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Biomedical subjects

Philip M Long

Publications and source records attributed to Philip M Long.

7 recordsLinked to original sources

Molecular changes from dysplastic nodule to hepatocellular carcinoma through gene expression profiling.

Progression of hepatocellular carcinoma (HCC) is a stepwise process that proceeds from pre-neoplastic lesions--including low-grade dysplastic nodules (LGDNs) and high-grade dysplastic nodules (HGDNs)--to advanced HCC. The molecular changes associated with this progression are unclear, however, and the morphological cues thought to distinguish pre-neoplastic lesions from well-differentiated HCC are not universally accepted. To understand the multistep process of hepato-carcinogenesis at the molecular level, we used oligo-nucleotide microarrays to investigate the transcription profiles of 50 hepatocellular nodular lesions ranging from LGDNs to primary HCC (Edmondson grades 1-3). We demonstrated that gene expression profiles can discriminate not only between dysplastic nodules and overt carcinoma but also between different histological grades of HCC via unsupervised hierarchical clustering with 10,376 genes. We identified 3,084 grade-associated genes, correlated with tumor progression, using one-way ANOVA and a one-versus-all unpooled t test. Functional assignment of these genes revealed discrete expression clusters representing grade-dependent biological properties of HCC. Using both diagonal linear discriminant analysis and support vector machines, we identified 240 genes that could accurately classify tumors according to histological grade, especially when attempting to discriminate LGDNs, HGDNs, and grade 1 HCC. In conclusion, a clear molecular demarcation between dysplastic nodules and overt HCC exists. The progression from grade 1 through grade 3 HCC is associated with changes in gene expression consistent with plausible functional consequences.

Carcinoma, Hepatocellular↗

Mutational dynamics of the SARS coronavirus in cell culture and human populations isolated in 2003.

BACKGROUND: The SARS coronavirus is the etiologic agent for the epidemic of the Severe Acute Respiratory Syndrome. The recent emergence of this new pathogen, the careful tracing of its transmission patterns, and the ability to propagate in culture allows the exploration of the mutational dynamics of the SARS-CoV in human populations. METHODS: We sequenced complete SARS-CoV genomes taken from primary human tissues (SIN3408, SIN3725V, SIN3765V), cultured isolates (SIN848, SIN846, SIN842, SIN845, SIN847, SIN849, SIN850, SIN852, SIN3408L), and five consecutive Vero cell passages (SIN2774_P1, SIN2774_P2, SIN2774_P3, SIN2774_P4, SIN2774_P5) arising from SIN2774 isolate. These represented individual patient samples, serial in vitro passages in cell culture, and paired human and cell culture isolates. Employing a refined mutation filtering scheme and constant mutation rate model, the mutation rates were estimated and the possible date of emergence was calculated. Phylogenetic analysis was used to uncover molecular relationships between the isolates. RESULTS: Close examination of whole genome sequence of 54 SARS-CoV isolates identified before 14th October 2003, including 22 from patients in Singapore, revealed the mutations engendered during human-to-Vero and Vero-to-human transmission as well as in multiple Vero cell passages in order to refine our analysis of human-to-human transmission. Though co-infection by different quasipecies in individual tissue samples is observed, the in vitro mutation rate of the SARS-CoV in Vero cell passage is negligible. The in vivo mutation rate, however, is consistent with estimates of other RNA viruses at approximately 5.7 x 10-6 nucleotide substitutions per site per day (0.17 mutations per genome per day), or two mutations per human passage (adjusted R-square = 0.4014). Using the immediate Hotel M contact isolates as roots, we observed that the SARS epidemic has generated four major genetic groups that are geographically associated: two Singapore isolates, one Taiwan isolate, and one North China isolate which appears most closely related to the putative SARS-CoV isolated from a palm civet. Non-synonymous mutations are centered in non-essential ORFs especially in structural and antigenic genes such as the S and M proteins, but these mutations did not distinguish the geographical groupings. However, no non-synonymous mutations were found in the 3CLpro and the polymerase genes. CONCLUSIONS: Our results show that the SARS-CoV is well adapted to growth in culture and did not appear to undergo specific selection in human populations. We further assessed that the putative origin of the SARS epidemic was in late October 2002 which is consistent with a recent estimate using cases from China. The greater sequence divergence in the structural and antigenic proteins and consistent deletions in the 3'--most portion of the viral genome suggest that certain selection pressures are interacting with the functional nature of these validated and putative ORFs.

Animals↗

Identification of discriminators of hepatoma by gene expression profiling using a minimal dataset approach.

The severity of hepatocellular carcinoma (HCC) and the lack of good diagnostic markers and treatment strategies have rendered the disease a major challenge. Previous microarray analyses of HCC were restricted to the selected tissue sample sets without validation on an independent series of tissue samples. We describe an approach to the identification of a composite discriminator cassette by intersecting different microarray datasets. We studied the global transcriptional profiles of matched HCC tumor and nontumor liver samples from 37 patients using cDNA (cDNA) microarrays. Application of nonparametric Wilcoxon statistical analyses (P < 1 x 10(-6)) and the criteria of 1.5-fold differential gene expression change resulted in the identification of 218 genes, including BMI-1, ERBB3, and those involved in the ubiquitin-proteasome pathway. Elevated ERBB2 and epidermal growth factor receptor (EGFR) expression levels were detected in ERBB3-expressing tumors, suggesting the presence of ERBB3 cognate partners. Comparison of our dataset with an earlier study of approximately 150 tissue sets identified multiple overlapping discriminator markers, suggesting good concordance of data despite differences in patient populations and technology platforms. These overlapping discriminator markers could distinguish HCC tumor from nontumor liver samples with reasonable precision and the features were unlikely to appear by chance, as measured by Monte Carlo simulations. More significantly, validation of the discriminator cassettes on an independent set of 58 liver biopsy specimens yielded greater than 93% prediction accuracy. In conclusion, these data indicate the robustness of expression profiling in marker discovery using limited patient tissue specimens as well as identify novel genes that are highly likely to be excellent markers for HCC diagnosis and treatment.

Biopsy↗

Breast cancer classification and prognosis based on gene expression profiles from a population-based study.

Comprehensive gene expression patterns generated from cDNA microarrays were correlated with detailed clinico-pathological characteristics and clinical outcome in an unselected group of 99 node-negative and node-positive breast cancer patients. Gene expression patterns were found to be strongly associated with estrogen receptor (ER) status and moderately associated with grade, but not associated with menopausal status, nodal status, or tumor size. Hierarchical cluster analysis segregated the tumors into two main groups based on their ER status, which correlated well with basal and luminal characteristics. Cox proportional hazards regression analysis identified 16 genes that were significantly associated with relapse-free survival at a stringent significance level of 0.001 to account for multiple comparisons. Of 231 genes previously reported by others [van't Veer, L. J., et al. (2002) Nature 415, 530-536] as being associated with survival, 93 probe elements overlapped with the set of 7,650 probe elements represented on the arrays used in this study. Hierarchical cluster analysis based on the set of 93 probe elements segregated our population into two distinct subgroups with different relapse-free survival (P < 0.03). The number of these 93 probe elements showing significant univariate association with relapse-free survival (P < 0.05) in the present study was 14, representing 11 unique genes. Genes involved in cell cycle, DNA replication, and chromosomal stability were consistently elevated in the various poor prognostic groups. In addition, glutathione S-transferase M3 emerged as an important survival marker in both studies. When taken together with other array studies, our results highlight the consistent biological and clinical associations with gene expression profiles.

Breast Neoplasms↗

Comparative full-length genome sequence analysis of 14 SARS coronavirus isolates and common mutations associated with putative origins of infection.

BACKGROUND: The cause of severe acute respiratory syndrome (SARS) has been identified as a new coronavirus. Whole genome sequence analysis of various isolates might provide an indication of potential strain differences of this new virus. Moreover, mutation analysis will help to develop effective vaccines. METHODS: We sequenced the entire SARS viral genome of cultured isolates from the index case (SIN2500) presenting in Singapore, from three primary contacts (SIN2774, SIN2748, and SIN2677), and one secondary contact (SIN2679). These sequences were compared with the isolates from Canada (TOR2), Hong Kong (CUHK-W1 and HKU39849), Hanoi (URBANI), Guangzhou (GZ01), and Beijing (BJ01, BJ02, BJ03, BJ04). FINDINGS: We identified 129 sequence variations among the 14 isolates, with 16 recurrent variant sequences. Common variant sequences at four loci define two distinct genotypes of the SARS virus. One genotype was linked with infections originating in Hotel M in Hong Kong, the second contained isolates from Hong Kong, Guangzhou, and Beijing with no association with Hotel M (p<0.0001). Moreover, other common sequence variants further distinguished the geographical origins of the isolates, especially between Singapore and Beijing. INTERPRETATION: Despite the recent onset of the SARS epidemic, genetic signatures are emerging that partition the worldwide SARS viral isolates into groups on the basis of contact source history and geography. These signatures can be used to trace sources of infection. In addition, a common variant associated with a non-conservative aminoacid change in the S1 region of the spike protein, suggests that immunological pressures might be starting to influence the evolution of the SARS virus in human populations.

Amino Acid Sequence↗

Optimal gene expression analysis by microarrays.

DNA microarrays make possible the rapid and comprehensive assessment of the transcriptional activity of a cell, and as such have proven valuable in assessing the molecular contributors to biological processes and in the classification of human cancers. The major challenge in using this technology is the analysis of its massive data output, which requires computational means for interpretation and a heightened need for quality data. The optimal analysis requires an accounting and control of the many sources of variance within the system, an understanding of the limitations of the statistical approaches, and the ability to make sense of the results through intelligent database interrogation.

Algorithms↗