title: Conservation of immune gene signatures in solid tumors and prognostic implications.
abstract: Tumor-infiltrating leukocytes can either limit cancer growth or facilitate its spread. Diagnostic strategies that comprehensively assess the functional complexity of tumor immune infiltrates could have wide-reaching clinical value. In previous work we identified distinct immune gene signatures in breast tumors that reflect the relative abundance of infiltrating immune cells and exhibited significant associations with patient outcomes. Here we hypothesized that immune gene signatures agnostic to tumor type can be identified by de novo discovery of gene clusters enriched for immunological functions and possessing internal correlation structure conserved across solid tumors from different anatomic sites.
  
  
  
  We assembled microarray expression datasets encompassing 5,295 tumors of the breast, colon, lung, ovarian and prostate. Unsupervised clustering methods were used to determine number and composition of gene clusters within each dataset. Immune-enriched gene clusters (signatures) identified by gene ontology enrichment were analyzed for internal correlation structure and conservation across tumors then compared against expression profiles of: 1) flow-sorted leukocytes from peripheral blood and 2) >300 cancer cell lines from solid and hematologic cancers. Cox regression analysis was used to identify signatures with significant associations with clinical outcome.
  
  
  
  We identified nine distinct immune-enriched gene signatures conserved across all five tumor types. The signatures differentiated specific leukocyte lineages with moderate discernment overall, and naturally organized into six discrete groups indicative of admixed lineages. Moreover, seven of the signatures exhibit minimal and uncorrelated expression in cancer cell lines, suggesting that these signatures derive predominantly from infiltrating immune cells. All nine immune signatures achieved statistically significant associations with patient prognosis (p<0.05) in one or more tumor types with greatest significance observed in breast and skin cancers. Several signatures indicative of myeloid lineages exhibited poor outcome associations that were most apparent in brain and colon cancers.
  
  
  
  These findings suggest that tumor infiltrating immune cells can be differentiated by immune-specific gene expression patterns that quantify the relative abundance of multiple immune infiltrates across a range of solid tumor types. That these markers of immune involvement are significantly associated with patient prognosis in diverse cancers suggests their clinical utility as pan-cancer markers of tumor behavior and immune responsiveness.
authors.affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA.
authors.forename: Julia
authors.initials: J
authors.lastname: Chifman
authors.affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA.
authors.forename: Ashok
authors.initials: A
authors.lastname: Pullikuth
authors.affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA.|Department of Biostatistical Sciences, Wake Forest Public Health Sciences, Medical Center Boulevard, Winston-Salem, 27157, NC, USA.
authors.forename: Jeff W
authors.initials: JW
authors.lastname: Chou
authors.affiliation: Sidra Medical and Research Center, Doha, Qatar.
authors.forename: Davide
authors.initials: D
authors.lastname: Bedognetti
authors.affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA. ldmiller@wakehealth.edu.
authors.forename: Lance D
authors.identifier: 0000-0003-3799-2528
authors.initials: LD
authors.lastname: Miller
mesh_terms: D015415:Biomarkers; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D066264:Datasets as Topic; D019143:Evolution, Molecular; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D007109:Immunity / Q000235:genetics*; D007962:Leukocytes / Q000378:metabolism; D058977:Molecular Sequence Annotation; D009369:Neoplasms / Q000235:genetics* / Q000276:immunology / Q000401:mortality*; D011379:Prognosis; D059467:Transcriptome
chemical_list: D015415:Biomarkers
keywords: Consensus clustering; Enrichment scores; Immune signatures; Survival analysis