Vali Barsan, MD is a clinical fellow in the Division of Pediatric Hematology and Oncology at the Lucile Packard Children's Hospital, Stanford University School of Medicine. Dr. Barsan obtained his BS in bioengineering at UC San Diego Jacobs School of Engineering prior to developing Next Generation Sequencing tools as an engineer at Illumina. He earned his MD at Baylor College of Medicine and completed pediatrics residency at UC San Diego. At Stanford, he is focused on expanding the utility of immunotherapy in pediatric and adult cancers through the use of molecular techniques that both inform personalized therapy and trend response to treatment.

Clinical Focus

  • Fellow
  • Pediatric Hematology-Oncology
  • Cancer Immunology and Immunotherapy

Honors & Awards

  • Anne T. and Robert M. Bass Endowed Fellow, Stanford Maternal and Child Health Research Institute (MCHRI) (2019 -)

Professional Education

  • Residency, UC San Diego, Pediatrics (2018)
  • MD, Baylor College of Medicine (2015)
  • BS, UC San Diego, Bioengineering (2009)

Research & Scholarship

Current Research and Scholarly Interests

Adoptive T cell immunotherapy entails engineering immune cells to recognize cancer-specific antigens and target them for destruction. Barriers to efficacy can arise from both tumor antigen related as well as T cell related features. I am interested developing noninvasive molecular tools that enable us to understanding these relationships to improve the clinical application and development of cellular immunotherapeutics.


All Publications

  • Toward a comprehensive view of cancer immune responsiveness: a synopsis from the SITC workshop. Journal for immunotherapy of cancer Bedognetti, D., Ceccarelli, M., Galluzzi, L., Lu, R., Palucka, K., Samayoa, J., Spranger, S., Warren, S., Wong, K., Ziv, E., Chowell, D., Coussens, L. M., De Carvalho, D. D., DeNardo, D. G., Galon, J., Kaufman, H. L., Kirchhoff, T., Lotze, M. T., Luke, J. J., Minn, A. J., Politi, K., Shultz, L. D., Simon, R., Thorsson, V., Weidhaas, J. B., Ascierto, M. L., Ascierto, P. A., Barnes, J. M., Barsan, V., Bommareddy, P. K., Bot, A., Church, S. E., Ciliberto, G., De Maria, A., Draganov, D., Ho, W. S., McGee, H. M., Monette, A., Murphy, J. F., Nistico, P., Park, W., Patel, M., Quigley, M., Radvanyi, L., Raftopoulos, H., Rudqvist, N., Snyder, A., Sweis, R. F., Valpione, S., Butterfield, L. H., Disis, M. L., Fox, B. A., Cesano, A., Marincola, F. M., Society for Immunotherapy of Cancer (SITC) Cancer Immune Responsiveness Task Force and Working Groups 2019; 7 (1): 131


    Tumor immunology has changed the landscape of cancer treatment. Yet, not all patients benefit as cancer immune responsiveness (CIR) remains a limitation in a considerable proportion of cases. The multifactorial determinants of CIR include the genetic makeup of the patient, the genomic instability central to cancer development, the evolutionary emergence of cancer phenotypes under the influence of immune editing, and external modifiers such as demographics, environment, treatment potency, co-morbidities and cancer-independent alterations including immune homeostasis and polymorphisms in the major and minor histocompatibility molecules, cytokines, and chemokines. Based on the premise that cancer is fundamentally a disorder of the genes arising within a cell biologic process, whose deviations from normality determine the rules of engagement with the host's response, the Society for Immunotherapy of Cancer (SITC) convened a task force of experts from various disciplines including, immunology, oncology, biophysics, structural biology, molecular and cellular biology, genetics, and bioinformatics to address the complexity of CIR from a holistic view. The task force was launched by a workshop held in San Francisco on May 14-15, 2018 aimed at two preeminent goals: 1) to identify the fundamental questions related to CIR and 2) to create an interactive community of experts that could guide scientific and research priorities by forming a logical progression supported by multiple perspectives to uncover mechanisms of CIR. This workshop was a first step toward a second meeting where the focus would be to address the actionability of some of the questions identified by working groups. In this event, five working groups aimed at defining a path to test hypotheses according to their relevance to human cancer and identifying experimental models closest to human biology, which include: 1) Germline-Genetic, 2) Somatic-Genetic and 3) Genomic-Transcriptional contributions to CIR, 4) Determinant(s) of Immunogenic Cell Death that modulate CIR, and 5) Experimental Models that best represent CIR and its conversion to an immune responsive state. This manuscript summarizes the contributions from each group and should be considered as a first milestone in the path toward a more contemporary understanding of CIR. We appreciate that this effort is far from comprehensive and that other relevant aspects related to CIR such as the microbiome, the individual's recombined T cell and B cell receptors, and the metabolic status of cancer and immune cells were not fully included. These and other important factors will be included in future activities of the taskforce. The taskforce will focus on prioritization and specific actionable approach to answer the identified questions and implementing the collaborations in the follow-up workshop, which will be held in Houston on September 4-5, 2019.

    View details for DOI 10.1186/s40425-019-0602-4

    View details for PubMedID 31113486

  • Long-term follow-up and pregnancy after complete sacrectomy with lumbopelvic reconstruction: case report and literature review BMC PREGNANCY AND CHILDBIRTH Barsan, V. V., Briceno, V., Gandhi, M., Jea, A. 2016; 16: 1


    Sacrectomy remains a technically complex procedure for resection of malignant pelvic neoplasia. Commonly, postoperative complications include permanent neurological deficits. Only a few studies have reported the long-term functional outcomes of patients who had undergone sacrectomy.We previously reported on the utilization of complete sacrectomy and lumbopelvic reconstruction for the management of primary myofibroblastic sarcoma of the sacrum and ilium in a 15-year-old female patient. In this report, we update her postoperative course with an additional 5 years of follow-up and Health-Related Quality of Life (HRQoL) outcomes. During this time period, she gave birth to two healthy full-term babies.To the best of our knowledge, this is the first report of pregnancy after total sacrectomy and lumbopelvic reconstruction. We outline some of the challenges in the obstetrical management of this patient.

    View details for PubMedID 26728010

  • A novel embryonic plasticity gene signature that predicts metastatic competence and clinical outcome SCIENTIFIC REPORTS Soundararajan, R., Paranjape, A. N., Barsan, V., Chang, J. T., Mani, S. A. 2015; 5: 11766


    Currently, very few prognosticators accurately predict metastasis in cancer patients. In order to complete the metastatic cascade and successfully colonize distant sites, carcinoma cells undergo dynamic epithelial-mesenchymal-transition (EMT) and its reversal, mesenchymal-epithelial-transition (MET). While EMT-centric signatures correlate with response to therapy, they are unable to predict metastatic outcome. One reason is due to the wide range of transient phenotypes required for a tumor cell to disseminate and recreate a similar histology at distant sites. Since such dynamic cellular processes are also seen during embryo development (epithelial-like epiblast cells undergo transient EMT to generate the mesoderm, which eventually redifferentiates into epithelial tissues by MET), we sought to utilize this unique and highly conserved property of cellular plasticity to predict metastasis. Here we present the identification of a novel prognostic gene expression signature derived from mouse embryonic day 6.5 that is representative of extensive cellular plasticity, and predicts metastatic competence in human breast tumor cells. This signature may thus complement conventional clinical parameters to offer accurate prediction for outcome among multiple classes of breast cancer patients.

    View details for PubMedID 26123483

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