Baseline VDJ clonotype detection using a targeted sequencing NGS assay: allowing for subsequent MRD assessment

Tissue-Matched IgH Gene Rearrangement of Circulating Tumor DNA Shows Significant Value in Predicting the Progression of Diffuse Large B Cell Lymphoma

BACKGROUND

Evidence has demonstrated that monitoring of the variable, diversity, and joining gene segments (VDJ) rearrangement of the immunoglobulin (Ig) genes in the circulating tumor DNA (ctDNA) is of value in predicting the outcomes of diffuse large B cell lymphoma (DLBCL). In this study, we investigated the role of VDJ rearrangement proportion in ctDNA for predicting DLBCL progression.

METHODS

Patients diagnosed with newly diagnosed DLBCL were included in this study. The VDJ sequences of IgH were detected using next-generation sequencing (NGS) in formalin-fixed paraffin-embedded tissue and/or peripheral blood. The clonotype of the highest proportion in the peripheral blood was defined as the "dominant circulating clonotype," whilst the clonotype of the highest proportion in matched tissue that is detected in peripheral blood was defined as the "dominant tissue-matched clonotype." The decision tree, a machine learning-based methodology, was used to establish a progression-predicting model through a combination of "dominant tissue-matched clonotype" proportion or "dominant circulating clonotype" proportion, and the clinicopathological information, including age, sex, cell of origin, stage, international prognostic index, lactate dehydrogenase, number of extranodal involvements and β2-microglobulin.

RESULTS

A total of 55 patients with eligible sequencing data were used for prognosis analysis, among which 36 patients had matched tissue samples. The concordance rate of "dominant circulating clonotype" and "dominant tissue-matched clonotype" was 19.44% (7/36). The decision tree model showed that the combination of extranodal involvement event and "dominant circulating clonotype" proportion (≥37%) had a clinical value in predicting the prognosis of DLBCL following combined chemotherapy (sensitivity, 0.63; specificity, 0.81; positive prediction value (PPV), 0.59; negative prediction value, 0.83; kappa value, 0.42). Noticeably, the combination of the "dominant tissue-matched clonotype" and extranodal involvement event showed a higher value in predicting the progression (sensitivity, 0.85; specificity, 0.78; PPV, 0.69; kappa value, 0.64).

CONCLUSION

IgH proportion detected in the ctDNA samples traced from tissue samples has a high clinical value in predicting the progression of DLBCL.

Liquid biopsy-based monitoring of residual disease in multiple myeloma by analysis of the rearranged immunoglobulin genes-A feasibility study

The need for sensitive monitoring of minimal/measurable residual disease (MRD) in multiple myeloma emerged as novel therapies led to deeper responses. Moreover, the potential benefits of blood-based analyses, the so-called liquid biopsy is prompting more and more studies to assess its feasibility. Considering these recent demands, we aimed to optimize a highly sensitive molecular system based on the rearranged immunoglobulin (Ig) genes to monitor MRD from peripheral blood. We analyzed a small group of myeloma patients with the high-risk t(4;14) translocation, using next-generation sequencing of Ig genes and droplet digital PCR of patient-specific Ig heavy chain (IgH) sequences. Moreover, well established monitoring methods such as multiparametric flow cytometry and RT-qPCR of the fusion transcript IgH::MMSET (IgH and multiple myeloma SET domain-containing protein) were utilized to evaluate the feasibility of these novel molecular tools. Serum measurements of M-protein and free light chains together with the clinical assessment by the treating physician served as routine clinical data. We found significant correlation between our molecular data and clinical parameters, using Spearman correlations. While the comparisons of the Ig-based methods and the other monitoring methods (flow cytometry, qPCR) were not statistically evaluable, we found common trends in their target detection. Regarding longitudinal disease monitoring, the applied methods yielded complementary information thus increasing the reliability of MRD evaluation. We also detected indications of early relapse before clinical signs, although this implication needs further verification in a larger patient cohort.

Single-Cell RNA Sequencing for the Detection of Clonotypic V(D)J Rearrangements in Multiple Myeloma

Multiple myeloma (MM) has a highly heterogeneous genetic background, which complicates its molecular tracking over time. Nevertheless, each MM patient's malignant plasma cells (PCs) share unique V(D)J rearranged sequences at immunoglobulin loci, which represent ideal disease biomarkers. Because the tumor-specific V(D)J sequence is highly expressed in bulk RNA in MM patients, we wondered whether it can be identified by single-cell RNA sequencing (scRNA-seq). To this end we analyzed CD138⁺ cells purified from bone marrow aspirates of 19 samples with PC dyscrasias by both a standard method based on bulk DNA and by an implementation of the standard 10x Genomics protocol to detect expressed V(D)J sequences. A dominant clonotype was easily identified in each sample, accounting on average for 83.65% of V(D)J-rearranged cells. Compared with standard methods, scRNA-seq analysis proved highly concordant and even more effective in identifying clonal productive rearrangements, by-passing limitations related to the misannealing of consensus primers in hypermutated regions. We next validated its accuracy to track 5 clonal cells with absolute sensitivity in a virtual sample containing 3180 polyclonal cells. This shows that single-cell V(D)J analysis may be used to find rare clonal cells, laying the foundations for functional single-cell dissection of minimal residual disease.

Perspectives on the Risk-Stratified Treatment of Multiple Myeloma

The multiple myeloma treatment landscape has changed dramatically. This change, paralleled by an increase in scientific knowledge, has resulted in significant improvement in survival. However, heterogeneity remains in clinical outcomes, with a proportion of patients not benefiting from current approaches and continuing to have a poor prognosis. A significant proportion of the variability in outcome can be predicted on the basis of clinical and biochemical parameters and tumor-acquired genetic variants, allowing for risk stratification and a more personalized approach to therapy. This article discusses the principles that can enable the rational and effective development of therapeutic approaches for high-risk multiple myeloma.

Capture Rate of V(D)J Sequencing for Minimal Residual Disease Detection in Multiple Myeloma

PURPOSE

Minimal residual disease (MRD) negativity is a strong predictor for outcome in multiple myeloma. To assess V(D)J clonotype capture using the updated Adaptive next-generation sequencing (NGS) MRD assay in a clinical setting, we analyzed baseline and follow-up samples from patients with multiple myeloma who achieved deep clinical responses.

EXPERIMENTAL DESIGN

A total of 159 baseline and 31 follow-up samples from patients with multiple myeloma were sequenced using the NGS MRD assay. Baseline samples were also sequenced using a targeted multiple myeloma panel (myTYPE). We estimated ORs with 95% confidence intervals (CI) for clonotypes detection using logistic regression.

RESULTS

The V(D)J clonotype capture rate was 93% in baseline samples with detectable genomic aberrations, indicating presence of tumor DNA, assessed through myTYPE. myTYPE-positive samples had significantly higher V(D)J clonotype detection rates in univariate (OR, 7.3; 95% CI, 2.8-22.6) and multivariate analysis (OR, 4.4; 95% CI, 1.4-16.9; P = 0.016). Higher disease burden was associated with higher probability of V(D)J clonotype capture, meanwhile no such association was found for age, gender, or type of heavy or light immunoglobulin chain. All V(D)J clonotypes detected at baseline were detected in MRD-positive samples indicating that the V(D)J clonotypes remained stable and did not undergo further rearrangements during follow-up. Of the 31 posttreatment samples, 12 were MRD-negative using the NGS MRD assay.

CONCLUSIONS

NGS for V(D)J rearrangements in multiple myeloma offers a reliable and sensitive method for MRD tracking with high detection rates in the clinical setting.

Single-cell RNA-seq reveals clonal diversity and prognostic genes of relapsed multiple myeloma

BACKGROUND

Multiple myeloma (MM) is a clinically and biologically heterogeneous plasma-cell malignancy. Despite extensive research, disease heterogeneity and relapse remain a big challenge in MM therapeutics. We tried to dissect this disease and identify novel biomarkers for patient stratification and treatment outcome prediction by applying single-cell technology.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) and variable-diversity-joining regions-targeted sequencing (scVDJ-seq) concurrently on bone marrow samples from a cohort of 18 patients with newly diagnosed MM (NDMM; n = 12) or refractory/relapsed MM (RRMM; n = 6). We analysed the malignant clonotypes using scVDJ-seq data and conducted data integration and cell-type annotation through the CCA algorithm based on gene expression profiling. Furthermore, we identified disease status-specific genes and modules by comparison of NDMM and RRMM datasets and explored the findings in a larger MM cohort from the MMRF CoMMpass study.

RESULTS

We found that all the myeloma cells in either diagnosed or relapsed samples were dominated by a major clone, with a few subclones in several samples (n = 5). Next, we investigated the universal transcriptional features of myeloma cells and identified eight meta-programs correlated with this disease, especially meta-programs 1 and 8 (M1 and M8), which were the most significant and related to cell cycle and stress response, respectively. Furthermore, we classified the malignant plasma cells into eight clusters and found that the cell numbers in clusters 2/6/7 were exclusively higher in relapsed samples. Besides, we identified several attractive candidates for biomarkers (e.g. SMAD1 and STMN1) associated with disease progression and relapse in our dataset and related to overall survival in the CoMMpass dataset.

CONCLUSIONS

Our data provide insights into the heterogeneity of MM as well as highlight the relevance of intra-tumour heterogeneity and discover novel biomarkers that might be a potent therapy.

Clonotypic Features of Rearranged Immunoglobulin Genes Yield Personalized Biomarkers for Minimal Residual Disease Monitoring in Multiple Myeloma

BACKGROUND

Due to improved treatment, more patients with multiple myeloma (MM) reach a state of minimal residual disease (MRD). Different strategies for MM MRD monitoring include flow cytometry, allele-specific oligonucleotide-quantitative PCR, next-generation sequencing, and mass spectrometry (MS). The last 3 methods rely on the presence and the stability of a unique immunoglobulin fingerprint derived from the clonal plasma cell population. For MS-MRD monitoring it is imperative that MS-compatible clonotypic M-protein peptides are identified. To support implementation of molecular MRD techniques, we studied the presence and stability of these clonotypic features in the CoMMpass database.

METHODS

An analysis pipeline based on MiXCR and HIGH-VQUEST was constructed to identify clonal molecular fingerprints and their clonotypic peptides based on transcriptomic datasets. To determine the stability of the clonal fingerprints, we compared the clonal fingerprints during disease progression for each patient.

RESULTS

The analysis pipeline to establish the clonal fingerprint and MS-suitable clonotypic peptides was successfully validated in MM cell lines. In a cohort of 609 patients with MM, we demonstrated that the most abundant clone harbored a unique clonal molecular fingerprint and that multiple unique clonotypic peptides compatible with MS measurements could be identified for all patients. Furthermore, the clonal immunoglobulin gene fingerprints of both the light and heavy chain remained stable during MM disease progression.

CONCLUSIONS

Our data support the use of the clonal immunoglobulin gene fingerprints in patients with MM as a suitable MRD target for MS-MRD analyses.