Using RNA Sequencing to Characterize the Tumor Microenvironment.

RNA sequencing (RNA-seq) is an integral tool in immunogenomics, allowing for interrogation of the transcriptome of a tumor and its microenvironment. Analytical methods to deconstruct the genomics data can then be applied to infer gene expression patterns associated with the presence of various immunocyte populations. High quality RNA-seq is possible from formalin-fixed, paraffin-embedded (FFPE), fresh-frozen, and fresh tissue, with a wide variety of sequencing library preparation methods, sequencing platforms, and downstream bioinformatics analyses currently available. Selection of an appropriate library preparation method is largely determined by tissue type, quality of RNA, and quantity of RNA. Downstream of sequencing, many analyses can be applied to the data, including differential gene expression analysis, immune gene signature analysis, gene pathway analysis, T/B-cell receptor inference, HLA inference, and viral transcript quantification. In this chapter, we will describe our workflow for RNA-seq from bulk tissue to evaluable data, including extraction of RNA, library preparation methods, sequencing of libraries, alignment and quality assurance of data, and initial downstream analyses of RNA-seq data to extract relevant immunogenomics features. Systems biology methods that draw additional insights by integrating these features are covered further in Chapters 28 - 30 .

Breast cancer PAM50 signature: correlation and concordance between RNA-Seq and digital multiplexed gene expression technologies in a triple negative breast cancer series.

BACKGROUND: Full RNA-Seq is a fundamental research tool for whole transcriptome analysis. However, it is too costly and time consuming to be used in routine clinical practice. We evaluated the transcript quantification agreement between RNA-Seq and a digital multiplexed gene expression platform, and the subtype call after running the PAM50 assay in a series of breast cancer patients classified as triple negative by IHC/FISH. The goal of this study is to analyze the concordance between both expression platforms overall, and for calling PAM50 triple negative breast cancer intrinsic subtypes in particular. RESULTS: The analyses were performed in paraffin-embedded tissues from 96 patients recruited in a multicenter, prospective, non-randomized neoadjuvant triple negative breast cancer trial (NCT01560663). Pre-treatment core biopsies were obtained following clinical practice guidelines and conserved as FFPE for further RNA extraction. PAM50 was performed on both digital multiplexed gene expression and RNA-Seq platforms. Subtype assignment was based on the nearest centroid classification following this procedure for both platforms and it was concordant on 96% of the cases (N = 96). In four cases, digital multiplexed gene expression analysis and RNA-Seq were discordant. The Spearman correlation to each of the centroids and the risk of recurrence were above 0.89 in both platforms while the agreement on Proliferation Score reached up to 0.97. In addition, 82% of the individual PAM50 genes showed a correlation coefficient > 0.80. CONCLUSIONS: In our analysis, the subtype calling in most of the samples was concordant in both platforms and the potential discordances had reduced clinical implications in terms of prognosis. If speed and cost are the main driving forces then the preferred technique is the digital multiplexed platform, while if whole genome patterns and subtype are the driving forces, then RNA-Seq is the preferred method.

In vitro and in vivo analysis of B-Myb in basal-like breast cancer.

A defining feature of basal-like breast cancer, a breast cancer subtype with poor clinical prognosis, is the high expression of 'proliferation signature' genes. We identified B-Myb, a MYB family transcription factor that is often amplified and overexpressed in many tumor types, as being highly expressed in the proliferation signature. However, the roles of B-Myb in disease progression, and its mammary-specific transcriptional targets, are poorly understood. Here, we showed that B-Myb expression is a significant predictor of survival and pathological complete response to neoadjuvant chemotherapy in breast cancer patients. We also identified a significant association between the G/G genotype of a nonsynonymous B-Myb germline variant (rs2070235, S427G) and an increased risk of basal-like breast cancer [OR 2.0, 95% CI (1.1-3.8)]. In immortalized, human mammary epithelial cell lines, but not in basal-like tumor lines, cells ectopically expressing wild-type B-Myb or the S427G variant showed increased sensitivity to two DNA topoisomerase IIalpha inhibitors, but not to other chemotherapeutics. In addition, microarray analyses identified many G2/M genes as being induced in B-Myb overexpressing cells. These results confirm that B-Myb is involved in cell cycle control, and that its dysregulation may contribute to increased sensitivity to a specific class of chemotherapeutic agents. These data provide insight into the influence of B-Myb in human breast cancer, which is of potential clinical importance for determining disease risk and for guiding treatment.