Biology subjects

Pattwell, S. S.

Publications and source records attributed to Pattwell, S. S..

6 recordsLinked to original sources

bioRxiv2026

Transcriptomic analysis reveals differential regulation of synaptic components in pediatric and adult brain tumors

Neuronal-cancer cell interactions are a key component of brain tumor pathophysiology, yet many fundamental questions remain unanswered, with even more remaining unasked. Here, we present a comprehensive brain tumor reference map generated from bulk RNA-seq data of ~4,300 adult and pediatric brain tumors, including various glioma subtypes, medulloblastomas, ependymomas, and meningiomas, alongside ~1,400 healthy brain samples. By analyzing synaptic processes and synaptic gene expression across tumor types, we reveal the complexity of neuron-tumor crosstalk and its potential impact on patient survival. Our findings identify key synaptic signaling pathways and dysregulated patterns in brain tumors, including HNRNPH2 upregulation, a key factor in RNA processing and metabolism, in gliomas and medulloblastomas. Additionally, we highlight the role of cholinergic signaling, particularly CHRNA9, as a driver of glioma progression, which is also upregulated in WNT and Group 4 medulloblastomas, ependymomas, and meningiomas. Furthermore, P2 purinergic signaling emerges as a key player in glioma progression. These insights lay the groundwork for future studies exploring whether targeting these pathways could reprogram the tumor microenvironment toward an anti-tumor state, ultimately leading to novel therapeutic strategies and improved patient outcomes.

cancer biology↗

bioRxiv2025

Elucidating Neurodevelopmental Trajectories in Cancer with Topic Modeling: Revealing Persistent External Granule Layer Lineages in Medulloblastoma

Single-cell transcriptomics transformed our understanding of cellular heterogeneity, yet cross-dataset comparison remains fundamentally limited by batch effects, technology differences, and inconsistent annotation frameworks. These challenges have impeded efforts to connect developmental programs with disease states which creates a critical gap for understanding pediatric cancers with suspected developmental origins. Here, we demonstrate that topic modeling, an unsupervised natural language processing technique, overcomes these barriers by learning transferable transcriptional genetic signatures that generalize across datasets, technologies, and biological contexts without requiring data integration. Applying this framework to over one million fetal cerebellar nuclei, we identify seven distinct topics that capture the developmental spectrum of rhombic lip progenitors through external granule layer (EGL) differentiation, including transitional states missed by conventional clustering. These topics transfer successfully across sequencing technologies (SPLiT-seq to sci-RNA-seq3), developmental timepoints, species (human to mouse), and from single-cell to bulk RNA sequencing of 876 medulloblastoma tumors. We reveal that Sonic hedgehog (SHH) medulloblastoma subtypes retain these topics, corresponding to distinct stages of EGL development. Our findings highlight that developmental timing at tumor initiation fundamentally shapes tumor biology, with immediate implications for subtype-specific therapeutic strategies in pediatric brain cancer. Our workflow establishes topic modeling as a scalable solution for mining expanding genomic atlases with broad applications across different datasets, technologies, and biological contexts.

bioinformatics↗

bioRxiv2024

CTPS1 inhibition synergizes with replication stress signaling inhibition in MYC-amplified Group 3 medulloblastoma

MYC-driven medulloblastomas (MBs) represent the most aggressive and deadly subgroup of MB, the most common malignant pediatric brain tumor. Direct targeting of MYC itself remains an unmet clinical need, therefore focusing on vulnerabilities driven by MYC may be a viable option for novel therapeutic interventions. Using whole-genome CRISPR screening, we identified the de novo pyrimidine synthesis enzyme CTP synthase (CTPS1) as a strong dependency in MYC-driven MB. CTPS1 is the final and rate-limiting step in the de novo pyrimidine synthesis pathway. Targeted inhibition of CTPS1 leads to decreased tumor cell proliferation and markedly reduces MYC expression in G3 MB models. Mechanistically, we demonstrate that single agent CTPS1 inhibition activates the replication stress signaling pathway mediated by ATM-CHK2 and ATR-CHK1. Blockade of CHK1 kinase activity increases sensitivity to CTPS1 inhibition and significantly impedes heterotopic MB tumor growth. CTPS1 enzymatic activity requires the amino acid glutamine, therefore we inhibited CTPS1 using the glutamine antagonists, JHU083 and JHU395. These compounds are prodrugs of 6-diazo-5-oxo-L-norleucine (DON) which were developed to exhibit better tumor targeting and enhanced blood-brain barrier penetrability. Combining JHU083 and CHK1 inhibition demonstrates potent synergy against patient-derived MB xenografts in vivo. Our findings strongly suggest that combining de novo pyrimidine synthesis and ATR-CHK1 inhibitors is a promising treatment for MYC-driven MBs. Key PointsO_LICTPS1 is a unique vulnerability in MYC-driven medulloblastoma C_LIO_LICTPS1 inhibition activates the ATR-CHK1 replication stress response pathway for cell survival C_LIO_LIBlockade of CTPS1 enzymatic activity synergizes with CHK1 inhibition in vitro and in vivo C_LI Importance of the StudyMYC hyperactivation in tumors drives multiple anabolic processes which contribute to tumor proliferation and aggressiveness in patients. We show that targeting de novo pyrimidine synthesis (via CTPS1) limits tumor growth and targets MYC itself through a feedback mechanism. CTPS1 inhibition potently combines with CHK1 blockade and enhances disease control in both heterotopic and orthotopic models of medulloblastoma (MB). Our results support the clinical evaluation of combined CTPS1 and CHK1 inhibition in patients with MYC-driven MB.

cancer biology↗

bioRxiv2023

An RNA seq-based reference landscape of human normal and neoplastic brain

In order to better understand the relationship between normal and neoplastic brain, we combined five publicly available large-scale datasets, correcting for batch effects and applying Uniform Manifold Approximation and Projection (UMAP) to RNA-seq data. We assembled a reference Brain-UMAP including 702 adult gliomas, 802 pediatric tumors and 1409 healthy normal brain samples, which can be utilized to investigate the wealth of information obtained from combining several publicly available datasets to study a single organ site. Normal brain regions and tumor types create distinct clusters and because the landscape is generated by RNA seq, comparative gene expression profiles and gene ontology patterns are readily evident. To our knowledge, this is the first meta-analysis that allows for comparison of gene expression and pathways of interest across adult gliomas, pediatric brain tumors, and normal brain regions. We provide access to this resource via the open source, interactive online tool Oncoscape, where the scientific community can readily visualize clinical metadata, gene expression patterns, gene fusions, mutations, and copy number patterns for individual genes and pathway over this reference landscape.

bioinformatics↗

bioRxiv2022

Oncogenic role of a developmentally regulated NTRK2 splice variant

Temporally-regulated alternative splicing choices are vital for proper development yet the wrong splice choice may be detrimental. Here we highlight a novel role for the neurotrophin receptor splice variant TrkB.T1 in neurodevelopment, embryogenesis, transformation, and oncogenesis across multiple tumor types in both humans and mice. TrkB.T1 is the predominant NTRK2 isoform across embryonic organogenesis and forced over-expression of this embryonic pattern causes multiple solid and nonsolid tumors in mice in the context of tumor suppressor loss. TrkB.T1 also emerges the predominant NTRK isoform expressed in a wide range of adult and pediatric tumors, including those harboring TRK fusions. Affinity purification-mass spectrometry (AP-MS) proteomic analysis reveals TrkB.T1 has distinct interactors with known developmental and oncogenic signaling pathways such as Wnt, TGF-{beta}, Hedgehog, and Ras. From alterations in splicing factors to changes in gene expression, the discovery of isoform specific oncogenes with embryonic ancestry has the potential to shape the way we think about developmental systems and oncology.

cancer biology↗

bioRxiv2018

Errors in RNA-seq transcript abundance estimates

RNA-sequencing data is widely used to identify disease biomarkers and therapeutic targets. Here, using data from five RNA-seq processing pipelines applied to 6,690 human tumor and normal tissues, we show that for >12% of protein-coding genes, in at least 1% of samples, current best-in-class RNA-seq processing pipelines differ in their abundance estimates by more than four-fold using the same samples and the same set of RNA-seq reads, raising clinical concern.

bioinformatics↗