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.

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.

Banking of perinatal mesenchymal stem/stromal cells for stem cellbased personalized medicine over lifetime:Matters arising

Mesenchymal stromal/stem cells(MSCs)are currently applied in regenerative medicine and tissue engineering.Numerous clinical studies have indicated that MSCs from different tissue sources can provide therapeutic benefits for patients.MSCs derived from either human adult or perinatal tissues have their own unique advantages in their medical practices.Usually,clinical studies are conducted by using of cultured MSCs after thawing or short-term cryopreserved-then-thawed MSCs prior to administration for the treatment of a wide range of diseases and medical disorders.Currently,cryogenically banking perinatal MSCs for potential personalized medicine for later use in lifetime has raised growing interest in China as well as in many other countries.Meanwhile,this has led to questions regarding the availability,stability,consistency,multipotency,and therapeutic efficiency of the potential perinatal MSC-derived therapeutic products after longterm cryostorage.This opinion review does not minimize any therapeutic benefit of perinatal MSCs in many diseases after short-term cryopreservation.This article mainly describes what is known about banking perinatal MSCs in China and,importantly,it is to recognize the limitation and uncertainty of the perinatal MSCs stored in cryobanks for stem cell medical treatments in whole life.This article also provides several recommendations for banking of perinatal MSCs for potentially future personalized medicine,albeit it is impossible to anticipate whether the donor will benefit from banked MSCs during her/his lifetime.

Personalized medicine approach to osteoporosis management in women: integrating genetics, pharmacogenomics, and precision treatments

Osteoporosis has emerged as a significant health issue among postmenopausal women.Addressing this concern necessitates a multifaceted approach encompassing genetics,pharmacogenomics,bone turnover markers,lifestyle factors,concurrent medical conditions,biomarkers,and advanced imaging techniques.Nonetheless,challenges in terms of cost-effectiveness and ethical considerations do exist.Fortunately,the convergence of technological progress and research endeavors offers a promising trajectory.The integration of genetic testing and pharmacogenomics into clinical practice holds substantial potential.This integration empowers healthcare professionals to forecast treatment responses and pinpoint individuals with elevated susceptibility,thereby enabling the implementation of tailored and efficacious interventions that optimize outcomes–personalized medicine.Given the intricate nature of osteoporosis,personalized strategies stand to greatly benefit women grappling with this condition.Further research and collaborative efforts are imperative to propel advancements within this domain,paving the way for further breakthroughs.

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.

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.

Genomics in personalized cancer medicine and its impact on earlydrug development in China: report from the 6th Annual Meeting of the US Chinese Anti-Cancer Association(USCACA) at the 50th ASCOAnnual Meeting

The 6th Annual Meeting of the United States Chinese Anti-Cancer Association(USCACA) was held in conjunction with the 50 th Annual Meeting of American Society of Clinical Oncology(ASCO) on May 30, 2014 in Chicago, Illinois, the United States of America. With a focus on personalized medicine, the conference featured novel approaches to investigate genomic aberrations in cancer cells and innovative clinical trial designs to expedite cancer drug development in biomarker-defined patient populations. A panel discussion further provided in-depth advice on advancing development of personalized cancer medicines in China. The conference also summarized USCACA key initiatives and accomplishments, including two awards designated to recognize young investigators from China for their achievements and to support their training in the United States. As an effort to promote international collaboration, USCACA will team up with Chinese Society of Clinical Oncology(CSCO) to host a joint session on "Breakthrough Cancer Medicines" at the upcoming CSCO Annual Meeting on September 20 th, 2014 in Xiamen, China.

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.

An Optimal Control Approach to Structured Treatment Interruptions for HIV Patients: A Personalized Medicine Perspective

Highly Active Antiretroviral Therapy (HAART) has changed the course of human immunodeficiency virus (HIV) treatments since its introduction. However, for many patients, long term continuous HAART is expensive and can include problems with drug toxicity and side effects, as well as increased drug resistance. Because of these reasons, some HIV infected patients will voluntarily terminate HAART. Some of these patients will also interrupt the continuous prescribed therapies for short or long periods. After discontinuing HAART, patients will usually experience a rapid increase in viral load coupled with an immediate decline in CD4+ counts. The canonical example of a patient undergoing unsupervised breaks in HAART is that of the “Berlin patient”. In this case, the patient was able to control viral load in the absence of treatment by cycling HAART on and off due to non-related infections. Due to this patient, interest in the use of structured treatment interruptions (STI) as a mechanism to regulate an HIV infection piqued. This paper describes an optimal control approach to determine STI regimen for HIV patients. The optimal STI was implemented in the context of the receding horizon control (RHC) using a mathematical model for the in-vivo dynamics of an HIV type 1 infection. Using available clinical data, we calibrate the model by estimating on a patient specific basis, a best estimable set of parameters using sensitivity analysis and subset selection. We demonstrate how customized STI protocols can be designed through the variation of control parameters on a patient specific basis.

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.

Healthcare practice strategies for integrating personalized medicine:Management of COVID-19

Personalized medicine is the tailor-made clinical treatment to the individual characteristics of each patient.It may be considered an extension of traditional approaches to knowing and treating diseases.Personalized medicine has the potential to change the way of identification and management of health problems.Coronavirus disease 2019(COVID-19)is an infectious disease that primarily affects the patients’lungs.The first case of pneumonia of unknown cause was reported in Wuhan,China on December 31,2019.As thus,we are quickly approaching the era of personalized medicine.This review discusses the practices currently used in the management of COVID-19 and how they relate to person-alized medicine.

PPPM (Predictive, Preventive and Personalized Medicine) as a New Model of the National and International Healthcare Services and Thus a Promising Strategy to Prevent a Disease: From Basics to Practice

Nowadays the system of public health is constructed in such a manner so that its main objective is the recovery of an already sick person, while prediction and prevention receive little attention. Meanwhile the development of these aspects of medicine can lead to the ability to control morbidity among the population, to identify chronic and genetic diseases in the early stages of development, and thus to prevent their further progression. This will reduce traditionally high costs of sick people treatment and the number of disabled population, and improve the quality and duration of life. The elaboration of new fields of science that are working on the study and interpretation of data obtained during laboratory and clinical research, creation of new methods for diagnosis, prognosis and treatment, provides an opportunity now to implement a new strategy, called PPPM, and gets promising results, which should lead to further development of an existing medicine.

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.

Harnessing pharmacological knowledge for personalized medicine and pharmacotyping: Challenges and lessons learned

The contribution of the genetic make-up to an individual’s capacity has long been recognized in modern pharmacology as a crucial factor leading to therapy ineffciency and toxicity, negatively impacting the economic burden of healthcare and restricting the monitoring of diseases. In practical terms, and in order for drug prescription to be improved toward meeting the personalized medicine concept in drug delivery, the maximum clinical outcome for most, if not all, patients must be achieved, i.e. , pharmacotyping. Such a direction although promising and of high expectation from the society, it is however hardly to be afforded for healthcare worldwide. To overcome any existed hurdles, this means that practical clinical utility of personalized medicine decisions have to be documented and validated in the clinical setting. The latter implies for drug delivery the effcient implementation of previously gained in vivo pharmacology experience with pharmacogenomics knowledge. As an approach to work faster and in a more productive way, the elaboration of advanced physiologically based phar-macokinetics models is discussed. And in better clarifying this topic, the example of tamoxifen is thoroughly presented. Overall, pharmacotyping represents a major challenge in modern therapeutics for which pharmacologists need to work in successfully fulflling this task.

Translation in Data Mining to Advance Personalized Medicine for Health Equity

Personalized medicine is the development of “tailored” therapies that reflect traditional medical approaches with the incorporation of the patient’s unique genetic profile and the environmental basis of the disease. These individualized strategies encompass disease prevention and diagnosis, as well as treatment strategies. Today’s healthcare workforce is faced with the availability of massive amounts of patient- and disease-related data. When mined effectively, these data will help produce more efficient and effective diagnoses and treatment, leading to better prognoses for patients at both the individual and population level. Designing preventive and therapeutic interventions for those patients who will benefit most while minimizing side effects and controlling healthcare costs requires bringing diverse data sources together in an analytic paradigm. A resource to clinicians in the development and application of personalized medicine is largely facilitated, perhaps even driven, by the analysis of “big data”. For example, the availability of clinical data warehouses is a significant resource for clinicians in practicing personalized medicine. These “big data” repositories can be queried by clinicians, using specific questions, with data used to gain an understanding of challenges in patient care and treatment. Health informaticians are critical partners to data analytics including the use of technological infrastructures and predictive data mining strategies to access data from multiple sources, assisting clinicians’ interpretation of data and development of personalized, targeted therapy recommendations. In this paper, we look at the concept of personalized medicine, offering perspectives in four important, influencing topics: 1) the availability of “big data” and the role of biomedical informatics in personalized medicine, 2) the need for interdisciplinary teams in the development and evaluation of personalized therapeutic approaches, and 3) the impact of electronic medical record systems and clinical data warehouses on the field of personalized medicine. In closing, we present our fourth perspective, an overview to some of the ethical concerns related to personalized medicine and health equity.

Mini-review on personalized medicine:a revolution in health care

Health care has evolved since the reduction in mortality caused by infections as well as chronic and noncommunicable diseases.This has had a direct influence on the expense of public health and individual health care,as well as the quality of health care.It’s time to move away from traditional reactive medicine centered on symptoms,diagnosis,and treatment to a system that targets illness before it develops and,if it cannot be prevented,treats it in a customized manner.The expansion of established techniques to understanding and treating disease is personalized medicine.Individual genetic and epigenetic information is a fast-growing multiple-faceted therapeutic strategy,used to customize pharmacological therapy or preventative treatment.Personalized medicine seeks to make early intervention better diagnoses and to improve medication development and therapy.In this study,the impact of customized medicine on the therapy,its applications,and prospects for healthcare are evaluated.

Myocarditis—Personalized Medicine by Expanded Endomyocardial Biopsy Diagnostics

Myocarditis and dilated cardiomyopathy (DCM) are acute or chronic disorders of myocardium. The gold standard for final confirmation of causative reasons of these heart muscle diseases is the endomyocardial biopsy (EMB) analysis. Due to focal pathology, diagnostics are failing if the EMB does not contain the area of interest. Personalized medicine comprises the genetic information together with the phenotypic and environmental factors to yield a tailored healthcare for each individual and removes the limitations of the “one-size-fits-all” therapy approach. This provides the opportunity to translate therapies from bench to bedside, to diagnose and predict disease, and to improve patient-tailored treatments based on the unique signatures of a patient’s disease. Furthermore, novel treatment schedules can be identified which have eventually the chance to enhance long-term survivals. Global biomarkers such as specific gene expression signatures or miRNA profiles not only have the potential to reduce this problem but also add valuable information for individualized therapy decisions. In future, multiplex approaches allowing rapid and absolutely reliable identification of inflammatory or virally-induced myocardial diseases will replace singleplex methods such as direct detection of viral genomes in one single biopsy. Gene or miRNA profiles are upcoming diagnostic biomarkers for cardiomyopathies which are not only detectable in tissue samples but in body fluids as well. Consequently, a systemic diagnostic approach by determination of distinct expression pattern in e.g., peripheral blood samples will support the characterization of distinct cardiomyopathies by means of non-invasive methods.

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.

Utilizing gastric cancer organoids to assess tumor biology and personalize medicine

While the incidence and mortality of gastric cancer (GC) have declined due to public health programs, it remains the third deadliest cancer worldwide. For patients with early disease, innovative endoscopic and complex surgical techniques have improved survival. However, for patients with advanced disease, there are limited treatment options and survival remains poor. Therefore, there is an urgent need for more effective therapies. Since novel therapies require extensive preclinical testing prior to human trials, it is important to identify methods to expedite this process. Traditional cancer models are restricted by the inability to accurately recapitulate the primary human tumor, exorbitant costs, and the requirement for extended periods of development time. An emerging in vitro model to study human disease is the patient-derived organoid, which is a three-dimensional system created from fresh surgical or biopsy tissues of a patient’s gastric tumor. Organoids are cultured in plastic wells and suspended in a gelatinous matrix, providing a substrate for extension and growth in all dimensions. They are rapid-growing and highly representative of the molecular landscape, histology, and morphology of the various subtypes of GC. Organoids uniquely model tumor initiation and growth, including steps taken by normal stomach cells to transform into invasive, intestinal-type tumor cells. Additionally, they provide ample material for biobanking and screening novel therapies. Lastly, organoids are a promising model for personalized therapy and warrant further investigation in drug sensitivity studies for GC patients.