| Title | Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer. |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Authors | Petralia F, Tignor N, Reva B, Koptyra M, Chowdhury S, Rykunov D, Krek A, Ma W, Zhu Y, Ji J, Calinawan A, Whiteaker JR, Colaprico A, Stathias V, Omelchenko T, Song X, Raman P, Guo Y, Brown MA, Ivey RG, Szpyt J, Thakurta SGuha, Gritsenko MA, Weitz KK, Lopez G, Kalayci S, Gümüş ZH, Yoo S, Leprevost Fda Veiga, Chang H-Y, Krug K, Katsnelson L, Wang Y, Kennedy JJ, Voytovich UJ, Zhao L, Gaonkar KS, Ennis BM, Zhang B, Baubet V, Tauhid L, Lilly JV, Mason JL, Farrow B, Young N, Leary S, Moon J, Petyuk VA, Nazarian J, Adappa ND, Palmer JN, Lober RM, Rivero-Hinojosa S, Wang L-B, Wang JM, Broberg M, Chu RK, Moore RJ, Monroe ME, Zhao R, Smith RD, Zhu J, Robles AI, Mesri M, Boja E, Hiltke T, Rodriguez H, Zhang B, Schadt EE, Mani DR, Ding L, Iavarone A, Wiznerowicz M, Schürer S, Chen XS, Heath AP, Rokita JLynne, Nesvizhskii AI, Fenyö D, Rodland KD, Liu T, Gygi SP, Paulovich AG, Resnick AC, Storm PB, Rood BR, Wang P |
| Corporate Authors | Children’s Brain Tumor Network, Clinical Proteomic Tumor Analysis Consortium |
| Journal | Cell |
| Volume | 183 |
| Issue | 7 |
| Pagination | 1962-1985.e31 |
| Date Published | 2020 Dec 23 |
| ISSN | 1097-4172 |
| Abstract | We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection. |
| DOI | 10.1016/j.cell.2020.10.044 |
| Alternate Journal | Cell |
| PubMed ID | 33242424 |
| Grant List | R01 NS091620 / NS / NINDS NIH HHS / United States U2C HL138346 / HL / NHLBI NIH HHS / United States R50 CA211499 / CA / NCI NIH HHS / United States R01 NS085336 / NS / NINDS NIH HHS / United States U01 CA214114 / CA / NCI NIH HHS / United States |