Results 111 to 120 of about 551,720 (296)
Molecular Oncology, EarlyView.Cancer stem cells are associated with aggressive disease, but a deep characterization of such markers is lacking in endometrial cancer. This study uses imaging mass cytometry to explore putative cancer stem cell markers in endometrial tumors and corresponding organoid models.
Hilde E. Lien +7 more
wiley +1 more source
Frontiers in Public HealthBackgroundAdverse events in the primary care setting result in a direct cost equivalent to at least 2.5% of total healthcare spending. Across OECD countries, they lead to more than seven million avoidable hospital admissions annually. In this manuscript,
Maria A. Fiol-deRoque +57 more
doaj +1 more source
Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression
Molecular Oncology, EarlyView.Immune status significantly influences cancer progression. This study used plasma proteomics to analyze benign 67NR and malignant 4T1 breast tumor models at early and late tumor stages. Immune‐related proteins–osteopontin (Spp1), lactotransferrin (Ltf), calreticulin (Calr) and peroxiredoxin 2 (Prdx2)–were associated with systemic myeloid‐derived ...
Yeon Ji Park +6 more
wiley +1 more source
Stochastic variation in the FOXM1 transcription program mediates replication stress tolerance
Molecular Oncology, EarlyView.Cellular heterogeneity is a major cause of drug resistance in cancer. Segeren et al. used single‐cell transcriptomics to investigate gene expression events that correlate with sensitivity to the DNA‐damaging drugs gemcitabine and prexasertib. They show that dampened expression of transcription factor FOXM1 and its target genes protected cells against ...
Hendrika A. Segeren +4 more
wiley +1 more source
Molecular Oncology, EarlyView.The study evaluated the function and therapeutic implications of PRAME in basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). The findings demonstrate that PRAME impairs keratinocyte differentiation pathways. Furthermore, PRAME impairs anticancer response to retinoid compounds in BCC and SCC cells.
Brandon Ramchatesingh +6 more
wiley +1 more source
Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value
Molecular Oncology, EarlyView.The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song +13 more
wiley +1 more source
On the Power of Interactive Proofs for Learning [PDF]
We continue the study of doubly-efficient proof systems for verifying agnostic PAC learning, for which we obtain the following results. - We construct an interactive protocol for learning the $t$ largest Fourier characters of a given function $f \colon \{0,1\}^n \to \{0,1\}$ up to an arbitrarily small error, wherein the verifier uses $\mathsf{poly}(t)
arxiv +1 more source
Adverse prognosis gene expression patterns in metastatic castration‐resistant prostate cancer
Molecular Oncology, EarlyView.We aggregated a cohort of 1012 mCRPC tissue samples from 769 patients and investigated the association of gene expression‐based pathways with clinical outcomes. Loss of AR signaling, high proliferation, and a glycolytic phenotype were independently prognostic for poor outcomes, and an adverse transcriptional feature score incorporating these pathways ...
Marina N. Sharifi +26 more
wiley +1 more source
Transcriptome‐wide analysis of circRNA and RBP profiles and their molecular relevance for GBM
Molecular Oncology, EarlyView.CircRNAs are differentially expressed in glioblastoma primary tumors and might serve as therapeutic targets and diagnostic markers. The investigation of circRNA and RNA‐binding proteins (RBPs) interactions shows that distinct RBPs play a role in circRNA biogenesis and function.
Julia Latowska‐Łysiak +14 more
wiley +1 more source
Conditional Entropy as a Supervised Primitive Segmentation Loss Function [PDF]
arXiv, 2018 Supervised image segmentation assigns image voxels to a set of labels, as defined by a specific labeling protocol. In this paper, we decompose segmentation into two steps. The first step is what we call "primitive segmentation", where voxels that form sub-parts (primitives) of the various segmentation labels available in the training data, are grouped ...
arxiv