Abstract 2293: Evaluation of multiple myeloma research samples by analysis of B cell heavy and light chain receptors in a single NGS assay
Bibliographic record
Abstract
Abstract Introduction: B cell repertoire analysis by next-generation sequencing (NGS) is at the forefront of leukemia and lymphoma research. Some advantages provided by NGS-based techniques include a lower limit-of-detection and simpler paths to standardization compared to other methods. Importantly, in research of post-germinal B cell disorders, such as multiple myeloma (MM), NGS methods allow for the study of clonal lineage based on somatic hypermuation patterns. Current targeted NGS assays require multiple libraries to survey each B cell receptor chain (IGH, IgK, IgL), and this fact is highlighted when initial clonality detection fails due to mutations under primer binding sites. Methods: A B cell pan-clonality panel (Oncomine™ BCR Pan-Clonality Assay) targets the framework 3 (FR3) portion of the variable gene and the joining gene region of heavy- and light-chain loci (IGH, IgK, IgL) for all alleles found within the IMGT database, enabling readout of the complementary-determining region 3 (CDR3) sequence of each immunoglobulin chain. Primers are included to amplify rearrangements involving Kappa deletion element. Reproducibility studies and clonality assessment were conducted using gDNA from a total of 45 MM research samples. All MM cases examined in this work were confirmed clonal via flow cytometry or IHC/ISH in tissue sections. Sequencing and repertoire analyses were performed using the Ion GeneStudio S5 System and Ion Reporter 5.16 analysis software. Results: Clonality assessment of MM research samples show an 93% overall positive detection rate by an assay which combines the IGH, IgK, and IgL chains using published guidelines for clonality assignment. Thirty-four of 45 samples show positive detection of an IGH rearrangement, while 41 of 45 showed positive detection of at least one light chain receptor. Clonality results for this sample set are well correlated with orthogonal data from flow, IHC/ISH, or alternate NGS assays. A clonal lambda light chain was identified in 14 of 16 samples determined to be lambda restricted by flow cytometry. Estimates of somatic hypermutation rates were calculated using the BCR pan-clonality assay. Most MM samples contained somatic hypermutation with 6 of 45 samples showing mutation rates greater than 10%. Lineage analysis, based on somatic hypermuation signatures within each sample, identified 8 of 45 MM samples which contained 5 or more clones in the primary clonal lineage, with one case containing a lineage with 23 clones. Conclusions: These results demonstrate the utility of a novel assay for combined repertoire analysis of B cell receptor heavy and light chains in a single library preparation reaction. We expect this assay to simplify workflow and inclusion of analysis tools such as automated somatic hypermutation rate determination and clonal lineage identification to open new paths for research in B cell disorders. Citation Format: Geoffrey Marc Lowman, Landon Pastushok, Karen Mochoruk, Wayne Hill, Michelle Toro, Loni Pickle, Carolina Gonzalez, Stephanie Ostresh, Shrutii Sarda, Chenchen Yang, Julie Stakiw, Mark Bosch, Hadi Goubran, Ron Geyer, John DeCoteau. Evaluation of multiple myeloma research samples by analysis of B cell heavy and light chain receptors in a single NGS assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2293.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".