Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

Petralia, Francesca; Tignor, Nicole; Reva, Boris; Koptyra, Mateusz; Chowdhury, Shrabanti; Rykunov, Dmitry; Krek, Azra; Ma, Wanli; Zhu, Yuankun; Ji, Jiayi; Calinawan, Anna; Whiteaker, Jeffrey R.; Colaprico, Antonio; Stathias, Vasileios; Omelchenko, Tatiana; Song, Xiaoyu; Raman, Pichai; Guo, Yiran; Brown, Miguel; Ivey, Richard G.; Szpyt, John; Thakurta, Sanjukta Guha; Gritsenko, Marina; Weitz, Karl K.; López, Gonzalo; Kalayci, Selim; Gümüş, Zeynep H.; Yoo, Seungyeul; Leprevost, Felipe da Veiga; Chang, Hui-Yin; Krug, Karsten; Katsnelson, Lizabeth; Wang, Ying; Kennedy, Jacob J.; Voytovich, Uliana J.; Zhao, Lei; Gaonkar, Krutika S.; Ennis, Brian; Zhang, Bo; Baubet, Valérie; Tauhid, Lamiya; Lilly, Jena; Mason, J. L.; Farrow, Bailey; Young, Nathan; Leary, Sarah; Moon, Jamie; Petyuk, Vladislav; Nazarian, Javad; Adappa, Nithin D.; Palmer, James N.; Lober, Robert M.; Rivero-Hinojosa, Samuel; Wang, Liang-Bo; Wang, Joshua M.; Broberg, Matilda; Chu, Rosalie K.; Moore, Ronald J.; Monroe, Matthew E.; Zhao, Rui; Smith, Richard; Zhu, Jun; Robles, Ana I.; Mesri, Mehdi; Boja, Emily S.; Hiltke, Tara; Rodriguez, Henry; Zhang, Bing; Schadt, Eric E.; Mani, D. R.; Li, Ding; Iavarone, Antonio; Wiznerowicz, Maciej; Schürer, Stephan C.; Chen, Xi S.; Heath, Allison P.; Rokita, Jo Lynne; Nesvizhskii, Alexey I.; Fenyö, David; Rodland, Karin D.; Liu, Tao; Gygi, Steven P.; Paulovich, Amanda G.; Resnick, Adam; Storm, Phillip B.; Rood, Brian R.; Wang, Pei; Francis, Alicia; Morgan, Allison M.; Waanders, Angela J.; Viaene, Angela N.; Buccoliero, Anna Maria; Chinnaiyan, Arul M.; Leonard, Carina A.; Kline, Cassie; Caporalini, Chiara; Kinsinger, Christopher R.; Li, Chunde; Kram, David E.; Hanson, Derek; Appert, Elizabeth; Kawaler, Emily; Raabe, Eric H.; Jackson, Eric M.; Greenfield, Jeffrey P.; Stone, Gabrielle S.; Getz, Gad; Grant, Gerald A.; Teo, Guo Ci; Pollack, Ian F.; Cain, Jason; Foster, Jessica; Phillips, Joanna J.; Palma, July E.; Ketchum, Karen A.; Ruggles, Kelly V.; Blumenberg, Lili M.; Cornwell, MacIntosh; Sarmady, Mahdi; Domagalski, Marcin J.; Cieślik, Marcin; Santi, Mariarita; Li, Marilyn M.; Ellis, Matthew J.; Wyczalkowski, Matthew A.; Connors, Meghan; Scagnet, Mirko; Gupta, Nalin; Edwards, Nathan; Vitanza, Nicholas A.; Vaske, Olena M.; Becher, Oren J.; McGarvey, Peter B.; Firestein, Ron; Mueller, Sabine; Winebrake, Samuel G.; Dhanasekaran, Saravana M.; Cai, Shuang; Partap, Sonia; Patton, Tatiana; Le, Toan; Lorentzen, Travis D.; Liu, Wenke; Bocik, William

doi:10.1016/j.cell.2020.10.044

Cited by 226 publications

(202 citation statements)

References 211 publications

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“…It has been shown that the plasma level of metabolites of interest can help to define the grading of brain glioma and to provide prognostic information in patients with a similar glioma grade [ 87 ]. Nevertheless, data are still rare for these emerging approaches; however, the promise of precision medicine and the surge of multimodal data-driven strategies can provide valuable tools for the development of biomarkers and innovative therapies in glioblastomas [ 88 ].…”

Section: Resultsmentioning

confidence: 99%

Diagnosis and Management of Glioblastoma: A Comprehensive Perspective

Gilard

Tebani

Dabaj

et al. 2021

JPM

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Glioblastoma is the most common malignant brain tumor in adults. The current management relies on surgical resection and adjuvant radiotherapy and chemotherapy. Despite advances in our understanding of glioblastoma onset, we are still faced with an increased incidence, an altered quality of life and a poor prognosis, its relapse and a median overall survival of 15 months. For the past few years, the understanding of glioblastoma physiopathology has experienced an exponential acceleration and yielded significant insights and new treatments perspectives. In this review, through an original R-based literature analysis, we summarize the clinical presentation, current standards of care and outcomes in patients diagnosed with glioblastoma. We also present the recent advances and perspectives regarding pathophysiological bases as well as new therapeutic approaches such as cancer vaccination and personalized treatments.

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Section: Resultsmentioning

confidence: 99%

Diagnosis and Management of Glioblastoma: A Comprehensive Perspective

Gilard

Tebani

Dabaj

et al. 2021

JPM

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“…The loss of correlation between RNA and protein highlights the need for protein evidence-based investigations, for example pediatric cancer subtypes were identified based on only proteome data (Petralia et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Deep Proteome Profiling of Human Mammary Epithelia at Lineage and Age Resolution

Hinz¹,

Manousopoulou

Miyano³

et al. 2021

Preprint

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Age is the major risk factor in most carcinomas, yet little is known about how proteomes change with age in any human epithelium. We present comprehensive proteomes comprised of >9,000 total proteins, and >15,000 phosphopeptides, from normal primary human mammary epithelia at lineage resolution from ten women ranging in age from 19 to 68. Data were quality controlled, and results were biologically validated with cell-based assays. Age-dependent protein signatures were identified using differential expression analyses and weighted protein co-expression network analyses. Up-regulation of basal markers in luminal cells, including KRT14 and AXL, were a prominent consequence of aging. PEAK1 was identified as an age-dependent signaling kinase in luminal cells, which revealed a potential age-dependent vulnerability for targeted ablation. Correlation analyses between transcriptome and proteome revealed age-associated loss of proteostasis regulation. Protein expression and phosphorylation changes in the aging breast epithelium identify potential therapeutic targets for reducing breast cancer susceptibility.

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“…Proteomics and metabolomics are areas with opportunities for expanded understanding of gliomas. Nevertheless, inter-and intra-tumor differences in proteome profile have been reported in small series of adult patients [102][103][104], and in pediatric neuro-oncology [105]. Multi-institutional studies in adult populations are needed, aiming to identify molecular targets not observed from RNAseq data, as gene expression data often does not correlate highly to changes in proteomic expression.…”

Section: Future Directionsmentioning

confidence: 99%

Tumor Heterogeneity in Glioblastomas: From Light Microscopy to Molecular Pathology

Becker

Sells

Haque

et al. 2021

Cancers

117

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One of the main reasons for the aggressive behavior of glioblastoma (GBM) is its intrinsic intra-tumor heterogeneity, characterized by the presence of clonal and subclonal differentiated tumor cell populations, glioma stem cells, and components of the tumor microenvironment, which affect multiple hallmark cellular functions in cancer. “Tumor Heterogeneity” usually encompasses both inter-tumor heterogeneity (population-level differences); and intra-tumor heterogeneity (differences within individual tumors). Tumor heterogeneity may be assessed in a single time point (spatial heterogeneity) or along the clinical evolution of GBM (longitudinal heterogeneity). Molecular methods may detect clonal and subclonal alterations to describe tumor evolution, even when samples from multiple areas are collected in the same time point (spatial-temporal heterogeneity). In GBM, although the inter-tumor mutational landscape is relatively homogeneous, intra-tumor heterogeneity is a striking feature of this tumor. In this review, we will address briefly the inter-tumor heterogeneity of the CNS tumors that yielded the current glioma classification. Next, we will take a deeper dive in the intra-tumor heterogeneity of GBMs, which directly affects prognosis and response to treatment. Our approach aims to follow technological developments, allowing for characterization of intra-tumor heterogeneity, beginning with differences on histomorphology of GBM and ending with molecular alterations observed at single-cell level.

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Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

Cited by 226 publications

References 211 publications

Diagnosis and Management of Glioblastoma: A Comprehensive Perspective

Diagnosis and Management of Glioblastoma: A Comprehensive Perspective

Deep Proteome Profiling of Human Mammary Epithelia at Lineage and Age Resolution

Tumor Heterogeneity in Glioblastomas: From Light Microscopy to Molecular Pathology

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