Areas of Interest

Research Interests

Cell Signaling Programs in Cancer

Cell Signaling, Transcriptional Regulation, Genomics, Bioinformatics

Our lab deciphers cell signaling programs. Briefly, receptors in the cell membrane initiate cascades of reactions (pathways) that ultimately change the expression of genes. While cellular pathways are often thought of as independent and linear entities, the reality is that there is significant crosstalk among them. Indeed, the dense interconnections among signaling molecules exhibit a network structure.

The complexity of the cell signaling network provides it the capacity to produce organisms like ourselves (a good thing) as well as diseases that are difficult to manage (a bad thing). Therefore, a challenge is to explain how the network operates in normal circumstances, and how it is rewired in disease. Specifically, we wish to understand how the propagation of cell cycle signals becomes altered in cancer.

Our research program can be grouped into three cores:

  1. We are dissecting the structure of signaling cascades, focusing on the Ras network. Ras controls numerous tumorigenic processes through multiple downstream effectors. To better understand the structure of Ras signaling, we are developing strategies to dissect Ras activities into discrete sub-components called modules, represented by gene expression profiles. We have previously shown that these modules link to disease. We now wish to identify the genes that drive each module, and investigate how they may form the basis of a rational strategy for selecting clinical treatments.
  2. We are also decoding combinatorial transcriptional regulatory programs. Here, we focus on E2F, a family of transcription factors that regulate a range of activities through interactions with cofactors. E2F1 has a unique ability to regulate both cell cycle progression and apoptosis, processes whose decoupling is a fundamental step in the development of cancer. To better understand this, we are investigating the combinatorial interactions that underlie this transcriptional program, and how alterations can lead to the uncontrolled proliferation seen in cancer.
  3. Lastly, we are developing infrastructure to distribute our computational algorithms. Each of our projects contains a computational component, and an important aspect of our work is to make our methods available. We have previously developed the GATHER website for analysis of gene sets, and are now developing a platform SIGNATURE for the analysis of oncogenic pathways.

Across our investigations, we use genomics to reveal the simple fundamental units that constitute complex biological phenotypes (such as the workings of a cancer cell). We use human cell culture as a model and leverage a range of techniques including bioinformatics, molecular biology, and biochemistry.


  • Yam C, Abuhadra N, Sun R, Ding Q, Valero V, Tripathy D, Damodaran S, Arun B, Litton JK, Ueno NT, Murthy R, Lim B, Baez L, Li X, Buzdar A, Hortobagyi GN, Thompson A, Mittendorf EA, Rauch GM, Candelaria RP, Adrada BE, Huo L, Moulder SL, and Chang JT.  (2022).  Molecular characterization and prospective evaluation of pathological response and survival outcomes with neoadjuvant therapy in metaplastic triple-negative breast cancer.  Clin Cancer Res, 28(13):2878-2889.
  • Liu X, Gosline SJC, Pflieger LT, Wallet P, Iyer A, Guinney J, Bild AH, Chang JT. ( 2021). Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data. Brief Bioinform, 22(5):bbab039.
  • He J, Zhang F, Tay LW, Boroda S, Nian W, Levental KR, Levental I, Harris TE, Chang JT, Du G.  (2017).  Lipin-1 regulation of phospholipid synthesis maintains endoplasmic reticulum homeostasis and is critical for triple-negative breast cancer cell survival. FASEB J. Jul;31(7):2893-2904. doi: 10.1096/fj.201601353R. Epub 2017 Mar 27.
  • Bild, AH., Chang, JT., Johnson, WE., Piccolo, SR. (2014). A field guide to genomics research. PLoS Biology 12, 3523-5.
  • Cheng, Q., Chang, JT., Gwin, WR., Zhu, J., Ambs, S., Geradts, J., Lyerly, HK. (2014). A signature of epithelial-mesenchymal plasticity and stromal activation in primary tumor modulates late recurrence in breast cancer independent of disease subtype. Breast Cancer Rese 16, 407.
  • El-Chaar, NN., Piccolo, SR., Boucher, K., Cohen, AL., Chang, JT., Moos, P., Bild, AH. (2014). Genomic classification of the RAS network identifies a personalized treatment strategy for lung cancer. Mol Oncol., 8, 1339-54.
  • Gong, X., Yi, J., Carmon, KS., Crumbley, CA., Xiong, W., Thomas, A., Fan, X., Guo, S., An, Z., Chang, JT., Liu, Q. (2014). Aberrant RSPO3-LGR4 signaling in Keap1-deficient lung adenocarcinomas promotes tumor aggressiveness. Oncogene, [Epub ahead of print Dec 22].
  • Hong, B., Li, H., Zhang, M., Xu, J., Lu, Y., Zheng, Y., Qian, J., Chang, JT., Yang, J., Yi, Q. (2014). p38 MAPK inhibits breast cancer metastasis through regulation of stromal expansion. Int J Cancer, 136, 34-43.
  • Li, L., Liu, C., Amato, RJ., Chang, JT., Du, G., Li, W. (2014). CDKL2 promotes epithelial-mesenchymal transition and breast cancer progression. Oncotarget. 5: 10840-53.
  • Lu, E., Elizondo-Riojas, MA., Chang, JT., Volk, DE. (2014). Aptaligner: Automated Software for Aligning Pseudo-Random DNA X-Aptamers from Next-Generation Sequencing Data. Biochemistry 53, 3523-5.
  • Sarkar, TR., Battula, VL., Werden, SJ., Vijay, GV., Ramirez-Péna, EQ., Rodriguez-Canales, J., Taube, JH., Sphyris, N., Chang, JT., Mills, GB., Wistuba II, Miura, N., Lewis, MT., Porter, W., Andreeff, M., Mani, SA. (2014). GD3 synthase regulates EMT and metastasis in breast cancer. Oncogene, [Epub ahead of print Aug 11].
  • Assassi, S., Wu, M., Tan, F.K., Chang, J., Furst, D.E., Khanna, D., Feghali-Bostwick, C., Mayes, M.D. (2013).  Skin gene expression correlates of severity of interstitial lung disease in systemic sclerosis. Arthritis & Rheum., 65(11), 2917-27.
  • Chang, J.T., Mani, S.A. (2013).  Sheep, Wolf, or Werewolf: Cancer Stem Cells and the Epithelial-to-Mesenchymal Transition. Cancer Lttrs.,  341(1), 16-23.
  • Hollier, B.G., Tinnirello, A.A., Werden, S.J., Evans, K.W., Taube, J.H., Sarkar, T.R., Sphyris, N., Shariati, M., Kumar, S.V., Battula, V.L., Herschkowitz, J.I., Guerra, R., Chang, J.T., Miura, N., Rosen, J.M., Mani, S.A. (2013). FOXC2 expression links epithelial-mesenchymal transition and stem cell properties in breast cancer.  Cancer Res., 73(6), 1981-92.
  • Lin, S.H., Beane, L., Chasse, D., Zhu, K., Mathey-Prevot, B., Chang, J.T. (2013). Cross-platform prediction of gene expression signatures.  PLoS One,  8(11): e79228.
  • Steiling, K., van den Berge, M., Hijazi, K., Florido, R., Campbell, J., Liu, G., Xiao, J., Zhang, X., Duclos, G., Drizik, E., Si, H., Perdomo, C., Dumont, C., Coxson, H.O., Alekseyev, Y.O., Sin, D., Pare, P., Hogg, J.C., McWilliams, A., Hiemstra, P.S., Sterk, P.J., Timens, W., Chang, J.T., Sebastiani, P., O’Connor, G.T., Bild, A.H., Postma, D.S., Lam, S., Spira, A., Lenburg, M.E. (2013). A Dynamic Bronchial Airway Gene Expression Signature of COPD and Lung Function Impairment. Am J Respiratory Critical Care Med., 187(9), 933-42.
  • Tan, T.Z., Miow, Q.H., Huang, R.Y., Wong, M.K., Ye, J., Lau, J.A., Wu, M.C., Hadi, L.H.B.A., Soong, R., Choolani, M., Davidson, B., Nesland, J.M., Wang, L.Z., Matsumura, N., Mandai, M., Konishi, I., Goh, B.C., Chang, J.T., Thiery, J.P., Mori, S. (2013). Functional genomics identifies five distinct molecular subtypes with clinical relevance and pathways for growth control in epithelial ovarian cancer. EMBO Mol Med., 5(7), 983-98.
  • Taube, J.H., Malouf, G.G., Lu, E., Ramachandran, P.P., Gaur, S., Nicoloso, M.S., Rossi, S., Issa, J.J., Calin, G.A., Chang, J.T., Mani, S.A. (2013). Epigenetic silencing and loss of expression of microRNA-203 is required for EMT and cancer stem cell properties. Sci Reports, 3:2687.
  • Chang, J.T. (2012).  Deriving transcriptional programs and functional processes from gene expression databases. Bioinformatics, 28(8), 1122-9.
  • Cheng, Q., Chang, J.T., Geradts, J., Neckers, L.M., Haystead, T., Spector, N.L., Lyerly, H.K. (2012). Amplification and high‐level expression of HSP90 marks aggressive phenotypes of HER2 negative breast cancer. Breast Can Res., 14(2), R62.
  • Chang, J.T., Gatza, M.L., Lucas, J.E., Barry, W.T., Nevins, J.R. (2011). A Software Platform for Gene Expression Signature Analysis. BMC Bioinformatics, 12(443).
  • Cohen, A.L., Soldi, R., Zhang, H., Gustafson, A.M., Wilcox, R., Welm, B.E., Chang, J.T., Johnson, E., Spira, A., Jeffrey, S.S., Bild, A.H. (2011). A pharmacogenomic method for individualized prediction of drug sensitivity. Mol Syst Biology, 7(513).
  • Shats, I., Gatza, M.L., Chang, J.T., Mori, S., Freedman, J.A., Wang, J., Potti, A., Rich, J., Nevins, J.R. (2011). Development of an Expression Signature-Based Approach to Quantify and Target a Stem-Like Phenotype in Cancer. Cancer Res., 71(5), 1772-80.
  • Freedman, J.A., Chang, J.T., Jakoi, L., and Nevins, J.R. (2009). A Combinatorial Basis for E2F Transcription Factor Specificity. Oncogene, 28(32): 2873-81.
  • Chang, J.T., Carvalho, C., Mori, S., Bild, A.H., Gatza, M., Wang, Q., Lucas, J., Potti, A., Febbo, P., West, M., and Nevins, J.R. (2009). A Genomic Strategy to Elucidate Modules of Oncogenic Pathway Signaling Networks. Mol Cell,  34(1): 104-114.
  • Carvalho, C., Chang, J., Lucas, J., Nevins, J.R., Wang, Q., and West, M. (2008). High – Dimensional Sparse Factor Modelling: Applications in Gene Expression Genomics. J Amer Stat Assoc., 103:1438-1456.
  • Chang, J.T., and Nevins, J.R. (2006). GATHER: a systems approach to interpreting genomic signatures. Bioinformatics, 22(23): 2926-2933.
  • Bild, A.H., Yao, G., Chang, J.T., Wang, Q., Potti, A., Chasse, D., Joshi, M.B., Harpole, D., Lancaster, J.M., Berchuck, A., Olson, J.A., Marks, J.R., Dressman, H.K., West, M., and Nevins, J.R. (2005). Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature, 439(7074): 353-357.