EGFL7 drives the evolution of resistance to EGFR inhibitors in lung cancer by activating NOTCH signaling

Wang, Yubo; Chen, Pu; Zhao, Man; Cao, Hongxin; Zhao, Yangyang; Ji, Meiju; Hou, Peng; Chen, Mingwei

doi:10.1038/s41419-022-05354-y

Cited by 9 publications

(4 citation statements)

References 68 publications

(85 reference statements)

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“…On the other hand, the CAV1 gene, notorious for bolstering lung cancer cell proliferation, manifests heightened expression during pathological conditions [56]. Other markers, such as HSPB1, EGFL7, and PPIA, while not overtly differentially expressed, resonate strongly with their established biological significance [57,58,59]. Figure 3(b) serves as an emblem of scSniper's autoencoder module's finesse in sculpting biologically coherent cell embeddings, facilitating a precise delineation of diverse cell type clusters.…”

Section: Resultsmentioning

confidence: 99%

scSniper: Single-cell Deep Neural Network-based Identification of Prominent Biomarkers

Li,

Chen,

Ding

2023

Preprint

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Discovering disease biomarkers at the single-cell level is crucial for advancing our understanding of diseases and improving diagnostic accuracy. However, current computational methods often have limitations, such as a reliance on prior knowledge, constraints to unimodal data, and the use of conventional statistical tests for feature selection. To address these issues, we introduce scSniper, a novel approach that employs a specialized deep neural network framework tailored for robust single-cell multiomic biomarker detection. A standout feature of scSniper is the mimetic attention block, enhancing alignment across multi-modal data types. Moreover, scSniper utilizes sensitivity analysis based on a deep neural network for feature selection and uncovers intricate gene regulatory networks without requiring prior knowledge. Comprehensive evaluations on real-world datasets, including COVID-19 CITE-Seq and LUAD scRNA-Seq, demonstrate scSniper’s exceptional ability to identify critical biomarkers consistently outperforming traditional methods like MAST, Wilcox, and DESeq2. The scSniper tool and related experimental codes are publicly accessible athttps://github.com/mcgilldinglab/scSniper.

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Section: Resultsmentioning

confidence: 99%

scSniper: Single-cell Deep Neural Network-based Identification of Prominent Biomarkers

Li,

Chen,

Ding

2023

Preprint

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“…EGFL7 is a gene that has been found to play a role in cancer. It has been identified as a driver gene for resistance to EGFR kinase inhibition in lung cancer cells (66). ].…”

Section: Discussionmentioning

confidence: 99%

Identification of Key Regulators in Pancreatic Ductal Adenocarcinoma using Network theoretical Approach

Bhattacharjee,

Ghosh

2024

Preprint

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Pancreatic Ductal Adenocarcinoma (PDAC) is a devastating disease with poor clinical outcomes which is mainly because of delayed disease detection resistance to chemotherapy and lack of specific targeted therapies. The disease's development involves complex interactions among immunological, genetic, and environmental factors, yet its molecular mechanism remains elusive. A major challenge in understanding PDAC etiology lies in unraveling the genetic profiling that governs the PDAC network. To address this, we examined the gene expression profile of PDAC and compared it with that of healthy controls, identifying differentially expressed genes (DEGs). These DEGs formed the basis for constructing the PDAC protein interaction network, and their network topological properties were calculated. It was found that the PDAC network self-organizes into a scale-free fractal state with weakly hierarchical organization. Newman and Girvan algorithm (leading eigenvector (LEV) method) of community detection enumerated four communities leading to at least one motif. Our analysis revealed 33 key regulators were predominantly enriched in neuroactive ligand-receptor interaction, Cell adhesion molecules, Leukocyte transendothelial migration pathways; positive regulation of cell proliferation, positive regulation of protein kinase B signaling biological functions; G-protein beta-subunit binding, receptor binding molecular functions etc. Transcription Factor and mi-RNA of the key regulators were obtained. Recognizing the therapeutic potential and biomarker significance of PDAC Key regulators, we also identified approved drugs for specific genes. However, it is imperative to subject Key regulators to experimental validation to establish their efficacy in the context of PDAC.

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“…Additionally, there is a crosstalk between Notch signaling and other pathways, such as TGF-β and EGFR. Activated Notch pathway leads to an expansion of TGF-β-induced smad2/3 signaling and EGFR inhibitors resistance [ 14 , 76 ]. Notably, the pathogenic role of the Notch pathway appears to be tumor type dependent.…”

Section: Csc Biomarkers Stemness-associated Pathways Targeting Therapiesmentioning

confidence: 99%

The strategies to cure cancer patients by eradicating cancer stem-like cells

Mai,

Su,

Yang

et al. 2023

Mol Cancer

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Cancer stem-like cells (CSCs), a subpopulation of cancer cells, possess remarkable capability in proliferation, self-renewal, and differentiation. Their presence is recognized as a crucial factor contributing to tumor progression and metastasis. CSCs have garnered significant attention as a therapeutic focus and an etiologic root of treatment-resistant cells. Increasing evidence indicated that specific biomarkers, aberrant activated pathways, immunosuppressive tumor microenvironment (TME), and immunoevasion are considered the culprits in the occurrence of CSCs and the maintenance of CSCs properties including multi-directional differentiation. Targeting CSC biomarkers, stemness-associated pathways, TME, immunoevasion and inducing CSCs differentiation improve CSCs eradication and, therefore, cancer treatment. This review comprehensively summarized these targeted therapies, along with their current status in clinical trials. By exploring and implementing strategies aimed at eradicating CSCs, researchers aim to improve cancer treatment outcomes and overcome the challenges posed by CSC-mediated therapy resistance.

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EGFL7 drives the evolution of resistance to EGFR inhibitors in lung cancer by activating NOTCH signaling

Cited by 9 publications

References 68 publications

scSniper: Single-cell Deep Neural Network-based Identification of Prominent Biomarkers

scSniper: Single-cell Deep Neural Network-based Identification of Prominent Biomarkers

Identification of Key Regulators in Pancreatic Ductal Adenocarcinoma using Network theoretical Approach

The strategies to cure cancer patients by eradicating cancer stem-like cells

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