Stanford
Research to the People

Research

Our Approach

Enhancing Personalized Cancer Treatment through Patient-Centered, Innovative, Cutting-Edge, Data-Driven, Multidisciplinary, and Open Data Access Strategy.

Our program adopts an integrated and multidisciplinary approach that leverages longitudinal multiomics data in conjunction with clinical information to drive personalized cancer treatment. We engage a diverse group of experts, including biologists, oncologists with expertise in precision health, pharmacists, bioinformaticians with advanced skills in multi-omics analysis, computer scientists, patients, patient advocates, and caregivers. By connecting bench-side research to bedside care and incorporating a wide range of data sources, we strive to achieve a comprehensive understanding of each patient's cancer and provide actionable insights to the patient's medical team for personalized treatment decisions. Some of the key data sources we utilize include:

  • Genomic Data: We analyze a patient's DNA to identify cancer-associated mutations or genetic variants that inform targeted treatment approaches.
  • Transcriptomic Data: By studying the RNA molecules produced by a patient's cells, we gain insights into gene expression patterns, aiding in the identification of potential therapeutic targets.
  • TCR (T-cell receptor), HLA (human leukocyte antigen), and neoantigen characterization: TCR , HLA , and neoantigen characterization are vital in cancer therapy. TCR recognizes antigens presented by HLA molecules, enabling immune targeting of cancer cells. Neoantigens, unique to cancer cells, guide T-cell response. Understanding and characterizing these factors enhance personalized treatment and immunotherapy development, harnessing the immune system's power against cancer.
  • Proteomic Data: Analyzing the proteins expressed by a patient's cells allows us to delve into cellular functions and signaling pathways, facilitating the development of tailored treatment strategies.
  • Metabolomic Data: We examine the small molecules produced by a patient's cells, providing valuable information about metabolic pathways and cellular processes relevant to cancer progression.
  • Imaging Data: Incorporating data from various imaging tests, such as CT scans or MRIs, helps us visualize tumor characteristics, size, and location, enabling precise treatment planning.
  • PBMC CyTOF Data: Our program utilizes cutting-edge PBMC CyTOF analysis to assess immune cells within a patient's blood. This detailed immune cell profiling informs the development of personalized treatments that target specific immune cell populations involved in the patient's cancer. Moreover, PBMC CyTOF data enables us to monitor treatment response and disease progression by tracking changes in the immune system over time.
  • Establishment of primary patient-derived cancer cell lines: Primary patient-derived cancer cells (PDCs) are cells directly derived from tumor samples of cancer patients. They maintain the characteristics and molecular profile of the original tumor, making them valuable for studying cancer biology and developing personalized therapies.
  • Electronic Health Records (EHRs): By leveraging patients' medical records, including their history, medications, and treatment records, we gain valuable insights into their overall health status, contributing to personalized treatment decisions.
  • Patient-Reported Outcomes: We prioritize patient-reported outcomes to understand their symptoms, quality of life, and other health-related aspects. Incorporating their perspectives allows us to tailor treatments to meet their individual needs.

By integrating and analyzing these diverse data sources, our program creates a holistic and comprehensive understanding of each patient's cancer. This knowledge empowers us to develop highly personalized treatment plans, optimizing outcomes, and improving the overall cancer care experience.