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联合增殖和凋亡指数能为乳腺癌提供更好的风险分层。

Combined proliferation and apoptosis index provides better risk stratification in breast cancer.

作者信息

Ibrahim Asmaa, Toss Michael S, Atallah Nehal M, Al Saleem Mansour, Green Andrew R, Rakha Emad A

机构信息

Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham Biodiscovery Institute, University Park, Nottingham, UK.

Histopathology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt.

出版信息

Histopathology. 2023 Jun;82(7):1029-1047. doi: 10.1111/his.14887. Epub 2023 Mar 6.

Abstract

AIMS

Breast cancer (BC) risk stratification is critical for predicting behaviour and guiding management decision-making. Despite the well-established prognostic value of cellular proliferation in BC, the interplay between proliferation and apoptosis remains to be defined. In this study, we hypothesised that the combined proliferation and apoptosis indices can provide a more accurate in-vivo growth rate measure and a precise prognostic predictor.

METHODS AND RESULTS

Apoptotic and mitotic figures were counted in whole slide images (WSI) generated from haematoxylin and eosin-stained sections of 1545 BC cases derived from two well-defined BC cohorts. Counts were carried out visually within defined areas. There was a significant correlation between mitosis and apoptosis scores. High apoptotic counts were associated with features of aggressive behaviour, including high grade, high pleomorphism score and hormonal receptor negativity. Although the mitotic index (MI) and apoptotic index (AI) were independent prognostic indicators, the prognostic value was synergistically higher when combined. BC patients with a high combined AI and MI had the shortest survival. Replacing the mitosis score with the mitosis-apoptosis index in the Nottingham grading system revealed that the modified grade with the new score had a higher significant association with BC-specific survival with a higher hazard ratio.

CONCLUSION

Apoptotic figures count provides additional prognostic value in BC when combined with MI; such a combination can be implemented to assess the behaviour of BC and provides an accurate prognostic indicator. This can be considered when using artificial intelligence algorithms to assess proliferation in BC.

摘要

目的

乳腺癌(BC)风险分层对于预测病情发展及指导管理决策至关重要。尽管细胞增殖在乳腺癌中的预后价值已得到充分确立,但增殖与凋亡之间的相互作用仍有待明确。在本研究中,我们假设增殖和凋亡指数相结合可提供更准确的体内生长速率测量方法及精确的预后预测指标。

方法与结果

对来自两个明确的乳腺癌队列的1545例乳腺癌病例的苏木精和伊红染色切片生成的全切片图像(WSI)中的凋亡和有丝分裂图像进行计数。在规定区域内进行目视计数。有丝分裂和凋亡评分之间存在显著相关性。高凋亡计数与侵袭性行为特征相关,包括高级别、高多形性评分和激素受体阴性。尽管有丝分裂指数(MI)和凋亡指数(AI)是独立的预后指标,但两者结合时预后价值协同更高。AI和MI均高的乳腺癌患者生存期最短。在诺丁汉分级系统中用有丝分裂 - 凋亡指数取代有丝分裂评分后发现,新评分的改良分级与乳腺癌特异性生存的显著相关性更高,风险比也更高。

结论

凋亡图像计数与MI结合时可为乳腺癌提供额外的预后价值;这种组合可用于评估乳腺癌的病情,并提供准确的预后指标。在使用人工智能算法评估乳腺癌增殖时可考虑这一点。

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