En-Min Li

Deciphering the Signature of Selective Constraints on Cancerous Mitochondrial Genome

In accordance with the hypothesis that cancer formation is a process of somatic evolution driven by natural selection, signature of positive selection has been detected on a number of cancer-related nuclear genes. It remains, however, controversial whether a similar selective pressure has also acted on mitochondrial DNA (mtDNA), a small molecule in mitochondrion that may play an important role in tumorigenesis by altering oxidative phosphorylation. To better understand the mutational pattern on cancerous mtDNA and decipher the genetic signature left by natural selection, a total of 186 entire mitochondrial genomes of cancerous and adjacent normal tissues from 93 esophageal cancer patients were obtained and extensively studied. Our results revealed that the observed mutational pattern on the cancerous mtDNAs might be best explained as relaxation of negative selection. Taking into account an additional 1,235 cancerous (nearly) complete mtDNA sequences retrieved from the literature, our results suggested that the relaxed selective pressure was the most likely explanation for the accumulation of mtDNA variation in different types of cancer. This notion is in good agreement with the observation that aerobic glycolysis, instead of mitochondrial respiration, plays the key role in generating energy in cancer cells. Furthermore, our study provided solid evidence demonstrating that problems in some of the published cancerous mtDNA data adequately explained the previously contradictory conclusions about the selective pressure on cancer mtDNA, thus serving as a paradigm emphasizing the importance of data quality in affecting our understanding on the role of mtDNA in tumorigenesis.

ANO1 protein as a potential biomarker for esophageal cancer prognosis and precancerous lesion development prediction

Objectives Anoctamin 1 (ANO1) has been found to be overexpressed in esophageal squamous cell carcinoma (ESCC) in our previous study. Herein we showed the clinical relevance of ANO1 alterations with ESCC and esophageal precancerous lesion progression. Results ANO1 was detected in 38.1% (109/286) and 25.4% (77/303) of tumors in the two cohorts, but in none of morphologically normal operative margin tissues. ANO1 expression was significantly associated with a shorter overall survival (OS), especially in patients with moderately differentiated and stage IIA tumors. In 499 iodine-unstained biopsies from the endoscopic screening cohort in 2005-2007, all the 72 pathologically normal epithelial mucosa presented negative immunostaining, whereas ANO1 expression was observed in 3/11 tumors and 5/231 intraepithelial lesions. 7/8 ANO1-positive cases had developed unfavorable outcomes revealed by endoscopic follow-up in 2012. Analysis of another independent cohort of 148 intraepithelial lesions further confirmed the correlation between ANO1 expression and progression of precancerous lesions. 3/4 intraepithelial lesions with ANO1 expression had developed ESCC within 4-9 years after the initial endoscopic examination. Methods Immunohistochemistry (IHC) was performed to examine ANO1 expression in surgical ESCC specimens and two independent cohorts of esophageal biopsies from endoscopic screening in high-incidence area of ESCC in northern China. Association between ANO1 expression, clinico-pathologic parameters, and the impact on overall survival was analyzed. Conclusions Positive ANO1 is a promising biomarker to predict the unfavorable outcome for ESCC patients. More importantly, it can predict disease progression of precancerous lesions.

Expression and clinical significance of connective tissue growth factor in thyroid carcinomas

Objectives To examine expression of the connective tissue growth factor (CTGF) gene in human thyroid cancer and establish whether a correlation exists between the presence of CTGF protein and clinicopathological parameters of the disease. Methods CTGF protein expression was investigated retrospectively by immunohistochemical analysis of CTGF protein levels in thyroid tumour tissue. Associations between immunohistochemical score and several clinicopathological parameters were examined. Results In total, 131 thyroid tissue specimens were included. High levels of CTGF protein were observed in papillary thyroid carcinoma tissue; benign thyroid tumour tissue scored negatively for CTGF protein. In papillary thyroid carcinoma, there was a significant relationship between high CTGF protein levels and Union for International Cancer Control disease stage III–IV, and presence of lymph node metastasis. In papillary thyroid carcinomas, CTGF protein levels were not significantly associated with sex or age. Conclusions These findings suggest that the CTGF protein level is increased in papillary thyroid carcinoma cells compared with benign thyroid tumours. CTGF expression might play a role in the development of malignant tumours in the thyroid.

The interaction of lncRNA EZR-AS1 with SMYD3 maintains overexpression of EZR in ESCC cells

Abstract EZR, a member of the ezrin-radixin-moesin (ERM) family, is involved in multiple aspects of cell migration and cancer. SMYD3, a histone H3–lysine 4 (H3–K4)-specific methyltransferase, regulates EZR gene transcription, but the molecular mechanisms of epigenetic regulation remain ill-defined. Here, we show that antisense lncRNA EZR-AS1 was positively correlated with EZR expression in both human esophageal squamous cell carcinoma (ESCC) tissues and cell lines. Both in vivo and in vitro studies revealed that EZR-AS1 promoted cell migration through up-regulation of EZR expression. Mechanistically, antisense lncRNA EZR-AS1 formed a complex with RNA polymerase II to activate the transcription of EZR. Moreover, EZR-AS1 could recruit SMYD3 to a binding site, present in a GC-rich region downstream of the EZR promoter, causing the binding of SMYD3 and local enrichment of H3K4me3. Finally, the interaction of EZR-AS1 with SMYD3 further enhanced EZR transcription and expression. Our findings suggest that antisense lncRNA EZR-AS1, as a member of an RNA polymerase complex and through enhanced SMYD3-dependent H3K4 methylation, plays an important role in enhancing transcription of the EZR gene to promote the mobility and invasiveness of human cancer cells.

PPI Network Analysis of mRNA Expression Profile of Ezrin Knockdown in Esophageal Squamous Cell Carcinoma

Ezrin, coding protein EZR which cross-links actin filaments, overexpresses and involves invasion, metastasis, and poor prognosis in various cancers including esophageal squamous cell carcinoma (ESCC). In our previous study, Ezrin was knock down and analyzed by mRNA expression profile which has not been fully mined. In this study, we applied protein-protein interactions (PPI) network knowledge and methods to explore our understanding of these differentially expressed genes (DEGs). PPI subnetworks showed that hundreds of DEGs interact with thousands of other proteins. Subcellular localization analyses found that the DEGs and their directly or indirectly interacting proteins distribute in multiple layers, which was applied to analyze the shortest paths between EZR and other DEGs. Gene ontology annotation generated a functional annotation map and found hundreds of significant terms, especially those associated with cytoskeleton organization of Ezrin protein, such as “cytoskeleton organization,” “regulation of actin filament-based process,” and “regulation of actin cytoskeleton organization.” The algorithm of Random Walk with Restart was applied to prioritize the DEGs and identified several cancer related DEGs ranked closest to EZR. These analyses based on PPI network have greatly expanded our comprehension of the mRNA expression profile of Ezrin knockdown for future examination of the roles and mechanisms of Ezrin.

Increased expression of miR-221 and miR-222 in patients with thyroid carcinoma

To determine the diagnostic significance of miR-221 and miR-222 expression in papillary thyroid carcinoma and the associations with clinicopathological features of patients, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed in 83 cases of papillary thyroid carcinoma and the corresponding normal tissues, as well as in 25 cases of multinodular goiters and 15 cases of normal thyroid tissues. Expression of two miRNAs was then associated with patient clinicopathological features. After that receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic values of miR-221 and miR-222 in papillary thyroid carcinoma. These results demonstrate that both mir-221 and miR-222 were significantly over-expressed in papillary thyroid carcinoma compared to non-tumor tissues. ROC curves indicated a sensitivity and specificity of 80.7 and 74.8%, respectively for miR-221 and 78.3 and 83.2%, respectively for mir-222. Moreover, expression of miR-221 and miR-222 was significantly associated with extrathyroidal invasion of papillary thyroid carcinoma (p = 0.027 and 0.034, respectively) with a sensitivity of 63.6 and 63.6% and the specificity of 52.5, 73.8%, respectively. Expression of both miRNAs was correlated in papillary thyroid carcinomas (r = 0.468, p = 0.000), which suggested that expression of both miR-221 and miR-222 might be used as tumor markers for diagnosis and prediction of tumor progression.

MASAN: a novel staging system for prognosis of patients with oesophageal squamous cell carcinoma

BackgroundOesophageal squamous cell carcinoma (ESCC) is one of the most malignant cancers worldwide. Treatment of ESCC is in progress through accurate staging and risk assessment of patients. The emergence of potential molecular markers inspired us to construct novel staging systems with better accuracy by incorporating molecular markers.MethodsWe measured H scores of 23 protein markers and analysed eight clinical factors of 77 ESCC patients in a training set, from which we identified an optimal MASAN (MYC, ANO1, SLC52A3, Age and N-stage) signature. We constructed MASAN models using Cox PH models, and created MASAN-staging systems based on k-means clustering and minimum-distance classifier. MASAN was validated in a test set (nu2009=u200977) and an independent validation set (nu2009=u2009150).ResultsMASAN possessed high predictive accuracies and stratified ESCC patients into three prognostic groups that were more accurate than the current pTNM-staging system for both overall survival and disease-free survival. To facilitate clinical utilisation, we also constructed MASAN-SI staging systems based on staining indices (SI) of protein markers, which possessed similar prognostic performance as MASAN.ConclusionMASAN provides a good alternative staging system for ESCC prognosis with a high precision using a simple model.

A three-lncRNA signature predicts overall survival and disease-free survival in patients with esophageal squamous cell carcinoma

BackgroundIncreasing evidence shows that dysregulated long non-coding RNAs (lncRNAs) can serve as potential biomarkers for cancer prognosis. However, lncRNA signatures, as potential prognostic biomarkers for esophageal squamous cell carcinoma (ESCC), have been seldom reported.MethodsBased on our previous transcriptome RNA sequencing analysis from 15 paired ESCC tissues and adjacent normal tissues, we selected 10 lncRNAs with high score rank and characterized the expression of those lncRNAs, by qRT-PCR, in 138 ESCC and paired adjacent normal samples. These 138 patients were divided randomly into training (nu2009=u200977) and test (nu2009=u200959) groups. A prognostic signature of lncRNAs was identified in the training group and validated in the test group and in an independent cohort (nu2009=u2009119). Multivariable Cox regression analysis evaluated the independence of the signature in overall survival (OS) and disease-free survival (DFS) prediction. GO and KEGG pathway analysis, combined with cell transwell and proliferation assays, are applied to explore the function of the three lncRNAs.ResultsA novel three-lncRNA signature, comprised of RP11-366H4.1.1 (ENSG00000248370), LINC00460 (ENSG00000233532) and AC093850.2 (ENSG00000230838), was identified. The signature classified patients into high-risk and low-risk groups with different overall survival (OS) and disease-free survival (DFS). For the training group, median OS: 23.1xa0months vs. 39.1xa0months, Pu2009<u20090.001; median DFS: 15.2xa0months vs. 33.3xa0months, Pu2009<u20090.001. For the test group, median OS: 23xa0months vs. 59xa0months, Pu2009<u20090.001; median DFS: 16.4xa0months vs. 50.8xa0months, Pu2009<u20090.001. For the independent cohort, median OS: 22.4xa0months vs. 60.4xa0months, Pu2009<u20090.001). The signature indicates that patients in the high-risk group show poor OS and DFS, whereas patients with a low-risk group show significantly better outcome. The independence of the signature was validated by multivariable Cox regression analysis. GO and KEGG pathway analysis for 588 protein-coding genes-associated with the three lncRNAs indicated that the three lncRNAs were involved in tumorigenesis. In vitro assays further demonstrated that the three lncRNAs promoted the migration and proliferation of ESCC cells.ConclusionsThe three-lncRNA signature is a novel and potential predictor of OS and DFS for patients with ESCC.

RWCFusion: identifying phenotype-specific cancer driver gene fusions based on fusion pair random walk scoring method

While gene fusions have been increasingly detected by next-generation sequencing (NGS) technologies based methods in human cancers, these methods have limitations in identifying driver fusions. In addition, the existing methods to identify driver gene fusions ignored the specificity among different cancers or only considered their local rather than global topology features in networks. Here, we proposed a novel network-based method, called RWCFusion, to identify phenotype-specific cancer driver gene fusions. To evaluate its performance, we used leave-one-out cross-validation in 35 cancers and achieved a high AUC value 0.925 for overall cancers and an average 0.929 for signal cancer. Furthermore, we classified 35 cancers into two classes: haematological and solid, of which the haematological got a highly AUC which is up to 0.968. Finally, we applied RWCFusion to breast cancer and found that top 13 gene fusions, such as BCAS3-BCAS4, NOTCH-NUP214, MED13-BCAS3 and CARM-SMARCA4, have been previously proved to be drivers for breast cancer. Additionally, 8 among the top 10 of the remaining candidate gene fusions, such as SULF2-ZNF217, MED1-ACSF2, and ACACA-STAC2, were inferred to be potential driver gene fusions of breast cancer by us.

Co-activation of super-enhancer-driven CCAT1 by TP63 and SOX2 promotes squamous cancer progression

Squamous cell carcinomas (SCCs) are aggressive malignancies. Previous report demonstrated that master transcription factors (TFs) TP63 and SOX2 exhibited overlapping genomic occupancy in SCCs. However, functional consequence of their frequent co-localization at super-enhancers remains incompletely understood. Here, epigenomic profilings of different types of SCCs reveal that TP63 and SOX2 cooperatively and lineage-specifically regulate long non-coding RNA (lncRNA) CCAT1 expression, through activation of its super-enhancers and promoter. Silencing of CCAT1 substantially reduces cellular growth both in vitro and in vivo, phenotyping the effect of inhibiting either TP63 or SOX2. ChIRP analysis shows that CCAT1 forms a complex with TP63 and SOX2, which regulates EGFR expression by binding to the super-enhancers of EGFR, thereby activating both MEK/ERK1/2 and PI3K/AKT signaling pathways. These results together identify a SCC-specific DNA/RNA/protein complex which activates TP63/SOX2-CCAT1-EGFR cascade and promotes SCC tumorigenesis, advancing our understanding of transcription dysregulation in cancer biology mediated by master TFs and super-enhancers.Master regulator transcription factors TP63 and SOX2 have been reported to overlap in genomic occupancy in squamous cell carcinomas (SCCs). Here, the authors demonstrate that TP63 and SOX2 promote co-operatively long non-coding RNA CCAT1 expression through activating its super-enhancer, and CCAT1 forms a complex with TP63 and SOX2, which regulates EGFR super-enhancers and enhances both the MEK/ERK1/2 and PI3K/AKT signaling pathways in SCC.