Results 61 to 70 of about 156,516 (263)

The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers

Molecular Oncology, EarlyView.
The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce, Simone Bini, Marialuisa Sponziello, Giorgio Grani, Giulia Fiscon, Paola Paci, Lorenzo Farina, Rosa Falcone, Valentina Maggisano, Sebastiano Filetti, Cosimo Durante, Antonella Verrienti   +11 more
wiley   +1 more source

One-Step Graph Fusion Fuzzy Clustering Network

IEEE Access
Graph clustering plays a crucial role in uncovering implicit information within data which can be used to rationally classify potential data samples in unsupervised scenarios.
Bin Tang, Zhongyang Zhou, Xuewen Liu, Feiyu Chen   +3 more
doaj   +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

A Scalable Deep Network for Graph Clustering via Personalized PageRank

Applied Sciences, 2022
Recently, many models based on the combination of graph convolutional networks and deep learning have attracted extensive attention for their superior performance in graph clustering tasks. However, the existing models have the following limitations: (1)
Yulin Zhao, Xunkai Li, Yinlin Zhu, Jin Li, Shuo Wang, Bin Jiang   +5 more
doaj   +1 more source

Differential expression of cancer‐related genes supports prediction of poor response to first‐line treatments in T‐ALL pediatric patients with high minimal residual disease

Molecular Oncology, EarlyView.
In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera, Laura Vela‐Martín, Pablo Fernández‐Navarro, José Luis López‐Lorenzo, Javier Cornago, Pilar Llamas, Eduardo Pérez‐Gómez, José Luis Marín‐Rubio, Manuel Fresno, Javier Santos, José Fernández‐Piqueras, María Villa‐Morales   +11 more
wiley   +1 more source

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

Molecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh, Nitzan Medina‐Itzhaki, Milena Chekov, Eden Gal‐Swisa, Roba Gabesh‐Wahabi, Inbar Savyon, Inna Naroditsky, Hilary A. Kenny, Basem Fares, Lina Korsensky, Einav Girsh, Liron Berger, Ruth Perets   +12 more
wiley   +1 more source

Fast Spectral Clustering via Efficient Multilayer Anchor Graph

International Journal of Aerospace Engineering
Recent studies have shown that graph-based clustering methods are good at processing hyperspectral images (HSIs), while falling short for large-scale HSIs due to high time complexity.
Yiwei Wei, Chao Niu, Dejun Liu, Peinan Ren   +3 more
doaj   +1 more source

Metastasis on pause: How dormant tumor cells stay hidden within the tumor microenvironment and evade immune surveillance

Molecular Oncology, EarlyView.
Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary, Jose Javier Bravo‐Cordero   +1 more
wiley   +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska, Stephany Gallardo, Nur S. Zainal, Leena Arora, Matthew Ellis, Maria‐Antoinette Lopez, Judith Austine, Sai Pittla, Serena J Chee, Aiman Alzetani, Emily C Shaw, Christian H Ottensmeier, Gareth J Thomas, Christopher J Hanley   +13 more
wiley   +1 more source

Completely connected clustered graphs

Journal of Discrete Algorithms, 2003
A clustered graph \((G,T,r)\) consists of a graph \(G=(V,E)\), a tree \(T\), and an inner vertex \(r\) of \(T\) such that the set of leaves of \(T\) is exactly \(V\). A clustered graph is said to be completely connected if every cluster, and also each complement of a cluster, induces a connected subgraph.
Sabine Cornelsen, Dorothea Wagner
openaire   +2 more sources