Presence of Serum Antinuclear Antibodies Correlating Unfavorable Overall Survival in Patients with Chronic Lymphocytic Leukemia
Chronic lymphocytic leukemia (CLL) is a hematologic malignancy characterized by the progressive accumulation of small, mature lymphocytes in the peripheral blood, bone marrow, and lymphoid tissues. Although CLL is relatively rare in East Asia, its incidence has been increasing in recent years. The clinical course of CLL is highly heterogeneous, with some patients experiencing rapid disease progression and poor survival, while others may live for decades without requiring treatment. This heterogeneity has prompted extensive research into prognostic factors that can help predict outcomes and guide treatment decisions. Among the various biomarkers studied, serum antinuclear antibodies (ANAs) have recently emerged as a potential prognostic indicator in CLL. This article explores the role of ANAs in CLL, their association with clinical outcomes, and their potential utility in improving risk stratification.
Background and Rationale
CLL is often accompanied by immune disturbances, including autoimmune cytopenias such as autoimmune hemolytic anemia (AIHA) and immune thrombocytopenia (ITP), as well as non-hematological autoimmune diseases (AIDs) like rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Autoantibodies, including ANAs, are commonly observed in CLL patients, but their prognostic significance remains poorly understood. ANAs are autoantibodies directed against nuclear antigens and are typically associated with rheumatic diseases. However, their presence in CLL patients has been reported, raising questions about their role in disease progression and survival.
This study aimed to evaluate the prognostic value of ANAs in CLL by analyzing clinical data from 216 newly diagnosed CLL patients. The study focused on the relationship between ANAs positivity and key clinical outcomes, including time to first treatment (TTFT), progression-free survival (PFS), and overall survival (OS). Additionally, the study explored whether ANAs could enhance the predictive accuracy of established prognostic models, such as the CLL-international prognostic index (CLL-IPI).
Methods
The study retrospectively analyzed data from 216 CLL patients diagnosed between 2007 and 2017 at the First Affiliated Hospital of Nanjing Medical University. All patients underwent ANAs testing at diagnosis, and those with ANA titers of ≥1:100 were considered positive. The study also collected data on other prognostic factors, including TP53 disruption, immunoglobulin heavy chain variable region (IGHV) mutational status, and cytogenetic abnormalities. Survival outcomes were assessed using Kaplan-Meier curves, and multivariate Cox regression analyses were performed to identify independent prognostic factors. Receiver operator characteristic (ROC) curves and area under the curve (AUC) were used to evaluate the predictive accuracy of ANAs in combination with other factors.
Results
Incidence and Clinical Characteristics of ANAs Positivity
Among the 216 CLL patients, 30 (13.9%) tested positive for ANAs at diagnosis. This incidence is significantly higher than that reported in the general population (5.6%–8.5%). The study found that ANAs positivity was associated with higher levels of beta-2 microglobulin (b2-MG) and CD38 expression, but not with other clinical or biological characteristics such as age, gender, Binet stage, or TP53 mutational status. Notably, only 5 of the 12 patients with concomitant autoimmune diseases tested positive for ANAs, suggesting that ANAs positivity in CLL may be more closely related to the malignancy itself rather than to coexisting autoimmune conditions.
Prognostic Impact of ANAs
The study revealed that ANAs positivity was significantly associated with shorter TTFT and OS. The median TTFT for ANAs-positive patients was 13 months, compared to 40 months for ANAs-negative patients (P=0.049). Similarly, the median OS for ANAs-positive patients was 54 months, while it was not reached for ANAs-negative patients (P=0.017). However, ANAs status did not significantly impact PFS (56 months vs. 75 months, P=0.988).
Multivariate Cox regression analyses identified ANAs positivity and TP53 disruption as independent prognostic factors for OS. The hazard ratio (HR) for ANAs positivity was 2.237 (95% confidence interval [CI]: 1.058–4.729, P=0.035), indicating a significant adverse effect on survival. The study also found that combining ANAs positivity with TP53 disruption improved the predictive accuracy for OS, with an AUC of 0.766 (95% CI: 0.697–0.826), compared to 0.706 for TP53 disruption alone (P=0.034) and 0.595 for ANAs positivity alone (P<0.001).
Integration of ANAs into Prognostic Models
The study further explored the potential of ANAs to enhance the CLL-IPI, a widely used prognostic index that incorporates TP53 status, IGHV mutational status, b2-MG levels, clinical stage, and age. By adding one point to the CLL-IPI score for ANAs positivity, the study developed a novel prognostic index (CLL-PI). The CLL-PI demonstrated improved risk stratification for OS, with more distinct differences in survival outcomes between risk groups. Although the difference in AUC between the CLL-PI and CLL-IPI was not statistically significant (0.781 vs. 0.769, P=0.431), the CLL-PI provided more granular risk stratification, particularly for high-risk patients.
Discussion
The findings of this study highlight the prognostic significance of ANAs in CLL, particularly in relation to OS. ANAs positivity was associated with shorter TTFT and OS, and it emerged as an independent prognostic factor alongside TP53 disruption. The study also demonstrated that combining ANAs positivity with TP53 disruption or the CLL-IPI could improve risk stratification and enhance the predictive accuracy of existing prognostic models.
The mechanisms underlying the association between ANAs and poor outcomes in CLL remain unclear. One possible explanation is that ANAs may interact with B-cell receptors (BCRs) on CLL cells, activating signaling pathways that promote cell proliferation and survival. This hypothesis is supported by evidence that BCR signaling plays a critical role in CLL pathogenesis, and that antigens binding to BCRs can drive disease progression. Additionally, the production of ANAs by CLL cells or normal B cells in response to immune dysregulation may contribute to the aggressive clinical behavior observed in ANAs-positive patients.
The study also raises important questions about the origins of ANAs in CLL. While some evidence suggests that ANAs may be produced by the neoplastic B cells themselves, other studies propose that they may arise from normal B cells in response to T-cell disturbances or inhibitory cytokines secreted by CLL cells. Further research is needed to elucidate the precise mechanisms by which ANAs contribute to disease progression and poor outcomes in CLL.
Limitations and Future Directions
This study has several limitations, including its retrospective design, relatively small sample size, and insufficient follow-up duration. Additionally, the study did not assess dynamic changes in ANAs titers over time, particularly in patients with disease progression or relapse. Future studies should address these limitations by conducting prospective, longitudinal investigations with larger cohorts and longer follow-up periods. Such studies could provide further insights into the role of ANAs in CLL and validate their utility as a prognostic marker.
Conclusion
In conclusion, this study provides compelling evidence that ANAs positivity is an independent prognostic factor for OS in CLL. The findings suggest that ANAs could be a valuable addition to existing prognostic models, offering a simple and easily measurable parameter for risk stratification. While further research is needed to confirm these findings and explore the underlying mechanisms, the study underscores the importance of considering autoimmune phenomena in the management of CLL. By integrating ANAs into clinical practice, clinicians may be better equipped to predict outcomes and tailor treatment strategies for individual patients.
doi.org/10.1097/CM9.0000000000000114
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