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Background:
ATF5 suppresses differentiation of neuroprogenitor cells and is overexpressed in glioblastoma (GBM). A reduction of its expression leads to apoptotic GBM cell death. Data on ATF5 expression in astrocytoma WHO grade II (low-grade astrocytoma [LGA]) are scarce and lacking on recurrent GBM.
Patients and methods:
ATF5 mRNA was extracted from frozen samples of patients’ GBM (n=79), LGA (n=40), and normal brain (NB, n=10), quantified by duplex qPCR and correlated with retrospectively collected clinical data. ATF5 protein expression was evaluated by measuring staining intensity on immunohistochemistry.
Results:
ATF5 mRNA was overexpressed in LGA (sevenfold, P<0.001) and GBM (tenfold, P<0.001) compared to NB, which was confirmed on protein level. Although ATF5 mRNA expression in GBM showed a considerable fluctuation range, groups of varying biological behavior, that is, local/multifocal growth or primary tumor/relapse and the tumor localization at diagnosis, were not significantly different. ATF5 mRNA correlated with the patients’ age (r=0.339, P=0.028) and inversely with Ki67-staining (r=-0.421, P=0.007). GBM patients were allocated to a low and a high ATF5 expression group by the median ATF5 overexpression compared to NB. Kaplan–Meier analysis and Cox regression indicated that ATF5 mRNA expression significantly correlated with short-term survival (t<12 months, median survival 18 vs 13 months, P=0.022, HR 2.827) and progression-free survival (PFS) (12 vs 6 months, P=0.024). This advantage vanished after 24 months (P=0.084).
Conclusion:
ATF5 mRNA expression could be identified as an additional, though not independent factor correlating with overall survival and PFS. Since its inhibition might lead to the selective death of glioma cells, it might serve as a potential ubiquitous therapeutic target in astrocytic tumors.
Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRAS\(^{G12C}\) or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRAS\(^{G12C}\) inhibitor in KRAS\(^{G12C}\) mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.