Serum Spectroscopy Reveals Prognostic Risk Factors in CLL

An innovative application of micro-Raman spectroscopy integrated with multivariate statistical analysis could be used for prognosis in patients with chronic lymphocytic leukemia (CLL).¹ The approach successfully discriminated between favorable and unfavorable prognostic groups, revealing biochemical heterogeneity beyond conventional molecular classifications. The findings, published in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, highlight the potential of this rapid, label-free, and non-invasive method for detecting metabolic alterations associated with disease progression and outcomes.

CLL is the most common adult leukemia, primarily affecting individuals older than 65 years, with an estimated annual incidence of 5 per 100,000 people. Prognosis depends largely on molecular markers such as IGHV mutation status and TP53 aberrations, which together inform the CLL International Prognostic Index (CLL-IPI). Yet, these genomic assays can be expensive, technically complex, and invasive.²

To address this need, investigators analyzed dried serum samples from 22 untreated patients with CLL (median age, 69.2 years) and 7 age- and sex-matched healthy controls.¹ Patients were stratified into a favorable group (mutated IGHV and/or wild-type TP53; n = 15) and an unfavorable group (unmutated IGHV and/or TP53 aberrations; n = 7). All samples were therapy-naïve and free of TP53 mutations or 17p deletions.

Raman spectroscopy provides a biochemical fingerprint of blood serum, capturing vibrational modes of biomolecules relevant to malignancy. This approach, when combined with statistical tools such as Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), examines the distinct molecular signatures corresponding to CLL prognosis, revealing differences unappreciable by conventional morphology or immunophenotyping.

Distinct spectral variations were observed at 1652 cm⁻¹ (amide I, protein backbone), 1205 cm⁻¹ (tryptophan), 1344 cm⁻¹ (collagen/lipid), and 1003 cm⁻¹ (phenylalanine), reflecting differences in protein secondary structure, amino acid composition, and collagen-associated metabolism that strongly correlate with disease progression. These biochemical alterations were more pronounced between CLL patients and healthy controls, as well as between the favorable and unfavorable prognosis groups.

Interestingly, PCA identified 2 distinct subclusters within the favorable group. Two distinctly clustered subgroups (termed "favorable 1" and "favorable 2") emerged, with favorable 1 closely resembling the healthy control spectra, while favorable 2 paralleled the unfavorable group, suggesting that conventional molecular criteria for a “good” prognosis may conceal additional risk stratification.

The initial three-class PLS-DA model (healthy, favorable, unfavorable) achieved an overall accuracy of 37.9%. Sensitivity was 28.6% for healthy controls, 53.3% for favorable cases, and 14.3% for unfavorable cases, with a specificity of 81.8%, 28.6%, and 81.8%, respectively. When the model was expanded to a four-class system, including the 2 favorable subgroups, classification accuracy improved to 41.4%. Sensitivity increased to 42.9% for controls, 42.9% for favorable 1, 50.0% for favorable 2, and 28.6% for unfavorable cases. Specificity rose to 90.9%, 86.4%, 66.7%, and 77.3%, respectively.

The study found that a lower serum collagen signature (as indicated by the ratio of 1003/1344 cm⁻¹ peaks) was associated with the unfavorable group and with favorable group 2, in contrast to the controls and favorable group 1, suggesting that serum collagen loss correlates with disease progression. This observation aligns with previous findings linking a reduction in serum collagen to increased bone marrow fibrosis and shorter survival in high-risk CLL.³ 

“The results, presented and discussed in this paper, indicate that the Raman spectroscopy technique represents a promising approach to analyze dried serum from CLL patients and providing insights into the biochemical alterations associated with the disease,” the authors wrote,¹ emphasizing its potential role in real-time monitoring and prognostic refinement. Although preliminary, this approach could augment conventional CLL prognostication with a rapid, cost-effective, and minimally invasive assay.

References

1. Fazio E, Corsaro C, Speciale A, et al. Biochemical fingerprinting of dried blood serum from chronic lymphocytic leukemia patients by Raman spectroscopy: Towards prognostic classification. Spectrochim Acta A Mol Biomol Spectrosc. Published September 26, 2025. doi:10.1016/j.saa.2025.126961.

2. Hallek M. Chronic lymphocytic leukemia: 2025 update on the epidemiology, pathogenesis, diagnosis, and therapy. Am J Hematol. 2025;100(3):450-480. doi:10.1002/ajh.27546

3. Bai Y, Yu Z, Yi S, Yan Y, Huang Z, Qiu L. Raman spectroscopy-based biomarker screening by studying the fingerprint characteristics of chronic lymphocytic leukemia and diffuse large B-cell lymphoma. J Pharm Biomed Anal. 2020;190:113514. doi:10.1016/j.jpba.2020.113514