multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles

Clustering Gene Expressions Using the Table Invitation Prior

A prior for Bayesian nonparametric clustering called the Table Invitation Prior (TIP) is used to cluster gene expression data. TIP uses information concerning the pairwise distances between subjects (e.g., gene expression samples) and automatically estimates the number of clusters. TIP's hyperparameters are estimated using a univariate multiple change point detection algorithm with respect to the subject distances, and thus TIP does not require an analyst's intervention for estimating hyperparameters. A Gibbs sampling algorithm is provided, and TIP is used in conjunction with a Normal-Inverse-Wishart likelihood to cluster 801 gene expression samples, each of which belongs to one of five different types of cancer.

Machine learning implicates the IL-18 signaling axis in severe asthma

Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous studies of the Severe Asthma Research Program (SARP) cohort linked gene expression changes to specific clinical and physiologic characteristics. While invaluable for hypothesis generation, these data include extensive candidate gene lists that complicate target identification and validation. In this analysis, we performed unsupervised clustering of the SARP cohort using bronchial epithelial cell gene expression data, identifying a transcriptional signature for participants suffering exacerbation-prone asthma with impaired lung function. Clinically, participants in this asthma cluster exhibited a mixed inflammatory process and bore transcriptional hallmarks of NF-κB and activator protein 1 (AP-1) activation, despite high corticosteroid exposure. Using supervised machine learning, we found a set of 31 genes that classified patients with high accuracy and could reconstitute clinical and transcriptional hallmarks of our patient clustering in an external cohort. Of these genes, IL18R1 (IL-18 Receptor 1) negatively associated with lung function and was highly expressed in the most severe patient cluster. We validated IL18R1 protein expression in lung tissue and identified downstream NF-κB and AP-1 activity, supporting IL-18 signaling in severe asthma pathogenesis and highlighting this approach for gene and pathway discovery.

Prospective clinical trial testing COXEN-based gene expression models of chemosensitivity in dogs with spontaneous osteosarcoma

BACKGROUND

This study is a prospective clinical trial in dogs with osteosarcoma testing a gene expression model (GEM) predicting the chemosensitivity of tumors to carboplatin (CARBO) or doxorubicin (DOX) developed using the COXEN method.

PATIENTS AND METHODS

Sixty dogs with appendicular osteosarcoma were enrolled in this trial. RNA isolation and gene expression profiling were conducted with 2 biopsies for 54/63 screened tumors, and with a single biopsy for 9 tumors. Resulting gene expression data were used for calculation of a COXEN score for CARBO and DOX based on a previous study showing the significance of this predictor on patient outcome utilizing retrospective data (BMC Bioinformatics 17:93). Dogs were assigned adjuvant CARBO, DOX or the combination based on the results of the COXEN score following surgical removal of the tumor via amputation and were monitored for disease progression by chest radiograph every 2 months.

RESULTS

The COXEN predictor of chemosensitivity to CARBO or DOX was not a significant predictor of progression-free interval or overall survival for the trial participants. The calculation of DOX COXEN score using gene expression data from two independent biopsies of the same tumor were highly correlated (P < 0.0001), whereas the calculated CARBO COXEN score was not (P = 0.3039).

CONCLUSION

The COXEN predictor of chemosensitivity to CARBO or DOX is not a significant predictor of outcome when utilized in this prospective study. This trial represents the first prospective trial of a GEM predictor of chemosensitivity and establishes pet dogs with cancer as viable surrogates for prospective trials of prognostic indicators.

Genome-Wide Chromatin Analysis of FFPE Tissues Using a Dual-Arm Robot with Clinical Potential

Although chromatin immunoprecipitation and next-generation sequencing (ChIP-seq) using formalin-fixed paraffin-embedded tissue (FFPE) has been reported, it remained elusive whether they retained accurate transcription factor binding. Here, we developed a method to identify the binding sites of the insulator transcription factor CTCF and the genome-wide distribution of histone modifications involved in transcriptional activation. Importantly, we provide evidence that the ChIP-seq datasets obtained from FFPE samples are similar to or even better than the data for corresponding fresh-frozen samples, indicating that FFPE samples are compatible with ChIP-seq analysis. H3K27ac ChIP-seq analyses of 69 FFPE samples using a dual-arm robot revealed that driver mutations in EGFR were distinguishable from pan-negative cases and were relatively homogeneous as a group in lung adenocarcinomas. Thus, our results demonstrate that FFPE samples are an important source for epigenomic research, enabling the study of histone modifications, nuclear chromatin structure, and clinical data.

ParticleMDI: particle Monte Carlo methods for the cluster analysis of multiple datasets with applications to cancer subtype identification

We present a novel nonparametric Bayesian approach for performing cluster analysis in a context where observational units have data arising from multiple sources. Our approach uses a particle Gibbs sampler for inference in which cluster allocations are jointly updated using a conditional particle filter within a Gibbs sampler, improving the mixing of the MCMC chain. We develop several approaches to improving the computational performance of our algorithm. These methods can achieve greater than an order-of-magnitude improvement in performance at no cost to accuracy and can be applied more broadly to Bayesian inference for mixture models with a single dataset. We apply our algorithm to the discovery of risk cohorts amongst 243 patients presenting with kidney renal clear cell carcinoma, using samples from the Cancer Genome Atlas, for which there are gene expression, copy number variation, DNA methylation, protein expression and microRNA data. We identify 4 distinct consensus subtypes and show they are prognostic for survival rate ($$p < 0.0001$$ p < 0.0001 ).

Antibody targeting of B7-H4 enhances the immune response in urothelial carcinoma

Patients with locally advanced and metastatic urothelial carcinoma have a low survival rate (median 15.7 months, 13.1-17.8), with only a 23% response rate to monotherapy treatment with anti-PDL1 checkpoint immunotherapy. To identify new therapeutic targets, we profiled the immune regulatory signatures during murine cancer development using the BBN carcinogen and identified an increase in the expression of the T cell inhibitory protein B7-H4 (VTCN1, B7S1, B7X). B7-H4 expression temporally correlated with decreased lymphocyte infiltration. While the increase in B7-H4 expression within the bladder by CD11b+ monocytes is shared with human cancers, B7-H4 expression has not been previously identified in other murine cancer models. Higher expression of B7-H4 was associated with worse survival in muscle-invasive bladder cancer in humans, and increased B7-H4 expression was identified in luminal and luminal-papillary subtypes of bladder cancer. Evaluation of B7-H4 by single-cell RNA-Seq and immune mass cytometry of human bladder tumors found that B7-H4 is expressed in both the epithelium of urothelial carcinoma and CD68+ macrophages within the tumor. To investigate the function of B7-H4, treatment of human monocyte and T cell co-cultures with a B7-H4 blocking antibody resulted in enhanced IFN-γ secretion by CD4+ and CD8+ T cells. Additionally, anti-B7-H4 antibody treatment of BBN-carcinogen bladder cancers resulted in decreased tumor size, increased CD8+ T cell infiltration within the bladder, and a complimentary decrease in tumor-infiltrating T regulatory cells (Tregs). Furthermore, treatment with a combination of anti-PD-1 and anti-B7-H4 antibodies resulted in a significant reduction in tumor stage, a reduction in tumor size, and an increased level of tumor necrosis. These findings suggest that antibodies targeting B7-H4 may be a viable strategy for bladder cancers unresponsive to PD-1 checkpoint inhibitors.

The effect of H1N1 vaccination on serum miRNA expression in children: A tale of caution for microRNA microarray studies

Background

MicroRNAs (miRNAs) are a class of small regulatory RNAs around 21–25 nucleotides in length which govern many aspects of immunity including the host innate and adaptive responses to infection. RT-qPCR studies of select microRNAs show that vaccination alters the expression circulating microRNAs but the effect of vaccination on the global microRNA population (i.e. micronome) has never been studied.

Aim

To describe vaccine associated changes in the expression of microRNAs 21 days after vaccination in children receiving a pandemic influenza (H1N1) vaccination.

Method

Serum samples were obtained from children aged 6 months to 12 years enrolled in an open label randomised control trial of two pandemic influenza (H1N1) vaccines, in which participants received either ASO3B adjuvanted split virion or a whole virion non-adjuvanted vaccine. MicroRNA expression was profiled in a discovery cohort of participants prior to, and 21 days after vaccination using an Agilent microarray platform. Findings were followed up by RT-qPCR in the original discovery cohort and then in a validation cohort of participants taken from the same study.

Results

44 samples from 22 children were assayed in a discovery cohort. The microarray results revealed 19 microRNAs were differentially expressed after vaccination after adjustment for multiple testing. The microarray detected ubiquitous expression of several microRNAs which could not be validated by RT-qPCR, many of which have little evidence of existence in publicly available RNA sequencing data. Real time PCR (RT-qPCR) confirmed downregulation of miR-142-3p in the discovery cohort. These findings were not replicated in the subsequent validation cohort (n = 22).

Conclusion

This study is the first study to profile microRNA expression after vaccination. An important feature of this study is many of the differentially expressed microRNAs could not be detected and validated by RT-qPCR. This study highlights the care that should be taken when interpreting omics biomarker discovery, highlighting the need for supplementary methods to validate microRNA microarray findings, and emphasises the importance of validation cohorts. Data from similar studies which do not meet these requirements should be interpreted with caution.

APOBEC-mediated mutagenesis in urothelial carcinoma is associated with improved survival, mutations in DNA damage response genes, and immune response

APOBEC enzymes are responsible for a mutation signature (TCW>T/G) implicated in a wide variety of tumors. We explore the APOBEC mutational signature in bladder cancer and the relationship with specific mutations, molecular subtype, gene expression, and survival using sequencing data from The Cancer Genome Atlas (n = 395), Beijing Genomics Institute (n = 99), and Cancer Cell Line Encyclopedia. Tumors were split into “APOBEC-high” and “APOBEC-low” based on APOBEC enrichment. Patients with APOBEC-high tumors have better overall survival compared to those with APOBEC-low tumors (38.2 vs. 18.5 months, p = 0.005). APOBEC-high tumors are more likely to have mutations in DNA damage response genes (TP53, ATR, BRCA2) and chromatin regulatory genes (ARID1A, MLL, MLL3), while APOBEC-low tumors are more likely to have mutations in FGFR3 and KRAS. APOBEC3A and APOBEC3B expression correlates with mutation burden, regardless of bladder tumor molecular subtype. APOBEC mutagenesis is associated with increased expression of immune signatures, including interferon signaling, and expression of APOBEC3B is increased after stimulation of APOBEC-high bladder cancer cell lines with IFNγ. In summary, APOBEC-high tumors are more likely to have mutations in DNA damage response and chromatin regulatory genes, potentially providing more substrate for APOBEC enzymes, leading to a hypermutational phenotype and the subsequent enhanced immune response.