Non-canonical transcriptional regulation of the poor prognostic factor UGT2B17 in chronic lymphocytic leukemic and normal B cells.

BACKGROUND: High expression of the glycosyltransferase UGT2B17 represents an independent adverse prognostic marker in chronic lymphocytic leukemia (CLL). It also constitutes a predictive marker for therapeutic response and a drug resistance mechanism. The key determinants driving expression of the UGT2B17 gene in normal and leukemic B-cells remain undefined. The UGT2B17 transcriptome is complex and is comprised of at least 10 alternative transcripts, identified by previous RNA-sequencing of liver and intestine. We hypothesized that the transcriptional program regulating UGT2B17 in B-lymphocytes is distinct from the canonical expression previously characterized in the liver. RESULTS: RNA-sequencing and genomics data revealed a specific genomic landscape at the UGT2B17 locus in normal and leukemic B-cells. RNA-sequencing and quantitative PCR data indicated that the UGT2B17 enzyme is solely encoded by alternative transcripts expressed in CLL patient cells and not by the canonical transcript widely expressed in the liver and intestine. Chromatin accessible regions (ATAC-Seq) in CLL cells mapped with alternative promoters and non-coding exons, which may be derived from endogenous retrotransposon elements. By luciferase reporter assays, we identified key cis-regulatory STAT3, RELA and interferon regulatory factor (IRF) binding sequences driving the expression of UGT2B17 in lymphoblastoid and leukemic B-cells. Electrophoretic mobility shift assays and pharmacological inhibition demonstrated key roles for the CLL prosurvival transcription factors STAT3 and NF-κB in the leukemic expression of UGT2B17. CONCLUSIONS: UGT2B17 expression in B-CLL is driven by key regulators of CLL progression. Our data suggest that a NF-κB/STAT3/IRF/UGT2B17 axis may represent a novel B-cell pathway promoting disease progression and drug resistance.

SARS-CoV-2 infection modifies the transcriptome of the megakaryocytes in the bone marrow.

ABSTRACT: Megakaryocytes (MKs), integral to platelet production, predominantly reside in the bone marrow (BM) and undergo regulated fragmentation within sinusoid vessels to release platelets into the bloodstream. Inflammatory states and infections influence MK transcription, potentially affecting platelet functionality. Notably, COVID-19 has been associated with altered platelet transcriptomes. In this study, we investigated the hypothesis that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection could affect the transcriptome of BM MKs. Using spatial transcriptomics to discriminate subpopulations of MKs based on proximity to BM sinusoids, we identified ∼19 000 genes in MKs. Machine learning techniques revealed that the transcriptome of healthy murine BM MKs exhibited minimal differences based on proximity to sinusoid vessels. Furthermore, at peak SARS-CoV-2 viremia, when the disease primarily affected the lungs, MKs were not significantly different from those from healthy mice. Conversely, a significant divergence in the MK transcriptome was observed during systemic inflammation, although SARS-CoV-2 RNA was never detected in the BM, and it was no longer detectable in the lungs. Under these conditions, the MK transcriptional landscape was enriched in pathways associated with histone modifications, MK differentiation, NETosis, and autoimmunity, which could not be explained by cell proximity to sinusoid vessels. Notably, the type I interferon signature and calprotectin (S100A8/A9) were not induced in MKs under any condition. However, inflammatory cytokines induced in the blood and lungs of COVID-19 mice were different from those found in the BM, suggesting a discriminating impact of inflammation on this specific subset of cells. Collectively, our data indicate that a new population of BM MKs may emerge through COVID-19-related pathogenesis.

Transcriptomic Analysis of Mineralized Adipose-Derived Stem Cell Tissues for Calcific Valve Disease Modelling.

Calcific aortic valve disease (CAVD) is characterized by the fibrosis and mineralization of the aortic valve, which leads to aortic stenosis and heart failure. At the cellular level, this is due to the osteoblastic-like differentiation of valve interstitial cells (VICs), resulting in the calcification of the tissue. Unfortunately, human VICs are not readily available to study CAVD pathogenesis and the implicated mechanisms in vitro; however, adipose-derived stromal/stem cells (ASCs), carrying the patient's specific genomic features, have emerged as a promising cell source to model cardiovascular diseases due to their multipotent nature, availability, and patient-specific characteristics. In this study, we describe a comprehensive transcriptomic analysis of tissue-engineered, scaffold-free, ASC-embedded mineralized tissue sheets using bulk RNA sequencing. Bioinformatic and gene set enrichment analyses revealed the up-regulation of genes associated with the organization of the extracellular matrix (ECM), suggesting that the ECM could play a vital role in the enhanced mineralization observed in these tissue-engineered ASC-embedded sheets. Upon comparison with publicly available gene expression datasets from CAVD patients, striking similarities emerged regarding cardiovascular diseases and ECM functions, suggesting a potential link between ECM gene expression and CAVDs pathogenesis. A matrisome-related sub-analysis revealed the ECM microenvironment promotes the transcriptional activation of the master gene runt-related transcription factor 2 (RUNX2), which is essential in CAVD development. Tissue-engineered ASC-embedded sheets with enhanced mineralization could be a valuable tool for research and a promising avenue for the identification of more effective aortic valve replacement therapies.

Loss of testosterone induces postprandial insulin resistance and increases the expression of the hepatic antioxidant flavin-containing monooxygenases in mice exposed to intermittent hypoxia.

AIM: We tested the hypothesis that low testosterone alters the effects of intermittent hypoxia (IH) on glucose homeostasis, hepatic oxidative stress, and transcriptomic profile in male mice. METHODS: We used sham-operated or orchiectomized (ORX) mice exposed to normoxia (Nx) or IH for 2 weeks. We performed fasting insulin and glucose tolerance tests and assessed fasting and postprandial insulin resistance with the HOMA-IR. The activity of hepatic prooxidant (NADPH oxidase-NOX), antioxidant enzymes (superoxide dismutase, catalase, and glutathione peroxidase-SOD, Cat, GPx), lipid peroxidation (MDA concentration), and the total concentration of glutathione (GSH) were measured under postprandial conditions. mRNA sequencing and pathway enrichment analyses were used to identify hepatic genes underlying the interactions between IH and testosterone. RESULTS: In Sham mice, IH improves fasting insulin sensitivity and glucose tolerance, while there are no effects of IH in ORX mice. In ORX mice, IH induces postprandial hyperinsulinemia, insulin resistance, and a prooxidant profile of enzyme activity (low SOD activity) without altering hepatic MDA and GSH content. ORX and IH altered the expression of genes involved in oxidoreductase activities, cytochromes-dependent pathways, and glutathione metabolism. Among the genes upregulated in ORX-IH mice, the flavin-containing monooxygenases (FMO) are particularly relevant since these are potent hepatic antioxidants that could help prevent overt oxidative stress in ORX-IH mice. CONCLUSION: Low levels of testosterone in male mice exposed to IH induce post-prandial hyperinsulinemia and insulin resistance and determine the mechanisms by which the liver handles IH-induced oxidative stress.

Developing a cluster-based approach for deciphering complexity in individuals with neurodevelopmental differences.

Objective: Individuals with neurodevelopmental disorders such as global developmental delay (GDD) present both genotypic and phenotypic heterogeneity. This diversity has hampered developing of targeted interventions given the relative rarity of each individual genetic etiology. Novel approaches to clinical trials where distinct, but related diseases can be treated by a common drug, known as basket trials, which have shown benefits in oncology but have yet to be used in GDD. Nonetheless, it remains unclear how individuals with GDD could be clustered. Here, we assess two different approaches: agglomerative and divisive clustering. Methods: Using the largest cohort of individuals with GDD, which is the Deciphering Developmental Disorders (DDD), characterized using a systematic approach, we extracted genotypic and phenotypic information from 6,588 individuals with GDD. We then used a k-means clustering (divisive) and hierarchical agglomerative clustering (HAC) to identify subgroups of individuals. Next, we extracted gene network and molecular function information with regard to the clusters identified by each approach. Results: HAC based on phenotypes identified in individuals with GDD revealed 16 clusters, each presenting with one dominant phenotype displayed by most individuals in the cluster, along with other minor phenotypes. Among the most common phenotypes reported were delayed speech, absent speech, and seizure. Interestingly, each phenotypic cluster molecularly included several (3-12) gene sub-networks of more closely related genes with diverse molecular function. k-means clustering also segregated individuals harboring those phenotypes, but the genetic pathways identified were different from the ones identified from HAC. Conclusion: Our study illustrates how divisive (k-means) and agglomerative clustering can be used in order to group individuals with GDD for future basket trials. Moreover, the result of our analysis suggests that phenotypic clusters should be subdivided into molecular sub-networks for an increased likelihood of successful treatment. Finally, a combination of both agglomerative and divisive clustering may be required for developing of a comprehensive treatment.

Early Diagnosis: End-to-End CNN-LSTM Models for Mass Spectrometry Data Classification.

Liquid chromatography-mass spectrometry (LC-MS) is a powerful method for cell profiling. The use of LC-MS technology is a tool of choice for cancer research since it provides molecular fingerprints of analyzed tissues. However, the ubiquitous presence of noise, the peaks shift between acquisitions, and the huge amount of information owing to the high dimensionality of the data make rapid and accurate cancer diagnosis a challenging task. Deep learning (DL) models are not only effective classifiers but are also well suited to jointly learn feature representation and classification tasks. This is particularly relevant when applied to raw LC-MS data and hence avoid the need for costly preprocessing and complicated feature selection. In this study, we propose a new end-to-end DL methodology that addresses all of the above challenges at once, while preserving the high potential of LC-MS data. Our DL model is designed to early discriminate between tumoral and normal tissues. It is a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) Network. The CNN network allows for significantly reducing the high dimensionality of the data while learning spatially relevant features. The LSTM network enables our model to capture temporal patterns. We show that our model outperforms not only benchmark models but also state-of-the-art models developed on the same data. Our framework is a promising strategy for improving early cancer detection during a diagnostic process.

Multi-omics analysis: Paving the path toward achieving precision medicine in cancer treatment and immuno-oncology.

The acceleration of large-scale sequencing and the progress in high-throughput computational analyses, defined as omics, was a hallmark for the comprehension of the biological processes in human health and diseases. In cancerology, the omics approach, initiated by genomics and transcriptomics studies, has revealed an incredible complexity with unsuspected molecular diversity within a same tumor type as well as spatial and temporal heterogeneity of tumors. The integration of multiple biological layers of omics studies brought oncology to a new paradigm, from tumor site classification to pan-cancer molecular classification, offering new therapeutic opportunities for precision medicine. In this review, we will provide a comprehensive overview of the latest innovations for multi-omics integration in oncology and summarize the largest multi-omics dataset available for adult and pediatric cancers. We will present multi-omics techniques for characterizing cancer biology and show how multi-omics data can be combined with clinical data for the identification of prognostic and treatment-specific biomarkers, opening the way to personalized therapy. To conclude, we will detail the newest strategies for dissecting the tumor immune environment and host-tumor interaction. We will explore the advances in immunomics and microbiomics for biomarker identification to guide therapeutic decision in immuno-oncology.

Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry.

Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.

Recurrent chromosomal translocations in sarcomas create a megacomplex that mislocalizes NuA4/TIP60 to Polycomb target loci.

Chromosomal translocations frequently promote carcinogenesis by producing gain-of-function fusion proteins. Recent studies have identified highly recurrent chromosomal translocations in patients with endometrial stromal sarcomas (ESSs) and ossifying fibromyxoid tumors (OFMTs), leading to an in-frame fusion of PHF1 (PCL1) to six different subunits of the NuA4/TIP60 complex. While NuA4/TIP60 is a coactivator that acetylates chromatin and loads the H2A.Z histone variant, PHF1 is part of the Polycomb repressive complex 2 (PRC2) linked to transcriptional repression of key developmental genes through methylation of histone H3 on lysine 27. In this study, we characterize the fusion protein produced by the EPC1-PHF1 translocation. The chimeric protein assembles a megacomplex harboring both NuA4/TIP60 and PRC2 activities and leads to mislocalization of chromatin marks in the genome, in particular over an entire topologically associating domain including part of the HOXD cluster. This is linked to aberrant gene expression-most notably increased expression of PRC2 target genes. Furthermore, we show that JAZF1-implicated with a PRC2 component in the most frequent translocation in ESSs, JAZF1-SUZ12-is a potent transcription activator that physically associates with NuA4/TIP60, its fusion creating outcomes similar to those of EPC1-PHF1 Importantly, the specific increased expression of PRC2 targets/HOX genes was also confirmed with ESS patient samples. Altogether, these results indicate that most chromosomal translocations linked to these sarcomas use the same molecular oncogenic mechanism through a physical merge of NuA4/TIP60 and PRC2 complexes, leading to mislocalization of histone marks and aberrant Polycomb target gene expression.

DIA Proteomics and Machine Learning for the Fast Identification of Bacterial Species in Biological Samples.

Identification of bacterial species in biological samples is essential in many applications. However, the standard methods usually use a time-consuming bacterial culture (24-48 h) and sometimes lack in specificity. To overcome these limitations, we developed a new protocol, combining LC-MS/MS analysis in Data Independent Acquisition mode and machine learning algorithms, enabling the accurate identification of the bacterial species contaminating a sample in a few hours without bacterial culture. In this chapter, we describe the three steps of the protocol (spectral libraries generation, training step, identification step) to generate customized peptide signatures and use them for bacterial identification in biological samples through targeted proteomics analyses and prediction models.

MRG Proteins Are Shared by Multiple Protein Complexes With Distinct Functions.

MRG15/MORF4L1 is a highly conserved protein in eukaryotes that contains a chromodomain (CHD) recognizing methylation of lysine 36 on histone H3 (H3K36me3) in chromatin. Intriguingly, it has been reported in the literature to interact with several different factors involved in chromatin modifications, gene regulation, alternative mRNA splicing, and DNA repair by homologous recombination. To get a complete and reliable picture of associations in physiological conditions, we used genome editing and tandem affinity purification to analyze the stable native interactome of human MRG15, its paralog MRGX/MORF4L2 that lacks the CHD, and MRGBP (MRG-binding protein) in isogenic K562 cells. We found stable interchangeable association of MRG15 and MRGX with the NuA4/TIP60 histone acetyltransferase/chromatin remodeler, Sin3B histone deacetylase/demethylase, ASH1L histone methyltransferase, and PALB2-BRCA2 DNA repair protein complexes. These associations were further confirmed and analyzed by CRISPR tagging of endogenous proteins and comparison of expressed isoforms. Importantly, based on structural information, point mutations could be introduced that specifically disrupt MRG15 association with some complexes but not others. Most interestingly, we also identified a new abundant native complex formed by MRG15/X-MRGBP-BRD8-EP400NL (EP400 N-terminal like) that is functionally similar to the yeast TINTIN (Trimer Independent of NuA4 for Transcription Interactions with Nucleosomes) complex. Our results show that EP400NL, being homologous to the N-terminal region of NuA4/TIP60 subunit EP400, creates TINTIN by competing for BRD8 association. Functional genomics indicate that human TINTIN plays a role in transcription of specific genes. This is most likely linked to the H4ac-binding bromodomain of BRD8 along the H3K36me3-binding CHD of MRG15 on the coding region of transcribed genes. Taken together, our data provide a complete detailed picture of human MRG proteins-associated protein complexes, which are essential to understand and correlate their diverse biological functions in chromatin-based nuclear processes.

T cell apoptosis characterizes severe Covid-19 disease.

Severe SARS-CoV-2 infections are characterized by lymphopenia, but the mechanisms involved are still elusive. Based on our knowledge of HIV pathophysiology, we hypothesized that SARS-CoV-2 infection-mediated lymphopenia could also be related to T cell apoptosis. By comparing intensive care unit (ICU) and non-ICU COVID-19 patients with age-matched healthy donors, we found a strong positive correlation between plasma levels of soluble FasL (sFasL) and T cell surface expression of Fas/CD95 with the propensity of T cells to die and CD4 T cell counts. Plasma levels of sFasL and T cell death are correlated with CXCL10 which is part of the signature of 4 biomarkers of disease severity (ROC, 0.98). We also found that members of the Bcl-2 family had modulated in the T cells of COVID-19 patients. More importantly, we demonstrated that the pan-caspase inhibitor, Q-VD, prevents T cell death by apoptosis and enhances Th1 transcripts. Altogether, our results are compatible with a model in which T-cell apoptosis accounts for T lymphopenia in individuals with severe COVID-19. Therefore, a strategy aimed at blocking caspase activation could be beneficial for preventing immunodeficiency in COVID-19 patients.

Association between genome-wide epigenetic and genetic alterations in breast cancer tissue and response to HER2-targeted therapies in HER2-positive breast cancer patients: new findings and a systematic review.

Recent evidence suggests that genetic and epigenetic mechanisms might be associated with acquired resistance to cancer therapies. The aim of this study was to assess the association of genome-wide genetic and epigenetic alterations with the response to anti-HER2 agents in HER2-positive breast cancer patients. PubMed was screened for articles published until March 2021 on observational studies investigating the association of genome-wide genetic and epigenetic alterations, measured in breast cancer tissues or blood, with the response to targeted treatment in HER2-positive breast cancer patients. Sixteen studies were included in the review along with ours, in which we compared the genome-wide DNA methylation pattern in breast tumor tissues of patients who acquired resistance to treatment (case group, n = 6) to that of patients who did not develop resistance (control group, n = 6). Among genes identified as differentially methylated between the breast cancer tissue of cases and controls, one of them, PRKACA, was also reported as differentially expressed in two studies included in the review. Although included studies were heterogeneous in terms of methodology and study population, our review suggests that genes of the PI3K pathway may play an important role in developing resistance to anti-HER2 agents in breast cancer patients. Genome-wide genetic and epigenetic alterations measured in breast cancer tissue or blood might be promising markers of resistance to anti-HER2 agents in HER2-positive breast cancer patients. Further studies are needed to confirm these data.

Identification of Abundant and Functional dodecaRNAs (doRNAs) Derived from Ribosomal RNA.

Using a modified RNA-sequencing (RNA-seq) approach, we discovered a new family of unusually short RNAs mapping to ribosomal RNA 5.8S, which we named dodecaRNAs (doRNAs), according to the number of core nucleotides (12 nt) their members contain. Using a new quantitative detection method that we developed, we confirmed our RNA-seq data and determined that the minimal core doRNA sequence and its 13-nt variant C-doRNA (doRNA with a 5' Cytosine) are the two most abundant doRNAs, which, together, may outnumber microRNAs. The C-doRNA/doRNA ratio is stable within species but differed between species. doRNA and C-doRNA are mainly cytoplasmic and interact with heterogeneous nuclear ribonucleoproteins (hnRNP) A0, A1 and A2B1, but not Argonaute 2. Reporter gene activity assays suggest that C-doRNA may function as a regulator of Annexin II receptor (AXIIR) expression. doRNAs are differentially expressed in prostate cancer cells/tissues and may control cell migration. These findings suggest that unusually short RNAs may be more abundant and important than previously thought.

A Homozygous Deep Intronic Mutation Alters the Splicing of Nebulin Gene in a Patient With Nemaline Myopathy.

Nemaline myopathy is a rare disorder affecting the muscle sarcomere. Mutations in nebulin gene (NEB) are known to be responsible for about 50% of nemaline myopathy cases. Nebulin is a giant protein which is formed integrally with the sarcomeric thin filament. This complex gene is under extensive alternative splicing giving rise to multiple isoforms. In this study, we report a 6-year-old boy presenting with general muscular weaknesses. Identification of rod-shaped structures in the patient' biopsy raised doubt about the presence of a nemaline myopathy. Next-generation sequencing was used to identify a causative mutation for the patient syndrome. A homozygous deep intronic substitution was found in the intron 144 of the NEB. The variant was predicted by in silico tools to create a new donor splice site. Molecular analysis has shown that the mutation could alter splicing events of the nebulin gene leading to a significant decrease of isoforms level. This change in the expression level of nebulin could give rise to functional consequences in the sarcomere. These results are consistent with the phenotypes observed in the patient. Such a discovery of variants in this gene will allow a better understanding of the involvement of nebulin in neuromuscular diseases and help find new treatments for the nemaline myopathy.

Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation (PERSPECTIVE I&I).

Early detection of breast cancer through screening reduces breast cancer mortality. The benefits of screening must also be considered within the context of potential harms (e.g., false positives, overdiagnosis). Furthermore, while breast cancer risk is highly variable within the population, most screening programs use age to determine eligibility. A risk-based approach is expected to improve the benefit-harm ratio of breast cancer screening programs. The PERSPECTIVE I&I (Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation) project seeks to improve personalized risk assessment to allow for a cost-effective, population-based approach to risk-based screening and determine best practices for implementation in Canada. This commentary describes the four inter-related activities that comprise the PERSPECTIVE I&I project. 1: Identification and validation of novel moderate to high-risk susceptibility genes. 2: Improvement, validation, and adaptation of a risk prediction web-tool for the Canadian context. 3: Development and piloting of a socio-ethical framework to support implementation of risk-based breast cancer screening. 4: Economic analysis to optimize the implementation of risk-based screening. Risk-based screening and prevention is expected to benefit all women, empowering them to work with their healthcare provider to make informed decisions about screening and prevention.

A founder mutation in the PLPBP gene in families from Saguenay-Lac-St-Jean region affected by a pyridoxine-dependent epilepsy.

Pyridoxine-dependent epilepsy (PDE) is a relatively rare subgroup of epileptic disorders. They generally present in infancy as an early onset epileptic encephalopathy or seizures, refractory to standard treatments, with rapid and variable responses to vitamin B6 treatment. Whole exome sequencing of three unrelated families identified homozygous pathogenic mutation c.370_373del, p.Asp124fs in PLPBP gene in five persons. Haplotype analysis showed a single shared profile for the affected persons and their parents, leading to a hypothesis about founder effect of the mutation in Saguenay-Lac-St-Jean region of French Canadians. All affected probands also shared one single mitochondrial haplotype T2b3 and two rare variations in the mitochondrial genome m.801A>G and m.5166A>G suggesting that a single individual female introduced PLPBP mutation c.370_373del, p.Asp124fs in Quebec. The mutation p.Asp124fs causes a severe disease phenotype with delayed myelination and cortical/subcortical brain atrophy. The most noteworthy radiological finding in this Quebec founder mutation is the presence of the temporal cysts that can be used as a marker of the disease. Also, both patients, who are alive, had a history of prenatal supplements taken by their mothers as antiemetic medication with high doses of pyridoxine. In the context of suspected PDE in patients with neonatal refractory seizures, treatment with pyridoxine and/or Pyridoxal-5-phophate has to be started immediately and continued until the results of genetic analysis received. Even with early appropriate treatment, neurological outcome of our patient is still poor.

KLF5 and NFYA factors as novel regulators of prostate cancer cell metabolism.

Prostate cancer (PCa) cells rely on the androgen receptor (AR) signaling axis to reprogram metabolism to sustain aberrant proliferation. Whether additional transcription factors participate to this reprogramming remains mostly unknown. To identify such factors, DNA motif analyses were performed in the promoter and regulatory regions of genes sensitive to androgens in PCa cells. These analyses identified two transcription factors, KLF5 and NFYA, as possibly associated with PCa cell metabolism. In clinical datasets, KLF5 and NFYA expression levels were associated with disease aggressiveness, being significantly decreased and increased, respectively, during PCa progression. Their expression was next investigated by qPCR and Western blot in human PCa cell models, revealing a positive regulation of KLF5 by androgens and a correlation between NFYA and AR protein expression status. siRNA-mediated knockdown of KLF5 increased human PCa cell proliferation rate in AR-positive cell models, suggesting a tumor suppressor function. Live-cell metabolic assays showed that knockdown of KLF5 promoted mitochondrial respiration, a key metabolic pathway associated with PCa progression. The opposite was observed for knockdown of NFYA regarding proliferation and respiration. RNA-seq analyses following the knockdown of either KLF5 and NFYA confirmed that both factors regulated distinct metabolic gene signatures, as well as other gene signatures, explaining their differential impact on PCa cell proliferation and metabolism. Overall, our findings identify KLF5 and NFYA as novel regulators of PCa cell metabolism.

Modulating HSF1 levels impacts expression of the estrogen receptor α and antiestrogen response.

Master transcription factors control the transcriptional program and are essential to maintain cellular functions. Among them, steroid nuclear receptors, such as the estrogen receptor α (ERα), are central to the etiology of hormone-dependent cancers which are accordingly treated with corresponding endocrine therapies. However, resistance invariably arises. Here, we show that high levels of the stress response master regulator, the heat shock factor 1 (HSF1), are associated with antiestrogen resistance in breast cancer cells. Indeed, overexpression of HSF1 leads to ERα degradation, decreased expression of ERα-activated genes, and antiestrogen resistance. Furthermore, we demonstrate that reducing HSF1 levels reinstates expression of the ERα and restores response to antiestrogens. Last, our results establish a proof of concept that inhibition of HSF1, in combination with antiestrogens, is a valid strategy to tackle resistant breast cancers. Taken together, we are proposing a mechanism where high HSF1 levels interfere with the ERα-dependent transcriptional program leading to endocrine resistance in breast cancer.

eTumorMetastasis: A Network-based Algorithm Predicts Clinical Outcomes Using Whole-exome Sequencing Data of Cancer Patients.

Continual reduction in sequencing cost is expanding the accessibility of genome sequencing data for routine clinical applications. However, the lack of methods to construct machine learning-based predictive models using these datasets has become a crucial bottleneck for the application of sequencing technology in clinics. Here, we develop a new algorithm, eTumorMetastasis, which transforms tumor functional mutations into network-based profiles and identifies network operational gene (NOG) signatures. NOG signatures model the tipping point at which a tumor cell shifts from a state that doesn't favor recurrence to one that does. We show that NOG signatures derived from genomic mutations of tumor founding clones (i.e., the 'most recent common ancestor' of the cells within a tumor) significantly distinguish the recurred and non-recurred breast tumors as well as outperform the most popular genomic test (i.e., Oncotype DX). These results imply that mutations of the tumor founding clones are associated with tumor recurrence and can be used to predict clinical outcomes. As such, predictive tools could be used in clinics to guide treatment routes. Finally, the concepts underlying the eTumorMetastasis pave the way for the application of genome sequencing in predictions for other complex genetic diseases. eTumorMetastasis pseudocode and related data used in this study are available at https://github.com/WangEdwinLab/eTumorMetastasis.