Treatment resistance to cancer therapy may be a difficult task in a patient''s clinical journey, but it may be addressed with combination therapy or personalized medicine.
OncoHost offers patients with patient-specific information to tailor treatment strategies to each individual, reducing the likelihood of treatment resistance occurring. Proteomic analyses and AI-driven technology provide insight into how a patient will respond to treatment, providing the patient with the information they need to take them to the driver seat of their care journey.
Katie Brighton (KB): Can you tell us about how personalized oncology treatments have evolved in the last decade? How has this altered the patient experience?
Over the years, drug-based anti-cancer therapy has evolved from a non-specific carpet bombing approach to targeted therapies biologic therapies that target specific cancer cells that harbor driver mutations. In addition, there has been a spike in immunotherapies used in the clinic.
Immunotherapy is a new type of anti-cancer therapy that activates the patient''s immune response to the cancer. Targeted therapies offer improved response rates with a different set of adverse events, in that patients are longer-lived at treatment and are more likely to respond well. Despite this approach to cancer management, immunotherapy also greatly improves clinical outcomes.
One problem with targeted therapies is that they are only applicable to a minority of patients for whom driver mutations may be identified. At some point during treatment, the patients may experience a cancer resistance breakthrough and they eventually stop responding to their given treatment. This issue stems from the inability to pre-emptively determine which patient will respond and benefit from the course of treatment, including frustration, frustration, and uncertainty.
How does cancer patients treat treatment resistance? Are certain cancer types more likely to become treatment-resistant? How do we deal with this?
OS: Treatment resistance is a multifactorial process. When cancer cells have a specific molecular trait that is likely to be resistant to a specific medication due to biological mechanisms linked to the body''s response. This phenomenon, known as host response, is one of the main reasons for today''s treatment resistance.
Resistance mechanisms are typically varied and non-specific to certain cancer types, and may present themselves as primary resistance, intrinsic resistance, or acquired resistance. Combination therapies are well-known approaches used to mitigate treatment resistance. Additionally, personalized medicine is a way to use the patient''s specific needs rather than adopting a one-size-fits-all therapy protocol.
KB: What benefits do proteomics analysis and artificial intelligence (AI) offer to understanding which treatment is optimal for the patient?
Proteins are the building blocks and drivers of biological processes in our bodies. We can improve on the complex interaction of the tumor, the therapy, and the host (patient). This complex biological interaction involves intrinsic cancer cell traits with the body''s host response to therapy and is the basis for treatment resistance.
Thousands of proteins exist in the body, and research to understand these protein levels and dynamics requires advanced mathematical and bioinformatic techniques. We can meet three clinical questions by combinating plasma protein analysis with machine learning techniques.
1.Will the patient be able to respond?
2.Why is there resistance?
3.What may be the next type of therapy?
This combination analysis is done in full, including that it is very personalized, specific and beneficial to each individual patient.
How does OncoHost assist patients in making decisions on their treatment plan?
OS: We provide oncologists with insights on the response probability for individual patients for the first year of treatment, along with analysis of the biological pathways involved in resistance, and the identification of potentially resistant proteins. We also provide guidance on therapeutic interventions that are aimed at those resistant proteins. This analysis allows us to intervene early and assist the clinical decision-making process with a significant improvement in scope of knowledge.
Are there any considerations to be taken into account when it comes to managing patient information?
As with any other type of personal health information, we must adhere to the principles set by legislation, patient privacy standards, and best practices, according to the OS. HIPAA and GDPR are good examples of these measures.
KB: Where will your computer screen record personalized therapy in the near future?
Diagnostics will be based on several assessments across the disease''s continuum in the future. I believe that the data to identify these factors and guide clinical decisions will be based on multiomic analysis at different times in time. This will allow for clinical decisions to be individualized for each individual patient.