SUMMARY Liver cancer has the second highest worldwide cancer mortality rate and has limited therapeutic options. We analyzed 363 hepatocellular carcinoma (HCC) cases by whole exome sequencing and DNA copy number analyses, and 196 HCC also by DNA methylation, RNA, miRNA, and proteomic expression. DNA sequencing and mutation analysis identified significantly mutated genes including LZTR1, EEF1A1, SF3B1, and SMARCA4. Significant alterations by mutation or down-regulation by hypermethylation in genes likely to result in HCC metabolic reprogramming (ALB, APOB, and CPS1) were observed. Integrative molecular HCC subtyping incorporating unsupervised clustering of five data platforms identified three subtypes, one of which was associated with poorer prognosis in three HCC cohorts. Integrated analyses enabled development of a p53 target gene expression signature correlating with poor survival. Potential therapeutic targets for which inhibitors exist include WNT signaling, MDM4, MET, VEGFA, MCL1, IDH1, TERT, and immune checkpoint proteins CTLA-4, PD-1, and PD-L1.

Purpose The Cancer Genome Atlas (TCGA) project recently uncovered four molecular subtypes of gastric cancer: Epstein-Barr virus (EBV), microsatellite instability (MSI), genomically stable (GS), and chromosomal instability (CIN). However, their clinical significances are currently unknown. We aimed to investigate the relationship between subtypes and prognosis of patients with gastric cancer. Experimental Design Gene expression data from a TCGA cohort (n = 262) were used to develop a subtype prediction model, and the association of each subtype with survival and benefit from adjuvant chemotherapy was tested in 2 other cohorts (n = 267 and 432). An integrated risk assessment model (TCGA risk score) was also developed. Results EBV subtype was associated with the best prognosis and GS subtype was associated with the worst prognosis. Patients with MSI and CIN subtypes had poorer overall survival than those with EBV subtype but better overall survival than those with GS subtype (P = 0.004 and 0.03 in two cohorts respectively). In multivariate Cox regression analyses, TCGA risk score was an independent prognostic factor (hazard ratio [HR] = 1.5; 95% confidence interval [CI] = 1.2–1.9; P = 0.001). Patients with the CIN subtype experienced the greatest benefit from adjuvant chemotherapy (HR = 0.39; 95% CI = 0.16–0.94; P = 0.03) and those with the GS subtype had the least benefit from adjuvant chemotherapy (HR = 0.83; 95% CI = 0.36–1.89; P = 0.65). Conclusion Our prediction model successfully stratified patients by survival and adjuvant chemotherapy outcomes. Further development of the prediction model is warranted.

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Gastric cancer is a heterogeneous cancer, making treatment responses difficult to predict. Here we show that we identify two distinct molecular subtypes, mesenchymal phenotype (MP) and epithelial phenotype (EP), by analyzing genomic and proteomic data. Molecularly, MP subtype tumors show high genomic integrity characterized by low mutation rates and microsatellite stability, whereas EP subtype tumors show low genomic integrity. Clinically, the MP subtype is associated with markedly poor survival and resistance to standard chemotherapy, whereas the EP subtype is associated with better survival rates and sensitivity to chemotherapy. Integrative analysis shows that signaling pathways driving epithelial-to-mesenchymal transition and insulin-like growth factor 1 (IGF1)/IGF1 receptor (IGF1R) pathway are highly activated in MP subtype tumors. Importantly, MP subtype cancer cells are more sensitive to inhibition of IGF1/IGF1R pathway than EP subtype. Detailed characterization of these two subtypes could identify novel therapeutic targets and useful biomarkers for prognosis and therapy response.

Purpose Activation of YAP1, novel oncogene in Hippo pathway, has been observed in many cancers including colorectal cancer (CRC). We investigated if activation of YAP1 is significantly associated with prognosis or treatment outcomes in CRC Experimental Design A gene expression signature reflecting YAP1 activation was identified in CRC cells, and CRC patients were stratified into two groups according to this signature: activated YAP1 CRC (AYCC) or inactivated YAP1 CRC (IYCC). Stratified patients in five test cohorts were evaluated to determine the effect of the signature on CRC prognosis and response to cetuximab treatment. Results The activated YAP1 signature was associated with poor prognosis for CRC in four independent patient cohorts with stage I–III disease (total n = 1,028). In a multivariate analysis, the impact of the YAP1 signature on the disease-free survival was independent of other clinical variables [hazard ratio (HR), 1.63; 95% confidence interval (CI), 1.25–2.13; P < 0.001]. In patients with stage IV CRC and wild-type KRAS, IYCC patients had a better disease control rate and progression-free survival (PFS) after cetuximab monotherapy than did AYCC patients; however, in patients with KRAS mutations, PFS duration after cetuximab monotherapy was not different between IYCC and AYCC patients. In multivariate analysis, the effect of YAP1 activation on PFS was independent of KRAS mutation status and other clinical variables (HR, 1.82; 95% CI, 1.05–3.16; P = 0.03). Conclusions Activation of YAP1 is highly associated with poor prognosis for CRC and may be useful in identifying patients with metastatic CRC resistant to cetuximab.