Elevated expression of HMGA1 correlates with the malignant status and prognosis of non-small cell lung cancer

PI3K/AKT pathway as a pivotal regulator of epithelial-mesenchymal transition in lung tumor cells

Lung cancer, as the leading cause of cancer related deaths, is one of the main global health challenges. Despite various progresses in diagnostic and therapeutic methods, there is still a high rate of mortality among lung cancer patients, which can be related to the lack of clinical symptoms to differentiate lung cancer from the other chronic respiratory disorders in the early tumor stages. Most lung cancer patients are identified in advanced and metastatic tumor stages, which is associated with a poor prognosis. Therefore, it is necessary to investigate the molecular mechanisms involved in lung tumor progression and metastasis in order to introduce early diagnostic markers as well as therapeutic targets. Epithelial-mesenchymal transition (EMT) is considered as one of the main cellular mechanisms involved in lung tumor metastasis, during which tumor cells gain the metastatic ability by acquiring mesenchymal characteristics. Since, majority of the oncogenic signaling pathways exert their role in tumor cell invasion by inducing the EMT process, in the present review we discussed the role of PI3K/AKT signaling pathway in regulation of EMT process during lung tumor metastasis. It has been reported that the PI3K/AKT acts as an inducer of EMT process through the activation of EMT-specific transcription factors in lung tumor cells. MicroRNAs also exerted their inhibitory effects during EMT process by inhibition of PI3K/AKT pathway. This review can be an effective step towards introducing the PI3K/AKT pathway as a suitable therapeutic target to inhibit the EMT process and tumor metastasis in lung cancer patients.

Increased heterogeneity in expression of genes associated with cancer progression and drug resistance

Fluctuations in the number of regulatory molecules and differences in timings of molecular events can generate variation in gene expression among genetically identical cells in the same environmental condition. This variation, termed as expression noise, can create differences in metabolic state and cellular functions, leading to phenotypic heterogeneity. Expression noise and phenotypic heterogeneity have been recognized as important contributors to intra-tumor heterogeneity, and have been associated with cancer growth, progression, and therapy resistance. However, how expression noise changes with cancer progression in actual cancer patients has remained poorly explored. Such an analysis, through identification of genes with increasing expression noise, can provide valuable insights into generation of intra-tumor heterogeneity, and could have important implications for understanding immune-suppression, drug tolerance and therapy resistance. In this work, we performed a genome-wide identification of changes in gene expression noise with cancer progression using single-cell RNA-seq data of lung adenocarcinoma patients at different stages of cancer. We identified 37 genes in epithelial cells that showed an increasing noise trend with cancer progression, many of which were also associated with cancer growth, EMT and therapy resistance. We found that expression of several of these genes was positively associated with expression of mitochondrial genes, suggesting an important role of mitochondria in generation of heterogeneity. In addition, we uncovered substantial differences in sample-specific noise profiles which could have implications for personalized prognosis and treatment.

A robust six-gene prognostic signature based on two prognostic subtypes constructed by chromatin regulators is correlated with immunological features and therapeutic response in lung adenocarcinoma

Accumulating evidence has demonstrated that chromatin regulators (CRs) regulate immune cell infiltration and are correlated with prognoses of patients in some cancers. However, the immunological and prognostic roles of CRs in lung adenocarcinoma (LUAD) are still unclear. Here, we systematically revealed the correlations of CRs with immunological features and the survival in LUAD patients based on a cohort of gene expression datasets from the public TCGA and GEO databases and real RNA-seq data by an integrative analysis using a comprehensive bioinformatics method. Totals of 160 differentially expressed CRs (DECRs) were identified between LUAD and normal lung tissues, and two molecular prognostic subtypes (MPSs) were constructed and evaluated based on 27 prognostic DECRs using five independent datasets (p =0.016, <0.0001, =0.008, =0.00038 and =0.00055, respectively). Six differentially expressed genes (DEGs) (CENPK, ANGPTL4, CCL20, CPS1, GJB3, TPSB2) between two MPSs had the most important prognostic feature and a six-gene prognostic model was established. LUAD patients in the low-risk subgroup showed a higher overall survival (OS) rate than those in the high-risk subgroup in nine independent datasets (p <0.0001, =0.021, =0.016, =0.0099, <0.0001, =0.0045, <0.0001, =0.0038 and =0.00013, respectively). Six-gene prognostic signature had the highest concordance index of 0.673 compared with 19 reported prognostic signatures. The risk score was significantly correlated with immunological features and activities of oncogenic signaling pathways. LUAD patients in the low-risk subgroup benefited more from immunotherapy and were less sensitive to conventional chemotherapy agents. This study provides novel insights into the prognostic and immunological roles of CRs in LUAD.

Targeting HMGA1 contributes to immunotherapy in aggressive breast cancer while suppressing EMT

Metastasis is an obstacle to the clinical treatment of aggressive breast cancer (BC). Studies have shown that high mobility group A1 (HMGA1) is abnormally expressed in various cancers and mediates tumor proliferation and metastasis. Here, we provided more evidence that HMGA1 mediated epithelial to mesenchymal transition (EMT) through the Wnt/β-catenin pathway in aggressive BC. More importantly, HMGA1 knockdown enhanced antitumor immunity and improved the response to immune checkpoint blockade (ICB) therapy by upregulating programmed cell death ligand 1 (PD-L1) expression. Simultaneously, we revealed a novel mechanism by which HMGA1 and PD-L1 were regulated by the PD-L1/HMGA1/Wnt/β-catenin negative feedback loop in aggressive BC. Taken together, we believe that HMGA1 can serve as a target for the dual role of anti-metastasis and enhancing immunotherapeutic responses.

HMGA1 gene expression level in cancer tissue and blood samples of non-small cell lung cancer (NSCLC) patients: preliminary report

The study aimed to assess the HMGA1 gene expression level in NSCLC patients and to evaluate its association with selected clinicopathological features and overall survival of patients. The expression of the HMGA1, coding non-histone transcription regulator HMGA1, was previously proved to correlate with the ability of cancer cells to metastasize the advancement of the disease. The prognostic value of the HMGA1 expression level was demonstrated in some neoplasms, e.g., pancreatic, gastric, endometrial, hepatocellular cancer, but the knowledge about its role in non-small cell lung cancer (NSCLC) is still limited. Thus, the HMGA1 expression level was evaluated by real-time PCR method in postoperative tumor tissue and blood samples collected at the time of diagnosis, 100 days and 1 year after surgery from 47 NSCLC patients. Mean HMGA1 expression level in blood decreased systematically from the time of cancer diagnosis to 1 year after surgery. The blood HMGA1 expression level 1 year after surgery was associated with the tobacco smoking status of patients (p= 0.0230). Patients with high blood HMGA1 expression levels measured 100 days after surgery tend to have worse overall survival than those with low expression levels (p= 0.1197). Tumor HMGA1 expression level was associated with neither features nor the overall survival of NSCLC patients. Moreover, no correlation between HMGA1 expression level measured in tumor tissue and blood samples was stated. Blood HMGA1 mRNA level could be a promising factor in the prognostication of non-small cell lung cancer patients.

Prognostic Significance of HMGA1 Expression in Lung Cancer Based on Bioinformatics Analysis

High-mobility group protein 1 (HMGA1) participates in the processes of DNA transcription, replication, recombination, and repair. The HMGA1 gene is expressed abundantly during embryogenesis and is reactivated during carcinogenesis. HMGA1 gene expression has been associated with a high degree of malignancy, metastatic tendency, and poor survival in breast, colon, ovary, and pancreatic cancers. However, its prognostic significance in lung cancer remains unclear. Using publicly available data, HMGA1 was shown to be overexpressed in both small and non-small lung tumors, with higher expression compared to both the adjacent non-malignant lung tissues and non-tumor lung tissues of healthy individuals. Elevated HMGA1 expression could result from lowered HMGA1 methylation and was connected with some clinicopathological features like sex, age, and stage of the disease. The high HMGA1 expression level was connected with shorter overall and first progression survival time among lung adenocarcinoma patients, but not lung squamous cell carcinoma patients. HMGA1 could interact with proteins involved in cellular senescence and cell cycle control (TP53, RB1, RPS6KB1, and CDK1), transcription regulation (EP400 and HMGA2), chromatin assembly and remodeling (LMNB1), and cholesterol and isoprene biosynthesis (HMGCR and INSIG1). Taken together, HMGA1 overexpression could be an essential element of lung carcinogenesis and a prognostic feature in lung cancer.

Bioinformatics and System Biology Approach to Reveal the Interaction Network and the Therapeutic Implications for Non-Small Cell Lung Cancer Patients With COVID-19

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the leading cause of coronavirus disease-2019 (COVID-19), is an emerging global health crisis. Lung cancer patients are at a higher risk of COVID-19 infection. With the increasing number of non-small-cell lung cancer (NSCLC) patients with COVID-19, there is an urgent need of efficacious drugs for the treatment of COVID-19/NSCLC.

Methods: Based on a comprehensive bioinformatic and systemic biological analysis, this study investigated COVID-19/NSCLC interactional hub genes, detected common pathways and molecular biomarkers, and predicted potential agents for COVID-19 and NSCLC.

Results: A total of 122 COVID-19/NSCLC interactional genes and 21 interactional hub genes were identified. The enrichment analysis indicated that COVID-19 and NSCLC shared common signaling pathways, including cell cycle, viral carcinogenesis, and p53 signaling pathway. In total, 10 important transcription factors (TFs) and 44 microRNAs (miRNAs) participated in regulations of 21 interactional hub genes. In addition, 23 potential candidates were predicted for the treatment of COVID-19 and NSCLC.

Conclusion: This study increased our understanding of pathophysiology and screened potential drugs for COVID-19 and NSCLC.

Novel Gene Signatures as Prognostic Biomarkers for Predicting the Recurrence of Hepatocellular Carcinoma

Simple Summary

A high percentage of patients who undergo surgical resection for hepatocellular carcinoma (HCC) experience recurrence. Therefore, identification of accurate molecular markers for predicting recurrence of HCC is important. We analyzed recurrence and non-recurrence HCC tissues using two public omics datasets comprising microarray and RNA-sequencing and found novel gene signatures associated with recurrent HCC. These molecules might be used to not only predict for recurrence of HCC but also act as potential prognostic indicators for patients with HCC.

Abstract

Hepatocellular carcinoma (HCC) has a high rate of cancer recurrence (up to 70%) in patients who undergo surgical resection. We investigated prognostic gene signatures for predicting HCC recurrence using in silico gene expression analysis. Recurrence-associated gene candidates were chosen by a comparative analysis of gene expression profiles from two independent whole-transcriptome datasets in patients with HCC who underwent surgical resection. Five promising candidate genes, CETN2, HMGA1, MPZL1, RACGAP1, and SNRPB were identified, and the expression of these genes was evaluated using quantitative reverse transcription PCR in the validation set (n = 57). The genes CETN2, HMGA1, RACGAP1, and SNRPB, but not MPZL1, were upregulated in patients with recurrent HCC. In addition, the combination of HMGA1 and MPZL1 demonstrated the best area under the curve (0.807, 95% confidence interval [CI] = 0.681–0.899) for predicting HCC recurrence. In terms of clinicopathological correlation, CETN2, MPZL1, RACGAP1, and SNRPB were upregulated in patients with microvascular invasion, and the expression of MPZL1 and SNRPB was increased in proportion to the Edmonson tumor differentiation grade. Additionally, overexpression of CETN2, HMGA1, and RACGAP1 correlated with poor overall survival (OS) and disease-free survival (DFS) in the validation set. Finally, Cox regression analysis showed that the expression of serum alpha-fetoprotein and RACGAP1 significantly affected OS, whereas platelet count, microvascular invasion, and HMGA1 expression significantly affected DFS. In conclusion, HMGA1 and RACGAP1 may be potential prognostic biomarkers for predicting the recurrence of HCC after surgical resection.

Long non‑coding RNA LINC01748 exerts carcinogenic effects in non‑small cell lung cancer cell lines by regulating the microRNA‑520a‑5p/HMGA1 axis

The important functions of long non‑coding RNAs in the malignancy of non‑small cell lung cancer (NSCLC) has been increasingly highlighted. However, whether LINC01748 functions in a crucial regulatory role still requires further research. The aim of the present study was to investigate the biological roles of LINC01748 in NSCLC. Furthermore, different experiments were utilized to investigate the mechanism of action of LINC01748 in 2 NSCLC cell lines. Reverse transcription‑quantitative PCR was used to measure mRNA expression levels. Cell Counting Kit‑8 assay, flow cytometry analysis and Transwell and Matrigel assays were also used to analyze, cell viability, apoptosis, and migration and invasion, respectively. A tumor xenograft model was used for in vivo experiments. RNA immunoprecipitation experiments, luciferase reporter assays and rescue experiments were used to investigate the mechanisms involved. Data from The Cancer Genome Atlas dataset and patients recruited into the present study showed that LINC01748 was overexpressed in NSCLC. Patients with high LINC01748 mRNA expression level had shorter overall survival rate compared with that in patients with low LINC01748 mRNA expression level. Then, knockdown of LINC01748 mRNA expression level reduced cell proliferation, migration and invasion, but increased cell apoptosis in vitro. Knockdown of LINC01748 also reduced tumor growth in vivo. Mechanistically, LINC01748 could act as a competing endogenous (ce)RNA to sponge microRNA(miR)‑520a‑5p, to increase the expression level of the target gene, high mobility group AT‑hook 1 (HMGA1) in the NSCLC cell lines. Furthermore, rescue experiments illustrated that the functions exerted by LINC01748 knockdown were negated by miR‑520a‑5p inhibition or HMGA1 overexpression. In summary, LINC01748 acted as a ceRNA by sponging miR‑520a‑5p, leading to HMGA1 overexpression, thus increasing the aggressiveness of the NSCLC cells. Accordingly, targeting the LINC01748/miR‑520a‑5p/HMGA1 pathway may benefit NSCLC therapy.

GRP75-mediated upregulation of HMGA1 stimulates stage I lung adenocarcinoma progression by activating JNK/c-JUN signaling

Background

Recurrence is a major challenge in early‐stage lung adenocarcinoma (LUAD) treatment. Here, we investigated the role and mechanism of high‐mobility group AT‐hook 1 (HMGA1) and glucose‐regulated protein 75‐kDa (GRP75) in stage I LUAD and evaluated their potential as biomarkers for predicting the recurrence and prognosis of stage I LUAD.

Methods

The TCGA dataset was used to investigate the clinical significance of HMGA1 and GRP75 in early‐stage LUAD. The biological functions of HMGA1 and GRP75 in LUAD were investigated both in vitro and in vivo through overexpression and knockdown experiments. The interaction and regulation between HMGA1 and GRP75 were evaluated with coimmunoprecipitation and ubiquitination assays. The downstream signaling pathway of the GRP75/HMGA1 axis was investigated by mRNA‐sequencing analysis.

Results

Both HMGA1 expression levels and GRP75 expression levels were associated with recurrence in stage I LUAD patients. In particular, HMGA1 had potential as an independent prognostic factor in stage I LUAD patients. Overexpression of GRP75 or HMGA1 significantly stimulated LUAD cell growth and metastasis, while silencing GRP75 or HMGA1 inhibited LUAD cell growth and metastasis in vitro and in vivo. Importantly, GRP75 inhibited ubiquitination‐mediated HMGA1 degradation by directly binding to HMGA1, thereby causes HMGA1 upregulation in LUAD. In addition, the GRP75/HMGA1 axis played its role by activating JNK/c‐JUN signaling in LUAD.

Conclusions

The activation of GRP75/HMGA1/JNK/c‐JUN signaling is an important mechanism that promotes the progression of stage I LUAD, and a high level of HMGA1 is a novel biomarker for predicting recurrence and a poor prognosis in stage I LUAD patients.

Deregulation of a Cis-Acting lncRNA in Non-small Cell Lung Cancer May Control HMGA1 Expression

Background

Long non-coding RNAs (lncRNAs) have long been implicated in cancer-associated phenotypes. Recently, a class of lncRNAs, known as cis-acting, have been shown to regulate the expression of neighboring protein-coding genes and may represent undiscovered therapeutic action points. The chromatin architecture modification gene HMGA1 has recently been described to be aberrantly expressed in lung adenocarcinoma (LUAD). However, the mechanisms mediating the expression of HMGA1 in LUAD remain unknown. Here we investigate the deregulation of a putative cis-acting lncRNA in LUAD, and its effect on the oncogene HMGA1.

Methods

LncRNA expression was determined from RNA-sequencing data of tumor and matched non-malignant tissues from 36 LUAD patients. Transcripts with significantly deregulated expression were identified and validated in a secondary LUAD RNA-seq dataset (TCGA). SiRNA-mediated knockdown of a candidate cis-acting lncRNA was performed in BEAS-2B cells. Quantitative real-time PCR was used to observe the effects of lncRNA knockdown on the expression of HMGA1.

Results

We identified the lncRNA RP11.513I15.6, which we refer to as HMGA1-lnc, neighboring HMGA1 to be significantly downregulated in both LUAD cohorts. Conversely, we found HMGA1 significantly overexpressed in LUAD and anticorrelated with HMGA1-lnc. In vitro experiments demonstrated siRNA-mediated inhibition of HMGA1-lnc in immortalized non-malignant lung epithelial cells resulted in a significant increase in HMGA1 gene expression.

Conclusion

Our results suggest that HMGA1-lnc is a novel cis-acting lncRNA that negatively regulates HMGA1 gene expression in lung cells. Further characterization of this regulatory mechanism may advance our understanding of the maintenance of lung cancer phenotypes and uncover a novel therapeutic intervention point for tumors driven by HMGA1.

Machine Learning Approach for Predicting Past Environmental Exposures From Molecular Profiling of Post-Exposure Human Serum Samples

OBJECTIVE

To develop an approach for a retrospective analysis of post-exposure serum samples using diverse molecular profiles.

METHODS

The 236 molecular profiles from 800 de-identified human serum samples from the Department of Defense Serum Repository were classified as smokers or non-smokers based on direct measurement of serum cotinine levels. A machine-learning pipeline was used to classify smokers and non-smokers from their molecular profiles.

RESULTS

The refined supervised support vector machines with recursive feature elimination predicted smokers and non-smokers with 78% accuracy on the independent held-out set. Several of the identified classifiers of smoking status have previously been reported and four additional miRNAs were validated with experimental tobacco smoke exposure in mice, supporting the computational approach.

CONCLUSIONS

We developed and validated a pipeline that shows retrospective analysis of post-exposure serum samples can identify environmental exposures.

Comparative Analysis of Putative Prognostic and Predictive Markers in Neuroblastomas: High Expression of PBX1 Is Associated With a Poor Response to Induction Therapy

The survival rate for patients with high-risk neuroblastomas remains poor despite new improvements in available therapeutic modalities. A detailed understanding of the mechanisms underlying clinical responses to multimodal treatment is one of the important aspects that may provide precision in the prediction of a patient's clinical outcome. Our study was designed as a detailed comparative analysis of five selected proteins (DDX39A, HMGA1, HOXC9, NF1, and PBX1) in one cohort of patients using the same methodical approaches. These proteins were already reported separately as related to the resistance or sensitivity to retinoids and as useful prognostic markers of survival probability. In the cohort of 19 patients suffering from high-risk neuroblastomas, we analyzed initial immunohistochemistry samples obtained by diagnostic biopsy and post-induction samples taken after the end of induction therapy. The expression of DDX39A, HMGA1, HOXC9, and NF1 showed varied patterns with almost no differences between responders and non-responders. Nevertheless, we found very interesting results for PBX1: non-responders had significantly higher expression levels of this protein in the initial tumor samples when compared with responders; this expression pattern changed inversely in the post-induction samples, and this change was also statistically significant. Moreover, our results from survival analyses reveal the prognostic value of PBX1, NF1, and HOXC9 expression in neuroblastoma tissue. In addition to the prognostic importance of PBX1, NF1, and HOXC9 proteins, our results demonstrated that PBX1 could be used for the prediction of the clinical response to induction chemotherapy in patients suffering from high-risk neuroblastoma.

Regulatory Network Analysis to Reveal Important miRNAs and Genes in Non-Small Cell Lung Cancer

Objective

Lung cancer has high incidence and mortality rate, and non-small cell lung cancer (NSCLC) takes up approximately 85% of lung cancer cases. This study is aimed to reveal miRNAs and genes involved in the mechanisms of NSCLC.

Materials and Methods

In this retrospective study, GSE21933 (21 NSCLC samples and 21 normal samples), GSE27262 (25 NSCLC samples and 25 normal samples), GSE43458 (40 NSCLC samples and 30 normal samples) and GSE74706 (18 NSCLC samples and 18 normal samples) were searched from gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) were screened from the four microarray datasets using MetaDE package, and then conducted with functional annotation using DAVID tool. Afterwards, protein-protein interaction (PPI) network and module analyses were carried out using Cytoscape software. Based on miR2Disease and Mirwalk2 databases, microRNAs (miRNAs)-DEG pairs were selected. Finally, Cytoscape software was applied to construct miRNA-DEG regulatory network.

Results

Totally, 727 DEGs (382 up-regulated and 345 down-regulated) had the same expression trends in all of the four microarray datasets. In the PPI network, TP53 and FOS could interact with each other and they were among the top 10 nodes. Besides, five network modules were found. After construction of the miRNA-gene network, top 10 miRNAs (such as hsa-miR-16-5p, hsa-let-7b-5p, hsa-miR-15a-5p, hsa-miR-15b-5p, hsa-let-7a-5p and hsa-miR-34a- 5p) and genes (such as HMGA1, BTG2, SOD2 and TP53) were selected.

Conclusion

These miRNAs and genes might contribute to the pathogenesis of NSCLC.

Overexpression of HMGA1 Figures as a Potential Prognostic Factor in Endometrioid Endometrial Carcinoma (EEC)

Endometrioid endometrial carcinomas (EEC) are the most common malignant gynecologic tumors. Despite the increase in EEC molecular knowledge, the identification of new biomarkers involved in disease's development and/or progression would represent an improvement in its course. High-mobility group A protein (HMGA) family members are frequently overexpressed in a wide range of malignancies, correlating with a poor prognosis. Thus, the aim of this study was to analyze HMGA1 and HMGA2 expression pattern and their potential role as EEC biomarkers. HMGA1 and HMGA2 expression was initially evaluated in a series of 46 EEC tumors (stages IA to IV), and the findings were then validated in The Cancer Genome Atlas (TCGA) EEC cohort, comprising 381 EEC tumors (stages IA to IV). Our results reveal that HMGA1 and HMGA2 mRNA and protein are overexpressed in ECC, but only HMGA1 expression is associated with increased histological grade and tumor size. Moreover, HMGA1 but not HMGA2 overexpression was identified as a negative prognostic factor to EEC patients. Finally, a positive correlation between expression of HMGA1 pseudogenes-HMGA1-P6 and HMGA1-P7-and HMGA1 itself was detected, suggesting HMGA1 pseudogenes may play a role in HMGA1 expression regulation in EEC. Thus, these results indicate that HMGA1 overexpression possesses a potential role as a prognostic biomarker for EEC.

MicroRNA-4458 suppresses migration and epithelial-mesenchymal transition via targeting HMGA1 in non-small-cell lung cancer cells

Purpose

Increasing studies have shown that microRNA-4458 (miR-4458) is associated with human cancer progression. However, the molecular mechanism of miR-4458 in non-small-cell lung cancer (NSCLC) remains largely unknown. This study aims to reveal the biological function of miR-4458 in NSCLC.

Materials and methods

The expression of miR-4458 in NSCLC cells was evaluated by qRT-PCR. Cell proliferation and migration assay were carried out in vitro after transfection. A luciferase reporter and Western blot assay were performed to identify the functional target of miR-4458.

Results

The study indicated that miR-4458 was markedly downregulated in NSCLC cells. Overexpression of miR-4458 strongly reduced the proliferation and migration in NSCLC cell lines. In addition, miR-4458 inhibited the progression of migration and epithelial–mesenchymal transition (EMT) through the PI3K/AKT pathway. Luciferase report assay demonstrated that HMGA1 was a target gene for miR-4458.

Conclusion

The results indicate that miR-4458 participated in the process of migration and EMT via directly targeting HMGA1 and miR-4458 might be a potential novel therapeutic target in NSCLC.

HMGA1 in cancer: Cancer classification by location

The high mobility group A1 (HMGA1) gene plays an important role in numerous malignant cancers. HMGA1 is an oncofoetal gene, and we have a certain understanding of the biological function of HMGA1 based on its activities in various neoplasms. As an architectural transcription factor, HMGA1 remodels the chromatin structure and promotes the interaction between transcriptional regulatory proteins and DNA in different cancers. Through analysis of the molecular mechanism of HMGA1 and clinical studies, emerging evidence indicates that HMGA1 promotes the occurrence and metastasis of cancer. Within a similar location or the same genetic background, the function and role of HMGA1 may have certain similarities. In this paper, to characterize HMGA1 comprehensively, research on various types of tumours is discussed to further understanding of the function and mechanism of HMGA1. The findings provide a more reliable basis for classifying HMGA1 function according to the tumour location. In this review, we summarize recent studies related to HMGA1, including its structure and oncogenic properties, its major functions in each cancer, its upstream and downstream regulation associated with the tumourigenesis and metastasis of cancer, and its potential as a biomarker for clinical diagnosis of cancer.

Adaptively capturing the heterogeneity of expression for cancer biomarker identification

Background

Identifying cancer biomarkers from transcriptomics data is of importance to cancer research. However, transcriptomics data are often complex and heterogeneous, which complicates the identification of cancer biomarkers in practice. Currently, the heterogeneity still remains a challenge for detecting subtle but consistent changes of gene expression in cancer cells.

Results

In this paper, we propose to adaptively capture the heterogeneity of expression across samples in a gene regulation space instead of in a gene expression space. Specifically, we transform gene expression profiles into gene regulation profiles and mathematically formulate gene regulation probabilities (GRPs)-based statistics for characterizing differential expression of genes between tumor and normal tissues. Finally, an unbiased estimator (aGRP) of GRPs is devised that can interrogate and adaptively capture the heterogeneity of gene expression. We also derived an asymptotical significance analysis procedure for the new statistic. Since no parameter needs to be preset, aGRP is easy and friendly to use for researchers without computer programming background. We evaluated the proposed method on both simulated data and real-world data and compared with previous methods. Experimental results demonstrated the superior performance of the proposed method in exploring the heterogeneity of expression for capturing subtle but consistent alterations of gene expression in cancer.

Conclusions

Expression heterogeneity largely influences the performance of cancer biomarker identification from transcriptomics data. Models are needed that efficiently deal with the expression heterogeneity. The proposed method can be a standalone tool due to its capacity of adaptively capturing the sample heterogeneity and the simplicity in use.

Software availability

The source code of aGRP can be downloaded from https://github.com/hqwang126/aGRP.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2437-2) contains supplementary material, which is available to authorized users.

IL‑17 induces NSCLC A549 cell proliferation via the upregulation of HMGA1, resulting in an increased cyclin D1 expression

Non-small cell lung cancer (NSCLC) is considered to be an inflammation-associated carcinoma. Although interleukin‑17 (IL‑17) production contributes to the proliferation and growth of NSCLC, the mechanisms underlying IL‑17-induced NSCLC cell proliferation have not been fully elucidated. In the present study, by using ELISA and immunohistochemical analyses, we first found that the expression levels of IL‑17, IL‑17 receptor (IL‑17R), high-mobility group A1 (HMGA1) and cyclin D1 were elevated in the samples of patients with NSCLC. Subsequently, by RT-qPCR, western blot analysis and cell proliferation assay in vitro, we revealed that stimulation with recombinant human IL‑17 (namely IL‑17A) markedly induced the expression of HMGA1 and cyclin D1 in the A549 cells (a human lung adenocarcinoma cell line) and promoted cell proliferation. Furthermore, luciferase reporter and ChIP assays confirmed that upregulated HMGA1 directly bound to the cyclin D1 gene promoter and activated its transcription. Notably, the response element of HMGA1 binding to the cyclin D1 promoter was disclosed for the first time, at least to the best of our knowledge. Taken together, our findings indicate that the IL‑17/HMGA1/cyclin D1 axis plays an important role in NSCLC cell proliferation and may provide new insight into NSCLC pathogenesis and may thus aid in the development of novel therapeutic targets for NSCLC.

IL-24 modulates the high mobility group (HMG) A1/miR222 /AKT signaling in lung cancer cells

Interleukin (IL)-24, a novel tumor suppressor/cytokine exhibits antitumor activity against a broad-spectrum of human cancer cells. In a recent study, we showed that IL-24 inhibited AKT in lung cancer cells. However, the molecular mechanism of AKT inhibition by IL-24 remains elusive.The high mobility group (HMG) A1 a member of the non-histone chromosomal proteins and commonly referred to as architectural transcription factor, regulates transcription of various genes involved in cell growth and survival. Overexpression of HMGA1 has been shown to be associated with tumor progression and metastasis in several cancers, including human lung cancer. A recent study demonstrated that HMGA1 activates AKT function by reducing the activity of the protein phosphatase, phosphatase 2A subunit B (PPP2R2A) via the oncogenic micro (mi) RNA-222. Based on this report we hypothesized that IL-24-mediated AKT inhibition involved the HMGA1/miR-222 axis.To test our hypothesis, in the present study we used a H1299 lung cancer cell line that expressed exogenous human IL-24 when induced with doxycycline (DOX). Induction of IL-24 expression in the tumor cells markedly reduced HMGA1 mRNA and protein levels. Using a mechanistic approach, we found that IL-24 reduced miR-222-3p and -5p levels, as determined by qRT-PCR. Associated with HMGA1 and miR-222 inhibition was a marked increase in PPP2R2A, with a concomitant decrease in phosphorylated AKTT308/S473 expression. SiRNA-mediated knockdown of HMGA1 in combination with IL-24 significantly reduced AKT T308/S473 protein expression and greatly reduced cell migration and invasion compared with individual treatments. Further combination of IL-24 and a miR-222-3p inhibitor significantly increased PPP2R2A expression.Our results demonstrate for the first time that IL-24 inhibits AKT via regulating the HMGA1/miR-222 signaling node in human lung cancer cells and acts as an effective tumor suppressor. Thus, a therapy combining IL-24 with HMGA1 siRNA or miR-222-3p inhibitor should present effective treatment of lung cancer.

Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma

Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma.

HMGA1-pseudogenes and cancer

Pseudogenes are DNA sequences with high homology to the corresponding functional gene, but, because of the accumulation of various mutations, they have lost their initial functions to code for proteins. Consequently, pseudogenes have been considered until few years ago dysfunctional relatives of the corresponding ancestral genes, and then useless in the course of genome evolution. However, several studies have recently established that pseudogenes are owners of key biological functions. Indeed, some pseudogenes control the expression of functional genes by competitively binding to the miRNAs, some of them generate small interference RNAs to negatively modulate the expression of functional genes, and some of them even encode functional mutated proteins. Here, we concentrate our attention on the pseudogenes of the HMGA1 gene, that codes for the HMGA1a and HMGA1b proteins having a critical role in development and cancer progression. In this review, we analyze the family of HMGA1 pseudogenes through three aspects: classification, characterization, and their possible function and involvement in cancer.

High mobility group protein A2 overexpression indicates poor prognosis for cancer patients: a meta-analysis

Overexpression of the high mobility group protein A2 (HMGA2), an architectural transcription factor, has been linked to poor prognosis in many malignancies, although this remains controversial. Herein, we conducted a meta-analysis to investigate whether HMGA2 has prognostic value, and evaluated the association between HMGA2 and clinicopathologic factors in malignancies. A total of 29 studies involving 4114 patients were included in this meta-analysis. The pooled results demonstrated that elevated HMGA2 predicted a poor overall survival (OS) (hazard ratio [HR] = 1.82; 95% confidence interval [CI] = 1.62-2.05; P < 0.001) and disease-free survival/progression-free survival/recurrence-free survival (HR = 1.94; 95% CI = 1.27-2.98; P = 0.002). Subgroup analysis conducted by study region, sample size, detection method, and analysis method indicated that HMGA2 overexpression correlated with poor OS. Furthermore, HMGA2 overexpression was found to be linked to poor OS in various cancers except ovarian cancer (pooled HR = 1.14; 95% CI = 0.62-2.09; P = 0.673). High HMGA2 expression level also correlated with advanced TNM stage (OR = 2.44; 95% CI =1.87-3.2; P < 0.001), lymphovascular invasion (OR = 2.46, 95% CI = 1.67-3.64; P < 0.001), distant metastasis (OR = 2.66; 95% CI =1.51-4.69; P < 0.001), and lymph node metastasis (OR = 1.83; 95% CI =1.27-2.64; P = 0.001). In conclusion, HMGA2 overexpression indicates a worse prognosis and may serve as a prognostic predictor in cancer patients.

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification

BACKGROUND

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal.

RESULTS

This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis.

CONCLUSIONS

Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

High mobility group A1 enhances tumorigenicity of human cholangiocarcinoma and confers resistance to therapy

High mobility group A1 (HMGA1) protein has been described to play an important role in numerous types of human carcinoma. By the modulation of several target genes HMGA1 promotes proliferation and epithelial-mesenchymal transition of tumor cells. However, its role in cholangiocarcinoma (CCA) has not been addressed yet. Therefore, we determined HMGA1 mRNA expression in CCA samples in a transcriptome array (n = 104) and a smaller cohort (n = 13) by qRT-PCR. Protein expression was evaluated by immunohistochemistry in a tissue microarray (n = 67). In addition, we analyzed changes in cell proliferation, colony formation, response to gemcitabine treatment, and target gene expression after modulation of HMGA1 expression in CCA cell lines. mRNA levels of HMGA1 were found to be upregulated in 15-62% depending on the cohort analyzed. Immunohistochemistry showed HMGA1 overexpression in 51% of CCA specimens. Integration with clinico-pathological data revealed that high HMGA1 expression was associated with reduced time to recurrence and a positive lymph node status in extrahepatic cholangiocellular carcinoma. In vitro experiments showed that overexpression of HMGA1 in CCA cell lines promoted cell proliferation, whereas its suppression reduced growth rate. HMGA1 further promoted colony formation in an anchorage independent growth and conferred resistance to gemcitabine treatment. Finally, HMGA1 modulated the expression of two genes involved in CCA carcinogenesis, iNOS and ERBB2. In conclusion, our findings indicate that HMGA1 expression is increased in a substantial number of CCA specimens. HMGA1 further promotes CCA tumorigenicity and confers resistance to chemotherapy.

HMGA1 Expression in Human Hepatocellular Carcinoma Correlates with Poor Prognosis and Promotes Tumor Growth and Migration in in vitro Models

BACKGROUND

HMGA1 is a non-histone nuclear protein that regulates cellular proliferation, invasion and apoptosis and is overexpressed in many carcinomas. In this study we sought to explore the expression of HMGA1 in HCCs and cirrhotic tissues, and its effect in in vitro models.

METHODS

We evaluated HMGA1 expression using gene expression microarrays (59 HCCs, of which 37 were matched with their corresponding cirrhotic tissue and 5 normal liver donors) and tissue microarray (192 HCCs, 108 cirrhotic tissues and 79 normal liver samples). HMGA1 expression was correlated with clinicopathologic features and patient outcome. Four liver cancer cell lines with stable induced or knockdown expression of HMGA1 were characterized using in vitro assays, including proliferation, migration and anchorage-independent growth.

RESULTS

HMGA1 expression increased monotonically from normal liver tissues to cirrhotic tissue to HCC (P<.01) and was associated with Edmondson grade (P<.01). Overall, 51% and 42% of HCCs and cirrhotic tissues expressed HMGA1, respectively. Patients with HMGA1-positive HCCs had earlier disease progression and worse overall survival. Forced expression of HMGA1 in liver cancer models resulted in increased cell growth and migration, and vice versa. Soft agar assay showed that forced expression of HMGA1 led to increased foci formation, suggesting an oncogenic role of HMGA1 in hepatocarcinogenesis.

CONCLUSIONS

HMGA1 is frequently expressed in cirrhotic tissues and HCCs and its expression is associated with high Edmondson grade and worse prognosis in HCC. Our results suggest that HMGA1 may act as oncogenic driver of progression, implicating it in tumor growth and migration potential in liver carcinogenesis.

HMGA1 facilitates tumor progression through regulating Wnt/β-catenin pathway in endometrial cancer

Recent studies have identified a unique role for high mobility group protein A1 (HMGA1) as a major regulator of tumor progression and in diverse tumor models. Emerging evidences indicate that overexpressed HMGA1 facilitates multiple malignant phenotypes of cancer cells, however, the oncogenic activities of HMGA1 in endometrial cancer (EC) remains elusive. Here we showed that HMGA1 was more frequently expressed in human EC tissues compared to non-tumor tissues. Elevated HMGA1 was significantly associated with advanced clinical stage. Wound-healing assay and transwell assay showed that HMGA1 can positively regulate cell migration and invasion. Mechanistically, luciferase reporter assay and Western blotting assay demonstrated that activation of Wnt/β-catenin pathway contributed to the oncogenic activity of HMGA1. Taken together, our data reveal that HMGA1 may function as an oncogene and modulate EC cell migration and invasion by activating Wnt/β-catenin pathway, implying that suppression of HMGA1 might be a potential therapeutic strategy for EC.

miR-625 suppresses cell proliferation and migration by targeting HMGA1 in breast cancer

Dysregulation of microRNA contributes to the high incidence and mortality of breast cancer. Here, we show that miR-625 was frequently down-regulated in breast cancer. Decrease of miR-625 was closely associated with estrogen receptor (P = 0.004), human epidermal growth factor receptor 2 (P = 0.003) and clinical stage (P = 0.001). Kaplan-Meier and multivariate analyses indicated miR-625 as an independent factor for unfavorable prognosis (hazard ratio = 2.654, 95% confident interval: 1.300-5.382, P = 0.007). Re-expression of miR-625 impeded, whereas knockdown of miR-625 enhanced cell viabilities and migration abilities in breast cancer cells. HMGA1 was confirmed as a direct target of miR-625. The expressions of HMGA1 mRNA and protein were induced by miR-625 mimics, but reduced by miR-625 inhibitor. Re-introduction of HMGA1 in cells expressing miR-625 distinctly abrogated miR-625-mediated inhibition of cell growth. Taken together, our data demonstrate that miR-625 suppresses cell proliferation and migration by targeting HMGA1 and suggest miR-625 as a promising prognostic biomarker and a potential therapeutic target for breast cancer.

Fusion of the TBL1XR1 and HMGA1 genes in splenic hemangioma with t(3;6)(q26;p21)

RNA-sequencing of a splenic hemangioma with the karyotype 45~47,XX,t(3;6)(q26;p21) showed that this translocation generated a chimeric TBL1XR1-HMGA1 gene. This is the first time that this tumor has been subjected to genetic analysis, but the finding of an acquired clonal chromosome abnormality in cells cultured from the lesion and the presence of the TBL1XR1-HMGA1 fusion in them strongly favor the conclusion that splenic hemangiomas are of a neoplastic nature. Genomic PCR confirmed the presence of the TBL1XR1-HMGA1 fusion gene, and RT-PCR together with Sanger sequencing verified the presence of the fusion transcripts. The molecular consequences of the t(3;6) would be substantial. The cells carrying the translocation would retain only one functional copy of the wild-type TBL1XR1 gene while the other, rearranged allele could produce a putative truncated form of TBL1XR1 protein containing the LiSH and F-box-like domains. In the TBL1XR1-HMGA1 fusion transcript, furthermore, untranslated exons of HMGA1 are replaced by the first 5 exons of the TBL1XR1 gene. The result is that the entire coding region of HMGA1 comes under the control of the TBL1XR1 promoter, bringing about dysregulation of HMGA1. This is reminiscent of similar pathogenetic mechanisms involving high mobility genes in benign connective tissue tumors such as lipomas and leiomyomas.

High mobility group a proteins as tumor markers

Almost 30 years ago, overexpression of HMGA proteins was associated with malignant phenotype of rat thyroid cells transformed with murine retroviruses. Thereafter, several studies have analyzed HMGA expression in a wide range of human neoplasias. Here, we summarize all these results that, in the large majority of the cases, confirm the association of HMGA overexpression with high malignant phenotype as outlined by chemoresistance, spreading of metastases, and a global poor survival. Even though HMGA proteins’ overexpression indicates a poor prognosis in almost all malignancies, their detection may be particularly useful in determining the prognosis of breast, lung, and colon carcinomas, suggesting for the treatment a more aggressive therapy. In particular, the expression of HMGA2 in lung carcinomas is frequently associated with the presence of metastases. Moreover, recent data revealed that often the cause for the high HMGA proteins levels detected in human malignancies is a deregulated expression of non-coding RNA. Therefore, the HMGA proteins represent tumor markers whose detection can be a valid tool for the diagnosis and prognosis of neoplastic diseases.