International Journal Publication | Dr. Qinlong Zheng and Collaborators Identify 9 Key Protein Biomarkers and Develop a New Model for Pediatric B-ALL Diagnosis and Risk Assessment

Summary: Dr. Qinlong Zheng of Beijing GoBroad Boren Hospital, together with collaborating investigators, published a study in Cancer Letters using Olink proteomics to identify nine key protein biomarkers that were differentially expressed between children with B-cell acute lymphoblastic leukemia (B-ALL) and B-ALL patients in complete molecular remission (CMR). The resulting diagnostic model achieved an area under the curve (AUC) of 0.98 in the validation cohort, providing new proteomics-based evidence and potential tools for more precise assessment and clinical decision-making in pediatric B-ALL.

Genomic analysis has fundamentally reshaped risk assessment and clinical decision-making in pediatric B-cell acute lymphoblastic leukemia (B-ALL). However, genomic testing can be complex, time-consuming, and costly, which may limit rapid use in some clinical settings. Proteomics offers a complementary perspective by capturing dynamic changes in disease biology and the immune microenvironment at the functional protein level, creating new possibilities for more precise assessment and clinical translation in pediatric B-ALL.

Recently, Dr. Qinlong Zheng of Beijing GoBroad Boren Hospital, one of the corresponding authors, collaborated with Professor Yizhi Jiang, Professor Dongping Huang, and their team at The First Affiliated Hospital of Wannan Medical College on a study published in Cancer Letters (IF 10.1). Using Olink proteomics, the researchers systematically profiled protein expression in pediatric B-ALL and identified and validated nine key biomarkers that differed between patients with active B-ALL and CMR controls: CXCL13, NCR1, ADA, IL6, HO-1, CCL3, CCL4, CD27, and ADGRG1. The findings provide a new proteomics-based perspective for more precise assessment and clinical decision-making in pediatric B-ALL.

Study Design

The study included 50 children with B-ALL and 43 control samples from B-ALL patients who had achieved complete molecular remission (CMR). Participants were divided into discovery and validation cohorts. The discovery cohort included 30 patients with B-ALL and 26 CMR controls, while the validation cohort included 20 patients with B-ALL and 17 CMR controls.

The researchers used Olink proteomic analysis with the Olink Target 96 Oncology Response protein panel. After screening for differentially expressed proteins (DEPs), statistical modeling was used to identify the protein combination with the strongest discriminatory performance. Key findings were then independently validated using enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC).

Study Results

1. Key Finding: Pediatric B-ALL Has a Distinctive Protein Expression Profile

The study first identified clear differences in protein expression between pediatric B-ALL and CMR controls. A total of 37 differentially expressed proteins were found, involving regulators of cellular function, chemokines and inflammatory mediators, and tumor-related proteins. Together, these proteins were able to clearly distinguish active disease from molecular remission.

These findings suggest that pediatric B-ALL involves not only abnormal proliferation of leukemia cells, but also substantial remodeling of the bone marrow immune microenvironment. Proteomics can capture these functional changes at the protein level.

Figure 1. Thirty-Seven Differentially Expressed Proteins Identified Between Pediatric B-ALL and CMR Control Samples

2. Key Finding: A 9-Protein Panel Showed Near Clinical-Grade Discriminatory Performance

Based on the differentially expressed proteins, the researchers used a LASSO regression model to identify nine key proteins — CXCL13, NCR1, ADA, IL6, HO-1, CCL3, CCL4, CD27, and ADGRG1 — and used them to build a diagnostic model.

The model achieved an area under the curve (AUC) of 1.00 in the discovery cohort and 0.98 in the validation cohort, demonstrating very strong ability to distinguish pediatric B-ALL from CMR controls.

Figure 2. Diagnostic Performance of LASSO-Selected Differentially Expressed Proteins in Pediatric B-ALL. AUC curves show the discriminatory performance of the most significant DEPs in the discovery cohort (a) and validation cohort (b).

3. Key Finding: Key Proteins Were Consistently Validated by ELISA and IHC

To strengthen reproducibility and translational potential, the researchers validated key protein signals using independent methods. ELISA was used to confirm trends in plasma protein levels, while IHC was used to evaluate protein expression in patient-derived xenograft (PDX) tissues.

Proteins including CCL3, CCL4, and CD27 showed consistent patterns across different testing platforms, supporting their stability and potential clinical relevance.

4. Key Finding: Higher Levels of Differential Proteins Were Associated with Genetic Alterations Linked to Poorer Prognosis

The researchers also found that several differentially expressed proteins were present at higher levels in children carrying genetic alterations associated with poorer prognosis. These proteins included CD27, TNF, CCL3, CCL4, IL12RB1, PDCD1, and GZMB.

This suggests that pediatric B-ALL with poor-risk genetic alterations may also be accompanied by more pronounced immune- and inflammation-related protein changes.

Overall, the study uses proteomics to provide a new perspective beyond existing molecular classification frameworks for pediatric B-ALL. The findings may help make disease assessment and risk evaluation more refined and support clinical decisions that better reflect each child's underlying disease biology. Over time, this could help clinicians pursue effective treatment while reducing unnecessary treatment burden and improving long-term outcomes and quality of life for children with leukemia.

The publication also reflects the growing capabilities of the Molecular Diagnostics Laboratory at GoBroad Diagnostic Center. As an important platform supporting precision care in hematologic malignancies, the laboratory has developed an integrated workflow covering molecular classification and detection of key genetic alterations, support for measurable residual disease (MRD) testing, standardized quality control across the full sample-processing pathway, and biomarker discovery, validation, and translation. These capabilities provide clinicians with stable, traceable, and potentially translatable evidence for diagnosis and monitoring, while also supporting consistent data generation in multicenter collaborative research. Building on this platform, GoBroad will continue integrating advanced testing with clinical pathways and accelerating the translation of research findings into practical decision-making tools, with the goal of making precision medicine more meaningful for patients.