A UHPLC/MS/MS Assay Based on an Isotope-Labeled Peptide for Sensitive miR-21 Detection in HCC Serum

Wang, Xinyue; Xu, Jing; Gu, Qihong; Tang, Dingxuan; Ji, Huoyan; Ju, Shaoqing; Wang, Rui; Chen, Lin; Yuan, Ruoyu

doi:10.32604/oncologie.2022.024373

Cited by 4 publications

(4 citation statements)

References 42 publications

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“…This requires more in-depth studies on the mechanism of action of TUBB in LIHC in the future. The above results indicated that the risk model based on these 4 genes had a strong reliability for LIHC patient’s diagnosis and prognosis, and their detection in biological samples such as serum [ 62 ] or urine may be prospective.…”

Section: Discussionmentioning

confidence: 99%

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Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

Liu,

Zhang,

Cui

et al. 2024

PLoS ONE

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Background Liver hepatocellular carcinoma (LIHC) is a prevalent form of primary liver cancer. Research has demonstrated the contribution of tumor stem cells in facilitating tumor recurrence, metastasis, and treatment resistance. Despite this, there remains a lack of established cancer stem cells (CSCs)-associated genes signatures for effectively predicting the prognosis and guiding the treatment strategies for patients diagnosed with LIHC. Methods The single-cell RNA sequencing (scRNA-seq) and bulk RNA transcriptome data were obtained based on public datasets and computerized firstly using CytoTRACE package and One Class Linear Regression (OCLR) algorithm to evaluate stemness level, respectively. Then, we explored the association of stemness indicators (CytoTRACE score and stemness index, mRNAsi) with survival outcomes and clinical characteristics by combining clinical information and survival analyses. Subsequently, weighted co-expression network analysis (WGCNA) and Cox were applied to assess mRNAsi-related genes in bulk LIHC data and construct a prognostic model for LIHC patients. Single-sample gene-set enrichment analysis (ssGSEA), Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Tumor Immune Estimation Resource (TIMER) analysis were employed for immune infiltration assessment. Finally, the potential immunotherapeutic response was predicted by the Tumor Immune Dysfunction and Exclusion (TIDE), and the tumor mutation burden (TMB). Additionally, pRRophetic package was applied to evaluate the sensitivity of high and low-risk groups to common chemotherapeutic drugs. Results A total of four genes (including STIP1, H2AFZ, BRIX1, and TUBB) associated with stemness score (CytoTRACE score and mRNAsi) were identified and constructed a risk model that could predict prognosis in LIHC patients. It was observed that high stemness cells occurred predominantly in the late stages of LIHC and that poor overall survival in LIHC patients was also associated with high mRNAsi scores. In addition, pathway analysis confirmed the biological uniqueness of the two risk groups. Personalized treatment predictions suggest that patients with a low risk benefited more from immunotherapy, while those with a high risk group may be conducive to chemotherapeutic drugs. Conclusion The current study developed a novel prognostic risk signature with genes related to CSCs, which provides novel ideas for the diagnosis, prognosis and treatment of LIHC.

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Section: Discussionmentioning

confidence: 99%

“…had a strong reliability for LIHC patient's diagnosis and prognosis, and their detection in biological samples such as serum [62] or urine may be prospective.…”

Section: Plos Onementioning

confidence: 99%

Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

Liu,

Zhang,

Cui

et al. 2024

PLoS ONE

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“…Despite advances in the treatment of liver cancer [ 6 ], most patients with HCC do not respond well to cell programmed death 1 (anti-PD1) therapy [ 7 ]. Therefore, the identification of key molecular features [ 8 ] with advanced techniques [ 9 , 10 ] related to HCC is helpful for the specific mechanism research of HCC, and may provide new ideas for the search for more potential therapeutic targets and prognostic diagnosis in the future.…”

Section: Introductionmentioning

confidence: 99%

Establishment and verification of a prognostic model based on coagulation and fibrinolysis-related genes in hepatocellular carcinoma

Fan,

Lu,

Shang

et al. 2024

Aging

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Background: Studies have shown that coagulation and fibrinolysis (CFR) are correlated with Hepatocellular carcinoma (HCC) progression and prognosis. We aim to build a model based on CFR-correlated genes for risk assessment and prediction of HCC patient. Methods: HCC samples were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases respectively. The Molecular Signatures Database (MSigDB) was used to select the CFR genes. RiskScore model were established by single sample gene set enrichment analysis (ssGSEA), weighted correlation network analysis (WGCNA), multivariate Cox regression analysis, LASSO regression analysis. Results: PCDH17, PGF, PDE2A, FAM110D, FSCN1, FBLN5 were selected as the key genes and designed a RiskScore model. Those key genes were Differential expressions in HCC cell and patients. Overexpression PDE2A inhibited HCC cell migration and invasion. The higher the RiskScore, the lower the probability of survival. The model has high AUC values in the first, third and fifth year prediction curves, indicating that the model has strong prediction performance. The difference analysis of clinicopathological features found that a great proportion of high clinicopathological grade samples showed higher RiskScore. RiskScore were positively correlated with immune scores and TIDE scores. High levels of immune checkpoints and immunomodulators were observed in high RiskScore group. High RiskScore groups may benefit greatly from taking traditional chemotherapy drugs. Conclusions: We screened CFR related genes to design a RiskScore model, which could accurately evaluate the prognosis and survival status of HCC patients, providing certain value for optimizing the clinical treatment of cancer in the future.

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“…A variety of factors such as lack of curative treatment in patients with early detection, inadequate early detection strategies, inconsistent application of curative treatment and concurrent liver disease all contribute to a high death rate of HCC patients [ 8 ]. Further substantial reduction of HCC cases requires more widespread use of effective treatment of HBV and HCV-related chronic hepatitis and liver cirrhosis, reduction of alcohol consumption, more effective exercise, universal HBV vaccination, promotion of correct eating habits, and enhanced understanding of the molecular biology of HCC [ [9] , [10] , [11] ].…”

Section: Introductionmentioning

confidence: 99%

Construction of a circadian rhythm-relevant gene signature for hepatocellular carcinoma prognosis, immunotherapy and chemosensitivity prediction

Ye,

Du,

et al. 2024

Heliyon

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A UHPLC/MS/MS Assay Based on an Isotope-Labeled Peptide for Sensitive miR-21 Detection in HCC Serum

Cited by 4 publications

References 42 publications

Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

Establishment and verification of a prognostic model based on coagulation and fibrinolysis-related genes in hepatocellular carcinoma

Construction of a circadian rhythm-relevant gene signature for hepatocellular carcinoma prognosis, immunotherapy and chemosensitivity prediction

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