67 research outputs found

    Scoring mechanisms of p16INK4a immunohistochemistry based on either independent nucleic stain or mixed cytoplasmic with nucleic expression can significantly signal to distinguish between endocervical and endometrial adenocarcinomas in a tissue microarray study

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    <p>Abstract</p> <p>Background</p> <p>Endocervical adenocarcinomas (ECAs) and endometrial adenocarcinomas (EMAs) are malignancies that affect uterus; however, their biological behaviors are quite different. This distinction has clinical significance, because the appropriate therapy may depend on the site of tumor origin. The purpose of this study is to evaluate 3 different scoring mechanisms of p16<sup>INK4a </sup>immunohistochemical (IHC) staining in distinguishing between primary ECAs and EMAs.</p> <p>Methods</p> <p>A tissue microarray (TMA) was constructed using formalin-fixed, paraffin-embedded tissue from hysterectomy specimens, including 14 ECAs and 24 EMAs. Tissue array sections were immunostained with a commercially available antibody of p16<sup>INK4a</sup>. Avidin-biotin complex (ABC) method was used for antigens visualization. The staining intensity and area extent of the IHC reactions was evaluated using the semi-quantitative scoring system. The 3 scoring methods were defined on the bases of the following: (1) independent cytoplasmic staining alone (Method C), (2) independent nucleic staining alone (Method N), and (3) mean of the sum of cytoplasmic score plus nucleic score (Method Mean of C plus N).</p> <p>Results</p> <p>Of the 3 scoring mechanisms for p16<sup>INK4a </sup>expression, Method N and Method Mean of C plus N showed significant (<it>p-values </it>< 0.05), but Method C showed non-significant (p = 0.245) frequency differences between ECAs and EMAs. In addition, Method Mean of C plus N had the highest overall accuracy rate (81.6%) for diagnostic distinction among these 3 scoring methods.</p> <p>Conclusion</p> <p>According to the data characteristics and test effectiveness in this study, Method N and Method Mean of C plus N can significantly signal to distinguish between ECAs and EMAs; while Method C cannot do. Method Mean of C plus N is the most promising and favorable means among the three scoring mechanisms.</p

    Progesterone receptor does not improve the performance and test effectiveness of the conventional 3-marker panel, consisting of estrogen receptor, vimentin and carcinoembryonic antigen in distinguishing between primary endocervical and endometrial adenocarcinomas in a tissue microarray extension study

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    <p>Abstract</p> <p>Objective</p> <p>Endocervical adenocarcinomas (ECA) and endometrial adenocarcinomas (EMA) are uterine malignancies that have differing biological behaviors. The choice of an appropriate therapeutic plan rests on the tumor's site of origin. In this study, we propose to evaluate whether PR adds value to the performance and test effectiveness of the conventional 3-marker (ER/Vim/CEA) panel in distinguishing between primary ECA and EMA.</p> <p>Methods</p> <p>A tissue microarray was constructed using paraffin-embedded, formalin-fixed tissues from 38 hysterectomy specimens, including 14 ECA and 24 EMA. Tissue microarray (TMA) sections were immunostained with 4 antibodies, using the avidin-biotin complex (ABC) method for antigen visualization. The staining intensity and extent of the immunohistochemical (IHC) reactions were appraised using a semi-quantitative scoring system.</p> <p>Results</p> <p>The three markers (ER, Vim and CEA) and their respective panel expressions showed statistically significant (p < 0.05) frequency differences between ECA and EMA tumors. Although the additional ancillary PR-marker also revealed a significant frequency difference (p < 0.05) between ECA and EMA tumors, it did not demonstrate any supplementary benefit to the 3-marker panel.</p> <p>Conclusion</p> <p>According to our data, when histomorphological and clinical doubt exists as to the primary site of origin, we recommend that the conventional 3-marker (ER/Vim/CEA) panel is easier, sufficient and appropriate to use in distinguishing between primary ECA and EMA. Although the 4-marker panel containing PR also reveals statistically significant results, the PR-marker offers no supplemental benefit to the pre-existing 3-marker (ER/Vim/CEA) panel in the diagnostic distinction between ECA and EMA.</p

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    The transcriptional landscape of Shh medulloblastoma

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    © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Sonic hedgehog medulloblastoma encompasses a clinically and molecularly diverse group of cancers of the developing central nervous system. Here, we use unbiased sequencing of the transcriptome across a large cohort of 250 tumors to reveal differences among molecular subtypes of the disease, and demonstrate the previously unappreciated importance of non-coding RNA transcripts. We identify alterations within the cAMP dependent pathway (GNAS, PRKAR1A) which converge on GLI2 activity and show that 18% of tumors have a genetic event that directly targets the abundance and/or stability of MYCN. Furthermore, we discover an extensive network of fusions in focally amplified regions encompassing GLI2, and several loss-of-function fusions in tumor suppressor genes PTCH1, SUFU and NCOR1. Molecular convergence on a subset of genes by nucleotide variants, copy number aberrations, and gene fusions highlight the key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma and open up opportunities for therapeutic intervention.info:eu-repo/semantics/publishedVersio
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