A major rate-limiting step in developing more effective immunotherapies for GBM is our inadequate understanding of the cellular complexity and the molecular heterogeneity of immune infiltrates in ...gliomas. Here, we report an integrated analysis of 201,986 human glioma, immune, and other stromal cells at the single cell level. In doing so, we discover extensive spatial and molecular heterogeneity in immune infiltrates. We identify molecular signatures for nine distinct myeloid cell subtypes, of which five are independent prognostic indicators of glioma patient survival. Furthermore, we identify S100A4 as a regulator of immune suppressive T and myeloid cells in GBM and demonstrate that deleting S100a4 in non-cancer cells is sufficient to reprogram the immune landscape and significantly improve survival. This study provides insights into spatial, molecular, and functional heterogeneity of glioma and glioma-associated immune cells and demonstrates the utility of this dataset for discovering therapeutic targets for this poorly immunogenic cancer.
Street dust samples were collected from five different types of land use patterns (busy traffic zone, urban residential area, national highways, industrial area and sensitive area) in a medium sized ...industrial city Asansol, India. The samples were fractionated into ≤53µm and analyzed for potential toxic elements (PTEs) viz. Zn, Cd, Pb and Cu. The mean total concentration of Zn, Cd, Pb and Cu in the urban street dust samples were 192, 0.75, 110 and 132mgkg−1 respectively. Chemical speciation was performed for PTEs to evaluate the bio-available fractions. Cu was mostly associated with organic matter phase while Zn, Pb and Cd with residual phase. Mean mobility factor (MF) for heavy metals in Asansol was Zn (54.6%)>Pb (49.1%)>Cu (25.3%)>Cd (22.7%). Geo-chemical indices such as Enrichment Factor (EF), geo-accumulation index (Igeo) and contamination Factor (CF) were in the order of Pb>Cd>Zn>Cu. Cluster analysis was done to understand the similarities among the sites. The risks of all metals was calculated with mobile fraction, which indicated actual risk due to PTEs was less (HI<1).
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•Speciation and bio-availability of Cd, Cu, Pb and Zn was evaluated in street dust.•Zn and Pb had higher amount in bio-available fraction.•Pollution load index showed that all sites in Asansol were highly deteriorated.•Bio-available content of Cd, Cu, Pb and Zn is within the exposure risk limit.
Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are ...associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type-specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis.
Street dust samples from Durgapur, the steel city of eastern India, were collected from five different land use patterns, i.e., national highways, urban residential area, sensitive area, industrial ...area and busy traffic zone during summer, monsoon, and winter to analyze the pollution characteristics, chemical fractionation, source apportionment and health risk of heavy metals (HMs). The samples were fractionated into ≤ 53 µm and analyzed for potentially harmful elements (PHEs) viz. Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn. Summer season indicated higher concentrations of PHEs when compared to the other two seasons. Mean enrichment factor (EF), geo-accumulation index (Igeo), and contamination factor (CF) were high for Cd followed by Pb during all the three season in Durgapur. Chemical fractionation was executed in order to obtain distribution patterns of PHEs and to evaluate their bioavailable fractions in street dust samples. Mn was found to be highly bioavailable and bioavailability of the PHEs were in the order of Mn > Zn > Pb > Ni > Cd > Cu > Fe > Cr. Principal Component Analysis (PCA), cluster analysis, correlation analysis indicated the main sources of PHEs could be industrial, especially coal powered thermal plant, iron and steel industries and cement industries and vehicular. Multivariate analysis of variance (MANOVA) indicated that sites, seasons and their interaction were significantly affected by different PHEs as a whole. The health risk was calculated with total metal as well as mobile fraction of PHEs, which indicated that the actual non-carcinogenic risk due to bioavailable PHEs was less (HI < 1) when compared to total concentrations of PHEs. Carcinogenic risk was observed for total Cr in street dust (Child: 4.6E-06; Adult: 3.6E-06).
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•Chemical speciation of PHEs in street dust were assessed in ≤ 53 µm.•Higher concentrations of Cu, Cr, Pb, and Zn were found in busy traffic areas while Fe and Mn were found to be higher in industrial areas.•Carcinogenic risk was present for Cr in street dust with total PHEs concentration and risk was absent with bioavailable content.•Ecological risk was higher for Cd; though the potential health risks of PHEs were lower than regulatory guideline levels.
The frequency of BRCA1 and BRCA2 germ-line mutations in women with ovarian cancer is unclear; reports vary from 3% to 27%. The impact of germ-line mutation on response requires further investigation ...to understand its impact on treatment planning and clinical trial design.
Women with nonmucinous ovarian carcinoma (n = 1,001) enrolled onto a population-based, case-control study were screened for point mutations and large deletions in both genes. Survival outcomes and responses to multiple lines of chemotherapy were assessed.
Germ-line mutations were found in 14.1% of patients overall, including 16.6% of serous cancer patients (high-gradeserous, 17.1%); corrected 44% had no reported family history of breast orovarian cancer.Patients carrying germ-line mutations had improved rates of progression-free and overall survival. In the relapse setting, patients carrying mutations more frequently responded to both platin- and nonplatin-based regimens than mutation-negative patients, even in patients with early relapse after primary treatment. Mutation-negative patients who responded to multiple cycles of platin-based treatment were more likely to carry somatic BRCA1/2 mutations.
BRCA mutation status has a major influence on survival in ovarian cancer patients and should be an additional stratification factor in clinical trials. Treatment outcomes in BRCA1/2 carriers challenge conventional definitions of platin resistance, and mutation status may be able to contribute to decision making and systemic therapy selection in the relapse setting. Our data, together with the advent of poly(ADP-ribose) polymerase inhibitor trials, supports the recommendation that germ-line BRCA1/2 testing should be offered to all women diagnosed with nonmucinous, ovarian carcinoma, regardless of family history.
Myc transcriptional activity is frequently deregulated in human cancers, but a Myc-driven gene signature with prognostic ability across multiple tumor types remains lacking. Here, we selected 18 ...Myc-regulated genes from published studies of Myc family targets in epithelial ovarian cancer (EOC) and neuroblastoma. A Myc family activity score derived from the 18 genes was correlated to
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expression in a panel of 35 cancer cell lines. The prognostic ability of this signature was evaluated in neuroblastoma, medulloblastoma, diffuse large B-cell lymphoma (DLBCL), and EOC microarray gene expression datasets using Kaplan-Meier and multivariate Cox regression analyses and was further validated in 42 primary neuroblastomas using qPCR. Cell lines with high
, and/or
gene expression exhibited elevated expression of the signature genes. Survival analysis showed that the signature was associated with poor outcome independently of well-defined prognostic factors in neuroblastoma, breast cancer, DLBCL, and medulloblastoma. In EOC, the 18-gene Myc activity signature was capable of identifying a group of patients with poor prognosis in a "high-
" molecular subtype but not in the overall cohort. The predictive ability of this signature was reproduced using qPCR analysis of an independent cohort of neuroblastomas, including a subset of tumors without
amplification. These data reveal an 18-gene Myc activity signature that is highly predictive of poor prognosis in diverse Myc-associated malignancies and suggest its potential clinical application in the identification of Myc-driven tumors that might respond to Myc-targeted therapies.
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•Elevated concentration of 16 polycyclic aromatic hydrocarbons (PAHs) in street dust in winter season.•The 2-ring to 3-ring PAHs dominated in winter season whereas 5-ring to 6-ring PAHs contributed ...maximum in summer season.•Principal component analysis (PCA) and ratio determination were performed to identify the potential sources of PAHs.•Total cancer risk for children and adults were maximum at industrial sites i e., 1.4E-05 and 1.5E-05 respectively.
The sources, distribution and total concentration of 16 polycyclic aromatic hydrocarbons (PAHs) in 15 urban street dust samples (each for summer, winter and monsoon season) from Asansol, an industrial city were investigated to evaluate and understand the carcinogenic risk of urban inhabitants exposed to street dust. The results showed that the total PAHs (∑PAHs) in urban street dust at Asansol ranged from 1708 ± 1345 ng/g to 9688 ± 3257 ng/g with an average value of 4532 ± 2031 ng/g. The 2-ring to 3-ring PAHs dominated in winter; whereas 5-ring to 6-ring PAHs contributed maximum in summer. Principal component analysis (PCA) and ratio determination were performed to identify the potential sources of PAHs. Anth/(Phe + Anth), BaP/BghiP, Fla/(Pyr + Fla), IP/(IP + BghiP), Flt/Pyr, Phen/Anth, and BaA/Chry ratios indicated mixed sources of PAHs. Our result concluded that at Asansol, biomass combustion, coal combustion, traffic emission (gasoline and diesel powered vehicles), thrash burning and domestic coal utilization activity, along with temperature and meteorological dependent played an important role in controlling the distribution of PAHs in street dust. According to the Incremental Lifetime Cancer Risk (ILCR) model, the total cancer risk for children and adults were maximum at industrial sites, i e., 1.4E-05 and 1.5E-05 respectively.
The RNA isoform repertoire is regulated by splicing factor (SF) expression, and alterations in SF levels are associated with disease. SFs contain ultraconserved poison exon (PE) sequences that ...exhibit greater identity across species than nearby coding exons, but their physiological role and molecular regulation is incompletely understood. We show that PEs in serine-arginine-rich (SR) proteins, a family of 14 essential SFs, are differentially spliced during induced pluripotent stem cell (iPSC) differentiation and in tumors versus normal tissues. We uncover an extensive cross-regulatory network of SR proteins controlling their expression via alternative splicing coupled to nonsense-mediated decay. We define sequences that regulate PE inclusion and protein expression of the oncogenic SF TRA2β using an RNA-targeting CRISPR screen. We demonstrate location dependency of RS domain activity on regulation of TRA2β-PE using CRISPR artificial SFs. Finally, we develop splice-switching antisense oligonucleotides to reverse the increased skipping of TRA2β-PE detected in breast tumors, altering breast cancer cell viability, proliferation, and migration.
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•SR proteins levels are coordinated through splicing of their poison exons•SR protein poison exon splicing is altered during cell differentiation and in tumors•ASOs promotingTRA2β poison exon inclusion have anti-cancer effects in vitro
Leclair et al. demonstrate that expression of 14 SR proteins is coordinated through splicing of their poison exons during cell differentiation and tumorigenesis. Using the TRA2β poison exon as an example, they identify splicing-regulatory sequences and design splice-switching antisense oligonucleotides that decrease TRA2β protein expression and exhibit anti-cancer effects.
Aging is linked to deficiencies in immune responses and increased systemic inflammation. To unravel the regulatory programs behind these changes, we applied systems immunology approaches and profiled ...chromatin accessibility and the transcriptome in PBMCs and purified monocytes, B cells, and T cells. Analysis of samples from 77 young and elderly donors revealed a novel and robust aging signature in PBMCs, with simultaneous systematic chromatin closing at promoters and enhancers associated with T cell signaling and a potentially stochastic chromatin opening mostly found at quiescent and repressed sites. Combined analyses of chromatin accessibility and the transcriptome uncovered immune molecules activated/inactivated with aging and identified the silencing of the
gene and the IL-7 signaling pathway genes as potential biomarkers. This signature is borne by memory CD8
T cells, which exhibited an aging-related loss in binding of NF-κB and STAT factors. Thus, our study provides a unique and comprehensive approach to identifying candidate biomarkers and provides mechanistic insights into aging-associated immunodeficiency.
Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for ...selecting candidate genes, knowledge-driven methods must contend with the challenge of efficiently sifting through extensive volumes of biomedical information. This work aimed to assess the utility of large language models (LLMs) for knowledge-driven gene prioritization and selection.
In this proof of concept, we focused on 11 blood transcriptional modules associated with an Erythroid cells signature. We evaluated four leading LLMs across multiple tasks. Next, we established a workflow leveraging LLMs. The steps consisted of: (1) Selecting one of the 11 modules; (2) Identifying functional convergences among constituent genes using the LLMs; (3) Scoring candidate genes across six criteria capturing the gene's biological and clinical relevance; (4) Prioritizing candidate genes and summarizing justifications; (5) Fact-checking justifications and identifying supporting references; (6) Selecting a top candidate gene based on validated scoring justifications; and (7) Factoring in transcriptome profiling data to finalize the selection of the top candidate gene.
Of the four LLMs evaluated, OpenAI's GPT-4 and Anthropic's Claude demonstrated the best performance and were chosen for the implementation of the candidate gene prioritization and selection workflow. This workflow was run in parallel for each of the 11 erythroid cell modules by participants in a data mining workshop. Module M9.2 served as an illustrative use case. The 30 candidate genes forming this module were assessed, and the top five scoring genes were identified as BCL2L1, ALAS2, SLC4A1, CA1, and FECH. Researchers carefully fact-checked the summarized scoring justifications, after which the LLMs were prompted to select a top candidate based on this information. GPT-4 initially chose BCL2L1, while Claude selected ALAS2. When transcriptional profiling data from three reference datasets were provided for additional context, GPT-4 revised its initial choice to ALAS2, whereas Claude reaffirmed its original selection for this module.
Taken together, our findings highlight the ability of LLMs to prioritize candidate genes with minimal human intervention. This suggests the potential of this technology to boost productivity, especially for tasks that require leveraging extensive biomedical knowledge.
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