The extracellular matrix (ECM) is a three-dimensional network of proteins of diverse nature, whose interactions are essential to provide tissues with the correct mechanical and biochemical cues they need for proper development and homeostasis. Changes in the quantity of extracellular matrix (ECM) components and their balance within the tumor microenvironment (TME) accompany and fuel all steps of tumor development, growth and metastasis, and a deeper and more systematic understanding of these processes is fundamental for the development of future therapeutic approaches. The wealth of "big data" from numerous sources has enabled gigantic steps forward in the comprehension of the oncogenic process, also impacting on our understanding of ECM changes in the TME. Most of the available studies, however, have not considered the network nature of ECM and the possibility that changes in the quantity of components might be regulated (co-occur) in cancer and significantly "rebound" on the whole network through its connections, fundamentally altering the matrix interactome. To facilitate the exploration of these network-scale effects we have implemented MatriNet (www.matrinet.org), a database enabling the study of structural changes in ECM network architectures as a function of their protein-protein interaction strengths across 20 different tumor types. The use of MatriNet is intuitive and offers new insights into tumor-specific as well as pan-cancer features of ECM networks, facilitating the identification of similarities and differences between cancers as well as the visualization of single-tumor events and the prioritization of ECM targets for further experimental investigations.

Accurate identification of independent predictors of stillbirth is needed to define preventive strategies. We aim to examine the independent contribution of maternal race in the risk of stillbirth after adjusting for maternal characteristics and medical history. There are two components to the study: first, prospective screening in 168,966 women with singleton pregnancies coordinated by the Fetal Medicine Foundation (FMF) and second, a systematic review and meta-analysis of studies reporting on race and stillbirth. In the FMF study, logistic regression analysis found that in black women, the risk of stillbirth, after adjustment for confounders, was higher than in white women (odds ratio 1.78, 95% confidence interval 1.50 to 2.11). The risk for other racial groups was not significantly different. The literature search identified 20 studies that provided data on over 6,500,000 pregnancies, but only 10 studies provided risks adjusted for some maternal characteristics; consequently, the majority of these studies did not provide accurate contribution of different racial groups to the prediction of stillbirth. It is concluded that in women of black origin, the risk of stillbirth, after adjustment for confounders, is about twofold higher than in white women. Consequently, closer surveillance should be granted for these women.

Background and Objectives: The aim of this study was to analyze the association between maternal risk factors, such as age, body mass index (BMI), and cigarette smoking, and perinatal outcomes. Materials and Methods: We conducted a retrospective analysis based on prospectively collected data at Hospital Universitario de Torrejón (Madrid, Spain) between September 2017 and December 2019. All pregnant women with singleton pregnancies and non-malformed live fetuses attending their routine ultrasound examination at 11+0 to 13+6 weeks’ gestation were invited to participate. The association between preeclampsia, preterm birth, gestational diabetes mellitus (GDM), small-for-gestational-age (SGA) or fetal-growth-restricted (FGR) neonates, and type of delivery and maternal age, BMI, and cigarette smoking was studied. Logistic mixed models were used to analyze the data. Results: A total of 1921 patients were included in the analysis. Women who were ≥40 years old had a significantly higher risk of having GDM (odds ratio (OR) 1.61, 95% confidence interval (CI) 1.08 to 2.36) and SGA neonates (OR 1.54, 95% CI 1.00 to 2.37). Women with a BMI < 18 had an increased rate of giving birth to SGA and FGR neonates (OR 3.28, 95% CI 1.51 to 7.05, and OR 3.73, 95% CI 1.54 to 8.37, respectively), whereas women with a BMI ≥ 35 had a higher risk of GDM (OR 3.10, 95% CI 1.95 to 4.89). Smoking increased the risk of having SGA and FGR neonates (OR 1.83, 95% CI 1.36 to 2.46, and OR 1.91, 95% CI 1.29 to 2.78). Conclusions: Advanced maternal age, low or high BMI, and smoking status are significant risk factors for pregnancy complications. Both clinicians and society should concentrate their efforts on addressing these factors to enhance reproductive health.

Background: In around 40–60% of Hypertrophic Cardiomyopathy (HCM) cases pathogenic variants are not identified. Our aim was to evaluate the possible association of lncRNAs with the risk of developing HCM. Methods: We sequenced 10 lncRNAs coding genes that have been associated with cardiovascular disease in a discovery cohort (238 HCM patients and 212 controls) by NGS, and genotyped rs74035787 G>A and rs1424019 A>G polymorphism in a validation cohort (962 HCM patients and 923 controls). Finally, we sequenced the FENDRR promoter by Sanger sequencing. Results: We observed by NGS that FENDRR rs39527, rs39529 and rs40384 polymorphisms were significantly associated with HCM in our cohort (p = 0.0284; OR: 0.24, 95%CI: 0.07–0.86). NGS results were confirmed by genotyping rs74035787 polymorphism (p = 0.001; OR:0.38, 95%CI: 0.21–0.66). Moreover, it is also associated when stratification by sex (p = 0.003; OR:0.20, 95%CI: 0.06–0.53), and age (≥50 years old p = 0.001, OR:0.33, 95%CI: 0.16–0.63) Moreover, the risk of HCM in the carriers of the GG genotype of the rs1424019 polymorphism was significantly higher than that of the AA/AG genotypes carriers in the elderly subjects (p = 0.045, OR:1.24, 95%CI: 1.01–1.53). On the other hand, we observed significant differences in the rs74035787 A/rs1424019 G haplotype frequency (p = 0.0035; OR: 0.20, 95%CI: 0.07–0.59). Conclusions: Our study suggested a significant association between FENDRR gene variants and HCM.