Immunological, Molecular and Imaging Biomarkers of Malignant Progression in Brain Cancer: Improving Precision Neuro-Oncology

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Pathophysiology".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 5200

Special Issue Editors


E-Mail Website
Guest Editor
Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020 Bergen, Norway
Interests: Glioblastoma; NK cells; Targeted therapies; clinical trials

E-Mail Website
Guest Editor
Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
Interests: Immunology; T cell biology; immunodeficiency; transcriptomics; molecular genetics

E-Mail Website
Guest Editor
Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5020 Bergen, Norway
Interests: neuroinformatics; image analysis; multimodal MRI; physiological modelling; machine learning; deep learning; computational medicine

Special Issue Information

Dear Colleagues,

Cancer poses major health and socioeconomic challenges worldwide as the global burden increases, with 19.3 million new cases expected in 2020 and projected to surpass 27 million by 2040. Despite improved molecular diagnostics, surgical, and radiotherapy techniques, the 5-year survival rate for patients diagnosed with the most aggressive brain cancer in adults remains less than 10%.

A paradigm shift towards more personalised cancer treatment has developed with the identification of measurable immunological, molecular, or radiological features that determine the patient’s prognosis and may represent druggable targets for innovative therapy. Biomarkers may be characterised by cellular markers, type of tumour infiltrating, or resident innate and adaptive immune cells obtained from the biopsy or blood sample, their activity, and molecular or cellular profiles in response to the tumour in situ or a predisposing systemic disease such as allergy or virus infection. Through multimodal MRI and subsequent machine learning algorithms, in particular deep learning-based approaches, trained on large patient population databases, key features (imaging-derived biomarkers) that predict future sites of tumour recurrence or aid generation of innovative treatments for brain cancer may be identified. Biomarkers not only inform the biological behaviour of the tumour and expected outcome for the patient but may predict efficacy of given treatments and expected side effects. Effective treatment modalities harnessing the ability of cytotoxic immune cells to recognize malignant cells with particular genetic mutations, such as adoptive cell transfer of native and engineered chimeric antigen receptor (CAR) T- and natural killer (NK-) cells, may emerge.

This Special Issue invites multidisciplinary papers (expert opinion reviews or original data) that characterise the immunoactive brain tumour environment, the interplay between tumour and immune cells, molecular and imaging-based features (including non-invasive radiological examinations as well as microscopic imaging techniques such as imaging mass cytometry from tissue samples) of malignant brain tumours impacting patient outcome, and treatment responses to the tumour in situ or responses generated by predisposing systemic diseases such as allergy or virus infection. This focused issue aims to contribute new knowledge to the burgeoning need to implement effective management of malignant brain cancer.

Prof. Dr. Martha Chekenya
Dr. Eirik Bratland
Prof. Dr. Arvid Lundervold
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • prognostic and predictive Cellular and molecular markers
  • immune response
  • neuroimaging
  • imaging mass cytometry
  • deep learning and AI
  • radiomics and radiogenomics
  • allergy and brain cancer
  • cytomegalovirus and brain cancer
  • adaptive memory NK subsets
  • microglia
  • chimeric antigen receptor T cells
  • chimeric antigen receptor NK cells

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Review

24 pages, 2838 KiB  
Review
Challenges and Prospects for Designer T and NK Cells in Glioblastoma Immunotherapy
by Victoria Smith Arnesen, Andrea Gras Navarro and Martha Chekenya
Cancers 2021, 13(19), 4986; https://doi.org/10.3390/cancers13194986 - 5 Oct 2021
Cited by 7 | Viewed by 4249
Abstract
Glioblastoma (GBM) is the most prevalent, aggressive primary brain tumour with a dismal prognosis. Treatment at diagnosis has limited efficacy and there is no standardised treatment at recurrence. New, personalised treatment options are under investigation, although challenges persist for heterogenous tumours such as [...] Read more.
Glioblastoma (GBM) is the most prevalent, aggressive primary brain tumour with a dismal prognosis. Treatment at diagnosis has limited efficacy and there is no standardised treatment at recurrence. New, personalised treatment options are under investigation, although challenges persist for heterogenous tumours such as GBM. Gene editing technologies are a game changer, enabling design of novel molecular-immunological treatments to be used in combination with chemoradiation, to achieve long lasting survival benefits for patients. Here, we review the literature on how cutting-edge molecular gene editing technologies can be applied to known and emerging tumour-associated antigens to enhance chimeric antigen receptor T and NK cell therapies for GBM. A tight balance of limiting neurotoxicity, avoiding tumour antigen loss and therapy resistance, while simultaneously promoting long-term persistence of the adoptively transferred cells must be maintained to significantly improve patient survival. We discuss the opportunities and challenges posed by the brain contexture to the administration of the treatments and achieving sustained clinical responses. Full article
Show Figures

Figure 1

Back to TopTop