Age, Diagnostic Category, Tumor Grade, and Mitosis-Karyorrhexis Index Are Independently Prognostic in Neuroblastoma: An INRG Project

Proteomic analysis of serum small extracellular vesicles identifies diagnostic biomarkers for neuroblastoma

Background

Neuroblastoma (NB) primarily arises in children who are <10 years of age, and originates from developing sympathetic nervous system, which results in tumors in adrenal glands and/or sympathetic ganglia. The diagnosis of NB involves a combination of laboratory and imaging tests, and biopsies. Small extracellular vesicles (sEVs) have gained attention as potential biomarkers for various types of tumors. Here, we performed proteomic analysis of serum sEVs and identified potential biomarkers for NB.

Methods

Label-free proteomics of serum sEVs were performed in the discovery phase. A bulk RNA-seq dataset of NB tissues was used to analyze the association between genes encoding sEVs proteins and prognosis. Potential biomarkers were validated via multiple reaction monitoring (MRM) or western blot analysis in the validation phase. A public single-cell RNA-seq (scRNA-seq) dataset was integrated to analyze the tissue origin of sEVs harboring biomarkers.

Results

A total of 104 differentially expressed proteins were identified in NB patients with label-free proteomics, and 26 potential biomarkers were validated with MRM analysis. Seven proteins BSG, HSP90AB1, SLC44A1, CHGA, ATP6V0A1, ITGAL and SELL showed the strong ability to distinguish NB patients from healthy controls and non-NB patients as well. Integrated analysis of scRNA-seq and sEVs proteomics revealed that these sEVs-derived biomarkers originated from different cell populations in tumor tissues.

Conclusion

sEVs-based biomarkers may aid the molecular diagnosis of NB, representing an innovative strategy to improve NB detection and management.

Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology

A deep learning model using attention-based multiple instance learning (aMIL) and self-supervised learning (SSL) was developed to perform pathologic classification of neuroblastic tumors and assess MYCN-amplification status using H&E-stained whole slide digital images. The model demonstrated strong performance in identifying diagnostic category, grade, mitosis-karyorrhexis index (MKI), and MYCN-amplification on an external test dataset. This AI-based approach establishes a valuable tool for automating diagnosis and precise classification of neuroblastoma tumors.

Development and validation of a novel nomogram for predicting overall survival patients with neuroblastoma

PURPOSE

The aim of this study was to develop a nomogram specially for predicting overall survival (OS) for Chinese patients with neuroblastoma (NB).

METHODS

Patients with pathologically confirmed NB who were newly diagnosed and received treatments at our hospital from October 2013 to October 2021 were retrospectively reviewed. The nomogram for OS were built based on Cox regression analysis. The validation of the prognostic model was evaluated by concordance index (C-index), calibration curves, and decision curve analyses (DCAs).

RESULTS

A total of 254 patients with NB were included in this study. They were randomly divided into a training cohort (n = 178) and a validation cohort (n = 76) at a ratio of 7:3. Multivariate analyses revealed that prognostic variables significantly related to the OS were age at diagnosis, bone metastasis, hepatic metastasis, INSS stage, MYCN status and DNA ploidy. The nomogram was constructed based on above 6 factors. The C-index values of the nomogram for predicting 3-year and 5-year OS were 0.926 and 0.964, respectively. The calibration curves of the nomogram showed good consistency between nomogram prediction and actual survival. The DCAs showed great clinical usefulness of the nomograms. Furthermore, patients with low-risk identified by our nomogram had much higher OS than those with high-risk (p < 0.001).

CONCLUSION

The nomogram we constructed exhibited good predictive performance and could be used to assist clinicians in their decision-making process.

The relationship between contrast-enhanced computed tomography radiomics features and mitosis karyorrhexis index in neuroblastoma

OBJECTIVE

Mitosis karyorrhexis index (MKI) can reflect the proliferation status of neuroblastoma cells. This study aimed to investigate the contrast-enhanced computed tomography (CECT) radiomics features associated with the MKI status in neuroblastoma.

MATERIALS AND METHODS

246 neuroblastoma patients were retrospectively included and divided into three groups: low-MKI, intermediate-MKI, and high-MKI. They were randomly stratified into a training set and a testing set at a ratio of 8:2. Tumor regions of interest were delineated on arterial-phase CECT images, and radiomics features were extracted. After reducing the dimensionality of the radiomics features, a random forest algorithm was employed to establish a three-class classification model to predict MKI status.

RESULTS

The classification model consisted of 5 radiomics features. The mean area under the curve (AUC) of the classification model was 0.916 (95% confidence interval (CI) 0.913-0.921) in the training set and 0.858 (95% CI 0.841-0.864) in the testing set. Specifically, the classification model achieved AUCs of 0.928 (95% CI 0.927-0.934), 0.915 (95% CI 0.912-0.919), and 0.901 (95% CI 0.900-0.909) for predicting low-MKI, intermediate-MKI, and high-MKI, respectively, in the training set. In the testing set, the classification model achieved AUCs of 0.873 (95% CI 0.859-0.882), 0.860 (95% CI 0.852-0.872), and 0.820 (95% CI 0.813-0.839) for predicting low-MKI, intermediate-MKI, and high-MKI, respectively.

CONCLUSIONS

CECT radiomics features were found to be correlated with MKI status and are helpful for reflecting the proliferation status of neuroblastoma cells.

The prognostic role of 18F-FDG PET/CT-based response evaluation in children with stage 4 neuroblastoma

OBJECTIVES

To evaluate the association between metabolic response on 18F-FDG PET/CT and long-term survival in children with neuroblastoma (NB).

METHODS

A total of 39 consecutive children with newly diagnosed stage 4 NB undergoing both 18F-FDG PET/CT imaging at baseline and after chemotherapy were retrospectively analyzed. The associations between metabolic parameters, including SUVmax of the lesion with the most intense 18F-FDG uptake at baseline (SUVb), after chemotherapy (SUVe), and the percentage change between SUVb and SUVe, and long-term survival were evaluated.

RESULTS

With a median follow-up of 56 months, 22 patients who had achieved complete resolution on PET (no residual 18F-FDG uptake higher than the surrounding backgrounds) after chemotherapy had superior 5-year overall survival (OS) (73.6% vs. 39.0%, p = 0.044). SUVb > 6.9 indicated significantly poorer 5-year event-free survival (EFS) (12.5% vs. 59.3%, p = 0.005), as did SUVe > 1.2 (18.8% vs. 41.7%, p = 0.041). Children with SUVe > 1.2 had shorter 5-year OS (33.9% vs. 75.0%, p = 0.018). Multivariate analysis identified SUVe > 1.2 as an independent predictor for both EFS [hazard ratio (HR), 3.479, 95% CI, 1.381-8.761, p = 0.008] and OS (HR, 6.948, 95% CI, 1.663-29.025, p = 0.008), while SUVb > 6.9 was a predictor for EFS (HR, 2.889, 95% CI, 1.064-7.842, p = 0.037). Among 11 children with both SUVb > 6.9 and SUVe > 1.2, all experienced disease progression or relapse within 2 years since diagnosis.

CONCLUSION

18F-FDG PET/CT could be of useful to evaluate treatment response in children with stage 4 NB.

CLINICAL RELEVANCE STATEMENT

18F-FDG PET/CT after chemotherapy exhibits prognostic significance in neuroblastoma and holds potential as an alternative imaging modality for response evaluation, especially in cases with metaiodobenzylguanidine-nonavid or persistent avid disease.

KEY POINTS

The prognostic value of chemotherapy response on 18F-FDG PET/CT in advanced neuroblastoma is unknown. Higher 18F-FDG uptake after chemotherapy was associated with worse long-term event-free survival and overall survival. 18F-FDG PET/CT after chemotherapy holds prognostic significance in children with stage 4 neuroblastoma.

Extracting Electronic Health Record Neuroblastoma Treatment Data With High Fidelity Using the REDCap Clinical Data Interoperability Services Module

PURPOSE

Although the International Neuroblastoma Risk Group Data Commons (INRGdc) has enabled seminal large cohort studies, the research is limited by the lack of real-world, electronic health record (EHR) treatment data. To address this limitation, we evaluated the feasibility of extracting treatment data directly from EHRs using the REDCap Clinical Data Interoperability Services (CDIS) module for future submission to the INRGdc.

METHODS

Patients enrolled on the Children's Oncology Group neuroblastoma biology study ANBL00B1 (ClinicalTrials.gov identifier: NCT00904241) who received care at the University of Chicago (UChicago) or the Vanderbilt University Medical Center (VUMC) after the go-live dates for the Fast Healthcare Interoperability Resources (FHIR)-compliant EHRs were identified. Antineoplastic drug orders were extracted using the CDIS module. To validate the CDIS output, antineoplastic agents extracted through FHIR were compared with those queried through EHR relational databases (UChicago's Clinical Research Data Warehouse and VUMC's Epic Clarity database) and manual chart review.

RESULTS

The analytic cohort consisted of 41 patients at UChicago and 32 VUMC patients. Antineoplastic drug orders were identified in the extracted EHR records of 39 (95.1%) UChicago patients and 26 (81.3%) VUMC patients. Manual chart review confirmed that patients with missing (n = 8) or discontinued (n = 1) orders in the CDIS output did not receive antineoplastic agents during the timeframe of the study. More than 99% of the antineoplastic drug orders in the EHR relational databases were identified in the corresponding CDIS output.

CONCLUSION

Our results demonstrate the feasibility of extracting EHR treatment data with high fidelity using HL7-FHIR via REDCap CDIS for future submission to the INRGdc.

Differentiation of early relapse and late relapse in intermediate- and high-risk neuroblastoma with an 18F-FDG PET/CT-based radiomics nomogram

OBJECTIVES

To develop and validate an 18F-FDG PET/CT-based radiomics nomogram for differentiating early relapse and late relapse of intermediate- and high-risk neuroblastoma (NB).

METHODS

A total of eighty-five patients with relapsed NB who underwent 18F-FDG PET/CT were retrospectively evaluated. All selected patients were randomly assigned to the training set and the validation set in a 7:3 ratio. Tumors were segmented using the 3D slicer, followed by radiomics features extraction. Features selection was performed using random forest, and the radiomics score was constructed by logistic regression analysis. Clinical risk factors were identified, and the clinical model was constructed using logistic regression analysis. A radiomics nomogram was constructed by combining the radiomics score and clinical risk factors, and its performance was evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

Finally, the 12 most important radiomics features were used for modeling, with an area under the curve (AUC) of 0.835 and 0.824 in the training and validation sets, respectively. Age at diagnosis and International Neuroblastoma Pathology Classification were determined as clinical risk factors to construct the clinical model. In addition, the nomogram achieved an AUC of 0.902 and 0.889 for identifying early relapse in the training and validation sets, respectively, which is higher than the clinical model (AUC of 0.712 and 0.588, respectively). The predicted early relapse and actual early relapse in the calibration curves were in good agreement. The DCA showed that the radiomics nomogram was clinically useful.

CONCLUSION

Our 18F-FDG PET/CT-based radiomics nomogram can well predict early relapse and late relapse of intermediate- and high-risk NB, which contributes to follow-up and management in clinical practice.

Anti-PD-1 Therapy in Advanced Pediatric Malignancies in Nationwide Study: Good Outcome in Skin Melanoma and Hodgkin Lymphoma

BACKGROUND/AIM

The role of immune checkpoint inhibitors (ICIs; anti-PD1) in the treatment of childhood cancers is still evolving. The aim of this nationwide retrospective study was to assess the safety and effectiveness of ICIs used in a group of 42 patients, with a median age of 13.6 years, with various types of advanced malignancies treated in pediatric oncology centers in Poland between 2015 and 2023.

RESULTS

The indications for treatment with anti-PD1 were as follows: Hodgkin lymphoma (11); malignant skin melanoma (9); neuroblastoma (8); and other malignancies (14). At the end of follow-up, complete remission (CR) was observed in 37.7% (15/42) of children and disease stabilization in 9.5% (4/42), with a mean survival 3.6 (95% CI = 2.6-4.6) years. The best survival (OS = 1.0) was observed in the group of patients with Hodgkin lymphoma. For malignant melanoma of the skin, neuroblastoma, and other rare malignancies, the estimated 3-year OS values were, respectively, 0.78, 0.33, and 0.25 (p = 0.002). The best progression-free survival value (0.78) was observed in the group with malignant melanoma. Significantly better effects of immunotherapy were confirmed in patients ≥ 14 years of age and good overall performance ECOG status. Severe adverse events were observed in 30.9% (13/42) patients.

Clinical application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography radiomics-based machine learning analyses in the field of oncology

Machine learning (ML) analyses using 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) radiomics features have been applied in the field of oncology. The current review aimed to summarize the current clinical articles about 18F-FDG PET/CT radiomics-based ML analyses to solve issues in classifying or constructing prediction models for several types of tumors. In these studies, lung and mediastinal tumors were the most commonly evaluated lesions, followed by lymphatic, abdominal, head and neck, breast, gynecological, and other types of tumors. Previous studies have commonly shown that 18F-FDG PET radiomics-based ML analysis has good performance in differentiating benign from malignant tumors, predicting tumor characteristics and stage, therapeutic response, and prognosis by examining significant differences in the area under the receiver operating characteristic curves, accuracies, or concordance indices (> 0.70). However, these studies have reported several ML algorithms. Moreover, different ML models have been applied for the same purpose. Thus, various procedures were used in 18F-FDG PET/CT radiomics-based ML analysis in oncology, and 18F-FDG PET/CT radiomics-based ML models, which are easy and universally applied in clinical practice, would be expected to be established.

Association of Computed Tomography Radiomics Signature with Progression-free Survival in Neuroblastoma Patients

AIMS

To investigate the association of computed tomography radiomics signature with progression-free survival (PFS) in neuroblastoma patients.

MATERIALS AND METHODS

We retrospectively included 167 neuroblastoma patients who were divided into a training set and a test set through stratified sampling at a ratio of 7:3. Regions of interest of the primary tumours were delineated on pretreatment contrast-enhanced computed tomography images and radiomics features were extracted from them. The intraclass correlation coefficient, Pearson correlation coefficient, and least absolute shrinkage and selection operator Cox regression algorithm were applied to select radiomics features and construct the radiomics signature. The effectiveness of the signature in predicting PFS was evaluated using the concordance index (C-index) and 95% confidence interval in both the training and the test sets. The time-dependent receiver operator characteristic curve of the radiomics signature was plotted and the area under the curve (AUC) was calculated. A calibration curve was used to assess the difference between the predicted probability of the radiomics signature and the observed probability at different time points.

RESULTS

The radiomics signature was composed of six features, which achieved a C-index of 0.733 (95% confidence interval 0.664-0.803) in the training set and 0.734 (95% confidence interval 0.608-0.861) in the test set. In the training set, the radiomics signature yielded an AUC of 0.707, 0.737, 0.788, 0.859 and 0.829 for 1-, 2-, 3-, 4- and 5-year PFS, respectively. Similarly, the radiomics signature exhibited an AUC of 0.738, 0.807, 0.761, 0.787 and 0.818 for 1-, 2-, 3-, 4- and 5-year PFS, respectively, in the test set. The calibration curves showed no significant difference between the predicted probability of the radiomics signature and the observed probability for up to 5 years.

CONCLUSIONS

Computed tomography radiomics features exhibit a significant correlation with the PFS of neuroblastoma patients, particularly in terms of long-term outcomes.

A practical nomogram and risk stratification system for predicting survival outcomes in neuroblastoma patients: a SEER population-based study

BACKGROUND

Neuroblastoma (NB) is a childhood malignancy with marked heterogeneity, resulting in highly variable outcomes among patients. This study aims to establish a novel nomogram and risk stratification system to predict the overall survival (OS) for patients with NB.

METHODS

We analyzed neuroblastoma patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The nomogram was constructed using independent risk factors for OS, identified through univariate and multivariate Cox regression analyses. The accuracy of this nomogram was evaluated with the concordance index, receiver operating characteristic curve, calibration curve, and decision curve analysis. In addition, we developed a risk stratification system based on the total score of each patient in the nomogram.

RESULTS

A total of 2185 patients were randomly assigned to the training group and the testing group. Six risk factors, including age, chemotherapy, brain metastases, primary site, tumor stage, and tumor size, were identified in the training group. Using these factors, a nomogram was constructed to predict 1-, 3-, and 5-year OS of NB patients. This model exhibited superior accuracy in the training and testing groups, exceeding traditional tumor stage prediction. Subgroup analysis suggested worse prognosis for retroperitoneal origin in the intermediate-risk group and adrenal gland origin in the high-risk group compared to other sites. Additionally, the prognosis for high-risk patients significantly improved after surgery. We also developed a web application to make the nomogram more user-friendly in clinical practices.

CONCLUSION

This nomogram demonstrates excellent accuracy and reliability, offering more precise personalized prognostic predictions to clinical patients.

MYCN amplification and International Neuroblastoma Risk Group stratification on fine-needle aspiration biopsy and their correlation to survival in neuroblastoma

AIMS

Risk stratification as per the International Neuroblastoma Risk Group (INRG) stratification is important for management of neuroblastoma. INRG incorporates various parameters including histological category as per the International Neuroblastoma Pathology Classification (INPC) and MYCN amplification, which were evaluated in fine needle aspiration biopsy (FNAB) samples of neuroblastoma patients to ascertain their impact in our population.

METHODS

This was a retrospective study including 60 neuroblastoma cases diagnosed on FNAB, staged and stratified by INRG. Mitosis Karyorrhexis Index (MKI), INPC morphological category and MYCN status by fluorescence in situ hybridisation (n=46) were evaluated and correlated to outcome.

RESULTS

The mean age was 29 months (21 days to 9 years) with 27 and 33 children

CONCLUSION

FNAB is a complete modality for diagnosing neuroblastoma and providing all information required for risk stratification as per INRG including MKI, MYCN amplification, INPC category. Our cohort with predominant high-risk neuroblastoma cases highlights regional variation.

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Key Words

• FISH
• NEUROBLASTOMA
• Pathology, Molecular

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MESH Headings

• Child
• Child, Preschool
• Female
• Humans
• Infant
• Male
• Biopsy, Fine-Needle
• Gene Amplification
• N-Myc Proto-Oncogene Protein/genetics
• Neuroblastoma/genetics
• Neuroblastoma/pathology
• Prognosis
• Retrospective Studies
• Infant, Newborn

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Affiliation(s)

Neha Bhardwaj Pathology, Post Graduate Institute of Medical Education and Research, Chandigarh, India
Manish Rohilla Cytology & Gynecological Pathology, Post Graduate Institute of Medical Education and Research, Chandigarh, India
Amita Trehan Department of Pediatrics (Hematology-Oncology Division), Post Graduate Institute of Medical Education and Research, Chandigarh, India
Deepak Bansal Department of Pediatrics (Hematology-Oncology Division), Post Graduate Institute of Medical Education and Research, Chandigarh, India
Nandita Kakkar Histopathology, Post Graduate Institute of Medical Education and Research, Chandigarh, India
Radhika Srinivasan Cytology & Gynecological Pathology, Post Graduate Institute of Medical Education and Research, Chandigarh, India

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Survival of Patients With Neuroblastoma After Assignment to Reduced Therapy Because of the 12- to 18-Month Change in Age Cutoff in Children's Oncology Group Risk Stratification

PURPOSE

In 2006, Children's Oncology Group (COG) reclassified subgroups of toddlers diagnosed with neuroblastoma from high-risk to intermediate-risk, when the age cutoff for high-risk assignment was raised from 365 days (12 months) to 547 days (18 months). The primary aim of this retrospective study was to determine if excellent outcome was maintained after assigned reduction of therapy.

PATIENTS AND METHODS

Children <3 years old at diagnosis, enrolled on a COG biology study from 1990 to 2018, were eligible (n = 9,189). Assigned therapy was reduced for two cohorts of interest on the basis of the age cutoff change: 365-546 days old with International Neuroblastoma Staging System (INSS) stage 4, MYCN not amplified (MYCN-NA), favorable International Neuroblastoma Pathology Classification (INPC), hyperdiploid tumors (12-18mo/Stage4/FavBiology), and 365-546 days old with INSS stage 3, MYCN-NA, and unfavorable INPC tumors (12-18mo/Stage3/MYCN-NA/Unfav). Log-rank tests compared event-free survival (EFS) and overall survival (OS) curves.

RESULTS

For 12-18mo/Stage4/FavBiology, 5-year EFS/OS (± SE) before (≤2006; n = 40) versus after (>2006; n = 55) assigned reduction in therapy was similar: 89% ± 5.1%/89% ± 5.1% versus 87% ± 4.6%/94% ± 3.2% (P = .7; P = .4, respectively). For 12-18mo/Stage3/MYCN-NA/Unfav, the 5-year EFS and OS were both 100%, before (n = 6) and after (n = 4) 2006. The 12-18mo/Stage4/FavBiology plus 12-18mo/Stage3/MYCN-NA/Unfav classified as high-risk ≤2006 had an EFS/OS of 91% ± 4.4%/91% ± 4.5% versus 38% ± 1.3%/43% ± 1.3% for all other high-risk patients <3 years old (P < .0001; P < .0001, respectively). The 12-18mo/Stage4/FavBiology plus 12-18mo/Stage3/MYCN-NA/Unfav classified as intermediate-risk >2006 had an EFS/OS of 88% ± 4.3%/95% ± 2.9% versus 88% ± 0.9%/95% ± 0.6% for all other intermediate-risk patients <3 years old (P = .87; P = .85, respectively).

CONCLUSION

Excellent outcome was maintained among subsets of toddlers with neuroblastoma assigned to reduced treatment after reclassification of risk group from high to intermediate on the basis of new age cutoffs. Importantly, as documented in prior trials, intermediate-risk therapy is not associated with the degree of acute toxicity and late effects commonly observed with high-risk regimens.

Whole-tumor radiomics analysis of T2-weighted imaging in differentiating neuroblastoma from ganglioneuroblastoma/ganglioneuroma in children: an exploratory study

PURPOSE

To examine the potential of whole-tumor radiomics analysis of T2-weighted imaging (T2WI) in differentiating neuroblastoma (NB) from ganglioneuroblastoma/ganglioneuroma (GNB/GN) in children.

MATERIALS AND METHODS

This study included 102 children with peripheral neuroblastic tumors, comprising 47 NB patients and 55 GNB/GN patients, which were randomly divided into a training group (n = 72) and a test group (n = 30). Radiomics features were extracted from T2WI images, and feature dimensionality reduction was applied. Linear discriminant analysis was used to construct radiomics models, and one-standard error role combined with leave-one-out cross-validation was used to choose the optimal radiomics model with the least predictive error. Subsequently, the patient age at initial diagnosis and the selected radiomics features were incorporated to construct a combined model. The receiver operator characteristic (ROC) curve, decision curve analysis (DCA) and clinical impact curve (CIC) were applied to evaluate the diagnostic performance and clinical utility of the models.

RESULTS

Fifteen radiomics features were eventually chosen to construct the optimal radiomics model. The area under the curve (AUC) of the radiomics model in the training group and test group was 0.940 [95% confidence interval (CI) 0.886, 0.995] and 0.799 (95%CI 0.632, 0.966), respectively. The combined model, which incorporated patient age and radiomics features, achieved an AUC of 0.963 (95%CI 0.925, 1.000) in the training group and 0.871 (95%CI 0.744, 0.997) in the test group. DCA and CIC demonstrated that the radiomics model and combined model could provide benefits at various thresholds, with the combined model being superior to the radiomics model.

CONCLUSION

Radiomics features derived from T2WI, in combination with the age of the patient at initial diagnosis, may offer a quantitative method for distinguishing NB from GNB/GN, thus aiding in the pathological differentiation of peripheral neuroblastic tumors in children.

Identification of a novel eighteen-gene signature of recurrent metastasis neuroblastoma

Neuroblastoma is the most common malignant tumor in childhood, and metastases occur in more than 30% patients. Recurrent metastasis is the main cause of poor prognosis and high mortality in neuroblastoma. In this regard, there is still a lack of sufficient biomarkers and effective therapies. Therefore, we performed a multi-omics analysis of neuroblastoma patients from Therapeutically Applicable Research To Generate Effective Treatments (TARGET). With clinical relapse site information, tumor samples derived from the primary site were divided into recurrent metastasis and primary tumor groups. The initial gene signature was obtained by comparing RNA-Seq and copy number variation differences. Survival data was used to further filter prognosis-related genes. This 18-gene signature consists of three clusters: tumor suppression, cell proliferation, and immunity. A super enhancer is involved in the enhanced expression of NCAPG in cluster2 together with IRF3. Based on the gene signature expression in primary neuroblastoma, it is possible to predict tumor metastasis before it occurs. According to the anticancer drug dataset of Genomics of Drug Sensitivity in Cancer (GDSC), vinorelbine and docetaxel were predicted to have high sensitivity against recurrent metastatic neuroblastoma. In conclusion, our study offers a novel metastasis biomarker and helps understand the mechanisms of tumor recurrent metastasis. KEY MESSAGES: We identified a novel eighteen-gene signature of recurrent metastasis neuroblastoma and build risk and classification models. We dissected the regulatory role of NCAPG in signatures. We found immune exhaustion and immunosuppression in recurrent metastasis neuroblastoma. Vinorelbine and docetaxel were predicted to have high sensitivity against recurrent metastatic neuroblastoma.

Combining multiple cell death pathway-related risk scores to develop neuroblastoma cell death signature

PURPOSE

Cell death plays an important role in tumourigenesis and progression; nevertheless, the clinical significance of cell death-related genes in neuroblastoma remains incompletely understood.

METHODS

We separately constructed the corresponding risk scores for each of the eight cell death pathways separately and assessed their predictive performance. Through Cox regression analysis, these eight risk scores were integrated to obtain final cell death risk scores (CDRS). We evaluated the predictive performance of CDRS in multiple datasets and compared its accuracy with the clinical characteristics of patients and some existing prognostic models for neuroblastoma. We then explored the differences in immune infiltration between the high and low CDRS groups, and the significance of CDRS on EFS and disease progression.

RESULTS

All eight risk scores have high predictive accuracy, with the Immunogenic-RS being the most accurate and the cuproptosis-RS the least accurate. Model genes are mainly enriched in a variety of cancer-related pathways and are closely related to the clinical characteristics. CDRS showed superior and robust predictive performance in multiple datasets and was more accurate than the clinical characteristics of patients and some existing prognostic models for neuroblastoma. High CDRS group featured distinct immune cold tumor profiles and may have poorer immune checkpoint inhibitor efficacy. CDRS had significance in predicting EFS and disease progression.

CONCLUSION

We integrated risk scores associated with multiple cell death pathways to develop a high-performing and robust neuroblastoma signature. CDRS was a promising tool that may help with risk assessment and prediction of overall prognosis, and thus improve clinical outcomes.

A nomogram for the preoperative estimation of neuroblastoma risk despite inadequate biopsy information

BACKGROUND AND PURPOSE

If the preoperative pathological information is inadequate, a risk classification may not be able to be determined for some patients with neuroblastoma. Our objectives were to include imaging factors, serum biomarkers, and demographic factors in a nomogram to distinguish high-risk patients before surgical resection based on the COG classification.

METHOD

A total of 106 patients were included in the study. Of these, patients with clinicopathologically confirmed neuroblastoma at Tianjin Children's Hospital from January 2013 to November 2021 formed the training cohort (n = 82) for nomogram development, and those patients from January 2010 to December 2013 formed the validation cohort (n = 24) to confirm the model's performance.

RESULT

On multivariate analysis of the primary cohort, independent factors for high risk were the presence of distant metastasis (p = 0.004), lactate dehydrogenase (LDH) (p = 0.009), and tumor volume (p = 0.033), which were all selected into the nomogram. The calibration curve for probability showed good agreement between prediction by nomogram and actual observation. The C-index of the nomogram was 0.95 95% [0.916-0.99]. Application of the nomogram in the validation cohort still gave good discrimination and good calibration.

CONCLUSION

Three independent factors including the presence of distant metastasis, lactate dehydrogenase (LDH), and tumor volume are associated with high-risk neuroblastoma and selected into the nomogram. The novel nomogram has the flexibility to apply a clinically suitable cutoff to identify high-risk neuroblastoma patients despite inadequate preoperative pathological information. The nomogram can allow these patients to be offered suitable induction chemotherapy regimens and surgical plans.

LEVELS OF EVIDENCE

Level III.

A Novel Online Nomogram Established with Five Features before Surgical Resection for Predicating Prognosis of Neuroblastoma Children: A Population-Based Study

Background: Neuroblastoma (NB) is the most common childhood cancer, but doctors are unable to predict its overall survival (OS) rate before surgery. We aimed to predict the OS of NB children with some clinical features obtained from biopsy before surgery. Methods: Clinical features of NB children were retrospectively collected from the Therapeutically Applicable Research to Generate Effective Treatments database. The C-index, area under the receiver operating characteristic curve (AUC), calibration curves, and decision curves analysis were used to estimate nomogram models. Results: A total of 488 NB children were evaluated, and the Boruta algorithm was used to detect risk factors. The results showed that artificial neural networks with selected features were able to predict more than 90% of NB children. Five risk factors were used in the construction of the nomogram, including age at diagnosis, MYCN status, ploidy value, histology, and mitosis-karyorrhexis index (MKI). The C-index of the nomogram in training cohort and validation cohort was 0.716 and 0.731. AUC values for 1-, 3-, and 5-years OS predictions were 0.706, 0.755, and 0.762, respectively, and showed good calibrations. Decision curve analysis indicated a better predictability with the nomogram model based on Cox regression compared with one that included all variables and histology only. Also, the Kaplan-Meier curves showed a significantly higher survival probability in the low-risk group (total score <118.34) versus the high-risk group (total score ≥ 118.34) (p < 0.05) using the nomogram model. Conclusions: A web application based on the nomogram model in the present study can be accessed at https://mdzhou.shinyapps.io/DynNomapp/, which could help doctors make accurate clinical decisions about NB children.

18F-FDG PET/CT imaging of pediatric peripheral neuroblastic tumor: a combined model to predict the International Neuroblastoma Pathology Classification

Background

The aim of this study was to evaluate the effect of a model combining a 18F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT)-based radiomics signature with clinical factors in the preoperative prediction of the International Neuroblastoma Pathology Classification (INPC) type of pediatric peripheral neuroblastic tumor (pNT).

Methods

A total of 106 consecutive pediatric pNT patients confirmed by pathology were retrospectively analyzed. Significant features determined by multivariate logistic regression were retained to establish a clinical model (C-model), which included clinical parameters and PET/CT radiographic features. A radiomics model (R-model) was constructed on the basis of PET and CT images. A semiautomatic method was used for segmenting regions of interest. A total of 1,016 radiomics features were extracted. Univariate analysis and the least absolute shrinkage selection operator were then used to select significant features. The C-model was combined with the R-model to establish a combination model (RC-model). The predictive performance was validated by receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA) in both the training cohort and validation cohort.

Results

The radiomics signature was constructed using 5 selected radiomics features. The RC-model, which was based on the 5 radiomics features and 3 clinical factors, showed better predictive performance compared with the C-model alone [area under the curve in the validation cohort: 0.908 vs. 0.803; accuracy: 0.903 vs. 0.710; sensitivity: 0.895 vs. 0.789; specificity: 0.917 vs. 0.583; net reclassification improvement (NRI) 0.439, 95% confidence interval (CI): 0.1047-0.773; P=0.01]. The calibration curve showed that the RC-model had goodness of fit, and DCA confirmed its clinical utility.

Conclusions

In this preliminary single-center retrospective study, an R-model based on ¹⁸F-FDG PET/CT was shown to be promising in predicting INPC type in pediatric pNT, allowing for the noninvasive prediction of INPC and assisting in therapeutic strategies.

Establishment and validation of a nomogram to predict cancer-specific survival in pediatric neuroblastoma patients

Background

The term "neuroblastoma (NB)" refers to a type of solid pediatric tumor that develops from undivided neuronal cells. According to the American Cancer Society report, between 700 and 800 children under the age of 14 are diagnosed with NB every year in the United States (U.S.). About 6% of all cases of pediatric cancer in the U.S. are caused by NB. NB is the most frequent malignancy in children younger than 1 year; however, it is rarely found in those over the age of 10 and above.

Objective

To accurately predict cancer-specific survival (CSS) in children with NB, this research developed and validated an all-encompassing prediction model.

Methods

The present retrospective study used the Surveillance, Epidemiology, and End Results (SEER) database to collect information on 1,448 individuals diagnosed with NB between 1998 and 2019. The pool of potentially eligible patients was randomly split into two groups, a training cohort (N = 1,013) and a validation cohort (N = 435). Using multivariate Cox stepwise regression, we were able to identify the components that independently predicted outcomes. The accuracy of this nomogram was measured employing the consistency index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), calibration curve, and decision-curve analysis (DCA).

Results

In this study, we found that age, primary location, tumor size, summary stage, chemotherapy, and surgery were all significant predictors of CSS outcomes and integrated them into our model accordingly. The C-index for the validation cohort was 0.812 (95% CI: 0.773-0.851), while for the training cohort it was 0.795 (95% CI: 0.767-0.823). The C-indexes and AUC values show that the nomogram is able to discriminate well enough. The calibration curves suggest that the nomogram is quite accurate. Also, the DCA curves demonstrated the prediction model's value.

Conclusion

A novel nomogram was developed and validated in this work to assess personalized CSS in NB patients, and it has been indicated that this model could be a useful tool for calculating NB patients' survival on an individual basis and enhancing therapeutic decision-making.

A nomogram for predicting recurrence-free survival of intermediate and high-risk neuroblastoma

This study aimed to confirm the independent risk factors for recurrence-free survival (RFS) in intermediate and high-risk neuroblastoma (NB) patients and set up an effective nomogram model for predicting the recurrence of NB. A total of 212 children with intermediate- and high-risk neuroblastoma, who had ever achieved complete remission (CR) or very good partial remission (VGPR) after standardized treatment in this hospital, were chosen as study objects. After retrospective analysis of the clinical data, Cox regression model was used to explore the factors related to the recurrence of neuroblastoma, to determine the variables to construct the Nomogram. The consistency index would predict the accuracy of this nomogram. RFS rate in 1-year, 3-year, 5-year, and 10-year was 0.811, 0.662, 0.639, and 0.604, respectively. Children with MYCN amplification had a higher neuron-specific enolase (NSE) value (P = 0.031) at the initial diagnosis than MYCN non-amplification. The univariate analysis predicted that increased vanillylmandelic acid (VMA) and NSE value and dehydrogenase (LDH) > 1000 U/L were important adverse factors for the recurrence of NB. Multivariate analysis demonstrated that age at diagnosis, tumor localization, MYCN state, histologic subtype, and tumor capsule were significantly associated with RFS (all P values < 0.05). Nomograms were established for predicting the recurrence of NB according to the Cox regression analysis. Internal verification by the Bootstrap method showed that the prediction of the nomogram's consistency index (C-index) was 0.824 (P = 0.023).   Conclusion: Age at diagnosis, tumor localization, MYCN state, histologic category, and tumor capsule were independent risk factors for the recurrence of NB. The nomogram model could accurately predict the recurrence of children with neuroblastoma. What is Known: • The prognoses of neuroblastoma (NB) could vary greatly due to the high heterogeneity, the 5-year survival rate of low-risk NB exceeded 90%, while the 5-year survival rate of children in the intermediate and high-risk groups was not satisfactory.. What is New: • Increased vanillylmandelic acid (VMA) and neuron-specific enolase (NSE) value, and lactate dehydrogenase (LDH)>1000U/L were important adverse factors for the recurrence of NB. • NSE value was more valuable for predicting NB recurrence.

Association of Image-Defined Risk Factors with Clinical, Biological Features and Outcome in Neuroblastoma

Background: Neuroblastoma (NB) is the most common pediatric extracranial solid tumor and the most common cancer encountered in children younger than 12 months of age. Localized tumors have a good prognosis, but some cases undergo treatment failure and recurrence. The aim of the study was to analyze the link between the neuroblastoma risk factors and the prognosis for patients diagnosed with NB. Method: All patients admitted to the department of Pediatric Surgery, “Grigore Alexandrescu” Clinical Emergency Hospital for Children, between 1 January 2010 and 1 July 2022 were included in this analysis when diagnosed with neuroblastoma. Results: Thirty-one patients with NB were admitted to the surgical department, 20 boys and 11 girls. We observed an association between large tumors and positive imaging-defined risk factor (IDRF) status; The Fisher test showed an association between the tumor’s diameter when bigger than 8 cm and a positive IDRF status, with p < 0.001. We supposed that positive IDRF status at diagnosis may be linked to other prognostic factors. We discovered that an NSE value over 300 was associated with IDRF status (p < 0.001, phi = 0.692) and death. Conclusions: This study confirms the impact of IDRF status at diagnosis as it can be clearly correlated with other risk factors, such as a high level of NSE, MYCN amplification status, large tumor size, incomplete tumor resection, and an unfavorable outcome.

GDPD5 Related to Lipid Metabolism Is a Potential Prognostic Biomarker in Neuroblastoma

Neuroblastoma (NB) is an extracranial solid tumor in children with poor prognosis in high-risk patients and its pathogenesis and prognostic markers urgently need to be explored. This study aimed to explore potential biomarkers related to NB from the aspect of lipid metabolism. Fifty-eight lipid metabolism-related differentially expressed genes between high-risk NB and non-high-risk NB in the GSE49710 dataset were analyzed using bioinformatics, including 45 down-regulated genes and 13 up-regulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified steroid hormone biosynthesis as an abnormal metabolic pathway in high-risk NB. Survival analysis established a three-gene prognostic model, including ACHE, GDPD5 and PIK3R1. In the test data, the AUCs of the established prognostic models used to predict patient survival at 1, 3 and 5 years were 0.84, 0.90 and 0.91, respectively. Finally, in the SH-SY5Y cell line, it was verified that overexpression of GDPD5 can inhibit cell proliferation and migration, as well as affect the lipid metabolism of SH-SY5Y, but not the sugar metabolism. hsa-miR-592 was predicted to be a potential target miRNA of GDPD5 by bioinformatics. In conclusion, this study develops a lipid-metabolism-related gene-based prognostic model for NB and demonstrates that GDPD5 inhibits SH-SY5Y proliferation and migration and may be targeted by hsa-miR-592 and inhibit SH-SY5Y fat synthesis.

Prognostic value of texture analysis of the primary tumour in high-risk neuroblastoma: An 18 F-DOPA PET study

PURPOSE

To evaluate the prognostic value of texture analysis of the primary tumour with ¹⁸ fluorine-dihydroxyphenylalanine positron emission tomography/X-ray computed tomography (¹⁸ F-DOPA PET/CT) in patients affected by high-risk neuroblastoma (HR-NBL).

METHODS

We retrospectively analysed 18 patients with HR-NBL, which had been prospectively enrolled in the course of a previous trial investigating the diagnostic role of ¹⁸ F-DOPA PET/CT at the time of the first onset. Texture analysis of the primary tumour was carried out on the PET images using LifeX. Conventional indices, histogram parameters, grey level co-occurrence (GLCM), run-length (GLRLM), neighbouring difference (NGLDM) and zone-length (GLZLM) matrices parameter were extracted; their values were compared with the overall metastatic load, expressed by means of whole-body metabolic burden (WBMB) score and the progression-free/overall survival (PFS and OS).

RESULTS

There was a direct correlation between WBMB and radiomics parameter describing uptake intensity (SUV_mean : p = .004) and voxel heterogeneity (entropy: p = .026; GLCM_Contrast: p = .001). Conversely, texture indices of homogeneity showed an inverse correlation with WBMB (energy: p = .026; GLCM_Homogeneity: p = .006). On the multivariate model, WBMB (p < .01) and the first standardised uptake value (SUV) quartile (p < .001) predicted PFS; OS was predicted by WBMB and the N-myc proto-oncogene protein (MYCN) amplification (p < .05) for both.

CONCLUSIONS

Textural parameters describing heterogeneity and metabolic intensity of the primary HR-NBL are closely associated with its overall metastatic burden. In turn, the whole-body tumour load appears to be one of the most relevant predictors of progression-free and overall survival.

MYCN Impact on High-Risk Neuroblastoma: From Diagnosis and Prognosis to Targeted Treatment

Among childhood cancers, neuroblastoma is the most diffuse solid tumor and the deadliest in children. While to date, the pathology has become progressively manageable with a significant increase in 5-year survival for its less aggressive form, high-risk neuroblastoma (HR-NB) remains a major issue with poor outcome and little survivability of patients. The staging system has also been improved to better fit patient needs and to administer therapies in a more focused manner in consideration of pathology features. New and improved therapies have been developed; nevertheless, low efficacy and high toxicity remain a staple feature of current high-risk neuroblastoma treatment. For this reason, more specific procedures are required, and new therapeutic targets are also needed for a precise medicine approach. In this scenario, MYCN is certainly one of the most interesting targets. Indeed, MYCN is one of the most relevant hallmarks of HR-NB, and many studies has been carried out in recent years to discover potent and specific inhibitors to block its activities and any related oncogenic function. N-Myc protein has been considered an undruggable target for a long time. Thus, many new indirect and direct approaches have been discovered and preclinically evaluated for the interaction with MYCN and its pathways; a few of the most promising approaches are nearing clinical application for the investigation in HR-NB.

Pathological prognosis classification of patients with neuroblastoma using computational pathology analysis

Neuroblastoma is the most common extracranial solid tumor in early childhood. International Neuroblastoma Pathology Classification (INPC) is a commonly used classification system that provides clinicians with a reference for treatment stratification. However, given the complex and subjective assessment of the INPC, there will be inconsistencies in the analysis of the same patient by multiple pathologists. An automated, comprehensive and objective classification method is needed to identify different prognostic groups in patients with neuroblastoma. In this study, we collected 563 hematoxylin and eosin-stained histopathology whole-slide images from 107 patients with neuroblastoma who underwent surgical resection. We proposed a novel processing pipeline for nuclear segmentation, cell-level image feature extraction, and patient-level feature aggregation. Logistic regression model was built to classify patients with favorable histology (FH) and patients with unfavorable histology (UH). On the training/test dataset, patient-level of nucleus morphological/intensity features and age could correctly classify patients with a mean area under the receiver operating characteristic curve (AUC) of 0.946, a mean accuracy of 0.856, and a mean Matthews Correlation Coefficient (MCC) of 0.703,respectively. On the independent validation dataset, the classification model achieved a mean AUC of 0.938, a mean accuracy of 0.865 and a mean MCC of 0.630, showing good generalizability. Our results suggested that automatically derived image features could identify the differences in nuclear morphological and intensity between different prognostic groups, which could provide a reference to pathologists and facilitate the evaluation of the pathological prognosis in patients with neuroblastoma.

[Clinical efficacy of combined therapy in children with stage 4 neuroblastoma]

OBJECTIVES

To study the early clinical efficacy of combined therapy of stage 4 neuroblastoma.

METHODS

A retrospective analysis was performed on the medical data and follow-up data of 14 children with stage 4 neuroblastoma who were diagnosed in Hong Kong University-Shenzhen Hospital from January 2016 to June 2021.

RESULTS

The median age of onset was 3 years and 7.5 months in these 14 children. Among these children, 9 had positive results of bone marrow biopsy, 4 had N-Myc gene amplification, 13 had an increase in neuron-specific enolase, and 7 had an increase in vanilmandelic acid in urine. Based on the results of pathological examination, differentiated type was observed in 6 children, undifferentiated type in one child, mixed type, in one child and poorly differentiated type in 6 children. Of all the children, 10 received chemotherapy with the N7 regimen (including 2 children receiving arsenic trioxide in addition) and 4 received chemotherapy with the Rapid COJEC regimen. Thirteen children underwent surgery, 14 received hematopoietic stem cell transplantation, and 10 received radiotherapy. A total of 8 children received Ch14.18/CHO immunotherapy, among whom 1 child discontinued due to anaphylactic shock during immunotherapy, and the other 7 children completed Ch14.18/CHO treatment without serious adverse events, among whom 1 child was treated with Lu177 Dotatate 3 times after recurrence and is still undergoing chemotherapy at present. The median follow-up time was 45 months for all the 14 children. Four children experienced recurrence within 2 years, and the 2-year overall survival rate was 100%; 4 children experienced recurrence within 3 years, and 7 achieved disease-free survival within 3 years.

CONCLUSIONS

Multidisciplinary combined therapy is recommended for children with stage 4 neuroblastoma and can help them achieve better survival and prognosis.

Extracellular Vesicle-Based Method for Detecting MYCN Amplification Status of Pediatric Neuroblastoma

Simple Summary

MYCN gene amplification, the strongest prognostic marker of aggressive neuroblastoma, is detected on invasive biopsy tissues. This study aimed to establish a less invasive method to detect MYCN status based on MYCN mRNA contents in large extracellular vesicles or microvesicles. MYCN mRNA-containing microvesicles were detectable in three distinct MYCN-amplified neuroblastoma cell lines but absent in three neuroblastoma cells with MYCN-non-amplification. The feasibility of this EV-based workflow was successfully demonstrated by using the simulated samples (prepared by pulsing neuroblastoma MVs into the normal human serum) and bone marrow plasma specimens obtained from nine patients at various disease stages. Taken together, this study established the novel EV-based method for detecting MYCN status in pediatric neuroblastoma.

Abstract

MYCN amplification is the strongest predictor of high-risk neuroblastoma (NB). The standard procedure to detect MYCN status requires invasive procedures. Extracellular vesicles (EVs) contain molecular signatures of originated cells, present in biofluids, and serve as an invaluable source for cancer liquid biopsies. This study aimed to establish an EV-based method to detect the MYCN status of NB. Two EV subtypes, i.e., microvesicles (MVs) and exosomes, were sequentially isolated from the culture supernatant by step-wise centrifugation, ultrafiltration, and size-exclusion chromatography. Quantitative RT-PCR was performed to detect MYCN mRNA. As a result, MYCN mRNA was detectable in the MVs, but not exosomes, of MYCN-amplified NB cells. MYCN mRNA-containing MVs (MYCN-MV) were successfully detected in three distinct MYCN-amplified NB cell lines but absent in three MYCN non-amplification cells. The simulated samples were prepared by pulsing MVs into human serum. MYCN–MV detection in the simulated samples showed a less interfering effect from the human blood matrix. Validation using clinical specimens (2 mL bone marrow plasma) obtained from patients at various disease stages showed a promising result. Five out of six specimens of MYCN-amplified patients showed positive results, while there were no false positives in four plasma samples of the MYCN non-amplification group. This study communicated a novel EV-based method for detecting the MYCN status of pediatric NB based on MYCN mRNA contents in MVs. Future studies should be pursued in a prospective cohort to determine its true diagnostic performance.

Identification and Validation of Inflammatory Response-Related Gene Signatures to Predict the Prognosis of Neuroblastoma

Background. Neuroblastoma (NB) is the third most common malignant tumor in children. The inflammation is believed to be closely related to NB patients’ prognosis. However, there is no comprehensive research to study the role of inflammatory response-related gene (IRRG) in NB patients. Methods. We downloaded the gene expression profiles of NB patients from GEO and TARGET database, and the expression of 200 IRRGs was extracted. Then, we performed differentially analysis between INSS stage 4 and INSS stage 4S NB patients. The univariate and multivariate Cox regression analyses were performed to screen out the overall survival- (OS-) and event-free survival- (EFS-) related IRRGs in GSE49710, and two signatures were constructed; both signatures were evaluated by Kaplan-Meier (K-M) survival curve and receiver operating characteristic (ROC) curve. Finally, the TARGET cohort was used to validate IRRG signatures, and the independence of the prognostic IRRG signatures was evaluated by integrating clinical information. Results. We screened out 10 OS-related IRRGs and 11 EFS-related IRRGs. Then, we identified that OS- and EFS-related IRRG signatures and found that the OS and EFS of NB patients in the low-risk group were significantly superior than those in the high-risk group (both $P$ value < 0.0001). The AUC values of 3-, 5-, and 7-year OS are 0.910, 0.933, and 0.921, respectively, and 3-, 5-, and 7-year EFS are 0.840, 0.835, and 0.837, respectively. In addition, we found that both IRRG signatures can be used as independent prognostic indicators for patients with NB. Both IRRG signatures still have good predictive ability in validation cohort. Conclusions. We constructed and validated two prognostic gene signatures based on IRRGs. Our study helped us to better understand the role of inflammation in NB and provided new insights for the prognosis assessment and treatment strategy for NB patients.

Using a Gene Network of Pyroptosis to Quantify the Responses to Immunotherapy and Prognosis for Neuroblastoma Patients

Background

Pyroptosis, as an inflammatory form of cell death, is involved in many physiological and pathological processes. Neuroblastoma is the most common extra-cranial solid tumor in children. In this study, the relationship between pyroptosis and tumor microenvironment in neuroblastoma was systematically studied.

Methods

We integrated four datasets of neuroblastomas. Through robust clustering of the mRNA expression profiles of 24 pyroptosis-related genes, a total of three pyroptosis patterns were identified. We then constructed a novel scoring method named as pyroscore to quantify the level of pyroptosis in neuroblastoma. Multi-omics data and single-cell RNA sequencing were used to accurately and comprehensively evaluate the effectiveness of pyroscore. Clinical data sets were used to evaluate the use of pyroscore to predict the responsiveness of immune checkpoint treatment.

Results

High pyroscore was associated with good prognosis, immune activation, and increased response to checkpoint blockade immunotherapy. Multivariate Cox analysis revealed that the pyroscore was an independent prognostic biomarker and could increase the accuracy of clinical prediction models. Etoposide, a drug picked up by our analysis, could increase the sensitivity of neuroblastoma cells to pyroptosis. External verification using four cohorts of patients who had received immunotherapy showed that high pyroscore was significantly associated with immunotherapy treatment benefit.

Conclusions

Taken together, this study revealed that pyroptosis-related gene network could quantify the response of neuroblastoma to immune checkpoint blockade therapy and prognosis, and it may be helpful for clinical practitioners to choose treatment strategies for neuroblastoma patients.

Identification of a Glycosyltransferase Signature for Predicting Prognosis and Immune Microenvironment in Neuroblastoma

Neuroblastoma (NB) is one of the most common solid tumors in children. Glycosyltransferases (GTs) play a crucial role in tumor development and immune escape and have been used as prognostic biomarkers in various tumors. However, the biological functions and prognostic significance of GTs in NB remain poorly understood. The expression data from Gene Expression Omnibus (GEO) and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) were collected as training and testing data. Based on a progression status, differentially expressed GTs were identified. We constructed a GTscore through support vector machine, least absolute shrinkage and selection operator, and Cox regression in NB, which included four prognostic GTs and was an independent prognostic risk factor for NB. Patients in the high GTscore group had an older age, MYCN amplification, advanced International Neuroblastoma Staging System stage, and high risk. Samples with high GTscores revealed high disialoganglioside (GD2) and neuron-specific enolase expression levels. In addition, a lack of immune cell infiltration was observed in the high GTscore group. This GTscore was also associated with the expression of chemokines (CCL2, CXCL9, and CXCL10) and immune checkpoint genes (cytotoxic T-lymphocyte–associated protein 4, granzyme H, and granzyme K). A low GTscore was also linked to an enhanced response to anti–PD-1 immunotherapy in melanoma patients, and one type of tumor was also derived from neuroectodermal cells such as NB. In conclusion, the constructed GTscore revealed the relationship between GT expression and the NB outcome, GD2 phenotype, and immune infiltration and provided novel clues for the prediction of prognosis and immunotherapy response in NB.

Prediction for Mitosis-Karyorrhexis Index Status of Pediatric Neuroblastoma via Machine Learning Based 18F-FDG PET/CT Radiomics

Accurate differentiation of intermediate/high mitosis-karyorrhexis index (MKI) from low MKI is vital for the further management of neuroblastoma. The purpose of this research was to investigate the efficacy of ¹⁸F-FDG PET/CT–based radiomics features for the prediction of MKI status of pediatric neuroblastoma via machine learning. A total of 102 pediatric neuroblastoma patients were retrospectively enrolled and divided into training (68 patients) and validation sets (34 patients) in a 2:1 ratio. Clinical characteristics and radiomics features were extracted by XGBoost algorithm and were used to establish radiomics and clinical models for MKI status prediction. A combined model was developed, encompassing clinical characteristics and radiomics features and presented as a radiomics nomogram. The predictive performance of the models was evaluated by AUC and decision curve analysis. The radiomics model yielded AUC of 0.982 (95% CI: 0.916, 0.999) and 0.955 (95% CI: 0.823, 0.997) in the training and validation sets, respectively. The clinical model yielded AUC of 0.746 and 0.670 in the training and validation sets, respectively. The combined model demonstrated AUC of 0.988 (95% CI: 0.924, 1.000) and 0.951 (95% CI: 0.818, 0.996) in the training and validation sets, respectively. The radiomics features could non-invasively predict MKI status of pediatric neuroblastoma with high accuracy.

Characterization of m6A-related lncRNA signature in neuroblastoma

N6-methyladenosine (m6A) constitutes one of the most common modifications in mRNA, rRNA, tRNA, microRNA, and long-chain noncoding RNA. The influence of modifications of m6A on the stability of RNA depends upon the expression of methyltransferase ("writer") and demethylase ("eraser") and m6A binding protein ("reader"). In this study, we identified a set of m6A-related lncRNA expression profiles in neuroblastoma (NBL) based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program. Thereupon, we identified two subgroups of neuroblastoma (high-risk group and low-risk group) by applying consensus clustering to m6A RNA methylation regulators ("Readers,", "Writer," and "Erase"). Relative to the low-risk group, the high-risk group correlates with a poorer prognosis. Moreover, the present study also revealed that the high-risk group proves to be significantly positively enriched in the tumor-related signaling pathways, including the P53 signaling pathway, cell cycle, and DNA repair. This finding indicates that these molecular prognostic markers may also be potentially valuable in early diagnosis, which provides a new research direction for the study of molecular mechanisms underlying the development of NBL. In conclusion, this study constructed a new model of NBL prognosis based on m6a-associated lncRNAs. Ultimately, this model is helpful for stratification of prognosis and development of treatment strategies.

Upfront Treatment of Pediatric High-Risk Neuroblastoma With Chemotherapy, Surgery, and Radiotherapy Combination: The CCCG-NB-2014 Protocol

Purpose

The Chinese Children’s Cancer Group developed the CCCG-NB-2014 study to formulate optimal treatment strategies for high-risk (HR) neuroblastoma (NB). The safety and efficacy of this protocol were evaluated.

Method

Patients with newly diagnosed neuroblastoma and defined as HR according to the Children’s Oncology Group study were included. They were treated with a combination of chemotherapy, surgery, and radiotherapy. The treatment-related toxicities, response rate, 3-year progression-free survival (PFS), and overall survival (OS) were analyzed.

Results

Of 159 patients enrolled between 2014 and 2018, 80 were eligible, including 19 girls and 61 boys, with a median age of 3.9 years (range 0.9–11). After a median follow-up of 24 months (range 3–40), the median OS was 31.8 months, and 3-year OS was 83.8%. In multivariate analyses, the OS was affected by N-MYC amplification (hazard ratio 0.212, 95% confidence interval (CI) 0.049–0.910; p = 0.037) and giant tumor mass (hazard ratio 0.197, 95% CI 0.071–0.552; p = 0.002). The median 3-year PFS was 25.8 months, and 3-year PFS was 57.5%. The univariate analysis showed that only the giant tumor mass was associated with the outcome. Of the 13 deaths, 11 died from the rapid progression of the disease and two from treatment-related toxicities. The most common adverse reaction was chemotherapy-induced hematological toxicity.

Conclusion

The PFS and OS reported in our study were similar to Western countries. The CCCG-NB-2014 protocol proved to be an efficient regimen with tolerable side-effect for the treatment of pediatric HR-NB.

Mitosis-Karyorrhexis Index evaluation by digital image visual analysis for application of International Neuroblastoma Pathology Classification in FNA biopsy

BACKGROUND

The Mitosis-Karyorrhexis Index (MKI) score is important in neuroblastoma evaluation and in the application of the International Neuroblastoma Pathology Classification (INPC). Currently, it is not standardized for smears. Hence, the aim of this study was to devise and validate methods for MKI evaluation in fine-needle aspiration biopsy (FNAB) of neuroblastoma.

METHODS

A total of 50 cases of neuroblastoma diagnosed by FNAB from January 2017 to December 2019 were retrieved, and detailed cytomorphological evaluations were performed. The MKI was evaluated, and the eyeball visual assessment score (EVAS) was compared with the digital image visual analysis score (DIVAS) on cytology smears and corresponding histology sections of cell blocks. The interobserver reproducibility and concordance were calculated. INPC subtyping into favorable and unfavorable groups was performed by the collation of age, MKI, and cytomorphology and was correlated to clinical outcomes.

RESULTS

Neuroblastoma was categorized as undifferentiated (22 of 50) or poorly differentiated (28 of 50) on cytomorphology. The overall concordance for the MKI by 3 observers was 86% (κ = 0.85), and this increased to 98% in the high MKI category. MKI evaluations on smears showed 96% concordance with cell block histology, and the EVAS was concordant with the DIVAS in 86% of the cases. Overall, the MKI was high in 39 cases, intermediate in 4 cases, and low in 7 cases. The INPC category was unfavorable in 90% (n = 45) and favorable in 10% (n = 5) and had significant correlations with outcomes (P = .029).

CONCLUSIONS

An MKI assessment on smears by digital image visual analysis is accurate, reproducible, and objective and should be incorporated into the routine reporting of neuroblastoma FNAB for diagnostic schemas as per the INPC.

Revised Neuroblastoma Risk Classification System: A Report From the Children's Oncology Group

PURPOSE

Treatment planning for children with neuroblastoma requires accurate assessment of prognosis. The most recent Children's Oncology Group (COG) risk classification system used tumor stage as defined by the International Neuroblastoma Staging System. Here, we validate a revised classifier using the International Neuroblastoma Risk Group Staging System (INRGSS) and incorporate segmental chromosome aberrations (SCA) as an additional genomic biomarker.

METHODS

Newly diagnosed patients enrolled on the COG neuroblastoma biology study ANBL00B1 between 2007 and 2017 with known age, International Neuroblastoma Staging System, and INRGSS stage were identified (N = 4,832). Tumor MYCN status, ploidy, SCA status (1p and 11q), and International Neuroblastoma Pathology Classification histology were determined centrally. Survival analyses were performed for combinations of prognostic factors used in COG risk classification according to the prior version 1, and to validate a revised algorithm (version 2).

RESULTS

Most patients with locoregional tumors had excellent outcomes except for those with image-defined risk factors (INRGSS L2) with MYCN amplification (5-year event-free survival and overall survival: 76.3% ± 5.8% and 79.9% ± 5.5%, respectively) or patients age ≥ 18 months with L2 MYCN nonamplified tumors with unfavorable International Neuroblastoma Pathology Classification histology (72.7% ± 5.4% and 82.4% ± 4.6%), which includes the majority of L2 patients with SCA. For patients with stage M (metastatic) and MS (metastatic, special) disease, genomic biomarkers affected risk group assignment for those < 12 months (MYCN) or 12-18 months (MYCN, histology, ploidy, and SCA) of age. In a retrospective analysis of patient outcome, the 5-year event-free survival and overall survival using COG version 1 were low-risk: 89.4% ± 1.1% and 97.9% ± 0.5%; intermediate-risk: 86.1% ± 1.3% and 94.9% ± 0.8%; high-risk: 50.8% ± 1.4% and 61.9% ± 1.3%; and using COG version 2 were low-risk: 90.7% ± 1.1% and 97.9% ± 0.5%; intermediate-risk: 85.1% ± 1.4% and 95.8% ± 0.8%; high-risk: 51.2% ± 1.4% and 62.5% ± 1.3%, respectively.

CONCLUSION

A revised 2021 COG neuroblastoma risk classifier (version 2) that uses the INRGSS and incorporates SCAs has been adopted to prospectively define COG clinical trial eligibility and treatment assignment.

Recent progress in the treatment of cancer in children

Although significant improvements have been made in the outcomes of children with cancer, the pace of improvement has slowed in recent years as the limits of therapy intensification may have been reached for many pediatric cancers. Furthermore, with increasing numbers of pediatric cancer survivors, the long-term side effects of treatment have become increasingly apparent. Therefore, attention has shifted to the use of molecularly targeted agents and immunotherapies to improve the outcomes of children who are not cured by traditional cytotoxic chemotherapies and to decrease exposure to cytotoxic chemotherapy and reduce late effects. This review describes the recent progress in the treatment of children with cancer, focusing in particular on diseases in which targeted and immunotherapeutic agents have made an impact.

Clinical Characteristics and Survival Outcomes in Neuroblastoma With Bone Metastasis Based on SEER Database Analysis

Purpose

Clinical features and survival analysis of neuroblastoma (NB) are well explored. However, clinical research of NB patients with bone metastasis is rarely reported. Thus, the current study was performed to analyze the clinical features, survival outcome, and risk factors in those patients.

Materials and Methods

We reviewed the Surveillance, Epidemiology, and End Results (SEER) database to select cases diagnosed with NB with bone metastasis from 2010 to 2016. Overall survival (OS) and cancer-specific survival (CSS) were analyzed through univariate Cox regression analysis. Subsequently, we performed multivariate analysis to determine independent predictors of survival. The Kaplan–Meier method was applied to intuitively show differences in prognostic value between independent risk factors.

Results

We finally identified 393 NB patients with bone metastasis who were selected for survival analysis. Nearly half of the patients (47.3%) were aged >3 years. The adrenal gland was the primary tumor site, accounting for approximately two thirds of cases (66.2%). The 5-year OS and CSS rates of all patients were 62.1% and 64.1%, respectively. The univariate analysis indicated that age, lung metastasis, and tumor size were significantly associated with OS and CSS. Based on the multivariable analysis, age at 2 and 3 years, lung metastasis, and tumor size >10 cm remained significant negative predictors of OS and CSS.

Conclusion

For NB patients with bone metastasis, three independent prognostic risk factors (age, lung metastasis, and tumor size) are helpful to clinicians for predicting prognosis and guiding treatment. Reasonable treatment modalities for these patients should be further investigated to prolong survival.

Downregulation of fibronectin 1 attenuates ATRA-induced inhibition of cell migration and invasion in neuroblastoma cells

Neuroblastoma (NB) is the most common malignant extra cranial solid tumors in children. It has been well established that retinoic acid (RA) inhibits proliferation of neuroblastoma (NB) by blocking cells at G1 phase of the cell cycle. Clinically, RA has been successfully used to treat NB patients. However, the precise mechanism underlying the potent action of RA-treated NB is not fully explored. In this work, we carried out a gene expression profiling by RNA sequencing on all-trans retinoic acid (ATRA)-treated NB cells. Cancer-related pathway enrichment and subsequent protein-protein interaction (PPI) network analysis identified fibronectin 1 (FN1) as one of the central molecules in the network, which was significantly upregulated during ATRA treatment. In addition, we found that although downregulation of FN1 had no significant effects on either cell proliferation or cell cycle distributions in the presence or absence of ATRA, it increased cell migration and invasion in NB cells and partially blocked ATRA-induced inhibition of cell migration and invasion in SY5Y NB cells. Consistent with this finding, FN1 expression levels in NB patients positively correlate with their overall survivals. Taken together, our data suggest that FN1 is a potential target for effective ATRA treatment on NB patients, likely by facilitating ATRA-induced inhibition of cell migration and invasion.

Clinical Relevance of CD4 Cytotoxic T Cells in High-Risk Neuroblastoma

Neuroblastoma is the most common extracranial childhood solid tumor. The majority of high-risk neuroblastoma is resistant/refractory to the current high intensity therapy, and the survival of these patients remains poor for the last three decades. To effectively treat these extremely unfavorable neuroblastomas, innovative immunotherapy approaches would be the most promising. In this article, we discuss the identity of tumor-infiltrating effector cells and immunosuppressive cells in high-risk neuroblastoma. Neuroblastoma is unique in that it expresses little or no classical HLA Class I and II. In contrast, high-risk neuroblastomas express the stress-responsive non-classical Class I, HLA-E molecule. HLA-E is the ligand of activating receptors NKG2C/E that are expressed on memory NK cells, CD8+T cells and CD4 CTLs. By examining a comprehensive RNA-seq gene expression dataset, we detected relatively high levels of CD4 expression in high-risk neuroblastoma tissues. The majority of CD4+ cells were CD3+, and thus they were likely tumor-associated CD4+T cells. In addition, high-level of both CD4 and NKG2C/E expression was associated with prolonged survival of the high-risk neuroblastoma patients, but CD8 levels were not, further suggesting that the CD4+ NKG2C/E+ T cells or CD4 CTL conferred cytotoxicity against the neuroblastoma cells. However, this T cell mediated- "protective effect" declined over time, in part due to the progressive formation of immunosuppressive tumor microenvironment. These observations suggest that to improve survival of high-risk neuroblastoma patients, it is essential to gain insights into how to enhance CD4 CTL cytotoxicity and control the immunosuppressive tumor microenvironment during the course of the disease.

Single-Cell Characterization of Malignant Phenotypes and Developmental Trajectories of Adrenal Neuroblastoma

Neuroblastoma (NB), which is a subtype of neural-crest-derived malignancy, is the most common extracranial solid tumor occurring in childhood. Despite extensive research, the underlying developmental origin of NB remains unclear. Using single-cell RNA sequencing, we generate transcriptomes of adrenal NB from 160,910 cells of 16 patients and transcriptomes of putative developmental cells of origin of NB from 12,103 cells of early human embryos and fetal adrenal glands at relatively late development stages. We find that most adrenal NB tumor cells transcriptionally mirror noradrenergic chromaffin cells. Malignant states also recapitulate the proliferation/differentiation status of chromaffin cells in the process of normal development. Our findings provide insight into developmental trajectories and cellular states underlying human initiation and progression of NB.

New Prognostic Indicators in Pediatric Adrenal Tumors: Neuroblastoma and Adrenal Cortical Tumors, Can We Predict When These Will Behave Badly?

Pediatric adrenal tumors are unique entities with specific diagnostic, prognostic, and therapeutic challenges. The adrenal medulla gives rise to peripheral neuroblastic tumors (pNTs), pathologically defined by their architecture, stromal content, degree of differentiation, and mitotic-karyorrhectic index. Successful risk stratification of pNTs uses patient age, stage, tumor histology, and molecular/genetic aberrations. The adrenal cortex gives rise to adrenocortical tumors (ACTs), which present diagnostic and prognostic challenges. Histologic features that signify poor prognosis in adults can be meaningless in children, who have superior outcomes. The key clinical, pathologic, and molecular findings of pediatric ACTs have yet to be completely identified.

Tailoring Therapy for Children With Neuroblastoma on the Basis of Risk Group Classification: Past, Present, and Future

For children with neuroblastoma, the likelihood of cure varies widely according to age at diagnosis, disease stage, and tumor biology. Treatments are tailored for children with this clinically heterogeneous malignancy on the basis of a combination of markers that are predictive of risk of relapse and death. Sequential risk-based, cooperative-group clinical trials conducted during the past 4 decades have led to improved outcome for children with neuroblastoma. Increasingly accurate risk classification and refinements in treatment stratification strategies have been achieved with the more recent discovery of robust genomic and molecular biomarkers. In this review, we discuss the history of neuroblastoma risk classification in North America and Europe and highlight efforts by the International Neuroblastoma Risk Group (INRG) Task Force to develop a consensus approach for pretreatment stratification using seven risk criteria including an image-based staging system-the INRG Staging System. We also update readers on the current Children's Oncology Group risk classifier and outline plans for the development of a revised 2021 Children's Oncology Group classifier that will incorporate INRG Staging System criteria to facilitate harmonization of risk-based frontline treatment strategies conducted around the globe. In addition, we discuss new approaches to establish increasingly robust, future risk classification algorithms that will further refine treatment stratification using machine learning tools and expanded data from electronic health records and the INRG Data Commons.