Rejection continues to be an important cause of graft loss in solid organ transplantation, but deep exploration of intragraft alloimmunity has been limited by the scarcity of clinical biopsy ...specimens. Emerging single cell immunoprofiling technologies have shown promise in discerning mechanisms of autoimmunity and cancer immunobiology. Within these applications, Imaging Mass Cytometry (IMC) has been shown to enable highly multiplexed, single cell analysis of immune phenotypes within fixed tissue specimens. In this study, an IMC panel of 10 validated markers was developed to explore the feasibility of IMC in characterizing the immune landscape of chronic rejection (CR) in clinical tissue samples obtained from liver transplant recipients. IMC staining was highly specific and comparable to traditional immunohistochemistry. A single cell segmentation analysis pipeline was developed that enabled detailed visualization and quantification of 109,245 discrete cells, including 30,646 immune cells. Dimensionality reduction identified 11 unique immune subpopulations in CR specimens. Most immune subpopulations were increased and spatially related in CR, including two populations of CD45+/CD3+/CD8+ cytotoxic T-cells and a discrete CD68+ macrophage population, which were not observed in liver with no rejection (NR). Modeling
principal component analysis and logistic regression revealed that single cell data can be utilized to construct statistical models with high consistency (Wilcoxon Rank Sum test, p=0.000036). This study highlights the power of IMC to investigate the alloimmune microenvironment at a single cell resolution during clinical rejection episodes. Further validation of IMC has the potential to detect new biomarkers, identify therapeutic targets, and generate patient-specific predictive models of clinical outcomes in solid organ transplantation.
Immune checkpoint therapy has resulted in minimal clinical response in many pediatric cancers. We sought to understand the influence of immune checkpoint inhibition using anti-PD-1 and anti-CTLA-4 ...antibodies individually, in combination, and after chemotherapy on immune responses in minimal and established murine neuroblastoma models. We also sought to understand the role of the tumor microenvironment (TME) and PD-L1 expression and their alteration post-chemotherapy in our models and human tissues. PD-L1 expression was enriched in human tumor-associated macrophages and up-regulated after chemotherapy. In a murine minimal disease model, single and dual immune checkpoint blockade promoted tumor rejection, improved survival, and established immune memory with long-term anti-tumor immunity against re-challenge. In an established tumor model, only dual immune checkpoint blockade showed efficacy. Interestingly, dual immune checkpoint therapy distinctly influenced adaptive and innate immune responses, with significant increase in CD8
+
CD28
+
PD-1
+
T cells and inflammatory macrophages (CD11b
hi
CD11c
−
F4/80
+
Ly6C
hi
) in tumor-draining lymph nodes. Adding chemotherapy before immunotherapy provided significant survival benefit for mice with established tumors receiving anti-PD-1 or dual immune checkpoint blockade. Our findings demonstrate anti-PD-1 and anti-CTLA-4 therapy induces a novel subset of effector T cells, and support administration of induction chemotherapy immediately prior to immune checkpoint blockade in children with high-risk neuroblastoma.
Retinoids play key roles in differentiation, growth arrest, and apoptosis and are increasingly being used in the clinic for the treatment of a variety of cancers, including neuroblastoma. Here, using ...a large-scale RNA interference-based genetic screen, we identify
ZNF423 (also known as
Ebfaz,
OAZ, or
Zfp423) as a component critically required for retinoic acid (RA)-induced differentiation. ZNF423 associates with the RARα/RXRα nuclear receptor complex and is essential for transactivation in response to retinoids. Downregulation of
ZNF423 expression by RNA interference in neuroblastoma cells results in a growth advantage and resistance to RA-induced differentiation, whereas overexpression of
ZNF423 leads to growth inhibition and enhanced differentiation. Finally, we show that low
ZNF423 expression is associated with poor disease outcome in neuroblastoma patients.
Motivation: The complexity of a large number of recently discovered copy number polymorphisms is much higher than initially thought, thus making it more difficult to detect them in the presence of ...significant measurement noise. In this scenario, separate normalization and segmentation is prone to lead to many false detections of changes in copy number. New approaches capable of jointly modeling the copy number and the non-copy number (noise) hybridization effects across multiple samples will potentially lead to more accurate results. Methods: In this article, the genome alteration detection analysis (GADA) approach introduced in our previous work is extended to a multiple sample model. The copy number component is independent for each sample and uses a sparse Bayesian prior, while the reference hybridization level is not necessarily sparse but identical on all samples. The expectation maximization (EM) algorithm used to fit the model iteratively determines whether the observed hybridization levels are more likely due to a copy number variation or to a shared hybridization bias. Results: The new proposed approach is compared with the currently used strategy of separate normalization followed by independent segmentation of each array. Real microarray data obtained from HapMap samples are randomly partitioned to create different reference sets. Using the new approach, copy number and reference intensity estimates are significantly less variable if the reference set changes; and a higher consistency on copy numbers detected within HapMap family trios is obtained. Finally, the running time to fit the model grows linearly in the number samples and probes. Availability:http://biron.usc.edu/∼piquereg/GADA Contact: rpique@ieee.org; shahab@chla.usc.edu Supplementary information:Supplementary data are available at Bioinformatics online.
To evaluate the impact of a predefined gene expression-based classifier for clinical risk estimation and cytotoxic treatment decision making in neuroblastoma patients.
Gene expression profiles of 440 ...internationally collected neuroblastoma specimens were investigated by microarray analysis, 125 of which were examined prospectively. Patients were classified as either favorable or unfavorable by a 144-gene prediction analysis for microarrays (PAM) classifier established previously on a separate set of 77 patients. PAM classification results were compared with those of current prognostic markers and risk estimation strategies.
The PAM classifier reliably distinguished patients with contrasting clinical courses (favorable n = 249 and unfavorable n = 191; 5-year event free survival EFS 0.84 +/- 0.03 v 0.38 +/- 0.04; 5-year overall survival OS 0.98 +/- 0.01 v 0.56 +/- 0.05, respectively; both P < .001). Moreover, patients with divergent outcome were robustly discriminated in both German and international cohorts and in prospectively analyzed samples (P <or= .001 for both EFS and OS for each). In subgroups with clinical low-, intermediate-, and high-risk of death from disease, the PAM predictor significantly separated patients with divergent outcome (low-risk 5-year OS: 1.0 v 0.75 +/- 0.10, P < .001; intermediate-risk: 1.0 v 0.82 +/- 0.08, P = .042; and high-risk: 0.81 +/- 0.08 v 0.43 +/- 0.05, P = .001). In multivariate Cox regression models based on both EFS and OS, PAM was a significant independent prognostic marker (EFS: hazard ratio HR, 3.375; 95% CI, 2.075 to 5.492; P < .001; OS: HR, 11.119, 95% CI, 2.487 to 49.701; P < .001). The highest potential clinical impact of the classifier was observed in patients currently considered as non-high-risk (n = 289; 5-year EFS: 0.87 +/- 0.02 v 0.44 +/- 0.07; 5-year OS: 1.0 v 0.80 +/- 0.06; both P < .001).
Gene expression-based classification using the 144-gene PAM predictor can contribute to improved treatment stratification of neuroblastoma patients.
Neuroblastomas with a high mitosis-karyorrhexis index (High-MKI) are often associated with
amplification, MYCN protein overexpression and adverse clinical outcome. However, the prognostic effect of ...MYC-family protein expression on these neuroblastomas is less understood, especially when
is not amplified. To address this, MYCN and MYC protein expression in High-MKI cases (120
amplified and 121 non-
amplified) was examined by immunohistochemistry. The majority (101) of
-amplified High-MKI tumors were MYCN(+), leaving one MYC(+), 2 both(+), and 16 both(-)/(+/-), whereas non-
-amplified cases appeared heterogeneous, including 7 MYCN(+), 36 MYC(+), 3 both(+), and 75 both(-)/(+/-) tumors. These MYC-family proteins(+), or MYC-family driven tumors, were most likely to have prominent nucleolar (PN) formation (indicative of augmented rRNA synthesis). High-MKI neuroblastoma patients showed a poor survival irrespective of
amplification. However, patients with MYC-family driven High-MKI neuroblastomas had significantly lower survival than those with non-MYC-family driven tumors. MYCN(+), MYC-family protein(+), PN(+), and clinical stage independently predicted poor survival. Specific inhibition of hyperactive rRNA synthesis and protein translation was shown to be an effective way to suppress MYC/MYCN protein expression and neuroblastoma growth. Together, MYC-family protein overexpression and PN formation should be included in new neuroblastoma risk stratification and considered for potential therapeutic targets.
The vast array of in silico resources and data of high throughput profiling currently available in life sciences research offer the possibility of aiding cancer gene and drug discovery process. Here ...we propose to take advantage of these resources to develop a tool, TARGETgene, for efficiently identifying mutation drivers, possible therapeutic targets, and drug candidates in cancer. The simple graphical user interface enables rapid, intuitive mapping and analysis at the systems level. Users can find, select, and explore identified target genes and compounds of interest (e.g., novel cancer genes and their enriched biological processes), and validate predictions using user-defined benchmark genes (e.g., target genes detected in RNAi screens) and curated cancer genes via TARGETgene. The high-level capabilities of TARGETgene are also demonstrated through two applications in this paper. The predictions in these two applications were then satisfactorily validated by several ways, including known cancer genes, results of RNAi screens, gene function annotations, and target genes of drugs that have been used or in clinical trial in cancer treatments. TARGETgene is freely available from the Biomedical Simulations Resource web site (http://bmsr.usc.edu/Software/TARGET/TARGET.html).
Medulloblastomas are the most common malignant pediatric brain tumor and have been divided into four major molecular subgroups. Animal models that mimic the principal molecular aberrations of these ...subgroups will be important tools for preclinical studies and allow greater understanding of medulloblastoma biology. We report a new transgenic model of medulloblastoma that possesses a unique combination of desirable characteristics including, among others, the ability to incorporate multiple and variable genes of choice and to produce bioluminescent tumors from a limited number of somatic cells within a normal cellular environment. This model, termed BarTeL, utilizes a Barhl1 homeobox gene promoter to target expression of a bicistronic transgene encoding both the avian retroviral receptor TVA and an eGFP-Luciferase fusion protein to neonatal cerebellar granule neuron precursor (cGNP) cells, which are cells of origin for the sonic hedgehog (SHH) subgroup of human medulloblastomas. The Barhl1 promoter-driven transgene is expressed strongly in mammalian cGNPs and weakly or not at all in mature granule neurons. We efficiently induced bioluminescent medulloblastomas expressing eGFP-luciferase in BarTeL mice by infection of a limited number of somatic cGNPs with avian retroviral vectors encoding the active N-terminal fragment of SHH and a stabilized MYCN mutant. Detection and quantification of the increasing bioluminescence of growing tumors in young BarTeL mice was facilitated by the declining bioluminescence of their uninfected maturing cGNPs. Inclusion of eGFP in the transgene allowed enriched sorting of cGNPs from neonatal cerebella. Use of a single bicistronic avian vector simultaneously expressing both Shh and Mycn oncogenes increased the medulloblastoma incidence and aggressiveness compared to mixed virus infections. Bioluminescent tumors could also be produced by ex vivo transduction of neonatal BarTeL cerebellar cells by avian retroviruses and subsequent implantation into nontransgenic cerebella. Thus, BarTeL mice provide a versatile model with opportunities for use in medulloblastoma biology and therapeutics.
BackgroundIn the Children’s Oncology Group ANBL1221 phase 2 trial for patients with first relapse/first declaration of refractory high-risk neuroblastoma, irinotecan and temozolomide (I/T) combined ...with either temsirolimus (TEMS) or immunotherapy (the anti-GD2 antibody dinutuximab (DIN) and granulocyte macrophage colony stimulating factory (GM-CSF)) was administered. The response rate among patients treated with I/T/DIN/GM-CSF in the initial cohort (n=17) was 53%; additional patients were enrolled to permit further evaluation of this chemoimmunotherapy regimen. Potential associations between immune-related biomarkers and clinical outcomes including response and survival were evaluated.MethodsPatients were evaluated for specific immunogenotypes that influence natural killer (NK) cell activity, including killer immunoglobulin-like receptors (KIRs) and their ligands, Fc gamma receptors, and NCR3. Total white cells and leucocyte subsets were assessed via complete blood counts, and flow cytometry of peripheral blood mononuclear cells was performed to assess the potential association between immune cell subpopulations and surface marker expression and clinical outcomes. Appropriate statistical tests of association were performed. The Bonferroni correction for multiple comparisons was performed where indicated.ResultsOf the immunogenotypes assessed, the presence or absence of certain KIR and their ligands was associated with clinical outcomes in patients treated with chemoimmunotherapy rather than I/T/TEMS. While median values of CD161, CD56, and KIR differed in responders and non-responders, statistical significance was not maintained in logistic regression models. White cell and neutrophil counts were associated with differences in survival outcomes, however, increases in risk of event in patients assigned to chemoimmunotherapy were not clinically significant.ConclusionsThese findings are consistent with those of prior studies showing that KIR/KIR-ligand genotypes are associated with clinical outcomes following anti-GD2 immunotherapy in children with neuroblastoma. The current study confirms the importance of KIR/KIR-ligand genotype in the context of I/T/DIN/GM-CSF chemoimmunotherapy administered to patients with relapsed or refractory disease in a clinical trial. These results are important because this regimen is now widely used for treatment of patients at time of first relapse/first declaration of refractory disease. Efforts to assess the role of NK cells and genes that influence their function in response to immunotherapy are ongoing.Trial registration numberNCT01767194.
There have been several reports about the potential for predicting prognosis of neuroblastoma patients using microarray gene expression profiling of the tumors. However these studies have revealed an ...apparent diversity in the identity of the genes in their predictive signatures. To test the contribution of the platform to this discrepancy we applied the
z-scoring method to minimize the impact of platform and combine gene expression profiles of neuroblastoma (NB) tumors from two different platforms, cDNA and Affymetrix. A total of 12442 genes were common to both cDNA and Affymetrix arrays in our data set. Two-way ANOVA analysis was applied to the combined data set for assessing the relative effect of prognosis and platform on gene expression. We found that 26.6% (3307) of the genes had significant impact on survival. There was no significant impact of microarray platform on expression after application of
z-scoring standardization procedure. Artificial neural network (ANN) analysis of the combined data set in a leave-one-out prediction strategy correctly predicted the outcome for 90% of the samples. Hierarchical clustering analysis using the top-ranked 160 genes showed the great separation of two clusters, and the majority of matched samples from the different platforms were clustered next to each other. The ANN classifier trained with our combined cross-platform data for these 160 genes could predict the prognosis of 102 independent test samples with 71% accuracy. Furthermore it correctly predicted the outcome for 85/102 (83%) NB patients through the leave-one-out cross-validation approach. Our study showed that gene expression studies performed in different platforms could be integrated for prognosis analysis after removing variation resulting from different platforms.
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