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- Panel Features
- Panels List
- Workflow
- Why CP
- Demo
- Sample Requirements
- Case
- FAQ
What is the Olink Explore 384 Oncology Ⅱ Panel
Customized panel for human
The Olink Explore 384 Oncology II Panel employs Proximity Extension Assay technology to simultaneously measure 368 protein biomarkers relevant to oncology research, including both established markers and exploratory targets, using only 1 microliter of plasma or serum per sample while processing 88 samples per analytical run. This advanced platform achieves exceptional sensitivity with detection limits below 1 picogram per milliliter and demonstrates outstanding reproducibility with less than 5 percent coefficient of variation through Normalized Protein Expression data standardization. Featuring a flexible design incorporating eight distinct biomarker subpanels, the system supports comprehensive immunological characterization as well as targeted pathway investigations, while maintaining rigorous quality assurance through National Institute of Standards and Technology-traceable reference materials for dependable biomarker identification in cancer research.
Features of the pane
- Species: Human-specific applications.
- Proteins: 384-plex oncology protein analysis.
- Sample: 1 µL plasma/serumt.
- Readout: NPX-normalized quantification.
- Platform: Olink Signature Q100 platform exclusive.
List of 384 human derived biomarkers
Protein category
The Olink Explore 384 Oncology II Panel analyzes 368 protein biomarkers categorized into eight functional classes: Enzymes, Receptors, Cytokines/Chemokines, Structural/Adhesion Molecules, Signaling Proteins, Immune Regulators, Growth Factors/Binding Proteins, and Additional Functional Proteins. (see Table. List of Olink Explore 384 Oncology Ⅱ Panel). These targets encompass human proteins linked to oncogenic mechanisms critical for tumor development, including angiogenesis, intercellular communication, metabolic regulation, programmed cell death, and proliferation/differentiation pathways. Furthermore, DisGenNet-curated entries within the panel cover biomarkers associated with tumorigenesis, malignancy progression, solid neoplasms, and recurrent disease states.
Protein Functions
Biological process
Principally connected to immune system - related diseases, signal transduction, metabolism, and the innate immunity system.
Disease area
Mainly associated with metabolic, circulatory, malignant tumor, immune system, and neural system aspects.
The Application of Olink Explore 384 Oncology ⅡPanel.
The Olink Explore 384 Oncology II Panel enables simultaneous quantification of 384 protein biomarkers linked to cancer biology, providing researchers with a powerful tool for:
- Identification of novel protein signatures in tumor-immune interactions (e.g., immune checkpoint molecules, cytokines, chemokines);
- Mechanistic investigation of stromal remodeling (fibroblast activation, extracellular matrix regulation);
- Discovery of biomarkers for immunotherapy response or resistance in preclinical models (e.g., PDX, organoids);
- Stratification of experimental groups based on proteomic profiles (e.g., high vs. low immune infiltration).
Workflow of Olink Proteomics
Why CPR
Rigorous QC Protocols
Implements 14-stage quality control with inter-plate normalization, ensuring <5% coefficient of variation (CV) for >95% of biomarkers, critical for reproducible research data.
Disease-Specific Analytical Frameworks
Preconfigured workflows for solid tumors, hematologic malignancies, and tumor microenvironment (TME) studies, including 68 validated biomarker ratios for mechanistic insights.
Researcher Capacity Building
Includes oncology-specific training modules, bioinformatics workshops, and visualization toolkits to empower researchers in data interpretation and hypothesis generation.
Sample Integrity Validation
Integrated protocols verify sample quality (e.g., hemolysis, stability), reducing technical variability and enhancing data reliability in longitudinal studies.
Demo Results of Olink Data
Soluble factors at baseline in patients with ICI-refractory melanoma and matched healthy controls were determined by O-link multiplex assay. (Orme, J. J., et al. 2025)
Sample Requirements
| Sample Type | Recommended Sample Size | Sample Quality | Pre-treatment and Storage | Sample Transport |
| Plasma/Serum/Body Fluid | 40µL/sample | Protein concentration: 0.5mg/ml ~ 1mg/ml | Prepare aliquots in sterile tubes or plates and freeze at -80°C. | For foil-sealed specimens, use dry ice shipment (-80°C). |
| Tissue | ||||
| Cells | ||||
| Exosomes | ||||
| Other |
Case Study
Basal cell adhesion molecule (BCAM) promotes mesothelial-to-mesenchymal transition and tumor angiogenesis through paracrine signaling
Journal: Cell communication and signaling
Year: 2025
- Background
- Methods
- Results
High expression of basal cell adhesion molecules (BCAM) is a marker of ovarian cancer (OC) progression. BCAM promotes transbody cavity dissemination by promoting mesothelial cell clearance at the peritoneal attachment site of tumor cell globules. We investigated how BCAM mediates this effect and may drive other pro-metastatic functions.
The supernatants of BCAM-OE cells were analyzed using the Olink Explore 3072 platform for translational proteomics at the core facility of Phillips-Marburg University (UMR) Medical School based on the Olink protocol adjusted for cell culture supernatant analysis. All samples for the combined analysis were randomly assigned to 96-well plates. The samples were processed in a single batch. Next-generation sequencing (NGS) was conducted on the resulting libraries at the Genomics Core Facility of the UMR Faculty of Medicine.
To elucidate the bcam-induced secreted proteome in OC cells, researchers performed conditional medium (CM) from bcam overexpressing OVCAR-8 cells (BCAM-OE: clones BCAM1-2, BCAM1-8, BCAM2-1, BCAM2-3) and CM from control cells transduced with empty expression vectors (clone pcDNA-3) with PEA-based proteomics. As shown in the volcano plot in Figure 1A, this analysis identified n = 978 proteins that were significantly upregulated in BCAM-OE cells, while only n = 8 proteins were downregulated.
Figure 1. The volcano plot depicts the fold change (FC) of the BCAM-induced signal intensity (log2). (Sivakumar, S., et al. 2025)
FAQs
Can I receive sequencing raw data or FASTQ and analyze myself?
All Olink Explore sequencing data needs to be processed using Olink preprocessing software in order to convert sequencing reads into counts. The software recognizes company's predefined sequences in each read and assigns each correct read value to a sample and a protein (count) and outputs a count file containing the counts for each protein in each sample. This output is used to calculate the NPX value. Raw data/sequences that have not been preprocessed do not provide meaningful information on their own.
What are the main differences between proteomic sequencing using Olink technology and traditional DNA sequencing?
Olink uses NGS (next-generation sequencing) as a tool to measure the relative concentration of specific protein biomarkers in a sample. During sample and library preparation, short pieces of DNA with a unique sequence for each protein biomarker are generated. After sequencing, the number of counts (reads) of a particular DNA sequence is proportional to the original protein biomarker concentration.
How many protein biomarkers were measured in one Olink Explore kit?
One Explore 384 kit contains approximately 368 protein biomarkers, while one Explore 3072 consists of eight Explore 384 panels measuring approximately 2925 proteins in parallel. The remaining positions in the toolbox are used as controls.
References
- Orme, J. J., Zhang, H., Lingamaneni, P., et al. (2025). Plasma exchange and radiation resensitize immunotherapy-refractory melanoma: a phase I trial. Nature communications, 16(1), 2507. https://doi.org/10.1038/s41467-025-57865-9
- Sivakumar, S., Lieber, S., Dietze, R., et al. (2025). Basal cell adhesion molecule (BCAM) promotes mesothelial-to-mesenchymal transition and tumor angiogenesis through paracrine signaling. Cell communication and signaling: CCS, 23(1), 136. https://doi.org/10.1186/s12964-025-02128-9