Integrated Human Transcriptomics Identifies Fallopian Tube Progenitors as Plausible Precursors of High-Grade Serous Ovarian Cancer

Reviewer #1 (Public review):

Summary:

Using comprehensive profiling of normal and cancerous tissue via bulk and single-cell RNA sequencing, the authors identified that high-grade serous ovarian cancer is likely to originate from the epithelial progenitor cells from the distal fimbrial region of the fallopian tube, where it has been previously shown to be most prone to ovulatory stress and other microenvironmental influences. The authors also included a CNV analysis to identify hotspots in HGSOCs.

The findings are preliminary, but the resource on its own has great potential and can be used for developing methods for early detection, stratification and treatment.

The main limitation of this study is that the lineage is purely inferred from bioinformatics analysis. More validation work is required, perhaps using cell models / other model organisms.

Strengths and weaknesses:

The authors investigated the origin of high-grade serous ovarian cancer, which is one of the deadliest. They performed comparative analysis using both bulk and single-nucleus RNA sequencing between cancerous and normal tissues (fallopian tube and ovaries) and identified a population of epithelial progenitor cells from the distal fimbrial region that are exposed to ovulatory stress, as the most plausible cells of origin. The extensive profiling of the molecular signatures can also be used for early detection and stratification for treating the disease.

Previous studies have shown that HGSOCs likely originated from the epithelial lining of the fallopian tubes (PMID 32349388). The bulk RNAseq data is confusing in that neither the overall correlation of the transcriptome nor the sample clustering (Figure 1) supports the idea that the HGSOCs are close to the fallopian tube. The authors could perform a more comprehensive marker gene-based analysis to demonstrate their relationship.

The authors also performed a comprehensive analysis of single-cell datasets on both normal and cancerous tissue in humans. From there, they performed a combination of RNA velocity, PAGA and pseudotime, etc, to try and delineate the relationship amongst related cell populations. It would be helpful if the authors could clarify why they applied this particular suite of tools (explaining the differences between tools and bioinformatic approaches) to assist the broader readership who may not be familiar with this type of single-cell bioinformatic analysis.

It also seems to me that the authors did not account for patient effect when they performed the data integration (this point is discussed in the text). This may explain at least partially why the clusters are segregated by patient samples. Another explanation is that it could be due to uneven sampling, as only very few cells (1000s) were captured from each of the tumour samples, and this is clear when a dramatic difference can be seen in their cellular composition.

The trajectory analysis of normal and cancer single-cell data should also include other cells to prevent confirmation bias, as these analyses would only consider relationships amongst the cells available in the model.

As the authors indicated in the limitations, the cell lineage in the studies is largely inferred from the bioinformatics analysis. Experimental lineage tracing via other experimental models (organoids/animal models) would be required.

Despite these limitations, this study will serve as an important resource for the scientific community. I would also suggest that the authors should share this resource via additional portals in addition to the GEO data deposit (e.g. the HCA, or single-cell portals such as at the Broad Institute or CellXGene Discover).

Reviewer #2 (Public review):

Summary:

The authors used single-nuclei sequencing of benign fallopian tubes and ovarian cancer to delineate the plausible cell of origin of high-grade serous ovarian cancer.

Strengths:

These substantial data provide the field with significant research resources to examine additional features in normal fallopian tubes and ovarian cancers. The highly detailed bioinformatic analysis, rooted in a strong biological framework, is convincing. The methodology was appropriate and used validated methodology based on biological relevance (region selection and transcriptomics analysis).

The authors propose a convincing model of epithelial progenitor cells and their localisation in high-grade serous ovarian cancers. These findings are important and useful.

Weaknesses:

Overall, the weaknesses are clearly stated in the discussion. The study provides a novel framework for future study, and proposes a model which will require validation.

Within the ovarian cancer field, the endometrioid and clear cell histotypes are thought to arise from ciliated or secretory cells. Typically these are thought to be from the cervix or uterus. This concept was not mentioned in the work.

Further, in the ovarian cancer field, stemness is judged by some classic assays - aldehyde assays looking at ALDH1A1 and spheroid-producing ability. These were not mentioned - could these be useful in a population of fallopian tube epithelial cells, or would other assays/markers be more appropriate?

The choice of ES2 and OVCAR was not sufficiently justified, as ES2 is widely regarded as a clear cell ovarian cancer cell line in many research circles. Additionally, I did not see confirmation of gene knockdown by Western blot or qPCR.

PGR loss through copy number variant was surprising, as this was a marker. So would the marker be lost through one of these mechanisms randomly or specifically?

Author response:

We are particularly encouraged by the consensus that our study provides a substantial resource and that the bioinformatic framework is biologically grounded and convincing, while appropriately noting that further experimental validation will be required. We fully agree with this point. As clarified in the revised manuscript, the lineage relationships we describe are inferred from integrative transcriptomic analyses and are intended to provide a mechanistic and conceptual framework rather than definitive proof of cellular origin. We have further strengthened the Discussion to explicitly acknowledge these limitations and outline future directions, including lineage tracing and functional validation studies.

At the same time, we respectfully note that such experimental validation would require a substantial extension of this work and likely 2–3 years of additional studies, including development of appropriate model systems. We believe these efforts represent an important next phase of investigation rather than a revision-level addition to the current manuscript. Our primary goal here is to present a high-resolution human transcriptomic resource and a coherent framework that identifies biologically plausible epithelial intermediates linking normal fallopian tube hierarchy to malignant states.

Given the reviewers’ positive evaluation and recognition of the value and rigor of the dataset and analyses, we respectfully request consideration to proceed with publication as an eLife Version of Record without further experimental revision. We believe that the timely dissemination of these findings will provide a useful resource for the field and help guide the experimental studies needed to test the hypotheses generated here.