Combined Assessment of Tumor Cell Proliferation and Cell Death Using Digital Pathology Improves Risk Prediction in Breast Cancer

by Christos Evangelou, MSc, PhD – Medical Writer and Editor.

Predictive and prognostic biomarkers can help clinicians stratify patients with cancer according to different risk metrics and identify the appropriate treatment for each patient. Cancer cell proliferation, traditionally measured by immunohistochemical staining of cancer tissues for the proliferation index Ki67, is one of the most well-established prognostic biomarkers in breast cancer. Nevertheless, the prognostic role of cell death alone or in combination with cancer cell proliferation remains unclear.

In a recent study, researchers from the University of Nottingham employed digital pathology tools to establish a robust prognostic model for patients with breast cancer.1 The results of the study suggest that the combined assessment of cell proliferation and cell death in histological breast cancer sections offers a precise growth rate measurement and accurately determines patient outcomes.

“Our findings show that the measurement of both cell proliferation and cell apoptosis in breast cancer could facilitate the accurate risk classification of patients with breast cancer,” stated Asmaa Ibrahim, Assistant Lecturer of Pathology, PhD candidate at the University of Nottingham and first author of the study. “Patients with tumors showing high tumor cell proliferation and high apoptosis have the worst outcome and should be treated using more aggressive therapy,” she added. The study was published as a preprint and is publicly available through Research Square.


Study Rationale: Improving the Accuracy of Risk Stratification in Patients with Breast Cancer

In this study, the team aimed to gain insights into the potential link between cell proliferation and cell death in breast cancer using a large series of cases. They also sought to develop an index incorporating both cell proliferation and cell death into a single parameter to stratify patients with breast cancer according to their risk of death and tumor recurrence.

“Even though cell proliferation and evasion of apoptosis are separate hallmarks of cancer, in a pilot study, we noticed a relationship between highly proliferative breast tumors and the presence of apoptotic bodies,” Dr Ibrahim explained.

“We hypothesized that combining cell proliferation and apoptosis scores into a single index would provide a more accurate in vivo growth rate measure and a precise prognostic indicator for patients with breast cancer,” she added.


Prognostic Model

Cell proliferation and apoptosis were assessed using whole slide images (WSIs) generated from breast cancer tissue sections stained with hematoxylin and eosin (H&E). The tissue sections were obtained from two cohorts: the Nottingham cohort, which included 715 patients with early-stage operable breast cancer, and the Cancer Genomic Atlas (TCGA) cohort, which included 830 patients with breast cancer.1

Mitotic figures and apoptotic bodies were counted in predefined tissue areas. Apoptotic bodies were defined by the presence of at least one of the morphological features of apoptosis, including nuclear pyknosis, cellular shrinkage, nuclear fragmentation, and loss of cell-to-cell contact.1 The number of apoptotic bodies or mitotic figures per 3mm2 were used to calculate the apoptotic and mitotic indexes.

Apoptosis assessment is based on the morphological features of the tissues. Dr Ibrahim explained that one of the main challenges hindering the clinical adoption of apoptosis as a prognostic marker is the subjectivity of the assessment of morphological tissue features. The use of AI algorithms can help increase the objectivity of apoptosis assessment in clinical specimens.

“Using a large breast cancer case series and digital pathology, we combined the analysis of cell proliferation and cell death demonstrating a substantial significant correlation between the two distinct entities,” she noted.


Morphological Features are A Reliable Indicator of Tumor Cell Apoptosis

Assessment of tumor cell proliferation and apoptosis using the morphological scoring method revealed a significant correlation between apoptotic score and mitotic index in both cohorts (Nottingham cohort: r = 0.54, p < 0.001; TCGA cohort: r = 0.49, p < 0.001).1 The strong correlation between apoptosis score and the levels of the apoptotic marker cleaved caspase-3 (r = 0.874, p < 0.001) confirmed the reliability of the apoptosis scoring method using morphological features.


Tumor Cell Proliferation and Apoptosis Are Associated with Clinicopathological Characteristics

High apoptotic counts were significantly associated with various aggressive tumor characteristics, including high mitotic score (p < 0.001), high tumor grade (p < 0.001), high Nottingham prognostic index (p = 0.002), and lymph vascular invasion (p = 0.008).1 Additionally, high apoptotic counts were associated with estrogen receptor negativity (p = 0.046), HER2 negativity (p = 0.021), and high nuclear pleomorphism score (p = 0.048).

In both cohorts, the mitosis-apoptosis index was significantly associated with aggressive features, including high tumor grade (p < 0.001), high Nottingham prognostic index (p < 0.001), lymphovascular invasion (p = 0.005), and high nuclear pleomorphism (p = 0.005).


Tumor Cell Proliferation and Apoptosis Are Associated with Patient Outcomes

Multivariate Cox regression analysis showed that apoptosis score was an independent predictor of survival in Nottingham and TCGA cohorts (hazard ratio [HR]: 3.49, 95% confidence interval [CI]: 2.56–4.77, p < 0.001; and HR: 3.31, 95% CI: 1.37–7.95, p = 0.007).1 However, the prognostic value of the mitotic index increased when combined with the apoptosis score.

In the Nottingham cohort, a high mitotic-apoptosis index was significantly associated with poor breast cancer-specific survival (HR: 2.00, 95% CI: 1.76–2.26, p < 0.001), distant metastasis-free survival (HR: 1.83, 95% CI: 1.63–2.05; p < 0.001), and recurrence-free survival (HR: 1.49, 95% CI: 1.36–1.64, p < 0.001).


Tumor Cell Proliferation and Apoptosis Are Associated with Gene Expression Profiles

Comparison of gene expression profiles between tumors with high mitotic-apoptosis index and those with low mitotic-apoptosis index revealed that breast cancer cases with a high mitotic-apoptosis index were associated with upregulation of various genes that have DNA-binding transcription activity and encode proteins that control the transcriptional activity of several genes involved in cell cycle progression from G1 to S phase and in apoptosis regulation. These genes could be responsible for this unfavorable prognosis, and targeting them would likely improve patient survival and recurrence.


Remaining Challenges

Dr Ibrahim noted that there remains subjectivity in the assessment of apoptotic bodies, as they are captured at different phases of the process, and cells undergoing apoptosis and necrosis may show similar morphological features.

“We tried to overcome this limitation by using immunohistochemical staining for cleaved caspase-3, a maker highly specific to apoptotic cells, but this would require further validation,” she said. “In addition, the assessment of apoptotic bodies is a very time-consuming and tedious process, so applying automated detection algorithms would allow scoring a larger number of cases with precision.”




1. Ibrahim A, Toss M, Al Saleem M, Atalla N, Green A, Rakha E. Breast cancer risk stratification based on combined analysis of proliferation and apoptosis. 2022.

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