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Comment Re:cancer stem cells? (Score 1) 149

yes, it seems amazing, but in most solid tumors the vast majority of cells are completely different. unfortunately it is not incompatible with cancer cell life.

you are also getting genome (chromosome) change confused with mutations ie the difference between genomic and genetic instability. each cell in a tumor has 10s to 100s of mutations, but chromosomal change in the form of rearrangments, deletions, duplications, inversions, and aneuploidy play a much larger role.

Comment Re:cancer stem cells? (Score 1) 149

haha...yeah i'm quite familiar with the cancer stem cell field. recent discoveries have fallen far short of showing what recent rhetoric claims.

although the stem cell hypothesis has become a popular idea, there at lest as much resistance to the hypothesis as there is support for it. try to find a cancer stem cell paper where karyotypic analysis has been applied to 'cancer stem cells'. you won't find one. you know why? the supposed stem cells are actually very heterogeneous when you look at the genome on a cell by cell basis. it really shoots the hypothesis dead in its tracks. try getting 'cancer stem cells' from a group that has published on them to do a proper analysis, and you either get told no, or don't hear back from them after the results come out.

the reason tumors are so hard to treat, especially solid tumors? each cell is different. each cell responds differently to the chemo regimen which increase the probability that one or a few cells survive and evolve which leads to resistance.

Comment cancer stem cells? (Score 1) 149

there is no such thing, as by definition stem cells must faithfully reproduce their genome. in cancer nearly each cell has its own genome, therefore there is little to no faithful reproduction and hence there can be no true stem cells.

metformin treatment will make the inevitable splash in the media along with whatever 'cancer gene' is found next week. will it lead to better treatments? doubtful. look at how well anti-angiogenesis drugs have worked in humans, and how well they worked in mice. in mice they worked well enough for a nobel prize. in humans they work for about two weeks before resistance is aquired

Comment Re:Data analysis a rapidly growing problem in Biol (Score 1) 101

You have to be very careful about what findings at different levels actually mean, and how the various levels correlate.

For example when looking at duplications/expansions in cancer, an expansion of a locus results in about a 50% correlation between DNA level change and expression level chane. Protein and gene expression levels correlate 50 to 60% of the time (or less depending on who's data you look at). So therefore, being gracious and assuming a 60% correlation at the two levels you are already below a 40% correlation. Add in post translation modifications, sub-cellular localization and the requirement for other players within a functional pathway to exhibit a specific behavior and what you have is a tangled mess that you can spin almost any story about a favorite gene. But does it have meaning for diagnosis and treatment? I'd definitely hedge my bet.

Its that big of a mess and that isn't even considering the vast population heterogeneity of each tumor.

Comment Buttload of data (Score 2, Interesting) 101

Illumina's Solexa sequencing produces around 7 TB of data per genome sequencing. Its a feat just to move the data around, let alone analyze it. Its amazing how far sequencing technology has come, but how little our knowledge of biology as a whole has advanced. 'The Cancer Genome' does not exist. No tumor is the same and in cancer, especially solid tumors, no two cells are the same. Sequencing a gamish of cells from a tumor only gives you the average which may or may not give any pertinent information about the tumor. Vogelstein's group has shown this quite convincingly but hardly anyone truly looks at what the data really says.

The Manga Guide to Statistics 164

stoolpigeon writes "Many manga titles that are popular in Japan are being translated into English and published in the United States. This trend continues with a book that puts a slightly different spin on manga. The Manga Guide to Statistics, part of a series already popular in Japan, seeks to entertain while it informs. There are many elements here that can be found in any manga; a young love-struck girl, giant eyes, small noses and exaggerated emotional responses. What many may not have seen in manga before are things like calculating the mean, median and deviation of bowling scores. And that is just the start." Read below for the rest of JR's review.

Comment Re:Not realistic (Score 1) 198

You always have to be skeptical when an institute pushes news of a discovery that has not been published yet. There are definitely inherent problems with current stem cell work (embryonic and non-embryonic), but we're getting better. However I don't think we've even thought about the largest hurdles and how to get over them. The biggest problem I see with this and other stem cell work is it involves transforming cells with multiple genes (often these genes are integrated into the host genome) which a number of them are usually potent oncogenes (c-myc is a good example used often). The result you typically get is a cell with similar phenotype to the tissue that the researcher is trying to grow, but these cells often aren't normal karyotypically. Karyotypic change is one of (if not the major) driving force of tumorigenesis and is involved in a number of other diseases, but most of the stem cell labs never check karyotypes. They are always assumed to be normal when they aren't. Unstable karyotypes are one of the reasons that embryonic stem cell research has been problematic. For some reason, when put into culture especially for extended periods of time embryonic stem cells are less stable than somatic stem cells. Hence embryonic stem cell therapy often results in cancer.

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