Tempus AI announces 31 abstracts for presentation at AACR annual meeting

Tempus AI (TEM) announced the acceptance of 31 abstracts-including one oral presentation-for the American Association for Cancer Research Annual Meeting 2026 taking place April 17-22 in San Diego. Tempus will host an Exhibitor Spotlight Theater session on Monday, April 20, 2026, from 10:00-11:00 AM PST in Theater B of the Sails Pavilion. In “Beyond the Pilot: Scaling Multimodal AI and Lab-in-the-Loop for Breakthrough R&D,” Sasser and Neil Bence, PhD, Senior Vice President of the Protein Homeostasis Thematic Research Center at Bristol Myers Squibb, will explore how combining deep molecular insights with high-throughput Lab-in-the-Loop functional screening can accelerate breakthroughs. Tempus research highlights presented at this year’s conference include: Co-occurrence of gene fusions and microsatellite instability defines a clinically distinct subtype of colorectal cancer: Investigation into the co-occurrence of gene fusions and microsatellite instability in 30,884,099 colorectal cancer patients revealed that clinically relevant fusions are significantly enriched in MSI versus MSS tumors. These findings suggest that the clinical impact of gene fusions is mediated by MSI status, defining a distinct molecular subtype of colorectal cancer that may influence therapeutic stratification. Oral Presentation: Real-world evidence of KMT2C mutation as a biomarker of sensitivity to platinum-based therapy in solid cancers: Researchers leveraged Tempus Lens to define a real-world cohort of 143,961 patients with solid tumors from the Tempus multimodal database. They sought to determine if KMT2C mutations are a biomarker for sensitivity to platinum-based chemotherapy. Their analysis revealed that patients with KMT2C mutations had significantly improved real-world overall survival after PBC treatment compared to patients without the mutation. The survival benefit was most significant in colorectal cancer, where patients with the mutation had a median rwOS of 51.0 months versus 25.3 months for those without. These findings, validated in the AACR Genie dataset, support KMT2C as a predictive biomarker for platinum response-particularly in CRC and GI cancers-with laboratory studies underway to clarify mechanisms. Analysis of RNA expression of 47 cell surface proteins in real-world small cell lung cancer patients: The research team performed an exploratory analysis of 56 cell surface proteins in 1,353 small cell lung cancer patients to identify differential expression patterns across subtypes, disease stages, and treatment statuses. Leveraging Tempus xT DNA-seq and xR RNA-seq data, the study identified subtype-specific expression. Machine learning predicts retained retinoblastoma function in real-world small cell lung cancer patients: To challenge the long-held belief that the retinoblastoma tumor suppressor is always inactive in small cell lung cancer, the research team developed a machine learning model to predict RB function. Using genomic and transcriptomic data from a real-world cohort of approximately 1,400 SCLC patients, the model found that nearly 30% of patients with RB1 genomic alterations still showed evidence of RB function transcriptionally. Immune-related RNA-seq biomarker-based clustering reveals heterogeneous immunotherapy responses and guides subtype-specific strategies in metastatic NSCLC: Patients with metastatic non-small cell lung cancer respond variably to first-line immunotherapy plus chemotherapy, yet the underlying immune biology driving these differences remains poorly understood. In a real-world cohort of 2,235 mNSCLC patients from the Tempus database, RNA-seq-based unsupervised clustering using immune markers identified four biologically distinct immune subtypes. Validation of HER2, TROP2, and NECTIN4 IHC prediction algorithms for the ADC MATCH trial: To facilitate patient selection for the ADC MATCH clinical trial, investigators validated RNA-seq algorithms designed to identify patients likely to test positive for HER2, TROP2, and NECTIN4 via immunohistochemistry. Detection of rare oncogenic fusions through concurrent DNA and RNA next-generation sequencing in a pan-cancer clinical setting: By retrospectively analyzing de-identified records from 74,182 patients with advanced cancer, this study quantified the clinical benefit of concurrent DNA and RNA testing for identifying rare oncogenic fusions.

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