The immune landscape of solid pediatric tumors

Abstract

Background Large immunogenomic analyses have demonstrated the prognostic role of the functional orientation of the tumor microenvironment in adult solid tumors, this variable has been poorly explored in the pediatric counterpart. Methods We performed a systematic analysis of public RNAseq data (TARGET) for five pediatric tumor types (408 patients): Wilms tumor (WLM), neuroblastoma (NBL), osteosarcoma (OS), clear cell sarcoma of the kidney (CCSK) and rhabdoid tumor of the kidney (RT). We assessed the performance of the Immunologic Constant of Rejection (ICR), which captures an active Th1/cytotoxic response. We also performed gene set enrichment analysis (ssGSEA) and clustered more than 100 well characterized immune traits to define immune subtypes and compared their outcome. Results A higher ICR score was associated with better survival in OS and high risk NBL without MYCN amplification but with poorer survival in WLM. Clustering of immune traits revealed the same five principal modules previously described in adult tumors (TCGA). These modules divided pediatric patients into six immune subtypes (S1-S6) with distinct survival outcomes. The S2 cluster showed the best overall survival, characterized by low enrichment of the wound healing signature, high Th1, and low Th2 infiltration, while the reverse was observed in S4. Upregulation of the WNT/Beta-catenin pathway was associated with unfavorable outcomes and decreased T-cell infiltration in OS. Conclusions We demonstrated that extracranial pediatric tumors could be classified according to their immune disposition, unveiling similarities with adults’ tumors. Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune-responsive tumors.

An integrated tumor, immune and microbiome atlas of colon cancer

“…A modular immune gene signature capturing the continuum of cancer immune surveillance, termed as the Immunologic Constant of Rejection (ICR) 18 , had been proposed 19 . We subsequently optimized and condensed it into a fixed 20-gene panel, showing prognostic significance in different cancer types (for example, melanoma 10 , bladder cancer 10 , breast cancer 20 , 21 , neuroblastoma 22 and soft-tissue sarcoma 23 ). The ICR also correlates with response to immunotherapy across multiple cancer types, including breast 24 , melanoma 10 and non-small-cell lung cancer 25 .…”

Recurrence or progression of neuroblastoma in children with MYCN amplification, 1p deletion or 11q deletion may due to altered immune status

“…In the previously reported pan-cancer analysis, CD8 + T cells, NK cells and neutrophils were signi cantly associated with a better prognosis, while Th2 cells were associated with a poorer prognosis (25). In the study by Sherif S et al (49), patients were classi ed into six immune subtypes, of which S6 was the immune/lymphocyte suppressed subtype, in which both Th2 and Treg were highly enriched. The prognosis of the S6 immune subtype was also relatively poor in the pan-cancer study.…”

Upregulation of interferon signaling predicts sustained complete remission in pediatric AML patients

“…To assess whether the 3-genes signature represented the same TH1-enriched L-TME seen in the Discovery Cohort, we performed an enrichment analysis using a previously published immune subpopulations genes set (see Methods section) (33). The analysis con rmed a contextual cytotoxic/NK/Th1 rich-TME present at AML onset in the high 3-genes of standard-risk patients' group (Fig.…”

“…transformed expression data to calculate gene enrichment scores (ES) using the R package GSVA (v. 1.44.5) (20). Gene sets of immune cell-speci c signatures were used as described in Bindea et al (21) with slight modi cations (22). To visualize the enrichment scores of different signatures we used the ComplexHeatmap R package (v. 2.12.1) (17).…”

“…(a) Heatmap displaying immune cells subpopulation enrichment scores across 3-genes ES groups within the standard group. These immune signatures were previously described in Sherif et al (22). For each ES…”