Overexpression of BP1, an isoform of Homeobox Gene DLX4, promotes cell proliferation, migration and predicts poor prognosis in endometrial cancer

Knockdown of DLK4 inhibits non-small cell lung cancer tumor growth by downregulating CKS2

Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancer cases and is considered as the most common type of cancer. DLX4 was originally identified as a β-globin gene suppressor in red blood cells, which plays critical roles in several types of cancers. However, the role and related mechanism of DLX4 in NSCLC are still unclear. The study aimed to uncover the expression of DLX4 in human NSCLC cells and tissues, reveal its possible role in NSCLC, and investigate the underlying mechanisms. Immunoblot and TCGA database were used to detect the expression of DLX4 in human NSCLC cells and tissues. CCK-8, colony formation, and FCM assays were conducted to detect the effects of DLX4 on the viability and cell cycle of NCI-H2170 and A549 cells. Immunoblot assays were further performed to investigate the possible mechanism underlying DLX4 affecting the growth of NSCLC. We revealed that knockdown of DLX4 inhibited NSCLC cell proliferation. We further revealed that DLX4 knockdown induced the NSCLC cell cycle arrest. Our results further showed that downregulation of DLX4 suppressed YB-1 expression, which further suppressed CKS2 expression, thereby suppressing tumor growth of NSCLC. In conclusion, DLX4 has the potential to serve as a promising drug for NSCLC treatment.

Identification and validation of DLX4 as a prognostic and diagnostic biomarker for clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a lethal cancer, and biomarkers for exact diagnosis and predicting prognosis are urgently needed. The present study aimed to determine the roles of distal-less homeobox (DLX) family genes in ccRCC. The clinicopathological and mRNA expression data of patients with ccRCC were derived from The Cancer Genome Atlas database. Kaplan-Meier curves, univariate and multivariate Cox hazard analyses, in addition to receiver operator characteristic curves were used to evaluate the prognostic and diagnostic values. A single-sample gene set enrichment analysis was used to quantify the infiltration levels of immune cells. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry were conducted to examine the expression levels of DLX4 in tumor and adjacent tissue; the results demonstrated that DLX4 was highly expressed in ccRCC tissues compared with normal renal tissues. Furthermore, DLX4 expression was associated with tumor stage and grade. High proportions of males, advanced pathological stage, higher tumor grade and T, N and M stage were also observed in the high DLX4 expression group. Patients with the high DLX4 expression levels tended to have lower overall survival and disease-free survival rates compared with those with low DLX4 expression. DLX4 expression also showed favorable diagnostic efficiency in ccRCC patients. Based on functional enrichment analysis, cell cycle related pathways, epithelial-mesenchymal transition, glycolysis and inflammatory response were associated with the expression levels of DLX4. Furthermore, DLX4 expression was revealed to be associated with tumor immunosuppressive microenvironment. Overall, the expression level of DLX4 may be considered a novel prognostic indicator in ccRCC and a specific diagnostic biomarker for patients with ccRCC.

DNA methylation-mediated differential expression of DLX4 isoforms has opposing roles in leukemogenesis

Background

Previously, we reported the expression of DLX4 isoforms (BP1 and DLX7) in myeloid leukemia, but the functional role of DLX4 isoforms remains poorly understood. In the work described herein, we further determined the underlying role of DLX4 isoforms in chronic myeloid leukemia (CML) leukemogenesis.

Methods

The expression and methylation of DLX4 isoforms were detected by real-time quantitative PCR (RT-qPCR) and real-time quantitative methylation-specific PCR (RT-qMSP) in patients with CML. The functional role of DLX4 isoforms was determined in vitro and in vivo. The molecular mechanism of DLX4 isoforms in leukemogenesis was identified based on chromatin immunoprecipitation with high-throughput sequencing (ChIP-Seq)/assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-Seq) and RNA sequencing (RNA-Seq).

Results

BP1 expression was increased in patients with CML with unmethylated promoter, but DLX7 expression was decreased with hypermethylated promoter. Functionally, overexpression of BP1 increased the proliferation rate of K562 cells with S/G2 promotion, whereas DLX7 overexpression reduced the proliferation rate of K562 cells with G1 arrest. Moreover, K562 cells with BP1 overexpression increased the tumorigenicity in NCG mice, whereas K562 cells with DLX7 overexpression decreased the tumorigenicity. Mechanistically, a total of 91 genes including 79 messenger RNAs (mRNAs) and 12 long noncoding RNAs (lncRNAs) were discovered by ChIP-Seq and RNA-Seq as direct downstream targets of BP1. Among the downstream genes, knockdown of RREB1 and SGMS1-AS1 partially revived the proliferation caused by BP1 overexpression in K562 cells. Similarly, using ATAC-Seq and RNA-Seq, a total of 282 genes including 151 mRNA and 131 lncRNAs were identified as direct downstream targets of DLX7. Knockdown of downstream genes PTPRB and NEAT1 partially revived the proliferation caused by DLX7 overexpression in K562 cells. Finally, we also identified and validated a SGMS1-AS1/miR-181d-5p/SRPK2 competing endogenous RNA (ceRNA) network caused by BP1 overexpression in K562 cells.

Conclusions

The current findings reveal that DNA methylation-mediated differential expression of DLX4 isoforms BP1 and DLX7 plays opposite functions in leukemogenesis. BP1 plays an oncogenic role in leukemia development, whereas DLX7 acts as a tumor suppressor gene. These results suggest DLX4 as a therapeutic target for antileukemia therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11658-022-00358-0.

Comprehensive bioinformatic analyses of lncRNA-mediated ceRNA network for uterine corpus endometrial carcinoma

Background

Given that long non-coding RNAs (lncRNAs) involved in the tumor initiation or progression of the endometrium and that competing endogenous RNA (ceRNA) plays an important role in increasingly more biological processes, lncRNA-mediated ceRNA is likely to function in the pathogenesis of uterine corpus endometrial carcinoma (UCEC). Our present study aimed to explore the potential molecular mechanisms for the prognosis of UCEC through a lncRNA-mediated ceRNA network.

Methods

The transcriptome profiles and corresponding clinical profiles of UCEC dataset were retrieved from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) databases respectively. Differentially expressed genes (DEGs) in UCEC samples were identified via "Edge R" package. Then, an integrated bioinformatics analysis including functional enrichment analysis, tumor infiltrating immune cell (TIIC) analysis, Kaplan-Meier curve, Cox regression analysis were conducted to analyze the prognostic biomarkers.

Results

In the CPTAC dataset of UCEC, a ceRNA network comprised of 36 miRNAs, 123 lncRNAs and 124 targeted mRNAs was established, and 8 of 123 prognostic-related Differentially Expressed long noncoding RNAs (DElncRNAs) were identified. While in the TCGA dataset, a ceRNA network comprised of 38 miRNAs, 83 lncRNAs and 110 targeted mRNAs was established, and 2 of 83 prognostic-related DElncRNAs were identified. After filtered by risk grouping and Cox regression analysis, 10 prognostic-related lncRNAs including LINC00443, LINC00483, C2orf48, TRBV11-2, MEG-8 were identified. In addition, 33 survival-related Differentially Expressed messenger RNA (DEmRNAs) in two ceRNA networks were further validated in the Human Protein Atlas Portal (HPA) database. Finally, six lncRNA/miRNA/mRNA axes were established to elucidate prognostic regulatory roles in UCEC.

Conclusions

Several prognostic lncRNAs are identified and prognostic model of lncRNA-mediated ceRNA network is constructed, which promotes the understanding of UCEC development mechanisms and potential therapeutic targets.

A validation study of potential prognostic DNA methylation biomarkers in patients with acute myeloid leukemia using a custom DNA methylation sequencing panel

BACKGROUND

Multiple studies have reported the prognostic impact of DNA methylation changes in acute myeloid leukemia (AML). However, these epigenetic markers have not been thoroughly validated and therefore are still not considered in clinical practice. Hence, we aimed to independently verify results of selected studies describing the relationship between DNA methylation of specific genes and their prognostic potential in predicting overall survival (OS) and event-free survival (EFS).

RESULTS

Fourteen studies (published 2011-2019) comprising of 27 genes were subjected to validation by a custom NGS-based sequencing panel in 178 newly diagnosed non-M3 AML patients treated by 3 + 7 induction regimen. The results were considered as successfully validated, if both the log-rank test and multivariate Cox regression analysis had a p-value ≤ 0.05. The predictive role of DNA methylation was confirmed for three studies comprising of four genes: CEBPA (OS: p = 0.02; EFS: p = 0.03), PBX3 (EFS: p = 0.01), LZTS2 (OS: p = 0.05; EFS: p = 0.0003), and NR6A1 (OS: p = 0.004; EFS: p = 0.0003). For all of these genes, higher methylation was an indicator of longer survival. Concurrent higher methylation of both LZTS2 and NR6A1 was highly significant for survival in cytogenetically normal (CN) AML group (OS: p < 0.0001; EFS: p < 0.0001) as well as for the whole AML cohort (OS: p = 0.01; EFS < 0.0001). In contrast, for two studies reporting the poor prognostic effect of higher GPX3 and DLX4 methylation, we found the exact opposite, again linking higher GPX3 (OS: p = 0.006; EFS: p < 0.0001) and DLX4 (OS: p = 0.03; EFS = 0.03) methylation to a favorable treatment outcome. Individual gene significance levels refer to the outcomes of multivariate Cox regression analysis.

CONCLUSIONS

Out of twenty-seven genes subjected to DNA methylation validation, a prognostic role was observed for six genes. Therefore, independent validation studies are necessary to reveal truly prognostic DNA methylation changes and to enable the introduction of these promising epigenetic markers into clinical practice.

Evaluating the Expression of Candidate Homeobox Genes and Their Role in Local-Site Inflammation in Mucosal Tissue Obtained from Children with Non-Syndromic Cleft Lip and Palate

Craniofacial development including palatogenesis is a complex process which requires an orchestrated and spatiotemporal expression of various genes and factors for proper embryogenesis and organogenesis. One such group of genes essential for craniofacial development is the homeobox genes, transcriptional factors that are commonly associated with congenital abnormalities. Amongst these genes, DLX4, HOXB3, and MSX2 have been recently shown to be involved in the etiology of non-syndromic cleft lip and palate. Hence, we investigated the gene and protein expression of these genes in normal and cleft affected mucosal tissue obtained from 22 children, along with analyzing their role in promoting local-site inflammation using NF-κB. Additionally, we investigated the role of PTX3, which plays a critical role in tissue remodeling and wound repair. We found a residual gene and protein expression of DLX4 in cleft mucosa, although no differences in gene expression levels of HOXB3 and MSX2 were noted. However, a significant increase in protein expression for these genes was noted in the cleft mucosa (p < 0.05), indicating increased cellular proliferation. This was coupled with a significant increase in NF-κB protein expression in cleft mucosa (p < 0.05), highlighting the role of these genes in promotion of pro-inflammatory environment. Finally, no differences in gene expression of PTX3 were noted.

Development and validation of m6A regulators' prognostic significance for endometrial cancer

BACKGROUND

Endometrial cancer (EC) is the sixth most common cancer in women globally. It has been found that the expression levels of m6A regulators can be potentially used for prognostic stratification in some cancers, but the role of m6A regulators in EC prognosis remains unclear.

METHODS

The data of 584 EC samples were downloaded from The Cancer Genome Atlas and the mRNA expression profiles of 20 m6A regulators were analyzed, followed by functional enrichment analysis, immune infiltration analysis, and least absolute shrinkage and selection operator method-COX regression analysis.

RESULTS

The mRNA expression levels of 20 m6A regulators were significantly different between cancer samples across different grades. The 548 EC samples could be clearly divided into 2 clusters. Kaplan-Meier survival analysis proved that these two groups had highly different overall survival probabilities. Besides, the univariate regression analysis further reserved eight genes related to overall survival from the 20 m6A regulators. We established a prognostic signature including two genes, that is, IGF2BP1 and YTHDF3, that showed a strong ability for stratifying prognostically different EC patients. We identified 3239 differentially expressed genes between the high- and low-risk groups, involving in multiple biological processes and signaling pathways. Meanwhile, 6 differentially infiltrated immune cell types between the high- and low-risk groups could effectively distinguish the high- and low-risk EC groups. The expressions of immune checkpoints were different between high- and low-risk EC patients.

CONCLUSION

We first report the prognostic role of m6A regulators in EC, which should contribute to a better understanding of the underlying mechanisms of EC pathogenesis and progression.

Transcription Factors BARX1 and DLX4 Contribute to Progression of Clear Cell Renal Cell Carcinoma via Promoting Proliferation and Epithelial-Mesenchymal Transition

Dysregulation of transcription factors contributes to the carcinogenesis and progression of cancers. However, their roles in clear cell renal cell carcinoma remain largely unknown. This study aimed to evaluate the clinical significance of TFs and investigate their potential molecular mechanisms in ccRCC. Data were accessed from the cancer genome atlas kidney clear cell carcinoma cohort. Bioinformatics algorithm was used in copy number alterations mutations, and differentially expressed TFs’ analysis. Univariate and multivariate Cox regression analyses were performed to identify clinically significant TFs and construct a six-TF prognostic panel. TFs’ expression was validated in human tissues. Gene set enrichment analysis (GSEA) was utilized to find enriched cancer hallmark pathways. Functional experiments were conducted to verify the cancer-promoting effect of BARX homeobox 1 (BARX1) and distal-less homeobox 4 (DLX4) in ccRCC, and Western blot was performed to explore their downstream pathways. As for results, many CNAs and mutations were identified in transcription factor genes. TFs were differentially expressed in ccRCC. An applicable predictive panel of six-TF genes was constructed to predict the overall survival for ccRCC patients, and its diagnostic efficiency was evaluated by the area under the curve (AUC). BARX1 and DLX4 were associated with poor prognosis, and they could promote the proliferation and migration of ccRCC. In conclusion, the six-TF panel can be used as a prognostic biomarker for ccRCC patients. BARX1 and DLX4 play oncogenic roles in ccRCC via promoting proliferation and epithelial–mesenchymal transition. They have the potential to be novel therapeutic targets for ccRCC.

Human serum mid-infrared spectroscopy combined with machine learning algorithms for rapid detection of gliomas

Glioma has a low cure rate and a high mortality rate. Therefore, correct diagnosis and treatment are essential for patients. This research aims to use mid-infrared spectroscopy combined with machine learning algorithms to identify patients with glioma. The glioma infrared spectra and the control group serum are smoothed and normalized, then the principal component analysis (PCA) algorithm is used to reduce the data dimensionality, and finally, the particle swarm optimization-support vector machine (PSO-SVM), backpropagation (BP) neural network and decision tree (DT) model are established. The classification accuracy of the three models was 92.00 %, 91.83 %, 87.20 %, and the AUC values were 0.919, 0.945, and 0.866, respectively. The results show that PCA-PSO-SVM has a better classification effect. This study shows that mid-infrared spectroscopy combined with machine learning algorithms has great potential in the application of non-invasive, rapid and accurate identification of glioma patients.

A Novel Transcription Factor-Based Prognostic Signature in Endometrial Cancer: Establishment and Validation

Background

Endometrial cancer (EC) is a common malignancy of the female reproductive system worldwide. Increasing evidence has suggested that many transcription factors are aberrantly expressed in various cancers. This study aimed to develop a transcription factor-based prognostic signature for EC.

Methods

Gene expression data and clinical data of EC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression and Multivariate Cox regression analysis was used to construct a prognostic signature. Then, the efficacy of the prognostic signature was validated in a training cohort, testing cohort and then the entire cohort. Correlations between clinical features and the model were also analyzed, and a nomogram based on the multivariate Cox analysis was developed. Furthermore, we verified the effect of a key transcription factor, E2F1, on biological functions of EC in vitro.

Results

We developed a nine-transcription factor (MSX1, HOXB9, E2F1, DLX4, BNC2, DLX2, PDX1, POU3F2, and FOXP3) prognostic signature. Compared with those in the low-risk group, patients in the high-risk group had worse clinical outcomes. The area under the curve (AUC) of this prognostic signature for 5-year survival was 0.806 in the training cohort, 0.710 in the testing cohort and 0.761 in the entire cohort. Gene set enrichment analysis (GSEA) revealed a correlation between the prognostic signature and various cancer signaling pathways, and a hub transcription factor regulatory network was constructed. The prognostic signature was confirmed to have independent predictive value. Finally, a nomogram based on the prognostic signature and clinical independent prognostic factors was also established and performed well according to the calibration curves. Further, knockdown of E2F1 inhibited invasion and metastasis of EC cells.

Conclusion

Our study developed and validated a transcription factor-based prognostic signature that accurately predicts prognosis of EC patients. Moreover, E2F1 may represent a potential target for the treatment of EC.

Alterations of RNA splicing patterns in esophagus squamous cell carcinoma

Alternative splicing (AS) is an important biological process for regulating the expression of various isoforms from a single gene and thus to promote proteome diversity. In this study, RNA-seq data from 15 pairs of matched esophageal squamous cell carcinoma (ESCC) and normal tissue samples as well as two cell lines were analyzed. AS events with significant differences were identified between ESCC and matched normal tissues, which were re-annotated to find protein coding genes or non-coding RNAs. A total of 45,439 AS events were found. Of these, 6019 (13.25%) significant differentially AS events were identified. Exon skipping (SE) events occupied the largest proportion of abnormal splicing events. Fifteen differential splicing events with the same trends of ΔΨ values in ESCC tissues, as well in the two cell lines were found. Four pathways and 20 biological processes related to pro-metastasis cell junction and migration were significantly enriched for the differentially spliced genes. The upregulated splicing factor SF3B4, which regulates 92 gene splicing events, could be a potential prognostic factor of ESCC. Differentially spliced genes, including HNRNPC, VCL, ZNF207, KIAA1217, TPM1 and CALD1 are shown with a sashimi plot. These results suggest that cell junction- and migration-related biological processes are influenced by AS abnormalities, and aberrant splicing events can be affected by splicing factor expression changes. The involved splicing factor SF3B4 was found to be a survival-related gene in ESCC and is presumed to regulate AS in multiple cancers. In summary, we identified significant differentially expressed AS events which may be related to the development of ESCC.

IGF2BP1 overexpression stabilizes PEG10 mRNA in an m6A-dependent manner and promotes endometrial cancer progression

Rationale: N6-methyladenosine (m6A) mRNA methylation is the most abundant chemical posttranscriptional modification in mRNA and is involved in the regulation of a number of biological processes. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) has recently been reported as having the capacity to recognize m6A sites in mRNA and plays a role in regulating mRNA metabolization. However, it is unclear which genes IGF2BP1 targets to identify m6A sites and what are their respective functions in endometrial cancer (EC). Methods: Quantitative PCR, western blot and immunohistochemistry were used to measure IGF2BP1 expression in EC cell lines and tissues. Xenograft experiments were performed to examine the in vivo role of IGF2BP1 in EC cell growth. RNA-binding protein immunoprecipitation sequencing, methylated RNA-binding protein immunoprecipitation sequencing and RNA-sequencing were also conducted to identify potential IGF2BP1 targets involved in EC regulation. Co-immunoprecipitation and mass spectrometry were used to identify IGF2BP1-interacting proteins. Results: IGF2BP1 expression increased in EC, and high expression of this protein correlated with poor prognosis. IGF2BP1 overexpression/knockdown can promote (and inhibit) cell proliferation and regulate the tumor cell cycle and cancer progression, both in vivo and in vitro. Mechanistically, IGF2BP1 can recognize m6A sites in the 3' untranslated region (3'UTR) of Paternally Expressed Gene 10 (PEG10) mRNA and recruits polyadenylate-binding protein 1 (PABPC1) to enhance PEG10 mRNA stability, which consequently promotes PEG10 protein expression. Additionally, it would appear that a large number of PEG10 proteins bind p16 and p18 gene promoter sequences, thereby repressing expression and accelerating the cell cycle. Conclusion: This investigation found that IGF2BP1 has a crucial role in the m6A-dependent regulatory mechanism for endometrial cancer. This study provides new insights into our understanding of disease progression and provides another potential route for understanding biological functions.

FTO demethylates m6A modifications in HOXB13 mRNA and promotes endometrial cancer metastasis by activating the WNT signalling pathway

Although many studies have confirmed the relationship between obesity and endometrial cancer (EC), the molecular mechanism between obesity and EC progression has not been elucidated. Overexpression of fat mass and the obesity associated protein FTO leads to weight gain, although recently it has been discovered that FTO can serve as a demethylase which erases N6-methyladenosine (m6A) modification and regulates the metabolization of mRNAs. In this study, we found high expression of FTO in metastatic EC and that this action promote both metastasis and invasion in vivo and in vitro. Mechanistically, FTO can catalyse demethylation modification in 3'UTR region of HOXB13 mRNA, thereby abolishing m6A modification recognition with the YTHDF2 protein. Decreasing HOXB13 mRNA decay and increasing HOXB13 protein expression was accompanied by WNT signalling pathway activation and the expression of downstream proteins, leading to tumour metastasis and invasion. We also found the WNT signalling pathway inhibitor ICG-001 can block HOXB13 gene-induced tumour metastasis, therefore ICG-001 may be a promising molecular intervention. This study provides insight into the relationship between obesity and the pathogenesis of endometrial cancer while highlighting future areas of research.