A mitochondrial NADPH-cholesterol axis regulates extracellular vesicle biogenesis to support hematopoietic stem cell fate.

Mitochondrial fatty acid oxidation (FAO) is essential for hematopoietic stem cell (HSC) self-renewal; however, the mechanism by which mitochondrial metabolism controls HSC fate remains unknown. Here, we show that within the hematopoietic lineage, HSCs have the largest mitochondrial NADPH pools, which are required for proper HSC cell fate and homeostasis. Bioinformatic analysis of the HSC transcriptome, biochemical assays, and genetic inactivation of FAO all indicate that FAO-generated NADPH fuels cholesterol synthesis in HSCs. Interference with FAO disturbs the segregation of mitochondrial NADPH toward corresponding daughter cells upon single HSC division. Importantly, we have found that the FAO-NADPH-cholesterol axis drives extracellular vesicle (EV) biogenesis and release in HSCs, while inhibition of EV signaling impairs HSC self-renewal. These data reveal the existence of a mitochondrial NADPH-cholesterol axis for EV biogenesis that is required for hematopoietic homeostasis and highlight the non-stochastic nature of HSC fate determination.

Genomic instability analysis in DNA from Papanicolaou test provides proof-of-principle early diagnosis of high-grade serous ovarian cancer.

Late diagnosis and the lack of screening methods for early detection define high-grade serous ovarian cancer (HGSOC) as the gynecological malignancy with the highest mortality rate. In the work presented here, we investigated a retrospective and multicentric cohort of 250 archival Papanicolaou (Pap) test smears collected during routine gynecological screening. Samples were taken at different time points (from 1 month to 13.5 years before diagnosis) from 113 presymptomatic women who were subsequently diagnosed with HGSOC (pre-HGSOC) and from 77 healthy women. Genome instability was detected through low-pass whole-genome sequencing of DNA derived from Pap test samples in terms of copy number profile abnormality (CPA). CPA values of DNA extracted from Pap test samples from pre-HGSOC women were substantially higher than those in samples from healthy women. Consistently with the longitudinal analysis of clonal pathogenic TP53 mutations, this assay could detect HGSOC presence up to 9 years before diagnosis. This finding confirms the continual shedding of tumor cells from fimbriae toward the endocervical canal, suggesting a new path for the early diagnosis of HGSOC. We integrated the CPA score into the EVA (early ovarian cancer) test, the sensitivity of which was 75% (95% CI, 64.97 to 85.79), the specificity 96% (95% CI, 88.35 to 100.00), and the accuracy 81%. This proof-of-principle study indicates that the early diagnosis of HGSOC is feasible through the analysis of genomic alterations in DNA from endocervical smears.

A pan-cancer landscape of pathogenic somatic copy number variations.

OBJECTIVE: Copy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions. METHODS: Starting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients' survival. RESULTS: Our analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression. CONCLUSION: This study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.

Transglutaminase Type 2-MITF axis regulates phenotype switching in skin cutaneous melanoma.

Skin cutaneous melanoma (SKCM) is the deadliest form of skin cancer due to its high heterogeneity that drives tumor aggressiveness. Melanoma plasticity consists of two distinct phenotypic states that co-exist in the tumor niche, the proliferative and the invasive, respectively associated with a high and low expression of MITF, the master regulator of melanocyte lineage. However, despite efforts, melanoma research is still far from exhaustively dissecting this phenomenon. Here, we discovered a key function of Transglutaminase Type-2 (TG2) in regulating melanogenesis by modulating MITF transcription factor expression and its transcriptional activity. Importantly, we demonstrated that TG2 expression affects melanoma invasiveness, highlighting its positive value in SKCM. These results suggest that TG2 may have implications in the regulation of the phenotype switching by promoting melanoma differentiation and impairing its metastatic potential. Our findings offer potential perspectives to unravel melanoma vulnerabilities via tuning intra-tumor heterogeneity.

Genome-wide profiling of patient-derived glioblastoma stem-like cells reveals recurrent genetic and transcriptomic signatures associated with brain tumors.

PURPOSE: Patient-derived cancer cell lines can be very useful to investigate genetic as well as epigenetic mechanisms of transformation and to test new drugs. In this multi-centric study, we performed genomic and transcriptomic characterization of a large set of patient-derived glioblastoma (GBM) stem-like cells (GSCs). METHODS: 94 (80 I surgery/14 II surgery) and 53 (42 I surgery/11 II surgery) GSCs lines underwent whole exome and trascriptome analysis, respectively. RESULTS: Exome sequencing revealed TP53 as the main mutated gene (41/94 samples, 44%), followed by PTEN (33/94, 35%), RB1 (16/94, 17%) and NF1 (15/94, 16%), among other genes associated to brain tumors. One GSC sample bearing a BRAF p.V600E mutation showed sensitivity in vitro to a BRAF inhibitor. Gene Ontology and Reactome analysis uncovered several biological processes mostly associated to gliogenesis and glial cell differentiation, S - adenosylmethionine metabolic process, mismatch repair and methylation. Comparison of I and II surgery samples disclosed a similar distribution of mutated genes, with an overrepresentation of mutations in mismatch repair, cell cycle, p53 and methylation pathways in I surgery samples, and of mutations in receptor tyrosine kinase and MAPK signaling pathways in II surgery samples. Unsupervised hierarchical clustering of RNA-seq data produced 3 clusters characterized by distinctive sets of up-regulated genes and signaling pathways. CONCLUSION: The availability of a large set of fully molecularly characterized GCSs represents a valuable public resource to support the advancement of precision oncology for the treatment of GBM.

signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data.

Over the last decade, many studies and some clinical trials have proposed gene expression signatures as a valuable tool for understanding cancer mechanisms, defining subtypes, monitoring patient prognosis, and therapy efficacy. However, technical and biological concerns about reproducibility have been raised. Technical reproducibility is a major concern: we currently lack a computational implementation of the proposed signatures, which would provide detailed signature definition and assure reproducibility, dissemination, and usability of the classifier. Another concern regards intratumor heterogeneity, which has never been addressed when studying these types of biomarkers using bulk transcriptomics. With the aim of providing a tool able to improve the reproducibility and usability of gene expression signatures, we propose signifinder, an R package that provides the infrastructure to collect, implement, and compare expression-based signatures from cancer literature. The included signatures cover a wide range of biological processes from metabolism and programmed cell death, to morphological changes, such as quantification of epithelial or mesenchymal-like status. Collected signatures can score tumor cell characteristics, such as the predicted response to therapy or the survival association, and can quantify microenvironmental information, including hypoxia and immune response activity. signifinder has been used to characterize tumor samples and to investigate intra-tumor heterogeneity, extending its application to single-cell and spatial transcriptomic data. Through these higher-resolution technologies, it has become increasingly apparent that the single-sample score assessment obtained by transcriptional signatures is conditioned by the phenotypic and genetic intratumor heterogeneity of tumor masses. Since the characteristics of the most abundant cell type or clone might not necessarily predict the properties of mixed populations, signature prediction efficacy is lowered, thus impeding effective clinical diagnostics. Through signifinder, we offer general principles for interpreting and comparing transcriptional signatures, as well as suggestions for additional signatures that would allow for more complete and robust data inferences. We consider signifinder a useful tool to pave the way for reproducibility and comparison of transcriptional signatures in oncology.

Spatial compartmentalization of signaling imparts source-specific functions on secreted factors.

Efficient regeneration requires multiple cell types acting in coordination. To better understand the intercellular networks involved and how they change when regeneration fails, we profile the transcriptome of hematopoietic, stromal, myogenic, and endothelial cells over 14 days following acute muscle damage. We generate a time-resolved computational model of interactions and identify VEGFA-driven endothelial engagement as a key differentiating feature in models of successful and failed regeneration. In addition, the analysis highlights that the majority of secreted signals, including VEGFA, are simultaneously produced by multiple cell types. To test whether the cellular source of a factor determines its function, we delete VEGFA from two cell types residing in close proximity: stromal and myogenic progenitors. By comparing responses to different types of damage, we find that myogenic and stromal VEGFA have distinct functions in regeneration. This suggests that spatial compartmentalization of signaling plays a key role in intercellular communication networks.

Defective excitation-contraction coupling and mitochondrial respiration precede mitochondrial Ca2+ accumulation in spinobulbar muscular atrophy skeletal muscle.

Polyglutamine expansion in the androgen receptor (AR) causes spinobulbar muscular atrophy (SBMA). Skeletal muscle is a primary site of toxicity; however, the current understanding of the early pathological processes that occur and how they unfold during disease progression remains limited. Using transgenic and knock-in mice and patient-derived muscle biopsies, we show that SBMA mice in the presymptomatic stage develop a respiratory defect matching defective expression of genes involved in excitation-contraction coupling (ECC), altered contraction dynamics, and increased fatigue. These processes are followed by stimulus-dependent accumulation of calcium into mitochondria and structural disorganization of the muscle triads. Deregulation of expression of ECC genes is concomitant with sexual maturity and androgen raise in the serum. Consistent with the androgen-dependent nature of these alterations, surgical castration and AR silencing alleviate the early and late pathological processes. These observations show that ECC deregulation and defective mitochondrial respiration are early but reversible events followed by altered muscle force, calcium dyshomeostasis, and dismantling of triad structure.

A comprehensive investigation of histotype-specific microRNA and their variants in Stage I epithelial ovarian cancers.

isomiRs, the sequence-variants of microRNA, are known to be tissue and cell type specific but their physiological role is largely unknown. In our study, we explored for the first time the expression of isomiRs across different Stage I epithelial ovarian cancer (EOC) histological subtypes, in order to shed new light on their biological role in tumor growth and progression. In a multicentric retrospective cohort of tumor biopsies (n = 215) we sequenced small RNAs finding 971 expressed miRNAs, 64% of which are isomiRs. Among them, 42 isomiRs showed a clear histotype specific pattern, confirming our previously identified miRNA markers (miR192/194 and miR30a-3p/5p for mucinous and clear cell subtypes, respectively) and uncovering new biomarkers for all the five subtypes. Using integrative models, we found that the 38% of these miRNA expression alterations is the result of copy number variations while the 17% of differential transcriptional activities. Our work represents the first attempt to characterize isomiRs expression in Stage I EOC within and across subtypes and to contextualize their alterations in the framework of the large genomic heterogeneity of this tumor.

benchdamic: benchmarking of differential abundance methods for microbiome data.

SUMMARY: Recently, an increasing number of methodological approaches have been proposed to tackle the complexity of metagenomics and microbiome data. In this scenario, reproducibility and replicability have become two critical issues, and the development of computational frameworks for the comparative evaluations of such methods is of utmost importance. Here, we present benchdamic, a Bioconductor package to benchmark methods for the identification of differentially abundant taxa. AVAILABILITY AND IMPLEMENTATION: benchdamic is available as an open-source R package through the Bioconductor project at https://bioconductor.org/packages/benchdamic/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hydrogen peroxide induced by nerve injury promotes axon regeneration via connective tissue growth factor.

Regeneration of the neuromuscular junction (NMJ) leverages on extensive exchange of factors released from motor axon terminals (MATs), muscle fibers and perisynaptic Schwann cells (PSCs), among which hydrogen peroxide (H2O2) is a major pro-regenerative signal. To identify critical determinants of NMJ remodeling in response to injury, we performed temporal transcriptional profiling of NMJs from 2 month-old mice during MAT degeneration/regeneration, and cross-referenced the differentially expressed genes with those elicited by H2O2 in SCs. We identified an enrichment in extracellular matrix (ECM) transcripts, including Connective Tissue Growth Factor (Ctgf), which is usually expressed during development. We discovered that Ctgf levels are increased in a Yes-associated protein (YAP)-dependent fashion in response to rapid, local H2O2 signaling generated by stressed mitochondria in the injured sciatic nerve, a finding highlighting the importance of signals triggered by mechanical force to motor nerve repair. Through sequestration of Ctgf or inactivation of H2O2, we delayed the recovery of neuromuscular function by impairing SC migration and, in turn, axon-oriented re-growth. These data indicate that H2O2 and its downstream effector Ctgf are pro-regenerative factors that enable axonal growth, and reveal a striking ECM remodeling process during nerve regeneration upon local H2O2 signaling. Our study identifies key transcriptomic changes at the regenerating NMJ, providing a rich source of pro-regenerative factors with potential for alleviating the consequences of peripheral nerve injuries.

A thorough annotation of the krill transcriptome offers new insights for the study of physiological processes.

The krill species Euphausia superba plays a critical role in the food chain of the Antarctic ecosystem. Significant changes in climate conditions observed in the Antarctic Peninsula region in the last decades have already altered the distribution of krill and its reproductive dynamics. A deeper understanding of the adaptation capabilities of this species is urgently needed. The availability of a large body of RNA-seq assays allowed us to extend the current knowledge of the krill transcriptome. Our study covered the entire developmental process providing information of central relevance for ecological studies. Here we identified a series of genes involved in different steps of the krill moulting cycle, in the reproductive process and in sexual maturation in accordance with what was already described in previous works. Furthermore, the new transcriptome highlighted the presence of differentially expressed genes previously unknown, playing important roles in cuticle development as well as in energy storage during the krill life cycle. The discovery of new opsin sequences, specifically rhabdomeric opsins, one onychopsin, and one non-visual arthropsin, expands our knowledge of the krill opsin repertoire. We have collected all these results into the KrillDB2 database, a resource combining the latest annotation of the krill transcriptome with a series of analyses targeting genes relevant to krill physiology. KrillDB2 provides in a single resource a comprehensive catalog of krill genes; an atlas of their expression profiles over all RNA-seq datasets publicly available; a study of differential expression across multiple conditions. Finally, it provides initial indications about the expression of microRNA precursors, whose contribution to krill physiology has never been reported before.

Detecting differentially expressed circular RNAs from multiple quantification methods using a generalized linear mixed model.

Finding differentially expressed circular RNAs (circRNAs) is instrumental to understanding the molecular basis of phenotypic variation between conditions linked to circRNA-involving mechanisms. To date, several methods have been developed to identify circRNAs, and combining multiple tools is becoming an established approach to improve the detection rate and robustness of results in circRNA studies. However, when using a consensus strategy, it is unclear how circRNA expression estimates should be considered and integrated into downstream analysis, such as differential expression assessment. This work presents a novel solution to test circRNA differential expression using quantifications of multiple algorithms simultaneously. Our approach analyzes multiple tools' circRNA abundance count data within a single framework by leveraging generalized linear mixed models (GLMM), which account for the sample correlation structure within and between the quantification tools. We compared the GLMM approach with three widely used differential expression models, showing its higher sensitivity in detecting and efficiently ranking significant differentially expressed circRNAs. Our strategy is the first to consider combined estimates of multiple circRNA quantification methods, and we propose it as a powerful model to improve circRNA differential expression analysis.

Copy number alterations in stage I epithelial ovarian cancer highlight three genomic patterns associated with prognosis.

BACKGROUND: Stage I epithelial ovarian cancer (EOC) encompasses five histologically different subtypes of tumors confined to the ovaries with a generally favorable prognosis. Despite the intrinsic heterogeneity, all stage I EOCs are treated with complete resection and adjuvant therapy in most of the cases. Owing to the lack of robust prognostic markers, this often leads to overtreatment. Therefore, a better molecular characterization of stage I EOCs could improve the assessment of the risk of relapse and the refinement of optimal treatment options. MATERIALS AND METHODS: 205 stage I EOCs tumor biopsies with a median follow-up of eight years were gathered from two independent Italian tumor tissue collections, and the genome distribution of somatic copy number alterations (SCNAs) was investigated by shallow whole genome sequencing (sWGS) approach. RESULTS: Despite the variability in SCNAs distribution both across and within the histotypes, we were able to define three common genomic instability patterns, namely stable, unstable, and highly unstable. These patterns were based on the percentage of the genome affected by SCNAs and on their length. The genomic instability pattern was strongly predictive of patients' prognosis also with multivariate models including currently used clinico-pathological variables. CONCLUSIONS: The results obtained in this study support the idea that novel molecular markers, in this case genomic instability patterns, can anticipate the behavior of stage I EOC regardless of tumor subtype and provide valuable prognostic information. Thus, it might be propitious to extend the study of these genomic instability patterns to improve rational management of this disease.

NewWave: a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA-seq data.

SUMMARY: We present NewWave, a scalable R/Bioconductor package for the dimensionality reduction and batch effect removal of single-cell RNA sequencing data. To achieve scalability, NewWave uses mini-batch optimization and can work with out-of-memory data, enabling users to analyze datasets with millions of cells. AVAILABILITY AND IMPLEMENTATION: NewWave is implemented as an open-source R package available through the Bioconductor project at https://bioconductor.org/packages/NewWave/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Zebrafish Mutant Lines Reveal the Interplay between nr3c1 and nr3c2 in the GC-Dependent Regulation of Gene Transcription.

Glucocorticoids mainly exert their biological functions through their cognate receptor, encoded by the nr3c1 gene. Here, we analysed the glucocorticoids mechanism of action taking advantage of the availability of different zebrafish mutant lines for their receptor. The differences in gene expression patterns between the zebrafish gr knock-out and the grs357 mutant line, in which a point mutation prevents binding of the receptor to the hormone-responsive elements, reveal an intricate network of GC-dependent transcription. Particularly, we show that Stat3 transcriptional activity mainly relies on glucocorticoid receptor GR tethering activity: several Stat3 target genes are induced upon glucocorticoid GC exposure both in wild type and in grs357/s357 larvae, but not in gr knock-out zebrafish. To understand the interplay between GC, their receptor, and the mineralocorticoid receptor, which is evolutionarily and structurally related to the GR, we generated an mr knock-out line and observed that several GC-target genes also need a functional mineralocorticoid receptor MR to be correctly transcribed. All in all, zebrafish mutants and transgenic models allow in vivo analysis of GR transcriptional activities and interactions with other transcription factors such as MR and Stat3 in an in-depth and rapid way.

BrewerIX enables allelic expression analysis of imprinted and X-linked genes from bulk and single-cell transcriptomes.

Genomic imprinting and X chromosome inactivation (XCI) are two prototypical epigenetic mechanisms whereby a set of genes is expressed mono-allelically in order to fine-tune their expression levels. Defects in genomic imprinting have been observed in several neurodevelopmental disorders, in a wide range of tumours and in induced pluripotent stem cells (iPSCs). Single Nucleotide Variants (SNVs) are readily detectable by RNA-sequencing allowing the determination of whether imprinted or X-linked genes are aberrantly expressed from both alleles, although standardised analysis methods are still missing. We have developed a tool, named BrewerIX, that provides comprehensive information about the allelic expression of a large, manually-curated set of imprinted and X-linked genes. BrewerIX does not require programming skills, runs on a standard personal computer, and can analyze both bulk and single-cell transcriptomes of human and mouse cells directly from raw sequencing data. BrewerIX confirmed previous observations regarding the bi-allelic expression of some imprinted genes in naive pluripotent cells and extended them to preimplantation embryos. BrewerIX also identified misregulated imprinted genes in breast cancer cells and in human organoids and identified genes escaping XCI in human somatic cells. We believe BrewerIX will be useful for the study of genomic imprinting and XCI during development and reprogramming, and for detecting aberrations in cancer, iPSCs and organoids. Due to its ease of use to non-computational biologists, its implementation could become standard practice during sample assessment, thus raising the robustness and reproducibility of future studies.

The power of word-frequency-based alignment-free functions: a comprehensive large-scale experimental analysis.

MOTIVATION: Alignment-free (AF) distance/similarity functions are a key tool for sequence analysis. Experimental studies on real datasets abound and, to some extent, there are also studies regarding their control of false positive rate (Type I error). However, assessment of their power, i.e. their ability to identify true similarity, has been limited to some members of the D2 family. The corresponding experimental studies have concentrated on short sequences, a scenario no longer adequate for current applications, where sequence lengths may vary considerably. Such a State of the Art is methodologically problematic, since information regarding a key feature such as power is either missing or limited. RESULTS: By concentrating on a representative set of word-frequency-based AF functions, we perform the first coherent and uniform evaluation of the power, involving also Type I error for completeness. Two alternative models of important genomic features (CIS Regulatory Modules and Horizontal Gene Transfer), a wide range of sequence lengths from a few thousand to millions, and different values of k have been used. As a result, we provide a characterization of those AF functions that is novel and informative. Indeed, we identify weak and strong points of each function considered, which may be used as a guide to choose one for analysis tasks. Remarkably, of the 15 functions that we have considered, only four stand out, with small differences between small and short sequence length scenarios. Finally, to encourage the use of our methodology for validation of future AF functions, the Big Data platform supporting it is public. AVAILABILITY AND IMPLEMENTATION: The software is available at: https://github.com/pipp8/power_statistics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Regional and temporal heterogeneity of epithelial ovarian cancer tumor biopsies: implications for therapeutic strategies.

Stage III/IV epithelial ovarian cancer (EOC) is a systemic disease. The clonal relationship among different tumor lesions at diagnosis (spatial heterogeneity) and how tumor clonal architecture evolves over time (temporal heterogeneity) have not yet been defined. Such knowledge would help to develop new target-based strategies, as biomarkers which can adjudge the success of therapeutic intervention should be independent of spatial and temporal heterogeneity. The work described in this paper addresses spatial and temporal heterogeneity in a cohort of 71 tumor biopsies using targeted NGS technology. These samples were taken from twelve high grade serous (HGS) and seven non HSG-EOC, both at the time of primary surgery when the tumor was naïve to chemotherapy and after chemotherapy. Matched tumor lesions growing in the ovary or at other anatomical sites show very different mutational landscapes with branched tumor evolution. Mutations in ATM, ATR,TGFB3,VCAM1 and COL3A1 genes were shared across all lesions. BRCA1 and BRCA2 genes were frequently mutated in synchronous lesions of non HGS-EOC. Relapsed disease seems to originate from resistant clones originally present at the time of primary surgery rather than from resistance acquired de novo during platinum based therapy. Overall the work suggests that EOC continues to evolve. More detailed mapping of genetic lesions is necessary to improve therapeutic strategies.

Circulating miR-185-5p as a Potential Biomarker for Arrhythmogenic Right Ventricular Cardiomyopathy.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiac disease characterized by progressive myocardial fibro-fatty replacement, arrhythmias and risk of sudden death. Its diagnosis is challenging and often it is achieved after disease onset or postmortem. In this study, we sought to identify circulating microRNAs (miRNAs) differentially expressed in ARVC patients compared to healthy controls. In the pilot study, we screened the expression of 754 miRNAs from 21 ARVC patients and 20 healthy controls. After filtering the miRNAs considering a log fold-change cut-off of ±1, p-value < 0.05, we selected five candidate miRNAs for a subsequent validation study in which we used TaqMan-based real-time PCR to analyse samples from 37 ARVC patients and 30 healthy controls. We found miR-185-5p significantly upregulated in ARVC patients. Receiver operating characteristic analysis indicated an area under the curve of 0.854, corroborating the link of this miRNA and ARVC pathophysiology.