The invasive capabilities of glioblastoma (GBM) define the cancer’s aggressiveness, treatment resistance, and overall mortality. The tumor microenvironment influences the molecular behavior of cells, both epigenetically and genetically. Current forces being studied include properties of the extracellular matrix (ECM), such as stiffness and “sensing” capabilities. There is currently limited data on the physical forces in GBM—both relating to how they influence their environment and how their environment influences them. This review outlines the advances that have been made in the field. It is our hope that further investigation of the physical forces involved in GBM will highlight new therapeutic options and increase patient survival. A search of the PubMed database was conducted through to 23 March 2022 with the following search terms: (glioblastoma) AND (physical forces OR pressure OR shear forces OR compression OR tension OR torsion) AND (migration OR invasion). Our review yielded 11 external/applied/mechanical forces and 2 tumor microenvironment (TME) forces that affect the ability of GBM to locally migrate and invade. Both external forces and forces within the tumor microenvironment have been implicated in GBM migration, invasion, and treatment resistance. We endorse further research in this area to target the physical forces affecting the migration and invasion of GBM.

Background Acute Ischemic Stroke (AIS), a major cause of disability, was previously associated with multiple metabolomic changes, but many findings were contradictory. Case-control and longitudinal study designs could have played a role in that. To clarify metabolomic changes, we performed a simultaneous comparison of ischemic stroke metabolome in acute, chronic stages of stroke and controls. Methods Through the nuclear magnetic resonance (NMR) platform, we evaluated 271 serum metabolites from a cohort of 297 AIS patients in acute and chronic stages and 159 controls. We used Sparse Partial Least Squares-Discriminant analysis (sPLS-DA) to evaluate group disparity; multivariate regression to compare metabolome in acute, chronic stages of stroke and controls; and mixed regression to compare metabolome acute and chronic stages of stroke. We applied false discovery rate (FDR) to our calculations. Results The sPLS-DA revealed separation of the metabolome in acute, chronic stages of stroke and controls. Regression analysis identified 38 altered metabolites. Ketone bodies, branched-chain amino acids (BCAAs), energy, and inflammatory compounds were elevated in the acute stage, but declined in the chronic stage, often to the same levels as in controls. Levels of other amino acids, phosphatidylcholines, phosphoglycerides, and sphingomyelins mainly did not change between acute and chronic stages, but was different comparing to controls. Conclusion Our pilot study identified metabolites associated with acute stage of ischemic stroke and those that are altered in stroke patients comparing to controls regardless of stroke acuity. Future investigation in a larger independent cohort is needed to validate these findings.