The tumor suppressor DLC1 inhibits cancer progression and oncogenic autophagy in hepatocellular carcinoma

Invention of circRNA promoting RNA to specifically promote circRNA production

CircRNA, an essential RNA molecule involved in various biological functions and diseases, often exhibits decreased expression in tumor tissues, playing a role as a tumor suppressor, and suggesting therapeutic potential for cancer. However, current methods for promoting circRNA production are limited. This study introduces a novel approach for enhancing circRNA biogenesis, termed circRNA promoting RNA (cpRNA). CpRNA is designed to complement the flanking sequences of reverse complementary matches (RCMs) within pre-mRNA, thereby facilitating circRNA formation through improved exon circularization. Using a split-GFP reporter system, we demonstrated that cpRNA significantly enhance circGFP production. Optimization identified the best conditions for cpRNA to promote circRNA biogenesis, and these cpRNAs were then used to augment the production of endogenous circRNAs. These results indicate that cpRNAs can specifically increase the production of endogenous circRNAs with RCMs, such as circZKSCAN1 and circSMARCA5 in cancer cells, thereby inhibiting cell proliferation and migration by modulating circRNA-related pathways, showcasing the therapeutic potential of cpRNAs. Mechanistic studies have also shown that cpRNA promotes circRNA biogenesis, in part, by antagonizing the unwinding function of DHX9. Overall, these findings suggest that cpRNA represents a promising strategy for circRNA overexpression, offering a potential treatment for diseases marked by low circRNA levels.

Investigation of the Mechanism of SEMA5A and Its Associated Autophagy-Related Genes in Gastric Cancer

Purpose

Semaphorin 5A (SEMA5A) and autophagy-related genes (ARGs) are pivotal in the pathogenesis of gastric cancer (GC). However, the potential regulatory role of SEMA5A in autophagy via its associated ARGs and the underlying molecular mechanisms remain unresolved.

Patients and Methods

GC-related datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify differentially expressed genes (DEGs) between GC and control samples. The intersection of DEGs with ARGs produced candidate genes, which were further analyzed using Spearman correlation with SEMA5A to identify signature genes. Stratification of GC samples based on signature gene expression, followed by Kaplan-Meier survival analysis, identified key genes. Subsequent analyses, including gene set enrichment analysis (GSEA), immune infiltration, and immune checkpoint evaluation, were conducted on the key genes and SEMA5A. The mRNA expression level was quantified using real-time quantitative polymerase chain reaction (RT-qPCR).

Results

Ninety candidate genes were identified for Spearman correlation with SEMA5A, revealing TNFSF11, BMP6, ITPR1, and DLC1 with correlation coefficients exceeding 0.3. Survival analysis underscored DLC1 and BMP6 as key genes due to significant prognostic differences. GSEA implicated SEMA5A, BMP6, and DLC1 in the ECM receptor interaction pathway. Immune infiltration analysis indicated a negative correlation of SEMA5A and BMP6 with M1 macrophages, while DLC1 exhibited the strongest association with the immune checkpoint PDCD1LG2 (p < 0.05, cor = 0.43). The mRNA expression level of SEMA5A was significantly upregulated in AGS parental cells compared to GES-1 cells (p < 0.01), whereas DLC1 and BMP6 mRNA levels were markedly downregulated in AGS parental cells relative to GES-1 (p < 0.0001).

Conclusion

ARGs BMP6 and DLC1, associated with SEMA5A, were identified, and their prognostic significance in GC was demonstrated. Additionally, their regulatory mechanisms were further elucidated through immune infiltration analysis and molecular network construction, providing a theoretical foundation for future research on the molecular mechanisms in patients with GC.

Aberrant DNA Methylation Patterns of Deleted in Liver Cancer 1 Isoforms in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), a common primary liver cancer, is the third leading cause of death worldwide. DNA methylation changes are common in HCC and have been studied to be associated with hepatocarcinogenesis. In our study, we used the MassARRAY^® EpiTYPER technology to investigate the methylation differences of deleted in liver cancer 1 (DLC1) (isoform 1 and 3) promoter between HCC tissues and corresponding adjacent noncancerous tissues and the association between methylation levels and clinicopathological features. In addition, the modified CRISPR-Cas9 system and the DNA methyltransferase inhibitor (DNMTi) were utilized to explore the functional correlation of epigenetic modifications and DLC1 gene regulation. The methylation levels of the DLC1 isoforms in HCC samples were found significantly lower than those in the adjacent noncancerous tissues (all p < 0.0001). Also, we found that the expression of DLC1 could be bidirectionally regulated by the modified CRISPR-Cas9 system and the DNMTi. Moreover, the hypomethylation of DLC1 in HCC samples was connected with the presence of satellite lesions (p = 0.0305) and incomplete tumor capsule (p = 0.0204). Receiver operator characteristic curve analysis demonstrated that the methylation levels of DLC1 could be applied to discriminate HCC patients (area under the curve = 0.728, p < 0.0001). The hypomethylation status was a key regulatory mechanism of DLC1 expression and might serve as a potential biomarker for HCC.

LINC00114 stimulates growth and glycolysis of esophageal cancer cells by recruiting EZH2 to enhance H3K27me3 of DLC1

Objective

LINC00114 could promote the development of colorectal cancer, but its mechanism has been rarely discussed in esophageal cancer (EC). Herein, we explored the molecular mechanism of LINC00114 via mediating enhancer of zeste homolog 2/deleted in liver cancer 1 (EZH2/DLC1) axis in EC.

Methods

LINC00114, EZH2 and DLC1 expression in EC tissues and cells were tested. LINC00114, EZH2 and DLC1 expression were altered in EC cells through transfection with different constructs, and cell proliferation, migration, invasion, apoptosis and glycolysis were subsequently observed. The interaction between LINC00114 and EZH2 and that between EZH2 and DLC1 were explored. Tumor formation was also conducted to confirm the in vitro results.

Results

The expression levels of LINC00114 and EZH2 were elevated while those of DLC1 were reduced in EC. Inhibiting LINC00114 or reducing EZH2 blocked cell proliferation, migration, invasion and glycolysis and induce cell apoptosis in EC. LINC00114 promoted H3K27 trimethylation of DLC1 by recruiting EZH2. Knockdown of DLC1 stimulated cell growth and glycolysis in EC and even mitigated the role of LINC00114 inhibition in EC. In vivo experiment further confirmed the anti-tumor effect of LINC00114 inhibition in EC.

Conclusion

The data indicate that LINC00114 promotes the development of EC by recruiting EZH2 to enhance H3K27me3 of DLC1.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01258-y.

Sarcopenia and a 5-mRNA risk module as a combined factor to predict prognosis for patients with stomach adenocarcinoma

BACKGROUND

Sarcopenia is an important factor affecting the prognostic outcomes in adult cancer patients. Gastric cancer is considered an age-related disease and is one of the leading causes of global cancer mortality. We aimed to establish an effective age-related model at a molecular level to predict the prognosis of patients with gastric cancer.

METHODS

TCGA STAD (stomach adenocarcinoma) and NCBI GEO database were utilized in this study to explore the expression, clinical relevance and prognostic value of age-related mRNAs in stomach adenocarcinoma through an integrated bioinformatics analysis. WGCNA co-expression network, Univariate Cox regression analysis, LASSO regression and Multivariate Cox regression analysis were implemented to construct an age-related prognostic signature.

RESULTS

As a result, sarcopenia is not only an unfavorable factor for OS (overall survival) in patients with tumor of gastric (HR: 1.707, 95%CI: 1.437-2.026), but also increases the risk of postoperative complications in patients with gastric cancer (OR: 2.904, 95%CI: 2.150-3.922). A panel of 5 mRNAs (DCBLD1, DLC1, IGFBP1, RNASE1 and SPC24) were identified to dichotomize patients with significantly different OS and independently predicted the OS in TCGA STAD (HR = 3.044, 95%CI = 2.078-4.460, P < 0.001).

CONCLUSION

The study provided novel insights to understand STAD at a molecular level and indicated that the 5 mRNAs might act as independent promising prognosis biomarkers for STAD. Sarcopenia and the 5-mRNA risk module as a combined factor to predict prognosis may play an important role in clinical diagnosis.

CircZKSCAN1 Suppresses Hepatocellular Carcinoma Tumorigenesis by Regulating miR-873-5p/Downregulation of Deleted in Liver Cancer 1

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-associated mortality worldwide. CircZKSCAN1 (hsa_circ_0001727) was reported to be related to HCC development. The present study aims to elucidate the potential role and molecular mechanism of circZKSCAN1 in the regulation of HCC progression.

METHODS

CircZKSCAN1, miR-873-5p, and downregulation of deleted in liver cancer 1 (DLC1) in HCC tissues and cells were detected by RT-qPCR. Correlation between circZKSCAN1 expression and overall survival rate was measured by Kaplan-Meier survival analysis. The effects of circZKSCAN1, miR-873-5p, and DLC1 on proliferation, migration, and invasion were analyzed by CCK-8 and transwell assays, respectively. CyclinD1, Matrix metalloproteinase (MMP)-9, MMP-2, and DLC1 in HCC cells were detected by Western blot assay. The binding relationship between miR-873-5p and circZKSCAN1 or DLC1 was predicted by the Circinteractome or Starbase, and then confirmed by dual-luciferase reporter assays, respectively. Tumor volume and tumor weight were measured in vivo.

RESULTS

CircZKSCAN1 was downregulated in HCC tissues and cells. Kaplan-Meier survival analysis suggested that there was a positive correlation between circZKSCAN1 expression and overall survival rate. Functionally, circZKSCAN1 blocked proliferation, migration, and invasion of HCC cells. MiR-873-5p was a target miRNA of circZKSCAN1, and miR-873-5p directly bound with DLC1. Rescue experiments confirmed that miR-873-5p overexpression or DLC1 knockdown attenuated the suppressive effects of circZKSCAN1 on HCC tumor growth in vitro. Besides, circZKSCAN1 inhibited HCC cell growth in vivo.

CONCLUSIONS

This study firstly revealed that circZKSCAN1 curbed HCC progression via modulating miR-873-5p/DLC1 axis, providing a potential therapeutic target for HCC treatment.

Identification of Autophagy-Related Prognostic Signature and Analysis of Immune Cell Infiltration in Low-Grade Gliomas

Autophagy plays an important role in cancer. Many studies have demonstrated that autophagy-related genes (ARGs) can act as a prognostic signature for some cancers, but little has been known in low-grade gliomas (LGG). In our study, we aimed to establish a prognostical model based on ARGs and find prognostic risk-related key genes in LGG. In the present study, a prognostic signature was constructed based on a total of 8 ARGs (MAPK8IP1, EEF2, GRID2, BIRC5, DLC1, NAMPT, GRID1, and TP73). It was revealed that the higher the risk score, the worse was the prognosis. Time-dependent ROC analysis showed that the risk score could precisely predict the prognosis of LGG patients. Additionally, four key genes (TGFβ2, SERPING1, SERPINE1, and TIMP1) were identified and found significantly associated with OS of LGG patients. Besides, they were also discovered to be strongly related to six types of immune cells which infiltrated in LGG tumor. Taken together, the present study demonstrated the promising potential of the ARG risk score formula as an independent factor for LGG prediction. It also provided the autophagy-related signature of prognosis and potential therapeutic targets for the treatment of LGG.

MiR-200a-3p promotes gastric cancer progression by targeting DLC-1

Gastric cancer (GC) is one of the most common malignancies, ranking the third highest mortality rate worldwide. Due to the insidious symptoms and difficulty in early detection, patients with GS were mostly in the middle and late stages when they were diagnosed. Although ontogenetic or tumor-suppressive effects of miRNA-200a-3p have been demonstrated, the exact mechanism underlying GC is not clear. Therefore, the expression, effect, and mechanism of miRNA-200a-3p in GC progression were systematically investigated in this study. qRT-PCR, Western blotting, and immunohistochemical staining were applied to investigate the miRNA-200a-3p and deleted in liver cancer 1 (DLC-1) expression. Cell viability, proliferation, apoptosis, migration, and invasion capabilities of GC cells were assessed using cell counting kit-8 (CCK-8) colorimetry, EdU integration, flow cytometry, wound healing, and the transwell assay. The relationship between miRNA-200a-3p and tumor growth was investigated by tumor xenograft assay in vivo. A dual-luciferase reporter assay was estimated to verify the connection between miR-200-3p and DLC-1. The results showed that miRNA-200a-3p expression was significantly increased in both GC tissues and cells. Furthermore, via DLC-1, miRNA-200a-3p promotes tumor growth and development. miRNA-200a-3p, by targeting DLC-1, can function as an oncogene in GC cells. Collectively, our findings indicated that the miRNA-200a-3p/DLC axis might provide a theological basis for potential improvements in GC treatment strategies.

Immune implication of an autophagy-related prognostic signature in uveal melanoma

Uveal Melanoma (UM) is a rare cancer deriving from melanocytes within the uvea. It has a high rate of metastasis, especially to the liver, and a poor prognosis thereafter. Autophagy, an intracellular programmed digestive process, has been associated with the development and progression of cancers, with controversial pro- and anti-tumour roles. Although previous studies have been conducted on autophagy-related genes (ARGs) in various cancer types, its role in UM requires a deeper understanding for improved diagnosis and development of novel therapeutics. In the current study, Zheng et al. used univariate Cox regression followed by least absolute shrinkage and selection operator (Lasso) regression to identify a robust 9-ARG signature prognostic of survival in a total of 230 patients with UM. The authors used the Cancer Genome Atlas (TCGA) UM cohort as a training cohort (n=80) to identify the signature and validated it in another four independent cohorts of 150 UM patients from the Gene Expression Omnibus (GEO) repository (GSE22138, GSE27831, GSE44295 and GSE84976). This 9-ARG signature was also significantly associated with the enrichment of cancer hallmarks, including angiogenesis, IL6-KJAK-STAT3 signalling, reactive oxygen species pathway and oxidative phosphorylation. More importantly, this signature is associated with immune-related functional pathways and immune cell infiltration. Thus, this 9-ARG signature predicts prognosis and provides deeper insights into the immune mechanisms in UM, with potential implications for future immunotherapy.

Authentication of differential gene expression in oral squamous cell carcinoma using machine learning applications

BACKGROUND

Recently, the possibility of tumour classification based on genetic data has been investigated. However, genetic datasets are difficult to handle because of their massive size and complexity of manipulation. In the present study, we examined the diagnostic performance of machine learning applications using imaging-based classifications of oral squamous cell carcinoma (OSCC) gene sets.

METHODS

RNA sequencing data from SCC tissues from various sites, including oral, non-oral head and neck, oesophageal, and cervical regions, were downloaded from The Cancer Genome Atlas (TCGA). The feature genes were extracted through a convolutional neural network (CNN) and machine learning, and the performance of each analysis was compared.

RESULTS

The ability of the machine learning analysis to classify OSCC tumours was excellent. However, the tool exhibited poorer performance in discriminating histopathologically dissimilar cancers derived from the same type of tissue than in differentiating cancers of the same histopathologic type with different tissue origins, revealing that the differential gene expression pattern is a more important factor than the histopathologic features for differentiating cancer types.

CONCLUSION

The CNN-based diagnostic model and the visualisation methods using RNA sequencing data were useful for correctly categorising OSCC. The analysis showed differentially expressed genes in multiwise comparisons of various types of SCCs, such as KCNA10, FOSL2, and PRDM16, and extracted leader genes from pairwise comparisons were FGF20, DLC1, and ZNF705D.

Autophagy-Related Gene Pairs Signature for the Prognosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has been recognized as the third leading cause of cancer-related deaths worldwide. There is increasing evidence that the abnormal expression of autophagy-related genes plays an important role in the occurrence and development of HCC. Therefore, the study of autophagy-related genes can further elucidate the genetic drivers of cancer and provide valuable therapeutic targets for clinical treatment. In this study, we used 232 autophagy-related genes extracted from the Human Autophagy Database (HADb) and Molecular Signatures Database (MSigDB) to construct 1884 autophagy-related gene pairs. On this basis, we developed a prognostic model based on autophagy-related gene pairs using least absolute shrinkage and selection operator (LASSO) Cox regression to evaluate the prognosis of patients after liver cancer resection. We then used 845 liver cancer samples from three different databases to test the reliability of the risk signature through survival analysis, receiver operating characteristic (ROC) curve analysis, univariate and multivariate analysis. To further explore the underlying biological mechanisms, we conducted an enrichment analysis of autophagy-related genes. Finally, we combined the signature with independent prognostic factors to construct a nomogram. Based on the autophagy-related gene pair (ARGP) signature, we can divide patients into high- or low-risk groups. Survival analysis and ROC curve analysis verified the validity of the signature (AUC: 0.786—0.828). Multivariate Cox regression showed that the risk score can be used as an independent predictor of the clinical outcomes of liver cancer patients. Notably, this model has a more accurate predictive effect than most prognostic models for hepatocellular carcinoma. Moreover, our model is a powerful supplement to the HCC staging indicator, and a nomogram comprising both indicators can provide a better prognostic effect. Based on pairs of multiple autophagy-related genes, we proposed a prognostic model for predicting the overall survival rate of HCC patients after surgery, which is a promising prognostic indicator. This study confirms the importance of autophagy in the occurrence and development of HCC, and also provides potential biomarkers for targeted treatments.

Downregulation of ARID1B, a tumor-suppressor in the WNT subgroup medulloblastoma, activates multiple oncogenic signaling pathways

Medulloblastoma, a common pediatric malignant brain tumor, consists of four distinct molecular subgroups WNT, SHH, Group 3, and Group 4. Exome sequencing of 11 WNT subgroup medulloblastomas from an Indian cohort identified mutations in several chromatin modifier genes, including genes of the mammalian SWI/SNF complex. The genome of WNT subgroup tumors is known to be stable except for monosomy 6. Two tumors, having monosomy 6, carried a loss of function mutation in the ARID1B gene located on chromosome 6. ARID1B expression is also lower in the WNT subgroup tumors compared to other subgroups and normal cerebellar tissues that could result in haploinsufficiency. The shRNA-mediated knockdown of ARID1B expression resulted in a significant increase in the malignant potential of medulloblastoma cells. Transcriptome sequencing identified upregulation of several genes encoding cell adhesion proteins, matrix metalloproteases indicating the epithelial-mesenchymal transition. The ARID1B knockdown also upregulated ERK1/ERK2 and PI3K/AKT signaling with a decrease in the expression of several negative regulators of these pathways. The expression of negative regulators of the WNT signaling like TLE1, MDFI, GPX3, ALX4, DLC1, MEST decreased upon ARID1B knockdown resulting in the activation of the canonical WNT signaling pathway. Synthetic lethality has been reported between SWI-SNF complex mutations and EZH2 inhibition, suggesting EZH2 inhibition as a possible therapeutic modality for WNT subgroup medulloblastomas. Thus, the identification of ARID1B as a tumor suppressor and its downregulation resulting in the activation of multiple signaling pathways opens up opportunities for novel therapeutic modalities for the treatment of WNT subgroup medulloblastoma.

Germline and somatic mutations in the pathology of pineal cyst: A whole-exome sequencing study of 93 individuals

Background

Pineal cyst is a benign lesion commonly occurring in people of any age. Until now, the underlying molecular alterations have not been explored.

Methods

We performed whole exome sequencing of 93 germline samples and 21 pineal cyst tissue samples to illustrate its genetic architecture and somatic mutations. The dominant and recessive inheritance modes were considered, and a probability was calculated to evaluate the significance of variant overrepresentation.

Results

By analyzing pineal cyst as a Mendelian disease with a dominant inheritance pattern, we identified 42,325 rare germline variants, and NM_001004711.1:c.476A>G was highly enriched (FDR<0.2). By analyzing it as a recessive disorder, we identified 753 homozygous rare variants detected in at least one pineal cyst sample each. One STIM2 rare variant, NM_001169117.1:c.1652C>T, was overrepresented (FDR<0.05). Analyzing at a gene‐based level, we identified a list of the most commonlymutated germline genes, including POP4, GNGT2 and TMEM254. A somatic mutation analysis of 21 samples identified 16 variants in 15 genes, which mainly participated in the biological processes of gene expression and epigenetic regulation, immune response modulation, and transferase activity.

Conclusion

These molecular profiles are novel for this condition and provide data for investigators interested in pineal cysts.

Tumor suppressor gene DLC1: Its modifications, interactive molecules, and potential prospects for clinical cancer application

Deleted in liver cancer 1 (DLC1) is a recognized tumor suppressor gene that negatively regulates Rho family proteins by hydrolyzing the active GTP-bound state to its inactive GDP-bound state. Active Rho proteins play a positive role in tumorigenesis. Numerous in vitro and in vivo experiments have shown that DLC1 is downregulated or inactivated in various solid tumors, which may be due to the following five reasons: genomic deletion, epigenetic modification and ubiquitin-dependent proteasomal degradation may cause DLC1 underexpression; phosphorylation at the post-translation level may cause DLC1 inactivation; and failure to localize at focal adhesions (FAs) may prevent DLC1 from exerting full activity. All of the causes could be attributed to molecular binding. Experimental evidence suggests that direct or indirect targeting of DLC1 is feasible for cancer treatment. Therefore, elucidating the interaction of DLC1 with its binding partners might provide novel targeted therapies for cancer. In this review, we summarized the binding partners of DLC1 at both the gene and protein levels and expounded a variety of anticancer drugs targeting DLC1 to provide information about DLC1 as a cancer diagnostic indicator or therapeutic target.

Identification and Validation of a Prognostic Model Based on Three Autophagy-Related Genes in Hepatocellular Carcinoma

Background

Accumulating studies have demonstrated that autophagy plays an important role in hepatocellular carcinoma (HCC). We aimed to construct a prognostic model based on autophagy-related genes (ARGs) to predict the survival of HCC patients.

Methods

Differentially expressed ARGs were identified based on the expression data from The Cancer Genome Atlas and ARGs of the Human Autophagy Database. Univariate Cox regression analysis was used to identify the prognosis-related ARGs. Multivariate Cox regression analysis was performed to construct the prognostic model. Receiver operating characteristic (ROC), Kaplan-Meier curve, and multivariate Cox regression analyses were performed to test the prognostic value of the model. The prognostic value of the model was further confirmed by an independent data cohort obtained from the International Cancer Genome Consortium (ICGC) database.

Results

A total of 34 prognosis-related ARGs were selected from 62 differentially expressed ARGs identified in HCC compared with noncancer tissues. After analysis, a novel prognostic model based on ARGs (PRKCD, BIRC5, and ATIC) was constructed. The risk score divided patients into high- or low-risk groups, which had significantly different survival rates. Multivariate Cox analysis indicated that the risk score was an independent risk factor for survival of HCC after adjusting for other conventional clinical parameters. ROC analysis showed that the predictive value of this model was better than that of other conventional clinical parameters. Moreover, the prognostic value of the model was further confirmed in an independent cohort from ICGC patients.

Conclusion

The prognosis-related ARGs could provide new perspectives on HCC, and the model should be helpful for predicting the prognosis of HCC patients.

DLC1 inhibits lung adenocarcinoma cell proliferation, migration and invasion via regulating MAPK signaling pathway

Lung adenocarcinoma (LUAD), one of the most common cancers, is a major threat to people's health due to its high mortality, and the survival of most patients suffering LUAD remains poor. This study aimed to explore the mechanism of Deleted in Liver Cancer 1 (DLC1) as a tumor suppressor underlying the occurrence and progression of LUAD. As revealed by bioinformatics analysis and qRT-PCR, DLC1 was significantly down-regulated in LUAD tumor tissue and cells. A series of cellular experiments including CCK-8, wound healing and Transwell assays were performed to detect the effect of DLC1 on the biological function of LUAD cells. It was found that overexpressing DLC1 significantly inhibited LUAD cell proliferative, migratory and invasive abilities, while knockdown of DLC1 promoted these abilities. Gene Set Enrichment Analysis (GSEA) and dual-luciferase assay were used to explore the downstream signaling pathway of DLC1, finding that DLC1 could remarkably inhibit the activity of mitogen-activated protein kinase (MAPK) signaling pathway. Western blot implemented for MAPK signaling pathway-related proteins further identified that DLC1 restrained the activation of MAPK/ERK signaling pathway. Furthermore, rescue experiments suggested that DLC1 inhibited LUAD cell proliferation and invasion by suppressing the MAPK/ERK signaling pathway. Overall, our study discussed the DLC1-dependent mechanism involved in LUAD. We found that the up-regulation of DLC1 may inhibit the malignant progression of LUAD by suppressing MAPK signaling pathway, which supports the view that DLC1 may serve as a molecular target for the targeted therapy of LUAD patients.

TMEM106C contributes to the malignant characteristics and poor prognosis of hepatocellular carcinoma

Transmembrane protein (TMEM) is a kind of integral membrane protein that spans biological membranes. The functions of most members of the TMEM family are unknown. Here, we conducted bioinformatic analysis and biological validation to investigate the role of TMEM106C in HCC. First, GEPIA and Oncomine^TM were used to analyze TMEM106C expression, which was verified by real-time PCR and western blot analyses. Then, the biological functions of TMEM106C were explored by CCK8 and transwell assays. The prognostic value of TMEM106C was analyzed by UALCAN. LinkedOmics was used to analyze TMEM106C pathways generated by Gene Ontology. A protein-protein interaction network (PPI) was constructed by GeneMANIA. We demonstrated that TMEM106C was overexpressed in HCC and that inhibition of TMEM106C significantly suppressed the proliferation and metastasis of HCC through targeting CENPM and DLC-1. Upregulation of TMEM106C was closely correlated with sex, tumor stage, tumor grade and prognosis. Overexpression of TMEM106C was linked to functional networks involving organelle fission and cell cycle signaling pathways through the regulation of CDK kinases, E2F1 transcription factors and miRNAs. Our data demonstrated that TMEM106C contributes to malignant characteristics and poor prognosis in HCC, which may serve as a prognostic biomarker and potential therapeutic target.

Frequent Downregulation and Promoter Hypermethylation of DLC1: Relationship with Clinical Outcome in Gallbladder Cancer

INTRODUCTION

Down regulation of DLC1 is associated with poor prognosis in many cancers, however, its role in gallbladder cancer (GBC) is still unclear. In present study, we investigated the expression profile and promoter methylation status of DLC1.

METHODS

Expression profiles of DLC1 in 55 GBC and their paired adjacent control samples were analyzed through real time RT-PCR and immunohistochemistry. The mRNA data was correlated with clinico-pathological parameters. Promoter hypermethylation was analyzed through MSP.

RESULTS

DLC1 shows downregulation in 76.4%, upregulation in 10.9% whereas no change in 12.7% of GBC samples. Its underexpression shows significant correlation with tumor grade and nodal spread. IHC shows cytoplasmic expression of DLC1 in normal as well as tumor samples. IHC result was concordant to mRNA result. Samples having downregulated DLC1 expression show heterozygous methylation in 83.3% of samples and homozygous methylation in 9.5% of samples whereas 7% of samples have no methylation. Kaplan-Meier analysis shows patient with decreased mRNA of DLC1 have significant low mean survival compared to patients with higher mRNA expression of DLC1.

CONCLUSION

Our findings suggested that dysregulated expression of DLC1 and its hypermethylation may be one of the events playing roles in tumorigenesis of GBC and may serve as a potential target for development of future GBC gene therapy.