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Brenda C. Minatel
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MA21 - Molecular Subtyping, CBL3, and Non Coding RNA (ID 924)
- Event: WCLC 2018
- Type: Mini Oral Abstract Session
- Track: Biology
- Presentations: 1
- Moderators:
- Coordinates: 9/25/2018, 15:15 - 16:45, Room 205 BD
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MA21.10 - Large-Scale Discovery of Novel Human Oncofetal Transcripts in Lung (ID 13552)
16:20 - 16:25 | Presenting Author(s): Brenda C. Minatel
- Abstract
- Presentation
Background
Oncofetal genes are those expressed during both embryogenesis and tumourigenesis, but silenced in normal adult tissues. Although most described oncofetal genes have been shown to play important roles in tumour development and display potential as diagnostic and prognostic markers, this area of research remains largely unexplored. The advent of high-throughput technologies has not only allowed for large-scale discovery of biomarkers, but has also highlighted the role of non-coding RNAs from tissue development to malignant transformation. Small non-coding RNAs (sncRNAs, e.g., miRNA, snoRNA, piRNA, snRNA) are key players in gene-regulatory networks, and have shown promise as fluid-based biomarkers. In this study, we performed a comprehensive characterization of the sncRNA transcriptome of fetal, non-malignant and tumour lung tissues to identify development-associated (oncofetal) sncRNAs with roles in lung cancer, including the discovery of previously unannotated miRNAs.
a9ded1e5ce5d75814730bb4caaf49419 Method
Here, 209 paired non-malignant/tumour lung samples from two cohorts (BCCA, n=118 and TCGA, n=91) and 25 fetal lung samples were analyzed through the platform miRMaster. This platform aligns sequence reads to the hg38 genomic build, quantifies known sncRNA species and predicts novel miRNA candidates using the mirDeep2 algorithm. The sncRNA species that had no significant alterations in expression between fetal and tumours samples, but displayed significant differential expression between fetal/non-malignant and tumour/non-malignant tissues were classified as oncofetal sncRNAs. The biological relevance of the oncofetal sncRNAs and the novel miRNA candidates was investigated by gene-target prediction and pathway enrichment analyses, using mirDIP, IID and pathDIP databases.
4c3880bb027f159e801041b1021e88e8 Result
Our study provides the first large-scale characterization of the lung sncRNA transcriptome in fetal, non-malignant and tumour tissues. In particular, we discovered the expression of 464 novel miRNA candidates and identified a large subset of oncofetal sncRNAs. Target prediction analysis showed that the novel miRNA candidates discovered in all lung tissues are involved in cellular processes associated with cell proliferation, migration and survival, including the Wnt, MAPK and Notch signaling pathways, which are known to be associated with the development and progression of lung cancer. Additionally, oncofetal sncRNAs were found to be associated with cell cycle control and differentiation, highlighting the functional relevance of these molecules.
8eea62084ca7e541d918e823422bd82e Conclusion
We have not only expanded the lung sncRNA transcriptome, but also revealed the expression of a large number of sncRNAs relevant to lung tumourigenesis that are not expressed in normal adult tissues. Our results will aid in the development of more accurate fluid-based biomarkers for the early-detection of lung cancer.
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MA24 - Genomic Evolution, KEAP 3 and More Non-Coding RNA (ID 928)
- Event: WCLC 2018
- Type: Mini Oral Abstract Session
- Track: Biology
- Presentations: 1
- Moderators:
- Coordinates: 9/26/2018, 10:30 - 12:00, Room 205 BD
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MA24.06 - Long Non-Coding Rna Expression Patterns Delineate Infiltrating Immune Cells in the Lung Tumour Microenvironment (ID 13978)
11:05 - 11:10 | Author(s): Brenda C. Minatel
- Abstract
- Presentation
Background
The tumour microenvironment is characterized by complex interactions between different cell types, including immune cells that may exhibit pro- or anti-tumour effects. Sequencing and deconvolution techniques present opportunities to identify immune cell composition of bulk tumour data; similarly, these have renewed an interest in the non-coding transcriptome and its regulation of immune- and tumour-biology. Numerous long non-coding RNAs (lncRNAs; >200nt) have emerged as regulators of tumour initiation, progression, and metastasis. Additionally, several immune-related lncRNAs mediate fine-level regulation to balance pro- and anti-inflammatory phenotypes; yet, the landscape of lncRNA expression in human immune cells remains uncharacterized. Thus, delineating these multifaceted regulatory networks is critical to cancer immunology, particularly in immunogenic malignancies such as lung cancer.
a9ded1e5ce5d75814730bb4caaf49419 Method
RNA-sequencing data of purified immune-cell subsets (CD8+ T, CD4+ T, B, Monocytes, Neutrophils, and Natural Killer) obtained from flow-sorted healthy peripheral blood samples were probed for lncRNA expression. Sequencing reads were aligned to the hg38 reference genome and quantified to Ensembl v89, yielding 4919 expressed lncRNAs. These immune-associated lncRNAs were correlated with immune cell infiltrate in tumour and paired non-malignant lung adenocarcinoma samples (n=54, The Cancer Genome Atlas) as estimated by the proportion of consistent immune-associated methylation profiles, denoted by leukocytes unmethylation for purity (LUMP) scores.
4c3880bb027f159e801041b1021e88e8 Result
We observed that lncRNA expression patterns display a greater degree of cell-type specificity than protein-coding genes in immune cells. In fact, 676 lncRNAs had detectable expression in exclusively one cell type. We uncovered previously-uncharacterized lncRNAs that have expression patterns suggestive of immune-regulatory roles. Compared with lung tumour samples, 19 immune-associated lncRNAs were significantly negatively correlated with LUMP scores (r<-0.400, BH-p<0.0100), 17 of which were also strongly positively correlated with CD45 gene expression (r>0.400, BH-p<0.0100) suggesting expression from immune rather than tumour cells. For instance, the lncRNA USP30-AS1 is significantly downregulated in tumours (average fold-change=2.96, BH-p=6.88*10-13), suggesting its relevance to tumour biology; however, higher transcript expression is correlated with decreased LUMP score (r=-0.685, BH-p=1.02*10-4), illustrating its specificity to immune cells.
8eea62084ca7e541d918e823422bd82e Conclusion
Here, we present an atlas of cell-type specific lncRNAs in human immune cells. Our data suggest a functional relevance of lncRNAs to the biology of the tumour microenvironment, and the necessary consideration of tumour purity when examining non-coding RNA expression in order to avoid conclusions confounded by immune cells in bulk tumour data. Thus, we provide a resource for further elucidation of genomic links between immune and malignant cells, which may aid the development of future prognostic and therapeutic strategies.
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OA08 - Mesothelioma: Immunotherapy and microRNA for Diagnosis and Treatment (ID 907)
- Event: WCLC 2018
- Type: Oral Abstract Session
- Track: Mesothelioma
- Presentations: 1
- Moderators:
- Coordinates: 9/24/2018, 15:15 - 16:45, Room 201 BD
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OA08.07 - In Silico Discovery of Unannotated miRNAs in Malignant Pleural Mesothelioma Reveals Novel Tissue-of-Origin Markers (ID 14155)
16:20 - 16:30 | Presenting Author(s): Brenda C. Minatel
- Abstract
- Presentation
Background
Malignant pleural mesothelioma (MPM) is an aggressive disease. One of the major clinical challenges associated with MPM is the lack of biomarkers capable of distinguishing primary MPM from cancers that have metastasized to the pleura. The current gold standard consists of a panel of positive and negative protein markers to confirm tissue-of-origin; however, many cases remain undistinguishable from other thoracic cancers. Recent studies have suggested that the human genome encodes more microRNAs (miRNAs) than currently annotated. These undescribed sequences have been shown to display enhanced tissue and lineage specificity. Therefore, we hypothesize that MPM tumors express a specific set of previously unannotated miRNA sequences with tissue-specific expression capable of distinguishing MPM from other thoracic diseases.
a9ded1e5ce5d75814730bb4caaf49419 Method
Novel miRNA candidates were detected from small RNA-sequencing data generated by The Cancer Genome Atlas (TCGA) (n=87 MPM) using the miRDeep2 algorithm, a well-established novel-miRNA prediction algorithm. The possible biological roles of these miRNA candidates were investigated by performing a genome-wide 3’UTR target prediction analysis. Additionally, their tissue-specificity was assessed using expression profiles of 1,093 lung tumors from four independent cohorts of adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Finally, we developed a miRNA-based classifier model using the weighted voting class prediction method to distinguish MPM from other thoracic cancers.
4c3880bb027f159e801041b1021e88e8 Result
Our initial analysis revealed 424 miRNA candidates, which were subsequently filtered by RNA structure, abundance of sequencing reads, and genomic location, resulting in 154 previously unannotated miRNA sequences. Interestingly, the novel miRNAs were predicted to target protein-coding genes involved in MPM biology, including the Ataxia Telangiectasia Mutated (ATM) gene, a tumour-supressor gene frequently mutated in MPM. Likewise BRCA1 Associated Protein 1 (BAP1), involved in the DNA damage response pathway, was also a predicted target. Principal component analyses revealed that novel-miRNA expression was able to distinguish MPM from LUAD and LUSC. Furthermore, our miRNA-based classifier model revealed 10 novel miRNAs capable of successfully identifying 86 out of the 87 MPM cases (98.80%) and 100% of LUAD cases (true positive rate = 98.85%, false positive rate = 1.150%).
8eea62084ca7e541d918e823422bd82e Conclusion
Here, we provide evidence for the presence of 154 previously unannotated miRNA species relevant to MPM. These miRNAs not only significantly expand the miRNA repertoire but also unveil specific roles in MPM biology. Most importantly, the strikingly high sensitivity and specificity of the novel miRNA-based classifier in distinguishing MPM from LUAD illustrates the potential of using these novel miRNAs to supplement current clinical markers to define MPM.
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