Highlights d Proteomic subgroups stratify patient survival and allocate specific treatments d Alterations of the liver-specific proteome and metabolism in HCC are identified d Multi-omics profile of key signaling and metabolic pathways in HCC is depicted d CTNNB1 mutation-associated ALDOA phosphorylation promotes HCC cell proliferation

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Background: In recent years, the maturation of microarray technology has allowed the genomewide analysis of gene expression patterns to identify tissue-specific and ubiquitously expressed ('housekeeping') genes. We have performed a functional and topological analysis of housekeeping and tissue-specific networks to identify universally necessary biological processes, and those unique to or characteristic of particular tissues.

A minority of the 1% to 9% IHC ER-positive tumors show molecular features similar to those of ER-positive, potentially endocrine-sensitive tumors, whereas most show ER-negative, basal-like molecular characteristics. The safest clinical approach may be to use both adjuvant endocrine therapy and chemotherapy in this rare subset of patients.