Digital PCR: A Reliable Tool for Analyzing and Monitoring Hematologic Malignancies

A highly integrated digital PCR system with on-chip heating for accurate DNA quantitative analysis

Digital polymerase chain reaction (dPCR) is extensively used for highly sensitive disease diagnosis due to its single-molecule detection ability. However, current dPCR systems require intricate DNA sample distribution, rely on cumbersome external heaters, and exhibit sluggish thermal cycling, hampering efficiency and speed of the dPCR process. Herein, we presented the development of a microwell array based dPCR system featuring an integrated self-heating dPCR chip. By utilizing hydrodynamic and electrothermal simulations, the chip's structure is optimized, resulting in improved partitioning within microwells and uniform thermal distribution. Through strategic hydrophilic/hydrophobic modifications on the chip's surface, we effectively secured the compartmentalization of sample within the microwells by employing an overlaying oil phase, which renders homogeneity and independence of samples in the microwells. To achieve precise, stable, uniform, and rapid self-heating of the chip, the ITO heating layer and the temperature control algorithm are deliberately designed. With a capacity of 22,500 microwells that can be easily expanded, the system successfully quantified EGFR plasmid solutions, exhibiting a dynamic linear range of 105 and a detection limit of 10 copies per reaction. To further validate its performance, we employed the dPCR platform for quantitative detection of BCR-ABL1 mutation gene fragments, where its performance was compared against the QuantStudio 3D, and the self-heating dPCR system demonstrated similar analytical accuracy to the commercial dPCR system. Notably, the individual chip is produced on a semiconductor manufacturing line, benefiting from mass production capabilities, so the chips are cost-effective and conducive to widespread adoption and accessibility.

Measurable residual disease monitoring by ddPCR in the early posttransplant period complements the traditional MFC method to predict relapse after HSCT in AML/MDS: a multicenter retrospective study

BACKGROUND

Droplet digital PCR (ddPCR) is widely applied to monitor measurable residual disease (MRD). However, there are limited studies on the feasibility of ddPCR-MRD monitoring after allogeneic hematopoietic stem cell transplantation (allo-HSCT), especially targeting multiple molecular markers simultaneously.

METHODS

Our study collected samples from patients with acute myeloid leukemia (AML) or high-risk myelodysplastic syndrome (MDS) in complete remission after allo-HSCT between January 2018 and August 2021 to evaluate whether posttransplant ddPCR-MRD monitoring can identify patients at high risk of relapse.

RESULTS

Of 152 patients, 58 (38.2%) were MRD positive by ddPCR within 4 months posttransplant, with a median variant allele frequency of 0.198%. The detectable DTA mutations (DNMT3A, TET2, and ASXL1 mutations) after allo-HSCT were not associated with an increased risk of relapse. After excluding DTA mutations, patients with ddPCR-MRD positivity had a significantly higher cumulative incidence of relapse (CIR, 38.7% vs. 9.7%, P < 0.001) and lower rates of relapse-free survival (RFS, 55.5% vs. 83.7%, P < 0.001) and overall survival (OS, 60.5% vs. 90.5%, P < 0.001). In multivariate analysis, ddPCR-MRD positivity of non-DTA genes was an independent adverse predictor for CIR (hazard ratio [HR], 4.02; P < 0.001), RFS (HR, 2.92; P = 0.002) and OS (HR, 3.12; P = 0.007). Moreover, the combination of ddPCR with multiparameter flow cytometry (MFC) can further accurately identify patients at high risk of relapse (F+/M+, HR, 22.44; P < 0.001, F+/M-, HR, 12.46; P < 0.001 and F-/M+, HR, 4.51; P = 0.003).

CONCLUSION

ddPCR-MRD is a feasible approach to predict relapse after allo-HSCT in AML/MDS patients with non-DTA genes and is more accurate when combined with MFC.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT06000306. Registered 17 August 2023 -Retrospectively registered ( https://clinicaltrials.gov/study/NCT06000306?term=NCT06000306&rank=1 ).

Benchmarking digital PCR partition classification methods with empirical and simulated duplex data

Digital PCR (dPCR) is a highly accurate technique for the quantification of target nucleic acid(s). It has shown great potential in clinical applications, like tumor liquid biopsy and validation of biomarkers. Accurate classification of partitions based on end-point fluorescence intensities is crucial to avoid biased estimators of the concentration of the target molecules. We have evaluated many clustering methods, from general-purpose methods to specific methods for dPCR and flowcytometry, on both simulated and real-life data. Clustering method performance was evaluated by simulating various scenarios. Based on our extensive comparison of clustering methods, we describe the limits of these methods, and formulate guidelines for choosing an appropriate method. In addition, we have developed a novel method for simulating realistic dPCR data. The method is based on a mixture distribution of a Poisson point process and a skew-$t$ distribution, which enables the generation of irregularities of cluster shapes and randomness of partitions between clusters ('rain') as commonly observed in dPCR data. Users can fine-tune the model parameters and generate labeled datasets, using their own data as a template. Besides, the database of experimental dPCR data augmented with the labeled simulated data can serve as training and testing data for new clustering methods. The simulation method is available as an R Shiny app.

Applications of Digital Polymerase Chain Reaction (dPCR) in Molecular and Clinical Testing

BACKGROUND

Digital polymerase chain reaction (dPCR) is an accurate and sensitive molecular method that can be used in clinical diagnostic, prognostic, and predictive tests. The key component of the dPCR method is the partitioning of a single reaction into many thousands of droplets, nanochannels or other nano- or picoliter-sized reactions. This results in high enough sensitivity to detect rare nucleic acid targets and provides an absolute quantification of target sequences or alleles compared to other PCR-based methods.

CONTENT

An increasing number of dPCR platforms have been introduced commercially in recent years and more are being developed. These platforms differ in the method of partitioning, degree of automation, and multiplexing capabilities but all can be used in similar ways for sensitive and highly accurate quantification of a variety of nucleic acid targets. Currently, clinical applications of dPCR include oncology, microbiology and infectious disease, genetics, and prenatal/newborn screening. Commercially available tests for clinical applications are being developed for variants with diagnostic, prognostic, and therapeutic significance in specific disease types.

SUMMARY

The power of dPCR technology relies on the partitioning of the reactions and results in increased sensitivity and accuracy compared to qPCR. More recently, the sensitivity of dPCR has been applied to the detection of known variants in cell-free DNA and circulating tumor DNA. Future clinical applications of dPCR include liquid biopsy, treatment resistance detection, screening for minimal residual disease, and monitoring allograft engraftment in transplanted patients.

Nucleic Acid Based Testing (NABing): A Game Changer Technology for Public Health

Timely and accurate detection of the causal agent of a disease is crucial to restrict suffering and save lives. Mere symptoms are often not enough to detect the root cause of the disease. Better diagnostics applied for screening at a population level and sensitive detection assays remain the crucial component of disease surveillance which may include clinical, plant, and environmental samples, including wastewater. The recent advances in genome sequencing, nucleic acid amplification, and detection methods have revolutionized nucleic acid-based testing (NABing) and screening assays. A typical NABing assay consists of three modules: isolation of the nucleic acid from the collected sample, identification of the target sequence, and final reading the target with the help of a signal, which may be in the form of color, fluorescence, etc. Here, we review current NABing assays covering the different aspects of all three modules. We also describe the frequently used target amplification or signal amplification procedures along with the variety of applications of this fast-evolving technology and challenges in implementation of NABing in the context of disease management especially in low-resource settings.

Digital PCR Partition Classification

BACKGROUND

Partition classification is a critical step in the digital PCR data analysis pipeline. A range of partition classification methods have been developed, many motivated by specific experimental setups. An overview of these partition classification methods is lacking and their comparative properties are often unclear, likely impacting the proper application of these methods.

CONTENT

This review provides a summary of all available digital PCR partition classification approaches and the challenges they aim to overcome, serving as a guide for the digital PCR practitioner wishing to apply them. We additionally discuss strengths and weaknesses of these methods, which can further guide practitioners in vigilant application of these existing methods. This review provides method developers with ideas for improving methods or designing new ones. The latter is further stimulated by our identification and discussion of application gaps in the literature, for which there are currently no or few methods available.

SUMMARY

This review provides an overview of digital PCR partition classification methods, their properties, and potential applications. Ideas for further advances are presented and may bolster method development.

Clinical Impact of JAK2V617F Allele Burden in Philadelphia-Negative Myeloproliferative Neoplasms

Objective

The impact of JAK2V617F allele burden on clinical course in Philadelphia-negative (Ph-negative) myeloproliferative neoplasms (MPNs) is not clear. We analyzed the clinical impact of JAK2V617F allele burden in a relatively large series of patients with Ph-negative MPNs and long-term follow-up.

Materials and Methods

A total of 228 patients with Ph-negative MPNs, including 118 with essential thrombocythemia (ET), 84 with primary myelofibrosis (PMF), and 26 with polycythemia vera (PV), were analyzed. The JAK2 MutaScreen assay was used to quantify JAK2V617F allele burden in genomic DNA.

Results

In PV cases, high JAK2V617F allele burden was associated with a trend towards inferior overall survival. In ET, high JAK2V617F allele burden was associated with lower hemoglobin and hematocrit levels, higher lactate dehydrogenase (LDH) levels, larger spleen size, and increased bleeding and mortality rates. In PMF, high JAK2V617F allele burden was associated with higher leukocyte counts and larger spleen size. In the entire cohort, high allele burden was associated with higher leukocyte and lower platelet counts, higher LDH levels, larger spleen size, higher percentage of bleeding events, higher death rate, and inferior overall survival.

Conclusion

Our results suggest that high JAK2V617F allele burdens are associated with more severe disease in PV and ET. In PMF, high JAK2V617F allele burdens were associated with more pronounced myeloproliferative phenotypes. In Ph-negative MPNs, high allele burdens were associated with more aggressive phenotypes. Our data with a long follow-up period support the possibility of JAK2V617F allele burden being used as a marker for predicting clinical phenotype in cases of Ph-negative MPNs.

Molecular Aspects of Hematological Malignancies and Benign Hematological Disorders

Hematology represents a dynamic specialty in clinical medicine that requires solid knowledge of normal and pathological hematopoiesis, cytomorphology, pathology, immunology, genetics and molecular biology [...].

Novel Tools for Diagnosis and Monitoring of AML

In recent years, major advances in the understanding of acute myeloid leukemia (AML) pathogenesis, together with technological progress, have led us into a new era in the diagnosis and follow-up of patients with AML. A combination of immunophenotyping, cytogenetic and molecular studies are required for AML diagnosis, including the use of next-generation sequencing (NGS) gene panels to screen all genetic alterations with diagnostic, prognostic and/or therapeutic value. Regarding AML monitoring, multiparametric flow cytometry and quantitative PCR/RT-PCR are currently the most implemented methodologies for measurable residual disease (MRD) evaluation. Given the limitations of these techniques, there is an urgent need to incorporate new tools for MRD monitoring, such as NGS and digital PCR. This review aims to provide an overview of the different technologies used for AML diagnosis and MRD monitoring and to highlight the limitations and challenges of current versus emerging tools.

Research Topic: Measurable Residual Disease in Hematologic Malignancies. Can digital droplet PCR improve measurable residual disease monitoring in chronic lymphoid malignancies?

Minimal/measurable residual disease (MRD) monitoring is progressively changing the management of hematologic malignancies. The possibility of detecting the persistence/reappearance of disease in patients in apparent clinical remission offers a refined risk stratification and a treatment decision making tool. Several molecular techniques are employed to monitor MRD, from conventional real-time quantitative polymerase chain reaction (RQ-PCR) to next generation sequencing and digital droplet PCR (ddPCR), in different tissues or compartments through the detection of fusion genes, immunoglobulin and T-cell receptor gene rearrangements or disease-specific mutations. RQ-PCR is still the gold standard for MRD analysis despite some limitations. ddPCR, considered the third-generation PCR, yields a direct, absolute, and accurate detection and quantification of low-abundance nucleic acids. In the setting of MRD monitoring it carries the major advantage of not requiring a reference standard curve built with the diagnostic sample dilution and of allowing to reduce the number of samples below the quantitative range. At present, the broad use of ddPCR to monitor MRD in the clinical practice is limited by the lack of international guidelines. Its application within clinical trials is nonetheless progressively growing both in acute lymphoblastic leukemia as well as in chronic lymphocytic leukemia and non-Hodgkin lymphomas. The aim of this review is to summarize the accumulating data on the use of ddPCR for MRD monitoring in chronic lymphoid malignancies and to highlight how this new technique is likely to enter into the clinical practice.

Digital PCR as a New Method for Minimal Residual Disease Monitoring and Treatment Free Remission Management in Chronic Myeloid Leukemia Patients: Is It Reliable?

The effective and sensitive monitoring of Minimal Residual Disease or Measurable Residual Disease (MRD) is a very important aspect in the management of patients affected by hematologic malignancies. The recent availability of new technologies has opened to the improvement of MRD monitoring. It is particularly relevant in patients affected by Chronic Myeloid Leukemia (CML). MRD monitoring is key in the management of CML patients thanks to the efficacy of TKIs therapy. Moreover, the policies of TKIs discontinuation aimed at treatment free remission are strongly based on the good selection of patients eligible for stopping TKIs therapy. The recently described application of digital PCR in CML patients monitoring seems to improve the accuracy and precision in the identification of optimal responders. The present review reports an overview on the application of digital PCR in the monitoring of MRD in CML and its impact on TKIs discontinuation trials and, consequently, on TFR success.

Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients

DNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expressed at low levels. Here, we consider the employment of a digital PCR assay (ddPCR) to validate a gene signature previously identified by gene expression profile. This signature included ten Hedgehog (HH) pathways' genes able to stratify multiple myeloma (MM) patients according to their self-renewal status. Results show that the designed assay is able to validate gene expression data, both in a retrospective as well as in a prospective cohort. In addition, the plasma cells' differentiation status determined by ddPCR was further confirmed by other techniques, such as flow cytometry, allowing the identification of patients with immature plasma cells' phenotype (i.e., expressing CD19+/CD81+ markers) upregulating HH genes, as compared to others, whose plasma cells lose the expression of these markers and were more differentiated. To our knowledge, this is the first technical report of gene expression data validation by ddPCR instead of classical qPCR. This approach permitted the identification of a Maturation Index through the integration of molecular and phenotypic data, able to possibly define upfront the differentiation status of MM patients that would be clinically relevant in the future.

Next-generation sequencing for MRD monitoring in B-lineage malignancies: from bench to bedside

Minimal residual disease (MRD) is considered the strongest relevant predictor of prognosis and an effective decision-making factor during the treatment of hematological malignancies. Remarkable breakthroughs brought about by new strategies, such as epigenetic therapy and chimeric antigen receptor-T (CAR-T) therapy, have led to considerably deeper responses in patients than ever, which presents difficulties with the widely applied gold-standard techniques of MRD monitoring. Urgent demands for novel approaches that are ultrasensitive and provide sufficient information have put a spotlight on high-throughput technologies. Recently, advances in methodology, represented by next-generation sequencing (NGS)-based clonality assays, have proven robust and suggestive in numerous high-quality studies and have been recommended by some international expert groups as disease-monitoring modalities. This review demonstrates the applicability of NGS-based clonality assessment for MRD monitoring of B-cell malignancies by summarizing the oncogenesis of neoplasms and the corresponding status of immunoglobulin (IG) rearrangements. Furthermore, we focused on the performance of NGS-based assays compared with conventional approaches and the interpretation of results, revealing directions for improvement and prospects in clinical practice.

Application of digital PCR for public health-related water quality monitoring

Digital polymerase chain reaction (dPCR) is emerging as a reliable platform for quantifying microorganisms in the field of water microbiology. This paper reviews the fundamental principles of dPCR and its application for health-related water microbiology. The relevant literature indicates increasing adoption of dPCR for measuring fecal indicator bacteria, microbial source tracking marker genes, and pathogens in various aquatic environments. The adoption of dPCR has accelerated recently due to increasing use for wastewater surveillance of Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) - the virus that causes Coronavirus Disease 2019 (COVID-19). The collective experience in the scientific literature indicates that well-optimized dPCR assays can quantify genetic material from microorganisms without the need for a calibration curve and often with superior analytical performance (i.e., greater sensitivity, precision, and reproducibility) than quantitative polymerase chain reaction (qPCR). Nonetheless, dPCR should not be viewed as a panacea for the fundamental uncertainties and limitations associated with measuring microorganisms in water microbiology. With dPCR platforms, the sample analysis cost and processing time are typically greater than qPCR. However, if improved analytical performance (i.e., sensitivity and accuracy) is critical, dPCR can be an alternative option for quantifying microorganisms, including pathogens, in aquatic environments.

Skin Cancer Research Goes Digital: Looking for Biomarkers within the Droplets

Skin cancer, which includes the most frequent malignant non-melanoma carcinomas (basal cell carcinoma, BCC, and squamous cell carcinoma, SCC), along with the difficult to treat cutaneous melanoma (CM), pose important worldwide issues for the health care system. Despite the improved anti-cancer armamentarium and the latest scientific achievements, many skin cancer patients fail to respond to therapies, due to the remarkable heterogeneity of cutaneous tumors, calling for even more sophisticated biomarker discovery and patient monitoring approaches. Droplet digital polymerase chain reaction (ddPCR), a robust method for detecting and quantifying low-abundance nucleic acids, has recently emerged as a powerful technology for skin cancer analysis in tissue and liquid biopsies (LBs). The ddPCR method, being capable of analyzing various biological samples, has proved to be efficient in studying variations in gene sequences, including copy number variations (CNVs) and point mutations, DNA methylation, circulatory miRNome, and transcriptome dynamics. Moreover, ddPCR can be designed as a dynamic platform for individualized cancer detection and monitoring therapy efficacy. Here, we present the latest scientific studies applying ddPCR in dermato-oncology, highlighting the potential of this technology for skin cancer biomarker discovery and validation in the context of personalized medicine. The benefits and challenges associated with ddPCR implementation in the clinical setting, mainly when analyzing LBs, are also discussed.

Digital Droplet PCR Is a Reliable Tool to Improve Minimal Residual Disease Stratification in Adult Philadelphia-Negative Acute Lymphoblastic Leukemia

Digital droplet PCR (ddPCR) is an implementation of conventional PCR, with the potential of overcoming some limitations of real-time quantitative PCR (RQ-PCR). To evaluate if ddPCR may improve the quantification of disease levels and refine patients' risk stratification, 116 samples at four time points from 44 (35 B-lineage and 9 T-lineage) adult Philadelphia-negative acute lymphoblastic leukemia patients enrolled in the GIMEMA LAL1913 protocol were analyzed by RQ-PCR and ddPCR. A concordance rate between RQ-PCR and ddPCR of 79% (P < 0.0001) was observed; discordances were identified in 21% of samples, with the majority being RQ-PCR-negative (NEG) or positive not quantifiable (PNQ). ddPCR significantly reduced the proportion of PNQ samples-2.6% versus 14% (P = 0.003)-and allowed disease quantifiability in 6.6% of RQ-PCR-NEG, increasing minimal residual disease quantification in 14% of samples. Forty-seven samples were also investigated by next-generation sequencing, which confirmed the ddPCR results in samples classified as RQ-PCR-PNQ or NEG. By reclassifying samples on the basis of the ddPCR results, a better event-free survival stratification of patients was observed compared with RQ-PCR: indeed, ddPCR captured more true-quantifiable samples, with five relapses occurring in three patients who resulted RQ-PCR-PNQ/NEG but proved ddPCR positive quantifiable. At variance, no relapses were recorded in patients whose follow-up samples were RQ-PCR-PNQ but reclassified as ddPCR-NEG. A broader application of ddPCR in acute lymphoblastic leukemia clinical trials will help to improve patients' stratification.

Cell-Free Tumor DNA (cf-tDNA) Liquid Biopsy: Current Methods and Use in Brain Tumor Immunotherapy

Gliomas are tumors derived from mutations in glial brain cells. Gliomas cause significant morbidity and mortality and development of precision diagnostics and novel targeted immunotherapies are critically important. Radiographic imaging is the most common technique to diagnose and track response to treatment, but is an imperfect tool. Imaging does not provide molecular information, which is becoming critically important for identifying targeted immunotherapies and monitoring tumor evolution. Furthermore, immunotherapy induced inflammation can masquerade as tumor progression in images (pseudoprogression) and confound clinical decision making. More recently, circulating cell free tumor DNA (cf-tDNA) has been investigated as a promising biomarker for minimally invasive glioma diagnosis and disease monitoring. cf-tDNA is shed by gliomas into surrounding biofluids (e.g. cerebrospinal fluid and plasma) and, if precisely quantified, might provide a quantitative measure of tumor burden to help resolve pseudoprogression. cf-tDNA can also identify tumor genetic mutations to help guide targeted therapies. However, due to low concentrations of cf-tDNA, recovery and analysis remains challenging. Plasma cf-tDNA typically represents <1% of total cf-DNA due to the blood-brain barrier, limiting their usefulness in practice and motivating the development and use of highly sensitive and specific detection methods. This mini review summarizes the current and future trends of various approaches for cf-tDNA detection and analysis, including new methods that promise more rapid, lower-cost, and accessible diagnostics. We also review the most recent clinical case studies for longitudinal disease monitoring and highlight focus areas, such as novel accurate detection methodologies, as critical research priorities to enable translation to clinic.

Accurate Detection of Subclonal Variants in Paired Diagnosis-Relapse Acute Myeloid Leukemia Samples by Next Generation Duplex Sequencing

Mutations characterize diverse human cancers; there is a positive correlation between elevated mutation frequency and tumor progression. One exception is acute myeloid leukemia (AML), which has few clonal single nucleotide mutations. We used highly sensitive and accurate Duplex Sequencing (DS) to show now that AML, in addition, has an extensive repertoire of variants with low allele frequencies, < 1%, which is below the accurate detection limit of most other sequencing methodologies. The subclonal variants are unique to each individual and change in composition, frequency, and sequence context from diagnosis to relapse. Their functional significance is apparent by the observation that many are known variants and cluster within functionally important protein domains. Subclones provide a reservoir of variants that could expand and contribute to the development of drug resistance and relapse. In accord, we accurately identified subclonal variants in AML driver genes NRAS and RUNX1 at allele frequencies between 0.1% and 0.3% at diagnosis, which expanded to comprise a major fraction (14-53%) of the blast population at relapse. Early and accurate detection of subclonal variants with low allele frequency thus offers the opportunity for early intervention, prior to detection of clinical relapse, to improve disease outcome and enhance patient survival.

Quantitative detections of TP53 gene mutations improve the diagnosis and prognostic prediction of biliary tract cancers using droplet digital PCR

OBJECTIVE

Biliary tract cancer (BTC) is a rare malignancy and lack of effective diagnostic and prognostic marker. Here, we aimed to investigate the clinical implication of TP53 mutation detection in BTC using droplet digital PCR (ddPCR).

METHODS

TP53 gene (loci p.R175H, p.R248Q, p.R248W, and p.R273H) mutation frequencies of 45 pairs of tumor tissues (TTs) and adjacent normal tissues (ANTTs) were analyzed, respectively, using ddPCR. Meanwhile, the same detections were conducted in plasma cell-free DNA (cfNDA) of 156 subjects including BTC, disease control (DC), and healthy controls (HC). The logistic regression algorithm was established to identify BTC. The correlations between mutations and clinicopathological features as well as the effects of TP53 mutation frequency on BTC prognosis were assessed.

RESULTS

The higher mutation of p.R175H was found in TTs compared with ANTT (p = 0.006). The mutation at p.R273H in cfDNA was also higher in BTC when compared with DC and HC (p < 0.05). The logistic algorithms combining p.R273H mutation demonstrated the higher diagnostic efficacy trend than carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and alpha-fetoprotein (AFP) in identifying BTC from DC (the area under the curves of the algorithm: 0.845, 95% CI:0.775-0.914). The median overall survival (OS) and progression-free survival (PFS) were significantly shorter when the BTC patients harboring the p.R273H mutation (OS: p = 0.032; PFS: p = 0.046).

CONCLUSION

This study revealed for the first time that the quantitative TP53 mutations using the ddPCR might serve as a potential genetic biomarker for BTC diagnosis and prognosis assessment.

DCD-chip designed for the digital and ultraprecise quantification of copy number variation

The progress of CNV detection in DCD-chip.

Making Treatment-Free Remission (TFR) Easier in Chronic Myeloid Leukemia: Fact-Checking and Practical Management Tools

In chronic-phase chronic myeloid leukemia (CML), tyrosine kinase inhibitors (TKIs) are the standard of care, and treatment-free remission (TFR) following the achievement of a stable deep molecular response (DMR) has become, alongside survival, a primary goal for virtually all patients. The GIMEMA CML working party recently suggested that the possibility of achieving TFR cannot be denied to any patient, and proposed specific treatment policies according to the patient's age and risk. However, other international recommendations (including 2020 ELN recommendations) are more focused on survival and provide less detailed suggestions on how to choose first and subsequent lines of treatment. Consequently, some grey areas remain. After literature review, a panel of Italian experts discussed the following controversial issues: (1) early prediction of DMR and TFR: female sex, non-high disease risk score, e14a2 transcript and early MR achievement have been associated with stable DMR, but the lack of these criteria is not sufficient to exclude any patient from TFR; (2) criteria for first and subsequent line therapy choice: a number of patient and drug characteristics have been proposed to make a personalized decision; (3) monitoring of residual disease after discontinuation: after the first 6 months, the frequency of molecular tests can be reduced based on MR4.5 persistence and short turnaround time; (4) prognosis of TFR: therapy and DMR duration are important to predict TFR; although immunological control of CML plays a role, no immunological predictive phenotype is currently available. This guidance is intended as a practical tool to support physicians in decision making.

Liquid Biopsy-Based Biosensors for MRD Detection and Treatment Monitoring in Non-Small Cell Lung Cancer (NSCLC)

Globally, non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths. Despite advancements in chemotherapy and targeted therapies, the 5-year survival rate has remained at 16% for the past forty years. Minimal residual disease (MRD) is described as the existence of either isolated tumour cells or circulating tumour cells in biological liquid of patients after removal of the primary tumour without any clinical signs of cancer. Recently, liquid biopsy has been promising as a non-invasive method of disease monitoring and treatment guidelines as an MRD marker. Liquid biopsy could be used to detect and assess earlier stages of NSCLC, post-treatment MRD, resistance to targeted therapies, immune checkpoint inhibitors (ICIs) and tumour mutational burden. MRD surveillance has been proposed as a potential marker for lung cancer relapse. Principally, biosensors provide the quantitative analysis of various materials by converting biological functions into quantifiable signals. Biosensors are usually operated to detect antibodies, enzymes, DNA, RNA, extracellular vesicles (EVs) and whole cells. Here, we present a category of biosensors based on the signal transduction method for identifying biosensor-based biomarkers in liquid biopsy specimens to monitor lung cancer treatment.

Recent Advances in the Use of Molecular Analyses to Inform the Diagnosis and Prognosis of Patients with Polycythaemia Vera

Genetic studies in the past decade have improved our understanding of the molecular basis of the BCR-ABL1-negative myeloproliferative neoplasm (MPN) polycythaemia vera (PV). Such breakthroughs include the discovery of the JAK2V617F driver mutation in approximately 95% of patients with PV, as well as some very rare cases of familial hereditary MPN caused by inherited germline mutations. Patients with PV often progress to fibrosis or acute myeloid leukaemia, both associated with very poor clinical outcome. Moreover, thrombosis and major bleeding are the principal causes of morbidity and mortality. As a result of increasingly available and economical next-generation sequencing technologies, mutational studies have revealed the prognostic relevance of a few somatic mutations in terms of thrombotic risk and risk of transformation, helping to improve the risk stratification of patients with PV. Finally, knowledge of the molecular basis of PV has helped identify targets for directed therapy. The constitutive activation of the tyrosine kinase JAK2 is targeted by ruxolitinib, a JAK1/JAK2 tyrosine kinase inhibitor for PV patients who are resistant or intolerant to cytoreductive treatment with hydroxyurea. Other molecular mechanisms have also been revealed, and numerous agents are in various stages of development. Here, we will provide an update of the recent published literature on how molecular testing can improve the diagnosis and prognosis of patients with PV and present recent advances that may have prognostic value in the near future.

Minimal Residual Disease in Acute Lymphoblastic Leukemia: Current Practice and Future Directions

Simple Summary

Acute lymphoblastic leukemia minimal residual disease (MRD) refers to the presence of residual leukemia cells following the achievement of complete remission, but below the limit of detection using conventional morphologic assessment. Up to two thirds of children may have MRD detectable after induction therapy depending on the biological subtype and method of detection. Patients with detectable MRD have an increased likelihood of relapse. A rapid reduction of MRD reveals leukemia sensitivity to therapy and under this premise, MRD has emerged as the strongest independent predictor of individual patient outcome and is crucial for risk stratification. However, it is a poor surrogate for treatment effect on long term outcome at the trial level, with impending need of randomized trials to prove efficacy of MRD-adapted interventions.

Abstract

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer and advances in its clinical and laboratory biology have grown exponentially over the last few decades. Treatment outcome has improved steadily with over 90% of patients surviving 5 years from initial diagnosis. This success can be attributed in part to the development of a risk stratification approach to identify those subsets of patients with an outstanding outcome that might qualify for a reduction in therapy associated with fewer short and long term side effects. Likewise, recognition of patients with an inferior prognosis allows for augmentation of therapy, which has been shown to improve outcome. Among the clinical and biological variables known to impact prognosis, the kinetics of the reduction in tumor burden during initial therapy has emerged as the most important prognostic variable. Specifically, various methods have been used to detect minimal residual disease (MRD) with flow cytometric and molecular detection of antigen receptor gene rearrangements being the most common. However, many questions remain as to the optimal timing of these assays, their sensitivity, integration with other variables and role in treatment allocation of various ALL subgroups. Importantly, the emergence of next generation sequencing assays is likely to broaden the use of these assays to track disease evolution. This review will discuss the biological basis for utilizing MRD in risk assessment, the technical approaches and limitations of MRD detection and its emerging applications.

A Quantitative Paradigm for Decision-Making in Precision Oncology

The complexity and variability of cancer progression necessitate a quantitative paradigm for therapeutic decision-making that is dynamic, personalized, and capable of identifying optimal treatment strategies for individual patients under substantial uncertainty. Here, we discuss the core components and challenges of such an approach and highlight the need for comprehensive longitudinal clinical and molecular data integration in its development. We describe the complementary and varied roles of mathematical modeling and machine learning in constructing dynamic optimal cancer treatment strategies and highlight the potential of reinforcement learning approaches in this endeavor.

Molecular Testing in CML between Old and New Methods: Are We at a Turning Point?

Molecular monitoring of minimal residual disease (MRD) and BCR-ABL1 kinase domain (KD) mutation testing have a well consolidated role in the routine management of chronic myeloid leukemia (CML) patients, as they provide precious information for therapeutic decision-making. Molecular response levels are used to define whether a patient has an "optimal", "warning", or "failure" response to tyrosine kinase inhibitor (TKI) therapy. Mutation status may be useful to decide whether TKI therapy should be changed and which alternative TKI (or TKIs) are most likely to be effective. Real-time quantitative polymerase chain reaction (RQ-qPCR) and Sanger sequencing are currently the gold standard for molecular response monitoring and mutation testing, respectively. However, in recent years, novel technologies such as digital PCR (dPCR) and next-generation sequencing (NGS) have been evaluated. Here, we critically describe the main features of these old and novel technologies, provide an overview of the recently published studies assessing the potential clinical value of dPCR and NGS, and discuss how the state of the art might evolve in the next years.

Clonal Hematopoiesis and Mutations of Myeloproliferative Neoplasms

Myeloproliferative neoplasms (MPNs) are associated with the fewest number of mutations among known cancers. The mutations propelling these malignancies are phenotypic drivers providing an important implement for diagnosis, treatment response monitoring, and gaining insight into the disease biology. The phenotypic drivers of Philadelphia chromosome negative MPN include mutations in JAK2, CALR, and MPL. The most prevalent driver mutation JAK2V617F can cause disease entities such as essential thrombocythemia (ET) and polycythemia vera (PV). The divergent development is considered to be influenced by the acquisition order of the phenotypic driver mutation relative to other MPN-related mutations such as TET2 and DNMT3A. Advances in molecular biology revealed emergence of clonal hematopoiesis (CH) to be inevitable with aging and associated with risk factors beyond the development of blood cancers. In addition to its well-established role in thrombosis, the JAK2V617F mutation is particularly connected to the risk of developing cardiovascular disease (CVD), a pertinent issue, as deep molecular screening has revealed the prevalence of the mutation to be much higher in the background population than previously anticipated. Recent findings suggest a profound under-diagnosis of MPNs, and considering the impact of CVD on society, this calls for early detection of phenotypic driver mutations and clinical intervention.

Accurate In-Vivo Quantification of CD19 CAR-T Cells after Treatment with Axicabtagene Ciloleucel (Axi-Cel) and Tisagenlecleucel (Tisa-Cel) Using Digital PCR

Immunotherapy with CD19-specific chimeric antigen receptor (CAR-) T cells has shown excellent efficacy in relapsed/refractory B-cell cancers. The in vivo expansion and persistence of CAR-T cells after infusion are important response- and toxicity-determining variables, but diagnostic tools are largely missing. We showed previously for axi-cel that digital PCR (dPCR) is excellently suited to monitoring CAR-T cells in vivo. Here, we aimed to develop an analogous dPCR assay for tisa-cel. To do so, we cloned and sequenced the CAR construct from the lentiviral tisa-cel vector and designed primers and Black hole quencher (BHQ) probes complimentary to sequences present in the FMC63 scFv part of axi-cel (assay A), tisa-cel (T), and both constructs (U = “universal”). In conjunction with excellent specificity, all assays have a detection limit of one single CAR copy, corresponding to a sensitivity of approximately 1 in 5000 cells (0.02%) for 100 ng genomic DNA (for one vector copy per transduced cell). The new universal assay was first validated using patient samples previously quantified with the axi-cel-specific dPCR and thereafter applied to quantify and monitor adoptively transferred axi-cel and tisa-cel T cells in post-infusion samples (peripheral blood, bone marrow, liquor, and ascites). Actual CAR-T counts per µl were calculated, taking into account vector copy and peripheral blood mononuclear cell (PBMC) numbers, and showed very good correlation with flow cytometry results. We conclude that our novel dPCR assay is optimally suited to monitoring tisa-cel and axi-cel CAR-T cells in real-time in various body fluids.