QuantAnts machines discover biomarkers for RAS signaling activation and design sgRNAs for CRISPR to target complex CD9, CD34, and CD74.

In this work, we introduce a quantum algorithm for biomarker identification in oncology, named QuantAnts machines, pronounced "quantant machine." Our proposed machine intelligence allows sampling biomarker-verse for the targeted RAS signaling activation, revealing combinations of biomarkers with therapeutic applications. Notable, the QuantAnts for Clinical Oncology model, ASCO(ant-4) discovers the complex CD9, CD34, and CD74 as targeting for RAS pathway for some cancer phenotypes such as gastric, colorectal (with/without metastasis), ovarian, breast and brain cancer. To the end, we show the generalization of QuantAnts machines by altering the model for genetic code designs (named QuantAnts-CRISPR), which enabling optimized sgRNA for CRISPR-Cas9 to target the complex CD9, CD34, and CD74 all-together. The found sgRNA designs are optimized by reversing mutation processes over the targeted complex, i.e., balancing the mutated contents over the input biomarker-verse.