Elevated C-reactive protein level is associated with poor prognosis in follicular lymphoma patients undergoing rituximab-containing chemotherapy

C-Reactive Protein: Pathophysiology, Diagnosis, False Test Results and a Novel Diagnostic Algorithm for Clinicians

The current literature provides a body of evidence on C-Reactive Protein (CRP) and its potential role in inflammation. However, most pieces of evidence are sparse and controversial. This critical state-of-the-art monography provides all the crucial data on the potential biochemical properties of the protein, along with further evidence on its potential pathobiology, both for its pentameric and monomeric forms, including information for its ligands as well as the possible function of autoantibodies against the protein. Furthermore, the current evidence on its potential utility as a biomarker of various diseases is presented, of all cardiovascular, respiratory, hepatobiliary, gastrointestinal, pancreatic, renal, gynecological, andrological, dental, oral, otorhinolaryngological, ophthalmological, dermatological, musculoskeletal, neurological, mental, splenic, thyroid conditions, as well as infections, autoimmune-supposed conditions and neoplasms, including other possible factors that have been linked with elevated concentrations of that protein. Moreover, data on molecular diagnostics on CRP are discussed, and possible etiologies of false test results are highlighted. Additionally, this review evaluates all current pieces of evidence on CRP and systemic inflammation, and highlights future goals. Finally, a novel diagnostic algorithm to carefully assess the CRP level for a precise diagnosis of a medical condition is illustrated.

Proteomics Identifies Circulating TIMP-1 as a Prognostic Biomarker for Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, although disease stratification using in-depth plasma proteomics has not been performed to date. By measuring more than 1000 proteins in the plasma of 147 DLBCL patients using data-independent acquisition mass spectrometry and antibody array, DLBCL patients were classified into four proteomic subtypes (PS-I-IV). Patients with the PS-IV subtype and worst prognosis had increased levels of proteins involved in inflammation, including a high expression of metalloproteinase inhibitor-1 (TIMP-1) that was associated with poor survival across two validation cohorts (n = 180). Notably, the combination of TIMP-1 with the international prognostic index (IPI) identified 64.00% to 88.24% of relapsed and 65.00% to 80.49% of deceased patients in the discovery and two validation cohorts, which represents a 24.00% to 41.67% and 20.00% to 31.70% improvement compared to the IPI score alone, respectively. Taken together, we demonstrate that DLBCL heterogeneity is reflected in the plasma proteome and that TIMP-1, together with the IPI, could improve the prognostic stratification of patients.

Impact of serum C-reactive protein level as a biomarker of cancer dissemination in canine lymphoid neoplasia

Background and Aim

C-reactive protein (CRP) is a highly sensitive but non-specific acute phase protein that has been widely used to predict the biological behavior of patients with cancer. This study aimed to examine the significance of the serum CRP biomarker in predicting the prognosis of dogs with lymphoma.

Materials and Methods

Blood samples (5 mL) were collected from 34 lymphoma dogs and control healthy dogs. Canine lymphoma clinical staging was classified using the World Health Organization (WHO) criteria. All lymphoma dogs were reclassified into two groups based on the disease stage. Stages IV and V were designated as advanced stages, and Stages I-III were designated as other stages. The serum CRP level was then determined using a commercial canine CRP fluorescent immunoassay kit and routine hematological and biochemical analyses. C-reactive protein levels, circulating inflammatory parameters, such as neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and platelet-to-lymphocyte ratio, and albumin levels were compared between advanced stages (IV and V) and Stages I to III using Mann-Whitney U tests. Receiver operating characteristic (ROC) curves were also generated to determine the cutoff value, diagnostic sensitivity, and specificity of the CRP level.

Results

A prospective study identified 34 dogs recently diagnosed with canine lymphoma. C-reactive protein levels were significantly higher in lymphoma dogs in advanced stages (IV and V) than in lymphoma dogs in Stages I-III. According to the ROC curve analysis, a CRP cutoff level of 54.1 mg/L indicates advanced-stage canine lymphoma, which can be used as a biomarker to predict cancer dissemination.

Conclusion

Serum CRP concentrations can assist clinical decision-making on the WHO stage in lymphoma dogs in clinical applications. The limitations of this study include a small number of lymphomas and no survival analysis.

Artificial Neural Network Analysis of Gene Expression Data Predicted Non-Hodgkin Lymphoma Subtypes with High Accuracy

Predictive analytics using artificial intelligence is a useful tool in cancer research. A multilayer perceptron neural network used gene expression data to predict the lymphoma subtypes of 290 cases of non-Hodgkin lymphoma (GSE132929). The input layer included both the whole array of 20,863 genes and a cancer transcriptome panel of 1769 genes. The output layer was lymphoma subtypes, including follicular lymphoma, mantle cell lymphoma, diffuse large B-cell lymphoma, Burkitt lymphoma, and marginal zone lymphoma. The neural networks successfully classified the cases consistent with the lymphoma subtypes, with an area under the curve (AUC) that ranged from 0.87 to 0.99. The most relevant predictive genes were LCE2B, KNG1, IGHV7_81, TG, C6, FGB, ZNF750, CTSV, INGX, and COL4A6 for the whole set; and ARG1, MAGEA3, AKT2, IL1B, S100A7A, CLEC5A, WIF1, TREM1, DEFB1, and GAGE1 for the cancer panel. The characteristic predictive genes for each lymphoma subtypes were also identified with high accuracy (AUC = 0.95, incorrect predictions = 6.2%). Finally, the topmost relevant 30 genes of the whole set, which belonged to apoptosis, cell proliferation, metabolism, and antigen presentation pathways, not only predicted the lymphoma subtypes but also the overall survival of diffuse large B-cell lymphoma (series GSE10846, n = 414 cases), and most relevant cancer subtypes of The Cancer Genome Atlas (TCGA) consortium including carcinomas of breast, colorectal, lung, prostate, and gastric, melanoma, etc. (7441 cases). In conclusion, neural networks predicted the non-Hodgkin lymphoma subtypes with high accuracy, and the highlighted genes also predicted the survival of a pan-cancer series.

Significance of initial, interim and end-of-therapy 18F-FDG PET/CT for predicting transformation risk in follicular lymphoma

Background

Histological transformation (HT) of follicular lymphoma to a more aggressive lymphoma is a serious event affecting patients’ outcomes. To date, no strong clinical HT predictors present at diagnosis have yet been identified. The fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) is highlighted as a non-invasive diagnostic tool for the detection of HT, but its ability to predict HT at early stage of disease has not been clear. Therefore, this study investigated the predictive values of the pre-transformation standardized uptake value (SUV_max) for the risk of transformation in FL.

Methods

This retrospective study involved 219 patients with FL between June 2008 and October 2019 who had undergone ¹⁸F-FDG PET/CT scan. One hundred and thirty-two, 64, and 78 patients underwent PET at baseline (PET_baseline), interim (PET_interim) and end-of-induction therapy (PET_end), respectively. Qualitative assessment was performed using the 5-point Deauville scale. Statistical analysis was done using Cox regression models, receiver operating characteristic (ROC) analysis, and Kaplan–Meir survival curves.

Results

Of the 219 patients included, 128 had low-grade FL (grade 1–2) and 91 had high-grade FL (grade 3a). HT eventually occurred in 30 patients. The median time to HT was 13.6 months. Among clinical indicators, advance pathological grade was shown as the most significant predictor of HT (HR = 4.561, 95% CI 1.604–12.965). We further assessed the relationship between PET and HT risk in FL. Univariate Cox regression determined that SUV_baseline and SUV_end were significant predictors for HT, while neither SUV_interim nor qualitative assessment of Deauville score has predictive value for HT. Due to the noticeable impact of high pathological grade on the HT risk, we conducted the subgroup analysis in patients with low/high pathological grade, and found SUV_baseline could still predict HT risk in both low-grade and high-grade subgroups. Multivariate analysis adjusted by FLIPI2 score showed the SUV_baseline (HR 1.065, 95% CI 1.020–1.111) and SUV_end (HR 1.261, 95% CI 1.076–1.478) remained as significant predictors independently of the FLIPI2 score. According to the cut-off determined from the ROC analysis, increased SUV_baseline with a cutoff value of 14.3 and higher SUV_end with a cutoff value of 7.3 were highly predictive of a shorter time to HT.

Conclusions

In follicular lymphoma, quantitative assessment used SUV_max at the pre-treatment and end-of-treatment PET/CT scan may be helpful for early screen out patients at high risk of transformation and guide treatment decisions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02094-5.