RÉSUMÉ
Multi-omics technologies, encompassing genomics, proteomics, and transcriptomics, provide profound insights into cancer biology. A fundamental computational approach for analyzing multi-omics data is differential analysis, which identifies molecular distinctions between cancerous and normal tissues. Traditional methods, however, often fail to address the distinct heterogeneity of individual tumors, thereby neglecting crucial patient-specific molecular traits. This shortcoming underscores the necessity for tailored differential analysis algorithms, which focus on particular patient variations. Such approaches offer a more nuanced understanding of cancer biology and are instrumental in pinpointing personalized therapeutic strategies. In this review, we summarize the principles of current individualized techniques. We also review their efficacy in analyzing cancer multi-omics data and discuss their potential applications in clinical practice.
RÉSUMÉ
BACKGROUND: Liquid chromatography-mass spectrometry (LC-MS)-based quantitative phosphoproteomics has been widely used to detect thousands of protein phosphorylation modifications simultaneously from the biological specimens. However, the complicated procedures for analyzing phosphoproteomics data has become a bottleneck to widening its application. METHODS: Here, we develop PhosMap, a versatile and scalable tool to accomplish phosphoproteomics data analysis. A standardized phosphorylation data format was created for data analyses, from data preprocessing to downstream bioinformatic analyses such as dimension reduction, differential phosphorylation analysis, kinase activity, survival analysis, and so on. For better usability, we distribute PhosMap as a Docker image for easy local deployment upon any of Windows, Linux, and Mac system. RESULTS: The source code is deposited at https://github.com/BADD-XMU/PhosMap. A free PhosMap webserver (https://huggingface.co/spaces/Bio-Add/PhosMap), with easy-to-follow fashion of dashboards, is curated for interactive data analysis. CONCLUSIONS: PhosMap fills the technical gap of large-scale phosphorylation research by empowering researchers to process their own phosphoproteomics data expediently and efficiently, and facilitates better data interpretation.
Sujet(s)
Biologie informatique , Phosphoprotéines , Protéomique , Logiciel , Protéomique/méthodes , Phosphoprotéines/analyse , Phosphoprotéines/métabolisme , Biologie informatique/méthodes , Humains , Phosphorylation , Spectrométrie de masse/méthodes , Chromatographie en phase liquide/méthodesRÉSUMÉ
Multi-frame super-resolution (MFSR) leverages complementary information between image sequences of the same scene to increase the resolution of the reconstructed image. As a branch of MFSR, burst super-resolution aims to restore image details by leveraging the complementary information between noisy sequences. In this paper, we propose an efficient burst-enhanced super-resolution network (BESR). Specifically, we introduce Geformer, a gate-enhanced transformer, and construct an enhanced CNN-Transformer block (ECTB) by combining convolutions to enhance local perception. ECTB efficiently aggregates intra-frame context and inter-frame correlation information, yielding an enhanced feature representation. Additionally, we leverage reference features to facilitate inter-frame communication, enhancing spatiotemporal coherence among multiple frames. To address the critical processes of inter-frame alignment and feature fusion, we propose optimized pyramid alignment (OPA) and hybrid feature fusion (HFF) modules to capture and utilize complementary information between multiple frames to recover more high-frequency details. Extensive experiments demonstrate that, compared to state-of-the-art methods, BESR achieves higher efficiency and competitively superior reconstruction results. On the synthetic dataset and real-world dataset of BurstSR, our BESR achieves PSNR values of 42.79 dB and 48.86 dB, respectively, outperforming other MFSR models significantly.
RÉSUMÉ
Voltage-gated sodium channels (Nav) undergo conformational shifts in response to membrane potential changes, a mechanism known as the electromechanical coupling. To delineate the structure-function relationship of human Nav channels, we have performed systematic structural analysis using human Nav1.7 as a prototype. Guided by the structural differences between wild-type (WT) Nav1.7 and an eleven mutation-containing variant, designated Nav1.7-M11, we generated three additional intermediate mutants and solved their structures at overall resolutions of 2.9-3.4 Å. The mutant with nine-point mutations in the pore domain (PD), named Nav1.7-M9, has a reduced cavity volume and a sealed gate, with all voltage-sensing domains (VSDs) remaining up. Structural comparison of WT and Nav1.7-M9 pinpoints two residues that may be critical to the tightening of the PD. However, the variant containing these two mutations, Nav1.7-M2, or even in combination with two additional mutations in the VSDs, named Nav1.7-M4, failed to tighten the PD. Our structural analysis reveals a tendency of PD contraction correlated with the right shift of the static inactivation I-V curves. We predict that the channel in the resting state should have a "tight" PD with down VSDs.
Sujet(s)
Canaux sodiques voltage-dépendants , Humains , Canaux sodiques voltage-dépendants/génétique , Potentiels de membrane , Mutation , Relation structure-activitéRÉSUMÉ
Voltage-gated sodium (Nav) channels are targeted by a number of widely used and investigational drugs for the treatment of epilepsy, arrhythmia, pain, and other disorders. Despite recent advances in structural elucidation of Nav channels, the binding mode of most Nav-targeting drugs remains unknown. Here we report high-resolution cryo-EM structures of human Nav1.7 treated with drugs and lead compounds with representative chemical backbones at resolutions of 2.6-3.2 Å. A binding site beneath the intracellular gate (site BIG) accommodates carbamazepine, bupivacaine, and lacosamide. Unexpectedly, a second molecule of lacosamide plugs into the selectivity filter from the central cavity. Fenestrations are popular sites for various state-dependent drugs. We show that vinpocetine, a synthetic derivative of a vinca alkaloid, and hardwickiic acid, a natural product with antinociceptive effect, bind to the III-IV fenestration, while vixotrigine, an analgesic candidate, penetrates the IV-I fenestration of the pore domain. Our results permit building a 3D structural map for known drug-binding sites on Nav channels summarized from the present and previous structures.