scholarly journals Development of Molecularly Targeted Agents and Immunotherapies in Glioblastoma: A Personalized Approach

2018 ◽  
Vol 12 ◽  
pp. 117955491875907 ◽  
Author(s):  
Niamh Coleman ◽  
Malaka Ameratunga ◽  
Juanita Lopez
Keyword(s):  
Precision Medicine ◽  
Complex Disease ◽  
Targeted Agents ◽  
Multiple Cancer ◽  
Genomic Landscape ◽  
Molecularly Targeted Agents ◽  
Critical Issues ◽  
Cancer Types ◽  
Personalized Approach ◽  
The Impact

Over the past decade, precision cancer medicine has driven major advances in the management of advanced solid tumours with the identification and targeting of putative driver aberrations transforming the clinical outcomes across multiple cancer types. Despite pivotal advances in the characterization of genomic landscape of glioblastoma, targeted agents have shown minimal efficacy in clinical trials to date, and patient survival remains poor. Immunotherapy strategies similarly have had limited success. Multiple deficiencies still exist in our knowledge of this complex disease, and further research is urgently required to overcome these critical issues. This review traces the path undertaken by the different therapeutics assessed in glioblastoma and the impact of precision medicine in this disease. We highlight challenges for precision medicine in glioblastoma, focusing on the issues of tumour heterogeneity, pharmacokinetic-pharmacodynamic optimization and outline the modern hypothesis-testing strategies being undertaken to address these key challenges.

scholarly journals Impact on Oncology Practices of Including Drug Costs in Bundled Payments

2018 ◽  
Vol 14 (5) ◽  
pp. e259-e268 ◽  
Author(s):  
Jeffery C. Ward ◽  
Laura A. Levit ◽  
Ray D. Page ◽  
John E. Hennessy ◽  
John V. Cox ◽  
...  
Keyword(s):  
Complex Disease ◽  
Drug Costs ◽  
Fee For Service ◽  
Patient Case ◽  
Bundled Payment ◽  
Bundled Payments ◽  
Average Patient ◽  
Cancer Types ◽  
The Impact ◽  
Probabilistic Risk

Introduction: This analysis evaluates the impact of bundling drug costs into a hypothetic bundled payment. Methods: An economic model was created for patient vignettes from: advanced-stage III colon cancer and metastatic non–small-cell lung cancer. First quarter 2016 Medicare reimbursement rates were used to calculate the average fee-for-service (FFS) reimbursement for these vignettes. The probabilistic risk faced by practices was captured by the type of patients seen in practices and randomly assigned in a Monte Carlo simulation on the basis of the given distribution of patient types within each cancer. Simulations were replicated 1,000 times. The impact of bundled payments that include drug costs for various practice sizes and cancer types was quantified as the probability of incurring a loss at four magnitudes: any loss, > 10%, > 20%, or > 30%. A loss was defined as receiving revenue from the bundle that was less than what the practice would have received under FFS; the probability of loss was calculated on the basis of the number of times a practice reported a loss among the 1,000 simulations. Results: Practices that treat a substantial proportion of patients with complex disease compared with the average patient in the bundle would have revenue well below that expected from FFS. Practices that treat a disproportionate share of patients with less complex disease, as compared with the average patient in the bundle, would have revenue well above the revenue under FFS. Overall, bundled payments put practices at greater risk than FFS because their patient case mix could greatly skew financial performance. Conclusion: Including drug costs in a bundle is subject to the uncontrollable probabilistic risk of patient case mixes.

scholarly journals Suppressing immunotherapy by organ-specific tumor microenvironments: what is in the brain?

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Chenyu Zhang ◽  
Dihua Yu
Keyword(s):  
Immune Checkpoint Blockade ◽  
Multiple Cancer ◽  
Tissue Specific ◽  
Tumor Microenvironments ◽  
Specific Tumor ◽  
Organ Specific ◽  
Metastasis Models ◽  
Cancer Types ◽  
The Impact ◽  
The Brain

Abstract Recent breakthroughs in cancer immunotherapy have led to curative efficacy and significantly prolonged survival in a subset of patients of multiple cancer types; and immunotherapy has become the newest pillar of cancer treatment in addition to surgery, chemotherapy, radiotherapy and precision targeted therapies. In the metastatic disease setting, responses to immunotherapy are heterogeneous depending on the metastatic organ sites. The tissue-specific immuno-biology in the tumor microenvironments (TMEs) contributes to the differential therapeutic responses. Herein, we review the impact of tissue-specific tumor microenvironment on the efficacy of immunotherapy, with a focus on historically under-represented central nervous system (CNS) metastasis, which was excluded from most clinical trials. Retrospective examination of patient specimens and prospective clinical studies with immune checkpoint blockade (ICB) have established that brain can harbor an “active” immune microenvironment for effective immunotherapy. Regulation by the innate immune microglial cells and remodeling of the blood–brain barrier (BBB) may contribute to immunotherapeutic responses mediated by T lymphocytes. How to convert an “inactive” (cold) brain microenvironment into an “active” (hot) brain TME should be the focus of future efforts. Thus, procurement and complete examination of clinical specimens from brain metastases as well as development of appropriate preclinical brain metastasis models susceptible to external manipulation of the TME are critical steps towards that goal. A deeper understanding of the immuno-biology in distinct organ microenvironments will help to expand the benefits of immunotherapy to more needed patients.

Functional cell profiling (FCP) of ~100,000 CTCs from multiple cancer types identifies morphologically distinguishable CTC subtypes within and between cancer types.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14553-e14553
Author(s):  
Gordon Vansant ◽  
Adam Jendrisak ◽  
Ramsay Sutton ◽  
Sarah Orr ◽  
David Lu ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Single Cell ◽  
Digital Pathology ◽  
Disease Patient ◽  
Therapy Response ◽  
K Nearest Neighbor ◽  
Training Set ◽  
Multiple Cancer ◽  
Cluster Assignment ◽  
Cancer Types

e14553 Background: Different cancers subtypes can often be effectively treated with similar Rx classes (i.e. platinum or taxane Rx). Yet, within a disease patient therapy benefit can be variable. The origins of precision medicine derive from pathologic sub-stratification to guide therapy (e.g. SCLC vs. NSCLC). Using the Epic Sciences platform, we performed FPC analysis of ~100,000 single CTCs from multiple indications and sought to utilize high resolution digital pathology and machine learning to index metastatic cancers for the purpose of improving our understanding of therapy response and precision medicine. Methods: 92,300 CTCs underwent FCP analysis (single cell digital pathology features of cellular and sub-cellular morphometrics) were collected from prostate (1641 pts, 70,747 CTCs), breast (268 pts, 8,718 CTCs), NSCLC ( 110 pts, 1884 CTCs), SCLC ( 141 pts, 8,872 CTCs) and bladder (65 pts, 2079 CTCs) cancer pts. After pre-processing the raw data, a training set was balanced by sampling the same number of CTCs from each indication. K-means clustering was applied on the training set and optimized number of clusters were determined by using the elbow approach. After generating the clusters on the training set, the cluster centers were extracted from k-means, and used to train a k-Nearest Neighbor (k-NN) classifier to predict the cluster assignment for the remaining CTCs (test set). Results: The optimized # of clusters was 9. The % and characteristics of CTCs in each indication are listed below. BCa CTCs were more enriched in cluster c1, which had higher CK expression, while SCLC and some of mCRPC shared the small cell features (c5). Conclusions: Heterogeneous CTC phenotypic subtypes were observed across multiple indications. Each indication harbored subtype heterogeneity and shared clusters with other disease subtypes. Patient cluster subtype analysis to prognosis and therapy benefit are on-going. Analysis of linking of CTC subtypes genotypes (by single cell sequencing) and to patient survival on multiple indications is ongoing.[Table: see text]

scholarly journals CancerImmunityQTL: a database to systematically evaluate the impact of genetic variants on immune infiltration in human cancer

2020 ◽  
Vol 49 (D1) ◽  
pp. D1065-D1073
Author(s):  
Jianbo Tian ◽  
Yimin Cai ◽  
Yue Li ◽  
Zequn Lu ◽  
Jinyu Huang ◽  
...  
Keyword(s):  
Immune Cells ◽  
Genetic Variants ◽  
Immune Cell ◽  
Human Cancer ◽  
Tumor Development ◽  
Multiple Cancer ◽  
Immune Infiltration ◽  
Cancer Types ◽  
Cell Fractions ◽  
The Impact

Abstract Tumor-infiltrating immune cells as integral component of the tumor microenvironment are associated with tumor progress, prognosis and responses to immunotherapy. Genetic variants have been demonstrated to impact tumor-infiltrating, underscoring the heritable character of immune landscape. Therefore, identification of immunity quantitative trait loci (immunQTLs), which evaluate the effect of genetic variants on immune cells infiltration, might present a critical step toward fully understanding the contribution of genetic variants in tumor development. Although emerging studies have demonstrated the determinants of germline variants on immune infiltration, no database has yet been developed to systematically analyze immunQTLs across multiple cancer types. Using genotype data from TCGA database and immune cell fractions estimated by CIBERSORT, we developed a computational pipeline to identify immunQTLs in 33 cancer types. A total of 913 immunQTLs across different cancer types were identified. Among them, 5 immunQTLs are associated with patient overall survival. Furthermore, by integrating immunQTLs with GWAS data, we identified 527 immunQTLs overlapping with known GWAS linkage disequilibrium regions. Finally, we constructed a user-friendly database, CancerImmunityQTL (http://www.cancerimmunityqtl-hust.com/) for users to browse, search and download data of interest. This database provides an informative resource to understand the germline determinants of immune infiltration in human cancer and benefit from personalized cancer immunotherapy.

scholarly journals New Drugs Bringing New Challenges to AML: A Brief Review

2021 ◽  
Vol 11 (10) ◽  
pp. 1003
Author(s):  
Zhi Han Yeoh ◽  
Ashish Bajel ◽  
Andrew H. Wei
Keyword(s):  
Acute Myeloid Leukaemia ◽  
Precision Medicine ◽  
Side Effect ◽  
Mechanisms Of Action ◽  
New Drugs ◽  
Novel Therapies ◽  
Genomic Landscape ◽  
New Challenges ◽  
The Impact ◽  
Acute Myeloid

The better understanding of the genomic landscape in acute myeloid leukaemia (AML) has progressively paved the way for precision medicine in AML. There is a growing number of drugs with novel mechanisms of action and unique side-effect profiles. This review examines the impact of evolving novel therapies on survival in AML and the challenges that ensue.

Article Review: The Impact of Fun and Enjoyment on Adult Learning

2019 ◽  
Vol 1 (2) ◽  
pp. 96
Author(s):  
Laily Yahya
Keyword(s):  
Adult Learners ◽  
Adult Learning ◽  
Teaching And Learning ◽  
Educational Programme ◽  
Continuous Quality ◽  
Teachers Beliefs ◽  
Critical Issues ◽  
Affective Experiences ◽  
The Impact

The article review of ‘The Impact of Fun and Enjoyment on Adult Learning’ (Lucardie, 2014) opens doors to the kaleidoscope of fun and enjoyment amongst adult learners. The essence of this review is an informative snapshot on the critical issues of how fun and joy have impacted adult learning through a qualitative research drawing upon traditions of phenomenology. It aims to explore the affective experiences of fun and enjoyment. This article review attempts to highlight an insightful assessment of the ideas and the arguments that are being discussed by the author. The different interpretation of this concept draws out contrasting elements between learners and teachers’ beliefs. A twist to this review is a reflective stance procured to address central issues emerging in the article related to the Malaysian context. It is through the lens of the reader, Continuous Quality Improvement (CQI):4R is proposed. This refers to the process of continuously improving the quality of teaching and learning of an educational programme. This review concludes with the framing of CQI:4R to illustrate reflect, revisit, realign and reconstruct processes that could possibly navigate the architectural landscape of the Malaysian Teacher Education.

Artificial Intelligence as a Business Partner in Cardiovascular Precision Medicine: an Emerging Approach for Disease Detection and Treatment Optimization

2020 ◽  
Vol 28 ◽  
Author(s):  
Valeria Visco ◽  
Germano Junior Ferruzzi ◽  
Federico Nicastro ◽  
Nicola Virtuoso ◽  
Albino Carrizzo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Heart Failure ◽  
Atrial Fibrillation ◽  
Precision Medicine ◽  
Clinical Decision Making ◽  
Disease Detection ◽  
Physician Patient Relationship ◽  
Invasive Approach ◽  
Tailored Treatment ◽  
The Impact

Background: In the real world, medical practice is changing hand in hand with the development of new Artificial Intelligence (AI) systems and problems from different areas have been successfully solved using AI algorithms. Specifically, the use of AI techniques in setting up or building precision medicine is significant in terms of the accuracy of disease discovery and tailored treatment. Moreover, with the use of technology, clinical personnel can deliver a very much efficient healthcare service. Objective: This article reviews AI state-of-the-art in cardiovascular disease management, focusing on diagnostic and therapeutic improvements. Methods: To that end, we conducted a detailed PubMed search on AI application from distinct areas of cardiology: heart failure, arterial hypertension, atrial fibrillation, syncope and cardiovascular rehabilitation. Particularly, to assess the impact of these technologies in clinical decision-making, this research considers technical and medical aspects. Results: On one hand, some devices in heart failure, atrial fibrillation and cardiac rehabilitation represent an inexpensive, not invasive or not very invasive approach to long-term surveillance and management in these areas. On the other hand, the availability of large datasets (big data) is a useful tool to predict the development and outcome of many cardiovascular diseases. In summary, with this new guided therapy, the physician can supply prompt, individualised, and tailored treatment and the patients feel safe as they are continuously monitored, with a significant psychological effect. Conclusion: Soon, tailored patient care via telemonitoring can improve the clinical practice because AI-based systems support cardiologists in daily medical activities, improving disease detection and treatment. However, the physician-patient relationship remains a pivotal step.

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