Cancer is a heterogeneous disease characterized by aberrant cellular signaling. Hyperactive kinase activity is one of the drivers of tumorigenesis and cancer progression and results in altered phosphorylation abundance and activity of downstream substrates. A prime prerequisite for personalized treatment is that kinase activity inference can be based on a single (patient) sample. This is pivotal in a clinical setting with the aim to select the best kinase inihibitor treatment for individual patients.
To this end, phosphoproteomics coupled to INKA analysis has emerged as an advantageous approach that achieves an optimized ranking of inferred kinase activities in single samples (www.inkascore.org) (1-5). INKA integrates kinase phosphorylation and substrate phosphorylation to infer kinase activity. The output is a ranked kinase activity bar graph and an individualized kinase-substrate network that can be used by biologists and clinicians to extract actionable information from modern deep comprehensive (patient) phosphoproteomic data.
In my lecture, I will present our progress in (phospho)proteomics profiling and INKA of xenograft tumor models and tumor needle biopsies collected as part of side-studies in precision medicine clinical trials (IMPACT, colorectal cancer patients treated with anti-EGFR therapy; REPOSIT, melanoma patients treated with anti-BRAF-MEK combination therapy; DRUP-Lenvatinib cohort, pan-cancer). Our findings show that needle biopsy protein yields are compatible with phosphoproteomics (~200 mg protein) and a large fraction of the samples is also amendable to pTyr-phosphoproteomics that we recently down-scaled to 500 mg protein input. The analyses offer explanation for (lack of) drug response and uncover actionable resistance mechanisms.
Ultimately, prospective clinical trials that include drug selection based on patient phosphoproteomic data coupled to individualized kinase and pathway activity inference, will show the added value of phosphoproteomics (combined with genomics) for precision medicine.
Beekhof R, Henneman AA, Jimenez CR et al.,. INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases. Mol Syst Biol. 2019 May 24;15(5):e8981.Cordo' V, et al., Phosphoproteomic profiling of T cell acute lymphoblastic leukemia reveals targetable kinases and combination treatment strategies. Nat Commun. 2022 Feb 25;13(1):1048. Vallés-Martí A, et al. Phosphoproteomics guides effective low-dose drug combinations against pancreatic ductal adenocarcinoma. Cell Rep. 2023 Jun 1;42(6):112581.Beekhof R, et al., Phosphoproteomics of patient-derived xenografts identifies targets and markers associated with sensitivity and resistance to EGFR blockade in colorectal cancer. Sci Transl Med. 2023 Aug 16;15(709):eabm3687.Vallés-Martí A, et al. Kinase activities in pancreatic ductal adenocarcinoma with prognostic and therapeutic avenues. Mol Oncol. 2024 Aug;18(8):2020-2041.