I am an instructor in medical oncology in the lymphoma group at Stanford. After a career in software development, I pursued training first in computational genomics and then in clinical medicine. My primary clinical interest is the detection, treatment, and surveillance of lymphomas. My current line of research as a member of the Alizadeh lab is focused on novel approaches to cell-free DNA. As a faculty member in the lymphoma group, I treat all lymphoma subtypes with a special emphasis on Hodgkin lymphoma and follicular lymphoma.
Instructor, Medicine - Oncology
Honors & Awards
2017 Cancer Fellow, Stanford Cancer Institute (2017)
Abstract Achievement Award, American Society of Hematology (2018)
ACP Award for Excellence in Internal Medicine, University of Hawaii John A. Burns School of Medicine (2015)
Alpha Omega Alpha, University of Hawaii John A. Burns School of Medicine (2014)
Gold Humanism Honor Society, University of Hawaii John A. Burns School of Medicine (2013)
Merit Achievement Scholarship, University of Hawaii John A. Burns School of Medicine (2012)
Current Research and Scholarly Interests
I am a medical oncology & hematology fellow at Stanford University planning to pursue a career in academic oncology focused on molecular cancer diagnostics. After a career in software development, I pursued training first in computational genomics and then in clinical medicine. My primary clinical interest is the detection, treatment, and surveillance of lymphomas. My current line of research as a member of the Alizadeh lab is focused on novel approaches to cell-free DNA including viral and immune dynamics and fragmentation analysis.
Graduate and Fellowship Programs
Hematology (Fellowship Program)
Oncology (Fellowship Program)
- Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA CANCER DISCOVERY 2019; 9 (4): 500–509
Circulating tumor DNA analysis for detection of minimal residual disease after chemoradiotherapy for localized esophageal cancer.
Biomarkers are needed to identify patients at risk of tumor progression following chemoradiotherapy for localized esophageal cancer. These could improve identification of patients at risk for cancer progression and selection of therapy.We performed deep sequencing (CAPP-Seq) analyses of plasma cell-free DNA collected from 45 patients before and after chemoradiotherapy for esophageal cancer, as well as DNA from leukocytes, and fixed esophageal tumor biopsies collected during esophagogastroduodenoscopy. Patients were treated from May 2010 through October 2015; 23 patients subsequently underwent esophagectomy and 22 did not undergo surgery. We also sequenced DNA from blood samples from 40 healthy individuals (controls). We analyzed 802 regions of 607 genes for single-nucleotide variants previously associated with esophageal adenocarcinoma or squamous cell carcinoma. Patients underwent imaging analyses 6-8 weeks after chemoradiotherapy and were followed for 5 years. Our primary aim was to determine whether detection of circulating tumor DNA (ctDNA) following chemoradiotherapy is associated with risk of tumor progression (growth of local, regional, or distant tumors, detected by imaging or biopsy).The median proportion of tumor-derived DNA in total cell-free DNA before treatment was 0.07%, indicating that ultrasensitive assays are needed for quantification and analysis of ctDNA from localized esophageal tumors. Detection of ctDNA following chemoradiotherapy was associated with tumor progression (hazard ratio, 18.7; P<.0001), formation of distant metastases (hazard ratio, 32.1; P<.0001), and shorter disease-specific survival times (hazard ratio, 23.1; P<.0001). A higher proportion of patients with tumor progression had new mutations detected in plasma samples collected after chemoradiotherapy than patients without progression (P=.03). Detection of ctDNA after chemoradiotherapy preceded radiographic evidence of tumor progression by an average of 2.8 months. Among patients who received chemoradiotherapy without surgery, combined ctDNA and metabolic imaging analysis predicted progression in 100% of patients with tumor progression, compared with 71% for only ctDNA detection and 57% for only metabolic imaging analysis (P<.001 for comparison of either technique to combined analysis).In an analysis of cell-free DNA in blood samples from patients who underwent chemoradiotherapy for esophageal cancer, detection of ctDNA was associated with tumor progression, metastasis, and disease-specific survival. Analysis of ctDNA might be used to identify patients at highest risk for tumor progression.
View details for DOI 10.1053/j.gastro.2019.10.039
View details for PubMedID 31711920
- Lymphoma Virome Dynamics Revealed By Cell-Free DNA Sequencing AMER SOC HEMATOLOGY. 2018
- Noninvasive Genotyping and Monitoring of Classical Hodgkin Lymphoma AMER SOC HEMATOLOGY. 2018
- Distinct Chromatin Accessibility Profiles of Lymphoma Subtypes Revealed By Targeted Cell Free DNA Profiling AMER SOC HEMATOLOGY. 2018
Detection and surveillance of bladder cancer using urine tumor DNA.
Current regimens for the detection and surveillance of bladder cancer (BLCA) are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage BLCA who either had urine collected prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per BLCA patient and observed surprisingly frequent mutations of the PLEKHS1 promoter (46%), suggesting these mutations represent a useful biomarker for detection of BLCA. We detected utDNA pre-treatment in 93% of cases using a tumor mutation-informed approach and in 84% when blinded to tumor mutation status, with 96-100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, p=0.02) and cytology and cystoscopy combined (p is less than or equal to 0.006), detecting 100% of BLCA cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of BLCA.
View details for PubMedID 30578357