In vitro evolution and whole genome analysis to study chemotherapy drug resistance in haploid human cells
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Summary: The authors examined the genomic basis of resistance evolution in human chronic myelogenous leukemia (CML) near-haploid cell lines to 5 separate chemotherapeutic agents.
Using either whole genome or whole exome analysis, they found numerous instances of single nucleotide polymorphisms and copy number variants, including amplifications and deletions, among lines. They then used subsequent knockdown or knockout experiments to confirm that these variants, in fact, lead to increased resistance in these lines.
The work is interesting, timely, and has potential clinical implications. For example, the resistance alleles identified here could be closely examined in future studies in order to develop treatment strategies. However, the experimental design has certain limitations, advances in understanding chemotherapy resistance mechanisms is currently modest, and the presentation of results can be improved. We feel overall that these could be addressed, but that they will require significant extra experimental work.
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Abstract
Background
In vitro evolution and whole genome analysis has proven to be a powerful method for studying the mechanism of action of small molecules in many haploid microbes but has generally not been applied to human cell lines in part because their diploid state complicates the identification of variants that confer drug resistance. To determine if haploid human cell could be used in MOA studies, we evolved resistance to five different anticancer drugs (doxorubicin, gemcitabine, etoposide, topotecan, and paclitaxel) using a near-haploid cell line (HAP1) and then analyzed the genomes of the drug resistant clones, developing a bioinformatic pipeline that involved filtering for high frequency alleles predicted to change protein sequence, or alleles which appeared in the same gene for multiple independent selections with the same compound. Applying the filter to sequences from 28 drug resistant clones identified a set of 21 genes which was strongly enriched for known resistance genes or known drug targets ( TOP1, TOP2A, DCK, WDR33, SLCO3A1) . In addition, some lines carried structural variants that encompassed additional known resistance genes ( ABCB1, WWOX and RRM1) . Gene expression knockdown and knockout experiments of 10 validation targets showed a high degree of specificity and accuracy in our calls and demonstrates that the same drug resistance mechanisms found in diverse clinical samples can be evolved, discovered and studied in an isogenic background.
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Reviewer #3:
The authors showcase results from an experimental pipeline aiming at demonstrating how evolution of in vitro cancer models can be exploited to identify somatic genomic and structural variants associated with the emergence of drug resistance.
To this aim the authors unbiasedly selected 5 widely used chemotherapeutic agents via systematically treating the HAP-1 cell line with 16 different drugs then chose those yielding clinically compatible half-maximal effective concentrations. After generating stably resistant clones ) of the HAP-1 parental cell line, across a number of replicates (by culturing in sublethal doses of the selected compounds), the authors whole-exome/whole-genome sequenced their models and compared variants observed in the resistant clones versus those present in the parental line.
In this way the authors …
Reviewer #3:
The authors showcase results from an experimental pipeline aiming at demonstrating how evolution of in vitro cancer models can be exploited to identify somatic genomic and structural variants associated with the emergence of drug resistance.
To this aim the authors unbiasedly selected 5 widely used chemotherapeutic agents via systematically treating the HAP-1 cell line with 16 different drugs then chose those yielding clinically compatible half-maximal effective concentrations. After generating stably resistant clones ) of the HAP-1 parental cell line, across a number of replicates (by culturing in sublethal doses of the selected compounds), the authors whole-exome/whole-genome sequenced their models and compared variants observed in the resistant clones versus those present in the parental line.
In this way the authors identified recurrent loss of function variants across replicates in the drug resistant clones per each drug and were able to reproduce the increase in drug resistance of the parental line by knocking out the genes found altered in the drug resistant clones or they were able to reproduce the same finding by pharmacologically inhibiting genes found to host gain-of-function mutations in the resistant clones. Thus highlighting a new potential target for combinatorial cancer therapy and chemosensitization.
Briefly, this is a nice piece of work showing for the first time that exploiting in vitro evolution paired with whole genome analysis for identifying targets for combinatorial therapy and elucidate the mechanisms involved in the emergence of drug resistance is practically feasible.
The experimental pipeline and the followup validation experiments are well thought and designed and outcomes convincingly support the authors' final claim. There are no arbitrary nor unjustified choices and the showcased platform seems to be robust enough.
I would like to see the following few points addressed/answered:
The authors focused only on chemotherapeutics while composing their initial search basin. Would considering also few targeted therapies worthy? or it is known that no effects would be exerted on HAP-1? This should be briefly mentioned.
The title of the manuscript can be improved: the authors are deconvolving genomic alterations whose acquisition is linked to the development of drug resistance, thus potential chemosensitising targets or targets for combinatorial therapies. This could be better reflected by the title. As it is now it reads like the main aim is to identify 'innate/intrinsic' targets/cancer-dependencies.
Mutagenesis experiments to identify mutations that are linked to the emergence of drug resistance might be mentioned in the introduction, and the following work cited: PMID: 28179366.
When mentioning the 'Genomics of Drug Sensitivity in Cancer' portal (www.cancerrxgene.org) the following two works (describing the online resource) should be cited: PMID: 23180760 and PMID: 27397505
Figure 1 nicely describes the experimental pipeline presented in this manuscript however it should be completed with a final panel or a couple of panels illustrating the genomic comparison between parental and drug resistant clones to identify SNV and CNV associated with drug resistance.
It is not clear what the numbers in the 'fennel' in figure S3A refer to. Resistant clones within an individual tested drug? individual resistant clone or overall cases? This should be specified.
As it is presented, Table 1 is not very informative/clear, I would replace it with a barplot.
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Reviewer #2:
In this manuscript, Jado et al. studied the in vitro evolution of the haploid cell line HAP1 in the presence of five common anti drug agents. The authors exposed the cells to the drugs and then performed whole-exome or whole-genome sequencing (WES or WGS) in order to identify point mutations (SNVs) and copy number changes (CNVs) associated with resistance. In multiple cases, the authors confirmed that shRNA-mediated knockdown of a candidate gene (that is, a gene that was recurrently mutated at high allele fractions, or recurrently lost/gained) indeed conferred resistance to the drug.
Overall, this is an elegant demonstration that in vitro evolution in cancer cell lines can be useful for the study of chemotherapy resistance. Surprisingly, relatively few studies attempted to identify resistance mechanisms to anticancer drugs …
Reviewer #2:
In this manuscript, Jado et al. studied the in vitro evolution of the haploid cell line HAP1 in the presence of five common anti drug agents. The authors exposed the cells to the drugs and then performed whole-exome or whole-genome sequencing (WES or WGS) in order to identify point mutations (SNVs) and copy number changes (CNVs) associated with resistance. In multiple cases, the authors confirmed that shRNA-mediated knockdown of a candidate gene (that is, a gene that was recurrently mutated at high allele fractions, or recurrently lost/gained) indeed conferred resistance to the drug.
Overall, this is an elegant demonstration that in vitro evolution in cancer cell lines can be useful for the study of chemotherapy resistance. Surprisingly, relatively few studies attempted to identify resistance mechanisms to anticancer drugs using spontaneous evolution experiments, despite the prevalence of this approach in the study of antibiotics resistance. While the authors were able to identify and validate a few known resistance mechanisms to very commonly-used drugs, a major limitation of the current study is that it doesn't really shed any new light on chemotherapy resistance mechanisms. While I appreciate the time and effort that were required to perform the drug experiments and sequence the various clones, the follow-up studies are rather superficial and do not really extend our knowledge on any of the proposed mechanisms of drug resistance.
Specific Comments:
The AF threshold of 0.85 seems pretty arbitrary. Can this threshold be determined empirically based on the sequencing depth and noise of each sample? Mutations with AF>0.85 may still be subclonal, whereas mutations with AF<0.85 may still be of interest.
While the rationale for performing the initial experiments in HAP1 cells is clear, it is unclear why no validation experiments were performed in additional cancer cell lines. It is imperative to perform the knockdown experiments not only in HAP1 cells but in a panel of additional cancer cell lines, in order to examine whether these are general mechanisms of resistance.
Multiple CRISPR-Cas9 studies were performed to identify mechanisms of drug resistance to anticancer drugs. The authors note in the Discussion that these studies "are useful but cannot readily reveal critical gain-of-function, single nucleotide alleles". This makes sense, yet in almost all cases the authors use a simple loss-of-function shRNA assay in order to confirm their initial sequencing results. This means that the added value of the spontaneous evolution approach is rather limited, either because other mechanisms of resistance are much less common or because it is much easier to identify them.
In the gemcitabine resistance experiment, the authors confirmed that RRM1 KD increased the sensitivity of the cells to the drug. A complementary experiment should be to test whether the overexpression of RRM1 would increase the resistance.
In several cases, multiple SNVs or CNVs were identified in the same resistant clone at a clonal (or near-clonal) AF. Other than following up on "immediate suspects", is there a systematic way to tease apart resistance "drivers" from "passengers"? This should be at least discussed.
The manuscript would benefit from language editing, there are quite a few grammatical errors.
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Reviewer #1:
Major Comments:
The experimental design is inconsistent in at least three ways:
The genomes of 14 resistant clones were analyzed by whole exome sequencing (WES), whereas the genomes of the remaining 21 clones were analyzed using whole genome sequencing (WGS).
And the sequencing approach even differed among the six lines evolved in three separate drugs: doxorubicin, paclitaxel, and gemcitabine.
We feel the authors did not adequately explain how the different sequencing methodologies could affect their results and the inferences drawn from them. For example, one is likely to miss information with respect to copy number variants by only sequencing exomes. The authors highlight this fact in their discussion, but they do not explain by how much they could be off in their assessment.
In some cases the same parental clone was used …
Reviewer #1:
Major Comments:
The experimental design is inconsistent in at least three ways:
The genomes of 14 resistant clones were analyzed by whole exome sequencing (WES), whereas the genomes of the remaining 21 clones were analyzed using whole genome sequencing (WGS).
And the sequencing approach even differed among the six lines evolved in three separate drugs: doxorubicin, paclitaxel, and gemcitabine.
We feel the authors did not adequately explain how the different sequencing methodologies could affect their results and the inferences drawn from them. For example, one is likely to miss information with respect to copy number variants by only sequencing exomes. The authors highlight this fact in their discussion, but they do not explain by how much they could be off in their assessment.
In some cases the same parental clone was used to find replicate lines subjected to the same selective pressure, and in other cases, the same parental clone was used to find replicate lines subjected to different selective pressures.
Lines were evolved anywhere from seven to thirty weeks, and the length of the evolution experiments does not correlate with the selecting drug (e.g., three replicate lines were evolved in doxorubicin for 9 weeks and three other lines were evolved to this same drug for 12 weeks). Did the authors normalize by generations? Again, the authors do not address this issue in their manuscript.
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Summary: The authors examined the genomic basis of resistance evolution in human chronic myelogenous leukemia (CML) near-haploid cell lines to 5 separate chemotherapeutic agents.
Using either whole genome or whole exome analysis, they found numerous instances of single nucleotide polymorphisms and copy number variants, including amplifications and deletions, among lines. They then used subsequent knockdown or knockout experiments to confirm that these variants, in fact, lead to increased resistance in these lines.
The work is interesting, timely, and has potential clinical implications. For example, the resistance alleles identified here could be closely examined in future studies in order to develop treatment strategies. However, the experimental design has certain limitations, advances in understanding chemotherapy resistance …
Summary: The authors examined the genomic basis of resistance evolution in human chronic myelogenous leukemia (CML) near-haploid cell lines to 5 separate chemotherapeutic agents.
Using either whole genome or whole exome analysis, they found numerous instances of single nucleotide polymorphisms and copy number variants, including amplifications and deletions, among lines. They then used subsequent knockdown or knockout experiments to confirm that these variants, in fact, lead to increased resistance in these lines.
The work is interesting, timely, and has potential clinical implications. For example, the resistance alleles identified here could be closely examined in future studies in order to develop treatment strategies. However, the experimental design has certain limitations, advances in understanding chemotherapy resistance mechanisms is currently modest, and the presentation of results can be improved. We feel overall that these could be addressed, but that they will require significant extra experimental work.
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