Circulating microbial content in myeloid malignancy patients is associated with disease subtypes and patient outcomes

Intestinal microbiome and myelodysplastic syndromes: Current state of knowledge and perspectives for future

The intestinal microbiome has been mechanistically linked with health and many disease processes. Cancer is no exception. Both in solid tumors and hematologic malignancies, there is increasing evidence supporting the involvement of the intestinal microbiome in tumor development, disease progression, response to treatment, and treatment toxicity. Consistent with microbiome mediation of the immune system and the potent effect of the immune system on cancer, the most compelling evidence has been obtained in the setting of cancer immunotherapy. Here, we review the current state of knowledge about microbiome effects in myelodysplastic syndromes, identify gaps and challenges in related research, and provide insights for future work.

From microbes to medicine: harnessing the power of the microbiome in esophageal cancer

Esophageal cancer (EC) is a malignancy with a high incidence and poor prognosis, significantly influenced by dysbiosis in the esophageal, oral, and gut microbiota. This review provides an overview of the roles of microbiota dysbiosis in EC pathogenesis, emphasizing their impact on tumor progression, drug efficacy, biomarker discovery, and therapeutic interventions. Lifestyle factors like smoking, alcohol consumption, and betel nut use are major contributors to dysbiosis and EC development. Recent studies utilizing advanced sequencing have revealed complex interactions between microbiota dysbiosis and EC, with oral pathogens such as Porphyromonas gingivalis and Fusobacterium nucleatum promoting inflammation and suppressing immune responses, thereby driving carcinogenesis. Altered esophageal microbiota, characterized by reduced beneficial bacteria and increased pathogenic species, further exacerbate local inflammation and tumor growth. Gut microbiota dysbiosis also affects systemic immunity, influencing chemotherapy and immunotherapy efficacy, with certain bacteria enhancing or inhibiting treatment responses. Microbiota composition shows potential as a non-invasive biomarker for early detection, prognosis, and personalized therapy. Novel therapeutic strategies targeting the microbiota-such as probiotics, dietary modifications, and fecal microbiota transplantation-offer promising avenues to restore balance and improve treatment efficacy, potentially enhancing patient outcomes. Integrating microbiome-focused strategies into current therapeutic frameworks could improve EC management, reduce adverse effects, and enhance patient survival. These findings highlight the need for further research into microbiota-tumor interactions and microbial interventions to transform EC treatment and prevention, particularly in cases of late-stage diagnosis and poor treatment response.

Star wars against leukemia: attacking the clones

Leukemia, although most likely starts as a monoclonal genetic/epigenetic anomaly, is a polyclonal disease at manifestation. This polyclonal nature results from ongoing evolutionary changes in the genome/epigenome of leukemia cells to promote their survival and proliferation advantages. We discuss here how genetic and/or epigenetic aberrations alter intracellular microenvironment in individual leukemia clones and how extracellular microenvironment selects the best fitted clones. This dynamic polyclonal composition of leukemia makes designing an effective therapy a challenging task especially because individual leukemia clones often display substantial differences in response to treatment. Here, we discuss novel therapeutic approach employing single cell multiomics to identify and eradicate all individual clones in a patient.

A View of Myeloid Transformation through the Hallmarks of Cancer

The development of myeloid malignancies is influenced by a range of cell-intrinsic and cell-extrinsic factors, which can be conceptualized using the hallmarks of cancer. Although many facets of myeloid transformation are similar to those in solid tumors, there are also notable differences. Unlike solid tumors, hematologic malignancies typically exhibit fewer genetic mutations, which have been well characterized. However, understanding the cell-extrinsic factors contributing to myeloid malignancies can be challenging due to the complex interactions in the hematopoietic microenvironment. Researchers need to focus on these intricate factors to prevent the early onset of myeloid transformation and develop appropriate interventions. Significance: Myeloid malignancies are common in the elderly, and acute myeloid leukemia has an adverse prognosis in older patients. Investigating cell-extrinsic factors influencing myeloid malignancies is crucial to developing approaches for preventing or halting disease progression and predicting clinical outcomes in patients with advanced disease. Whereas successful intervention may require targeting various mechanisms, understanding the contribution of each cell-extrinsic factor will help prioritize clinical targets.

Applications of artificial intelligence to myeloproliferative neoplasms: a narrative review

INTRODUCTION

Artificial intelligence (AI) is a rapidly growing field of computational research with the potential to extract nuanced biomarkers for the prediction of outcomes of interest. AI implementations for the prediction for clinical outcomes for myeloproliferative neoplasms (MPNs) are currently under investigation.

AREAS COVERED

In this narrative review, we discuss AI investigations for the improvement of MPN clinical care utilizing either clinically available data or experimental laboratory findings. Abstracts and manuscripts were identified upon querying PubMed and the American Society of Hematology conference between 2000 and 2023. Overall, multidisciplinary researchers have developed AI methods in MPNs attempting to improve diagnostic accuracy, risk prediction, therapy selection, or pre-clinical investigations to identify candidate molecules as novel therapeutic agents.

EXPERT OPINION

It is our expert opinion that AI methods in MPN care and hematology will continue to grow with increasing clinical utility. We believe that AI models will assist healthcare workers as clinical decision support tools if appropriately developed with AI-specific regulatory guidelines. Though the reported findings in this review are early investigations for AI in MPNs, the collective work developed by the research community provides a promising framework for improving decision-making in the future of MPN clinical care.

Gut Microbiota Disruption in Hematologic Cancer Therapy: Molecular Insights and Implications for Treatment Efficacy

Hematologic malignancies (HMs), including leukemia, lymphoma, and multiple myeloma, involve the uncontrolled proliferation of abnormal blood cells, posing significant clinical challenges due to their heterogeneity and varied treatment responses. Despite recent advancements in therapies that have improved survival rates, particularly in chronic lymphocytic leukemia and acute lymphoblastic leukemia, treatments like chemotherapy and stem cell transplantation often disrupt gut microbiota, which can negatively impact treatment outcomes and increase infection risks. This review explores the complex, bidirectional interactions between gut microbiota and cancer treatments in patients with HMs. Gut microbiota can influence drug metabolism through mechanisms such as the production of enzymes like bacterial β-glucuronidases, which can alter drug efficacy and toxicity. Moreover, microbial metabolites like short-chain fatty acids can modulate the host immune response, enhancing treatment effectiveness. However, therapy often reduces the diversity of beneficial bacteria, such as Bifidobacterium and Faecalibacterium, while increasing pathogenic bacteria like Enterococcus and Escherichia coli. These findings highlight the critical need to preserve microbiota diversity during treatment. Future research should focus on personalized microbiome-based therapies, including probiotics, prebiotics, and fecal microbiota transplantation, to improve outcomes and quality of life for patients with hematologic malignancies.

Intratumoral Microbiome: Foe or Friend in Reshaping the Tumor Microenvironment Landscape?

The role of the microbiome in cancer and its crosstalk with the tumor microenvironment (TME) has been extensively studied and characterized. An emerging field in the cancer microbiome research is the concept of the intratumoral microbiome, which refers to the microbiome residing within the tumor. This microbiome primarily originates from the local microbiome of the tumor-bearing tissue or from translocating microbiome from distant sites, such as the gut. Despite the increasing number of studies on intratumoral microbiome, it remains unclear whether it is a driver or a bystander of oncogenesis and tumor progression. This review aims to elucidate the intricate role of the intratumoral microbiome in tumor development by exploring its effects on reshaping the multileveled ecosystem in which tumors thrive, the TME. To dissect the complexity and the multitude of layers within the TME, we distinguish six specialized tumor microenvironments, namely, the immune, metabolic, hypoxic, acidic, mechanical and innervated microenvironments. Accordingly, we attempt to decipher the effects of the intratumoral microbiome on each specialized microenvironment and ultimately decode its tumor-promoting or tumor-suppressive impact. Additionally, we portray the intratumoral microbiome as an orchestrator in the tumor milieu, fine-tuning the responses in distinct, specialized microenvironments and remodeling the TME in a multileveled and multifaceted manner.

Blood Microbiota and Its Products: Mechanisms of Interference with Host Cells and Clinical Outcomes

In healthy conditions, blood was considered a sterile environment until the development of new analytical approaches that allowed for the detection of circulating bacterial ribosomal DNA. Currently, debate exists on the origin of the blood microbiota. According to advanced research using dark field microscopy, fluorescent in situ hybridization, flow cytometry, and electron microscopy, so-called microbiota have been detected in the blood. Conversely, others have reported no evidence of a common blood microbiota. Then, it was hypothesized that blood microbiota may derive from distant sites, e.g., the gut or external contamination of blood samples. Alteration of the blood microbiota's equilibrium may lead to dysbiosis and, in certain cases, disease. Cardiovascular, respiratory, hepatic, kidney, neoplastic, and immune diseases have been associated with the presence of Gram-positive and Gram-negative bacteria and/or their products in the blood. For instance, lipopolysaccharides (LPSs) and endotoxins may contribute to tissue damage, fueling chronic inflammation. Blood bacteria can interact with immune cells, especially with monocytes that engulf microorganisms and T lymphocytes via spontaneous binding to their membranes. Moreover, LPSs, extracellular vesicles, and outer membrane vesicles interact with red blood cells and immune cells, reaching distant organs. This review aims to describe the composition of blood microbiota in healthy individuals and those with disease conditions. Furthermore, special emphasis is placed on the interaction of blood microbiota with host cells to better understand disease mechanisms.

A review of machine learning methods for cancer characterization from microbiome data

Recent studies have shown that the microbiome can impact cancer development, progression, and response to therapies suggesting microbiome-based approaches for cancer characterization. As cancer-related signatures are complex and implicate many taxa, their discovery often requires Machine Learning approaches. This review discusses Machine Learning methods for cancer characterization from microbiome data. It focuses on the implications of choices undertaken during sample collection, feature selection and pre-processing. It also discusses ML model selection, guiding how to choose an ML model, and model validation. Finally, it enumerates current limitations and how these may be surpassed. Proposed methods, often based on Random Forests, show promising results, however insufficient for widespread clinical usage. Studies often report conflicting results mainly due to ML models with poor generalizability. We expect that evaluating models with expanded, hold-out datasets, removing technical artifacts, exploring representations of the microbiome other than taxonomical profiles, leveraging advances in deep learning, and developing ML models better adapted to the characteristics of microbiome data will improve the performance and generalizability of models and enable their usage in the clinic.

Circulating microbiome DNA as biomarkers for early diagnosis and recurrence of lung cancer

Lung cancer mortality is exacerbated by late-stage diagnosis. Emerging evidence indicates the potential clinical significance of distinct microbial signatures as diagnostic and prognostic biomarkers across various cancers. However, circulating microbiome DNA (cmDNA) profiles are underexplored in lung cancer (LC). Here, whole-genome sequencing is performed on plasma of LC patients and healthy controls (HCs). Differentially enriched microbial species are identified between LC and HC. A diagnostic model is developed, which has a high sensitivity of 87.7% and achieves an AUC of 93.2% in the independent validation dataset. Crucially, this model demonstrates the capability to detect early-stage LC, achieving a sensitivity of 86.5% for stage I and 87.1% for tumors <1 cm. In addition, we construct a cmDNA model for recurrence, which precisely predicts LC recurrence after surgery. Overall, this study highlights the significant alterations of cmDNA profiles in LC, indicating its potential as biomarkers for early diagnosis and recurrence.

Gut Microbiota Composition Correlates with Disease Severity in Myelodysplastic Syndrome

The myelodysplastic syndrome (MDS) is a heterogeneous group of clonal disorders of hematopoietic progenitor cells related to ineffective hematopoiesis and an increased risk of transformation to acute myelogenous leukemia. MDS is divided into categories, namely lineage dysplasia (MDS-SLD), MDS with ring sideroblasts (MDS-RS), MDS with multilineage dysplasia (MDS-MLD), MDS with excess blasts (MDS-EB). The International Prognostic Classification System (IPSS) ranks the patients as very low, low, intermediate, high, and very high based on disease evolution and survival rates. Evidence points to toll-like receptor (TLR) abnormal signaling as an underlying mechanism of this disease, providing a link between MDS and immune dysfunction. Microbial signals, such as lipopolysaccharides from gram-negative bacteria, can activate or suppress TLRs. Therefore, we hypothesized that MDS patients present gut microbiota alterations associated with disease subtypes and prognosis. To test this hypothesis, we sequenced the 16S rRNA gene from fecal samples of 30 MDS patients and 16 healthy elderly controls. We observed a negative correlation between Prevotella spp. and Akkermansia spp. in MDS patients compared with the control group. High-risk patients presented a significant increase in the genus Prevotella spp. compared to the other risk categories. There was a significant reduction in the abundance of the genus Akkermansia spp. in high-risk patients compared with low- and intermediate-risk. There was a significant decrease in the genus Ruminococcus spp. in MDS-EB patients compared with controls. Our findings show a new association between gut dysbiosis and higher-risk MDS, with a predominance of gram-negative bacteria.

Robustness of cancer microbiome signals over a broad range of methodological variation

In 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2-12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.

Microbiome and lung cancer: carcinogenic mechanisms, early cancer diagnosis, and promising microbial therapies

Microbiomes in the lung, gut, and oral cavity are correlated with lung cancer initiation and progression. While correlations have been preliminarily established in earlier studies, delving into microbe-mediated carcinogenic mechanisms will extend our understanding from correlation to causation. Building upon the causative relationships between microbiome and lung cancer, a novel concept of microbial biomarkers has emerged, mainly encompassing cancer-specific bacteria and circulating microbiome DNA. They might function as noninvasive liquid biopsy techniques for lung cancer early detection. Furthermore, potential microbial therapies have displayed initial efficacy in lung cancer treatment, providing multiple avenues for therapeutic intervention. Herein, we will discuss the molecular mechanisms and signaling pathways through which microbes influence lung cancer initiation and development. Additionally, we will summarize recent findings on microbial biomarkers as a member of tumor liquid biopsy techniques and provide an overview of the latest advances in various microbe-assisted/mediated therapeutic approaches for lung cancer.

Identification of novel Carnobacterium maltaromaticum strains in bone marrow samples of patients with acute myeloid leukemia using a metagenomic binning approach

The aim of this study aimed to examine the existence of a bacterial metagenome in the bone marrow of patients with acute myeloid leukemia (AML). We re-examined whole-genome sequencing data from the bone marrow samples of seven patients with AML, four of whom were remitted after treatment, for metagenomic analysis. After the removal of human reads, unmapped reads were used to profile the species-level composition. We used the metagenomic binning approach to confirm whether the identified taxon was a complete genome of known or novel strains. We observed a unique and novel microbial signature in which Carnobacterium maltaromaticum was the most abundant species in five patients with AML or remission. The complete genome of C. maltaromaticum "BMAML_KR01," which was observed in all samples, was 100% complete with 8.5% contamination and closely clustered with C. maltaromaticum strains DSM20730 and SF668 based on single nucleotide polymorphism variations. We identified five unique proteins that could contribute to cancer progression and 104 virulent factor proteins in the BMAML_KR01 genome. To our knowledge, this is the first report of a new strain of C. maltaromaticum in patients with AML. The presence of C. maltaromaticum and its new strain in patients indicates an urgent need to validate the existence of this bacterium and evaluate its pathophysiological role.

Disrupted epithelial permeability as a predictor of severe COVID-19 development

BACKGROUND

An impaired epithelial barrier integrity in the gastrointestinal tract is important to the pathogenesis of many inflammatory diseases. Accordingly, we assessed the potential of biomarkers of epithelial barrier dysfunction as predictive of severe COVID-19.

METHODS

Levels of bacterial DNA and zonulin family peptides (ZFP) as markers of bacterial translocation and intestinal permeability and a total of 180 immune and inflammatory proteins were analyzed from the sera of 328 COVID-19 patients and 49 healthy controls.

RESULTS

Significantly high levels of circulating bacterial DNA were detected in severe COVID-19 cases. In mild COVID-19 cases, serum bacterial DNA levels were significantly lower than in healthy controls suggesting epithelial barrier tightness as a predictor of a mild disease course. COVID-19 patients were characterized by significantly elevated levels of circulating ZFP. We identified 36 proteins as potential early biomarkers of COVID-19, and six of them (AREG, AXIN1, CLEC4C, CXCL10, CXCL11, and TRANCE) correlated strongly with bacterial translocation and can be used to predict and discriminate severe cases from healthy controls and mild cases (area under the curve (AUC): 1 and 0.88, respectively). Proteomic analysis of the serum of 21 patients with moderate disease at admission which progressed to severe disease revealed 10 proteins associated with disease progression and mortality (AUC: 0.88), including CLEC7A, EIF4EBP1, TRANCE, CXCL10, HGF, KRT19, LAMP3, CKAP4, CXADR, and ITGB6.

CONCLUSION

Our results demonstrate that biomarkers of intact or defective epithelial barriers are associated with disease severity and can provide early information on the prediction at the time of hospital admission.

A Photo-Activated Thermoelectric Catalyst for Ferroptosis-/Pyroptosis-Boosted Tumor Nanotherapy

Phototherapy including photothermal therapy (PTT) and photodynamic therapy (PDT) has gradually come into the limelight for oncological treatment due to its noninvasiveness, high specificity, and low side effects. However, upregulated heat-shock proteins (HSPs) and reactive oxygen species (ROS)-defensing system such as glutathione (GSH) or MutT homolog 1 (MTH1) protein in tumor microenvironment counteract the efficiency of single-modality therapy either PTT or PDT. Herein, the well-defined bismuth telluride nanoplates (Bi2 Te3 NPs) are engineered with a high-performance photo-thermo-electro-catalytic effect for tumor-synergistic treatment. Upon near-infrared light illumination, Bi2 Te3 NPs induce a significant temperature elevation for PTT, which effectively inhibits MTH1 expression. Especially, heating and cooling alteration caused temperature variations result in electron-hole separation for ROS generation, which not only damages HSPs to reduce the thermotolerance for enhance PTT, but also arouses tumor cell pyroptosis. Additionally, Bi2 Te3 NPs conspicuously reduce GSH, further improving ROS level and leading to decrease glutathione peroxidase 4 (GPX4) activity, which triggers tumor cell ferroptosis. Due to the photo-thermo-electro-catalytic synergistic therapy, Bi2 Te3 NPs are gifted with impressive tumor suppression on both ectopic and orthotopic ocular tumor models. This work highlights a high-performance multifunctional energy-conversion nanoplatform for reshaping tumor microenvironment to boost the tumor-therapeutic efficacy of phototherapy.

Microbiota Influences on Hematopoiesis and Blood Cancers: New Horizons?

Hematopoiesis governs the generation of immune cells through the differentiation of hematopoietic stem cells (HSC) into various progenitor cells, a process controlled by intrinsic and extrinsic factors. Among extrinsic factors influencing hematopoiesis is the microbiota, or the collection of microorganisms present in various body sites. The microbiota has a profound impact on host homeostasis by virtue of its ability to release various molecules and structural components, which promote normal organ function. In this review, we will discuss the role of microbiota in influencing hematopoiesis and how disrupting the microbiota/host network could lead to hematologic malignancies, as well as highlight important knowledge gaps to move this field of research forward.

SIGNIFICANCE

Microbiota dysfunction is associated with many pathologic conditions, including hematologic malignancies. In this review, we discuss the role of microbiota in influencing hematopoiesis and how disrupting the microbiota/host network could lead to hematologic malignancies. Understanding how the microbiota influences hematologic malignancies could have an important therapeutic impact for patients.

The Blood Microbiome and Health: Current Evidence, Controversies, and Challenges

Blood is conventionally thought to be sterile. However, emerging evidence on the blood microbiome has started to challenge this notion. Recent reports have revealed the presence of genetic materials of microbes or pathogens in the blood circulation, leading to the conceptualization of a blood microbiome that is vital for physical wellbeing. Dysbiosis of the blood microbial profile has been implicated in a wide range of health conditions. Our review aims to consolidate recent findings about the blood microbiome in human health and to highlight the existing controversies, prospects, and challenges around this topic. Current evidence does not seem to support the presence of a core healthy blood microbiome. Common microbial taxa have been identified in some diseases, for instance, Legionella and Devosia in kidney impairment, Bacteroides in cirrhosis, Escherichia/Shigella and Staphylococcus in inflammatory diseases, and Janthinobacterium in mood disorders. While the presence of culturable blood microbes remains debatable, their genetic materials in the blood could potentially be exploited to improve precision medicine for cancers, pregnancy-related complications, and asthma by augmenting patient stratification. Key controversies in blood microbiome research are the susceptibility of low-biomass samples to exogenous contamination and undetermined microbial viability from NGS-based microbial profiling, however, ongoing initiatives are attempting to mitigate these issues. We also envisage future blood microbiome research to adopt more robust and standardized approaches, to delve into the origins of these multibiome genetic materials and to focus on host-microbe interactions through the elaboration of causative and mechanistic relationships with the aid of more accurate and powerful analytical tools.

CHIPing away the progression potential of CHIP: A new reality in the making

Over the past few years, we have gained a deeper understanding of clonal hematopoiesis of indeterminate potential (CHIP), especially with regard to the epidemiology, clinical sequelae, and mechanical aspects. However, interventional strategies to prevent or delay the potential negative consequences of CHIP remain underdeveloped. In this review, we highlight the latest updates on clonal hematopoiesis research, including molecular mechanisms and clinical implications, with a particular focus on the evolving strategies for the interventions that are being evaluated in ongoing observational and interventional trials. There remains an urgent need to formulate standardized and evidence-based recommendations and guidelines for evaluating and managing individuals with clonal hematopoiesis. In addition, patient-centric endpoints must be defined for clinical trials, which will enable us to continue the robust development of effective preventive strategies and improve clinical outcomes.

Deepening Our Understanding of the Factors Affecting Landscape of Myeloproliferative Neoplasms: What Do We Know about Them?

Myeloproliferative neoplasms (MPNs) arise from the uncontrolled proliferation of hematopoietic stem and progenitor cells in bone marrow. As with all tumors, the development of MPNs is a consequence of alterations in malignant cells and their interaction with other extrinsic factors that support and promote tumor progression. Since the discovery of driver mutations, much work has focused on studying and reviewing the genomic features of the disease but has neglected to delve into the important role that many other mechanisms may play. This review discusses the genetic component of MPNs but focuses mainly on some of the most relevant work investigating other non-genetic factors that may be crucial for the disease. The studies summarized here address MPN cell-intrinsic or -extrinsic factors and the interaction between them through transcriptomic, proteomic and microbiota studies, among others.

Bacterial biomarkers capable of identifying recurrence or metastasis carry disease severity information for lung cancer

Background

Local recurrence and distant metastasis are the main causes of death in patients with lung cancer. Multiple studies have described the recurrence or metastasis of lung cancer at the genetic level. However, association between the microbiome of lung cancer tissue and recurrence or metastasis remains to be discovered. Here, we aimed to identify the bacterial biomarkers capable of distinguishing patients with lung cancer from recurrence or metastasis, and how it related to the severity of patients with lung cancer.

Methods

We applied microbiome pipeline to bacterial communities of 134 non-recurrence and non-metastasis (non-RM) and 174 recurrence or metastasis (RM) samples downloaded from The Cancer Genome Atlas (TCGA). Co-occurrence network was built to explore the bacterial interactions in lung cancer tissue of RM and non-RM. Finally, the Kaplan–Meier survival analysis was used to evaluate the association between bacterial biomarkers and patient survival.

Results

Compared with non-RM, the bacterial community of RM had lower richness and higher Bray–Curtis dissimilarity index. Interestingly, the co-occurrence network of non-RM was more complex than RM. The top 500 genera in relative abundance obtained an area under the curve (AUC) of 0.72 when discriminating between RM and non-RM. There were significant differences in the relative abundances of Acidovorax, Clostridioides, Succinimonas, and Shewanella, and so on between RM and non-RM. These biomarkers played a role in predicting the survival of lung cancer patients and were significantly associated with lung cancer stage.

Conclusion

This study provides the first evidence for the prediction of lung cancer recurrence or metastasis by bacteria in lung cancer tissue. Our results highlights that bacterial biomarkers that distinguish RM and non-RM are also associated with patient survival and disease severity.

Molecular Pathways in Clonal Hematopoiesis: From the Acquisition of Somatic Mutations to Transformation into Hematologic Neoplasm

Hematopoietic stem cell aging, through the acquisition of somatic mutations, gives rise to clonal hematopoiesis (CH). While a high prevalence of CH has been described in otherwise healthy older adults, CH confers an increased risk of both hematologic and non-hematologic diseases. Classification of CH into clonal hematopoiesis of indeterminate potential (CHIP) and clonal cytopenia of undetermined significance (CCUS) further describes this neoplastic myeloid precursor state and stratifies individuals at risk of developing clinically significant complications. The sequential acquisition of driver mutations, such as DNMT3A, TET2, and ASXL1, provide a selective advantage and lead to clonal expansion. Inflammation, microbiome signatures, and external selective pressures also contribute to clonal evolution. Despite significant progress in recent years, the precise molecular mechanisms driving CH transformation to hematologic neoplasms are not well defined. Further understanding of these complex mechanisms may improve risk stratification and introduce therapeutic interventions in CH. Here we discuss the genetic drivers underpinning CH, mechanisms for clonal evolution, and transformation to hematologic neoplasm.