Precision Oncology and Systems Biology

Identifying novel diagnostics and therapies for the most challenging cancers requires systems-level analysis of the molecular, cellular, and physiologic processes underlying tumor initiation, metastatic progression, and drug resistance. The Precision Oncology and Systems Biology (POSB) program brings together multidisciplinary teams of HICCC members with expertise in experimental and computational systems biology, translational science, and clinical oncology to tackle and solve these complexities, advancing the HICCC’s strategic focus on fostering impactful discovery science, accelerating translation into innovative clinical and population science research.

Major research themes 

Investigators in this program combine single-cell genomics, multi-modal imaging, and sophisticated cancer models with computational methods to interrogate high-dimensional datasets, allowing them to address challenges in cancer treatment including tumor heterogeneity, plasticity, and drug responses in complex tissues. Physician-scientists and systems biologists in this program collaborate to translate pre-clinical systems biology findings and bring genomic analyses and computational modeling to investigator-initiated trials.

  • Model systems and computational approaches
  • Precision clinical trials and system-based analysis

Within these themes, the program elucidates the mechanisms of tumor initiation, plasticity, metastasis, and therapeutic response, defining the mechanisms of novel and existing drugs, developing novel endpoints for clinical trials, using systems biology and single-cell genomics, and interrogating human tumor biology through systems-based analyses of clinical samples.

Current projects

The program has a number of exciting studies underway, including an innovative, RNA-based N-of-1 clinical trial at Columbia focused on identifying key vulnerabilities of any human malignancy and the drugs with the greatest potential to benefit the patients. Other projects under POSB center on single-cell algorithms and their use in direct analysis of tumor heterogeneity for combination therapies and exploring targeted therapeutic intervention in glioblastoma.

Leadership