Treatment of metastatic cancer is often a challenge, thus accounting for over 90% of cancer deaths. Main treatment options are only partially effective, leading to resistance and failure, as there are no well-established markers to predict response. Molecular characterization of individual tumor samples can provide information on actionable targets, allowing selection of the most beneficial treatment for the patient.

We developed a workflow including morphological and molecular profiling for aiding treatment decision making in late-stage cancer patients. AI-based morphological characterization of the FFPE resected tissues was applied to identify areas of interest for further laser microdissection (LMD) of tumor, stroma components, and different subclones. Molecular profiling of the tissue samples included multi-omics strategies, such as gene mutation panels, transcriptomics, and proteomic analysis. The established workflow was applied to multiple metastatic cancer patients with advanced clinical stages.

In all cases, we were able to identify targetable molecular signatures, proposing new treatment directions for each patient. Patient 1 (metastatic melanoma) presented multiple subclones with different molecular signatures, indicating high intra-tumor heterogeneity. Overall, this patient presented low immune cell infiltration and high metabolic activity in both primary and metastatic tumors, suggesting a non-response to the current immunotherapy and possible response to targeted treatment. In Patient 2 (metastatic prostate cancer), we identified high mitochondrial metabolic activity and presence of immune system response. LMD analysis revealed that mitochondria activation was more present in tumor compared to stroma regions, where PI3K/AKT/MTOR signaling pathway was upregulated. Our data suggested the use of mitochondrial complex inhibitors could be effective in combination with targeted treatment. Patient 3 (metastatic melanoma) also revealed multiple subclones in the morphological profile, suggesting high intra-tumor heterogeneity in the primary. However, its molecular profile compared with the metastases did not show high inter-tumor heterogeneity. In general, this patient exhibited a high proliferative profile in all tumors but indicated a higher metabolic activity in the metastases. These results implied that the patient could respond well to inhibitors of key metabolic components.

In all case studies, we have proved that high-throughput molecular profiling allied with morphology can be essential elements for implementing precision medicine and selecting the most beneficial treatment for individual patients with advanced metastatic disease. Our data predicted treatment response and aided clinical decision making, prolonging patient survival from the predicted prognosis, and setting the ground for omic analysis inside the clinical surroundings.