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Cancer Biology - Articles and news items
Webinars / 6 January 2016 /
This webinar will present real-world methods and examples of how to monitor and assess DNA damage in these cells using the Comet Assay and an insight into the software used to carry out this analysis – Komet…
In this free-to-view in-depth focus: Mesenchymal stem cells in cancer therapy – our chance to take charge, and Ovarian cancer stem cells – an essential target for durable remission…
The mammalian target of rapamycin (mTOR) has emerged as a promising cancer therapeutic target. Some rapamycin analogues (rapalogues) as mTOR allosteric inhibitors are FDA-approved drugs for treatment of certain types of cancers. However, the modest clinical anticancer activity of rapalogues, which preferentially inhibit mTOR complex 1, in most types of cancer, has spurred the development of ATP competitive mTOR kinase inhibitors (TORKinibs) that inhibit both mTOR complex 1 and complex 2, in the hope of developing a novel generation of mTOR inhibitors with better therapeutic efficacy than rapalogues. So far, several TORKinibs have been developed and some are under clinical testing. With a strong rationale, we expect great success in the treatment of cancer with TORKinibs.
There is an urgent need to predict which treatment will report the most benefit to a patient with cancer. To that end, scientists are exploring any possible biomolecule in the organism that can mark each individual for its adequate treatment. If achieved, it will open a personalised medicine era.
Early stage data on investigational anti-PDL1 immunotherapy…
The HOX genes are a family of closely related transcription factors that help to define the identity of cells and tissues during embryonic development and which are also frequently deregulated in cancer, where they have been shown to promote cell survival and proliferation. The high level of cancer-associated HOX expression and the pro-oncogenic functions of these genes make them strong candidates for biomarkers in multiple roles including diagnosis, prognosis, drug sensitivity and drug resistance. The HOX genes are a family of homeodomaincontaining transcription factors that were first identified as determinates of cell and tissue identity in early development, although they are now also known to function in adult stem cell renewal and differentiation. A series of duplication events is thought to have given rise to the four separate clusters of HOX genes found in vertebrates, with each cluster consisting of a group of closely linked members that often share enhancer regions. These clusters are named A, B, C and D, and together they contain the 39 HOX genes found in mammals. Each gene within a cluster is labelled with a number according to their relative position in the chromosome, so for example HOXB1 is the 3’ most member of the B cluster, and HOXB13 is the 5’ most member. The linkage of genes within each cluster is closely reflected in both their temporal and spatial order of expression in the embryo, with the 3’ genes being expressed more anteriorly and earlier than their 5’ neighbours. The relative position within the cluster is also reflected in the co-factor interactions, DNA binding specificity and regulation of each member.
Issue 1 2011, Proteomics / 16 February 2011 / Hubert Hondermarck, Professor and head of U908 INSERM research unit – Growth factor signalling in breast cancer – functional proteomics, University of Lille
The recent progresses in the field of proteomics now enable large scale, high throughput, sensitive and quantitative protein analysis. Therefore, applying proteomics in clinical oncology becomes realistic. From the analysis of cell cultures to biological fluids and tumour biopsies, proteomic investigations of cancers are flourishing and new candidate biomarkers and therapeutic targets are slowly emerging. In the meantime, what we know of the cancer proteome is also an evolving figure that is progressively unveiled. Given the multiparametric nature and diversity of cancers, it should not be underestimated that a great deal of time and effort will be necessary for translating that knowledge into practical applications in oncology.
The rate of progress in molecular cell biological sciences has become dramatic. This is fuelled in part by developments in technology, none more so than in the field of nucleic acid sequencing. So-called Next Generation Sequencing Platforms promise to revolutionise our understanding of the importance of genetic differences on an individual basis. According to the modern personalised or stratified medicine paradigms, this will revolutionise current practices in terms of early detection, treatment, diagnosis, prognosis and even prevention. Revolutions are apt to disappoint and drug pipelines have yet to justify such optimism yet molecular geneticists can point already to notable successes like the completion of their flagship project, the human genome in 2001, within time and within budget. What are the current realities? The field of cancer serves as an excellent test and would suggest that advances are being made incrementally but rapidly.
The delivery of personalised medicine is a key goal of modern cancer medicine and refers to the tailoring of anticancer therapy to the molecular characteristics of an individual tumour. To facilitate personalised medicine, it is important to have robust and reproducible means of gaining molecular information about a patient’s cancer that can be used to guide clinical decision-making. There have therefore been tremendous efforts to identify molecular signatures – biomarkers – that can be used to help predict a cancer patient’s prognosis or their likelihood of a response to targeted drug therapies. Such molecular profiling has long been applied to haematological malignancies and is increasingly becoming the norm in the most common epithelial cancers such as lung and colorectal cancer. This article will focus on the role of the polymerase chain reaction (PCR) in helping to meet the challenges involved in the design, testing and delivery of personalised cancer medicine.
Flow cytometry can be used to advance our understanding of diseases in multiple ways. Drug effects and dosages can be ascertained in vitro, along with patient selection based on mutations and antigen profiles. Within the Diagnostic Biomarkers group of Translational Research at Pfizer, we are utilising flow cytometry in conjunction with other diagnostic tools to assist in gaining a clearer understanding of drug target biology and to identify patients that would benefit most from a specified drug regimen.
Despite innumerable clinical studies in the past three decades with lots of traditional chemotherapeutical drugs and drug combinations, survival in lung cancer has increased by far less than other entities. Research now focuses on inhibitors of tyrosine kinases which have been shown to have a central role in the development of lung cancer. However, as recent developments show, unselected use of those ‘targeted therapies’ is not always effective and may even be harmful to lung cancer patients if given at the wrong time or to the wrong patient. Biomarkers with predictive value will, in future, be of utmost importance for an individualised tumour tailored therapy. In this perspective, we describe the latest developments in EGF-R directed tyrosine kinase inhibitors and other targeted therapies. Additionally, the actual (limited) predictive role of biomarkers is discussed in this context and further directions are pinpointed.
Improved understanding of the molecular alterations in cancer cells has fuelled the development of more specific and directed cancer therapies. However, it has become clear that response rates can be low due to confounding genetic alterations that render these highly specific therapies ineffective. As a result, the costs of cancer treatment will increase enormously unless we are able to identify those patients that will benefit most from these directed therapies. In addition, it will be necessary to identify additional targets in these complex molecular networks that can be further exploited to increase overall response rates in the highly heterogenic populations of human tumours. In recent years, great expectations have been put forward for the use of functional genomic screening technologies to reach these goals.
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