Presence of bone marrow micrometastasis (BMM) in breast cancer patients predicts a poor-prognosis pattern of first distant metastasis: Results from the pooled analysis

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 567-567
Author(s):  
S. Braun ◽  
F. D. Vogl ◽  
K. Pantel

567 Background: As a putative surrogate marker of ubiquitous distant metastasis, which is assessable both at initial diagnosis of breast cancer and during adjuvant therapy, BMM would be a valuable end-point marker for adjuvant clinical trials. Methods: Based on individual pt data of 4,686 breast cancer pts with a 10-year follow-up (median, 62 months), we analyzed distant disease-free survival (DDFS) of BMM+/BMM− pts, and looked specifically into sites of first metastatic relapse, expressed as bone metastasis-free (BFS), visceral metastasis-free (VFS), and multiple metastasis-free survival (MFS; i.e., simultaneous diagnosis of bone and visceral metastases). We performed Kaplan-Meier analysis and computed incidence rates (IR)/ incidence rate ratios (IRR) for the occurrence of metastasis at different sites. Results: BMM were detected in 1,432 (30.6%) of pts overall and significantly more often in pts with subsequent diagnosis of distant metastasis as compared to those who survived without metastases (48.5% vs. 26.0%, P<0.001). BMM+ pts had a significantly shorter DDFS than BMM- pts (IRR 2.36; 95%CI, 2.07–2.69; P<0.001). This was also true when we analyzed either bone (IRR 2.73; 95%CI, 2.27–3.29; P<0.001) or visceral metastases only (IRR, 2.48; 95%CI, 2.11–2.91; P<0.001). Among 952 pts with occurrence of distant metastasis, IR of such an event was 1.28-fold (95%CI, 1.12–1.46; P<0.001) higher in BMM+ pts than in BMM- pts. Among 462 BMM+ pts (but not among those 490 BMM- pts), IRs for MFS were significantly increased as compared to both VFS (IRR 1.72; 95%CI, 1.36–2.18; P<0.001) and BFS (IRR 1.85; 95%CI 1.21–2.06; P=0.001). IR for BFS of BMM+ patients (1.08; 95%CI 0.87–1.34) was not significantly increased over VFS. Conclusion: Our data provide conclusive evidence that presence of BMM predicts an early onset and a poor prognosis pattern of overt distant metastasis. With the similar likelihood of the occurrence of subsequent metastasis in bone and at visceral sites, BMM appears to be a marker of generalized tumor cell spread. No significant financial relationships to disclose.

2019 ◽  
Vol 39 (4) ◽  
Author(s):  
Wei-xian Chen ◽  
Liang-gen Yang ◽  
Ling-yun Xu ◽  
Lin Cheng ◽  
Qi Qian ◽  
...  

Abstract Background: Ribonucleotide reductase M2 subunit (RRM2) plays vital roles in many cellular processes such as cell proliferation, invasiveness, migration, angiogenesis, senescence, and tumorigenesis. However, the prognostic significance of RRM2 gene in breast cancer remains to be investigated. Methods:RRM2 expression was initially evaluated using the Oncomine database. The relevance between RRM2 level and clinical parameters as well as survival data in breast cancer was analyzed using the Kaplan–Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases. Results:RRM2 was overexpressed in different subtypes of breast cancer patients. Estrogen receptor (ER) and progesterone receptor (PR) were negatively correlated with RRM2 expression. Conversely, the Scarff–Bloom–Richardson (SBR) grade, Nottingham prognostic index (NPI), human epidermal growth factor receptor-2 (HER-2) status, nodal status, basal-like status, and triple-negative status were positively related to RRM2 level in breast cancer samples with respect to normal tissues. Patients with increased RRM2 showed worse overall survival, relapse-free survival, distant metastasis-free survival, disease-specific survival, and disease-free survival. RRM2 also exerted positive effect on metastatic relapse event. Besides, a positive correlation between RRM2 and KIF11 genes was confirmed. Conclusion: Bioinformatics analysis revealed that RRM2 might be used as a predictive biomarker for prognosis of breast cancer. Further studies are needed to more precisely elucidate the value of RRM2 in evaluating breast cancer prognosis.


2018 ◽  
Vol Volume 10 ◽  
pp. 329-335 ◽  
Author(s):  
Lakmini Mudduwa ◽  
Gaya Wijayaratne ◽  
Harshini Peiris ◽  
Shania N Gunasekera ◽  
Deepthika Abeysiriwardhana ◽  
...  

2006 ◽  
Vol 12 (22) ◽  
pp. 6696-6701 ◽  
Author(s):  
Patrizia Querzoli ◽  
Massimo Pedriali ◽  
Rosa Rinaldi ◽  
Anna Rita Lombardi ◽  
Elia Biganzoli ◽  
...  

2020 ◽  
Vol 33 (4) ◽  
pp. 137-144
Author(s):  
Guillermo Peralta-Castillo ◽  
Antonio Maffuz-Aziz ◽  
Mariana Sierra-Murguía ◽  
Sergio Rodriguez-Cuevas

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