Flexibility in metabolism bestows tenacious viability on cancer

Nano-energy interference: A novel strategy for blunting tumor adaptation and metastasis

Blunting the tumor's stress-sensing ability is an effective strategy for controlling tumor adaptive survival and metastasis. Here, we have designed a cyclically amplified nano-energy interference device based on lipid nanoparticles (LNP), focused on altering cellular energy metabolism. This innovative nano device efficiently targets and monitors the tumor's status while simultaneously inhibiting mitochondrial respiration, biogenesis and ribosome production. To this end, we first identified azelaic acid (AA), a binary acid capable of disrupting the mitochondrial respiratory chain. Upon encapsulation in LNP and linkage to mitochondrial-targeting molecules, this disruptive effect is further augmented. Consequently, tumors exhibit a substantial upregulation of the glycolytic pathway, intensifying their glucose demand and worsening the tumor's energy-deprived microenvironment. Then, the glucose analog, 2-Deoxy-D-glucose (2-DG), linked to the LNP, efficiently targets tumors and competitively inhibits the tumor's normal glucose uptake. The synergetic results of combining AA with 2-DG induce comprehensive energy deficiency within tumors, blocking the generation of energy-sensitive ribosomes. Ultimately, the disruption of both mitochondria and ribosomes depletes energy supply and new protein-generating capacity, weakening tumor's ability to adapt to environmental stress and thereby inhibiting growth and metastasis. Comprehensively, this nano-energy interference device, by controlling the tumor's stress-sensing ability, provides a novel therapeutic strategy for refractory tumors.

Investigating skewness to understand gene expression heterogeneity in large patient cohorts

BACKGROUND

Skewness is an under-utilized statistical measure that captures the degree of asymmetry in the distribution of any dataset. This study applied a new metric based on skewness to identify regulators or genes that have outlier expression in large patient cohorts.

RESULTS

We investigated whether specific patterns of skewed expression were related to the enrichment of biological pathways or genomic properties like DNA methylation status. Our study used publicly available datasets that were generated using both RNA-sequencing and microarray technology platforms. For comparison, the datasets selected for this study also included different samples derived from control donors and cancer patients. When comparing the shift in expression skewness between cancer and control datasets, we observed an enrichment of pathways related to the immune function that reflects an increase towards positive skewness in the cancer relative to control datasets. A significant correlation was also detected between expression skewness and the top 500 genes corresponding to the most significant differential DNA methylation occurring in the promotor regions for four Cancer Genome Atlas cancer cohorts.

CONCLUSIONS

Our results indicate that expression skewness can reveal new insights into transcription based on outlier and asymmetrical behaviour in large patient cohorts.