Collectively, these findings validate the relationship between antibody response to brain induced by P. falciparum infection and plasma cytokine patterns with clinical outcome of malaria.
The success of our approach does not negate the importance of previous individual expression studies, which have identified gene patterns with clinical and biologic relevance; rather effective integration of these studies may represent an important step forward towards wider clinical application of gene expression assays.
Additionally, we correlated methylation patterns with clinical features and prognosis.
Biological signature analysis was performed to correlate gene expression patterns with clinical characteristics, including age, gender, pathology, differentiation, lymph node metastasis and survival time, which were commonly used to predict clinical outcomes and prognosis.
These same studies and others have also begun to explore the clinical relevance of such model signatures by inferring pathway activity across human tumours and correlating the inferred patterns with clinical variables [ 1, 6, 7, 9- 14].
Recent cancer research has applied a variety of machine learning algorithms for tumor prediction by associating expression patterns with clinical outcomes for patients with tumors in various stages [ 3, 4, 8, 9].
In order to validate this approach, further studies should focus on the transporter localisation in tumour cells isolated from different patients and correlation of protein localisation patterns with clinical response to cisplatin chemotherapy.
Efforts to dissect EOC heterogeneity have correlated expression patterns with clinical features, such as histological types, aggressiveness and patient outcomes (Denkert et al, 2009; Helland et al, 2011; Mok et al, 2009; The Cancer Genome Atlas Research Network, 2011; Tothill et al, 2008).
In the special-interest group 'Systems Biology and the Cell: Are There Simple Rules Governing Complexity?', Therese Sorlie described her work on the subclassification of breast tumors by identifying a 'molecular portrait' of various tumor types and the correlation of these expression patterns with clinical parameters such as survival and the likelihood of metastasis.
The aim of this study was to determine whether such responses reflect a particular pattern of SOX2 protein expression in the tumor and whether this pattern associates with clinical outcome.
