[Clinical Evaluation of Dural (Spinal) Membrane Repair Materials].

Objective: To select high-quality and cost-effective dural (spinal) membrane repair materials, in order to reduce the cost of consumables procurement, save medical insurance funds, and optimize hospital operation and management. Methods: Taking the BS06B disease group (spinal cord and spinal canal surgery without extremely severe or severe complications and comorbidities, mainly diagnosed as congenital tethered cord syndrome) as an example, a retrospective analysis was conducted on the relevant data of surgical treatment for congenital tethered cord syndrome conducted in our hospital from January 2021 to June 2023. Safety and efficacy indicators in clinical application (incidence of postoperative epidural hemorrhage, incidence of postoperative purulent cerebrospinal meningitis, incidence of cerebrospinal fluid leakage, surgical duration, and postoperative hospital stay) were compared. Results: There was no difference in safety and effectiveness between different brands of dura mater repair materials. Conclusion: For the repair of small incisions in dura mater surgery, high-quality and cost-effective dura mater repair materials can be selected to reduce hospital costs and control expenses for the disease group.

Themis: advancing precision oncology through comprehensive molecular subtyping and optimization.

Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.

Tumor immune dysfunction and exclusion subtypes in bladder cancer and pan-cancer: a novel molecular subtyping strategy and immunotherapeutic prediction model.

BACKGROUND: Molecular subtyping is expected to enable precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE), we aimed to develop a novel TIDE-based subtyping strategy to guide personalized immunotherapy in the bladder cancer (BC). METHODS: Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. Subsequently, consensus clustering was applied to classify BC patients based on TIDE marker-genes. Patients' clinicopathological, molecular features and signaling pathways of the different TIDE subtypes were well characterized. We also utilize the deconvolution algorithms to analyze the tumor microenvironment, and further explore the sensitivity and mechanisms of each subtype to immunotherapy. Furthermore, BC patient clinical information, real-world BC samples and urine samples were collected for the validation of our findings, which were used for RNA-seq analysis, H&E staining, immunohistochemistry and immunofluorescence staining, and enzyme-linked immunosorbent assay. Finally, we also explored the conservation of our novel TIDE subtypes in pan-cancers. RESULTS: We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples and collected patient clinical data. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors. CONCLUSIONS: Our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.

Discovery of Novel 5,6-Dihydro-4H-pyrido[2,3,4-de]quinazoline Irreversible Inhibitors Targeting Both Wild-Type and A775_G776insYVMA Mutated HER2 Kinases.

HER2 mutations were seen in 4% of non-small-cell lung cancer (NSCLC) patients. Most of these mutations (90%) occur as an insertion mutation within the exon 20 frame, leading to the downstream activation of the PI3K-AKT and RAS/MAPK pathways. However, no targeted therapies have yet been approved worldwide. Here a novel series of highly potent HER2 inhibitors with a pyrido[2,3,4-de]quinazoline core were designed and developed. The derivatives with the pyrido[2,3,4-de]quinazoline core displayed superior efficacy of antiproliferation in BaF3 cells harboring HER2insYVMA mutation compared with afatinib and neratinib. Rat studies showed that 8a and 9a with the newly developed core have good pharmacokinetic properties with an oral bioavailability of 41.7 and 42.0%, respectively. Oral administration of 4a and 10e (30 mg/kg, QD) displayed significant antitumor efficacy in an in vivo xenograft model. We proposed promising strategies for the development of HER2insYVMA mutant inhibitors in this study.

Mining channel-regulated peptides from animal venom by integrating sequence semantics and structural information.

Channel-regulated peptides (CRPs) derived from animal venom hold great promise as potential drug candidates for numerous diseases associated with channel proteins. However, discovering and identifying CRPs using traditional bio-experimental methods is a time-consuming and laborious process. While there were a few computational studies on CRPs, they were limited to specific channel proteins, relied heavily on complex feature engineering, and lacked the incorporation of multi-source information. To address these problems, we proposed a novel deep learning model, called DeepCRPs, based on graph neural networks for systematically mining CRPs from animal venom. By combining the sequence semantic and structural information, the classification performance of four CRPs was significantly enhanced, reaching an accuracy of 0.92. This performance surpassed baseline models with accuracies ranging from 0.77 to 0.89. Furthermore, we employed advanced interpretable techniques to explore sequence and structural determinants relevant to the classification of CRPs, yielding potentially valuable bio-function interpretations. Comprehensive experimental results demonstrated the precision and interpretive capability of DeepCRPs, making it an accurate and bio-explainable suit for the identification and categorization of CRPs. Our research will contribute to the discovery and development of toxin peptides targeting channel proteins. The source data and code are freely available at https://github.com/liyigerry/DeepCRPs.

Modified Y-V plasty based on MRU evaluation for iatrogenic bladder outlet obliteration: a multicentre experience in China.

PURPOSE: To compare the diagnostic ability of traditional radiographic urethrography and magnetic resonance urethrography (MRU) for iatrogenic bladder outlet obliteration (BOO), and explore the efficacy and complications of laparoscopic modified Y-V plasty for patients selected based on MRU evaluation. METHODS: 31 patients with obliteration segments ≤ 2 cm and no false passages or diverticula based on MRU evaluation from eight centers in China were included. Obliteration segments were measured preoperatively by MRU and conventional RUG/VCUG and compared with intra-operative measurements. Surgical effects were evaluated by uroflow rates, urethrography, or cystoscopy at 1, 3, 6, and 12 months post-operation and then every 12 months. Postoperative urinary continence was assessed by 24-h urine leakage (g/day). RESULTS: The results showed that MRU measured the length of obliteration more accurately than RUG/VCUG (MRU 0.91 ± 0.23 cm, RUG/VCUG 1.72 ± 1.08 cm, Actual length 0.96 ± 0.36 cm, p < 0.001), and clearly detected false passages and diverticula. Laparoscopic Y-V plasty was modified by incisions at 5 and 7 o'clock positions and double-layer suture with barbed sutures. All operations were successfully completed within a median time of 75 (62-192) minutes and without any complications. Urethral patency and urinary continence rates were 90.3% (28/31) and 87.1% (27/31), respectively. Three recurrences were cured by direct visual internal urethrotomy. Four patients had stress urinary incontinence after catheter removal 14 days post-operation, with urine leakage of 80-120 g/day, not relieved during follow-up. CONCLUSIONS: Laparoscopic modified Y-V plasty based on MRU evaluation is a promising approach for iatrogenic BOO, with a high patency rate and a low incontinence rate.

In situ Activation of Molecular Oxygen at Intermetallic Spacing-Optimized Iron Network-Like Sites for Boosting Electrocatalytic Oxygen Reduction.

The oxygen reduction reaction (ORR) catalyzed by transition-metal single-atom catalysts (SACs) is promising for practical applications in energy-conversion devices, but great challenges still remain due to the sluggish kinetics of O═O cleavage. Herein, a kind of high-density iron network-like sites catalysts are constructed with optimized intermetallic distances on an amino-functionalized carbon matrix (Fe-HDNSs). Quasi-in situ soft X-ray absorption spectroscopy and in situ synchrotron infrared characterizations demonstrate that the optimized intermetallic distances in Fe-HDNSs can in situ activate the molecular oxygen by fast electron compensation through the hybridized Fe 3d-O 2p, which efficiently facilitates the cleavage of the O═O bond to *O species and highly suppresses the side reactions for an accelerated kinetics of the 4e- ORR. As a result, the well-designed Fe-HDNSs catalysts exhibit superior performances with a half-wave potential of 0.89 V versus reversible hydrogen electrode (RHE) and a kinetic current density of 72 mA cm-2 @0.80 V versus RHE, exceeding most of the noble-metal-free ORR catalysts. This work offers some new insights into the understanding of 4e- ORR kinetics and reaction pathways to boost electrochemical performances of SACs.

The quantification of circular RNA 0007841 during induction therapy helps estimate the response and survival benefits to bortezomib-based regimen in multiple myeloma.

OBJECTIVE: Circular RNA_0007841 (Circ_0007841) facilitates multiple myeloma (MM) progression and resistance of the bortezomib by experimental studies, while its clinical implication in MM patients is still unclear. This study intended to evaluate the longitudinal change and prognostic role of circ_0007841 expression in MM patients receiving bortezomib-based induction therapy. METHODS: In this prospective study, bone marrow plasma cell (BMPC) samples were gained from 97 MM patients at diagnosis and after bortezomib-based induction therapy, and from 30 healthy controls (HCs) proposing BM donation. Then, circ_0007841 expression in BMPC samples was measured by reverse transcription-quantitative polymerase chain reaction. Additionally, MM patients were followed up for a median of 29.4 months. RESULTS: Circ_0007841 expression was increased in MM patients compared to HCs (P < 0.001), but it was decreased after bortezomib-based induction therapy in MM patients (P < 0.001). Moreover, circ_0007841 expression at diagnosis was associated with the presence of t (4; 14) (P = 0.034), while its expression after bortezomib-based induction therapy was linked with higher revised international staging system stage (P = 0.025) in MM patients. Interestingly, circ_0007841 expression after bortezomib-based induction therapy was lower in MM patients who achieved complete remissions (P = 0.001) and overall responses (P = 0.002) compared to those who did not. Prognostically, circ_0007841 expression after bortezomib-based induction therapy (over the median vs. below the median) independently predicted shorter progression-free survival (hazard ratio (HR): 2.497, P = 0.002) and overall survival (HR: 3.107, P = 0.008) in MM patients. CONCLUSION: Circ_0007841 quantification during induction therapy may reflect the response and survival benefits to bortezomib-based regimen in MM patients.

Macrophage KLF15 prevents foam cell formation and atherosclerosis via transcriptional suppression of OLR-1.

BACKGROUND: Macrophage-derived foam cells are a hallmark of atherosclerosis. Scavenger receptors, including lectin-like oxidized low-density lipoprotein (LDL) receptor-1 (OLR-1), are the principal receptors responsible for the uptake and modification of LDL, facilitating macrophage lipid load and the uptake of oxidized LDL by arterial wall cells. Krüppel-like factor 15 (KLF15) is a transcription factor that regulates the expression of genes by binding to the promoter during transcription. Therefore, this study aimed to investigate the precise role of macrophage KLF15 in atherogenesis. METHODS: We used two murine models of atherosclerosis: mice injected with an adeno-associated virus (AAV) encoding the Asp374-to-Tyr mutant version of human PCSK9, followed by 12 weeks on a high-fat diet (HFD), and ApoE-/-- mice on a HFD. We subsequently injected mice with AAV-KLF15 and AAV-LacZ to assess the role of KLF15 in the development of atherosclerosis in vivo. Oil Red O, H&E, and Masson's trichome staining were used to evaluate atherosclerotic lesions. Western blots and RT-qPCR were used to assess protein and mRNA levels, respectively. RESULTS: We determined that KLF15 expression was downregulated during atherosclerosis formation, and KLF15 overexpression prevented atherosclerosis progression. KLF15 expression levels did not affect body weight or serum lipid levels in mice. However, KLF15 overexpression in macrophages prevented foam cell formation by reducing OLR-1-meditated lipid uptake. KLF15 directly targeted and transcriptionally downregulated OLR-1 levels. Restoration of OLR-1 reversed the beneficial effects of KLF15 in atherosclerosis. CONCLUSION: Macrophage KLF15 transcriptionally downregulated OLR-1 expression to reduce lipid uptake, thereby preventing foam cell formation and atherosclerosis. Thus, our results suggest that KLF15 is a potential therapeutic target for atherosclerosis.

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance.

BACKGROUND: Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy. METHODS: An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms. RESULTS: We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments. CONCLUSIONS: The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

Risk factors for renal outcomes in children with antineutrophil cytoplasmic antibody-associated vasculitis: a nationwide retrospective study in China.

BACKGROUND: Pediatric antineutrophil cytoplasmic antibody-associated vasculitis (AAV) is a life-threatening systemic vasculitis featured by liability to renal involvement. However, there are few studies on the risk factors and predictive models for renal outcomes of AAV in children. METHODS: Data from 179 AAV children in multiple centers between January 2012 and March 2020 were collected retrospectively. The risk factors and predictive model of end-stage renal disease (ESRD) in AAV were explored. RESULTS: Renal involvement was the most typical manifestation (95.5%), and the crescent was the predominant pathological lesion (84.9%). The estimated glomerular filtration rate (eGFR) was evaluated in 114 patients, of whom 59.6% developed ESRD, and the median time to ESRD was 3.20 months. The eGFR [P = 0.006, odds ratio (OR) = 0.955, 95% confidence interval (CI) = 0.924-0.987] and the percentages of global glomerulosclerosis (pGGS; P = 0.018, OR = 1.060, 95% CI = 1.010-1.112) were independent risk factors for ESRD of renal biopsy. Based on the pGGS and eGFR at renal biopsy, we developed three risk grades of ESRD and one predictive model. The Kaplan‒Meier curve indicated that renal outcomes were significantly different in different risk grades (P < 0.001). Compared with serum creatinine at baseline, the predictive model had higher accuracy (0.86 versus 0.58, P < 0.001) and a lower coefficient of variation (0.07 versus 0.92) in external validation. CONCLUSIONS: Renal involvement is the most common manifestation of pediatric AAV in China, of which more than half deteriorates into ESRD. The predictive model based on eGFR at renal biopsy and the pGGS may be stable and accurate in speculating the risk of ESRD in AAV children. Supplementary file 2 (MP4 18937 KB).

Validation of a renal risk score in a cohort of children with ANCA-associated glomerulonephritis.

Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is extremely rare in children. Renal involvement is a common and severe complication of AAV as it can cause end stage kidney disease (ESKD). ANCA renal risk score (ARRS) is helpful in predicting long-term ESKD in patients with ANCA-associated glomerulonephritis (AAGN). This retrospective study included 61 consecutive patients with kidney biopsy specimen-proven AAGN from Clinical Center for Children's Kidney Disease in China. Each patient was assessed by eGFR, normal glomeruli, and tubular atrophy/interstitial fibrosis, and the renal outcome was evaluated using the ARRS. Based on the ARRS, 27 (44.26%), 21 (34.43%), and 13 (21.31%) patients were divided into the low-risk, medium-risk, and high-risk groups, respectively. The median follow-up period was 46.36 (14.58-95.62) months. The high-risk group had worse renal outcomes than the low-risk group (p< 0.05) and the medium-risk group (p < 0.05). COX multivariate regression analysis showed that eGFR ≤ 15 ml/min/1.73 m2 (p = 0.015, Hazard Ratio (HR) = 9.574, 95% CI 4.205-25.187) and ARRS (p = 0.012, HR = 2.115, 95% CI 1.206-4.174) were independent risk factors for ESKD.The area under the curve for ESKD prediction of ARRS was 0.880, and the best cutoff value was 5.50. Delong test result showed that ARRS exhibited better predictive value for ESKD than the Berden classification (p < 0.001) and rapidly progressive glomerulonephritis (p < 0.001). This is the first study to investigate the value of the ARRS for predicting renal prognosis among Chinese children. The ARRS is a preferred index that can predict ESKD in Chinese children with AAGN.

A chemotherapy response prediction model derived from tumor-promoting B and Tregs and proinflammatory macrophages in HGSOC.

Background: Most patients with high-grade serous ovarian cancer (HGSOC) experienced disease recurrence with cumulative chemoresistance, leading to treatment failure. However, few biomarkers are currently available in clinical practice that can accurately predict chemotherapy response. The tumor immune microenvironment is critical for cancer development, and its transcriptomic profile may be associated with treatment response and differential outcomes. The aim of this study was to develop a new predictive signature for chemotherapy in patients with HGSOC. Methods: Two HGSOC single-cell RNA sequencing datasets from patients receiving chemotherapy were reinvestigated. The subtypes of endoplasmic reticulum stress-related XBP1+ B cells, invasive metastasis-related ACTB+ Tregs, and proinflammatory-related macrophage subtypes with good predictive power and associated with chemotherapy response were identified. These results were verified in an independent HGSOC bulk RNA-seq dataset for chemotherapy. Further validation in clinical cohorts used quantitative real-time PCR (qRT-PCR). Results: By combining cluster-specific genes for the aforementioned cell subtypes, we constructed a chemotherapy response prediction model containing 43 signature genes that achieved an area under the receiver operator curve (AUC) of 0.97 (p = 2.1e-07) for the GSE156699 cohort (88 samples). A huge improvement was achieved compared to existing prediction models with a maximum AUC of 0.74. In addition, its predictive capability was validated in multiple independent bulk RNA-seq datasets. The qRT-PCR results demonstrate that the expression of the six genes has the highest diagnostic value, consistent with the trend observed in the analysis of public data. Conclusions: The developed chemotherapy response prediction model can be used as a valuable clinical decision tool to guide chemotherapy in HGSOC patients.

Post-translational regulation of muscle growth, muscle aging and sarcopenia.

Skeletal muscle makes up 30-40% of the total body mass. It is of great significance in maintaining digestion, inhaling and exhaling, sustaining body posture, exercising, protecting joints and many other aspects. Moreover, muscle is also an important metabolic organ that helps to maintain the balance of sugar and fat. Defective skeletal muscle function not only limits the daily activities of the elderly but also increases the risk of disability, hospitalization and death, placing a huge burden on society and the healthcare system. Sarcopenia is a progressive decline in muscle mass, muscle strength and muscle function with age caused by environmental and genetic factors, such as the abnormal regulation of protein post-translational modifications (PTMs). To date, many studies have shown that numerous PTMs, such as phosphorylation, acetylation, ubiquitination, SUMOylation, glycosylation, glycation, methylation, S-nitrosylation, carbonylation and S-glutathionylation, are involved in the regulation of muscle health and diseases. This article systematically summarizes the post-translational regulation of muscle growth and muscle atrophy and helps to understand the pathophysiology of muscle aging and develop effective strategies for diagnosing, preventing and treating sarcopenia.

KRASG12C mutation-induced TOPK overexpression contributes to tumour progression in non-small cell lung cancer.

KRAS mutation is the most frequent type of genetic mutation in non-small cell lung cancer (NSCLC), especially in lung adenocarcinoma. However, KRAS mutation can affect many biological processes and the mechanisms underlying KRAS mutation-mediate carcinogenesis in NSCLC have not been fully understood. In this research, we found that KRASG12C mutation was associated with the upregulation of T-LAK cell-originated protein kinase (TOPK), which is a well-known serine/threonine MAPK-like protein kinase implicated in tumorigenesis. The overexpression of TOPK significantly promoted the malignant phenotype of A549 cells, and TOPK silencing impaired the malignant phenotype with KRASG12C mutation. Moreover, we demonstrated that TOPK level was regulated by MAPK/ERK signalling and the transcription factor Elk1. TOPK was also found to promote the activation of NF-κB signalling in A549 cells with KRASG12C mutation via facilitating the phosphorylation of TAK1. In the in vivo tumorigenesis model, the administration of TOPK inhibitor OTS514 enhanced the anticancer effect of 5-FU, and the combinatory use of OTS514 and KRASG12C inhibitor AMG510 showed synergistic anti-tumour effect. These results suggest that KRAS-TOPK axis contributes to the progression of NSCLC and targeting this axis could synergize with anticancer effect of the existing chemotherapeutics.

Comprehensive analysis of the expression and prognosis for RAI2: A promising biomarker in breast cancer.

Introduction: Retinoic acid-induced 2 (RAI2) was initially related to cell differentiation and induced by retinoic acid. RAI2 has been identified as an emerging tumor suppressor in breast cancer and colorectal cancer. Methods: In this study, we performed systematic analyses of RAI2 in breast cancer. Meta-analysis and Kaplan-Meier survival curves were applied to identify the survival prediction potential of RAI2. Moreover, the association between RAI2 expression and the abundance of six tumor-infiltrating immune cells was investigated by TIMER, including B cells, CD8+ T cells, CD4+ T cells, B cells, dendritic cells, neutrophils, and macrophages. The expression profiles of high and low RAI2 mRNA levels in GSE7390 were compared to identify differentially expressed genes (DEGs) and the biological function of these DEGs was analyzed by R software, which was further proved in GSE7390. Results: Our results showed that the normal tissues had more RAI2 expression than breast cancer tissues. Patients with high RAI2 expression were related to a favorable prognosis and more immune infiltrates. A total of 209 DEGs and 182 DEGs were identified between the expression profiles of high and low RAI2 mRNA levels in the GSE7390 and GSE21653 databases, respectively. Furthermore, Gene Ontology (GO) enrichment indicated that these DEGs from two datasets were both mainly distributed in "biological processes" (BP), including "organelle fission" and "nuclear division". Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis demonstrated that these DEGs from two datasets were both significantly enriched in the "cell cycle". Common hub genes between the DEGs in GSE7390 and GSE21653 were negatively associated with RAI2 expression, including CCNA2, MAD2L1, MELK, CDC20, and CCNB2. Discussions: These results above suggested that RAI2 might play a pivotal role in preventing the initiation and progression of breast cancer. The present study may contribute to understanding the molecular mechanisms of RAI2 and enriching biomarkers to predict patient prognosis in breast cancer.

Molecular features and predictive models identify the most lethal subtype and a therapeutic target for osteosarcoma.

Background: Osteosarcoma is the most common primary malignant bone tumor. The existing treatment regimens remained essentially unchanged over the past 30 years; hence the prognosis has plateaued at a poor level. Precise and personalized therapy is yet to be exploited. Methods: One discovery cohort (n=98) and two validation cohorts (n=53 & n=48) were collected from public data sources. We performed a non-negative matrix factorization (NMF) method on the discovery cohort to stratify osteosarcoma. Survival analysis and transcriptomic profiling characterized each subtype. Then, a drug target was screened based on subtypes' features and hazard ratios. We also used specific siRNAs and added a cholesterol pathway inhibitor to osteosarcoma cell lines (U2OS and Saos-2) to verify the target. Moreover, PermFIT and ProMS, two support vector machine (SVM) tools, and the least absolute shrinkage and selection operator (LASSO) method, were employed to establish predictive models. Results: We herein divided osteosarcoma patients into four subtypes (S-I ~ S-IV). Patients of S- I were found probable to live longer. S-II was characterized by the highest immune infiltration. Cancer cells proliferated most in S-III. Notably, S-IV held the most unfavorable outcome and active cholesterol metabolism. SQLE, a rate-limiting enzyme for cholesterol biosynthesis, was identified as a potential drug target for S-IV patients. This finding was further validated in two external independent osteosarcoma cohorts. The function of SQLE to promote proliferation and migration was confirmed by cell phenotypic assays after the specific gene knockdown or addition of terbinafine, an inhibitor of SQLE. We further employed two machine learning tools based on SVM algorithms to develop a subtype diagnostic model and used the LASSO method to establish a 4-gene model for predicting prognosis. These two models were also verified in a validation cohort. Conclusion: The molecular classification enhanced our understanding of osteosarcoma; the novel predicting models served as robust prognostic biomarkers; the therapeutic target SQLE opened a new way for treatment. Our results served as valuable hints for future biological studies and clinical trials of osteosarcoma.

Self-Assembled Nanodelivery System with Rapamycin and Curcumin for Combined Photo-Chemotherapy of Breast Cancer.

Nanodelivery systems combining photothermal therapy (PTT) and chemotherapy (CT), have been widely used to improve the efficacy and biosafety of chemotherapeutic agents in cancer. In this work, we constructed a self-assembled nanodelivery system, formed by the assembling of photosensitizer (IR820), rapamycin (RAPA), and curcumin (CUR) into IR820-RAPA/CUR NPs, to realize photothermal therapy and chemotherapy for breast cancer. The IR820-RAPA/CUR NPs displayed a regular sphere, with a narrow particle size distribution, a high drug loading capacity, and good stability and pH response. Compared with free RAPA or free CUR, the nanoparticles showed a superior inhibitory effect on 4T1 cells in vitro. The IR820-RAPA/CUR NP treatment displayed an enhanced inhibitory effect on tumor growth in 4T1 tumor-bearing mice, compared to free drugs in vivo. In addition, PTT could provide mild hyperthermia (46.0 °C) for 4T1 tumor-bearing mice, and basically achieve tumor ablation, which is beneficial to improving the efficacy of chemotherapeutic drugs and avoiding damage to the surrounding normal tissue. The self-assembled nanodelivery system provides a promising strategy for coordinating photothermal therapy and chemotherapy to treat breast cancer.

Protective Effect of the SIRT1-Mediated NF-κB Signaling Pathway against Necrotizing Enterocolitis in Neonatal Mice.

OBJECTIVE: To discover the mechanism of the sirtuin 1 (SIRT1)-mediated nuclear factor-κB (NF-κB) pathway in the protection against necrotizing enterocolitis (NEC) in neonatal mice. MATERIALS AND METHODS: Neonatal mice were treated with EX527 (an inhibitor of SIRT1) and/or pyrrolidine dithiocarbamate (PDTC, an inhibitor of NF-κB). The survival rate of the mice was recorded. Hematoxylin and eosin (HE) staining was performed to observe the pathological changes in the intestines. Furthermore, western blotting, enzyme-linked immunosorbent assay, and real-time quantitative polymerase chain reaction were conducted to measure the protein and gene expression, while corresponding kits were used to detect the levels of oxidative stress indicators. RESULTS: PDTC increased the survival rate of NEC mice. When compared with the NEC+ EX527 + PDTC group, the histological NEC score was higher in the NEC + EX527 group but lower in the NEC + PDTC group. SIRT1 expression in the intestines of NEC mice was downregulated, with an increase in p65 nuclear translocation. Additionally, malondialdehyde increased and glutathione peroxidase decreased in the intestines of NEC mice, with the upregulation of interleukin (IL)-6, IL-1ß, and tumor necrosis factor-α, as well as the downregulation of ZO-1, occludin, and claudin-4 in the intestines. However, the above changes could be improved by PDTC, which could be further reversed by EX527. CONCLUSION: SIRT1 can mitigate inflammation and the oxidative stress response and improve intestinal permeability by mediating the NF-κB pathway, playing an important role in the alleviation of NEC.

A methylation-related signature for predicting prognosis and sensitivity to first-line therapies in gastric cancer.

Background: Methylation modification patterns play a crucial role in human cancer progression, especially in gastrointestinal cancers. We aimed to use methylation regulators to classify patients with gastric adenocarcinoma and build a model to predict prognosis, promoting the application of precision medicine. Methods: We obtained RNA sequencing data and clinical data from The Cancer Genome Atlas (TCGA) database (n=335) and Gene Expression Omnibus (GEO) database (n=865). Unsupervised consensus clustering was used to identify subtypes of gastric adenocarcinoma. We performed functional enrichment analysis, immune infiltration analysis, drug sensitivity analysis, and molecular feature analysis to determine the clinical application for different subtypes. The univariate Cox regression analysis and the LASSO regression analysis were subsequently used to identify prognosis-related methylation regulators and construct a risk model. Results: Through unsupervised consensus clustering, patients were divided into two subtypes (cluster A and cluster B) with different clinical outcomes. Cluster B included patients with a better prognosis outcome and who were more likely to respond to immunotherapy. We then successfully built a predictive model and found five methylation-related genes (CHAF1A, CPNE8, PHLDA3, SPARC, and EHF) potentially significant to the prognosis of patients. The 1-, 3-, and 5-year areas under the curve of the risk model were 0.712, 0.696, and 0.759, respectively. The risk score was an independent prognostic factor and had the highest concordance index among common clinical indicators. Meanwhile, the tumor microenvironment, sensitivity of chemotherapeutic drugs, molecular features, and oncogenic dedifferentiation differed significantly across the risk groups and subtypes. Conclusions: We classified patients with gastric adenocarcinoma based on methylation regulators, which has positive implications for first-line clinical treatment. The prognostic model could predict the prognosis of patients and help to promote the development of precision medicine.