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39 results on '"Haradhvala, Nicholas J."'

1. Phase 1 study of CAR-37 T cells in patients with relapsed or refractory CD37+ lymphoid malignancies

Author

Frigault, Matthew J., Graham, Charlotte E., Berger, Trisha R., Ritchey, Julie, Horick, Nora K., El-Jawahri, Areej, Scarfò, Irene, Schmidts, Andrea, Haradhvala, Nicholas J., Wehrli, Marc, Lee, Won-Ho, Parker, Aiyana L., Wiggin, Hadley R., Bouffard, Amanda, Dey, Aonkon, Leick, Mark B., Katsis, Katelin, Elder, Eva L., Dolaher, Maria A., Cook, Daniella T., Chekmasova, Alena A., Huang, Lu, Nikiforow, Sarah, Daley, Heather, Ritz, Jerome, Armant, Myriam, Preffer, Fred, DiPersio, John F., Nardi, Valentina, Chen, Yi-Bin, Gallagher, Kathleen M. E., and Maus, Marcela V.

Published
2024
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2. Latent human herpesvirus 6 is reactivated in CAR T cells

Author

Lareau, Caleb A., Yin, Yajie, Maurer, Katie, Sandor, Katalin D., Daniel, Bence, Yagnik, Garima, Peña, José, Crawford, Jeremy Chase, Spanjaart, Anne M., Gutierrez, Jacob C., Haradhvala, Nicholas J., Riberdy, Janice M., Abay, Tsion, Stickels, Robert R., Verboon, Jeffrey M., Liu, Vincent, Buquicchio, Frank A., Wang, Fangyi, Southard, Jackson, Song, Ren, Li, Wenjing, Shrestha, Aastha, Parida, Laxmi, Getz, Gad, Maus, Marcela V., Li, Shuqiang, Moore, Alison, Roberts, Zachary J., Ludwig, Leif S., Talleur, Aimee C., Thomas, Paul G., Dehghani, Houman, Pertel, Thomas, Kundaje, Anshul, Gottschalk, Stephen, Roth, Theodore L., Kersten, Marie J., Wu, Catherine J., Majzner, Robbie G., and Satpathy, Ansuman T.

Published
2023
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3. Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation

Author

An, Eunkyung, Anurag, Meenakshi, Bavarva, Jasmin, Birrer, Michael J., Babur, Özgün, Cao, Song, Ceccarelli, Michele, Chan, Daniel W., Chinnaiyan, Arul M., Cho, Hanbyul, Chowdhury, Shrabanti, Cieslik, Marcin P., Colaprico, Antonio, Carr, Steven A., da Veiga Leprevost, Felipe, Day, Corbin, Domagalski, Marcin J., Dou, Yongchao, Druker, Brian J., Edwards, Nathan, Ellis, Matthew J., Fenyo, David, Foltz, Steven M., Francis, Alicia, Gonzalez Robles, Tania J., Gosline, Sara J.C., Gümüş, Zeynep H., Hiltke, Tara, Hong, Runyu, Hostetter, Galen, Hu, Yingwei, Huang, Chen, Iavarone, Antonio, Jaehnig, Eric J., Jewel, Scott D., Ji, Jiayi, Jiang, Wen, Katsnelson, Lizabeth, Ketchum, Karen A., Kolodziejczak, Iga, Kumar-Sinha, Chandan, Krug, Karsten, Lei, Jonathan T., Liang, Wen-Wei, Liao, Yuxing, Lindgren, Caleb M., Liu, Tao, Liu, Wenke, Ma, Weiping, McKerrow, Wilson, Mesri, Mehdi, Mani, D.R., Nesvizhskii, Alexey I., Newton, Chelsea, Oldroyd, Robert, Omenn, Gilbert S., Paulovich, Amanda G., Petralia, Francesca, Pugliese, Pietro, Reva, Boris, Rodland, Karin D., Ruggles, Kelly V., Rykunov, Dmitry, Rodrigues, Fernanda Martins, Savage, Sara R., Schadt, Eric E., Schnaubelt, Michael, Schraink, Tobias, Shi, Zhiao, Smith, Richard D., Song, Xiaoyu, Stathias, Vasileios, Storrs, Erik P., Schürer, Stephan, Selvan, Myvizhi Esai, Tan, Jimin, Terekhanova, Nadezhda V., Thangudu, Ratna R., Tignor, Nicole, Thiagarajan, Mathangi, Wang, Joshua M., Wang, Pei, Wang, Ying (Cindy), Wen, Bo, Wiznerowicz, Maciej, Wu, Yige, Wyczalkowski, Matthew A., Yao, Lijun, Yi, Xinpei, Zhang, Bing, Zhang, Hui, Zhang, Xu, Zhang, Zhen, Zhou, Daniel Cui, Geffen, Yifat, Anand, Shankara, Akiyama, Yo, Yaron, Tomer M., Song, Yizhe, Johnson, Jared L., Govindan, Akshay, Li, Yize, Huntsman, Emily, Wang, Liang-Bo, Birger, Chet, Heiman, David I., Zhang, Qing, Miller, Mendy, Maruvka, Yosef E., Haradhvala, Nicholas J., Calinawan, Anna, Belkin, Saveliy, Kerelsky, Alexander, Clauser, Karl R., Satpathy, Shankha, Payne, Samuel H., Gillette, Michael A., Dhanasekaran, Saravana M., Rodriguez, Henry, Robles, Ana I., Lazar, Alexander J., Aguet, François, Cantley, Lewis C., Ding, Li, and Getz, Gad

Published
2023
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4. Distinct cellular dynamics associated with response to CAR-T therapy for refractory B cell lymphoma

Author

Haradhvala, Nicholas J., Leick, Mark B., Maurer, Katie, Gohil, Satyen H., Larson, Rebecca C., Yao, Ning, Gallagher, Kathleen M. E., Katsis, Katelin, Frigault, Matthew J., Southard, Jackson, Li, Shuqiang, Kann, Michael C., Silva, Harrison, Jan, Max, Rhrissorrakrai, Kahn, Utro, Filippo, Levovitz, Chaya, Jacobs, Raquel A., Slowik, Kara, Danysh, Brian P., Livak, Kenneth J., Parida, Laxmi, Ferry, Judith, Jacobson, Caron, Wu, Catherine J., Getz, Gad, and Maus, Marcela V.

Published
2022
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5. Designing sensitive viral diagnostics with machine learning

Author

Metsky, Hayden C., Welch, Nicole L., Pillai, Priya P., Haradhvala, Nicholas J., Rumker, Laurie, Mantena, Sreekar, Zhang, Yibin B., Yang, David K., Ackerman, Cheri M., Weller, Juliane, Blainey, Paul C., Myhrvold, Cameron, Mitzenmacher, Michael, and Sabeti, Pardis C.

Published
2022
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6. CAR T cell killing requires the IFNγR pathway in solid but not liquid tumours

Author

Larson, Rebecca C., Kann, Michael C., Bailey, Stefanie R., Haradhvala, Nicholas J., Llopis, Paula Montero, Bouffard, Amanda A., Scarfó, Irene, Leick, Mark B., Grauwet, Korneel, Berger, Trisha R., Stewart, Kai, Anekal, Praju Vikas, Jan, Max, Joung, Julia, Schmidts, Andrea, Ouspenskaia, Tamara, Law, Travis, Regev, Aviv, Getz, Gad, and Maus, Marcela V.

Published
2022
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8. Comparative analysis of Bcl-2 family protein overexpression in CAR T cells alone and in combination with BH3 mimetics.

Author

Korell, Felix, Olson, Michael L., Salas-Benito, Diego, Leick, Mark B., Larson, Rebecca C., Bouffard, Amanda, Silva, Harrison, Gasparetto, Alessandro, Berger, Trisha R., Kann, Michael C., Mergen, Markus, Kienka, Tamina, Wehrli, Marc, Haradhvala, Nicholas J., Bailey, Stefanie R., Letai, Anthony, and Maus, Marcela V.

Subjects
BCL-2 proteins, PROTEIN overexpression, T cells, CHIMERIC antigen receptors, CANCER cells
Abstract

Approximately 50% of patients with hematologic malignancies relapse after chimeric antigen receptor (CAR) T cell treatment; mechanisms of failure include loss of CAR T persistence and tumor resistance to apoptosis. We hypothesized that both of these challenges could potentially be overcome by overexpressing one or more of the Bcl-2 family proteins in CAR T cells to reduce their susceptibility to apoptosis, both alone and in the presence of BH3 mimetics, which can be used to activate apoptotic machinery in malignant cells. We comprehensively investigated overexpression of different Bcl-2 family proteins in CAR T cells with different signaling domains as well as in different tumor types. We found that Bcl-xL and Bcl-2 overexpression in CAR T cells bearing a 4-1BB costimulatory domain resulted in increased expansion and antitumor activity, reduced exhaustion, and decreased apoptotic priming. In addition, CAR T cells expressing either Bcl-xL or a venetoclax-resistant Bcl-2 variant led to enhanced antitumor efficacy and survival in murine xenograft models of lymphoma and leukemia in the presence or absence of the BH3 mimetic venetoclax, a clinically approved BH3 mimetic. In this setting, Bcl-xL overexpression had stronger effects than overexpression of Bcl-2 or the Bcl-2(G101V) variant. These findings suggest that CAR T cells could be optimally engineered by overexpressing Bcl-xL to enhance their persistence while opening a therapeutic window for combination with BH3 mimetics to prime tumors for apoptosis. Editor's summary: A major issue with chimeric antigen receptor (CAR) T cell therapy is poor persistence of the CAR T cells. To address this, Korell et al. developed CAR T cells overexpressing members of the Bcl-2 family, proteins involved in protection from apoptosis. The authors found that overexpression of Bcl-xL in particular improved CAR T cell persistence and function in vivo and could be combined with the BH3 mimetic venetoclax to further improve tumor control in mice. Together, these data highlight a potential strategy to improve CAR T cell therapies as well as suggest a combination therapy with BH3 mimetics. —Courtney Malo [ABSTRACT FROM AUTHOR]

Published
2024
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9. Author Correction: Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

Author

Rheinbay, Esther, Nielsen, Morten Muhlig, Abascal, Federico, Wala, Jeremiah A., Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M., Juul, Randi Istrup, Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzós, Andrés, Herrmann, Carl, Maruvka, Yosef E., Shen, Ciyue, Amin, Samirkumar B., Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A., Busanovich, John, Carlevaro-Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A., Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P., Haradhvala, Nicholas J., Hong, Chen, Isaev, Keren, Johnson, Todd A., Juul, Malene, Kahles, Andre, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric Minwei, Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D., Saksena, Gordon, Schumacher, Steven E., Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M. C., Umer, Husen M., Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E., Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S., von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J., Rubin, Mark A., Sander, Chris, Stein, Lincoln D., Stuart, Joshua M., Tsunoda, Tatsuhiko, Wheeler, David A., Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J., López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob Skou, and Getz, Gad

Published
2023
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10. Author Correction: The repertoire of mutational signatures in human cancer

Author

Alexandrov, Ludmil B., Kim, Jaegil, Haradhvala, Nicholas J., Huang, Mi Ni, Tian Ng, Alvin Wei, Wu, Yang, Boot, Arnoud, Covington, Kyle R., Gordenin, Dmitry A., Bergstrom, Erik N., Islam, S. M. Ashiqul, Lopez-Bigas, Nuria, Klimczak, Leszek J., McPherson, John R., Morganella, Sandro, Sabarinathan, Radhakrishnan, Wheeler, David A., Mustonen, Ville, Getz, Gad, Rozen, Steven G., and Stratton, Michael R.

Published
2023
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11. The repertoire of mutational signatures in human cancer

Author

Alexandrov, Ludmil B., Kim, Jaegil, Haradhvala, Nicholas J., Huang, Mi Ni, Tian Ng, Alvin Wei, Wu, Yang, and Boot, Arnoud

Subjects
Gene mutations -- Health aspects, Cancer -- Genetic aspects -- Identification and classification, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature.sup.1. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium.sup.2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses.sup.3-15, enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated--but distinct--DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer. The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development., Author(s): Ludmil B. Alexandrov [sup.1] , Jaegil Kim [sup.2] , Nicholas J. Haradhvala [sup.2] [sup.3] , Mi Ni Huang [sup.4] [sup.5] , Alvin Wei Tian Ng [sup.4] [sup.5] , Yang [...]

Published
2020
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12. Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

Author

Zavidij, Oksana, Haradhvala, Nicholas J., Mouhieddine, Tarek H., Sklavenitis-Pistofidis, Romanos, Cai, Songjie, Reidy, Mairead, Rahmat, Mahshid, Flaifel, Abdallah, Ferland, Benjamin, Su, Nang K., Agius, Michael P., Park, Jihye, Manier, Salomon, Bustoros, Mark, Huynh, Daisy, Capelletti, Marzia, Berrios, Brianna, Liu, Chia-Jen, He, Meng Xiao, Braggio, Esteban, Fonseca, Rafael, Maruvka, Yosef E., Guerriero, Jennifer L., Goldman, Melissa, Van Allen, Eliezer M., McCarroll, Steven A., Azzi, Jamil, Getz, Gad, and Ghobrial, Irene M.

Published
2020
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13. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

Author

Rheinbay, Esther, Nielsen, Morten Muhlig, Abascal, Federico, Wala, Jeremiah A., Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M., Juul, Randi Istrup, Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzós, Andrés, Herrmann, Carl, Maruvka, Yosef E., Shen, Ciyue, Amin, Samirkumar B., Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A., Busanovich, John, Carlevaro-Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A., Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P., Haradhvala, Nicholas J., Hong, Chen, Isaev, Keren, Johnson, Todd A., Juul, Malene, Kahles, Andre, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric Minwei, Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D., Saksena, Gordon, Schumacher, Steven E., Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M. C., Umer, Husen M., Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E., Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S., von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J., Rubin, Mark A., Sander, Chris, Stein, Lincoln D., Stuart, Joshua M., Tsunoda, Tatsuhiko, Wheeler, David A., Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J., López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob Skou, and Getz, Gad

Published
2020
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16. A post-transcriptional program of chemoresistance by AU-rich elements and TTP in quiescent leukemic cells

Author

Lee, Sooncheol, Micalizzi, Douglas, Truesdell, Samuel S., Bukhari, Syed I. A., Boukhali, Myriam, Lombardi-Story, Jennifer, Kato, Yasutaka, Choo, Min-Kyung, Dey-Guha, Ipsita, Ji, Fei, Nicholson, Benjamin T., Myers, David T., Lee, Dongjun, Mazzola, Maria A., Raheja, Radhika, Langenbucher, Adam, Haradhvala, Nicholas J., Lawrence, Michael S., Gandhi, Roopali, Tiedje, Christopher, Diaz-Muñoz, Manuel D., Sweetser, David A., Sadreyev, Ruslan, Sykes, David, Haas, Wilhelm, Haber, Daniel A., Maheswaran, Shyamala, and Vasudevan, Shobha

Published
2020
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18. Single-Cell RNA Sequencing Reveals Hypo-Responsiveness of T and NK Cells to Interferon Stimulation As an Immune Hallmark in Asymptomatic Waldenstrom's Macroglobulinemia

Author

Konishi, Yoshinobu, Sklavenitis-Pistofidis, Romanos, Mallory, Daniel L., Wu, Ting, Aranha, Michelle P., Tsuji, Junko, Haradhvala, Nicholas J, Lightbody, Elizabeth D., Towle, Katherine, Hevenor, Laura, Tsakmaklis, Nickolas, Wang, Xiyue, Canning, Alexa G, Liacos, Christine-Ivy, Kastritis, Efstathios, Dimopoulos, Meletios Athanasios, Treon, Steven P, Getz, Gady, and Ghobrial, Irene M.

Published
2023
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19. Single-Cell RNA Sequencing of Circulating Tumor Cells in Precursor Myeloma Patients Reveals Mechanisms of Disease Dissemination

Author

Lightbody, Elizabeth D., Sklavenitis-Pistofidis, Romanos, Firer, Danielle T., Tsuji, Junko, Agius, Mike P., Dutta, Ankit K., Wu, Ting, Barr, Hadley, Kim, Sungjae, Coorens, Tim, Alberge, Jean-Baptiste, Aranha, Michelle P., Haradhvala, Nicholas J, Kham Su, Nang, Boehner, Cody J., Walsh, Kelly, Rahmat, Mahshid, Konishi, Yoshinobu, Hevenor, Laura, Towle, Katherine, Horowitz, Erica M., Perry, Jacqueline, Fleming, Grace, El-Khoury, Habib, Vinyard, Michael, Cowan, Annie, Auclair, Daniel, Ready, John E., Marinac, Catherine R., Getz, Gad, and Ghobrial, Irene M.

Published
2023
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20. Analyses of non-coding somatic drivers in 2,658cancer whole genomes

Author

Group, PCAWG Drivers, Functional Interpretation Working, Group, PCAWG Structural Variation Working, Consortium, PCAWG, PCAWG Consortium, Rheinbay, Esther, Nielsen, Morten M., Abascal, Federico, Wala, Jeremiah A, Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M, Juul, Randi I., Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzós, Andrés, Herrmann, Carl, Maruvka, Yosef E., Shen, Ciyue, Amin, Samirkumar B., Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A., Busanovich, John, Carlevaro-Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A., Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P., Haradhvala, Nicholas J., Hong, Chen, Isaev, Keren, Johnson, Todd A., Juul, Malene, Kahles, André, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric M., Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D., Saksena, Gordon, Schumacher, Steven E, Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M.C., Umer, Husen M., Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E., Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S., von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J., Rubin, Mark A., Sander, Chris, Stein, Lincoln D., Stuart, Joshua M., Tsunoda, Tatsuhiko, Wheeler, David A., Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J., López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob S., and Getz, Gad

Subjects
Cancer genomics, Computational biology and bioinformatics
Abstract

The discovery of drivers of cancer has traditionally focused on protein-coding genes14. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5 region of TP53, in the 3 untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that althoughpoint mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available., Nature, 578 (7793), ISSN:0028-0836, ISSN:1476-4687

Published
2020
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21. The premalignant state captured in the landscape of somatic mutations can reveal the cancer cell-of-origin

Author

Kubler, Kirsten, Karlic, Rosa, Haradhvala, Nicholas J., Ha, Kyungsik, Kim, Jaegil, Kuzman, Maja, Jiao, Wei, Gakkhar, Sitanshu, Mouw, Kent W., Braunstein, Lior Z., Elemento, Olivier, Biankin, Andrew V., Rooman, Ilse, Miller, Mendy, Nogiec, Christopher D., Curry, Edward, Mino-Kenudson, Mari, Ellisen, Leif W., Brown, Robert, Gusev, Alexander, Tomasetti, Cristian, Kim, Hong-Gee, Lee, Hwajin, Vlahovicek, Kristian, Sawyers, Charles, Hoadley, Katherine A., Cuppen, Edwin, Koren, Amnon, Arndt, Peter F., Louis, David N., Stein, Lincoln, Foulkes, William D., Polak, Paz, Getz, Gad, Basic (bio-) Medical Sciences, and Laboratory of Molecular and Medical Oncology

Subjects
Cancer Research, premalignant state, somatic mutations, cancer cell
Published
2019

23. Single-Cell RNA-Sequencing of 245 Tumor Samples from Patients with MGUS and Smoldering Multiple Myeloma Reveals Novel Insights into Malignant Plasma Cell Biology

Author

Tsuji, Junko, Lightbody, Elizabeth D., Sklavenitis-Pistofidis, Romanos, Agius, Michael P., Rahmat, Mahshid, Barr, Hadley, Konishi, Yoshinobu, Dutta, Ankit K., Su, Nang Kham, Boehner, Cody J., Firer, Danielle T., Wu, Ting, Aranha, Michelle P., Hevenor, Laura, Horowitz, Erica, Perry, Jacqueline, Aguet, François, Haradhvala, Nicholas J., Boiarsky, Rebecca, Getz, Gad, and Ghobrial, Irene

Published
2022
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24. Single-Cell RNA-Sequencing of 370 Bone Marrow and Peripheral Blood Immune Cell Samples from Patients with MGUS and Smoldering Multiple Myeloma Reveal Significant Immune Dysregulation at the MGUS Stage, and Novel Interactions between Tumor and Immune Cells

Author

Sklavenitis-Pistofidis, Romanos, Wu, Ting, Rahmat, Mahshid, Konishi, Yoshinobu, Lightbody, Elizabeth D., Timonian, Michael, Tsuji, Junko, Firer, Danielle T., Haradhvala, Nicholas J., Soekojo, Cinnie Yentia, Wang, Xiyue, Heilpern-Mallory, Daniel, Aguet, François, Getz, Gad, and Ghobrial, Irene

Published
2022
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25. Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma

Author

Zavidij, Oksana, Haradhvala, Nicholas J., Mouhieddine, Tarek, Sklavenitis-Pistofidis, Romanos, Agius, Michael P., Cai, Songjie, Reidy, Mairead, Rahmat, Mahshid, Flaifel, Abdallah, Ferland, Benjamin, Park, Jihye, Manier, Salomon, Bustoros, Mark, Huynh, Daisy, Capelletti, Marzia, Berrios, Brianna, Liu, Chia-Jen, He, Meng Xiao, Braggio, Esteban, Fonseca, Rafael, Maruvka, Yosef, Guerriero, Jennifer L., Goldman, Melissa, Van Allen, Eliezer, McCarroll, Steven A., Azzi, Jamil, Getz, Gad, and Ghobrial, Irene

Published
2019
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27. Analysis of somatic microsatellite indels identifies driver events in human tumors.

Author

Maruvka, Yosef E, Mouw, Kent W, Karlic, Rosa, Parasuraman, Prasanna, Kamburov, Atanas, Polak, Paz, Haradhvala, Nicholas J, Hess, Julian M, Rheinbay, Esther, Brody, Yehuda, Koren, Amnon, Braunstein, Lior Z, D'Andrea, Alan, Lawrence, Michael S, Bass, Adam, Bernards, Andre, Michor, Franziska, and Getz, Gad

Abstract

Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3). [ABSTRACT FROM AUTHOR]

Published
2017
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28. Mutational Strand Asymmetries in Cancer Genomes Reveal Mechanisms of DNA Damage and Repair.

Author

Haradhvala, Nicholas J., Polak, Paz, Stojanov, Petar, Covington, Kyle R., Shinbrot, Eve, Hess, Julian M., Rheinbay, Esther, Kim, Jaegil, Maruvka, Yosef E., Braunstein, Lior Z., Kamburov, Atanas, Hanawalt, Philip C., Wheeler, David A., Koren, Amnon, Lawrence, Michael S., and Getz, Gad

Subjects
*DNA damage, *CANCER genetics, *GENETIC mutation, *DNA repair, *TRANSCRIPTION factors
Abstract

Summary Mutational processes constantly shape the somatic genome, leading to immunity, aging, cancer, and other diseases. When cancer is the outcome, we are afforded a glimpse into these processes by the clonal expansion of the malignant cell. Here, we characterize a less explored layer of the mutational landscape of cancer: mutational asymmetries between the two DNA strands. Analyzing whole-genome sequences of 590 tumors from 14 different cancer types, we reveal widespread asymmetries across mutagenic processes, with transcriptional (“T-class”) asymmetry dominating UV-, smoking-, and liver-cancer-associated mutations and replicative (“R-class”) asymmetry dominating POLE-, APOBEC-, and MSI-associated mutations. We report a striking phenomenon of transcription-coupled damage (TCD) on the non-transcribed DNA strand and provide evidence that APOBEC mutagenesis occurs on the lagging-strand template during DNA replication. As more genomes are sequenced, studying and classifying their asymmetries will illuminate the underlying biological mechanisms of DNA damage and repair. [ABSTRACT FROM AUTHOR]

Published
2016
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31. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

Author

Rheinbay, Esther, Nielsen, Morten Muhlig, Abascal, Federico, Wala, Jeremiah A, Shapira, Ofer, Tiao, Grace, Hornshøj, Henrik, Hess, Julian M, Juul, Randi Istrup, Lin, Ziao, Feuerbach, Lars, Sabarinathan, Radhakrishnan, Madsen, Tobias, Kim, Jaegil, Mularoni, Loris, Shuai, Shimin, Lanzos, Andrés, Herrmann, Carl, Maruvka, Yosef E, Shen, Ciyue, Amin, Samirkumar B, Bandopadhayay, Pratiti, Bertl, Johanna, Boroevich, Keith A, Busanovich, John, Carlevaro Fita, Joana, Chakravarty, Dimple, Chan, Calvin Wing Yiu, Craft, David, Dhingra, Priyanka, Diamanti, Klev, Fonseca, Nuno A, Gonzalez-Perez, Abel, Guo, Qianyun, Hamilton, Mark P, Haradhvala, Nicholas J, Hong, Chen, Isaev, Keren, Johnson, Todd A, Juul, Malene, Kahles, Andre, Kahraman, Abdullah, Kim, Youngwook, Komorowski, Jan, Kumar, Kiran, Kumar, Sushant, Lee, Donghoon, Lehmann, Kjong-Van, Li, Yilong, Liu, Eric Minwei, Lochovsky, Lucas, Park, Keunchil, Pich, Oriol, Roberts, Nicola D, Saksena, Gordon, Schumacher, Steven E, Sidiropoulos, Nikos, Sieverling, Lina, Sinnott-Armstrong, Nasa, Stewart, Chip, Tamborero, David, Tubio, Jose M C, Umer, Husen M, Uusküla-Reimand, Liis, Wadelius, Claes, Wadi, Lina, Yao, Xiaotong, Zhang, Cheng-Zhong, Zhang, Jing, Haber, James E, Hobolth, Asger, Imielinski, Marcin, Kellis, Manolis, Lawrence, Michael S, Von Mering, Christian, Nakagawa, Hidewaki, Raphael, Benjamin J, Rubin, Mark Andrew, Sander, Chris, Stein, Lincoln D, Stuart, Joshua M, Tsunoda, Tatsuhiko, Wheeler, David A, Johnson, Rory, Reimand, Jüri, Gerstein, Mark, Khurana, Ekta, Campbell, Peter J, López-Bigas, Núria, Weischenfeldt, Joachim, Beroukhim, Rameen, Martincorena, Iñigo, Pedersen, Jakob Skou, and Getz, Gad

Subjects
610 Medicine & health, 3. Good health
Abstract

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

32. Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation.

Author

Geffen, Yifat, Anand, Shankara, Akiyama, Yo, Yaron, Tomer M., Song, Yizhe, Johnson, Jared L., Govindan, Akshay, Babur, Özgün, Li, Yize, Huntsman, Emily, Wang, Liang-Bo, Birger, Chet, Heiman, David I., Zhang, Qing, Miller, Mendy, Maruvka, Yosef E., Haradhvala, Nicholas J., Calinawan, Anna, Belkin, Saveliy, and Kerelsky, Alexander

Subjects
*POST-translational modification, *METABOLIC regulation, *DNA repair, *IMMUNOREGULATION, *CELL physiology, *TUMOR proteins
Abstract

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues. [Display omitted] • Unsupervised clustering reveals 33 pan-cancer multi-omic signatures • PTM dysregulation is associated with distinct DNA damage repair mechanisms • Changes in acetylation of metabolic proteins correlate with tumor immune state • Phosphorylation of Thr/Ser kinases is affected by proximal acetylation An analytical resource of post-translational modifications from over 1,000 patients across 11 cancer types reveals pan-cancer changes involved in hallmark cancer processes and reveals potential new therapeutic avenues. [ABSTRACT FROM AUTHOR]

Published
2023
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33. Immune biomarkers of response to immunotherapy in patients with high-risk smoldering myeloma.

Author

Sklavenitis-Pistofidis, Romanos, Aranha, Michelle P., Redd, Robert A., Baginska, Joanna, Haradhvala, Nicholas J., Hallisey, Margaret, Dutta, Ankit K., Savell, Alexandra, Varmeh, Shohreh, Heilpern-Mallory, Daniel, Ujwary, Sylvia, Zavidij, Oksana, Aguet, Francois, Su, Nang K., Lightbody, Elizabeth D., Bustoros, Mark, Tahri, Sabrin, Mouhieddine, Tarek H., Wu, Ting, and Flechon, Lea

Subjects
*MULTIPLE myeloma, *BONE marrow, *CYTOTOXIC T cells, *T cell receptors, *IMMUNE response, *RNA sequencing, *IMMUNOTHERAPY
Abstract

Patients with smoldering multiple myeloma (SMM) are observed until progression, but early treatment may improve outcomes. We conducted a phase II trial of elotuzumab, lenalidomide, and dexamethasone (EloLenDex) in patients with high-risk SMM and performed single-cell RNA and T cell receptor (TCR) sequencing on 149 bone marrow (BM) and peripheral blood (PB) samples from patients and healthy donors (HDs). We find that early treatment with EloLenDex is safe and effective and provide a comprehensive characterization of alterations in immune cell composition and TCR repertoire diversity in patients. We show that the similarity of a patient's immune cell composition to that of HDs may have prognostic relevance at diagnosis and after treatment and that the abundance of granzyme K (GZMK)+ CD8+ effector memory T (TEM) cells may be associated with treatment response. Last, we uncover similarities between immune alterations observed in the BM and PB, suggesting that PB-based immune profiling may have diagnostic and prognostic utility. [Display omitted] • EloLenDex is associated with 4-year PFS of 89% in patients with high-risk SMM • Immune reactivity, post-therapy immune normalization are associated with longer PFS • Higher abundance of GZMK+ cytotoxic T cells is associated with longer PFS • Blood-based immune profiling detects immune dysregulation associated with disease Sklavenitis-Pistofidis et al. report results of a phase II trial of EloLenDex in patients with high-risk smoldering multiple myeloma and use single-cell RNA sequencing to identify biomarkers of outcomes. They show that immune cell composition affects progression-free survival and that blood-based immune profiling can detect immune alterations observed in the bone marrow. [ABSTRACT FROM AUTHOR]

Published
2022
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34. Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing.

Author

Viswanathan, Srinivas R., Ha, Gavin, Hoff, Andreas M., Wala, Jeremiah A., Carrot-Zhang, Jian, Whelan, Christopher W., Haradhvala, Nicholas J., Freeman, Samuel S., Reed, Sarah C., Rhoades, Justin, Polak, Paz, Cipicchio, Michelle, Wankowicz, Stephanie A., Wong, Alicia, Kamath, Tushar, Zhang, Zhenwei, Gydush, Gregory J., Rotem, Denisse, Love, J. Christopher, and Getz, Gad

Subjects
*CASTRATION-resistant prostate cancer, *ANDROGEN receptors, *NUCLEOTIDE sequencing, *TANDEM repeats, *GENOMICS, *CANCER treatment
Abstract

Summary Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%–87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered. [ABSTRACT FROM AUTHOR]

Published
2018
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35. Understanding Mechanisms of Response to CAR T-cell Therapy through Single-Cell Sequencing: Insights and Challenges.

Author

Haradhvala NJ and Maus MV

Subjects
Humans, Immunotherapy, Adoptive, Research Personnel
Abstract

Summary: Single-cell RNA sequencing has emerged as a powerful technique to understand the molecular features of chimeric antigen receptor (CAR) T cells that associate with clinical outcomes. Here we discuss the common themes that have emerged from across single-cell studies of CAR T-cell therapy, and summarize the challenges in interpreting this complex data type., (©2024 American Association for Cancer Research.)

Published
2024
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36. Systematic characterization of therapeutic vulnerabilities in Multiple Myeloma with Amp1q reveals increased sensitivity to the combination of MCL1 and PI3K inhibitors.

Author

Sklavenitis-Pistofidis R, Lightbody ED, Reidy M, Tsuji J, Aranha MP, Heilpern-Mallory D, Huynh D, Chong SJF, Hackett L, Haradhvala NJ, Wu T, Su NK, Berrios B, Alberge JB, Dutta A, Davids MS, Papaioannou M, Getz G, Ghobrial IM, and Manier S

Abstract

The development of targeted therapy for patients with Multiple Myeloma (MM) is hampered by the low frequency of actionable genetic abnormalities. Gain or amplification of chr1q (Amp1q) is the most frequent arm-level copy number gain in patients with MM, and it is associated with higher risk of progression and death despite recent advances in therapeutics. Thus, developing targeted therapy for patients with MM and Amp1q stands to benefit a large portion of patients in need of more effective management. Here, we employed large-scale dependency screens and drug screens to systematically characterize the therapeutic vulnerabilities of MM with Amp1q and showed increased sensitivity to the combination of MCL1 and PI3K inhibitors. Using single-cell RNA sequencing, we compared subclones with and without Amp1q within the same patient tumors and showed that Amp1q is associated with higher levels of MCL1 and the PI3K pathway. Furthermore, by isolating isogenic clones with different copy number for part of the chr1q arm, we showed increased sensitivity to MCL1 and PI3K inhibitors with arm-level gain. Lastly, we demonstrated synergy between MCL1 and PI3K inhibitors and dissected their mechanism of action in MM with Amp1q., Competing Interests: DECLARATION OF INTEREST E.D.L., M.R., J.T., M.P.A., D.H.M., D.H., S.J.F.C., L.H., N.J.H., T.W., N.K.S., B.B., J.A., and M.P. declare no competing interests. R.S.P. is a co-founder and equity holder in PreDICTA Biosciences. M.S.D. has received research funding from AbbVie, AstraZeneca, Ascentage Pharma, Genentech, MEI Pharma, Novartis, Surface Oncology, TG Therapeutics and personal consulting income from AbbVie, Adaptive Biosciences, Ascentage Pharma, AstraZeneca, BeiGene, BMS, Eli Lilly, Genentech, Genmab, Janssen, Merck, Mingsight Pharmaceuticals, Nuvalent, Secura Bio, TG Therapeutics, and Takeda. G.G. receives research funds from IBM, Pharmacyclics, and Ultima Genomics and is an inventor on patent applications filed by the Broad Institute related to MSMuTect, MSMutSig, POLYSOLVER, SignatureAnalyzer-GPU, MSIDetect, and MinumuMM-seq. He is also a founder, consultant, and holds privately held equity in Scorpion Therapeutics and PreDICTA Biosciences. I.M.G. has a consulting or advisory role with AbbVie, Adaptive, Amgen, Aptitude Health, Bristol Myers Squibb, GlaxoSmithKline, Huron Consulting, Janssen, Menarini Silicon Biosystems, Oncopeptides, Pfizer, Sanofi, Sognef, Takeda, The Binding Site, and Window Therapeutics; has received speaker fees from Vor Biopharma and Veeva Systems, Inc.; is a co-founder and equity holder in PreDICTA Biosciences; and her spouse is the CMO and equity holder of Disc Medicine. S.M. has a consulting role with Abbvie, Adaptive Biotechnology, Amgen, Celgene/BMS, GlaxoSmithKline, Janssen, Novartis, Oncopeptides, Regeneron, Roche, Takeda, and has received research funding from Abbvie, Adaptive Biotechnology, Amgen, Celgene/BMS, GlaxoSmithKline, Janssen, Novartis, Oncopeptides, Regeneron, Roche, Takeda.

Published
2023
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37. DNA Polymerase and Mismatch Repair Exert Distinct Microsatellite Instability Signatures in Normal and Malignant Human Cells.

Author

Chung J, Maruvka YE, Sudhaman S, Kelly J, Haradhvala NJ, Bianchi V, Edwards M, Forster VJ, Nunes NM, Galati MA, Komosa M, Deshmukh S, Cabric V, Davidson S, Zatzman M, Light N, Hayes R, Brunga L, Anderson ND, Ho B, Hodel KP, Siddaway R, Morrissy AS, Bowers DC, Larouche V, Bronsema A, Osborn M, Cole KA, Opocher E, Mason G, Thomas GA, George B, Ziegler DS, Lindhorst S, Vanan M, Yalon-Oren M, Reddy AT, Massimino M, Tomboc P, Van Damme A, Lossos A, Durno C, Aronson M, Morgenstern DA, Bouffet E, Huang A, Taylor MD, Villani A, Malkin D, Hawkins CE, Pursell ZF, Shlien A, Kunkel TA, Getz G, and Tabori U

Subjects
Humans, Exome Sequencing, Cell Transformation, Neoplastic, DNA Mismatch Repair, DNA-Directed DNA Polymerase, Gene Expression Regulation, Neoplastic, Microsatellite Instability, Neoplasms genetics
Abstract

Although replication repair deficiency, either by mismatch repair deficiency (MMRD) and/or loss of DNA polymerase proofreading, can cause hypermutation in cancer, microsatellite instability (MSI) is considered a hallmark of MMRD alone. By genome-wide analysis of tumors with germline and somatic deficiencies in replication repair, we reveal a novel association between loss of polymerase proofreading and MSI, especially when both components are lost. Analysis of indels in microsatellites (MS-indels) identified five distinct signatures (MS-sigs). MMRD MS-sigs are dominated by multibase losses, whereas mutant-polymerase MS-sigs contain primarily single-base gains. MS deletions in MMRD tumors depend on the original size of the MS and converge to a preferred length, providing mechanistic insight. Finally, we demonstrate that MS-sigs can be a powerful clinical tool for managing individuals with germline MMRD and replication repair-deficient cancers, as they can detect the replication repair deficiency in normal cells and predict their response to immunotherapy. SIGNIFICANCE: Exome- and genome-wide MSI analysis reveals novel signatures that are uniquely attributed to mismatch repair and DNA polymerase. This provides new mechanistic insight into MS maintenance and can be applied clinically for diagnosis of replication repair deficiency and immunotherapy response prediction. This article is highlighted in the In This Issue feature, p. 995 ., (©2020 American Association for Cancer Research.)

Published
2021
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38. Passenger Hotspot Mutations in Cancer.

Author

Hess JM, Bernards A, Kim J, Miller M, Taylor-Weiner A, Haradhvala NJ, Lawrence MS, and Getz G

Subjects
DNA Mutational Analysis, Datasets as Topic, Genes, Tumor Suppressor, Humans, Poisson Distribution, ROC Curve, Selection, Genetic, Exome Sequencing, Carcinogenesis genetics, Genomics methods, Models, Genetic, Mutagenesis, Neoplasms genetics
Abstract

Current statistical models for assessing hotspot significance do not properly account for variation in site-specific mutability, thereby yielding many false-positives. We thus (i) detail a Log-normal-Poisson (LNP) background model that accounts for this variability in a manner consistent with models of mutagenesis; (ii) use it to show that passenger hotspots arise from all common mutational processes; and (iii) apply it to a ∼10,000-patient cohort to nominate driver hotspots with far fewer false-positives compared with conventional methods. Overall, we show that many cancer hotspot mutations recurring at the same genomic site across multiple tumors are actually passenger events, recurring at inherently mutable genomic sites under no positive selection., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Published
2019
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39. Quantification of somatic mutation flow across individual cell division events by lineage sequencing.

Author

Brody Y, Kimmerling RJ, Maruvka YE, Benjamin D, Elacqua JJ, Haradhvala NJ, Kim J, Mouw KW, Frangaj K, Koren A, Getz G, Manalis SR, and Blainey PC

Subjects
Cell Line, DNA Copy Number Variations, Genotype, Humans, Polymorphism, Single Nucleotide, Single-Cell Analysis methods, Time-Lapse Imaging, Cell Division genetics, DNA Mutational Analysis mortality, High-Throughput Nucleotide Sequencing methods, Mutation
Abstract

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon ( POLE ) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations., (© 2018 Brody et al.; Published by Cold Spring Harbor Laboratory Press.)

Published
2018
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