Towards Precision Medicine in the Clinic: From Biomarker Discovery to Novel Therapeutics

Implementing liquid biopsies into clinical decision making for cancer immunotherapy

During the last decade, novel immunotherapeutic strategies, in particular antibodies directed against immune checkpoint inhibitors, have revolutionized the treatment of different malignancies leading to an improved survival of patients. Identification of immune-related biomarkers for diagnosis, prognosis, monitoring of immune responses and selection of patients for specific cancer immunotherapies is urgently required and therefore areas of intensive research. Easily accessible samples in particular liquid biopsies (body fluids), such as blood, saliva or urine, are preferred for serial tumor biopsies.

Although monitoring of immune and tumor responses prior, during and post immunotherapy has led to significant advances of patients’ outcome, valid and stable prognostic biomarkers are still missing. This might be due to the limited capacity of the technologies employed, reproducibility of results as well as assay stability and validation of results. Therefore solid approaches to assess immune regulation and modulation as well as to follow up the nature of the tumor in liquid biopsies are urgently required to discover valuable and relevant biomarkers including sample preparation, timing of the collection and the type of liquid samples. This article summarizes our knowledge of the well-known liquid material in a new context as liquid biopsy and focuses on collection and assay requirements for the analysis and the technical developments that allow the implementation of different high-throughput assays to detect alterations at the genetic and immunologic level, which could be used for monitoring treatment efficiency, acquired therapy resistance mechanisms and the prognostic value of the liquid biopsies.

Nanomaterials for Cancer Precision Medicine

Medical science has recently advanced to the point where diagnosis and therapeutics can be carried out with high precision, even at the molecular level. A new field of "precision medicine" has consequently emerged with specific clinical implications and challenges that can be well-addressed by newly developed nanomaterials. Here, a nanoscience approach to precision medicine is provided, with a focus on cancer therapy, based on a new concept of "molecularly-defined cancers." "Next-generation sequencing" is introduced to identify the oncogene that is responsible for a class of cancers. This new approach is fundamentally different from all conventional cancer therapies that rely on diagnosis of the anatomic origins where the tumors are found. To treat cancers at molecular level, a recently developed "microRNA replacement therapy" is applied, utilizing nanocarriers, in order to regulate the driver oncogene, which is the core of cancer precision therapeutics. Furthermore, the outcome of the nanomediated oncogenic regulation has to be accurately assessed by the genetically characterized, patient-derived xenograft models. Cancer therapy in this fashion is a quintessential example of precision medicine, presenting many challenges to the materials communities with new issues in structural design, surface functionalization, gene/drug storage and delivery, cell targeting, and medical imaging.

Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges

Patient-specific computer models have been developed representing a variety of aspects of the cardiovascular system spanning the disciplines of electrophysiology, electromechanics, solid mechanics, and fluid dynamics. These physiological mechanistic models predict macroscopic phenomena such as electrical impulse propagation and contraction throughout the entire heart as well as flow and pressure dynamics occurring in the ventricular chambers, aorta, and coronary arteries during each heartbeat. Such models have been used to study a variety of clinical scenarios including aortic aneurysms, coronary stenosis, cardiac valvular disease, left ventricular assist devices, cardiac resynchronization therapy, ablation therapy, and risk stratification. After decades of research, these models are beginning to be incorporated into clinical practice directly via marketed devices and indirectly by improving our understanding of the underlying mechanisms of health and disease within a clinical context.

Drug discovery targeting the mTOR pathway

Mechanistic target of rapamycin (mTOR) is the kinase subunit of two structurally and functionally distinct large multiprotein complexes, referred to as mTOR complex 1 (mTORC1) and mTORC2. mTORC1 and mTORC2 play key physiological roles as they control anabolic and catabolic processes in response to external cues in a variety of tissues and organs. However, mTORC1 and mTORC2 activities are deregulated in widespread human diseases, including cancer. Cancer cells take advantage of mTOR oncogenic signaling to drive their proliferation, survival, metabolic transformation, and metastatic potential. Therefore, mTOR lends itself very well as a therapeutic target for innovative cancer treatment. mTOR was initially identified as the target of the antibiotic rapamycin that displayed remarkable antitumor activity in vitro Promising preclinical studies using rapamycin and its derivatives (rapalogs) demonstrated efficacy in many human cancer types, hence supporting the launch of numerous clinical trials aimed to evaluate the real effectiveness of mTOR-targeted therapies. However, rapamycin and rapalogs have shown very limited activity in most clinical contexts, also when combined with other drugs. Thus, novel classes of mTOR inhibitors with a stronger antineoplastic potency have been developed. Nevertheless, emerging clinical data suggest that also these novel mTOR-targeting drugs may have a weak antitumor activity. Here, we summarize the current status of available mTOR inhibitors and highlight the most relevant results from both preclinical and clinical studies that have provided valuable insights into both their efficacy and failure.

Clinical Outcome of Patients with Advanced Biliary Tract Cancer in a Dedicated Phase I Unit

AIMS

Advanced biliary tract carcinomas (ABC) are malignancies with limited effective therapies for advanced disease. There is little published evidence of outcomes of ABC patients participating in phase I clinical trials.

MATERIALS AND METHODS

Patient characteristics, treatment details and outcomes of ABC patients treated at a dedicated phase I unit were captured and analysed from case and trial records.

RESULTS

In total, 123 ABC patients were included in the study, of which 48 patients participated in 41 different phase I trials; 75 (61%) did not participate due to rapid disease progression or patient choice. Molecular characterisation of tumours using a targeted panel was conducted in 15 (31%), yielding several potentially actionable mutations, including BRCA, PIK3CA, FGFR, AKT and PTEN loss. Of the 39 evaluable patients there was one exceptional responder. Eighteen (46%) other patients achieved stable disease as their best response, with a clinical benefit rate at 4 months of 10%. Treatment was generally well tolerated with grade 3 or 4 adverse events only observed in eight patients (17 %), of which six were drug related and led to trial discontinuation in one (3%), with no toxicity-related deaths.

CONCLUSION

Carefully selected ABC patients have been found to tolerate experimental phase I clinical trials without excess toxicity. The aggressive nature of this disease warrants consideration of early referral to a phase I unit. Future work will require comprehensive molecular profiling in an attempt to understand the biology underlying the exceptional responders and to match patients in real-time to targeted therapies.

Biomarkers: Delivering on the expectation of molecularly driven, quantitative health

Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

Robust phenotype prediction from gene expression data using differential shrinkage of co-regulated genes

Discovery of robust diagnostic or prognostic biomarkers is a key to optimizing therapeutic benefit for select patient cohorts - an idea commonly referred to as precision medicine. Most discovery studies to derive such markers from high-dimensional transcriptomics datasets are weakly powered with sample sizes in the tens of patients. Therefore, highly regularized statistical approaches are essential to making generalizable predictions. At the same time, prior knowledge-driven approaches have been successfully applied to the manual interpretation of high-dimensional transcriptomics datasets. In this work, we assess the impact of combining two orthogonal approaches for the discovery of biomarker signatures, namely (1) well-known lasso-based regression approaches and its more recent derivative, the group lasso, and (2) the discovery of significant upstream regulators in literature-derived biological networks. Our method integrates both approaches in a weighted group-lasso model and differentially weights gene sets based on inferred active regulatory mechanism. Using nested cross-validation as well as independent clinical datasets, we demonstrate that our approach leads to increased accuracy and generalizable results. We implement our approach in a computationally efficient, user-friendly R package called creNET. The package can be downloaded at https://github.com/kouroshz/creNethttps://github.com/kouroshz/creNet and is accompanied by a parsed version of the STRING DB data base.

Use of Real-World Data for the Research, Development, and Evaluation of Oncology Precision Medicines

Although randomized controlled trials remain the scientific ideal for determining the efficacy and safety of new treatments, they are sometimes insufficient to address the evidentiary requirements of regulators and payers. This is particularly the case when it comes to precision medicines because trials are often small, deliver incomplete insights into outcomes of most interest to policymakers (eg, overall survival), and may fail to address other complex diagnostic and treatment-related questions. Additional methods, both experimental and observational, are increasingly being used to fill critical evidentiary gaps. A number of modified early- and late-phase trial designs have been proposed to better support earlier biomarker validation, patient identification, and selection for regulatory studies, but there is still a need for confirmatory evidence from real-world data sources. These data are usually provided through observational, postapproval, phase IIIB and IV studies, which rely heavily on registries and other electronic data sets—most notably data from electronic health records. It is, therefore, crucial to understand what ethical, practical, and scientific challenges are raised by the use of electronic health records to generate evidence about precision medicines.

The Generation and Application of Patient-Derived Xenograft Model for Cancer Research

Establishing an appropriate preclinical model is crucial for translational cancer research. The most common way that has been adopted by far is grafting cancer cell lines, derived from patients. Although this xenograft model is easy to generate, but has several limitations because this cancer model could not represent the unique features of each cancer patient sufficiently. Moreover, accumulating evidences demonstrate cancer is a highly heterogeneous disease so that a tumor is comprised of cancer cells with diverse characteristics. In attempt to avoid these discrepancies between xenograft model and patients' tumor, a patient-derived xenograft (PDX) model has been actively generated and applied. The PDX model can be developed by the implantation of cancerous tissue from a patient's tumor into an immune-deficient mouse directly, thereby it preserves both cell-cell interactions and tumor microenvironment. In addition, the PDX model has shown advantages as a preclinical model in drug screening, biomarker development and co-clinical trial. In this review, we will summarize the methodology and applications of PDX in detail, and cover critical issues for the development of this model for preclinical research.

A system for detecting high impact-low frequency mutations in primary tumors and metastases

Tumor complexity and intratumor heterogeneity contribute to subclonal diversity. Despite advances in next-generation sequencing (NGS) and bioinformatics, detecting rare mutations in primary tumors and metastases contributing to subclonal diversity is a challenge for precision genomics. Here, in order to identify rare mutations, we adapted a recently described epithelial reprograming assay for short-term propagation of epithelial cells from primary and metastatic tumors. Using this approach, we expanded minor clones and obtained epithelial cell-specific DNA/RNA for quantitative NGS analysis. Comparative Ampliseq Comprehensive Cancer Panel sequence analyses were performed on DNA from unprocessed breast tumor and tumor cells propagated from the same tumor. We identified previously uncharacterized mutations present only in the cultured tumor cells, a subset of which has been reported in brain metastatic but not primary breast tumors. In addition, whole-genome sequencing identified mutations enriched in liver metastases of various cancers, including Notch pathway mutations/chromosomal inversions in 5/5 liver metastases, irrespective of cancer types. Mutations/rearrangements in FHIT, involved in purine metabolism, were detected in 4/5 liver metastases, and the same four liver metastases shared mutations in 32 genes, including mutations of different HLA-DR family members affecting OX40 signaling pathway, which could impact the immune response to metastatic cells. Pathway analyses of all mutated genes in liver metastases showed aberrant tumor necrosis factor and transforming growth factor signaling in metastatic cells. Epigenetic regulators including KMT2C/MLL3 and ARID1B, which are mutated in >50% of hepatocellular carcinomas, were also mutated in liver metastases. Thus, irrespective of cancer types, organ-specific metastases may share common genomic aberrations. Since recent studies show independent evolution of primary tumors and metastases and in most cases mutation burden is higher in metastases than primary tumors, the method described here may allow early detection of subclonal somatic alterations associated with metastatic progression and potentially identify therapeutically actionable, metastasis-specific genomic aberrations.

Modularly Constructed Synthetic Granzyme B Molecule Enables Interrogation of Intracellular Proteases for Targeted Cytotoxicity

Targeted therapies promise to increase the safety and efficacy of treatments against diseases ranging from cancer to viral infections. However, the vast majority of targeted therapeutics relies on the recognition of extracellular biomarkers, which are rarely restricted to diseased cells and are thus prone to severe and sometimes-fatal off-target toxicities. In contrast, intracellular antigens present a diverse yet underutilized repertoire of disease markers. Here, we report a protein-based therapeutic platform-termed Cytoplasmic Oncoprotein VErifier and Response Trigger (COVERT)-which enables the interrogation of intracellular proteases to trigger targeted cytotoxicity. COVERT molecules consist of the cytotoxic protein granzyme B (GrB) fused to an inhibitory N-terminal peptide, which can be removed by researcher-specified proteases to activate GrB function. We demonstrate that fusion of a small ubiquitin-like modifier 1 (SUMO1) protein to GrB yields a SUMO-GrB molecule that is specifically activated by the cancer-associated sentrin-specific protease 1 (SENP1). SUMO-GrB selectively triggers apoptotic phenotypes in HEK293T cells that overexpress SENP1, and it is highly sensitive to different SENP1 levels across cell lines. We further demonstrate the rational design of additional COVERT molecules responsive to enterokinase (EK) and tobacco etch virus protease (TEVp), highlighting the COVERT platform's modularity and adaptability to diverse protease targets. As an initial step toward engineering COVERT-T cells for adoptive T-cell therapy, we verified that primary human T cells can express, package, traffic, and deliver engineered GrB molecules in response to antigen stimulation. Our findings set the foundation for future intracellular-antigen-responsive therapeutics that can complement surface-targeted therapies.

Using omics approaches to understand pulmonary diseases

Omics approaches are high-throughput unbiased technologies that provide snapshots of various aspects of biological systems and include: 1) genomics, the measure of DNA variation; 2) transcriptomics, the measure of RNA expression; 3) epigenomics, the measure of DNA alterations not involving sequence variation that influence RNA expression; 4) proteomics, the measure of protein expression or its chemical modifications; and 5) metabolomics, the measure of metabolite levels. Our understanding of pulmonary diseases has increased as a result of applying these omics approaches to characterize patients, uncover mechanisms underlying drug responsiveness, and identify effects of environmental exposures and interventions. As more tissue- and cell-specific omics data is analyzed and integrated for diverse patients under various conditions, there will be increased identification of key mechanisms that underlie pulmonary biological processes, disease endotypes, and novel therapeutics that are efficacious in select individuals. We provide a synopsis of how omics approaches have advanced our understanding of asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), and pulmonary arterial hypertension (PAH), and we highlight ongoing work that will facilitate pulmonary disease precision medicine.

A versatile nanoplatform for synergistic combination therapy to treat human esophageal cancer

One of the major goals of precision oncology is to promote combination therapy to improve efficacy and reduce side effects of anti-cancer drugs based on their molecular mechanisms. In this study, we aimed to develop and validate new nanoformulations of docetaxel (DTX) and bortezomib (BTZ) for targeted combination therapy to treat human esophageal cancer. By leveraging our versatile disulfide cross-linked micelles (DCMs) platform, we developed nanoformulations of DTX and BTZ (named DTX-DCMs and BTZ-DCMs). Their physical properties were characterized; their anti-cancer efficacies and mechanisms of action were investigated in a human esophageal cancer cell line in vitro. Furthermore, the in vitro anti-tumor activities of combination therapies (concurrent drug treatment, sequential drug treatment, and treatment using different ratios of the drugs) were examined in comparison with the single drug treatment and free drug strategies. These drug-loaded nanoparticles were spherical in shape and relatively small in size of approximately 20-22 nm. The entrapment efficiencies of DTX and BTZ into nanoparticles were 82.4% and 84.1%, respectively. The drug release rates of DTX-DCMs and BTZ-DCMs were sustained, and greatly increased in the presence of GSH. These nanodrugs were effectively internalized by KYSE30 esophageal cancer cells, and dose-dependently induced cell apoptosis. We further revealed a strong synergistic effect between DTX-DCMs and BTZ-DCMs against KYSE30 esophageal cancer cells. Sequential combination therapy with DTX-DCMs followed by BTZ-DCMs exhibited the best anti-tumor efficacy in vitro. This study demonstrates that DTX and BTZ could be successfully nanoformulated into disulfide cross-linked micelles. The nanoformulations of DTX and BTZ demonstrate an immense potential for synergistic combination therapy to treat human esophageal cancer.

State of Art of Cancer Pharmacogenomics in Latin American Populations

Over the past decades, several studies have shown that tumor-related somatic and germline alterations predicts tumor prognosis, drug response and toxicity. Latin American populations present a vast geno-phenotypic diversity due to the great interethnic and interracial mixing. This genetic flow leads to the appearance of complex characteristics that allow individuals to adapt to endemic environments, such as high altitude or extreme tropical weather. These genetic changes, most of them subtle and unexplored, could establish a mutational profile to develop new pharmacogenomic therapies specific for Latin American populations. In this review, we present the current status of research on somatic and germline alterations in Latin America compared to those found in Caucasian and Asian populations.