Short-term serotonergic but not noradrenergic antidepressant administration reduces attentional vigilance to threat in healthy volunteers

Anxiety is associated with threat-related biases in information processing such as heightened attentional vigilance to potential threat. Such biases are an important focus of psychological treatments for anxiety disorders. Selective serotonin reuptake inhibitors (SSRIs) are effective in the treatment of a range of anxiety disorders. The aim of this study was to assess the effect of an SSRI on the processing of threat in healthy volunteers. A selective noradrenergic reuptake inhibitor (SNRI), which is not generally used in the treatment of anxiety, was used as a contrast to assess the specificity of SSRI effects on threat processing. Forty-two healthy volunteers were randomly assigned to 7 d double-blind intervention with the SSRI citalopram (20 mg/d), the SNRI reboxetine (8 mg/d), or placebo. On the final day, attentional and interpretative bias to threat was assessed using the attentional probe and the homograph primed lexical decision tasks. Citalopram reduced attentional vigilance towards fearful faces but did not affect the interpretation of ambiguous homographs as threatening. Reboxetine had no significant effect on either of these measures. Citalopram reduces attentional orienting to threatening stimuli, which is potentially relevant to its clinical use in the treatment of anxiety disorders. This finding supports a growing literature suggesting that an important mechanism through which pharmacological agents may exert their effects on mood is by reversing the cognitive biases that characterize the disorders that they treat. Future studies are needed to clarify the neural mechanisms through which these effects on threat processing are mediated

Optimizing exosomal RNA isolation for RNA-Seq analyses of archival sera specimens

Exosomes are endosome-derived membrane vesicles that contain proteins, lipids, and nucleic acids. The exosomal transcriptome mediates intercellular communication, and represents an understudied reservoir of novel biomarkers for human diseases. Next-generation sequencing enables complex quantitative characterization of exosomal RNAs from diverse sources. However, detailed protocols describing exosome purification for preparation of exosomal RNA-sequence (RNA-Seq) libraries are lacking. Here we compared methods for isolation of exosomes and extraction of exosomal RNA from human cell-free serum, as well as strategies for attaining equal representation of samples within pooled RNA-Seq libraries. We compared commercial precipitation with ultracentrifugation for exosome purification and confirmed the presence of exosomes via both transmission electron microscopy and immunoblotting. Exosomal RNA extraction was compared using four different RNA purification methods. We determined the minimal starting volume of serum required for exosome preparation and showed that high quality exosomal RNA can be isolated from sera stored for over a decade. Finally, RNA-Seq libraries were successfully prepared with exosomal RNAs extracted from human cell-free serum, cataloguing both coding and non-coding exosomal transcripts. This method provides researchers with strategic options to prepare RNA-Seq libraries and compare RNA-Seq data quantitatively from minimal volumes of fresh and archival human cell-free serum for disease biomarker discovery

ABCB1 (MDR1) polymorphisms and ovarian cancer progression and survival: A comprehensive analysis from the Ovarian Cancer Association Consortium and The Cancer Genome Atlas

<b>Objective</b> <i>ABCB1</i> encodes the multi-drug efflux pump P-glycoprotein (P-gp) and has been implicated in multi-drug resistance. We comprehensively evaluated this gene and flanking regions for an association with clinical outcome in epithelial ovarian cancer (EOC).<p></p> <b>Methods</b> The best candidates from fine-mapping analysis of 21 <i>ABCB1</i> SNPs tagging C1236T (rs1128503), G2677T/A (rs2032582), and C3435T (rs1045642) were analysed in 4616 European invasive EOC patients from thirteen Ovarian Cancer Association Consortium (OCAC) studies and The Cancer Genome Atlas (TCGA). Additionally we analysed 1,562 imputed SNPs around ABCB1 in patients receiving cytoreductive surgery and either ‘standard’ first-line paclitaxel–carboplatin chemotherapy (n = 1158) or any first-line chemotherapy regimen (n = 2867). We also evaluated ABCB1 expression in primary tumours from 143 EOC patients.<p></p> <b>Result</b> Fine-mapping revealed that rs1128503, rs2032582, and rs1045642 were the best candidates in optimally debulked patients. However, we observed no significant association between any SNP and either progression-free survival or overall survival in analysis of data from 14 studies. There was a marginal association between rs1128503 and overall survival in patients with nil residual disease (HR 0.88, 95% CI 0.77–1.01; p = 0.07). In contrast, <i>ABCB1</i> expression in the primary tumour may confer worse prognosis in patients with sub-optimally debulked tumours.<p></p> <b>Conclusion</b> Our study represents the largest analysis of <i>ABCB1</i> SNPs and EOC progression and survival to date, but has not identified additional signals, or validated reported associations with progression-free survival for rs1128503, rs2032582, and rs1045642. However, we cannot rule out the possibility of a subtle effect of rs1128503, or other SNPs linked to it, on overall survival.<p></p&gt

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

Peer reviewedPublisher PD

Diagnostic value of exome and whole genome sequencing in craniosynostosis

Background Craniosynostosis, the premature fusion of one or more cranial sutures, occurs in ~1 in 2250 births, either in isolation or as part of a syndrome. Mutations in at least 57 genes have been associated with craniosynostosis, but only a minority of these are included in routine laboratory genetic testing. Methods We used exome or whole genome sequencing to seek a genetic cause in a cohort of 40 subjects with craniosynostosis, selected by clinical or molecular geneticists as being high-priority cases, and in whom prior clinically driven genetic testing had been negative. Results We identified likely associated mutations in 15 patients (37.5%), involving 14 different genes. All genes were mutated in single families, except for IL11RA (two families). We classified the other positive diagnoses as follows: commonly mutated craniosynostosis genes with atypical presentation (EFNB1, TWIST1); other core craniosynostosis genes (CDC45, MSX2, ZIC1); genes for which mutations are only rarely associated with craniosynostosis (FBN1, HUWE1, KRAS, STAT3); and known disease genes for which a causal relationship with craniosynostosis is currently unknown (AHDC1, NTRK2). In two further families, likely novel disease genes are currently undergoing functional validation. In 5 of the 15 positive cases, the (previously unanticipated) molecular diagnosis had immediate, actionable consequences for either genetic or medical management (mutations in EFNB1, FBN1, KRAS, NTRK2, STAT3). Conclusions This substantial genetic heterogeneity, and the multiple actionable mutations identified, emphasises the benefits of exome/whole genome sequencing to identify causal mutations in craniosynostosis cases for which routine clinical testing has yielded negative results

Resistance to receptor-blocking therapies primes tumors as targets for HER3-homing nanobiologics

Resistance to anti-tumor therapeutics is an important clinical problem. Tumor-targeted therapies currently used in the clinic are derived from antibodies or small molecules that mitigate growth factor activity. These have improved therapeutic efficacy and safety compared to traditional treatment modalities but resistance arises in the majority of clinical cases. Targeting such resistance could improve tumor abatement and patient survival. A growing number of such tumors are characterized by prominent expression of the human epidermal growth factor receptor 3 (HER3) on the cell surface. This study presents a “Trojan-Horse” approach to combating these tumors by using a receptor-targeted biocarrier that exploits the HER3 cell surface protein as a portal to sneak therapeutics into tumor cells by mimicking an essential ligand. The biocarrier used here combines several functions within a single fusion protein for mediating targeted cell penetration and non-covalent self-assembly with therapeutic cargo, forming HER3-homing nanobiologics. Importantly, we demonstrate here that these nanobiologics are therapeutically effective in several scenarios of resistance to clinically approved targeted inhibitors of the human EGF receptor family. We also show that such inhibitors heighten efficacy of our nanobiologics on naïve tumors by augmenting HER3 expression. This approach takes advantage of a current clinical problem (i.e. resistance to growth factor inhibition) and uses it to make tumors more susceptible to HER3 nanobiologic treatment. Moreover, we demonstrate a novel approach in addressing drug resistance by taking inhibitors against which resistance arises and re-introducing these as adjuvants, sensitizing tumors to the HER3 nanobiologics described here

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.

Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of tiles and classification problems are often weakly-supervised: the ground truth is only known for the slide, not for every single tile. In classical weakly-supervised analysis pipelines, all tiles inherit the slide label while in multiple-instance learning (MIL), only bags of tiles inherit the label. However, it is still unclear how these widely used but markedly different approaches perform relative to each other. We implemented and systematically compared six methods in six clinically relevant end-to-end prediction tasks using data from N=2980 patients for training with rigorous external validation. We tested three classical weakly-supervised approaches with convolutional neural networks and vision transformers (ViT) and three MIL-based approaches with and without an additional attention module. Our results empirically demonstrate that histological tumor subtyping of renal cell carcinoma is an easy task in which all approaches achieve an area under the receiver operating curve (AUROC) of above 0.9. In contrast, we report significant performance differences for clinically relevant tasks of mutation prediction in colorectal, gastric, and bladder cancer. In these mutation prediction tasks, classical weakly-supervised workflows outperformed MIL-based weakly-supervised methods for mutation prediction, which is surprising given their simplicity. This shows that new end-to-end image analysis pipelines in computational pathology should be compared to classical weakly-supervised methods. Also, these findings motivate the development of new methods which combine the elegant assumptions of MIL with the empirically observed higher performance of classical weakly-supervised approaches. We make all source codes publicly available at https://github.com/KatherLab/HIA, allowing easy application of all methods to any similar task

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

SMAD6 variants in craniosynostosis: genotype and phenotype evaluation

Purpose: Enrichment of heterozygous missense and truncating SMAD6 variants was previously reported in nonsyndromic sagittal and metopic synostosis, and interaction of SMAD6 variants with a common polymorphism near BMP2 (rs1884302) was proposed to contribute to inconsistent penetrance. We determined the occurrence of SMAD6 variants in all types of craniosynostosis, evaluated the impact of different missense variants on SMAD6 function, and tested independently whether rs1884302 genotype significantl

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management