Metabolomic Profiling of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy for Predicting Disease-Free and Overall Survival

被引:2
作者
Talarico, Maria Cecilia Ramiro [1 ]
Derchain, Sophie [1 ]
da Silva, Lucas Ferreira [2 ]
Sforca, Mauricio L. [3 ]
Rocco, Silvana A. [3 ]
Cardoso, Marcella R. [4 ,5 ]
Sarian, Luis Otavio [1 ]
机构
[1] UNICAMP Univ Estadual Campinas, Univ Campinas, Sch Med Sci, Dept Obstet & Gynecol,Div Gynecol & Breast Oncol, BR-13083881 Campinas, SP, Brazil
[2] Harvard Med Sch, Dept Pathol, Boston, MA 02115 USA
[3] Brazilian Ctr Res Energy & Mat CNPEM, Brazilian Biosci Natl Lab LNBio, BR-13083100 Campinas, SP, Brazil
[4] Harvard Med Sch, Massachusetts Gen Hosp, Div Gynecol Oncol, Div Gynecol Oncol, Boston, MA 02114 USA
[5] Massachusetts Gen Hosp, Ctr Global Hlth, Boston, MA 02114 USA
关键词
mammary cancer; neoadjuvant chemotherapy; NMR spectroscopy; metabolome; survival analysis; SERINE; APOPTOSIS; DIAGNOSIS; HALLMARKS; URINE;
D O I
10.3390/ijms25168639
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Breast cancer (BC) remains a significant global health concern, with neoadjuvant chemotherapy (NACT) offering preoperative benefits like tumor downstaging and treatment response assessment. However, identifying factors influencing post-NACT treatment response and survival outcomes is challenging. Metabolomic approaches offer promising insights into understanding these outcomes. This study analyzed the serum of 80 BC patients before and after NACT, followed for up to five years, correlating with disease-free survival (DFS) and overall survival (OS). Using untargeted nuclear magnetic resonance (NMR) spectroscopy and a novel statistical model that avoids collinearity issues, we identified metabolic changes associated with survival outcomes. Four metabolites (histidine, lactate, serine, and taurine) were significantly associated with DFS. We developed a metabolite-related survival score (MRSS) from these metabolites, stratifying patients into low- and high-risk relapse groups, independent of classical prognostic factors. High-risk patients had a hazard ratio (HR) for DFS of 3.42 (95% CI 1.51-7.74; p = 0.003) after adjustment for disease stage and age. A similar trend was observed for OS (HR of 3.34, 95% CI 1.64-6.80; p < 0.001). Multivariate Cox proportional hazards analysis confirmed the independent prognostic value of the MRSS. Our findings suggest the potential of metabolomic data, alongside traditional markers, in guiding personalized treatment decisions and risk stratification in BC patients undergoing NACT. This study provides a methodological framework for leveraging metabolomics in survival analyses.
引用
收藏
页数:16
相关论文
共 50 条
[1]  
[Anonymous], Team R Core R: A Language and Environment for Statistical Computing.
[2]   Early Detection of Recurrent Breast Cancer Using Metabolite Profiling [J].
Asiago, Vincent M. ;
Alvarado, Leiddy Z. ;
Shanaiah, Narasimhamurthy ;
Gowda, G. A. Nagana ;
Owusu-Sarfo, Kwadwo ;
Ballas, Robert A. ;
Raftery, Daniel .
CANCER RESEARCH, 2010, 70 (21) :8309-8318
[3]   Plasma amino acid profiles of breast cancer patients early in the trajectory of the disease differ from healthy comparison groups [J].
Barnes, Tyler ;
Bell, Kirsten ;
DiSebastiano, Katie M. ;
Vance, Vivienne ;
Hanning, Rhona ;
Russell, Caryl ;
Dubin, Joel A. ;
Bahl, Mala ;
Califaretti, Nadia ;
Campbell, Carolyn ;
Mourtzakis, Marina .
APPLIED PHYSIOLOGY NUTRITION AND METABOLISM, 2014, 39 (06) :740-744
[4]   Histidine Metabolism and Function [J].
Brosnan, Margaret E. ;
Brosnan, John T. .
JOURNAL OF NUTRITION, 2020, 150 :2570S-2575S
[5]   Prognostic value of metabolic response in breast cancer patients receiving neoadjuvant chemotherapy [J].
Cao, Maria D. ;
Giskeodegard, Guro F. ;
Bathen, Tone F. ;
Sitter, Beathe ;
Bofin, Anna ;
Lonning, Per E. ;
Lundgren, Steinar ;
Gribbestad, Ingrid S. .
BMC CANCER, 2012, 12
[6]   Metabolomics by NMR Combined with Machine Learning to Predict Neoadjuvant Chemotherapy Response for Breast Cancer [J].
Cardoso, Marcella R. ;
Silva, Alex Ap Rosini ;
Talarico, Maria Cecilia R. ;
Sanches, Pedro H. Godoy ;
Sforca, Mauricio L. ;
Rocco, Silvana A. ;
Rezende, Luciana M. ;
Quintero, Melissa ;
Costa, Tassia B. B. C. ;
Viana, Lais R. ;
Canevarolo, Rafael R. ;
Ferracini, Amanda C. ;
Ramalho, Susana ;
Gutierrez, Junier Marrero ;
Guimaraes, Fernando ;
Tasic, Ljubica ;
Tata, Alessandra ;
Sarian, Luis O. ;
Cheng, Leo L. ;
Porcari, Andreia M. ;
Derchain, Sophie F. M. .
CANCERS, 2022, 14 (20)
[7]   Roles of taurine in cognitive function of physiology, pathologies and toxication [J].
Chen, Chaoran ;
Xia, ShuFang ;
He, Jialiang ;
Lu, Guangli ;
Xie, Zhenxing ;
Han, Hongjie .
LIFE SCIENCES, 2019, 231
[8]   An integrated metabonomics study to reveal the inhibitory effect and metabolism regulation of taurine on breast cancer [J].
Chen, Wanting ;
Li, Qian ;
Hou, Ranran ;
Liang, Huaguo ;
Zhang, Yongli ;
Yang, Yongxia .
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, 2022, 214
[9]   HR-MAS MR Spectroscopy of Breast Cancer Tissue Obtained with Core Needle Biopsy: Correlation with Prognostic Factors [J].
Choi, Ji Soo ;
Baek, Hyeon-Man ;
Kim, Suhkmann ;
Kim, Min Jung ;
Youk, Ji Hyun ;
Moon, Hee Jung ;
Kim, Eun-Kyung ;
Han, Kyung Hwa ;
Kim, Dong-Hyun ;
Kim, Seung Il ;
Koo, Ja Seung .
PLOS ONE, 2012, 7 (12)
[10]   Metabolomics: an emerging but powerful tool for precision medicine [J].
Clish, Clary B. .
COLD SPRING HARBOR MOLECULAR CASE STUDIES, 2015, 1 (01)