Abstract
BackgroundWhile standard RNA expression tests stratify patients into risk groups, RNA-Seq can guide personalized drug selection based on expressed mutations, fusion genes, and differential expression (DE) between tumor and normal tissue. However, patient-matched normal tissue may be unavailable. Additionally, biological variability in normal tissue and technological biases may confound results. Therefore, we present normal expression reference data for two sequencing methods that are suitable for breast biopsies.ResultsWe identified breast cancer related and drug related genes that are expressed uniformly across our normal samples. Large subsets of these genes are identical for formalin fixed paraffin embedded samples and fresh frozen samples. Adipocyte signatures were detected in frozen compared to formalin samples, prepared by surgeons and pathologists, respectively. Gene expression confounded by adipocytes was identified using fat tissue samples. Finally, immune repertoire statistics were obtained for healthy breast, tumor and fat tissues.ConclusionsOur reference data can be used with patient tumor samples that are asservated and sequenced with a matching aforementioned method. Coefficients of variation are given for normal gene expression. Thus, potential drug selection can be based on confidently overexpressed genes and immune repertoire statistics.Materials and MethodsNormal expression from formalin and frozen healthy breast tissue samples using Roche Kapa RiboErase (total RNA) (19 formalin, 9 frozen) and Illumina TruSeq RNA Access (targeted RNA-Seq, aka TruSeq RNA Exome) (11 formalin, 1 frozen), and fat tissue (6 frozen Access). Tumor DE using 10 formalin total RNA tumor samples and 1 frozen targeted RNA tumor sample.
Highlights
Breast cancer is the most common cancer affecting women, with over 265,000 newly diagnosed cases in the USA [1] and over 70,000 in Germany [2], respectively
Our reference data can be used with patient tumor samples that are asservated and sequenced with a matching aforementioned method
Coefficients of variation are given for normal gene expression
Summary
Breast cancer is the most common cancer affecting women, with over 265,000 newly diagnosed cases in the USA [1] and over 70,000 in Germany [2], respectively. Patients are treated according to the histological, molecular and in some cases even genetic classification of their cancer. Tumor tissue based DNA testing with targeted next-generation sequencing panels is performed in a growing number of centers. Genetic counselling and blood tests for hereditary breast cancer risk variants in BRCA1, BRCA2, TP53 and other genes are routinely offered. Standard treatment with curative intent contains surgical resection of the tumor (segmentectomy or mastectomy) and lymph node staging. Patients with hereditary risk variants in BRCA1, BRCA2 or other core breast cancer risk genes may be offered bilateral subcutaneous mastectomy and ovarectomy. While standard RNA expression tests stratify patients into risk groups, RNA-Seq can guide personalized drug selection based on expressed mutations, fusion genes, and differential expression (DE) between tumor and normal tissue. We present normal expression reference data for two sequencing methods that are suitable for breast biopsies
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