hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine

The mutational profile of immune surveillance genes in diagnostic and refractory/relapsed DLBCLs

Background

Diffuse large B-cell lymphoma (DLBCL) is the most frequent lymphoid neoplasm among adults,and approximately 30–40% of patients will experience relapse while 5–10% will suffer from primary refractory disease caused by different mechanisms, including treatment-induced resistance. For refractory and relapsed DLBCL (rrDLBCL) patients, early detection and understanding of the mechanisms controlling treatment resistance are of great importance to guide therapy decisions. Here, we have focused on genetic variations in immune surveillance genes in diagnostic DLBCL (dDLBCL) and rrDLBCL patients to elaborate on the suitability of new promising immunotherapies.

Methods

Biopsies from 30 dDLBCL patients who did not progress or relapse during follow up and 17 rrDLBCL patients with refractory disease or who relapsed during follow up were analyzed by whole-exome sequencing, including matched individual germline samples to include only somatic genetic variants in downstream analysis of a curated list of 58 genes involved in major immune surveillance pathways.

Results

More than 70% of both dDLBCLs and rrDLBCLs harbored alterations in immune surveillance genes, but rrDLBCL tumor samples have a lower number of genes affected compared to dDLBCL tumor samples. Increased gene mutation frequencies in rrDLBCLs were observed in more than half of the affected immune surveillance genes than dDLBCLs.

Conclusion

Genetic variants in the antigen-presenting genes affect a higher number of rrDLBCL patients supporting an important role for these genes in tumor progression and development of refractory disease and relapse.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08556-3.

MicroRNAs associated to single drug components of R-CHOP identifies diffuse large B-cell lymphoma patients with poor outcome and adds prognostic value to the international prognostic index

Background

Treatment resistance is a major clinical challenge of diffuse large B-cell lymphoma (DLBCL) where approximately 40% of the patients have refractory disease or relapse. Since DLBCL is characterized by great clinical and molecular heterogeneity, the purpose of the present study was to investigate whether miRNAs associated to single drug components of R-CHOP can improve robustness of individual markers and serve as a prognostic classifier.

Methods

Fifteen DLBCL cell lines were tested for sensitivity towards single drug compounds of the standard treatment R-CHOP: rituximab (R), cyclophosphamide (C), doxorubicin (H), and vincristine (O). For each drug, cell lines were ranked using the area under the dose-response curve and grouped as either sensitive, intermediate or resistant. Baseline miRNA expression data were obtained for each cell line in untreated condition, and differential miRNA expression analysis between sensitive and resistant cell lines identified 43 miRNAs associated to growth response after exposure towards single drugs of R-CHOP. Using the Affymetrix HG-U133 platform, expression levels of miRNA precursors were assessed in 701 diagnostic DLBCL biopsies, and miRNA-panel classifiers predicting disease progression were build using multiple Cox regression or random survival forest. Classifiers were validated and ranked by repeated cross-validation.

Results

Prognostic accuracies were assessed by Brier Scores and time-varying area under the ROC curves, which revealed better performance of multivariate Cox models compared to random survival forest models. The Cox model including miR-146a, miR-155, miR-21, miR-34a, and miR-23a~miR-27a~miR-24-2 cluster performed the best and successfully stratified GCB-DLBCL patients into high- and low-risk of disease progression. In addition, combination of the Cox miRNA-panel and IPI substantially increased prognostic performance in GCB classified patients.

Conclusion

As a proof of concept, we found that expression data of drug associated miRNAs display prognostic utility and adding these to IPI improves prognostic stratification of GCB-DLBCL patients treated with R-CHOP.

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM.

A B-cell-associated gene signature classification of diffuse large B-cell lymphoma by NanoString technology

Gene expression profiling (GEP) by microarrays of diffuse large B-cell lymphoma (DLBCL) has enabled the categorization of DLBCL into activated B-cell-like and germinal center B-cell-like subclasses. However, as this does not fully embrace the great diversity of B-cell subtypes, we recently developed a gene expression assay for B-cell-associated gene signature (BAGS) classification. To facilitate quick and easy-to-use BAGS profiling, we developed in this study the NanoString-based BAGS2Clinic assay. Microarray data from 4 different cohorts (n = 970) were used to select genes and train the assay. The locked assay was validated in an independent cohort of 88 sample biopsies. The assay showed good correspondence with the original BAGS classifier, with an overall accuracy of 84% (95% confidence interval, 72% to 93%) and a subtype-specific accuracy ranging between 80% and 99%. BAGS classification has the potential to provide valuable insight into tumor biology as well as differences in resistance to immuno- and chemotherapy that can lead to novel treatment strategies for DLBCL patients. BAGS2Clinic can facilitate this and the implementation of BAGS classification as a routine clinical tool to improve prognosis and treatment guidance for DLBCL patients.

Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow - A proof of concept study

Diagnostic and prognostic evaluation of chronic lymphocytic leukemia (CLL) involves blood cell counts, immunophenotyping, IgVH mutation status, and cytogenetic analyses. We generated B-cell associated gene-signatures (BAGS) based on six naturally occurring B-cell subsets within normal bone marrow. Our hypothesis is that by segregating CLL according to BAGS, we can identify subtypes with prognostic implications in support of pathogenetic value of BAGS. Microarray-based gene-expression samples from eight independent CLL cohorts (1,024 untreated patients) were BAGS-stratified into pre-BI, pre-BII, immature, naïve, memory, or plasma cell subtypes; the majority falling within the memory (24.5-45.8%) or naïve (14.5-32.3%) categories. For a subset of CLL patients (n = 296), time to treatment (TTT) was shorter amongst early differentiation subtypes (pre-BI/pre-BII/immature) compared to late subtypes (memory/plasma cell, HR: 0.53 [0.35-0.78]). Particularly, pre-BII subtype patients had the shortest TTT among all subtypes. Correlates derived for BAGS subtype and IgVH mutation (n = 405) revealed an elevated mutation frequency in late vs. early subtypes (71% vs. 45%, P < .001). Predictions for BAGS subtype resistance towards rituximab and cyclophosphamide varied for rituximab, whereas all subtypes were sensitive to cyclophosphamide. This study supports our hypothesis that BAGS-subtyping may be of tangible prognostic and pathogenetic value for CLL patients.

Molecular classification of tissue from a transformed non-Hogkin's lymphoma case with unexpected long-time remission

BACKGROUND

The concept of precision medicine in cancer includes individual molecular studies to predict clinical outcomes. In the present N = 1 case we retrospectively have analysed lymphoma tissue by exome sequencing and global gene expression in a patient with unexpected long-term remission following relaps. The goals were to phenotype the diagnostic and relapsed lymphoma tissue and evaluate its pattern. Furthermore, to identify mutations available for targeted therapy and expression of genes to predict specific drug effects by resistance gene signatures (REGS) for R-CHOP as described at http://www.hemaclass.org. We expected that such a study could generate therapeutic information and a frame for future individual evaluation of molecular resistance detected at clinical relapse.

CASE PRESENTATION

The patient was diagnosed with a transformed high-grade non-Hodgkin lymphoma stage III and treated with conventional R-CHOP [rituximab (R), cyclophosphamide (C), doxorubicin (H), vincristine (O) and prednisone (P)]. Unfortunately, she suffered from severe toxicity but recovered during the following 6 months' remission until biopsy-verified relapse. The patient refused second-line combination chemotherapy, but accepted 3 months' palliation with R and chlorambucil. Unexpectedly, she obtained continuous complete remission and is at present >9 years after primary diagnosis. Molecular studies and data evaluation by principal component analysis, mutation screening and copy number variations of the primary and relapsed tumor, identified a pattern of branched lymphoma evolution, most likely diverging from an in situ follicular lymphoma. Accordingly, the primary diagnosed transformed lymphoma was classified as a diffuse large B cell lymphoma (DLBCL) of the GCB/centrocytic subtype by "cell of origin BAGS" assignment and R sensitive and C, H, O and P resistant by "drug specific REGS" assignment. The relapsed DLBCL was classified as NC/memory subtype and R, C, H sensitive but O and P resistant.

CONCLUSIONS

Thorough analysis of the tumor DNA and RNA documented a branched evolution of the two clinical diagnosed tFL, most likely transformed from an unknown in situ lymphoma. Classification of the malignant tissue for drug-specific resistance did not explain the unexpected long-term remission and potential cure. However, it is tempting to consider the anti-CD20 immunotherapy as the curative intervention in the two independent tumors of this case.