Development of a prediction model for radiosensitivity using the expression values of genes and long non-coding RNAs.
ABSTRACT: 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.
Project description: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.
Project description:Radiotherapy is a cancer treatment that applies high doses of ionizing radiation to induce cell death, mainly by triggering DNA double-strand breaks. The outcome of radiotherapy greatly depends on radiosensitivity of cancer cells, which is determined by multiple proteins and cellular processes. In this review, we summarize current knowledge on the role of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in determining the response to radiation. Non-coding RNAs modulate ionizing radiation response by targeting key signaling pathways, including DNA damage repair, apoptosis, glycolysis, cell cycle arrest, and autophagy. Additionally, we indicate miRNAs and lncRNAs that upon overexpression or inhibition alter cellular radiosensitivity. Current data indicate the potential of using specific non-coding RNAs as modulators of cellular radiosensitivity to improve outcome of radiotherapy.
Project description:Background: The aim of the present study was to identify the potential long non-coding (lnc.)-RNA and its associated molecular mechanisms involved in the regulation of the radiosensitivity of esophageal squamous cell cancer (ESCC) in order to assess whether it could be a biomarker for the prediction of the response to radiotherapy and prognosis in patients with ESCC. Methods: Microarrays and bioinformatics analysis were utilized to screen the potential lncRNAs associated with radiosensitivity in radiosensitive (n = 3) and radioresistant (n = 3) ESCC tumor tissues. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed in 35 ESCC tumor tissues (20 radiosensitive and 15 radioresistant tissues, respectively) to validate the lncRNA that contributed the most to the radiosensitivity of ESCC (named the candidate lncRNA). MTT, flow cytometry, and western blot assays were conducted to assess the effect of the candidate lncRNA on radiosensitivity in vitro in ECA109/ECA109R ESCC cells. A mouse xenograft model was established to confirm the function of the candidate lncRNA in the radiosensitivity of ESCC in vivo. The putative downstream target genes regulated by the candidate lncRNA were predicted using Starbase 2.0 software and the TargetScan database. The interactions between the candidate lncRNA and the putative downstream target genes were examined by Luciferase reporter assay, and were confirmed by PCR. Results: A total of 113 aberrantly expressed lncRNAs were identified by microarray analysis, of which family with sequence similarity 201-member A (FAM201A) was identified as the lncRNA that contributed the most to the radiosensitivity of ESCC. FAM201A was upregulated in radioresistant ESCC tumor tissues and had a poorer short-term response to radiotherapy resulting in inferior overall survival. FAM201A knockdown enhanced the radiosensitivity of ECA109/ECA109R cells by upregulating ataxia telangiectasia mutated (ATM) and mammalian target of rapamycin (mTOR) expression via the negative regulation of miR-101 expression. The mouse xenograft model demonstrated that FAM201A knockdown improved the radiosensitivity of ESCC. Conclusion: The lncRNA FAM201A, which mediated the radiosensitivity of ESCC by regulating ATM and mTOR expression via miR-101 in the present study, may be a potential biomarker for predicting radiosensitivity and patient prognosis, and may be a therapeutic target for enhancing cancer radiosensitivity in ESCC.
Project description:Characterising and predicting the effects of ionising radiation on cells remains challenging, with the lack of robust models of the underlying mechanism of radiation responses providing a significant limitation to the development of personalised radiotherapy. In this paper we present a mechanistic model of cellular response to radiation that incorporates the kinetics of different DNA repair processes, the spatial distribution of double strand breaks and the resulting probability and severity of misrepair. This model enables predictions to be made of a range of key biological endpoints (DNA repair kinetics, chromosome aberration and mutation formation, survival) across a range of cell types based on a set of 11 mechanistic fitting parameters that are common across all cells. Applying this model to cellular survival showed its capacity to stratify the radiosensitivity of cells based on aspects of their phenotype and experimental conditions such as cell cycle phase and plating delay (correlation between modelled and observed Mean Inactivation Doses R(2)?>?0.9). By explicitly incorporating underlying mechanistic factors, this model can integrate knowledge from a wide range of biological studies to provide robust predictions and may act as a foundation for future calculations of individualised radiosensitivity.
Project description:Background:Radioresistance is an obstacle to limit efficacy of radiotherapy. Meanwhile, long non-coding RNAs (lncRNAs) have been reported to affect radioresistance. Here, we aimed to investigate lncRNAs involving radioresistance development of clear cell renal cell carcinoma (ccRCC), the most frequent type of renal cell carcinoma (RCC). Methods:The mRNA and protein expressions of genes were measured via qRT-PCR and western blot. The relationships among genes were verified by RIP and luciferase reporter assay. The radioresistance of ccRCC cells was evaluated through clonogenic survival assay, MTT assay and TUNEL assay. Results:LINC01094 was over-expressed in ccRCC cell lines. LINC01094 expression was increased along with the radiation exposure time and the final stable level was 8 times of the initial level. Knockdown of LINC01094 resulted in enhanced radiosensitivity of ccRCC cells. Mechanically, LINC01094 was a ceRNA of CHEK2 by sponging miR-577. Also, the enhancement of LINC01094 on ccRCC radioresistance was mediated by CHEK2-stabilized FOXM1 protein. Conclusion:LINC01094 facilitates ccRCC radioresistance by targeting miR-577/CHEK2/FOXM1 axis, blazing a new trail for overcoming radioresistance in ccRCC.
Project description:Protein phosphatase 2A (PP2A) is a tumor suppressor whose function is lost in many cancers. An emerging, though counterintuitive, therapeutic approach is inhibition of PP2A to drive damaged cells through the cell cycle, sensitizing them to radiotherapy. We investigated the effects of PP2A inhibition on U251 glioblastoma cells following radiation treatment in vitro and in a xenograft mouse model in vivo. Radiotherapy alone augmented PP2A activity, though this was significantly attenuated with combination LB100 treatment. LB100 treatment yielded a radiation dose enhancement factor of 1.45 and increased the rate of postradiation mitotic catastrophe at 72 and 96 hours. Glioblastoma cells treated with combination LB100 and radiotherapy maintained increased ?-H2AX expression at 24 hours, diminishing cellular repair of radiation-induced DNA double-strand breaks. Combination therapy significantly enhanced tumor growth delay and mouse survival and decreased p53 expression 3.68-fold, compared with radiotherapy alone. LB100 treatment effectively inhibited PP2A activity and enhanced U251 glioblastoma radiosensitivity in vitro and in vivo. Combination treatment with LB100 and radiation significantly delayed tumor growth, prolonging survival. The mechanism of radiosensitization appears to be related to increased mitotic catastrophe, decreased capacity for repair of DNA double-strand breaks, and diminished p53 DNA-damage response pathway activity.
Project description:A small percentage of cancer radiotherapy patients develop abnormally severe side effects as a consequence of intrinsic radiosensitivity. We analysed the ?-H2AX response to ex-vivo irradiation of peripheral blood lymphocytes (PBL) and plucked eyebrow hair follicles from 16 patients who developed severe late radiation toxicity following radiotherapy, and 12 matched control patients. Longer retention of the ?-H2AX signal and lower colocalization efficiency of repair factors in over-responding patients confirmed that DNA repair in these individuals was compromised. Five of the radiosensitive patients harboured LoF mutations in DNA repair genes. An extensive range of quantitative parameters of the ?-H2AX response were studied with the objective to establish a predictor for radiosensitivity status. The most powerful predictor was the combination of the fraction of the unrepairable component of ?-H2AX foci and repair rate in PBL, both derived from non-linear regression analysis of foci repair kinetics. We introduce a visual representation of radiosensitivity status that allocates a position for each patient on a two-dimensional "radiosensitivity map". This analytical approach provides the basis for larger prospective studies to further refine the algorithm, ultimately to triage capability.
Project description:Heat shock protein 27 (HSP27), a regulator of cell survival, can enhance the resistance of cancer cells to radiotherapy. As microRNA-541-3p (miR-541-3p) was recently predicted to be a putative upstream modulator of HSP27, the present study was designed to investigate the function and mechanism underlying how miR-541-3p modulates the radiosensitivity of prostate cancer (PCa) cells by regulating HSP27. Through quantitative PCR, miR-541-3p was determined to be poorly expressed in PCa tissues relative to normal controls, whereas its expression was enhanced after radiotherapy. Consistently, miR-541-3p expression levels in PCa cells were elevated after radiation. Cell viability and proliferation and apoptosis under radiation were subsequently evaluated in response to loss-of-function of miR-541-3p. It was found that inhibition of miR-541-3p facilitated the viability and proliferation of PCa cells and promoted their apoptosis post radiation, hence reducing the radiosensitivity of LNCaP cells. Dual-luciferase reporter assay identified that miR-541-3p negatively regulated the HSP27 mRNA expression by targeting its 3'-UTR. Meanwhile, miR-541-3p overexpression inhibited the ?-catenin expression by targeting HSP27. Furthermore, HSP27 or ?-catenin overexpression was noted to significantly reverse the miR-541-3p-mediated changes in the biological functions of PCa cells post radiation, suggesting that HSP27-dependent activation of ?-catenin might be the mechanism responsible for the promotive effect of miR-541-3p on radiosensitivity. Collectively, this study suggests that miR-541-3p specifically inhibits the HSP27 expression and downregulates ?-catenin, thereby enhancing the radiosensitivity of PCa cells. Our findings highlight the underlying mechanism of the miR-541-3p/HSP27/Wnt/?-catenin axis regarding radiotherapy for PCa.
Project description:Radiotherapy using high linear energy transfer (LET) radiation results in effectively killing tumor cells while minimizing dose (biological effective) to normal tissues to block toxicity. It is well known that high LET radiation leads to lower cell survival per absorbed dose than low LET radiation. High-linear energy transfer (LET) neutron treatment induces autophagy in tumor cells, but its precise mechanisms in osteosarcoma are unknown. Here, we investigated this mechanism and the underlying signaling pathways. Autophagy induction was examined in gamma-ray-treated KHOS/NP and MG63 osteosarcoma cells along with exposure to high-LET neutrons. The relationship between radiosensitivity and autophagy was assessed by plotting the cell surviving fractions against autophagy levels. Neutron treatment increased autophagy rates in irradiated KHOS/NP and MG63 cells; neutrons with high-LETs showed more effective inhibition than those with lower LET gamma-rays. To determine whether the unfolded protein response and Akt-mTOR pathways triggered autophagy, phosphorylated eIF2? and JNK levels, and phospho-Akt, phosphor-mTOR, and phospho-p70S6 levels were, respectively, investigated. High-LET neutron exposure inhibited Akt phosphorylation and increased Beclin 1 expression during the unfolded protein response, thereby enhancing autophagy. The therapeutic efficacy of high-LET neutron radiation was also assessed in vivo using an orthotopic mouse model. Neutron-irradiated mice showed reduced tumor growth without toxicity relative to gamma-ray-treated mice. The effect of high-LET neutron exposure on the expression of signaling proteins LC3, p-elF2a, and p-JNK was investigated by immunohistochemistry. Tumors in high-LET-neutron radiation-treated mice showed higher apoptosis rates, and neutron exposure significantly elevated LC3 expression, and increased p-elF2a and p-JNK expression levels. Overall, these results demonstrate that autophagy is important in radiosensitivity, cell survival, and cellular resistance against high-LET neutron radiation. This correlation between cellular radiosensitivity and autophagy may be used to predict radiosensitivity in osteosarcoma.
Project description:BACKGROUND: In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy. RESULTS: Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2 Gy (SF2, range from 0 to 1) was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2). Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM) and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway. CONCLUSIONS: Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that integrin signaling via adhesion molecules could be a target for radiosensitization.