@article{PAR00011905,
  title = {{MALDI}-{T}o{F} mass spectrometry for the rapid diagnosis of cancerous lung nodules},
  author = {{B}regeon, {F}. and {B}rioude, {G}. and {D}e {D}ominicis, {F}. and {A}tieh, {T}. and {D}'{J}ourno, {X}. {B}. and {F}laudrops, {C}. and {R}olain, {J}. {M}. and {R}aoult, {D}idier and {T}homas, {P}. {A}.},
  editor = {},
  language = {{ENG}},
  abstract = {{R}ecently, tissue-based methods for proteomic analysis have been used in clinical research and appear reliable for digestive, brain, lymphomatous, and lung cancers classification. {H}owever simple, tissue-based methods that couple signal analysis to tissue imaging are time consuming. {T}o assess the reliability of a method involving rapid tissue preparation and analysis to discriminate cancerous from non-cancerous tissues, we tested 141 lung cancer/non-tumor pairs and 8 unique lung cancer samples among the stored frozen samples of 138 patients operated on during 2012. {S}amples were crushed in water, and 1.5 mu l was spotted onto a steel target for analysis with the {M}icroflex {LT} analyzer ({B}ruker {D}altonics). {S}pectra were analyzed using {C}lin{P}ro{T}ools software. {A} set of samples was used to generate a random classification model on the basis of a list of discriminant peaks sorted with the k-nearest neighbor genetic algorithm. {T}he rest of the samples (n = 43 cancerous and n = 41 non-tumoral) was used to verify the classification capability and calculate the diagnostic performance indices relative to the histological diagnosis. {T}he analysis found 53 m/z valid peaks, 40 of which were significantly different between cancerous and non-tumoral samples. {T}he selected genetic algorithm model identified 20 potential peaks from the training set and had 98.81% recognition capability and 89.17% positive predictive value. {I}n the blinded set, this method accurately discriminated the two classes with a sensitivity of 86.7% and a specificity of 95.1% for the cancer tissues and a sensitivity of 87.8% and a specificity of 95.3% for the non-tumor tissues. {T}he second model generated to discriminate primary lung cancer from metastases was of lower quality. {T}he reliability of {MALDI}-{T}o{F} analysis coupled with a very simple lung preparation procedure appears promising and should be tested in the operating room on fresh samples coupled with the pathological examination.},
  keywords = {},
  booktitle = {},
  journal = {{P}los {O}ne},
  volume = {9},
  numero = {5},
  pages = {e97511},
  ISSN = {1932-6203},
  year = {2014},
  DOI = {10.1371/journal.pone.0097511},
  URL = {https://www.documentation.ird.fr/hor/{PAR}00011905},
}