Updated: Mar 17
What is cancer relapse ?
Cancer relapses between 5 - 20 years for most cancers types. That is why the survival rate is presented as a 5-year survival rate. Although, for some cancer types, the relapse happens early. But why does the cancer relapse? Even after a no evidence of disease (NED) diagnosis, why does the cancer relapse? It has to do with the population biology of the cancer cells. Even though 99.99999% cancer cells can be killed by chemotherapy, immunotherapy, targeted therapy, radiation therapy and combination therapy, still a few cells will survive and will lay dormant. These cells are naturally resistant against the drugs used. This is true for any population. For example, if a deadly virus was to wipe out the human race, there will be a few humans who will be naturally resistant against the most deadliest virus. Therefore, relapse id unavoidable and it is only a matter of time before those cancer cells starts to grow. And that is when the cancer relapse. There are many large scale datasets available from patients that can educate us about the pattern of relapse and disease-free survival. The figure above shows the disease-free survival/relapse-free survival of four different cancer types determined from large datasets.
Factors that should be considered
There are several other factors, which contribute towards early or late relapse. For example, age, sex, previous treatments, hormone receptor status (in some cancers), type and stage of the disease, mutations in the primary cancer, mutation burden etc. can all contribute towards relapse differently. Every patient's cancer profile is unique and different. Fortunately, now there are large scale datasets available, which could help patients learn about the timeline of relapse based on their unique cancer profile. Why is that important? It can immensely help patients in making educated decisions and initiate a meaningful conversation with their doctors about the subsequent management of the disease.
At Cancer Therapies 4 U, one of the things that we offer is bioinformatic analysis of large scale data sets and check how the patient profile best fit in. Such analysis provides an estimate of disease prognosis, which may help the patient to make educated decisions about their treatment approaches.
Author: Anirban Mukherjee, PhD
Scientist, UT Austin
Founder, Cancer Therapies 4 U