PMID- 35743734
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220716
IS  - 2075-4426 (Print)
IS  - 2075-4426 (Electronic)
IS  - 2075-4426 (Linking)
VI  - 12
IP  - 6
DP  - 2022 Jun 10
TI  - Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for 
      Cancer Liquid Biopsy.
LID - 10.3390/jpm12060949 [doi]
LID - 949
AB  - Extracellular vesicles (EVs) are abundantly released into the systemic 
      circulation, where they show remarkable stability and harbor molecular 
      constituents that provide biochemical information about their cells of origin. 
      Due to this characteristic, EVs are attracting increasing attention as a source 
      of circulating biomarkers for cancer liquid biopsy and personalized medicine. 
      Despite this potential, none of the discovered biomarkers has entered the 
      clinical practice so far, and novel approaches for the label-free 
      characterization of EVs are highly demanded. In this regard, Fourier Transform 
      Infrared Spectroscopy (FTIR) has great potential as it provides a quick, 
      reproducible, and informative biomolecular fingerprint of EVs. In this pilot 
      study, we investigated, for the first time in the literature, the capability of 
      FTIR spectroscopy to distinguish between EVs extracted from sera of cancer 
      patients and controls based on their mid-IR spectral response. For this purpose, 
      EV-enriched suspensions were obtained from the serum of patients diagnosed with 
      Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our 
      data point out the presence of statistically significant differences in the 
      integrated intensities of major mid-IR absorption bands, including the 
      carbohydrate and nucleic acids band, the protein amide I and II bands, and the 
      lipid CH stretching band. Additionally, we used Principal Component Analysis 
      combined with Linear Discriminant Analysis (PCA-LDA) for the automated 
      classification of spectral data according to the shape of specific mid-IR 
      spectral signatures. The diagnostic performances of the proposed spectral 
      biomarkers, alone and combined, were evaluated using multivariate logistic 
      regression followed by a Receiving Operator Curve analysis, obtaining large Areas 
      Under the Curve (AUC = 0.91, 95% CI 0.81-1.0). Very interestingly, our analyses 
      suggest that the discussed spectral biomarkers can outperform the classification 
      ability of two widely used circulating HCC markers measured on the same groups of 
      subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of 
      vitamin K or antagonist-II (PIVKA-II).
FAU - Di Santo, Riccardo
AU  - Di Santo R
AD  - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
FAU - Vaccaro, Maria
AU  - Vaccaro M
AUID- ORCID: 0000-0002-4275-0729
AD  - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
FAU - Romano, Sabrina
AU  - Romano S
AD  - Dipartimento di Neuroscienze, Sezione di Fisica, Universita Cattolica del Sacro 
      Cuore, 00168 Rome, Italy.
FAU - Di Giacinto, Flavio
AU  - Di Giacinto F
AD  - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
AD  - Dipartimento di Neuroscienze, Sezione di Fisica, Universita Cattolica del Sacro 
      Cuore, 00168 Rome, Italy.
FAU - Papi, Massimiliano
AU  - Papi M
AUID- ORCID: 0000-0002-0029-1309
AD  - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
AD  - Dipartimento di Neuroscienze, Sezione di Fisica, Universita Cattolica del Sacro 
      Cuore, 00168 Rome, Italy.
FAU - Rapaccini, Gian Ludovico
AU  - Rapaccini GL
AD  - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
AD  - Sezione di Medicina Interna, Dipartimento di Medicina e Chirurgia Traslazionale, 
      Universita Cattolica del Sacro Cuore, 00168 Rome, Italy.
FAU - De Spirito, Marco
AU  - De Spirito M
AUID- ORCID: 0000-0003-4260-5107
AD  - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
AD  - Dipartimento di Neuroscienze, Sezione di Fisica, Universita Cattolica del Sacro 
      Cuore, 00168 Rome, Italy.
FAU - Miele, Luca
AU  - Miele L
AD  - Sezione di Medicina Interna, Dipartimento di Medicina e Chirurgia Traslazionale, 
      Universita Cattolica del Sacro Cuore, 00168 Rome, Italy.
FAU - Basile, Umberto
AU  - Basile U
AUID- ORCID: 0000-0002-8328-2570
AD  - Dipartimento di Scienze di Laboratorio e Infettivologiche, Fondazione Policlinico 
      Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
FAU - Ciasca, Gabriele
AU  - Ciasca G
AD  - Fondazione Policlinico Universitario "A. Gemelli" IRCCS, 00168 Rome, Italy.
AD  - Dipartimento di Neuroscienze, Sezione di Fisica, Universita Cattolica del Sacro 
      Cuore, 00168 Rome, Italy.
LA  - eng
GR  - GR-2016-02363310/Ministry of Health, Italy/
PT  - Journal Article
DEP - 20220610
PL  - Switzerland
TA  - J Pers Med
JT  - Journal of personalized medicine
JID - 101602269
PMC - PMC9224706
OTO - NOTNLM
OT  - FTIR
OT  - cancer
OT  - extracellular vesicles
OT  - hepatocellular carcinoma
OT  - liquid biopsy
COIS- The authors declare no conflict of interest.
EDAT- 2022/06/25 06:00
MHDA- 2022/06/25 06:01
PMCR- 2022/06/10
CRDT- 2022/06/24 01:26
PHST- 2022/05/12 00:00 [received]
PHST- 2022/06/01 00:00 [revised]
PHST- 2022/06/05 00:00 [accepted]
PHST- 2022/06/24 01:26 [entrez]
PHST- 2022/06/25 06:00 [pubmed]
PHST- 2022/06/25 06:01 [medline]
PHST- 2022/06/10 00:00 [pmc-release]
AID - jpm12060949 [pii]
AID - jpm-12-00949 [pii]
AID - 10.3390/jpm12060949 [doi]
PST - epublish
SO  - J Pers Med. 2022 Jun 10;12(6):949. doi: 10.3390/jpm12060949.