Genetic insights in infectious diseases:Insights from a case report and implications for personalized medicine

The relationship between genetics and infectious diseases is important in shaping our understanding of disease susceptibility,progression,and treatment.Recent research shows the impact of genetic variations,such as heme-oxygenase promoter length,on diseases like malaria and sepsis,revealing both protective and inconclusive effects.Studies on vaccine responses highlight genetic markers like human leukocyte antigens,emphasizing the potential for personalized immunization strategies.The ongoing battle against drug-resistant tuberculosis(TB)illustrates the complexity of genomic variants in predicting resistance,highlighting the need for integrated diagnostic tools.Additionally,genome-wide association studies reveal antibiotic resistance mechanisms in bacterial genomes,while host genetic polymorphisms,such as those in solute carrier family 11 member 1 and vitamin D receptor,demonstrate their role in TB susceptibility.Advanced techniques like metagenomic next-generation sequencing promise detailed pathogen detection but face challenges in cost and accessibility.A case report involving a highly virulent Mycobacterium TB strain with the pks1 gene further highlights the need for genetic insights in understanding disease severity and developing targeted interventions.This evolving landscape emphasizes the role of genetics in infectious diseases,while also addressing the need for standardized studies and accessible technologies.

Mutations in Ras homolog family member A in patients with peripheral T-cell lymphoma and implications for personalized medicine

Genome sequencing has revealed frequent mutations in Ras homolog family member A(RHOA)among various cancers with unique aberrant profiles and pathogenic effects,especially in peripheral T-cell lymphoma(PTCL).The discrete positional distribution and types of RHOA amino acid substitutions vary according to the tumor type,thereby leading to different functional and biological properties,which provide new insight into the molecular pathogenesis and potential targeted therapies for various tumors.However,the similarities and discrepancies in characteristics of RHOA mutations among various histologic subtypes of PTCL have not been fully elucidated.Herein we highlight the inconsistencies and complexities of the type and location of RHOA mutations and demonstrate the contribution of RHOA variants to the pathogenesis of PTCL by combining epigenetic abnormalities and activating multiple downstream pathways.The promising potential of targeting RHOA as a therapeutic modality is also outlined.This review provides new insight in the field of personalized medicine to improve the clinical outcomes for patients.

Transforming Healthcare:AI-NLP Fusion Framework for Precision Decision-Making and Personalized Care Optimization in the Era of IoMT

In the rapidly evolving landscape of healthcare,the integration of Artificial Intelligence(AI)and Natural Language Processing(NLP)holds immense promise for revolutionizing data analytics and decision-making processes.Current techniques for personalized medicine,disease diagnosis,treatment recommendations,and resource optimization in the Internet of Medical Things(IoMT)vary widely,including methods such as rule-based systems,machine learning algorithms,and data-driven approaches.However,many of these techniques face limitations in accuracy,scalability,and adaptability to complex clinical scenarios.This study investigates the synergistic potential of AI-driven optimization techniques and NLP applications in the context of the IoMT.Through the integration of advanced data analytics methodologies with NLP capabilities,we propose a comprehensive framework designed to enhance personalized medicine,streamline disease diagnosis,provide treatment recommendations,and optimize resource allocation.Using a systematic methodology data was collected from open data repositories,then preprocessed using data cleaning,missing value imputation,feature engineering,and data normalization and scaling.Optimization algorithms,such as Gradient Descent,Adam Optimization,and Stochastic Gradient Descent,were employed in the framework to enhance model performance.These were integrated with NLP processes,including Text Preprocessing,Tokenization,and Sentiment Analysis to facilitate comprehensive analysis of the data to provide actionable insights from the vast streams of data generated by IoMT devices.Lastly,through a synthesis of existing research and real-world case studies,we demonstrated the impact of AI-NLP fusion on healthcare outcomes and operational efficiency.The simulation produced compelling results,achieving an average diagnostic accuracy of 93.5%for the given scenarios,and excelled even further in instances involving rare diseases,achieving an accuracy rate of 98%.With regard to patient-specific treatment plans it generated them with an average precision of 96.7%.Improvements in early risk stratification and enhanced documentation were also noted.Furthermore,the study addresses ethical considerations and challenges associated with deploying AI and NLP in healthcare decision-making processes,offering insights into risk-mitigating strategies.This research contributes to advancing the understanding of AI-driven optimization algorithms in healthcare data analytics,with implications for healthcare practitioners,researchers,and policymakers.By leveraging AI and NLP technologies in IoMT environments,this study paves the way for innovative strategies to enhance patient care and operational effectiveness.Ultimately,this work underscores the transformative potential of AI-NLP fusion in shaping the future of healthcare.

Personalized medicine and opioid use disorder

Opioid use disorder(OUD)is a major public health problem affecting millions of people worldwide.Although OUD is a chronic and relapsing disorder,a variety of pharmacological and non-pharmacological interventions are available.Medication-assisted treatment of OUD generally relies on competition for opioid receptors against the addictive substance.The mechanisms of this competition are to block or inactivate the opioid receptor or activate the receptor with a substance that is intermittent or long acting.Methadone and buprenorphine are two United States Food and Drug Administration-approved medications that have long-term positive effects on the health of opioid-dependent individuals.Although clinical studies of drugs generally demonstrate efficacy in thousands of people and toxicity is excluded,it cannot be predicted whether the given drug will cause side effects in one of the patients at the treatment dose.Individual differences can be explained by many biological and environmental factors.Variations in genes encoding drug metabolism or cellular drug targets significantly explain the variability in drug response between individuals.Therefore,for the effects of candidate genes to be accepted and included in individual treatment protocols,it is important to repeat studies on individuals of different ethnic backgrounds and prove a similar effect.

Personalized medicine:Clinical oncology on molecular view of treatment

Cancer,the second leading global cause of death,impacts both physically and emotionally.Conventional treatments such as surgeries,chemotherapy,and radiotherapy have adverse effects,driving the need for more precise approaches.Precision medicine enables more targeted treatments.Genetic mapping,alongside other molecular biology approaches,identifies specific genes,contributing to accurate prognoses.The review addresses,in clinical use,a molecular perspective on treatment.Biomarkers like alpha-fetoprotein,beta-human chorionic gonadotropin,5-hydroxyindoleacetic acid,programmed death-1,and cytotoxic T lymphocyte-associated protein 4 are explored,providing valuable information.Bioinformatics,with an emphasis on artificial intelligence,revolutionizes the analysis of biological data,offering more accurate diagnoses.Techniques like liquid biopsy are emphasized for early detection.Precision medicine guides therapeutic strategies based on the molecular characteristics of the tumor,as evidenced in the molecular subtypes of breast cancer.Classifications allow personalized treatments,highlighting the role of trastuzumab and endocrine therapies.Despite the benefits,challenges persist,including high costs,tumor heterogeneity,and ethical issues.Overcoming obstacles requires collaboration,ensuring that advances in molecular biology translate into accessible benefits for all.

Spastin and alsin protein interactome analyses begin to reveal key canonical pathways and suggest novel druggable targets

Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.

Revolutionizing diabetic retinopathy screening and management:The role of artificial intelligence and machine learning

Diabetic retinopathy(DR)remains a leading cause of vision impairment and blindness among individuals with diabetes,necessitating innovative approaches to screening and management.This editorial explores the transformative potential of artificial intelligence(AI)and machine learning(ML)in revolutionizing DR care.AI and ML technologies have demonstrated remarkable advancements in enhancing the accuracy,efficiency,and accessibility of DR screening,helping to overcome barriers to early detection.These technologies leverage vast datasets to identify patterns and predict disease progression with unprecedented precision,enabling clinicians to make more informed decisions.Furthermore,AI-driven solutions hold promise in personalizing management strategies for DR,incorpo-rating predictive analytics to tailor interventions and optimize treatment path-ways.By automating routine tasks,AI can reduce the burden on healthcare providers,allowing for a more focused allocation of resources towards complex patient care.This review aims to evaluate the current advancements and applic-ations of AI and ML in DR screening,and to discuss the potential of these techno-logies in developing personalized management strategies,ultimately aiming to improve patient outcomes and reduce the global burden of DR.The integration of AI and ML in DR care represents a paradigm shift,offering a glimpse into the future of ophthalmic healthcare.

Revisiting dexamethasone dosage in COVID-19 management

The ongoing coronavirus disease 2019(COVID-19)pandemic has necessitated rapid advancements in therapeutic strategies,with dexamethasone emerging as a key treatment for severe cases.This editorial discusses the systematic review conducted by Sethi et al,published in the World Journal of Virology.The review critically examines the efficacy and safety of varying dosages of dexamethasone in severe COVID-19 patients,providing a comprehensive meta-analysis that underscores the current clinical recommendations favoring a low-dose regimen.Despite these findings,the review highlights the potential benefits of tailored dosages for specific patient subgroups,suggesting a need for personalized treatment approaches.This editorial expands on the implications of these findings,advocating for the integration of evolving clinical data into treatment protocols and calling for further research into patient-specific responses to therapy.It emphasizes the importance of adaptability and precision in pandemic response,urging the medical community to consider both the robustness of existing evidence and the potential for innovative approaches to enhance patient outcomes in the face of global health challenges.

Therapeutic insights into epidermal growth factor receptor/reactive oxygen species proto-oncogene 1-receptor co-mutated non-small cell lung cancer:Crizotinib as a promising option

This letter provides a review of the report by Peng et al on a unique case of non-small cell lung cancer(NSCLC),specifically lung adenocarcinoma,featuring reactive oxygen species proto-oncogene 1-receptor(ROS1)co-mutation.The case involves a 64-year-old patient who exhibited both epidermal growth factor receptor(EGFR)L858R mutation and ROS1 rearrangement,achieving significant disease stabilization following treatment with crizotinib.This rare EGFR/ROS1 co-mutation poses distinct challenges for clinical management and highlights the necessity of personalized treatment strategies.While third-generation EGFR tyrosine kinase inhibitors(TKIs),such as osimertinib,are commonly regarded as first-line therapies,recent studies indicate that crizotinib may offer superior disease control in certain EGFR-mutant patients,particularly those who exhibit poor responses to EGFR TKIs.The case also examines the influence of tumor cell genetic heterogeneity on treatment response,underscoring the importance of evaluating tumor characteristics.In patients with EGFR/ROS1 co-mutation,gefitinib is generally effective as a first-line treatment;however,its efficacy can be limited,whereas crizotinib has demonstrated improved disease control.Future research should focus on identifying optimal treatment strategies for patients with EGFR/ROS1 co-mutation to enhance patient outcomes.In conclusion,this case report not only illustrates the effectiveness of crizotinib in managing patients with EGFR/ROS1 co-mutation but also underscores the importance of personalized treatment approaches,offering valuable insights for improving clinical outcomes in NSCLC patients with complex genetic profiles.TO THE EDITOR I read with great interest the case report by Peng et al[1],titled“Concomitant Epidermal Growth Factor Receptor Mutation/C-ROS Oncogene 1 Rearrangement in Non-Small Cell Lung Cancer”,published in the World Journal of Clinical Oncology[1].This report presents a compelling case of the exceedingly rare epidermal growth factor receptor(EGFR)/reactive oxygen species proto-oncogene 1-receptor(ROS1)co-mutation in non-small cell lung cancer(NSCLC),specifically in a patient with lung adenocarcinoma.The authors describe a 64-year-old woman with an EGFR L858R mutation and ROS1 rearrangement,who achieved notable disease stability with prolonged crizotinib treatment.This case,with its distinct clinical features and challenges inherent to EGFR/ROS1 co-mutations,provides valuable insights for the oncology community and underscores the potential efficacy of ROS1-targeted therapies in treating co-mutated NSCLC.

Hepatic arterial infusion pump chemotherapy for colorectal liver metastases: Revisiting traditional techniques to explore new frontiers

Hepatic arterial infusion(HAI)chemotherapy,first introduced in the 1980s,has gained recognition as an effective locoregional treatment for colorectal liver metastasis(CRLM).Initially used for unresectable liver metastases,HAI’s app-lication has expanded to the adjuvant setting following hepatic resection,with early studies indicating improved hepatic disease-free survival.Recent research demonstrates that combining HAI with modern systemic therapies enhances conversion to resectability and prolongs both recurrence-free and overall survival,even in heavily pretreated patients with diverse RAS mutational statuses.Person-alization through approaches like microsatellite instability status and dose mo-difications further optimize outcomes.However,the complexity of HAI requires expertise across multidisciplinary teams,limiting its widespread adoption to specialized centers.Ongoing clinical trials continue to investigate HAI’s role in CRLM management,highlighting its potential to become a cornerstone of liver-directed therapy.We explore how HAI chemotherapy,in combination with personalized medicine,can advance treatment strategies for metastatic colorectal cancer.

Evaluating the scope of human leukocyte antigen polymorphisms influencing hepatitis B virus-related liver cancer and cirrhosis through multi-clustering analysis

Hepatitis B virus remains a major cause of cirrhosis and hepatocellular carcinoma,with genetic polymorphisms and mutations influencing immune responses and disease progression.Nguyen et al present novel findings on specific human leukocyte antigen(HLA)alleles,including rs2856718 of HLA-DQ and rs3077 and rs9277535 of HLA-DP,which may predispose individuals to cirrhosis and liver cancer,based on multi-clustering analysis.Here,we discuss the feasibility of this approach and identify key areas for further investigation,aiming to offer insights for advancing clinical practice and research in liver disease and related cancers.

The genetics of pediatric inflammatory bowel disease:Towards precision medicine

Pediatric inflammatory bowel disease(IBD)is a chronic and heterogeneous disease.IBD is commonly classified into Crohn’s disease and ulcerative colitis.It is linked to serious symptoms and complications.The onset of IBD commonly occurs during adolescence.Despite the significant number of cases globally(~5 million),the causes of pediatric IBD,which constitutes 25%of IBD patients,are not yet fully understood.Apart from environmental factors,genetic factors contribute to a higher risk of developing IBD.The predisposition risk of IBD can be investigated using genetic testing.Genetic mechanisms of pediatric IBD are highly complex which resulted in difficulty in selecting effective treatment or patient management.Genetic variation of IBD would serve as a basis for precision medicine and allow for the discovery of more robust treatment avenues for this condition in pediatric patients.This review aims to discuss the genetics of pediatric IBD,and current development in the screening,diagnosis,and treatment based on genetic profiling of pediatric IBD subjects toward more personalized management of this disease.

Personalized immunotherapy in cancer precision medicine

With the significant advances in cancer genomics using next-generation sequencing technologies,genomic and molecular profilingbased precision medicine is used as a part of routine clinical test for guiding and selecting the most appropriate treatments for individual cancer patients.Although many molecular-targeted therapies for a number of actionable genomic alterations have been developed,the clinical application of such information is still limited to a small proportion of cancer patients.In this review,we summarize the current status of personalized drug selection based on genomic and molecular profiling and highlight the challenges how we can further utilize the individual genomic information.Cancer immunotherapies,including immune checkpoint inhibitors,would be one of the potential approaches to apply the results of genomic sequencing most effectively.Highly cancer-specific antigens derived from somatic mutations,the so-called neoantigens,occurring in individual cancers have been in focus recently.Cancer immunotherapies,which target neoantigens,could lead to a precise treatment for cancer patients,despite the challenge in accurately predicting neoantigens that can induce cytotoxic T cells in individual patients.Precise prediction of neoantigens should accelerate the development of personalized immunotherapy including cancer vaccines and T-cell receptor-engineered T-cell therapy for a broader range of cancer patients.

Neoadjuvant therapy for pancreatic ductal adenocarcinoma:Opportunities for personalized cancer care

Pancreatic ductal adenocarcinoma(PDAC)is an aggressive malignancy that is best treated in a multidisciplinary fashion using surgery,chemotherapy,and radiation.Adjuvant chemotherapy has shown to have a significant survival benefit in patients with resected PDAC.However,up to 50%of patients fail to receive adjuvant chemotherapy due to postoperative complications,poor patient performance status or early disease progression.In order to ensure the delivery of chemotherapy,an alternative strategy is to administer systemic treatment prior to surgery.Precision oncology refers to the application of diverse strategies to target therapies specific to characteristics of a patient’s cancer.While traditionally emphasized in selecting targeted therapies based on molecular,genetic,and radiographic biomarkers for patients with metastatic disease,the neoadjuvant setting is a prime opportunity to utilize personalized approaches.In this article,we describe the current evidence for the use of neoadjuvant therapy(NT)and highlight unique opportunities for personalized care in patients with PDAC undergoing NT.

Tumor organoids for cancer research and personalized medicine

Organoids are three-dimensional culture systems generated from embryonic stem cells,induced pluripotent stem cells,and adult stem cells.They are capable of cell proliferation,differentiation,and self-renewal.Upon stimulation by signal factors and/or growth factors,organoids self-assemble to replicate the morphological and structural characteristics of the corresponding organs.They provide an extraordinary platform for investigating organ development and mimicking pathological processes.Organoid biobanks derived from a wide range of carcinomas have been established to represent different lesions or stages of clinical tumors.Importantly,genomic and transcriptomic analyses have confirmed maintenance of intra-and interpatient heterogeneities in organoids.Therefore,this technology has the potential to revolutionize drug screening and personalized medicine.In this review,we summarized the characteristics and applications of organoids in cancer research by the establishment of organoid biobanks directly from tumor organoids or from genetically modified non-cancerous organoids.We also analyzed the current state of organoid applications in drug screening and personalized medicine.

Applications of artificial intelligence in, early detection of cancer, clinical diagnosis and personalized medicine

Artificial intelligence(AI)refers to the simulation of human intelligence in machines programmed to convert raw input data into decision-making actions,like humans.AI programs are designed to make decisions,often using deep learning and computer-guided programs that analyze and process raw data into clinical decision making for effective treatment.New techniques for predicting cancer at an early stage are needed as conventional methods have poor accuracy and are not applicable to personalized medicine.AI has the potential to use smart,intelligent computer systems for image interpretation and early diagnosis of cancer.AI has been changing almost all the areas of the medical field by integrating with new emerging technologies.AI has revolutionized the entire health care system through innovative digital diagnostics with greater precision and accuracy.AI is capable of detecting cancer at an early stage with accurate diagnosis and improved survival outcomes.AI is an innovative technology of the future that can be used for early prediction,diagnosis and treatment of cancer.

Translational genomics in cancer research: converting profiles into personalized cancer medicine

Cancer genomics is a rapidly growing discipline in which the genetic molecular basis of malignancy is studied at the scale of whole genomes.While the discipline has been successful with respect to identifying specific oncogenes and tumor suppressors involved in oncogenesis,it is also challenging our approach to managing patients suffering from this deadly disease.Specifically cancer genomics is driving clinical oncology to take a more molecular approach to diagnosis,prognostication,and treatment selection.We review here recent work undertaken in cancer genomics with an emphasis on translation of genomic findings.Finally,we discuss scientific challenges and research opportunities emerging from findings derived through analysis of tumors with high-depth sequencing.

Use of zebrafish embryos as avatar of patients with pancreatic cancer:A new xenotransplantation model towards personalized medicine

BACKGROUND The response to chemotherapy treatment of patients with pancreatic ductal adenocarcinoma(PDAC)is difficult to predict and the identification of patients who most likely will benefit from aggressive chemotherapy approaches is crucial.The concept of personalized medicine has emerged in the last years with the objective to tailor the medical treatment to the individual characteristics of each patient,and particularly to the tumor biology of each patient.The need for invivo xenotransplantation models for cancer patients has increased exponentially,and for this reason zebrafish avatars have gained popularity.Preliminary studies were conducted also with PDAC tissue.AIM To develop a simple,not expensive,diffusible zebrafish embryo model as avatar for patients affected by PDAC.METHODS Tumor tissue was taken from the surgical specimen by the histopathologist.After its fragmentation into small pieces,they are stained with CM-Dil.Small pieces of stained tissue were transplanted into the yolk of wt AB zebrafish embryos with a glass capillary needle.Embryos were incubated at 35°C in E3 medium supplemented with 1%Pen/Strep in the presence or absence of drugs for the following days in respect of the treatment plan(Gemcitabine;Gemcitabine and Oxaliplatin;Gemcitabine and nab-Paclitaxel;5-Fluorouracil and Folinic acid and Oxaliplatin and Irinotecan).The response of zebrafish xenografts to the chemotherapy options has been analyzed by monitoring the fluorescent stained area at 2 h post injection(hpi),1 d and 2 d post injection(dpi).In each time point,the mean size of the stained area was measured by ImageJ and it was normalized with respect to the 1 dpi time point mean relative tumor area(RTA).We evaluated the effect of the chemotherapy exposition comparing the mean RTA of each treated subgroup and the control group and evaluating the percentage reduction of the mean RTA by comparing each treated subgroup with the control group.RESULTS Between July 2018 and October 2019,a total of 15 patients with pancreatic cancer were prospectively enrolled.In all cases,it was possible to take a fragment of the tumor from the surgical specimen for the xenotransplantation in the zebrafish embryos.The histological examination confirmed the presence of a PDAC in all cases.In absence of chemotherapy(control group),over time the Dil-stained area showed a statistically significant increase in all cases.A statistically significant reduction of the mean RTA in the treated subgroups for at least one chemotherapy scheme was reported in 6/15(40%)cases.The analysis of the percentage reduction of the RTA in treated subgroups in comparison to the control group revealed the presence of a linear relationship in each subgroup between the percentage reduction of the RTA and the number of cases reporting each percentage threshold considered for the analysis.CONCLUSION Our model seems to be effective for the xenotransplantation of PDAC tissue and evaluation of the effect of each chemotherapy scheme on the xenotransplanted tumor tissue.

Feasibility of personalized treatment concepts in gastrointestinal malignancies： Sub-group results of prospective clinical phase Ⅱ trial EXACT

Objective： Advances in high-throughput genomic profiling and the development of new targeted therapies improve patient＇s survival. In gastrointestinal （GI） malignancies, the concept of personalized medicine （PM） was not investigated so far. The aim of this prospective study was to evaluate the efficacy of a personalized treatment in GI patients who failed standard treatment. Methods： Out of the original prospective clinical phase II EXACT trial, 21 （38%） GI cancer patients who had no further treatment options were identified. A molecular profile （MP） via a 50 gene next generation sequencing （NGS） panel in combination with immunohistochemistry （IHC） was conducted using real-time biopsy tumor material. Results were discussed by a multidisciplinary team （MDT） to translate the individual MP in an experimental treatment. Results： Of the 55 patients originally included in the EXACT trial, 21 （38%） suffered from GI malignancies. The final analysis showed that 15 （71%） patients had experienced a longer progression-free survival （PFS） upon experimental targeted treatment （124 d, quartiles 70/193 d）, when compared with the PFS achieved by the previous conventional therapy （62 d, quartiles 55/83 d） （P=0.014）. Thirteen （62%） patients receiving targeted treatment experienced a disease control according to Response Evaluation Criteria in Solid Tumors （RECIST）. Median overall survival （OS） from the start of experimental therapy to time of censoring or death was 193 d （quartiles 115/374 d）. Conclusions： PM was not investigated in GI malignancies so far in a prospective trial. This study shows that treatment based on real-time molecular tumor profiling led to a superior clinical benefit, and survival as well as response was significantly improved when compared with previous standard medications.

Integration of molecular testing for the personalized management of patients with diffuse large B-cell lymphoma and follicular lymphoma

Diffuse large B-cell lymphoma(DLBCL)and follicular lymphoma(FL)are the most common forms of aggressive and indolent lymphoma,respectively.The majority of patients are cured by standard R-CHOP immunochemotherapy,but 30%–40%of DLBCL and 20%of FL patients relapse or are refractory(R/R).DLBCL and FL are phenotypically and genetically hereterogenous B-cell neoplasms.To date,the diagnosis of DLBCL and FL has been based on morphology,immunophenotyping and cytogenetics.However,next-generation sequencing(NGS)is widening our understanding of the genetic basis of the B-cell lymphomas.In this review we will discuss how integrating the NGS-based characterization of somatic gene mutations with diagnostic or prognostic value in DLBCL and FL could help refine B-cell lymphoma classification as part of a multidisciplinary pathology work-up.We will also discuss how molecular testing can identify candidates for clinical trials with targeted therapies and help predict therapeutic outcome to currently available treatments,including chimeric antigen receptor T-cell,as well as explore the application of circulating cell-free DNA,a non-invasive method for patient monitoring.We conclude that molecular analyses can drive improvements in patient outcomes due to an increased understanding of the different pathogenic pathways affected by each DLBCL subtype and indolent FL vs R/R FL.