One of the most confusing parts of cancer treatment is how two people can have the same cancer, receive the same therapy and have totally different experiences. What may work for one person might not work at all for another. I touched on this concept in my last blog post but now I’d like to introduce one of the biggest challenges in cancer research and treatment: heterogeneity. In simple terms, heterogeneity just means “differences.” Whether it’s between people, tumours or even within one tumour, cancer has it all. Understanding the different types of heterogeneity helps explain why cancer treatment is rarely one-size-fits all and the importance of precision medicine! In the world of drug development, our job is to understand these layers so we can design treatments that match the right drug to the right patient and the right features of their cancer.
The first type is interpatient heterogeneity, or the biological and genetic differences seen between people. On paper, two patients might have the same diagnosis and treatment. However, their bodies might process that treatment differently. Age, organ function, other medications or illnesses and even our genes can influence how drugs are absorbed, transported and cleared from the body. As a result, a treatment that works well for one person may provide little benefit or even cause side effects in another.
One neat example (neat for scientists, less neat for patients) of how drugs are processed differently is the breast cancer drug tamoxifen, and a drug-metabolizing enzyme in our livers called cytochrome P450 2D6 or CYP2D6 for short. CYP2D6 helps the body convert tamoxifen into endoxifen, which is the active form of tamoxifen that fights cancer. In some people, CYP2D6 is less active, meaning they may not get the same benefit from tamoxifen as someone whose CYP2D6 works at full speed. In the world of precision medicine, studying how our DNA influences our responses to drugs is called pharmacogenomics, and it has the potential to help us better match the right drug and dose to the right person.
The second type of heterogeneity is intertumoral heterogeneity, which refers to the differences between tumours in different people or between tumours within one person. From a bird’s eye view, two people may both have breast cancer, but their tumours can be driven by different combinations of mutations, rely on different signals or live in different environments within the breast tissue. Now zoom in on a single person whose cancer has spread through the body, a process called metastasis. Interestingly, a metastatic tumour isn’t just a copy-paste of the original tumour. To grow in a new location, the cancer cells must adapt to a new environment with different nutrients and challenges. As they travel through the body, cancer cells can acquire new mutations that allow them to grow faster or resist treatments that once worked. The result is that tumours from different patients, and even within the same patient, can respond very differently to the same therapy. This is one reason why you may see some tumours shrink on a scan, while others aren’t impacted at all by the same treatment.
Finally, the third type of heterogeneity is intratumoral heterogeneity, which looks at differences within a tumour itself. When you think of a tumour, you may think of one big uniform blob of cancer cells. But under the microscope, a tumour is more like a mini ecosystem with many different groups of cells with their own resources and habits. There can even be different types of cancer cells within a tumour! They may carry different mutations or rely on different survival tricks. As a tumour grows, new populations of cells can emerge that are a little tougher, sneakier or more resistant than their neighbours. What this means is that even within one tumour, not all cells may respond the same way to a therapy. This is the challenge that modern targeted drug development is trying to solve: designing treatments that can find and hit the right cells in this patchwork, instead of treating every tumour as if it were the same.
In my next blog post, we’ll talk about one of the most challenging cells to target in this patchwork: cancer stem cells!
Illustration by Pixeliota on Unsplash
