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Breast cancer intratumor heterogeneity, progression and metastasis

A recent focus of study in the laboratory is ITH and molecular evolution in breast cancer progression. We recently reported on ITH of the five major gene expression prognostic tests in breast cancer, and the effect ITH has on risk prediciton. We examined intrinsic gene signatures in patient matched primary breast cancer and brain metastases and identified a hgih rate (~20%) of swtiching to HER2 amplified. Whole-exome capture RNA seqeuncing analysis of bone metastases also indentified both subtype swtiching

We collaborate with numerous computational biologists and biostatisticians to develop new algorithms, and apply current algorithms, to develop hypotheses from large data that can be tested in the wet lab. Examples of this include a new time-dependent lasso regression method for identifying changes in proteomic data (a), a novel method to deconvolute epigenomic data and ascribe transcription to individual cell types (b), statistical methods based upon pointwise mutual information for understanding intratumor heterogeneity (c-d), comparison of current RNA fusion detection algorithms (e), development of a computational resource that holds all TCGA data (f), and use of causal discovery for understanding breast cancer outcomes (g-h).

a.            Erdem C, Nagle AM, Casa AJ, Litzenburger BC, Wang YF, Taylor DL, Lee AV, Lezon TR*. Proteomic screening and lasso regression reveal differential signaling in insulin and insulin-like growth factor I pathways. Mol Cell Proteomics. 2016 Jun 30 PMID: 27364358

b.            Onuchic V, Hartmaier RJ, Boone DN, Samuels ML, Patel RY, White WM, Garovic VD, Oesterreich S, Roth ME, Lee AV, Milosavljevic A. Epigenomic Deconvolution of Breast Tumors Reveals Metabolic Coupling between Constituent Cell Types. Cell Rep. 2016 Nov 15;17(8):2075-2086. PMID: 2785196

c.           Spagnolo DM, Gyanchandani R, Al-Kofahi Y, Stern AM, Lezon TR, Gough A, Meyer DE, Ginty F, Sarachan B, Fine J, Lee AV, Taylor DL, Chennubhotla SC. Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers. J Pathol Inform. 2016 Nov 29;7:47. PMID: 2799493

d.           Spagnolo DM, Al-Kofahi Y, Zhu P, Lezon TR, Gough A, Stern AM, Lee AV, Ginty F, Sarachan B, Taylor DL, Chennubhotla SC. Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images. Cancer Res. 2017 Nov 1;77(21):e71-e74. doi: 10.1158/0008-5472.CAN-17-0676. PMID: 29092944

e.            Liu S, Tsai WH, Ding Y, Chen R, Fang Z, Huo Z, Kim S, Ma T, Chang TY, Priedigkeit NM, Lee AV, Luo J, Wang HW, Chung IF, Tseng GC. Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data. Nucleic Acids Res. 2016 Mar 18;44(5):e47. PMID: 26582927

f.            Chandran UR, Medvedeva OP, Barmada MM, Blood PD, Chakka A, Luthra S, Ferreira A, Wong KF, Lee AV, Zhang Z, Budden R, Scott JR, Berndt A, Berg JM, Jacobson RS. TCGA Expedition: A Data Acquisition and Management System for TCGA Data. PLoS One. 2016 Oct 27;11(10):e0165395.PMID: 27788220

g.           Cooper GF, Bahar I, Becich MJ, Benos PV, Berg J, Espino JU, Glymour C, Jacobson RC, Kienholz M, Lee AV, Lu X, Scheines R; Center for Causal Discovery team. The center for causal discovery of biomedical knowledge from big data. J Am Med Inform Assoc. 2015 Nov;22(6):1132-6. PMID: 26138794

h.           Lu S, Cai C, Yan G, Zhou Z, Wan Y, Chen V, Chen L, Cooper GF, Obeid LM, Hannun YA, Lee AV, Lu X. Signal-Oriented Pathway Analyses Reveal a Signaling Complex as a Synthetic Lethal Target for p53 Mutations. Cancer Res. 2016 Dec 1;76(23):6785-6794. Epub 2016 Oct 10.