Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature.

The diagnosis of breast cancer-including determination of prognosis and prediction-has been traditionally based on clinical and pathological characteristics such as tumor size, nodal status, and tumor grade. The decision-making process has been expanded by the recent introduction of molecular signatures. These signatures, however, have not reached the highest levels of evidence thus far. Yet they have been brought to clinical practice based on statistical significance in prospective as well as retrospective studies. Intriguingly, it has also been reported that most random sets of genes are significantly associated with disease outcome. These facts raise two highly relevant questions: What information gain do these signatures procure? How can one find a signature that is substantially better than a random set of genes? Our study addresses these questions. To address the latter question, we present a hybrid signature that joins the traditional approach with the molecular one by combining the Nottingham Prognostic Index with gene expressions in a data-driven fashion. To address the issue of information gain, we perform careful statistical analysis and comparison of the hybrid signature, gene expression lists of two commercially available tests as well as signatures selected at random, and introduce the Signature Skill Score-a simple measure to assess improvement on random signatures. Despite being based on in silico data, our research is designed to be useful for the decision-making process of oncologists and strongly supports association of random signatures with outcome. Although our study shows that none of these signatures can be considered as the main candidate for providing prognostic information, it also demonstrates that both the hybrid signature and the gene expression list of the OncotypeDx signature identify patients who may not require adjuvant chemotherapy. More importantly, we show that combining signatures substantially improves the identification of patients who do not need adjuvant chemotherapy.

Improved Risk Stratification for Breast Cancer Samples Based on the Expression Ratio of the Estrogen and Progesterone Receptor.

BACKGROUND: The receptors for estrogen (ESR1) and progesterone (PGR) are both part of the same signaling pathway and routinely used for breast cancer stratification. We tested the hypothesis if a coordinated analysis could add extra information for prognostic stratification. MATERIALS AND METHODS: ESR1 and PGR gene expression was first investigated by quantitative reverse transcription polymerase chain reaction in fresh-frozen invasive ductal breast cancer samples (Hamburg collective, case-control, n=317). Our results were then tested using two datasets generated by different technical approaches: i) a public DNA-chip data set (GSE3494, n=251) and ii) semiquantitative protein expression data based on immunohistochemistry (Stuttgart collective, n=18,528). RESULTS: The PGR/ESR1 gene-expression ratio was a prognostic indicator in those with ESR1/PGR-positive breast cancer (Hamburg collective), with a high PGR/ESR1 expression ratio indicating a favorable outcome. In all three collectives, the PGR/ESR1 mRNA ratio or its protein equivalent was a univariate prognostic factor and also a multivariate prognostic factor in the Hamburg and Stuttgart collectives. CONCLUSION: Calculation of the PGR/ESR1 gene-expression ratio and its immunohistochemical surrogate could be a useful and simple addition to routine breast cancer diagnostics. A high PGR/ESR1 ratio could be indicative of a favorable clinical outcome.

Tubular breast cancer. A retrospective study.

BACKGROUND: The well-characterized tubular-type of breast tumors is classified as low-risk breast cancer. PATIENTS AND METHODS: We report on the results of a retrospective analysis on clinical and biological features of 248 tubular breast tumors including follow-up and treatment data from two German series of 21,065 breast cancer cases. The majority of tumors were stage I or stage II, ER- and PR-positive and c-erbB2-negative with a 5-year survival-rate of 96.3%. 51.3% of patients received hormonal treatment, 75.5% had post-operative radiotherapy and 11.8% were treated with a chemotherapeutical regimen. CONCLUSION: Our retrospective analysis showed no treatment benefit for either anti-hormonal or chemotherapeutical regimens. Post-operative radiotherapy, however, improved the survival rate of patients with tubular carcinoma (log-rank=5, p=0.025). Our data suggest that post-operative radiotherapy is an important treatment to prolong survival for patients suffering from tubular breast cancer.

A compartment-specific transcriptome analysis reveals survival-relevant marker genes in the stroma fraction of squamous non-small cell lung cancer.

Although it is increasingly recognized that the tumor biology is influenced by the tumor stroma, prognostic gene signatures are usually derived from tissue consisting of tumor cells and surrounding stroma. This study presents a compartment-specific transcriptome analysis of lung squamous cell carcinoma (SCC) samples microdissected into tumor parenchyma and stroma fractions. Typical tumor and stroma genes were identified based on the expression ratios between the two compartments. Our results indicate that in SCC many markers related to longer survival are predominantly expressed in the stroma, particularly genes of the MHC-II complex. Stromal upregulation of MHC-II genes seems crucial for a clinically relevant antitumor immune response in SCC.

Determinants of RNA quality from FFPE samples.

The large archives of formalin-fixed paraffin-embedded (FFPE) tissue specimens that exist are a highly valuable source of sample material for molecular biological analysis, including gene expression profiling. However, current data on adverse effects of standard pathological practice on the usefulness of biomolecular analytes obtained from such archived specimens is largely anecdotal. Here, we present a systematic examination of the most relevant parameters for integrity and useability of RNA obtained from FFPE samples, including storage time and conditions, fixation time, and specimen size. The results are particularly relevant for any application relying on cDNA synthesis as an initial step of the procedure, such as RT-PCR, and microarray analysis.