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Dennis C. Sgroi, MD
Professor of Pathology, Harvard Medical SchoolExecutive Vice-Chair and Director of Breast Pathology, Massachusetts General Hospital
Molecular Pathology UnitMassachusetts General Hospital149 13th Street, 6th FloorCharlestown, MA 02129Phone: 617-726-5697Fax: 617-726-5684Email: firstname.lastname@example.org
The overarching goals of research in the Sgroi laboratory are to develop better ways to identify patients who are at risk for the development of breast cancer and to identify those breast cancer patients who are likely to benefit from targeted drug therapies. We are taking several different approaches to achieving these goals. First, we are deciphering specific molecular events that occur during the earliest stages of tumor development and using this knowledge to develop biomarkers that will predict for increased risk of progression to cancer. Second, using DNA microarray technologies, we are searching for novel breast cancer biomarkers to identify patients with hormone-receptor-positive breast cancer who are most likely to benefit from extended hormonal therapy. Finally, we are taking a combined approach—based on analysis of tissue from breast cancer patients and various laboratory studies—to identifying biomarkers that will predict how individual breast cancer patients will respond to novel targeted therapeutics.
Rachel BrookeStacy Francis BS Dennis Sgroi, MD
Our research focuses on understanding the molecular genetic events associated with the pathogenesis of human breast cancer. My laboratory has developed technological approaches to study gene expression in the earliest microscopic precursor lesions as well as in the latest stages of human breast cancer. Specifically, we have been successful in combining laser capture microdissection, high-density cDNA array, and real-time quantitative PCR (RTQ-PCR) technologies to identify novel gene expression patterns in human breast cancer. Using this approach, we have demonstrated for the first time that atypical intraductal hyperplasia and ductal carcinoma in situ are direct precursors to invasive ductal carcinoma. More specifically, we have shown that the various pathological stages of breast cancer progression are highly similar at the transcriptional level, and that atypical intraductal hyperplasia—the earliest identifiable stage of breast cancer—is a genetically advanced lesion with an expression profile that resembles that of invasive breast cancer. More recently, we have studied the gene expression changes of the stromal microenvironment during breast cancer progression, and we have demonstrated that the transition from preinvasive to invasive breast cancer is associated with distinct stromal gene expression changes. In collaboration with Barry Karger, PhD, of the Barnett Institute, we have used advanced tandem mass spectrometry to perform comparative proteomic profiling of normal breast epithelium with neoplastic epithelium of the preinvasive and invasive stages of breast cancer. Through a novel bioinformatic approach, we recently integrated our transcriptomic and proteomic data sets to identify a novel, robust biomarker of clinical outcome in estrogen-receptor-positive breast cancer patients. We are currently applying tandem mass spectometry technologies to standard formalin-fixed, paraffin-embedded breast tumor samples as a means to identify biomarkers of therapeutic response to HER2- and estrogen-receptor pathway-driven tumors. Presently, my laboratory is focused on applying high-throughput DNA microarray and proteomic technologies as a means to predict the clinical behavior of human breast cancer in the setting of specific hormonal and chemotherapeutic regimens. We have independently developed two complementary biomarkers—the Molecular Grade Index (MGI) and the HOXB13/IL17BR (H/I). MGI is a molecular surrogate for histological grade and a highly precise biomarker for risk of breast cancer recurrence. The HOXB13:IL17BR index, on the other hand, is a biomarker of endocrine responsiveness in ER+ breast cancer, as it has been shown to predict for benefit from adjuvant tamoxifen and extended adjuvant aromatase inhibitor therapy. Most recently, we demonstrated that the combination MGI and H/I, called the Breast Cancer Index (BCI), outperforms the Oncotype Dx Recurrence Score for predicting risk of recurrence. As a result of our collective data, we anticipate assessing BCI in clinical trials of extended adjuvant hormonal therapy. Given that HOXB13 expression in clinical breast cancers is associated with endocrine therapy responsiveness, we are currently investigating the functional activity of HOXB13 and assessing its possible role as a surrogate marker for a nonclassical estrogen receptor signaling pathway. Lastly, using an artificial zinc-finger transcription factors combinatorial library technology, we developed an in vitro breast cancer model of drug resistance to a clinically important antiendocrine therapeutic agent. Our results demonstrate that this approach can be used successfully to induce stable drug resistance in human cancer cell lines and to identify a gene expression signature that is associated with a clinically relevant drug-resistance phenotype. These experiments provide an important proof of principle for the use of combinatorial zinc-finger transcription factor libraries to induce and to study important cellular phenotypes, including human cancer drug resistance. We are currently using this approach to identify potential biomarkers for HER2-directed and PARP1-directed therapies.
Bibliography of Dennis C. Sgroi via PubMed
A BRCA1 deficient-like signature is enriched in breast cancer brain metastases and predicts DNA damage-induced poly (ADP-ribose) polymerase inhibitor sensitivity. McMullin RP, Wittner BS, Yang C, Denton-Schneider BR, Hicks D, Singavarapu R, Moulis S, Lee J, Akbari MR, Narod SA, Aldape KD, Steeg PS, Ramaswamy S, Sgroi DC. Breast Cancer Res. 2014 Mar 14;16(2):R25.
Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: a prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Sgroi DC, Sestak I, Cuzick J, Zhang Y, Schnabel CA, Schroeder B, Erlander MG, Dunbier A, Sidhu K, Lopez-Knowles E, Goss PE, Dowsett M. Lancet Oncol. 2013 Oct;14(11):1067-76.
Prediction of late disease recurrence and extended adjuvant letrozole benefit by the HOXB13/IL17BR biomarker. Sgroi DC, Carney E, Zarrella E, Steffel L, Binns SN, Finkelstein DM, Szymonifka J, Bhan AK, Shepherd LE, Zhang Y, Schnabel CA, Erlander MG, Ingle JN, Porter P, Muss HB, Pritchard KI, Tu D, Rimm DL, Goss PE. J Natl Cancer Inst. 2013 Jul 17;105(14):1036-42.
Breast cancer index identifies early-stage estrogen receptor-positive breast cancer patients at risk for early- and late-distant recurrence. Zhang Y, Schnabel CA, Schroeder BE, Jerevall PL, Jankowitz RC, Fornander T, Stål O, Brufsky AM, Sgroi D, Erlander MG. Clin Cancer Res. 2013 Aug 1;19(15):4196-205.
Integrated proteomic, transcriptomic, and biological network analysis of breast carcinoma reveals molecular features of tumorigenesis and clinical relapse.
Imielinski M, Cha S, Rejtar T, Richardson EA, Karger BL, Sgroi DC. Mol Cell Proteomics. 2012 Jun;11(6):M111.014910.
Massachusetts General Hospital
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