Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma.

Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA

Therapeutic Implications of Hepatitis C virus Resistance to Antiviral Drugs

Treatment of chronic hepatitis C is currently based on a combination of pegylated interferon-o! and ribavirin. Neither drug exerts direct selective pressure on viral functions, meaning that interferon-a/ribavirin treatment failure is not due to selection of interferon-a- or ribavirin-resistant viral variants. Several novel antiviral approaches are currently in preclinical or clinical development, and most target viral enzymes and functions, such as hepatitis C virus protease and polymerase. These new drugs all potentially select resistant viral variants both in vitro and in vivo, and resistance is therefore likely to become an important issue in clinical practice

Intrahepatic mRNA levels of SOCS1 and SOCS3 are associated with cirrhosis but do not predict virological response to therapy in chronic hepatitis C.

BACKGROUND: Antiviral treatment of chronic hepatitis C is not invariably successful, costly and associated with serious side-effects, and therefore should be indicated only when the chances of benefitting patients exceed the potential risks. The suppressor of cytokine signalling (SOCS) family members have been suggested to affect the rate of virological response to therapy, but the published evidence is conflicting. METHODS: We measured the intrahepatic SOCS1, SOCS3 and SOCS7 mRNA levels in 107 chronic hepatitis C patients and assessed their clinical and histological correlates with the virological response to therapy and with some factors known for affecting treatment outcome. RESULTS: By multivariate analysis, SOCS1, SOCS3 and SOCS7 mRNA levels were not associated with rapid or sustained virological response. Similarly, no association was found between the levels of any intrahepatic SOCS mRNA and those of the homeostasis model assessment of insulin resistance. Conversely, SOCS1 (OR 2.185, 95% CI 1.223-3.906, P=0.0083) and SOCS3 (OR 40.601, 95% CI 2.357-699.25, P=0.0108) mRNA level (but not SOCS7), together with age (OR 1.156, 95% CI 1.049-1.275, P=0.0036), were independently associated with cirrhosis. CONCLUSIONS: Intrahepatic SOCS1, SOCS3 and SOCS7 mRNA levels do not predict virological response to therapy in chronic hepatitis C. The association between SOCS1, SOCS3 and cirrhosis warrants further study