Radiosensitive Research Articles

Differential biological effect of low doses of ionizing radiation depending on the radiosensitivity in a cell line model

Purpose Exposure to low doses (LD) of ionizing radiation (IR), such as the ones employed in computed tomography (CT) examination, can be associated with cancer risk. However, cancer development could depend on individual radiosensitivity. In the present study, we evaluated the differences in the response to a CT-scan radiation dose of 20 mGy in two lymphoblastoid cell lines with different radiosensitivity. Materials and Methods Several parameters were studied: gene expression, DNA damage, and its repair, as well as cell viability, proliferation, and death. Results were compared with those after a medium dose of 500 mGy. Results After 20 mGy of IR, the radiosensitive (RS) cell line showed an increase in DNA damage, and higher cell proliferation and apoptosis, whereas the radioresistant (RR) cell line was insensitive to this LD. Interestingly, the RR cell line showed a higher expression of an antioxidant gene, which could be used by the cells as a protective mechanism. After a dose of 500 mGy, both cell lines were affected by IR but with significant differences. The RS cells presented an increase in DNA damage and apoptosis, but a decrease in cell proliferation and cell viability, as well as less antioxidant response. Conclusions A differential biological effect was observed between two cell lines with different radiosensitivity, and these differences are especially interesting after a CT scan dose. If this is confirmed by further studies, one could think that individuals with radiosensitivity-related genetic variants may be more vulnerable to long-term effects of IR, potentially increasing cancer risk after LD exposure.

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.

Abstract 1126: Extracellular vesicle mediated radioresistance in H3K27M-diffuse midline glioma

Abstract H3K27M-Diffuse Midline Gliomas (DMGs) are a subset of uncurable malignant pediatric gliomas and the deadliest form of brain tumors in children worldwide. Radiation therapy, the current standard of care, is initially effective but all tumors become resistant within 4-6 months. H3K27M-DMGs are heterogenous, comprised of an average of 6 genetically distinct subclones. Some subclones harbor mutations in genes previously linked to radiation resistance, such as TP53. We have found subclones are also functionally distinct, with some clones harboring intrinsic radiation resistance. Extracellular signaling between clones is linked with therapy resistance and tumor progression in other tumors, and we hypothesized that radioresistant H3K27M-DMG release small extracellular vesicles (sEVs) that impact the radiosensitivity of neighboring tumor cells. We found that all patient-derived H3K27M-DMG samples examined (n=6) produced sEVs (< 220nm), indicating this is a common feature in this tumor type. We isolated sEVs from a radioresistant (RR) patient-derived H3K27M-DMG cell line and used them to treat radiosensitive (RS) DMG cells. Using flow cytometry to profile sEV uptake dynamics, we found that RR-sEVs are internalized by RS cells within 2 hours of exposure and are retained at 18 hours (p<0.001, compared to control). This uptake can be significantly abrogated by proteinase K treatment of the sEVs, (p<0.001), indicating that uptake involves sEV surface proteins. We then applied a biosensor approach to assess single-cell phenotypic changes in RS DMG after RR-sEV treatment on radiation-induced cell death, DNA damage, and cell senescence, three dynamic processes. Using a genetically encoded death indicator (GEDI), we found that RR-sEVs significantly enhanced the survival of RS cells after acute radiation exposure (p<0.001). This was due to enhanced DNA damage repair as measured by 53BP1 foci (p<0.01). Small RNA sequencing of sEV cargo demonstrated that RR-sEVs express multiple miRNAs that are involved in oncogenic signaling such as the miR-7 family, miR-1246, and miR-1290 at several log fold higher than RS-sEVs. Overall, this data reveals the first functional role for sEVs in the context of radiation induced tumor transformation in DMG. We plan to further investigate the primary route of sEV uptake and define the mechanism through which sEV cargo alters radiosensitivity. This study provides new insight into the impact of heterogeneity and sEVs in mediating radioresistance in H3K27M-DMG and may lead to the development of novel radiosensitizers, which are critically needed for all patients. Citation Format: Viral Oza, Shilpa Sampathi, Yelena Chernyavskava, Kenan Flores, Jessica Blackburn. Extracellular vesicle mediated radioresistance in H3K27M-diffuse midline glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1126.

Multivariate piecewise linear regression model to predict radiosensitivity using the association with the genome-wide copy number variation.

The search for biomarkers to predict radiosensitivity is important not only to individualize radiotherapy of cancer patients but also to forecast radiation exposure risks. The aim of this study was to devise a machine-learning method to stratify radiosensitivity and to investigate its association with genome-wide copy number variations (CNVs) as markers of sensitivity to ionizing radiation. We used the Affymetrix CytoScan HD microarrays to survey common CNVs in 129 fibroblast cell strains. Radiosensitivity was measured by the surviving fraction at 2 Gy (SF2). We applied a dynamic programming (DP) algorithm to create a piecewise (segmented) multivariate linear regression model predicting SF2 and to identify SF2 segment-related distinctive CNVs. SF2 ranged between 0.1384 and 0.4860 (mean=0.3273 The DP algorithm provided optimal segmentation by defining batches of radio-sensitive (RS), normally-sensitive (NS), and radio-resistant (RR) responders. The weighted mean relative errors (MRE) decreased with increasing the segments' number. The borders of the utmost segments have stabilized after partitioning SF2 into 5 subranges. The 5-segment model associated C-3SFBP marker with the most-RS and C-7IUVU marker with the most-RR cell strains. Both markers were mapped to gene regions (MCC and SLC1A6, respectively). In addition, C-3SFBP marker is also located in enhancer and multiple binding motifs. Moreover, for most CNVs significantly correlated with SF2, the radiosensitivity increased with the copy-number decrease.In conclusion, the DP-based piecewise multivariate linear regression method helps narrow the set of CNV markers from the whole radiosensitivity range to the smaller intervals of interest. Notably, SF2 partitioning not only improves the SF2 estimation but also provides distinctive markers. Ultimately, segment-related markers can be used, potentially with tissues' specific factors or other clinical data, to identify radiotherapy patients who are most RS and require reduced doses to avoid complications and the most RR eligible for dose escalation to improve outcomes.

Predicting Acute Radio-Induced Toxicity for Head and Neck Cancer Patients: Combining Dosimetry with Biomarker Data, Disclosing a Synergistic Effect

We aimed to establish the added value of combining dosimetry with a binary blood assay for radiosensitivity based on quantification of pATM protein (RADIODTECT©) to predict acute radiotherapy (RT) induced mucositis (MUC) and dysphagia (DYS) in head & neck cancer patients (pts). We enrolled 101 pts prospectively scored for acute toxicity with CTCAE. We considered four endpoints: grade≥2 (G2+) and grade≥3 (G3+) MUC, G2+, and G3+ DYS. We dichotomized the pATM concentration to define radiosensitive (RS) vs. radioresistant (RR) pts using previously described cutoffs for G2+ (57.8 ng/mL) and G3+ toxicity (46 ng/mL). We did RADIODTECT© and toxicity scoring blindly. We considered two already published NTCP models, including (i) the Equivalent Uniform Dose to the oral cavity (n = 0.05, EUD_OC, Odds Ratio [OR] = 1.02) and the mean dose to the parotid glands (Dmean_PG, OR = 1.06) for MUC and (ii) EUD_OC (OR = 1.04), the glottic larynx EUD (n = 0.35, EUD_GL, OR = 1.02) and the volume of pharyngeal constrictor muscles receiving>50Gy (V50Gy_CM, OR = 1.02) for DYS. To account for the association of toxicity with the dose distribution in multiple organs at risk (OARs), we derived a "Weighted Dose Score" (WDS) as a linear combination of the dose factors, using their β-coefficients (= lnOR) as weights. WDS for MUC (WDS_OM) = 0.06*Dmean_PG + 0.02*EUD_OC WDS for DYS (WDS_DYS) = 0.02*V50Gy_CM + 0.02*EUD_GL + 0.04*EUD_OC We used WDS as a comprehensive dose feature to fit a dose response and allowed WDS50 (i.e., the WDS associated with 50% toxicity probability) to be different for RR (WDS50_RR) and RS pts (WDS50_RS). The dose-modifying factor (DMF) is the ratio of WDS50_RS/WDS50_RR. It measures the horizontal shift of the dose-response curve when comparing RS vs. RR pts. We scored G2+ and G3+ MUC in 80 and 41 pts; G2+ and G3+ DYS in 73 and 35 pts. The average concentration of pATM was 57.4ng/mL (sd 22.3ng/mL): 53/101 pts were classified as RS for G2+ toxicity and 35/101 as RS for G3+. On the whole cohort, the RADIODTECT© did not significantly associate with the risk of toxicity. However, we found two different dose-response curves at low WDS. There, the intrinsic biological sensitivity significantly affects the toxicity probability: ORs for RADIODTECT© are 2.6/2.4 for G2+/G3+ DYS, 6.4/2.9 for G2+/G3+ MUC. Furthermore, the difference in the incidence of side effects in RR vs. RS pts decreases as the WDS increases, reaching a region where the doses of OARs play a significant role. When combined with WDS, the RADIODTECT© effectively predicted RS pts, with DMF ranging from 0.77 for G3+ DYS to 0.40 for G2+ MUC. These findings support the hypothesis that dose and biomarkers act synergistically; biologically based radiosensitivity plays a significant role when OARs are exposed at lower doses, while high doses of OARs determine toxicity irrespective of the underlying single pt biological characterization.

Managing RT Schedules of Early-Stage Breast Cancer Patients with a Genetic-Dosimetric Validated Model for Late Fibrosis

Define a multifactorial risk prediction model for RT-induced fibrosis and investigate the benefit of a personalized approach for breast cancer (BC) patients (pts) treated with whole breast RT. In a previous study, we confirmed the predictive role of 30 SNPs from the literature and built an interaction aware Polygenic Risk Score (PRS, following the methods from Franco RO 2021) for Late Fibrosis (FG2+) on a cohort of 1500 pts from the REQUITE EU/USA prospective observational study. The PRS weights the radiosensitive (RS) and radioresistant (RR) genetic components and can be included in NTCP models. In a subgroup from the same cohort (390 pts), we have also confirmed an NTCP model based on biologically Equivalent Uniform Dose (BEUD) from PTV DVHs for pts treated at 40-50 Gy and no RT boost. Here, we combine PRS and BEUD into a sigmoid model allowing PRS to modulate BEUD50 (BEUD leading to 50% FG2+), i.e., we permitted a personalized BEUD50. We can also consider this as translating the PRS into a personalized equivalent BEUD, which is added/subtracted to the treatment BEUD. We evaluated model performances through ROC-AUC, calibration plot and Precision-Recall AUC. A total of 381 pts had complete dosimetric/genetic data, prescribed dose 40-50 Gy, and no fibrotic alteration at RT start. We scored FG2+ in 87 pts (23%). PRS ranged from -13 (more RR pts) to 7 (more RS), and a unit in PRS corresponds to 5.3 Gy BEUD or 3 Gy in EQ EUD2 Gy. Table 1 summarizes model performances, with details for subgroups below/above the quartiles I/III of the BEUD distribution. The PRS-only model correctly describes the toxicity rates in the whole population (calibration slope/offset = 0/1). Still, it overestimates/underestimates the absolute risks in the low/high dose ranges. The integrated model improves AUC-ROC and AUC-PRC by 5% and 10% and guarantees a better calibration in pts receiving low/high BEUD to the PTV. We developed a multifactorial model for FG2+ based on two previously validated models and reported the improvement against single-factor models. The BEUD+PRS model is suitable for assisting clinicians in managing early-stage BC pts. The number of fractions or the daily dose could be reduced for RS pts. The integrated model resulted in a possible quantitative tool for driving the planning decision process. Also, it showed a better performance in the high BEUD region, suggesting the potential value of its extension toward RT including boost or ultra hypofractionation. We are testing this extension in the whole REQUITE cohort.

Chemotherapy and cryopreservation affects DNA repair foci in lymphocytes of breast cancer patients

Purpose Although breast cancer (BC) patients benefit from radiotherapy (RT), some radiosensitive (RS) patients suffer from side effects caused by ionizing radiation in healthy tissues. It is thought that RS is underlaid by a deficiency in the repair of DNA double-strand breaks (DSB). DNA repair proteins such as p53-binding protein 1 (53BP1) and phosphorylated histone H2AX (γH2AX), form DNA repair foci at the DSB locations and thus serve as DSB biomarkers. Peripheral blood lymphocytes (PBL) are commonly believed to be an appropriate cell system for RS assessment using DNA repair foci. The amount of DSB may also be influenced by chemotherapy (CHT), which is often chosen as the first treatment modality before RT. As it is not always possible to analyze blood samples immediately after collection, there is a need for cryopreservation of PBL in liquid nitrogen. However, cryopreservation may potentially affect the number of DNA repair foci. In this work, we studied the effect of cryopreservation and CHT on the amount of DNA repair foci in PBL of BC patients undergoing radiotherapy. Materials and methods The effect of cryopreservation was studied by immunofluorescence analysis of 53BP1 and γH2AX proteins at different time intervals after in vitro irradiation. The effect of chemotherapy was analyzed by fluorescent labelling of 53BP1 and γH2AX proteins in PBL collected before, during, and after RT. Results Higher number of primary 53BP1/γH2AX foci was observed in frozen cells indicating that cryopreservation affects the formation of DNA repair foci in PBL of BC patients. In CHT-treated patients, a higher number of foci were found before RT, but no differences were observed during and after the RT. Conclusions Cryopreservation is the method of choice for analyzing DNA repair residual foci, but only similarly treated and preserved cells should be used for comparison of primary foci. CHT induces DNA repair foci in PBL of BC patients, but this effect disappears during radiotherapy.

Assessment of Individual Radiosensitivity in Breast Cancer Patients Using a Combination of Biomolecular Markers

About 5% of patients undergoing radiotherapy (RT) develop RT-related side effects. To assess individual radiosensitivity, we collected peripheral blood from breast cancer patients before, during and after the RT, and γH2AX/53BP1 foci, apoptosis, chromosomal aberrations (CAs) and micronuclei (MN) were analyzed and correlated with the healthy tissue side effects assessed by the RTOG/EORTC criteria. The results showed a significantly higher level of γH2AX/53BP1 foci before the RT in radiosensitive (RS) patients in comparison to normal responding patients (NOR). Analysis of apoptosis did not reveal any correlation with side effects. CA and MN assays displayed an increase in genomic instability during and after RT and a higher frequency of MN in the lymphocytes of RS patients. We also studied time kinetics of γH2AX/53BP1 foci and apoptosis after in vitro irradiation of lymphocytes. Higher levels of primary 53BP1 and co-localizing γH2AX/53BP1 foci were detected in cells from RS patients as compared to NOR patients, while no difference in the residual foci or apoptotic response was found. The data suggested impaired DNA damage response in cells from RS patients. We suggest γH2AX/53BP1 foci and MN as potential biomarkers of individual radiosensitivity, but they need to be evaluated with a larger cohort of patients for clinics.

Evaluation of a Functional Assay for Radiosensitivity in the Pediatric Prospective Cohort ARPEGE

<h3>Purpose/Objective(s)</h3> Approximately 900 children/adolescents are treated with radiotherapy (RT) every year in France. However, among the 80% of survivors, the cumulative incidence of long-term morbidity – including second malignancies - reach 73.4% thirty years after the cancer diagnosis. Identifying a priori the subjects at risk for RT sequelae is a major challenge of pediatric oncology. Individual radiosensitivity (IRS) of children/adolescents is unknown at this time. The cellular response to radiation depends on the recognition and repair of radiation-induced DNA double-strand breaks (DSB). Unrepaired DSB as well as a delay in the intra nuclear activation of the pATM protein are common features to patients with RT toxicity. From these conclusions, we proposed and retrospectively validated a functional IRS immunofluorescence assay based on Radio-Induced ATM Nucleoshuttling (RIANS) (Granzotto et al, 2016). The purpose of this study was to define prospectively the predictive impact of RIANS assay in children. <h3>Materials/Methods</h3> Patients of the ARPEGE prospective open-label, non-randomized multicenter clinical trial were included in the study and prospectively evaluated for early toxicities. For each patient, skin samples were collected prior RT to raise a primary dermal fibroblast line and carry out in blind the RIANS assay. Different endpoints were measured: residual double-strand breaks at 24 h (γH2AX marker), pATM foci at 10 min and 1 h (pATM marker) and micronuclei at 24 h respectively after ex vivo radiation (2 Gy). The procedures were repeated in triplicates in blind in two independent expert centers (Neolys and Institut de Cancerologie de Lorraine). In parallel early toxicity was reported according to NCI-CTCAE v4.0 three months after the completion of RT. Patients with grade <2 or ≥2 toxicity were considered as radioresistant (RR) and radiosensitive (RS) respectively. We correlated the parameters of the RIANS assay according to toxicity with logistic regression. <h3>Results</h3> Among the 29 analyzable patients, 37 % exhibit brain cancers, 10% Hodgkin lymphomas, 10% nephroblastoma, 10% neuroblastoma, 10% Ewing cancer and 13% malignant mesenchymal cancer. The mean delivered dose was 32.5 Gy (range 1,5 - 60 Gy) with fractionation between 1.5 to 2 Gy. 16/29 (56%) patients were clinically considered as RS. There was no significant difference in total dose delivered between the two groups. Among the radiobiological factors tested, the number of Micronuclei at 24h post irradiation provided the best discrimination among RS patients (p-value= 0.0216). Overall, the RIANS assay provided the following performance: sensitivity=0.82, specificity=0.70 and AUC=0.75 (0.550-0.888). <h3>Conclusion</h3> ARPEGE is the first study to document the distribution of IRS in such a population. Screening hypersensitive patients would be a major step forward in the management of cancers, opening a way to personalized pediatric oncology.

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.

Diagnostic and Therapeutic Challenges for Infants with Radiosensitive (RS)-SCID Identified by Newborn Screening (NBS)

NBS for SCID has been universally implemented in the U.S. Patients with DNA double-strand break repair defects RS-SCID constitute a rare sub-group, who are susceptible to developing malignancies and non-lymphoid comorbidities. Here, we describe three patients and discuss challenges in clinical management of RS-SCID defects.

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.

Explore association of genes in PDL1/PD1 pathway to radiotherapy survival benefit based on interaction model strategy

PurposeTo explore the association of genes in “PD-L1 expression and PD-1 check point pathway in cancer” to radiotherapy survival benefit.Methods and materialsGene expression data and clinical information of cancers were downloaded from TCGA. Radiotherapy survival benefit was defined based on interaction model. Fast backward multivariate Cox regression was performed using stacking multiple interpolation data to identify radio-sensitive (RS) genes.ResultsAmong the 73 genes in PD-L1/PD-1 pathway, we identified 24 RS genes in BRCA data set, 25 RS genes in STAD data set and 20 RS genes in HNSC data set, with some crossover genes. Theoretically, there are two types of RS genes. The expression level of Type I RS genes did not affect patients' overall survival (OS), but when receiving radiotherapy, patients with different expression level of Type I RS genes had varied survival benefit. Oppositely, Type II RS genes affected patients' OS. And when receiving radiotherapy, those with lower OS could benefit a lot. Type II RS genes in BRCA had strong positive correlation and closely biological interactions. When performing cluster analysis using these related Type II RS genes, patients could be divided into RS group and non-RS group in BRCA and METABRIC data sets.ConclusionsOur study explored potential radio-sensitive biomarkers of several main cancer types in an important tumor immune checkpoint pathway and revealed a strong association between this pathway and radiotherapy survival benefit. New types of RS genes could be identified based on expanded definition to RS genes.

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.

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.

Identification of Radiotherapy-Associated Genes in Lung Adenocarcinoma by an Integrated Bioinformatics Analysis Approach

Radiotherapy (RT) plays an important role in the prognosis of lung adenocarcinoma (LUAD) patients, but the radioresistance (RR) of LUAD is still a challenge that needs to be overcome. The current study aimed to investigate LUAD patients with RR to illuminate the underlying mechanisms. We utilized gene set variation analysis (GSVA) and The Cancer Immunome Atlas (TCIA) database to characterize the differences in biological functions and neoantigen-coding genes between RR and radiosensitive (RS) patients. Weighted Gene co-expression network analysis (WGCNA) was used to explore the relationship between RT-related traits and hub genes in two modules, i.e., RR and RS; two representative hub genes for RR (MZB1 and DERL3) and two for RS (IFI35 and PSMD3) were found to be related to different RT-related traits. Further analysis of the hub genes with the Lung Cancer Explorer (LCE), PanglaoDB and GSVA resources revealed the differences in gene expression levels, cell types and potential functions. On this basis, the Tumor and Immune System Interaction Database (TISIDB) was used to identify the potential association between RR genes and B cell infiltration. Finally, we used the Computational Analysis of Resistance (CARE) database to identify specific gene-associated drugs for RR patients and found that GSK525762A and nilotinib might be promising candidates for RR treatment. Taken together, these results demonstrate that B cells in TME may have a significant impact on the RT and that these two drug candidates, GSK525762A and nilotinib, might be helpful for the treatment of RR patients.

Impaired DNA Repair Fidelity in a Breast Cancer Patient With Adverse Reactions to Radiotherapy.

We tested the hypothesis that differences in DNA double-strand break (DSB) repair fidelity underlies differences in individual radiosensitivity and, consequently, normal tissue reactions to radiotherapy. Fibroblast cultures derived from a radio-sensitive (RS) breast cancer patient with grade 3 adverse reactions to radiotherapy were compared with normal control (NC) and hyper-radiosensitive ataxia-telangiectasia mutated (ATM) cells. DSB repair and repair fidelity were studied by Southern blotting and hybridization to Alu repetitive sequence and to a specific 3.2-Mbp NotI restriction fragment on chromosome 21, respectively. Results for DNA repair kinetics using the NotI fidelity assay showed significant differences (P < 0.001) with higher levels of misrepaired (misrejoined and unrejoined) DSBs in RS and ATM compared with NC. At 24-h postradiation, the relative fractions of misrepaired DSBs were 10.64, 23.08, and 44.70% for NC, RS, and ATM, respectively. The Alu assay showed significant (P < 0.05) differences in unrepaired DSBs only between the ATM and both NC and RS at the time points of 12 and 24 h. At 24 h, the relative percentages of DSBs unrepaired were 1.33, 3.43, and 12.13% for NC, RS, and ATM, respectively. The comparison between the two assays indicated an average of 5-fold higher fractions of misrepaired (NotI assay) than unrepaired (Alu assay) DSBs. In conclusion, this patient with increased radiotoxicity displayed more prominent misrepaired than unrepaired DSBs, suggesting that DNA repair fidelity is a potential marker for the adverse reactions to radiotherapy. More studies are required to confirm these results and further develop DSB repair fidelity as a hallmark biomarker for interindividual differences in radiosensitivity.

MiR-219a-5p enhances the radiosensitivity of non-small cell lung cancer cells through targeting CD164

Lung cancer is one of the leading causes of cancer-associated mortality. Non-small cell lung carcinoma (NSCLC) accounts for 70–85% of the total cases of lung cancer. Radioresistance frequently develops in NSCLC in the middle and later stages of radiotherapy. We investigated the role of miR-219a-5p in radioresistance of NSCLC. miR-219a-5p expression in serum and lung tissue of lung cancer patients was lower than that in control. Compared with radiosensitive (RS) NSCLC patients, miR-219a-5p expression was decreased in serum and lung tissue in radioresistant patients. miR-219a-5p expression level was negatively associated with radioresistance in NSCLC cell lines. Up-regulation of miR-219a-5p increased radiosensitivity in radioresistant NSCLC cells in vitro and in vivo. Down-regulation of miR-219a-5p decreased radiosensitivity in radiosensitive A549 and H358 cells. miR-219a-5p could directly bind in the 3′UTR of CD164 and negatively regulated CD164 expression. CD164 expression was higher in radioresistant NSCLC tissues than RS tissues. Up-regulation of CD164 significantly inhibited miR-219a-5p-induced regulation of RS in radioresistant A549 and H358 cells. Down-regulation of CD164 significantly inhibited the effect of anti-miR-219a-5p on radiosensitive A549 and H358 cells. miR-219a-5p or down-regulation of CD164 could increase apoptosis and γ-H2A histone family member X (γ-H2AX) expression in radioresistant cells in vitro and in vivo. Up-regulation of CD164 could inhibit the effect of miR-219a-5p on apoptosis and γ-H2AX expression. Our results indicated that miR-219a-5p could inhibit CD164, promote DNA damage and apoptosis and enhance irradiation-induced cytotoxicity. The data highlight miR-219a-5p/CD164 pathway in the regulation of radiosensitivity in NSCLC and provide novel targets for potential intervention.

Tumor mutation burden, immune checkpoint crosstalk and radiosensitivity in single-cell RNA sequencing data of breast cancer

IntroductionWe analyzed transcriptional and mutational profile mainly focused on tumor mutation burden (TMB), immune checkpoint crosstalk, and radiosensitivity using scRNA-seq data derived from breast cancer and immune cells. Materials and methodsscRNA-seq transcriptome data were acquired from the GEO database (GSE75688). The radiosensitivity index (RSI) was used to evaluate radiosensitivity of each cell. CD274 mRNA expression was used to surrogate PD-L1 expression status. A computational approach was utilized for the immune and tumor cell group (N = 492) to identify potential interactions between tumor and immune cells with respect to immune checkpoint ligand–receptor gene pairs. Mutation data was profiled from raw scRNA-seq data of tumor cells acquired from both primary tumor and metastatic lymph node (N = 317). TMB and mutational signatures were compared between radiosensitive (RS) and radioresistant (RR) tumor cells. ResultsMost RR cells were a basal subtype and showed the higher rate of PD-L1 positivity. The patients with TNBC or HER2 subtype showed increased number of immune checkpoint ligand-receptor interactions between tumor and immune cells. PD-L1 ligand–receptor interactions between tumor cells and T cells were differentially increased in patients with the HER2 subtype compared to patients with the luminal subtype. Meanwhile, CTLA-4 ligand–receptor interactions were increased in patients with the TNBC subtype. TMB was significantly higher in RR cells than RS cells. Mutational signatures including microsatellite instability (MSI) and NRF2 pathway were altered in RR cells. ConclusionsRR cells exhibited a basal subtype, high PD-L1 expression, and high TMB with mutational signature found in tumors having MSI. Differential crosstalk between tumor and immune cells was associated with the patient subtype of breast cancer. These findings could be useful to identify potential biomarker(s) and optimal combination strategies of immune checkpoint blockades and radiation therapy in the management of breast cancer.