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Interferon regulatory factor 4 (IRF4), a critical member of the IRF transcription factor family, harbors an elusive biological role in cervical cancer. Through immunohistochemical staining and immunoblotting, CCK‐8 viability assays, EdU incorporation tests, clonogenic survival experiments, flow cytometric detection, transmission electron microscopy, immunofluorescence staining and heterotopic transplantation model, we discover that IRF4 expression was markedly decreased in cervical cancer tissues and cell lines compared to normal controls. Overexpression of IRF4 suppressed proliferation, migration, and invasion in both Siha and HeLa cells, while concurrently enhancing radiosensitivity. Mechanistically, IRF4 upregulated autophagy‐related proteins (LC3, Beclin‐1) and promoted autophagosome formation, while downregulating P62 by inhibiting the PI3K/Akt/mTOR pathway. In vivo studies demonstrated that IRF4 augmented the tumor response to radiation and further potentiated the effects when combined with rapamycin treatment, confirming its pivotal role in promoting radiosensitivity through PI3K/Akt/mTOR‐mediated autophagy. IRF4 emerges as a critical regulator of cervical cancer progression via modulation of autophagy and influences the tumor's response to radiotherapy. It holds promise as a potential therapeutic target to enhance cervical cancer radiosensitivity.

Owing to advances in radiotherapy, the physical properties of radiation can be optimized to enable individualized treatment; however, optimization is rarely based on biological properties and, therefore, treatments are generally planned with the assumption that all tumours respond similarly to radiation. Radiation affects multiple cellular pathways, including DNA damage, hypoxia, proliferation, stem cell phenotype and immune response. In this Review, we summarize the effect of these pathways on tumour responses to radiotherapy and the current state of research on genomic classifiers designed to exploit these variations to inform treatment decisions. We also discuss whether advances in genomics have generated evidence that could be practice changing and whether advances in genomics are now ready to be used to guide the delivery of radiotherapy alone or in combination.Although radiotherapy affects multiple cellular pathways, treatments are generally planned with the assumption that all tumours respond similarly to radiation. The authors of this Review summarize the effect of various pathways activated by radiotherapy on tumour responses to radiotherapy and present the current knowledge on genomic classifiers designed to inform treatment decisions.

Conventional external beam radiotherapy is the standard palliative treatment for spinal metastases; however, complete response rates for pain are as low as 10–20%. Stereotactic body radiotherapy delivers high-dose, ablative radiotherapy. We aimed to compare complete response rates for pain after stereotactic body radiotherapy or conventional external beam radiotherapy in patients with painful spinal metastasis. This open-label, multicentre, randomised, controlled, phase 2/3 trial was done at 13 hospitals in Canada and five hospitals in Australia. Patients were eligible if they were aged 18 years and older, and had painful (defined as ≥2 points with the Brief Pain Inventory) MRI-confirmed spinal metastasis, no more than three consecutive vertebral segments to be included in the treatment volume, an Eastern Cooperative Oncology Group performance status of 0–2, a Spinal Instability Neoplasia Score of less than 12, and no neurologically symptomatic spinal cord or cauda equina compression. Patients were randomly assigned (1:1) with a web-based, computer-generated allocation sequence to receive either stereotactic body radiotherapy at a dose of 24 Gy in two daily fractions or conventional external beam radiotherapy at a dose of 20 Gy in five daily fractions using standard techniques. Treatment assignment was done centrally by use of a minimisation method to achieve balance for the stratification factors of radiosensitivity, the presence or absence of mass-type tumour (extraosseous or epidural disease extension, or both) on imaging, and centre. The primary endpoint was the proportion of patients with a complete response for pain at 3 months after radiotherapy. The primary endpoint was analysed in the intention-to-treat population and all safety and quality assurance analyses were done in the as-treated population (ie, all patients who received at least one fraction of radiotherapy). The trial is registered with ClinicalTrials.gov, NCT02512965. Between Jan 4, 2016, and Sept 27, 2019, 229 patients were enrolled and randomly assigned to receive conventional external beam radiotherapy (n=115) or stereotactic body radiotherapy (n=114). All 229 patients were included in the intention-to-treat analysis. The median follow-up was 6·7 months (IQR 6·3–6·9). At 3 months, 40 (35%) of 114 patients in the stereotactic body radiotherapy group, and 16 (14%) of 115 patients in the conventional external beam radiotherapy group had a complete response for pain (risk ratio 1·33, 95% CI 1·14–1·55; p=0·0002). This significant difference was maintained in multivariable-adjusted analyses (odds ratio 3·47, 95% CI 1·77–6·80; p=0·0003). The most common grade 3–4 adverse event was grade 3 pain (five [4%] of 115 patients in the conventional external beam radiotherapy group vs five (5%) of 110 patients in the stereotactic body radiotherapy group). No treatment-related deaths were observed. Stereotactic body radiotherapy at a dose of 24 Gy in two daily fractions was superior to conventional external beam radiotherapy at a dose of 20 Gy in five daily fractions in improving the complete response rate for pain. These results suggest that use of conformal, image-guided, stereotactically dose-escalated radiotherapy is appropriate in the palliative setting for symptom control for selected patients with painful spinal metastases, and an increased awareness of the need for specialised and multidisciplinary involvement in the delivery of end-of-life care is needed. Canadian Cancer Society and the Australian National Health and Medical Research Council.

N6-methyladenosine (m6A) is the most abundant epitranscriptome modification in mammalian mRNA. Recent years have seen substantial progress in m6A epitranscriptomics, indicating its crucial roles in the initiation and progression of cancer through regulation of RNA stabilities, mRNA splicing, microRNA processing and mRNA translation. However, by what means m6A is dynamically regulated or written by enzymatic components represented by methyltransferase-like 3 (METTL3) and how m6A is significant for each of the numerous genes remain unclear. We focused on METTL3 in pancreatic cancer, the prognosis of which is not satisfactory despite the development of multidisciplinary therapies. We established METTL3-knockdown pancreatic cancer cell line using short hairpin RNA. Although morphologic and proliferative changes were unaffected, METTL3-depleted cells showed higher sensitivity to anticancer reagents such as gemcitabine, 5-fluorouracil, cisplatin and irradiation. Our data suggest that METTL3 is a potent target for enhancing therapeutic efficacy in patients with pancreatic cancer. In addition, we performed cDNA expression analysis followed by Gene Ontology and protein-protein interaction analysis using the Database for Annotation, Visualization, and Integrated Discovery and Search Tool for the Retrieval of Interacting Genes/Proteins databases, respectively. The results demonstrate that METTL3 was associated with mitogen-activated protein kinase cascades, ubiquitin-dependent process and RNA splicing and regulation of cellular process, suggesting functional roles and targets of METTL3.

Radioresistance is a principal culprit for the failure of radiotherapy in hepatocellular carcinoma (HCC). Insights on the regulation genes of radioresistance and underlying mechanisms in HCC are awaiting for profound investigation. In this study, the suppressor of cytokine signaling 2 (SOCS2) were screened out by RNA-seq and bioinformatics analyses as a potential prognosis predictor of HCC radiotherapy and then were determined to promote radiosensitivity in HCC both in vivo or in vitro. Meanwhile, the measurements of ferroptosis negative regulatory proteins of solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4), intracellular lipid peroxidation and Fe2+ concentration suggested that a high level of ferroptosis contributed to the radiosensitization of HCC. Moreover, SOCS2 and SLC7A11 were expressed oppositely in HCC clinical tissues and tumour xenografts with different radiosensitivities. Mechanistically, the N-terminal domain of SLC7A11 was specifically recognized by the SH2-structural domain of SOCS2. While the L162 and C166 of SOCS2-BOX region could bind elongin B/C compound to co-form a SOCS2/elongin B/C complex to recruit ubiquitin molecules. Herein, SOCS2 served as a bridge to transfer the attached ubiquitin to SLC7A11 and promoted K48-linked polyubiquitination degradation of SLC7A11, which ultimately led to the onset of ferroptosis and radiosensitization of HCC. In conclusion, it was demonstrated for the first time that high-expressed SOCS2 was one of the biomarkers predicting radiosensitivity of HCC by advancing the ubiquitination degradation of SLC7A11 and promoting ferroptosis, which indicates that targeting SOCS2 may enhance the efficiency of HCC radiotherapy and improve the prognosis of patients.

Background Prediction of radiobiological response is a major challenge in radiotherapy. Of several radiobiological models, the linear-quadratic (LQ) model has been best validated by experimental and clinical data. Clinically, the LQ model is mainly used to estimate equivalent radiotherapy schedules (e.g. calculate the equivalent dose in 2 Gy fractions, EQD 2 ), but increasingly also to predict tumour control probability (TCP) and normal tissue complication probability (NTCP) using logistic models. The selection of accurate LQ parameters α, β and α/β is pivotal for a reliable estimate of radiation response. The aim of this review is to provide an overview of published values for the LQ parameters of human tumours as a guideline for radiation oncologists and radiation researchers to select appropriate radiobiological parameter values for LQ modelling in clinical radiotherapy. Methods and materials We performed a systematic literature search and found sixty-four clinical studies reporting α, β and α/β for tumours. Tumour site, histology, stage, number of patients, type of LQ model, radiation type, TCP model, clinical endpoint and radiobiological parameter estimates were extracted. Next, we stratified by tumour site and by tumour histology. Study heterogeneity was expressed by the I 2 statistic, i.e. the percentage of variance in reported values not explained by chance. Results A large heterogeneity in LQ parameters was found within and between studies (I 2  > 75%). For the same tumour site, differences in histology partially explain differences in the LQ parameters: epithelial tumours have higher α/β values than adenocarcinomas. For tumour sites with different histologies, such as in oesophageal cancer, the α/β estimates correlate well with histology. However, many other factors contribute to the study heterogeneity of LQ parameters, e.g. tumour stage, type of LQ model, TCP model and clinical endpoint (i.e. survival, tumour control and biochemical control). Conclusions The value of LQ parameters for tumours as published in clinical radiotherapy studies depends on many clinical and methodological factors. Therefore, for clinical use of the LQ model, LQ parameters for tumour should be selected carefully, based on tumour site, histology and the applied LQ model. To account for uncertainties in LQ parameter estimates, exploring a range of values is recommended.

Long noncoding RNAs (lncRNAs) play important roles in regulating the development and progression of many cancers. However, the clinical significance of specific lncRNAs in the context of nasopharyngeal carcinoma (NPC) and the molecular mechanisms by which they regulate this form of cancer remain largely unclear. In this study we found that the lncRNA PVT1 was upregulated in NPC, and that in patients this upregulation was associated with reduced survival. RNA sequencing revealed that PVT1 was responsible for regulating NPC cell proliferation and for controlling a hypoxia-related phenotype in these cells. PVT1 knockdown reduced NPC cell proliferation, colony formation, and tumorigenesis in a subcutaneous mouse xenograft model systems. We further found that PVT1 serves as a scaffold for the chromatin modification factor KAT2A, which mediates histone 3 lysine 9 acetylation (H3K9), recruiting the nuclear receptor binding protein TIF1β to activate NF90 transcription, thereby increasing HIF-1α stability and promoting a malignant phenotype in NPC cells. Overexpression of NF90 or HIF-1α restored the proliferation in cells that had ceased proliferating due to PVT1 or KAT2A depletion. Conversely, overexpression of active KAT2A or TIF1β, but not of KAT2A acetyltransferase activity-deficient mutants or TIF1β isoforms lacking H3K9ac binding sites, promoted a PVT1-mediated increase in NF90 transcription, as well as increased HIF-1α stability and cell proliferation. PVT1 knockdown enhanced the radiosensitization effect in NPC cells via inhibiting binding between H3K9ac and TIF1β in a manner. Taken together, our results demonstrate that PVT1 serves an oncogenic role and plays an important role in radiosensitivity in malignant NPC via activating the KAT2A acetyltransferase and stabilizing HIF-1α.

Background Solute carrier family 7 member 11(SLC7A11) is a component of cysteine/glutamate transporter, which plays a key role in tumor growth; however, its underlying effect on radiosensitivity in esophageal squamous cell carcinoma (ESCC) remains unclear. This study aimed to clarify SLC7A11’s expression and correlation with nuclear expression of nuclear factor erythroid-2 ( NRF2)-associated radioresistance in ESCC. Methods We included 127 ESCC patients who received radical chemoradiotherapy. Immunohistochemical staining was used to detect SLC7A11 and NRF2 nuclear expression, and the relationship between clinicopathological characteristics and survival rates or therapy response were evaluated. Western blot, dual-reporter assays and Chromatin immunoprecipitation (ChIP)-sequencing were used to analyze their relationship in vitro. Their roles in radioresistance were then investigated through multiple validation steps. Results NRF2 nuclear expression and SLC7A11 expression were overexpressed in ESCC tissues and were positively correlated with one another. NRF2 nuclear expression was significantly associated with tumor length, lymph node metastasis, and TNM stage, while SLC7A11 expression was associated with lymph node metastasis. Patients with high NRF2 nuclear expression and SLC7A11 expression had significantly shorter overall and progression-free survival, and poor treatment response. The multivariate model showed that NRF2 nuclear expression and SLC7A11 expression, sex and tumor location are independent prognostic factors. In vitro analysis confirmed that hyperactivation of NRF2 induced SLC7A11 expression by directly binding to its promoter region, promoting radioresistance, reducing radiotherapy-induced lipid peroxidation levels, PTGS2 expression, and radiotherapy-related ferroptosis morphologic features. Conclusion Our study reveals a connection between high SLC7A11 expression and NRF2 nuclear expression in patients with ESCC that was related to worse survival and poorer therapy outcomes. SLC7A11-mediated ferroptosis inhibition induced NRF2-associated radioresistance, highlighting potential of NRF2/SLC7A11/ferroptosis axis as future therapeutic targets against therapy resistance biomarker.

[This corrects the article DOI: 10.1371/journal.pone.0199312.].

Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitivity is not currently implemented clinically due to insufficient accuracy of existing machine learning classifiers. Despite the acknowledged role of tumor metabolism in radiation response, metabolomics data is rarely collected in large multi-omics initiatives such as The Cancer Genome Atlas (TCGA) and consequently omitted from algorithm development. In this study, we circumvent the paucity of personalized metabolomics information by characterizing 915 TCGA patient tumors with genome-scale metabolic Flux Balance Analysis models generated from transcriptomic and genomic datasets. Metabolic biomarkers differentiating radiation-sensitive and -resistant tumors are predicted and experimentally validated, enabling integration of metabolic features with other multi-omics datasets into ensemble-based machine learning classifiers for radiation response. These multi-omics classifiers show improved classification accuracy, identify clinical patient subgroups, and demonstrate the utility of personalized blood-based metabolic biomarkers for radiation sensitivity. The integration of machine learning with genome-scale metabolic modeling represents a significant methodological advancement for identifying prognostic metabolite biomarkers and predicting radiosensitivity for individual patients. Personalized prediction of tumor radiosensitivity would facilitate development of precision medicine workflows for cancer treatment. Here, the authors integrate machine learning and genome-scale metabolic modeling approaches to identify multi-omics biomarkers predictive of radiation response.