A 16 Yin Yang gene expression ratio signature for ER+/node- breast cancer.

Breast cancer is one of the leading causes of cancer death in women. It is a complex and heterogeneous disease with different clinical outcomes. Stratifying patients into subgroups with different outcomes could help guide clinical decision making. In this study, we used two opposing groups of genes, Yin and Yang, to develop a prognostic expression ratio signature. Using the METABRIC cohort we identified a16-gene signature capable of stratifying breast cancer patients into four risk levels with intention that low-risk patients would not undergo adjuvant systemic therapy, intermediate-low-risk patients will be treated with hormonal therapy only, and intermediate-high- and high-risk groups will be treated by chemotherapy in addition to the hormonal therapy. The 16-gene signature for four risk level stratifications of breast cancer patients has been validated using 14 independent datasets. Notably, the low-risk group (n = 51) of 205 estrogen receptor-positive and node negative (ER+/node-) patients from three different datasets who had not had any systemic adjuvant therapy had 100% 15-year disease-specific survival rate. The Concordance Index of YMR for ER+/node negative patients is close to the commercially available signatures. However, YMR showed more significance (HR = 3.7, p = 8.7e-12) in stratifying ER+/node- subgroup than OncotypeDx (HR = 2.7, p = 1.3e-7), MammaPrint (HR = 2.5, p = 5.8e-7), rorS (HR = 2.4, p = 1.4e-6), and NPI (HR = 2.6, p = 1.2e-6). YMR signature may be developed as a clinical tool to select a subgroup of low-risk ER+/node- patients who do not require any adjuvant hormonal therapy (AHT).

A 10-Gene Yin Yang Expression Ratio Signature for Stage IA and IB Non-Small Cell Lung Cancer.

INTRODUCTION: Lung cancer is the leading killer cancer worldwide. There is an urgent need for easy-to-use and robust clinical gene signatures for improved prognosis and treatment prediction. METHODS: We used a gene expression signature termed the Yin and Yang mean ratio (YMR), which is based on two groups of genes with opposing function, to determine lung cancer prognosis. The YMR signature represents the relative state of an individual tumor on a gene expression spectrum ranging from malignancy to the normal healthy lung. The genes in the YMR signature have therefore been determined independently of survival time, which is different from previous regression models. We then leveraged the cross-platform utility of the YMR signature to optimize the signature into a smaller set of genes that validated the robustness of the signature in many independent lung cancer expression data sets. RESULTS: Four Yin and six Yang genes were optimized using 741 NSCLC cases from diverse platforms, including microarray and RNA sequencing. The 10-gene signature demonstrated significant differences in survival in eight individual independent data sets and a larger combined 1346-patient data set. When multivariate analysis taking into account other common predictors of survival was used, the 5-year recurrence-free rate of YMR (p = 6.4 × 10-6, HR =1.71 [1.36-2.16]) was secondary only to stage. The YMR signature significantly separated high- and low-risk patients with stage IA or 1B adenocarcinoma and squamous cell carcinomas of all stages. The YMR signature can also predict the benefit of adjuvant chemotherapy in high-risk patients with stage I NSCLC. CONCLUSIONS: The YMR signature has great potential for guiding clinical management for NSCLC, particularly early-stage disease. The signature appears more reproducible than older signatures and functions using a variety of common gene expression platforms.