Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance.

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC. We identified 1256 non-redundant proteins, and 456 of these were quantified. Further analysis identified 29 proteins that were differentially expressed (12 overexpressed and 17 underexpressed) in metastatic and primary RCC. Dysregulated protein expressions of profilin-1 (Pfn1), 14-3-3 zeta/delta (14-3-3ζ), and galectin-1 (Gal-1) were verified on two independent sets of tissues by means of Western blot and immunohistochemical analysis. Hierarchical clustering analysis showed that the protein expression profile specific for metastatic RCC can distinguish between aggressive and non-aggressive RCC. Pathway analysis showed that dysregulated proteins are involved in cellular processes related to tumor progression and metastasis. Furthermore, preliminary analysis using a small set of tumors showed that increased expression of Pfn1 is associated with poor outcome and is a potential prognostic marker in RCC. In addition, 14-3-3ζ and Gal-1 also showed higher expression in tumors with poor prognosis than in those with good prognosis. Dysregulated proteins in metastatic RCC represent potential prognostic markers for kidney cancer patients, and a greater understanding of their involved biological pathways can serve as the foundation of the development of novel targeted therapies for metastatic RCC.

The chromatin remodeling gene ARID1A is a new prognostic marker in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common tumor of the adult kidney, with an increasing rate of incidence. Recently, exome sequencing studies have revealed that the SWI/SNF (switch/sucrose nonfermentable) members PBRM1 and ARID1A are mutated in ccRCC, and it has also been suggested that aberrant chromatin regulation is a key step in kidney cancer pathogenesis. Herein, we show that down-regulation of another SW/SNF component, ARID1A, occurs frequently in ccRCC. We detected copy number loss of ARID1A in 16% of patients with ccRCC. Immunohistochemistry indicated that 67% of ccRCC (53 of 79) had significantly lower expression of BAF250a, the protein product of ARID1A, than did the matched normal kidney cortex. In parallel, we conducted in silico mRNA expression analysis on 404 ccRCC tumors and 167 normal kidney cortex samples using publicly available databases and confirmed significant down-regulation of ARID1A in 68.8% of patients. We also show that decreased BAF250a protein and ARID1A mRNA expression correlate with tumor stage and grade. Our results indicate that both the protein and mRNA levels of ARID1A are statistically significant prognostic markers for ccRCC. Even after controlling for other confounders in the multivariate analysis, BAF250 retained its prognostic significance. BAF250a IHC is easy to perform and represents a potential biomarker that could be incorporated in laboratory practice to enhance the accuracy of the existing prognostic models.

Identification and validation of dysregulated metabolic pathways in metastatic renal cell carcinoma.

Metastatic renal cell carcinoma (mRCC) is a devastating disease with a 5-year survival rate of approximately 9 % and low response to chemotherapy and radiotherapy. Targeted therapies have slightly improved patient survival, but are only effective in a small subset of patients, who eventually develop resistance. A better understanding of pathways contributing to tumor progression and metastasis will allow for the development of novel targeted therapies and accurate prognostic markers. We performed extensive bioinformatics coupled with experimental validation on proteins dysregulated in mRCC. Gene ontology analysis showed that many proteins are involved in oxidation reduction, metabolic processes, and signal transduction. Pathway analysis showed metabolic pathways are altered in mRCC including glycolysis and pyruvate metabolism, the citric acid cycle, and the pentose phosphate pathway. RT-qPCR analysis showed that genes involved in the citric acid cycle were downregulated in metastatic RCC while genes of the pentose phosphate pathway were overexpressed. Protein-protein interaction analysis showed that most of the 198 proteins altered in mRCC clustered together and many were involved in glycolysis and pyruvate metabolism. We identified 29 reported regions of chromosomal aberrations in metastatic disease that correlate with the direction of protein dysregulation in mRCC. Furthermore, 36 proteins dysregulated in mRCC are predicted to be targets of metastasis-related miRNAs. A more comprehensive understanding of the pathways dysregulated in metastasis can be useful for the development of new therapies and novel prognostic markers. Also, multileveled analyses provide a unique "snapshot" of the molecular "environment" in RCC with prognostic and therapeutic implications.

The miRNA-kallikrein axis of interaction: a new dimension in the pathogenesis of prostate cancer.

Kallikrein-related peptidases (KLKs) are a family of serine proteases that were shown to be useful cancer biomarkers. KLKs have been shown to be dysregulated in prostate cancer (PCa). microRNAs (miRNAs) are short RNA nucleotides that negatively regulate gene expression and have been reportedly dysregulated in PCa. We compiled a comprehensive list of 55 miRNAs that are differentially expressed in PCa from previous microarray analysis and published literature. Target prediction analyses showed that 29 of these miRNAs are predicted to target 10 KLKs. Eight of these miRNAs were predicted to target more than one KLK. Quantitative real-time (qRT)-PCR demonstrated that there was an inverse correlation pattern in the expression (normal vs. cancer) between dysregulated miRNAs and their target KLKs. In addition, we experientially validated the miRNA-KLK interaction by transfecting miR-331-3p and miR-143 into a PCa cell line. Decreased expression of targets KLK4 and KLK10, respectively, and decreased cellular growth were observed. In addition to KLKs, dysregulated miRNAs were predicted to target other genes involved in the pathogenesis of PCa. These data show that miRNAs can contribute to KLK regulation in PCa. The miRNA-KLK axis of interaction projects a new element in the pathogenesis of PCa that may have therapeutic implications.

Exploring the role of miRNAs in renal cell carcinoma progression and metastasis through bioinformatic and experimental analyses.

Metastasis results in most of the cancer deaths in clear cell renal cell carcinoma (ccRCC). MicroRNAs (miRNAs) regulate many important cell functions and play important roles in tumor development, metastasis and progression. In our previous study, we identified a miRNA signature for metastatic RCC. In this study, we validated the top differentially expressed miRNAs on matched primary and metastatic ccRCC pairs by quantitative polymerase chain reaction. We performed bioinformatics analyses including target prediction and combinatorial analysis of previously reported miRNAs involved in tumour progression and metastasis. We also examined the co-expression of the miRNAs clusters and compared expression of intronic miRNAs and their host genes. We observed significant dysregulation between primary and metastatic tumours from the same patient. This indicates that, at least in part, the metastatic signature develops gradually during tumour progression. We identified metastasis-dysregulated miRNAs that can target a number of genes previously found to be involved in metastasis of kidney cancer as well as other malignancies. In addition, we found a negative correlation of expression of miR-126 and its target vascular endothelial growth factor (VEGF)-A. Cluster analysis showed that members of the same miRNA cluster follow the same expression pattern, suggesting the presence of a locus control regulation. We also observed a positive correlation of expression between intronic miRNAs and their host genes, thus revealing another potential control mechanism for miRNAs. Many of the significantly dysregulated miRNAs in metastatic ccRCC are highly conserved among species. Our analysis suggests that miRNAs are involved in ccRCC metastasis and may represent potential biomarkers.

miRNA profiling for clear cell renal cell carcinoma: biomarker discovery and identification of potential controls and consequences of miRNA dysregulation.

PURPOSE: Renal cell carcinoma is the most common neoplasm of the adult kidney. Currently to our knowledge there are no biomarkers for diagnostic, prognostic or predictive applications for renal cell carcinoma. miRNAs are nonprotein coding RNAs that negatively regulate gene expression and are potential biomarkers for cancer. MATERIALS AND METHODS: We analyzed 70 matched pairs of clear cell renal cell carcinoma and normal kidney tissues from the same patients by microarray analysis and validated our results by quantitative real-time polymerase chain reaction. We also performed extensive bioinformatic analysis to explore the role and regulation of miRNAs in clear cell renal cell carcinoma. RESULTS: We identified 166 miRNAs that were significantly dysregulated in clear cell renal cell carcinoma, including miR-122, miR-155 and miR-210, which had the highest over expression, and miR-200c, miR-335 and miR-218, which were most down-regulated. Analysis of previously reported miRNAs dysregulated in RCC showed overall agreement in the direction of dysregulation. Extensive target prediction analysis revealed that many miRNAs were predicted to target genes involved in renal cell carcinoma pathogenesis. In renal cell carcinoma miRNA dysregulation can be attributed in part to chromosomal aberrations, co-regulation of miRNA clusters and co-expression with host genes. We also performed a preliminary analysis showing that miR-155 expression correlated with clear cell renal cell carcinoma size. This finding must be validated in a larger independent cohort. CONCLUSIONS: Analysis showed that miRNAs are dysregulated in clear cell renal cell carcinoma and may contribute to kidney cancer pathogenesis by targeting more than 1 key molecule. We identified mechanisms that may contribute to miRNA dysregulation in clear cell renal cell carcinoma. Dysregulated miRNAs represent potential biomarkers for kidney cancer.

MicroRNAs: exploring a new dimension in the pathogenesis of kidney cancer.

Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney. The role of the von-Hippel-Lindeau (VHL) tumour suppressor gene is well established in RCC with a loss of VHL protein leading to accumulated hypoxia-induced factor (HIF) and the subsequent transcriptional activation of multiple downstream targets. Recently, microRNAs (miRNAs) have been shown to be differentially expressed in RCC and their role in RCC pathogenesis is emerging. This month, in BMC Medicine, Gleadle and colleagues show that certain miRNAs are regulated by VHL in either a hypoxia-inducible factor (HIF)-dependent or HIF-independent manner in RCC. They also show that miRNA expression correlates with the survival of RCC patients.In this commentary, we discuss the current understanding of the role of miRNAs in RCC and the different possible scenarios of their involvement in RCC pathogenesis. We also address their clinical significance as tumour markers, together with the potential use of miRNAs as therapeutic targets. Finally, we discuss some of the challenges that face the fast-evolving field of miRNAs, including the identification and validation of miRNA targets and the difficulties associated with establishing a link between miRNA expression and biological effects. A more thorough understanding of the biological nature of miRNAs and careful experimental planning will help us to reveal the complex role that miRNAs play in RCC pathogenesis. See research article: http://www.biomedcentral.com/1741-7015/8/64.

KLK6-regulated miRNA networks activate oncogenic pathways in breast cancer subtypes.

KLK6 is expressed in normal mammary tissues and is aberrantly regulated in breast cancer. At physiological levels of expression, i.e. those found in normal mammary tissues, KLK6 acts as a tumor suppressor in human breast cancer. However, aberrant overexpression of KLK6 (i.e. 50-100-fold higher than normal), a characteristic of a subset of human breast cancers is associated with increased tumorigenicity (Pampalakis et al. Cancer Res 69:3779-3787, 2009). Here, we stably transfected KLK6-non-expressing MDA-MB-231 breast cancer cells with the full-length KLK6 cDNA to overexpress KLK6 at levels comparable to those observed in patients, and investigated potential oncogenic miRNA networks regulated by these abnormally high KLK6 expression levels and increased activity of this serine protease. A number of miRNAs that are upregulated (e.g. miR-146a) or downregulated (e.g. miR-34a) via KLK6-induced alterations in the miRNA biogenesis machinery were identified. Integrated experimental and bioinformatics analyses identified convergent miRNA networks targeting the cell cycle, MYC, MAPK, and other signaling pathways. In large clinical datasets, significant correlations between KLK6 and downstream MAPK and MYC targets at both the RNA and protein levels was confirmed, as well as negative correlation with GATA3. It was also demonstrated that KLK6 overexpression and likely its proteolytic activity is associated with alterations in downstream miRNAs and their targets, and these differ with the molecular subtypes of breast cancer. The data partly explains the different characteristics of breast cancer subtypes. Importantly, we introduce a combined KLK6-CDKN1B+MYC+CDKN1C score for prediction of long-term patient survival outcomes, with higher scores indicating poor survival.

Kallikrein-related peptidase 5 induces miRNA-mediated anti-oncogenic pathways in breast cancer.

Kallikrein-related peptidase 5 (KLK5) displays aberrant expression in cancer. Recently, we showed KLK5 reconstitution in breast cancer cell lines suppresses malignancy. Present study aims to investigate the functional KLK5 mediated miRNA network on breast cancer progression, molecular subtype and survival. 28 miRNAs were up-regulated and 62 miRNAs were down-regulated upon KLK5 expression. Extracellular matrix (ECM) molecules and cell-adhesion pathways were the most significant KLK5-induced miRNA-mediated regulatory targets. Validation from The Cancer Genome Atlas (TCGA) database indicated KLK5 was specifically down-regulated in luminal B and basal-like breast cancer subtypes. There was a correlation between KLK5, miRNAs and their downstream ECM gene targets. Long-term patient survival correlated with dysregulation of KLK5 and interacting ECM target genes. It suggests biological differences between breast cancer molecular subtypes, patient survival, and their propensity for invasion and metastasis can be explained in part by altered miRNA networks induced by KLK5 dysregulation. We provide the first evidence that KLK5 can affect miRNA networks, which regulate MMPs and other novel ECM targets and a new compelling hypothesis of interplay between serine proteases and miRNAs. We developed a combined KLK5-(ITGB1+COL12A1) predictive score for recurrence-free survival that could be exploited in clinical applications.

Quantitative proteomic analysis reveals potential diagnostic markers and pathways involved in pathogenesis of renal cell carcinoma.

There are no serum biomarkers for the accurate diagnosis of clear cell renal cell carcinoma (ccRCC). Diagnosis and decision of nephrectomy rely on imaging which is not always accurate. Non-invasive diagnostic biomarkers are urgently required. In this study, we preformed quantitative proteomics analysis on a total of 199 patients including 30 matched pairs of normal kidney and ccRCC using isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify differentially expressed proteins. We found 55 proteins significantly dysregulated in ccRCC compared to normal kidney tissue. 54 were previously reported to play a role in carcinogenesis, and 39 are secreted proteins. Dysregulation of alpha-enolase (ENO1), L-lactate dehydrogenase A chain (LDHA), heat shock protein beta-1 (HSPB1/Hsp27), and 10 kDa heat shock protein, mitochondrial (HSPE1) was confirmed in two independent sets of patients by western blot and immunohistochemistry. Pathway analysis, validated by PCR, showed glucose metabolism is altered in ccRCC compared to normal kidney tissue. In addition, we examined the utility of Hsp27 as biomarker in serum and urine. In ccRCC patients, Hsp27 was elevated in the urine and serum and high serum Hsp27 was associated with high grade (Grade 3-4) tumors. These data together identify potential diagnostic biomarkers for ccRCC and shed new light on the molecular mechanisms that are dysregulated and contribute to the pathogenesis of ccRCC. Hsp27 is a promising diagnostic marker for ccRCC although further large-scale studies are required. Also, molecular profiling may help pave the road to the discovery of new therapies.

The clinical utility of miR-21 as a diagnostic and prognostic marker for renal cell carcinoma.

Renal cell carcinoma (RCC) is the most common neoplasm of the kidney. Increasing evidence suggests that microRNAs are dysregulated in RCC and are important factors in RCC pathogenesis. miR-21 is a known oncogene with tumor-promoting effects in many types of cancer. In this study, we analyzed miR-21 in 121 cases of healthy kidney and different RCC subtypes, including clear cell (ccRCC), papillary (pRCC), chromophobe (chRCC), and oncocytoma. Total RNA was extracted, and the expression of miR-21 was measured with real-time quantitative RT-PCR using miR-21-specific probes. The expression of miR-21 was significantly up-regulated in RCC compared with healthy kidney. There was a significant difference in the expression levels between RCC subtypes, with the highest levels of expression in ccRCC and pRCC subtypes. miR-21 expression distinguished ccRCC and pRCC from chRCC and oncocytoma with 90% specificity (95% CI, 63.9% to 98.1%) and 83% sensitivity (95% CI, 53.5% to 97.6%). Significantly higher miR-21 levels were associated with higher stage and grade. Patients who were miR-21 positive had statistically significant shorter disease-free and overall survival rates. Thus, miR-21 is up-regulated in RCC, and its expression levels can be used as a diagnostic marker to distinguish ccRCC and pRCC from chRCC and oncocytoma. Moreover, it has potential as a prognostic marker in RCC, although it is not independent of tumor stage and grade.

Accurate molecular classification of kidney cancer subtypes using microRNA signature.

BACKGROUND: Renal cell carcinoma (RCC) encompasses different histologic subtypes. Distinguishing between the subtypes is usually made by morphologic assessment, which is not always accurate. OBJECTIVE: Our aim was to identify microRNA (miRNA) signatures that can distinguish the different RCC subtypes accurately. DESIGN, SETTING, AND PARTICIPANTS: A total of 94 different subtype cases were analysed. miRNA microarray analysis was performed on fresh frozen tissues of three common RCC subtypes (clear cell, chromophobe, and papillary) and on oncocytoma. Results were validated on the original as well as on an independent set of tumours, using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis with miRNA-specific primers. MEASUREMENTS: Microarray data were analysed by standard approaches. Relative expression for qRT-PCR was determined using the ΔΔC(T) method, and expression values were normalised to small nucleolar RNA, C/D box 44 (SNORD44, formerly RNU44). Experiments were done in triplicate, and an average was calculated. Fold change was expressed as a log(2) value. The top-scoring pairs classifier identified operational decision rules for distinguishing between different RCC subtypes and was robust under cross-validation. RESULTS AND LIMITATIONS: We developed a classification system that can distinguish the different RCC subtypes using unique miRNA signatures in a maximum of four steps. The system has a sensitivity of 97% in distinguishing normal from RCC, 100% for clear cell RCC (ccRCC) subtype, 97% for papillary RCC (pRCC) subtype, and 100% accuracy in distinguishing oncocytoma from chromophobe RCC (chRCC) subtype. This system was cross-validated and showed an accuracy of about 90%. The oncogenesis of ccRCC is more closely related to pRCC, whereas chRCC is comparable with oncocytoma. We also developed a binary classification system that can distinguish between two individual subtypes. CONCLUSIONS: MiRNA expression patterns can distinguish between RCC subtypes.

Metastamirs: a stepping stone towards improved cancer management.

MicroRNAs (miRNAs) are non-coding RNAs that regulate protein expression. Aberrant miRNA expression in cancer has been well documented; miRNAs can act as oncogenes or tumor-suppressor genes, depending on the cellular context and target genes that they regulate, and are involved in tumor progression and metastasis. The potential mechanisms by which miRNAs are involved in tumor aggressiveness include migration, invasion, cell proliferation, epithelial-to-mesenchymal transition, angiogenesis and apoptosis. MiRNAs are involved in various cellular pathways and an miRNA can elicit more than one biological effect in a given cell. Existing data show the potential clinical utility of miRNAs as prognostic and predictive markers for aggressive and metastatic cancers. The stability of miRNAs in formalin-fixed, paraffin-embedded tissues and body fluids is advantageous for biomarker discovery and validation. In addition, miRNAs can be extracted from small biopsy specimens, which is a further advantage. Finally, miRNAs are potential therapeutic agents for personalized cancer management.

Personalized medicine: marking a new epoch in cancer patient management.

Personalized medicine (PM) is defined as "a form of medicine that uses information about a person's genes, proteins, and environment to prevent, diagnose, and treat disease." The promise of PM has been on us for years. The suite of clinical applications of PM in cancer is broad, encompassing screening, diagnosis, prognosis, prediction of treatment efficacy, patient follow-up after surgery for early detection of recurrence, and the stratification of patients into cancer subgroup categories, allowing for individualized therapy. PM aims to eliminate the "one size fits all" model of medicine, which has centered on reaction to disease based on average responses to care. By dividing patients into unique cancer subgroups, treatment and follow-up can be tailored for each individual according to disease aggressiveness and the ability to respond to a certain treatment. PM is also shifting the emphasis of patient management from primary patient care to prevention and early intervention for high-risk individuals. In addition to classic single molecular markers, high-throughput approaches can be used for PM including whole genome sequencing, single-nucleotide polymorphism analysis, microarray analysis, and mass spectrometry. A common trend among these tools is their ability to analyze many targets simultaneously, thus increasing the sensitivity, specificity, and accuracy of biomarker discovery. Certain challenges need to be addressed in our transition to PM including assessment of cost, test standardization, and ethical issues. It is clear that PM will gradually continue to be incorporated into cancer patient management and will have a significant impact on our health care in the future.

Human kallikrein related peptidases 6 and 13 in combination withCA125 is a more sensitive test for ovarian cancer than CA125 alone.

The current biomarker for ovarian cancer, CA125, lacks the sensitivity and specificity required to detect early stage ovarian cancers. Since several Kallikreins (KLKs) are up regulated in ovarian cancer, they represent a potential pool of biomarkers for ovarian cancer. The purpose of this study is to determine if elevated expression levels of Muc16 (CA125 gene), KLK6 and KLK13 represent a more sensitive test for detection of early stage ovarian cancer than Muc16 alone. Using quantitative real-time PCR, 106 sporadic ovarian tumors and 8 normal ovaries were evaluated for mRNA expression. Analysis for increased expression levels, above controls, of either KLK6, KLK13 or Muc16 improved overall sensitivity to 93%, from 82% for Muc16 alone. Likewise, the negative predictive value increased from 27% to 50% (Muc16 alone compared to combined). With early stage cancers (n=32), both sensitivity increased 50-56% (individually) to 72% (combined), and negative predictive value increased (30% Muc16 to 58% combined). These results show a combined panel of KLK6, KLK13, and Muc16, is a more sensitive test to detect early stage ovarian cancer than Muc16 alone, indicating assaying for several kallikrein-related peptidases, in addition to CA125, could provide a significant advantage to detect ovarian cancer in the early stages.

Identification of new splice variants and differential expression of the human kallikrein 10 gene, a candidate cancer biomarker.

The human kallikrein gene 10 (KLK10) is a member of the kallikrein gene family on chromosome 19q13.4. This gene was identified by its downregulation in breast cancer, and preliminary evidence suggests that it may act as a tumor suppressor. A computer-based analysis was performed on EST and SAGE clones from the Cancer Genome Anatomy Project and other databases. Experimental verification of differential expression of KLK10 in cancer was performed by PCR using gene-specific primers. The mRNA and EST analysis allowed the construction of the longest transcript of the gene and characterization of a 5' extension of the reported mRNA. In addition, seven new splice variants of KLK10 were identified. One of these variants, named KLK10 splice variant 3 (KLK10-SV3) which starts with a novel first exon, was experimentally verified. This variant is predicted to encode for the same protein as the 'classical' KLK10 mRNA, since the first exon is untranslated. One variant mRNA partially matches with the sequence of KLK10, while the rest of the mRNA matches with a portion of the polycystic kidney disease gene, found on chromosome 15. This variant could not be experimentally verified in either normal or cancerous tissues. There are 39 reported single nucleotide polymorphisms (SNPs) for the gene, in which three result in amino acid substitutions. SAGE analysis shows a clear upregulation of KLK10 in ovarian, pancreatic, colon, and gastric cancers. The gene is, however, downregulated in breast and prostate cancers. A three-fold decrease in expression levels was noted in actinic keratosis, compared to normal skin from the same patient. The differential regulation of KLK10 in ovarian and prostate cancers was experimentally verified by RT-PCR analysis. In addition, a significant number of clones were isolated from carcinomas of the head and neck. Fewer clones were found in carcinomas of the skin, brain and prostate. Orthologues were identified in three other species, with the highest degree of homology observed with the mouse and rat orthologues (42% in each). In conclusion new splice variants of the KLK10 gene were identified. These in silico analyses show a differential expression of the gene in various malignancies and provide the basis for directing experimental efforts to investigate the possible role of the gene as a cancer biomarker.

The kallikrein gene 5 splice variant 2 is a new biomarker for breast and ovarian cancer.

The presence of more than one mRNA form for the same gene is common among kallikreins, and many of the kallikrein splice variants may hold significant clinical value. The human kallikrein gene 5 (KLK5) is a member of the human kallikrein gene family of serine proteases on chromosome 19q13.4. KLK5 has been shown to be differentially expressed in a variety of endocrine tumors including ovarian, breast and prostate cancer. Utilizing Expressed Sequence Tag database analysis and reverse transcriptase polymerase chain reaction, we identified a new alternatively spliced form of KLK5(KLK5-splice variant 2, KLK5-SV2). This variant mRNA is 1,438 bp in length; formed of 195 bp of 5' untranslated region, 882 bp of protein coding sequence and a 3' untranslated region of 326 nucleotides. KLK5-SV2 has 7 exons, the first 2 of which are untranslated, and 6 intervening introns. KLK5-SV2 is different from the classic form of the KLK5 mRNA in its 5' untranslated region, where the first 5' untranslated exon of the classic form is split into 2 exons with an intervening intron of 135 nucleotides. KLK5-SV2 is expressed in a variety of tissues, with higher expression levels in the mammary gland, cervix, salivary gland and trachea. The steroid hormone receptor-positive breast cancer cell line BT-474 was used to examine the effect of different steroids on the expression levels of KLK5-SV2. Expression levels were significantly higher after stimulation with androgens, but not estrogens, progestins, aldosterone or corticosteroids. While relatively high levels of expression were found in all 10 normal breast tissues examined, no expression was detected in 16 breast cancer tissues, and expression was significantly lower than normal in the remaining 4 cancers. Expression levels comparable to normal were found in only 1 breast cancer cell line. Weak to no expression was detected in 3 other breast cancer cell lines. KLK5-SV2 was not detectable in any of the 10 normal ovarian tissues examined. It was, however, expressed at relatively high levels in 10 out of 20 ovarian cancer tissues, and lower levels were found in 4 other cancers. No expression was detected in the remaining 6 cancers. High expression levels were also detected in the CAOV-3 ovarian cancer cell line. KLK5-SV2 is a potential biomarker for breast and ovarian cancers.

In silico analysis of the human kallikrein gene 6.

Kallikreins are a family of 15 serine proteases clustered together on the long arm of chromosome 19. Recent reports have linked kallikreins to malignancy. The human kallikrein gene 6 (KLK6) is a newly characterized member of the human kallikrein gene family. Recent work has focused on the possible role of this gene and its protein product as a tumor marker and its involvement in diseases of the central nervous system. In this study, we performed extensive in silico analyses of KLK6 expression from different databases using various bioinformatic tools. These data enabled us to construct and verify the longest transcript for this kallikrein, to identify several polymorphisms among published sequences and to summarize the 21 single-nucleotide polymorphisms of the gene. Our expressed sequence tag (EST) analyses suggest the existence of seven new splice variants of the gene, in addition to the already reported ones. Most of these variants were identified in libraries from cancerous tissues. KLK6 orthologues were identified from three other species with approximately 86% overall homology with rat and mouse orthologues. We also utilized several databases to compare KLK6 gene expression in normal and cancerous tissues. The serial analysis of gene expression and EST expression profiles showed upregulation of the gene in female genital (ovarian and uterine) and gastrointestinal (gastric, colon, esophageal and pancreatic) cancers. Significant downregulation was observed in breast cancers and brain tumors, in relation to their normal counterparts.