BACKGROUND Early detection of lung cancer is urgently needed in clinical practice. AIM To evaluate the diagnostic value of conventional tumor markers and cytokines for lung cancer and construct a multiparameter diagnostic model lung cancer detection. METHODS A total of 152 healthy controls and 113 lung cancer patients were included in the model. In addition, 21 healthy controls and 36 lung cancer patients were separately included to validate the model. Three conventional tumor markers and 10 cytokines were detected. Four multiparameter joint analysis methods, binary logistic regression analysis, discriminant analysis, a classification tree and a neural network, were used to establish and compare multiparameter joint diagnosis models. RESULTS Six differentially expressed indicators [carcinoembryonic antigen (CEA), cytokeratin 19 fragment (CY211), neuron-specific enolase, interleukin (IL)-8, monocyte chemoattractant protein-1, and tumor necrosis factor-alpha (TNF-alpha)] were screened out, among which IL-8 [area under the curve (AUC) = 0.957] and TNF-alpha (AUC = 0.936) had the optimal diagnostic efficacy. The binary logistic regression model was chosen as the optimal multiparameter combined auxiliary diagnostic model. When 152 healthy controls and 113 lung cancer s were differentiated via the model, the AUC was 0.980. After validation, when 21 healthy controls and 36 lung cancer patients were distinguished, the AUC was 0.922, indicating good stability and superior performance to that of CEA alone. CONCLUSION We constructed a multiparameter binary logistic regression diagnostic model that included CEA, CY211, IL-8 and TNF-alpha for the auxiliary detection of lung cancer. Compared with conventional CEA, it significantly improved diagnostic accuracy.

Centrosome abnormalities are a distinguishing feature of cancer and play a role in the aging process. Cancer cells may evade the immune system by activating immune checkpoints, altering their surrounding microenvironment, abnormalities in antigen presentation and recognition, and metabolic reprogramming to inhibit T-cell activity, allowing cancer cells to survive and spread within the host. When the centrosomes are abnormally shaped or numbered, mitotic errors can occur, cellular senescence occurs, cell death occurs, genomic instability occurs, and aneuploidy forms, resulting in diseases such as cancer. The present study is exploring the strategy of research progress in which centrosome abnormalities contribute to the aging process in various different ways as well as fuel immune escape from cancer cells, providing a new direction for cancer immunotherapy.

e15083 Background: Pharmacotherapy remains a pivotal treatment strategy for patients with advanced hepatocellular carcinoma (HCC). Donafenib, globally the first targeted therapy proven to offer superior survival benefits and safety over sorafenib in a large-scale phase III clinical trial with head-to-head comparison, has been adopted for first-line treatment of advanced HCC. Given the limited basic research on Donafenib both domestically and internationally, and its constrained clinical efficacy, this study aims to explore combination drug therapy for HCC in an attempt to achieve further breakthroughs and enhance the anticancer activity of Donafenib. Methods: A xenograft tumor model in nude mice was established to observe the in vivo antitumor effects of Donafenib. Transcriptomics and proteomics were employed to characterize the gene expression changes in HCC cell lines after Donafenib intervention and to screen for key molecules. A series of assays, including the Cell Counting Kit-8 (CCK8), flow cytometry, scratch assays, Transwell assays, Western blotting, and in vivo tumorigenicity in nude mice, were conducted to determine the impact of the hub gene on the malignant behavior of HCC and to evaluate the combined antitumor effects of the molecular inhibition and Donafenib treatment in HCC. Results: Treatment with Donafenib significantly slowed tumor growth in a nude mouse xenograft model, resulting in a marked reduction in final tumor volumes compared to control subjects. Proteomic analyses post-Donafenib treatment identified FADS2 as the protein with the highest absolute log2 fold change among all differentially expressed proteins in HCC cells. This finding was corroborated by transcriptomic data, which indicated a concurrent downregulation of FADS2 at the mRNA level. Subsequent in vitro and in vivo assays validated the inhibitory effect of FADS2 blockade on the malignant biological behaviors of HCC cells. Importantly, the concomitant administration of Donafenib and the FADS2 inhibitor SC-26196 exhibited a synergistic antitumor action, significantly enhancing therapeutic efficacy in both HCC cell lines and xenografted tumors in nude mice. Conclusions: Combination therapy, a prevalent approach in clinical oncology, has the potential to augment treatment efficacy while simultaneously diminishing toxicity. This study employed an extensive multi-omics approach complemented by a range of both in vitro and in vivo experiments. It revealed that the synergistic use of Donafenib and SC-26196 markedly enhances Donafenib-induced the inhibition of cancer cell growth and metastasis, demonstrating a significant synergistic antitumor effect. These findings from our preclinical investigations may offer a promising new combinational drug regimen for the therapeutic management of HCC patients.

Extrachromosomal DNAs (eccDNAs) frequently carry amplified oncogenes. This investigation aimed to examine the occurrence and role of eccDNAs in individuals diagnosed with advanced perihilar cholangiocarcinoma (pCCA) who exhibited distinct prognostic outcomes. Five patients with poor survival outcomes and five with better outcomes were selected among patients who received first-line hepatic arterial infusion chemotherapy from June 2021 to June 2022. The extracted eccDNAs were amplified for high-throughput sequencing. Genes associated with the differentially expressed eccDNAs were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The differentially expressed bile eccDNA-related genes were used to construct a prognostic model. Across all 10 patients, a total of 19,024 and 3,048 eccDNAs were identified in bile and plasma, respectively. The concentration of eccDNA detected in the bile was 9-fold higher than that in plasma. The chromosome distribution of the eccDNAs were similar between bile and matched plasma. GO and KEGG pathway analyses showed enrichment in the mitogen-activated protein kinase (MAPK) and Wnt/β-catenin pathways in patients with poor survival outcomes. According to the prognostic model constructed by eccDNA-related genes, the high-risk group of cholangiocarcinoma patients displayed significantly shorter overall survival (p < 0.001). Moreover, the degree of infiltration of immunosuppressive cells was higher in patients in the high-risk group. In conclusion, EccDNA could be detected in bile and plasma of pCCA patients, with a higher concentration. A prognostic model based on eccDNA-related genes showed the potential to predict the survival and immune microenvironment of patients with cholangiocarcinoma.

Pharmacotherapy is crucial for advanced hepatocellular carcinoma (HCC). The multi-kinase inhibitor donafenib offers superior survival benefits over sorafenib. Donafenib has first-line status, but there is limited research for combination therapies with this anticancer agent. This study aimed to delineate donafenib's antitumor effects, including transcriptomics and proteomics to characterize gene expression changes in donafenib-treated HCC cell lines. In vitro and in vivo tumorigenicity studies were conducted to evaluate the combined antitumor effects of donafenib. Proteomic and transcriptomic analyses identified that donafenib downregulated fatty acid desaturase 2 (FADS2) at the protein and mRNA levels. In vitro and in vivo assays revealed an inhibitory effect of FADS2 blockade on HCC cell malignancy. The combination of donafenib and the FADS2 inhibitor sc-26,196 produced synergistic antitumor action, enhancing therapeutic efficacy in HCC cell lines and xenografted tumors in nude mice. These findings highlight the potential of FADS2 as a biomarker for HCC and show a promising combinatorial therapy for its treatment. Thus, we provide a theoretical basis for translating laboratory research into clinical applications.

目的 通过检测血清中CEA、CA19-9,以及尿液中MMP9(matrix metalloproteinases 9,MMP9)的水平,评价其对于早期结直肠癌(colorectal cancer,CRC)的诊断价值,旨在建立一种早期CRC的辅助诊断方法.方法 采集141例健康对照者、118例结肠息肉患者以及202例CRC患者的血清及尿液样本.二元Logistic回归建立3项指标的联合诊断模型,受试者工作特征曲线(receiver operating characteristic curve,ROC)和曲线下面积(area under curve,AUC)评价3项指标的单独和联合诊断价值.结果 与健康对照组和结肠息肉组相比,CRC组的CEA、CA19-9和MMP9水平均显著升高(P＜0.05).当CEA、CA19-9和MMP9联合建立诊断模型用于区分141例健康对照组与202例CRC患者时,其AUC为0.891(95％置信区间为0.858和0.924),灵敏度和特异性分别为88.12％和70.21％,对于早期CRC和晚期CRC的灵敏度和特异性分别为79.41％和70.21％,92.54％和70.21％.联合诊断模型用于区分118例结肠息肉患者与202例CRC患者时,其AUC为0.815(95％置信区间为0.768和0.861),其灵敏度和特异性分别为78.22％和67.80％,对于早期CRC的AUC为0.819(95％置信区间为0.773和0.863),灵敏度和特异性分别为82.35％和67.80％,晚期CRC的AUC为0.811(95％置信区间为0.760和0.862),其灵敏度和特异性分别为76.27％和67.80％.结论 与常用指标CEA和CA19-9相比,本研究所建立的联合诊断模型诊断性能有显著提升,可作为潜在的CRC辅助诊断方法.

BACKGROUND:A noninvasive biomarker with high diagnostic performance is urgently needed for the early diagnosis of colorectal cancer (CRC).AIM:To evaluate the diagnostic value of matrix metalloproteinases (MMPs) 2, 7 and 9 in urine for CRC.METHODS:Of 59 healthy controls, 47 patients with colon polyps and 82 patients with CRC were included in this study. Carcinoembryonic antigen (CEA) in serum and MMP2, MMP7, and MMP9 in urine were detected. The combined diagnostic model of the indicators was established by binary logistic regression. The receiver operating characteristic curve (ROC) of the subjects was used to evaluate the independent and combined diagnostic value of the indicators.RESULTS:The MMP2, MMP7, MMP9, and CEA levels in the CRC group differed significantly from levels in the healthy controls (P < 0.05). The levels of MMP7, MMP9, and CEA also differed significantly between the CRC group and the colon polyps group (P < 0.05). The area under the curve (AUC) distinguishing between the healthy control and the CRC patients using the joint model with CEA, MMP2, MMP7 and MMP9 was 0.977, and the sensitivity and specificity were 95.10% and 91.50%, respectively. For early-stage CRC, the AUC was 0.975, and the sensitivity and specificity were 94.30% and 98.30%, respectively. For advanced stage CRC, the AUC was 0.979, and the sensitivity and specificity were 95.70% and 91.50%, respectively. Using CEA, MMP7 and MMP9 to jointly established a model distinguishing the colorectal polyp group from the CRC group, the AUC was 0.849, and the sensitivity and specificity were 84.10% and 70.20%, respectively. For early-stage CRC, the AUC was 0.818, and the sensitivity and specificity were 76.30% and 72.30%, respectively. For advanced stage CRC, the AUC was 0.875, and the sensitivity and specificity were 81.80% and 72.30%, respectively.CONCLUSION:MMP2, MMP7 and MMP 9 may exhibit diagnostic value for the early detection of CRC and may serve as auxiliary diagnostic markers for CRC.

BACKGROUND Colorectal cancer (CRC) is the third most common cancer worldwide, and it is the second leading cause of death from cancer in the world, accounting for approximately 9% of all cancer deaths. Early detection of CRC is urgently needed in clinical practice. AIM To build a multi-parameter diagnostic model for early detection of CRC. METHODS Total 59 colorectal polyps (CRP) groups, and 101 CRC patients (38 early-stage CRC and 63 advanced CRC) for model establishment. In addition, 30 CRP groups, and 62 CRC patients (30 early-stage CRC and 32 advanced CRC) were separately included to validate the model. 51 commonly used clinical detection indicators and the 4 extrachromosomal circular DNA markers NDUFB7, CAMK1D, PIK3CD and PSEN2 that we screened earlier. Four multi-parameter joint analysis methods: binary logistic regression analysis, discriminant analysis, classification tree and neural network to establish a multi-parameter joint diagnosis model. RESULTS Neural network included carcinoembryonic antigen (CEA), ischemia-modified albumin (IMA), sialic acid (SA), PIK3CD and lipoprotein a (LPa) was chosen as the optimal multi-parameter combined auxiliary diagnosis model to distinguish CRP and CRC group, when it differentiated 59 CRP and 101 CRC, its overall accuracy was 90.8%, its area under the curve (AUC) was 0.959 (0.934, 0.985), and the sensitivity and specificity were 91.5% and 82.2%, respectively. After validation, when distinguishing based on 30 CRP and 62 CRC patients, the AUC was 0.965 (0.930-1.000), and its sensitivity and specificity were 66.1% and 70.0%. When distinguishing based on 30 CRP and 32 early-stage CRC patients, the AUC was 0.960 (0.916-1.000), with a sensitivity and specificity of 87.5% and 90.0%, distinguishing based on 30 CRP and 30 advanced CRC patients, the AUC was 0.970 (0.936-1.000), with a sensitivity and specificity of 96.7% and 86.7%. CONCLUSION We built a multi-parameter neural network diagnostic model included CEA, IMA, SA, PIK3CD and LPa for early detection of CRC, compared to the conventional CEA, it showed significant improvement.

BACKGROUND DNA methylation is a part of epigenetic modification, that is closely related to the growth and development of colorectal cancer (CRC). Specific methylated genes and methylated diagnostic models of tumors have become current research focuses. The methylation status of circulating DNA in plasma might serve as a potential biomarker for CRC. AIM To investigate genome-wide methylation pattern in early CRC using the Illumina Infinium Human Methylation 850K BeadChip. METHODS The 850K Methylation BeadChip was used to analyze the genome-wide methylation status of early CRC patients (n = 5) and colorectal adenoma patients (n = 5). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses were performed on the selected differentially methylated sites to further discover candidate methylation biomarkers in plasma. RESULTS A total of 1865 methylated CpG sites with significant differences were detected, including 676 hypermethylated sites and 1189 hypomethylated sites. The distribution of these sites covered from the 1st to 22nd( )chromosomes and are mainly distributed on the gene body and gene promoter region. GO and KEGG enrichment analysis showed that the functions of these genes were related to biological regulation, molecular binding, transcription factor activity and signal transduction pathway. CONCLUSION The study demonstrated that the Illumina Infinium Human Methylation 850K BeadChip can be used to investigate genome-wide methylation status of plasma DNA in early CRC and colorectal adenoma patients.

BACKGROUND:Gastric cancer is a common malignant tumor. Early detection and diagnosis are crucial for the prevention and treatment of gastric cancer.AIM:To develop a blood index panel that may improve the diagnostic value for discriminating gastric cancer and gastric polyps.METHODS:Thirteen tumor-related detection indices, 38 clinical biochemical indices and 10 cytokine indices were examined in 139 gastric cancer patients and 40 gastric polyp patients to build the model. An additional 68 gastric cancer patients and 22 gastric polyp patients were enrolled for validation. After area under the curve evaluation and univariate and multivariate analyses.RESULTS:Five tumor-related detection indices, 12 clinical biochemical indices and 1 cytokine index showed significant differences between the gastric cancer and gastric polyp groups. Carbohydrate antigen (CA) 724, phosphorus (P) and ischemia-modified albumin (IMA) were included in the blood index panel, and the area under the curve (AUC) of the index panel was 0.829 (0.754, 0.905). After validation, the AUC was 0.811 (0.700, 0.923). Compared to the conventional index CA724, the blood index panel showed significantly increased diagnostic value.CONCLUSION:We developed an index model that included CA724, P and IMA to discriminate the gastric cancer and gastric polyp groups, which may be a potential diagnostic method for clinical practice.

BACKGROUNDColorectal cancer (CRC) is a highly malignant cancer with a high incidence and mortality in China. It is urgent to find a diagnostic marker with higher sensitivity and specificity than the traditional approaches for CRC diagnosis.AIMTo provide new ideas for the diagnosis of CRC based on serum proteomics.METHODSSpecimens from 83 healthy people, 62 colon polyp (CRP) patients, and 101 CRC patients were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The diagnostic value of the profiles of differentially expressed proteins was then analyzed.RESULTSCompared with the healthy control group, CRC patients had elevated expression of 5 proteins and reduced expression of 14 proteins. The area under the curve (AUC) for a differentially expressed protein with a mass-to-charge ratio of 2022.34 was the largest; the AUC was 0.843, which was higher than the AUC of 0.717 observed with carcinoembryonic antigen (CEA), and the sensitivity and specificity of this identified marker were 75.3% and 79.5%, respectively. After cross-validation, the accuracy of diagnosis using levels of this differentially expressed protein was 82.37%. Compared with the CRP group, the expression of 3 proteins in the serum of CRC patients was elevated and 11 proteins were expressed at reduced levels. Proteins possessing mass-to-charge ratio values of 2899.38 and 877.3 were selected to establish a classification tree model. The results showed that the accuracy of CRC diagnosis was 89.5%, the accuracy of CRP diagnosis was 81.6%, and the overall accuracy of this approach was 86.3%. The overall sensitivity and specificity of diagnosis using the proteomics approach were 81.8% and 66.75%, respectively. The sensitivities and specificities of diagnoses based on CEA and carbohydrate antigen 19-9 expression were 55.6% and 91.3% and 65.4% and 65.2%, respectively.CONCLUSIONWe demonstrated that serum proteomics may be helpful for the detection of CRC, and it may assist clinical practice for CRC diagnosis.

Background: Nucleic acid detection and CT scanning have been reported in COVID-19 diagnosis. Here, we aimed to investigate the clinical significance of IgM and IgG testing for the diagnosis of highly suspected COVID-19. Methods: A total of 63 patients with suspected COVID-19 were observed, 57 of whom were enrolled (24 males and 33 females). The selection was based on the diagnosis and treatment protocol for COVID-19 (trial Sixth Edition) released by the National Health Commission of the People's Republic of China. Patients were divided into positive and negative groups according to the first nucleic acid results from pharyngeal swab tests. Routine blood tests were detected on the second day after each patient was hospitalized. The remaining serum samples were used for detection of novel coronavirus-specific IgM/IgG antibodies. Results: The rate of COVID-19 nucleic acid positivity was 42.10%. The positive detection rates with a combination of IgM and IgG testing for patients with COVID-19 negative and positive nucleic acid test results were 72.73 and 87.50%, respectively. Conclusions: We report a rapid, simple, and accurate detection method for patients with suspected COVID-19 and for on-site screening for close contacts within the population. IgM and IgG antibody detection can identify COVID-19 after a negative nucleic acid test. Diagnostic accuracy of COVID-19 might be improved by nucleic acid testing in patients with a history of epidemic disease or with clinical symptoms, as well as CT scans when necessary, and serum-specific IgM and IgG antibody testing after the window period.

癌症目前仍是医学界面临的第一大难题,其早期诊断、预后风险预测及治疗疗效评估有利于提高患者的生存率.目前临床上诊断癌症主要依靠肿瘤组织病理、内窥镜等检查,但都存在侵入性和异质性的问题.而在肿瘤细胞DNA中发生的分子变化如突变、易位和甲基化等,在循环肿瘤DNA(circulating tumor DNA,ctDNA)中也能反映出来.因此,体液活检检测ctDNA逐渐成为癌症诊断和监测的新方式.DNA甲基化与癌症中许多基因的表达沉默有关,在肿瘤基因组中发现了许多异常的甲基化改变,也有研究证明患者体液中也能检测到甲基化DNA,因此甲基化DNA有望成为新的癌症预测生物标志物.本文拟介绍DNA甲基化与癌症的关系、ctDNA的生物学基础,总结ctDNA的甲基化检测技术,阐述将甲基化ctDNA作为肿瘤生物标志物的作用及研究进展,并提出将ctDNA的甲基化检测应用于临床肿瘤方面的前景和挑战.

真核细胞的DNA具有独特的基因组甲基化模式,它作为一个分子开关来控制细胞的转录机制,参与癌症等疾病的发生发展过程.不断发展的甲基化检测技术为DNA甲基化变化对癌症进展的影响提供了更好的理解.在本文中,主要讨论了近年来发展的几种常见DNA甲基化检测方法,对MSP、MethyLight、digital MSP、核酸质谱、甲基化芯片、测序(一代测序、二代测序和三代测序)方法进行解读与比较,并展望未来检测技术的挑战与发展.

BACKGROUND Early screening for colorectal cancer (CRC) is important in clinical practice. However, the currently methods are inadequate because of high cost and low diagnostic value. AIM To develop a new examination method based on the serum biomarker panel for the early detection of CRC. METHODS Three hundred and fifty cases of CRC, 300 cases of colorectal polyps and 360 cases of normal controls. Combined with the results of area under curve (AUC) and correlation analysis, the binary Logistic regression analysis of the remaining indexes which is in accordance with the requirements was carried out, and discriminant analysis, classification tree and artificial neural network analysis were used to analyze the remaining indexes at the same time. RESULTS By comparison of these methods, we obtained the ability to distinguish CRC from healthy control group, malignant disease group and benign disease group. Artificial neural network had the best diagnostic value when compared with binary logistic regression, discriminant analysis, and classification tree. The AUC of CRC and the control group was 0.992 (0.987, 0.997), sensitivity and specificity were 98.9% and 95.6%. The AUC of the malignant disease group and benign group was 0.996 (0.992, 0.999), sensitivity and specificity were 97.4% and 96.7%. CONCLUSION Artificial neural network diagnosis method can improve the sensitivity and specificity of the diagnosis of CRC, and a novel assistant diagnostic method was built for the early detection of CRC.

BACKGROUND In early gastric cancer (GC), tumor markers are increased in the blood. The levels of these markers have been used as important indexes for GC screening, early diagnosis and prognostic evaluation. However, specific tumor markers have not yet been discovered. Diagnosis based on a single tumor marker has limited significance. The detection rate of GC is still very low. AIM To improve the diagnostic value of blood markers for GC. METHODS We used a multiparameter joint analysis of 77 indexes of malignant GC and gastric polyp (GP), 64 indexes of GC and healthy controls (Ctrls). RESULTS By analyzing the data, there are 27 indexes in the final Ctrls vs GC with P values < 0.01, the area under the curve (AUC) of albumin is the largest in Ctrls vs GC, and the AUC was 0.907. 30 indexes in GP vs GC have P values < 0.01. Among them, the D-dimer showed an AUC of 0.729. The 27 indexes in Ctrls vs GC and 30 indexes in GP vs GC were used for binary logistic regression, discriminant analysis, classification tree analysis and artificial neural network analysis model. For the ability to distinguish between Ctrls vs GC, GP vs GC, artificial neural networks had better diagnostic value when compared with classification tree, binary logistic regression, and discriminant analysis. When compared Ctrl and GC, the overall prediction accuracy was 92.9%, and the AUC was 0.992 (0.980, 1.000). When compared GP and GC, the overall prediction accuracy was 77.9%, and the AUC was 0.969 (0.948, 0.990). CONCLUSION The diagnostic effect of multi-parameter joint artificial neural networks analysis is significantly better than the single-index test diagnosis, and it may provide an assistant method for the detection of GC.

BACKGROUND Transarterial chemoembolization (TACE) and hepatic arterial infusion chemotherapy (HAIC) have shown promising local benefits for advanced hepatocellular carcinoma (HCC). S-1, a composite preparation of a 5-fluorouracil prodrug, has proven to be a convenient oral chemotherapeutic agent with definite efficacy against advanced HCC. AIM To evaluate the efficacy and safety of TACE followed by HAIC with or without oral S-1 for treating advanced HCC. METHODS In this single-center, open-label, prospective, randomized controlled trial, 117 participants with advanced HCC were randomized to receive TACE followed by oxaliplatin-based HAIC either with (TACE/HAIC + S-1,n= 56) or without (TACE/HAIC,n= 61) oral S-1 between December 2013 and September 2017. Two participants were excluded from final analysis for withdrawing consent. The primary endpoint was progression-free survival (PFS) and secondary endpoints included overall survival (OS), objective response rate, disease control rate and safety. RESULTS In total, 115 participants (100 males and 15 females; mean age, 57.7 years +/- 11.9) were analyzed. The median PFS and OS were 5.0 mo (0.4-58.6 mo) (95% confidence interval (CI): 3.82 to 6.18)vs4.4 mo (1.1-54.4 mo) (95%CI: 2.54 to 6.26;P= 0.585) and 8.4 mo (0.4-58.6 mo) (95%CI: 6.88 to 9.92)vs8.3 mo (1.4-54.4 m) (95%CI: 5.71 to 10.96;P= 0.985) in the TACE/HAIC + S-1 and TACE/HAIC groups, respectively. The objective response rate and disease control rate were 30.9%vs18.4% and 72.7%vs56.7% in the TACE/HAIC + S-1 and TACE/HAIC groups, respectively. Grade 3/4 adverse events had a similar frequency in both treatment groups. CONCLUSION No improvements in tumor response rates, PFS or OS were observed with the addition of S-1 to TACE/HAIC in advanced HCC. Both treatment regimens had a similar safety profile.

BACKGROUND In hepatocellular carcinoma (HCC), abnormal expression of multiple microRNAs (miRNAs) has been shown to be involved in the malignant biological behavior of liver cancer. The vast majority of liver cancer cases in China are closely related to hepatitis B virus (HBV) infection, but there are few studies on the changes of miRNA expression in the progression from HBV infection to hepatoma. AIM To explore the role of miRNAs in the progression of HBV infection to cirrhosis and even to liver cancer. METHODS We screened differentially expressed miRNAs in 40 HBV cirrhosis, 40 normal and 15 HCC tissues by using a TaqMan Low Density Array and real time quantitative polymerase chain reaction. To evaluate the power of the selected miRNAs to predict disease, we calculated the area under the receiver-operating-characteristic curves. The overall survival of HBV cirrhosis patients was analyzed via Kaplan-Meier analysis. RESULTS The levels of miR-375, miR-122 and miR-143 were significantly lower in HBV cirrhosis tissues, while miR-224 was significantly higher than in the controls (P < 0.0001). The area under the curves of the receiver-operating-characteristic curve for the 4-miRNA panel was 0.991 (95%CI: 0.974-1). Patients with a lower expression level of miR-224 or higher expression levels of miR-375, miR-122 and miR-143 had longer overall survival. CONCLUSION The four miRNAs (miR-375, miR-122, miR-143 and miR-224) may be helpful for early diagnosis of HBV infection, HBV cirrhosis, and prediction of its overall survival.

目的 分析野外军训中床旁即时检测仪(point of care testing,POCT)检测尿液肌红蛋白(myoglobin,Mb)的应用价值.方法 选取2019年10月8-10月19日某军校参加野外军训的新学员,采集其第1天训练后和最后1天训练后的血清和尿液样本,比较第1天和最后1天训练后的血清Mb和尿液Mb;以血清肌酸激酶(creatine kinase,CK)为检测肌肉损伤的标准,比较第1天训练后血清Mb与尿液Mb的敏感度和准确度.结果 65名新学员,均为男性,平均年龄18岁.相较于第1天,最后1天训练后POCT仪检测的尿液Mb水平明显下降(下降90.4％),差异有统计学意义(P<0.01).第1天训练后,血清检测CK阳性40例,血清Mb阳性2例,POCT仪检测尿液Mb阳性19例;血清Mb诊断肌肉损伤的敏感度为5.0％,显著低于尿液Mb的敏感度47.5％(P<0.001);血清Mb和尿液Mb的特异性均为100％;血清Mb的准确度小于尿液Mb的准确度(41.5％vs 67.7％,P=0.003).结论 相较于检测血清Mb,POCT仪检测尿液Mb敏感度和准确度更高,且尿液样本获取方便,POCT仪容易携带,因此POCT仪检测尿液Mb适用于野外军训条件下身体训练状态的预警监测.

数字PCR是近几年新兴的核酸检测手段,因其具有高灵敏度、高精确度、高重现性,正在逐渐取代先前的普通PCR方法.数字PCR目前已广泛应用在SNP、甲基化、二代测序辅助建库、疾病的诊断和治疗监控、微生物(病毒、细菌等)的检测,它将会有力推动生命科学、医学诊断、检验检疫、农业等领域的快速发展.本综述主要讨论数字PCR在检测血浆游离DNA方面的研究进展.