About the Project
In order to identify new candidate cancer-related genes, our lab developed a bioinformatics “guilt-by-association” method to identify and rank genes that are co-expressed with known cancer-related genes. Using this method, we identified C1ORF112, an unstudied gene which we found to be strongly co-expressed with many cancer-related genes, including RAD51, BRCA1 and BRCA2, and with genes involved in DNA repair and cell cycle regulation. We also showed that siRNA knock-down of C1ORF112 in HeLa cells significantly decreases cell growth. Microarray data shows that C1ORF112 is overexpressed in various cancers when compared to normal tissues and that C1ORF112 has high levels of expression in several tumours, and markedly in breast cancer. A gain in copy number in C1ORF112 has been observed in some types of cancer and most significantly in breast cancer. Therefore, we aim to further explore C1ORF112 as a drug target in the context of oncology.
In this project, we aim to evaluate further the role of C1ORF112 in cell proliferation and begin to unravel its functions. Based on its co-expression patterns, we hypothesize that C1ORF112 is related to cell cycle regulation under DNA damage, a hypothesis we will test by studying how disrupting C1ORF112 affects cell cycle progression and levels of DNA damage with and without exposure to genotoxic stress. In addition, we aim to study the C1ORF112 protein in human benign and malignant breast tumours as well as determine if C1ORF112 is correlated with patient outcome. Lastly, we have generated a C1ORF112 conditional knockout mouse to allow further studies. The exact direction of this project and methods to be used, however, will be adapted to fit the research interests and background of the student.
This project’s successful outcome can culminate in the development of new and improved techniques for diagnostic and treatment of cancer, and for breast cancer in particular.
Training associated with this project:
This project will provide a rich and diverse training in contemporary cell and molecular biology techniques, genomics and biogerontology. Specifically, the student will be trained in cell and molecular biology techniques such as mammalian cell culture, qRT-PCR, RNAi and molecular cloning. The student will also obtain training in modern methods in genomics, including in the generation and analysis of high-throughput transcriptional data from next-generation sequencing platforms.
In addition to the generic skills training that is provided through the Institute and University PhD programme, the student will be supported by an excellent infrastructure and will work closely with experts on the biology and genetics of ageing, cell biology, stress response mechanisms and genomics. This diverse and stimulating environment will allow a creative and talented student to develop key skills and the project is flexible enough to allow the student to develop his or her own research interests. The student will be well-prepared for a successful career in research and in biotechnology.
The Institute of Ageing and Chronic Disease is fully committed to promoting gender equality in all activities. In recruitment we emphasize the supportive nature of the working environment and the flexible family support that the University provides. The Institute holds a silver Athena SWAN award in recognition of on-going commitment to ensuring that the Athena SWAN principles are embedded in its activities and strategic initiatives.
Potential applicants are encouraged to contact Professor de Magalhaes (firstname.lastname@example.org) in the first instance for an informal discussion.
To apply: please send your CV and a covering letter to email@example.com with a copy to firstname.lastname@example.org
The successful candidate should have an Honours Degree at 2.1 or above (or equivalent). Candidates whose first language is not English should have an IELTS score of 6.5 or equivalent.
Doherty A, Kernogitski Y, Kulminski AM, de Magalhães JP (2017) “Identification of polymorphisms in cancer patients that differentially affect survival with age.” AGING 9:2117-2136.
Fernandes M, Wan C, Tacutu R, Barardo D, Rajput A, Wang J, Thoppil H, Thornton D, Yang C, Freitas A, de Magalhães JP (2016) “Systematic analysis of the gerontome reveals links between aging and age-related diseases.” Human Molecular Genetics 25:4804-4818.
de Magalhães JP (2013) "How ageing processes influence cancer." Nature Reviews Cancer 13:357-365.
van Dam S et al. (2012) “GeneFriends: An online co-expression analysis tool to identify novel gene targets for aging and complex diseases.” BMC Genomics 13:535.
Further details about our work on aging and age-related diseases are available at:
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