Prognostic value of creatine kinase (CK)-MB to total-CK ratio in colorectal cancer patients after curative resection.

OBJECTIVES: This study aimed to evaluate the prognostic significance of postoperative Creatine Kinase type M and B (CK-MB) to total Creatine Kinase (CK) ratio (CK-MB/CK) in colorectal cancer (CRC) patients after radical resection. METHODS: This was a single-center retrospective cohort analysis. Subjects were stage I-III CRC patients hospitalized in Sichuan Cancer Hospital from January 2017 to May 2021. Patients were divided into abnormal group and normal group according to whether the CK-MB/CK ratio was abnormal after surgery. Through a comparative analysis of clinical data, laboratory test results, and prognosis differences between the two groups, we aimed to uncover the potential relationship between abnormal CK-MB > CK results and CRC patients. To gauge the impact of CK-MB/CK on overall survival (OS) and disease-free survival (DFS), we employed the multivariable COX regression and LASSO regression analysis. Additionally, Spearman correlation analysis, logistic regression, and receiver-operating characteristic (ROC) curve analysis were conducted to assess the predictive value of the CK-MB/CK ratio for postoperative liver metastasis. RESULTS: Cox regression analysis revealed that the CK-MB/CK ratio was a stable risk factors for OS (HR = 3.82, p < 0.001) and DFS (HR = 2.31, p < 0.001). To distinguish hepatic metastases after surgery, the ROC area under the curve of CK-MB/CK was 0.697 (p < 0.001), and the optimal cut-off value determined by the Youden index was 0.347. CONCLUSIONS: Postoperative abnormal CK-MB/CK ratio predicts worse prognosis in CRC patients after radical resection and serves as a useful biomarker for detecting postoperative liver metastasis.

Signal amplification strategy of DNA self-assembled biosensor and typical applications in pathogenic microorganism detection.

Biosensors have emerged as ideal analytical devices for various bio-applications owing to their low cost, convenience, and portability, which offer great potential for improving global healthcare. DNA self-assembly techniques have been enriched with the development of innovative amplification strategies, such as dispersion-to-localization of catalytic hairpin assembly, and dumbbell hybridization chain reaction, which hold great significance for building biosensors capable of realizing sensitive, rapid and multiplexed detection of pathogenic microorganisms. Here, focusing primarily on the signal amplification strategies based on DNA self-assembly, we concisely summarized the strengths and weaknesses of diverse isothermal nucleic acid amplification techniques. Subsequently, both single-layer and cascade amplification strategies based on traditional catalytic hairpin assembly and hybridization chain reaction were critically explored. Furthermore, a comprehensive overview of the recent advances in DNA self-assembled biosensors for the detection of pathogenic microorganisms is presented to summarize methods for biorecognition and signal amplification. Finally, a brief discussion is provided about the current challenges and future directions of DNA self-assembled biosensors.

Platelet-Based Nanoparticles with Stimuli-Responsive for Anti-Tumor Therapy.

In addition to hemostasis and coagulation, years of studies have proved that platelets are involved in the whole process of tumor progression, including tumor invasion, intravasation, extravasation, and so on. It means that this property of platelets can be used in anti-tumor therapy. However, traditional platelet-based antitumor drugs often cause autologous platelet damage due to lack of targeting, resulting in serious side effects. Therefore, the researchers designed a variety of anti-tumor drug delivery systems based on platelets by targeting platelets or platelet membrane coating. The drug delivery systems have special response modes, which is crucial in the design of nanoparticles. These modes enhance the targeting and improve the anti-tumor effect. Here, we present a review of recent discoveries in the field of the crosstalk between platelets and tumors and the progress of platelet-based anti-tumor nanoparticles.

A prognostic nomogram that includes MPV in esophageal squamous cell carcinoma.

BACKGROUND: Mean platelet volume (MPV), as a marker of platelet activity, has been shown to be an efficient prognostic biomarker in several types of cancer. Using MPV, this study aimed to create and validate a prognostic nomogram to the overall survival in esophageal squamous cell carcinoma (ESCC) patients. METHODS: The nomogram was constructed and tested using data from a retrospective study of 1893 patients who were randomly assigned to the training and testing cohorts with a 7:3 randomization. In order to screen out the optimal predictors for overall survival (OS), we conducted the LASSO-cox regression, univariate, and multivariate cox regression analyses. Subsequently, the predictive accuracy of the nomogram was validated in both the training and the testing cohorts. Finally, decision curve analysis (DCA) was used to confirm clinical validity. RESULTS: Age, MPV, nerve invasion, T stage, and N stage were found as independent prognostic variables for OS and were further developed into a nomogram. The nomogram's prediction accuracy for 1-, 3-, and 5-year OS was 0.736, 0.749, 0.774, and 0.724, 0.719, 0.704 in the training and testing cohorts, respectively. Furthermore, DCA results indicated that nomograms outperformed the AJCC 8th and conventional T, N staging systems in both the training and testing cohorts. CONCLUSIONS: The nomogram, in conjunction with MPV and standard clinicopathological markers, could improve the accuracy of prediction of OS in ESCC patients.

The Progress of Platelets in Breast Cancer.

Breast cancer is the most common female cancer and the sixth leading cause of death, seriously affecting the quality of life of women. Platelets, one of the fragments derived from megakaryocytes, are being increasingly investigated by tumor researchers because of their anticoagulant function. According to relevant studies, platelets, as the key source of circulating angiogenesis-related factors, can regulate tumor angiogenesis and vascular integrity, and they can also affect the tumor microenvironment, thereby facilitating the proliferation and differentiation of tumor cells. By covering or transferring normal MHC I molecules to tumor cells, platelets can protect tumor cells from being killed by the immune system and facilitate tumor cell metastasis. However, details on the mechanisms involved have remained elusive. This paper reviews and analyzes studies of the role of platelets in tumorigenesis, tumor cell proliferation, tumor metastasis, and cancer treatment to provide readers with a better understanding of the relevant studies.

Machine learning­based prediction of survival prognosis in esophageal squamous cell carcinoma.

The current prognostic tools for esophageal squamous cell carcinoma (ESCC) lack the necessary accuracy to facilitate individualized patient management strategies. To address this issue, this study was conducted to develop a machine learning (ML) prediction model for ESCC patients' survival management. Six ML approaches, including Rpart, Elastic Net, GBM, Random Forest, GLMboost, and the machine learning-extended CoxPH method, were employed to develop risk prediction models. The model was trained on a dataset of 1954 ESCC patients with 27 clinical features and validated on a dataset of 487 ESCC patients. The discriminative performance of the models was assessed using the concordance index (C-index). The best performing model was used for risk stratification and clinical evaluation. The study found that N stage, T stage, surgical margin, tumor grade, tumor length, sex, MPV, AST, FIB, and Mg are the important feature for ESCC patients' survival. The machine learning-extended CoxPH model, Elastic Net, and Random Forest had similar performance in predicting the mortality risk of ESCC patients, and outperformed GBM, GLMboost, and Rpart. The risk scores derived from the CoxPH model effectively stratified ESCC patients into low-, intermediate-, and high-risk groups with distinctly different 3-year overall survival (OS) probabilities of 80.8%, 58.2%, and 29.5%, respectively. This risk stratification was also observed in the validation cohort. Furthermore, the risk model demonstrated greater discriminative ability and net benefit than the AJCC8th stage, suggesting its potential as a prognostic tool for predicting survival events and guiding clinical decision-making. The classical algorithm of the CoxPH method was also found to be sufficiently good for interpretive studies.

Serum laser Raman spectroscopy as a potential diagnostic tool to discriminate the benignancy or malignancy of pulmonary nodules.

It has been proved that Raman spectral intensities could be used to diagnose lung cancer patients. However, the application of Raman spectroscopy in identifying the patients with pulmonary nodules was barely studied. In this study, we revealed that Raman spectra of serum samples from healthy participants and patients with benign and malignant pulmonary nodules were significantly different. A support vector machine (SVM) model was developed for the classification of Raman spectra with wave points, according to ANOVA test results. It got a good performance with a median area under the curve (AUC) of 0.89, when the SVM model was applied in discriminating benign from malignant individuals. Compared with three common clinical models, the SVM model showed a better discriminative ability and added more net benefits to participants, which were also excellent in the small-size nodules. Thus, the Raman spectroscopy could be a less-invasive and low-costly liquid biopsy.

Identification and panoramic analysis of drug response-related genes in triple negative breast cancer using as an example NVP-BEZ235.

Taking NVP-BEZ235 (BEZ235) as an example to screen drug response-related genes (DRRGs) and explore their potential value in triple-negative breast cancer (TNBC). Through high-throughput technique, multidimensional transcriptome expression data (mRNA, miRNA and lncRNA) of BEZ235-treated and -untreated MDA-MB-468 cell lines were obtained. Combined with transcriptome data of the MDA-MB-468 cells and TCGA-TNBC tissues, differential gene expression analysis and WGCNA were performed to identify DRRGs associated with tumor trait by simulating the drug response microenvironment (DRM) of BEZ235-treated patients. Based on DRRGs, we constructed a ceRNA network and verified the expression levels of three key molecules by RT-qPCR, which not only demonstrated the successful construction of a BEZ235-treated cell line model but also explained the antitumor mechanism of BEZ235. Four molecular subtypes related to the DRM with survival difference were proposed using cluster analysis, namely glycolysis subtype, proliferation depression subtype, immune-suppressed subtype, and immune-activated subtype. A novel prognostic signature consisting of four DRRGs was established by Lasso-Cox analysis, which exhibited outstanding performance in predicting overall survival compared with several excellent reported signatures. The high- and low-risk groups were characterized by enrichment of metabolism-related pathways and immune-related pathways, respectively. Of note, the low-risk group had a better response to immune checkpoint blockade. Besides, pRRophetic analysis found that patients in the low-risk group were more sensitive to methotrexate and cisplation, whereas more resistant to BEZ235, docetaxel and paclitaxel. In conclusion, the DRRGs exemplified by BEZ235 are potential biomarkers for TNBC molecular typing, prognosis prediction and targeted therapy. The novel DRRGs-guided strategy for predicting the subtype, survival and therapy efficacy, might be also applied to more cancers and drugs other than TNBC and BEZ235.

Clinical relevance of plasma EBV DNA as a biomarker for nasopharyngeal carcinoma in non-endemic areas: A multicenter study in southwestern China.

BACKGROUND: Numerous clinical studies have validated plasma EBV DNA as a reliable biomarker for nasopharyngeal carcinoma (NPC) screening, tumor load monitoring, and prognosis prediction in endemic regions. However, the clinical relevance of plasma EBV DNA as a biomarker for NPC in non-endemic areas is still unclear. METHOD: The pretreatment plasma EBV DNA of 1405 newly diagnosed NPC patients from three major regional hospitals in non-endemic areas were analyzed retrospectively. The medical records of 244 age- and gender-matched healthy individuals were reviewed. EBV DNA was detected using Polymerase Chain Reaction (PCR). Based on the baseline of 400 and 0 copies/mL, the distribution characteristics of the pretreatment EBV DNA load in different clinical stages and geographic regions were analyzed. The diagnostic value of pretreatment plasma EBV DNA for NPC with two baselines was evaluated using the ROC curve. RESULTS: NPC patients had a significantly higher pretreatment EBV DNA level than healthy controls (P＜0.001). Pretreatment EBV DNA was closely associated with clinical and TNM stages in non-endemic areas, as it was in endemic areas. However, when 400 copies/mL set as the detection baseline, the sensitivity and specificity for NPC diagnosis were 40.8 % and 100 %, respectively (AUC = 0.704, cut off = 200.5 copies/mL). This sensitivity was lower than that reported in endemic regions (41.5 % - 97.1 %). Lower sensitivity may result in false negatives, missing diagnoses during NPC screening. Further investigation revealed that 39.7 % (558/1405) of NPC patients had detectable EBV DNA and S amplification curves. Optimizing the detection limit to 0 copies/mL, the sensitivity could be improved to 80.5 % (AUC = 0.901). CONCLUSIONS: In non-endemic areas, the clinical significance of plasma EBV DNA as a biomarker for NPC was restricted due to the low detection limit of 400 copies/mL. More efficient nucleic acid extraction and detection methods are needed to optimize the detection limit and increase the clinical application of plasma EBV DNA for NPC.

Isothermal amplification based on specific signal extraction and output for fluorescence and colorimetric detection of nucleic acids.

Due to the complexity of compositions and low abundance of target in clinical sample, nucleic acids detection often suffers from false positives caused by nonspecific amplification. In in vitro diagnosis (IVD), PCR usually employ TaqMan probe to report specific signals and block false positive signals. However, nucleic acid isothermal amplifications, such as loop-mediated isothermal amplification (LAMP), lack of mature specific signal output mechanism, which prevents them from being used for IVD and point-of-care testing (POCT). In this work, we constructed a specific signal extract-to-output isothermal detection system (SSEI). SSEI contains a well-designed DNA probe for specific signal extraction and output in LAMP. This probe is a double-stranded DNA with an overhang sequence and named as extract-to-output probe (ETO probe). ETO probe can recognize the target-specific intermediate products in LAMP and release another signal-output probe (OP) to report the target-specific signals. With these unique properties, SSEI can detect as low as 10 copies of target DNA per reaction either by fluorescence detector or naked eyes. Moreover, due to the excellent performance against background nucleic acids interference, this biosensing platform had been successfully used for hepatitis B virus (HBV) clinical samples detection.

Adjuvant chemotherapy for lymph node positive esophageal squamous cell cancer: The prediction role of low mean platelet volume.

Background: This study aimed to examine whether MPV is a useful prognostic marker and investigated whether MPV is a risk factor that helps identify patients with locally advanced-stage ESCC who will most likely benefit from adjuvant chemotherapy. Methods: Patients (n =1690) with histologically confirmed ESCC were diagnosed with locally advanced stage (pT3-4N0M0 and pT1-4N+M0) at Sichuan Cancer Hospital from 2009 to 2017. Clinicopathological factors and platelet-related values were tested for their associations with survival using univariate and multivariate Cox regression analyses. The optimal cut-off value for continuous variables was determined using the 'maxstat' R package. The KM curve continuous variable analysis was performed to identify the optimal cut-off value for MPV. Cumulative survival rates were determined using the Kaplan-Meier estimator and compared using the log-rank test. The survival analysis was performed using the 'survival' R package. All statistical analyses were performed using R software 4.1.3 (https://www.r-project.org/), and a two-sided p-value <0.05 was considered to indicate statistical significance. Results: Multivariate analysis indicated that low MPV was an important risk factor for overall survival in locally advanced ESCC, independent of classic clinicopathological factors. The optimal cut-off value of MPV (11.8 fL) was used to stratify high-risk patients. Patients with low mean platelet volumes had a worse prognosis than those with larger platelet volumes, according to Kaplan-Meier analysis and the log-rank test. Patients diagnosed with a pathological lymph node-positive stage with a low MPV (≤11.8 fL) benefited from postoperative chemotherapy, but not those with a high-level MPV (>11.8 fL). Conclusion: MPV served as an independent predictor of prognosis of locally advanced-stage ESCC and predicted a survival benefit conferred by postoperative adjuvant chemotherapy in lymph node-positive ESCC.

Prognostic value of nutritional and inflammatory indicators in females with esophageal squamous cell cancer: A propensity score matching study.

Background: Esophageal squamous cell cancer (ESCC) is a disease with a male predominance. Accordingly, the applicability of prognostic indicators values previously set for the general population with ESCC has not been reported for determining the physical state in females. Methods: Patients with ESCC were pooled from 2009 to 2017 at Sichuan Cancer Hospital. We determined the differences in the nutritional and inflammatory indicators between gender by sex-stratified survival analysis in all cohorts (n = 2,660) and matching cohorts (n = 483 pairs) separately. Propensity score matching (PSM) was employed to eliminate selection bias between genders. We further performed the prognostic value of total cholesterol (TC) by subgroup analysis in the female cohort. The area ROC curve was used to assess the predictive performance of TC in females. Results: There were a total of 2,660 patients with ESCC, of whom 2,173 (81.7%) were male and 487 (18.3%) were female. Before PSM, the prognostic nutritional index was an independent factor for OS in males but not in females. For cohort with or without matching, TC was an independent prognostic factor in females not for males. Furthermore, female patients with high TC level had significant poor OS in stages III and IV. The AUCs of TC were 0.63 and 0.70 for predicting 3- and 5-year OS, respectively. Conclusion: Based on a much larger cohort, we confirmed that gender was a significant prognostic factor for ESCC patients. Interestingly, we found a significant difference in TC related to ESCC prognosis between genders. Collectively, TC might be an independent prognostic factor in females with ESCC.

Clinlabomics: leveraging clinical laboratory data by data mining strategies.

The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up to now, AI has been applied to various aspects of medicine, including disease diagnosis, surveillance, treatment, predicting future risk, targeted interventions and understanding of the disease. There have been plenty of successful examples in medicine of using big data, such as radiology and pathology, ophthalmology cardiology and surgery. Combining medicine and AI has become a powerful tool to change health care, and even to change the nature of disease screening in clinical diagnosis. As all we know, clinical laboratories produce large amounts of testing data every day and the clinical laboratory data combined with AI may establish a new diagnosis and treatment has attracted wide attention. At present, a new concept of radiomics has been created for imaging data combined with AI, but a new definition of clinical laboratory data combined with AI has lacked so that many studies in this field cannot be accurately classified. Therefore, we propose a new concept of clinical laboratory omics (Clinlabomics) by combining clinical laboratory medicine and AI. Clinlabomics can use high-throughput methods to extract large amounts of feature data from blood, body fluids, secretions, excreta, and cast clinical laboratory test data. Then using the data statistics, machine learning, and other methods to read more undiscovered information. In this review, we have summarized the application of clinical laboratory data combined with AI in medical fields. Undeniable, the application of Clinlabomics is a method that can assist many fields of medicine but still requires further validation in a multi-center environment and laboratory.

A novel prognostic model for malignant patients with Gram-negative bacteremia based on real-world research.

Gram-negative bacteremia (GNB) is a common complication in malignant patients. Identifying risk factors and developing a prognostic model for GNB might improve the survival rate. In this observational and real-world study, we retrospectively analyzed the risk factors and outcomes of GNB in malignant patients. Multivariable regression was used to identify risk factors for the incidence of GNB, while Cox regression analysis was performed to identify significant prognostic factors. A prognostic model was constructed based on Cox regression analysis and presented on a nomogram. ROC curves, calibration plots, and Kaplan-Meier analysis were used to estimate the model. It comprised 1004 malignant patients with Bloodstream infection (BSI) in the study cohort, 65.7% (N = 660) acquired GNB. Multivariate analysis showed gynecologic cancer, hepatobiliary cancer, and genitourinary cancer were independent risk factors related to the incidence of GNB. Cox regression analysis raised that shock, admission to ICU before infection, pulmonary infection, higher lymphocyte counts, and lower platelet counts were independent risk factors for overall survival (OS). The OS was significantly different between the two groups classified by optimal cut-off value (log-rank, p < 0.001). Above all, a nomogram was created based on the prognostic model, which was presented on a website freely. This real-world study was concentrated on the malignant patients with GNB and proved that shock, admission to ICU before infection, pulmonary infection, higher lymphocyte counts, and lower platelet counts were related to the death of these patients. And a prognostic model was constructed to estimate the risk score of mortality, further to reduce the risk of death.

Selection and Validation of Reference Genes for Pan-Cancer in Platelets Based on RNA-Sequence Data.

Many studies in recent years have demonstrated that some messenger RNA (mRNA) in platelets can be used as biomarkers for the diagnosis of pan-cancer. The quantitative real-time polymerase chain reaction (RT-qPCR) molecular technique is most commonly used to determine mRNA expression changes in platelets. Accurate and reliable relative RT-qPCR is highly dependent on reliable reference genes. However, there is no study to validate the reference gene in platelets for pan-cancer. Given that the expression of some commonly used reference genes is altered in certain conditions, selecting and verifying the most suitable reference gene for pan-cancer in platelets is necessary to diagnose early stage cancer. This study performed bioinformatics and functional analysis from the RNA-seq of platelets data set (GSE68086). We generated 95 candidate reference genes after the primary bioinformatics step. Seven reference genes (YWHAZ, GNAS, GAPDH, OAZ1, PTMA, B2M, and ACTB) were screened out among the 95 candidate reference genes from the data set of the platelets' transcriptome of pan-cancer and 73 commonly known reference genes. These candidate reference genes were verified by another platelets expression data set (GSE89843). Then, we used RT-qPCR to confirm the expression levels of these seven genes in pan-cancer patients and healthy individuals. These RT-qPCR results were analyzed using the internal stability analysis software programs (the comparative Delta CT method, geNorm, NormFinder, and BestKeeper) to rank the candidate genes in the order of decreasing stability. By contrast, the GAPDH gene was stably and constitutively expressed at high levels in all the tested samples. Therefore, GAPDH was recommended as the most suitable reference gene for platelet transcript analysis. In conclusion, our result may play an essential part in establishing a molecular diagnostic platform based on the platelets to diagnose pan-cancer.

A new classifier constructed with platelet features for malignant and benign pulmonary nodules based on prospective real-world data.

Objectives: As the pulmonary nodules were hard to be discriminated as benignancy or malignancy only based on imageology, a prospective and observational real-world research was devoted to develop and validate a predictive model for managing the diagnostic challenge. Methods: This study started in 2018, and a predictive model was constructed using eXtreme Gradient Boosting (XGBoost) based on computed tomographic, clinical, and platelet data of all the eligible patients. And the model was evaluated and compared with other common models using ROC curves, continuous net reclassification improvement (NRI), integrated discrimination improvement (IDI), and net benefit (NB). Subsequently, the model was validated in an external cohort. Results: The development group included 419 participants, while there were 62 participants in the external validation cohort. The most accurate XGBoost model called SCHC model including age, platelet counts in platelet rich plasma samples (pPLT), plateletcrit in platelet rich plasma samples (pPCT), nodule size, and plateletcrit in whole blood samples (bPCT). In the development group, the SCHC model performed well in whole group and subgroups. Compared with VA, MC, BU model, the SCHC model had a significant improvement in reclassification as assessed by the NRI and IDI, and could bring the patients more benefits. For the external validation, the model performed not as well. The algorithm of SCHC, VA, MC, and BU model were first integrated using a web tool (http://i.uestc.edu.cn/SCHC). Conclusions: In this study, a platelet feature-based model could facilitate the discrimination of early-stage malignancy from benignancy patients, to ensure accurate diagnosis and optimal management. This research also indicated that common laboratory results also had the potential in diagnosing cancers.

The ability of inflammatory markers to recognize infection in cancer patients with fever at admission.

Infection is one of the main causes of death in cancer patients. Accurate identification of fever caused by infection could avoid unnecessary antibiotic treatment and hospitalization. This study evaluated the diagnostic value of procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6), interleukin-10 (IL-10), and other commonly used inflammatory markers in suspected infected adult cancer patients with fever, for better use of antibiotics. This research retrospective analyzed the clinical data of 102 adult cancer patients with fever and compared the serum levels of commonly used inflammatory markers for different fever reasons. Receiver-operating characteristic (ROC) curve and logistic regression analyses were performed. In adult cancer patients with fever, the serum PCT, CRP, IL-6, and IL-10 levels of infected patients were significantly higher than uninfected patients (median 1.19 ng/ml vs 0.14 ng/ml, 93.11 mg/l vs 56.55 mg/l, 123.74 pg/ml vs 47.35 pg/ml, 8.74 pg/ml vs 3.22 pg/ml; Mann-Whitney p = 0.000, p = 0.009, p = 0.004, p = 0.000, respectively). The ROC area under the curve(AUC) was 0.769 (95% confidence interval (CI) 0.681-0.857; p = 0.000) for PCT, 0.664 (95% CI 0.554-0.775; p = 0.009) for CRP, 0.681(95% CI 0.576-0.785; p = 0.004) for IL-6, and 0.731(95% CI 0.627-0.834; p = 0.000) for IL-10. PCT had specificity of 96.67% and positive predictive value (PPV) of 97.6%, when the cut-off value is set as 0.69 ng/ml. The serum IL-6 and IL-10 levels also had significant differences between the infected and uninfected cancer patients with advanced disease (median 128.92 pg/ml vs 36.40 pg/ml, 8.05 pg/ml vs 2.92 pg/ml; Mann-Whitney p = 0.003, p = 0.001, respectively). For the patients with neutropenia, IL-6 and IL-10 had higher AUC of 0.811 and 0.928, respectively. With a cut-off of 9.10 pg/ml, IL-10 had the highest sensitivity 83.33% and specificity 100%. In adult cancer patients, PCT had the best performance compared to CRP, IL-6, and IL-10 in differentiating infected from uninfected causes of fever, with high specificity and PPV. IL-6 and IL-10 might be useful in cancer patients with severe bloodstream infections and advanced disease. However, for patients with neutropenia, IL-10 might be more valuable than PCT in diagnosing infection.

Targeted Intervention of NF2-YAP Signaling Axis in CD24-Overexpressing Cells Contributes to Encouraging Therapeutic Effects in TNBC.

Triple-negative breast cancer (TNBC) cells have not been usefully classified, and no targeted therapeutic plans are currently available, resulting in a high recurrence rate and metastasis potential. In this research, CD24high cells accounted for the vast majority of TNBC cells, and they were insensitive to Taxol but sensitive to ferroptosis agonists and effectively escaped phagocytosis by tumor-associated macrophages. Furthermore, the NF2-YAP signaling axis modulated the expression of ferroptosis suppressor protein 1 (FSP1) and CD24 in CD24high cells, with subsequent ferroptotic regulation and macrophage phagocytosis. In addition, a precision targeted therapy system was designed based on the pH level and glutathione response, and it can be effectively used to target CD24high cells to induce lysosomal escape and drug burst release through CO2 production, resulting in enhanced ferroptosis and macrophage phagocytosis through FSP1 and CD24 inhibition mediated by the NF2-YAP signaling axis. This system achieved dual antitumor effects, ultimately promoting cell death and thus inhibiting TNBC tumor growth, with some tumors even disappearing. The composite nanoprecision treatment system reported in this paper is a potential strategic tool for future use in the treatment of TNBC.

CircSEC24A promotes tumor progression through sequestering miR-455-3p in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) ranks third in the cause of death due to cancer. Circular RNA circSEC24 Homolog A (circSEC24A) has been uncovered to be upregulated in liver cancer. However, the function of circSEC24A in HCC is indistinct. We analyzed the microarray datasets GSE78520 and GSE94508 to search for differentially expressed circRNAs associated with HCC. Expression of circSEC24A, microRNA (miR)-455-3p, and protein phosphatase, Mg2+/Mn2+ dependent 1F (PPM1F) mRNA was detected by quantitative real-time polymerase chain reaction (RT-qPCR). Loss-of-function experiments were conducted to validate the biological function of circSEC24A in HCC cells in vitro and in vivo. Protein levels were evaluated by western blotting and immunohistochemistry (IHC). The relationship between circSEC24A or PPM1F and miR-455-3p was verified by a dual-luciferase reporter and/or RNA immunoprecipitation (RIP) assays. circSEC24A was overexpressed in HCC. circSEC24A silencing decreased xenograft tumor growth in vivo and repressed proliferation, metastasis, invasion, epithelial-to-mesenchymal transition (EMT), induced cell cycle arrest, and apoptosis of HCC cells in vitro. circSEC24A acted as a molecular sponge to sequester miR-455-3p, resulting in elevating the expression of PPM1F. miR-455-3p inhibitor reversed the suppressive impact of circSEC24A silencing on malignant behaviors of HCC cells. PPM1F overexpression offsets the inhibitory effect of miR-455-3p mimic on malignant behaviors of HCC cells. circSEC24A sponged miR-455-3p to elevate the PPM1F expression, resulting in accelerating malignant behaviors of HCC cells. The study provided a potential therapeutic target for patients with HCC.

Analysis of drug-resistance-associated mutations and genetic barriers in hepatitis C virus NS5B sequences in China.

The hepatitis C virus (HCV) NS5B protein is an RNA-dependent RNA polymerase that is required for viral genome replication and constitutes the most important target region for drugs being developed as direct-acting antivirals (DAAs) against HCV genotype 1. However, the extreme genetic variability leading to drug resistance mutations and genetic barriers has dramatically compromised the effectiveness of DAA therapy. The purpose of this study was to analyze the genetic variability of NS5B polymerase in HCV patients from different provinces of China to identify the impact of these resistance sites on genetic barriers. We analyzed 3489 NS5B sequences of HCV strains circulating in different regions of China, obtained from the GenBank database, 153 of which were from three cities in Sichuan Province (Yibin, Zigong and Zhangzhou). Sequence alignment was conducted using MEGA 6.0, the genetic information was translated into amino acids, and the percentage of polymorphic amino acid sites was calculated. The Vijver method was used to evaluate the occurrence of genetic barriers in HCV NS5B sequences. Blood samples were collected from 153 HCV patients from Sichuan for NS5B sequence analysis using real-time PCR and the Sanger method. Of the 17 antiviral drug resistance sites summarized from the published literature, nine were found in Chinese NS5B sequences, and C316Y was identified as the dominant mutation. Analysis of genetic barriers revealed that the probability of mutation to a drug-resistance-associated amino acid, in response to selective pressure from antiviral drugs was 100% at site 96 and 99.7% at site 282. Our study is the first to analyze the drug resistance sites and to evaluate genetic barriers in NS5B sequences that could affect the responsiveness of Chinese HCV patients to DAA therapy. The results provide a valuable basis for drug development and introduction of foreign-origin antiviral drugs in China that targeting the HCV NS5B region.