Facile and direct detection of human papillomavirus (HPV) DNA in cells using loop-mediated isothermal amplification (LAMP).

Human papillomavirus (HPV)-mediated cancers, particularly cervical and oropharyngeal cancer, lead to hundreds of thousands of deaths worldwide each year. Simple, straightforward, and cost-effective detection of HPV DNA from patients with these malignancies or at risk for developing cancer can improve outcomes for patients, serving as a tool for early detection, monitoring treatment response, and assessment of cancer recurrence. Loop-mediated isothermal amplification (LAMP) is a simple and robust method for the detection and amplification of DNA in a single tube, utilizing the Bst strand-displacing DNA polymerase. We developed a workflow utilizing LAMP for the visual detection of HPV DNA in oral rinses. We demonstrate that LAMP is able to easily discriminate between two of the high-risk HPV subtypes, HPV16 and HPV18. We then utilized LAMP to visually detect HPV DNA directly from cells in oral rinses, mimicking a clinical inspired scenario of detecting HPV DNA in clinical samples. Our results suggest that LAMP is a robust, colorimetric assay method for the detection of HPV DNA in complex cellular samples, and further development is warranted to bring LAMP into the clinic.

Musashi1 Impacts Radio-Resistance in Glioblastoma by Controlling DNA-Protein Kinase Catalytic Subunit.

The conserved RNA-binding protein Musashi1 (MSI1) has been characterized as a stem cell marker, controlling the balance between self-renewal and differentiation and as a key oncogenic factor in numerous solid tumors, including glioblastoma. To explore the potential use of MSI1 targeting in therapy, we studied MSI1 in the context of radiation sensitivity. Knockdown of MSI1 led to a decrease in cell survival and an increase in DNA damage compared to control in cells treated with ionizing radiation. We subsequently examined mechanisms of double-strand break repair and found that loss of MSI1 reduces the frequency of nonhomologous end-joining. This phenomenon could be attributed to the decreased expression of DNA-protein kinase catalytic subunit, which we have previously identified as a target of MSI1. Collectively, our results suggest a role for MSI1 in double-strand break repair and that its inhibition may enhance the effect of radiotherapy.

RNA binding protein HuR regulates the expression of ABCA1.

ABCA1 is a major regulator of cellular cholesterol efflux and plasma HDL biogenesis. Even though the transcriptional activation of ABCA1 is well established, the posttranscriptional regulation of ABCA1 expression is poorly understood. Here, we investigate the potential contribution of the RNA binding protein (RBP) human antigen R (HuR) on the posttranscriptional regulation of ABCA1 expression. RNA immunoprecipitation assays demonstrate a direct interaction between HuR and ABCA1 mRNA. We found that HuR binds to the 3' untranslated region of ABCA1 and increases ABCA1 translation, while HuR silencing reduces ABCA1 expression and cholesterol efflux to ApoA1 in human hepatic (Huh-7) and monocytic (THP-1) cells. Interestingly, cellular cholesterol levels regulate the expression, intracellular localization, and interaction between HuR and ABCA1 mRNA. Finally, we found that HuR expression was significantly increased in macrophages from human atherosclerotic plaques, suggesting an important role for this RBP in controlling macrophage cholesterol metabolism in vivo. In summary, we have identified HuR as a novel posttranscriptional regulator of ABCA1 expression and cellular cholesterol homeostasis, thereby opening new avenues for increasing cholesterol efflux from atherosclerotic foam macrophages and raising circulat-ing HDL cholesterol levels.

Detailed Image Data Quality and Cleaning Practices for Artificial Intelligence Tools for Breast Cancer.

Standardizing image-data preparation practices to improve accuracy/consistency of AI diagnostic tools.

The RNA-binding protein Musashi1 affects medulloblastoma growth via a network of cancer-related genes and is an indicator of poor prognosis.

Musashi1 (Msi1) is a highly conserved RNA-binding protein that is required during the development of the nervous system. Msi1 has been characterized as a stem cell marker, controlling the balance between self-renewal and differentiation, and has also been implicated in tumorigenesis, being highly expressed in multiple tumor types. We analyzed Msi1 expression in a large cohort of medulloblastoma samples and found that Msi1 is highly expressed in tumor tissue compared with normal cerebellum. Notably, high Msi1 expression levels proved to be a sign of poor prognosis. Msi1 expression was determined to be particularly high in molecular subgroups 3 and 4 of medulloblastoma. We determined that Msi1 is required for tumorigenesis because inhibition of Msi1 expression by small-interfering RNAs reduced the growth of Daoy medulloblastoma cells in xenografts. To characterize the participation of Msi1 in medulloblastoma, we conducted different high-throughput analyses. Ribonucleoprotein immunoprecipitation followed by microarray analysis (RIP-chip) was used to identify mRNA species preferentially associated with Msi1 protein in Daoy cells. We also used cluster analysis to identify genes with similar or opposite expression patterns to Msi1 in our medulloblastoma cohort. A network study identified RAC1, CTGF, SDCBP, SRC, PRL, and SHC1 as major nodes of an Msi1-associated network. Our results suggest that Msi1 functions as a regulator of multiple processes in medulloblastoma formation and could become an important therapeutic target.

Modeling gamma knife radiosurgical toxicity for multiple brain metastases.

BACKGROUND AND PURPOSE: Radiation oncology protocols for single fraction radiosurgery recommend setting dosing criteria based on assumed risk of radionecrosis, which can be predicted by the 12 Gy normal brain volume (V12). In this study, we show that tumor surface area (SA) and a simple power-law model using only preplan variables can estimate and minimize radiosurgical toxicity. MATERIALS AND METHODS: A 245-patient cohort with 1217 brain metastases treated with single or distributed Gamma Knife sessions was reviewed retrospectively. Univariate and multivariable linear regression models and power-law models determined which modeling parameters best predicted V12. The V12 power-law model, represented by a product of normalized Rx dose Rxn, and tumor longest axial dimension LAD (V12 âˆ¼ Rxn1.5*LAD2), was independently validated using a secondary 63-patient cohort with 302 brain metastases. RESULTS: Surface area was the best univariate linear predictor of V12 (adjR2 = 0.770), followed by longest axial dimension (adjR2 = 0.755) and volume (adjR2 = 0.745). The power-law model accounted for 90% variance in V12 for 1217 metastatic lesions (adjR2 = 0.906) and 245 patients (adjR2 = 0.896). The average difference ΔV12 between predicted and measured V12s was (0.28 ± 0.55) cm3 per lesion and (1.0 ± 1.2) cm3 per patient. The power-law predictive capability was validated using a secondary 63-patient dataset (adjR2 = 0.867) with 302 brain metastases (adjR2 = 0.825). CONCLUSION: Surface area was the most accurate univariate predictor of V12 for metastatic lesions. We developed a preplan model for brain metastases that can help better estimate radionecrosis risk, determine prescription doses given a target V12, and provide safe dose escalation strategies without the use of any planning software.

3D printed integrated bolus/headrest for radiation therapy for malignancies involving the posterior scalp and neck.

BACKGROUND: Malignancies of the head and neck region, encompassing cutaneous, mucosal, and sarcomatous histologies, are complex entities to manage, comprising of coordination between surgery, radiation therapy, and systemic therapy. Malignancies of the posterior scalp are particular challenging to treat with radiation therapy, given its irregular contours and anatomy as well as the superficial location of the target volume. Bolus material is commonly used in radiation therapy to ensure that the dose to the skin and subcutaneous tissue is appropriate and adequate, accounting for the buildup effect of megavoltage photon treatment. The use of commercially available bolus material on the posterior scalp potentially creates air gaps between the bolus and posterior scalp. CASE PRESENTATIONS: In this report, we created and utilized a custom 3D-printed integrated bolus and headrest for 5 patients to irradiate malignancies involving the posterior scalp, including those with cutaneous squamous cell carcinoma, melanoma, malignant peripheral nerve sheath tumor, and dermal sarcoma. Treatment setup was consistently reproducible, and patients tolerated treatment well without any unexpected adverse effects. CONCLUSIONS: We found that the use of this custom 3D-printed integrated bolus/headrest allowed for comfortable, consistent, and reproducible treatment set up while minimizing the risk of creating significant air gaps and should be considered in the radiotherapeutic management of patients with posterior scalp malignancies.

Socioeconomic and demographic determinants of radiation treatment and outcomes in glioblastoma patients.

Introduction: Poor outcomes in glioblastoma patients, despite advancing treatment paradigms, indicate a need to determine non-physiologic prognostic indicators of patient outcome. The impact of specific socioeconomic and demographic patient factors on outcomes is unclear. We sought to identify socioeconomic and demographic patient characteristics associated with patient survival and tumor progression, and to characterize treatment options and healthcare utilization. Methods: A cohort of 169 patients with pathologically confirmed glioblastomas treated at our institution was retrospectively reviewed. Multivariable cox proportional hazards analysis for overall survival (OS) and cumulative incidence of progression was performed. Differences in treatment regimen, patient characteristics, and neuro-oncology office use between different age and depressive disorder history patient subgroups were calculated two-sample t-tests, Fisher's exact tests, or linear regression analysis. Results: The median age of all patients at the time of initiation of radiation therapy was 60.5 years. The median OS of the cohort was 13.1 months. Multivariable analysis identified age (Hazard Ratio 1.02, 95% CI 1.00-1.04) and total resection (Hazard Ratio 0.52, 95% CI 0.33-0.82) as significant predictors of OS. Increased number of radiation fractions (Hazard Ratio 0.90, 95% CI 0.82-0.98), depressive disorder history (Hazard Ratio 0.59, 95% CI 0.37-0.95), and total resection (Hazard Ratio 0.52, 95% CI 0.31-0.88) were associated with decreased incidence of progression. Notably, patients with depressive disorder history were observed to have more neuro-oncology physician office visits over time (median 12 vs. 16 visits, p = 0.0121). Patients older than 60 years and those with Medicare (vs. private) insurance were less likely to receive as many radiation fractions (p = 0.0014) or receive temozolomide concurrently with radiation (Odds Ratio 0.46, p = 0.0139). Conclusion: Older glioblastoma patients were less likely to receive as diverse of a treatment regimen as their younger counterparts, which may be partially driven by insurance type. Patients with depressive disorder history exhibited reduced incidence of progression, which may be due to more frequent health care contact during neuro-oncology physician office visits.

Registration-guided deep learning image segmentation for cone beam CT-based online adaptive radiotherapy.

PURPOSE: Adaptive radiotherapy (ART), especially online ART, effectively accounts for positioning errors and anatomical changes. One key component of online ART process is accurately and efficiently delineating organs at risk (OARs) and targets on online images, such as cone beam computed tomography (CBCT). Direct application of deep learning (DL)-based segmentation to CBCT images suffered from issues such as low image quality and limited available contour labels for training. To overcome these obstacles to online CBCT segmentation, we propose a registration-guided DL (RgDL) segmentation framework that integrates image registration algorithms and DL segmentation models. METHODS: The RgDL framework is composed of two components: image registration and RgDL segmentation. The image registration algorithm transforms/deforms planning contours that were subsequently used as guidance by the DL model to obtain accurate final segmentations. We had two implementations of the proposed framework-Rig-RgDL (Rig for rigid body) and Def-RgDL (Def for deformable)-with rigid body (RB) registration or deformable image registration (DIR) as the registration algorithm, respectively, and U-Net as the DL model architecture. The two implementations of RgDL framework were trained and evaluated on seven OARs in an institutional clinical head-and-neck dataset. RESULTS: Compared to the baseline approaches using the registration or the DL alone, RgDLs achieved more accurate segmentation, as measured by higher mean Dice similarity coefficients (DSCs) and other distance-based metrics. Rig-RgDL achieved a DSC of 84.5% on seven OARs on average, higher than RB or DL alone by 4.5% and 4.7%. The average DSC of Def-RgDL was 86.5%, higher than DIR or DL alone by 2.4% and 6.7%. The inference time required by the DL model component to generate final segmentations of seven OARs was less than 1 s in RgDL. By examining the contours from RgDLs and DL case by case, we found that RgDL was less susceptible to image artifacts. We also studied how the performances of RgDL and DL vary with the size of the training dataset. The DSC of DL dropped by 12.1% as the number of training data decreased from 22 to 5, whereas RgDL only dropped by 3.4%. CONCLUSION: By incorporating the patient-specific registration guidance to a population-based DL segmentation model, RgDL framework overcame the obstacles associated with online CBCT segmentation, including low image quality and insufficient training data, and achieved better segmentation accuracy than baseline methods. The resulting segmentation accuracy and efficiency show promise for applying this RgDL framework for online ART.

T Stage and Pretreatment Standardized Uptake Values Predict Tumor Recurrence With 5-Fraction SABR in Early-Stage Non-Small Cell Lung Cancer.

Purpose: Five-fraction stereotactic ablative radiotherapy (SABR) regimens are frequently used to treat centrally located early-stage non-small cell lung cancer or disease in the proximity of the chest wall as a means of optimizing tumor control and reducing treatment toxicity. However, increasing these SABR regimens to 5 fractions may reduce tumor control outcomes. We sought to identify the clinical parameters predictive of treatment failures with these 5-fraction courses. Methods: Ninety patients with T1-2 non-small cell lung cancer were treated with 50 or 60 Gy in 5 fractions. Failure over time was modeled using cumulative incidences of local, regional, or distant failure, with death as a competing risk. Cox proportional hazards analysis for incidences of failure was performed to control for patient variables. Results: Of 90 patients, 24 of 53 patients with T1 tumors and 19 of 37 patients with T2 tumors received 50 Gy SABR, and the other 47 patients received 60 Gy. Two-year overall survival and progression-free survival for the whole cohort were 75.8% and 59.3%, respectively. Total SABR dose (50 vs 60 Gy) did not influence survival nor failure rates at 2 and 5 years. Within 2 years of treatment, 7.8% of all patients developed local failure. For all patient and tumor characteristics evaluated, only T stage and pretreatment positron emission tomography standardized uptake values served as predictors of local, regional, and distant failure at 2 and 5 years posttreatment on univariate and multivariable analysis. Conclusions: Five-fraction SABR provides excellent in-field control. T2 and high fluorodeoxyglucose uptake tumors have increased failure rates, suggesting the potential need for adjuvant therapies, which are being assessed in randomized phase 3 trials.

Impact of CDKN2A/B, MTAP, and TERT Genetic Alterations on Survival in IDH Wild Type Glioblastomas.

PURPOSE: Poor outcomes in IDH wild-type (IDHwt) glioblastomas indicate the need to determine which genetic alterations can indicate poor survival and guidance of patient specific treatment options. We sought to identify the genetic alterations in these patients that predict for survival when adjusting particularly for treatments and other genetic alterations. METHODS: A cohort of 167 patients with pathologically confirmed IDHwt glioblastomas treated at our institution was retrospectively reviewed. Next generation sequencing was performed for each patient to determine tumor genetic alterations. Multivariable cox proportional hazards analysis for overall survival (OS) was performed to control for patient variables. RESULTS: CDKN2A, CDKN2B, and MTAP deletion predict for worse OS independently of other genetic alterations and patient characteristics (hazard ratio [HR] 2.192, p = 0.0017). Patients with CDKN2A copy loss (HR 2.963, p = 0.0037) or TERT mutated (HR 2.815, p = 0.0008) glioblastomas exhibited significant associations between radiation dose and OS, while CDKN2A and TERT wild type patients did not. CDKN2A deleted patients with NF1 mutations had worse OS (HR 1.990, p = 0.0540), while CDKN2A wild type patients had improved OS (HR 0.229, p = 0.0723). Patients with TERT mutated glioblastomas who were treated with radiation doses < 45 Gy (HR 3.019, p = 0.0010) but not those treated with ≥ 45 Gy exhibited worse OS compared to those without TERT mutations. CONCLUSION: In IDHwt glioblastomas, CDKN2A, CDKN2B, and MTAP predict for poor prognosis. TERT and CDKN2A mutations are associated with worse survival only when treated with lower radiation doses, thus potentially providing a genetic marker that can inform clinicians on proper dose-fractionation schemes.

Neutrophilia and post-radiation thrombocytopenia predict for poor prognosis in radiation-treated glioma patients.

Introduction: Poor outcomes in glioma patients indicate a need to determine prognostic indicators of survival to better guide patient specific treatment options. While preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) have been suggested as prognostic systemic inflammation markers, the impact of post-radiation changes in these cell types is unclear. We sought to identify which hematologic cell measurements before, during, or after radiation predicted for patient survival. Methods: A cohort of 182 patients with pathologically confirmed gliomas treated at our institution was retrospectively reviewed. Patient blood samples were collected within one month before, during, or within 3 months after radiation for quantification of hematologic cell counts, for which failure patterns were evaluated. Multivariable cox proportional hazards analysis for overall survival (OS) and progression-free survival (PFS) was performed to control for patient variables. Results: Multivariable analysis identified pre-radiation NLR > 4.0 (Hazard ratio = 1.847, p = 0.0039) and neutrophilia prior to (Hazard ratio = 1.706, p = 0.0185), during (Hazard ratio = 1.641, p = 0.0277), or after (Hazard ratio = 1.517, p = 0.0879) radiation as significant predictors of worse OS, with similar results for PFS. Post-radiation PLR > 200 (Hazard ratio = 0.587, p = 0.0062) and a percent increase in platelets after radiation (Hazard ratio = 0.387, p = 0.0077) were also associated with improved OS. Patients receiving more than 15 fractions of radiation exhibited greater post-radiation decreases in neutrophil and platelet counts than those receiving fewer. Patients receiving dexamethasone during radiation exhibited greater increases in neutrophil counts than those not receiving steroids. Lymphopenia, changes in lymphocyte counts, monocytosis, MLR, and changes in monocyte counts did not impact patient survival. Conclusion: Neutrophilia at any time interval surrounding radiotherapy, pre-radiation NLR, and post-radiation thrombocytopenia, but not lymphocytes or monocytes, are predictors of poor patient survival in glioma patients.

The oncogenic RNA-binding protein Musashi1 is regulated by tumor suppressor miRNAs.

Musashi1 (Msi1) is an evolutionarily conserved RNA-binding protein that has been implicated in processes like stem cell fate, nervous system development, and tumorigenesis via its activities as a specific regulator of translation. While Msi1 is barely detected in normal adult tissue, it has been observed to be highly expressed in numerous tumor types (e.g. breast, colon, medulloblastoma, glioblastoma, and et cetera). Unfortunately, the molecular cues that are responsible for Msi1 upregulation in cancer cells are largely unknown. Tumor suppressor microRNAs (miRNAs) are known for targeting genes with oncogenic properties like Msi1 and for being either downregulated or deleted in tumor tissue. We observed that Msi1 long 3'UTR region is potentially targeted by several tumor suppressor miRNAs (miR-34a, -101, -128, -137, and -138). Western blotting of endogenous Msi1 protein as well as luciferase assays confirmed Msi1 regulation by these tumor suppressor miRNAs. Furthermore, we observed when examining different cellular states that these miRNAs and Msi1 have opposite expression profiles. Cell proliferation inhibition induced by the tumor suppressor miRNAs was partially rescued by Msi1 transgenic expression. We conclude that tumor suppressor miRNAs are direct and influential regulators of Msi1, affecting its expression pattern during tumorigenesis of malignant nervous system tumors.

Quality of Anatomic Staging of Breast Carcinoma in Hospitals in the United States, With Focus on Measurement of Tumor Dimension.

OBJECTIVES: We investigated the accuracy of clinical breast carcinoma anatomic staging and the greatest tumor dimension measurements. METHODS: We compared clinical stage and greatest dimension values with the pathologic reference standard values using 57,747 cases from the 2016 US National Cancer Institute Surveillance, Epidemiology, and End Results program who were treated by surgical resection without prior neoadjuvant therapy. RESULTS: Agreement for clinical vs pathologic anatomic TNM group stage, overall, is 74.3% ± 0.4%. Lymph node N staging overall agrees very well (85.1% ± 0.4%). Based on tumor dimension and location, T staging has an agreement of only 64.2% ± 0.4%, worsening to 55% without carcinoma in situ (Tis) cases. In approximately 25% of cases, pathologic T stage is higher than clinical T stage. The mean difference in the greatest dimension is 1.36 ± 9.59 mm with pathologic values being generally larger than clinical values; pathologic and clinical measurements correlate well. T-stage disagreement is associated with histology, tumor grade, tumor size, N stage, patient age, periodic biases in tumor size measurements, and overuse of family T-stage categories. Pathologic measurement biases include rounding and specimen-slicing intervals. CONCLUSIONS: Clinical and pathologic T-staging values agree only moderately. Pathologists face challenges in increasing the precision of gross tumor measurements, with the goal of improving the accuracy of clinical T staging and measurement.

Clinical Non-Small Cell Lung Cancer Staging and Tumor Length Measurement Results From U.S. Cancer Hospitals.

RATIONALE AND OBJECTIVES: Examine the accuracy of clinical non-small cell lung cancer staging and tumor length measurements, which are critical to prognosis and treatment planning. MATERIALS AND METHODS: Compare clinical and pathological staging and lengths using 10,320 2016 National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) and 559 2010-2018 non-SEER single-institute surgically-treated cases, and analyze modifiable causes of disagreement. RESULTS: The SEER clinical and pathological group-stages agree only 62.3% ± 0.9% over all stage categories. The lymph node N-stage agrees much better at 83.0% ± 1.0%, but the tumor length-location T-stage agrees only 57.7% ± 0.8% with approximately 29% of the cases having a greater pathology than clinical T-stage. Individual T-stage category agreements with respect to the number of pathology cases are Tis, T1a, T1b, T2a, T2b, T3, T4: 89.9% ± 10.0%; 78.7% ± 1.7%; 51.8% ± 1.9%; 46.1% ± 1.3%; 40.5% ± 3.1%; 44.1% ± 2.2%; 56.4% ± 4.7%, respectively. Most of the single-institute results statistically agree with SEER's. Excluding Tis cases, the mean difference in SEER tumor length is ∼1.18 ± 9.26 mm (confidence interval: 0.97-1.39 mm) with pathological lengths being longer than clinical lengths except for small tumors; the two measurements correlate well (Pearson-r >0.87, confidence interval: 0.86-0.87). Reasons for disagreement include the use of family-category descriptors (e.g., T1) instead of their subcategories (e.g., T1a and T1b), which worsens the T-stage agreement by over 15%. Disagreement is also associated with higher tumor grade, larger resected specimens, higher N-stage, patient age, and periodic biases in clinical and pathological tumor size measurements. CONCLUSIONS: By including preliminary non-small cell lung cancer clinical stage values in their evaluation, diagnostic radiologists can improve the accuracy of staging and standardize tumor-size measurements, which improves patient care.

Simplified, standardized methods to assess the accuracy of clinical cancer staging.

BACKGROUND: Hospitals lack intuitive methods to monitor their accuracy of clinical cancer staging, which is critical to treatment planning, prognosis, refinements, and registering quality data. METHODS: We introduce a tabulation framework to compare clinical staging with the reference-standard pathological staging, and quantify systematic errors. As an example, we analyzed 9,644 2016 U.S. National Cancer Institute SEER surgically-treated non-small cell lung cancer (NSCLC) cases, and computed concordance with different denominators to compare with incompatible past results. RESULTS: The concordance for clinical versus pathological lymph node N-stage is very good, 83.4 ± 1.0%, but the tumor length-location T-stage is only 58.1 ± 0.9%. There are intuitive insights to the causes of discordance. Approximately 29% of the cases are pathological T-stage greater than clinical T-stage, and 12% lower than the clinical T-stage, which is due partly to the fact that surgically-treated NSCLC are typically lower-stage cancer cases, which results in a bounded higher probability for pathological upstaging. Individual T-stage categories Tis, T1a, T1b, T2a, T2b, T3, T4 invariant percent-concordances are 85.2 ± 9.7 + 10.3%; 72.7 ± 1.6 + 11.3%; 46.6 ± 1.8 + 10.9%; 54.6 ± 1.6 - 20.5%; 41.6 ± 3.3 - 0.1%; 54.7 ± 2.8 - 24.1%; 55.2 ± 4.7 + 2.6%, respectively. Each percent-concordance is referenced to an averaged number of pathological and clinical cases. The first error number quantifies statistical fluctuations; the second quantifies clinical and pathological staging biases. Lastly, comparison of over and under staging versus clinical characteristics provides further insights. CONCLUSIONS: Clinical NSCLC staging accuracy and concordance with pathological values can improve. As a first step, the framework enables standardizing comparing staging results and detecting possible problem areas. Cancer hospitals and registries can implement the efficient framework to monitor staging accuracy.

Publisher Correction: Genomic analyses of early responses to radiation in glioblastoma reveal new alterations at transcription, splicing, and translation levels.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genomic analyses of early responses to radiation inglioblastoma reveal new alterations at transcription,splicing, and translation levels.

High-dose radiation is the main component of glioblastoma therapy. Unfortunately, radio-resistance is a common problem and a major contributor to tumor relapse. Understanding the molecular mechanisms driving response to radiation is critical for identifying regulatory routes that could be targeted to improve treatment response. We conducted an integrated analysis in the U251 and U343 glioblastoma cell lines to map early alterations in the expression of genes at three levels: transcription, splicing, and translation in response to ionizing radiation. Changes at the transcriptional level were the most prevalent response. Downregulated genes are strongly associated with cell cycle and DNA replication and linked to a coordinated module of expression. Alterations in this group are likely driven by decreased expression of the transcription factor FOXM1 and members of the E2F family. Genes involved in RNA regulatory mechanisms were affected at the mRNA, splicing, and translation levels, highlighting their importance in radiation-response. We identified a number of oncogenic factors, with an increased expression upon radiation exposure, including BCL6, RRM2B, IDO1, FTH1, APIP, and LRIG2 and lncRNAs NEAT1 and FTX. Several of these targets have been previously implicated in radio-resistance. Therefore, antagonizing their effects post-radiation could increase therapeutic efficacy. Our integrated analysis provides a comprehensive view of early response to radiation in glioblastoma. We identify new biological processes involved in altered expression of various oncogenic factors and suggest new target options to increase radiation sensitivity and prevent relapse.