Immunophenotype-associated gene signature in ductal breast tumors varies by receptor subtype, but the expression of individual signature genes remains consistent

Academic Article


  • Background: In silico deconvolution of invasive immune cell infiltration in bulk breast tumors helps characterize immunophenotype, expands treatment options, and influences survival endpoints. In this study, we identify the differential expression (DE) of the LM22 signature to classify immune-rich and -poor breast tumors and evaluate immune infiltration by receptor subtype and lymph node metastasis. Methods: Using publicly available data, we applied the CIBERSORT algorithm to estimate immune cells infiltrating the tumor into immune-rich and immune-poor groups. We then tested the association of receptor subtype and nodal status with immune-rich/poor phenotype. We used DE to test individual signature genes and over-representation analysis for related pathways. Results: CCL19 and CXCL9 expression differed between rich/poor signature groups regardless of subtype. Overexpression of CHI3L2 and FES was observed in triple negative breast cancers (TNBCs) relative to other subtypes in immune-rich tumors. Non-signature genes, LYZ, C1QB, CORO1A, EVI2B, GBP1, PSMB9, and CD52 were consistently overexpressed in immune-rich tumors, and SCUBE2 and GRIA2 were associated with immune-poor tumors. Immune-rich tumors had significant upregulation of genes/pathways while none were identified in immune-poor tumors. Conclusions: Overall, the proportion of immune-rich/poor tumors differed by subtype; however, a subset of 10 LM22 genes that marked immune-rich status remained the same across subtype. Non-LM22 genes differentially expressed between the phenotypes suggest that the biologic processes responsible for immune-poor phenotype are not yet well characterized.
  • Published In

  • Cancer Medicine  Journal
  • Digital Object Identifier (doi)

    Pubmed Id

  • 19280246
  • Author List

  • Behring M; Ye Y; Elkholy A; Bajpai P; Agarwal S; Kim HG; Ojesina AI; Wiener HW; Manne U; Shrestha S
  • Start Page

  • 5712
  • End Page

  • 5720
  • Volume

  • 10
  • Issue

  • 16