Translational Cancer Biology Laboratory

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The Translational Cancer Biology (TCB) Laboratory is focused on developing biological correlates relevant to clinical trials and the translational arena, and on establishing an interface between engineering and medicine. Specific areas include:

1. Circulating cancer markers; e.g. circulating tumour cells (CTC). The laboratory has been developing CTC technologies in collaboration with the NUS Mechanobiology Institute and local start-up companies, such as Clearbridge Biomedics. We are looking at the utility of these markers in the establishment of diagnosis and during treatment, and their potential utility as screening tools in conjunction with existing screening technologies, such as low-dose computed tomography in lung cancer.
   
   
2. Establishing in vitro primary cell line cultures. The laboratory has established ovarian disease models across a variety of malignant and benign ovarian conditions. These models will be used to understand the biological progression of disease and for discovery of novel drug targets relevant to the disease model. We are expanding this into other tumour histologies and collaborating with like-minded investigators on humanised mouse models.
   
   
3. Extracellular matrix signatures relevant to cancer. We adopted a big data approach to differential gene expression and mining public data, and have described a novel gene expression signature that prognosticates across lung and other cancer types. We are now looking into correlating this signature in CTCs for metastasis, and examining gene expression changes in whole tumours to draw relations to the immune response and the development of resistance.

Dr. Darren Lim is a clinician-scientist awardee and senior Principal Investigator at IMCB, A*Star. He is an active international clinical trialist, and is Clinical and Scientific Director, Investigational Medicine Unit, SingHealth. The laboratory is supported by an NMRC Clinician Scientist Award, Industrial Alignment Funds, and IMCB core funding.

Selected publications:

1. Lim SB, Yeo T, Lee WD, Bhagat AAS, Tan SJ, Tan DSW, Lim WT, Lim CT. Addressing cellular heterogeneity in tumor and circulation for refined prognostication. Proc Natl Acad Sci U S A. 2019;116(36):17957-17962.
2. Lim SB, Lim CT, Lim WT. Single-Cell Analysis of Circulating Tumor Cells: Why Heterogeneity Matters. Cancers (Basel). 2019;11(10):1595.
3. Wang Z, Yip LY, Lee JHJ, et al. Methionine is a metabolic dependency of tumor-initiating cells. Nat Med. 2019;25(5):825-837.
4. Lim SB, Lee WD, Vasudevan J, Lim WT, Lim CT. Liquid biopsy: one cell at a time. NPJ Precis Oncol. 2019;3:23.
5. Lim SB, Tan SJ, Lim WT, Lim CT. Compendiums of cancer transcriptomes for machine learning applications. Sci Data. 2019;6(1):194
6. Bin Lim S, Chua MLK, Yeong JPS, Tan SJ, Lim WT, Lim CT. Pan-cancer analysis connects tumor matrisome to immune response. NPJ Precis Oncol. 2019;3:15. 
7. Ma BB, Lim WT, Goh BC, et al. Antitumor activity of nivolumab and biomarkers in recurrent and metastatic nasopharyngeal carcinoma: An international multicenter study of the Mayo Clinic Phase 2 Consortium
(NCI-9742, NCT02339558). J Clin Oncol. 2018;36:1412–1418.
8. Lim SB, Tan SJ, Lim WT, Lim CT. A merged lung cancer transcriptome dataset for clinical predictive modeling. Sci Data. 2018;5:180136.
9. Lim SB, Tan SJ, Lim WT, Lim CT. An extracellular matrix-related prognostic and predictive indicator for earlystage non-small cell lung cancer. Nat Commun. 2017;8:1734.
10. Soh SX, Siddiqui FJ, Allen JC, et al. A systematic review and meta-analysis of individual patient data on the impact of the BIM deletion polymorphism on treatment outcomes in epidermal growth factor receptor mutant lung cancer. Oncotarget. 2017;8:41474–41486.
11. Tan CL, Lim TH, Lim TK, et al. Concordance of anaplastic lymphoma kinase (ALK) gene rearrangements between circulating tumor cells and tumor in non-small cell lung cancer. Oncotarget. 2016;7:23251–23262.
12. Yeo T, Tan SJ, Lim CL, et al. Microfluidic enrichment for the single-cell analysis of circulating tumor cells. Sci Rep. 2016;6:22076.