Bacteria associated with glioma: a next wave in cancer treatment

Abstract

Malignant gliomas occur more often in adults and may affect any part of the central nervous system (CNS). Although their results could be better, surgical excision, postoperative radiation and chemotherapy, and electric field therapy are today’s mainstays of glioma care. However, bacteria can also exert anti-tumor effects via mechanisms such as immune regulation and bacterial toxins to promote apoptosis, inhibit angiogenesis, and rely on their natural characteristics to target the tumor microenvironment of hypoxia, low pH, high permeability, and immunosuppression. Tumor-targeted bacteria expressing anticancer medications will go to the cancer site, colonize the tumor, and then produce the therapeutic chemicals that kill the cancer cells. Targeting bacteria in cancer treatment has promising prospects. Rapid advances have been made in the study of bacterial treatment of tumors, including using bacterial outer membrane vesicles to load chemotherapy drugs or combine with nanomaterials to fight tumors, as well as the emergence of bacteria combined with chemotherapy, radiotherapy, and photothermal/photodynamic therapy. In this study, we look back at the previous years of research on bacteria-mediated glioma treatment and move forward to where we think it is headed.

The Role of Bacteria in Central Nervous System Tumors: Opportunities and Challenges

“…In glioma, a combination of Lactobacillus plantarum and Bifidobacterium bifidum has been shown to inhibit glioma growth by suppressing the phosphoinositide 3-kinase/serine-threonine kinase (PI3K/AKT) pathway [ 130 ]. This suggests that LAB-based microbial formulations or their metabolic byproducts, such as lactate, could be potential therapeutic options for glioma treatment [ 131 ]. However, some researchers indicated that lactate accumulated in gliomas could induce regional metabolic reprogramming and activate oxidative metabolism to protect GBM cells from nutrient deprivation-mediated cell death [ 132 , 133 ].…”