Literature DB >> 33594122

Raman spectroscopy and group and basis-restricted non negative matrix factorisation identifies radiation induced metabolic changes in human cancer cells.

Kirsty Milligan1, Xinchen Deng1, Phillip Shreeves2, Ramie Ali-Adeeb1, Quinn Matthews3, Alexandre Brolo4, Julian J Lum5,6, Jeffrey L Andrews2, Andrew Jirasek7.   

Abstract

This work combines single cell Raman spectroscopy (RS) with group and basis restricted non-negative matrix factorisation (GBR-NMF) to identify individual biochemical changes associated with radiation exposure in three human cancer cell lines. The cell lines analysed were derived from lung (H460), breast (MCF7) and prostate (LNCaP) tissue and are known to display varying degrees of radio sensitivity due to the inherent properties of each cell type. The GBR-NMF approach involves the deconstruction of Raman spectra into component biochemical bases using a library of Raman spectra of known biochemicals present in the cells. Subsequently, scores are obtained on each of these bases which can be directly correlated with the contribution of each chemical to the overall Raman spectrum. We validated GBR-NMF through the correlation of GBR-NMF-derived glycogen scores with scores that were previously observed using principal component analysis (PCA). Phosphatidylcholine, glucose, arginine and asparagine showed a distinct differential score pattern between radio-resistant and radio-sensitive cell types. In summary, the GBR-NMF approach allows for the monitoring of individual biochemical radiation-response dynamics previously unattainable with more traditional PCA-based approaches.

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Year:  2021        PMID: 33594122      PMCID: PMC7886912          DOI: 10.1038/s41598-021-83343-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  37 in total

1.  Learning the parts of objects by non-negative matrix factorization.

Authors:  D D Lee; H S Seung
Journal:  Nature       Date:  1999-10-21       Impact factor: 49.962

2.  Understanding the molecular information contained in principal component analysis of vibrational spectra of biological systems.

Authors:  F Bonnier; H J Byrne
Journal:  Analyst       Date:  2011-11-24       Impact factor: 4.616

Review 3.  Glucose metabolism in cancer cells.

Authors:  Alessandro Annibaldi; Christian Widmann
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2010-07       Impact factor: 4.294

Review 4.  Cancer cell metabolism: the essential role of the nonessential amino acid, glutamine.

Authors:  Ji Zhang; Natalya N Pavlova; Craig B Thompson
Journal:  EMBO J       Date:  2017-04-18       Impact factor: 11.598

Review 5.  Metabolic pathways promoting cancer cell survival and growth.

Authors:  Lindsey K Boroughs; Ralph J DeBerardinis
Journal:  Nat Cell Biol       Date:  2015-03-16       Impact factor: 28.824

6.  Monitor Ionizing Radiation-Induced Cellular Responses with Raman Spectroscopy, Non-Negative Matrix Factorization, and Non-Negative Least Squares.

Authors:  Xinchen Deng; Ramie Ali-Adeeb; Jeffrey L Andrews; Phillip Shreeves; Julian J Lum; Alexandre Brolo; Andrew Jirasek
Journal:  Appl Spectrosc       Date:  2020-03-18       Impact factor: 2.388

Review 7.  Targeting Phospholipid Metabolism in Cancer.

Authors:  Menglin Cheng; Zaver M Bhujwalla; Kristine Glunde
Journal:  Front Oncol       Date:  2016-12-27       Impact factor: 6.244

Review 8.  The Central Role of Amino Acids in Cancer Redox Homeostasis: Vulnerability Points of the Cancer Redox Code.

Authors:  Milica Vučetić; Yann Cormerais; Scott K Parks; Jacques Pouysségur
Journal:  Front Oncol       Date:  2017-12-21       Impact factor: 6.244

Review 9.  Amino acids in cancer.

Authors:  Elizabeth L Lieu; Tu Nguyen; Shawn Rhyne; Jiyeon Kim
Journal:  Exp Mol Med       Date:  2020-01-24       Impact factor: 8.718

Review 10.  New aspects of amino acid metabolism in cancer.

Authors:  Lisa Vettore; Rebecca L Westbrook; Daniel A Tennant
Journal:  Br J Cancer       Date:  2019-12-10       Impact factor: 7.640

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  6 in total

1.  Nanotube abundance from non-negative matrix factorization of Raman spectra as an example of chemical purity from open source machine learning.

Authors:  Elijah Flores; Jianying Ouyang; François Lapointe; Paul Finnie
Journal:  Sci Rep       Date:  2022-07-08       Impact factor: 4.996

Review 2.  Unveiling Cancer Metabolism through Spontaneous and Coherent Raman Spectroscopy and Stable Isotope Probing.

Authors:  Jiabao Xu; Tong Yu; Christos E Zois; Ji-Xin Cheng; Yuguo Tang; Adrian L Harris; Wei E Huang
Journal:  Cancers (Basel)       Date:  2021-04-05       Impact factor: 6.639

3.  Raman Research on Bleomycin-Induced DNA Strand Breaks and Repair Processes in Living Cells.

Authors:  Michał Czaja; Katarzyna Skirlińska-Nosek; Olga Adamczyk; Kamila Sofińska; Natalia Wilkosz; Zenon Rajfur; Marek Szymoński; Ewelina Lipiec
Journal:  Int J Mol Sci       Date:  2022-03-24       Impact factor: 5.923

4.  A Machine Learning Framework for Detecting COVID-19 Infection Using Surface-Enhanced Raman Scattering.

Authors:  Eloghosa Ikponmwoba; Okezzi Ukorigho; Parikshit Moitra; Dipanjan Pan; Manas Ranjan Gartia; Opeoluwa Owoyele
Journal:  Biosensors (Basel)       Date:  2022-08-02

5.  Prediction of disease progression indicators in prostate cancer patients receiving HDR-brachytherapy using Raman spectroscopy and semi-supervised learning: a pilot study.

Authors:  Kirsty Milligan; Xinchen Deng; Ramie Ali-Adeeb; Phillip Shreeves; Samantha Punch; Nathalie Costie; Juanita M Crook; Alexandre G Brolo; Julian J Lum; Jeffrey L Andrews; Andrew Jirasek
Journal:  Sci Rep       Date:  2022-09-06       Impact factor: 4.996

6.  Group and Basis Restricted Non-Negative Matrix Factorization and Random Forest for Molecular Histotype Classification and Raman Biomarker Monitoring in Breast Cancer.

Authors:  Xinchen Deng; Kirsty Milligan; Ramie Ali-Adeeb; Phillip Shreeves; Alexandre Brolo; Julian J Lum; Jeffrey L Andrews; Andrew Jirasek
Journal:  Appl Spectrosc       Date:  2021-08-06       Impact factor: 2.388

  6 in total

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