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The making of the glioblastoma classification.

British journal of cancer

Lasorella A, Iavarone A.
PMID: 33767415
Br J Cancer. 2021 Jul;125(1):4-6. doi: 10.1038/s41416-021-01360-7. Epub 2021 Mar 25.

Classification of cancer should lead to informative patients' stratification and selective therapeutic vulnerabilities. A pathway-based classification of glioblastoma uncovered a mitochondrial subtype with a unique sensitivity to inhibitors of oxidative phosphorylation. Precision targeting of cancer metabolism could provide therapeutic...

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Lasorella A, Iavarone A. The making of the glioblastoma classification. Br J Cancer. 2021;125(1):4-6doi: 10.1038/s41416-021-01360-7.
Lasorella, A., & Iavarone, A. (2021). The making of the glioblastoma classification. British journal of cancer, 125(1), 4-6. https://doi.org/10.1038/s41416-021-01360-7
Lasorella, Anna, and Iavarone, Antonio. "The making of the glioblastoma classification." British journal of cancer vol. 125,1 (2021): 4-6. doi: https://doi.org/10.1038/s41416-021-01360-7
Lasorella A, Iavarone A. The making of the glioblastoma classification. Br J Cancer. 2021 Jul;125(1):4-6. doi: 10.1038/s41416-021-01360-7. Epub 2021 Mar 25. PMID: 33767415; PMCID: PMC8257735.
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A Random Matrix Theory Approach to Denoise Single-Cell Data.

Patterns (New York, N.Y.)

Aparicio L, Bordyuh M, Blumberg AJ, Rabadan R.
PMID: 33205104
Patterns (N Y). 2020 May 04;1(3):100035. doi: 10.1016/j.patter.2020.100035. eCollection 2020 Jun 12.

Single-cell technologies provide the opportunity to identify new cellular states. However, a major obstacle to the identification of biological signals is noise in single-cell data. In addition, single-cell data are very sparse. We propose a new method based on...

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Aparicio L, Bordyuh M, Blumberg AJ, et al. A Random Matrix Theory Approach to Denoise Single-Cell Data. Patterns (N Y). 2020;1(3):100035doi: 10.1016/j.patter.2020.100035.
Aparicio, L., Bordyuh, M., Blumberg, A. J., & Rabadan, R. (2020). A Random Matrix Theory Approach to Denoise Single-Cell Data. Patterns (New York, N.Y.), 1(3), 100035. https://doi.org/10.1016/j.patter.2020.100035
Aparicio, Luis, et al. "A Random Matrix Theory Approach to Denoise Single-Cell Data." Patterns (New York, N.Y.) vol. 1,3 (2020): 100035. doi: https://doi.org/10.1016/j.patter.2020.100035
Aparicio L, Bordyuh M, Blumberg AJ, Rabadan R. A Random Matrix Theory Approach to Denoise Single-Cell Data. Patterns (N Y). 2020 May 04;1(3):100035. doi: 10.1016/j.patter.2020.100035. eCollection 2020 Jun 12. PMID: 33205104; PMCID: PMC7660363.
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Mutational and functional genetics mapping of chemotherapy resistance mechanisms in relapsed acute lymphoblastic leukemia.

Nature cancer

Oshima K, Zhao J, Pérez-Durán P, Brown JA, Patiño-Galindo JA, Chu T, Quinn A, Gunning T, Belver L, Ambesi-Impiombato A, Tosello V, Wang Z, Sulis ML, Kato M, Koh K, Paganin M, Basso G, Balbin M, Nicolas C, Gastier-Foster JM, Devidas M, Loh ML, Paietta E, Tallman MS, Rowe JM, Litzow M, Minden MD, Meijerink J, Rabadan R, Ferrando A.
PMID: 33796864
Nat Cancer. 2020 Nov;1(11):1113-1127. doi: 10.1038/s43018-020-00124-1. Epub 2020 Oct 19.

Multi-agent combination chemotherapy can be curative in acute lymphoblastic leukemia (ALL). Still, patients with primary refractory disease or with relapsed leukemia have a very poor prognosis. Here we integrate an in-depth dissection of the mutational landscape across diagnostic and...

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Oshima K, Zhao J, Pérez-Durán P, et al. Mutational and functional genetics mapping of chemotherapy resistance mechanisms in relapsed acute lymphoblastic leukemia. Nat Cancer. 2020;1(11):1113-1127doi: 10.1038/s43018-020-00124-1.
Oshima, K., Zhao, J., Pérez-Durán, P., Brown, J. A., Patiño-Galindo, J. A., Chu, T., Quinn, A., Gunning, T., Belver, L., Ambesi-Impiombato, A., Tosello, V., Wang, Z., Sulis, M. L., Kato, M., Koh, K., Paganin, M., Basso, G., Balbin, M., Nicolas, C., Gastier-Foster, J. M., Devidas, M., Loh, M. L., Paietta, E., Tallman, M. S., Rowe, J. M., Litzow, M., Minden, M. D., Meijerink, J., Rabadan, R., & Ferrando, A. (2020). Mutational and functional genetics mapping of chemotherapy resistance mechanisms in relapsed acute lymphoblastic leukemia. Nature cancer, 1(11), 1113-1127. https://doi.org/10.1038/s43018-020-00124-1
Oshima, Koichi, et al. "Mutational and functional genetics mapping of chemotherapy resistance mechanisms in relapsed acute lymphoblastic leukemia." Nature cancer vol. 1,11 (2020): 1113-1127. doi: https://doi.org/10.1038/s43018-020-00124-1
Oshima K, Zhao J, Pérez-Durán P, Brown JA, Patiño-Galindo JA, Chu T, Quinn A, Gunning T, Belver L, Ambesi-Impiombato A, Tosello V, Wang Z, Sulis ML, Kato M, Koh K, Paganin M, Basso G, Balbin M, Nicolas C, Gastier-Foster JM, Devidas M, Loh ML, Paietta E, Tallman MS, Rowe JM, Litzow M, Minden MD, Meijerink J, Rabadan R, Ferrando A. Mutational and functional genetics mapping of chemotherapy resistance mechanisms in relapsed acute lymphoblastic leukemia. Nat Cancer. 2020 Nov;1(11):1113-1127. doi: 10.1038/s43018-020-00124-1. Epub 2020 Oct 19. PMID: 33796864; PMCID: PMC8011577.
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On statistical modeling of sequencing noise in high depth data to assess tumor evolution.

Journal of statistical physics

Rabadan R, Bhanot G, Marsilio S, Chiorazzi N, Pasqualucci L, Khiabanian H.
PMID: 30034030
J Stat Phys. 2018 Jul;172(1):143-155. doi: 10.1007/s10955-017-1945-1. Epub 2017 Dec 21.

One cause of cancer mortality is tumor evolution to therapy-resistant disease. First line therapy often targets the dominant clone, and drug resistance can emerge from preexisting clones that gain fitness through therapy-induced natural selection. Such mutations may be identified...

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Rabadan R, Bhanot G, Marsilio S, et al. On statistical modeling of sequencing noise in high depth data to assess tumor evolution. J Stat Phys. 2017;172(1):143-155doi: 10.1007/s10955-017-1945-1.
Rabadan, R., Bhanot, G., Marsilio, S., Chiorazzi, N., Pasqualucci, L., & Khiabanian, H. (2018). On statistical modeling of sequencing noise in high depth data to assess tumor evolution. Journal of statistical physics, 172(1), 143-155. https://doi.org/10.1007/s10955-017-1945-1
Rabadan, Raul, et al. "On statistical modeling of sequencing noise in high depth data to assess tumor evolution." Journal of statistical physics vol. 172,1 (2018): 143-155. doi: https://doi.org/10.1007/s10955-017-1945-1
Rabadan R, Bhanot G, Marsilio S, Chiorazzi N, Pasqualucci L, Khiabanian H. On statistical modeling of sequencing noise in high depth data to assess tumor evolution. J Stat Phys. 2018 Jul;172(1):143-155. doi: 10.1007/s10955-017-1945-1. Epub 2017 Dec 21. PMID: 30034030; PMCID: PMC6051708.
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Computing the Role of Alternative Splicing in Cancer.

Trends in cancer

Liu Z, Rabadan R.
PMID: 33500226
Trends Cancer. 2021 Apr;7(4):347-358. doi: 10.1016/j.trecan.2020.12.015. Epub 2021 Jan 23.

Most human genes undergo alternative splicing (AS), and dysregulation of alternative splicing contributes to tumor initiation and progression. Computational analysis of genomic and transcriptomic data enables the systematic characterization of alternative splicing and its functional role in cancer. In...

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Liu Z, Rabadan R. Computing the Role of Alternative Splicing in Cancer. Trends Cancer. 2021;7(4):347-358doi: 10.1016/j.trecan.2020.12.015.
Liu, Z., & Rabadan, R. (2021). Computing the Role of Alternative Splicing in Cancer. Trends in cancer, 7(4), 347-358. https://doi.org/10.1016/j.trecan.2020.12.015
Liu, Zhaoqi, and Rabadan, Raul. "Computing the Role of Alternative Splicing in Cancer." Trends in cancer vol. 7,4 (2021): 347-358. doi: https://doi.org/10.1016/j.trecan.2020.12.015
Liu Z, Rabadan R. Computing the Role of Alternative Splicing in Cancer. Trends Cancer. 2021 Apr;7(4):347-358. doi: 10.1016/j.trecan.2020.12.015. Epub 2021 Jan 23. PMID: 33500226; PMCID: PMC7969404.
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Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.

Nature cancer

Garofano L, Migliozzi S, Oh YT, D'Angelo F, Najac RD, Ko A, Frangaj B, Caruso FP, Yu K, Yuan J, Zhao W, Di Stefano AL, Bielle F, Jiang T, Sims P, Suvà ML, Tang F, Su XD, Ceccarelli M, Sanson M, Lasorella A, Iavarone A.
PMID: 33681822
Nat Cancer. 2021 Feb;2(2):141-156. doi: 10.1038/s43018-020-00159-4. Epub 2021 Jan 11.

The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed...

Cite
Garofano L, Migliozzi S, Oh YT, et al. Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nat Cancer. 2021;2(2):141-156doi: 10.1038/s43018-020-00159-4.
Garofano, L., Migliozzi, S., Oh, Y. T., D'Angelo, F., Najac, R. D., Ko, A., Frangaj, B., Caruso, F. P., Yu, K., Yuan, J., Zhao, W., Di Stefano, A. L., Bielle, F., Jiang, T., Sims, P., Suvà, M. L., Tang, F., Su, X. D., Ceccarelli, M., Sanson, M., Lasorella, A., & Iavarone, A. (2021). Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nature cancer, 2(2), 141-156. https://doi.org/10.1038/s43018-020-00159-4
Garofano, Luciano, et al. "Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities." Nature cancer vol. 2,2 (2021): 141-156. doi: https://doi.org/10.1038/s43018-020-00159-4
Garofano L, Migliozzi S, Oh YT, D'Angelo F, Najac RD, Ko A, Frangaj B, Caruso FP, Yu K, Yuan J, Zhao W, Di Stefano AL, Bielle F, Jiang T, Sims P, Suvà ML, Tang F, Su XD, Ceccarelli M, Sanson M, Lasorella A, Iavarone A. Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nat Cancer. 2021 Feb;2(2):141-156. doi: 10.1038/s43018-020-00159-4. Epub 2021 Jan 11. PMID: 33681822; PMCID: PMC7935068.
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Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.

Nature cancer

Garofano L, Migliozzi S, Oh YT, D'Angelo F, Najac RD, Ko A, Frangaj B, Caruso FP, Yu K, Yuan J, Zhao W, Di Stefano AL, Bielle F, Jiang T, Sims P, Suvà ML, Tang F, Su XD, Ceccarelli M, Sanson M, Lasorella A, Iavarone A.
PMID: 33681822
Nat Cancer. 2021 Feb;2(2):141-156. doi: 10.1038/s43018-020-00159-4. Epub 2021 Jan 11.

The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed...

Cite
Garofano L, Migliozzi S, Oh YT, et al. Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nat Cancer. 2021;2(2):141-156doi: 10.1038/s43018-020-00159-4.
Garofano, L., Migliozzi, S., Oh, Y. T., D'Angelo, F., Najac, R. D., Ko, A., Frangaj, B., Caruso, F. P., Yu, K., Yuan, J., Zhao, W., Di Stefano, A. L., Bielle, F., Jiang, T., Sims, P., Suvà, M. L., Tang, F., Su, X. D., Ceccarelli, M., Sanson, M., Lasorella, A., & Iavarone, A. (2021). Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nature cancer, 2(2), 141-156. https://doi.org/10.1038/s43018-020-00159-4
Garofano, Luciano, et al. "Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities." Nature cancer vol. 2,2 (2021): 141-156. doi: https://doi.org/10.1038/s43018-020-00159-4
Garofano L, Migliozzi S, Oh YT, D'Angelo F, Najac RD, Ko A, Frangaj B, Caruso FP, Yu K, Yuan J, Zhao W, Di Stefano AL, Bielle F, Jiang T, Sims P, Suvà ML, Tang F, Su XD, Ceccarelli M, Sanson M, Lasorella A, Iavarone A. Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nat Cancer. 2021 Feb;2(2):141-156. doi: 10.1038/s43018-020-00159-4. Epub 2021 Jan 11. PMID: 33681822; PMCID: PMC7935068.
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A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies.

Nature cancer

Degasperi A, Amarante TD, Czarnecki J, Shooter S, Zou X, Glodzik D, Morganella S, Nanda AS, Badja C, Koh G, Momen SE, Georgakopoulos-Soares I, Dias JML, Young J, Memari Y, Davies H, Nik-Zainal S.
PMID: 32118208
Nat Cancer. 2020 Feb;1(2):249-263. doi: 10.1038/s43018-020-0027-5. Epub 2020 Feb 17.

No abstract available.

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Degasperi A, Amarante TD, Czarnecki J, et al. A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies. Nat Cancer. 2020;1(2):249-263doi: 10.1038/s43018-020-0027-5.
Degasperi, A., Amarante, T. D., Czarnecki, J., Shooter, S., Zou, X., Glodzik, D., Morganella, S., Nanda, A. S., Badja, C., Koh, G., Momen, S. E., Georgakopoulos-Soares, I., Dias, J. M. L., Young, J., Memari, Y., Davies, H., & Nik-Zainal, S. (2020). A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies. Nature cancer, 1(2), 249-263. https://doi.org/10.1038/s43018-020-0027-5
Degasperi, Andrea, et al. "A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies." Nature cancer vol. 1,2 (2020): 249-263. doi: https://doi.org/10.1038/s43018-020-0027-5
Degasperi A, Amarante TD, Czarnecki J, Shooter S, Zou X, Glodzik D, Morganella S, Nanda AS, Badja C, Koh G, Momen SE, Georgakopoulos-Soares I, Dias JML, Young J, Memari Y, Davies H, Nik-Zainal S. A practical framework and online tool for mutational signature analyses show inter-tissue variation and driver dependencies. Nat Cancer. 2020 Feb;1(2):249-263. doi: 10.1038/s43018-020-0027-5. Epub 2020 Feb 17. PMID: 32118208; PMCID: PMC7048622.
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Identification of potentially oncogenic alterations from tumor-only samples reveals Fanconi anemia pathway mutations in bladder carcinomas.

NPJ genomic medicine

Madubata CJ, Roshan-Ghias A, Chu T, Resnick S, Zhao J, Arnes L, Wang J, Rabadan R.
PMID: 29263839
NPJ Genom Med. 2017 Oct 03;2:29. doi: 10.1038/s41525-017-0032-5. eCollection 2017.

Cancer is caused by germline and somatic mutations, which can share biological features such as amino acid change. However, integrated germline and somatic analysis remains uncommon. We present a framework that uses machine learning to learn features of recurrent...

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Madubata CJ, Roshan-Ghias A, Chu T, et al. Identification of potentially oncogenic alterations from tumor-only samples reveals Fanconi anemia pathway mutations in bladder carcinomas. NPJ Genom Med. 2017;2:29doi: 10.1038/s41525-017-0032-5.
Madubata, C. J., Roshan-Ghias, A., Chu, T., Resnick, S., Zhao, J., Arnes, L., Wang, J., & Rabadan, R. (2017). Identification of potentially oncogenic alterations from tumor-only samples reveals Fanconi anemia pathway mutations in bladder carcinomas. NPJ genomic medicine, 229. https://doi.org/10.1038/s41525-017-0032-5
Madubata, Chioma J, et al. "Identification of potentially oncogenic alterations from tumor-only samples reveals Fanconi anemia pathway mutations in bladder carcinomas." NPJ genomic medicine vol. 2 (2017): 29. doi: https://doi.org/10.1038/s41525-017-0032-5
Madubata CJ, Roshan-Ghias A, Chu T, Resnick S, Zhao J, Arnes L, Wang J, Rabadan R. Identification of potentially oncogenic alterations from tumor-only samples reveals Fanconi anemia pathway mutations in bladder carcinomas. NPJ Genom Med. 2017 Oct 03;2:29. doi: 10.1038/s41525-017-0032-5. eCollection 2017. PMID: 29263839; PMCID: PMC5677944.
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Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities.

Nature cancer

Garofano L, Migliozzi S, Oh YT, D'Angelo F, Najac RD, Ko A, Frangaj B, Caruso FP, Yu K, Yuan J, Zhao W, Di Stefano AL, Bielle F, Jiang T, Sims P, Suvà ML, Tang F, Su XD, Ceccarelli M, Sanson M, Lasorella A, Iavarone A.
PMID: 33681822
Nat Cancer. 2021 Feb;2(2):141-156. doi: 10.1038/s43018-020-00159-4. Epub 2021 Jan 11.

The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and therapeutic vulnerabilities. A computational approach for unbiased identification of core biological traits of single cells and bulk tumors uncovered four tumor cell states and GBM subtypes distributed...

Cite
Garofano L, Migliozzi S, Oh YT, et al. Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nat Cancer. 2021;2(2):141-156doi: 10.1038/s43018-020-00159-4.
Garofano, L., Migliozzi, S., Oh, Y. T., D'Angelo, F., Najac, R. D., Ko, A., Frangaj, B., Caruso, F. P., Yu, K., Yuan, J., Zhao, W., Di Stefano, A. L., Bielle, F., Jiang, T., Sims, P., Suvà, M. L., Tang, F., Su, X. D., Ceccarelli, M., Sanson, M., Lasorella, A., & Iavarone, A. (2021). Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nature cancer, 2(2), 141-156. https://doi.org/10.1038/s43018-020-00159-4
Garofano, Luciano, et al. "Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities." Nature cancer vol. 2,2 (2021): 141-156. doi: https://doi.org/10.1038/s43018-020-00159-4
Garofano L, Migliozzi S, Oh YT, D'Angelo F, Najac RD, Ko A, Frangaj B, Caruso FP, Yu K, Yuan J, Zhao W, Di Stefano AL, Bielle F, Jiang T, Sims P, Suvà ML, Tang F, Su XD, Ceccarelli M, Sanson M, Lasorella A, Iavarone A. Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities. Nat Cancer. 2021 Feb;2(2):141-156. doi: 10.1038/s43018-020-00159-4. Epub 2021 Jan 11. PMID: 33681822; PMCID: PMC7935068.
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Showing 1 to 10 of 10 entries