The Immortal Life of Henrietta Lacks

This is my 150th post, so I want to talk about something meaningful. I just finished reading a book I started sometime in the middle of spring semester. I got about halfway before my mom borrowed it to read. I brought it on the flight to India knowing I would have plenty of time to read, but I ended up sleeping for a large portion of that time.

At any rate, I finally picked it up again yesterday, and I want to tell you about it because it affected me strongly. It's called The Immortal Life of Henrietta Lacks.

In it, Rebecca Skloot (who signed my book!) tells the story of the woman behind HeLa cells, as well as her descendants and family. HeLa cell lines all originated from a cervical cancer tissue sample taken from a black woman named Henrietta Lacks. As the first human cells found to be immortal (able to survive infinite divisions rather than stopping at 50 like normal cells), they were - and still are - used in research on pretty much everything. They are the lab mice of the cellular biology field. They could be cultured easily, and are (relatively) genetically identical. Experiments can be done with the knowledge that other researchers would be able to replicate the results (which is necessary to get rid of bias in science) because they can use the same cells.

Yet Henrietta Lacks never knew what was being done with her cells, and her family was never informed. What they were told was made difficult to understand by their lack of education. Nobody bothered to explain exactly what cells were, and how Henrietta herself was not being tortured by all the things being done to the cells. Researchers took blood samples to study the genetics of the cells, and the family thought they were being tested for cancer. When no results were forthcoming, they lived in constant fear that they would develop the same type of cancer and die. Entrepreneurs cultured and sold HeLa cells, but not a cent went to the Lacks family, which was left with no knowledge of this business, still living in poverty.

The story is eye opening. The only cells I have worked with are Chinese Hamster ovarian (CHO) cells, but it made me realize that when working with anything human, you really have to think about the patients. The purpose and possible good that could come from you research may be obvious to you, but to someone who has not dived as deeply into the subject as you have, it can be terrifying.

Biology has advanced to the point that scientists have to narrow down their focus and specialize in order to discover anything new (or so we usually think). This means that understanding most breaking news in the scientific world requires a grasp of a wealth of previous knowledge. So we get a little lazy and stop trying to explain all of our results.

Even I was caught up in this. Science has too many subtleties for the general public, I thought. People want absolutes, and every one of the "maybe"s that is part of the essence of science decreases their belief that science works, I thought. What could I do to alleviate that? There's not really much hope. But that's not true and what is is not all their fault. Science has come to be seen as something elite, something that is not relevant to normal people's lives. Compared to the decades of the Space Race, it's become unimportant. But scientists are partially to blame for not reaching out to make themselves understood.

I honestly think that this book should be required reading for any students interested in going into a biological field. Whether it's research or medicine that that fills up your time in your imagined future, this book will remind you to not forget that even while working for the greater good, you need to give a little time to the smaller good.

People Who Know More Than You

Okay, so the Maker Faire story is taking a while. I was only there for 5 hours or so and there was still a ton of stuff to write about, and I'm being slightly lazy.

In the meanwhile, let me fill the gap by talking about presentations, since one of those is the reason I was in Berkeley the last few days. Basically, I had to make a little presentation in lab meeting on Wednesday about what I've been doing. A little background about the project and the techniques, a quick recounting of my various failed attempts, and the display/explanation of the data from the one trial in which things did work, followed up by a short list of where to go from here.

I'm not usually nervous about presentations, but this one had me worrying a little bit. I've realized that it's quite nerve-wracking to give a presentation to people who know the subject better than you. Hell, the main paper involved was written by my PI. Who knows it better than she does?

Two days before, I was still figuring out thresholds for comparing the experimental and control data, turning my huge tables in Excel (240 rows x DW columns is no joke) into pretty graphs, and figuring out the best way to show off my awesome-looking results.

Negative control on the top left - no response. With the thing  I'm testing - huge response. Inhibiting the thing I'm testing - no response again. Woooo, the assay works!

That lasted up until the evening before the meeting. Now it was time to start on my Powerpoint.
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Yeah, a little late, but I actually don't procrastinate unless I know (unconsciously) I can make the deadline without too much stress. And this is something I've been working on for a whole semester, so I've got a pretty good understanding of it. Making the outline and the Powerpoint itself didn't take long.

The thing was, though, I'd seen some of the grad students in the lab presenting at lab meetings as well (one was practicing for her quals). They got asked a lot of tough questions. When I started, it was background, and nobody asked any questions. They all knew the stuff back and forth (I did mix up an important part, but my post-doc mentor was the only who caught it, and he waited until afterward to tell me). So I thought I was off the hook.

As soon as I got to my results, though, it was like a frenzy of (rather friendly) sharks. Most of the questions I got were on my data. How did I analyze it? Did I do this particular statistical analysis? Did I compare those two things? etc. Oh man. There were plenty of things I still had to do, so I couldn't answer everything, but apparently I still did a pretty good job.

So even though I'm not usually nervous about presentations, I've got to say: Whew. I'm glad that's over. For now.

A (Kind of ) New Take On Cancer Treatment

Cancer is a difficult disease to cure. Our current systems of classification for it are based on the symptoms rather than the cause. Yet the actual causes vary so much that it is difficult to generalize treatment anyway.

In essence, cancer is a disease of sociopathic cells. These cells no longer follow the rules of the cellular environment around them - they don't care about their neighbors and they don't listen to the advice that staying low is better for society (i.e., the body) as a whole.

Hey, I write a blog, not a webcomic, okay?

Now, anthropomorphizing aside, human cells are complex little things. The problem with finding a simple cure for cancer is that each instance of cancer may involve a different set of proteins becoming disabled or overactive. Cells have redundancies and backup pathways for most of their processes, but sometimes, even the backups break down. Add to that the existing genetic variation between individuals and you have a mess more complicated than a tesseract. The best we can do is try to prevent it by living healthily.

But now we may have a new weapon in our arsenal: a cancer vaccine. It is still being studied, but I can talk about the possibilities.

It won't prevent cancer in healthy people. That would be amazing, but you would have to correctly predict what type of cancer they were about to get and give them a vaccination specific for the markers those cells would express. And how would you know if it worked? Maybe you just cured something that wasn't even going to happen in the first place.

What it can do is prevent relapses. Once somebody has been diagnosed with cancer and treated with drugs and/or chemo, adding the vaccine helps the immune system do its part in the fight in getting rid of the few remaining cells. It helps to highlight parts of the cancer cells that are not normal so that our white blood cells know that these targets can be attacked. If you can catch the micrometastases before they grow back into full-fledged tumors, you can theoretically nip the problem of relapse in the bud and be fully cancer-free.

There's a lot of possibilities here, and I hope this avenue of research proves fruitful.

Why Neuroscience?

I've talked about why I do science in general. Now I want to talk about why out of all the interesting, amazing, and groundbreaking fields out there, I chose neuroscience.

For me, neuroscience is the next frontier though we still have yet to foray further than a figurative few feet into space and the ocean's depths (believe it or not, that alliteration was accidental).

Get out there, do some learning about the nervous system! Grab the spinal cord by the (dorsal and ventral) horns!

I want to know what makes me me. I want to know why I think the way I do, whether others think the same way, how it came to be that humans are able to do all of these tasks that would be tough for a (current-day) computer in a snap.

Wait, humans are faster than computers? I must have that backwards, right? The majority of us may not be able to do math at the speed of electricity, but we perform computations on problems that would take hours just to input into a computer in a matter of seconds, or less. Where a computer has to work through all of the possibilities for a thousand little variables that may be affecting the situation, we can take one glance and intuit the solution.

As Jonah Lehrer posits in How We Decide, our feelings and emotions and instincts and hunches are not inferior to the careful, methodical calculations of computers; they are actually the product of massive parallel processing that takes place beneath your consciousness. The problem is knowing when something is off in that processing, when a variable is not right, when a thought from a nearby stream is interfering - when to trust your instinct, and when not to.

In order to know when to trust our gut, however, we must know how we think so we can keep a mental eye out for those mistakes.

That brings me back to the point I want to make. After looking at the world around us, we've finally turned our attention and our questions back to ourselves. And now we've got the tools to actually get some of those answers.

Put A Sock On It: How Seals Follow Fish

How do you think seals catch fish?

Well, let’s guess. Humans rely greatly on vision to catch prey. Sharks can smell blood in the water from a mile away. Or since they’re in water, it could be taste.

How would anybody find this out?

A couple of scientists from Germany blindfolded seals and had them follow and find a small toy submarine. The blindfold ruled out tracking by vision, and the plastic of the submarine meant that no fishy smells could come into play.

Even when the submarine turned a corner before the seal was released, the seal followed the path of the sub exactly. If they had been listening, they would have gone straight to the sub.

The yellow curve is the path of the submarine, the red curve the path of the seal. The green (straight) line is the expected path of the seal if it were using sight or sound. The picture in the paper was much better, but I am rather proud of my seal despite its slight turtle-like appearance.

So what’s left is touch. That’s right, touch. The highly sensitive whiskers of seals can follow the trail of turbulence left in the water by a swimming fish. Covering a seal's whiskers with a sock prevents the animal from being able to find the sub (or fish).

It's difficult to think of seeing your world in touch, but many animals rely on senses other than vision. I wonder how it would feel to echolocate...

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Original paper:
Dehnhardt, G. et al. Hydrodynamic Trail-Following in Harbor Seals (Phoca vitulina). Science 293, 102-104(2001).

The War on Cancer

I just watch a TED talk by David Agus on the next steps in the war on cancer, and it reminded me of a class I took last semester.

What I learned in my Bio of Cancer class last semester is that we’ve pretty much got clinical cancer diagnosis and classification all wrong.

Because we didn’t initially (and to some extent still don’t) have the tools to do much else, we look at the symptoms – a tumor in your lung, a lump in your brain, an overproliferation of white blood cells.

But that doesn’t help in treating the cancer. One breast cancer may have the protein HER2 amplified, while another may not. You can’t use Herceptin for both.

It’s true that certain mutations show up more often in certain cell types or body parts, because the pathways involved are the ones expressed in those cells. Still, there are usually plenty of other mutations that show up in the same cell types and even the same cells.

Just classifying cancers by their mutations isn’t enough though, because just as in real estate, location matters. The environment around the cells (extracellular matrix, blood vessels, neighboring cells) can help determine whether the abnormal cells can grow. There are carcinoma (epithelial cell cancers) cells that are provided with growth factors by the cancer-associated (but not cancerous themselves) fibroblasts surrounding them.

Look at all the cell types and growth factors involved in the tumor microenvironment! 
(I stole this picture from the Pittet Lab at the Center for Systems Biology)

So what we need then is some integration of our current form of diagnosis and our knowledge of the cancer genome. I'll link to Agus's TedMed talk again, since it's pretty informative. Take a look.

Also, HTML does not show up on titles in a Google Reader. Oops.

Contact Inhibition

Naked mole rats never get cancer.

Their contact inhibition mechanism is more sensitive, which means they stop dividing more quickly when they touch nearby cells.

But so many factors are involved in cancer development that I think the real difference is that they have two contact inhibition mechanisms. A backup ensures that losing a single gene isn’t enough to knock out the whole pathway and allow hyperplasia (overproliferation of cells, the first step towards cancer).

Fighting HIV: It's What's Inside That Counts (Really)

So researchers are finding another approach to battling HIV that makes use of genes we already have? Cool. Here's an excerpt from the paper that came out a few months ago:

A group of scientists led by Nitya Venkataraman and Alexander Colewhether wanted to try a new approach to fighting HIV - one that worked with the body's own immune system. They knew Old World monkeys had a built-in immunity to HIV: a protein called retrocyclin, which can prevent HIV from entering cell walls and starting an infection. So they began poring over the human genome, looking to see if humans had a latent gene that could manufacture retrocyclin too. It turned out that we did, but a "nonsense mutation" in the gene had turned it off at some point in our evolutionary history.
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The team found a way to use a compound called aminoglycosides, which itself can cause errors when RNA transcribes information from DNA to make proteins. But this time, the aminoglycoside error would work in their favor: It would cause that RNA to ignore the nonsense mutation in the junk gene, and therefore start making retrocyclin again. In preliminary tests, their scheme worked. The human cells made retrocyclin, fended off HIV, and effectively became AIDS-resistant.

Wow. Seriously, that's amazing. Unfortunately, judging by some of the comments on the article, I think a few people might interpret this the wrong way. I'm taking a look at the paper, and I want to make a few points: