Aspartate Transaminase-to-Albumin Ratio (ATAR), a Novel Prognostic Index, Predicts Outcomes in Patients with Small-Cell Lung Cancer.

BACKGROUND: Small cell lung cancer (SCLC) is characterized by high invasion rates, rapid progression, and poor prognoses. Thus, identifying SCLC patients at high risk of progression and death is critical to improve long-term survival. In this study, the aspartate transaminase-to-albumin ratio (ATAR) was examined as a prognostic factor for SCLC patients. METHODS: We screened 196 SCLC patients from December 2013 to September 2022 at the Sichuan Cancer Hospital. The data was collected from patients' medical information as well as from their blood results during diagnosis. Using the Youden index as a cutoff value, patients were divided into high-risk（> 0.54) and low-risk (≤ 0.54) ATAR groups. We analyzed the prognostic factors for overall survival (OS) using the Kaplan-Meier method, univariate and multivariate analyses, Cox regression, and the C-index. RESULTS: There were 109 (55.6%) smokers among the patients, and the median OS was 17.55 months. The Kaplan-Meier analysis indicated that patients with high-risk ATAR had significantly lower OS (p < 0.0001). A multivariate analysis demonstrated that elevated ATAR is an independent adverse predictor of OS (p < 0.001, HR = 1.907). Our study found that ATAR is an independent predictor of survival outcomes in SCLC, which was superior to ALB, PNI, and SII in predicting outcomes in low-risk and high-risk groups (all p < 0.05). Models combining ATAR with ALB, PNI, and SII showed more powerful prognostic value than their corresponding original models. Moreover, the prognostic indicator ATAR can significantly stratify stage I - II and III - IV SCLC patients (p ＜ 0.05). CONCLUSIONS: Peripheral blood ATAR prognostic index can be used as an independent predictor of SCLC patients before treatment.

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.

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.

Research progress on the interaction between oxidative stress and platelets: Another avenue for cancer?

Oxidative stress (OS) is a chemical imbalance between an oxidant and an antioxidant, causing damage to redox signaling and control or causing molecular damage. Unbalanced oxidative metabolism can produce excessive reactive oxygen species (ROS). These excess ROS can cause drastic changes in platelet metabolism and further affect platelet function. It will also lead to an increase in platelet procoagulant phenotype and cell apoptosis, which will increase the risk of thrombosis. The creation of ROS and subsequent platelet activation, adhesion, and recruitment are then further encouraged in an auto-amplifying loop by ROS produced from platelets. Meanwhile, cancer cells produce a higher concentration of ROS due to their fast metabolism and high proliferation rate. However, excessive ROS can result in damage to and modification of cellular macromolecules. The formation of cancer and its progression is strongly associated with oxidative stress and the resulting oxidative damage. In addition, platelets are an important part of the tumor microenvironment, and there is a significant cross-communication between platelets and cancer cells. Cancer cells alter the activation status of platelets, their RNA spectrum, proteome, and other properties. The "cloaking" of cancer cells by platelets providing physical protection，avoiding destruction from shear stress and the attack of immune cells, promoting tumor cell invasion.We explored the vicious circle interaction between ROS, platelets, and cancer in this review, and we believe that ROS can play a stimulative role in tumor growth and metastasis through platelets.

Factors influencing platelet isolation: a prospective multicenter study from Western China.

Tumor-educated platelets (TEPs) have been widely reported to have promising application potential; nonetheless, platelet isolation from peripheral blood is an important but neglected step in TEPs research for platelet-based liquid biopsy. In this article, we discussed some common influence factors for platelet isolation. To investigate the factors involved in platelet isolation, a prospective multicenter study was conducted on healthy Han Chinese adults (18 to 79 years of age). A total of 208 individuals were included in the final statistical analysis out of the 226 healthy volunteers who were prospectively enrolled from four hospitals. The primary study metric was the platelet recovery rate (PRR). The similar pattern was observed in the four hospitals, The PRR at room temperature (23°C±2°C) was slightly higher than the PRR at cold temperature (4°C±2°C). Moreover, the PRR gradually decreased as the storage time increased. The PRR for samples within 2 hours of storage is significantly higher than for samples beyond 2 hours (p < .05). Additionally, PRR was also affected by the equipment used in different centers. This study confirmed several factors that influence platelet isolation. In our study, we indicated that platelet isolation should be performed within two hours of peripheral blood draw and held at room temperature until isolation, and that centrifuge models should be fixed during the extraction process, which will further improve the research progress of platelet-based liquid biopsy in cancer.

What is the context? Globally, cancer is one of the leading cause of premature death. Early screening is important for cancer diagnosis and treatment and can even significantly lower cancer mortalityGlobally, cancer is one of the leading cause of premature death. Early screening is important for cancer diagnosis and treatment and can even significantly lower cancer mortalityFor the liquid biopsy, isolation is an important step. Early studies have explored the influencing factors of exosome, circulating tumor cells (CTCs), and other components extraction in liquid biopsy.Despite platelet also being an excellent source of liquid biopsy, few studies have explored the factors that influence platelet isolation.Considering the importance of platelet isolation in tumor-based platelet liquid biopsy, our aim is to optimize platelet isolation conditions as much as possible to obtain a high platelet recovery rate.What is new? In this study, we conducted a prospective multicenter study ofhealthy adults from four centers, combining whole blood with platelet-richplasma to investigate factors influencing platelet recovery rate (PRR) during platelet isolation.In our study, we indicated that platelet isolation should be performed within two hours at room temperature, and that centrifuge models should be fixed during the extraction process, which will further improve the research progress of platelet-based liquid biopsy in cancer.What is the impact? In future platelet-related studies, we should fix the sample storage temperature, storage time and centrifuge model in the process of platelet extraction, so as to reduce the variables affecting platelet extraction as much as possible and ensure the stable recovery rate of platelet extraction.

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.

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.

Synergistic Effect of Berberine Hydrochloride and Fluconazole Against Candida albicans Resistant Isolates.

The emergence of resistant Candida albicans has made clinical fluconazole (FLC) treatment difficult. Improving sensitivity to FLC is an effective way to treat resistant isolates. Berberine hydrochloride (BBH) is a commonly used traditional Chinese medicine with antimicrobial effects, especially in resistant isolates. We investigated the molecular mechanisms underlying BBH and FLC synergism on biofilm-positive FLC-resistant C. albicans inhibition. Checkerboard microdilution assays and time-kill assays showed a strong synergistic effect between BBH and FLC in resistant C. albicans isolates, causing a significant 32-512-fold reduction in minimum inhibitory concentrations. BBH combined with FLC inhibited intracellular FLC efflux due to key efflux pump gene CDR1 downregulation, whereas FLC alone induced high CDR1 transcription in resistant strains. Further, BBH + FLC inhibited yeast adhesion, morphological hyphae transformation, and biofilm formation by downregulating the hyphal-specific genes ALS3, HWP1, and ECE1. BBH caused cytoplasmic Ca2+ influx, while FLC alone did not induce high intracellular Ca2+ levels. The vacuolar calcium channel gene YVC1 was upregulated, while the vacuolar calcium pump gene PMC1 was downregulated in the BBH + FLC and BBH alone groups. However, vacuolar calcium gene expression after FLC treatment was opposite in biofilm-positive FLC-resistant C. albicans, which might explain why BBH induces Ca2+ influx. These results demonstrate that BBH + FLC exerts synergistic effects to increase FLC sensitivity by regulating multiple targets in FLC-resistant C. albicans. These findings further show that traditional Chinese medicines have multi-target antimicrobial effects that may inhibit drug-resistant strains. This study also found that the vacuolar calcium regulation genes YVC1 and PMC1 are key BBH + FLC targets which increase cytoplasmic Ca2+ in resistant isolates, which might be critical for reversing biofilm-positive FLC-resistant C. albicans.

Integration of platelet features in blood and platelet rich plasma for detection of lung cancer.

OBJECTIVES: To determine whether the integration platelet features in blood and platelet rich plasma can establish a model to diagnose lung cancer and colon cancer, even differentiate lung malignancy from lung benign diseases. METHODS: 245 individuals including 159 lung cancer and 86 normal participants were divided into the training cohort and testing cohort randomly. Then, 32 colon cancers, 37 lung cancers, and 21 benign patients were enrolled into validate cohort. The whole blood and corresponding platelet rich plasma (PRP) samples from all participants were prospectively collected, and the platelet features were determined. The features which are statistically significant at the univariate analysis in the training cohort and reported significant features were entered the diagnostic model. A receiver operator characteristic (ROC) curve was drawn to evaluate the accuracy of the model in each cohort. RESULTS: In the training cohort, multiple platelet features were significantly different in lung cancer patients, including MPV in whole blood, MPV, and platelet count in PRP and platelet recovery rate (PRR). For the training cohort, the diagnostic model for lung cancer performed well (AUC = 0.92). The probability distribution of lung cancers and controls in testing cohort were also separated well by the diagnostic model (AUC = 0.79). The diagnostic model for colon cancer also performed well (AUC = 0.79). The model also has a potential value in differentiating the lung malignancy from the benign (AUC = 0.69). CONCLUSION: The PRR was first raised and used in the detection of lung cancer. This study identified a diagnostic model based on PRR and other platelet features in whole blood and PRP samples with the potential to distinguish patients with lung cancer or colon cancer from healthy controls. The model could also be used to distinguish between lung cancer from the benign disease.