External Validation of SAFE Score to Predict Atrial Fibrillation Diagnosis after Ischemic Stroke: A Retrospective Multicenter Study

Diagnóstico; Fibrilación auricular; Ictus isquémicoDiagnòstic; Fibril·lació auricular; Ictus isquèmicDiagnosis; Atrial fibrillation; Ischemic strokeIntroduction: The screening for atrial fibrillation (AF) scale (SAFE score) was recently developed to provide a prediction of the diagnosis of AF after an ischemic stroke. It includes 7 items: age ≥ 65 years, bronchopathy, thyroid disease, cortical location of stroke, intracranial large vessel occlusion, NT-ProBNP ≥250 pg/mL, and left atrial enlargement. In the internal validation, a good performance was obtained, with an AUC = 0.88 (95% CI 0.84-0.91) and sensitivity and specificity of 83% and 80%, respectively, for scores ≥ 5. The aim of this study is the external validation of the SAFE score in a multicenter cohort. Methods: A retrospective multicenter study, including consecutive patients with ischemic stroke or transient ischemic attack between 2020 and 2022 with at least 24 hours of cardiac monitoring. Patients with previous AF or AF diagnosed on admission ECG were excluded. Results: Overall, 395 patients were recruited for analysis. The SAFE score obtained an AUC = 0.822 (95% CI 0.778-0.866) with a sensitivity of 87.2%, a specificity of 65.4%, a positive predictive value of 44.1%, and a negative predictive value of 94.3% for a SAFE score ≥ 5, with no significant gender differences. Calibration analysis in the external cohort showed an absence of significant differences between the observed values and those predicted by the model (Hosmer-Lemeshow's test 0.089). Conclusions: The SAFE score showed adequate discriminative ability and calibration, so its external validation is justified. Further validations in other external cohorts or specific subpopulations of stroke patients might be required.We acknowledge FIBAO (Biomedical Research Foundation) and Adrián Aparicio Mota for their assistance with statistical analysis. Adrián Aparicio (a FIBAO statistician) analyzed the collected data. The project was the winner of the IV research grant “STROKE PROJECT 2020” from the Spanish Society of Neurology

Challenges in genetic counseling in hereditary cancer syndromes in a Mexican oncologic center

Background: In Mexico, hereditary cancer is underdiagnosed, medical geneticists give genetic counseling, but the access is limited due to the socio-economic characteristics of the population. The CUCC (Centro Universitario Contra el Cáncer) Early Cancer Detection Clinic (CECIL) created a model in which patients without cancer are enrolled in a prevention cancer screening program. Methods: From 2016 to 2021, 3014 patients were enrolled in the prevention program. Patients were evaluated with a hereditary cancer risk survey before a consultation. Those with at least one familial hereditary risk positive answer were assessed in a consultation. We also included patients with cancer diagnoses referred by oncologists of the CUCC. Those who fulfill hereditary cancer criteria were referred for genetic testing. Results: A total of 1119 subjects were evaluated. Of these, 248 (21%) were candidates for genetic testing, only 149 (60%) could be analyzed, 52 probands (59%) and 32 relatives (51%) had at least one variant. Among the probands: 33 had HBOC (Hereditary Breast and Ovarian Cancer syndrome), 7 had Lynch, 1 LFS (Li-Fraumeni syndrome), 1 LFLS (Li-Fraumeni like syndrome), 1 FAP (Familial Adenomatous Polyposis), and 9 had benign variants. In the relative\u27s group: 17 had Lynch, 10 HBOC, 1 LFS, and 4 FAP. To date, 3 patients under surveillance had an in situlesions (1 endometrial and two colon), and 3 more had a premalignant colon lesion, one in the not tested group. To achieve the genetic test cost for the probands, 50% had partial sponsors, 31% paid for their tests, research projects were supported by 13%, and 4.5% were donations. Among relatives, 94.4% paid for the tests, and 5.5% were supported by research. All relatives were tested using an in-house low-cost test. Conclusion: The model\u27s success made awareness of these diseases, leading last year to the formation of a state detection program, including all public and private health institutions attending to patients with cancer, these patients are referred to CECIL. We found an effective way to find support low-cost genetic testing via foundations

DPYD pathogenic variants associated with fluoropyrimidines toxicity

Background: Genetic variants in dihydropyrimidine dehydrogenase gene (DPYD) coding for the key enzyme (DPD) of fluoropyrimidines (FPs) catabolism. DPYD contributes to the development of severe FPs-related toxicity, and pathogenic DPYD variants detection reduces side effects and complications associated with FP-toxicity. The allelic frequency of these variants in the Mexican population is currently unknown. Methods: The study was carried out at the Centro Universitario Contra el Cáncer (CUCC) of the Universidad Autónoma de Nuevo León (UANL) in Monterrey México. Genomic DNA was isolated from 154 subjects using the QIAamp DNA Blood Midi kit (QIAGEN) following the manufacturer\u27s recommendations. We analyze the variants c.1156G-\u3eT, c.2846A-\u3eT, and c.1129-5923C-\u3eG by qPCR using predesigned probes. For the remaining genomic variants (c.1905+1G-\u3eA, c.1679T-\u3eG, c.1898delC and c.299_302delTCAT), we design sequencing oligos using the software Oligo Primer v.7®. The allele frequency was calculated for each variant. Results: We analyzed a total of 154 samples to detect the seven variants analyzed. So far, only 2 samples have been found that presented the variant c.1129-5923C\u3eG in a state of heterozygosis, representing 1.2987% of the total of our population. Conclusions: The allele frequency for the variant c.1129-5923C-\u3eG was higher than reported in other populations. So this allele is more common in our population, which could attribute to the large percentage of side effects in our patients. However, more studies and increasing the number of samples are needed to establish DPYD the allele frequency more precisely

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Healthcare workers hospitalized due to COVID-19 have no higher risk of death than general population. Data from the Spanish SEMI-COVID-19 Registry

Aim To determine whether healthcare workers (HCW) hospitalized in Spain due to COVID-19 have a worse prognosis than non-healthcare workers (NHCW). Methods Observational cohort study based on the SEMI-COVID-19 Registry, a nationwide registry that collects sociodemographic, clinical, laboratory, and treatment data on patients hospitalised with COVID-19 in Spain. Patients aged 20-65 years were selected. A multivariate logistic regression model was performed to identify factors associated with mortality. Results As of 22 May 2020, 4393 patients were included, of whom 419 (9.5%) were HCW. Median (interquartile range) age of HCW was 52 (15) years and 62.4% were women. Prevalence of comorbidities and severe radiological findings upon admission were less frequent in HCW. There were no difference in need of respiratory support and admission to intensive care unit, but occurrence of sepsis and in-hospital mortality was lower in HCW (1.7% vs. 3.9%; p = 0.024 and 0.7% vs. 4.8%; p<0.001 respectively). Age, male sex and comorbidity, were independently associated with higher in-hospital mortality and healthcare working with lower mortality (OR 0.211, 95%CI 0.067-0.667, p = 0.008). 30-days survival was higher in HCW (0.968 vs. 0.851 p<0.001). Conclusions Hospitalized COVID-19 HCW had fewer comorbidities and a better prognosis than NHCW. Our results suggest that professional exposure to COVID-19 in HCW does not carry more clinical severity nor mortality

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio