8 datasets found
  1. f

    Data from: A novel lncRNA derived from an ultraconserved region: lnc-uc.147,...

    • tandf.figshare.com
    docx
    Updated Mar 21, 2024
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    Erika Pereira Zambalde; Recep Bayraktar; Tayana Schultz Jucoski; Cristina Ivan; Ana Carolina Rodrigues; Carolina Mathias; Erik knutsen; Rubens Silveira de Lima; Daniela Fiori Gradia; Enilze Maria de Souza Fonseca Ribeiro; Samir Hannash; George Adrian Calin; Jaqueline Carvalhode Oliveira (2024). A novel lncRNA derived from an ultraconserved region: lnc-uc.147, a potential biomarker in luminal A breast cancer [Dataset]. http://doi.org/10.6084/m9.figshare.15164250.v1
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    docxAvailable download formats
    Dataset updated
    Mar 21, 2024
    Dataset provided by
    Taylor & Francis
    Authors
    Erika Pereira Zambalde; Recep Bayraktar; Tayana Schultz Jucoski; Cristina Ivan; Ana Carolina Rodrigues; Carolina Mathias; Erik knutsen; Rubens Silveira de Lima; Daniela Fiori Gradia; Enilze Maria de Souza Fonseca Ribeiro; Samir Hannash; George Adrian Calin; Jaqueline Carvalhode Oliveira
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The human genome contains 481 ultraconserved regions (UCRs), which are genomic stretches of over 200 base pairs conserved among human, rat, and mouse. The majority of these regions are transcriptionally active (T-UCRs), and several have been found to be differentially expressed in tumours. Some T-UCRs have been functionally characterized, but of those few have been associated to breast cancer (BC). Using TCGA data, we found 302 T-UCRs related to clinical features in BC: 43% were associated with molecular subtypes, 36% with oestrogen-receptor positivity, 17% with HER2 expression, 12% with stage, and 10% with overall survival. The expression levels of 12 T-UCRs were further analysed in a cohort of 82 Brazilian BC patients using RT-qPCR. We found that uc.147 is high expressed in luminal A and B patients. For luminal A, a subtype usually associated with better prognosis, high uc.147 expression was associated with a poor prognosis and suggested as an independent prognostic factor. The lncRNA from uc.147 (lnc-uc.147) is located in the nucleus. Northern blotting results show that uc.147 is a 2,8 kb monoexonic trancript, and its sequence was confirmed by RACE. The silencing of uc.147 increases apoptosis, arrests cell cycle, and reduces cell viability and colony formation in BC cell lines. Additionally, we identifed 19 proteins that interact with lnc-uc.147 through mass spectrometry and demonstrated a high correlation of lnc-uc.147 with the neighbour gene expression and miR-18 and miR-190b. This is the first study to analyse the expression of all T-UCRs in BC and to functionally assess the lnc-uc.147.

  2. f

    Diagnostic and prognostic value of long noncoding RNAs as biomarkers in...

    • plos.figshare.com
    tiff
    Updated Jun 2, 2023
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    Johanna Droop; Tibor Szarvas; Wolfgang A. Schulz; Christian Niedworok; Günter Niegisch; Kathrin Scheckenbach; Michèle J. Hoffmann (2023). Diagnostic and prognostic value of long noncoding RNAs as biomarkers in urothelial carcinoma [Dataset]. http://doi.org/10.1371/journal.pone.0176287
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    tiffAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Johanna Droop; Tibor Szarvas; Wolfgang A. Schulz; Christian Niedworok; Günter Niegisch; Kathrin Scheckenbach; Michèle J. Hoffmann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Many long noncoding RNAs (lncRNAs) are deregulated in cancer and contribute to oncogenesis. In urothelial carcinoma (UC), several lncRNAs have been reported to be overexpressed and proposed as biomarkers. As most reports have not been confirmed independently in large tissue sets, we aimed to validate the diagnostic and prognostic value of lncRNA upregulation in independent cohorts of UC patients. Thus, expression of seven lncRNA candidates (GAS5, H19, linc-UBC1, MALAT1, ncRAN, TUG1, UCA1) was measured by RT-qPCR in cell lines and tissues and correlated to clinicopathological parameters including follow-up data (set 1: N n = 10; T n = 106). Additionally, publicly available TCGA data was investigated for differential expression in UC tissues (set 2: N n = 19; T n = 252,) and correlation to overall survival (OS). All proposed candidates tended to be upregulated in tumour tissues, with the exception of MALAT1, which was rather diminished in cancer tissues of both data sets. However, strong overexpression was generally limited to individual tumour tissues and statistically significant overexpression was only observed for UCA1, TUG1, ncRAN and linc-UBC1 in tissue set 2, but for no candidate in set 1. Altered expression of individual lncRNAs was associated with overall survival, but not consistently between both patient cohorts. Interestingly, lower expression of TUG1 in a subset of UC patients with muscle-invasive tumours was significantly correlated with worse OS in both cohorts. Further analysis revealed that tumours with low TUG1 expression are characterized by a basal-squamous-like subtype signature accounting for the association with poor outcome. In conclusion, our study demonstrates that overexpression of the candidate lncRNAs is found in many UC cases, but does not occur consistently and strongly enough to provide reliable diagnostic or prognostic value as an individual biomarker. Subtype-dependent expression patterns of lncRNAs like TUG1 could become useful to stratify patients by molecular subtype, thus aiding personalized treatments.

  3. Data from: Reproducibility of Differential Proteomic Technologies in CPTAC...

    • acs.figshare.com
    xlsx
    Updated May 31, 2023
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    David L. Tabb; Xia Wang; Steven A. Carr; Karl R. Clauser; Philipp Mertins; Matthew C. Chambers; Jerry D. Holman; Jing Wang; Bing Zhang; Lisa J. Zimmerman; Xian Chen; Harsha P. Gunawardena; Sherri R. Davies; Matthew J. C. Ellis; Shunqiang Li; R. Reid Townsend; Emily S. Boja; Karen A. Ketchum; Christopher R. Kinsinger; Mehdi Mesri; Henry Rodriguez; Tao Liu; Sangtae Kim; Jason E. McDermott; Samuel H. Payne; Vladislav A. Petyuk; Karin D. Rodland; Richard D. Smith; Feng Yang; Daniel W. Chan; Bai Zhang; Hui Zhang; Zhen Zhang; Jian-Ying Zhou; Daniel C. Liebler (2023). Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts [Dataset]. http://doi.org/10.1021/acs.jproteome.5b00859.s002
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    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    ACS Publications
    Authors
    David L. Tabb; Xia Wang; Steven A. Carr; Karl R. Clauser; Philipp Mertins; Matthew C. Chambers; Jerry D. Holman; Jing Wang; Bing Zhang; Lisa J. Zimmerman; Xian Chen; Harsha P. Gunawardena; Sherri R. Davies; Matthew J. C. Ellis; Shunqiang Li; R. Reid Townsend; Emily S. Boja; Karen A. Ketchum; Christopher R. Kinsinger; Mehdi Mesri; Henry Rodriguez; Tao Liu; Sangtae Kim; Jason E. McDermott; Samuel H. Payne; Vladislav A. Petyuk; Karin D. Rodland; Richard D. Smith; Feng Yang; Daniel W. Chan; Bai Zhang; Hui Zhang; Zhen Zhang; Jian-Ying Zhou; Daniel C. Liebler
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC–MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

  4. Data from: Discovery of TBC1D7 as a potential driver for melanoma cell...

    • data.niaid.nih.gov
    • ebi.ac.uk
    xml
    Updated Aug 15, 2022
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    Tianyu Qi; Yinsheng Wang (2022). Discovery of TBC1D7 as a potential driver for melanoma cell invasion. [Dataset]. https://data.niaid.nih.gov/resources?id=pxd014368
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    xmlAvailable download formats
    Dataset updated
    Aug 15, 2022
    Dataset provided by
    Professor of Chemistry University of California Riverside Riverside, CA 92521-0403
    UC RIVERSIDE
    Authors
    Tianyu Qi; Yinsheng Wang
    Variables measured
    Proteomics
    Description

    Melanoma is a common type of cancer, and metastasis remains the leading cause for mortality in melanoma patients. In this study, we utilized an unbiased mass spectrometry-based quantitative proteomic method to assess, at the global proteome scale, differential protein expression in a matched pair of primary/metastatic melanoma cell lines derived from the same patient, i.e. WM-115/WM-266-4. We found that TBC1D7 is overexpressed in metastatic (WM-266-4) relative to primary (WM-115) melanoma cells. We also observed that elevated expression of TBC1D7 promotes melanoma metastasis in vitro. Bioinformatic analyses of The Cancer Genome Atlas (TCGA) data suggested that higher mRNA expression levels of TBC1D7 predict poorer survival in melanoma patients. Furthermore, we showed that TBC1D7 promotes invasion of cultured melanoma cells in vitro, at least in part, through modulating the expression levels and activities of matrix metalloproteinases 2 and 9 (MMP2 and MMP9). Together, the results from the present study support TBC1D7 as a potential driver for melanoma metastasis.

  5. f

    Table1_Glycogen Metabolism Predicts the Efficacy of Immunotherapy for...

    • figshare.com
    xlsx
    Updated Jun 10, 2023
    + more versions
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    Yueming Zhang; Xuechun Li; Rui Zhou; Anqi Lin; Manming Cao; Qingwen Lyu; Peng Luo; Jian Zhang (2023). Table1_Glycogen Metabolism Predicts the Efficacy of Immunotherapy for Urothelial Carcinoma.xlsx [Dataset]. http://doi.org/10.3389/fphar.2021.723066.s002
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    xlsxAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    Frontiers
    Authors
    Yueming Zhang; Xuechun Li; Rui Zhou; Anqi Lin; Manming Cao; Qingwen Lyu; Peng Luo; Jian Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Urothelial cancer (UC) is one of the common refractory tumors and chemotherapy is the primary treatment for it. The advent of immune checkpoint inhibitors (ICI) has facilitated the development of treatment strategies for UC patients. To screen out UC patients sensitive to ICI, researchers have proposed that PD-L1, tumor mutation burden and TCGA molecular subtypes can be used as predictors of ICI efficacy. However, the performance of these predictors needs further validation. We need to identify novel biomarkers to screen out UC patients sensitive to ICI. In our study, we collected the data of two clinical cohorts: the ICI cohort and the TCGA cohort. The result of the multivariate Cox regression analysis showed that glycogen metabolism score (GMS) (HR = 1.26, p = 0.017) was the negative predictor of prognosis for UC patients receiving ICI treatment. Low-GMS patients had a higher proportion of patients achieving complete response or partial response to ICI. After the comparison of gene mutation status between high-GMS and low-GMS patients, we identified six genes with significant differences in mutation frequencies, which may provide new directions for potential drug targets. Moreover, we analyzed the immune infiltration status and immune-related genes expression between high-GMS and low-GMS patients. A reduced proportion of tumor-associated fibroblasts and elevated proportion of CD8+ T cells can be observed in low-GMS patients while several immunosuppressive molecules were elevated in the high-GMS patients. Using the sequencing data of the GSE164042 dataset, we also found that myeloid-derived suppressor cell and neutrophil related signature scores were lower in α-glucosidase knockout bladder carcinoma cells when compared to the control group. In addition, angiogenesis, classic carcinogenic pathways, immunosuppressive cells related pathways and immunosuppressive cytokine secretion were mainly enriched in high-GMS patients and cell samples from the control group. Finally, we suspected that the combination treatment of ICI and histone deacetylase inhibitors may achieve better clinical responses in UC patients based on the analysis of drug sensitivity data. In conclusion, our study revealed the predictive value of GMS for ICI efficacy of UC patients, providing a novel perspective for the exploration of new drug targets and potential treatment strategies.

  6. f

    Supplementary Material for: ANXA10 Expression Is Inversely Associated with...

    • karger.figshare.com
    tiff
    Updated May 31, 2023
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    Kobayashi G.; Hayashi T.; Sentani K.; Ikeda K.; Babasaki T.; Shigematsu Y.; Sekino Y.; Uraoka N.; Teishima J.; Matsubara A.; Hinata N.; Oue N. (2023). Supplementary Material for: ANXA10 Expression Is Inversely Associated with Tumor Stage, Grade, and TP53 Expression in Upper and Lower Urothelial Carcinoma [Dataset]. http://doi.org/10.6084/m9.figshare.20208755.v1
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    tiffAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Karger Publishers
    Authors
    Kobayashi G.; Hayashi T.; Sentani K.; Ikeda K.; Babasaki T.; Shigematsu Y.; Sekino Y.; Uraoka N.; Teishima J.; Matsubara A.; Hinata N.; Oue N.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Introduction: Urothelial carcinoma (UC) is a common type of malignant disease, but little is known about the diagnostic and prognostic markers of upper urinary tract urothelial cancer (UTUC) because of its rarity. To clarify the significance of ANXA10 in UTUC, we studied ANXA10 expression with immunohistochemistry (IHC). Methods: The expression of ANXA10 was analyzed in the upper and lower urinary tract of UC by IHC in combination with The Cancer Genome Atlas (TCGA) data analysis. The association between ANXA10 expression and representative cancer-related molecules was also evaluated. Results: ANXA10 expression was weak in normal upper tract urothelium but was positive in 39/117 (33%) UTUCs. ANXA10 was more frequently positive in tumors with pure UC (36%, p < 0.05), papillary morphology (50%, p < 0.01), low grade (G1/2: 57%, p < 0.01), and pTa/is/1 stage (55%, p < 0.01) than in those with histological variants (0%), nodular morphology (9%), G3 (16%), and pT2/3/4 (13%), respectively. ANXA10-positive patients showed better cancer-specific survival and progression-free survival than ANXA10-negative patients (p < 0.05). IHC showed that ANXA10 positivity was detected more in cases with the low expression of TP53 (p < 0.01) and Ki-67 labeling index

  7. f

    Univariate analyses of the impact of lncRNA expression on patient survival.

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Johanna Droop; Tibor Szarvas; Wolfgang A. Schulz; Christian Niedworok; Günter Niegisch; Kathrin Scheckenbach; Michèle J. Hoffmann (2023). Univariate analyses of the impact of lncRNA expression on patient survival. [Dataset]. http://doi.org/10.1371/journal.pone.0176287.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Johanna Droop; Tibor Szarvas; Wolfgang A. Schulz; Christian Niedworok; Günter Niegisch; Kathrin Scheckenbach; Michèle J. Hoffmann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Univariate analyses of the impact of lncRNA expression on patient survival.

  8. Clinical and histopathological parameters of tissue set 1.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Johanna Droop; Tibor Szarvas; Wolfgang A. Schulz; Christian Niedworok; Günter Niegisch; Kathrin Scheckenbach; Michèle J. Hoffmann (2023). Clinical and histopathological parameters of tissue set 1. [Dataset]. http://doi.org/10.1371/journal.pone.0176287.t001
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Johanna Droop; Tibor Szarvas; Wolfgang A. Schulz; Christian Niedworok; Günter Niegisch; Kathrin Scheckenbach; Michèle J. Hoffmann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Clinical and histopathological parameters of tissue set 1.

  9. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Erika Pereira Zambalde; Recep Bayraktar; Tayana Schultz Jucoski; Cristina Ivan; Ana Carolina Rodrigues; Carolina Mathias; Erik knutsen; Rubens Silveira de Lima; Daniela Fiori Gradia; Enilze Maria de Souza Fonseca Ribeiro; Samir Hannash; George Adrian Calin; Jaqueline Carvalhode Oliveira (2024). A novel lncRNA derived from an ultraconserved region: lnc-uc.147, a potential biomarker in luminal A breast cancer [Dataset]. http://doi.org/10.6084/m9.figshare.15164250.v1

Data from: A novel lncRNA derived from an ultraconserved region: lnc-uc.147, a potential biomarker in luminal A breast cancer

Related Article
Explore at:
docxAvailable download formats
Dataset updated
Mar 21, 2024
Dataset provided by
Taylor & Francis
Authors
Erika Pereira Zambalde; Recep Bayraktar; Tayana Schultz Jucoski; Cristina Ivan; Ana Carolina Rodrigues; Carolina Mathias; Erik knutsen; Rubens Silveira de Lima; Daniela Fiori Gradia; Enilze Maria de Souza Fonseca Ribeiro; Samir Hannash; George Adrian Calin; Jaqueline Carvalhode Oliveira
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The human genome contains 481 ultraconserved regions (UCRs), which are genomic stretches of over 200 base pairs conserved among human, rat, and mouse. The majority of these regions are transcriptionally active (T-UCRs), and several have been found to be differentially expressed in tumours. Some T-UCRs have been functionally characterized, but of those few have been associated to breast cancer (BC). Using TCGA data, we found 302 T-UCRs related to clinical features in BC: 43% were associated with molecular subtypes, 36% with oestrogen-receptor positivity, 17% with HER2 expression, 12% with stage, and 10% with overall survival. The expression levels of 12 T-UCRs were further analysed in a cohort of 82 Brazilian BC patients using RT-qPCR. We found that uc.147 is high expressed in luminal A and B patients. For luminal A, a subtype usually associated with better prognosis, high uc.147 expression was associated with a poor prognosis and suggested as an independent prognostic factor. The lncRNA from uc.147 (lnc-uc.147) is located in the nucleus. Northern blotting results show that uc.147 is a 2,8 kb monoexonic trancript, and its sequence was confirmed by RACE. The silencing of uc.147 increases apoptosis, arrests cell cycle, and reduces cell viability and colony formation in BC cell lines. Additionally, we identifed 19 proteins that interact with lnc-uc.147 through mass spectrometry and demonstrated a high correlation of lnc-uc.147 with the neighbour gene expression and miR-18 and miR-190b. This is the first study to analyse the expression of all T-UCRs in BC and to functionally assess the lnc-uc.147.

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