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DavidMacPherson

@DMacPhersonLab

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Cancer Biologist @fredhutch

Seattle, WA
Joined February 2019
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@DMacPhersonLab
DavidMacPherson
7 months
📣The MacPherson lab @fredhutch is hiring a postdoc to study the biology of small cell lung cancer. We employ in vivo models, genetic screens and genomic approaches to understand + therapeutically target subsets of SCLC. $78K salary ⬆️ to >$90K after 2 yrs.
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@DMacPhersonLab
DavidMacPherson
2 months
Thanks for highlighting our efforts to use in vivo CRISPR screens to identify drivers of resistance to chemotherapy in small cell lung cancer.
@fredhutch
Fred Hutch Cancer Center
2 months
In work published in Science Advances, researchers in the @DMacPhersonLab used #CRISPRCas9 on #SCLC tumor cells to better model how tumors that initially respond to chemotherapy become resistant.
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@DMacPhersonLab
DavidMacPherson
1 year
This work was possible only because of the contributions of our collaborators – Anish Thomas, @charlesrudin, Keith Eaton, McGarry Houghton, Caroline Dive, as well as SCLC patients and funding from NCI and @KuniFoundation 14/14.
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@DMacPhersonLab
DavidMacPherson
1 year
Our fragmentomics approach complements other emerging strategies towards SCLC liquid biopsy phenotyping such as DNA methylation analyses and ChIPseq approaches. We advocate for broad application of different phenotyping approaches to patient samples 13/X.
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@DMacPhersonLab
DavidMacPherson
1 year
We are continuing to validate the performance of SCLCpheno-seq, identify additional informative sites, and incorporate new phenotyping modules into the targeted panel to comprehensively phenotype SCLC and better understand therapeutic responses 12/X.
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@DMacPhersonLab
DavidMacPherson
1 year
As targeted sequencing is also used to call driver gene mutations, we layered on mutation analyses to develop an all-in-one assay to also call exonic mutations in >800 cancer-relevant genes, along with TF activation 11/X
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@DMacPhersonLab
DavidMacPherson
1 year
Probabilistic models focusing only on informative sites in PDXs distinguished NSCLC from SCLC in patients, suggesting utility in calling NSCLC-SCLC transformation. Our assay also showed strong performance at calling SCLC patient subsets for which TF expression was available 10/X
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@DMacPhersonLab
DavidMacPherson
1 year
Many informative TSS sites from ctDNA included known lineage-defining TFs and their targets/collaborators. For example, POU2F3 TSS activity matched RNAseq expression and matched TSS activity of its co-activator C11orf53/POU2AF2 9/X
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@DMacPhersonLab
DavidMacPherson
1 year
Joe then developed a clustering approach to distinguish TFBSs and TSSs where ctDNA coverage profiles synched with gene expression vs those that were non-informative. By analyzing PDX models, we could identify informative sites using an idealized system with 100% tumor ctDNA 8/X
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@DMacPhersonLab
DavidMacPherson
1 year
From the ASCL1, NEUROD1, POU2F3 and REST TFBS regions, aggregating all sites together did well for some TFs, such as REST, NEUROD1 and POU2F3, but not for ASCL1 7/X
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@DMacPhersonLab
DavidMacPherson
1 year
We built an assay to capture potentially informative regions including most genomic transcriptional start sites (TSSs) along with hundreds of TFBS regions for key TFs: ASCL1, NEUROD1, POU2F3 and REST. 6/X.
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@DMacPhersonLab
DavidMacPherson
1 year
Cell-free DNA is protected from nucleases by nucleosomes, while active regulatory regions such as TF binding sites and TSS regions get degraded. Deep WGS shows a nucleosome-depleted region at the TSS of NEUROD1 only in the NEUROD1-active SCLC patient/PDX model samples. 5/X
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@DMacPhersonLab
DavidMacPherson
1 year
Also, EGFR-mutant non small cell lung cancer (NSCLC) can transform to SCLC as a mechanism of resistance to EGFR inhibitors, but the field lacks a liquid biopsy assay to detect such transformation 4/X.
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@DMacPhersonLab
DavidMacPherson
1 year
Activation of transcription factors ASCL1, NEUROD1, POU2F3, and repressor of neuronal/neuroendocrine state, REST defines distinct subsets of SCLC with differing therapeutic vulnerabilities. How can we distinguish TF activation in SCLC from blood samples? 3/X.
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@DMacPhersonLab
DavidMacPherson
1 year
Correlative analyses to reveal features of SCLC with differential therapeutic responses in clinical trials are limited by challenges in obtaining tissue biopsies. SCLC has remarkably high levels of ctDNA, leading to an opportunity to phenotype SCLC from liquid biopsies 2/X
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@DMacPhersonLab
DavidMacPherson
1 year
Our collaborative study with @GavinHa @fredhutch is out in @ScienceAdvances. Led by Joe Hiatt and Anna Lisa Doebley, we developed a liquid biopsy approach, SCLCpheno-seq, to classify SCLC subsets and distinguish from NSCLC based on analyses of ctDNA 1/X
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@DMacPhersonLab
DavidMacPherson
2 years
RT @GavinHa: We have an open joint-postdoc position with @DMacPhersonLab to work on new computational approaches for studying #lungcancer u….
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@DMacPhersonLab
DavidMacPherson
2 years
RT @Sutherland_Lab: I’m counting down the sleeps to @IASLC #SCLC23! Was thrilled to help organise this meeting together with @AlvaroQuinta….
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@DMacPhersonLab
DavidMacPherson
2 years
RT @AlvaroQuintanal: Looking forward to @IASLC #SCLC23! So much fun to help organise this meeting together with superstars @Sutherland_Lab,….
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@DMacPhersonLab
DavidMacPherson
3 years
Happy to share news of a faculty search @fredhutch for an Assistant/Associate Professor building a research program focused on lung cancer. Applications considered from Nov. 1. Please DM or email with questions, and share with colleagues! .
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