Can multiple SNP testing in BRCA2 and BRCA1 female carriers be used to improve risk prediction models in conjunction with clinical assessment?

Assessment of prognosis by established prognosis scores and physicians' judgement in mRCC patients: an analysis of the STAR-TOR registry

Background

Temsirolimus is a mTOR inhibitor approved for the first-line treatment of advanced or metastatic renal cell carcinoma (a/mRCC) with poor prognosis. In treatment of a/mRCC several prognostic scoring systems are used. We assessed the prognostic value of these scores in a large temsirolimus treated cohort and compared the results with the physician’s prognosis.

Methods

A German multicenter registry (STAR-TOR) for a/mRCC patients (NCT00700258) was established to evaluate the efficacy and safety of temsirolimus 25 mg weekly in a routine clinical setting. These prospective data were systematically analyzed and followed-up by an independent clinical research organization to compare established prognostic scores (MSKCC, IMDC and Hudes) with the risk assessment by treating physicians based on their medical expertise and match them with survival outcomes.

Results

This interim analysis included 547 patients between 02/2008 and 05/2015 in 87 centers. Either prognostic tool resulted in significant and clinically meaningful differentiation between good, intermediate and poor prognosis. However, physician’s prognosis identified more patients with good prognosis (9.1% vs. 1.3%). In patients with good physician’s prognosis and intermediate prognosis by MSKCC, overall survival was nearly doubled compared to consensual intermediate prognosis (26.6 vs. 13.6 months), albeit without reaching statistical significance (P=0.09). For poor prognosis assessed by the physician, MSKCC performed statistically better for differentiation between poor and intermediate prognosis with a median overall survival of 10.3 vs. 5.5 months (P<0.01).

Conclusions

Physician’s prognosis may be able to identify a subset of patients treated with temsirolimus with good prognosis when MSKCC-determines intermediate prognosis while the MSKCC score could identify patients which were falsely placed in the poor risk group by physicians.

K3326X and Other C-Terminal BRCA2 Variants Implicated in Hereditary Cancer Syndromes: A Review

Simple Summary

The cancer associated protein BRCA2 is the subject of intense continual study. Because of this, new insights into the relation of specific variants of this gene and cancer are regularly generated. These discoveries shed light on cancer risk and management for patients carrying these mutations. Additionally, new techniques for variant discovery and investigation are developed and tested, further enhancing scientific and clinical understanding of this key protein. In this review we will investigate the recent literature associated with variants in the C-terminus of BRCA2 and their effect on health and cancer predisposition.

Abstract

Whole genome analysis and the search for mutations in germline and tumor DNAs is becoming a major tool in the evaluation of risk as well as the management of hereditary cancer syndromes. Because of the identification of cancer predisposition gene panels, thousands of such variants have been catalogued yet many remain unclassified, presenting a clinical challenge for the management of hereditary cancer syndromes. Although algorithms exist to estimate the likelihood of a variant being deleterious, these tools are rarely used for clinical decision-making. Here, we review the progress in classifying K3326X, a rare truncating variant on the C-terminus of BRCA2 and review recent literature on other novel single nucleotide polymorphisms, SNPs, on the C-terminus of the protein, defined in this review as the portion after the final BRC repeat (amino acids 2058–3418).

Specific detection of stable single nucleobase mismatch using SU-8 coated silicon nanowires platform

Novel microarray platform for single nucleotide polymorphisms (SNPs) detection has been developed using silicon nanowires (SiNWs) as support and two different surface modification methods for attaining the necessary functional groups. Accordingly, we compared the detection specificity and stability over time of the probes printed on SiNWs modified with (3-aminopropyl)triethoxysilane (APTES) and glutaraldehyde (GAD), or coated with a simpler procedure using epoxy-based SU-8 photoresist. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) were used for comparative characterization of the unmodified and coated SiNWs. The hybridization efficiency was assessed by comprehensive statistical analysis of the acquired data from confocal fluorescence scanning of the manufactured biochips. The high detection specificity between the hybridized probes containing different mismatch types was demonstrated on SU-8 coating by one way ANOVA test (adjusted p value *** < .0001). The stability over time of the probes tethered on SiNWs coated with SU-8 was evaluated after 1, 4, 8 and 21 days of probe incubation, revealing values for coefficient of variation (CV) between 2.4% and 5.6%. The signal-to-both-standard-deviations ratio measured for SU-8 coated SiNWs platform was similar to the commercial support, while the APTES-GAD coated SiNWs exhibited the highest values.

Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis

BACKGROUND

The application of metabolomics in prospective cohort studies is statistically challenging. Given the importance of appropriate statistical methods for selection of disease-associated metabolites in highly correlated complex data, we combined random survival forest (RSF) with an automated backward elimination procedure that addresses such issues.

METHODS

Our RSF approach was illustrated with data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study, with concentrations of 127 serum metabolites as exposure variables and time to development of type 2 diabetes mellitus (T2D) as outcome variable. Out of this data set, Cox regression with a stepwise selection method was recently published. Replication of methodical comparison (RSF and Cox regression) was conducted in two independent cohorts. Finally, the R-code for implementing the metabolite selection procedure into the RSF-syntax is provided.

RESULTS

The application of the RSF approach in EPIC-Potsdam resulted in the identification of 16 incident T2D-associated metabolites which slightly improved prediction of T2D when used in addition to traditional T2D risk factors and also when used together with classical biomarkers. The identified metabolites partly agreed with previous findings using Cox regression, though RSF selected a higher number of highly correlated metabolites.

CONCLUSIONS

The RSF method appeared to be a promising approach for identification of disease-associated variables in complex data with time to event as outcome. The demonstrated RSF approach provides comparable findings as the generally used Cox regression, but also addresses the problem of multicollinearity and is suitable for high-dimensional data.

TOX3 protein expression is correlated with pathological characteristics in breast cancer

TOX3 is a newly identified gene that has been observed to correlate with breast cancer by genome-wide association studies (GWAS) in recent years. In addition, it has been noted that single-nucleotide polymorphisms (SNPs) in the TOX3 gene have a strong correlation with estrogen receptor (ER)-positive tumors. However, the role of TOX3 in breast carcinoma development is still unclear. There are limited studies on the subject of TOX3 mRNA expression in breast tumors and little information on the variation of TOX3 protein expression in relation to the clinical pathological features in breast cancer and healthy tissues. In this study, we characterize the protein expression of TOX3 in breast tumors with respect to various clinical and pathological characteristics and explore the correlation between TOX3 protein expression and ER-positive tumors. A breast cancer tissue microarray containing 267 human breast tumors and 25 healthy controls, breast cancer cell lines (ZR-75-1, MDA-MB-231, MCF-7 and Bcap-37) with positive or negative ER expression, tumor tissues and matched controls were used to analyze the protein expression levels of TOX3 by immunohistochemistry, western blot analysis and quantitative polymerase chain reaction. Among the 267 breast tumor specimens, ER expression was detected in 66 tumor tissues. The expression levels of TOX3 increased in breast carcinoma tissue compared with controls, and were higher in advanced carcinoma (T3 and T4), lymph node metastases tissues (N2) and stage III tissues. Furthermore, TOX3 protein expression was more intense in ER-positive tumors, but did not demonstrate a statistical significance. However, it was significantly increased in ER-positive breast cancer cell lines (ZR-75-1, MCF-7 and Bcap-37) compared with the MDA-MB-231 cell line, which had ER-negative expression. Our findings provide support to the hypothesis that TOX3 has a strong correlation with the development of breast cancer. The current study is likely to assist in investigating the mechanisms involved in breast cancer development.