Biology subjects

Powley, I.

Publications and source records attributed to Powley, I..

9 recordsLinked to original sources

bioRxiv2026

mTORC2 stabilizes HIF-1β to coordinate metabolic adaptation in lung cancer

Despite extensive genetic heterogeneity, lung tumors frequently converge on shared signaling dependencies that remain therapeutically underexploited. Here, we identify mTORC2 signaling as a convergent dependency across genetically distinct lung cancer subtypes and uncover HIF-1{beta} as a selective metabolic effector downstream of mTORC2 that promotes lung tumor progression. Elevated mTORC2 signaling in lung adenocarcinoma was associated with poor overall survival, metastatic dissemination and metabolic rewiring. Using complementary genetically engineered mouse models of Rictor deletion or overexpression in Kras-driven lung tumors, we show that mTORC2 activity is dispensable for normal lung homeostasis but required for tumor progression and metabolic adaptation in vivo. Mechanistically, mTORC2 stabilized HIF-1{beta} by preventing its ubiquitin-independent proteasomal degradation through a non-canonical PKC-CK2 signaling axis, independently of AKT. Integrated multi-omics analyses identified extensive metabolic rewiring downstream of the mTORC2-HIF-1{beta} axis, with sphingolipid metabolism emerging as a prominent and therapeutically exploitable vulnerability. Accordingly, pharmacological targeting of sphingolipid metabolism markedly impaired the growth of mTORC2-driven lung tumors in vivo. Together, our findings establish a non-canonical mTORC2-HIF-1{beta} signaling axis that couples oncogenic signaling to metabolic adaptation and defines therapeutically actionable metabolic vulnerabilities in lung cancer.

cancer biology↗

bioRxiv2026

CYCLOPS: an open end-to-end platform for cyclic multiplex imaging and single-cell phenotyping

Multiplex immunofluorescent imaging enables deep spatial profiling of protein expression in tissues but is often limited by reliance on proprietary reagents, dedicated hardware, and closed analysis ecosystems. Here we present CYCLOPS (Cyclic Open Platform for Spatial Proteomics), an end-to-end, open-source workflow for cyclic multiplex imaging and single-cell phenotyping using standard microscopy infrastructure. CYCLOPS integrates an Arduino-based automated fluidics system, an open-chamber stage insert, and antibody-oligonucleotide conjugation based entirely on published chemistries and off-the-shelf components. We demonstrate robust and reproducible antibody conjugation, high-quality multiplexed staining, and stable imaging across >10 cycles with minimal drift (<1 {micro}m) and consistent fluorescence retention with low signal carry-over. The system supports efficient buffer exchange and consistent performance across multiple markers and imaging rounds. Using confocal microscopy, the workflow is compatible with three-dimensional imaging, enabling multiplexed analysis of volumetric tissue structures. To enable quantitative analysis, we establish an open-source image processing and analysis pipeline for single-cell feature extraction and phenotypic classification, avoiding reliance on proprietary software or black-box workflows. This framework integrates image registration, segmentation, and supervised classification to generate biologically interpretable single-cell data. Together, CYCLOPS provides a flexible and accessible platform for cyclic multiplex imaging, lowering barriers to adoption and enabling broader use of spatial proteomics across diverse research settings. This accessible framework democratizes high-plex imaging by enabling any laboratory with a standard confocal microscope to perform iterative multiplexing without reliance on proprietary reagents or hardware.

Cell Biology↗

bioRxiv2026

YBX3 overexpression in mesothelioma drives aberrant cell proliferation

Malignant pleural mesothelioma (MpM) is a lethal tumour closely linked to asbestos exposure and is a cancer of unmet clinical need with no known oncogenic drivers. Recent advancements in technologies to identify RNA-binding proteins (RBPs) has uncovered an emerging role for RBP-RNA interactions in cancer progression and we therefore assessed changes in the RBPome of patient-derived MpM cell lines. We identify over 350 RBPs showing altered RNA binding, with functions consistent with key cancer hallmarks, and discovered YBX3 as a potential oncoprotein driving cell proliferation in MpM. Mechanistically we show the impact of YBX3 on cell growth is achieved through its control of the expression of the amino acid transporter SLC7A5/LAT1, with increased amino acid uptake increasing protein synthesis rates. Notably, we show the inhibition of cell growth by YBX3 deletion is recapitulated by the clinically-relevant SLC7A5/LAT1 inhibitor JPH203. Finally, we demonstrate that JPH203 sensitizes MpM cells to radiotherapy, which could provide a promising therapeutic strategy for MpM. TeaserHigher levels of YBX3 expression in mesothelioma increases cell proliferation and protein synthesis rates by upregulation of amino acid uptake.

molecular biology↗

bioRxiv2025

Self-supervised AI reveals a lethal discohesive phenotype in lung adenocarcinoma

Applications of artificial intelligence (AI) to histopathology are now common, but most require supervision which inherently limits their scope. By using self-supervised learning (SSL), we discover and quantify the full range of histopathological appearances in a disease, and associate them with clinicopathological ground truths such as prognosis. We used this approach to discover under-appreciated morphologies of lung adenocarcinoma (LUAD), using a highly characterised resected tumour cohort of over 4000 slides from over 1000 patients. By constructing an authoritative lexicon of recurrent LUAD appearances, we ab initio discovered several stromal morphologies strongly predictive of outcome. With multimodal data integration and external dataset validation, we propose that epithelial discohesion is lethal, but only in the context of immunologically cold stroma. Both these morphological features are independent of current prognostic schema. Crucially, we describe these features in the context of real-world diagnostic histopathology, giving them immediate clinical translatability. Statement of SignificanceHistopathology relies heavily on epithelial morphology, often neglecting the stroma. We use self-supervised AI to identify under-appreciated morphologies in LUAD linked to poor outcome and validate these observations in an external cohort, demonstrating the utility of self-supervised AI as a powerful biological discovery tool.

cancer biology↗

bioRxiv2025

Increased mRNA translation delays lung adenocarcinoma initiation and exposes a therapeutic vulnerability to MEK inhibitors

Although protein synthesis inhibitors are being evaluated as anti-cancer agents, the dynamics of mRNA translation in early tumorigenesis are still poorly understood. We report that deletion of the mRNA-translation repressor, eIF4A2 in early KRAS-driven lung adenocarcinoma leads to a dysregulated protein synthesis landscape characterised by a strongly upregulated secretome, enlarged secretory compartments, increased oxidative metabolism and acquisition of senescence-like characteristics. Paradoxically, this overdriven protein synthesis landscape delays tumorigenesis and leads to appearance of clusters of non-proliferative, p21-positive KRAS-expressing cells in the lung. Administration of rapamycin to reduce mRNA translation suppresses senescence and restores tumorigenesis following eIF4A2 deletion. Importantly, some eIF4A2 knockout cells overcome senescence to form tumours that exhibit enhanced MAP-kinase signalling and, in contrast to eIF4A2+/+ lesions, these may be eradicated by administration of a MEK inhibitor. Thus, dysregulated mRNA translation exposes a potential therapeutic vulnerability in KRAS-driven lung adenocarcinoma by forcing cancer cells to rely on MEK signalling. Statement of significanceThe requirement for anabolism in cancers has led to the search for inhibitors of mRNA translation as anti-cancer agents. However, we report that increased rates of mRNA translation promote a senescence-like phenotype in KRAS-driven lung cancer which delays tumorigenesis and renders the resulting tumours sensitive to MEK inhibition.

cancer biology↗

bioRxiv2025

The characteristic of epithelial-specific phenotypes and immunosuppressive microenvironment in the context of tumour budding in colorectal cancer

BackgroundTumour budding (TB), defined as a small cluster of up to four cells at the invasive front of the tumour, is a well-established independent and robust prognostic biomarker in colorectal cancer (CRC). This is strongly associated with adverse clinicopathological features and poor survival outcomes. Despite its clinical relevance, the precise underlying mechanism responsible for TB phenomenon remains unclear. MethodsMulti-omic approaches from bulk, regional GeoMx and Spatial Molecular Imager (SMI) RNA were used to identify the underlying mechanism of TB and its possible correlation with tumour microenvironment (TME) in CRC tissue. The results were validated using immunohistochemistry (IHC) and multiplex immunofluorescence (mIF) staining. ResultsPatients with high TB experience worse outcomes and associate with adverse clinical factors across two independent CRC cohorts. Bulk and regional RNA expression analyses reveal that tumours with high TB are significantly enriched for TNF- and TGF-{beta} signatures in both cohorts. Single cell CosMx SMI analysis confirmed TB cells exhibit higher expression of these signatures than adjacent invasive edge tumour cells. Elevated cyclinD1 expression was also observed within TB, and high cyclinD1 levels tend to experience poorer CRC prognosis. Furthermore, regional bulk RNA expression within the non-tumour (PanCK-) invasive edge areas demonstrated that tumours exhibiting high TB revealed the significantly differential expressions of immune-related genes (e.g. CD3, NKG7, IL6, CXCR6, CD47, IFNAR1 and VSIR). Single cell CosMx SMI analysis revealed that cancer-associated fibroblasts (CAFs) were physically the closest cells to TB cells. This spatial proximity was confirmed at the protein level using mIF, where the distance from TB to CD68+ macrophages predicted significantly poorer CRC outcomes. ConclusionThis multi-omic study confirms the prognostic significance of TB in CRC patients across two independent cohorts. Our findings highlight that TNF- and TGF-{beta} signalling play a crucial role in budding cells development by regulating cyclinD1. Furthermore, the transcriptomic analysis reveals an immunosuppressive niche characterised by reduced immune activity and close spatial interactions with CAFs and macrophages Ultimately, this study provides valuable insight into TBs underlying mechanism and its complex interactions within the TME. This could provide a foundation for developing targeted therapeutic strategies in CRC.

cancer biology↗

bioRxiv2024

Spatial resolution of transcriptomic plasticity states underpinning lethal morphologies in lung adenocarcinoma

Adenocarcinoma of the lung (LUAD) is a common and highly lethal disease. Clinical grading of disease strongly predicts recurrence and survival after surgery and is determined by morphological assessment of histological growth patterns in resected tumours. The molecular basis of growth pattern is poorly understood at present, as are the mechanisms linking growth pattern to recurrence and death. Interestingly, the two archetypal lethal morphologies, solid and micropapillary patterns, are characterised by their biphasic appearance. Both have an epithelial fraction which is in direct stromal contact, and a fraction which is not. This morphological variance seems likely to represent plasticity, and to be causally linked to mechanisms of virulence. To investigate the gene expression changes related to growth pattern both intra- and intertumoral, we applied spatial transcriptomics (Nanostring GeoMx DSP) to tissue microarray specimens of primary resected human lung adenocarcinoma. Using a variety of region-of-interest (ROI) selection strategies, we sampled 160 pure epithelial ROIs across 7 distinct morphological features of LUAD from 51 patients. Analyses of gene expression reveal fundamental trajectories connecting growth patterns, and crucial modes of plasticity which underly high-risk morphologies. These modes suggest mechanisms for the origins of growth pattern and mechanisms of virulence. Our work highlights dramatic divergence in gene expression programmes between highly lethal but morphologically diverse modes of tumour growth. Furthermore, it provides an explanation for how microscopically localised hypoxia in the primary tumour helps to establish and maintain survival strategies which ultimately determine morphology-specific mechanisms of tumour metastasis, suggesting new therapeutic vulnerabilities.

cancer biology↗

bioRxiv2023

eIF4A1 is essential for reprogramming the translational landscape of Wnt-driven colorectal cancers

Dysregulated translation is a hallmark of cancer. Targeting the translational machinery represents a therapeutic avenue which is being actively explored. eIF4A inhibitors target both eIF4A1, which promotes translation as part of the eIF4F complex, and eIF4A2, which can repress translation via the CCR4-NOT complex. While high eIF4A1 expression is associated with poor patient outcome, the role of eIF4A2 in cancer remains unclear. Furthermore, the on-target toxicity of targeting specific eIF4A paralogues in healthy tissue is under-explored. We show that while loss of either paralogue is tolerated in the wild-type intestine, eIF4A1 is specifically required to support the translational demands of oncogenic Wnt signalling. Intestinal tumourigenesis is suppressed in colorectal cancer models following loss of eIF4A1 but accelerated following loss of eIF4A2, while eIF4A inhibition with eFT226 mimics loss of eIF4A1 in these models.

cancer biology↗

bioRxiv2023

ERBB signalling contributes to immune evasion in KRAS-driven lung adenocarcinoma

Immunotherapy is increasingly viewed as treatment of choice for lung cancer, however, clinical responses to immune checkpoint blockade remain highly unpredictable and are largely transient. A deeper mechanistic understanding of the dynamics of tumour:immune interactions is needed to drive rational development of improved treatment strategies. Progress is hampered by a paucity of autochthonous model systems in which to interrogate the 2-way interactions of immune responses to evolving tumours and vice-versa. Specifically, commonly used genetically engineered mouse models typically lack the genetic diversity needed to drive an adaptive immune response. APOBEC mutagenesis signatures are prominent in lung cancer and APOBEC activity is predicted to drive immune visibility through Cytidine deaminase activity, coupled with inaccurate DNA-repair responses. We therefore generated a CRE-inducible APOBEC3B allele, interbred with multiple oncogenic drivers of lung adenocarcinoma, and used the resulting mice to investigate the response to PD1 blockade at single cell resolution. SIGNIFICANCE Using our novel immune-visible model of KRas-driven autochthonous lung adenocarcinoma, we uncovered a surprising increase in tumour-cell expression of EGFR/ERBB ligands following treatment with -PD1 and present evidence that transient ERBB blockade can restore immune surveillance in KRas mutant LuAd and combine effectively with immune checkpoint blockade.

cancer biology↗