We foster dialogue between data scientists and researchers in clinics and laboratories in order to drive excellence in health care research at Stanford.
About the Data Studio
The Data Studio is a collaboration between Spectrum (The Stanford Center for Clinical and Translational Research and Education) and the Department of Biomedical Data Science. The Data Studio is open to the Stanford community engaged in biomedical research. We expect it to have educational value for students and postdocs interested in biomedical data science. The Data Studio features DBDS faculty and staff who offer the following services: workshops, office hours, and one-to-one consultations. When you complete the Data Studio request form, our coordinator and consultants will work with you to choose the right service for your research project. Appointments may be requested by completing the required form.
Workshops are an extensive and in-depth consultation for a Medical School researcher based on research questions, data, statistical models, and other material prepared by the researcher with the aid of our facilitator. During the Data Studio Workshop, the researcher explains the project, goals, and needs. Experts in the related topic from across campus will be invited and contribute to the brainstorming. After the meeting, the facilitator will follow up, helping with immediate action items and summary of the discussion. Ultimately, we strive to pair each PI with a data scientist for long-term collaboration.Office Hours are brief consultations for Medical School researchers during the last session of each month. DBDS faculty are available to advise about your research questions. Consult the schedule below to complete the Office Hour registration form. Once you have registered, you will receive a calendar invitation with the date, time, and location of the session. Bring any data, prior analyses, or other materials that you have. Our consultants may even recommend your project for a Workshop if it is appropriate.
One-to-one consultations for Medical School researchers are available year-round. Our facilitator assigns each request to a data scientist with the relevant expertise.
Partners
General questions about statistical issues may be brought to the STAT390 Consulting Workshop. This is a class offered by the Department of Statistics during each academic quarter that is staffed by graduate students and directed by a faculty instructor. The service typically consists of a single meeting with the researcher to address a specific concern, such as planning of experiments and data analysis. For more information, consult the STAT390 Consulting Workshop web page.
Researchers who are members of the Stanford Cancer Institute (SCI) conducting research projects related to cancer may request assistance from the SCI Biostatistics Shared Resource.
The Genetics Bioinformatics Service Center (GBSC) offers an end-to-end bioinformatics consulting service (BaaS) that provides high performance computational infrastructure and cutting-edge bioinformatics services for the Stanford community. The team consults on genomics, transcriptomics, proteomics, epigenetics, and metabolomics projects, and also develop custom workflows. For consulting and hands-on bioinformatics help with your projects please reach out to gbsc-baas-team@lists.stanford.edu to set up an initial meeting.
Schedule
The Data Studio is held each Wednesday from 3:00 until 4:30 pm during the fall, winter, and spring quarters of the academic year. Consult the schedule below for the location of each session. Students may participate by enrolling in BMDS 291 for an introduction to the art of statistical consultation and practicum working on projects with a biomedical researcher. All are welcome to attend. Click here to sign up for our mailing list.
The currently scheduled topic is listed below.
TITLE: Defining T Cell-Mediated Immune Rejection as a Barrier to Durable CAR T Cell Therapy
INVESTIGATORS:
Maximilian RA Koch (1)
Yiyun Chen (1)
Sabine Heitzeneder (1)
Elena Sotillo (1)
Michelle Monje (1)
Sneha Ramakrishna (1)
Crystal L Mackall (1)
DATE: Wednesday, March 11, 2026
TIME: 3:00–4:30 PM
LOCATION: Room R358, Edwards Building, 300 Pasteur Drive, Stanford, CA (or Zoom Link Below)
ABSTRACT
The Data Studio Workshop brings together a biomedical investigator with a group of experts for an in-depth session to solicit advice about statistical and study design issues that arise while planning or conducting a research project. This week, the investigator(s) will discuss the following project with the group.
INTRODUCTION
Chimeric antigen receptor (CAR) T cell therapy has transformed the care of childhood leukemia and has recently proven well-positioned for the treatment of solid tumors and brain tumors. In this treatment, a patient’s own immune cells are engineered to recognize and attack cancer cells. Despite these successes, CAR T cell therapy often does not provide sufficient durability, especially in solid tumors. Preliminary observations from an ongoing clinical trial testing GD2 CAR T cell therapy for diffuse midline glioma (DMG) at the Stanford Center for Cell Therapy (NCT04196413) demonstrate CAR T cell loss coinciding with the emergence of human anti-CAR antibodies. Robust antibody responses require cognate CD4+ T cell help, suggesting coordinated adaptive immunity against CAR-derived epitopes.
HYPOTHESIS & AIM
We hypothesize that I hypothesize that CAR constructs function as immunogenic neo-antigens that elicit antigen-specific CD4+ and CD8+ T cell responses, which in turn drive immune-mediated rejection and limit therapeutic durability. T cell responses can be measured in blood. Patients’ blood T cells (PBMCs) are tested for responsiveness to CAR-derived peptides. Responses are defined by expression of activation marker and cytokines. CAR-naïve samples (so far only healthy donors) are expected to show no response at all (background).
DATASET
The dataset comprises multiparameter flow cytometry measurements of antigen-specific T cell responses following peptide pool stimulation. While I measured 10 readout parameters, I had defined one primary readout (a-priori-test). Responses for multiple cytokines and activation markers were quantified across 16 partially overlapping peptide pools in peripheral blood samples from 4 healthy controls and 5 treated patients sampled at two timepoints (pre- and post-HACA). Importantly, if there is reactivity to CAR peptides, the different pools are expected to show variable response with most staying negative. Measurements were normalized to DMSO controls, resulting in a hierarchical dataset with repeated observations per patient across stimulation pools and timepoints. The data from 2 Experiments are organized in tidy dataframe and processed in python (pandas).
STATISTICAL MODELS
Group differences in antigen-specific T cell responses were primarily assessed using linear mixed-effects models with group as a fixed effect and patient and peptide pool included as random effects to account for repeated measurements and pool-specific variability. As a complementary analysis, responses were aggregated at the patient level and compared using non-parametric tests to provide a distribution-free assessment of group differences. In addition, antigen-specific responses were operationally defined using a threshold approach (background + 3 standard deviations of healthy controls), and paired t-tests were used to directly compare pre- and post-HACA measurements within patients.
STATISTICAL QUESTIONS
(1) Are my statistical methods to assess anti-CAR T cell immunity (both on a group level as well as on an individual pool:patient level) scientifically sound and justified?
(2) Which of the approaches should I include in a manuscript that is currently in preparation?
(3) In general, should I prefer simpler tests than LMM if the dataset allows it? In other words, are they overpowered and therefore less convincing?
ZOOM MEETING INFORMATION
Join from PC, Mac, Linux, iOS or Android:
https://stanford.zoom.us/j/94497734913?pwd=8Oggacm7IWHQ2L9Yix6P5ArcXZEJZa.1
Password: 988119
Or iPhone one-tap (US Toll):
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or
+1 833 302 1536 (US, Canada, Caribbean Toll Free)
Meeting ID: 944 9773 4913
Password: 988119
International numbers available: https://stanford.zoom.us/u/axKLcm1v2
Meeting ID: 944 9773 4913
Password: 988119
Password: 988119