FAQs
Precision Oncology - Frequently Asked Questions (FAQ)
What is #KNOWvember
#KNOWvember is Precision Oncology Awareness Month — a national effort to build shared understanding of what precision oncology is, why it matters, and who can benefit from it, and to advocate for a system where everyone who can benefit actually receives it.
It’s about making the science clear, the language simple, and the purpose shared — so patients, caregivers, and clinicians across Canada have the knowledge and tools to ensure that everyone who can benefit gets tested and to champion the policies, resourcing, and system alignment needed to make that possible everywhere.
What is precision oncology?
Precision oncology is a tailored approach to healthcare that uses information about an individual's genetic makeup, environment, and lifestyle to guide decisions about the prevention, diagnosis, and treatment of diseases. In oncology, this includes targeted therapies designed to attack specific genetic mutations in cancer cells.
How does precision oncology work in cancer care?
In cancer care, precision oncology often involves genomic testing to analyze the genetic mutations or alterations in a patient’s tumor. This information helps identify therapies that specifically target these changes, offering treatments that are more effective and less likely to cause unnecessary side effects.
How is precision oncology different from traditional treatments?
Traditional treatments, like chemotherapy, often work by targeting fast-growing cells, which can harm both cancerous and healthy cells, leading to significant side effects. Precision oncology, however, targets specific genetic or molecular changes driving the cancer, making treatments more focused and less damaging to healthy tissue.
Who can benefit from precision oncology?
Patients with cancers driven by specific genetic or molecular changes—such as lung, breast, or certain blood cancers—may benefit most from precision oncology. However, its applications are expanding, and more patients are being identified as candidates for targeted therapies through advanced testing.
What are biomarkers ?
Biomarkers are biological features found in a tumour or in the blood that help us understand what is driving a cancer and which treatments may work — and which may not. They can include things like gene mutations, proteins, receptors, immune markers, and changes in DNA or RNA.
By understanding these biological signals, clinicians can match treatments to the characteristics of each cancer, improving the chances that patients who can benefit from precision oncology receive access to it.
What is biomarker testing?
Biomarker testing analyzes a person’s tumour tissue or sometimes their blood to identify these molecular changes. There are different types of testing — from immunohistochemistry to gene panels, next-generation sequencing, comprehensive genomic profiling, and liquid biopsy — and each plays a role depending on the cancer type and setting.
There is no one “right” test for every situation, but what matters is ensuring people who can benefit from precision oncology are identified and given the opportunity to receive it.
Is biomarker testing the same as genomic or genetic testing?
Biomarker testing, genomic testing, and genetic testing are terms people sometimes use interchangeably, but they mean slightly different things. In cancer care, biomarker testing and genomic testing often refer to the same thing — looking at the biology of the tumour to understand what is driving it and which treatments may help. This can include DNA changes (genomics), but also proteins and other markers.
Genetic testing, however, is different. It looks at the DNA you are born with to understand whether you carry inherited cancer risk.
So while many people say “genomic testing” when they mean tumour biomarker testing, the most accurate umbrella term in precision oncology is biomarker testing, because it includes genomic information along with other important tumour features.
What is genomic testing, and why is it important?
Genomic testing identifies genetic mutations or biomarkers in a patient’s DNA. This information helps healthcare providers choose the most effective treatments for the patient, reducing trial-and-error prescribing and improving outcomes. For example, genomic testing can identify whether a patient’s cancer will respond to a specific targeted therapy.
What is the difference between genetic and genomic testing in cancer care?
Genetic testing in cancer care typically examines specific inherited mutations, like those in the BRCA1 or BRCA2genes, which increase the risk of certain cancers. It helps identify familial cancer syndromes and assess an individual’s inherited risk.
Genomic testing, on the other hand, analyzes the genetic changes (mutations) that occur within the tumor itself. These changes are not inherited but develop over time and drive the cancer’s growth. Understanding these mutations through genomic testing can guide the selection of targeted therapies and improve treatment outcomes.
Why is understanding the difference between genetic and genomic important?
Understanding the difference helps patients and healthcare providers choose the most appropriate tests and interventions. It ensures that diagnostic and treatment decisions are based on the right level of genetic insight.
Who should I talk to about genetic or genomic testing?
Discuss your options with a healthcare professional, such as a genetic counselor or oncologist, who can guide you toward the best approach based on your medical history and needs.
How do I talk to my doctor about biomarker testing?
Asking informed questions can help ensure you're receiving care that reflects current knowledge and standards. We've created a simple guide you can use, whether you're meeting an oncologist for the first time or discussing next steps in your treatment journey.
👉 See our resource: Questions to Ask About Biomarker Testing (link)
How do I know if precision oncology is right for me?
If you or a loved one has cancer, speak with your oncologist about genomic testing and whether targeted therapies might be an option. They can help determine if precision oncology aligns with your specific diagnosis and treatment goals.
Why isn’t access the same everywhere?
Access varies across provinces, hospitals, and practice settings — and that means some people benefit while others do not. Shared understanding helps drive shared access. Part of #KNOWvember is building momentum and alignment so precision oncology isn’t dependent on geography or institution.
Data Sharing and AI in Precision Oncology - Frequently Asked Questions (FAQ)
What is data sharing in precision oncology, and why is it important?
Data sharing in precision oncology means pooling health information from patients—such as genetic profiles, treatment outcomes, and demographics—to create a comprehensive understanding of diseases like cancer. This shared data helps researchers identify patterns and develop targeted treatments, ultimately leading to faster diagnoses and more effective, personalized care for patients.
How does AI (Artificial Intelligence) use shared data to improve cancer care?
AI algorithms analyze massive datasets to spot patterns and predict outcomes more accurately than human analysis alone. In precision oncology, AI can help identify genetic markers associated with specific cancers, predict treatment responses, and assist doctors in making more informed treatment decisions. With shared data, AI becomes a powerful tool for accelerating research and improving patient outcomes.
How does data sharing benefit individual patients?
Shared data provides doctors and researchers with insights based on the experiences of thousands of patients. This knowledge allows healthcare providers to offer more precise diagnoses and personalized treatment options. By sharing data, patients contribute to a collective understanding that leads to better care and targeted therapies for themselves and others facing similar conditions.
What kind of data is shared in precision oncology?
In precision oncology, the types of data shared include genetic information, treatment histories, side effects, and outcomes. Some programs also gather environmental and lifestyle data, as these factors can influence cancer risk and treatment response. All shared data is de-identified, meaning it is stripped of personal details to protect patient privacy.
Why is AI especially helpful for rare or complex cancers?
AI’s ability to analyze large datasets is crucial for rare and complex cancers, where fewer cases make it harder to draw conclusions. By aggregating data from multiple sources, AI can detect trends that might not be apparent in smaller datasets. This helps doctors find effective treatment paths for rare cancers more quickly and with greater confidence.
How is data privacy protected when data is shared?
Data sharing in precision oncology follows strict privacy standards. Before being shared, data is anonymized to remove personally identifiable information. Additionally, data is stored securely, and access is granted only to authorized researchers and healthcare providers. Many initiatives also adhere to regional privacy regulations, such as HIPAA in the U.S. or GDPR in Europe, to ensure patient rights are protected.
Does data sharing only help people with specific types of cancer?
No, data sharing benefits patients across all types of cancer. By analyzing diverse data, researchers can discover biomarkers, understand disease progression, and identify treatments that are effective for various cancers. Precision oncology aims to improve care for all cancer patients, regardless of the type or stage of their disease.
How does data sharing ensure that advances are inclusive of diverse populations?
Data sharing encourages the inclusion of people from different backgrounds, ensuring research is representative and treatments work effectively across diverse populations. This diversity helps identify genetic markers and treatment responses that vary by ethnicity, gender, and other factors. Diverse data also supports health equity by reducing disparities in cancer treatment and outcomes.
What role does AI play in discovering new cancer treatments?
AI accelerates the discovery of new treatments by identifying patterns and predicting outcomes. For example, AI can sift through data to find specific genetic mutations that respond well to certain drugs, helping to develop targeted therapies. AI also helps pharmaceutical companies design more effective clinical trials, bringing new treatments to market faster.
How can patients get involved in data sharing initiatives?
Patients can contribute by participating in clinical trials, joining biobanks, or enrolling in health data-sharing programs through healthcare providers or research institutions. Many of these initiatives allow patients to contribute anonymously, helping advance precision oncology research without compromising privacy.
Can AI make mistakes? If so, how are these addressed?
Yes, AI can make errors, often due to biased or incomplete data. To mitigate this, AI models are rigorously tested, and data scientists review results to ensure accuracy. Transparency is key, and ongoing validation is essential to refine AI algorithms. As data sharing expands, AI becomes more reliable by learning from a larger and more representative dataset.
Inclusion, Diversity, Equity & Access (IDEA) FAQ
What does IDEA mean in the context of precision oncology?
Inclusion, Diversity, Equity, and Access (IDEA) in precision oncology means ensuring that everyone who can benefit from biomarker testing and precision treatments has the opportunity to receive them. This is not yet the reality in Canada. Access varies by geography, care setting, socioeconomic factors, and historical inequities in the health system.
It also means recognizing that certain communities have faced systemic barriers in cancer care. Precision oncology must extend to communities that experience inequities, including racialized and marginalized populations, ensuring they are included in testing, data collection, care pathways, and system planning.
Why does IDEA matter in precision oncology?
Precision oncology has the potential to meaningfully improve outcomes, but this promise is only realized when access is broad, consistent, and fair. When understanding, testing, and treatment are unevenly available, inequities in cancer outcomes can widen. Equity is not just about innovation — it is about implementation. Ensuring diverse communities understand precision oncology and can access it strengthens the quality, reach, and impact of cancer care across Canada.
How does inequitable access show up in cancer care?
Inequities can appear in many ways: delays in diagnosis, limited access to biomarker testing, fewer referrals to specialized centres or clinical trials, uneven access to new therapies, or lack of awareness about testing options.
Sometimes inequities reflect geography or capacity. Other times they reflect structural barriers or historical gaps in trust and communication. Regardless of cause, the outcome is the same: people who could benefit may not receive opportunities for testing or precision treatment.
How does #KNOWvember support IDEA?
#KNOWvember helps build shared understanding of precision oncology by making information clear, accessible, and available to communities across Canada. By focusing on education, awareness, and advocacy, the campaign supports informed conversations and encourages consistent standards in offering testing and discussing treatment options.
This includes amplifying diverse voices, collaborating with patient and community groups, and directing people to resources that can support informed questions and shared decision-making.
How can patients and caregivers support equitable access?
Patients and caregivers play an important role by learning about biomarker testing, discussing it within their communities, and asking questions in care settings. Shared understanding helps normalize conversations about testing and ensures that more people know it exists and why it matters.
Advocacy does not require expertise — it begins with informed questions and confidence in seeking information.
How can clinicians support IDEA in precision oncology?
Clinicians can support equity by initiating biomarker testing conversations consistently, regardless of care setting or patient background. Offering clear explanations, identifying when testing may be appropriate, and connecting patients to referral pathways or second-opinion services when needed all help ensure equitable access. Supporting IDEA is not an added step — it is part of delivering high-quality, evidence-based care.