Constant immune surveillance prevents normal stem cells from uncontrolled proliferation; however, cancer cells evolve to evade the host immune system through various mechanisms. The enormous amount of omics data generated in cancer cells has made it possible to identify patterns in transcriptome and “mutatome” that drive immune escape. One focus of our lab is to understand tumor immune escape by integrating the expression and sequence profiles of immune related genes in tumors and to develop prognosis procedures for immunotherapies.

Another goal of our lab is to improve the efficacy of immunotherapy by repotentiating immune cells against tumor cells. The critical role of T cells in targeting and eliminating tumor cells is evidentiated by the strong correlation between high T cell infiltration and the prolonged survival of patients. Both natural host T cells and engineered T cells targeting common tumor antigens have been used to treat patients with advanced solid tumors. However, most host T cells react weakly or not at all to tumor cells and engineered T cells can lead to severe off-tumor toxicity or even death in patients. Recognition of tumor cells by T cells is mediated through the binding of T cell receptors (TCRs) to the mutated antigens presented on the surface of tumor cells. We seek to use personalized genomics data to guide the engineering of TCRs, which can target tumor cells with high sensitivity and specificity.

Selected Publications

(* Corresponding author，# co-first author）

1.X. Lan* and J. K. Pritchard*, “Coregulation of tandem duplicate genes slows evolution of subfunctionalization in mammals.,” Science, vol. 352, no. 6288, pp. 1009–1013, 2016.

2.B. Liu*, L. Fang, R. Long, X. Lan*, and K.-C. Chou*, “iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition,” Bioinformatics,2016.

3.Z. Chen#, X. Lan#, J. M. Thomas-Ahner, D. Wu, X. Liu, Z. Ye, L. Wang, B. Sunkel, C. Grenade, J.Chen, et al., “Agonist and antagonist switch DNA motifs recognized by human androgen receptor in prostate cancer,” The EMBO Journal, 2015.

4.Z. Chen, X. Lan, D. Wu, B. Sunkel, Z. Ye, J. Huang, Z. Liu, S. K. Clinton, V. X. Jin, and Q. Wang,“Ligand-dependent genomic function of glucocorticoid receptor in triple-negative breast cancer,”Nature Communications, vol. 6, 2015.

5.N. E. Banovich#, X. Lan#, G. McVicker, B. Van de Geijn, J. F. Degner, J. D. Blischak, J. Roux, J. K. Pritchard, and Y. Gilad, “Methylation QTLs are associated with coordinated changes in transcription factor binding, histone modifications, and gene expression levels,” PLoS Genetics, vol. 10, no. 9, e1004663, 2014.

6.P.-Y. Hsu, H.-K. Hsu, X. Lan, L. Juan, P. S. Yan, J. Labanowska, N. Heerema, T.-H. Hsiao, Y.-C. Chiu, Y. Chen, et al., “Amplification of distant estrogen response elements deregulates target genes associated with tamoxifen resistance in breast cancer,” Cancer Cell, vol. 24, no. 2, pp. 197–212, 2013

7.X. Lan, H. Witt, K. Katsumura, Z. Ye, Q. Wang, E. H. Bresnick, P. J. Farnham, and V. X. Jin,“Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin linkages,” Nucleic Acids Research, vol. 40, no. 16, pp. 7690–7704, 2012.

8.X. Lan, P. J. Farnham, and V. X. Jin, “Uncovering transcription factor modules using one-and three-dimensional analyses,” Journal of Biological Chemistry, vol. 287, no. 37, pp. 30 914–30 921, 2012

9.X. Lan, R. Bonneville, J. Apostolos, W. Wu, and V. X. Jin, “W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data,” Bioinformatics, vol. 27, no. 3, pp. 428–430, 2011.

10.X. Lan, C. Adams, M. Landers, M. Dudas, D. Krissinger, G. Marnellos, R. Bonneville, M. Xu, J.Wang, T. H.-M. Huang, et al., “High resolution detection and analysis of CpG dinucleotides methylation using MBD-Seq technology,” PLoS ONE, vol. 6, no. 7, e22226, 2011.