Tumoral PD-L1 expression defines a subgroup of poor-prognosis vulvar carcinomas with non-viral etiology

Vulvar cancer is rare but incidence rates are increasing due to an aging population and higher frequencies of young women being affected. In locally advanced, metastatic or recurrent disease prognosis is poor and new treatment modalities are needed. Immune checkpoint blockade of the PD-1/PD-L1 pathway is one of the most important advancements in cancer therapy in the last years. The clinical relevance of PD-L1 expression in vulvar cancer, however, has not been studied so far. We determined PD-L1 expression, numbers of CD3+ T cells, CD20+ B cells, CD68+ monocytes/macrophages, Foxp3+ regulatory T cells and CD163+ tumor-associated macrophages by immunohistochemistry in 103 patients. Correlation analysis with clinicopathological parameters was undertaken; the cause-specific outcome was modeled with competing risk analysis; multivariate Cox regression was used to determine independent predictors of survival. Membranous PD-L1 was expressed in a minority of tumors, defined by HPV-negativity. Its presence geographically correlated with immunocyte-rich regions of cancer islets and was an independent prognostic factor for poor outcome. Our data support the notion that vulvar cancer is an immunomodulatory tumor that harnesses the PD-1/PD-L1 pathway to induce tolerance. Accordingly, immunotherapeutic approaches might have the potential to improve outcome in patients with vulvar cancer and could complement conventional cancer treatment

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

Abstract: In cancer, the primary tumour’s organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here,as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Animals reduce drop-out rates in psychotherapy – results of a quantitative meta-analysis

Animal-assisted psychotherapy is an emerging field with great potential and growing popularity. However, empirical research on its effectiveness is insufficient, and consistent evidence about patients’ commitment is missing. The present meta-analysis addresses this gap by systematically investigating whether drop-out rates in animal-assisted psychotherapy are lower than in conventional psychotherapy settings

Frontal-Midline Theta Neurofeedback - Metaanalysis

Frontal Midline Theta (FMT) is an oscillation of roughly 4-8Hz with a source estimated to be in the dorsal anterior cingulate cortex (dACC) (Cavanagh &amp; Frank, 2014; Mitchell et al., 2008). It is associated with several behavioral measures, such as those of cognitive control, anxiety and flow experience (Cavanagh &amp; Frank, 2014; Katahira et al., 2018; Mitchell et al., 2008; Osinsky et al., 2017; Schmidt et al., 2018). Neurofeedback (NF) is a method that presents feedback of a user's brain activity measured in real-time (e.g., by EEG or fMRI). This allows users to become aware of specific neuronal activity (e.g., FMT amplitude) and to learn to voluntarily modify it. Thus, NF provides a unique opportunity to validate links between brain activity and behavior (Kvamme et al., 2022). The main goal of this study is to provide a systematic review and a quantitative meta-analysis of studies investigating the effectiveness of neurofeedback, as a tool to modulate FMT. Further, specific variables influencing the behavioral effects induced by FMT modulation will be investigated

Cardiorenal Syndrome is Present in Human Fetuses with Severe, Isolated Urinary Tract Malformations

<div><p>Objective</p><p>We analyzed the association between renal and cardiovascular parameters in fetuses with isolated severe urinary tract malformations.</p><p>Methods</p><p>39 fetuses at a mean gestational age of 23.6 weeks with nephropathies or urinary tract malformations and markedly impaired or absent renal function were prospectively examined. Fetal echocardiography was performed, and thicknesses of the interventricular septum, and left and right ventricular wall were measured. Blood flow velocity waveforms of the umbilical artery, middle cerebral artery, and ductus venosus were obtained by color Doppler ultrasound. Concentrations of circulating n-terminal pro-B-type natriuretic peptide (nt-proBNP), cystatin C, ß₂-microglobulin, and hemoglobin were determined from fetal blood samples.</p><p>Results</p><p>Malformations included 21 cases of obstructive uropathy, 10 fetuses with bilateral nephropathy, and 8 cases of bilateral renal agenesis. Marked biventricular myocardial hypertrophy was present in all cases. The ratio between measured and gestational age-adjusted normal values was 2.01 (interventricular septum), 1.85, and 1.78 (right and left ventricular wall, respectively). Compared to controls, levels of circulating nt-proBNP were significantly increased (median (IQR) 5035 ng/L (5936 ng/L) vs. 1874 ng/L (1092 ng/L); p<0.001). Cystatin C and ß₂-microglobulin concentrations were elevated as follows (mean ± SD) 1.85±0.391 mg/L and 8.44±2.423 mg/L, respectively (normal range 1.66±0.202 mg/L and 4.25±0.734 mg/L, respectively). No correlation was detected between cardiovascular parameters and urinary tract morphology and function. Despite increased levels of nt-proBNP cardiovascular function was preserved, with normal fetal Doppler indices in 90.2% of cases.</p><p>Conclusion</p><p>Urinary tract malformations resulting in severe renal impairment are associated with biventricular myocardial hypertrophy and elevated concentrations of circulating nt-proBNP during fetal life. Cardiovascular findings do not correlate with kidney function or morphology.</p></div

In vivo intratumor angiogenic treatment effects during taxane-based neoadjuvant chemotherapy of ovarian cancer

Abstract Background The aim of our study was to analyze the effect of taxane-based chemotherapy on tumor angiogenesis in patients with advanced epithelial ovarian cancer. Methods Within a prospective phase II trial, 32 patients with stage IIIC and IV ovarian cancer were treated with either two or three cycles of neoadjuvant chemotherapy prior to cytoreductive surgery. Carboplatin (AUC5) and docetaxel (75 mg/m2) were administered intravenously in a 3-weekly schedule. Changes in intratumor microvessel density (MVD) were assessed with immunohistochemistry by staining pre- and posttreatment surgical tumor specimens with panendothelial, neovascular and lymphatic vessel markers. Results Mean values of MVD defined by CD31, CD34, CD105 and D2-40 antibodies showed 12.3, 21.0, 2.7 and 3.1 vessels per high power field (HPF) before chemotherapy and increased after treatment to 15.3, 21.8, 4.8 and 3.6 per HPF, respectively. These changes were significant for CD31 (p = 0.04) and for CD105 (p = 0.02). Conclusion Taxane-based chemotherapy appears to promote tumor vascularization when administered every 3 weeks. A possible explanation is the secondary recovery of MVD in response to immediate cytotoxic and antiangiogenic effects of the chemotherapy. If confirmed prospectively, these findings favor shorter treatment intervals of taxane-based chemotherapy to counteract proangiogenic recovery.</p

COOBoostR: An Extreme Gradient Boosting-Based Tool for Robust Tissue or Cell-of-Origin Prediction of Tumors

We present here COOBoostR, a computational method designed for the putative prediction of the tissue- or cell-of-origin of various cancer types. COOBoostR leverages regional somatic mutation density information and chromatin mark features to be applied to an extreme gradient boosting-based machine-learning algorithm. COOBoostR ranks chromatin marks from various tissue and cell types, which best explain the somatic mutation density landscape of any sample of interest. A specific tissue or cell type matching the chromatin mark feature with highest explanatory power is designated as a potential tissue- or cell-of-origin. Through integrating either ChIP-seq based chromatin data, along with regional somatic mutation density data derived from normal cells/tissue, precancerous lesions, and cancer types, we show that COOBoostR outperforms existing random forest-based methods in prediction speed, with comparable or better tissue or cell-of-origin prediction performance (prediction accuracy—normal cells/tissue: 76.99%, precancerous lesions: 95.65%, cancer cells: 89.39%). In addition, our results suggest a dynamic somatic mutation accumulation at the normal tissue or cell stage which could be intertwined with the changes in open chromatin marks and enhancer sites. These results further represent chromatin marks shaping the somatic mutation landscape at the early stage of mutation accumulation, possibly even before the initiation of precancerous lesions or neoplasia