Lung Transplantation and Precision Medicine
Ontology highlight
ABSTRACT:
SUBMITTER: Gomez J
PROVIDER: S-EPMC7120453 | biostudies-literature | 2019 Sep
REPOSITORIES: biostudies-literature
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Project description:In kidney transplantation, precision medicine has already entered clinical practice. Donor and recipient human leucocyte antigen (HLA) regions are genotyped in two class 1 and usually three class 2 loci, and the individual degree of sensitization against alloimmune antigens is evaluated by the detection of anti-HLA donor-specific antibodies. Recently, the contribution of non-HLA mismatches to outcomes such as acute T- and B-cell-mediated rejection and even long-term graft survival was described. Tracking of specific alloimmune T- and B-cell clones by next generation sequencing and refinement of the immunogenicity of allo-epitopes specifically in the interaction with HLA and T- and B-cell receptors may further support individualized therapy. Although the choices of maintenance immunosuppression are rather limited, individualization can be accomplished by adjustment of dosing based on these risk predictors. Finally, supplementing histopathology by a transcriptomics analysis allows for a biological interpretation of the histological findings and avoids interobserver variability of results. In contrast to transplantation, the prescription of hemodialysis therapy is far from precise. Guidelines do not consider modifications by age, diet or many comorbid conditions. Patients with residual kidney function routinely receive the same treatment as those without. A major barrier hitherto is the definition of 'adequate' treatment based on urea removal. Kt/Vurea and related parameters neither reflect the severity of uremic symptoms nor predict long-term outcomes. Urea is poorly representative for numerous other compounds that accumulate in the body when the kidneys fail, yet clinicians prescribe treatment based on its measurement. Modern technology has provided the means to identify other solutes responsible for specific features of uremic illness and their measurement will be a necessary step in moving beyond the standardized prescription of hemodialysis.
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Project description:Both tumors and patients are complex and models that determine survival and toxicity of radiotherapy or any other treatment ideally must take into account this variability as well as its dynamic state. The genetic features of the tumor and the host, and increasingly also the epi-genetic and proteomic characteristics, are being unraveled. Multiple techniques, including histological examination, blood sampling, measurement of circulating tumor cells (CTCs), and functional and molecular imaging, can be used for this purpose. However, the effects of radiation on the tumor and on organs at risk (OARs) are also influenced by the applied dose and volume of irradiated tissues. Combining all these biological, clinical, imaging, and dosimetric parameters in a validated prognostic or predictive model poses a major challenge. Here we aimed to provide an objective review of the potential of blood markers to guide high precision radiation therapy. A combined biological-mathematical approach opens new doors beyond prognostication of patients, as it allows truly precise oncological treatment. Indeed, the core for individualized and precision medicine is not only selection of patients, but even more the optimization of the therapeutic window on an individual basis. A holistic model will allow for determination of an individual dose-response relationship for each organ at risk for each tumor in each individual patient for the complete oncological treatment package. This includes, but is not limited to, radiotherapy alone. Individualized dose-response curves will allow for consideration of different doses of radiation and combinations with other drugs to plan for both optimal toxicity and complete response. Insights into the interactions between a multitude of parameters will lead to the discovery of new pathways and networks that will fuel new biological research on target discovery.
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Project description:Lung adenocarcinoma (LADC), the most frequent histological type of lung cancer, is often triggered by an aberration in a driver oncogene in tumor cells. Examples of such aberrations are EGFR mutation and ALK fusion. Lung adenocarcinoma harboring such mutations can be treated with anticancer drugs that target the aberrant gene products. Additional oncogene aberrations, including RET, ROS1, and NRG1 fusions, skipping of exon 14 of MET, and mutations in BRAF, HER2, NF1, and MEK1, were recently added to the list of such "druggable" driver oncogene aberrations, and their responses to targeted therapies are currently being evaluated in clinical trials. However, approximately 30% and 50% of LADCs in patients in Japan and Europe/USA, respectively, lack the driver oncogene aberrations listed above. Therefore, novel therapeutic strategies, such as those that exploit the vulnerabilities of cancer cells with non-oncogene aberrations, are urgently required. This review summarizes the current status of research on precision medicine against LADC and enumerates the research priorities for the near future.
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Project description:The past decade has been transformative for lung cancer patients, physicians, and scientists. The discovery of EGFR mutations that confer sensitivity to tyrosine kinase inhibitors in lung adenocarcinomas in 2004 heralded the beginning of the era of precision medicine for lung cancer. Indeed, it precipitated concerted efforts by many investigators to define molecular subgroups of lung cancer, characterize the genomic landscape of lung cancer subtypes, identify novel therapeutic targets, and define mechanisms of sensitivity and resistance to targeted therapies. The fruits of these efforts are visible every day now in lung cancer clinics: Patients receive molecular testing to determine whether their tumor harbors an actionable mutation, new and improved targeted therapies that can overcome resistance to first-generation drugs are in clinical trials, and drugs targeting the immune system are showing activity in patients. This extraordinary promise is tempered by the sobering fact that even the newest treatments for metastatic disease are rarely curative and are effective only in a small fraction of all patients. Ongoing and future efforts to find new vulnerabilities of lung cancers, unravel the complexity of drug resistance, increase the efficacy of immunotherapies, and perform biomarker-driven clinical trials are necessary to improve outcomes for patients with lung cancer.
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Project description:We previously demonstrated that altered activity of lysophosphatidic acid in murine mammary glands promotes tumorigenesis. We have now established and characterized a heterogeneous collection of mouse-derived syngeneic transplants (MDSTs) as preclinical platforms for the assessment of personalized pharmacological therapies. Detailed molecular and phenotypic analyses revealed that MDSTs are the most heterogeneous group of genetically engineered mouse models (GEMMs) of breast cancer yet observed. Response of MDSTs to trametinib, a mitogen-activated protein kinase (MAPK) kinase inhibitor, correlated with RAS/MAPK signaling activity, as expected from studies in xenografts and clinical trials providing validation of the utility of the model. Sensitivity of MDSTs to talazoparib, a poly(adenosine 5'-diphosphate-ribose) polymerase (PARP) inhibitor, was predicted by PARP1 protein levels and by a new PARP sensitivity predictor (PSP) score developed from integrated analysis of drug sensitivity data of human cell lines. PSP score-based classification of The Cancer Genome Atlas breast cancer suggested that a subset of patients with limited therapeutic options would be expected to benefit from PARP-targeted drugs. These results indicate that MDSTs are useful models for studies of targeted therapies, and propose novel potential biomarkers for identification of breast cancer patients likely to benefit from personalized pharmacological treatments.
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Project description:Desirable outcomes including rejection- and infection-free kidney transplantation are not guaranteed despite current strategies for immunosuppression and using prophylactic antimicrobial medications. Graft survival depends on factors beyond human leukocyte antigen matching such as the level of immunosuppression, infections, and management of other comorbidities. Risk stratification of transplant patients based on predisposing genetic modifiers and applying precision pharmacotherapy may help improving the transplant outcomes. Unlike certain fields such as oncology in which consistent attempts are being carried out to move away from the "error and trial approach," transplant medicine is lagging behind in implementing personalized immunosuppressive therapy. The need for maintaining a precarious balance between underimmunosuppression and overimmunosuppression coupled with adverse effects of medications calls for a gene-based guidance for precision pharmacotherapy in transplantation. Technologic advances in molecular genetics have led to increased accessibility of genetic tests at a reduced cost and have set the stage for widespread use of gene-based therapies in clinical care. Evidence-based guidelines available for precision pharmacotherapy have been proposed, including guidelines from Clinical Pharmacogenetics Implementation Consortium, the Pharmacogenomics Knowledge Base National Institute of General Medical Sciences of the National Institutes of Health, and the US Food and Drug Administration. In this review, we discuss the implications of pharmacogenetics and potential role for genetic variants-based risk stratification in kidney transplantation. A single score that provides overall genetic risk, a polygenic risk score, can be achieved by combining of allograft rejection/loss-associated variants carried by an individual and integrated into practice after clinical validation.
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Project description:The management of interstitial lung disease (ILD) may benefit from a conceptual shift. Increased understanding of this complex and heterogeneous group of disorders over the past 20 years has highlighted the need for individualised treatment strategies that encompass diagnostic classification and disease behaviour. Biomarker-based approaches to precision medicine hold the greatest promise. Robust, large-scale biomarker-based technologies supporting ILD diagnosis have been developed, and future applications relating to staging, prognosis and assessment of treatment response are emerging. Artificial intelligence may redefine our ability to base prognostic evaluation on both diagnosis and underlying disease processes, sharpening individualised treatment algorithms to a level not previously achieved. Compared with therapeutic areas such as oncology, precision medicine in ILD is still in its infancy. However, the heterogeneous nature of ILD suggests that many relevant molecular, environmental and behavioural targets may serve as useful biomarkers if we are willing to invest in their identification and validation.
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Project description:Data are limited regarding whether the availability of biomarker-directed therapy for lung cancer exacerbates racial and socioeconomic disparities. Patients diagnosed with stage IV lung adenocarcinoma from 2008 to 2013 were identified using Surveillance, Epidemiology, and End Results Program-Medicare. The primary outcome was a Medicare claim for molecular testing within 60 days of diagnosis, analyzed using multivariable logistic regression; the secondary outcome was overall survival, analyzed using multivariable Cox proportional hazards models. All statistical tests were two-sided. Of 5556 patients, 1437 (25.9%) had molecular testing. Testing rates were 14.1% among black, 26.2% among white, and 32.8% among patients of Asian/other descent (adjusted P < .001); 20.6% among patients with Medicaid eligibility vs 28.4% among those without (adjusted P = .01); and 19.9% among patients in the highest census tract-level poverty rate quintile vs 30.7% among patients in the lowest quintile (for all quintiles, adjusted P = .18). Median survival from 60 days was 8.2 months among patients with molecular testing within 60 days of diagnosis and 6.1 months among those without (hazard ratio = 0.92, 95% confidence interval = 0.86 to 0.99; adjusted P = .02). Equitable precision medicine requires concerted implementation efforts.
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