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ConnecTF: A platform to integrate transcription factor-gene interactions and validate regulatory networks.
Brooks, MD, Juang, CL, Katari, MS, Alvarez, JM, Pasquino, A, Shih, HJ, Huang, J, Shanks, C, Cirrone, J, Coruzzi, GM
Plant physiology. 2021;(1):49-66
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Abstract
Deciphering gene regulatory networks (GRNs) is both a promise and challenge of systems biology. The promise lies in identifying key transcription factors (TFs) that enable an organism to react to changes in its environment. The challenge lies in validating GRNs that involve hundreds of TFs with hundreds of thousands of interactions with their genome-wide targets experimentally determined by high-throughput sequencing. To address this challenge, we developed ConnecTF, a species-independent, web-based platform that integrates genome-wide studies of TF-target binding, TF-target regulation, and other TF-centric omic datasets and uses these to build and refine validated or inferred GRNs. We demonstrate the functionality of ConnecTF by showing how integration within and across TF-target datasets uncovers biological insights. Case study 1 uses integration of TF-target gene regulation and binding datasets to uncover TF mode-of-action and identify potential TF partners for 14 TFs in abscisic acid signaling. Case study 2 demonstrates how genome-wide TF-target data and automated functions in ConnecTF are used in precision/recall analysis and pruning of an inferred GRN for nitrogen signaling. Case study 3 uses ConnecTF to chart a network path from NLP7, a master TF in nitrogen signaling, to direct secondary TF2s and to its indirect targets in a Network Walking approach. The public version of ConnecTF (https://ConnecTF.org) contains 3,738,278 TF-target interactions for 423 TFs in Arabidopsis, 839,210 TF-target interactions for 139 TFs in maize (Zea mays), and 293,094 TF-target interactions for 26 TFs in rice (Oryza sativa). The database and tools in ConnecTF will advance the exploration of GRNs in plant systems biology applications for model and crop species.
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Expression of PBRM1 as a prognostic predictor in metastatic renal cell carcinoma patients treated with tyrosine kinase inhibitor.
Cai, W, Wang, Z, Cai, B, Yuan, Y, Kong, W, Zhang, J, Chen, Y, Liu, Q, Huang, Y, Huang, J, et al
International journal of clinical oncology. 2020;(2):338-346
Abstract
OBJECTIVE PBRM1, located on 3p21, functions as a tumor suppressor and somatic mutation of PBRM1 is frequent in clear cell renal cell carcinoma (ccRCC). This study aims to determine the influence of PBRM1 expression on the prognosis of patients with mRCC receiving tyrosine kinase inhibitor (TKI) treatment. METHODS We identified 116 mRCC patients who were administered sunitinib or sorafenib as first-line therapy, between January 2006 and December 2016 at our institution. PBRM1 expression was assessed by immunohistochemistry. The Kaplan-Meier method was used to estimate the progression-free survival (PFS) and overall survival (OS), log-rank test was used to compare the survival outcomes between patients with low and high PBRM1 expression levels, and the Cox proportional hazard regression model was used to estimate the prognostic value. Prognostic accuracy was determined using Harrell concordance index, and nomograms were built to evaluate the prognosis of mRCC. RESULTS Patients with low PBRM1 expression had significantly shorter median PFS (9 vs 26 months, P < 0.001) and OS (21 vs 44 months, P < 0.001) than those with high expression. Multivariate analysis showed that PBRM1 expression was an independent predictor of PFS (HR 1.975, P = 0.013) and OS (HR 2.282, P = 0.007). The model built by the addition of PBRM1 improved the C-index of PFS and OS to 0.72 and 0.82, respectively. CONCLUSIONS The expression of PBRM1 could be a significant prognostic factor for mRCC patients treated with targeted therapy, and it increases the prognostic accuracy of the established prognostic model.
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Chemical basis for the recognition of trimethyllysine by epigenetic reader proteins.
Kamps, JJ, Huang, J, Poater, J, Xu, C, Pieters, BJ, Dong, A, Min, J, Sherman, W, Beuming, T, Matthias Bickelhaupt, F, et al
Nature communications. 2015;:8911
Abstract
A large number of structurally diverse epigenetic reader proteins specifically recognize methylated lysine residues on histone proteins. Here we describe comparative thermodynamic, structural and computational studies on recognition of the positively charged natural trimethyllysine and its neutral analogues by reader proteins. This work provides experimental and theoretical evidence that reader proteins predominantly recognize trimethyllysine via a combination of favourable cation-π interactions and the release of the high-energy water molecules that occupy the aromatic cage of reader proteins on the association with the trimethyllysine side chain. These results have implications in rational drug design by specifically targeting the aromatic cage of readers of trimethyllysine.