MEANS AND METHODS FOR ACCURATELY ASSESSING CLONAL IMMUNOGLOBULIN (IG)/T CELL RECEPTOR (TR) GENE REARRANGEMENTS

Abstract

The invention relates to means and methods for assessing clonal immunoglobulin (IG)/T cell receptor (TR) gene rearrangements in a clinical, diagnostic and/or research setting. Provided is a quality control composition comprising a mixture of genomic DNA isolated from a set of nine cultured cell lines, said set comprising the B cell lines ALL/MIK (ALL), Raji (Burkitt lymphoma), REH (B cell precursor ALL), TMM (CML-BC/EBV+B-LCL), TOM-1 (B cell precursor ALL), WSU-NHL (B cell lymphoma) and the T cell lines JB6 (ALCL), Karpas299 (ALCL) and MOLT-13 (ALL), or wherein one or more cell lines of said set is replaced with one or more other cell line(s) comprising the same IG/TR gene rearrangements. Also provided is a quality control composition consisting of essentially equimolar amounts of genomic DNA isolated from healthy human thymus, healthy human tonsil and healthy human peripheral blood mononuclear cells.

Claims

1. A composition comprising a mixture of genomic DNA isolated from a set of nine cultured cell lines, said set comprising the B cell lines ALL/MIK (B cell precursor ALL), Raji (Burkitt lymphoma), REH (B cell precursor ALL), TMM (CML-BC/EBV+B-LCL), TOM-1 (B cell precursor ALL), WSU-NHL (B cell lymphoma) and the T cell lines JB6 (ALCL), Karpas299 (ALCL) and MOLT-13 (T-ALL), or wherein one or more cell lines of said set is replaced with one or more other cell line(s) comprising the same immunoglobulin (IG)/T cell receptor (TR) gene rearrangements.

2. The composition according to claim 1, comprising a mixture of genomic DNA isolated from the B cell lines ALL/MIK, Raji, REH, TMM, TOM-1, WSU-NHL and the T cell lines JB6, Karpas299 and MOLT-13.

3. The composition according to claim 1, wherein said composition comprises essentially equal amounts of genomic DNA of each of said cell lines.

4. A composition consisting of essentially equimolar amounts of genomic DNA isolated from healthy human thymus, healthy human tonsil and healthy human peripheral blood mononuclear cells.

5. The composition according to claim 4, wherein, for each tissue, the genomic DNA is obtained from a number, preferably 3 to 10, different human individuals.

6. A diagnostic kit comprising a container comprising a composition according to claim 1, and/or a container comprising a composition according to claim 4.

7. The diagnostic kit according to claim 6, comprising a first container comprising the composition according to claim 1, and a second container comprising the composition according to claim 4.

8. The diagnostic kit according to claim 6, further comprising one or more reagents for detecting immunoglobulin (IG)/T cell receptor (TR) gene rearrangements.

9. The diagnostic kit according to claim 8, comprising a set of primers for amplicon-based next-generation sequencing (NGS) of IG/TR gene rearrangements.

10. The diagnostic kit according to claim 8, comprising primer sets for detecting one or more of the IG/TR gene rearrangements selected from the group consisting of IGH-VJ, IGH-DJ, IGK-VJ-Kde, TRB-VJ, TRB-DJ, TRG and TRD.

11. The diagnostic kit according to claim 9, comprising one or more of the primers selected from the primers shown in FIG. 5, preferably one or more of the primers selected from the primers shown in Table 3.

12. A set of primers for amplicon-based next-generation sequencing (NGS) of IG/TR gene rearrangements, comprising two or more of the primers selected from the primers shown in FIG. 5.

13. The set of primers according to claim 12, comprising two or more of the primers selected from the primers shown in Table 3.

14. The use of a composition according to claim 1, a kit according to claim 6, and/or a primer set according to claim 12 in an assay for detecting IG/TR gene rearrangements.

15. The use according to claim 14, wherein said assay is a clinical diagnostic assay, preferably an assay for detecting clonality, identifying minimal residual disease (MRD) markers and/or MRD monitoring and/or analyzing the (clonal) immune repertoire in a lymphoid malignancy.

16. An in vitro method for detecting IG/TR gene rearrangements in at least one biological sample using NGS, comprising the steps of sample preparation, PCR and/or library construction, sequencing and bioinformatics analysis, wherein the at least one biological sample is spiked with a composition according to claim 1, and/or wherein a composition according to claim 4 is run as a sample parallel to the at least one biological sample(s).

17. The method according to claim 16, wherein the at least one biological sample is a clinically relevant sample, preferably a sample for detection of clonality to support or exclude the diagnosis of malignant lymphoproliferation, or a sample taken for MRD marker identification or for MRD monitoring analysis or for (clonal) immune repertoire analysis.

18. The method according to claim 17, wherein at least part of the method is performed using a microfluidics device.

19. The method according to claim 18, wherein said microfluidics device comprises a centrifugal-microfluidic disk system, preferably wherein the disk comprises pre-stored reagents for automated and integrated DNA extraction, PCR and/or library generation.

20. The method according to claim 17, wherein the step of bioinformatic analysis comprises the use of a web-based, interactive application for pre-processing of raw data, primer sequence analysis, immunogenetic annotation, post-processing of results, analysis and use of the cIT-QC (including for marker quantification), analysis and use of the cPT-QC (including for comparison to pre-analyzed stored reference datasets), reporting of/access to/visualization of results.

Description

LEGEND TO THE FIGURES

[0040] FIG. 1. Study design: workflows of development and application for cIT-QC and cPT-QC, and schematic overview of test dataset based on a 96-well plate.

[0041] FIG. 2. Schematic overview of the SOP for quality control and quantification in marker identification: library preparation, PCR & NGS, bioinformatics with ARResT/Interrogate.

[0042] FIG. 3. Plots of relationships between cIT-QC and markers in the test dataset. A. Relationship between % abundances of reads for cIT-QC and markers (at the x-axis). For cIT-QC, the % denominator is reads with junction; for markers, the % denominator is what we term usable reads with junction, which excludes cIT-QC reads; this leads to sums of >100%. B. Abundance of markers before and after normalisation to percentage of cells. *normalisation may lead to values >100%.

[0043] FIG. 4: Schematic overview of the workflow for multicentre validation of IG/TR NGS assays for MRD marker identification in ALL. The IG and TR gene rearrangements are amplified in a two-step approach using multiplex PCR assays. Each of the participating laboratories performed NGS-based IG/TR MRD marker identification in 10 patients with ALL. The central polytarget control (cPT-QC) composition of the invention was used to monitor primer performance, and central in-tube quality/quantification controls (cIT-QC) of the invention were spiked to each sample as library-specific quality control and calibrator. Pipetting was performed in a 96-well format. The data analysis was performed employing ARResT/Interrogate.

[0044] FIG. 5: Schematic diagrams of rearrangements and primer sets, and histograms showing junctions nucleotide lengths for each investigated locus.

5A-1) Schematic diagrams of IGH-VJ and IGH-DJ rearrangements. The relative position of the VH family primers, DH family primers and consensus JH primers is given according to their most 5nucleotide upstream () or downstream (+) of the involved RSS.
5A-2) Histograms showing junction nucleotide lengths of complete IGH rearrangements (IGH-VJ tube) in a BCP-ALL patient, cPT-QC, BC, thymus, and tonsil. Bars are coloured according to the V-J genes combination.
5A-3) Histograms showing junction nucleotide lengths of incomplete IGH rearrangements (IGH-DJ tube) in a BCP-ALL patient, cPT-QC, BC, thymus, and tonsil. Bars are coloured according to the D-J genes combination.
5B-1) Schematic diagrams of IGK-VJ rearrangement and the two types of Kde rearrangements (V-Kde and intronRSS-Kde). The relative position of the VK, JK, Kde, and intronRSS (INTR) primers is given according to their most 5nucleotide upstream () or downstream (+) of the involved RSS.
5B-2) Histograms showing junction nucleotide lengths of IGK-VJ and IGK-V-Kde rearrangements (IGK-VJ-Kde tube) in a B-ALL patient, cPT-QC, BC, thymus, and tonsil. Bars are coloured according to the V-J-Kde genes combination.
5B-3) Histograms showing junction nucleotide lengths of intron-Kde rearrangements (intron-Kde tube) in a BCP-ALL patient, cPT-QC, BC, thymus, and tonsil.
5C-1) Schematic diagrams of TRB-VJ rearrangement and DJ rearrangement. The relative position of the TRB V family primers, TRB D primers and the TRB J primers is given according to their most 5nucleotide upstream () or downstream (+) of the involved RSS.
5C-2) Histograms showing junction nucleotide lengths of complete TRB rearrangements (TRB-VJ tube) in a T-ALL patient, cPT-QC, BC, thymus, and tonsil. Bars are coloured according to the V-J genes combination.
5C-3) Histograms showing junction nucleotide lengths of incomplete TRB rearrangements (TRB-DJ tube) in a T-ALL patient, cPT-QC, BC, thymus, and tonsil. Bars are coloured according to the D-J genes combination.
5D-1) Schematic diagrams of TRG V-J rearrangement and the relative position of the TRG V and TRG J primers. The relative position of the TRG V primers and the TRG J primers is given according to their most 5nucleotide upstream () or downstream (+) of the involved RSS.
5D-2) Histograms showing junction nucleotide lengths of TRG rearrangements (TRG tube) in a T-ALL patient, cPT-QC, BC, thymus, and tonsil. Bars are coloured according to the V-J genes combination.
5E-1) Schematic diagram of VD-JD, DD-JD, DD-DD, and VD-DD, VD-JA29 rearrangements, showing the positioning of VD, JD, DD, and JA29 primers, all combined in a single tube. The relative position of the Vd, Dd, and Jd primers is indicated according to their most 50 nucleotide upstream () or downstream (+) of the involved RSS.
5E-2) Histograms showing junction nucleotide lengths of TRD rearrangements (TRD tube) in a T-ALL patient, cPT-QC, BC, thymus, and tonsil. Bars are coloured according to the V-D-J genes combination.

[0045] FIG. 6: Results of multicentre validation of assays for MRD marker identification in ALL. Left hand columns: Index sequences identified by Sanger sequencing. Right hand columns: Index sequences identified by NGS. Darkest colored sections of the columns reflect clonal sequences identified by both methods, lightest colored sections are sequences identified only by the respective method. Median colored sections are clonal sequences identified by both methods, but by NGS with an abundance of <5% after normalization.

EXPERIMENTAL SECTION

Example 1: Design and Production of the Central In-Tube Quality/Quantification Control (cIT-QC)

Sources and Methods

[0046] In total, 59 human B (n=30) and T (n=29) lymphoid cell lines were obtained from the American Type Culture Collection (ATCC; www.lgcpromochem-atcc.com, Manassas, VA, USA) and the German Collection of Microorganisms and Cell Cultures GmbH (DSMZ; www.dsmz.de, Braunschweig, Germany), or were derived from internal cell line banks. DNA from cultured cell lines was isolated using a phenol-chloroform extraction protocol, followed by ethanol precipitation and elution in Tris ethylenediaminetetra-acetic acid (TE) buffer. Alternatively, DNA was isolated with the GenElute Mammalian Genomic DNA Miniprep Kit (Sigma-Aldrich, St. Louis, MO, USA) according to manufacturer's protocol.

Identification of Cell Line-Specific Clonal IG/TR Gene Rearrangements

[0047] Each of the 59 cell lines was screened for clonal IG/TR gene rearrangements using the aforementioned EuroClonality-NGS assay with 100 ng of DNA (quantified with Qubit 3.0, Thermo Fisher Scientific) from each cell line, without addition of buffy coat (BC). Paired-end sequencing (2250 bp) was performed on an Illumina MiSeq (Illumina, San Diego, CA, USA) with a final concentration of 7 pM per library aiming for at least 2000 reads per sample. To avoid low-complexity library issues 10% PhiX control was added to each sequencing run.

Verification of Cell Line-Specific Clonal IG/TR Gene Rearrangements

[0048] Additional methods were used to verify the NGS-amplicon-identified cell line rearrangements: [0049] 1. A capture-based protocol, established within EuroClonality-NGS Working Group and covering the coding V, D and J genes of IG/TR loci.sup.37: in short, cell line DNA was fragmented and processed with the KAPA Hyperplus Kit with Library Amplification (Roche Sequencing Solutions, Pleasanton, CA, USA); hybridisation of libraries was performed with customised SeqCap EZ Choice Probes (Roche Sequencing Solutions, Pleasanton, CA, USA), developed based on Wren et al.sup.37; 2150 bp paired-end sequencing was performed on Illumina NextSeq. [0050] 2. Multiplex amplification and Sanger sequencing according to the BIOMED-2 protocol: PCR products were checked for fragment sizes and clonality in the QIAXCEL Advanced System.sup.11,46. Clonal PCR products were subjected to heteroduplex analysis and sequenced on either an ABI 3130 or ABI 3500 platform (Applied Biosystems, Foster City, CA, USA).

[0051] IG/TR rearrangement profiles of all cell lines, as obtained with the different methods, were compared.

Verification of Cell Line-Specific Gene Rearrangements from Human B and T Cell Lines Via ddPCR

[0052] For cases with discrepant results between the three methods, IG/TR allele-specific PCR assays were designed for digital droplet PCR (ddPCR) (QX200 Droplet Digital PCR System, Bio-Rad) to verify the respective rearrangement. Absolute quantification of IG/TR gene rearrangements by ddPCR was performed using two different gDNA amounts (50 ng, 100 ng). Each experiment included a polyclonal buffy coat BC control and a no template control.

[0053] Allele-specific primers for clonal IG/TR rearrangements and probes for quantification were synthesized by Sigma Aldrich. All primers were cleaned by desalting, while hydrolysis probes containing a 5-FAM/3-TAMRA reporter dye were cleaned by HPLC. All oligonucleotides were resuspended in TE buffer at a total strand concentration Ct=100 M and stored at 20 C. before use.

[0054] ddPCR reactions were prepared in a volume of 20 L using 10 L by 2ddPCR SuperMix (Bio-Rad Laboratories, Hercules, CA), testing two different amounts of cell line gDNA (50 ng/500 ng) quantified before with the Qubit dsDNA High Sensitivity Assay Kit (Thermo Fisher Scientific, Waltham, MA), forward primer (FP) and reverse primer (RP), each at a final concentration 300 nmol/L, and FAM-labelled probes (100 nmol/L). Droplets were generated by the QX200 droplet generator (Bio-Rad) using 20 L of the reaction mixture and 70 L of the droplet generation oil for probes (Bio-Rad), located onto suitable holes in a DG8 cartridge (Bio-Rad). About 45 L of the drop-oil mixture (12,000-20,000 drops) were transferred to a 96-well plate (Bio-Rad) and loaded on a DNA Engine Dyad Peltier Thermal Cycler with the following amplification protocol: 95 C. for 10 min, followed by 40 cycles: denaturation at 94 C. for 30 s; annealing at 60 C. for 1 min; extension at 60 C. for 1 min. PCR products were loaded into the QX200 droplet reader and analysed by QuantaSoft Version 1.2 (Bio-Rad Laboratories).

Cell Line Mixture Preparation

[0055] Initially, quantification of DNA of selected B- and T-cell lines was done by Qubit dsDNA High Sensitivity Assay Kit (Thermo Fisher Scientific, Waltham, MA). Quantitative values were checked again by ddPCR-based quantification of the albumin housekeeping gene using 50-200 ng DNA/cell line in order to precisely determine the number of cells per l of DNA. Primers and probe for albumin quantitation were synthesized by Sigma Aldrich. ddPCR was carried out according to the protocol described above, in duplicates for each cell line. After completion of the PCR, samples were analyzed in the Droplet Reader in terms of number of copies of cell lines per 20 l reaction volume. Based on the values from the ddPCR, the cell line DNA was diluted in TE buffer down to 400 copies/l. Thereafter, another ddPCR quantification was performed to check the dilution of each cell line DNA again. Two different volumes of the diluted cell line solution (0.5 l DNA [200 copies] and 2 l DNA [800 copies]) were used as input amount. With suitable quantitative values, cell line DNAs were further diluted and mixed with each other leading to 40 copies of each cell line being present in 2 l of the DNA mixture. This mixture was added to each sample as cIT-QC and subjected to simultaneous library preparation prior to sequencing.

Implementation of the cIT-QC

[0056] Bioinformatically, cIT-QC reads are identified using an immunogenetic annotation-based approach that is extremely fast while allowing for variations in sequence, avoiding compute-intensive and potentially inaccurate alignment-based approaches. In ARResT/Interrogate, the term spike-ins is also used to refer to the cIT-QC.

[0057] Regarding QC, identification of at least one read per cIT-QC rearrangement and of at least as many total cIT-QC reads as total cells used is required, otherwise the sample is tagged as QC-failed (see below for how this is used in ARResT/Interrogate). The quantification factorcalculated by dividing total cIT-QC cells by total readsis stored and applied in any case, thus still allowing the user to analyse the sample.

[0058] Quantification is based on applying the quantification factor to convert the read counts of a clonotype to cell counts, and then calculate the relative abundance against the total input cells.

Example 2: Design and Production of the Central Polytarget Quality Control (cPT-QC)

Sources and Methods

[0059] A cPT-QC composition was prepared that consists of genomic DNA isolated from healthy human thymus, healthy human tonsil and healthy human peripheral blood mononuclear cells (DNA amounts mixed in a ratio 1:1:1). To that end, a (semi-)automated genomic DNA extraction was performed on cell suspensions obtained after dissecting and mincing tissues or Ficoll density blood separation.

[0060] The cPT-QC composition is suitable used to undergo NGS library preparation alongside the investigated samples. For the EuroClonality-NGS assay, this involves one cPT-QC sample per run, amplified in eight tubes.

Implementation of the cPT-QC

[0061] Primers are bioinformatically identified in the reads of each of the eight cPT-QC tubes of the run and their abundances compared to stored cPT-QC reference results using the test of proportions.

[0062] Stored reference results are the output of ARResT/Interrogate from the analysis of a cPT-QC sample. These results should be confirmed through replicate runs over time in each lab to accommodate for technical variability. The results and not the raw data are stored to ensure that the bioinformatic analysis is not compromised inadvertently by the user; this means that the results are updated with every major release of ARResT/Interrogate to ensure compatibility with new runs.

[0063] Issues with abundances of particular primers or a specific primer set are used to tag the corresponding cPT-QC samples plus all user samples of the same primer set as QC-failed.

Replicate Runs

[0064] As reproducibility is important for a QC of this type, replicate runs of the cPT-QC were performed. Relative abundances of 5 primers were compared employing the test of proportions.

Primer Perturbation Runs

[0065] To assess the usability of the cPT-QC to detect problems with primer performance, artificial perturbations of primer concentrations were created to simulate missing pipetting a primer or pipetting the wrong primer concentration.

[0066] First the 5 primer usage was analysed in a cPT-QC sample and two primers of differing abundances were selected from each primer set, thereby skipping the intron-Kde primer set, which only has two primers; IGH-VJ-FR1-M-1, IGH-V-FR1-O-1; IGH-D-B-1, IGH-D-E-1; IGK-V-G-1, IGK-V-I-1; TRB-V-AD-1, TRB-V-G-1; TRB-D-A-1, TRB-D-B-1; TRG-V-F-1, TRG-V-E-1; TRD-D-A-1, TRD-V-B-1. Those primers were perturbed by fully excluding them from the primer pool and changing their concentration by reduction to 10% and increase to 200%. Relative abundances of 5 primers were compared between these perturbed sets and cPT-QC employing the test of proportions.

Creation of a Test Dataset

[0067] A dataset was created to evaluate and showcase the aforementioned concepts and functionalities, which consists of the following samples: [0068] 1. Four diagnostic bone marrow B-/T-ALL samples with high leukemic cell content (leukemic infiltration assessed by routine cytomorphology to be 60-80%). [0069] 2. Four samples of patients with B/T cell aplasia after B/T cell targeted treatment. The two samples with B cell aplasia were CLL samples after Rituximab (anti-CD20) treatment and the two samples with T cell aplasia were T-PLL (prolymphocytic leukemia) samples after Alemtuzumab (anti-CD52) treatment. In all these samples lineage-specific aplasia was confirmed by flow cytometry. [0070] 3. cPT-QC for all IG/TR primer sets, but with the TRB-VJ primer set results swapped with perturbed results from validation experiments as outlined above. To showcase the generic QC functionalities, <1000 random reads from one of the diagnostic samples were artificially chosen.

Methodology

[0071] The diagnostic samples and the cPT-QC were run with all primer sets, while the aplastic follow-up samples were only run with the corresponding primer sets, i.e. the IG sets for samples with B cell aplasia, and the TR sets for samples with T cell aplasia (as depicted in FIG. 1; test dataset). Additionally, the follow-up samples were run without addition of buffy coat (BC) to test if the addition of the cIT-QC composition is sufficient to stabilise the samples for sequencing, without compromising their immunogenetic profile. To this end, the protocol visualised in FIG. 2 was followed.

Primer Performance Assessment Using the cPT-QC

[0072] The tests of proportions of 5 primer relative abundances, applied to the cPT-QC, BC, their replicates, and to the libraries with primer perturbations, showed that there is a clear difference in p-values between sets of un-perturbed and perturbed primers. In other words, the p-values of the differences in abundance of the perturbed primers are noticeably lower. Table 2 presents a simplified view of the results, focusing on the abundances of perturbed primers plus at least one other un-perturbed primer per primer set either to show their normal behavior or discuss their abnormal behavior. Percentage abundances of 5 primers across all primer sets. Top group of primers were perturbed; bottom group is a selection of primers that were left un-perturbed: one per primer set selected alphabetically, plus two examples where the primer behavior is of interest to the discussion (see text). Results are shown: in cPT-QC replicates (third column); against samples where primers were excluded (0%, fourth column), reduced to 10% (fifth column), increased to 200% (sixth column). Changes in percentages (indicated separately and as +/) that led to the test of proportions.

[0073] At a p-value threshold of 1e-200, none of the primers are flagged in the cPT-QC, which highlights the reproducibility of the assay, while all the perturbed primers are flagged in the perturbed scenarios. In fact, the lowest p-value in the normal samples is 7.86e-142 for primer TRD-V-A-1 (Table 2), compared to multiple zero values in the perturbed comparisons (with a few exceptions, mainly for the 200% perturbation). Significant changes in abundance were also visible in other cells, with the most likely explanation that those primers were indirectly affected by perturbations of other primers. That is, a primer taking over when an initially abundant primer was excluded, such as IGH-V-FR1-D-1 when IGH-VJ-FR1-M-1 is perturbed either way especially since these primers amplify partially overlapping lists of genes.

Evaluation of QC Aspects in ARResT/Interrogate

[0074] Information on the in silico quality control based on both the cPT-QC and cIT-QC is available in ARResT/Interrogate, with QC-failed samples excluded by default to warn and prevent the user from their unintended use. However, the user is notified and has the option to include them back in the analysis.

[0075] Generic quality control is also performed on samples, specifically to check for low number of raw reads and low percentage of reads with an identified junction. Such samples are also tagged as QC-failed.

TABLE-US-00002 TABLE 2 primers cPT-QC cPT-QC vs 0% cPT-QC vs 0% cPT-QC vs 200% primer set primer name rep1 <diff> rep2 <diff rep1 <diff rep1 <diff rep1 IGH-VJ-FR1 perturbed IGH-V-FR1-M-1 27.44 5.2 22.24 26.71 0.7297 25.42 2.017 +7.72 35.16 IGH-VJ-FR1 IGH-V-FR1-0-1 1.184 0.089 1.095 1.121 0.06314 1.116 0.06792 +1.681 2.865 IGH-DJ IGH-D-B-1:#1:14C 7.318 +0.12 7.438 7.318 0 7.271 0.0474 +7.152 14.47 IGH-DJ IGH-D-B-1:#2:14T 11.74 +0.48 12.22 11.74 0.0008552 11.65 0.08643 +11.48 23.22 IGH-DJ IGH-D-E-1:#4:14G22G 1.664 0.099 1.765 1.859 0.005364 1.853 0.01096 0.2 1.664 IGK-VJ-Kde IGK-V-G-1 8.08 +0.169 6.249 5.954 0.1259 5.911 0.169 +7.51 13.59 IGK-VJ-Kde IGK-V-I-1 8.648 +0.057 8.905 8.789 0.0588 8.495 0.3527 +11.86 20.71 TRB-VJ TRB-V-AD-1 31.76 +1.88 33.64 31.41 0.3514 28.86 4.905 +3.93 35.69 TRB-VJ TRB-V-G-1 10.09 0.515 9.575 10.06 0.02769 9.889 0.2006 +1.76 11.85 TRB-DJ TRB-D-A-1 63.2 +0.95 64.15 63.19 0.01025 48.89 14.31 +6.53 69.73 TRB-DJ TRB-D-B-1 36.14 1.36 34.78 36.06 0.0784 33.22 2.919 +12.71 48.85 TRD TRD-V-B-1 12.55 +2.33 14.88 12.49 0.06142 12.14 0.4108 +30.74 43.29 TRD TRB-D-A-1 84.8 +8.36 70.96 64.51 0.0914 62.44 2.182 7.41 57.19 TRG TRG-V-E-1 3.515 0.113 3.402 3.512 0.003061 3.455 0.05982 +5.547 9.062 TRG TRG-V-F-1 14.48 0.08 14.4 14.37 0.1087 14.45 0.02861 +9.05 23.53 IGH-VJ-FR1 IGH-V-FR1-A-1 15.34 +1.7 17.04 0.89 14.45 3.65 11.69 +7.41 22.75 IGH-VJ-FR1 IGH-V-FR1-D-1 16.41 1.62 14.79 +26.18 42.59 +22.64 39.05 9.999 6.411 IGH-DJ IGH-D-A-1:#1:6C 8.291 +1.512 9.803 +1.779 10.07 +1.258 9.549 0.508 7.783 IGK-VJ-Kde IGK-V-A-1 9.787 +0.08 9.867 +3.863 13.65 +3.403 13.19 +0.147 9.934 TRB-VJ TRB-V-AB-1 1.423 +0.054 1.477 +1.48 2.903 +0.517 1.94 0.069 1.354 TRD TRD-V-A-1 14.37 7.114 7.256 +9.44 23.81 +8.12 22.49 4.508 9.862 TRG TRG-V-A-1 18.71 +1.7 20.41 +3.06 21.77 +1.9 20.61 2.63 16.08 cPT-QC: replicates and primer perturbations. all numbers % abundances; rep: replicate; test of productions vs cPT-QC rep1, dark grey: <1e199, light grey: <1e99

Example 3: Marker Identification & Quantification

[0076] Abundances of lymphocyte subpopulations are frequently not available for samples of patients with lymphoid malignancies. Furthermore, as IG/TR NGS only reflects relative representation of the rearrangements, it was important to establish a calibrator, which would allow to normalise sequencing reads to input DNA cells. This is particularly important for tubes that exclusively cover rearrangements being present only in a minority of lymphoid cells (especially the TRD and intron-Kde tubes). TRD genes are not rearranged in normal B cells and are deleted in most TR cells. Therefore, oligoclonal TCR T-cells might give rise to dominant clonotypes in the TRD NGS assay, in particular as the normal TCR T cell repertoire is strikingly skewed during childhood. Here the cIT-QC-based abundance correction is of utmost importance to avoid miss-assignment of (minor) clonal TRD rearrangements from minor TCR cell populations as leukemic rearrangements that would then serve as markers in further MRD analysis.

[0077] Analysis of the test dataset showed the utility of the cIT-QC in marker identification and quantification. Without the cIT-QC, both diagnostic and aplastic samples seem to be oligoclonal if simply based on the number of reads (FIG. 3). However, the very high number of reads from only a very limited number of cIT-QC cells (120-440, dependent on number of cIT-QC rearrangements per primer set), in all aplastic and a few of the diagnostic samples, are an indirect, yet clear indication of the restricted numbers of patient-related input cells harbouring rearrangements of the particular IG/TR locus in those samples. From another perspective, the total read percentage of cIT-QC is much greater than those of rearrangements in these samples, suggesting that also the number of cIT-QC cells is greater than the number of patient-related input cells. Indeed, after quantification with the cIT-QC, cell abundances fall well below the thresholds implying clonality.

[0078] On the other hand, and as expected, in the diagnostic samples cIT-QC sequences constitute a minority. Hence, this implies that with the cIT-QC the abundance of a certain rearrangement can much more accurately be determined and recalculated to cell abundances.

[0079] Additionally, five experienced EuroMRD ALL reference laboratories performed IG/TR NGS in 50 diagnostic ALL samples, and compared results with those generated through routine IG/TR Sanger sequencing. A cPT-QC composition was used to monitor primer performance, and a cIT-QC composition was spiked into each sample as a library-specific quality control and calibrator. NGS identified 259 (average 5.2/sample, range 0-14) clonal sequences vs. Sanger-sequencing 248 (average 5.0/sample, range 0-14). The overall concordance between Sanger and NGS, including negative libraries, was 78%.

Example 4: Development and Multicentre Validation of IG/TR NGS Assays for MRD Marker Identification in ALL

[0080] This example describes the development and design of an IG/TR assay, including bioinformatics, and its validation for MRD marker identification in acute lymphoblastic leukemia (ALL). Five EuroMRD ALL MRD reference laboratories performed IG/TR NGS in 50 diagnostic ALL samples, and compared results with those generated through routine IG/TR marker screening and Sanger sequencing. A cPT-QC composition was used to monitor primer performance, and a cIT-QC composition was spiked into each sample as a library-specific quality control and calibrator. The overall workflow of the validation study is shown in FIG. 4.

Materials and Methods

General Concept of Assay Design

[0081] With the objective of developing a universal amplicon-based NGS approach for IG/TR sequence analysis at the DNA level, applicable in all lymphoid malignancies, assays for multiple IG/TR loci were designed for: IG heavy (IGH), IG kappa (IGK), TR beta (TRB), TR gamma (TRG), and TR delta (TRD), including complete and incomplete rearrangements whenever applicable. IG lambda (IGL) was excluded due to its limited complementarity to other IG loci and its reduced diversity. TR alpha (TRA) was excluded due to its high complexity, hampering a reasonable multiplex PCR approach at the DNA level.

[0082] The IGH locus is rearranged in two steps (FIG. 5A). After initial coupling of a single IGH-D gene to an IGH-J gene, an IGH-V gene is joined to the incomplete IGH-DJ rearrangement, resulting in a complete IGH-VJ rearrangement. For amplification of complete IGH rearrangements, primers located in the FR1, FR2 and FR3 regions were designed, but here we only describe the FR1 assay for marker identification in ALL. IGH-DJ rearrangements were amplified in a separate multiplex PCR reaction. The IGK light chain locus is composed of functional IGKV and IGKJ genes, as well as the so-called kappa deleting element (Kde) that can rearrange to IGKV genes, or to a recombination signal sequence (RSS) in the IGKJ-IGKC intron, leading to functional inactivation of the IGK allele (FIG. 5B). The IGKV forward primers were designed to be used in combination with IGKJ and Kde reverse primers in one multiplex reaction, whereas a second PCR was developed for the forward intron RSS and reverse Kde primers.

[0083] The TRB locus also features a two-step process with initial formation of incomplete TRB-DJ rearrangements followed by complete TRB-VJ rearrangements. Incomplete and complete TRB rearrangements were designed to be detected in two separate multiplex PCR reactions (FIG. 5C). As TRG locus rearrangements are one-step VJ recombinations involving a limited number of TRGV and TRGJ genes, a single multiplex assay could be developed (FIG. 5D). Finally, in the TRD locus, complete VJ rearrangements are preceded by DD, VD and DJ rearrangements. In addition, certain TRAV genes can rearrange to both TRDJ and TRAJ, whereas TRDV-TRAJ rearrangements, usually involving TRAJ29, can also occur. All of these rearrangements were designed to be amplified in one multiplex PCR assay (FIG. 5E). The bioinformatic platform ARResT/Interrogate.sup.43, already developed from the ground-up within the EuroClonality-NGS working group to assist with its multi-faceted activities, was further adapted for this study as described below.

Primer Design and Technical Validation of Primer Performance

[0084] Primers were designed to be gene-specific, but in case of allelic variants, degenerate primers were designed to facilitate multiplexing. For the same reason, single mismatches in the middle or at the 5-end of the primer were accepted. Table 3 shows the primer sequences comprising nucleotide sequences of FIG. 5 and additional adapter sequences (forward or reverse). Those of skill in the art will realize that the Example is only illustrative and that many variations of the specific methods of the Example are possible. For example, there is no need to use the M13 sequences as part of the primers as used in the Example. This could be replaced by any other known sequence of DNA.

TABLE-US-00003 TABLE3 Primersequencesforthe1.sup.stand2.sup.ndstepPCRinIG/TRNGS. 1.sup.ststep PCR Primer Primer Primersequencewithuniversalprimersequences tube nomenclature MinPCR direction attached(forward/reverse)5to3 TRBV-J TRB-V-C-1 0.00625M 5 GTAAAACGACGGCCAGTTCGCTTCTCACCTGAATGCCC TRB-V-A-1 0.0125M 5 GTAAAACGACGGCCAGTCTCAGTTGAAAGGCCTGATGGA TRB-V-X-1 0.0125M 5 GTAAAACGACGGCCAGTGGAAGCATCCCTGATCGATTCT TRB-V-AA-1 0.0125M 5 GTAAAACGACGGCCAGTTCAGCTAAGTGCCTCCCAAATT TRB-V-B-1 0.025M 5 GTAAAACGACGGCCAGTAGTTCCAAATCGCTTCTCACCT TRB-V-F-1 0.025M 5 GTAAAACGACGGCCAGTTTCCCTAATCGATTCTCAGGGC TRB-V-J-1 0.025M 5 GTAAAACGACGGCCAGTTACAACTGCCAAAGGAGAGGTC TRB-V-L-1 0.025M 5 GTAAAACGACGGCCAGTTAAAGGAGAAGTCCCGAATGGC TRB-V-M-1 0.025M 5 GTAAAACGACGGCCAGTGGAGAAGTTCCCAATGGCTACA TRB-V-S-1 0.025M 5 GTAAAACGACGGCCAGTATAAAGGAGAAGTCCCCGATGG TRB-V-W-1 0.025M 5 GTAAAACGACGGCCAGTCTCTAGATGATTCGGGGATGCC TRB-V-Z-1 0.025M 5 GTAAAACGACGGCCAGTTGAAGCAGACACCCCTGATAAC TRB-V-AE-1 0.025M 5 GTAAAACGACGGCCAGTTGAGCGATTTTTAGCCCAATGC TRB-V-AG-1 0.025M 5 GTAAAACGACGGCCAGTACAAAGGAGAGATCTCTGATGGA TRB-J-A-1 0.025M 3 TAATACGACTCACTATAGGGCTACAACTGTGAGTCTGGTGCC TRB-J-B-1 0.025M 3 TAATACGACTCACTATAGGGCTACAACGGTTAACCTGGTCC TRB-J-C-1 0.025M 3 TAATACGACTCACTATAGGGTACAACAGTGAGCCAACTTCCC TRB-J-D-1 0.025M 3 TAATACGACTCACTATAGGGCAAGACAGAGAGCTGGGTTCC TRB-J-E-1 0.025M 3 TAATACGACTCACTATAGGGCTAGGATGGAGAGTCGAGTCCC TRB-J-F-1 0.025M 3 TAATACGACTCACTATAGGGCTGTCACAGTGAGCCTGGTC TRB-J-G-1 0.025M 3 TAATACGACTCACTATAGGGCCTTCTTACCTAGCACGGTGAG TRB-J-H-1 0.025M 3 TAATACGACTCACTATAGGGTTACCCAGTACGGTCAGCCTAG TRB-J-I-1 0.025M 3 TAATACGACTCACTATAGGGCTTACCGAGCACTGTCAGCC TRB-J-J-1 0.025M 3 TAATACGACTCACTATAGGGCTTACCCAGCACTGAGAGCC TRB-J-K-1 0.025M 3 TAATACGACTCACTATAGGGTCACCGAGCACCAGGAGCC TRB-J-N-1 0.025M 3 TAATACGACTCACTATAGGGGAATCTCACCTGTGACCGTGAG TRB-V-D-1 0.05M 5 GTAAAACGACGGCCAGTGGAAACTTCCCTGGTCGATTC TRB-V-N-1 0.05M 5 GTAAAACGACGGCCAGTCAACGATCGGTTCTTTGCAGTC TRB-V-O-1 0.05M 5 GTAAAACGACGGCCAGTTAAATCAGGGCTGCTCAGTGAT TRB-V-P-1 0.05M 5 GTAAAACGACGGCCAGTCAGTGATCGGTTCTCTGCAGAG TRB-V-R-1 0.05M 5 GTAAAACGACGGCCAGTCTTGAACGATTCTCCGCACAAC TRB-V-V-1 0.05M 5 GTAAAACGACGGCCAGTCCGAGGATCGATTCTCAGCTAA TRB-V-AB-1 0.05M 5 GTAAAACGACGGCCAGTGCCAAAGGAACGATTTTCTGCT TRB-V-AI-1 0.05M 5 GTAAAACGACGGCCAGTAGGGAGATGTTCCTGAAGGGTA TRB-V-AJ-1 0.05M 5 GTAAAACGACGGCCAGTCCTGAGGGGTACAGTGTCTCTA TRB-V-AL-1 0.05M 5 GTAAAACGACGGCCAGTCAGAATCTCTCAGCCTCCAGAC TRB-V-E-1 0.1M 5 GTAAAACGACGGCCAGTACTTCCCTGATCGATTCTCAGC TRB-V-H-1 0.1M 5 GTAAAACGACGGCCAGTCTCAGGTCACCAGTTCCCTAAC TRB-V-I-1 0.1M 5 GTAAAACGACGGCCAGTCCTAGATTTTCAGGTCGCCAGT TRB-V-Q-1 0.1M 5 GTAAAACGACGGCCAGTCTCAACTAGACAAATCGGGGCT TRB-V-U-1 0.1M 5 GTAAAACGACGGCCAGTATCGATTTTCTGCAGAGAGGCT TRB-V-Y-1 0.1M 5 GTAAAACGACGGCCAGTCGGTATGCCCAACAATCGATTC TRB-V-AC-1 0.1M 5 GTAAAACGACGGCCAGTCTGAAGGGTACAGCGTCTCTC TRB-V-AH-1 0.1M 5 GTAAAACGACGGCCAGTTCCTCTGAGTCAACAGTCTCCA TRB-V-AK-1 0.1M 5 GTAAAACGACGGCCAGTCTGAGGCCACATATGAGAGTGG TRB-J-L-1 0.1M 3 TAATACGACTCACTATAGGGGAAAACTCACCCAGCACGGTC TRB-J-M-1 0.1M 3 TAATACGACTCACTATAGGGTCACCCAGCACGGTCAGCC TRB-V-G-1 0.15M 5 GTAAAACGACGGCCAGTGATTCTCAGGTCTCCAGTTCCC TRB-V-K-1 0.15M 5 GTAAAACGACGGCCAGTTACCACTGGCAAAGGAGAAGTC TRB-V-T-1 0.15M 5 GTAAAACGACGGCCAGTCAAAGGAGAAGTCTCAGATGGC TRB-V-AD-1 0.15M 5 GTAAAACGACGGCCAGTTTTCTCATCAACCATGCAAGCC TRB-V-AF-1 0.15M 5 GTAAAACGACGGCCAGTGGAGATGCACAAGAAGCGATTC TRBD-J TRB-J-A-1 0.025M 3 TAATACGACTCACTATAGGGCTACAACTGTGAGTCTGGTGCC TRB-J-B-1 0.025M 3 TAATACGACTCACTATAGGGCTACAACGGTTAACCTGGTCC TRB-J-C-1 0.025M 3 TAATACGACTCACTATAGGGTACAACAGTGAGCCAACTTCCC TRB-J-D-1 0.025M 3 TAATACGACTCACTATAGGGCAAGACAGAGAGCTGGGTTCC TRB-J-E-1 0.025M 3 TAATACGACTCACTATAGGGCTAGGATGGAGAGTCGAGTCCC TRB-J-F-1 0.025M 3 TAATACGACTCACTATAGGGCTGTCACAGTGAGCCTGGTC TRB-J-G-1 0.025M 3 TAATACGACTCACTATAGGGCCTTCTTACCTAGCACGGTGAG TRB-J-H-1 0.025M 3 TAATACGACTCACTATAGGGTTACCCAGTACGGTCAGCCTAG TRB-J-I-1 0.025M 3 TAATACGACTCACTATAGGGCTTACCGAGCACTGTCAGCC TRB-J-J-1 0.025M 3 TAATACGACTCACTATAGGGCTTACCCAGCACTGAGAGCC TRB-J-K-1 0.025M 3 TAATACGACTCACTATAGGGTCACCGAGCACCAGGAGCC TRB-J-N-1 0.025M 3 TAATACGACTCACTATAGGGGAATCTCACCTGTGACCGTGAG TRB-D-A-1 0.1M 5 GTAAAACGACGGCCAGTCCTCCACTCCCCTCAAAGGA TRB-D-B-1 0.1M 5 GTAAAACGACGGCCAGTCAGACTAACCTCTGCCACCTG TRB-J-L-1 0.1M 3 TAATACGACTCACTATAGGGGAAAACTCACCCAGCACGGTC TRB-J-M-1 0.1M 3 TAATACGACTCACTATAGGGTCACCCAGCACGGTCAGCC TRG TRG-V-E-1 0.05M 5 GTAAAACGACGGCCAGTCAAGCATGAGGAGGAGCTGGAAATTG TRG-V-F-1 0.05M 5 GTAAAACGACGGCCAGTACGTCTACATCCACTCTCACC TRG-V-A-1 0.1M 5 GTAAAACGACGGCCAGTGCACAAGGAACAACTTGAGATTG TRG-V-B-1 0.1M 5 GTAAAACGACGGCCAGTTGGAAGCACAAGGAAGAACTTGAGAA TRG-V-C-1 0.1M 5 GTAAAACGACGGCCAGTGCACAGGGAAGAGCCTTAAATT TRG-V-D-1 0.1M 5 GTAAAACGACGGCCAGTCAGGAGGTGGAGCTGGATATT TRG-V-G-1 0.1M 5 GTAAAACGACGGCCAGTCTCTCACTTCAATCCTTACCATCAA TRG-V-H-1 0.2M 5 GTAAAACGACGGCCAGTGCTCACACTTCCACTTCCACTTTGAAAATAAAGT TRG-J-A-1 0.2M 3 TAATACGACTCACTATAGGGAGTGTTGTTCCACTGCCAAAG TRG-J-B-1 0.2M 3 TAATACGACTCACTATAGGGGTTCCGGGACCAAATACCTTG TRG-J-C-1 0.2M 3 TAATACGACTCACTATAGGGGAGCTTAGTCCCTTCAGCAAATA TRG-J-D-1 0.2M 3 TAATACGACTCACTATAGGGCCTAGTCCCTTTTGCAAACG TRD TRD-V-A-1 0.2M 5 GTAAAACGACGGCCAGTGAATGCAAAAAGTGGTCGCTATTC TRD-V-B-1 0.2M 5 GTAAAACGACGGCCAGTTGCAAAGAACCTGGCTGTACT TRD-V-C-1 0.2M 5 GTAAAACGACGGCCAGTTGCAGATTTTACTCAAGGACGG TRD-V-D-1 0.2M 5 GTAAAACGACGGCCAGTGCAAAATGCAACAGAAGGTCG TRD-V-E-1 0.2M 5 GTAAAACGACGGCCAGTGATAAAAATGAAGATGGAAGATTCACTGT TRD-V-F-1 0.2M 5 GTAAAACGACGGCCAGTCTCCTTCAATAAAAGTGCCAAGC TRD-V-G-1 0.2M 5 GTAAAACGACGGCCAGTATTGAAAAGAAGTCAGGAAGACTAAGT TRD-V-H-1 0.2M 5 GTAAAACGACGGCCAGTTCCAGAAAGCAGCCAAATCC TRD-D-A-1 0.2M 5 GTAAAACGACGGCCAGTAGGGGTATTGTGGATGGCAG TRD-J-A-1 0.2M 3 TAATACGACTCACTATAGGGTTCCACAGTCACACGGGT TRD-J-B-1 0.2M 3 TAATACGACTCACTATAGGGGGTTCCACGATGAGTTGTGTT TRD-J-C-1 0.2M 3 TAATACGACTCACTATAGGGCACGAAGAGTTTGATGCCAGT TRD-J-D-1 0.2M 3 TAATACGACTCACTATAGGGGTTGTTGTACCTCCAGATAGGTT TRD-J-E-1 0.2M 3 TAATACGACTCACTATAGGGTGGCTAGAAACACTTACTTGCA TRD-D-B-1 0.2M 3 TAATACGACTCACTATAGGGCCCAGGGAAATGGCACTTTTG IGHD-J IGH-D-A-1 0.2M 5 GTAAAACGACGGCCAGTGATTCYGAACAGCCCCGAGTCA IGH-D-B-1 0.2M 5 GTAAAACGACGGCCAGTGATTTTGTGGGGGYTCGTGTC IGH-D-C-1 0.2M 5 GTAAAACGACGGCCAGTGTTTGRRGTGAGGTCTGTGTCA IGH-D-D-1 0.2M 5 GTAAAACGACGGCCAGTGTTTRGRRTGAGGTCTGTGTCACT IGH-D-E-1 0.2M 5 GTAAAACGACGGCCAGTCTTTTTGTGAAGGSCCCTCCTR IGH-D-F-1 0.2M 5 GTAAAACGACGGCCAGTGTTATTGTCAGGSGRTGTCAGAC IGH-D-G-1 0.2M 5 GTAAAACGACGGCCAGTGTTATTGTCAGGGGGTGYCAGRC IGH-D-H-1 0.2M 5 GTAAAACGACGGCCAGTGTTTCTGAAGSTGTCTGTRTCAC IGH-J-A-1 0.4M 3 TAATACGACTCACTATAGGGCTTACCTGAGGAGACGGTGACC IGHV-J IGH-V-FR1-B- 0.1M 5 GTAAAACGACGGCCAGTGCAGTCTGGAGCAGAGGTGAAAA 1 IGH-V-FR1-E- 0.1M 5 GTAAAACGACGGCCAGTGAGGTGCAGCTGTTGGAGTC 1 IGH-V-FR1-G- 0.1M 5 GTAAAACGACGGCCAGTCAGTGGGGCGCAGGACTGTT 1 IGH-V-FR1-H- 0.1M 5 GTAAAACGACGGCCAGTCCAGGACTGGTGAAGCCTCC 1 IGH-V-FR1-K- 0.1M 5 GTAAAACGACGGCCAGTCCTCAGTGAAGGTTTCCTGCAAGG 1 IGH-V-FR1-L- 0.1M 5 GTAAAACGACGGCCAGTAAACCCACAGAGACCCTCACGCTGAC 1 IGH-V-FR1-M- 0.1M 5 GTAAAACGACGGCCAGTCTGGGGGGTCCCTGAGACTCTCCTG 1 IGH-V-FR1-N- 0.1M 5 GTAAAACGACGGCCAGTCTTCACAGACCCTGTCCCTCACCTG 1 IGH-V-FR1-O- 0.1M 5 GTAAAACGACGGCCAGTTCGCAGACCCTCTCACTCACCTGTG 1 IGH-J-A-1 0.1M 3 TAATACGACTCACTATAGGGCTTACCTGAGGAGACGGTGACC IGH-J-B-1 0.1M 3 TAATACGACTCACTATAGGGCTCACCTGAGGAGACGGTGACC IGH-V-FR1-A- 0.2M 5 GTAAAACGACGGCCAGTCTGGGGCTGAGGTGAAGAAG 1 IGH-V-FR1-C- 0.2M 5 GTAAAACGACGGCCAGTTCACCTTGAAGGAGTCTGGTCC 1 IGH-V-FR1-D- 0.2M 5 GTAAAACGACGGCCAGTAGGTGCAGCTGGTGGAGTC 1 IGH-V-FR1-F- 0.2M 5 GTAAAACGACGGCCAGTCCAGGACTGGTGAAGCCTTC 1 IGH-V-FR1-I- 0.2M 5 GTAAAACGACGGCCAGTGTACAGCTGCAGCAGTCAGG 1 IGH-V-FR1-J- 0.2M 5 GTAAAACGACGGCCAGTGCTGGTGCAATCTGGGTCTG 1 IGK-A IGK-V-A-1 0.1M 5 GTAAAACGACGGCCAGTAAGTGGGGTCCCATCAAGGTTCAG IGK-V-B-1 0.1M 5 GTAAAACGACGGCCAGTAGTCCCATCTCGGTTCAGTGGCAG IGK-V-C-1 0.1M 5 GTAAAACGACGGCCAGTGAAACAGGGGTCCCATCAAGGTTC IGK-V-D-1 0.1M 5 GTAAAACGACGGCCAGTTCCCAGACAGATTCAGTGGCAGTG IGK-V-E-1 0.1M 5 GTAAAACGACGGCCAGTCTGGAGTGCCAGATAGGTTCAGTG IGK-V-F-1 0.1M 5 GTAAAACGACGGCCAGTCCCTGGAGTCCCAGACAGGTTCAG IGK-V-G-1 0.1M 5 GTAAAACGACGGCCAGTGCATCCCAGCCAGGTTCAGTG IGK-V-H-1 0.1M 5 GTAAAACGACGGCCAGTGTCCCTGACCGATTCAGTGGCA IGK-V-I-1 0.1M 5 GTAAAACGACGGCCAGTAATCCCACCTCGATTCAGTGGC IGK-V-J-1 0.1M 5 GTAAAACGACGGCCAGTCTCAGGGGTCCCCTCGAGGTT IGK-V-K-1 0.1M 5 GTAAAACGACGGCCAGTAGACACTGGGGTCCCAGCCA IGK-DE-A-1 0.1M 3 TAATACGACTCACTATAGGGGCAGCTGCAGACTCATGAGGAG IGk-J-A-1 0.1M 3 TAATACGACTCACTATAGGGACGTTTGATCTCCACCTTGGTCCC IGK-J-B-1 0.1M 3 TAATACGACTCACTATAGGGACGTTTGATATCCACTTTGGTCCC IGK-J-C-1 0.1M 3 TAATACGACTCACTATAGGGACGTTTAATCTCCAGTCGTGTCCC IGK-B IGK-INTR-A-1 0.1M 5 GTAAAACGACGGCCAGTGAGTGGCTTTGGTGGCCATGC IGK-DE-A-1 0.1M 3 TAATACGACTCACTATAGGGCAGCTGCAGACTCATGAGGAG 2.sup.nd step Primer Primer BarcodedprimersequencewithM13adapter PCR nomenclature MinPCR direction (forward/reverse)5to3 forward Ill-D501-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACTATAGCCTACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT Ill-D502-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACATAGAGGCACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT Ill-D503-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACCCTATCCTACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT Ill-D504-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACGGCTCTGAACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT Ill-D505-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACAGGCGAAGACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT Ill-D506-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACTAATCTTAACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT Ill-D507-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACCAGGACGTACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT Ill-D508-F 0.2M 5 AATGATACGGCGACCACCGAGATCTACACGTACTGACACACTCTTTCCCTACACGACGCTCTTCCGATCTGTAAAACGACGGCCAGT reverse Ill-D701-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATCGAGTAATGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D702-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATTCTCCGGAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D703-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATAATGAGCGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D704-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATGGAATCTCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D705-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATTTCTGAATGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D706-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATACGAATTCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D707-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATAGCTTCAGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D708-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATGCGCATTAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D709-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATCATAGCCGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D710-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATTTCGCGGAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D711-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATGCGCGAGAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG Ill-D712-R 0.2M 3 CAAGCAGAAGACGGCATACGAGATCTATCGCTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTAATACGACTCACTATAGGG

[0085] Primer3.sup.31, Primer Digital (PrimerDigital Ltd, Helsinki, Finland) MFEprimer-2.0.sup.32 and Oligo (Molecular Biology Insights, Inc., Colorado, USA) were used for checking primer specificity and multiplexing. Primer design criteria were followed for all loci: primer melting temperature 57-63 C.; comparable size of final amplicon; primer length 20-24 nt; avoidance of primer dimers; minimal distance of 3primer end to the junctional region of, preferably, >10-15 bp to avoid false negativity for rearrangements with larger nucleotide deletions from the germline sequence; avoidance of regions with known single nucleotide polymorphisms to allow identical primer annealing for all alleles of the respective V, D or J genes; targeting of, preferably, all V, D and J genes known to be rearranged plus the intronRSS and Kde regions for IGK.

[0086] Following in silico design, primers were first tested in monoplex and multiplex reactions using primary patient samples or cell lines with defined rearrangements. In occasional cases where no such samples were available, healthy tonsil or mononuclear DNA samples were employed. Oligoclonal template pools were then created from mixtures of rearranged cell lines and diagnostic samples with defined rearrangements covering many different V, D and/or J genes. Alternatively, for some loci, plasmid pools were produced, covering as many different rearrangements as possible. These multi-target pools allowed fine-tuning of reaction conditions and/or primer concentrations to assess comparable amplification efficiencies. This iterative process of testing also led to a reduction of primers if these appeared redundant. Further multicentre testing was performed with a limited number of monoclonal and poly/oligoclonal samples and on different sequencing platforms, which allowed assessment of robustness of the primer mixes and protocols.

[0087] Since the assays were designed with the aim to be platform-independent, a two-step PCR was employed, enabling to switch the sequencing adaptors and to reduce the total number of primers even if a large number of barcodes is necessary. Also, maximal amplicon lengths were defined with respect to the possible maximal sequencing read lengths of current sequencers. PCR conditions were optimized with the aim to find optimal conditions common for all reactions, thus allowing for parallel library preparation. Various numbers of PCR cycles in 1.sup.st and 2.sup.nd PCR, different polymerases and several library purification methods were tested and compared.

[0088] Although this study was exclusively performed on the Illumina MiSeq, the applicability of the same PCR panel on the IonTorrent instrument (ThermoFischer Scientific) was tested in a single-centre setting and a one-step Illumina MiSeq PCR approach was also tested in a single-center setting.

Multicentre Validation of Assays for MRD Marker Identification in ALL

[0089] Five experienced EuroClonality-NGS laboratories tested the robustness and applicability of the optimized assays for IG/TR marker identification in ALL in comparison to standard techniques. All laboratories (Bristol/London, Paris, Monza, Prague and Kiel) are members of the EuroMRD consortium and reference laboratories for ALL MRD analysis. Each of the participating laboratories performed NGS-based IG/TR MRD marker identification in 10 patients with B- or T-lineage ALL. A central standard operating procedure was strictly followed by all laboratories. The study was executed using the Illumina MiSeq (2250 bp v2 kit). NGS analyses were performed fully in parallel to conventional PCR plus Sanger sequencing of clonal products following standard guidelines.sup.11. For a part of the cases with unexplained discrepant results between the two methods, allele-specific PCR assays (either for digital droplet PCR or real-time quantitative PCR) were designed to clarify if the respective clonal rearrangement represented the leukemic bulk. EuroMRD guidelines were used to design and interpret allele-specific PCR assays.sup.33,34.

Results

Primer Design and Technical Validation of Primer Performance

[0090] Based on the results of the testing and validation phases, the final IG/TR primer mixes consist of eight tubes with 92 forward and 30 reverse primers, 15 of the latter being used in pairs of different tubes). Primer positions and sequences are presented in FIG. 5 and Table 3.

Implementation of Quality Control Compositions

[0091] Quality control of robust amplification, library preparation and sequencing are of utmost importance for these complex assays. Different primers need to work under the same reaction conditions, while additional variability can be introduced by sample characteristics and sequencing. Primer performance has to be monitored longitudinally, and for the exact estimation of clonal abundance it is important to correct for the number of sequencing reads per input molecule.

[0092] To address these issues, two types of quality control compositions were included: (i) the cIT-QC of Example 1 was spiked to each tube as library control and calibrator, and (ii) the cPT-QC of Example 2 was run in parallel to monitor general primer performance and sequencing.

Laboratory Protocol

[0093] Primers were tailed with universal and T7-linker sequences, and divided over eight tubes (IGH-VJ, IGH-DJ, IGK-VJ-Kde, intron-Kde, TRB-VJ, TRB-DJ, TRG, TRD). The PCR protocol is summarized in Table 4. Sequencing libraries were prepared via a two-step PCR, each using a final reaction volume of 50 l with 100 ng diagnostic DNA and 10 ng of polyclonal DNA. For the cIT-QC, genomic DNA of 40 cell equivalents of each the 9 different cell lines were spiked into all samples. MgCl.sub.2 was intended to be used at a final concentration of 1.5 mM, but needed optimization for some tubes. Therefore, master-mixes for the 1.sup.st PCR were tube-specific, but the temperature profile was uniform for all tubes.

[0094] After the 1.sup.st round of PCR, gel electrophoresis was performed to check for the successful amplification of all targets. For TRB, gel extraction of the specific PCR products was performed prior to the 2.sup.nd PCR.

[0095] All first round PCR products, except for TRB, the PCR products were diluted 1:50 unless amplicons were very weak. The TRB PCR products and PCR products with weak amplicons were used undiluted. Master-mixes for the 2.sup.nd PCR and the temperature profiles were identical for all tubes (Table 4). Primers for the 2.sup.nd PCR contained sequencing adaptors and sequencing indexes (barcodes). Unique combination of forward and reverse indexes was used for each library. Three l of undiluted TRB PCR products and 1 l of 1:50-diluted IGH, IGK, TRG, and TRD PCR products were amplified in the 2.sup.nd PCR.

TABLE-US-00004 TABLE 4 Standardized PCR protocol. (A) Reaction conditions of 1.sup.st and 2.sup.nd PCR. (B) PCR Cycling conditions. A 1.sup.st PCR IGK-VJ-Kde, IGH-VJ IGH-DJ Intron-Kde TRS-VJ, TRB-DJ TRG TRD Stock Final Final Final Final Final Final concen- concen- concen- concen- concen- concen- concen- tration tration tration tration tration tration tration PCR Buffer 10x 1x 5 1x 5 1x 5 1x 5 1x 5 1x 5 MgCl2 25 mM 2.5 mM 5 3 mM 6 1.5 mM 3 4 mM 8 4 mM 8 2 mM 4 dNTP-Mix 10 mM 0.2 mM 1 0.4 mM 2.0 0.2 mM 1 0.2 mM 1 0.2 mM 1 0.2 mM 1 EagleTaq/AmpliTaq 5 1 0.2 1.5 0.3 1 0.2 1 0.2 1 0.2 1 0.8 Gold Reaction volume: 50 l 2.sup.nd PCR Stock Final concentration concentration l/sample PCR Buffer with 10x 1x 5 MgCl2 18 mM 1.8 mM 0 dNTP-Mix 10 mM 0.2 mM 1 Fast Start High 5 2.5 0.5 Fidelity polymerase Reaction volume: 50 l B 1.sup.st PCR 2.sup.nd PCR initial initial denaturation 94 C. 10 min denaturation 95 C. 2 min 35 denaturation 94 C. 1 min 20 denaturation 94 C. 30 sec cycles annealing 63 C. 1 min cycles annealing 63 C. 30 sec extension 72 C. 30 sec extension 72 C. 30 sec final 72 C. 30 min final 72 C. 5 min extension extension 12 C. 12 C. indicates data missing or illegible when filed

[0096] Following 2.sup.nd PCR, products from all samples of a run were pooled in equimolar ratios into 8 tube-wise subpools and purified by gel-extraction (see Table 5 for the amplicon lengths). Finally, the subpools were pooled equimolarly into one final pool. Sequencing was performed on Illumina MiSeq sequencers, using 2250 bp v2 chemistry with a final concentration of 7 pM for the amplicon library and 10% PhiX control added to avoid low-complexity library issues.

TABLE-US-00005 TABLE 5 Mean size of PCR products after the 2.sup.nd PCR (containing the Illumina sequencing adaptors and barcodes). Amplicon length Gene (bp) TRB-VJ 309-407 TRB-DJ 300-408 TRG 256-360 TRD 309-450 IGH-VJ 484-681 IGH-DJ 266-358 IGK-VJ-Kde 296-384 intron-Kde 309-382

Bioinformatic Protocol

[0097] ARResT/Interrogate was the main bioinformatics platform used in this study, along with Vidjil.sup.47 and IMGT.sup.48 resources for specific aspects of this work. Demultiplexing was performed accepting no mismatches. Reads were annotated with EuroClonality-NGS primer sequences (to trim non-amplicon sequence, and for the cPT-QC-based quality control), paired-end joined, dereplicated, immunogenetically annotated.sup.48, and classified into rearrangement types (complete and incomplete, and other special types like intron-Kde rearrangements), or junction classes. Reads with no rearrangement were excluded from the total read count used for relative abundances.

[0098] cIT-QC sequences described above were identified in the data through their immunogenetic annotation. Their counts served both as in-tube control and for normalization per primer set: total cIT-QC cells are divided by cIT-QC total reads, the resulting factor used to convert rearrangement reads to cells, those cells divided by total input cells (15,000 in this example). Identified IG/TR sequences were defined as index sequences if abundance after cIT-QC normalisation exceeded 5%. ARResT/Interrogate can track the DNJ 3stem of a junction, the sequence remaining stable during IGH or TRB clonal evolution in case of V-replacement or ongoing V to DJ rearrangements. The stem consists of the last 3 nt of D (or of the NDN if no D is identifiable), any and all of N2 nucleotides, and the J nucleotides of the junction. This stem is available as a separate immunogenetic feature across all samples and thus able to link other features, e.g. clonotypes.

Multicentre Validation of Assays for MRD Marker Identification in ALL

[0099] Next, fifty ALL diagnostic samples (29 BCP-ALL and 21 T-ALL) were analysed for the multicentre validation study. Each of the five participating laboratories received preconfigured 96-well plates containing the different multiplexed NGS primer combinations per target (FIG. 4).

[0100] In summary, 96 libraries were generated per lab (total of 480 libraries), and sequenced with a total output of 47M reads (9.2M/lab). Centralised analysis was performed with ARResT/Interrogate.sup.43 using IMGT germline sequences.sup.48further analyses and verifications were performed with Vidjil.sup.47 and IMGT/V-QUEST.sup.48.

[0101] Overall, 311 clonal IG/TR rearrangements (clonotypes) were identified, with a mean of 5.9 (0-14)/sample by NGS (a 5% threshold was applied for NGS after cIT-QC-based normalization) vs. 5.0 (0-14)/sample by Sanger, while 217 (45%) libraries demonstrated no clonotypes above threshold by either method. A total of 196/311 (63%) clonotypes were fully concordant between NGS and Sanger (FIG. 6). NGS exclusively identified 63 index sequences, whereas 52 IG/TR Sanger sequences were not assigned as NGS index sequence by ARResT/Interrogate. 26 NGS pos/Sanger neg cases showed a clonal PCR product also in the respective low-throughput approach but subsequent Sanger sequencing failed due to polyclonal background, mixed sequences or weak PCR products. In an additional 6 Sanger neg/NGS pos cases, the respective primer was missing in the low-throughput approach. For the remaining 31 discrepancies no technical explanation for Sanger failure could be found (in 16/19 q/ddPCR evaluated cases the rearrangement was confirmed by ASO-PCR, in 3/16 on a subclonal level).

[0102] Conversely, 52 clonal IG/TR rearrangements were only detected by Sanger when the 5% NGS threshold was applied: for 5 sequences (1 TRG, 2 TRB-VJ, and 2 IGH-DJ) the relevant primer was not present in the NGS primer set, in 12 cases no explanation was found for the discrepancy. However, in the majority of discordant cases (35/52) the Sanger identified sequences (7 TRD, 8 TRB-VJ, 6 TRG, 4 TRB-DJ, 2 IGK-VJ-Kde, 5 IGH-VJ, 3 IGH-DJ) were also detectable by NGS, but with and abundance below 5%. In 36/39 q/ddPCR evaluated cases the rearrangement was confirmed by ASO-PCR, including all low NGS positive sequences, in 14/36 cases on a subclonal level. Overall concordance between Sanger and NGS, including negative libraries, was 78%.

[0103] In 12/29 B-lineage ALL samples the evolution of the dominant clonal IGH sequence was identified employing ARResT/Interrogate. The evolved clonotypes shared the DNJ stem with the dominant one, but the VND part of the rearrangement differed.

[0104] The assay performance was also analysed by standardized evaluation of QC samples (cIT-QC and cPT-QC). This showed a remarkably high intra- and inter-lab consistency without statistically significant differences between the five labs.

Suitable Modifications of the Central SOP for MRD Marker Identification

[0105] During the process of multicentre validation, suitable modifications of the SOP were tested in particular laboratories as parallel actions.

[0106] One-step versus two-step PCR: The EuroClonality-NGS working group decided to use two-step PCR to enable switching of sequencing adaptors and to limit the total number of required primer batches even if a large number of barcodes is necessary. As first round PCR products are not barcoded, identification of contamination phenomena is hampered in this approach. Therefore, a one-step PCR was tested in a single center (Paris) as an alternative for laboratories that are able to maintain higher numbers of different primer batches. The one-step approach reduces the risk of contamination and thus favours use of NGS not only for marker identification, but also for MRD assessment. The standard operating procedures are shown in supplementary information.

[0107] Bead extraction: In our single target evaluation and validation phase, gel extraction of the specific TRB amplicons turned out to lead to more specific libraries compared to bead extraction. However, gel extraction is not used in all laboratories, therefore, in a later phase of the study bead purification of all libraries was also tested. Optimization of the purification processes led to comparable ratios of specific reads irrespective of the type of library purification.

[0108] Withdrawal of addition of polyclonal DNA to reaction mix: Polyclonal DNA was added to each reaction in order to prevent excessive primer dimer formation in samples lacking particular rearrangements. The addition of polyclonal DNA, however, alters the composition of polyclonal background of the samples and hampers the analysis of the immune repertoire. We therefore performed testing on 4 samples with B and 4 samples with T cell aplasia and showed that addition of cIT-QC is sufficient to prevent the excessive formation of unspecific PCR products.

REFERENCES

[0109] 1 Tonegawa S. Somatic generation of antibody diversity. Nature 1983; 302: 575-581. [0110] 2 Davis M M, Bjorkman P J. T-cell antigen receptor genes and T-cell recognition. Nature 1988; 334: 395-402. [0111] 3 Schlissel M S. Regulating antigen-receptor gene assembly. Nat Rev Immunol 2003; 3: 890-899. [0112] 4 Lefranc M-P, Lefranc G. The T cell receptor factsbook. Academic Press, 2001. [0113] 5 Lefranc M-P, Lefranc G. The immunoglobulin factsbook. Academic Press, 2001. [0114] 6 Monroe J G, Dorshkind K. Fate Decisions Regulating Bone Marrow and Peripheral B Lymphocyte Development. In: Advances in immunology. 2007, pp 1-50. [0115] 7 von Boehmer H, Melchers F. Checkpoints in lymphocyte development and autoimmune disease. Nat Immunol 2010; 11: 14-20. [0116] 8 Evans P A S, Pott C, Groenen P J T A, Salles G, Davi F, Berger F et al. Significantly improved PCR-based clonality testing in B-cell malignancies by use of multiple immunoglobulin gene targets. Report of the BIOMED-2 Concerted Action BHM4-CT98-3936. Leukemia 2007; 21: 207-214. [0117] 9 Brggemann M, White H, Gaulard P, Garcia-Sanz R, Gameiro P, Oeschger S et al. Powerful strategy for polymerase chain reaction-based clonality assessment in T-cell malignancies Report of the BIOMED-2 Concerted Action BHM4 CT98-3936. Leukemia 2007; 21: 215-221. [0118] 10 Langerak A W, Groenen P J T A, Brggemann M, Beldjord K, Bellan C, Bonello L et al. EuroClonality/BIOMED-2 guidelines for interpretation and reporting of Ig/TCR clonality testing in suspected lymphoproliferations. Leukemia 2012; 26: 2159-2171. [0119] 11 van Dongen J J M, Langerak A W, Brggemann M, Evans P A, Hummel M, Lavender F L et al. Design and standardization of PCR primers and protocols for detection of clonal immunoglobulin and T-cell receptor gene recombinations in suspect lymphoproliferations: report of the BIOMED-2 Concerted Action BMH4-CT98-3936. Leukemia 2003; 17: 2257-2317. [0120] 12 Boyd S D, Marshall E L, Merker J D, Maniar J M, Zhang L N, Sahaf B et al. Measurement and clinical monitoring of human lymphocyte clonality by massively parallel VDJ pyrosequencing. Sci Transl Med 2009; 1: 12ra23. [0121] 13 DeKosky B J, Ippolito G C, Deschner R P, Lavinder J J, Wine Y, Rawlings B M et al. High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire. Nat Biotechnol 2013; 31: 166-169. [0122] 14 Freeman J D, Warren R L, Webb J R, Nelson B H, Holt R A. Profiling the T-cell receptor beta-chain repertoire by massively parallel sequencing. Genome Res 2009; 19: 1817-1824. [0123] 15 Gawad C, Pepin F, Carlton V E H, Klinger M, Logan A C, David B et al. Massive evolution of the immunoglobulin heavy chain locus in children with B precursor acute lymphoblastic leukemia Massive evolution of the immunoglobulin heavy chain locus in children with B precursor acute lymphoblastic leukemia. 2012; 120: 4407-4417. [0124] 16 Logan A C, Gao H, Wang C, Sahaf B, Jones C D, Marshall E L et al. High-throughput VDJ sequencing for quantification of minimal residual disease in chronic lymphocytic leukemia and immune reconstitution assessment. Proc Natl Acad Sci USA 2011; 108: 21194-21199. [0125] 17 Logan A C, Zhang B, Narasimhan B, Carlton V, Zheng J, Moorhead M et al. Minimal residual disease quantification using consensus primers and high-throughput IGH sequencing predicts post-transplant relapse in chronic lymphocytic leukemia. Leukemia 2013; 27: 1659-1665. [0126] 18 Robins H S, Srivastava S K, Campregher P V, Turtle C J, Andriesen J, Riddell S R et al. Overlap and Effective Size of the Human CD8+ T Cell Receptor Repertoire. Sci Transl Med 2010; 2: 47ra64-47ra64. [0127] 19 Wang C, Sanders C M, Yang Q, Schroeder H W, Wang E, Babrzadeh F et al. High throughput sequencing reveals a complex pattern of dynamic interrelationships among human T cell subsets. Proc Natl Acad Sci 2010; 107: 1518-1523. [0128] 20 Wu D, Sherwood A, Fromm J R, Winter S S, Dunsmore K P, Loh M L et al. High-throughput sequencing detects minimal residual disease in acute T lymphoblastic leukemia. Sci Transl Med 2012; 4: 134ra63. [0129] 21 Wu Y-C, Kipling D, Leong H S, Martin V, Ademokun A A, Dunn-Walters D K. High-throughput immunoglobulin repertoire analysis distinguishes between human IgM memory and switched memory B-cell populations. Blood 2010; 116: 1070-1078. [0130] 22 Bartram J, Goulden N, Wright G, Adams S, Brooks T, Edwards D et al. High throughput sequencing in acute lymphoblastic leukemia reveals clonal architecture of central nervous system and bone marrow compartments. Haematologica 2018; 103: e110-e114. [0131] 23 Faham M, Zheng J, Moorhead M, Carlton V E, Stow P, Coustan-Smith E et al. Deep-sequencing approach for minimal residual disease detection in acute lymphoblastic leukemia. Blood 2012; 120: 5173-5180. [0132] 24 Ladetto M, Bruggemann M, Monitillo L, Ferrero S, Pepin F, Drandi D et al. Next-generation sequencing and real-time quantitative PCR for minimal residual disease detection in B-cell disorders. Leukemia 2014; 28: 1299-1307. [0133] 25 Pulsipher M A, Carlson C, Langholz B, Wall D A, Schultz K R, Bunin N et al. IgH-V(D)J NGS-MRD measurement pre- and early post-allo-transplant defines very low and very high risk ALL patients. Blood 2015; 125: 3501-3508. [0134] 26 Kotrova M, Muzikova K, Mejstrikova E, Novakova M, Bakardjieva-Mihaylova V, Fiser K et al. The predictive strength of next-generation sequencing MRD detection for relapse compared with current methods in childhood ALL. Blood 2015; 126: 1045-7. [0135] 27 Langerak A W, Brggemann M, Davi F, Darzentas N, Gonzalez D, Cazzaniga G et al. High throughput immunogenetics for clinical and research applications in immunohematology: potential and challenges. J Immunol 2017; 198: 3765-3774. [0136] 28 Kotrova M, van der Velden V H J, van Dongen J J M, Formankova R, Sedlacek P, Brggemann M et al. Next-generation sequencing indicates false-positive MRD results and better predicts prognosis after SCT in patients with childhood ALL. Bone Marrow Transplant 2017; 52: 962-968. [0137] 29 Kotrova M, Trka J, Kneba M, Brggemann M. Is Next-Generation Sequencing the way to go for Residual Disease Monitoring in Acute Lymphoblastic Leukemia? Mol Diagn Ther 2017. doi:10.1007/s40291-017-0277-9. [0138] 30 Pott C. Minimal Residual Disease Detection in Mantle Cell Lymphoma: Technical Aspects and Clinical Relevance. Semin Hematol 2011; 48: 172-184. [0139] 31 Ferrero S, Drandi D, Mantoan B, Ghione P, Omed P, Ladetto M. Minimal residual disease detection in lymphoma and multiple myeloma: Impact on therapeutic paradigms. Hematol. Oncol. 2011; 29: 167-176. [0140] 32 Brggemann M, Gkbuget N, Kneba M. Acute Lymphoblastic Leukemia: Monitoring Minimal Residual Disease as a Therapeutic Principle. Semin Oncol 2012; 39: 47-57. [0141] 33 Brggemann M, Raff T, Kneba M. Has MRD monitoring superseded other prognostic factors in adult ALL? Blood 2012; 120: 4470-4481. [0142] 34 van Dongen J J M, Seriu T, Panzer-Grumayer E R, Biondi A, Pongers-Willemse M J, Corral L et al. Prognostic value of minimal residual disease in acute lymphoblastic leukaemia in childhood. Lancet 1998; 352: 1731-1738. [0143] 35 Brggemann M, Kotrova M. Minimal residual disease in adult ALL: technical aspects and implications for correct clinical interpretation. Hematol Am Soc Hematol Educ Progr 2017: 13-21. [0144] 36 Logan A C, Vashi N, Faham M, Carlton V, Kong K, Buo I et al. Immunoglobulin and t cell receptor gene high-throughput sequencing quantifies minimal residual disease in acute lymphoblastic leukemia and predicts post-transplantation relapse and survival. Biol Blood Marrow Transplant 2014; 20: 1307-1313. [0145] 37 Wren D, Walker B A, Brggemann M, Catherwood M A, Pott C, Stamatopoulos K et al. Comprehensive translocation and clonality detection in lymphoproliferative disorders by next-generation sequencing. Haematologica. 2017; 102: e57-e60. [0146] 38 Hardwick S A, Deveson I W, Mercer T R. Reference standards for next-generation sequencing. Nat. Rev. Genet. 2017; 18: 473-484. [0147] 39 Gargis A S, Kalman L, Lubin I M. Assuring the quality of next-generation sequencing in clinical microbiology and public health laboratories. J Clin Microbiol 2016; 54: 2857-2865. [0148] Endrullat C, Glkler J, Franke P, Frohme M. Standardization and quality management in next-generation sequencing. Appl. Transl. Genomics. 2016; 10: 2-9. [0149] 41 Kurtz D M, Green M R, Bratman S V., Scherer F, Liu C L, Kunder C A et al. Noninvasive monitoring of diffuse large B-cell lymphoma by immunoglobulin high-throughput sequencing. Blood 2015; 125: 3679-3687. [0150] 42 Pulsipher M A, Carlson C, Langholz B, Wall D A, Schultz K R, Bunin N et al. IgH-V(D) J NGS-MRD measurement pre- and early post-allotransplant defines very low- and very high-risk ALL patients. Blood 2015; 125: 3501-3509. [0151] 43 Bystry V, Reigl T, Krejci A, Demko M, Hanakova B, Grioni A et al. ARResT/Interrogate: an interactive immunoprofiler for IG/TR NGS data. Bioinformatics 2016; 33: btw634. [0152] 44 Grupp S A, Kalos M, Barrett D, Aplenc R, Porter D L, Rheingold S R et al. Chimeric Antigen Receptor-Modified T Cells for Acute Lymphoid Leukemia. N Engl J Med 2013; 368:1509-1518. [0153] 45 Tang M, Wang G, Kong S K, Ho HP4. A Review of Biomedical Centrifugal Microfluidic Platforms. Micromachines (Basel) 2016; 7: E26. [0154] 46 Langerak A W, Szczepaski T, Van Der Burg M, Wolvers-Tettero I L M, Van Dongen J J M. Heteroduplex PCR analysis of rearranged T cell receptor genes for clonality assessment in suspect T cell proliferations. Leukemia 1997; 11: 2192-2199. [0155] 47 Duez M, Giraud M, Herbert R, Rocher T, Salson M, Thonier F. Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing. PLoS One 2016; 11: e0166126. [0156] 48 Lefranc M P, Giudicelli V, Duroux P, Jabado-Michaloud J, Folch G, Aouinti S, Carillon E, Duvergey H, Houles A, Paysan-Lafosse T, Hadi-Saljoqi S, Sasorith S, Lefranc G, Kossida S. IMGT, the international ImMunoGeneTics information System 25 years on. Nucleic Acids Res 2015; 43: D413-22.