Research in my laboratory is focused on the discovery and characterization of cancer biomarkers and novel druggable targets. In my lab we use integrative genomic approaches to identify genetic and cellular properties of tumors that explain systems-level variation in cancer aggressiveness and treatment response. We employ next-generation sequencing technologies such as whole-exome sequencing, bulk RNA-Seq and single-cell RNA-Seq to study how the molecular and cellular composition of tumors impacts tumor form and phenotype. In breast cancers and other solid tumors, we investigate the dynamics of tumor-immune interactions on a population scale. Our work shows that biomarkers predictive of immune-mediated patient outcomes reflect differences in tumor immunological configurations, as well as states of molecular polarization that favor immunosuppressive or immunostimulatory phenotypes. Using multivariable statistics to guide the discovery process, we have identified novel molecular interactions between tumors and their immunological environments that are the focus of ongoing mechanistic studies involving immunocompetent mouse tumor models and immune functional characterization assays.
Prognostic and predictive breast cancer immune subclasses
Through analysis of the tumor transcriptome, we have gained detailed insights into the pathobiology of cancer and its clinical manifestations. Immunological gene networks that reflect the abundance of distinct tumor-infiltrating leukocyte populations can be quantified in breast tumors and are predictive of multiple clinical endpoints. Key among them are signatures of cytolytic CD8+ T cells and antibody-producing plasma B cells that show strong and independent statistical associations with reduced cancer recurrence, positive neoadjuvant drug response and long-term overall survival of patients. We find that immune-mediated breast cancer survival is significantly linked to tumors with high proliferative capacity or high mutational burden, and is measurable in all breast cancer subtypes. Conversely, tumors absent of these signatures are defined by poor clinical outcomes, high intratumoral TGF-beta expression, and chromosomal amplification of immune-modulatory genes that may potentiate immune evasion. We are currently investigating the implications of these findings for emerging immunotherapeutic treatments for breast cancer.
Mechanisms of immunosuppression
Using tumor gene expression and mutational profiles, we have developed genetic triangulation algorithms to pinpoint cancer oncogenes and pathways of cancer progression. In this framework, we are studying hypotheses related to: 1) druggable myeloid-derived signaling cascades that orchestrate the recruitment, expansion and survival of immunosuppressive myeloid cells at the tumor site that inhibit anti-tumor immunity and promote breast cancer malignant progression through paracrine signaling, and 2) the discovery of tumor-agnostic transcriptional programs exploited by tumors to evade immune destruction by inhibiting the trafficking and subsequent activation of effector T cells.
Other current and collaborative research interests include
- Blood-based biomarkers of immunotherapy response
- Use of patient-derived tumor organoids to track treatment-induced changes in tumor clonal architecture
- Characterization of immunomodulatory tumor microenvironments by scRNA-Seq
- Development of molecular signatures to guide clinical decision making for appendiceal cancer
- Blockade of TREM-1 signaling in myeloid-derived suppressor cells to enhance efficacy of immune checkpoint inhibitors
Song Q, Hawkins GA, Wudel L, Chou PC, Forbes E, Pullikuth AK, Liu L, Jin G, Craddock L, Topaloglu U, Kucera G, O'Neill S, Levine EA, Sun P, Watabe K, Lu Y, Alexander-Miller MA, Pasche B, Miller LD*, Zhang W*. Dissecting intratumoral myeloid cell plasticity by single cell RNA-seq. Cancer Med. 2019 Jun;8(6):3072-3085. PMCID: PMC6558497; *Co-corresponding authors
Thomas A, Routh ED, Pullikuth A, Jin G, Su J, Chou JW, Hoadley KA, Print C, Knowlton N, Black MA, Demaria S, Wang E, Bedognetti D, Jones WD, Mehta GA, Gatza ML, Perou CM, Page DB, Triozzi P, Miller LD. Tumor mutational burden is a determinant of immune-mediated survival in breast cancer. Oncoimmunology. 2018 Jul 30;7(10):e1490854. PMCID: PMC6207420
Gnjatic S, Bronte V, Brunet LR, Butler MO, Disis ML, Galon J, Hakansson LG, Hanks BA, Karanikas V, Khleif SN, Kirkwood JM, Miller LD, Schendel DJ, Tanneau I, Wigginton JM, Butterfield L. Identifying baseline immune-related biomarkers to predict clinical outcome of immunotherapy. J Immunother Cancer. 2017 May 16;5:44. PMCID: PMC5432988
Miller LD, Chou JA, Black MA, Print C, Chifman J, Alistar A, Putti T, Zhou X, Bedognetti D, Hendrickx W, Pullikuth A, Rennhack J, Andrechek ER, Demaria S, Wang E, Marincola FM. Immunogenic subtypes of breast cancer delineated by gene classifiers of immune responsiveness. Cancer Immunol Res. 2016; 4(7):600-10. PMCID: PMC4930674
Chifman J, Pullikuth A, Chou JW, Bedognetti D, Miller LD. Conservation of immune gene signatures in solid tumors and prognostic implications. BMC Cancer. 2016 Nov 22;16(1):911. PMCID: PMC5118876
Levine EA, Votanopoulos KI, Qasem SA, Philip J, Cummins KA, Chou JW, Ruiz J, D'Agostino R, Shen P, Miller LD. Prognostic Molecular Subtypes of Low-Grade Cancer of the Appendix. J Am Coll Surg. 2016 Apr;222(4):493-503. PMCID: PMC4808611
Alistar A, Chou JW, Nagalla S, Black MA, D'Agostino R Jr, Miller LD. Dual roles for immune metagenes in breast cancer prognosis and therapy prediction. Genome Med. 2014 Oct 28;6(10):80. PMCID: PMC4240891
Nagalla S, Chou JW, Willingham MC, Ruiz J, Vaughn JP, Dubey P, Lash TL, Hamilton-Dutoit SJ, Bergh J, Sotiriou C, Black MA, Miller LD. Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis. Genome Biol. 2013 Apr 29;14(4):R34. PMCID: PMC3798758
Prat A, Parker JS, Fan C, Cheang MC, Miller LD, Bergh J, Chia SK, Bernard PS, Nielsen TO, Ellis MJ, Carey LA, Perou CM. Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen. Ann Oncol. 2012 Nov;23(11):2866-73. PMCID: PMC3477878
Miller LD, Coffman LG, Chou JW, Black MA, Bergh J, D'Agostino R Jr, Torti SV, Torti FM. An Iron Regulatory Gene Signature Predicts Outcome in Breast Cancer. Cancer Res. 2011 Aug 29. PMCID: PMC3206152
Zhang J, Liu X, Datta A, Govindarajan K, Tam WL, Han J, George J, Wong C, Ramnarayanan K, Phua TY, Leong WY, Chan YS, Palanisamy N, Liu ET, Karuturi KM, Lim B, Miller LD. RCP is a human breast cancer–promoting gene with Ras-activating function. J Clin Invest. 2009 Aug;119(8):2171-83. PMCID: PMC2719918
Broët P, Camilleri-Broët S, Zhang S, Alifano M, Bangarusamy D, Battistella M, Wu Y, Tuefferd M, Régnard JF, Lim E, Tan P, Miller LD. Prediction of clinical outcome in multiple lung cancer cohorts by integrative genomics: implications for chemotherapy selection. Cancer Res. 2009 Feb 1;69(3):1055-62. PMID: 19176396
Ivshina AV, George J, Senko O, Mow B, Putti T, Smeds J, Lindahl T, Nordgren H, Wong JEL, Bergh J, Liu ET, Kuznetsov VA, Miller LD. Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res. 2006 Nov 1;66(21):10292-301. PMID: 17079448
Miller LD, Smeds J, George J, Vega VB, Vergara L, Ploner A, Pawitan Y, Hall P, Klaar S, Liu ET and Bergh J. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. Proc Natl Acad Sci U S A. 2005 Sep 20;102(38):13550-5. PMCID: PMC1197273