TARO: tree-aggregated factor regression for microbiome data integration.

MOTIVATION: Although the human microbiome plays a key role in health and disease, the biological mechanisms underlying the interaction between the microbiome and its host are incompletely understood. Integration with other molecular profiling data offers an opportunity to characterize the role of the microbiome and elucidate therapeutic targets. However, this remains challenging to the high dimensionality, compositionality, and rare features found in microbiome profiling data. These challenges necessitate the use of methods that can achieve structured sparsity in learning cross-platform association patterns. RESULTS: We propose Tree-Aggregated factor RegressiOn (TARO) for the integration of microbiome and metabolomic data. We leverage information on the taxonomic tree structure to flexibly aggregate rare features. We demonstrate through simulation studies that TARO accurately recovers a low-rank coefficient matrix and identifies relevant features. We applied TARO to microbiome and metabolomic profiles gathered from subjects being screened for colorectal cancer to understand how gut microrganisms shape intestinal metabolite abundances. AVAILABILITY AND IMPLEMENTATION: The R package TARO implementing the proposed methods is available online at https://github.com/amishra-stats/taro-package.

A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies.

The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are associated with many diseases. Several metaproteomics platforms are currently available to study microbial proteins within complex microbial communities. In this study, we attempted to develop an integrated pipeline to provide deeper insights into both the taxonomic and functional aspects of the cultivated human gut microbiomes derived from clinical colon biopsies. We combined a rapid peptide search by MSFragger against the Unified Human Gastrointestinal Protein database and the taxonomic and functional analyses with Unipept Desktop and MetaLab-MAG. Across seven samples, we identified and matched nearly 36,000 unique peptides to approximately 300 species and 11 phyla. Unipept Desktop provided gene ontology, InterPro entries, and enzyme commission number annotations, facilitating the identification of relevant metabolic pathways. MetaLab-MAG contributed functional annotations through Clusters of Orthologous Genes and Non-supervised Orthologous Groups categories. These results unveiled functional similarities and differences among the samples. This integrated pipeline holds the potential to provide deeper insights into the taxonomy and functions of the human gut microbiome for interrogating the intricate connections between microbiome balance and diseases.

Development of a Strategic Initiative at MD Anderson Cancer Center to Improve Outcomes in Immune-Related Adverse Events.

Immune checkpoint inhibitors (ICIs) have transformed the treatment paradigm for many cancer types. The clinical use of ICIs is increasing rapidly, including in combinations associated with increased risk of toxicities, termed "immune-related adverse events" (irAEs). Therefore, MD Anderson Cancer Center (MDACC) in Houston, Texas has proactively responded by developing a priority endeavor known as the Immuno-Oncology Toxicity (IOTOX) initiative. This strategic initiative aims to facilitate the seamless integration of key domains: (1) standardized clinical practice and innovative decision toolsets; (2) patient and provider education; and (3) a comprehensive clinical and translational research platform. The ultimate goal of this initiative is to develop and disseminate clinical best practices and biologic insights into irAEs to improve outcomes of patients with irAEs at MDACC and in the wider oncology community.

The SagA of E. faecium.

An enzyme that remodels the cell wall of Enterococcus faecium helps these gut bacteria to divide and generate peptide fragments that enhance the immune response against cancer.

survivalContour: visualizing predicted survival via colored contour plots.

Summary: Advances in survival analysis have facilitated unprecedented flexibility in data modeling, yet there remains a lack of tools for illustrating the influence of continuous covariates on predicted survival outcomes. We propose the utilization of a colored contour plot to depict the predicted survival probabilities over time. Our approach is capable of supporting conventional models, including the Cox and Fine-Gray models. However, its capability shines when coupled with cutting-edge machine learning models such as random survival forests and deep neural networks. Availability and implementation: We provide a Shiny app at https://biostatistics.mdanderson.org/shinyapps/survivalContour/ and an R package available at https://github.com/YushuShi/survivalContour as implementations of this tool.

Antibiotic-associated neutropenia is marked by depletion of intestinal Lachnospiraceae in pediatric patients.

Hematologic side effects are associated with prolonged antibiotic exposure in up to 34% of patients. Neutropenia, reported in 10-15% of patients, increases the risk of sepsis and death. Murine studies have established a link between the intestinal microbiota and normal hematopoiesis. We sought to identify predisposing factors, presence of microbiota-derived metabolites, and changes in intestinal microbiota composition in otherwise healthy pediatric patients who developed neutropenia after prolonged courses of antibiotics. In this multi-center study, patients with infections requiring anticipated antibiotic treatment of two or more weeks were enrolled. Stool samples were obtained at the start and completion of antibiotics and at the time of neutropenia. We identified 10 patients who developed neutropenia on antibiotics and 29 controls matched for age, sex, race, and ethnicity. Clinical data demonstrated no association between neutropenia and type of infection or type of antibiotic used; however intensive care unit admission and length of therapy were associated with neutropenia. Reduced intestinal microbiome richness and decreased abundance of Lachnospiraceae family members correlated with neutropenia. Untargeted stool metabolomic profiling revealed several metabolites that were depleted exclusively in patients with neutropenia, including members of the urea cycle pathway, pyrimidine metabolism and fatty acid metabolism that are known to be produced by Lachnospiraceae . Our study confirms a relationship between intestinal microbiota disruption and abnormal hematopoiesis and identifies taxa and metabolites likely to contribute to microbiota-sustained hematopoiesis. As the microbiome is a key determinant of stem cell transplant and immunotherapy outcomes, these findings are likely to be of broad significance. Key Points: Neutropenia occurred in 17% of patients receiving prolonged antibiotic therapy.We found no association between neutropenia and type of infection or class of antibiotic used. Development of neutropenia after prolonged antibiotic treatment was associated with decreased prevalence of Lachnospiraceae and Lachnospiraceae metabolites such as citrulline.

Intratumoral microbiome of adenoid cystic carcinomas and comparison with other head and neck cancers.

Adenoid cystic carcinoma (ACC) is a rare, usually slow-growing yet aggressive head and neck malignancy. Despite its clinical significance, our understanding of the cellular evolution and microenvironment in ACC remains limited. We investigated the intratumoral microbiomes of 50 ACC tumor tissues and 33 adjacent normal tissues using 16S rRNA gene sequencing. This allowed us to characterize the bacterial communities within the ACC and explore potential associations between the bacterial community structure, patient clinical characteristics, and tumor molecular features obtained through RNA sequencing. The bacterial composition in the ACC was significantly different from that in adjacent normal salivary tissue, and the ACC exhibited diverse levels of species richness. We identified two main microbial subtypes within the ACC: oral-like and gut-like. Oral-like microbiomes, characterized by increased diversity and abundance of Neisseria, Leptotrichia, Actinomyces, Streptococcus, Rothia, and Veillonella (commonly found in healthy oral cavities), were associated with a less aggressive ACC-II molecular subtype and improved patient outcomes. Notably, we identified the same oral genera in oral cancer and head and neck squamous cell carcinomas. In both cancers, they were part of shared oral communities associated with a more diverse microbiome, less aggressive tumor phenotype, and better survival that reveal the genera as potential pancancer biomarkers for favorable microbiomes in ACC and other head and neck cancers. Conversely, gut-like intratumoral microbiomes, which feature low diversity and colonization by gut mucus layer-degrading species, such as Bacteroides, Akkermansia, Blautia, Bifidobacterium, and Enterococcus, were associated with poorer outcomes. Elevated levels of Bacteroides thetaiotaomicron were independently associated with significantly worse survival and positively correlated with tumor cell biosynthesis of glycan-based cell membrane components.

Third-party fecal microbiota transplantation for high-risk treatment-naïve acute GVHD of the lower GI tract.

ABSTRACT: Disruption of the intestinal microbiome is observed with acute graft-versus-host disease (GVHD) of the lower gastrointestinal (LGI) tract, and fecal microbiota transplantation (FMT) has successfully cured steroid-refractory cases. In this open-label, single-arm, pilot study, third-party, single-donor FMT was administered in combination with systemic corticosteroids to participants with high-risk acute LGI GVHD, with a focus on treatment-naïve cases. Participants were scheduled to receive 1 induction dose (15 capsules per day for 2 consecutive days), followed by 3 weekly maintenance doses, consisting of 15 capsules per dose. The primary end point of the study was feasibility, which would be achieved if ≥80% of participants able to swallow ≥40 of the 75 scheduled capsules. Ten participants (9 treatment-naïve; 1 steroid-refractory) were enrolled and treated. The study met the primary end point, with 9 of 10 participants completing all eligible doses. Organ-specific LGI complete response rate at day 28 was 70%. Initial clinical response was observed within 1 week for all responders, and clinical responses were durable without recurrent LGI GVHD in complete responders. Exploratory analyses suggest that alpha diversity increased after FMT. Although recipient microbiome composition never achieved a high degree of donor similarity, expansion of donor-derived species and increases in tryptophan metabolites and short-chain fatty acids were observed within the first 7 days after FMT. Investigation into the use of microbiome-targeted interventions earlier in the treatment paradigm for acute LGI GVHD is warranted. This trial was registered at www.ClinicalTrials.gov as #NCT04139577.

Tsyn-Seq: a T-cell Synapse-Based Antigen Identification Platform.

Tools for genome-wide rapid identification of peptide-major histocompatibility complex targets of T-cell receptors (TCR) are not yet universally available. We present a new antigen screening method, the T-synapse (Tsyn) reporter system, which includes antigen-presenting cells (APC) with a Fas-inducible NF-κB reporter and T cells with a nuclear factor of activated T cells (NFAT) reporter. To functionally screen for target antigens from a cDNA library, productively interacting T cell-APC aggregates were detected by dual-reporter activity and enriched by flow sorting followed by antigen identification quantified by deep sequencing (Tsyn-seq). When applied to a previously characterized TCR specific for the E7 antigen derived from human papillomavirus type 16 (HPV16), Tsyn-seq successfully enriched the correct cognate antigen from a cDNA library derived from an HPV16-positive cervical cancer cell line. Tsyn-seq provides a method for rapidly identifying antigens recognized by TCRs of interest from a tumor cDNA library. See related Spotlight by Makani and Joglekar, p. 515.