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Namiot ED, Zembatov GM, Tregub PP. Insights into brain tumor diagnosis: exploring in situ hybridization techniques. Front Neurol 2024; 15:1393572. [PMID: 39022728 PMCID: PMC11252041 DOI: 10.3389/fneur.2024.1393572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/31/2024] [Indexed: 07/20/2024] Open
Abstract
Objectives Diagnosing brain tumors is critical due to their complex nature. This review explores the potential of in situ hybridization for diagnosing brain neoplasms, examining their attributes and applications in neurology and oncology. Methods The review surveys literature and cross-references findings with the OMIM database, examining 513 records. It pinpoints mutations suitable for in situ hybridization and identifies common chromosomal and gene anomalies in brain tumors. Emphasis is placed on mutations' clinical implications, including prognosis and drug sensitivity. Results Amplifications in EGFR, MDM2, and MDM4, along with Y chromosome loss, chromosome 7 polysomy, and deletions of PTEN, CDKN2/p16, TP53, and DMBT1, correlate with poor prognosis in glioma patients. Protective genetic changes in glioma include increased expression of ADGRB3/1, IL12B, DYRKA1, VEGFC, LRRC4, and BMP4. Elevated MMP24 expression worsens prognosis in glioma, oligodendroglioma, and meningioma patients. Meningioma exhibits common chromosomal anomalies like loss of chromosomes 1, 9, 17, and 22, with specific genes implicated in their development. Main occurrences in medulloblastoma include the formation of isochromosome 17q and SHH signaling pathway disruption. Increased expression of BARHL1 is associated with prolonged survival. Adenomas mutations were reviewed with a focus on adenoma-carcinoma transition and different subtypes, with MMP9 identified as the main metalloprotease implicated in tumor progression. Discussion Molecular-genetic diagnostics for common brain tumors involve diverse genetic anomalies. In situ hybridization shows promise for diagnosing and prognosticating tumors. Detecting tumor-specific alterations is vital for prognosis and treatment. However, many mutations require other methods, hindering in situ hybridization from becoming the primary diagnostic method.
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Affiliation(s)
- E. D. Namiot
- Department of Pathophysiology, First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - G. M. Zembatov
- Department of Pathophysiology, First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - P. P. Tregub
- Department of Pathophysiology, First Moscow State Medical University (Sechenov University), Moscow, Russia
- Brain Research Department, Federal State Scientific Center of Neurology, Moscow, Russia
- Scientific and Educational Resource Center, Innovative Technologies of Immunophenotyping, Digital Spatial Profiling and Ultrastructural Analysis, Peoples' Friendship University of Russia (RUDN University), Moscow, Russia
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Dekker J, Alber F, Aufmkolk S, Beliveau BJ, Bruneau BG, Belmont AS, Bintu L, Boettiger A, Calandrelli R, Disteche CM, Gilbert DM, Gregor T, Hansen AS, Huang B, Huangfu D, Kalhor R, Leslie CS, Li W, Li Y, Ma J, Noble WS, Park PJ, Phillips-Cremins JE, Pollard KS, Rafelski SM, Ren B, Ruan Y, Shav-Tal Y, Shen Y, Shendure J, Shu X, Strambio-De-Castillia C, Vertii A, Zhang H, Zhong S. Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project. Mol Cell 2023; 83:2624-2640. [PMID: 37419111 PMCID: PMC10528254 DOI: 10.1016/j.molcel.2023.06.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 06/10/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023]
Abstract
The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.
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Affiliation(s)
- Job Dekker
- University of Massachusetts Chan Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Frank Alber
- University of California, Los Angeles, Los Angeles, CA, USA
| | | | | | - Benoit G Bruneau
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | - Bo Huang
- University of California, San Francisco, San Francisco, CA, USA
| | - Danwei Huangfu
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Reza Kalhor
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Wenbo Li
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yun Li
- University of North Carolina, Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Jian Ma
- Carnegie Mellon University, Pittsburgh, PA, USA
| | | | | | | | - Katherine S Pollard
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | | | - Bing Ren
- University of California, San Diego, La Jolla, CA, USA
| | - Yijun Ruan
- Zhejiang University, Hangzhou, Zhejiang, China
| | | | - Yin Shen
- University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiaokun Shu
- University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | - Sheng Zhong
- University of California, San Diego, La Jolla, CA, USA.
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Akhoundova D, Rubin MA. Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future. Cancer Cell 2022; 40:920-938. [PMID: 36055231 DOI: 10.1016/j.ccell.2022.08.011] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 05/22/2022] [Accepted: 08/11/2022] [Indexed: 12/17/2022]
Abstract
Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.
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Affiliation(s)
- Dilara Akhoundova
- Department for BioMedical Research, University of Bern, 3008 Bern, Switzerland; Department of Medical Oncology, Inselspital, University Hospital of Bern, 3010 Bern, Switzerland
| | - Mark A Rubin
- Department for BioMedical Research, University of Bern, 3008 Bern, Switzerland; Bern Center for Precision Medicine, Inselspital, University Hospital of Bern, 3008 Bern, Switzerland.
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