EuroClonality-NGS Recommendations for Evaluation of B-Cell Clonality Analysis by Next-Generation Sequencing: A Structured Approach with the DEPART Algorithm

Molecular Screening in Anaplastic Lymphoma Kinase-Positive Anaplastic Large Cell Lymphoma: Anaplastic Lymphoma Kinase Analysis, Next-Generation Sequencing Fusion Gene Detection, and T-Cell Receptor Immunoprofiling

Anaplastic lymphoma kinase-positive anaplastic large cell lymphoma (ALK+ ALCL) originates from the T-lineage and is marked by rearrangements of the ALK gene. More than 10 fusion partners with the ALK gene are known, with the most common being the t(2;5)(p23;q35) translocation resulting in the NPM1::ALK fusion. In 10% to 20% of the ALK+ ALCL cases, the ALK gene fuses with various other partners. Modern molecular techniques, especially next-generation sequencing (NGS), have eased the identification of ALK gene fusion partners and have allowed in-depth characterization of the T-cell receptor (TCR) repertoire. We devised a real-time quantitative reverse-transcription polymerase chain reaction to measure the expression of the translocated portion of the ALK gene. Fusion partners for the ALK gene were analyzed using rapid amplification of 5'cDNA ends (RACE) method or NGS. TCR immunoprofiling was performed by amplicon NGS. We studied 96 ALK+ ALCL patients. NPM1::ALK fusion gene was observed in 71 patients, ATIC::ALK in 9, and TPM3::ALK in 3. CLTC::ALK, MYH9::ALK, and RNF213::ALK fusions were identified in 2 patients each. We also discovered the TPM4::ALK and SATB1::ALK fusion genes, plus the following 2 previously unidentified ALK+ ALCL fusions: SQSTM1::ALK and CAPRIN1::ALK. High expression of the translocated ALK gene segment was observed in all 93 analyzed samples. TCR testing was conducted on 23 patients with available DNA. In 18 (78%) patients, we discerned at least one (ranging from 1 to 4) clonal TCR rearrangement. In 59% of the patients, clonal TCR beta junctions corresponded with sequences previously observed in both healthy donors and under various pathological conditions. Reverse-transcriptase quantitative detection of ALK expression is a fast and reliable method for both diagnosing and monitoring treatment response in ALK+ ALCL patients, irrespective of the ALK gene translocation. NGS reveals new ALK translocation partners. Both malignant and reactive TCR repertoires in ALK+ ALCL patients are unique and do not consistently occur among different patients.

Diagnostic and prognostic molecular pathology of lymphoid malignancies

With the explosion in knowledge about the molecular landscape of lymphoid malignancies and the increasing availability of high throughput techniques, molecular diagnostics in hematopathology has moved from isolated marker studies to a more comprehensive approach, integrating results of multiple genes analyzed with a variety of techniques on the DNA and RNA level. Although diagnosis of lymphoma still relies on the careful integration of clinical, morphological, phenotypic, and, if necessary molecular features, and only few entities are defined strictly by genetic features, genetic profiling has contributed profoundly to our current understanding of lymphomas and shaped the two current lymphoma classifications, the International Consensus Classification and the fifth edition of the WHO classification of lymphoid malignancies. In this review, the current state of the art of molecular diagnostics in lymphoproliferations is summarized, including clonality analysis, mutational studies, and gene expression profiling, with a focus on practical applications for diagnosis and prognostication. With consideration for differences in accessibility of high throughput techniques and cost limitations, we tried to distinguish between diagnostically relevant and in part disease-defining molecular features and optional, more extensive genetic profiling, which is usually restricted to clinical studies, patients with relapsed or refractory disease or specific therapeutic decisions. Although molecular diagnostics in lymphomas currently is primarily done for diagnosis and subclassification, prognostic stratification and predictive markers will gain importance in the near future.