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.

Soft interface confined DNA walker for sensitive and specific detection of SARS-CoV-2 variants.

Nucleic acid detection is conducive to preventing the spread of COVID-19 pandemic. In this work, we successfully designed a soft interface confined DNA walker by anchoring hairpin reporter probes on cell membranes for the detection of SARS-CoV-2 variants. In the presence of target RNA, the cyclic self-assembly reaction occurred between hairpin probes H1 and H2, and the continuous walking of target RNA on cell membranes led to the gradual amplification of fluorescence signal. The enrichment of H1 on membranes and the unique fluidity of membranes promoted the collision efficiency between DNA strands in the reaction process, endowing this method with high sensitivity. In addition, the double-blind test of synthetic RNA in 5% normal human serum demonstrated the good stability and anti-interference in complex environment of this method, which exhibited great potential in clinical diagnostics.

Drugs targeting structural and nonstructural proteins of the chikungunya virus: A review.

Chikungunya virus (CHIKV) is a single positive-stranded RNA virus of the Togaviridae family and Alphavirus genus, with a typical lipid bilayer envelope structure, and is the causative agent of human chikungunya fever (CHIKF). The U.S. Food and Drug Administration has recently approved the first chikungunya vaccine, Ixchiq; however, vaccination rates are low, and CHIKF is prevalent owing to its periodic outbreaks. Thus, developing effective anti-CHIKV drugs in clinical settings is imperative. Viral proteins encoded by the CHIKV genome play vital roles in all stages of infection, and developing therapeutic agents that target these CHIKV proteins is an effective strategy to improve CHIKF treatment efficacy and reduce mortality rates. Therefore, in the present review article, we aimed to investigate the basic structure, function, and replication cycle of CHIKV and comprehensively outline the current status and future advancements in anti-CHIKV drug development, specifically targeting nonstructural (ns) proteins, including nsP1, nsP2, nsP3, and nsP4 and structural proteins such as capsid (C), E3, E2, 6K, and E1.

Expression Significance of Estrogen Receptor ER-α36 in Breast Cancer Treated by Chemotherapy: A Meta-Analysis.

Estrogen receptor (ER) is a molecular marker and target for diagnosing and treating breast cancer (BC). ER-α36, a novel estrogen receptor subtype, involved in the proliferation, differentiation, metastasis, and invasion of tumor cells. It is closely linked to the progression of various cancers. Therefore, studying ER is of high significance in treating BC. In this study, we will investigate the changes in the expression level of ER-α36 in patients with BC treated by chemotherapy through meta-analysis, so as to evaluate the clinical value of ER-α36 in the prognosis of BC treated by chemotherapy. English databases such as PubMed, Web of Science, Embase, and The Cochrane Library were searched to retrieve the articles published from the establishment of the database to April 2023. The keywords included chemotherapy, neoadjuvant chemotherapy, breast cancer, estrogen receptor alpha, and ER-α36. Five suitable studies, encompassing 636 patients, were ultimately selected. The meta-analysis results revealed that, following the chemotherapy, the analysis of ER-α36 positive cases yielded an Odds Ratio (OR) of 0.42, a 95% confidence interval (CI) of 0.28-0.64 (Z = 4.00, P < 0.0001). Additionally, the analysis of cases exhibiting remission in BC demonstrated an OR of 2.22 (95% CI = 1.40-3.50, Z = 3.40, P = 0.0007). Compared to patients receiving single chemotherapy agents or those untreated with chemotherapy, the combined use of multiple chemotherapy drugs can significantly reduce the levels of ER-α36 in BC patients, enhancing the remission rate of BC. ER-α36 can serve as a critical indicator for assessing the prognosis of BC following chemotherapy.

Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types.

Lung cancer is a highly fatal disease that poses a significant global health burden. The absence of characteristic clinical symptoms frequently results in the diagnosis of most patients at advanced stages of lung cancer. Although low-dose computed tomography (LDCT) screening has become increasingly prevalent in clinical practice, its high rate of false positives continues to present a significant challenge. In addition to LDCT screening, tumor biomarker detection represents a critical approach for early diagnosis of lung cancer; unfortunately, no tumor marker with optimal sensitivity and specificity is currently available. Metabolomics has recently emerged as a promising field for developing novel tumor biomarkers. In this paper, we introduce metabolic pathways, instrument platforms, and a wide variety of sample types for lung cancer metabolomics. Specifically, we explore the strengths, limitations, and distinguishing features of various sample types employed in lung cancer metabolomics research. Additionally, we present the latest advances in lung cancer metabolomics research that utilize diverse sample types. We summarize and enumerate research studies that have investigated lung cancer metabolomics using different metabolomic sample types. Finally, we provide a perspective on the future of metabolomics research in lung cancer. Our discussion of the potential of metabolomics in developing new tumor biomarkers may inspire further study and innovation in this dynamic field.

FBXW7 in breast cancer: mechanism of action and therapeutic potential.

Breast cancer is one of the frequent tumors that seriously endanger the physical and mental well-being in women. F-box and WD repeat domain-containing 7 (FBXW7) is a neoplastic repressor. Serving as a substrate recognition element for ubiquitin ligase, FBXW7 participates in the ubiquitin-proteasome system and is typically in charge of the ubiquitination and destruction of crucial oncogenic proteins, further performing a paramount role in cell differentiation, apoptosis and metabolic processes. Low levels of FBXW7 cause abnormal stability of pertinent substrates, mutations and/or deletions in the FBXW7 gene have been reported to correlate with breast cancer malignant progression and chemoresistance. Given the lack of an effective solution to breast cancer's clinical drug resistance dilemma, elucidating FBXW7's mechanism of action could provide a theoretical basis for targeted drug exploration. Therefore, in this review, we focused on FBXW7's role in a range of breast cancer malignant behaviors and summarized the pertinent cellular targets, signaling pathways, as well as the mechanisms regulating FBXW7 expression. We also proposed novel perspectives for the exploitation of alternative therapies and specific tumor markers for breast cancer by therapeutic strategies aiming at FBXW7.

Research progress on the role of PDGF/PDGFR in type 2 diabetes.

Platelet-derived growth factors (PDGFs) are basic proteins stored in the α granules of platelets. PDGFs and their receptors (PDGFRs) are widely expressed in platelets, fibroblasts, vascular endothelial cells, platelets, pericytes, smooth muscle cells and tumor cells. The activation of PDGFR plays a number of critical roles in physiological functions and diseases, including normal embryonic development, cellular differentiation, and responses to tissue damage. In recent years, emerging experimental evidence has shown that activation of the PDGF/PDGFR pathway is involved in the development of diabetes and its complications, such as atherosclerosis, diabetic foot ulcers, diabetic nephropathy, and retinopathy. Research on targeting PDGF/PDGFR as a treatment has also made great progress. In this mini-review, we summarized the role of PDGF in diabetes, as well as the research progress on targeted diabetes therapy, which provides a new strategy for the treatment of type 2 diabetes.

Identification and validation of molecular subtype and prognostic signature for lung adenocarcinoma based on neutrophil extracellular traps.

Background: Neutrophil Extracellular Traps (NETs) are fibrous networks made of DNA-histone complexes and proteins protruded from activated neutrophils. Accumulating evidences have highlighted the vital role of NETs in tumor progression and diffusion. However, limited systematic studies regarding the role of NETs in LUAD have been performed. Methods: Differentially expressed NETs-related genes and their mutation landscape were identified with TCGA database. Consensus clustering analysis was performed to determine the NETs-related subtypes of LUAD. LASSO algorithm was employed to construct a prognostic signature. Moreover, GSE30219 and GSE31210 were used as independent validation. We also constructed a lncRNA-miRNA-mRNA regulatory axis with several miRNA and lncRNA databases. Results: Consensus clustering identified two NETs-related clusters in LUAD. High NETs score was correlated with a favorable overall survival, abundant immune cell infiltration, and high activity of immune response signal pathways. Six NET-related genes (G0S2, KCNJ15, S100A12, AKT2, CTSG, and HMGB1) with significant prognostic value were screened to develop a prognostic signature. LUAD patients with low-risk had a significantly favorable overall survival both in the training set and validation set. Moreover, NETs-related risk score and clinical stage could act as an independent prognostic factor for LUAD patients. Significant correlation was obtained between risk score and tumor immune microenvironment. We also identified lncRNA BCYRN1/miR-3664-5p/CTSG regulatory axis that may be involved in the progression of LUAD. Conclusion: We developed two molecular subtypes and a prognostic signature for LUAD based on NETs-related genes. This stratification could provide more evidences for estimating the prognosis and immunotherapy of LAUD patients.

Global transmission of monkeypox virus-a potential threat under the COVID-19 pandemic.

Monkeypox virus (MPXV) cases have increased dramatically worldwide since May 2022. The Atlanta Center for Disease Control and Prevention (Atlanta CDC) had reported a total of 85,922 cases as of February 20th, 2023. During the COVID-19 pandemic, MPXV has emerged as a potential public threat. MPXV transmission and prevalence must be closely monitored. In this comprehensive review, we explained the basic characteristics and transmission routes of MPXV, individuals susceptible to it, as well as highlight the impact of the behavior of men who have sex with men (MSM) and airline traveling on recent outbreaks of MPXV. We also describe the clinical implications, the prevention of MPXV, and clinical measures of viral detection.

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.

Chromosome-scale genome assembly and insights into the metabolome and gene regulation of leaf color transition in an important oak species, Quercus dentata.

Quercus dentata Thunb., a dominant forest tree species in northern China, has significant ecological and ornamental value due to its adaptability and beautiful autumn coloration, with color changes from green to yellow into red resulting from the autumnal shifts in leaf pigmentation. However, the key genes and molecular regulatory mechanisms for leaf color transition remain to be investigated. First, we presented a high-quality chromosome-scale assembly for Q. dentata. This 893.54 Mb sized genome (contig N50 = 4.21 Mb, scaffold N50 = 75.55 Mb; 2n = 24) harbors 31 584 protein-coding genes. Second, our metabolome analyses uncovered pelargonidin-3-O-glucoside, cyanidin-3-O-arabinoside, and cyanidin-3-O-glucoside as the main pigments involved in leaf color transition. Third, gene co-expression further identified the MYB-bHLH-WD40 (MBW) transcription activation complex as central to anthocyanin biosynthesis regulation. Notably, transcription factor (TF) QdNAC (QD08G038820) was highly co-expressed with this MBW complex and may regulate anthocyanin accumulation and chlorophyll degradation during leaf senescence through direct interaction with another TF, QdMYB (QD01G020890), as revealed by our further protein-protein and DNA-protein interaction assays. Our high-quality genome assembly, metabolome, and transcriptome resources further enrich Quercus genomics and will facilitate upcoming exploration of ornamental values and environmental adaptability in this important genus.

Exploration of the link between gut microbiota and purinergic signalling.

Growing evidence reveals that microorganisms in the gut are linked to metabolic health and disease risk in human beings to a considerable extent. The focus of research at this stage must tend to focus on cause-and-effect studies. In addition to being a component of DNA and RNA, purine metabolites can be involved in purine signalling in the body as chemical messengers. Abnormalities in purinergic signalling may lead to neuropathy, rheumatic immune diseases, inflammation, tumors, and a wide range of other diseases. It has proved that gut microbes are involved in purinergic signalling. The relationship between these gut-derived purinergic signalling molecules and host metabolism may be one of the important clues to our understanding of the mechanisms by which the microbiota affects host metabolism.

Crosstalk between Methylation and ncRNAs in Breast Cancer: Therapeutic and Diagnostic Implications.

Breast cancer, as a highly heterogeneous malignant tumor, is one of the primary causes of death among females worldwide. The etiology of breast cancer involves aberrant epigenetic mechanisms and abnormal expression of certain non-coding RNA (ncRNAs). DNA methylation, N6-methyladenosine(m6A), and histone methylation are widely explored epigenetic regulation types in breast cancer. ncRNAs are a group of unique RNA transcripts, mainly including microRNA (miRNAs), long non-coding RNA (lncRNAs), circular RNA (circRNAs), small interfering RNA (siRNAs), piwi-interacting RNA (piRNAs), etc. Different types of methylation and ncRNAs mutually regulate and interact to form intricate networks to mediate precisely breast cancer genesis. In this review, we elaborate on the crosstalk between major methylation modifications and ncRNAs and discuss the role of their interaction in promoting breast cancer oncogenesis. This review can provide novel insights into establishing a new diagnostic marker system on methylation patterns of ncRNAs and therapeutic perspectives of combining ncRNA oligonucleotides and phytochemical drugs for breast cancer therapy.

Transcriptome analysis identifies key gene LiMYB305 involved in monoterpene biosynthesis in Lilium 'Siberia'.

Lilium is a popular cut flower that is highly favored by consumers due to its snowy white color and strong fragrance, which originates from the release of monoterpenes. However, the underlying molecular mechanism of monoterpene synthesis remains poorly understood. In this study, the content of three main monoterpenes (linalool, ocimene, and myrcene) was examined in Lilium 'Siberia', and RNA sequencing of the 11 stages of flower development was conducted. The biosynthesis of the three monoterpenes increased with flower development, reaching their peak levels at the full flowering stage. Transcriptome data revealed 257,140 unigenes, with an average size of 794 bp, from which 43,934 differentially expressed genes were identified and enriched in the KEGG pathways partly involved in plant hormone signal transduction and monoterpenoid biosynthesis. Furthermore, the essential factor LiMYB305 was identified by WGCNA after the release of the flower fragrance. The transient silencing of LiMYB305 in petals using VIGS technology showed that the mRNA expression levels of LiLiS, LiOcS, and LiMyS were significantly downregulated and that the release of linalool, ocimene, and myrcene had decreased significantly. Y1H, LUC, and EMSA experiments revealed that LiMYB305 directly bound and activated the LiOcS promoter to increase the synthesis of monoterpenes. Taken together, these results provide insight into the molecular mechanism of monoterpene synthesis and provide valuable information to investigate the formation of the flower fragrance in Lilium.

Comprehensive Analysis of the Molecular Characteristics and Prognosis value of AT II-associated Genes in Non-small Cell Lung Cancer.

Alveolar type II (AT II) is a key structure of the distal lung epithelium and essential to maintain normal lung homeostasis. Dedifferentiation of AT II cells is significantly correlated with lung tumor progression. However, the potential molecular mechanism and clinical significance of AT II-associated genes for lung cancer has not yet been fully elucidated. In this study, we comprehensively analyzed the gene expression, prognosis value, genetic alteration, and immune cell infiltration of eight AT II-associated genes (AQP4, SFTPB, SFTPC, SFTPD, CLDN18, FOXA2, NKX2-1, and PGC) in Nonsmall Cell Lung Cancer (NSCLC). The results have shown that the expression of eight genes were remarkably reduced in cancer tissues and observably relating to clinical cancer stages. Survival analysis of the eight genes revealed that low-expression of CLDN18, FOXA2, NKX2-1, PGC, SFTPB, SFTPC, and SFTPD were significantly related to a reduced progression-free survival (FP), and low CLDN18, FOXA2, and SFTPD mRNA expression led to a short postprogression survival (PPS). Meanwhile, the alteration of 8 AT II-associated genes covered 273 out of 1053 NSCLC samples (26%). Additionally, the expression level of eight genes were significantly correlated with the infiltration of diverse immune cells, including six types of CD4+T cells, macrophages, neutrophils, B cells, CD8+ T cells, and dendritic cells. In summary, this study provided clues of the values of eight AT II-associated genes as clinical biomarkers and therapeutic targets in NSCLC and might provide some new inspirations to assist the design of new immunotherapies.

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.

Salvianolic acid A promotes mitochondrial biogenesis and mitochondrial function in 3T3-L1 adipocytes through regulation of the AMPK-PGC1α signalling pathway.

Mitochondrial dysfunction is associated with insulin resistance and type 2 diabetes (T2DM). Decreased mitochondrial abundance and function were found in white adipose tissue (WAT) of T2DM patients. Therefore, promoting WAT mitochondrial biogenesis and improving adipocyte metabolism may be strategies to prevent and reverse T2DM. Salvianolic acid A (SAA) has been found to exert anti-diabetic and lipid disorder-improving effects. However whether SAA benefits mitochondrial biogenesis and function in adipose tissue is unclear. Here, we evaluated SAA's effect on mitochondrial biogenesis and function in 3T3-L1 adipocytes and investigated its potential regulatory mechanism. Results showed that SAA treatment significantly promoted the transcription and expression of peroxisome proliferator-activated receptor γ coactivator- 1α (PGC-1α), nuclear respiratory factor 1 (NRF1) and mitochondrial transcription factor A (TFAM). Meanwhile, SAA treatment significantly promoted mitochondrial biogenesis by increasing mitochondrial DNA (mtDNA) quantity, mitochondrial mass, and expression of mitochondrial respiratory chain enzyme complexes III and complex IV. These enhancements were accompanied by enhanced phosphorylation of AMPK and ACC and were suppressed by Compound C, a specific AMPK inhibitor. Furthermore, SAA treatment improved adipocytes mitochondrial respiration and stimulated ATP generation. These findings indicate that SAA exerts a potential therapeutic capacity against adipocytes mitochondrial dysfunction in diabetes by activating the AMPK-PGC-1α pathway.

Lilac (Syringa oblata) genome provides insights into its evolution and molecular mechanism of petal color change.

Color change during flower opening is common; however, little is understood on the biochemical and molecular basis related. Lilac (Syringa oblata), a well-known woody ornamental plant with obvious petal color changes, is an ideal model. Here, we presented chromosome-scale genome assembly for lilac, resolved the flavonoids metabolism, and identified key genes and potential regulatory networks related to petal color change. The genome assembly is 1.05 Gb anchored onto 23 chromosomes, with a BUSCO score of 96.6%. Whole-genome duplication (WGD) event shared within Oleaceae was revealed. Metabolome quantification identified delphinidin-3-O-rutinoside (Dp3Ru) and cyanidin-3-O-rutinoside (Cy3Ru) as the major pigments; gene co-expression networks indicated WRKY an essential regulation factor at the early flowering stage, ERF more important in the color transition period (from violet to light nearly white), while the MBW complex participated in the entire process. Our results provide a foundation for functional study and molecular breeding in lilac.

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.