Search results for "Mach"
showing 10 items of 3360 documents
Assessment of tumor-infiltrating TCRV γ 9V δ 2 γδ lymphocyte abundance by deconvolution of human cancers microarrays
2017
Most human blood γδ cells are cytolytic TCRVγ9Vδ2+lymphocytes with antitumor activity. They are currently investigated in several clinical trials of cancer immunotherapy but so far, their tumor infiltration has not been systematically explored across human cancers. Novel algorithms allowing the deconvolution of bulk tumor transcriptomes to find the relative proportions of infiltrating leucocytes, such as CIBERSORT, should be appropriate for this aim but in practice they fail to accurately recognize γδ T lymphocytes. Here, by implementing machine learning from microarray data, we first improved the computational identification of blood-derived TCRVγ9Vδ2+γδ lymphocytes and then appl…
TLR1 and PRKAA1 Gene Polymorphisms in the Development of Atrophic Gastritis and Gastric Cancer.
2018
Background & Aims: Previous genome-wide association studies showed that genetic polymorphisms in toll-like receptor 1 (TLR1) and protein kinase AMP-activated alpha 1 catalytic subunit (PRKAA1) genes were associated with gastric cancer (GC) or increased Helicobacter pylori (H. pylori) infection susceptibility. The aim of this study was to evaluate the association between TLR1 and PRKAA1 genes polymorphisms and H.pylori infection, atrophic gastritis (AG) or GC in the European population.Methods: Single-nucleotide polymorphisms (SNPs) were analysed in 511 controls, 340 AG patients and 327 GC patients. TLR1 C>T (rs4833095) and PRKAA1 C>T (rs13361707) were genotyped by the real-time po…
FAST: a randomised phase II study of zolbetuximab (IMAB362) plus EOX versus EOX alone for first-line treatment of advanced CLDN18.2-positive gastric …
2021
Claudin 18.2 (CLDN18.2) is contained within normal gastric mucosa epithelial tight junctions; upon malignant transformation, CLDN18.2 epitopes become exposed. Zolbetuximab, a chimeric monoclonal antibody, mediates specific killing of CLDN18.2-positive cells through immune effector mechanisms.The FAST study enrolled advanced gastric/gastro-oesophageal junction and oesophageal adenocarcinoma patients (aged ≥18 years) with moderate-to-strong CLDN18.2 expression in ≥40% tumour cells. Patients received first-line epirubicin + oxaliplatin + capecitabine (EOX, arm 1, n = 84) every 3 weeks (Q3W), or zolbetuximab + EOX (loading dose, 800 mg/mIn the overall population, both PFS [hazard ratio (HR) = 0…
Telomere length and health outcomes: An umbrella review of systematic reviews and meta-analyses of observational studies.
2019
The aim of the present study was to map and grade evidence for the relationships between telomere length with a diverse range of health outcomes, using an umbrella review of systematic reviews with meta-analyses. We searched for meta-analyses of observational studies reporting on the association of telomere length with any health outcome (clinical disease outcomes and intermediate traits). For each association, random-effects summary effect size, 95% confidence interval (CI), and 95% prediction interval were calculated. To evaluate the credibility of the identified evidence, we assessed also heterogeneity, evidence for small-study effect and evidence for excess significance bias. Twenty-one…
Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms
2020
Author(s): Christopher, Mark; Nakahara, Kenichi; Bowd, Christopher; Proudfoot, James A; Belghith, Akram; Goldbaum, Michael H; Rezapour, Jasmin; Weinreb, Robert N; Fazio, Massimo A; Girkin, Christopher A; Liebmann, Jeffrey M; De Moraes, Gustavo; Murata, Hiroshi; Tokumo, Kana; Shibata, Naoto; Fujino, Yuri; Matsuura, Masato; Kiuchi, Yoshiaki; Tanito, Masaki; Asaoka, Ryo; Zangwill, Linda M | Abstract: PurposeTo compare performance of independently developed deep learning algorithms for detecting glaucoma from fundus photographs and to evaluate strategies for incorporating new data into models.MethodsTwo fundus photograph datasets from the Diagnostic Innovations in Glaucoma Study/African Descent…
Risk Assessment of Hip Fracture Based on Machine Learning
2020
[EN] Identifying patients with high risk of hip fracture is a great challenge in osteoporosis clinical assessment. Bone Mineral Density (BMD) measured by Dual-Energy X-Ray Absorptiometry (DXA) is the current gold standard in osteoporosis clinical assessment. However, its classification accuracy is only around 65%. In order to improve this accuracy, this paper proposes the use of Machine Learning (ML) models trained with data from a biomechanical model that simulates a sideways-fall. Machine Learning (ML) models are models able to learn and to make predictions from data. During a training process, ML models learn a function that maps inputs and outputs without previous knowledge of the probl…
Deep learning in next-generation sequencing
2020
Highlights • Machine learning increasingly important for NGS. • Deep learning can improve many NGS applications.
Mutant p53 induces Golgi tubulo-vesiculation driving a prometastatic secretome
2020
TP53 missense mutations leading to the expression of mutant p53 oncoproteins are frequent driver events during tumorigenesis. p53 mutants promote tumor growth, metastasis and chemoresistance by affecting fundamental cellular pathways and functions. Here, we demonstrate that p53 mutants modify structure and function of the Golgi apparatus, culminating in the increased release of a pro-malignant secretome by tumor cells and primary fibroblasts from patients with Li-Fraumeni cancer predisposition syndrome. Mechanistically, interacting with the hypoxia responsive factor HIF1α, mutant p53 induces the expression of miR-30d, which in turn causes tubulo-vesiculation of the Golgi apparatus, leading …
The role of tumor-associated macrophages in gastric cancer development and their potential as a therapeutic target.
2020
Gastric cancer (GC) represents the fifth cause of cancer-related death worldwide. Molecular biology has become a central area of research in GC and there are currently at least three major classifications available to elucidate the mechanisms that drive GC oncogenesis. Further, tumor microenvironment seems to play a crucial role, and tumor-associated macrophages (TAMs) are emerging as key players in GC development. TAMs are cells derived from circulating chemokine- receptor-type 2 (CCR2) inflammatory monocytes in blood and can be divided into two main types, M1 and M2 TAMs. M2 TAMs play an important role in tumor progression, promoting a pro-angiogenic and immunosuppressive signal in the tu…
A Pan-Cancer Approach to Predict Responsiveness to Immune Checkpoint Inhibitors by Machine Learning
2019
Immunotherapy by using immune checkpoint inhibitors (ICI) has dramatically improved the treatment options in various cancers, increasing survival rates for treated patients. Nevertheless, there are heterogeneous response rates to ICI among different cancer types, and even in the context of patients affected by a specific cancer. Thus, it becomes crucial to identify factors that predict the response to immunotherapeutic approaches. A comprehensive investigation of the mutational and immunological aspects of the tumor can be useful to obtain a robust prediction. By performing a pan-cancer analysis on gene expression data from the Cancer Genome Atlas (TCGA, 8055 cases and 29 cancer types), we …