Potential Plasma Proteins (LGALS9, LAMP3, PRSS8 and AGRN) as Predictors of Hospitalisation Risk in COVID-19 Patients.

Background: The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has posed unprecedented challenges to healthcare systems worldwide. Here, we have identified proteomic and genetic signatures for improved prognosis which is vital for COVID-19 research. Methods: We investigated the proteomic and genomic profile of COVID-19-positive patients (n = 400 for proteomics, n = 483 for genomics), focusing on differential regulation between hospitalised and non-hospitalised COVID-19 patients. Signatures had their predictive capabilities tested using independent machine learning models such as Support Vector Machine (SVM), Random Forest (RF) and Logistic Regression (LR). Results: This study has identified 224 differentially expressed proteins involved in various inflammatory and immunological pathways in hospitalised COVID-19 patients compared to non-hospitalised COVID-19 patients. LGALS9 (p-value < 0.001), LAMP3 (p-value < 0.001), PRSS8 (p-value < 0.001) and AGRN (p-value < 0.001) were identified as the most statistically significant proteins. Several hundred rsIDs were queried across the top 10 significant signatures, identifying three significant SNPs on the FSTL3 gene showing a correlation with hospitalisation status. Conclusions: Our study has not only identified key signatures of COVID-19 patients with worsened health but has also demonstrated their predictive capabilities as potential biomarkers, which suggests a staple role in the worsened health effects caused by COVID-19.

Precision Oncology, Artificial Intelligence, and Novel Therapeutic Advancements in the Diagnosis, Prevention, and Treatment of Cancer: Highlights from the 59th Irish Association for Cancer Research (IACR) Annual Conference.

Advancements in oncology, especially with the era of precision oncology, is resulting in a paradigm shift in cancer care. Indeed, innovative technologies, such as artificial intelligence, are paving the way towards enhanced diagnosis, prevention, and personalised treatments as well as novel drug discoveries. Despite excellent progress, the emergence of resistant cancers has curtailed both the pace and extent to which we can advance. By combining both their understanding of the fundamental biological mechanisms and technological advancements such as artificial intelligence and data science, cancer researchers are now beginning to address this. Together, this will revolutionise cancer care, by enhancing molecular interventions that may aid cancer prevention, inform clinical decision making, and accelerate the development of novel therapeutic drugs. Here, we will discuss the advances and approaches in both artificial intelligence and precision oncology, presented at the 59th Irish Association for Cancer Research annual conference.

Genomic, Proteomic, and Phenotypic Biomarkers of COVID-19 Severity: Protocol for a Retrospective Observational Study.

BACKGROUND: Health organizations and countries around the world have found it difficult to control the spread of COVID-19. To minimize the future impact on the UK National Health Service and improve patient care, there is a pressing need to identify individuals who are at a higher risk of being hospitalized because of severe COVID-19. Early targeted work was successful in identifying angiotensin-converting enzyme-2 receptors and type II transmembrane serine protease dependency as drivers of severe infection. Although a targeted approach highlights key pathways, a multiomics approach will provide a clearer and more comprehensive picture of severe COVID-19 etiology and progression. OBJECTIVE: The COVID-19 Response Study aims to carry out an integrated multiomics analysis to identify biomarkers in blood and saliva that could contribute to host susceptibility to SARS-CoV-2 and the development of severe COVID-19. METHODS: The COVID-19 Response Study aims to recruit 1000 people who recovered from SARS-CoV-2 infection in both community and hospital settings on the island of Ireland. This protocol describes the retrospective observational study component carried out in Northern Ireland (NI; Cohort A); the Republic of Ireland cohort will be described separately. For all NI participants (n=519), SARS-CoV-2 infection has been confirmed by reverse transcription-quantitative polymerase chain reaction. A prospective Cohort B of 40 patients is also being followed up at 1, 3, 6, and 12 months postinfection to assess longitudinal symptom frequency and immune response. Data will be sourced from whole blood, saliva samples, and clinical data from the electronic care records, the general health questionnaire, and a 12-item general health questionnaire mental health survey. Saliva and blood samples were processed to extract DNA and RNA before whole-genome sequencing, RNA sequencing, DNA methylation analysis, microbiome analysis, 16S ribosomal RNA gene sequencing, and proteomic analysis were performed on the plasma. Multiomics data will be combined with clinical data to produce sensitive and specific prognostic models for severity risk. RESULTS: An initial demographic and clinical profile of the NI Cohort A has been completed. A total of 249 hospitalized patients and 270 nonhospitalized patients were recruited, of whom 184 (64.3%) were female, and the mean age was 45.4 (SD 13) years. High levels of comorbidity were evident in the hospitalized cohort, with cardiovascular disease and metabolic and respiratory disorders being the most significant (P<.001), grouped according to the International Classification of Diseases 10 codes. CONCLUSIONS: This study will provide a comprehensive opportunity to study the mechanisms of COVID-19 severity in recontactable participants. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50733.

Mapping the Immune Landscape in Metastatic Melanoma Reveals Localized Cell-Cell Interactions That Predict Immunotherapy Response.

While immune checkpoint-based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types. Here, we used multiplexed IHC to spatially characterize the immune landscape of metastatic melanoma from responders and nonresponders to ICI. Such high-dimensional pathology maps showed that Tcy gradually evolve toward an exhausted phenotype as they approach and infiltrate the tumor. Moreover, a key cellular interaction network functionally linked Tcy and PD-L1+ macrophages. Mapping the respective spatial distributions of these two cell populations predicted response to anti-PD-1 immunotherapy with high confidence. These results suggest that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI. SIGNIFICANCE: This study shows that spatial characterization can address the challenge of finding efficient biomarkers, revealing that localization of macrophages and T cells in melanoma predicts patient response to ICI. See related commentary by Smalley and Smalley, p. 3198.

Role of Senescence and Aging in SARS-CoV-2 Infection and COVID-19 Disease.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global pandemic associated with substantial morbidity and mortality worldwide, with particular risk for severe disease and mortality in the elderly population. SARS-CoV-2 infection is driven by a pathological hyperinflammatory response which results in a dysregulated immune response. Current advancements in aging research indicates that aging pathways have fundamental roles in dictating healthspan in addition to lifespan. Our review discusses the aging immune system and highlights that senescence and aging together, play a central role in COVID-19 pathogenesis. In our review, we primarily focus on the immune system response to SARS-CoV-2 infection, the interconnection between severe COVID-19, immunosenescence, aging, vaccination, and the emerging problem of Long-COVID. We hope to highlight the importance of identifying specific senescent endotypes (or "sendotypes"), which can used as determinants of COVID-19 severity and mortality. Indeed, identified sendotypes could be therapeutically exploited for therapeutic intervention. We highlight that senolytics, which eliminate senescent cells, can target aging-associated pathways and therefore are proving attractive as potential therapeutic options to alleviate symptoms, prevent severe infection, and reduce mortality burden in COVID-19 and thus ultimately enhance healthspan.

Prognostic value of the 6-gene OncoMasTR test in hormone receptor-positive HER2-negative early-stage breast cancer: Comparative analysis with standard clinicopathological factors.

AIM: The aim of the study was to assess the prognostic performance of a 6-gene molecular score (OncoMasTR Molecular Score [OMm]) and a composite risk score (OncoMasTR Risk Score [OM]) and to conduct a within-patient comparison against four routinely used molecular and clinicopathological risk assessment tools: Oncotype DX Recurrence Score, Ki67, Nottingham Prognostic Index and Clinical Risk Category, based on the modified Adjuvant! Online definition and three risk factors: patient age, tumour size and grade. METHODS: Biospecimens and clinicopathological information for 404 Irish women also previously enrolled in the Trial Assigning Individualized Options for Treatment [Rx] were provided by 11 participating hospitals, as the primary objective of an independent translational study. Gene expression measured via RT-qPCR was used to calculate OMm and OM. The prognostic value for distant recurrence-free survival (DRFS) and invasive disease-free survival (IDFS) was assessed using Cox proportional hazards models and Kaplan-Meier analysis. All statistical tests were two-sided ones. RESULTS: OMm and OM (both with likelihood ratio statistic [LRS] P < 0.001; C indexes = 0.84 and 0.85, respectively) were more prognostic for DRFS and provided significant additional prognostic information to all other assessment tools/factors assessed (all LRS P ≤ 0.002). In addition, the OM correctly classified more patients with distant recurrences (DRs) into the high-risk category than other risk classification tools. Similar results were observed for IDFS. DISCUSSION: Both OncoMasTR scores were significantly prognostic for DRFS and IDFS and provided additional prognostic information to the molecular and clinicopathological risk factors/tools assessed. OM was also the most accurate risk classification tool for identifying DR. A concise 6-gene signature with superior risk stratification was shown to increase prognosis reliability, which may help clinicians optimise treatment decisions.

Advances in tissue-based imaging: impact on oncology research and clinical practice.

INTRODUCTION: Tissue-based imaging has emerged as a critical tool in translational cancer research and is rapidly gaining traction within a clinical context. Significant progress has been made in the digital pathology arena, particularly in respect of brightfield and fluorescent imaging. Critically, the cellular context of molecular alterations occurring at DNA, RNA, or protein level within tumor tissue is now being more fully appreciated. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumor microenvironment, including the potential interplay between various cell types. AREAS COVERED: This review summarizes the recent developments within the field of tissue-based imaging, centering on the application of these approaches in oncology research and clinical practice. EXPERT OPINION: Significant advances have been made in digital pathology during the last 10 years. These include the use of quantitative image analysis algorithms, predictive artificial intelligence (AI) on large datasets of H&E images, and quantification of fluorescence multiplexed tissue imaging data. We believe that new methodologies that can integrate AI-derived histologic data with omic data, together with other forms of imaging data (such as radiologic image data), will enhance our ability to deliver better diagnostics and treatment decisions to the cancer patient.

miR-210 is induced by hypoxia and regulates neural cell adhesion molecule in prostate cells.

Hypoxia in prostate tumours has been associated with disease progression and metastasis. MicroRNAs are short noncoding RNA molecules that are important in several cell processes, but their role in hypoxic signalling is still poorly understood. miR-210 has been linked with hypoxic mechanisms, but this relationship has been poorly characterised in prostate cancer. In this report, the link between hypoxia and miR-210 in prostate cancer cells is investigated. Polymerase chain reaction analysis demonstrates that miR-210 is induced by hypoxia in prostate cancer cells using in vitro cell models and an in vivo prostate tumour xenograft model. Analysis of The Cancer Genome Atlas prostate biopsy datasets shows that miR-210 is significantly correlated with Gleason grade and other clinical markers of prostate cancer progression. Neural cell adhesion molecule (NCAM) is identified as a target of miR-210, providing a biological mechanism whereby hypoxia-induced miR-210 expression can contribute to prostate cancer. This study provides evidence that miR-210 is an important regulator of cell response to hypoxic stress and proposes that its regulation of NCAM may play an important role in the pathogenesis of prostate cancer.

Serum levels of miR-199a-5p correlates with blood pressure in premature cardiovascular disease patients homozygous for the MTHFR 677C > T polymorphism.

This investigation profiled circulating serum concentrations of microRNAs (miRNAs) in premature cardiovascular disease (CVD) patients screened for the 677C > T polymorphism in methylenetetrahydrofolate reductase (MTHFR), a risk factor for hypertension. Serum samples from 75 premature CVD patients of known MTHFR genotype were analysed for CVD-related miRNA expression, to identify those that were associated with blood pressure. Samples were collected at baseline and following intervention with riboflavin as part of a randomized controlled trial. In patients with the MTHFR 677TT genotype, expression of miR-199a-5p in serum was inversely correlated with hypertension at baseline, and with change in blood pressure in TT genotype patients who responded to riboflavin intervention. These correlations were not observed in MTHFR 677CC genotype patients. In vitro experiments and in silico data analysis provided evidence that miR-199a-5p targets SMAD4. This is the first study to link miR-199a-5p expression with hypertension in a genetically at-risk cohort of premature CVD patients.

Regulation of miR-200c and miR-141 by Methylation in Prostate Cancer.

BACKGROUND: In prostate cancer (PCa), abnormal expression of several microRNAs (miRNAs) has been previously reported. Increasing evidence shows that aberrant epigenetic regulation of miRNAs is a contributing factor to their altered expression in cancer. In this study, we investigate whether expression of miR-200c and miR-141 in PCa is related to the DNA methylation status of their promoter. METHODS: PCR analysis of miR-200c and miR-141, and CpG methylation analysis of their common promoter, was performed in PCa cell-lines and in archived prostate biopsy specimens. The biological significance of miR-200c and miR-141 expression in prostate cancer cells was assessed by a series of in vitro bioassays and the effect on proposed targets DNMT3A and TET1/TET3 was investigated. The effect on promoter methylation status in cells treated with demethylating agents was also examined. RESULTS: miR-200c and miR-141 are both highly elevated in LNCaP, 22RV1, and DU145 cells, but significantly reduced in PC3 cells. This correlates inversely with the methylation status of the miR-200c/miR-141 promoter, which is unmethylated in LNCaP, 22RV1, and DU145 cells, but hypermethylated in PC3. In PC3 cells, miR-200c and miR-141 expression is subsequently elevated by treatment with the demethylating drug decitabine (5-aza-2'deoxycytidine) and by knockdown of DNA methyltransferase 1 (DNMT1), suggesting their expression is regulated by methylation. Expression of miR-200c and miR-141 in prostate biopsy tissue was inversely correlated with methylation in promoter CpG sites closest to the miR-200c/miR-141 loci. In vitro, over-expression of miR-200c in PC3 cells inhibited growth and clonogenic potential, as well as inducing apoptosis. Expression of the genes DNMT3A and TET1/TET3 were down-regulated by miR-200c and miR-141 respectively. Finally, treatment with the soy isoflavone genistein caused demethylation of the promoter CpG sites closest to the miR-200c/miR-141 loci resulting in increased miR-200c expression. CONCLUSIONS: Our findings provide evidence that miR-200c and miR-141 are under epigenetic regulation in PCa cells. We propose that profiling their expression and methylation status may have potential as a novel biomarker or focus of therapeutic intervention in the diagnosis and prognosis of PCa. Prostate 76:1146-1159, 2016. © 2016 Wiley Periodicals, Inc.

miR-24 regulates CDKN1B/p27 expression in prostate cancer.

BACKGROUND: MicroRNAs (miRNAs) are small, non-coding RNA molecules with an important role in cancer. In prostate cancer, several miRNAs are expressed abnormally suggesting they may be useful markers for diagnosis, prognosis, and potential therapeutic intervention in this disease. However, the contribution of individual miRNAs to the development and progression of this disease remains poorly understood. This study investigated the role of miR-24, which has not been extensively studied in relation to prostate cancer. METHODS: We used PCR to investigate the expression of miR-24 in a panel of prostate cancer cell-lines and in a series of clinical prostate biopsy specimens. The biological significance of miR-24 expression in prostate cancer cells was assessed by a series of in vitro bioassays and the effect on proposed targets p27 (CDKN1B) and p16 (CDK2NA) was investigated. RESULTS: We showed that miR-24 expression was significantly lower in prostate cancer cell lines compared to a normal prostate epithelial cell line. Decreased expression of miR-24 was also more frequently observed in both needle core and prostatectomy tumor tissue relative to matched normal tissue. Low miR-24 expression correlated with high PSA serum levels and other markers of increased prostate cancer progression. Importantly, over-expression of miR-24 inhibited cell cycle, proliferation, migration, and clonogenic potential of prostate cancer cells, as well as inducing apoptosis. p27 and p16 were confirmed as targets of miR-24 in prostate cancer cells and a significant inverse correlation between miR-24 and p27 was revealed in clinical prostatectomy specimens. CONCLUSIONS: These findings provide evidence that miR-24 has a tumor suppressor role in prostate cancer and also targets p27 and p16 in prostate cancer cells. We propose that it may be a useful progression biomarker or focus of therapeutic intervention for this disease.