About
Rita Nanda, MD, is an Associate Professor of Medicine in the Department of Medicine at The University of Chicago. Her clinical and research interests focus on breast cancer, including the use of advanced imaging techniques such as ultrafast DCE-MRI to predict response to neoadjuvant chemotherapy, and the application of gene expression signatures of systemic immunity to understand tumor microenvironment biology and therapeutic response. Her work also encompasses the evaluation of targeted therapies such as CDK4/6 inhibitors in hormone receptor-positive, HER2-negative breast cancer, as well as the study of treatment outcomes, toxicity, and mortality in breast cancer survivors, including those with a history of childhood cancer. Dr. Nanda's research contributes to improving personalized treatment strategies and understanding disparities in breast cancer care.
Research topics
- Medicine
- Oncology
- Internal medicine
- Biology
- Computer Science
- Artificial Intelligence
- Machine Learning
- Surgery
- Cancer research
- Nuclear medicine
- Genetics
- Radiology
Selected publications
Breast Cancer Targets and Therapy · 2026-04-01
articleOpen accessPurpose: Analyses of patients with early-stage, treatment-naïve triple-negative breast cancer (TNBC) have demonstrated that high glucocorticoid receptor (GR) expression in primary tumors is associated with poor prognosis. We previously observed that GR-high primary TNBCs exhibited significantly increased numbers of tumor-infiltrating regulatory T cells (Tregs) compared with GR-low tumors. To further investigate GR-associated immunologic features, we leveraged imaging mass cytometry (IMC) to profile additional immune cell phenotypes and spatial architecture in GR-high versus GR-low primary TNBC. Patients and Methods: Tumor-infiltrating immune cells were profiled in formalin-fixed paraffin-embedded (FFPE) core biopsies from five untreated GR-high and four GR-low TNBC tumors using IMC with a 21-antibody panel. Regions of interest (ROI) were selected within pan-cytokeratin-positive tumor nests. Data underwent unsupervised clustering, and cell types were identified based on protein expression profiles. Analyses compared cell-type abundance and spatial interactions in GR-high versus GR-low tumors. Results: GR-high tumors exhibited significantly greater Treg infiltration within tumor nests than GR-low tumors. GR-high TNBC also showed a comparatively greater abundance of activated memory CD8+ T cells, cytotoxic CD4+ T cells, and effector memory CD4+ T cells. In contrast, GR-low tumors exhibited relatively greater representation of HLA-ABC-positive (HLA-ABC+) cancer cells as well as early-activated dendritic cells (DCs) and natural killer (NK) cells. Spatial analysis revealed that Tregs in GR-high tumors colocalized more frequently with proliferating tumor cells relative to Tregs in GR-low tumors. NK cells in GR-high tumors displayed relatively less colocalization with proliferating tumor cells. Conclusion: Compared with GR-low disease, treatment-naïve GR-high primary TNBC exhibits a more immunosuppressive tumor microenvironment characterized by greater Treg density, closer Treg-cancer cell proximity, reduced NK cell infiltration, impaired immune surveillance, and decreased abundance of HLA-ABC+ cancer cells. These findings implicate TNBC cell GR signaling as immunosuppressive, likely through mechanisms resulting in both differential immune cell enrichment and altered spatial organization.
Science Translational Medicine · 2026-04-22
articleDynamic biomarkers of therapy response are critical for precision oncology but often rely on serial tissue biopsies, which are invasive and not always feasible. In contrast, peripheral blood offers a minimally invasive, dynamic window into the evolving systemic immune landscape. Leveraging this, we performed RNA sequencing on 546 peripheral blood samples from 160 patients with high-risk stage II/III human epidermal growth factor receptor 2 (HER2)-negative breast cancer treated with either chemotherapy alone or in combination with immunotherapy (chemoimmunotherapy). Our analysis uncovered immune correlates of tumor subtype and treatment response. For example, samples from patients with triple-negative breast cancer exhibited elevated T cell receptor clonality and robust immune activation profiles. Among patients receiving chemoimmunotherapy, early responders demonstrated high baseline T cell receptor diversity, followed by rapid clonal expansion and activation of T cells after just one treatment cycle. We developed a multiparametric peripheral immune biomarker that integrated baseline and early on-treatment features to predict response to pembrolizumab, which was successfully validated in an independent cohort of 59 patients with breast cancer treated with neoadjuvant dostarlimab. These findings reveal the potential of blood-based immune monitoring to predict immunotherapy benefit, offering an accessible tool for tailoring treatment strategies in breast cancer.
2025-11-25
articleOpen access<p>Overall and within batch Coefficient of Variation for CM and each Gene.</p>
2025-11-25
articleOpen access<p>Supplementary Tables</p>
2025-11-25
articleOpen access<p>Supplementary Figure S3. Distribution of intrinsic subtypes in (A) TBCRC023 and (B) PAMELA cohort.</p>
2025-11-25
articleOpen access<p>Supplementary figure 4 displays time updates ROC curves for week 4 CM level using two additional methods (A) binary thresholding and (B) random forest.</p>
2025-11-25
articleOpen access<p>Association between week 4 CM and PFS and OS</p>
Annals of Oncology · 2025-09-17 · 3 citations
articleOpen access2025-11-25
articleOpen access<p>Association between week 4 CM and disease status at first restaging after adjusting for CA27-29.</p>
2025-11-25
articleOpen access<p>Supplementary Figure S6. Distribution of HER2 gene ratio in relation to PIK3CA mutation status and HER2-enriched subtype.</p>
Recent grants
Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant Therapy
NIH · $4.5M · 2010–2022
NIH · $2.1M · 2018–2021
Frequent coauthors
- 999 shared
HS Rugo
UCSF Helen Diller Family Comprehensive Cancer Center
- 976 shared
Christina Yau
University of California, San Francisco
- 938 shared
Angela DeMichele
University of Pennsylvania
- 921 shared
Lajos Pusztai
- 900 shared
Claudine Isaacs
- 887 shared
Douglas Yee
Masonic Cancer Center
- 882 shared
MC Liu
- 823 shared
Ruby Singhrao
University of California, San Francisco
Labs
Education
- 1998
Medical Degree
University of Chicago
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