The potential of gas plasma technology for targeting breast cancer

Bekeschus, Sander; Saadati, Fariba; Emmert, Steffen

doi:10.1002/ctm2.1022

Cited by 12 publications

(7 citation statements)

References 267 publications

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“…The first application is the direct and topical treatment of superficial tumors. In terms of potential targets for gas plasma treatment in patient-derived samples, this includes skin cancer, such as melanoma [217] and cutaneous squamous cell and basal cell carcinoma [218], as well as ulcerating cancers breaking through the skin, such as breast cancer [219][220][221] and oral and head and neck squamous cell carcinoma [161,222,223] and oral precancerous lesions [224]. In addition, for most of these tumor types, in vivo studies had shown pro-immunogenic effects of plasma treatment as indicated above.…”

Section: Clinic-related Concepts For Plasma Supporting Anticancer Imm...mentioning

confidence: 99%

Plasma, cancer, immunity

Bekeschus

Clemen

2022

J. Phys. D: Appl. Phys.

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Albeit heavily investigated for several decades already, the importance of the immune system in targeting cancer has received wide clinical attention only in recent years. This is partly because of long-standing rather traditional concepts on tumor biology on the one hand and the complexity of the immune system and its processes on the other. The viewpoint of evaluating existing and emerging approaches in oncology based on toxicity to tumors and the ability to engage antitumor-immunity is gaining ground across several disciplines. Along those lines, cold physical plasma was suggested as potential anticancer tool more than a decade ago, but solid evidence of the immune system playing a role in plasma cancer treatment only emerged in recent years. Moreover, plasma may support cancer immunotherapies in the future. Cancer immunotherapies are systemic treatments with biologicals that were reported to synergize with existing local physical modalities before, such as radiotherapy and photodynamic therapy. This review outlines key concepts in oncology, immunology, and tumor therapy, links them to plasma research, and discusses immuno-oncological consequences. Finally, promising future clinical applications are summarized. Synoptically, first scientific evidence supports an immuno-oncological dimension of plasma cancer treatment in selected instances, but robust clinical evidence is still lacking. More basic and clinical research is needed to determine the immuno-molecular mechanisms and detailed plasma application modalities to facilitate real patient benefit in the long term.

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Section: Clinic-related Concepts For Plasma Supporting Anticancer Imm...mentioning

confidence: 99%

Plasma, cancer, immunity

Bekeschus

Clemen

2022

J. Phys. D: Appl. Phys.

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“…Breast cancer (BC), the most prevalent malignant tumor globally, is characterized by significant heterogeneity 1 . It poses a considerable health risk to women 2–4 .…”

Section: Introductionmentioning

confidence: 99%

“…Breast cancer (BC), the most prevalent malignant tumor globally, is characterized by significant heterogeneity. 1 It poses a considerable health risk to women. [2][3][4] Despite advances in early detection and treatment, drug resistance remains a primary obstacle, often leading to poor prognosis in various malignancies.…”

Section: Introductionmentioning

confidence: 99%

Development of a novel prognostic signature based on single‐cell combined bulk RNA analysis in breast cancer

Xiao,

Hu,

Xie

et al. 2024

The Journal of Gene Medicine

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BackgroundBreast cancer (BC), a malignant tumor, is a significant cause of death and disability among women globally. Recent research indicates that copy number variation plays a crucial role in tumor development. In this study, we employed the Single‐Cell Variational Aneuploidy Analysis (SCEVAN) algorithm to differentiate between malignant and non‐malignant cells, aiming to identify genetic signatures with prognostic relevance for predicting patient survival.MethodsWe analyzed gene expression profiles and associated clinical data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Using the SCEVAN algorithm, we distinguished malignant from non‐malignant cells and investigated cellular interactions within the tumor microenvironment (TME). We categorized TCGA samples based on differentially expressed genes (DEGs) between these cell types. Subsequent Kyoto Encyclopedia of Genes and Genomes pathway analysis was conducted. Additionally, we developed polygenic models for the DEGs using least absolute shrinkage and selection operator‐penalized Cox regression analysis. To assess the prognostic accuracy of these characteristics, we generated Kaplan–Meier and receiver operating characteristic curves from training and validation datasets. We also monitored the expression variations of prognostic genes across the pseudotime of malignant cells. Patients were divided into high‐risk and low‐risk groups based on median risk scores to compare their TME and identify potential therapeutic agents. Lastly, polymerase chain reaction was used to validate seven pivotal genes.ResultsThe SCEVAN algorithm identified distinct malignant and non‐malignant cells in GSE180286. Cellchat analysis revealed significantly increased cellular communication, particularly between fibroblasts, endothelial cells and malignant cells. The DEGs were predominantly involved in immune‐related pathways. TCGA samples were classified into clusters A and B based on these genes. Cluster A, enriched in immune pathways, was associated with poorer prognosis, whereas cluster B, predominantly involved in circadian rhythm pathways, showed better outcomes. We constructed a 14‐gene prognostic signature, validated in a 1:1 internal TCGA cohort and external GEO datasets (GSE42568 and GSE146558). Kaplan–Meier analysis confirmed the prognostic signature's accuracy (p < 0.001). Receiver operating characteristic curve analysis demonstrated the predictive reliability of these prognostic features. Single‐cell pseudotime analysis with monocle2 highlighted the distinct expression trends of these genes in malignant cells, underscoring the intratumoral heterogeneity. Furthermore, we explored the differences in TME between high‐ and low‐risk groups and identified 16 significantly correlated drugs.ConclusionOur findings suggest that the 14‐gene prognostic signature could serve as a novel biomarker for forecasting the prognosis of BC patients. Additionally, the immune cells and pathways in different risk groups indicate that immunotherapy may be a crucial component of treatment strategies for BC patients.

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“…Many genetic, environmental, and lifestyle factors have a role in the onset and spread of BRCA [ 1 ]. Much research has been done over the years to identify the underlying causes of BRCA and to create efficient treatment plans [ [ 2 , 3 ]].…”

Section: Introductionmentioning

confidence: 99%