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

Transcriptional profiling of synovial macrophages using minimally invasive ultrasound-guided synovial biopsies in rheumatoid arthritis

Objective Currently, there are no reliable biomarkers for predicting therapeutic response in patients with rheumatoid arthritis (RA). The synovium may unlock critical information for determining efficacy as reduction in numbers of sublining synovial macrophages remains the most reproducible biomarker. Thus, a clinically actionable method for collection of synovial tissue, which can be analyzed using high-throughput strategies, must become a reality. Methods Rheumatologists at six United States academic sites were trained in minimally invasive ultrasound-guided synovial tissue biopsy. Histology, fluorescence-activated cell sorting and RNA-seq were performed on biopsy synovial tissue from patients with RA and compared with osteoarthritis (OA) samples. An optimized protocol for digesting synovial tissue was developed to generate high quality RNA-seq libraries from isolated macrophage populations. Associations were determined between macrophage transcriptional profiles and clinical parameters of RA patients. Results Patients with RA reported minimal adverse effects in response to synovial biopsy. Comparable RNA quality was observed between synovial tissue and isolated macrophages from patients with RA and OA. Whole tissue samples from patients with RA demonstrated a high degree of transcriptional heterogeneity. In contrast, the transcriptional profile of isolated RA synovial macrophages highlighted a subpopulation of patients and identified six novel transcriptional modules that were associated with disease activity and therapy. Conclusion Performance of synovial tissue biopsies by rheumatologists in the United States is feasible and generates high-quality samples for research. By utilizing cutting-edge technologies on synovial biopsies with corresponding clinical information, a precision-based medicine approach for patients with RA is attainable

MCL1 is deregulated in subgroups of diffuse large B-cell lymphoma.

Myeloid cell leukemia-1 (MCL1) is an anti-apoptotic member of the BCL2 family that is deregulated in various solid and hematological malignancies. However, its role in the molecular pathogenesis of diffuse large B-cell lymphoma (DLBCL) is unclear. We analyzed gene expression profiling data from 350 DLBCL patient samples and detected that activated B-cell-like (ABC) DLBCLs express MCL1 at significantly higher levels compared with germinal center B-cell-like DLBCL patient samples (P=2.7 × 10(-10)). Immunohistochemistry confirmed high MCL1 protein expression predominantly in ABC DLBCL in an independent patient cohort (n=249; P=0.001). To elucidate molecular mechanisms leading to aberrant MCL1 expression, we analyzed array comparative genomic hybridization data of 203 DLBCL samples and identified recurrent chromosomal gains/amplifications of the MCL1 locus that occurred in 26% of ABC DLBCLs. In addition, aberrant STAT3 signaling contributed to high MCL1 expression in this subtype. Knockdown of MCL1 as well as treatment with the BH3-mimetic obatoclax induced apoptotic cell death in MCL1-positive DLBCL cell lines. In summary, MCL1 is deregulated in a significant fraction of ABC DLBCLs and contributes to therapy resistance. These data suggest that specific inhibition of MCL1 might be utilized therapeutically in a subset of DLBCLs

Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments

Distinct synovial tissue macrophage subsets regulate inflammation and remission in rheumatoid arthritis.

Immune-regulatory mechanisms of drug-free remission in rheumatoid arthritis (RA) are unknown. We hypothesized that synovial tissue macrophages (STM), which persist in remission, contribute to joint homeostasis. We used single-cell transcriptomics to profile 32,000 STMs and identified phenotypic changes in patients with early/active RA, treatment-refractory/active RA and RA in sustained remission. Each clinical state was characterized by different frequencies of nine discrete phenotypic clusters within four distinct STM subpopulations with diverse homeostatic, regulatory and inflammatory functions. This cellular atlas, combined with deep-phenotypic, spatial and functional analyses of synovial biopsy fluorescent activated cell sorted STMs, revealed two STM subpopulations (MerTKTREM2 and MerTKLYVE1) with unique remission transcriptomic signatures enriched in negative regulators of inflammation. These STMs were potent producers of inflammation-resolving lipid mediators and induced the repair response of synovial fibroblasts in vitro. A low proportion of MerTK STMs in remission was associated with increased risk of disease flare after treatment cessation. Therapeutic modulation of MerTK STM subpopulations could therefore be a potential treatment strategy for RA

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90)+HLA-DRAhi sublining fibroblasts, IL1B+ pro-inflammatory monocytes, ITGAX+TBX21+ autoimmune-associated B cells and PDCD1+ peripheral helper T (TPH) cells and follicular helper T (TFH) cells. We defined distinct subsets of CD8+ T cells characterized by GZMK+, GZMB+, and GNLY+ phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1+HLA-DRAhi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.</p

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry.

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90)HLA-DRA sublining fibroblasts, IL1B pro-inflammatory monocytes, ITGAXTBX21 autoimmune-associated B cells and PDCD1 peripheral helper T (T) cells and follicular helper T (T) cells. We defined distinct subsets of CD8 T cells characterized by GZMK, GZMB, and GNLY phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1HLA-DRA fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis

Practical algorithm to inform clinical decision‐making in the topical treatment of atopic dermatitis

Atopic dermatitis is a chronic relapsing, inflammatory skin disorder associated with skin barrier dysfunction, the prevalence of which has increased dramatically in developing countries. In this article, we propose a treatment algorithm for patients with mild-tomoderate and severe atopic dermatitis flares in daily clinical practice. An international panel of 15 dermatology and allergy experts from eight countries was formed to develop a practical algorithm for the treatment of patients with atopic dermatitis, with a particular focus on topical therapies. In cases of mild-to-moderate atopic dermatitis involving sensitive skin areas, the topical calcineurin inhibitor pimecrolimus should be applied twice daily at the first signs of atopic dermatitis. For other body locations, patients should apply a topical calcineurin inhibitor, either pimecrolimus or tacrolimus, twice daily at the first signs of atopic dermatitis, such as pruritus, or twice weekly in previously affected skin areas. Emollients should be used regularly. Patients experiencing acute atopic dermatitis flares in sensitive skin areas should apply a topical corticosteroid twice daily or alternate once-daily topical corticosteroid/topical calcineurin inhibitor until symptoms improve. Following improvement, topical corticosteroid therapy should be discontinued and patients switched to a topical calcineurin inhibitor. Maintenance therapy should include the use of pimecrolimus once daily for sensitive areas and tacrolimus for other body locations. This treatment algorithm can help guide clinical decision-making in the treatment of atopic dermatitis