The Cancer Genome Atlas Project (TCGA): Understanding Glioblastoma

TCGAIn 2003, Cold Spring Harbor Laboratory (CSHL) and researchers around the world celebrated the 50th Anniversary of the discovery of the structure of DNA by Jim Watson and Francis Crick.  I was a graduate student in the Watson School of Biological Science at CSHL, named after James Watson who was the chancellor of the CSHL, and in 2003, I participated in (and planned!) some of the 50th anniversary events. Coinciding with this celebration was a meeting about DNA that brought world-renowned scientists and Nobel Prize winners from around the world to CSHL to celebrate how much had been accomplished in 50 years (including sequencing the human genome) and to look to the future for what could be done next. That meeting was the first time I had heard about the Cancer Genome Atlas Project. At this point, the TCGA (as the project was affectionately called) was just a pipe dream – a proposal by the National Cancer Institute and the National Human Genome Research Institute (two institutes in the National Institutes of Health – the NIH).  The idea was to use DNA sequencing and other techniques to understand different types of cancer at the genome level. The goal was to see what changes are happening in these cancer cells that might be exploited to detect or treat these cancers.  I remember that there was a heated debate about whether or not this idea would work. I was actually firmly against it, but now with the luxury of hindsight, the scientific advances of the TCGA seem to be clearly worth the time and cost.

The first part of the TCGA started in 2006 as a pilot project to study glioblastoma multiforme, lung, and ovarian cancer. In 2009, the project was expanded, and in the end, the TCGA consortium studied over 33 cancer types (including 10 rare cancers).  All of the data that was made publically available so that any results could be used by any scientist to better understand these diseases. To accomplish this goal, the TCGA created a network of institutions to provide the tissue for over 11,000 tumor and normal samples (from biobanks including the one that I currently manage).  These samples were analyzed using techniques like Next Generation Sequencing and researchers used heavy-duty computing power to put all of the data together. So what did they find? This data has contributed to hundreds of publications, but the one I’m going to talk about today is the results from the analysis of the glioblastoma multiforme tumors.

Title: Comprehensive genomic characterization defines human glioblastoma genes and core pathways published in Nature in October 2008.

Authors: The Cancer Genome Atlas Network

gbmBackground: Glioblastoma is a fast-growing, high grade, malignant brain tumor​ that is the most common brain tumor found in adults.  The most common treatments are surgery​, radiation therapy​, and/or chemotherapy (temozolomide​). Researchers are also testing new treatments such as NovoTFF, but these have not yet been approved for regular use. However, even with these treatments the median survival for someone diagnosed with glioblastoma is only ~15 months.  At the time that this study was published, little was known about the genetic cause of glioblastoma – a small handful of mutations were known, but nothing comprehensive. Because of the poor prognosis and lack of understanding of this disease, the TGCA targeting it for a full molecular analysis.

Methods: The TCGA requested tissue samples from glioblastoma patients from biobanks around the country. They received 206 samples that were of good enough quality to use for these experiments.  143 of these also had matching blood samples.  Because the DNA changes in the tumor only happen in the tumor, the blood is a good source of normal, unchanged DNA to compare the tumor DNA to. To these samples, the study sites did a number of different analyses:

  • They looked at the number of copies of each piece of DNA. This is called DNA copy number, and copy number is often changed in tumor cells (see more about what changes in the number of chromosomes can do here)
  • They looked at gene expression.  The genes are what makes proteins, which do all of the stuff in your body.  If you have a mutation in a gene, it could change the protein so that it contributes to the development of cancer.
  • They also looked at DNA methylation.  Methylation is a mark that can be added to the DNA telling the cell to turn off that part of DNA.  If there is methylation on gene that normally stops a cell from growing like crazy, that methylation would turn that gene off and the cell could grow out of control.
  • In a subset of samples, they performed next generation sequencing to know the full sequence of the tumor genomes.

Results and Discussion: From all of this data, the researchers found  quite a bit.

  • Copy number results: There were many differences in copy number including deletions of genes important for slowing growth and duplications of genes the told the cell to grow more.
  • Gene expression results: Genes that are responsible for cell growth, like the gene EGFR, were expressed more in glioblastoma tumor cells.  This has proven to be an interesting result because there are drugs that inhibit EGFR.  These drugs are currently being tested in the clinic to see if this EGFR drug is a good treatment for patients with a glioblastoma that expresses a lot of EGFR.
  • Methylation results: They found a gene called MGMT that is responsible for fixing mutated DNA was highly methylated.  This mutation was actually beneficial to patients because it made them more sensitive to the most common chemotherapy, temozolomide.  However, this result also suggests that losing MGMT methylation may cause treatment resistance.
  • Sequencing results: From all of the sequencing they created over 97 million base pairs of data! They found mutations in over 200 human genes. From statistical analysis, seven genes had significant mutations including a gene called p53, which usually prevents damaged cells from growing, but when mutated the cell can more easily grow out of control
glioblastoma_pathways

This is the summary figure from this paper that shows the three main pathways changed in glioblastoma and the evidence they found to support these genes’ involvement. Each colored circle or rectangle represents a different gene. Blue means that the gene is deleted and red means that there is more of that gene in glioblastoma tumors.

Bringing all of this data together, scientists found three main pathways that lead to cancer in glioblastoma (see the image above for these pathways).  These pathways provide targets for treatment by targeting drugs to specific genes in these pathways. Scientists also identified a new glioblastoma subtype that has improved survival​. This is great for patients who find out that they have this subtype!  Changes in the methylation also show how patients could acquire resistance to chemotherapy. Although chemotherapy resistance is bad for the patient, understanding how it happens allows scientists to develop drugs to overcome the resistance based on these specific pathways.

Although this is where the story ended for this article, the TCGA data has been used for many more studies about glioblastoma.  For example, in 2010, TCGA data was used to identify four different subtypes of glioblastoma: Proneural, Neural, Classical, and Mesenchymal that have helped to tailor the type of treatments use for each group. For example proneural glioblastoma does not benefit from aggressive treatment, whereas other subtypes do. Other researchers are using the information about glioblastoma mutations to develop new treatments for the disease

To learn more about the Cancer Genome Atlas Project, check out this article “The Cancer Genome Atlas: an immeasurable source of knowledge” in the journal or watch this video about the clinical implications of the TCGA finding about glioblastoma

The best week ever – Nobel Prize week!

nobelLast week was one of my favorite weeks of the year – Nobel Prize week. Some people wait for the Emmys or the Superbowl or Christmas.  I wait for the Nobels. To be fair, I care most about the science Nobels – Physics, Chemistry and Physiology or Medicine, though one cannot ignore the amazing accomplishments of the winners in Literature, Peace, and Economics. Every year, I try to guess who may win – though Thomson Reuters and others are far more scientific about their guesses than I am.  And each morning of Nobel Week, first thing I do is check the news on my phone to see who won, what for and whether or not I know them (this year – no).  Let’s talk about who won the science awards this year and what amazing discoveries they won for.

Physiology or Medicine. A lot of attention has been given to infectious diseases this year with the huge Ebola outbreak in western Africa.  Although tens of thousands of people were infected and died, other infectious diseases are even more widespread and affect millions of people a year. Malaria is a parasitic disease transmitted by mosquitoes that 3.4 billion people are at risk of contracting and that kills over 450,000 people per year. Parasitic worms are also rampant in the third world, can affect up to a third of the human population, and cause such diseases as river blindness.  This is the second most common cause of blindness by infection, with 17 million people infected and 0.8 million blinded by the disease.  The three winners of the Nobel for Physiology or Medicine this year discovered novel treatments for these parasitic diseases.  William C. Campbell and Satoshi Ōmura for roundworm parasites and Youyou Tu for malaria, saving hundreds of thousands of lives each year.

Chemistry. This is by far my favorite award this year because it is directly related to how humans safeguard their DNA, but also why when this safeguard does work, that we get cancer.  Awarded to Tomas Lindahl (UK), Paul Modrich (USA), and Aziz Sancar (USA), this Nobel celebrates the discovery of the mechanism of DNA repair. I’ve discussed in this blog how UV and other environmental factors can cause mutations in DNA, and with too many mutations, people can develop cancer or other diseases.  However, the genome doesn’t mutate out of control because cell contain the machinery that is always working to fix any DNA damage using DNA repair mechanisms. It’s like a NASCAR race, where the car is always being monitored, wheels replaced, and minor problems fixed by the pit crew.  DNA repair is the genome’s pit crew and these three scientists figured out three different ways that the cells monitors and fixes the DNA depending on the type of damage that has occurred.

Physics. We all know I’m not a physicist, but I’ll try my best. The Physics Nobel was awarded to Takaaki Kajita of Japan and Arthur B. McDonald of Canada for discovering that neutrinos have mass.  You may remember from high school that atoms are made up of protons, neutrons and electrons. However, scientists now know that there are even tinier parts of an atom called subatomic particles that include the neutrino, fermions and bosons (and others). Other than photons, which are the particles of light, neutrinos are the most numerous subatomic particle in the entire cosmos, so understanding how they work is incredibly important.  These researchers found that the three different types of neutrinos can convert from one to the other. It was predicted by the Standard Model of Physics that these neutrinos wouldn’t have mass, but these scientists also proved that they did. Their studies help to better understand matter and the universe. My favorite reporting of this award was by NPR.

So until next year Nobel Prizes.  I will be waiting with baited breath!

 

What is a mutation?

X-Men are mutants.  So is Dr. David Banner, who turns into the Incredible Hulk.  And the Joker in Batman is a mutant (along with most of the other villains in Batman).  So many superheros and supervillains are considered mutants that the word MUTANT has come to mean something a little terrifying.

Before we start talking about diseases that are caused by gene mutations, it’s important to really understand what a mutation is and how it’s not necessarily terrifying, and won’t turn you into Wolverine or The Hulk.

A mutation is a change in the DNA.  Change is such a broad term, but it’s broad because the DNA can change in a lot of different ways.  One nucleotide of DNA could be replaced with a different nucleotide, a nucleotide or several nucelotides or big long stretches of nucleotides could be removed or added (this is called a deletion or insertion), pieces of chromosomes could be moved from one place to another (or switched, which is called a translocation), or pieces of DNA can be duplicated (this includes whole genes being copied, which is called an amplification).

MutationsWhat actually happens when there is a mutation in your DNA? Let’s first remind ourselves of what DNA does – about 2% of the DNA codes for proteins and the other 98% either does nothing (that we know of) or regulates the DNA.  So when there is a mutation, the mutation may be in a gene or it may not.  And it may affect the protein or not. So in terms of changing a trait or causing a diseases, sometimes it may do this and sometimes not.

So let’s talk about when mutations are good.  Mutations that happen by chance are what’s responsible for evolution.  For example, without genetic changes, humans wouldn’t be able to drink milk.  We’d still all be lactose intolerant since a mutation in the gene that allows us to metabolize milk allows us to process milk as adults.

There are also mutations that are neutral or have no noticeable affect.  These could be in places in the genome that don’t contain genes or regulate gene expression.  They could also be mutations that don’t change the 3D shape or function of a protein.  So even though the DNA is different, the protein isn’t affected.

But what about when the protein is affected?  Mutations can decrease the activity of a protein, increase the activity of a protein, change the amount of protein (making too much or too little), change the function of a protein, or remove a protein altogether.

As an example, let’s think about what would happen if we changed the function of a protein that was responsible for telling cells to grow and divide.  Usually, the protein would be turned on only if it received the proper signal, and then it would grow and divide.  If there was a mutation that make this protein always on, then the cell would grow and divide uncontrollably – like having a broken copy machine that keeps copying even though you didn’t want it to.  Sound familiar?  This is one of the ways that mutations can cause cancer, by turning proteins on that make the cells copy themselves when they shouldn’t forming a tumor.

protein_mt_analogy