AML leukocyte classification method for small samples based on ACGAN.

Leukemia is a class of hematologic malignancies, of which acute myeloid leukemia (AML) is the most common. Screening and diagnosis of AML are performed by microscopic examination or chemical testing of images of the patient's peripheral blood smear. In smear-microscopy, the ability to quickly identify, count, and differentiate different types of blood cells is critical for disease diagnosis. With the development of deep learning (DL), classification techniques based on neural networks have been applied to the recognition of blood cells. However, DL methods have high requirements for the number of valid datasets. This study aims to assess the applicability of the auxiliary classification generative adversarial network (ACGAN) in the classification task for small samples of white blood cells. The method is trained on the TCIA dataset, and the classification accuracy is compared with two classical classifiers and the current state-of-the-art methods. The results are evaluated using accuracy, precision, recall, and F1 score. The accuracy of the ACGAN on the validation set is 97.1 % and the precision, recall, and F1 scores on the validation set are 97.5 , 97.3, and 97.4 %, respectively. In addition, ACGAN received a higher score in comparison with other advanced methods, which can indicate that it is competitive in classification accuracy.

Identification of Comprehensive Biomarkers in Patients With Mismatch Repair-Deficient Colon Adenocarcinoma Based on Parallel Multiomics.

Immunocheckpoint inhibitors have shown impressive efficacy in patients with colon cancer and other types of solid tumor that are mismatch repair-deficient (dMMR). Currently, PCR-capillary electrophoresis is one of the mainstream detection methods for dMMR, but its accuracy is still limited by germline mismatch repair (MMR) mutations, the functional redundancy of the MMR system, and abnormal methylation of MutL Homolog 1 promoter. Therefore, this study aimed to develop new biomarkers for dMMR based on artificial intelligence (AI) and pathologic images, which may help to improve the detection accuracy. To screen for the differential expression genes (DEGs) in dMMR patients and validate their diagnostic and prognostic efficiency, we used the expression profile data from the Cancer Genome Atlas (TCGA). The results showed that the expression of Immunoglobulin Lambda Joining 3 in dMMR patients was significantly downregulated and negatively correlated with the prognosis. Meanwhile, our diagnostic models based on pathologic image features showed good performance with area under the curves (AUCs) of 0.73, 0.86, and 0.81 in the training, test, and external validation sets (Jiangsu Traditional Chinese Medicine Hospital cohort). Based on gene expression and pathologic characteristics, we developed an effective prognosis model for dMMR patients through multiple Cox regression analysis (with AUC values of 0.88, 0.89, and 0.88 at 1-, 3-, and 5-year intervals, respectively). In conclusion, our results showed that Immunoglobulin Lambda Joining 3 and nucleus shape-related parameters (such as nuclear texture, nuclear eccentricity, nuclear size, and nuclear pixel intensity) were independent diagnostic and prognostic factors, suggesting that they could be used as new biomarkers for dMMR patients.

The genomic characteristics of RET fusion positive tumors in Chinese non-small cell lung cancer (NSCLC) patients.

BACKGROUND: Approximately 1-2% of non-small cell lung cancer (NSCLC) patients harbor RET (rearranged during transfection) fusions. The oncogenic RET fusions could lead to constitutive kinase activation and oncogenesis. METHODS: 1746 Chinese NSCLC patients were analyzed in this study. Tumor tissues were collected, and were formalin fixed, paraffin-embedded (FFPE) and archived. Peripheral blood (PB) samples were also collected from each patient as control. In addition, we selected 17 of them for cfDNA NGS testing and 14 tumor samples for immunohistochemistry testing using PD-L1 rabbit monoclonal antibody, clones 28-8 (Abcam, Cambridge, UK). RESULTS: Of the 1746 NSCLC cases, RET rearrangements were identified in 25 cases (1.43%) with locally advanced or metastatic NSCLC, of which 20 (80%) were female. We found that 14 out of 25 patients had an KIF5B-RET fusion, with KIF5B exon15-RET exon12, KIF5B exon23-RET exon12, and KIF5B exon24-RET exon11 detected in 14, 3, and 1 patients, respectively. We also identified one novel RET fusion partner PLCE1 and 4 intergenic-breakpoint fusions. CONCLUSION: In this study, using the hybrid capture based next generation sequencing (NGS) techniques, we revealed the genomic profiling for the patients with RET fusion-positive NSCLC. To the best of our knowledge, this is the first study that exhibited the detailed breakpoints of Chinese NSCLC patients with RET rearrangement, and we found a novel new partner PLCE1. The results provided genomic information for patients with RET fusion which is significant for personalized clinical management in the era of precision medicine.

Comparison of clinicopathological features and prognosis of papillary thyroid carcinoma and microcarcinoma: A population-based propensity score matching analysis.

Background: Overtreatment of papillary thyroid microcarcinoma (PTMC) has become a common concern. This study aimed to compare clinicopathological features between PTMC and papillary thyroid carcinoma (PTC) and to explore whether surgery can confer significant survival benefits in all patients with PTC or PTMC. Methods: Data of 145,951 patients with PTC registered in Surveillance, Epidemiology, and End Results (SEER) database and 8,751 patients with PTC in our institution were retrospectively collected. Patients with tumors less than 10 mm in diameter were classified as PTMC cohort and the rest as PTC cohort. Clinicopathological features between PTMC and PTC were compared on the basis of SEER cohort and validated with institutional data. Survival analysis was conducted to explore the effect of surgery on the prognosis of patients. To minimize potential confounders and selection bias, we performed propensity score matching (PSM) analysis to match more comparable cohorts. Results: Compared with PTC, PTMC exhibited the following characteristics: more common in women and whites, older age at diagnosis, lower proportion of follicular variants, intraglandular dissemination, extraglandular and capsular invasion, higher proportion of multifocality, fewer lymph node and distant metastases, and higher cancer-specific survival (CSS) and overall survival (OS) (all p-value < 0.05). Regarding treatment, patients with PTMC received a lower proportion of radiotherapy, chemotherapy, and total thyroidectomy but a higher proportion of lobectomy and/or isthmectomy. There was no significant difference in CSS for patients with PTMC at stage T1N0M0 with or without surgery (P = 0.36). Conclusion: Generally, PTMC showed higher biological indolence than PTC, which meant a higher survival rate for patients in both OS and CSS. For patients with PTMC at staged T1N0M0, active surveillance (AS) may be a potentially feasible management strategy. However, the maintenance of good medical compliance and the management of psychological burden cannot be ignored for patients included in AS.

Pyroptosis may play a crucial role in modifications of the immune microenvironment in periodontitis.

BACKGROUND AND OBJECTIVE: Published studies proved that both pyroptosis and periodontitis owned a substantial relationship with immunity, and recent research revealed a solid correlation between periodontitis and pyroptosis. While abundant findings have confirmed pyroptosis has a strong impact on the tumor microenvironment, the function of pyroptosis in influencing the periodontitis immune microenvironment remains poorly understood. Thus, we aimed to identify pyroptosis-related genes whose expression signature can well discriminate periodontitis from healthy controls and to comprehend the role of pyroptosis in the periodontitis immune microenvironment. MATERIALS AND METHODS: The periodontitis-related datasets were acquired from the Gene Expression Omnibus (GEO) database. A series of bioinformatics analyses were conducted to investigate the underlying mechanism of pyroptosis in the periodontitis immune microenvironment. Infiltrating immunocytes, immunological reaction gene sets, and the human leukocyte antigen (HLA) gene were all investigated as potential linkages between periodontitis immune microenvironment and pyroptosis. RESULTS: Twenty-one pyroptosis-related genes were dysregulated. A four-mRNA combined classification model was constructed, and the receiver operating characteristic (ROC) curve analysis demonstrated its prominent classification capabilities. Subsequently, the mRNA levels of the four hub markers (CYCS, CASP3, NOD2, CHMP4B) were validated by quantitative real-time PCR (qRT-PCR). The correlation coefficients between each hub gene and immune characteristics were calculated, and CASP3 exhibited the most significant correlations with the immune characteristics. Furthermore, distinct pyroptosis-related expression patterns were revealed, along with immunological features of each pattern. Afterward, we discovered 1868 pyroptosis phenotype-related genes, 134 of which were related to immunity. According to the functional enrichment analysis, these 134 genes were closely related to cytokine signaling in immune system, and defense response. Finally, a co-expression network was constructed via the 1868 gene expression profiles. CONCLUSION: Four hub mRNAs (CYCS, CASP3, NOD2, and CHMP4B) formed a classification model and concomitant results revealed the crucial role of pyroptosis in the periodontitis immune microenvironment, providing fresh insights into the etiopathogenesis of periodontitis and potential immunotherapy.

Clinical Significance and Immune Landscape of Recurrence-Associated Ferroptosis Signature in Early-Stage Lung Adenocarcinoma.

BACKGROUND: The prevalence of patients newly diagnosed with early-stage lung adenocarcinoma (LUAD) is growing alongside significant advances in screening approaches. This study aimed to construct ferroptosis-related gene score (FRGscore) for predicting recurrence, explore immune-molecular characteristics, and determine the benefit of immunotherapy in distinct ferroptosis-based patterns and FRGscore-defined subgroups. METHODS: A total of 1,085 early-stage LUAD patients from four independent cohorts were included. Consensus clustering analysis was performed using 217 co-expressed FRGs to explore different ferroptosis-mediated patterns. An FRG scoring system was established to predict relapse, quantify ferroptosis-mediated patterns, and evaluate the response to immunotherapy in individual patients based on Lasso-penalized and stepwise Cox regression analyses. Immune landscape involving multiple parameters was further evaluated, stratified by cluster subtypes and FRGscore subgroups. RESULTS: Two ferroptosis-mediated patterns were identified and verified, which were characterized by significantly distinct prognosis and immune profiles. Analyses of immune characteristics showed that identified ferroptosis patterns were characterized as immune-inflamed phenotype and immune-exhausted phenotype. The FRG scoring model based on 11 FRG-derived signatures panel classified patients into the FRGscore-high and FRGscore-low subgroups. Significantly longer recurrence-free survival (RFS) and overall survival (OS) were observed in the FRGscore-low subgroup. FRGscore-low patients were characterized by higher tumor mutational burden (TMB), immunoscore, immunophenoscore, and PD-L1 expression level and were associated with lower Tumor Immune Dysfunction and Exclusion (TIDE) score, whereas the opposite was observed in FRGscore-high patients. Immune-active pathways were remarkably enriched in the FRGscore-low subgroup. This scoring model remained highly predictive of prognosis across different clinical, molecular, and immune subgroups. Further analysis indicated that FRGscore-low patients exhibited higher response to anti-PD-1/PD-L1 immunotherapy and better clinical benefits based on two independent immunotherapy cohorts. CONCLUSION: The proposed FRGscore could highly distinguish the recurrence patterns and molecular and immune characteristics and could predict immunotherapy prognosis, potentially representing a powerful prognostic tool for further optimization of individuated treatment and management strategies in early-stage LUAD.

A practical method to screen and identify functioning biomarkers in nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a rare malignancy, with the unique geographical and ethnically characteristics of distribution. Gene chip and bioinformatics have been employed to reveal regulatory mechanisms in current functional genomics. However, a practical solution addressing the unresolved aspects of microarray data processing and analysis have been long pursuit. This study developed a new method to improve the accuracy of identifying key biomarkers, namely Unit Gamma Measurement (UGM), accounting for multiple hypotheses test statistics distribution, which could reduce the dependency problem. Three mRNA expression profile of NPC were selected to feed UGM. Differentially expressed genes (DEGs) were identified with UGM and hub genes were derived from them to explore their association with NPC using functional enrichment and pathway analysis. 47 potential DEGs were identified by UGM from the 3 selected datasets, and affluent in cysteine-type endopeptidase inhibitor activity, cilium movement, extracellular exosome etc. also participate in ECM-receptor interaction, chemical carcinogenesis, TNF signaling pathway, small cell lung cancer and mismatch repair pathway. Down-regulation of CAPS and WFDC2 can prolongation of the overall survival periods in the patients. ARMC4, SERPINB3, MUC4 etc. have a close relationship with NPC. The UGM is a practical method to identify NPC-associated genes and biomarkers.

Chemokine (C-X-C Motif) Ligand 4 Is a Restrictor of Respiratory Syncytial Virus Infection and an Indicator of Clinical Severity.

Rationale: Respiratory syncytial virus (RSV) is the leading cause of childhood respiratory infections worldwide; however, no vaccine is available, and treatment options are limited. Identification of host factors pivotal to viral replication may inform the development of novel therapies, prophylaxes, or diagnoses.Objectives: To identify host factors involved in RSV replication and to evaluate their potential for disease management.Methods: A gain-of-function screening was performed on the basis of a genome-wide human complementary DNA library screen for host factors involved in RSV replication. The antiviral mechanism of CXCL4 (chemokine [C-X-C motif] ligand 4) was analyzed. Its clinical role was evaluated via nasopharyngeal aspirates and plasma samples from patients with RSV infection and different disease severities.Measurements and Main Results: Forty-nine host factors restricting RSV replication were identified by gain-of-function screening, with CXCL4 showing the strongest antiviral effect, which was secretion dependent. CXCL4 blocked viral attachment through binding to the RSV main receptor heparan sulfate, instead of through interacting with RSV surface proteins. Intranasal pretreatment with CXCL4 alleviated inflammation in RSV-infected mice, as shown by decreased concentrations of tumor necrosis factor and viral load in BAL fluid samples as well as by viral nucleocapsid protein histological staining in lungs. Compared with non-RSV infections, RSV infections induced elevated CXCL4 concentrations both in plasma and airway samples from mice and pediatric patients. The airway CXCL4 concentration was correlated with viral load and disease severity in patients (P < 0.001).Conclusions: Our results suggest that CXCL4 is an RSV restriction factor that can block viral entry and serve as an indicator of clinical severity in RSV infections.

UGM: a more stable procedure for large-scale multiple testing problems, new solutions to identify oncogene.

Variations of gene expression levels play an important role in tumors. There are numerous methods to identify differentially expressed genes in high-throughput sequencing. Several algorithms endeavor to identify distinctive genetic patterns susceptable to particular diseases. Although these processes have been proved successful, the probability that the number of non-differentially expressed genes measured by false discovery rate (FDR) has a large standard deviation, and the misidentification rate (type I error) grows rapidly when the number of genes to be detected become larger. In this study we developed a new method, Unit Gamma Measurement (UGM), accounting for multiple hypotheses test statistics distribution, which could reduce the dependency problem. Simulated expression profile data and breast cancer RNA-Seq data were utilized to testify the accuracy of UGM. The results show that the number of non-differentially expressed genes identified by the UGM is very close to the real-evidence data, and the UGM also has a smaller standard error, range, quartile range and RMS error. In addition, the UGM can be used to screen many breast cancer-associated genes, such as BRCA1, BRCA2, PTEN, BRIP1, etc., provides better accuracy, robustness and efficiency, the method of identification differentially expressed genes in high-throughput sequencing.

Melatonin Suppresses Neuropathic Pain via MT2-Dependent and -Independent Pathways in Dorsal Root Ganglia Neurons of Mice.

Melatonin (Mel) and its receptors (MT1 and MT2) have a well-documented efficacy in treating different pain conditions. However, the anti-nociceptive effects of Mel and Mel receptors in neuropathic pain (NP) are poorly understood. To elucidate this process, pain behaviors were measured in a dorsal root ganglia (DRG)-friendly sciatic nerve cuffing model. We detected up-regulation of MT2 expression in the DRGs of cuff-implanted mice and its activation by the agonist 8-M-PDOT (8MP). Also, Mel attenuated the mechanical and thermal allodynia induced by cuff implantation. Immunohistochemical analysis demonstrated the expression of MT2 in the DRG neurons, while MT1 was expressed in the satellite cells. In cultured primary neurons, microarray analysis and gene knockdown experiments demonstrated that MT2 activation by 8MP or Mel suppressed calcium signaling pathways via MAPK1, which were blocked by RAR-related orphan receptor alpha (RORα) activation with a high dose of Mel. Furthermore, expression of nitric oxide synthase 1 (NOS1) was down-regulated upon Mel treatment regardless of MT2 or RORα. Application of Mel or 8MP in cuff-implanted models inhibited the activation of peptidergic neurons and neuro-inflammation in the DRGs by down-regulating c-fos, calcitonin gene-related peptide [CGRP], and tumor necrosis factor-1α [TNF-1α] and interleukin-1ß [IL-1ß]. Addition of the MT2 antagonist luzindole blocked the effects of 8MP but not those of Mel. In conclusion, only MT2 was expressed in the DRG neurons and up-regulated upon cuff implantation. The analgesic effects of Mel in cuff-implanted mice were closely associated with both MT2-dependent (MAPK-calcium channels) and MT2-independent (NOS1) pathways in the DRG.