Reliable biomarkers for monitoring and predicting disease course, stage and progression are invaluable. They offer particular value in therapeutic decision-making when there is a risk of severe adverse events.

Autoantibody biomarkers can be used to establish signatures for predicting if patients are likely to respond to treatment. These predictive signatures can also be used to identify patient populations likely to experience adverse events.

Having the ability to interrogate many autoantibody targets in a single assay can help accelerate the identification and validation of signatures with high predictive value.

Accelerating discovery of autoantibody signatures

Sengenics can help, with solutions to support discovery of biomarker signatures. Our high-density protein microarray assays enable highly specific and reproducible detection of disease-relevant autoantibodies directly from patient serum.

Related Study

Predictive Autoantibody Biomarker Panel in NSCLC

Kaplan Meier curve showing overall survival of patients with high and low expression of a 13-autoantibody biomarker signature in non-small cell lung cancer (NSCLC) patients who have undergone lung resection.  Poor survivor ship is demonstrated in patient with high expression of the signature with an overall 5-year survival rate of 7.6%.​

Source: Patel, A.J., et. al., A highly predictive autoantibody-based biomarker panel for prognosis in early-stage NSCLC with potential therapeutic implications, British Journal of Cancer (2021)​.

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