Ferroptosis: a critical mechanism of N6-methyladenosine modification involved in carcinogenesis and tumor progression.

Ferroptosis is an iron-dependent regulatory cell necrosis induced by iron overload and lipid peroxidation. It occurs when multiple redox-active enzymes are ectopically expressed or show abnormal function. Hence, the precise regulation of ferroptosis-related molecules is mediated across multiple levels, including transcriptional, posttranscriptional, translational, and epigenetic levels. N6-methyladenosine (m6A) is a highly evolutionarily conserved epigenetic modification in mammals. The m6A modification is commonly linked to tumor proliferation, progression, and therapy resistance because it is involved in RNA metabolic processes. Intriguingly, accumulating evidence suggests that dysregulated ferroptosis caused by the m6A modification drives tumor development. In this review, we summarized the roles of m6A regulators in ferroptosis-mediated malignant tumor progression and outlined the m6A regulatory mechanism involved in ferroptosis pathways. We also analyzed the potential value and application strategies of targeting m6A/ferroptosis pathway in the clinical diagnosis and therapy of tumors.

Identifying gray matter alterations in Cushing's disease using machine learning: An interpretable approach.

BACKGROUND: Cushing's Disease (CD) is a rare clinical syndrome characterized by excessive secretion of adrenocorticotrophic hormone, leading to significant functional and structural brain alterations as observed in Magnetic Resonance Imaging (MRI). While traditional statistical analysis has been widely employed to investigate these MRI changes in CD, it has lacked the ability to predict individual-level outcomes. PURPOSE: To address this problem, this paper has proposed an interpretable machine learning (ML) framework, including model-level assessment, feature-level assessment, and biology-level assessment to ensure a comprehensive analysis based on structural MRI of CD. METHODS: The ML framework has effectively identified the changes in brain regions in the stage of model-level assessment, verified the effectiveness of these altered brain regions to predict CD from normal controls in the stage of feature-level assessment, and carried out a correlation analysis between altered brain regions and clinical symptoms in the stage of biology-level assessment. RESULTS: The experimental results of this study have demonstrated that the Insula, Fusiform gyrus, Superior frontal gyrus, Precuneus, and the opercular portion of the Inferior frontal gyrus of CD showed significant alterations in brain regions. Furthermore, our study has revealed significant correlations between clinical symptoms and the frontotemporal lobes, insulin, and olfactory cortex, which also have been confirmed by previous studies. CONCLUSIONS: The ML framework proposed in this study exhibits exceptional potential in uncovering the intricate pathophysiological mechanisms underlying CD, with potential applicability in diagnosing other diseases.

Validation of Core Ingredients and Molecular Mechanism of Cinobufotalin Injection Against Liver Cancer.

Purpose: Cinobufotalin injection has obvious curative effects on liver cancer patients with less toxicity and fewer side effects than other therapeutic approaches. However, the core ingredients and mechanism underlying these anti-liver cancer effects have not been fully clarified due to its complex composition. Methods: Multidimensional network analysis was used to screen the core ingredients, key targets and pathways underlying the therapeutic effects of cinobufotalin injection on liver cancer, and in vitro and in vivo experiments were performed to confirm the findings. Results: By construction of ingredient networks and integrated analysis, eight core ingredients and ten key targets were finally identified in cinobufotalin injection, and all of the core ingredients are tightly linked with the key targets, and these key targets are highly associated with the cell cycle-related pathways, supporting that both cinobufotalin injection and its core ingredients exert anti-liver cancer roles by blocking cell cycle-related pathways. Moreover, in vitro and in vivo experiments confirmed that either cinobufotalin injection or one of its core ingredients, cinobufagin, significantly inhibited cell proliferation, colony formation, cell cycle progression and xenograft tumor growth, and the key target molecules involved in the cell cycle pathway such as CDK1, CDK4, CCNB1, CHEK1 and CCNE1, exhibit consistent changes in expression after treatment with cinobufotalin injection or cinobufagin. Interestingly, some key targets CDK1, CDK4, PLK1, CHEK1, TTK were predicted to bind with multiple of core ingredients of cinobufotalin injection, and the affinity between one of the critical ingredients cinobufagin and key target CDK1 was further confirmed by SPR assay. Conclusion: Cinobufotalin injection was confirmed to includes eight core ingredients, and they play therapeutic effects in liver cancer by blocking cell cycle-related pathways, which provides important insights for the mechanism of cinobufotalin injection antagonizing liver cancer and the development of novel small molecule anti-cancer drugs.

CircBRD7 attenuates tumor growth and metastasis in nasopharyngeal carcinoma via epigenetic activation of its host gene.

BRD7 was identified as a tumor suppressor in nasopharyngeal carcinoma (NPC). Circular RNAs (CircRNAs) are involved in the occurrence and development of NPC as oncogenes or tumor suppressors. However, the function and mechanism of the circular RNA forms derived from BRD7 in NPC are not well understood. In this study, we first identified that circBRD7 was a novel circRNA derived from BRD7 that inhibited cell proliferation, migration, invasion of NPC cells, as well as the xenograft tumor growth and metastasis in vivo. Mechanistically, circBRD7 promoted the transcriptional activation and expression of BRD7 by enhancing the enrichment of histone 3 lysine 27 acetylation (H3K27ac) in the promoter region of its host gene BRD7, and BRD7 promoted the formation of circBRD7. Therefore, circBRD7 formed a positive feedback loop with BRD7 to inhibit NPC development and progression. Moreover, restoration of BRD7 expression rescued the inhibitory effect of circBRD7 on the malignant progression of NPC. In addition, circBRD7 demonstrated low expression in NPC tissues, which was positively correlated with BRD7 expression and negatively correlated with the clinical stage of NPC patients. Taken together, circBRD7 attenuates the tumor growth and metastasis of NPC by forming a positive feedback loop with its host gene BRD7, and targeting the circBRD7/BRD7 axis is a promising strategy for the clinical diagnosis and treatment of NPC.

Yin Yang 1 suppresses tumor invasion and metastasis in nasopharyngeal carcinoma by negatively regulating eIF4E transcriptional activity and expression.

Tumor metastasis is a leading cause of death in nasopharyngeal carcinoma (NPC) patients. Previous research has identified that transcription factor Yin Yang 1 (YY1) acts as a tumor suppressor that inhibits cell proliferation and tumor growth in NPC; however, the role and the molecular mechanisms of YY1 in NPC invasion and metastasis remain unclear. In this study, we discovered that YY1 could inhibit the migration and invasion of NPC cells in vitro as well as NPC xenograft tumor metastasis in vivo. Furthermore, we identified eIF4E as a direct downstream target of YY1, and YY1 could negatively regulate the expression of eIF4E at transcriptional level. Moreover, we found that eIF4E promoted the migration and invasion of NPC cells as well as NPC lung metastasis, suggesting its potential as a pro-metastatic mediator in NPC. Importantly, restoring eIF4E expression could partially reverse the inhibitory effects of YY1 on NPC malignancy. In consistent with these findings, the expression of YY1 was downregulated while eIF4E was upregulated in NPC patients with metastasis, and there was a negative correlation between YY1 and eIF4E expression. Collectively, our results indicate that YY1 suppresses the invasion and metastasis of NPC by negatively regulating eIF4E transcription. Therefore, targeting the YY1/eIF4E transcriptional axis could be a potential therapeutic strategy for the treatment of patients with NPC.

NOP2/Sun RNA methyltransferase 2 is a potential pan-cancer prognostic biomarker and is related to immunity.

BACKGROUND: NOP2/Sun RNA methyltransferase 2 (NSUN2), an important methyltransferase of m5C, has been poorly studied in cancers, and the relationship between NSUN2 and immunity remains largely unclear. Therefore, the purpose of this study was to explore the expression and prognostic value of NSUN2 and the role of NSUN2 in immunity in cancers. METHODS: The TIMER, CPTAC and other databases were used to analyze the expression of NSUN2, its correlation with clinical stage and its prognostic value across cancers. Moreover, the TISIDB, TIMER2.0 and Sangerbox platform were used to depict the relationships between NSUN2 and immune molecular subtypes, tumor-infiltrating lymphocytes (TILs), immune checkpoints (ICPs) and immunoregulatory genes. Furthermore, the NSUN2-interacting proteins and related genes as well as the coexpression networks of NSUN2 in LIHC, LUAD and HNSC were explored with the STRING, DAVID, GEPIA2 and LinkedOmics databases. Finally, the subcellular location and function of NSUN2 in HepG2, A549 and 5-8F cells were investigated by performing immunofluorescence, CCK-8 and wound healing assays. RESULTS: Overall, NSUN2 was highly expressed and related to a poor prognosis in most types of cancers and was also significantly associated with immune molecular subtypes in some cancer types. Furthermore, NSUN2 was significantly associated with the levels of ICPs and immunoregulatory genes. In addition, NSUN2 was found to be involved in a series of immune-related biological processes, such as the humoral immune response in LIHC and LUAD and T-cell activation and B-cell activation in HNSC. Immunofluorescence and CCK-8 assays also confirmed that NSUN2 was widely expressed in the nucleus and cytoplasm, and overexpression of NSUN2 promoted the proliferation and migration of HepG2, A549 and 5-8F cells. NSUN2 was also confirmed to positively regulate the expression of PD-L1. CONCLUSION: NSUN2 serves as a pan-cancer prognostic biomarker and is correlated with the immune infiltration of tumors.

Dissecting the roles and clinical potential of YY1 in the tumor microenvironment.

Yin-Yang 1 (YY1) is a member of the GLI-Kruppel family of zinc finger proteins and plays a vital dual biological role in cancer as an oncogene or a tumor suppressor during tumorigenesis and tumor progression. The tumor microenvironment (TME) is identified as the "soil" of tumor that has a critical role in both tumor growth and metastasis. Many studies have found that YY1 is closely related to the remodeling and regulation of the TME. Herein, we reviewed the expression pattern of YY1 in tumors and summarized the function and mechanism of YY1 in regulating tumor angiogenesis, immune and metabolism. In addition, we discussed the potential value of YY1 in tumor diagnosis and treatment and provided a novel molecular strategy for the clinical diagnosis and treatment of tumors.

BRD7 inhibits enhancer activity and expression of BIRC2 to suppress tumor growth and metastasis in nasopharyngeal carcinoma.

BRD7 functions as a crucial tumor suppressor in numerous malignancies including nasopharyngeal carcinoma (NPC). However, its function and exact mechanisms involved in tumor progression are not well understood. Here, we found that the B7BS was a potential enhancer region of BIRC2, and BRD7 negatively regulated the transcriptional activity and expression of BIRC2 by targeting the activation of the BIRC2 enhancer. Moreover, BIRC2 promoted cell proliferation, migration, invasion as well as xenograft tumor growth and metastasis in vivo, thus functioning as an oncogene in NPC. Furthermore, the recovery of BIRC2 expression could rescue the inhibitory effect of BRD7 on cell proliferation, migration, invasion and xenograft tumor growth and metastasis. In addition, BIRC2 was highly-expressed in NPC tissues, and positively correlated with the TNM stage and negatively correlated with the expression of BRD7. Therefore, these results suggest that BRD7 suppresses tumor growth and metastasis thus functioning as a tumor suppressor at least partially by negatively regulating the enhancer activity and expression of BIRC2, and targeting the BRD7/BIRC2 regulation axis might be a potential strategy for the diagnosis and treatment of NPC.

Identification of tumour-infiltrating myeloid subsets associated with overall survival in lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is a primary subtype of lung cancer with limited therapeutic options and poor prognosis, and tumour-infiltrating myeloid cells (TIMs) are key regulators of LUSC. However, the correlation between the abundance of TIM subtypes and clinical outcomes of LUSC remains unexplored. This study aimed to develop and validate a prognostic model for low- and high-risk patients with LUSC based on myeloid cell microenvironments. TIM markers in the tumoural (T) and stromal (S) regions were quantified using immunohistochemistry for 502 LUSC patients. L1-penalized Cox regression was used to develop a myeloid survival score (MSS) model based on the training cohort, followed by validation in distinct cohorts from multiple centres. RNA sequencing and immunostaining were used to examine the mechanisms of myeloid cells in LUSC progression and predict potential drug targets and therapeutic agents. Of the 12 myeloid markers, CD163T, CD163S, and S100A12T were highly associated with overall survival (OS) in LUSC patients. The MSS of the three myeloid signatures accurately categorized LUSC patients into risk categories, with an observable difference in OS between the training and validation cohorts. Tumours with high MSS were associated with enhanced antioxidative ability and hedgehog signalling and a shift to a more pro-tumorigenic microenvironment, accompanied by a reduced tumour cell immunogenicity and increased CD8+ T cell exhaustion patterns. Additionally, in high-risk patients, potential drug targets and compounds regulating hedgehog signalling were identified. Our study provides the first prognostic myeloid signature for LUSC, which may help advance precision medicine. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Deciphering the vital roles and mechanism of m5C modification on RNA in cancers.

5-methylcytosine (m5C modification) plays an essential role in tumors, which affects different types of RNA, the expression of downstream target genes, and downstream pathways, thus participating in the tumor process. However, the effect of m5C modification on RNA in tumors and the exact mechanism have not been systematically reviewed. Therefore, we reviewed the status and sites of m5C modification, as well as the expression pattern and biological functions of m5C regulators in tumors, and further summarized the effects and regulation mechanism of m5C modification on messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), long non-coding RNA (lncRNA) and other RNA in tumors. Finally, we summed up the interaction network, potential application, and value in clinical diagnosis and treatment of tumors. Taken together, this review benefits revealing the mechanism of m5C modification in tumor progression and provides new strategies for tumor diagnosis and treatment.

Identifying and distinguishing of essential tremor and Parkinson's disease with grouped stability analysis based on searchlight-based MVPA.

BACKGROUND: Since both essential tremor (ET) and Parkinson's disease (PD) are movement disorders and share similar clinical symptoms, it is very difficult to recognize the differences in the presentation, course, and treatment of ET and PD, which leads to misdiagnosed commonly. PURPOSE: Although neuroimaging biomarker of ET and PD has been investigated based on statistical analysis, it is unable to assist the clinical diagnosis of ET and PD and ensure the efficiency of these biomarkers. The aim of the study was to identify the neuroimaging biomarkers of ET and PD based on structural magnetic resonance imaging (MRI). Moreover, the study also distinguished ET from PD via these biomarkers to validate their classification performance. METHODS: This study has developed and implemented a three-level machine learning framework to identify and distinguish ET and PD. First of all, at the model-level assessment, the searchlight-based machine learning method has been used to identify the group differences of patients (ET/PD) with normal controls (NCs). And then, at the feature-level assessment, the stability of group differences has been tested based on structural brain atlas separately using the permutation test to identify the robust neuroimaging biomarkers. Furthermore, the identified biomarkers of ET and PD have been applied to classify ET from PD based on machine learning techniques. Finally, the identified biomarkers have been compared with the previous findings of the biology-level assessment. RESULTS: According to the biomarkers identified by machine learning, this study has found widespread alterations of gray matter (GM) for ET and large overlap between ET and PD and achieved superior classification performance (PCA + SVM, accuracy = 100%). CONCLUSIONS: This study has demonstrated the significance of a machine learning framework to identify and distinguish ET and PD. Future studies using a large data set are needed to confirm the potential clinical application of machine learning techniques to discern between PD and ET.

The Emerging Roles and Clinical Potential of circSMARCA5 in Cancer.

Circular RNAs (circRNAs) are a type of endogenous non-coding RNA and a critical epigenetic regulation way that have a closed-loop structure and are highly stable, conserved, and tissue-specific, and they play an important role in the development of many diseases, including tumors, neurological diseases, and cardiovascular diseases. CircSMARCA5 is a circRNA formed by its parental gene SMARCA5 via back splicing which is dysregulated in expression in a variety of tumors and is involved in tumor development with dual functions as an oncogene or tumor suppressor. It not only serves as a competing endogenous RNA (ceRNA) by binding to various miRNAs, but it also interacts with RNA binding protein (RBP), regulating downstream gene expression; it also aids in DNA damage repair by regulating the transcription and expression of its parental gene. This review systematically summarized the expression and characteristics, dual biological functions, and molecular regulatory mechanisms of circSMARCA5 involved in carcinogenesis and tumor progression as well as the potential applications in early diagnosis and gene targeting therapy in tumors.

The emerging roles of the interaction between m6A modification and c-Myc in driving tumorigenesis and development.

N6-methyladenosine (m6A) is an extremely common and conservative posttranscriptional modification, that can specifically target and regulate the expression or stability of a series of tumor-related genes, thus playing critical roles in the occurrence and development of tumors. c-Myc is an important tumorigenic transcription factor that promotes tumorigenesis and development by mainly regulating the expression of downstream target genes. Increasing evidence shows that m6A modification, as well as abnormal expression and regulation of c-Myc, is critical molecular mechanisms driving tumorigenesis and development. Although more evidence has been uncovered about the individual roles of m6A modification or c-Myc in tumors, the interaction between m6A modification and c-Myc in tumorigenesis and development has not been systematically summarized. Therefore, this review is focused on the mutual regulation between m6A modification and c-Myc expression and stability as well as its roles in tumorigenesis and development. We also summarized the potential value of the interaction between m6A modification and m6A expression and stability in tumor diagnosis and treatment, which provides a specific reference for revealing the mechanism of tumor occurrence and development as well as clinical diagnosis and treatment.

SIK2 maintains breast cancer stemness by phosphorylating LRP6 and activating Wnt/ß-catenin signaling.

Breast cancer stem cells (BCSCs) are the main drivers of recurrence and metastasis. However, commonly used drugs rarely target BCSCs. Via screenings, we found that Salt-inducible kinase 2 (SIK2) participated in breast cancer (BC) stemness maintenance and zebrafish embryos development. SIK2 was upregulated in recurrence samples. Knockdown of SIK2 expression reduced the proportion of BCSCs and the tumor initiation of BC cells. Mechanistically, SIK2, phosphorylated by CK1α, directly phosphorylated LRP6 in a SIK2 kinase activity-dependent manner, leading to Wnt/ß-catenin signaling pathway activation. ARN-3236 and HG-9-91-01, inhibitors of SIK2, inhibited LRP6 phosphorylation and ß-catenin accumulation and disturbed stemness maintenance. In addition, the SIK2-activated Wnt/ß-catenin signaling led to induction of IDH1 expression, causing metabolic reprogramming in BC cells. These findings demonstrate a novel mechanism whereby Wnt/ß-catenin signaling pathway is regulated by different kinases in response to metabolic requirement of CSCs, and suggest that SIK2 inhibition may potentially be a strategy for eliminating BCSCs.

Low Expression of ECT2 Confers Radiation Therapy Resistance Through Transcription Coupled Nucleolar DNA Damage Repair.

PURPOSE: Radioresistance contributes to poor clinical therapeutic efficacy in most cancers. Emerging evidence shows that aberrant DNA damage repair is involved in radioresistance. This study aimed to elucidate the mechanism for radioresistance and explore the precise treatment to sensitize the radioresistant tumors. METHODS AND MATERIALS: Real-time polymerase chain reaction and Western blot were used to confirm the differential expression of epithelial cell transforming 2 (ECT2) in irradiation-resistant and sensitive cell lines. Laser microirradiation was used to examine the ribosome DNA (rDNA) damage response of ECT2. Biotin-identification, in vivo, in vitro binding assay, and dot blotting were used to confirm the interaction of ECT2 and PARP1. The xenograft mouse model and cell survival assay were used to assess the irradiation sensitivity with or without PARP1 inhibitor. RESULTS: We found the expression of ECT2 correlates with sensitivity to radiation therapy in both lung cancer and nasopharyngeal carcinoma. We demonstrated that low expression of ECT2 causes radioresistance, mainly by protecting rDNA in nucleoli from persistent irradiation exposure through transcriptional recovery prevention. ECT2 is recruited to the rDNA damage site in an ataxia-telangiectasia-mutated RNA polymerase I dependent manner. The recruited ECT2 interacts with PARP1 and facilitates the disassociation of PARP1 from rDNA in nucleoli. Thus, ECT2 deficiency results in sustained activation of PARP1, which subsequently inhibits nucleolar transcription and results in a low frequency of rDNA exposure under DNA damage. PARP inhibition synergized with irradiation can sensitize radioresistant tumors with low ECT2 expression. CONCLUSIONS: Our study provides a potential perspective for the application of PARP inhibitor to sensitize low-ECT2 expressing tumors to radiation therapy.

Stability Evaluation of Brain Changes in Parkinson's Disease Based on Machine Learning.

Structural MRI (sMRI) has been widely used to examine the cerebral changes that occur in Parkinson's disease (PD). However, previous studies have aimed for brain changes at the group level rather than at the individual level. Additionally, previous studies have been inconsistent regarding the changes they identified. It is difficult to identify which brain regions are the true biomarkers of PD. To overcome these two issues, we employed four different feature selection methods [ReliefF, graph-theory, recursive feature elimination (RFE), and stability selection] to obtain a minimal set of relevant features and nonredundant features from gray matter (GM) and white matter (WM). Then, a support vector machine (SVM) was utilized to learn decision models from selected features. Based on machine learning technique, this study has not only extended group level statistical analysis with identifying group difference to individual level with predicting patients with PD from healthy controls (HCs), but also identified most informative brain regions with feature selection methods. Furthermore, we conducted horizontal and vertical analyses to investigate the stability of the identified brain regions. On the one hand, we compared the brain changes found by different feature selection methods and considered these brain regions found by feature selection methods commonly as the potential biomarkers related to PD. On the other hand, we compared these brain changes with previous findings reported by conventional statistical analysis to evaluate their stability. Our experiments have demonstrated that the proposed machine learning techniques achieve satisfactory and robust classification performance. The highest classification performance was 92.24% (specificity), 92.42% (sensitivity), 89.58% (accuracy), and 89.77% (AUC) for GM and 71.93% (specificity), 74.87% (sensitivity), 71.18% (accuracy), and 71.82% (AUC) for WM. Moreover, most brain regions identified by machine learning were consistent with previous findings, which means that these brain regions are related to the pathological brain changes characteristic of PD and can be regarded as potential biomarkers of PD. Besides, we also found the brain abnormality of superior frontal gyrus (dorsolateral, SFGdor) and lingual gyrus (LING), which have been confirmed in other studies of PD. This further demonstrates that machine learning models are beneficial for clinicians as a decision support system in diagnosing PD.

A Novel Integrated Metabolism-Immunity Gene Expression Model Predicts the Prognosis of Lung Adenocarcinoma Patients.

Background: Although multiple metabolic pathways are involved in the initiation, progression, and therapy of lung adenocarcinoma (LUAD), the tumor microenvironment (TME) for immune cell infiltration that is regulated by metabolic enzymes has not yet been characterized. Methods: 517 LUAD samples and 59 non-tumor samples were obtained from The Cancer Genome Atlas (TCGA) database as the training cohort. Kaplan-Meier analysis and Univariate Cox analysis were applied to screen the candidate metabolic enzymes for their role in relation to survival rate in LUAD patients. A prognostic metabolic enzyme signature, termed the metabolic gene risk score (MGRS), was established based on multivariate Cox proportional hazards regression analysis and was verified in an independent test cohort, GSE31210. In addition, we analyzed the immune cell infiltration characteristics in patients grouped by their Risk Score. Furthermore, the prognostic value of these four enzymes was verified in another independent cohort by immunohistochemistry and an optimized model of the metabolic-immune protein risk score (MIPRS) was constructed. Results: The MGRS model comprising 4 genes (TYMS, NME4, LDHA, and SMOX) was developed to classify patients into high-risk and low-risk groups. Patients with a high-risk score had a poor prognosis and exhibited activated carbon and nucleotide metabolism, both of which were associated with changes to TME immune cell infiltration characteristics. In addition, the optimized MIPRS model showed more accurate predictive power in prognosis of LUAD. Conclusion: Our study revealed an integrated metabolic enzyme signature as a reliable prognostic tool to accurately predict the prognosis of LUAD.

Association between Sleep Traits and Lung Cancer: A Mendelian Randomization Study.

Multidimensional sleep trait, which is related to circadian rhythms closely, affects some cancers predominantly, while the relationship between sleep and lung cancer is rarely illustrated. We aimed to investigate whether sleep is causally associated with risk of lung cancer, through a two-sample Mendelian randomization study. The main analysis used publicly available GWAS summary data from two large consortia (UK Biobank and International Lung Cancer Consortium). Two-sample Mendelian randomization (MR) analysis was used to examine whether chronotype, getting up in the morning, sleep duration, nap during the day, or sleeplessness was causally associated with the risk of lung cancer. Additionally, multivariate MR analysis was also conducted to estimate the direct effects between sleep traits and lung cancer risks independent of smoking status including pack years of smoking or current tobacco smoking. There was no evidence of causal association between chronotype, getting up in the morning, or nap during the day and lung cancer. Sleeplessness was associated with higher risk of lung adenocarcinoma (odds ratio 5.75, 95% confidence intervals 2.12-15.65), while sleep duration played a protective role in lung cancer (0.46, 0.26-0.83). In multivariate MR analysis, sleeplessness and sleep duration remained to have similar results. In conclusion, we found robust evidence for effect of sleeplessness on lung adenocarcinoma risk and inconsistent evidence for a protective effect of sleep duration on lung cancer risk.

PKCα is a Potentially Useful Marker for Planning Individualized Radiotherapy for Nasopharyngeal Carcinoma.

PURPOSE: To examine the expression of protein kinase C alpha (PKCα) in nasopharyngeal carcinoma (NPC) and determine its relationship to the radio-sensitivity of NPC in order to evaluate its potential as a molecular marker for the guidance of individualized radiation therapy for NPC. MATERIALS AND METHODS: PKCα expression levels were detected in tumor samples from patients and in NPC cell lines with varying degrees of radio-sensitivity. A survival analysis was performed to analyze the association of PKCα expression with the 5-year overall survival (OS), progression-free survival (PFS), locoregional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS) in patients. In vitro and in vivo experiments using NPC cell lines were performed to study the effects of down-regulation of PKCα by short hairpin RNA treatment on the radio-sensitivity of NPC. RESULTS: PKCα expression was up-regulated in the well-differentiated NPC tissues of patients and in the more radio-resistant NPC cell lines. Moreover, high PKCα expression was associated with a worse 5-year PFS and LRFS of patients. shRNA-mediated knockdown of PKCα led to an increase in the sensitivity of NPC cells to radiation therapy, both in vitro as cultured cells and in vivo as tumor xenografts. CONCLUSION: The elevated expression of PKCα in NPC and its association with patient PFS indicates that PKCα is a potential molecular marker for guiding precision radiotherapy in NPC patients. Also, the increased radiosensitivity of NPC cells after loss of PKCα identifies PKCα as a promising therapeutic target for enhancing the radio-sensitivity of NPC.