22 reported cases of uveal melanoma in Huntersville, NC
(15 females, 7 males)
Consented 11 patients/family members for archival tissue collection
Obtained 7 primary (6 enucleation, 1 FNA) and 2 metastatic (liver)
*Tissue missing or inadequate in other cases
Whole genome sequencing (40X-80X) on 6 enucleation and 2 liver
samples underway – anticipate results in May-June 2019
National Human Genome Research Institute
DNA Structure | BioNinja
Whole Genome Sequencing (WGS)
Figure out the cancer’s entire DNA sequence (all 6.4 billion letters)
Step 1: Separate tumor and adjacent normal tissue
Step 2: Extract DNA from tumor and matched normal tissue
Step 3: Whole genome sequencing (New York Genome Center)
National Human Genome Research Institute
What can we learn from WGS?
Compare to public
genome databases e.g.
The Cancer Genome
Compare to genomic data
from other unique UM
populations e.g. Auburn, AL
signatures that may point
to carcinogen exposure or
evaluation of key driver
mutations such as BAP1
Molecular landscape of uveal melanoma
Field MG et al. Nature Communications 2018.
Royer-Bertrand B et al. Am J Hum Genet 2016.
UV mutational signature
Relationship between UV exposure and UM risk is unclear:
welding identified as significant risk factor, but all forms of
sun exposure were non-significant
Characterized by CT transitions at pyrimidine dimers,
UV light triggers formation
of covalent bonds between
adjacent cytosine (C) or
thymine (T) bases leads
to DNA kinking and faulty
Error-prone polymerase misreads template
C to T mutation at site of
Hi, I’m Jessica, one of the medical oncology fellows working with Dr. Carvajal at Columbia University. I just wanted to spend a few minutes discussing some the work we’ve done so far in analyzing the tumor samples from Huntersville, NC and to briefly review what we ultimately hope to learn.
Of the 22 reported cases, we consented 11 patients/family members allowing us to obtain and use any leftover tumor tissue. We were able to get 7 primary tumor samples (one of which was a needle aspiration so there really wasn’t enough material to be used) and 2 liver samples. DNA was extracted from the 6 enucleation samples and 2 liver samples, and these were sent to the NYGC for whole genome sequencing. So what is whole genome sequencing, what does the whole process entail, and why is it taking so long?
So just to start with the basics, nearly every cell in the human body including cancer cells contains a complete set of DNA, which provide the genetic instructions that influence everything from a person’s hair color to disease susceptibility to how a cancer cell develops and spreads.
Cell there are different structures inside including the nucleus contains DNA in the form of chromosomes which you can think of as a very condensed and tightly wound form of DNA to allow it to fit inside the nucleus (humans have 23 pairs = 46 chromosomes) if you untangle the chromosomes, DNA in its basic form resembles a long, twisty ladder formed by two strands of genetic material that connect to create what’s called a “double helix.” Each rung of the ladder joins together a pair of molecules called nucleotides: adenine (A), thymine (T), cytosine (C) and guanine (G). A always teams up with T, and C always pairs with G.
Genes are made up of long stretches of DNA, and different genes or groups of genes are responsible for unique traits and cellular functions. Mutations or abnormalities in the DNA sequence can lead to diseases such as cancer, and these can either be inherited or develop randomly, sometimes in cases of exposure to specific mutagens or carcinogens.
Whole genome sequencing is figuring out the order of the DNA nucleotides, or bases, in a genome—that is the order of the 6.4 billion As, Cs, Gs, and Ts that make up the cancer’s DNA. In order to perform WGS, you need both tumor and normal DNA since there has to be a reference sequence of letters against which we can compare the tumor DNA. This way, we can figure out the mutations that are unique to the cancer genome.
The tumor samples arrive in the form of very thin sections of tissue that are mounted on glass slides. We ask the pathologist to look at the sample under the microscope to determine what’s tumor and what’s normal tissue. In the laboratory, we can then dissect away the tumor from the normal tissue and extract DNA from both tumor and normal tissue (this involves a number of different steps using chemicals to break open the cell membranes, gather the DNA, and strip away surrounding proteins to isolate just the DNA). The DNA samples are then sent to NYGC for analysis because they have a special protocol for sequencing DNA that’s taken from old, archival, formalin-fixed tissue.
The whole genome can’t be sequenced at once since it’s billions of base pairs long so the DNA is first broken up into small overlapping pieces that are sequenced and then reassembled into the proper order using these overlaps, kind of like putting together a giant biological jigsaw puzzle.
*** Compare that to the 17 million estimated to have had their DNA analyzed with direct-to-consumer tests sold by 23andMe and Ancestry. They use a technology called genotyping, which takes about a million snapshots of a person’s genome. That might sound like a lot, but it’s really less than 1 percent of the full picture. Genotyping targets short strings of DNA that scientists already know have a strong association with a given trait. So say, for example, scientists discover a new gene that increases your risk of developing brain cancer. If that gene is not one that 23andMe looks at (because how would it know to look if the gene hasn’t been discovered yet), then you’d have to get tested all over again to learn more about your brain cancer risk. Whole genome data on the other hand, once you have it, can be queried with computer algorithms whenever a new genetic discovery gets made.
What are we hoping to learn from WGS? We can compare the genomic data to other unique UM populations such as Auburn, AL. We can also make comparisons to publicly available genomic data, such as The Cancer Genome Atlas, which contains sequencing information for 80 primary uveal melanomas, to see if there are any differences that may suggest a unique etiology. We can also look for different mutational signatures that may point to carcinogen exposure…
Just to give you a sense of what we already know about the genetics of uveal melanoma, this is taken from a paper by Bill Harbour’s group in Miami. They analyzed 139 primary uveal melanoma samples using data from TCGA and other public databases. The horizontal axis represents different tumor samples, and the vertical axis lists the most common mutations. You’ve probably read or heard about GNAQ and GNA11 mutations which are found in virtually all uveal melanomas.
This is a separate study where they compared the mutational profile of uveal melanoma to other types of cancers. The different colors represent different point mutations. For example, blue is C to A mutations where the C nucleotide is replaced by an A nucleotide. Orange is C to T, etc. You can see that the mutational profile of uveal melanoma at the bottom is quite different from skin melanoma and conjunctival melanoma, but maybe more similar to thyroid and kidney cancer. So it will be interesting to compare the sequencing data from the Huntersville and Auburn cases to these larger public databases to see what the similarities and differences are, not only with other melanomas, but also other types of cancer.
Lastly, I just want to show you a few examples of common mutational signatures. We know that UV light is a risk factor for skin melanoma, but its relationship to uveal melanoma is less clear. In one study, welding was identified as a significant risk factor, but all other forms of sun exposure were non-significant.
The UV mutational signature is characterized by ≥60% C→T transitions specifically at pyrimidine dimer sites (where there are two Cs or two Ts next to each other), including CC to TT changes. This arises because UV light triggers the formation of a bond/link between adjacent C or T bases. This causes the DNA to become kinked and misshapen so when it’s being replicated, errors are introduced where the C is replaced with a T.
Tobacco is another common carcinogen that’s associated with a unique mutational signature characterized by a high prevalence of C to A changes. This occurs because polycyclic hydrocarbons and other carcinogens like benzo(a)pyrene interact with DNA to form bulky adducts on guanine (G). During the replication and repair process, the C:G base pair is replaced with an A:T base pair (C to A transversion since the C is on the transcribed strand).
Cancer types: Signature 4 has been found in head and neck cancer, liver cancer, lung adenocarcinoma, lung squamous carcinoma, small cell lung carcinoma, and oesophageal cancer. Proposed aetiology: Signature 4 is associated with smoking and its profile is similar to the mutational pattern observed in experimental systems exposed to tobacco carcinogens (e.g., benzo[a]pyrene). Signature 4 is likely due to tobacco mutagens. Additional mutational features: Signature 4 exhibits transcriptional strand bias for C>A mutations, compatible with the notion that damage to guanine is repaired by transcription-coupled nucleotide excision repair. Signature 4 is also associated with CC>AA dinucleotide substitutions. Comments: Signature 29 is found in cancers associated with tobacco chewing and appears different from Signature 4.
There are a total of 30 mutational signatures that have been identified associated with certain viral infections and other carcinogens like aflatoxin (produced by different fungi), but not all have a clear etiology. So it will be interesting to see if any of these signatures are found in the Huntersville cases.
Cancer types: Signature 2 has been found in 22 cancer types, but most commonly in cervical and bladder cancers. In most of these 22 cancer types, Signature 2 is present in at least 10% of samples. Proposed aetiology: Signature 2 has been attributed to activity of the AID/APOBEC family of cytidine deaminases. On the basis of similarities in the sequence context of cytosine mutations caused by APOBEC enzymes in experimental systems, a role for APOBEC1, APOBEC3A and/or APOBEC3B in human cancer appears more likely than for other members of the family. Additional mutational features: Transcriptional strand bias of mutations has been observed in exons, but is not present or is weaker in introns. Comments: Signature 2 is usually found in the same samples as Signature 13. It has been proposed that activation of AID/APOBEC cytidine deaminases is due to viral infection, retrotransposon jumping or to tissue inflammation. Currently, there is limited evidence to support these hypotheses. A germline deletion polymorphism involving APOBEC3A and APOBEC3B is associated with the presence of large numbers of Signature 2 and 13 mutations and with predisposition to breast cancer. Mutations of similar patterns to Signatures 2 and 13 are commonly found in the phenomenon of local hypermutation present in some cancers, known as kataegis, potentially implicating AID/APOBEC enzymes in this process as well.
Many of the other mutational signatures are associated with defective DNA repair pathways, and some don’t have a clear etiology.