Similar Datasets
Project description:Renal cell carcinoma (RCC) is one of the most common cancers worldwide with a nearly non-symptomatic course until the advanced stages of the disease. RCC can be distinguished into three subtypes: papillary (pRCC), chromophobe (chRCC) and clear cell renal cell carcinoma (ccRCC) representing up to 75% of all RCC cases. Detection and RCC monitoring tools are limited to standard imaging techniques, in combination with non-RCC specific morphological and biochemical read-outs. RCC subtype identification relays mainly on results of pathological examination of tumor slides. Molecular, clinically applicable and ideally non-invasive tools aiding RCC management are still non-existent, although molecular characterization of RCC is relatively advanced. Hence, many research efforts concentrate on the identification of molecular markers that will assist with RCC sub-classification and monitoring. Due to stability and tissue-specificity miRNAs are promising candidates for such biomarkers. Here, we performed a meta-analysis study, utilized seven NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), pRCC-specific (miRNA-127-3p, miRNA-139-5p) and ccRCC-specific miRNAs (miRNA-200c-3p, miRNA-362-5p, miRNA-363-3p and miRNA-204-5p, 21-5p, miRNA-224-5p, miRNA-155-5p, miRNA-210-3p) and validated their expression in an independent sample set. Additionally, we found ccRCC-specific miRNAs to be differentially expressed in ccRCC tumor according to Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in the expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and we propose a miRNA panel aiding RCC subtype distinction.
| S-EPMC7867039 | biostudies-literature
Project description:Renal cell carcinoma (RCC) is one of the most common cancers worldwide with nearly non-symptomatic course till advanced stage of disease. RCC can be distinguished into three subtypes: papillary (pRCC), chromophobe (chRCC) and clear cell renal cell carcinoma (ccRCC) representing up to 75% of all RCC cases. Detection and RCC monitoring tools are limited to standard imaging techniques, in combination with non-RCC specific morphological and biochemical read-outs. RCC subtype identification relays mainly on results of pathological examination of tumor slides. Molecular, clinically applicable and ideally non-invasive tools aiding RCC management are still non-existent, although molecular characterization of RCC is relatively advanced. Hence many research efforts concentrate on identification of molecular markers that will assist with RCC sub-classification and monitoring. Due to stability and tissue-specificity miRNAs are promising candidates for such biomarkers. Here we performed a meta-analysis study, utilized seven available NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on four potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), two pRCC (miRNA-127-3p, miRNA-139-5p) and eight ccRCC specific miRNAs (miRNA-200c-3p, miRNA-362-5p, miRNA-363-3p and miRNA-204-5p, 21-5p, miRNA-224-5p, miRNA-155-5p, miRNA-210-3p) and validated their expression in an independent sample set. Additionally, we found ccRCC-specific miRNAs to be differentially expressed in ccRCC Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and propose a miRNA panel aiding RCC subtype distinction.
2021-02-01 | GSE151423 | GEO
Project description:Renal cell carcinoma (RCC) is one of the most common cancers worldwide with nearly non-symptomatic course till advanced stage of disease. RCC can be distinguished into three subtypes: papillary (pRCC), chromophobe (chRCC) and clear cell renal cell carcinoma (ccRCC) representing up to 75% of all RCC cases. Detection and RCC monitoring tools are limited to standard imaging techniques, in combination with non-RCC specific morphological and biochemical read-outs. RCC subtype identification relays mainly on results of pathological examination of tumor slides. Molecular, clinically applicable and ideally non-invasive tools aiding RCC management are still non-existent, although molecular characterization of RCC is relatively advanced. Hence many research efforts concentrate on identification of molecular markers that will assist with RCC sub-classification and monitoring. Due to stability and tissue-specificity miRNAs are promising candidates for such biomarkers. Here we performed a meta-analysis study, utilized seven available NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on four potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), two pRCC (miRNA-127-3p, miRNA-139-5p) and eight ccRCC specific miRNAs (miRNA-200c-3p, miRNA-362-5p, miRNA-363-3p and miRNA-204-5p, 21-5p, miRNA-224-5p, miRNA-155-5p, miRNA-210-3p) and validated their expression in an independent sample set. Additionally, we found ccRCC-specific miRNAs to be differentially expressed in ccRCC Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and propose a miRNA panel aiding RCC subtype distinction.
2021-02-01 | GSE151419 | GEO
Project description:Identification of RCC subtype-specific microRNAs – meta-analysis of high-throughput RCC tumor microRNA expression data
| PRJNA635800 | ENA
Project description:Identification of RCC subtype-specific microRNAs – meta-analysis of high-throughput RCC tumor microRNA expression data [miRNA-Seq]
| PRJNA635803 | ENA
Project description:Identification of RCC subtype-specific microRNAs – meta-analysis of high-throughput RCC tumor microRNA expression data [RNA-Seq]
| PRJNA635798 | ENA
Project description:Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.
| S-EPMC7858121 | biostudies-literature
Project description:BackgroundmicroRNAs (miRNAs) are small and non-coding RNAs which play critical roles in physiological and pathological processes. A number of methods have been established to detect and quantify miRNA expression. However, method for high-throughput miRNA function detection is still lacking.Principal findingsWe describe an adeno-associated virus (AAV) vector-based microRNA (miRNA) sensor (Asensor) array for high-throughput functional miRNA profiling. Each Asensor contains a Gaussia luciferase (Gluc) and a firefly luciferase (Fluc) expression cassette to sense functional miRNA and to serve as an internal control respectively. Using this array, we acquired functional profiles of 115 miRNAs for 12 cell lines and found "functional miRNA signatures" for several specific cell lines. The activities of specific miRNAs including the let-7 family, miR-17-92 cluster, miR-221, and miR-222 in HEK 293 cells were compared with their expression levels determined by quantitative reverse transcriptase polymerase chain reaction (QRT-PCR). We also demonstrate two other practical applications of the array, including a comparison of the miRNA activity between HEK293 and HEK293T cells and the ability to monitor miRNA activity changes in K562 cells treated with 12-O-tetradecanoylphorbol-13-acetate (TPA).Conclusions/significanceOur approach has potential applications in the identification of cell types, the characterization of biological and pathological processes, and the evaluation of responses to interventions.
| S-EPMC3252342 | biostudies-literature
Project description:BACKGROUND: MicroRNAs are short (approximately 21 base) single stranded RNAs that, in plants, are generally coded by specific genes and cleaved specifically from hairpin precursors. MicroRNAs are critical for the regulation of multiple developmental, stress related and other physiological processes in plants. The recent annotation of the genome of the grapevine (Vitis vinifera L.) allowed the identification of many putative conserved microRNA precursors, grouped into multiple gene families. RESULTS: Here we use oligonucleotide arrays to provide the first indication that many of these microRNAs show differential expression patterns between tissues and during the maturation of fruit in the grapevine. Furthermore we demonstrate that whole transcriptome sequencing and deep-sequencing of small RNA fractions can be used both to identify which microRNA precursors are expressed in different tissues and to estimate genomic coordinates and patterns of splicing and alternative splicing for many primary miRNA transcripts. CONCLUSION: Our results show that many microRNAs are differentially expressed in different tissues and during fruit maturation in the grapevine. Furthermore, the demonstration that whole transcriptome sequencing can be used to identify candidate splicing events and approximate primary microRNA transcript coordinates represents a significant step towards the large-scale elucidation of mechanisms regulating the expression of microRNAs at the transcriptional and post-transcriptional levels.
| S-EPMC2822795 | biostudies-literature
Project description:The humoral immune response plays a critical role in controlling infection, and the rapid adaptation to a broad range of pathogens depends on a highly diverse antibody repertoire. The advent of high-throughput sequencing technologies in the past decade has enabled insights into this immense diversity. However, not only the variable, but also the constant region of antibodies determines their in vivo activity. Antibody isotypes differ in effector functions and are thought to play a defining role in elicitation of immune responses, both in natural infection and in vaccination. We have developed an Illumina MiSeq high-throughput sequencing protocol that allows determination of the human IgG subtype alongside sequencing full-length antibody variable heavy chain regions. We thereby took advantage of the Illumina procedure containing two additional short reads as identifiers. By performing paired-end sequencing of the variable regions and customizing one of the identifier sequences to distinguish IgG subtypes, IgG transcripts with linked information of variable regions and IgG subtype can be retrieved. We applied our new method to the analysis of the IgG variable region repertoire from PBMC of an HIV-1 infected individual confirmed to have serum antibody reactivity to the Membrane Proximal External Region (MPER) of gp41. We found that IgG3 subtype frequencies in the memory B cell compartment increased after halted treatment and coincided with increased plasma antibody reactivity against the MPER domain. The sequencing strategy we developed is not restricted to analysis of IgG. It can be adopted for any Ig subtyping and beyond that for any research question where phasing of distant regions on the same amplicon is needed.
| S-EPMC4218849 | biostudies-literature