High nuclear expression levels of histone-modifying enzymes LSD1, HDAC2 and SIRT1 in tumor cells correlate with decreased survival and increased relapse in breast cancer patients.

BACKGROUND: Breast cancer is a heterogeneous disease with a highly variable clinical outcome in which both genetic and epigenetic changes have critical roles. We investigated tumor expression levels of histone-modifying enzymes LSD1, HDAC2 and SIRT1 in relation with patient survival and tumor relapse in a retrospective cohort of 460 breast cancer patients. Additionally, we correlated expression levels with tumor differentiation and tumor cell proliferation. METHODS: Immunohistochemical staining for LSD1, HDAC2 and SIRT1 was performed on tissue microarrays of tumor and corresponding normal formalin-fixed paraffin-embedded tissues from breast cancer patients. Median nuclear expression levels in tumor tissues were used to divide the patients into low and high expression categories. In combined expression analyses, patients were divided into four subgroups: 1, all enzymes below-median; 2, one enzyme above-median; 3, two enzymes above-median; 4, all three enzymes above-median. The Cox proportional hazard model was used for univariate and multivariate survival analyses. The Pearson Chi-square method was used to assess correlation of combined expression levels with tumor cell proliferation and tumor differentiation. RESULTS: Expression of LSD1 and SIRT1, but not of HDAC2, was significantly increased in tumor tissues compared to their normal counterparts (both p < 0.001). Multivariate survival analyses identified SIRT1 as independent prognostic factor for relapse-free survival (RFS) with a hazard ratio (HR) of 1.34 (95% CI = 1.04-1.74, p = 0.02). For overall survival (OS), no significant differences were found when the individual enzymes were analyzed. Analyses of combined expression levels of the three histone-modifying enzymes correlated with OS (p = 0.03) and RFS (p = 0.006) with a HR of respectively 1.49 (95% CI = 1.07-2.08) and 1.68 (95% CI = 1.16-2.44) in multivariate analyses and were also related to tumor differentiation (p < 0.001) and tumor cell proliferation (p = 0.002). CONCLUSIONS: When the combined expression levels were analyzed, high expression of LSD1, HDAC2 and SIRT1 showed shorter patient survival time and shorter time to tumor relapse and correlated with poor tumor differentiation and a high level of tumor cell proliferation. Expression of these histone-modifying enzymes might therefore be involved in breast cancer pathogenesis.

The Extended ToxTracker Assay Discriminates Between Induction of DNA Damage, Oxidative Stress, and Protein Misfolding.

Chemical exposure of cells may damage biomolecules, cellular structures, and organelles thereby jeopardizing cellular homeostasis. A multitude of defense mechanisms have evolved that can recognize specific types of damaged molecules and will initiate distinct cellular programs aiming to remove the damage inflicted and prevent cellular havoc. As a consequence, quantitative assessment of the activity of the cellular stress responses may serve as a sensitive reporter for the induction of specific types of damage. We have previously developed the ToxTracker assay, a mammalian stem cell-based genotoxicity assay employing two green fluorescent protein reporters specific for DNA damage and oxidative stress. We have now expanded the ToxTracker assay with an additional four reporter cell lines to include monitoring of additional stress signaling pathways. This panel of six green fluorescent protein reporters is able to discriminate between different primary reactivity of chemicals being their ability to react with DNA and block DNA replication, induce oxidative stress, activate the unfolded protein response, or cause a general P53-dependent cellular stress response. Extensive validation using the compound library suggested by the European Centre for the Validation of Alternative Methods (ECVAM) and a large panel of reference chemicals shows that the ToxTracker assay has an outstanding sensitivity and specificity. In addition, we developed Toxplot, a dedicated software tool for automated data analysis and graphical representation of the test results. Rapid and reliable identification by the ToxTracker assay of specific biological reactivity can significantly improve in vitro human hazard assessment of chemicals.

MicroRNA classifier and nomogram for metastasis prediction in colon cancer.

BACKGROUND: Colon cancer prognosis and treatment are currently based on a classification system still showing large heterogeneity in clinical outcome, especially in TNM stages II and III. Prognostic biomarkers for metastasis risk are warranted as development of distant recurrent disease mainly accounts for the high lethality rates of colon cancer. miRNAs have been proposed as potential biomarkers for cancer. Furthermore, a verified standard for normalization of the amount of input material in PCR-based relative quantification of miRNA expression is lacking. METHODS: A selection of frozen tumor specimens from two independent patient cohorts with TNM stage II-III microsatellite stable primary adenocarcinomas was used for laser capture microdissection. Next-generation sequencing was performed on small RNAs isolated from colorectal tumors from the Dutch cohort (N = 50). Differential expression analysis, comparing in metastasized and nonmetastasized tumors, identified prognostic miRNAs. Validation was performed on colon tumors from the German cohort (N = 43) using quantitative PCR (qPCR). RESULTS: miR25-3p and miR339-5p were identified and validated as independent prognostic markers and used to construct a multivariate nomogram for metastasis risk prediction. The nomogram showed good probability prediction in validation. In addition, we recommend combination of miR16-5p and miR26a-5p as standard for normalization in qPCR of colon cancer tissue-derived miRNA expression. CONCLUSIONS: In this international study, we identified and validated a miRNA classifier in primary cancers, and propose a nomogram capable of predicting metastasis risk in microsatellite stable TNM stage II-III colon cancer. IMPACT: In conjunction with TNM staging, by means of a nomogram, this miRNA classifier may allow for personalized treatment decisions based on individual tumor characteristics.