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Victor D Martinez
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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 | Author(s): Victor D Martinez
- 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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MA24.07 - A Novel cis-Acting lncRNA Controls HMGA1 Expression in Lung Adenocarcinoma (ID 13979)
11:10 - 11:15 | Author(s): Victor D Martinez
- Abstract
- Presentation
Background
High mobility group A1 (HMGA1) chromatin remodeling protein is enriched in several aggressive cancer types, including NSCLC, where mRNA and protein expression are markedly increased. Additionally, high HMGA1 expression has been associated with poor overall survival and chemotherapy resistance. While HMGA1 is deregulated in lung cancer, the mechanisms that mediate its expression are only beginning to emerge. Long non-coding RNAs (lncRNAs), are a class of transcripts have been implicated in the onset of cancer-associated phenotypes in tumourigenesis and metastasis. Recently, an emerging class of lncRNAs - cis-acting - has been shown to regulate the expression of neighbouring protein-coding genes, including oncogenes and tumour suppressor genes. Thus, lncRNAs may represent novel actionable therapeutic intervention points in known cancer driving pathways. Here we investigate the role of a cis-acting lncRNA, RP11.513I15.6, its deregulation in NSCLC, and its relationship with HMGA1.
a9ded1e5ce5d75814730bb4caaf49419 Method
LncRNA transcriptomes were deduced from RNA-sequences of 36 microdissected tumour and matched non-malignant tissues. Normalized sequence read counts were used to identify transcripts with significantly deregulated expression (Wilcoxon Signed-Rank Test, BH-p<0.05). Sequencing data obtained from The Cancer Genome Atlas were analyzed to validate these results. SiRNA-mediated knockdown of lncRNA candidates identified in these analyses were performed in a non-malignant lung epithelial cell line (BEAS-2B). Quantitative real-time PCR quantified the effects of lncRNA knockdown on the expression of neighbouring cancer-associated protein-coding genes.
4c3880bb027f159e801041b1021e88e8 Result
Our analyses identified RP11.513I15.6, an undescribed lncRNA neighbouring HMGA1, to be significantly downregulated in adenocarcinoma (>2-fold downregulation in 81.5% of cases). This observation was confirmed in our validation cohort. HMGA1 expression was found to be anticorrelated with RP11.513I15.6, as tumours with downregulated RP11.513I15.6 displayed significant overexpression of HMGA1. This suggested that this lncRNA may be a key negative regulator of HMGA1. In vitro experiments demonstrated siRNA-mediated inhibition of RP11.513I15.6 in immortalized lung epithelial cells resulted in a significant increase in the expression of HMGA1 mRNA and protein. Taken together, our results suggest that RP11.513I15.6 is a novel cis-acting lncRNA that negatively regulates HMGA1, and may contribute mechanistically to the maintenance of cancer phenotypes.
8eea62084ca7e541d918e823422bd82e Conclusion
We have discovered a novel, 18-fold downregulated transcript that is anti-correlated with expression of HMGA1, a well established oncogene. In vitro studies support the hypothesis that this transcript, RP11.513I15.6, is a cis-acting lncRNA as siRNA-mediated inhibition led to upregulation of neighbouring HMGA1. Characterizing this oncogene regulatory mechanism will not only further our understanding of cancer biology, but could uncover a novel therapeutic intervention point.
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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 | Author(s): Victor D Martinez
- 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.
6f8b794f3246b0c1e1780bb4d4d5dc53Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
