Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

Carolina Moretto Carnielli; Carolina Carneiro Soares Macedo; Tatiane De Rossi; Daniela Campos Granato; César Rivera; Romênia Ramos Domingues; Bianca Alves Pauletti; Sami Yokoo; Henry Heberle; Ariane Fidelis Busso-Lopes; Nilva Karla Cervigne; Iris Sawazaki-Calone; Gabriela Vaz Meirelles; Fábio Albuquerque Marchi; Guilherme Pimentel Telles; Rosane Minghim; Ana Carolina Prado Ribeiro; Thaís Bianca Brandão; Gilberto de Castro; Wilfredo Alejandro González-Arriagada; Alexandre Gomes; Fabio Penteado; Alan Roger Santos-Silva; Márcio Ajudarte Lopes; Priscila Campioni Rodrigues; Elias Sundquist; Tuula Salo; Sabrina Daniela da Silva; Moulay A. Alaoui-Jamali; Edgard Graner; Jay W. Fox; Ricardo Della Coletta; Adriana Franco Paes Leme

doi:10.1038/s41467-018-05696-2

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

Carolina Moretto Carnielli, Carolina Carneiro Soares Macedo, Tatiane De Rossi, Daniela Campos Granato, César Rivera, Romênia Ramos Domingues, Bianca Alves Pauletti, Sami Yokoo, Henry Heberle, Ariane Fidelis Busso-Lopes, Nilva Karla Cervigne, Iris Sawazaki-Calone, Gabriela Vaz Meirelles, Fábio Albuquerque Marchi, Guilherme Pimentel Telles, Rosane Minghim, Ana Carolina Prado Ribeiro, Thaís Bianca Brandão, Gilberto de Castro, Wilfredo Alejandro González-ArriagadaAlexandre Gomes, Fabio Penteado, Alan Roger Santos-Silva, Márcio Ajudarte Lopes, Priscila Campioni Rodrigues, Elias Sundquist, Tuula Salo, Sabrina Daniela da Silva, Moulay A. Alaoui-Jamali, Edgard Graner, Jay W. Fox, Ricardo Della Coletta, Adriana Franco Paes Leme^*

^*Autor correspondiente de este trabajo

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

142 Citas (Scopus)

Resumen

Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor−node−metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.

Idioma original	Inglés
Número de artículo	3598
Páginas (desde-hasta)	1-17
Número de páginas	17
Publicación	Nature Communications
Volumen	9
N.º	1
DOI	https://doi.org/10.1038/s41467-018-05696-2
Estado	Publicada - 1 dic. 2018
Publicado de forma externa	Sí

Nota bibliográfica

Funding Information:
This work was supported by FAPESP Grants 2009/54067-3, 2010/19278-0, 2013/16483-0, 2014/02288-0, 2016/07846-0, CNPq Grants 152619/2015-1, 470268/2013-1, 305432/ 2014-1. We acknowledge Prof. Dr. Tsai Siu Mui, CENA, USP for the use of the Leica Laser Microdissection Systems (FAPESP 2009/53998-3). We acknowledge Prof. Dr. Débora Lima Pereira for the assistance in histopathological images. We thank Dr. Ana Karina de Oliveira and Jamile de Oliveira Sá for all the assistance in primary cell culture experiments.

Publisher Copyright:
© 2018, The Author(s).

Palabras clave

Biomarkers, Tumor
Carcinoma, Squamous Cell
Clinical Decision-Making
Female
Follow-Up Studies
Humans
Immunohistochemistry
Lymphatic Metastasis
Machine Learning
Male
Middle Aged
Mouth Neoplasms
Neoplasm Recurrence, Local
Peptides
Predictive Value of Tests
Prognosis
Proteomics
Retrospective Studies
Saliva
Survival Rate

ODS de las Naciones Unidas

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Carnielli, C. M., Macedo, C. C. S., De Rossi, T., Granato, D. C., Rivera, C., Domingues, R. R., Pauletti, B. A., Yokoo, S., Heberle, H., Busso-Lopes, A. F., Cervigne, N. K., Sawazaki-Calone, I., Meirelles, G. V., Marchi, F. A., Telles, G. P., Minghim, R., Ribeiro, A. C. P., Brandão, T. B., de Castro, G., ... Paes Leme, A. F. (2018). Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer. Nature Communications, 9(1), 1-17. Artículo 3598. https://doi.org/10.1038/s41467-018-05696-2

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title = "Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer",

abstract = "Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor−node−metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.",

keywords = "Biomarkers, Tumor, Carcinoma, Squamous Cell, Clinical Decision-Making, Female, Follow-Up Studies, Humans, Immunohistochemistry, Lymphatic Metastasis, Machine Learning, Male, Middle Aged, Mouth Neoplasms, Neoplasm Recurrence, Local, Peptides, Predictive Value of Tests, Prognosis, Proteomics, Retrospective Studies, Saliva, Survival Rate",

author = "Carnielli, {Carolina Moretto} and Macedo, {Carolina Carneiro Soares} and {De Rossi}, Tatiane and Granato, {Daniela Campos} and C{\'e}sar Rivera and Domingues, {Rom{\^e}nia Ramos} and Pauletti, {Bianca Alves} and Sami Yokoo and Henry Heberle and Busso-Lopes, {Ariane Fidelis} and Cervigne, {Nilva Karla} and Iris Sawazaki-Calone and Meirelles, {Gabriela Vaz} and Marchi, {F{\'a}bio Albuquerque} and Telles, {Guilherme Pimentel} and Rosane Minghim and Ribeiro, {Ana Carolina Prado} and Brand{\~a}o, {Tha{\'i}s Bianca} and {de Castro}, Gilberto and Gonz{\'a}lez-Arriagada, {Wilfredo Alejandro} and Alexandre Gomes and Fabio Penteado and Santos-Silva, {Alan Roger} and Lopes, {M{\'a}rcio Ajudarte} and Rodrigues, {Priscila Campioni} and Elias Sundquist and Tuula Salo and {da Silva}, {Sabrina Daniela} and Alaoui-Jamali, {Moulay A.} and Edgard Graner and Fox, {Jay W.} and Coletta, {Ricardo Della} and {Paes Leme}, {Adriana Franco}",

note = "Publisher Copyright: {\textcopyright} 2018, The Author(s).",

year = "2018",

month = dec,

day = "1",

doi = "10.1038/s41467-018-05696-2",

language = "English",

volume = "9",

pages = "1--17",

journal = "Nature Communications",

issn = "2041-1723",

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Carnielli, CM, Macedo, CCS, De Rossi, T, Granato, DC, Rivera, C, Domingues, RR, Pauletti, BA, Yokoo, S, Heberle, H, Busso-Lopes, AF, Cervigne, NK, Sawazaki-Calone, I, Meirelles, GV, Marchi, FA, Telles, GP, Minghim, R, Ribeiro, ACP, Brandão, TB, de Castro, G, González-Arriagada, WA, Gomes, A, Penteado, F, Santos-Silva, AR, Lopes, MA, Rodrigues, PC, Sundquist, E, Salo, T, da Silva, SD, Alaoui-Jamali, MA, Graner, E, Fox, JW, Coletta, RD & Paes Leme, AF 2018, 'Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer', Nature Communications, vol. 9, n.º 1, 3598, pp. 1-17. https://doi.org/10.1038/s41467-018-05696-2

TY - JOUR

T1 - Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

AU - Carnielli, Carolina Moretto

AU - Macedo, Carolina Carneiro Soares

AU - De Rossi, Tatiane

AU - Granato, Daniela Campos

AU - Rivera, César

AU - Domingues, Romênia Ramos

AU - Pauletti, Bianca Alves

AU - Yokoo, Sami

AU - Heberle, Henry

AU - Busso-Lopes, Ariane Fidelis

AU - Cervigne, Nilva Karla

AU - Sawazaki-Calone, Iris

AU - Meirelles, Gabriela Vaz

AU - Marchi, Fábio Albuquerque

AU - Telles, Guilherme Pimentel

AU - Minghim, Rosane

AU - Ribeiro, Ana Carolina Prado

AU - Brandão, Thaís Bianca

AU - de Castro, Gilberto

AU - González-Arriagada, Wilfredo Alejandro

AU - Gomes, Alexandre

AU - Penteado, Fabio

AU - Santos-Silva, Alan Roger

AU - Lopes, Márcio Ajudarte

AU - Rodrigues, Priscila Campioni

AU - Sundquist, Elias

AU - Salo, Tuula

AU - da Silva, Sabrina Daniela

AU - Alaoui-Jamali, Moulay A.

AU - Graner, Edgard

AU - Fox, Jay W.

AU - Coletta, Ricardo Della

AU - Paes Leme, Adriana Franco

PY - 2018/12/1

Y1 - 2018/12/1

N2 - Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor−node−metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.

AB - Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics limiting the standard tumor−node−metastasis prognosis classification. Therefore, defining biological signatures that allow assessing the prognostic outcomes for OSCC patients would be of great clinical significance. Using histopathology-guided discovery proteomics, we analyze neoplastic islands and stroma from the invasive tumor front (ITF) and inner tumor to identify differentially expressed proteins. Potential signature proteins are prioritized and further investigated by immunohistochemistry (IHC) and targeted proteomics. IHC indicates low expression of cystatin-B in neoplastic islands from the ITF as an independent marker for local recurrence. Targeted proteomics analysis of the prioritized proteins in saliva, combined with machine-learning methods, highlights a peptide-based signature as the most powerful predictor to distinguish patients with and without lymph node metastasis. In summary, we identify a robust signature, which may enhance prognostic decisions in OSCC and better guide treatment to reduce tumor recurrence or lymph node metastasis.

KW - Biomarkers, Tumor

KW - Carcinoma, Squamous Cell

KW - Clinical Decision-Making

KW - Female

KW - Follow-Up Studies

KW - Humans

KW - Immunohistochemistry

KW - Lymphatic Metastasis

KW - Machine Learning

KW - Male

KW - Middle Aged

KW - Mouth Neoplasms

KW - Neoplasm Recurrence, Local

KW - Peptides

KW - Predictive Value of Tests

KW - Prognosis

KW - Proteomics

KW - Retrospective Studies

KW - Saliva

KW - Survival Rate

UR - http://www.scopus.com/inward/record.url?scp=85053009368&partnerID=8YFLogxK

U2 - 10.1038/s41467-018-05696-2

DO - 10.1038/s41467-018-05696-2

M3 - Article

C2 - 30185791

AN - SCOPUS:85053009368

SN - 2041-1723

VL - 9

SP - 1

EP - 17

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 3598

ER -

Combining discovery and targeted proteomics reveals a prognostic signature in oral cancer

Resumen

Nota bibliográfica

Palabras clave

ODS de las Naciones Unidas

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