Go to the content. | Move to the navigation | Go to the site search | Go to the menu | Contacts | Accessibility

| Create Account

Goldin, Elena (2018) Predictive factors of non-sentinel axillary lymph nodes in breast cancer patients. Molecular markers of primary tumor and variability of patient's microenvironment. [Ph.D. thesis]

Full text disponibile come:

PDF Document

Abstract (english)

Background: The management of breast cancer has changed dramatically over the past two decades, from radical mastectomy to breast conservative surgery. Axillary lymph node dissection (ALND) has moved from a complete dissection to a less invasive procedure, the sentinel lymph node biopsy (SNLB), which has less morbidity compared to ALND and is used to evaluate lymph node status. Patients with positive sentinel lymph node (SNL) undergo a complete ALND of axillary level I and II lymph nodes. This operation is burdened by relevant postoperative morbidity, such as upper limb lymphedema, wound complications, nerve injury, limited mobility, neuropathic pain, numbness and sensory loss. Axillary lymph node metastasis in early T stage breast cancer are often be confined within the SNL(s), which offers no information about the presence of additional non-SNL (NSNL) metastasis, which may not occur in 40% to 70% of cases. The identification of these low risk patients would prevent them the morbidity associated with a full ALND. In order to avoid unnecessary, highly morbid ALND, it has become imperative for breast surgeons to find diagnostic tool that can identify SNL positive patients at low risk of NSNL metastasis and also who can safely avoid an ALND.

Material and Methods: We analysed whether a panel of molecular genes, expressed in primary breast cancer patients who underwent SNLB for breast cancer at our Institution, could predict NSNL metastasis and the influence of polymorphisms of genes related to inflammatory and angiogenetic pathways (IL8 rs4073, VEGF-2 rs11133360) on axillary lymph node status and to predict NSNL metastasis.
Molecular Markers:
• Pilot study: We calculated the expression of a panel of genes in 24 frozen tissue samples from selected patients with positive SNL received ALND, 12 with negative NSNL and 12 with positive NSNL. We customized our PCR arrays that include the genes of RT2 Profiler ‘human modified breast cancer’ PCR arrays (SABiosciences) and 4 genes (NDUFA7, MERTK, FN1, PSMB6) obtained from a previous microarray study performed in our department (unpublished). These 88 genes are involved in tumor classification, signal transduction and pathways such as angiogenesis, adhesion, proteolysis, cell cycle, and apoptosis.
• Validation study: We evaluated the expression of five significant genes (THBS1, IGF1, ERBB2, GRB7, MGMT), obtained from previous pilot experiment, in 171 frozen tissue samples from primary breast cancer of patient, who underwent breast surgery and SNLB for invasive breast cancer, between 2000 to 2013 in 1st Surgical Clinic, with RT-PCR.
Polymorphisms (IL8 rs4073 VEGFr-2 rs11133360):
Genomic DNA was isolated from peripheral whole blood/buffy coat of 234 patients. 10 to 20 ng of DNA of each patient were used for TaqMan SNP genotyping assays (Applied Biosystems). Genotyping was performed by Real Time PCR using allelic discrimination in the 7300 RT PCR System (Applied Biosystems). Post run data were by 7300 SDS software (Applied Biosystems) and Automatic calls were assigned with approximately 99.8% quality analysed.

Molecular Markers: THBS1 (p:0.0012) and IGF1 (p:0,05) were statistically differently expressed between patients with positive SNLs and negative NSNLs and patients with positive SNLs and positive NSNLs. ERBB2, GRB7, MGMT were differently expressed between the two groups, not statistically significant (p:0,07; p:0,07; p:0,08), but we included in the validation study. The RT-PCR for THBS1, IGF1, ERBB2, GRB7, MGMT was performed in 171 patients. Only GRB7 level was differently expressed in the interest group of our research. The median expression level of GRB7 in patients with positive SNLB and negative NSNL was 3,14 ng/ul, in the group of patients with positive SNL and positive ALND the median level was 6,76 ng/ul (p:0,014). The other genes (IGF1, MGMT, ERBB2, THBS1) had a similar expression in these groups of patients
Vascular invasion (IV) and frozen section analysis were predictive factors of NSNLs status on univariate logistic regression analysis (p<0,05). Multivariate logistic regression analysis confirmed that GRB7 was an independent predictive factor of NSNLs in patients with positive SNLB (p:0,017). Moreover, frozen section analysis proved to be statistically different in the two groups on multivariate analysis (p:0,047).
The discrimination of the multivariable model was assessed with the area under the receiver ROC curve and AUC was 0,77.
Polymorphisms (IL8 rs4073 VEGFr-2 rs11133360): We considered two models for both polymorphism: dominant and recessive. When we analysed the correlation between the genotype and NSNLs status in patients with positive SNLs, no statistically significant results were obtained for both models. The two polymorphisms investigated were no predictive of axillary status in patients with positive SNL, but only IL8 rs4073, in recessive model, was significantly different between patients with axillary metastasis (N+) and patient with negative axillary status (N0)

Conclusion: Our data suggest that the expression level of GRB7 could be a predictive tool of axilla status in patients with positive SNLB and could help the surgeon to decide the better axillary surgery in this group of patients. The polymorphisms investigated are not predictive of NSNL status, but a homozygous woman for the allele A of the polymorphism IL-8 rs4073 has a probability 2.28 times greater than the rest of the sick population of developing axillary metastasis from breast cancer.

Abstract (italian)

Background: il trattamento del cancro alla mammella è cambiata radicalmente negli ultimi due decenni, si è passati dalla mastectomia radicale alla chirurgia conservativa. La dissezione linfonodale ascellare è stata sostituita da una procedura meno invasiva, la biopsia del linfonodo sentinella, che ha una minore morbilità rispetto alla linfadenectomia ascellare e viene utilizzata per valutare lo stato dei linfonodi. I pazienti con linfonodo sentinella positivo subiscono uno svuotamento di linfonodi ascellari di I e II livello. Questa operazione è gravata da una rilevante morbilità postoperatoria, come linfedema dell'arto superiore, complicanze della ferita, danno ai nervi, mobilità limitata, dolore neuropatico, intorpidimento e perdita sensoriale. Le metastasi linfonodali ascellari nel carcinoma mammario in stadio T precoce sono spesso confinate all'interno del linfonodo sentinella, che non offre informazioni sulla presenza di metastasi addizionali ai linfonodi non sentinella, 40% -70% dei casi . L'identificazione di questi pazienti a basso rischio di metastasi ai linfonodi non sentinella eviterebbe a questi pazienti una dissezione ascellare inutile. Al fine di evitare uno svuotamento ascellare non necessario è indispensabile trovare uno strumento diagnostico in grado di identificare i pazienti con linfonodo sentinella positivo a basso rischio di metastasi ai linfonodi non sentinella.

Materiale e metodi: Abbiamo valutato se l’espressione di un panel di geni in pazienti con carcinoma mammario sottoposte a biopsia del linfonodo sentinella presso la nostra U.O, potesse predire le metastasi ai linfonodi non sentinella e l'influenza di polimorfismi di geni correlati a vie infiammatorie e angiogenetiche (IL8 rs4073, VEGF-2 rs11133360) sullo stato linfonodale ascellare e per predire le metastasi ai linfonodi non sentinella.
Marcatori molecolari:
• Studio pilota: abbiamo calcolato l'espressione di un pannello di geni in 24 campioni di tessuto congelato da pazienti selezionati con linfonodo sentinella positivo sottoposte anche a linfadenectomia ascellare, 12 con linfonodi non sentinella negativi e 12 con linfonodi non sentinella positivo. Abbiamo personalizzato i nostri array di PCR che includono i geni delle sequenze PCR del cancro della mammella RT2 Profiler (SABiosciences) e 4 geni (NDUFA7, MERTK, FN1, PSMB6) ottenuti da uno studio precedente di microarray eseguito nel nostro dipartimento (non pubblicato). Questi 88 geni sono coinvolti nella classificazione del tumore, nella trasduzione del segnale e in percorsi come l'angiogenesi, l'adesione, la proteolisi, il ciclo cellulare e l'apoptosi.
• Studio di validazione: abbiamo valutato l'espressione di cinque geni significativi (THBS1, IGF1, ERBB2, GRB7, MGMT), ottenuti dal precedente esperimento pilota, in 171 campioni di tessuto congelato da carcinoma mammario di paziente, sottoposte a chirurgia mammaria e biopsia del linfonodo sentinella per cancro alla mammella, tra il 2000 e il 2013 nella nostra UO, con RT-PCR.

Polimorfismi (IL8 rs4073 VEGFr-2 rs11133360):
Il DNA genomico è stato isolato dal sangue periferico / buffy coat di 234 pazienti. Sono stati utilizzati da 10 a 20 ng di DNA di ciascun paziente per i saggi di genotipizzazione di TaqMan SNP (Applied Biosystems). La genotipizzazione è stata eseguita mediante Real Time PCR utilizzando la discriminazione allelica nel sistema PCR RT 7300 (Applied Biosystems). I dati post-esecuzione sono stati forniti dal software SDS 7300 (Applied Biosystems) e le chiamate automatiche sono state assegnate con una qualità analizzata del 99,8% circa.

Marcatori molecolari: THBS1 (p: 0,0012) e IGF1 (p: 0,05) sono statisticamente differentemente espressi tra pazienti con linfonodi sentinella positivi e linfonodi non sentinella negativi e pazienti con linfonodi sentinella positivi e linfonodi non sentinella positivi. ERBB2, GRB7, MGMT sono differentemente espressi tra i due gruppi, ma in maniera non statisticamente significativa (p: 0,07; p: 0,07; p: 0,08), ma li abbiamo inclusi nello studio di convalida. La RT-PCR per THBS1, IGF1, ERBB2, GRB7, MGMT è stata eseguita in 171 pazienti. Solo il livello di GRB7 è espresso in modo diverso nel gruppo di interesse della nostra ricerca. Il livello di espressione medio di GRB7 in pazienti con linfonodo sentinella positivo e linfonodo non sentinella negativo era 3,14 ng / ul, nel gruppo di pazienti con linfonodo sentinella positivo e svuotamento ascellare positivo il livello mediano era di 6,76 ng / ul (p: 0,014). Gli altri geni (IGF1, MGMT, ERBB2, THBS1) hanno un'espressione simile in questi gruppi di pazienti
L'invasione vascolare (IV) e l'analisi della sezione congelata sono fattori predittivi dello stato delle NSNL sull'analisi di regressione logistica univariata (p <0,05). L'analisi di regressione logistica multivariata ha confermato che GRB7 è un fattore predittivo indipendente di stato dei linfonodi non sentinella in pazienti con linfonodo sentinella positivo (p: 0,017). Inoltre, l'analisi della sezione congelata si è dimostrata statisticamente diversa nei due gruppi sull'analisi multivariata (p: 0,047).
La discriminazione della multivariata è stata valutata con l'area sotto la curva ROC ricevente e l'AUC è 0,77.

Polimorfismi (IL8 rs4073 VEGFr-2 rs11133360): Abbiamo considerato due modelli per entrambi i polimorfismi: dominante e recessivo. Quando abbiamo analizzato la correlazione tra lo stato genotipo e lo stato dei linfonodi non sentinella in pazienti con linfonodi sentinella positivi, non sono stati ottenuti risultati statisticamente significativi per entrambi i modelli. I due polimorfismi studiati non sono predittivi dello stato ascellare in pazienti con linfonodo sentinella positivo, ma solo IL8 rs4073, nel modello recessivo, è significativamente differente tra pazienti con metastasi ascellari (N +) e pazienti con stato ascellare negativo (N0)

Conclusione: I nostri dati suggeriscono che il livello di espressione di GRB7 potrebbe essere uno strumento predittivo dello stato ascellare in pazienti con linfonodo sentinella positivo e potrebbe aiutare il chirurgo a decidere la migliore chirurgia in questo gruppo di pazienti. I polimorfismi studiati non sono predittivi dello stato di NSNL, ma una donna omozigote per l'allele A del polimorfismo IL-8 rs4073 ha una probabilità di 2,28 volte maggiore rispetto al resto della popolazione malata di sviluppare metastasi ascellari se affetta da tumore della mammella.

Statistiche Download
EPrint type:Ph.D. thesis
Tutor:Nitti, Donato
Data di deposito della tesi:09 January 2018
Anno di Pubblicazione:09 January 2018
Key Words:breast predictive factors
Settori scientifico-disciplinari MIUR:Area 06 - Scienze mediche > MED/18 Chirurgia generale
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Chirurgiche Oncologiche e Gastroenterologiche
Codice ID:10602
Depositato il:26 Oct 2018 08:42
Simple Metadata
Full Metadata
EndNote Format


I riferimenti della bibliografia possono essere cercati con Cerca la citazione di AIRE, copiando il titolo dell'articolo (o del libro) e la rivista (se presente) nei campi appositi di "Cerca la Citazione di AIRE".
Le url contenute in alcuni riferimenti sono raggiungibili cliccando sul link alla fine della citazione (Vai!) e tramite Google (Ricerca con Google). Il risultato dipende dalla formattazione della citazione.

New concepts in the management of primary breast cancer. Fisher B, Wolmark N. Cancer. 1975 Aug;36(2):627-32. Cerca con Google

Surgery in the primary treatment of breast cancer. Wolmark N, Fisher B. Breast Cancer Res Treat. 1981;1(4):339-48. Cerca con Google

Twenty-year follow-up of a randomized study comparing breast-conserving surgery with radical mastectomy for early breast cancer. Veronesi U, Cascinelli N, Mariani L, Greco M, Saccozzi R, Luini A, Aguilar M, Marubini E. N Engl J Med. 2002 Oct 17;347(16):1227-32 Cerca con Google

Twenty-year follow-up of a randomized trial comparing total mastectomy, lumpectomy, and lumpectomy plus irradiation for the treatment of invasive breast cancer. Fisher B, Anderson S, Bryant J, Margolese RG, Deutsch M, Fisher ER, Jeong JH, Wolmark N. N Engl J Med. 2002 Oct 17;347(16):1233-41 Cerca con Google

A randomized comparison of sentinel-node biopsy with routine axillary dissection in breast cancer. Veronesi U, Paganelli G, Viale G. N Engl J Med 2003 Cerca con Google

Molecular and protein markers for clinical decision making in breast cancer: today and tomorrow. Harbeck N, Sotlar K, Wuerstlein R, Doisneau-Sixou S. Cancer Treat Rev. 2014 Apr;40(3):434-44 Cerca con Google

Predictors of axillary lymph node metastasis in breast cancer: a systematic review. Patani NR, Dwek MV, Douek M. Eur J Surg Oncol. 2007 May;33(4):409-19. Cerca con Google

Axillary lymph node metastases in patients with small carcinomas of the breast: Is accurate prediction possible? Anan K, Mitsuyama S, Tamae K, et al. Eur J Surg 2000;166(8):610–5. Cerca con Google

Prediction of axillary lymph node involvement of women with invasive breast carcinoma: a multivariate analysis Olivotto IA, Jackson JS, Mates D, et al. Cancer 1998;83(5):948–55. Cerca con Google

Power doppler sonography of invasive breast carcinoma: Does tumor vascularization contribute to prediction of axillary status? Santamaria G, Velasco M, Farre X, Vanrell JA, Cardesa A, Fernandez PL Radiology 2005;234(2):374–80. Cerca con Google

Prediction of axillary lymph node status in invasive breast cancer with dynamic contrast-enhanced MR imaging. Mussurakis S, Buckley DL, Horsman A Radiology 1997;203:317–21. Cerca con Google

Role of ultrasonography to detect axillary node involvement in operable breast cancer. Eur J Surg Oncol 1996;22:140–3 Cerca con Google

High resolution sonographic detection of axillary lymph node metastases in breast cancer. Yang WT, Ahuja A, Tang A, Suen M, King W, Metreweli C J Ultrasound Med 1996;15(3):241–6 Cerca con Google

Gamma probe and ultrasonographically-guided fine-needle aspiration biopsy of sentinel lymph nodes in breast cancer patients. Motomura K, Inaji H, Komoike Y, et al. Eur J Surg Oncol 2001;27(2):141–5. Cerca con Google

Fluorodeoxyglucose positron emission tomography with sentinel lymph node biopsy for evaluation of axillary involvement in breast cancer. Gil-Rendo A, Zornoza G, Garcia-Velloso MJ, Regueira FM, Beorlegui C, Cervera M. Br J Surg 2006;93(6):707–12. Cerca con Google

Prospective multicenter study of axillary nodal staging by positron emission tomography in breast cancer: a report of the staging breast cancer with PET Study Group. Wahl RL, Siegel BA, Coleman RE, Gatsonis CG. J Clin Oncol 2004;22:277–85. Cerca con Google

Dynamic contrast enhanced MRI of the axilla in women with breast cancer: Comparison with pathology of excised nodes. Murray AD, Staff RT, Redpath TW, et al. Br J Radiol 2002;75(891):220–8. Cerca con Google

Relation of tumor size, lymph node status, and survival in 24,740 breast cancer cases. Carter CL, Allen C, Henson DE Cancer 1989;63:181–7. Cerca con Google

Prediction of axillary lymph node metastases in a screened breast cancer population. South-east Sweden Breast Cancer Group. Ahlgren J, Stal O, Westman G, Arnesson LG Acta Oncol 1994;33:603–8 Cerca con Google

Predicting the status of axillary sentinel lymph nodes in 4351 patients with invasive breast carcinoma treated in a single institution. Viale G, Zurrida S, Maiorano E, et al. Cancer 2005;103(3):492–500. Cerca con Google

Role of primary breast cancer characteristics in predicting positive sentinel lymph node biopsy results: a multivariate analysis. Chen M, Palleschi S, Khoynezhad A, Gecelter G, Marini CP, Simms HH. Arch Surg 2002;137(5):606–9. Cerca con Google

Pathological prognostic factors in breast cancer. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. C.W. Elston & I.O. Ellis. Histopathology 1991; 19; 403e410. Histopathology 2002;41:151 Cerca con Google

Predictors of lymph node metastasis in T1 breast carcinoma, stratified by patient age. Orucevic A, Reddy VB, Bloom KJ, et al. Breast J 2002;8(6):349–55. Cerca con Google

Proliferative activity of intratumoral fibroblasts is closely correlated with lymph node and distant organ metastases of invasive ductal carcinoma of the breast. Hasebe T, Sasaki S, Imoto S, Ochiai A. Am J Pathol 2000;156:1701–10 Cerca con Google

Frequency and predictors of axillary lymph node metastases in invasive breast cancer. Chua B, Ung O, Taylor R, Boyages J. ANZ J Surg 2001;71:723–8. Cerca con Google

Factors correlating with lymph node metastases in patients with T1 breast cancer. Brenin DR, Manasseh DM, El Tamer M, et al. Ann Surg Oncol 2001;8(5):432–7. Cerca con Google

The role of angiogenesis in tumor growth. Folkman J. Semin Cancer Biol 1992;3:65–71. Cerca con Google

Angiogenic and lymphangiogenic microvessel density in breast carcinoma: correlation with clinicopathologic parameters and VEGF-family gene expression. Choi WW, Lewis MM, Lawson D, et al. Mod Pathol 2005;18(1):143–52. Cerca con Google

Microvessel density as a prognostic factor in women with breast cancer: a systematic review of the literature and meta-analysis. Uzzan B, Nicolas P, Cucherat M, Perret GY Cancer Res 2004;64:2941–55. Cerca con Google

Predictors of axillary lymph node metastases in patients with T1 breast cancer. A multivariate analysis. Chadha M, Chabon AB, Friedmann P, Vikram B. Cancer 1994;73:350–3. Cerca con Google

Prediction of the axillary lymph node status in mammary cancer on the basis of clinicopathological data and flow cytometry. Mattfeldt T, Kestler HA, Sinn HP. Med Biol Eng Comput 2004;42:733–9. Cerca con Google

A quantitative analysis of lymphatic vessels in human breast cancer, based on LYVE-1 immunoreactivity. Kato T, Prevo R, Steers G, et al. Br J Cancer 2005;93(10):1168–74. Cerca con Google

Prediction of axillary lymph node status in breast cancer patients by use of prognostic indicators. Ravdin PM, De Laurentiis M, Vendely T, Clark GM. J Natl Cancer Inst 1994;86:1771–5. Cerca con Google

Histopathological predictors of axillary lymph node metastases in patients with breast cancer. Mitsuyama S, Anan K, Toyoshima S, et al. Breast Cancer 1999;6(3):237–41. Cerca con Google

Lymph node metastasis in breast cancer: common prognostic markers lack predictive value. Velanovich V, Szymanski W. Ann Surg Oncol 1998;5:613–9. Cerca con Google

Correlations between estrogen receptor, progesterone receptor, and patient characteristics in human breast cancer. Clark GM, Osborne CK, McGuire WL. J Clin Oncol 1984;2:1102–9. Cerca con Google

AlphaB-crystallin as a marker of lymph node involvement in breast carcinoma. Chelouche-Lev D, Kluger HM, Berger AJ, Rimm DL, Price JE. Cancer 2004;100:2543–8. Cerca con Google

Histologic grade and CD44 are independent predictors of axillary lymph node invasion in early (T1) breast cancer. Schneider J, Pollan M, Ruibal A, et al Tumour Biol 1999;20(6):319–30. Cerca con Google

Immunohistochemical staining of human breast cancer with a new tumour marker MCA: relation to axillary lymph node involvement, metastasis, and survival. Eskelinen M, Lipponen P, Collan Y. Anticancer Res 1990;10:591–6. Cerca con Google

RhoC-GTPase is a novel tissue biomarker associated with biologically aggressive carcinomas of the breast. Kleer CG, Griffith KA, Sabel MS, et al. Breast Cancer Res Treat 2005;93(2):101–10. Cerca con Google

Cyclo-oxygenase 2 expression is associated with angiogenesis and lymph node metastasis in human breast cancer. Costa C, Soares R, Reis-Filho JS, Leitao D, Amendoeira I, Schmitt FC. J Clin Pathol 2002;55(6):429–34. Cerca con Google

Reduced expression of both Bax and Bcl-2 is independently associated with lymph node metastasis in human breast carcinomas. Bukholm IR, Bukholm G, Nesland JM. APMIS 2002;110:214–20. Cerca con Google

Prediction of lymph node involvement in breast cancer by detection of altered glycosylation in the primary tumour. Brooks SA, Leathem AJ. Lancet 1991;338:71–4. Cerca con Google

DNA ploidy and helix pomatia lectin binding as predictors of regional lymph node metastases and prognostic factors in breast cancer. Noguchi M, Thomas M, Kitagawa H, et al. Breast Cancer Res Treat 1993;26(1):67–75. Cerca con Google

Prediction of nodal involvement in breast cancer based on multiparametric protein analyses from preoperative core needle biopsies of the primary lesion. Sauer G, Schneiderhan-Marra N, Kazmaier C, Hutzel K, Koretz K, Muche R, Kreienberg R, Joos T, Deissler H. Clin Cancer Res. 2008 Jun 1;14(11):3345 Cerca con Google

Molecular markers of breast axillary lymph node metastasis. Cavalli LR. Expert Rev Mol Diagn. 2009 Jul;9(5):441-54 Cerca con Google

DNA ploidy and helix pomatia lectin binding as predictors of regional lymph node metastases and prognostic factors in breast cancer. Noguchi M, Thomas M, Kitagawa H, et al. Breast Cancer Res Treat 1993;26(1):67–75. Cerca con Google

Frequency of chromosome 7 gain in human breast cancer cells: Correlation with the number of metastatic lymph nodes and prognosis. Hirata K, Tagawa Y, Kashima K, et al. Tohoku J Exp Med 1998;184(2):85–97. Cerca con Google

Microsatellite instability is correlated with lymph node-positive breast cancer. De Marchis L, Contegiacomo A, D’Amico C, et al. Clin Cancer Res 1997;3(2):241–8. Cerca con Google

Overexpression of HRad17 MRNA in human breast cancer: Correlation with lymph node metastasis. Kataoka A, Sadanaga N, Mimori K, et al. Clin Cancer Res 2001;7(9):2815–20. Cerca con Google

Prediction of nodal spread of breast cancer by using artificial neural network-based analyses of S100A4, nm23 and steroid receptor expression. Grey SR, Dlay SS, Leone BE, Cajone F, Sherbet GV. Clin Exp Metastasis 2003;20:507–14. Cerca con Google

Gene expression profiling predicts clinical outcome of breast cancer. van’t VeerLJ, DaiH, vandeVijverMJ, et al. Nature 2002 Jan;415(6871):530–6. Cerca con Google

A gene-expression signature as a predictor of survival in breast cancer. van de Vijver MJ, He YD, van’t Veer LJ, et al. N Engl J Med 2002; 347(25):1999–2009. Cerca con Google

Genome-wide gene-expression profiles of breast-cancer cells purified with laser microbeam microdissection: Identification of genes associated with progression and metastasis. Nishidate T, Katagiri T, Lin ML, et al. Int J Oncol 2004;25(4):797–819. Cerca con Google

Differentially expressed genes between primary cancer and paired lymph node metastases predict clinical outcome of node-positive breast cancer patients. Feng Y, Sun B, Li X, Zhang L, Niu Y, Xiao C, Ning L, Fang Z, Wang Y, Zhang L, Cheng J, Zhang W, Hao X. Breast Cancer Res Treat. 2007 Jul;103(3):319-29. Cerca con Google

The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1-3 positive lymph nodes in an independent validation study. Mook S, Schmidt MK, Viale G, Pruneri G, Eekhout I, Floore A, Glas AM, Bogaerts J, Cardoso F, Piccart-Gebhart MJ, Rutgers ET, Van't Veer LJ; TRANSBIG Consortium. Breast Cancer Res Treat. 2009 Jul;116(2):295-3 Cerca con Google

Proteomic profiling of primary breast cancer predicts axillary lymph node metastasis. Nakagawa T, Huang SK, Martinez SR, Tran AN, Elashoff D, Ye X, Turner RR, Giuliano AE, Hoon DS. Cancer Res. 2006 Dec 15;66(24):11825-30. Cerca con Google

Differential protein expression in primary breast cancer and matched axillary node metastasis. Thongwatchara P, Promwikorn W, Srisomsap C, Chokchaichamnankit D, Boonyaphiphat P, Thongsuksai P. Oncol Rep. 2011 Jul;26(1):185-91. Cerca con Google

Differential gene and protein expression in primary breast malignancies and their lymph node metastases as revealed by combined cDNA microarray and tissue microarray analysis. Hao X, Sun B, Hu L, Lähdesmäki H, Dunmire V, Feng Y, Zhang SW, Wang H, Wu C, Wang H, Fuller GN, Symmans WF, Shmulevich I, Zhang W. Cancer. 2004 Mar 15;100(6):1110-22 Cerca con Google

Omics-based profiling of carcinoma of the breast and matched regional lymph node metastasis. Li J, Gromov P, Gromova I, Moreira JM, Timmermans-Wielenga V, Rank F, Wang K, Li S, Li H, Wiuf C, Yang H, Zhang X, Bolund L, Celis JE. Proteomics. 2008 Dec;8(23-24):5038-52. Cerca con Google

Clinicopathologic features of metastasis in nonsentinel lymph nodes of breast carcinoma patients. Degnim AC, Griffith KA, Sabel MS, Hayes DF, Cimmino VM, Diehl KM, Lucas PC, Snyder ML, Chang AE, Newman LA. Cancer. 2003 Dec 1;98(11):2307-15. Cerca con Google

Molecular subtype classification is a determinant of non-sentinel lymph node metastasis in breast cancer patients with positive sentinel lymph nodes. Zhou W, He Z, Xue J, Wang M, Zha X, Ling L, Chen L, Wang S, Liu X. PLoS One. 2012;7(4):e35881. Cerca con Google

Prediction of metastatic breast cancer in non-sentinel lymph nodes based on metalloprotease-1 expression by the sentinel lymph node. Eiró N, González LO, Atienza S, González-Quintana JM, Beridze N, Fernandez-Garcia B, Pérez-Fernández R, García-Caballero T, Schneider J, Vizoso FJ. Eur J Cancer. 2013 Mar;49(5):1009-17 Cerca con Google

The molecular subtype classification is a determinant of sentinel node positivity in early breast carcinoma. Reyal F, Rouzier R, Depont-Hazelzet B, Bollet MA, Pierga JY, Alran S, Salmon RJ, Fourchotte V, Vincent-Salomon A, Sastre-Garau X, Antoine M, Uzan S, Sigal-Zafrani B, De Rycke Y. PLoS One. 2011;6(5):e20297 Cerca con Google

Clinicopathological parameters and biological markers predicting non-sentinel node metastasis in sentinel node-positive breast cancer patients. Kwon Y, Ro J, Kang HS, Kim SK, Hong EK, Khang SK, Gong G, Ro JY. Oncol Rep. 2011 Apr;25(4):1063-71. Cerca con Google

Non-sentinel lymph node metastasis prediction in breast cancer with metastatic sentinel lymph node: impact of molecular subtypes classification. Reyal F, Belichard C, Rouzier R, de Gournay E, Senechal C, Bidard FC, Pierga JY, Cottu P, Lerebours F, Kirova Y, Feron JG, Fourchotte V, Vincent-Salomon A, Guinebretiere JM, Sigal-Zafrani B, Sastre-Garau X, De Rycke Y, Coutant C. PLoS One. 2012;7(10):e47390. Cerca con Google

Impact of CD44+CD24- cells on non-sentinel axillary lymph node metastases in sentinel node-positive breast cancer. Nogi H, Suzuki M, Kamio M, Kato K, Kawase K, Toriumi Y, Takeyama H, Fukushima H, Morikawa T, Uchida K. Oncol Rep. 2011 Apr;25(4):1109-15. Cerca con Google

Prediction of non-sentinel lymph node metastasis in early breast cancer by assessing total tumoral load in the sentinel lymph node by molecular assay. Espinosa-Bravo M, Sansano I, Pérez-Hoyos S, Ramos M, Sancho M, Xercavins J, Rubio IT, Peg V. Eur J Surg Oncol. 2013 Jul;39(7):766-73 Cerca con Google

Quantitation of sentinel node metastatic burden and Her-2/neu over-expression accurately predicts residual axillary nodal involvement and extranodal disease in breast cancer. Chae AW, Vandewalker KM, Li YJ, Beckett LA, Ramsamooj R, Bold RJ, Khatri VP. Eur J Surg Oncol. 2013 Jun;39(6):627-33 Cerca con Google

A scoring system to predict nonsentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: a comparison with other scoring systems. Cho J, Han W, Lee JW, Ko E, Kang SY, Jung SY, Kim EK, Moon WK, Cho N, Park IA, Chung JK, Hwang KT, Kim SW, Noh DY. Ann Surg Oncol. 2008 Aug;15(8):2278-86 Cerca con Google

Comparison of models to predict nonsentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: a prospective multicenter study. Coutant C, Olivier C, Lambaudie E, Fondrinier E, Marchal F, Guillemin F, Seince N, Thomas V, Levêque J, Barranger E, Darai E, Uzan S, Houvenaeghel G, Rouzier R. J Clin Oncol. 2009 Jun 10;27(17):2800-8. Cerca con Google

Evaluation of three scoring systems predicting non sentinel node metastasis in breast cancer patients with a positive sentinel node biopsy. Dauphine CE, Haukoos JS, Vargas MP, Isaac NM, Khalkhali I, Vargas HI. Ann Surg Oncol. 2007 Mar;14(3):1014-9 Cerca con Google

Validation and comparison of models to predict non-sentinel lymph node metastasis in breast cancer patients. Chen K, Zhu L, Jia W, Rao N, Fan M, Huang H, Shan Q, Han J, Song E, Zeng Y, Su F. Cancer Sci. 2012 Feb;103(2):274-81 Cerca con Google

An axilla scoring system to predict non-sentinel lymph node status in breast cancer patients with sentinel lymph node involvement. Barranger E, Coutant C, Flahault A, Delpech Y, Darai E, Uzan S. Breast Cancer Res Treat. 2005 May;91(2):113-9 Cerca con Google

Predicting Non-sentinel Lymph Node Metastasis in a Chinese Breast Cancer Population with 1-2 Positive Sentinel Nodes: Development and Assessment of a New Predictive Nomogram. Chen JY, Chen JJ, Xue JY, Chen Y, Liu GY, Han QX, Yang WT, Shen ZZ, Shao ZM, Wu J. World J Surg. 2015 Dec;39(12):2919-27. Cerca con Google

Comparison of two models for the prediction of nonsentinel node metastases in breast cancer. Ponzone R, Maggiorotto F, Mariani L, Jacomuzzi ME, Magistris A, Mininanni P, Biglia N, Sismondi P.Am J Surg. 2007 Jun;193(6):686-92 Cerca con Google

Models for predicting non-sentinel lymph node positivity in sentinel node positive breast cancer: the importance of scoring system. Unal B, Gur AS, Kayiran O, Johnson R, Ahrendt G, Bonaventura M, Soran A. Int J Clin Pract. 2008 Nov;62(11):1785-91. Cerca con Google

Which nomogram is best for predicting non-sentinel lymph node metastasis in breast cancer patients? A meta-analysis. Zhu L, Jin L, Li S, Chen K, Jia W, Shan Q, Walter S, Song E, Su F. Breast Cancer Res Treat. 2013 Feb;137(3):783-95. Cerca con Google

New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients. Kohrt HE, Olshen RA, Bermas HR, Goodson WH, Wood DJ, Henry S, Rouse RV, Bailey L, Philben VJ, Dirbas FM, Dunn JJ, Johnson DL, Wapnir IL, Carlson RW, Stockdale FE, Hansen NM, Jeffrey SS; Bay Area SLN Study. BMC Cancer. 2008 Mar 4;8:66. Cerca con Google

Molecular analysis of sentinel lymph nodes and search for molecular signatures of the metastatic potential of breast cancer. Hoon DS, Bernet L, Cano R, Viale G. Q J Nucl Med Mol Imaging. 2014 Jun;58(2):180-92. Review. Cerca con Google

Analysis and clinical value of the expression of metalloproteases and their inhibitors by intratumor stromal fibroblasts and those at the invasive front of breast carcinomas. Del Casar JM1, González LO, Alvarez E, Junquera S, Marín L, González L, Bongera M, Vázquez J, Vizoso FJ. Cerca con Google

Breast Cancer Res Treat 2009;116(1):39–52. Cerca con Google

Study of matrix metalloproteinases and their inhibitors in breast cancer. FJ Vizoso, LO González, MD Corte, J C Rodríguez, J Vázquez, ML Lamelas, S Junquera, AM Merino, J L García-Muñiz Br J Cancer 2007;96(6):903–11 Cerca con Google

Molecular indicators of non-sentinel node status in breast cancer determined in preoperative biopsies by multiplexed sandwich immunoassays. Sauer G, Schneiderhan-Marra N, Muche R, Koretz K, Kazmaier C, Kreienberg R, Joos T, Deissler H. J Cancer Res Clin Oncol. 2011 Aug;137(8):1175-84 Cerca con Google

Molecular biomarkers screened by next-generation RNA sequencing for non-sentinel lymph node status prediction in breast cancer patients with metastatic sentinel lymph nodes. Liang F, Qu H, Lin Q, Yang Y, Ruan X, Zhang B, Liu Y, Yu C, Zhang H, Fang X, Hao X. World J Surg Oncol. 2015 Aug 28;13:258. Cerca con Google

Genetic polymorphisms in inflammatory response genes and their associations with breast cancer risk. Wang Z, Liu QL, Sun W, Yang CJ, Tang L, Zhang X, Zhong XM. Croat Med J. 2014 Dec;55(6):638-46. Cerca con Google

Genetic variants in interleukin genes are associated with breast cancer risk and survival in a genetically admixed population: the Breast Cancer Health Disparities Study. Slattery ML, Herrick JS, Torres-Mejia G, John EM, Giuliano AR, Hines LM, Stern MC, Baumgartner KB, Presson AP, Wolff RK Carcinogenesis. 2014 Aug;35(8):1750-9. Cerca con Google

Interleukin-6 -174G--&gt;C polymorphism is associated with improved outcome in high-risk breast cancer. DeMichele A, Martin AM, Mick R, Gor P, Wray L, Klein-Cabral M, Athanasiadis G, Colligan T, Stadtmauer E, Weber B. Cancer Res. 2003 Nov 15 Cerca con Google

Genetic variation in pro-inflammatory cytokines (interleukin-1beta, interleukin-1alpha and interleukin-6) associated with the aggressive forms, survival, and relapse prediction of breast carcinoma. Snoussi K, Strosberg AD, Bouaouina N, Ben Ahmed S, Chouchane L. Eur Cytokine Netw. 2005 Dec Cerca con Google

Interleukin-8 and human cancer biology. Xie K. Cytokine Growth Factor Rev. 2001 Dec;12(4):375-91. Review Cerca con Google

Genetic variation in IL-8 associated with increased risk and poor prognosis of breast carcinoma. Snoussi K, Mahfoudh W, Bouaouina N, Ahmed SB, Helal AN, Chouchane L. Hum Immunol. 2006 Jan-Feb;67(1-2):13-21. Cerca con Google

Combined effects of IL-8 and CXCR2 gene polymorphisms on breast cancer susceptibility and aggressiveness. Snoussi K, Mahfoudh W, Bouaouina N, Fekih M, Khairi H, Helal AN, Chouchane L. BMC Cancer. 2010 Jun 12;10:283. Cerca con Google

Prognostic and predictive role of vascular endothelial growth factor polymorphisms in breast cancer. Koutras A, Kotoula V, Fountzilas G. Pharmacogenomics. 2015 Jan;16(1):79-94. Cerca con Google

Vascular endothelial growth factor polymorphisms affect gene expression and tumor aggressiveness in patients with breast cancer. Sa-Nguanraksa D, Kooptiwut S, Chuangsuwanich T, Pongpruttipan T, Malasit P, O-Charoenrat P. Mol Med Rep. 2014 Mar Cerca con Google

Association of vascular endothelial growth factor--a gene polymorphisms and haplotypes with breast cancer metastases. Langsenlehner U, Hofmann G, Renner W, Gerger A, Krenn-Pilko S, Thurner EM, Krippl P, Langsenlehner T. Acta Oncol. 2015 Mar;54(3):368-76 Cerca con Google

Vascular endothelial growth factor gene polymorphism (-634G/C) and breast cancer risk. Yao W, Yan R, Ma L, Wan H, Yu Y, Cheng X, Li Y.Tumour Biol. 2014 Aug;35(8):7793-8 Cerca con Google

Vascular endothelial growth factor +405G/C and -2578C/A polymorphisms and breast cancer risk: a meta-analysis. Zhang Y, Yu YF, Wang JZ, Jia H. Genet Mol Res. 2015 Aug 3;14(3):8909-18. Cerca con Google

Association between the Functional Polymorphism of Vascular Endothelial Growth Factor Gene and Breast Cancer: A Meta-Analysis. Li J, Ju Y. Iran J Med Sci. 2015 Jan;40(1):2-12. Review. Cerca con Google

A new mathematical model for relative quantification in real-time RT–PCR Michael W. Pfaffl Nucleic Acids Res. 2001 May 1; 29(9): e45. Cerca con Google

Axillary dissection versus no axillary dissection in patients with sentinel-node micrometastases (IBCSG 23-01): a phase 3 randomised controlled trial. Galimberti V, Cole BF, Zurrida S, Viale G, Luini A, Veronesi P, Baratella P, Chifu C, Sargenti M, Intra M, Gentilini O, Mastropasqua MG, Mazzarol G, Massarut S, Garbay JR, Zgajnar J, Galatius H, Recalcati A, Littlejohn D, Bamert M, Colleoni M, Price KN, Regan MM, Goldhirsch A, Coates AS, Gelber RD, Veronesi U; International Breast Cancer Study Group Trial 23-01 investigators. Lancet Oncol. 2013 Apr;14(4):297-305. Epub 2013 Mar 11. Cerca con Google

The intertwining of structure and function: proposed helix-swapping of the SH2 domain of Grb7, a regulatory protein implicated in cancer progression and inflammation. Pias S, Peterson TA, Johnson DL, Lyons BA. Crit Rev Immunol. 2010;30(3):299-304. Review. Cerca con Google

Association of Grb7 with phosphoinositides and its role in the regulation of cell migration. Shen TL, Han DC, Guan JL.J Biol Chem. 2002 Aug 9;277(32):29069-77 Cerca con Google

The Grb7 family proteins: structure, interactions with other signaling molecules and potential cellular functions. Han DC, Shen TL, Guan JL. Oncogene. 2001 Oct 1;20(44):6315-21. Review Cerca con Google

Grb7 and Filamin-a associate and are colocalized to cell membrane ruffles upon EGF stimulation. Paudyal P, Shrestha S, Madanayake T, Shuster CB, Rohrschneider LR, Rowland A, Lyons BA. J Mol Recognit. 2013 Nov;26(11):532-41. Cerca con Google

Growth factor receptor-bound protein-7 (Grb7) as a prognostic marker and therapeutic target in breast cancer. Nadler Y, González AM, Camp RL, Rimm DL, Kluger HM, Kluger Y.Ann Oncol. 2010 Mar;21(3):466-73 Cerca con Google

Prospective Validation of a 21-Gene Expression Assay in Breast Cancer. Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, Geyer CE Jr, Dees EC, Perez EA, Olson JA Jr, Zujewski J, Lively T, Badve SS, Saphner TJ, Wagner LI, Whelan TJ, Ellis MJ, Paik S, Wood WC, Ravdin P, Keane MM, Gomez Moreno HL, Reddy PS, Goggins TF, Mayer IA, Brufsky AM, Toppmeyer DL, Kaklamani VG, Atkins JN, Berenberg JL, Sledge GW. N Engl J Med. 2015 Nov 19;373(21):2005-14. Epub 2015 Sep 27 Cerca con Google

Radiotherapy or surgery of the axilla after a positive sentinel node in breast cancer (EORTC 10981-22023 AMAROS): a randomised, multicentre, open-label, phase 3 non-inferiority trial. Donker M, van Tienhoven G, Straver ME, Meijnen P, van de Velde CJ, Mansel RE, Cataliotti L, Westenberg AH, Klinkenbijl JH, Orzalesi L, Bouma WH, van der Mijle HC, Nieuwenhuijzen GA, Veltkamp SC, Slaets L, Duez NJ, de Graaf PW, van Dalen T, Marinelli A, Rijna H, Snoj M, Bundred NJ, Merkus JW, Belkacemi Y, Petignat P, Schinagl DA, Coens C, Messina CG, Bogaerts J, Rutgers EJ. Lancet Oncol. 2014 Nov;15(12):1303-10. Cerca con Google

Effect of Axillary Dissection vs No Axillary Dissection on 10-Year Overall Survival Among Women With Invasive Breast Cancer and Sentinel Node Metastasis: The ACOSOG Z0011 (Alliance) Randomized Clinical Trial. Giuliano AE, Ballman KV, McCall L, Beitsch PD, Brennan MB, Kelemen PR, Ollila DW, Hansen NM, Whitworth PW, Blumencranz PW, Leitch AM, Saha S, Hunt KK, Morrow M. JAMA. 2017 Sep 12;318(10):918-926 Cerca con Google

Download statistics

Solo per lo Staff dell Archivio: Modifica questo record