Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma

Data standards for single-cell RNA-sequencing of paediatric cancer

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for investigating paediatric cancers, but individual studies often profile a small number of individuals. It is now the standard practice to upload the scRNA-seq data to data repositories to support scientific reproducibility. Public data deposition is a cost-effective and sustainability-conscious solution that allows any researcher to download and analyse existing scRNA-seq data to develop new ideas. This is incredibly valuable, especially in the context of paediatric cancer research, where access to funding and to patient cohorts may be prohibitive. However, standards for data deposition are absent, leading to significant issues that may slow progress. As a consequence, it is difficult, even impossible, for other researchers to validate findings or utilise these data for tailored analyses. Here, we systematically accessed and reviewed publicly available scRNA-seq data sets from various paediatric cancer studies, covering over 1.3 million cells across 488 clinical samples. We highlight striking inconsistencies with study design and data availability across several levels, which hinder downstream analyses and data reproducibility. To address these challenges, we propose a recommendations framework to improve data deposition practices that promote more effective use of scRNA-seq data sets deposited on public repositories and accelerate discoveries in paediatric cancer research and beyond. We urge data standards institutes and repositories, such as NCBI Gene Expression Omnibus (GEO) and European Genome-Phenome Archive (EGA), to strictly enforce these standardised data practices.

Integrated multi-omics characterization of neuroblastoma with bone or bone marrow metastasis

The pathogenesis of neuroblastoma with bone or bone marrow metastasis (NB-BBM) and its complex immune microenvironment remain poorly elucidated, hampering the advancement of effective risk prediction for BBM and limiting therapeutic strategies. Feature recognition of 142 paraffin-embedded hematoxylin-eosin-stained tumor section images was conducted using a Swin-Transformer for pathological histology to predict NB-BBM occurrence. Single-cell transcriptomics identified a tumor cell subpopulation (NB3) and two tumor-associated macrophage (TAM) subpopulations (SPP1+ TAMs and IGHM+ TAMs) closely associated with BBM and highlighted transketolase (TKT) as a key molecular marker for metastatic progression in NB. This extensive multi-omics investigation into NB-BBM enhances our understanding of single-cell transcriptional dynamics in NB beyond existing research, outlining the evolution from in situ carcinoma through tumorigenesis to bone marrow metastases. Furthermore, exploration of the immune microenvironment identified specific subpopulations of TAMs crucial in promoting NB-BBM, presenting new avenues for immunotherapy. These insights enhance our understanding of the metastatic process from NB to BBM and facilitate the development of more effective diagnostic and therapeutic strategies for this aggressive pediatric cancer.

PHD-2/HIF-1α axis mediates doxorubicin-induced angiogenesis in SH-SY5Y neuroblastoma microenvironment: a potential survival mechanism

The response of neuroblastoma (NB) cells to chemotherapeutics and their influence on NB microenvironment remain incompletely understood. Herein, we examined the underlying molecular mechanism via which Doxorubicin, a chemotherapeutic agent used for NB treatment, promotes proangiogenic response in the SH-SY5Y microenvironment. Doxorubicin treatment at 1 µg/ml reduced SH-SY5Y cell proliferation and primed the apoptosis pathway. Unexpectedly, SH-SY5Y cells treated with doxorubicin upregulated their expression of the pro-angiogenic factors, including vascular endothelial growth factor (VEGF), platelets-derived growth factor (PDGF), and matrix metalloprotease-2 (MMP-2) and secretion of nitric oxide. To assess the functional angiogenesis of SH-SY5Y cells pre-treated with doxorubicin, an indirect co-culture system with human umbilical vein endothelial cells (HUVEC) was established. These HUVECs acquired enhanced proliferation, migration capacity, and tube formation capability and exhibited increased nitric oxide (NO) production, in addition to upregulated α-smooth muscle actin expression, suggesting enhanced contractility. In-ovo studies of the neo-angiogenic response of SH-SY5Y pre-treated with doxorubicin further show their promoted neo-angiogenesis as indicated by the generated blood vessels and histological analysis of CD31 expression. Inhibition of PHD-2 could be a potential target for doxorubicin, as indicated by molecular docking, molecular dynamics (MD) simulation, and MM-GBSA calculations, leading to hypoxia-inducible factor-1 alpha (HIF-1α) stabilization. Bioinformatics analyses and enrichment analyses of RNA-seq data revealed activation of Pi3K pathway which is further validated in-vitro. These results provide evidence of the unexpected pro-angiogenic response of SH-SY5Y cells to doxorubicin treatment and suggest the potential use of multi-modal therapeutic regimens for a more comprehensive approach to NB treatment.

The role of cell cycle-related genes in the tumorigenesis of adrenal and thyroid neuroendocrine tumors

The molecular mechanisms underlying adrenal and thyroid neuroendocrine tumors, including their tumorigenesis, progression, and metastasis, involve unique pathways regulating cell cycle progression. To better understand these mechanisms and pathways, extensive in-depth research on cell cycle-related genes is necessary. This review aims to describe and interpret current single-cell RNA sequencing studies on neuroblastoma, medullary thyroid cancer, and pheochromocytoma tumors. Our review summarizes differentially expressed cell cycle-related genes with distinct functions, highlighting their potential as therapeutic targets and components of panels used to determine tumor type or aggressiveness. Although some insights have been gained, there is still limited information on these topics, and further research is required to explore the regulatory mechanisms of these tumors.

Causal genes identification of giant cell arteritis in CD4+ Memory t cells: an integration of multi-omics and expression quantitative trait locus analysis

BACKGROUND

Giant cell arteritis (GCA) is a prevalent artery and is strongly correlated with age. The role of CD4+ Memory T cells in giant cell arteritis has not been elucidated.

METHOD

Through single-cell analysis, we focused on the CD4+ Memory T cells in giant cell arteritis. eQTL analysis and mendelian randomization analysis identified the significant genes which have a causal effect on giant cell arteritis risk. CD4+ Memory T cells were subsequently divided into gene-positive and gene-negative groups, then further single-cell analysis was conducted. Mendelian randomization of plasma proteins, blood-urine biomarkers and metabolites were also performed. Eventually, the PMA induced Jurkat cell lines were used for biological experiments to explore the specific functions of significant causal genes in CD4+ Memory T cells.

RESULTS

Similarity of CD4+ Memory T cells in GCA and old samples were explored. DDIT4 and ARHGAP15 were identified as significant risk genes via mendelian randomization. The CD4+ Memory T cells were then divided into DDIT4 ± or ARHGAP15 ± groups, and further single-cell analysis indicated the differences in aspects involving intercellular communication, functional pathways, protein activity, metabolism and drug sensitivity between positive and negative groups. In vitro experiments, including overexpression and knockdown, demonstrated that DDIT4 leading to a chronic, low-intensity inflammatory state in CD4+ Memory T cells, eventually promoting the development of GCA.

CONCLUSION

DDIT4 and ARHGAP15 have significant causal effects on giant cell arteritis risk. Specifically, DDIT4 exhibit pro-inflammatory effects on GCA via promotes chronic, low-intensity inflammatory in CD4+ Memory T cell.

Defining neuroblastoma: From origin to precision medicine

Neuroblastoma (NB), a heterogenous pediatric tumor of the sympathetic nervous system, is the most common and deadly extracranial solid malignancy diagnosed in infants. Numerous efforts have been invested in understanding its origin and in development of novel curative targeted therapies. Here, we summarize the recent advances in the identification of the cell of origin and the genetic alterations occurring during development that contribute to NB. We discuss current treatment regimens, present and future directions for the identification of novel therapeutic metabolic targets, differentiation agents, as well as personalized combinatory therapies as potential approaches for improving the survival and quality of life of children with NB.

Single-cell RNA sequencing explored potential therapeutic targets by revealing the tumor microenvironment of neuroblastoma and its expression in cell death

BACKGROUND

Neuroblastoma (NB) is the most common extracranial solid tumor in childhood and is closely related to the early development and differentiation of neuroendocrine (NE) cells. The disease is mainly represented by high-risk NB, which has the characteristics of high mortality and difficult treatment. The survival rate of high-risk NB patients is not ideal. In this article, we not only conducted a comprehensive study of NB through single-cell RNA sequencing (scRNA-seq) but also further analyzed cuproptosis, a new cell death pathway, in order to find clinical treatment targets from a new perspective.

MATERIALS AND METHODS

The Seurat software was employed to process the scRNA-seq data. This was followed by the utilization of GO enrichment analysis and GSEA to unveil pertinent enriched pathways. The inferCNV software package was harnessed to investigate chromosomal copy number variations. pseudotime analyses involved the use of Monocle 2, CytoTRACE, and Slingshot software. CellChat was employed to analyze the intercellular communication network for NB. Furthermore, PySCENIC was deployed to review the profile of transcription factors.

RESULT

Using scRNA-seq, we studied cells from patients with NB. NE cells exhibited superior specificity in contrast to other cell types. Among NE cells, C1 PCLAF + NE cells showed a close correlation with the genesis and advancement of NB. The key marker genes, cognate receptor pairing, developmental trajectories, metabolic pathways, transcription factors, and enrichment pathways in C1 PCLAF + NE cells, as well as the expression of cuproptosis in C1 PCLAF + NE cells, provided new ideas for exploring new therapeutic targets for NB.

CONCLUSION

The results revealed the specificity of malignant NE cells in NB, especially the key subset of C1 PCLAF + NE cells, which enhanced our understanding of the key role of the tumor microenvironment in the complexity of cancer progression. Of course, cell death played an important role in the progression of NB, which also promoted our research on new targets. The scrutiny of these findings proved advantageous in uncovering innovative therapeutic targets, thereby bolstering clinical interventions.

Molecular profiling of core immune-escape genes highlights TNFAIP3 as an immune-related prognostic biomarker in neuroblastoma

BACKGROUND

Neuroblastoma (NB) is the most prevalent and deadliest pediatric solid tumor. With of over 50% of high-risk neuroblastoma cases relapse, the imperative for novel drug targets and therapeutic strategies is accentuated. In neuroblastoma, the existence of tumor-associated macrophages (TAMs) correlates with an unfavorable patient prognosis. However, the clinical relevance and prognostic implications of regulatory genes linked to TAMs infiltration in neuroblastoma remain unclear, and further study is required.

METHODS

We conducted a comprehensive analysis utilizing transcriptome expression profiles from three primary datasets associated with neuroblastoma (GSE45547, GSE49710, TARGET) to identify hub genes implicated in immune evasion within neuroblastoma. Subsequently, we utilized single-cell RNA sequencing analysis on 17 clinical neuroblastoma samples to investigate the expression and distribution of these hub genes, leading to the identification of TNFAIP3. The above three public databases were merged to allowed for the validation of TNFAIP3's molecular functions through GO and KEGG analysis. Furthermore, we assessed TNFAIP3's correlation with immune infiltration and its potential immunotherapeutic impact by multiple algorithms. Our single-cell transcriptome data revealed the role of TNFAIP3 in macrophage polarization. Finally, preliminary experimental verifications to confirm the biological functions of TNFAIP3-mediated TAMs in NB.

RESULTS

A total of 6 genes related to immune evasion were screened and we found that TNFAIP3 exhibited notably higher expression in macrophages than other immune cell types, based on the scRNA-sequencing data. GO and KEGG analysis showed that low expression of TNFAIP3 significantly correlated with the activation of multiple oncogenic pathways as well as immune-related pathways. Then validation affirmed that individuals within the TNFAIP3 high-expression cohort could potentially derive greater advantages from immunotherapeutic interventions, alongside exhibiting heightened immune responsiveness. Deciphering the pseudotime trajectory of macrophages, we revealed the potential of TNFAIP3 in inducing the polarization of macrophages towards the M1 phenotype. Finally, we confirmed that patients in the TNFAIP3 high expression group might benefit more from immunotherapy or chemotherapy as substantiated by RT-qPCR and immunofluorescence examinations. Moreover, the role of TNFAIP3 in macrophage polarization was validated. Preliminary experiment showed that TNFAIP3-mediated TAMs inhibit the proliferation, migration and invasion capabilities of NB cells.

CONCLUSIONS

Our results suggest that TNFAIP3 was first identified as a promising biomarker for immunotherapy and potential molecular target in NB. Besides, the presence of TNFAIP3 within TAMs may offer a novel therapeutic strategy for NB.

Single-cell RNA-Seq reveals the heterogeneity of fibroblasts within the tympanojugular paraganglioma microenvironment

Tympanojugular paragangliomas (TJP) originate from the parasympathetic ganglia in the lateral base of the skull. Although the cellular composition and oncogenic mechanisms of paragangliomas have been evaluated, a comprehensive transcriptomic atlas specific to TJP remains to be established to facilitate further investigations. In this study, single-cell RNA sequencing and whole-exome sequencing were conducted on six surgically excised TJP samples to determine their cellular composition and intratumoral heterogeneity. Fibroblasts were sub-classified into two distinct groups: myofibroblasts and fibroblasts associated with bone remodeling. Additionally, an elaborate regulatory and cell-cell communication network was determined, highlighting the multifaceted role of fibroblasts, which varies depending on expression transitions. The Kit receptor (KIT) signaling pathway mediated interactions between fibroblasts and mast cells, whereas robust connections with endothelial and Schwann cell-like cells were facilitated through the platelet-derived growth factor signaling pathway. These findings establish a foundation for studying the mechanisms underlying protumor angiogenesis and the specific contributions of fibroblasts within the TJP microenvironment. IL6 signaling pathway of fibroblasts interacting with macrophages and endothelial cells may be involved in tumor regrowth. These results enhance our understanding of fibroblast functionality and provide a resource for future therapeutic targeting of TJP.

The neuroblastoma tumor microenvironment: From an in-depth characterization towards novel therapies

Neuroblastoma is a cancer of the sympathetic nervous system that develops in young children, either as low-risk or high-risk disease. The tumor microenvironment (TME) is now recognized as an important player of the tumor ecosystem that may promote drug resistance and immune escape. Targeting the TME in combination with therapies directly targeting tumor cells therefore represents an interesting strategy to prevent the emergence of resistance in cancer and improve patient's outcome. The development of such strategies however requires an in-depth understanding of the TME landscape, due to its high complexity and intra and inter-tumoral heterogeneity. Various approaches have been used in the last years to characterize the immune and non-immune cell populations present in tumors of neuroblastoma patients, both quantitatively and qualitatively, in particular with the use of single-cell transcriptomics. It is anticipated that in the near future, both genomic and TME information in tumors will contribute to a precise approach to therapy in neuroblastoma. Deciphering the mechanisms of interaction between neuroblastoma cells and stromal or immune cells in the TME is key to identify novel therapeutic combinations. Over the last decade, numerous in vitro studies and in vivo pre-clinical experiments in immune-competent and immune-deficient models have identified therapeutic approaches to circumvent drug resistance and immune escape. Some of these studies have formed the basis for early phase I and II clinical trials in children with recurrent and refractory high-risk neuroblastoma. This review summarizes recently published data on the characterization of the TME landscape in neuroblastoma and novel strategies targeting various TME cellular components, molecules and pathways activated as a result of the tumor-host interactions.

Development and validation of a novel stemness-related prognostic model for neuroblastoma using integrated machine learning and bioinformatics analyses

BACKGROUND

Neuroblastoma (NB) is a common solid tumor in children, with a dismal prognosis in high-risk cases. Despite advancements in NB treatment, the clinical need for precise prognostic models remains critical, particularly to address the heterogeneity of cancer stemness which plays a pivotal role in tumor aggressiveness and patient outcomes. By utilizing machine learning (ML) techniques, we aimed to explore the cancer stemness features in NB and identify stemness-related hub genes for future investigation and potential targeted therapy.

METHODS

The public dataset GSE49710 was employed as the training set for acquire gene expression data and NB sample information, including age, stage, and MYCN amplification status and survival. The messenger RNA (mRNA) expression-based stemness index (mRNAsi) was calculated and patients were grouped according to their mRNAsi value. Stemness-related hub genes were identified from the differentially expressed genes (DEGs) to construct a gene signature. This was followed by evaluating the relationship between cancer stemness and the NB immune microenvironment, and the development of a predictive nomogram. We assessed the prognostic outcomes including overall survival (OS) and event-free survival, employing machine learning methods to measure predictive accuracy through concordance indices and validation in an independent cohort E-MTAB-8248.

RESULTS

Based on mRNAsi, we categorized NB patients into two groups to explore the association between varying levels of stemness and their clinical outcomes. High mRNAsi was linked to the advanced International Neuroblastoma Staging System (INSS) stage, amplified MYCN, and elder age. High mRNAsi patients had a significantly poorer prognosis than low mRNAsi cases. According to the multivariate Cox analysis, the mRNAsi was an independent risk factor of prognosis in NB patients. After least absolute shrinkage and selection operator (LASSO) regression analysis, four key genes (ERCC6L, DUXAP10, NCAN, DIRAS3) most related to mRNAsi scores were discovered and a risk model was built. Our model demonstrated a significant prognostic capacity with hazard ratios (HR) ranging from 18.96 to 41.20, P values below 0.0001, and area under the receiver operating characteristic curve (AUC) values of 0.918 in the training set, suggesting high predictive accuracy which was further confirmed by external verification. Individuals with a low four-gene signature score had a favorable outcome and better immune responses. Finally, a nomogram for clinical practice was constructed by integrating the four-gene signature and INSS stage.

CONCLUSIONS

Our findings confirm the influence of CSC features in NB prognosis. The newly developed NB stemness-related four-gene signature prognostic signature could facilitate the prognostic prediction, and the identified hub genes may serve as promising targets for individualized treatments.

Targeting the myeloid microenvironment in neuroblastoma

Myeloid cells (granulocytes and monocytes/macrophages) play an important role in neuroblastoma. By inducing a complex immunosuppressive network, myeloid cells pose a challenge for the adaptive immune system to eliminate tumor cells, especially in high-risk neuroblastoma. This review first summarizes the pro- and anti-tumorigenic functions of myeloid cells, including granulocytes, monocytes, macrophages, and myeloid-derived suppressor cells (MDSC) during the development and progression of neuroblastoma. Secondly, we discuss how myeloid cells are engaged in the current treatment regimen and explore novel strategies to target these cells in neuroblastoma. These strategies include: (1) engaging myeloid cells as effector cells, (2) ablating myeloid cells or blocking the recruitment of myeloid cells to the tumor microenvironment and (3) reprogramming myeloid cells. Here we describe that despite their immunosuppressive traits, tumor-associated myeloid cells can still be engaged as effector cells, which is clear in anti-GD2 immunotherapy. However, their full potential is not yet reached, and myeloid cell engagement can be enhanced, for example by targeting the CD47/SIRPα axis. Though depletion of myeloid cells or blocking myeloid cell infiltration has been proven effective, this strategy also depletes possible effector cells for immunotherapy from the tumor microenvironment. Therefore, reprogramming of suppressive myeloid cells might be the optimal strategy, which reverses immunosuppressive traits, preserves myeloid cells as effectors of immunotherapy, and subsequently reactivates tumor-infiltrating T cells.

Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction

OBJECTIVE

Seek new candidate prognostic markers for neuroblastoma outcome, relapse or progression.

MATERIALS AND METHODS

In this multicentre and retrospective study, Random Forests coupled with recursive feature elimination techniques were applied to electronic records (55 clinical features) of 3034 neuroblastoma patients. To assess model performance and feature importance, dataset was split into a training set (80%) and a test set (20%).

RESULTS

In the test set, the mean Matthews correlation coefficient for the Random Forests models was greater than 0.46. Feature importance analysis revealed that, together with maximum response to first-line treatment (D_MAX_RESP), time to maximum response to first-line treatment (TIME_MAX_RESP.days) is a relevant predictor of both patients' outcome and relapse\progression. We showed the prognostic value of the max response to first-line treatment in clinically relevant subsets of high-, intermediate-, and low-risk patients for both overall and relapse-free survival (Log-rank p-value<0.0001). In high-risk patients older than 18 months and stage 4 tumour achieving a complete response or very good partial response, patients who exhibited a D_MAX_RESP greater than 9 months showed a better prognosis with respect to patients achieving D_MAX_RESP earlier than 9 months (overall survival): hazard ratio 3.3 95% confidence interval 1.8-5.9, Log-rank p-value p < 0.0001; relapse-free survival: 3.2 95%CI 1.8-5.6, Log-rank p-value p < 0.0001).

CONCLUSION

Our findings evidence the emerging role of the TIME_MAX_RESP.days in addition to the D_MAX_RESP as relevant predictors of outcome and relapse\progression in neuroblastoma with potential clinical impact on the management and treatment of patients.

Palbociclib releases the latent differentiation capacity of neuroblastoma cells

Neuroblastoma is the most common extracranial solid tumor in infants, arising from developmentally stalled neural crest-derived cells. Driving tumor differentiation is a promising therapeutic approach for this devastating disease. Here, we show that the CDK4/6 inhibitor palbociclib not only inhibits proliferation but induces extensive neuronal differentiation of adrenergic neuroblastoma cells. Palbociclib-mediated differentiation is manifested by extensive phenotypic and transcriptional changes accompanied by the establishment of an epigenetic program driving expression of mature neuronal features. In vivo palbociclib significantly inhibits tumor growth in mouse neuroblastoma models. Furthermore, dual treatment with retinoic acid resets the oncogenic adrenergic core regulatory circuit of neuroblastoma cells, further suppresses proliferation, and can enhance differentiation, altering gene expression in ways that significantly correlate with improved patient survival. We therefore identify palbociclib as a therapeutic approach to dramatically enhance neuroblastoma differentiation efficacy that could be used in combination with retinoic acid to improve patient outcomes.

NLRRC: A Novel Clustering Method of Jointing Non-Negative LRR and Random Walk Graph Regularized NMF for Single-Cell Type Identification

The development of single-cell RNA sequencing (scRNA-seq) technology has opened up a new perspective for us to study disease mechanisms at the single cell level. Cell clustering reveals the natural grouping of cells, which is a vital step in scRNA-seq data analysis. However, the high noise and dropout of single-cell data pose numerous challenges to cell clustering. In this study, we propose a novel matrix factorization method named NLRRC for single-cell type identification. NLRRC joins non-negative low-rank representation (LRR) and random walk graph regularized NMF (RWNMFC) to accurately reveal the natural grouping of cells. Specifically, we find the lowest rank representation of single-cell samples by non-negative LRR to reduce the difficulty of analyzing high-dimensional samples and capture the global information of the samples. Meanwhile, by using random walk graph regularization (RWGR) and NMF, RWNMFC captures manifold structure and cluster information before generating a cluster allocation matrix. The cluster assignment matrix contains cluster labels, which can be used directly to get the clustering results. The performance of NLRRC is validated on simulated and real single-cell datasets. The results of the experiments illustrate that NLRRC has a significant advantage in single-cell type identification.

Single-cell transcriptome sequencing reveals tumor heterogeneity in family neuroblastoma

Neuroblastoma(NB) is the most common extracranial solid tumor in childhood, and it is now believed that some patients with NB have an underlying genetic susceptibility, which may be one of the reasons for the multiplicity of NB patients within a family line. Even within the same family, the samples show great variation and can present as ganglioneuroblastoma or even benign ganglioneuroma. The genomics of NB is still unclear and more in-depth studies are needed to reveal its key components. We first performed single-cell RNA sequencing(sc-RNAseq) analysis on clinical specimens of two family neuroblastoma(FNB) and four sporadic NB cases. A complete transcriptional profile of FNB was constructed from 18,394 cells from FNB, and we found that SDHD may be genetically associated with FNB and identified a prognostic related CAF subtype in FNB: Fib-4. Single-cell flux estimation analysis (scFEA) results showed that malignant cells were associated with arginine spermine, oxaloacetate and hypoxanthine, and that malignant cells metabolize lactate at lower levels than T cells. Our study provides new resources and ideas for the development of the genomics of family NB, and the mechanisms of cell-to-cell interactions and communication and the metabolic landscape will provide new therapeutic targets.

Niclosamide (NA) overcomes cisplatin resistance in human ovarian cancer

Ovarian cancer (OC) is one of the most lethal malignancies of the female reproductive system. OC patients are usually diagnosed at advanced stages due to the lack of early diagnosis. The standard treatment for OC includes a combination of debulking surgery and platinum-taxane chemotherapy, while several targeted therapies have recently been approved for maintenance treatment. The vast majority of OC patients relapse with chemoresistant tumors after an initial response. Thus, there is an unmet clinical need to develop new therapeutic agents to overcome the chemoresistance of OC. The anti-parasite agent niclosamide (NA) has been repurposed as an anti-cancer agent and exerts potent anti-cancer activities in human cancers including OC. Here, we investigated whether NA could be repurposed as a therapeutic agent to overcome cisplatin-resistant (CR) in human OC cells. To this end, we first established two CR lines SKOV3CR and OVCAR8CR that exhibit the essential biological characteristics of cisplatin resistance in human cancer. We showed that NA inhibited cell proliferation, suppressed cell migration, and induced cell apoptosis in both CR lines at a low micromole range. Mechanistically, NA inhibited multiple cancer-related pathways including AP1, ELK/SRF, HIF1, and TCF/LEF, in SKOV3CR and OVCAR8CR cells. NA was further shown to effectively inhibit xenograft tumor growth of SKOV3CR cells. Collectively, our findings strongly suggest that NA may be repurposed as an efficacious agent to combat cisplatin resistance in chemoresistant human OC, and further clinical trials are highly warranted.

Tumoral heterogeneity in neuroblastoma

Neuroblastoma is a solid, neuroendocrine tumor with divergent clinical behavior ranging from asymptomatic to fatal. The diverse clinical presentations of neuroblastoma are directly linked to the high intra- and inter-tumoral heterogeneity it presents. This heterogeneity is strongly associated with therapeutic resistance and continuous relapses, often leading to fatal outcomes. The development of successful risk assessment and tailored treatment strategies lies in evaluating the extent of heterogeneity via the accurate genetic and epigenetic profiling of distinct cell subpopulations present in the tumor. Recent studies have focused on understanding the molecular mechanisms that drive tumoral heterogeneity in pursuing better therapeutic and diagnostic approaches. This review describes the cellular, genetic, and epigenetic aspects of neuroblastoma heterogeneity. In addition, we summarize the recent findings on three crucial factors that can lead to heterogeneity in solid tumors: the inherent diversity of the progenitor cells, the presence of cancer stem cells, and the influence of the tumor microenvironment.