A novel aging-associated lncRNA signature for predicting prognosis in osteosarcoma.

Osteosarcoma (OS) is one of the most prevalent bone tumors in adolescents, and the correlation between aging and OS remains unclear. Currently, few accurate and reliable biomarkers have been determined for OS prognosis. To address this issue, we carried out a detailed bioinformatics analysis based on OS with data from the Cancer Genome Atlas data portal and Human Aging Genomic Resources database, as well as in vitro experiments. A total of 88 OS samples with gene expression profiles and corresponding clinical characteristics were obtained. Through univariate Cox regression analysis and survival analysis, 10 aging-associated survival lncRNAs (AASRs) were identified to be associated with the overall survival of OS patients. Based on the expression levels of the 10 AASRs, the OS patients were classified into two clusters (Cluster A and Cluster B). Cluster A had a worse prognosis, while Cluster B had a better prognosis. Then, 5 AASRs were ultimately included in the signature through least absolute shrinkage and selection operator-Cox regression analysis. Kaplan‒Meier survival analysis verified that the high-risk group exhibited a worse prognosis than the low-risk group. Furthermore, univariate and multivariate Cox regression analyses confirmed that the riskScore was an independent prognostic factor for OS patients. Subsequently, we discovered that the risk signature was correlated with the properties of the tumor microenvironment and immune cell infiltration. Specifically, there was a positive association between the risk model and naïve B cells, resting dendritic cells and gamma delta T cells, while it was negatively related to CD8+ T cells. Finally, in vitro experiments, we found that UNC5B-AS1 inhibited OS cells from undergoing cellular senescence and apoptosis, thereby promoting OS cells proliferation. In conclusion, we constructed and verified a 5 AASR-based signature, that exhibited excellent performance in evaluating the overall survival of OS patients. In addition, we found that UNC5B-AS1 might inhibit the senescence process, thus leading to the development and progression of OS. Our findings may provide novel insights into the treatment of OS patients.

The prognostic value and response to immunotherapy of immunogenic cell death-associated genes in breast cancer.

Breast cancer (BRCA) remains the most prevalent cancer worldwide and the tumor microenvironment (TME) has been discovered to exert a wide influence on the overall survival and therapeutic response. Numerous lines of evidence reported that the effects of immunotherapy of BRCA were manipulated by TME. Immunogenic cell death (ICD) is a form of regulated cell death (RCD) that is capable of fueling adaptive immune responses and aberrant expression of ICD-related genes (ICDRGs) can govern the TME system by emitting danger signals or damage-associated molecular patterns (DAMPs). In the current study, we obtained 34 key ICDRGs in BRCA. Subsequently, using the transcriptome data of BRCA from the TCGA database, we constructed a risk signature based on 6 vital ICDRGs, which had a good performance in predicting the overall survival of BRCA patients. We also examined the efficacy of our risk signature in the validation dataset (GSE20711) in the GEO database and it performed excellently. According to the risk model, patients with BRCA were divided into high-risk and low-risk groups. Also, the unique immune characteristics and TME between the two subgroups and 10 promising small molecule drugs targeting BRCA patients with different ICDRGs risk have been investigated. The low-risk group had good immunity indicated by T cell infiltration and high immune checkpoint expression. Moreover, the BRCA samples could be divided into three immune subtypes according to immune response severity (ISA, ISB, and ISC). ISA and ISB predominated in the low-risk group and patients in the low-risk group exhibited a more vigorous immune response. In conclusion, we developed an ICDRGs-based risk signature that can predict the prognosis of BRCA patients and offer a novel therapeutic strategy for immunotherapy, which would be of great significance in the BRCA clinical setting.

Norepinephrine inhibits CD8+ T-cell infiltration and function, inducing anti-PD-1 mAb resistance in lung adenocarcinoma.

BACKGROUND: Mental stress-induced neurotransmitters can affect the immune system in various ways. Therefore, a better understanding of the role of neurotransmitters in the tumour immune microenvironment is expected to promote the development of novel anti-tumour therapies. METHODS: In this study, we analysed the plasma levels of neurotransmitters in anti-programmed cell death protein 1 (PD-1) monoclonal antibody (mAb)-resistance patients and sensitive patients, to identify significantly different neurotransmitters. Subsequently, animal experiments and experiments in vitro were used to reveal the specific mechanism of norepinephrine's (NE) effect on immunotherapy. RESULTS: The plasma NE levels were higher in anti-PD-1 mAb-resistance patients, which may be the main cause of anti-PD-1 mAb resistance. Then, from the perspective of the immunosuppressive microenvironment to explore the specific mechanism of NE-induced anti-PD-1 mAb resistance, we found that NE can affect the secretion of C-X-C Motif Chemokine Ligand 9 (CXCL9) and adenosine (ADO) in tumour cells, thereby inhibiting chemotaxis and function of CD8+ T cells. Notably, the WNT7A/ß-catenin signalling pathway plays a crucial role in this progression. CONCLUSION: NE can affect the secretion of CXCL9 and ADO in tumour cells, thereby inhibiting chemotaxis and the function of CD8+ T cells and inducing anti-PD-1 mAb resistance in lung adenocarcinoma (LUAD).

Multi-scale information fusion network with label smoothing strategy for corneal ulcer classification in slit lamp images.

Corneal ulcer is the most common symptom of corneal disease, which is one of the main causes of corneal blindness. The accurate classification of corneal ulcer has important clinical importance for the diagnosis and treatment of the disease. To achieve this, we propose a deep learning method based on multi-scale information fusion and label smoothing strategy. Firstly, the proposed method utilizes the densely connected network (DenseNet121) as backbone for feature extraction. Secondly, to fully integrate the shallow local information and the deep global information and improve the classification accuracy, we develop a multi-scale information fusion network (MIF-Net), which uses multi-scale information for joint learning. Finally, to reduce the influence of the inter-class similarity and intra-class diversity on the feature representation, the learning strategy of label smoothing is introduced. Compared with other state-of-the-art classification networks, the proposed MIF-Net with label smoothing achieves high classification performance, which reaches 87.07 and 83.84% for weighted-average recall (W_R) on the general ulcer pattern and specific ulcer pattern, respectively. The proposed method holds promise for corneal ulcer classification in fluorescein staining slit lamp images, which can assist ophthalmologists in the objective and accurate diagnosis of corneal ulcer.

The Role of Ferroptosis-Related Molecules and Significance of Ferroptosis Score in Cervical Cancer.

Background: Ferroptosis, a form of cell death driven by iron-dependent lipid peroxidation, may be a potential treatment for many cancers, including cervical cancer (CC). However, the regulation of long noncoding RNAs (lncRNAs) in the process of ferroptosis and whether ferroptosis inducers could increase the cytotoxicity of conventional chemotherapy drugs remain to be further elucidated. Methods: We analyzed the variation of 55 differentially ferroptosis-related genes (FRGs) and the influence of mutations in CC patients. The patients with CC were classified into two ferroptosis clusters by the non-negative matrix factorization (NMF) algorithm. The principal components analysis (PCA) was used to measure the ferroptosis score (FerroScore) in patients with CC. Besides, FerroScore was used to predict the sensitivity of chemotherapy and responses to immunotherapy in patients with CC. Finally, experiments were performed to verify the regulatory effect of AC026790.1 on erastin-induced ferroptosis, as well as the effect of erastin in combination with cisplatin on the toxicity of CC cells (SiHa, HeLa). Result: There were significant differences in the overall survival and immune cell infiltration between the two ferroptosis clusters. Patients with low FerroScore were more sensitive to chemotherapy drugs such as cisplatin and docetaxel. The low-FerroScore group had higher CD8+ T cell infiltration and immune checkpoint expression, demonstrating that patients with lower FerroScores were more sensitive to immunotherapy, which was consistent with the result of the submap method. In vitro, overexpression of AC026790.1 could promote erastin-induced ferroptosis, and the combination of erastin and cisplatin could increase the toxicity of CC cells. Conclusion: FerroScore has a potential prognostic value for CC that may provide a reference for chemotherapy and immunotherapy. LncRNA AC026790.1 can influence ferroptosis, and the combination of ferroptosis inducers and chemotherapy drugs can provide a new perspective on cancer treatment.

Identification and validation of immunotherapy for four novel clusters of colorectal cancer based on the tumor microenvironment.

The incidence and mortality of colorectal cancer (CRC) are increasing year by year. The accurate classification of CRC can realize the purpose of personalized and precise treatment for patients. The tumor microenvironment (TME) plays an important role in the malignant progression and immunotherapy of CRC. An in-depth understanding of the clusters based on the TME is of great significance for the discovery of new therapeutic targets for CRC. We extracted data on CRC, including gene expression profile, DNA methylation array, somatic mutations, clinicopathological information, and copy number variation (CNV), from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) (four datasets-GSE14333, GSE17538, GSE38832, and GSE39582), cBioPortal, and FireBrowse. The MCPcounter was utilized to quantify the abundance of 10 TME cells for CRC samples. Cluster repetitive analysis was based on the Hcluster function of the Pheatmap package in R. The ESTIMATE package was applied to compute immune and stromal scores for CRC patients. PCA analysis was used to remove batch effects among different datasets and transform genome-wide DNA methylation profiling into methylation of tumor-infiltrating lymphocyte (MeTIL). We evaluated the mutation differences of the clusters using MOVICS, DeconstructSigs, and GISTIC packages. As for therapy, TIDE and SubMap analyses were carried out to forecast the immunotherapy response of the clusters, and chemotherapeutic sensibility was estimated based on the pRRophetic package. All results were verified in the TCGA and GEO data. Four immune clusters (ImmClust-CS1, ImmClust-CS2, ImmClust-CS3, and ImmClust-CS4) were identified for CRC. The four ImmClusts exhibited distinct TME compositions, cancer-associated fibroblasts (CAFs), functional orientation, and immune checkpoints. The highest immune, stromal, and MeTIL scores were observed in CS2, in contrast to the lowest scores in CS4. CS1 may respond to immunotherapy, while CS2 may respond to immunotherapy after anti-CAFs. Among the four ImmClusts, the top 15 markers with the highest mutation frequency were acquired, and CS1 had significantly lower CNA on the focal level than other subtypes. In addition, CS1 and CS2 patients had more stable chromosomes than CS3 and CS4. The most sensitive chemotherapeutic agents in these four ImmClusts were also found. IHC results revealed that CD29 stained significantly darker in the cancer samples, indicating that their CD29 was highly expressed in colon cancer. This work revealed the novel clusters based on TME for CRC, which would guide in predicting the prognosis, biological features, and appropriate treatment for patients with CRC.

Immune Infiltration-Related ceRNA Network Revealing Potential Biomarkers for Prognosis of Head and Neck Squamous Cell Carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC. Materials and Methods: ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed. Results: Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress. Conclusion: In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

FABP6 Expression Correlates with Immune Infiltration and Immunogenicity in Colorectal Cancer Cells.

Background: Immune checkpoint inhibitors (ICIs) have rapidly revolutionized colorectal cancer (CRC) treatment, but resistance caused by the heterogeneous tumor microenvironment (TME) still presents a challenge. Therefore, it is necessary to characterize TME immune infiltration and explore new targets to improve immunotherapy. Methods: The compositions of 64 types of infiltrating immune cells and their relationships with CRC patient clinical characteristics were assessed. Differentially expressed genes (DEGs) between "hot" and "cold" tumors were used for functional analysis. A prediction model was constructed to explore the survival of CRC patients treated with and without immunotherapy. Finally, fatty acid-binding protein (FABP6) was selected for in vitro experiments, which revealed its roles in the proliferation, apoptosis, migration, and immunogenicity of CRC tissues and cell lines. Results: The infiltration levels of several immune cells were associated with CRC tumor stage and prognosis. Different cell types showed the synergistic or antagonism infiltration patterns. Enrichment analysis of DEGs revealed that immune-related signaling was significantly activated in hot tumors, while metabolic process pathways were altered in cold tumors. In addition, the constructed model effectively predicted the survival of CRC patients treated with and without immunotherapy. FABP6 knockdown did not significantly alter tumor cell proliferation, apoptosis, and migration. FABP6 was negatively correlated with immune infiltration, and knockdown of FABP6 increased major histocompatibility complex (MHC) class 1 expression and promoted immune-related chemokine secretion, indicating the immunogenicity enhancement of tumor cells. Finally, knockdown of FABP6 could promote the recruitment of CD8+ T cells. Conclusion: Collectively, we described the landscape of immune infiltration in CRC and identified FABP6 as a potential immunotherapeutic target for treatment.

Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma.

Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of "competing endogenous RNAs (ceRNA)" network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis "MIAT/miR-532-3p/STC1" was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.

Comprehensive Characterization of the Function of Metabolic Genes and Establishment of a Prediction Model in Breast Cancer.

Background: Breast cancer (BC) is a highly heterogeneous disease with high morbidity and mortality. Its subtypes may have distinctly different biological behaviors, clinical outcomes, and therapeutic responses. The metabolic status of BC tissue is closely related to its progress. Therefore, we comprehensively characterized the function of metabolic genes in BC and identified new biomarkers to predict BC patients' prognoses. Methods: Metabolic genes were identified by intersecting genes obtained from two published pieces of literature. The function of metabolic genes in BC was determined by extracting differentially expressed genes (DEGs), performing functional enrichment analyses, analyzing the infiltrating proportion of immune cells, and conducting metabolic subgroup analyses. A risk score model was constructed to assess the prognoses of BC patients by performing the univariate Cox regression, LASSO algorithm, multivariate Cox regression, Kaplan-Meier survival analyses, and ROC curve analyses in the training set. The prognostic model was then validated on the testing dataset, external dataset, the whole TCGA-BC database, and our clinical specimens. Finally, a nomogram was constructed for clinical prognostic prediction based on the risk score model and other clinicopathological parameters. Results: 955 metabolic genes were obtained. Among these, 157 metabolic DEGs were identified between BC and normal tissues for subsequent GO and KEGG pathway enrichment analyses. 5 metabolic genes were negatively correlated with CD8+ T cells, while 49 genes were positively correlated with CD8+ T cells. Furthermore, 5 metabolic subgroups with varying proportions of PAM50 subtypes, TNM classification, and immune cell infiltration were obtained. Finally, a risk score model was constructed to predict the prognoses of BC patients, and a nomogram incorporating the risk score model was established for clinical application. Conclusion: In this study, we elucidated tumor heterogeneity from metabolite profiling of BC. The roles of metabolic genes in the occurrence of BC were comprehensively characterized, clarifying the relationship between the tumor microenvironment (TME) and metabolic genes. Meanwhile, a concise prediction model was also constructed based on metabolic genes, providing a convenient and precise method for the individualized diagnosis and treatment of BC patients.

ATAD2 drives colorectal cancer progression by regulating TRIM25 expression via a positive feedback loop with E2F transcriptional factors.

ATPase family AAA domain-containing protein 2 (ATAD2) is highly expressed in a variety of cancer types, and acts as a co-activator of androgen and estrogen receptors, as well as MYC and E2F transcription factors, to promote tumor cell proliferation. However, the regulation of ATAD2 and its related mechanisms are still elusive. Here, we show that ATAD2 protein was stabilized during DNA damage response in colorectal cancer (CRC) cells. TRIM25, an oncogenic ubiquitin E3 ligase, can interact with ATAD2 and stabilize ATAD2 upon genotoxic insult. We further demonstrated that ATAD2 played a tumor promoting role in CRC and acted as a transcriptional co-activator of E2Fs to promote the expression of TRIM25. Thus, our results revealed an unknown ATAD2-E2Fs-TRIM25 positive feedback loop that drove CRC progression.

Constructing a Novel Signature Based on Immune-Related lncRNA to Improve Prognosis Prediction of Cervical Squamous Cell Carcinoma Patients.

We downloaded gene expression data, clinical data, and somatic mutation data of cervical squamous cell carcinoma (CSCC) patients from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Predictive lncRNAs were screened using univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and risk scores were calculated for each patient according to the expression levels of lncRNAs and regression coefficients to establish a risk model that could be a novel signature. We assessed the correlation between immune infiltration status, chemotherapeutics sensitivity, immune checkpoint proteins (ICP), and the signature. Therefore, we selected 11 immune-related lncRNAs (WWC2,AS2, STXBP5.AS1, ERICH6.AS1, USP30.AS1, LINC02073, RBAKDN, IL21R.AS1, LINC02078, DLEU1, LINC00426, BOLA3.AS1) to construct the risk model. Patients who were in the high-risk group had a shorter survival time than those in the low-risk group (p < 0.001). Risk scores in the signature were negatively correlated with macrophage M1, macrophage M2, and T cell CD8 + ; what's more, T cell CD8 + was higher in the low-risk group. The expression levels of ICP such as PD-L1, PD-1, CTLA-4, TIGIT, LAG-3, and TIM-3 were substantially higher in the low-risk group. For chemotherapeutic agents, high-risk scores were associated with higher half-inhibitory concentrations (IC50) of cisplatin. These findings suggested that the risk model can be a novel signature for predicting CSCC patients' prognosis, and it also can be used to formulate clinical treatment plans for CSCC patients.

Integrated analysis of key microRNAs /TFs /mRNAs/ in HPV-positive cervical cancer based on microRNA sequencing and bioinformatics analysis.

BACKGROUND: Cervical squamous cell carcinoma (CESC) is one of the most common malignancies associated with mortality in females. Its onset and prognosis are primarily concerned with persistent infection with high-risk types of human papillomavirus (HPV). However, the molecular mechanisms of HPV-positive CESC remain unclear. METHODS: In this study, we conducted a high-throughput sequencing to identify differentially expressed miRNAs (DEMs). Besides, three series were selected from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Then the miRNA-TF-gene regulatory network was constructed using bioinformatic methods. Genes in the network were performed functional enrichment analysis and protein-protein interaction (PPI) network analysis. Ultimately, the expression levels of six key miRNAs, TFs, and mRNAs were validated by 20 HPV-positive CESC tissues and 15 normal cervical samples. RESULTS: A total of 52 DEMs and 300 DEGs differed between the HPV-positive CESC and normal cervical samples. Then the miRNA-TF-gene regulatory network was constructed consisting of 22 miRNAs, 6 TFs, and 76 corresponding genes, among which miR-149-5p, miRNA-1248 and E2F4 acted as key regulators. PPI network analysis showed that ten genes including TOP2A, AURKA, CHEK1, KIF11, MCM4, MKI67, DTL, FOXM1, SMC4, and FBXO5 were recognized as hub genes with the highest connectivity degrees. Besides, five key molecules miRNA-149-5p, E2F4, KIF11, DTL, and SMC4 were suggested to play crucial roles in the development of HPV-positive CESC. CONCLUSION: These results present a unique insight into the pathological mechanisms of HPV-positive CESC and possibly provides potential therapeutic targets.

Identification of novel biomarkers affecting the metastasis of colorectal cancer through bioinformatics analysis and validation through qRT-PCR.

BACKGROUND: Tumor progression and distant metastasis are the main causes of deaths in colorectal cancer (CRC) patients, and the molecular mechanisms in CRC metastasis have not been completely discovered. METHODS: We identified differentially expressed genes (DEGs) and lncRNAs (DELs) of CRC from The Cancer Genome Atlas (TCGA) database. Then we conducted the weighted gene co-expression network analysis (WGCNA) to investigate co-expression modules related with CRC metastasis. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, DEG-DEL co-expression network and survival analyses of significant modules were also conducted. Finally, the expressions of selected biomarkers were validated in cell lines by quantitative real-time PCR (qRT-PCR). RESULTS: 2032 DEGs and 487 DELs were involved the construction of WGCNA network, and greenyellow, turquoise and brown module were identified to have more significant correlation with CRC metastasis. GO and KEGG pathway analysis of these three modules have proven that the functions of DEGs were closely involved in many important processes in cancer pathogenesis. Through the DEG-DEL co-expression network, 12 DEGs and 2 DELs were considered as hub nodes. Besides, survival analysis showed that 30 DEGs were associated with the overall survival of CRC. Then 10 candidate biomarkers were chosen for validation and the expression of CA2, CHP2, SULT1B1, MOGAT2 and C1orf115 were significantly decreased in CRC cell lines when compared to normal human colonic epithelial cells, which were consistent with the results of differential expression analysis. Especially, low expression of SULT1B1, MOGAT2 and C1orf115 were closely correlated with poorer survival of CRC. CONCLUSION: This study identified 5 genes as new biomarkers affecting the metastasis of CRC. Besides, SULT1B1, MOGAT2 and C1orf115 might be implicated in the prognosis of CRC patients.

LRP1B Polymorphisms Are Associated with Multiple Myeloma Risk in a Chinese Han Population.

Multiple myeloma (MM) is an extremely complex plasma cell malignancy that is genetically heterogeneous. A recent Genome-wide association study (GWAS) indicated that variation at 2q22 (rs61070260) influences MM risk. This association has not been validated to date in a Chinese Han population. In this study, we evaluated the association between rs61070260 in LRP1B and MM risk in a Chinese Han population involving 739 MM patients and 592 healthy controls. Our results indicated that rs61070260 in LRP1B was significantly associated with MM susceptibility (P=3.937×10-37). Furthermore, the linkage disequilibrium (LD) analysis of rs61070260 revealed an LD block encompassing exons 26, 27 and 28 of the LRP1B gene, and a subsequent sequencing analysis identified three SNPs (rs762074421, rs756168629, rs113600691) in exons 26 and 28 of LRP1B. For the SNP rs756168629 in exon 26, a missense mutation which results in a transition from arginine to histidine at position 1661 of the LRP1B protein, has not been found in Chinese populations according to the Chinese Millionome Database and Genome Aggregation Database (EAS), and this mutation was predicted to be deleterious or damaging by SIFT and PolyPhen. These findings firmly establish the role of LRP1B in contributing to MM susceptibility. In addition, the identification of a rare coding mutation (p.R1661H) in LRP1B detected in MM individuals was suggested to be harmful to the encoded protein, which was characterized as a candidate tumour suppressor; thus, LRP1B is likely to be a disease-associated gene that is implicated in the development and progression of MM.

Integrated analysis of dysregulated long non-coding RNAs/microRNAs/mRNAs in metastasis of lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD), largely remains a primary cause of cancer-related death worldwide. The molecular mechanisms in LUAD metastasis have not been completely uncovered. METHODS: In this study, we identified differentially expressed genes (DEGs), miRNAs (DEMs) and lncRNAs (DELs) underlying metastasis of LUAD from The Cancer Genome Atlas database. Intersection mRNAs were used to perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and co-expression network analysis. In addition, survival analyses of intersection mRNAs were conducted. Finally, intersection mRNAs, miRNAs and lncRNAs were subjected to construct miRNA-mRNA-lncRNA network. RESULTS: A total of 1015 DEGs, 54 DEMs and 22 DELs were identified in LUAD metastasis and non-metastasis samples. GO and KEGG pathway analysis had proven that the functions of intersection mRNAs were closely related with many important processes in cancer pathogenesis. Among the co-expression interactions network, 22 genes in the co-expression network were over the degree 20. These genes imply that they have connections with many other gene nodes. In addition, 14 target genes (ARHGAP11A, ASPM, HELLS, PRC1, TMPO, ARHGAP30, CD52, IL16, IRF8, P2RY13, PRKCB, PTPRC, SASH3 and TRAF3IP3) were found to be associated with survival in patients with LUAD significantly (log-rank P < 0.05). Two lncRNAs (LOC96610 and ADAM6) acting as ceRNAs were identified based on the miRNA-mRNA-lncRNA network. CONCLUSIONS: Taken together, the results may provide a novel perspective to develop a multiple gene diagnostic tool for LUAD prognosis, which might also provide potential biomarkers or therapeutic targets for LUAD.

ERCC1 rs11615 polymorphism increases susceptibility to breast cancer: a meta-analysis of 4547 individuals.

Excision repair cross-complementation group 1 (ERCC1), a DNA repair protein, is vital for maintaining genomic fidelity and integrity. Despite the fact that a mounting body of case-control studies has concentrated on investigating the association of the ERCC1 rs11615 polymorphism and breast cancer risk, there is still no consensus on it. We conducted the current meta-analysis of all eligible articles to reach a much more explicit conclusion on this ambiguous association. A total of seven studies involving 2354 breast cancer cases and 2193 controls were elaborately selected for this analysis from the Embase, EBSCO, PubMed, WanFang, and China National Knowledge Infrastructure (CNKI) databases. Pooled odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated in our meta-analysis. We found that the ERCC1 rs11615 polymorphism was significantly associated with breast cancer risk under all genetic models. When excluded, the studies that deviated from Hardy-Weinberg equilibrium (HWE), the pooled results of what remained significantly increase the risk of breast cancer under the allele model (OR = 1.14, 95% CI = 1.02-1.27, P=0.02), heterozygote model (OR = 1.24, 95% CI = 1.06-1.44, P=0.007), and dominant model (OR = 1.21, 95% CI = 1.05-1.41, P=0.01). This increased breast cancer risk was found in Asian population as well as under the heterozygote model (OR = 1.24, 95% CI = 1.05-1.48, P=0.013) and dominant model (OR = 1.20, 95% CI = 1.02-1.42, P=0.03). Our results suggest that the ERCC1 rs11615 polymorphism is associated with breast cancer susceptibility, and in particular, this increased risk of breast cancer existence in Asian population.

Association between NME1 polymorphisms and cancer susceptibility: A meta-analysis based on 1644 cases and 2038 controls.

The association between polymorphisms in the nucleoside diphosphate kinase 1 (NME1) gene and overall risk of cancer remains to be elucidated. Here, we performed a meta-analysis of the association between rs16949649, rs2302254, and rs34214448 polymorphisms in the NME1 gene and cancer risk. PubMed, Web of Science, and CNKI databases (as of June 6, 2017) were searched. Eight studies, encompassing 1644 cases and 2038 controls, were selected. The results revealed no significant relationship between NME1 polymorphisms and overall cancer susceptibility. Interestingly, the rs16949649 polymorphism was associated with increased susceptibility to gynecological cancer (heterozygous model: odds ratio [OR] = 1.74, 95% confidence interval [CI] = 1.06-2.86, P = 0.029). The rs2302254 polymorphism was linked to decreased susceptibility to gastric cancer in the other groups (recessive model: OR = 0.53, 95% CI = 0.28-0.98, P = 0.045). The rs34214448 polymorphism correlated significantly with increased susceptibility to non-small cell lung cancer according to all genetic models (P < 0.05) and was linked to decreased risk in cervical cancer (recessive model: OR = 0.51, 95% CI = 0.27-0.94, P = 0.031). Thus, our meta-analysis found rs16949649 associated with increased susceptibility to gynecological cancer and rs2302254 was linked to reduced gastric cancer risk; additional, larger studies are required to confirm these findings.

NOTCH4 is a possible novel susceptibility gene for dilated cardiomyopathy in the Chinese population: A case-control study.

BACKGROUND: The incidence of dilated cardiomyopathy (DCM) has increased in recent years, and many studies have sought to further improve the general understanding of this condition. Previous studies have demonstrated that some single nucleotide polymorphisms (SNPs) associated with systemic lupus erythematosus also affect susceptibility to DCM, suggesting that immune-related diseases may share similar genetic susceptibility. Recent large-scale and genome-wide association studies have identified NCR3, NOTCH4, CYP1A2, ITGA1, OPRM1, ST8SIA2, and LINC00704 as genetic risk factors associated with cardiac manifestations of neonatal lupus. Here, we aimed to determine whether these SNPs conferred susceptibility to DCM in the Chinese Han population. METHODS: We investigated the relationship between these polymorphisms and DCM risk in 273 patients with DCM and 548 healthy controls. Genotyping was performed using MassArray iPLEX system. RESULTS: Logistic regression analysis indicated that the T allele of rs3134942 in NOTCH4 gene increased the risk of DCM by 61% compared with the G allele (Pa  = 6.57 × 10-3 ). The SNP rs3134942 was also significantly associated with increased DCM risk in the additive (Pa  = 6.57 × 10-3 ) and dominant models (Pa  = 1.01 × 10-2 ). Additionally, rs2472299 in CYP1A2 gene showed suggestive association with reduced risk of DCM in the dominant model (Pa  = 4.24 × 10-2 ) and was correlated with smoking status in patients with DCM (Pa  = 1.56 × 10-2 ). CONCLUSIONS: Our findings suggested that rs3134942 in NOTCH4 may be involved in DCM risk. Further, studies in larger and ethnically diverse populations are required to confirm the results reported in this study.