Can somatic GATA2 mutation mimic germ line GATA2 mutation?

Somatic GATA2 mutation is associated with immunodeficiency and pulmonary alveolar proteinosis in a patient with myeloproliferative neoplasm

Microenvironmental immune cell alterations across the spectrum of nodular lymphocyte predominant Hodgkin lymphoma and T-cell/histiocyte-rich large B-cell lymphoma

BACKGROUND: The clinicopathological spectrum of nodular lymphocyte predominant Hodgkin lymphoma (NLPHL), also known as nodular lymphocyte predominant B-cell lymphoma, partially overlaps with T-cell/histiocyte-rich large B-cell lymphoma (THRLCBL). NLPHL histology may vary in architecture and B-cell/T-cell composition of the tumour microenvironment. However, the immune cell phenotypes accompanying different histological patterns remain poorly characterised. METHODS: We applied a multiplexed immunofluorescence workflow to identify differential expansion/depletion of multiple microenvironmental immune cell phenotypes between cases of NLPHL showing different histological patterns (as described by Fan et al, 2003) and cases of THRLBCL. RESULTS: FOXP3-expressing T-regulatory cells were conspicuously depleted across all NLPHL cases. As histology progressed to variant Fan patterns C and E of NLPHL and to THRLBCL, there were progressive expansions of cytotoxic granzyme-B-expressing natural killer and CD8-positive T-cells, PD1-expressing CD8-positive T-cells, and CD163-positive macrophages including a PDL1-expressing subset. These occurred in parallel to depletion of NKG2A-expressing natural killer and CD8-positive T-cells. DISCUSSION: These findings provide new insights on the immunoregulatory mechanisms involved in NLPHL and THLRBCL pathogenesis, and are supportive of an increasingly proposed biological continuum between these two lymphomas. Additionally, the findings may help establish new biomarkers of high-risk disease, which could support a novel therapeutic program of immune checkpoint interruption targeting the PD1:PDL1 and/or NKG2A:HLA-E axes in the management of high-risk NLPHL and THRLBCL

Pan-cancer deconvolution of cellular composition identifies molecular correlates of antitumour immunity and checkpoint blockade response

The nature and extent of immune cell infiltration into solid tumours are key determinants of therapeutic response. Here, using a novel DNA methylation-based approach to tumour cell fraction deconvolution, we report the integrated analysis of tumour composition and genomics across a wide spectrum of solid cancers. Initially studying head and neck squamous cell carcinoma, we identify two distinct tumour subgroups: ‘immune hot’ and ‘immune cold’, which display differing prognosis, mutation burden, cytokine signalling, cytolytic activity, and oncogenic driver events. We demonstrate the existence of such tumour subgroups pan-cancer, link clonal-neoantigen burden to hot tumours, and show that transcriptional signatures of hot tumours are selectively engaged in immunotherapy responders. We also find that treatment-naive hot tumours are markedly enriched for known immune-resistance genomic alterations and define a catalogue of novel and known mediators of active antitumour immunity, deriving biomarkers and potential targets for precision immunotherapy

Lymph node core biopsies reliably permit diagnosis of lymphoproliferative diseases. Real‐World Experience from 554 sequential core biopsies from a single centre

INTRODUCTION: Whilst excision biopsy is traditionally preferred, advances in radiological and histological techniques warrant a re-look at core biopsy as a viable primary diagnostic method. METHOD: Over a 3-year period, all patients who underwent core biopsy to investigate lymphoma at our centre were included. RESULTS: 554 consecutive patients were included (40.1% prior lymphoma and 59.4% new presentations). Three or more cores were taken in 420 (75.8%) cases. Median time from request to biopsy and biopsy to histology report was 2 (0-40) days and 7 (1-24) days respectively. 510/544 (93.8%) biopsies were diagnostic. There was no difference in whether the biopsy was diagnostic based on indication (new vs. relapsed lymphoma) (p=0.445), whether biopsy was PET-directed (p=0.507), for T-cell lymphoma (p=0.468) or nodal vs. extra-nodal (p=0.693). Thirty-eight patients (6.9%) required a second biopsy due to inadequate tissue. In a patient experience survey, only 13.9% reported any complications (1 self-limiting minor bleeding, 4 bruising) whilst 16.7% reported any discomfort beyond 12 hours. CONCLUSION: Core biopsy performed by experienced radiologists and analysed by expert haemato-pathologists is a reliable, well-tolerated method for diagnosing lymphoma and confirming relapse. Multiple cores can be obtained under local anaesthetic yielding sufficient material in the majority of cases

Functional immune characterization of HIV-associated non-small-cell lung cancer.

Dear Editor, In the combined anti-retroviral therapy (cART) era, non-small cell lung cancer (NSCLC) is a highly incident cause of morbidity and mortality in people living with HIV (PLHIV)[1]. The immune-pathogenesis of NSCLC and HIV infection both rely on programmed-death 1 (PD-1) receptor-ligand interaction as a mechanism to induce T-cell exhaustion. To date, PLHIV have been excluded from clinical trials of immune-checkpoint inhibitors (ICPI), on the presumption that anti-tumour immunity might be compromised by HIV infection. To verify this, we evaluated the clinico-pathologic significance of PD-ligands expression in a consecutive series of 221 archival NSCLC samples, 24 of which were HIV-associated (Table S1)

Self-supervised deep learning for highly efficient spatial immunophenotyping

Background: Efficient biomarker discovery and clinical translation depend on the fast and accurate analytical output from crucial technologies such as multiplex imaging. However, reliable cell classification often requires extensive annotations. Label-efficient strategies are urgently needed to reveal diverse cell distribution and spatial interactions in large-scale multiplex datasets. / Methods: This study proposed Self-supervised Learning for Antigen Detection (SANDI) for accurate cell phenotyping while mitigating the annotation burden. The model first learns intrinsic pairwise similarities in unlabelled cell images, followed by a classification step to map learnt features to cell labels using a small set of annotated references. We acquired four multiplex immunohistochemistry datasets and one imaging mass cytometry dataset, comprising 2825 to 15,258 single-cell images to train and test the model. / Findings: With 1% annotations (18–114 cells), SANDI achieved weighted F1-scores ranging from 0.82 to 0.98 across the five datasets, which was comparable to the fully supervised classifier trained on 1828–11,459 annotated cells (−0.002 to −0.053 of averaged weighted F1-score, Wilcoxon rank-sum test, P = 0.31). Leveraging the immune checkpoint markers stained in ovarian cancer slides, SANDI-based cell identification reveals spatial expulsion between PD1-expressing T helper cells and T regulatory cells, suggesting an interplay between PD1 expression and T regulatory cell-mediated immunosuppression. / Interpretation: By striking a fine balance between minimal expert guidance and the power of deep learning to learn similarity within abundant data, SANDI presents new opportunities for efficient, large-scale learning for histology multiplex imaging data. / Funding: This study was funded by the Royal Marsden/ ICR National Institute of Health Research Biomedical Research Centre

Phenotypic Characteristics of the Tumour Microenvironment in Primary and Secondary Hepatocellular Carcinoma

(1) Background: The intra-tumoural heterogeneity (ITH) of hepatocellular carcinoma (HCC) and its microenvironment (TME) across primary and secondary disease is poorly characterised. (2) Methods: Intra-tumoural (IT) and peri-tumoural (PT) staining of matched primary and secondary samples was conducted to evaluate the distribution of CD4+/FOXP3+ and CD8+/PD1+ T-cells. Samples underwent PD-L1/2 immunostaining, tumour mutational burden (TMB) evaluation, and high-resolution T-cell receptor (TCR) sequencing to derive T-cell clonality and targeted transcriptomics. (3) Results: We analysed 24 samples from matched primary (n = 11) and secondary (n = 13; 5 synchronous, 6 metachronous) deposits, 11 being extrahepatic (84.6%). IT CD8+ density was lower than PT in both primary (p = 0.005) and secondary deposits (p = 0.01), consistent with immune exclusion. PD-L1+ tumours displayed higher IT and PT CD8+/PD1+ cell density compared to PD-L1- (p < 0.05), and primary IT infiltrate was enriched in CD4+/FOXP3+ cells, compared to PT regions (p = 0.004). TCR-sequencing demonstrated enrichment of the top T-cell clonotype in secondary versus primary HCC (p = 0.02), without differences in overall productive clonality (p = 0.35). TMB was similar across primary versus secondary HCC (p = 0.95). While directed gene set analysis demonstrated the uniformity of transcriptional signatures of individual immune cell types, secondary deposits demonstrated higher COLEC12 (p = 0.004), CCL26 (p = 0.02), CD1E (p = 0.02) and CD36 (p = 0.03) expression with downregulation of CXCL1 (p = 0.03), suggesting differential regulation of innate immunity. (4) Conclusion: Immune exclusion is a defining feature of the HCC TME. Despite evidence of homogeneity in somatic TMB, secondary HCC is characterised by the expansion of a distinct T-cell clonotype and differential regulation of innate immune pathways