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Related Concept Videos

Tumor Immunotherapy01:27

Tumor Immunotherapy

596
Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
596
Cancer Vaccines01:30

Cancer Vaccines

456
Cancer treatment vaccines are a rapidly evolving field that offers a promising approach to immunotherapy. Unlike traditional vaccines that prevent diseases, cancer treatment vaccines are designed to treat existing cancers by stimulating the immune system to recognize and attack cancer cells.
Cancer vaccines come in two categories: preventive (prophylactic) and treatment (active). Preventive vaccines, such as the Human Papillomavirus (HPV) vaccine, protect against viruses that cause certain...
456
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
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Converging on a Cure: The Roads to Predictive Immunotherapy.

Genevieve L Stein-O'Brien1,2,3,4,5, Dung T Le1,3,6, Elizabeth M Jaffee1,3,6

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New forecast systems integrate diverse expertise to predict tumor-immune evolution during cancer progression. These advances aim to personalize cancer immunotherapy for lasting patient benefits.

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Area of Science:

  • Oncology
  • Immunology
  • Computational Biology
  • Translational Medicine

Background:

  • Tumor evolution and immune interactions dynamically change during cancer progression.
  • Predicting these changes is crucial for effective cancer treatment.
  • Current therapeutic strategies often lack personalization for dynamic tumor states.

Purpose of the Study:

  • To develop advanced forecast systems for monitoring tumor-immune dynamics.
  • To enable a predictive medicine approach for cancer therapy.
  • To personalize immunotherapeutic regimens based on real-time tumor and immune status.

Main Methods:

  • Integrating clinical, biological, engineering, and computational expertise.
  • Developing novel computational models for forecasting evolutionary changes.
  • Utilizing systems biology approaches to understand tumor-immune interactions.

Main Results:

  • Successful invention of new forecast systems for tumor-immune interactions.
  • Demonstrated ability to monitor and predict evolutionary dynamics.
  • Established a foundation for personalized adaptive immunotherapies.

Conclusions:

  • Convergence science is key to advancing cancer prediction and treatment.
  • New forecast systems offer a paradigm shift towards predictive medicine.
  • Personalized, adaptive immunotherapies hold promise for durable patient responses.