# introduction to cancer vaccines

## cancer neoantigens

For cells to become cancerous, they must have mutations that cause uncontrolled replication and mutations that prevent that uncontrolled replication from causing apoptosis. Because cancer requires several mutations, it often begins with damage to mutation-preventing mechanisms. As such, cancers often have many mutations not required for their growth, which often cause changes to structure of some surface proteins.

The modified surface proteins of cancer cells are called "neoantigens". An approach to cancer treatment that's currently being researched is to identify some specific neoantigens of a patient's cancer, and create a personalized vaccine to cause their immune system to recognize them. Such vaccines would use either mRNA or synthetic long peptides. The steps required are as follows:

1. The cancer must develop neoantigens that are sufficiently distinct from human surface proteins and consistent across the cancer.
2. Cancer cells must be isolated and have their surface proteins characterized.
3. A surface protein must be found that the immune system can recognize well without (much) cross-reactivity to normal human proteins.
4. A vaccine that contains that neoantigen or its RNA sequence must be produced.

Most drugs are mass-produced, but with cancer vaccines that target neoantigens, all those steps must be done for every patient, which is expensive.


## protein characterization

The current methods for (2) are DNA sequencing and mass spectrometry.


#### sequencing

DNA sequencing is now good enough to sequence the full genome of cancer cells. That sequence can be compared to the DNA of normal cells, and some algorithms can be used to find differences that correspond to mutant proteins. However, guessing how DNA will be transcribed, how proteins will be [modified](https://en.wikipedia.org/wiki/Post-translational_modification), and which proteins will be displayed on the surface is difficult.

Practical nanopore sequencing has been a long time coming, but it's recently become a good option for sequencing cancer cell DNA.


#### MHC mass spec

Proteins are often bound to a [MHC](https://en.wikipedia.org/wiki/Major_histocompatibility_complex) for presentation on the surface, and those complexes can be isolated by mass spectrometry. You then know that the attached proteins can be on the cell surface. However...
- It's currently hard to guess which of those MHC-bound proteins could have a good immune response.
- This requires more cells than sequencing.
- This doesn't find all the mutant surface proteins.
- [Peptide sequencing](https://en.wikipedia.org/wiki/De_novo_peptide_sequencing) is necessary, and it's not easy.


## comments on AlphaFold

I've seen a lot of comments on [AlphaFold](https://en.wikipedia.org/wiki/AlphaFold) by people who don't really understand how it works or what it can do, so I thought I'd explain that.

AlphaFold (and similar systems) input the amino acid sequence of a protein to a neural network, using a typical Transformer design. That NN predicts relative positions of atoms, which is possible because:
- Some sequences form common types of [local structures](https://en.wikipedia.org/wiki/Protein_secondary_structure), and relative positions within those structures can be predicted.
- Some distant pairs of sequences tend to bind to each other.
- AlphaFold training included evolutionary history, and multiple mutations that happen at the same time tend to be near each other.

The positions predicted by the neural network are not used directly; they're an initial guess for a protein force field model. What neural networks provide is a better initialization than previous approaches.

The above points indicate some limitations that AlphaFold-type approaches have, such as:
- They're not as good for prions or otherwise "unnatural" proteins.
- They don't predict protein functions from structure, or vice-versa.
- They're not as good when evolutionary history isn't available.

While this approach is more limited than some people seem to think, it's still effective enough that, if a surface protein can be sequenced, its structure can probably be determined well enough to design [affimers](https://en.wikipedia.org/wiki/Affimer) for it.


## related methods

#### cryo-EM

[Cryo-EM](https://en.wikipedia.org/wiki/Cryogenic_electron_microscopy) is relatively new, it's one of the most powerful techniques for protein characterization, and it's produced many interesting results such as [the structure](https://www.nature.com/articles/s41564-024-01674-1) of bacterial flagellal motors, so I feel practically obligated to mention it at every opportunity.

Cryo-EM can produce structures from small crystals. If a protein can be isolated, "single particle cryo-EM" can even produce structures without crystallizing them at all. Still, it's currently easier to determine protein sequences with mass spectrometry, and I think nanopore approaches have more chance of reducing costs for this application.


#### nanopore protein analysis

The same basic approach used for current nanopore DNA sequencing [can be used](https://www.ox.ac.uk/news/2023-08-04-nanopore-technology-achieves-breakthrough-protein-variant-detection) to detect protein post-translational modifications.

Because such nanopore sequencing detects changes in ion flow through the nanopore, it's obviously better at detecting something like phosphorylation or glycosylation than the (smaller) differences between amino acids. But it should be fairly good at detecting charged groups - which does provide some data about protein sequences that could be combined with mass spec data.


#### monoclonal antibodies

Rather than inducing production of antibodies that target cancer neoantigens, it's also possible to produce those antibodies directly and inject them.

There are already [monoclonal antibody](https://en.wikipedia.org/wiki/Monoclonal_antibody) treatments for cancer, such as [Nivolumab](https://en.wikipedia.org/wiki/Nivolumab), but they're not individualized. Surface proteins that are common in cancers across different people are normal human receptors that are overexpressed by the cancer cells, not neoantigens that don't occur in normal cells. So, there are serious side effects to drugs targeting them.

Monoclonal antibodies treatments are expensive, but individualized treatments targeting cancer-specific proteins would be much more expensive.

Wikipedia also has a [decent page](https://en.wikipedia.org/wiki/Cancer_immunotherapy) on cancer immunotherapy in general.


#### affimers

Instead of creating antibodies that bind to a target and directly signal immune cells with the [crystallizable region](https://en.wikipedia.org/wiki/Fragment_crystallizable_region), it's possible to create smaller proteins that bind to a target and expose a native antigen that natural antibodies bind to. In other words, the cancer neoantigens (that don't trigger an immune response) would get covered by something that does trigger an immune response, producing a similar effect with a smaller protein. On the other hand, such aptamers could also get bound to antibodies and captured by immune cells before they bind to cancer cells.


#### aptamers

Instead of using synthetic proteins that bind to neoantigens, it's sometimes possible to use synthetic DNA sequences instead; those are sometimes called [aptamers](https://en.wikipedia.org/wiki/Aptamer). DNA has less versatility than proteins in terms of the structures it can form and bind to, but DNA sequences can be easily amplified by PCR, which could make them cheaper to produce than proteins.



## other cancer treatments

To evaluate the merits of research on a cancer treatment approach, we have to briefly consider how it compares to other promising approaches.

#### replication disruptors

Cancer treatments involve targeting some difference between cancer cells and normal cells. The most obvious such difference is that cancer cells replicate more, and the most common cancer treatments (besides surgery) target that. Mitosis is a complex process that can be disrupted in many ways; a notable example is [cisplatin](https://en.wikipedia.org/wiki/Cisplatin).

Obviously, cell replication is normally important, and even if replicating cells could be targeted without any effect on other cells, disrupting it results in serious side effects. This puts some limits on how good this approach could theoretically be, but currently the bigger problem is that cancers tend to find a way to replicate anyway.


#### mitochondria-mediated apoptosis

Normal cells have several safeguards that cause apoptosis before they'd become cancerous. One of the most important is mitochondria-mediated apoptosis, so cancer cells often disrupt normal mitochondria function. Targeting this difference is the basis of most of my own thoughts on potential cancer treatments.

There are 2 basic approaches to this: reactivating mitochondria-mediated apoptosis, and disrupting mitochondria-independent metabolism to prevent cancer ATP generation. I consider both approaches worth pursuing, but details are beyond the scope of this post.


## vaccine production

DNA can be amplified by PCR, but RNA amplification is somewhat more complex; mRNA for vaccines is currently produced with "in vitro transcription".

Directly synthesizing polypeptides (using [native chemical ligation](https://en.wikipedia.org/wiki/Native_chemical_ligation)) isn't harder than directly synthesizing mRNA. If direct synthesis is used, synthetic long peptides seem better to me than mRNA, because the immune response works somewhat better, but details are beyond the scope of this post.

The immune system often recognizes non-human proteins; the mRNA vaccines for COVID don't need adjuvants because the COVID spike protein is recognized as foreign. However, if cancer neoantigens provoke an immune response, the immune system kills those cells, so remaining cancer neoantigens wouldn't be recognized on their own. This also means that cancers are strongly selected to have fewer and more human-like neoantigens, which makes it harder to produce vaccines for them, and makes cross-reactivity with normal surface proteins more likely. Also, cancers can mutate ("tumor antigen loss") such that they stop producing some surface proteins.

Synthesized cancer neoantigens can be directly attached to a native antigen, and when the immune system recognizes the native antigen it will produce antibodies for the neoantigen part. With mRNA vaccines, either a native antigen would be added to the sequence (in a way that doesn't interfere with the neoantigen structure) or adjuvants would be added. Typically, adjuvants kill some cells, causing release of human double-stranded DNA fragments that indicate to immune cells that something killed some cells nearby, and triggering production of antibodies to everything foreign in the area. But that obviously only works if the neoantigens are recognizable enough that an indication that "something bad is in this area" is sufficient.


## conclusion

Individualized cancer vaccines are not yet practical, but I consider them a promising possibility for significantly better cancer treatments. I think research on that should prioritize:
- combining mass spectrometry and nanopore data for protein characterization
- continued development of nanopore sequencing
- continued surveying of cancer genomes, such as TCGA
- developing lower-cost methods for isolation of cell surface proteins
- developing equipment and methods for lower-cost production of long polypeptides