The Technological Drivers Powering Precision Oncology

Previously, we talked about some of the factors that will enhance the adoption of precision oncology. But at its core, precision oncology utilizes a powerful toolbox of technologies that have fundamentally transformed how we understand, diagnose, and treat cancer.  In this blog, we’ll explore the key technological drivers that will propel the field of precision oncology forward.

1. Next-Generation Sequencing (NGS): Super-powered Gene Readers

Imagine NGS as a super-powered instruction decoder for cancer cells. It can quickly and accurately read the instructions (genes) inside them, revealing the specific mistakes (mutations) causing the tumor to grow. By knowing the specific genes that are mutated, doctors can choose treatments that target those weaknesses more effectively. NGS can also analyze how active all your genes are (called RNASeq), giving doctors a broader picture of the biological processes happening within your tumor.

2. Single-Cell Analysis: Unveiling Hidden Diversity

Cancer isn’t a simple disease. It’s more like a complex ecosystem. Inside a tumor, there are different types of cells, including cells that nourish cancer cells, immune cells, and cells that line blood vessels. Each cell type has unique characteristics, and the characteristics of these cells can affect the tumor’s growth properties. What makes the ecosystem even more complex is that there can be a lot of variation in cells that are the same type. For example, cancer cells in one area of the tumor may have very different characteristics than cancer cells in another region. The presence of these diverse cell populations is called tumor heterogeneity. Tumor heterogeneity is a challenge because a one-size-fits-all treatment might not work for all the different cell types.

To address this, scientists have developed ways to study these cell types individually. This helps them find rare groups of cancer cells that might be tougher to treat. With this knowledge, doctors can create more personalized treatments that target the specific needs of each patient’s tumor.

3. Artificial Intelligence and Machine Learning

There are subtle differences between artificial intelligence (AI) and machine learning (ML). Put simply, imagine AI as a super-smart computer program that can learn and act like a human in some ways. It can be programmed to follow complex rules and make decisions based on those rules. Think of ML as a tool within AI that helps the computer learn on its own from data. You feed it a lot of information, like pictures of cats and dogs, and it learns to tell the difference without needing specific rules for each type of animal.

Doctors and scientists are benefitting greatly from AI and ML. AI can sift through massive amounts of information about your genes, medical history, and scans. Using information from past patients, AI can be used to identify unknown connections between your genes, the tumor’s molecular features, and the effects of treatment. This helps doctors figure out which treatments might work best for you.

In a future blog, we will provide more detail on how AI and ML are being applied to advance Precision Oncology.

4. Liquid Biopsies: Blood Tests for Cancer

In the past, checking a tumor’s genes meant taking a small piece of it. Now, there’s a simpler option called a liquid biopsy. These tests analyze fragments of DNA, RNA, and proteins shed by tumors into the bloodstream. This way, doctors can learn about your tumor’s genes without any invasive procedures, and even get real-time updates on how the tumor is responding to treatment. That way, doctors can make more timely decisions on when and how to change their treatment strategy.

5. Imaging Technologies

Advanced imaging technologies, such as positron emission tomography (PET), magnetic resonance imaging (MRI), and computed tomography (CT), have become a cornerstone of precision oncology. These technologies provide a detailed view of tumors, revealing their size, shape, and even biological characteristics. But there’s a new game-changer on the block: radiomics.

With radiomics, the regular pictures from imaging tests are analyzed by a supercomputer. The computer then analyzes millions of tiny details in the picture, things our eyes can’t even see. By looking at these details, radiomics can help doctors understand more about the tumor, like how fast it’s growing or how well it’s responding to treatment. It might even help them find smaller tumors that might be missed otherwise. This is a new and exciting way for doctors to get a more complete picture of what’s going on inside your body.

6. CRISPR Gene Editing: Rewriting the Code

CRISPR technology has revolutionized our ability to precisely modify genes. In the realm of precision oncology, CRISPR offers the potential to correct or disable cancer-causing mutations, opening up new avenues for therapeutic intervention.  This is exciting because it could lead to new ways to treat cancer. Scientists can also use CRISPR to see which genes are essential for cancer cells to survive. By understanding these genes, they can develop treatments that target those weaknesses and kill cancer cells more effectively

7. Telemedicine and Remote Monitoring: Care from Anywhere

Getting expert cancer care used to mean lots of trips to the hospital. This is a challenge for people who live in remote communities. Now, thanks to telemedicine, you can talk to cancer specialists from the comfort of your own home! A doctor’s visit takes place over a video call. Remote monitoring technologies, like smartwatches, can keep track of your health throughout the day. This enables doctors to monitor vital signs and detect potential issues early on.

8. Building the Future: Data Integration and Knowledge Platforms

To make the diagnostic tools of the future, we need data. That includes data about patients (age, health history, etc.), what treatments have been received, how well those treatments worked, and the molecular characteristics of patients’ cancers.

Data availability has exploded in recent years. Much of this has been the result of cooperation between cancer researchers, clinicians and cooperative groups. It’s important to keep everyone’s information private, so there are strict rules in place.

To make sense of all this information, scientists use powerful computers to sort it, organize it, and find patterns. The platforms used for this work – powered by cloud computing and advanced data analytics (AI and ML) – help gather different kinds of information from various sources, so that scientists and doctors can generate important ideas and come up with new ways to address the Cancer Problem.

Importantly, scientists have developed new and better tools to make sense of the reams of data. Data can be organized in a more accessible format, and patterns in the data can be found more easily. These patterns can be used to find subtypes of cancer, including subtypes that are vulnerable to specific treatments.

In conclusion, the remarkable advancements in technology have fueled the progress of precision oncology. This arsenal of tools empowers doctors to make more accurate diagnoses, tailor treatments, and monitor patient responses in real-time. As technology continues to evolve, so too will our ability to fight cancer with ever-increasing precision, offering renewed hope to patients worldwide.