Loss of endogenous estrogen alters mitochondrial metabolism and muscle clock-related protein Rbm20 in female mdx mice.

Female carriers of a Duchenne muscular dystrophy (DMD) gene mutation manifest exercise intolerance and metabolic anomalies that may be exacerbated following menopause due to the loss of estrogen, a known regulator of skeletal muscle function and metabolism. Here, we studied the impact of estrogen depletion (via ovariectomy) on exercise tolerance and muscle mitochondrial metabolism in female mdx mice and the potential of estrogen replacement therapy (using estradiol) to protect against functional and metabolic perturbations. We also investigated the effect of estrogen depletion, and replacement, on the skeletal muscle proteome through an untargeted proteomic approach with TMT-labelling. Our study confirms that loss of estrogen in female mdx mice reduces exercise capacity, tricarboxylic acid cycle intermediates, and citrate synthase activity but that these deficits are offset through estrogen replacement therapy. Furthermore, ovariectomy downregulated protein expression of RNA-binding motif factor 20 (Rbm20), a critical regulator of sarcomeric and muscle homeostasis gene splicing, which impacted pathways involving ribosomal and mitochondrial translation. Estrogen replacement modulated Rbm20 protein expression and promoted metabolic processes and the upregulation of proteins involved in mitochondrial dynamics and metabolism. Our data suggest that estrogen mitigates dystrophinopathic features in female mdx mice and that estrogen replacement may be a potential therapy for post-menopausal DMD carriers.

"seeing" ENF From Neuromorphic Events: Modeling and Robust Estimation.

Most artificial lights exhibit subtle fluctuations in intensity and frequency in response to the influence of the grid's alternating current, providing the potential to estimate the Electric Network Frequency (ENF) from conventional frame-based videos. Nevertheless, the performance of Video-based ENF (V-ENF) estimation largely relies on the imaging quality and thus may suffer from significant interference caused by non-ideal sampling, scene diversity, motion interference, and extreme lighting conditions. In this paper, we show that the ENF can be extracted without the above limitations from a new modality provided by the so-called event camera, a neuromorphic sensor that encodes the light intensity variations and asynchronously emits events with extremely high temporal resolution and high dynamic range. Specifically, we formulate and validate the physical mechanism for the ENF captured in events and then propose a simple yet robust Event-based ENF (E-ENF) estimation method through mode filtering and harmonic enhancement. To validate the effectiveness, we build the first Event-Video ENF Dataset (EV-ENFD) and its extension EV-ENFD+ with diverse scenarios, including static, dynamic, and extreme lighting scenes. Comprehensive experiments have been conducted on our proposed datasets, showcasing that our proposed E-ENF significantly outperforms the V-ENF in extracting accurate ENF traces, especially in challenging environments. The code and dataset are available at https://xlx-creater.github.io/Improved_E-ENF/.

Analysis and visualization of quantitative proteomics data using FragPipe-Analyst.

The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.

An ultrasound-based nomogram model in the assessment of pathological complete response of neoadjuvant chemotherapy in breast cancer.

Introduction: We aim to predict the pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) in breast cancer patients by constructing a Nomogram based on radiomics models, clinicopathological features, and ultrasound features. Methods: Ultrasound images of 464 breast cancer patients undergoing NAC were retrospectively analyzed. The patients were further divided into the training cohort and the validation cohort. The radiomics signatures (RS) before NAC treatment (RS1), after 2 cycles of NAC (RS2), and the different signatures between RS2 and RS1 (Delta-RS/RS1) were obtained. LASSO regression and random forest analysis were used for feature screening and model development, respectively. The independent predictors of pCR were screened from clinicopathological features, ultrasound features, and radiomics models by using univariate and multivariate analysis. The Nomogram model was constructed based on the optimal radiomics model and clinicopathological and ultrasound features. The predictive performance was evaluated with the receiver operating characteristic (ROC) curve. Results: We found that RS2 had better predictive performance for pCR. In the validation cohort, the area under the ROC curve was 0.817 (95%CI: 0.734-0.900), which was higher than RS1 and Delta-RS/RS1. The Nomogram based on clinicopathological features, ultrasound features, and RS2 could accurately predict the pCR value, and had the area under the ROC curve of 0.897 (95%CI: 0.866-0.929) in the validation cohort. The decision curve analysis showed that the Nomogram model had certain clinical practical value. Discussion: The Nomogram based on radiomics signatures after two cycles of NAC, and clinicopathological and ultrasound features have good performance in predicting the NAC efficacy of breast cancer.

MAPbI3perovskite photodetectors for high-performance optical wireless communication.

High-sensitivity and fast-response photodetectors (PDs) are vital part of optical wireless communication (OWC) system. In this work, we develop an organic-inorganic hybrid perovskite material (MAPbI3) based p-i-n structured PD. By optimizing the precursor solution concertation, the PD showed a high responsivity of 0.98 A W-1, a fast response timetrise/tfallof 12/12.5 µs, a specific detectivity of 2.62 × 1013Jones, and the f-3dBof 24 kHz under the 532 nm laser and -0.2 V bias voltage. Furthermore, we designed an OWC system based on the prepared PD. With the baud rate of 19200 bps, the system exhibits a bit error rate less than 10-6, and it can realize 9.63 m long-distance communication and quick transmission applications such as strings, texts, photos, and audios. Our work demonstrates the great application potential of perovskite PDs in the field of optical communication.

Phospho-Analyst: An Interactive, Easy-to-Use Web Platform To Analyze Quantitative Phosphoproteomics Data.

Phosphoproteomics is nowadays the method of choice to comprehensively identify and quantify thousands of phosphorylated peptides and their associated proteins with the goal of interrogating changes in signal transduction pathways and other cellular processes. One of the most popular software suites to analyze phosphoproteomic data sets is MaxQuant, which converts mass spectrometric raw data into quantitative information on phosphopeptides and proteins. However, despite the increased utilization of phosphoproteomics in biomedical research, simple and user-friendly tools supporting downstream statistical analysis and interpretation of these highly complex outputs are still lacking. We have therefore developed Phospho-Analyst, which─similar to its sibling LFQ-Analyst─is an easy-to-use, interactive web application specifically designed to reproducibly perform differential expression analyses with "one click" and to visualize phosphoproteomic results in a meaningful and practical manner. Furthermore, if quantitative total proteomic information is available for the same samples, Phospho-Analyst automatically normalizes all phosphoproteomic results to underlying protein abundance levels, thereby ensuring that only genuine changes in phosphorylation events are considered. As such, Phospho-Analyst can not only be used by experienced proteomic veterans but also by researchers without any prior knowledge in (phospho)proteomics, statistics, or bioinformatics. Phospho-Analyst, including a detailed manual, is freely available at https://analyst-suites.org/apps/phospho-analyst/.

Learning to Super-Resolve Blurry Images With Events.

Super-Resolution from a single motion Blurred image (SRB) is a severely ill-posed problem due to the joint degradation of motion blurs and low spatial resolution. In this article, we employ events to alleviate the burden of SRB and propose an Event-enhanced SRB (E-SRB) algorithm, which can generate a sequence of sharp and clear images with High Resolution (HR) from a single blurry image with Low Resolution (LR). To achieve this end, we formulate an event-enhanced degeneration model to consider the low spatial resolution, motion blurs, and event noises simultaneously. We then build an event-enhanced Sparse Learning Network (eSL-Net++) upon a dual sparse learning scheme where both events and intensity frames are modeled with sparse representations. Furthermore, we propose an event shuffle-and-merge scheme to extend the single-frame SRB to the sequence-frame SRB without any additional training process. Experimental results on synthetic and real-world datasets show that the proposed eSL-Net++ outperforms state-of-the-art methods by a large margin. Datasets, codes, and more results are available at https://github.com/ShinyWang33/eSL-Net-Plusplus.

Histone acetylation modification regulator-mediated tumor microenvironment infiltration characteristics and prognostic model of lung adenocarcinoma patients.

Background: The incidence rate of lung adenocarcinoma (LUAD) is rapidly increasing. Recent studies have reported that histone acetylation modification plays an important role in the occurrence and development of tumors. However, the potential role of modification of histone acetylation modification in the development of tumor immune microenvironment is still unclear. Methods: In this study, we comprehensively evaluated the acetylation modification patterns of LUAD samples obtained from various different databases based on 36 histone modification regulators, and constructed a prognostic model based on The Cancer Genome Atlas (TCGA) LUAD cohort using the Cox regression method. The close relationship between histone acetylation and tumor immune characteristics was further studied, including immune infiltration, immune escape and immunotherapy. Finally, we combined three cohort (GSE30219, GSE72094 and GSE50081) from Gene Expression Omnibus (GEO) database to verify the above results. Results: We analyzed the expression, mutation and interaction of 36 histone acetylation regulated genes. After Univariate Cox regression analysis and least absolute shrinkage and selection operator regression (LASSO), 5 genes (KAT2B, SIRT2, HDAC5, KAT8, HDAC2) were screened to establish the prognosis model and calculate the risk score. Then, patients in the TCGA cohort were divided into high- and low-risk groups based on the risk scores. Further analysis indicated that patients in the high-risk group exhibited significantly reduced overall survival (OS) compared with those in the low-risk group. The high- and low-risk groups exhibited significant differences in terms of tumor immune characteristics, such as immune infiltration, immune escape and immunotherapy. The high-risk group had lower immune score, less immune cell infiltration and higher clinical stage. Moreover, multivariate analysis revealed that this prognostic model might be a powerful prognostic predictor for LUAD. In addition, drugs sensitive for this classification were identified. Finally, the efficacy of the prognostic model was validated by cohort (GSE30219, GSE72094 and GSE50081) from GEO database. Conclusions: Our study provided a robust signature for predicting changing prognosis of patients with LUAD. Thus, it appears to be a potentially useful prognostic tool. Moreover, the important relationship between histone acetylation and tumor immune microenvironment was revealed.

A-kinase interacting protein 1 regulates the cell proliferation, invasion, migration and angiogenesis of clear cell renal cell carcinoma cells and affects the ERK/c-Myc signaling pathway by binding to Rac1.

A-kinase interacting protein 1 (AKIP1) has previously been demonstrated to be overexpressed in clear cell renal cell carcinoma (ccRCC) tissues and is associated with patient prognosis. The aim of the present study was to explore whether AKIP1 can affect the proliferation, invasion, migration and angiogenesis of ccRCC cells via its interaction with Rac1. Furthermore, the influence of AKIP1 and therefore Rac1 on the expression of the downstream ERK/cellular (c)-Myc signaling pathway was explored. The interaction between AKIP1 and Rac1 was determined using co-immunoprecipitation. The mRNA and protein expression levels of AKIP1 and Rac1 in normal renal epithelial cell lines and ccRCC cell lines were detected using reverse transcription-quantitative PCR (RT-qPCR) and western blotting, respectively. The transfection efficiency of small interfering RNA-AKIP1 and the Rac1 overexpression vector were also confirmed using RT-qPCR and western blotting. The viability, proliferation, invasion and migration of ccRCC cells following transfection were analyzed using the Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine staining, Transwell and wound healing assays, respectively. The tube formation ability of HUVECs was assessed using the tube formation assay. The protein expression levels of proliferation, invasion, migration and tube-formation-associated proteins as well as proteins associated with the ERK/c-Myc signaling pathway, were detected via western blotting. The results demonstrated that AKIP1 expression levels were increased in ccRCC cell lines. AKIP1 knockdown inhibited the proliferation, invasion and migration of ccRCC cells and HUVEC tube-formation. In addition, AKIP1 was demonstrated to bind to Rac1 in ccRCC cells and AKIP1 downregulation inhibited Rac1 expression. Furthermore, Rac1 overexpression reversed the effects of AKIP1 knockdown on ccRCC cells. AKIP1 knockdown also suppressed the ERK/c-Myc signaling pathway, which was reversed by Rac1 overexpression. In conclusion, AKIP1 knockdown potentially suppressed the proliferation, invasion, migration and angiogenesis of ccRCC cells and inhibited the ERK/c-Myc signaling pathway by binding to Rac1.

Identification of m6A- and ferroptosis-related lncRNA signature for predicting immune efficacy in hepatocellular carcinoma.

Background: N6-methyladenosine (m6A) methylation and ferroptosis assist long noncoding RNAs (lncRNAs) in promoting immune escape in hepatocellular carcinoma (HCC). However, the predictive value of m6A- and ferroptosis-related lncRNAs (mfrlncRNAs) in terms of immune efficacy remains unknown. Method: A total of 365 HCC patients with complete data from The Cancer Genome Atlas (TCGA) database were used as the training cohort, and half of them were randomly selected as the validation cohort. A total of 161 HCC patients from the International Cancer Genome Consortium (ICGC) database were used as external validation (ICGC cohort). Results: We first identified a group of specific lncRNAs associated with both m6A regulators and ferroptosis-related genes and then constructed prognosis-related mfrlncRNA pairs. Based on this, the mfrlncRNA signature was constructed using the least absolute shrinkage and selection operator (LASSO) analysis and Cox regression. Notably, the risk score of patients was proven to be an independent prognostic factor and was better than the TNM stage and tumor grade. Moreover, patients with high-risk scores had lower survival rates, higher infiltration of immunosuppressive cells (macrophages and Tregs), lower infiltration of cytotoxic immune cells (natural killer cells), poorer immune efficacy (both immunophenoscore and score of tumor immune dysfunction and exclusion), higher IC50, and enrichment of the induced Treg pathway, which confirmed that the mfrlncRNA signature contributed to survival prediction and risk stratification of patients with HCC. Conclusions: The mfrlncRNA signature, which has great prognostic value, provides new clues for identifying "cold" and "hot" tumors and might have crucial implications for individualized therapy to improve the survival rate of patients with HCC.

LncRNA PTAR activates the progression of bladder cancer by modulating miR-299-3p/CD164 axis.

Bladder cancer (BC) occurs in the urinary system which has high incidence and mortality. During past decades, lots of long noncoding RNAs (lncRNAs) have been identified to function in cancer progression, including BC. In our research, we targeted at investigating the functions and mechanisms of lncRNA pro-transition associated RNA (PTAR) in BC. Functional assays were implemented to access the changes of BC cell phenotype. Mechanistic assays were applied for confirming the interaction between RNAs. Based on the collected data, PTAR expression was high in BC cells and silenced PTAR repressed BC cell proliferative, migratory and invasive abilities but improved cell apoptotic ability. In vivo study also verified PTAR depletion inhibited BC tumor growth. Furthermore, miR-299-3p was confirmed to bind with PTAR and its overexpression suppressed malignant behaviors of BC cells. Cluster of differentiation 164 (CD164) was proved to be miR-299-3p target. Rescue experiments implied overexpressed CD164 offset the inhibitory function of PTAR depletion on BC cell phenotype. Additionally, CD164 was uncovered to combine with C-X-C motif chemokine receptor 4 (CXCR4) to switch on PI3K/AKT pathway. To conclude, PTAR facilitates BC development via regulating miR-299-3p/CD164 axis and activating PI3K/AKT pathway.

Emerging Optoelectronic Devices Based on Microscale LEDs and Their Use as Implantable Biomedical Applications.

Thin-film microscale light-emitting diodes (LEDs) are efficient light sources and their integrated applications offer robust capabilities and potential strategies in biomedical science. By leveraging innovations in the design of optoelectronic semiconductor structures, advanced fabrication techniques, biocompatible encapsulation, remote control circuits, wireless power supply strategies, etc., these emerging applications provide implantable probes that differ from conventional tethering techniques such as optical fibers. This review introduces the recent advancements of thin-film microscale LEDs for biomedical applications, covering the device lift-off and transfer printing fabrication processes and the representative biomedical applications for light stimulation, therapy, and photometric biosensing. Wireless power delivery systems have been outlined and discussed to facilitate the operation of implantable probes. With such wireless, battery-free, and minimally invasive implantable light-source probes, these biomedical applications offer excellent opportunities and instruments for both biomedical sciences research and clinical diagnosis and therapy.

PRKCB is relevant to prognosis of lung adenocarcinoma through methylation and immune infiltration.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the tumor-related diseases with high morbidity worldwide. Epigenetic modifications such as DNA methylation changes may involve in tumorigenesis. This study aimed to explore new biomarkers that have prognostic significance of LUAD. METHODS: First, we downloaded the gene expression and methylation data set from Gene Expression Omnibus. R software was then used to identify abnormally methylated differentially expressed genes (MDEGs). Next, R package Cluster Profiler was used to analyze the enrichment and pathway of the MDEGs. Analysis using STRING revealed the protein-protein interaction network. The result was then visualized by Cytoscape and obtained 10 hub genes. Afterward, they were further verified by The Cancer Genome Atlas to select candidate genes. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry were used to verify the expression and prognostic value of candidate genes in LUAD patients. RESULTS: The results showed that the expressions of ADCY5 and PRKCB are indeed related to LUAD. The clinical relevance to PRKCB was confirmed by its clinical correlation analysis. Gene set enrichment analysis (GSEA) and tumor immune estimation resource (TIMER) tumor immune correlations showed that PRKCB is involved in the cancer-related Kyoto Encyclopedia of Genes and Genomes pathway and is involved in immune infiltration. It was also verified by qRT-PCR and immunohistochemistry that PRKCB was lowly expressed in LUAD patients and correlated with prognosis. CONCLUSIONS: PRKCB is relevant to prognosis of LUAD through methylation and immune infiltration.

Do older patients with stage IB non-small-cell lung cancer obtain survival benefits from surgery? A propensity score matching study using SEER data.

BACKGROUND: Surgical resection is the preferred treatment for Stage IB non-small cell lung cancer (NSCLC), but one-third of patients still do not receive surgery, which might be due to the lack of robust and dedicated studies on the outcomes of surgical treatment in older patients with stage IB NSCLC. This study aims to investigate whether older patients with stage IB NSCLC benefit from surgery. METHODS: Data of patients with NSCLC were downloaded from the SEER (Surveillance, Epidemiology, and End Results) database classifications were converted from the 7th edition staging system to the 8th edition staging system, and older patients (aged ≥65 years at diagnosis) with stage IB NSCLC were included. The propensity score matching (PSM) method was used to balance the distribution proportions of clinical characteristics between the surgery and no surgery groups. RESULTS: After 1:1 propensity score matching, the distribution proportions of clinical characteristics were balanced between the surgery and no surgery groups (all P > 0.05). The overall and disease-specific survival rates of patients in the surgery group were significantly higher than those of patients in the no-surgery group (both P < 0.001). Furthermore, subgroup analysis showed that receiving surgery was a protective factor for overall survival and disease-specific survival of patients in all clinical character-related subgroups. Ultimately, univariate and multivariate Cox regression analyses showed that sex, tumor size, tumor grade, and tumor classification were independent prognostic factors for overall and disease-specific survival in patients undergoing surgery. CONCLUSIONS: Older patients with Stage IB NSCLC can benefit significantly from surgical treatment after eliminating confounding factors, which is expected to provide strong medical evidence for surgical treatment.

Nrf2 Promotes Inflammation in Early Myocardial Ischemia-Reperfusion via Recruitment and Activation of Macrophages.

Cardiomyocyte apoptosis in response to inflammation is a primary cause of myocardial ischemia-reperfusion injury (IRI). Nuclear factor erythroid 2 like 2 (Nrf2) reportedly plays an important role in myocardial IRI, but the underlying mechanism remains obscure. Expression data from the normal heart tissues of mice or heart tissues treated with reperfusion for 6 h after ischemia (IR6h) were acquired from the GEO database; changes in biological function and infiltrating immune cells were analyzed. The binding between the molecules was verified by chromatin immunoprecipitation sequencing. Based on confirmation that early myocardial ischemia-reperfusion (myocardial ischemia/reperfusion for 6 hours, IR6h) promoted myocardial apoptosis and inflammatory response, we found that Nrf2, cooperating with Programmed Cell Death 4, promoted transcription initiation of C-C Motif Chemokine Ligand 3 (Ccl3) in myocardial tissues of mice treated with IR6h. Moreover, Ccl3 contributed to the high signature score of C-C motif chemokine receptor 1 (Ccr1)-positive macrophages. The high signature score of Ccr1-positive macrophages leads to the release of pro-inflammatory factors interleukin 1 beta and interleukin 6. This study is the first to elucidate the damaging effect of Nrf2 via remodeling of the immune microenvironment in early myocardial ischemia-reperfusion, which provides us with new perspectives and treatment strategies for myocardial ischemia-reperfusion.

Relationship of shear wave elastography anisotropy with tumor stem cells and epithelial-mesenchymal transition in breast cancer.

BACKGROUND: This study is to examine the feasibility of shear wave elastography (SWE) anisotropy in assessing the prognosis of breast cancer. METHODS: We enrolled 119 breast cancer patients from January 2017 to October 2019. SWE was performed before operation. Emax (maximum elasticity value), Emean (average elasticity value), Esd (standard deviation of the lesion elasticity value), Eratio (elasticity value of adipose tissue), anisotropy coefficient and difference were recorded. After operation, we collected clinical pathological data, and performed immunohistochemistry and real-time PCR tests on CD44, CD24, E-cadherin, ß-catenin, vimentin and N-cadherin. Finally, we analyzed the correlation among parameters of SWE, anisotropy and clinicopathology, and markers of CSCs (cancer stem cells) and EMT (epithelial-mesenchymal transition). RESULTS: Emax, Emean and Esd of the cross section were higher than those of the longitudinal section. Breast cancer with a higher elastic modulus was often accompanied by a hyperechoic halo, which was manifested as mixed echo and post-echo attenuation, and was accompanied by a higher BI-RADS (breast imaging reporting and data system) classification. When breast cancer had hyperechoic halo and weakened posterior echo, SWE of the lesion showed more obvious anisotropy. In addition, larger diameter of the longitudinal section indicated higher stiffness of the cross section. Correlation analysis showed that E-cadherin was negatively correlated with SWE in longitudinal section. CD44, N-cadherin, ß-catenin were positively correlated with SWE in longitudinal and cross sections. Vimentin and CD24 had no correlation with SWE parameters. CONCLUSION: SWE of breast cancer is anisotropic. The cross-sectional SWE is better than the longitudinal SWE, Emax is better than Emean, the anisotropy of SWE is better than SWE, and the anisotropy factor is better than the anisotropy difference.

Immune inactivation by APOBEC3B enrichment predicts response to chemotherapy and survival in gastric cancer.

Apolipoprotein B mRNA editing enzyme catalytic polypeptide 3B (APOBEC3B) plays an important role in tumor mutagenesis. However, its clinical significance in gastric cancer (GC) remains largely unknown. We enrolled a total of 482 GC patients from Zhongshan Hospital, Fudan University for immunohistochemistry (IHC) staining to evaluate the prognostic and predictive values of APOBEC3B. Genomic and phenotypic datasets from the Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) cohort were downloaded for external validation and complementary bioinformatic analysis. Fresh specimens of additional 60 patients from Zhongshan Hospital, Fudan University were collected to detect CD8+ T cell phenotype with flow cytometry (FCM). The high expression of APOBEC3B indicated inferior overall survival (OS, P < .001 and P = .003) and disease-free survival (DFS, P < .001 and P < .001), yet superior therapeutic responsiveness to fluorouracil-based adjuvant chemotherapy (ACT) in TNM stage II patients. The tumor microenvironment (TME) of APOBEC3B-enriched tumors was characterized by reduced infiltration of tumor reactive CD8+ T cells expressing both effector molecules and immune checkpoints. APOBEC3B high CD8+ T cell high GC patients were most likely to benefit from ACT and PD-1 blockade. Our study demonstrates that APOBEC3B was an independent prognostic and predictive factor in GC. The potential interplay between APOBEC3B and CD8+ T cells merited further investigations.

SMOX expression predicts the prognosis of non-small cell lung cancer.

BACKGROUND: The development of non-small cell lung cancer (NSCLC) is very rapid, and the effect of its treatment is often closely related to the diagnosis time of the disease. Therefore, simple and convenient tumor biomarkers are helpful for the timely diagnosis and prevention of NSCLC. METHODS: Through univariate and multivariate Cox regression analyses, SMOX was determined as an independent prognostic factor of GSE42127, GSE41271, GSE68465, and TCGA datasets. Furthermore, western blot, reverse transcription-polymerase chain reaction (RT-PCR), and immunohistochemical analysis were performed to confirm the predictive efficiency of SMOX expression in NSCLC. RESULTS: Patients were divided into high and low expression groups according to the median value of SMOX expression, and Kaplan-Meier curves of multiple datasets indicated that patients with low SMOX expression had a better survival rate. According to the analysis of immune infiltration, the immune microenvironment, and immune checkpoints, SMOX expression of the high and low groups showed differences in immunity in NSCLC. By comparing cancer and adjacent tissues using western blot analysis, RT-PCR and immunohistochemical analysis, we found that SMOX was highly expressed in tumor tissues and had low expression in adjacent tissues. Simultaneously, the Kaplan-Meier curve suggested that among the 155 NSCLC patients, those with low SMOX expression had better survival. CONCLUSIONS: SMOX can be used as an effective predictive target for NSCLC.

Low expression of IL6R predicts poor prognosis for lung adenocarcinoma.

BACKGROUND: Interleukin 6 (IL6) is both a pleiotropic cytokine and an immune-related gene. Interleukin 6 receptor (IL6R) is the receptor for IL6. It may be closely connected to the development of lung cancer. This research aims to explore the prognostic value of IL6R and prevent overtreatment of patients with lung adenocarcinoma (LUAD). METHODS: In this study, the expression of IL6R in tumor tissues and surrounding tissues was first analyzed by immunohistochemistry in the Affiliated Hospital of Nantong University (NTU) cohort. Secondly, we downloaded information from The Cancer Genome Atlas (TCGA) for the TCGA cohort and used this information to explore the messenger RNA (mRNA) level of IL6R. We then used Kaplan-Meier survival analyses, univariate and multivariate Cox analyses, nomogram models, and decision curve analyses to assess the prognostic value of IL6R. In addition, we also analyzed immune cell infiltration and the signaling pathways related to IL6R through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). RESULTS: Through the data analysis of the NTU cohort and the TCGA cohort, it was found that the expression of IL6R in normal tissues around the tumor was higher than that in tumor tissue, and was positively correlated with the overall survival (OS) of LUAD patients. Additionally, low expression of IL6R was found to be an independent predictor of poor prognosis among the patients in these two research cohorts. Next, using GO, KEGG, and GSEA analyses, we found that partially infiltrated tumor immune cells might be related to earlier staging and better prognosis of patients with LUAD. Finally, the study of the 3-5-year survival rate of LUAD patients through the nomogram showed that the expression of IL6R could improve the accuracy of prediction to prevent the overtreatment of some LUAD patients. CONCLUSIONS: In summary, our study indicated that the low expression of IL6R was associated with poor prognosis among LUAD patients and that low expression of IL6R is a potential independent risk factor that could provide a basis for strengthening postoperative classification management of such patients.

Loss of IL-34 Expression Indicates Poor Prognosis in Patients With Lung Adenocarcinoma.

Interleukin 34 (IL-34), an additional ligand of the colony-stimulating factor-1 receptor (CSF-1R), promotes the secretion of pro-inflammatory cytokines and stimulates NF-κB and JNK-related signaling pathways. However, the potential mechanism and prognostic value of IL-34 in lung adenocarcinoma (LUAD) remain obscure. In this study, IL-34 was found to be downregulated in LUAD tissues compared with para-carcinoma tissues, and loss of IL-34 expression was correlated with shorter overall survival (OS), which was validated by bioinformatics\ analysis in TCGA (The Cancer Genome Atlas) cohort and immunohistochemical analysis in the NTU (Nantong University) cohort, respectively. Subsequently, loss of IL-34 promotes negative regulation of the immune system and inhibits the infiltration of immune cells. Moreover, IL-34 deficiency was shown to be an independent adverse prognostic factor for patients with LUAD, and subgroup analysis indicated that IL-34 might contribute to the stratified management of patients with LUAD. IL-34-based nomogram model significantly improved the accuracy of prognostic predictions for OS of patients with LUAD, both in the TCGA cohort and the NTU cohort. Taken together, our data suggested that loss of IL-34 expression is associated with poor prognosis and negative regulation of the immune system of patients with LUAD, contributing to the stratified management of patients with LUAD.