Met exon 14 skipping: A case study for the detection of genetic variants in cancer driver genes by deep learning

Background: Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell lung cancer (NSCLC) MET exon 14 skipping was shown to be targetable. Methods: We constructed neural networks (NN/CNN) specifically designed to detect MET exon 14 skipping events using RNAseq data. Furthermore, for discovery purposes we also developed a sparsely connected autoencoder to identify uncharacterized MET isoforms. Results: The neural networks had a Met exon 14 skipping detection rate greater than 94% when tested on a manually curated set of 690 TCGA bronchus and lung samples. When globally applied to 2605 TCGA samples, we observed that the majority of false positives was characterized by a blurry coverage of exon 14, but interestingly they share a common coverage peak in the second intron and we speculate that this event could be the transcription signature of a LINE1 (Long Interspersed Nuclear Element 1)-MET (Mesenchymal Epithelial Transition receptor tyrosine kinase) fusion. Conclusions: Taken together, our results indicate that neural networks can be an effective tool to provide a quick classification of pathological transcription events, and sparsely connected autoencoders could represent the basis for the development of an effective discovery tool

Characterization of a genetic mouse model of lung cancer: a promise to identify Non-Small Cell Lung Cancer therapeutic targets and biomarkers.

Background: Non-small cell lung cancer (NSCLC) accounts for 81% of all cases of lung cancer and they are often fatal because 60% of the patients are diagnosed at an advanced stage. Besides the need for earlier diagnosis, there is a high need for additional effective therapies. In this work, we investigated the feasibility of a lung cancer progression mouse model, mimicking features of human aggressive NSCLC, as biological reservoir for potential therapeutic targets and biomarkers. Results: We performed RNA-seq profiling on total RNA extracted from lungs of a 30 week-old K-rasLA1/p53R172H\u394g and wild type (WT) mice to detect fusion genes and gene/exon-level differential expression associated to the increase of tumor mass. Fusion events were not detected in K-rasLA1/p53R172H\u394g tumors. Differential expression at exon-level detected 33 genes with differential exon usage. Among them nine, i.e. those secreted or expressed on the plasma membrane, were used for a meta-analysis of more than 500 NSCLC RNA-seq transcriptomes. None of the genes showed a significant correlation between exon-level expression and disease prognosis. Differential expression at gene-level allowed the identification of 1513 genes with a significant increase in expression associated to tumor mass increase. 74 genes, i.e. those secreted or expressed on the plasma membrane, were used for a meta-analysis of two transcriptomics datasets of human NSCLC samples, encompassing more than 900 samples. SPP1 was the only molecule whose over-expression resulted statistically related to poor outcome regarding both survival and metastasis formation. Two other molecules showed over-expression associated to poor outcome due to metastasis formation: GM-CSF and ADORA3. GM-CSF is a secreted protein, and we confirmed its expression in the supernatant of a cell line derived by a K-rasLA1/p53R172H\u394g mouse tumor. ADORA3 is instead involved in the induction of p53-mediated apoptosis in lung cancer cell lines. Since in our model p53 is inactivated, ADORA3 does not negatively affect tumor growth but remains expressed on tumor cells. Thus, it could represent an interesting target for the development of antibody-targeted therapy on a subset of NSCLC, which are p53 null and ADORA3 positive. Conclusions: Our study provided a complete transcription overview of the K-rasLA1/p53R172H\u394g mouse NSCLC model. This approach allowed the detection of ADORA3 as a potential target for antibody-based therapy in p53 mutated tumors

Extracellular Vesicles Derived From Plasma of Patients With Neurodegenerative Disease Have Common Transcriptomic Profiling

Objectives: There is a lack of effective biomarkers for neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia. Extracellular vesicle (EV) RNA cargo can have an interesting potential as a non-invasive biomarker for NDs. However, the knowledge about the abundance of EV-mRNAs and their contribution to neurodegeneration is not clear. Methods: Large and small EVs (LEVs and SEVs) were isolated from plasma of patients and healthy volunteers (control, CTR) by differential centrifugation and filtration, and RNA was extracted. Whole transcriptome was carried out using next generation sequencing (NGS). Results: Coding RNA (i.e., mRNA) but not long non-coding RNAs (lncRNAs) in SEVs and LEVs of patients with ALS could be distinguished from healthy CTRs and from other NDs using the principal component analysis (PCA). Some mRNAs were found in commonly deregulated between SEVs of patients with ALS and frontotemporal dementia (FTD), and they were classified in mRNA processing and splicing pathways. In LEVs, instead, one mRNA and one antisense RNA (i.e., MAP3K7CL and AP003068.3) were found to be in common among ALS, FTD, and PD. No deregulated mRNAs were found in EVs of patients with AD. Conclusion: Different RNA regulation occurs in LEVs and SEVs of NDs. mRNAs and lncRNAs are present in plasma-derived EVs of NDs, and there are common and specific transcripts that characterize LEVs and SEVs from the NDs considered in this study

Reversible and Noisy Progression towards a Commitment Point Enables Adaptable and Reliable Cellular Decision-Making

Cells must make reliable decisions under fluctuating extracellular conditions, but also be flexible enough to adapt to such changes. How cells reconcile these seemingly contradictory requirements through the dynamics of cellular decision-making is poorly understood. To study this issue we quantitatively measured gene expression and protein localization in single cells of the model organism Bacillus subtilis during the progression to spore formation. We found that sporulation proceeded through noisy and reversible steps towards an irreversible, all-or-none commitment point. Specifically, we observed cell-autonomous and spontaneous bursts of gene expression and transient protein localization events during sporulation. Based on these measurements we developed mathematical population models to investigate how the degree of reversibility affects cellular decision-making. In particular, we evaluated the effect of reversibility on the 1) reliability in the progression to sporulation, and 2) adaptability under changing extracellular stress conditions. Results show that reversible progression allows cells to remain responsive to long-term environmental fluctuations. In contrast, the irreversible commitment point supports reliable execution of cell fate choice that is robust against short-term reductions in stress. This combination of opposite dynamic behaviors (reversible and irreversible) thus maximizes both adaptable and reliable decision-making over a broad range of changes in environmental conditions. These results suggest that decision-making systems might employ a general hybrid strategy to cope with unpredictably fluctuating environmental conditions

PIK3R1W624R Is an Actionable Mutation in High Grade Serous Ovarian Carcinoma.

Identifying cancer drivers and actionable mutations is critical for precision oncology. In epithelial ovarian cancer (EOC) the majority of mutations lack biological or clinical validation. We fully characterized 43 lines of Patient-Derived Xenografts (PDXs) and performed copy number analysis and whole exome sequencing of 12 lines derived from naïve, high grade EOCs. Pyrosequencing allowed quantifying mutations in the source tumours. Drug response was assayed on PDX Derived Tumour Cells (PDTCs) and in vivo on PDXs. We identified a PIK3R1W624R variant in PDXs from a high grade serous EOC. Allele frequencies of PIK3R1W624R in all the passaged PDXs and in samples of the source tumour suggested that it was truncal and thus possibly a driver mutation. After inconclusive results in silico analyses, PDTCs and PDXs allowed the showing actionability of PIK3R1W624R and addiction of PIK3R1W624R carrying cells to inhibitors of the PI3K/AKT/mTOR pathway. It is noteworthy that PIK3R1 encodes the p85α regulatory subunit of PI3K, that is very rarely mutated in EOC. The PIK3R1W624R mutation is located in the cSH2 domain of the p85α that has never been involved in oncogenesis. These data show that patient-derived models are irreplaceable in their role of unveiling unpredicted driver and actionable variants in advanced ovarian cancer

Optimizing a Massive Parallel Sequencing Workflow for Quantitative miRNA Expression Analysis

BACKGROUND: Massive Parallel Sequencing methods (MPS) can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated. PRIMARY FINDINGS: A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS data derived from healthy donor peripheral blood mononuclear cells. Using this data set we observed that short reads counts estimation is strongly under estimated in case of duplicates miRNAs, if whole genome is used as reference. Furthermore, the sensitivity of miRNAs detection is strongly dependent by the primary tool used in the analysis. Within the six aligners tested, specifically devoted to miRNA detection, SHRiMP and MicroRazerS show the highest sensitivity. Differential expression estimation is quite efficient. Within the five tools investigated, two of them (DESseq, baySeq) show a very good specificity and sensitivity in the detection of differential expression. CONCLUSIONS: The results provided by our analysis allow the definition of a clear and simple analytical optimized workflow for miRNAs digital quantitative analysis

The yield of essential oils in Melaleuca alternifolia (Myrtaceae) is regulated through transcript abundance of genes in the MEP pathway

Medicinal tea tree (Melaleuca alternifolia) leaves contain large amounts of an essential oil, dominated by monoterpenes. Several enzymes of the chloroplastic methylerythritol phosphate (MEP) pathway are hypothesised to act as bottlenecks to the production of monoterpenes. We investigated, whether transcript abundance of genes encoding for enzymes of the MEP pathway were correlated with foliar terpenes in M. alternifolia using a population of 48 individuals that ranged in their oil concentration from 39 -122 mg x g DM(-1). Our study shows that most genes in the MEP pathway are co-regulated and that the expression of multiple genes within the MEP pathway is correlated with oil yield. Using multiple regression analysis, variation in expression of MEP pathway genes explained 87% of variation in foliar monoterpene concentrations. The data also suggest that sesquiterpenes in M. alternifolia are synthesised, at least in part, from isopentenyl pyrophosphate originating from the plastid via the MEP pathway

MicroRNA-135b Regulates Leucine Zipper Tumor Suppressor 1 in Cutaneous Squamous Cell Carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin malignancy and it presents a therapeutic challenge in organ transplant recipient patients. Despite the need, there are only a few targeted drug treatment options. Recent studies have revealed a pivotal role played by microRNAs (miRNAs) in multiple cancers, but only a few studies tested their function in cSCC. Here, we analyzed differential expression of 88 cancer related miRNAs in 43 study participants with cSCC; 32 immunocompetent, 11 OTR patients, and 15 non-lesional skin samples by microarray analysis. Of the examined miRNAs, miR-135b was the most upregulated (13.3-fold, 21.5-fold; p=0.0001) in both patient groups. Similarly, the miR-135b expression was also upregulated in three cSCC cell lines when evaluated by quantitative real-time PCR. In functional studies, inhibition of miR-135b by specific anti-miR oligonucleotides resulted in upregulation of its target gene LZTS1 mRNA and protein levels and led to decreased cell motility and invasion of both primary and metastatic cSCC cell lines. In contrast, miR-135b overexpression by synthetic miR-135b mimic induced further down-regulation of LZTS1 mRNA in vitro and increased cancer cell motility and invasiveness. Immunohistochemical evaluation of 67 cSCC tumor tissues demonstrated that miR-135b expression inversely correlated with LZTS1 staining intensity and the tumor grade. These results indicate that miR-135b functions as an oncogene in cSCC and provide new understanding into its pathological role in cSCC progression and invasiveness