急性髓系白血病患者HtrA2基因、Set基因表达与疗效和预后的关系研究

摘要 目的：探讨急性髓系白血病（AML）患者HtrA2基因、Set基因表达与疗效和预后的关系。方法：选择2017年6月~2019年6月来我院进行治疗的90例病历资料完整的初诊为AML患者作为本次研究对象,作为AML组,另选取同时期来我院进行健康体检的90例志愿者作为对照组。检测HtrA2基因、Set基因在两组受试者外周血中的表达;分析HtrA2基因、Set基因的表达与AML患者年龄、性别、白细胞计数、NCCN预后分型和疗效的关系。结果：HtrA2基因在AML组中表达水平低于对照组,Set基因在AML组中表达水平高于对照组（P<0.05）。HtrA2基因的表达和年龄、性别、白细胞计数无关（P>0.05）;Set基因的表达和年龄、性别无关（P>0.05）,与白细胞计数有关（P<0.05）。HtrA2基因在NCCN不同的预后分组中的表达差异无统计学意义（P>0.05）;Set基因在NCCN不同的预后分组中的表达差异有统计学意义（P<0.05）。HtrA2基因和Set基因在不同疗效患者中的表达差异有统计学意义（P<0.05）。结论：AML患者HtrA2基因表达下降,Set基因表达升高,Set基因和HtrA2基因具有评估AML疗效的潜力,Set基因可辅助评估AML患者的预后。     

Single-cell sequencing analysis and transcriptome analysis constructed the macrophage related gene-related signature in lung adenocarcinoma and verified by an independent cohort

BackgroundRecent studies have emphasized the close relationship between macrophages and tumor immunity, and the prognosis of lung adenocarcinoma (LUAD) patients is intimately linked to this. Nonetheless, the prognostic signature and classification of different immune patterns in LUAD patients based on the macrophages is largely unexplored.MethodsTwo sc-RNAseq datasets of LUAD patients were collected and reprocessed. The differentially expressed genes (DEGs) related to macrophages between LUAD tissues and normal lung tissues were then identified. Based upon the above genes, three distinct immune patterns in the TCGA-LUAD cohort were identified. The ssGSEA and CIBERSORT were applied for immune profiling and characterization of different subtypes. A four-gene prognostic signature for LUAD patients was established based on the DEGs between the subtypes using stepwise multi-Cox regression. TCGA-LUAD cohort was used as training set. Five GEO-LUAD datasets and an independent cohort containing 112 LUAD samples were used for validation. TIDE (tumor immune dysfunction and exclusion) and drug sensitivity analyses were also performed.ResultsMacrophage-related differentially expressed genes were found out using the publicly available scRNA-seq data of LUAD. Three different immune patterns which were proved to have distinct immune infiltration characteristics in the TCGA-LUAD cohort were recognized based on the above macrophage-related genes. Thereafter, 174 DEGs among the above three different immune patterns were figured out; on the basis of this, a four-gene prognostic signature was constructed. This signature distinguished the prognosis of LUAD patients well in various GSE datasets as well as our independent cohort. Further analyses revealed that patients which had a higher risk score also accompanied with a lower immune infiltration level and a worse response to several immunotherapy biomarkers.ConclusionThis study highlighted that macrophage were significantly associated with TME diversity and complexity. The four-gene prognostic signature could be used for predicting outcomes and immune landscapes for patients with LUAD.     

Construction and validation of a novel apoptosis-associated prognostic signature related to osteosarcoma metastasis and immune infiltration

BackgroundApoptosis played vital roles in the formation and progression of osteosarcoma. However, no studies elucidated the prognostic relationships between apoptosis-associated genes (AAGs) and osteosarcoma.MethodsThe differentially expressed genes associated with osteosarcoma metastasis and apoptosis were identified from GEO and MSigDB databases. The apoptosis-associated prognostic signature was established through univariate and multivariate cox regression analyses. The Kaplan–Meier (KM) survival curve, ROC curve and nomogram were constructed to investigate the predictive value of this signature. CIBERSORT algorithm and ssGSEA were used to explore the relationships between immune infiltration and AAG signature. The above results were validated in another GEO dataset and the expression of AAGs was also validated in osteosarcoma patient samples by immunohistochemistry.ResultsHSPB1 and IER3 were involved in AAG signature. In training and validation datasets, apoptosis-associated risk scores were negatively related to patient survival rates and the AAG signature was regarded as the independent prognostic factor. ROC and calibration curves demonstrated the signature and nomogram were reliable. GSEA revealed the signature related to immune-associated pathways. ssGSEA indicated that one immune cell and three immune functions were significantly dysregulated. The immunohistochemistry analyses of patients’ samples revealed that AAGs were significantly differently expressed between metastasis and non-metastasis osteosarcomas.ConclusionsThe present study identified and validated a novel apoptosis-associated prognostic signature related to osteosarcoma metastasis. It could serve as the potential biomarker and therapeutic targets for osteosarcoma in the future.     

Construction of a paclitaxel-related competitive endogenous RNA network and identification of a potential regulatory axis in pancreatic cancer

BackgroundIncreasing numbers of studies have elucidated the role of competitive endogenous RNA (ceRNA) networks in carcinogenesis. However, the potential role of the paclitaxel-related ceRNA network in the innate mechanism and prognosis of pancreatic cancer has not been identified.MethodsComprehensive bioinformatics analyses were performed to identify drug-related miRNAs (DRmiRNAs), drug-related mRNAs (DRmRNAs) and drug-related lncRNAs (DRlncRNAs) and construct a ceRNA network. The ssGSEA and CIBERSORT algorithms were utilized for immune cell infiltration analysis. Additionally, we validated our paclitaxel-related ceRNA regulatory axis at the gene expression level; functional experiments were conducted to explore the biological functions of the key genes.ResultsA total of 182 mRNAs, 13 miRNAs, and 53 lncRNAs were confirmed in the paclitaxel-related ceRNA network. In total, 6 mRNAs, 4 miRNAs, and 6 lncRNAs were identified to establish a risk signature and exhibited optimal prognostic effects. The mRNA signature can predict the abundance of immune cell infiltration and the sensitivity of different chemotherapeutic drugs and may also have a guiding effect in immune checkpoint therapy. A potential PART1/hsa-mir-21/SCRN1 axis was confirmed according to the ceRNA theory and was verified by qPCR. The results indicated that PART1 knockdown markedly increased hsa-mir-21 expression but inhibited SCRN1 expression, weakening the proliferation and migration abilities.ConclusionsWe hypothesized that the paclitaxel-related ceRNA network strongly influences the innate mechanism, prognosis, and immune infiltration of pancreatic cancer. Our risk signatures can accurately predict survival outcomes and provide a clinical basis.     

Construction of a prognostic signature in Ewing's sarcoma: Based on metabolism-related genes

ObjectiveBy combining the expression profiles of metabolism-related genes (MRGS) with clinical information, the expression quantities of MRGS and the influence on development and prognosis were systematically analyzed, so as to provide a theoretical basis for the clinical study on the prognosis of Ewing's sarcoma.MethodsMRGs expression profiles of 64 patients with Ewing's sarcoma were obtained from GEO dataset. Univariate Cox regression analysis was used to identify metabolization-related differentially expressed genes (DEGs) related with prognosis in Ewing's sarcoma patients. Then, multivariate Cox analysis was used to calculate novel prognostic markers based on metabolism-related DEGs. Besides, We validate the model using ICGC datasets. Finally, the new prognostic index was verified on the basis of the prognostic models.ResultsMultivariate Cox regression analysis identified 74 metabolization-related DEGs, 25 of which were associated with Ewing's sarcoma patients' overall survival. Subsequently, we used 25 DEGs to construct metabolism-related prognostic signature for patients with Ewing's sarcoma. Based on the 18 DEGs regression coefficient, we propose the formula of each patient's risk score, and then divided the patients into high-risk group and low-risk group. The results indicated that the survival rate and survival time were higher in the low-risk group and lower in the high-risk group. Multivariate Cox analysis showed that risk score index was an independent prognostic factor for Ewing's sarcoma.ConclusionThe experimental results suggest that the 18 metabolism-related DEGs marker may be effective in predicting the prognosis of Ewing's sarcoma to some extent, helping to individualize treatment of patients at different risks.     

Construction of a prognostic signature in Ewing's sarcoma: Based on metabolism-related genes

ObjectiveBy combining the expression profiles of metabolism-related genes (MRGS) with clinical information, the expression quantities of MRGS and the influence on development and prognosis were systematically analyzed, so as to provide a theoretical basis for the clinical study on the prognosis of Ewing's sarcoma.MethodsMRGs expression profiles of 64 patients with Ewing's sarcoma were obtained from GEO dataset. Univariate Cox regression analysis was used to identify metabolization-related differentially expressed genes (DEGs) related with prognosis in Ewing's sarcoma patients. Then, multivariate Cox analysis was used to calculate novel prognostic markers based on metabolism-related DEGs. Besides, We validate the model using ICGC datasets. Finally, the new prognostic index was verified on the basis of the prognostic models.ResultsMultivariate Cox regression analysis identified 74 metabolization-related DEGs, 25 of which were associated with Ewing's sarcoma patients' overall survival. Subsequently, we used 25 DEGs to construct metabolism-related prognostic signature for patients with Ewing's sarcoma. Based on the 18 DEGs regression coefficient, we propose the formula of each patient's risk score, and then divided the patients into high-risk group and low-risk group. The results indicated that the survival rate and survival time were higher in the low-risk group and lower in the high-risk group. Multivariate Cox analysis showed that risk score index was an independent prognostic factor for Ewing's sarcoma.ConclusionThe experimental results suggest that the 18 metabolism-related DEGs marker may be effective in predicting the prognosis of Ewing's sarcoma to some extent, helping to individualize treatment of patients at different risks.     

NDRG2 and TLR7 as novel DNA methylation prognostic signatures for acute myelocytic leukemia

Acute myelocytic leukemia (AML) is an aggressive malignant tumor and typically fatal without treatment. Identification and development of novel biomarkers could be beneficial for the diagnosis and prognosis of AML patients. Here, we aimed to identify the accurate DNA methylation prognostic signatures for AML patients. The DNA methylation data of AML patients and corresponding clinical information were retrieved from The Cancer Genome Atlas database. CPG sites that correlates closely with the survival of the AML patients were identified and further combined into CPG sites pairs to screen the survival-related pairs. The prognostic signatures were identified by the C-index and forward search algorithms and validated by the verification group. Finally, the functional enrichment analysis was performed on these CPG sites. As a result, a total of 498 CPG sites associated with the overall survival of AML patients was obtained. A prognostic signature composed of 10 CPG sites pairs was obtained and validated. The functional enrichment analysis showed prognostic genes were mainly enriched in tumor protein processing, cell differentiation, blood leukocyte immunity, and platelet growth factor pathways. In summary, we identified two accurate prognostic methylation signatures (NDRG2 and TLR7), which would be served as a novel therapy target for AML.     

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

Background

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively.

Methods and Findings

Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER− patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome.

Conclusions

The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer.     

Prognostic role of Wnt and Fzd gene families in acute myeloid leukaemia

Wnt-Fzd signalling pathway plays a critical role in acute myeloid leukaemia (AML) progression and oncogenicity. There is no study to investigate the prognostic value of Wnt and Fzd gene families in AML. Our study screened 84 AML patients receiving chemotherapy only and 71 also undergoing allogeneic haematopoietic stem cell transplantation (allo-HSCT) from the Cancer Genome Atlas (TCGA) database. We found that some Wnt and Fzd genes had significant positive correlations. The expression levels of Fzd gene family were independent of survival in AML patients. In the chemotherapy group, AML patients with high Wnt2B or Wnt11 expression had significantly shorter event-free survival (EFS) and overall survival (OS); high Wnt10A expressers had significantly longer OS than the low expressers (all P < .05), whereas, in the allo-HSCT group, the expression levels of Wnt gene family were independent of survival. We further found that high expression of Wnt10A and Wnt11 had independent prognostic value, and the patients with high Wnt10A and low Wnt11 expression had the longest EFS and OS in the chemotherapy group. Pathway enrichment analysis showed that genes related to Wnt10A, Wnt11 and Wnt 2B were mainly enriched in ‘cell morphogenesis involved in differentiation’, ‘haematopoietic cell lineage’, ‘platelet activation, signalling and aggregation’ and ‘mitochondrial RNA metabolic process’ signalling pathways. Our results indicate that high Wnt2B and Wnt11 expression predict poor prognosis, and high Wnt10A expression predicts favourable prognosis in AML, but their prognostic effects could be neutralized by allo-HSCT. Combined Wnt10A and Wnt11 may be a novel prognostic marker in AML.     

Overexpression miR-520a-3p inhibits acute myeloid leukemia progression via targeting MUC1

BackgroundAcute myeloid leukemia (AML) is one of the familiar malignant tumors in the hematological system. miR-520a-3p is reported to be involved in several cancers’ progression. However, miR-520a-3p role in AML remains unclear. In this study, we aimed to clarify the role and potential mechanism of miR-520a-3p in AML.MethodsCell viability, proliferation, cycle and apoptosis were detected by MTT assay, colony formation assay, flow cytometry, respectively. The levels of PNCA, Bcl-2, Cleaved caspase 3, Cleaved caspase 9 and β-catenin protein were detected by Western blot. Dual-luciferase reported assay was performed to detect the regulation between miR-520a-3p and MUC1. To verify the effect of miR-520a-3p on tumor proliferation in vivo, a non-homogenous transplant model of tumors was established.ResultsmiR-520a-3p expression was down-regulated, and MUC1 expression was up-regulated in AML patients. miR-520a-3p overexpression suppressed THP-1 cell proliferation, induced cell cycle G0/G1 inhibition and promoted apoptosis. miR-520a-3p targeted MUC1 and negatively regulated its expression. MUC1 knockdown inhibited THP-1 cell proliferation and promoted apoptosis. miR-520a-3p overexpression inhibited AML tumors growth.ConclusionOverexpression miR-520a-3p inhibited AML cell proliferation, and promoted apoptosis via inhibiting MUC1 expression and repressing Wnt/β-catenin pathway activation.     

Identification of Common Prognostic Gene Expression Signatures with Biological Meanings from Microarray Gene Expression Datasets

Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.     

FBXL6 depletion restrains clear cell renal cell carcinoma progression

BackgroundF-box proteins play important roles in cell cycle and tumorigenesis. However, its prognostic value and molecular function in clear cell renal cell carcinoma (ccRCC) remain unclear. In this study, we established a survival model to evaluate the prognosis of patients with ccRCC using the F-box gene signature and investigated the function of FBXL6 in ccRCC.MethodsComprehensive bioinformatics analyses were used to identify differentially expressed F-box and hub genes associated with ccRCC carcinogenesis. Based on the F-box gene signature, we constructed a risk model and nomogram to predict the overall survival (OS) of patients with ccRCC and assist clinicians in decision-making. Finally, we verified the function and underlying molecular mechanisms of FBXL6 in ccRCC using CCK-8 and EdU assays, flow cytometry, and subcutaneous xenografts.ResultsA risk model based on FBXO39, FBXL6, FBXO1, and FBXL16 was developed. In addition, we drew a nomogram based on the risk score and clinical features to assess the prognosis of patients with ccRCC. Subsequently, we identified FBXL6 as an independent prognostic marker that was highly expressed in ccRCC cell lines. In vivo and in vitro assays revealed that the depletion of FBXL6 inhibited cell proliferation and induced apoptosis. We also demonstrated that SP1 regulated the expression of FBXL6.ConclusionsFBXL6 was first identified as a diagnostic and prognostic marker in patients with ccRCC. Loss of FBXL6 attenuates proliferation and induces apoptosis in ccRCC cells. SP1 was also found to regulate the expression of FBXL6.     

Selenium and Glutathione Peroxidase Status in Adult Egyptian Patients with Acute Myeloid Leukemia

This study was undertaken to evaluate selenium (Se) and glutathione peroxidase (GPX) status in patients with newly diagnosed acute myeloid leukemia (AML) before and after induction therapy. Twenty-five patients with newly diagnosed AML and 15 healthy age- and sex-matched control subjects were included in this study. Serum Se level by the graphite furnace atomic absorption spectrometric technique and GPX activity by an adaptation of Beutler method was performed for the patients before and after receiving the induction therapy. Serum Se level was significantly lower in patients with AML versus control subjects (63.1?±?8.8 versus 77?±?8.8 µg/L before therapy with a P value <0.01 and 69?±?6.8 versus 77?±?8.8 µg/L after therapy with a P value <0.01).GPX activity was significantly lower in patients with AML versus control subjects (1.6?±?0.4 versus 3.4?±?0.7 µ/g protein pretreatment with a P value <0.01and 1.9?±?0.6 versus 3.4?±?0.7 µ/g protein post induction treatment with P value <0.01).Se level and GPX activity significantly increased in AML patients after treatment. Patients who accomplished complete remission after induction harbored significantly higher Se levels than resistant patients before and after treatment. There was no significant correlation between serum Se level and GPX activity. Decreased Se level and reduced GPX activity in AML patients support the association of carcinogenesis and subnormal Se states.     

Development and Validation of a Novel Platform-Independent Metastasis Signature in Human Breast Cancer

PurposeThe molecular drivers of metastasis in breast cancer are not well understood. Therefore, we sought to identify the biological processes underlying distant progression and define a prognostic signature for metastatic potential in breast cancer.ResultsWe identified a broad range of metastatic potential that was independent of intrinsic breast cancer subtypes. 146 genes were significantly associated with metastasis progression and were linked to cancer-related biological functions, including cell migration/adhesion, Jak-STAT, TGF-beta, and Wnt signaling. These genes were used to develop a platform-independent gene expression signature (M-Sig), which was trained and subsequently validated on 5 independent cohorts totaling nearly 1800 breast cancer patients with all p-values < 0.005 and hazard ratios ranging from approximately 2.5 to 3. On multivariate analysis accounting for standard clinicopathologic prognostic variables, M-Sig remained the strongest prognostic factor for metastatic progression, with p-values < 0.001 and hazard ratios > 2 in three different cohorts.ConclusionM-Sig is strongly prognostic for metastatic progression, and may provide clinical utility in combination with treatment prediction tools to better guide patient care. In addition, the platform-independent nature of the signature makes it an excellent research tool as it can be directly applied onto existing, and future, datasets.     

Identification of a four immune-related genes signature based on an immunogenomic landscape analysis of clear cell renal cell carcinoma

Renal clear cell carcinoma (ccRCC) is the most common type of renal cell carcinoma, which has strong immunogenicity. A comprehensive study of the role of immune-related genes (IRGs) in ccRCC is of great significance in finding ccRCC treatment targets and improving patient prognosis. In this study, we comprehensively analyzed the expression of IRGs in ccRCC based on The Cancer Genome Atlas datasets. The mechanism of differentially expressed IRGs in ccRCC was analyzed by bioinformatics. In addition, Cox regression analysis was used to screen prognostic related IRGs from differentially expressed IRGs. We also identified a four IRGs signature consisting of four IRGs (CXCL2, SEMA3G, PDGFD, and UCN) through lasso regression and multivariate Cox regression analysis. Further analysis results showed that the four IRGs signature could effectively predict the prognosis of patients with ccRCC, and its predictive power is independent of other clinical factors. In addition, the correlation analysis of immune cell infiltration showed that this four IRGs signature could effectively reflect the level of immune cell infiltration of ccRCC. We also found that the expression of immune checkpoint genes CTLA-4, LAG3, and PD-1 in the high-risk group was higher than that in the low-risk group. Our research revealed the role of IRGs in ccRCC, and developed a four IRGs signature that could be used to evaluate the prognosis of patients with ccRCC, which will help to develop personalized treatment strategies for patients with ccRCC and improve their prognosis. In addition, these four IRGs may be effective therapeutic targets for ccRCC.     

血清miR-203、miR-217表达与急性髓系白血病患者预后的关系

摘要 目的：探究血清miR-203、miR-217表达与急性髓系白血病(AML)患者预后的关系。方法：选择2010年4月至2014年4月我院诊治的101例AML患者作为AML组,AML组根据治疗效果进一步分为完全缓解组和复发组,选择同期在我院体检的101例健康者作为健康组。采用荧光定量PCR检测各组的血清miR-203、miR-217表达水平,分析血清miR-203、miR-217表达水平与患者临床病理特征的关系,采用Kaplan-Meier法分析不同血清miR-203、miR-217表达水平AML患者的预后。结果：与健康组相比,AML组的血清miR-203、miR-217表达水平明显更低（P<0.05）。与完全缓解组相比,复发组的血清miR-203、miR-217表达水平明显更低（P<0.05）。血清miR-203表达水平与AML患者白细胞计数相关（P<0.05）,而血清miR-217表达水平与AML患者血小板计数相关（P<0.05）。血清miR-203相对高表达和miR-217相对高表达的AML患者5年生存率分别高于血清miR-203相对低表达和miR-217相对低表达患者（Log Rank ^miR-203 =17.870,Log Rank ^miR-217 =28.926,均P=0.000）。结论：血清miR-203、miR-217的表达水平与AML密切相关,检测血清miR-203、miR-217表达水平可能有助于评估AML患者的预后。