84 results on '"Pagadala, Meghana"'
Search Results
52. Abstract 3825: Germline modifiers of the tumor immune microenvironment reveal drivers of immunotherapy response
- Author
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Pagadala, Meghana, primary, Wu, Victoria, additional, Pérez-Guijarro, Eva, additional, Kim, Hyo, additional, Castro, Andrea, additional, Talwar, James, additional, Gonzalez-Colin, Cristian, additional, Cao, Steven, additional, Schmiedel, Benjamin J., additional, Sears, Timothy, additional, Goudarzi, Shervin, additional, Kirani, Divya, additional, Salem, Rany M., additional, Morris, Gerald P., additional, Harismendy, Olivier, additional, Patel, Sandip P., additional, Mesirov, Jill P., additional, Zanetti, Maurizio, additional, Day, Chi-Ping, additional, Fan, Chun C., additional, Thompson, Wesley K., additional, Merlino, Glenn, additional, Gutkind, J. Silvio, additional, Vijayanand, Pandurangan, additional, and Carter, Hannah, additional
- Published
- 2022
- Full Text
- View/download PDF
53. EPEN-18. Oncogenic 3D genome conformations identify novel therapeutic targets in ependymoma
- Author
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Okonechnikov, Konstantin, primary, Camgöz, Aylin, additional, Park, Donglim Esther, additional, Chapman, Owen, additional, Hübner, Jens-Martin, additional, Jenseit, Anne, additional, Chakraborty, Abhijit, additional, Pagadala, Meghana, additional, Bump, Rosalind, additional, Chandran, Sahaana, additional, Kraft, Katherina, additional, Hidalgo, Rocio Acuna, additional, Reid, Derek, additional, Juarez, Edwin F, additional, Robinson, James T, additional, Pajtler, Kristian W, additional, Milde, Till, additional, Coufal, Nicole, additional, Levy, Michael, additional, Malicki, Denise, additional, Nahas, Shareef, additional, Snuderl, Matija, additional, Crawford, John, additional, Wechsler-Reya, Robert, additional, Mundlos, Stefan, additional, Schmitt, Anthony, additional, Carter, Hannah, additional, Michealraj, Kulandaimanuvel Antony, additional, Kumar, Sachin A, additional, Taylor, Michael D, additional, Rich, Jeremy, additional, Mesirov, Jill, additional, Pfister, Stefan P, additional, Ay, Ferhat, additional, Dixon, Jesse, additional, Kool, Marcel, additional, and Chavez, Lukas, additional
- Published
- 2022
- Full Text
- View/download PDF
54. Accurate genome-wide germline profiling from decade-old archival tissue DNA reveals the contribution of common variants to precancer disease outcome
- Author
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Nachmanson, Daniela, primary, Pagadala, Meghana, additional, Steward, Joseph, additional, Cheung, Callie, additional, Bruce, Lauryn Keeler, additional, Lee, Nicole Q., additional, O’Keefe, Thomas J., additional, Lin, Grace Y., additional, Hasteh, Farnaz, additional, Morris, Gerald P., additional, Carter, Hannah, additional, and Harismendy, Olivier, additional
- Published
- 2022
- Full Text
- View/download PDF
55. PRState: Incorporating Genetic Ancestry in Prostate Cancer Risk scores for African American Men
- Author
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Pagadala, Meghana, primary, Linscott, Joshua A., additional, Talwar, James, additional, Seibert, Tyler, additional, Rose, Brent, additional, Lynch, Julie, additional, Panizzon, Matthew S, additional, Hauger, Richard, additional, Hansen, Moritz H., additional, Sammon, Jesse D., additional, Hayn, Matthew H., additional, Kader, Karim, additional, Carter, Hannah K., additional, and Ryan, Stephen T., additional
- Published
- 2022
- Full Text
- View/download PDF
56. Evaluating a polygenic hazard score to predict risk of developing metastatic or fatal prostate cancer in the multi-ancestry Million Veteran Program cohort.
- Author
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Pagadala, Meghana, primary, Lynch, Julie Ann, additional, Karunamuni, Roshan, additional, Alba, Patrick, additional, Lee, Kyung Min, additional, Agiri, Fatai, additional, Anglin-Foote, Tori, additional, Carter, Hannah, additional, Gaziano, J. Michael, additional, Jasuja, Guneet Kaur, additional, Deka, Rishi, additional, Rose, Brent S., additional, Panizzon, Matthew, additional, Hauger, Richard, additional, and Seibert, Tyler, additional
- Published
- 2022
- Full Text
- View/download PDF
57. Discovery of Novel Trans-Ancestry and Ancestry-Specific Gene Loci for Total Testosterone in a Multi-Ancestral Analysis of Men in the Million Veteran Program
- Author
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Pagadala, Meghana S., primary, Jasuja, Guneet K., additional, Palnati, Madhuri, additional, Lynch, Julie, additional, Anglin, Tori, additional, Chang, Nelson, additional, Deka, Rishi, additional, Lee, Kyung Min, additional, Agiri, Fatai Y., additional, Seibert, Tyler M., additional, Rose, Brent S., additional, Carter, Hannah, additional, Panizzon, Matthew S., additional, and Hauger, Richard L., additional
- Published
- 2022
- Full Text
- View/download PDF
58. The landscape of extrachromosomal circular DNA in medulloblastoma
- Author
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Chapman, Owen S, primary, Luebeck, Jens, additional, Wani, Sameena, additional, Tiwari, Ashutosh, additional, Pagadala, Meghana, additional, Wang, Shanqing, additional, Larson, Jon D, additional, Lange, Joshua T, additional, Wong, Ivy Tsz-Lo, additional, Dehkordi, Siavash R, additional, Chandran, Sahaana, additional, Adam, Miriam, additional, Lin, Yingxi, additional, Juarez, Edwin, additional, Robinson, James T, additional, Sridhar, Sunita, additional, Malicki, Denise M, additional, Coufal, Nicole, additional, Levy, Michael, additional, Crawford, John R, additional, Pomeroy, Scott L, additional, Rich, Jeremy, additional, Scheuermann, Richard H, additional, Carter, Hannah, additional, Dixon, Jesse, additional, Mischel, Paul S, additional, Fraenkel, Ernest, additional, Wechsler-Reya, Robert J, additional, Bafna, Vineet, additional, Mesirov, Jill P, additional, and Chavez, Lukas, additional
- Published
- 2021
- Full Text
- View/download PDF
59. Polygenic risk of any, metastatic, and fatal prostate cancer in the Million Veteran Program
- Author
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Pagadala, Meghana S., primary, Lynch, Julie, additional, Karunamuni, Roshan, additional, Alba, Patrick R., additional, Lee, Kyung Min, additional, Agiri, Fatai Y., additional, Anglin, Tori, additional, Carter, Hannah, additional, Gaziano, J. Michael, additional, Jasuja, Guneet Kaur, additional, Deka, Rishi, additional, Rose, Brent S., additional, Panizzon, Matthew S., additional, Hauger, Richard L., additional, and Seibert, Tyler M., additional
- Published
- 2021
- Full Text
- View/download PDF
60. MP60-06 PROSTATE: INCORPORATING GENETIC ANCESTRY IN PROSTATE CANCER RISK SCORES FOR MEN OF AFRICAN DESCENT
- Author
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Linscott, Joshua, primary, Pagadala, Meghana, additional, Carter, Hannah, additional, Hayn, Matthew, additional, Hansen, Moritz, additional, Sammon, Jesse, additional, Kader, Karim, additional, and Ryan, Stephen, additional
- Published
- 2021
- Full Text
- View/download PDF
61. Autoimmune Alleles at the Major Histocompatibility Locus Modify Melanoma Susceptibility
- Author
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Talwar, James, primary, Laub, David, additional, Pagadala, Meghana, additional, Castro, Andrea, additional, Lewis, McKenna, additional, Luebeck, Georg E., additional, Morris, Gerald P., additional, Salem, Rany M., additional, Thompson, Wesley K., additional, Curtius, Kit, additional, Zanetti, Maurizio, additional, and Carter, Hannah, additional
- Published
- 2021
- Full Text
- View/download PDF
62. Abstract 828: Common genetic variants influence the composition of the tumor immune microenvironment and host anti-tumor responses
- Author
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Pagadala, Meghana, primary, Kim, Hyo, additional, Castro, Andrea, additional, Gonzalez-Colin, Cristian, additional, Wu, Victoria, additional, Cao, Steven, additional, Schmiedel, Benjamin, additional, Salem, Rany, additional, Gutkind, Silvio, additional, Thompson, Wes, additional, Pandurangan, Vijayanand, additional, and Carter, Hannah, additional
- Published
- 2021
- Full Text
- View/download PDF
63. SnpReportR: A Tool for Clinical Reporting of RNAseq Expression and Variants
- Author
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Khleifat, Ahmad Al, Smith, Jenny Leopoldina, Blobner, Brandon M, Miller, Sierra D, Kymberleigh Pagel, Nadkarni, Annie, Gainey, Melanie, Campbell, Patrick, Olaitan I Awe, Belmadani, Manuel, Cleary, Alan M, Cooley, Nicholas P, Dhuri, Shamika, Grosboillot, Virginie, Haas, Brian, Hokin, Samuel, Orlova, Ekaterina, Pagadala, Meghana, Price, Stephen, Rhodes, Adelaide, Kyla, Janice, Smith, Nascimento, Chaitanya Srinivasan, Zorman, Barry, and Busby, Ben
- Published
- 2021
- Full Text
- View/download PDF
64. Additional file 4 of Non-cancer-related pathogenic germline variants and expression consequences in ten-thousand cancer genomes
- Author
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Wang, Zishan, Fan, Xiao, Shen, Yufeng, Pagadala, Meghana S, Signer, Rebecca, Cygan, Kamil J., Fairbrother, William G., Carter, Hannah, Chung, Wendy K., and Huang, Kuan-lin
- Abstract
Additional file 4: Figure S1. Carrier frequency (left panel) and NC P/LPs count (right panel) of autosomal recessive (AR) and autosomal dominant (AD) genes across ancestries. Figure S2. Validation of identified NC P/LPs in TCGA by respective ancestral population in gnomAD. Figure S3. Validation of genes impacted by identified NC P/LPs in TCGA for respective ancestral population in gnomAD. Figure S4. Carrier density for the distribution of percentile expression of impacted genes. Figure S5. Lolliplots showing the positions of NC P/LPs in genes suggestively enriched with significant ASE NC P/LPs.
- Published
- 2021
- Full Text
- View/download PDF
65. Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Response.
- Author
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Zhang, Ping, Zhang, Ping, Kitchen-Smith, Isaac, Xiong, Lingyun, Stracquadanio, Giovanni, Brown, Katherine, Richter, Philipp H, Wallace, Marsha D, Bond, Elisabeth, Sahgal, Natasha, Moore, Samantha, Nornes, Svanhild, De Val, Sarah, Surakhy, Mirvat, Sims, David, Wang, Xuting, Bell, Douglas A, Zeron-Medina, Jorge, Jiang, Yanyan, Ryan, Anderson J, Selfe, Joanna L, Shipley, Janet, Kar, Siddhartha, Pharoah, Paul D, Loveday, Chey, Jansen, Rick, Grochola, Lukasz F, Palles, Claire, Protheroe, Andrew, Millar, Val, Ebner, Daniel V, Pagadala, Meghana, Blagden, Sarah P, Maughan, Timothy S, Domingo, Enric, Tomlinson, Ian, Turnbull, Clare, Carter, Hannah, Bond, Gareth L, Zhang, Ping, Zhang, Ping, Kitchen-Smith, Isaac, Xiong, Lingyun, Stracquadanio, Giovanni, Brown, Katherine, Richter, Philipp H, Wallace, Marsha D, Bond, Elisabeth, Sahgal, Natasha, Moore, Samantha, Nornes, Svanhild, De Val, Sarah, Surakhy, Mirvat, Sims, David, Wang, Xuting, Bell, Douglas A, Zeron-Medina, Jorge, Jiang, Yanyan, Ryan, Anderson J, Selfe, Joanna L, Shipley, Janet, Kar, Siddhartha, Pharoah, Paul D, Loveday, Chey, Jansen, Rick, Grochola, Lukasz F, Palles, Claire, Protheroe, Andrew, Millar, Val, Ebner, Daniel V, Pagadala, Meghana, Blagden, Sarah P, Maughan, Timothy S, Domingo, Enric, Tomlinson, Ian, Turnbull, Clare, Carter, Hannah, and Bond, Gareth L
- Abstract
Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.
- Published
- 2021
66. SnpReportR: A Tool for Clinical Reporting of RNAseq Expression and Variants
- Author
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Al Khleifat, Ahmad, primary, Smith, Jenny Leopoldina, additional, Blobner, Brandon, additional, Miller, Sierra, additional, Pagel, Kymberleigh, additional, Nadkarni, Annie, additional, Gainey, Melanie, additional, Campbell, Patrick, additional, Awe, Olaitan, additional, Belmadani, Manuel, additional, Cleary, Alan M., additional, Cooley, Nicholas, additional, Dhuri, Shamika, additional, Grosboillot, Virginie, additional, Haas, Brian W., additional, Hokin, Sam, additional, Orlova, Ekaterina, additional, Pagadala, Meghana, additional, Price, Stephen, additional, Rhodes, Adelaide, additional, Smith, Janice Kyla Nascimento, additional, Srinivasan, Chaitanya, additional, Zorman, Barry, additional, and Busby, Ben, additional
- Published
- 2021
- Full Text
- View/download PDF
67. Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response
- Author
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Pagadala, Meghana, primary, Wu, Victoria H., additional, Pérez-Guijarro, Eva, additional, Kim, Hyo, additional, Castro, Andrea, additional, Talwar, James, additional, Sears, Timothy, additional, Gonzalez-Colin, Cristian, additional, Cao, Steven, additional, Schmiedel, Benjamin J., additional, Goudarzi, Shervin, additional, Kirani, Divya, additional, Salem, Rany M., additional, Morris, Gerald P., additional, Harismendy, Olivier, additional, Patel, Sandip Pravin, additional, Mesirov, Jill P., additional, Zanetti, Maurizio, additional, Day, Chi-Ping, additional, Fan, Chun Chieh, additional, Thompson, Wesley K., additional, Merlino, Glenn, additional, Gutkind, J. Silvio, additional, Vijayanand, Pandurangan, additional, and Carter, Hannah, additional
- Published
- 2021
- Full Text
- View/download PDF
68. EPEN-04. ONCOGENIC 3D TUMOR GENOME ORGANIZATION IDENTIFIES NEW THERAPEUTIC TARGETS IN EPENDYMOMA
- Author
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Okonechnikov, Konstantin, primary, Hübner, Jens-Martin, additional, Chapman, Owen, additional, Chakraborty, Abhijit, additional, Pagadala, Meghana, additional, Bump, Rosalind, additional, Chandran, Sahaana, additional, Kraft, Katerina, additional, Hidalgo, Rocio Acuna, additional, Mundlos, Stefan, additional, Wechsler-Reya, Robert, additional, Juarez, Edwin F, additional, Coufal, Nicole, additional, Levy, Michael, additional, Crawford, John, additional, Pajtler, Kristian, additional, Reid, Derek, additional, Schmitt, Anthony, additional, Carter, Hannah, additional, Ay, Ferhat, additional, Dixon, Jesse, additional, Mesirov, Jill, additional, Pfister, Stefan M, additional, Kool, Marcel, additional, and Chavez, Lukas, additional
- Published
- 2020
- Full Text
- View/download PDF
69. Oncogenic 3D genome conformations identify novel therapeutic targets in ependymoma
- Author
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Okonechnikov, Konstantin, primary, Camgoz, Aylin, additional, Park, Donglim Esther, additional, Chapman, Owen, additional, Hübner, Jens-Martin, additional, Chakraborty, Abhijit, additional, Pagadala, Meghana, additional, Bump, Rosalind, additional, Chandran, Sahaana, additional, Kraft, Katerina, additional, Acuna-Hidalgo, Rocio, additional, Reid, Derek, additional, Juarez, Edwin F., additional, Robinson, James T., additional, Pajtler, Kristian W., additional, Mauermann, Monika, additional, Milde, Till, additional, Coufal, Nicole G., additional, Levy, Michael, additional, Malicki, Denise, additional, Nahas, Shareef, additional, Snuderl, Matija, additional, Crawford, John, additional, Wechsler-Reya, Robert J., additional, Mundlos, Stefan, additional, Schmitt, Anthony, additional, Carter, Hannah, additional, Michaelraj, Kulandaimanuvel Antony, additional, Kumar, Sachin A., additional, Taylor, Michael D., additional, Rich, Jeremy, additional, Buchholz, Frank, additional, Mesirov, Jill P., additional, Pfister, Stefan M., additional, Ay, Ferhat, additional, Dixon, Jesse R., additional, Kool, Marcel, additional, and Chavez, Lukas, additional
- Published
- 2020
- Full Text
- View/download PDF
70. Germline and somatic genetic variants in the p53 pathway interact to affect cancer risk, progression and drug response
- Author
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Zhang, Ping, primary, Kitchen-Smith, Isaac, additional, Xiong, Lingyun, additional, Stracquadanio, Giovanni, additional, Brown, Katherine, additional, Richter, Philipp, additional, Wallace, Marsha, additional, Bond, Elisabeth, additional, Sahgal, Natasha, additional, Moore, Samantha, additional, Nornes, Svanhild, additional, De Val, Sarah, additional, Surakhy, Mirvat, additional, Sims, David, additional, Wang, Xuting, additional, Bell, Douglas A., additional, Zeron-Medina, Jorge, additional, Jiang, Yanyan, additional, Ryan, Anderson, additional, Selfe, Joanna, additional, Shipley, Janet, additional, Kar, Siddhartha, additional, Pharoah, Paul, additional, Loveday, Chey, additional, Jansen, Rick, additional, Grochola, Lukasz F., additional, Palles, Claire, additional, Protheroe, Andrew, additional, Millar, Val, additional, Ebner, Daniel, additional, Pagadala, Meghana, additional, Blagden, Sarah P., additional, Maughan, Tim, additional, Domingo, Enric, additional, Tomlinson, Ian, additional, Turnbull, Clare, additional, Carter, Hannah, additional, and Bond, Gareth, additional
- Published
- 2019
- Full Text
- View/download PDF
71. Author response: Domain-swapped T cell receptors improve the safety of TCR gene therapy
- Author
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Bethune, Michael T, primary, Gee, Marvin H, additional, Bunse, Mario, additional, Lee, Mark S, additional, Gschweng, Eric H, additional, Pagadala, Meghana S, additional, Zhou, Jing, additional, Cheng, Donghui, additional, Heath, James R, additional, Kohn, Donald B, additional, Kuhns, Michael S, additional, Uckert, Wolfgang, additional, and Baltimore, David, additional
- Published
- 2016
- Full Text
- View/download PDF
72. Osteoclast Activated FoxP3+ CD8+ T-Cells Suppress Bone Resorption in vitro
- Author
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Buchwald, Zachary S., primary, Kiesel, Jennifer R., additional, DiPaolo, Richard, additional, Pagadala, Meghana S., additional, and Aurora, Rajeev, additional
- Published
- 2012
- Full Text
- View/download PDF
73. Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Response
- Author
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Zhang, Ping, Kitchen-Smith, Isaac, Xiong, Lingyun, Stracquadanio, Giovanni, Brown, Katherine, Richter, Philipp H, Wallace, Marsha D, Bond, Elisabeth, Sahgal, Natasha, Moore, Samantha, Nornes, Svanhild, De Val, Sarah, Surakhy, Mirvat, Sims, David, Wang, Xuting, Bell, Douglas A, Zeron-Medina, Jorge, Jiang, Yanyan, Ryan, Anderson J, Selfe, Joanna L, Shipley, Janet, Kar, Siddhartha, Pharoah, Paul D, Loveday, Chey, Jansen, Rick, Grochola, Lukasz F, Palles, Claire, Protheroe, Andrew, Millar, Val, Ebner, Daniel V, Pagadala, Meghana, Blagden, Sarah P, Maughan, Timothy S, Domingo, Enric, Tomlinson, Ian, Turnbull, Clare, Carter, Hannah, and Bond, Gareth L
- Subjects
Male ,Carcinogenesis ,Mutation, Missense ,Mice, Nude ,Antineoplastic Agents ,Polymorphism, Single Nucleotide ,Biomarkers, Pharmacological ,Mice ,Risk Factors ,Cell Line, Tumor ,Neoplasms ,Animals ,Humans ,Genetic Predisposition to Disease ,Germ-Line Mutation ,Mice, Inbred BALB C ,Prognosis ,3. Good health ,Treatment Outcome ,Drug Resistance, Neoplasm ,Case-Control Studies ,Disease Progression ,Female ,Tumor Suppressor Protein p53 ,Genome-Wide Association Study ,Signal Transduction - Abstract
Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.
74. Germline and somatic genetic variants in the p53 pathway interact to affect cancer risk, progression, and drug response
- Author
-
Ping Zhang, Enric Domingo, Daniel Ebner, Marsha D. Wallace, Natasha Sahgal, Hannah Carter, Andrew Protheroe, Philipp Harald Richter, Paul D.P. Pharoah, Janet Shipley, Val Millar, Lingyun Xiong, Katherine A. Brown, Rick Jansen, Svanhild Nornes, Jorge Zeron-Medina, Anderson J. Ryan, Ian Tomlinson, Joanna Selfe, Isaac Kitchen-Smith, Elisabeth E. Bond, Sarah P. Blagden, Chey Loveday, David Sims, Sarah De Val, Tim Maughan, Douglas A. Bell, Samantha Moore, Gareth L. Bond, Meghana Pagadala, Yanyan Jiang, Claire Palles, Giovanni Stracquadanio, Siddhartha Kar, Xuting Wang, Mirvat Surakhy, Clare Turnbull, Lukasz Filip Grochola, Zhang, Ping [0000-0001-7063-7769], Xiong, Lingyun [0000-0003-4594-4120], Surakhy, Mirvat [0000-0001-7101-984X], Ryan, Anderson J [0000-0001-6241-7969], Pharoah, Paul D [0000-0001-8494-732X], Loveday, Chey [0000-0002-2291-372X], Grochola, Lukasz F [0000-0002-7606-7266], Palles, Claire [0000-0002-9670-2263], Ebner, Daniel V [0000-0002-6495-7026], Pagadala, Meghana [0000-0002-7591-6035], Blagden, Sarah P [0000-0001-8783-3491], Maughan, Timothy S [0000-0002-0580-5065], Domingo, Enric [0000-0003-4390-8767], Tomlinson, Ian [0000-0003-3037-1470], Carter, Hannah [0000-0002-1729-2463], Apollo - University of Cambridge Repository, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, and APH - Mental Health
- Subjects
0301 basic medicine ,Male ,Cancer Research ,Somatic cell ,Carcinogenesis ,Nude ,Drug Resistance ,Genome-wide association study ,Bioinformatics ,medicine.disease_cause ,Germline ,Biomarkers, Pharmacological ,Mice ,0302 clinical medicine ,Risk Factors ,Neoplasms ,2.1 Biological and endogenous factors ,Aetiology ,Inbred BALB C ,Cancer ,Mutation ,0303 health sciences ,Mice, Inbred BALB C ,Tumor ,Single Nucleotide ,Prognosis ,3. Good health ,Treatment Outcome ,Oncology ,030220 oncology & carcinogenesis ,Disease Progression ,Female ,Patient Safety ,Biotechnology ,Signal Transduction ,Oncology and Carcinogenesis ,Mutation, Missense ,Mice, Nude ,Single-nucleotide polymorphism ,Antineoplastic Agents ,Biology ,Affect (psychology) ,Polymorphism, Single Nucleotide ,Article ,Cell Line ,03 medical and health sciences ,Clinical Research ,Cell Line, Tumor ,Genetic variation ,medicine ,Genetics ,SNP ,Animals ,Humans ,Genetic Predisposition to Disease ,Oncology & Carcinogenesis ,Polymorphism ,Gene ,Germ-Line Mutation ,030304 developmental biology ,Prevention ,Pharmacological ,Human Genome ,medicine.disease ,030104 developmental biology ,Drug Resistance, Neoplasm ,Case-Control Studies ,Cancer research ,Neoplasm ,Missense ,Tumor Suppressor Protein p53 ,Digestive Diseases ,Biomarkers ,Genome-Wide Association Study - Abstract
Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. Significance: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.
- Published
- 2021
- Full Text
- View/download PDF
75. Integrated Germline and Somatic Features Reveal Divergent Immune Pathways Driving Response to Immune Checkpoint Blockade.
- Author
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Sears TJ, Pagadala MS, Castro A, Lee KH, Kong J, Tanaka K, Lippman SM, Zanetti M, and Carter H
- Subjects
- Humans, Machine Learning, Lymphocyte Activation Gene 3 Protein, Histocompatibility Antigens Class I immunology, Histocompatibility Antigens Class II immunology, Antigens, Neoplasm immunology, Biomarkers, Tumor, Antigens, CD immunology, T Follicular Helper Cells immunology, Lymphocytes, Tumor-Infiltrating immunology, Lymphocytes, Tumor-Infiltrating metabolism, Immune Checkpoint Inhibitors therapeutic use, Immune Checkpoint Inhibitors pharmacology, Tumor Microenvironment immunology, Neoplasms immunology, Neoplasms drug therapy
- Abstract
Immune checkpoint blockade (ICB) has revolutionized cancer treatment; however, the mechanisms determining patient response remain poorly understood. Here, we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher infiltration of T-follicular helper cells had responses even in the presence of defects in the MHC class-I (MHC-I). Further investigation uncovered different ICB responses in tumors when responses were reliant on MHC-I versus MHC-II neoantigens. Despite similar response rates, MHC II-reliant responses were associated with significantly longer durable clinical benefits (discovery: median overall survival of 63.6 vs. 34.5 months; P = 0.0074; validation: median overall survival of 37.5 vs. 33.1 months; P = 0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC II-reliant but not MHC I-reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses., (©2024 The Authors; Published by the American Association for Cancer Research.)
- Published
- 2024
- Full Text
- View/download PDF
76. Genetic risk and likelihood of prostate cancer detection on first biopsy by ancestry.
- Author
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Lee KM, Nelson TJ, Bryant A, Teerlink CC, Gulati R, Pagadala MS, Tcheandjieu C, Pridgen KM, DuVall SL, Yamoah K, Vassy JL, Seibert TM, Hauger RL, Rose BS, and Lynch JA
- Subjects
- Humans, Male, Middle Aged, Aged, Retrospective Studies, Biopsy, Cross-Sectional Studies, White People genetics, White People statistics & numerical data, Risk Factors, Risk Assessment, Black or African American genetics, Black or African American statistics & numerical data, Prostatic Neoplasms genetics, Prostatic Neoplasms pathology, Prostatic Neoplasms diagnosis, Genetic Predisposition to Disease
- Abstract
Despite differences in prostate cancer risk across ancestry groups, relative performance of prostate cancer genetic risks scores (GRS) for positive biopsy prediction in different ancestry groups is unknown. This cross-sectional retrospective analysis examines the association between a polygenic hazard score (PHS290) and risk of prostate cancer diagnosis upon first biopsy in male veterans using 2-sided tests. Our analysis included 36 717 veterans (10 297 of African ancestry). Unadjusted rates of positive first prostate biopsy increased with higher genetic risk (low risk: 34%, high risk: 58%; P < .001). Among men of African ancestry, higher genetic risk was associated with increased prostate cancer detection on first biopsy (odds ratio = 2.18, 95% confidence interval = 1.93 to 2.47), but the effect was stronger among men of European descent (odds ratio = 3.89, 95% confidence interval = 3.62 to 4.18). These findings suggest that incorporating genetic risk into prediction models could better personalize biopsy decisions, although further study is needed to achieve equitable genetic risk stratification among ancestry groups., (Published by Oxford University Press 2024.)
- Published
- 2024
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77. Radiation and anti-PD-L1 synergize by stimulating a stem-like T cell population in the tumor-draining lymph node.
- Author
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Shen Y, Connolly E, Aiello M, Zhou C, Chappa P, Song H, Tippitak P, Clark T, Cardenas M, Prokhnevska N, Mariniello A, Pagadala MS, Dhere VR, Rafiq S, Kesarwala AH, Orthwein A, Thomas SN, Khan MK, Brandon Dixon J, Lesinski GB, Lowe MC, Kissick H, Yu DS, Paulos CM, Schmitt NC, and Buchwald ZS
- Abstract
Radiotherapy (RT) and anti-PD-L1 synergize to enhance local and distant (abscopal) tumor control. However, clinical results in humans have been variable. With the goal of improving clinical outcomes, we investigated the underlying synergistic mechanism focusing on a CD8+ PD-1+ Tcf-1+ stem-like T cell subset in the tumor-draining lymph node (TdLN). Using murine melanoma models, we found that RT + anti-PD-L1 induces a novel differentiation program in the TdLN stem-like population which leads to their expansion and differentiation into effector cells within the tumor. Our data indicate that optimal synergy between RT + anti-PD-L1 is dependent on the TdLN stem-like T cell population as either blockade of TdLN egress or specific stem-like T cell depletion reduced tumor control. Together, these data demonstrate a multistep stimulation of stem-like T cells following combination therapy which is initiated in the TdLN and completed in the tumor., Competing Interests: DECLARATION OF INTERESTS N.C.S. has a consulting role at Checkpoint Surgical, Sensorion, and Synergy Research, Inc, is a member of the advisory board of Regeneron, receives book royalties from Plural Publishing, and has received funding from Astex Pharmaceuticals. GBL has received research funding through a sponsored research agreement between Emory University and Merck and Co., Bristol-Myers Squibb, Boerhinger-Ingelheim, and Vaccinex.
- Published
- 2024
- Full Text
- View/download PDF
78. Integrated germline and somatic features reveal divergent immune pathways driving ICB response.
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Sears T, Pagadala M, Castro A, Lee KH, Kong J, Tanaka K, Lippman S, Zanetti M, and Carter H
- Abstract
Immune Checkpoint Blockade (ICB) has revolutionized cancer treatment, however mechanisms determining patient response remain poorly understood. Here we used machine learning to predict ICB response from germline and somatic biomarkers and interpreted the learned model to uncover putative mechanisms driving superior outcomes. Patients with higher T follicular helper infiltrates were robust to defects in the class-I Major Histocompatibility Complex (MHC-I). Further investigation uncovered different ICB responses in MHC-I versus MHC-II neoantigen reliant tumors across patients. Despite similar response rates, MHC-II reliant responses were associated with significantly longer durable clinical benefit (Discovery: Median OS=63.6 vs. 34.5 months P=0.0074; Validation: Median OS=37.5 vs. 33.1 months, P=0.040). Characteristics of the tumor immune microenvironment reflected MHC neoantigen reliance, and analysis of immune checkpoints revealed LAG3 as a potential target in MHC-II but not MHC-I reliant responses. This study highlights the value of interpretable machine learning models in elucidating the biological basis of therapy responses., Competing Interests: Disclosures M.Z. is board member of Invectys Inc. All other authors declare they have no competing interests. S.M.L. is on the Biological Dynamics, Inc. Scientific Advisory Board and is a co-founder of io9
- Published
- 2024
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79. The GPCR-Gα s -PKA signaling axis promotes T cell dysfunction and cancer immunotherapy failure.
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Wu VH, Yung BS, Faraji F, Saddawi-Konefka R, Wang Z, Wenzel AT, Song MJ, Pagadala MS, Clubb LM, Chiou J, Sinha S, Matic M, Raimondi F, Hoang TS, Berdeaux R, Vignali DAA, Iglesias-Bartolome R, Carter H, Ruppin E, Mesirov JP, and Gutkind JS
- Subjects
- Mice, Animals, Signal Transduction, Mice, Transgenic, Immunotherapy, Tumor Microenvironment, CD8-Positive T-Lymphocytes, Neoplasms
- Abstract
Immune checkpoint blockade (ICB) targeting PD-1 and CTLA-4 has revolutionized cancer treatment. However, many cancers do not respond to ICB, prompting the search for additional strategies to achieve durable responses. G-protein-coupled receptors (GPCRs) are the most intensively studied drug targets but are underexplored in immuno-oncology. Here, we cross-integrated large singe-cell RNA-sequencing datasets from CD8
+ T cells covering 19 distinct cancer types and identified an enrichment of Gαs -coupled GPCRs on exhausted CD8+ T cells. These include EP2 , EP4 , A2A R, β1 AR and β2 AR, all of which promote T cell dysfunction. We also developed transgenic mice expressing a chemogenetic CD8-restricted Gαs -DREADD to activate CD8-restricted Gαs signaling and show that a Gαs -PKA signaling axis promotes CD8+ T cell dysfunction and immunotherapy failure. These data indicate that Gαs -GPCRs are druggable immune checkpoints that might be targeted to enhance the response to ICB immunotherapies., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)- Published
- 2023
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- View/download PDF
80. Prevalence, Morbidity, and Mortality of 1,609 Men with Sex Chromosome Aneuploidy: Results from the Diverse Million Veteran Program Cohort.
- Author
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Davis SM, Teerlink C, Lynch JA, Gorman BR, Pagadala M, Liu A, Panizzon MS, Merritt VC, Genovese G, Pyarajan S, Ross JL, and Hauger RL
- Abstract
Importance: The reported phenotypes of men with 47,XXY and 47,XYY syndromes include tall stature, multisystem comorbidities, and poor health-related quality of life (HRQoL). However, knowledge about these sex chromosome aneuploidy (SCA) conditions has been derived from studies in the <15% of patients who are clinically diagnosed and also lack diversity in age and genetic ancestry., Objectives: Determine the prevalence of clinically diagnosed and undiagnosed X or Y chromosome aneuploidy among men enrolled in the Million Veteran Program (MVP); describe military service metrics of men with SCAs; compare morbidity and mortality outcomes between men with SCA with and without a clinical diagnosis to matched controls., Design: Cross-sectional, case-control., Setting: United States Veterans Administration Healthcare System., Participants: Biologic males enrolled in the MVP biobank with genomic identification of an additional X or Y chromosome (cases); controls matched 1:5 on sex, age, and genetic ancestry., Main Outcomes and Measures: Prevalence of men with SCAs from genomic analysis; clinical SCA diagnosis; Charlson Comorbidity Index (CCI); rates of outpatient, inpatient, and emergency encounters per year; self-reported health outcomes; standardized mortality ratio (SMR)., Results: An additional X or Y chromosome was present in 145 and 125 per 100,000 males in the MVP, respectively, with the highest prevalence among men with European and East Asian ancestry. At a mean age of 61±12 years, 74% of male veterans with 47,XXY and >99% with 47,XYY remained undiagnosed. Individuals with 47,XXY (n=862) and 47,XYY (n=747) had similar military service history, all-cause SMR, and age of death compared to matched controls. CCI and healthcare utilization were higher among individuals with SCA, while several measures of HRQoL were lower. Men with a clinical diagnosis of 47,XXY had higher healthcare utilization but lower comorbidity score compared to those undiagnosed., Conclusion and Relevance: One in 370 males in the MVP cohort have SCA, a prevalence comparable to estimates in the general population. While these men have successfully served in the military, they have higher morbidity and report poorer HRQoL with aging. Longer longitudinal follow-up of this sample will be informative for clinical and patient-reported outcomes, the role of ancestry, and mortality statistics., Key Points: Comparable to the general population, approximately 1 in 370 male veterans have a sex chromosome aneuploidy, but most are undiagnosed.Men with X or Y chromosome aneuploidy successfully complete US miliary duty with similar service history compared to their 46,XY peers.Medical comorbidities and healthcare utilization metrics are higher in male veterans with 47,XXY and 47,XYY during aging, however life expectancy is similar to matched controls.
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- 2023
- Full Text
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81. Epigenetic Germline Variants Predict Cancer Prognosis and Risk and Distribute Uniquely in Topologically Associating Domains.
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Goudarzi S, Pagadala M, Klie A, Talwar JV, and Carter H
- Abstract
Cancer is a highly heterogeneous disease caused by genetic and epigenetic alterations in normal cells. A recent study uncovered methylation quantitative trait loci (meQTLs) associated with different levels of local DNA methylation in cancers. Here, we investigated whether the distribution of cancer meQTLs reflected functional organization of the genome in the form of chromatin topologically associated domains (TADs), and evaluated whether cancer meQTLs near known driver genes have the potential to influence cancer risk or progression. At TAD boundaries, we observed differences in the distribution of meQTLs when one or both of the adjacent TADs was transcriptionally active, with higher densities near inactive TADs. Furthermore, we found differences in cancer meQTL distributions in active versus inactive TADs and observed an enrichment of meQTLs in active TADs near tumor suppressors, whereas there was a depletion of such meQTLs near oncogenes. Several meQTLs were associated with cancer risk in the UKBioBank, and we were able to reproduce breast cancer risk associations in the DRIVE cohort. Survival analysis in TCGA implicated a number of meQTLs in 13 tumor types. In 10 of these, polygenic meQTL scores were associated with increased hazard in a CoxPH analysis. Risk and survival-associated meQTLs tended to affect cancer genes involved in DNA damage repair and cellular adhesion and reproduced cancer-specific associations reported in prior literature. In summary, this study provides evidence that genetic variants that influence local DNA methylation are affected by chromatin structure and can impact tumor evolution.
- Published
- 2023
- Full Text
- View/download PDF
82. Agent Orange exposure and prostate cancer risk in the Million Veteran Program.
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Lui AJ, Pagadala MS, Zhong AY, Lynch J, Karunamuni R, Lee KM, Plym A, Rose BS, Carter H, Kibel AS, DuVall SL, Gaziano JM, Panizzon MS, Hauger RL, and Seibert TM
- Abstract
Purpose: Exposure to Agent Orange, a known carcinogen, might increase risk of prostate cancer (PCa). We sought to investigate the association of Agent Orange exposure and PCa risk when accounting for race/ethnicity, family history, and genetic risk in a diverse population of US Vietnam War veterans., Methods & Materials: This study utilized the Million Veteran Program (MVP), a national, population-based cohort study of United States military veterans conducted 2011-2021 with 590,750 male participants available for analysis. Agent Orange exposure was obtained using records from the Department of Veterans Affairs (VA) using the US government definition of Agent Orange exposure: active service in Vietnam while Agent Orange was in use. Only veterans who were on active duty (anywhere in the world) during the Vietnam War were included in this analysis (211,180 participants). Genetic risk was assessed via a previously validated polygenic hazard score calculated from genotype data. Age at diagnosis of any PCa, diagnosis of metastatic PCa, and death from PCa were assessed via Cox proportional hazards models., Results: Exposure to Agent Orange was associated with increased PCa diagnosis (HR 1.04, 95% CI 1.01-1.06, p=0.003), primarily among Non-Hispanic White men (HR 1.09, 95% CI 1.06- 1.12, p<0.001). When accounting for race/ethnicity and family history, Agent Orange exposure remained an independent risk factor for PCa diagnosis (HR 1.06, 95% CI 1.04-1.09, p<0.05). Univariable associations of Agent Orange exposure with PCa metastasis (HR 1.08, 95% CI 0.99-1.17) and PCa death (HR 1.02, 95% CI 0.84-1.22) did not reach significance on multivariable analysis. Similar results were found when accounting for polygenic hazard score., Conclusions: Among US Vietnam War veterans, Agent Orange exposure is an independent risk factor for PCa diagnosis, though associations with PCa metastasis or death are unclear when accounting for race/ethnicity, family history, and/or polygenic risk.
- Published
- 2023
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83. Immune niches in brain metastases contain TCF1+ stem-like T cells, are associated with disease control and are modulated by preoperative SRS.
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Jansen CS, Prabhu RS, Pagadala MS, Chappa P, Goyal S, Zhou C, Neill SG, Prokhnevska N, Cardenas M, Hoang KB, Zhong J, Torres M, Logan S, Olson JJ, Nduom EK, Del Balzo L, Patel K, Burri SH, Asher AL, Wilkinson S, Lake R, Higgins KA, Patel P, Dhere V, Sowalsky AG, Khan MK, Kissick H, and Buchwald ZS
- Abstract
The CD8
+ T-cell response is prognostic for survival outcomes in several tumor types. However, whether this extends to tumors in the brain, an organ with barriers to T cell entry, remains unclear. Here, we analyzed immune infiltration in 67 brain metastasis (BrM) and found high frequencies of PD1+ TCF1+ stem-like CD8+ T-cells and TCF1- effector-like cells. Importantly, the stem-like cells aggregate with antigen presenting cells in immune niches, and niches were prognostic for local disease control. Standard of care for BrM is resection followed by stereotactic radiosurgery (SRS), so to determine SRS's impact on the BrM immune response, we examined 76 BrM treated with pre-operative SRS (pSRS). pSRS acutely reduced CD8+ T cells at 3 days. However, CD8+ T cells rebounded by day 6, driven by increased frequency of effector-like cells. This suggests that the immune response in BrM can be regenerated rapidly, likely by the local TCF1+ stem-like population.- Published
- 2023
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84. Response to Haiman, Kote-Jarai, Darst et al.
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Seibert TM, Pagadala MS, Lynch J, Karunamuni R, Carter H, Rose BS, and Hauger RL
- Published
- 2023
- Full Text
- View/download PDF
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