Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer.

Background: Technological advances enable the cost-effective acquisition of Multi-Modal Data Sets (MMDS) composed of measurements for multiple, high-dimensional data types obtained from a common set of bio-samples. The joint analysis of the data matrices associated with the different data types of a MMDS should provide a more focused view of the biology underlying complex diseases such as cancer that would not be apparent from the analysis of a single data type alone. As multi-modal data rapidly accumulate in research laboratories and public databases such as The Cancer Genome Atlas (TCGA), the translation of such data into clinically actionable knowledge has been slowed by the lack of computational tools capable of analyzing MMDSs.

Comparison of genome-scale DNA methylation profiles in hepatocellular carcinoma by viral status.

Hepatocellular carcinoma (HCC) incidence has steadily increased in the US over the past 30 years. Our understanding of epigenetic regulation in HCC is still limited, especially the impact of hepatitis B virus (HBV) or hepatitis C virus (HCV) infection on aberrant DNA methylation. We performed genome-wide DNA methylation profiling in 33 fresh frozen tumor samples, including 10 HBV-HCC, 13 HCV-HCC, and 10 non-infected (NIV-HCC) using the Illumina HumanMethylation450 BeadChip.

Metabolic characteristics distinguishing intrahepatic cholangiocarcinoma: a negative pilot study of (18)F-fluorocholine PET/CT clarified by transcriptomic analysis.

PET using fluorine-18 fluorocholine ((18)F-fluorocholine) may detect malignancies that involve altered choline metabolism. While (18)F-fluorocholine PET/CT has shown greater sensitivity for detecting hepatocellular carcinoma (HCC) than (18)F-fluoro-D-deoxyglucose (FDG) PET/CT, it is not known whether it can also detect intrahepatic cholangiocarcinoma (ICC), a less common form of primary liver cancer. Clinical, radiographic, and histopathologic data from 5 patients with ICC and 23 patients with HCC from a diagnostic trial of liver (18)F-fluorocholine PET/CT imaging were analyzed to preliminarily evaluate (18)F-fluorocholine PET/CT for ICC.

Continuous exposure to chrysotile asbestos can cause transformation of human mesothelial cells via HMGB1 and TNF-α signaling.

Malignant mesothelioma is strongly associated with asbestos exposure. Among asbestos fibers, crocidolite is considered the most and chrysotile the least oncogenic. Chrysotile accounts for more than 90% of the asbestos used worldwide, but its capacity to induce malignant mesothelioma is still debated.

Viral hepatitis markers in liver tissue in relation to serostatus in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) incidence is increasing in the United States. Hepatitis B virus (HBV) and hepatitis C virus (HCV) are major causes of HCC. Hepatitis infection in patients with HCC is generally diagnosed by serology, which is not always consistent with the presence of HBV and HCV in the liver.

Elucidating the landscape of aberrant DNA methylation in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most common cancers and frequently presents with an advanced disease at diagnosis. There is only limited knowledge of genome-scale methylation changes in HCC.

Methods And Findings: We performed genome-wide methylation profiling in a total of 47 samples including 27 HCC and 20 adjacent normal liver tissues using the Illumina HumanMethylation450 BeadChip.

Healthcare disparities in Asians and Pacific Islanders with hepatocellular cancer.

Background: Hawaii has the highest incidence of hepatocellular cancer (HCC) in the United States and the largest proportion of Asians and Pacific Islanders. HCC studies generally combine these groups into 1 ethnicity, and we sought to examine differences between Asian and Pacific Islander subpopulations.

Methods: Demographic, clinical, and treatment data for 617 patients with HCC (420 Asians, 114 whites, and 83 Pacific Islanders) were reviewed.

Initial neural net construction for the detection of cervical intraepithelial neoplasia by fluorescence imaging.

Objective: The aim of this study was to initiate neural net construction for the detection of cervical intraepithelial neoplasia by fluorescence imaging.

Study Design: Thirty-three women with abnormal Papanicolaou smears underwent fluorescence imaging during colposcopy. With the use of >4000 training pixels and >1000 test pixels, intrapatient nets were constructed from the spectral data of 17 women.