Results 141 to 150 of about 464,133 (328)

Towards the Application of Atorvastatin to Intensify Proapoptotic Potential of Conventional Antileukemic Agents In Vitro [PDF]

, 2015
It has been previously revealed that statins used at high concentrations display antileukemic potential towards chronic lymphocytic leukemia (CLL) cells.
Błoński, Jerzy Z., Cebula-Obrzut, Barbara, Hikisz, Paweł, Kaźmierczuk, Arleta, Kiliańska, Zofia M., Misiewicz, Małgorzata, Robak, Paweł, Smolewski, Piotr, Wawrzyniak, Ewa, Żołnierczyk, Jolanta   +9 more
core   +3 more sources

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, Jae Won Oh, Hyewon Chung, Jung Won Kwon, Yi Rang Na, Kwang Pyo Kim, Seung Hyeok Seok   +6 more
wiley   +1 more source

Unlocking the potential of anti-CD33 therapy in adult and childhood acute myeloid leukaemia [PDF]

, 2017
Acute Myeloid Leukaemia (AML) develops when there is a block in differentiation and uncontrolled proliferation of myeloid precursors, resulting in bone marrow failure.
Gibson, Brenda E.S., Harrison, Christine J., Keeshan, Karen, Laing, Alison A.   +3 more
core   +1 more source

Predicting trajectories and mechanisms of antibiotic resistance evolution [PDF]

arXiv, 2020
Bacteria evolve resistance to antibiotics by a multitude of mechanisms. A central, yet unsolved question is how resistance evolution affects cell growth at different drug levels. Here we develop a fitness model that predicts growth rates of common resistance mutants from their effects on cell metabolism. We map metabolic effects of resistance mutations
arxiv  

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, Kathryn A. Wierenga, Frank M. Riemers, Elsbeth A. van Liere, Bart Westendorp   +4 more
wiley   +1 more source

The under-appreciated promiscuity of the epidermal growth factor receptor family.

Frontiers in Cell and Developmental Biology, 2016
Each member of the epidermal growth factor receptor (EGFR) family plays a key role in normal development, homeostasis and a variety of pathophysiological conditions, most notably in cancer.
Sean P Kennedy, Jordan F Hastings, Jeremy Z.R. Han, David R Croucher, David R Croucher, David R Croucher   +5 more
doaj   +1 more source

CircCCNB1 inhibits vasculogenic mimicry by sequestering NF90 to promote miR‐15b‐5p and miR‐7‐1‐3p processing in nasopharyngeal carcinoma

Molecular Oncology, EarlyView.
CircCCNB1 expression is down‐regulated in nasopharyngeal carcinoma (NPC); thus, less NF90 protein is bound to circCCNB1 and more binds to pri‐miRNAs, blocking their (pri‐miRNAs) binding to DGCR8 and inhibiting the processing and generation of miR‐15b‐5p/miR‐7‐1‐3p. Furthermore, decreased miR‐15b‐5p/miR‐7‐1‐3p promotes the expression of the target genes
Chunmei Fan, Fenghua Tan, Jie Wu, Zhaoyang Zeng, Wenjia Guo, He Huang, Wei Xiong   +6 more
wiley   +1 more source

Dynamics of growth factor production in monolayers of cancer cells and evolution of resistance to anticancer therapies [PDF]

, 2013
Tumor heterogeneity is well documented for many characters, including the production of growth factors, which improve tumor proliferation and promote resistance against apoptosis and against immune reaction.
Achilles, Aktipis, Aktipis, Amit, André, Archetti, Archetti, Archetti, Archetti, Archetti, Archetti, Armitage, Ashley, Axelrod, Basanta, Basanta, Basanta, Basanta, Basanta, Boza, Byrne, Cairns, Charles, Chuang, Crespi, Crespi, Dexter, Dingli, Durrett, Eungdamrong, Fisher, Foster, Frank, Gatenby, Gatenby, Gerstung, Gonzalez-Garcia, Greaves, Hanahan, Hardin, Hauert, Hemker, Ifti, Iwasa, Jouanneau, Knudson, Lambert, Maley, Marusyk, Maynard Smith, Mendes, Merlo, Motro, Nagy, Nordling, Nowell, Ohtsuki, Pacheco, Palfrey, Pepper, Perc, Rapoport, Ricard, Sugden, Tomlinson, Tomlinson, Traulsen, Traulsen   +67 more
core   +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, Zhe Wang, Guangji Zhang, Jiangxue Hou, Kaiqi Liu, Shuning Wei, Yan Li, Chunlin Zhou, Dong Lin, Min Wang, Hui Wei, Jianxiang Wang, Tao Cheng, Yingchang Mi   +13 more
wiley   +1 more source

Novel strategy for rapid functional in vivo validation of oncogenic drivers in haematological malignancies [PDF]

, 2019
In cancer research, it remains challenging to functionally validate putative novel oncogenic drivers and to establish relevant preclinical models for evaluation of novel therapeutic strategies.
Berx, Geert, D'Hont, Jinke, Demoen, Lisa, Goossens, Steven, Haenebalcke, Lieven, Haigh, Jody J., Hochepied, Tino, Lammens, Tim, Lemeire, Kelly, Lintermans, Béatrice, Matthijssens, Filip, Pedro Pinto De Almeida, André, Pieters, Tim, Reunes, Lindy, T'Sas, Sara, Van Vlierberghe, Pieter, Vanrockeghem, Frédérique   +16 more
core   +2 more sources