High Keratin 8/18 Ratio Predicts Aggressive Hepatocellular Cancer Phenotype
TRANSLATIONAL ONCOLOGY
Authors: Golob-Schwarzi, Nicole; Bettermann, Kira; Mehta, Anita Kuldeep; Kessler, Sonja M.; Unterluggauer, Julia; Krassnig, Stefanie; Kojima, Kensuke; Chen, Xintong; Hoshida, Yujin; Bardeesy, Nabeel M.; Mueller, Heimo; Svendova, Vendula; Schimek, Michael G.; Diwoky, Clemens; Lipfert, Alexandra; Mahajan, Vineet; Stumptner, Cornelia; Thueringer, Andrea; Froehlich, Leopold F.; Stojakovic, Tatjana; Nilsson, K. P. R.; Kolbe, Thomas; Ruelicke, Thomas; Magin, Thomas M.; Strnad, Pavel; Kiemer, Alexandra K.; Moriggl, Richard; Haybaeck, Johannes
Abstract
BACKGROUND & AIMS: Steatohepatitis (SH) and SH-associated hepatocellular carcinoma (HCC) are of considerable clinical significance. SH is morphologically characterized by steatosis, liver cell ballooning, cytoplasmic aggregates termedMallory-Denk bodies (MDBs), inflammation, and fibrosis at late stage. Disturbance of the keratin cytoskeleton and aggregation of keratins (KRTs) are essential for MDB formation. METHODS: Weanalyzed livers of aged Krt18(-/-) mice that spontaneously developed in the majority of cases SH-associated HCC independent of sex. Interestingly, the hepatic lipid profile in Krt18(-/-) mice, which accumulate KRT8, closely resembles human SH lipid profiles and shows that the excess of KRT8 over KRT18 determines the likelihood to develop SH-associated HCC linked with enhanced lipogenesis. RESULTS: Our analysis of the genetic profile of Krt18(-/-) mice with 26 human hepatoma cell lines and with data sets of >300 patients with HCC, where Krt18(-/-) gene signatures matched human HCC. Interestingly, a high KRT8/18 ratio is associated with an aggressive HCC phenotype. CONCLUSIONS: We can prove that intermediate filaments and their binding partners are tightly linked to hepatic lipid metabolism and to hepatocarcinogenesis. We suggest KRT8/18 ratio as a novel HCC biomarker for HCC.
Biomarkers of Breast Cancer Apoptosis Induced by Chemotherapy and TRAIL
JOURNAL OF PROTEOME RESEARCH
Authors: Leong, Sharon; McKay, Matthew J.; Christopherson, Richard I.; Baxter, Robert C.
Abstract
Treatment of breast cancer is complex and challenging due to the heterogeneity of the disease. To avoid significant toxicity and adverse side-effects of chemotherapy in patients who respond poorly, biomarkers predicting therapeutic response are essential. This study has utilized a proteomic approach integrating 2D-DIGE, LC-MS/MS, and bioinformatics to analyze the proteome of breast cancer (ZR-75-1 and MDA-MB-231) and breast epithelial (MCF-10A) cell lines induced to undergo apoptosis using a combination of doxorubicin and TRAIL administered in sequence (Dox-TRAIL). Apoptosis induction was confirmed using a caspase-3 activity assay. Comparative proteomic analysis between whole cell lysates of Dox-TRAIL and control samples revealed 56 differentially expressed spots (>= 2-fold change and p < 0.05) common to at least two cell lines. Of these, 19 proteins were identified yielding 11 unique protein identities: CFL1, EIF5A, HNRNPIC, KRT8, KRT18, LMNA, MYH9, NACA, RPLP0, RPLP2, and RAD23B. A subset of the identified proteins was validated by selected reaction monitoring (SRM) and Western blotting. Pathway analysis revealed that the differentially abundant proteins were associated with cell death, cellular organization, integrin-linked kinase signaling, and actin cytoskeleton signaling pathways. The 2D-DIGE analysis has yielded candidate biomarkers of response to treatment in breast cancer cell models. Their clinical utility will depend on validation using patient breast biopsies pre- and post-treatment with anticancer drugs.