Characterization of pediatric non-hematopoietic tumor metastases to the central nervous system: A single institution review

Central nervous system (CNS) metastases represent a small portion of pediatric CNS neoplasms and data surrounding this condition with high morbidity is scarce. Single institutional archival institutional pathology records between 1999 and 2022 were searched for patients over 21 years old and younger with CNS, dura, cranial nerve, CSF, or leptomeningeal metastases; 41 cases were identified. We documented primary tumor types and locations, metastasis locations, types of invasion (direct extension vs distant metastasis), times from imaging or pathologic diagnosis to CNS involvement, and outcomes. Distant metastasis was the most common mechanism of metastasis (n = 32, 78%). Interval times to CNS metastasis varied by both tumor type and primary tumor location. In this cohort, osteosarcoma portended the shortest survival following CNS metastasis. This study highlights the diverse mechanisms and locations of CNS involvement in pediatric CNS metastases and illuminates a need for varied monitoring strategies when considering primary tumor type and anatomic location.

An immunosuppressed microenvironment distinguishes lateral ventricle-contacting glioblastomas

Radiographic contact of glioblastoma (GBM) tumors with the lateral ventricle and adjacent stem cell niche correlates with poor patient prognosis, but the cellular basis of this difference is unclear. Here, we reveal and functionally characterize distinct immune microenvironments that predominate in subtypes of GBM distinguished by proximity to the lateral ventricle. Mass cytometry analysis of IDH-wildtype human tumors identified elevated T cell checkpoint receptor expression and greater abundance of a specific CD32+CD44+HLA-DRhigh macrophage population in ventricle-contacting GBM. Multiple computational analysis approaches, phospho-specific cytometry, and focal resection of GBMs confirmed and extended these findings. Phospho-flow quantified cytokine-induced immune cell signaling in ventricle-contacting GBM revealing differential signaling between GBM subtypes. Subregion analysis within a given tumor supported initial findings and revealed intratumoral compartmentalization of T cell memory and exhaustion phenotypes within GBM subtypes. Collectively, these results characterize immunotherapeutically targetable features of macrophages and suppressed lymphocytes in glioblastomas defined by MRI-detectable lateral ventricle contact.

TMIC-26. USING INTEGRATED MULTIDIMENSIONAL MASS CYTOMETRY AND MULTIPLEX IMMUNOHISTOCHEMISTRY TO INFER SPATIAL RELATIONSHIPS BETWEEN PHENOTYPICALLY DISTINCT GLIOBLASTOMA INFILTRATING IMMUNE CELLS

Glioblastomas (GBM) account for ~60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit; however, no predictive immune features have informed therapeutic stratification. Radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse prognosis compared to patients with ventricle non-contacting GBM (NC-GBM), yet the influence of ventricle contact on anti-tumor immunity is unknown. This study characterized the GBM immune microenvironment and identified targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM patients.Primary glioblastoma tissue was provided with written informed consent in accordance with the Declaration of Helsinki and with approval of the Vanderbilt Institutional Review Board (IRB #131870). Seventeen patients presented with primary, IDH-wildtype C-GBM and 15 with NC-GBM. Machine learning integrated mass cytometry and matched multiplex immunohistochemistry on FFPE embedded tissue to identify phenotypic, functional, and spatial biomarkers correlating with patient outcome. C-GBM tumors were enriched in STAT3-driven CD32+CD44+HLA-DR+ monocyte-derived macrophages (MDM) compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p< 0.001) and depleted in lymphocytes (2.9 ± 1% vs. 7.6 ± 2%; p< 0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p< 0.001). Exhausted T cells in C-GBM co-expressed checkpoint receptors PD-1 and TIGIT. K-means clustering identified 10 immunological niches in GBM. Macrophage-tumor niches were most common in C-GBM (17.93% of niches), followed by T cell-microglia-tumor niches (17.72%). Within NC-GBM niches, T cell-T cell interactions were more prevalent (log odds ratio = 0.90) and correlated with improved outcome.These findings suggest that factors within the periventricular space negatively influence the immune microenvironment within GBM tumors. Clinically targetable immune biomarkers were identified in C-GBM. Notably, radiologic assessment of lateral ventricle contact may guide clinical trial design for immunotherapies in neuro-oncology based on tumor proximity to the ventricle wall.

Histological changes associated with laser interstitial thermal therapy for radiation necrosis: illustrative cases

BACKGROUND

Patients with lung cancer and melanoma remain the two largest groups to develop brain metastases. Immunotherapy has been approved for treatment of stage IV disease in both groups. Many of these patients are additionally treated with stereotactic radiosurgery for their brain metastases during ongoing immunotherapy. Use of immunotherapy has been reported to increase the rates of radiation necrosis (RN) after radiosurgery, causing neurological compromise due to growth of the enhancing lesion as well as worsening of associated cerebral edema.

OBSERVATIONS

Laser interstitial thermal therapy (LITT) is a surgical approach that has been shown effective in the management of RN, especially given its efficacy in early reduction of perilesional edema. However, little remains known about the pathology of the post-LITT lesions and how LITT works in this condition. Here, we present two patients who needed surgical decompression after LITT for RN. Clinical, histopathological, and imaging features of both patients are presented.

LESSONS

Criteria for selecting the best patients with RN for LITT therapy remains unclear. Given two similarly sized lesions and not too dissimilar clinical histories but with differing outcomes, further investigation is clearly needed to identify predictors of response to LITT in the setting of SRS and immunotherapy-induced RN.

Development of an immunohistochemical assay for Siglec-15

Siglec-15, a member of sialic-acid binding immunoglobulin type lectins, is normally expressed by myeloid cells and upregulated in some human cancers and represents a promising new target for immunotherapy. While PD-L1 blockade is an important strategy for immunotherapy, its effectiveness is limited. The expression of Siglec-15 has been demonstrated to be predominantly mutually exclusive to PD-L1 in certain cancer histologies. Thus, there is significant opportunity for Siglec-15 as an immunotherapeutic target for patients that do not respond to PD-1/PD-L1 inhibition. The aim of this study was to prospectively develop an immunohistochemical (IHC) assay for Siglec-15 to be used as a companion diagnostic for future clinical trials. Here, we create and validate an IHC assay with a novel recombinant antibody to the cytoplasmic domain of Siglec-15. To find an enriched target, this antibody was first used in a quantitative fluorescence (QIF) assay to screen a broad range of tumor histologies to determine tumor types where Siglec-15 demonstrated high expression. Based on this and previous data, we focused on development of a chromogenic IHC assay for lung cancer. Then we developed a scoring system for this assay that has high concordance amongst pathologist readers. We then use this chromogenic IHC assay to test the expression of Siglec-15 in two cohorts of NSCLC. We found that this assay shows a higher level of staining in both tumor and immune cells compared to previous QIF assays utilizing a polyclonal antibody. However, similar to that study, only a small percentage of positive Siglec-15 cases showed high expression for PD-L1. This validated assay for Siglec-15 expression may support development of a companion diagnostic assay to enrich for patients expressing the Siglec-15 target for therapy.

Correction to 'Tumor-selective, antigen-independent delivery of a pH sensitive peptide-topoisomerase inhibitor conjugate suppresses tumor growth without systemic toxicity'

[This corrects the article DOI: 10.1093/narcan/zcab021.].

IMMU-11. SELECTIVE ENRICHMENT OF SUPPRESSED IMMUNE CELLS IN THE TUMOR MICROENVIRONMENT CORRELATES WITH ESTABLISHMENT OF DISTINCT IMMUNOLOGIC NICHES IN HUMAN GLIOBLASTOMAS CONTACTING THE LATERAL VENTRICLE

Glioblastomas (GBM) account for 60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit in GBM patients; however, no predictive immune features currently inform therapeutic stratification in GBM. We have shown that, independently of known prognosticators, radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse prognosis compared to patients with ventricle non-contacting GBM (NC-GBM). This study sought to characterize the GBM immune microenvironment and identify targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM. Primary glioblastoma specimens were resected in accordance with the Declaration of Helsinki (IRB #131870). Twelve patients presented with C-GBM and thirteen with NC-GBM. Machine learning tools applied to mass cytometry data characterized tumor-infiltrating immune populations and identified biomarkers correlating with C-GBM and patient survival. C-GBM tumors were enriched in blood-derived macrophages compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p< 0.001) and depleted in lymphocytes (2.9 ± 1% vs. 7.6 ± 2%; p< 0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p< 0.001). Further, T cells in C-GBM co-expressed the checkpoint receptors PD-1 and TIGIT, suggesting acute T cell exhaustion. Multiplex immunohistochemistry (mxIHC) on matched FFPE tissue provided spatial context to risk-stratifying immune populations, and defined structured immunological niches within the TME. Macrophage-tumor niches were most common (36%), followed by T cell-microglia-tumor niches (26%). Within niches, T cell-T cell interactions were more prevalent (log odds ratio = 0.90) whereas T cell-macrophage interactions were less prevalent (log odds ratio = -1.61). These findings suggest that factors within the periventricular space may influence antitumor immunity within tumors, and identify clinically targetable immune biomarkers in glioblastoma. Notably, radiologic assessment of lateral ventricle contact by standard-of-care MRI may guide clinical trial design for immunotherapies in neuro-oncology.

38 Spatial immune profiling of human glioblastoma tissue reveals the presence of aggregated lymphoid niches in the tumor microenvironment

Background

Glioblastomas (GBM) account for 60% of adult primary brain tumors. With few advances in therapeutics, median overall survival remains 15-months post-diagnosis. Immunotherapies may provide therapeutic benefit in GBM patients; however, no predictive immune features currently inform therapeutic stratification in GBM. We have shown that, independently of known prognosticators, radiographic tumor contact with the lateral ventricle (C-GBM) correlates with 7-months worse survival prognosis compared to patients with ventricle non-contacting GBM (NC-GBM). This study sought to characterize the GBM immune microenvironment and identify targetable mechanisms of immunosuppression correlating with worse outcomes in C-GBM.

Methods

Twelve patients presented with pathologically confirmed primary, IDH wildtype C-GBM and thirteen with NC-GBM. Multiplex immunohistochemistry (mxIHC) was performed on formalin-fixed paraffin embedded (FFPE) tissue for each patient interrogating 8 predictive immune markers (CD3, CD4, CD8, FOXP3, CD68, IBA1, PD-1, and PD-L1). Machine learning tools characterized tumor-infiltrating immune populations and identified biomarkers correlating with C-GBM and patient survival. K-means clustering identified immunological neighborhoods within the tissue and a log odds ratio was used to quantify the likelihood of cell-cell interactions in the tissue.

Results

C-GBM tumors were enriched in monocyte-derived macrophages (MDM) compared to NC-GBM (19 ± 8% vs. 6 ± 2%; p<0.001) and depleted in lymphocytes (2.9 ± 1% vs. 7.6 ± 2%; p<0.001) and tissue-resident microglia (1.8 ± 0.3% vs. 7 ± 3%; p<0.001). Further, T cells in C-GBM co-expressed the checkpoint receptors PD-1, suggesting T cell exhaustion in the C-GBM tumor microenvironment. K-means clustering identified 10 immunological niches prevalent in GBM tissue. Macrophage-tumor niches were most common niche in the tissue accounting for 17.93% of all niches, followed by T cell-microglia-tumor niches (17.72%). Conversely, tumor-tumor niches were the least prevalent, accounting for only 2.51% of niches. Within niches, T cell-T cell interactions occurred more frequently than expected by random chance (log odds ratio = 0.90) whereas T cell-macrophage interactions occurred less frequently than expected by random chance (log odds ratio = -1.61). Pathological assessment of the tissue confirmed the presence of lymphoid aggregates in regions of myeloid exclusion in the tissue.

Conclusions

These findings suggest that factors within the periventricular space may influence antitumor immunity within GBM, and have identified clinically targetable immune biomarkers in glioblastoma. The prevalence of T cell niches in GBM tumors suggests the establishment tertiary lymphoid aggregates may be targetable to improve patient outcomes. Lastly, radiologic assessment of lateral ventricle contact by standard-of-care MRI may guide clinical trial design for immunotherapies in neuro-oncology.

Acknowledgements

This study was funded by NIH/NCI grant K00 CA212447 and supported by the Translational Pathology Shared Resource at Vanderbilt University (P30 CA068485).

Ethics Approval

Primary glioblastoma tumors obtained in accordance with the Declaration of Helsinki and with institutional IRB approval (#131870) along with patient written informed consent.

Tumor-selective, antigen-independent delivery of a pH sensitive peptide-topoisomerase inhibitor conjugate suppresses tumor growth without systemic toxicity

Topoisomerase inhibitors are potent DNA damaging agents which are widely used in oncology, and they demonstrate robust synergistic tumor cell killing in combination with DNA repair inhibitors, including poly(ADP)-ribose polymerase (PARP) inhibitors. However, their use has been severely limited by the inability to achieve a favorable therapeutic index due to severe systemic toxicities. Antibody-drug conjugates address this issue via antigen-dependent targeting and delivery of their payloads, but this approach requires specific antigens and yet still suffers from off-target toxicities. There is a high unmet need for a more universal tumor targeting technology to broaden the application of cytotoxic payloads. Acidification of the extracellular milieu arises from metabolic adaptions associated with the Warburg effect in cancer. Here we report the development of a pH-sensitive peptide-drug conjugate to deliver the topoisomerase inhibitor, exatecan, selectively to tumors in an antigen-independent manner. Using this approach, we demonstrate potent in vivo cytotoxicity, complete suppression of tumor growth across multiple human tumor models, and synergistic interactions with a PARP inhibitor. These data highlight the identification of a peptide-topoisomerase inhibitor conjugate for cancer therapy that provides a high therapeutic index, and is applicable to all types of human solid tumors in an antigen-independent manner.

The Role of Mismatch Repair in Glioblastoma Multiforme Treatment Response and Resistance

Mismatch repair (MMR) is a highly conserved DNA repair pathway that is critical for the maintenance of genomic integrity. This pathway targets base substitution and insertion-deletion mismatches, which primarily arise from replication errors that escape DNA polymerase proof-reading function. Here, the authors review key concepts in the molecular mechanisms of MMR in response to alkylation damage, approaches to detect MMR status in the clinic, and the clinical relevance of this pathway in glioblastoma multiforme treatment response and resistance.

IMMU-16. TWO DISTINCT SUBSETS OF NATURAL KILLER CELLS ARE ENRICHED IN THE TUMOR MICROENVIRONMENT AND CORRELATE WITH SURVIVAL OUTCOME IN HUMAN GLIOBLASTOMA

Glioblastomas (GBM) account for up to 60% of all adult primary brain tumors. With few advances in therapeutics, median overall survival (mOS) remains at 15-months post diagnosis. Success of immunotherapy in peripheral solid tumors may offer an alternative therapeutic approach for patients with GBM tumors; however, no predictive immune features currently inform therapeutic stratification for GBM. Recently, we have identified radiographic tumor contact with the lateral ventricle (LV) as a prognostic indicator of OS, as patients with LV+ GBM survive 7 months less than patients with LV- gliomas. This disparity was independent of known prognostic factors (e.g. KPS, extent of resection). Further, we have identified a correlation between greater immune infiltration and the frequency of tumor subtypes with more favorable prognosis. We therefore hypothesized that differences in overall survival between patients with LV+ and LV- are due, in part, to a uniquely immunosuppressive microenvironment within the LV. Using 35-parameter single-cell mass cytometry (CyTOF) we profiled the immune infiltrate of human GBM tissue acquired in accordance with the Declaration of Helsinki and with the approval of the institutional review board (IRB #131870). Computational approaches (tSNE, Citrus, RAPID) correlated natural killer (NK) cell populations correlating with prognosis. NK cells made of 1–14% of the total immune infiltrate in GBM. Ninety percent of NK cells infiltrating LV- tumors were CD16+CD56dim cytotoxic NK cells (cNK). LV+ gliomas, however, were enriched in CD16+CD56bright immunoregulatory NK cells (irNK). The presence of cNK cells correlated with a 2.5-fold improvement of OS, whereas irNK cells correlated with a 2.2-fold reduction in OS. Further, 30–60% of NK cells infiltrating LV+ tumors expressed checkpoint receptors (TIGIT, TIM3, B7-H3) compared to only 10–20% in LV- tumors. These results suggest that NK cells contribute to immunosuppression in the LV and may serve as alternative targets to T cell-based therapies for GBM.

Unilateral leg pain caused by cryptococcal myositis: An unusual presentation of disseminated cryptococcosis in a kidney transplant recipient

Cryptococcal disease is a rare but often serious infection in solid organ transplant recipients, commonly presenting as meningitis and pneumonia but can rarely cause myositis. We report the case of a 43-year-old female kidney transplant recipient with two previous graft failures requiring re-transplantations who presented with a 1-month duration of worsening unilateral leg pain, swelling, and shortness of breath. Blood cultures isolated Cryptococcus neoformans. A calf biopsy was performed and histopathology revealed myonecrosis with yeast forms consistent with Cryptococcus spp. Liposomal amphotericin B (LamB) was administered. Her course was complicated by hypoxemic respiratory failure with development of ground glass opacities on chest imaging. Work-up revealed bacterial and C neoformans pneumonia and probable Pneumocystis jirovecii pneumonia (PJP) She received trimethoprim-sulfamethoxazole and LamB and was discharged on fluconazole. Shortly thereafter she was re-admitted with confusion, septic shock, and multi-organ failure. Work-up revealed PJP with subsequent development of cryptococcal meningitis. Despite aggressive management, she expired. Disseminated cryptococcal infection may manifest as myositis. Presence of cryptococcal infection is a marker of severe net state of immunosuppression (IS), hence, presence of other opportunistic infections is likely. Early recognition of cryptococcal infection, institution of targeted therapy, and IS reduction are important to improve overall survival.

Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells

A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to generate new therapeutic and biomarker hypotheses. We introduce a machine learning algorithm, Risk Assessment Population IDentification (RAPID), that is unsupervised and automated, identifies phenotypically distinct cell populations, and determines whether these populations stratify patient survival. With a pilot mass cytometry dataset of 2 million cells from 28 glioblastomas, RAPID identified tumor cells whose abundance independently and continuously stratified patient survival. Statistical validation within the workflow included repeated runs of stochastic steps and cell subsampling. Biological validation used an orthogonal platform, immunohistochemistry, and a larger cohort of 73 glioblastoma patients to confirm the findings from the pilot cohort. RAPID was also validated to find known risk stratifying cells and features using published data from blood cancer. Thus, RAPID provides an automated, unsupervised approach for finding statistically and biologically significant cells using cytometry data from patient samples.

Single-cell systems neuroimmunology reveals a highly immunosuppressive microenvironment in human glioblastomas contacting the ventricular stem cell niche

Glioblastomas make up more than 60% of adult primary brain tumors and carry a 15 month overall survival despite aggressive standard-of-care therapy. Recent advances in immunotherapy offer an appealing alternative that may improve outcomes for patients with glioblastoma; however, clinical trials have proven unsuccessful due in part to a lack of predictive features that may inform responsiveness to immunotherapy. We have recently shown a strong correlation between 1) immune infiltration, 2) tumor cell phenotype, and 3) patient outcome. Further, patients whose tumors demonstrate radiographic contact with the ventricular-subventricular zone (V-SVZ) have reduced survival compared to patients whose tumors do not contact the V-SVZ. We therefore hypothesized that the V-SVZ acts as a previously unappreciated immunosuppressive microenvironment within the brain that promotes tumor growth by suppressing anti-tumor immunity. Primary human glioblastomas were disaggregated into single-cell suspensions and mass cytometry (CyTOF) measured &gt;30 parameters in thirteen immune populations infiltrating human glioblastomas. Cutting-edge machine-learning tools identified key differences in the abundance and phenotypes of T cells, B cells, NK cells, microglia, and peripheral macrophages infiltrating ventricle-contacting gliomas. Further, enriched expression of immune checkpoint receptors (PD-1, TIGIT, LAG-3, TIM3) correlated with ventricular contact and outcome. These results provide key insights into the immune microenvironment of glioblastomas and elucidate several clinically actionable immunotherapeutic targets that may be used to optimize treatment strategies for glioblastoma patients based on V-SVZ contact status.

Neuropathologic Changes in Sudden Unexplained Death in Childhood

Sudden unexplained death in childhood (SUDC) affects children >1-year-old whose cause of death remains unexplained following comprehensive case investigation and is often associated with hippocampal abnormalities. We prospectively performed systematic neuropathologic investigation in 20 SUDC cases, including (i) autopsy data and comprehensive ancillary testing, including molecular studies, (ii) ex vivo 3T MRI and extensive histologic brain samples, and (iii) blinded neuropathology review by 2 board-certified neuropathologists. There were 12 girls and 8 boys; median age at death was 33.3 months. Twelve had a history of febrile seizures, 85% died during apparent sleep and 80% in prone position. Molecular testing possibly explained 3 deaths and identified genetic mutations in TNNI3, RYR2, and multiple chromosomal aberrations. Hippocampal abnormalities most often affected the dentate gyrus (altered thickness, irregular configuration, and focal lack of granule cells), and had highest concordance between reviewers. Findings were identified with similar frequencies in cases with and without molecular findings. Number of seizures did not correlate with hippocampal findings. Hippocampal alterations were the most common finding on histological review but were also found in possibly explained deaths. The significance and specificity of hippocampal findings is unclear as they may result from seizures, contribute to seizure pathogenesis, or be an unrelated phenomenon.

COMP-11. SINGLE CELL MASS CYTOMETRY SIGNALING PROFILES AND A NOVEL COMPUTATIONAL TOOL IDENTIFY HIGH RISK GLIOBLASTOMA CELLS

In glioblastoma, changes in signaling, gene sequence, copy number, or transcript expression can define patient subgroups, but these subgroups are not yet associated with differential outcome for most patients with high-risk, IDH wild-type disease. Single cell interrogation of phospho-protein signaling has successfully revealed novel cell types associated with patient outcomes in blood cancers, suggesting that a comparable approach could be used in brain tumors. The goal of this study was to combine a single cell phospho-protein profiling approach with novel, automated computational analysis to identify abnormal glioblastoma cells that stratify patient clinical risk. Effective tissue dissociation strategies and validated antibody panels were created for mass cytometry analyses of resected glioblastoma tissue. These panels simultaneously measured 45 determinants of neural and glioma cell identity, including transcription factors, phospho-proteins, and surface receptors. 28 glioblastoma tumors were stained and analyzed using traditional gating, existing computational tools, and a new risk assessment population identification algorithm (RAPID, https://www.biorxiv.org/content/10.1101/632208v3). RAPID revealed two malignant cell types closely associated with differential patient outcomes. Glioblastoma negative prognostic (GNP) cells were associated with poor survival and defined by phospho-protein signaling in cells with aberrant neural developmental phenotypes. Glioblastoma positive prognostic (GPP) cells were associated with better progression free survival and defined by increased immunogenic signaling. A Cox proportional-hazards regression model was created to assess the influence of GNP and GPP cells on OS and PFS as continuous variables while accounting for other well-known clinical predictors. Each 1% increase of GNP cells was associated with an 7% increase in annual mortality rate (HR=1.07 [95% CI 1.03–1.12], p=0.001). Tumors containing GNP cells also significantly lacked CD45+ immune cell infiltration (Pearson r=-0.8). The signaling events that define these clinically significant glioblastoma cells represent a useful molecular classification, may indicate responsiveness to immunotherapy, and are themselves important targets of opportunity for new therapeutic approaches.

IMMU-37. SINGLE-CELL SYSTEMS NEUROIMMUNOLOGY REVEALS IMMUNOSUPPRESSIVE CORRELATES WITH VENTRICULAR STEM CELL NICHE CONTACT IN HUMAN GLIOBLASTOMA

Glioblastomas make up more than 60% of adult primary brain tumors and carry a median survival of less than 15 months despite aggressive standard therapy. Immunotherapy, which is now standard of care for many solid tumors, offers an appealing therapeutic approach that may improve outcomes for glioblastoma patients. Predictive features in glioblastomas that may inform responsiveness to different immunotherapeutic modalities, however, are still lacking. Recent studies have demonstrated that patients whose tumors show radiographic contact with the lateral ventricles, and thus the stem cell niche of the ventricular-subventricular zone (V-SVZ), have reduced survival outcomes compared to patients whose tumors do not contact the V-SVZ. We therefore hypothesized that tumor contact with the V-SVZ engenders a unique, immunosuppressive microenvironment that promotes tumor growth by suppressing anti-tumor immunity. Glioblastoma tumors, obtained in accordance with the Declaration of Helsinki and with institutional IRB approval (#131870, #030372, #181970), were disaggregated into single-cell suspensions and multi-dimensional single-cell mass cytometry was performed to interrogate >30 immune parameters in thirteen immune populations infiltrating human glioblastomas. Using advanced computational dimensionality-reduction tools (Citrus, t-SNE, FlowSOM, and MEM), we identified distinctions among the abundance and phenotypes of tumor-infiltrating immune cells. Firstly, on the basis of tumor contact with the V-SVZ, Citrus identified differential abundance of five T and myeloid cell subsets among glioblastomas. Secondly, differential expression of five functional immune markers was observed in seven distinct immune cell subsets infiltrating glioblastoma tumors. Further, both immune abundance and marker expression correlated with patient outcome. Manual gating analysis and parallel computational pipelines confirmed that comparable cell subsets could be identified with traditional approaches and unsupervised algorithmic analysis. These results provide key insights into the immune microenvironment of glioblastomas. In addition, several clinically actionable immunotherapeutic targets were uncovered that may be used to optimize treatment strategies for glioblastomas based on V-SVZ contact status.

Location-dependent maintenance of intrinsic susceptibility to mTORC1-driven tumorigenesis

Per-cell quantification of mTORC1 signaling activity in neural stem/progenitor cells reveals differential signaling, proliferative, and tumor-forming capability between dorsal and ventral cells within a single niche.

Neural stem/progenitor cells (NSPCs) of the ventricular–subventricular zone (V-SVZ) are candidate cells of origin for many brain tumors. However, whether NSPCs in different locations within the V-SVZ differ in susceptibility to tumorigenic mutations is unknown. Here, single-cell measurements of signal transduction intermediates in the mechanistic target of rapamycin complex 1 (mTORC1) pathway reveal that ventral NSPCs have higher levels of signaling than dorsal NSPCs. These features are linked with differences in mTORC1-driven disease severity: introduction of a pathognomonic Tsc2 mutation only results in formation of tumor-like masses from the ventral V-SVZ. We propose a direct link between location-dependent intrinsic growth properties imbued by mTORC1 and predisposition to tumor development.

Computational Immune Monitoring Reveals Abnormal Double-Negative T Cells Present across Human Tumor Types

Advances in single-cell biology have enabled measurements of >40 protein features on millions of immune cells within clinical samples. However, the data analysis steps following cell population identification are susceptible to bias, time-consuming, and challenging to compare across studies. Here, an ensemble of unsupervised tools was developed to evaluate four essential types of immune cell information, incorporate changes over time, and address diverse immune monitoring challenges. The four complementary properties characterized were (i) systemic plasticity, (ii) change in population abundance, (iii) change in signature population features, and (iv) novelty of cellular phenotype. Three systems immune monitoring studies were selected to challenge this ensemble approach. In serial biopsies of melanoma tumors undergoing targeted therapy, the ensemble approach revealed enrichment of double-negative (DN) T cells. Melanoma tumor-resident DN T cells were abnormal and phenotypically distinct from those found in nonmalignant lymphoid tissues, but similar to those found in glioblastoma and renal cell carcinoma. Overall, ensemble systems immune monitoring provided a robust, quantitative view of changes in both the system and cell subsets, allowed for transparent review by human experts, and revealed abnormal immune cells present across multiple human tumor types.

Discovery of human cell selective effector molecules using single cell multiplexed activity metabolomics

Discovering bioactive metabolites within a metabolome is challenging because there is generally little foreknowledge of metabolite molecular and cell-targeting activities. Here, single-cell response profiles and primary human tissue comprise a response platform used to discover novel microbial metabolites with cell-type-selective effector properties in untargeted metabolomic inventories. Metabolites display diverse effector mechanisms, including targeting protein synthesis, cell cycle status, DNA damage repair, necrosis, apoptosis, or phosphoprotein signaling. Arrayed metabolites are tested against acute myeloid leukemia patient bone marrow and molecules that specifically targeted blast cells or nonleukemic immune cell subsets within the same tissue biopsy are revealed. Cell-targeting polyketides are identified in extracts from biosynthetically prolific bacteria, including a previously unreported leukemia blast-targeting anthracycline and a polyene macrolactam that alternates between targeting blasts or nonmalignant cells by way of light-triggered photochemical isomerization. High-resolution cell profiling with mass cytometry confirms response mechanisms and is used to validate initial observations.

Abstract 3935: Dissecting small cell lung carcinoma heterogeneity and chemotherapy resistance with mass cytometry

Introduction: Small cell lung cancer (SCLC) is a high grade neuroendocrine carcinoma of the lung responsible for up to 25% of lung cancer deaths. Treatment in SCLC has not changed significantly in the last 20 years. SCLC initially responds well to chemotherapy, but inevitably recurs. Characterization of tumor heterogeneity and changes in SCLC cell signaling and phenotypes after chemotherapy could yield new insights and therapeutic options. Mass cytometry uses metal labeled antibodies to profile expression and phosphorylation of more than 40 proteins in single cells and offers the opportunity to identify new subpopulations including potential cancer stem cell populations as well as targets for novel therapies in SCLC.

Methods: Nude mice with SCLC patient derived xenografts (PDXs) were treated with one cycle of carboplatin/etoposide or saline injection. Tumors were harvested at ~2000mm3, disaggregated, and cryopreserved. PDX samples were stained with a 22 marker panel and an intercalator dye to identify nucleated cells. This panel measured phospho-signaling, neuroendocrine, immune, and mesenchymal cell markers, and functional markers including ki67 and cleaved caspase 3. ViSNE analysis and biaxial gating were used to identify major subpopulations of interest.

Results: PDX tumors released viable tumor and stromal cells suitable for cryopreservation and mass cytometry. ACK buffer and enzymatic dissociation yielded the best quality cells by depleting red blood cells. Mouse cells, including leukocytes, were excluded using mouse MHC1 gating and iridium intercalator was used to identify nucleated cells. Single cell protein expression and phosphorylation was analyzed using viSNE and yielded at least 9 distinct subpopulations based on density islands with neuroendocrine (CD56+) and non-neuroendocrine (CD56-) populations. Chemotherapy treated cells had dramatic changes in subpopulation distribution compared to matched mock treated tumor. This included 2-3 fold expansion of SOX2+, CD117+, and pSTAT3+ populations with chemotherapy treatment. A small CD44+ tumor subpopulation identified in the chemotherapy treated cells was not present in the matched mock treated tumor suggesting a potential chemotherapy resistant/ stem- like subpopulation. Kinase activity showed stable p-AKT overall, but increased p-S6 in the chemotherapy treated cells.

Conclusions: Mass cytometry was able to identify multiple neuroendocrine and non-neuroendocrine cell populations from SCLC PDXs and characterize their signaling. Chemotherapy treated PDX had differential subpopulation distribution with enrichment of multiple stem-like signaling factors. This work demonstrates the utility of mass cytometry and viSNE as novel techniques to identify subpopulations associated with chemotherapy resistance for future targeting and demonstrates the feasibility of this technique for characterizing signaling heterogeneity in human SCLC tumors.

Citation Format: Jonathan M. Lehman, Nalin Leelatian, Bradford Harris, Megan Hoeksema, Zou Yong, Deon B. Doxie, Jonathan M. Irish, Pierre P. Massion. Dissecting small cell lung carcinoma heterogeneity and chemotherapy resistance with mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3935. doi:10.1158/1538-7445.AM2017-3935

Abstract 1772: PIK3CA C2 domain deletions hyperactivate PI3K, generate oncogene dependence and are exquisitely sensitive to PI3Kα inhibitors

Background: A 63 year old postmenopausal woman with advanced ER+ breast cancer resistant to endocrine therapy exhibited an exceptional response to the PI3Kα inhibitor alpelisib (BYL719) and the aromatase inhibitor letrozole (Mayer et al. Clin Cancer Res 2016). Targeted capture next generation sequence (NGS) of DNA from a liver metastasis identified a P447_L455 deletion in the C2 domain of PIK3CA. About 80% of PIK3CA activating mutations are in ‘hot spots’ within the helical and kinase domains. C2 domain mutations make up ~10% of all PIK3CA mutations in breast cancer (TCGA, Foundation Medicine) and are frequently not reported by tumor and plasma cell-free DNA NGS panels. Deletions and mutations in this domain cluster in a region encompassing amino acids 446-460 of PIK3CA. We investigated herein the functional role of PIK3CA C2 domain mutations and their response to PI3K inhibitors.

Methods: V5-tagged lentiviral vectors encoding wild type, delP447-L455, and delH450-P458 were stably transduced into MCF10A non-tumorigenic human breast epithelial cells. Cell viability and acini formation in 3D Matrigel were examined in media ± EGF or insulin or alpelisib. Markers of PI3K activation were examined by immunoblot and phosphoflow analysis. The Rosetta software suite was used to construct a structural model that would predict the change in stability of the p85/p110α complex. Physical association of p85α and p110α was determined by precipitation with V5 antibodies and immunoblot analysis.

Results: MCF10A cells stably expressing V5-tagged PIK3CAdelP447-L455 and PIK3CAdelH450-P458 exhibited EGF- and insulin-independent growth and higher phosphorylation of AKT, ERK and S6 when compared to parental MCF10A cells. In 3D Matrigel, MCF10A cells with PIK3CA C2 domain deletions formed invasive acini with increased protrusions, spindling, and bridging between acini. All these changes were ablated upon the addition of 1 µM of alpelisib whereas parental MCF10A cells were unaffected by alpelisib. We hypothesized that delP447-L455 would reduce the binding affinity of p110α with the p85 regulatory subunit of PI3K. A structural model of PIK3CAdelP447-L455 in the context of the regulatory complex revealed specific favorable inter-residue contacts that would be lost as a result of the deletion, predicting a significant decrease in binding energy. Consistent with this structural analysis, coimmunoprecipitation of p85 with V5 antibodies showed reduced binding of the C2 domain deletion mutants with p85 compared to wild type p110α.

Conclusions: These data suggest that C2 domain deletions in PIK3CA are activating mutations and generate oncogene dependence. As a result, tumors expressing these mutations are exquisitely sensitive to PI3Kα inhibitors. Thus, in addition to PIK3CA ‘hot spot’ mutations, C2 domain mutations should also be considered biomarkers of sensitivity to PI3K inhibitors.

Citation Format: Sarah Croessmann, Jonathan Sheehan, Gregory Sliwoski, Nalin Leelatian, Jie He, Rebecca Nagy, Justin M. Balko, Ingrid A. Mayer, Richard B. Lanman, Vincent Miller, Lewis C. Cantley, Jonathan M. Irish, Jens Meiler, Carlos L. Arteaga. PIK3CA C2 domain deletions hyperactivate PI3K, generate oncogene dependence and are exquisitely sensitive to PI3Kα inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1772. doi:10.1158/1538-7445.AM2017-1772

Abstract 364: Mass cytometry of human glioblastoma characterizes more than 99 percent of cells and reveals intratumoral cell subsets defined by contrasting signaling network profiles

Background: Glioblastoma (GBM) remains largely incurable despite intense study of resected tissue. Prior studies have revealed GBM cell subsets (Patel et al., Science 2014) and have implicated subset emergence as a potential mechanism of poor outcome in other cancer types. Signaling in rare cells or a mix of cell subsets may enable therapy resistance and recurrence of GBM. For example, STAT3 RNA expression has been previously shown to correlate with poor outcome in GBM (Jahani-Asl et al., Nat Neurosci 2016 and TCGA). The complexity of GBM, combined with the interconnectedness between cancer and host cells in the microenvironment, means that a single cell biology approach is needed to comprehensively characterize patient biopsy cells and determine how protein expression, signaling, and functional capabilities impact treatment response.

Methods: We developed a novel mass cytometry approach to characterize human GBM that identified ~90-95% of tumor cells (Leelatian & Doxie et al., Cytometry B 2016). Here, we applied this approach using a newly created 35-antibody mass cytometry panel focused on basal phospho-protein signaling. The published panel of 16 identity proteins included SOX2, CD44, Nestin, PDGFRα, S100B, and NCAM. This panel was augmented to measure 10 additional proteins and 9 phospho-proteins including p-STAT3, p-EGFR, and p-NFκB. Signaling measurements were chosen to match prior single cell studies of signaling networks that stratified clinical outcomes in blood cancers (Irish et al., Cell 2004; PNAS 2010, Levine et al., Cell 2015). Between 10,000 and 250,000 viable cells were characterized for each tumor (N = 7). Tumors were collected with informed consent and in accord with the Declaration of Helsinki.

Results: This new 35-antibody mass cytometry panel positively identified &gt;99% of GBM cells. Subsets of GBM cells displayed protein expression that matched previously observed transcriptional molecular subclasses (Verhaak et al., Cancer Cell 2010 and TCGA). Strikingly, this panel revealed novel GBM cell subsets defined by contrasting basal signaling profiles. An inverse correlation was observed between baseline STAT3 phosphorylation and the abundance of CD45+ leukocytes. Additionally, similar signaling patterns were seen in cells that expressed proteins associated with distinct functions, such as proliferation and migration.

Conclusions: The correlation between low STAT3 signaling and high immune cell abundance provides evidence for the idea that an intimate relationship exists between immune cells and GBM tumor growth and survival. Moreover, single cell analysis may reveal biomarkers of treatment response and allow prediction of clinical outcomes. The abnormal signaling mechanisms observed here in some GBM cell subsets should be studied further as potential targets for novel cancer-selective combination therapies.

Citation Format: Nalin Leelatian, Justine Sinnaeve, Bret C. Mobley, Akshitkumar M. Mistry, Daniel Liu, Kyle D. Weaver, Reid C. Thompson, Lola B. Chambless, Rebecca A. Ihrie, Jonathan M. Irish. Mass cytometry of human glioblastoma characterizes more than 99 percent of cells and reveals intratumoral cell subsets defined by contrasting signaling network profiles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 364. doi:10.1158/1538-7445.AM2017-364

Preparing Viable Single Cells from Human Tissue and Tumors for Cytomic Analysis

Mass cytometry is a single-cell biology technique that samples >500 cells per second, measures >35 features per cell, and is sensitive across a dynamic range of >104 relative intensity units per feature. This combination of technical assets has powered a series of recent cytomic studies where investigators used mass cytometry to measure protein and phospho-protein expression in millions of cells, characterize rare cell types in healthy and diseased tissues, and reveal novel, unexpected cells. However, these advances largely occurred in studies of blood, lymphoid tissues, and bone marrow, since the cells in these tissues are readily obtained in single-cell suspensions. This unit establishes a primer for single-cell analysis of solid tumors and tissues, and has been tested with mass cytometry. The cells obtained from these protocols can be fixed for study, cryopreserved for long-term storage, or perturbed ex vivo to dissect responses to stimuli and inhibitors. © 2017 by John Wiley & Sons, Inc.

Characterizing cell subsets using marker enrichment modeling

Learning cell identity from single-cell data presently relies on human experts. Here, we present Marker Enrichment Modeling (MEM), an algorithm that objectively describes cells by quantifying contextual feature enrichment and reporting a human and machine-readable text label. MEM outperformed traditional metrics in describing immune and cancer cell subsets from fluorescence and mass cytometry. MEM provides a quantitative language to communicate characteristics of new and established cytotypes observed in complex tissues.

Single cell analysis of human tissues and solid tumors with mass cytometry

BACKGROUND

Mass cytometry measures 36 or more markers per cell and is an appealing platform for comprehensive phenotyping of cells in human tissue and tumor biopsies. While tissue disaggregation and fluorescence cytometry protocols were pioneered decades ago, it is not known whether established protocols will be effective for mass cytometry and maintain cancer and stromal cell diversity.

METHODS

Tissue preparation techniques were systematically compared for gliomas and melanomas, patient derived xenografts of small cell lung cancer, and tonsil tissue as a control. Enzymes assessed included DNase, HyQTase, TrypLE, collagenase (Col) II, Col IV, Col V, and Col XI. Fluorescence and mass cytometry were used to track cell subset abundance following different enzyme combinations and treatment times.

RESULTS

Mechanical disaggregation paired with enzymatic dissociation by Col II, Col IV, Col V, or Col XI plus DNase for 1 h produced the highest yield of viable cells per gram of tissue. Longer dissociation times led to increasing cell death and disproportionate loss of cell subsets. Key markers for establishing cell identity included CD45, CD3, CD4, CD8, CD19, CD64, HLA-DR, CD11c, CD56, CD44, GFAP, S100B, SOX2, nestin, vimentin, cytokeratin, and CD31. Mass and fluorescence cytometry identified comparable frequencies of cancer cell subsets, leukocytes, and endothelial cells in glioma (R = 0.97), and tonsil (R = 0.98).

CONCLUSIONS

This investigation establishes standard procedures for preparing viable single cell suspensions that preserve the cellular diversity of human tissue microenvironments. © 2016 International Clinical Cytometry Society.

Head of the Class: OLIG2 and Glioblastoma Phenotype

Genomic mapping has driven the classification of glioblastoma into distinct molecular subclasses, but mechanisms that regulate tumor subclass phenotypes are only now emerging. In this issue of Cancer Cell, Lu et al. describe a phenotypic switch from PDGFRA-enriched "proneural" to EGFR-enriched "classical" features in glioblastoma upon ablation of Olig2.

Characterizing Phenotypes and Signaling Networks of Single Human Cells by Mass Cytometry

Single cell mass cytometry is revolutionizing our ability to quantitatively characterize cellular biomarkers and signaling networks. Mass cytometry experiments routinely measure 25-35 features of each cell in primary human tissue samples. The relative ease with which a novice user can generate a large amount of high quality data and the novelty of the approach have created a need for example protocols, analysis strategies, and datasets. In this chapter, we present detailed protocols for two mass cytometry experiments designed as training tools. The first protocol describes detection of 26 features on the surface of human peripheral blood mononuclear cells. In the second protocol, a mass cytometry signaling network profile measures 25 node states comprised of five key signaling effectors (AKT, ERK1/2, STAT1, STAT5, and p38) quantified under five conditions (Basal, FLT3L, SCF, IL-3, and IFNγ). This chapter compares manual and unsupervised data analysis approaches, including bivariate plots, heatmaps, histogram overlays, SPADE, and viSNE. Data files in this chapter have been shared online using Cytobank ( http://www.cytobank.org/irishlab/ ).

Highly sensitive EGFR mutation detection by specific amplification of mutant alleles

Mutations in the tyrosine kinase domain of the epidermal growth factor receptor (EGFR) gene predict benefit from tyrosine kinase inhibitors in patients suffering from non-small-cell lung cancer. In this study, we developed a fast, simple, cost-effective and highly sensitive assay for detection of five clinically important EGFR mutations in exon 19 (2235_2249del and 2236_2250del), exon 20 (C2369T) and exon 21 (T2573G and c.2573_2574 TG > GT). We designed EGFR mutation detection assays by combining allele-specific PCR amplification with the detection of SYBR Green I fluorescence, and optimized PCR conditions to specifically amplify mutant alleles. These one-step assays were able to detect the mutations at levels as low as 1.5 mutant copies in a DNA sample. Commercially available probe-based allele-specific PCR exhibited relatively poor performance when detecting very low copies of mutated DNA, especially in exon 19 and 20. Our assays offered dramatically less reagent cost than that of the commercial kit and generated results in less than 90 min after DNA extraction. These protocols can also be applied to conventional thermal cyclers followed by gel electrophoresis detection.