AI Article Synopsis

  • PANoptosis is involved in the immune response and cancer development, particularly in hepatocellular carcinoma (HCC), but its clinical implications remain unclear.
  • Research utilized RNA sequencing and single-cell analysis to identify molecular subtypes and associations with PANoptosis, establishing a scoring system to predict clinical outcomes.
  • Patients were classified into low- and high-PANoptosis groups, with high-PANoptosis tumors showing increased immune activity but more aggressive cancer characteristics, along with elevated levels of the protein HSP90AA1 in their circulation.

Article Abstract

PANoptosis is engaged in the program of immune response and carcinogenicity. Nonetheless, the actual impacts of PANoptosis on clinical management and oncology immunity in hepatocellular carcinoma (HCC) are not fully grasped. RNA-seq-derived computations were conducted to sort out the molecular subtypes and elucidate the disparities based on PANoptosis molecules. Single-cell sequencing (scRNA-seq) tools including Cytotrace and Addmodulescore were extracted to characterize diversification potency and quantify the PANoptosis motion. Transcriptional factors were inferred by the pySCENIC package and Cellchat program scrutinized the intercellular exchange across cell compartments. The PANoptosis score system originated by incorporating 10 machine learning algorithms and 101 compositions to project clinical results and deteriorate tendencies. Circulatory PANoptosis-associated protein HSP90AA1 was determined by enzyme-linked immunosorbent assay (ELISA). HCC individuals could be categorized into low- and high-PANoptosis groups with diverse biogenic and pharmacotherapy heterogeneity. Individuals in the elevated PANoptosis subtype were characterized as "hot tumor" conveying the increased presence of immunogenicity while reiterating an explicit negative connection with tumor stemness. Compared to immune and stromal cells, cancerous cells showcased decreased PANoptosis and heightened PANoptosis malignant cell subgroups might be tied to a substantial level of genomic expression of SREBF2, JUND, GATAD1, ZBTB20, SMAD5 and implied a more aggressive potential. The PANoptosis index, derived from machine learning, has been established to provide succinct frameworks for predicting outcomes and clarified the noteworthy utility of conventional regimens, as the differentiated power of HCC occurred together with vascular invasion and hepatocellular adenoma (HCA). The experiment confirmed that the circulating HSP90AA1 was aberrantly augmented in HCC patients, thus demonstrating its potential as a discriminatory biomarker. We systematically deciphered the molecular and immune ecosystem traits of PANoptosis in bulk and scRNA-seq degrees, which may deliver advantageous insights for customized treatment, awareness of the pathological process and prognosis scrutiny for HCC patients.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438900PMC
http://dx.doi.org/10.1038/s41598-024-73847-1DOI Listing

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