Conflicting objectives in chemotherapy with drug resistance

Optimum multi-drug regime for compartment model of tumour: cell-cycle-specific dynamics in the presence of resistance

This work is focused on multi-objective optimisation of a multi-drug chemotherapy schedule for cell-cycle-specific cancer treatment under the influence of drug resistance. The acquired drug resistance to chemotherapeutic agents is incorporated into the existing compartmental model of breast cancer. Furthermore, the toxic effect of drugs on healthy cells and overall drug concentration in the patient body are also constrained in the proposed model. The objective is to determine the optimal drug schedule according to the patient's physiological condition so that the tumour burden is minimised. A multi-objective optimisation algorithm, non-dominated sorting genetic algorithm-II (NSGA-II) is utilised to solve the problem. The obtained results are thoroughly analysed to illustrate the impact of drug resistance on the treatment. The capability of optimised schedules to deal with parametric uncertainty is also analysed. The drug schedules obtained in this work align well with the clinical standards. It is also revealed that the NSGA-II optimised drug schedule with proper rest period between successive dosages yields the minimum cancer load at the end of the treatment.

A new conceptual framework for the therapy by optimized multidimensional pulses of therapeutic activity. The case of multiple myeloma model

We developed simulation methodology to assess eventual therapeutic efficiency of exogenous multiparametric changes in a four-component cellular system described by the system of ordinary differential equations. The method is numerically implemented to simulate the temporal behavior of a cellular system of multiple myeloma cells. The problem is conceived as an inverse optimization task where the alternative temporal changes of selected parameters of the ordinary differential equations represent candidate solutions and the objective function quantifies the goals of the therapy. The system under study consists of two main cellular components, tumor cells and their cellular environment, respectively. The subset of model parameters closely related to the environment is substituted by exogenous time dependencies - therapeutic pulses combining continuous functions and discrete parameters subordinated thereafter to the optimization. Synergistic interaction of temporal parametric changes has been observed and quantified whereby two or more dynamic parameters show effects that absent if either parameter is stimulated alone. We expect that the theoretical insight into unstable tumor growth provided by the sensitivity and optimization studies could, eventually, help in designing combination therapies.

How to Use a Chemotherapeutic Agent When Resistance to It Threatens the Patient

When resistance to anticancer or antimicrobial drugs evolves in a patient, highly effective chemotherapy can fail, threatening patient health and lifespan. Standard practice is to treat aggressively, effectively eliminating drug-sensitive target cells as quickly as possible. This prevents sensitive cells from acquiring resistance de novo but also eliminates populations that can competitively suppress resistant populations. Here we analyse that evolutionary trade-off and consider recent suggestions that treatment regimens aimed at containing rather than eliminating tumours or infections might more effectively delay the emergence of resistance. Our general mathematical analysis shows that there are situations in which regimens aimed at containment will outperform standard practice even if there is no fitness cost of resistance, and, in those cases, the time to treatment failure can be more than doubled. But, there are also situations in which containment will make a bad prognosis worse. Our analysis identifies thresholds that define these situations and thus can guide treatment decisions. The analysis also suggests a variety of interventions that could be used in conjunction with cytotoxic drugs to inhibit the emergence of resistance. Fundamental principles determine, across a wide range of disease settings, the circumstances under which standard practice best delays resistance emergence-and when it can be bettered.

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation

BACKGROUND

Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level.

SCOPE OF REVIEW

We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies.

MAJOR CONCLUSIONS

Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies.

GENERAL SIGNIFICANCE

Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Growth inhibitory and chemo-sensitization effects of naringenin, a natural flavanone purified from Thymus vulgaris, on human breast and colorectal cancer

BACKGROUND

Natural products with diverse bioactivities are becoming an important source of novel agents with medicinal potential. Cancer is a devastating disease that causes the death of millions of people each year. Thus, intense research has been conducted on several natural products to develop novel anticancer drugs.

METHODS

Chromatographic and spectral techniques were used for the isolation and identification of naringenin (Nar). MTT, flow cytometry, western blotting, Real Time PCR were used to test anticancer and chemosensitizing effects of Nar, cell cycle, apoptosis, and expression of cell cycle, apoptosis, pro-survival and anti-survival-related genes.

RESULTS

In the present study, Thymus vulgaris ethanol extract was purified repeatedly to produce several compounds including the known flavanone, Nar which was identified using different spectral techniques. Nar was shown to inhibit both human colorectal and breast cancer cell growth in a dose- and time-dependent manner through cell cycle arrest at S- and G2/M-phases accompanied by an increase in apoptotic cell death. Additionally, Nar altered the expression of apoptosis and cell-cycle regulatory genes by down-regulating Cdk4, Cdk6, Cdk7, Bcl2, x-IAP and c-IAP-2 and up-regulating p18, p19, p21, caspases 3, 7, 8 and 9, Bak, AIF and Bax in both colorectal and breast cancer cells. Conversely, it diminished the expression levels of the cell survival factors PI3K, pAkt, pIκBα and NFκBp65. Moreover, Nar enhanced the sensitivity of colorectal and breast cancer cells to DNA-acting drugs.

DISCUSSION

These findings provide evidence that Nar's pro-apoptotic and chemo-sensitizing effects are mediated by perturbation of cell cycle, upregulation of pro-apoptotic genes and down-regulation of anti-apoptotic genes and inhibition of pro-survival signaling pathways.

CONCLUSION

In conclusion, Nar might be a promising candidate for chemoprevention and/or chemotherapy of human cancers. However, further studies exploring this therapeutic strategy are necessary.

Spatholobus suberectus inhibits cancer cell growth by inducing apoptosis and arresting cell cycle at G2/M checkpoint

AIM OF THE STUDY

Although herbs have long been alternatively applied for cancer treatment in China, its treatment effects and their potential mechanisms have not been sufficiently investigated. The chinese herb Spatholobus suberectus (SS) is commonly prescribed to cancer patients. In this study, the anti-cancer effect of SS and its molecular mechanisms have been investigated.

MATERIALS AND METHODS

The effect of SS on cell proliferation was studied by cell growth assay and flow cytometry on breast cancer cell lines MCF-7 and colon cancer cell line HT-29. The role of SS in apoptosis was studied by flow cytometry, DNA fragmentation assay and mitochondrial membrane potential assay. Expression of proteins associated with cell cycle and apoptosis was determined by Western blot analysis. The in vivo effect of SS was tested in nude mouse cancer xenografts.

RESULTS

Cell growth assay showed that SS effectively inhibits tumor cell growth in a dose-dependent manner. Flow cytometry analysis showed that SS could arrest the cell cycle at G2/M checkpoint, which is associated with DNA damage and activation of phosphor-Chk1/Chk2. The pro-apoptotic effect of SS was demonstrated by Annexin V-PI staining and mitochondrial membrane potential assay. In vivo experiments show that the efficiency of SS alone group was superior to docetaxel or to docetaxel and SS combined. No obvious body weight loss or blood toxicity was observed in SS tested animals.

CONCLUSIONS

Our data demonstrates that SS is a potential herb for cancer treatment by inhibiting tumor growth via induction of apoptosis and arrest of the cell cycle at G2/M phase.