{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T05:11:25Z","timestamp":1772169085214,"version":"3.50.1"},"update-to":[{"DOI":"10.12688\/wellcomeopenres.23249.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000}}],"reference-count":38,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MC_PC_17230"],"award-info":[{"award-number":["MC_PC_17230"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["203151\/Z\/16\/Z"],"award-info":[{"award-number":["203151\/Z\/16\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["203151\/A\/16\/Z"],"award-info":[{"award-number":["203151\/A\/16\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["212253"],"award-info":[{"award-number":["212253"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000289","name":"Cancer Research UK","doi-asserted-by":"publisher","award":["A25636"],"award-info":[{"award-number":["A25636"]}],"id":[{"id":"10.13039\/501100000289","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["wellcomeopenresearch.org"],"crossmark-restriction":false},"short-container-title":["Wellcome Open Res"],"abstract":"<ns3:p>\n                    Background Neuroblastoma is the most common extra-cranial childhood solid tumour, arising during development from stalled neural crest-derived precursor cells. In a subset of children younger than 18 months of age, neuroblastoma can undergo spontaneous regression driven by differentiation, leading to great interest in developing differentiation therapies to re-direct neuroblastoma cells down their correct developmental pathway. Recently, we have shown that combinatorial treatment with the CDK4\/6 inhibitor palbociclib and differentiation-inducing agent retinoic acid inhibits proliferation and drives neuronal differentiation of adrenergic-type neuroblastoma cell lines. Methods Here, we explore the differentiation potential of neuroblastoma cell lines\n                    <ns3:italic>in vitro<\/ns3:italic>\n                    in response to palbociclib and retinoic acid treatment using microscopy, transcriptomic and qRT-PCR analyses. Results We present evidence suggesting that neuroblastoma cells can give rise to mixtures of neural crest-derived adrenal gland cell types, and that differentiation responses correspond to changes in patterns of extracellular matrix substrate expression. Conclusions This study builds a case to further investigate and consider heterogeneity in neuroblastoma cell differentiation and extracellular matrix changes during these cell fate decisions.\n                  <\/ns3:p>","DOI":"10.12688\/wellcomeopenres.23249.2","type":"journal-article","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T14:00:07Z","timestamp":1758031207000},"page":"671","update-policy":"https:\/\/doi.org\/10.12688\/wellcomeopenres.crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Neuroblastoma cell lines display heterogeneity in differentiation responses"],"prefix":"10.12688","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6738-5203","authenticated-orcid":false,"given":"Kirsty M.","family":"Ferguson","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah L.","family":"Gillen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5316-4030","authenticated-orcid":false,"given":"Fiona M. Y.","family":"Abou Grealy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aditi","family":"Vedi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna","family":"Philpott","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2560","published-online":{"date-parts":[[2025,9,16]]},"reference":[{"key":"ref-1","doi-asserted-by":"publisher","first-page":"683-693","DOI":"10.1038\/s41588-021-00806-1","article-title":"Single-cell transcriptomic analyses provide insights into the developmental origins of neuroblastoma.","volume":"53","author":"S Jansky","year":"2021","journal-title":"Nat Genet."},{"key":"ref-2","doi-asserted-by":"publisher","first-page":"397-411","DOI":"10.1038\/nrc3526","article-title":"Neuroblastoma: developmental biology, cancer genomics and immunotherapy.","volume":"13","author":"N Cheung","year":"2013","journal-title":"Nat Rev Cancer."},{"key":"ref-3","doi-asserted-by":"publisher","first-page":"2916-2928","DOI":"10.1016\/j.neuron.2022.07.012","article-title":"Neuroblastoma: when differentiation goes awry.","volume":"110","author":"M Zeineldin","year":"2022","journal-title":"Neuron."},{"key":"ref-4","doi-asserted-by":"publisher","first-page":"277-286","DOI":"10.1007\/s00441-017-2761-2","article-title":"Spontaneous regression of neuroblastoma.","volume":"372","author":"G Brodeur","year":"2018","journal-title":"Cell Tissue Res."},{"key":"ref-5","doi-asserted-by":"publisher","first-page":"1624-1638","DOI":"10.1016\/j.gendis.2021.12.020","article-title":"Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma.","volume":"9","author":"Q Liu","year":"2022","journal-title":"Genes Dis."},{"key":"ref-6","doi-asserted-by":"publisher","DOI":"10.1016\/j.tranon.2021.101166","article-title":"The spontaneous remission of cancer: current insights and therapeutic significance.","volume":"14","author":"G Radha","year":"2021","journal-title":"Transl Oncol."},{"key":"ref-7","doi-asserted-by":"publisher","first-page":"1967-1982","DOI":"10.1016\/j.devcel.2023.08.028","article-title":"Palbociclib releases the latent differentiation capacity of neuroblastoma cells.","volume":"58","author":"K Ferguson","year":"2023","journal-title":"Dev Cell."},{"key":"ref-8","first-page":"484-496","article-title":"Differentiation of human neuroblastoma recapitulates neural crest development. 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status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.21956\/wellcomeopenres.25621.r111423, Subrata Sinha, Biochemistry, All India Institute of Medical Sciences, New Delhi, Delhi, 110029, 09 Dec 2024, version 1, 4 approved with reservations","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v1#referee-response-111423","order":0,"name":"referee-response-111423","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Anna Philpott<\/b>; \n<i>Posted: 24 Aug 2025<\/i>; We thank the reviewer for their helpful comments and respond to each of these below.  Comment 1: One of the main claims of the paper is that the differentiation patterns of ADRN cell lines correspond to changes in ECM substrate expression. They have identified a group of genes in the RNA seq analysis of SK-N-BE(2)C, that were upregulated in response to PB plus RA but not to any one individually. These were initially identified as one of a group of genes related to neuronal cell body and ECM. Of these, selected ECM genes have been studied. To substantiate this claim, in Fig 3 they have presented qRT-PCR of these 3 cell lines exposed to PB plus RA, and almost all the genes depicted, show a differing response. An issue that is not clear is whether ECM substrates produced by the cells determine the nature of differentiation, or whether ECM gene expression patterns are associated with the differentiation pattern as an intrinsic cellular property.&nbsp; In vivo, ECM is likely to be generated by a variety of cells and it is very likely there is some kind of cumulative effect of the cell type. Author response: We thank the Reviewer for this insightful comment. As in Tsokos et al [8], our data support that differentiation responses correspond to changes in patterns of ECM substrate expression. We agree with the Reviewer that whether changes in ECM substrate expression are a cause or a consequence of differentiation remains to be determined.  As noted, there are indications in the literature that the ECM may direct cell fate choices, and for example reference 36 where increasing ECM stiffness has been found to modulate neuronal differentiation of neuroblastoma cells and reference 37 where ECM topography has been shown to drive a transition between adrenergic and mesenchymal cell types. As noted, \u2018The role of the ECM during neural crest development is well-described, with cells interacting with a dynamic ECM in a spatiotemporal manner to direct their correct differentiation and migration. As such, the ECM composition is a key component of many protocols for neuronal differentiation from stem cell states [29]\u2019. In referencing this literature in the first manuscript version, we intended to discuss whether ECM changes are a cause or consequence of cell fate decisions as an interesting topic for further exploration. For example, \u2018it would be interesting to further explore whether ECM modification is able to alter neuroblastoma cell identity in response to PB+RA, and if so, whether drugs altering mechano-transduction pathways may offer additional differentiation benefits.\u2019 We have added to the text to clarify this (Discussion, Paragraph 4), acknowledging that our data are an initial observation to prompt further investigation. We agree with the reviewer that it would be important to test this in an in vivo system where cumulative effects of cell types will exist, and have further discussed this in the discussion in paragraph 4. We have also modified the text from \u2018build a case\u2026 for investigating the effect of ECM on neuroblastoma cell fate decisions\u2019 to \u2018investigating ECM changes in neuroblastoma differentiation\u2019 (e.g. end of Introduction and end of Results) to reflect this increased discussion. &nbsp;  Comment 2: However, the question is, what relevant biological meaning can be drawn from these mRNA expression values. Heterogeneity of gene expression response is very well known, indeed it can occur after multiple passages of the same cell line, let alone in different cell lines, derived from different primary tumours, having differing genetic backgrounds. It is difficult to claim that the differentiation patterns correspond to the ECM gene expression based on this one experiment of qRT PCR values. How can one conclude that these are not random changes in gene expression by the different cell lines? How were these genes selected for performing qRT PCR, and would the results have been different if others were chosen? Also, how many biological replicates for differentiation were performed and what was the consistency of gene expression in each cell line over different sets of differentiation? It is difficult to claim that the differentiation patterns correspond to the ECM gene expression based on this one experiment of qRT PCR values. How can one conclude that these are not random changes in gene expression by the different cell lines? Author response: Three biological replicates were performed for each cell line, corresponding to three independent passages of each cell line. As stated in the \u2018Statistical Analysis\u2019 section of the Methods, \u2018Biological replicates were considered as different passage numbers of the same cell line plated in independent experiments.\u2019 We are therefore confident that the changes in gene expression seen are indeed not random events, as they were consistently seen across three independent experiments in different cell line passages. We have now clarified in the text of the figure legends for Figures 2 and 3.  &nbsp;  Comment 3: Again, it is evident from morphology, that the proportion of flat and neurite bearing cells were different post differentiation in the cell lines. So the RT PCR results represent a mixture of post differentiation cell types. At least some indication of the different cell types post differentiation, could be given from morphological counts and staining by IHC or ICC. Author response: We agree with the reviewer that further exploration of the cell types emerging from PB+RA treatment of each cell line could be performed. As stated in the discussion \u2018Further exploration could include characterisation of the emerging cell types using single-cell RNA-seq, immunocytochemistry and flow cytometry analyses.\u2019 It would be a significant piece of new work to perform a full characterisation of the emerging cell types using single-cell techniques such as single-cell RNA-seq that we would like to have undertaken. This would allow an accurate identification and comprehensive characterization of the cells emerging following PB+RA treatment. However, this is unfortunately not possible due to funding constraints. We have expanded on these future work suggestions in the discussion and invite this as an important area for further research (Discussion, Paragraph 5).  &nbsp;  Comment 4: Again the SH-SY5Y response to differentiation seems to be the expression of more MMP 1. What about the other MMPs? Conventional teaching says that high expression of MMPs is associated with invasive malignancies and not differentiation, and publications for this are also available for MMP1. Some references are below: MMP1 Overexpression Promotes Cancer Progression and Associates with Poor Outcome in Head and Neck Carcinoma. Zhang W, Huang X, Huang R, Zhu H, Ye P, Lin X, Zhang S, Wu M, Jiang F. Comput Math Methods Med. 2022 Sep 5;2022:3058342. doi: 10.1155\/2022\/3058342. eCollection 2022.PMID: 36105241, Downregulation of MMP1 functions in preventing perineural invasion of pancreatic cancer through blocking the NT-3\/TrkC signaling pathway. Xu X, Lu X, Chen L, Peng K, Ji F.J Clin Lab Anal. 2022 Nov;36(11):e24719. doi: 10.1002\/jcla.24719. Epub 2022 Sep 30.PMID: 36181286 Author response: Thank you for this comment and pointing out references we had missed. We have expanded on the interesting observation of increased MMP1 expression in PB+RA treated SH-SY5Y cells in the discussion to include these references (end of paragraph 3). We agree that this is a surprising observation, and surmised that upregulation of a matrix metalloproteinase responsible for degradation of ECM components may link to unique cell fates in this cell line as increasing ECM stiffness has been found to modulate neuronal differentiation of neuroblastoma cells. Further characterisation of the other MMPs would be interesting as part of a more extensive analysis of neuroblastoma differentiation heterogeneity, as detailed in the above comment, but it is not possible for us to undertake this work at this time.  &nbsp; We thank the reviewer for their helpful comments which have guided submission of version 2 of this manuscript. While we note that the Reviewer quite rightly states that we could take this work further, we are unable to do so because of staffing\/funding&nbsp;constraints. However, we feel strongly that it is important to disseminate our findings to allow others to build on the work that we have done and feel that Wellcome Open Research is&nbsp;an appropriate venue for this. We hope that the reviewer can consider this when evaluating our responses.","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v2#referee-comment-6213","order":1,"name":"referee-comment-6213","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.25621.r113578, C\u00e9cile Thirant, Institut Curie, Paris, 19 Dec 2024, version 1, 4 approved with reservations","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v1#referee-response-113578","order":2,"name":"referee-response-113578","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Anna Philpott<\/b>; \n<i>Posted: 24 Aug 2025<\/i>; We thank the reviewer for their helpful comments and respond to each of these below.  \n<b>Comment 1:<\/b> In the introduction, the authors may reformulate these two sentences: \u201cDuring normal development, sympathoadrenal precursor cells derived from the neural crest differentiate into cell types including sympathetic neurons, adrenal chromaffin cells and Schwann cells. In neuroblastoma, these sympathetic precursor cells fail to differentiate and are locked into an immature state that drives tumour growth\u201d. First, they are a copy and paste from Ferguson KM DevCell 2023 introduction and then, to my knowledge, neural crest cells indeed produced neurons, chromaffins and Schwann cells, but sympathoadrenal progenitors do not produce Schwann cells. \n<b>Author response<\/b>: Thank you for bringing this to our attention. We have reworded the above introductory sentences and have amended the text (paragraph 1, Introduction).  &nbsp; &nbsp;  \n<b>Comment 2a<\/b>: In the results, the authors re-used their RNAseq data obtained in the SKNBE2C cell line. They projected the deregulated genes upon treatment at bulk level into the trajectory of differentiation drawn from scRNAseq studies on normal adrenal development, published by Jansky et al. They show that almost all clusters could be highlighted by one of the lists of genes, and propose that this cell line has the potential to enter different lineage pathways, in addition to neuronal differentiation. Figure 1C: Could the authors harmonize the scale and avoid -0.05. I think it would be helpful to provide as supplementary tables the lists of genes used to define the 5 clusters and plotted as signatures. Could the authors also indicate how many and which genes from these lists contribute to the plotted signatures ? \n<b>Author response:<\/b> In Figure 1C the values and scale represent&nbsp;a module score for a given geneset. This was conducted using Seurat AddModuleScore from which the scores reflect&nbsp;how the expression of a given gene set&nbsp;varies across the single cells in the dataset compared to a randomly selected set of control genes. Therefore, it is most appropriate for the scales to remain as originally&nbsp;plotted for each plot. We provided the requested table of genes associated with each signature in the data and code available on zenodo, but we have now added this&nbsp;to Extended Data, Table S2, so that it is more readily findable, and have directly&nbsp;referred to this table within the text and figure legend. In addition, as often a greater number of genes are detectable by bulk RNA-seq than scRNA-seq, we have added a column to this table 'gene_in_Jansky_et_al_2021' to be clear which genes from our clusters derived from bulk RNA-seq were also detectable in the single cell RNA-seq dataset. We have now also clarified in the Figure 1 legend and Results text the gene groups associated with each cluster 1-5 (identified in our previous publication [7]).  &nbsp;  \n<b>Comment 2b<\/b>: However, without any single-cell RNAseq data showing that after treatment, distinct cells harbor distinct cell type genes according to normal differentiation, it is really difficult from bulk RNAseq data to suggest that those cells \u201chave the potential to enter different human adrenal medullary developmental lineages (\u2026).\u201d \n<b>Author response:<\/b> We agree with the Reviewer that further exploration of the cell types emerging from PB+RA treatment of each cell line could be performed. As stated in the discussion \u2018Further exploration could include characterisation of the emerging cell types using single-cell RNA-seq, immunocytochemistry and flow cytometry analyses.\u2019 We would very much like to perform a full characterisation of the emerging cell types, using single cell techniques - this would allow an accurate identification and comprehensive characterization of the cells emerging following PB+RA treatment. However, this is unfortunately not possible due to funding and staffing constraints. We have expanded on these future work suggestions in the discussion and invite this for further research (Discussion, paragraph 5). We have also modified the text to \u2018While further validation is required as detailed in the discussion\u2026this suggests that SK-N-BE(2)C neuroblastoma cells may have the potential\u2026\u2019 (Results, end of paragraph 1).  &nbsp;  \n<b>Comment 3:<\/b> The study follows by the more precise characterization of the heterogeneity of differentiation response to PB+RA of distinct cell lines, using 3 neuroblastoma models and a prolonged exposure of treatment of 10 days. First, in addition to their distinct genetic background, could the authors precise the different origin of the three selected NB models ? Primary tumor or metastases; before or after treatment; grade; primary tumor location (adrenal gland or sympathetic ganglia) etc\u2026 As neuroblastoma is a disease well known for its heterogeneity and so possibly \u201cstalled at different stages of developmental differentiation\u201d as rightly mentioned by the authors in the introduction, could this point be discussed because possibly explaining the obtained results? Minor point: \u201cThese cell lines represent a mixture of genetic background\u201d should be replace by \u201cThese cell lines represent different genetic backgrounds\u201d. \n<b>Author response:<\/b> Thank you for this interesting point. We have corrected the wording to \u2018represent different genetic backgrounds.\u2019 We have also now included available cell line details in the text with references (Results, paragraph 2). We have also included more detail in the discussion as to how the different features of the cell lines may influence their differentiation responses (Discussion, end of paragraph 2).  &nbsp;  \n<b>Comment 4:<\/b> To illustrate distinct differentiation states after treatment, they looked at the cellular morphology (Figure 2A). Whereas the IMR-32 cell line seems only differentiating towards a neuronal fate, BE2C and 5Y showed other phenotype that is not easy to recognize using phase-contrast images. Could the authors find a way to quantify the changes of morphology ? IF maybe ? Photos of control cells at confluence do not allow to really evaluate changes of morphology and may be replace. \n<b>Author response:<\/b> We agree with the Reviewer that further exploration of the cell types emerging from PB+RA treatment of each cell line could be performed. As detailed in the above comment it would be ideal if we could perform a full characterisation of the emerging cell types using single cell techniques such as single cell RNA-seq, however, this is unfortunately not possible. This would allow an accurate identification and comprehensive characterization of the cells emerging following PB+RA treatment, using the markers identified for validation by ICC and flow cytometry. We have expanded on these future work suggestions in the discussion and invite this for further research (Discussion, paragraph 5). Regarding the differentiation images, additional low-confluence images were not provided as these experiments are a follow-on from previous studies where live imaging is performed to track the cells from day 0 of treatment [7]. These movies show clearly the morphology of the cells prior to treatment, which we have clarified in the text for the readers\u2019 reference (Figure 2 legend).  &nbsp;  \n<b>Comment 5a:<\/b> Additionally, they looked at the expression of selected genes by RT-qPCR to evaluate the potential of differentiation in distinct normal cell types of the sympathetic nervous system of the tumor cell lines treated with PB+RA. How these genes have been selected ? It is quite difficult to be certain of a way of differentiation based on the expression of one marker, and at the bulk level. Of note, adrenal cortical cells are coming from a complete different tissue of origin than the adrenal medulla or the sympathetic ganglia, so could the authors justify the use of CYP11A1 ? \n<b>Author response:<\/b> The differentiation markers shown in Figure 2 were selected using marker genes of adrenal medullary cell populations referenced in Jansky et al [1].&nbsp; NEFM, GAP43 and SYT5 were chosen as markers of sympathetic neuroblasts. PNMT, the enzyme catalyzing methylation of norepinephrine to form epinephrine, was chosen as a marker of mature chromaffin cells, ACTA2 as a marker of myofibroblasts, MYH3 as a marker of myocytes, and CYP11A1 as a marker of adrenal cortical cells. This has now been clarified in the text (Results section, \u201cDifferentiation patterns of adrenergic neuroblastoma cell lines correspond to changes in ECM substrate expression\u201c). We note that CYP11A1, as well as MYH3 and ACTA2, mark populations outside of the sympathoadrenal lineage - this is indeed interesting and could suggest malignant transformation at an early stage of neural crest development from bipotent or mesenchymal lineage precursors, and\/or plasticity of neuroblastoma cells (26) - we have discussed this further in the text (Discussion, end of paragraph 2). We agree that it would be excellent if we could have performed a full characterisation of the emerging cell types, encompassing all cell type markers and transcription factors in Jansky et al [1] and more, using single cell RNA-seq - we have expanded on these future work suggestions in the discussion and invite this for further research (Discussion, paragraph 5).  &nbsp;  \n<b>Comment 5b: <\/b>How many times this experiment has been conducted ? Does \u201c3 biological replicates\u201d mean 3 independent experiments with how many technical replicates ? To better compare responses between cell lines and to conclude about inter-cell line heterogeneity, it would be necessary to compare also their basal level of expression. \n<b>Author response:<\/b> Three biological replicates were performed for each cell line, corresponding to three independent passages of each cell line. As stated in the \u2018Statistical Analysis\u2019 section of the Methods, \u2018Biological replicates were considered as different passage numbers of the same cell line plated in independent experiments\u2019. This has been further clarified in the text of the figure legends for Figures 2 and 3. Regarding the comparison of basal levels, the experiments were performed in a manner to compare DMSO with PB+RA treatment within each cell line. We therefore make conclusions as to whether fold changes in gene expression are seen within each line in response to PB+RA treatment. Comparison of the basal gene expression levels would indeed be also interesting, however is beyond the scope of the manuscript.  &nbsp;  \n<b>Comment 6:<\/b> Whereas the IMR32 and the 5Y seem mainly able to go towards a neuronal differentiation, the BE2C seems able to express genes of several cell types from adrenergic to mesenchymal phenotypes (ACTA2, ITGA5, FN1, COLs etc\u2026). Interestingly this cell line has been previously used to study NB tumor cell plasticity, cells being able to shift from a noradrenergic towards a mesenchymal identity. Why the authors did not address the summary of literature on this subject or at least discuss this point? When cells after treatment change phenotypes, in what degree can we distinguish differentiation versus plasticity ? \n<b>Author response:<\/b> This is an interesting point and we thank the Reviewer for prompting us to look further. We have now included reference to cell line plasticity (Introduction, paragraph 2) and features of the cell line details (Results, paragraph 2), including their phenotypic characterisations, noting SK-N-BE(2)C as an \u2018I type\u2019 cell line. We have also included more detail in the discussion as to how the different features of the cell lines may influence their differentiation responses (Discussion, paragraph 2). In the Discussion we now \u201cspeculate that intra-tumoral differentiation heterogeneity could be associated with heterogeneity within the starting tumour; it would therefore be interesting to investigate the differentiation capacity of a larger cohort of cell lines with I, N and S-type phenotypic characteristics\u201d (end of paragraph 2).  &nbsp; Thank you for the discussion regarding plasticity vs differentiation. In all three cell lines tested, we observe a dramatic decrease in proliferation with PB+RA treatment (seen in Figures 5, S4, S6, 7 and videos of [7]), further evident after 10 days. This is in contrast to the highly proliferative nature of MES-type neuroblastoma cell lines, such as SH-EP, which may be expected if cells were simply interconverting between malignant cell states. It would indeed be interesting to determine if the resulting cell states seen after treatment are stably differentiated, and single-cell RNA-seq to determine markers of the emerging cell types would be extremely useful to resolve this question. Such an experiment is difficult to truly determine in vitro however; we therefore suggest in vivo experiments would be required to assess the terminal differentiation of the resulting cell states, which is beyond the scope of this manuscript. We have now noted the literature on cell line plasticity in the introduction and discuss in the Discussion (paragraph 2) that phenotypic heterogeneity in cell lines may influence differentiation capacity. Furthermore, we have added to the discussion (last paragraph) \u201cSingle cell tracking studies would be insightful to determine if heterogeneous differentiation occurs in response to treatment-induced plasticity, or is predetermined by starting cell identity. Finally, it would also be of interest to treat cells for further extended time periods, in vitro and in vivo, as well as investigate whether continued treatment is required for stable differentiation\u201d. &nbsp;  \n<b>Comment 7:<\/b> Finally, authors looked at ECM factors expression, which is inherently linked to cell identity (especially for mesenchymal cells). Again, the pertinence of looking to these particular genes is missing and would help to interpret the data. What is the biological difference between COL3A1, COL5A1 and COL4A2? Is it known that each of this gene is associated to a specific cell type? Same question about LAMB3 and EGFLAM, why the authors selected those genes? \n<b>Author response:<\/b> As discussed in the Results (section \u201cDifferentiation patterns of adrenergic neuroblastoma cell lines correspond to changes in ECM substrate expression\u201c) our investigations into ECM factor expression were led by Tsokos et al\u2019s finding [8] that \u201cspecific patterns of ECM expression emerged after differentiation, proportional to the normal tissue cell types observed\u201d, particularly laminin, fibronectin and collagen. In addition, \u201cRNA-seq analyses were performed on SK-N-BE(2)C cells treated with DMSO vehicle control, PB, RA or PB+RA for five days [7]. This identified a subset of genes (cluster 4) upregulated in cells treated with a combination of PB+RA, but not PB or RA alone (Figure 1A and C). Gene ontology analyses revealed that these genes were associated with neuronal cell body and extracellular matrix (ECM) cellular components\u201d. Our choice of ECM markers was guided by Tsokos et al and these genes found to be differentially upregulated in PB+RA treated cells. We have now clarified this in the Results text (paragraph 4-5). As mentioned \u2018Further exploration could include characterisation of the emerging cell types using single-cell RNA-seq, immunocytochemistry and flow cytometry analyses.\u2019 As well as the emerging cell states, this would enable a full characterisation of ECM factors and their relation to individual cell types. Unfortunately, this wide-scale characterization was not possible due to time and funding constraints; we have added discussion about this as a future area of research (Discussion, paragraph 5).  &nbsp;  \n<b>Comment 8<\/b>: Concerning the conclusion, these results illustrate inter- neuroblastoma cell line heterogeneity of responses to this therapy, in line with the fact that heterogeneity is a well-known characteristic of neuroblastoma. However, pointing towards \u201c the role of the ECM in these cell fate decisions\u201d is over-interpreted, not shown nor suggested here, as I would rather say that ECM factors here reflect tumor cell identity and not the other way round. \n<b>Author response<\/b>: We thank the reviewer for this thoughtful comment. As in Tsokos et al [8], our data support that differentiation responses correspond to changes in patterns of ECM substrate expression. We agree with the Reviewer that whether changes in ECM substrate expression are a cause or a consequence of differentiation remains to be determined.  As noted, there are indications in the literature that the ECM may direct cell fate choices, and for example reference 36 where increasing ECM stiffness has been found to modulate neuronal differentiation of neuroblastoma cells and reference 37 where ECM topography has been shown to drive a transition between adrenergic and mesenchymal cell types. As noted, \u2018The role of the ECM during neural crest development is well-described, with cells interacting with a dynamic ECM in a spatiotemporal manner to direct their correct differentiation and migration. As such, the ECM composition is a key component of many protocols for neuronal differentiation from stem cell states [29]\u2019. In referencing this literature in the first manuscript version, we intended to discuss whether ECM changes are a cause or consequence of cell fate decisions as an interesting topic for further exploration. For example, \u2018it would be interesting to further explore whether ECM modification is able to alter neuroblastoma cell identity in response to PB+RA, and if so, whether drugs altering mechano-transduction pathways may offer additional differentiation benefits.\u2019 We have added to the text to clarify this (Discussion, Paragraph 4), acknowledging that our data are an initial observation to prompt further investigation. It would be important to test this in an in vivo system where cumulative effects of cell types will exist, and have further discussed this in the discussion in paragraph 4. We have also modified the text from \u2018build a case\u2026 for investigating the effect of ECM on neuroblastoma cell fate decisions\u2019 to \u2018investigating ECM changes in neuroblastoma differentiation\u2019 (e.g. end of Introduction and end of Results) to reflect this increased discussion. &nbsp; We thank the reviewer for their helpful comments which have guided submission of version 2 of this manuscript. While we note that the Reviewer quite rightly states that we could take this work further, we are unable to do so because of staffing constraints. However, we feel strongly that it is important to disseminate our findings to allow others to build on the work that we have done and feel that Wellcome Open Research would be an appropriate venue for this. We hope that the reviewer can consider this when evaluating our responses.","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v2#referee-comment-6214","order":3,"name":"referee-comment-6214","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.27411.r133019, Sheron Cogo, School of Medicine and Health Sciences, Pontifical Catholic University of Parana, Curitiba, 03 Dec 2025, version 2, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v2#referee-response-133019","order":4,"name":"referee-response-133019","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.25621.r113580, Carmen Mej\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Quer\u00e9taro, 24 Dec 2024, version 1, 4 approved with reservations","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v1#referee-response-113580","order":5,"name":"referee-response-113580","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Anna Philpott<\/b>; \n<i>Posted: 24 Aug 2025<\/i>; We thank the reviewer for their helpful comments and respond to each of these below.  \n<b>Comment 1: <\/b>&nbsp;Information on the characteristics of the cell lines is missing. \n<b>Author response<\/b>: &nbsp;Thank you for this comment. We have now included available cell line details in the text with references (Results, paragraph 2), including details of phenotypic classifications.  &nbsp;  \n<b>Comment 2: <\/b>They do not show the genes that make up the 5 groups and that is why it is difficult to follow the graphs. I suggest that they include the lists of these genes to know how they contribute to the differentiation analysis. \n<b>Author response:<\/b> &nbsp;We provided the requested table of genes associated with each signature in the data and code available on zenodo, but we have now added this&nbsp;to Extended Data, Table S2, so that it is more readily findable, and have directly&nbsp;referred to this table within the text and figure legend. In addition, as often a greater number of genes are detectable by bulk RNA-seq than scRNA-seq, we have added a column to this table 'gene_in_Jansky_et_al_2021' to be clear which genes from our clusters derived from bulk RNA-seq were also detectable in the single cell RNA-seq dataset. We have now also clarified in the legend of Figure 1A the gene groups associated with each cluster 1-5 (identified in our previous publication [7]).  &nbsp;  \n<b>Comment 3<\/b>: From a massive sequencing analysis, it is very risky for the authors to define the lineage that each cell line undergoes as a result of the various treatments\u2026.. \n<b>Author response: <\/b>&nbsp;We believe we have been cautious in not over-defining the lineages or exact cell types emerging. We have presented the findings in Figure 1 with supporting qRTPCR data, presenting interesting gene expression changes reminiscent of differentiation into different human adrenal gland cell lineages. We are aware of the caveats of bulk sequencing analyses, and indeed agree in the discussion that single-cell analysis would be enriching (Discussion, paragraph 5). However, despite our analyses being at the bulk level we see significant gene expression changes, worthy of presenting as interesting data for future exploration in the field of neuroblastoma differentiation heterogeneity.  &nbsp;  \n<b>Comment 4:<\/b> In Figure 2, where differentiation is analyzed by confocal microscopy, more information on the different states of differentiation is needed, in addition to quantifying these changes. \n<b>Author response:<\/b> &nbsp;We agree with the Reviewer that further exploration of the cell types emerging from PB+RA treatment of each cell line could be performed. As stated in the discussion \u2018Further exploration could include characterisation of the emerging cell types using single-cell RNA-seq, immunocytochemistry and flow cytometry analyses.\u2019 It would have been ideal to perform a full characterisation of the emerging cell types, using single cell techniques such as single cell RNA-seq.&nbsp; This would allow an accurate identification and comprehensive characterization of the cells emerging following PB+RA treatment, using the markers identified for validation by ICC and flow cytometry. However, this is unfortunately not possible due to funding constraints. We have expanded on these future work suggestions in the discussion and invite this for further research (Discussion, paragraph 5).  &nbsp;  \n<b>Comment 5:<\/b> In the same Figure, it is not clear why the authors decided to analyze these genes and not others. It would be important to include something about this in the text. \n<b>Author response: <\/b>&nbsp;The differentiation markers shown in Figure 2 were selected using marker genes of adrenal medullary cell populations referenced in Jansky et al [1].&nbsp; NEFM, GAP43 and SYT5 were chosen as markers of sympathetic neuroblasts. PNMT, the enzyme catalyzing methylation of norepinephrine to form epinephrine, was chosen as a marker of mature chromaffin cells, ACTA2 as a marker of myofibroblasts, MYH3 as a marker of myocytes, and CYP11A1 as a marker of adrenal cortical cells. This has been clarified in the text of the Results (section 2). We note that CYP11A1, as well as MYH3 and ACTA2, mark populations outside of the sympathoadrenal lineage - this is indeed interesting and could suggest malignant transformation at an early stage of neural crest development from bipotent or mesenchymal lineage precursors, and\/or plasticity of neuroblastoma cells (26) - we have discussed this further in the text (Discussion, paragraph 2). We agree that it would have been ideal to perform a full characterisation of the emerging cell types, encompassing all cell type markers, ECM factors, and transcription factors in Jansky et al [1] and more, using single cell RNA-seq - we have expanded on these future work suggestions in the discussion and invite this for further research (Discussion, paragraph 5).  &nbsp;  \n<b>Comment 6: <\/b>It is also not clear whether the authors performed the experiments in triplicate or even a greater number of times, given the statement \u201c3 biological replicates\u201d \n<b>Author response: &nbsp;<\/b>Three biological replicates were performed for each cell line, corresponding to three independent passages of each cell line. As stated in the \u2018Statistical Analysis\u2019 section of the Methods, \u2018Biological replicates were considered as different passage numbers of the same cell line plated in independent experiments\u2019. This has been further clarified in the text of the figure legends for Figures 2 and 3.  &nbsp;  \n<b>Comment 7:<\/b> A basal expression control of the cell lines is missing, which would support the response towards differentiation. \n<b>Author response:<\/b> &nbsp;Regarding the comparison of basal levels, the experiments were performed in a manner allowing us to compare DMSO with PB+RA treatment within each cell line. We therefore make conclusions as to whether fold changes in gene expression are seen within each line in response to PB+RA treatment. Comparison of the basal gene expression levels would indeed be also interesting, however is beyond the scope of the manuscript.  &nbsp;  \n<b>Comment 8:<\/b> The authors also analyze the expression of ECM factors. This is especially important for cells that acquire a mesenchymal phenotype. \n<b>Author response:<\/b> &nbsp;We agree with the Reviewer that expression of ECM factors may be particularly pertinent to differentiation into non-neuronal lineages. As discussed in the text (Results, section 3), our investigations into ECM factor expression were led by Tsokos et al\u2019s finding [8] that \u201cspecific patterns of ECM expression emerged after differentiation, proportional to the normal tissue cell types observed\u201d, particularly laminin, fibronectin and collagen. Our choice of ECM markers was guided by this list of genes, found to be differentially upregulated in PB+RA treated cells in [7]. We have now clarified this in the text (Results, section 3). We also mention in the discussion how ECM factors relate to mesenchymal-type differentiation - \u201cFor example, in fitting with the formation of unattached neurospheres, IMR-32 showed few changes in ECM factor expression upon PB+RA treatment, with exception of a significant downregulation in FN1 (Figure 3A). In contrast, a significant increase in FN1 and ITGA5 expression was observed in differentiating SK-N-BE(2)C cells; this aligns with differentiation into myofibroblasts (marked by ACTA2) which enhance fibronectin assembly. Myofibroblasts also secrete multiple collagen types, also seen to be significantly upregulated in SK-N-BE(2)C cells following PB+RA treatment\u201d.  &nbsp;  \n<b>Comment 9<\/b>: Finally, they propose studying the heterogeneity of the ECM as a new route in the differentiation process of NB. Something that is not fully supported by the results achieved. \n<b>Author response<\/b>: &nbsp;As in Tsokos et al [8], our data support that differentiation responses correspond to changes in patterns of ECM substrate expression. We agree with the Reviewer that whether changes in ECM substrate expression are a cause or a consequence of differentiation remains to be determined.  As noted, there are indications in the literature that the ECM may direct cell fate choices, and for example reference 36 where increasing ECM stiffness has been found to modulate neuronal differentiation of neuroblastoma cells and reference 37 where ECM topography has been shown to drive a transition between adrenergic and mesenchymal cell types. As noted, \u2018The role of the ECM during neural crest development is well-described, with cells interacting with a dynamic ECM in a spatiotemporal manner to direct their correct differentiation and migration. As such, the ECM composition is a key component of many protocols for neuronal differentiation from stem cell states [29]\u2019. In referencing this literature in the first manuscript version, we intended to discuss whether ECM changes are a cause or consequence of cell fate decisions as an interesting topic for further exploration. For example, \u2018it would be interesting to further explore whether ECM modification is able to alter neuroblastoma cell identity in response to PB+RA, and if so, whether drugs altering mechano-transduction pathways may offer additional differentiation benefits.\u2019 We have added to the text to clarify this (Discussion, Paragraph 4), acknowledging that our data are an initial observation to prompt further investigation. It would be important to test this in an in vivo system where cumulative effects of cell types will exist, and have further discussed this in the discussion in paragraph 4. We have also modified the text from \u2018build a case\u2026 for investigating the effect of ECM on neuroblastoma cell fate decisions\u2019 to \u2018investigating ECM changes in neuroblastoma differentiation\u2019 (e.g. end of Introduction and end of Results) to reflect this increased discussion. &nbsp; We thank the reviewer for their helpful comments which have guided submission of version 2 of this manuscript. While we note that the Reviewer quite rightly states that we could take this work further, we are unable to do so because of funding and staffing constraints.&nbsp; However, we feel strongly that it is important to disseminate our findings to allow others to build on the work that we have done and feel that Wellcome Open Research would be an appropriate venue for this.&nbsp;We hope that the reviewer can consider this when evaluating our responses.","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v2#referee-comment-6216","order":6,"name":"referee-comment-6216","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.27411.r133731, Nathaniel W Mabe, Purdue University, West Lafayette, Indiana, 26 Sep 2025, version 2, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v2#referee-response-133731","order":7,"name":"referee-response-133731","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.27411.r133729, Anand G Patel, St. Jude Children\u2019s Research Hospital, , Memphis, Tennessee, 06 Oct 2025, version 2, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/9-671\/v2#referee-response-133729","order":8,"name":"referee-response-133729","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This work was supported by the Cancer Research UK grant A25636 (to A.P., K.M.F., S.L.G., F.M.Y.A.G), Wellcome Trust Investigator award 212253\/Z\/ 18\/Z (to A.P.). Core support was provided from the Wellcome Trust 203151\/Z\/16\/Z, 203151\/A\/16\/Z] and the UKRI Medical Research Council MC_PC_17230. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":9,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}