L Amler's research while affiliated with Genentech and other places

Publications (5)

Data
Supplementary Report presenting (i) details of gene filtering, (ii) details of cross-validation procedure to choose 64-gene signature, (iii) list of 64 genes, and (iv) other statistical analyses based on secondary endpoints.
Article
Full-text available
Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction. We obtained the gene expression prof...
Article
Given the promise of rich biological information in microarray data we will expect an increasing demand for a robust, practical and well-tested methodology to provide patient prognosis based on gene expression data. In standard settings, with few clinical predictors, such a methodology has been provided by the Cox proportional hazard model, but no...

Citations

... Jonas Bergh (Karolinska Institute and Hospital, Stockholm, Sweden) presented results of a microarray analysis of a cohort of 186 patients treated for breast cancer between 1994 and 1996, and from whom stored frozen tissue was available [4]. The RNA from the tissue was extracted and examined using two different gene chips of 39,000 and 10,000 genes, respectively. ...
... In cases where mutation-based biomarkers do not exist, researchers have explored prognostic models based on tumor gene expression data. The proposed methods for selecting biomarkers include using univariate gene selection [4], penalized Cox regression [5,6], supervised principal component analysis [7], partial least squares algorithm [8] and some other machine learning techniques such as Random Forest [9]. While some expression-based models such as Oncotype Dx have been successful, these models can be difficult to implement due to high cost, limited performance and complexity in their interpretation. ...
... 13 The GEO study data are a curated aggregate of six Affymetrix Human Genome HG-U133A array datasets. 15 Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) and Array Express (http://www.ebi.ac.uk/array express) accession numbers are: E-TABM-158, 16 GSE6532, 17 GSE3494, 18 GSE1456, 19 GSE7390, 20 and GSE2603. 21 All RNA intensities and read counts were either available at, or converted to gene level measurements. ...