Journal Club – A mutation in mice to study ALS

Amyotrophic Lateral Sclerosis (ALS) is a debilitating neurodegenerative disease that affects neurons in the brain, brain stem, and spinal cord. When these neurons die, it affects the connections that they have to muscles throughout the body resulting in muscle weakness that affects speaking, swallowing and breathing leading to paralysis and eventual dead.  The cause of ALS isn’t known in 90-95% of cases.  However, recently scientists have identified a mutation in a gene nondescriptly called “chromosome 9 open reading frame 72,” which is abbreviated to C9ORF72.  This mutation results in six nucleotides, GGGGCC, being repeating up to 1000 times within this gene in ALS patients.  Even though this is the most common mutation found in ALS patients, it’s still unclear exactly how these repeats affect neurons or the progression of the disease. The two hypotheses that are most studied are that the mutated C9ORF72 makes mutated RNA transcripts (RNA is the molecule that usually helps DNA be translated into proteins) or makes unusual proteins called dipeptide repeat proteins (DRPs), each of which can aggregate (clump) together and disrupt the normal activity of the neurons leading to neurodegeneration.


The pink dots show clumped up RNA from the many many repeats in the C9ORF72 gene. Each panel shows these clumps in different areas of the mouse brain. Taken from the article Peters et al. 2015 Neuron

In two recent publications in the journal Neuron, researchers have used mice as a model system to look at how these large GGGGCC repeats in C9ORF72 affect the mouse nervous system.  Why use a mouse? First, scientists know how to experimentally change the mouse genome in order to add hundreds or thousands of repeats to a single gene, like C9ORF72.  Second, mouse and human genes are about 85% identical, so if scientists can understand how a gene like the mutated C9ORF72 affects neurons in mice, it may also help scientists understand how it works in humans. Third, by creating a mouse “model” of ALS, scientists can use this model to better understand ALS and to test potential future therapies (it’s worth noting that only one drug currently exists for ALS and it typically extends life only by a few months).

In each article, the mouse model was slightly different – one had a mutated C9ORF72 with 500 GGGGCC repeats and the other varied between 100-1000 repeats. However, both sets of researchers found the same results.  The mice had aggregated RNA transcripts and DRPs in their neurons just like what are found in human patients with ALS, but none of the mice had behavioral changes or neurodegeneration that are seen in human ALS patients.  So why didn’t the clumped up RNA and proteins cause neurodegeneration in mice like they do in humans?  There are lots of potential reasons – including the fact that even though mice and humans are similar, there are still lots of differences and mice may respond to these aggregated RNA and proteins differently than humans.  However, the authors of these papers suggest that other environmental and/or genetic factors along with the aggregates caused by the C9ORF72 mutation must be involved in developing the neurodegeneration.  It may also mean that getting rid of these aggregates before neurodegeneration occurs may prevent development of ALS.  Now that these mice are available to study, they should help in identifying the other factors involved in ALS development along with developing possible treatments for this debilitating disease.

Want to read the articles?  Unfortunately, they are behind a paywall, but you can see the abstracts here:

O’Rourke et al. (2015) C9orf72 BAC Transgenic Mice Display Typical Pathologic Features of ALS/FTD. Neuron. Volume 88, Issue 5, p892–901, 2 December 2015 Article

Peters et al. (2015) Human C9OFR72 Hexanucleotide Expansion Reproduces RNA Foci and Dipeptide Repeat Proteins but Not Neurodegeneration in BAC Transgenic Mice. Neuron. Volume 88, Issue 5, p902–909, 2 December 2015 Article

Read the Article from PN News that I contributed to here

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

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

Personalized Medicine: A Cure for HIV

Personalized Medicine – finding the right treatment for the right patient at the right time – is quickly becoming a buzzword both in the medical field but also to the public. But is it just hype? No!  I discussed a number of examples of how personalized medicine is currently be used in breast cancer in a previous post. In this and future posts, I’ll talk about a few fascinating emerging examples of the promise of personalized medicine.  These are NOT currently being used for patient treatment as part of standard of care, but could be someday.


HIV lentivirus

The Human Immunodeficiency Virus (HIV), the cause of AIDS, is a virus that attacks the immune system.  This attack prevents immune cells from fighting other infections.  The result of this is that the patient is more likely to acquire other infections and cancers that ultimately kill them.  When first discovered in the early 1980s, HIV infection was a death sentence. Untreated, survival is 9 to 11 years.  In the past 30 years, antiviral treatments have been developed that, when taken as prescribed, essentially make HIV infection a chronic disease, extending life to 25-50 years. But there is no cure for HIV, and as of 2012, over 35.3 million people were infected with the virus.

The lack of a vaccine to prevent the disease or of a cure to treat those infected isn’t because no one is trying. Since the virus was identified as the cause of the disease, scientists have been working to find a prevention or cure (along with developing all of the antiretroviral drugs that delay/treat the disease). I’m not going to discuss all of this interesting research (though it is worthy of discussion), instead I’m going to talk about one patient, Timothy Ray Brown, who was cured of HIV/AIDS through a stroke of genetic understanding and luck!

Brown was HIV positive and had been on antiretroviral therapy for over 10 years when he was diagnosed with leukemia in 2007. His leukemia – Acute Myeloid Leukemia (AML) – is caused by too many white blood cells in the bone marrow, which interferes with the creation of red blood cells, platelets and normal white blood cells. Chemotherapy and radiation are used to treat AML by wiping out all of the cells in the bone marrow – both the cancer cells and the normal cells. Brown’s doctors then replaced the cells in the bone marrow with non-cancerous bone marrow cells of a donor.  This is called a stem cell transplant, and it is commonly used to treat leukemia – often resulting in long term remission or a cure of the disease.

But the really cool part of this story isn’t the treatment itself.  Rather it’s that that Brown’s doctor selected bone marrow from a donor that had a mutation in the gene CCR5. So what? The CCR5 protein is found on the outside of the cells that the HIV virus infects. CCR5 is REQUIRED for the virus to get inside the cell, replicate, and kill the cell. Without CCR5, HIV is harmless. There is a deletion mutation in CCR5 called delta32 that prevents HIV from binding to the cell and infecting it.  Blocking HIV from getting into the cell prevents HIV infection.  In fact, it’s been found that some people are naturally resistant to HIV infection because they have this deletion. Two copies of the gene are found in 1% of the Caucasian population, and it’s thought that this mutation was selected for because it also prevents smallpox infection.
HIV_ccr5So Brown’s doctors repopulated his bone marrow with cells that had the CCR5-delta32 mutation.  This didn’t just cure his leukemia but it also prevented the HIV from infecting his new blood cells, curing his HIV. He is still cured from HIV today!

What does this mean for others who are infected with HIV? Is a stem cell transplant going to work for everyone?  Unfortunately, no. This mutation is very rare, so finding donors with this mutation isn’t feasible.  Plus, this is a very expensive therapy that comes with risks such as graft-versus-host disease from the mismatch between the person receiving the transplant and the transplanted cells themselves. However, there are possible options to overcoming these challenges, including “gene editing.” In this method, T cells from HIV-positive patients would be removed from the body and then gene editing would be used to to make the CCR5-delta32 mutation in these cells.  These cells could then be re-introduced into the patient.  With the mutation, HIV won’t be able to infect these T cells, which would hopefully cure the disease, while avoiding some of the major graft-versus-host side effects. A small clinical trial tested this idea in 2014 (full article can be found in the New England Journal of Medicine), and HIV couldn’t be detected in one out of four patients who could be evaluated. Although this is a preliminary study using an older gene-editing technique, it shows promise for “personalized gene therapy” to potentially cure HIV.

How scientists “cured” melanoma

When talking about Personalized Medicine, one of the recent shining examples of this concept in practice is in the treatment of melanoma. Melanoma is a cancer of the pigment cells called melanocytes and is most commonly diagnosed as a skin cancer. The prognosis for melanoma is dismal when caught at later stages where the cancer cells have spread into lower layer of the skin or throughout the body (see the stats in the image below). Treatment typically involves surgery to remove the cancer cells, followed by chemotherapy and/or radiation therapy, but the response to these treatments is low.


There are two interesting personalized medicine examples for melanoma.  The first is in determining whether a low stage (I or II) melanoma has a likelihood of spreading.  Once a low stage melanoma has been removed by surgery, there is still a 14% chance that these patients will develop metastatic (melanoma that spreads) disease. To determine which patients are more at risk, a biotech company developed DecisionDx-Melanoma. This test looks at the expression of 31 genes and separates the patients into two groups based on the gene expression profiles.  One group only has a 3% risk of developing invasive melanoma within 5 years whereas the other group has a 69% chance.

However, whether the cancer progresses or not, treatment is still an issue. That is, it was until a few years ago when scientists found that  50-60% of all melanoma patients have a mutation in the gene called “BRAF.” This mutation tells the cancer cells to grow faster, so you can imagine that if you stop this signal telling the cancer cells to GROW, then they might stop growing and die. This is exactly what the drug PLX4032 (vemurafenib) does – it inhibits this mutated BRAF and stops the cancer cells from growing in 81% of the patients with this mutation (see the photo at the bottom of the post to see how dramatic this effect is).  On the other hand, in patients without this mutation, the drug has severe adverse effects and shouldn’t be used.  Because of this, doctors don’t want to prescribe this treatment to patients without the mutation.  Therefore, scientists created a companion diagnostic.  These are tests that are used to identify specific mutations before treatment to help decide what treatment to give (see image below). In the case of melanoma, this companion diagnostic tests if the patient has the BRAF mutation, and the patient is only treated with vemurafenib if they have this mutation.

This treatment was revolutionary with an incredible ability to cure melanoma. It was like melanoma was previously being treated with the destruction of a nuclear bomb, and now it is being treated with the precision of a sniper rifle – targeting the exact source of the cancer. So why is the word “cure” so obviously in quotes? Unfortunately, after continued therapy, the cancer relapses (see the image below). Imagine treating cancer cells being like closing a road- it’ll block up traffic (kill the cancer cells), but then you’ll be able to find back roads that get you to the same place.  In the case of cancer, the drug is targeting mutations in BRAF, and BRAF finds ways to evade the drug by mutating again (effectively removing the roadblock).  Or the cancer cells themselves may have other routes besides mutated BRAF making the cancer grow. So although this drug is a life extender, scientists have been working to combine it with other targeted drugs (blocking off alternative routes) to make it a long-term life saver.


From the Journal of Clinical Oncology

Journal Club: The Microbiome Autism Connection

As I’ve mentioned in other posts, scientists have to read about and understand the current scientific literature. Lots of the time this is done alone, at your desk in the office or the lab, for hours and hours so that you can really understand whatever topic it is that you’re studying. But one of my favorite ways to share scientific papers is through a weekly meeting with the whole lab called a Journal Club. Although my husband laughs about this kind of nerdy science “club” (akin to his amusement about scientific societies), it’s a great way to discuss a particular topic and dive deep into a discussion about how the researchers got their results and came to their conclusions. This is the first of many Journal Clubs where we will do an abbreviated version of what we would discuss in a typical journal club in the lab. 

Paper TItle:  Reduced Incidence of Prevotella and Other Fermenters in Intestinal Microflora of Autistic Children

Authors: Dae-Wook Kang , Jin Gyoon Park ,Zehra Esra Ilhan, Garrick Wallstrom, Joshua LaBaer, James B. Adams, Rosa Krajmalnik-Brown
Full disclosure, Dr. LaBaer is the Director of the center I previously worked in at the Biodesign Institute at ASU. Drs. Park and Wallstrom worked in offices down the hall from me and Dr. Krajmalnik-Brown was in another center at the Biodesign Institute.

Journal: PLOS One (PLOS stands for “Public Library of Science”). In case you want to read the whole article, it can be downloaded (for free) here

Background/Introduction: Before this paper was published, scientists knew that many children with autism also had gastrointestinal (GI) issues suggesting that there may be a connection between the two. There have been some studies looking at antibiotic treatment (which could change the gut microbiome) before 3 years of age and how this might be connected with autism.  There have also been studies connecting the gut microbiome and the brain. So there was evidence that the gut microbiome and autism may be related in some way.

When this paper was written, scientists also knew about the microbiome and how changes in the bacteria (all 1,000,000,000,000,000 of them) that are in the gut are found in patients with many different diseases – from C. diff infection to obesity to depression.

Goal of this paper: Look closely at the changes in the gut microbiome of children with autism to better understand how these two might be related.

Methods/what did they do?: Bacteria in fecal samples is considered representative of bacteria in the gut microbiome. Therefore, the researchers collected fecal samples from children both with (20 children) and without (20 children) autism.  The samples from patients without autism were used as a “control” to compare to the autistic samples. The researchers also asked the children (or their parents) questions to help determine the level of GI issues, the severity of their autism, and their environmental factors like their diet. The researchers isolated bacterial DNA from each of these fecal samples and then sequenced the DNA to determine what types of bacteria are in the gut.

autism microbiome diversity

A figure from the paper comparing the phylogenetic diversity (PD) of the bacteria in autistic versus non-autistic children. you can see that the red boxes (for autistic children) are lower than the blue boxes (for non-autistic children) indicating a lower microbiome diversity.

Results: Through sequence analysis and other statistical methods, the authors found that children who did not have autism have a more diverse microbiome compared to autistic children.  If there is higher diversity, it means that the gut contains more different types of bacteria, and lower diversity means a smaller variety of bacteria in the gut. They also found that in the autistic patients with a greater diversity in their microbiome, their autism was generally less severe. They also did not find any correlation between age, gender or diet with these microbiome changes.

The scientists also looked at what specific genus and species of bacteria were more represented in non-autistic versus autistic children. Specifically the bacteria from genus Veillonellacaea, Provetella, and Coprococcus  are less abundant in autistic children.

Discussion/Significance: What does this all mean?  The researchers did find a correlation between decreased gut microbiome diversity and autism. It should be clarified that just because GI problems are often found in autistic children and the severity of the GI issues correlates with the severity of autism, this does not necessary mean that GI issues cause autism or vice versa.  That still needs to be determined. Also because the diversity of bacteria in autistic children is low, it is not clear if this is a cause of autism or an effect of a child having autism.  However, this paper does provide a “stepping stone” to better understand what is happening in the gut of autistic children and may help define a target for diagnosing autism (by looking at the decreased diversity in the gut as a diagnostic test) or treatment (perhaps through fecal transplant).

What has been done since? This paper was published in 2013.  So what has changed since the paper was published?  Do we know whether or not changes in the gut microbiome cause autism or not?  Unfortunately, this is still unclear.  However, if these microbiome changes are a cause of the neurological changes in autism, then one would want to do a clinical trial to test what happens to autism symptoms when the microbiome has been altered.  This could be done in a number ways including diet modulations, prebiotics, probiotics, synbiotics, postbiotics, antibiotics, fecal transplantation, and activated charcoal.  Researchers have started this process by holding a meeting that included patients and their families to figure out how this type of trial could be designed (for more details, check out this journal article).

For more information about the microbiome/autism connection, check out Autism Speaks. To read more Journal Clubs, visit the archives here.

What is a sunburn? Featuring Olympic Gold Medalist Misty Hyman


Misty (left) and me getting ready to swim

In this two part series, I partner with my friend, Olympic Gold Medalist Misty Hyman, winner of the women’s 200 meter butterfly in the 2000 Australian games.  Misty currently coaches private lessons, leads swim clinics, and gives motivational speeches around the world.  Misty was also recently named the senior assistant coach for the Arizona State University swim team. In her spare time, Misty extends her passion for swimming into the community as a spokesperson for FitPHX and encouraging everyone to learn how to swim.

Swimmers, as opposed to scientists, spend a lot of time outside.  Whether in the pool, by the pool, or in and around the beach, swimmers have a thing for the outdoors. With the outdoors, comes the sun.  With the sun, comes the possibility of a sunburn. And in Phoenix, where there are nearly 300 days a year with sun, a sunburn is even more likely. We all know that you should wear sunscreen to avoid getting a sunburn, but most people don’t know what a sunburn is or why you want to avoid it.  That’s what I’m going to talk about today.

sunburned_hubbySo what is sunburn? Sunburn is a response to the UV light of the sun.  The UV light is a damaging agent to DNA, the genetic code within each of your cells responsible for making your cell function properly. If there is a lot of DNA damage caused by the UV light – if you are in the sun for too long – this is a trigger for these damaged skin cells to commit suicide in a process called apoptosis. Before your cells die, this damage induces an inflammatory response, which is what causes the redness and the heat that accompany a sunburn. A few days after the sunburn, your skin starts to peel – this is the layer of skin cells that committed suicide peeling away from your body.  To summarize – sunburn is essentially a form of radiation poisoning to the skin that kills an entire layer of skin cells because the DNA was too damaged for the cells to live.


Taken by Nick Sherman and used under the Creative Commons License

Now as you and I both know, you don’t always get a sunburn when you lay in the sun (or a tanning bed, which also using UV light and has the same affect as the sun’s UV rays). Instead you could tan.  Tanning is a defense mechanism of your cells against the DNA damage caused by the sun’s UV rays.  How does it work?  The UV triggers special cells in your skin called melanocytes to redistribute or darken a pigment called melanin.  This pigment absorbs the UV light and protects the DNA from the damaging effect of UV.  If you are naturally darker skinned or already tan, the melanin absorbs the UV light so you are less likely to damage your DNA and less likely to sunburn.  But this doesn’t mean that you should just spend all of your ‘working on your tan.”  The melanin isn’t a fail safe UV protector and DNA damage still occurs.

Now that you know how sunburn and tanning works, maybe you’re thinking about how you’re out in the sun all the time, but you don’t get burned or you burn every once in a while but not all the time, so you must be okay. Maybe not.  When the UV light damages your DNA and you don’t burn, your cells still have to repair this DNA damage.  If the DNA damage isn’t repaired, you could end up with permanent mutations in the DNA of of your skin cells. These mutations may change the function of a protein and affect how your skin cells function.  Let’s say for example that you get a mutation in a gene that prevents your skin cells from dying next time they are hit with too much UV from the sun. The next time you get a sunburn, this cell will get damaged, it won’t die, and it will grow and divide with this mutation. Mutations then have the opportunity to accumulate and at a certain point will have enough mutations that the cells grow out of control and form skin cancer.

This can all be avoided in a number of ways.  You could become a scientist and never have the time to go outside because you’re always in the lab (or in my case, because your office is in the basement).  Since that likely won’t happen, you do have the option to avoid UV exposure by covering your skin with light clothing, a hat, or sunscreen.  You can also avoid spending long periods of time in the sun or limit your exposure to times of day where the UV rays are not as strong (when the UV Index is low).  Either way, the DNA mutations accumulate over a lifetime of exposure, so decreasing exposure or protecting your skin at any age will provide an added benefit and decrease your risk of skin cancer.

Misty’s Message: In the 4th grade, Misty did a science project on sunscreen and won the elementary school science fair.  Clearly, avoiding sunburn has been an interest of hers from early on.  Her advice is still the same as her science fair conclusions in the 4th grade: ” no matter what time of day it is, you should always wear your sunscreen especially when you’re in the pool.” The one exception is swimming at midnight – then you’re okay.

How do you find a biomarker? A needle in the haystack.

biomarker_useBiomarkers are biological substances that can be measured to indicate some state of disease.  They can be used to detect a disease early, diagnose a disease, track the progression of the disease, predict how quickly a disease will progress, determine what the best treatment is for the disease, or monitor whether or not a treatment is working. Biomarkers have the potential to do so much, and identifying biomarkers for different steps in the health/disease continuum would help doctors to provide each individual with targeted, precision healthcare.  Biomarkers have the potential to save billions of healthcare dollars by helping prevent disease, by treating disease early (when it’s usually less expensive to treat), or by targeting treatments and avoid giving a treatment that won’t be effective.

spotthedifferencesWith all this potential, you would expect doctors to be using data from biomarkers to guide every single healthcare decision – but this isn’t the case quite yet.  First scientists have to find these biomarkers – a process often referred to as biomarker discovery.  I like to compare finding a biomaker to those “spot the differences” games where you have to look at two images and circle what is different in one picture compared to the other.  This is exactly what scientists do when finding a biomarker, except instead of comparing pictures, they are comparing patients.  And it’s not an easy game of “spot the differences” it’s complicated: the pictures are small and there are tons of details.

Let’s imagine a scenario that a scientist might face when wanting to find a biomarker for the early detection of pancreatic cancer.   Cancer is caused by mutations in the DNA, so you decide to look for DNA mutations as your biomarker for pancreatic cancer. So how do you “spot the differences” to find DNA biomarkers for pancreatic cancer?  First, you will need patient samples – maybe tissue or blood samples from a biobank that already has samples from patients with pancreatic cancer.  If samples aren’t already available, you will have to initiate a study partnering with doctors to collect samples from pancreatic cancer patients for you.  You will also need the second “picture” to compare the pancreatic cancer “picture” to.  This second picture will be samples from people who don’t have pancreatic cancer (scientists usually call this group the “control” group).  Then you have to “look” at the two groups’ DNA so you can find those differences.  This “looking” is often done by some genomics method like sequencing the DNA. This is where a lot of the complication comes in because if you look at all of the DNA, you will be comparing 3 billion individual nucleotides (the A, T, G, and Cs we’ve discussed in earlier posts) from each patient to each of the controls.  Even if you just look at the DNA that makes proteins, you’re still comparing 30 million nucleotides per patient.  And you can’t just compare one patient to one control!  Each of us is genetically different by ~1%, so you need to compare many patients to many controls to make sure that you find DNA that is involved in the disease and not just the ~1% that is already different between individuals.  But wait, we’re not done yet!  The biomarkers that you identify have to be validated – or double checked – to make sure that these differences just weren’t found by mistake.  And before biomarkers can be used in the clinic, they need to be approved by the Food and Drug Administration (FDA)



Whew… that was a lot of work! And so many people were involved: lead scientists who directed the project and got the money to fund it, researchers who do most of the work, computer people who are experts at crunching all of the data, and maybe even engineers to help run the equipment. Finding the biomarker needle in the biological haystack is difficult and takes time, money, and lots of people.  This is one of the reasons why there are only 20 FDA approved biomarkers for cancer (data from 2014).  But just because it’s difficult, doesn’t mean it’s impossible.  Furthermore, this effort is necessary to improve healthcare and decrease healthcare costs in the future.  It just might take a bit more time than we’d all like.

If you want to read more about the challenges and some of the solutions to biomarker discovery in cancer, take a look at this scientific article.  Or read about some successes from right in our backyard at Arizona State University on identifying biomarkers for the early detection of ovarian cancer and breast cancer.


How and why do cells divide? The cell cycle!

You started off as one cell: one tiny little zygote containing a full set of DNA (23 pairs of chromosomes).  As an adult human being, you are now made up of over 37 trillion cells. This means that that one cell  divided to make two cells, each of those cells divided to make 4 cells, those 4 cells divided to make 8 cells and on and on until the 37 trillion cells that make up you today. Even now, your body makes around 60 billion cells each day to create new skin cells, intestine cells, hair cells and and nail cells. When you cut yourself, the body needs to make new cells to heal.  And if your cells divide out of control, this can cause cancer and if they stop diving this causes of aging. So understanding how cells divide is super important!

The cell cycle, which is the process of one cell and one set of DNA turing into two cells with two sets of DNA.  There are three main parts of the cell cycle:

1.  To make two cells from one, you can imagine that a few important things need to happen.  First, you need the cell to grow to get bigger and to accumulate enough nutrients to support two cells.  Second, you need to replicate the DNA so that when the cell divides, each “daughter” cell gets one copy of the DNA. These two things happen in the interphase part of the cell cycle.  Interphase is separated into 3 parts

  • Gap 1 (usually just called G1 phase) where the cell grows
  • Synthesis (usually just called S phase) where the DNA is copied so that two complete copies of DNA are now in the cell
  • Gap 2 (usually just called G2) where the cell grows some more


The chromosomes (shown in blue) condense and line up before being pulled into two cells by microtubules (shown in green)
By Roy van Heesbeen (Roy) [Public domain], via Wikimedia Commons 

2. Once the cell has copied the DNA and grown big enough to split into two cells, the cell undergoes mitosis.  Mitosis is when the copied chromosomes are separated into two different cells.  Remember that if you took all the DNA in a cell and stretched it out from end to end that it would be 6-10 feet long? Since this DNA is already replicated by the time the cell gets to mitosis, there are 92 chromosomes (two copies of the two pairs of 23 chromosomes) and 12-20 feet of DNA that needs to be organized and sorted into two separate cells.  How does the cell make this nearly impossible sounding task happen?  First, when each chromosome makes a copy of itself, it stays connected to the orignal (kind of like if there were little protein magnets holding them together). mitosis Second, when the chromosomes are ready to separate into different cells they “condense”, getting much, much smaller (see the blue DNA in the photo above).  Third, there are mechanisms in the cell that make the chromosomes line up.  So what you end up with are all of the chromosomes in tight little bundles lined up in a row.  At that point, the cell creates “ropes” out of a protein called microtubules that pull the copied chromosomes apart into the two separate cells.

cytokinesis3.  Finally, now that the DNA is separated into the two new cells, these cells have to officially split into two in a process called cytokinesis.  You can imagine this is like pulling a drawstring closed to pinch the space between the two cells until they have completely split apart.

If this sounds like a complicated process, you’re right.  It is.  But it happens flawlessly 10,000 trillion times in a lifetime.  Part of the reason why this is a flawless process is because the cell puts checkpoints into the process.  It’s like when your bank calls you because they observed a strange transaction on your credit card and they put your card on hold.  If the cell sees something strange happening when the cell is trying to undergo cell division, it puts a hold on the whole process until it gets fixed.  We’ll discuss this a lot more in the future because when the cell cycle isn’t running flawlessly and these checkpoints aren’t working, this contributes to causing cancer and other diseases.

What does it mean when I have genes that increase my “risk” of disease? Like Alzheimer’s?

The last few posts (here and here) have been about people who have carrier mutations.  These people have one recessive gene mutation that they could pass on to their child.  If the child inherits two recessive genes (one from each parent), they will get the disease.  That’s how it works with recessive diseases that are caused by one gene.  About 4,000 diseases are caused by mutations in one gene (either in dominant or recessive genes).  But that leaves all of the other diseases…

Since we’re still talking about genetics, let’s stick to diseases that are caused at least in
part by gene mutations as compared to diseases caused by infection, for example.  There are many diseases that are caused by mutations in multiple genes (the technical word for this is polygenic). In these cases, no one gene can be identified as the single cause of the disease.  The genes that are involved in causing the disease can be on many different chromosomes in many different locations on these chromosomes and only if mutated in combination will someone get the disease.  And these mutations may only cause the disease if exposed to a certain environmental factor (like cigarette smoke).


If this sounds confusing and complicated to you – it is.  Scientists find it confusing and complicated too. It’s much more difficult to pinpoint the exact genes that cause a  disease if there is more than one mutation in more than one gene.  It’s like a puzzle, but you don’t know the number of pieces in advance or what the puzzle looks like.  So if you fit two pieces together (or identify two genes that are mutated), you don’t know if you have completed the puzzle and figured out what is causing a disease or if you need to look deeper.

Scientifically, this is a complicated question, but for the patient who doesn’t care how many genes cause the disease, what does it mean to them? What does this mean for risk?  If a gene is found to be associated with a polygenic disease, mutations in this gene may increase or decrease your risk of that disease.  But unlike genes cause by dominant or recessive genes, no one can say for sure 100% either way if you have a particular gene mutation that you will or won’t get a disease.

A great example of this is Alzheimer’s disease.  Only in early onset Alzheimer’s (0.1% of all cases), one dominant genetic mutation the cause of the disease. However, in 99.9% of Alzheimer’s Disease cases, more than one gene is involved (at least three genes, but probably more).  One gene that is well studied in association with Alzheimer’s Disease risk is the gene apolipoprotein E (ApoE, for short).  There are three different versions of the ApoE gene called ApoE2, ApoE3, and ApoE4 – each representing a different mutation in the ApoE gene.  The E2 version (found with 8.4% frequency in the population) is protective against Alzheimer’s Disease.  The E3 version (found with 77.9% frequency in the population) is essentially neutral (neither causing or protecting from disease).  The E4 version (found with 13.7% frequency in the general population) is the one that causes the problems and and increase the risk from 20% in a person who has zero copies of E4 to 91% risk in a person with two ApoE4 copies.  The more copied of E4 the more likely a person is to get Alzheimer’s disease at a younger age as well. And if you’re wondering, this is ABSOLUTE risk, not relative.

alzheimersAlzheimer’s disease is a particularly tricky example to use because there are few, if any, preventative treatments for the disease.  So even if you know that you have two copies of ApoE4, there isn’t much that you can do.  However, there are other diseases, where certain genes increase risk for a disease (like I described for the BRCA mutations and breast cancer risk).  In this case there are potential preventative treatments, though even after those treatments, the decrease in risk is significant but cannot be eliminated.  Overall, it’s important to understand the complexity of disease and how many factors (including unknown factors) can contribute to disease risk and onset. For scientists, knowing the risk factors can help to detect disease early or develop targeted therapies to treat the disease. For doctors, it helps to predict disease risk and tailor treatment.  And for the patient, it helps to know that diseases are complicated and risk isn’t 0% or 100%.


What can you do if you’re a genetic carrier?

In my last post, I talked all about what is means when you are a genetic carrier of a recessive gene.  To recap, the recessive gene will not cause disease, but your partner also has that recessive gene, you may have a child with a disease. Let’s think about the options, using a capital letter (G) as the normal gene and a lower case letter (g) as the recessive mutated gene.

carrier-noncarrier youandpartnercarrierIf you are a carrier, you’re have one copy of G and one copy of g (or Gg).  What if you have a child with someone who isn’t a carrier (GG)?  If you look at the possibilities (to the left) you have a 50/50 chance of having a child who isn’t a carrier or one who is.  But you will not have a child who has the disease.  On the other hand, if both you and your partner are carriers (see the picture on the right), you have 25% chance of having a child who isn’t a carrier, 50% chance of having a child who’s a carrier, and 25% chance of having a child who has the disease.

If you’re a carrier and your partner is a carrier, you know your odds.  So what are your options?  Before I start, if you’re dealing with this personally, please discuss all of this with a trained medical professional.  I can explain the biology of why things happen, but only your doctor can give you medical advice and treatment options.  Also, these decisions are all personal to you.  There is no one answer, and what works for you may not work for someone else – and this is often what we face when making these very personal medical decisions.


  • If you know that you and your partner are both carriers for a particular disease, you can choose not to get pregnant and avoid the risk altogether
  • Alternatively, you can get pregnant and  monitor the pregnancy closely.  Go ahead and roll the dice!  There is a 25% chance of having a child with that disease and a 75% chance that they won’t.  Having the knowledge in advance, you will know the likelihood and can monitor the pregnancy accordingly
  • There are tests like chorionic villus sampling  (CVS) that can test for genetic diseases (such as Tay-Sachs disease) before birth, if both you and your partner are carriers for a recessive gene that causes disease
  • If the developing child is found to have a genetic disease, depending on the disease and severity (e.g., if they will or will not survive at birth), there is the option to terminate the pregnancy. There also may be options for treatments while the child is developing or immediately at birth that may help decrease the severity of the disease right away.
  • You can choose instead to use a sperm or egg donor from someone who doesn’t carry that recessive gene.
  • You can use in vitro fertilization and check the genes of the embryo pre-implantation to select those that do not have two copies of the recessive genes.
  • Choose to adopt

As an aside, I asked my primary care physician about carrier testing a few years ago.peopleDNA  Without a family history of any genetic diseases, she was resistant (if not downright hostile) about me wanting to get carrier testing, and mentioned that insurance likely wouldn’t pay for the testing.  I’m hoping that my experience was not the norm, however, I don’t think that most primary care physicians have a deep understanding of genetics and genetics diseases and may be uncomfortable suggesting this type of screening because they would not know how to best interpret the results.  Interestingly, a number of companies now exist that will perform the carrier testing for you for a nominal fee, such as Pathway Genomics, Counsyl, and Natera.  I cannot recommend or discourage you from using or not using these services, however you generally need to work with your doctor to order these tests.

Again, these are all options, not medical advice, and all up to you as to what works best for you and your partner.  But with the knowledge of what may happen and why it may happen, you are at least armed with information to ask meaningful questions about yours and your non-existent child’s potential genes before or during your pregnancy,