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PubMed2003

Molecular differentiation of high- and moderate-grade human prostate cancer by cDNA microarray analysis.

The prognosis of men with moderate-grade prostate cancer is uncertain. At present, there are few if any reliable molecular markers that can distinguish moderate-grade tumors from those that behave more aggressively. To better understand the molecular basis of human prostate cancer and potentially provide information toward more accurate prognosis, we measured and analyzed gene expression profiles of 13 high- and moderate-grade human prostate tumors using cDNA microarrays. The expression of 136 genes was observed to differ significantly (P < 0.001) between normal prostate and tumors using one-sample t testing and Wilcoxon ranking. Hierarchical clustering of genes demonstrated a relatively similar pattern of differential expression across the tumors. However, importantly, permutation t tests (two-tailed P < 0.001) revealed 21 genes whose expression profiles segregated moderate- and high-grade tumors from each other, which was significantly (P < 0.03) greater than what was expected by chance. These results were compared in silico with prostate cancer profiling efforts performed by other groups, including a meta-analysis of four data sets, which validated many of the dysregulated genes. We suggest that these data provide insight into the molecular nature of clinically aggressive prostate cancer.

Adenocarcinoma↗

PubMed2004

Gene expression profiling of human adrenocortical tumors using complementary deoxyribonucleic Acid microarrays identifies several candidate genes as markers of malignancy.

The aim of this study was to identify predictor sets of genes whose over- or underexpression in human sporadic adrenocortical tumors would help to identify malignant vs. benign tumors and to predict postsurgical metastatic recurrence. For this, we analyzed the expression of 230 candidate genes using cDNA microarrays in a series of 57 well-characterized human sporadic adrenocortical tumors (33 adenomas and 24 carcinomas). We identified two clusters of genes (the IGF-II cluster containing eight genes, including IGF-II, and the steroidogenesis cluster containing six genes encoding steroidogenic enzymes plus eight other genes) whose combined levels of expression appeared to be good predictors of malignancy. This predictive value was as strong as that of the pathological score of Weiss. The analysis of the population of carcinomas (13 tumors) for genes whose expression would be strongly different between recurring and nonrecurring tumors allowed identification of 14 genes meeting these criteria. Among these genes, there are probably new markers of tumor evolution that will deserve additional validation on a larger scale. Taken together, these results show that the parallel analysis of the expression levels of a selected group of genes on microgram quantities of tumor RNA (a quantity that can be obtained from fine needle aspirations) appears as a complementary method to histopathology for the diagnosis and prognosis of evolution of adrenocortical carcinomas.

Adolescent↗

PubMed2005

Discovery of a new biomarker for gastroenterological cancers.

Various genomic technologies have been applied to address crucial problems in cancer biology, because cancer develops through the accumulation of various genetic alterations. Of these, gene expression profiling analysis using microarray technology has been widely applied not only to classify cancers at molecular levels, but also to identify novel molecular targets for therapeutics and/or diagnostics. To gain molecular understanding of gastric carcinogenesis, progression, and diversity, we analyzed primary advanced gastric cancer and noncancerous gastric tissues by high-density oligonucleotide microarray. Genes differentially expressed between cancer and noncancerous tissues were identified. In cancer tissues, genes related to cell cycle, growth factor, cell motility, cell adhesion, and matrix remodeling were highly expressed, whereas those related to gastrointestinal-specific function and immune response were rather downregulated. These results provide not only a new molecular basis for understanding biological properties of gastric cancer but also useful resources for future development of therapeutic and diagnostic biomarkers for gastric cancer. Several microarray studies have been published since and have been compared for validation in meta-analysis. As integration of transcriptome information with other biological data is crucial to interpret gene expression data, we have applied oligonucleotide microarray technology to assess allelic gene dosage at 10000 polymorphic loci, namely with an average interval of 200kb. Using a newly developed algorithm, genome imbalance map, loss of heterozygosity (LOH) status can be determined simultaneously. Besides several loci with genomic amplification, we also identified a homozygously deleted chromosomal region in 7q, where frequent chromosomal instability was observed. Finally, we are currently developing novel biomarkers for gastroenterological cancers. Glypican 3 is detected at high levels in serum of hepatocellular carcinoma patients and could be a potential target for antibody therapy.

Carcinoma, Hepatocellular↗

PubMed2006

Contrasting patterns of transcript abundance in tumour tissue and cancer cell lines.

Comparison of data on transcript abundance in ovarian, prostate and colon tumours with the corresponding cancer cell lines was used to assess the similarities of expression profiles. Although transcript abundances in tumours and cell lines were positively correlated, there were substantial differences with respect to the overall expression pattern. Compared with tumours, cancer cell lines showed more variable patterns of transcript abundance among tissue types. In the ovary and colon, cancer cell lines showed greater overall transcript abundance than normal tissue; this increase was much more marked in the case of the colon. However, in the prostate, cancer cell lines showed overall reduced transcript abundance when compared with normal tissue. Principal component analyses, applied separately to each tissue type, showed that approximately 80% of the variance was explained by overall expression level differences, which were maintained across normal tissue, tumour tissue and cancer cell lines. The remaining variance ( approximately 20%) could be attributed to contrasts in expression pattern among normal tissue, tumour tissue and cancer cell lines. In each dataset and in a combined dataset of transcripts shared among the three datasets, principal components revealed both contrasts in expression pattern between tumour tissue and cancer cell lines, and common features in the expression pattern of cancer cell lines that were distinct from those of tumour tissue and were shared across the different tissue types. These results imply that data on gene expression in cancer cell lines should be used with caution in inferring gene expression of in vivo tumours.

Biomarkers, Tumor↗

PubMed2007

Transcription profiling of adult and fetal human neuroprogenitors identifies divergent paths to maintain the neuroprogenitor cell state.

Global gene expression profiling was performed using RNA from adult human hippocampus-derived neuroprogenitor cells (NPCs) and multipotent frontal cortical fetal NPCs compared with adult human mesenchymal stem cells (hMSCs) as a multipotent adult stem cell control, and adult human hippocampal tissue, to define a gene expression pattern that is specific for human NPCs. The results were compared with data from various databases. Hierarchical cluster analysis of all neuroectodermal cell/tissue types revealed a strong relationship of adult hippocampal NPCs with various white matter tissues, whereas fetal NPCs strongly correlate with fetal brain tissue. However, adult and fetal NPCs share the expression of a variety of genes known to be related to signal transduction, cell metabolism and neuroectodermal tissue. In contrast, adult NPCs and hMSCs overlap in the expression of genes mainly involved in extracellular matrix biology. We present for the first time a detailed transcriptome analysis of human adult NPCs suggesting a relationship between hippocampal NPCs and white matter-derived precursor cells. We further provide a framework for standardized comparative gene expression analysis of human brain-derived NPCs with other stem cell populations or differentiated tissues. Disclosure of potential conflicts of interest is found at the end of this article.

Adolescent↗

PubMedDate not supplied

Genomic profiles in stage I primary non small cell lung cancer using comparative genomic hybridization analysis of cDNA microarrays.

To investigate the genomic aberrations that are involved in lung tumorigenesis and therefore may be developed as biomarkers for lung cancer diagnosis, we characterized the genomic copy number changes associated with individual genes in 14 tumors from patients with primary non small cell lung cancer (NSCLC). Six squamous cell carcinomas (SQCAs) and eight adenocarcinomas (ADCAs) were examined by high-resolution comparative genomic hybridization (CGH) analysis of cDNA microarray. The SQCAs and ADCAs shared common frequency distributions of recurrent genomic gains of 63 genes and losses of 72 genes. Cluster analysis using 57 genes defined the genomic differences between these two major histologic types of NSCLC. Genomic aberrations from a set of 18 genes showed distinct difference of primary ADCAs from their paired normal lung tissues. The genomic copy number of four genes was validated by fluorescence in situ hybridization of 32 primary NSCLC tumors, including those used for cDNA microarray CGH analysis; a strong correlation with cDNA microarray CGH data emerged. The identified genomic aberrations may be involved in the initiation and progression of lung tumorigenesis and, most importantly, may be developed as new biomarkers for the early detection and classification of lung cancer.

Adenocarcinoma↗

PubMed2005

Pharmacogenomics and clinical biomarkers in drug discovery and development.

The fields of pathology and clinical pharmacology are in an era of rapid evolution, reflecting continuous technological advancements in molecular diagnostics focused on improving drug efficacy and reducing toxicity. The discovery and refinement of the human genome sequence, further understanding of epigenetic events, and the expansion of proteomics research combined with emerging technologies such as functional imaging, biosensors, and sophisticated computational biology are having an unprecedented impact on the pharmaceutical industry. This review focuses on the discovery and development of DNA-based gene sequence tests and RNA-based gene expression profiles as applied to the prediction of response, resistance, and toxicity of both new and existing anticancer, cardiovascular, and anti-inflammatory drugs. This review will also consider the potential of emerging biomarkers designed to assist in the clinical development of these agents.

Biomarkers↗

PubMed2003

Overexpression of kallikrein 10 in epithelial ovarian carcinomas.

OBJECTIVE: We wanted to identify genes up-regulated in ovarian tumors that might serve as early markers for ovarian cancer. One promising focus is the family of genes that encode secreted proteases, which play essential roles in tumor invasion and metastasis. Kallikrein 10 (KLK10) is a member of the kallikrein family of serine proteases which include 15 proteins, including the prostate-specific antigen (PSA), also known as hK3. We investigated whether KLK10 and its related protein, hK10, might serve as equally accurate markers for ovarian carcinoma. METHODS: Transcriptional profiling was performed using RNA isolated from normal ovarian epithelium, ovarian cancer cell lines, and primary ovarian tumors. Microarray data were confirmed by Northern blot analysis of 66 ovarian tumor samples and 6 ovarian cancer cell lines. In situ hybridization and Western blot analysis confirmed the Northern blot findings. RESULTS: KLK10 was more highly expressed by primary ovarian tumors than by NOE. Thirty-two of 35 primary serous ovarian carcinoma samples (91.4%) expressed higher levels of KLK10 than NOE did. Eleven of 15 nonserous epithelial ovarian carcinoma samples (73.3%) and 8 of 11 primary peritoneal carcinoma samples (72.7%) also expressed KLK10. Overall, 84.8% of all epithelial ovarian and peritoneal carcinoma tumor samples showed elevated expression of KLK10. Similarly, Western blot analysis demonstrated that levels of the KLK10-related protein, designated hK10, are elevated in primary ovarian tissue lysates, but the protein is undetectable in immortalized ovarian epithelium. Finally, in situ hybridization established that KLK10 mRNA is much more highly expressed by tumor tissue than by normal epithelium and stromal tissues. CONCLUSIONS: Our data support recent immunoassay findings of elevated levels of hK10 in the tumor tissue and serum of ovarian cancer patients. Thus, it is likely that KLK10 and other kallikreins will serve as useful diagnostic and prognostic markers in patients with ovarian carcinoma.

Biomarkers, Tumor↗

PubMed2004

Altered gene expression in phenotypically normal renal cells from carriers of tumor suppressor gene mutations.

BACKGROUND: The inherently complex signaling networks of tumors result from genetic and epigenetic alterations that occur during cancer initiation and progression. METHODS: In an attempt to identify early molecular changes associated with dominantly inherited predisposition to "two-hit" renal tumors, the expression profiles of primary cultures of phenotypically normal renal epithelial cells from individuals bearing a germline mutation in either the von Hippel-Lindau (VHL) or the tuberous sclerosis complex (TSC) gene were compared to that of renal epithelial cells from control nonmutation carriers by microarray analysis. RESULTS: Reliability of the microarray data from pooled samples was confirmed by real-time RT-PCR. Principal Component Analysis revealed substantial differences in the gene expression profiles of the renal epithelial cells from VHL and TSC mutation carriers. In several instances, the microarray data confirm our present knowledge of the cellular pathways affected by biallelic VHL and TSC mutations. CONCLUSIONS: These findings demonstrate that heterozygosity for a mutant tumor suppressor gene may alter the expression profiles of phenotypically normal epithelial cells in a gene-specific manner. Detectable effects of "one-hit" represent early molecular changes in tumorigenesis that may serve as targets for chemopreventive intervention.

Biomarkers, Tumor↗

PubMed2004

Comparative transcriptional profiling of two human embryonic stem cell lines.

Human embryonic stem cells (ESCs) have generated enormous interest due to their ability to self-renew and produce many different cell types. In conjunction with microarray technology, human ESCs provide a powerful tool for employing a systems-based approach to deciphering the molecular mechanisms that control pluripotency and early development. Recent work has focused on defining "stemness" and pluripotency based on different experimental and analytical approaches in both mouse and human ESCs. Using a mixed linear model statistical approach, we report a stringent direct comparison between data sets obtained from two human ESCs (BG01 and H1) in order to obtain a list of genes that are enriched in ESCs. In addition, we used another pluripotent population derived from BG01 ESCs to obtain a list of genes that we consider important to the maintenance of pluripotency. A total of 133 genes overlapped between the three pluripotent populations. A majority of the 133 genes were classified under the key functional categories of cell-cycle regulation, signaling, and regulation of transcription. Key genes expressed were Oct4, Sox2, LeftyA, and Fgf2. Also found to be enriched in all three populations is FLJ10713, a gene encoding a hypothetical protein of unknown function that has been shown in earlier studies to possess a homolog in mouse ESCs and also to cluster tightly with Oct4 in human ESCs. Although there were many genes unique to each pluripotent population, they shared similarities based on functional ontologies that define pluripotency. The significance of our studies underscores the need for direct comparison of stem cell populations that share biological similarities using uniform stringent analytical approaches, in order to better define pluripotency. Our findings have important implications for the maintenance of pluripotency and in developing directed differentiation strategies for various regenerative applications.

Algorithms↗

PubMed2025

A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma.

BACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear. METHOD: Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database. RESULTS: A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes (p < 0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings. CONCLUSION: This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.

Humans↗

PubMed2005

Investigation of HMN-176 anticancer activity in human tumor specimens in vitro and the effects of HMN-176 on differential gene expression.

HMN-176, (E)-4-(2-[2-(N-[4-methoxybenzene-sulfonyl]amino)phenyl]ethenyl) pyridine 1-oxide, is a stilbene derivative which inhibits mitosis without significant effect on tubulin polymerization and displays potent cytotoxicity against a variety of human tumor cell lines. The present study evaluated the activity profile of the antineoplastic agent HMN-176 in an ex-vivo soft agar cloning assay (human tumor colony-forming assay) in a panel of 132 human tumor specimens under 14-day continuous exposure at 0.1, 1.0, and 10.0 microg/ml. Thirty percent of specimens in the different treatment groups (39/132 in 0.1 and 1.0 test groups; 40/132 in 10.0 test group) were assessable, falling within the negative and positive control parameters. At these dose levels, responses were observed in 32% (11/34), 62% (21/34), and 71% (25/35) of assessable specimens, respectively. HMN-176 demonstrated activity towards 75% of the breast cancer specimens (6/8) treated with 1.0 microg/ml, 67% of non small-cell lung (4/6) and 57% of ovarian (4/7) cancer specimens treated with 10 microg/ml. Low levels of cross-resistance to cisplatin, cyclophosphamide, 5-fluorouracil, and etoposide were also observed. There was a positive relationship between HMN-176 concentration and effect, demonstrating greatest overall activity at 10.0 microg/ml. Evaluation of differential gene expression in drug-sensitive (A2780) and drug-resistant (A2780cp) ovarian carcinoma cell lines exposed to 0.1 microg/ml HMN-176 up to 48 h using cDNA microarrays with 1,154 known human genes revealed significant drug effects on tumor associated genes, including upregulation of tissue inhibitor matrix metalloproteinases gene (TIMP) in both cell lines, suggesting that HMN-176 could potentially overcome tumor drug resistance. In conclusion, in vitro responses demonstrate efficacy at pharmacologically relevant concentrations, which suggests that HMN-176 deserves further evaluation in clinical trials.

Antineoplastic Agents↗

PubMed2004

Distinguishing key biological pathways between primary breast cancers and their lymph node metastases by gene function-based clustering analysis.

In order to identify key biological pathways that can distinguish between primary breast cancers and their lymph node metastases, we employed gene expression profiling together with gene function-based clustering analysis. We first acquired gene expression profiles of 9 matched primary tumors and the corresponding metastases that contained at least 75% of tumor cells. Then, we applied a clustering algorithm to the preprocessed data. In order to focus on the most informative genes, we ranked all the genes individually based on their abilities to separate the primary breast tumor and metastases samples. Further, we separated these genes into six functional groups according to the Stanford SOURCE database: 'cell cycle,' 'apoptosis,' 'metabolism,' 'cell adhesion and migration,' 'signal transduction,' and 'transcriptional factor and DNA binding molecules.' Unsupervised clustering analysis using all of the 2,303 genes on the microarrays was not able to separate the primary and metastases samples. Clustering analysis using the most informative genes revealed that primary tumors were more tightly clustered, whereas the metastases samples were relatively heterogeneous. The clustering analysis with the genes belonging to different functional groups showed that different functional gene sets varied in their abilities to separate primary tumors and their metastases. Marked separations were found with genes involved in metabolism, signal transduction, cell cycle, and transcriptional factor and DNA binding molecules. In contrast, apoptosis and cell adhesion and migration genes did not provide a clear separation of the two groups of samples. These results suggest that metastatic cells have different metabolism and signal transduction activities, regulated by transcriptional events, from the primary tumor cells. The results also suggest that the altered cell adhesion and migration potentials that are required for tumors to metastasize already exist in the primary tumors as a whole.

Biomarkers, Tumor↗

PubMed2006

Predictive factors for response to docetaxel in human breast cancers.

Docetaxel has come into wide use recently for the treatment of breast cancer in neoadjuvant, adjuvant and metastatic settings. Docetaxel binds to beta-tubulin and causes kinetic abnormalities in the dynamics of microtubules by increasing their polymerization and inhibiting their depolymerization, resulting in elevated levels of microtubule formation. During metaphase, defective spindle formation induced by docetaxel activates the mitotic checkpoint and leads to cell cycle arrest, culminating in apoptosis. However, docetaxel is not effective for all breast cancers. For example, in metastatic settings, the response rate to docetaxel reportedly ranges from 30 to 50%. It is therefore very important to develop a diagnostic method with high accuracy for the prediction of sensitivity to docetaxel in order to avoid unnecessary treatment. Currently it is impossible to identify, before the initiation of therapy, the patients for whom docetaxel will be effective. Various biological parameters have been studied clinically for their ability to predict response to docetaxel, such as parameters related to: (1) efflux (p-glycoprotein) and metabolism (CYP3A4); (2) beta-tubulin (somatic mutation of beta-tubulin and changes in beta-tubulin isotypes levels); (3) cell cycle (HER2, BRCA1 and Aurora-A); and (4) apoptosis (p53, BCL2 and thioredoxin). More recently, gene expression profiling techniques have been used for the development of a prediction model for response to docetaxel. In the present paper, clinical studies that have been conducted recently to identify predictive factors for response to docetaxel are reviewed together with a presentation of our recent work in this field.

Antineoplastic Agents, Phytogenic↗

PubMedDate not supplied

Monitoring gene expression profile changes in bladder transitional cell carcinoma using cDNA microarray.

PURPOSE: Differential gene expression profiles between normal bladder mucosas and bladder transitional cell carcinomas TCC were detected. MATERIALS AND METHODS: cDNA microarrays were prepared by spotting PCR products of 12,800 human genes onto specially treated glass slides. The cDNA probes were prepared by labeling normal bladder mucosa mRNA and TCC tissue mRNA with Cy3-dUTP and Cy5-dUTP respectively through reverse transcription. The arrays were then hybridized against the cDNA probe mixture and the fluorescent signals were scanned. The ratios of Cy5/Cy3 were computed. Northern analysis was used to confirm the results of microarray hybridization. RESULTS: Eighty-three genes (0.65%), whose ratios of Cy5/Cy3 were greater than 4.0 or less than 0.25, were screened out after 10 groups of hybridization. In the cancerous tissues 28 of them showed higher expression and 55 lower. Twenty-three genes are unregistered in GenBank. These differentially expressed genes are always involved in the physiological processes such as signal transduction, apoptosis and cell cycle, etc. CONCLUSIONS: This technique provides a powerful method for quantitative analysis of the expression levels of thousands of genes in parallel, and is used to identify genes involved in TCC carcinogenesis. The data obtained by this means are comparable to those obtained by other methods. Using cDNA microarrays to define alterations in gene expression associated with a specific cancer may be an efficient way to uncover the clues to specific molecular derangements that account for its pathogenesis and thus identify potential targets for therapeutic intervention.

Aged↗

PubMed2004

Can we identify a 'high risk' patient profile to determine who will experience rapid progression of osteoarthritis?

Disease modifying drugs for osteoarthritis (OA) that may halt or retard joint destruction and at the same time possibly improve symptoms are being developed and tested at various stages in clinical trials. This has, for at least two reasons, focused attention on the need for identification of patient groups at high risk for incident or progressive OA. First, well characterized such groups may be useful in clinical trials. Second, assuming that disease modifying OA drugs become available in the future, primary target groups in need of such therapy have to be identified. Risk factors for incident OA may differ from those for OA progression. Interactions between risk factors for OA is little understood. Factors that have consistently been reported as associated with radiographic OA progression are obesity, generalized OA, alignment and synovitis. Other factors such as bone scintigraphic lesions, joint injury nad biomarkers (such as type II collagen fragments, COMP and HA) show promise. Further evaluation of these variables and their individual and combined influence will be useful to design a risk profile for OA incidence and progression.

Biomarkers↗

PubMed2004

Neuronal gene expression and function in the growth-stimulated R28 retinal precursor cell line.

PURPOSE: Proliferative retinal progenitor cells that express neuronal characteristics are potentially useful for developmental studies and as experimental graft material. The continuously-growing R28 retinal cell line has been distributed to over 60 laboratories for a variety of studies, yet has not been fully characterized. In this study, we tested the hypothesis that the proliferative R28 retinal cell line contains subpopulations of cells that express neuronal mRNAs and proteins characteristic of CNS neurons. METHODS: To this end, we sought to determine the potential retinal, neuronal, and growth-related characteristics of this retinal cell line through gene expression profiling, coupled with confirmatory immunocytochemistry and electrophysiology. RESULTS: Despite expression of growth-stimulatory oncogenes and growth-promoting factors, subpopulations of R28 cells express abundant retinal and neuronal markers, as well as the functional capacity to respond to specific neurotransmitters such as dopamine, acetylcholine, serotonin, and glycine. CONCLUSION: Proliferative R28 cells retain functional neuronal properties that may prove useful in future studies of neuronal differentiation and development.

Animals↗

PubMed2005

Phenotypic profiling of engineered mouse melanomas with manipulated histamine production identifies histamine H2 receptor and rho-C as histamine-regulated melanoma progression markers.

In the present study, the impact of acquired neoplastic L-histidine decarboxylase (HDC) expression, and its direct consequence, the release of histamine in the tumor environment, was assessed on melanoma tumor progression. B16-F10 mouse melanoma cells were manipulated via stable transfection, and nine novel transgenic variants were generated in triplicates, constitutively expressing the full-length sense mouse HDC mRNA, a mock control, and an antisense HDC RNA segment, respectively. Establishing both primary skin tumors and lung metastases in C57BL/6 mice, the nine variants with different histamine-releasing capacities were subjected to a comprehensive comparative progression profiling in vivo. Our analyses showed trends of markedly accelerated tumor growth (P < 0.001), and moderately increased metastatic colony-forming potential (P = 0.010) along with rising levels of local histamine production. Using RNase protection assay for screening of the melanoma progression profile, and Western blotting for subsequent result validation, we looked for molecular progression markers affected by melanoma histamine secretion. Investigation of 21 functionally clustered markers associated with tumor proliferation, angiogenesis, invasivity, metastasis formation, local or systemic immunomodulation, and histamine signaling revealed positive correlations between histamine production, tumor histamine H2 receptor and rho-C expression (P < 0.001, P = 0.002, respectively). These observations confirm the involvement of histamine in the molecular machinery of melanoma progression.

Animals↗