Anti-Infectious Pathogen Specificity of Purified Monoclonal Immunoglobulins from Patients with MGUS and Multiple Myeloma
Bibliographic record
Abstract
Abstract Background: Multiple myeloma (MM) is characterized by the accumulation of malignant plasma cells, which secrete >30g/L of monoclonal immunoglobulin (mc Ig). MM is always preceded by the usually asymptomatic stage called "monoclonal gammapathy of undetermined significance" (MGUS). Presently the detection of a mc Ig does not lead to analysis of its specificity of antigen (Ag) recognition. Yet certain infectious pathogens are associated with the development of B-cell malignancy: for instance, Epstein-Barr virus (EBV) and Burkitt lymphoma, Helicobacter pylori (H. pylori) and MALT lymphoma. Objective: Our aim was to determine the frequency of recognition by purified mc Ig from MGUS and MM patients, of infectious pathogens associated with chronic infection and B-cell malignancy. Methods: We used the "Multiplex Infectious Antigen Array" (MIAA)test set up by the team to study the specificity of purified mc IgG against 8 infectious pathogens: hepatitis C virus (HCV), EBV, H. pylori, varicella zoster virus (VZV), cytomegalovirus (CMV), herpesvirus simplex 1 (HSV-1), HSV-2, and Toxoplasma gondii. Second or third methods were used to verify the specificity of mc IgG (western blotting, ELISA, or another multiplex array). Sialylation of mc Ig, which reflects chronic inflammation, was also studied, via ELISAs and Western blotting, for 98 MGUS and MM patients and 43 controls. Results: The specificity of purified mc IgG was analyzed for 291 patients (60 MGUS, including 4 associated with a B-cell lymphoma; 108 MM; for the 123 other patients the diagnosis of MGUS or MM was not available). Purified mc IgG were found to be specific for one of the 8 infectious pathogens of the MIAA test for 17.5% of patients (51/291: 25 MGUS, 1 SMM, and 25 MM). Purified mc Ig specifically recognized EBV (n=27, including 8 MGUS, 1 SMM and 18 MM ; the Ag recognized were EBNA-1, 25 cases; and VCA, 2 cases); HCV (10 cases: 9 MGUS and 1 MM) ; HSV-1 (7 cases: 5 MGUS including 3 associated with a B-cell malignancy, and 2 MM) ; H. pylori (5 cases: 2 MGUS including 1 associated with a B-cell malignancy, and 3 MM); VZV (1 MM); and CMV (1 MGUS). The Ag most frequently recognized by purified mc IgG was EBV EBNA-1; MM patients with EBNA-1-specific mc IgG represented 10% of the MM in this series. Consistent with a pro-inflammatory effect, for 81.6% of MGUS and MM patients (80/98), the purified mc IgG was found to be hyposialylated. Moreover, purified polyclonal Ig were also hyposialylated for 37% of MM (compared to <2.3% of the polyclonal Ig from healthy donors or MGUS). Conclusion: At least 6 infectious pathogens (EBV, HCV, H. pylori, HSV, VZV, CMV) may be involved in the pathogenesis of MGUS and MM with mc IgG. Importantly, EBV, HCV, H. pylori and HSV are known as oncogenic pathogens associated with solid cancer and/or B-cell malignancy. Finally, for 37% of the MM patients examined, both the polyclonal and mc Ig were found to be hyposialylated, which suggests that inflammation existed prior to clonality and MM. Disclosures Garderet: Takeda: Consultancy; Amgen: Consultancy; BMS: Consultancy, Honoraria; Novartis: Consultancy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".