A radiosensitivity gene signature in predicting glioma prognostic via EMT pathway

Red light-activated depletion of drug-refractory glioblastoma stem cells and chemosensitization of an acquired-resistant mesenchymal phenotype

Glioblastoma stem cells (GSCs) are potent tumor initiators resistant to radiochemotherapy, and this subpopulation is hypothesized to re-populate the tumor milieu due to selection following conventional therapies. Here, we show that 5-aminolevulinic acid (ALA) treatment-a pro-fluorophore used for fluorescence-guided cancer surgery-leads to elevated levels of fluorophore conversion in patient-derived GSC cultures, and subsequent red light-activation induces apoptosis in both intrinsically temozolomide chemotherapy-sensitive and -resistant GSC phenotypes. Red light irradiation of ALA-treated cultures also exhibits the ability to target mesenchymal GSCs (Mes-GSCs) with induced temozolomide resistance. Furthermore, sub-lethal light doses restore Mes-GSC sensitivity to temozolomide, abrogating GSC-acquired chemoresistance. These results suggest that ALA is not only useful for fluorescence-guided glioblastoma tumor resection, but that it also facilitates a GSC drug-resistance agnostic, red light-activated modality to mop up the surgical margins and prime subsequent chemotherapy.

Clinical Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy: A Systematic Review

Modern advanced radiotherapy techniques have improved the precision and accuracy of radiotherapy delivery, with resulting plans being highly personalised based on individual anatomy. Adaptation for individual tumour biology remains elusive. There is an unmet need for biomarkers of intrinsic radiosensitivity that can predict tumour response to radiation to facilitate individualised decision-making, dosing and treatment planning. Over the last few decades, the use of high throughput molecular biology technologies has led to an explosion of newly discovered cancer biomarkers. Gene expression signatures are now used routinely in clinic to aid decision-making regarding adjuvant systemic therapy. They have great potential as radiotherapy biomarkers. A previous systematic review published in 2015 reported only five studies of signatures evaluated for their ability to predict radiotherapy benefits in clinical cohorts. This updated systematic review encompasses the expanded number of studies reported in the last decade. An additional 27 studies were identified. In total, 22 distinct signatures were recognised (5 pre-2015, 17 post-2015). Seventeen signatures were 'radiosensitivity' signatures and five were breast cancer prognostic signatures aiming to identify patients at an increased risk of local recurrence and therefore were more likely to benefit from adjuvant radiation. Most signatures (15/22) had not progressed beyond the discovery phase of development, with no suitable validated clinical-grade assay for application. Very few signatures (4/17 'radiosensitivity' signatures) had undergone any laboratory-based biological validation of their ability to predict tumour radiosensitivity. No signatures have been assessed prospectively in a phase III biomarker-led trial to date and none are recommended for routine use in clinical guidelines. A phase III prospective evaluation is ongoing for two breast cancer prognostic signatures. The most promising radiosensitivity signature remains the radiosensitivity index (RSI), which is used to calculate a genomic adjusted radiation dose (GARD). There is an ongoing phase II prospective biomarker-led study of RSI/GARD in triple negative breast cancer. The results of these trials are eagerly anticipated over the coming years. Future work in this area should focus on (1) robust biological validation; (2) building biobanks alongside large radiotherapy randomised controlled trials with dose variance (to demonstrate an interaction between radiosensitivity signature and dose); (3) a validation of clinical-grade cost-effective assays that are deliverable within current healthcare infrastructure; and (4) an integration with biomarkers of other determinants of radiation response.

Understanding Glioblastoma Signaling, Heterogeneity, Invasiveness, and Drug Delivery Barriers

The most prevalent and aggressive type of brain cancer, namely, glioblastoma (GBM), is characterized by intra- and inter-tumor heterogeneity and strong spreading capacity, which makes treatment ineffective. A true therapeutic answer is still in its infancy despite various studies that have made significant progress toward understanding the mechanisms behind GBM recurrence and its resistance. The primary causes of GBM recurrence are attributed to the heterogeneity and diffusive nature; therefore, monitoring the tumor's heterogeneity and spreading may offer a set of therapeutic targets that could improve the clinical management of GBM and prevent tumor relapse. Additionally, the blood-brain barrier (BBB)-related poor drug delivery that prevents effective drug concentrations within the tumor is discussed. With a primary emphasis on signaling heterogeneity, tumor infiltration, and computational modeling of GBM, this review covers typical therapeutic difficulties and factors contributing to drug resistance development and discusses potential therapeutic approaches.

Roles of N6-methyladenosine (m6A) modifications in gynecologic cancers: mechanisms and therapeutic targeting

Uterine and ovarian cancers are the most common gynecologic cancers. N6−methyladenosine (m6A), an important internal RNA modification in higher eukaryotes, has recently become a hot topic in epigenetic studies. Numerous studies have revealed that the m6A-related regulatory factors regulate the occurrence and metastasis of tumors and drug resistance through various mechanisms. The m6A-related regulatory factors can also be used as therapeutic targets and biomarkers for the early diagnosis of cancers, including gynecologic cancers. This review discusses the role of m6A in gynecologic cancers and summarizes the recent advancements in m6A modification in gynecologic cancers to improve the understanding of the occurrence, diagnosis, treatment, and prognosis of gynecologic cancers.

Integrating Radiosensitivity Gene Signature Improves Glioma Outcome and Radiotherapy Response Prediction

Response to radiotherapy (RT) in gliomas varies widely between patients. It is necessary to identify glioma-associated radiosensitivity gene signatures for clinically stratifying patients who will benefit from adjuvant radiotherapy after glioma surgery. Methods: Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) glioma patient datasets were used to validate the predictive potential of two published biomarkers, the radiosensitivity index (RSI) and 31-gene signature (31-GS). To adjust these markers for the characteristics of glioma, we integrated four new glioma-associated radiosensitivity predictive indexes based on RSI and 31-GS by the Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. A receiver operating characteristic (ROC) curve, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to compare the radiosensitivity predictive ability of these six gene signatures. Subgroup analysis was used to evaluate the discriminative capacity of those gene signatures in identifying radiosensitive patients, and a nomogram was built to improve the histological grading system. Gene Ontology (GO) analysis and Gene Set Enrichment Analysis (GSEA) were used to explore related biological processes. Results: We validated and compared the predictive potential of two published predictive indexes. The AUC area of 31-GS was higher than that of RSI. Based on the RSI and 31-GS, we integrated four new glioma-associated radiosensitivity predictive indexes—PI10, PI12, PI31 and PI41. Among them, a 12-gene radiosensitivity predictive index (PI12) showed the most promising predictive performance and discriminative capacity. Examination of a nomogram created from clinical features and PI12 revealed that its predictive capacity was superior to the traditional WHO classification system. (C-index: 0.842 vs. 0.787, p ≤ 2.2 × 10⁻¹⁶) The GO analysis and GSEA showed that tumors with a high PI12 score correlated with various aspects of the malignancy of glioma. Conclusions: The glioma-associated radiosensitivity gene signature PI12 is a promising radiosensitivity predictive biomarker for guiding effective personalized radiotherapy for gliomas.

Association of the tissue infiltrated and peripheral blood immune cell subsets with response to radiotherapy for rectal cancer

Background

Tumor microenvironment plays pivotal roles in carcinogenesis, cancer development and metastasis. Composition of cancer immune cell subsets can be inferred by deconvolution of gene expression profile accurately. Compositions of the cell types in cancer microenvironment including cancer infiltrating immune and stromal cells have been reported to be associated with the cancer outcomes markers for cancer prognosis. However, rare studies have been reported on their association with the response to preoperative radiotherapy for rectal cancer.

Methods

In this paper, we deconvoluted the immune/stromal cell composition from the gene expression profiles. We compared the composition of immune/stromal cell types in the RT responsive versus nonresponsive for rectal cancer. We also compared the peripheral blood immune cell subset composition in the stable diseases versus progressive diseases of rectal cancer patients with fluorescence-activated cell sorting from our institution.

Results

Compared with the non-responsive group, the responsive group showed higher proportions of CD4⁺ T cell (0.1378 ± 0.0368 vs. 0.1071 ± 0.0373, p = 0.0215), adipocytes, T cells CD4 memory resting, and lower proportions of CD8⁺ T cell (0.1798 ± 0.0217 vs. 0.2104 ± 0.0415, p = 0.0239), macrophages M2, and preadipocytes in their cancer tissue. The responsive patients showed a higher ratio of CD4⁺/CD8⁺ T cell proportions (mean 0.7869 vs. 0.5564, p = 0.0210). Consistently, the peripheral blood dataset showed higher proportion of CD4⁺ T cells and higher ratio of CD4⁺/CD8⁺ T cells, and lower proportion of CD8⁺ T cells for favorable prognosis. We validated these results with a pooled dataset of GSE3493 and GSE35452, and more peripheral blood data, respectively. Finally, we imported these eight cell features including eosinophils and macrophage M1 to Support Vector Machines and could predict the pre-radiotherapy responsive versus non-responsive with an accuracy of 76%, ROC AUC 0.77, 95% confidential interval of 0.632–0.857, better than the gene signatures.

Conclusions

Our results showed that the proportions of tumor-infiltrating subsets and peripheral blood immune cell subsets can be important immune cell markers and treatment targets for outcomes of radiotherapy for rectal cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01252-6.

Development and validation of an immune-related gene signature for predicting the radiosensitivity of lower-grade gliomas

Radiotherapy is an important treatment modality for lower-grade gliomas (LGGs) patients. This analysis was conducted to develop an immune-related radiosensitivity gene signature to predict the survival of LGGs patients who received radiotherapy. The clinical and RNA sequencing data of LGGs were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Lasso regression analyses were used to construct a 21-gene signature to identify the LGGs patients who could benefit from radiotherapy. Based on this radiosensitivity signature, patients were classified into a radiosensitive (RS) group and a radioresistant (RR) group. According to the Kaplan–Meier analysis results of the TCGA dataset and the two CGGA validation datasets, the RS group had a higher overall survival rate than that of the RR group. This gene signature was RT-specific and an independent prognostic indicator. The nomogram model performed well in predicting 3-, and 5-year survival of LGGs patients after radiotherapy by this gene signature and other clinical factors (age, sex, grade, IDH mutations, 1p/19q codeletion). In summary, this signature is a powerful supplement to the prognostic factors of LGGs patients with radiotherapy and may provide an opportunity to incorporate individual tumor biology into clinical decision making in radiation oncology.

How to Improve SBRT Outcomes in NSCLC: From Pre-Clinical Modeling to Successful Clinical Translation

Simple Summary

Despite major research and clinical efforts, lung cancer remains the leading cause of cancer-related death. Stereotactic body radiotherapy (SBRT) has emerged as a major treatment modality for lung cancer in the last decade. Additional research is needed to elucidate underlying mechanisms of resistance and to develop improved therapeutic strategies. Clinical progress relies on accurate preclinical modelling of human disease in order to yield clinically meaningful results; however, successful translation of pre-clinical research is still lagging behind. In this review, we summarize the major clinical developments of radiation therapy for non-small-cell lung cancer (NSCLC), and we discuss the pre-clinical research models at our disposal, highlighting ongoing translational challenges and future perspectives.

Abstract

Despite major research and clinical efforts, lung cancer remains the leading cause of cancer-related death. While the delivery of conformal radiotherapy and image guidance of stereotactic body radiotherapy (SBRT) have revolutionized the treatment of early-stage non-small-cell lung cancer (NSCLC), additional research is needed to elucidate underlying mechanisms of resistance and identify novel therapeutic combinations. Clinical progress relies on the successful translation of pre-clinical work, which so far has not always yielded expected results. Improved clinical modelling involves characterizing the preclinical models and selecting appropriate experimental designs that faithfully mimic precise clinical scenarios. Here, we review the current role of SBRT and the scope of pre-clinical armamentarium at our disposal to improve successful clinical translation of pre-clinical research in the radiation oncology of NSCLC.

Current insights on extracellular vesicle-mediated glioblastoma progression: Implications in drug resistance and epithelial-mesenchymal transition

BACKGROUND

Glioblastoma multiforme (GBM) is one of the most fatal tumors of the central nervous system with high rate of disease progression, diagnosis, prognosis and low survival rate. Therapeutic approaches that relied on surgical resection and chemotherapy have been unable to curb the disease progression and subsequently leading to increase in incidences of GBM reoccurrence.

SCOPE OF THE REVIEW

In the recent times, membrane-bound extracellular vesicles (EVs) have been observed as one of the key reasons for the uncontrolled growth of GBM. EVs are shown to have the potential to contribute to the disease progression via mediating drug resistance and epithelial-mesenchymal transition. The GBM-derived EVs (GDEVs) with its cargo contents act as the biological trojan horse and lead to disease progression after being received by the recipient target cells. This review article highlights the biophysical, biochemical properties of EVs, its cargo contents and its potential role in the growth and progression of GBM by altering tumour microenvironment.

MAJOR CONCLUSIONS

EVs are being explored for serving as novel disease biomarkers in a variety of cancer types such as adenocarcinoma, pancreatic cancer, color rectal cancer, gliomas and glioblastomas. Improvement in the EV isolation protocols, polymer-based separation techniques and transcriptomics, have made EVs a key diagnostic marker to unravel the progression and early GBM diagnosis. GDEVs role in tumour progression is under extensive investigations.

GENERAL SIGNIFICANCE

Attempts have been also made to discuss and compare the usage of EVs as potential therapeutic targets versus existing therapies targeting drug resistance and EMT.

Identification of hub genes associated with EMT-induced chemoresistance in breast cancer using integrated bioinformatics analysis

Chemoresistance is one of the major challenges in the treatment of breast cancer. Recent evidence suggests that epithelial-to-mesenchymal transition (EMT) plays a critical role in not only metastasis but also in chemoresistance, hence causing tumor relapse. This study aimed to identify the hub genes associated with EMT and chemoresistance in breast cancer affecting patient/clinical survival. Commonly differentially expressed genes (DEGs) during EMT and chemoresistance in breast cancer cells were identified using publicly available datasets, GSE23655, GSE39359, GSE33146 and GSE76540. Hierarchical clustering analysis was utilized to determine the commonly DEGs expression pattern in chemoresistant (CR) breast cancer cells. GSEA revealed that EMT-related genes sets were enriched in the CR samples. Further, we found that EMT-induced breast cancer cells showed overexpression of drug efflux transporters along with resistance to chemotherapeutic drug. Pathway enrichment analysis revealed that the commonly DEGs were enriched in immunological pathways, early endosome, protein dimerization, and proteoglycans in cancer. Further, we identified eight hub genes from the protein-protein interaction (PPI) network. We validated the gene expression levels of the hub genes among TCGA breast cancer samples using UALCAN. Survival analysis for the hub genes was performed using KM plotter, which showed a worse relapse-free survival (RFS) of the hub genes among breast cancer patients. In conclusion, this study identified eight hub genes that play an important role in the pathways underlying EMT-induced chemoresistance in breast cancer and can be used as therapeutic targets after clinical validation.

RadSigBench: a framework for benchmarking functional genomics signatures of cancer cell radiosensitivity

Multiple transcriptomic predictors of tumour cell radiosensitivity (RS) have been proposed, but they have not been benchmarked against one another or to control models. To address this, we present RadSigBench, a comprehensive benchmarking framework for RS signatures. The approach compares candidate models to those developed from randomly resampled control signatures and from cellular processes integral to the radiation response. Robust evaluation of signature accuracy, both overall and for individual tissues, is performed. The NCI60 and Cancer Cell Line Encyclopaedia datasets are integrated into our workflow. Prediction of two measures of RS is assessed: survival fraction after 2 Gy and mean inactivation dose. We apply the RadSigBench framework to seven prominent published signatures of radiation sensitivity and test for equivalence to control signatures. The mean out-of-sample R² for the published models on test data was very poor at 0.01 (range: −0.05 to 0.09) for Cancer Cell Line Encyclopedia and 0.00 (range: −0.19 to 0.19) in the NCI60 data. The accuracy of both published and cellular process signatures investigated was equivalent to the resampled controls, suggesting that these signatures contain limited radiation-specific information. Enhanced modelling strategies are needed for effective prediction of intrinsic RS to inform clinical treatment regimes. We make recommendations for methodological improvements, for example the inclusion of perturbation data, multiomics, advanced machine learning and mechanistic modelling. Our validation framework provides for robust performance assessment of ongoing developments in intrinsic RS prediction.

Developing ZNF Gene Signatures Predicting Radiosensitivity of Patients with Breast Cancer

Adjuvant radiotherapy is one of the main treatment methods for breast cancer, but its clinical benefit depends largely on the characteristics of the patient. This study aimed to explore the relationship between the expression of zinc finger (ZNF) gene family proteins and the radiosensitivity of breast cancer patients. Clinical and gene expression data on a total of 976 breast cancer samples were obtained from The Cancer Genome Atlas (TCGA) database. ZNF gene expression was dichotomized into groups with a higher or lower level than the median level of expression. Univariate and multivariate Cox regression analyses were used to evaluate the relationship between ZNF gene expression levels and radiosensitivity. The Molecular Taxonomy Data of the International Federation of Breast Cancer (METABRIC) database was used for validation. The results revealed that 4 ZNF genes were possible radiosensitivity markers. High expression of ZNF644 and low expression levels of the other 3 genes (ZNF341, ZNF541, and ZNF653) were related to the radiosensitivity of breast cancer. Hierarchical cluster, Cox, and CoxBoost analysis based on these 4 ZNF genes indicated that patients with a favorable 4-gene signature had better overall survival on radiotherapy. Thus, this 4-gene signature may have value for selecting those patients most likely to benefit from radiotherapy. ZNF gene clusters could act as radiosensitivity signatures for breast cancer patients and may be involved in determining the radiosensitivity of cancer.

Establishment of a nomogram with EMP3 for predicting clinical outcomes in patients with glioma: A bi-center study

Aim

To demonstrate the clinical value of epithelial membrane protein 3 (EMP3) with bioinformatic analysis and clinical data, and then to establish a practical nomogram predictive model with bicenter validation.

Methods

The data from CGGA and TCGA database were used to analyze the expression of EMP3 and its correlation with clinical prognosis. Then, we analyzed EMP3 expression in samples from 179 glioma patients from 2013 to 2017. Univariate and multivariate cox regression were used to predict the prognosis with multiple factors. Finally, a nomogram to predict poor outcomes was formulated. The accuracy and discrimination of nomograms were determined with ROC curve and calibration curve in training and validation cohorts.

Results

EMP3 was significantly higher in higher‐grade glioma and predicted poor prognosis. In multivariate analysis, high expression of EMP3 (HR = 2.842, 95% CI 1.984–4.071), WHO grade (HR = 1.991, 95% CI 1.235–3.212), and IDH1 mutant (HR = 0.503, 95% CI 0.344–0.737) were included. The nomogram was constructed based on the above features, which represented great predictive value in clinical outcomes.

Conclusion

This study demonstrated EMP3 as a novel predictor for clinical progression and clinical outcomes in glioma. Moreover, the nomogram with EMP3 expression represented a practical approach to provide individualized risk assessment for glioma patients.

More evidence for prediction model of radiosensitivity

With the development of precision medicine, searching for potential biomarkers plays a major role in personalized medicine. Therefore, how to predict radiosensitivity to improve radiotherapy is a burning question. The definition of radiosensitivity is complex. Radiosensitive gene/biomarker can be useful for predicting which patients would benefit from radiotherapy. The discovery of radiosensitivity biomarkers require multiple pieces of evidence. A prediction model of breast cancer radiosensitivity based on six genes was established. We had put forward some supplements on the basis of the present study. We found that there were no differences between high- and low-risk scores in the non-radiotherapy group. Patients who received radiotherapy had a significantly better overall survival than non-radiotherapy patients in the predicted low-risk score patients. Furthermore, there was no difference between radiotherapy group and non-radiotherapy group in the high-risk score group. Those results firmly supported the prediction model of radiosensitivity. In addition, building a radiosensitivity prediction model was systematically discussed. Genes of model could be screened by different methods, such as Cox regression analysis, Lasso Cox regression method, random forest algorithm and other methods. In the future, precision radiotherapy might depend on the combination of multi-omics data and high dimensional image data.

Developing Tumor Radiosensitivity Signatures Using LncRNAs

Long non-coding RNAs (lncRNAs) are involved in diverse biological processes, including DNA damage repair, and are of interest as potential biomarkers of radiosensitivity. We investigated whether lncRNA radiosensitivity signatures could be derived for use in cancer patients treated with radiotherapy. Signature development involved radiosensitivity measurements for cell lines and primary tumor samples, and patient outcome after radiotherapy. A 10-lncRNA signature trained on radiosensitivity measurements in bladder cell lines showed a trend towards independent validation. In multivariable analyses, patients with tumors classified as radioresistant by the lncRNA signature had poorer local relapse-free survival (P = 0.065) in 151 patients with muscle-invasive bladder cancer who underwent radiotherapy. An mRNA-based radiosensitivity index signature performed similarly to the lncRNA bladder signature for local relapse-free survival (P = 0.055). Pathway analysis showed the lncRNA signature associated with molecular processes involved in radiation responses. Knockdown of one of the lncRNAs in the signature showed a modest increase in radiosensitivity in one cell line. An alternative approach involved training on primary cervical tumor radiosensitivity or local control after radiotherapy. Both approaches failed to generate a cervix lncRNA radiosensitivity signature, which was attributed to the age of samples in our cohorts. Our work highlights challenges in validating lncRNA signatures as biomarkers in archival tissue from radiotherapy cohorts, but supports continued investigation of lncRNAs for a role in radiosensitivity.

Elevated Asparagine Biosynthesis Drives Brain Tumor Stem Cell Metabolic Plasticity and Resistance to Oxidative Stress

Asparagine synthetase (ASNS) is a gene on the long arm of chromosome 7 that is copy-number amplified in the majority of glioblastomas. ASNS copy-number amplification is associated with a significantly decreased survival. Using patient-derived glioma stem cells (GSC), we showed that significant metabolic alterations occur in gliomas when perturbing the expression of ASNS, which is not merely restricted to amino acid homeostasis. ASNS-high GSCs maintained a slower basal metabolic profile yet readily shifted to a greatly increased capacity for glycolysis and oxidative phosphorylation when needed. This led ASNS-high cells to a greater ability to proliferate and spread into brain tissue. Finally, we demonstrate that these changes confer resistance to cellular stress, notably oxidative stress, through adaptive redox homeostasis that led to radiotherapy resistance. Furthermore, ASNS overexpression led to modifications of the one-carbon metabolism to promote a more antioxidant tumor environment revealing a metabolic vulnerability that may be therapeutically exploited. IMPLICATIONS: This study reveals a new role for ASNS in metabolic control and redox homeostasis in glioma stem cells and proposes a new treatment strategy that attempts to exploit one vulnerable metabolic node within the larger multilayered tumor network.

Prognostic and predictive value of FCER1G in glioma outcomes and response to immunotherapy

PURPOSE

Glioma is the most prevalent malignant form of brain tumors, with a dismal prognosis. Currently, cancer immunotherapy has emerged as a revolutionary treatment for patients with advanced highly aggressive therapy-resistant tumors. However, there is no effective biomarker to reflect the response to immunotherapy in glioma patient so far. So we aim to assess the clinical predictive value of FCER1G in patients with glioma.

METHODS

The expression level and correlation between clinical prognosis and FER1G levels were analyzed with the data from CGGA, TCGA, and GEO database. Univariate and multivariate cox regression model was built to predict the prognosis of glioma patients with multiple factors. Then the correlation between FCER1G with immune cell infiltration and activation was analyzed. At last, we predict the immunotherapeutic response in both high and low FCER1G expression subgroups.

RESULTS

FCER1G was significantly higher in glioma with greater malignancy and predicted poor prognosis. In multivariate analysis, the hazard ratio of FCER1G expression (Low versus High) was 0.66 and 95 % CI is 0.54 to 0.79 (P < 0.001), whereas age (HR = 1.26, 95 % CI  1.04-1.52), grade (HR = 2.75, 95 % CI 2.06-3.68), tumor recurrence (HR = 2.17, 95 % CI  1.81-2.62), IDH mutant (HR = 2.46, 95 % CI 1.97-3.01) and chemotherapeutic status (HR = 1.4, 95 % CI  1.20-1.80) are also included. Furthermore, we illustrated that gene FCER1G stratified glioma cases into high and low FCER1G expression subgroups that demonstrated with distinct clinical outcomes and T cell activation. At last, we demonstrated that high FCER1G levels presented great immunotherapeutic response in glioma patients.

CONCLUSIONS

This study demonstrated FCER1G as a novel predictor for clinical diagnosis, prognosis, and response to immunotherapy in glioma patient. Assess expression of FCER1G is a promising method to discover patients that may benefit from immunotherapy.

Machine Learning Based on a Multiparametric and Multiregional Radiomics Signature Predicts Radiotherapeutic Response in Patients with Glioblastoma

Methods

The MRI images, genetic data, and clinical data of 152 patients with GBM were analyzed. 122 patients from the TCIA dataset (training set: n = 82; validation set: n = 40) and 30 patients from local hospitals were used as an independent test dataset. Radiomics features were extracted from multiple regions of multiparameter MRI. Kaplan-Meier survival analysis was used to verify the ability of the imaging signature to predict the response of GBM patients to radiotherapy before an operation. Multivariate Cox regression including radiomics signature and preoperative clinical risk factors was used to further improve the ability to predict the overall survival (OS) of individual GBM patients, which was presented in the form of a nomogram.

Results

The radiomics signature was built by eight selected features. The C-index of the radiomics signature in the TCIA and independent test cohorts was 0.703 (P < 0.001) and 0.757 (P = 0.001), respectively. Multivariate Cox regression analysis confirmed that the radiomics signature (HR: 0.290, P < 0.001), age (HR: 1.023, P = 0.01), and KPS (HR: 0.968, P < 0.001) were independent risk factors for OS in GBM patients before surgery. When the radiomics signature and preoperative clinical risk factors were combined, the radiomics nomogram further improved the performance of OS prediction in individual patients (C‐index = 0.764 and 0.758 in the TCIA and test cohorts, respectively).

Conclusion

This study developed a radiomics signature that can predict the response of individual GBM patients to radiotherapy and may be a new supplement for precise GBM radiotherapy.

A Radiosensitivity Gene Signature and XPO1 Predict Clinical Outcomes for Glioma Patients

Objective: Glioma is the most common and fatal primary brain tumor that has a high risk of recurrence in adults. Identification of predictive biomarkers is necessary to optimize therapeutic strategies. This study investigated the predictive efficacy of a previously identified radiosensitivity signature as well as Exportin 1 (XPO1) expression levels.

Methods: A total of 1,552 patients diagnosed with glioma were analyzed using the Chinese Glioma Genome Atlas and The Cancer Genome Atlas databases. The radiosensitive and radioresistant groups were identified based on a radiosensitivity signature. Patients were also stratified into XPO1-high and XPO1-low groups based on XPO1 mRNA expression levels. Overall survival rates were compared across patient groups. Differential gene expression was detected and analyzed through pathway enrichment and Gene Set Enrichment Analysis (GSEA). To predict 1-, 3-, and 5-years survival rates for glioma patients, a nomogram was established combining the radiosensitivity gene signature, XPO1 status, and clinical characteristics. An artificial intelligence clustering system and a survival prediction system of glioma were developed to predict individual risk.

Results: This proposed classification based on a radiosensitivity gene signature and XPO1 expression levels provides an independent prognostic factor for glioma. The RR-XPO1-high group shows a poor prognosis and may benefit most from radiotherapy-combined anti-XPO1 treatment. The nomogram based on the radiosensitivity gene signature, XPO1 expression, and clinical characteristics performs more optimally compared to the WHO classification and IDH status in predicting survival rates for glioma patients. The online clustering and prediction systems make it accessible to predict risk and optimize treatment for a special patient. The cell cycle, p53, and focal adhesion pathways are associated with more invasive glioma cases.

Conclusion: Combining the radiosensitivity signature and XPO1 expression is a favorable approach to predict outcomes as well as determine optimal therapeutic strategies for glioma patients.

Association between breast cancer cell migration and radiosensitivity in vitro

The aim of the present study was to examine the association between the migration of breast cancer cells in vitro and radiosensitivity by establishing a breast cancer cell model with different migratory capacities. Transwell chambers in a 24-well plate were used to separate MDA-MB-231 and ZR-7530 cells and to establish cell models with different migratory capacities. Subsequently, the radiosensitivity of the cell models was measured using a radiation clone formation assay. Furthermore, differential gene expression was determined using gene microarray analysis. The protein expression levels of the differentially expressed genes (DEGs) were assessed using western blot analysis. From each parental cell line, a pair of daughter cell lines were established in with differing migratory abilities. These daughter cell lines were named MDA-MB-231 UP-10 (231 UP-10), MDA-MB-231 Down-10 (231 Down-10), ZR-75-30 UP-10 (7530 UP-10) and ZR-75-30 Down-10 (7530 Down-10). Radiation clone formation assays revealed that the cell lines with increased migratory abilities (231 Down-10 and 7530 Down-10) demonstrated higher radio-resistance compared with the cell lines with decreased migratory abilities (231 UP-10 and 7530 UP-10). Gene microarrays identified numerous DEGs between the pairs of UP and Down cell lines. A focus was placed on genes associated with cell adhesion and it was identified that phosphorylated Fak and phosphorylated EGFR expression levels were increased in 231 Down-10 and 7530 Down-10 cells, compared with the 231 UP-10 and 7530 UP-10 cells. Other genes including ZO-1, FN1 and SOX9 expression were also increased in the 231 Down-10 and 7530 Down-10 cells compared with 231 UP-10 and 7530 UP-10 cells. Cell lines with increased migratory capacities may be more radio-resistant compared with cell lines with a decreased migratory capabilities. The mechanism may be associated with changes in the expression of cell adhesion molecules and epithelial-mesenchymal transition (EMT). Therapeutic strategies targeting cell adhesion or EMT may increase the radiation sensitivity of breast cancer cells, in addition to improving the effect of radiation therapy.

Proton Therapy and Src Family Kinase Inhibitor Combined Treatments on U87 Human Glioblastoma Multiforme Cell Line

Glioblastoma Multiforme (GBM) is the most common of malignant gliomas in adults with an exiguous life expectancy. Standard treatments are not curative and the resistance to both chemotherapy and conventional radiotherapy (RT) plans is the main cause of GBM care failures. Proton therapy (PT) shows a ballistic precision and a higher dose conformity than conventional RT. In this study we investigated the radiosensitive effects of a new targeted compound, SRC inhibitor, named Si306, in combination with PT on the U87 glioblastoma cell line. Clonogenic survival assay, dose modifying factor calculation and linear-quadratic model were performed to evaluate radiosensitizing effects mediated by combination of the Si306 with PT. Gene expression profiling by microarray was also conducted after PT treatments alone or combined, to identify gene signatures as biomarkers of response to treatments. Our results indicate that the Si306 compound exhibits a radiosensitizing action on the U87 cells causing a synergic cytotoxic effect with PT. In addition, microarray data confirm the SRC role as the main Si306 target and highlights new genes modulated by the combined action of Si306 and PT. We suggest, the Si306 as a new candidate to treat GBM in combination with PT, overcoming resistance to conventional treatments.

A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening

Accurate patient-derived models of cancer are needed for profiling the disease and for testing therapeutics. These models must not only be accurate, but also suitable for high-throughput screening and analysis. Here we compare two derivative cancer models, microtumors and spheroids, to the gold standard model of patient-derived orthotopic xenografts (PDX) in glioblastoma multiforme (GBM). To compare these models, we constructed a custom NanoString panel of 350 genes relevant to GBM biology. This custom assay includes 16 GBM-specific gene signatures including a novel GBM subtyping signature. We profiled 11 GBM-PDX with matched orthotopic cells, derived microtumors, and derived spheroids using the custom NanoString assay. In parallel, these derivative models underwent drug sensitivity screening. We found that expression of certain genes were dependent on the cancer model while others were model-independent. These model-independent genes can be used in profiling tumor-specific biology and in gauging therapeutic response. It remains to be seen whether or not cancer model-specific genes may be directly or indirectly, through changes to tumor microenvironment, manipulated to improve the concordance of in vitro derivative models with in vivo models yielding better prediction of therapeutic response.

EMT Regulation by Autophagy: A New Perspective in Glioblastoma Biology

Epithelial-to-mesenchymal transition (EMT) and its reverse process MET naturally occur during development and in tissue repair in vertebrates. EMT is also recognized as the crucial event by which cancer cells acquire an invasive phenotype through the activation of specific transcription factors and signalling pathways. Even though glial cells have a mesenchymal phenotype, an EMT-like process tends to exacerbate it during gliomagenesis and progression to more aggressive stages of the disease. Autophagy is an evolutionary conserved degradative process that cells use in order to maintain a proper homeostasis, and defects in autophagy have been associated to several pathologies including cancer. Besides modulating cell resistance or sensitivity to therapy, autophagy also affects the migration and invasion capabilities of tumor cells. Despite this evidence, few papers are present in literature about the involvement of autophagy in EMT-like processes in glioblastoma (GBM) so far. This review summarizes the current understanding of the interplay between autophagy and EMT in cancer, with special regard to GBM model. As the invasive behaviour is a hallmark of GBM aggressiveness, defining a new link between autophagy and EMT can open a novel scenario for targeting these processes in future therapeutical approaches.

PD-1 and PD-L1 Expression Predicts Radiosensitivity and Clinical Outcomes in Head and Neck Cancer and is Associated with HPV Infection

Objectives: PD-1 and PD-L1 overexpression in malignant tumors in response to radiotherapy is correlated with a poor prognosis. Human papilloma virus (HPV) infection impacts intrinsic radiosensitivity of head and neck cancers (HNCs). Herein, this study aims to determine PD-1/PD-L1 expression differences in tumors with different HPV statuses and their prognostic value in patients with different radiosensitivity gene signatures to define the characteristics of patients who will benefit from radiotherapy combined with anti-PD-1/PD-L1 therapy. Material and methods: According to the identified gene signature related to radiosensitivity, 517 patients from the TCGA HNSCC cohort were selected and divided into the radioresistant (RR) group and radiosensitive (RS) group using a K-mean clustering algorithm. All data analyses were conducted using SPSS and GraphPad Prism. Results: PD-L1 expression is upregulated in tumor tissue (unpaired t test, P=0.0363; paired t test, P=0.0584) compared with normal tissue. PD-L1 was positively correlated with PD-1 expression (P<0.0001). The HPV/p16-positive group was significantly high PD-1 expression (P<0.0001). PD-L1 expression (P=0.0005) and PD-1 expression (P<0.0001) were significantly increased in the RS group compared with that in the RR group. In the patients who were treated with radiotherapy, the PD-1-high group was associated with better recurrence-free survival (RFS) (HR, 0.4892; 95% CI, 0.2357-1.015; P=0.023). Within the RR group, high PD-L1 expression was associated with reduced overall survival (OS) (HR, 2.196; 95% CI, 1.081-4.46; P=0.0108) compared with low PD-L1 expression. In the RR group, HPV/p16-negative patients with high PD-L1 expression exhibited reduced OS (HPV: HR, 2.334; 95% CI, 0.7828-6.961; P=0.0313; p16: HR,2.486; 95% CI, 0.8559-7.219; P=0.0192) compared with that of patients with low PD-L1 expression. In the PD-L1-high group, RR patients exhibited reduced OS (HR, 0.4858; 95% CI, 0.2136-1.105; P=0.0189) and RFS (HR, 0.4371; 95% CI, 0.1421-1.345; P=0.0231) compared with that of RS patients. Conclusion: Our findings demonstrated that high PD-1/PD-L1 expression was strongly related to radiosensitivity, and high PD-1 expression was significantly associated with HPV/p16-positive HNCs. Patients in the radioresistant group and patients in the HPV/p16-negative group with a radioresistant gene signature could benefit from the combination of radiotherapy and anti-PD-1/PD-L1 therapy.

Developing Predictive or Prognostic Biomarkers for Charged Particle Radiotherapy

The response to radiotherapy can vary greatly among individuals, even though advances in technology allow for the highly localized placement of therapeutic doses of radiation to a tumor. This variability in patient response to radiation is biologically driven, but the individuality of tumor and healthy tissue biology are not used to create individual treatment plans. Biomarkers of radiosensitivity, whether intrinsic or from hypoxia, would move radiation oncology from precision medicine to precise, personalized medicine. Charged particle radiotherapy allows for even greater dose conformity, but the biological advantages of charged particle radiotherapy have not yet been cultivated. The development of biomarkers that would drive biologically based clinical trials, identify patients for whom charged particles are most appropriate, or aid in particle-selection strategies could be envisioned with appropriate biomarkers. Initially, biomarkers for low-linear energy transfer (LET) radiation responses should be tested against charged particles. Biomarkers of tumor radioresistance to low-LET radiations could be used to identify patients for whom the enhanced relative biological effectiveness (RBE) of charged particles would be more effective compared with low-LET radiations and those for whom specific DNA-repair inhibitors, in combination with charged particles, may also be appropriate. Furthermore, heavy charged particles can overcome the radioresistance of hypoxic tumors when used at the appropriate LET. Biomarkers for hypoxia could identify hypoxic tumors and, in combination with imaging, define hypoxic regions of a tumor for specific ion selection. Moreover, because of the enhanced RBE for charged particles, the risk for adverse healthy tissue effects may be greater, even though charged particles have greater tumor conformality. There are many validated healthy-tissue biomarkers available to test against charged particle exposures. Lastly, newer biological techniques, as well as newer bioinformatic and computational methods, are rapidly changing the landscape for biomarker identification, validation, and clinical trial design.

TPD52L2 impacts proliferation, invasiveness and apoptosis of glioblastoma cells via modulation of wnt/β-catenin/snail signaling

Intratumoral heterogeneity greatly hinders efficiency of target therapy in glioblastoma (GBM). To decipher the underlying mechanisms of heterogeneity, patient-derived adult GBM cells were separately isolated from margins of T1 gadolinium enhancing tumor lesions (PNCs) and T1 gadolinium enhancing core lesions (ECs). Single clone culture was conducted in ECs and U87MG cell line to screen clones with distinct biological phenotypes. Single cell clones with diverse phenotypes were simultaneously separated from ECs and U87 cell line. PNCs, GCs(H) and U87(H) exhibited longer cellular protrusion than ECs, GCs(L) and U87(L), respectively. Cell strains with longer protrusion exhibited higher invasive ability and lower sensitivity to temozolomide (TMZ) and radiation. Subsequently, TPD52L2 was verified as the functional protein to regulate the cellular heterogeneity by the proteomics analysis. Downregulation of TPD52L2 enhanced cell invasion whereas inhibited cell proliferation rate and sensitivity to chemotherapy in vivo and in vitro, this condition was reversed when TPD52L2 was overexpressed. The invasiveness was facilitated by up-regulating CTNNB1/β-catenin and SNAI1/Snail mediated EMT process. In addition, the clinical data of 88 GBM cases in our neurosurgery center was analyzed to reveal the influence of TPD52L2 in the prognosis of GBM. Low expression of TPD52L2 exacerbated prognosis of GBM patients received standard radiotherapy plus concomitant and adjuvant TMZ (Stupp strategy). Taken together, TPD52L2 is an important biomarker influencing GBM prognosis.

Emerging biomarkers for the combination of radiotherapy and immune checkpoint blockers

Over the past few years, multiple immune checkpoint blockers (ICBs) have achieved unprecedented clinical success and have been approved by regulatory agencies for the treatment of an increasing number of malignancies. However, only a limited fraction of patients responds to ICBs employed as a standalone intervention, calling for the development of combinatorial regimens. Radiation therapy (RT) stands out as a very promising candidate for this purpose. Indeed, RT mediates antineoplastic effects not only by cytotoxic and cytostatic mechanisms, but also by modulating immunological functions, both locally (within the irradiated field) and systemically. As combinatorial regimens involving RT and ICBs are being developed and clinically tested at an accelerating pace, it is paramount to identify biomarkers that reliably predict the likelihood of individual patients to respond. Here, we discuss emerging biomarkers that may potentially predict the response of cancer patients to RT plus ICBs.

Blocking MIR155HG/miR-155 axis inhibits mesenchymal transition in glioma

Background

MIR155 host gene (MIR155HG) is a long noncoding RNA that has been considered as the primary micro (mi)RNA of miR-155. MIR155HG plays an essential role in hematopoiesis, inflammation, and tumorigenesis. Our study investigated the clinical significance, biological function, mechanisms, and small-molecule inhibitors of the MIR155HG/miR-155 axis in glioma.

Methods

We analyzed the expression of the MIR155HG/miR-155 axis and the correlation with glioma grade and patient survival using 2 different glioma gene expression datasets. Biological significance was elucidated through a series of in vitro and in vivo experiments. Furthermore, we conducted a high-throughput screening for small molecules to identify a potential inhibitor of the MIR155HG/miR-155 axis.

Results

Increased MIR155HG was associated with glioma grade, mesenchymal transition, and poor prognosis. Functionally, MIR155HG reduction by small interfering RNA inhibited cell proliferation, migration, invasion, and orthotopic glioma growth by repressing the generation of its derivatives miR-155-5p and miR-155-3p. Bioinformatics and luciferase reporter assays revealed that protocadherin 9 and protocadherin 7, which act as tumor suppressors by inhibiting the Wnt/β-catenin pathway, were direct targets of miR-155-5p and miR-155-3p, respectively. Finally, we identified NSC141562 as a potent small-molecule inhibitor of the MIR155HG/miR-155 axis.

Conclusions

Our results demonstrate that the MIR155HG/miR-155 axis plays a critical role in facilitating glioma progression and serves as a prognostic factor for patient survival in glioblastoma. High-throughput screening indicated that the MIR155HG/miR-155 axis inhibitor NSC141562 may be a useful candidate anti-glioma drug.

Circadian regulator NR1D2 regulates glioblastoma cell proliferation and motility

Nuclear receptor NR1D2 is originally characterized as the repressor of genes involved in circadian rhythm. Recently, it is documented that NR1D2 is overexpressed in various cancers. However, the pathways and biological functions that NR1D2 involved in cancers remain poorly understood. Here, we reported that NR1D2 was abundant in human glioblastoma (GBM) tissue and cell lines but not primary human astrocytes. Silencing of NR1D2 changed the morphology of GBM cells, inhibited cell proliferation and motility, whereas had no effects on apoptosis. Importantly, based on RNA-seq and ChIP assay, we identified receptor tyrosine kinase AXL as a new transcriptional target of NR1D2 in GBM cells. AXL mediated partially the regulatory effects of NR1D2 on PI3K/AKT axis and promoted proliferation, migration, and invasion of GBM cells. Besides, NR1D2 knockdown remarkably impaired the maturation of focal adhesion and assembly of F-actin, along with downregulated p-FAK, and proteins involved in actin nucleation and polymerization (p-Rac1/Cdc42, WAVE and PFN2). Moreover, NR1D2 had more targets other than AXL to regulate epithelial-to-mesenchymal transition and cell motility in GBM cells. Altogether, our findings uncover a GBM-promoting role of NR1D2 and provide the rationale for targeting NR1D2 as a potential therapeutic approach.

A radiosensitivity gene signature and PD-L1 predict the clinical outcomes of patients with lower grade glioma in TCGA

PURPOSE

Identifying predictive factors for the clinical outcome of patients with lower grade gliomas following radiotherapy could help optimize patient treatments. Here, we investigate the predictive efficacy of both a previously identified "31-gene signature" and programmed death ligand-1 (PD-L1) expression.

MATERIAL AND METHODS

We identified 511 patients with lower grade glioma (Grade 2 and 3) in The Cancer Genome Atlas dataset and divided them into two clusters: radiosensitive (RS) and radioresistant (RR). Patients were also classified as PD-L1-high or PD-L1-low based on CD274 mRNA expression. Five-year survival rates were compared across patient groups, and differentially expressed genes were identified via a gene enrichment analysis.

RESULTS

Among 511 patients with lower grade glioma in The Cancer Genome Atlas dataset, we identified a group that was characterized by radioresistant and high PD-L1 (the PD-L1-high-RR group). Multivariate Cox models demonstrated that the membership in the PD-L1-high-RR can predict overall survival regarding to RT. Differentially expressed genes associated with the PD-L1-high-RR group were found to play a role in the immune response, including the T-cell receptor signaling pathway.

CONCLUSION

We tested the predictive value of a "31-gene signature" and PD-L1 expression status in a dataset of patients with lower grade glioma. Our results suggest that the patient population classified as the PD-L1-high-RR may benefit most from radiotherapy combined with anti-PD-1/PD-L1 treatment. Prospective clinical trial is necessary to validate the findings in a homogenous treated patient cohort.

Mesenchymal stem cells enhance tumorigenic properties of human glioblastoma through independent cell-cell communication mechanisms

Mesenchymal stem cells (MSC) display tumor tropism and have been addressed as vehicles for delivery of anti-cancer agents. As cellular components of the tumor microenvironment, MSC also influence tumor progression. However, the contribution of MSC in brain cancer is not well understood since either oncogenic or tumor suppressor effects have been reported for these cells. Here, MSC were found capable of stimulating human Glioblastoma (GBM) cell proliferation through a paracrine effect mediated by TGFB1. Moreover, when in direct cell-cell contact with GBM cells, MSC elicited an increased proliferative and invasive tumor cell behavior under 3D conditions, as well as accelerated tumor development in nude mice, independently of paracrine TGFB1. A secretome profiling of MSC-GBM co-cultures identified 126 differentially expressed proteins and 10 proteins exclusively detected under direct cell-cell contact conditions. Most of these proteins are exosome cargos and are involved in cell motility and tissue development. These results indicate a dynamic interaction between MSC and GBM cells, favoring aggressive tumor cell traits through alternative and independent mechanisms. Overall, these findings indicate that MSC may exert pro-tumorigenic effects when in close contact with tumor cells, which must be carefully considered when employing MSC in targeted cell therapy protocols against cancer.

Developmentally regulated signaling pathways in glioma invasion

Malignant gliomas are the most common, infiltrative, and lethal primary brain tumors affecting the adult population. The grim prognosis for this disease is due to a combination of the presence of highly invasive tumor cells that escape surgical resection and the presence of a population of therapy-resistant cancer stem cells found within these tumors. Several studies suggest that glioma cells have cleverly hijacked the normal developmental program of neural progenitor cells, including their transcriptional programs, to enhance gliomagenesis. In this review, we summarize the role of developmentally regulated signaling pathways that have been found to facilitate glioma growth and invasion. Furthermore, we discuss how the microenvironment and treatment-induced perturbations of these highly interconnected signaling networks can trigger a shift in cellular phenotype and tumor subtype.

FTO regulates the chemo-radiotherapy resistance of cervical squamous cell carcinoma (CSCC) by targeting β-catenin through mRNA demethylation

The role of N⁶ -methyladenosine (m⁶ A) demethylase fat mass and obesity-associated protein (FTO) in the regulation of chemo-radiotherapy resistance remains largely unknown. Here, we show that the mRNA level of FTO is elevated in cervical squamous cell carcinoma (CSCC) tissues when compared with respective adjacent normal tissues. FTO enhances the chemo-radiotherapy resistance both in vitro and in vivo through regulating expression of β-catenin by reducing m⁶ A levels in its mRNA transcripts and in turn increases excision repair cross-complementation group 1 (ERCC1) activity. Clinically, the prognostic value of FTO for overall survival is found to be dependent on β-catenin expression in human CSCC samples. Taken together, these findings uncover a critical function for FTO and its substrate m⁶ A in the regulation of chemo-radiotherapy resistance, which may bear potential clinical implications for CSCC treatment.

Actin-capping protein CapG is associated with prognosis, proliferation and metastasis in human glioma

Glioma is the most aggressive and malignant primary brain tumor in adults. In the present study, we identified a vital oncoprotein, capping actin protein, gelsolin-like (CapG), and investigated its roles in the prognosis, proliferation and metastasis in glioma. The mRNA and protein levels of CapG were significantly increased in human glioma, and higher CapG expression was an independent prognostic factor for predicting unfavorable prognosis. The expression level of CapG was found to be associated with several common molecular features of glioblastoma (GBM; WHO grade IV glioma) in The Cancer Genome Atlas (TCGA) cohort. When analyzing the prognosis of GBM patients according to these molecular features, we observed that the prognostic value of CapG was affected by amplification of CDK6 or EGFR. However, overexpression of CapG markedly promoted cell growth in vitro, while depletion of CapG significantly inhibited cell proliferation by blocking the cell cycle in G1/S transition. Moreover, CapG manipulation in glioma cell lines U87 and U251 showed CapG-dependent cellular migration and invasiveness. These data suggest that CapG may serve as a prognostic biomarker with potentially important therapeutic implications for glioma.

Development of a prediction model for radiosensitivity using the expression values of genes and long non-coding RNAs

Radiotherapy has become a popular and standard approach for treating cancer patients because it greatly improves patient survival. However, some of the patients receiving radiotherapy suffer from adverse effects and do not obtain survival benefits. This may be attributed to the fact that most radiation treatment plans are designed based on cancer type, without consideration of each individual's radiosensitivity. A model for predicting radiosensitivity would help to address this issue. In this study, the expression levels of both genes and long non-coding RNAs (lncRNAs) were used to build such a prediction model. Analysis of variance and Tukey's honest significant difference tests (P < 0.001) were utilized in immortalized B cells (GSE26835) to identify differentially expressed genes and lncRNAs after irradiation. A total of 41 genes and lncRNAs associated with radiation exposure were revealed by a network analysis algorithm. To develop a predictive model for radiosensitivity, the expression profiles of NCI-60 cell lines along, with their radiation parameters, were analyzed. A genetic algorithm was proposed to identify 20 predictors, and the support vector machine algorithm was used to evaluate their prediction performance. The model was applied to 2 datasets of glioblastoma, The Cancer Genome Atlas and GSE16011, and significantly better survival was observed in patients with greater predicted radiosensitivity.

MicroRNA-200c increases radiosensitivity of human cancer cells with activated EGFR-associated signaling

MicroRNA-200c (miR-200c) recently was found to have tumor-suppressive properties by inhibiting the epithelial-mesenchymal transition (EMT) in several cancers. miR-200c also interacts with various cellular signaling molecules and regulates many important signaling pathways. In this study, we investigated the radiosensitizing effect of miR-200c and its mechanism in a panel of human cancer cell lines. Malignant glioma (U251, T98G), breast cancer (MDA-MB-468), and lung carcinoma (A549) cells were transfected with control pre-microRNA, pre-miR-200c, or anti-miR-200c. Then, RT-PCR, clonogenic assays, immunoblotting, and immunocytochemisty were performed. To predict the potential targets of miR-200c, microRNA databases were used for bioinformatics analysis. Ectopic overexpression of miR-200c downregulated p-EGFR and p-AKT and increased the radiosensitivity of U251, T98G, A549, and MDA-MB-468 cells. In contrast, miR-200c inhibition upregulated p-EGFR and p-AKT, and decreased radiation-induced cell killing. miR-200c led to persistent γH2AX focus formation and downregulated pDNA-PKc expression. Autophagy and apoptosis were major modes of cell death. Bioinformatics analysis predicted that miR-200c may be associated with EGFR, AKT2, MAPK1, VEGFA, and HIF1AN. We also confirmed that miR-200c downregulated the expression of VEGF, HIF-1α, and MMP2 in U251 and A549 cells. In these cells, overexpressing miR-200c inhibited invasion, migration, and vascular tube formation. These phenotypic changes were associated with E-cadherin and EphA2 downregulation and N-cadherin upregulation. miR-200c showed no observable cytotoxic effect on normal human fibroblasts and astrocytes. Taken together, our data suggest that miR-200c is an attractive target for improving the efficacy of radiotherapy via a unique modulation of the complex regulatory network controlling cancer pro-survival signaling and EMT.

EMT- and MET-related processes in nonepithelial tumors: importance for disease progression, prognosis, and therapeutic opportunities

The epithelial-to mesenchymal (EMT) process is increasingly recognized for playing a key role in the progression, dissemination, and therapy resistance of epithelial tumors. Accumulating evidence suggests that EMT inducers also lead to a gain in mesenchymal properties and promote malignancy of nonepithelial tumors. In this review, we present and discuss current findings, illustrating the importance of EMT inducers in tumors originating from nonepithelial/mesenchymal tissues, including brain tumors, hematopoietic malignancies, and sarcomas. Among these tumors, the involvement of mesenchymal transition has been most extensively investigated in glioblastoma, providing proof for cell autonomous and microenvironment-derived stimuli that provoke EMT-like processes that regulate stem cell, invasive, and immunogenic properties as well as therapy resistance. The involvement of prominent EMT transcription factor families, such as TWIST, SNAI, and ZEB, in promoting therapy resistance and tumor aggressiveness has also been reported in lymphomas, leukemias, and sarcomas. A reverse process, resembling mesenchymal-to-epithelial transition (MET), seems particularly relevant for sarcomas, where (partial) epithelial differentiation is linked to less aggressive tumors and a better patient prognosis. Overall, a hybrid model in which more stable epithelial and mesenchymal intermediates exist likely extends to the biology of tumors originating from sources other than the epithelium. Deeper investigation and understanding of the EMT/MET machinery in nonepithelial tumors will shed light on the pathogenesis of these tumors, potentially paving the way toward the identification of clinically relevant biomarkers for prognosis and future therapeutic targets.

A radiosensitivity gene signature and PD-L1 status predict clinical outcome of patients with invasive breast carcinoma in The Cancer Genome Atlas (TCGA) dataset

BACKGROUND AND PURPOSE

We investigated the link between the radiosensitivity gene signature and programmed cell death ligand 1 (PD-L1) status and clinical outcome in order to identify a group of patients that would possibly receive clinical benefit of radiotherapy (RT) combined with anti-PD1/PD-L1 therapy.

MATERIAL AND METHODS

We validated the identified gene signature related to radiosensitivity and analyzed the PD-L1 status of invasive breast cancer in The Cancer Genome Atlas (TCGA) dataset. To validate the gene signature, 1045 patients were selected and divided into two clusters using a consensus clustering algorithm based on their radiosensitive (RS) or radioresistant (RR) designation according to their prognosis. Patients were also stratified as PD-L1-high or PD-L1-low based on the median value of CD274 mRNA expression level as surrogates of PD-L1.

RESULTS

Patents assigned to the RS group had decreased risk of recurrence-free survival (RFS) rate than patients in the RR group by univariate analysis (HR 0.45, 95% CI 0.25-0.81, p=0.008) only when treated with RT. The RS group was independently associated with the PD-L1-high group, and CD274 mRNA expression was significantly higher in the RS group (p<0.001) than the RR group. In the PD-L1-high group, the RS group was associated with better RFS compared to the RR group (HR 0.37, 95% CI 0.16-0.87, p=0.022) in multivariate analysis. The level of PD-L1 expression may represent the immunogenicity of tumors, and thus, we speculated that the PD-L1-high group had more immunogenic tumors, which could be more sensitive to radiation-induced immunologic cell death.

CONCLUSION

We first evaluated the predictive value of the radiosensitivity gene signature and described a relationship with this radiosensitivity gene signature and PD-L1. The radiosensitivity gene signature and PD-L1 status were important factors for prediction of the clinical outcome of RT in patients with invasive breast cancer and may be used for selecting patients who will benefit from RT combined with anti-PD1/PDL1 therapy.

Blocking epithelial-to-mesenchymal transition in glioblastoma with a sextet of repurposed drugs: the EIS regimen

This paper outlines a treatment protocol to run alongside of standard current treatment of glioblastoma- resection, temozolomide and radiation. The epithelial to mesenchymal transition (EMT) inhibiting sextet, EIS Regimen, uses the ancillary attributes of six older medicines to impede EMT during glioblastoma. EMT is an actively motile, therapy-resisting, low proliferation, transient state that is an integral feature of cancers’ lethality generally and of glioblastoma specifically. It is believed to be during the EMT state that glioblastoma’s centrifugal migration occurs. EMT is also a feature of untreated glioblastoma but is enhanced by chemotherapy, by radiation and by surgical trauma. EIS Regimen uses the antifungal drug itraconazole to block Hedgehog signaling, the antidiabetes drug metformin to block AMP kinase (AMPK), the analgesic drug naproxen to block Rac1, the anti-fibrosis drug pirfenidone to block transforming growth factor-beta (TGF-beta), the psychiatric drug quetiapine to block receptor activator NFkB ligand (RANKL) and the antibiotic rifampin to block Wnt- all by their previously established ancillary attributes. All these systems have been identified as triggers of EMT and worthy targets to inhibit. The EIS Regimen drugs have a good safety profile when used individually. They are not expected to have any new side effects when combined. Further studies of the EIS Regimen are needed.

A novel interaction of PAK4 with PPARγ to regulate Nox1 and radiation-induced epithelial-to-mesenchymal transition in glioma

Tumor recurrence in glioblastoma (GBM) is, in part, attributed to increased epithelial-to-mesenchymal transition (EMT) and enhanced tumor cell dissemination in adjacent brain parenchyma after ionizing radiation (IR). EMT is associated with aggressive behavior, increased stem-like characteristics and treatment resistance in malignancies; however, the underlying signaling mechanisms that regulate EMT are poorly understood. We identified grade-dependent PAK4 upregulation in gliomas and further determined its role in mesenchymal transition and radioresistance. IR treatment significantly elevated expression and nuclear localization of PAK4 in correlation with induction of reactive oxygen species (ROS) and mesenchymal transition in GBM cells. Stable PAK4 overexpression promoted mesenchymal transition by elevating EMT marker expression in these cells. Of note, transcription factor-DNA binding arrays and chromatin immunoprecipitation experiments identified the formation of a novel nuclear PAK4/PPARγ complex which was recruited to the promoter of Nox1, a PPARγ target gene. In addition, IR further elevated PAK4/PPARγ complex co-recruitment to Nox1 promoter, and increased Nox1 expression and ROS levels associated with mesenchymal transition in these cells. Conversely, specific PAK4 downregulation decreased PPARγ-mediated Nox1 expression and suppressed EMT in IR-treated cells. In vivo orthotopic tumor experiments showed inhibition of growth and suppression of IR-induced PPARγ and Nox1 expression by PAK4 downregulation in tumors. Our results provide the first evidence of a novel role for PAK4 in IR-induced EMT and suggest potential therapeutic efficacy of targeting PAK4 to overcome radioresistance in gliomas.

Inhibition of miR-630 enhances the cell resistance to radiation by directly targeting CDC14A in human glioma

Radio-resistance becomes a large obstacle for effective cancer treatment. MicroRNAs (miRNAs) play important roles in response to radiation. However, the underlying mechanism of miR-630 on the radio-resistance of human glioma is less elucidated. In this study, we found that miR-630 was downregulated in glioma cell lines after radiation. MiR-630 inhibition enhanced the survival fraction, cell number in S stage and colony formation ability in glioma cells after radiation, while miR-630 overexpression resulted in inverse effects. By detecting the molecular mechanism of miR-630, we validated that CDC14A was a direct target of miR-630 and miR-630 suppressed CDC14A protein level. CDC14A overexpression can attenuate the inhibitory roles of miR-630 in survival fraction and cell proliferation. Finally, in vivo study demonstrated that miR-630 inhibition increased the volumes of xenografts bearing with glioma cells after radiation. In conclusion, our data indicate that anti-miR-630 enhances the radio-resistance of human glioma cells by targeting CDC14A, implying that miR-630 may act as a novel therapeutic target for enhancing the radiation efficiency on glioma patients.

Expression of CD133 and CD44 in glioblastoma stem cells correlates with cell proliferation, phenotype stability and intra-tumor heterogeneity

Glioblastoma (GBM) is a heterogeneous tumor of the brain with a poor prognosis due to recurrence and drug resistance following therapy. Genome-wide profiling has revealed the existence of distinct GBM molecular subtypes that respond differently to aggressive therapies. Despite this, molecular subtype does not predict recurrence or drug resistance and overall survival is similar across subtypes. One of the key features contributing to tumor recurrence and resistance to therapy is proposed to be an underlying subpopulation of resistant glioma stem cells (GSC). CD133 expression has been used as a marker of GSCs, however recent evidence suggests the relationship between CD133 expression, GSCs and molecular subtype is more complex than initially proposed. The expression of CD133, Olig2 and CD44 was investigated using patient derived glioma stem-like cells (PDGCs) in vitro and in vivo. Different PDGCs exhibited a characteristic equilibrium of distinct CD133+ and CD44+ subpopulations and the influence of environmental factors on the intra-tumor equilibrium of CD133+ and CD44+ cells in PDGCs was also investigated, with hypoxia inducing a CD44+ to CD133+ shift and chemo-radiotherapy inducing a CD133+ to CD44+ shift. These data suggest that surveillance and modulation of intra-tumor heterogeneity using molecular markers at initial surgery and surgery for recurrent GBM may be important for more effective management of GBM.

Dendrosomal nanocurcumin and p53 overexpression synergistically trigger apoptosis in glioblastoma cells

Objective(s):

Glioblastoma is the most lethal tumor of the central nervous system. Here, we aimed to evaluate the effects of exogenous delivery of p53 and a nanoformulation of curcumin called dendrosomal curcumin (DNC), alone and in combination, on glioblastoma tumor cells.

Materials and Methods:

MTT assay was exploited to measure the viability of U87-MG cells against DNC treatment. Cells were separately subjected to DNC treatment and transfected with p53-containing vector and then were co-exposed to DNC and p53 overexpression[A GA1][B2]. Annexin-V-FLUOS staining followed by flow cytometry and real-time PCR were applied to examine apoptosis and analyze the expression levels of the genes involved in cell cycle and oncogenesis, respectively.

Results:

The results of cell viability assay through MTT indicated that DNC inhibits the proliferation of U87-MG cells in a time- and dose-dependent manner. Apoptosis evaluation revealed that p53 overexpression accompanied by DNC treatment can act in a synergistic manner to significantly enhance the number of apoptotic cells (90%) compared with their application alone (15% and 38% for p53 overexpression and DNC, respectively). Also, real-time PCR data showed that the concomitant exposure of cells to both DNC and p53 overexpression leads to an enhanced expression of GADD45 and a reduced expression of NF-κB and c-Myc.

Conclusion:

The findings of the current study suggest that our combination strategy, which merges two detached gene (p53) and drug (curcumin) delivery systems into an integrated platform, may represent huge potential as a novel and efficient modality for glioblastoma treatment.

Cathepsin L is involved in X-ray-induced invasion and migration of human glioma U251 cells

An important therapeutic method of glioblastoma, the most common primary brain tumor, is radiotherapy. However, several studies reported recently that radiation could also promote the invasion and migration of malignant tumor. Herein, we have identified that a significant increase of migration and invasiveness of human glioma U251 cells undergoing X-ray was observed compared to controls, accompanied by the increase of cathepsin L (CTSL), which is a lysosomal cysteine protease overexpressed and secreted by tumor cells. To verify if there was a relationship between CTSL and the X-ray-induced glioma invasion, a CTSL specific inhibitor Z-FY-CHO or a short hairpin RNA interference was used to pretreat U251 cells. As a result, the cell invasion and migration was impaired via down-regulation of CTSL. Additionally, a marked reduction of the cell-signaling molecules Rho kinase was also detected compared with controls. We also found that CTSL is involved in EMT progress: both in vitro and in clinical specimens. Overall, our findings show that CTSL is an important protein which mediates cell invasion and migration of human glioma U251 cells induced by X-ray, and the inhibition of CTSL expression might diminish the invasion of U251 cells by reducing the activity of RhoA and CDC42 as well as EMT positive markers.

The radiosensitivity index predicts for overall survival in glioblastoma

We have previously developed a multigene expression model of tumor radiosensitivity (RSI) with clinical validation in multiple cohorts and disease sites. We hypothesized RSI would identify glioblastoma patients who would respond to radiation and predict treatment outcomes. Clinical and array based gene expression (Affymetrix HT Human Genome U133 Array Plate Set) level 2 data was downloaded from the cancer genome atlas (TCGA). A total of 270 patients were identified for the analysis: 214 who underwent radiotherapy and temozolomide and 56 who did not undergo radiotherapy. Median follow-up for the entire cohort was 9.1 months (range: 0.04–92.2 months). Patients who did not receive radiotherapy were more likely to be older (p < 0.001) and of poorer performance status (p < 0.001). On multivariate analysis, RSI is an independent predictor of OS (HR = 1.64, 95% CI 1.08–2.5; p = 0.02). Furthermore, on subset analysis, radiosensitive patients had significantly improved OS in the patients with high MGMT expression (unmethylated MGMT), 1 year OS 84.1% vs. 53.7% (p = 0.005). This observation held on MVA (HR = 1.94, 95% CI 1.19–3.31; p = 0.008), suggesting that RT has a larger therapeutic impact in these patients. In conclusion, RSI predicts for OS in glioblastoma. These data further confirm the value of RSI as a disease-site independent biomarker.

Transforming growth factor-β and stem cell markers are highly expressed around necrotic areas in glioblastoma

Invasion into surrounding normal brain and resistance to genotoxic therapies are the main devastating aspects of glioblastoma (GBM). These biological features may be associated with the stem cell phenotype, which can be induced through a dedifferentiation process known as epithelial-mesenchymal transition (EMT). We show here that tumor cells around pseudopalisading necrotic areas in human GBM tissues highly express the most important EMT inducer, transforming growth factor (TGF-β), concurrently with the EMT-related transcriptional factor, TWIST. In addition, the stem cell markers CD133 and alkaline phosphatase (ALPL) were also highly expressed around necrotic foci in GBM tissues. The high expression of TGF-β around necrotic regions was significantly correlated with shorter progression-free survival and overall survival in patients with GBM. High expression of stem cell markers, ALPL, CD133, and CD44 was also correlated with poor outcomes. These results collectively support the hypothesis that tissue hypoxia induces the stem cell phenotype through TGF-β-related EMT and contributes to the poor outcome of GBM patients.