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Immune infiltrate diversity confers a good prognosis in follicular lymphoma

From Springer Nature via Jisc Publications RouterHistory: received 2020-08-25, accepted 2021-04-14, registration 2021-04-15, pub-electronic 2021-04-30, online 2021-04-30, pub-print 2021-12Publication status: PublishedFunder: Manchester Biomedical Research Centre; doi: http://dx.doi.org/10.13039/100014653; Grant(s): IS-BRC-1215–20007Funder: Manchester Cancer Research CentreAbstract: Background: Follicular lymphoma (FL) prognosis is influenced by the composition of the tumour microenvironment. We tested an automated approach to quantitatively assess the phenotypic and spatial immune infiltrate diversity as a prognostic biomarker for FL patients. Methods: Diagnostic biopsies were collected from 127 FL patients initially treated with rituximab-based therapy (52%), radiotherapy (28%), or active surveillance (20%). Tissue microarrays were constructed and stained using multiplex immunofluorescence (CD4, CD8, FOXP3, CD21, PD-1, CD68, and DAPI). Subsequently, sections underwent automated cell scoring and analysis of spatial interactions, defined as cells co-occurring within 30 μm. Shannon’s entropy, a metric describing species biodiversity in ecological habitats, was applied to quantify immune infiltrate diversity of cell types and spatial interactions. Immune infiltrate diversity indices were tested in multivariable Cox regression and Kaplan–Meier analysis for overall (OS) and progression-free survival (PFS). Results: Increased diversity of cell types (HR = 0.19 95% CI 0.06–0.65, p = 0.008) and cell spatial interactions (HR = 0.39, 95% CI 0.20–0.75, p = 0.005) was associated with favourable OS, independent of the Follicular Lymphoma International Prognostic Index. In the rituximab-treated subset, the favourable trend between diversity and PFS did not reach statistical significance. Conclusion: Multiplex immunofluorescence and Shannon’s entropy can objectively quantify immune infiltrate diversity and generate prognostic information in FL. This automated approach warrants validation in additional FL cohorts, and its applicability as a pre-treatment biomarker to identify high-risk patients should be further explored. The multiplex image dataset generated by this study is shared publicly to encourage further research on the FL microenvironment

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Modelling the Common Agricultural Policy Impact over the EU Agricultural and Rural Environment through a Machine Learning Predictive Framework

This research provides an analytical and predictive framework, based on state-of-the-art machine-learning (ML) algorithms (random forest (RF) and generalized additive models (GAM)), that can be used to assess and improve the Common Agricultural Policy (CAP) impact/performance over the agricultural and rural environments, easing the identification of proper instruments that can be used by EU policy makers in CAP’s financial management. The applied methodology consists of elaborating a custom-developed analytical framework based on a dataset containing 22 relevant indicators, considering four main dimensions that describe the intricacies of the EU agricultural and rural environment, in the CAP context: rural, emissions, macroeconomic, and financial. The results highlight that an increase of the agricultural research and development funding, as well as the agriculture employment rate, negatively influence the degree of rural poverty. The rural GDP per capita is influenced by the size of the employment rate in agriculture. It seems that environmental sustainability, identified by both fertilizers used and emissions from agriculture parameters, significantly influences the GDP per capita. In predicting emissions in agriculture, the direct payment, degree of rural poverty, fertilizer use, employment in agriculture, and agriculture labor productivity are the main independent parameters with the highest future importance. It was found that when predicting direct payments, the rural employment rate, employment in agriculture, and gross value added must be considered the most. The agricultural, entrepreneurial income prediction is mainly influenced by the total factor productivity, while agricultural research and development investments depend on gross value added, direct payments, and gross value added in the agricultural sector. Future research, related to prediction models based on CAP indicators, should also consider the marketing dimension. It is recommended for direct payments to be used to invest in upgrading the fertilizers technologies, since environmental sustainability will influence economic growth

Identification of a new benzimidazole derivative as an antiviral against hepatitis C virus

Aminoquinolines and piperazines, linked or not, have been used successfully to treat malaria, and some molecules of this family also exhibit antiviral properties. Here we tested several derivatives of 4-aminoquinolines and piperazines for their activity against hepatitis C virus (HCV). We screened 11 molecules from three different families of compounds, and we identified anti-HCV activity in cell culture for six of them. Of these, we selected a compound (B5) that is currently ending clinical phase I evaluation for neurodegenerative diseases. In hepatoma cells, B5 inhibited HCV infection in a pangenotypic and dose-dependent manner, and its antiviral activity was confirmed in primary hepatocytes. B5 also inhibited infection by pseudoparticles expressing HCV envelope glycoproteins E1 and E2, and we demonstrated that it affects a postattachment stage of the entry step. Virus with resistance to B5 was selected by sequential passage in the presence of the drug, and reverse genetics experiments indicated that resistance was conferred mainly by a single mutation in the putative fusion peptide of E1 envelope glycoprotein (F291I). Furthermore, analyses of the effects of other closely related compounds on the B5-resistant mutant suggest that B5 shares a mode of action with other 4-aminoquinoline-based molecules. Finally, mice with humanized liver that were treated with B5 showed a delay in the kinetics of the viral infection. In conclusion, B5 is a novel interesting anti-HCV molecule that could be used to decipher the early steps of the HCV life cycle

Tumour Infiltrating Lymphocytes in Follicular Lymphoma - additional data

The composition of the tumour microenvironment in follicular lymphoma (FL) is a relevant factor in determining disease progression and treatment response. This dataset is a collection of 349 FL diagnostic tissue micro-array (TMA) cores from 130 patients, stained using multi-plex immunofluorescence for: • CD4+ cells • Cytotoxic T cells (CD8+) • T regulatory cells (Tregs [CD4+FOXP3+]) • Macrophages (CD68+) • PD1+ lymphocytes • B cells/follicular dendritic cells (CD21+) • DAPI (4′,6-diamidino-2-phenylindole) nuclear counterstain Changes from previous version 2 ---------- - Raw .im3 image files provided - Spectral library images provided - Labels of nuclear annotations in 16bit format Cohort -------- FL patients according to the WHO 2008 classification were identified from the archives of The Christie NHS Foundation Trust, Manchester, UK. The study was conducted with approval by the North-West Multi-centre Ethics Committee (03/08/016) and according to the Declaration of Helsinki. Examination of the records of 350 FL patients in a random order identified 262 patients meeting the inclusion criteria: adult patients with previously untreated FL; diagnosed from incisional or excisional biopsy; and treated at first presentation with radiotherapy, watchful waiting or a combination of chemotherapy and rituximab immunotherapy. Pre-treatment biopsies were requested for 262 patients, of which 130 had sufficient tissue for analysis. A histological diagnosis of FL was confirmed by an expert haemato-pathologist (R.B). Note: Three patients (FL_59, FL_106 and FL_129) have grade 3b, which is considered equivalent to Diffuse Large B-cell lymphoma. Image format and software compatibility --------------------------------------------- Each image represents a single TMA core as a .im3 raw multispectral image format, containing the following spectra: • DAPI (nuclear) • 650 fluorophore signal for CD68 marker (membrane) • 570 fluorophore signal for CD21 marker (membrane) • 540 fluorophore signal for CD8 marker (membrane) • 690 fluorophore signal for PD1 marker (membrane) • 620 fluorophore signal for CD4 marker (membrane) • 520 fluorophore signal for FOXP3 (nuclear) • Auto-fluorescence The commercial software inForm 2.4 (Akoya Biosciences) is compatible with this format. The images can be unmixed with inForm software by using the spectral library provided. Annotations ------------- Annotations are provided for nuclear segmentation. In a set of 41 small patches the outlines have been drawn manually for 69780 nuclei. A patch from the DAPI channel and corresponding label are given as .tif images. Data structure ---------------- The data is split across multiple different datasets, all referenced below. They include: • FL_0-129 zip files: Raw images for 130 patients, each zip file a single patient. • nuclear_segmentation_annotations.zip: The nuclear segmentation annotations. • spectral library.zip: The raw images used to build the spectral library with inForm software