Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 11368287

Bendamustine.

J A Balfour·K L Goa
View original source ↗Export metadata ↓

Abstract

Bendamustine is a bifunctional alkylating agent with cytotoxic activity against human ovarian and breast cancers in vitro. It shows only partial in vitro cross-resistance with cyclophosphamide, melphalan, carmustine and cisplatin. Bendamustine as monotherapy or as part of combination chemotherapy protocols for first-line or subsequent treatment produced objective response rates of 61 to 97% in patients with Hodgkin's disease or non-Hodgkin's lymphoma (NHL) [41 to 48% in high grade NHL]. In patients with multiple myeloma, a bendamustine/prednisone regimen produced a higher rate of complete response (32 vs 11%) and more durable responses than a melphalan/prednisone regimen. Substitution of bendamustine for cyclophosphamide in a standard first-line COP regimen (cyclophosphamide, vincristine and prednisolone) yielded similar response rates in patients with advanced low grade NHL. Substituting bendamustine for cyclophosphamide in the CMF protocol (cyclophosphamide, methotrexate and fluorouracil) prolonged remission from 6.2 to 15.2 months in patients with metastatic breast cancer. The most common adverse events in patients receiving bendamustine are haematological events and gastrointestinal disturbances. Bendamustine has a relatively low propensity to induce alopecia.

Explore related subjects

Antineoplastic AgentsBendamustine HydrochlorideBreast NeoplasmsFemaleHalf-LifeHodgkin DiseaseHumansLymphoma, Non-HodgkinMetabolic Clearance RateNitrogen Mustard CompoundsJournal ArticleReview

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J A Balfour, K L Goa. 2001. Bendamustine.. https://doi.org/10.2165/00003495-200161050-00009

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2021

Deep generative neural network for accurate drug response imputation.

Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response.

Antineoplastic Agents↗
PubMed2002

Flavanols and procyanidins of cocoa and chocolate inhibit growth and polyamine biosynthesis of human colonic cancer cells.

The effects of cocoa powder and extracts with different amounts of flavanols and related procyanidin oligomers were investigated on the growth of Caco-2 cells. Treatment of the cells with 50 microg/ml of procyanidin-enriched (PE) extracts caused a 70% growth inhibition with a blockade of the cell cycle at the G2/M phase. PE extracts caused a significant decrease of ornithine decarboxylase and S-adenosylmethionine decarboxylase activities, two key enzymes of polyamine biosynthesis. This led to a decrease in the intracellular pool of the polyamines. These observations indicate that polyamine metabolism might be an important target in the anti-proliferative effects of cocoa polyphenols.

Antineoplastic Agents↗
PubMed2002

Selective cytotoxicity of betulinic acid on tumor cell lines, but not on normal cells.

Betulinic acid is a triterpene with selective cytotoxicity against melanoma, neuroectodermal and malignant brain tumor cell lines. In this study the betulinic acid activity was evaluated, in comparison with doxorubicin, on different human neoplastic and non-neoplastic cell lines and on proliferating normal lymphocytes. Growth inhibition was evident in all the neoplastic cell lines independently on p53 status and histotype. Antiproliferative activity of betulinic acid was related to a cytotoxic effect on two p53 wild-type and on one p53 mutant cell lines and to a cytostatic effect on one p53 mutant melanoma clone. At the same concentrations, normal cells were unaffected indicating a selective effect of this agent. A cytotoxic activity of doxorubicin was evident on all the tested systems. In vivo experiments, performed on one of these cell lines, confirmed the antineoplastic activity of this drug. These data support further preclinical studies of betulinic acid not confined to melanoma and neuroectodermal tumors independently of p53 status.

Antineoplastic Agents↗