Multiplexed spatial profiling of Hodgkin Reed-Sternberg cell neighborhoods in classic Hodgkin lymphoma.

PURPOSE: Classic Hodgkin lymphoma (cHL) is a B cell lymphoma that occurs primarily in young adults and, less frequently, in elderly individuals. A hallmark of cHL is the exceptional scarcity (1-5%) of the malignant Hodgkin Reed-Sternberg (HRS) cells within a network of non-malignant immune cells. Molecular determinants governing the relationship between HRS cells and their proximal microenvironment remain largely unknown. EXPERIMENTAL DESIGN: We performed spatially resolved multiplexed protein imaging and transcriptomic sequencing to characterize HRS cell states, cellular neighborhoods, and gene expression signatures of 23.6 million cells from 36 newly diagnosed Epstein-Barr virus (EBV) positive and EBV-negative cHL tumors. RESULTS: We show that MHC-I expression on HRS cells is associated with immune inflamed neighborhoods containing CD8+ T cells, MHC-II+ macrophages, and immune checkpoint expression (i.e., PD-1 and VISTA). We identified spatial clustering of HRS cells, consistent with the syncytial variant of cHL, and its association with T cell excluded neighborhoods in a subset of EBV-negative tumors. Finally, a subset of both EBV-positive and EBV-negative tumors contained regulatory T cells high neighborhoods harboring HRS cells with augmented proliferative capacity. CONCLUSIONS: Our study links HRS cell properties with distinct immunophenotypes and potential immune escape mechanisms in cHL.

Automated classification of cellular expression in multiplexed imaging data with Nimbus.

Multiplexed imaging offers a powerful approach to characterize the spatial topography of tissues in both health and disease. To analyze such data, the specific combination of markers that are present in each cell must be enumerated to enable accurate phenotyping, a process that often relies on unsupervised clustering. We constructed the Pan-Multiplex (Pan-M) dataset containing 197 million distinct annotations of marker expression across 15 different cell types. We used Pan-M to create Nimbus, a deep learning model to predict marker positivity from multiplexed image data. Nimbus is a pre-trained model that uses the underlying images to classify marker expression across distinct cell types, from different tissues, acquired using different microscope platforms, without requiring any retraining. We demonstrate that Nimbus predictions capture the underlying staining patterns of the full diversity of markers present in Pan-M. We then show how Nimbus predictions can be integrated with downstream clustering algorithms to robustly identify cell subtypes in image data. We have open-sourced Nimbus and Pan-M to enable community use at https://github.com/angelolab/Nimbus-Inference.

Nivolumab for mismatch-repair-deficient or hypermutated gynecologic cancers: a phase 2 trial with biomarker analyses.

Programmed death-1 (PD-1) inhibitors are approved for therapy of gynecologic cancers with DNA mismatch repair deficiency (dMMR), although predictors of response remain elusive. We conducted a single-arm phase 2 study of nivolumab in 35 patients with dMMR uterine or ovarian cancers. Co-primary endpoints included objective response rate (ORR) and progression-free survival at 24 weeks (PFS24). Secondary endpoints included overall survival (OS), disease control rate (DCR), duration of response (DOR) and safety. Exploratory endpoints included biomarkers and molecular correlates of response. The ORR was 58.8% (97.5% confidence interval (CI): 40.7-100%), and the PFS24 rate was 64.7% (97.5% one-sided CI: 46.5-100%), meeting the pre-specified endpoints. The DCR was 73.5% (95% CI: 55.6-87.1%). At the median follow-up of 42.1 months (range, 8.9-59.8 months), median OS was not reached. One-year OS rate was 79% (95% CI: 60.9-89.4%). Thirty-two patients (91%) had a treatment-related adverse event (TRAE), including arthralgia (n = 10, 29%), fatigue (n = 10, 29%), pain (n = 10, 29%) and pruritis (n = 10, 29%); most were grade 1 or grade 2. Ten patients (29%) reported a grade 3 or grade 4 TRAE; no grade 5 events occurred. Exploratory analyses show that the presence of dysfunctional (CD8+PD-1+) or terminally dysfunctional (CD8+PD-1+TOX+) T cells and their interaction with programmed death ligand-1 (PD-L1)+ cells were independently associated with PFS24. PFS24 was associated with presence of MEGF8 or SETD1B somatic mutations. This trial met its co-primary endpoints (ORR and PFS24) early, and our findings highlight several genetic and tumor microenvironment parameters associated with response to PD-1 blockade in dMMR cancers, generating rationale for their validation in larger cohorts.ClinicalTrials.gov identifier: NCT03241745 .

Immune-Related Colitis Is Associated with Fecal Microbial Dysbiosis and Can Be Mitigated by Fecal Microbiota Transplantation.

Colitis induced by treatment with immune-checkpoint inhibitors (ICI), termed irColitis, is a substantial cause of morbidity complicating cancer treatment. We hypothesized that abnormal fecal microbiome features would be present at the time of irColitis onset and that restoring the microbiome with fecal transplant from a healthy donor would mitigate disease severity. Herein, we present fecal microbiota profiles from 18 patients with irColitis from a single center, 5 of whom were treated with healthy-donor fecal microbial transplantation (FMT). Although fecal samples collected at onset of irColitis had comparable α-diversity to that of comparator groups with gastrointestinal symptoms, irColitis was characterized by fecal microbial dysbiosis. Abundances of Proteobacteria were associated with irColitis in multivariable analyses. Five patients with irColitis refractory to steroids and biologic anti-inflammatory agents received healthy-donor FMT, with initial clinical improvement in irColitis symptoms observed in four of five patients. Two subsequently exhibited recurrence of irColitis symptoms following courses of antibiotics. Both received a second "salvage" FMT that was, again, followed by clinical improvement of irColitis. In summary, we observed distinct microbial community changes that were present at the time of irColitis onset. FMT was followed by clinical improvements in several cases of steroid- and biologic-agent-refractory irColitis. Strategies to restore or prevent microbiome dysbiosis in the context of immunotherapy toxicities should be further explored in prospective clinical trials.

Integration of peripheral blood- and tissue-based biomarkers of response to immune checkpoint blockade in urothelial carcinoma.

As predictive biomarkers of response to immune checkpoint inhibitors (ICIs) remain a major unmet clinical need in patients with urothelial carcinoma (UC), we sought to identify tissue-based immune biomarkers of clinical benefit to ICIs using multiplex immunofluorescence and to integrate these findings with previously identified peripheral blood biomarkers of response. Fifty-five pretreatment and 12 paired on-treatment UC specimens were identified from patients treated with nivolumab with or without ipilimumab. Whole tissue sections were stained with a 12-plex mIF panel, including CD8, PD-1/CD279, PD-L1/CD274, CD68, CD3, CD4, FoxP3, TCF1/7, Ki67, LAG-3, MHC-II/HLA-DR, and pancytokeratin+SOX10 to identify over three million cells. Immune tissue densities were compared to progression-free survival (PFS) and best overall response (BOR) by RECIST version 1.1. Correlation coefficients were calculated between tissue-based and circulating immune populations. The frequency of intratumoral CD3+ LAG-3+ cells was higher in responders compared to nonresponders (p = 0.0001). LAG-3+ cellular aggregates were associated with response, including CD3+ LAG-3+ in proximity to CD3+ (p = 0.01). Exploratory multivariate modeling showed an association between intratumoral CD3+ LAG-3+ cells and improved PFS independent of prognostic clinical factors (log HR -7.0; 95% confidence interval [CI] -12.7 to -1.4), as well as established biomarkers predictive of ICI response (log HR -5.0; 95% CI -9.8 to -0.2). Intratumoral LAG-3+ immune cell populations warrant further study as a predictive biomarker of clinical benefit to ICIs. Differences in LAG-3+ lymphocyte populations across the intratumoral and peripheral compartments may provide complementary information that could inform the future development of multimodal composite biomarkers of ICI response. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

GABA Regulates Electrical Activity and Tumor Initiation in Melanoma.

Oncogenes can initiate tumors only in certain cellular contexts, which is referred to as oncogenic competence. In melanoma, whether cells in the microenvironment can endow such competence remains unclear. Using a combination of zebrafish transgenesis coupled with human tissues, we demonstrate that GABAergic signaling between keratinocytes and melanocytes promotes melanoma initiation by BRAFV600E. GABA is synthesized in melanoma cells, which then acts on GABA-A receptors in keratinocytes. Electron microscopy demonstrates specialized cell-cell junctions between keratinocytes and melanoma cells, and multielectrode array analysis shows that GABA acts to inhibit electrical activity in melanoma/keratinocyte cocultures. Genetic and pharmacologic perturbation of GABA synthesis abrogates melanoma initiation in vivo. These data suggest that GABAergic signaling across the skin microenvironment regulates the ability of oncogenes to initiate melanoma. SIGNIFICANCE: This study shows evidence of GABA-mediated regulation of electrical activity between melanoma cells and keratinocytes, providing a new mechanism by which the microenvironment promotes tumor initiation. This provides insights into the role of the skin microenvironment in early melanomas while identifying GABA as a potential therapeutic target in melanoma. See related commentary by Ceol, p. 2128. This article is featured in Selected Articles from This Issue, p. 2109.

A spatially resolved timeline of the human maternal-fetal interface.

Beginning in the first trimester, fetally derived extravillous trophoblasts (EVTs) invade the uterus and remodel its spiral arteries, transforming them into large, dilated blood vessels. Several mechanisms have been proposed to explain how EVTs coordinate with the maternal decidua to promote a tissue microenvironment conducive to spiral artery remodelling (SAR)1-3. However, it remains a matter of debate regarding which immune and stromal cells participate in these interactions and how this evolves with respect to gestational age. Here we used a multiomics approach, combining the strengths of spatial proteomics and transcriptomics, to construct a spatiotemporal atlas of the human maternal-fetal interface in the first half of pregnancy. We used multiplexed ion beam imaging by time-of-flight and a 37-plex antibody panel to analyse around 500,000 cells and 588 arteries within intact decidua from 66 individuals between 6 and 20 weeks of gestation, integrating this dataset with co-registered transcriptomics profiles. Gestational age substantially influenced the frequency of maternal immune and stromal cells, with tolerogenic subsets expressing CD206, CD163, TIM-3, galectin-9 and IDO-1 becoming increasingly enriched and colocalized at later time points. By contrast, SAR progression preferentially correlated with EVT invasion and was transcriptionally defined by 78 gene ontology pathways exhibiting distinct monotonic and biphasic trends. Last, we developed an integrated model of SAR whereby invasion is accompanied by the upregulation of pro-angiogenic, immunoregulatory EVT programmes that promote interactions with the vascular endothelium while avoiding the activation of maternal immune cells.

Stem cell-like T cell depletion in the recurrent head and neck cancer immune microenvironment.

Human papilloma virus (HPV)-related oncogenesis in head and neck cancer establishes a local microenvironment rich with immune cells, however the composition of the microenvironment in recurrent disease following definitive treatment is poorly understood. Here, we investigate the composition and spatial relationships between tumor and immune cells in recurrent head and neck cancer following curative intent chemoradiotherapy. Multiplexed immunofluorescence with 12 unique markers, through two multiplex immunofluorescent panels, was performed to evaluate 27 tumor samples including 18 pre-treatment primary and 9 paired recurrent tumors. Tumor and immune cell populations were phenotyped and quantified using a previously validated semi-automated digital pathology platform for cell segmentation. Spatial analysis was conducted by evaluating immune cells within the tumor, peri-tumoral stroma, and distant stroma. Initial tumors in patients with subsequent recurrence were found to be enriched in tumor associated macrophages and displayed an immune excluded spatial distribution. Recurrent tumors after chemoradiation were hypo-inflamed, with a statistically significant reduction in the recently identified stem-like TCF1+ CD8 T-cells, which normally function to maintain HPV-specific immune responses in the setting of chronic antigen exposure. Our findings indicate that the tumor microenvironment of recurrent HPV-related head and neck cancers displays a reduction in stem-like T cells, consistent with an immune microenvironment with a reduced ability to mount T-cell-driven anti-tumor immune responses.

Tissue-specific features of the T cell repertoire after allogeneic hematopoietic cell transplantation in human and mouse.

T cells are the central drivers of many inflammatory diseases, but the repertoire of tissue-resident T cells at sites of pathology in human organs remains poorly understood. We examined the site-specificity of T cell receptor (TCR) repertoires across tissues (5 to 18 tissues per patient) in prospectively collected autopsies of patients with and without graft-versus-host disease (GVHD), a potentially lethal tissue-targeting complication of allogeneic hematopoietic cell transplantation, and in mouse models of GVHD. Anatomic similarity between tissues was a key determinant of TCR repertoire composition within patients, independent of disease or transplant status. The T cells recovered from peripheral blood and spleens in patients and mice captured a limited portion of the TCR repertoire detected in tissues. Whereas few T cell clones were shared across patients, motif-based clustering revealed shared repertoire signatures across patients in a tissue-specific fashion. T cells at disease sites had a tissue-resident phenotype and were of donor origin based on single-cell chimerism analysis. These data demonstrate the complex composition of T cell populations that persist in human tissues at the end stage of an inflammatory disorder after lymphocyte-directed therapy. These findings also underscore the importance of studying T cell in tissues rather than blood for tissue-based pathologies and suggest the tissue-specific nature of both the endogenous and posttransplant T cell landscape.

Moving Spatially Resolved Multiplexed Protein Profiling toward Clinical Oncology.

The shift in cancer therapy from broadly cytotoxic agents toward "personalized" treatments that target specific alterations in each patient's tumor requires diagnostic pathology approaches that are quantitative and biospecimen-friendly. Novel multiplexed antibody-based imaging technologies can measure single-cell expression of over 60 proteins in intact tumor sections and hold promise for clinical oncology.

Cross-platform dataset of multiplex fluorescent cellular object image annotations.

Defining cellular and subcellular structures in images, referred to as cell segmentation, is an outstanding obstacle to scalable single-cell analysis of multiplex imaging data. While advances in machine learning-based segmentation have led to potentially robust solutions, such algorithms typically rely on large amounts of example annotations, known as training data. Datasets consisting of annotations which are thoroughly assessed for quality are rarely released to the public. As a result, there is a lack of widely available, annotated data suitable for benchmarking and algorithm development. To address this unmet need, we release 105,774 primarily oncological cellular annotations concentrating on tumor and immune cells using over 40 antibody markers spanning three fluorescent imaging platforms, over a dozen tissue types and across various cellular morphologies. We use readily available annotation techniques to provide a modifiable community data set with the goal of advancing cellular segmentation for the greater imaging community.

T cell immunotherapies engage neutrophils to eliminate tumor antigen escape variants.

Cancer immunotherapies, including adoptive T cell transfer, can be ineffective because tumors evolve to display antigen-loss-variant clones. Therapies that activate multiple branches of the immune system may eliminate escape variants. Here, we show that melanoma-specific CD4+ T cell therapy in combination with OX40 co-stimulation or CTLA-4 blockade can eradicate melanomas containing antigen escape variants. As expected, early on-target recognition of melanoma antigens by tumor-specific CD4+ T cells was required. Surprisingly, complete tumor eradication was dependent on neutrophils and partly dependent on inducible nitric oxide synthase. In support of these findings, extensive neutrophil activation was observed in mouse tumors and in biopsies of melanoma patients treated with immune checkpoint blockade. Transcriptomic and flow cytometry analyses revealed a distinct anti-tumorigenic neutrophil subset present in treated mice. Our findings uncover an interplay between T cells mediating the initial anti-tumor immune response and neutrophils mediating the destruction of tumor antigen loss variants.

Deep Learning-Inferred Multiplex ImmunoFluorescence for Immunohistochemical Image Quantification.

Reporting biomarkers assessed by routine immunohistochemical (IHC) staining of tissue is broadly used in diagnostic pathology laboratories for patient care. To date, clinical reporting is predominantly qualitative or semi-quantitative. By creating a multitask deep learning framework referred to as DeepLIIF, we present a single-step solution to stain deconvolution/separation, cell segmentation, and quantitative single-cell IHC scoring. Leveraging a unique de novo dataset of co-registered IHC and multiplex immunofluorescence (mpIF) staining of the same slides, we segment and translate low-cost and prevalent IHC slides to more expensive-yet-informative mpIF images, while simultaneously providing the essential ground truth for the superimposed brightfield IHC channels. Moreover, a new nuclear-envelop stain, LAP2beta, with high (>95%) cell coverage is introduced to improve cell delineation/segmentation and protein expression quantification on IHC slides. By simultaneously translating input IHC images to clean/separated mpIF channels and performing cell segmentation/classification, we show that our model trained on clean IHC Ki67 data can generalize to more noisy and artifact-ridden images as well as other nuclear and non-nuclear markers such as CD3, CD8, BCL2, BCL6, MYC, MUM1, CD10, and TP53. We thoroughly evaluate our method on publicly available benchmark datasets as well as against pathologists' semi-quantitative scoring. The code, the pre-trained models, along with easy-to-run containerized docker files as well as Google CoLab project are available at https://github.com/nadeemlab/deepliif.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer.

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

Sotigalimab and/or nivolumab with chemotherapy in first-line metastatic pancreatic cancer: clinical and immunologic analyses from the randomized phase 2 PRINCE trial.

Chemotherapy combined with immunotherapy has improved the treatment of certain solid tumors, but effective regimens remain elusive for pancreatic ductal adenocarcinoma (PDAC). We conducted a randomized phase 2 trial evaluating the efficacy of nivolumab (nivo; anti-PD-1) and/or sotigalimab (sotiga; CD40 agonistic antibody) with gemcitabine/nab-paclitaxel (chemotherapy) in patients with first-line metastatic PDAC ( NCT03214250 ). In 105 patients analyzed for efficacy, the primary endpoint of 1-year overall survival (OS) was met for nivo/chemo (57.7%, P = 0.006 compared to historical 1-year OS of 35%, n = 34) but was not met for sotiga/chemo (48.1%, P = 0.062, n = 36) or sotiga/nivo/chemo (41.3%, P = 0.223, n = 35). Secondary endpoints were progression-free survival, objective response rate, disease control rate, duration of response and safety. Treatment-related adverse event rates were similar across arms. Multi-omic circulating and tumor biomarker analyses identified distinct immune signatures associated with survival for nivo/chemo and sotiga/chemo. Survival after nivo/chemo correlated with a less suppressive tumor microenvironment and higher numbers of activated, antigen-experienced circulating T cells at baseline. Survival after sotiga/chemo correlated with greater intratumoral CD4 T cell infiltration and circulating differentiated CD4 T cells and antigen-presenting cells. A patient subset benefitting from sotiga/nivo/chemo was not identified. Collectively, these analyses suggest potential treatment-specific correlates of efficacy and may enable biomarker-selected patient populations in subsequent PDAC chemoimmunotherapy trials.

Tumor Immune Microenvironment and Response to Neoadjuvant Chemotherapy in Hormone Receptor/HER2+ Early Stage Breast Cancer.

BACKGROUND: Pathologic response at the time of surgery after neoadjuvant therapy for HER2 positive early breast cancer impacts both prognosis and subsequent adjuvant therapy. Comprehensive descriptions of the tumor microenvironment (TME) in patients with HER2 positive early breast cancer is not well described. We utilized standard stromal pathologist-assessed tumor infiltrating lymphocyte (TIL) quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. METHODS: We utilized standard stromal pathologist-assessed TIL quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in 28 patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. RESULTS: Pathologist-assessed stromal TILs were significantly associated with pathologic complete response (pCR). By quantitative multiplex immunofluorescence, univariate analysis revealed significant increases in CD3+, CD3+CD8-FOXP3-, CD8+ and FOXP3+ T-cell densities as well as increased immune cell aggregates in pCR patients. In subsets of paired pre/post-treatment samples, we observed significant changes in gene expression signatures in non-pCR patients and significant decreases in CD8+ densities after treatment in pCR patients. No RNA based pathway signature was associated with pCR. CONCLUSION: TME characterization HER2 positive breast cancer patients revealed several stromal T-cell densities and immune cell aggregates associated with pCR. These results demonstrate the feasibility of these novel methods in TME evaluation and contribute to ongoing investigations of the TME in HER2+ early breast cancer to identify robust biomarkers to best identify patients eligible for systemic de-escalation strategies.

Treatment of ovarian clear cell carcinoma with immune checkpoint blockade: a case series.

BACKGROUND: Although immune checkpoint blockade has demonstrated limited effectiveness against ovarian cancer, subset analyses from completed trials suggest possible superior efficacy in the clear cell carcinoma subtype. OBJECTIVE: To describe the outcomes of patients with ovarian clear cell carcinoma treated with immune checkpoint blockade. METHODS: This was a single-institution, retrospective case series of patients with ovarian clear cell carcinoma treated with a programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibitor with or without concomitant cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibition between January 2016 and June 2021. Demographic variables, tumor microenvironment, molecular data, and clinical outcomes were examined. Time to treatment failure was defined as the number of days between start of treatment and next line of treatment or death. RESULTS: A total of 16 eligible patients were analyzed. The median treatment duration was 56 days (range 14-574); median time to treatment failure was 99 days (range 27-1568). The reason for discontinuation was disease progression in 88% of cases. Four patients (25%) experienced durable clinical benefit (time to treatment failure ≥180 days). One patient was treated twice with combined immune checkpoint blockade and experienced a complete response each time. All 12 patients who underwent clinical tumor-normal molecular profiling had microsatellite-stable disease, and all but one had low tumor mutation burden. Multiplex immunofluorescence analysis available from pre-treatment biopsies of two patients with clinical benefit demonstrated abundant tumor-infiltrating lymphocytes expressing PD-1. CONCLUSION: Our study suggests a potential role for immune checkpoint blockade in patients with clear cell carcinoma of the ovary. Identification of genetic and microenvironmental biomarkers predictive of response will be key to guide therapy.

Immune cell subsets in interface cutaneous immune-related adverse events associated with anti-PD-1 therapy resemble acute graft versus host disease more than lichen planus.

BACKGROUND: Checkpoint immunotherapy is frequently associated with cutaneous immune-related adverse events (cirAEs), and among those, the most common subtype shows interface reaction patterns that have been likened to lichen planus (LP); however, cutaneous acute graft versus host disease (aGVHD) may be a closer histopathologic comparator. We used quantitative pathology to compare the immunologic composition of anti-PD-1-associated interface reactions to LP and aGVHD to assess for similarities and differences between these cutaneous eruptions. METHODS: Immunohistochemistry for CD4, CD8, CD68, PD-1, and PD-L1 was performed on formalin-fixed paraffin-embedded tissue from patients with anti-PD-1 interface cirAEs (n = 4), LP (n = 9), or aGVHD (n = 5). Densities of immune cell subsets expressing each marker were quantified using the HALO image analysis immune cell module. Plasma cell and eosinophil density were quantified on routine H&E slides. RESULTS: Specimens from patients with anti-PD-1 interface cirAEs showed equivalent total cell densities and immune cell composition to those with aGVHD. Patients with LP showed higher total immune cell infiltration, higher absolute T-cell densities, increased CD8 proportion, and reduced histiocytic component. The cases with the highest plasma cell counts were all anti-PD-1 interface cirAEs and aGVHD. CONCLUSION: The composition of immune cell subsets in anti-PD-1 interface cirAEs more closely resembles the immune response seen in aGVHD than LP within our cohort. This warrants a closer look via advanced analytics and may have implications for shared pathogenesis and potential treatment options.

Genomic and transcriptomic analysis of a library of small cell lung cancer patient-derived xenografts.

Access to clinically relevant small cell lung cancer (SCLC) tissue is limited because surgical resection is rare in metastatic SCLC. Patient-derived xenografts (PDX) and circulating tumor cell-derived xenografts (CDX) have emerged as valuable tools to characterize SCLC. Here, we present a resource of 46 extensively annotated PDX/CDX models derived from 33 patients with SCLC. We perform multi-omic analyses, using targeted tumor next-generation sequencing, RNA-sequencing, and immunohistochemistry to deconvolute the mutational landscapes, global expression profiles, and molecular subtypes of these SCLC models. SCLC subtypes characterized by transcriptional regulators, ASCL1, NEUROD1 and POU2F3 are confirmed in this cohort. A subset of SCLC clinical specimens, including matched PDX/CDX and clinical specimen pairs, confirm that the primary features and genomic and proteomic landscapes of the tumors of origin are preserved in the derivative PDX models. This resource provides a powerful system to study SCLC biology.