Upregulation of HOXA11 during the progression of lung adenocarcinoma detected via multiple approaches

Clinicopathologic and prognostic implications of HOXA gene and its associated long-noncoding RNAs expression in non-small cell carcinoma: A meta-analysis

BACKGROUND

We conducted an investigation into the correlation between HOXA and associated long-noncoding RNAs, along with their clinicopathologic and prognostic features in non-small cell lung cancer (NSCLC).

METHODS

A comprehensive search across multiple electronic databases, including PubMed and the Web of Science, was conducted to identify relevant studies. The association between HOXA, clinicopathologic parameters, and prognosis was assessed using relative risk (RR) and hazard ratio (HR) with a 95% confidence interval (CI). Data compilation was performed using STATA 12.0 software.

RESULTS

A total of 11 trials involving 2058 patients with NSCLC were included in our study. Significant correlations were observed between HOXA-AS2 and TNM stage (III-IV) (RR=2.173, 95% CI: 1.386-5.437, P< 0.05) and HOTTIP and age (≥60-year-old) (RR=2.628, 95% CI: 1.185-5.829, P< 0.05) and non-smoking (RR=0.387, 95% CI: 0.156-0.959, P< 0.05). The combined results indicated a significant association between HOXA5 and increased overall survival (HR = 0.69, 95% CI = 0.57-0.84, P < .001). Additionally, HOXA-AS2, HOXA11 and HOTTIP were identified as potential independent predictors for poorer OS (HOXA-AS2: HR =3.48, 95% CI = 1.95 to 6.21, P < 0.05; HOXA11: HR=1.39, 95%CI = 1.08 to 1.79, P < 0.05; HOTTIP: HR=2.44, 95%CI = 1.10 to 5.42, P < 0.05). The prognostic significance of HOXA1, HOXA3 and HOXA4 was uncertain (HOXA1: HR=1.40, 95% CI =0.28 to 7.06, P > 0.05; HOXA3: HR=1.20, 95% CI = 0.96 to 1.50, P > 0.05; HOXA4: HR=0.97, 95% CI = 0.77 to 1.23, P > 0.05).

CONCLUSIONS

The HOXA gene family has some potential to emerge as a novel prognostic factor for NSCLC and is correlated with some clinicopathological parameters such as the TNM stage, age and smoking. However, further meticulously designed prospective studies are warranted to substantiate these findings.

BTG2 and SerpinB5, a novel gene pair to evaluate the prognosis of lung adenocarcinoma

Introduction

Lung adenocarcinoma (LUAD), as the most frequent pathological subtype of non−small cell lung cancer, is often characterized by poor prognosis and low 5-year survival rate. Exploriton of new biomarkers and accurate molecular mechanisms for effectively predicting the prognosis of LUAD patients is still necessary. Presently, BTG2 and SerpinB5, which play important roles in tumors, are studied as a gene pair for the first time with the aim of exploring whether they can be used as potential prognostic markers.

Methods

Using the bioinformatics method to explore whether BTG2 and SerpinB5 can become independent prognostic factors, and explore their clinical application value and whether they can be used as immunotherapeutic markers. In addition, we also verify the conclusions obtained from external datasets, molecular docking, and SqRT-PCR.

Results

The results show that compared with normal lung tissue, BTG2 expression level was down-regulated and SerpinB5 was up-regulated in LUAD. Additionally, Kaplan–Meier survival analysis demonstrate that the prognosis of low expression level of BTG2 was poor, and that of high expression level of SerpinB5 was poor, suggesting that both of them can be used as independent prognostic factors. Moreover, the prognosis models of the two genes were constructed respectively in this study, and their prediction effect was verified by external data. Besides, ESTIMATE algorithm reveals the relationship between this gene pair and the immune microenvironment. Furthermore, patients with a high expression level of BTG2 and a low expression level of SerpinB5 have higher immunophenoscore for CTLA-4 and PD-1 inhibitors than patients with a low expression level of BTG2 and a high expression level of SerpinB5, indicating that such patients have a more obvious effect of immunotherapy.

Discussion

Collectively, all the results demonstrate that BTG2 and SerpinB5 might serve as potential prognostic biomarkers and novel therapeutic targets for LUAD.

Identifying a 6-Gene Prognostic Signature for Lung Adenocarcinoma Based on Copy Number Variation and Gene Expression Data

The occurrence of lung adenocarcinoma (LUAD) is a complicated process, involving the genetic and epigenetic changes of proto-oncogenes and oncogenes. The objective of this study was to establish new predictive signatures of lung adenocarcinoma based on copy number variations (CNVs) and gene expression data. Next-generation sequencing was implemented to obtain gene expression and CNV information. According to univariate, multivariate survival Cox regression analysis, and LASSO analysis, the expression profiles of lung adenocarcinoma patients were screened and a risk score formula was established and experimentally validated in a local cohort. The model was evaluated by three independent cohorts (TCGA-LUAD, GSE31210, and GSE30219), and then validated by clinical samples from LUAD patients. A total of 844 CNV-related differentially expressed genes (CNV-related DEGs) were identified. These genes are significantly associated with the imbalance of various oxidative stress pathways. A CNV-associated-six gene signature was dramatically linked to overall survival in lung adenocarcinoma samples from both training and validation groups. Functional enrichment analysis further revealed involvement of genes in p53 signaling pathway and cell cycle as well as the mismatch repair pathway. Risk score is an independent marker considering clinical parameters and had better prediction in clinical subpopulation. The same signature also classified tumor tissues of clinical patients with CNV detected from their corresponding nontumorous tissues with an accuracy of 0.92. In conclusion, we identified a new class of 6 CNV-related gene markers that may act as efficient prognostic predictors of lung adenocarcinoma, thus contributing to individualized treatment decisions in patients.

Expression Landscape and Functional Roles of HOXA4 and HOXA5 in Lung Adenocarcinoma

BACKGROUND

The role of HOXA family genes in the occurrence and progression of a variety of human cancers has been scatteredly reported. However, there is no systematic study on the differential expression, prognostic significance and potential molecular mechanism of HOXA4 and HOXA5 in LUAD.

METHODS

In-house immunohistochemistry (IHC), multi-center microarrays, RT-qPCR and RNA-seq data were incorporated for comprehensively evaluating the expression and prognostic value of HOXA4 and HOXA5 in LUAD. The mechanism of HOXA4 and HOXA5 in the formation and development of LUAD was analyzed from multiple aspects of immune correlations, upstream transcriptional regulation, functional states of single cells and co-expressed gene network. The functional roles of HOXA4 and HOXA5 in LUAD were validated by in vitro experiments.

RESULTS

As a result, in 3201 LUAD samples and 2494 non-cancer lung samples, HOXA4 and HOXA5 were significantly downexpressed (P < 0.05). The aberrant expression of HOXA5 was significantly correlated with the clinical progression of LUAD (P < 0.05). HOXA5 showed remarkable prognostic value for LUAD patients (P < 0.05). The expression of HOXA4 and HOXA5 in LUAD were negatively correlated with tumor purity and positively correlated with the infiltration of various immune cells such as B cells, T cells and macrophages. HOXA4 and HOXA5 overexpression had notable inhibitory effect on the proliferation, migration and invasion of LUAD cells.

CONCLUSIONS

In conclusion, the identified downexpressed HOXA4 and HOXA5 had significant distinguishing ability for LUAD samples and affected the cellular functions of LUAD cells. The low expression of HOXA5 indicated worse overall survival of LUAD patients. Therefore, the two HOXA family genes especially HOXA5 may serve as potential biomarkers for LUAD.

Downregulation of LINC00665 suppresses the progression of lung adenocarcinoma via regulating miR-181c-5p/ZIC2 axis

Long non-coding RNA (lncRNA) LINC00665 was demonstrated to be upregulated in lung adenocarcinoma (LUAD) and target miR-181c-5p. ZIC2, which is upregulated in LUAD, serves as a putative target of miR-181c-5p. In this study, we aimed to reveal whether LINC00665 regulates miR-181c-5p/ZIC2 axis to promote LUAD progression. The results showed that LINC00665, HOXA1, ZIC2, and HOXA11 levels were increased in LUAD tissues, while miR-181c-5p level was decreased when compared to the adjacent normal tissues. High expression levels of LINC00665, ZIC2, HOXA1 and HOXA11, and low expression of miR-181c-5p were closely linked to poor prognosis of LUAD patients. Knockdown of LINC00665 induced obvious inhibitions in cell viability, clone formation, invasion and tumorigenesis in LUAD cells, whereas miR-181c-5p downregulation significantly neutralized these effects. In addition, downregulation of ZIC2 obviously reversed the enhancements of cell viability, clone formation, invasion and tumorigenesis induced by miR-181c-5p knockdown. In summary, the present study reveals that silencing of LINC00665 suppresses LUAD progression through targeting miR-181c-5p/ZIC2 axis.

Expression Profile Analysis Identifies a Novel Seven Immune-Related Gene Signature to Improve Prognosis Prediction of Glioblastoma

Glioblastoma multiform (GBM) is a malignant central nervous system cancer with dismal prognosis despite conventional therapies. Scientists have great interest in using immunotherapy for treating GBM because it has shown remarkable potential in many solid tumors, including melanoma, non-small cell lung cancer, and renal cell carcinoma. The gene expression patterns, clinical data of GBM individuals from the Cancer Genome Atlas database (TCGA), and immune-related genes (IRGs) from ImmPort were used to identify differentially expressed IRGs through the Wilcoxon rank-sum test. The association between each IRG and overall survival (OS) of patients was investigated by the univariate Cox regression analysis. LASSO Cox regression assessment was conducted to explore the prognostic potential of the IRGs of GBM and construct a risk score formula. A Kaplan–Meier curve was created to estimate the prognostic role of IRGs. The efficiency of the model was examined according to the area under the receiver operating characteristic (ROC) curve. The TCGA internal dataset and two GEO external datasets were used for model verification. We evaluated IRG expression in GBM and generated a risk model to estimate the prognosis of GBM individuals with seven optimal prognostic expressed IRGs. A landscape of 22 types of tumor-infiltrating immune cells (TIICs) in glioblastoma was identified, and we investigated the link between the seven IRGs and the immune checkpoints. Furthermore, there was a correlation between the IRGs and the infiltration level in GBM. Our data suggested that the seven IRGs identified in this study are not only significant prognostic predictors in GBM patients but can also be utilized to investigate the developmental mechanisms of GBM and in the design of personalized treatments for them.

Polo like kinase 1 expression in cervical cancer tissues generated from multiple detection methods

Background

Existing studies of PLK1 in cervical cancer had several flaws. The methods adopted by those studies of detecting PLK1 expression in cervical cancer were single and there lacks comprehensive evaluation of the clinico-pathological significance of PLK1 in cervical cancer.

Methods

A total of 303 cervical tissue samples were collected for in-house tissue microarrays. Immunohistochemistry was performed for evaluating PLK1 expression between cervical cancer (including cervical squamous cell carcinoma (CESC) and cervical adenocarcinoma) and non-cancer samples. The Expression Atlas database was searched for querying PLK1 expression in different cervical cancer cell lines and different tissues in the context of pan-cancer. Standard mean difference (SMD) was calculated and the summarized receiver's operating characteristics (SROC) curves were plotted for integrated tissue microarrays, exterior high-throughput microarrays and RNA sequencing data as further verification. The effect of PLK1 expression on the overall survival, disease-free survival and event-free survival of cervical cancer patients was analyzed through Kaplan Meier survival curves for cervical cancer patients from RNA-seq and GSE44001 datasets. The gene mutation and alteration status of PLK1 in cervical cancer was inspected in COSMIC and cBioPortal databases. Functional enrichment analysis was performed for genes correlated with PLK1 from aggregated RNA-seq and microarrays.

Results

A total of 963 cervical cancer samples and 178 non-cancer samples were collected from in-house tissue microarrays and exterior microarrays and RNA-seq datasets. The combined expression analysis supported overexpression of PLK1 in CESC, cervical adenocarcinoma and all types of cervical cancer (SMD = 1.59, 95%CI [0.56-2.63]; SMD = 2.99, 95%CI [0.75-5.24]; SMD = 1.57, 95% CI [0.85-2.29]) and the significant power of PLK1 expression in distinguishing CESC or all types of cervical cancer samples from non-cancer samples (AUC = 0.94, AUC = 0.92). Kaplan-Meier survival curves showed that the event-free survival rate of cervical cancer patients with higher expression of PLK1 was shorter than that of patients with lower PLK1 (HR = 2.020, P = 0.0197). Genetic alteration of PLK1 including missense mutation and mRNA low occurred in 6% of cervical cancer samples profiled in mRNA expression. Genes positively or negatively correlated with PLK1 were mainly assembled in pathways such as DNA replication, cell cycle, mismatch repair, Ras signaling pathway, melanoma, EGFR tyrosine kinase inhibitor resistance and homologous recombination (P < 0.05).

Conclusions

Here, we provided sufficient evidence of PLK1 overexpression in cervical cancer. The overexpression of PLK1 in cervical cancer and the contributory effect of it on clinical progression indicated the hopeful prospect of PLK1 as a biomarker for cervical cancer.

Long non-coding RNA LINC01194 promotes the proliferation, migration and invasion of lung adenocarcinoma cells by targeting miR-641/SETD7 axis

Background

It is increasingly evidenced that long non-coding RNAs (lncRNAs) play an important role in various diseases. LncRNA LINC01194 acts as an oncogene in several cancer types. Nevertheless, the role of LINC01194 in lung adenocarcinoma (LUAD) has not yet been revealed.

Methods

qRT-PCR was used to detect the expression of LINC01194, miR-641 and SETD7 mRNA, while western blot was exploited to examine SETD7 protein level. Cell proliferation was detected by colony formation and EdU assays. Transwell assays detected cell migration and invasion. TUNEL assay and flow cytometry analysis were used to detect cell apoptosis. RIP, RNA pull down and luciferase reporter assays detected the binding among LINC01194, miR-641 and SETD7.

Results

LINC01194 was significantly upregulated in LUAD tissues and cell lines. Knockdown of LINC01194 resulted in decreased cell proliferation, migration and invasion, and increased apoptosis. Mechanistic experiments unveiled that LINC01194 augmented SETD7 expression in LUAD cells by competitively interacting with miR-641. Rescue experiments showed that miR-641 inhibition and SETD7 overexpression rescued the repressing impacts on LUAD cell proliferation, migration and invasion caused by LINC01194 knockdown.

Conclusion

LINC01194 promotes the progression of LUAD by enhancing miR-641-targeted SETD7. The LINC01194/miR-641/SETD7 axis might provide new molecular targets for treating LUAD.

Development and Validation of a Clinical Prognostic Model Based on Immune-Related Genes Expressed in Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is the most frequent and terminal subtype of RCC. Reliable markers associated with the immune response are not available to predict the prognosis of patients with ccRCC. We exploited the extensive number of ccRCC samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repository to perform a comprehensive analysis of immune-related genes (IRGs). Methods: Based on TCGA data, we incorporated IRGs and their expression profiles of 72 normal and 539 ccRCC samples. Univariate Cox analysis was used to evaluate the relationship between overall survival (OS) and IRGs expression. The Lasso Cox regression model identified prognostic genes used to establish a clinical immune prognostic model. The TF-IRG network was used to study the potential molecular mechanisms of action and properties of ccRCC-specific IRGs. Multivariate Cox analysis established a clinical prognostic model of IRGs. Results: We found a significant correlation among 15 differentially expressed IRGs with the OS of patients with ccRCC. Gene function enrichment analysis showed that these IRGs are significantly associated with response to receptor ligand activity. Lasso Cox regression analysis identified 10 genes with the greatest prognostic value. A clinical prognostic model based on six IRGs, which performed well for predicting prognosis, revealed significant associations of patients' survival with age, sex, stage, tumor, node, and metastasis. Moreover, these findings reflect the infiltration of tumors by various immune cells. Conclusion: We identified six clinically significant IRGs and incorporated them into a clinical prognostic model with great significance for monitoring and predicting prognosis of ccRCC.

Multi-omics Data Analyses Construct TME and Identify the Immune-Related Prognosis Signatures in Human LUAD

Lung cancer has been the focus of attention for many researchers in recent years for the leading contribution to cancer-related death worldwide, in which lung adenocarcinoma (LUAD) is the most common histological type. However, the potential mechanism behind LUAD initiation and progression remains unclear. Aiming to dissect the tumor microenvironment of LUAD and to discover more informative prognosis signatures, we investigated the immune-related differences in three types of genetic or epigenetic characteristics (expression status, somatic mutation, and DNA methylation) and considered the potential roles that these alterations have in the immune response and both the immune-related metabolic and neural systems by analyzing the multi-omics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct the prognostic prediction model. For the prognostic predictions on the independent test set, the performance of the trained models (average concordance index [C-index] = 0.839) is satisfied, with average 1-year, 3-year, and 5-year areas under the curve (AUCs) equal to 0.796, 0.786, and 0.777. Finally, the overall model was constructed based on all samples, which comprised 27 variables and achieved a high degree of accuracy on the 1-year (AUC = 0.861), 3-year (AUC = 0.850), and 5-year (AUC = 0.916) survival predictions.

Expression Profile and Prognostic Values of HOXA Family Members in Laryngeal Squamous Cell Cancer

The homeobox A cluster (HOXA) gene family, comprising 11 members, is involved in a wide spectrum of biological functions in human cancers. However, there is little research on the expression profile and prognostic values of HOXA genes in laryngeal squamous cell cancer (LSCC). Based on updated public resources and integrative bioinformatics analysis, we assessed the expression profile and prognostic values of the HOXA family members. Expression and methylation data on HOXA family members were obtained from The Cancer Genome Atlas (TCGA). The prognostic values of HOXA members and clinical features were identified. A gene set enrichment analysis (GSEA) was conducted to explore the mechanism underlying the involvement of HOXA members in LSCC. The associations between tumor immune infiltrating cells (TIICs) and the HOXA family members were evaluated using the Tumor Immune Estimation Resource (TIMER) database. HOXA2 and HOXA4 were downregulated and HOXA7 and HOXA9–13 were upregulated in LSCC. Upregulation of HOXA10, HOXA11, and HOXA13, along with two clinical characteristics (M stage and gender), were associated with a poor LSCC prognosis based on the results of univariate and multivariate Cox proportional hazards regression analyses. Although there were no significant correlations between TIICs and HOXA members, the GSEA results indicated that HOXA members participate in multiple biological processes underlying tumorigenesis. This study comprehensively analyzed the HOXA members, providing insights for further investigation of the HOXA family members as potential targets in LSCC.

A self-enforcing HOXA11/Stat3 feedback loop promotes stemness properties and peritoneal metastasis in gastric cancer cells

Rationale: Peritoneal metastasis is one of the most common and life-threatening metastases in gastric cancer patients. The disseminated gastric cancer cells forming peritoneal metastasis exhibit a variety of characteristics that contrast with those of adjacent epithelial cell of gastric mucosa and even primary gastric cancer cells. We hypothesized that the gene expression profiles of peritoneal foci could reveal the identities of genes that might function as metastatic activator.

Methods: In this study, we show, using in vitro, in vivo, in silico and gastric cancer tissues studies in humans and mice, that Homoebox A11 (HOXA11) potently promote peritoneal metastasis of gastric cancer cells.

Results: Its mechanism of action involves alternation of cancer stemness and subsequently enhancement of the adhesion, migration and invasion and anti-apoptosis. This is achieved, mainly, through formation of a positive feedback loop between HOXA11 and Stat3, which is involved in the stimulation of Stat3 signaling pathway.

Conclusions: These observations uncover a novel peritoneal metastatic activator and demonstrate the association between HOXA11, Stat3 and cancer stemness of gastric cancer cells, thereby revealing a previously undescribed mechanism of peritoneal metastasis.

Diagnostic and prognostic values of integrin α subfamily mRNA expression in colon adenocarcinoma

The integrin α (ITGA) subfamily genes play a fundamental role in various cancers. However, the potential mechanism and application values of ITGA genes in colon adenocarcinoma (COAD) remain elusive. The present study investigated the significance of the expression of ITGA genes in COAD from the perspective of diagnosis and prognosis. A COAD RNA-sequencing dataset was obtained from The Cancer Genome Atlas. The present study investigated the biological function of the ITGA subfamily genes through bioinformatics analysis. Reverse transcription-quantitative polymerase chain reaction was applied to investigate the distribution of integrin α8 (ITGA8) expression in COAD tumors and adjacent normal tissues. Bioinformatics analysis indicated that ITGA genes were noticeably enriched in cell adhesion and the integrin-mediated signaling pathway, and co-expressed with each other. It was also revealed through observation that the majority of gene expression was significantly low in tumor tissues (P<0.05), and diagnostic receiver operating characteristic curves revealed that most of the genes could serve as significant diagnostic markers in COAD (P<0.05), especially ITGA8 which had a high diagnostic value with an area under curve (AUC) of 0.989 [95% confidence interval (CI) 0.980–0.997] in COAD (P<0.0001). In addition, ITGA8 expression was verified in clinical samples and it was revealed that it was higher in adjacent normal tissues (P=0.041) compared to COAD tissues, and the AUC was 0.704 (95% CI, 0.577–0.831; P<0.0085). Multivariate survival analysis indicated that integrin α (ITGA5) may be an independent prognostic indicator for COAD overall survival. Gene set enrichment analysis indicated that ITGA5 may participate in multiple biological processes and pathways. The present study revealed that ITGA genes were associated with the diagnosis and prognosis of COAD. The mRNA expression of ITGA8 may be a potential diagnosis biomarker and ITGA5 may serve as an independent prognosis indicator for COAD.

Protective potential of miR-146a-5p and its underlying molecular mechanism in diverse cancers: a comprehensive meta-analysis and bioinformatics analysis

Background/aims

Studies have shown that miR-146a-5p was differentially expressed in diverse cancers, but the associations between miR-146a-5p expression and prognosis across multiple types of cancer as well its potential targets and downstream pathways have not been comprehensively analyzed. In this study, we performed the first meta-analysis of the prognostic value of miR-146a-5p expression in diverse malignancies and explored prospective targets of miR-146a-5p and related signaling pathways.

Methods

A thorough search for articles related to miR-146a-5p was performed, and RNA-seq data from The Cancer Genome Atlas (TCGA) and microarray data from gene expression omnibus profiles were used to collect information about the prognostic value of miR-146a-5p. A comprehensive meta-analysis was conducted. Twelve platforms in miRWalk 2.0 were applied to predict targets of miR-146a-5p. TCGA RNA-seq data were used to validate the inverse relationships between miR-146a-5p and its likely targets. Subsequently, gene ontology and pathway analyses were conducted using Funrich version 3.1.3. Potential protein–protein interaction (PPI) networks were constructed. Potential target genes of miR-146a-5p in lung cancer were validated by RT-qPCR.

Results

We included 10 articles in the meta-analysis. In a pooled analysis, the high miR-146a-5p expression group showed a better overall survival in solid cancers, particularly in reproductive system cancers and digestive system cancers. A total of 120 predicted target genes were included in a bioinformatics analysis. Five pathways involving phospholipase C (PLC) and aquaporins (AQPs) were the most significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways. Moreover, the PPI network displayed the related signaling pathways and interactions among proteins. AQP1 and FYN were validated by RT-qPCR to be potential targets of miR-146a-5p in lung cancer.

Conclusion

There is a close link between high miR-146a-5p expression and better overall survival in 21 types of solid cancer, especially in reproductive system and digestive system cancers. Furthermore, miR-146a-5p could inhibit diverse malignancies by modulating pathways linked to PLC or AQPs. In summary, miR-146a-5p is a potential prognostic biomarker and therapeutic target for various cancers.

An inverse interaction between HOXA11 and HOXA11-AS is associated with cisplatin resistance in lung adenocarcinoma

HOXA11, which is a member of the homeobox (HOX) gene family, and its natural antisense transcript (NAT) HOXA11-AS have been reported to be closely related to the development of lung cancer. We aimed to investigate their specific roles in cisplatin (DDP) resistance in lung adenocarcinoma (LUAD). First, we found that HOXA11 is hypermethylated and significantly downregulated in a DDP-resistant A549 cell line (A549/DDP) and LUAD tissues, while the HOXA11-AS expression level is elevated. Although HOXA11 and HOXA11-AS mRNA overlap in the 5'-untranslated region (5' UTR) and share two CpG islands, DNA methylation only regulates the expression of HOXA11. Then, we found that HOXA11 and HOXA11-AS have an inverse interaction by transfecting their siRNAs and overexpression vectors into A549 and A549/DDP cells. A dual-luciferase reporter assay further confirmed that the overlapping 5'UTR is essential for the bidirectional regulation between HOXA11 and HOXA11-AS. Functional analysis showed that knockdown of HOXA11 expression in A549 cells induced DDP resistance and activated Akt/β-catenin signaling, while overexpression of HOXA11 in A549/DDP cells increased DDP sensitivity and inhibited Akt/β-catenin signaling. Moreover, HOXA11-AS knockdown in A549 cells increased DDP sensitivity and inhibited Akt/β-catenin signaling, while the overexpression of HOXA11-AS in A549/DDP cells induced DDP resistance and activated Akt/β-catenin signaling. In conclusion, our study demonstrates that the inverse interaction between HOXA11 and HOXA11-AS promotes DDP resistance in LUAD.

Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer

BACKGROUND

Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, and inflammation relates significantly to its initiation and prognosis. Systematic exploration of the immunogenomic landscape therein to assist in PTC prognosis is therefore urgent. The Cancer Genome Atlas (TCGA) project provides a large number of genetic PTC samples that enable a comprehensive and reliable immunogenomic study.

METHODS

We integrated the expression profiles of immune-related genes (IRGs) and progression-free intervals (PFIs) in survival in 493 PTC patients based on the TCGA dataset. Differentially-expressed and survival-associated IRGs in PTC patients were estimated a computational difference algorithm and COX regression analysis. The potential molecular mechanisms and properties of these PTC-specific IRGs were also explored with the help of computational biology. A new prognostic index based on immune-related genes was developed by using multivariable COX analysis.

RESULTS

A total of 46 differentially expressed immune-related genes were significantly correlated with clinical outcome of PTC patients. Functional enrichment analysis revealed that these genes were actively involved in a cytokine-cytokine receptor interaction KEGG pathway. A prognostic signature based on RGs (AGTR1, CTGF, FAM3B, IL11, IL17C, PTH2R and SPAG11A) performed moderately in prognostic predictions and correlated with age, tumor stage, metastasis, number of lesions, and tumor burden. Intriguingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells.

CONCLUSIONS

Together, our results screened several IRGs of clinical significance, revealed drivers of the immune repertoire, and demonstrated the importance of a personalized, IRG-based immune signature in the recognition, surveillance, and prognosis of PTC.

Comprehensive clinical implications of homeobox A10 in 3,199 cases of non-small cell lung cancer tissue samples combining qRT-PCR, RNA sequencing and microarray data

In the current study, we proposed to explore the potential role and related signaling pathways of Homobox A10 (HOXA10) in non-small cell lung cancer (NSCLC). HOXA10 levels in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were detected by qRT-PCR and the expression of HOXA10 was significantly up-regulated in the NSCLC tissue of all 55 pairs (P = 0.037). Overexpression of HOXA10 was closely correlated with the clinical stage of LUSC (P = 0.011). HOXA10 expression in RNA sequencing data based on 1, 077 cases exhibited concordant significant up-regulation in NSCLC, LUAD and LUSC (P < 0.001). In NSCLC, HOXA10 expression was closely correlated to patient T stage (P = 0.006). In LUAD, HOXA10 expression was compactly correlated to patient N stage (P = 0.02). Some of the microarrays from Gene Expression Omnibus (GEO) and ArrayExpress showed consistent over-expression of HOXA10 levels in NSCLCs. More importantly, the combined SMD value was 0.052 (95% CI: 0.29-0.75, P < 0.001) generated by meta-analysis from 47 datasets based on 4, 616 cases of NSCLC. The area under the curve (AUC) of SROC supported the over-expression of HOXA10 in NSCLC as being 0.88 (95% CI: 0.81-0.93), with sensitivity and specificity of 0.88 (95% CI: 0.81-0.93) and 0.56 (95% CI: 0.44-0.66), respectively. In addition, 111 co-expressed genes were collected from cBioPortal and enriched in "cell cycle", "cell adhesion molecules", "p53 signaling", and "adherens junction". Interestingly, an up-regulation trend of HOXA10 protein expression was also observed in NSCLC through tissue chips and immunohistochemistry. In conclusion, the overexpression of HOXA10 may play a pivotal role in the tumorigenesis of NSCLC, and this effect is observed more obviously in LUSC than in LUAD.

Expression of exportin-1 in diffuse large B-cell lymphoma: immunohistochemistry and TCGA analyses

Exportin-1 (XPO1) is an essential nuclear export receptor that is involved in the pathogenesis of multiple tumors. However, the role of XPO1 in diffuse large B-cell lymphoma (DLBCL) requires clarification. This study aims to detect XPO1 expression in DLBCL and to explore its relationships with clinicopathologic parameters and prognoses.

METHODS

A total of 131 cases of DLBCL and 30 cases of reactive lymphoid hyperplasia were selected for immunohistochemistry to examine XPO1 expression and analyze the relationships of XPO1 expression with clinicopathologic parameters and prognosis. DLBCL datasets downloaded from The Cancer Genome Atlas (TCGA) were used to analyze the mutations, expressions, and clinical values of XPO1 in DLBCL.

RESULTS

XPO1 expression was markedly upregulated in DLBCL compared to the reactive lymphoid hyperplasia group (χ² = 10.734, P = 0.001). High XPO1 expression was associated with an advanced clinical stage (χ² = 4.036, P = 0.045) and a risky International Prognostic Index (IPI) score (χ² = 5.301, P = 0.025). Moreover, high XPO1 expression was associated with a lower overall survival rate compared with low expression (P = 0.043). XPO1 was an independent prognostic factor for DLBCL (risk ratio, RR = 3.772, P = 0.006). Furthermore, XPO1 overexpression in DLBCL was correlated with a high IPI score (P = 0.024) in TCGA datasets.

CONCLUSION

High XPO1 expression in DLBCL was related to an advanced clinical stage, poor IPI score, and poor prognosis. Thus, XPO1 may be useful for condition identification and prognostic assessment.