Cross-species genomics identifies DLG2 as a tumor suppressor in osteosarcoma

Ilex hainanensis Merr targets ITGAV to suppress the proliferation and metastasis of osteosarcoma cells

Background: Osteosarcoma (OS) is the most common primary malignant bone tumor. Hence, there is an urgent need to identify effective and safe therapeutic agents against OS. It has been reported that Ilex hainanensis Merr (IME) possesses antitumor properties. Integrin subunit alpha V (ITGAV) is important for the diagnosis, treatment, and prognosis of tumors.

Purpose: The objective of this study was to whether IME can play a role in the treatment of osteosarcoma by regulating ITGAV.

Methods: Western blot and real-time PCR were used to detect the expression of ITGAV in non-tumorous tissues, osteosarcoma tissues, and metastatic tumors. The expression of ITGAV in MG63, U2OS, and hFOB1. A total of 19 cells was determined through Western blotting and real-time PCR. The expression of ITGAV in OS cells treated with different concentrations of DDP was determined through Western blotting. Agter transfecting with control or si-ITGAV, and subsequently treated with control or 5 μmol/L DDP, MTT assay and transwell assay were used to detect the proliferaion and migration of cells. Western blot was used to detect the expression of ITGAV in cells treated with different concentrations of IME and MTT assay and transwell assay were used to detect the proliferaion and migration of cells. MG63 and U2OS cells were treated with control, 5 μmol/L DDP, 25 μmol/L IME, or 5 μmol/L DDP combined with 25 μmol/L IME, the expression of ITGAV was determined through Western blotting and real-time PCR. MTT assay and transwell assay were used to detect the proliferation and migration of cells. Inhibitory effect of IME on lung metastasis of osteosarcoma in vivo.

Results: ITGAV was highly expressed in tumors, with the highest expression found in metastatic tumors and higher in OS cells. A low concentration of DDP (5 μmol/L) inhibited the expression of ITGAV. However, ITGAV may be related to the development of resistance to DDP. Silencing of ITGAV downregulates the proliferation and migration of OS cells as the effect of low-concentration DDP (5 μmol/L). IME inhibited the proliferation and migration of MG63 and U2OS cells in a concentration-dependent manner and decreased the expression of ITGAV. MTT and Transwell assays showed that 25 μmol/L IME and 5 μmol/L DDP exhibited similar inhibitory effects on the proliferation and migration of OS cells. The combination of IME with DDP resulted in the amplification of these inhibitory effects. Both DDP and IME downregulated the expression of ITGAV, and the inhibition of ITGAV was amplified by the combination of IME with DDP. In-vivo studies have shown that IME and DDP, independently or in combination, may significantly inhibit the metastasis of OS to the lungs.

Conclusion: IME may reduce the resistance of OS cells to DDP to some extent.

The promising novel biomarkers and candidate small molecule drugs in lower-grade glioma: Evidence from bioinformatics analysis of high-throughput data

Overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty-eight nodes with 603 interactions were obtained from the establishment of protein-protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients' prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS-275 (enrichment score = -0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.

A Six-Gene-Based Prognostic Model Predicts Survival in Head and Neck Squamous Cell Carcinoma Patients

Background and Objective

Head and neck cancer is a malignant tumor that begins in the head and neck region, and has the sixth highest incidence worldwide. Previous studies have indicated several prognostic markers for head and neck squamous cell carcinoma (HNSCC), but due to poor accuracy and sensitivity of these clinical characteristic markers attention has been gradually switched to molecular biomarkers. This study aimed to sort out the mRNAs correlated with patient survival time to establish an mRNA combination prognostic biomarker model for HNSCC patient risk stratification, providing optimal therapeutic regimens and improving patient prognosis.

Methods

Clinical data and transcriptome sequencing data of HNSCC were retrieved from TCGA database and were allocated into training and validation datasets. The prognostic model was established using the mRNAs, which were sorted out from training dataset by a significant correlation with survival time. Eventually, the prediction property of the model was evaluated by Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curve.

Results

An optimal prognostic model by the combination of six mRNAs was established. Kaplan-Meier survival analysis revealed effective risk stratification by this model for patients in the two datasets. The area under ROC curve (AUC) was > 0.65 for training and validation datasets, indicating good sensitivity and specificity of this model. Moreover, prominent superiority of this model to investigate prognostic biomarkers was demonstrated.

Conclusion

Our model provided effective prognostication in terms of death risk stratification and evaluation in HNSCC patients. Combination of this prognostic model with current treatment measures is expected to greatly improve the patients' prognosis.

Risk-modeling of dog osteosarcoma genome scans shows individuals with Mendelian-level polygenic risk are common

Background

Despite the tremendous therapeutic advances that have stemmed from somatic oncogenetics, survival of some cancers has not improved in 50 years. Osteosarcoma still has a 5-year survival rate of 66%. We propose the natural canine osteosarcoma model can change that: it is extremely similar to the human condition, except for being highly heritable and having a dramatically higher incidence. Here we reanalyze published genome scans of osteosarcoma in three frequently-affected dog breeds and report entirely new understandings with immediate translational indications.

Results

First, meta-analysis revealed association near FGF9, which has strong biological and therapeutic relevance. Secondly, risk-modeling by multiple logistic regression shows 22 of the 34 associated loci contribute to risk and eight have large effect sizes. We validated the Greyhound stepwise model in our own, independent, case-control cohort. Lastly, we updated the gene annotation from approximately 50 genes to 175, and prioritized those using cross-species genomics data. Mostly positional evidence suggests 13 genes are likely to be associated with mapped risk (including MTMR9, EWSR1 retrogene, TANGO2 and FGF9). Previous annotation included seven of those 13 and prioritized four by pathway enrichment. Ten of our 13 priority genes are in loci that contribute to risk modeling and thus can be studied epidemiologically and translationally in pet dogs. Other new candidates include MYCN, SVIL and MIR100HG.

Conclusions

Polygenic osteosarcoma-risk commonly rises to Mendelian-levels in some dog breeds. This justifies caninized animal models and targeted clinical trials in pet dogs (e.g., using CDK4/6 and FGFR1/2 inhibitors).

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5531-6) contains supplementary material, which is available to authorized users.

The Clonal Evolution of Metastatic Osteosarcoma as Shaped by Cisplatin Treatment

To investigate the genomic evolution of metastatic pediatric osteosarcoma, we performed whole-genome and targeted deep sequencing on 14 osteosarcoma metastases and two primary tumors from four patients (two to eight samples per patient). All four patients harbored ancestral (truncal) somatic variants resulting in TP53 inactivation and cell-cycle aberrations, followed by divergence into relapse-specific lineages exhibiting a cisplatin-induced mutation signature. In three of the four patients, the cisplatin signature accounted for >40% of mutations detected in the metastatic samples. Mutations potentially acquired during cisplatin treatment included NF1 missense mutations of uncertain significance in two patients and a KIT G565R activating mutation in one patient. Three of four patients demonstrated widespread ploidy differences between samples from the sample patient. Single-cell seeding of metastasis was detected in most metastatic samples. Cross-seeding between metastatic sites was observed in one patient, whereas in another patient a minor clone from the primary tumor seeded both metastases analyzed. These results reveal extensive clonal heterogeneity in metastatic osteosarcoma, much of which is likely cisplatin-induced. IMPLICATIONS: The extent and consequences of chemotherapy-induced damage in pediatric cancers is unknown. We found that cisplatin treatment can potentially double the mutational burden in osteosarcoma, which has implications for optimizing therapy for recurrent, chemotherapy-resistant disease.