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Predicting The Response To Neoadjuvant Therapy For Early-stage Breast Cancer: Tumor-, Blood-, And Imaging-related Biomarkers

Wenyong Tan, Ming Yang, H. Yang, Fangbin Zhou, W. Shen
Published 2018 · Medicine

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Neoadjuvant therapy (NAT) has been used increasingly in patients with locally advanced or early-stage breast cancer. However, the accurate evaluation and prediction of response to NAT remain the great challenge. Biomarkers could prove useful to identify responders or nonresponders, or even to distinguish between early and delayed responses. These biomarkers could include markers from the tumor itself, such as versatile proteins, genes, and ribonucleic acids, various biological factors or peripheral blood cells, and clinical and pathological features. Possible predictive markers could also include multiple features from functional imaging, such as standard uptake values in positron emission tomography, apparent diffusion coefficient in magnetic resonance, or radiomics imaging biomarkers. In addition, cells that indirectly present the immune status of tumor cells and/or their host could also potentially be used as biomarkers, eg, tumor-infiltrating lymphocytes, tumor-associated macrophages, and myeloid-derived suppressor cells. Though numerous biomarkers have been widely investigated, only estrogen and/or progesterone receptors and human epidermal growth factor receptor have been proven to be reliable biomarkers to predict the response to NAT. They are the only biomarkers recommended in several international guidelines. The other aforementioned biomarkers warrant further validation studies. Some multigene profiling assays that are commercially available, eg, Oncotype DX and MammaPrint, should be used with caution when extrapolated to NAT settings. A panel of combined multilevel biomarkers might be able to predict the response to NAT more robustly than individual biomarkers. To establish such a panel and its prediction model, reliable methods and extensive clinical validation are warranted.
This paper references
10.1016/j.ejrad.2017.06.019
Radiomic analysis of DCE-MRI for prediction of response to neoadjuvant chemotherapy in breast cancer patients.
Ming Fan (2017)
10.1016/S1470-2045(18)30111-6
Addition of the PARP inhibitor veliparib plus carboplatin or carboplatin alone to standard neoadjuvant chemotherapy in triple-negative breast cancer (BrighTNess): a randomised, phase 3 trial.
S. Loibl (2018)
10.1158/1078-0432.CCR-16-3206
NeoPalAna: Neoadjuvant Palbociclib, a Cyclin-Dependent Kinase 4/6 Inhibitor, and Anastrozole for Clinical Stage 2 or 3 Estrogen Receptor–Positive Breast Cancer
C. Ma (2017)
Tissue M. breast cancer risk, serial image analysis, and digital mammography. Part 1. Tissue and related risk factors
JJ Heine (2002)
Breast intervention and breast cancer treatment options.
O. Peart (2015)
10.1007/s13277-015-3944-7
Breast cancer circulating biomarkers: advantages, drawbacks, and new insights
Andrea Ravelli (2015)
10.1016/j.radonc.2015.11.016
Comparative analysis of the effects of radiotherapy versus radiotherapy after adjuvant chemotherapy on the composition of lymphocyte subpopulations in breast cancer patients.
E. Sage (2016)
10.1056/NEJMoa1510764
Prospective Validation of a 21-Gene Expression Assay in Breast Cancer.
J. Sparano (2015)
10.1038/bjc.2013.634
Tumour-infiltrating CD8+ lymphocytes as an independent predictive factor for pathological complete response to primary systemic therapy in breast cancer
A. Seo (2013)
10.3322/caac.21393
Breast Cancer—Major changes in the American Joint Committee on Cancer eighth edition cancer staging manual
A. Giuliano (2017)
10.1186/1471-2407-12-403
Analysis of and prognostic information from disseminated tumour cells in bone marrow in primary breast cancer: a prospective observational study
Anna-Karin Falck (2012)
10.1007/s00281-013-0367-7
Tumor-associated macrophages: functional diversity, clinical significance, and open questions
S. Biswas (2013)
10.1158/1078-0432.CCR-14-1622
Multiplexed Quantitative Analysis of CD3, CD8, and CD20 Predicts Response to Neoadjuvant Chemotherapy in Breast Cancer
Jason R. Brown (2014)
A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
J. (2002)
10.1016/j.amjsurg.2009.03.012
Accuracy of ultrasonography and mammography in predicting pathologic response after neoadjuvant chemotherapy for breast cancer.
J. Keune (2010)
10.1016/S1470-2045(17)30074-8
iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics.
L. Seymour (2017)
10.1371/journal.pone.0143308
Identifying Triple-Negative Breast Cancer Using Background Parenchymal Enhancement Heterogeneity on Dynamic Contrast-Enhanced MRI: A Pilot Radiomics Study
J. Wang (2015)
The cancer biomarker
CL Sawyers (2008)
breast cancer risk , serial image analysis , and digital mammography . Part 1 . Tissue and related risk factors
JJ Heine (2002)
10.7314/APJCP.2014.15.4.1685
Relationship between preoperative serum CA 15-3 and CEA levels and clinicopathological parameters in breast cancer.
Neda Moazzezy (2014)
10.17352/2455-8591.000007
Endothelial Progenitor Cells in Breast Cancer.
M. Botelho (2016)
10.1186/s12967-016-1025-3
Decoding the usefulness of non-coding RNAs as breast cancer markers
M. Amorim (2016)
10.1007/s00262-008-0523-4
Increased circulating myeloid-derived suppressor cells correlate with clinical cancer stage, metastatic tumor burden, and doxorubicin–cyclophosphamide chemotherapy
C. Diaz-Montero (2008)
Cancer statistics in China
W Chen (2015)
10.7314/APJCP.2012.13.3.857
Relationships among serum CA15-3 tumor marker, TNM staging, and estrogen and progesterone receptor expression in benign and malignant breast lesions.
M. Atoum (2012)
10.7314/APJCP.2014.15.23.10277
Correlation between Ki67 and histological grade in breast cancer patients treated with preoperative chemotherapy.
Militza Petric (2014)
10.1056/NEJMOA040766
Circulating tumor cells, disease progression, and survival in metastatic breast cancer.
M. Cristofanilli (2004)
10.7150/ntno.22419
A dual biomarker detection platform for quantitating circulating tumor DNA (ctDNA)
Chunyan Cai (2018)
10.1245/s10434-015-4404-8
Pathological Complete Response in Neoadjuvant Treatment of Breast Cancer
P. Cortázar (2015)
10.3233/CBM-2009-0119
Prognostic significance of serum Her2/neu, BCL2, CA15-3 and CEA in breast cancer patients: a short follow-up.
N. Samy (2010)
10.1007/s10147-013-0570-5
Orally administered S-1 suppresses circulating endothelial cell counts in metastatic breast cancer patients
W. Tsuji (2013)
Tumor-Infiltrating Lymphocytes and Associations With Pathological Complete Response and EventFree Survival in HER2-Positive Early-Stage Breast Cancer Treated With Lapatinib and Trastuzumab
R Salgado (2015)
10.1007/s00262-017-2038-3
Circulating myeloid-derived suppressor cells increase in patients undergoing neo-adjuvant chemotherapy for breast cancer
R. Wesolowski (2017)
10.1158/1078-0432.CCR-10-0468
Reproducibility of [11C]Choline-Positron Emission Tomography and Effect of Trastuzumab
L. Kenny (2010)
10.1097/CJI.0b013e3181d32e74
Cancer and Inflammation: Promise for Biologic Therapy
S. Demaria (2010)
10.1002/jmri.25870
Background, current role, and potential applications of radiogenomics
K. Pinker (2018)
10.1097/MNM.0b013e328313b7bc
Preliminary study of carbon-11 methionine PET in the evaluation of early response to therapy in advanced breast cancer
P. Lindholm (2009)
10.1093/jnci/djs528
Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy.
M. L. Marinovich (2013)
10.1093/annonc/mdm507
Prognosis of women with stage IV breast cancer depends on detection of circulating tumor cells rather than disseminated tumor cells.
F. Bidard (2008)
10.1038/nrclinonc.2017.141
Radiomics: the bridge between medical imaging and personalized medicine
P. Lambin (2017)
Accuracy of mammography, digital breast tomosynthesis, ultrasound and MR imaging in preoperative assessment of breast cancer.
G. Mariscotti (2014)
10.1038/nrclinonc.2015.215
Clinical relevance of host immunity in breast cancer: from TILs to the clinic
P. Savas (2016)
MR Imaging Radiomics
ES Burnside
Mamounas E. Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy
N Houssami (2012)
10.1093/ANNONC/MDM538
Preoperative CA 15-3 and CEA serum levels as predictor for breast cancer outcomes.
B. Park (2008)
10.18632/oncotarget.15736
Prognostic significance of tumor-associated macrophages in breast cancer: a meta-analysis of the literature
X. Zhao (2017)
10.1002/cncr.26202
Disseminated tumor cells predict survival after neoadjuvant therapy in primary breast cancer
C. Hall (2012)
10.1007/978-3-319-67577-0_8
Targeting Myeloid-Derived Suppressor Cells in Cancer.
W. Anani (2017)
10.1245/s10434-012-2814-4
Prognostic Value of Disseminated Tumor Cells in the Bone Marrow of Patients with Operable Primary Breast Cancer: A Long-term Follow-up Study
C. Domschke (2012)
10.1093/annonc/mdv221
Tailoring therapies—improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015
A. Coates (2015)
10.1007/s13244-013-0219-y
The role of magnetic resonance imaging in assessing residual disease and pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy: a systematic review
M. Lobbes (2013)
10.1016/j.ejca.2012.05.023
Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy.
Nehmat Houssami (2012)
10.1016/j.mric.2013.04.007
Diffusion weighted magnetic resonance imaging of the breast: protocol optimization, interpretation, and clinical applications.
S. Partridge (2013)
10.1038/srep13855
Monocyte-derived macrophage assisted breast cancer cell invasion as a personalized, predictive metric to score metastatic risk
Keon-Young Park (2015)
10.1007/s00262-017-1977-z
Myeloid cells in circulation and tumor microenvironment of breast cancer patients
S. M. Toor (2017)
10.1111/j.1538-7836.2006.01794.x
Isolation and enumeration of circulating endothelial cells by immunomagnetic isolation: proposal of a definition and a consensus protocol
A. Woywodt (2006)
10.2214/AJR.17.18708
Biomarkers and Imaging of Breast Cancer.
Olena Weaver (2018)
10.1200/JCO.2006.08.2271
Residual ductal carcinoma in situ in patients with complete eradication of invasive breast cancer after neoadjuvant chemotherapy does not adversely affect patient outcome.
C. Mazouni (2007)
for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint , Oncotype DX , and PAM 50 Gene Assays
K Pinker (2016)
10.4048/jbc.2017.20.2.119
Recent Advances in the Neoadjuvant Treatment of Breast Cancer
G. Rubovszky (2017)
10.1038/s41598-017-01524-7
Metabolic Radiomics for Pretreatment 18F-FDG PET/CT to Characterize Locally Advanced Breast Cancer: Histopathologic Characteristics, Response to Neoadjuvant Chemotherapy, and Prognosis
Seunggyun Ha (2017)
10.1186/s13058-015-0645-5
Circulating DNA as biomarker in breast cancer
H. Schwarzenbach (2015)
10.1097/01.sla.0000197714.14318.6f
Accuracy of Physical Examination, Ultrasonography, and Mammography in Predicting Residual Pathologic Tumor Size in Patients Treated With Neoadjuvant Chemotherapy
A. Chagpar (2006)
10.12659/MSM.896563
Assessing Clinical Significance of Serum CA15-3 and Carcinoembryonic Antigen (CEA) Levels in Breast Cancer Patients: A Meta-Analysis
Yijie Fu (2016)
10.1056/NEJMoa1602253
70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer.
F. Cardoso (2016)
10.1038/bjc.2015.206
miR-30e* is an independent subtype-specific prognostic marker in breast cancer
F. D’Aiuto (2015)
10.1158/1078-0432.CCR-11-0926
A New Molecular Predictor of Distant Recurrence in ER-Positive, HER2-Negative Breast Cancer Adds Independent Information to Conventional Clinical Risk Factors
M. Filipits (2011)
10.1002/jmri.25279
Intratumor partitioning and texture analysis of dynamic contrast‐enhanced (DCE)‐MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy
J. Wu (2016)
10.1038/nrclinonc.2016.144
Circulating and disseminated tumour cells — mechanisms of immune surveillance and escape
M. Mohme (2017)
10.1007/s10549-014-3192-3
Pathological non-response to chemotherapy in a neoadjuvant setting of breast cancer: an inter-institutional study
D. Balmativola (2014)
10.1007/s10549-014-3072-x
Assessing response in breast cancer with dynamic contrast-enhanced magnetic resonance imaging: Are signal intensity–time curves adequate?
D. Woolf (2014)
update of recommendations for the use of tumor markers in breast cancer
L Harris
10.1054/bjoc.2000.1711
Evaluation of total choline from in-vivo volume localized proton MR spectroscopy and its response to neoadjuvant chemotherapy in locally advanced breast cancer
N. Jagannathan (2001)
10.1158/0008-5472.CAN-14-1041
Loss of estrogen-regulated microRNA expression increases HER2 signaling and is prognostic of poor outcome in luminal breast cancer.
S. T. Bailey (2015)
10.1158/1078-0432.CCR-17-3783
Radiomics Signature on Magnetic Resonance Imaging: Association with Disease-Free Survival in Patients with Invasive Breast Cancer
Hyunjin Park (2018)
10.1056/NEJMOA041588
A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.
S. Paik (2004)
10.1373/clinchem.2013.210542
Prognostic significance of metastasis-related microRNAs in early breast cancer patients with a long follow-up.
A. Markou (2014)
10.1634/theoncologist.2017-0535
Luminal A Breast Cancer and Molecular Assays: A Review.
Jennifer J. Gao (2018)
10.1001/jamaoncol.2015.5482
Association of Depressed Anti-HER2 T-Helper Type 1 Response With Recurrence in Patients With Completely Treated HER2-Positive Breast Cancer: Role for Immune Monitoring.
J. Datta (2016)
10.1038/nature06913
The cancer biomarker problem
C. Sawyers (2008)
update of recommendations for the use of tumor markers in breast cancer
FJ Nassar
10.3389/fonc.2016.00217
Clinical Breast MR Using MRS or DWI: Who Is the Winner?
F. Sardanelli (2016)
10.1158/0008-5472.CAN-05-4005
Distinct role of macrophages in different tumor microenvironments.
C. Lewis (2006)
10.1016/j.coi.2014.01.004
New insights into cancer immunoediting and its three component phases--elimination, equilibrium and escape.
D. Mittal (2014)
10.1053/j.seminoncol.2015.05.007
Immune Effects of Chemotherapy, Radiation, and Targeted Therapy and Opportunities for Combination With Immunotherapy.
J. Wargo (2015)
10.1038/nrclinonc.2016.162
Imaging biomarker roadmap for cancer studies
J. O’Connor (2017)
10.1016/S1470-2045(17)30904-X
Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: a pooled analysis of 3771 patients treated with neoadjuvant therapy.
C. Denkert (2018)
10.1200/JCO.2015.63.5383
West German Study Group Phase III PlanB Trial: First Prospective Outcome Data for the 21-Gene Recurrence Score Assay and Concordance of Prognostic Markers by Central and Local Pathology Assessment.
O. Gluz (2016)
10.1007/s00262-013-1424-8
Elevated level of peripheral CD8+CD28− T lymphocytes are an independent predictor of progression-free survival in patients with metastatic breast cancer during the course of chemotherapy
G. Song (2013)
10.1016/j.amjsurg.2016.03.016
Predictors of 5-year local, regional, and distant recurrent events in a population-based cohort of breast cancer patients.
Filgen Fung (2017)
10.1016/j.imlet.2012.08.002
Models and methods for analysis of lymphocyte repertoire generation, development, selection and evolution.
R. Mehr (2012)
10.1016/S0140-6736(13)62422-8
Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis
P. Cortázar (2014)
10.1158/1078-0432.CCR-13-0804
Breast Cancer Index Identifies Early-Stage Estrogen Receptor–Positive Breast Cancer Patients at Risk for Early- and Late-Distant Recurrence
Y. Zhang (2013)
10.1259/bjr.20160715
The potential of multiparametric MRI of the breast.
K. Pinker (2017)
10.1002/jmri.25921
DCE‐MRI texture analysis with tumor subregion partitioning for predicting Ki‐67 status of estrogen receptor‐positive breast cancers
Ming Fan (2018)
10.1200/JCO.2011.38.8595
Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes.
G. von Minckwitz (2012)
Early prediction of response to chemotherapy in metastatic breast cancer using sequential 18F-FDG PET.
J. Dose Schwarz (2005)
10.1016/S1470-2045(17)30777-5
Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials
Bernard William John Jonas Elizabeth Judith Francesco Clar Asselain Barlow Bartlett Bergh Bergsten-Nordström (2018)
10.1038/nrclinonc.2016.217
Tumour-associated macrophages as treatment targets in oncology
A. Mantovani (2017)
10.1007/s10147-008-0773-3
Long-term prognostic study of carcinoembryonic antigen (CEA) and carbohydrate antigen 15-3 (CA 15-3) in breast cancer
Masahiro Uehara (2008)
10.1148/radiol.10092021
Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer.
S. Park (2010)
10.1038/sj.bjc.6605884
Relevance of BCAR4 in tamoxifen resistance and tumour aggressiveness of human breast cancer
M. Godinho (2010)
10.1016/j.ejca.2011.06.015
Determining circulating endothelial cells using CellSearch system during preoperative systemic chemotherapy in breast cancer patients.
A. M. Ali (2011)
10.2967/jnumed.108.057307
From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors
R. Wahl (2009)
10.1093/annonc/mdu450
The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014.
R. Salgado (2015)
10.1186/1471-2407-12-620
Dynamics of circulating endothelial cells and endothelial progenitor cells in breast cancer patients receiving cytotoxic chemotherapy
Yu-Hsuan Kuo (2012)
10.1016/j.anndiagpath.2009.02.003
Incidence of pathologic complete response in women treated with preoperative chemotherapy for locally advanced breast cancer: correlation of histology, hormone receptor status, Her2/Neu, and gross pathologic findings.
I. Alvarado-Cabrero (2009)
10.1016/j.jim.2008.07.006
Quantification of circulating mature endothelial cells using a whole blood four-color flow cytometric assay.
N. Jacques (2008)
10.1016/j.it.2010.10.002
Molecular mechanisms regulating myeloid-derived suppressor cell differentiation and function.
T. Condamine (2011)
10.1200/JOP.0768504
American Society of Clinical Oncology 2007 Update of Recommendations for the Use of Tumor Markers in Breast Cancer.
Lyndsay Harris (2007)
10.1097/CCO.0000000000000223
Liquid biopsy: will it be the ‘magic tool’ for monitoring response of solid tumors to anticancer therapies?
I. Gingras (2015)
10.1200/JCO.2015.65.2289
Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline.
Lyndsay N. Harris (2016)
10.3892/BR.2016.694
Identification of CD4+CD25+CD127- regulatory T cells and CD14+HLA-DR-/low myeloid-derived suppressor cells and their roles in the prognosis of breast cancer.
J. Wang (2016)
10.2214/AJR.09.3908
Accuracy of MRI in prediction of pathologic complete remission in breast cancer after preoperative therapy: a meta-analysis.
Y. Yuan (2010)
10.1016/j.ctro.2017.04.004
Time to surgery and pathologic complete response after neoadjuvant chemoradiation in rectal cancer: A population study on 2094 patients
G. Macchia (2017)
10.1634/THEONCOLOGIST.9-6-606
Prognostic and predictive factors in early-stage breast cancer.
M. Cianfrocca (2004)
DNA fragments in the blood plasma of cancer patients: quantitations and evidence for their origin from apoptotic and necrotic cells.
S. Jahr (2001)
10.2967/jnumed.116.183335
Prospective Clinical Trial of 18F-Fluciclovine PET/CT for Determining the Response to Neoadjuvant Therapy in Invasive Ductal and Invasive Lobular Breast Cancers
G. Ulaner (2017)
10.1002/prca.201000073
Taking a new biomarker into routine use – A perspective from the routine clinical biochemistry laboratory
C. Sturgeon (2010)
Circulating tumor cells: what we know, what do we want to know about them and are they ready to be used in clinics?
Z. Bielčiková (2017)
10.1016/j.jcyt.2017.08.018
Circulating CD8+CD28- suppressor T cells tied to poorer prognosis among metastatic breast cancer patients receiving adoptive T-cell therapy: A cohort study.
Qingkun Song (2018)
10.1002/jcp.26379
Breast cancer diagnosis: Imaging techniques and biochemical markers
S. H. Jafari (2018)
10.1093/jnci/djy018
Circulating Tumor Cells in Breast Cancer Patients Treated by Neoadjuvant Chemotherapy: A Meta-analysis
F. Bidard (2018)
Circulating Tumor Cells ( CTC ) and Cell - Free DNA ( cfDNA ) Workshop
L Lowes (2016)
10.1016/S1470-2045(17)30021-9
HER2-enriched subtype as a predictor of pathological complete response following trastuzumab and lapatinib without chemotherapy in early-stage HER2-positive breast cancer (PAMELA): an open-label, single-group, multicentre, phase 2 trial.
A. Llombart-cussac (2017)
10.2967/jnumed.115.160663
A Phase II Study of 3′-Deoxy-3′-18F-Fluorothymidine PET in the Assessment of Early Response of Breast Cancer to Neoadjuvant Chemotherapy: Results from ACRIN 6688
L. Kostakoglu (2015)
10.14670/HH-11-916
The role of tumor-associated macrophage in breast cancer biology.
J. Choi (2018)
10.1200/JCO.2011.41.0902
Prognostic and predictive value of tumor-infiltrating lymphocytes in a phase III randomized adjuvant breast cancer trial in node-positive breast cancer comparing the addition of docetaxel to doxorubicin with doxorubicin-based chemotherapy: BIG 02-98.
S. Loi (2013)
10.1093/annonc/mdx806
De-escalating and escalating treatments for early-stage breast cancer: the St. Gallen International Expert Consensus Conference on the Primary Therapy of Early Breast Cancer 2017.
G. Curigliano (2018)
10.1007/s10585-013-9602-9
Predictive and prognostic factors in locally advanced breast cancer: effect of intratumoral FOXP3+ Tregs
L. Demir (2013)
10.2967/jnumed.115.166322
The Prognostic Impact of Early Change in 18F-FDG PET SUV After Neoadjuvant Chemotherapy in Patients with Locally Advanced Breast Cancer
H. W. Lee (2016)
10.1186/bcr3242
Persistence of disseminated tumor cells after neoadjuvant treatment for locally advanced breast cancer predicts poor survival
R. R. Mathiesen (2012)
10.1002/jmri.25855
Quantitative evaluation of breast cancer response to neoadjuvant chemotherapy by diffusion tensor imaging: Initial results
E. Furman-Haran (2018)
10.1016/S1470-2045(09)70314-6
Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial.
K. Albain (2010)
10.1148/radiol.2017170180
Imaging Neoadjuvant Therapy Response in Breast Cancer.
Amy M Fowler (2017)
10.1016/j.ejca.2008.09.037
MicroRNA profiling as a tool to understand prognosis, therapy response and resistance in breast cancer.
M. Iorio (2008)
10.3322/canjclin.39.6.399
Cancer statistics
N. Dubrawsky (1989)
10.1002/cncr.25660
Use of standard markers and incorporation of molecular markers into breast cancer therapy
M. Kaufmann (2011)
10.1016/j.clbc.2016.12.010
Role of Magnetic Resonance Imaging in Detection of Pathologic Complete Remission in Breast Cancer Patients Treated With Neoadjuvant Chemotherapy: A Meta‐analysis
Y. Gu (2017)
10.1093/annonc/mdv148
Disseminated tumor cells from the bone marrow of patients with nonmetastatic primary breast cancer are predictive of locoregional relapse.
A. Hartkopf (2015)
10.1002/jmri.25790
Multiparametric MRI of the breast: A review
M. A. Marino (2018)
10.1245/s10434-011-2108-2
Recommendations from an International Consensus Conference on the Current Status and Future of Neoadjuvant Systemic Therapy in Primary Breast Cancer
M. Kaufmann (2011)
10.1038/bjc.1995.249
An evaluation of preoperative CA 15-3 measurement in primary breast carcinoma.
D. O'hanlon (1995)
Prognostic significance of tumor-associated macrophages in breast cancer: a meta-analysis of the literature. Oncotarget
X Zhao (2017)
10.1007/s10549-015-3479-z
Outcome after neoadjuvant chemotherapy in young breast cancer patients: a pooled analysis of individual patient data from eight prospectively randomized controlled trials
S. Loibl (2015)
10.1007/s10549-009-0360-y
Prognostic and predictive impact of central necrosis and fibrosis in early breast cancer: Results from two International Breast Cancer Study Group randomized trials of chemoendocrine adjuvant therapy
E. Maiorano (2009)
10.1016/j.ejca.2017.01.017
Clinical use of biomarkers in breast cancer: Updated guidelines from the European Group on Tumor Markers (EGTM).
M. Duffy (2017)
10.1016/j.breast.2012.07.006
Early prediction of pathologic response to neoadjuvant therapy in breast cancer: systematic review of the accuracy of MRI.
M. L. Marinovich (2012)
10.1093/jnci/djp335
Use of archived specimens in evaluation of prognostic and predictive biomarkers.
R. Simon (2009)
10.1007/s10549-007-9768-4
Histologic grading is an independent prognostic factor in invasive lobular carcinoma of the breast
E. Rakha (2007)
Prognostic value of mitotic counts in breast cancer of Saudi Arabian patients.
A. Buhmeida (2011)
10.1200/JCO.2005.04.7985
Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer.
S. Paik (2006)
1687Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials : Early Breast Cancer Trialists' Collaborative Group (EBCTCG)
C. Legrand (2005)
10.1007/s10549-008-0143-x
Molecular profiling and predictive value of circulating tumor cells in patients with metastatic breast cancer: an option for monitoring response to breast cancer related therapies
M. Tewes (2008)
10.1148/RADIOL.2332031285
Neoadjuvant chemotherapy of locally advanced breast cancer: predicting response with in vivo (1)H MR spectroscopy--a pilot study at 4 T.
Sina Meisamy (2004)
10.1007/s10549-009-0486-y
Breast cancer risk in women who fulfill high-risk criteria: at what age should surveillance start?
A. Brandt (2009)
10.1007/s00330-012-2653-5
Pre-treatment differences and early response monitoring of neoadjuvant chemotherapy in breast cancer patients using magnetic resonance imaging: a systematic review
R. Prevos (2012)
10.1093/annonc/mdn121
Proton MR spectroscopy for monitoring early treatment response of breast cancer to neo-adjuvant chemotherapy.
H-M Baek (2008)
10.1186/s12885-016-2454-3
Detection of circulating tumor cells using manually performed immunocytochemistry (MICC) does not correlate with outcome in patients with early breast cancer – Results of the German SUCCESS-A- trial
J. Jueckstock (2016)
10.1593/NEO.09490
Circulating endothelial cells and circulating progenitor cells in breast cancer: relationship to endothelial damage/dysfunction/apoptosis, clinicopathologic factors, and the Nottingham Prognostic Index.
P. Goon (2009)
10.1016/j.breast.2015.05.007
Mammographic breast density: Predictive value for pathological response to neoadjuvant chemotherapy in breast cancer patients.
S. Elsamany (2015)
10.1016/j.pharmthera.2016.11.012
MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction
Farah Nassar (2017)
10.1182/blood-2008-02-078071
B lymphocytes: how they develop and function.
T. Lebien (2008)
10.1038/nri2506
Myeloid-derived suppressor cells as regulators of the immune system
D. Gabrilovich (2009)
10.1093/annonc/mdt494
Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone.
M. Gnant (2014)
10.1177/0962280214537344
Quantitative imaging biomarkers: A review of statistical methods for technical performance assessment
D. Raunig (2015)
10.1186/s13058-015-0584-1
Anti-HER2 CD4+ T-helper type 1 response is a novel immune correlate to pathologic response following neoadjuvant therapy in HER2-positive breast cancer
J. Datta (2015)
10.3390/ijms17091505
Circulating Tumor Cells (CTC) and Cell-Free DNA (cfDNA) Workshop 2016: Scientific Opportunities and Logistics for Cancer Clinical Trial Incorporation
L. Lowes (2016)
10.1007/s10549-012-2033-5
Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer?
L. Wu (2012)
10.1093/annonc/mdw535
Circulating tumour cells and pathological complete response: independent prognostic factors in inflammatory breast cancer in a pooled analysis of two multicentre phase II trials (BEVERLY-1 and -2) of neoadjuvant chemotherapy combined with bevacizumab
J.-Y. Pierga (2017)
10.1007/s10549-013-2697-5
Racial disparities in treatment patterns and clinical outcomes in patients with HER2-positive metastatic breast cancer
H. Rugo (2013)
10.1148/radiol.11102493
Use of dynamic contrast-enhanced MR imaging to predict survival in patients with primary breast cancer undergoing neoadjuvant chemotherapy.
S. Li (2011)
10.1016/j.ejca.2008.10.026
New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).
E. Eisenhauer (2009)
10.1158/1078-0432.CCR-04-1707
Prognostic Role of a Multigene Reverse Transcriptase-PCR Assay in Patients with Node-Negative Breast Cancer Not Receiving Adjuvant Systemic Therapy
F. Esteva (2005)
10.1007/s13277-016-4909-1
Linc-ROR induces epithelial-mesenchymal transition and contributes to drug resistance and invasion of breast cancer cells
Y. Chen (2016)
10.1016/J.MRREV.2006.11.002
Circulating free DNA in plasma or serum as biomarker of carcinogenesis: practical aspects and biological significance.
E. Gormally (2007)
10.1093/annonc/mdu191
Association between CD8+ T-cell infiltration and breast cancer survival in 12,439 patients.
H. R. Ali (2014)
10.1093/annonc/mdu480
Circulating tumor cells and circulating tumor DNA for precision medicine: dream or reality?
M. Ignatiadis (2014)
10.1038/415530a
Gene expression profiling predicts clinical outcome of breast cancer
L. J. Veer (2002)
10.1111/j.1524-4741.2011.01160.x
Diffusion‐weighted Imaging in Evaluating the Response to Neoadjuvant Breast Cancer Treatment
P. Belli (2011)
10.1001/jamaoncol.2016.3824
RNA Sequencing to Predict Response to Neoadjuvant Anti-HER2 Therapy: A Secondary Analysis of the NeoALTTO Randomized Clinical Trial
D. Fumagalli (2017)
10.1158/1078-0432.CCR-05-1769
Circulating Tumor Cells versus Imaging—Predicting Overall Survival in Metastatic Breast Cancer
G. Budd (2006)
10.1245/s10434-011-1919-5
Accuracy of Clinical Examination, Digital Mammogram, Ultrasound, and MRI in Determining Postneoadjuvant Pathologic Tumor Response in Operable Breast Cancer Patients
Randal L Croshaw (2011)
For Personal Use Only
D. Cox (2015)
10.1200/JCO.2000.18.8.1689
Positron Emission Tomography Using [18F]Fluorodeoxyglucose for Monitoring Primary Chemotherapy in Breast Cancer
M. Schelling (2000)
10.1007/s10549-016-3750-y
A phase I/II trial of the safety and clinical activity of a HER2-protein based immunotherapeutic for treating women with HER2-positive metastatic breast cancer
G. Curigliano (2016)
10.1148/RADIOL.2016152110
MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays.
H. Li (2016)
10.2463/mrms.mp.2016-0037
Diagnostic Performance of Diffusion Tensor Imaging with Readout-segmented Echo-planar Imaging for Invasive Breast Cancer: Correlation of ADC and FA with Pathological Prognostic Markers
K. Yamaguchi (2017)
10.1093/annonc/mdr263
High independent prognostic and predictive value of circulating tumor cells compared with serum tumor markers in a large prospective trial in first-line chemotherapy for metastatic breast cancer patients.
J.-Y. Pierga (2012)
10.2147/CMAR.S157837
Optimized multiparametric flow cytometric analysis of circulating endothelial cells and their subpopulations in peripheral blood of patients with solid tumors: a technical analysis
Fangbin Zhou (2018)
10.1200/JCO.2008.18.1370
Supervised risk predictor of breast cancer based on intrinsic subtypes.
J. Parker (2009)
10.2217/bmm-2017-0143
Circulating endothelial cells and their subsets: novel biomarkers for cancer.
Fangbin Zhou (2017)



This paper is referenced by
10.1016/j.tranon.2020.100831
Multiparametric MRI-based radiomics analysis for the prediction of breast tumor regression patterns after neoadjuvant chemotherapy
Xiaosheng Zhuang (2020)
10.1259/bjr.20200287
Radiomic signatures derived from multiparametric magnetic resonance imaging for the pretreatment prediction of response to neoadjuvant chemotherapy in breast cancer.
T. Bian (2020)
10.1007/s12032-020-01353-1
Will traditional biopsy be substituted by radiomics and liquid biopsy for breast cancer diagnosis and characterisation?
F. Pesapane (2020)
10.3389/fonc.2020.00412
Correlation Between Mammographic Radiomics Features and the Level of Tumor-Infiltrating Lymphocytes in Patients With Triple-Negative Breast Cancer
Hong-wei Yu (2020)
10.3390/jpm10030132
Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism
Chanwoo Kim (2020)
10.1007/s10549-020-05660-z
Value of CXCL8–CXCR1/2 axis in neoadjuvant chemotherapy for triple-negative breast cancer patients: a retrospective pilot study
Ruo-xi Wang (2020)
10.1002/jbio.201900216
Evaluation of breast carcinoma regression after preoperative chemotherapy by label-free multiphoton imaging and image analysis.
Lianhuang Li (2019)
10.1186/s13244-020-00885-4
Imaging diagnosis of metastatic breast cancer
F. Pesapane (2020)
10.7150/ijbs.41579
Label-free multiphoton imaging to assess neoadjuvant therapy responses in breast carcinoma
Lianhuang Li (2020)
10.3892/ijmm.2019.4239
Screening of differentially expressed genes and identification of NUF2 as a prognostic marker in breast cancer
W. Xu (2019)
10.1158/1535-7163.MCT-19-0940
Genomic and Expression Analyses Define MUC17 and PCNX1 as Predictors of Chemotherapy Response in Breast Cancer
Waleed S Al Amri (2019)
10.7150/jca.46430
Indications of neoadjuvant chemotherapy for locally advanced Gastric Cancer patients based on pre-treatment clinicalpathological and laboratory parameters
Yue Wang (2020)
10.3390/ijms20030471
Gold Nanoparticle-Based Fluorescent Theranostics for Real-Time Image-Guided Assessment of DNA Damage and Repair
S. Srinivasan (2019)
10.21037/ATM.2019.04.10
A randomized multicenter phase II trial of mecapegfilgrastim single administration versus granulocyte colony-stimulating growth factor on treating chemotherapy-induced neutropenia in breast cancer patients.
T. Wang (2019)
10.1109/IST48021.2019.9010068
Extraction of Radiomic Features from Breast DCE-MRI Responds to Pathological Changes in Patients During Neoadjuvant Chemotherapy Treatment
Priscilla Dinkar Moyya (2019)
10.3233/cbm-190085
Circulating lncRNA H19 may be a useful marker of response to neoadjuvant chemotherapy in breast cancer.
Emre Özgür (2019)
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