Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma

Exploration of the radiosensitivity-related prognostic risk signature in patients with glioma: evidence from microarray data

BACKGROUND

Gene expression signatures can be used as prognostic biomarkers in various types of cancers. We aim to develop a gene signature for predicting the response to radiotherapy in glioma patients.

METHODS

Radio-sensitive and radio-resistant glioma cell lines (M059J and M059K) were subjected to microarray analysis to screen for differentially expressed mRNAs. Additionally, we obtained 169 glioblastomas (GBM) samples and 5 normal samples from The Cancer Genome Atlas (TCGA) database, as well as 80 GBM samples and 4 normal samples from the GSE7696 set. The "DESeq2" R package was employed to identify differentially expressed genes (DEGs) between the normal brain samples and GBM samples. Combining the prognostic-related molecules identified from the TCGA, we developed a radiosensitivity-related prognostic risk signature (RRPRS) in the training set, which includes 152 patients with glioblastoma. Subsequently, we validated the reliability of the RRPRS in a validation set containing 616 patients with glioma from the TCGA database, as well as an internal validation set consisting of 31 glioblastoma patients from the Nanfang Hospital, Southern Medical University.

RESULTS

Based on the microarray and LASSO COX regression analysis, we developed a nine-gene radiosensitivity-related prognostic risk signature. Patients with glioma were divided into high- or low-risk groups based on the median risk score. The Kaplan-Meier survival analysis showed that the progression-free survival (PFS) of the high-risk group was significantly shorter. The signature accurately predicted PFS as assessed by time-dependent receiver operating characteristic curve (ROC) analyses. Stratified analysis demonstrated that the signature is specific to predict the outcome of patients who were treated using radiotherapy. Univariate and multivariate Cox regression analysis revealed that the predictor was an independent predictor for the prognosis of patients with glioma. The prognostic nomograms accompanied by calibration curves displayed the 1-, 2-, and 3-year PFS and OS in patients with glioma.

CONCLUSION

Our study established a new nine-gene radiosensitivity-related prognostic risk signature that can predict the prognosis of patients with glioma who received radiotherapy. The nomogram showed great potential to predict the prognosis of patients with glioma treated using radiotherapy.

Prognostic factors affecting outcome of multifocal or multicentric glioblastoma: A scoping review

It has been reported that patients with multiple lesions have shorter overall survival compared to single lesion in glioblastoma (GBM). Number of lesions can profoundly impact the prognosis and treatment outcome in GBM. In view of the advancement of imaging, multiple GBM (mGBM) lesions are increasingly recognized and reported. The scoping review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension statement for systematic review. Database was searched to collect relevant articles based on predefined eligibility criteria. Our observations suggest that multifocal/multicentric GBM has poorer outcome compared to GBM with singular lesion (sGBM). As the factors influencing the prognosis and outcome is poorly understood and there is no consensus in the existing literature, this review is clinically relevant. As patients with single lesion are more likely to undergo gross total excision, it is likely that further adjuvant treatment may be decided by extent of resection. This review will be helpful for design of further prospective randomized studies for optimal management of mGBM.

Multicentric Glioma: An Ideal Model to Reveal the Mechanism of Glioma

As a special type of glioma, multicentric glioma provides an ideal pathological model for glioma research. According to the stem-cell-origin theory, multiple lesions of multicentric glioma share the same neuro-oncological origin, both in gene level and in cell level. Although the number of studies focusing on genetic evolution in gliomas with the model of multicentric gliomas were limited, some mutations, including IDH1 mutations, TERTp mutations and PTEN deletions, are found to be at an early stage in the process of genetic aberrance during glioma evolution based on the results of these studies. This article reviews the clinical reports and genetic studies of multicentric glioma, and intends to explain the various clinical phenomena of multicentric glioma from the perspective of genetic aberrance accumulation and tumor cell evolution. The malignant degree of a glioma is determined by both the tumorigenicity of early mutant genes, and the stemness of early suffered cells.

Radiomics for precision medicine in glioblastoma

INTRODUCTION

Being the most common primary brain tumor, glioblastoma presents as an extremely challenging malignancy to treat with dismal outcomes despite treatment. Varying molecular epidemiology of glioblastoma between patients and intra-tumoral heterogeneity explains the failure of current one-size-fits-all treatment modalities. Radiomics uses machine learning to identify salient features of the tumor on brain imaging and promises patient-specific management in glioblastoma patients.

METHODS

We performed a comprehensive review of the available literature on studies investigating the role of radiomics and radiogenomics models for the diagnosis, stratification, prognostication as well as treatment planning and monitoring of glioblastoma.

RESULTS

Classifiers based on a combination of various MRI sequences, genetic information and clinical data can predict non-invasive tumor diagnosis, overall survival and treatment response with reasonable accuracy. However, the use of radiomics for glioblastoma treatment remains in infancy as larger sample sizes, standardized image acquisition and data extraction techniques are needed to develop machine learning models that can be translated effectively into clinical practice.

CONCLUSION

Radiomics has the potential to transform the scope of glioblastoma management through personalized medicine.

Identification of prognostic values defined by copy number variation, mRNA and protein expression of LANCL2 and EGFR in glioblastoma patients

BACKGROUND

Epidermal growth factor receptor (EGFR) and lanthionine synthetase C-like 2 (LanCL2) genes locate in the same amplicon, and co-amplification of EGFR and LANCL2 is frequent in glioblastoma. However, the prognostic value of LANCL2 and EGFR co-amplification, and their mRNA and protein expression in glioblastoma remain unclear yet.

METHODS

This study analyzed the prognostic values of the copy number variations (CNVs), mRNA and protein expression of LANCL2 and EGFR in 575 glioblastoma patients in TCGA database and 100 glioblastoma patients in tumor banks of the Shenzhen Second People's Hospital and the Sun Yat-sen University Cancer Center.

RESULTS

The amplification of LANCL2 or EGFR, and their co-amplification were frequent in glioblastoma of TCGA database and our tumor banks. A significant correlation was found between the CNVs of LANCL2 and EGFR (p < 0.001). CNVs of LANCL2 or EGFR were significantly correlated with IDH1/2 mutation but not MGMT promoter methylation. Multivariate analysis showed that LANCL2 amplification was significantly correlated with reduced overall survival (OS) in younger (< 60 years) glioblastoma patients of TCGA database (p = 0.043, HR = 1.657) and our tumor banks (p = 0.018, HR = 2.199). However, LANCL2 or EGFR amplification, and their co-amplification had no significant impact on OS in older (≥ 60 years) or IDH1/2-wild-type glioblastoma patients. mRNA and protein overexpression of LANCL2 and EGFR was also frequently found in glioblastoma. The mRNA expression rather than the protein expression of LANCL2 and EGFR was positively correlated (p < 0.001). However, mRNA or protein expression of EGFR and LANCL2 was not significantly correlated with OS of glioblastoma patients. The protein expression level of LANCL2, rather than EGFR, was elevated in relapsing glioblastoma, compared with newly diagnosed glioblastoma. In addition, the intracellular localization of LanCL2, not EGFR, was associated with the grade of gliomas.

CONCLUSIONS

Taken together, amplification and mRNA overexpression of LANCL2 and EGFR, and their co-amplification and co-expression were frequent in glioblastoma patients. Our findings suggest that amplification of LANCL2 and EGFR were the independent diagnostic biomarkers for glioblastoma patients, and LANCL2 amplification was a significant prognostic factor for OS in younger glioblastoma patients.

Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome for patients with hepatocellular carcinoma

Aims: Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bidirectional deep neural networks (BiDNNs), an unsupervised machine-learning approach, to integrate multi-omics data and predict survival in HCC. Methods: DNA methylation and mRNA expression data for HCC samples from the TCGA database were integrated using BiDNNs. With optimal clusters as labels, a support vector machine model was developed to predict survival. Results: Using the BiDNN-based model, samples were clustered into two survival subgroups. The survival subgroup classification was an independent prognostic factor. BiDNNs were superior to multimodal autoencoders. Conclusion: This study constructed and validated a BiDNN-based model for predicting prognosis in HCC, with implications for individualized therapies in HCC.

Low expression of CDHR1 is an independent unfavorable prognostic factor in glioma

Background: Analysis of the differentially expressed genes between lower grade glioma (LGG) and glioblastoma (GBM) will identify genes involved in a more aggressive phenotype of glioma. Methods: Differentially expressed genes between GBM and LGG were identified using published datasets. Kaplan-Meier estimator was used to determine the overall survival of different groups of glioma patients. The biological functions of CDHR1 in glioma were tested using CCK-8 and trans-well assays. Results: CCDC109B, CD58, CLIC1, EFEMP2, EMP3, LAMC1, LGALS1, PDLIM1 and TNFRSF1A were over-expressed, while, CDHR1 was down-regulated in GBM in The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), GSE4412 and GSE43378 datasets. Compared with normal brain tissues, CDHR1 was down-regulated in glioma tissues. And low expression of CDHR1 was an unfavorable prognostic factor in glioma. Moreover, CDHR1 was lowly expressed in mesenchymal GBM subtype and lower expression of CDHR1 was associated with the worse clinical prognosis of GBM. Furthermore, CDHR1 was down-regulated in astrocytoma LGG subtype and low expression of CDHR1 was a bad prognosis of LGG. CDHR1 expression levels were also associated with IDH mutation. IDH mutant LGG or GBM patients were with higher CDHR1 expression. High expression of CDHR1 was a favorable prognosis in IDH mutant or IDH wild type LGG patients. CHDR1 expression was associated with MGMT methylation and CDHR1 was down-regulated in chemotherapy un-responsive LGG patients. CDHR1 was an independent prognostic factor and negatively associated with EMP3 expression. Glioma patients with low CDHR1 and high EMP3 expression had worse clinical outcomes. At last, we showed that over-expression of CDHR1 could inhibit glioma cell growth and invasion. Conclusion: Low expression of CDHR1 was an independent unfavorable prognostic factor in glioma.

Human Mitoribosome Biogenesis and Its Emerging Links to Disease

Mammalian mitochondrial ribosomes (mitoribosomes) synthesize a small subset of proteins, which are essential components of the oxidative phosphorylation machinery. Therefore, their function is of fundamental importance to cellular metabolism. The assembly of mitoribosomes is a complex process that progresses through numerous maturation and protein-binding events coordinated by the actions of several assembly factors. Dysregulation of mitoribosome production is increasingly recognized as a contributor to metabolic and neurodegenerative diseases. In recent years, mutations in multiple components of the mitoribosome assembly machinery have been associated with a range of human pathologies, highlighting their importance to cell function and health. Here, we provide a review of our current understanding of mitoribosome biogenesis, highlighting the key factors involved in this process and the growing number of mutations in genes encoding mitoribosomal RNAs, proteins, and assembly factors that lead to human disease.

Multicentric non-enhancing lesions in glioblastoma: A retrospective study

Glioblastoma (GBM) typically presents as a single lesion. Multicentric GBM are defined as well separated lesions on MRI (enhancing and non-enhancing). Multicentric GBM with non-enhancing lesions (MNE-GBM) are rarely described in literature. We aimed at describing the radiologic characteristics, treatment, and clinical course of those patients. The institutional neuropathological database was searched for GBM patients diagnosed between 1/1/2015 and 31/05/2018. All pre-operative MRI brain scans were reviewed to identify patients with MNE-GBM. Electronic medical records and follow-up MRI scans were reviewed to assess progression-free survival (PFS) and overall survival (OS). Out of 149 adult patients with newly diagnosed GBM, 12 met the inclusion criteria of MNE-GBM, all of them presented at least one enhancing lesion. Median follow-up for the MNE-GBM patients was 16.1 months. At last follow-up, all patients had recurrence (median PFS 7.6 months) and eleven patients had deceased. Median OS was 16.2 months (95% CI, 4.1-27.5). Eleven patients received radiotherapy concomitant with temozolomide as initial treatment. Radiation field included all the disease foci (enhancing and non-enhancing lesions) in 8 patients, five of them progressed within the non-enhancing lesion. Three patients did not receive radiation for the entire non-enhancing lesions, and two of them progressed within the non-irradiated areas. In conclusion, MNE-GBM is not rare, and has high risk of aggressive progression within the separate non-enhancing lesion.

Identification of ZG16B as a prognostic biomarker in breast cancer

Zymogen granule protein 16B (ZG16B) has been identified in various cancers, while so far the association between ZG16B and breast cancer hasn’t been explored. Our aim is to confirm whether it can serve as a prognostic biomarker in breast cancer. In this study, Oncomine, Cancer Cell Line Encyclopedia (CCLE), Ualcan, and STRING database analyses were conducted to detect the expression level of ZG16B in breast cancer with different types. Kaplan–Meier plotter was used to analyze the prognosis of patients with high or low expression of ZG16B. We found that ZG16B was significantly upregulated in breast cancer. Moreover, ZG16B was closely associated with foregone biomarkers and crucial factors in breast cancer. In the survival analysis, high expression of ZG16B represents a favorable prognosis in patients. Our work demonstrates the latent capacity of ZG16B to be a biomarker for prognosis of breast cancer.

Imaging signatures of glioblastoma molecular characteristics: A radiogenomics review

Over the past few decades, the advent and development of genomic assessment methods and computational approaches have raised the hopes for identifying therapeutic targets that may aid in the treatment of glioblastoma. However, the targeted therapies have barely been successful in their effort to cure glioblastoma patients, leaving them with a grim prognosis. Glioblastoma exhibits high heterogeneity, both spatially and temporally. The existence of different genetic subpopulations in glioblastoma allows this tumor to adapt itself to environmental forces. Therefore, patients with glioblastoma respond poorly to the prescribed therapies, as treatments are directed towards the whole tumor and not to the specific genetic subregions. Genomic alterations within the tumor develop distinct radiographic phenotypes. In this regard, MRI plays a key role in characterizing molecular signatures of glioblastoma, based on regional variations and phenotypic presentation of the tumor. Radiogenomics has emerged as a (relatively) new field of research to explore the connections between genetic alterations and imaging features. Radiogenomics offers numerous advantages, including noninvasive and global assessment of the tumor and its response to therapies. In this review, we summarize the potential role of radiogenomic techniques to stratify patients according to their specific tumor characteristics with the goal of designing patient-specific therapies. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:54-69.

Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks

Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs. We used the t-distributed stochastic neighbor embedding (t-SNE) method to identify PTM clusters and then integrated each with known protein-protein interactions (PPIs) to elucidate functional cell signaling pathways. The CFN identified known and previously unknown cell signaling pathways in lung cancer cells that were not present in normal lung epithelial tissue. In various proteins modified by more than one type of PTM, the incidence of those PTMs exhibited inverse relationships, suggesting that molecular exclusive "OR" gates determine a large number of signal transduction events. We also showed that the acetyltransferase EP300 appears to be a hub in the network of pathways involving different PTMs. In addition, the data shed light on the mechanism of action of geldanamycin, an HSP90 inhibitor. Together, the findings reveal that cell signaling pathways mediated by acetylation, methylation, and phosphorylation regulate the cytoskeleton, membrane traffic, and RNA binding protein-mediated control of gene expression.

Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis

With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including EGFR-mutations and ALK-rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.

Multiple high-grade gliomas: epidemiology, management, and outcome. A systematic review and meta-analysis

Multiple high-grade gliomas (M-HGGs) are well--separated tumors, differentiated as multifocal (MF) and multicentric (MC) by their MRI features. The authors performed a systematic review and meta-analysis of literature examining epidemiology, clinical and radiological characteristics, management, and the overall survival from M-HGGs. According to PRISMA guidelines, a comprehensive review of studies published between January 1990 and January 2017 was carried out. The authors identified studies that examined the prevalence rate, clinical and radiological characteristics, treatment, and overall survival from M-HGGs in patients with HGG. Data were analyzed using a random-effects meta-analysis model. Finally, we systematically reviewed demographic characteristics, lesion location, and surgical and adjuvant treatments. Twenty-three studies were included in this systematic review. The M-HGGs prevalence rate was 19% (95% CI 13-26%) and the hazard ratio of death from M-HGGs in the HGGs population was 1.71 (95% CI 1.49-1.95, p < 0.0001). The MC prevalence rate was 6% (CI 95% 4-10%), whereas MF prevalence rate was 11% (CI 95% 6-20%) (p < 0.0001). There were no statistically significant differences between MF and MC HGGs in gender, lesion location, histological type, and surgical treatment. Survival analysis of MC tumors showed that surgical resection (gross total resection or subtotal resection) is an independent predictor of improved outcome (HR 7.61 for biopsy subgroup, 95% CI 1.94-29.78, p = 0.004). The prevalence of M-HGGs is approximately 20% of HGGs. The clinical relevance of separating M-HGGs in MF and MC tumors remains questionable and its prognostic significance is unclear. When patient status and lesion characteristics make it safe and feasible, cytoreduction should be attempted in patients with M-HGGs because it improves overall survival.