-Small-Cell Lung Cancer (NSCLC) patients and the associated to lymph node status. Performances of six classifiers combined with six feature selection (FS) methods were assessed on the simulated data using AUC (Area Under the Receiver Operating Characteristics Curves), sensitivity, and specificity. For all the FS methods and regardless of the association strength, the tree-based classifiers Random Forest and Extreme Gradient Boosting obtained good performances (AUC ≥ 0.73), showing the best trade-off between sensitivity and specificity. On small samples, performances were generally lower than in large-medium samples and with larger variations. FS methods generally did not improve performances. Thus, in radiomic studies, we suggest evaluating the choice of FS and classifiers, considering specific sample size, balancing, and association strength.