The Potential of Tumor Debulking to Support Molecular Targeted Therapies

• Published in: Frontiers in oncology Vol. 10; p. 801
• Main Authors: Oppel, Felix, Görner, Martin, Sudhoff, Holger
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 18.06.2020
• Subjects: cancer genetics; cancer therapy; clonal heterogeneity; molecular targeting; Oncology; precision oncology; therapy resistance
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2020.00801

Tumors may consist of billions of cells, which in malignant cases disseminate and form distant metastases. The large number of tumor cells formed by the high number of cell divisions during tumor progression creates a heterogeneous set of genetically diverse tumor cell clones. For cancer therapy this poses unique challenges, as distinct clones have to be targeted in different tissue locations. Recent research has led to the development of specific inhibitors of defined targets in cellular signaling cascades which promise more effective and more tumor-specific therapy approaches. Many of these molecular targeted therapy (MTT) compounds have already been translated into clinics or are currently being tested in clinical studies. However, the outgrowth of tumor cell clones resistant to such inhibitors is a drawback that affects specific inhibitors in a similar way as classical cytotoxic chemotherapeutics, because additionally acquired genetic alterations can enable tumor cells to circumvent the particular regulators of cellular signaling being targeted. Thus, it might be desirable to reduce genetic heterogeneity prior to molecular targeting, which could reduce the statistical chance of tumor relapse initiated by resistant clones. One way to achieve this is employing unspecific methods to remove as much tumor material as possible before MTT, e.g., by tumor debulking (TD). Currently, this is successfully applied in the clinical treatment of ovarian cancer. We believe that TD followed by treatment with a combination of molecular targeted drugs, optimally guided by biomarkers, might advance survival of patients suffering from various cancer types.