To date, no studies are available in which pituitary
adenomas (PAs)
have been studied using techniques like confocal Raman spectroscopy,
attenuated total reflection-Fourier transform infrared (FT-IR), and
liquid chromatography–tandem mass spectrometry (LC–MS/MS)
in the same serum samples. To understand the metabolomics fingerprint,
Raman spectra of 16 acromegaly, 19 Cushing’s, and 33 nonfunctional
PA (NFPA) and ATR-FTIR spectral acquisition of 16 acromegaly, 18 Cushing’s,
and 22 NFPA patient’s serum samples were acquired. Next, Principal
component-based linear discriminant analysis (PC-LDA) models were
developed, Raman spectral analysis classified acromegaly with an accuracy
of 79.17%, sensitivity of 75%, and specificity of 81.25%, Cushing’s
with an accuracy of 66.67%, sensitivity of 100%, and specificity of
52.63%, and NFPA with an accuracy of 73.17%, sensitivity of 75%, and
specificity of 72.73%. ATR-FTIR spectral analysis classified acromegaly
with an accuracy of 95.83%, sensitivity of 100%, and specificity of
93.75%, Cushing’s with an accuracy of 65.38%, sensitivity of
87.5%, and specificity of 55.56%, and NFPA with an accuracy of 70%,
sensitivity of 87.5%, and specificity of 43.75%. In either of the
cases, healthy individual cohorts were clearly segregated from the
disease cohort, which identified differential regulated regions of
nucleic acids, lipids, amides, phosphates, and polysaccharide/C–C
residue α helix regions. Furthermore, LC–MS/MS-based
analysis of sera samples resulted in the identification of various
sphingosine, lipids, acylcarnitines, amino acids, ethanolamine, choline,
and their derivatives that differentially regulated in each tumor
cohort. We believe cues obtained from the study may be used to generate
the metabolite-based test to diagnose PAs from serum in addition to
conventional techniques and also to understand disease biology for
better disease management, point of care, and improving quality of
life in PA patients.
