Multicenter Study Using Desorption-Electrospray-Ionization-Mass-Spectrometry Imaging for Breast-Cancer Diagnosis

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Porcari, Andreia M. ^{[1, 2]} ; Zhang, Jialing ^[3] ; Garza, Kyana Y. ^[3] ; Rodrigues-Peres, Raquel M. ^[4] ; Lin, John Q. ^[3] ; Young, Jonathan H. ^[3] ; Tibshirani, Robert ^{[5, 6]} ; Nagi, Chandandeep ^[7] ; Paiva, Geisilene R. ^[4] ; Carter, Stacey A. ^[8] ; Sarian, Luis Otavio ^[4] ; Eberlin, Marcos N. ^{[9, 1]} ; Eberlin, Livia S. ^[3]

Afiliação do(s) autor(es)

^[1] Univ Campinas UNICAMP, Dept Chem, Thomson Mass Spectrometry Lab, BR-13083970 Campinas, SP - Brazil

^[2] Sao Francisco Univ, Lab Multidisciplinary Res, BR-12916900 Braganca Paulista, SP - Brazil

^[3] Univ Texas Austin, Dept Chem, Austin, TX 78712 - USA

^[4] Univ Estadual Campinas, CAISM Womens Hosp, Fac Med Sci, Dept Gynecol & Breast Oncol, BR-13083881 Campinas, SP - Brazil

^[5] Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 - USA

^[6] Stanford Univ, Dept Stat, Stanford, CA 94305 - USA

^[7] Baylor Coll Med, Dept Pathol & Immunol, Houston, TX 77030 - USA

^[8] Baylor Coll Med, Dept Surg, Houston, TX 77030 - USA

^[9] Mackenzie Presbiterian Univ, Sch Engn, BR-01302907 Sao Paulo, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Analytical Chemistry; v. 90, n. 19, p. 11324-11332, OCT 2 2018.
• Citações Web of Science: 9

Resumo

The histological and molecular subtypes of breast cancer demand distinct therapeutic approaches. Invasive ductal carcinoma (IDC) is subtyped according to estrogen-receptor (ER), progesterone-receptor (PR), and HER2 status, among other markers. Desorption-electrospray-ionization-mass-spectrometry imaging (DESI-MSI) is an ambient-ionization MS technique that has been previously used to diagnose IDC. Aiming to investigate the robustness of ambient-ionization MS for IDC diagnosis and subtyping over diverse patient populations and interlaboratory use, we report a multicenter study using DESI-MSI to analyze samples from 103 patients independently analyzed in the United States and Brazil. The lipid profiles of IDC and normal breast tissues were consistent across different patient races and were unrelated to country of sample collection. Similar experimental parameters used in both laboratories yielded consistent mass-spectral data in mass-to-charge ratios (m/z) above 700, where complex lipids are observed. Statistical classifiers built using data acquired in the United States yielded 97.6% sensitivity, 96.7% specificity, and 97.6% accuracy for cancer diagnosis. Equivalent performance was observed for the intralaboratory validation set (99.2% accuracy) and, most remarkably, for the interlaboratory validation set independently acquired in Brazil (95.3% accuracy). Separate classification models built for ER and PR statuses as well as the status of their combined hormone receptor (HR) provided predictive accuracies (>89.0%), although low classification accuracies were achieved for HER2 status. Altogether, our multicenter study demonstrates that DESI-MSI is a robust and reproducible technology for rapid breast-cancer-tissue diagnosis and therefore is of value for clinical use. (AU)

• Processo FAPESP: 15/18830-5 - Comparação do perfil genômico e metabolômico de mulheres brasileiras e norte-americanas portadoras de câncer de mama
• Beneficiário: Raquel Mary Rodrigues Peres
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 13/25683-3 - Comparação do perfil genômico de mulheres brasileiras e norte-americanas portadoras de câncer de mama receptor de estrógeno positivo/HER2 negativo
• Beneficiário: Luís Otávio Zanatta Sarian
• Modalidade de apoio: Auxílio à Pesquisa - Regular