High-Throughput Sequencing Detects Minimal Residual Disease in Acute T Lymphoblastic Leukemia

High-throughput sequencing can detect minimal residual disease comparable to multiparametric flow cytometry in T-ALL patients. Finding a Needle in a Haystack Even in seemingly successful cancer therapy, a small number of cells can survive treatment and persist in patients in remission. This minimal residual disease (MRD) is a major cause of cancer relapse, and until recently was undetectable. New ways to track MRD can determine whether cancer has been eradicated, compare the efficacy of different treatments, monitor patient remission status, and aid in treatment selection. Wu et al. use high-throughput sequencing (HTS) of lymphoid receptor genes to track MRD in T-lineage acute lymphoblastic leukemia/lymphoma (T-ALL). The authors sequence the variable regions of two T cell antigen receptor genes (TCRB and TCRG) using multiplexed polymerase chain reaction. First, they identified clonal T cell receptor (TCR) sequences in individual T-ALL patients and then looked in the same patients after treatment. Their strategy identified clonality at diagnosis in most cases and also detected subsequent MRD. In a subset of cases, HTS detected MRD in patients where it was not detected by flow cytometry, which is currently used in the clinic. Thus, HTS may lower the threshold of detection for MRD and affect treatment decisions. High-throughput sequencing (HTS) of lymphoid receptor genes is an emerging technology that can comprehensively assess the diversity of the immune system. Here, we applied HTS to the diagnosis of T-lineage acute lymphoblastic leukemia/lymphoma. Using 43 paired patient samples, we then assessed minimal residual disease (MRD) at day 29 after treatment. The variable regions of TCRB and TCRG were sequenced using an Illumina HiSeq platform after performance of multiplexed polymerase chain reaction, which targeted all potential V-J rearrangement combinations. Pretreatment samples were used to define clonal T cell receptor (TCR) complementarity-determining region 3 (CDR3) sequences, and paired posttreatment samples were evaluated for MRD. Abnormal T lymphoblast identification by multiparametric flow cytometry was concurrently performed for comparison. We found that TCRB and TCRG HTS not only identified clonality at diagnosis in most cases (31 of 43 for TCRB and 27 of 43 for TCRG) but also detected subsequent MRD. As expected, HTS of TCRB and TCRG identified MRD that was not detected by flow cytometry in a subset of cases (25 of 35 HTS compared with 13 of 35, respectively), which highlights the potential of this technology to define lower detection thresholds for MRD that could affect clinical treatment decisions. Thus, next-generation sequencing of lymphoid receptor gene repertoire may improve clinical diagnosis and subsequent MRD monitoring of lymphoproliferative disorders.

[1]  C. Desmarais,et al.  Ultra-sensitive detection of rare T cell clones. , 2012, Journal of immunological methods.

[2]  B. Wood,et al.  9-color and 10-color flow cytometry in the clinical laboratory. , 2006, Archives of pathology & laboratory medicine.

[3]  David L. Porter,et al.  T Cells with Chimeric Antigen Receptors Have Potent Antitumor Effects and Can Establish Memory in Patients with Advanced Leukemia , 2011, Science Translational Medicine.

[4]  M. Schrappe,et al.  Optimization of PCR-based minimal residual disease diagnostics for childhood acute lymphoblastic leukemia in a multi-center setting , 2007, Leukemia.

[5]  Cheng Cheng,et al.  Early T-cell precursor leukaemia: a subtype of very high-risk acute lymphoblastic leukaemia. , 2009, The Lancet. Oncology.

[6]  T. Szczepański,et al.  T cell receptor gamma (TCRG) gene rearrangements in T cell acute lymphoblastic leukemia reflect ‘end-stage’ recombinations: implications for minimal residual disease monitoring , 2000, Leukemia.

[7]  D. Campana Progress of Minimal Residual Disease Studies in Childhood Acute Leukemia , 2010, Current hematologic malignancy reports.

[8]  W. Hop,et al.  Prognostic value of minimal residual disease in acute lymphoblastic leukaemia in childhood , 1998, The Lancet.

[9]  B. Wood,et al.  Immaturity associated antigens are lost during induction for T cell lymphoblastic leukemia: Implications for minimal residual disease detection , 2010, Cytometry. Part B, Clinical cytometry.

[10]  C. Desmarais,et al.  Deep Sequencing of the Human TCRγ and TCRβ Repertoires Suggests that TCRβ Rearranges After αβ and γδ T Cell Commitment , 2011, Science Translational Medicine.

[11]  G. Basso,et al.  Drug-induced immunophenotypic modulation in childhood ALL: implications for minimal residual disease detection , 2005, Leukemia.

[12]  Prognostic value of minimal residual disease in acute lymphoblastic leukaemia in childhood , 1998 .

[13]  J. Dongen,et al.  Comparative analysis of T-cell receptor gene rearrangements at diagnosis and relapse of T-cell acute lymphoblastic leukemia (T-ALL) shows high stability of clonal markers for monitoring of minimal residual disease and reveals the occurrence of second T-ALL , 2003, Leukemia.

[14]  A. Biondi,et al.  Molecular monitoring of childhood acute lymphoblastic leukemia using antigen receptor gene rearrangements and quantitative polymerase chain reaction technology. , 2005, Haematologica.

[15]  Dario Campana,et al.  Minimal residual disease in acute lymphoblastic leukemia. , 2010, Hematology. American Society of Hematology. Education Program.

[16]  J. Dongen,et al.  Rearranged T-cell receptor beta genes represent powerful targets for quantification of minimal residual disease in childhood and adult T-cell acute lymphoblastic leukemia , 2004, Leukemia.

[17]  M. Loh,et al.  Absence of biallelic TCRgamma deletion predicts early treatment failure in pediatric T-cell acute lymphoblastic leukemia. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[18]  J. Dongen,et al.  Validation of BIOMED-2 multiplex PCR tubes for detection of TCRB gene rearrangements in T-cell malignancies , 2004, Leukemia.

[19]  FLOW CYTOMETRY IN THE CLINICAL LABORATORY , 2012 .

[20]  W. Hop,et al.  Detection of minimal residual disease identifies differences in treatment response between T-ALL and precursor B-ALL. , 2002, Blood.

[21]  Marie-Paule Lefranc,et al.  IMGT/JunctionAnalysis: the first tool for the analysis of the immunoglobulin and T cell receptor complex V-J and V-D-J JUNCTIONs , 2004, ISMB/ECCB.

[22]  M. Kami,et al.  Prognostic value of minimal residual disease in acute lymphoblastic leukaemia in childhood , 1998, The Lancet.

[23]  M. Egholm,et al.  Measurement and Clinical Monitoring of Human Lymphocyte Clonality by Massively Parallel V-D-J Pyrosequencing , 2009, Science Translational Medicine.

[24]  J. Cayuela,et al.  Analysis of minimal residual disease by Ig/TCR gene rearrangements: guidelines for interpretation of real-time quantitative PCR data , 2007, Leukemia.

[25]  T. Scheetz,et al.  Cell of origin strongly influences genetic selection in a mouse model of T-ALL. , 2011, Blood.

[26]  Abigail Wacher,et al.  Comprehensive assessment of T-cell receptor beta-chain diversity in alphabeta T cells. , 2009, Blood.

[27]  B. Schäfer,et al.  Minimal residual disease-directed risk stratification using real-time quantitative PCR analysis of immunoglobulin and T-cell receptor gene rearrangements in the international multicenter trial AIEOP-BFM ALL 2000 for childhood acute lymphoblastic leukemia , 2008, Leukemia.

[28]  J. V. van Dongen,et al.  Late MRD response determines relapse risk overall and in subsets of childhood T-cell ALL: results of the AIEOP-BFM-ALL 2000 study. , 2011, Blood.

[29]  C. Carlson,et al.  Overlap and Effective Size of the Human CD8+ T Cell Receptor Repertoire , 2010, Science Translational Medicine.

[30]  J. Dongen,et al.  Non-specific amplification of patient-specific Ig/TCR gene rearrangements depends on the time point during therapy: implications for minimal residual disease monitoring , 2008, Leukemia.

[31]  M. Valsecchi,et al.  Results of the AIEOP-BFM ALL 2000 Study for Childhood Acute Lymphoblastic Leukemia IN AIEOP High Risk Patients. , 2009 .