The relative utilities of genome-wide, gene panel, and individual gene sequencing in clinical practice

Acute Myeloid Leukemia and Next-Generation Sequencing Panels for Diagnosis: A Comprehensive Review

Acute myeloid leukemia (AML) is a genetically heterogeneous clonal disorder characterized by the accumulation of acquired somatic genetic alterations in hematopoietic progenitor cells, which alter the normal mechanisms of self-renewal, proliferation, and differentiation. Due to significant technological advancements in sequencing technologies in the last 2 decades, classification and prognostic scoring of AML has been refined, and multiple guidelines are now available for the same. The authors have tried to summarize, latest guidelines for AML diagnosis, important markers associated, epigenetics markers, various AML fusions and their importance, etc. Review of literature suggests lack of study or comprehensive information about current NGS panels for AML diagnosis, genes and fusions covered, their technical know-how, etc. To solve this issue, the authors have tried to present detailed review about currently in use next-generation sequencing myeloid panels and their offerings.

Artificial intelligence in cardiology: a bibliometric study

OBJECTIVES

To perform a comprehensive bibliometric analysis of global publications on the applications of artificial intelligence (AI) in cardiology.

METHODS

Documents related to AI in cardiology published between 2002 and 2022 were retrieved from Web of Science Core Collection. R package "bibliometrix", VOSviewers and Microsoft Excel were applied to perform the bibliometric analysis.

RESULTS

A total of 4332 articles were included. United States topped the list of countries publishing articles, followed by China and United Kingdom. The Harvard University was the institution that contributed the most to this field, followed by University of California System and University of London. Disease risk prediction, diagnosis, treatment, disease detection, and prognosis assessment were the research hotspots for AI in cardiology.

CONCLUSIONS

Enhancing cooperation between different countries and institutions is a critical step in leading to breakthroughs in the application of AI in cardiology. It is foreseeable that the application of machine learning and deep learning in various areas of cardiology will be a research priority in the coming years.

Aptamer-Based Multiparameter Analysis for Molecular Profiling of Hematological Malignancies

The subtypes of hematological malignancies (HM) with minimal molecular profile differences display an extremely heterogeneous clinical course and a discrepant response to certain treatment regimens. Profiling the surface protein markers offers a potent solution for precision diagnosis of HM by differentiating among the subtypes of cancer cells. Herein, we report the use of Cell-SELEX technology to generate a panel of high-affinity aptamer probes that are able to discriminate subtle differences among surface protein profiles between different HM cells. Experimental results show that these aptamers with apparent dissociation constants (Kd) below 10 nM display a unique recognition pattern on different HM subtypes. By combining a machine learning model on the basis of partial least-squares discriminant analysis, 100% accuracy was achieved for the classification of different HM cells. Furthermore, we preliminarily validated the effectiveness of the aptamer-based multiparameter analysis strategy from a clinical perspective by accurately classifying complex clinical samples, thus providing a promising molecular tool for precise HM phenotyping.

Highly-Efficient Gallium-Interference Tumor Therapy Mediated by Gallium-Enriched Prussian Blue Nanomedicine

Prussian blue (PB)-based nanomedicines constructed from metal ion coordination remain restricted due to their limited therapeutic properties, and their manifold evaluation complexity still needs to be unraveled. Owing to the high similarities of its ionic form to iron (Fe) and the resulting cellular homeostasis disruption performance, physiologically unstable and low-toxicity gallium (Ga) has garnered considerable attention clinically as an anti-carcinogen. Herein, Ga-based nanoparticles (NPs) with diverse Ga contents are fabricated in one step using PB with abundant Fe sites as a substrate for Ga substitution, which aims to overcome the deficiencies of both and develop an effective nanomedicine. A systematic comparison of their physicochemical properties effectively reveals the saturated Ga introduction state during the synthesis process, further identifying the most Ga-enriched PB NPs with a substitution content of >50% as a nanomedicine for subsequent exploration. It is verified that the Ga interference mechanisms mediated by the most Ga-enriched PB NPs are implicated in metabolic disorders, ionic homeostasis disruption, cellular structure dysfunction, apoptosis, autophagy, and target activation of the mammalian target of the rapamycin (mTOR) and mitogen-activated protein kinase (MAPK) pathways. This study provides significant guidance on exploiting clinically approved agents for Ga interference and lays the foundation for the next generation of PB-based theranostic agents.

Gene mutation analysis using next-generation sequencing and its clinical significance in patients with myeloid neoplasm: A multi-center study from China

BACKGROUND

Myeloid neoplasms (MN) tend to relapse and deteriorate. Exploring the genomic mutation landscape of MN using next-generation sequencing (NGS) is a great measure to clarify the mechanism of oncogenesis and progression of MN.

METHODS

This multicenter retrospective study investigated 303 patients with MN using NGS from 2019 to 2021. The characteristics of the mutation landscape in the MN subgroups and the clinical value of gene variants were analyzed.

RESULTS

At least one mutation was detected in 88.11% of the patients (267/303). TET2 was the most common mutation in the cohort, followed by GATA2, ASXL1, FLT3, DNMT3A, and TP53. Among patients with myeloid leukemia (ML), multivariate analysis showed that patients aged ≥60 years had lower overall survival (OS, p = 0.004). Further analysis showed TET2, NPM1, SRSF2, and IDH1 gene mutations, and epigenetic genes (p < 0.050) presented significantly higher frequency in older patients. In patients with myelodysplastic syndrome (MDS) and myelodysplastic neoplasms (MPN), univariate analysis showed that BCORL1 had a significant impact on OS (p = 0.040); however, in multivariate analysis, there were no factors significantly associated with OS. Differential analysis of genetic mutations showed FLT3, TP53, MUC16, SRSF2, and KDM5A mutated more frequently (p < 0.050) in secondary acute myeloid leukemia (s-AML) than in MDS and MPN. TP53, U2AF1, SRSF2, and KDM5A were mutated more frequently (p < 0.050) in s-AML than in primary AML. KDM5A was observed to be restricted to patients with s-AML in this study, and only co-occurred with MUC16 and TP53 (2/2, 100%). Another mutation was MUC16, and its co-occurrence pattern differed between s-AML and AML. MUC16 mutations co-occurred with KDM5A and TP53 in 66.7% (2/3) of patients with s-AML and co-occurred with CEBPA in 100% (4/4) of patients with AML.

CONCLUSIONS

Our results demonstrate different genomic mutation patterns in the MN subgroups and highlight the clinical value of genetic variants.

Risk stratifying MDS in the time of precision medicine

Myelodysplastic syndromes (MDS) are myeloid neoplasms characterized by morphologic dysplasia, persistent cytopenia, and a variable risk of evolution to acute myeloid leukemia (AML). Risk stratification is crucial in a patient-centered approach to the treatment of MDS. Based on hematologic parameters and cytogenetic abnormalities, the Revised International Prognostic Scoring System is currently used for this purpose. In the past years, the use of massively parallel DNA sequencing has clarified the genetic basis of MDS and has enabled development of novel diagnostic and prognostic approaches. When conventional cytogenetics is combined with gene sequencing, more than 90% of patients are found to carry a somatic genetic lesion. In addition, a portion of patients has germline variants that predispose them to myeloid neoplasms. The recently developed International Consensus Classification of MDS includes new entities that are molecularly defined-namely, SF3B1-mutant and TP53-mutant MDS. The International Working Group for Prognosis in MDS has just developed the International Prognostic Scoring System-Molecular (IPSS-M) for MDS, which considers hematologic parameters, cytogenetic abnormalities, and somatic gene mutations. The IPSS-M score is personalized and can be obtained using a web-based calculator that returns not only the individual score but also the expected leukemia-free survival, overall survival, and risk of AML transformation. Providing an efficient risk stratification of patients with MDS, the IPSS-M represents a valuable tool for individual risk assessment and treatment decisions.

Patient-Specific Assays Based on Whole-Genome Sequencing Data to Measure Residual Disease in Children With Acute Lymphoblastic Leukemia: A Proof of Concept Study

Risk-adapted treatment in acute lymphoblastic leukemia (ALL) relies on genetic information and measurable residual disease (MRD) monitoring. In this proof of concept study, DNA from diagnostic bone marrow (BM) of six children with ALL, without stratifying genetics or central nervous system (CNS) involvement, underwent whole-genome sequencing (WGS) to identify structural variants (SVs) in the leukemic blasts. Unique sequences generated by SVs were targeted with patient-specific droplet digital PCR (ddPCR) assays. Genomic DNA (gDNA) from BM and cell-free DNA (cfDNA) from plasma and cerebrospinal fluid (CSF) were analyzed longitudinally. WGS with 30× coverage enabled target identification in all cases. Limit of quantifiability (LoQ) and limit of detection (LoD) for the ddPCR assays (n = 15) were up to 10^-5 and 10^-6, respectively. All targets were readily detectable in a multiplexed ddPCR with minimal DNA input (1 ng of gDNA) at a 10^-1 dilution, and targets for half of the patients were also detectable at a 10^-2 dilution. The level of MRD in BM at end of induction and end of consolidation block 1 was in a comparable range between ddPCR and clinical routine methods for samples with detectable residual disease, although our approach consistently detected higher MRD values for patients with B-cell precursor ALL. Additionally, several samples with undetectable MRD by flow cytometry were MRD-positive by ddPCR. In plasma, the level of leukemic targets decreased in cfDNA over time following the MRD level detected in BM. cfDNA was successfully extracted from all diagnostic CSF samples (n = 6), and leukemic targets were detected in half of these. The results suggest that our approach to design molecular assays, together with ddPCR quantification, is a technically feasible option for accurate MRD quantification and that cfDNA may contribute valuable information regarding MRD and low-grade CNS involvement.

Of drills and bones: Giovanni Ghedini and the origin of bone marrow biopsy

Bone marrow (BM) studies are pivotal for the diagnosis of haematological disorders. Their introduction into clinical haematology dates back to the work of Giovanni Ghedini (1877-1959), an Italian physician who first conceived BM sampling in 1908. Ghedini's proposal stemmed from his clinical experience and from the scientific developments that characterised his epoch. By presenting selected passages of Ghedini's publications, this report considers the theoretical and historical bases of his work and analyses its practical implications for modern haematology.

Analysis of genetic variants in myeloproliferative neoplasms using a 22-gene next-generation sequencing panel

Background

The Philadelphia (Ph)-negative myeloproliferative neoplasms (MPNs), namely essential thrombocythaemia (ET), polycythaemia vera (PV) and primary myelofibrosis (PMF), are a group of chronic clonal haematopoietic disorders that have the propensity to advance into bone marrow failure or acute myeloid leukaemia; often resulting in fatality. Although driver mutations have been identified in these MPNs, subtype-specific markers of the disease have yet to be discovered. Next-generation sequencing (NGS) technology can potentially improve the clinical management of MPNs by allowing for the simultaneous screening of many disease-associated genes.

Methods

The performance of a custom, in-house designed 22-gene NGS panel was technically validated using reference standards across two independent replicate runs. The panel was subsequently used to screen a total of 10 clinical MPN samples (ET n = 3, PV n = 3, PMF n = 4). The resulting NGS data was then analysed via a bioinformatics pipeline.

Results

The custom NGS panel had a detection limit of 1% variant allele frequency (VAF). A total of 20 unique variants with VAFs above 5% (4 of which were putatively novel variants with potential biological significance) and one pathogenic variant with a VAF of between 1 and 5% were identified across all of the clinical MPN samples. All single nucleotide variants with VAFs ≥ 15% were confirmed via Sanger sequencing.

Conclusions

The high fidelity of the NGS analysis and the identification of known and novel variants in this study cohort support its potential clinical utility in the management of MPNs. However, further optimisation is needed to avoid false negatives in regions with low sequencing coverage, especially for the detection of driver mutations in MPL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01145-0.

Exosomes in the Healthy and Malignant Bone Marrow Microenvironment

The bone marrow (BM) is a complex organ that sustains hematopoiesis via mechanisms involving the microenvironment. The microenvironment includes several cell types, neurotransmitters from innervated fibers, growth factors, extracellular matrix proteins, and extracellular vesicles. The main function of the BM is to regulate hematopoietic function to sustain the production of blood and immune cells. However, the BM microenvironment can also accommodate the survival of malignant cells. A major mechanism by which the cancer cells communicate with cells of the BM microenvironment is through the exchange of exosomes, a subset of extracellular vesicles that deliver molecular signals bidirectionally between malignant and healthy cells. The field of exosomes is an active area of investigation since an understanding of how the exosomal packaging, cargo, and production can be leveraged therapeutically to deter cancer progression and sensitize malignant cells to other therapies. Altogether, this chapter discusses the crucial role of exosomes in the development and progression of BM-associated cancers, such as hematologic malignancies and marrow-metastatic breast cancer. Exosome-based therapeutic strategies and their limitations are also considered.

Precision diagnostics in lymphomas - Recent developments and future directions

Genetics is an integral part of the clinical diagnostics of lymphomas that improves disease subclassification and patient risk-stratification. With the introduction of high-throughput sequencing technologies, a rapid, in-depth portrayal of the genomic landscape in major lymphoma entities was achieved. Whilst a few lymphoma entities were characterized by a predominant gene mutation (e.g. Waldenström's macroglobulinemia and hairy cell leukemia), the vast majority demonstrated a very diverse genetic landscape with a high number of recurrent gene mutations (e.g. chronic lymphocytic leukemia and diffuse large B cell lymphoma), indeed reflecting the great clinical heterogeneity among lymphomas. These studies have allowed better understanding of the ontogeny and evolution of different lymphomas, while also identifying new genetic markers that can complement lymphoma diagnostics and improve prognostication. However, despite these efforts, there is still a limited number of gene mutations with predictive impact that can guide treatment selection. In this review, we will highlight clinically relevant diagnostic, prognostic and predictive markers in lymphomas that are used today in routine diagnostics. We will also discuss how comprehensive genomic characterization using broad sequencing panels, allowing for the simultaneous detection of different types of genetic aberrations, may aid future development of precision diagnostics in lymphomas. This may in turn pave the way for the implementation of tailored precision therapy strategies at the individual patient level.

Interrogation of novel CDK2/9 inhibitor fadraciclib (CYC065) as a potential therapeutic approach for AML

Over the last 50 years, there has been a steady improvement in the treatment outcome of acute myeloid leukemia (AML). However, median survival in the elderly is still poor due to intolerance to intensive chemotherapy and higher numbers of patients with adverse cytogenetics. Fadraciclib (CYC065), a novel cyclin-dependent kinase (CDK) 2/9 inhibitor, has preclinical efficacy in AML. In AML cell lines, myeloid cell leukemia 1 (MCL-1) was downregulated following treatment with fadraciclib, resulting in a rapid induction of apoptosis. In addition, RNA polymerase II (RNAPII)-driven transcription was suppressed, rendering a global gene suppression. Rapid induction of apoptosis was observed in primary AML cells after treatment with fadraciclib for 6-8 h. Twenty-four hours continuous treatment further increased efficacy of fadraciclib. Although preliminary results showed that AML cell lines harboring KMT2A rearrangement (KMT2A-r) are more sensitive to fadraciclib, we found that the drug can induce apoptosis and decrease MCL-1 expression in primary AML cells, regardless of KMT2A status. Importantly, the diversity of genetic mutations observed in primary AML patient samples was associated with variable response to fadraciclib, confirming the need for patient stratification to enable a more effective and personalized treatment approach. Synergistic activity was demonstrated when fadraciclib was combined with the BCL-2 inhibitor venetoclax, or the conventional chemotherapy agents, cytarabine, or azacitidine, with the combination of fadraciclib and azacitidine having the most favorable therapeutic window. In summary, these results highlight the potential of fadraciclib as a novel therapeutic approach for AML.

LYmphoid NeXt-Generation Sequencing (LYNX) Panel: A Comprehensive Capture-Based Sequencing Tool for the Analysis of Prognostic and Predictive Markers in Lymphoid Malignancies

B-cell neoplasms represent a clinically heterogeneous group of hematologic malignancies with considerably diverse genomic architecture recently endorsed by next-generation sequencing (NGS) studies. Because multiple genetic defects have a potential or confirmed clinical impact, a tendency toward more comprehensive testing of diagnostic, prognostic, and predictive markers is desired. This study introduces the design, validation, and implementation of an integrative, custom-designed, capture-based NGS panel titled LYmphoid NeXt-generation sequencing (LYNX) for the analysis of standard and novel molecular markers in the most common lymphoid neoplasms (chronic lymphocytic leukemia, acute lymphoblastic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and mantle cell lymphoma). A single LYNX test provides the following: i) accurate detection of mutations in all coding exons and splice sites of 70 lymphoma-related genes with a sensitivity of 5% variant allele frequency, ii) reliable identification of large genome-wide (≥6 Mb) and recurrent chromosomal aberrations (≥300 kb) in at least 20% of the clonal cell fraction, iii) the assessment of immunoglobulin and T-cell receptor gene rearrangements, and iv) lymphoma-specific translocation detection. Dedicated bioinformatic pipelines were designed to detect all markers mentioned above. The LYNX panel represents a comprehensive, up-to-date tool suitable for routine testing of lymphoid neoplasms with research and clinical applicability. It allows a wide adoption of capture-based targeted NGS in clinical practice and personalized management of patients with lymphoproliferative diseases.

Targeted massively parallel sequencing of mature lymphoid neoplasms: assessment of empirical application and diagnostic utility in routine clinical practice

Massively parallel sequencing (MPS) has become a viable diagnostic tool to interrogate genetic profiles of numerous tumors but has yet to be routinely adopted in the setting of lymphoma. Here, we report the empirical application of a targeted 40-gene panel developed for use in mature lymphoid neoplasms (MLNs) and report our experience on over 500 cases submitted for MPS during the first year of its clinical use. MPS was applied to both fresh and fixed specimens. The most frequent diagnoses were diffuse large B-cell lymphoma (116), chronic lymphocytic leukemia/small lymphocytic lymphoma (60), marginal zone lymphoma (52), and follicular lymphoma (43), followed by a spectrum of mature T-cell neoplasms (40). Of 534 cases submitted, 471 generated reportable results in MLNs, with disease-associated variants (DAVs) detected in 241 cases (51.2%). The most frequent DAVs affected TP53 (30%), CREBBP (14%), MYD88 (14%), TNFRSF14 (10%), TNFAIP3 (10%), B2M (7%), and NOTCH2 (7%). The bulk of our findings confirm what is reported in the scientific literature. While a substantial majority of mutations did not directly impact diagnosis, MPS results were utilized to either change, refine, or facilitate the final diagnosis in ~10.8% of cases with DAVs and 5.5% of cases overall. In addition, we identified preanalytic variables that significantly affect assay performance highlighting items for specimen triage. We demonstrate the technical viability and utility of the judicious use of a targeted MPS panel that may help to establish general guidelines for specimen selection and diagnostic application in MLNs in routine clinical practice.

Analytical validation and performance characteristics of a 48-gene next-generation sequencing panel for detecting potentially actionable genomic alterations in myeloid neoplasms

Identification of genomic mutations by molecular testing plays an important role in diagnosis, prognosis, and treatment of myeloid neoplasms. Next-generation sequencing (NGS) is an efficient method for simultaneous detection of clinically significant genomic mutations with high sensitivity. Various NGS based in-house developed and commercial myeloid neoplasm panels have been integrated into routine clinical practice. However, some genes frequently mutated in myeloid malignancies are particularly difficult to sequence with NGS panels (e.g., CEBPA, CARL, and FLT3). We report development and validation of a 48-gene NGS panel that includes genes that are technically challenging for molecular profiling of myeloid neoplasms including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Target regions were captured by hybridization with complementary biotinylated DNA baits, and NGS was performed on an Illumina NextSeq500 instrument. A bioinformatics pipeline that was developed in-house was used to detect single nucleotide variations (SNVs), insertions/deletions (indels), and FLT3 internal tandem duplications (FLT3-ITD). An analytical validation study was performed on 184 unique specimens for variants with allele frequencies ≥5%. Variants identified by the 48-gene panel were compared to those identified by a 35-gene hematologic neoplasms panel using an additional 137 unique specimens. The developed assay was applied to a large cohort (n = 2,053) of patients with suspected myeloid neoplasms. Analytical validation yielded 99.6% sensitivity (95% CI: 98.9-99.9%) and 100% specificity (95% CI: 100%). Concordance of variants detected by the 2 tested panels was 100%. Among patients with suspected myeloid neoplasms (n = 2,053), 54.5% patients harbored at least one clinically significant mutation: 77% in AML patients, 48% in MDS, and 45% in MPN. Together, these findings demonstrate that the assay can identify mutations associated with diagnosis, prognosis, and treatment options of myeloid neoplasms even in technically challenging genes.

Familial thrombocytopenia due to a complex structural variant resulting in a WAC-ANKRD26 fusion transcript

Advances in genome sequencing have resulted in the identification of the causes for numerous rare diseases. However, many cases remain unsolved with standard molecular analyses. We describe a family presenting with a phenotype resembling inherited thrombocytopenia 2 (THC2). THC2 is generally caused by single nucleotide variants that prevent silencing of ANKRD26 expression during hematopoietic differentiation. Short-read whole-exome and genome sequencing approaches were unable to identify a causal variant in this family. Using long-read whole-genome sequencing, a large complex structural variant involving a paired-duplication inversion was identified. Through functional studies, we show that this structural variant results in a pathogenic gain-of-function WAC-ANKRD26 fusion transcript. Our findings illustrate how complex structural variants that may be missed by conventional genome sequencing approaches can cause human disease.

Bioinformatic strategies for the analysis of genomic aberrations detected by targeted NGS panels with clinical application

Molecular profiling of tumor samples has acquired importance in cancer research, but currently also plays an important role in the clinical management of cancer patients. Rapid identification of genomic aberrations improves diagnosis, prognosis and effective therapy selection. This can be attributed mainly to the development of next-generation sequencing (NGS) methods, especially targeted DNA panels. Such panels enable a relatively inexpensive and rapid analysis of various aberrations with clinical impact specific to particular diagnoses. In this review, we discuss the experimental approaches and bioinformatic strategies available for the development of an NGS panel for a reliable analysis of selected biomarkers. Compliance with defined analytical steps is crucial to ensure accurate and reproducible results. In addition, a careful validation procedure has to be performed before the application of NGS targeted assays in routine clinical practice. With more focus on bioinformatics, we emphasize the need for thorough pipeline validation and management in relation to the particular experimental setting as an integral part of the NGS method establishment. A robust and reproducible bioinformatic analysis running on powerful machines is essential for proper detection of genomic variants in clinical settings since distinguishing between experimental noise and real biological variants is fundamental. This review summarizes state-of-the-art bioinformatic solutions for careful detection of the SNV/Indels and CNVs for targeted sequencing resulting in translation of sequencing data into clinically relevant information. Finally, we share our experience with the development of a custom targeted NGS panel for an integrated analysis of biomarkers in lymphoproliferative disorders.

Clinical Utility of Next-Generation Sequencing in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a genetically heterogeneous disease that, even with current advancements in therapy, continues to have a poor prognosis. Recurrent somatic mutations have been identified in a core set of pathogenic genes including FLT3 (25-30% prevalence), NPM1 (25-30%), DNMT3A (25-30%), IDH1/2 (5-15%), and TET2 (5-15%), with direct diagnostic, prognostic, and targeted therapeutic implications. Advances in the understanding of the complex mechanisms of AML leukemogenesis have led to the development and recent US Food and Drug Administration (FDA) approval of several targeted therapies: midostaurin and gilteritinib targeting activated FLT3, and ivosidenib and enasidenib targeting mutated IDH1/2. Several additional drug candidates targeting other recurrently mutated gene pathways in AML are also being actively developed. Furthermore, outside of the realm of predicting responses to targeted therapies, many other mutated genes, which comprise the so-called long tail of oncogenic drivers in AML, have been shown to provide clinically useful diagnostic and prognostic information for AML patients. Many of these recurrently mutated genes have also been shown to be excellent biomarkers for post-treatment minimal residual disease (MRD) monitoring for assessing treatment response and predicting future relapse. In addition, the identification of germline mutations in a set of genes predisposing to myeloid malignancies may directly inform treatment decisions (particularly stem cell transplantation) and impact other family members. Recent advances in sequencing technology have made it practically and economically feasible to evaluate many genes simultaneously using next-generation sequencing (NGS). Mutation screening with NGS panels has been recommended by national and international professional guidelines as the standard of care for AML patients. NGS-based detection of the heterogeneous genes commonly mutated in AML has practical clinical utility for disease diagnosis, prognosis, prediction of targeted therapy response, and MRD monitoring.

A Combined Epithelial Mesenchymal Transformation and DNA Repair Gene Panel in Colorectal Cancer With Prognostic and Therapeutic Implication

Background

Epithelial mesenchymal transformation (EMT) and DNA repair status represent intrinsic features of colorectal cancer (CRC) and are associated with patient prognosis and treatment responsiveness. We sought to develop a combined EMT and DNA repair gene panel with potential application in patient classification and precise treatment.

Methods

We comprehensively evaluated the EMT and DNA repair patterns of 1,652 CRC patients from four datasets. Unsupervised clustering was used for classification. The clinical features, genetic mutation, tumor mutation load, and chemotherapy as well as immunotherapy sensitivity among different clusters were systematically compared. The least absolute shrinkage and selection operator regression method was used to develop the risk model.

Results

Three distinct CRC clusters were determined. Clustet1 was characterized by down-regulated DNA repair pathways but active epithelial markers and metabolism pathway and had intermediate prognosis. Clustet2 was characterized by down-regulated both epithelial markers and DNA repair pathways and had poor outcome. Clustet3 presented with activation of DNA repair pathway and epithelial markers had favorable prognosis. Clustet1 might benefit form chemotherapy and Clustet3 had a higher response rate to immunotherapy. An EMT and DNA repair risk model related to prognosis and treatment response was developed.

Conclusions

This work developed and validated a combined EMT and DNA repair gene panel for CRC classification, which may be an effective tool for survival prediction and treatment guidance in CRC patients.

Artificial intelligence in cardiology

This review examines the current state and application of artificial intelligence (AI) and machine learning (ML) in cardiovascular medicine. AI is changing the clinical practice of medicine in other specialties. With progress continuing in this emerging technology, the impact for cardiovascular medicine is highlighted to provide insight for the practicing clinician and to identify potential patient benefits.

Prognostic roles of metabolic reprogramming-associated genes in patients with hepatocellular carcinoma

Metabolic reprogramming for adaptation to the tumor microenvironment is recognized as a hallmark of cancer. Although many altered metabolic genes have been reported to be associated with tumor pathological processes, systematic analysis of metabolic genes implicated in hepatocellular carcinoma prognosis remains rare. The aim of this study was to identify key metabolic genes related to hepatocellular carcinoma, and to explore their clinical significance. We downloaded mRNA expression profiles and clinical hepatocellular carcinoma data from The Cancer Genome Atlas database to explore the prognostic roles of metabolic genes. Five prognosis-associated metabolic genes, including POLA1, UCK2, ACYP1, ENTPD2, and TXNRD1, were screened via univariate Cox regression analysis and a LASSO Cox regression model, which divided patients into high- and low-risk groups. Furthermore, gene set enrichment analysis revealed that significantly-enriched gene ontology terms and pathways involving high-risk patients were focused on regulation of nucleic and fatty acid metabolism. Taken together, our study identified five metabolic genes related to survival, which can be used to predict the prognosis of patients with hepatocellular carcinoma. These genes may play essential roles in metabolic microenvironment regulation, and represent potentially important candidate targets in metabolic therapy.

Uncovering Clinically Relevant Gene Fusions with Integrated Genomic and Transcriptomic Profiling of Metastatic Cancers

PURPOSE

Gene fusions are important oncogenic drivers and many are actionable. Whole-genome and transcriptome (WGS and RNA-seq, respectively) sequencing can discover novel clinically relevant fusions.

EXPERIMENTAL DESIGN

Using WGS and RNA-seq, we reviewed the prevalence of fusions in a cohort of 570 patients with cancer, and compared prevalence to that predicted with commercially available panels. Fusions were annotated using a consensus variant calling pipeline (MAVIS) and required that a contig of the breakpoint could be constructed and supported from ≥2 structural variant detection approaches.

RESULTS

In 570 patients with advanced cancer, MAVIS identified 81 recurrent fusions by WGS and 111 by RNA-seq, of which 18 fusions by WGS and 19 by RNA-seq were noted in at least 3 separate patients. The most common fusions were EML4-ALK in thoracic malignancies (9/69, 13%), and CMTM8-CMTM7 in colorectal cancer (4/73, 5.5%). Combined genomic and transcriptomic analysis identified novel fusion partners for clinically relevant genes, such as NTRK2 (novel partners: SHC3, DAPK1), and NTRK3 (novel partners: POLG, PIBF1).

CONCLUSIONS

Utilizing WGS/RNA-seq facilitates identification of novel fusions in clinically relevant genes, and detected a greater proportion than commercially available panels are expected to find. A significant benefit of WGS and RNA-seq is the innate ability to retrospectively identify variants that becomes clinically relevant over time, without the need for additional testing, which is not possible with panel-based approaches.

Precision medicine in acute myeloid leukemia: where are we now and what does the future hold?

INTRODUCTION

Precision medicine has revolutionized the diagnostic and therapeutic management of acute myeloid leukemia (AML), from standardized schemes based on chemotherapy to tailored approaches according to molecular and genetic profile and targeted therapy.

AREAS COVERED

The main topics of precision medicine in AML were reviewed in MEDLINE, EMBASE, and Cochrane Central Register databases, and future directions in this therapeutic area were addressed. This review included targeted therapies, drug-sensitivity tests and predictive biomarkers, and genetic studies employing pharmacogenetic and deep sequencing strategies.

EXPERT OPINION

Precision medicine has opened the door to personalized therapy for specific AML patient populations with promising results. Several targeted therapies have been approved or are being tested for specific mutations (i.e. FLT3, IDH, BCL-2, TP53), obtaining improvements in clinical outcomes and less toxicity as compared with intensive treatment, allowing potential combination therapy. Ongoing trials and real data will establish the role of these molecules in monotherapy or combined in different AML settings (front-line, relapsed/refractory, or post-transplant). Experience in drug-sensitivity predictors and pharmacogenetic biomarkers is encouraging and could be useful tools in the next years, but we need a better understanding of AML biology and pathogenesis as well as confirmatory studies to demonstrate the utility in clinical practice.

Tumor mutation burden and JARID2 gene alteration are associated with short disease-free survival in locally advanced triple-negative breast cancer

Background

In locally advanced triple-negative breast cancer (TNBC), patients who did not achieve pathologic complete response (non-pCR) after neoadjuvant chemotherapy develop rapid tumor metastasis. Tumor mutation burden (TMB) is a potential biomarker of cancer therapy, though whether it is applicable to TNBC is still unclear.

Methods

A total of 14 non-pCR TNBC patients were enrolled, and tissue samples from radical operation were collected. Of these, 7 cases developed disease progression within 12 months after operation [short disease-free survival (short DFS)], while others showed longer DFS over 1 year (long DFS). Next generation sequencing (NGS) analysis targeting 422 cancer-related genes and in vitro studies were performed.

Results

A total of 72 mutations were detected within 14 patients, which ranged from 1 to 8 per patient with a median mutations number of 5. The median number of mutations in the short-DFS group was higher than that in the long-DFS group (6.0 vs. 4.3; P=0.094). Furthermore, 6 gene mutation types were detected, with missense mutations displayed in the majority (36/72, 50.0%). No correlation between mutation type and DFS was found. Among 422 cancer-related genes, alterations in 30 genes were detected. TP53 (12/14, 85.7%) was the most common mutation gene in the entire cohort. RB1 mutations significantly occurred in patients with high Ki-67 scores (P=0.013). Additionally, 4 mutations of PTPN13 (57.1%, 4/7) and 3 of JARID2 (42.9%, 3/7) were only detected in the short-DFS group, while patients with JARID2 mutation had a significantly shorter DFS period (P=0.026). Experiments in vitro confirmed that JARID2 gene was widely expressed in various breast cancer cell lines. Knockdown of JARID2 in MD-MBA-231 cells by small interfering RNA (siRNA) decreased the expression of E-cadherin, and increased the levels of vimentin, MMP7, and MMP9.

Conclusions

In non-pCR TNBC, JARID2 mutation and TMB elevated in patients with short-DFS, indicating the potential prognostic biomarkers and therapeutic molecular targets for locally advanced TNBC.

Genetic Markers in Lung Cancer Diagnosis: A Review

Lung cancer is the most often diagnosed cancer in the world and the most frequent cause of cancer death. The prognosis for lung cancer is relatively poor and 75% of patients are diagnosed at its advanced stage. The currently used diagnostic tools are not sensitive enough and do not enable diagnosis at the early stage of the disease. Therefore, searching for new methods of early and accurate diagnosis of lung cancer is crucial for its effective treatment. Lung cancer is the result of multistage carcinogenesis with gradually increasing genetic and epigenetic changes. Screening for the characteristic genetic markers could enable the diagnosis of lung cancer at its early stage. The aim of this review was the summarization of both the preclinical and clinical approaches in the genetic diagnostics of lung cancer. The advancement of molecular strategies and analytic platforms makes it possible to analyze the genome changes leading to cancer development-i.e., the potential biomarkers of lung cancer. In the reviewed studies, the diagnostic values of microsatellite changes, DNA hypermethylation, and p53 and KRAS gene mutations, as well as microRNAs expression, have been analyzed as potential genetic markers. It seems that microRNAs and their expression profiles have the greatest diagnostic potential value in lung cancer diagnosis, but their quantification requires standardization.

Detection of the KITD816V mutation in myelodysplastic and/or myeloproliferative neoplasms and acute myeloid leukemia with myelodysplasia-related changes predicts concurrent systemic mastocytosis

Greater than 90% of cases of systemic mastocytosis (SM) harbor pathogenic KIT mutations, particularly KIT^D816V. Prognostically-significant pathogenic KIT mutations also occur in 30-40% of core binding factor-associated acute myeloid leukemia (CBF-AML), but are uncommonly associated with concurrent SM. By comparison, the occurrence of SM in other myeloid neoplasms bearing pathogenic KIT mutations, particularly those with a chronic course, is poorly understood. Review of clinical next-generation sequencing (NGS) performed at our institutions in patients with known or suspected hematologic malignancies over an 8-year period revealed 64 patients with both a pathogenic KIT mutation detected at one or more timepoints and available bone marrow biopsy materials. Patients with KIT^D816V-mutated myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), or overlap MDS/MPN (n = 22) accounted for approximately one-third of our cohort (34%). Comprehensive morphologic and immunophenotypic characterization revealed that nearly all cases (n = 20, 91%) exhibited concurrent SM. In contrast, of the 18 patients (28%) with AML and KIT^D816V, only eight (44%) showed evidence of SM at any point in their disease course (p = 0.0021); of these eight, the AML component was characterized as AML with myelodysplasia-related changes (AML-MRC) in all but one instance (n = 7, 87%). Twelve patients (19%) had pathogenic KIT mutations other than p.D816V, all in the setting of AML (CFB-AML, n = 7; AML, not otherwise specified, n = 2; AML-MRC, n = 1; acute promyelocytic leukemia, n = 1); only two of these patients (17%), both with CBF-AML, exhibited concurrent SM. The remaining 12 patients (19%) had SM without evidence of an associated hematological neoplasm (AHN). For nearly one-third of the 30 SM-AHN patients in our cohort (n = 9, 30%), the SM component of their disease was not initially clinicopathologically recognized. We propose that identification of the KIT^D816V mutation in patients diagnosed with MDS, MPN, MDS/MPN, or AML-MRC should trigger reflex testing for SM.

Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects

Background

DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions.

Research Question

Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis?

Study Design and Methods

Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated.

Results

Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10^–17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10^–18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC_{3 year}, 0.88 [95% CI, 0.83-0.93]; and AUC_{5 year}, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively.

Interpretation

The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.

Nanopore Sequencing in Blood Diseases: A Wide Range of Opportunities

The molecular pathogenesis of hematological diseases is often driven by genetic and epigenetic alterations. Next-generation sequencing has considerably increased our genomic knowledge of these disorders becoming ever more widespread in clinical practice. In 2012 Oxford Nanopore Technologies (ONT) released the MinION, the first long-read nanopore-based sequencer, overcoming the main limits of short-reads sequences generation. In the last years, several nanopore sequencing approaches have been performed in various "-omic" sciences; this review focuses on the challenge to introduce ONT devices in the hematological field, showing advantages, disadvantages and future perspectives of this technology in the precision medicine era.

Clinical genetic testing in endocrinology: Current concepts and contemporary challenges

Recent advances in DNA sequencing technology have led to an unprecedented period of disease-gene discovery offering many new opportunities for genetic testing in the clinical setting. Endocrinology has seen a rapid expansion in the taxonomy of monogenic disorders, which can be detected by an expanding portfolio of genetic tests in both diagnostic and predictive settings. Successful testing relies on many factors including the ability to identify those at increased risk of genetic disease in the busy clinic as well as a working knowledge of the various testing platforms and their limitations. The clinical utility of a given test is dependent upon many factors, which include the reliability of the genetic testing platform, the accuracy of the test result interpretation and knowledge of disease penetrance and expression. The increasing adoption of "high-content" genetic testing based on next-generation sequencing (NGS) to diagnose hereditary endocrine disorders brings a number of challenges including the potential for uncertain test results and/or genetic findings unrelated to the indication for testing. Therefore, it is increasingly important that the clinician is aware of the current evolution in genetic testing, and understands the different settings in which it may be employed. This review provides an overview of the genetic testing workflow, focusing on each of the major components required for successful testing in adult and paediatric endocrine settings. In addition, the challenges of variant interpretation are highlighted, as are issues related to informed consent, prenatal diagnosis and predictive testing. Finally, the future directions of genetic testing relevant to endocrinology are discussed.

Artificial Intelligence in Cardiology

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes.

[From panel diagnostics to comprehensive genomic analysis : Infobesity or empowerment?]

Precision oncology is obtaining a central role in the therapy of malignant diseases. The indication for targeted therapy is based on the identification of molecular targets for which next-generation sequencing (NGS) is commonly used nowadays. All approved predictive biomarkers and molecular targets, including gene fusions and copy number alterations, can be identified depending on panel design and method applied. Some clinical scenarios, however, may require more holistic genomic approaches, such as whole-genome/whole-exome and transcriptome analysis, which must be embedded in a clinical trial. Here, key aspects and applications of each method are summarized and discussed.

Acute myeloid leukemia: 2019 update on risk-stratification and management

Outcome in patients with acute myeloid leukemia (AML) ranges from death within a few days of beginning treatment (treatment related mortality, TRM) to likely cure. The major reason patients are not cured is resistance to treatment, often manifested as relapse from remission, rather than, even in older patients, TRM, whose incidence is decreasing. Knowledge of the pre-treatment mutation status of various genes has improved our ability to assign initial treatment and, of particular importance, knowledge of whether patients ostensibly in remission have measurable residual disease should influence subsequent management. Several new drugs have been approved by the FDA and we discuss their role in treatment.

Measurement of Residual Disease in Acute Myeloid Leukemia

PURPOSE OF REVIEW

Assessment of measurable residual disease (MRD) after treatment can identify patients with acute myeloid leukemia (AML) that are at high risk of poor outcomes. However, there is no consensus yet regarding a standardized approach to measuring MRD that is most clinically meaningful. We review multiparameter flow cytometry (MFC) and reverse transcriptase polymerase chain reaction (RT-PCR), and discuss a framework for assessing remission MRD using next-generation sequencing (NGS).

RECENT FINDINGS

MFC and RT-PCR may not fully capitalize on the major advances that have been made in characterizing the genetic landscape of AML, which has offered insight into the biological and clinical implications of clonal genetic architecture. NGS has increasingly been shown to provide a qualitative and quantitative assessment of MRD with significant prognostic implications. The assessment of clonal architecture by NGS may complement or extend existing approaches for MRD monitoring. Long-term serial monitoring of diagnostic, remission, and relapse samples with clinical correlation will need to be performed in order to determine the impact of various MRD patterns using this technique.