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Showing 1 to 12 of 34 entries
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Proteomics on Fixed Tissue Specimens - A Review.

Current proteomics

Reimel BA, Pan S, May DH, Shaffer SA, Goodlett DR, McIntosh MW, Yerian LM, Bronner MP, Chen R, Brentnall TA.
PMID: 19829741
Curr Proteomics. 2009 Apr 01;6(1):63-69. doi: 10.2174/157016409787847420.

The vast majority of clinical tissue samples are formalin-fixed and paraffin-preserved. This type of preservation has been considered an obstacle to protein extraction from these tissues. However, these are the very tissue samples that have associated patient histories, diagnoses...

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Reimel BA, Pan S, May DH, et al. Proteomics on Fixed Tissue Specimens - A Review. Curr Proteomics. 2009;6(1):63-69doi: 10.2174/157016409787847420.
Reimel, B. A., Pan, S., May, D. H., Shaffer, S. A., Goodlett, D. R., McIntosh, M. W., Yerian, L. M., Bronner, M. P., Chen, R., & Brentnall, T. A. (2009). Proteomics on Fixed Tissue Specimens - A Review. Current proteomics, 6(1), 63-69. https://doi.org/10.2174/157016409787847420
Reimel, Beth Ann, et al. "Proteomics on Fixed Tissue Specimens - A Review." Current proteomics vol. 6,1 (2009): 63-69. doi: https://doi.org/10.2174/157016409787847420
Reimel BA, Pan S, May DH, Shaffer SA, Goodlett DR, McIntosh MW, Yerian LM, Bronner MP, Chen R, Brentnall TA. Proteomics on Fixed Tissue Specimens - A Review. Curr Proteomics. 2009 Apr 01;6(1):63-69. doi: 10.2174/157016409787847420. PMID: 19829741; PMCID: PMC2760948.
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Proteins That Underlie Neoplastic Progression of Ulcerative Colitis.

Proteomics. Clinical applications

Brentnall TA, Pan S, Bronner MP, Crispin DA, Mirzaei H, Cooke K, Tamura Y, Nikolskaya T, Jebailey L, Goodlett DR, McIntosh M, Aebersold R, Rabinovitch PS, Chen R.
PMID: 20098637
Proteomics Clin Appl. 2009 Sep 14;3(11):1326. doi: 10.1002/prca.200900061.

Patients with ulcerative colitis (UC) have an increased risk for developing colorectal cancer. Because UC tumorigenesis is associated with genomic field defects that can extend throughout the entire colon, including the non-dysplastic mucosa; we hypothesized that the same field...

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Brentnall TA, Pan S, Bronner MP, et al. Proteins That Underlie Neoplastic Progression of Ulcerative Colitis. Proteomics Clin Appl. 2009;3(11):1326doi: 10.1002/prca.200900061.
Brentnall, T. A., Pan, S., Bronner, M. P., Crispin, D. A., Mirzaei, H., Cooke, K., Tamura, Y., Nikolskaya, T., Jebailey, L., Goodlett, D. R., McIntosh, M., Aebersold, R., Rabinovitch, P. S., & Chen, R. (2009). Proteins That Underlie Neoplastic Progression of Ulcerative Colitis. Proteomics. Clinical applications, 3(11), 1326. https://doi.org/10.1002/prca.200900061
Brentnall, Teresa A, et al. "Proteins That Underlie Neoplastic Progression of Ulcerative Colitis." Proteomics. Clinical applications vol. 3,11 (2009): 1326. doi: https://doi.org/10.1002/prca.200900061
Brentnall TA, Pan S, Bronner MP, Crispin DA, Mirzaei H, Cooke K, Tamura Y, Nikolskaya T, Jebailey L, Goodlett DR, McIntosh M, Aebersold R, Rabinovitch PS, Chen R. Proteins That Underlie Neoplastic Progression of Ulcerative Colitis. Proteomics Clin Appl. 2009 Sep 14;3(11):1326. doi: 10.1002/prca.200900061. PMID: 20098637; PMCID: PMC2809935.
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A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer.

JAMA oncology

Sun L, Brentnall A, Patel S, Buist DSM, Bowles EJA, Evans DGR, Eccles D, Hopper J, Li S, Southey M, Duffy S, Cuzick J, Dos Santos Silva I, Miners A, Sadique Z, Yang L, Legood R, Manchanda R.
PMID: 31580391
JAMA Oncol. 2019 Oct 03; doi: 10.1001/jamaoncol.2019.3323. Epub 2019 Oct 03.

IMPORTANCE: Moving to multigene testing for all women with breast cancer (BC) could identify many more mutation carriers who can benefit from precision prevention. However, the cost-effectiveness of this approach remains unaddressed.OBJECTIVE: To estimate incremental lifetime effects, costs, and...

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Sun L, Brentnall A, Patel S, et al. A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer. JAMA Oncol. 2019;doi: 10.1001/jamaoncol.2019.3323.
Sun, L., Brentnall, A., Patel, S., Buist, D. S. M., Bowles, E. J. A., Evans, D. G. R., Eccles, D., Hopper, J., Li, S., Southey, M., Duffy, S., Cuzick, J., Dos Santos Silva, I., Miners, A., Sadique, Z., Yang, L., Legood, R., & Manchanda, R. (2019). A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer. JAMA oncology, . https://doi.org/10.1001/jamaoncol.2019.3323
Sun, Li, et al. "A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer." JAMA oncology vol. (2019). doi: https://doi.org/10.1001/jamaoncol.2019.3323
Sun L, Brentnall A, Patel S, Buist DSM, Bowles EJA, Evans DGR, Eccles D, Hopper J, Li S, Southey M, Duffy S, Cuzick J, Dos Santos Silva I, Miners A, Sadique Z, Yang L, Legood R, Manchanda R. A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer. JAMA Oncol. 2019 Oct 03; doi: 10.1001/jamaoncol.2019.3323. Epub 2019 Oct 03. PMID: 31580391; PMCID: PMC6777250.
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Gene Expression and Proteomic Analysis of Pancreatic Cancer: a Recent Update.

Cancer genomics & proteomics

Chen RU, Pan S, Crispin DA, Brentnall TA.
PMID: 31394637
Cancer Genomics Proteomics. 2006 Jan-Feb;3(1):1-9. Epub 2006 Jan 01.

Pancreatic cancer is a lethal disease for which little progress in early diagnosis or treatment has been made for many decades. Better biomarkers are urgently needed for early detection while the cancer is potentially curable. Recently, expression profiling, including...

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Chen RU, Pan S, Crispin DA, et al. Gene Expression and Proteomic Analysis of Pancreatic Cancer: a Recent Update. Cancer Genomics Proteomics. 2006;3(1):1-9
Chen, R. U., Pan, S., Crispin, D. A., & Brentnall, T. A. (2006). Gene Expression and Proteomic Analysis of Pancreatic Cancer: a Recent Update. Cancer genomics & proteomics, 3(1), 1-9.
Chen, R U, et al. "Gene Expression and Proteomic Analysis of Pancreatic Cancer: a Recent Update." Cancer genomics & proteomics vol. 3,1 (2006): 1-9.
Chen RU, Pan S, Crispin DA, Brentnall TA. Gene Expression and Proteomic Analysis of Pancreatic Cancer: a Recent Update. Cancer Genomics Proteomics. 2006 Jan-Feb;3(1):1-9. Epub 2006 Jan 01. PMID: 31394637.
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Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy.

Clinical proteomics

Peng H, Chen R, Brentnall TA, Eng JK, Picozzi VJ, Pan S.
PMID: 31346328
Clin Proteomics. 2019 Jul 17;16:31. doi: 10.1186/s12014-019-9251-3. eCollection 2019.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer that is characterized by its poor prognosis, rapid progression and development of drug resistance. Chemotherapy is a vital treatment option for most of PDAC patients. Stratification of PDAC patients, who...

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Peng H, Chen R, Brentnall TA, et al. Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy. Clin Proteomics. 2019;16:31doi: 10.1186/s12014-019-9251-3.
Peng, H., Chen, R., Brentnall, T. A., Eng, J. K., Picozzi, V. J., & Pan, S. (2019). Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy. Clinical proteomics, 1631. https://doi.org/10.1186/s12014-019-9251-3
Peng, Hong, et al. "Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy." Clinical proteomics vol. 16 (2019): 31. doi: https://doi.org/10.1186/s12014-019-9251-3
Peng H, Chen R, Brentnall TA, Eng JK, Picozzi VJ, Pan S. Predictive proteomic signatures for response of pancreatic cancer patients receiving chemotherapy. Clin Proteomics. 2019 Jul 17;16:31. doi: 10.1186/s12014-019-9251-3. eCollection 2019. PMID: 31346328; PMCID: PMC6636003.
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PolyG-DS: An ultrasensitive polyguanine tract-profiling method to detect clonal expansions and trace cell lineage.

Proceedings of the National Academy of Sciences of the United States of America

Zhang Y, Kohrn BF, Yang M, Nachmanson D, Soong TR, Lee IH, Tao Y, Clevers H, Swisher EM, Brentnall TA, Loeb LA, Kennedy SR, Salk JJ, Naxerova K, Risques RA.
PMID: 34330826
Proc Natl Acad Sci U S A. 2021 Aug 03;118(31). doi: 10.1073/pnas.2023373118.

Polyguanine tracts (PolyGs) are short guanine homopolymer repeats that are prone to accumulating mutations when cells divide. This feature makes them especially suitable for cell lineage tracing, which has been exploited to detect and characterize precancerous and cancerous somatic...

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Zhang Y, Kohrn BF, Yang M, et al. PolyG-DS: An ultrasensitive polyguanine tract-profiling method to detect clonal expansions and trace cell lineage. Proc Natl Acad Sci U S A. 2021;118(31)doi: 10.1073/pnas.2023373118.
Zhang, Y., Kohrn, B. F., Yang, M., Nachmanson, D., Soong, T. R., Lee, I. H., Tao, Y., Clevers, H., Swisher, E. M., Brentnall, T. A., Loeb, L. A., Kennedy, S. R., Salk, J. J., Naxerova, K., & Risques, R. A. (2021). PolyG-DS: An ultrasensitive polyguanine tract-profiling method to detect clonal expansions and trace cell lineage. Proceedings of the National Academy of Sciences of the United States of America, 118(31), . https://doi.org/10.1073/pnas.2023373118
Zhang, Yuezheng, et al. "PolyG-DS: An ultrasensitive polyguanine tract-profiling method to detect clonal expansions and trace cell lineage." Proceedings of the National Academy of Sciences of the United States of America vol. 118,31 (2021). doi: https://doi.org/10.1073/pnas.2023373118
Zhang Y, Kohrn BF, Yang M, Nachmanson D, Soong TR, Lee IH, Tao Y, Clevers H, Swisher EM, Brentnall TA, Loeb LA, Kennedy SR, Salk JJ, Naxerova K, Risques RA. PolyG-DS: An ultrasensitive polyguanine tract-profiling method to detect clonal expansions and trace cell lineage. Proc Natl Acad Sci U S A. 2021 Aug 03;118(31). doi: 10.1073/pnas.2023373118. PMID: 34330826; PMCID: PMC8346827.
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The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study.

Cancers

Atakpa EC, Brentnall AR, Astley S, Cuzick J, Evans DG, Warren RML, Howell A, Harvie M.
PMID: 34209579
Cancers (Basel). 2021 Jun 29;13(13). doi: 10.3390/cancers13133245.

We evaluated the association between short-term change in body mass index (BMI) and breast density during a 1 year weight-loss intervention (Manchester, UK). We included 65 premenopausal women (35-45 years, ≥7 kg adult weight gain, family history of breast...

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Atakpa EC, Brentnall AR, Astley S, et al. The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study. Cancers (Basel). 2021;13(13)doi: 10.3390/cancers13133245.
Atakpa, E. C., Brentnall, A. R., Astley, S., Cuzick, J., Evans, D. G., Warren, R. M. L., Howell, A., & Harvie, M. (2021). The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study. Cancers, 13(13), . https://doi.org/10.3390/cancers13133245
Atakpa, Emma C, et al. "The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study." Cancers vol. 13,13 (2021). doi: https://doi.org/10.3390/cancers13133245
Atakpa EC, Brentnall AR, Astley S, Cuzick J, Evans DG, Warren RML, Howell A, Harvie M. The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study. Cancers (Basel). 2021 Jun 29;13(13). doi: 10.3390/cancers13133245. PMID: 34209579; PMCID: PMC8269424.
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Dynamic tracking of microvascular hemoglobin content for continuous perfusion monitoring in the intensive care unit: pilot feasibility study.

Journal of clinical monitoring and computing

Mendelson AA, Rajaram A, Bainbridge D, Lawrence KS, Bentall T, Sharpe M, Diop M, Ellis CG.
PMID: 33104968
J Clin Monit Comput. 2021 Dec;35(6):1453-1465. doi: 10.1007/s10877-020-00611-x. Epub 2020 Oct 26.

PURPOSE:  There is a need for bedside methods to monitor oxygen delivery in the microcirculation. Near-infrared spectroscopy commonly measures tissue oxygen saturation, but does not reflect the time-dependent variability of microvascular hemoglobin content (MHC) that attempts to match oxygen...

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Mendelson AA, Rajaram A, Bainbridge D, et al. Dynamic tracking of microvascular hemoglobin content for continuous perfusion monitoring in the intensive care unit: pilot feasibility study. J Clin Monit Comput. 2020;35(6):1453-1465doi: 10.1007/s10877-020-00611-x.
Mendelson, A. A., Rajaram, A., Bainbridge, D., Lawrence, K. S., Bentall, T., Sharpe, M., Diop, M., Ellis, C. G. (2021). Dynamic tracking of microvascular hemoglobin content for continuous perfusion monitoring in the intensive care unit: pilot feasibility study. Journal of clinical monitoring and computing, 35(6), 1453-1465. https://doi.org/10.1007/s10877-020-00611-x
Mendelson, Asher A, et al. "Dynamic tracking of microvascular hemoglobin content for continuous perfusion monitoring in the intensive care unit: pilot feasibility study." Journal of clinical monitoring and computing vol. 35,6 (2021): 1453-1465. doi: https://doi.org/10.1007/s10877-020-00611-x
Mendelson AA, Rajaram A, Bainbridge D, Lawrence KS, Bentall T, Sharpe M, Diop M, Ellis CG. Dynamic tracking of microvascular hemoglobin content for continuous perfusion monitoring in the intensive care unit: pilot feasibility study. J Clin Monit Comput. 2021 Dec;35(6):1453-1465. doi: 10.1007/s10877-020-00611-x. Epub 2020 Oct 26. PMID: 33104968; PMCID: PMC7586414.
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External validation of a mammographic texture marker for breast cancer risk in a case-control study.

Journal of medical imaging (Bellingham, Wash.)

Wang C, Brentnall AR, Mainprize J, Yaffe M, Cuzick J, Harvey JA.
PMID: 32064299
J Med Imaging (Bellingham). 2020 Jan;7(1):014003. doi: 10.1117/1.JMI.7.1.014003. Epub 2020 Feb 12.

No abstract available.

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Wang C, Brentnall AR, Mainprize J, et al. External validation of a mammographic texture marker for breast cancer risk in a case-control study. J Med Imaging (Bellingham). 2020;7(1):014003doi: 10.1117/1.JMI.7.1.014003.
Wang, C., Brentnall, A. R., Mainprize, J., Yaffe, M., Cuzick, J., & Harvey, J. A. (2020). External validation of a mammographic texture marker for breast cancer risk in a case-control study. Journal of medical imaging (Bellingham, Wash.), 7(1), 014003. https://doi.org/10.1117/1.JMI.7.1.014003
Wang, Chao, et al. "External validation of a mammographic texture marker for breast cancer risk in a case-control study." Journal of medical imaging (Bellingham, Wash.) vol. 7,1 (2020): 014003. doi: https://doi.org/10.1117/1.JMI.7.1.014003
Wang C, Brentnall AR, Mainprize J, Yaffe M, Cuzick J, Harvey JA. External validation of a mammographic texture marker for breast cancer risk in a case-control study. J Med Imaging (Bellingham). 2020 Jan;7(1):014003. doi: 10.1117/1.JMI.7.1.014003. Epub 2020 Feb 12. PMID: 32064299; PMCID: PMC7013151.
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SNPs for breast cancer risk assessment.

Oncotarget

Cuzick J, Brentnall A, Dowsett M.
PMID: 29245890
Oncotarget. 2017 Nov 03;8(59):99211-99212. doi: 10.18632/oncotarget.22278. eCollection 2017 Nov 21.

No abstract available.

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Cuzick J, Brentnall A, Dowsett M. SNPs for breast cancer risk assessment. Oncotarget. 2017;8(59):99211-99212doi: 10.18632/oncotarget.22278.
Cuzick, J., Brentnall, A., & Dowsett, M. (2017). SNPs for breast cancer risk assessment. Oncotarget, 8(59), 99211-99212. https://doi.org/10.18632/oncotarget.22278
Cuzick, Jack, et al. "SNPs for breast cancer risk assessment." Oncotarget vol. 8,59 (2017): 99211-99212. doi: https://doi.org/10.18632/oncotarget.22278
Cuzick J, Brentnall A, Dowsett M. SNPs for breast cancer risk assessment. Oncotarget. 2017 Nov 03;8(59):99211-99212. doi: 10.18632/oncotarget.22278. eCollection 2017 Nov 21. PMID: 29245890; PMCID: PMC5725081.
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A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model.

Journal of breast imaging

Brentnall AR, Cohn WF, Knaus WA, Yaffe MJ, Cuzick J, Harvey JA.
PMID: 31423486
J Breast Imaging. 2019 Jun;1(2):99-106. doi: 10.1093/jbi/wbz006. Epub 2019 May 11.

BACKGROUND: Accurate breast cancer risk assessment for women attending routine screening is needed to guide screening and preventive interventions. We evaluated the accuracy of risk predictions from both visual and volumetric mammographic density combined with the Tyrer-Cuzick breast cancer...

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Brentnall AR, Cohn WF, Knaus WA, et al. A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model. J Breast Imaging. 2019;1(2):99-106doi: 10.1093/jbi/wbz006.
Brentnall, A. R., Cohn, W. F., Knaus, W. A., Yaffe, M. J., Cuzick, J., & Harvey, J. A. (2019). A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model. Journal of breast imaging, 1(2), 99-106. https://doi.org/10.1093/jbi/wbz006
Brentnall, Adam R, et al. "A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model." Journal of breast imaging vol. 1,2 (2019): 99-106. doi: https://doi.org/10.1093/jbi/wbz006
Brentnall AR, Cohn WF, Knaus WA, Yaffe MJ, Cuzick J, Harvey JA. A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model. J Breast Imaging. 2019 Jun;1(2):99-106. doi: 10.1093/jbi/wbz006. Epub 2019 May 11. PMID: 31423486; PMCID: PMC6690422.
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Proteomics studies of pancreatic cancer.

Proteomics. Clinical applications

Chen R, Pan S, Aebersold R, Brentnall TA.
PMID: 18633454
Proteomics Clin Appl. 2007;1(12):1582-1591. doi: 10.1002/prca.200700414.

Pancreatic cancer is the fourth leading cause of cancer death in the United States, with 4% survival 5 years after diagnosis. Biomarkers are desperately needed to improve earlier, more curable cancer diagnosis and to develop new effective therapeutic targets....

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Chen R, Pan S, Aebersold R, et al. Proteomics studies of pancreatic cancer. Proteomics Clin Appl. 2007;1(12):1582-1591doi: 10.1002/prca.200700414.
Chen, R., Pan, S., Aebersold, R., & Brentnall, T. A. (2007). Proteomics studies of pancreatic cancer. Proteomics. Clinical applications, 1(12), 1582-1591. https://doi.org/10.1002/prca.200700414
Chen, Ru, et al. "Proteomics studies of pancreatic cancer." Proteomics. Clinical applications vol. 1,12 (2007): 1582-1591. doi: https://doi.org/10.1002/prca.200700414
Chen R, Pan S, Aebersold R, Brentnall TA. Proteomics studies of pancreatic cancer. Proteomics Clin Appl. 2007;1(12):1582-1591. doi: 10.1002/prca.200700414. PMID: 18633454; PMCID: PMC2467510.
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Showing 1 to 12 of 34 entries