Publications by authors named "Weigang Ge"

Article Synopsis
  • Prostate cancer (PCa) is the most common cancer in men, but there are few reliable ways to predict outcomes and guide treatments.
  • Researchers conducted proteomic profiling on 918 tissue samples from 306 Chinese PCa patients, identifying over 10,000 proteins and classifying PCa into three distinct molecular subtypes.
  • They developed a 16-protein panel that predicts biochemical recurrence (BCR) in PCa patients better than existing methods, and found that knocking out two proteins from this panel may inhibit cancer cell growth and spread, presenting potential new treatment strategies.
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  • * A study analyzed tissue and plasma samples from 813 patients, identifying eight proteins that may indicate tumor severity and could serve as potential blood biomarkers.
  • * The research also reveals the use of machine learning to predict tumor recurrence and explores the link between DNA damage proteins and treatment resistance, enhancing the understanding of EOC for better diagnosis and therapy.
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  • A study was conducted on 773 Chinese breast cancer patients to address the lack of representation in large-scale molecular profiling studies and to analyze their unique biological characteristics.
  • Findings revealed that Asian patients had more targetable AKT1 mutations, a higher prevalence of the HER2-enriched subtype, and increased HER2 protein levels, suggesting a need for anti-HER2 therapy.
  • The comprehensive analysis also identified ferroptosis as a potential therapeutic target for basal-like tumors and established a method for classifying patients based on their recurrence risk, providing valuable insights for precision treatment.
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Amyloid-β, tau pathology, and biomarkers of neurodegeneration make up the core diagnostic biomarkers of Alzheimer disease (AD). However, these proteins represent only a fraction of the complex biological processes underlying AD, and individuals with other brain diseases in which AD pathology is a comorbidity also test positive for these diagnostic biomarkers. More AD-specific early diagnostic and disease staging biomarkers are needed.

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The molecular basis of circadian rhythm, driven by core clock genes such as Per1/2, has been investigated on the transcriptome level, but not comprehensively on the proteome level. Here we quantified over 11,000 proteins expressed in eight types of tissues over 46 h with an interval of 2 h, using WT and Per1/Per2 double knockout mouse models. The multitissue circadian proteome landscape of WT mice shows tissue-specific patterns and reflects circadian anticipatory phenomena, which are less obvious on the transcript level.

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Background: Papillary thyroid cancer (PTC) is one of the most common endocrine malignancies with different risk levels. However, preoperative risk assessment of PTC is still a challenge in the worldwide. Here, the authors first report a Preoperative Risk Assessment Classifier for PTC (PRAC-PTC) by multidimensional features including clinical indicators, immune indices, genetic feature, and proteomics.

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Article Synopsis
  • - Metabolic syndrome (MetS) affects 20%-25% of the global population, and early detection could reduce the strain on healthcare systems.
  • - Researchers analyzed over 400 proteins from serum samples of nearly 3,840 participants over 10 years to create a machine-learning model that predicts MetS risk within a decade.
  • - The study identified key proteins linked to MetS and suggests that this large-scale proteomics research could help in developing effective prevention and treatment strategies.
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Chimeric antigen receptor (CAR)-modified T cells have demonstrated remarkable efficacy in treating B-cell leukemia. However, treated patients may potentially develop side effects, such as cytokine release syndrome (CRS), the mechanisms of which remain unclear. Here, we collected 43 serum samples from eight patients with B-cell acute lymphoblastic leukemia (B-ALL) before and five time points after CD19-specific CAR-T cell treatment.

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Data-independent acquisition (DIA) mass spectrometry-based proteomics generates reproducible proteome data. The complex processing of the DIA data has led to the development of multiple data analysis tools. In this study, we assessed the performance of five tools (OpenSWATH, EncyclopeDIA, Skyline, DIA-NN, and Spectronaut) using six DIA datasets obtained from TripleTOF, Orbitrap, and TimsTOF Pro instruments.

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Prostate cancer (PCa) is the second most prevalent malignancy and the fifth cause of cancer-related deaths in men. A crucial challenge is identifying the population at risk of rapid progression from hormone-sensitive prostate cancer (HSPC) to lethal castration-resistant prostate cancer (CRPC). We collected 78 HSPC biopsies and measured their proteomes using pressure cycling technology and a pulsed data-independent acquisition pipeline.

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Treatment and relevant targets for breast cancer (BC) remain limited, especially for triple-negative BC (TNBC). We identified 6091 proteins of 76 human BC cell lines using data-independent acquisition (DIA). Integrating our proteomic findings with prior multi-omics datasets, we found that including proteomics data improved drug sensitivity predictions and provided insights into the mechanisms of action.

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  • The study analyzed over 1,000 blood samples from patients infected with the Omicron variant of SARS-CoV-2 to understand the host's immune response using various advanced techniques, known as multi-omics.
  • Researchers found that Omicron infections led to increased antiviral activity in platelets and changes in how these cells interacted with other immune cells, highlighting a unique immune response.
  • The study also identified a decrease in B cell activity and antibody production in patients who tested positive again for the virus, while a machine learning model was developed to predict the likelihood of re-positivity in these patients.
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Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated COVID-19 vaccine (CoronaVac®) at a 28-day interval. Using TMT-based proteomics, we identified 1,715 serum and 7,342 peripheral blood mononuclear cells (PBMCs) proteins.

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High-grade serous ovarian carcinoma (HGSOC) is the most common subtype of ovarian cancer with 5-year survival rates below 40%. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is recommended for patients with advanced-stage HGSOC unsuitable for primary debulking surgery (PDS). However, about 40% of patients receiving this treatment exhibited chemoresistance of uncertain molecular mechanisms and predictability.

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Isobaric labeling-based proteomics is widely applied in deep proteome quantification. Among the platforms for isobaric labeled proteomic data analysis, the commercial software Proteome Discoverer (PD) is widely used, incorporating the search engine CHIMERYS, while FragPipe (FP) is relatively new, free for noncommercial purposes, and integrates the engine MSFragger. Here, we compared PD and FP over three public proteomic data sets labeled using 6plex, 10plex, and 16plex tandem mass tags.

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Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue samples from a retrospective cohort.

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The mouse is a valuable model organism for biomedical research. Here, we established a comprehensive spectral library and the data-independent acquisition-based quantitative proteome maps for 41 mouse organs, including some rarely reported organs such as the cornea, retina, and nine paired organs. The mouse spectral library contained 178,304 peptides from 12,320 proteins, including 1678 proteins not reported in previous mouse spectral libraries.

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High-throughput lysis and proteolytic digestion of biopsy-level tissue specimens is a major bottleneck for clinical proteomics. Here we describe a detailed protocol of pressure cycling technology (PCT)-assisted sample preparation for proteomic analysis of biopsy tissues. A piece of fresh frozen or formalin-fixed paraffin-embedded tissue weighing ~0.

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Article Synopsis
  • - The study investigated the molecular differences between follicular thyroid tumors, specifically follicular adenoma (FA), follicular carcinoma (FTC), and follicular variant of papillary thyroid carcinoma (FvPTC), using proteomic analysis and advanced mass spectrometry techniques.
  • - A total of 4,107 proteins were analyzed from 52 tumor specimens, revealing significant differences in protein expression: 287 proteins differed between FTC and FA, 303 between FvPTC and FA, and 23 between FTC and FvPTC.
  • - The findings highlighted ANXA1 as a key protein biomarker that can effectively distinguish FvPTC from both FA and FTC, aiding in the diagnosis of these challenging tumors. *
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  • A study investigated why some COVID-19 patients experience prolonged positivity for the virus, finding that these patients had higher levels of IgG antibodies and regulatory T cells compared to those with shorter viral infections.
  • The research identified that prolonged viral shedding was linked to disruption of specific biological pathways, reduced metabolites, increased inflammation, and boosted viral replication.
  • A predictive model was developed based on ten molecules, aimed at forecasting the duration of viral RNA shedding in patients, highlighting the role of inflammation and immune suppression in prolonged infections.
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Background: Recent efforts have described the evolution of glioblastoma from initial diagnosis to post-treatment recurrence on a genomic and transcriptomic level. However, the evolution of the proteomic landscape is largely unknown.

Methods: Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to characterize the quantitative proteomes of two independent cohorts of paired newly diagnosed and recurrent glioblastomas.

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