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N-Glycosylation Patterns Correlate with Hepatocellular Carcinoma Genetic Subtypes.

Andrew DelaCourtAlyson BlackPeggi M AngelRichard DrakeYujin HoshidaAmit SingalDavid LewinBachir A TaouliSara LewisMyron E SchwartzM Isabel FielAnand S Mehta
Published in: Molecular cancer research : MCR (2021)
Hepatocellular carcinoma (HCC) is the second leading cause of cancer deaths globally, and the incidence rate in the United States is increasing. Studies have identified inter- and intratumor heterogeneity as histologic and/or molecular subtypes/variants associated with response to certain molecular targeted therapies. Spatial HCC tissue profiling of N-linked glycosylation by matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) may serve as a new method to evaluate the tumor heterogeneity. Previous work has identified significant changes in the N-linked glycosylation of HCC tumors but has not accounted for the heterogeneous genetic and molecular nature of HCC. To determine the correlation between HCC-specific N-glycosylation changes and genetic/molecular tumor features, we profiled HCC tissue samples with MALDI-IMS and correlated the spatial N-glycosylation with a widely used HCC molecular classification (Hoshida subtypes). MALDI-IMS data displayed trends that could approximately distinguish between subtypes, with subtype 1 demonstrating significantly dysregulated N-glycosylation versus adjacent nontumor tissue. Although there were no individual N-glycan structures that could identify specific subtypes, trends emerged regarding the correlation of branched glycan expression to HCC as a whole and fucosylated glycan expression to subtype 1 tumors specifically. IMPLICATIONS: Correlating N-glycosylation to specific subtypes offers the specific detection of subtypes of HCC, which could both enhance early HCC sensitivity and guide targeted clinical therapies.
Keyphrases
  • mass spectrometry
  • poor prognosis
  • copy number
  • single cell
  • genome wide
  • risk factors
  • gene expression
  • photodynamic therapy
  • electronic health record
  • drug delivery
  • big data
  • label free