Next Generation Sequencing (NGS) panels are increasingly used in advanced patients with cancer to guide therapy. There is, however, controversy about when should these panels be used, and about their impact on the clinical course. In an observational study of 139 patients with cancer having an NGS test [from January 1st, 2017 to December 30th, 2020, in two hospitals (Hospital Universitario de La Princesa and Hospital Universitario Quironsalud Madrid) from Spain], we evaluated whether the clinical course (progression-free survival, PFS) was influenced by drug-based criteria [druggable alterations, receiving a recommended drug, having a favourable ESCAT category (ESMO Scale for Clinical Actionability of molecular Targets)] or clinical judgement criteria. In 111 of 139 cases that were successfully profiled, PFS was not significantly influenced by either having druggable alterations [median PFS for patients with druggable alterations was 170 (95% C.I.: 139-200) days compared to 299 (95% C.I.: 114-483) for those without; p = 0.37], receiving a proposed matching agent [median PFS for patients receiving a genomics-informed drug was 195 days (95% C.I.: 144-245), compared with 156 days for those that did not (95% C.I.: 85-226); p = 0.50], or having favourable ESCAT categories [median PFS for patients with ESCAT I-III was 183 days (95% C.I.: 104-261), compared with 180 (95% C.I.:144-215) for patients with ESCAT IV-X; p = 0.87]. In contrast, NGS testing performed within clinical judgement showed a significantly improved PFS [median PFS for patients that were profiled under the recommended scenarios was 319 days (95% C.I.: 0-658), compared to 123 days (95% C.I.: 89-156) in the non-recommended categories; p = 0.0020]. According to our data, real-world outcomes after NGS testing provide evidence of the benefit of clinical judgement in patients with either advanced cancers that routinely need multiple genetic markers, patients with advanced rare cancers, or patients that are screened for molecular clinical trials. By contrast, NGS does not seem to be valuable when performed in cases with a poor PS, rapidly progressing cancer, short expected lifetime, or cases with no standard therapeutic options. RC, NR-L and MQF are recipients of the PMP22/00032 grant, funded by the ISCIII and co-funded by the European Regional Development Fund (ERDF). The study also received funds from the CRIS Contra el Cancer Foundation.

Immunotherapy delivered a new therapeutic option to the oncologist: Ipilimumab (anti-CTLA-4), Nivolumab and Pembrolizumab (anti-PD1), and Atezolizumab (anti-PD-L1) increase overall survival and show a better safety profile compared to chemotherapy in patients with metastatic melanoma, lung, renal cancer among others. But all that glitters is not gold and there is an increasing number of reports of adverse effects while using immune-checkpoint inhibitors. While chemotherapy could weaken the immune system, this novel immunotherapy could hyper-activate it, resulting in a unique and distinct spectrum of adverse events, called immune-related adverse events (IRAEs). IRAEs, ranging from mild to potentially life-threatening events, can involve many systems, and their management is radically different from that of cytotoxic drugs: immunosuppressive treatments, such as corticoids, infliximab or mycophenolate mofetil, usually result in complete reversibility, but failing to do so can lead to severe toxicity or even death. Patient selection is an indirect way to reduce adverse events minimizing the number of subjects exposed to this drugs: unfortunately PDL-1, the actual predictive biomarker, would not allow clinicians select or exclude patients for treatment with checkpoint inhibitors.

Purpose: To explore the tumor proteome of patients diagnosed with localized clear cell renal cancer (ccRCC) and treated with surgery. Material and methods: A total of 165 FFPE tumor samples from patients diagnosed with ccRCC were analyzed using DIA-proteomics. Proteomics ccRCC subtypes were defined using a consensus cluster algorithm (CCA) and characterized by a functional approach using probabilistic graphical models and survival analyses. Results: We identified and quantified 3091 proteins, including 2026 high-confidence proteins. Two proteomics subtypes of ccRCC (CC1 and CC2) were identified by CC using the high-confidence proteins only. Characterization of molecular differences between CC1 and CC2 was performed in two steps. First, we defined 514 proteins showing differential expression between the two subtypes using a significance analysis of microarrays analysis. Proteins overexpressed in CC1 were mainly related to translation and ribosome, while proteins overexpressed in CC2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. CC1 subtype is characterized by an increased expression of proteins related to glycolysis, mitochondria, translation, adhesion proteins related to cytoskeleton and actin, nucleosome, and spliceosome, while CC2 subtype showed higher expression of proteins involved in focal adhesion, extracellular matrix, and collagen organization. Conclusions: ccRCC tumors can be classified in two different proteomics subtypes. CC1 and CC2 present specific proteomics profiles, reflecting alterations of different molecular pathways in each subtype. The knowledge generated in this type of studies could help in the development of new drugs targeting subtype-specific deregulated pathways.