CGCC

Program Description

The value of molecular subtype for colorectal cancer in the aspect of disease diagnosis as well as prognostic prediction is still controversial. Therefore, we will assess the combination of multiple-omics, and developed a new individualized signature. Then further validation based on our massively parallel sequencing in 2,000 CRC samples will be carried out in order to evaluate its clinical utility. This constructed signature may uncover the specific molecular sub-type of CRC based on the population of China. Moreover, it will be used in the disease diagnosis and prognostic prediction for CRC patients, especially in the aspect of disease screening, surgical strategy, indication of chemotherapy and molecular-targeted agents as well as monitoring tumor recurrence.

Program Goals and Expected Outcomes

By carrying out this clinical genomic study on a large-scale cohort of colorectal cancer, we will achieve a most comprehensive database for this common cancer, as multi-omics data (including genome, transcriptome, epigenetics), as well as full-traced clinical records (including diagnosis, pathology, therapeutic strategies, response, progression and survival records, etc.) will be integrated to support systematic exploration of the characteristics of this cancer, and what’s more, will tell us more about the association between genotype and clinical phenotype. This will help us to promote further advance on novel therapeutic development, provide better molecular classification on patients to achieve better clinical outcome.

What gaps in existing knowledge will be addressed by the study?

Although the genomic landscape of colorectal cancer has been profiled in recent years, there is still limit association been made between comprehensive multi-omics profiling and clinical features, especially the exact mechanism of distinct response to therapies in different patients, is not fully explored. In this clinical genomic study on colorectal cancer, not only pathological samples are collected for sequencing, but also the full traced clinical information, which provides more elaborate phenotypic data of patients will also be included for integrated analysis. The accomplishment of such investigation will accelerate the translation of omics-based technologies to real world clinical applications.

Program Team

Xiaojian Wu, Ph.D, M.D

The Sixth Affiliated Hospital of Sun Yat-sen University, China

Lead Investigator

Funding Organisations