Objective To analyze the gene expression of patients with head and neck squamous cell carcinoma(HNSCC)using bioinformatics methods,identifying immune-related genes that impact prognosis and exploring new therapeutic targets for HNSCC.Methods This study was based on The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus database to download RNA sequencing data from HNSCC and non-tumor tissue samples.Differential expression gene analysis and weighted gene co-expression network analysis were performed respectively to screen immune-related genes.Univariate Cox regression,Lasso regression and multifactor Cox regression analyses were used to identify the genes significantly associated with HNSCC prognosis,and on this basis,the risk score of each TCGA sample was calculated and the correlation prognosis model was constructed.The sample was divided into high and low risk groups according to the median risk score.Gene differential expression analysis was performed in high and low risk groups to reveal gene expression changes under different immune states,and pathway enrichment analysis was performed for differential genes.Results Screening identified MS4A1,IL12RB2,DMBT1 and LTF as immune-related genes affecting the prognosis of HNSCC.Among them,MS4A1 and IL12RB2 were highly expressed in HNSCC,and DMBT1 and LTF were lowly expressed.Risk score of HNSCC death group was significantly higher than that of the survival group.Risk score could be used as an independent prognostic indicator for HNSCC.Differential genes in high and low risk groups were significantly enriched in immune response-regulating cell surface receptor signaling pathways.Conclusion MS4A1,IL12RB2,DMBT1 and LTF can be used for risk assessment,disease surveillance and efficacy evaluation of HNSCC.The immune response is crucial in the prognosis of HNSCC patients,and further studies are expected to drive the development of new therapeutic strategies.

Objective To analyze the gene expression of patients with head and neck squamous cell carcinoma(HNSCC)using bioinformatics methods,identifying immune-related genes that impact prognosis and exploring new therapeutic targets for HNSCC.Methods This study was based on The Cancer Genome Atlas(TCGA)and Gene Expression Omnibus database to download RNA sequencing data from HNSCC and non-tumor tissue samples.Differential expression gene analysis and weighted gene co-expression network analysis were performed respectively to screen immune-related genes.Univariate Cox regression,Lasso regression and multifactor Cox regression analyses were used to identify the genes significantly associated with HNSCC prognosis,and on this basis,the risk score of each TCGA sample was calculated and the correlation prognosis model was constructed.The sample was divided into high and low risk groups according to the median risk score.Gene differential expression analysis was performed in high and low risk groups to reveal gene expression changes under different immune states,and pathway enrichment analysis was performed for differential genes.Results Screening identified MS4A1,IL12RB2,DMBT1 and LTF as immune-related genes affecting the prognosis of HNSCC.Among them,MS4A1 and IL12RB2 were highly expressed in HNSCC,and DMBT1 and LTF were lowly expressed.Risk score of HNSCC death group was significantly higher than that of the survival group.Risk score could be used as an independent prognostic indicator for HNSCC.Differential genes in high and low risk groups were significantly enriched in immune response-regulating cell surface receptor signaling pathways.Conclusion MS4A1,IL12RB2,DMBT1 and LTF can be used for risk assessment,disease surveillance and efficacy evaluation of HNSCC.The immune response is crucial in the prognosis of HNSCC patients,and further studies are expected to drive the development of new therapeutic strategies.

Objective:To evaluate the performance of an artificial intelligent (AI)-based automated digital cell morphology analyzer (hereinafter referred as AI morphology analyzer) in detecting peripheral white blood cells (WBCs).Methods:A multi-center study. 1. A total of 3010 venous blood samples were collected from 11 tertiary hospitals nationwide, and 14 types of WBCs were analyzed with the AI morphology analyzers. The pre-classification results were compared with the post-classification results reviewed by senior morphological experts in evaluate the accuracy, sensitivity, specificity, and agreement of the AI morphology analyzers on the WBC pre-classification. 2. 400 blood samples (no less than 50% of the samples with abnormal WBCs after pre-classification and manual review) were selected from 3 010 samples, and the morphologists conducted manual microscopic examinations to differentiate different types of WBCs. The correlation between the post-classification and the manual microscopic examination results was analyzed. 3. Blood samples of patients diagnosed with lymphoma, acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndrome, or myeloproliferative neoplasms were selected from the 3 010 blood samples. The performance of the AI morphology analyzers in these five hematological malignancies was evaluated by comparing the pre-classification and post-classification results. Cohen′s kappa test was used to analyze the consistency of WBC pre-classification and expert audit results, and Passing-Bablock regression analysis was used for comparison test, and accuracy, sensitivity, specificity, and agreement were calculated according to the formula.Results:1. AI morphology analyzers can pre-classify 14 types of WBCs and nucleated red blood cells. Compared with the post-classification results reviewed by senior morphological experts, the pre-classification accuracy of total WBCs reached 97.97%, of which the pre-classification accuracies of normal WBCs and abnormal WBCs were more than 96% and 87%, respectively. 2. The post-classification results reviewed by senior morphological experts correlated well with the manual differential results for all types of WBCs and nucleated red blood cells (neutrophils, lymphocytes, monocytes, eosinophils, basophils, immature granulocytes, blast cells, nucleated erythrocytes and malignant cells r>0.90 respectively, reactive lymphocytes r=0.85). With reference, the positive smear of abnormal cell types defined by The International Consensus Group for Hematology, the AI morphology analyzer has the similar screening ability for abnormal WBC samples as the manual microscopic examination. 3. For the blood samples with malignant hematologic diseases, the AI morphology analyzers showed accuracies higher than 84% on blast cells pre-classification, and the sensitivities were higher than 94%. In acute myeloid leukemia, the sensitivity of abnormal promyelocytes pre-classification exceeded 95%. Conclusion:The AI morphology analyzer showed high pre-classification accuracies and sensitivities on all types of leukocytes in peripheral blood when comparing with the post-classification results reviewed by experts. The post-classification results also showed a good correlation with the manual differential results. The AI morphology analyzer provides an efficient adjunctive white blood cell detection method for screening malignant hematological diseases.

To explore the pharmacogenomic markers that affect the platinum-based chemotherapy response in non-small-cell lung carcinoma (NSCLC), we performed a two-cohort of genome-wide association studies (GWAS), including 34 for WES-based and 433 for microarray-based analyses, as well as two independent validation cohorts. After integrating the results of two studies, the genetic variations related to the platinum-based chemotherapy response were further determined by fine-mapping in 838 samples, and their potential functional impact were investigated by eQTL analysis and in vitro cell experiments. We found that a total of 68 variations were significant at P < 1 × 10^-3 in cohort 1 discovery stage, of which 3 SNPs were verified in 262 independent samples. A total of 541 SNPs were significant at P < 1 × 10^-4 in cohort 2 discovery stage, of which 8 SNPs were verified in 347 independent samples. Comparing the validated SNPs in two GWAS, ADCY1 gene was verified in both independent studies. The results of fine-mapping showed that the G allele carriers of ADCY1 rs2280496 and C allele carriers of rs189178649 were more likely to be resistant to platinum-based chemotherapy. In conclusion, our study found that rs2280496 and rs189178649 in ADCY1 gene were associated the sensitivity of platinum-based chemotherapy in NSCLC patients.

Inherited bleeding and thrombotic disorders (BTD) are a group of heterogeneous diseases related to the coagulation system, platelet function and fibrinolytic system. In addition to the common BTD, it is difficult to diagnose such patients by routine laboratory tests, and special laboratory tests are often required to confirm the diagnosis. Therefore, the diagnosis and treatment of patients may be delayed, or even life-threatening. With the increasing use of high-throughput sequencing (HTS) technology in clinical practice, the diagnosis and differential diagnosis of BTD have made great progress.

Central nervous system (CNS) involvement is a serious complication of hematological malignancies. At present, the gold standard to detect CNS involvement is cerebrospinal fluid (CSF) cytology, but it has low sensitivity. The multiparameter flow cytometry (MFC) shows higher sensitivity than CSF cytology. The occult central nervous system involvement with negative conventional cytology but positive MFC result is the same as dominant central nervous system involvement, which is associated with a high risk of recurrence of hematological tumors. However, due to the particularity of cerebrospinal fluid specimens--less number of cells, low activity, and more interfering cells, the application of MFC for detection of cerebrospinal fluid is limited. Therefore, there is an urgent need to standardize the MFC detection of CSF for hematological tumors, including defining specimen transportation, antibody selection and cut-off value, standardizing data analysis and strengthening employee training, which will greatly improve the role of MFC in the diagnosis of CNS with hematological malignancies.

Flow cytometry has been widely used in clinical practice. Due to the powerful user-defined function of flow cytometry, different instrument settings among manufacturers and lack of standard materials, the comparability of results needs to be improved and flow cytometry is facing the great challenge of normalization and standardization. In this paper, the recent progress of normalization and standardization about flow cytometry was discussed form the aspects of standardizing operation protocol, including specimen and centrifugation, standardizingantibody selection and panel combination and ensuring instrument and data analysis consistency.

Objective:To investigate the role and influencing factors of case design in PBL teaching.Methods:Thirty-two six-year-program undergraduates from the Department of Medicine of Peking University in batch 2014 and batch 2015 were selected as the subjects. PBL teaching was used in the practice class of experimental diagnostics. The feedback effects of four times PBL courses were analyzed by collecting questionnaires for teachers, students, and supervisors. The data obtained from the five-point questionnaire and the question-and-answer questionnaire were analyzed by one-way ANOVA and statistics respectively. Then the problems in case preparation process are discussed and the experience of case design is summarized. SPSS 13.0 was used in this study.Results:The 5-point questionnaire showed that the average score of anemia PBL course was the highest among students' self-evaluation and mutual evaluation of teachers and students (4.84 points, 4.79 points), with statistical significance compared with other courses ( P<0.05). The question-and-answer questionnaire survey showed that 93.75% of the students generally agreed with the teaching model of anemia cases; 78.13% and 59.38% of the students believed that it was difficult to set up cases of infection and coagulation, which affected the classroom effect; and 50% of the supervisors thinked that the students' level should be taken into account in case design and oral expression should be avoided. Conclusion:Case design is the key to PBL teaching. Summarizing the experience of case design can lay a good foundation for the establishment of PBL teaching database.

Objective:To evaluate the diagnostic value of HPV detection in squamous cell carcinoma of the cervical lymph node metastasis from an unknown primary site.Methods:Clinical data of 6 patients who were initially diagnosed with squamous cell carcinoma of the cervical lymph node metastasis from an unknown primary site and eventually diagnosed with HPV-related oropharyngeal squamous cell carcinoma were collected, and the process of diagnosis was analyzed.Results:Upon the initial admission, all patients were diagnosed with squamous cell carcinoma of the cervical lymph node metastasis with positive p16 expression, positive HPV-16 subtype and negative EBER expression. No obvious primary lesion was found after comprehensive examination. Subsequently, four of them underwent ipsilateral tonsollar blind biopsy ( n=2) and ipsilateral tonsillectomy ( n=2). All these four patients were pathologically diagnosed with tonsillar squamous cell carcinoma. For the other two cases, MRI detected the thickening complicated with enhancement of ipsilateral wall of oropharynx and tongue root after follow-up for D149 and D545 , respectively. Biopsy confirmed the diagnosis of squamous cell carcinoma of the tonsil and tongue root, respectively. Conclusion:For patients with HPV-positive squamous cell carcinoma of the cervical lymph node metastasis from an unknown primary site, the possibility that the primary lesion originates from the oropharyngeal site, especially the tonsil and tongue root, should be highly suspected.

Objective: To establish a set of rules for autoverification of blood analysis, in order to provide a way to validate autoverification rules for different analytical systems, which can ensure the accuracy of test results as well as shorten turnaround time (TAT) of test reports. Methods: A total of 34 629 EDTA-K2 anticoagulated blood samples were collected from multicenter cooperative units including the First Hospital of Jinlin University during January 2017 to November 2017. These samples included: 3 478 cases in Autoverification Establishment Group, including 288 cases for Delta check rules; 5 362 cases in Autoverification Validation Group, including 2 494 cases for Delta check; 25 789 cases in Clinical Application Trial Group. All these samples were analyzed for blood routine tests using Sysmex XN series automatic blood analyzers.Blood smears, staining and microscopic examination were done for each sample; then the clinical information, instrument parameters, test results and microscopic results were summarized; screening and determination of autoverification conditions including parameters and cutoff values were done using statistical analysis. The autoverification rules were input into Sysmex Laboman software and undergone stage Ⅰ validation using simulated data, and stage Ⅱ validation for post-analytical samples successively. True negative, false negative, true positive, false positive, autoverification pass rate and passing accuracy were calculated. Autoverification rules were applied to autoverification blood routine results and missed detection rates were validated, and also data of autoverification pass rate and TAT were obtained. Results: (1)The selected autoverification conditions and cutoff values included 43 rules involving WBC, RBC, PLT, Delta check and abnormal characteristics. (2)Validation of 3 190 cases in Autoverification Establishment Group showed the false negative rate was 1.94%(62/3 190)(P<0.001), autoverification pass rate was 76.74%, passing accuracy was 97.47%; Validation of 2 868 cases in Autoverification Validation Group, the false negative rate was 3.38%(97/2 868)(P=0.002), autoverification pass rate was 42.26%, passing accuracy was 92.00%; Validation of Delta check on 288 cases in Autoverification Establishment Group and 2 494 cases in Autoverification Validation Group showed the false negative rates were respectively 1.39% and 2.61%(P<0.001). (3)Three hospitals adopted these rules of autoverification for 25 789 blood routine samples, and found that the average TAT of blood routine test reports were shortened by 24min, 32min and 7min respectively, the rate of samples reported within 30min were elevated by 33%, 53% and 7%. The autoverification pass rates were 72%-74%. Conclusions The application of this set of 43 autoverification rules in blood sample analysis can ensure test quality while shortenTAT and improve work efficiency. It is worth pointing out that for the same analytical systems in this research, validation is necessary before application of this set of rules, and periodic validation is required during application to make necessary adjustment; for different analytical systems, as this research provide a way to establish autoverification rules for blood routine tests.Clinical labs may establish their own suitable autoverification rules on the basis of technological parameters. (Chin J Lab Med, 2018, 41: 601-607)