Citations

Abstract Artificial intelligence (AI) based digital pathology has been getting rapid adoption over the last 2 to 3 years These AI based digital pathology models can analyze samples at high resolution and scale Retaining that resolution at scale through molecular analysis is key to the discovery of novel biomarkers We have developed a technology that can integrate AI-supported digital pathology (DP) algorithms to identify informative tissue regions for selective microdissection to improve molecular analysis of FFPE material The system is capable of extracting DNA, RNA or proteins with cellular (10 micron) resolution from FFPE tissue sections. The samples are ready for use in off-the-shelf molecular analysis workflows (qPCR, Next Gen Sequencing, etc) The system decreases the tumor cellularity requirements for clinical analysis by extracting only the area enriched for informative biomarkers To demonstrate the capability of the system we used an AI based digital pathology model that was developed to identify multiple cellular phenotypes from a H&E stained colorectal cancer FFPE tissue sections We used the digital pathology output to guide the microdissection of RNA from tumor buds, carcinoma, immature stroma and inflammatory stroma in a paired designed RNA seq experiment The data showed that the system is capable of enriching the tumor-bud tissue content from<1% in the tissue to ~50% purity in the crude lysate Bioinformatic analysis of the RNAseq signatures showed that the tumor buds had a distinct RNAseq signature relative to the other three cell types and that the gene expression pattern was consistent with EMT pathways. The methodology is scalable, robust, and simpler than current microdissection techniques. This technology can be used to develop novel tests by integrating with AI algorithms, targeting tissue enriched for predictive biomarkers, and enabling low tumor cellularity samples to be analyzed with high precision. Citation Format: John H. Butler, Bidhan Chaudhuri, Katie Konigsfeld, Rish Pai. A novel digitally directed tissue microdissection platform integrates digital pathology with molecular analysis: Case study in metastatic colorectal cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4320.

In patients treated with macitentan (Opsumit®, Actelion Pharmaceuticals Ltd., Basel, Switzerland) for pulmonary arterial hypertension (PAH), prevention and/or effective management of treatment‐related adverse events may improve adherence. However, management of these adverse events can be challenging and the base of evidence and clinical experience for macitentan is limited. In the absence of evidence, consensus recommendations from physicians experienced in using macitentan to treat PAH may benefit patients and physicians who are using macitentan. Consensus recommendations were developed by a panel of physicians experienced with macitentan and PAH using a modified Delphi process. Over three iterations, panelists developed and refined a series of statements on the use of macitentan in PAH and rated their agreement with each statement on a Likert scale. The panel of 18 physicians participated and developed a total of 118 statements on special populations, add‐on therapy, drug–drug interactions, warnings and precautions, hospitalization and functional class, and adverse event management. The resulting consensus recommendations are intended to provide practical guidance on real‐world issues in using macitentan to treat patients with PAH.