Exploring the single-cell immune landscape of kidney allograft inflammation using imaging mass cytometry.

Kidney allograft inflammation, mostly attributed to rejection and infection, is an important cause of graft injury and loss. Standard histopathological assessment of allograft inflammation provides limited insights into biological processes and the immune landscape. Here, using imaging mass cytometry with a panel of 28 validated biomarkers, we explored the single-cell landscape of kidney allograft inflammation in 32 kidney transplant biopsies and 247 high-dimensional histopathology images of various phenotypes of allograft inflammation (antibody-mediated rejection, T cell-mediated rejection, BK nephropathy, and chronic pyelonephritis). Using novel analytical tools, for cell segmentation, we segmented over 900 000 cells and developed a tissue-based classifier using over 3000 manually annotated kidney microstructures (glomeruli, tubules, interstitium, and arteries). Using PhenoGraph, we identified 11 immune and 9 nonimmune clusters and found a high prevalence of memory T cell and macrophage-enriched immune populations across phenotypes. Additionally, we trained a machine learning classifier to identify spatial biomarkers that could discriminate between the different allograft inflammatory phenotypes. Further validation of imaging mass cytometry in larger cohorts and with more biomarkers will likely help interrogate kidney allograft inflammation in more depth than has been possible to date.

Picosecond Infrared Laser Mass Spectrometry Identifies a Metabolite Array for 10 s Diagnosis of Select Skin Cancer Types: A Proof-of-Concept Feasibility Study.

Currently, a large number of skin biopsies are taken for each true skin cancer case detected, creating a need for a rapid, high sensitivity, and specificity skin cancer detection tool to reduce the number of unnecessary biopsies taken from benign tissue. Picosecond infrared laser mass spectrometry (PIRL-MS) using a hand-held sampling probe is reported to detect and classify melanoma, squamous cell carcinoma, and normal skin with average sensitivity and specificity values of 86-95% and 91-98%, respectively (at a 95% confidence level) solely requiring 10 s or less of total data collection and analysis time. Classifications are not adversely affected by specimen's quantity of melanin pigments and are mediated by a number of metabolic lipids, further identified herein as potential biomarkers for skin cancer-type differentiation, 19 of which were sufficient here (as a fully characterized metabolite array) to provide high specificity and sensitivity classification of skin cancer types. In situ detection was demonstrated in an intradermal melanoma mouse model wherein in vivo sampling did not cause significant discomfort. PIRL-MS sampling is further shown to be compatible with downstream gross histopathologic evaluations despite loss of tissue from the immediate laser sampling site(s) and can be configured using selective laser pulses to avoid thermal damage to normal skin. Therefore, PIRL-MS may be employed as a decision-support tool to reduce both the subjectivity of clinical diagnosis and the number of unnecessary biopsies currently required for skin cancer screening.

Mass Spectrometry Imaging Reveals a Gradient of Cancer-like Metabolic States in the Vicinity of Cancer Not Seen in Morphometric Margins from Microscopy.

Spatially resolved ambient mass spectrometry imaging methods have gained popularity to characterize cancer sites and their borders using molecular changes in the lipidome. This utility, however, is predicated on metabolic homogeneity at the border, which would create a sharp molecular transition at the morphometric borders. We subjected murine models of human medulloblastoma brain cancer to mass spectrometry imaging, a technique that provides a direct readout of tissue molecular content in a spatially resolved manner. We discovered a distance-dependent gradient of cancer-like lipid molecule profiles in the brain tissue within 1.2 mm of the cancer border, suggesting that a cancer-like state progresses beyond the histologic border, into the healthy tissue. The results were further corroborated using orthogonal liquid chromatography and mass spectrometry (LC-MS) analysis of selected tissue regions subjected to laser capture microdissection. LC-MS/MS analysis for robust identification of the affected molecules implied changes in a number of different lipid classes, some of which are metabolized from the essential docosahexaenoic fatty acid (DHA) present in the interstitial fluid. Metabolic molecular borders are thus not as sharp as morphometric borders, and mass spectrometry imaging can reveal molecular nuances not observed with microscopy. Caution must be exercised in interpreting multimodal imaging results stipulated on a coincidental relationship between metabolic and morphometric borders of cancer, at least within animal models used in preclinical research.

Oncogenic ETS fusions promote DNA damage and proinflammatory responses via pericentromeric RNAs in extracellular vesicles.

Aberrant expression of the E26 transformation-specific (ETS) transcription factors characterizes numerous human malignancies. Many of these proteins, including EWS:FLI1 and EWS:ERG fusions in Ewing sarcoma (EwS) and TMPRSS2:ERG in prostate cancer (PCa), drive oncogenic programs via binding to GGAA repeats. We report here that both EWS:FLI1 and ERG bind and transcriptionally activate GGAA-rich pericentromeric heterochromatin. The respective pathogen-like HSAT2 and HSAT3 RNAs, together with LINE, SINE, ERV, and other repeat transcripts, are expressed in EwS and PCa tumors, secreted in extracellular vesicles (EVs), and are highly elevated in plasma of patients with EwS with metastatic disease. High human satellite 2 and 3 (HSAT2,3) levels in EWS:FLI1- or ERG-expressing cells and tumors were associated with induction of G2/M checkpoint, mitotic spindle, and DNA damage programs. These programs were also activated in EwS EV-treated fibroblasts, coincident with accumulation of HSAT2,3 RNAs, proinflammatory responses, mitotic defects, and senescence. Mechanistically, HSAT2,3-enriched cancer EVs induced cGAS-TBK1 innate immune signaling and formation of cytosolic granules positive for double-strand RNAs, RNA-DNA, and cGAS. Hence, aberrantly expressed ETS proteins derepress pericentromeric heterochromatin, yielding pathogenic RNAs that transmit genotoxic stress and inflammation to local and distant sites. Monitoring HSAT2,3 plasma levels and preventing their dissemination may thus improve therapeutic strategies and blood-based diagnostics.

Cytokines and Immune Cell Phenotype in Acute Kidney Injury Associated With Immune Checkpoint Inhibitors.

Introduction: Immune checkpoint inhibitors (ICIs) induce impressive antitumor responses but may lead to acute kidney injury (AKI) associated with ICI therapy (AKI-ICI). Biomarkers distinguishing AKI-ICI from AKI because of other causes (AKI-other) are currently lacking. Because ICIs block immunoregulatory pathways, we hypothesized that biomarkers related to immune cell dysregulation, including tumor necrosis factor alpha (TNF-α) and other markers of B and T cell activation in the systemic circulation and kidney tissue, may aid with the diagnosis of AKI-ICI. Methods: This is a prospective study consisting of 24 participants who presented with AKI during ICI therapy, adjudicated to either have AKI-ICI (n = 14) or AKI-other (n = 10). We compared markers of kidney inflammation and injury (neutrophil gelatinase-associated lipocalin, kidney injury molecule-1) as well as plasma and urine levels of T cell-associated cytokines (TNF-α, interferon-γ, interleukin (IL)-2, IL-4, IL-6, IL-8, IL-9, and IL-10) between groups. We also compared T-cell responses in the systemic circulation and in kidney tissue across groups, using mass cytometry systems. Results: We observed increase in several specific immune cells, including CD4 memory, T helper cells, and dendritic cells in the kidney tissue, as well as in the urine cytokines IL-2, IL-10, and TNF-α, in patients who developed AKI-ICI compared to patients with AKI-other (P < 0.05 for all). The discriminatory ability of TNF-α on AKI cause was strong (area under the curve = 0.814, 95% confidence interval: 0.623-1.00. The CD4+ T cells with memory phenotype formed the dominant subset. Conclusion: These results suggest that specific T-cell responses and their respective cytokines may be indicative of AKI associated with ICI therapy and may help to differentiate AKI-ICI from AKI-other. Urine TNF-α is a promising biomarker for AKI-ICI, which is most often caused by acute interstitial nephritis (AIN), and TNF-α pathway may serve as a potential target for therapeutic intervention.

In situ tissue pathology from spatially encoded mass spectrometry classifiers visualized in real time through augmented reality.

Integration between a hand-held mass spectrometry desorption probe based on picosecond infrared laser technology (PIRL-MS) and an optical surgical tracking system demonstrates in situ tissue pathology from point-sampled mass spectrometry data. Spatially encoded pathology classifications are displayed at the site of laser sampling as color-coded pixels in an augmented reality video feed of the surgical field of view. This is enabled by two-way communication between surgical navigation and mass spectrometry data analysis platforms through a custom-built interface. Performance of the system was evaluated using murine models of human cancers sampled in situ in the presence of body fluids with a technical pixel error of 1.0 ± 0.2 mm, suggesting a 84% or 92% (excluding one outlier) cancer type classification rate across different molecular models that distinguish cell-lines of each class of breast, brain, head and neck murine models. Further, through end-point immunohistochemical staining for DNA damage, cell death and neuronal viability, spatially encoded PIRL-MS sampling is shown to produce classifiable mass spectral data from living murine brain tissue, with levels of neuronal damage that are comparable to those induced by a surgical scalpel. This highlights the potential of spatially encoded PIRL-MS analysis for in vivo use during neurosurgical applications of cancer type determination or point-sampling in vivo tissue during tumor bed examination to assess cancer removal. The interface developed herein for the analysis and the display of spatially encoded PIRL-MS data can be adapted to other hand-held mass spectrometry analysis probes currently available.

Quantitative Visualization of Hypoxia and Proliferation Gradients Within Histological Tissue Sections.

The formation of hypoxic microenvironments within solid tumors is known to contribute to radiation resistance, chemotherapy resistance, immune suppression, increased metastasis, and an overall poor prognosis. It is therefore crucial to understand the spatial and molecular mechanisms that contribute to tumor hypoxia formation to improve the efficacy of radiation treatment, develop hypoxia-directed therapies, and increase patient survival. The objective of this study is to present a number of complementary novel methods for quantifying tumor hypoxia and proliferation in multiplexed immunofluorescence images, especially in relation to the location of perfused blood vessels. A standard marker analysis strategy is to take a positive pixel count approach, in which a threshold for positive stain is used to compute a positive area fraction for hypoxia. This work is a reassessment of that approach, utilizing not only cell segmentation but also distance to nearest blood vessel in order to incorporate spatial information into the analysis. We describe a reproducible pipeline for the visualization and quantitative analysis of hypoxia using a vessel distance analysis approach. This methodological pipeline can serve to further elucidate the relationship between vessel distance and microenvironment-linked markers such as hypoxia and proliferation, can help to quantify parameters relating to oxygen consumption and hypoxic tolerance in tissues, as well as potentially serve as a hypothesis generating tool for future studies testing hypoxia-linked markers.

Evofosfamide for the treatment of human papillomavirus-negative head and neck squamous cell carcinoma.

Evofosfamide (TH-302) is a clinical-stage hypoxia-activated prodrug of a DNA-crosslinking nitrogen mustard that has potential utility for human papillomavirus (HPV) negative head and neck squamous cell carcinoma (HNSCC), in which tumor hypoxia limits treatment outcome. We report the preclinical efficacy, target engagement, preliminary predictive biomarkers and initial clinical activity of evofosfamide for HPV-negative HNSCC. Evofosfamide was assessed in 22 genomically characterized cell lines and 7 cell line-derived xenograft (CDX), patient-derived xenograft (PDX), orthotopic, and syngeneic tumor models. Biomarker analysis used RNA sequencing, whole-exome sequencing, and whole-genome CRISPR knockout screens. Five advanced/metastatic HNSCC patients received evofosfamide monotherapy (480 mg/m2 qw × 3 each month) in a phase 2 study. Evofosfamide was potent and highly selective for hypoxic HNSCC cells. Proliferative rate was a predominant evofosfamide sensitivity determinant and a proliferation metagene correlated with activity in CDX models. Evofosfamide showed efficacy as monotherapy and with radiotherapy in PDX models, augmented CTLA-4 blockade in syngeneic tumors, and reduced hypoxia in nodes disseminated from an orthotopic model. Of 5 advanced HNSCC patients treated with evofosfamide, 2 showed partial responses while 3 had stable disease. In conclusion, evofosfamide shows promising efficacy in aggressive HPV-negative HNSCC, with predictive biomarkers in development to support further clinical evaluation in this indication.