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European Journal of Nuclear Medicine and Molecular Imaging

Published in:

01-09-2013 | Original Article

Molecular subtypes of breast cancer: metabolic correlation with ¹⁸F-FDG PET/CT

Authors: Ana María García Vicente, Ángel Soriano Castrejón, Alberto León Martín, Ignacio Chacón López-Muñiz, Vicente Muñoz Madero, María del Mar Muñoz Sánchez, Azahara Palomar Muñoz, Ruth Espinosa Aunión, Ana González Ageitos

Published in: European Journal of Nuclear Medicine and Molecular Imaging | Issue 9/2013

Abstract

Purpose

To determine whether the metabolic features of breast tumours differ among molecular subtypes.

Methods

This prospective study included 168 women diagnosed with locally advanced breast cancer. PET/CT was requested in the initial staging before neoadjuvant treatment (multicentre study, FISCAM grant). All patients underwent an ¹⁸F-FDG PET/CT scan with a dual time-point acquisition. Both examinations (PET-1 and PET-2) were evaluated qualitatively and semiquantitatively with calculation of SUVmax (SUV-1 and SUV-2, respectively), and the percentage variation in the SUVs and retention indexes (RI) between PET-1 and PET-2 in the breast tumour were calculated. Biological prognostic parameters, including the steroid receptor status, HER-2 expression, proliferation rate (Ki-67) and grading, were determined from primary tumour tissue. Tumour subtypes were classified following the recommendations of the 12th International Breast Conference, by immunohistochemical surrogates as luminal A, luminal B-HER2(−), luminal B-HER2(+), HER2(+) or basal. Metabolic semiquantitative parameters and molecular subtypes were correlated.

Results

Of the 168 tumours, 151 were classified: 16 were luminal A, 53 were luminal B-HER2(−), 29 were luminal B-HER2(+), 18 were HER2(+) and 35 were basal. There were significant differences between SUV-1 and SUV-2 and the different subtypes, with higher SUVs in HER2(+) and basal tumours. No significant differences were found with respect to RI.

Conclusion

Semiquantitative metabolic parameters showed statistically significant differences among the molecular subtypes of the tumours evaluated. Therefore, there seems to be a relationship between molecular and glycolytic phenotypes.

Prat A, Perou CM. Deconstructing the molecular portraits of breast cancer. Mol Oncol. 2011;5:5–23.PubMedCrossRef

Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27:1160–7.PubMedCrossRefPubMedCentral

Blows FM, Driver KE, Schmidt MK, Broeks A, van Leeuwen FE, Wesseling J, et al. Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med. 2010;7:e1000279.PubMedCrossRefPubMedCentral

Cheang MC, Chia SK, Voduc D, Gao D, Leung S, Snider J, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst. 2009;101:736–50.PubMedCrossRefPubMedCentral

Tang G, Shak S, Paik S, Anderson SJ, Costantino JP, Geyer Jr CE, et al. Comparison of the prognostic and predictive utilities of the 21-gene recurrence score assay and Adjuvant! for women with node-negative, ER-positive breast cancer: results from NSABP B-14 and NSABP B-20. Breast Cancer Res Treat. 2011;127:133–42.PubMedCrossRef

Ueda S, Tsuda H, Asakawa H, Shigekawa T, Fukatsu K, Kondo N, et al. Clinicopathological and prognostic relevance of uptake level using 18F-fluorodeoxyglucose positron emission tomography/computed tomography fusion imaging (18F-FDG PET/CT) in primary breast cancer. Jpn J Clin Oncol. 2008;38:250–8.PubMedCrossRef

Zytoon AA, Murakami K, El-Kholy MR, El-Shorbagy E. Dual time point FDG-PET/CT imaging. Potential tool for diagnosis of breast cancer. Clin Radiol. 2008;63:1213–27.PubMedCrossRef

Mavi A, Urhan M, Yu JQ, Zhuang H, Houseni M, Cermik TF, et al. Dual time point 18F-FDG PET imaging detects breast cancer with high sensitivity and correlates well with histologic subtypes. J Nucl Med. 2006;47:1440–6.PubMed

Zytoon AA, Murakami K, El-Kholy MR, El-Shorbagy E, Ebied O. Breast cancer with low FDG uptake: characterization by means of dual-time point FDG-PET/CT. Eur J Radiol. 2009;70:530–8.PubMedCrossRef

10.

Gil-Rendo A, Martínez-Regueira F, Zornoza G, García-Velloso MJ, Beorlegui C, Rodriguez-Spiteri N. Association between [18F]fluorodeoxyglucose uptake and prognostic parameters in breast cancer. Br J Surg. 2009;96:166–70.PubMedCrossRef

11.

Buck A, Schirrmeister H, Kühn T, Shen C, Kalker T, Kotzerke J, et al. FDG uptake in breast cancer: correlation with biological and clinical prognostic parameters. Eur J Nucl Med. 2002;29:1317–23.CrossRef

12.

Avril N, Menzel M, Dose J, Schelling M, Weber W, Jänicke F, et al. Glucose metabolism of breast cancer assessed by 18F-FDG PET: histologic and immunohistochemical tissue analysis. J Nucl Med. 2001;42:9–16.PubMed

13.

Basu S, Chen W, Tchou J, Mavi A, Cermik T, Czerniecki B, et al. Comparison of triple-negative and estrogen receptor-positive/progesterone receptor-positive/HER2-negative breast carcinoma using quantitative fluorine-18 fluorodeoxyglucose/positron emission tomography imaging parameters: a potentially useful method for disease characterization. Cancer. 2008;112:995–1000.PubMedCrossRef

14.

Shimoda W, Hayashi M, Murakami K, Oyama T, Sunagawa M. The relationship between FDG uptake in PET scans and biological behavior in breast cancer. Breast Cancer. 2007;14:260–8.PubMedCrossRef

15.

García Vicente A, Soriano Castrejón A, Relea Calatayud F, Muñoz Madero V, Molina Garrido MJ, León Martín AA, et al. 18F-FDG semi-quantitative parameters and biological prognostic factors in locally advanced breast cancer. Rev Esp Med Nucl. 2012;31:308–14.

16.

Groheux D, Giacchetti S, Moretti JL, Porcher R, Espié M, Lehmann-Che J, et al. Correlation of high 18F-FDG uptake to clinical, pathological and biological prognostic factors in breast cancer. Eur J Nucl Med Mol Imaging. 2011;38:426–35.PubMedCrossRef

17.

Heudel P, Cimarelli S, Montella A, Bouteille C, Mognetti T. Value of PET-FDG in primary breast cancer based on histopathological a immunohistochemical prognostic factors. Int J Clin Oncol. 2010;15:588–93.PubMedCrossRef

18.

García JR, Rodríguez A, Cabrera A. Tomografía por emisión de positrones de cuerpo completo (PET/TAC) con 18F-fluorodesoxiglucosa. Rev Esp Med Nucl. 2009;28:85–9.CrossRef

19.

American Joint Committee on Cancer (AJCC) 7th edition. http://www.cancerstaging.org/staging/index.html.

20.

Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thürlimann B, Senn HJ, et al. Strategies for subtypes – dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol. 2011;22:1736–47.PubMedCrossRefPubMedCentral

21.

Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–52.PubMedCrossRef

22.

Vander Heiden MG, Plas DR, Rathmell JC, Fox CJ, Harris MH, Thompson CB. Growth factors can influence cell growth and survival through effects on glucose metabolism. Mol Cell Biol. 2001;21:5899–912.PubMedCrossRefPubMedCentral

23.

Bertucci F, Finetti P, Birnbaum D. Basal breast cancer: a complex and deadly molecular subtype. Curr Molec Med. 2012;12:96–110.CrossRef

24.

Wiechmann L, Sampson M, Stempel M, Jacks LM, Patil SM, King T, et al. Presenting features of breast cancer differ by molecular subtype. Ann Surg Oncol. 2009;16:2705–10.PubMedCrossRef

25.

Zhou W, He Z, Xue J, Wang M, Zha X, Ling L, Chen L, et al. Molecular subtype classification is a determinant of non-sentinel lymph node metastasis in breast cancer patients with positive sentinel lymph nodes. PLoS One. 2012;7:e35881. doi:10.1371/journal.pone.0035881.PubMedCrossRefPubMedCentral

26.

Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A. 2003;100:8418–23.PubMedCrossRefPubMedCentral

27.

Vargo JA, Beriwal S, Ahrendt GM, Soran A, Johnson RR, McGuire K, et al. Molecular class as a predictor of locoregional and distant recurrence in the neoadjuvant setting for breast cancer. Oncology. 2011;80:341–9.PubMedCrossRef

28.

Brenton JD, Carey LA, Ahmed AA, Caldas C. Molecular classification and molecular forecasting of breast cancer: ready for clinical application? J Clin Oncol. 2005;23:7350–60.PubMedCrossRef

29.

Ikenaga N, Otomo N, Toyofuku A, Ueda Y, Toyoda K, Hayashi T, et al. Standardized uptake values for breast carcinomas assessed by fluorodeoxyglucose-positron emission tomography correlate with prognostic factors. Am Surg. 2007;73:1151–7.PubMed

30.

Mavi A, Cermik TF, Urhan M, Puskulcu H, Basu S, Yu JQ, et al. The effects of estrogen, progesterone, and C-erbB-2 receptor states on 18F-FDG uptake of primary breast cancer lesions. J Nucl Med. 2007;48:1266–72.PubMedCrossRef

31.

Osborne JR, Port E, Gonen M, Doane A, Yeung H, Gerald W, et al. 18F-FDG PET of locally invasive breast cancer and association of estrogen receptor status with standardized uptake value: microarray and immunohistochemical analysis. J Nucl Med. 2010;51:543–50.PubMedCrossRef

32.

Kumar R, Loving VA, Chauhan A, Zhuang H, Mitchell S, Alavi A. Potential of dual-time-point imaging to improve breast cancer diagnosis with 18F-FDG PET. J Nucl Med. 2005;46:1819–24.PubMed

33.

García Vicente AM, Soriano Castrejón A, Relea Calatayud F, Muñoz AP, León Martín AA, López-Muñiz IC, et al. 18F-FDG retention index and biologic prognostic parameters in breast cancer. Clin Nucl Med. 2012;37:460–6.PubMedCrossRef

34.

Crippa F, Agresti R, Seregni E, Greco M, Pascali C, Bogni A, et al. Prospective evaluation of fluorine-18-FDG PET in presurgical staging of the axilla in breast cancer. J Nucl Med. 1998;39:4–8.PubMed

35.

Reyal F, Rouzier R, Depont-Hazelzet B, Bollet MA, Pierga JY, Alran S, et al. The molecular subtype classification is a determinant of sentinel node positivity in early breast carcinoma. PLoS One. 2011;6:e20297.PubMedCrossRefPubMedCentral

36.

Yin WJ, Lu JS, Di GH, Lin YP, Zhou LH, Liu GY, et al. Clinicopathological features of the triple-negative tumors in Chinese breast cancer patients. Breast Cancer Res Treat. 2009;115:325–33.PubMedCrossRef

37.

Crabb SJ, Cheang MC, Leung S, Immonen T, Nielsen TO, Huntsman DD, et al. Basal breast cancer molecular subtype predicts for lower incidence of axillary lymph node metastases in primary breast cancer. Clin Breast Cancer. 2008;8:249–56.PubMedCrossRef

38.

Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA. 2006;295:2492–502.PubMedCrossRef

39.

Viale G. Integrating molecular profiling, histological type and other variables: defining the fingerprint of responsiveness to treatment. Breast. 2009;18:S32–6.PubMedCrossRef

Title: Molecular subtypes of breast cancer: metabolic correlation with 18F-FDG PET/CT
Authors: Ana María García Vicente
Ángel Soriano Castrejón
Alberto León Martín
Ignacio Chacón López-Muñiz
Vicente Muñoz Madero
María del Mar Muñoz Sánchez
Azahara Palomar Muñoz
Ruth Espinosa Aunión
Ana González Ageitos
Publication date: 01-09-2013
Publisher: Springer Berlin Heidelberg
Published in: European Journal of Nuclear Medicine and Molecular Imaging / Issue 9/2013
Print ISSN: 1619-7070
Electronic ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-013-2418-7

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Molecular subtypes of breast cancer: metabolic correlation with ¹⁸F-FDG PET/CT

Abstract

Purpose

Methods

Results

Conclusion

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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