Dataset Information

Subcellular analysis of nuclear and cytoplasmic redox indices differentiates breast cancer cell subtypes better than nuclear-to-cytoplasmic area ratio.

ABSTRACT:

Significance

Stratification of malignancy is valuable for cancer treatment. Both optical redox imaging (ORI) indices and nuclear-to-cytoplasmic volume/area ratio (N:C ratio) have been investigated to differentiate between cancers with varying aggressiveness, but these two methods have not been directly compared. The redox status in the cell nucleus has not been studied by ORI, and it remains unknown whether nuclear ORI indices add new biological information.

Aim

We sought to compare the capacity of whole-cell and subcellular ORI indices and N:C ratio to differentiate between breast cancer subtypes with varying aggressiveness and between mitotic and nonmitotic cells.

Approach

ORI indices for whole cell, cytoplasm, and nucleus as well as the N:C area ratio were generated for two triple-negative (more aggressive) and two receptor-positive (less aggressive) breast cancer cell lines by fluorescence microscopy.

Results

We found positive correlations between nuclear and cytoplasmic ORI indices within individual cells. On average, a nuclear redox status was found to be more oxidized than cytoplasm in triple-negative cells but not in receptor-positive cells. Whole-cell and subcellular ORI indices distinguished between the receptor statuses better than the N:C ratio. However, N:C ratio was a better differentiator between nonmitotic and mitotic triple-negative cells.

Conclusions

Subcellular ORI analysis differentiates breast cancer subtypes with varying aggressiveness better than N:C area ratio.

SUBMITTER: Jacob A

PROVIDER: S-EPMC9360498 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Publications

Subcellular analysis of nuclear and cytoplasmic redox indices differentiates breast cancer cell subtypes better than nuclear-to-cytoplasmic area ratio.

Jacob Annemarie A Xu He N HN Stout Andrea L AL Li Lin Z LZ

Journal of biomedical optics 20220801 8

<h4>Significance</h4>Stratification of malignancy is valuable for cancer treatment. Both optical redox imaging (ORI) indices and nuclear-to-cytoplasmic volume/area ratio (N:C ratio) have been investigated to differentiate between cancers with varying aggressiveness, but these two methods have not been directly compared. The redox status in the cell nucleus has not been studied by ORI, and it remains unknown whether nuclear ORI indices add new biological information.<h4>Aim</h4>We sought to compa ...[more]

PMID: 35945669

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Project description:BackgroundConflicting data exist regarding the prognostic and predictive impact of survivin (BIRC5) in breast cancer. We previously reported survivin cytoplasmic-to-nuclear ratio (CNR) as an independent prognostic indicator in breast cancer. Here, we validate survivin CNR in a separate and extended cohort. Furthermore, we present new data suggesting that a low CNR may predict outcome in tamoxifen-treated patients.MethodsSurvin expression was assessed using immunhistochemistry on a breast cancer tissue microarray (TMA) containing 512 tumours. Whole slide digital images were captured using an Aperio XT scanner. Automated image analysis was used to identify tumour from stroma and then to quantify tumour-specific nuclear and cytoplasmic survivin. A decision tree model selected using a 10-fold cross-validation approach was used to identify prognostic subgroups based on nuclear and cytoplasmic survivin expression.ResultsFollowing optimisation of the staining procedure, it was possible to evaluate survivin protein expression in 70.1% (n = 359) of the 512 tumours represented on the TMA. Decision tree analysis predicted that nuclear, as opposed to cytoplasmic, survivin was the most important determinant of overall survival (OS) and breast cancer-specific survival (BCSS). The decision tree model confirmed CNR of 5 as the optimum threshold for survival analysis. Univariate analysis demonstrated an association between a high CNR (>5) and a prolonged BCSS (HR 0.49, 95% CI 0.29-0.81, p = 0.006). Multivariate analysis revealed a high CNR (>5) was an independent predictor of BCSS (HR 0.47, 95% CI 0.27-0.82, p = 0.008). An increased CNR was associated with ER positive (p = 0.045), low grade (p = 0.007), Ki-67 (p = 0.001) and Her2 (p = 0.026) negative tumours. Finally, a high CNR was an independent predictor of OS in tamoxifen-treated ER-positive patients (HR 0.44, 95% CI 0.23-0.87, p = 0.018).ConclusionUsing the same threshold as our previous study, we have validated survivin CNR as a marker of good prognosis in breast cancer in a large independent cohort. These findings provide robust evidence of the importance of survivin CNR as a breast cancer biomarker, and its potential to predict outcome in tamoxifen-treated patients.

Dataset Information

Subcellular analysis of nuclear and cytoplasmic redox indices differentiates breast cancer cell subtypes better than nuclear-to-cytoplasmic area ratio.

Significance

Aim

Approach

Results

Conclusions

Publications

Subcellular analysis of nuclear and cytoplasmic redox indices differentiates breast cancer cell subtypes better than nuclear-to-cytoplasmic area ratio.

Similar Datasets

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