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Although the science of cancer vaccines has developed rapidly over the past few decades, researchers are facing a major bottleneck. Past cancer vaccines have often been developed for "common" mutations; however, many mutations tend to be “patient-specific”. That is to say, a large number of mutations in one patient may not be reproduced in another patient. Therefore, the results were not that satisfactory.

One of the keys to individualized cancer vaccines is to accurately locate the "mutanome" of the tumor and thereby select those mutations that will bring the optimal immune response. To do this, researchers first need to find mutations in cancer patients. At present, the commonly used method is to compare the similarities and differences between tumor samples and healthy tissue exomes by using NGS technology. However, there may be several limitations to this approach. One is that these tumor samples are often from biopsy of patients, while the small tumors obtained by biopsy may not be representative; the second is that the current analysis algorithm can only ensure the accuracy of SNV and insertion/deletion mutations (indels), but it is not accurate to reflect the impact of epigenetics, transcription, translation, post-translational modification on new cancer epitopes.

After finding a tumor mutation, researchers also need to make a choice and select the type of mutation that is most suitable for development into a vaccine. Limited to cost and technology, it is impossible to put all the mutations into the product, and only some of the mutant sequences are enough for the effector T cells to respond. Therefore, how to select the most immunogenic mutation under these constraints has become a key to the development of cancer vaccines.

At present, there is no consensus on how to select these mutations for subsequent development. But researchers have come up with several well-established principles, such as putting up requirements on the amount of expression of a mutant gene in a tumor, or on the ability of a mutation to produce a "presentable" epitope. In addition, experience has also taught us that if a particular mutation is commonly expressed in multiple clones of a heterogeneous tumor, the potential for the mutation to become a vaccine may be higher.

Individualized vaccines

One of the biggest challenges in clinical applications of individualized vaccines is how to make these vaccines quickly and deliver them to each patient in a timely manner. At present, there are many types of individualized cancer vaccines, including long polypeptides, RNA, DNA plasmids, viral vectors, engineered bacteria, and dendritic cells loaded with antigen. Depending on the type, the manufacturing cycle of cancer vaccines is also different. From the data obtained from clinical trials, this process takes 3-4 months, whether it is a peptide or RNA type, from mutation to vaccine development to vaccine administration. Therefore, patients have to be treated with other therapies while waiting. In the future, researchers expect to shorten this time to one month.

Another challenge in the clinical application of individualized vaccines is to determine the best treatment strategy. For those patients whose immune system has not been inhibited, cancer vaccines are expected to perform surprisingly. For patients with large numbers of tumors, we should consider a combination of cancer vaccine and immune checkpoint inhibitors. This is because the cancer vaccine can turn "cold tumor" into "hot tumor", and up-regulate the level of PD-L1 in the tumor microenvironment, therefore the anti-PD-1/PD-L1 immunological checkpoint inhibitor can also be used. Currently, combinations of new epitope vaccines with PD-1/PD-L1, CTLA4, LAG-3, TIM-3, and TGF-β are being evaluated in a number of clinical trials.

The future prospect of individualized immunotherapy

In a review in Science, Dr. Ugur Sahin and Dr. Özlem Türeci pointed out that in the current context, “individualized treatment” is often synonymous with “patient stratification”. Grouping according to the patient's biomarkers and developing specific treatments is a big step forward and has achieved good results, but in a narrow sense, this treatment concept has not yet achieved true individualization. Many cancer patients who do not have biomarkers that can be used for grouping also need effective treatments. At this point, cancer vaccines may bring a breakthrough.

It should also be admitted that although the cancer vaccine has broken through the key bottlenecks and has successfully entered clinical trials, the road ahead is still long. To make this innovative treatment popular, we also need to optimize clinical design, reduce production practices, increase production scale, and ensure patient access.

But the future prospect is bright after all. As our understanding of cancer biology deepens, with the introduction of new antigen epitope prediction algorithms (including the introduction of machine learning algorithms), and with the innovation of production technology, cancer vaccines are expected to truly become a type of cancer. Individualized therapy for treatment patterns. No matter what cancer the patient has, we can quickly provide an effective cancer vaccine to control their condition. We look forward to the early arrival of this day!

Fully aware of the importance of vaccines, Creative Peptides also provides neoantigen peptides vaccine that could be used in cancer immunotherapy. Since these vaccines are patient-specific, the effect would be more effective. Meanwhile, a whole range of custom peptide synthesis, modification, and analysis services are also available at Creative Peptides.

Reference materials:

[1] Sahin et al., Science 359, 1355–1360 (2018)