OncoHost's New Study Bridges Serum and Plasma Proteomics for Enhanced Biomarker Discovery
OncoHost, an innovative technology company specializing in precision oncology, has made headlines with the release of a transformative study published in the Journal of Pharmaceutical and Biomedical Analysis (JPBA). This pivotal research, titled "Bridging the Gap: A Systematic Approach to Integrating Serum and Plasma Proteomic Datasets for Biomarker Studies," reveals a novel computational framework designed to harmonize serum and plasma proteomic datasets. Traditionally, these specimen types have been viewed as non-comparable due to biological and pre-analytical differences, resulting in fragmented data that limited effective research methodologies.
This groundbreaking study addresses a significant challenge in the realm of proteomic biomarker research, unlocking new possibilities for researchers by allowing them to combine disparate data sets that were previously siloed. The enhanced analytical depth and broad applicability of this approach make significant strides in accelerating biomarker discovery and validation efforts, ultimately paving the way for improved patient outcomes in oncology.
Harnessing Cross-Specimen Data Integration
The differentiation in serum and plasma sample preparation has long hindered direct comparisons and data integration within clinical research and biobanking. Large cohorts from each specimen type often remained unassimilated, reducing the potential insights that could be gained from comprehensive analysis. However, the OncoHost study involved high-throughput proteomic profiling of an impressive 7,289 proteins using the cutting-edge SomaScan® platform, analyzing 177 matched serum-plasma sample pairs drawn from cancer patients across three independent cohorts. Astonishingly, the results showed that 91.6% of the proteins exhibited statistically significant correlation (p < 0.05) between serum and plasma.
The researchers derived linear scaling factors from these matched sample pairs, demonstrating a consistent methodology that enhances the robustness and generalizability of the bridging technique.
"This research tackles a persistent problem within proteomic biomarker studies," remarked Coren Lahav, MSc, Senior Data Scientist and the lead author of the publication. "By offering a systematic method for transitioning between serum and plasma measurements, we open the door to leverage datasets that were once isolated. This not only strengthens analytical reliability but also enhances clinical sample flexibility and supports scalable multi-cohort validations."
Validation via PROphet®
A key component of OncoHost's study includes the validation of the bridging strategy through the use of the PROphet® platform. This AI-driven model focuses on plasma proteomics specifically to predict immunotherapy outcomes, particularly in patients diagnosed with non-small cell lung cancer (NSCLC). The exceptional findings revealed that when the PROphet model was applied to the scaled serum proteomic measurements, it retained predictive accuracy. The classification of clinical benefits and survival rates generated from the transformed serum data was comparable to that derived from plasma, thereby affirming the preservation of the underlying biological signals.
"This achievement signifies a significant advancement for the field of liquid proteomics," stated Ofer Sharon, MD, CEO of OncoHost. "The ability to reliably extend plasma-based predictive models to serum through meticulous harmonization underscores the robustness of our approach and encourages broader clinical use. The implications of generalizing findings across specimen types substantially amplify the viability of proteomic diagnostics, facilitating wider acceptance in precision oncology."
Expanding Technical and Clinical Capabilities
The implications of this study extend beyond immediate dataset alignment; it lays the foundation for standardized methodologies concerning sample types, including the compatibility of varying collection tubes and biological matrices. This cross-specimen comparability could unveil valuable serum-based cohorts, providing new horizons for discovery and validation in clinical applications.
As the role of proteomics continues to evolve within precision oncology, systematic approaches like this are essential for fostering reproducible and scalable biomarker development, thus propelling advancements in clinical diagnostics and patient care.
For further insights, you can access the full publication through this link: JPBA Study.
About OncoHost
Headquartered in Binyamina, Israel, and Cary, North Carolina, OncoHost is dedicated to revolutionizing precision medicine to enhance patient outcomes. Their flagship platform, PROphet®, utilizes plasma-based proteomic analysis to assist in guided immunotherapy decisions for non-small cell lung cancer (NSCLC). The PROphetNSCLC® test offers actionable clinical insights, aiding physicians in determining the optimal treatment pathway for each patient, ultimately affecting overall survival positively. With the backing of seasoned entrepreneurs and industry specialists, alongside an extensive clinical trial network comprising over 40 sites and more than 1,700 patient recruits globally, OncoHost is well-equipped to shape the future of precision diagnostics and biomarker innovation.
This groundbreaking study addresses a significant challenge in the realm of proteomic biomarker research, unlocking new possibilities for researchers by allowing them to combine disparate data sets that were previously siloed. The enhanced analytical depth and broad applicability of this approach make significant strides in accelerating biomarker discovery and validation efforts, ultimately paving the way for improved patient outcomes in oncology.
Harnessing Cross-Specimen Data Integration
The differentiation in serum and plasma sample preparation has long hindered direct comparisons and data integration within clinical research and biobanking. Large cohorts from each specimen type often remained unassimilated, reducing the potential insights that could be gained from comprehensive analysis. However, the OncoHost study involved high-throughput proteomic profiling of an impressive 7,289 proteins using the cutting-edge SomaScan® platform, analyzing 177 matched serum-plasma sample pairs drawn from cancer patients across three independent cohorts. Astonishingly, the results showed that 91.6% of the proteins exhibited statistically significant correlation (p < 0.05) between serum and plasma.
The researchers derived linear scaling factors from these matched sample pairs, demonstrating a consistent methodology that enhances the robustness and generalizability of the bridging technique.
"This research tackles a persistent problem within proteomic biomarker studies," remarked Coren Lahav, MSc, Senior Data Scientist and the lead author of the publication. "By offering a systematic method for transitioning between serum and plasma measurements, we open the door to leverage datasets that were once isolated. This not only strengthens analytical reliability but also enhances clinical sample flexibility and supports scalable multi-cohort validations."
Validation via PROphet®
A key component of OncoHost's study includes the validation of the bridging strategy through the use of the PROphet® platform. This AI-driven model focuses on plasma proteomics specifically to predict immunotherapy outcomes, particularly in patients diagnosed with non-small cell lung cancer (NSCLC). The exceptional findings revealed that when the PROphet model was applied to the scaled serum proteomic measurements, it retained predictive accuracy. The classification of clinical benefits and survival rates generated from the transformed serum data was comparable to that derived from plasma, thereby affirming the preservation of the underlying biological signals.
"This achievement signifies a significant advancement for the field of liquid proteomics," stated Ofer Sharon, MD, CEO of OncoHost. "The ability to reliably extend plasma-based predictive models to serum through meticulous harmonization underscores the robustness of our approach and encourages broader clinical use. The implications of generalizing findings across specimen types substantially amplify the viability of proteomic diagnostics, facilitating wider acceptance in precision oncology."
Expanding Technical and Clinical Capabilities
The implications of this study extend beyond immediate dataset alignment; it lays the foundation for standardized methodologies concerning sample types, including the compatibility of varying collection tubes and biological matrices. This cross-specimen comparability could unveil valuable serum-based cohorts, providing new horizons for discovery and validation in clinical applications.
As the role of proteomics continues to evolve within precision oncology, systematic approaches like this are essential for fostering reproducible and scalable biomarker development, thus propelling advancements in clinical diagnostics and patient care.
For further insights, you can access the full publication through this link: JPBA Study.
About OncoHost
Headquartered in Binyamina, Israel, and Cary, North Carolina, OncoHost is dedicated to revolutionizing precision medicine to enhance patient outcomes. Their flagship platform, PROphet®, utilizes plasma-based proteomic analysis to assist in guided immunotherapy decisions for non-small cell lung cancer (NSCLC). The PROphetNSCLC® test offers actionable clinical insights, aiding physicians in determining the optimal treatment pathway for each patient, ultimately affecting overall survival positively. With the backing of seasoned entrepreneurs and industry specialists, alongside an extensive clinical trial network comprising over 40 sites and more than 1,700 patient recruits globally, OncoHost is well-equipped to shape the future of precision diagnostics and biomarker innovation.
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