Block sequential adriamycin CMF – optimal non-myeloablative chemotherapy for high risk adjuvant breast cancer?

After the publication of the 10-year survival data from Milan on the adjuvant use of the block sequential regimen consisting of four cycles of adriamycin followed by eight cycles of intravenous CMF, many centres adopted this as standard of care for high risk, multiple node-positive breast cancer. For this reason it was identified as the standard arm for the Anglo-Celtic adjuvant high-dose chemotherapy trial. This study reports on the experience of this regimen in 329 women with early breast cancer involving at least four axillary nodes, who were treated outside any adjuvant chemotherapy trial. At a median follow-up of 3 years, the overall 5-year disease-free survival is 61%, and the overall survival is 70%. These data confirm the efficacy of this regimen in non-trial patients, and, for the same high risk subgroup, indicate that this approach offers an outcome at least as good as that seen in the CALGB 9344 AC-Taxol arm, and the NCIC days 1 and 8 CEF

Computational Cancer Biology: An Evolutionary Perspective

ISSN:1553-734XISSN:1553-735

Cancer-selective, single agent chemoradiosensitising gold nanoparticles

Two nanometre gold nanoparticles (AuNPs), bearing sugar moieties and/or thiol-polyethylene glycol-amine (PEG-amine), were synthesised and evaluated for their in vitro toxicity and ability to radiosensitise cells with 220 kV and 6 MV X-rays, using four cell lines representing normal and cancerous skin and breast tissues. Acute 3 h exposure of cells to AuNPs, bearing PEG-amine only or a 50:50 ratio of alpha-galactose derivative and PEG-amine resulted in selective uptake and toxicity towards cancer cells at unprecedentedly low nanomolar concentrations. Chemotoxicity was prevented by co-administration of N-acetyl cysteine antioxidant, or partially prevented by the caspase inhibitor Z-VAD-FMK. In addition to their intrinsic cancer-selective chemotoxicity, these AuNPs acted as radiosensitisers in combination with 220 kV or 6 MV X-rays. The ability of AuNPs bearing simple ligands to act as cancer-selective chemoradiosensitisers at low concentrations is a novel discovery that holds great promise in developing low-cost cancer nanotherapeutics

Determinants of impact : towards a better understanding of encounters with the arts

The article argues that current methods for assessing the impact of the arts are largely based on a fragmented and incomplete understanding of the cognitive, psychological and socio-cultural dynamics that govern the aesthetic experience. It postulates that a better grasp of the interaction between the individual and the work of art is the necessary foundation for a genuine understanding of how the arts can affect people. Through a critique of philosophical and empirical attempts to capture the main features of the aesthetic encounter, the article draws attention to the gaps in our current understanding of the responses to art. It proposes a classification and exploration of the factors—social, cultural and psychological—that contribute to shaping the aesthetic experience, thus determining the possibility of impact. The ‘determinants of impact’ identified are distinguished into three groups: those that are inherent to the individual who interacts with the artwork; those that are inherent to the artwork; and ‘environmental factors’, which are extrinsic to both the individual and the artwork. The article concludes that any meaningful attempt to assess the impact of the arts would need to take these ‘determinants of impact’ into account, in order to capture the multidimensional and subjective nature of the aesthetic experience

Optimizing Combination Therapies with Existing and Future CML Drugs

Small-molecule inhibitors imatinib, dasatinib and nilotinib have been developed to treat Chromic Myeloid Leukemia (CML). The existence of a triple-cross-resistant mutation, T315I, has been a challenging problem, which can be overcome by finding new inhibitors. Many new compounds active against T315I mutants are now at different stages of development. In this paper we develop an algorithm which can weigh different combination treatment protocols according to their cross-resistance properties, and find the protocols with the highest probability of treatment success. This algorithm also takes into account drug toxicity by minimizing the number of drugs used, and their concentration. Although our methodology is based on a stochastic model of CML microevolution, the algorithm itself does not require measurements of any parameters (such as mutation rates, or division/death rates of cells), and can be used by medical professionals without a mathematical background. For illustration, we apply this algorithm to the mutation data obtained in [1], [2]

An integrated analysis of molecular aberrations in NCI-60 cell lines

<p>Abstract</p> <p>Background</p> <p>Cancer is a complex disease where various types of molecular aberrations drive the development and progression of malignancies. Large-scale screenings of multiple types of molecular aberrations (e.g., mutations, copy number variations, DNA methylations, gene expressions) become increasingly important in the prognosis and study of cancer. Consequently, a computational model integrating multiple types of information is essential for the analysis of the comprehensive data.</p> <p>Results</p> <p>We propose an integrated modeling framework to identify the statistical and putative causal relations of various molecular aberrations and gene expressions in cancer. To reduce spurious associations among the massive number of probed features, we sequentially applied three layers of logistic regression models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions. Layer 1 models associate gene expressions with the molecular aberrations on the same loci. Layer 2 models associate expressions with the aberrations on different loci but have known mechanistic links. Layer 3 models associate expressions with nonlocal aberrations which have unknown mechanistic links. We applied the layered models to the integrated datasets of NCI-60 cancer cell lines and validated the results with large-scale statistical analysis. Furthermore, we discovered/reaffirmed the following prominent links: (1)Protein expressions are generally consistent with mRNA expressions. (2)Several gene expressions are modulated by composite local aberrations. For instance, CDKN2A expressions are repressed by either frame-shift mutations or DNA methylations. (3)Amplification of chromosome 6q in leukemia elevates the expression of MYB, and the downstream targets of MYB on other chromosomes are up-regulated accordingly. (4)Amplification of chromosome 3p and hypo-methylation of PAX3 together elevate MITF expression in melanoma, which up-regulates the downstream targets of MITF. (5)Mutations of TP53 are negatively associated with its direct target genes.</p> <p>Conclusions</p> <p>The analysis results on NCI-60 data justify the utility of the layered models for the incoming flow of cancer genomic data. Experimental validations on selected prominent links and application of the layered modeling framework to other integrated datasets will be carried out subsequently.</p

Self-adjuvanting polymer-peptide conjugates as therapeutic vaccine candidates against cervical cancer

Dendrimers are structurally well-defined, synthetic polymers with sizes and physicochemical properties often resembling those of biomacromolecules (e.g. proteins). As a result they are promising candidates for peptide-based vaccine delivery platforms. Herein, we established a synthetic pathway to conjugate a human papillomavirus (HPV) E7 protein-derived peptide antigen to a star-polymer to create a macromolecular vaccine candidate to treat HPV-related cancers. These conjugates were able to reduce tumor growth and eradicate E7-expressing TC-1 tumors in mice after a single immunization, without the help of any external adjuvant

Breast cancer response to neoadjuvant chemotherapy: predictive markers and relation with outcome

The aim of this study was to provide a better insight into breast cancer response to chemotherapy. Chemotherapy improves outcome in breast cancer patients. The effect of cytotoxic treatment cannot be predicted for individual patients. Therefore, the identification of tumour characteristics associated with tumour response and outcome is of great clinical interest. We studied 97 patients, who received anthracycline-based neoadjuvant chemotherapy. Tumour samples were taken prior to and after chemotherapy. We quantified the response to chemotherapy clinically and pathologically and determined histological and molecular tumour characteristics. We assessed changes in the expression of Bcl-2, ER, P53 HER2 and Ki-67. Association with response and outcome was tested for all parameters. The experimental results showed 15 clinical (17%) and three (3%) pathological complete remissions. There were 18 (20%) clinical vs 29 (33%) pathological nonresponders. The expression of most markers was similar before and after chemotherapy. Only Ki-67 was significantly decreased after chemotherapy. Factors correlated with response were: large tumour size, ER negativity, high Ki-67 count and positive P53 status. Tumour response and marker expression did not predict disease-free or overall survival. In conclusion, clinical and pathological response assessments are poorly associated. Proliferation decreases significantly after chemotherapy. ER negativity and a high proliferation index are associated with better response. HER2 status does not predict response, and outcome is not related to tumour response