Results 151 to 160 of about 878,882 (266)

Correlation of the differential expression of PIK3R1 and its spliced variant, p55α, in pan‐cancer

Molecular Oncology, EarlyView.
PIK3R1 undergoes alternative splicing to generate the isoforms, p85α and p55α. By combining large patient datasets with laboratory experiments, we show that PIK3R1 spliced variants shape cancer behavior. While tumors lose the protective p85α isoform, p55α is overexpressed, changes linked to poorer survival and more pronounced in African American ...
Ishita Gupta, Yang Song, Madeleine Ndahayo, Anirudh Saxena, Theresa Guo, Dylan Z. Kelley, Jessica Gore, Andrew Hennigan, Alexa Anderson, John C. Papadimitriou, Daria A. Gaykalova   +10 more
wiley   +1 more source

Codon usage optimization contributes to evolutionary dynamics of TetM following its acquisition via interspecies and intergeneric recombination events in recipient bacteria. [PDF]

BMC Microbiol
Kobakhidze S, Janelidze D, Kuchuloria N, Kotetishvili M.   +3 more
europepmc   +1 more source

Circular RNA expression landscapes in myelodysplastic neoplasms: Associations with mutational signatures and disease progression

Molecular Oncology, EarlyView.
In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge, Morten Tulstrup, Gabriele Todisco, Pedro Moura, Christophe Côme, Jakob Werner Hansen, Jakob Schmidt Jespersen, Balthasar Schlotmann, Maria Creignou, Mette Dahl, Claudia Schöllkopf, Klas Raaschou‐Jensen, Krister Wennerberg, Bo Porse, Joachim Weischenfeldt, Eva Hellström‐Lindberg, Lasse Sommer Kristensen, Kirsten Grønbæk   +17 more
wiley   +1 more source

Mutational biases and selection in mitochondrial genomes: insights from a comparative analysis of natural and laboratory populations of Caenorhabditis elegans. [PDF]

G3 (Bethesda)
Schifano A, Bergthorsson U, Katju V.
europepmc   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Colorectal cancer‐derived FGF19 is a metabolically active serum biomarker that exerts enteroendocrine effects on mouse liver

Molecular Oncology, EarlyView.
Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley, Michael W. Rohr, Joseph A. Goode, Sai Preethi Nakkina, Jignesh G. Parikh, Deborah A. Altomare   +5 more
wiley   +1 more source

Computational approaches for RNA structure prediction and design. [PDF]

Cell Rep Phys Sci
Kagaya Y, Liu B, Kihara D.
europepmc   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

Molecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns, Jaclyn S. Long, Sergio Lilla, Kelly Hodge, Marcus J. G. W. Ladds, Colin Nixon, Paula Fernández‐Palanca, Sara Zanivan, Pilar Acedo, Stephen P. Pereira, Kevin M. Ryan   +10 more
wiley   +1 more source

NTFold: Structure-Sensing Nucleotide Attention Learning for RNA Secondary Structure Prediction. [PDF]

Sensors (Basel)
Jin K, Zhang Z, Lan G, Xiao S, Yang J.
europepmc   +1 more source

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

Molecular Oncology, EarlyView.
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel, Peyman Zarrineh, Nathnael T. Tuffa, Jigar H. Sheth, Sumitra Mohan, Mudassar Iqbal, Sankari Nagarajan   +6 more
wiley   +1 more source