Biology subjects

Gui, P.

Publications and source records attributed to Gui, P..

7 recordsLinked to original sources

bioRxiv2024

CDK4 and CDK6 upregulation promotes DNA replication stress, genomic instability and resistance to EGFR targeted therapy in lung cancer

Epidermal growth factor receptor (EGFR) mutant lung adenocarcinomas (LUAD) harbor a complex landscape of genetic co-alterations and potential oncogenic interactions. Among them are recurrent amplifications of the cell cycle regulatory genes CDK4 and CDK6, which have been clinically implicated in resistance to EGFR tyrosine kinase inhibitors (TKIs). However, the mechanisms by which CDK4/6 upregulation promotes therapy resistance remain poorly defined. Here, we demonstrate that CDK4 or CDK6 overexpression limits EGFR inhibitor-induced proliferative arrest, promoting continued cell cycle progression. This is accompanied by elevated replication stress, increased TPX2 expression, DNA damage leading to ATM activation, and ultimately genomic instability. Integrative transcriptomic and copy number analyses of EGFR-mutant LUAD tumors from both patients and preclinical models revealed that CDK4 or CDK6 amplification is associated with the upregulation of genes linked to tumor progression, including AGR2, ASNS, and STEAP1. CDK4 amplification was also highly correlated with gene expression changes associated with epithelial-to-mesenchymal transition (EMT) in a single-cell RNA sequencing dataset from patient biopsies. In preclinical models, co-treatment with CDK4/6 and EGFR inhibitors restored proliferative arrest, induced tumor cell apoptosis, and reduced replication stress, DNA damage, and genomic instability. Our findings uncover a mechanistic basis for EGFR inhibitor resistance of CDK4 and CDK6 amplified EGFR-mutant LUAD. They also provide a rationale for the biomarker-driven clinical development of combination EGFR and CDK4/6-targeted therapies for the treatment of a subset of EGFR-mutant LUAD patients.

cancer biology↗

bioRxiv2024

The role of conscious attention in statistical learning: evidence from patients with impaired consciousness

The debate over whether conscious attention is necessary for statistical learning has produced mixed and conflicting results. Testing individuals with impaired consciousness may provide some insight, but very few studies have been conducted due to the difficulties associated with testing such patients. In this study, we examined the ability of patients with varying levels of consciousness disorders (DOC), including coma, unresponsive wakefulness syndrome, minimally conscious patients, and emergence from minimally conscious state patients, to extract statistical regularities from an artificial language composed of four randomly concatenated pseudowords. We used a methodology based on frequency tagging in EEG, which was developed in our previous studies on speech segmentation in sleeping neonates. Our study had two main objectives: firstly, to assess the automaticity of the segmentation process and explore correlations between the level of covert consciousness and the abilities to extract statistical regularities, second, to explore a potential new diagnostic indicator to aid in patient management by examining the correlation between successful statistical learning markers and consciousness level. We observed that segmentation abilities were preserved in some minimally conscious patients, suggesting that statistical learning is an inherently automatic low-level process. Due to significant inter-individual variability, word segmentation may not be a sufficiently robust candidate for clinical use, unlike temporal accuracy of auditory syllable responses, which correlates strongly with coma severity. Therefore, we propose that frequency tagging of an auditory stimulus train, a simple and robust measure, should be further investigated as a possible metric candidate for DOC diagnosis.

neuroscience↗

bioRxiv2021

3-Phosphoinositide-dependent kinase 1 drives acquired resistance to osimertinib

Osimertinib sensitive and resistant NSCLC NCI-H1975 clones were used to model osimertinib acquired resistance in humanized mice and delineate potential resistance mechanisms. No new EGFR mutations or loss of the EGFR T790M mutation were found in resistant clones. Resistant tumors in humanized mice were initially partially responsive to osimertinib, then aggressive tumor regrowth occurred accompanied by an immunosuppressive tumor microenvironment. 3-phosphoinositide-dependent kinase 1 (PDK1) was identified as a potential driver of osimertinib acquired resistance, and its selective inhibition by BX795 and CRISPR gene knock out, sensitized resistant clones and a patient derived xenograft (PDX) with acquired resistance to osimertinib. PDK1 knock-out dysregulated PI3K/Akt/mTOR signaling, promoted cell cycle arrest at the G1 phase, and inhibited nuclear translocation of yes-associated protein (YAP). Higher expression of PDK1 was found in patients with progressive disease following osimertinib treatment. PDK1 is a central upstream regulator of two critical drug resistance pathways: PI3K/AKT/mTOR and YAP.

cancer biology↗

bioRxiv2021

Constructing the hierarchy of predictive auditory sequences in the marmoset brain

Our brains constantly generate predictions of sensory input that are compared with actual inputs, propagate the prediction-errors through a hierarchy of brain regions, and subsequently update the internal predictions of the world. However, the essential feature of predictive coding, the notion of hierarchical depth and its neural mechanisms, remains largely unexplored. Here, we investigated the hierarchical depth of predictive auditory processing by combining functional magnetic resonance imaging (fMRI) and high-density whole-brain electrocorticography (ECoG) in marmoset monkeys during an auditory local-global paradigm in which the temporal regularities of the stimuli were designed at two hierarchical levels. The prediction-errors and prediction updates were examined as neural responses to auditory mismatches and omissions. Using fMRI, we identified a hierarchical gradient along the auditory pathway: midbrain and sensory regions represented local, short-time-scale predictive processing followed by associative auditory regions, whereas anterior temporal and prefrontal areas represented global, long-time-scale sequence processing. The complementary ECoG recordings confirmed the activations at cortical surface areas and further differentiated the signals of prediction-error and update, which were transmitted via putatively bottom-up {gamma} and top-down {beta} oscillations, respectively. Furthermore, omission responses caused by absence of input, reflecting solely the two levels of prediction signals that are unique to the hierarchical predictive coding framework, demonstrated the hierarchical predictions in the auditory, temporal, and prefrontal areas. Thus, our findings support the hierarchical predictive coding framework, and outline how neural circuits and spatiotemporal dynamics are used to represent and arrange a hierarchical structure of auditory sequences in the marmoset brain.

neuroscience↗

bioRxiv2020

Targeted cancer therapy induces APOBEC fuelling the evolution of drug resistance

Introductory paragraphThe clinical success of targeted cancer therapy is limited by drug resistance that renders cancers lethal in patients1-4. Human tumours can evolve therapy resistance by acquiring de novo genetic alterations and increased heterogeneity via mechanisms that remain incompletely understood1. Here, through parallel analysis of human clinical samples, tumour xenograft and cell line models and murine model systems, we uncover an unanticipated mechanism of therapy-induced adaptation that fuels the evolution of drug resistance. Targeted therapy directed against EGFR and ALK oncoproteins in lung cancer induced adaptations favoring apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC)-mediated genome mutagenesis. In human oncogenic EGFR-driven and ALK-driven lung cancers and preclinical models, EGFR or ALK inhibitor treatment induced the expression and DNA mutagenic activity of APOBEC3B via therapy-mediated activation of NF-{kappa}B signaling. Moreover, targeted therapy also mediated downregulation of certain DNA repair enzymes such as UNG2, which normally counteracts APOBEC-catalyzed DNA deamination events. In mutant EGFR-driven lung cancer mouse models, APOBEC3B was detrimental to tumour initiation and yet advantageous to tumour progression during EGFR targeted therapy, consistent with TRACERx data demonstrating subclonal enrichment of APOBEC-mediated mutagenesis. This study reveals how cancers adapt and drive genetic diversity in response to targeted therapy and identifies APOBEC deaminases as future targets for eliciting more durable clinical benefit to targeted cancer therapy.

cancer biology↗

bioRxiv2019

Heterogeneity and targeted therapy-induced adaptations in lung cancer revealed by longitudinal single-cell RNA sequencing

Lung cancer, the leading cause of cancer mortality, exhibits heterogeneity that enables adaptability, limits therapeutic success, and remains incompletely understood. Single-cell RNA sequencing (scRNAseq) of metastatic lung cancer was performed using 44 tumor biopsies obtained longitudinally from 27 patients before and during targeted therapy. Over 20,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ecosystem. scRNAseq of cancer cells illuminated targetable oncogenes beyond those detected clinically. Cancer cells surviving therapy as residual disease (RD) expressed an alveolar-regenerative cell signature suggesting a therapy-induced primitive cell state transition, whereas those present at on-therapy progressive disease (PD) upregulated kynurenine, plasminogen, and gap junction pathways. Active T-lymphocytes and decreased macrophages were present at RD and immunosuppressive cell states characterized PD. Biological features revealed by scRNAseq were biomarkers of clinical outcomes in independent cohorts. This study highlights how therapy-induced adaptation of the multi-cellular ecosystem of metastatic cancer shapes clinical outcomes.

cancer biology↗

bioRxiv2018

Co-occurring genetic alterations in the RAS pathway promote resistance to MET inhibitor treatment in non-small cell lung cancer with a MET exon 14 skipping mutation

PURPOSEWhile patients with advanced-stage non-small cell lung cancers (NSCLCs) harboring MET exon 14 skipping mutations (METex14) often benefit from MET tyrosine kinase inhibitor (TKI) treatment, clinical benefit is limited by primary and acquired drug resistance. The molecular basis for this resistance remains incompletely understood.\n\nMETHODSTargeted sequencing analysis was performed on cell-free circulating tumor DNA obtained from 289 patients with advanced-stage METex14-mutated NSCLC.\n\nRESULTSProminent co-occurring RAS-MAPK pathway gene alterations (e.g. in KRAS, NF1) were detected in NSCLCs with METex14 skipping alterations as compared to EGFR-mutated NSCLCs. There was an association between decreased MET TKI treatment response and RAS-MAPK pathway co-occurring alterations. In a preclinical model expressing a canonical METex14 mutation, KRAS overexpression or NF1 downregulation hyperactivated MAPK signaling to promote MET TKI resistance. This resistance was overcome by co-treatment with crizotinib and the MEK inhibitor trametinib.\n\nCONCLUSIONOur study provides a genomic landscape of co-occurring alterations in advanced-stage METex14-mutated NSCLC and suggests a potential combination therapy strategy targeting MAPK pathway signaling to enhance clinical outcomes.

cancer biology↗