Oncology for Biostatisticians - PD-1 vs PD-L1
Avoiding mistakes with understanding the PD-1 and PD-L1 labels in Biostatistics datasets and their Biology
Darko Medin
3/21/20242 min read
Immuno-Oncology is one of the most important Oncology fields today and Biostatisticians play a key role in its Research, especially in Immuno-Oncology clinical trials.
Labels such as PD-1 and PD-L1 will end up in the Oncology datasets very frequently and is important to understand them. One of the biggest mistakes of a Statistician would be mixing or misunderstanding these terms.
Only 1 letter of difference but a huge Biological difference. PD-1 is a receptor found on T and B cells and stands for programmed death or apoptosis. Its pathway is associated with programmed cell death of cancer cells mediated by T cells. However cancer cells often express a ligand called PD-L1 to block the PD-1 receptor on T cells and evade their immune response. This is just one of the way of cancer cell immune evasion and is critical to designing novel Immuno-Oncology treatments, usually antibodies to counter the effect of PD-L1 ligand by Biotech companies.
The interaction between PD-1 and PD-L1 is what reduces the immune response by the T cells and other cells towards cancer cells. This interaction can be blocked by using antibodies that bind either to PD-1 or PD-L1 or both.
If you see these in the datasets : Pembrolizumab or Keytruda
Nivolumab or Opdivo
Cempilimab or Libtayo
They belong to the class of PD-1 inhibitors or antibodies that bind to PD-1, thus blocking the interaction between cancer PD-L1 ligands and PD-1 receptors on T cells, enabling immune response.
If you see these in the datasets : Atezolizumab or Tecentriq
Avelumab or Bevencio
Durvalumab or Imfinzi
These block the interaction by binding to PD-L1 on cancer cells.
Very important : Don't confuse the PD-1 as a receptor on T cells and the PD-L1 as a ligand that binds to that receptor. You may encounter these terms frequently in Immuno-oncology trials, but also in the Precision medicine studies for different types of mutations related to PD-1 and the levels of PD-1 on the membranes of T and B cells. When designing data wrangling and data structuring code, make sure to differentiate 'PD-1' and 'PD-L1'.
Also PD-L1 countering antibodies are frequently part of the combination therapies, both adjuvant and neoadjuvant and make sure to identify and understand these to be able to give context to your result intepretation.Recently cutting edge Clinical trials are starting to show strong effects of such drugs on the CR (complete response) of lymph node located cancers as shown in this ASCO pub https://dailynews.ascopubs.org/do/asco24-first-look-dr-matt-galsky-checkmate-901.
Worth noting that PD-L1 is also present on some normal cells, which is why on of the reasons T cells sometimes confuse them and the cancer cells.