https://bura.brunel.ac.uk/handle/2438/8630 2026-11-04T15:45:10Z 2026-11-04T15:45:10Z Kiriy, Daria Favero, Francesco Gerhäuser, Clarissa Heilmann, Jessica Lutsik, Pavlo Gonzalez, Francisco German Rodriguez Locallo, Alessio Jespersen, Jakob Schmidt Gruber, Andreas J Olsen, Andre V Hernando, Barbara Fu, Yunfan Haberland, Valleriia Furlano, Kira Georgeson, Peter Graefen, Markus Phal, Pramit M Hong, Matthew KH Hutchison, William J Jaratlerdsiri, Weerachai Jiang, Jue Schlomm, Thorsten Cheng, Kevin CL Mensah, Nana Ureta, Jennifer Keane, Thomas Kerger, Michael Kerry, Giselle Kurganovs, Natalie Pirhady, Parsa Lach, Radoslaw Lamb, Alastair D Pellegrina, Diogo Lim, Beng Lu, Yong-Jie Lynch, Andy G Van Loo, Peter Mills, Ian Milne-Clark, Toby Nguyen, Anne Norden, Sam Imada, Eddie L Bova, G Steven Reimand, Jüri Nuzzo, Pier Vitale Nykter, Matti Macintyre, Geoff Olofinsae, Samson Voith von Voithenberg, Lena Omar, Mohamed Pakula, Hubert Pan, Yidan Park, Daniel J Pederzoli, Filippo Weischenfeldt, Joachim Plass, Christoph Raine, Keiran Rodrigues, Silvia Pereira, Ronnie Rodrigues Xu, Yaobo Khani, Francesca Rubin, Alan F Ryan, Andrew Jung, Chol-Hee Sankar, Aravind Pan Prostate Cancer Group (PPCG) Schlotmann, Balthasar C Stuchbery, Ryan Sültmann, Holger Brewer, Daniel S Taylor, Avigail Wakefield, Matthew Warren, Anne Wirth, Christopher Woodcock, Dan J Baena, Esther Zanettini, Claudio Zhang, Jingjing Bristow, Robert G Yamaguchi, Takafumi N Ziuboniewicz, Aleksandra S Simon, Ronald Sauter, Guido Batra, Rajbir RN Kote-Jarai, Zsofia Cooper, Colin S Brook, Mark N Brors, Benedikt Butler, Adam Cancel-Tassin, Géraldine Costello, Tony Corcoran, Niall M Lamy, Philippe P Barrowdale, Daniel Cussenot, Olivier Eeles, Ros A Gihawi, Abraham Girma, Etsehiwot G Torres, Marina Gnanapragasam, Vincent J Hamid, Anis Jakobsdottir, G Maria Hayes, Vanessa M He, Housheng Hansen Hovens, Christopher M Bedő, Justin Leeman, Gregory Loda, Massimo Marchionni, Luigi Molania, Ramyar Grima, Corinna Fernández-Sanromán, Angel Dennis, Nening Papenfuss, Anthony T Pope, Bernard Queiroz, Lucio R Rausch, Tobias Bergeron, Alain Robinson, Brian Sahli, Atef Sørensen, Karina D Uhrig, Sebastian Wedge, David C Dev, Harveer Roldan-Romero, Juan Maria Barton, Lucy Corcoran, Niall M Gnanapragasam, Vincent J Mangiola, Stefano He, Xiaotong Hamid, Anis He, Housheng Hansen Hall, Grace A Hovens, Christopher M Dinalankara, Wikum Kote-Jarai, Zsofia Loda, Massimo Molania, Ramyar Papenfuss, Anthony T Al-Muftah, Noora Berlin, Alejandro Borre, Michael Burns, Wi Campbell, Bethany K Penington, Jocelyn McCoy, Patrick Carelli, Ryan Cheung, Melissa Massie, Charlie E Chow, Ken Clarkson, Michael J Cmero, Marek Collins, Colin Holmes, Vivien Faini, Angelo Corso Dong, Ruining Dundee, Philip Foster, Chris Erickson, Andrew Tennstedt, Pierre Esentürk, Emre Hong, Chen Peters, Justin S Falkenbach, Fabian Fanelli, Giuseppe N Feran, Breon Feuerbach, Lars Mehmood, Arfa Fradet, Yves https://bura.brunel.ac.uk/handle/2438/34121 2026-11-02T03:00:43Z 2026-09-09T00:00:00Z

Title: Recurrent mechanisms of biallelic epigenetic inactivation reveal new putative tumour suppressor genes in prostate cancer Authors: Kiriy, Daria; Favero, Francesco; Gerhäuser, Clarissa; Heilmann, Jessica; Lutsik, Pavlo; Gonzalez, Francisco German Rodriguez; Locallo, Alessio; Jespersen, Jakob Schmidt; Gruber, Andreas J; Olsen, Andre V; Hernando, Barbara; Fu, Yunfan; Haberland, Valleriia; Furlano, Kira; Georgeson, Peter; Graefen, Markus; Phal, Pramit M; Hong, Matthew KH; Hutchison, William J; Jaratlerdsiri, Weerachai; Jiang, Jue; Schlomm, Thorsten; Cheng, Kevin CL; Mensah, Nana; Ureta, Jennifer; Keane, Thomas; Kerger, Michael; Kerry, Giselle; Kurganovs, Natalie; Pirhady, Parsa; Lach, Radoslaw; Lamb, Alastair D; Pellegrina, Diogo; Lim, Beng; Lu, Yong-Jie; Lynch, Andy G; Van Loo, Peter; Mills, Ian; Milne-Clark, Toby; Nguyen, Anne; Norden, Sam; Imada, Eddie L; Bova, G Steven; Reimand, Jüri; Nuzzo, Pier Vitale; Nykter, Matti; Macintyre, Geoff; Olofinsae, Samson; Voith von Voithenberg, Lena; Omar, Mohamed; Pakula, Hubert; Pan, Yidan; Park, Daniel J; Pederzoli, Filippo; Weischenfeldt, Joachim; Plass, Christoph; Raine, Keiran; Rodrigues, Silvia; Pereira, Ronnie Rodrigues; Xu, Yaobo; Khani, Francesca; Rubin, Alan F; Ryan, Andrew; Jung, Chol-Hee; Sankar, Aravind; Pan Prostate Cancer Group (PPCG); Schlotmann, Balthasar C; Stuchbery, Ryan; Sültmann, Holger; Brewer, Daniel S; Taylor, Avigail; Wakefield, Matthew; Warren, Anne; Wirth, Christopher; Woodcock, Dan J; Baena, Esther; Zanettini, Claudio; Zhang, Jingjing; Bristow, Robert G; Yamaguchi, Takafumi N; Ziuboniewicz, Aleksandra S; Simon, Ronald; Sauter, Guido; Batra, Rajbir RN; Kote-Jarai, Zsofia; Cooper, Colin S; Brook, Mark N; Brors, Benedikt; Butler, Adam; Cancel-Tassin, Géraldine; Costello, Tony; Corcoran, Niall M; Lamy, Philippe P; Barrowdale, Daniel; Cussenot, Olivier; Eeles, Ros A; Gihawi, Abraham; Girma, Etsehiwot G; Torres, Marina; Gnanapragasam, Vincent J; Hamid, Anis; Jakobsdottir, G Maria; Hayes, Vanessa M; He, Housheng Hansen; Hovens, Christopher M; Bedő, Justin; Leeman, Gregory; Loda, Massimo; Marchionni, Luigi; Molania, Ramyar; Grima, Corinna; Fernández-Sanromán, Angel; Dennis, Nening; Papenfuss, Anthony T; Pope, Bernard; Queiroz, Lucio R; Rausch, Tobias; Bergeron, Alain; Robinson, Brian; Sahli, Atef; Sørensen, Karina D; Uhrig, Sebastian; Wedge, David C; Dev, Harveer; Roldan-Romero, Juan Maria; Barton, Lucy; Corcoran, Niall M; Gnanapragasam, Vincent J; Mangiola, Stefano; He, Xiaotong; Hamid, Anis; He, Housheng Hansen; Hall, Grace A; Hovens, Christopher M; Dinalankara, Wikum; Kote-Jarai, Zsofia; Loda, Massimo; Molania, Ramyar; Papenfuss, Anthony T; Al-Muftah, Noora; Berlin, Alejandro; Borre, Michael; Burns, Wi; Campbell, Bethany K; Penington, Jocelyn; McCoy, Patrick; Carelli, Ryan; Cheung, Melissa; Massie, Charlie E; Chow, Ken; Clarkson, Michael J; Cmero, Marek; Collins, Colin; Holmes, Vivien; Faini, Angelo Corso; Dong, Ruining; Dundee, Philip; Foster, Chris; Erickson, Andrew; Tennstedt, Pierre; Esentürk, Emre; Hong, Chen; Peters, Justin S; Falkenbach, Fabian; Fanelli, Giuseppe N; Feran, Breon; Feuerbach, Lars; Mehmood, Arfa; Fradet, Yves Abstract: The inactivation of tumour suppressor genes is a key step in cancer development, and is usually achieved by homozygous loss. In prostate cancer, however, large genomic regions are often hemizygously lost, which complicates the identification of putative tumour suppressors in these regions. Here, we develop Epi2Hit, an integrative computational method that leverages whole genome sequencing, epigenomic profiling and gene expression to identify biallelic inactivation of tumour suppressor genes involving DNA methylation of promoter and enhancer regions of one allele and genomic loss of the other allele. We apply Epi2Hit to a cohort of 2,021 prostate cancers to discover tumour suppressor genes. In particular, we identify epigenetic biallelic inactivation of ZFHX3 at a recurrence level similar to TP53. Biallelic inactivation of ZFHX3, a transcriptional repressor, leads to upregulation of oncogenes, including MYC and a shorter time to metastasis. Finally, we provide evidence that epigenetic silencing as 2nd hit is particularly enriched in regions with nearby essential genes, precluding homozygous loss. Description: Data availability: PPCG dataset comprises whole-genome sequencing (WGS), RNA-seq, DNA methylation, clinical, and histopathological data from 2,021 prostate cancer donors. Due to the sensitive nature of human genomic/clinical data and participant-consent restrictions, PPCG data are provided under controlled access and are available only for approved research purposes. Raw genome sequencing data have been deposited in the European Genome-Phenome 1360 Archive (EGA) under the study ID EGAS00001002876 and is described in the Reporting Summary and our companion manuscript29. In addition, PPCG working project data (e.g., variant calls, pipeline outputs and intermediate analyses) and harmonised RNA-seq/methylation data are made available to approved projects through secure transfer (Globus), and clinical/histopathological data are hosted in a GDPR-compliant secure environment (REDCap); access is limited to approved PPCG researchers. Access to PPCG controlled data requires submission of a Project Concept Form, available at https://panprostate.org, and approval by the PPCG Steering Committee. Requests are submitted by emailing the completed form to PPCG@icr.ac.uk. We will respond to the data access request within 14 days. We will provide guidance on the application process; access, once granted, is provided for the duration of the approved project under the applicable data access agreement/terms. To support reproducibility without redistribution of controlled PPCG data, we provide a compact, self-contained example dataset in the project repository that is sufficient to run the Epi2Hit workflow end-to-end and reproduce representative outputs. Specifically, the repository includes a TCGA-PRAD chromosome 8 example dataset (450 K methylation β-values for chr8, a matched gene expression matrix, prostate ATAC-seq peaks, ChromHMM segmentation, and Hi-C loops), together with example mutation calls and copy-number segment inputs used for downstream biallelic analyses. These files are provided under the repository’s data/ directory and are used by analysis/TCGA_run.ipynb (and the containerised demo) to reproduce the main workflow outputs on the example dataset. The publicly available data used in this study are available in the NCBI Gene Expression Omnibus (GEO) database under accession code GSE164347 (prostate Hi-C loops): https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE16434737. The publicly available data used in this study are available in the GEO database under accession code GSE188797 (tumour ATAC-seq peaks): https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE18879736. The publicly available data used in this study are available in the GEO database under accession code GSE49402 (GSM1208743, ZFHX3 ChIP-seq): https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4940272. The publicly available data used in this study are available from the ENCODE Project database (epigenetic marks (H3K4me3, H3K27ac) and CTCF tracks derived for prostate cancer cells (PC-3, C4-2B)): https://www.encodeproject.org/110. The remaining data are available within the Article, Supplementary Information or Source Data file. Source data are provided with this paper.; Code availability: Code used to generate results and plots are available at https://github.com/panprostate/Epi2Hit. A static version of the code is available at https://doi.org/10.5281/ZENODO.18788787 [122. Kiriy, D. Recurrent Mechanisms of Biallelic Epigenetic Inactivation Reveal New Putative Tumour Suppressor Genes in Prostate Cancer. (Zenodo, 2026). https://doi.org/10.5281/ZENODO.18788787.].

2026-09-09T00:00:00Z Gruber, Andreas J Olsen, André V Hernando, Barbara Cheng, Kevin CL Gerhäuser, Clarissa Torres, Marina Favero, Francesco Kiriy, Daria Fernández-Sanromán, Ángel Roldan-Romero, Juan Maria Barton, Lucy Khani, Francesca Kote-Jarai, Zsofia Brewer, Daniel S Yamaguchi, Takafumi N Lamy, Philippe Leeman, Gregory Loda, Massimo Pope, Bernard Queiroz, Lucio R Uhrig, Sebastian Heilmann, Jessica Xu, Yaobo Zanettini, Claudio Peters, Justin S Feran, Breon Bergeron, Alain Rubin, Alan F Cmero, Marek Collins, Colin Lamb, Alastair D Berlin, Alejandro Zhang, Jingjing Ziuboniewicz, Aleksandra S Erickson, Andrew Ryan, Andrew Lynch, Andy G Massie, Charlie E Raine, Keiran Faini, Angelo Corso Nguyen, Anne Warren, Anne Sankar, Aravind Sahli, Atef Grima, Corinna Graefen, Markus Mehmood, Arfa Schlotmann, Balthasar C Hong, Chen Foster, Chris Woodcock, Dan J Barrowdale, Daniel Park, Daniel J Phal, Pramit M Nykter, Matti Esentürk, Emre Baena, Esther Carelli, Ryan Chow, Ken Falkenbach, Fabian Pederzoli, Filippo Kerry, Giselle Wakefield, Matthew Fanelli, Giuseppe N Hall, Grace Penington, Jocelyn Sietsma Lach, Radoslaw Dev, Harveer Sültmann, Holger Pakula, Hubert Mills, Ian Furlano, Kira Stuchbery, Ryan Korbel, Jan Ureta, Jennifer Jiang, Jue Bedő, Justin Feuerbach, Lars von Voithenberg, Lena Voith Cheung, Melissa Simon, Ronald Borre, Michael Clarkson, Michael J Wedge, David C Batra, Rajbir N Kerger, Michael Scherer, Michael Pellegrina, Diogo Norden, Sam Omar, Mohamed Mensah, Nana Sauter, Guido Kurganovs, Natalie Dennis, Nening Al-Muftah, Noora Pirhady, Parsa Pacey, Simon Schlomm, Thorsten McCoy, Patrick Georgeson, Peter Van Loo, Peter Dundee, Philip Hong, Matthew KH Olofinsae, Samson Bova, G Steven Nuzzo, Pier Vitale Tennstedt, Pierre Pereira, Ronnie Rodrigues Dong, Ruining Rodrigues, Silvia Mangiola, Stefano Keane, Thomas Lutsik, Pavlo Brors, Benedikt Milne-Clark, Toby Costello, Tony Rausch, Tobias Macintyre, Geoff Haberland, Valeriia Holmes, Vivien Jaratlerdsiri, Weerachai Brook, Mark N Burns, Wi Dinalankara, Wikum Eeles, Ros A Marchionni, Luigi Hutchison, William J He, Xiaotong Pan, Yidan Lu, Yong-Jie Reimand, Jüri Robinson, Brian Fu, Yunfan Fradet, Yves Cooper, Colin S Bristow, Robert G Weischenfeldt, Joachim Pan-Prostate Cancer Group (PPCG) Butler, Adam Lim, Beng Cancel-Tassin, Géraldine Corcoran, Niall M Plass, Christoph Molania, Ramyar Cussenot, Olivier Gihawi, Abraham Girma, Etsehiwot G Sørensen, Karina D Gnanapragasam, Vincent J Hamid, Anis A Campbell, Bethany K Hayes, Vanessa M He, Housheng Hansen Hovens, Christopher M Imada, Eddie L Papenfuss, Anthony T Wirth, Christopher Jakobsdottir, G Maria Jung, Chol-Hee https://bura.brunel.ac.uk/handle/2438/34120 2026-11-02T03:00:41Z 2026-09-09T00:00:00Z

Title: Integrated signatures define mutational processes in prostate cancer Authors: Gruber, Andreas J; Olsen, André V; Hernando, Barbara; Cheng, Kevin CL; Gerhäuser, Clarissa; Torres, Marina; Favero, Francesco; Kiriy, Daria; Fernández-Sanromán, Ángel; Roldan-Romero, Juan Maria; Barton, Lucy; Khani, Francesca; Kote-Jarai, Zsofia; Brewer, Daniel S; Yamaguchi, Takafumi N; Lamy, Philippe; Leeman, Gregory; Loda, Massimo; Pope, Bernard; Queiroz, Lucio R; Uhrig, Sebastian; Heilmann, Jessica; Xu, Yaobo; Zanettini, Claudio; Peters, Justin S; Feran, Breon; Bergeron, Alain; Rubin, Alan F; Cmero, Marek; Collins, Colin; Lamb, Alastair D; Berlin, Alejandro; Zhang, Jingjing; Ziuboniewicz, Aleksandra S; Erickson, Andrew; Ryan, Andrew; Lynch, Andy G; Massie, Charlie E; Raine, Keiran; Faini, Angelo Corso; Nguyen, Anne; Warren, Anne; Sankar, Aravind; Sahli, Atef; Grima, Corinna; Graefen, Markus; Mehmood, Arfa; Schlotmann, Balthasar C; Hong, Chen; Foster, Chris; Woodcock, Dan J; Barrowdale, Daniel; Park, Daniel J; Phal, Pramit M; Nykter, Matti; Esentürk, Emre; Baena, Esther; Carelli, Ryan; Chow, Ken; Falkenbach, Fabian; Pederzoli, Filippo; Kerry, Giselle; Wakefield, Matthew; Fanelli, Giuseppe N; Hall, Grace; Penington, Jocelyn Sietsma; Lach, Radoslaw; Dev, Harveer; Sültmann, Holger; Pakula, Hubert; Mills, Ian; Furlano, Kira; Stuchbery, Ryan; Korbel, Jan; Ureta, Jennifer; Jiang, Jue; Bedő, Justin; Feuerbach, Lars; von Voithenberg, Lena Voith; Cheung, Melissa; Simon, Ronald; Borre, Michael; Clarkson, Michael J; Wedge, David C; Batra, Rajbir N; Kerger, Michael; Scherer, Michael; Pellegrina, Diogo; Norden, Sam; Omar, Mohamed; Mensah, Nana; Sauter, Guido; Kurganovs, Natalie; Dennis, Nening; Al-Muftah, Noora; Pirhady, Parsa; Pacey, Simon; Schlomm, Thorsten; McCoy, Patrick; Georgeson, Peter; Van Loo, Peter; Dundee, Philip; Hong, Matthew KH; Olofinsae, Samson; Bova, G Steven; Nuzzo, Pier Vitale; Tennstedt, Pierre; Pereira, Ronnie Rodrigues; Dong, Ruining; Rodrigues, Silvia; Mangiola, Stefano; Keane, Thomas; Lutsik, Pavlo; Brors, Benedikt; Milne-Clark, Toby; Costello, Tony; Rausch, Tobias; Macintyre, Geoff; Haberland, Valeriia; Holmes, Vivien; Jaratlerdsiri, Weerachai; Brook, Mark N; Burns, Wi; Dinalankara, Wikum; Eeles, Ros A; Marchionni, Luigi; Hutchison, William J; He, Xiaotong; Pan, Yidan; Lu, Yong-Jie; Reimand, Jüri; Robinson, Brian; Fu, Yunfan; Fradet, Yves; Cooper, Colin S; Bristow, Robert G; Weischenfeldt, Joachim; Pan-Prostate Cancer Group (PPCG); Butler, Adam; Lim, Beng; Cancel-Tassin, Géraldine; Corcoran, Niall M; Plass, Christoph; Molania, Ramyar; Cussenot, Olivier; Gihawi, Abraham; Girma, Etsehiwot G; Sørensen, Karina D; Gnanapragasam, Vincent J; Hamid, Anis A; Campbell, Bethany K; Hayes, Vanessa M; He, Housheng Hansen; Hovens, Christopher M; Imada, Eddie L; Papenfuss, Anthony T; Wirth, Christopher; Jakobsdottir, G Maria; Jung, Chol-Hee Abstract: Prostate cancer follows a long and heterogeneous disease course with incompletely understood aetiology¹. Here we dissect the mutational processes shaping the genomes of 959 donors from the Pan Prostate Cancer Group and assess their clinical relevance. By integrating de novo extracted single-base substitution, insertion–deletion and copy-number signatures with six novel complex structural variant signatures, we identify eight integrated mutational footprints (IMFs) that collectively explain the mutational processes in 85% of primary prostate cancer genomes. IMFs were strongly influenced by regional biases in the genome, most prevalently androgen receptor-mediated mutagenesis and replication stress. Four IMFs, present in 37% of primary tumours, were significantly associated with shorter time to metastasis. These included reactive oxygen-species-driven mutagenesis and both canonical and non-canonical homologous recombination deficiency, the latter being enriched in patients of African ancestry. Extending to the metastatic setting, we found that IMFs predicted sensitivity to androgen receptor pathway inhibitors. Taken together, our study delineates the aetiologies and mutational processes that drive the genomic and clinical heterogeneity of prostate cancer, introduces IMFs as a unifying framework, and highlights their potential to improve both risk stratification and biomarker-guided treatment selection. Description: Data availability: The PPCG dataset comprises WGS, RNA-seq, DNA methylation, clinical and histopathological data from 2,021 prostate cancer donors. Owing to the sensitive nature of human genomic and clinical data and participant-consent restrictions, PPCG data are provided under controlled access and are available only for approved research purposes. Raw genome sequencing data have been deposited in the European Genome-Phenome Archive (EGA) under the study ID EGAS00001002876 and are described in the Reporting Summary and our companion paper24. Access to raw, processed and clinical data from the Hartwig Medical Foundation can be requested at https://www.hartwigmedicalfoundation.nl/en/data/data-access-request/. XML files used to construct the TCGA clinical data can be accessed through the Genomic Data Commons portal, and the procedure for requesting access to controlled genomic data is outlined online (https://gdc.cancer.gov/access-data/obtaining-access-controlled-data). Source data are provided with this paper.; Code availability: The source code for reproducing analyses and figures is available at GitHub (https://github.com/panprostate/mutational-signatures). A static code repository is available at Zenodo98 (https://doi.org/10.5281/ZENODO.18754193).

2026-09-09T00:00:00Z Liao, Sichong Hou, Jinbo Zhao, Yi Liu, Ziming Hu, Haonan Li, Zeyang Wang, Kezhi Zhang, Jie https://bura.brunel.ac.uk/handle/2438/34117 2026-11-02T03:00:44Z 2026-08-19T00:00:00Z

Title: LLM-enhanced-EA-driven automated optimization framework for joint indoor deployment of multiple BSs and RISs Authors: Liao, Sichong; Hou, Jinbo; Zhao, Yi; Liu, Ziming; Hu, Haonan; Li, Zeyang; Wang, Kezhi; Zhang, Jie Abstract: The joint deployment of base stations (BSs) and reconfigurable intelligent surfaces (RISs) is considered a promising but underexplored solution to simultaneously improve indoor coverage performance and reduce network costs. Classical evolutionary algorithms (EAs) can solve this bi-objective non-convex mixed integer programming problem. However, EAs often suffer from efficiency issues due to convergence on local optima, and require redesigning the mechanism to concentrate on the fruitful areas of the search space, especially when the space is large. In this work, we use the large language model (LLM)-enhanced non-dominated sorting genetic algorithm II (NSGA-II) to directly solve the bi-objective optimization problem, assisted by an LLM to enhance its concentrated exploration capability by extending the exploration in language space. To minimize manual engineering, we designed an automated LLM-based module that generates tailored optimization prompts from templates, user descriptions, and reference materials. Simulations show that LLM-NSGA-II, guided by these automated prompts, matches the performance of manual engineering. When applied to joint BS and RIS deployment, LEAO achieves a cost efficiency of 55.7% ± 7.9% across five independent runs, exceeding the strongest baseline by 11.2 percentage points and indicating a more favorable balance between deployment cost and indoor coverage. Description: An Erratum to this article was published on 18 September 2026: In the original publication [1] of this paper, the fifth author’s affiliation should be ‘School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, China’. The sixth author’s affiliation should be ‘School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Sweden’. The eighth author’s affiliation should be ‘R&D Department, Ranplan Wireless Network Design Ltd., UK’. References: 1 Liao S C, Hou J B, Zhao Y, et al. LLM-enhanced-EA-driven automated optimization framework for joint indoor deployment of multiple BSs and RISs. Sci China Inf Sci, 2026, 69(9): 190304

2026-08-19T00:00:00Z Shen, Qianju Wu, Qiong Fan, Pingyi Wang, Kezhi Chen, Wen Zhang, Cui Mao, Guoqiang Letaief, Khaled B https://bura.brunel.ac.uk/handle/2438/34116 2026-11-02T03:00:45Z 2026-10-06T00:00:00Z

Title: Communication-Aware Distributed Control for Cooperative Ramp Merging in Vehicular Networks Authors: Shen, Qianju; Wu, Qiong; Fan, Pingyi; Wang, Kezhi; Chen, Wen; Zhang, Cui; Mao, Guoqiang; Letaief, Khaled B Abstract: Cooperative ramp merging requires reliable coordination among connected vehicles, but practical NR V2X Mode 2 communications may suffer from delay, packet loss, and resource collision due to distributed sidelink resource selection. Existing distributed control methods often assume ideal communication or treat communication impairments as external disturbances, without explicitly linking communication states to vehicle safety constraints. Accordingly, this paper proposes a communication aware distributed model predictive control (CA-DMPC) frame work for cooperative ramp merging. A Markov-chain-based model is developed to characterize NR V2X Mode 2 resource reservation and re-evaluation, including collision persistence, resource reselection, and re-evaluation failure. Predicted communication states are converted into spatial prediction uncertainty and incorporated into MPC safety constraints through an adaptive safety margin. To improve real-time performance, the communication-control optimization problem is decomposed into tractable subproblems, and the vehicle-control component is reformulated as a quadratic programming problem. Simulation results show that the proposed framework achieves smoother control, more stable inter-vehicle spacing, better trajectory tracking, and lower computational cost than benchmark methods.

2026-10-06T00:00:00Z