Bingjian Lü

Identification of Serum Biomarkers for Colorectal Cancer Metastasis Using a Differential Secretome Approach

Lymph node metastasis is the major concern that causes death in colorectal cancers. However, biomarkers for cancer metastasis are still lacking. In this study, we applied an LC-MS/MS-based label-free quantitative proteomics approach to compare the differential secretome of a primary cell line SW480 and its lymph node metastatic cell line SW620 from the same colorectal cancer patient. We identified a total of 910 proteins from the conditioned media and 145 differential proteins between SW480 and SW620 (>1.5-fold change). The differential expression pattern of 6 candidate proteins was validated by Western blot analysis. Among them, trefoil factor 3 and growth/differentiation factor 15, two up-regulated proteins in SW620, were further analyzed in a large cohort of clinical tissue and serum samples. Sandwich ELISA assay showed that the serum levels of both proteins were significantly higher in lymph node metastatic colorectal cancers. Receiver operating characteristic curve analysis confirmed that serum trefoil factor 3 and growth/differentiation factor 15 could provide a discriminatory diagnostic test for predicting colorectal cancer metastasis. Immunohistochemical analysis also showed that the overexpression of trefoil factor 3 or growth/differentiation factor 15 in colorectal cancer was associated with lymph node metastatic behavior. This study showed an accurate, sensitive, and robust label-free quantitation approach for differential analysis of cancer secretome. The comparison of the cancer secretome in vitro is a feasible strategy to obtain valuable biomarkers for potential clinical application. Both trefoil factor 3 and growth/differentiation factor 15 could serve as potential biomarkers for the prediction of colorectal cancer metastasis.

Analysis of SOX9 Expression in Colorectal Cancer

Our purpose was to investigate the role of SOX9, a novel downstream molecule of beta-catenin, in colorectal cancer. Expression of SOX9 and beta-catenin was detected by immunostaining, quantitative real-time reverse transcription-polymerase chain reaction (Q-PCR), and Western blot in colorectal cancer. The correlation between SOX9 or beta-catenin expression and clinicopathologic parameters was also analyzed. Immunostaining, Q-PCR, and Western blot consistently confirmed SOX9 up-regulation in colorectal cancer compared with normal mucosa (P < .05). Immunostaining showed more SOX9+ cells in the lower zone of colonic crypts than in the upper zone (P < .05). Cancers with strong SOX9 immunostaining were significantly associated with a lower 5-year overall survival (40% [17/43] vs low expression, 69% [66/95]; P < .01). The Cox proportional hazards model showed that strong SOX9 expression was an independent adverse prognosticator in colorectal cancer (P < .05). The detection of SOX9 expression might contribute to predicting clinical outcomes for patients with colorectal cancer.

Downregulation of Kruppel-like factor 9 in human colorectal cancer

Mammalian Sp and Krüppel‐like factors (KLF), a family of zinc finger‐containing transcription factors, are involved in growth control, proliferation, apoptosis and angiogenesis of a wide variety of tissues and cells. Several KLF have been linked to various types of human cancers, but the relationship between Krüppel‐like factor 9 (KLF9) and colorectal cancer has not been explored. The purpose of the present study was to investigate KLF9 expression in human colorectal cancer tissue. KLF9 mRNA was detected on quantitative real‐time reverse transcriptase–polymerase chain reaction (Q‐PCR). Of the 50 cancerous tissues examined, 86% (43/50) expressed lower levels of KLF9 mRNA than individually matched normal mucosa (P < 0.0001). On western blot, reduced or absent expression of KLF9 protein was observed in 65% (13/20) of the samples (P < 0.01). A total of 81% (35/43) of normal samples had expression of KLF9 protein, whereas its protein was detected in only 9% (4/43) of tumor tissues (P < 0.001) on tissue microarray. These results indicate that KLF9 may be involved in the carcinogenesis of human colorectal cancer.

TCF7L2 gene polymorphisms and type 2 diabetes risk: a comprehensive and updated meta-analysis involving 121 174 subjects

Recently, many new loci associated with type 2 diabetes have been uncovered by genetic association studies and genome-wide association studies. As more reports are made, particularly with respect to varying ethnicities, there is a need to determine more precisely the effect sizes in each major racial group. In addition, some reports have claimed ethnic-specific associations with alternative single-nucleotide polymorphisms (SNPs), and to that end there has been a degree of confusion. We conducted a meta-analysis using an additive genetic model. Eight polymorphisms in 155 studies with 121174 subjects (53385 cases and 67789 controls) were addressed in this meta-analysis. Significant associations were found between type 2 diabetes and rs7903146, rs12255372, rs11196205, rs7901695, rs7895340 and rs4506565, with summary odds ratios (ORs) (95% confidence interval) of 1.39 (1.34-1.45), 1.33 (1.27-1.40), 1.20 (1.14-1.26), 1.32 (1.25-1.39), 1.21 (1.13-1.29) and 1.39 (1.29-1.49), respectively. In addition, no significant associations were found between the two polymorphisms (rs290487 and rs11196218) and type 2 diabetes. The summary ORs for the six statistically significant associations (P < 0.05) were further evaluated by estimating the false-positive report probability, with results indicating that all of the six significant associations were considered noteworthy, and may plausibly be true associations. Significant associations were found between the six polymorphisms (rs7903146, rs12255372, rs11196205, rs7901695, rs7895340 and rs4506565) in the TCF7L2 gene and type 2 diabetes risk, and the other two polymorphisms (rs11196218 and rs290487) were not found to be significantly associated with type 2 diabetes. Subgroups analyses show that significant associations are not found between the six SNPs (rs7903146, rs12255372, rs11196205, rs7901695, rs7895340, and rs4506565) and the type 2 diabetes in some ethnic populations.

SVM–T-RFE: A novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles

Although metastasis is the principal cause of death cause for colorectal cancer (CRC) patients, the molecular mechanisms underlying CRC metastasis are still not fully understood. In an attempt to identify metastasis-related genes in CRC, we obtained gene expression profiles of 55 early stage primary CRCs, 56 late stage primary CRCs, and 34 metastatic CRCs from the expression project in Oncology (http://www.intgen.org/expo/). We developed a novel gene selection algorithm (SVM-T-RFE), which extends support vector machine recursive feature elimination (SVM-RFE) algorithm by incorporating T-statistic. We achieved highest classification accuracy (100%) with smaller gene subsets (10 and 6, respectively), when classifying between early and late stage primary CRCs, as well as between metastatic CRCs and late stage primary CRCs. We also compared the performance of SVM-T-RFE and SVM-RFE gene selection algorithms on another large-scale CRC dataset and the five public microarray datasets. SVM-T-RFE bestowed SVM-RFE algorithm in identifying more differentially expressed genes, and achieving highest prediction accuracy using equal or smaller number of selected genes. A fraction of selected genes have been reported to be associated with CRC development or metastasis.

Epithelioid trophoblastic tumor: an outcome-based literature review of 78 reported cases.

Objectives Epithelioid trophoblastic tumor (ETT) is very rare; and therefore, a substantially increased data set is unlikely to be obtained in the near future. This analysis aimed to assess the effects of current management on clinical outcomes and to identify potential prognostic indicators in ETT. Methods We applied a literature search using PubMed to analyze the clinical data of 78 published cases of ETT. Results Women with ETT present at reproductive age (mean ± SD, 37.1 ± 8.7 years) and have a slightly to moderately elevated serum β-human chorionic gonadotropin (median, 665 IU/L). Epithelioid trophoblastic tumor is frequently present in the lower uterine segment/cervix (26/58 cases) and can be misdiagnosed as squamous cell carcinoma (6/26). Lung is the most common extrauterine site of ETT (5/11 with uterine ETT and 10/20 without uterine ETT). Kaplan-Meier analysis indicates that chemotherapy (surgery with postoperative chemotherapy vs surgery alone) is associated with increased ETT relapse (P = 0.005), even after stratification by International Federation of Gynecology and Obstetrics (FIGO) stage (P = 0.008); but FIGO stage remains the only significant prognostic indicator for ETT (P = 0.015). Conclusions This analysis confirms the hypothetical chemotherapy resistance and prognostic value of FIGO staging in ETT. These findings remain tentative given the small data set available for analysis and the reporting bias from these published cases; however, they may confer a risk-adapted therapy. Finally, both gynecologists and pathologists should be alert to the potential misdiagnosis of squamous cell carcinoma when ETT is present in the lower uterine segment/cervix.

Tumor suppressor gene insulin-like growth factor binding protein-related protein 1 (IGFBP-rP1) induces senescence-like growth arrest in colorectal cancer cells

Insulin-like growth factor binding protein-related protein 1 (IGFBP-rP1) is a potential tumor suppressor gene. This study attempted to explore a potential senescence-like role for IGFBP-rP1 in suppressing human colorectal cancer. Recombinant IGFBP-rP1 inhibited cell proliferation and induced G1 cell cycle arrest in RKO and CW2 cells. It induced a senescence-like phenotype by showing 2-fold higher beta-galactosidase activity in IGFBP-rP1-transfectants over that in control cells. Western blot confirmed down-regulation of phosphorylated retinoblastoma protein (pRB) and up-regulation of p53 in IGFBP-rP1-transfectants as compared with control cells. Thus, IGFBP-rP1 might be a key molecule in the cellular senescence pathway. Our results uncovered a novel molecular mechanism involving the altered expression of pRB and p53 for tumor suppressor gene IGFBP-rP1 in colorectal cancer. Restoration of IGFBP-rP1 function might have potential therapeutic significance in colorectal cancer.

TaqMan low density array is roughly right for gene expression quantification in colorectal cancer

BACKGROUND TaqMan low density array (LDA) is promising for high throughput screening in functional genomics by simultaneously measuring mRNA expression of multiple genes. However, the reproducibility and reliability remain to be explored. METHODS We applied LDA to detect mRNA expression of 95 gastrointestinal differentiation associated genes in 27 colorectal cancers with individual-matched normal mucosa. Conventional Q-PCR assay was done to detect 18 differentially expressed genes in additional 22 colorectal cancers. RESULTS A total of 97.2% (11,520/11,844) gene samples were successfully amplified by LDA. There was a perfect agreement between intra-LDA assays in all gene samples (CCC=0.952, p<0.0001). Seventy-nine genes showed perfect or substantial agreement between intra-LDA tests (CCC>0.713). Genes with low Ct values (<30 cycles) had more genes showing perfect agreement, less showing moderate agreement, and lower DeltaCt variances between intra-plate assays than that with high Ct values (>30 cycles) (p<0.01). All 18 genes showed the same directional changes in colorectal cancers versus normal mucosa by both SYBR Green and LDA approaches. CONCLUSIONS LDA is a roughly robust method for gene quantification in colorectal cancer, but its reproducibility decreased in low copy genes. Hence, we strongly recommend caution when analyzing LDA results of those low copy genes.

−8p12–23 and +20q Are Predictors of Subtypes and Metastatic Pathways in Colorectal Cancer: Construction of Tree Models Using Comparative Genomic Hybridization Data

A substantial body of evidence suggests the genetic heterogeneous pattern and multiple pathways in colorectal cancer initiation and progression. In this study, we construct a branching tree and multiple distance-based tree models to elucidate these genetic patterns and pathways in colorectal cancer by using a data set comprised of 244 cases of comparative genomic hybridization. We identify the six most common gains of chromosomal regions of 7p (37.0%), 7q11-32 (34.8%), 8q (48.3%), 13q (49.1%), 20p (36.1%), and 20q (50.4%), and the nine most common losses of 1p13-36 (30.9%), 4p15 (24.3%), 4q33-34 (24.3%), 8p12-23 (50.9%), 15q13-14 (23.5%), 15q24-25 (24.3%), 17p (34.8%), 18p (36.5%), and 18q (61.7%) in colorectal cancer. We classify colorectal cancer into two distinct groups: one preceding with -8p12-23, and the other with +20q. The sample-based classification tree also demonstrates that colorectal cancer can be classified into multiple subtypes marked by -8p12-23 and +20q. By comparing chromosomal abnormalities between primary and metastatic colorectal cancer, we identify five potential metastatic pathways: (-18q, -18p), (-8p12-23, -4p15, -4q33-34), (+20q, +20p), (+20q, +7p, +7q11-32), and +8q. -8p12-23 and +20q are inferred to be the two marker events of colorectal cancer metastasis. The current oncogenetic tree models may contribute to our understanding towards molecular genetics in colorectal cancer. Particularly, the metastatic pathways we describe may provide pivotal clues for metastatic candidate genes, and thus impact on the prediction and intervention of metastatic colorectal cancer.

A novel approach to detect differentially expressed genes from count-based digital databases by normalizing with housekeeping genes.

Sequence tag count-based gene expression analysis is potent for the identification of candidate genes relevant to the cancerous phenotype. With the public availability of count-based data, the computational approaches for differentially expressed genes, which are mainly based on Binomial or beta-Binomial distribution, become practical and important in cancer biology. It remains a permanent need to select a proper statistical model for these methods. In this study, we developed a novel Bayesian algorithm-based method, Electronic Differential Gene Expression Screener (EDGES), in which a statistical model was determined by geometric averaging of 12 common housekeeping genes. EDGES identified a set of differentially expressed genes in lung, breast and colorectal cancers by using publically available Serial Analysis of Gene Expression (SAGE) and Expressed Sequence Tag (EST data). Gene expression microarray analysis and quantitative reverse transcription real-time PCR demonstrated the effectiveness of this procedure. We conclude that current normalization of calibrators provides a new insight into count-based digital subtraction in cancer research.