Precise Identification of Cancer Recurrent Driven Targets for Sequential Treatment in Metastatic Gastric Cancer and Melanoma

Abstract Background: Because of intratumor heterogeneity, most patients with solid tumor received limit benefits from the first line regimen. The intratumor heterogeneous molecules are known to drive tumor progression, therapeutic resistance, and disease relapse at late stage across many cancers. The strategy of precise identify the cancer recurrent drive-related heterogeneous molecules from residual tumor tissues is the urgent and unmet clinical need, and it will help clinicians to optimal match the approved cancer-cross-drugs.Methods: The potential cancer recurrent driven targets recognition algorithm was constructed based on proteomics data followed by signal network analysis of tumor tissues before and after treatment. The weight and ranking of the candidate targets were further determined according to advanced research progress and related network databases. Sequential therapies were conducted to confirm the role of cancer recurrent driven molecules in mice with lung metastasis of either BGC823 or B16F10 cells.Results: The algorithm system was established successfully for precise identifying the cancer driven targets from the metastatic lung tumor foci. Thirty-eight candidate targets were identified from residual metastatic foci of GC (gastric cancer) in mice model; and 5 of 38 targets including JWA, MDM2, FASN, USP9X, and PFN1 were sequentially treated with target-specific peptide or inhibitors in BALB/c nude mice; similarly, 5 of 54 candidate targets including JWA, MDM2, SMAD3, IDH1/2, and mTOR were identified from the metastatic lung foci of melanoma and treated sequentially in C57BL/6 mice. Data showed that each additional sequential therapy of new target significantly reduced GC lung metastasis and prolonged the survival in melanoma lung metastasis mice. Meanwhile, both JWA and MDM2 were identified as re-cyclable targets for treatment in both GC and melanoma models. Together, our results may make possible for real individual therapeutic regimens on metastatic GC and melanoma.Conclusions: The highlight of our study should be the tumor recurrent driven targets recognition approach which may pave the way for the rational design of improved therapies against resistant malignancies. More importantly, the recognition algorithm may get into translational significance, and make possible for real precise individual therapeutic regimen of every cancer cases.