Clustering subtypes of breast cancer by combining immunohistochemistry profiles and metabolism characteristics measured using FDG PET/CT

Abstract

Background The aim of this study was to investigate the effect of combining immunohistochemical profiles and metabolic information to characterize breast cancer subtypes. Methods This retrospective study included 289 breast tumors from 284 patients who underwent preoperative 18 F-fluorodeoxyglucose (FDG) positron emission tomography/ computed tomography (PET/CT). Molecular subtypes of breast cancer were classified as Hormonal, HER2, Dual (a combination of both Hormonal and HER2 features), and triple-negative (TN). Histopathologic findings and immunohistochemical results for Ki-67, EGFR, CK 5/6, and p53 were also analyzed. The maximum standardized uptake value (SUV) measured from FDG PET/CT was used to evaluate tumoral glucose metabolism. Results Overall, 182, 24, 47, and 36 tumors were classified as Hormonal, HER2, Dual, and TN subtypes, respectively. Molecular profiles of tumor aggressiveness and the tumor SUV revealed a gradual increase from the Hormonal to the TN type. The tumor SUV was significantly correlated with tumor size, expression levels of p53, Ki-67, and EGFR, and nuclear grade (all p < 0.001). In contrast, the tumor SUV was negatively correlated with the expression of estrogen receptors (r = − 0.234, p < 0.001) and progesterone receptors (r = − 0.220, p < 0.001). Multiple linear regression analysis revealed that histopathologic markers explained tumor glucose metabolism (adjusted R-squared value 0.238, p < 0.001). Tumor metabolism can thus help define breast cancer subtypes with aggressive/adverse prognostic features. Conclusions Metabolic activity measured using FDG PET/CT was significantly correlated with the molecular alteration profiles of breast cancer assessed using immunohistochemical analysis. Combining molecular markers and metabolic information may aid in the recognition and understanding of tumor aggressiveness in breast cancer and be helpful as a prognostic marker.

18F-FDG Micro PET/CT imaging to evaluate the effect of BRCA1 knockdown on MDA-MB231 breast cancer cell radiosensitivity

“…The expression of HIF-1α, Glut-1 and Ki-67 correlated significantly with the 18 F-FDG uptake, which agreed with the findings of Bravatà et al. [42] , [43] , [44] . Together, these results suggested that RT can largely inhibit the growth of tumor tissues with a radiosensitizing effect in BRCA1 knockdown group, and this change can be dynamically monitored and assessed by the 18 F-FDG PET/CT imaging.…”

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“…An improved PET/CT model has previously been reported; the model determined the optimal cutoff value of the pSUVmax for each molecular subtype ( 19 ). This may be biologically plausible since several reports have elucidated the association between HER2 oncogene expression and 18F-FDG uptake ( 21 ), and pSUVmax was negatively correlated with the ER and PR ( 22 ). In this study, the optimal cutoff value of pSUVmax for each subtype was established by applying the receiver-operating characteristic curve analysis (cutoff values: luminal A-like type, 4.6; luminal B-like type, 4.8; luminal-HER2 type, 5.9; pure HER2 type 13.5; and triple-negative type, 7.9).…”

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“…The authors found significantly higher SUV max values in the total population of TNBC patients and across subgroups by tumor size, grade, and stage, compared to the ERpositive/PR-positive/HER2-negative breast cancer group, suggesting increased tumor glycolysis may contribute to the aggressiveness of TNBC (70). Similarly, a retrospective study by Kwon et al studied pre-operative PET/CT scans of 284 newly diagnosed breast cancer patients (36 with TNBC) to correlate PET findings with histopathology, and found triple negative tumors to have significantly higher SUV values than other subtypes (71). Accordingly, in a prior prospective study by Garcia Vicente et al in 168 patients, SUV values in PET/CT scans obtained before neoadjuvant treatment correlated with molecular breast cancer subtype, with significantly higher SUV measures seen in HER2positive tumors and in the basal-like subtype, which is mostly comprised of TNBC (72).…”

“…Similarly, a retrospective study by Kwon et al. studied pre-operative PET/CT scans of 284 newly diagnosed breast cancer patients (36 with TNBC) to correlate PET findings with histopathology, and found triple negative tumors to have significantly higher SUV values than other subtypes ( 71 ). Accordingly, in a prior prospective study by Garcia Vicente et al.…”