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Call for papers - Advances in personalized radiotherapy

Guest Editors:
Venkata SK. Manem: University of Quebec at Trois-Rivières, Canada
Farzad Taghizadeh-Hesary: Iran University of Medical Sciences, Iran

Submission Status: Open   |   Submission Deadline: 31 December 2023


BMC Cancer is calling for submissions to our Collection on advances in personalized radiotherapy. We welcome studies that aim to improve clinical outcomes following radiotherapy by the personalization of treatment as well as a further understanding of radiosensitivity and the development of biomarkers.

Meet the Guest Editors

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Venkata SK. Manem: University of Quebec at Trois-Rivières, Canada

Dr. Venkata Manem is a Professor Sous Octroi in the Department of Mathematics and Computer Science at the Université du Québec à Trois Rivières and an early-career researcher at the Quebec Heart & Lung Institute (IUCPQ) as well as an Adjunct Professor at the Faculty of Pharmacy at Université Laval. He is an FRQS Research Scholar - Junior 1 in the AI and Digital Health program. Trained as an Applied Mathematician, he obtained his Ph.D. from the University of Waterloo and subsequently completed his postdoctoral training at Harvard Medical School & Massachusetts General Hospital and at the Princess Margaret Cancer Center, as well as worked as a Bioinformatics researcher at the IUCPQ. Dr. Manem’s research expertise is to employ AI and statistical tools with the aim to develop data-driven diagnostic and predictive biomarkers by integrating high-dimensional data from various sources. He has extensive experience in translational research and has worked on several computational biology projects, including prognostic, diagnostic, and predictive biomarkers in oncology. 

Farzad Taghizadeh-Hesary: Iran University of Medical Sciences, Iran

Farzad Taghizadeh-Hesary, M.D., is an Assistant Professor of Radiation Oncology at the Iran University of Medical Sciences (IUMS). His familiarity with the research methodologies has enabled him to conduct various research types, such as meta-analysis, systematic review, clinical trial, and prospective and retrospective studies. His areas of expertise are radiation oncology, radiation biology, medical oncology, and cancer biology. Now, he serves as an Editorial Board member for BMC Cancer, PLOS ONE, Medicine, BMC Research Notes, Asian Pacific Journal of Cancer Prevention, Human Gene, Journal of Medical Case Reports, and the Guest Editor of Human Gene.

About the collection

BMC Cancer is calling for submissions to our Collection on advances in personalized radiotherapy. We welcome studies that aim to improve clinical outcomes following radiotherapy by the personalization of treatment as well as a further understanding of radiosensitivity and the development of biomarkers.

Radiotherapy (RT) is a mainstay of cancer treatment. The tumor response to the RT is heterogeneous, from a complete response to even disease progression during radiation. This issue urges understanding factors mediating different RT responses in different individuals. This approach has evolved into a discipline in Oncology called Personalized Radiotherapy. This discipline aims to modulate the RT intensity, schedule, and concomitant treatments to improve the therapeutic index. In recent years, technological advances and the increased use of combined-modality RT, such as chemoradiotherapy and immunoradiotherapy, have improved clinical outcomes. Improvements in imaging technologies have led to the field of radiomics and the use of its potential to improve theranostic objectives. Alongside radiomics, genomics, proteomics, and metabolomics are also all accelerating the discovery of predictive biomarkers of radiosensitivity and treatment efficacy as well as adverse events and toxicity. The increased integration of biomarkers from various high-dimensional data modalities and combination of RT with other systemic treatments such as immunotherapy and targeted therapeutics, as well as a better understanding of tumor heterogeneity and the effect of the tumor microenvironment, offers the true promise of personalized radiotherapy.

In recognition of the multidisciplinary research needs to improve personalized radiotherapy further, BMC Cancer is inviting submissions to a collection on this subject. Topics of interest include, but are not limited to, the following:

  • Development of radiosensitizing agents
  • Use of machine learning to develop/modify treatment plans
  • Genomic signatures of radiation sensitivity
  • Radiomics biomarkers
  • Biology and effect of tumor microenvironment on radiation sensitivity
  • Use of radiotracers and PET-CT imaging to identify an area of active tumor growth and metabolism
  • Individualization of radiation and systemic treatment sequencing
  • Improvement of imaging changes in tumor and anatomy changes
  • Radiotherapy as adjuvants for personalized immunotherapy and targeted therapeutics
  • Use of hypoxia-targeted interventions to improve treatment outcomes
  • Targeted anti-mitochondrial treatments to improve therapeutic index

© Mark Kostich / Getty Images / iStock

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes the submission of Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Advances in personalized radiotherapy" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.