Imaging Biomarkers As Predictors for Breast Cancer Death

Overview

Journal J Oncol

Specialty Oncology

Date 2019 May 17

PMID 31093281

Citations 5

Authors

Wendy Yi-Ying Wu

Laszlo Tabar

Tibor Tot

Ching-Yuan Fann

Amy Ming-Fang Yen

Sam Li-Sheng Chen

Sherry Yueh-Hsia Chiu

May Mei-Sheng Ku

Chen-Yang Hsu

Kerri R Beckmann

Robert A Smith

Stephen W Duffy

Hsiu-Hsi Chen

Affiliations

Soon will be listed here.

Abstract

Background: To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes.

Methods: Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other predictors on the risk of breast cancer death. External validation was performed with a cohort of 848 patients diagnosed between 2006 and 2010.

Results: Mammographic tumor appearance was an independent predictor of risk of breast cancer death (P=0.0003) when conventional tumor attributes and treatment modalities were controlled. The casting type calcifications and architectural distortion were associated with 3.13-fold and 3.19-fold risks of breast cancer death, respectively. The basal phenotype independently conferred a 2.68-fold risk compared with nonbasal phenotype. The observed deaths did not differ significantly from expected deaths in the validation cohort. The application of imaging biomarkers together with other predictors classified twelve categories of risk for breast cancer death.

Conclusion: Combining imaging biomarkers such as the mammographic appearance of the tumor with the histopathologic distribution and basal phenotype, accurately predicted long-term risk of breast cancer death. The information may be relevant for determining the need for molecular testing, planning treatment, and determining the most appropriate clinical surveillance schedule for breast cancer patients.

Citing Articles

Clinicopathological characteristics and prognostic significance of casting-type calcifications in patients with invasive breast cancer presenting with microcalcification.

Wang J, Zhao L, Hu X, Lv L, Zhang X, Lu M Sci Rep. 2024; 14(1):13351.

PMID: 38858542 PMC: 11164990. DOI: 10.1038/s41598-024-64353-5.

Does Diffusely Infiltrating Lobular Carcinoma of the Breast Arise from Epithelial-Mesenchymal Hybrid Cells?.

Tabar L, Bozo R, Dean P, Ormandi K, Puchkova O, Olah-Nemeth O Int J Mol Sci. 2023; 24(13).

PMID: 37445938 PMC: 10341583. DOI: 10.3390/ijms241310752.

Ultrasound features for prediction of long-term outcomes of women with primary breast cancer <20 mm.

Shao S, Yao M, Li C, Li X, Wang J, Chen J Front Oncol. 2023; 13:1103397.

PMID: 37007100 PMC: 10061109. DOI: 10.3389/fonc.2023.1103397.

Precision Science on Incidence and Progression of Early-Detected Small Breast Invasive Cancers by Mammographic Features.

Chang R, Chuang S, Hsu C, Yen A, Wu W, Chen S Cancers (Basel). 2020; 12(7).

PMID: 32664200 PMC: 7408735. DOI: 10.3390/cancers12071855.

Microcalcifications Drive Breast Cancer Occurrence and Development by Macrophage-Mediated Epithelial to Mesenchymal Transition.

Scimeca M, Bonfiglio R, Menichini E, Albonici L, Urbano N, De Caro M Int J Mol Sci. 2019; 20(22).

PMID: 31718020 PMC: 6888678. DOI: 10.3390/ijms20225633.

References

Tabar L, Chen H, Duffy S, Yen M, Chiang C, Dean P . A novel method for prediction of long-term outcome of women with T1a, T1b, and 10-14 mm invasive breast cancers: a prospective study. Lancet. 2000; 355(9202):429-33. DOI: 10.1016/s0140-6736(00)82008-5. View

Perou C, Sorlie T, Eisen M, van de Rijn M, Jeffrey S, Rees C . Molecular portraits of human breast tumours. Nature. 2000; 406(6797):747-52. DOI: 10.1038/35021093. View

Zunzunegui R, Chung M, Oruwari J, Golding D, Marchant D, Cady B . Casting-type calcifications with invasion and high-grade ductal carcinoma in situ: a more aggressive disease?. Arch Surg. 2003; 138(5):537-40. DOI: 10.1001/archsurg.138.5.537. View

Sotiriou C, Neo S, McShane L, Korn E, Long P, Jazaeri A . Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A. 2003; 100(18):10393-8. PMC: 193572. DOI: 10.1073/pnas.1732912100. View

Tabar L, Tony Chen H, Amy Yen M, Tot T, Tung T, Chen L . Mammographic tumor features can predict long-term outcomes reliably in women with 1-14-mm invasive breast carcinoma. Cancer. 2004; 101(8):1745-59. DOI: 10.1002/cncr.20582. View

Subramaniam D, Isaacs C . Utilizing prognostic and predictive factors in breast cancer. Curr Treat Options Oncol. 2005; 6(2):147-59. DOI: 10.1007/s11864-005-0022-1. View

Livasy C, Karaca G, Nanda R, Tretiakova M, Olopade O, Moore D . Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. Mod Pathol. 2005; 19(2):264-71. DOI: 10.1038/modpathol.3800528. View

Tot T . The limited prognostic value of measuring and grading small invasive breast carcinomas: the whole sick lobe versus the details within it. Med Sci Monit. 2006; 12(8):RA170-5. View

Turner N, Reis-Filho J, Russell A, Springall R, Ryder K, Steele D . BRCA1 dysfunction in sporadic basal-like breast cancer. Oncogene. 2006; 26(14):2126-32. DOI: 10.1038/sj.onc.1210014. View

10.

Elston C, Ellis I . Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology. 1991; 19(5):403-10. DOI: 10.1111/j.1365-2559.1991.tb00229.x. View

11.

Duffy S, Tabar L, Fagerberg G, Gad A, GRONTOFT O, South M . Breast screening, prognostic factors and survival--results from the Swedish two county study. Br J Cancer. 1991; 64(6):1133-8. PMC: 1977849. DOI: 10.1038/bjc.1991.477. View

12.

Tot T . Clinical relevance of the distribution of the lesions in 500 consecutive breast cancer cases documented in large-format histologic sections. Cancer. 2007; 110(11):2551-60. DOI: 10.1002/cncr.23052. View

13.

Liu H, Fan Q, Zhang Z, Li X, Yu H, Meng F . Basal-HER2 phenotype shows poorer survival than basal-like phenotype in hormone receptor-negative invasive breast cancers. Hum Pathol. 2007; 39(2):167-74. DOI: 10.1016/j.humpath.2007.06.012. View

14.

Cheang M, Voduc D, Bajdik C, Leung S, McKinney S, Chia S . Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype. Clin Cancer Res. 2008; 14(5):1368-76. DOI: 10.1158/1078-0432.CCR-07-1658. View

15.

Luck A, Evans A, J James J, Rakha E, Paish E, Green A . Breast carcinoma with basal phenotype: mammographic findings. AJR Am J Roentgenol. 2008; 191(2):346-51. DOI: 10.2214/AJR.07.2659. View

16.

Sotiriou C, Pusztai L . Gene-expression signatures in breast cancer. N Engl J Med. 2009; 360(8):790-800. DOI: 10.1056/NEJMra0801289. View

17.

Choi Y, Oh E, Park S, Kim Y, Park Y, Song K . Triple-negative, basal-like, and quintuple-negative breast cancers: better prediction model for survival. BMC Cancer. 2010; 10:507. PMC: 2957395. DOI: 10.1186/1471-2407-10-507. View

18.

Tot T, Pekar G . Multifocality in "basal-like" breast carcinomas and its influence on lymph node status. Ann Surg Oncol. 2010; 18(6):1671-7. DOI: 10.1245/s10434-010-1480-7. View

19.

Tot T, Gere M, Pekar G, Tarjan M, Hofmeyer S, Hellberg D . Breast cancer multifocality, disease extent, and survival. Hum Pathol. 2011; 42(11):1761-9. DOI: 10.1016/j.humpath.2011.02.002. View

20.

Bennett R, Evans A, Kutt E, Record C, Bobrow L, Ellis I . Pathological and mammographic prognostic factors for screen detected cancers in a multi-centre randomised, controlled trial of mammographic screening in women from age 40 to 48 years. Breast. 2011; 20(6):525-8. DOI: 10.1016/j.breast.2011.05.008. View