Analysis of cells in the fallopian tube, from which most ovarian cancers develop, can help classify ovarian cancer subtypes, with potential implications for cancer prognoses and treatment strategies, a new study shows.
Serous ovarian cancer (SOC) is the most common type of ovarian cancer, accounting for around 70% of cases. Despite its name, most SOCs don’t originate in the ovary but typically start in the fallopian tube, which connects the ovary and uterus. Understanding the normal biology of these cells could help provide insights into what happens when they become cancerous.
In the new study, researchers analyzed cells from the inner layer (epithelium) of the fallopian tube using a relatively new technology called single-cell RNA sequencing (scRNA-seq). This technology can assess the transcriptome, or gene expression profile, of individual cells — essentially determining the extent to which thousands of genes in each cell are “off” or “on.”
The researchers analyzed the transcriptomes of 2,132 non-cancerous fallopian tube cells. Then, computer programs were used to group the cells into clusters based on patterns in gene expression. In so doing, the researchers identified several hitherto unrecognized subtypes of cells.
Notably, the analysis was done using fresh cells — that is, cells were analyzed shortly after being recovered from a patient. In research, cells will often be grown in a lab (cultured) to get more cells for analysis and allow experiments to be repeated.
Interestingly, when the fallopian tube cells were cultured, whether overnight or for longer periods of time, the researchers “observed striking effects induced by culture conditions on the transcriptomes of single cells,” they wrote. This serves as a cautionary note about how cells grown in a lab, however briefly, are not necessarily reflective of those same cells in a human body. As such, fresh cells were used in all subsequent analyses.
Having identified subsets of normal fallopian tube cells, the researchers then analyzed transcriptome data for SOC samples recorded in public databases, The Cancer Genome Atlas and the Australian Ovarian Cancer Study. The gene expression profiles identified for subtypes of normal cells were reflected in similar differences in the SOC cell samples.
Of particular note, certain cells (cancerous or not) expressed high levels of genes associated with a cellular process called epithelial-to-mesenchymal transition (EMT). Basically, this process allows cells to become more mobile, playing a critical part in cancer spreading (metastasis).
Interestingly, a “mesenchymal” subtype exists within the current TCGA classification system. Presumably, these two classifications should have considerable overlap. However, of 238 TCGA tumors labeled “non-mesenchymal” in the database, 87 (37%) were classified as “EMT-high” based on their transcriptome. And, “these tumors carried worse prognosis when compared with the non-mesenchymal and EMT-low group of cancer,” the researchers wrote.
A single tumor contains not only cancer cells, but also other cell types, such as those that help make up connective tissue. Thus, it’s possible that this “EMT-high” subtype is actually a different type of cell entirely. To rule out this possibility, the researchers analyzed cells from 36 SOC tumors that had undergone microdisection. This confirmed that the “EMT-high” cells were indeed fallopian tube epithelial cells, not another cell type.
The researchers also noted that another subtype, dubbed the ciliated subtype owing to the presence of cilia (hair-like protrusions on cells), was particularly enriched in low-grade tumors in the AOCS dataset. No tumors of this subtype were identified in TCGA data, which only includes high-grade SOC samples. This suggests that, “the enrichment in these ciliated markers is most probably a distinguishing molecular feature of low-grade tumors,” the researchers wrote.
Overall, this study provides further insight into the types of cells found in the fallopian tube epithelium, both in its normal state and when cancer develops.
“Identifying the type of cancer cells is an important early step in choosing which drugs and treatments to use because different types of cells respond differently to treatment,” study co-author Ahmed Ashour Ahmed, MD, PhD, professor at Oxford University, said in a press release. “Our new tumour classifier should give us much more accurate predictions for disease outcome in patients as well as helping us to develop targeted therapies for each type of cancer.”
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