Merry Xmas, Happy Hanukkah, etc

I haven't updated for the past few days as most of the stuff I own is now in boxes, waiting for the big move on Monday, however, I just wanted to take a couple of seconds to wish everyone the best over the holidays. I'll be back to blogging around New Years, by which point I should be in the new house, and ready to get back to FindPeaks and SNP finding. Wheee!!

In any case, I hope everyone is able to spend some time with their family, and enjoy a few days of rest. For those people in Vancouver, I hope you haven't had to push as many cars around as I have. (-;

Cheers!

The Biology of Cancer - Robert A. Weinberg

I spent the last three weeks reading this textbook, as suggested by one of the members of my committee and have become intimately familiar with it's content. So, it only makes sense for me to do a quick synopsis of this book, to share my opinions on it. (Not that my opinion makes a big difference to the author, I'm sure, but hey, if you're reading my blog, you'll be used to hearing my opinions.)

The first thing I have to say is that this textbook is very well written. It's clear, it's concise, and it explains complex processes very well. On that point alone, I can't see anyone in this field who would find any reason not to keep a copy nearby. This book is now one of two that actually sits out on my book case, within arms reach. (The other is Voet and Voet, Biochemistry - My other textbooks sit in a filing cabinet a few feet away.)

One of the things that impressed me most about this textbook was the CD-Rom in the back. I can't tell you how many times I've been disappointed by the contents of the CDs that accompany textbooks, but this one surprised me. I watched the small number of movies, which didn't do much for me, but moved on into the "sidebars" and artwork, and that's where I found the true value. The supplementary sidebars are really neat, and add a lot of context to the material in the text. They're optional, but are a really great way of reinforcing some of the information that appears in the text. The artwork is also incredibly valuable. I know I've often looked at figures in textbooks and wished it were available to include in a presentation I'm working on - eg. my comprehensive exam talk - and not been able to find something comparable elsewhere that fits. Here, every single figure in the text is given to you as a .jpg or comparable file. That alone might make this textbook worth buying! (Note, the images are copyright, so you can't distribute them, but you can certainly incorporate them or modify them under the fair use section of copyright law - or whatever your local laws provide.)

I mentioned the supplementary sidebars on the CD, but the text itself is full of them, and they are a very effective way of keeping you interested in the material. They're full of interesting facts, examples of how information was discovered, what exceptions exist to the rules... and the occasional discussion of how the information impacts cancer patients. They truly make the textbook a joy to read.

Of course, with all the positive comments above, you might think this is the perfect textbook - and it's pretty close, I'll have to admit, but there were a few things that I wasn't too thrilled about.

My biggest complaint is that much of the textbook is organized around either chronological events, or a sort of detective style story, leading you through the "how" and the "why" of each discovery. In many chapters, this is an extremely effective device, but there were times when I just wanted to find out how things work and not have to follow all of the twists and turns that faced the scientists who did the work.

With that said, the next complaint was that when the twists and turns were interesting and I wanted to follow up more on the work, I found it difficult or impossible to figure out which of the references cited for each chapter were relevant. There is no guide to which articles or publications were used at any point. It makes the paragraphs easier on the eyes, I suppose, but can be very discouraging if you just want to track down a particular experiment or two.

Finally, my third complaint is the synopsis and prospects section at the end of each chapter. For the most part, I really enjoyed these sections, but their purpose was relatively vague. Sometimes they performed a review, while in other chapters they introduced entirely new concepts. Again, this is a minor complaint, but it did irk me when I thought I was reviewing the chapter and would come across things I did not recall seeing earlier. (Much page flipping would ensue.)

Making up for the synopsis and prospects section, however, is a great "key concepts" section that invariably follows. This was a key tool for my review - if anything in the key concepts section that seemed unfamiliar or unclear would send me back into the chapter to make sure I hadn't missed things. It really reinforced the lessons found earlier in the chapter, in case I'd been dozing somewhere earlier in the 60-80 pages per chapter.

So, to sum up my review, this textbook got a 9 out of 10. It was infinitely more readable than most science textbooks, told a great story, and provides an extremely valuable reference for people in the field. However, that last 10% was somewhat disappointing in making it a great starting point for further research, simply because the author didn't provide an easy way to access the primary material while reading, and the matter of having to wade through a lot of history to get to the current status of the research on each topic.

If Programming languages were religions.

Ages ago, I said I'd write a post comparing the different programming languages out there for bioinformtics. I never got around to it, but someone else wrote a nice comparison of each language to religions. (Yes, I found it on slashdot, so probably everyone who reads my blog will have come across it somewhere else.)

At any rate, if you haven't yet seen it, you might enjoy taking a peak. It's quite funny.

http://www.aegisub.net/2008/12/if-programming-languages-were-religions.html

I'm now back at work, and getting ready to do some serious pre-xmas/post-comps programming, but I can't seem to get back in to the logical thinking thing...

For those who are curious, yes, I have some findpeaks updates coming. No, I havent stopped supporting it. (-:

Progeria follow up.

I mentioned progeria in one of my posts, this week, and how I proposed it would be a depletion of stem cells, as opposed to a depletion of cells, in general. As is often the case, it turns out someone else is already working on that idea. Oddly enough, it's even one of my committee members. While waiting for my committee to finish deliberating on my fate, I saw a paper tacked up on the wall:

Progeria of Stem Cells: Stem Cell Exhaustion in Hutchinson-Gilford Progeria Syndrome

Oh well. At the very least, it's nice to know I wasn't wrong. (=

new title

That's right - I'm no longer just a "graduate student," I'm now officially a "PhD Candidate."

Not that that means anything, and not that it was really worth the pain, but I guess it's some compensation for going through the adventure of comprehensive exams.

Pain, you ask? Why pain?

Well, there was the whole idea that I should learn all of the biology of cancer in 3 weeks, which I think I did a reasonably good job of doing, only to have VERY few questions on it. Instead, my committee members asked about the following topics:

• What are common breast cancer drugs, and what are their mechanisms?
  
• How does Blast work? What algorithms are used for analyzing DNA arrays?
• What are ESTs, and how could you apply those technologies to your research?

In general, they're not bad topics, but I didn't study a single one of those, since they're utterly unrelated to my thesis.

The examiner who asked about ESTs was making a point, suggesting that I should use a Motif scanner to search my ~220Million DNA fragments (of ~36bp each) for motifs that would indicate a splice junction point, and then use the fragments on either side of the presumed break point (down to ~16-mers) and blast those against the genome. The more I think about this idea, the less I like it. I also don't have 5 years to let the job run.

Anyhow, the exam is over with. I could have answered the questions better, I could have done a better presentation, and I probably could have prepared differently, but it never would have occurred to me to study the blast algorithm, drug mechanisms and clustering techniques for arrays. Who knew?

If I had to do comps again, I probably wouldn't have done much differently. I asked my committee members for what topics they would like to discuss with me and what I needed to study, and then prepared for those questions. One committee member was very helpful in that respect, and I learned a lot preparing for the suggested questions. I think I even answered that set reasonably well. (nerves notwithstanding.)

At the end of the day, I'm just glad it's over. It's humbling to know how much you don't know.

In my presentation today, I closed with two quotes, and I thought I'd share them here. I'm sure all graduate students can immediately grasp their relevance.

“In the fields of observation chance favors only the prepared mind.”
--Louis Pasteur

“To achieve great things, two things are needed; a plan, and not quite enough time.”
--Leonard Bernstein

Edit: I suppose I shouldn't be quite so obtuse. Many of the things my committee brought up were to demonstrate that many of the issues facing 2nd generation sequencing have been tackled by other technologies in the past, and that knowing those technologies would be a good way to keep from reinventing the wheel. That part, I take as constructive criticism. I will have to read up on how array data is processed at some point, though I still don't think I'll use motif finding on 220Million+ fragments. (-;

countdown to comps continues..

Today has been a relatively productive day in one sense. I finally finished reading the Biology of Cancer (Weinberg), after about 2 solid weeks of doing a chapter a day. At about 60-75 pages a day, it was pretty intense, but I learned a LOT. (Well, how could I not?)

Since the last chapter was on drug design, an area I'm familiar with, it was pretty easy reading and went by pretty quickly. There are only so many times you can learn about Gleevec.

So I moved on to a few other review questions suggested by my committee... such as "Draw a gene" and "penetrance vs. expressivity," which made for a nice general review.

And then I moved on to a few papers. One of them discussed doing PET sequencing from 2nd generation machines to find chromosomal fusion points in cancer (Bashir et al., 2008). The math was interesting enough, but the end result was that they tested it on BACs. When I get around to doing PET on my samples, this will be a good review to make sure we get the parameters right, but the paper didn't go far enough, really, in my humble opinion. I was hoping for more.

A second paper that I went over was on identifying SNPs in 2nd generation sequencing, using bovine DNA (Tassell et al, 2008). I don't know what to make of their method though. They combined samples from 8 different types of cow (I didn't know there were that many types of cow!), and then sequenced it to a depth of 10x, so that on average, each read covering a specific location should reflect the sequence from a different breed. Maybe I'm missing something, but SNP calling on this should technically be impossible - even assuming you get 0% sequencing errors, how confident can you be in a SNP found only once? Anyhow, I had to abandon this paper... I just didn't understand how they could draw any conclusions at all from this data.

Finally, a colleague of mine (Thanks Simon!) recommended a review by Weinburg himself on "Mechanisms of Malignant Progression." (Weinburg, 2008). For anyone who ends up reading his textbook from cover to cover, I highly suggest following up with his review. Things have changed a bit from the time the textbook was published to now, which makes this review a timely followup. In particular, it flushes out much of the textbook's discussion of Epithelial-Mesenchymal Transitions (EMTs). Not that I want to go into much detail, but it's clearly worth a browse - and it's only 4 pages long. (MUCH shorter than the 790 pages I had to read to understand what he was talking about in the first place.) (-:

So now, this leaves me with 1 day left - just enough time to gather together my 15 minute presentation, to review the chapter summaries from the Biology of Cancer, and still have enough time to freak out a little bit. Perfect timing.

Nothing like reading to stimulate ideas

Well, this week has been exciting. The house sale competed last night, with only a few hiccups. Both us and the seller of the house we were buying got low-ball offers during the week, which provided the real estate agents lots to talk about, but never really made an impact. We had a few sleepless nights waiting to find out of the seller would drop our offer and take the competing one that came in, but in the end it all worked out.

On the more science-related side, despite the fact I'm not doing any real work, I've learned a lot, and had the chance to talk about a lot of ideas.

There's been a huge ongoing discussion about the qcal values, or calibrated base call scores that are appearing in Illumina runs these days. It's my understanding that in some cases, these scores are calibrated by looking at the number of perfect alignments, 1-off alignments, and so on, and using the SNP rate to identify some sort of metric which can be applied to identify an expected rate of mismatched base calls. Now, that's fine if you're sequencing an organism that has a genome identical to, or nearly identical to the reference genome. When you're working on cancer genomes, however, that approach may seriously bias your results for very obvious reasons. I've had this debate with three people this week, and I'm sure the conversation will continue on for a few more weeks.

In terms of studying for my comprehensive exam, I'm now done the first 12 chapters of the Weinberg "Biology of Genomes" textbook, and I seem to be retaining it fairly well. My girlfriend quizzed me on a few things last night, and I did reasonably well answering the questions. 6 more days, 4 more chapters to go.

The most interesting part of the studying was Thursday's seminar day. In preparation for the Genome Sciences Centre's bi-annual retreat, there was an all-day seminar series, in which many of the PIs spoke about their research. Incidentally, 3 of my committee members were speaking, so I figured it would be a good investment of my time to attend. (Co-incidentally, the 4th committee member was also speaking that day, but on campus, so I missed his talk.)

Indeed - having read so many chapters of the textbook on cancer biology, I was FAR better equipped to understand what I was hearing - and many of the research topics presented picked up exactly where the textbook left off. I also have a pretty good idea what questions they will be asking now: I can see where the questions during my committee meetings have come from; it's never far from the research they're most interested in. Finally, the big picture is coming together!

Anyhow, two specific things this week have stood out enough that I wanted to mention them here.

The first was the keynote speaker's talk on Thursday. Dr. Morag Park spoke about the environment of tumours, and how it has a major impact on the prognosis of the cancer patient. One thing that wasn't settled was why the environment is responding to the tumour at all. Is the reaction of the environment dictated by the tumour, making this just another element of the cancer biology, or does the environment have it's own mechanism to detect growths, which is different in each person. This is definitely an area I hadn't put much thought into until seeing Dr. Park speak. (She was a very good speaker, I might add.)

The second item was something that came out of the textbook. They have a single paragraph at the end of chapter 12, which was bothering me. After discussing cancer stem cells, DNA damage and repair, and the whole works (500 pages of cancer research into the book...), they mention progeria. In progeria, children age dramatically quickly, such that a 12-14 year old has roughly the appearance of an 80-90 year old. It's a devastating disease. However, the textbook mentions it in the context of DNA damage, suggesting that the progression of this disease may be caused by general DNA damage sustained by the majority of cells in the body over the short course of the life of a progeria patient. This leaves me of two minds: 1), the DNA damage to the somatic cells of a patient would cause them to lose tissues more rapidly, which would have to be regenerated more quickly, causing more rapid degradation of tissues - shortening telomeres would take care of that. This could be cause a more rapid aging process. However, 2) the textbook just finished describing how stem cells and rapidly reproducing progenitor cells are dramatically more sensitive to DNA damage, which are the precursors involved in tissue repair. Wouldn't it be more likely then that people suffering with this disease are actually drawing down their supply of stem cells more quickly than people without DNA repair defects? All of their tissues may also suffer more rapid degradation than normal, but it's the stem cells which are clearly required for long term tissue maintenance. An interesting experiment could be done on these patients requiring no more than a few milliliters of blood - has their CD34+ ratio of cells dropped compared to non-sufferers of the disease? Alas, that's well outside of what I can do in the next couple of years, so I hope someone else gives this a whirl.

Anyhow, just some random thoughs. 6 days left till the exam!