Scheid, Adam D.

Abstract To test the hypothesis that complex immune phenotypes can be defined by stable gene expression profiles we are using a RNAseq-based transcriptome analysis to relate phenotypes of activated peripheral blood CD4+ cells from healthy subjects and stage IV melanoma patients to their freshly-isolated counterparts. We have defined molecular immune response signatures (MIRS) containing genes that consistently differentiate individuals from one another. Two different phenotypic groups are defined using this approach, both of which are mathematically distinct from randomly-selected groups. First, a MIRS generated using healthy donor T cells stimulated with α-CD3/CD28 beads defines a distinct response phenotype and successfully predicts 17 independent healthy subject and melanoma patient responses, demonstrating the predictive capability of the approach. Second, our comparison of melanoma patient signatures with those of healthy subjects revealed a group of healthy individuals with distinct expression signatures that did not cluster with those of any of the melanoma patients. These results indicate that our RNAseq-based transcriptome analysis has the potential to identify phenotypic groups as well as gene sets that have response-predictive capabilities. Our work has both discovery and translational implications, as our approach can be used to investigate complex genetic contributions to immune responses and predict how individual patients will respond to therapeutic interventions.

Abstract The complexity of molecular networks regulating the immune response presents challenges to measuring immune response potential in human populations. We measured gene expression in CD4+ peripheral blood cells from healthy subjects using RNAseq. RNA expression was assessed twice, one month apart to identify the subset of genes expressed stably within individuals over time yet discriminating individuals in a cohort. This immune response signature gene set then was used to identify and successfully order the immune response phenotypes of independent, unrelated subjects. Following a brief 4 hr stimulation of freshly isolated cells with anti-CD3/C28 antibody-coated beads, changes in gene expression were measured using a similar approach, defining individual response profiles and clustering response patterns. Examination of the RNA expression signatures of unstimulated CD4 cells revealed a gene subset which when analyzed for gene expression levels correctly aligned independent test subjects into the defined response-phenotype clusters following stimulation. Therefore, there exists a subset of genes stably expressed over time in circulating CD4+ cells which discriminate among individuals in a manner associated with immune response potential. Thus a systems approach can be used to describe the complex immune phenotypes of individuals in ways that might be useful in determining how individuals will respond to complex stimuli or in disease and treatment settings.

Abstract Breast tumors develop under environmental pressures with phenotypically variant cells generated by mutation and epigenetic changes providing the substrate for clonal selection. Chromosomal mutations are a feature of spontaneous breast tumors in the BALB-neuT mouse model. However, there is little evidence that specific changes in chromosomal structure or ploidy confer selective advantage in these spontaneous tumors. The prominent exception is a consistent loss of chromosome 4, a little understood feature common to several mouse tumors. We previously measured heterozygosity in spontaneous breast tumors from FVB X BALB-neuT F1 mice using Illumina’s Golden Gate assay. In addition to the expected gain and loss of heterozygosity (LOH) evident throughout the genomes of a cohort of spontaneous tumors, the assay also detected wide-spread stochastic pseudo-“LOH” at 600 discrete loci spread throughout the genome in unique patterns among the tumors. Several of these positions were examined by sequence analysis revealing no deviations from the WT sequences, suggesting the detected “LOH” may have been generated by epigenetic modification of DNA which altered sequence detection. While, epigenetically modified DNA templates recapitulated the observed “LOH” signals, no canonical CpG motifs were present in the majority of the 600 loci probed, suggesting that an unusual DNA modification could be responsible for the unexpected wide-spread stochastic structural changes in the breast tumor DNA. We next assessed whether these putative epigenetic changes in DNA structure might impact gene regulation, and have reported that the stochastic pattern observed as “LOH” in DNA was recapitulated in the transcriptomes in unique patterns among the tumors. A direct correlation between the number of “LOH” variants and the down regulation of hundreds of non-polymorphic genes in the transcriptome also was noted. Furthermore, pathway analyses of the genes exhibiting changes in allelic ratios in these tumors revealed significant enrichments within gene networks regulating tissue homeostasis and antigen presentation, providing strong evidence that the perturbations in gene expression translated into selectable tumor cell phenotypes. We now have extended this study to examine the relationship between the magnitude of change in the expression of genes mapping within the pathways regulating tissue homeostasis (Molecular Mechanisms of Cancer). A remarkable feature of the flagged genes is that the magnitude of change in gene expression was not great in each case, yet the biological consequences were strongly reflected in the evolutionary history of the tumors. Importantly, the polymorphisms marking the parental alleles are mostly silent, not altering the structure of the encoded products. Therefore magnitude and timing of gene expression are the likely determinants of phenotypic variation. Each tumor contained several outliers within the pathways regulating tissue homeostasis, suggesting that the integration of multiple small perturbations in the expression of genes comprising functional networks could influence the biology properties of the tumor cells. Overall expression of the loci marked by allelic outliers was significantly below the average expression found among tumors in the cohort highlighting the importance of down regulation of one allele in the establishment of selectable traits. We find a similar direct correlation of multiple small changes in the transcriptome of normal lymphocytes with immune response phenotypes, suggesting this principle of integration of multiple small deviations in gene expression applies widely to the phenotypes of normal cells, tumors, and by extension to organismic traits. Citation Format: Larry R Pease, Sara J Felts, Adam D Scheid, Xiaojia Tang, Krishna R Kalari. Phenotypes of breast tumor cells and normal lymphocytes are determined by the integration of minor changes in expression of multiple genes: A new dimension in quantitative inheritance [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-09-03.

Abstract Genome-wide identification and characterization of long noncoding RNAs (lncRNA) in individual immune cell lineages helps us better understand the driving mechanisms behind melanoma and advance personalized patient treatment. To elucidate the transcriptional landscape in diverse immune cell types of peripheral blood cells (PBC) in stage IV melanoma, we used whole transcriptome RNA sequencing to profile lncRNAs in CD4+, CD8+, and CD14+ PBC from 132 patient samples. Our integrative computational approach identified 27,625 expressed lncRNAs, 2,744 of which were novel. Both T cells (i.e., CD4+ and CD8+ PBC) and monocytes (i.e., CD14+ PBC) exhibited differential transcriptional expression profiles between patients with melanoma and healthy subjects. Cis- and trans-level coexpression analysis suggested that lncRNAs are potentially involved in many important immune-related pathways and the programmed cell death receptor 1 checkpoint pathways. We also identified nine gene coexpression modules significantly associated with melanoma status, all of which were significantly enriched for three mRNA translation processes. Age and melanoma traits closely correlated with each other, implying that melanoma contains age-associated immune changes. Our computational prediction analysis suggests that many cis- and trans-regulatory lncRNAs could interact with multiple transcriptional and posttranscriptional regulatory elements in CD4+, CD8+, and CD14+ PBC, respectively. These results provide novel insights into the regulatory mechanisms involving lncRNAs in individual immune cell types in melanoma and can help expedite cell type-specific immunotherapy treatments for such diseases. Significance: These findings elucidate melanoma-associated changes to the noncoding transcriptional landscape of distinct immune cell classes, thus providing cell type-specific guidance to targeted immunotherapy regimens. Cancer Res; 78(15); 4411–23. ©2018 AACR.

Abstract Human immunity exhibits remarkable heterogeneity among individuals, which engenders variable responses to immune perturbations in human populations. Population studies reveal that, in addition to interindividual heterogeneity, systemic immune signatures display longitudinal stability within individuals, and these signatures may reliably dictate how given individuals respond to immune perturbations. We hypothesize that analyzing relationships among these signatures at the population level may uncover baseline immune phenotypes that correspond with response outcomes to immune stimuli. To test this, we quantified global gene expression in peripheral blood CD4+ cells from healthy individuals at baseline and following CD3/CD28 stimulation at two time points 1 mo apart. Systemic CD4+ cell baseline and poststimulation molecular immune response signatures (MIRS) were defined by identifying genes expressed at levels that were stable between time points within individuals and differential among individuals in each state. Iterative differential gene expression analyses between all possible phenotypic groupings of at least three individuals using the baseline and stimulated MIRS gene sets revealed shared baseline and response phenotypic groupings, indicating the baseline MIRS contained determinants of immune responsiveness. Furthermore, significant numbers of shared phenotype-defining sets of determinants were identified in baseline data across independent healthy cohorts. Combining the cohorts and repeating the analyses resulted in identification of over 6000 baseline immune phenotypic groups, implying that the MIRS concept may be useful in many immune perturbation contexts. These findings demonstrate that patterns in complex gene expression variability can be used to define immune phenotypes and discover determinants of immune responsiveness.

Abstract Immunosuppression in the tumor microenvironment blunts vaccine-induced immune effectors. PD-1/B7-H1 is an important inhibitory axis in the tumor microenvironment. Our goal in this study was to determine the effect of blocking this inhibitory axis during and following vaccination against breast cancer. We observed that using anti-PD-1 antibody and a multipeptide vaccine (consisting of immunogenic peptides derived from breast cancer antigens, neu, legumain, and β-catenin) as a combination therapy regimen for the treatment of breast cancer–bearing mice prolonged the vaccine-induced progression-free survival period. This prolonged survival was associated with increase in number of Tc1 and Tc2 CD8 T cells with memory precursor phenotype, CD27+IL-7RhiT-betlo, and decrease in number of PD-1+ dendritic cells (DC) in regressing tumors and enhanced antigen reactivity of tumor-infiltrating CD8 T cells. It was also observed that blockade of PD-1 on tumor DCs enhanced IL-7R expression on CD8 T cells. Taken together, our results suggest that PD-1 blockade enhances breast cancer vaccine efficacy by altering both CD8 T cell and DC components of the tumor microenvironment. Given the recent success of anti-PD-1 monotherapy, our results are encouraging for developing combination therapies for the treatment of patients with cancer in which anti-PD-1 monotherapy alone may be ineffective (i.e., PD-L1–negative tumors). Cancer Res; 74(11); 2974–85. ©2014 AACR.