Personalized cancer medicine: molecular diagnostics, predictive biomarkers, and drug resistance.

The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution.

Médecine génomique et oncologie [Genomics medicine and oncology].

Progress in genomics with, in particular, high throughput next generation sequencing is revolutionizing oncology. The impact of these techniques is seen on the one hand the identification of germline mutations that predispose to a given type of cancer, allowing for a personalized care of patients or healthy carriers and, on the other hand, the characterization of all acquired somatic mutation of the tumor cell, opening the door to personalized treatment targeting the driver oncogenes. In both cases, next generation sequencing techniques allow a global approach whereby the integrality of the genome mutations is analyzed and correlated with the clinical data. The benefits on the quality of care delivered to our patients are extremely impressive.

Systems medicine and integrated care to combat chronic noncommunicable diseases

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

Systems Medicine and Integrated Care to Combat Chronic Noncommunicable Diseases.

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

Targeting the undruggable: immunotherapy meets personalized oncology in the genomic era.

Owing to recent advances in genomic technologies, personalized oncology is poised to fundamentally alter cancer therapy. In this paradigm, the mutational and transcriptional profiles of tumors are assessed, and personalized treatments are designed based on the specific molecular abnormalities relevant to each patient's cancer. To date, such approaches have yielded impressive clinical responses in some patients. However, a major limitation of this strategy has also been revealed: the vast majority of tumor mutations are not targetable by current pharmacological approaches. Immunotherapy offers a promising alternative to exploit tumor mutations as targets for clinical intervention. Mutated proteins can give rise to novel antigens (called neoantigens) that are recognized with high specificity by patient T cells. Indeed, neoantigen-specific T cells have been shown to underlie clinical responses to many standard treatments and immunotherapeutic interventions. Moreover, studies in mouse models targeting neoantigens, and early results from clinical trials, have established proof of concept for personalized immunotherapies targeting next-generation sequencing identified neoantigens. Here, we review basic immunological principles related to T-cell recognition of neoantigens, and we examine recent studies that use genomic data to design personalized immunotherapies. We discuss the opportunities and challenges that lie ahead on the road to improving patient outcomes by incorporating immunotherapy into the paradigm of personalized oncology.

L'échographie dans le dépistage du cancer du sein: un outil efficace dans un dépistage personnalisé [Ultrasound for Breast Cancer Screening: an Effective Tool in a Personalized Screening].

Screening mammography is the only imaging modality with proved decrease in breast cancer mortality. Ultrasound has been proposed as additional tool for screening. Controversies remain about the real value of sonography in this setting. In Caucasian women with dense breast, sonography improves significantly breast cancer detection, but also increases the false positive cases, biopsies and costs. A careful selection of women who may benefit from additional screening with sonography is mandatory.

Personalized therapy in pain management: where do we stand?

Genomic variations influencing response to pharmacotherapy of pain are currently under investigation. Drug-metabolizing enzymes represent a major target of ongoing research in order to identify associations between an individual's drug response and genetic profile. Polymorphisms of the cytochrome P450 enzymes (CYP2D6) influence metabolism of codeine, tramadol, hydrocodone, oxycodone and tricyclic antidepressants. Blood concentrations of some NSAIDs depend on CYP2C9 and/or CYP2C8 activity. Genomic variants of these genes associate well with NSAIDs' side effect profile. Other candidate genes, such as those encoding (opioid) receptors, transporters and other molecules important for pharmacotherapy in pain management, are discussed; however, study results are often equivocal. Besides genetic variants, further variables, for example, age, disease, comorbidity, concomitant medication, organ function as well as patients' compliance, may have an impact on pharmacotherapy and need to be addressed when pain therapists prescribe medication. Although pharmacogenetics as a diagnostic tool has the potential to improve patient therapy, well-designed studies are needed to demonstrate superiority to conventional dosing regimes.

Systems medicine and integrated care to combat chronic noncommunicable diseases

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

Adaptive Algorithms for Personalized Diabetes Treatment

Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

Five Years Of Implementation Of Guidelines In Hematology And Transfusion Medicine In Brazil.

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Juan César García: Social Medicine As Project And Endeavor.

This paper analyses some aspects of the trajectory of the Argentinian physician and sociologist Juan César García (1932-1984) in the field of Latin American Social Medicine. Three dimensions constituting his basic orientations are highlighted: the elaboration of systematic and reflective social thought; a critical attitude in questioning teaching and professional practices; a commitment to the institutionalization and dissemination of health knowledge.

Highlights from the I international symposium of thrombosis and anticoagulation in internal medicine, October 23–25, 2008, Sao Paulo, Brazil

Abstract The importance of thrombosis and anticoagulation in clinical practice is rooted firmly in several fundamental constructs that can be applied both broadly and globally. Awareness and the appropriate use of anticoagulant therapy remain the keys to prevention and treatment. However, to assure maximal efficacy and safety, the clinician must, according to the available evidence, choose the right drug, at the right dose, for the right patient, under the right indication, and for the right duration of time. The first International Symposium of Thrombosis and Anticoagulation in Internal Medicine was a scientific program developed by clinicians for clinicians. The primary objective of the meeting was to educate, motivate and inspire internists, cardiologists and hematologists by convening national and international visionaries, thought-leaders and dedicated clinician-scientists in Sao Paulo, Brazil. This article is a focused summary of the symposium proceedings

Five-year follow-up of angiographic disease progression after medicine, angioplasty, or surgery

Background: Progression of atherosclerosis in coronary artery disease is observed through consecutive angiograms. Prognosis of this progression in patients randomized to different treatments has not been established. This study compared progression of coronary artery disease in native coronary arteries in patients undergoing surgery, angioplasty, or medical treatment. Methods: Patients (611) with stable multivessel coronary artery disease and preserved ventricular function were randomly assigned to CABG, PCI, or medical treatment alone (MT). After 5-year follow-up, 392 patients (64%) underwent new angiography. Progression was considered a new stenosis of >= 50% in an arterial segment previously considered normal or an increased grade of previous stenosis > 20% in nontreated vessels. Results: Of the 392 patients, 136 underwent CABG, 146 PCI, and 110 MT. Baseline characteristics were similar among treatment groups, except for more smokers and statin users in the MT group, more hypertensives and lower LDL-cholesterol levels in the CABG group, and more angina in the PCI group at study entry. Analysis showed greater progression in at least one native vessel in PCI patients (84%) compared with CABG (57%) and MT (74%) patients (p < 0.001). LAD coronary territory had higher progression compared with LCX and RCA (P < 0.001). PCI treatment, hypertension, male sex, and previous MI were independent risk factors for progression. No statistical difference existed between coronary events and the development of progression. Conclusion: The angioplasty treatment conferred greater progression in native coronary arteries, especially in the left anterior descending territories and treated vessels. The progression was independently associated with hypertension, male sex, and previous myocardial infarction.