Abstract
BackgroundThe tumor-associated microenvironment plays important roles in tumor progression and drug resistance. However, systematic investigations of macrophage–tumor cell interactions to identify novel macrophage-related gene signatures in gliomas for predicting patient prognoses and responses to targeted therapies are lacking.MethodsWe developed a multicellular gene network approach to investigating the prognostic role of macrophage–tumor cell interactions in tumor progression and drug resistance in gliomas. Multicellular gene networks connecting macrophages and tumor cells were constructed from re-grouped drug-sensitive and drug-resistant samples of RNA-seq data in mice gliomas treated with BLZ945 (a CSF1R inhibitor). Subsequently, a differential network-based COX regression model was built to identify the risk signature using a cohort of 310 glioma samples from the Chinese Glioma Genome Atlas database. A large independent validation set of 690 glioma samples from The Cancer Genome Atlas database was used to test the prognostic significance and accuracy of the gene signature in predicting prognosis and targeted therapeutic response of glioma patients.ResultsA macrophage-related gene signature was developed consisting of twelve genes (ANPEP, DPP4, PRRG1, GPNMB, TMEM26, PXDN, CDH6, SCN3A, SEMA6B, CCDC37, FANCA, NETO2), which was tested in the independent validation set to examine its prognostic significance and accuracy. The generation of 1000 random gene signatures by a bootstrapping scheme justified the non-random nature of the macrophage-related gene signature. Moreover, the discovered gene signature was verified to be predictive of the sensitivity or resistance of glioma patients to molecularly targeted therapeutics and outperformed other existing gene signatures. Additionally, the macrophage-related gene signature was an independent and the strongest prognostic factor when adjusted for clinicopathologic risk factors and other existing gene signatures.ConclusionThe multicellular gene network approach developed herein indicates profound roles of the macrophage-mediated tumor microenvironment in the progression and drug resistance of gliomas. The identified macrophage-related gene signature has good prognostic value for predicting resistance to targeted therapeutics and survival of glioma patients, implying that combining current targeted therapies with new macrophage-targeted therapy may be beneficial for the long-term treatment outcomes of glioma patients.
Highlights
The tumor-associated microenvironment plays important roles in tumor progression and drug resistance
We developed a multicellular gene network-based approach to investigating intercellular gene associations between tumor cells (TCs) and tumorassociated macrophages (TAMs) and to identify biomarkers of prognosis and drug resistance in gliomas
The preclinical experiment [10] investigated the role of TAMs in glioma immunotherapy with BLZ945, a CSF1R inhibitor, where all TC-TAM paired samples were divided into 3 groups, i.e., Vehicle (Veh, 5 samples), Endpoint (EP, 6 samples, i.e., drug-sensitive), and Rebound (Reb, 4 samples, i.e., drug-resistant) tumors (Additional file 1: Table S1)
Summary
The tumor-associated microenvironment plays important roles in tumor progression and drug resistance. Many cancer cell-targeted therapeutic agents have been developed, intrinsic or acquired resistance to such therapies often emerges during long-term treatment [2]. The preexisting or newly developed tolerance of cancer cells to molecularly targeted therapeutic drugs is a main cause of the eventual failure of most existing targeted therapies. Several forms of cancer cell-intrinsic mechanisms of drug resistance have been revealed, including genetic/ epigenetic mechanisms [3], posttranslational mechanisms [4,5,6], cellular mechanisms [7, 8], and metabolic mechanisms [9]. An increasing number of experiments indicated that the tumor microenvironment may play important roles in cancer progression and drug resistance [10]. Several macrophage-targeted therapies for gliomas have been developed [10], further highlighting the importance of tumor–microenvironment interactions in determining glioma outcome
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