Lihua Cao

ORCID: 0000-0003-0761-3224
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About
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Research Areas
  • Machine Learning in Bioinformatics
  • Cancer Genomics and Diagnostics
  • Pancreatic and Hepatic Oncology Research
  • Genomics and Phylogenetic Studies
  • Receptor Mechanisms and Signaling
  • Health, Environment, Cognitive Aging
  • Pharmacogenetics and Drug Metabolism
  • Radiomics and Machine Learning in Medical Imaging
  • Gene expression and cancer classification
  • Peptidase Inhibition and Analysis
  • Ferroptosis and cancer prognosis
  • Advanced Proteomics Techniques and Applications
  • Hepatocellular Carcinoma Treatment and Prognosis
  • Ubiquitin and proteasome pathways
  • MicroRNA in disease regulation
  • Bioinformatics and Genomic Networks
  • Neuroblastoma Research and Treatments
  • Neuroendocrine Tumor Research Advances
  • Biomedical Text Mining and Ontologies
  • Cancer, Hypoxia, and Metabolism
  • Medical Imaging and Pathology Studies
  • Statistical Methods in Clinical Trials
  • Cancer Cells and Metastasis

Peking University Cancer Hospital
2021-2025

Peking University
2021-2025

Peking University International Hospital
2024

Inter- and intra-tumor heterogeneity is a major hurdle in primary liver cancer (PLC) precision therapy. Here, we establish PLC biobank, consisting of 399 tumor organoids derived from 144 patients, which recapitulates histopathology genomic landscape parental tumors, reliable for drug sensitivity screening, as evidenced by both vivo models patient response. Integrative analysis dissects heterogeneity, regarding genomic/transcriptomic characteristics to seven clinically relevant drugs, well...

10.1016/j.ccell.2024.03.004 article EN cc-by Cancer Cell 2024-04-01

Early detection of gastric cancer (GC) remains challenging. We aimed to examine urine proteomic signatures and identify protein biomarkers that predict the progression lesions risk GC.A case-control study was initially designed, covering subjects with GC different stages. Subjects were aged 40-69 years, without prior diagnosis renal or urological diseases. enrolled a total 255 subjects, 123 in discovery stage from Linqu, China, high-risk area for 132 validation Linqu Beijing. A prospective...

10.1016/j.ebiom.2022.104340 article EN cc-by-nc-nd EBioMedicine 2022-11-07

β-Arrestin 1 (ARRB1) has been recognized as a multifunctional adaptor protein in the last decade, beyond its original role desensitizing G protein-coupled receptor signaling. Here, we identify that ARRB1 plays essential roles mediating gastric cancer (GC) cell metabolism and proliferation, by combining cohort analysis functional investigation using patient-derived preclinical models. Overexpression of was associated with poor outcome GC patients knockdown impaired proliferation both ex vivo...

10.1073/pnas.2123231119 article EN cc-by-nc-nd Proceedings of the National Academy of Sciences 2022-09-26

Patient-derived organoids recently emerged as promising ex vivo 3D culture models recapitulating histological and molecular characteristics of original tissues, thus proteomic profiling could be valuable for function investigation clinical translation. However, are usually cultured in murine Matrigel (served scaffolds matrix), which brings an issue to separate from Matrigel. Because the complex compositions thousands identical peptides shared between organoids, insufficiently dissolved...

10.1016/j.mcpro.2021.100181 article EN cc-by-nc-nd Molecular & Cellular Proteomics 2021-12-03

E3 ubiquitin ligases (E3s) and deubiquitinating enzymes (DUBs) play key roles in protein degradation. However, a large number of substrate interactions (ESIs) DUB (DSIs) remain elusive. Here, we present DeepUSI, deep learning-based framework to identify ESIs DSIs using the rich information sequences. Utilizing collected golden standard dataset, hyperparameters process model training, including ones relevant data sampling epochs, have been systematically assessed. The performance DeepUSI was...

10.1016/j.csbj.2023.01.021 article EN cc-by-nc-nd Computational and Structural Biotechnology Journal 2023-01-01

Adequate reporting is essential for evaluating the performance and clinical utility of a prognostic prediction model. Previous studies indicated prevalence incomplete or suboptimal in translational involving development multivariable models prognosis, which limited potential applications these models. While templates introduced by established guidelines provide an invaluable framework uniformly, there widespread lack qualified adherence, may be due to miscellaneous challenges manual...

10.1093/bib/bbad267 article EN Briefings in Bioinformatics 2023-07-05

ABSTRACT Genome variant detection is a challenge task in cancer genome analysis. Current software for very time-consuming and the same time not accurate enough to satisfy requirements of clinical applications precision oncology. We developed an all-round ultra-fast Genomic Variant Caller (GVC), which can detect Germline Somatic variants, including SNVs INDELs from sequencing data with super high speed accuracy. GVC achieved mean F1-measure 99.34% 97.92% WGS WES datasets, respectively. And...

10.1101/182089 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2017-08-29

Abstract Although mass spectrometry is powerful for proteomic quantification, the inherent issue of missing values remains a significant challenge. We found prevalent lack quantification valuable proteins (e.g., immune cell markers and drug targets) in published datasets, limiting functional utilities quantitative profiles. This was exemplified by substantial marker, which impede dissection tissue-infiltrating cells deconvolution analysis cancer Thus, we introduce network-based method...

10.1158/1538-7445.am2024-2325 article EN Cancer Research 2024-03-22
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