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Poster Display session 2

5792 - A novel PET parameter for cancer stem cell metabolism: early prediction of chemosensitivity to neoadjuvant chemotherapy in locally advanced breast cancer

Date

29 Sep 2019

Session

Poster Display session 2

Topics

Tumour Site

Breast Cancer

Presenters

Chanwoo Kim

Citation

Annals of Oncology (2019) 30 (suppl_5): v99-v103. 10.1093/annonc/mdz241

Authors

C. Kim1, H.J. Choi2

Author affiliations

  • 1 Nuclear Medicine, Kyung Hee University Hospital at Gangdong, 05278 - Seoul/KR
  • 2 Nuclear Medicine, Hanyang University Medical Center, 04736 - Seoul/KR

Resources

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Abstract 5792

Background

Early predicting the pathologic complete response (pCR) after neoadjuvant chemotherapy in patients with locally advanced breast cancer (LABC) is closely associated with clinical outcomes. However, conventional metabolic parameters using baseline 18F-FDG PET/CT have failed to accurately predict the pCR. Breast cancer stem cells (CSCs) are known for their established role in chemoresistance. We designed a new PET parameter for CSC metabolism (MTVcsc) from pretreatment 18F-FDG PET/CT by using distinctive glucose metabolism between CSCs and differentiated cancer cells, and aimed to evaluate the prognostic value of the MTVcsc.

Methods

A total of 71 patients with LABC who underwent initial 18F-FDG PET/CT before NAC were included in this study. The SUV values of single voxels within the primary tumor were clustered by performing k-means clustering using R version 3.5.3 and MTVcsc was derived by calculating the volume of the most glycolytic cluster. The predictive values of the MTVcsc, as well as clinicopathologic and conventional metabolic parameters (SUVmax, MTV, TLG) for pCR, were analyzed by multivariable logistic regression.

Results

Seventeen patients were excluded from the final analysis due to small tumor size (< 64 voxels). The lower MTVcsc and non-luminal subtypes were significantly associated with achieving pCR following NAC (Table). The MTVcsc outperformed the conventional PET parameters in predicting pCR. Table Univariable and multivariable logistic regression model of clinicopathologic and metabolic parameters for predicting pathologic complete response.Table: 301P

ParametersUnivariable analysisMultivariable analysis
OR95% CIP valueOR95% CIP value
Ki-67
Low, < 20% High, ≥ 20%1.00
5.571.06-29.270.043
Molecular subtype
Luminal A and B HER2 positive Triple negative1.001.00
11.462.07-63.360.00513.71.75-107.360.013
6.551.05-40.670.04417.421.41-215.040.026
Metabolic parameters
SUVmax Metabolic tumor volume (MTV) Total lesion glycolysis (TLG) MTVcsc0.980.83-1.160.814
0.980.94-1.020.281
0.990.98-1.000.231
0.290.10-0.890.0310.210.05-0.820.025

Conclusions

MTVcsc, a novel PET parameter for CSC metabolism, provides predictive value for pCR. By further stratifying LABC patients with a combination of MTVcsc and molecular subtype at initial staging workup, achieving pCR after NAC can be early predicted more accurately.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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