Radioresistant Group Research Articles

Predicting radiotherapy efficacy and prognosis in tongue squamous cell carcinoma through an in-depth analysis of a radiosensitivity gene signature.

Tongue squamous cell carcinoma (TSCC) is a prevalent tumor that affects many people worldwide. Radiotherapy is a common treatment option, but its efficacy varies greatly. This study seeks to validate the identified gene signature associated with radiosensitivity in TSCC, and its potential in predicting radiotherapy response and prognosis. We analyzed 122 TSCC patients from TCGA database using the radiosensitivity signature and classified them into radiosensitive (RS) and radioresistant (RR) groups. Immune infiltration analysis methods were applied to investigate the immune status between different subgroups. Immunophenotype Score (IPS) and pRRophetic algorithm were employed to estimate the efficiency of treatment. A radioresistant TSCC cell line was established by gradually increasing radiation doses. Cell radiosensitivity was evaluated using the CCK-8 and colony formation assays. The expression of radiosensitivity-related genes was validated by qRT-PCR. Our study validated the predictive capacity of a previously identified "31-gene signature" in the TCGA-TSCC cohort, which effectively stratified patients into RS and RR groups. We observed that the RS group exhibited superior overall survival and progression-free survival rates relative to the RR group when treated with radiotherapy. The RS group was significantly enriched in most immune-related hallmark pathways, and may therefore benefit from immune checkpoint inhibitors. However, the RS group displayed lower sensitivity to first-line chemotherapy. A radioresistant TSCC cell line (CAL-27R) exhibited increased clonogenic potential and cell viability following irradiation, accompanied by downregulation of three radiosensitivity-related genes compared to its parental non-resistant cell (CAL-27). In addition, we constructed and validated a radiosensitivity-related prognostic index (PI) using 4 radiosensitivity-related genes associated with TSCC prognosis. We assessed the ability of the radiosensitivity gene signature to predict outcomes in TSCC patients. our research provided valuable insights into the molecular pathways associated with radiosensitivity in TSCC and offered clinicians a practical tool to predict patient radiotherapy effectiveness and prognosis.

Uncovering a novel DNA repair-related radiosensitivity model for evaluation of radiotherapy susceptibility in uterine corpus endometrial cancer

BackgroundUterine corpus endometrial cancer (UCEC) exhibit heterogeneity in their DNA repair capacity, which can impact their response to radiotherapy. Our study aimed to identify potential DNA repair-related biomarkers for predicting radiation response in UCEC. MethodsWe conducted a thorough analysis of 497 UCEC samples obtained from TCGA database. Using LASSO-COX regression analysis, we constructed a radiosensitivity signature and subsequently divided patients into the radiosensitive (RS) and the radioresistant (RR) groups based on their radiosensitivity index. The GSVA and GSEA were performed to explore functional annotations. The CIBERSORT and ESTIMATE algorithms were utilized to investigate the immune infiltration status of the two groups. Additionally, we utilized the Tumor Immune Dysfunction and Exclusion (TIDE), Immunophenotype Score (IPS), and pRRophetic algorithms to predict the effectiveness of different treatment modalities. ResultsWe constructed a radiosensitivity index consists of four DNA repair-related genes. Patients in the RS group demonstrated significantly improved prognosis compared to patients in the RR group when treated with radiotherapy. We observed that the RS group exhibited a higher proportion of the POLE ultra-mutated subtype, while the RR group had a higher proportion of the copy number high subtype. GSVA enrichment analysis revealed that the RS group exhibited enrichment in DNA damage repair pathways. Notably, the RS group demonstrated a higher proportion of naïve B cells and follicular helper T cells, while regulatory T cells (Tregs) and memory B cells were more abundant in the RR group. Furthermore, patients in the RS-PD-L1-high subgroup exhibited enrichment in immune-related pathways and increased sensitivity to immunotherapy, which is likely to contribute to their improved prognosis. Additionally, we conducted in vitro experiments to validate the expression of radiosensitivity genes in non-radioresistant (AN3CA) and radioresistant (AN3CA/IR) endometrial cancer cells. ConclusionsIn conclusion, our research successfully constructed a radiosensitivity signature with robust predictive capacity. These findings shed light on the association between immune activation, PD-L1 expression, and the response to immunotherapy in the context of radiotherapy.

Radiosensitivity is associated with antitumor immunity in estrogen receptor-negative breast cancer.

This study evaluated radiosensitivity and the tumor microenvironment (TME) to identify characteristics of breast cancer patients who would benefit most from radiation therapy. We analyzed 1903 records from the Molecular Taxonomy of Breast Cancer International Consortium cohort using the radiosensitivity index and gene expression deconvolution algorithms, CIBERSORT and xCell, that estimates the TME composition of tumor samples. In this study, patients were stratified according to TME and radiosensitivity. We performed integrative analyses of clinical and immuno-genomic data to characterize molecular features associated with radiosensitivity. Radiosensitivity was significantly associated with activation of antitumor immunity. In contrast, radioresistance was associated with a reactive stromal microenvironment. The immuno-genomic analysis revealed that estrogen receptor (ER) pathway activity was correlated with suppression of antitumor immunity. In ER-negative disease, the best prognosis was shown in the immune-high and radiosensitive group patients, and the lowest was in the immune-low and radioresistant group patients. In ER-positive disease, immune signature and radiosensitivity had no prognostic significance. Taken together, these results suggest that tumor radiosensitivity is associated with activation of antitumor immunity and a better prognosis, particularly in patients with ER-negative breast cancer.

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.

An 11-Gene Signature Based on Treatment Responsiveness Predicts Radiation Therapy Survival Benefit Among Breast Cancer Patients.

PurposeWe developed a strategy of building prognosis gene signature based on clinical treatment responsiveness to predict radiotherapy survival benefit in breast cancer patients.Methods and MaterialsAnalyzed data came from the public database. PFS was used as an indicator of clinical treatment responsiveness. WGCNA was used to identify the most relevant modules to radiotherapy response. Based on the module genes, Cox regression model was used to build survival prognosis signature to distinguish the benefit group of radiotherapy. An external validation was also performed.ResultsIn the developed dataset, MEbrown module with 534 genes was identified by WGCNA, which was most correlated to the radiotherapy response of patients. A number of 11 hub genes were selected to build the survival prognosis signature. Patients that were divided into radio-sensitivity group and radio-resistant group based on the signature risk score had varied survival benefit. In developed dataset, the 3-, 5-, and 10-year AUC of the signature were 0.814 (CI95%: 0.742–0.905), 0.781 (CI95%: 0.682–0.880), and 0.762 (CI95%: 0.626–0.897), respectively. In validation dataset, the 3- and 5-year AUC of the signature were 0.706 (CI95%: 0.523–0.889) and 0.743 (CI95%: 0.595–0.891). The signature had higher predictive power than clinical factors alone and had more clinical prognosis efficiency. Functional enrichment analysis revealed that the identified genes were mainly enriched in immune-related processes. Further immune estimated analysis showed the difference in distribution of immune micro-environment between radio-sensitivity group and radio-resistant group.ConclusionsThe 11-gene signature may reflect differences in tumor immune micro-environment that underlie the differential response to radiation therapy and could guide clinical-decision making related to radiation in breast cancer patients.

Combination of Radiosensitivity Gene Signature and PD-L1 Status Predicts Clinical Outcome of Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma: A Study Based on The Cancer Genome Atlas Dataset.

Aim: The aim of our study was to investigate the potential predictive value of the combination of radiosensitivity gene signature and PD-L1 expression for the prognosis of locally advanced head and neck squamous cell carcinoma (HNSCC). Methods: The cohort was selected from The Cancer Genome Atlas (TCGA) and classified into the radiosensitive (RS) group and radioresistant (RR) group by a radiosensitivity-related gene signature. The cohort was also grouped as PD-L1-high or PD-L1-low based on PD-L1 mRNA expression. The least absolute shrinkage and selection operator (lasso)-based Cox model was used to select hub survival genes. An independent validation cohort was obtained from the Gene Expression Omnibus (GEO) database. Results: We selected 288 locally advanced HNSCC patients from TCGA. The Kaplan–Meier method found that the RR and PD-L1-high group had a worse survival than others (p = 0.033). The differentially expressed gene (DEG) analysis identified 553 upregulated genes and 486 downregulated genes (p < 0.05, fold change >2) between the RR and PD-L1-high group and others. The univariate Cox analysis of each DEG and subsequent lasso-based Cox model revealed five hub survival genes (POU4F1, IL34, HLF, CBS, and RNF165). A further hub survival gene-based risk score model was constructed, which was validated by an external cohort. We observed that a higher risk score predicted a worse prognosis (p = 0.0013). The area under the receiver operating characteristic curve (AUC) plots showed that this risk score model had good prediction value (1-year AUC = 0.684, 2-year AUC = 0.702, and 3-year AUC = 0.688). Five different deconvolution methods all showed that the B cells were lower in the RR and PD-L1-high group (p < 0.05). Finally, connectivity mapping analysis showed that the histone deacetylase (HDAC) inhibitor trichostatin A might have the potential to reverse the phenotype of RR and PD-L1-high in locally advanced HNSCC (p < 0.05, false discovery rate <0.1). Conclusion: The combination of 31-gene signature and the PD-L1 mRNA expression had a potential predictive value for the prognosis of locally advanced HNSCC who had RT. The B cells were lower in the RR and PD-L1-high group. The identified risk gene signature of locally advanced HNSCC and the potential therapeutic drug trichostatin A for the RR and PD-L1-high group are worth being further studied in a prospective homogenous cohort.

Pain as the evaluation criterion for bone metastasis radiosensitivity. Comparative efficacy of radiation therapy in patients with bone metastases of various primary tumors.

Purpose: Assessment of the comparative radiosensitivity of bone metastases of various nature and histogenesis. Material/methods: As part of a randomized study, 810 courses of 3D-conformal or IMRT / VIMAT radiotherapy were performed for bone metastases of various origins and localization with persistent pain syndrome. Radiotherapy protocol included hypofractionation regimes of 2, 3 or 4 fractions of 6,5 Gy with total dose of 13-26 Gy or standard fractionation regime with total dose of 46 Gy. Results: The overall effectiveness (сomplete and partial pain relief) of radiotherapy was 96.2%, complete response rate (CRR) – 56.2%, partial response rate – 40.0%. Pain relapse rate was 8.6%, on average after 9.5 months after irradiation. The independent predictors of the CRR were: the initial pain intensity [hazard ratio (RR): 0.48, confidence interval (CI): 0.40-0.58; p = 0.0001], dose/number of fractions (RR: 1.26, CI: 1.07-1.50; p = 0.0059) and primary tumor site (RR: 0.95, CI: 0.92-0,99; p = 0.0053). We constructed a scale of comparative radiosensitivity of bone metastases of various primary tumors, taking into account the complete response rate and the probability of surviving without pain relapse for 6, 12 and 24 months after radiotherapy. The radiosensitive group included metastases from breast and prostate cancer, melanoma, bladder and PNET (CRR 60% or more), and relatively radioresistant group - metastases from unknown origin, colon, stomach and kidney cancer (CRR 40% or less). Conclusion: More than 95% overall effectiveness of radiotherapy for bone metastases, with pain relapse rate of less than 10% of cases, allows us to consider widefield irradiation in doses of 19.5-26 Gy, in 3-4 fractions of 6.5 Gy, the preferred treatment for multifocal lesions. Dose escalation in patients with bone metastases of kidney, colon, lung cancer and metastases from unknown origin seems to be justified in the cases with a life expectancy of more than a year.

A Radioresponse-Related lncRNA Biomarker Signature for Risk Classification and Prognosis Prediction in Non-Small-Cell Lung Cancer.

Purpose Radiotherapy resistance is now recognized as the major obstacle to the effective therapeutic management of non-small-cell lung cancer (NSCLC). As a single biomarker has limited effect in stratifying NSCLC patients, this research aimed to identify long non-coding RNAs (lncRNAs) correlated with radiotherapy response to ameliorate forecast of NSCLC prognosis. Methods In a cohort of NSCLC patients with radiotherapy history (n = 96) from TCGA, genetic data of lncRNA expression profiling were performed. To identify radioresponse-related lncRNA sets which dysregulated significantly between radiosensitive (RS) and radioresistant (RR) groups, differential expression analysis was carried out. Cox relative regression was implemented to set up a radioresponse-related risk model. Moreover, we adopted survival analysis to measure the predictive potentiality of the prognosis model. Results Four radioresponse-related lncRNAs (CASC19, LINC01977, LINC02471, and MAGI2-AS3) were screened to create a prognostic signature. Then, we described a lncRNA signature-based regulatory network and explored the correlation of the immune microenvironment and the signature. Additionally, in vitro assays uncovered inhibition of LINC01977 weakened radioresistance of NSCLC cells. Conclusion We provided a novel radioresponse-related lncRNAs signature with excellent clinical potency for an effective prognostic forecast of patients.

Key radioresistance regulation models and marker genes identified by integrated transcriptome analysis in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignancy that is endemic to China and Southeast Asia. Radiotherapy is the usual treatment, however, radioresistance remains a major reason for failure. This study aimed to find key radioresistance regulation models and marker genes of NPC and clarify the mechanism of NPC radioresistance by RNA sequencing and bioinformatics analysis of the differences in gene expression profiles between radioresistant and radiosensitive NPC tissues. A total of 21 NPC biopsy specimens with different radiosensitivity were analyzed by RNA sequencing. Differentially expressed genes in RNA sequencing data were identified using R software. The differentially expressed gene data derived from RNA sequencing as well as prior knowledge in the form of pathway databases were integrated to find sub‐networks of related genes. The data of RNA sequencing with the GSE48501 data from the GEO database were combined to further search for more reliable genes associated with radioresistance of NPC. Survival analyses using the Kaplan–Meier method based on the expression of the genes were conducted to facilitate the understanding of the clinical significance of the differentially expressed genes. RT‐qPCR was performed to validate the expression levels of the differentially expressed genes. We identified 1182 differentially expressed genes between radioresistant and radiosensitive NPC tissue samples. Compared to the radiosensitive group, 22 genes were significantly upregulated and 1160 genes were downregulated in the radioresistant group. In addition, 10 major NPC radiation resistance network models were identified through integration analysis with known NPC radiation resistance‐associated genes and mechanisms. Furthermore, we identified three core genes, DOCK4, MCM9, and POPDC3 among 12 common downregulated genes in the two datasets, which were validated by RT‐qPCR. The findings of this study provide new clues for clarifying the mechanism of NPC radioresistance, and further experimental studies of these core genes are warranted.

Integrating Intrinsic Radiosensitivity and Immune Status for Predicting Benefits of Radiotherapy in Head and Neck Squamous Cell Carcinoma.

BackgroundHNSCC (head and neck squamous cell carcinoma) is a heterogeneous disease for which radiotherapy is a main treatment. As intrinsic radiosensitivity and immune status affect the initial and effective stage of the radiation-induced cancer immunity cycle, respectively, it is important to consider both of them when we select patients who can benefit from radiotherapy.Material/MethodsOur study included all HNSCC patients with complete survival and radiotherapy information in TCGA database. Patients were divided into RS (radiosensitive), RR (radioresistant), immune, and non-immune groups according to their RSI (radiosensitivity index) and immune score calculated by the ESTIMATE algorithm. Survival analysis was performed to compare OS (overall survival) between patients receiving and not receiving radiotherapy. GO and KEGG pathway enrichment analysis was performed for functional analysis. Univariate Cox and ridge regression analysis were performed to construct a predictive gene signature based on the combined stratification.ResultsOnly patients in the RS-immune group could benefit from radiotherapy, and the survival analysis results remained consistent after we performed propensity score matching between patients receiving and not receiving radiotherapy. The differentially expressed genes between the RS-immune and non-RS-immune groups were mainly enriched in pathways related to immune process. The 3-gene signature we built exhibited predictive value in training and validation cohorts when treated as a binary or continuous variable.ConclusionsThe combined stratification of intrinsic radiosensitivity and immune status was superior to considering intrinsic radiosensitivity or immune status alone and could be used in preclinical evaluation to select patients or to decide whether radiotherapy sensitizers and immunotherapy should be used at the same time.

Predicting the radiosensitivity of HPV-negative oropharyngeal squamous cell carcinoma using miR-130b

Background Human papillomavirus (HPV)-negative oropharyngeal squamous cell carcinoma shows a higher rate of radiation resistance than HPV-positive oropharyngeal squamous cell carcinoma (OPSCC). Radioresistant HPV-negative OPSCC is associated with unfavourable outcomes, but validated prognostic biomarkers remain lacking. Aims/Objectives This study investigated biomarkers for radioresistant HPV-negative OPSCC. Material and methods The Cancer Genome Atlas included miRNA sequence and mRNA sequence data from 528 HNSCC tumours. Of these, we used gene expression data for HPV-negative head and neck squamous cell carcinoma for which data were available on the effects of radiation, and compared miRNA sequence and mRNA sequence data between radioresistant and radiosensitive groups. We subsequently estimated downstream miRNA from the results. Finally, we validated miRNAs related to the outcomes of radiotherapy in our clinical cases. Results Investigation of miRNA sequence revealed expression of miR-130b as the greatest difference between radiosensitive and radioresistant groups. We subsequently evaluated miR-130b expression in our clinical OPSCC cases. Values of miR-130b >5.372 (low expression), determined from receiver operating characteristic curve analyses, were associated with significantly longer progression-free survival and overall survival (p = .006, p = .04, respectively). Conclusions and significance Our results suggest that miR-130b has potential as a biomarker for the radiosensitivity of HPV-negative OPSCC.

The Role of Cyclin D1 and VEGF in Radiotherapy Response of Advance Stage Undifferentiated Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma has a high incidence and mortality rate in Southeast Asia and Indonesia. Radioresistance is a major obstacle to successful treatment of nasopharyngeal carcinoma. DNA repair in the cell cycle and angiogenesis factors affects the response of tumor cells to radiotherapy. Cyclin D1 that functions in the cell cycle process and VEGF as an angiogenesis factor are considered to play a role in the occurrence of radioresistance. The objective of this study is to find the association between immunoexpression of Cyclin D1 and VEGF with radiotherapy response in undifferentiated nasopharyngeal carcinoma. This study used a retrospective case control analysis design, secondary data from medical records of patients diagnosed as undifferentiated nasopharyngeal carcinoma who received complete radiotherapy at the Radiation Oncology Department Dr Hasan Sadikin Bandung were taken. There were 44 samples divided into radiosensitive (22 samples) and radioresistant (22 samples) groups. Immunohistochemical examination of Cyclin D1 and VEGF was performed on paraffin blocks of patients' biopsy. Data analysis using Chi-Square test (p ≤0.05) , OR 95% CI. Cyclin D1 expressed strongly in 86.4% of the radioresistant group and 59.1% in the radiosensitive group (p&lt;0.05) and the OR 4,385 (0.993-19.356), VEGF was strongly expressed in 77.3% of the radioresistant group and 54.5% in the radiosensitive group (p&gt;0.05). As conclusion, there were significant association between Cyclin D1 with radiotherapy respons in undifferentiated nasopharyngeal carcinoma. The stronger immunoexpression of Cyclin D1, the higher likelihood of radioresistancy. VEGF immunoexpression showed no significant association with radiotherapy response.

The Role of Cyclin D1 and VEGF in Radiotherapy Response of Advance Stage Undifferentiated Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma has a high incidence and mortality rate in Southeast Asia and Indonesia. Radioresistance is a major obstacle to successful treatment of nasopharyngeal carcinoma. DNA repair in the cell cycle and angiogenesis factors affects the response of tumor cells to radiotherapy. Cyclin D1 that functions in the cell cycle process and VEGF as an angiogenesis factor are considered to play a role in the occurrence of radioresistance. The objective of this study is to find the association between immunoexpression of Cyclin D1 and VEGF with radiotherapy response in undifferentiated nasopharyngeal carcinoma. This study used a retrospective case control analysis design, secondary data from medical records of patients diagnosed as undifferentiated nasopharyngeal carcinoma who received complete radiotherapy at the Radiation Oncology Department, Dr. Hasan Sadikin Bandung were taken. There were 44 samples divided into radiosensitive (22 samples) and radioresistant (22 samples) groups. Immunohistochemical examination of Cyclin D1 and VEGF was performed on paraffin blocks of patients' biopsy. Data analysis using Chi-Square test (p≤0.05) , OR 95% CI. Cyclin D1 expressed strongly in 86.4% of the radioresistant group and 59.1% in the radiosensitive group (p&lt;0.05) and the OR 4,385 (0.993-19.356), VEGF was strongly expressed in 77.3% of the radioresistant group and 54.5% in the radiosensitive group (p&gt;0.05). As conclusion, there were significant association between Cyclin D1 with radiotherapy respons in undifferentiated nasopharyngeal carcinoma. The stronger immunoexpression of Cyclin D1, the higher likelihood of radioresistancy. VEGF immunoexpression showed no significant association with radiotherapy response.

Transcriptomic and Mutational Analyses Identify Biological Processes Correlated with Bladder Cancer Cell Line (BlaCCL) Radiation Response

We aimed to identify biological pathways that correlate with in vitro radiation response of an expanded panel of BlaCCL based upon analysis of whole-transcriptomic RNA-seq and targeted mutational profiling. Twenty established BlaCCL were verified by genomic fingerprinting and profiled with RNA-seq and targeted mutational analysis. Raw RNA-seq counts were normalized via log(FPKM+1) and mutations were profiled via custom panel enriched for 176 genes involved in DNA-damage response, chromatin remodeling, cell cycle control, inflammatory signaling and others (Nextera). We performed colony forming assays on all cell lines in triplicate with cumulative survival quantified via area-under-the-cell-survival curve (AUC) through a range of radiation doses (0-8Gy). Unsupervised learning of complex biological processes based on RNA-seq data was conducted via the CoGAPS package v.3.6 in R v.3.6.2. CoGAPS was run for k = 13 at 10,000 iterations and resulting patterns were correlated with AUC via Spearman’s rho. Differences in number of mutations between radio-sensitive and -resistant lines (based on AUC relative to median) were compared via Student’s t-test. Gene ontology (GO) enrichment was conducted via String-DB with significant terms identified with an FDR cut-off <0.05. RNA-seq analysis identified 18,634 genes for the panel of BlaCCL and mutational calling identified mutations in 63/176 unique genes in 18 cell lines ranging from 2-15 mutations per cell line. Satisfactory colony forming results were obtained for 17/20 cell lines with AUC ranging from 3.40-5.94 with a median of 4.58. CoGAPS factorization of the RNA-seq dataset revealed 2/13 gene sets that had a significant correlation with AUC (Pattern 2, 605 genes, rho = -0.75, p = 0.0007; Pattern 9, 176 genes, rho = 0.56, p = 0.0190). Pattern 2 was significantly enriched for cytokine-mediated signaling and Pattern 9 was significantly enriched for 43 processes including epithelial cell differentiation and activation of immune response. Notably, radioresistant cell lines had significantly more mutations (median 10 vs 4, p = 0.039; 52 vs 25 unique genes mutated in total between groups). GO enrichment based on mutated genes was similar between the two groups including radiation response, hypoxia, and regulation of immune system processes although the top-10 GO-terms in the radioresistant group were notable for chromosome organization, cellular stress response and DNA repair as opposed to cell cycle processes in the sensitive group. Based on biological process enrichment analysis of RNA-seq and targeted mutational profiling, several processes, particularly inflammation, are correlated with in vitro radiation response in BlaCCL. Further mechanistic studies are necessary to determine true modulators of radiosensitivity and to establish potential genetic biomarkers for prospective clinical validation.

Inhibition of Delta-like Ligand 4 enhances the radiosensitivity and inhibits migration in cervical cancer via the reversion of epithelial\u2013mesenchymal transition

BackgroundConcurrent chemoradiotherapy is the common first-line treatment for patients with advanced cervical cancer. However, radioresistance remains a major clinical challenge, which results in recurrence and poor survival. Many studies have shown the potential of Delta-like Ligand 4 (DLL4) as a novel prognostic biomarker and therapeutic target in many solid tumors. Previously, we have found that high DLL4 expression in tumor cells may predict the pelvic lymph node metastasis and poor prognosis in patients with cervical cancer. In our present study, we further studied the effects of DLL4 on the biological behavior and radiosensitivity of cervical cancer cells.MethodsThe expression of DLL4 and epithelial–mesenchymal transition (EMT) phenotype markers in cervical cancer cell lines or tissues were detected using Western blotting, and the expression of DLL4 mRNA in cervical cancer cell lines or tissues was detected using Quantitative real-time PCR. The effect of DLL4 on cell proliferation, migration, and radiosensitivity was evaluated using the CCK8 assay, flow cytometry, Transwell assays for cell invasion and migration, and Immunofluorescence staining in vitro.ResultsThe expression of DLL4 in radiotherapy-resistant SiHa cells was significantly higher than that in radiotherapy-sensitive Me-180 cells. Furthermore, downregulation of DLL4 enhanced the radiosensitivity of SiHa and Caski cells via the inhibition of cell proliferation, promotion of radiation-induced apoptosis, and inhibition of the DNA damage repair. Moreover, downregulation of DLL4 inhibited the EMT and reduced the proliferation, invasion, and migration ability in SiHa and Caski cells. Consistent with the DLL4 expression in the cell lines, the expression of DLL4 in the tissues of the radioresistant group was also higher than that of the radiosensitive group.ConclusionsDownregulation of DLL4 inhibited the progression and increased the radiosensitivity in cervical cancer cells by reversing EMT. These results indicated the promising prospect of DLL4 against the radioresistance and metastasis of cervical cancer and its potential as a predictive biomarker for radiosensitivity and prognosis in patients with cervical cancer patients receiving concurrent chemoradiotherapy (cCRT).

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.

Gene signature for prediction of radiosensitivity in human papillomavirus-negative head and neck squamous cell carcinoma.

PurposeThe probability of recurrence of cancer after adjuvant or definitive radiotherapy in patients with human papillomavirus-negative (HPV(–)) head and neck squamous cell carcinoma (HNSCC) varies for each patient. This study aimed to identify and validate radiation sensitivity signature (RSS) of patients with HPV(–) HNSCC to predict the recurrence of cancer after radiotherapy.Materials and MethodsClonogenic survival assays were performed to assess radiosensitivity in 14 HNSCC cell lines. We identified genes closely correlated with radiosensitivity and validated them in The Cancer Genome Atlas (TCGA) cohort. The validated RSS were analyzed by ingenuity pathway analysis (IPA) to identify canonical pathways, upstream regulators, diseases and functions, and gene networks related to radiosensitive genes in HPV(–) HNSCC.ResultsThe survival fraction of 14 HNSCC cell lines after exposure to 2 Gy of radiation ranged from 48% to 72%. Six genes were positively correlated and 35 genes were negatively correlated with radioresistance, respectively. RSS was validated in the HPV(–) TCGA HNSCC cohort (n = 203), and recurrence-free survival (RFS) rate was found to be significantly lower in the radioresistant group than in the radiosensitive group (p = 0.035). Cell death and survival, cell-to-cell signaling, and cellular movement were significantly enriched in RSS, and RSSs were highly correlated with each other.ConclusionWe derived a HPV(–) HNSCC-specific RSS and validated it in an independent cohort. The outcome of adjuvant or definitive radiotherapy in HPV(–) patients with HNSCC can be predicted by analyzing their RSS, which might help in establishing a personalized therapeutic plan.

A three-lncRNA signature predicts clinical outcomes in low-grade glioma patients after radiotherapy.

Although radiation therapy (RT) plays a critical role in the treatment of low-grade glioma (LGG), many patients suffer from adverse effects without experiencing survival benefits. In various carcinomas, long non-coding RNAs (lncRNAs) contribute to pathogenic processes, including tumorigenesis, metastasis, chemoresistance, and radioresistance. Currently, the role of lncRNAs in the radiosensitivity of LGG is largely unknown. Here, we downloaded clinical data for 167 LGG patients from The Cancer Genome Atlas database and divided them between radiosensitive and radioresistant groups based on their clinical outcomes after receiving radiotherapy. We identified 37 lncRNAs that were differentially expressed (DElncRNAs) between the groups. Functional enrichment analysis revealed that their potential target mRNAs were mainly enriched in the PI3K-Akt and MAPK signaling pathways and in DNA damage response. Kaplan-Meier survival analysis revealed that increased expression of six lncRNAs was significantly associated with radiosensitivity. We then developed a risk signature based on three of the DElncRNAs that served as an independent biomarker for predicting LGG patient outcomes after radiotherapy. In vitro experiments further validated the biological function of these lncRNAs on low-grade glioma radiation response.

Monitor Ionizing Radiation-Induced Cellular Responses with Raman Spectroscopy, Non-Negative Matrix Factorization, and Non-Negative Least Squares

Radiation therapy (RT) is one of the most commonly prescribed cancer treatments. New tools that can accurately monitor and evaluate individual patient responses would be a major advantage and lend to the implementation of personalized treatment plans. In this study, Raman spectroscopy (RS) was applied to examine radiation-induced cellular responses in H460, MCF7, and LNCaP cancer cell lines across different dose levels and times post-irradiation. Previous Raman data analysis was conducted using principal component analysis (PCA), which showed the ability to extract biological information of glycogen. In the current studies, the use of non-negative matrix factorization (NMF) allowed for the discovery of multiplexed biological information, specifically uncovering glycogen-like and lipid-like component bases. The corresponding scores of glycogen and previously unidentified lipids revealed the content variations of these two chemicals in the cellular data. The NMF decomposed glycogen and lipid-like bases were able to separate the cancer cell lines into radiosensitive and radioresistant groups. A further lipid phenotype investigation was also attempted by applying non-negative least squares (NNLS) to the lipid-like bases decomposed individually from three cell lines. Qualitative differences found in lipid weights for each lipid-like basis suggest the lipid phenotype differences in the three tested cancer cell lines. Collectively, this study demonstrates that the application of NMF and NNLS on RS data analysis to monitor ionizing radiation-induced cellular responses can yield multiplexed biological information on bio-response to RT not revealed by conventional chemometric approaches.

A Radiosensitivity Gene Signature and PD-L1 Status Predict Clinical Outcome of Patients with Glioblastoma Multiforme in The Cancer Genome Atlas Dataset.

PurposeCombination of radiotherapy and immune checkpoint blockade such as programmed death-1 (PD-1) or programmed death-ligand 1 (PD-L1) blockade is being actively tested in clinical trial. We aimed to identify a subset of patients that could potentially benefit from this strategy using The Cancer Genome Atlas (TCGA) dataset for glioblastoma (GBM).Materials and MethodsA total of 399 cases were clustered into radiosensitive versus radioresistant (RR) groups based on a radiosensitivity gene signature and were also stratified as PD-L1 high versus PD-L1 low groups by expression of CD274 mRNA. Differential and integrated analyses with expression and methylation data were performed. CIBERSORT was used to enumerate the immune repertoire that resulted from transcriptome profiles.ResultsWe identified a subset of GBM, PD-L1-high-RR group which showed worse survival compared to others. In PD-L1-high-RR, differentially expressed genes (DEG) were highly enriched for immune response and mapped into activation of phosphoinositide 3-kinase–AKT and mitogen-activated protein kinase (MAPK) signaling pathways. Integration of DEG and differentially methylated region identified that the kinase MAP3K8-involved in T-cell receptor signaling was upregulated and BAI1, a factor which inhibits angiogenesis, was silenced. CIBERSORT showed that a higher infiltration of the immune repertoire, which included M2 macrophages and regulatory T cells.ConclusionTaken together, PD-L1-high-RR group could potentially benefit from radiotherapy combined with PD-1/PD-L1 blockade and angiogenesis inhibition.