Abstract
Motivation and backgroundThe patient’s immune system plays an important role in cancer pathogenesis, prognosis and susceptibility to treatment. Recent work introduced an immune related breast cancer. This subtyping is based on the expression profiles of the tumor samples. Specifically, one study showed that analyzing 658 genes can lead to a signature for subtyping tumors. Furthermore, this classification is independent of other known molecular and clinical breast cancer subtyping. Finally, that study shows that the suggested subtyping has significant prognostic implications.ResultsIn this work we develop an efficient signature associated with survival in breast cancer. We begin by developing a more efficient signature for the above-mentioned breast cancer immune-based subtyping. This signature represents better performance with a set of 579 genes that obtains an improved Area Under Curve (AUC). We then determine a set of 193 genes and an associated classification rule that yield subtypes with a much stronger statistically significant (log rank p-value < 2 × 10−4 in a test cohort) difference in survival. To obtain these improved results we develop a feature selection process that matches the high-dimensionality character of the data and the dual performance objectives, driven by survival and anchored by the literature subtyping.
Highlights
Molecular profiling of tumors has improved disease management and personalized cancer medicine
Trained classifier results are associated with tumor infiltrating lymphocytes levels We further examined our classification results on the training set, using the 193 gene set (Point B)
Ranking genes according to differential expressions between these two sets, we found 21 genes that have a significantly lower expression in Cluster B (CB) at False Discovery Rate (FDR) = 0.05
Summary
Molecular profiling of tumors has improved disease management and personalized cancer medicine. Gene expression-based signatures distinguish five breast cancer subtypes [1,2,3]—Luminal A, Luminal B, Her2-enriched, Basal-like and Normal-like. These subtypes are clinically relevant for breast cancer management and personalized treatment [4]. Understanding the effect of the immune landscape of tumors and their environment can lead to better characterization and subtyping in breast cancer. Such insight could possibly contribute significantly to improving disease management. As immunotherapies emerge as a new treatment option for breast cancer, it is important to determine which patients will benefit from such treatment alternatives
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