Soft threshold partial least squares predicts the survival fraction of malignant glioma cells against different concentrations of methotrexate’s derivatives

Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects...

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Published in:Scientific reports Vol. 11; no. 1; p. 18741
Main Authors: Mehmood, Tahir, Iqbal, Mudassir
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 21-09-2021
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Abstract Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects and increase efficacy. The current study uses FTIR spectroscopy to predict the survival fraction of human malignant glioma U87 (MG-U87) cell lines against MTX derivatives. Together with Parent MTX several aldehydes viz. Benzaldehyde, Chlorobenzaldehyde, 2-Chlorobenzaldehyde, 3-Nitrobenzaldehyde, 5-Chloro-2-hydroxybenz-aldehyde, 2-Hydroxy-5-Nitrobenzaldehyde, 2-Thiocarboxyaldehyde, Trans-2-pentenal, and Glutaraldehyde are treated with MTX to obtain MTX derivatives. The prediction of survival fraction of malignant glioma cells is carried out by Lasso, Elastic net and Soft PLS at different concentration levels of synthesized derivatives, including 400 μM, 200 μM, 100 μM, 50 μM, 25 μM and 12.5 μM. The cross-validated prediction error is minimised to optimise spectral wavelength selection and model parameters. It appears that the RMSE computed from test data is significantly varying with the change of models (p = 0.012), with the change of concentrations levels (p  ≤ 0.001 ) and with the change of combination of models and concentration level (p ≤ 0.001 ). StPLS outperforms in predicting survival fraction of glioma cells at the concentration level 50 μM, 100 μM and 400 μM respectively with relative RMSE = 0.1,0.14 and 0.55. Lasso outperforms at the concentration level 12.5 μM, and 200 μM respectively with relative RMSE = 0.4 and 0.14. Elastic net outperforms at the concentration level 25 μM with relative RMSE = 0.8. Consistently appeared influential wavelength identifies the influential functional compounds which best predicts the survival fraction. Hence FTIR appears potential candidate for estimating survival fraction of MTX derivatives.
AbstractList Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects and increase efficacy. The current study uses FTIR spectroscopy to predict the survival fraction of human malignant glioma U87 (MG-U87) cell lines against MTX derivatives. Together with Parent MTX several aldehydes viz. Benzaldehyde, Chlorobenzaldehyde, 2-Chlorobenzaldehyde, 3-Nitrobenzaldehyde, 5-Chloro-2-hydroxybenz-aldehyde, 2-Hydroxy-5-Nitrobenzaldehyde, 2-Thiocarboxyaldehyde, Trans-2-pentenal, and Glutaraldehyde are treated with MTX to obtain MTX derivatives. The prediction of survival fraction of malignant glioma cells is carried out by Lasso, Elastic net and Soft PLS at different concentration levels of synthesized derivatives, including 400 μM, 200 μM, 100 μM, 50 μM, 25 μM and 12.5 μM. The cross-validated prediction error is minimised to optimise spectral wavelength selection and model parameters. It appears that the RMSE computed from test data is significantly varying with the change of models (p = 0.012), with the change of concentrations levels (p [Formula: see text]) and with the change of combination of models and concentration level (p [Formula: see text]). StPLS outperforms in predicting survival fraction of glioma cells at the concentration level 50 μM, 100 μM and 400 μM respectively with relative RMSE = 0.1,0.14 and 0.55. Lasso outperforms at the concentration level 12.5 μM, and 200 μM respectively with relative RMSE = 0.4 and 0.14. Elastic net outperforms at the concentration level 25 μM with relative RMSE = 0.8. Consistently appeared influential wavelength identifies the influential functional compounds which best predicts the survival fraction. Hence FTIR appears potential candidate for estimating survival fraction of MTX derivatives.
Abstract Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects and increase efficacy. The current study uses FTIR spectroscopy to predict the survival fraction of human malignant glioma U87 (MG-U87) cell lines against MTX derivatives. Together with Parent MTX several aldehydes viz. Benzaldehyde, Chlorobenzaldehyde, 2-Chlorobenzaldehyde, 3-Nitrobenzaldehyde, 5-Chloro-2-hydroxybenz-aldehyde, 2-Hydroxy-5-Nitrobenzaldehyde, 2-Thiocarboxyaldehyde, Trans-2-pentenal, and Glutaraldehyde are treated with MTX to obtain MTX derivatives. The prediction of survival fraction of malignant glioma cells is carried out by Lasso, Elastic net and Soft PLS at different concentration levels of synthesized derivatives, including 400 μM, 200 μM, 100 μM, 50 μM, 25 μM and 12.5 μM. The cross-validated prediction error is minimised to optimise spectral wavelength selection and model parameters. It appears that the RMSE computed from test data is significantly varying with the change of models (p = 0.012), with the change of concentrations levels (p  $$\le 0.001$$ ≤ 0.001 ) and with the change of combination of models and concentration level (p $$\le 0.001$$ ≤ 0.001 ). StPLS outperforms in predicting survival fraction of glioma cells at the concentration level 50 μM, 100 μM and 400 μM respectively with relative RMSE = 0.1,0.14 and 0.55. Lasso outperforms at the concentration level 12.5 μM, and 200 μM respectively with relative RMSE = 0.4 and 0.14. Elastic net outperforms at the concentration level 25 μM with relative RMSE = 0.8. Consistently appeared influential wavelength identifies the influential functional compounds which best predicts the survival fraction. Hence FTIR appears potential candidate for estimating survival fraction of MTX derivatives.
Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects and increase efficacy. The current study uses FTIR spectroscopy to predict the survival fraction of human malignant glioma U87 (MG-U87) cell lines against MTX derivatives. Together with Parent MTX several aldehydes viz. Benzaldehyde, Chlorobenzaldehyde, 2-Chlorobenzaldehyde, 3-Nitrobenzaldehyde, 5-Chloro-2-hydroxybenz-aldehyde, 2-Hydroxy-5-Nitrobenzaldehyde, 2-Thiocarboxyaldehyde, Trans-2-pentenal, and Glutaraldehyde are treated with MTX to obtain MTX derivatives. The prediction of survival fraction of malignant glioma cells is carried out by Lasso, Elastic net and Soft PLS at different concentration levels of synthesized derivatives, including 400 μM, 200 μM, 100 μM, 50 μM, 25 μM and 12.5 μM. The cross-validated prediction error is minimised to optimise spectral wavelength selection and model parameters. It appears that the RMSE computed from test data is significantly varying with the change of models (p = 0.012), with the change of concentrations levels (p ≤0.001) and with the change of combination of models and concentration level (p ≤0.001). StPLS outperforms in predicting survival fraction of glioma cells at the concentration level 50 μM, 100 μM and 400 μM respectively with relative RMSE = 0.1,0.14 and 0.55. Lasso outperforms at the concentration level 12.5 μM, and 200 μM respectively with relative RMSE = 0.4 and 0.14. Elastic net outperforms at the concentration level 25 μM with relative RMSE = 0.8. Consistently appeared influential wavelength identifies the influential functional compounds which best predicts the survival fraction. Hence FTIR appears potential candidate for estimating survival fraction of MTX derivatives.
Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects and increase efficacy. The current study uses FTIR spectroscopy to predict the survival fraction of human malignant glioma U87 (MG-U87) cell lines against MTX derivatives. Together with Parent MTX several aldehydes viz. Benzaldehyde, Chlorobenzaldehyde, 2-Chlorobenzaldehyde, 3-Nitrobenzaldehyde, 5-Chloro-2-hydroxybenz-aldehyde, 2-Hydroxy-5-Nitrobenzaldehyde, 2-Thiocarboxyaldehyde, Trans-2-pentenal, and Glutaraldehyde are treated with MTX to obtain MTX derivatives. The prediction of survival fraction of malignant glioma cells is carried out by Lasso, Elastic net and Soft PLS at different concentration levels of synthesized derivatives, including 400 μM, 200 μM, 100 μM, 50 μM, 25 μM and 12.5 μM. The cross-validated prediction error is minimised to optimise spectral wavelength selection and model parameters. It appears that the RMSE computed from test data is significantly varying with the change of models (p = 0.012), with the change of concentrations levels (p  \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\le 0.001$$\end{document} ≤ 0.001 ) and with the change of combination of models and concentration level (p \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\le 0.001$$\end{document} ≤ 0.001 ). StPLS outperforms in predicting survival fraction of glioma cells at the concentration level 50 μM, 100 μM and 400 μM respectively with relative RMSE = 0.1,0.14 and 0.55. Lasso outperforms at the concentration level 12.5 μM, and 200 μM respectively with relative RMSE = 0.4 and 0.14. Elastic net outperforms at the concentration level 25 μM with relative RMSE = 0.8. Consistently appeared influential wavelength identifies the influential functional compounds which best predicts the survival fraction. Hence FTIR appears potential candidate for estimating survival fraction of MTX derivatives.
Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects and increase efficacy. The current study uses FTIR spectroscopy to predict the survival fraction of human malignant glioma U87 (MG-U87) cell lines against MTX derivatives. Together with Parent MTX several aldehydes viz. Benzaldehyde, Chlorobenzaldehyde, 2-Chlorobenzaldehyde, 3-Nitrobenzaldehyde, 5-Chloro-2-hydroxybenz-aldehyde, 2-Hydroxy-5-Nitrobenzaldehyde, 2-Thiocarboxyaldehyde, Trans-2-pentenal, and Glutaraldehyde are treated with MTX to obtain MTX derivatives. The prediction of survival fraction of malignant glioma cells is carried out by Lasso, Elastic net and Soft PLS at different concentration levels of synthesized derivatives, including 400 μM, 200 μM, 100 μM, 50 μM, 25 μM and 12.5 μM. The cross-validated prediction error is minimised to optimise spectral wavelength selection and model parameters. It appears that the RMSE computed from test data is significantly varying with the change of models (p = 0.012), with the change of concentrations levels (p  ≤ 0.001 ) and with the change of combination of models and concentration level (p ≤ 0.001 ). StPLS outperforms in predicting survival fraction of glioma cells at the concentration level 50 μM, 100 μM and 400 μM respectively with relative RMSE = 0.1,0.14 and 0.55. Lasso outperforms at the concentration level 12.5 μM, and 200 μM respectively with relative RMSE = 0.4 and 0.14. Elastic net outperforms at the concentration level 25 μM with relative RMSE = 0.8. Consistently appeared influential wavelength identifies the influential functional compounds which best predicts the survival fraction. Hence FTIR appears potential candidate for estimating survival fraction of MTX derivatives.
Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with strong activity but serious side effects. Several MTX derivatives have been reported, with modifications at various sites to reduce side effects and increase efficacy. The current study uses FTIR spectroscopy to predict the survival fraction of human malignant glioma U87 (MG-U87) cell lines against MTX derivatives. Together with Parent MTX several aldehydes viz. Benzaldehyde, Chlorobenzaldehyde, 2-Chlorobenzaldehyde, 3-Nitrobenzaldehyde, 5-Chloro-2-hydroxybenz-aldehyde, 2-Hydroxy-5-Nitrobenzaldehyde, 2-Thiocarboxyaldehyde, Trans-2-pentenal, and Glutaraldehyde are treated with MTX to obtain MTX derivatives. The prediction of survival fraction of malignant glioma cells is carried out by Lasso, Elastic net and Soft PLS at different concentration levels of synthesized derivatives, including 400 μM, 200 μM, 100 μM, 50 μM, 25 μM and 12.5 μM. The cross-validated prediction error is minimised to optimise spectral wavelength selection and model parameters. It appears that the RMSE computed from test data is significantly varying with the change of models (p = 0.012), with the change of concentrations levels (p  $$\le 0.001$$ ≤ 0.001 ) and with the change of combination of models and concentration level (p $$\le 0.001$$ ≤ 0.001 ). StPLS outperforms in predicting survival fraction of glioma cells at the concentration level 50 μM, 100 μM and 400 μM respectively with relative RMSE = 0.1,0.14 and 0.55. Lasso outperforms at the concentration level 12.5 μM, and 200 μM respectively with relative RMSE = 0.4 and 0.14. Elastic net outperforms at the concentration level 25 μM with relative RMSE = 0.8. Consistently appeared influential wavelength identifies the influential functional compounds which best predicts the survival fraction. Hence FTIR appears potential candidate for estimating survival fraction of MTX derivatives.
ArticleNumber 18741
Author Iqbal, Mudassir
Mehmood, Tahir
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Cites_doi 10.1016/j.bbamem.2009.02.016
10.1039/c0an00872a
10.1016/S0169-7439(00)00113-1
10.1039/C9AN00801B
10.1016/j.chemolab.2013.01.008
10.1016/j.ejmech.2018.09.027
10.1366/000370210792434350
10.1016/j.yexcr.2004.03.031
10.18637/jss.v033.i01
10.1093/rheumatology/keh512
10.1038/bjc.1997.164
10.1007/s00216-009-3140-y
10.4322/rbeb.2014.004
10.1007/s11749-008-0104-z
10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3
10.1016/S0378-4347(01)00402-9
10.1080/03602559.2018.1447126
10.1039/B307294K
10.1158/1078-0432.CCR-19-3717
10.1093/bioinformatics/bty199
10.1039/C4AN01831A
10.1097/00000441-195102000-00009
10.1016/j.microc.2012.06.016
10.1155/2010/910694
10.1111/j.1467-9868.2005.00503.x
10.1016/j.chemolab.2020.104124
10.32614/CRAN.package.plsVarSel
10.1007/BFb0062108
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References Liland, Almøy, Mevik (CR24) 2010; 64
Draux (CR12) 2009; 395
Kinder (CR4) 2005; 44
Liland, Høy, Martens, Sæbø (CR33) 2013; 122
Mehmood, Iqbal, Hassan (CR7) 2020; 206
CR37
CR36
CR35
CR34
Abdel Bary, Harmal, Saeed, Gouda (CR3) 2018; 57
Basu, Mitra, Liu, Schreiber, Clemons (CR21) 2018; 34
Zou, Hastie (CR32) 2005; 67
Gubner, August, Ginsberg (CR1) 1951; 221
Wald, Goormaghtigh (CR16) 2015; 140
Parachalil (CR18) 2019; 144
Hall, Giaccia (CR9) 2006
Batchelor, Kolak, Ciordia, Foster, Henson (CR5) 2003; 9
Martens, Næs (CR27) 1989
Derenne, Gasper, Goormaghtigh (CR19) 2010; 24
Gasper, Dewelle, Kiss, Mijatovic, Goormaghtigh (CR11) 2009; 1788
Lu (CR22) 2020; 26
Carvalho (CR15) 2014; 30
Derenne, Gasper, Goormaghtigh (CR17) 2011; 136
CR26
CR25
Gaigneaux (CR10) 2004; 297
Keleş, Chun (CR29) 2008; 17
Rubino (CR8) 2001; 764
CR23
Perez-Guaita (CR14) 2013; 106
Friedman, Hastie, Tibshirani (CR28) 2010; 33
Wang, Zhou, Liu (CR6) 2018; 158
Sæbø, Almøy, Aarøe, Aastveit (CR20) 2007; 20
Kasemsumran, Du, Murayama, Huehne, Ozaki (CR13) 2003; 128
Höskuldsson (CR30) 2001; 55
Kinsella, Smith, Pickard (CR2) 1997; 75
Tibshirani (CR31) 1997; 16
A Höskuldsson (97891_CR30) 2001; 55
CDS Carvalho (97891_CR15) 2014; 30
KH Liland (97891_CR33) 2013; 122
F Draux (97891_CR12) 2009; 395
J Friedman (97891_CR28) 2010; 33
H Martens (97891_CR27) 1989
97891_CR37
R Gubner (97891_CR1) 1951; 221
T Mehmood (97891_CR7) 2020; 206
G Lu (97891_CR22) 2020; 26
E Abdel Bary (97891_CR3) 2018; 57
97891_CR25
A Gaigneaux (97891_CR10) 2004; 297
97891_CR23
A Kinsella (97891_CR2) 1997; 75
EJ Hall (97891_CR9) 2006
H Zou (97891_CR32) 2005; 67
S Sæbø (97891_CR20) 2007; 20
R Tibshirani (97891_CR31) 1997; 16
K Liland (97891_CR24) 2010; 64
A Derenne (97891_CR17) 2011; 136
97891_CR26
S Kasemsumran (97891_CR13) 2003; 128
R Gasper (97891_CR11) 2009; 1788
D Perez-Guaita (97891_CR14) 2013; 106
DR Parachalil (97891_CR18) 2019; 144
97891_CR35
97891_CR36
A Derenne (97891_CR19) 2010; 24
TT Batchelor (97891_CR5) 2003; 9
W Wang (97891_CR6) 2018; 158
N Wald (97891_CR16) 2015; 140
97891_CR34
FM Rubino (97891_CR8) 2001; 764
S Keleş (97891_CR29) 2008; 17
A Basu (97891_CR21) 2018; 34
A Kinder (97891_CR4) 2005; 44
References_xml – volume: 1788
  start-page: 1263
  year: 2009
  end-page: 1270
  ident: CR11
  article-title: Ir spectroscopy as a new tool for evidencing antitumor drug signatures
  publication-title: Biochim. Biophys. Acta (BBA) Biomemb.
  doi: 10.1016/j.bbamem.2009.02.016
  contributor:
    fullname: Goormaghtigh
– volume: 136
  start-page: 1134
  year: 2011
  end-page: 1141
  ident: CR17
  article-title: The FTIR spectrum of prostate cancer cells allows the classification of anticancer drugs according to their mode of action
  publication-title: Analyst
  doi: 10.1039/c0an00872a
  contributor:
    fullname: Goormaghtigh
– volume: 55
  start-page: 23
  year: 2001
  end-page: 38
  ident: CR30
  article-title: Variable and subset selection in PLS regression
  publication-title: Chemom. Intell. Lab. Syst.
  doi: 10.1016/S0169-7439(00)00113-1
  contributor:
    fullname: Höskuldsson
– volume: 144
  start-page: 5207
  year: 2019
  end-page: 5214
  ident: CR18
  article-title: Raman spectroscopy as a potential tool for label free therapeutic drug monitoring in human serum: The case of busulfan and methotrexate
  publication-title: Analyst
  doi: 10.1039/C9AN00801B
  contributor:
    fullname: Parachalil
– volume: 122
  start-page: 103
  year: 2013
  end-page: 111
  ident: CR33
  article-title: Distribution based truncation for variable selection in subspace methods for multivariate regression
  publication-title: Chemom. Intell. Lab. Syst.
  doi: 10.1016/j.chemolab.2013.01.008
  contributor:
    fullname: Sæbø
– volume: 158
  start-page: 502
  year: 2018
  end-page: 516
  ident: CR6
  article-title: Side effects of methotrexate therapy for rheumatoid arthritis: A systematic review
  publication-title: Eur. J. Med. Chem.
  doi: 10.1016/j.ejmech.2018.09.027
  contributor:
    fullname: Liu
– ident: CR37
– volume: 64
  start-page: 1007
  year: 2010
  end-page: 10016
  ident: CR24
  article-title: Optimal choice of baseline correction for multivariate calibration of spectra
  publication-title: Appl. Spectrosc.
  doi: 10.1366/000370210792434350
  contributor:
    fullname: Mevik
– volume: 297
  start-page: 294
  year: 2004
  end-page: 301
  ident: CR10
  article-title: The infrared spectrum of human glioma cells is related to their in vitro and in vivo behavior
  publication-title: Exp. Cell Res.
  doi: 10.1016/j.yexcr.2004.03.031
  contributor:
    fullname: Gaigneaux
– volume: 33
  start-page: 1
  year: 2010
  ident: CR28
  article-title: Regularization paths for generalized linear models via coordinate descent
  publication-title: J. Stat. Softw.
  doi: 10.18637/jss.v033.i01
  contributor:
    fullname: Tibshirani
– ident: CR35
– volume: 44
  start-page: 61
  year: 2005
  end-page: 66
  ident: CR4
  article-title: The treatment of inflammatory arthritis with methotrexate in clinical practice: Treatment duration and incidence of adverse drug reactions
  publication-title: Rheumatology
  doi: 10.1093/rheumatology/keh512
  contributor:
    fullname: Kinder
– volume: 75
  start-page: 935
  year: 1997
  end-page: 945
  ident: CR2
  article-title: Resistance to chemotherapeutic antimetabolites: A function of salvage pathway involvement and cellular response to DNA damage
  publication-title: Br. J. Cancer
  doi: 10.1038/bjc.1997.164
  contributor:
    fullname: Pickard
– volume: 395
  start-page: 2293
  year: 2009
  end-page: 2301
  ident: CR12
  article-title: Ir spectroscopy reveals effect of non-cytotoxic doses of anti-tumour drug on cancer cells
  publication-title: Anal. Bioanal. Chem.
  doi: 10.1007/s00216-009-3140-y
  contributor:
    fullname: Draux
– volume: 30
  start-page: 54
  year: 2014
  end-page: 63
  ident: CR15
  article-title: Study of advanced rheumatoid arthritis
  publication-title: Revista Brasileira de Engenharia Biomédica
  doi: 10.4322/rbeb.2014.004
  contributor:
    fullname: Carvalho
– ident: CR25
– year: 1989
  ident: CR27
  publication-title: Multivariate Calibration
  contributor:
    fullname: Næs
– volume: 20
  start-page: 54
  year: 2007
  end-page: 62
  ident: CR20
  article-title: ST-PLS: A multi-dimensional nearest shrunken centroid type classifier via PLS
  publication-title: J. Chemom.
  contributor:
    fullname: Aastveit
– volume: 17
  start-page: 36
  year: 2008
  end-page: 39
  ident: CR29
  article-title: Comments on: Augmenting the bootstrap to analyze high dimensional genomic data
  publication-title: TEST
  doi: 10.1007/s11749-008-0104-z
  contributor:
    fullname: Chun
– ident: CR23
– volume: 16
  start-page: 385
  year: 1997
  end-page: 395
  ident: CR31
  article-title: The Lasso method for variable selection in the Cox model
  publication-title: Stat. Med.
  doi: 10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3
  contributor:
    fullname: Tibshirani
– volume: 764
  start-page: 217
  year: 2001
  end-page: 254
  ident: CR8
  article-title: Separation methods for methotrexate, its structural analogues and metabolites
  publication-title: J. Chromatogr. B Biomed. Sci. Appl.
  doi: 10.1016/S0378-4347(01)00402-9
  contributor:
    fullname: Rubino
– volume: 57
  start-page: 1906
  year: 2018
  end-page: 1914
  ident: CR3
  article-title: Design, synthesis, characterization, swelling and in vitro drug release behavior of composite hydrogel beads based on methotrexate and chitosan incorporating antipyrine moiety
  publication-title: Polym. Plast. Technol. Eng.
  doi: 10.1080/03602559.2018.1447126
  contributor:
    fullname: Gouda
– volume: 128
  start-page: 1471
  year: 2003
  end-page: 1477
  ident: CR13
  article-title: Simultaneous determination of human serum albumin, -globulin, and glucose in a phosphate buffer solution by near-infrared spectroscopy with moving window partial least-squares regression
  publication-title: Analyst
  doi: 10.1039/B307294K
  contributor:
    fullname: Ozaki
– volume: 26
  start-page: 2582
  year: 2020
  end-page: 2594
  ident: CR22
  article-title: Predicting therapeutic antibody delivery into human head and neck cancers
  publication-title: Clin. Cancer Res.
  doi: 10.1158/1078-0432.CCR-19-3717
  contributor:
    fullname: Lu
– volume: 34
  start-page: 3332
  year: 2018
  end-page: 3339
  ident: CR21
  article-title: RWEN: Response-weighted elastic net for prediction of chemosensitivity of cancer cell lines
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/bty199
  contributor:
    fullname: Clemons
– volume: 9
  start-page: 711
  year: 2003
  end-page: 715
  ident: CR5
  article-title: High-dose methotrexate for intraocular lymphoma
  publication-title: Clin. Cancer Res.
  contributor:
    fullname: Henson
– volume: 140
  start-page: 2144
  year: 2015
  end-page: 2155
  ident: CR16
  article-title: Infrared imaging of primary melanomas reveals hints of regional and distant metastases
  publication-title: Analyst
  doi: 10.1039/C4AN01831A
  contributor:
    fullname: Goormaghtigh
– volume: 221
  start-page: 176
  year: 1951
  end-page: 182
  ident: CR1
  article-title: Therapeutic suppression of tissue reactivity. 2. Effect of aminopterin in rheumatoid arthritis and psoriasis
  publication-title: Am. J. Med. Sci.
  doi: 10.1097/00000441-195102000-00009
  contributor:
    fullname: Ginsberg
– volume: 106
  start-page: 202
  year: 2013
  end-page: 211
  ident: CR14
  article-title: Evaluation of infrared spectroscopy as a screening tool for serum analysis: Impact of the nature of samples included in the calibration set
  publication-title: Microchem. J.
  doi: 10.1016/j.microc.2012.06.016
  contributor:
    fullname: Perez-Guaita
– volume: 24
  start-page: 55
  year: 2010
  end-page: 60
  ident: CR19
  article-title: Monitoring of metabolism perturbation in prostate pc-3 cancer cells by sub-lethal concentrations of methotrexate
  publication-title: Spectroscopy
  doi: 10.1155/2010/910694
  contributor:
    fullname: Goormaghtigh
– ident: CR34
– ident: CR36
– volume: 67
  start-page: 301
  issue: 2
  year: 2005
  end-page: 320
  ident: CR32
  article-title: Regularization and variable selection via the elastic-net
  publication-title: J. R. Stat. Soc. B
  doi: 10.1111/j.1467-9868.2005.00503.x
  contributor:
    fullname: Hastie
– ident: CR26
– year: 2006
  ident: CR9
  publication-title: Radiobiology for the Radiologist
  contributor:
    fullname: Giaccia
– volume: 206
  start-page: 104124
  year: 2020
  ident: CR7
  article-title: Prediction of antibacterial activity in ionic liquids through FTIR spectroscopy with selection of wavenumber by pls
  publication-title: Chemom. Intell. Lab. Syst.
  doi: 10.1016/j.chemolab.2020.104124
  contributor:
    fullname: Hassan
– volume: 26
  start-page: 2582
  year: 2020
  ident: 97891_CR22
  publication-title: Clin. Cancer Res.
  doi: 10.1158/1078-0432.CCR-19-3717
  contributor:
    fullname: G Lu
– ident: 97891_CR37
  doi: 10.32614/CRAN.package.plsVarSel
– ident: 97891_CR34
– volume: 34
  start-page: 3332
  year: 2018
  ident: 97891_CR21
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/bty199
  contributor:
    fullname: A Basu
– volume: 297
  start-page: 294
  year: 2004
  ident: 97891_CR10
  publication-title: Exp. Cell Res.
  doi: 10.1016/j.yexcr.2004.03.031
  contributor:
    fullname: A Gaigneaux
– volume: 764
  start-page: 217
  year: 2001
  ident: 97891_CR8
  publication-title: J. Chromatogr. B Biomed. Sci. Appl.
  doi: 10.1016/S0378-4347(01)00402-9
  contributor:
    fullname: FM Rubino
– volume: 106
  start-page: 202
  year: 2013
  ident: 97891_CR14
  publication-title: Microchem. J.
  doi: 10.1016/j.microc.2012.06.016
  contributor:
    fullname: D Perez-Guaita
– volume: 144
  start-page: 5207
  year: 2019
  ident: 97891_CR18
  publication-title: Analyst
  doi: 10.1039/C9AN00801B
  contributor:
    fullname: DR Parachalil
– volume: 16
  start-page: 385
  year: 1997
  ident: 97891_CR31
  publication-title: Stat. Med.
  doi: 10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3
  contributor:
    fullname: R Tibshirani
– volume: 44
  start-page: 61
  year: 2005
  ident: 97891_CR4
  publication-title: Rheumatology
  doi: 10.1093/rheumatology/keh512
  contributor:
    fullname: A Kinder
– volume: 33
  start-page: 1
  year: 2010
  ident: 97891_CR28
  publication-title: J. Stat. Softw.
  doi: 10.18637/jss.v033.i01
  contributor:
    fullname: J Friedman
– volume: 75
  start-page: 935
  year: 1997
  ident: 97891_CR2
  publication-title: Br. J. Cancer
  doi: 10.1038/bjc.1997.164
  contributor:
    fullname: A Kinsella
– volume: 17
  start-page: 36
  year: 2008
  ident: 97891_CR29
  publication-title: TEST
  doi: 10.1007/s11749-008-0104-z
  contributor:
    fullname: S Keleş
– volume: 55
  start-page: 23
  year: 2001
  ident: 97891_CR30
  publication-title: Chemom. Intell. Lab. Syst.
  doi: 10.1016/S0169-7439(00)00113-1
  contributor:
    fullname: A Höskuldsson
– volume: 136
  start-page: 1134
  year: 2011
  ident: 97891_CR17
  publication-title: Analyst
  doi: 10.1039/c0an00872a
  contributor:
    fullname: A Derenne
– ident: 97891_CR36
– volume: 1788
  start-page: 1263
  year: 2009
  ident: 97891_CR11
  publication-title: Biochim. Biophys. Acta (BBA) Biomemb.
  doi: 10.1016/j.bbamem.2009.02.016
  contributor:
    fullname: R Gasper
– volume: 140
  start-page: 2144
  year: 2015
  ident: 97891_CR16
  publication-title: Analyst
  doi: 10.1039/C4AN01831A
  contributor:
    fullname: N Wald
– volume-title: Multivariate Calibration
  year: 1989
  ident: 97891_CR27
  contributor:
    fullname: H Martens
– volume: 67
  start-page: 301
  issue: 2
  year: 2005
  ident: 97891_CR32
  publication-title: J. R. Stat. Soc. B
  doi: 10.1111/j.1467-9868.2005.00503.x
  contributor:
    fullname: H Zou
– volume-title: Radiobiology for the Radiologist
  year: 2006
  ident: 97891_CR9
  contributor:
    fullname: EJ Hall
– volume: 24
  start-page: 55
  year: 2010
  ident: 97891_CR19
  publication-title: Spectroscopy
  doi: 10.1155/2010/910694
  contributor:
    fullname: A Derenne
– volume: 64
  start-page: 1007
  year: 2010
  ident: 97891_CR24
  publication-title: Appl. Spectrosc.
  doi: 10.1366/000370210792434350
  contributor:
    fullname: K Liland
– ident: 97891_CR25
– ident: 97891_CR26
  doi: 10.1007/BFb0062108
– volume: 221
  start-page: 176
  year: 1951
  ident: 97891_CR1
  publication-title: Am. J. Med. Sci.
  doi: 10.1097/00000441-195102000-00009
  contributor:
    fullname: R Gubner
– volume: 395
  start-page: 2293
  year: 2009
  ident: 97891_CR12
  publication-title: Anal. Bioanal. Chem.
  doi: 10.1007/s00216-009-3140-y
  contributor:
    fullname: F Draux
– volume: 122
  start-page: 103
  year: 2013
  ident: 97891_CR33
  publication-title: Chemom. Intell. Lab. Syst.
  doi: 10.1016/j.chemolab.2013.01.008
  contributor:
    fullname: KH Liland
– volume: 158
  start-page: 502
  year: 2018
  ident: 97891_CR6
  publication-title: Eur. J. Med. Chem.
  doi: 10.1016/j.ejmech.2018.09.027
  contributor:
    fullname: W Wang
– volume: 9
  start-page: 711
  year: 2003
  ident: 97891_CR5
  publication-title: Clin. Cancer Res.
  contributor:
    fullname: TT Batchelor
– volume: 206
  start-page: 104124
  year: 2020
  ident: 97891_CR7
  publication-title: Chemom. Intell. Lab. Syst.
  doi: 10.1016/j.chemolab.2020.104124
  contributor:
    fullname: T Mehmood
– ident: 97891_CR23
– volume: 30
  start-page: 54
  year: 2014
  ident: 97891_CR15
  publication-title: Revista Brasileira de Engenharia Biomédica
  doi: 10.4322/rbeb.2014.004
  contributor:
    fullname: CDS Carvalho
– volume: 57
  start-page: 1906
  year: 2018
  ident: 97891_CR3
  publication-title: Polym. Plast. Technol. Eng.
  doi: 10.1080/03602559.2018.1447126
  contributor:
    fullname: E Abdel Bary
– volume: 20
  start-page: 54
  year: 2007
  ident: 97891_CR20
  publication-title: J. Chemom.
  contributor:
    fullname: S Sæbø
– ident: 97891_CR35
– volume: 128
  start-page: 1471
  year: 2003
  ident: 97891_CR13
  publication-title: Analyst
  doi: 10.1039/B307294K
  contributor:
    fullname: S Kasemsumran
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Snippet Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug with...
Abstract Chemotherapy appeared to be a significant advancement in cancer research, with fewer side effects. Methotrexate (MTX) is a widely used anticancer drug...
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StartPage 18741
SubjectTerms 631/45
639/705/531
692/308
Aldehydes
Antineoplastic Agents - pharmacology
Antineoplastic Agents - therapeutic use
Antitumor agents
Arthritis
Benzaldehyde
Brain Neoplasms - drug therapy
Brain Neoplasms - pathology
Cancer
Cancer research
Cell Survival - drug effects
Chemotherapy
Drug dosages
Glioma
Glioma - drug therapy
Glioma - pathology
Glioma cells
Humanities and Social Sciences
Humans
Least-Squares Analysis
Metabolism
Methotrexate
Methotrexate - pharmacology
Methotrexate - therapeutic use
multidisciplinary
Science
Science (multidisciplinary)
Side effects
Solvents
Spectrum analysis
Survival
Wavelength
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Title Soft threshold partial least squares predicts the survival fraction of malignant glioma cells against different concentrations of methotrexate’s derivatives
URI https://link.springer.com/article/10.1038/s41598-021-97891-3
https://www.ncbi.nlm.nih.gov/pubmed/34548518
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https://search.proquest.com/docview/2575366819
https://pubmed.ncbi.nlm.nih.gov/PMC8455530
https://doaj.org/article/1513b5bdf9cb4ad786ef47a14029e228
Volume 11
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