MétaCan
Menu
Back to cohort
Record W4415135301 · doi:10.1101/2025.10.11.681805

Large-scale single-cell phylogenetic mapping of clonal evolution in the human aging esophagus

2025· preprint· en· W4415135301 on OpenAlexaff
Tamara Prieto, Dennis J. Yuan, John Zinno, Clayton Hughes, Nicholas Midler, Sheng Kao, Jani Huuhtanen, Ramya Raviram, Foteini Fotopoulou, Neil Ruthen, Srinivas Rajagopalan, Joshua S. Schiffman, Sang-Ho Yoon, Jesús Alfonso López Sotélo, Nathaniel D. Omans, Alejandro Garcés, Barun Pradhan, Alexandre Pellan Cheng, Nicolas Robine, Catherine Potenski, Nobuyuki Kakiuchi, Akira Yokoyama, Seishi Ogawa, Julian A. Abrams, Ivan Raimondi, Dan A. Landau

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsÉcole de Technologie SupérieureCentre Hospitalier de l’Université de Montréal
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsPhylogenetic treeSomatic cellGenomeSomatic evolution in cancerPhylogeneticsTranscriptomeNegative selectionWhole genome sequencing

Abstract

fetched live from OpenAlex

Abstract The human somatic genome evolves throughout our lifespan, producing mosaic individuals comprising clones harboring different mutations across tissues. While clonal expansions in the hematopoietic system have been extensively characterized and reported to be nearly ubiquitous, clonal mosaicism (CM) has more recently also been described across multiple solid tissues. However, outstanding questions remain about the parameters and processes of human somatic evolution in non-cancerous solid human tissues, including when clones arise, how they evolve over time, and what mechanisms lead to their expansion. Questions of timing and clonal dynamics can be addressed through phylogenetic reconstruction, which serves as a ‘temporal microscope’, while uncovering the mechanisms of expansion necessitates simultaneous phenotypic profiling. To address this gap, here we develop Single-cell Miniaturized Automated Reverse Transcription and Primary Template-directed Amplification (SMART-PTA) for joint single-cell whole-genome and whole-transcriptome sequencing for large scale and cost efficient interrogation of solid tissue CM. We established a workflow that generates hundreds of matched single-cell whole genome and transcriptome libraries within a week. We profiled phenotypically normal esophagus tissue from four aged donors and used somatic variants to build high-resolution single-cell lineages from >2,700 cells with accompanying transcriptomic information, reconstructing >70 years of somatic evolution. T cell expansions identified from T cell receptor (TCR) sequences validated the clonal structure of the single-nucleotide variant (SNV)-based phylogenies and phylogenetic cross-correlation analysis showed that epithelial cells had higher degrees of shared ancestry by spatial location compared to immune cells. Mapping mutation signatures to the phylogenetic tree revealed the emergence of tobacco/alcohol exposure-related signatures later in life, consistent with the donors’ exposure histories. We identified variants in driver genes that were previously reported in the phenotypically normal esophagus, detecting clonal expansions harboring mutations in genes including TP53 and FAT1 . We mapped the evolution of clones with both monoallelic as well as biallelic TP53 loss, including a clone associated with high expression of cell cycling genes and higher chromosome instability. Leveraging the matched transcriptome data, we uncovered cell type biases in mutant clones, with a higher proportion of TP53 or FAT1 -mutant cells in an earlier basal epithelial cell state compared to wild-type cells. We further observed copy-neutral loss of heterozygosity (CNLOH) events on chromosome 9q that spanned the NOTCH1 locus in up to ∼35% of epithelial cells. Mapping CNLOH events to the phylogenetic tree revealed a striking pattern in which CNLOH was separately acquired many times, reflecting convergent evolution. Cells with CNLOH events were biased towards the earlier basal epithelial state, suggestive of a selective advantage that leads to prevalent recurrence of chr9q CNLOH. Together, we demonstrate that SMART-PTA is an efficient, scalable approach for single-cell whole-genome and whole-transcriptome profiling to build phenotypically annotated single-cell phylogenies with enough throughput and power for application to normal tissue somatic evolution. Moreover, we reconstruct the evolutionary history of the esophageal epithelium at high scale and resolution, providing a window into the dynamics and processes that shape clonal expansions in phenotypically normal tissues throughout a lifespan.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.267
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicEsophageal Cancer Research and TreatmentFrench-language works237,207