We performed a comprehensive molecular and genomic characterization of 104 surgically resected CCAs. Our 238-gene classifier identified a high-risk group of patients with CCA, significantly differentiating patients according to overall and recurrence-free survival independent of specific clinical subtypes. Reflecting the strength of the classifier, it could be further reduced to 36 genes, which differentiated individuals in outcome-linked categories with greater accuracy. A comparison with our recent genomic data obtained from a limited number of CCAs24
confirmed a significant cholangio-specific association of our 238-gene classifier as well as the 36 survival genes identified in this study (Supplementary Figure 8
). Furthermore, in a meta-analysis, our classifier revealed a strong capacity to predict clinical outcome for other types of cancer, including HCC (Supplementary Figure 7B–D
). The close genomic relationships found between HCC and CCA suggest that acquisition of CCA-like expression traits may play a role in HCC heterogeneity.
Combining laser microdissection with transcriptomics allowed us to identify the core biological processes in tumor epithelium and stroma, which drive CCA disease progression and outcome. The most malignant tumor phenotype was characterized by a strong up-regulation of HER2 signaling in the epithelial cell compartment and concomitant overexpression of proinflammatory cytokines in tumor stroma, including interleukin-625
A recently described 26-gene stromal-derived prognostic predictor in breast cancer16
was significantly enriched in the stromal compartment of CCA.
Aberrant HER2 expression has been described in many cancers (eg, ovarian, gastric) and most prominently in breast cancer, where it has a significant role in malignant transformation27
and choice of therapy. In CCA, overexpression of HER2 was reported in ~30% of tumors.20
In our study, HER2 up-regulation was found only in tumors from patients with poor prognosis, who were also characterized by a frequent coactivation of ERBB3 and EGFR, 2 other members of the ErbB receptor family, as well as MET and mTOR. Multiple oncogenic pathways were frequently coactivated within a single tumor from the poor prognosis group (Supplementary Figure 5A
), indicating that oncogenic addiction may be a hallmark of CCA progression. To explore the effects of available drugs targeting RTKs for treatment of CCA, we used an integrated in vitro/in vivo approach to identify CCA cell lines that closely mimic the genomic phenotypes of the identified subclasses of patients with CCA (). The results showed that our newly recognized subclass of patients with poor outcome CCA with increased EGFR and HER2 signaling may benefit from dual-target TKIs, whereas KRAS
mutations may confer resistance to this treatment. Although TKIs may present a therapeutic strategy to target CCA, a secondary target downstream of KRAS may be required to sensitize TKI-resistant cancer cells to TKIs. Indeed, we found a significant association of activating KRAS
mutations (24.6%) in the cohort with outcome when integrated with the classifier. The presence of KRAS
mutations is predictive of resistance to EGFR therapy in colorectal cancer. Clinical trials with TKIs in non–small cell lung cancer show that patients responding to therapy typically have activating mutations in EGFR
Although a low frequency of EGFR
mutations (13.6%) was described in CCA,30
we found no EGFR
-specific mutations or amplification of EGFR
in our cohort. A recent phase 2 study with erlotinib in advanced biliary cancers7
showed a therapeutic benefit against tumors overexpressing EGFR. Also, given a strong activation of the downstream mTOR pathway in tumors from patients with poor outcome, targeting this pathway may present an alternative treatment option for CCA. A more in-depth analysis of the prognostic subclasses by class comparison identified a group of patients (SGIII) characterized by overrepresentation of genes involved in proteasomal activity, suggesting a potential therapeutic benefit of proteasome and antiinflammatory inhibitors.
In conclusion, we identified 2 prognostic categories of patients with CCA, each containing 2 subclasses (SGI–IV) characterized by distinct gene expression profiles. A prognostic 36-gene classifier either alone or in combination with other molecular predictors (ie, mutations, coactivation of multiple oncogenic pathways) improved the molecular classification and outcome prediction in CCA. The study also shows the therapeutic potential for dual-target TKIs (eg, lapatinib) in CCA. Taken together, the present findings establish the foundation for future directions in the development of diagnostic and therapeutic modalities for CCA.