Genotype-Dependent Tumor Regression in Marek’s Disease Mediated at the Level of Tumor Immunity

Marek’s disease (MD) of chickens is a unique natural model of Hodgkin’s and Non Hodgkin’s lymphomas in which the neoplastically-transformed cells over-express CD30 (CD30hi) antigen. All chicken genotypes can be infected with MD virus and develop microscopic lymphomas. From 21 days post infection (dpi) microscopic lymphomas regress in resistant chickens but, in contrast, they progress to gross lymphomas in susceptible chickens. Here we test our hypothesis that in resistant chickens at 21 dpi the tissue microenvironment is pro T-helper (Th)-1 and compatible with cytotoxic T lymphocyte (CTL) immunity but in susceptible lines it is pro Th-2 or pro T-regulatory (T-reg) and antagonistic to CTL immunity. We used the B2, non-MHC-associated, MD resistance/susceptibility system (line [L]61/line [L]72) and quantified the levels of key mRNAs that can be used to define Th-1 (IL-2, IL-12, IL-18, IFNγ), Th-2 (IL-4, IL-10) and T-reg (TGFβ, GPR-83, CTLA-4, SMAD-7) lymphocyte phenotypes. We measured gene expression in both whole tissues (represents tissue microenvironment and tumor microenvironment) and in the lymphoma lesions (tumor microenvironment) themselves. Gene ontology-based modeling of our results shows that the dominant phenotype in whole tissue as well as in microscopic lymphoma lesions, is pro T-reg in both L61 and L72 but a minor pro Th-1 and anti Th-2 tissue microenvironment exists in L61 whereas there is an anti Th-1 and pro Th-2 tissue microenvironment in L72. The tumor microenvironment per se is pro T-reg, anti Th-1 and pro Th-2 in both L61 and L72. Together our data suggests that the neoplastic transformation is essentially the same in both L61 and L72 and that resistance/susceptibility is mediated at the level of tumor immunity in the tissues

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases