Cassio Murilo T. Hidalgo Filho
59 posts
@CMHidalgoFilho
🇧🇷 Medical Oncologist
🔥Overcoming primary & acquired resistance to ICI in NSCLC 🆙 @JCO_ASCO ☑Key: Impaired antigen present, T-cell exhaustion & TME remodeling 🎯Next-gen ICIs, epigen modul & metabolic agents against STK11/KEAP1 🎙 @CMHidalgoFilho #LCSM @OncoAlert @Larvol ascopubs.org/doi/full/10.12…
🔥Overcoming primary & acquired resistance to ICI in NSCLC 🆙 @JCO_ASCO ☑Key: Impaired antigen present, T-cell exhaustion & TME remodeling 🎯Next-gen ICIs, epigen modul & metabolic agents against STK11/KEAP1 🎙 @CMHidalgoFilho #LCSM @OncoAlert @Larvol ascopubs.org/doi/full/10.12…
Congratulations to #ESMOMeritAward recipients Guilherme Nader Marta (@GuiNaderMarta) Paolo Tarantino (@PTarantinoMD) and Carmine Valenza (@ValenzaCarmine)! #ESMOBreast26
Are you interested in #AI-powered tools in #oncology? Join the #YO4YO Session w/ @GuiNaderMarta, @MaximilianKloft, @mihaela_aldea & @rdienstmann 📌 How to Evaluate and Collaborate on AI-Powered Tools in Oncology #ESMOYOC 📅4 May 15:00-16:00 CEST 🔗 ow.ly/M9gC50YQqbu
📢 Applications are OPEN for the Yin & Yang Lung Cancer Masterclass 2nd Edition 🇫🇷 🗓 Paris | June 26–27, 2026 🎯 For early-career thoracic oncologists & residents under 40 ✈️ Travel & accommodation support provided ⏰ Deadline: April 21st Submit your CV, motivation letter & clinical case now 👇 🌐 yinyanglungcancer.com/how-to-partici… @RobertoFerrara_ @BRicciutiMD @MarceloCorassa #LungCancer #Thoracic #Oncology #NSCLC #YoungOncologist #Paris2026
Deep Learning Model for Predicting Immunotherapy Response in Advanced Non−Small Cell Lung Cancer Out on @JAMAOnc This study highlights the importance of identifying patients with advanced non-small cell lung cancer (NSCLC) who are most likely to benefit from immune checkpoint inhibitor (ICI) therapy. It developed and validated a deep learning-based model that predicts ICI treatment response using hematoxylin and eosin–stained images from multiple centers in the US and EU. The model’s performance was compared to traditional biomarkers such as PD-L1, tumor mutational burden (TMB), and tumor-infiltrating lymphocytes (TILs). The deep learning model achieved higher predictive accuracy than TMB and TILs and was comparable to PD-L1 in terms of objective response rate (ORR). When combined with PD-L1 scores, it showed further improvement in treatment specificity and patient outcomes, demonstrating its potential to enhance personalized NSCLC care by refining treatment decisions. buff.ly/3ZMTf8w @BiagioRicciutMD @alessi_joao @ACortelliniMD @FCitarellaMD @adib_elio @FulgenziClaudia @CMHidalgoFilho @DiFedericoMD @_SayedHashemi @Ilias_Houda @DJPinato @HellandAslaug @lmsholl @DrMarkAwad
👉🏼 Finding available cancer trials in Brazil is a thought task and most hem-oncs will end up asking friends. I recently began an open and collaborative data project of showcasing these trials built on top of the clinicaltrialsGov database - cancertrialsbr.com.br 1/n
