200 results on '"M Boca"'
Search Results
2. Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A
- Author
-
Xue Yin, Jaeil Ahn, and Simina M. Boca
- Subjects
Life expectancy ,Morquio syndrome A ,Simulations ,Kaplan–Meier ,Medicine ,Biology (General) ,QH301-705.5 ,Science (General) ,Q1-390 - Abstract
Abstract Objective Life expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. However, due to the resource-consuming nature of following a cohort prospectively, life expectancy is often assessed based upon retrospective death record reviews. This conventional approach may lead to potentially biased estimates, in particular when estimating life expectancy of rare diseases such as Morquio syndrome A. We investigated the accuracy of life expectancy estimation using death records by simulating the survival of individuals with Morquio syndrome A under four different scenarios. Results When life expectancy was constant during the entire period, using death data did not result in a biased estimate. However, when life expectancy increased over time, as is often expected to be the case in rare diseases, using only death data led to a substantial underestimation of life expectancy. We emphasize that it is therefore crucial to understand how estimates of life expectancy are obtained, to interpret them in an appropriate context, and to assess estimation methods within a sensitivity analysis framework, similar to the simulations performed herein.
- Published
- 2022
- Full Text
- View/download PDF
3. Ten quick tips for deep learning in biology.
- Author
-
Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra J. Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Brandon Signal, Benjamin J. Lengerich, Timothy J. Triche Jr., and Simina M. Boca
- Published
- 2022
- Full Text
- View/download PDF
4. Correction for Rando et al., 'Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure'
- Author
-
Halie M. Rando, Adam L. MacLean, Alexandra J. Lee, Ronan Lordan, Sandipan Ray, Vikas Bansal, Ashwin N. Skelly, Elizabeth Sell, John J. Dziak, Lamonica Shinholster, Lucy D’Agostino McGowan, Marouen Ben Guebila, Nils Wellhausen, Sergey Knyazev, Simina M. Boca, Stephen Capone, Yanjun Qi, YoSon Park, David Mai, Yuchen Sun, Joel D. Boerckel, Christian Brueffer, James Brian Byrd, Jeremy P. Kamil, Jinhui Wang, Ryan Velazquez, Gregory L. Szeto, John P. Barton, Rishi Raj Goel, Serghei Mangul, Tiago Lubiana, Anthony Gitter, and Casey S. Greene
- Subjects
Microbiology ,QR1-502 - Published
- 2022
- Full Text
- View/download PDF
5. Identification and Development of Therapeutics for COVID-19
- Author
-
Halie M. Rando, Nils Wellhausen, Soumita Ghosh, Alexandra J. Lee, Anna Ada Dattoli, Fengling Hu, James Brian Byrd, Diane N. Rafizadeh, Ronan Lordan, Yanjun Qi, Yuchen Sun, Christian Brueffer, Jeffrey M. Field, Marouen Ben Guebila, Nafisa M. Jadavji, Ashwin N. Skelly, Bharath Ramsundar, Jinhui Wang, Rishi Raj Goel, YoSon Park, Simina M. Boca, Anthony Gitter, and Casey S. Greene
- Subjects
COVID-19 ,review ,therapeutics ,Microbiology ,QR1-502 - Abstract
ABSTRACT After emerging in China in late 2019, the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread worldwide, and as of mid-2021, it remains a significant threat globally. Only a few coronaviruses are known to infect humans, and only two cause infections similar in severity to SARS-CoV-2: Severe acute respiratory syndrome-related coronavirus, a species closely related to SARS-CoV-2 that emerged in 2002, and Middle East respiratory syndrome-related coronavirus, which emerged in 2012. Unlike the current pandemic, previous epidemics were controlled rapidly through public health measures, but the body of research investigating severe acute respiratory syndrome and Middle East respiratory syndrome has proven valuable for identifying approaches to treating and preventing novel coronavirus disease 2019 (COVID-19). Building on this research, the medical and scientific communities have responded rapidly to the COVID-19 crisis and identified many candidate therapeutics. The approaches used to identify candidates fall into four main categories: adaptation of clinical approaches to diseases with related pathologies, adaptation based on virological properties, adaptation based on host response, and data-driven identification (ID) of candidates based on physical properties or on pharmacological compendia. To date, a small number of therapeutics have already been authorized by regulatory agencies such as the Food and Drug Administration (FDA), while most remain under investigation. The scale of the COVID-19 crisis offers a rare opportunity to collect data on the effects of candidate therapeutics. This information provides insight not only into the management of coronavirus diseases but also into the relative success of different approaches to identifying candidate therapeutics against an emerging disease. IMPORTANCE The COVID-19 pandemic is a rapidly evolving crisis. With the worldwide scientific community shifting focus onto the SARS-CoV-2 virus and COVID-19, a large number of possible pharmaceutical approaches for treatment and prevention have been proposed. What was known about each of these potential interventions evolved rapidly throughout 2020 and 2021. This fast-paced area of research provides important insight into how the ongoing pandemic can be managed and also demonstrates the power of interdisciplinary collaboration to rapidly understand a virus and match its characteristics with existing or novel pharmaceuticals. As illustrated by the continued threat of viral epidemics during the current millennium, a rapid and strategic response to emerging viral threats can save lives. In this review, we explore how different modes of identifying candidate therapeutics have borne out during COVID-19.
- Published
- 2021
- Full Text
- View/download PDF
6. Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure
- Author
-
Halie M. Rando, Adam L. MacLean, Alexandra J. Lee, Ronan Lordan, Sandipan Ray, Vikas Bansal, Ashwin N. Skelly, Elizabeth Sell, John J. Dziak, Lamonica Shinholster, Lucy D’Agostino McGowan, Marouen Ben Guebila, Nils Wellhausen, Sergey Knyazev, Simina M. Boca, Stephen Capone, Yanjun Qi, YoSon Park, David Mai, Yuchen Sun, Joel D. Boerckel, Christian Brueffer, James Brian Byrd, Jeremy P. Kamil, Jinhui Wang, Ryan Velazquez, Gregory L. Szeto, John P. Barton, Rishi Raj Goel, Serghei Mangul, Tiago Lubiana, Anthony Gitter, and Casey S. Greene
- Subjects
Microbiology ,QR1-502 - Abstract
COVID-19 involves a number of organ systems and can present with a wide range of symptoms. From how the virus infects cells to how it spreads between people, the available research suggests that these patterns are very similar to those seen in the closely related viruses SARS-CoV-1 and possibly Middle East respiratory syndrome-related CoV (MERS-CoV).
- Published
- 2021
- Full Text
- View/download PDF
7. Ten Quick Tips for Deep Learning in Biology.
- Author
-
Benjamin D. Lee, Anthony Gitter, Casey S. Greene, Sebastian Raschka, Finlay Maguire, Alexander J. Titus, Michael D. Kessler, Alexandra J. Lee, Marc G. Chevrette, Paul Allen Stewart, Thiago Britto-Borges, Evan M. Cofer, Kun-Hsing Yu, Juan Jose Carmona, Elana J. Fertig, Alexandr A. Kalinin, Beth Signal, Benjamin J. Lengerich, Timothy J. Triche Jr., and Simina M. Boca
- Published
- 2021
8. The National Cancer Institute's Informatics Technology for Cancer Research Program: Building a Community of Practice in Cancer Informatics.
- Author
-
Simina M. Boca, David Hanauer, Ian Holmes, Despina Kontos, and Juli D. Klemm
- Published
- 2019
9. POPSTR: Inference of Admixed Population Structure Based on Single-Nucleotide Polymorphisms and Copy Number Variations.
- Author
-
Jaeil Ahn, Brian Conkright, Simina M. Boca, and Subha Madhavan
- Published
- 2018
- Full Text
- View/download PDF
10. FWER and FDR control when testing multiple mediators.
- Author
-
Joshua N. Sampson, Simina M. Boca, Steven C. Moore, and Ruth Heller
- Published
- 2018
- Full Text
- View/download PDF
11. Real-world Studies Link NSAID Use to Improved Overall Lung Cancer Survival
- Author
-
Jason Roszik, J. Jack Lee, Yi-Hung Wu, Xi Liu, Masanori Kawakami, Jonathan M. Kurie, Anas Belouali, Simina M. Boca, Samir Gupta, Robert A. Beckman, Subha Madhavan, and Ethan Dmitrovsky
- Abstract
Inflammation is a cancer hallmark. NSAIDs improve overall survival (OS) in certain cancers. Real-world studies explored here whether NSAIDs improve non–small cell lung cancer (NSCLC) OS. Analyses independently interrogated clinical databases from The University of Texas MD Anderson Cancer Center (MDACC cohort, 1987 to 2015; 33,162 NSCLCs and 3,033 NSAID users) and Georgetown-MedStar health system (Georgetown cohort, 2000 to 2019; 4,497 NSCLCs and 1,993 NSAID users). Structured and unstructured clinical data were extracted from electronic health records using natural language processing (NLP). Associations were made between NSAID use and NSCLC prognostic features (tobacco use, gender, race, and body mass index, BMI). NSAIDs were statistically significantly (P < 0.0001) associated with increased NSCLC survival (5-year OS 29.7% for NSAID users vs. 13.1% for nonusers) in the MDACC cohort. NSAID users gained 11.6 months over nonusers in 5-year restricted mean survival time. Stratified analysis by stage, histopathology, and multicovariable assessment substantiated benefits. NSAID users were pooled independent of NSAID type and by NSAID type. Landmark analysis excluded immortal time bias. Survival improvements (P < 0.0001) were confirmed in the Georgetown cohort. Thus, real-world NSAID usage was independently associated with increased NSCLC survival in the MDACC and Georgetown cohorts. Findings were confirmed by landmark analyses and NSAID type. The OS benefits persisted despite tobacco use and did not depend on gender, race, or BMI (MDACC cohort, P < 0.0001). These real-world findings could guide future NSAID lung cancer randomized trials. Significance: NLP and real-world studies conducted in large cohorts explored whether NSAIDs improved survival across NSCLC stages, histopathology, gender, smoking history, or demographic groups. A statistically significant association between NSAID use and NSCLC survival was found. This provides a rationale for future NSAID randomized NSCLC trials.
- Published
- 2022
12. A direct approach to estimating false discovery rates conditional on covariates
- Author
-
Simina M. Boca and Jeffrey T. Leek
- Subjects
False discovery rates ,FDR regression ,Adaptive FDR ,Medicine ,Biology (General) ,QH301-705.5 - Abstract
Modern scientific studies from many diverse areas of research abound with multiple hypothesis testing concerns. The false discovery rate (FDR) is one of the most commonly used approaches for measuring and controlling error rates when performing multiple tests. Adaptive FDRs rely on an estimate of the proportion of null hypotheses among all the hypotheses being tested. This proportion is typically estimated once for each collection of hypotheses. Here, we propose a regression framework to estimate the proportion of null hypotheses conditional on observed covariates. This may then be used as a multiplication factor with the Benjamini–Hochberg adjusted p-values, leading to a plug-in FDR estimator. We apply our method to a genome-wise association meta-analysis for body mass index. In our framework, we are able to use the sample sizes for the individual genomic loci and the minor allele frequencies as covariates. We further evaluate our approach via a number of simulation scenarios. We provide an implementation of this novel method for estimating the proportion of null hypotheses in a regression framework as part of the Bioconductor package swfdr.
- Published
- 2018
- Full Text
- View/download PDF
13. Supplementary Table S6 from Real-world Studies Link NSAID Use to Improved Overall Lung Cancer Survival
- Author
-
Ethan Dmitrovsky, Subha Madhavan, Robert A. Beckman, Samir Gupta, Simina M. Boca, Anas Belouali, Jonathan M. Kurie, Masanori Kawakami, Xi Liu, Yi-Hung Wu, J. Jack Lee, and Jason Roszik
- Abstract
Supplementary Table 6: The MD Anderson cohort 5-year survival rate and difference of 5-year restricted mean survival time in months between NSAID users and non-users by gender, race, and smoking status corresponding to Figure 2. Comparisons are made to the Georgetown cohort.
- Published
- 2023
14. Supplementary Figure S2 from Real-world Studies Link NSAID Use to Improved Overall Lung Cancer Survival
- Author
-
Ethan Dmitrovsky, Subha Madhavan, Robert A. Beckman, Samir Gupta, Simina M. Boca, Anas Belouali, Jonathan M. Kurie, Masanori Kawakami, Xi Liu, Yi-Hung Wu, J. Jack Lee, and Jason Roszik
- Abstract
Supplemental Figure 2. The Kaplan-Meier analysis of overall survival and NSAID use in lung cancer cases within the MedStar-Georgetown University database (Georgetown cohort).
- Published
- 2023
15. Data from Real-world Studies Link NSAID Use to Improved Overall Lung Cancer Survival
- Author
-
Ethan Dmitrovsky, Subha Madhavan, Robert A. Beckman, Samir Gupta, Simina M. Boca, Anas Belouali, Jonathan M. Kurie, Masanori Kawakami, Xi Liu, Yi-Hung Wu, J. Jack Lee, and Jason Roszik
- Abstract
Inflammation is a cancer hallmark. NSAIDs improve overall survival (OS) in certain cancers. Real-world studies explored here whether NSAIDs improve non–small cell lung cancer (NSCLC) OS. Analyses independently interrogated clinical databases from The University of Texas MD Anderson Cancer Center (MDACC cohort, 1987 to 2015; 33,162 NSCLCs and 3,033 NSAID users) and Georgetown-MedStar health system (Georgetown cohort, 2000 to 2019; 4,497 NSCLCs and 1,993 NSAID users). Structured and unstructured clinical data were extracted from electronic health records using natural language processing (NLP). Associations were made between NSAID use and NSCLC prognostic features (tobacco use, gender, race, and body mass index, BMI). NSAIDs were statistically significantly (P < 0.0001) associated with increased NSCLC survival (5-year OS 29.7% for NSAID users vs. 13.1% for nonusers) in the MDACC cohort. NSAID users gained 11.6 months over nonusers in 5-year restricted mean survival time. Stratified analysis by stage, histopathology, and multicovariable assessment substantiated benefits. NSAID users were pooled independent of NSAID type and by NSAID type. Landmark analysis excluded immortal time bias. Survival improvements (P < 0.0001) were confirmed in the Georgetown cohort. Thus, real-world NSAID usage was independently associated with increased NSCLC survival in the MDACC and Georgetown cohorts. Findings were confirmed by landmark analyses and NSAID type. The OS benefits persisted despite tobacco use and did not depend on gender, race, or BMI (MDACC cohort, P < 0.0001). These real-world findings could guide future NSAID lung cancer randomized trials.Significance:NLP and real-world studies conducted in large cohorts explored whether NSAIDs improved survival across NSCLC stages, histopathology, gender, smoking history, or demographic groups. A statistically significant association between NSAID use and NSCLC survival was found. This provides a rationale for future NSAID randomized NSCLC trials.
- Published
- 2023
16. Suppl. Fig. S1-7 from Acquired Resistance to a MET Antibody In Vivo Can Be Overcome by the MET Antibody Mixture Sym015
- Author
-
Thomas Tuxen Poulsen, Michael Kragh, Emanuel F. Petricoin, Andreas Kjaer, Ivan D. Horak, Subha Madhavan, Simina M. Boca, Shruti Rao, Valerie S. Calvert, and Sofie Ellebaek Pollmann
- Abstract
Supplementary Figure S1. Sequence homology to human and mouse reference genomes. Supplementary Figure S2. No SNU-5 tumors establish upon continuous treatment with emibetuzumab Supplementary Figure S3. MET level in 7333 and with or without emibetuzumab treatment. Supplementary Figure S4. Log2 ratios for MYC, PVT1, and ERBB3 copy number gains in the 4626 tumor. Supplementary Figure S5. HER3 level in SNU-5 cell lines. Supplementary Figure S6. Both emibetuzumab-resistant cell lines are resistant to Sym015 in vitro. Supplementary Figure S7. SNU-5 are equally sensitive to Sym015 and Sym015 LALA in vivo.
- Published
- 2023
17. Suppl. Table S4 from Acquired Resistance to a MET Antibody In Vivo Can Be Overcome by the MET Antibody Mixture Sym015
- Author
-
Thomas Tuxen Poulsen, Michael Kragh, Emanuel F. Petricoin, Andreas Kjaer, Ivan D. Horak, Subha Madhavan, Simina M. Boca, Shruti Rao, Valerie S. Calvert, and Sofie Ellebaek Pollmann
- Abstract
Supplementary Table S4. Sensitivity of emibetuzumab-resistant cell lines to various TKIs compared with SNU-5 cells.
- Published
- 2023
18. Data from Acquired Resistance to a MET Antibody In Vivo Can Be Overcome by the MET Antibody Mixture Sym015
- Author
-
Thomas Tuxen Poulsen, Michael Kragh, Emanuel F. Petricoin, Andreas Kjaer, Ivan D. Horak, Subha Madhavan, Simina M. Boca, Shruti Rao, Valerie S. Calvert, and Sofie Ellebaek Pollmann
- Abstract
Failure of clinical trials due to development of resistance to MET-targeting therapeutic agents is an emerging problem. Mechanisms of acquired resistance to MET tyrosine kinase inhibitors are well described, whereas characterization of mechanisms of resistance toward MET-targeting antibodies is limited. This study investigated mechanisms underlying in vivo resistance to two antibody therapeutics currently in clinical development: an analogue of the MET-targeting antibody emibetuzumab and Sym015, a mixture of two antibodies targeting nonoverlapping epitopes of MET. Upon long-term in vivo treatment of a MET-amplified gastric cancer xenograft model (SNU-5), emibetuzumab-resistant, but not Sym015-resistant, tumors emerged. Resistant tumors were isolated and used to establish resistant cell lines. Characterization of both tumors and cell lines using extensive protein and signaling pathway activation mapping along with next-generation sequencing revealed two distinct resistance profiles, one involving PTEN loss and the other involving activation of the PI3K pathway, likely via MYC and ERBB3 copy number gains. PTEN loss left one model unaffected by PI3K/AKT targeting but sensitive to mTOR targeting, while the PI3K pathway–activated model was partly sensitive to targeting of multiple PI3K pathway proteins. Importantly, both resistant models were sensitive to treatment with Sym015 in vivo due to antibody-dependent cellular cytotoxicity–mediated tumor growth inhibition, MET degradation, and signaling inhibition. Taken together, our data provide key insights into potential mechanisms of resistance to a single MET-targeting antibody, demonstrate superiority of Sym015 in preventing acquired resistance, and confirm Sym015 antitumor activity in tumors resistant to a single MET antibody. Mol Cancer Ther; 17(6); 1259–70. ©2018 AACR.
- Published
- 2023
19. Supplementary Figure 2 from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 16K, The correlation of the (BIV) measured from PLCO and SPA.
- Published
- 2023
20. Supplementary Figure 3 from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 13K, The plot illustrates the distributions of the technical CV's (metabolite levels on a log scale), a measure of laboratory variability. The x-axis represents the metabolite quantile ranking (e.g. 0.5 represents the median), the y-axis represents the actual CV, and the curves (black for SPA and dashed red for PLCO) show the CV for the specified metabolite quantile ranking.
- Published
- 2023
21. Supplementary Figure 1 from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 15K, The correlation between the ICCs measured for the metabolites in both PLCO and SPA.
- Published
- 2023
22. Supplementary Table 3 from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 94K, Metabolite Classification
- Published
- 2023
23. Supplementary Methods and Figure Legend from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 65K
- Published
- 2023
24. Data from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
Background: Metabolite levels within an individual vary over time. This within-individual variability, coupled with technical variability, reduces the power for epidemiologic studies to detect associations with disease. Here, the authors assess the variability of a large subset of metabolites and evaluate the implications for epidemiologic studies.Methods: Using liquid chromatography/mass spectrometry (LC/MS) and gas chromatography-mass spectroscopy (GC/MS) platforms, 385 metabolites were measured in 60 women at baseline and year-one of the Shanghai Physical Activity Study, and observed patterns were confirmed in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening study.Results: Although the authors found high technical reliability (median intraclass correlation = 0.8), reliability over time within an individual was low. Taken together, variability in the assay and variability within the individual accounted for the majority of variability for 64% of metabolites. Given this, a metabolite would need, on average, a relative risk of 3 (comparing upper and lower quartiles of “usual” levels) or 2 (comparing quartiles of observed levels) to be detected in 38%, 74%, and 97% of studies including 500, 1,000, and 5,000 individuals. Age, gender, and fasting status factors, which are often of less interest in epidemiologic studies, were associated with 30%, 67%, and 34% of metabolites, respectively, but the associations were weak and explained only a small proportion of the total metabolite variability.Conclusion: Metabolomics will require large, but feasible, sample sizes to detect the moderate effect sizes typical for epidemiologic studies.Impact: We offer guidelines for determining the sample sizes needed to conduct metabolomic studies in epidemiology. Cancer Epidemiol Biomarkers Prev; 22(4); 631–40. ©2013 AACR.
- Published
- 2023
25. Supplementary Table 2 from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 46K, A)The proportion of metabolites in each of 10 categories that have an ICC exceeding 0.2, 0.5, and 0.8 in SPA. N is the total number of metabolites within the specified category. B) The proportion of metabolites in each of 10 categories that have an ICC exceeding 0.2, 0.5, and 0.8 in PLCO. N is the total number of metabolites within the specified category.
- Published
- 2023
26. Supplementary Figure 4 from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 22K, Each metabolite level was normalized by three steps: a) log transforming b) subtracting the mean of the log(metabolite) level c) dividing by the standard deviation of the log(metabolite) level. This figure shows the histogram of all (number of subjects x number of metabolites) normalized levels. The absence of longer tails (e.g. little kurtosis) suggests that taking the log of metabolite levels produced relatively normally distributed measurements.
- Published
- 2023
27. Supplementary Table 1 from Metabolomics in Epidemiology: Sources of Variability in Metabolite Measurements and Implications
- Author
-
Steven C. Moore, Amanda J. Cross, Rashmi Sinha, Wei Zheng, Yong Bing Xiang, Gong Yang, Da Ke Liu, Qiuyin Cai, Wong-Ho Chow, Bu-Tian Ji, Yu Ting Tan, Ann W. Hsing, Charles E. Matthews, Rachael Z. Stolzenberg-Solomon, Xiao Ou Shu, Simina M. Boca, and Joshua N. Sampson
- Abstract
PDF file - 59K, A list of the identified metabolites with the lowest values of between-subject variability, (e.g. the highest within-subject variability), among all metabolites with an ICC > 0.8. Rows include metabolite name, , the equivalent value from the age and gender adjusted (A.G.A) model, the equivalent from a female-only model, p-value for the metabolite's association with age, and p-value for the metabolite's association with gender.
- Published
- 2023
28. Modulation of Radiation Response by the Tetrahydrobiopterin Pathway
- Author
-
Rupak Pathak, Amrita K. Cheema, Simina M. Boca, Kimberly J. Krager, Martin Hauer-Jensen, and Nukhet Aykin-Burns
- Subjects
ionizing radiation ,metabolomics ,oxidative stress ,tetrahydrobiopterin ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Ionizing radiation (IR) is an integral component of our lives due to highly prevalent sources such as medical, environmental, and/or accidental. Thus, understanding of the mechanisms by which radiation toxicity develops is crucial to address acute and chronic health problems that occur following IR exposure. Immediate formation of IR-induced free radicals as well as their persistent effects on metabolism through subsequent alterations in redox mediated inter- and intracellular processes are globally accepted as significant contributors to early and late effects of IR exposure. This includes but is not limited to cytotoxicity, genomic instability, fibrosis and inflammation. Damage to the critical biomolecules leading to detrimental long-term alterations in metabolic redox homeostasis following IR exposure has been the focus of various independent investigations over last several decades. The growth of the “omics” technologies during the past decade has enabled integration of “data from traditional radiobiology research”, with data from metabolomics studies. This review will focus on the role of tetrahydrobiopterin (BH4), an understudied redox-sensitive metabolite, plays in the pathogenesis of post-irradiation normal tissue injury as well as how the metabolomic readout of BH4 metabolism fits in the overall picture of disrupted oxidative metabolism following IR exposure.
- Published
- 2015
- Full Text
- View/download PDF
29. Testing multiple biological mediators simultaneously.
- Author
-
Simina M. Boca, Rashmi Sinha, Amanda J. Cross, Steven C. Moore, and Joshua N. Sampson
- Published
- 2014
- Full Text
- View/download PDF
30. An Open-Publishing Response to the COVID-19 Infodemic
- Author
-
Halie M, Rando, Simina M, Boca, Lucy D'Agostino, McGowan, Daniel S, Himmelstein, Michael P, Robson, Vincent, Rubinetti, Ryan, Velazquez, Casey S, Greene, and Anthony, Gitter
- Subjects
open source ,open publishing ,COVID-19 ,data integration ,Article ,living document ,Manubot - Abstract
The COVID-19 pandemic catalyzed the rapid dissemination of papers and preprints investigating the disease and its associated virus, SARS-CoV-2. The multifaceted nature of COVID-19 demands a multidisciplinary approach, but the urgency of the crisis combined with the need for social distancing measures present unique challenges to collaborative science. We applied a massive online open publishing approach to this problem using Manubot. Through GitHub, collaborators summarized and critiqued COVID-19 literature, creating a review manuscript. Manubot automatically compiled citation information for referenced preprints, journal publications, websites, and clinical trials. Continuous integration workflows retrieved up-to-date data from online sources nightly, regenerating some of the manuscript's figures and statistics. Manubot rendered the manuscript into PDF, HTML, LaTeX, and DOCX outputs, immediately updating the version available online upon the integration of new content. Through this effort, we organized over 50 scientists from a range of backgrounds who evaluated over 1,500 sources and developed seven literature reviews. While many efforts from the computational community have focused on mining COVID-19 literature, our project illustrates the power of open publishing to organize both technical and non-technical scientists to aggregate and disseminate information in response to an evolving crisis.
- Published
- 2022
31. Evidence-Based Network Approach to Recommending Targeted Cancer Therapies
- Author
-
Subha Madhavan, Héctor Corrada Bravo, Krithika Bhuvaneshwar, Simina M. Boca, Robert A. Beckman, Shruti Rao, Jayaram Kancherla, and Rebecca B. Riggins
- Subjects
0301 basic medicine ,Evidence-based practice ,Computer science ,MEDLINE ,Antineoplastic Agents ,03 medical and health sciences ,0302 clinical medicine ,Neoplasms ,Original Reports ,Biomarkers, Tumor ,medicine ,Humans ,Gene Regulatory Networks ,Molecular Targeted Therapy ,Precision Medicine ,Evidence-Based Medicine ,Extramural ,Patient Selection ,Cancer ,General Medicine ,medicine.disease ,Data science ,3. Good health ,030104 developmental biology ,Work (electrical) ,030220 oncology & carcinogenesis ,Informatics ,Special Series: Informatics Tools for Cancer Research and Care ,Network approach - Abstract
PURPOSE In this work, we introduce CDGnet (Cancer-Drug-Gene Network), an evidence-based network approach for recommending targeted cancer therapies. CDGnet represents a user-friendly informatics tool that expands the range of targeted therapy options for patients with cancer who undergo molecular profiling by including the biologic context via pathway information. METHODS CDGnet considers biologic pathway information specifically by looking at targets or biomarkers downstream of oncogenes and is personalized for individual patients via user-inputted molecular alterations and cancer type. It integrates a number of different sources of knowledge: patient-specific inputs (molecular alterations and cancer type), US Food and Drug Administration–approved therapies and biomarkers (curated from DailyMed), pathways for specific cancer types (from Kyoto Encyclopedia of Genes and Genomes [KEGG]), gene-drug connections (from DrugBank), and oncogene information (from KEGG). We consider 4 different evidence-based categories for therapy recommendations. Our tool is delivered via an R/Shiny Web application. For the 2 categories that use pathway information, we include an interactive Sankey visualization built on top of d3.js that also provides links to PubChem. RESULTS We present a scenario for a patient who has estrogen receptor (ER)–positive breast cancer with FGFR1 amplification. Although many therapies exist for patients with ER-positive breast cancer, FGFR1 amplifications may confer resistance to such treatments. CDGnet provides therapy recommendations, including PIK3CA, MAPK, and RAF inhibitors, by considering targets or biomarkers downstream of FGFR1. CONCLUSION CDGnet provides results in a number of easily accessible and usable forms, separating targeted cancer therapies into categories in an evidence-based manner that incorporates biologic pathway information.
- Published
- 2020
32. Eye-Tracking Study to Enhance Usability of Molecular Diagnostics Reports in Cancer Precision Medicine
- Author
-
Subha Madhavan, Simina M. Boca, Allan Fong, Shruti Rao, Peter B. McGarvey, Raj M. Ratwani, Robert A. Beckman, and Vishakha Sharma
- Subjects
Cancer Research ,medicine.medical_specialty ,business.industry ,Cancer ,Usability ,Certification ,Precision medicine ,medicine.disease ,Molecular diagnostics ,Test (assessment) ,Oncology ,Medicine ,Eye tracking ,Medical physics ,Personalized medicine ,business - Abstract
Purpose We conducted usability studies on commercially available molecular diagnostic (MDX) test reports to identify strengths and weaknesses in content and form that drive clinical decision making. Given routine genomic testing in cancer medicine, oncologists must interpret MDX reports as well as evidence concerning clinical utility of biomarkers accurately for treatment or trial selection. This work aims to evaluate effectiveness of MDX reports in facilitating cancer treatment planning. Methods Fourteen clinicians at an academic tertiary care medical facility, with a wide range of experience in oncology and in the use of molecular testing, participated in this study. Three commercially available, widely used, Clinical Laboratory Improvement Amendments (CLIA)–certified, College of American Pathologists (CAP)–accredited test reports (labeled Laboratories A, B, and C) were used. Eye tracking, surveys, and think-aloud protocols were used to collect usability data for these MDX reports focusing on ease of comprehension and actionability Results Clinicians found two primary areas in molecular diagnostic reports most useful for patient care: therapy options with benefit or lack of benefit to patients, including enrolling clinical trials; and pathogenic tumor molecular anomalies detected. Therapeutic implications and therapy classes such as US Food and Drug Administration–approved off-label, on-label, clinical trials were critical for decision making. However, all reports had usability and comprehension issues in these areas and could be improved. Conclusion Focused usability studies can help drive our understanding of the clinical workflow for use of molecular diagnostic tests in cancer care. This in turn can have major effects on quality of care, outcomes, costs, and patient satisfaction. This study demonstrates the use of specific usability techniques (eye tracking and think-aloud protocols) to help clinical laboratories improve MDX report design in a precision oncology treatment setting.
- Published
- 2022
33. Correction: Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study.
- Author
-
Simina M Boca, Maki Nishida, Michael Harris, Shruti Rao, Amrita K Cheema, Kirandeep Gill, Difei Wang, Lin An, Robinder Gauba, Haeri Seol, Lauren P Morgenroth, Erik Henricson, Craig McDonald, Jean K Mah, Paula R Clemens, Eric P Hoffman, Yetrib Hathout, and Subha Madhavan
- Subjects
Medicine ,Science - Abstract
[This corrects the article DOI: 10.1371/journal.pone.0153461.].
- Published
- 2016
- Full Text
- View/download PDF
34. Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study.
- Author
-
Simina M Boca, Maki Nishida, Michael Harris, Shruti Rao, Amrita K Cheema, Kirandeep Gill, Haeri Seol, Lauren P Morgenroth, Erik Henricson, Craig McDonald, Jean K Mah, Paula R Clemens, Eric P Hoffman, Yetrib Hathout, and Subha Madhavan
- Subjects
Medicine ,Science - Abstract
Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.
- Published
- 2016
- Full Text
- View/download PDF
35. Parvalbumin+and Npas1+Pallidal Neurons Have Distinct Circuit Topology and Function
- Author
-
Simina M. Boca, Saivasudha Chalasani, Talia N. Lerner, Harry S. Xenias, Isabel Fan, Adam W. Hantman, Arin Pamukcu, Qiaoling Cui, Brianna L. Berceau, Elizabeth C. Augustine, and C. Savio Chan
- Subjects
0301 basic medicine ,Parkinson's disease ,General Neuroscience ,Motor control ,Optogenetics ,Biology ,medicine.disease ,03 medical and health sciences ,Electrophysiology ,Subthalamic nucleus ,030104 developmental biology ,0302 clinical medicine ,Globus pallidus ,medicine.anatomical_structure ,nervous system ,Basal ganglia ,medicine ,Neuron ,Neuroscience ,030217 neurology & neurosurgery - Abstract
The external globus pallidus (GPe) is a critical node within the basal ganglia circuit. Phasic changes in the activity of GPe neurons during movement and their alterations in Parkinson's disease (PD) argue that the GPe is important in motor control. Parvalbumin-positive (PV+) neurons and Npas1+neurons are the two principal neuron classes in the GPe. The distinct electrophysiological properties and axonal projection patterns argue that these two neuron classes serve different roles in regulating motor output. However, the causal relationship between GPe neuron classes and movement remains to be established. Here, by using optogenetic approaches in mice (both males and females), we showed that PV+neurons and Npas1+neurons promoted and suppressed locomotion, respectively. Moreover, PV+neurons and Npas1+neurons are under different synaptic influences from the subthalamic nucleus (STN). Additionally, we found a selective weakening of STN inputs to PV+neurons in the chronic 6-hydroxydopamine lesion model of PD. This finding reinforces the idea that the reciprocally connected GPe–STN network plays a key role in disease symptomatology and thus provides the basis for future circuit-based therapies.SIGNIFICANCE STATEMENTThe external pallidum is a key, yet an understudied component of the basal ganglia. Neural activity in the pallidum goes awry in neurologic diseases, such as Parkinson's disease. While this strongly argues that the pallidum plays a critical role in motor control, it has been difficult to establish the causal relationship between pallidal activity and motor function/dysfunction. This was in part because of the cellular complexity of the pallidum. Here, we showed that the two principal neuron types in the pallidum have opposing roles in motor control. In addition, we described the differences in their synaptic influence. Importantly, our research provides new insights into the cellular and circuit mechanisms that explain the hypokinetic features of Parkinson's disease.
- Published
- 2020
36. Group testing in mediation analysis
- Author
-
Joshua N. Sampson, Andriy Derkach, Simina M. Boca, and Steven C. Moore
- Subjects
Statistics and Probability ,Epidemiology ,Computer science ,Inference ,Breast Neoplasms ,Familywise error rate ,Machine learning ,computer.software_genre ,01 natural sciences ,Article ,Statistical power ,010104 statistics & probability ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,medicine ,Humans ,Computer Simulation ,030212 general & internal medicine ,0101 mathematics ,Set (psychology) ,Mediation Analysis ,business.industry ,medicine.disease ,Group testing ,Outcome (probability) ,Postselection ,Female ,Artificial intelligence ,business ,computer - Abstract
We consider the scenario where there is an exposure, multiple biologically defined sets of biomarkers, and an outcome. We propose a new two-step procedure that tests if any of the sets of biomarkers mediate the exposure/outcome relationship, while maintaining a prespecified familywise error rate. The first step of the proposed procedure is a screening step that removes all groups that are unlikely to be strongly associated with both the exposure and the outcome. The second step adapts recent advances in postselection inference to test if there are true mediators in each of the remaining candidate sets. We use simulation to show that this simple two-step procedure has higher statistical power to detect true mediating sets when compared with existing procedures. We then use our two-step procedure to identify a set of Lysine-related metabolites that potentially mediate the known relationship between increased body mass index and the increased risk of estrogen-receptor positive breast cancer in postmenopausal women.
- Published
- 2020
37. Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure
- Author
-
Simina M. Boca, Jinhui Wang, Serghei Mangul, Vikas Bansal, Halie M. Rando, Joel D. Boerckel, Elizabeth Sell, Sergey Knyazev, Casey S. Greene, Stephen Capone, Lucy D'Agostino McGowan, Jeremy P. Kamil, Yuchen Sun, Nils Wellhausen, Sandipan Ray, Tiago Lubiana, John P. Barton, James Brian Byrd, Lamonica Shinholster, Alexandra J. Lee, YoSon Park, Ronan Lordan, Gregory L. Szeto, David Mai, Marouen Ben Guebila, John J. Dziak, Yanjun Qi, Christian Brueffer, Anthony Gitter, Ryan Velazquez, Rishi R. Goel, Adam L. MacLean, Ashwin N Skelly, and Gilbert, Jack A
- Subjects
Michael P. Robson ,Disease ,Review ,Biochemistry ,0302 clinical medicine ,2.2 Factors relating to the physical environment ,Bharath Ramsundar ,Vincent Rubinetti ,Aetiology ,Lung ,Coronavirus ,0303 health sciences ,Diane N. Rafizadeh ,Shikta Das ,Lucy D’Agostino McGowan ,Ronan Lordan ,virus diseases ,3. Good health ,Nafisa M. Jadavji ,Modeling and Simulation ,Pneumonia & Influenza ,Infection ,Alexandra J. Lee ,Amruta Naik ,Genomics ,Microbiology ,Article ,Dimitri Perrin ,03 medical and health sciences ,Simina M. Boca ,Biodefense ,Genetics ,genomics ,Author Correction ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Rishi Raj Goel ,viral pathogenesis ,Stephen Capone ,Prevention ,fungi ,Jinhui Wang ,Pneumonia ,biochemical phenomena, metabolism, and nutrition ,Editor's Pick ,Marouen Ben Guebila ,respiratory tract diseases ,FOS: Biological sciences ,Likhitha Kolla ,Daniel S. Himmelstein ,Nils Wellhausen ,Physiology ,Viral pathogenesis ,viruses ,Sergey Knyazev ,medicine.disease_cause ,Quantitative Biology - Quantitative Methods ,David Mai ,Yanjun Qi ,YoSon Park ,Ashwin N. Skelly ,Pandemic ,2.1 Biological and endogenous factors ,Temitayo Lukan ,030212 general & internal medicine ,Lamonica Shinholster ,Quantitative Methods (q-bio.QM) ,Transmission (medicine) ,Jeffrey M. Field ,respiratory system ,Casey S. Greene ,QR1-502 ,Computer Science Applications ,Infectious Diseases ,Head start ,Ryan Velazquez ,Sandipan Ray ,John P. Barton ,John J. Dziak ,Biotechnology ,Yuchen Sun ,Jeremy P. Kamil ,review ,COVID-19 Review Consortium Vikas Bansal ,Soumita Ghosh ,Biology ,Virus ,Vaccine Related ,Fengling Hu ,ddc:570 ,James Brian Byrd ,medicine ,Tiago Lubiana ,Joel D. Boerckel ,Adam L. MacLean ,Anna Ada Dattoli ,030304 developmental biology ,Halie M. Rando ,Yusha Sun ,Gregory L. Szeto ,Christian Brueffer ,COVID-19 ,Anthony Gitter ,David Manheim ,Emerging Infectious Diseases ,Good Health and Well Being ,Elizabeth Sell ,Serghei Mangul - Abstract
The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host. Because the genomic content of coronaviruses, which specifies the virus’s structure, is highly conserved, early genomic analysis provided a significant head start in predicting viral pathogenesis and in understanding potential differences among variants. The pathogenesis of the virus offers insights into symptomatology, transmission, and individual susceptibility. Additionally, prior research into interactions between the human immune system and coronaviruses has identified how these viruses can evade the immune system’s protective mechanisms. We also explore systems-level research into the regulatory and proteomic effects of SARS-CoV-2 infection and the immune response. Understanding the structure and behavior of the virus serves to contextualize the many facets of the COVID-19 pandemic and can influence efforts to control the virus and treat the disease. IMPORTANCE COVID-19 involves a number of organ systems and can present with a wide range of symptoms. From how the virus infects cells to how it spreads between people, the available research suggests that these patterns are very similar to those seen in the closely related viruses SARS-CoV-1 and possibly Middle East respiratory syndrome-related CoV (MERS-CoV). Understanding the pathogenesis of the SARS-CoV-2 virus also contextualizes how the different biological systems affected by COVID-19 connect. Exploring the structure, phylogeny, and pathogenesis of the virus therefore helps to guide interpretation of the broader impacts of the virus on the human body and on human populations. For this reason, an in-depth exploration of viral mechanisms is critical to a robust understanding of SARS-CoV-2 and, potentially, future emergent human CoVs (HCoVs).
- Published
- 2021
38. Proteogenomic Characterization of Pancreatic Ductal Adenocarcinoma
- Author
-
Marcin J. Domagalski, Wen Jiang, Michael Smith, Li Ding, Michael Schnaubelt, Oxana Paklina, Gilbert S. Omenn, Magdalena Derejska, Karin D. Rodland, Johanna Gardner, Saravana M. Dhanasekaran, Pamela Grady, Pushpa Hariharan, David Mallery, Jesse Francis, Maciej Wiznerowicz, Eunkyung An, Nancy Roche, Ralph H. Hruban, Samuel H. Payne, Chen Huang, Olga Potapova, Gad Getz, Zhiao Shi, Shuai Guo, Oliver F. Bathe, Stacey Gabriel, Sandra Cottingham, Hui Zhang, Daniel Cui Zhou, Maureen Dyer, Houxiang Zhu, James Suh, Shuang Cai, Christopher R. Kinsinger, Felipe da Veiga Leprevost, Steven Chen, Chelsea J. Newton, Amanda G. Paulovich, Steven A. Carr, Melissa Borucki, Sandra Cerda, Troy Shelton, D. R. Mani, Tara Hiltke, Lijun Chen, Benjamin Haibe-Kains, Jiang Long, Ratna R. Thangudu, Arul M. Chinnaiyan, Mathangi Thiagarajan, Negin Vatanian, Peter Ronning, Thomas L. Bauer, Ki Sung Um, Christina Ayad, Seungyeul Yoo, Mitual Amin, Ruiyang Liu, Alicia Francis, Nikolay Gabrovski, Eric E. Schadt, Zhen Zhang, Alexey I. Nesvizhskii, Hariharan Easwaran, Huan Chen, Tao Liu, Elizabeth R. Duffy, Liwei Cao, Joshua M. Wang, Michael H.A. Roehrl, Antonio Colaprico, Ana I. Robles, Emily S. Boja, Rita Jui-Hsien Lu, Rodrigo Vargas Eguez, Yize Li, Jennifer M. Koziak, Wenke Liu, Weiming Yang, Arvind Singh Mer, Dana R. Valley, Sailaja Mareedu, Song Cao, Scott D. Jewell, William Bocik, Shilpi Singh, Yongchao Dou, Matthew A. Wyczalkowski, David Fenyö, Galen Hostetter, Liqun Qi, Wenyi Wang, Yvonne Shutack, Shirley Tsang, Karen A. Ketchum, Charles A. Goldthwaite, Katherine A. Hoadley, Richard D. Smith, Karsten Krug, Yuxing Liao, Nadezhda V. Terekhanova, Henry Rodriguez, Barbara Hindenach, Matthew J. Ellis, Yingwei Hu, Pei Wang, Daniel C. Rohrer, Sara R. Savage, Grace Zhao, Ludmila Danilova, Yige Wu, Parham Minoo, Jennifer M. Eschbacher, Nathan Edwards, T. Mamie Lih, Simina M. Boca, George D. Wilson, Alexey Shabunin, Bing Zhang, Michael A. Gillette, Brian J. Druker, David J. Clark, Jianbo Pan, Katarzyna Kusnierz, David Chesla, Ronald Matteotti, Corbin D. Jones, Michael J. Birrer, Lori J. Sokoll, Qing Kay Li, Mehdi Mesri, Peter B. McGarvey, Chet Birger, Barbara Pruetz, Daniel W. Chan, Bo Wen, Nicollette Maunganidze, and Jasmine Huang
- Subjects
Adult ,Male ,Pancreatic ductal adenocarcinoma ,Proteome ,Gene Dosage ,Biology ,Adenocarcinoma ,medicine.disease_cause ,General Biochemistry, Genetics and Molecular Biology ,Article ,Epigenesis, Genetic ,Substrate Specificity ,Cohort Studies ,medicine ,Humans ,Molecular Targeted Therapy ,Phosphorylation ,Aged ,Glycoproteins ,Proteogenomics ,Aged, 80 and over ,MicroRNA sequencing ,Genome, Human ,RNA ,Endothelial Cells ,Methylation ,Middle Aged ,Phosphoproteins ,Prognosis ,Pancreatic Neoplasms ,Phenotype ,Cancer research ,Female ,KRAS ,Signal transduction ,Carcinogenesis ,Transcriptome ,Glycolysis ,Protein Kinases ,Algorithms ,Carcinoma, Pancreatic Ductal - Abstract
Summary Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.
- Published
- 2021
39. Integrated copy number and miRNA expression analysis in triple negative breast cancer of Latin American patients
- Author
-
Kepher H. Makambi, Rodrigo Coutinho de Almeida, Bruna M. Sugita, Saurabh Kirolikar, Silma Regina Ferreira Pereira, Iglenir J. Cavalli, Rubens Silveira de Lima, Simina M. Boca, Subha Madhavan, Mandeep Gill, Enilze Maria de Souza Fonseca Ribeiro, Yuriy Gusev, Paolo Fadda, Akanksha Mahajan, Cicero Urban, Anju Duttargi, and Luciane R. Cavalli
- Subjects
latinas ,0301 basic medicine ,Oncology ,medicine.medical_specialty ,Biology ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,Mirna expression ,copy number ,Internal medicine ,microRNA ,Tumor stage ,medicine ,Mirna profiling ,Gene ,Triple-negative breast cancer ,disparities ,3. Good health ,Tumor Subtype ,030104 developmental biology ,030220 oncology & carcinogenesis ,triple-negative breast cancer ,Research Paper - Abstract
Triple negative breast cancer (TNBC), a clinically aggressive breast cancer subtype, affects 15–35% of women from Latin America. Using an approach of direct integration of copy number and global miRNA profiling data, performed simultaneously in the same tumor specimens, we identified a panel of 17 miRNAs specifically associated with TNBC of ancestrally characterized patients from Latin America, Brazil. This panel was differentially expressed between the TNBC and non-TNBC subtypes studied (p ≤ 0.05, FDR ≤ 0.25), with their expression levels concordant with the patterns of copy number alterations (CNAs), present mostly frequent at 8q21.3-q24.3, 3q24-29, 6p25.3-p12.2, 1q21.1-q44, 5q11.1-q22.1, 11p13-p11.2, 13q12.11-q14.3, 17q24.2-q25.3 and Xp22.33-p11.21. The combined 17 miRNAs presented a high power (AUC = 0.953 (0.78–0.99);95% CI) in discriminating between the TNBC and non-TNBC subtypes of the patients studied. In addition, the expression of 14 and 15 of the 17miRNAs was significantly associated with tumor subtype when adjusted for tumor stage and grade, respectively. In conclusion, the panel of miRNAs identified demonstrated the impact of CNAs in miRNA expression levels and identified miRNA target genes potentially affected by both CNAs and miRNA deregulation. These targets, involved in critical signaling pathways and biological functions associated specifically with the TNBC transcriptome of Latina patients, can provide biological insights into the observed differences in the TNBC clinical outcome among racial/ethnic groups, taking into consideration their genetic ancestry.
- Published
- 2019
40. A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients
- Author
-
Davendra Sohal, Bradley J. Monk, R Joseph Bender, Michael J. Pishvaian, Patricia DeArbeloa, Kathleen N. Moore, Robert L. Coleman, Shruti Rao, David D Halverson, Andrew Eugene Hendifar, Thomas J. Herzog, Subha Madhavan, Paula R. Pohlmann, Emanuel F. Petricoin, Edik M. Blais, Vincent Chung, Sam Mikhail, Kai He, and Simina M. Boca
- Subjects
0301 basic medicine ,medicine.medical_specialty ,Clinical Trials and Supportive Activities ,Bioengineering ,Health Informatics ,Cloud computing ,precision informatics ,Research and Applications ,Turnaround time ,Ranking (information retrieval) ,03 medical and health sciences ,virtual tumor boards ,0302 clinical medicine ,Clinical Research ,medicine ,Chat room ,Medical physics ,Cancer ,Point of care ,implementation science ,business.industry ,molecular tumor boards ,3. Good health ,Clinical trial ,Networking and Information Technology R&D ,Good Health and Well Being ,030104 developmental biology ,Asynchronous communication ,precision oncology ,030220 oncology & carcinogenesis ,Informatics ,business - Abstract
Objectives Scalable informatics solutions that provide molecularly tailored treatment recommendations to clinicians are needed to streamline precision oncology in care settings. Materials and Methods We developed a cloud-based virtual molecular tumor board (VMTB) platform that included a knowledgebase, scoring model, rules engine, an asynchronous virtual chat room and a reporting tool that generated a treatment plan for each of the 1725 patients based on their molecular profile, previous treatment history, structured trial eligibility criteria, clinically relevant cancer gene-variant assertions, biomarker-treatment associations, and current treatment guidelines. The VMTB systematically allows clinician users to combine expert-curated data and structured data from clinical charts along with molecular testing data to develop consensus on treatments, especially those that require off-label and clinical trial considerations. Results The VMTB was used as part of the cancer care process for a focused subset of 1725 patients referred by advocacy organizations wherein resultant personalized reports were successfully delivered to treating oncologists. Median turnaround time from data receipt to report delivery decreased from 14 days to 4 days over 4 years while the volume of cases increased nearly 2-fold each year. Using a novel scoring model for ranking therapy options, oncologists chose to implement the VMTB-derived therapies over others, except when pursuing immunotherapy options without molecular support. Discussion VMTBs will play an increasingly critical role in precision oncology as the compendium of biomarkers and associated therapy options available to a patient continues to expand. Conclusion Further development of such clinical augmentation tools that systematically combine patient-derived molecular data, real-world evidence from electronic health records and expert curated knowledgebases on biomarkers with computational tools for ranking best treatments can support care pathways at point of care.
- Published
- 2019
41. The Relationship Between Haplotype-Based F ST and Haplotype Length
- Author
-
Rohan S. Mehta, Noah A. Rosenberg, Alison F. Feder, and Simina M. Boca
- Subjects
Genetics ,0303 health sciences ,Genetic diversity ,Linkage disequilibrium ,Haplotype ,Locus (genetics) ,Single-nucleotide polymorphism ,Biology ,DNA sequencing ,03 medical and health sciences ,0302 clinical medicine ,Allele ,human activities ,Allele frequency ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
F ST is a statistic that is frequently used to analyze population structure. Recent work has shown that FST depends strongly on the underlying genetic diversity of a locus from which it is computed... The population-genetic statistic FST is used widely to describe allele frequency distributions in subdivided populations. The increasing availability of DNA sequence data has recently enabled computations of FST from sequence-based “haplotype loci.” At the same time, theoretical work has revealed that FST has a strong dependence on the underlying genetic diversity of a locus from which it is computed, with high diversity constraining values of FST to be low. In the case of haplotype loci, for which two haplotypes that are distinct over a specified length along a chromosome are treated as distinct alleles, genetic diversity is influenced by haplotype length: longer haplotype loci have the potential for greater genetic diversity. Here, we study the dependence of FST on haplotype length. Using a model in which a haplotype locus is sequentially incremented by one biallelic locus at a time, we show that increasing the length of the haplotype locus can either increase or decrease the value of FST, and usually decreases it. We compute FST on haplotype loci in human populations, finding a close correspondence between the observed values and our theoretical predictions. We conclude that effects of haplotype length are valuable to consider when interpreting FST calculated on haplotypic data.
- Published
- 2019
42. Endogenous Gastrin Collaborates With Mutant KRAS in Pancreatic Carcinogenesis
- Author
-
Ashley Jermusyck, Irene Collins, Juan Wang, Narayan Shivapurkar, Sandeep Nadella, Emanuel F. Petricoin, Matthew Huber, Simina M. Boca, Hong Cao, Eveline E. Vietsch, K. Alex Hodge, Jill P. Smith, Bhaskar Kallakury, Waxing Cui, Mariaelena Pierobon, Laufey T. Amundadottir, Robin D. Tucker, and Julian Burks
- Subjects
endocrine system diseases ,Carcinogenesis ,Endocrinology, Diabetes and Metabolism ,Pancreatic Intraepithelial Neoplasia ,Mice, Transgenic ,Biology ,medicine.disease_cause ,digestive system ,Proto-Oncogene Proteins p21(ras) ,03 medical and health sciences ,0302 clinical medicine ,Endocrinology ,Cell Line, Tumor ,Pancreatic cancer ,Gastrins ,microRNA ,Internal Medicine ,medicine ,Animals ,Humans ,Autocrine signalling ,Pancreas ,Cell Proliferation ,Laser capture microdissection ,Gastrin ,Mice, Knockout ,Hepatology ,Kinase ,Gene Expression Profiling ,medicine.disease ,Gene Expression Regulation, Neoplastic ,Pancreatic Neoplasms ,MicroRNAs ,030220 oncology & carcinogenesis ,Mutation ,Cancer research ,030211 gastroenterology & hepatology ,KRAS ,Carcinoma in Situ ,hormones, hormone substitutes, and hormone antagonists - Abstract
Objective The KRAS gene is the most frequently mutated gene in pancreatic cancer, and no successful anti-Ras therapy has been developed. Gastrin has been shown to stimulate pancreatic cancer in an autocrine fashion. We hypothesized that reactivation of the peptide gastrin collaborates with KRAS during pancreatic carcinogenesis. Methods LSL-Kras; P48-Cre (KC) mutant KRAS transgenic mice were crossed with gastrin-KO (GKO) mice to develop GKO/KC mice. Pancreata were examined for 8 months for stage of pancreatic intraepithelial neoplasia lesions, inflammation, fibrosis, gastrin peptide, and microRNA expression. Pancreatic intraepithelial neoplasias from mice were collected by laser capture microdissection and subjected to reverse-phase protein microarray, for gastrin and protein kinases associated with signal transduction. Gastrin mRNA was measured by RNAseq in human pancreatic cancer tissues and compared to that in normal pancreas. Results In the absence of gastrin, PanIN progression, inflammation, and fibrosis were significantly decreased and signal transduction was reversed to the canonical pathway with decreased KRAS. Gastrin re-expression in the PanINs was mediated by miR-27a. Gastrin mRNA expression was significantly increased in human pancreatic cancer samples compared to normal human pancreas controls. Conclusions This study supports the mitogenic role of gastrin in activation of KRAS during pancreatic carcinogenesis.
- Published
- 2019
43. Sources of variability in metabolite measurements from urinary samples.
- Author
-
Qian Xiao, Steven C Moore, Simina M Boca, Charles E Matthews, Nathaniel Rothman, Rachael Z Stolzenberg-Solomon, Rashmi Sinha, Amanda J Cross, and Joshua N Sampson
- Subjects
Medicine ,Science - Abstract
The application of metabolomics in epidemiological studies would potentially allow researchers to identify biomarkers associated with exposures and diseases. However, within-individual variability of metabolite levels caused by temporal variation of metabolites, together with technical variability introduced by laboratory procedures, may reduce the study power to detect such associations. We assessed the sources of variability of metabolites from urine samples and the implications for designing epidemiologic studies.We measured 539 metabolites in urine samples from the Navy Colon Adenoma Study using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectroscopy (GC-MS). The study collected 2-3 samples per person from 17 male subjects (age 38-70) over 2-10 days. We estimated between-individual, within-individual, and technical variability and calculated expected study power with a specific focus on large case-control and nested case-control studies.Overall technical reliability was high (median intraclass correlation = 0.92), and for 72% of the metabolites, the majority of total variance can be attributed to between-individual variability. Age, gender and body mass index explained only a small proportion of the total metabolite variability. For a relative risk (comparing upper and lower quartiles of "usual" levels) of 1.5, we estimated that a study with 500, 1,000, and 5,000 individuals could detect 1.0%, 4.5% and 75% of the metabolite associations.The use of metabolomics in urine samples from epidemiological studies would require large sample sizes to detect associations with moderate effect sizes.
- Published
- 2014
- Full Text
- View/download PDF
44. Proteogenomic and metabolomic characterization of human glioblastoma
- Author
-
Cristina E. Tognon, Larisa Polonskaya, Tara Skelly, Shuang Cai, Francesmary Modugno, Larissa Rossell, Nancy Roche, Chen Huang, Jessika Baral, Fulvio D'Angelo, Wen-Wei Liang, Chia-Feng Tsai, Sneha P. Couvillion, Karin D. Rodland, Jun Zhu, Liang-Bo Wang, Paul D. Piehowski, Antonio Colaprico, Anupriya Agarwal, Matthew A. Wyczalkowski, Umut Ozbek, Francesca Petralia, Alexis Demopoulos, William W. Maggio, Lin Chen, Katherine A. Hoadley, Richard D. Smith, Sandra Cottingham, John McGee, Marcin J. Domagalski, Houxiang Zhu, Emek Demir, Rebecca I. Montgomery, Jamie Moon, Rashna Madan, George D. Wilson, Luciano Garofano, Ewa P. Malc, Chelsea J. Newton, Steven A. Carr, Chandan Kumar-Sinha, Donghui Tan, Christopher R. Kinsinger, Oxana Paklina, Weiqing Wan, Stephanie De Young, Sandra Cerda, Shankha Satpathy, Wojciech Kaspera, Linda Hannick, Gad Getz, Runyu Hong, Shuangjia Lu, Ziad Hanhan, Daniel C. Rohrer, Annette Marrero-Oliveras, Wojciech Szopa, Yuxing Liao, Amanda G. Paulovich, Jiayi Ji, Denis A. Golbin, Tara Hiltke, Weiva Sieh, Piotr A. Mieczkowski, Matthew E. Monroe, Gilbert S. Omenn, Jill S. Barnholtz-Sloan, Azra Krek, Bing Zhang, Brittany Henderson, Peter B. McGarvey, Ratna R. Thangudu, Maciej Wiznerowicz, Saravana M. Dhanasekaran, Alex Webster, Kai Li, Karna Robinson, Nan Ji, Karl K. Weitz, Simina M. Boca, Xiaoyu Song, Anna Calinawan, Adam C. Resnick, Brian J. Druker, Dana R. Valley, David J. Clark, Tao Liu, Eric J. Jaehnig, Alicia Francis, Michele Ceccarelli, Rui Zhao, Dmitry Rykunov, Boris Reva, Elizabeth R. Duffy, Antonio Iavarone, Dave Tabor, Joshua F. McMichael, Daniel Cui Zhou, Maureen Dyer, Kimberly Elburn, Scott D. Jewell, Negin Vatanian, Shirley Tsang, Seungyeul Yoo, Alexander R. Pico, Grace Zhao, Kent J. Bloodsworth, Chet Birger, Jena Lilly, Eunkyung An, Jeffrey R. Whiteaker, Albert H. Kim, Yige Wu, Karen A. Ketchum, Felipe D. Leprevost, Alcida Karz, Uma Borate, Nathan Edwards, Uma Velvulou, Melissa Borucki, Vasileios Stathias, Sanford P. Markey, Corbin D. Jones, Ronald J. Moore, MacIntosh Cornwell, Karsten Krug, Michael J. Birrer, James Suh, Tomasz Czernicki, Jason E. McDermott, Emily S. Boja, Pei Wang, Nina Martinez, Wenke Liu, Yan Shi, Lili Blumenberg, Emily Kawaler, Jeffrey W. Tyner, Feng Chen, Jakub Stawicki, Ki Sung Um, Arul M. Chinnaiyan, Robert Zelt, Jacob J. Day, Zhen Zhang, Caleb M. Lindgren, Li Ding, Nikolay Gabrovski, Hongwei Liu, Jonathan T. Lei, Alla Karpova, Ramani B. Kothadia, Sailaja Mareedu, Mitual Amin, Hannah Boekweg, Jennifer E. Kyle, Sara R. Savage, Brian R. Rood, Yuriy Zakhartsev, Matthew L. Anderson, Alyssa Charamut, Wagma Caravan, Shakti Ramkissoon, Junmei Wang, Song Cao, Samuel H. Payne, Rosalie K. Chu, Rajiv Dhir, David W. Andrews, Galen Hostetter, Liqun Qi, Zhiao Shi, Milan G. Chheda, Robert Edwards, Hui Zhang, Weiping Ma, Jennifer M. Eschbacher, Stacey Gabriel, Jan Lubinski, Lijun Yao, Erika M. Zink, Kelly L. Stratton, William Bocik, Mathangi Thiagarajan, Shilpi Singh, Michael A. Gillette, Lisa M. Bramer, Thomas L. Bauer, Michael Vernon, Henry Rodriguez, Dimitris G. Placantonakis, Eric E. Schadt, Alexey I. Nesvizhskii, Vladislav A. Petyuk, Ana I. Robles, Yvonne Shutack, Anna Malovannaya, Stephen E. Stein, Xi Chen, Lyndon Kim, Yize Li, Shannon Richey, Stephan C. Schürer, Barbara Hindenach, Matthew J. Ellis, Yongchao Dou, David Fenyö, Amy M. Perou, Olga Potapova, Shrabanti Chowdhury, Andrew K. Godwin, Marcin Cieślik, Michael C. Wendl, Marina A. Gritsenko, Pietro Pugliese, Elie Traer, Simona Migliozzi, D. R. Mani, Houston Culpepper, Gregory J. Riggins, Xiaolu Yang, Mehdi Mesri, David Chesla, Lindsey K. Olsen, Lori J. Sokoll, Suhas Vasaikar, Liwei Zhang, Meghan C. Burke, Kelly V. Ruggles, Qing Kay Li, Daniel W. Chan, Bo Wen, Nicollette Maunganidze, Darlene Tansil, Joseph H. Rothstein, Barbara Pruetz, Pushpa Hariharan, Wang, L. -B., Karpova, A., Gritsenko, M. A., Kyle, J. E., Cao, S., Li, Y., Rykunov, D., Colaprico, A., Rothstein, J. H., Hong, R., Stathias, V., Cornwell, M., Petralia, F., Wu, Y., Reva, B., Krug, K., Pugliese, P., Kawaler, E., Olsen, L. K., Liang, W. -W., Song, X., Dou, Y., Wendl, M. C., Caravan, W., Liu, W., Cui Zhou, D., Ji, J., Tsai, C. -F., Petyuk, V. A., Moon, J., Ma, W., Chu, R. K., Weitz, K. K., Moore, R. J., Monroe, M. E., Zhao, R., Yang, X., Yoo, S., Krek, A., Demopoulos, A., Zhu, H., Wyczalkowski, M. A., Mcmichael, J. F., Henderson, B. L., Lindgren, C. M., Boekweg, H., Lu, S., Baral, J., Yao, L., Stratton, K. G., Bramer, L. M., Zink, E., Couvillion, S. P., Bloodsworth, K. J., Satpathy, S., Sieh, W., Boca, S. M., Schurer, S., Chen, F., Wiznerowicz, M., Ketchum, K. A., Boja, E. S., Kinsinger, C. R., Robles, A. I., Hiltke, T., Thiagarajan, M., Nesvizhskii, A. I., Zhang, B., Mani, D. R., Ceccarelli, M., Chen, X. S., Cottingham, S. L., Li, Q. K., Kim, A. H., Fenyo, D., Ruggles, K. V., Rodriguez, H., Mesri, M., Payne, S. H., Resnick, A. C., Wang, P., Smith, R. D., Iavarone, A., Chheda, M. G., Barnholtz-Sloan, J. S., Rodland, K. D., Liu, T., Ding, L., Agarwal, A., Amin, M., An, E., Anderson, M. L., Andrews, D. W., Bauer, T., Birger, C., Birrer, M. J., Blumenberg, L., Bocik, W. E., Borate, U., Borucki, M., Burke, M. C., Cai, S., Calinawan, A. P., Carr, S. A., Cerda, S., Chan, D. W., Charamut, A., Chen, L. S., Chesla, D., Chinnaiyan, A. M., Chowdhury, S., Cieslik, M. P., Clark, D. J., Culpepper, H., Czernicki, T., D'Angelo, F., Day, J., De Young, S., Demir, E., Dhanasekaran, S. M., Dhir, R., Domagalski, M. J., Druker, B., Duffy, E., Dyer, M., Edwards, N. J., Edwards, R., Elburn, K., Ellis, M. J., Eschbacher, J., Francis, A., Gabriel, S., Gabrovski, N., Garofano, L., Getz, G., Gillette, M. A., Godwin, A. K., Golbin, D., Hanhan, Z., Hannick, L. I., Hariharan, P., Hindenach, B., Hoadley, K. A., Hostetter, G., Huang, C., Jaehnig, E., Jewell, S. D., Ji, N., Jones, C. D., Karz, A., Kaspera, W., Kim, L., Kothadia, R. B., Kumar-Sinha, C., Lei, J., Leprevost, F. D., Li, K., Liao, Y., Lilly, J., Liu, H., Lubinski, J., Madan, R., Maggio, W., Malc, E., Malovannaya, A., Mareedu, S., Markey, S. P., Marrero-Oliveras, A., Martinez, N., Maunganidze, N., Mcdermott, J. E., Mcgarvey, P. B., Mcgee, J., Mieczkowski, P., Migliozzi, S., Modugno, F., Montgomery, R., Newton, C. J., Omenn, G. S., Ozbek, U., Paklina, O. V., Paulovich, A. G., Perou, A. M., Pico, A. R., Piehowski, P. D., Placantonakis, D. G., Polonskaya, L., Potapova, O., Pruetz, B., Qi, L., Ramkissoon, S., Resnick, A., Richey, S., Riggins, G., Robinson, K., Roche, N., Rohrer, D. C., Rood, B. R., Rossell, L., Savage, S. R., Schadt, E. E., Shi, Y., Shi, Z., Shutack, Y., Singh, S., Skelly, T., Sokoll, L. J., Stawicki, J., Stein, S. E., Suh, J., Szopa, W., Tabor, D., Tan, D., Tansil, D., Thangudu, R. R., Tognon, C., Traer, E., Tsang, S., Tyner, J., Um, K. S., Valley, D. R., Vasaikar, S., Vatanian, N., Velvulou, U., Vernon, M., Wan, W., Wang, J., Webster, A., Wen, B., Whiteaker, J. R., Wilson, G. D., Zakhartsev, Y., Zelt, R., Zhang, H., Zhang, L., Zhang, Z., Zhao, G., and Zhu, J.
- Subjects
Proteomics ,0301 basic medicine ,Cancer Research ,CPTAC ,Histone H2B acetylation ,Protein Tyrosine Phosphatase, Non-Receptor Type 11 ,Computational biology ,Biology ,Article ,03 medical and health sciences ,lipidome ,0302 clinical medicine ,Metabolomics ,proteogenomic ,Humans ,Phosphorylation ,EP300 ,proteomic ,Proteogenomics ,acetylome ,single nuclei RNA-seq ,Brain Neoplasms ,Phospholipase C gamma ,glioblastoma ,Computational Biology ,Lipidome ,030104 developmental biology ,Histone ,Oncology ,Acetylation ,030220 oncology & carcinogenesis ,Mutation ,biology.protein ,metabolome ,signaling - Abstract
Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment. Wang et al. perform integrated proteogenomic analysis of adult glioblastoma (GBM), including metabolomics, lipidomics, and single nuclei RNA-Seq, revealing insights into the immune landscape of GBM, cell-specific nature of EMT signatures, histone acetylation in classical GBM, and the existence of signaling hubs which could provide therapeutic vulnerabilities.
- Published
- 2021
45. Pathogenesis, Symptomatology, and Transmission of SARS-CoV-2 through Analysis of Viral Genomics and Structure.
- Author
-
Rando, Halie M, Rando, Halie M, MacLean, Adam L, Lee, Alexandra J, Lordan, Ronan, Ray, Sandipan, Bansal, Vikas, Skelly, Ashwin N, Sell, Elizabeth, Dziak, John J, Shinholster, Lamonica, D'Agostino McGowan, Lucy, Ben Guebila, Marouen, Wellhausen, Nils, Knyazev, Sergey, Boca, Simina M, Capone, Stephen, Qi, Yanjun, Park, YoSon, Mai, David, Sun, Yuchen, Boerckel, Joel D, Brueffer, Christian, Byrd, James Brian, Kamil, Jeremy P, Wang, Jinhui, Velazquez, Ryan, Szeto, Gregory L, Barton, John P, Goel, Rishi Raj, Mangul, Serghei, Lubiana, Tiago, COVID-19 Review Consortium Vikas Bansal, John P. Barton, Simina M. Boca, Joel D. Boerckel, Christian Brueffer, James Brian Byrd, Stephen Capone, Shikta Das, Anna Ada Dattoli, John J. Dziak, Jeffrey M. Field, Soumita Ghosh, Anthony Gitter, Rishi Raj Goel, Casey S. Greene, Marouen Ben Guebila, Daniel S. Himmelstein, Fengling Hu, Nafisa M. Jadavji, Jeremy P. Kamil, Sergey Knyazev, Likhitha Kolla, Alexandra J. Lee, Ronan Lordan, Tiago Lubiana, Temitayo Lukan, Adam L. MacLean, David Mai, Serghei Mangul, David Manheim, Lucy D’Agostino McGowan, Amruta Naik, YoSon Park, Dimitri Perrin, Yanjun Qi, Diane N. Rafizadeh, Bharath Ramsundar, Halie M. Rando, Sandipan Ray, Michael P. Robson, Vincent Rubinetti, Elizabeth Sell, Lamonica Shinholster, Ashwin N. Skelly, Yuchen Sun, Yusha Sun, Gregory L. Szeto, Ryan Velazquez, Jinhui Wang, Nils Wellhausen, Gitter, Anthony, Greene, Casey S, Rando, Halie M, Rando, Halie M, MacLean, Adam L, Lee, Alexandra J, Lordan, Ronan, Ray, Sandipan, Bansal, Vikas, Skelly, Ashwin N, Sell, Elizabeth, Dziak, John J, Shinholster, Lamonica, D'Agostino McGowan, Lucy, Ben Guebila, Marouen, Wellhausen, Nils, Knyazev, Sergey, Boca, Simina M, Capone, Stephen, Qi, Yanjun, Park, YoSon, Mai, David, Sun, Yuchen, Boerckel, Joel D, Brueffer, Christian, Byrd, James Brian, Kamil, Jeremy P, Wang, Jinhui, Velazquez, Ryan, Szeto, Gregory L, Barton, John P, Goel, Rishi Raj, Mangul, Serghei, Lubiana, Tiago, COVID-19 Review Consortium Vikas Bansal, John P. Barton, Simina M. Boca, Joel D. Boerckel, Christian Brueffer, James Brian Byrd, Stephen Capone, Shikta Das, Anna Ada Dattoli, John J. Dziak, Jeffrey M. Field, Soumita Ghosh, Anthony Gitter, Rishi Raj Goel, Casey S. Greene, Marouen Ben Guebila, Daniel S. Himmelstein, Fengling Hu, Nafisa M. Jadavji, Jeremy P. Kamil, Sergey Knyazev, Likhitha Kolla, Alexandra J. Lee, Ronan Lordan, Tiago Lubiana, Temitayo Lukan, Adam L. MacLean, David Mai, Serghei Mangul, David Manheim, Lucy D’Agostino McGowan, Amruta Naik, YoSon Park, Dimitri Perrin, Yanjun Qi, Diane N. Rafizadeh, Bharath Ramsundar, Halie M. Rando, Sandipan Ray, Michael P. Robson, Vincent Rubinetti, Elizabeth Sell, Lamonica Shinholster, Ashwin N. Skelly, Yuchen Sun, Yusha Sun, Gregory L. Szeto, Ryan Velazquez, Jinhui Wang, Nils Wellhausen, Gitter, Anthony, and Greene, Casey S
- Abstract
The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host. Because the genomic content of coronaviruses, which specifies the virus's structure, is highly conserved, early genomic analysis provided a significant head start in predicting viral pathogenesis and in understanding potential differences among variants. The pathogenesis of the virus offers insights into symptomatology, transmission, and individual susceptibility. Additionally, prior research into interactions between the human immune system and coronaviruses has identified how these viruses can evade the immune system's protective mechanisms. We also explore systems-level research into the regulatory and proteomic effects of SARS-CoV-2 infection and the immune response. Understanding the structure and behavior of the virus serves to contextualize the many facets of the COVID-19 pandemic and can influence efforts to control the virus and treat the disease. IMPORTANCE COVID-19 involves a number of organ systems and can present with a wide range of symptoms. From how the virus infects cells to how it spreads between people, the available research suggests that these patterns are very similar to those seen in the closely related viruses SARS-CoV-1 and possibly Middle East respiratory syndrome-related CoV (MERS-CoV). Understanding the pathogenesis of the SARS-CoV-2 virus also contextualizes how the different biological systems affected by COVID-19 connect. Exploring the str
- Published
- 2021
46. Understanding bias when estimating life expectancy from age at death: A simulation approach applied to Morquio Syndrome A
- Author
-
Simina M. Boca, Xue Yin, and Jaeil Ahn
- Subjects
Simulations ,Change over time ,Morquio syndrome ,Science (General) ,QH301-705.5 ,Context (language use) ,General Biochemistry, Genetics and Molecular Biology ,Cohort Studies ,Q1-390 ,Life Expectancy ,Bias ,Humans ,Medicine ,Biology (General) ,Retrospective Studies ,Estimation ,Kaplan–Meier ,business.industry ,Age at death ,Mucopolysaccharidosis IV ,Morquio syndrome A ,General Medicine ,medicine.disease ,Research Note ,Cohort ,Life expectancy ,business ,Estimation methods ,Demography - Abstract
BackgroundLife expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. Due to the difficult and time-consuming nature of following a cohort prospectively, life expectancy is often assessed based on death data, which may lead to potentially biased estimates. This is more likely to be a problem in rare diseases such as Morquio syndrome A.MethodTo investigate how accurate the estimation of life expectancy is using death data, we simulate the survival of individuals with Morquio syndrome A under four different survival scenarios. In each scenario, we estimate the mean and median survival times within a defined period and compare them with the true life expectancy.ResultsWhen life expectancy is constant during the entire period, using death data does not result in a biased estimate of life expectancy. However, when life expectancy increases during the follow-up period, using only death data leads to a substantial underestimation of life expectancy.ConclusionLife expectancy can change over time, along with changes in the environment and/or biomedical innovation. When the life expectancy is increasing — as is often expected to be the case in rare diseases — estimating it based on contemporary death data will result in a downward bias. Therefore, it is crucial to understand how estimates of life expectancy are obtained and to interpret them in an appropriate context, and to assess estimation methods within a sensitivity analysis framework, similar to the simulations performed herein.
- Published
- 2020
47. Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices
- Author
-
Samir Gupta, Subha Madhavan, Ian F. G. King, Shruti Rao, Matthew McCoy, Beth A. Pitel, Ben Ho Park, James L. Chen, Debyani Chakravarty, Peter K. Rogan, Malachi Griffith, Simina M. Boca, Obi L. Griffith, Alex H. Wagner, and Jeremy L. Warner
- Subjects
0301 basic medicine ,medicine.medical_specialty ,Special Series: Next Generation Sequencing ,Knowledge Bases ,Information Dissemination ,MEDLINE ,Genomics ,Biochemistry ,03 medical and health sciences ,0302 clinical medicine ,Multidisciplinary approach ,Artificial Intelligence ,Neoplasms ,medicine ,Humans ,Intensive care medicine ,Tumor biology ,business.industry ,REVIEW ARTICLES ,Cancer ,General Medicine ,medicine.disease ,Disease etiology ,030104 developmental biology ,030220 oncology & carcinogenesis ,Risk stratification ,business - Abstract
PURPOSE The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning. METHODS In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards. RESULTS Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence. CONCLUSION Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.
- Published
- 2020
48. Cardiovascular Phenotyping in Breast Cancer Patients Treated With Her2 Targeted Therapies Using Informatics Approaches
- Author
-
Brian Conkright, Ana Barac, Adil Alaoui, Yuriy Gusev, Krithika Bhuvaneshwar, Rebecca Torguson, Shahla Riazi, Federico M. Asch, Simina M. Boca, Subha Madhavan, Paula R. Pohlmann, Robert M. Johnson, and Michael Harris
- Subjects
Oncology ,medicine.medical_specialty ,Breast cancer ,business.industry ,Internal medicine ,Informatics ,medicine ,business ,medicine.disease - Abstract
Background Cardiotoxicity is a serious adverse event associated with some of the most effective breast cancer therapies. Currently, it is difficult to predict which patients will develop cardiotoxicity due to the multiplicity of clinical, behavioral, and biological factors involved. MethodsHere we describe an effort to apply biomedical informatics approaches to patient data from MedStar Health’s EHR systems to discover and characterize factors that contribute to cardiotoxicity in a real world breast cancer population.ResultsData wrangling techniques including merging data from disparate clinical systems, data transformation, and de-identification of personal health information (PHI)were appliedto the raw clinical data to produce a structured integrated dataset for predictive analysis and hypothesis generation. Using this dataset as input, weshowed howpredictive models can be developed to identify patients at high risk for cardiotoxicity. ConclusionsWe demonstrate how suchmodels can be used for hypothesis generation and data exploration with the ultimate goal of developing applications for precision medicine.
- Published
- 2020
49. Parvalbumin+ and Npas1+ Pallidal Neurons Have Distinct Circuit Topology and Function
- Author
-
Talia N. Lerner, Isabel Fan, Harry S. Xenias, Simina M. Boca, Adam W. Hantman, Elizabeth C. Augustine, Brianna L. Berceau, Qiaoling Cui, Saivasudha Chalasani, Arin Pamukcu, and C. Savio Chan
- Subjects
0303 health sciences ,NPAS1 ,biology ,Motor control ,Optogenetics ,03 medical and health sciences ,Electrophysiology ,Subthalamic nucleus ,0302 clinical medicine ,medicine.anatomical_structure ,nervous system ,Basal ganglia ,biology.protein ,medicine ,Neuron ,Neuroscience ,030217 neurology & neurosurgery ,Parvalbumin ,030304 developmental biology - Abstract
The external globus pallidus (GPe) is a critical node within the basal ganglia circuit. Phasic changes in the activity of GPe neurons during movement and their alterations in Parkinson’s disease (PD) argue that the GPe is important in motor control. PV+ neurons and Npas1+ neurons are the two principal neuron classes in the GPe. The distinct electrophysiological properties and axonal projection patterns argue that these two neuron classes serve different roles in regulating motor output. However, the causal relationship between GPe neuron classes and movement remains to be established. Here, by using optogenetic approaches in mice (both males and females), we showed that PV+ neurons and Npas1+ neurons promoted and suppressed locomotion, respectively. Moreover, PV+ neurons and Npas1+ neurons are under different synaptic influences from the subthalamic nucleus (STN). Additionally, we found a selective weakening of STN inputs to PV+ neurons in the chronic 6-hydroxydopamine lesion model of PD. This finding reinforces the idea that the reciprocally connected GPe-STN network plays a key role in disease symptomatology and thus provides the basis for future circuit-based therapies.Significance StatementThe external pallidum is a key, yet an understudied component of the basal ganglia. Neural activity in the pallidum goes awry in neurological diseases, such as Parkinson’s disease. While this strongly argues that the pallidum plays a critical role in motor control, it has been difficult to establish the causal relationship between pallidal activity and motor (dys)function. This was in part due to the cellular complexity of the pallidum. Here, we showed that the two principal neuron types in the pallidum have opposing roles in motor control. In addition, we described the differences in their synaptic influence. Importantly, our research provides new insights into the cellular and circuit mechanisms that explain the hypokinetic features of Parkinson’s disease.
- Published
- 2020
- Full Text
- View/download PDF
50. Parvalbumin
- Author
-
Arin, Pamukcu, Qiaoling, Cui, Harry S, Xenias, Brianna L, Berceau, Elizabeth C, Augustine, Isabel, Fan, Saivasudha, Chalasani, Adam W, Hantman, Talia N, Lerner, Simina M, Boca, and C Savio, Chan
- Subjects
Male ,Neurons ,Nerve Tissue Proteins ,Globus Pallidus ,Axons ,Electrophysiological Phenomena ,Optogenetics ,Mice ,Parvalbumins ,nervous system ,Subthalamic Nucleus ,Synapses ,Basic Helix-Loop-Helix Transcription Factors ,Animals ,Female ,Nerve Net ,Locomotion ,Research Articles - Abstract
The external globus pallidus (GPe) is a critical node within the basal ganglia circuit. Phasic changes in the activity of GPe neurons during movement and their alterations in Parkinson's disease (PD) argue that the GPe is important in motor control. Parvalbumin-positive (PV(+)) neurons and Npas1(+) neurons are the two principal neuron classes in the GPe. The distinct electrophysiological properties and axonal projection patterns argue that these two neuron classes serve different roles in regulating motor output. However, the causal relationship between GPe neuron classes and movement remains to be established. Here, by using optogenetic approaches in mice (both males and females), we showed that PV(+) neurons and Npas1(+) neurons promoted and suppressed locomotion, respectively. Moreover, PV(+) neurons and Npas1(+) neurons are under different synaptic influences from the subthalamic nucleus (STN). Additionally, we found a selective weakening of STN inputs to PV(+) neurons in the chronic 6-hydroxydopamine lesion model of PD. This finding reinforces the idea that the reciprocally connected GPe–STN network plays a key role in disease symptomatology and thus provides the basis for future circuit-based therapies. SIGNIFICANCE STATEMENT The external pallidum is a key, yet an understudied component of the basal ganglia. Neural activity in the pallidum goes awry in neurologic diseases, such as Parkinson's disease. While this strongly argues that the pallidum plays a critical role in motor control, it has been difficult to establish the causal relationship between pallidal activity and motor function/dysfunction. This was in part because of the cellular complexity of the pallidum. Here, we showed that the two principal neuron types in the pallidum have opposing roles in motor control. In addition, we described the differences in their synaptic influence. Importantly, our research provides new insights into the cellular and circuit mechanisms that explain the hypokinetic features of Parkinson's disease.
- Published
- 2020
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.