Molecular Pathology Unit
Dennis C. Sgroi, MD
Professor of Pathology, Harvard Medical School
Executive Vice-Chair and Director of Breast Pathology
Massachusetts General Hospital
149 13th Street, Room 7139
Charlestown, MA 2129
Explore This Laboratory
About the Lab
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 various high-throughput genetic and proteomic 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.
Presently, my laboratory is focused on applying high-throughput molecular technologies to identify biomarkers that will predict the clinical behavior of human estrogen receptor positive breast cancer in the setting of specific hormonal and chemotherapeutic regimens. We have developed the Breast Cancer Index (BCI) biomarker which is an algorithmic gene expression–based signature comprised of two functional biomarker panels, the Molecular Grade Index (MGI) and the two-gene ratio, HOXB13/IL17BR (H/I), that evaluate tumour proliferation and estrogen signalling, respectively. Integration of MGI and H/I generates a prognostic BCI score quantifying the risk of overall (0-10 years) and late (5-10 years) distant recurrence in ER+ HER2- breast cancer patients. The predictive component of BCI, the H/I ratio (henceforth BCI-H/I), has been shown to significantly predict endocrine response across several different treatment scenarios. In ER+ HER2- breast cancer patients in the extended endocrine setting, BCI predicted benefit from an additional 5 years of letrozole after ~5 years of initial tamoxifen in the MA.17 study, and most recently BCI predicted benefit from an additional 5 years of tamoxifen after 5 years of initial tamoxifen in the aTTom trial. These data provided further validation and established BCI as a unique biomarker that can help inform the decision to extend or not extend endocrine therapy beyond 5 years. BCI has been adopted in the most recent 2022 ASCO and NCCN guidelines. We are currently collaborating with the NSABP to assess our biomarker in the NSABP-42. Lastly, we are currently studying protein-protein dysregulations in H/I-low breast cancers to identify therapeutic vulnerabilities. In a comparative analysis of H/I-high versus H/I-low breast cancers, we have identified several dysregulated pathways that may be susceptible to therapeutic intervention.
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.
Meet our research team:
- Dennis Sgroi, MD
- Marinko Sremac, PhD
Sgroi DC, Treuner K, Zhang, Y, Piper T, Salunga R, Ahmed I, Doos L, Thornber S, Taylor KJ, Brachtel E, Pirrie S, Schnabel CA, Rea D, Bartlett JMS. Correlative studies of the Breast Cancer Index (HOXB13/IL17BR and ER, PR, AR, AR/ER ratio and Ki67 for prediction of extended endocrine therapy benefit: a Trans-aTTo study. Breast Cancer Res. 2022 Dec 16;24(1):90.
Bartlett JMS, Sgroi DC, Treuner K, Zhang Y, Piper T, Salunga RC, Ahmed I, Doos L, Thornber S, Taylor KJ, Brachtel EF, Pirrie SJ, Schnabel CA, Rea D. Breast Cancer Index is a predictive biomarker of treatment benefit and outcome from extend-ed tamoxifen therapy: final analysis of the TransaTTom study. Clin Cancer Res. 2022; 28:1871-80.
Bartlett JMS*, Sgroi DC*, Treuner K, Zhang Y, Ahmed I, Piper T, Salunga R, Brachtel EF, Pirrie SJ, Schnabel CA, Rea DW. Breast Cancer Index and Prediction of Benefit From Extended Endocrine Therapy in Breast Cancer Patients Treated in the Adjuvant Tamoxifen-To Offer More? (aTTom) Trial. Ann Oncol. 2019 Nov 1;30(11):1776-1783.
Jerevall PL, Brock J, Palazzo J, Wieczorek T, Misialek M, Guidi AJ, Wu Y, Erlander MG, Zhang Y, SchnabelCA, Goss PE, Horick N, Sgroi DC. Discrepancy in risk assessment of hormone receptor positive early-stage breast cancer patients using breast cancer index and recurrence score. Breast Cancer Res Treat. 2019 Jan;173(2):375-383.
Sgroi DC, Sestak I, Cuzick J, Zhang Y, Schnabel CA, Schroeder B, Erlander MG, Dunbier A, Sidhu K, Lopez- Knowles E, Goss PE, and Dowsett M. Prediction of late distant recurrence in patients with oestrogen-receptorpositive breast cancer: a prospective comparison of the Breast Cancer Index (BCI) assay, 21-gene recurrence score, and IHC4 in TransATAC study population. Lancet Oncol. 2013 Oct;14(11):1067-76.
*Denotes equal contribution
- Executive Vice Chair of Pathology, Massachusetts General Hospital
- Professor of Pathology, Harvard Medical School