Development of a multi-gene detection model for Chinese Luminal-type early breast cancer and its clinical translational study on the predictive value of breast cancer recurrence risk

Supervisors

Principal supervisor: Professor/Dr Jia Meng  (XJTLU)

Co-supervisor: Professor/Dr Xinghong Luo (JITRI)

Co-supervisor: Professor/Dr Chris Sanderson (UoL)

Project Description:

Breast cancer is the most common malignant tumor in women, and it is also one of the important reasons that threaten the health of the whole country. Optimizing the decision-making of adjuvant treatment after early breast cancer surgery is one of the important parts of tumor precision medicine, which can avoid unnecessary chemotherapy for patients with low-risk breast cancer, and reduce the physical and mental pressure of patients and the socio-economic burden. At present, Western countries have multi-gene testing products used to predict the risk of distant metastasis in breast cancer patients; low-risk patients can be exempted from adjuvant chemotherapy and only require endocrine therapy. However, statistics found that there are significant ethnic differences in breast cancer disease manifestations. In terms of stage I breast cancer, the risk of death among Asians is 0.6 times that of whites. There is uncertainty about whether polygenic predictions derived from the West are applicable. my country is currently in an environment where medical resources are sinking, serious illnesses do not come out of counties and cities, policy-oriented, and medical institutions have uneven diagnosis and treatment levels. Routine adjuvant treatment of early breast cancer is often completed in countylevel and city-level hospitals, over-treatment or under-treatment. Coexist, and our country has a large population base. Therefore, the social and economic benefits of clinical research that optimizes the decision-making for postoperative adjuvant treatment of early breast cancer in my country should not be underestimated. This project aims to develop a genomic model for breast cancer postoperative adjuvant treatment decision-making based on Chinese data, and analyze the impact of the model on the prediction of postoperative recurrence risk of early (I-II) Luminal breast cancer population in mainland China, aiming to further optimize The decision-making of postoperative adjuvant treatment for early-stage Luminal-type female breast cancer patients in China, avoiding over-treatment or under-treatment, not only promotes cross-strait scientific and technological exchanges and cooperation, but is also expected to break the market monopoly of Western countries in this field (Oncotype DX 21-Gene Testing must be sent to the United States for testing) to benefit the people of the country.

For more information about doctoral scholarship and PhD programme at Xi’an Jiaotong-Liverpool University (XJTLU): Please visit:

http://www.xjtlu.edu.cn/en/study-with-us/admissions/entry-requirements

http://www.xjtlu.edu.cn/en/admissions/phd/feesscholarships.html

Supervisor Profile:

Principal Supervisor:

Jia Meng received his bachelor degree in Electrical Engineering from Northwestern Polytechnic University in 2006, and earned his PhD in Electrical Engineering from University of Texas at San Antonio in 2011. He joined Massachusetts Institute of Technology in Feb 2012 as a Bioinformatician and the Supervisor of Bioinformatics Core Facility at Picower Institute for Learning and Memory. Between 2012 and 2014, he served as an Associate Scientist at Broad Institute of MIT and Harvard. He is now an Associate Professor at Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, and has an honorary appointment from Institute of Integrative Biology, University of Liverpool. Jia Meng has previously worked on a wide variety of computational biology projects that aim at a system level understanding of gene regulation and the integration of multiple high-throughput data types and databases with advanced multivariate techniques, such as, Bayesian generative modelling, sparse representation, factorization, nonparametric approaches, etc. He has authored or co-authored more than 100 peer-reviewed publications and is now focusing primarily on epitranscriptome bioinformatics.

JITRI co-supervisor:

Dr. Luo Xinghong, Doctor of Chinese Medicine, Chief Chinese Pharmacist, Adjunct Professor of Hainan Medical College, Distinguished Professor of Nanjing University of Traditional Chinese Medicine, and Adjunct Professor of Chengdu University of Traditional Chinese Medicine. From 1998 to 2000, he was engaged in new drug research at Sichuan Institute of Traditional Chinese Medicine. In 2000, he joined Simcere Pharmaceutical Co., Ltd. and successively served as production manager, quality management manager, new product development manager, company deputy general manager, and president office. Director, General Manager of the Policy Affairs Department and other positions. Since 2018, he has served as the Deputy Director of the Institute of Translational Medicine and Innovative Drug Technology. He has presided over or participated in the research and development of more than ten new drugs including Class I and Class II new drugs, and obtained 7 authorized invention patents. Won 2 first prizes of Provincial Science and Technology Progress, 1 second prize of National Science and Technology Progress, 1 China Patent Excellence Award, published more than 40 academic papers, edited and published more than 30 academic monographs.

Requirements:

The candidate should have a first class or upper second class honours degree, or a master’s degree (or equivalent qualification) in relevant discipline, such as, bioinformatics, biology, applied mathematics, computer science, data science, etc.

Evidence of good spoken and written English is essential. The candidate should have an IELTS score of 6.5 or above, if the first language is not English. This position is open to all qualified candidates irrespective of nationality.

Degree: 

The student will be awarded a PhD degree from the University of Liverpool (UK) upon successful completion of the program.

How to Apply:

Interested applicants are advised to email [Email Address Removed] (XJTLU principal supervisor’s email address) or [Email Address Removed] the following documents for initial review and assessment (please put the project title in the subject line).

• CV
• Two reference letters with company/university letterhead
• Personal statement outlining your interest in the position
• Proof of English language proficiency (an IELTS score of 6.5 or above)
• Verified school transcripts in both Chinese and English (for international students, only the English version is required)
• Verified certificates of education qualifications in both Chinese and English (for international students, only the English version is required) 
• PDF copy of Master Degree dissertation (or an equivalent writing sample) and examiners reports available