Immune Milieu and Genomic Alterations Set the Triple-Negative Breast Cancer Immunomodulatory Subtype Tumor Behavior.

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous disease. Seven subtypes have been described based on gene expression patterns. Herein, we characterized the tumor biology and clinical behavior of the immunomodulatory (IM) subtype. METHODS: Formalin-fixed paraffin-embedded tumor samples from 68 high-risk (stage III-IV) TNBC patients were analyzed through microarrays, immunohistochemistry, and DNA sequencing. RESULTS: The IM subtype was identified in 24% of TNBC tumor samples and characterized by a higher intratumoral (intT) and stromal (strml) infiltration of FOXP3+ TILs (Treg) compared with non-IM subtypes. Further, PD-L1+ (>1%) expression was significantly higher, as well as CTLA-4+ intT and strml expression in the IM subtype. Differential expression and gene set enrichment analysis identified biological processes associated with the immune system. Pathway analysis revealed enrichment of the ß-catenin signaling pathway. The non-coding analysis led to seven Long Intergenic Non-Protein Coding RNAs (lincRNAs) (6 up-regulated and 1 down-regulated) that were associated with a favorable prognosis in the TNBC-IM subtype. The DNA sequencing highlighted two genes relevant to immune system responses: CTNNB1 (Catenin ß-1) and IDH1. CONCLUSION: the IM subtype showed a distinct immune microenvironment, as well as subtype-specific genomic alterations. Characterizing TNBC at a molecular and transcriptomic level might guide immune-based therapy in this subgroup of patients.

SPEAQeasy: a scalable pipeline for expression analysis and quantification for R/bioconductor-powered RNA-seq analyses.

BACKGROUND: RNA sequencing (RNA-seq) is a common and widespread biological assay, and an increasing amount of data is generated with it. In practice, there are a large number of individual steps a researcher must perform before raw RNA-seq reads yield directly valuable information, such as differential gene expression data. Existing software tools are typically specialized, only performing one step-such as alignment of reads to a reference genome-of a larger workflow. The demand for a more comprehensive and reproducible workflow has led to the production of a number of publicly available RNA-seq pipelines. However, we have found that most require computational expertise to set up or share among several users, are not actively maintained, or lack features we have found to be important in our own analyses. RESULTS: In response to these concerns, we have developed a Scalable Pipeline for Expression Analysis and Quantification (SPEAQeasy), which is easy to install and share, and provides a bridge towards R/Bioconductor downstream analysis solutions. SPEAQeasy is portable across computational frameworks (SGE, SLURM, local, docker integration) and different configuration files are provided ( http://research.libd.org/SPEAQeasy/ ). CONCLUSIONS: SPEAQeasy is user-friendly and lowers the computational-domain entry barrier for biologists and clinicians to RNA-seq data processing as the main input file is a table with sample names and their corresponding FASTQ files. The goal is to provide a flexible pipeline that is immediately usable by researchers, regardless of their technical background or computing environment.

Prediction of neuropeptide precursors and differential expression of adipokinetic hormone/corazonin-related peptide, hugin and corazonin in the brain of malaria vector Nyssorhynchus albimanus during a Plasmodium berghei infection.

Insect neuropeptides, play a central role in the control of many physiological processes. Based on an analysis of Nyssorhynchus albimanus brain transcriptome a neuropeptide precursor database of the mosquito was described. Also, we observed that adipokinetic hormone/corazonin-related peptide (ACP), hugin and corazonin encoding genes were differentially expressed during Plasmodium infection. Transcriptomic data from Ny. albimanus brain identified 29 pre-propeptides deduced from the sequences that allowed the prediction of at least 60 neuropeptides. The predicted peptides include isoforms of allatostatin C, orcokinin, corazonin, adipokinetic hormone (AKH), SIFamide, capa, hugin, pigment-dispersing factor, adipokinetic hormone/corazonin-related peptide (ACP), tachykinin-related peptide, trissin, neuropeptide F, diuretic hormone 31, bursicon, crustacean cardioactive peptide (CCAP), allatotropin, allatostatin A, ecdysis triggering hormone (ETH), diuretic hormone 44 (Dh44), insulin-like peptides (ILPs) and eclosion hormone (EH). The analysis of the genome of An. albimanus and the generated transcriptome, provided evidence for the identification of myosuppressin neuropeptide precursor. A quantitative analysis documented increased expression of precursors encoding ACP peptide, hugin and corazonin in the mosquito brain after Plasmodium berghei infection. This work represents an initial effort to characterize the neuropeptide precursors repertoire of Ny. albimanus and provides information for understanding neuroregulation of the mosquito response during Plasmodium infection.