PONE-D-22-09003Single-cell Analysis of a High-grade Serous Ovarian Cancer Cell Line Reveals Transcriptomic Changes and Cell Subpopulations Sensitive to Epigenetic Combination TreatmentPLOS ONE

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Reviewers' comments:

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Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: I Don't Know

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Overview

Nephew, et al., present data on RNA expression in single cells from the Ovcar3 cell line comparing untreated cells to cells treated with inhibitors of EZH2 and RAC1. This work is a follow up to their previous publication that identified DAB2IP as a tumor suppressor that blocks ovarian cancer stem cells, based on cell line models.

Interesting findings reported include

No major changes in gene expression after treating with the EZH2 inhibitor for 48 hours (Fig 2B). This is quite surprising, as one might expect large scale gene expression changes after blocking this histone methyltransferase, which would then cause differential clustering. (eg, Tiffen, et al., Oncotarget 2015)

RAC1 inhibition has remarkable effects causing upregulation of chemokines, SIRT77 and OVGP1, while downregulating ox/phos genes, Pax8 and stem cell markers ADLH1A1, CD24 and SOX2 in OVCAR3 cell line.

The findings are interesting, although their implications for ovarian cancer are tenuous until they are confirmed in more cell lines and in primary ovarian cancer tissue.

Methods summary

Authors treated the Ovcar3 cell line for 48 hrs with DMSO (control), NSC23766 (RAC1 inhibitor), GSK126 (EZH2 inhibitor), or both inhibitors together and then performed single cell RNAseq (scRNAseq) using the 10X Genomics platform. Data was analyzed using CellRanger and Seurat R packages. Data from ~7 to 10k cells from each treatment were combined and analyzed together. Cells were also treated with JC-1 and analyzed by IFC. The Ovcar3 cell line is a hypotriploid, poorly differentiated papillary adenocarcinoma derived from the ascites of a patient who had been treated with cyclophosphamide, adriamycin, and cisplatin 8 months prior to cell collection in 1982 (Hamilton, et al., Cancer Research 1983).

Major concerns

Cluster numbers

Leiden based clustering implemented by Seurat is strongly affected by selection of the following four input parameters: number of PCs, k-value, prune value and resolution value. Altering these required input parameters affects the number of clusters identified. Authors should perform Leiden based clustering multiple times using a range of these parameters and demonstrate that the clustering solution of 12, which is extensively analyzed in the paper, is the most robust clustering solution. Without this assurance, it is difficult to justify the findings.

Effect of inhibiting RAC1 on cell differentiation conclusion

In figure 1B authors list GO terms and pathways significantly associated with upregulated genes from cluster 2. The second highest associated GO term, based on p-value, is "negative regulation of cell differentiation". In figure 2B, authors show that cluster 2 is enriched in cells treated with RAC1 inhibitor. This would suggest that RAC1i treatment increases "negative regulation of cell differentiation", and yet authors conclude that "…treatment with RAC1i alone or in combination with EZH2i increased the cell proportions from 7% to approximately 25% of the entire cell population while EZH2i alone had no effect on this cluster (Figure 2B), suggesting that RACi treatment induced differentiation." This conclusion seems to be contradictory to their data. Authors should explain how their data indicates RAC1i induces differentiation and does not negatively regulate cell differentiation, as cluster 2 is enriched in negative regulators of differentiation.

Minor concerns

Cell numbers

Fig 2B shows changes in the percentages of cells in each cluster based on treatment. The statistics indicate that RAC1 treatment statistically increases the proportion of cells in cluster 2 and reduces the proportion in cluster 4. As these numbers are based on relative proportion, it is important to know if there was a large difference in growth of the cell populations after treatment with the inhibitors. One assumes that the authors submitted equal numbers of viable cells for each condition for sequencing, but it should be reported how much the treatment affected viability and growth.

Line 263 describes cluster 2 as "…which is enriched for genes associated with cell death and differentiation (Figure 2C)". This is possibly a typo, as cluster 2 did not have any cell death pathways associated (Fig 1B). I think authors meant to say, "cell development and differentiation".

The exact number of cells depicted in Fig 2A in each panel should be listed somewhere in the paper, so it is known how many cells were analyzed in each condition.

The authors conclusion that RAC1 inhibition reduces numbers of ovarian cancer stem cells by analyzing more stem cell markers and presenting these findings (eg PROM1/CD133, cKIT/CD117, CD44, the other ALDH genes)

Reviewer #2: To draw a valid conclusion, it is necessary to provide more detailed scRNA-seq data and additional results of validation experiments as specified below.

1. For each cluster of cells in scRNA-seq analysis, the most significant markers across all the samples should be tabulated and presented.

2. Genes contributed to the enriched pathways in each cell cluster (Figure 1B-E) should be tabulated and presented.

3. Validation experiments should be conducted to confirm that RAC1i treatment induces expression of inflammatory genes in OVCAR3 cells. It will be interesting to examine whether RACi-induced expression of CXCL1-3 and 8 can be replicated using other OV cell lines.

4. Genes contributed to the altered pathways by EZH2i and RAC1i in Cluster 2 (Figure 4) should be tabulated and presented. Validation experiments should be conducted to confirm that RAC1i treatment induces SIRT7 expression in OVCAR3 cells and examine whether this effect can be extended to other OV cell lines.

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Reviewer #1: No

Reviewer #2: No

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Single-cell Analysis of a High-grade Serous Ovarian Cancer Cell Line Reveals Transcriptomic Changes and Cell Subpopulations Sensitive to Epigenetic Combination Treatment

PONE-D-22-09003R1

Dear Dr. Nephew,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Lawrence M. Pfeffer, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The authors have been highly responsive to the reviewers and the manuscript is markedly improved. It now merits publication in PLOS One

Reviewers' comments: