Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.

/pdf/cutoff-finder-a-comprehensive-and-straightforward-web-1wrxsr3xvo.pdf

Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736%2807%2961232-X.pdf

MRI for diagnosis of pure ductal carcinoma in situ: a prospective observational study

MRI for diagnosis of pure ductal carcinoma in situ : a prospective observational study. Commentary

Prostate cancer biology varies from locally confined tumors with low risk for relapse to tumors with high risk for progression even after radical prostatectomy. Currently, there are no reliable biomarkers to predict tumor relapse and poor clinical outcome. In this study, we correlated expression patterns of the androgen receptor (AR) coactivators lysine-specific histone demethylase 1 (LSD1) and four and a half LIM-domain protein 2 (FHL2), AR, Gleason score, Gleason grade, and p53 expression in clinically organ confined prostate cancers with relapse after radical prostatectomy. Our data reveal that high levels of LSD1, nuclear expression of the FHL2 coactivator, high Gleason score and grade, and very strong staining of nuclear p53 correlate significantly with relapse during follow-up. No correlation exists with relapse and the expression of AR and cytoplasmic expression of FHL2. To confirm these data, we did quantitative reverse transcription-PCR and Western blot analyses in a subset of tumor specimens. Consistently, both LSD1 mRNA and protein levels were significantly up-regulated in high-risk tumors. We previously identified LSD1 and FHL2 as nuclear cofactors interacting specifically with the AR in prostate cells and showed that both stimulate androgen-dependent gene transcription. Our present study suggests that LSD1 and nuclear FHL2 may serve as novel biomarkers predictive for prostate cancer with aggressive biology and point to a role of LSD1 and FHL2 in constitutive activation of AR-mediated growth signals.

https://cancerres.aacrjournals.org/content/canres/66/23/11341.full.pdf

Androgen receptor coactivators lysine-specific histone demethylase 1 and four and a half LIM domain protein 2 predict risk of prostate cancer recurrence.

Activation of lipid metabolism is an early event in carcinogenesis and a central hallmark of many cancers. However, the precise molecular composition of lipids in tumors remains generally poorly characterized. The aim of the present study was to analyze the global lipid profiles of breast cancer, integrate the results to protein expression, and validate the findings by functional experiments. Comprehensive lipidomics was conducted in 267 human breast tissues using ultraperformance liquid chromatography/ mass spectrometry. The products of de novo fatty acid synthesis incorporated into membrane phospholipids, such as palmitate-containing phosphatidylcholines, were increased in tumors as compared with normal breast tissues. These lipids were associated with cancer progression and patient survival, as their concentration was highest in estrogen receptor-negative and grade 3 tumors. In silico transcriptomics database was utilized in investigating the expression of lipid metabolism related genes in breast cancer, and on the basis of these results, the expression of specific proteins was studied by immunohistochemistry. Immunohistochemical analyses showed that several genes regulating lipid metabolism were highly expressed in clinical breast cancer samples and supported also the lipidomics results. Gene silencing experiments with seven genes [ACACA (acetyl-CoA carboxylase α), ELOVL1 (elongation of very long chain fatty acid-like 1), FASN (fatty acid synthase), INSIG1 (insulin-induced gene 1), SCAP (sterol regulatory element-binding protein cleavage-activating protein), SCD (stearoyl-CoA desaturase), and THRSP (thyroid hormone-responsive protein)] indicated that silencing of multiple lipid metabolism-regulating genes reduced the lipidomic profiles and viability of the breast cancer cells. Taken together, our results imply that phospholipids may have diagnostic potential as well as that modulation of their metabolism may provide therapeutic opportunities in breast cancer treatment.

https://cancerres.aacrjournals.org/content/canres/71/9/3236.full.pdf

Novel Theranostic Opportunities Offered by Characterization of Altered Membrane Lipid Metabolism in Breast Cancer Progression

Recommendation for uniform definition of an immunoreactive score (IRS) for immunohistochemical estrogen receptor detection (ER-ICA) in breast cancer tissue

H E Stegner

Papers

Recommendation for uniform definition of an immunoreactive score (IRS) for immunohistochemical estrogen receptor detection (ER-ICA) in breast cancer tissue