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316 results on '"Lillard, James W."'

2. Calibrated flux measurements reveal a nanostructure-stimulated transcytotic pathway

Author

Stewart, Tarianna, Koval, William T, Molina, Samuel A, Bock, Suzanne M, Lillard, James W, Ross, Russell F, Desai, Tejal A, and Koval, Michael

Subjects
Biochemistry and Cell Biology, Biological Sciences, Caco-2 Cells, Cell Line, Tumor, Drug Delivery Systems, Epithelial Cells, Epithelium, Humans, Nanostructures, Surface Properties, Transcytosis, Nanotopography, Drug delivery, Epithelial permeability, Calcium switch, Tight junctions, FcRn, Clinical Sciences, Biochemistry & Molecular Biology, Biochemistry and cell biology
Abstract

Transport of therapeutic agents across epithelial barriers is an important element in drug delivery. Transepithelial flux is widely used as a measure of transit across an epithelium, however it is most typically employed as a relative as opposed to absolute measure of molecular movement. Here, we have used the calcium switch approach to measure the maximum rate of paracellular flux through unencumbered intercellular junctions as a method to calibrate the flux rates for a series of tracers ranging in 0.6-900kDa in size across barriers composed of human colon epithelial (Caco-2) cells. We then examined the effects of nanostructured films (NSFs) on transepithelial transport. Two different NSF patterns were used, Defined Nanostructure (DN) 2 imprinted on polypropylene (PP) and DN3 imprinted on polyether ether ketone (PEEK). NSFs made direct contact with cells and decreased their barrier function, as measured by transepithelial resistance (TER), however cell viability was not affected. When NSF-induced transepithelial transport of Fab fragment (55kDa) and IgG (160kDa) was measured, it was unexpectedly found to be significantly greater than the maximum paracellular rate as predicted using cells cultured in low calcium. These data suggested that NSFs stimulate an active transport pathway, most likely transcytosis, in addition to increasing paracellular flux. Transport of IgG via transcytosis was confirmed by immunofluorescence confocal microscopy, since NSFs induced a significant level of IgG endocytosis by Caco-2 cells. Thus, NSF-induced IgG flux was attributable to both transcytosis and the paracellular route. These data provide the first demonstration that transcytosis can be stimulated by NSFs and that this was concurrent with increased paracellular permeability. Moreover, NSFs with distinct architecture paired with specific substrates have the potential to provide an effective means to regulate transepithelial transport in order to optimize drug delivery.

Published
2017

8. Abstract A056: Landscape of the molecular changes in the most frequent tumors in a safety net hospital

Author

Oprea-Ilies, Gabriella M., primary, Horne, LaTrisha L., additional, Stanley, Eddie R., additional, Lee, Regina, additional, Okoli, Joel, additional, Priore, Giuseppe Del, additional, Mishra, Pooja, additional, Matthew, Roland, additional, Flenaugh, Eric L., additional, Rivers, Brian, additional, Lillard, James W., additional, Sirotnikov, Sam, additional, and Matthews, Mallik, additional

Published
2023
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11. Abstract LB173: AACR President's initiative - 2020 by 2020: Democratizing precision cancer medicine and advancing health equity in the black belt

Author

Horne, Latrisha L., primary, Oprea-Ilies, Gabriella M., additional, Stanley, Eddie R., additional, Holloway, Carla M., additional, Hooker, Margaret P., additional, Isom, Amina, additional, Beech, Derrick J., additional, Gaonkar, Ana, additional, Harden, Shavette, additional, Hines, Jeffrey F., additional, Randolph, LaTonya, additional, Bennett, James K., additional, Canter, Daniel, additional, Carmen, Darrell J., additional, Mishra, Pooja, additional, Del Priore, Giuseppe, additional, Matthews, Roland, additional, Rivers, Brian M., additional, and Lillard, James W., additional

Published
2022
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16. Proteomic profiling based classification of CLL provides prognostication for modern therapy and identifies novel therapeutic targets

Author

Griffen, Ti’ara L., primary, Hoff, Fieke W., additional, Qiu, Yihua, additional, Lillard, James W., additional, Ferrajoli, Alessandra, additional, Thompson, Philip, additional, Toro, Endurance, additional, Ruiz, Kevin, additional, Burger, Jan, additional, Wierda, William, additional, and Kornblau, Steven M., additional

Published
2022
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18. Proteomic Profiling Based Classification of CLL Provides Prognostication for Modern Therapy and Identifies Novel Therapeutic Targets

Author

Griffen, Ti'ara L., primary, Hoff, Fieke W, additional, Qiu, Yihua, additional, Lillard, James W, additional, Ferrajoli, Alessandra, additional, Thompson, Philip A., additional, Toro, Endurance, additional, Ruiz, Kevin, additional, Burger, Jan A., additional, Wierda, William G., additional, and Kornblau, Steven M., additional

Published
2021
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20. RPPA-based proteomics recognizes distinct epigenetic signatures in chronic lymphocytic leukemia with clinical consequences

Author

van Dijk, Anneke D., primary, Griffen, Ti’ara L., additional, Qiu, Yihua H., additional, Hoff, Fieke W., additional, Toro, Endurance, additional, Ruiz, Kevin, additional, Ruvolo, Peter P., additional, Lillard, James W., additional, de Bont, Eveline S. J. M., additional, Burger, Jan A., additional, Wierda, William, additional, and Kornblau, Steven M., additional

Published
2021
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23. Racial disparities in Black men with prostate cancer: A literature review.

Author

Lillard, James W., Moses, Kelvin A., Mahal, Brandon A., and George, Daniel J.

Abstract

Black men are disproportionately affected by prostate cancer (PCa), with earlier presentation, more aggressive disease, and higher mortality rates versus White men. Furthermore, Black men have less access to PCa treatment and experience longer delays between diagnosis and treatment. In this review, the authors discuss the factors contributing to racial disparities and present solutions to improve access to care and increase clinical trial participation among Black men with PCa. Racial disparities observed among Black men with PCa are multifaceted, evolving from institutional racism. Cultural factors include generalized mistrust of the health care system, poor physician‐patient communication, lack of information on PCa and treatment options, fear of PCa diagnosis, and perceived societal stigma of the disease. In the United States, geographic trends in racial disparities have been observed. Economic factors, e.g., cost of care, recovery time, and cancer debt, play an important role in racial disparities observed in PCa treatment and outcomes. Racial diversity is often lacking in genomic and precision medicine studies. Black men are largely underrepresented in key phase 3 PCa trials and may be less willing to enroll in clinical trials due to lack of awareness, lack of diversity in clinical trial research teams, and bias of health care providers to recommend clinical research. The authors propose solutions to address these factors that include educating clinicians and institutions on the barriers Black men experience, increasing the diversity of health care providers and clinical research teams, and empowering Black men to be involved in their treatment, which are keys to creating equity for Black men with PCa. Lay summary: Prostate cancer negatively affects Black men more than men of other races.The history of segregation and mistreatment in the health care system may contribute to mistrust among Black men.Outcomes are worse for Black men because they are less likely to be screened or to receive treatment for prostate cancer.Black men also are unlikely to participate in clinical research, making it difficult for investigators to understand how Black men are affected by prostate cancer.Suggestions for addressing these differences include teaching physicians and nurses about the issues Black men experience getting treatment and improving how Black men get information on prostate cancer. Racial disparities seen within prostate cancer diagnosis, treatment, and outcomes are multifaceted and evolve from institutional racism. The disparities can be addressed by educating physicians about the barriers faced by Black men receiving health care, identifying the best practices for conveying information on treatments and clinical trials, and increasing diversity among health care professionals. [ABSTRACT FROM AUTHOR]

Published
2022
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25. Additional file 8 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 8. Modules with altered expression in Mutated CLL patients based on SF3B1 and Relapse Status. Violin plots of module eigengene tan, red, greenyellow, purple, yellow) expression (x-axis) based on SF3B1 (A) and relapse status (B). A Wilcoxon test was used to determine if module expression was altered between groups.

Published
2021
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26. Additional file 6 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 6. Module-Trait Heatmaps of Regressed and Unregressed ICGC Data (.pdf). Modules for unregressed (A) and regressed (B, C) datasets are denoted on the x-axis, traits on y-axis. B Modules-trait relationships following regression of sex and age. C reprEsents modules-trait relationships following regression of sex, age, and IGHV status. The blue-white-red colors inside of the heatmap indicate positive (red), negative (blue), and no(white) correlations. The numbers, inside the heatmaps, represent the correlation test p values. WGCNA of unregressed data produced more modules (13 vs 11) and significant module-trait relationships (45 vs 34) than the regressed (panel B) dataset.

Published
2021
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27. Additional file 2 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 2. Confounding Variable Variance. Variance scores (x-axis) of confounding variables (bold) and the top 25 genes (A, y-axis) and modules (B, y-axis) affected. At the individual gene level, age and sex contribute to less than 10% to the variance in gene expression of the top affected genes. At the module level, age at diagnosis and IGHV status are the largest contributors to variance in gene expression. 8 of 13 modules are minimally affected by confounding variables.

Published
2021
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28. Additional file 5 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 5. Module Preservation of Modules based on Regression and IGHV Status. WGCNA’s Module Preservation analysis was applied according to regression (A, B) and IGHV (C, D) status. Median rank (left figure, y-axis) of modules determined by module preservation scores (right figure, y-axis) are displayed. Modules ranked closest to zero are the most preserved. The blue and red dotted lines denote cutoffs for a –log rank p value of 0.05 (blue) and p value

Published
2021
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29. Additional file 12 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 12. Optimum RFS Gene Combination AUC in All ICGC CLL patients. Receiver Operator curves for Optimum biomarker gene combinations are shown for each time point: 15 months (A), 18 months (B), 3 years (C), and 5 years (D), The y-axis represents the percentage of patients who were true positives for relapse, whereas the x-axis represents the percentage of patients who were true negatives. The AUC (top left legend) for each time point is represented by a distinct color: dark orange (15 months), red (18 months), dark red (3 years), and magenta (5 years).

Published
2021
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30. Additional file 4 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 4. Module-trait Relationships of regressed ICGC data based on IGHV Status. Modules for Unmutated IGHV (A) and Mutated IGHV (B) datasets are denoted on the x-axis, traits on y-axis. The blue-white-red colors inside of the heatmap indicate positive (red), negative (blue), and no (white) correlations. The numbers, inside the heatmaps, represent the correlation test p values. WGCNA of unmutated patient data produced more modules (17 vs 11) than the mutated dataset.

Published
2021
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31. Additional file 9 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 9. Gene Ontology of Relapse-Associated M-CLL network modules. Biological processes (green), molecular processes (blue), and cellular locations (brown) of M6, M10, M11, and M12 modules are displayed on the y-axis. Z-scores are on the x-axis.

Published
2021
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32. Additional file 7 of Multivariate transcriptome analysis identifies networks and key drivers of chronic lymphocytic leukemia relapse risk and patient survival

Author

Griffen, Ti’ara L., Dammer, Eric B., Dill, Courtney D., Carey, Kaylin M., Young, Corey D., Nunez, Sha’Kayla K., Ohandjo, Adaugo Q., Kornblau, Steven M., and Lillard, James W.

Abstract

Additional file 7. Modules with altered expression in Unmutated CLL patients based on SF3B1 and Relapse Status. Violin plots of module eigengene (red and brown) expression (x-axis) based on SF3B1 (A) and relapse status (B). A Wilcoxon test was used to determine if module expression was altered between groups.

Published
2021
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34. Increasing Clinical Trial Participation of Black Women Diagnosed with Breast Cancer

Author

Fairley, Ricki, Lillard, James W., Berk, Alexandra, Cornew, Sophia, Gaspero, Joseph, Gillespie, James, Horne, LaTrisha L., Kidane, Sabrina, Munro, Sandra B., Parsons, Matthew, Powers, Emily R., Rizzo, Suzanne E., Tishcler, Alyson, Wohl, Hope, and Weiss, Marisa C.

Abstract

Despite racial disparities in breast cancer mortality, Black women remain underrepresented in clinical trials. In this mixed methods research, 48 Black women were engaged via focus group discussions and in-depth interviews to better understand the lived experience of women with breast cancer. The results of this qualitative study informed the development of a subsequent online survey to identify barriers, motivators, and other factors that influence decision-making by Black women diagnosed with breast cancer when considering clinical trial participation. Among the 257 Black survey participants, most (95%) were aware of clinical trials; of those, most viewed them as lifesaving (81%) and/or benefiting others (90%). Negative perceptions such as serious side effects (58%), not receiving real treatment (52%), or risk of potential harm (62%) were indicated. Barriers included financial expenses (49%), concerns that their condition could be made worse (29%), that they would receive a placebo (28%), or that treatment was unapproved (28%). Participants were more likely than their health care providers (HCPs) to initiate discussions of clinical trials (53% versus 33%), and 29% of participants indicated a need for more information about risks and benefits, even after having those conversations. The most trustworthy sources of information on clinical trials were HCPs (66%) and breast cancer support groups (64%). These results suggest that trusted communities are key for providing education on clinical trials. However, there is also a need for HCPs to proactively discuss clinical trials with patients to ensure that they are adequately informed about all aspects of participation.

Published
2023
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