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Dr. Martin C. Mihm, Jr.'s innovative work on the dysplastic nevus achieved a milestone in his chapter in the World Health Organisation Classification of Skin Tumours (WHO-C). WHO-C presents a dichotomous classification (high-grade versus low-grade dysplastic nevi) and a quantitative metric to assess melanocytic nuclear enlargement. The Duke classification is a related approach that provides mostly quantitative histopathologic criteria for dysplastic nevi and gives due weight to architectural features as well as cytology. This paper proposes and illustrates updated criteria for scoring and grading melanocytic dysplasia, incorporating some of the definitions and categories of WHO-C, while refining the quantitative and architectural elements of the Duke grading system to facilitate more detailed and precise assessment of dysplastic nevi., (© 2024 The Author(s). Journal of Cutaneous Pathology published by John Wiley & Sons Ltd.)

For genome-wide association studies, we propose a new method for identifying significant biological pathways. In this approach, we aggregate data across single-nucleotide polymorphisms to obtain summary measures at the gene level. We then use a hierarchical Bayesian model, which takes the gene-level summary measures as data, in order to evaluate the relevance of each pathway to an outcome of interest (e.g., disease status). Although shifting the focus of analysis from individual genes to pathways has proven to improve the statistical power and provide more robust results, such methods tend to eliminate a large number of genes whose pathways are unknown. For these genes, we propose to use a Bayesian multinomial logit model to predict the associated pathways by using the genes with known pathways as the training data. Our hierarchical Bayesian model takes the uncertainty regarding the pathway predictions into account while assessing the significance of pathways. We apply our method to two independent studies on type 2 diabetes and show that the overlap between the results from the two studies is statistically significant. We also evaluate our approach on the basis of simulated data., (Copyright © 2012 John Wiley & Sons, Ltd.)

We propose a hierarchical Bayesian model for analyzing gene expression data to identify pathways differentiating between two biological states (e.g., cancer vs. non-cancer and mutant vs. normal). Finding significant pathways can improve our understanding of biological processes. When the biological process of interest is related to a specific disease, eliciting a better understanding of the underlying pathways can lead to designing a more effective treatment. We apply our method to data obtained by interrogating the mutational status of p53 in 50 cancer cell lines (33 mutated and 17 normal). We identify several significant pathways with strong biological connections. We show that our approach provides a natural framework for incorporating prior biological information, and it has the best overall performance in terms of correctly identifying significant pathways compared to several alternative methods.

Histologic transformation (HT) of follicular lymphoma to diffuse large B-cell lymphoma (DLBCL-t) is associated with accelerated disease course and drastically worse outcome, yet the underlying mechanisms are poorly understood. We show that a network of gene transcriptional modules underlies HT. Central to the network hierarchy is a signature strikingly enriched for pluripotency-related genes. These genes are typically expressed in embryonic stem cells (ESCs), including MYC and its direct targets. This core ESC-like program was independent of proliferation/cell-cycle and overlapped but was distinct from normal B-cell transcriptional programs. Furthermore, we show that the ESC program is correlated with transcriptional programs maintaining tumor phenotype in transgenic MYC-driven mouse models of lymphoma. Although our approach was to identify HT mechanisms rather than to derive an optimal survival predictor, a model based on ESC/differentiation programs stratified patient outcomes in 2 independent patient cohorts and was predictive of propensity of follicular lymphoma tumors to transform. Transformation was associated with an expression signature combining high expression of ESC transcriptional programs with reduced expression of stromal programs. Together, these findings suggest a central role for an ESC-like signature in the mechanism of HT and provide new clues for potential therapeutic targets.

Background: Detection of single cell epitopes has been a mainstay of immunophenotyping for over three decades, primarily using fluorescence techniques for quantitation. Fluorescence has broad overlapping spectra, limiting multiplexing abilities., Methodology/principal Findings: To expand upon current detection systems, we developed a novel method for multi-color immuno-detection in single cells using "Composite Organic-Inorganic Nanoparticles" (COINs) Raman nanoparticles. COINs are Surface-Enhanced Raman Scattering (SERS) nanoparticles, with unique Raman spectra. To measure Raman spectra in single cells, we constructed an automated, compact, low noise and sensitive Raman microscopy device (Integrated Raman BioAnalyzer). Using this technology, we detected proteins expressed on the surface in single cells that distinguish T-cells among human blood cells. Finally, we measured intracellular phosphorylation of Stat1 (Y701) and Stat6 (Y641), with results comparable to flow cytometry., Conclusions/significance: Thus, we have demonstrated the practicality of applying COIN nanoparticles for measuring intracellular phosphorylation, offering new possibilities to expand on the current fluorescent technology used for immunoassays in single cells.

We demonstrate the use of electron microscopy as a powerful characterization tool to identify and locate antibody-conjugated composite organic-inorganic nanoparticle (COINs) surface enhanced Raman scattering (SERS) nanoparticles on cells. U937 leukemia cells labeled with antibody CD54-conjugated COINs were characterized in their native, hydrated state using wet scanning electron microscopy (SEM) and in their dehydrated state using high-resolution SEM. In both cases, the backscattered electron (BSE) detector was used to detect and identify the silver constituents in COINs due to its high sensitivity to atomic number variations within a specimen. The imaging and analytical capabilities in the SEM were further complemented by higher resolution transmission electron microscopy (TEM) images and scanning Auger electron spectroscopy (AES) data to give reliable and high-resolution information about nanoparticles and their binding to cell surface antigens.

MYC overexpression has been implicated in the pathogenesis of most types of human cancers. MYC is likely to contribute to tumorigenesis by its effects on global gene expression. Previously, we have shown that the loss of MYC overexpression is sufficient to reverse tumorigenesis. Here, we show that there is a precise threshold level of MYC expression required for maintaining the tumor phenotype, whereupon there is a switch from a gene expression program of proliferation to a state of proliferative arrest and apoptosis. Oligonucleotide microarray analysis and quantitative PCR were used to identify changes in expression in 3,921 genes, of which 2,348 were down-regulated and 1,573 were up-regulated. Critical changes in gene expression occurred at or near the MYC threshold, including genes implicated in the regulation of the G(1)-S and G(2)-M cell cycle checkpoints and death receptor/apoptosis signaling. Using two-dimensional protein analysis followed by mass spectrometry, phospho-flow fluorescence-activated cell sorting, and antibody arrays, we also identified changes at the protein level that contributed to MYC-dependent tumor regression. Proteins involved in mRNA translation decreased below threshold levels of MYC. Thus, at the MYC threshold, there is a loss of its ability to maintain tumorigenesis, with associated shifts in gene and protein expression that reestablish cell cycle checkpoints, halt protein translation, and promote apoptosis.

Statins are a class of drugs that inhibit 3-hydroxy-3-methylglutaryl-coenzyme A (HMGcoA) reductase, a critical enzyme in the mevalonate pathway. Several reports document that statins may prevent different human cancers. However, whether or not statins can prevent cancer is controversial due to discordant results. One possible explanation for these conflicting conclusions is that only some tumors or specific statins may be effective. Here, we demonstrate in an in vivo transgenic model in which atorvastatin reverses and prevents the onset of MYC-induced lymphomagenesis, but fails to reverse or prevent tumorigenesis in the presence of constitutively activated K-Ras (G12D). Using phosphoprotein fluorescence-activated cell sorter (FACS) analysis, atorvastatin treatment was found to result in the inactivation of the Ras and ERK1/2 signaling pathways associated with the dephosphorylation and inactivation of MYC. Correspondingly, tumors with a constitutively activated K-Ras (G12D) did not exhibit dephosphorylation of ERK1/2 and MYC. Atorvastatin's effects on MYC were specific to the inhibition of HMGcoA reductase, as treatment with mevalonate, the product of HMG-CoA reductase activity, abrogated these effects and inhibited the ability of atorvastatin to reverse or suppress tumorigenesis. Also, RNAi directed at HMGcoA reductase was sufficient to abrogate the neoplastic properties of MYC-induced tumors. Thus, atorvastatin, by inhibiting HMGcoA reductase, induces changes in phosphoprotein signaling that in turn prevent MYC-induced lymphomagenesis.

The inactivation of the MYC oncogene alone can reverse tumorigenesis. Upon MYC inactivation, tumors stereotypically reverse, undergoing proliferative arrest, cellular differentiation and/or apoptosis. The precise consequences of MYC inactivation appear to depend upon both genetic and epigenetic parameters. In some types of cancer following MYC inactivation, tumor cells become well differentiated and biologically and histologically normal, inducing sustained tumor regression. However, in some cases, these normal-appearing cells are actually dormant tumor cells and upon MYC reactivation they rapidly recover their tumorigenic properties. Future therapies to treat cancer will need to address the possibility that tumor cells can camouflage a normal phenotype following treatment, resting in a dormant, latently cancerous state.

Upon MYC inactivation, tumors variously undergo proliferative arrest, cellular differentiation, and apoptosis and in some cases, apparently permanently revoking tumorigenesis. In liver tumor cells, we recently showed that MYC inactivation uncovers stem cell properties and triggers differentiation, but in this case, their neoplastic properties are restorable by MYC reactivation. Thus, whereas oncogene inactivation can push cancer to the brink of normalcy, some cells retain the latent capacity to turn cancerous again, arguing that they may exist in a state of tumor dormancy.

Hepatocellular carcinoma is generally refractory to clinical treatment. Here, we report that inactivation of the MYC oncogene is sufficient to induce sustained regression of invasive liver cancers. MYC inactivation resulted en masse in tumour cells differentiating into hepatocytes and biliary cells forming bile duct structures, and this was associated with rapid loss of expression of the tumour marker alpha-fetoprotein, the increase in expression of liver cell markers cytokeratin 8 and carcinoembryonic antigen, and in some cells the liver stem cell marker cytokeratin 19. Using in vivo bioluminescence imaging we found that many of these tumour cells remained dormant as long as MYC remain inactivated; however, MYC reactivation immediately restored their neoplastic features. Using array comparative genomic hybridization we confirmed that these dormant liver cells and the restored tumour retained the identical molecular signature and hence were clonally derived from the tumour cells. Our results show how oncogene inactivation may reverse tumorigenesis in the most clinically difficult cancers. Oncogene inactivation uncovers the pluripotent capacity of tumours to differentiate into normal cellular lineages and tissue structures, while retaining their latent potential to become cancerous, and hence existing in a state of tumour dormancy.

The expression of CD5 increases progressively as thymocytes mature. We have shown that CD5 expression is controlled by a tissue-specific regulatory promoter located upstream of the CD5 translation start sites. Deletion of this regulatory promoter, which contains three potential transcription factor binding sites (CCAAT, kappa E2, and ets) reduces the promoter activity to basal level. Of these sites, only ets proved essential for CD5 expression in T cell lines. Here, we introduce a role for the E47 transcription factor and the CD5 promoter kappa E2 site in regulating CD5 expression during thymocyte development. Using T cell lines, we show that (i) mutation of the kappa E2 site in the CD5 regulatory promoter results in a significant elevation of CD5 promoter activity; (ii) the E47 transcription factor binds to the kappa E2 site; and (iii) overexpression of E47 inhibits CD5 expression. We then show, in high-dimensional fluorescence-activated cell sorting studies with primary thymocytes at successive developmental stages, that (i) intracellular E47 levels decrease as surface CD5 expression increases; (ii) E47 expression is down-regulated and CD5 expression is correspondingly up-regulated in DN3 thymocytes in RAG-2-deficient mice injected with anti-CD3 to mimic pre-T cell receptor stimulation; and (iii) E47 expression is down-regulated and CD5 expression is up-regulated when double positive thymocytes are stimulated in vitro with anti-CD3. Based on these data, we propose that E47 negatively regulates CD5 expression by interacting with the kappa E2 site in the CD5 regulatory promoter and that decreases in E47 in response to developmental signals are critical to the progressive increase in CD5 expression as thymocytes mature.

The ability to model cancer in the mouse has provided a robust methodology to dissect the molecular etiology of cancer. These models serve as potentially powerful platforms to preclinically evaluate novel therapeutics. In particular, the recent development of strategies to conditionally induce the or knockout the function of genes in a tissue specific manner has enabled investigators to engineer mice to demonstrate that the targeted inactivation of specific oncogenes can be effective in inducing sustained regression of tumors. Thus, these animal models will be useful to define the specific genes that will be therapeutically useful to target for the treatment of particular human cancers.