MSMAD: a computationally efficient method for the analysis of noisy array CGH data

High Keratin 8/18 Ratio Predicts Aggressive Hepatocellular Cancer Phenotype

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 termed Mallory-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: We analyzed 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.

Keratin 18-deficiency results in steatohepatitis and liver tumors in old mice: A model of steatohepatitis-associated liver carcinogenesis

Backround: Steatohepatitis (SH)-associated liver carcinogenesis is an increasingly important issue in clinical medicine. SH is morphologically characterized by steatosis, hepatocyte injury, ballooning, hepatocytic cytoplasmic inclusions termed Mallory-Denk bodies (MDBs), inflammation and fibrosis.

RESULTS

17-20-months-old Krt18-/- and Krt18+/- mice in contrast to wt mice spontaneously developed liver lesions closely resembling the morphological spectrum of human SH as well as liver tumors. The pathologic alterations were more pronounced in Krt18-/- than in Krt18+/- mice. The frequency of liver tumors with male predominance was significantly higher in Krt18-/- compared to age-matched Krt18+/- and wt mice. Krt18-deficient tumors in contrast to wt animals displayed SH features and often pleomorphic morphology. aCGH analysis of tumors revealed chromosomal aberrations in Krt18-/- liver tumors, affecting loci of oncogenes and tumor suppressor genes.

MATERIALS AND METHODS

Livers of 3-, 6-, 12- and 17-20-months-old aged wild type (wt), Krt18+/- and Krt18-/- (129P2/OlaHsd background) mice were analyzed by light and immunofluorescence microscopy as well as immunohistochemistry. Liver tumors arising in aged mice were analyzed by array comparative genomic hybridization (aCGH).

CONCLUSIONS

Our findings show that K18 deficiency of hepatocytes leads to steatosis, increasing with age, and finally to SH. K18 deficiency and age promote liver tumor development in mice, frequently on the basis of chromosomal instability, resembling human HCC with stemness features.

Penalized weighted low-rank approximation for robust recovery of recurrent copy number variations

BACKGROUND

Copy number variation (CNV) analysis has become one of the most important research areas for understanding complex disease. With increasing resolution of array-based comparative genomic hybridization (aCGH) arrays, more and more raw copy number data are collected for multiple arrays. It is natural to realize the co-existence of both recurrent and individual-specific CNVs, together with the possible data contamination during the data generation process. Therefore, there is a great need for an efficient and robust statistical model for simultaneous recovery of both recurrent and individual-specific CNVs.

RESULT

We develop a penalized weighted low-rank approximation method (WPLA) for robust recovery of recurrent CNVs. In particular, we formulate multiple aCGH arrays into a realization of a hidden low-rank matrix with some random noises and let an additional weight matrix account for those individual-specific effects. Thus, we do not restrict the random noise to be normally distributed, or even homogeneous. We show its performance through three real datasets and twelve synthetic datasets from different types of recurrent CNV regions associated with either normal random errors or heavily contaminated errors.

CONCLUSION

Our numerical experiments have demonstrated that the WPLA can successfully recover the recurrent CNV patterns from raw data under different scenarios. Compared with two other recent methods, it performs the best regarding its ability to simultaneously detect both recurrent and individual-specific CNVs under normal random errors. More importantly, the WPLA is the only method which can effectively recover the recurrent CNVs region when the data is heavily contaminated.

Visualization of genomic changes by segmented smoothing using an L0 penalty

Copy number variations (CNV) and allelic imbalance in tumor tissue can show strong segmentation. Their graphical presentation can be enhanced by appropriate smoothing. Existing signal and scatterplot smoothers do not respect segmentation well. We present novel algorithms that use a penalty on the L(0) norm of differences of neighboring values. Visualization is our main goal, but we compare classification performance to that of VEGA.

Post-genomics of Neisseria meningitidis: an update

Neisseria meningitidis infection still remains a major life-threatening bacterial disease worldwide. The availability of bacterial genomic sequences generated a paradigm shift in microbiological and vaccines sciences, and post-genomics (comparative genomics, functional genomics, proteomics and a combination/evolution of these techniques) played important roles in elucidating bacterial biological complexity and pathogenic traits, at the same time accelerating the development of therapeutic drugs and vaccines. This article summarizes the most recent technological and scientific advances in meningococcal biology and pathogenesis aimed at the development and characterization of vaccines against the pathogenic meningococci.

A robust penalized method for the analysis of noisy DNA copy number data

BACKGROUND

Deletions and amplifications of the human genomic DNA copy number are the causes of numerous diseases, such as, various forms of cancer. Therefore, the detection of DNA copy number variations (CNV) is important in understanding the genetic basis of many diseases. Various techniques and platforms have been developed for genome-wide analysis of DNA copy number, such as, array-based comparative genomic hybridization (aCGH) and high-resolution mapping with high-density tiling oligonucleotide arrays. Since complicated biological and experimental processes are often associated with these platforms, data can be potentially contaminated by outliers.

RESULTS

We propose a penalized LAD regression model with the adaptive fused lasso penalty for detecting CNV. This method contains robust properties and incorporates both the spatial dependence and sparsity of CNV into the analysis. Our simulation studies and real data analysis indicate that the proposed method can correctly detect the numbers and locations of the true breakpoints while appropriately controlling the false positives.

CONCLUSIONS

The proposed method has three advantages for detecting CNV change points: it contains robustness properties; incorporates both spatial dependence and sparsity; and estimates the true values at each marker accurately.

Microarray comparative genomic hybridisation analysis incorporating genomic organisation, and application to enterobacterial plant pathogens

Microarray comparative genomic hybridisation (aCGH) provides an estimate of the relative abundance of genomic DNA (gDNA) taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain.We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043) and Dickeya dadantii 3937 (Dda3937); and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE) Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937.Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic 'accessory' genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.

Postgenomics of Neisseria meningitidis: an update

Neisseria meningitidis infection represents a major life-threatening bacterial disease worldwide. Genomics has revolutionized every aspect of the field of microbiology. As a consequence of genome sequencing, the postgenomic era commenced 15 years ago. Comparative genomics, functional genomics and proteomics, as well as a combination of these techniques, will play important roles in providing vital information regarding bacterial biological complexity and pathogenic traits, and accelerate the development of therapeutic drugs and vaccines for combating infections. This review summarizes the current knowledge regarding different approaches aimed to shed light on meningococcal biology and pathogenesis, and to accelerate the development and characterization of vaccines against pathogenic meningococci.