5 ms·

This is overstating the issue in the present day. An immortalised cell line is after all a very convenient but very contrived model of a real system. For exampl

by Gatsky 9y ago

This is overstating the issue in the present day. An immortalised cell line is after all a very convenient but very contrived model of a real system. For example, the greatest revolution in cancer treatment in the last 10 years has been immunotherapy, which was developed using more realistic models than 'cell line in a dish'.

SubiculumCode 9y ago
30,000 studies are a lot, but are only 0.2% of studies using cell lines, per my light reading of the paper. Moreover, some results will still generalize, as even if contaminated, they may still be cancerous cells of another lineage. In some ways I think these kinds of things are more about having the time and resources to keep things organized. It is a constant struggle in labs by people who may be expert biologists, but amateur database managers.
- brfox 9y ago
  And real tumors are quite heterogeneous, so maybe experiments done with contaminated cell lines are more realistic than those done with pure cell lines.
iskander 9y ago
Immunotherapy research uses cell lines as much as every other branch of microbiology. For example, the T2 cell line is lacking in a peptide transport protein called TAP, which makes it handy for studying the immune recognition of arbitrary peptides (not just those from the cell). * Examining the presentation of tumor-associated antigens on peptide-pulsed T2 cells (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894244/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894244/) And if you want to study the effectiveness of any immunotherapy, it's very common to implant a mouse cell line like B16 in live mice and then see if the tumor regresses under different treatment conditions (e.g. with or without checkpoint blockade). Example: * Localized Oncolytic Virotherapy Overcomes Systemic Tumor Resistance to Immune Checkpoint Blockade Immunotherapy (http://stm.sciencemag.org/content/6/226/226ra32.short http://stm.sciencemag.org/content/6/226/226ra32.short) ...but really every preclinical paper on a new kind of vaccine or immunomodulatory antibody uses cancer cell lines in this way.
- Gatsky 9y ago
  They (and my lab) use cell lines for mechanistic studies, but the animal model is key. You describe a syngeneic model which is different of course.
nonbel 9y ago
This is what you always hear from biomed/psych/etc. It simply is not important to get details right. Misinterpret the results of your analysis (p-values), use the wrong cell lines, measure the wrong thing, etc. It rarely seems to affect the conclusions. If anyone who points out errors is being pedantic, it makes you wonder about the point of doing all that. Just come up with an idea A, say "heads = conclusion A", "tails = conclusion not A", and flip a coin.
- Fomite 9y ago
  I think one of the things that is actually happening is that for many examples, while the quantitative answer changes, the qualitative conclusion isn't altered by the errors. In graduate school, as part of a class on survival analysis, we subjected the same data set to increasingly sophisticated analysis techniques to account for all kinds of things. Each time, the effect estimate changed. At the end, while discussing them, the professor asked a very simple question: "Do any of these suggest that HAART is a bad idea?" Similarly, during the Ebola epidemic, when everyone was fussing about the various forecasts missing the mark, etc., what they were actually predicting was "This is a serious crisis that needs international intervention".
  - nonbel 9y ago
    I'm sure that HAART is a good idea sometimes and a bad idea other times. Also, this will change as time goes on (HIV mutates, demographics change, other treatments are available, etc) I'm also sure that there are many things going on at any given moment that should count as "serious crisis that needs international intervention". The real question is whether it is a more serious crisis than other things currently happening. To deal with both these issues you are going to need deeper understanding than "good idea vs bad idea" or "is crisis vs not crisis". But the real problem with being unable to quantify your understanding is that you are left unable to make precise predictions, thus you can never perform any stringent tests. If all you can predict is something vague (eg, HAART will increase 5 year survival), there will be many ways to misinterpret the data in support of your explanation even if it is totally wrong.

by Gatsky 9y ago

SubiculumCode 9y ago

30,000 studies are a lot, but are only 0.2% of studies using cell lines, per my light reading of the paper. Moreover, some results will still generalize, as even if contaminated, they may still be cancerous cells of another lineage. In some ways I think these kinds of things are more about having the time and resources to keep things organized. It is a constant struggle in labs by people who may be expert biologists, but amateur database managers.

brfox 9y ago
And real tumors are quite heterogeneous, so maybe experiments done with contaminated cell lines are more realistic than those done with pure cell lines.

iskander 9y ago

Immunotherapy research uses cell lines as much as every other branch of microbiology. For example, the T2 cell line is lacking in a peptide transport protein called TAP, which makes it handy for studying the immune recognition of arbitrary peptides (not just those from the cell). * Examining the presentation of tumor-associated antigens on peptide-pulsed T2 cells (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894244/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894244/) And if you want to study the effectiveness of any immunotherapy, it's very common to implant a mouse cell line like B16 in live mice and then see if the tumor regresses under different treatment conditions (e.g. with or without checkpoint blockade). Example: * Localized Oncolytic Virotherapy Overcomes Systemic Tumor Resistance to Immune Checkpoint Blockade Immunotherapy (http://stm.sciencemag.org/content/6/226/226ra32.short http://stm.sciencemag.org/content/6/226/226ra32.short) ...but really every preclinical paper on a new kind of vaccine or immunomodulatory antibody uses cancer cell lines in this way.

Gatsky 9y ago
They (and my lab) use cell lines for mechanistic studies, but the animal model is key. You describe a syngeneic model which is different of course.

nonbel 9y ago

This is what you always hear from biomed/psych/etc. It simply is not important to get details right. Misinterpret the results of your analysis (p-values), use the wrong cell lines, measure the wrong thing, etc. It rarely seems to affect the conclusions. If anyone who points out errors is being pedantic, it makes you wonder about the point of doing all that. Just come up with an idea A, say "heads = conclusion A", "tails = conclusion not A", and flip a coin.

Fomite 9y ago
I think one of the things that is actually happening is that for many examples, while the quantitative answer changes, the qualitative conclusion isn't altered by the errors. In graduate school, as part of a class on survival analysis, we subjected the same data set to increasingly sophisticated analysis techniques to account for all kinds of things. Each time, the effect estimate changed. At the end, while discussing them, the professor asked a very simple question: "Do any of these suggest that HAART is a bad idea?" Similarly, during the Ebola epidemic, when everyone was fussing about the various forecasts missing the mark, etc., what they were actually predicting was "This is a serious crisis that needs international intervention".
- nonbel 9y ago
  I'm sure that HAART is a good idea sometimes and a bad idea other times. Also, this will change as time goes on (HIV mutates, demographics change, other treatments are available, etc) I'm also sure that there are many things going on at any given moment that should count as "serious crisis that needs international intervention". The real question is whether it is a more serious crisis than other things currently happening. To deal with both these issues you are going to need deeper understanding than "good idea vs bad idea" or "is crisis vs not crisis". But the real problem with being unable to quantify your understanding is that you are left unable to make precise predictions, thus you can never perform any stringent tests. If all you can predict is something vague (eg, HAART will increase 5 year survival), there will be many ways to misinterpret the data in support of your explanation even if it is totally wrong.