Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92-0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83-0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.
Liquid biopsies have been considered the holy grail in achieving effective cancer management, with blood tests offering a minimally invasive, safe, and sensitive alternative or complementary approach for tissue biopsies. Currently, blood-based liquid biopsy measurements focus on the evaluation of biomarker types, including circulating tumor DNA, circulating tumor cells, extracellular vesicles (exosomes and oncosomes), and tumor-educated platelets (TEPs). Despite the potential of individual techniques, each has its own advantages and disadvantages. Here, we provide further insight into TEPs.
BRAF(V600E) mutant colon cancers (CCs) have a characteristic gene expression signature that is also found in some tumors lacking this mutation. Collectively, they are referred to as "BRAF-like" tumors and represent some 20% of CCs. We used a shRNA-based genetic screen focused on genes upregulated in BRAF(V600E) CCs to identify vulnerabilities of this tumor subtype that might be exploited therapeutically. Here, we identify RANBP2 (also known as NUP358) as essential for survival of BRAF-like, but not for non-BRAF-like, CC cells. Suppression of RANBP2 results in mitotic defects only in BRAF-like CC cells, leading to cell death. Mechanistically, RANBP2 silencing reduces microtubule outgrowth from the kinetochores, thereby inducing spindle perturbations, providing an explanation for the observed mitotic defects. We find that BRAF-like CCs display far greater sensitivity to the microtubule poison vinorelbine both in vitro and in vivo, suggesting that vinorelbine is a potential tailored treatment for BRAF-like CCs.
Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.