Overview of precision oncology trials: challenges and opportunities

Implications of trial eligibility in patients with heart failure with mildly reduced or preserved ejection fraction

AIMS

Clinical trials in heart failure with mildly reduced or preserved ejection fraction (HFmrEF/HFpEF) commonly have detailed eligibility criteria. This may contribute to challenges with efficient enrolment and questions regarding the generalizability of trial findings.

METHODS AND RESULTS

Patients with HFmrEF/HFpEF from a large US healthcare system were identified through a computable phenotype applied in linked imaging and electronic health record databases. We evaluated shared eligibility criteria from five recent/ongoing HFmrEF/HFpEF trials (PARAGON-HF, EMPEROR-Preserved, DELIVER, FINE-ARTS, and SPIRRIT-HFpEF) and compared clinical and echocardiographic features as well as outcomes between trial-eligible and trial-ineligible patients. Among 5552 patients with HFpEF/HFmrEF, 792 (14%) were eligible for trial consideration, having met all criteria assessed. Causes of ineligibility included lack of recent loop diuretics (37%), significant pulmonary disease (24%), reduced estimated glomerular filtration rate (17%), recent stroke/transient ischaemic attack (13%), or low natriuretic peptides (12%); 53% of ineligible patients had >1 reason for exclusion. Compared with eligible patients, ineligible patients were younger (age 71 vs. 75 years, P < 0.001) with higher rates of coronary artery disease (66% vs. 59%, P < 0.001) and peripheral vascular disease (40% vs. 33%, P < 0.001), but less mitral regurgitation, lower E/e' ratio, and smaller left atrial sizes. Both eligible and ineligible patients demonstrated high rates of structural heart disease consistent with HFpEF [elevated left atrial size or left ventricular (LV) hypertrophy/increased LV mass], although this was slightly higher among eligible patients (95% vs. 92%, P = 0.001). The two cohorts demonstrated similar LV global longitudinal strain along with a similar prevalence of atrial fibrillation/flutter, hypertension, and obesity. Ineligible patients had similar all-cause mortality (33% vs. 33% at 3 years) to those eligible but lower rates of heart failure hospitalization (20% vs. 28% at 3 years, P < 0.001).

CONCLUSIONS

Among patients with HFmrEF/HFpEF from a large health system, approximately one in seven were eligible for major trials based on key criteria applied through a clinical computable phenotype. These findings highlight the large proportion of patients with HFmrEF/HFpEF ineligible for contemporary trials for whom the generalizability of trial findings may be questioned and further investigation would be beneficial.

Organoids derived from metastatic cancers: Present and future

Organoids are three-dimensional structures derived from primary tissue or tumors that closely mimic the architecture, histology, and function of the parental tissue. In recent years, patient-derived organoids (PDOs) have emerged as powerful tools for modeling tumor heterogeneity, drug screening, and personalized medicine. Although most cancer organoids are derived from primary tumors, the ability of organoids from metastatic cancer to serve as a model for studying tumor biology and predicting the therapeutic response is an area of active investigation. Recent studies have shown that organoids derived from metastatic sites can provide valuable insights into tumor biology and may be used to validate predictive models of the drug response. In this comprehensive review, we discuss the feasibility of culturing organoids from multiple metastatic cancers and evaluate their potential for advancing basic cancer research, drug development, and personalized therapy. We also explore the limitations and challenges associated with using metastasis organoids for cancer research. Overall, this review provides a comprehensive overview of the current state and future prospects of metastatic cancer-derived organoids.

Making In Vitro Tumor Models Whole Again

As a reductionist approach, patient-derived in vitro tumor models are inherently still too simplistic for personalized drug testing as they do not capture many characteristics of the tumor microenvironment (TME), such as tumor architecture and stromal heterogeneity. This is especially problematic for assessing stromal-targeting drugs such as immunotherapies in which the density and distribution of immune and other stromal cells determine drug efficacy. On the other end, in vivo models are typically costly, low-throughput, and time-consuming to establish. Ex vivo patient-derived tumor explant (PDE) cultures involve the culture of resected tumor fragments that potentially retain the intact  TME of the original tumor. Although developed decades ago, PDE cultures have not been widely adopted likely because of their low-throughput and poor long-term viability. However, with growing recognition of the importance of patient-specific TME in mediating drug response, especially in the field of immune-oncology, there is an urgent need to resurrect these holistic cultures. In this Review, the key limitations of patient-derived tumor explant cultures are outlined and technologies that have been developed or could be employed to address these limitations are discussed. Engineered holistic tumor explant cultures may truly realize the concept of personalized medicine for cancer patients.

Individual Treatment Trials—Do Experts Know and Use This Option to Improve the Treatability of Mucopolysaccharidosis?

Mucopolysaccharidoses (MPS) are a group of rare, heterogeneous, lysosomal storage disorders. Patients show a broad spectrum of clinical features with a substantial unmet medical need. Individual treatment trials (ITTs) might be a valid, time- and cost-efficient way to facilitate personalized medicine in the sense of drug repurposing in MPS. However, this treatment option has so far hardly been used—at least hardly been reported or published. Therefore, we aimed to investigate the awareness and utilization of ITTs among MPS clinicians, as well as the potential challenges and innovative approaches to overcome key hurdles, by using an international expert survey on ITTs, namely, ESITT. Although 74% (20/27) were familiar with the concept of ITTs, only 37% (10/27) ever used it, and subsequently only 15% (2/16) published their results. The indicated hurdles of ITTs in MPS were mainly the lack of time and know-how. An evidence-based tool, which provides resources and expertise needed for high-quality ITTs, was highly appreciated by the vast majority (89%; 23/26). The ESITT highlights a serious deficiency of ITT implementation in MPS—a promising option to improve its treatability. Furthermore, we discuss the challenges and innovative approaches to overcome key barriers to ITTs in MPS.

Identification of a TGF-β signaling-related gene signature for prediction of immunotherapy and targeted therapy for lung adenocarcinoma

BACKGROUND

Transforming growth factor (TGF)-β signaling functions importantly in regulating tumor microenvironment (TME). This study developed a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical outcome of patients with lung adenocarcinoma (LUAD).

METHODS

TGF-β signaling-related genes came from The Molecular Signature Database (MSigDB). LUAD prognosis-related genes were screened from all the genes involved in TGF-β signaling using least absolute shrinkage and selection operator (LASSO) Cox regression analysis and then used to establish a risk score model for LUAD. ESTIMATE and CIBERSORT analyzed infiltration of immune cells in TME. Immunotherapy response was analyzed by the TIDE algorithm.

RESULTS

A LUAD prognostic 5-gene signature was developed based on 54 TGF-β signaling-related genes. Prognosis of high-risk patients was significantly worse than low-risk patients. Both internal validation and external dataset validation confirmed a high precision of the risk model in predicting the clinical outcomes of LUAD patients. Multivariate Cox analysis demonstrated the model independence in OS prediction of LUAD. The risk model was significantly related to the infiltration of 9 kinds of immune cells, matrix, and immune components in TME. Low-risk patients tended to respond more actively to anti-PD-1 treatment, while high-risk patients were more sensitive to chemotherapy and targeted therapy.

CONCLUSIONS

The 5-gene signature based on TGF-β signaling-related genes showed potential for LUAD management.

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.

The Landscape of Pediatric Precision Oncology: Program Design, Actionable Alterations, and Clinical Trial Development

Over the last years, various precision medicine programs have been developed for pediatric patients with high-risk, relapsed, or refractory malignancies, selecting patients for targeted treatment through comprehensive molecular profiling. In this review, we describe characteristics of these initiatives, demonstrating the feasibility and potential of molecular-driven precision medicine. Actionable events are identified in a significant subset of patients, although comparing results is complicated due to the lack of a standardized definition of actionable alterations and the different molecular profiling strategies used. The first biomarker-driven trials for childhood cancer have been initiated, but until now the effect of precision medicine on clinical outcome has only been reported for a small number of patients, demonstrating clinical benefit in some. Future perspectives include the incorporation of novel approaches such as liquid biopsies and immune monitoring as well as innovative collaborative trial design including combination strategies, and the development of agents specifically targeting aberrations in childhood malignancies.

Machine learning in the prediction of cancer therapy

Resistance to therapy remains a major cause of cancer treatment failures, resulting in many cancer-related deaths. Resistance can occur at any time during the treatment, even at the beginning. The current treatment plan is dependent mainly on cancer subtypes and the presence of genetic mutations. Evidently, the presence of a genetic mutation does not always predict the therapeutic response and can vary for different cancer subtypes. Therefore, there is an unmet need for predictive models to match a cancer patient with a specific drug or drug combination. Recent advancements in predictive models using artificial intelligence have shown great promise in preclinical settings. However, despite massive improvements in computational power, building clinically useable models remains challenging due to a lack of clinically meaningful pharmacogenomic data. In this review, we provide an overview of recent advancements in therapeutic response prediction using machine learning, which is the most widely used branch of artificial intelligence. We describe the basics of machine learning algorithms, illustrate their use, and highlight the current challenges in therapy response prediction for clinical practice.

Extracting Concepts for Precision Oncology from the Biomedical Literature

This paper describes an initial dataset and automatic natural language processing (NLP) method for extracting concepts related to precision oncology from biomedical research articles. We extract five concept types: Cancer, Mutation, Population, Treatment, Outcome. A corpus of 250 biomedical abstracts were annotated with these concepts following standard double-annotation procedures. We then experiment with BERT-based models for concept extraction. The best-performing model achieved a precision of 63.8%, a recall of 71.9%, and an F1 of 67.1. Finally, we propose additional directions for research for improving extraction performance and utilizing the NLP system in downstream precision oncology applications.

The Contribution of Clinical Pharmacologists in Precision Medicine: An Opportunity for Health Care Improvement

Background

Clinical pharmacologists play an important role and have professional value in the field, especially regarding their role within precision medicine (PM) and personalized therapies.

Objective

In this work, we sought to stimulate debate on the role of clinical pharmacologists.

Methods

A literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, through electronic consultation of 2 databases, PubMed/Medline and Embase, and Google Scholar with manual research taking into account the peer-reviewed literature such as observational studies, reviews, original research articles, comments, mini-reviews, and opinion papers published in English between 2010 and February 2020. Titles and abstracts were screened by 1 author, and studies identified for full-text analysis and selected according to inclusion criteria were agreed on by 2 reviewers.

Results

We identified a total of 535 peer-reviewed articles and the number of full texts eligible for the project was 43. Several publications highlight the clinical value of pharmacologists in highly complex hospitals, where the strategies of PM are implemented. Although there are still no studies measuring the clinical efficiency and the efficacy of clinical pharmacology services, and the applicability of PM protocols, this review shows the considerable debate around the future mission of clinical pharmacology services as a bridging discipline capable of combining the complex knowledge and different professional skills needed to fully implement PM.

Conclusions

Various strategies have been conceived and planned to facilitate the transition from mainstream medicine to PM, which will enable patients to be treated more accurately, with significant advantages in terms of safety and effectiveness of treatments. Therefore, in the future, to ensure that the evolutionary process of medicine can involve as many patients and caregivers as possible, infrastructures capable of bringing together different multidisciplinary skills among health professionals will have to be implemented. Clinical pharmacologists could be the main drivers of this strategy because they already, with their multidisciplinary training, operate in a series of services in high-level hospitals, facilitating the clinical governance of the most challenging patients. The implementation of these strategies will lastly allow national health organizations to adequately address the management and therapeutic challenges related to the advent of new drugs and cell and gene therapies by facilitating the removal of economic and organizational barriers to ensure equitable access to PM. (Curr Ther Res Clin Exp. 2021; 82:XXX–XXX)

Patient-derived cancer organoid tracking with wide-field one-photon redox imaging to assess treatment response

SIGNIFICANCE

Accessible tools are needed for rapid, non-destructive imaging of patient-derived cancer organoid (PCO) treatment response to accelerate drug discovery and streamline treatment planning for individual patients.

AIM

To segment and track individual PCOs with wide-field one-photon redox imaging to extract morphological and metabolic variables of treatment response.

APPROACH

Redox imaging of the endogenous fluorophores, nicotinamide dinucleotide (NADH), nicotinamide dinucleotide phosphate (NADPH), and flavin adenine dinucleotide (FAD), was used to monitor the metabolic state and morphology of PCOs. Redox imaging was performed on a wide-field one-photon epifluorescence microscope to evaluate drug response in two colorectal PCO lines. An automated image analysis framework was developed to track PCOs across multiple time points over 48 h. Variables quantified for each PCO captured metabolic and morphological response to drug treatment, including the optical redox ratio (ORR) and organoid area.

RESULTS

The ORR (NAD(P)H/(FAD + NAD(P)H)) was independent of PCO morphology pretreatment. Drugs that induced cell death decreased the ORR and growth rate compared to control. Multivariate analysis of redox and morphology variables identified distinct PCO subpopulations. Single-organoid tracking improved sensitivity to drug treatment compared to pooled organoid analysis.

CONCLUSIONS

Wide-field one-photon redox imaging can monitor metabolic and morphological changes on a single organoid-level, providing an accessible, non-destructive tool to screen drugs in patient-matched samples.

The evolving paradigm of biomarker actionability: Histology-agnosticism as a spectrum, rather than a binary quality

Precision medicine is progressively revolutionizing oncology, through the identification of biomarkers predictive of treatment response in cancer patients. For three of such biomarkers, namely NTRK-fusions, microsatellite instability and high tumor mutational burden, drugs have been approved by regulatory agencies regardless of tumor histology, realizing the paradigm of histology-agnostic actionability. Several additional biomarkers are being studied in a histology-agnostic manner, and may in the future expand this list. However, most available evidence suggest that histology-agnosticism may be the extreme of a continuous spectrum of actionability, rather than a binary quality. The present review recapitulates such evidence, highlighting opportunities and challenges posed by the emergence of the spectrum of biomarker actionability in the context of a prevalently histology-based oncology.

X-change symposium: status and future of modern radiation oncology-from technology to biology

Future radiation oncology encompasses a broad spectrum of topics ranging from modern clinical trial design to treatment and imaging technology and biology. In more detail, the application of hybrid MRI devices in modern image-guided radiotherapy; the emerging field of radiomics; the role of molecular imaging using positron emission tomography and its integration into clinical routine; radiation biology with its future perspectives, the role of molecular signatures in prognostic modelling; as well as special treatment modalities such as brachytherapy or proton beam therapy are areas of rapid development. More clinically, radiation oncology will certainly find an important role in the management of oligometastasis. The treatment spectrum will also be widened by the rational integration of modern systemic targeted or immune therapies into multimodal treatment strategies. All these developments will require a concise rethinking of clinical trial design. This article reviews the current status and the potential developments in the field of radiation oncology as discussed by a panel of European and international experts sharing their vision during the "X-Change" symposium, held in July 2019 in Munich (Germany).

Recommendations to improve the clinical adoption of NGS-based cancer diagnostics in Singapore

Next-generation sequencing (NGS)-based diagnostics have demonstrated clinical utility in predicting improved survival benefits with targeted treatment in certain cancer types, and positive cost-benefit in several healthcare systems. However, clinical adoption in Singapore remains low despite commercial availability of these diagnostics. This expert opinion review examines the key challenges to the clinical adoption of NGS-based diagnostics in Singapore, provides recommendations on impactful initiatives to improve adoption, and also offers practical guidance on specific cancer types in which NGS-based diagnostics are appropriate for use in Singapore. Limited patient affordability is one major challenge to clinical adoption of NGS-based diagnostics, which could be improved by enabling patient access to more funds for specific cancer types with clear benefits. Expert opinion based on current evidence and clinical experience supports the upfront use of hotspot panels in advanced non-small cell lung cancer (NSCLC), metastatic colorectal cancer, advanced and recurrent ovarian cancer, and acute myeloid leukemia. Comprehensive genomic profiling could be considered for upfront use in select patients with NSCLC and ovarian cancer, or in refractory patients with the four cancer types. Wider adoption of NGS-based diagnostics will improve the delivery of cancer care in Singapore and Asia-Pacific, and thus lead to better patient outcomes.

Position paper: new insights into the immunobiology and dynamics of tumor-host interactions require adaptations of clinical studies

INTRODUCTION

Prospective double-blind placebo-controlled randomized clinical trials (RCTs) are considered standard for the proof of the efficacy of oncologic therapies. Molecular methods have provided new insights into tumor biology and led to the development of targeted therapies. Due to the increasing complexity of molecular tumor characteristics and of the individuality of specific anti-tumor immune reactivity, RCTs are unfortunately only of limited use.

AREAS COVERED

The historical methods of drug research and approval and the related practices of reimbursement by statutory and private health insurance companies are being questioned. New, innovative methods for the documentation of evidence in personalized medicine will be addressed. Possible perspectives and new approaches are discussed, in particular with regard to glioblastoma.

EXPERT OPINION

Highly specialized translational oncology groups like the IOZK can contribute to medical progress and quick transfer 'from bench to bedside.' Their contribution should be acknowledged and taken into account more strongly in the development of guidelines and the reimbursement of therapy costs. Methodological plurality should be encouraged.

Applications of personalised signalling network models in precision oncology

As our ability to provide in-depth, patient-specific characterisation of the molecular alterations within tumours rapidly improves, it is becoming apparent that new approaches will be required to leverage the power of this data and derive the full benefit for each individual patient. Systems biology approaches are beginning to emerge within this field as a potential method of incorporating large volumes of network level data and distilling a coherent, clinically-relevant prediction of drug response. However, the initial promise of this developing field is yet to be realised. Here we argue that in order to develop these precise models of individual drug response and tailor treatment accordingly, we will need to develop mathematical models capable of capturing both the dynamic nature of drug-response signalling networks and key patient-specific information such as mutation status or expression profiles. We also review the modelling approaches commonly utilised within this field, and outline recent examples of their use in furthering the application of systems biology for a precision medicine approach to cancer treatment.

Patient-Derived Cancer Organoid Cultures to Predict Sensitivity to Chemotherapy and Radiation

PURPOSE

Cancer treatment is limited by inaccurate predictors of patient-specific therapeutic response. Therefore, some patients are exposed to unnecessary side effects and delays in starting effective therapy. A clinical tool that predicts treatment sensitivity for individual patients is needed.

EXPERIMENTAL DESIGN

Patient-derived cancer organoids were derived across multiple histologies. The histologic characteristics, mutation profile, clonal structure, and response to chemotherapy and radiation were assessed using bright-field and optical metabolic imaging on spheroid and single-cell levels, respectively.

RESULTS

We demonstrate that patient-derived cancer organoids represent the cancers from which they were derived, including key histologic and molecular features. These cultures were generated from numerous cancers, various biopsy sample types, and in different clinical settings. Next-generation sequencing reveals the presence of subclonal populations within the organoid cultures. These cultures allow for the detection of clonal heterogeneity with a greater sensitivity than bulk tumor sequencing. Optical metabolic imaging of these organoids provides cell-level quantification of treatment response and tumor heterogeneity allowing for resolution of therapeutic differences between patient samples. Using this technology, we prospectively predict treatment response for a patient with metastatic colorectal cancer.

CONCLUSIONS

These studies add to the literature demonstrating feasibility to grow clinical patient-derived organotypic cultures for treatment effectiveness testing. Together, these culture methods and response assessment techniques hold great promise to predict treatment sensitivity for patients with cancer undergoing chemotherapy and/or radiation.

Novel therapeutic strategies for spinal osteosarcomas

At the dawn of the third millennium, cancer has become the bane of twenty-first century man, and remains a predominant public health burden, affecting welfare and life expectancy globally. Spinal osteogenic sarcoma, a primary spinal malignant tumor, is a rare and challenging neoplastic disease to treat. After the conventional therapeutic modalities of chemotherapy, radiation and surgery have been exhausted, there is currently no available alternative therapy in managing cases of spinal osteosarcoma. The defining signatures of tumor survival are characterised by cancer cell ability to stonewall immunogenic attrition and apoptosis by various means. Some of these biomarkers, namely immune-checkpoints, have recently been exploited as druggable targets in osteosarcoma and many other different cancers. These promising strides made by the use of reinvigorated immunotherapeutic approaches may lead to significant reduction in spinal osteosarcoma disease burden and corresponding reciprocity in increase of survival rates. In this review, we provide the background to spinal osteosarcoma, and proceed to elaborate on contribution of the complex ecology within tumor microenvironment giving arise to cancerous immune escape, which is currently receiving considerable attention. We follow this section on the tumor microenvironment by a brief history of cancer immunity. Also, we draw on the current knowledge of treatment gained from incidences of osteosarcoma at other locations of the skeleton (long bones of the extremities in close proximity to the metaphyseal growth plates) to make a case for application of immunity-based tools, such as immune-checkpoint inhibitors and vaccines, and draw attention to adverse upshots of immune-checkpoint blockers as well. Finally, we describe the novel biotechnique of CRISPR/Cas9 that will assist in treatment approaches for personalized medication.

The Status and Impact of Clinical Tumor Genome Sequencing

Since the discovery that DNA alterations initiate tumorigenesis, scientists and clinicians have been exploring ways to counter these changes with targeted therapeutics. The sequencing of tumor DNA was initially limited to highly actionable hot spots-areas of the genome that are frequently altered and have an approved matched therapy in a specific tumor type. Large-scale genome sequencing programs quickly developed technological improvements that enabled the deployment of whole-exome and whole-genome sequencing technologies at scale for pristine sample materials in research environments. However, the turning point for precision medicine in oncology was the innovations in clinical laboratories that improved turnaround time, depth of coverage, and the ability to reliably sequence archived, clinically available samples. Today, tumor genome sequencing no longer suffers from significant technical or financial hurdles, and the next opportunity for improvement lies in the optimal utilization of the technologies and data for many different tumor types.

Driving the precision medicine highway: community health workers and patient navigators

The general public is currently bombarded with direct-to-consumer advertising, real time “medical” guidance through the internet, access to digital devices that capture health information, and science-based adds that promote foods, cosmetics, and dietary supplements. Unfortunately, much of this information relies on terminology and concepts not well-understood by consumers, particularly those with lower levels of health and genomic literacy. Such constraints align with the limitations of the American public to obtain and process the basic medical information needed to make appropriate healthcare decisions. Low levels of health and genomic literacy render the American public ill-equipped to make informed decisions, use and interpret genomic information, or appreciate the benefits afforded by genomics-based technologies. We propose that coordinated expansion of the roles of community health workers and patient navigators within the precision medicine space can be effectively used to disseminate the knowledge required for the public to benefit from precision medicine advances in healthcare. A well-organized and trained community health worker and patient navigator workforce will provide a voice for the disadvantaged, especially among recent immigrants likely to be experiencing social isolation, language barriers, and economic deprivation. Armed with this knowledge, community health workers and patient navigators can advance the precision medicine agenda and empower disadvantaged communities to take advantage of major advances in the precision medicine era.

Endometriosis-associated ovarian cancer: What have we learned so far?

Endometriosis is defined as the presence of ectopic endometrial tissue outside of the uterine cavity, most commonly in the ovaries and peritoneum. It is a complex disease that is influenced by multiple factors. It is also a common gynecological disorder and affects approximately 10-15% of all women of reproductive age. Recent molecular and pathological studies indicate that endometriosis may serve as a precursor of ovarian cancer (endometriosis-associated ovarian cancer, EAOC), particularly endometrioid and clear cell ovarian cancers. Although histological and epidemiological studies have demonstrated that endometriosis has a malignant potential, the molecular mechanism that underlies the malignant transformation of endometriosis is still controversial, and the precise mechanism of carcinogenesis must be fully elucidated. Currently, the development and improvement of a new sequencing technology, next-generation sequencing (NGS), has been increasingly relevant in cancer genomics research. Recently, NGS has also been utilized in clinical oncology to advance the personalized treatment of cancer. In addition, the sensitivity, speed, and cost make NGS a highly attractive platform compared to other sequencing modalities. For this reason, NGS may lead to the identification of driver mutations and underlying pathways associated with EAOC. Here, we present an overview of the molecular pathways that have led to the current opinions on the relationship between endometriosis and ovarian cancer.

Tissue and host species-specific transcriptional changes in models of experimental visceral leishmaniasis

Background: Human visceral leishmaniasis, caused by infection with Leishmania donovani or L. infantum, is a potentially fatal disease affecting 50,000-90,000 people yearly in 75 disease endemic countries, with more than 20,000 deaths reported. Experimental models of infection play a major role in understanding parasite biology, host-pathogen interaction, disease pathogenesis, and parasite transmission. In addition, they have an essential role in the identification and pre-clinical evaluation of new drugs and vaccines. However, our understanding of these models remains fragmentary. Although the immune response to Leishmania donovani infection in mice has been extensively characterized, transcriptomic analysis capturing the tissue-specific evolution of disease has yet to be reported. Methods: We provide an analysis of the transcriptome of spleen, liver and peripheral blood of BALB/c mice infected with L. donovani. Where possible, we compare our data in murine experimental visceral leishmaniasis with transcriptomic data in the public domain obtained from the study of L. donovani-infected hamsters and patients with human visceral leishmaniasis. Digitised whole slide images showing the histopathology in spleen and liver are made available via a dedicated website, www.leishpathnet.org. Results: Our analysis confirms marked tissue-specific alterations in the transcriptome of infected mice over time and identifies previously unrecognized parallels and differences between murine, hamster and human responses to infection. We show commonality of interferon-regulated genes whilst confirming a greater activation of type 2 immune pathways in infected hamsters compared to mice. Cytokine genes and genes encoding immune checkpoints were markedly tissue specific and dynamic in their expression, and pathways focused on non-immune cells reflected tissue specific immunopathology. Our data also addresses the value of measuring peripheral blood transcriptomics as a potential window into underlying systemic disease.  Conclusions: Our transcriptomic data, coupled with histopathologic analysis of the tissue response, provide an additional resource to underpin future mechanistic studies and to guide clinical research.

Tissue and host species-specific transcriptional changes in models of experimental visceral leishmaniasis

Background: Human visceral leishmaniasis, caused by infection with Leishmania donovani or L. infantum, is a potentially fatal disease affecting 50,000-90,000 people yearly in 75 disease endemic countries, with more than 20,000 deaths reported. Experimental models of infection play a major role in understanding parasite biology, host-pathogen interaction, disease pathogenesis, and parasite transmission. In addition, they have an essential role in the identification and pre-clinical evaluation of new drugs and vaccines. However, our understanding of these models remains fragmentary. Although the immune response to Leishmania donovani infection in mice has been extensively characterized, transcriptomic analysis capturing the tissue-specific evolution of disease has yet to be reported. Methods: We provide an analysis of the transcriptome of spleen, liver and peripheral blood of BALB/c mice infected with L. donovani. Where possible, we compare our data in murine experimental visceral leishmaniasis with transcriptomic data in the public domain obtained from the study of L. donovani-infected hamsters and patients with human visceral leishmaniasis. Digitised whole slide images showing the histopathology in spleen and liver are made available via a dedicated website, www.leishpathnet.org. Results: Our analysis confirms marked tissue-specific alterations in the transcriptome of infected mice over time and identifies previously unrecognized parallels and differences between murine, hamster and human responses to infection. We show commonality of interferon-regulated genes whilst confirming a greater activation of type 2 immune pathways in infected hamsters compared to mice. Cytokine genes and genes encoding immune checkpoints were markedly tissue specific and dynamic in their expression, and pathways focused on non-immune cells reflected tissue specific immunopathology. Our data also addresses the value of measuring peripheral blood transcriptomics as a potential window into underlying systemic disease.  Conclusions: Our transcriptomic data, coupled with histopathologic analysis of the tissue response, provide an additional resource to underpin future mechanistic studies and to guide clinical research.