ArticleScientific reports2016
Unique spectral markers discern recurrent Glioblastoma cells from heterogeneous parent population.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Raman Spectroscopy Revealed Cell Passage-Dependent Distinct Biochemical Alterations in Radiation-Resistant Breast Cancer Cells.ACS omega · 2023Article
- Lipid Alterations in Glioma: A Systematic Review.Metabolites · 2022Review
- The application of feature engineering in establishing a rapid and robust model for identifying patients with glioma.Lasers in medical science · 2022Article
- Article
- Inhibition of SETMAR-H3K36me2-NHEJ repair axis in residual disease cells prevents glioblastoma recurrence.Neuro-oncology · 2020Article
- Rise of Raman spectroscopy in neurosurgery: a review.Journal of biomedical optics · 2020Review
- Rapid Label-Free Analysis of Brain Tumor Biopsies by Near Infrared Raman and Fluorescence Spectroscopy-A Study of 209 Patients.Frontiers in oncology · 2019Article
- Upcoming imaging concepts and their impact on treatment planning and treatment response in radiation oncology.Radiation oncology (London, England) · 2018Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
An inability to discern resistant cells from bulk tumour cell population contributes to poor prognosis in Glioblastoma. Here, we compared parent and recurrent cells generated from patient derived primary cultures and cell lines to identify their unique molecular hallmarks. Although morphologically similar, parent and recurrent cells from different samples showed variable biological properties like proliferation and radiation resistance. However, total RNA-sequencing revealed transcriptional landscape unique to parent and recurrent populations. These data suggest that global molecular differences but not individual biological phenotype could differentiate parent and recurrent cells. We demonstrate that Raman Spectroscopy a label-free, non-invasive technique, yields global information about biochemical milieu of recurrent and parent cells thus, classifying them into distinct clusters based on Principal-Component-Analysis and Principal-Component-Linear-Discriminant-Analysis. Additionally, higher lipid related spectral peaks were observed in recurrent population. Importantly, Raman spectroscopic analysis could further classify an independent set of naïve primary glioblastoma tumour tissues into non-responder and responder groups. Interestingly, spectral features from the non-responder patient samples show a considerable overlap with the in-vitro generated recurrent cells suggesting their similar biological behaviour. This feasibility study necessitates analysis of a larger cohort of naïve primary glioblastoma samples to fully envisage clinical utility of Raman spectroscopy in predicting therapeutic response.
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Registered trials
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