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The Cancer Noise Atlas (TCNA): A Webserver of Multiscale Transcriptional Noise in Cancer.

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Τίτλος: The Cancer Noise Atlas (TCNA): A Webserver of Multiscale Transcriptional Noise in Cancer.
Συγγραφείς: Shah R; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan; Department of Computer Science, Dhanani School of Science and Engineering, Habib University, Karachi, Pakistan., Faisal A; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan; Department of Computer Science, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan., Faiz AB; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan., Bashir I; Department of Data Science, Islamia University Bahawalpur, Bahawalpur, Pakistan., Jawaid A; Translational Neuropsychiatry Research Group (TREND Lab), Lukasiewicz Research Network- PORT Polish Center for Technology Development, Wroclaw, Poland., Bashir K; Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan. Electronic address: khurram.bashir@lums.edu.pk., Shoaib M; Epigenome and Genome Integrity Laboratory (EAGIL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan. Electronic address: mshoaib@lums.edu.pk., Chaudhary SU; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan. Electronic address: safee.ullah.chaudhary@gmail.com.
Πηγή: Journal of molecular biology [J Mol Biol] 2026 Sep 15; Vol. 438 (18), pp. 169842. Date of Electronic Publication: 2026 May 07.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 2985088R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1089-8638 (Electronic) Linking ISSN: 00222836 NLM ISO Abbreviation: J Mol Biol Subsets: MEDLINE
Imprint Name(s): Publication: Amsterdam : Elsevier
Original Publication: 1959- : London : Academic Press
Ιατρικοί όροι (MeSH): Neoplasms*/genetics , Gene Expression Regulation, Neoplastic* , Software* , Transcription, Genetic* , Transcriptome*, Gene Expression Profiling/methods ; Genomics/methods ; Humans ; Internet ; Algorithms
Περίληψη: Cancer cells are characterized by highly divergent gene expression, resulting in expression heterogeneity in tumors, which contributes to variable therapeutic responses. The advent of next-generation sequencing has enabled the elucidation of genome-wide transcriptional variation ("noise") across tumor types. However, the current lack of data analysis pipelines for evaluating gene expression variation, their web-availability, and associated databases that catalog this variation across cancer sites, limits investigations into tumor heterogeneity. Here, we report an analytical platform for investigating transcriptional variation profiles in cancer - The Cancer Noise Atlas (TCNA), version 1.0. TCNA offers analysis and customized visualizations of transcriptional noise from bulk RNA-seq data, sourced from Genomics Data Commons (GDC), at three scales: (i) Genes, (ii) Pathways, and (iii) Tumors. The platform integrates and pipelines algorithms for analyzing transcriptional noise through tumor heterogeneity metrics such as coefficient of variation (CV), standard deviation (SD), mean absolute deviation (MAD), Differential Expression Phenotype Targeted Heterogeneity (DEPTH), and DEPTH2. Taken together, TCNA provides a significant advancement upon existing work in that it provides a simultaneous and comprehensive assessment of multiple integrated noise metrics for GDC datasets. Furthermore, with an increasing number of scRNA-seq datasets, TCNA is envisioned to grow into a high-resolution web portal for multiscale noise analysis across cancer types. Cataloging and mapping this heterogeneity can potentially assist in understanding tumor characteristics as well as disease progression and therapeutic response. The portal is freely available at https://tcna.lums.edu.pk/.
(Copyright © 2026 Elsevier Ltd. All rights reserved.)
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: cancer transcriptomics; differential gene expression; expression variance; transcriptional noise; tumor heterogeneity
Entry Date(s): Date Created: 20260509 Date Completed: 20260716 Latest Revision: 20260716
Update Code: 20260717
DOI: 10.1016/j.jmb.2026.169842
PMID: 42105973
Βάση Δεδομένων: MEDLINE
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  Data: The Cancer Noise Atlas (TCNA): A Webserver of Multiscale Transcriptional Noise in Cancer.
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  Data: <searchLink fieldCode="AU" term="%22Shah+R%22">Shah R</searchLink>; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan; Department of Computer Science, Dhanani School of Science and Engineering, Habib University, Karachi, Pakistan.<br /><searchLink fieldCode="AU" term="%22Faisal+A%22">Faisal A</searchLink>; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan; Department of Computer Science, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan.<br /><searchLink fieldCode="AU" term="%22Faiz+AB%22">Faiz AB</searchLink>; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan.<br /><searchLink fieldCode="AU" term="%22Bashir+I%22">Bashir I</searchLink>; Department of Data Science, Islamia University Bahawalpur, Bahawalpur, Pakistan.<br /><searchLink fieldCode="AU" term="%22Jawaid+A%22">Jawaid A</searchLink>; Translational Neuropsychiatry Research Group (TREND Lab), Lukasiewicz Research Network- PORT Polish Center for Technology Development, Wroclaw, Poland.<br /><searchLink fieldCode="AU" term="%22Bashir+K%22">Bashir K</searchLink>; Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan. Electronic address: khurram.bashir@lums.edu.pk.<br /><searchLink fieldCode="AU" term="%22Shoaib+M%22">Shoaib M</searchLink>; Epigenome and Genome Integrity Laboratory (EAGIL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan. Electronic address: mshoaib@lums.edu.pk.<br /><searchLink fieldCode="AU" term="%22Chaudhary+SU%22">Chaudhary SU</searchLink>; Biomedical Informatics & Engineering Research Laboratory (BIRL), Department of Life Sciences, Syed Babar Ali School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Lahore, Pakistan. Electronic address: safee.ullah.chaudhary@gmail.com.
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  Data: Cancer cells are characterized by highly divergent gene expression, resulting in expression heterogeneity in tumors, which contributes to variable therapeutic responses. The advent of next-generation sequencing has enabled the elucidation of genome-wide transcriptional variation ("noise") across tumor types. However, the current lack of data analysis pipelines for evaluating gene expression variation, their web-availability, and associated databases that catalog this variation across cancer sites, limits investigations into tumor heterogeneity. Here, we report an analytical platform for investigating transcriptional variation profiles in cancer - The Cancer Noise Atlas (TCNA), version 1.0. TCNA offers analysis and customized visualizations of transcriptional noise from bulk RNA-seq data, sourced from Genomics Data Commons (GDC), at three scales: (i) Genes, (ii) Pathways, and (iii) Tumors. The platform integrates and pipelines algorithms for analyzing transcriptional noise through tumor heterogeneity metrics such as coefficient of variation (CV), standard deviation (SD), mean absolute deviation (MAD), Differential Expression Phenotype Targeted Heterogeneity (DEPTH), and DEPTH2. Taken together, TCNA provides a significant advancement upon existing work in that it provides a simultaneous and comprehensive assessment of multiple integrated noise metrics for GDC datasets. Furthermore, with an increasing number of scRNA-seq datasets, TCNA is envisioned to grow into a high-resolution web portal for multiscale noise analysis across cancer types. Cataloging and mapping this heterogeneity can potentially assist in understanding tumor characteristics as well as disease progression and therapeutic response. The portal is freely available at https://tcna.lums.edu.pk/.<br /> (Copyright © 2026 Elsevier Ltd. All rights reserved.)
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  Data: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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  Data: <i>Keywords: </i>cancer transcriptomics; differential gene expression; expression variance; transcriptional noise; tumor heterogeneity
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