Dyskerin Downregulation Can Induce ER Stress and Promote Autophagy via AKT-mTOR Signaling Deregulation

: Dyskerin is an evolutionarily conserved nucleolar protein implicated in a wide range of fundamental biological roles, including telomere maintenance and ribosome biogenesis. Germline mutations of DKC1, the human gene encoding dyskerin, cause the hereditary disorders known as X-linked dyskeratosis congenita (X-DC). Moreover, dyskerin is upregulated in several cancers. Due to the pleiotropic functions of dyskerin, the X-DC clinical features overlap with those of both telomeropathies and ribosomopathies. In this paper, we evaluate the telomerase-independent effects of dyskerin depletion on cellular physiology by using inducible DCK1 knockdown. This system allows the downregulation of DKC1 expression within a short timeframe. We report that, in these cellular systems, dyskerin depletion induces the accumulation of unfolded/misfolded proteins in the endoplasmic reticulum, which in turn induces the activation of the PERK branch of the unfolded protein response. We also demonstrate that the PERK-eIF2a-ATF4-CHOP signaling pathway, activated by dyskerin downregulation, triggers a functional autophagic flux through the inhibition of the PI3K/AKT/mTOR pathway. By revealing a novel unpredicted connection between the loss of dyskerin, autophagy and UPR, our results establish a firm link between the lowering of dyskerin levels and the activation of the ER stress response, that plays a key role in the pathogenesis of several diseases

Spatial analysis of demersal food webs through integration of eDNA metabarcoding with fishing activities

The evaluation of the status of marine communities, and especially the monitoring of those heavily exploited by fisheries, is a key, challenging task in marine sciences. Fishing activities are a major source of disruption to marine food webs, both directly, by selectively removing components at specific trophic levels (TL), and indirectly, by altering habitats and production cycles. Food web analysis can be very useful in the context of an Ecosystem Approach to Fisheries, but food web reconstructions demand large and expensive data sets, which are typically available only for a small fraction of marine ecosystems. Recently, new technologies have been developed to easily, quickly and cost-effectively collect environmental DNA (eDNA) during fishing activities. By generating large, multi-marker metabarcoding data from eDNA samples obtained from commercial trawlers, it is possible to produce exhaustive taxonomic inventories for the exploited ecosystems, which are suitable for food-web reconstructions. Here, we integrate and re-analyse the data of a recent study in which the α diversity was investigated using the eDNA opportunistically collected during fishing operations. Indeed, we collect highly resolved information on species feeding relationships to reconstruct the food webs at different sites in the Strait of Sicily (Mediterranean Sea) from eDNA and catch data. After observing that the trophic networks obtained from eDNA metabarcoding data are more consistent with the available knowledge, a set of food web indicators (species richness, number of links, direct connectance and generality) is computed and analysed to unravel differences in food webs structure through different areas (spatial variations). Species richness, number of links and generality (positively) and direct connectance (negatively) are correlated with increasing distance from the coast and fishing effort intensity. The combined effects of environmental gradients and fishing effort on food web structure at different study sites are then examined and modelled. Taken together, these findings indicate the suitability of eDNA metabarcoding to assist and food web analysis, obtain several food web-related ecological indicators, and tease out the effect of fishing intensity from the environmental gradients of marine ecosystems

Spatial analysis of demersal food webs through integration of eDNA metabarcoding with fishing activities

The evaluation of the status of marine communities, and especially the monitoring of those heavily exploited by fisheries, is a key, challenging task in marine sciences. Fishing activities are a major source of disruption to marine food webs, both directly, by selectively removing components at specific trophic levels (TL), and indirectly, by altering habitats and production cycles. Food web analysis can be very useful in the context of an Ecosystem Approach to Fisheries, but food web reconstructions demand large and expensive data sets, which are typically available only for a small fraction of marine ecosystems. Recently, new technologies have been developed to easily, quickly and cost-effectively collect environmental DNA (eDNA) during fishing activities. By generating large, multi-marker metabarcoding data from eDNA samples obtained from commercial trawlers, it is possible to produce exhaustive taxonomic inventories for the exploited ecosystems, which are suitable for food-web reconstructions. Here, we integrate and re-analyse the data of a recent study in which the α diversity was investigated using the eDNA opportunistically collected during fishing operations. Indeed, we collect highly resolved information on species feeding relationships to reconstruct the food webs at different sites in the Strait of Sicily (Mediterranean Sea) from eDNA and catch data. After observing that the trophic networks obtained from eDNA metabarcoding data are more consistent with the available knowledge, a set of food web indicators (species richness, number of links, direct connectance and generality) is computed and analysed to unravel differences in food webs structure through different areas (spatial variations). Species richness, number of links and generality (positively) and direct connectance (negatively) are correlated with increasing distance from the coast and fishing effort intensity. The combined effects of environmental gradients and fishing effort on food web structure at different study sites are then examined and modelled. Taken together, these findings indicate the suitability of eDNA metabarcoding to assist and food web analysis, obtain several food web-related ecological indicators, and tease out the effect of fishing intensity from the environmental gradients of marine ecosystems

An Alkaloid from a Highly Invasive Seaweed Increases the Voracity and Reproductive Output of a Model Fish Species

The invasive macroalga Caulerpa cylindracea has spread widely in the Mediterranean Sea, becoming a favorite food item for native fish for reasons yet unknown. By using a combination of behavioral, morphological, and molecular approaches, herein we provide evidence that the bisindole alkaloid caulerpin, a major secondary metabolite of C. cylindracea, significantly increases food intake in the model fish Danio rerio, influencing the regulation of genes involved in the orexigenic pathway. In addition, we found that the compound improves fish reproductive performance by affecting the hypothalamus-pituitary-gonadal axis. The obtained results pave the way for the possible valorization of C. cylindracea as a sustainable source of a functional feed additive of interest to face critical challenges both in aquaculture and in human nutrition

Management of patients with early-stage colon cancer: guidelines of the Italian Medical Oncology Association

About 75% of colorectal cancers are diagnosed as early stage, in which radical surgery is achievable. In the last decade, in Italy, the overall incidence of colorectal cancer has remained stable, while mortality gradually decreased, which is attributable to early diagnosis and improved medical, surgical and locoregional treatments. The Italian Medical Oncology Association formulated guidelines to manage early-stage colon cancer, including screening, diagnosis, treatment and follow-up, which we herein present

Common germline variants within the CDKN2A/2B region affect risk of pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNETs) are heterogeneous neoplasms which represent only 2% of all pancreatic neoplasms by incidence, but 10% by prevalence. Genetic risk factors could have an important role in the disease aetiology, however only a small number of case control studies have been performed yet. To further our knowledge, we genotyped 13 SNPs belonging to the pleiotropic CDKN2A/B gene region in 320 PNET cases and 4436 controls, the largest study on the disease so far. We observed a statistically significant association between the homozygotes for the minor allele of the rs2518719 SNP and an increased risk of developing PNET (ORhom = 2.08, 95% CI 1.05-4.11, p = 0.035). This SNP is in linkage disequilibrium with another polymorphic variant associated with increased risk of several cancer types. In silico analysis suggested that the SNP could alter the sequence recognized by the Neuron-Restrictive Silencer Factor (NRSF), whose deregulation has been associated with the development of several tumors. The mechanistic link between the allele and the disease has not been completely clarified yet but the epidemiologic evidences that link the DNA region to increased cancer risk are convincing. In conclusion, our results suggest rs2518719 as a pleiotropic CDKN2A variant associated with the risk of developing PNETs

Minimally invasive vs. open segmental resection of the splenic flexure for cancer: a nationwide study of the Italian Society of Surgical Oncology-Colorectal Cancer Network (SICO-CNN)

Background Evidence on the efficacy of minimally invasive (MI) segmental resection of splenic flexure cancer (SFC) is not available, mostly due to the rarity of this tumor. This study aimed to determine the survival outcomes of MI and open treatment, and to investigate whether MI is noninferior to open procedure regarding short-term outcomes. Methods This nationwide retrospective cohort study included all consecutive SFC segmental resections performed in 30 referral centers between 2006 and 2016. The primary endpoint assessing efficacy was the overall survival (OS). The secondary endpoints included cancer-specific mortality (CSM), recurrence rate (RR), short-term clinical outcomes (a composite of Clavien-Dindo > 2 complications and 30-day mortality), and pathological outcomes (a composite of lymph nodes removed >= 12, and proximal and distal free resection margins length >= 5 cm). For these composites, a 6% noninferiority margin was chosen based on clinical relevance estimate. Results A total of 606 patients underwent either an open (208, 34.3%) or a MI (398, 65.7%) SFC segmental resection. At univariable analysis, OS and CSM were improved in the MI group (log-rank test p = 0.004 and Gray's tests p = 0.004, respectively), while recurrences were comparable (Gray's tests p = 0.434). Cox multivariable analysis did not support that OS and CSM were better in the MI group (p = 0.109 and p = 0.163, respectively). Successful pathological outcome, observed in 53.2% of open and 58.3% of MI resections, supported noninferiority (difference 5.1%; 1-sided 95%CI - 4.7% to infinity). Successful short-term clinical outcome was documented in 93.3% of Open and 93.0% of MI procedures, and supported noninferiority as well (difference - 0.3%; 1-sided 95%CI - 5.0% to infinity). Conclusions Among patients with SFC, the minimally invasive approach met the criterion for noninferiority for postoperative complications and pathological outcomes, and was found to provide results of OS, CSM, and RR comparable to those of open resection

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10−8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10−7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10−6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10−5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.</p

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10−8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10−7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10−6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10−5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.</p

Polygenic and multifactorial scores for pancreatic ductal adenocarcinoma risk prediction

Most cases of pancreatic ductal adenocarcinoma (PDAC) are asymptomatic in early stages, and the disease is typically diagnosed in advanced phases, resulting in very high mortality. Tools to identify individuals at high risk of developing PDAC would be useful to improve chances of early detection