Precision diagnostics in lymphomas - Recent developments and future directions

Multisite clinical cross-validation and variant interpretation of a next generation sequencing panel for lymphoid cancer prognostication

AIMS

Genomic sequencing of lymphomas is under-represented in routine clinical testing despite having prognostic and predictive value. Clinical implementation is challenging due to a lack of consensus on reportable targets and a paucity of reference samples. We organised a cross-validation study of a lymphoma-tailored next-generation sequencing panel between two College of American Pathologists (CAP)-accredited clinical laboratories to mitigate these challenges.

METHODS

A consensus for the genomic targets was discussed between the two institutes based on recurrence in diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, chronic lymphocytic leukaemia and T-cell lymphomas. Using the same genomic targets, each laboratory ordered libraries independently and a cross-validation study was designed to exchange samples (8 cell lines and 22 clinical samples) and their FASTQ files.

RESULTS

The sensitivity of the panel when comparing different library preparation and bioinformatic workflows was between 97% and 99% and specificity was 100% when a 5% limit of detection cut-off was applied. To evaluate how the current standards for variant classification of tumours apply to lymphomas, the Association for Molecular Pathology/American Society of Clinical Oncology/CAP and OncoKB classification systems were applied to the panel. The majority of variants were assigned a possibly actionable class or likely pathogenic due to more limited evidence in the literature.

CONCLUSIONS

The cross-validation study highlights the benefits of sample and data exchange for clinical validation and provided a framework for reporting the findings in lymphoid malignancies.

Smart variant filtering - A blueprint solution for massively parallel sequencing-based variant analysis

Massively parallel sequencing helps create new knowledge on genes, variants and their association with disease phenotype. This important technological advancement simultaneously makes clinical decision making, using genomic information for cancer patients, more complex. Currently, identifying actionable pathogenic variants with diagnostic, prognostic, or predictive impact requires substantial manual effort. Objective: The purpose is to design a solution for clinical diagnostics of lymphoma, specifically for systematic variant filtering and interpretation. Methods: A scoping review and demonstrations from specialists serve as a basis for a blueprint of a solution for massively parallel sequencing-based genetic diagnostics. Results: The solution uses machine learning methods to facilitate decision making in the diagnostic process. A validation round of interviews with specialists consolidated the blueprint and anchored it across all relevant expert disciplines. The scoping review identified four components of variant filtering solutions: algorithms and Artificial Intelligence (AI) applications, software, bioinformatics pipelines and variant filtering strategies. The blueprint describes the input, the AI model and the interface for dynamic browsing. Conclusion: An AI-augmented system is designed for predicting pathogenic variants. While such a system can be used to classify identified variants, diagnosticians should still evaluate the classification's accuracy, make corrections when necessary, and ultimately decide which variants are truly pathogenic.

Novel precision medicine approaches and treatment strategies in hematological malignancies

Genetic testing has been applied for decades in clinical routine diagnostics of hematological malignancies to improve disease (sub)classification, prognostication, patient management, and survival. In recent classifications of hematological malignancies, disease subtypes are defined by key recurrent genetic alterations detected by conventional methods (i.e., cytogenetics, fluorescence in situ hybridization, and targeted sequencing). Hematological malignancies were also one of the first disease areas in which targeted therapies were introduced, the prime example being BCR::ABL1 inhibitors, followed by an increasing number of targeted inhibitors hitting the Achilles' heel of each disease, resulting in a clear patient benefit. Owing to the technical advances in high-throughput sequencing, we can now apply broad genomic tests, including comprehensive gene panels or whole-genome and whole-transcriptome sequencing, to identify clinically important diagnostic, prognostic, and predictive markers. In this review, we give examples of how precision diagnostics has been implemented to guide treatment selection and improve survival in myeloid (myelodysplastic syndromes and acute myeloid leukemia) and lymphoid malignancies (acute lymphoblastic leukemia, diffuse large B-cell lymphoma, and chronic lymphocytic leukemia). We discuss the relevance and potential of monitoring measurable residual disease using ultra-sensitive techniques to assess therapy response and detect early relapses. Finally, we bring up the promising avenue of functional precision medicine, combining ex vivo drug screening with various omics technologies, to provide novel treatment options for patients with advanced disease. Although we are only in the beginning of the field of precision hematology, we foresee rapid development with new types of diagnostics and treatment strategies becoming available to the benefit of our patients.

The future of lymphoma diagnosis, prognosis, and treatment monitoring in countries with limited access to pathology services

The world is moving towards precision medicine for cancer. This movement goes hand in hand with the development of newer advanced technologies for early, precise diagnosis of cancer and personalized treatment plans with fewer adverse effects for the patient. Liquid biopsy is one such advancement. At the same time, it has the advantage of minimal invasion and avoids serial invasive biopsies. In countries with limited access to pathology services, such as sub-Saharan Africa, liquid biopsy may provide an opportunity for early detection and prognostication of lymphoma. We discuss the current diagnostic modalities for lymphoma, highlighting the existing challenges with tissue biopsy, and how feasible it is for countries with limited pathology resources to leverage advancements made in the clinical application of liquid biopsy to improve lymphoma care.

BTK and PLCG2 remain unmutated in one-third of patients with CLL relapsing on ibrutinib

Patients with chronic lymphocytic leukemia (CLL) progressing on ibrutinib constitute an unmet need. Though Bruton tyrosine kinase (BTK) and PLCG2 mutations are associated with ibrutinib resistance, their frequency and relevance to progression are not fully understood. In this multicenter retrospective observational study, we analyzed 98 patients with CLL on ibrutinib (49 relapsing after an initial response and 49 still responding after ≥1 year of continuous treatment) using a next-generation sequencing (NGS) panel (1% sensitivity) comprising 13 CLL-relevant genes including BTK and PLCG2. BTK hotspot mutations were validated by droplet digital polymerase chain reaction (ddPCR) (0.1% sensitivity). By integrating NGS and ddPCR results, 32 of 49 relapsing cases (65%) carried at least 1 hotspot BTK and/or PLCG2 mutation(s); in 6 of 32, BTK mutations were only detected by ddPCR (variant allele frequency [VAF] 0.1% to 1.2%). BTK/PLCG2 mutations were also identified in 6 of 49 responding patients (12%; 5/6 VAF <10%), of whom 2 progressed later. Among the relapsing patients, the BTK-mutated (BTKmut) group was enriched for EGR2 mutations, whereas BTK-wildtype (BTKwt) cases more frequently displayed BIRC3 and NFKBIE mutations. Using an extended capture-based panel, only BRAF and IKZF3 mutations showed a predominance in relapsing cases, who were enriched for del(8p) (n = 11; 3 BTKwt). Finally, no difference in TP53 mutation burden was observed between BTKmut and BTKwt relapsing cases, and ibrutinib treatment did not favor selection of TP53-aberrant clones. In conclusion, we show that BTK/PLCG2 mutations were absent in a substantial fraction (35%) of a real-world cohort failing ibrutinib, and propose additional mechanisms contributing to resistance.

Whole-genome informed circulating tumor DNA analysis by multiplex digital PCR for disease monitoring in B-cell lymphomas: a proof-of-concept study

Introduction

Analyzing liquid biopsies for tumor-specific aberrations can facilitate detection of measurable residual disease (MRD) during treatment and at follow-up. In this study, we assessed the clinical potential of using whole-genome sequencing (WGS) of lymphomas at diagnosis to identify patient-specific structural (SVs) and single nucleotide variants (SNVs) to enable longitudinal, multi-targeted droplet digital PCR analysis (ddPCR) of cell-free DNA (cfDNA).

Methods

In 9 patients with B-cell lymphoma (diffuse large B-cell lymphoma and follicular lymphoma), comprehensive genomic profiling at diagnosis was performed by 30X WGS of paired tumor and normal specimens. Patient-specific multiplex ddPCR (m-ddPCR) assays were designed for simultaneous detection of multiple SNVs, indels and/or SVs, with a detection sensitivity of 0.0025% for SV assays and 0.02% for SNVs/indel assays. M-ddPCR was applied to analyze cfDNA isolated from serially collected plasma at clinically critical timepoints during primary and/or relapse treatment and at follow-up.

Results

A total of 164 SNVs/indels were identified by WGS including 30 variants known to be functionally relevant in lymphoma pathogenesis. The most frequently mutated genes included KMT2D, PIM1, SOCS1 and BCL2. WGS analysis further identified recurrent SVs including t(14;18)(q32;q21) (IGH::BCL2), and t(6;14)(p25;q32) (IGH::IRF4). Plasma analysis at diagnosis showed positive circulating tumor DNA (ctDNA) levels in 88% of patients and the ctDNA burden correlated with baseline clinical parameters (LDH and sedimentation rate, p-value <0.01). While clearance of ctDNA levels after primary treatment cycle 1 was observed in 3/6 patients, all patients analyzed at final evaluation of primary treatment showed negative ctDNA, hence correlating with PET-CT imaging. One patient with positive ctDNA at interim also displayed detectable ctDNA (average variant allele frequency (VAF) 6.9%) in the follow-up plasma sample collected 2 years after final evaluation of primary treatment and 25 weeks before clinical manifestation of relapse.

Conclusion

In summary, we demonstrate that multi-targeted cfDNA analysis, using a combination of SNVs/indels and SVs candidates identified by WGS analysis, provides a sensitive tool for MRD monitoring and can detect lymphoma relapse earlier than clinical manifestation.

Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field.

Molecular classification and therapeutics in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) encompasses a wide variety of disease states that have to date been subgrouped and characterized based on immunohistochemical methods, which provide limited prognostic value to clinicians and no alteration in treatment regimen. The addition of rituximab to CHOP therapy was the last leap forward in terms of treatment, but regimens currently follow a standardized course when disease becomes refractory with no individualization based on genotype. Research groups are tentatively proposing new strategies for categorizing DLBCL based on genetic abnormalities that are frequently found together to better predict disease course following dysregulation of specific pathways and to deliver targeted treatment. Novel algorithms in combination with next-generation sequencing techniques have identified between 4 and 7 subgroups of DLBCL, depending on the research team, with potentially significant and actionable genetic alterations. Various drugs aimed at pathways including BCR signaling, NF-κB dysfunction, and epigenetic regulation have shown promise in their respective groups and may show initial utility as second or third line therapies to patients with recurrent DLBCL. Implementation of subgroups will allow collection of necessary data to determine which groups are significant, which treatments may be indicated, and will provide better insight to clinicians and patients on specific disease course.

Different prognostic impact of recurrent gene mutations in chronic lymphocytic leukemia depending on IGHV gene somatic hypermutation status: a study by ERIC in HARMONY

Recent evidence suggests that the prognostic impact of gene mutations in patients with chronic lymphocytic leukemia (CLL) may differ depending on the immunoglobulin heavy variable (IGHV) gene somatic hypermutation (SHM) status. In this study, we assessed the impact of nine recurrently mutated genes (BIRC3, EGR2, MYD88, NFKBIE, NOTCH1, POT1, SF3B1, TP53, and XPO1) in pre-treatment samples from 4580 patients with CLL, using time-to-first-treatment (TTFT) as the primary end-point in relation to IGHV gene SHM status. Mutations were detected in 1588 (34.7%) patients at frequencies ranging from 2.3-9.8% with mutations in NOTCH1 being the most frequent. In both univariate and multivariate analyses, mutations in all genes except MYD88 were associated with a significantly shorter TTFT. In multivariate analysis of Binet stage A patients, performed separately for IGHV-mutated (M-CLL) and unmutated CLL (U-CLL), a different spectrum of gene alterations independently predicted short TTFT within the two subgroups. While SF3B1 and XPO1 mutations were independent prognostic variables in both U-CLL and M-CLL, TP53, BIRC3 and EGR2 aberrations were significant predictors only in U-CLL, and NOTCH1 and NFKBIE only in M-CLL. Our findings underscore the need for a compartmentalized approach to identify high-risk patients, particularly among M-CLL patients, with potential implications for stratified management.

Genomic profiling for clinical decision making in lymphoid neoplasms

With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. Although the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet, the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification, and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses, and epigenetic profiling will be discussed because these will likely become important future tools for implementing precision medicine approaches in clinical decision making for patients with lymphoid malignancies.

Data-driven support to decision-making in molecular tumour boards for lymphoma: A design science approach

Background

The increasing amount of molecular data and knowledge about genomic alterations from next-generation sequencing processes together allow for a greater understanding of individual patients, thereby advancing precision medicine. Molecular tumour boards feature multidisciplinary teams of clinical experts who meet to discuss complex individual cancer cases. Preparing the meetings is a manual and time-consuming process.

Purpose

To design a clinical decision support system to improve the multimodal data interpretation in molecular tumour board meetings for lymphoma patients at Karolinska University Hospital, Stockholm, Sweden. We investigated user needs and system requirements, explored the employment of artificial intelligence, and evaluated the proposed design with primary stakeholders.

Methods

Design science methodology was used to form and evaluate the proposed artefact. Requirements elicitation was done through a scoping review followed by five semi-structured interviews. We used UML Use Case diagrams to model user interaction and UML Activity diagrams to inform the proposed flow of control in the system. Additionally, we modelled the current and future workflow for MTB meetings and its proposed machine learning pipeline. Interactive sessions with end-users validated the initial requirements based on a fictive patient scenario which helped further refine the system.

Results

The analysis showed that an interactive secure Web-based information system supporting the preparation of the meeting, multidisciplinary discussions, and clinical decision-making could address the identified requirements. Integrating artificial intelligence via continual learning and multimodal data fusion were identified as crucial elements that could provide accurate diagnosis and treatment recommendations.

Impact

Our work is of methodological importance in that using artificial intelligence for molecular tumour boards is novel. We provide a consolidated proof-of-concept system that could support the end-to-end clinical decision-making process and positively and immediately impact patients.

Conclusion

Augmenting a digital decision support system for molecular tumour boards with retrospective patient material is promising. This generates realistic and constructive material for human learning, and also digital data for continual learning by data-driven artificial intelligence approaches. The latter makes the future system adaptable to human bias, improving adequacy and decision quality over time and over tasks, while building and maintaining a digital log.

Critical Role of Aquaporins in Cancer: Focus on Hematological Malignancies

Simple Summary

Aquaporins are proteins able to regulate the transfer of water and other small substances such as ions, glycerol, urea, and hydrogen peroxide across cellular membranes. AQPs provide for a huge variety of physiological phenomena; their alteration provokes several types of pathologies including cancer and hematological malignancies. Our review presents data revealing the possibility of employing aquaporins as biomarkers in patients with hematological malignancies and evaluates the possibility that interfering with the expression of aquaporins could represent an effective treatment for hematological malignancies.

Abstract

Aquaporins are transmembrane molecules regulating the transfer of water and other compounds such as ions, glycerol, urea, and hydrogen peroxide. Their alteration has been reported in several conditions such as cancer. Tumor progression might be enhanced by aquaporins in modifying tumor angiogenesis, cell volume adaptation, proteases activity, cell–matrix adhesions, actin cytoskeleton, epithelial–mesenchymal transitions, and acting on several signaling pathways facilitating cancer progression. Close connections have also been identified between the aquaporins and hematological malignancies. However, it is difficult to identify a unique action exerted by aquaporins in different hemopathies, and each aquaporin has specific effects that vary according to the class of aquaporin examined and to the different neoplastic cells. However, the expression of aquaporins is altered in cell cultures and in patients with acute and chronic myeloid leukemia, in lymphoproliferative diseases and in multiple myeloma, and the different expression of aquaporins seems to be able to influence the efficacy of treatment and could have a prognostic significance, as greater expression of aquaporins is correlated to improved overall survival in leukemia patients. Finally, we assessed the possibility that modifying the aquaporin expression using aquaporin-targeting regulators, specific monoclonal antibodies, and even aquaporin gene transfer could represent an effective therapy of hematological malignancies.