Dataset Information

Gene expression predicts dormant metastatic breast cancer cell phenotype.

ABSTRACT:

Background

Breast cancer can recur months to decades after an initial diagnosis and treatment. The mechanisms that control tumor cell dormancy remain poorly understood, making it difficult to predict which patients will recur and thus benefit from more rigorous screening and treatments. Unfortunately, the extreme rarity of dormant DTCs has been a major obstacle to their study.

Methods

To overcome this challenge, we developed an efficient system to isolate and study rare dormant breast cancer cells from metastatic organs including bones, which represent a major site of metastasis. After isolation of cells from the long bones, we used single cell RNA-sequencing (scRNA-seq) to profile proliferative and dormant PyMT-Bo1 breast cancer cells. We also compared this signature to dormant versus proliferative tumor cells isolated from the lungs. Finally, we compared our dormant signature to human datasets.

Results

We identified a group of genes including Cfh, Gas6, Mme and Ogn that were highly expressed in dormant breast cancer cells present in the bone and lung. Expression of these genes had no impact on dormancy in murine models, but their expression correlated with disease-free survival in primary human breast cancer tumors, suggesting that these genes have predictive value in determining which patients are likely to recur.

Conclusions

Dormant breast cancer cells exhibit a distinct gene expression signature regardless of metastatic site. Genes enriched in dormant breast cancer cells correlate with recurrence-free survival in breast cancer patients.

SUBMITTER: Ren Q

PROVIDER: S-EPMC8800302 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeDisseminated tumor cells (DTCs) in the BM of breast cancer patients predict early disease relapse, but the molecular heterogeneity of these cells is less well characterized. Expression of a 46-gene panel was used to detect DTCs and classify patient BM samples to determine whether a composite set of biomarkers could better predict metastatic relapse.MethodsUsing a high-throughput qRT-PCR assay platform, BM specimens collected from 70 breast cancer patients prior to neoadjuvant therapy were analyzed for the expression of 46 gene transcripts. Gene expression was scored positive (detectable) relative to a reference pool of 16 healthy female control BM specimens. To validate findings from a subset of 28 triple-negative breast cancer (TNBC) patients in the initial 70 patient cohort, an independent set of pre-therapeutic BM specimens from 16 TNBC patients was analyzed.ResultsExpression of each of the 46 gene transcripts was highly variable between patients. Individual gene expression was detected in 0-84% of BM specimens analyzed and all but two patient BM specimens expressed at least one transcript. Among a subset of 28 patients with TNBC, positivity of one or more of eight transcripts correlated with time to distant relapse (p = 0.03). In an independent set of 16 triple-negative patient BM samples, detection of five of these same eight gene transcripts also correlated with time to distant relapse (p = 0.03) with a positive predictive value of 89%.ConclusionsWe identified a set of gene transcripts whose detection in the BM of TNBC patients, prior to any treatment intervention, predicts time to first distant relapse, thus identifying a TNBC patient population which requires additional treatment intervention. Because these genes are presumably expressed in populations of DTCs and many encode proteins that are known therapeutic targets (e.g., ERBB2), these results also suggest a potential approach for targeted DTC therapy to mitigate distant metastases in TNBC.