Rajan Gupta

Overview:

Abdominal Imaging; Multiparametric MR imaging of prostate cancer; MR imaging of the hepatobiliary system; Applications of dual energy CT in the abdomen and pelvis

Positions:

Associate Professor of Radiology

Radiology, Abdominal Imaging
School of Medicine

Assistant Professor in the Department of Surgery

Surgery, Urology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

M.D. 2003

Northwestern University

Grants:

Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) of Bone Marrow In Acute Myeloid Leukemia

Administered By
Radiology, Abdominal Imaging
Role
Principal Investigator
Start Date
End Date

Publications:

Characterization of tumor mutation burden, PD-L1 and DNA repair genes to assess relationship to immune checkpoint inhibitors response in metastatic renal cell carcinoma.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have expanded treatment options for metastatic renal cell carcinoma (mRCC); however, there are limited predictive biomarkers for response to ICIs in this indication, with programmed death-ligand 1 (PD-L1) status demonstrating little predictive utility in mRCC. While predictive of ICI response in other tumor types, the utility of tumor mutation burden (TMB) in mRCC is unclear. Here, we assess TMB, loss of antigen presentation genes and PD-L1 status correlated with outcomes to ICI treatment in mRCC. METHODS: Tumor samples from 34 patients with mRCC treated with ICI therapy at Duke Cancer Institute were retrospectively evaluated using Personal Genome Diagnostics elio tissue complete (RUO version), a tumor genomic profiling assay for somatic variants, TMB, microsatellite status and genomic status of antigen presentation genes. Tumor samples were also analyzed with the Dako 28-8 PD-L1 immunohistochemistry assay. Deidentified clinical information was extracted from the medical record, and tumor response was evaluated based on the Response Evaluation Criteria In Solid Tumors (RECIST) V.1.1 criteria. RESULTS: Patients were stratified by overall response following ICI therapy and designated as progressive disease (PD; n=18) or disease control groups (DC; n=16). TMB scores ranged from 0.36 to 12.24 mutations/Mb (mean 2.83 mutations/Mb) with no significant difference between the PD and DC groups (3.01 vs 2.63 mutations/Mb, respectively; p=0.7682). Interestingly, 33% of PD patients displayed loss of heterozygosity of major histocompatibility complex class I genes (LOH-MHC) vs 6% of DC patients. Nine of 34 samples were PD-L1-positive (4 in the PD group; 5 in the DC group), suggesting no correlation between PD-L1 expression and response to ICI therapy. Notably, the DC group displayed an enrichment of mutations in DNA repair genes (p=0.04), with 68.8% exhibiting at least one mutated homologous recombination repair (HRR)-related gene compared with only 38.9% of the PD group (p=0.03). CONCLUSIONS: Overall, neither TMB nor PD-L1 correlated with ICI response and TMB was not significantly associated with PD-L1 expression. The higher incidence of LOH-MHC in PD group suggests that loss of antigen presentation may restrict response to ICIs. Separately, enrichment of HRR gene mutations in the DC group suggests potential utility in predicting ICI response and a potential therapeutic target, warranting future studies.
Authors
Labriola, MK; Zhu, J; Gupta, R; McCall, S; Jackson, J; Kong, EF; White, JR; Cerqueira, G; Gerding, K; Simmons, JK; George, D; Zhang, T
MLA Citation
Labriola, Matthew Kyle, et al. “Characterization of tumor mutation burden, PD-L1 and DNA repair genes to assess relationship to immune checkpoint inhibitors response in metastatic renal cell carcinoma.J Immunother Cancer, vol. 8, no. 1, Mar. 2020. Pubmed, doi:10.1136/jitc-2019-000319.
URI
https://scholars.duke.edu/individual/pub1435838
PMID
32221016
Source
pubmed
Published In
Journal for Immunotherapy of Cancer
Volume
8
Published Date
DOI
10.1136/jitc-2019-000319

PROSPER: Phase III randomized study comparing perioperative nivolumab versus observation in patients with renal cell carcinoma (RCC) undergoing nephrectomy (ECOG-ACRIN EA8143)

Authors
Harshman, LC; Puligandla, M; Allaf, ME; McDermott, DF; Drake, CG; Signoretti, S; Cella, D; Gupta, RT; Shuch, BM; Lara, P; Kapoor, A; Heng, DYC; Leibovich, B; Michaelson, MD; Choueiri, TK; Master, VA; Jewett, MAS; Maskens, D; Haas, NB; Carducci, MA
MLA Citation
Harshman, Lauren Christine, et al. “PROSPER: Phase III randomized study comparing perioperative nivolumab versus observation in patients with renal cell carcinoma (RCC) undergoing nephrectomy (ECOG-ACRIN EA8143).” Journal of Clinical Oncology, vol. 38, no. 6, AMER SOC CLINICAL ONCOLOGY, 2020.
URI
https://scholars.duke.edu/individual/pub1441556
Source
wos
Published In
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology
Volume
38
Published Date

PROSPER: A phase III randomized study comparing perioperative nivolumab (nivo) versus observation in patients with localized renal cell carcinoma (RCC) undergoing nephrectomy (ECOG-ACRIN 8143).

<jats:p> TPS684 </jats:p><jats:p> Background: The anti-PD-1 antibody nivo improves overall survival in metastatic RCC and is well tolerated. There is no standard adjuvant systemic therapy that increases overall survival (OS) over surgery alone for non-metastatic RCC. Priming the immune system prior to surgery with anti-PD-1 has shown an OS benefit compared to a pure adjuvant approach in mouse solid tumor models. The PROSPER RCC trial aims to improve clinical outcomes by priming the immune system prior to nephrectomy with neoadjuvant nivo and continued engagement with adjuvant blockade in patients with high risk M0 RCC compared to surgery alone. Methods: This global, unblinded, phase 3 National Clinical Trials Network study is currently accruing patients with clinical stage ≥T2 or node positive M0 RCC of any histology. Tumor biopsy prior to randomization is mandatory to ensure RCC and permits in depth correlative science. The investigational arm will receive two doses of nivo 240mg prior to surgery followed by adjuvant nivo for 9 months (q2 wks x 3 mo followed by 480mg q4 wks x 6 mo). The control arm will undergo standard nephrectomy followed by observation. Randomized patients are stratified by clinical T stage, node positivity, and histology. To enhance accrual and patient quality of life, key upcoming amendments are being instituted. These include biopsy only in the nivo arm, allowance of oligometastatic disease and bilateral renal masses that can be fully resected/ablated, and change of nivo dosing to q4 wks (1 neoadj; 9 adj). With accrual of 766 patients, there is 84.2% power to detect a 14.4% absolute benefit in recurrence-free survival (RFS) at 5 years assuming the ASSURE historical control of ~56% to 70% (HR = 0.70). The study is also powered to evaluate a significant increase in overall survival (HR 0.67). Safety, feasibility, and quality of life endpoints critical to adjuvant therapy considerations are incorporated. PROSPER RCC embeds a wealth of translational work aimed at investigating the impact of the baseline immune milieu, the changes induced by neoadjuvant anti-PD-1 priming, and how both correlate with clinical outcomes. Clinical trial information: NCT03055013. </jats:p>
Authors
Harshman, LC; Puligandla, M; Haas, NB; Allaf, M; Drake, CG; McDermott, DF; Signoretti, S; Cella, D; Gupta, RT; Shuch, BM; Choueiri, TK; Lara, P; Kapoor, A; Heng, DYC; Jewett, MAS; Master, VA; Michaelson, MD; Leibovich, BC; Maskens, D; Carducci, MA
MLA Citation
Harshman, Lauren Christine, et al. “PROSPER: A phase III randomized study comparing perioperative nivolumab (nivo) versus observation in patients with localized renal cell carcinoma (RCC) undergoing nephrectomy (ECOG-ACRIN 8143).Journal of Clinical Oncology, vol. 37, no. 7_suppl, American Society of Clinical Oncology (ASCO), 2019, pp. TPS684–TPS684. Crossref, doi:10.1200/jco.2019.37.7_suppl.tps684.
URI
https://scholars.duke.edu/individual/pub1417283
Source
crossref
Published In
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology
Volume
37
Published Date
Start Page
TPS684
End Page
TPS684
DOI
10.1200/jco.2019.37.7_suppl.tps684

Characterization of Adrenal Masses: Can Dual Energy CT Improve Differentiation Between Adenomas and Metastases?

Authors
Gupta, R; Ho, L; Marin, D; Boll, D; Nelson, R
MLA Citation
Gupta, R., et al. “Characterization of Adrenal Masses: Can Dual Energy CT Improve Differentiation Between Adenomas and Metastases?American Journal of Roentgenology, vol. 192, no. 5, AMER ROENTGEN RAY SOC, 2009.
URI
https://scholars.duke.edu/individual/pub896331
Source
wos
Published In
Ajr. American Journal of Roentgenology
Volume
192
Published Date

Human-machine partnership with artificial intelligence for chest radiograph diagnosis.

Human-in-the-loop (HITL) AI may enable an ideal symbiosis of human experts and AI models, harnessing the advantages of both while at the same time overcoming their respective limitations. The purpose of this study was to investigate a novel collective intelligence technology designed to amplify the diagnostic accuracy of networked human groups by forming real-time systems modeled on biological swarms. Using small groups of radiologists, the swarm-based technology was applied to the diagnosis of pneumonia on chest radiographs and compared against human experts alone, as well as two state-of-the-art deep learning AI models. Our work demonstrates that both the swarm-based technology and deep-learning technology achieved superior diagnostic accuracy than the human experts alone. Our work further demonstrates that when used in combination, the swarm-based technology and deep-learning technology outperformed either method alone. The superior diagnostic accuracy of the combined HITL AI solution compared to radiologists and AI alone has broad implications for the surging clinical AI deployment and implementation strategies in future practice.
Authors
Patel, BN; Rosenberg, L; Willcox, G; Baltaxe, D; Lyons, M; Irvin, J; Rajpurkar, P; Amrhein, T; Gupta, R; Halabi, S; Langlotz, C; Lo, E; Mammarappallil, J; Mariano, AJ; Riley, G; Seekins, J; Shen, L; Zucker, E; Lungren, M
MLA Citation
Patel, Bhavik N., et al. “Human-machine partnership with artificial intelligence for chest radiograph diagnosis.Npj Digit Med, vol. 2, 2019, p. 111. Pubmed, doi:10.1038/s41746-019-0189-7.
URI
https://scholars.duke.edu/individual/pub1422392
PMID
31754637
Source
pubmed
Published In
Npj Digital Medicine
Volume
2
Published Date
Start Page
111
DOI
10.1038/s41746-019-0189-7