Biology subjects

Kearns, P.

Publications and source records attributed to Kearns, P..

4 recordsLinked to original sources

bioRxiv2026

CD180 identifies chemoresistant stem-like blasts and reveals a KMT2A-driven vulnerability in acute myeloid leukaemia

Relapse and chemoresistance remain major challenges in paediatric acute myeloid leukaemia (PAML), particularly in KMT2A-rearranged (KMT2A-r) subtypes where conventional markers such as CD34 are often absent, complicating measurable residual disease (MRD) detection. Leukaemia stem/regenerating cells (LSC/LRC) drive disease initiation, progression, and relapse, sharing stemness and chemoresistance properties that make them critical therapeutic targets. Using high-dimensional spectral flow cytometry, we identified CD180, a Toll-like receptor-like surface protein, as highly expressed on blasts and stem-like populations in KMT2A-r AML, while near absent on normal haematopoietic stem cells (HSCs). PAML KMT2A-r exhibits an unconventional immunophenotype dominated by CD34-CD180 populations. Integrated single-cell transcriptomics and functional profiling revealed CD180high clusters enriched for quiescence, oxidative phosphorylation, and KMT2A/LSC stemness signatures. CD180 cells demonstrated robust leukaemia-initiating capacity in xenograft models and persisted through therapy, re-emerging at relapse with phenotypic plasticity. Epigenomic analysis showed CD180 is a direct transcriptional target of the KMT2A::MLLT3 fusion complex, regulated by intragenic enhancers and downregulated by menin and BET inhibitors. Longitudinal single-cell analysis confirmed persistence and clonal evolution of CD180 populations during treatment and relapse, underscoring their mechanistic role in chemoresistance and disease progression. In summary, CD180 marks dynamic, relapse-driving populations in KMT2A-r PAML, persists through therapy, and importantly is near absent on normal HSCs, offering a selective therapeutic window. These findings position CD180 as a clinically actionable biomarker for MRD detection and a compelling therapeutic target for eradicating chemoresistant, stem-like cells in paediatric AML. Main PointsO_LICD180 marks chemoresistant, relapse-driving stem-like blasts in KMT2A-r paediatric AML, overcoming CD34-based MRD limitations. C_LIO_LIAbsent on normal HSCs, CD180 is a KMT2A::MLLT3 target and actionable for MRD, relapse prediction, and CD180-directed therapies. C_LI NoveltyThis study introduces CD180 as a novel biomarker and therapeutic target in AML, particularly KMT2A-rearranged subtypes where conventional markers are often absent. Unlike MRD strategies focused on bulk blasts, CD180 marks chemoresistant, stem-like populations driving relapse, critical reservoirs poorly defined in paediatric AML. This work fills a major gap in prognostic assessment and therapy by enabling precise detection of relapse-driving cells and offering a selective therapeutic window.

cancer biology↗

bioRxiv2026

High Diversity Gene Libraries Facilitate Machine Learning Guided Exploration of Fluorescent Protein Sequence Space

While protein language models (PLMs) have shown great promise for protein design, their performance is fundamentally constrained by the diversity and completeness of available training data. In particular, PLMs often struggle to extrapolate to sequences that fall outside the distribution spanned by their training sets, limiting their ability to discover proteins in sparsely sampled regions of sequence space. Here we test the hypothesis that experimentally expanding training diversity can convert extrapolation into interpolation and thereby enable discovery of functional sequences beyond natural protein manifolds. Using large-scale gene synthesis and DNA shuffling, we generate libraries that span a broad region of fluorescent protein sequence space and create chimeric variants that bridge between distant homologs. Functional screening for blue fluorescence yields thousands of active variants distributed across diverse sequence lineages. Fine-tuning ProtGPT2 on this expanded dataset enables generation of diverse fluorescent proteins, including designs that extend beyond the regions occupied by known natural sequences while retaining function. This work illustrates how synthetic approaches can help address key limitations in machine learning-guided protein design, especially for small or sparsely populated protein families, by actively creating novel sequences across unexplored but functional regions of sequence space.

synthetic biology↗

bioRxiv2025

Optimizing in-vitro Transcribed CRISPR-Cas9 single-guide RNA Libraries for Improved Uniformity and Affordability

We describe a scalable and cost-effective sgRNA synthesis workflow that reduces costs by over 70% through the use of large pools of microarray-derived oligos encoding unique sgRNA spacers. These sub-pool oligos are assembled into full-length dsDNA templates via Golden Gate Assembly before in vitro transcription with T7 RNA polymerase. RNA-seq analysis reveals severe biases in spacer representation, with some spacers being highly overrepresented while others are completely absent. Consistent with previous studies, we identify guanine-rich sequences within the first four nucleotides of the spacer, immediately downstream of the T7 promoter, as the primary driver of this bias. To address this issue, we introduced a guanine tetramer upstream of all spacers, which reduced bias by an average of 19% in sgRNA libraries containing 389 spacers. However, this modification also increased the presence of high-molecular-weight RNA species after transcription. We also tested two alternative bias-reduction strategies: compartmentalizing spacers within emulsions and optimizing DNA input and reaction volumes. Both methods independently reduced bias in 2,626-plex sgRNA libraries, though to a lesser extent than the guanine tetramer approach. These advancements enhance both the affordability and uniformity of sgRNA libraries, with broad implications for improving CRISPR-Cas9 screens and optimizing guide RNA design for other CRISPR and nuclease systems.

molecular biology↗

bioRxiv2020

High-Dimensional mass cytometry analysis reveals systemic immune perturbations in paediatric cancer influenced by age

Systemic immunity plays an important role in cancer immune surveillance and therapy but there is little detailed knowledge about the immune status of healthy children or children with cancer. We performed a high dimensional single cell analysis of systemic immunity in pediatric cancer patients and age-matched healthy children. In young children with cancer (age < 8years) NK cells were decreased in frequency, maturity, expression of perforin and granzyme-B, and were less cytotoxic in ex vivo assays. NK cell activity was restored after in vitro culture with interleukin-2. In contrast, older children with cancer (>8 years old) had decreased naive CD4 and CD8 T-cells with concomitant increases in effector memory and T effector memory RA-revertant (TEMRA) T-cells. These immunological changes in pediatric cancer patients are relevant to the better understanding of how cancers diagnosed in childhood interact with systemic immunity and could inform the development and application of effective immune-modulating therapies in the pediatric population. One Sentence SummaryHigh dimensional analysis of systemic immunity in pediatric cancer patients reveals clinically relevant immune changes in NK and T-cells that vary with patient age.

immunology↗