Hongguang Zhu

Plasma MicroRNA Panel to Diagnose Hepatitis B Virus–Related Hepatocellular Carcinoma

PURPOSE More than 60% of patients with hepatocellular carcinoma (HCC) do not receive curative therapy as a result of late clinical presentation and diagnosis. We aimed to identify plasma microRNAs for diagnosing hepatitis B virus (HBV) -related HCC. PATIENTS AND METHODS Plasma microRNA expression was investigated with three independent cohorts including 934 participants (healthy, chronic hepatitis B, cirrhosis, and HBV-related HCC), recruited between August 2008 and June 2010. First, we used microarray to screen 723 microRNAs in 137 plasma samples for diagnosing HCC. Quantitative reverse-transcriptase polymerase chain reaction assay was then applied to evaluate the expression of selected microRNAs. A logistic regression model was constructed using a training cohort (n = 407) and then validated using an independent cohort (n = 390). Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. RESULTS We identified a microRNA panel (miR-122, miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801) that provided a high diagnostic accuracy of HCC (AUC = 0.864 and 0.888 for training and validation data set, respectively). The satisfactory diagnostic performance of the microRNA panel persisted regardless of disease status (AUCs for Barcelona Clinic Liver Cancer stages 0, A, B, and C were 0.888, 0.888, 0.901, and 0.881, respectively). The microRNA panel can also differentiate HCC from healthy (AUC = 0.941), chronic hepatitis B (AUC = 0.842), and cirrhosis (AUC = 0.884), respectively. CONCLUSION We found a plasma microRNA panel that has considerable clinical value in diagnosing early-stage HCC. Thus, patients who would have otherwise missed the curative treatment window can benefit from optimal therapy.

Improvement of tissue preparation for laser capture microdissection: application for cell type-specific miRNA expression profiling in colorectal tumors.

BackgroundLaser capture microdissection (LCM) has successfully isolated pure cell populations from tissue sections and the combination of LCM with standard genomic and proteomic methods has revolutionized molecular analysis of complex tissue. However, the quantity and quality of material recovered after LCM is often still limited for analysis by using whole genomic and proteomic approaches. To procure high quality and quantity of RNA after LCM, we optimized the procedures on tissue preparations and applied the approach for cell type-specific miRNA expression profiling in colorectal tumors.ResultsWe found that the ethanol fixation of tissue sections for 2 hours had the maximum improvement of RNA quality (1.8 fold, p = 0.0014) and quantity (1.5 fold, p = 0.066). Overall, the quality (RNA integrity number, RIN) for the microdissected colorectal tissues was 5.2 ± 1.5 (average ± SD) for normal (n = 43), 5.7 ± 1.1 for adenomas (n = 14) and 7.2 ± 1.2 for carcinomas (n = 44). We then compared miRNA expression profiles of 18 colorectal tissues (6 normal, 6 adenomas and 6 carcinomas) between LCM selected epithelial cells versus stromal cells using Agilent miRNA microarrays. We identified 51 differentially expressed miRNAs (p <= 0.001) between these two cell types. We found that the miRNAs in the epithelial cells could differentiate adenomas from normal and carcinomas. However, the miRNAs in the stromal and mixed cells could not separate adenomas from normal tissues. Finally, we applied quantitative RT-PCR to cross-verify the expression patterns of 7 different miRNAs using 8 LCM-selected epithelial cells and found the excellent correlation of the fold changes between the two platforms (R = 0.996).ConclusionsOur study demonstrates the feasibility and potential power of discovering cell type-specific miRNA biomarkers in complex tissue using combination of LCM with genome-wide miRNA analysis.

Human miR-1228 as a stable endogenous control for the quantification of circulating microRNAs in cancer patients

Circulating microRNAs are promising biomarkers for non‐invasive testing and dynamic monitoring in cancer patients. However, no consensus exists regarding the normalization of circulating microRNAs in the quantification, making the results incomparable. We investigated global circulating microRNA profiles to identify a stable endogenous control for quantifying circulating microRNAs using three cohorts (n = 544), including 168 control individuals (healthy subjects and those with chronic hepatitis B and cirrhosis) and 376 cancer patients (hepatocellular, colorectal, lung, esophageal, gastric, renal, prostate, and breast cancer patients). GeNorm, NormFinder, and coefficient of variability (CV) were used to select the most stable endogenous control, whereas Ingenuity Pathway Analysis (IPA) was adopted to explore its signaling pathways. Seven candidates (miR‐1225‐3p, miR‐1228, miR‐30d, miR‐939, miR‐940, miR‐188‐5p, and miR‐134) from microarray analysis and four commonly used controls (miR‐16, miR‐223, let‐7a, and RNU6B) from literature were subjected to real‐time quantitative reverse transcription‐polymerase chain reaction validation using independent cohorts. MiR‐1228 (CV = 5.4%) with minimum M value and S value presented as the most stable endogenous control across eight cancer types and three controls. IPA showed miR‐1228 to be involved extensively in metabolism‐related signal pathways and organ morphology, implying that miR‐1228 functions as a housekeeping gene. Functional network analysis found that “hematological system development” was on the list of the top networks that associate with miR‐1228, implying that miR‐1228 plays an important role in the hematological system. The results explained the steady expression of miR‐1228 in the blood. In conclusion, miR‐1228 is a promising stable endogenous control for quantifying circulating microRNAs in cancer patients.

Hepatitis B virus X protein induces hypermethylation of p16INK4A promoter via DNA methyltransferases in the early stage of HBV-associated hepatocarcinogenesis

Summary.  The aim of the present study was to authenticate the involvement of DNA methyltransferases (DNMTs) and methyl‐CpG binding domain protein 2 (MBD2) in the process of HBx induced p16INK4A promoter hypermethylation in HBV‐related hepatocellular carcinoma (HCC) and their corresponding noncancerous liver tissues. Eighty‐eight fresh tissue specimens of surgically resected HBV‐associated HCC and their corresponding noncancerous liver tissues were studied. The methylation status of the p16INK4A promoter was determined by methylation‐specific polymerase chain reaction (MSP). Reverse transcription and real‐time polymerase chain reaction (RT‐PCR) showed the expression of DNMTs, MBD2 and HBx. Western blot and immunohistochemistry were used for the protein analysis of HBx, DNMT1, DNMT3A and P16. Tissue HBV‐DNA levels were determined by RT‐PCR. HBV genotype was examined by nested PCR and restriction fragment length polymorphism (RFLP). In the corresponding noncancerous liver tissues, higher HBx expression was associated with the hypermethylation of the p16INK4A promoter. HBx was positively correlated with the DNMT1 and DNMT3A at both the mRNA and protein level. Furthermore, HBx, DNMT1 and DNMT3A protein expression were negatively correlated with p16 protein expression. In HCC tissues, HBx was positively correlated with DNMT1 and DNMT3A at both mRNA and protein level, but HBx expression did not correlate with hypermethylation of the p16INK4A promoter or p16 protein expression. The methylation status of the p16INK4A promoter did not correlate with clinicopathological characteristics. DNMT1 and DNMT3A may play important roles in the process of HBx inducing hypermethylation of the p16INK4A promoter in the early stages of HBV‐associated HCC. HBx‐DNMTs‐p16INK4A promoter hypermethylation may constitute a mechanism for tumorigenesis during HBV‐associated hepatocarcinogenesis.

Association of p16INK4A hypermethylation with hepatitis B virus X protein expression in the early stage of HBV-associated hepatocarcinogenesis.

The aim of the present study was to explore the relationship between methylation status of the p16INK4A promoter and some HBV‐related factors, and the role of these factors in p16INK4A hypermethylation and hepatocellular carcinoma (HCC) progression. Twenty‐three cases of surgically resected HBV‐associated HCC and 25 fine‐needle aspiration biopsy cases of chronic hepatitis B (CHB) were studied. The methylation status of the p16INK4A promoter was determined by methylation‐specific polymerase chain reaction (PCR). Two‐step immunohistochemical staining showed the expression of viral antigens in situ. Tissue HBV‐DNA levels were determined by fluorescence quantitative real‐time PCR. PCR and the direct sequencing method were used for mutation analysis. In peritumoral tissues (P = 0.025) and CHB samples (P = 0.029), the expression of hepatitis B virus X protein (HBx) was higher in methylated groups of p16INK4A promoter than in unmethylated groups. Other HBV factors including hepatitis B surface antigen and hepatitis B core antigen, tissue HBV‐DNA levels and HBV x gene mutations had no relation to the methylation status of p16INK4A promoter. The data indicate that p16INK4A promoter hypermethylation correlated closely with higher HBx expression in the precancerous lesions, suggesting that HBx may play an important role in the early stage of HBV‐associated hepatocarcinogenesis via induction of hypermethylation of p16INK4A promoter.

PIK3CA mutations mostly begin to develop in ductal carcinoma of the breast.

Somatic mutations of PIK3CA are found in 20% to 40% of invasive breast cancers. To investigate the frequency of PIK3CA mutations in the intraductal proliferative lesions of the breast, which are precursor lesions for invasive carcinoma, we analyzed 125 intraductal proliferative lesions and 108 invasive breast cancer tissues for PIK3CA mutations in this study. Target cells were precisely isolated using a laser capture microdissection (LCM) system. Genomic DNA was extracted with QIAmp DNA Micro Kit. PCR amplification was done for exons 9 and 20 of PIK3CA, where 90% of mutations clustered, and the products were directly sequenced. Forty-six missense mutations were identified in total, of which, 14 and 32 mutations clustered in exon 9 and exon 20, respectively. The most common mutations were E542K (6 cases) and E545K (8 cases) in exon 9, and H1047R (29 cases) in exon 20. A novel mutation, G3292T, was also found. Mutations were found less frequently in the ductal intraepithelial neoplasia 1B (DIN1B) and lower grade ductal proliferative lesions (3 of 68; 4.41%) than in ductal carcinoma in situ (14 of 57; 24.56%, P=0.001, Chi-square test) or invasive carcinoma (29 of 108; 26.85%, P=0.000, Chi-square test). However, there was no significant difference in the frequency of PIK3CA mutations between carcinoma in situ and invasive carcinoma (P=0.750, Chi-square test). PIK3CA mutations mostly began to develop at the stage from the DIN1B to the carcinoma in situ (DCIS), which is a late event of breast oncogenesis. PIK3CA-mutated tumors were more frequently found in ER-a positive, PR positive, and PTEN positive tumors (P=0.012, P=0.004 and P=0.004, respectively, Chi-square test). The frequency of PIK3CA gene mutation in ER+/PR+ (32/98, 32.65%) tumors was not significantly different from that in ER+/PR- (9/39, 23.08%), tested by the Chi-square test (P=0.269). There was no significant association between PIK3CA mutations and HER2 expression status (P=0.294, Chi-square test).

DIXDC1 targets p21 and cyclin D1 via PI3K pathway activation to promote colon cancer cell proliferation.

DIXDC1 is the human homolog of Ccd1, a recently identified DIX domain containing protein in zebrafish. It is a positive regulator in the Wnt signaling pathway functioning downstream of Wnt and upstream of Axin. Since Wnt pathway activation is correlated with human colon cancer formation and progression, the biological role of DIXDC1 in human colon cancer was examined. In the current study, up‐regulation of DIXDC1 protein was detected in human colorectal adenocarcinoma tissues and was found to be correlated well with high cell proliferation index. Ectopic over‐expression of DIXDC1 resulted in increased cell proliferation in vitro and accelerated tumorigenesis on nude mice in vivo. We also showed that DIXDC1 promoted G0/G1 to S phase transition concomitantly with up‐regulation of cyclin D1 and down‐regulation of p21 protein. DIXDC1 over‐expression cells showed activation of the PI3K/AKT pathway. Both siRNA knockdown of DIXDC1 and blocking the PI3K pathway using a specific inhibitor caused G1/S phase arrest, as well as down‐regulation of cyclin D1 and up‐regulation of p21 in DIXDC1 over‐expression colon cancer cells. Collectively, this study demonstrates that over‐expression of DIXDC1 might target p21 and cyclin D1 to promote colon cancer cell proliferation and tumorigenesis at least partially through activation of the PI3K/Akt pathway. (Cancer Sci 2009; 100: 1801–1808)

Two MicroRNA Panels to Discriminate Three Subtypes of Lung Carcinoma in Bronchial Brushing Specimens

RATIONALE Effective treatment for lung cancer requires accuracy in subclassification of carcinoma subtypes. OBJECTIVES To identify microRNAs in bronchial brushing specimens for discriminating small cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC) and for further differentiating squamous cell carcinoma (SQ) from adenocarcinoma (AC). METHODS Microarrays were used to screen 723 microRNAs in laser-captured, microdissected cancer cells from 82 snap-frozen surgical lung specimens. Quantitative reverse-transcriptase polymerase chain reaction was performed on 153 macrodissected formalin-fixed, paraffin-embedded (FFPE) surgical lung specimens to evaluate seven microRNA candidates discovered from microarrays. Two microRNA panels were constructed on the basis of a training cohort (n = 85) and validated using an independent cohort (n = 68). The microRNA panels were applied as differentiators of SCLC from NSCLC and of SQ from AC in 207 bronchial brushing specimens. MEASUREMENTS AND MAIN RESULTS Two microRNA panels yielded high diagnostic accuracy in discriminating SCLC from NSCLC (miR-29a and miR-375; area under the curve [AUC], 0.991 and 0.982 for training and validation data set, respectively) and in differentiating SQ from AC (miR-205 and miR-34a; AUC, 0.977 and 0.982 for training and validation data set, respectively) in FFPE surgical lung specimens. Moreover, the microRNA panels accurately differentiated SCLC from NSCLC (AUC, 0.947) and SQ from AC (AUC, 0.962) in bronchial brushing specimens. CONCLUSIONS We found two microRNA panels that accurately discriminated between the three subtypes of lung carcinoma in bronchial brushing specimens. The identified microRNA panels may have considerable clinical value in differential diagnosis and optimizing treatment strategies based on lung cancer subtypes.

A microRNA panel to discriminate carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissue

Objective It is a challenge to differentiate invasive carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissues. In this study, microRNA profiles were evaluated in the transformation of colorectal carcinogenesis to discover new molecular markers for identifying a carcinoma in colonoscopy biopsy tissues where the presence of stromal invasion cells is not detectable by microscopic analysis. Methods The expression of 723 human microRNAs was measured in laser capture microdissected epithelial tumours from 133 snap-frozen surgical colorectal specimens. Three well-known classification algorithms were used to derive candidate biomarkers for discriminating carcinomas from adenomas. Quantitative reverse-transcriptase PCR was then used to validate the candidates in an independent cohort of macrodissected formalin-fixed paraffin-embedded colorectal tissue samples from 91 surgical resections. The biomarkers were applied to differentiate carcinomas from high-grade intraepithelial neoplasms in 58 colonoscopy biopsy tissue samples with stromal invasion cells undetectable by microscopy. Results One classifier of 14 microRNAs was identified with a prediction accuracy of 94.1% for discriminating carcinomas from adenomas. In formalin-fixed paraffin-embedded surgical tissue samples, a combination of miR-375, miR-424 and miR-92a yielded an accuracy of 94% (AUC=0.968) in discriminating carcinomas from adenomas. This combination has been applied to differentiate carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissues with an accuracy of 89% (AUC=0.918). Conclusions This study has found a microRNA panel that accurately discriminates carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissues. This microRNA panel has considerable clinical value in the early diagnosis and optimal surgical decision-making of colorectal cancer.

Hepatitis B virus X protein promotes hypermethylation of p16(INK4A) promoter through upregulation of DNA methyltransferases in hepatocarcinogenesis.

The hepatitis B virus×protein (HBx) has been implicated as a potential trigger of the epigenetic deregulation of some genes, but the underlying mechanism remains unknown. The aim of this study is to identify underlying mechanisms involved in HBx-mediated epigenetic modification in the process of HBx induced p16(INK4A) promoter hypermethylation. Liver cell lines were stably transfected with HBx-expressing vector. The methylation status of p16(INK4A) was examined by methyl-specific polymerase chain reaction (MSP) and bisulfite sequencing. Reverse transcription and real-time polymerase chain reaction (real-time RT-PCR), Western blot and immunohistochemistry were used to analyze the expression of HBx, HBx-mediated DNA methylation abnormalities and p16(INK4A). Some cases of HCC and corresponding noncancerous liver tissues were studied. HBx up-regulates DNMT1 and DNMT3A expression in both mRNA level and protein level, and HBx represses p16(INK4A) expression through inducing hypermethylation of p16(INK4A) promoter. Moreover, HBx induces hypermethylation of p16(INK4A) promoter through DNMT1 and DNMT3A. Regulation of DNMT1 and DNMT3A by HBx promoted hypermethylation of p16(INK4A) promoter region. HBx-DNMTs-p16(INK4A) promoter hypermethylation may suggest a mechanism for tumorigenesis during hepatocarcinogenesis.