Seer

The Proteograph® Product Suite empowers unbiased discoveries with the depth, accuracy, and scalability needed to accelerate breakthroughs in drug development, disease research, and precision medicine. Compatible with diverse sample types across human and non-human species, the Proteograph platform helps you uncover more of the proteome, putting you on the frontlines of discovery. Learn more: https://lnkd.in/gt7nksn9 #Proteomics #MassSpectrometry #Automation #LifeSciences #SeerBio #ProteinDiscovery

Professors Claudia Langenberg and Maik Pietzner (Queen Mary University of London) recently conducted a large-scale proteomics study with a genetically enriched cohort of 1,500 individuals—integrating Seer, Olink, SomaLogic, and whole-genome sequencing. Using Seer’s deep, unbiased MS approach, the study revealed new layers of biological insight: 8,000+ proteins detected → unprecedented depth for population studies Complete peptide absence in loss-of-function homozygotes → functional consequences beyond affinity-based methods 1,200+ pQTLs identified (50% novel) → at a scale previously requiring up to 40x more samples 690 colocalized genetic associations → disease-relevant cellular signals illuminated Why it matters: Deep MS is redefining what’s possible in population-scale proteomics—delivering insights unreachable by affinity-only approaches and paving the way for precision medicine. Watch the webinar: https://lnkd.in/gpXGegb6

Predefined markers can limit the performance of biomarker models. The performance of a biomarker model is limited by the biology available to train it. In a study of more than 2,500 subjects, investigators combined untargeted plasma proteomics with other molecular data to develop a blood-based model for early lung cancer detection. Unbiased protein features ranked among the model’s most informative inputs. Expanding beyond predefined markers can uncover higher-value features and strengthen the evidence used to decide which biomarkers move forward into validation. Learn more: https://bit.ly/4h6wLbv #BiomarkerDiscovery #EarlyDetection #LungCancer #Multiomics #Proteomics

Can protein biology reveal risk states that clinical staging misses? Patients with similar clinical staging can still experience very different outcomes. In multiple myeloma, deep proteomic profiling of bone marrow interstitial fluid identified 194 protein groups associated with overall survival and revealed coagulation-linked patient groups not explained by measured clinical covariates, including R-ISS. These findings are exploratory but show how broader protein biology may refine risk frameworks and support more biologically grounded stratification, enrichment, and patient-selection strategies. #PatientStratification #MultipleMyeloma #ClinicalDevelopment #PrecisionOncology #Proteomics

Clinical staging alone can leave important patient risk unresolved. Patients with similar clinical staging can still experience very different outcomes. In multiple myeloma, deep proteomic profiling of bone marrow interstitial fluid identified 194 protein groups associated with overall survival and revealed coagulation-linked patient groups not explained by measured clinical covariates, including R-ISS. These findings are exploratory but show how broader protein biology may refine risk frameworks and support more biologically grounded stratification, enrichment, and patient-selection strategies. Learn more: https://bit.ly/3UPNAA0 #PatientStratification #MultipleMyeloma #ClinicalDevelopment #PrecisionOncology #Proteomics

Is treatment effect accompanied by the biology you expected? Tumor control shows that a therapy had an effect. It does not fully explain the biology producing that effect. In a preclinical study of a sprayable therapeutic fibrin gel, matched tumor and serum proteomics revealed coordinated changes across local tumor and systemic host biology. Circulating proteins also provided blood-based readouts linked to tissue-level response. Cross-compartment, unbiased profiling can help teams evaluate whether efficacy is supported by aligned pathway biology and not phenotype alone. #MechanismOfAction #TranslationalOncology #TumorBiology #DrugDevelopment #Proteomics