Excited to share "Defining heritability, plasticity, and transition dynamics of cellular phenotypes in somatic evolution", from an amazing collaboration with @landau_lab @ar_davino @TamaraPrietoF @hara_toshiro @MarioSuva!. A tweetorial, or Xplanation .

RT @RuxandraTeslo: IMO one of the most important questions in somatic evolution.

RT @landau_lab: PATH (phylogenetic analysis of trait heritability) is out @NatureGenet! Excited about tackling the fundamentals of somatic….

Readcube link:

I'd also like to thank our peer reviewers, including Verena Körber and @arjunrajlab, who helped us improve the paper significantly, and specifically for encouraging the expansion of PATH to include proliferation rates.

This work would not have been possible w/o @landau_lab's vision and support, or the insights from co-1st authors @ar_davino + @TamaraPrietoF, and Catherine Potenski, or from the work done in @MarioSuva's lab with Yilin Fan and @hara_toshiro, and Chuck Gawad's lab w Yakun Pang.

PATH is not only for cancer evolution, and can also be used to study development. To demonstrate, we applied PATH to published mouse embryogenesis and zebrafish brain development datasets.

Afterwards, we used single-cell whole genome seq to reconstruct a pediatric patient B-ALL leukemia phylogeny. PATH showed that B-ALL cells clustered phylogenetically by B-cell maturity, and linked these with genetic changes.

Next, we studied GBM, a brain cancer, comprising corrupted neurodev cell states, including stem- and astrocyte-like cells, but also a mesenchymal-like, non neuro state. PATH showed that bidirectional transitions in + out of the astrocyte-like state link stem- and mes-like cells.

We applied PATH to a published mouse model of pancreatic cancer to study the.epithelial-to-mesenchymal transition (EMT), a dev process cancer cells hijack to metastasize. PATH revealed that intermediate EMT status, associated with peak metastatic aggression, was highly plastic.

PATH measures heritability vs. plasticity by quantifying cell state distributions on cellular lineages, or phylogenies.

By combining lineage tracing + scRNAseq, we can infer cell dynamics in somatic evolution. We developed PATH, which uses joint single-cell lineage tracing and phenotyping to measure cell state heritability vs plasticity, and to infer cell state proliferation + transition dynamics.

It is also thought that cell state plasticity, or the ability of cells to toggle between different states, may be related to resistance and metastasis. However, we cannot measure plasticity from just a snapshot of cell states, provided by scRNAseq.

By itself, single-cell RNA sequencing has shown us that cancers comprise a diversity of phenotypic cell states, and that this may be related to disease characteristics and progression.

Recent tech has enabled the simultaneous recording of phenotype and ancestry at single-cell resolution. For example, cell lineages can be traced by reading mutations, epimutations, or w engineered DNA barcodes randomly edited w CRISPR, and phenotypes can be measured w RNA seq.

RT @EricTopol: A major problem with cell-free tumor DNA to detect cancer (Liquid biopsy) is its very low quantity. Today @NatureMedicine us….

RT @landau_lab: "Did you know that you don't need targeted panels for ultra-sensitive MRD?". 🥳 Down right ebullient to share our latest 🥳@N….

RT @adamjwidman: MRD-EDGE is out today in @NatureMedicine! Thrilled to see this in print when the future for #ctdna in plasma whole genome….

RT @MatLupien: Postdoc position available to be co-supervised by myself and @fgaiti in cancer evolution and genomics. .