Discovering pathway biomarkers of hepatocellular carcinoma occurrence and development by dynamic network entropy analysis

Shen, Chen; Cao, Yi; Qi, Guoqiang; Huang, Jikun; Liu, Zhi Ping

doi:10.1016/j.gene.2023.147467

Cited by 1 publication

(1 citation statement)

References 28 publications

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“…Interestingly, several pathways identified by our PH method have been previously associated with HCC, or their association has been suggested by other computational approaches. For completeness, we provide a list: genetic information processing pathways (RNA polymerase [42], protein processing in endoplasmic reticulum [43], and base excision repair [44,45]), environmental information processing pathways (ABC transporters [46][47][48] and apelin signaling pathway [49,50]), a cellular processes pathway (p53 signaling pathway [51][52][53][54]), organismal systems pathways (IL-17 signaling pathway [55,56] and synaptic vesicle cycle [57]), and several metabolism pathways (riboflavin metabolism [58], citrate/TCA cycle [59][60][61], ascorbate and aldarate metabolism [62,63], drug metabolismcytochrome P450 [48,[64][65][66][67], glycine, serine, and threonine metabolism [48,64,68], primary bile acid biosynthesis [64], histidine metabolism [64], beta-alanine metabolism [64], tryptophan metabolism [54,64,69,70], pantothenate and CoA biosynthesis [58,[71][72][73], ...…”

Section: Comparison Of Pathways Identified By the Ph Methods And The ...mentioning

confidence: 99%

Persistent Homology Identifies Pathways Associated with Hepatocellular Carcinoma from Peripheral Blood Samples

Abdullahi,

Suratanee,

Piro

et al. 2024

Mathematics

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Topological data analysis (TDA) methods have recently emerged as powerful tools for uncovering intricate patterns and relationships in complex biological data, demonstrating their effectiveness in identifying key genes in breast, lung, and blood cancer. In this study, we applied a TDA technique, specifically persistent homology (PH), to identify key pathways for early detection of hepatocellular carcinoma (HCC). Recognizing the limitations of current strategies for this purpose, we meticulously used PH to analyze RNA sequencing (RNA-seq) data from peripheral blood of both HCC patients and normal controls. This approach enabled us to gain nuanced insights by detecting significant differences between control and disease sample classes. By leveraging topological descriptors crucial for capturing subtle changes between these classes, our study identified 23 noteworthy pathways, including the apelin signaling pathway, the IL-17 signaling pathway, and the p53 signaling pathway. Subsequently, we performed a comparative analysis with a classical enrichment-based pathway analysis method which revealed both shared and unique findings. Notably, while the IL-17 signaling pathway was identified by both methods, the HCC-related apelin signaling and p53 signaling pathways emerged exclusively through our topological approach. In summary, our study underscores the potential of PH to complement traditional pathway analysis approaches, potentially providing additional knowledge for the development of innovative early detection strategies of HCC from blood samples.

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Section: Comparison Of Pathways Identified By the Ph Methods And The ...mentioning

confidence: 99%

Persistent Homology Identifies Pathways Associated with Hepatocellular Carcinoma from Peripheral Blood Samples

Abdullahi,

Suratanee,

Piro

et al. 2024

Mathematics

View full text Add to dashboard Cite

show abstract

Discovering pathway biomarkers of hepatocellular carcinoma occurrence and development by dynamic network entropy analysis

Cited by 1 publication

References 28 publications

Persistent Homology Identifies Pathways Associated with Hepatocellular Carcinoma from Peripheral Blood Samples

Persistent Homology Identifies Pathways Associated with Hepatocellular Carcinoma from Peripheral Blood Samples

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