The Co-Expression of Kallikrein 5 and Kallikrein 7 Associates with Poor Survival in Non-HPV Oral Squamous-Cell Carcinoma.

OBJECTIVE: Oral squamous-cell carcinoma (OSCC) still has a poor prognosis. Lymph node metastasis (LNM) is a major determinant of treatment decisions and prognosis. Serine protease inhibitor Kazal-type 5 (SPINK5) is the inhibitor of kallikrein 5 (KLK5) and KLK7. SPINK5, KLK5 and KLK7 are three of the genes of a recently validated LNM-predicting gene expression profile in OSCC. This study evaluates their clinicopathological role and value as biomarkers in OSCC. METHODS: Eighty-three patients with primary OSCC, treated surgically between 1996 and 2000, were included. Gene expression data were acquired from a previously reported study. Human papillomavirus (HPV) status was determined by an algorithm for HPV-16. Protein expression for KLK5, KLK7 and SPINK5 was semi-quantitatively determined in all 83 tumours by immunohistochemistry. All expression data were correlated with clinicopathological parameters. RESULTS: Concurrent loss of KLK5 and KLK7 correlates with worse disease-specific and overall survival (DSS and OS). Multivariate analysis proved that co-expression is an independent prognostic factor for DSS (p = 0.029) and OS (p = 0.001). CONCLUSION: This report demonstrates that concurrent loss of KLK5 and KLK7 associates with a poor clinical outcome in OSCC and could therefore serve as prognostic marker in this disease.

Maspin is a marker for early recurrence in primary stage III and IV colorectal cancer.

BACKGROUND: Little is known about the factors that drive metastasis formation in colorectal cancer (CRC). Here, we set out to identify genes and proteins in patients with colorectal liver metastases that correlate with early disease recurrence. Such factors may predict a propensity for metastasis in earlier stages of CRC. METHODS: Gene expression profiling and proteomics were used to identify differentially expressed genes/proteins in resected liver metastases that recurred within 6 months following liver surgery vs those that did not recur for >24 months. Expression of the identified genes/proteins in stage II (n=243) and III (n=176) tumours was analysed by immunohistochemistry on tissue microarrays. Correlation of protein levels with stage-specific outcome was assessed by uni- and multivariable analyses. RESULTS: Both gene expression profiling and proteomics identified Maspin to be differentially expressed in colorectal liver metastases with early (<6 months) and prolonged (>24 months) time to recurrence. Immunohistochemical analysis of Maspin expression on tumour sections revealed that it was an independent predictor of time to recurrence (log-rank P=0.004) and CRC-specific survival (P=0.000) in stage III CRC. High Maspin expression was also correlated with mucinous differentiation. In stage II CRC patients, high Maspin expression did not correlate with survival but was correlated with a right-sided tumour location. CONCLUSION: High Maspin expression correlates with poor outcome in CRC after spread to the local lymph nodes. Therefore, Maspin may have a stage-specific function possibly related to tumour cell dissemination and/or metastatic outgrowth.

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

MOTIVATION: One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. RESULTS: We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. AVAILABILITY: The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). SUPPLEMENTARY INFORMATION: Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

Methylation of WNT target genes AXIN2 and DKK1 as robust biomarkers for recurrence prediction in stage II colon cancer.

Stage II colon cancer (CC) still remains a clinical challenge with patient stratification for adjuvant therapy (AT) largely relying on clinical parameters. Prognostic biomarkers are urgently needed for better stratification. Previously, we have shown that WNT target genes AXIN2, DKK1, APCDD1, ASCL2 and LGR5 are silenced by DNA methylation and could serve as prognostic markers in stage II CC patients using methylation-specific PCR. Here, we have extended our discovery cohort AMC90-AJCC-II (N=65) and methylation was analyzed by quantitative pyrosequencing. Subsequently, we validated the results in an independent EPICOLON1 CC cohort (N=79). Methylation of WNT target genes is negatively correlated to mRNA expression. A combination of AXIN2 and DKK1 methylation significantly predicted recurrences in univariate (area under the curve (AUC)=0.83, confidence interval (CI): 0.72-0.94, P<0.0001) analysis in stage II microsatellite stable (MSS) CC patients. This two marker combination showed an AUC of 0.80 (CI: 0.68-0.91, P<0.0001) in the EPICOLON1 validation cohort. Multivariate analysis in the Academic Medical Center (AMC) cohort revealed that both WNT target gene methylation and consensus molecular subtype 4 (CMS4) are significantly associated with poor recurrence-free survival (hazard ratio (HR)methylation: 3.84, 95% CI: 1.14-12.43; HRCMS4: 3.73, 95% CI: 1.22-11.48). CMS4 subtype tumors with WNT target methylation showed worse prognosis. Combining WNT target gene methylation and CMS4 subtype lead to an AUC of 0.89 (0.791-0.982, P<0.0001) for recurrence prediction. Notably, we observed that methylation of DKK1 is high in BRAF mutant and CIMP (CpG island methylator phenotype)-positive cancers, whereas AXIN2 methylation appears to be associated with CMS4. Methylation of AXIN2 and DKK1 were found to be robust markers for recurrence prediction in stage II MSS CC patients. Further validation of these findings in a randomized and prospective manner could pave a way to identify poor prognosis patients of stage II CC for AT.

Neoadjuvant chemotherapy affects molecular classification of colorectal tumors.

The recent discovery of 'molecular subtypes' in human primary colorectal cancer has revealed correlations between subtype, propensity to metastasize and response to therapy. It is currently not known whether the molecular tumor subtype is maintained after distant spread. If this is the case, molecular subtyping of the primary tumor could guide subtype-targeted therapy of metastatic disease. In this study, we classified paired samples of primary colorectal carcinomas and their corresponding liver metastases (n=129) as epithelial-like or mesenchymal-like, using a recently developed immunohistochemistry-based classification tool. We observed considerable discordance (45%) in the classification of primary tumors and their liver metastases. Discordant classification was significantly associated with the use of neoadjuvant chemotherapy. Furthermore, gene expression analysis of chemotherapy-exposed versus chemotherapy naive liver metastases revealed expression of a mesenchymal program in pre-treated tumors. To explore whether chemotherapy could cause gene expression changes influencing molecular subtyping, we exposed patient-derived colonospheres to six short cycles of 5-fluorouracil. Gene expression profiling and signature enrichment analysis subsequently revealed that the expression of signatures identifying mesenchymal-like tumors was strongly increased in chemotherapy-exposed tumor cultures. Unsupervised clustering of large cohorts of human colon tumors with the chemotherapy-induced gene expression program identified a poor prognosis mesenchymal-like subgroup. We conclude that neoadjuvant chemotherapy induces a mesenchymal phenotype in residual tumor cells and that this may influence the molecular classification of colorectal tumors.

A multidimensional network approach reveals microRNAs as determinants of the mesenchymal colorectal cancer subtype.

Colorectal cancer (CRC) is a heterogeneous disease posing a challenge for accurate classification and treatment of this malignancy. There is no common genetic molecular feature that would allow for the identification of patients at risk for developing recurrences and thus selecting patients who would benefit from more stringent therapies still poses a major clinical challenge. Recently, an international multicenter consortium (CRC Subtyping Consortium) was established aiming at the classification of CRC patients in biologically homogeneous CRC subtypes. Four consensus molecular subtypes (CMSs) were identified, of which the mesenchymal CMS4 presented with worse prognosis signifying the importance of identifying these patients. Despite the large number of samples analyzed and their clear association with unifying biological programs and clinical features, single-driver mutations could not be identified and patients are heterogeneous with regard to currently used clinical markers. We therefore set out to define the regulatory mechanisms underlying the distinct gene expression profiles using a network-based approach involving multiple molecular modalities such as gene expression, methylation levels and microRNA (miR) expression. The miR-200 family presented as the most powerful determinant of CMS4-specific gene expression, tuning the majority of genes differentially expressed in the poor prognosis subtype, including genes associated with the epithelial-mesenchymal transition program. Furthermore, our data show that two epigenetic marks, namely the methylation of the two miR-200 promoter regions, can identify tumors belonging to the mesenchymal subtype and is predictive of disease-free survival in CRC patients. Importantly, epigenetic silencing of the miR-200 family is also detected in epithelial CRC cell lines that belong to the mesenchymal CMS. We thus show that determining regulatory networks is a powerful strategy to define drivers of distinct cancer subtypes, which possess the ability to identify subtype affiliation and to shed light on biological behavior.