Background and Aims

High-Risk neuroblastoma (HR-NB) relapses in more than 30% of cases, despite using aggressive therapies including targeting of GD2. The presence of GD2^neg/low NB variants and/or the surface expression of different immune checkpoint ligands including B7-H3 might contribute to therapy resistance. The main aim of this study was to set a fast, unbiased method to unequivocally identify, quantify and characterize Bone Marrow (BM) infiltrating tumor cells.

Methods

We used a Multiparametric Flow Cytometry (MFC) panel to analyze 41 BM aspirates from 25 HR-NB patients, comparing results with Cytomorphological Analysis (CA) and/or immune-histochemical analysis (IHC). Spike-in experiments assessed the sensitivity of MFC. To find novel prognostic markers possibly integrating the MFC panel, Kaplan-Meier analysis on 498 primary NBs has been performed.

Results

No false-positive were detected, and MFC showed high sensitivity (0,0005%). Optimized MFC identified CD45^negCD56^pos NB cells in 11 out of 12 (91.6%) of BM indicated as infiltrated by CA, 7 of which co-expressed high levels of GD2 and B7-H3. MFC detected CD45^negCD56^posGD2^neg/low NB variants expressing high surface levels of B7-H3 in two patients diagnosed at 53 and 139 months of age. The first patient had a non-MYCN amplified tumor with unusual TH^posPHOX2B^neg phenotype, which relapsed 141 months post-diagnosis with BM infiltration and a humerus lesion. This patient did not receive anti-GD2 immunotherapy during the therapeutic protocol.

Kaplan-Meier analysis highlighted an interesting dichotomous prognostic value of different ligands involved in NB recognition by the immune system.

Conclusions

Our study describes a specific, sensitive and fast MFC analysis allowing a precise quantification of i) BM tumor burden; ii) surface expression of GD2; iii) surface expression of different immune checkpoint ligands. MFC might usefully support other routinely used diagnostic and prognostic tools, improving diagnosis, prognosis, and orienting novel personalized treatments in patients with GD2^neg/low NB, who might benefit from innovative therapies combining B7-H3 targeting.

Background and Aims

Treatment for neuroblastoma (NB) has been challenging. Though autophagy plays an important role in NB, however there`s no signature model based on the characteristics of autophagy-related (ATG) gene pairs. We aimed to construct and validate an ATG-gene-based prognostic signature model for NB.

Methods

After identifying differentially expressed ATG genes between INSS stage 4 and INSS stage No-4, we constructed an ATG genes risk model by Kaplan–Meier, univariate Cox regression, least absolute shrinkage and selection operator regression and multivariate Cox regression, followed by internal and external validation using K-M and ROC analysis. Then, we studied the correlation between risk score and immune microenvironment.

Results

This signature model based on four hub ATG (BIRC5, GRID2, RNASEL and HK2) can accurately predict the long term overall survival of NB patients (10 years) and is an independent prognostic factor for NB patients. For this we constructed a nomogram based on ATG-signature risk score and three other independent clinical factors (INSS_Stage, Age, MYCN-status). The results of the nomogram show that our signature can bring clinical net benefits. Since gene set enrichment analysis (GSEA) suggested that the signature was strongly associated with immune cell functions, CIBERSORT, LM22 matrix and Pearson correlation were further performed, showing that the risk signature was significantly correlated with T regulatory cells (Cor =0.115), T follicular helper cells (Cor =0.312), CD8+ T cell (Cor =0.137), CD4+ T cell (Cor =0.123), CD4 memory resting cells (Cor = 0.279), plasma cells (Cor=0.282), macrophage M2 cells (Cor=0.159), B memory cells (Cor = 0.207) and immune checkpoint genes consisting of PD-L1 and CTLA4.

Conclusions

we identified and independently validated an ATG gene risk signature for NB, as well as discovering its significant association with NB immune microenvironment. Low risk patients in our model may benefit more from immune checkpoint therapy.

Background and Aims

In neuroblastoma (NB) treatment, interventions targeting tumour-specific surface markers may enhance the efficacy of surgery generating anti-tumour immunological response from the ablated tumour residues. Here, we investigated the near-infrared photoimmunotherapy (NIR-PIT), a novel therapeutic approach combining the cytotoxicity of photodynamic therapy with the specificity of immunotherapy to enhance the antigenicity and adjuvanticity of NB tumour residues following surgery.

Methods

The anti-GD2 antibody Dinutuximab-beta was conjugated to the phthalocyanine dye, IR700DX, which, when excited with the light at 690 nm, produces cytotoxic and immunological responses. The anti-GD2–IR700DX binding specificity was confirmed by flow cytometry and confocal microscopy in NB cell lines expressing the GD2 antigen at different levels. Cell viability was measured with the CellTiter-Glo assay while the main hallmarks of immunogenic cell death (ICD) were investigated following the administration of NIR-PIT (8 and 16 J/cm²) to NB cancer cells. Proof-of-concept anti-GD2–IR700DX-PIT (100 μg, 100 J/cm²) in vivo studies were performed using mice bearing subcutaneous NB xenografts.

Results

The conjugate showed effective targeting to GD2 positive NB cells and blocking with an excess of non-labelled anti-GD2 antibody significantly reduced the median fluorescence in all tested cell lines, confirming probe specificity. Phototoxicity studies in vitro showed a significant decrease in cell viability in a dose dependent manner. Furthermore, the anti-GD2–IR700DX-PIT triggered the ICD leading to release of danger-associated molecular patterns (DAMPs). In vivo studies confirmed that the conjugate specifically targets GD2 positive tumours and significantly inhibits tumour growth post-irradiation.

Conclusions

Our preclinical feasibility study showed the therapeutic potential of anti-GD2–IR700DX-PIT for NB treatment, indicating this novel tool could become part of the armoury to improve loco-regional control and reduce the risk of microscopic residual disease after surgery.

Background and Aims

Neuroblastoma is one of the most malignant tumors in children. immune -related genes (IRGs) play an essential role in neuroblastoma. But the expression signature has rarely been investigated in prognosis. We aimed to identify and assess prognostic IRGs signature to predict overall survival (OS) in the patients.

Methods

IRGs were obtained from Immunology Database and Analysis Portal. Differentially expressed IRGs were identified based on Therapeutically Applicable Research To Generate Effective Treatments database. Bioinformatics analysis using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes platforms was performed. The Lasso cox regression analysis was performed to screen hub IRGs for overall survival, which were used to calculate the risk score of each patient. The prognostic nomogram based on risk scores and clinical factors was constructed. Receiver operating characteristic curve and calibration plot were used to evaluate the efficiency of the model. Finally, we prepared a Shiny R application to automatically calculate the predicted OS rate .

Results

The OS-related prognostic model was constructed based on 15 IRGs (AGT, LBP, PROC, FGHR3, PRLH, AR, ULBP2, KLRK1, PDF, IL1B, PDGFRA, S100A14, GH1, NRTN, HNF4G) and significantly stratified patients into high- and low-risk groups in terms of OS (P < 0.001). The area under the curves of the model were 0.87 in 3- year survival, 0.876 in 5- year survival, 0.919 in 10- year survival. Risk score based on the expression of 15 hub genes and 2 clinical factors (INSS stage and MKI index) were identified as significant prognostic factors. A nomogram was constructed by the above 3 poor factors, the calibration curves showed optimal agreement between the probability as predicted by the nomogram and the actual probability. A interactive online shiny-website was constructed finally.

Conclusions

Our IRGs based prediction model is a reliable prognostic and predictive tool for long term overall survival in neuroblastoma.

Background and Aims

Neuroblastoma is one of the most malignant tumors in children. Autophagy-related genes (ARGs) play an essential role in neuroblastoma, but the expression signature has rarely been investigated in prognosis. We aimed to identify and assess prognostic ARGs signature to predict overall survival (OS) in the patients.

Methods

234 ARGs were obtained from The Human Autophagy Database. Differentially expressed ARGs were identified based on Therapeutically Applicable Research To Generate Effective Treatments database. Bioinformatics analysis using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes platforms was performed. The Lasso cox regression analysis was performed to screen hub prognostic ARGs for overall survival, hub genes were used to calculate the risk score of each patient. The prognostic nomogram based on risk score and clinical factors was constructed. its performance was evaluated by receiver operating characteristic (ROC), and calibration curves. Finally, we prepared a Shiny R application to automatically calculate the predicted OS rate.

Results

The OS-related prognostic model was constructed based on 4 ARGs (VTN, EXOC4, BIRC5, CFTR) and significantly stratified patients into high- and low-risk groups in terms of OS (P < 0.001). The area under the curve of the model were 0.7 in 3- year survival, 0.672 in 5- year survival, 0.819 in 10- year survival. Risk score based on the expression of 4 hub genes and 3 clinical factors (DNA ploidy, INSS stage and MKI index) were identified as significant prognostic factors. A nomogram was constructed by the above 4 poor factors, the calibration curves showed optimal agreement between the probability as predicted by the nomogram and the actual probability. A interactive online shiny website was constructed finally.

Conclusions

Our ARGs based prediction model is a reliable prognostic and predictive tool for long term overall survival in neuroblastoma.