Impact of genome build on RNA-seq interpretation and diagnostics.

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network and Genomics Research to Elucidate the Genetics of Rare Disease Consortium. Across six routinely collected biospecimens, 61% of quantified genes were not influenced by genome build. However, we identified 1,492 genes with build-dependent quantification, 3,377 genes with build-exclusive expression, and 9,077 genes with annotation-specific expression across six routinely collected biospecimens, including 566 clinically relevant and 512 known OMIM genes. Further, we demonstrate that between builds for a given gene, a larger difference in quantification is well correlated with a larger change in expression outlier calling. Combined, we provide a database of genes impacted by build choice and recommend that transcriptomics-guided analyses and diagnoses are cross referenced with these data for robustness.

Molecular Transducers of Physical Activity Consortium (MoTrPAC): Human Studies Design and Protocol.

Physical activity, including structured exercise, is associated with favorable health-related chronic disease outcomes. While there is evidence of various molecular pathways that affect these responses, a comprehensive molecular map of these molecular responses to exercise has not been developed. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) is a multi-center study designed to isolate the effects of structured exercise training on the molecular mechanisms underlying the health benefits of exercise and physical activity. MoTrPAC contains both a pre-clinical and human component. The details of the human studies component of MoTrPAC that include the design and methods are presented here. The human studies contain both an adult and pediatric component. In the adult component, sedentary participants are randomized to 12 weeks of Control, Endurance Exercise Training, or Resistance Exercise Training with outcomes measures completed before and following the 12 weeks. The adult component also includes recruitment of highly active endurance trained or resistance trained participants who only complete measures once. A similar design is used for the pediatric component; however, only endurance exercise is examined. Phenotyping measures include weight, body composition, vital signs, cardiorespiratory fitness, muscular strength, physical activity and diet, and other questionnaires. Participants also complete an acute rest period (adults only) or exercise session (adults, pediatrics) with collection of biospecimens (blood only for pediatrics) to allow for examination of the molecular responses. The design and methods of MoTrPAC may inform other studies. Moreover, MoTrPAC will provide a repository of data that can be used broadly across the scientific community.

Immunotherapeutic IL-6R and targeting the MCT-1/IL-6/CXCL7/PD-L1 circuit prevent relapse and metastasis of triple-negative breast cancer.

Rationale: Multiple copies in T-cell malignancy 1 (MCT-1) is a prognostic biomarker for aggressive breast cancers. Overexpressed MCT-1 stimulates the IL-6/IL-6R/gp130/STAT3 axis, which promotes epithelial-to-mesenchymal transition and cancer stemness. Because cancer stemness largely contributes to the tumor metastasis and recurrence, we aimed to identify whether the blockade of MCT-1 and IL-6R can render these effects and to understand the underlying mechanisms that govern the process. Methods: We assessed primary tumor invasion, postsurgical local recurrence and distant metastasis in orthotopic syngeneic mice given the indicated immunotherapy and MCT-1 silencing (shMCT-1). Results: We found that shMCT-1 suppresses the transcriptomes of the inflammatory response and metastatic signaling in TNBC cells and inhibits tumor recurrence, metastasis and mortality in xenograft mice. IL-6R immunotherapy and shMCT-1 combined further decreased intratumoral M2 macrophages and T regulatory cells (Tregs) and avoided postsurgical TNBC expansion. shMCT-1 also enhances IL-6R-based immunotherapy effectively in preventing postsurgical TNBC metastasis, recurrence and mortality. Anti-IL-6R improved helper T, cytotoxic T and natural killer (NK) cells in the lymphatic system and decreased Tregs in the recurrent and metastatic tumors. Combined IL-6R and PD-L1 immunotherapies abridged TNBC cell stemness and M2 macrophage activity to a greater extent than monotherapy. Sequential immunotherapy of PD-L1 and IL-6R demonstrated the best survival outcome and lowest postoperative recurrence and metastasis compared with synchronized therapy, particularly in the shMCT-1 context. Multiple positive feedforward loops of the MCT-1/IL-6/IL-6R/CXCL7/PD-L1 axis were identified in TNBC cells, which boosted metastatic niches and immunosuppressive microenvironments. Clinically, MCT-1high/PD-L1high/CXCL7high and CXCL7high/IL-6high/IL-6Rhigh expression patterns predict worse prognosis and poorer survival of breast cancer patients. Conclusion: Systemic targeting the MCT-1/IL-6/IL-6R/CXCL7/PD-L1 interconnections enhances immune surveillance that inhibits the aggressiveness of TNBC.

3D Topographical Scanning for the Detection of Osteoporosis.

Objectives: Osteoporosis is associated with greater risk of fracture, which can lead to increased morbidity and mortality. DEXA scans are often inaccessible for patients, leaving many cases of osteoporosis undetected. A portable 3D topographical scan offers an easily accessible and inexpensive potential adjunct screening tool. We hypothesized that 3D scanning of arm and calf circumference and volume would correlate with DEXA T-scores. Methods: 96 female patients were enrolled. Patients were consented and completed a topographical scan of bilateral arms and lower legs with a mobile 3D scanner for arm and calf circumference and volume in clinic. Patient charts were then retrospectively reviewed for DEXA T-scores. Results: Forearm DEXA T-score was positively correlated with arm circumference (r = 0.49, p<0.01), arm volume (r=0.62, p<0.01), and calf volume (r=0.47, p<0.01). Femoral neck DEXA T-score was positively correlated with calf circumference (r=0.36, p<0.01) and calf volume (r=0.36, p<0.01). Conclusions: Our results showed significant correlations between DEXA T-scores and topographical measurements from mobile device acquired 3D scans, although these were in the "moderate" range. Mobile device-based 3D scanning may hold promise as an adjunct screening tool for osteoporosis when DEXA scanning is not available or feasible for patients, although further studies are needed to elucidate the full potential of its clinical utility. At a minimum, identifying a patient as high risk may promote earlier diagnostic DEXA scanning.

Using machine-learning to decode postoperative hip mortality Trends: Actionable insights from an extensive clinical dataset.

BACKGROUND: Hip fractures are one of the most common injuries experienced by the general population. Despite advances in surgical techniques, postoperative mortality rates remain high. identifying relevant clinical factors associated with mortality is essential to preoperative risk stratification and tailored post-surgical interventions to improve patient outcomes. The purpose of this study aimed to identify preoperative risk factors and develop predictive models for increased hip fracture-related mortality within 30 days post-surgery, using one of the largest patient cohorts to date. METHODS: Data from the American College of Surgeons National Surgical Quality Improvement Program database, comprising 107,660 hip fracture patients treated with surgical fixation was used. A penalized regression approach, least absolute shrinkage and selection operator was employed to develop two predictive models: one using preoperative factors and the second incorporating both preoperative and postoperative factors. RESULTS: The analysis identified 68 preoperative factor outcomes associated with 30-day mortality. The combined model revealed 84 relevant factors, showing strong predictive power for determining postoperative mortality, with an AUC of 0.83. CONCLUSIONS: The study's comprehensive methodology provides risk assessment tools for clinicians to identify high-risk patients and optimize patient-specific care.

Impact of genome build on RNA-seq interpretation and diagnostics.

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network (UDN) and Genomics Research to Elucidate the Genetics of Rare Disease (GREGoR) Consortium. We identified 2,800 genes with build-dependent quantification across six routinely-collected biospecimens, including 1,391 protein-coding genes and 341 known rare disease genes. We further observed multiple genes that only have detectable expression in a subset of genome builds. Finally, we characterized how genome build impacts the detection of outlier transcriptomic events. Combined, we provide a database of genes impacted by build choice, and recommend that transcriptomics-guided analyses and diagnoses are cross-referenced with these data for robustness.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models.

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on these widely used in vitro models of human and mouse adipogenesis, and on cell-to-cell variability during this process.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models.

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on human and mouse adipogenesis, as well as on cell-to-cell variability in gene expression during this process.

Immunotherapy of targeting MDSCs in tumor microenvironment.

Myeloid-derived suppressor cells (MDSCs) are a group of heterogeneous cells which are abnormally accumulated during the differentiation of myeloid cells. Immunosuppression is the main functional feature of MDSCs, which inhibit T cell activity in the tumor microenvironment (TME) and promote tumoral immune escape. The main principle for immunotherapy is to modulate, restore, and remodel the plasticity and potential of immune system to have an effective anti-tumor response. In the TME, MDSCs are major obstacles to cancer immunotherapy through reducing the anti-tumor efficacy and making tumor cells more resistant to immunotherapy. Therefore, targeting MDSCs treatment becomes the priority of relevant studies and provides new immunotherapeutic strategy for cancer treatment. In this review, we mainly discuss the functions and mechanisms of MDSCs as well as their functional changes in the TME. Further, we review therapeutic effects of immunotherapy against MDSCs and potential breakthroughs regarding immunotherapy targeting MDSCs and immune checkpoint blockade (ICB) immunotherapy.

Poly-γ-Glutamic Acids Contribute to Biofilm Formation and Plant Root Colonization in Selected Environmental Isolates of Bacillus subtilis.

Bacillus subtilis is long known to produce poly-γ-glutamic acids (γ-PGA) as one of the major secreted polymeric substances. In B. subtilis, the regulation of γ-PGA production and its physiological role are still unclear. B. subtilis is also capable of forming structurally complex multicellular communities, or biofilms, in which an extracellular matrix consisting of secreted proteins and polysaccharides holds individual cells together. Biofilms were shown to facilitate B. subtilis-plant interactions. In this study, we show that different environmental isolates of B. subtilis, all capable of forming biofilms, vary significantly in γ-PGA production. This is possibly due to differential regulation of γ-PGA biosynthesis genes. In many of those environmental isolates, γ-PGA seems to contribute to robustness and complex morphology of the colony biofilms, suggesting a role of γ-PGA in biofilm formation. Our evidence further shows that in selected B. subtilis strains, γ-PGA also plays a role in root colonization by the bacteria, pinpointing a possible function of γ-PGA in B. subtilis-plant interactions. Finally, we found that several pathways co-regulate both γ-PGA biosynthesis genes and genes for the biofilm matrix in B. subtilis, but in an opposing fashion. We discussed potential biological significance of that.