Glycogen synthase kinase-3 beta (GSK3β) is a serine/threonine kinase that plays key roles in glycogen metabolism, Wnt/β-catenin signaling cascade, synaptic modulation, and multiple autophagy-related signaling pathways. GSK3β is an attractive target for drug discovery since its aberrant activity is involved in the development of neurodegenerative diseases such as Alzheimer\'s and Parkinson\'s disease. In the present study, multiple machine learning models aimed at identifying novel GSK3β inhibitors were developed and evaluated for their predictive reliability. The most powerful models were combined in a consensus approach, which was used to screen about 2 million commercial compounds. Our consensus machine learning-based virtual screening led to the identification of compounds G1 and G4, which showed inhibitory activity against GSK3β in the low-micromolar and sub-micromolar range, respectively. These results demonstrated the reliability of our virtual screening approach. Moreover, docking and molecular dynamics simulation studies were employed for predicting reliable binding modes for G1 and G4, which represent two valuable starting points for future hit-to-lead and lead optimization studies.

Colorectal cancer (CRC) is a heterogeneous disease with different genetic and molecular backgrounds, leading to a diverse patient prognosis and treatment response. Four consensus molecular subtypes (CMS 1-4) have recently been proposed based on transcriptome profiling. A clinically practical immunohistochemistry (IHC) based CMS classifier consisting of the four markers FRMD6, ZEB1, HTR2B, and CDX2 was then demonstrated. However, the IHC-CMS classifier did not distinguish between CMS2 and CMS3 tumours. In this study, we have applied the proposed transcriptome based and IHC-based CMS classifiers in a CRC cohort of 65 patients and found a concordance of 77.5 %. Further, we modified the IHC-CMS classifier by analysing the differentially expressed genes between CMS2 and CMS3 tumours using RNA-sequencing data from the TCGA dataset. The result showed that WNT signalling was among the most upregulated pathways in CMS2 tumours, and the expression level of CTNNB1 (encoding β-catenin), a WNT pathway hallmark, was significantly upregulated (P = 1.15 × 10-6). We therefore introduced nuclear β-catenin staining to the IHC-CMS classifier. Using the modified classifier in our cohort, we found a 71.4 % concordance between the IHC and RNA-sequencing based CMS classifiers. Moreover, β-catenin staining could classify 16 out of the 19 CMS2/3 tumours into CMS2 or CMS3, thereby showing an 84.2 % concordance with the RNA-sequencing-based classifier. In conclusion, we evaluated CMS classifiers based on transcriptome and IHC analysis. We present a modified IHC panel that categorizes CRC tumours into the four CMS groups. To our knowledge, this is the first study using IHC to identify all four CMS groups.

Solid tumour growth is the consequence of a complex interplay between cancer cells and their microenvironment. Recently, a new global transcriptomic immune classification of solid tumours has identified six immune subtypes (ISs) (C1-C6). Our aim was to specifically characterise ISs in colorectal cancer (CRC) and assess their interplay with the consensus molecular subtypes (CMSs).
Clinical and molecular information, including CMSs and ISs, were obtained from The Cancer Genome Atlas (TCGA) (N = 625). Immune cell populations, differential gene expression and gene set enrichment analysis were performed to characterise ISs in the global CRC population by using CMSs.
Only 5 ISs were identified in CRC, predominantly C1 wound healing (77%) and C2 IFN-γ dominant (17%). CMS1 showed the highest proportion of C2 (53%), whereas C1 was particularly dominant in CMS2 (91%). CMS3 had the highest representation of C3 inflammatory (7%) and C4 lymphocyte depleted ISs (4%), whereas all C6 TGF-β dominant cases belonged to CMS4 (2.3%). Prognostic relevance of ISs in CRC substantially differed from that reported for the global TCGA, and ISs had a greater ability to stratify the prognosis of CRC patients than CMS classification. C2 had higher densities of CD8, CD4 activated, follicular helper T cells, regulatory T cells and neutrophils and the highest M1/M2 polarisation. C2 had a heightened activation of pathways related to the immune system, apoptosis and DNA repair, mTOR signalling and oxidative phosphorylation, whereas C1 was more dependent of metabolic pathways.
The correlation of IS and CMS allows a more precise categorisation of patients with relevant clinical and biological implications, which may be valuable tools to improve tailored therapeutic interventions in CRC patients.

OBJECTIVE: Interferon consensus sequence-binding protein 8 (IRF8) belongs to a family of interferon (IFN) regulatory factors that modulates various important physiological processes including carcinogenesis. As reported by others and our group, IRF8 expression is silenced by DNA methylation in both human solid tumors and hematological malignancies. However, the role of IRF8 in lung carcinoma remains elusive. In this study, we determined IRF8 epigenetic regulation, biological functions, and the signaling pathway involved in non-small cell lung cancer (NSCLC).
METHODS: IRF8 expression were determined by Q- PCR. MSP and A+T determined promotor methylation. MTS, clonogenic, Transwell assay, Flow cytometry, three-dimensional culture and AO/EB stain verified cell function. In vivo tumorigenesis examed the in vivo effects. By Chip-QPCR, RT-PCR, Western blot and Immunofluorescence staining, the mechanisms were studied.
RESULTS: IRF8 was significantly downregulated in lung tumor tissues compared with adjacent non-cancerous tissues. Furthermore, methylation-specific PCR analyses revealed that IRF8 methylation in NSCLC was a common event, and demethylation reagent treatment proved that downregulation of IRF8 was due to its promoter CpG hypermethylation. Clinical data showed that the IRF8 methylation was associated with tumor stage, lymph node metastasis status, patient outcome, and tumor histology. Exogenous expression of IRF8 in the silenced or downregulated lung cancer cell lines A549 and H1299 at least partially restored the sensitivity of lung cancer cells to apoptosis, and arrested cells at the G0/G1 phase. Cell viability, clonogenicity, and cell migration and invasive abilities were strongly inhibited by restored expression of IRF8. A three-dimensional culture system demonstrated that IRF8 changed the cells to a more spherical phenotype. Moreover, ectopic expression of IRF8 enhanced NSCLC chemosensitivity to cisplatin. Furthermore, as verified by Chip-qPCR, immunofluorescence staining, and western blotting, IRF8 bound to the T-cell factor/lymphoid enhancer factor (TCF /LEF) promoter, thus repressing β-catenin nuclear translocation and its activation. IRF8 significantly disrupted the effects of Wnt agonist, bml284, further suggesting its involvement in the Wnt/β-catenin pathway.
CONCLUSIONS: IRF8 acted as a tumor suppressor gene through the transcriptional repression of β-catenin-TCF/LEF in NSCLC. IRF8 methylation may serve as a potential biomarker in NSCLC prognosis.

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-β activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions.

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