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Uveal melanoma (UM) is a rare aggressive intraocular tumour that spreads most commonly to the liver in tumours with loss of one copy of chromosome 3 (HR-M3); current treatments for metastatic disease remain largely ineffective. Pre-clinical research is increasingly using three-dimensional models that better recapitulate the tumour microenvironment (TME). One aspect of the TME is the acellular extracellular matrix (ECM) that influences cell proliferation, migration and response to therapy. Although commercial matrices are used in culture, the composition and biochemical properties may not be representative of the tumour ECM in vivo. This study identifies UM metastatic risk specific ECM proteins by developing methodology for decellularisation of low- and high- metastatic risk tissue samples (LR-D3 vs. HR-M3). Proteomic analysis revealed a matrisome signature of 34 core ECM and ECM-associated proteins upregulated in HR-M3 UM. Combining additional UM secretome and whole cell iTRAQ proteomic datasets revealed enriched GO and KEGG pathways including ‘regulating ECM binding’ and ‘PI3K/Akt signalling’. Structural analyses of decellularised matrices revealed microarchitecture of differing fibre density and expression differences in collagen 4, collagen 6A1 and nidogen 1, between metastatic risk groups. This approach is a powerful tool for the generation of ECM matrices relevant to high metastatic risk UM.

Lymphoma of the conjunctiva is an ocular malignancy derived from clonal proliferation of lymphocytes. The majority of conjunctival lymphoma is extranodal marginal zone B-Cell lymphoma (EMZL), however diffuse large B-cell (DLBCL), follicular (FL), mantle cell (MCL) and T- cell subtypes are also seen. Clinical manifestations are non-specific, but include unilateral or bilateral painless salmon-pink conjunctival lesions. Approaches to treatment have centered around local immunomodulation, often with Interferon-α2b or Rituximab (anti-CD20 monoclonal antibody) with or without radiation. Although conjunctival lymphoma is generally considered an indolent disease, recent advances in next-generation sequencing have improved clinicians’ ability to predict future recurrence or systemic disease through assessment of cytogenic and molecular features. In this paper, we review the classification, clinical features, diagnostic techniques, and emerging strategies for management and prognostication of conjunctival lymphomas.

AimsTo examine whether the specific location of ocular adnexal lymphoma (OAL) and the American Joint Committee on Cancer (AJCC) TNM tumour stage are prognostic factors for mortality in the main OAL subtypes.MethodsClinical and survival data were retrospectively collected from seven international eye cancer centres. All patients from 1980 to 2017 with histologically verified primary or secondary OAL were included. Cox regression was used to compare the ocular adnexal tumour locations on all-cause mortality and disease-specific mortality.ResultsOAL was identified in 1168 patients. The most frequent lymphoma subtypes were extranodal marginal zone B-cell lymphoma (EMZL) (n=688, 59%); follicular lymphoma (FL) (n=150, 13%); diffuse large B-cell lymphoma (DLBCL) (n=131, 11%); and mantle cell lymphoma (MCL) (n=89, 8%). AJCC/TNM tumour-stage (T-stage) was significantly associated with disease-specific mortality in primary ocular adnexal EMZL and increased through T-categories from T1 to T3 disease. No associations between AJCC/TNM T-stage and mortality were found in primary ocular adnexal FL, DLBCL, or MCL. EMZL located in the eyelid had a significantly increased disease-specific mortality compared with orbital and conjunctival EMZL, in both primary EMZL and the full EMZL cohort. In DLBCL, eyelid location had a significantly higher disease-specific mortality compared with an orbital or lacrimal gland location.ConclusionDisease-specific mortality is associated with AJCC/TNM T-stage in primary ocular adnexal EMZL patients. Lymphoma of the eyelid has the highest disease-specific mortality in primary EMZL, and in the full cohort of EMZL and DLBCL patients.

Backgrounds/aimsTo date, this is the largest cohort study on extranodal marginal zone B-cell lymphoma (EMZL) of the ocular adnexa (OA). The aim of the study was to characterise the clinical features of OA-EMZL.MethodsA retrospective multicentre study involving seven international eye cancer centres. Data were collected from 1 January 1980 through 31 December 2017. A total of 689 patients with OA-EMZL were included.ResultsThe median follow-up time was 42 months. The median age was 62 years (range, 8–100 years), and 55 % (378/689 patients) of patients were women. The majority of patients (82%, 558/680 patients) were diagnosed with primary OA-EMZL with Ann Arbor stage IE (90%, 485/541 patients) and American Joint Committee on Cancer stage T2 (61%, 340/557 patients) at the time of diagnosis. The orbit (66%, 452/689 patients) and the conjunctiva (37%, 255/689 patients) were the most frequently involved anatomical structures. The 5-year, 10-year and 20-year disease-specific survival (DSS) were 96%, 91% and 90%, respectively. Stage IE patients treated with external beam radiation therapy (EBRT) as monotherapy (10-year DSS, 95%) were found to have a better DSS than stage IE patients treated with chemotherapy (10-year DSS, 86%). Stage IIIE/IVE patients treated with chemotherapy and rituximab had a better DSS (10-year DSS, 96%) than stage IIIE/IVE patients treated with chemotherapy without rituximab (10-year DSS, 63%).Conclusions and relevanceEMZL is a slow-growing tumour with an excellent long-term survival. Low-dose EBRT as monotherapy should be considered in localised OA-EMZL. Rituximab-based chemotherapy should be chosen in those patients with disseminated disease.

Severe anaemia is a major cause of morbidity and mortality in HIV-infected adults living in resource-limited countries. Comprehensive data on the aetiology are lacking but are needed to improve outcomes. HIV-infected adults with severe (haemoglobin ≤70g/l) or very severe anaemia (haemoglobin ≤ 50 g/l) were recruited at Queen Elizabeth Central Hospital, Blantyre, Malawi. Fifteen potential causes and associations with anaemia severity and mortality were explored. 199 patients were enrolled: 42.2% had very severe anaemia and 45.7% were on ART. More than two potential causes for anaemia were present in 94% of the patients including iron deficiency (55.3%), underweight (BMI<20: 49.7%), TB infection (41.2%) and unsuppressed HIV infection (viral load >1000 copies/ml) (73.9%). EBV/CMV co-infection (16.5%) was associated with very severe anaemia (OR 2.8 95% CI 1.1-6.9). Overall mortality was high (53%; 100/199) with a median time to death of 17.5 days (IQR 6-55) days. Death was associated with folate deficiency (HR 2.2; 95% CI 1.2-3.8) and end stage renal disease (HR 3.2; 95% CI 1.6-6.2). Mortality among severely anaemic HIV-infected adults is strikingly high. Clinicians should be aware of the urgent need for a multifactorial approach including starting or optimising HIV treatment, considering TB treatment, nutritional support and optimising renal management.

Immune checkpoint therapies (ICT) can reinvigorate the effector functions of anti-tumour T cells, improving cancer patient outcomes. Anti-tumour T cells are initially formed during their first contact (priming) with tumour antigens by antigen-presenting cells (APCs). Unfortunately, many patients are refractory to ICT because their tumours are considered to be ‘cold’ tumours—i.e., they do not allow the generation of T cells (so-called ‘desert’ tumours) or the infiltration of existing anti-tumour T cells (T-cell-excluded tumours). Desert tumours disturb antigen processing and priming of T cells by targeting APCs with suppressive tumour factors derived from their genetic instabilities. In contrast, T-cell-excluded tumours are characterised by blocking effective anti-tumour T lymphocytes infiltrating cancer masses by obstacles, such as fibrosis and tumour-cell-induced immunosuppression. This review delves into critical mechanisms by which cancer cells induce T-cell ‘desertification’ and ‘exclusion’ in ICT refractory tumours. Filling the gaps in our knowledge regarding these pro-tumoral mechanisms will aid researchers in developing novel class immunotherapies that aim at restoring T-cell generation with more efficient priming by APCs and leukocyte tumour trafficking. Such developments are expected to unleash the clinical benefit of ICT in refractory patients.

Uveal melanoma (UM) is the most common primary intraocular tumor that arises from neoplastic melanocytes in the choroid, iris, and ciliary body. Electrochemotherapy (ECT) has been successfully established for the treatment of skin and soft tissue metastatic lesions, deep-seated tumors of the liver, bone metastases, and unresectable pancreas lesions. The aim of this study was to evaluate the effect of ECT in vitro in 3D spheroid culture systems in primary and metastatic UM cell lines. We also investigated the chick embryo chorioallantoic membrane (CAM) as an in vivo model system for the growth and treatment of UM tumors using ECT. The cytotoxic effect of ECT in 3D spheroids was analyzed seven days following treatment by assessment of the size and MTT [(3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) tetrazolium reduction] assay. The cytotoxicity of ECT after intratumoral or intraarterial administration was evaluated histologically. In vitro and in vivo ECT caused a significant reduction in tumor size and viability compared to electroporation or chemotherapy in both sections of our study. The current results underline the effectiveness of ECT in the treatment of UM and prepare the way for further investigation of its potential application in UM.

We report a rare case of a rapidly growing and large conjunctival histoplasmosis lesion in an immunosuppressed West African woman in her 80s, affecting her only eye. The patient had undergone a renal transplant and was on immunosuppressive medications. Additionally, she had previously been treated for presumed systemic histoplasmosis with itraconazole more than 5 years ago. Despite receiving previous treatment, she presented with a large conjunctival lesion, which was confirmed to be histoplasmosis after an excisional biopsy. The lesion was observed to grow over a 2-week period, causing significant visual impairment. Following a comprehensive systems review and investigation, the conjunctiva was identified as the sole site of infection. This case underscores the rarity of sight-threatening Histoplasma infections in the conjunctiva of an immunosuppressed individual. Conjunctival histoplasmosis lesions are rarely reported, with even fewer cases documented as primarily originating from this location.

Background/Objectives: Breast cancer diagnosis heavily relies on histopathological assessment, which is prone to subjectivity and inefficiency, especially with whole-slide imaging (WSI). This study addressed these limitations by developing an automated breast cancer cell classification algorithm using an information-extreme machine learning approach and universal cytological features, aiming for objective and generalized histopathological diagnosis. Methods: Digitized histological images were processed to identify hyperchromatic cells. A set of 21 cytological features (10 geometric and 11 textural), chosen for their potential universality across cancers, were extracted from individual cells. These features were then used to classify cells as normal or malignant using an information-extreme algorithm. This algorithm optimizes an information criterion within a binary Hamming space to achieve robust recognition with minimal input features. The architectural innovation lies in the application of this information-extreme approach to cytological feature analysis for cancer cell classification. Results: The algorithm’s functional efficiency was evaluated on a dataset of 176 labeled cell images, yielding promising results: an accuracy of 89%, a precision of 85%, a recall of 84%, and an F1-score of 88%. These metrics demonstrate a balanced and effective model for automated breast cancer cell classification. Conclusions: The proposed information-extreme algorithm utilizing universal cytological features offers a potentially objective and computationally efficient alternative to traditional methods and may mitigate some limitations of deep learning in histopathological analysis. Future work will focus on validating the algorithm on larger datasets and exploring its applicability to other cancer types.