Characterization of microzooplankton communities in a polluted coastal area integrating high-throughput sequencing and microscopy

The Mediterranean Sea is subjected to strong anthropogenic pressures that may be causing important ecosystem changes, particularly in coastal areas under high anthropogenic pressure. We characterized the composition of the microzooplankton community in a coastal area in the N Alboran Sea (SW Mediterranean) highly impacted by urban wastewater pollution. Two offshore outfalls release urban wastewater to the sea at a 40 m bottom depth, from a nearby town. We applied an integrative taxonomic approach, combining metabarcoding of the mitochondrial COI and the 18S rRNA genes with morphological microscopic identification of organisms, collected with a CalVET net (50 µm mesh). Hydrology was notably affected near the bottom at the vicinity of the submarine emissaries exit, presenting increased temperature and turbidity, and decreased salinity due to the urban freshwater discharge. Nutrient concentrations exceeded the Water Framework Directive limits; however, chlorophyll a concentrations were not very high, due to strong water column stratification. Microzooplankton communities (50-200 µm) were dominated by dinoflagellates (50-80% relative abundance), followed by copepods (copepodites and nauplii), eggs and cysts. We found significant differences in communities’ composition between the coastal shallow area and the offshore waters, driven by pollution and stratification.Consejería de Economía, Innovación y Ciencia de la Junta de Andalucía; Unión Europea, Fondo Europeo de Desarrollo Regional (P20_00743

Comparison of Prediction Models for Lynch Syndrome among Individuals with Colorectal Cancer

BACKGROUND: Recent guidelines recommend the Lynch Syndrome prediction models MMRPredict, MMRPro, and PREMM1,2,6 for the identification of MMR gene mutation carriers. We compared the predictive performance and clinical usefulness of these prediction models to identify mutation carriers. METHODS: Pedigree data from CRC patients in 11 North American, European, and Australian cohorts (6 clinic- and 5 population-based sites) were used to calculate predicted probabilities of pathogenic MLH1, MSH2, or MSH6 gene mutations by each model and gene-specific predictions by MMRPro and PREMM1,2,6. We examined discrimination with area under the receiver operating characteristic curve (AUC), calibration with observed to expected (O/E) ratio, and clinical usefulness using decision curve analysis to select patients for further evaluation. All statistical tests were two-sided. RESULTS: Mutations were detected in 539 of 2304 (23%) individuals from the clinic-based cohorts (237 MLH1, 251 MSH2, 51 MSH6) and 150 of 3451 (4.4%) individuals from the population-based cohorts (47 MLH1, 71 MSH2, 32 MSH6). Discrimination was similar for clinic- and population-based cohorts: AUCs of 0.76 vs 0.77 for MMRPredict, 0.82 vs 0.85 for MMRPro, and 0.85 vs 0.88 for PREMM1,2,6. For clinic- and population-based cohorts, O/E deviated from 1 for MMRPredict (0.38 and 0.31, respectively) and MMRPro (0.62 and 0.36) but were more satisfactory for PREMM1,2,6 (1.0 and 0.70). MMRPro or PREMM1,2,6 predictions were clinically useful at thresholds of 5% or greater and in particular at greater than 15%. CONCLUSIONS: MMRPro and PREMM1,2,6 can well be used to select CRC patients from genetics clinics or population-based settings for tumor and/or germline testing at a 5% or higher risk. If no MMR deficiency is detected and risk exceeds 15%, we suggest considering additional genetic etiologies for the cause of cancer in the family

Impact of genetic testing on endometrial cancer risk-reducing practices in women at risk for Lynch syndrome

OBJECTIVE: Due to the increased lifetime risk of endometrial cancer (EC), guidelines recommend that women with Lynch syndrome (LS) age ≥35 undergo annual EC surveillance or prophylactic hysterectomy (PH). The aim of this study was to examine the uptake of these risk-reducing strategies. METHODS: The study population included women meeting clinical criteria for genetic evaluation for LS. Data on cancer risk-reducing behaviors were collected from subjects enrolled in two distinct studies: (1) a multicenter cross-sectional study involving completion of a one-time questionnaire, or (2) a single-center longitudinal study in which subjects completed questionnaires before and after undergoing genetic testing. The main outcome was uptake of EC risk-reducing practices. RESULTS: In the cross-sectional cohort, 58/77 (75%) women at risk for LS-associated EC reported engaging in EC risk-reduction. Personal history of genetic testing was associated with uptake of EC surveillance or PH (OR 17.1; 95% CI 4.1–70.9). Prior to genetic testing for LS, 26/40 (65%) women in the longitudinal cohort reported engaging in EC risk-reduction. At one-year follow-up, 16/16 (100%) mismatch repair (MMR) gene mutation carriers were adherent to guidelines for EC risk-reduction, 9 (56%) of whom had undergone PH. By three-year follow-up, 11/16 (69%) MMR mutation carriers had undergone PH. Among women with negative or uninformative genetic test results, none underwent PH after testing. CONCLUSIONS: Genetic testing for LS is strongly associated with uptake of EC risk-reducing practices. Women found to have LS in this study underwent prophylactic gynecologic surgery at rates comparable to those published for BRCA1/2 mutation carriers

Performance of PREM1,2,6, MMRpredict, and MMRpro in detecting Lynch syndrome among endometrial cancer cases

PURPOSE: Lynch syndrome accounts for 2-5% of endometrial cancer cases. Lynch syndrome prediction models have not been evaluated among endometrial cancer cases. METHODS: Area under the receiver operating curve (AUC), sensitivity and specificity of PREMM(1,2,6), MMRpredict, and MMRpro scores were assessed among 563 population-based and 129 clinic-based endometrial cancer cases. RESULTS: A total of 14 (3%) population-based and 80 (62%) clinic-based subjects had pathogenic mutations. PREMM(1,2,6), MMRpredict, and MMRpro were able to distinguish mutation carriers from noncarriers (AUC of 0.77, 0.76, and 0.77, respectively), among population-based cases. All three models had lower discrimination for the clinic-based cohort, with AUCs of 0.67, 0.64, and 0.54, respectively. Using a 5% cutoff, sensitivity and specificity were as follows: PREMM(1,2,6), 93% and 5% among population-based cases and 99% and 2% among clinic-based cases; MMRpredict, 71% and 64% for the population-based cohort and 91% and 0% for the clinic-based cohort; and MMRpro, 57% and 85% among population-based cases and 95% and 10% among clinic-based cases. CONCLUSION: Currently available prediction models have limited clinical utility in determining which patients with endometrial cancer should undergo genetic testing for Lynch syndrome. Immunohistochemical analysis and microsatellite instability testing may be the best currently available tools to screen for Lynch syndrome in endometrial cancer patients