Phosphoproteomics of retinoblastoma:A pilot study identifies aberrant kinases

Retinoblastoma is a malignant tumour of the retina which most often occurs in children. Earlier studies on retinoblastoma have concentrated on the identification of key players in the disease and have not provided information on activated/inhibited signalling pathways. The dysregulation of protein phosphorylation in cancer provides clues about the affected signalling cascades in cancer. Phosphoproteomics is an ideal tool for the study of phosphorylation changes in proteins. Hence, global phosphoproteomics of retinoblastoma (RB) was carried out to identify signalling events associated with this cancer. Over 350 proteins showed differential phosphorylation in RB compared to control retina. Our study identified stress response proteins to be hyperphosphorylated in RB which included H2A histone family member X (H2AFX) and sirtuin 1. In particular, Ser140 of H2AFX also known as gamma-H2AX was found to be hyperphosphorylated in retinoblastoma, which indicated the activation of DNA damage response pathways. We also observed the activation of anti-apoptosis in retinoblastoma compared to control. These observations showed the activation of survival pathways in retinoblastoma. The identification of hyperphosphorylated protein kinases including Bromodomain containing 4 (BRD4), Lysine deficient protein kinase 1 (WNK1), and Cyclin-dependent kinase 1 (CDK1) in RB opens new avenues for the treatment of RB. These kinases can be considered as probable therapeutic targets for RB, as small-molecule inhibitors for some of these kinases are already in clinical trials for the treatment other cancers

A Compendium of Potential Biomarkers of Pancreatic Cancer

Akhilesh Pandey and colleagues describe a compendium of potential biomarkers that can be systematically validated by the pancreatic cancer community

Unraveling the RNA world of retinoblastoma

Retinoblastoma is the most common primary intraocular tumor in children. It is the first ever cancer to have a genetic basis where inactivation of RB gene in both the alleles would cause the cancer1. Whole genome sequencing, gene expression studies, copy number variation analysis, miRNA expression studies, methylation studies have been carried out to identify the additional mutational events involved in causing retinoblastoma2. Here, transcriptome sequencing of retinoblastoma and control retina tissues was carried out to identify unique features in retinoblastoma transcriptome. Transcriptome sequencing of 7 retinoblastoma tumors and 3 control retina tissues was carried out using Illumina HiSeq 2500 platform. The paired end reads were aligned to the reference human genome Feb. 2009 release downloaded from the UCSC database (GRCh37/hg19). The reads were analyzed to identify unique genes expressed in retinoblastoma, fusion transcripts, lncRNA’s. To identify fusion transcripts EricScript software pipelines were employed that used genome build hg38 and ensemble version 84. This analysis identified over 100 candidate fusion transcript reads. These reads were further inspected by BLAST analysis to minimize the cases of false positives. We considered only those reads which mapped uniquely to gene 1 and gene 2 as candidate fusion transcripts. BLAST analysis of the identified fusion transcript reads revealed that most of the fusion transcript reads aligned 100% either to pseudogenes or other genes in the family and were regarded as false positives. In total, BLAST analysis identified 22 candidate fusion transcripts – 4 unique to retinoblastoma and 18 common between retinoblastoma and retina. Interestingly, all the identified fusion transcripts were found to occur between two adjacent genes on same genomic strand indicating the possibility of read through gene fusions or transcription-induced chimeras (TIC). Four TIC’s (LSG1-TMEM44, C19orf24-CIRBP, DSCAML1-FXYD2 and SLC26A6-UQCRC) found unique to retinoblastoma were verified by PCR in a larger cohort of retinoblastoma and retina tissues. LSG1-TMEM44 fusion transcript was previously shown to be present in a glioblastoma cell line – A172. C19orf24-CIRBP fusion transcript was found in burkit lymphoma. Other two fusion transcripts were found to be novel and not reported elsewhere. This work underscored that the retinoblastoma genome is stable where gross deletions and translocations other than RB1 gene are not common

Identification of targets of miR-200b by a SILAC-based quantitative proteomic approach

miRNAs regulate gene expression by binding to cognate mRNAs causing mRNA degradation or translational repression. Mass spectrometry-based proteomic analysis is being widely used to identify miRNA targets. The miR-200b miRNA cluster is often overexpressed in multiple cancer types, but the identity of the targets remains elusive. Using SILAC-based analysis, we examined the effects of overexpression of a miR-200b mimic or a control miRNA in fibrosarcoma cells. We identified around 300 potential targets of miR-200b based on a change in the expression of protein levels. We validated a subset of potential targets at the transcript level using quantitative PCR

Proteogenomic Analysis of <i>Candida glabrata</i> using High Resolution Mass Spectrometry

<i>Candida glabrata</i> is a common opportunistic human pathogen leading to significant mortality in immunosuppressed and immunodeficient individuals. We carried out proteomic analysis of <i>C. glabrata</i> using high resolution Fourier transform mass spectrometry with MS resolution of 60000 and MS/MS resolution of 7500. On the basis of 32453 unique peptides identified from 118815 peptide–spectrum matches, we validated 4421 of the 5283 predicted protein-coding genes (83%) in the <i>C. glabrata</i> genome. Further, searching the tandem mass spectra against a six frame translated genome database of <i>C. glabrata</i> resulted in identification of 11 novel protein coding genes and correction of gene boundaries for 14 predicted gene models. A subset of novel protein-coding genes and corrected gene models were validated at the transcript level by RT-PCR and sequencing. Our study illustrates how proteogenomic analysis enabled by high resolution mass spectrometry can enrich genome annotation and should be an integral part of ongoing genome sequencing and annotation efforts

Proteogenomic Analysis of <i>Candida glabrata</i> using High Resolution Mass Spectrometry

<i>Candida glabrata</i> is a common opportunistic human pathogen leading to significant mortality in immunosuppressed and immunodeficient individuals. We carried out proteomic analysis of <i>C. glabrata</i> using high resolution Fourier transform mass spectrometry with MS resolution of 60000 and MS/MS resolution of 7500. On the basis of 32453 unique peptides identified from 118815 peptide–spectrum matches, we validated 4421 of the 5283 predicted protein-coding genes (83%) in the <i>C. glabrata</i> genome. Further, searching the tandem mass spectra against a six frame translated genome database of <i>C. glabrata</i> resulted in identification of 11 novel protein coding genes and correction of gene boundaries for 14 predicted gene models. A subset of novel protein-coding genes and corrected gene models were validated at the transcript level by RT-PCR and sequencing. Our study illustrates how proteogenomic analysis enabled by high resolution mass spectrometry can enrich genome annotation and should be an integral part of ongoing genome sequencing and annotation efforts

Proteogenomic Analysis of <i>Candida glabrata</i> using High Resolution Mass Spectrometry

<i>Candida glabrata</i> is a common opportunistic human pathogen leading to significant mortality in immunosuppressed and immunodeficient individuals. We carried out proteomic analysis of <i>C. glabrata</i> using high resolution Fourier transform mass spectrometry with MS resolution of 60000 and MS/MS resolution of 7500. On the basis of 32453 unique peptides identified from 118815 peptide–spectrum matches, we validated 4421 of the 5283 predicted protein-coding genes (83%) in the <i>C. glabrata</i> genome. Further, searching the tandem mass spectra against a six frame translated genome database of <i>C. glabrata</i> resulted in identification of 11 novel protein coding genes and correction of gene boundaries for 14 predicted gene models. A subset of novel protein-coding genes and corrected gene models were validated at the transcript level by RT-PCR and sequencing. Our study illustrates how proteogenomic analysis enabled by high resolution mass spectrometry can enrich genome annotation and should be an integral part of ongoing genome sequencing and annotation efforts

Proteogenomic Analysis of <i>Candida glabrata</i> using High Resolution Mass Spectrometry

<i>Candida glabrata</i> is a common opportunistic human pathogen leading to significant mortality in immunosuppressed and immunodeficient individuals. We carried out proteomic analysis of <i>C. glabrata</i> using high resolution Fourier transform mass spectrometry with MS resolution of 60000 and MS/MS resolution of 7500. On the basis of 32453 unique peptides identified from 118815 peptide–spectrum matches, we validated 4421 of the 5283 predicted protein-coding genes (83%) in the <i>C. glabrata</i> genome. Further, searching the tandem mass spectra against a six frame translated genome database of <i>C. glabrata</i> resulted in identification of 11 novel protein coding genes and correction of gene boundaries for 14 predicted gene models. A subset of novel protein-coding genes and corrected gene models were validated at the transcript level by RT-PCR and sequencing. Our study illustrates how proteogenomic analysis enabled by high resolution mass spectrometry can enrich genome annotation and should be an integral part of ongoing genome sequencing and annotation efforts