AIMC Topic: Epithelial-Mesenchymal Transition
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Data-Driven Sustainable Campaigns to Decipher Invasive Breast Cancer Features.
ACS biomaterials science & engineering
Jul 25, 2025
The intrinsic complexity of biological processes often hides the role of dynamic microenvironmental cues in the development of pathological states. Microphysiological systems (MPSs) are emerging technological platforms that model dynamics of tissue-...
Identification and validation of epithelial‑mesenchymal transition‑related genes for diabetic nephropathy by WGCNA and machine learning.
Molecular medicine reports
Jul 11, 2025
Diabetic nephropathy (DN) is the main cause of end‑stage renal disease, with epithelial‑mesenchymal transition (EMT) serving a key role in its initiation and progression. Nevertheless, the precise mechanisms involved remain unidentified. The present ...
Multi-omics integration and machine learning uncover molecular basal-like subtype of pancreatic cancer and implicate A2ML1 in promoting tumor epithelial-mesenchymal transition.
Journal of translational medicine
Jul 4, 2025
BACKGROUND: Pancreatic cancer (PC) represents a highly heterogeneous malignancy with poor prognosis, where precise molecular subtyping facilitates comprehensive understanding of disease progression.
Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.
Scientific reports
Jun 5, 2025
Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the proneural subtype has a relatively good prognosis, and the mesenchymal type is the most aggressive form with the worst prognosis. GBM undergoes proneura...
Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.
Nature communications
May 17, 2025
Standard immunofluorescence imaging captures just ~4 molecular markers (4-plex) per cell, limiting dissection of complex biology. Inspired by multimodal omics-based data integration approaches, we propose an Extensible Immunofluorescence (ExIF) frame...
Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer.
Breast cancer research : BCR
Jan 12, 2025
Recent evidence indicates that endocrine resistance in estrogen receptor-positive (ER+) breast cancer is closely correlated with phenotypic characteristics of epithelial-to-mesenchymal transition (EMT). Nonetheless, identifying tumor tissues with a m...
AGML: Adaptive Graph-Based Multi-Label Learning for Prediction of RBP and as Event Associations During EMT.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Increasing evidence has indicated that RNA-binding proteins (RBPs) play an essential role in mediating alternative splicing (AS) events during epithelial-mesenchymal transition (EMT). However, due to the substantial cost and complexity of biological ...
Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy.
Biology direct
Nov 12, 2024
Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability of multiple treatment modalities, the prognosis for patients diagnosed with glioma remains unfavorable. Therefore, further exploration of new biomark...
Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Oct 9, 2024
Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversi...
Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer.
Cells
Aug 6, 2024
Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming an...
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