Darwinian Strategies to Avoid the Evolution of Drug Resistance During Cancer Treatment

2016 ◽  
pp. 167-175 ◽  
Author(s):  
John W. Pepper
Keyword(s):  
Drug Resistance ◽  
Cancer Treatment

Response to Ni et al.: The possible use of hypericin to overcome drug resistance in cancer treatment

2011 ◽  
Vol 190 (2-3) ◽  
pp. 190
Author(s):  
Ozlem Dalmizrak ◽  
Gulnihal Kulaksiz-Erkmen ◽  
Nazmi Ozer
Keyword(s):  
Drug Resistance ◽  
Cancer Treatment

Neural regulation of drug resistance in cancer treatment

2019 ◽  
Vol 1871 (1) ◽  
pp. 20-28 ◽  
Author(s):  
Dan Liu ◽  
Xiaoxi Li ◽  
Xintian Chen ◽  
Yu Sun ◽  
Anqun Tang ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Cancer Treatment ◽  
Neural Regulation

scholarly journals Platinum Complexes And Their Anti-Tumour Activity Against Chronic Lymphocytic Leukaemia Cells

2015 ◽  
Vol 16 (3) ◽  
pp. 181-186
Author(s):  
Žana Besser Silconi ◽  
Sasa Benazic ◽  
Jelena Milovanovic ◽  
Aleksandar Arsenijevic ◽  
Bojana Stojanovic ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Side Effects ◽  
Chronic Lymphocytic Leukaemia ◽  
Cancer Treatment ◽  
Lymphocytic Leukaemia ◽  
Clinical Stage ◽  
Phenotypic Expression ◽  
Platinum Complexes ◽  
Cancer Drug ◽  
Staging Systems

Abstract Since the discovery of the antitumor activity of cisplatin by Rosenberg and co-workers, the use of metal complexes in cancer treatment has caused a huge interest. Today, platinum-based drugs are part of standard chemotherapy in the management of a variety of ca ncers, germ cell tumours, sarcomas, and lymphomas. Unfortunately, toxicity and drug resistance are major obstacles to wider clinical application of these drugs. Their use is greatly limited by severe side effects such as nephrotoxicity, ototoxicity, and neurotoxicity. Although cisplatin is one of the most successful anticancer drugs to date, its biochemical mechanism of action is still unclear. Cisplatin is generally accepted as having the ability to interact with the purine bases on the DNA, causing DNA damage, interfering with DNA repair mechanisms, and subsequently inducing apoptosis in cancer cells. Chronic lymphocytic leukaemia is a neoplastic B cell lymphoproliferative disease characterized by a highly variable clinical course. Clinical stage at the diagnosis and biological prognostic factors are the important predictors for survival. The Rai and Binet staging systems describe three major prognostic subgroups. Commonly used prognostic biomarkers in chronic lymphocytic leukaemia can be divided into genotypic, DNA-level changes and phenotypic, expression-level changes. For chronic lymphocytic leukaemia, substantial progress in therapy has not been made over the past 40 years. The main goal of future scientific research is to find new platinum complexes that have better efficacy in cancer treatment, the ability to be administered orally, without developing a cancer-drug resistance, and reduced toxic side effects.

scholarly journals Challenging Drug Resistance in Cancer Therapy: Review of the First Nordic Conference on Chemoresistance in Cancer Treatment, October 9th and 10th, 1997

1998 ◽  
Vol 37 (5) ◽  
pp. 431-439 ◽  
Author(s):  
Gustav Lehne ◽  
Erkki Elonen ◽  
Mark Baekelandt ◽  
Torben Skovsgaard ◽  
Curt Peterson
Keyword(s):  
Drug Resistance ◽  
Cancer Therapy ◽  
Cancer Treatment

A novel method to assay molecular chaperone activity of HSP70: Evaluation of drug resistance in cancer treatment

2013 ◽  
Vol 47 ◽  
pp. 75-79 ◽  
Author(s):  
Xiaorong Ding ◽  
Hao Li ◽  
Haona Xie ◽  
Yue Huang ◽  
Yafei Hou ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Cancer Treatment ◽  
Molecular Chaperone ◽  
Chaperone Activity ◽  
Novel Method

scholarly journals MicroRNA-587 antagonizes 5-FU-induced apoptosis and confers drug resistance by regulating PPP2R1B expression in colorectal cancer

2015 ◽  
Vol 6 (8) ◽  
pp. e1845-e1845 ◽  
Author(s):  
Y Zhang ◽  
G Talmon ◽  
J Wang
Keyword(s):  
Colorectal Cancer ◽  
Drug Resistance ◽  
Cancer Treatment ◽  
Xenograft Model ◽  
Akt Inhibitor ◽  
Akt Phosphorylation ◽  
Xiap Expression ◽  
Mouse Xenograft Model ◽  
Response To Chemotherapy ◽  
Induced Apoptosis

Abstract Drug resistance is one of the major hurdles for cancer treatment. However, the underlying mechanisms are still largely unknown and therapeutic options remain limited. In this study, we show that microRNA (miR)-587 confers resistance to 5-fluorouracil (5-FU)-induced apoptosis in vitro and reduces the potency of 5-FU in the inhibition of tumor growth in a mouse xenograft model in vivo. Further studies indicate that miR-587 modulates drug resistance through downregulation of expression of PPP2R1B, a regulatory subunit of the PP2A complex, which negatively regulates AKT activation. Knockdown of PPP2R1B expression increases AKT phosphorylation, which leads to elevated XIAP expression and enhanced 5-FU resistance; whereas rescue of PPP2R1B expression in miR-587-expressing cells decreases AKT phosphorylation/XIAP expression, re-sensitizing colon cancer cells to 5-FU-induced apoptosis. Moreover, a specific and potent AKT inhibitor, MK2206, reverses miR-587-conferred 5-FU resistance. Importantly, studies of colorectal cancer specimens indicate that the expression of miR-587 and PPP2R1B positively and inversely correlates with chemoresistance, respectively, in colorectal cancer. These findings indicate that the miR-587/PPP2R1B/pAKT/XIAP signaling axis has an important role in mediating response to chemotherapy in colorectal cancer. A major implication of our study is that inhibition of miR-587 or restoration of PPP2R1B expression may have significant therapeutic potential to overcome drug resistance in colorectal cancer patients and that the combined use of an AKT inhibitor with 5-FU may increase efficacy in colorectal cancer treatment.

scholarly journals Mouse xenograft models for elucidating drug resistance mechanisms

2015 ◽  
Author(s):  
Wenfa Ng
Keyword(s):  
Drug Resistance ◽  
Drug Treatment ◽  
Cancer Treatment ◽  
Primary Tumour ◽  
Drug Regimen ◽  
Resistance Mechanisms ◽  
Fine Tuning ◽  
Blood Biomarkers ◽  
Levels Of Abstraction ◽  
Xenograft Models

Divergence of treatment responses to chemotherapy exists across patients (often with underlying mechanisms unknown), with some patients exhibiting worsened outcome upon treatment. Genomic approaches (such as microarray profiling and whole-genome sequencing) hold promise for transforming cancer treatment, particularly, in tailoring drug regimen to specific patients. Nevertheless, formulating effective personalized treatment via surveying the mutational landscape remains difficult, due to current deficiencies in predicting drug sensitivity from genotype. Xenografts, both indirect (via cell line) and direct (from primary tumours), are good physiologic models of cancers. Their utility in informing cancer treatment, however, is constrained by high cost of generating and maintaining genetically modified animals, and the paucity of tissue samples from biopsies. Advent of high throughput biomolecular profiling tools finally enables reading out the expansive molecular fingerprints that encode observed phenotypes in xenografts. Using pheochromocytoma (an adrenal medulla cancer) as example, this short essay provides a broad overview of the scientific and clinical possibilities offered by xenograft models for understanding resistance mechanisms to particular chemotherapeutic regimens, and upon identification of the putative mutations, confirms their functional roles as either oncogenes or tumour suppressors. Additionally, workflow involved in generating a predictive platform, based on non-invasive blood biomarkers, for informing drug treatment options is discussed. Known as an integrated genomic classifier, combination of physiological response of direct xenografts to drug treatment and bioinformatics-enabled correlation of blood biomarkers to observed phenotype at cellular and animal levels, provides the biological basis for predicting patients’ prognosis without invasive biopsy of solid tumours. Elucidation of drug resistance mechanisms entails: (i) recapitulating in vivo tumour behavior using cell lines derived from primary tumour; (ii) identification of aetiological mutations and longitudinal profiling of phenotypic response; and (iii) validation of mutations and phenotype via both knockout mice and direct allogenic xenografts. Biological models seek to recapitulate human physiology at specific levels of abstraction for answering particular questions, but incongruence in phenotype is inevitable. Nevertheless, xenografts (especially those derived from patients, PDTX), are powerful tools for addressing basic science, clinical and treatment-related questions using close functional replicas of patient physiology in an animal model. Residual incompatibility between model and patient response would require the expertise and clinical experience of oncologists for fine-tuning model suggested drug regimen to particular patients.

scholarly journals Mathematical Approach to Differentiate Spontaneous and Induced Evolution to Drug Resistance During Cancer Treatment

2019 ◽  
pp. 1-20 ◽  
Author(s):  
James M. Greene ◽  
Jana L. Gevertz ◽  
Eduardo D. Sontag
Keyword(s):  
Drug Resistance ◽  
Cancer Treatment ◽  
Treatment Resistance ◽  
Drug Dose ◽  
Modeling Framework ◽  
Drug Induced ◽  
Treatment Protocols ◽  
Genetic Changes ◽  
Induce Resistance

Purpose Drug resistance is a major impediment to the success of cancer treatment. Resistance is typically thought to arise from random genetic mutations, after which mutated cells expand via Darwinian selection. However, recent experimental evidence suggests that progression to drug resistance need not occur randomly, but instead may be induced by the treatment itself via either genetic changes or epigenetic alterations. This relatively novel notion of resistance complicates the already challenging task of designing effective treatment protocols. Materials and Methods To better understand resistance, we have developed a mathematical modeling framework that incorporates both spontaneous and drug-induced resistance. Results Our model demonstrates that the ability of a drug to induce resistance can result in qualitatively different responses to the same drug dose and delivery schedule. We have also proven that the induction parameter in our model is theoretically identifiable and propose an in vitro protocol that could be used to determine a treatment’s propensity to induce resistance.

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