PMID- 31340938
OWN - NLM
STAT- MEDLINE
DCOM- 20200908
LR  - 20210816
IS  - 1557-3265 (Electronic)
IS  - 1078-0432 (Linking)
VI  - 25
IP  - 21
DP  - 2019 Nov 1
TI  - Prediction of Lymph Node Metastasis in Breast Cancer by Gene Expression and 
      Clinicopathological Models: Development and Validation within a Population-Based 
      Cohort.
PG  - 6368-6381
LID - 10.1158/1078-0432.CCR-19-0075 [doi]
AB  - PURPOSE: More than 70% of patients with breast cancer present with node-negative 
      disease, yet all undergo surgical axillary staging. We aimed to define predictors 
      of nodal metastasis using clinicopathological characteristics (CLINICAL), gene 
      expression data (GEX), and mixed features (MIXED) and to identify patients at low 
      risk of metastasis who might be spared sentinel lymph node biopsy 
      (SLNB).Experimental Design: Breast tumors (n = 3,023) from the population-based 
      Sweden Cancerome Analysis Network-Breast initiative were profiled by RNA 
      sequencing and linked to clinicopathologic characteristics. Seven 
      machine-learning models present the discriminative ability of N0/N+ in 
      development (n = 2,278) and independent validation cohorts (n = 745) stratified 
      as ER(+)HER2(-), HER2(+), and TNBC. Possible SLNB reduction rates are proposed by 
      applying CLINICAL and MIXED predictors. RESULTS: In the validation cohort, the 
      MIXED predictor showed the highest area under ROC curves to assess nodal 
      metastasis; AUC = 0.72. For the subgroups, the AUCs for MIXED, CLINICAL, and GEX 
      predictors ranged from 0.66 to 0.72, 0.65 to 0.73, and 0.58 to 0.67, 
      respectively. Enriched proliferation metagene and luminal B features were noticed 
      in node-positive ER(+)HER2(-) and HER2(+) tumors, while upregulated basal-like 
      features were observed in node-negative TNBC tumors. The SLNB reduction rates in 
      patients with ER(+)HER2(-) tumors were 6% to 7% higher for the MIXED predictor 
      compared with the CLINICAL predictor accepting false negative rates of 5% to 10%. 
      CONCLUSIONS: Although CLINICAL and MIXED predictors of nodal metastasis had 
      comparable accuracy, the MIXED predictor identified more node-negative patients. 
      This translational approach holds promise for development of classifiers to 
      reduce the rates of SLNB for patients at low risk of nodal involvement.
CI  - (c)2019 American Association for Cancer Research.
FAU - Dihge, Looket
AU  - Dihge L
AD  - Department of Clinical Sciences Lund, Division of Surgery, Lund University, Lund, 
      Sweden. looket.dihge@med.lu.se.
AD  - Department of Plastic and Reconstructive Surgery, Skane University Hospital, 
      Malmo, Sweden.
FAU - Vallon-Christersson, Johan
AU  - Vallon-Christersson J
AUID- ORCID: 0000-0002-2195-0385
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Hegardt, Cecilia
AU  - Hegardt C
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Saal, Lao H
AU  - Saal LH
AUID- ORCID: 0000-0002-0815-1896
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Hakkinen, Jari
AU  - Hakkinen J
AUID- ORCID: 0000-0002-8466-9179
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Larsson, Christer
AU  - Larsson C
AD  - Department of Laboratory Medicine, Division of Translational Cancer Research, 
      Lund University, Lund, Sweden.
FAU - Ehinger, Anna
AU  - Ehinger A
AUID- ORCID: 0000-0001-9225-7396
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Loman, Niklas
AU  - Loman N
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
AD  - Department of Oncology, Skane University Hospital, Lund, Sweden.
FAU - Malmberg, Martin
AU  - Malmberg M
AD  - Department of Oncology, Skane University Hospital, Lund, Sweden.
FAU - Bendahl, Par-Ola
AU  - Bendahl PO
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Borg, Ake
AU  - Borg A
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Staaf, Johan
AU  - Staaf J
AUID- ORCID: 0000-0001-5254-5115
AD  - Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund 
      University, Lund, Sweden.
FAU - Ryden, Lisa
AU  - Ryden L
AUID- ORCID: 0000-0001-7515-3130
AD  - Department of Clinical Sciences Lund, Division of Surgery, Lund University, Lund, 
      Sweden.
AD  - Department of Surgery, Skane University Hospital, Lund, Sweden.
LA  - eng
PT  - Clinical Trial
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20190724
PL  - United States
TA  - Clin Cancer Res
JT  - Clinical cancer research : an official journal of the American Association for 
      Cancer Research
JID - 9502500
RN  - 0 (Biomarkers, Tumor)
RN  - 0 (ESR1 protein, human)
RN  - 0 (Estrogen Receptor alpha)
RN  - 0 (Neoplasm Proteins)
RN  - EC 2.7.10.1 (ERBB2 protein, human)
RN  - EC 2.7.10.1 (Receptor, ErbB-2)
SB  - IM
MH  - Adult
MH  - Aged
MH  - Biomarkers, Tumor/genetics
MH  - Breast Neoplasms/classification/*diagnosis/genetics/pathology
MH  - Disease-Free Survival
MH  - Estrogen Receptor alpha/genetics
MH  - Female
MH  - Gene Expression Regulation, Neoplastic/genetics
MH  - Humans
MH  - Lymph Node Excision/methods
MH  - Lymphatic Metastasis/*diagnosis/genetics/pathology
MH  - Machine Learning
MH  - Middle Aged
MH  - Neoplasm Proteins/*genetics
MH  - Receptor, ErbB-2/genetics
MH  - Sentinel Lymph Node/metabolism/pathology
MH  - Sentinel Lymph Node Biopsy
MH  - Sequence Analysis, RNA
MH  - Sweden/epidemiology
MH  - Triple Negative Breast Neoplasms/classification/*diagnosis/genetics/pathology
EDAT- 2019/07/26 06:00
MHDA- 2020/09/09 06:00
CRDT- 2019/07/26 06:00
PHST- 2019/01/10 00:00 [received]
PHST- 2019/05/24 00:00 [revised]
PHST- 2019/07/22 00:00 [accepted]
PHST- 2019/07/26 06:00 [pubmed]
PHST- 2020/09/09 06:00 [medline]
PHST- 2019/07/26 06:00 [entrez]
AID - 1078-0432.CCR-19-0075 [pii]
AID - 10.1158/1078-0432.CCR-19-0075 [doi]
PST - ppublish
SO  - Clin Cancer Res. 2019 Nov 1;25(21):6368-6381. doi: 10.1158/1078-0432.CCR-19-0075. 
      Epub 2019 Jul 24.