Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer

The development of reliable gene expression profiling technology is having an increasing impact on our understanding of lung cancer biology. Our study aimed to determine any correlation between the phenotypic heterogeneity and genetic diversity of lung cancer. Microarray analysis was performed on a set of 46 tumor samples and 45 paired nontumor samples of nonsmall cell lung cancer (NSCLC) samples to establish gene signatures in primary adenocarcinomas and squamous-cell carcinomas, determine differentially expressed gene sequences at different stages of the disease and identify sequences with biological significance for tumor progression. After the microarray analysis, the expression level of 92 selected genes was validated by qPCR and the robust Bonferroni test in an independent set of 70 samples composed of 48 tumor samples and 22 nontumor samples. Gene sequences were differentially expressed as a function of tumor type, stage and differentiation grade. High upregulation was observed for KRT15 and PKP1, which may be good markers to distinguish squamous-cell carcinoma samples. High downregulation was observed for DSG3 in stage IA adenocarcinomas.     

Gene expression profiling of renal medullary carcinoma: potential clinical relevance

BACKGROUND: Renal medullary carcinoma is a rare kidney tumor with highly aggressive behavior. This tumor occurs exclusively in young patients with sickle cell trait or disease. To the authors' knowledge, very little is known to date regarding the underlying molecular genetics of this tumor, and no effective therapy has been established. METHODS: The authors analyzed the gene expression profiles of 2 renal medullary carcinomas from patients with sickle cell trait using microarrays containing 21,632 cyclic DNA (cDNA) clones and compared them with the gene expression profiles of 64 renal tumors. RESULTS: Based on global gene clustering with 3583 selected cDNAs, the authors found a distinct molecular signature of renal medullary carcinoma, which clustered closely with urothelial (transitional cell) carcinoma of the renal pelvis, rather than renal cell carcinoma (RCC). This finding of a significant difference in the gene expression patterns of renal medullary carcinoma compared with RCC suggests that this tumor should not be treated as a conventional RCC but, rather, as a special malignancy. This study also identified genes/proteins that may serve as biomarkers for renal medullary carcinoma or as potential targets of novel therapies. In addition, comparative genomic microarray analysis allowed the authors to predict the lack of chromosomal imbalances in this tumor. CONCLUSIONS: To the authors' knowledge, the current study is the first molecular profiling of renal medullary carcinoma, a rare but highly aggressive kidney carcinoma. The genes that are expressed specifically in this tumor may lead to not only a better understanding of its molecular pathways and discoveries of novel diagnostic markers but also, more important, to effective therapeutic interventions.     

Gene expression profiling of human HBV- and/or HCV-associated hepatocellular carcinoma cells using expressed sequence tags

Liver cancer is one of the leading causes of cancer death worldwide. To identify novel target genes that are related to liver carcinogenesis, we examined new genes that are differentially expressed in human hepatocellular carcinoma (HCC) cell lines and tissues based on the expressed sequence tag (EST) frequency. Eleven libraries were constructed from seven HCC cell lines and three normal liver tissue samples obtained from Korean patients. An analysis of gene expression profiles for HCC was performed using the frequency of ESTs obtained from these cDNA libraries. Genes were identified (n=120) as being either up- or down-regulated in human liver cancer cells. Among these, 14 genes (FTL, K-ALPHA1, LDHA, RPL4, ENO1, ANXA2, RPL9, RPL10, RPL13A, GNB2L1, AMBP, GC, A1BG, and SERPINC1), in addition to previously well-known liver cancer related genes, were confirmed to be differentially expressed in seven liver cancer cell lines and 17 HCC tissues by semi-quantitative RT-PCR. In addition, 73 genes, in which there was a significant difference (P>0.99) between HBV- and HCV-associated HCC cells, were selected. Of these, expression patterns of 14 (RPLP0, AKR1C, KRT8, GPX4, RPS15, ID1, RPS21, VIM, EEF1G, EIF4A1, HLA-C, FN1, CD44, and RPS10) were confirmed by semi-quantitative RT-PCR in four of HBV- and three of HCV-associated HCC cell lines. Among those genes, an immunohistochemical analysis for ANXA2 showed that it is expressed at high levels in HCC. Using an analysis of EST frequency, the newly identified genes, especially ANXA2, represent potential biomarkers for HCC and useful targets for elucidating the molecular mechanisms associated with HCC involving virological etiology.     

Identification of potential prognostic biomarkers for hepatocellular carcinoma

BackgroundThe incidence of liver cancer is increasing every year. Hepatocellular carcinoma (HCC) accounts for nearly 90% of liver cancer, and the overall 5-year survival rate of become of Hepatocellular carcinoma patients less than 20%. However, the molecular mechanism of HCC progression and prognosis still requires further exploration.MethodsIn this study, we downloaded the gene expression data from the Cancer Genome Atlas (TCGA) Genomic Data and the official website of GEO database. Weighted gene co-expression network analysis (WGCNA) and Pearson’s correlation coefficient were utilized to detect the gene modules. The shared differentially-expressed genes (DEGs) were screened out by a Venn diagram, and the hub genes were identified through protein-protein interaction (PPI) network analyses. GO and KEGG enrichment analyses were constructed for these hub genes. Overall survival (OS) and correlation analysis were conducted to investigate the relationship between the hub genes and clinical features.ResultsWe screened out 27 shared DEGs, and the mainly enriched GO terms were mitotic nuclear division, chromosomal region, and tubulin binding. Furthermore, the top three enriched KEGG pathways were “cell cycle”, “oocyte meiosis”, and “p53 signaling pathway”. According to the Maximal Clique Centrality (MCC) algorithm, the top 10 candidate hub genes were MYC, MCM3, CDC20, CCNB1, BIRC5, UBE2C, TOP2A, RRM2, TK1, and PTTG1, among which BIRC5, CDC20, and UBE2C showed a strong correlation with the OS.ConclusionsThree hub genes (BIRC5, CDC20, and UBE2C) were identified and found to be correlated to the progression and prognosis of HCC. These may become potential targets for HCC therapy.     

PCR-array gene expression profiling of hepatocellular carcinoma

Many trials using DNA microarrays have been reported for various human malignancies, but an efficient molecular diagnostic system has yet to be established. Here, we adopted a high throughput quantitative PCR-array system based on adaptor-tagged competitive PCR (ATAC-PCR), as a novel technique for gene expression profiling of hepatocellular carcinoma (HCC). This PCR-array contained 3,072 genes derived from three different cDNA libraries, including 298 additional known genes suspected to be involved in hepatocarcinogenesis. Using this PCR-array with 20 pairs of liver tissues (20 HCC, 20 surrounding nontumor liver), we identified a total of 117 genes differing in expression levels in the two liver tissues. Hierarchical clustering analysis and principal component analysis with these genes revealed distinct gene expression patterns in the HBV-positive group and the HCV-positive groups. Among 117 genes, only 7 (GPAA1, TMEM9, FACL4, ADFP, MAWBP, PACE4, FOS) were common to both groups. In conclusion, this PCR-array analysis with an appropriate set of genes is considered useful for gene expression profiling of HCC, and we identified some genes which may play a common key role in hepatocarcinogenesis.     

The competitive endogenous RNA regulatory network reveals potential prognostic biomarkers for overall survival in hepatocellular carcinoma

The aim of the present study is to construct a competitive endogenous RNA (ceRNA) regulatory network by using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with hepatocellular carcinoma (HCC), and to construct a prognostic model for predicting overall survival (OS) of HCC patients. Differentially expressed lncRNAs, miRNAs, and mRNAs were explored between HCC tissues and normal liver tissues. A prognostic model was built for predicting OS of HCC patients and receiver operating characteristic curves were used to evaluate the performance of the prognostic model. There were 455 differentially expressed lncRNAs, 181 differentially expressed miRNAs, and 5035 differentially expressed mRNAs. A ceRNA regulatory network was constructed based on 43 lncRNAs, 37 miRNAs, and 105 mRNAs. Eight mRNA biomarkers (H2AFX, SQSTM1, ITM2A, PFKP, TPD52L1, ACSL4, STRN3, and CPEB3) were identified as independent risk factors by multivariate Cox regression and were used to develop a prognostic model for OS. The C‐indexes in the model group were 0.776 (95% confidence interval [CI], 0.730‐0.822), 0.745 (95% CI, 0.699‐0.791), and 0.789 (95% CI, 0.743‐0.835) for 1‐, 3‐, and 5‐year OS, respectively. The current study revealed potential molecular biological regulation pathways and prognostic biomarkers by the ceRNA regulatory network. A prognostic model based on prognostic mRNAs in the ceRNA network might be helpful to predict the individual mortality risk for HCC patients. The individual mortality risk calculator can be used by visiting the following URL: https://zhangzhiqiao.shinyapps.io/Smart_cancer_predictive_system_HCC/ .     

Future of molecular profiling of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a fatal disease occurring worldwide and developing mainly in chronic liver diseased patients. Despite routine screening of individuals at high risk, most of the patients are diagnosed at late stages of HCC. In addition, the recurrence rate after surgical resection of small tumors is high. Molecular profiling, including expression analysis, comparative genomics and proteomics, provides powerful tools to gain insight into the molecular mechanisms underlying carcinogenesis. Advances in bioinformatics have also allowed for the evaluation of large data sets. Therefore, molecular profiling of HCC using a Biological Expression Network Discovery (BLEND) strategy that integrates global molecular profiling data, including mRNA, miRNA, DNA methylation and DNA copy numbers from both the tumor and the surrounding microenvironment, along with mechanistic studies, may improve the diagnosis, treatment and prognosis of HCC patients. Such an approach will provide mechanistic insight into the pathogenesis of HCC, potentially leading to personalized medicine and the identification of new therapeutic targets.     

Gene microarray analysis reveals a novel hypoxia signal transduction pathway in human hepatocellular carcinoma cells.

The molecular details of hypoxia-induced cellular responses have been difficult to identify since there is as yet no known oxygen receptor. We used cDNA microarray technology to extend our studies pertaining to these molecular details in human hepatocellular carcinoma (Hep3B) cells that produce erythropoietin (Epo) in response to hypoxia. Of approximately 1200 genes in the array, those associated with integrin-linked kinase (ILK), fibronectin precursor and glycogen synthase kinase-3beta (GSK-3beta) were markedly stimulated after exposure of Hep3B cells to low oxygen (1%) for 6 h. Epo, HIF-1, and von Hippel-Lindau cDNAs were measured in parallel as markers of low oxygen responses in Hep3B cells. ILK is a serine, threonine protein kinase that interacts with the cytoplasmic domains of integrin beta1 and beta3. This interaction localizes ILK to focal adhesion plaques. ILK is stimulated by cell-fibronectin interaction as well as insulin. It is regulated in a phosphatidylinositol 3-kinase dependent manner and can phosphorylate protein kinase B (PKB/AKT) and GSK-3beta. As a result of these and other activities ILK has been shown to affect anchorage-independent cell survival, cell cycle progression and tumorigenesis in nude mice. ILK has also been implicated in the Wnt pathway and as a critical target in PTEN-dependent tumor therapies. To our knowledge this is the first report implicating the ILK pathway in low oxygen responses. Other genes identified as a result of the microarray analysis not previously known to change as a result of low oxygen treatment were elongation factor-1alpha, glycyl-tRNA synthetase, and laminin receptor protein-1. These findings were all corroborated by RT-PCR assays and in some instances Western blot analysis.     

Lipidomic profiling of exosomes from colorectal cancer cells and patients reveals potential biomarkers

Strong evidence suggests that differences in the molecular composition of lipids in exosomes depend on the cell type and has an influence on cancer initiation and progression. Here, we analyzed by liquid chromatography–mass spectrometry (LC‐MS) the lipidomic signature of exosomes derived from the human cell lines normal colon mucosa (NCM460D), and colorectal cancer (CRC) nonmetastatic (HCT116) and metastatic (SW620), and exosomes isolated from the plasma of nonmetastatic and metastatic CRC patients and healthy donors. Analysis of this exhaustive lipid study highlighted changes in some molecular species that were found in the cell lines and confirmed in the patients. For example, exosomes from primary cancer patients and nonmetastatic cells compared with healthy donors and control cells displayed a common marked increase in phosphatidylcholine (PC) 34 : 1, phosphatidylethanolamine (PE) 36 : 2, sphingomyelin (SM) d18 : 1/16 : 0, hexosylceramide (HexCer) d18 : 1/24 : 0 and HexCer d18 : 1/24 : 1. Interestingly, these same lipids species were decreased in the metastatic cell line and patients. Further, levels of PE 34 : 2, PE 36 : 2, and phosphorylated PE p16 : 0/20 : 4 were also significantly decreased in metastatic conditions when compared to the nonmetastatic counterparts. The only molecule species found markedly increased in metastatic conditions (in both patients and cells) when compared to controls was ceramide (Cer) d18 : 1/24 : 1. These decreases in lipid species in the extracellular vesicles might reflect function‐associated changes in the metastatic cell membrane. Although these potential biomarkers need to be validated in a larger cohort, they provide new insight toward the use of clusters of lipid biomarkers rather than a single molecule for the diagnosis of different stages of CRC.     

Gene expression profiling of human ovarian tumours

There is currently a lack of reliable diagnostic and prognostic markers for ovarian cancer. We established gene expression profiles for 120 human ovarian tumours to identify determinants of histologic subtype, grade and degree of malignancy. Unsupervised cluster analysis of the most variable set of expression data resulted in three major tumour groups. One consisted predominantly of benign tumours, one contained mostly malignant tumours, and one was comprised of a mixture of borderline and malignant tumours. Using two supervised approaches, we identified a set of genes that distinguished the benign, borderline and malignant phenotypes. These algorithms were unable to establish profiles for histologic subtype or grade. To validate these findings, the expression of 21 candidate genes selected from these analyses was measured by quantitative RT-PCR using an independent set of tumour samples. Hierarchical clustering of these data resulted in two major groups, one benign and one malignant, with the borderline tumours interspersed between the two groups. These results indicate that borderline ovarian tumours may be classified as either benign or malignant, and that this classifier could be useful for predicting the clinical course of borderline tumours. Immunohistochemical analysis also demonstrated increased expression of CD24 antigen in malignant versus benign tumour tissue. The data that we have generated will contribute to a growing body of expression data that more accurately define the biologic and clinical characteristics of ovarian cancers.     

Gene expression profiling of circulating CD133+ cells of hepatocellular carcinoma patients associated with HCV infection

Aim

Identifying the genetic expression profile of CD133⁺ cells from HCC patients compared to CD133⁺ cells from healthy volunteers that may contribute in hepatocarcinogenesis process.

Protein expression profiling identifies maspin and stathmin as potential biomarkers of adenoid cystic carcinoma of the salivary glands

Adenoid cystic carcinoma (ACC) is one of the most common malignant tumors of the salivary glands. It tends to grow slowly but is associated with a poor prognosis compared to other malignant salivary gland tumors. To identify specific markers of ACC, we examined protein expression profiling in ACC xenograft and normal salivary glands (NSG) using fluorescent 2-dimensional differential in-gel electrophoresis (2-D-DIGE), an emerging technique for comparative proteomics, that improves the reproducibility and reliability of differential protein expression analysis between the samples. To identify the proteins, matrix-assisted laser desorption/ionization time-of-flight peptide mass fingerprinting was carried out. Using these strategies, we detected 4 upregulated proteins and 5 downregulated proteins in ACC xenograft. Maspin and stathmin were selected for further analyses. Western blotting and immunohistochemical staining showed a higher expression of these proteins in ACC xenograft and clinical ACC tissue compared to NSG. Furthermore, Expression of these proteins was correlated with the histologic grading of ACC (n = 10). Therefore, our data indicate that maspin and stathmin may be not only useful biomarkers of ACC but also markers of biologic behavior in this tumor.     

不同转移潜能人肝癌细胞系的基因表达分析

目的：比较不同转移潜能人肝癌细胞系的基因表达谱,寻找与癌转移相关的基因表达改变。方法：采用基因芯片技术,比较遗传背景相同但转移力有明显差异的两个细胞系MHCC97－L和HCCLM3,分析其基因表达谱的差异。结果：在1626个候选基因中,筛选出25个差异表达基因。HCCLM3与MHCC97－L相比,表达上调的基因有8个,包括细胞增生基因E25、信号传导基因NKK6和免疫相关基因SP40,40等;下调的有17个,包括细胞周期调控基因Rb2、信号传导基因PKCβ2和错配修复基因hMSH2等。结论：肝癌转移是多基因作用的综合结果,筛选的基因对预测转移和抗转移干预措施可能有指导意义。     

HLA expression in human hepatocellular carcinoma

This study examines the expression of MHC class I and II antigens and their related invariant chains in 70 cases of human hepatocellular carcinoma (HCC), using monoclonal (Mabs) and polyclonal antibodies. In comparison with normal hepatocytes, the majority (94.3%) of HCCs show enhancement or acquisition of HLA-A, B, C in either a cytoplasmic or membranous distribution, with staining being uniformly distributed throughout the specimen. HLA-A, B, C was accompanied by beta 2-microglobulin expression in all but two cases. Although 44.9% of specimens showed HLA-DR expression, positively staining tumour cells were often sparse and heterogeneously distributed. By contrast, the invariant (I) chain, present in 47.1% of cases, was frequently intensively stained and extensive in distribution. HLA-DR staining was usually cytoplasmic although two cases showed faint membranous enhancement. In addition to HLA-DR and I-chain, two cases also showed HLA-DQ staining. Display of MHC antigens was not related to tumour differentiation or size of the lesion (resected vs. advanced tumours). It is possible that the acquisition of class I antigens by the majority of HCCs may influence tumour behaviour.     

Reduced expression of syndecan-1 in human hepatocellular carcinoma with high metastatic potential

Syndecans comprise a gene family of transmembrane proteoglycans that regulate cellular behavior through interactions with various effectors, including heparin-binding growth factors and insoluble matrix components. Syndecan-1, the most extensively studied, localizes in epithelial cells and has been shown to present in normal hepatocytes. However, little is known about the change of syndecan-1 expression in human hepatocellular carcinoma (HCC). We investigated syndecan-1-protein expression by immunohistochemistry in 57 HCC tissue samples. Syndecan-1 gene expression was also determined. Syndecan-1 protein was expressed in cytoplasm and cell membrane of the hepatocytes and in the bile duct epithelial cells of liver with underlying hepatitis and cirrhosis. Conversely, among 57 HCC tissues, 39 HCC (68.4%) showed negative staining; 50% of well-differentiated HCC showed positive staining, whereas 82.4% of poorly differentiated HCC were negative. Loss of syndecan-1-protein expression was more prevalent in HCC with intra-hepatic metastasis (85.2%) than those without metastasis (48.0%). Similarly, syndecan-1 expression was significantly reduced in HCC with extra-hepatic metastasis (91.7%) as compared with the HCC without extra-hepatic metastasis (62.2%). The gene expression of syndecan-1 was significantly lower in HCC tissue than that in non-tumoral liver tissue. In 2 human HCC cell lines with poorly differentiated phenotype, HLE and HLF, syndecan-1 expression was markedly decreased both at the mRNA and the protein levels. These results suggest that the loss of syndecan-1 expression is a characteristic feature of HCC with high metastatic potential. Int. J. Cancer 74:482–491, 1997. © 1997 Wiley-Liss, Inc.     

Circulating biomarkers in hepatocellular carcinoma

Purpose

Our aims are to determine levels of circulating cellular and protein biomarkers in hepatocellular carcinoma (HCC) patients and to analyse any relationships with clinical parameters.

Methods

Fifty-four consenting patients were recruited. Circulating tumour cells (CTCs) were enumerated (by CellSearch) and characterised via filtration [by isolation by size of epithelial tumour cells (ISET)] with downstream immunohistochemistry (IHC). Glypican-3 (GPC3) expression in tumour biopsies and CTCs (by IHC) was compared, and levels of circulating caspase-cleaved and full-length cytokeratin 18 (CK18, measured using M30 and M65 ELISAs) were examined as a putative prognostic factor and marker of tumour burden.

Results

CTCs were identified in 14 out of 50 (28 %) patients by CellSearch and in 19 out of 19 (100 %) patients by ISET. The presence of GPC3-positive CTCs by ISET was 100 % concordant with the presence of GPC3-positive cells in the original tumour (n = 5). No statistically significant correlations were observed between CTC number and clinical characteristics, although trends were noted between CTC subtypes, Child–Pugh score and tumour node metastasis stage. Serum M30 and M65 levels (as continuous variables) significantly correlated with overall survival (OS) in a univariate analysis (p = 0.003 and p < 0.001, respectively); M65 levels remained statistically significant in a multivariate analysis (p = 0.029).

Conclusions

This is the first study to detect GPC3-positive CTCs in HCC, important for drug development with this target. The significant association of circulating CK18 with OS in HCC further exemplifies the utility of circulating biomarkers in cancer.     

Identification of genes associated with dedifferentiation of hepatocellular carcinoma with expression profiling analysis.

To identify the genes associated with dedifferentiation of hepatocellular carcinoma (HCC), gene expression profiles of HCCs of well-and moderately differentiated grades were compared by means of oligonucleotide arrays. One tumor showed a nodule-in-nodule appearance (NIN), which is occasionally observed in the course of progression of HCC from well to less differentiated grade, when an inner, moderately differentiated tumor (MD) develops sequentially from the outer, well-differentiated tumor (WD). Seventy-six genes were identified to be up-regulated more than 3-fold and 33 genes were down-regulated in the inner nodule in NIN. By statistical analysis of the profiles from 10 individual additional liver tumors, 5 WDs and 5 MDs, we were able to identify 12 genes, LAMA3, PPIB, ADAR, PSMD4, NDUFS8, D9SVA, CCT3, GBAP, ARD1, RDBP, CSRP2, and TLE1, with significantly elevated expression, and 4 genes, CP, IL7R, CD48, and PLGL, with decreased expression in MD. These selected genes were further validated using another 12 tumors, 5 WDs and 7 MDs, with semi-quantitative RT-PCR. We also applied neighborhood analysis to list the genes with high predictability values as most closely correlated with WD-MD distinction. Seven genes, ADAR, PSMD4, D9SVA, CCT3, GBAP, RDBP, and CSRP2, whose expression was elevated and one gene, IL7R, whose expression was decreased, were included among the top 50 predictor genes. These genes are likely to be associated with dedifferentiation of HCC and their identification may help to elucidate the mechanism of liver cancer progression.