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Your search keyword '"Shah, Sohrab P."' showing total 13 results
Start Over Author "Shah, Sohrab P." Journal genome biology
13 results on '"Shah, Sohrab P."'

1. Eleven grand challenges in single-cell data science

Author

Lähnemann, David, Köster, Johannes, Szczurek, Ewa, McCarthy, Davis J., Hicks, Stephanie C., Robinson, Mark D., Vallejos, Catalina A., Campbell, Kieran R., Beerenwinkel, Niko, Mahfouz, Ahmed, Pinello, Luca, Skums, Pavel, Stamatakis, Alexandros, Attolini, Camille Stephan-Otto, Aparicio, Samuel, Baaijens, Jasmijn, Balvert, Marleen, Barbanson, Buys de, Cappuccio, Antonio, Corleone, Giacomo, Dutilh, Bas E., Florescu, Maria, Guryev, Victor, Holmer, Rens, Jahn, Katharina, Lobo, Thamar Jessurun, Keizer, Emma M., Khatri, Indu, Kielbasa, Szymon M., Korbel, Jan O., Kozlov, Alexey M., Kuo, Tzu-Hao, Lelieveldt, Boudewijn P.F., Mandoiu, Ion I., Marioni, John C., Marschall, Tobias, Mölder, Felix, Niknejad, Amir, Rączkowska, Alicja, Reinders, Marcel, Ridder, Jeroen de, Saliba, Antoine-Emmanuel, Somarakis, Antonios, Stegle, Oliver, Theis, Fabian J., Yang, Huan, Zelikovsky, Alex, McHardy, Alice C., Raphael, Benjamin J., Shah, Sohrab P., and Schönhuth, Alexander

Published
2020
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3. Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

Author

Kabeer, Farhia, Tran, Hoa, Andronescu, Mirela, Singh, Gurdeep, Lee, Hakwoo, Salehi, Sohrab, Wang, Beixi, Biele, Justina, Brimhall, Jazmine, Gee, David, Cerda, Viviana, O’Flanagan, Ciara, Algara, Teresa, Kono, Takako, Beatty, Sean, Zaikova, Elena, Lai, Daniel, Lee, Eric, Moore, Richard, Mungall, Andrew J., Williams, Marc J., Roth, Andrew, Campbell, Kieran R., Shah, Sohrab P., and Aparicio, Samuel

Abstract

Background: The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug-associated transcriptional cell states. Results: We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure. Conclusions: Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration, and re-treatment strategies.

Published
2024
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5. ReMixT: clone-specific genomic structure estimation in cancer

Author

McPherson, Andrew W., primary, Roth, Andrew, additional, Ha, Gavin, additional, Chauve, Cedric, additional, Steif, Adi, additional, de Souza, Camila P. E., additional, Eirew, Peter, additional, Bouchard-Côté, Alexandre, additional, Aparicio, Sam, additional, Sahinalp, S. Cenk, additional, and Shah, Sohrab P., additional

Published
2017
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9. Evolution of an adenocarcinoma in response to selection by targeted kinase inhibitors

Author

Jones, Steven JM, primary, Laskin, Janessa, additional, Li, Yvonne Y, additional, Griffith, Obi L, additional, An, Jianghong, additional, Bilenky, Mikhail, additional, Butterfield, Yaron S, additional, Cezard, Timothee, additional, Chuah, Eric, additional, Corbett, Richard, additional, Fejes, Anthony P, additional, Griffith, Malachi, additional, Yee, John, additional, Martin, Montgomery, additional, Mayo, Michael, additional, Melnyk, Nataliya, additional, Morin, Ryan D, additional, Pugh, Trevor J, additional, Severson, Tesa, additional, Shah, Sohrab P, additional, Sutcliffe, Margaret, additional, Tam, Angela, additional, Terry, Jefferson, additional, Thiessen, Nina, additional, Thomson, Thomas, additional, Varhol, Richard, additional, Zeng, Thomas, additional, Zhao, Yongjun, additional, Moore, Richard A, additional, Huntsman, David G, additional, Birol, Inanc, additional, Hirst, Martin, additional, Holt, Robert A, additional, and Marra, Marco A, additional

Published
2010
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10. Personalized oncogenomics

Author

Jones, Steven JM, primary, Laskin, Janessa, additional, Li, Yvonne Y, additional, Griffith, Obi L, additional, An, Jianghong, additional, Bilenky, Mikhail, additional, Butterfield, Yaron S, additional, Chuah, Eric, additional, Corbett, Richard, additional, Fejes, Anthony, additional, Chan, Simon, additional, Liao, Nancy, additional, Kasaian, Katayoon, additional, Griffith, Malachi, additional, Yee, John, additional, Martin, Montgomery, additional, Mayo, Michael, additional, Melnyk, Nataliya, additional, Morin, Ryan D, additional, Pugh, Trevor J, additional, Severson, Tesa, additional, Shah, Sohrab P, additional, Sutcliffe, Margaret, additional, Tam, Angela, additional, Terry, Jefferson, additional, Thiessen, Nina, additional, Thomson, Thomas, additional, Varhol, Richard, additional, Zeng, Thomas, additional, Zhao, Yongjun, additional, Moore, Richard A, additional, Huntsman, David G, additional, Birol, Inanc, additional, Hirst, Martin, additional, Holt, Robert A, additional, and Marra, Marco A, additional

Published
2010
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11. Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

Author

O’Flanagan, Ciara H., Campbell, Kieran R., Zhang, Allen W., Kabeer, Farhia, Lim, Jamie L. P., Biele, Justina, Eirew, Peter, Lai, Daniel, McPherson, Andrew, Kong, Esther, Bates, Cherie, Borkowski, Kelly, Wiens, Matt, Hewitson, Brittany, Hopkins, James, Pham, Jenifer, Ceglia, Nicholas, Moore, Richard, Mungall, Andrew J., McAlpine, Jessica N., Shah, Sohrab P., and Aparicio, Samuel

Abstract

Background: Single-cell RNA sequencing (scRNA-seq) is a powerful tool for studying complex biological systems, such as tumor heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumor tissues and patient-derived mouse xenografts for scRNA-seq are not well understood. Results: We use low temperature (6?°C) protease and collagenase (37?°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNA-seq dataset comprising 155,165 cells from patient cancer tissues, patient-derived breast cancer xenografts, and cancer cell lines. We observe substantial variation in standard quality control metrics of cell viability across conditions and tissues. From the contrast between tissue protease dissociation at 37?°C or 6?°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37?°C), which are minimized by dissociation with a cold active protease (6?°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. Conclusions: The method and conditions of tumor dissociation influence cell yield and transcriptome state and are both tissue- and cell-type dependent. Interpretation of stress pathway expression differences in cancer single-cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with the identification of such effects in dissociated scRNA-seq experiments.

Published
2019
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13. Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses.

Author

O'Flanagan CH, Campbell KR, Zhang AW, Kabeer F, Lim JLP, Biele J, Eirew P, Lai D, McPherson A, Kong E, Bates C, Borkowski K, Wiens M, Hewitson B, Hopkins J, Pham J, Ceglia N, Moore R, Mungall AJ, McAlpine JN, Shah SP, and Aparicio S

Subjects
Animals, Cold Temperature, Collagenases, Humans, Mice, Peptide Hydrolases, Stress, Physiological, Transcriptome, Genomics methods, Neoplasms metabolism, Sequence Analysis, RNA, Single-Cell Analysis
Abstract

Background: Single-cell RNA sequencing (scRNA-seq) is a powerful tool for studying complex biological systems, such as tumor heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumor tissues and patient-derived mouse xenografts for scRNA-seq are not well understood., Results: We use low temperature (6 °C) protease and collagenase (37 °C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNA-seq dataset comprising 155,165 cells from patient cancer tissues, patient-derived breast cancer xenografts, and cancer cell lines. We observe substantial variation in standard quality control metrics of cell viability across conditions and tissues. From the contrast between tissue protease dissociation at 37 °C or 6 °C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37 °C), which are minimized by dissociation with a cold active protease (6 °C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues., Conclusions: The method and conditions of tumor dissociation influence cell yield and transcriptome state and are both tissue- and cell-type dependent. Interpretation of stress pathway expression differences in cancer single-cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with the identification of such effects in dissociated scRNA-seq experiments.

Published
2019
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