Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment

Autor: Sverre Heim, Torstein R. Meling, Anita Sveen, Lina Cekaite, Petter Brandal, Marine Jeanmougin, Ragnhild A. Lothe, David Scheie, Annette Bentsen Håvik, Guro Elisabeth Lind, Trude H. Ågesen
Jazyk: angličtina
Rok vydání: 2020
Předmět:
0301 basic medicine
Male
Cancer Research
Kaplan-Meier Estimate
CD8-Positive T-Lymphocytes
infiltration
Cohort Studies
0302 clinical medicine
Databases
Genetic
Tumor Microenvironment
Research Articles
Oligonucleotide Array Sequence Analysis
Aged
80 and over
B-Lymphocytes
Brain Neoplasms
General Medicine
Middle Aged
lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Prognosis
Subtyping
Gene Expression Regulation
Neoplastic
Killer Cells
Natural
Oncology
030220 oncology & carcinogenesis
Multigene Family
Molecular Medicine
Female
Infiltration (medical)
Research Article
Adult
Stromal cell
In silico
Biology
lcsh:RC254-282
survival
03 medical and health sciences
Immune system
stratification
Glioma
Genetics
medicine
Humans
Computer Simulation
Aged
Proportional Hazards Models
Tumor microenvironment
Mesenchymal stem cell
glioblastoma
medicine.disease
microenvironment
Survival Analysis
030104 developmental biology
Multivariate Analysis
Cancer research
Stromal Cells
Transcriptome
Zdroj: Molecular Oncology
Jeanmougin, M, Håvik, A B, Cekaite, L, Brandal, P, Sveen, A, Meling, T R, Ågesen, T H, Scheie, D, Heim, S, Lothe, R A & Lind, G E 2020, ' Improved prognostication of glioblastoma beyond molecular subtyping by transcriptional profiling of the tumor microenvironment ', Molecular Oncology, vol. 14, no. 5, pp. 1016-1027 . https://doi.org/10.1002/1878-0261.12668
Molecular Oncology, Vol 14, Iss 5, Pp 1016-1027 (2020)
Molecular Oncology, Vol. 14, No 5 (2020) pp. 1016-1027
ISSN: 1878-0261
1574-7891
Popis: Glioblastoma (GBM), the most aggressive form of brain cancer, is characterized by a high level of molecular heterogeneity, and infiltration by various immune and stromal cell populations. Important advances have been made in deciphering the microenvironment of GBMs, but its association with existing molecular subtypes and its potential prognostic role remain elusive. We have investigated the abundance of infiltrating immune and stromal cells in silico, from gene expression profiles. Two cohorts, including in‐house normal brain and glioma samples (n = 70) and a large sample set from TCGA (n = 393), were combined into a single exploratory dataset. A third independent cohort (n = 124) was used for validation. Tumors were clustered based on their microenvironment infiltration profiles, and associations with known GBM molecular subtypes and patient outcome were tested a posteriori in a multivariable setting. We identified a subset of GBM samples with significantly higher abundances of most immune and stromal cell populations. This subset showed increased expression of both immune suppressor and immune effector genes compared to other GBMs and was enriched for the mesenchymal molecular subtype. Survival analyses suggested that tumor microenvironment infiltration pattern was an independent prognostic factor for GBM patients. Among all, patients with the mesenchymal subtype with low immune and stromal infiltration had the poorest survival. By combining molecular subtyping with gene expression measures of tumor infiltration, the present work contributes with improving prognostic models in GBM.
This work combined molecular subtyping of glioblastomas (GBMs) with gene expression measures of tumor infiltration and identified a subset of GBMs with high abundances of most immune and stromal cell populations. Survival analyses suggested that tumor microenvironment infiltration was an independent prognostic factor for GBM patients. Among all, patients with the mesenchymal subtype and low infiltration had the poorest survival.
Databáze: OpenAIRE
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