Prognostic Biomarkers for Hodgkin Lymphoma

Staege, Martin S.; Kewitz, Stefanie; Bernig, Toralf; Kühnöl, Caspar D.; Mauz‐Körholz, Christine

doi:10.3109/08880018.2015.1071903

Cited by 4 publications

(2 citation statements)

References 233 publications

(281 reference statements)

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“…We found several genes among the HL specific probe sets associated with HERV-like sequences with a known high expression in HL (Staege et al, 2008 , 2015 ; Hermes et al, 2016 ) such as the cancer/testis antigen PRAME (preferentially expressed antigen in melanoma), the cytokine EBI3 (Epstein-Barr virus induced 3), the chemokine fractalkine (CX3CL1), fascin (FSCN), or topoisomerase 2A (TOP2A). We also observed a high expression of all of these genes in HL cells in comparison to isolated B cells (Supplementary Figure 1 ).…”

Section: Resultsmentioning

confidence: 99%

WebHERV: A Web Server for the Computational Investigation of Gene Expression Associated With Endogenous Retrovirus-Like Sequences

et al. 2018

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More than eight percent of the human genome consists of human endogenous retroviruses (HERVs). Typically, the expression of HERVs is repressed, but varying activities of HERVs have been observed in diseases ranging from cancer to neuro-degeneration. Such activities can include the transcription of HERV-derived open reading frames, which can be translated into proteins. However, as a consequence of mutations that disrupt open reading frames, most HERV-like sequences have lost their protein-coding capacity. Nevertheless, these loci can still influence the expression of adjacent genes and, hence, mediate biological effects. Here, we present WebHERV (http://calypso.informatik.uni-halle.de/WebHERV/), a web server that enables the computational prediction of active HERV-like sequences in the human genome based on a comparison of genome coordinates of expressed sequences uploaded by the user and genome coordinates of HERV-like sequences stored in the specialized key-value store DRUMS. Using WebHERV, we predicted putative candidates of active HERV-like sequences in Hodgkin lymphoma (HL) cell lines, validated one of them by a modified SMART (switching mechanism at 5′ end of RNA template) technique, and identified a new alternative transcription start site for cytochrome P450, family 4, subfamily Z, polypeptide 1 (CYP4Z1).

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Section: Resultsmentioning

confidence: 99%

WebHERV: A Web Server for the Computational Investigation of Gene Expression Associated With Endogenous Retrovirus-Like Sequences

et al. 2018

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“…Contemporary treatment of Hodgkin's lymphoma (HL) in children and adolescents is based on chemotherapy (CTx), and in some cases, on CTx combined with radiotherapy (RTx). A significant reduction of treatment is currently considered in cases without manifesting risk factors due to good results of HL treatment [1][2][3]. Adapted risk therapy strategy allows reducing toxicity, which is a major factor, contributing to a considerable decrease in the long-term quality of life and life expectancy in patients treated for HL in childhood [4].…”

Section: Introductionmentioning

confidence: 99%

Hounsfield units and fractal dimension (test HUFRA) for determining PET positive/negative lymph nodes in pediatric Hodgkin’s lymphoma patients

et al. 2020

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Objectives We had developed a method that can help detect and identify lymph nodes affected by the neoplastic process. Our group evaluated the fractal dimension (FD) and X-ray attenuation (XRA) of lymph nodes in HL and compared to their metabolic activity as measured by 18F-FDG-PET examination. Methods The training set included 72 lymph nodes from 31 consecutive patients, and the tested set of 71 lymph nodes from next 19 patients. The measurement of FD of each lymph node was performed before the start of therapy using original software. X-ray attenuation (XRA) expressed in HU (Hounsfield Units) from CT scans was compared with the metabolic activity of the lymphatic nodes, measured by 18F-FDG-PET examination. Results Significant differences were observed between XRA max and FD max values in assessing the PET(+) and PET(-) nodes. All nodes were scored from 0 to 2. The HUFRA test properly qualified 95% with a score of 2 and 0 points as PET(+) or PET(-).

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GeneRaMeN enables integration, comparison, and meta-analysis of multiple ranked gene lists to identify consensus, unique, and correlated genes

Yousefi,

See,

Aw-Yong

et al. 2024

Briefings in Bioinformatics

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High-throughput experiments often produce ranked gene outputs, with forward genetic screening being a notable example. While there are various tools for analyzing individual datasets, those that perform comparative and meta-analytical examination of such ranked gene lists remain scarce. Here, we introduce Gene Rank Meta Analyzer (GeneRaMeN), an R Shiny tool utilizing rank statistics to facilitate the identification of consensus, unique, and correlated genes across multiple hit lists. We focused on two key topics to showcase GeneRaMeN: virus host factors and cancer dependencies. Using GeneRaMeN ‘Rank Aggregation’, we integrated 24 published and new flavivirus genetic screening datasets, including dengue, Japanese encephalitis, and Zika viruses. This meta-analysis yielded a consensus list of flavivirus host factors, elucidating the significant influence of cell line selection on screening outcomes. Similar analysis on 13 SARS-CoV-2 CRISPR screening datasets highlighted the pivotal role of meta-analysis in revealing redundant biological pathways exploited by the virus to enter human cells. Such redundancy was further underscored using GeneRaMeN’s ‘Rank Correlation’, where a strong negative correlation was observed for host factors implicated in one entry pathway versus the alternate route. Utilizing GeneRaMeN’s ‘Rank Uniqueness’, we analyzed human coronaviruses 229E, OC43, and SARS-CoV-2 datasets, identifying host factors uniquely associated with a defined subset of the screening datasets. Similar analyses were performed on over 1000 Cancer Dependency Map (DepMap) datasets spanning 19 human cancer types to reveal unique cancer vulnerabilities for each organ/tissue. GeneRaMeN, an efficient tool to integrate and maximize the usability of genetic screening datasets, is freely accessible via https://ysolab.shinyapps.io/GeneRaMeN.

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Prognostic Biomarkers for Hodgkin Lymphoma

Cited by 4 publications

References 233 publications

WebHERV: A Web Server for the Computational Investigation of Gene Expression Associated With Endogenous Retrovirus-Like Sequences

WebHERV: A Web Server for the Computational Investigation of Gene Expression Associated With Endogenous Retrovirus-Like Sequences

Hounsfield units and fractal dimension (test HUFRA) for determining PET positive/negative lymph nodes in pediatric Hodgkin’s lymphoma patients

GeneRaMeN enables integration, comparison, and meta-analysis of multiple ranked gene lists to identify consensus, unique, and correlated genes

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