Olfactory Receptors as Biomarkers in Human Breast Carcinoma Tissues

Weber, Lea; Maßberg, Désirée; Becker, Christian; Altmüller, Janine; Ubrig, Burkhard; Bonatz, G.; Wölk, Gerhard; Philippou, Stathis; Tannapfel, Andrea; Hatt, Hanns; Gisselmann, Günter

doi:10.3389/fonc.2018.00033

Cited by 56 publications

(55 citation statements)

References 56 publications

(69 reference statements)

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“…However, without the additional information provided by TIF-Seq2, those same RNA-seq datasets were not sufficient to confidently classify them as read-through transcripts. Interestingly, during the preparation of this work, a few cases have been investigated in detail and independently reported as fusion transcripts in agreement with our findings 26,27 .…”

Section: Identifying Read-through Transcriptssupporting

confidence: 90%

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Wang

Marques

et al. 2019

Preprint

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Eukaryotic transcriptomes are complex involving thousands of overlapping transcripts. The interleaved nature of the transcriptome complicates its annotation, limits our ability to identify regulatory regions and, in some cases, can lead to misinterpretation of gene expression. To improve the annotation of complex genomes, we have developed an optimized method, TIF-Seq2, able to sequence simultaneously the 5' and 3' end of individual mRNA molecules at single-nucleotide resolution. We investigate the transcriptome of a well characterized human cell line (K562) and identify thousands of new transcript isoforms. By focusing on RNAs challenging to investigate with RNA-seq, we accurately define boundaries of lowly expressed intergenic and read-through transcripts. We validate those novel features in cell lines and in Chronic Myeloid Leukaemia patients. Our results demonstrate that TIF-Seq2 improves the annotation of complex genomes facilitating the assignment of promoters to genes and the identification of transcriptionally fused proteins. Main

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Section: Identifying Read-through Transcriptssupporting

confidence: 90%

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Wang

Marques

et al. 2019

Preprint

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“…3g, h). Past reports evaluating the expression of chemosensory receptors in healthy tissues revealed the presence of multiple ORs 23,43 . We, therefore, examined the exclusivity of the ORs expressed in tumors.…”

Section: Resultsmentioning

confidence: 99%

Analysis of single-cell transcriptomes links enrichment of olfactory receptors with cancer cell differentiation status and prognosis

et al. 2020

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Ectopically expressed olfactory receptors (ORs) have been linked with multiple clinically-relevant physiological processes. Previously used tissue-level expression estimation largely shadowed the potential role of ORs due to their overall low expression levels. Even after the introduction of the single-cell transcriptomics, a comprehensive delineation of expression dynamics of ORs in tumors remained unexplored. Our targeted investigation into single malignant cells revealed a complex landscape of combinatorial OR expression events. We observed differentiation-dependent decline in expressed OR counts per cell as well as their expression intensities in malignant cells. Further, we constructed expression signatures based on a large spectrum of ORs and tracked their enrichment in bulk expression profiles of tumor samples from The Cancer Genome Atlas (TCGA). TCGA tumor samples stratified based on OR-centric signatures exhibited divergent survival probabilities. In summary, our comprehensive analysis positions ORs at the cross-road of tumor cell differentiation status and cancer prognosis.

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“…In addition to the previously described compartments of Basal-like tumor, Classical tumor, Activated stroma, Normal stroma, immune, endocrine and exocrine, we also identified two new compartments, which we annotated as olfactory and histone. Interestingly, a study has associated the olfactory transduction pathway with pancreatic cancer risk 27 , and additional studies have shown the overexpression of olfactory receptors in multiple cancer types, including prostate 28,29 , bladder 30 and breast 31 cancers. In agreement with these studies, we found that our olfactory compartment was indeed present in prostate adenocarcinoma (PRAD), bladder urothelial carcinoma (BLCA), as well as several other cancer types (Supplementary Data 1).…”

Section: Discussionmentioning

confidence: 99%

De novo compartment deconvolution and weight estimation of tumor samples (DECODER)

Peng¹,

Moffitt

Torphy³

et al. 2019

Preprint

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13Tumors are mixtures of different compartments. While global gene expression analysis 14 profiles the average expression of all compartments in a sample, identifying the specific 15 contribution of each compartment remains a challenge. With the increasing recognition 16 of the importance of non-neoplastic components, the ability to breakdown the gene 17 expression contribution of each is critical. To this end, we developed DECODER, an 18 integrated framework which performs de novo deconvolution, and compartment weight 19 estimation for a single sample. We use DECODER to deconvolve 33 TCGA tumor RNA-20 seq datasets and show that it may be applied to other data types including ATAC-seq. 21 We demonstrate that it can be utilized to reproducibly estimate cellular compartment 22 weights in pancreatic cancer that are clinically meaningful. Application of DECODER 23 across cancer types advances the capability of identifying cellular compartments in an 24 unknown sample and may have implications for identifying the tumor of origin for cancers 25 of unknown primary. 26 27 28 Tumor samples are mixtures of distinct cell populations that contribute to intra-tumor 29 heterogeneity, including immune, stroma and normal cells 1,2 . Therefore, with bulk tumor 30 samples, the analysis of tumor gene expression can be significantly confounded by the 31 presence of non-neoplastic cell types, while the contribution of the tumor 32 microenvironment is difficult to separate. Although laser-capture microdissection (LCM) 33 and single cell sequencing techniques strive to tackle these problems, both of them 34 present certain limitations. LCM is labor-intensive and may influence the quality of the 35 microdissected tissue for further analysis 3,4 . Single-cell sequencing is still expensive, 36 computing resource heavy, and currently limited by the lack of comprehensive cell-sorting 37 biomarkers 5,6 . 38 To eliminate the need of relying on LCM or single-cell-based techniques, a plethora of 39 computational strategies have been developed to deconvolve the mixed signal present in 40 a bulk tumor sample using RNA gene expression, DNA copy number data or DNA 41 methylation data. Algorithms based on DNA copy-number alterations, e.g. ABSOLUTE 7 , 42 and DNA methylation profiles, e.g. MethylPurify 8 and InfiniumPurify 9 , focus on inferring 43 tumor purity, while expression-based deconvolution methods mainly handle estimation of 44 compartment fractions, as well as extraction of compartment-specific expression profiles 2 . 45 However, the current expression-based deconvolution methods still pose a number of 46 limitations. Some methods are limited to the presupposition of a certain combination of 47 compartments, such as DeMix (tumor and normal) 10 , UNDO (tumor and stroma) 11 and 48 ESTIMATE (tumor, stroma and immune) 12 . Other methods such as DeconRNAseq 13 and 49 CIBERSORT 14 , provide the flexibility to measure any number of specific compartments. 50 However, they require knowledge of the pure expression of compartments as the 51 refe...

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Olfactory Receptors as Biomarkers in Human Breast Carcinoma Tissues

Cited by 56 publications

References 56 publications

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

Analysis of single-cell transcriptomes links enrichment of olfactory receptors with cancer cell differentiation status and prognosis

De novo compartment deconvolution and weight estimation of tumor samples (DECODER)

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