The computational research endeavors at CSI-Cancer are centered on three key areas: disease forecasting, therapy efficacy, and survival prediction. By focusing on disease forecasting, the team aims to predict disease progression and potential relapses, enabling proactive and timely interventions. Research on therapy efficacy evaluates how well treatments work for different patient groups, identifying the most effective therapies and minimizing side effects. Survival prediction models estimate patient outcomes based on various clinical and molecular factors, helping tailor personalized treatment plans. By advancing these specific areas, CSI-Cancer aims to develop effective, individualized treatment strategies that improve patient outcomes and quality of life.

Our work is transforming how we understand and manage cancer metastasis, bringing hope for more effective treatments and better patient care. Here’s how our work is transforming patient care:

 

1. Predicting How Cancer Spreads

  • Bladder Cancer: We’ve developed an innovative online tool to predict how bladder cancer spreads over time. By analyzing patient data, including genetics and imaging, our platform helps doctors tailor treatments to individual patients, leading to better outcomes.
  • Breast Cancer: For patients with inflammatory breast cancer, our advanced model predicts the likelihood and timing of bone metastasis. This helps doctors intervene earlier and more effectively to prevent the spread of cancer to bones.
  • Lung Cancer: In non-small cell lung cancer with specific genetic mutations, brain metastasis often follows lung metastasis. Our research highlights this pattern, emphasizing the importance of monitoring lung metastases to prevent the spread to the brain.

2. Predicting Patient Survival

  • Bladder Cancer: Using cutting-edge machine learning, we can predict the likelihood of cancer returning and patient survival after bladder cancer surgery. These personalized predictions help guide follow-up care and improve patient management.

3. Assessing Therapy Effectiveness

  • Breast Cancer: We developed a model to predict how well patients with advanced breast cancer will respond to a specific drug (CDK4/6 inhibitors). This helps doctors choose the best treatment plans for individual patients, increasing the chances of successful outcomes.

4. Monitoring Symptoms

  • COVID-19: Our models predict the onset and progression of COVID-19 symptoms, taking into account different viral variants. This helps with early detection, timely interventions, and understanding how different strains of the virus affect symptom development.

 

Our research is revolutionizing the way we understand and treat cancer. By predicting disease spread, survival rates, therapy response, and symptom progression, we are empowering doctors with powerful tools to personalize treatments, improve patient outcomes, and intervene early when it matters most. Together, we are working towards a future where every cancer patient receives the best possible treatment tailored to their unique needs.