Chiara Fania1, Ilaria Sogno2, Michele Vasso3, Enrica Torretta4, Roberta Leone5, Antonino Bruno6, Paolo Consonni7, Adriana Albini8, Cecilia Gelfi9. 1. Dipartimento di Scienze Biomediche per la Salute, Università degli Studi Di Milano, Via F.lli Cervi 93, Segrate, Milan 20090, Italy; IRCCS Policlinico San Donato, Piazza Edmondo Malan, San Donato Milanese, Milan 20097, Italy. Electronic address: chiara.fania@unimi.it. 2. Istituto di Ricovero e Cura a Carattere Scientifico MultiMedica, via Fantoli 16/15, Milan 20138, Italy. Electronic address: i.sogno@libero.it. 3. Istituto di Bioimmagini e Fisiologia Molecolare (IBFM)-CNR, C.da Pietrapollastra-Pisciotto, Cefalù, Palermo 90015, Italy. Electronic address: michele.vasso@ibfm.cnr.it. 4. Dipartimento di Scienze Biomediche per la Salute, Università degli Studi Di Milano, Via F.lli Cervi 93, Segrate, Milan 20090, Italy; IRCCS Policlinico San Donato, Piazza Edmondo Malan, San Donato Milanese, Milan 20097, Italy. Electronic address: enrica.torretta@unimi.it. 5. Dipartimento di Scienze Biomediche per la Salute, Università degli Studi Di Milano, Via F.lli Cervi 93, Segrate, Milan 20090, Italy. Electronic address: roberta.leone@unimi.it. 6. Istituto di Ricovero e Cura a Carattere Scientifico MultiMedica, via Fantoli 16/15, Milan 20138, Italy. Electronic address: 82antonino.bruno@gmail.com. 7. Istituto di Ricovero e Cura a Carattere Scientifico MultiMedica, via Fantoli 16/15, Milan 20138, Italy. Electronic address: paolo.consonni@multimedica.it. 8. IRCCS Tecnologie Avanzate e Modelli Assistenziali in Oncologia - Arcispedale Santa Maria Nuova, Viale Umberto I 50, Reggio Emilia 42123, Italy. Electronic address: adriana.albini@multimedica.it. 9. Dipartimento di Scienze Biomediche per la Salute, Università degli Studi Di Milano, Via F.lli Cervi 93, Segrate, Milan 20090, Italy; IRCCS Policlinico San Donato, Piazza Edmondo Malan, San Donato Milanese, Milan 20097, Italy; Istituto di Bioimmagini e Fisiologia Molecolare (IBFM)-CNR, Via F.lli Cervi 93, Segrate, Milan 20090, Italy. Electronic address: cecilia.gelfi@unimi.it.
Abstract
BACKGROUND: Prostate cancer (PCa) is the second cause of mortality in men worldwide. The prostate-specific antigen (PSA) test is routinely adopted in diagnosis; nevertheless more reliable biomarkers are continuously under investigation by monitoring the release of molecules into the bloodstream. The serum protein profiles appear to provide cancer-specific fingerprints that help to discriminate patients (especially with low PSA level) from controls, improving the performance of existing clinical tests. METHODS: Samples from healthy controls and PCa patients with low (≤4 ng/mL) and high PSA (>4 ng/mL) levels were analyzed by MALDI profiling, and by a multi fractionation approach coupled to ESI-MS for peaks identification. RESULTS: MALDI profiling achieved to detect 10 and 14 changed peaks (p-value <0.05), respectively, in PCa patients with low and high PSA versus controls. In particular, a peak identified as C3f fragment, resulted overexpressed in low PSA PCa patients. CONCLUSIONS: PSA test, coupled to MALDI profiling, is able to detect changes, specifically related to PCa, in low molecular weight protein range. Furthermore, for the first time in prostate cancer research, the identification and quantification of the small peptide C3f appears to be relevant for the detection of false negatives, providing an additive diagnostic power to PSA (p<0.01) and suggesting its use in clinical tests.
BACKGROUND:Prostate cancer (PCa) is the second cause of mortality in men worldwide. The prostate-specific antigen (PSA) test is routinely adopted in diagnosis; nevertheless more reliable biomarkers are continuously under investigation by monitoring the release of molecules into the bloodstream. The serum protein profiles appear to provide cancer-specific fingerprints that help to discriminate patients (especially with low PSA level) from controls, improving the performance of existing clinical tests. METHODS: Samples from healthy controls and PCa patients with low (≤4 ng/mL) and high PSA (>4 ng/mL) levels were analyzed by MALDI profiling, and by a multi fractionation approach coupled to ESI-MS for peaks identification. RESULTS: MALDI profiling achieved to detect 10 and 14 changed peaks (p-value <0.05), respectively, in PCa patients with low and high PSA versus controls. In particular, a peak identified as C3f fragment, resulted overexpressed in low PSA PCa patients. CONCLUSIONS: PSA test, coupled to MALDI profiling, is able to detect changes, specifically related to PCa, in low molecular weight protein range. Furthermore, for the first time in prostate cancer research, the identification and quantification of the small peptide C3f appears to be relevant for the detection of false negatives, providing an additive diagnostic power to PSA (p<0.01) and suggesting its use in clinical tests.
Authors: Adriana Albini; Antonino Bruno; Barbara Bassani; Gioacchino D'Ambrosio; Giuseppe Pelosi; Paolo Consonni; Laura Castellani; Matteo Conti; Simone Cristoni; Douglas M Noonan Journal: Front Endocrinol (Lausanne) Date: 2018-04-05 Impact factor: 5.555