Kallikrein family proteases KLK6 and KLK7 are potential early detection and diagnostic biomarkers for serous and papillary serous ovarian cancer subtypes

Current strategies for early epithelial ovarian cancer detection using miRNA as a potential tool

Ovarian cancer is one of the most aggressive and significant malignant tumor forms in the female reproductive system. It is the leading cause of death among gynecological cancers owing to its metastasis. Since its preliminary disease symptoms are lacking, it is imperative to develop early diagnostic biomarkers to aid in treatment optimization and personalization. In this vein, microRNAs, which are short sequence non-coding molecules, displayed great potential as highly specific and sensitive biomarker. miRNAs have been extensively advocated and proven to serve an instrumental part in the clinical management of cancer, especially ovarian cancer, by promoting the cancer cell progression, invasion, delayed apoptosis, epithelial-mesenchymal transition, metastasis of cancer cells, chemosensitivity and resistance and disease therapy. Here, we cover our present comprehension of the most up-to-date microRNA-based approaches to detect ovarian cancer, as well as current diagnostic and treatment strategies, the role of microRNAs as oncogenes or tumor suppressor genes, and their significance in ovarian cancer progression, prognosis, and therapy.

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis

OBJECTIVE

Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions, they have had only marginal impacts due to an inability to identify biomarkers at an early stage. Biomarker discovery is challenging, yet essential for improving drug discovery and clinical care. Machine learning (ML) techniques are invaluable for recognising complex patterns in biomarkers compared to conventional methods, yet they can lack physical insights into diagnosis. eXplainable Artificial Intelligence (XAI) is capable of providing deeper insights into the decision-making of complex ML algorithms increasing their applicability. We aim to introduce best practice for combining ML and XAI techniques for biomarker validation tasks.

METHODS

We focused on classification tasks and a game theoretic approach based on Shapley values to build and evaluate models and visualise results. We described the workflow and apply the pipeline in a case study using the CDAS PLCO Ovarian Biomarkers dataset to demonstrate the potential for accuracy and utility.

RESULTS

The case study results demonstrate the efficacy of the ML pipeline, its consistency, and advantages compared to conventional statistical approaches.

CONCLUSION

The resulting guidelines provide a general framework for practical application of XAI in medical research that can inform clinicians and validate and explain cancer biomarkers.

A novel theranostic activity-based probe targeting kallikrein 7 for the diagnosis and treatment of skin diseases

We applied a new in silico approach for using protease-substrate motifs to design a kallikrein 7 (KLK7)-specific phosphonate activity-based probe (ABP) to quantify the active KLK7 in situ. Epidermal application of the ABP-inhibitor on Spink5^-/-Klk5^-/- mice, a Netherton syndrome model, reversed disease hallmarks, providing preclinical proof-of-concept for using ABPs as theranostics.

The prognostic and diagnostic potential of kallikrein-related peptidases in ovarian cancer

Introduction: Ovarian cancer is one of the deadliest malignancies among women worldwide. The lack of early diagnostic markers fuels an unfavorable prognosis as most patients are at an advanced stage when the disease is diagnosed for the first time. The role of the kallikrein-related peptidase (KLK) family in ovarian cancer progression and prognosis has been thoroughly investigated in various studies. Most of these peptidases are upregulated in ovarian cancer tissue compared to normal ovarian tissue and their expression is linked to overall and progression-free survival (OS/PFS). In this review, we address the clinical relevance of KLKs in ovarian cancer and their diagnostic potential.Areas covered: This review covers the expression and regulation of KLKs in ovarian cancer with focus on the prognostic and diagnostic potential, especially in liquid biopsies.Expert opinion: In ovarian cancer, several kallikrein-related peptidases are markedly expressed in a tissue-specific manner. Tumor-derived protease secretion results in elevated levels in serum and ascites. KLKs may thus serve as potential biomarkers alone or in combination with other serum tumor markers, such as Cancer Antigen 125 (CA125), for early detection and assessment of the prognosis of ovarian cancer patients.

Application of machine learning to large in vitro databases to identify drug-cancer cell interactions: azithromycin and KLK6 mutation status

Recent advances in machine learning promise to yield novel insights by interrogation of large datasets ranging from gene expression and mutation data to CRISPR knockouts and drug screens. We combined existing and new algorithms with available experimental data to identify potentially clinically relevant relationships to provide a proof of principle for the promise of machine learning in oncological drug discovery. Specifically, we screened cell line data from the Cancer Dependency Map for the effects of azithromycin, which has been shown to kill cancer cells in vitro. Our findings demonstrate a strong relationship between Kallikrein Related Peptidase 6 (KLK6) mutation status and the ability of azithromycin to kill cancer cells in vitro. While the application of azithromycin showed no meaningful average effect in KLK6 wild-type cell lines, statistically significant enhancements of cell death are seen in multiple independent KLK6-mutated cancer cell lines. These findings suggest a potentially valuable clinical strategy in patients with KLK6-mutated malignancies.

Prognostic value of kallikrein-related peptidase 7 (KLK7) mRNA expression in advanced high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is the most common and lethal subtype of ovarian cancer. A growing body of evidence suggests tumor-supporting roles of several members of the kallikrein-related peptidase (KLK) family, including KLK5 and KLK7, in this cancer subtype. In normal physiology, KLK5 and KLK7 are the major proteases involved in skin desquamation. Moreover, in several cancer types KLK5 and KLK7 co-expression has been observed. Recently, we have shown that elevated KLK5 mRNA levels are associated with an unfavorable prognosis in HGSOC. Therefore, the aim of this study was to investigate the clinical significance of KLK7 mRNA expression and to explore its relation to KLK5 levels in HGSOC.

METHODS

mRNA expression levels of KLK7 were quantified by qPCR in a well-characterized patient cohort afflicted with advanced high-grade serous ovarian cancer (FIGO III/IV, n = 139). Previously determined KLK5 mRNA as well as KLK5 and KLK7 antigen concentrations were used to evaluate the relationship between the expression patterns of both factors on the mRNA as well as protein level in tumor tissue of HGSOC patients.

RESULTS

There were strong, significant positive correlations between KLK5 and KLK7 both at the mRNA and the protein level, suggesting coordinate expression of these proteases in HGSOC. In univariate analyses, elevated KLK7 levels as well as the combination of KLK5 + KLK7 (high and/or high versus low/low) were significantly associated with worse progression-free survival (PFS). High mRNA expression levels of KLK7 and the combination of KLK5 and KLK7 showed a trend towards significance for overall survival (OS). In multivariate analyses, KLK7 mRNA expression represented an unfavorable, statistically significant independent predictor for PFS and OS.

CONCLUSIONS

The findings imply that both increased KLK5 and KLK7 mRNA expression levels represent unfavorable prognostic biomarkers in advanced high-grade serous ovarian cancer, whereby multivariate analyses indicate that KLK7 mRNA exhibits a stronger predictive value as compared to KLK5 mRNA and the combination of KLK5 and KLK7.

Prediction of the treatment response in ovarian cancer: a ctDNA approach

Ovarian cancer is the eighth most commonly occurring cancer in women. Clinically, the limitation of conventional screening and monitoring approaches inhibits high throughput analysis of the tumor molecular markers toward prediction of treatment response. Recently, analysis of liquid biopsies including circulating tumor DNA (ctDNA) open new way toward cancer diagnosis and treatment in a personalized manner in various types of solid tumors. In the case of ovarian carcinoma, growing pre-clinical and clinical studies underscored promising application of ctDNA in diagnosis, prognosis, and prediction of treatment response. In this review, we accumulate and highlight recent molecular findings of ctDNA analysis and its associations with treatment response and patient outcome. Additionally, we discussed the potential application of ctDNA in the personalized treatment of ovarian carcinoma. ctDNA-monitoring usage during the ovarian cancer treatments procedures.

Analysis of expression and prognosis of KLK7 in ovarian cancer

Background

Ovarian cancer is one of the common malignant tumors in female reproductive organs. Kallikrein-related peptidase (KLK) 7 is a secreted serine peptidase that is related to different cancer. To investigate the expression and significance of KLK7 in ovarian cancer.

Materials and methods

The expression of KLK7 in human ovarian cancer was evaluated by Oncomine and Cancer Cell Line Encyclopedia database. Then the co-expression genes relevant to the KLK7 gene were analyzed by the Pearson correlation test. Finally, the impact of KLK7 on clinical prognosis was investigated in distinct subtypes of ovarian cancer patients by UALCAN database and Kaplan–Meier plotter database.

Results

It was found that the expression of KLK7 was higher in ovarian cancer compared with other types of cancer, such as gastric cancer and pancreatic cancer. The expression of KLK7 was found to be increased in four various ovarian cancer data sets compared with the healthy tissues. In addition, upregulation of KLK7 expression was associated with age and cancer stage. Moreover, survival analysis revealed that higher KLK7 expression was negatively associated with progression-free survival.

Conclusion

Knowledge of the expression of KLK7 may be useful for better understanding the outcome in ovarian cancer patients.

High levels of KLK7 protein expression are related to a favorable prognosis in triple-negative breast cancer patients

In normal physiology, kallikrein-related peptidase 7 (KLK7), together with other members of the kallikrein-related peptidase family, is mainly involved in skin desquamation and keratinization processes. Moreover, expression of KLK7 was shown in various tumor types to be dysregulated and to correlate to patients' survival time. However, there are contradictory reports in breast cancer whether KLK7 represents an unfavorable or favorable prognostic biomarker. In the present study, we examined the prognostic value of KLK7 protein expression in triple-negative breast cancer (TNBC), determined by immunohistochemistry (IHC). A cohort encompassing 133 TNBC specimens, present on tissue microarrays, was analyzed. For quantification of the staining intensity, an automated digital IHC image analysis algorithm was applied. In both Kaplan-Meier and univariate Cox analyses, elevated KLK7 protein levels were significantly linked with prolonged overall survival (OS). In multivariable Cox analysis, addition of KLK7 immunoreactivity scores to the base model (including the clinical parameters age, tumor size, and nodal status) demonstrated that KLK7 protein expression remained as a statistically significant, independent parameter for prolonged OS. These results strongly indicate that KLK7 is a favorable prognostic biomarker in triple-negative breast cancer.

Safety and Outcome Measures of First-in-Human Intraperitoneal α Radioimmunotherapy With 212Pb-TCMC-Trastuzumab

PURPOSE

One-year monitoring of patients receiving intraperitoneal (IP) Pb-TCMC-trastuzumab to provide long-term safety and outcome data. A secondary objective was to study 7 tumor markers for correlation with outcome.

METHODS

Eighteen patients with relapsed intra-abdominal human epidermal growth factor receptor-2 expressing peritoneal metastases were treated with a single IP infusion of Pb-TCMC-trastuzumab, delivered <4 h after 4 mg/kg IV trastuzumab. Seven tumor markers were studied for correlation with outcome.

RESULTS

Six dose levels (7.4, 9.6, 12.6, 16.3, 21.1, 27.4 MBq/m) were well tolerated with early possibly agent-related adverse events being mild, transient, and not dose dependent. These included asymptomatic, abnormal laboratory values. No late renal, liver, cardiac, or other toxicity was noted up to 1 year. There were no clinical signs or symptoms of an immune response to Pb-TCMC-trastuzumab, and assays to detect an immune response to this conjugate were negative for all tested. Tumor marker studies in ovarian cancer patients showed a trend of decreasing Cancer antigen 72-4 (CA 72-4) aka tumor-associated glycoprotein 72 (TAG-72) and tumor growth with increasing administered radioactivity. Other tumor markers, including carbohydrate antigen (CA125), human epididymis protein 4 (HE-4), serum amyloid A (SAA), mesothelin, interleukin-6 (IL-6), and carcinoembryonic antigen (CEA) did not correlate with imaging outcome.

CONCLUSIONS

IP Pb-TCMC-trastuzumab up to 27 MBq/m seems safe for patients with peritoneal carcinomatosis who have failed standard therapies. Serum TAG-72 levels better correlated to imaging changes in ovarian cancer patients than the more common tumor marker, CA125.

Molecular characteristics and association analysis with litter size trait for porcine KLK7 gene

Kallikrein-related peptidase 7(KLK7) is a tumor-related gene. In this study, the full-length coding sequence of porcine KLK7 gene was cloned through RT-PCR. Sequence analysis revealed that the pig KLK7 gene encodes a protein of 257 amino acids which has high homology with the KLK7 protein of six species: polar bear (95%), Weddell seal(94%), dog (92%), Pacific walrus (95%), domestic cat (92%), and Amur tiger (91%). This gene is structured in five exons and four introns as revealed by computer-assisted analysis. Phylogenetic analysis showed that the pig KLK7 gene has a closer genetic relationship with the KLK7 gene of a domestic cat. PCR-Alu I-RFLP was established to detect the GU373714:c.390 C > T substitution of porcine KLK7 gene and eight pig breeds displayed obvious genotype and allele frequency differences at this mutation locus. Association of this SNP with litter size trait was assessed in Large White (n = 200) and Landrace (n = 200) pig populations and results demonstrated that this polymorphic locus was significantly associated with the litter size of all parities in Large White and Landrace sows (p < 0.05). Therefore, KLK7 is also an important reproduction related gene.

A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome

The collection of proteins secreted from a cell-the secretome-is of particular interest in cancer pathophysiology due to its diagnostic potential and role in tumorigenesis. However, cancer secretome studies are often limited to one tissue or cancer type or focus on biomarker prediction without exploring the associated functions. We therefore conducted a pan-cancer analysis of secretome gene expression changes to identify candidate diagnostic biomarkers and to investigate the underlying biological function of these changes. Using transcriptomic data spanning 32 cancer types and 30 healthy tissues, we quantified the relative diagnostic potential of secretome proteins for each cancer. Furthermore, we offer a potential mechanism by which cancer cells relieve secretory pathway stress by decreasing the expression of tissue-specific genes, thereby facilitating the secretion of proteins promoting invasion and proliferation. These results provide a more systematic understanding of the cancer secretome, facilitating its use in diagnostics and its targeting for therapeutic development.

Probing the endogenous peptidomes of cancer for biomarkers: A new endeavor

The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.

A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer

Background

Over 500,000 women worldwide are diagnosed with ovarian or endometrial cancer each year. We have used a two-step strategy to identify plasma proteins that could be used to improve the diagnosis of women with an indication of gynecologic tumor and in population screening.

Methods

In the discovery step we screened 441 proteins in plasma using the proximity extension assay (PEA) and five Olink Multiplex assays (CVD II, CVD III, INF I, ONC II, NEU I) in women with ovarian cancer (n = 106), endometrial cancer (n = 74), benign ovarian tumors (n = 150) and healthy population controls (n = 399). Based on the discovery analyses a set of 27 proteins were selected and two focused multiplex PEA assays were developed. In a replication step the focused assays were used to study an independent set of cases with ovarian cancer (n = 280), endometrial cancer (n = 228), women with benign ovarian tumors (n = 76) and healthy controls (n = 57).

Results

In the discovery step, 27 proteins that showed an association to cancer status were identified. In the replication analyses, the focused assays distinguished benign tumors from ovarian cancer stage III-IV with a sensitivity of 0.88 and specificity of 0.92 (AUC = 0.92). The assays had a significantly higher AUC for distinguishing benign tumors from late stage ovarian cancer than using CA125 and HE4 (p = 9.56e-22). Also, population controls could be distinguished from ovarian cancer stage III-IV with a sensitivity of 0.85 and a specificity of 0.92 (AUC = 0.89).

Conclusion

The PEA assays represent useful tools for identification of new biomarkers for gynecologic cancers. The selected protein assays could be used to distinguish benign tumors from ovarian and endometrial cancer in women diagnosed with an unknown suspicious pelvic mass. The panels could also be used in population screening, for identification of women in need of specialized gynecologic transvaginal ultrasound examination.

Funding

The Swedish Cancer Foundation, Vinnova (SWELIFE), The Foundation for Strategic Research (SSF), Assar Gabrielsson Foundation.

Kallikrein-related peptidases represent attractive therapeutic targets for ovarian cancer

INTRODUCTION

Aberrant levels of kallikrein-related peptidases (KLK1-15) have been linked to cancer cell proliferation, invasion and metastasis. In ovarian cancer, the KLK proteolytic network has a crucial role in the tissue and tumor microenvironment. Publically available ovarian cancer genome and expression data from multiple patient cohorts show an upregulation of most KLKs. Areas covered: Here, we review the expression levels of all 15 members of this family in normal and ovarian cancer tissues, categorizing them into highly and moderately or weakly expressed KLKs, and their association with patient prognosis and survival. We summarize their tumor-biological functions determined in cell-based assays and xenograft models, further highlighting their suitability as cancer biomarkers and attractive candidates for drug development. Finally, we discuss some different pharmaceutical approaches, including peptide-based and small molecule inhibitors, cyclic peptides, depsipeptides, engineered natural inhibitors, antibodies, RNA/DNA-based aptamers, prodrugs, miRNA and siRNA. Expert opinion: In light of the results from clinical and tumor-biological studies, together with the available pharmaceutical tools, we suggest KLK4, KLK5, KLK6 and possibly KLK7 as preferred targets for inhibition in ovarian cancer.

Diagnostic and prognostic biomarker potential of kallikrein family genes in different cancer types

Purpose

The aim of this study was to compare and contrast the expression of all members of the Kallikrein (KLK) family of genes across 15 cancer types and to evaluate their utility as diagnostic and prognostic biomarkers.

Results

Severe alterations were found in the expression of different Kallikrein genes across various cancers. Interestingly, renal clear cell and papillary carcinomas have similar kallikrein expression profiles, whereas, chromophobe renal cell carcinoma has a unique expression profile. Several KLK genes have excellent biomarker potential (AUC > 0.90) for chromophobe renal cell carcinoma (KLK2, KLK3, KLK4, KLK7, KLK15), renal papillary carcinoma (KLK1, KLK6, KLK7), clear cell renal cell carcinoma (KLK1, KLK6), thyroid carcinoma (KLK2, KLK4, KLK13, KLK15) and colon adenocarcinoma (KLK6, KLK7, KLK8, KLK10). Several KLK genes were significantly associated with mortality in clear cell renal cell carcinoma (KLK2: HR = 1.69; KLK4: HR = 1.63; KLK8: HR = 1.71; KLK10: HR = 2.12; KLK11: HR = 1.76; KLK14: HR = 1.86), papillary renal cell carcinoma (KLK6: HR = 3.38, KLK7: HR = 2.50), urothelial bladder carcinoma (KLK5: HR = 1.89, KLK6: HR = 1.71, KLK8: HR = 1.60), and hepatocellular carcinoma (KLK13: HR = 1.75).

Methods

The RNA-seq gene expression data were downloaded from The Cancer Genome Atlas (TCGA). Statistical analyses, including differential expression analysis, receiver operating characteristic curves and survival analysis (Cox proportional-hazards regression models) were performed.

Conclusions

A comprehensive analysis revealed the changes in the expression of different KLK genes associated with specific cancers and highlighted their potential as a diagnostic and prognostic tool.

Regulatory network involving miRNAs and genes in serous ovarian carcinoma

Serous ovarian carcinoma (SOC) is one of the most life-threatening types of gynecological malignancy, but the pathogenesis of SOC remains unknown. Previous studies have indicated that differentially expressed genes and microRNAs (miRNAs) serve important functions in SOC. However, genes and miRNAs are identified in a disperse form, and limited information is known about the regulatory association between miRNAs and genes in SOC. In the present study, three regulatory networks were hierarchically constructed, including a differentially-expressed network, a related network and a global network to reveal associations between each factor. In each network, there were three types of factors, which were genes, miRNAs and transcription factors that interact with each other. Focus was placed on the differentially-expressed network, in which all genes and miRNAs were differentially expressed and therefore may have affected the development of SOC. Following the comparison and analysis between the three networks, a number of signaling pathways which demonstrated differentially expressed elements were highlighted. Subsequently, the upstream and downstream elements of differentially expressed miRNAs and genes were listed, and a number of key elements (differentially expressed miRNAs, genes and TFs predicted using the P-match method) were analyzed. The differentially expressed network partially illuminated the pathogenesis of SOC. It was hypothesized that if there was no differential expression of miRNAs and genes, SOC may be prevented and treatment may be identified. The present study provided a theoretical foundation for gene therapy for SOC.

A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-017-9169-6) contains supplementary material, which is available to authorized users.

Transcriptome analysis of human colorectal cancer biopsies reveals extensive expression correlations among genes related to cell proliferation, lipid metabolism, immune response and collagen catabolism

Precise characterization of biological processes critical to proliferation and metastasis of colorectal cancer should facilitate the development of diagnostic and prognostic biomarkers as well as novel treatments. Using mRNA-Seq, we examined the protein coding messenger RNA (mRNA) expression profiles across different histologically defined stages of primary colon cancers and compared them to their patient matched normal tissue controls. In comparing 79 colorectal cancers to their matched normal mucosa, tumors were distinguished from normal non-malignant tissues not only in the upregulation of biological processes pertaining to cell proliferation, inflammation, and tissue remodeling, but even more strikingly, in downregulated biological processes including fatty acid beta oxidization for ATP production and epithelial cell differentiation and function. A network analysis of deregulated genes revealed newly described cancer networks and putative hub genes.

Taken together, our findings suggest that, within an inflammatory microenvironment, invasive, dedifferentiated and rapidly dividing tumor cells divert the oxidation of fatty acids and lipids from energy production into lipid components of cell membranes and organelles to support tumor proliferation. A gene co-expression network analysis provides a clear and broad picture of biological pathways in tumors that may significantly enhance or supplant current histopathologic studies.

Epigenetic regulation of KLK7 gene expression in pancreatic and cervical cancer cells

Kallikrein-related peptidase 7 (KLK7) is a serine protease encoded within the kallikrein gene cluster located on human chromosome region 19q13.3-13.4. KLK7 is overexpressed in human pancreatic ductal adenocarcinomas (PDACs), but not in normal pancreas. Examination of KLK7 mRNA levels in pancreatic cancer cell lines revealed that it is readily detected in MIA PaCa-2 and PK-1 cells, but not in Panc-1 cells. Treatment of Panc-1 cells with the histone deacetylase (HDAC) inhibitor trichostatin A (TSA) significantly induced KLK7 mRNA expression. Similarly, KLK7 is highly expressed in cervical cancer cells, but its expression in the human cervical cancer cell line HeLa is only detected following TSA treatment. Promoter deletion analysis revealed that the proximal -238 promoter region, containing a putative Sp1-binding site, was sufficient for TSA activation of luciferase reporter activity, which was abrogated by the disruption of the Sp1-binding sequence. Consistent with the notion that TSA induced KLK7 expression via Sp1, co-expression of Sp1 with the KLK7-promoter/luciferase construct produced a significant increase in reporter activity. Chromatin immunoprecipitation (ChIP) analysis revealed enriched Sp1 occupancy on the KLK7 promoter following TSA treatment. Similarly, ChIP analysis showed the histone active mark, H3K4Me3, in the KLK7 promoter region was significantly increased after exposure to TSA.

Development of Monoclonal Antibodies and Characterization of an ELISA Platform Against Kallikrein-Related Peptidase 6 as a Tumor Biomarker

Kallikrein-related peptidase 6 (KLK6) is a serine protease, and one of fifteen kallikrein members located on chromosome 19. KLK6 is associated with the regulation of axonal growth following spinal injury, tumor cell metastasis, and alpha synuclein aggregate pathologies like Parkinson's, making KLK6 a potentially important biomarker. We generated a KLK6 expression vector for large-scale expression in Escherichia coli. After affinity chromatography purification and SDS-PAGE confirmation, mice were immunized with the purified protein for development of monoclonal B cell populations. Our immunizations generated five hybridomas (1D8, 2E3, 3B7, 5G8, and 5H12) against KLK6. Isotyping analysis revealed that clone 2E3 was IgG2b, while the other four clones were IgG1. Further studies found that clone 5G8 could be used to visualize specific KLK6 bands by Western blot analysis from ovarian cancer patient serum and plasma, and also in mouse liver lysates. Finally, we established a sandwich ELISA pair and determined their sensitivity for KLK6 to be 10 ng/mL. These findings establish an essential tool for the detection and analysis of KLK6.

Diagnostic Accuracy of Serum Kallikrein-Related Peptidases for Ovarian Cancer: A Systematic Review and Meta-Analysis

OBJECTIVE

At present, considerable efforts have been made to identify new cancer-specific markers for ovarian cancer (OC) diagnosis and the kallikrein-related peptidases (KLKs) family is one of the most studied candidates. This meta-analysis aims to evaluate the pooled diagnostic value of serum KLK measurement for diagnosing OC.

METHODS

The Cochrane Library, PubMed, Excerpt Medica Database were searched for all relevant literature. The Quality Assessment for Studies of Diagnostic Accuracy tool was applied to assess the quality of enrolled studies. Statistical analysis was conducted by using Stata 13.0 software and Meta-Disc.

RESULTS

A total of 15 studies from 13 articles were considered eligible for inclusion in the present analysis. The following pooled parameters were calculated by using the bivariate model: sensitivity of 0.582 (95% confidence interval [CI], 0.517-0.644), specificity of 0.909 (95% CI, 0.833-0.952), positive likelihood ratios of 6.367 (95% CI, 3.330-12.172), negative likelihood ratios of 0.460 (95% CI, 0.388-0.546), diagnostic odds ratio of 13.831 (95% CI, 6.460-29.614), respectively.

CONCLUSIONS

Kallikrein-related peptidase seems to be a promising candidate biomarker in diagnosing OC, but the associated poor sensitivity of KLK individually may limit its value in clinical application. To resolve this problem, the combination of KLK and other markers may offer improved performance than a single marker.

Biological markers of prognosis, response to therapy and outcome in ovarian carcinoma

INTRODUCTION

Ovarian cancer (OvCa) is among the most common types of cancer and is the leading cause of death from gynecological malignancies in western countries. Cancer biomarkers have a potential for improving the management of OvCa patients at every point from screening and detection, diagnosis, prognosis, follow up, response to therapy and outcome.

AREAS COVERED

The literature search has indicated a number of candidate biomarkers have recently emerged that could facilitate the molecular definition of OvCa, providing information about prognosis and predicting response to therapy. These potentially promising biomarkers include immune cells and their products, tumor-derived exosomes, nucleic acids and epigenetic biomarkers. Expert commentary: Although most of the biomarkers available today require prospective validation, the development of noninvasive liquid biopsy-based monitoring promises to improve their utility for evaluations of prognosis, response to therapy and outcome in OvCa.

The serine protease prostasin (PRSS8) is a potential biomarker for early detection of ovarian cancer

Background

Ovarian cancer (OVC) is the deadliest of all gynecologic cancers, primarily as a consequence of asymptomatic progression. The complex nature of OVC creates challenges for early detection, and there is a lack of specific and sensitive biomarkers suitable for screening and detecting early stage OVC.

Methods

Potential OVC biomarkers were identified by bioinformatic analysis. Candidates were further screened for differential expression in a library of OVC cell lines. OVC-specific overexpression of a candidate gene, PRSS8, which encodes prostasin, was confirmed against 18 major human cancer types from 390 cancer samples by qRT-PCR. PRSS8 expression profiles stratified by OVC tumor stage-, grade- and subtype were generated using cDNA samples from 159 OVC samples. Cell-specific expression and localization of prostasin was determined by immunohistological tissue array analysis of more than 500 normal, benign, and cancerous ovarian tissues. The presence of prostasin in normal, benign, and OVC serum samples was also determined.

Results

Gene expression analysis indicated that PRSS8 was expressed in OVC at levels more than 100 fold greater than found in normal or benign ovarian lesions. This overexpression signature was found in early stages of OVC and was maintained in higher stages and grades of OVC. The PRSS8 overexpression signature was specific for OVC and urinary bladder cancer among 18 human cancer types. The majority of ovarian cell lines overexpressed PRSS8. In situ hybridization and histopathology studies of OVC tissues indicated that overexpression of prostasin was largely localized to tumor epithelium and was absent in neighboring stroma. Significantly higher levels of prostasin were found in early stage OVC serum samples compared to benign ovarian and normal donor samples.

Conclusions

The abundant amounts of secreted prostasin found in sera of early stage OVC can potentially be used as a minimally invasive screening biomarker for early stage OVC. Overexpression of PRSS8 mRNA and high levels of prostasin in multiple subtypes of early stage ovarian tumors may provide clinical biomarkers for early detection of OVC, which can potentially be used with CA125 and HE4.

Electronic supplementary material

The online version of this article (doi:10.1186/s13048-016-0228-9) contains supplementary material, which is available to authorized users.

Early detection biomarkers for ovarian cancer

Despite the widespread use of conventional and contemporary methods to detect ovarian cancer development, ovarian cancer remains a common and commonly fatal gynecological malignancy. The identification and validation of early detection biomarkers highly specific to ovarian cancer, which would permit development of minimally invasive screening methods for detecting early onset of the disease, are urgently needed. Current practices for early detection of ovarian cancer include transvaginal ultrasonography, biomarker analysis, or a combination of both. In this paper we review recent research on novel and robust biomarkers for early detection of ovarian cancer and provide specific details on their contributions to tumorigenesis. Promising biomarkers for early detection of ovarian cancer include KLK6/7, GSTT1, PRSS8, FOLR1, ALDH1, and miRNAs.