Prediction of nodal spread of breast cancer by using artificial neural network-based analyses of S100A4, nm23 and steroid receptor expression

Clinical and Experimental Metastasis

Volumn 20, Issue 6, 2003, Pages 507-514

  Grey, S R ^a   Dlay, S S ^a   Leone, B E ^b   Cajone, F ^c   Sherbet, G V ^a,d  

^a NEWCASTLE UNIVERSITY   (United Kingdom)

^b Ospedale di Monza   (Italy)

^c UNIVERSITY OF MILAN   (Italy)

^d INSTITUTE FOR MOLECULAR MEDICINE   (United States)

Author keywords

Artificial neural networks; Breast cancer; Metastasis associated gene; Metastasis suppressor gene; nm23; Nodal spread prediction; Oestrogen receptor; Progesterone receptor; S100A4

Indexed keywords

CALVASCULIN; ESTROGEN RECEPTOR; MOLECULAR MARKER; PROGESTERONE RECEPTOR; PROTEIN S 100; STEROID RECEPTOR; UNCLASSIFIED DRUG;

ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; AXILLARY LYMPH NODE; BREAST CARCINOMA; CONTROLLED STUDY; DISSECTION; GENE EXPRESSION; HUMAN; METASTASIS; MOLECULAR SIZE; PREDICTION; PROTEIN EXPRESSION;

ADULT; AGED; AGED, 80 AND OVER; BREAST NEOPLASMS; FEMALE; GENE EXPRESSION REGULATION, NEOPLASTIC; GENES, TUMOR SUPPRESSOR; GENETIC MARKERS; HUMANS; LYMPHATIC METASTASIS; MIDDLE AGED; MODELS, THEORETICAL; MONOMERIC GTP-BINDING PROTEINS; NERVE NET; NUCLEOSIDE-DIPHOSPHATE KINASE; PREDICTIVE VALUE OF TESTS; PROMOTER REGIONS (GENETICS); RECEPTORS, ESTROGEN; RECEPTORS, PROGESTERONE; RECEPTORS, STEROID; S100 PROTEINS; TRANSCRIPTION FACTORS;

EID: 0142093552     PISSN: 02620898     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1025846019656     Document Type: Article

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