DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome

DNA repair and the contribution to chemotherapy resistance

The DNA damage response comprises a set of imperfect pathways that maintain cell survival following exposure to DNA damaging agents. Cancers frequently exhibit DNA repair pathway alterations that contribute to their intrinsic genome instability. This, in part, facilitates a therapeutic window for many chemotherapeutic agents whose mechanisms of action often converge at the generation of a double-strand DNA break. The development of therapy resistance occurs through countless molecular mechanisms that promote tolerance to DNA damage, often by preventing break formation or increasing repair capacity. This review broadly discusses the DNA damaging mechanisms of action for different classes of chemotherapeutics, how avoidance and repair of double-strand breaks can promote resistance, and strategic directions for counteracting therapy resistance.

Persistent postremission clonal hematopoiesis shapes the relapse trajectories of acute myeloid leukemia

ABSTRACT

Mutations found in acute myeloid leukemia (AML) such as DNMT3A, TET2, and ASXL1 can be found in the peripheral blood of healthy adults, a phenomenon termed clonal hematopoiesis (CH). These mutations are thought to represent the earliest genetic events in the evolution of AML. Genomic studies on samples acquired at diagnosis, remission, and at relapse have demonstrated significant stability of CH mutations after induction chemotherapy. Meanwhile, later mutations in genes such as NPM1 and FLT3 have been shown to contract at remission, and in the case of FLT3 often are absent at relapse. We sought to understand how early CH mutations influence subsequent evolutionary trajectories throughout remission and relapse in response to induction chemotherapy. We assembled a retrospective cohort of patients diagnosed with de novo AML at our institution that underwent genomic sequencing at diagnosis, remission, and/or relapse (total N = 182 patients). FLT3 and NPM1 mutations were generally eliminated at complete remission but subsequently reemerged upon relapse, whereas DNMT3A, TET2, and ASXL1 mutations often persisted through remission. CH-related mutations exhibited distinct constellations of co-occurring genetic alterations, with NPM1 and FLT3 mutations enriched in DNMT3Amut AML, whereas CBL and SRSF2 mutations were enriched in TET2mut and ASXL1mut AML, respectively. In the case of NPM1 and FLT3 mutations, these differences vanished at the time of complete remission yet readily reemerged upon relapse, indicating the reproducible nature of these genetic interactions. Thus, CH-associated mutations that likely precede malignant transformation subsequently shape the evolutionary trajectories of AML through diagnosis, therapy, and relapse.

Oncogenic gene fusions in cancer: from biology to therapy

Oncogenic gene fusions occur across a broad range of cancers and are a defining feature of some cancer types. Cancers driven by gene fusion products tend to respond well to targeted therapies, where available; thus, detection of potentially targetable oncogenic fusions is necessary to select optimal treatment. Detection methods include non-sequencing methods, such as fluorescence in situ hybridization and immunohistochemistry, and sequencing methods, such as DNA- and RNA-based next-generation sequencing (NGS). While NGS is an efficient way to analyze multiple genes of interest at once, economic and technical factors may preclude its use in routine care globally, despite several guideline recommendations. The aim of this review is to present a summary of oncogenic gene fusions, with a focus on fusions that affect tyrosine kinase signaling, and to highlight the importance of testing for oncogenic fusions. We present an overview of the identification of oncogenic gene fusions and therapies approved for the treatment of cancers harboring gene fusions, and summarize data regarding treating fusion-positive cancers with no current targeted therapies and clinical studies of fusion-positive cancers. Although treatment options may be limited for patients with rare alterations, healthcare professionals should identify patients most likely to benefit from oncogenic gene fusion testing and initiate the appropriate targeted therapy to achieve optimal treatment outcomes.

Advances in cancer genomics and precision oncology

BACKGROUND

Next-generation sequencing has revolutionized genome science over the last two decades. Indeed, the wealth of sequence information on our genome has deepened our understanding on cancer. Cancer is a genetic disease caused by genetic or epigenetic alternations that affect the expression of genes that control cell functions, particularly cell growth and division. Utilization of next-generation sequencing in cancer gene panels has enabled the identification of actionable gene alterations in cancer patients to guide personalized precision medicine.

OBJECTIVE

The aim is to provide information that can identify actionable gene alterations, enabling personalized precision medicine for cancer patients.

RESULTS & DISCUSSION

Equipped with next-generation sequencing techniques, international collaboration programs on cancer genomics have identified numerous mutations, gene fusions, microsatellite variations, copy number variations, and epigenetics changes that promote the transformation of normal cells into tumors. Cancer classification has traditionally been based on cell type or tissue-of-origin and the morphological characteristics of the cancer. However, interactive genomic analyses have currently reclassified cancers based on systemic molecular-based taxonomy. Although all cancer-causing genes and mechanisms have yet to be completely understood or identified, personalized or precision medicine is now currently possible for some forms of cancer. Unlike the "one-size-fits-all" approach of traditional medicine, precision medicine allows for customized or personalized treatment based on genomic information.

CONCLUSION

Despite the availability of numerous cancer gene panels, technological innovation in genomics and expansion of knowledge on the cancer genome will allow precision oncology to manage even more types of cancers.

Allele age estimators designed for whole genome datasets show only a moderate reduction in performance when applied to whole exome datasets

Personalized genomics in the healthcare system is becoming increasingly accessible as the costs of sequencing decreases. With the increase in the number of genomes, larger numbers of rare variants are being discovered, leading to important initiatives in identifying the functional impacts in relation to disease phenotypes. One way to characterize these variants is to estimate the time the mutation entered the population. However, allele age estimators such as those implemented in the programs Relate, Genealogical Estimator of Variant Age (GEVA), and Runtc, were developed based on the assumption that datasets include the entire genome. We examined the performance of each of these estimators on simulated exome data under a neutral constant population size model, as well as under population expansion and background selection models. We found that each provides usable estimates of allele age from whole-exome datasets. Relate performs the best amongst all three estimators with Pearson coefficients of 0.83 and 0.73 (with respect to true simulated values, for neutral constant and expansion population model, respectively) with a 12 percent and 20 percent decrease in correlation between whole genome and whole exome estimations. Of the three estimators, Relate is best able to parallelize to yield quick results with little resources, however, Relate is currently only able to scale to thousands of samples making it unable to match the hundreds of thousands of samples being currently released. While more work is needed to expand the capabilities of current methods of estimating allele age, these methods show a modest decrease in performance in the estimation of the age of mutations.

Inducing apoptosis in acute myeloid leukemia; mechanisms and limitations

Acute myeloid leukemia is the expansion of leukemic stem cells which might originate from a stem cell or a progenitor which has acquired self-renewal capacity. An aggregation of leukemic blasts in bone marrow, peripheral blood, and extramedullary tissue will result in acute myeloid leukemia. The main difficulty in treating acute myeloid leukemia is multidrug resistance, leading to treatment failure. This unfortunate phenomenon is practically elevated because of apoptosis inhibition in tumor cells. Two general apoptotic pathways are the Bcl-2 regulated pathway (the intrinsic pathway) and the death receptor pathway. Deficiencies in each of these apoptotic pathways can cause the usual resistance mechanism in this disease. This article reviews and highlights different antiapoptotic pathways, currently-used treatments, and new findings in this field, which may lead to the development of treatment methods for acute myeloid leukemia.

Comparative small molecule screening of primary human acute leukemias, engineered human leukemia and leukemia cell lines

Targeted therapeutics for high-risk cancers remain an unmet medical need. Here we report the results of a large-scale screen of over 11,000 molecules for their ability to inhibit the survival and growth in vitro of human leukemic cells from multiple sources including patient samples, de novo generated human leukemia models, and established human leukemic cell lines. The responses of cells from de novo models were most similar to those of patient samples, both of which showed striking differences from the cell-line responses. Analysis of differences in subtype-specific therapeutic vulnerabilities made possible by the scale of this screen enabled the identification of new specific modulators of apoptosis, while also highlighting the complex polypharmacology of anti-leukemic small molecules such as shikonin. These findings introduce a new platform for uncovering new therapeutic options for high-risk human leukemia, in addition to reinforcing the importance of the test sample choice for effective drug discovery.

Whole-Genome Sequencing Reveals the Progress of Genetic Breeding in Eriocheir sinensis

Eriocheir sinensis is an important and popular crustacean species in China, producing huge economic benefits. Large individuals of E. sinensis are preferred due to market demand. The long-term goal of our research group is to produce a new variety of E. sinensis with better growth performance and stronger abilities to resist environmental changes through mass selection. The present study aimed to evaluate the progress of the genetic breeding of E. sinensis by analyzing the genetic diversity and genetic distance between the basic breeding population (pooled population of Suqian and Yixing, G0) and generation 1 (G1) using whole-genome sequencing (WGS). The growth traits, including body weight, shell length, shell width, and third appendage length, in the G1 generation increased by 8.3%, 7.9%, 9.6%, and 9.3%, respectively, compared with those of the G0 generation, indicating that the G1 generation showed better growth performance. A total of 372,448,393 high-quality single nucleotide polymorphisms (SNPs) were detected in 40 E. sinensis individuals, with an average of 9,331,209.83 SNPs. The fixation index values were 0.007 between the Yixing and Suqian populations and 0.015 between the G0 generation and G1 generation, indicating a close genetic background between these groups, especially when considered in combination with the phylogenetic tree and principal component analysis. All of these data suggest that genetic information was stably inherited by the G1 generation, with no introduction of foreign genetic information during the genetic breeding process. In addition, the genetic diversity analysis revealed that the G0 and G1 generations showed a high level of genetic diversity and a relatively stable genetic structure. The present study evaluated the recent progress of the genetic improvement of E. sinensis by our research group, providing valuable evidence for further genetic improvement in this species. Future studies will be performed to select growth-related SNPs and genes through genome-wide association studies.

Acute myeloid leukemia management and research in 2025

The first 5 decades of research in acute myeloid leukemia (AML) were dominated by the cytarabine plus anthracyclines backbone, with advances in strategies including allogeneic hematopoietic stem cell transplantation, high-dose cytarabine, supportive care measures, and targeted therapies for the subset of patients with acute promyelocytic leukemia. Since 2017, a turning point in AML research, 12 agents have received regulatory approval for AML in the United States: venetoclax (BCL2 inhibitor); gemtuzumab ozogamicin (CD33 antibody-drug conjugate); midostaurin, gilteritinib, and quizartinib (fms-like tyrosine kinase 3 inhibitors); ivosidenib, olutasidenib, and enasidenib (isocitrate dehydrogenase 1 and 2 inhibitors); oral azacitidine (a partially absorbable formulation); CPX351 (liposomal encapsulation of cytarabine:daunorubicin at a molar ratio of 5:1); glasdegib (hedgehog inhibitor); and recently revumenib (menin inhibitor; approved November 2024). Oral decitabine-cedazuridine, which is approved as a bioequivalent alternative to parenteral hypomethylating agents in myelodysplastic syndrome, can be used for the same purpose in AML. Menin inhibitors, CD123 antibody-drug conjugates, and other antibodies targeting CD123, CD33, and other surface markers are showing promising results. Herein, the authors review the frontline and later line therapies in AML and discuss important research directions.

The Use of Next-Generation Sequencing in Personalized Medicine

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Optimization of Whole-Genome Resequencing Depth for High-Throughput SNP Genotyping in Litopenaeus vannamei

The application of whole-genome resequencing in genetic research is rapidly expanding, yet the impact of sequencing depth on data quality and variant detection remains unclear, particularly in aquaculture species. This study re-sequenced 31 Litopenaeus vannamei (L. vannamei) samples at over 28× sequencing depth using the Illumina NovaSeq system and down-sampled the data to simulate depths from 0.5× to 20×. Results showed that when the sequencing depth was below 10×, the number of SNP identifications increased sharply with the rise in depth, with single nucleotide polymorphisms (SNPs) detected at 10× accounting for approximately 69.16% of those detected at 20×. The genotyping accuracy followed a similar trend to SNP detection results, being approximately 0.90 at 6×. Further analyses showed that the main cause of genotyping errors was the misidentification of heterozygous variants as homozygous variants. Therefore, considering both the quantity and quality of SNPs, a sequencing depth of 10× is recommended for whole-genome studies and genetic mapping, while a depth of 6× is more cost-effective for population structure analysis. This study underscores the importance of selecting optimal sequencing depth to ensure reliable variant detection and high data quality, providing valuable guidance for whole-genome resequencing in shrimp and other aquatic species.

Estimation of demography and mutation rates from one million haploid genomes

As genetic sequencing costs have plummeted, datasets with sizes previously un-thinkable have begun to appear. Such datasets present new opportunities to learn about evolutionary history, particularly via rare alleles that record the very recent past. However, beyond the computational challenges inherent in the analysis of many large-scale datasets, large population-genetic datasets present theoretical problems. In particular, the majority of population-genetic tools require the assumption that each mutant allele in the sample is the result of a single mutation (the "infinite sites" assumption), which is violated in large samples. Here, we present DR EVIL, a method for estimating mutation rates and recent demographic history from very large samples. DR EVIL avoids the infinite-sites assumption by using a diffusion approximation to a branching-process model with recurrent mutation. The branching-process approach limits the method to rare alleles, but, along with recent results, renders tractable likelihoods with recurrent mutation. We show that DR EVIL performs well in simulations and apply it to rare-variant data from a million haploid samples, identifying a signal of mutation-rate heterogeneity within commonly analyzed classes and predicting that in modern sample sizes, most rare variants at sites with high mutation rates represent the descendants of multiple mutation events.

Distinct FLT3 Pathways Gene Expression Profiles in Pediatric De Novo Acute Lymphoblastic and Myeloid Leukemia with FLT3 Mutations: Implications for Targeted Therapy

Activating FLT3 mutations plays a crucial role in leukemogenesis, but identifying the optimal candidates for FLT3 inhibitor therapy remains controversial. This study aims to explore the impacts of FLT3 mutations in pediatric acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) and to compare the mutation profiles between the two types to inspire the targeted application of FLT3 inhibitors. We retrospectively analyzed 243 ALL and 62 AML cases, grouping them into FLT3-mutant and wild-type categories, respectively. We then assessed the associations between FLT3 mutations and the clinical manifestations, genetic characteristics, and prognosis in ALL and AML. Additionally, we compared the distinct features of FLT3 mutations between ALL and AML. In ALL patients, those with FLT3 mutations predominantly exhibited hyperdiploidy (48.6% vs. 14.9%, p < 0.001) and higher FLT3 expression (108.02 [85.11, 142.06] FPKM vs. 23.11 [9.16, 59.14] FPKM, p < 0.001), but lower expression of signaling pathway-related genes such as HRAS, PIK3R3, BAD, MAP2K2, MAPK3, and STAT5A compared to FLT3 wild-type patients. There was no significant difference in prognosis between the two groups. In contrast, AML patients with FLT3 mutations were primarily associated with leucocytosis (82.90 [47.05, 189.76] G/L vs. 20.36 [8.90, 55.39] G/L, p = 0.001), NUP98 rearrangements (30% vs. 4.8%, p = 0.018), elevated FLT3 expression (74.77 [54.31, 109.46] FPKM vs. 34.56 [20.98, 48.28] FPKM, p < 0.001), and upregulated signaling pathway genes including PIK3CB, AKT1, MTOR, BRAF, and MAPK1 relative to FLT3 wild-type, correlating with poor prognosis. Notably, internal tandem duplications were the predominant type of FLT3 mutation in AML (66.7%) with higher inserted base counts, whereas they were almost absent in ALL (6.3%, p < 0.001). In summary, our study demonstrated that the forms and impacts of FLT3 mutations in ALL differed significantly from those in AML. The gene expression profiles of FLT3-related pathways may provide a rationale for using FLT3 inhibitors in AML rather than ALL when FLT3 mutations are present.

Early drivers of clonal hematopoiesis shape the evolutionary trajectories of de novo acute myeloid leukemia

Mutations commonly found in AML such as DNMT3A, TET2 and ASXL1 can be found in the peripheral blood of otherwise healthy adults - a phenomenon referred to as clonal hematopoiesis (CH). These mutations are thought to represent the earliest genetic events in the evolution of AML. Genomic studies on samples acquired at diagnosis, remission, and at relapse have demonstrated significant stability of CH mutations following induction chemotherapy. Meanwhile, later mutations in genes such as NPM1 and FLT3, have been shown to contract at remission and in the case of FLT3 often are absent at relapse. We sought to understand how early CH mutations influence subsequent evolutionary trajectories throughout remission and relapse in response to induction chemotherapy. Here, we assembled a retrospective cohort of patients diagnosed with de novo AML at our institution that underwent genomic sequencing at diagnosis as well as at the time of remission and/or relapse (total n = 182 patients). Corroborating prior studies, FLT3 and NPM1 mutations were generally eliminated at the time of cytologic complete remission but subsequently reemerged upon relapse, whereas DNMT3A, TET2 and ASXL1 mutations often persisted through remission. Early CH-related mutations exhibited distinct constellations of co-occurring genetic alterations, with NPM1 and FLT3 mutations enriched in DNMT3A mut AML, while CBL and SRSF2 mutations were enriched in TET2 mut and ASXL1 mut AML, respectively. In the case of NPM1 and FLT3 mutations, these differences vanished at the time of complete remission yet readily reemerged upon relapse, indicating the reproducible nature of these genetic interactions. Thus, early CH-associated mutations that precede malignant transformation subsequently shape the evolutionary trajectories of AML through diagnosis, therapy, and relapse.

Identification and immunoassay of prognostic genes associated with the complement system in acute myeloid leukemia

Studies have associated the development of pulmonary leukemia with the activation of the complement system. However, the roles and mechanisms of complement system-related genes (CSRGs) in acute myeloid leukemia (AML) have not been investigated extensively. This study used The Cancer Genome Atlas (TCGA)-AML and GSE37642 datasets. Differentially expressed CSRGs (CSRDEGs) were identified by overlapping genes differentially expressed between the high and low CSRG score groups and key module genes identified in a weighted gene co-expression network analysis. Univariate and multivariate Cox analyses identified CSRG-related biomarkers, which were used to build a prognostic model. After gene set enrichment analysis (GSEA), immune-related and drug-sensitivity analyses were performed in the high- and low-risk groups. Four prognosis-related biomarkers were identified and used to develop a prognostic model: MEOX2, IGFBP5, CH25H, and RAB3B. The model's performance was verified in a test cohort (a subset of samples from the TCGA-AML dataset) and a validation cohort (GSE37642). The GSEA revealed that the high-risk group was mainly enriched for Golgi organization and cytokine-cytokine receptor interactions, and the low-risk group was mainly enriched in the hedgehog signaling pathway and spliceosome. Lastly, two immune cells were found to show differential infiltration between risk groups, which correlated with the risk scores. M1 macrophage infiltration was significantly positively correlated with RAB3B expression. Sensitivity to 36 drugs differed significantly between risk groups. This study screened four CSRG-related biomarkers (MEOX2, IGFBP5, CH25H, and RAB3B) to provide a basis for predicting AML prognosis.

CXCR4-Mediated Codelivery of FLT3 and BCL-2 Inhibitors for Enhanced Targeted Combination Therapy of FLT3-ITD Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is often associated with poor prognosis and survival. Small molecule inhibitors, though widening the treatment landscape, have limited monotherapy efficacy. The combination therapy, however, shows suboptimal clinical outcomes due to low bioavailability, overlapping systemic toxicity and drug resistance. Here, we report that CXCR4-mediated codelivery of the BCL-2 inhibitor venetoclax (VEN) and the FLT3 inhibitor sorafenib (SOR) via T22 peptide-tagged disulfide cross-linked polymeric micelles (TM) achieves synergistic treatment of FLT3-ITD AML. TM-VS with a VEN/SOR weight ratio of 1/4 and T22 peptide density of 20% exhibited an extraordinary inhibitory effect on CXCR4-overexpressing MV4-11 AML cells. TM-VS at a VEN/SOR dosage of 2.5/10 mg/kg remarkably reduced leukemia burden, prolonged mouse survival, and impeded bone loss in orthotopic MV4-11-bearing mice, outperforming the nontargeted M-VS and oral administration of free VEN/SOR. CXCR4-mediated codelivery of BCL-2 and FLT3 inhibitors has emerged as a prospective clinical treatment for FLT3-ITD AML.

Epigenetic determinants of fusion-driven sarcomas: paradigms and challenges

We describe exciting recent advances in fusion-driven sarcoma etiology, from an epigenetics perspective. By exploring the current state of the field, we identify and describe the central mechanisms that determine sarcomagenesis. Further, we discuss seminal studies in translational genomics, which enabled epigenetic characterization of fusion-driven sarcomas. Important context for epigenetic mechanisms include, but are not limited to, cell cycle and metabolism, core regulatory circuitry, 3-dimensional chromatin architectural dysregulation, integration with ATP-dependent chromatin remodeling, and translational animal modeling. Paradoxically, while the genetic requirements for oncogenic transformation are highly specific for the fusion partners, the epigenetic mechanisms we as a community have uncovered are categorically very broad. This dichotomy prompts the question of whether the investigation of rare disease epigenomics should prioritize studying individual cell populations, thereby examining whether the mechanisms of chromatin dysregulation are specific to a particular tumor. We review recent advances focusing on rhabdomyosarcoma, synovial sarcoma, alveolar soft part sarcoma, clear cell sarcoma, undifferentiated round cell sarcoma, Ewing sarcoma, myxoid/round liposarcoma, epithelioid hemangioendothelioma and desmoplastic round cell tumor. The growing number of groundbreaking discoveries in the field, motivated us to anticipate further exciting advances in the area of mechanistic epigenomics and direct targeting of fusion transcription factors in the years ahead.

Comprehensive insights into AML relapse: genetic mutations, clonal evolution, and clinical outcomes

INTRODUCTION

Acute myeloid leukemia (AML) is a complex hematologic malignancy characterized by uncontrolled proliferation of myeloid precursor cells within bone marrow. Despite advances in understanding of its molecular underpinnings, AML remains a therapeutic challenge due to its high relapse rate and clonal evolution.

METHODS

In this retrospective study, we analyzed data from 24 AML patients diagnosed at a single institution between January 2017 and August 2023. Comprehensive genetic analyses, including chromosomal karyotyping, next-generation sequencing, and gene fusion assays, were performed on bone marrow samples obtained at initial diagnosis and relapse. Clinical data, treatment regimens, and patient outcomes were also documented.

RESULTS

Mutations in core genes of FLT3, NPM1, DNMT3A, and IDH2 were frequently discovered in diagnostic sample and remained in relapse sample. FLT3-ITD, TP53, KIT, RUNX1, and WT1 mutation were acquired at relapse in one patient each. Gene fusion assays revealed stable patterns, while chromosomal karyotype analyses indicated a greater diversity of mutations in relapsed patients. Clonal evolution patterns varied, with some cases showing linear or branching evolution and others exhibiting no substantial change in core mutations between diagnosis and relapse.

CONCLUSIONS

Our study integrates karyotype, gene rearrangements, and gene mutation results to provide a further understanding of AML heterogeneity and evolution. We demonstrate the clinical relevance of specific mutations and clonal evolution patterns, emphasizing the need for personalized therapies and measurable residual disease monitoring in AML management. By bridging the gap between genetics and clinical outcome, we move closer to tailored AML therapies and improved patient prognoses.

Revolutionizing personalized cancer treatment: the synergy of next-generation sequencing and CRISPR/Cas9

In the context of cancer heterogeneity, the synergistic action of next-generation sequencing (NGS) and CRISPR/Cas9 plays a promising role in the personalized treatment of cancer. NGS enables high-throughput genomic profiling of tumors and pinpoints specific mutations that primarily lead to cancer. Oncologists use this information obtained from NGS in the form of DNA profiling or RNA analysis to tailor precision strategies based on an individual's unique molecular signature. Furthermore, the CRISPR technique enables precise editing of cancer-specific mutations, allowing targeted gene modifications. Harnessing the potential insights of NGS and CRISPR/Cas9 heralds a remarkable frontier in cancer therapeutics with unprecedented precision, effectiveness and minimal off-target effects.

Assessment of selective breeding effects and selection signatures in Qingyuan partridge chicken and its strains

Qingyuan partridge chicken (QYM) is a highly regarded native breed in China, highly esteemed for its exceptional breeding characteristics. However, the investigation into the selection signatures and its strains remains largely unexplored. In this study, blood sampling, DNA extracting, and high-depth resequencing were performed in 27 QYMs. Integrating the genomic data of 14 chicken (70 individuals) breeds from other researches, to analyze the genetic structure, selection signatures, and effects of selective breeding within QYM and its 3 strains (QYMA, QYMB, and QYMC). Population structure analysis revealed an independent QYM cluster, which exhibited distinct from other breeds, with each of its 3 strains displaying distinct clustering patterns. Linkage disequilibrium analysis highlighted QYMB's notably slower decay rate, potentially influenced by selection pressure from various production indicators. Examination of selection signatures uncovered genes and genetic mechanisms associated with genomic changes resulting from extensive selective breeding within the QYM and its strains. Intriguingly, diacylglycerol kinase beta (DGKB) and catenin alpha 2 (CTNNA2) were identified as commonly selected genes across the 3 QYM strains, linked to energy metabolism, muscle development, and fat metabolism. Our research validates the substantial impact of selective breeding on QYM and its strains, concurrently identifying genomic regions and signaling pathways associated with their distinctive characters. This research also establishes a fundamental framework for advancing yellow-feathered broiler breeding strategies.

Impact of Clonal Heterogeneity in Multiple Myeloma

Multiple myeloma is characterized by a highly heterogeneous disease distribution within the bone marrow-containing skeletal system. In this review, we introduce the molecular mechanisms underlying clonal heterogeneity and the spatio-temporal evolution of myeloma. We discuss the clinical impact of clonal heterogeneity, which is thought to be one of the biggest obstacles to overcome therapy resistance and to achieve cure.

Current and emerging sequencing-based tools for precision cancer medicine

Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.

Innovations in conditioning and post-transplant maintenance in AML: genomically informed revelations on the graft-versus-leukemia effect

Acute Myeloid Leukemia (AML) is the prototype of cancer genomics as it was the first published cancer genome. Large-scale next generation/massively parallel sequencing efforts have identified recurrent alterations that inform prognosis and have guided the development of targeted therapies. Despite changes in the frontline and relapsed standard of care stemming from the success of small molecules targeting FLT3, IDH1/2, and apoptotic pathways, allogeneic stem cell transplantation (alloHSCT) and the resulting graft-versus-leukemia (GVL) effect remains the only curative path for most patients. Advances in conditioning regimens, graft-vs-host disease prophylaxis, anti-infective agents, and supportive care have made this modality feasible, reducing transplant related mortality even among patients with advanced age or medical comorbidities. As such, relapse has emerged now as the most common cause of transplant failure. Relapse may occur after alloHSCT because residual disease clones persist after transplant, and develop immune escape from GVL, or such clones may proliferate rapidly early after alloHSCT, and outpace donor immune reconstitution, leading to relapse before any GVL effect could set in. To address this issue, genomically informed therapies are increasingly being incorporated into pre-transplant conditioning, or as post-transplant maintenance or pre-emptive therapy in the setting of mixed/falling donor chimerism or persistent detectable measurable residual disease (MRD). There is an urgent need to better understand how these emerging therapies modulate the two sides of the GVHD vs. GVL coin: 1) how molecularly or immunologically targeted therapies affect engraftment, GVHD potential, and function of the donor graft and 2) how these therapies affect the immunogenicity and sensitivity of leukemic clones to the GVL effect. By maximizing the synergistic action of molecularly targeted agents, immunomodulating agents, conventional chemotherapy, and the GVL effect, there is hope for improving outcomes for patients with this often-devastating disease.

The use of next-generation sequencing in personalized medicine

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Prognostic implications of cGAS and STING gene expression in acute myeloid leukemia

Acute myeloid leukemia (AML) is one of the most threatening hematological malignances. cGAS-STING pathway plays an important role in tumor immunity and development. However, the prognostic role of cGAS-STING pathway in AML remains unknown. Firstly, The expression of cGAS and STING was analyzed by bioinformatics analysis. Subsequently, Bone marrow samples were collected from 120 AML patients and 15 healthy individuals in an independent cohort. The cGAS and STING expression was significantly elevated in AML patients compared with healthy controls. Patients with high cGAS and STING expression had a higher NRAS/KRAS mutation rate and lower complete remission (CR) rate. High cGAS and STING expression was significantly associated with lower overall survival (OS) and disease-free survival (DFS). Our findings revealed that the expression levels of cGAS and STING in AML are elevated. High expression of cGAS and STING correlated with worse OS and DFS and may be a useful biomarker for inferior prognosis in AML patients.

Outcomes of acute myeloid leukemia patients undergoing allogeneic hematopoietic stem cell transplantation: validation, comparison and improvement of 2022 ELN genetic risk system

The 2022 European LeukemiaNet (ELN) updated the previous risk classification published in 2017 but the prognostic significance for allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains unclear. We enrolled 600 acute myeloid leukemia (AML) patients who underwent allo-HSCT to validate ELN-2022 genetic risk system and compared it with ELN-2017. There were 214 (35.67%), 162 (27.0%), and 224 (37.33%) patients in ELN-2022 favorable-, intermediate-, and adverse-risk group respectively and 86 patients (14.33%) experienced a shift in risk stratification compared to ELN-2017. Median and maximum follow-up time were 2.89 (95% CI 2.67 to 3.03) years and 8.78 years. The median overall survival (OS) was 73.8% (95% CI 67.5% to 80.3%), 63.9% (95% CI 56.7% to 72.0%) and 57.6% (95% CI 50.4% to 65.9%) in ELN-2022 favorable-, intermediate-, and adverse-risk group (P < 0.001). OS shortened significantly as the ELN-2022 risk stratification increased but didn't significantly in ELN-2017 intermediate-risk compared to favorable-risk. Both ELN-2022 and ELN-2017 adverse-risk were associated with increased cumulative incidence of relapse (CIR). Time-dependent receiver operating characteristic (ROC) analysis showed that both ELN-2017 and ELN-2022 risk systems had limited prognostic ability for OS. We modified ELN-2022 risk system with pre-transplant minimal residual disease (MRD) and the modified risk system performed a significantly superior efficacy to ELN-2022 system.

Structurally-informed human interactome reveals proteome-wide perturbations by disease mutations

Human genome sequencing studies have identified numerous loci associated with complex diseases. However, translating human genetic and genomic findings to disease pathobiology and therapeutic discovery remains a major challenge at multiscale interactome network levels. Here, we present a deep-learning-based ensemble framework, termed PIONEER (Protein-protein InteractiOn iNtErfacE pRediction), that accurately predicts protein binding partner-specific interfaces for all known protein interactions in humans and seven other common model organisms, generating comprehensive structurally-informed protein interactomes. We demonstrate that PIONEER outperforms existing state-of-the-art methods. We further systematically validated PIONEER predictions experimentally through generating 2,395 mutations and testing their impact on 6,754 mutation-interaction pairs, confirming the high quality and validity of PIONEER predictions. We show that disease-associated mutations are enriched in PIONEER-predicted protein-protein interfaces after mapping mutations from ~60,000 germline exomes and ~36,000 somatic genomes. We identify 586 significant protein-protein interactions (PPIs) enriched with PIONEER-predicted interface somatic mutations (termed oncoPPIs) from pan-cancer analysis of ~11,000 tumor whole-exomes across 33 cancer types. We show that PIONEER-predicted oncoPPIs are significantly associated with patient survival and drug responses from both cancer cell lines and patient-derived xenograft mouse models. We identify a landscape of PPI-perturbing tumor alleles upon ubiquitination by E3 ligases, and we experimentally validate the tumorigenic KEAP1-NRF2 interface mutation p.Thr80Lys in non-small cell lung cancer. We show that PIONEER-predicted PPI-perturbing alleles alter protein abundance and correlates with drug responses and patient survival in colon and uterine cancers as demonstrated by proteogenomic data from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium. PIONEER, implemented as both a web server platform and a software package, identifies functional consequences of disease-associated alleles and offers a deep learning tool for precision medicine at multiscale interactome network levels.

Population genetic structure of Hymenopellis radicata germplasm resources based on genome re-sequencing

Through whole-genome re-sequencing of 18 Hymenopellis radicata germplasm resources collected from diverse regions in China, we identified significant variations in the form of Single Nucleotide Polymorphisms (SNPs) and Insertions and Deletions (InDels). These variations were comprehensively annotated, shedding light on the mutation types present in the entire genome of the H. radicata germplasm. This analysis revealed the number and position information of each mutation and provided insights into the overall genomic landscape of H. radicata germplasm. Utilizing SNP data, we delved into the population structure of the 18 H. radicata germplasm resources. The results indicated the presence of 2,335,179 Indel sites and 12,050,448 SNP sites. The population structure analysis unveiled two distinct subgroups among the H. radicata germplasm resources. Phenotypic statistics, principal component analysis, and phylogenetic tree results echoed the findings of the population structure analysis. Different strains of H. radicata from various regions in China exhibited notable differences in genetic diversity, mycelial growth rate, yield, and fruiting body characteristics. Significant disparities were observed between the two subgroups, while strains within each subgroup shared common characteristics. This research establishes a solid foundation for integrating H. radicata into diverse breeding programs. The data underscore the potential of H. radicata for genetic improvement and exploitation in breeding initiatives, paving the way for future advancements in this field.

Detection of Genomic Structural Variations Associated with Drug Sensitivity and Resistance in Acute Leukemia

Acute leukemia is a particularly problematic collection of hematological cancers, and, while somewhat rare, the survival rate of patients is typically abysmal without bone marrow transplantation. Furthermore, traditional chemotherapies used as standard-of-care for patients cause significant side effects. Understanding the evolution of leukemia to identify novel targets and, therefore, drug treatment regimens is a significant medical need. Genomic rearrangements and other structural variations (SVs) have long been known to be causative and pathogenic in multiple types of cancer, including leukemia. These SVs may be involved in cancer initiation, progression, clonal evolution, and drug resistance, and a better understanding of SVs from individual patients may help guide therapeutic options. Here, we show the utilization of optical genome mapping (OGM) to detect known and novel SVs in the samples of patients with leukemia. Importantly, this technology provides an unprecedented level of granularity and quantitation unavailable to other current techniques and allows for the unbiased detection of novel SVs, which may be relevant to disease pathogenesis and/or drug resistance. Coupled with the chemosensitivities of these samples to FDA-approved oncology drugs, we show how an impartial integrative analysis of these diverse datasets can be used to associate the detected genomic rearrangements with multiple drug sensitivity profiles. Indeed, an insertion in the gene MUSK is shown to be associated with increased sensitivity to the clinically relevant agent Idarubicin, while partial tandem duplication events in the KMT2A gene are related to the efficacy of another frontline treatment, Cytarabine.

Glioma: bridging the tumor microenvironment, patient immune profiles and novel personalized immunotherapy

Glioma is the most common primary brain tumor, characterized by a consistently high patient mortality rate and a dismal prognosis affecting both survival and quality of life. Substantial evidence underscores the vital role of the immune system in eradicating tumors effectively and preventing metastasis, underscoring the importance of cancer immunotherapy which could potentially address the challenges in glioma therapy. Although glioma immunotherapies have shown promise in preclinical and early-phase clinical trials, they face specific limitations and challenges that have hindered their success in further phase III trials. Resistance to therapy has been a major challenge across many experimental approaches, and as of now, no immunotherapies have been approved. In addition, there are several other limitations facing glioma immunotherapy in clinical trials, such as high intra- and inter-tumoral heterogeneity, an inherently immunosuppressive microenvironment, the unique tissue-specific interactions between the central nervous system and the peripheral immune system, the existence of the blood-brain barrier, which is a physical barrier to drug delivery, and the immunosuppressive effects of standard therapy. Therefore, in this review, we delve into several challenges that need to be addressed to achieve boosted immunotherapy against gliomas. First, we discuss the hurdles posed by the glioma microenvironment, particularly its primary cellular inhabitants, in particular tumor-associated microglia and macrophages (TAMs), and myeloid cells, which represent a significant barrier to effective immunotherapy. Here we emphasize the impact of inducing immunogenic cell death (ICD) on the migration of Th17 cells into the tumor microenvironment, converting it into an immunologically "hot" environment and enhancing the effectiveness of ongoing immunotherapy. Next, we address the challenge associated with the accurate identification and characterization of the primary immune profiles of gliomas, and their implications for patient prognosis, which can facilitate the selection of personalized treatment regimens and predict the patient's response to immunotherapy. Finally, we explore a prospective approach to developing highly personalized vaccination strategies against gliomas, based on the search for patient-specific neoantigens. All the pertinent challenges discussed in this review will serve as a compass for future developments in immunotherapeutic strategies against gliomas, paving the way for upcoming preclinical and clinical research endeavors.

Technologies to Study Genetics and Molecular Pathways

Over the last few decades, the study of congenital heart disease (CHD) has benefited from various model systems and the development of molecular biological techniques enabling the analysis of single gene as well as global effects. In this chapter, we first describe different models including CHD patients and their families, animal models ranging from invertebrates to mammals, and various cell culture systems. Moreover, techniques to experimentally manipulate these models are discussed. Second, we introduce cardiac phenotyping technologies comprising the analysis of mouse and cell culture models, live imaging of cardiogenesis, and histological methods for fixed hearts. Finally, the most important and latest molecular biotechniques are described. These include genotyping technologies, different applications of next-generation sequencing, and the analysis of transcriptome, epigenome, proteome, and metabolome. In summary, the models and technologies presented in this chapter are essential to study the function and development of the heart and to understand the molecular pathways underlying CHD.

The Genomic Characteristics of an Arthritis-Causing Salmonella pullorum

Salmonella enterica subsp. enterica serovar Gallinarum biovar pullorum (Salmonella pullorum) is an avian-specific pathogen that has caused considerable economic losses to the poultry industry. High endemicity, poor implementation of hygiene measures, and lack of effective vaccines hinder the prevention and control of this disease in intensively maintained poultry flocks. In recent years, the incidence of arthritis in chicks caused by Salmonella pullorum infection has increased. In this study, four Salmonella pullorum strains were identified from the livers, spleens, and joint fluids of Qingjiaoma chicken breeders with arthritis clinical signs, and an arthritis model of chicks was successfully established using SP206-2. Whole genome sequencing of the SP206-2 strain showed that the genome was 4,730,579 bp, 52.16% GC content, and contained 5007 genes, including 4729 protein-coding regions. The genomic analysis of four arthritis-causing isolates and three diarrhea-causing isolates showed that the genome of arthritis-causing isolates was subject to nonsynonymous mutations, shift mutations, and gene copy deletions. An SNP phylogenetic tree analysis showed that arthritis-causing isolates are located in a different evolutionary branch from diarrhea-causing isolates. Further differential genes analysis showed that the genome of arthritis-causing isolates had missense mutations in genes related to substance metabolism and substance transport, as a result of adaptive evolution.

Combining Transcriptome and Whole Genome Re-Sequencing to Screen Disease Resistance Genes for Wheat Dwarf Bunt

Wheat dwarf bunt is a damaging disease caused by Tilletia controversa Kühn (TCK). Once the disease infects wheat, it is difficult to control and will significantly reduce wheat output and quality. RNA sequencing and whole genome re-sequencing were used to search for potential TCK resistance genes in Yili 053 (sensitive variety) and Zhongmai 175 (moderately resistant variety) in the mid-filling, late-filling, and maturity stages. The transcriptomic analysis revealed 11 potential disease resistance genes. An association analysis of the findings from re-sequencing found nine genes with single nucleotide polymorphism mutations. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that three up-regulated genes were involved in the synthesis of benzoxazinone and tryptophan metabolism. Additionally, quantitative real-time polymerase chain reaction confirmed the RNA sequencing results. The results revealed novel TCK resistance genes and provide a theoretical basis for researching the function of resistance genes and molecular breeding.

Analytic Validation of Optical Genome Mapping in Hematological Malignancies

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Standard-of-care (SOC) methods such as karyotyping and fluorescence in situ hybridization (FISH), which have been employed globally for the past three decades, have significant limitations in terms of resolution and the number of recurrent aberrations that can be simultaneously assessed, respectively. Next-generation sequencing (NGS)-based technologies are now widely used to detect clinically significant sequence variants but are limited in their ability to accurately detect SVs. Optical genome mapping (OGM) is an emerging technology enabling the genome-wide detection of all classes of SVs at a significantly higher resolution than karyotyping and FISH. OGM requires neither cultured cells nor amplification of DNA, addressing the limitations of culture and amplification biases. This study reports the clinical validation of OGM as a laboratory-developed test (LDT) according to stringent regulatory (CAP/CLIA) guidelines for genome-wide SV detection in different hematological malignancies. In total, 60 cases with hematological malignancies (of various subtypes), 18 controls, and 2 cancer cell lines were used for this study. Ultra-high-molecular-weight DNA was extracted from the samples, fluorescently labeled, and run on the Bionano Saphyr system. A total of 215 datasets, Inc.luding replicates, were generated, and analyzed successfully. Sample data were then analyzed using either disease-specific or pan-cancer-specific BED files to prioritize calls that are known to be diagnostically or prognostically relevant. Sensitivity, specificity, and reproducibility were 100%, 100%, and 96%, respectively. Following the validation, 14 cases and 10 controls were run and analyzed using OGM at three outside laboratories showing reproducibility of 96.4%. OGM found more clinically relevant SVs compared to SOC testing due to its ability to detect all classes of SVs at higher resolution. The results of this validation study demonstrate the superiority of OGM over traditional SOC methods for the detection of SVs for the accurate diagnosis of various hematological malignancies.

Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Reveals Widespread Degeneration from Focal Mutations

Although mutations in dozens of genes have been implicated in familial forms of amyotrophic lateral sclerosis (fALS) and frontotemporal degeneration (fFTD), most cases of these conditions are sporadic (sALS and sFTD), with no family history, and their etiology remains obscure. We tested the hypothesis that somatic mosaic mutations, present in some but not all cells, might contribute in these cases, by performing ultra-deep, targeted sequencing of 88 genes associated with neurodegenerative diseases in postmortem brain and spinal cord samples from 404 individuals with sALS or sFTD and 144 controls. Known pathogenic germline mutations were found in 20.6% of ALS, and 26.5% of FTD cases. Predicted pathogenic somatic mutations in ALS/FTD genes were observed in 2.7% of sALS and sFTD cases that did not carry known pathogenic or novel germline mutations. Somatic mutations showed low variant allele fraction (typically <2%) and were often restricted to the region of initial discovery, preventing detection through genetic screening in peripheral tissues. Damaging somatic mutations were preferentially enriched in primary motor cortex of sALS and prefrontal cortex of sFTD, mirroring regions most severely affected in each disease. Somatic mutation analysis of bulk RNA-seq data from brain and spinal cord from an additional 143 sALS cases and 23 controls confirmed an overall enrichment of somatic mutations in sALS. Two adult sALS cases were identified bearing pathogenic somatic mutations in DYNC1H1 and LMNA, two genes associated with pediatric motor neuron degeneration. Our study suggests that somatic mutations in fALS/fFTD genes, and in genes associated with more severe diseases in the germline state, contribute to sALS and sFTD, and that mosaic mutations in a small fraction of cells in focal regions of the nervous system can ultimately result in widespread degeneration.

Harnessing tumor immunogenomics: Tumor neoantigens in ovarian cancer and beyond

Ovarian cancer is a major cause of death among gynecological cancers due to its highly aggressive nature. Immunotherapy has emerged as a promising avenue for ovarian cancer treatment, offering targeted approaches with reduced off-target effects. With the advent of next-generation sequencing, it has become possible to identify genomic alterations that can serve as potential targets for immunotherapy. Furthermore, immunogenomics research has revealed the importance of genetic alterations in shaping the cancer immune responses. However, the heterogeneity of immunogenicity and the low tumor mutation burden pose challenges for neoantigen-based immunotherapies. Further research is needed to identify neoantigen-specific tumor-infiltrating lymphocytes (TIL) and establish guidelines for patient inclusion criteria in TIL-based therapy. The study of neoantigens and their implications in ovarian cancer immunotherapy holds great promise, and efforts focused on personalized treatment strategies, refined neoantigen selection, and optimized therapeutic combinations will contribute to improving patient outcomes in the future.

Influence on therapeutic outcome of platelet count at diagnosis in patients with de novo non-APL acute myeloid leukemia

BACKGROUND

Platelet (PLT) count at diagnosis plays an important role in cancer development and progression in solid tumors. However, it remains controversial whether PLT count at diagnosis influences therapeutic outcome in patients with non-acute promyelocytic leukemia (APL) acute myeloid leukemia (AML).

METHODS

This study analyzed the relationship between PLT count at diagnosis and genetic mutations in a cohort of 330 newly diagnosed non-APL AML patients. The impact of PLT count on complete remission, minimal residual disease status and relapse-free survival (RFS) were evaluated after chemotherapy or allogeneic hematopoietic stem cell transplantation (allo-HSCT).

RESULTS

Our studies showed that patients with DNMT3A mutations have a higher PLT count at diagnosis, while patients with CEBPA biallelic mutations or t(8;21)(q22; q22) translocation had lower PLT count at diagnosis. Furthermore, non-APL AML patients with high platelet count (> 65 × 109/L) at diagnosis had worse response to induction chemotherapy and RFS than those with low PLT count. In addition, allo-HSCT could not absolutely attenuated the negative impact of high PLT count on the survival of non-APL AML patients.

CONCLUSION

PLT count at diagnosis has a predictive value for therapeutic outcome for non-APL AML patients.

Genomics and transcriptomic alterations of the glutamate receptors in acute myeloid leukemia

Glutamine and glutamate have been widely explored as potential therapeutic targets in acute myeloid leukemia (AML). In addition to its bioenergetic role in leukemia cell proliferation, L-glutamate is a neurotransmitter that acts on glutamate receptors. However, the role of glutamate receptors in AML is largely understudied. Here, we comprehensively analyze the genomic and transcriptomic alterations of glutamate receptor genes in AML using publicly available data. We investigated the frequency of mutations in the glutamate receptor genes and whether an association exist between the presence of these mutations and clinical and molecular characteristics or patient's clinical outcome. We also assessed the dysregulation of glutamate receptor gene expression in AML with and without mutations and whether gene dysregulation is associated with clinical outcomes. We found that 29 (14.5%) of 200 patients with AML had a mutation in at least one glutamate receptor gene. The DNMT3A mutations were significantly more frequent in patients with mutations in at least one glutamate receptor gene compared with patients without mutations (13 of 29 [44.8%] vs. 41 of 171 [23.9%], p value: 0.02). Notably, patients with mutations in at least one glutamate receptor gene survived shorter than patients without mutations; however, the results did not reach statistical significance (overall survival: 15.5 vs. 19.0 months; p value: 0.10). Mutations in the glutamate receptor genes were not associated with changes in gene expression and the transcriptomic levels of glutamate receptor genes were not associated with clinical outcome.

Current Status of Next-Generation Sequencing in Bone Genetic Diseases

The development of next-generation sequencing (NGS) has dramatically increased the speed and volume of genetic analysis. Furthermore, the range of applications of NGS is rapidly expanding to include genome, epigenome (such as DNA methylation), metagenome, and transcriptome analyses (such as RNA sequencing and single-cell RNA sequencing). NGS enables genetic research by offering various sequencing methods as well as combinations of methods. Bone tissue is the most important unit supporting the body and is a reservoir of calcium and phosphate ions, which are important for physical activity. Many genetic diseases affect bone tissues, possibly because metabolic mechanisms in bone tissue are complex. For instance, the presence of specialized immune cells called osteoclasts in the bone tissue, which absorb bone tissue and interact with osteoblasts in complex ways to support normal vital functions. Moreover, the many cell types in bones exhibit cell-specific proteins for their respective activities. Mutations in the genes encoding these proteins cause a variety of genetic disorders. The relationship between age-related bone tissue fragility (also called frailty) and genetic factors has recently attracted attention. Herein, we discuss the use of genomic, epigenomic, transcriptomic, and metagenomic analyses in bone genetic disorders.

Precision and strategic targeting of novel mutation-specific vulnerabilities in acute myeloid leukemia: the semi-centennial of 7 + 3

The year 2023 marks the semi-centennial of the introduction of classic '7 + 3' chemotherapy for acute myeloid leukemia (AML) in 1973. It also marks the decennial of the first comprehensive sequencing efforts from The Cancer Genome Atlas (TCGA), which revealed that dozens of unique genes are recurrently mutated in AML genomes. Although more than 30 distinct genes have been implicated in AML pathogenesis, the current therapeutic armamentarium that is commercially available only targets FLT3 and IDH1/2 mutations, with olutasidenib as the most recent addition. This focused review spotlights management approaches that exploit the exquisite molecular dependencies of specific subsets of AML, with an emphasis on emerging therapies in the pipeline, including agents targeting TP53-mutant cells. We summarize precision and strategic targeting of AML based on leveraging functional dependencies and explore how mechanisms involving critical gene products can inform rational therapeutic design in 2024.

Pediatric acute myeloid leukemia: Insight into genetic landscape and novel targeted approaches

Acute myeloid leukemia (AML) is a very heterogeneous hematological malignancy that accounts for approximately 20% of all pediatric leukemia cases. The outcome of pediatric AML has improved over the last decades, with overall survival rates reaching up to 70%. Still, AML is among the leading types of pediatric cancers by its high mortality rate. Modulation of standard therapy, like chemotherapy intensification, hematopoietic stem cell transplantation and optimized supportive care, could only get this far, but for the significant improvement of the outcome in pediatric AML, development of novel targeted therapy approaches is necessary. In recent years the advances in genomic techniques have greatly expanded our knowledge of the AML biology, revealing molecular landscape and complexity of the disease, which in turn have led to the identification of novel therapeutic targets. This review provides a brief overview of the genetic landscape of pediatric AML, and how it's used for precise molecular characterization and risk stratification of the patients, and also for the development of effective targeted therapy. Furthermore, this review presents recent advances in molecular targeted therapy and immunotherapy with an emphasis on the therapeutic approaches with significant clinical benefits for pediatric AML.

Clonal evolution and hierarchy in myeloid malignancies

Myeloid malignancies, a group of hematopoietic disorders that includes acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPNs), are caused by the accumulation of genetic and epigenetic changes in hematopoietic stem and progenitor cells (HSPCs) over time. Despite the relatively low number of genomic drivers compared with other forms of cancer, the process by which these changes shape the genomic architecture of myeloid malignancies remains elusive. Recent advancements in clonal hematopoiesis research and the use of cutting-edge single cell technologies have shed new light on the developmental process of myeloid malignancies. In this review, we delve into the intricacies of clonal evolution in myeloid malignancies and its implications for the development of new diagnostic and therapeutic approaches.

A biallelic multiple nucleotide length polymorphism explains functional causality at 5p15.33 prostate cancer risk locus

To date, single-nucleotide polymorphisms (SNPs) have been the most intensively investigated class of polymorphisms in genome wide associations studies (GWAS), however, other classes such as insertion-deletion or multiple nucleotide length polymorphism (MNLPs) may also confer disease risk. Multiple reports have shown that the 5p15.33 prostate cancer risk region is a particularly strong expression quantitative trait locus (eQTL) for Iroquois Homeobox 4 (IRX4) transcripts. Here, we demonstrate using epigenome and genome editing that a biallelic (21 and 47 base pairs (bp)) MNLP is the causal variant regulating IRX4 transcript levels. In LNCaP prostate cancer cells (homozygous for the 21 bp short allele), a single copy knock-in of the 47 bp long allele potently alters the chromatin state, enabling de novo functional binding of the androgen receptor (AR) associated with increased chromatin accessibility, Histone 3 lysine 27 acetylation (H3K27ac), and ~3-fold upregulation of IRX4 expression. We further show that an MNLP is amongst the strongest candidate susceptibility variants at two additional prostate cancer risk loci. We estimated that at least 5% of prostate cancer risk loci could be explained by functional non-SNP causal variants, which may have broader implications for other cancers GWAS. More generally, our results underscore the importance of investigating other classes of inherited variation as causal mediators of human traits.

The Progression in Developing Genomic Resources for Crop Improvement

Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques.

Emerging small molecular inhibitors as targeted therapies for high-risk acute myeloid leukemias

INTRODUCTION

Acute myeloid leukemia (AML) is an aggressive disease which has traditionally been treated with intensive chemotherapy. Survival in patients with high-risk cytogenetic and molecular subsets has been poor with this approach due to suboptimal responses seen with intensive chemotherapy and due to many patients with higher risk disease being older and unable to tolerate intensive therapies. In recent years, several targeted therapies have been under investigation for patients with high-risk AML subsets.

AREAS COVERED

This review covers four different subsets of high-risk AML including TP53-mutated, KMT2A-rearranged, FLT3-mutated, and secondary AML developing after prior hypomethylating agent exposure. The research discussed in this review focuses on small molecule inhibitors that have been studied in the treatment of these high-risk AML subsets.

EXPERT OPINION

There are several small molecule inhibitors that have demonstrated promise in these high-risk AML subsets. Longer follow-up and ongoing investigation are needed to continue to optimize therapy for patients with high-risk AML.

The Interplay between Dysregulated Metabolism and Epigenetics in Cancer

Cellular metabolism (or energetics) and epigenetics are tightly coupled cellular processes. It is arguable that of all the described cancer hallmarks, dysregulated cellular energetics and epigenetics are the most tightly coregulated. Cellular metabolic states regulate and drive epigenetic changes while also being capable of influencing, if not driving, epigenetic reprogramming. Conversely, epigenetic changes can drive altered and compensatory metabolic states. Cancer cells meticulously modify and control each of these two linked cellular processes in order to maintain their tumorigenic potential and capacity. This review aims to explore the interplay between these two processes and discuss how each affects the other, driving and enhancing tumorigenic states in certain contexts.