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Your search keyword '"Rosenberg, Arlene S."' showing total 16 results
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16 results on '"Rosenberg, Arlene S."'

4. Histopathology - guided mass spectrometry differentiates benign nevi from malignant melanoma

Author

Lazova, Rossitza, Smoot, Katy, Anderson, Heather, Powell, Matthew J., Rosenberg, Arlene S., Rongioletti, Franco, Pilloni, Luca, D'Hallewin, Sara, Gueorguieva, Ralitza, Tantcheva-Poor, Iliana, Obadofin, Omobolade, Camacho, Christine, Hsi, Andy, Kluger, Harriet H., Fadare, Oluwole, Seeley, Erin H., Lazova, Rossitza, Smoot, Katy, Anderson, Heather, Powell, Matthew J., Rosenberg, Arlene S., Rongioletti, Franco, Pilloni, Luca, D'Hallewin, Sara, Gueorguieva, Ralitza, Tantcheva-Poor, Iliana, Obadofin, Omobolade, Camacho, Christine, Hsi, Andy, Kluger, Harriet H., Fadare, Oluwole, and Seeley, Erin H.

Abstract

Purpose Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which would more reliably differentiate between benign and malignant melanocytic lesions. Methods We performed histolpathology - guided mass spectrometry (HGMS) profiling analysis on formalin-fixed, paraffin embedded tissue samples to identify differences at the proteomic level between different types of benign nevi and melanomas. A total of 756 cases, of which 357 cases of melanoma and 399 benign nevi, were included in the study. The specimens originated from both biopsies (376 samples) and tissue microarray (TMA) cores (380 samples). After obtaining mass spectra from each sample, classification models were built using a training set of biopsy specimens from 111 nevi and 100 melanomas. The classification algorithm developed on the training data set was validated on an independent set of 288 nevi and 257 melanomas from both biopsies and TMA cores. Results In the melanoma cohort, 239/257 (93%) cases classified correctly in the validation set, 3/257 (1.2%) classified incorrectly, and 15/257 (5.8%) classified as indeterminate. In the cohort of nevi, 282/288 (98%) cases classified correctly, 1/288 (0.3%) classified incorrectly, and 5/288 (1.7%) were indeterminate. HGMS showed a sensitivity of 98.76% and specificity of 99.65% in determining benign vs malignant. Conclusion HGMS proteomic analysis is an objective and reliable test with minimal tissue requirements, which can be a helpful ancillary test in the diagnosis of challenging melanocytic lesions.

Published
2020

9. Histopathology‐guided mass spectrometry differentiates benign nevi from malignant melanoma

Author

Lazova, Rossitza, primary, Smoot, Katy, additional, Anderson, Heather, additional, Powell, Matthew J., additional, Rosenberg, Arlene S., additional, Rongioletti, Franco, additional, Pilloni, Luca, additional, D'Hallewin, Sara, additional, Gueorguieva, Ralitza, additional, Tantcheva‐Poór, Iliana, additional, Obadofin, Omobolade, additional, Camacho, Christine, additional, Hsi, Andy, additional, Kluger, Harriet H., additional, Fadare, Oluwole, additional, and Seeley, Erin H., additional

Published
2019
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10. Imaging mass spectrometry assists in the classification of diagnostically challenging atypical Spitzoid neoplasms

Author

Lazova, Rossitza, primary, Seeley, Erin H., additional, Kutzner, Heinz, additional, Scolyer, Richard A., additional, Scott, Glynis, additional, Cerroni, Lorenzo, additional, Fried, Isabella, additional, Kozovska, Milena E., additional, Rosenberg, Arlene S., additional, Prieto, Victor G., additional, Shehata, Bahig M., additional, Durham, Megan M., additional, Henry, Gina, additional, Rodriguez-Peralto, Jose L., additional, Riveiro-Falkenbach, Erica, additional, Schaefer, Jochen T., additional, Danialan, Richard, additional, Fraitag, Sylvie, additional, Vollenweider-Roten, Sonja, additional, Sepehr, Alireza, additional, Sangueza, Martin, additional, Hijazi, Nouf, additional, Corredoira, Yamile, additional, Kowal, Rachel, additional, Harris, Olga M., additional, Bravo, Francisco, additional, Boyd, Alan S., additional, Gueorguieva, Ralitza, additional, and Caprioli, Richard M., additional

Published
2016
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12. Trichodysplasia spinulosa is characterized by active polyomavirus infection

Author

Kazem, Siamaque, primary, van der Meijden, Els, additional, Kooijman, Sander, additional, Rosenberg, Arlene S., additional, Hughey, Lauren C., additional, Browning, John C., additional, Sadler, Genevieve, additional, Busam, Klaus, additional, Pope, Elena, additional, Benoit, Taylor, additional, Fleckman, Philip, additional, de Vries, Esther, additional, Eekhof, Just A., additional, and Feltkamp, Mariet C.W., additional

Published
2012
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16. Histopathology-guided mass spectrometry differentiates benign nevi from malignant melanoma.

Author

Lazova R, Smoot K, Anderson H, Powell MJ, Rosenberg AS, Rongioletti F, Pilloni L, D'Hallewin S, Gueorguieva R, Tantcheva-Poór I, Obadofin O, Camacho C, Hsi A, Kluger HH, Fadare O, and Seeley EH

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Diagnosis, Differential, Female, Humans, Male, Middle Aged, Proteomics methods, Young Adult, Melanoma, Cutaneous Malignant, Machine Learning, Mass Spectrometry methods, Melanoma diagnosis, Nevus diagnosis, Skin Neoplasms diagnosis
Abstract

Purpose: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which would more reliably differentiate between benign and malignant melanocytic lesions., Methods: We performed histolpathology - guided mass spectrometry (HGMS) profiling analysis on formalin-fixed, paraffin embedded tissue samples to identify differences at the proteomic level between different types of benign nevi and melanomas. A total of 756 cases, of which 357 cases of melanoma and 399 benign nevi, were included in the study. The specimens originated from both biopsies (376 samples) and tissue microarray (TMA) cores (380 samples). After obtaining mass spectra from each sample, classification models were built using a training set of biopsy specimens from 111 nevi and 100 melanomas. The classification algorithm developed on the training data set was validated on an independent set of 288 nevi and 257 melanomas from both biopsies and TMA cores., Results: In the melanoma cohort, 239/257 (93%) cases classified correctly in the validation set, 3/257 (1.2%) classified incorrectly, and 15/257 (5.8%) classified as indeterminate. In the cohort of nevi, 282/288 (98%) cases classified correctly, 1/288 (0.3%) classified incorrectly, and 5/288 (1.7%) were indeterminate. HGMS showed a sensitivity of 98.76% and specificity of 99.65% in determining benign vs malignant., Conclusion: HGMS proteomic analysis is an objective and reliable test with minimal tissue requirements, which can be a helpful ancillary test in the diagnosis of challenging melanocytic lesions., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Published
2020
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