Using RNA Sequencing to Characterize the Tumor Microenvironment

Abstract

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), freshfrozen, 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.

Defining best practices for tissue procurement in immuno-oncology clinical trials: consensus statement from the Society for Immunotherapy of Cancer Surgery Committee

“…26 Applying modern quality controls for NGS has also been shown to improve the analysis of immunerelated gene expression in FFPE tumor biospecimens. 27 These studies support the use of FFPE for immunological studies, and using current quality control measures helps support high accuracy and reproducibility of data derived from heterogeneous RNA samples.…”

Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

“…In recent years, some scholars have questioned that the current TNM staging system cannot accurately forecast cancer patipatient’sgnosis, so it should be revised [ 27 , 28 ]. A growing number of studies have found that HCC has a variety of molecular characteristics and clinical results, which are strongly bound up with the prognosis of HCC patients according to exon sequencing, genomic characteristics and transcriptome analysis [ 29 , 30 ], autophagy takes different parts in different stages of HCC, which substantially affects the efficacy of various treatments.…”

A Toolkit for Profiling the Immune Landscape of Pediatric Central Nervous System Malignancies

“…Briefly, RNA is isolated from fresh, frozen, or FFPE tumor tissue using preparation kits, followed by ribosomal RNA depletion. Total RNA (including mRNA, lncRNA, and miRNA) undergoes reverse transcription to convert it to cDNA libraries, which are subsequently fragmented, amplified by PCR, and sequenced ( 73 ). The sequence reads are then aligned to a reference genome and expression counts can be determined or other analyses can be performed.…”