AIMC Topic: Antineoplastic Agents

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Rumex dentatus could be a potent alternative to treatment of microbial infections and of breast cancer.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE: To investigate the phytochemicals and in vitro antioxidant, antimicrobial and cytotoxic potential of Rumex dentatus (R. dentatus) leaf extracts.

[Rectal Gastrointestinal Stromal Tumor(GIST)Excised by Two Teams Following Neoadjuvant Chemotherapy-A Case Report].

Gan to kagaku ryoho. Cancer & chemotherapy
A 67-year-old man presented with bloody stools. Colonoscopy showed a small submucosal tumor in the lower rectum. As the tumor was small, follow-up was chosen. Although he was instructed to undergo reexamination 1 year later, he did not comply. Four y...

Effects of Jiazhu decoction in combination with cyclophosphamide on breast cancer in mice.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan
OBJECTIVE: To investigate the therapeutic effects of Jiazhu decoction (JZD) in combination with cyclophosphamide (CTX) on the growth of breast cancer in mice and to explore the possible molecular mechanisms of action.

[French ccAFU guidelines – Update 2018–2020: Bladder cancer].

Progres en urologie : journal de l'Association francaise d'urologie et de la Societe francaise d'urologie
OBJECTIVE: To propose updated French guidelines for non-muscle invasive (NMIBC) and muscle-invasive (MIBC) bladder cancers.

Prediction of Drug Approval After Phase I Clinical Trials in Oncology: RESOLVED2.

JCO clinical cancer informatics
PURPOSE: Drug development in oncology currently is facing a conjunction of an increasing number of antineoplastic agents (ANAs) candidate for phase I clinical trials (P1CTs) and an important attrition rate for final approval. We aimed to develop a ma...

MOLI: multi-omics late integration with deep neural networks for drug response prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Historically, gene expression has been shown to be the most informative data for drug response prediction. Recent evidence suggests that integrating additional omics can improve the prediction accuracy which raises the question of how to ...

A deep learning model based on sparse auto-encoder for prioritizing cancer-related genes and drug target combinations.

Carcinogenesis
Prioritization of cancer-related genes from gene expression profiles and proteomic data is vital to improve the targeted therapies research. Although computational approaches have been complementing high-throughput biological experiments on the under...

A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care.

Clinical chemistry and laboratory medicine
Background uPA and PAI-1 are breast cancer biomarkers that evaluate the benefit of chemotherapy (CT) for HER2-negative, estrogen receptor-positive, low or intermediate grade patients. Our objectives were to observe clinical routine use of uPA/PAI-1 a...

Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

Tomography (Ann Arbor, Mich.)
We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre-...

canSAR: update to the cancer translational research and drug discovery knowledgebase.

Nucleic acids research
canSAR (http://cansar.icr.ac.uk) is a public, freely available, integrative translational research and drug discovery knowlegebase. canSAR informs researchers to help solve key bottlenecks in cancer translation and drug discovery. It integrates genom...