Cancer Precision Medicine: From Cancer Screening to Drug Selection and Personalized Immunotherapy

Colorectal Cancer Diagnosis through Breath Test Using a Portable Breath Analyzer-Preliminary Data

Screening methods available for colorectal cancer (CRC) to date are burdened by poor reliability and low patient adherence and compliance. An altered pattern of volatile organic compounds (VOCs) in exhaled breath has been proposed as a non-invasive potential diagnostic tool for distinguishing CRC patients from healthy controls (HC). The aim of this study was to evaluate the reliability of an innovative portable device containing a micro-gas chromatograph in enabling rapid, on-site CRC diagnosis through analysis of patients' exhaled breath. In this prospective trial, breath samples were collected in a tertiary referral center of colorectal surgery, and analysis of the chromatograms was performed by the Biomedical Engineering Department. The breath of patients with CRC and HC was collected into Tedlar bags through a Nafion filter and mouthpiece with a one-way valve. The breath samples were analyzed by an automated portable gas chromatography device. Relevant volatile biomarkers and discriminant chromatographic peaks were identified through machine learning, linear discriminant analysis and principal component analysis. A total of 68 subjects, 36 patients affected by histologically proven CRC with no evidence of metastases and 32 HC with negative colonoscopies, were enrolled. After testing a training set (18 CRC and 18 HC) and a testing set (18 CRC and 14 HC), an overall specificity of 87.5%, sensitivity of 94.4% and accuracy of 91.2% in identifying CRC patients was found based on three VOCs. Breath biopsy may represent a promising non-invasive method of discriminating CRC patients from HC.

NIMEQ-SACNet: A novel self-attention precision medicine model for vision-threatening diabetic retinopathy using image data

In the realm of precision medicine, the potential of deep learning is progressively harnessed to facilitate intricate clinical decision-making, especially when navigating multifaceted datasets encompassing Omics, Clinical, image, device, social, and environmental dimensions. This study accentuates the criticality of image data, given its instrumental role in detecting and classifying vision-threatening diabetic retinopathy (VTDR) - a predominant global contributor to vision impairment. The timely identification of VTDR is a linchpin for efficacious interventions and the mitigation of vision loss. Addressing this, This study introduces "NIMEQ-SACNet," a novel hybrid model by the prowess of the Enhanced Quantum-Inspired Binary Grey Wolf Optimizer (EQI-BGWO) with a self-attention capsule network. The proposed approach is characterized by two pivotal advancements: firstly, the augmentation of the Binary Grey Wolf Optimization through Quantum Computing methodologies, and secondly, the deployment of the enhanced EQI-BGWO to adeptly calibrate the SACNet's parameters, culminating in a notable uplift in VTDR classification accuracy. The proposed model's ability to handle binary, 5-stage, and 7-stage VTDR classifications adroitly is noteworthy. Rigorous assessments on the fundus image dataset, underscored by metrics such as Accuracy, Sensitivity, Specificity, Precision, F1-Score, and MCC, bear testament to NIMEQ-SACNet's pre-eminence over prevailing algorithms and classification frameworks.

Nanomedicine Combats Drug Resistance in Lung Cancer

Lung cancer is the second most prevalent cancer and the leading cause of cancer-related death worldwide. Surgery, chemotherapy, molecular targeted therapy, immunotherapy, and radiotherapy are currently available as treatment methods. However, drug resistance is a significant factor in the failure of lung cancer treatments. Novel therapeutics have been exploited to address complicated resistance mechanisms of lung cancer and the advancement of nanomedicine is extremely promising in terms of overcoming drug resistance. Nanomedicine equipped with multifunctional and tunable physiochemical properties in alignment with tumor genetic profiles can achieve precise, safe, and effective treatment while minimizing or eradicating drug resistance in cancer. Here, this work reviews the discovered resistance mechanisms for lung cancer chemotherapy, molecular targeted therapy, immunotherapy, and radiotherapy, and outlines novel strategies for the development of nanomedicine against drug resistance. This work focuses on engineering design, customized delivery, current challenges, and clinical translation of nanomedicine in the application of resistant lung cancer.

An Assessment of the Knowledge and Perceptions of Precision Medicine (PM) in the Rwandan Healthcare Setting

INTRODUCTION

Precision medicine (PM) or personalized medicine is an innovative approach that aims to tailor disease prevention and treatment to consider the differences in people's genes, environments, and lifestyles. Although many efforts have been made to accelerate the universal adoption of PM, several challenges need to be addressed in order to advance PM in Africa. Therefore, our study aimed to establish baseline data on the knowledge and perceptions of the implementation of PM in the Rwandan healthcare setting.

METHOD

A descriptive qualitative study was conducted in five hospitals offering diagnostics and oncology services to cancer patients in Rwanda. To understand the existing policies regarding PM implementation in the country, two additional institutions were surveyed: the Ministry of Health (MOH), which creates and sets policies for the overall vision of the health sector, and the Rwanda Biomedical Center (RBC), which coordinates the implementation of health sector policies in the country. The researchers conducted 32 key informant interviews and assessed the functionality of available PM equipment in the 5 selected health facilities. The data were thematically categorized and analyzed.

RESULTS

The study revealed that PM is perceived as a complex and expensive program by most health managers and health providers. The most cited challenges to implementing PM included the following: the lack of policies and guidelines; the lack of supportive infrastructures and limited suppliers of required equipment and laboratory consumables; financial constraints; cultural, behavioral, and religious beliefs; and limited trained, motivated, and specialized healthcare providers. Regarding access to health services for cancer treatment, patients with health insurance pay 10% of their medical costs, which is still too expensive for Rwandans.

CONCLUSION

The study participants highlighted the importance of PM to enhance healthcare delivery if the identified barriers are addressed. For instance, Rwandan health sector leadership might consider the creation of specialized oncology centers in all or some referral hospitals with all the necessary genomic equipment and trained staff to serve the needs of the country and implement a PM program.

Prioritization of genes associated with type 2 diabetes mellitus for functional studies

Existing therapies for type 2 diabetes mellitus (T2DM) show limited efficacy or have adverse effects. Numerous genetic variants associated with T2DM have been identified, but progress in translating these findings into potential drug targets has been limited. Here, we describe the tools and platforms available to identify effector genes from T2DM-associated coding and non-coding variants and prioritize them for functional studies. We discuss QSER1 and SLC12A8 as examples of genes that have been identified as possible T2DM candidate genes using these tools and platforms. We suggest further approaches, including the use of sequencing data with increased sample size and ethnic diversity, single-cell omics data for analyses, glycaemic trait associations to predict gene function and, potentially, human induced pluripotent stem cell 'village' cultures, to strengthen current gene functionalization workflows. Effective prioritization of T2DM-associated genes for experimental validation could expedite our understanding of the genetic mechanisms responsible for T2DM to facilitate the use of precision medicine in its treatment.

Differentiation of benign and malignant spinal schwannoma using guided attention inference networks on multi-source MRI: comparison with radiomics method and radiologist-based clinical assessment

BACKGROUND

Differentiating diagnosis between the benign schwannoma and the malignant counterparts merely by neuroimaging is not always clear and remains still confounding in many cases because of atypical imaging presentation encountered in clinic and the lack of specific diagnostic markers.

PURPOSE

To construct and validate a novel deep learning model based on multi-source magnetic resonance imaging (MRI) in automatically differentiating malignant spinal schwannoma from benign.

MATERIAL AND METHODS

We retrospectively reviewed MRI imaging data from 119 patients with the initial diagnosis of benign or malignant spinal schwannoma confirmed by postoperative pathology. A novel convolutional neural network (CNN)-based deep learning model named GAIN-CP (Guided Attention Inference Network with Clinical Priors) was constructed. An ablation study for the fivefold cross-validation and cross-source experiments were conducted to validate the novel model. The diagnosis performance among our GAIN-CP model, the conventional radiomics model, and the radiologist-based clinical assessment were compared using the area under the receiver operating characteristic curve (AUC) and balanced accuracy (BAC).

RESULTS

The AUC score of the proposed GAIN method is 0.83, which outperforms the radiomics method (0.65) and the evaluations from the radiologists (0.67). By incorporating both the image data and the clinical prior features, our GAIN-CP achieves an AUC score of 0.95. The GAIN-CP also achieves the best performance on fivefold cross-validation and cross-source experiments.

CONCLUSION

The novel GAIN-CP method can successfully classify malignant spinal schwannoma from benign cases using the provided multi-source MR images exhibiting good prospect in clinical diagnosis.

Multiplexing AAV Serotype-Specific Neutralizing Antibodies in Preclinical Animal Models and Humans

The accurate assessment of AAV-specific pre-existing humoral immunity due to natural viral infection is critical for the efficient use of clinical gene therapy. The method described in the present study applies equivalent infection conditions to each AAV serotype (AAV1, AAV2, AAV3, AAV5, AAV6, AAV7, AAV8, AAV9, AAV10, and AAVAnc80L65). In the current study, we validated the assay by assessing AAV-neutralizing antibody titers in a limited cohort of random human donors and well-established preclinical large animal models, including dogs and non-human primates (NHPs). We achieved a rapid and accurate evaluation of neutralizing titers for each individual subject that can be used for clinical enrollment based on specific AAV serotypes and individualized selection of the most suitable AAV serotype for each specific patient.

Genomic Signatures from Clinical Tumor Sequencing in Patients with Breast Cancer Having Germline BRCA1/2 Mutation

PURPOSE

BRCA1 and BRCA2 are among the most important genes involved in DNA repair via homologous recombination (HR). Germline BRCA1/2 (gBRCA1/2)-related cancers have specific characteristics and treatment options but conducting gBRCA1/2 testing and interpreting the genetic imprint are sometimes complicated. Here, we describe the concordance of gBRCA1/2 derived from a panel of clinical tumor tissues using next-generation sequencing (NGS) and genetic aspects of tumors harboring gBRCA1/2 pathogenic variants.

MATERIALS AND METHODS

Targeted sequencing was performed using available tumor tissue from patients who underwent gBRCA1/2 testing. Comparative genomic analysis was performed according to gBRCA1/2 pathogenicity.

RESULTS

A total of 321 patients who underwent gBRCA1/2 testing were screened, and 26 patients with gBRCA1/2 pathogenic (gBRCA1/2p) variants, eight patients with gBRCA1/2 variants of uncertain significance (VUS; gBRCA1/2v), and 43 patients with gBRCA1/2 wild-type (gBRCA1/2w) were included in analysis. Mutations in TP53 (49.4%) and PIK3CA (23.4%) were frequently detected in all samples. The number of single-nucleotide variants (SNVs) per tumor tissue was higher in the gBRCA1/2w group than that in the gBRCA1/2p group (14.81 vs. 18.86, p=0.278). Tumor mutation burden (TMB) was significantly higher in the gBRCA1/2w group than in the gBRCA1/2p group (10.21 vs. 13.47, p=0.017). Except for BRCA1/2, other HR-related genes were frequently mutated in patients with gBRCA1/2w.

CONCLUSION

We demonstrated high sensitivity of gBRCA1/2 in tumors analyzed by NGS using a panel of tumor tissues. TMB value and aberration of non-BRCA1/2 HR-related genes differed significantly according to gBRCA1/2 pathogenicity in patients with breast cancer.

Tackling heterogeneity in treatment-resistant breast cancer using a broad-spectrum therapeutic approach

Tumor heterogeneity can contribute to the development of therapeutic resistance in cancer, including advanced breast cancers. The object of the Halifax project was to identify new treatments that would address mechanisms of therapeutic resistance through tumor heterogeneity by uncovering combinations of therapeutics that could target the hallmarks of cancer rather than focusing on individual gene products. A taskforce of 180 cancer researchers, used molecular profiling to highlight key targets responsible for each of the hallmarks of cancer and then find existing therapeutic agents that could be used to reach those targets with limited toxicity. In many cases, natural health products and re-purposed pharmaceuticals were identified as potential agents. Hence, by combining the molecular profiling of tumors with therapeutics that target the hallmark features of cancer, the heterogeneity of advanced-stage breast cancers can be addressed.

Current and Future Immunotherapy-Based Treatments for Oesophageal Cancers

Oesophageal cancer is a disease that causes significant morbidity and mortality worldwide, and the prognosis of this condition has hardly improved in the past few years. Standard treatment includes a combination of chemotherapy, radiotherapy and surgery; however, only a proportion of patients go on to treatment intended to cure the disease due to the late presentation of this disease. New treatment options are of utmost importance, and immunotherapy is a new option that has the potential to transform the landscape of this disease. This treatment is developed to act on the changes within the immune system caused by cancer, including checkpoint inhibitors, which have recently shown great promise in the treatment of this disease and have recently been included in the adjuvant treatment of oesophageal cancer in many countries worldwide. This review will outline the mechanisms by which cancer evades the immune system in those diagnosed with oesophageal cancer and will summarize current and ongoing trials that focus on the use of our own immune system to combat disease.

Efficient privacy-preserving whole-genome variant queries

MOTIVATION

Diagnosis and treatment decisions on genomic data have become widespread as the cost of genome sequencing decreases gradually. In this context, disease-gene association studies are of great importance. However, genomic data are very sensitive when compared to other data types and contains information about individuals and their relatives. Many studies have shown that this information can be obtained from the query-response pairs on genomic databases. In this work, we propose a method that uses secure multi-party computation to query genomic databases in a privacy-protected manner. The proposed solution privately outsources genomic data from arbitrarily many sources to the two non-colluding proxies and allows genomic databases to be safely stored in semi-honest cloud environments. It provides data privacy, query privacy and output privacy by using XOR-based sharing and unlike previous solutions, it allows queries to run efficiently on hundreds of thousands of genomic data.

RESULTS

We measure the performance of our solution with parameters similar to real-world applications. It is possible to query a genomic database with 3 000 000 variants with five genomic query predicates under 400 ms. Querying 1 048 576 genomes, each containing 1 000 000 variants, for the presence of five different query variants can be achieved approximately in 6 min with a small amount of dedicated hardware and connectivity. These execution times are in the right range to enable real-world applications in medical research and healthcare. Unlike previous studies, it is possible to query multiple databases with response times fast enough for practical application. To the best of our knowledge, this is the first solution that provides this performance for querying large-scale genomic data.

AVAILABILITY AND IMPLEMENTATION

https://gitlab.com/DIFUTURE/privacy-preserving-variant-queries.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Recent Advances of Manganese-Based Hybrid Nanomaterials for Cancer Precision Medicine

Cancer precision medicine (CPM) could tailor the best treatment for individual cancer patients, while imaging techniques play important roles in its application. With the characteristics of noninvasion, nonionized, radiation-free, multidimensional imaging function, and real-time monitoring, magnetic resonance imaging (MRI) is an effective way for early tumor detection, and it has become a tower of strength in CPM imaging techniques. Due to linkage with nephrogenic systemic fibrosis (NSF), gadolinium (Gd)-based contrast agent (CA), which was long used in MRI, has been restricted by the Food and Drug Administration (FDA). In this review, we would like to introduce the manganese (Mn)-based CAs that could significantly increase the safety of MRI CAs by realizing more superior performance and functions simultaneously in the diagnosis and treatment of tumors. Also, recent advances in Mn-based hybrid nanomaterials for CPM are summarized and discussed.

Copy number alteration of the interferon gene cluster in cancer: Individual patient data meta-analysis prospects to personalized immunotherapy

Interferon (IFN) therapy has been the standard of care for a variety of cancers for decades due to the pleiotropic actions of IFNs against malignancies. However, little is known about the role of copy number alteration (CNA) of the IFN gene cluster, located at the 9p21.3, in cancer. This large individual patient data meta-analysis using 9937 patients obtained from cBioportal indicates that CNA of the IFN gene cluster is prevalent among 24 cancer types. Two statistical approaches showed that notably deletion of this cluster is significantly associated with increased mortality in many cancer types particularly uterus (OR = 2.71), kidney (OR = 2.26), and brain (OR = 2.08) cancers. The Cancer Genome Atlas PanCancer analysis also showed that CNA of the IFN gene cluster is significantly associated with decreased overall survival. For instance, the overall survival of patients with brain glioma reduced from 93m (diploidy) to 24m (with the CNA of the IFN gene). In conclusion, the CNA of the IFN gene cluster is associated with increased mortality and decreased overall survival in cancer. Thus, in the prospect of immunotherapy, CNA of IFN gene may be a useful biomarker to predict the prognosis of patients and also as a potential companion diagnostic test to prescribe IFN α/β therapy.

Cancer Stem Cell Assay for the Treatment of Platinum-Resistant Recurrent Ovarian Cancer

BACKGROUND

Disease recurrence and progression of ovarian cancer is a common event, which is accompanied by the development of platinum-resistant or refractory disease. The presence of chemo-resistant Cancer Stem Cells (CSCs) contribute to tumor propagation, maintenance, and treatment resistance of this difficult to treat disease. We have developed ChemoID, a cytotoxic synergy assay against CSCs that identifies the most effective chemotherapy treatment from a panel of FDA-approved chemotherapies using fresh cancer biopsies.

PATIENTS AND METHODS

Ascites or interventional radiology biopsies were collected under physician order from 78 consecutive patients affected by 3rd relapsed ovarian cancer. Test results from the assay were used when possible to treat patients with the highest cell kill drugs, taking into consideration their health status and using dose reductions, if needed. A chart analysis and review of CT and PET scans were performed to determine patients' outcomes for tumor response, Progression-Free Survival (PFS), and Overall Survival (OS).

RESULTS

We observed that recurrent ovarian cancer patients treated with high-cell kill chemotherapy agents guided by the CSCs drug response assay had an improvement in their median PFS and OS when compared to historical median PFS and OS and/or when compared to patients who could not receive high cell kill chemotherapies (PFS low cell kill 3.5 months vs. high cell kill 12.0 months; OS low cell kill 6.0 months vs. high cell kill 15.0 months).

CONCLUSION

This data indicates that the drug cytotoxicity assay aimed at targeting CSCs may be a useful tool for optimizing treatment selection when first-line therapy fails, and when there are multiple clinically-acceptable and -equivalent treatments available.

TIGIT Can Exert Immunosuppressive Effects on CD8+ T Cells by the CD155/TIGIT Signaling Pathway for Hepatocellular Carcinoma In Vitro

Supplemental Digital Content is available in the text.

The efficacy of adoptive cellular immunotherapy against cancer cells is limited due to the presence of immunosuppressive cells within the solid tumor microenvironment. The upregulation of certain coinhibitory receptors may lead to exhaustion of the immune effector cells. T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) is an immune inhibitory receptor expressed by regulatory T cells and activated T cells and natural killer cells. The aim of this study was to determine the immunosuppressive effects of CD155/TIGIT signaling on CD8⁺ T cells of adoptive cellular immunotherapy in hepatocellular carcinoma (HCC). Our studies found that CD155 was overexpressed in HCC, and CD155^hi HCC cells upregulated TIGIT on CD8⁺ T cells, which decreased the secretion of interferon-γ, tumor necrosis factor-α, and interleukin-17A and increased that of interleukin-10 from the effector cells. However, TIGIT blockade or CD155-knockdown reversed the inhibitory effect of HCC cells on CD8⁺ T-cell effector function. These results indicate that TIGIT can exert an immunosuppressive effect on CD8 T cells by modulating cytokine production through CD155, and is a promising target to optimize adoptive cellular immunotherapy against HCC.

Molecular Imaging, How Close to Clinical Precision Medicine in Lung, Brain, Prostate and Breast Cancers

Precision medicine is playing a pivotal role in strategies of cancer therapy. Unlike conventional one-size-fits-all chemotherapy or radiotherapy modalities, precision medicine could customize an individual treatment plan for cancer patients to acquire superior efficacy, while minimizing side effects. Precision medicine in cancer therapy relies on precise and timely tumor biological information. Traditional tissue biopsies, however, are often inadequate in meeting this requirement due to cancer heterogeneity, poor tolerance, and invasiveness. Molecular imaging could detect tumor biology characterization in a noninvasive and visual manner, and provide information about therapeutic targets, treatment response, and pharmacodynamic evaluation. This summates to significant value in guiding cancer precision medicine in aspects of patient screening, treatment monitoring, and estimating prognoses. Although growing clinical evidences support the further application of molecular imaging in precision medicine of cancer, some challenges remain. In this review, we briefly summarize and discuss representative clinical trials of molecular imaging in improving precision medicine of cancer patients, aiming to provide useful references for facilitating further clinical translation of molecular imaging to precision medicine of cancers.

Breast cancer immunotherapy: Current and novel approaches

The crucial role of the immune system in the progression/regression of breast cancer (BC) should always be taken into account. Various immunotherapy approaches have been investigated for BC, including tumor-targeting antibodies (bispecific antibodies), adoptive T cell therapy, vaccines, and immune checkpoint blockade such as anti-PD-1. In addition, a combination of conventional chemotherapy and immunotherapy approaches contributes to improving patients' overall survival rates. Although encouraging outcomes have been reported in most clinical trials of immunotherapy, some obstacles should still be resolved in this regard. Recently, personalized immunotherapy has been proposed as a potential complementary medicine with immunotherapy and chemotherapy for overcoming BC. Accordingly, this review discusses the brief association of these methods and future directions in BC immunotherapy.

Toward a fine-scale population health monitoring system

Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens and environmental factors impacting specific sub-populations. Here, we propose a framework for repurposing data from electronic health records (EHRs) in concert with genomic data to explore the demographic ties that can impact disease burdens. Using data from a diverse biobank in New York City, we identified 17 communities sharing recent genetic ancestry. We observed 1,177 health outcomes that were statistically associated with a specific group and demonstrated significant differences in the segregation of genetic variants contributing to Mendelian diseases. We also demonstrated that fine-scale population structure can impact the prediction of complex disease risk within groups. This work reinforces the utility of linking genomic data to EHRs and provides a framework toward fine-scale monitoring of population health.

Synthesis, Characterization and In Vitro Evaluation of Novel 5-Ene-thiazolo[3,2-b][1,2,4]triazole-6(5H)-ones as Possible Anticancer Agents

The present paper is devoted to the search for drug-like molecules with anticancer properties using the thiazolo[3,2-b][1,2,4]triazole-6-one scaffold. A series of 24 novel thiazolo-[3,2-b][1,2,4]triazole-6-ones with 5-aryl(heteryl)idene- and 5-aminomethylidene-moieties has been synthesized employing three-component and three-stage synthetic protocols. A mixture of Z/E-isomers was obtained in solution for the synthesized 5-aminomethylidene-thiazolo[3,2-b]-[1,2,4]triazole-6-ones. The compounds have been studied for their antitumor activity in the NCI 60 lines screen. Some compounds present excellent anticancer properties at 10 μM. Derivatives 2h and 2i were the most active against cancer cell lines without causing toxicity to normal somatic (HEK293) cells. A preliminary SAR study had been performed for the synthesized compounds.

Identification of synthetic chemosensitivity genes paired with BRAF for BRAF/MAPK inhibitors

Molecular-targeted approaches are important for personalised cancer treatment, which requires knowledge regarding drug target specificity. Here, we used the synthetic lethality concept to identify candidate gene pairs with synergistic effects on drug responses. A synergistic chemo-sensitivity response was identified if a drug had a significantly lower half-maximal inhibitory concentration (IC₅₀) in cell lines with a pair of mutated genes compared with those in other cell lines (wild-type or one mutated gene). Among significantly damaging mutations in the Genomics of Drug Sensitivity in Cancer database, we found 580 candidate synergistic chemo-sensitivity interaction sets for 456 genes and 54 commercial drugs. Clustering analyses according to drug/gene and drug/tissue interactions showed that BRAF/MAPK inhibitors clustered together; 11 partner genes for BRAF were identified. The combined effects of these partners on IC₅₀ values were significant for both drug-specific and drug-combined comparisons. Survival analysis using The Cancer Genome Atlas data showed that patients who had mutated gene pairs in synergistic interaction sets had longer overall survival compared with that in patients with other mutation profiles. Overall, this analysis demonstrated that synergistic drug-responsive gene pairs could be successfully used as predictive markers of drug sensitivity and patient survival, offering new targets for personalised medicine.

The efficacy of chemotherapeutic drug combinations may be predicted by concordance of gene response to the single agents

Determining the expression of genes in response to different classes of chemotherapeutic drugs may allow for a better understanding as to which may be used effectively in combination. In the present study, the human colorectal cancer cell line HCT116 was cultured with equi-active concentrations of a series of anti-cancer agents. Gene expression profiles were then measured by whole-genome microarray. Although each drug induced a unique signature of gene expression in tumour cells, there were marked similarities between certain drugs, even in those from different classes. For example, the antimalarial agent artesunate and the platinum-containing alkylating agent, oxaliplatin, produced a very similar mRNA expression pattern in HCT116 cells with ~14,000 genes being affected by the two drugs in the same way. Furthermore, the overall correlation of gene responses between two agents could predict whether their use in combination would lead to a greater or lesser effect on cell number, determined experimentally, than predicted by single agent experiments. The results indicated that even when working through different mechanisms, combining drugs that initiate a similar transcriptional response may constitute the best option for determining drug-combination strategies for the treatment of cancer.

CaliPro: A Calibration Protocol That Utilizes Parameter Density Estimation to Explore Parameter Space and Calibrate Complex Biological Models

Introduction

Mathematical and computational modeling have a long history of uncovering mechanisms and making predictions for biological systems. However, to create a model that can provide relevant quantitative predictions, models must first be calibrated by recapitulating existing biological datasets from that system. Current calibration approaches may not be appropriate for complex biological models because: 1) many attempt to recapitulate only a single aspect of the experimental data (such as a median trend) or 2) Bayesian techniques require specification of parameter priors and likelihoods to experimental data that cannot always be confidently assigned. A new calibration protocol is needed to calibrate complex models when current approaches fall short.

Methods

Herein, we develop CaliPro, an iterative, model-agnostic calibration protocol that utilizes parameter density estimation to refine parameter space and calibrate to temporal biological datasets. An important aspect of CaliPro is the user-defined pass set definition, which specifies how the model might successfully recapitulate experimental data. We define the appropriate settings to use CaliPro.

Results

We illustrate the usefulness of CaliPro through four examples including predator-prey, infectious disease transmission, and immune response models. We show that CaliPro works well for both deterministic, continuous model structures as well as stochastic, discrete models and illustrate that CaliPro can work across diverse calibration goals.

Conclusions

We present CaliPro, a new method for calibrating complex biological models to a range of experimental outcomes. In addition to expediting calibration, CaliPro may be useful in already calibrated parameter spaces to target and isolate specific model behavior for further analysis.

Transcriptional profiling reveals a subset of human breast tumors that retain wt TP53 but display mutant p53-associated features

TP53 gene mutations are very common in human cancer. While such mutations abrogate the tumor suppressive activities of the wild-type (wt) p53 protein, some of them also endow the mutant (mut) protein with oncogenic gain of function (GOF), facilitating cancer progression. Yet, p53 may acquire altered functionality even without being mutated; in particular, experiments with cultured cells revealed that wtp53 can be rewired to adopt mut-like features in response to growth factors or cancer-mimicking genetic manipulations. To assess whether such rewiring also occurs in human tumors, we interrogated gene expression profiles and pathway deregulation patterns in the METABRIC breast cancer (BC) dataset as a function of TP53 gene mutation status. Harnessing the power of machine learning, we optimized a gene expression classifier for ER+Her2- patients that distinguishes tumors carrying TP53 mutations from those retaining wt TP53. Interestingly, a small subset of wt TP53 tumors displayed gene expression and pathway deregulation patterns markedly similar to those of TP53-mutated tumors. Moreover, similar to TP53-mutated tumors, these 'pseudomutant' cases displayed a signature for enhanced proliferation and had worse prognosis than typical wtp53 tumors. Notably, these tumors revealed upregulation of genes which, in BC cell lines, were reported to be positively regulated by p53 GOF mutants. Thus, such tumors may benefit from mut p53-associated activities without having to accrue TP53 mutations.

Bi- and Tri-Specific T Cell Engager-Armed Oncolytic Viruses: Next-Generation Cancer Immunotherapy

Oncolytic viruses (OVs) are potent anti-cancer biologics with a bright future, having substantial evidence of efficacy in patients with cancer. Bi- and tri-specific antibodies targeting tumor antigens and capable of activating T cell receptor signaling have also shown great promise in cancer immunotherapy. In a cutting-edge strategy, investigators have incorporated the two independent anti-cancer modalities, transforming them into bi- or tri-specific T cell engager (BiTE or TriTE)-armed OVs for targeted immunotherapy. Since 2014, multiple research teams have studied this combinatorial strategy, and it showed substantial efficacy in various tumor models. Here, we first provide a brief overview of the current status of oncolytic virotherapy and the use of multi-specific antibodies for cancer immunotherapy. We then summarize progress on BiTE and TriTE antibodies as a novel class of cancer therapeutics in preclinical and clinical studies, followed by a discussion of BiTE- or TriTE-armed OVs for cancer therapy in translational models. In addition, T cell receptor mimics (TCRm) have been developed into BiTEs and are expected to greatly expand the application of BiTEs and BiTE-armed OVs for the effective targeting of intracellular tumor antigens. Future applications of such innovative combination strategies are emerging as precision cancer immunotherapies.

Feasibility study of in vitro drug sensitivity assay of advanced non-small cell lung adenocarcinomas

Background Despite improved screening techniques, diagnosis of lung cancer is often late and its prognosis is poor. In the present study, in vitro chemosensitivity of solid tumours and pleural effusions of lung adenocarcinomas were analysed and compared with clinical drug response.Methods Tumour cells were isolated from resected solid tumours or pleural effusions, and cryopreserved. Three-dimensional (3D) tissue aggregate cultures were set up when the oncoteam reached therapy decision for individual patients. The aggregates were then treated with the selected drug or drug combination and in vitro chemosensitivity was tested individually measuring ATP levels. The clinical response to therapy was assessed by standard clinical evaluation over an 18 months period.Results Based on the data, the in vitro chemosensitivity test results correlate well with clinical treatment response.Conclusions Such tests if implemented into the clinical decision making process might allow the selection of an even more individualised chemotherapy protocol which could lead to better therapy response.

Cisplatin treatment induced interleukin 6 and 8 production alters lung adenocarcinoma cell migration in an oncogenic mutation dependent manner

BACKGROUND

The predominant metastatic site of lung cancer (LC) is the brain. Although outdated, conventional cisplatin treatment is still the main therapeutic approach for patients with advanced non-small cell lung cancer (NSCLC), since targeted therapy that offers better tumor control is not always possible. In the present study brain metastasis associated cytokine expression was investigated in primary NSCLC adenocarcinoma (AC) tissues with known oncogenic mutations in the presence or absence of platina based and tyrosine kinase inhibitor (TKI) drugs.

METHODS

Primary lung tumor samples were isolated, DNA was sequenced and then the samples were grouped based on mutation. Experiments were also performed using KRAS mutant A549 and EGFR mutant PC-9 cells. Drug response was analyzed in three dimensional (3D) tissue cultures. We assessed drug response and IL-6 and IL-8 cytokine expression in relation to cellular invasion using ATP dependent cell viability, qRT-PCR analysis, cytokine bead array, and migration assay.

RESULTS

In 3D co-cultures, primary NSCLC derived cells harboring EGFR mutation responded better to erlotinib treatment than KRAS mutant or KRAS/EGFR wild type (WT) cancer cells. In contrast, under the same culture conditions KRAS/EGFR WT or KRAS mutant cancer cells are more sensitive to cisplatin than EGFR mutant cells. Drug response and pro-inflammatory cytokine production varied depending on the driver mutations. Cisplatin but not erlotinib increased both IL-6 and IL-8 secretion and only IL-6 increased cellular migration and proliferation.

CONCLUSION

In vitro assays are available to determine the response to planned therapeutic approach of lung cancer subtypes. The sequence of administration of therapeutic drugs determines cytokine production and therefore therapeutic response.

Future avenues for Alzheimer's disease detection and therapy: liquid biopsy, intracellular signaling modulation, systems pharmacology drug discovery

When Alzheimer's disease (AD) disease-modifying therapies will be available, global healthcare systems will be challenged by a large-scale demand for clinical and biological screening. Validation and qualification of globally accessible, minimally-invasive, and time-, cost-saving blood-based biomarkers need to be advanced. Novel pathophysiological mechanisms (and related candidate biomarkers) - including neuroinflammation pathways (TREM2 and YKL-40), axonal degeneration (neurofilament light chain protein), synaptic dysfunction (neurogranin, synaptotagmin, α-synuclein, and SNAP-25) - may be integrated into an expanding pathophysiological and biomarker matrix and, ultimately, integrated into a comprehensive blood-based liquid biopsy, aligned with the evolving ATN + classification system and the precision medicine paradigm. Liquid biopsy-based diagnostic and therapeutic algorithms are increasingly employed in Oncology disease-modifying therapies and medical practice, showing an enormous potential for AD and other brain diseases as well. For AD and other neurodegenerative diseases, newly identified aberrant molecular pathways have been identified as suitable therapeutic targets and are currently investigated by academia/industry-led R&D programs, including the nerve-growth factor pathway in basal forebrain cholinergic neurons, the sigma1 receptor, and the GTPases of the Rho family. Evidence for a clinical long-term effect on cognitive function and brain health span of cholinergic compounds, drug candidates for repositioning programs, and non-pharmacological multidomain interventions (nutrition, cognitive training, and physical activity) is developing as well. Ultimately, novel pharmacological paradigms, such as quantitative systems pharmacology-based integrative/explorative approaches, are gaining momentum to optimize drug discovery and accomplish effective pathway-based strategies for precision medicine. This article is part of the special issue on 'The Quest for Disease-Modifying Therapies for Neurodegenerative Disorders'.

Update on gastric cancer treatments and gene therapies

Gastric cancer is an active topic of clinical and basic research due to high morbidity and mortality. To date, gastrectomy and chemotherapy are the only therapeutic options for gastric cancer patients, but drug resistance, either acquired or primary, is the main cause for treatment failure. Differences in development and response to cancer treatments have been observed among ethnically diverse GC patient populations. In spite of major incidence, GC Asian patients have a significantly better prognosis and response to treatments than Caucasian ones due to genetic discordances between the two populations. Gene therapy could be an alternative strategy to overcome such issues and especially CRISPR/Cas9 represents one of the most intriguing gene-editing system. Thus, in this review article, we want to provide an update on the currently used therapies for the treatment of advanced GC. Graphical abstract.

Nanomedicine and Immunotherapy: A Step Further towards Precision Medicine for Glioblastoma

Owing to the advancement of technology combined with our deeper knowledge of human nature and diseases, we are able to move towards precision medicine, where patients are treated at the individual level in concordance with their genetic profiles. Lately, the integration of nanoparticles in biotechnology and their applications in medicine has allowed us to diagnose and treat disease better and more precisely. As a model disease, we used a grade IV malignant brain tumor (glioblastoma). Significant improvements in diagnosis were achieved with the application of fluorescent nanoparticles for intraoperative magnetic resonance imaging (MRI), allowing for improved tumor cell visibility and increasing the extent of the surgical resection, leading to better patient response. Fluorescent probes can be engineered to be activated through different molecular pathways, which will open the path to individualized glioblastoma diagnosis, monitoring, and treatment. Nanoparticles are also extensively studied as nanovehicles for targeted delivery and more controlled medication release, and some nanomedicines are already in early phases of clinical trials. Moreover, sampling biological fluids will give new insights into glioblastoma pathogenesis due to the presence of extracellular vesicles, circulating tumor cells, and circulating tumor DNA. As current glioblastoma therapy does not provide good quality of life for patients, other approaches such as immunotherapy are explored. To conclude, we reason that development of personalized therapies based on a patient's genetic signature combined with pharmacogenomics and immunogenomic information will significantly change the outcome of glioblastoma patients.

The Present and Future of Novel Protein Degradation Technology

Proteolysis targeting chimeras (PROTACs), as a novel therapeutic modality, play a vital role in drug discovery. Each PROTAC contains three key parts; a protein-of-interest (POI) ligand, a E3 ligase ligand, and a linker. These bifunctional molecules could mediate the degradation of POIs by hijacking the activity of E3 ubiquitin ligases for POI ubiquitination and subsequent degradation via the ubiquitin proteasome system (UPS). With several advantages over other therapeutic strategies, PROTACs have set off a new upsurge of drug discovery in recent years. ENDTAC, as the development of PROTACs technology, is now receiving more attention. In this review, we aim to summarize the rapid progress from 2018 to 2019 in protein degradation and analyze the challenges and future direction that need to be addressed in order to efficiently develop potent protein degradation technology.

Patient Dossier: Healthcare queries over distributed resources

As with many other aspects of the modern world, in healthcare, the explosion of data and resources opens new opportunities for the development of added-value services. Still, a number of specific conditions on this domain greatly hinders these developments, including ethical and legal issues, fragmentation of the relevant data in different locations, and a level of (meta)data complexity that requires great expertise across technical, clinical, and biological domains. We propose the Patient Dossier paradigm as a way to organize new innovative healthcare services that sorts the current limitations. The Patient Dossier conceptual framework identifies the different issues and suggests how they can be tackled in a safe, efficient, and responsible way while opening options for independent development for different players in the healthcare sector. An initial implementation of the Patient Dossier concepts in the Rbbt framework is available as open-source at https://github.com/mikisvaz and https://github.com/Rbbt-Workflows.

Investigating Novel Genes Potentially Involved in Endometrial Adenocarcinoma using Next-Generation Sequencing and Bioinformatic Approaches

Endometrial cancer is one of the most common cancers in women worldwide, affecting more than 300,000 women annually. Dysregulated gene expression, especially those mediated by microRNAs, play important role in the development and progression of cancer. This study aimed to investigate differentially expressed genes in endometrial adenocarcinoma using next generation sequencing (NGS) and bioinformatics. The gene expression profiles and microRNA profiles of endometrial adenocarcinoma (cancer part) and normal endometrial tissue (non-cancer part) were assessed with NGS. We identified 56 significantly dysregulated genes, including 47 upregulated and 9 downregulated genes, in endometrial adenocarcinoma. Most of these genes were associated with defense response, response to stimulus, and immune system process, and further pathway analysis showed that human papillomavirus infection was the most significant pathway in endometrial adenocarcinoma. In addition, these genes were also associated with decreased cell death and survival as well as increased cellular movement. The analyses using Human Protein Atlas, identified 6 genes (PEG10, CLDN1, ASS1, WNT7A, GLDC, and RSAD2) significantly associated with poorer prognosis and 3 genes (SFN, PIGR, and CDKN1A) significantly associated with better prognosis. Combining with the data of microRNA profiles using microRNA target predicting tools, two significantly dysregulated microRNA-mediated gene expression changes in endometrial adenocarcinoma were identified: downregulated hsa-miR-127-5p with upregulated CSTB and upregulated hsa-miR-218-5p with downregulated HPGD. These findings may contribute important new insights into possible novel diagnostic or therapeutic strategies for endometrial adenocarcinoma.

Polymeric Reactor for the Synthesis of Superparamagnetic-Thermal Treatment of Breast Cancer

Engineered superparamagnetic iron oxide nanoparticles (SPIONs) have been studied extensively for their localized homogeneous heat generation in breast cancer therapy. However, challenges such as aggregation and inability to produce sub-10 nm SPIONs limit their potential in magnetothermal ablation. We report a facile, efficient, and robust in situ method for the synthesis of SPIONs within a poly(ethylene glycol) (PEG) reactor adsorbed onto reduced graphene oxide nanosheets (rGO) via the microwave hydrothermal route. This promising modality yields crystalline, stable, biocompatible, and superparamagnetic PEGylated SPION-rGO nanocomposites (NCs) with uniform dispersibility. Our findings show that rGO acts as a breeding ground for the spatially distributed nanosites around which the ferrihydrite seeds accumulate to ultimately transform into immobilized SPIONs. PEG, in parallel, acts as a critical confining agent physically trapping the accumulated seeds to prevent their aggregation and create multiple domains on rGO for the synthesis of quantum-sized SPIONs (9 ± 1 nm in diameter). This dual functionality (rGO and PEG) exhibits a pronounced effect on reducing both the aggregation and the sizes of fabricated SPIONs as confirmed by the scanning transmission electron microscopy images, dynamic light scattering analyses, and the specific absorption rates (SARs). Reduced aggregation lowered the toxicity of NCs, where PEGylated SPION-rGO NCs are more biocompatible than PEGylated SPIONs, showing no significant induction of cell apoptosis, mitochondrial membrane injury, or oxidative stress. Significantly less lactate dehydrogenase release and hence less necrosis are observed after 48 h exposure to high doses of PEGylated SPION-rGO NCs compared with PEGylated SPIONs. NCs induce local heat generation with a SAR value of 1760 ± 97 W/g, reaching up to 43 ± 0.3 °C and causing significant MCF-7 breast tumor cell ablation of about 78 ± 10% upon applying an external magnetic field. Collectively, rGO and PEG functionalities have a synergistic effect on improving the synthesis, stability, biocompatibility, and magnetothermal properties of SPIONs.

Mutational signatures and mutable motifs in cancer genomes

Cancer is a genetic disorder, meaning that a plethora of different mutations, whether somatic or germ line, underlie the etiology of the 'Emperor of Maladies'. Point mutations, chromosomal rearrangements and copy number changes, whether they have occurred spontaneously in predisposed individuals or have been induced by intrinsic or extrinsic (environmental) mutagens, lead to the activation of oncogenes and inactivation of tumor suppressor genes, thereby promoting malignancy. This scenario has now been recognized and experimentally confirmed in a wide range of different contexts. Over the past decade, a surge in available sequencing technologies has allowed the sequencing of whole genomes from liquid malignancies and solid tumors belonging to different types and stages of cancer, giving birth to the new field of cancer genomics. One of the most striking discoveries has been that cancer genomes are highly enriched with mutations of specific kinds. It has been suggested that these mutations can be classified into 'families' based on their mutational signatures. A mutational signature may be regarded as a type of base substitution (e.g. C:G to T:A) within a particular context of neighboring nucleotide sequence (the bases upstream and/or downstream of the mutation). These mutational signatures, supplemented by mutable motifs (a wider mutational context), promise to help us to understand the nature of the mutational processes that operate during tumor evolution because they represent the footprints of interactions between DNA, mutagens and the enzymes of the repair/replication/modification pathways.

Application of immune repertoire sequencing in cancer immunotherapy

With the prominent breakthrough in the field of tumor immunology, diverse cancer immunotherapies have attracted great attention in the last decade. The immune checkpoint inhibitors, adoptive cell therapies, and therapeutic cancer vaccines have already achieved impressive clinical success. However, the fact that only a small subset of patients with specific tumor types can benefit from these treatments limits the application of cancer immunotherapy. To seek out the molecular mechanisms behind this challenge and to select cancer precision medicine for different individuals, researchers apply the immune repertoire sequencing (IRS) to evaluate genetic responses of each patient to current immunotherapies. This review summarizes the technical advances and recent applications of IRS in cancer immunotherapy, indicates the limitations of this technique, and predicts future perspectives both in basic studies and clinical trials.

Blocking the PD-1/PD-L1 axis in dendritic cell-stimulated Cytokine-Induced Killer Cells with pembrolizumab enhances their therapeutic effects against hepatocellular carcinoma

Immune checkpoint therapies for cancer, like the anti-programmed cell death 1 (PD-1) agent pembrolizumab, have gained considerable attention. However, the use of immune checkpoint inhibitors in the context of adoptive immunotherapy is poorly characterized. We investigated the therapeutic efficacy of dendritic cell-stimulated CIK (DC-CIK) cells pretreated with pembrolizumab against hepatocellular carcinoma (HCC) in cytotoxicity assay in vitro and in a nude mouse xenograft model. We used time-lapse imaging to investigate tumor killing. We also performed a survival analysis based on lymphocyte subpopulation-specific mRNA signatures using The Cancer Genome Atlas (TCGA) HCC cohort (n=371 patients). The results indicated that PD-1 inhibition increased the anti-tumor effects of DC-CIK cells over those of DC-CIK cells alone, resulting in a survival benefit importantly. Time-lapse imaging revealed that DC-CIK cells appeared to be more effective and aggressive after anti-PD-1 treatment than after culture in control conditions. The PD-1 inhibitor also induced more effective immune cell infiltration of the tumor. Our analysis of the TCGA HCC cohort confirmed that a genetic signature consistent with a high degree of intratumoral CD8+ T cell infiltration is associated with good prognosis. These results suggest that blockade of the PD-1/PD-L1 axis in DC-CIK cells with a PD-1 inhibitor prior to infusion is a promising therapeutic strategy against HCC.

Cancer Immunotherapies and Humanized Mouse Drug Testing Platforms

Cancer immunotherapy is a type of treatment that restores and stimulates human immune system to inhibit cancer growth or eradicate cancer. It serves as one of the latest systemic therapies, which has been approved to treat different types of cancer in patients. Nevertheless, the clinical response rate is unsatisfactory and the response observed is mostly a partial response in patients. Despite the continuous improvement and identification of novel cancer immunotherapy, there is a pressing need to establish a robust platform to evaluate the efficacy and safety of pre-clinical drugs, simulate the interaction between patients’ tumor and immune system, and predict patients’ responses to the treatment. In this review, we summarize the pros and cons of existing immuno-oncology assay platforms, especially the humanized mouse models for the screening of cancer immunotherapy drugs. In addition, various emerging trends and progress of utilizing humanized mouse models as the screening tool are discussed. Of note, humanized mouse models can also be used for further development of personalized precision medicines to treat cancer. Collectively, these highlight the significance of humanized mouse models as the important platform for the screening of next generation cancer immunotherapy in vivo.

Biomarker-Drug and Liquid Biopsy Co-development for Disease Staging and Targeted Therapy: Cornerstones for Alzheimer's Precision Medicine and Pharmacology

Systems biology studies have demonstrated that different (epi)genetic and pathophysiological alterations may be mapped onto a single tumor’s clinical phenotype thereby revealing commonalities shared by cancers with divergent phenotypes. The success of this approach in cancer based on analyses of traditional and emerging body fluid-based biomarkers has given rise to the concept of liquid biopsy enabling a non-invasive and widely accessible precision medicine approach and a significant paradigm shift in the management of cancer. Serial liquid biopsies offer clues about the evolution of cancer in individual patients across disease stages enabling the application of individualized genetically and biologically guided therapies. Moreover, liquid biopsy is contributing to the transformation of drug research and development strategies as well as supporting clinical practice allowing identification of subsets of patients who may enter pathway-based targeted therapies not dictated by clinical phenotypes alone. A similar liquid biopsy concept is emerging for Alzheimer’s disease, in which blood-based biomarkers adaptable to each patient and stage of disease, may be used for positive and negative patient selection to facilitate establishment of high-value drug targets and counter-measures for drug resistance. Going beyond the “one marker, one drug” model, integrated applications of genomics, transcriptomics, proteomics, receptor expression and receptor cell biology and conformational status assessments during biomarker-drug co-development may lead to a new successful era for Alzheimer’s disease therapeutics. We argue that the time is now for implementing a liquid biopsy-guided strategy for the development of drugs that precisely target Alzheimer’s disease pathophysiology in individual patients.

Personalized Medicine and the Power of Electronic Health Records

Personalized medicine has largely been enabled by the integration of genomic and other data with electronic health records (EHRs) in the United States and elsewhere. Increased EHR adoption across various clinical settings and the establishment of EHR-linked population-based biobanks provide unprecedented opportunities for the types of translational and implementation research that drive personalized medicine. We review advances in the digitization of health information and the proliferation of genomic research in health systems and provide insights into emerging paths for the widespread implementation of personalized medicine.

Cancer prevention and screening: the next step in the era of precision medicine

A primary mode of cancer prevention and early detection in the United States is the widespread practice of screening. Although many strategies for early detection and prevention are available, adverse outcomes, such as overdiagnosis and overtreatment, are prevalent among those utilizing these approaches. Broad use of mammography and prostate cancer screening are key examples illustrating the potential harms stemming from the detection of indolent lesions and the subsequent overtreatment. Furthermore, there are several cancers for which prevention strategies do not currently exist. Clinical and experimental evidence have expanded our understanding of cancer initiation and progression, and have instructed the development of improved, precise modes of cancer prevention and early detection. Recent cancer prevention and early detection innovations have begun moving towards the integration of molecular knowledge and risk stratification profiles to allow for a more accurate representation of at-risk individuals. The future of cancer prevention and early detection efforts should emphasize the incorporation of precision cancer prevention integration where screening and cancer prevention regimens can be matched to one's risk of cancer due to known genomic and environmental factors.

Liquid Biopsy Promotes Non-Small Cell Lung Cancer Precision Therapy

The range of potential applications of liquid biopsies for non-small cell lung cancer management is expanded by the use of circulating tumor deoxyribonucleic acid and circulating tumor cells. Principal studies have demonstrated the predictive accuracy of droplet digital polymerase chain reaction detection, next-generation sequencing, and circulating tumor cells detection in patients with non-small cell lung cancer. The translational potential of these liquid biopsy technologies promotes the improvement of sensitivity and specificity in genomic and molecular methods. Here, we highlight the realities and challenges associated with the use of liquid biopsies for the detection of non-small cell lung cancer in patients. However, liquid biopsy technologies including circulating tumor cells detection, droplet digital polymerase chain reaction detection, and next-generation sequencing detection for precision therapy in non-small cell lung cancer will show substantive clinical applications in the future.

The Impact of Pharmacogenomics in Personalized Medicine

Recent advances in Pharmacogenomics have made it possible to understand the reasons behind the different response of a drug. Discovery of genetic variants and its association with the varying response of drug provide the basis for recommending a drug and its dose to an individual patient. Genetic makeup-based prescription, design, and implementation of therapy not only improve the outcome of treatments but also reduce the risk of toxicity and other adverse effects. A better understanding of individual variations and their effect on drug response, metabolism excretion, and toxicity will replace the trial-and-error approach of treatment. Evidence of the clinical utility of pharmacogenetics testing is only available for a few medications, and FDA labels only require pharmacogenetics testing for a small number of drugs. Although there is a great promise, there are not many examples where Pharmacogenomics impacts clinical utility. Some genetic variants related to different diseases have been reported, and many have not been studied yet. The information related to the outcome of treatment with a particular drug and a genetic variant can be used to release a warning/label for the use of that drug. There are many limitations in the way of implementing the goal of personalized medicine. Future advances in the field of genomics, diagnosis approaches, data analysis, clinical decision-making, and sustainable business model for personalization of therapy can speed up the individualization of therapy based on genetic makeup.

Concern over cost of and access to cancer treatments: A meta-narrative review of nivolumab and pembrolizumab studies

BACKGROUND

A better understanding of the modulation of the immune system has resulted in the development of new classes of antitumor agents such as nivolumab and pembrolizumab. Despite the proven effectiveness and tolerability of these new drugs for specific types of cancer, the high cost of treatment has affected their accessibility.

OBJECTIVE

The aim of this study is to conduct a meta-narrative review of studies that have addressed the concerns that have been voiced regarding the cost of and access to nivolumab and pembrolizumab in oncology health care. This meta-narrative review attempts to answer the following questions: (1) which papers have considered this broad topic area?; (2) what are the main empirical/theoretical findings?; and (3) what insights can be drawn by combining and comparing findings from different papers?

METHODS AND DATA SOURCE

A meta-narrative review has been conducted in 5 research databases (Web of Science, Science Direct, Scopus, Embase and Pubmed) without time limitations up to January of 2017 to address concerns related to the cost of and access to nivolumab and pembrolizumab in oncology health care. From each research base, articles were selected that had a key word related to the theme of pharmacoeconomics and nivolumab or pembrolizumab in any field of scientific work. The research questions were analyzed through the application of a meta-narrative review approach and the use of a convergence-coding matrix to summarize similarities and differences directly related to the research topic between the different papers.

KEY FINDINGS

The first contribution of this meta-narrative review is that it summarizes economic-based works on the use of nivolumab and pembrolizumab, particularly for three therapeutic indications: melanoma, NSCLC and RCC. In general, despite the clinical benefit of nivolumab and pembrolizumab being well accepted and proven by scientific works, the published studies show that there are contradictory results with regard to the cost-effectiveness of these anti-PD-1s. The regulatory, economic and epidemiological variations mean that healthcare costs for cancer patients vary greatly from country to country and according to the type of tumor. The second contribution has to do with the recommendations for the development of high quality process for pharmacoeconomic analyses, especially in the new field of immuno-oncology. Finally, the third contribution is with regard to recommendations for the sustainable use of immunotherapies.

CONCLUSIONS

Given the revolution in cancer therapy in recent years, the efficient allocation of existing resources is essential for healthcare systems to meet the evolving needs of populations and remain sustainable in the long term. The application of high quality information that stems from scientific evidence and economic modeling can help considerably to make the healthcare system sustainable over time mainly due to a higher number of therapeutic indications or more countries giving regulatory approval for the use of new and expensive cancer drugs.

Novel therapeutic strategy for cancer and autoimmune conditions: Modulating cell metabolism and redox capacity

Dysregulation of cell metabolism and redox balance is implicated in the pathogenesis and progression of cancer and autoimmune diseases. Because the cell proliferation and apoptotic regulatory pathways are interconnected with metabolic and redox signalling pathways, the current mono-target treatment is ineffective, and multi-drug resistance remains common. Complex diseases are often implicated in a network-based context of pathology; therefore, a new holistic intervention approach is required to block multi-crosstalk in such complicated circumstances. The use of therapeutic agents isolated from herbs to holistically modulate metabolism and redox state has been shown to relieve carcinoma growth and the inflammatory response in autoimmune disorders. Multiple clinically applied or novel herbal chemicals with metabolic and redox modulatory capacity as well as low toxicity have recently been identified. Moreover, new metabolic targets and mechanisms of drug action have been discovered, leading to the exploration of new pathways for drug repositioning, clinical biomarker spectra, clinical treatment strategies and drug development. Taken together with multiple supporting examples, the modulation of cell metabolism and the redox capacity using herbal chemicals is emerging as a new, alternative strategy for the holistic treatment of cancer and autoimmune disorders. In the future, the development of new diagnostic tools based on the detection of metabolic and redox biomarkers, reformulation of optimized herbal compositions using artificial intelligence, and the combination of herbs with mono-targeting drugs will reveal new potential for clinical application.

Emerging Trends in Clinical Research: With Implications for Population Health and Health Policy

Policy Points: Significant advances in clinical medicine that have broader societal relevance may be less accessible to population health researchers and policymakers because of increased specialization within fields. We describe important recent clinical advances and discuss their broader societal impact. These advances include more expansive strategies for disease prevention, the rise of precision medicine, applications of human microbiome research, and new and highly successful treatments for hepatitis C infection. These recent developments in clinical research raise important issues surrounding health care costs and equitable resource allocation that necessitate an ongoing dialogue among the fields of clinical medicine, population health, and health policy.

CONTEXT

Developments in clinical medicine have important implications for population health, and there is a need for interdisciplinary engagement among clinical medicine, the social sciences, and public health research. The aim of this article is to help bridge the divide between these fields by exploring major recent advances in clinical medicine that have important implications for population health.

METHODS

We reviewed the most cited articles published from 2010 to 2015 in 5 high-impact clinical journals and selected 5 randomized controlled trials and 2 related clinical practice guidelines that are broadly relevant to population health and policy.

FINDINGS

We discuss the following themes: (1) expanding indications for drug therapy and the inherent medicalization of the population as highlighted by studies and clinical guidelines supporting lower blood pressure targets or widespread statin use; (2) the tension in nutritional research between quantifying the impact of isolated nutrients and studying specific foods and dietary patterns, for example, the role of the Mediterranean diet in the primary prevention of cardiovascular disease; (3) the issue of high medication costs and the challenge of providing equitable access raised by the development of new and effective treatments for hepatitis C infection; (4) emerging clinical applications of research on the human microbiome as illustrated by fecal transplant to treat Clostridium difficile infections; and (5) the promise and limitations of precision medicine as demonstrated by the rise of novel targeted therapies in oncology.

CONCLUSIONS

These developments in clinical science hold promise for improving individual and population health and raise important questions about resource allocation, the role of prevention, and health disparities.