Master regulators of FGFR2 signalling and breast cancer risk

Expression-Driven Genetic Dependency Reveals Targets for Precision Medicine

Cancer cells are heterogeneous, each harboring distinct molecular aberrations and are dependent on different genes for their survival and proliferation. While successful targeted therapies have been developed based on driver DNA mutations, many patient tumors lack druggable mutations and have limited treatment options. Here, we hypothesize that new precision oncology targets may be identified through "expression-driven dependency", whereby cancer cells with high expression of a targeted gene are more vulnerable to the knockout of that gene. We introduce a Bayesian approach, BEACON, to identify such targets by jointly analyzing global transcriptomic and proteomic profiles with genetic dependency data of cancer cell lines across 17 tissue lineages. BEACON identifies known druggable genes, e.g., BCL2, ERBB2, EGFR, ESR1, MYC , while revealing new targets confirmed by both mRNA- and protein-expression driven dependency. Notably, the identified genes show an overall 3.8-fold enrichment for approved drug targets and enrich for druggable oncology targets by 7 to 10-fold. We experimentally validate that the depletion of GRHL2 , TP63 , and PAX5 effectively reduce tumor cell growth and survival in their dependent cells. Overall, we present the catalog of express-driven dependency targets as a resource for identifying novel therapeutic targets in precision oncology.

Mammary adipocytes promote breast tumor cell invasion and angiogenesis in the context of menopause and obesity

The mechanism(s) underlying obesity-related postmenopausal (PM) breast cancer (BC) are not clearly understood. We hypothesized that the increased local presence of 'obese' mammary adipocytes within the BC microenvironment promotes the acquisition of an invasive and angiogenic BC cell phenotype and accelerates tumor proliferation and progression. BC cells, treated with primary mammary adipocyte secretome from premenopausal (Pre-M) and PM obese women (ObAdCM; obese adipocyte conditioned-media) upregulated the expression of several pro-tumorigenic factors including VEGF, lipocalin-2 and IL-6. Both Pre-M and PM ObAdCM stimulated endothelial cell recruitment and proliferation and significantly stimulated BC cell proliferation, migration and invasion. IL-6 and LCN2 induced STAT3/Akt signaling in BC cells and STAT3 inhibition abrogated the ObAdCM-stimulated BC cell proliferation and migration. Expression of proangiogenic regulators including VEGF, NRP1, NRP2, IL8RB, TGFβ2, and TSP-1 were found to be differentially regulated in mammary adipocytes from obese PM women. Comparative RNAseq indicated an upregulation of PI3K/Akt signaling, ECM-receptor interactions and lipid/fatty acid metabolism in PM versus Pre-M mammary adipocytes. Our results demonstrate that irrespective of menopausal status, cross-talk between obese mammary adipocytes and BC cells promotes tumor aggressiveness and suggest that targeting the LCN2/IL-6/STAT3 signaling axis may be a useful strategy in obesity-driven breast tumorigenesis.

Omics-derived biological modules reflect metabolic brain changes in Alzheimer's disease

INTRODUCTION

Brain glucose hypometabolism, indexed by the fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging, is a metabolic signature of Alzheimer's disease (AD). However, the underlying biological pathways involved in these metabolic changes remain elusive.

METHODS

Here, we integrated [18F]FDG-PET images with blood and hippocampal transcriptomic data from cognitively unimpaired (CU, n = 445) and cognitively impaired (CI, n = 749) individuals using modular dimension reduction techniques and voxel-wise linear regression analysis.

RESULTS

Our results showed that multiple transcriptomic modules are associated with brain [18F]FDG-PET metabolism, with the top hits being a protein serine/threonine kinase activity gene cluster (peak-t(223) = 4.86, P value < 0.001) and zinc-finger-related regulatory units (peak-t(223) = 3.90, P value < 0.001).

DISCUSSION

By integrating transcriptomics with PET imaging data, we identified that serine/threonine kinase activity-associated genes and zinc-finger-related regulatory units are highly associated with brain metabolic changes in AD.

HIGHLIGHTS

We conducted an integrated analysis of system-based transcriptomics and fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) at the voxel level in Alzheimer's disease (AD). The biological process of serine/threonine kinase activity was the most associated with [18F]FDG-PET in the AD brain. Serine/threonine kinase activity alterations are associated with brain vulnerable regions in AD [18F]FDG-PET. Zinc-finger transcription factor targets were associated with AD brain [18F]FDG-PET metabolism.

DCS, a novel classifier system based on disulfidptosis reveals tumor microenvironment heterogeneity and guides frontline therapy for clear cell renal carcinoma

Background

Emerging evidence suggests that cell deaths are involved in tumorigenesis and progression, which may be treated as a novel direction of cancers. Recently, a novel type of programmed cell death, disulfidptosis, was discovered. However, the detailed biological and clinical impact of disulfidptosis and related regulators remains largely unknown.

Methods

In this work, we first enrolled pancancer datasets and performed multi-omics analysis, including gene expression, DNA methylation, copy number variation and single nucleic variation profiles. Then we deciphered the biological implication of disulfidptosis in clear cell renal cell carcinoma (ccRCC) by machine learning. Finally, a novel agent targeting at disulfidptosis in ccRCC was identified and verified.

Results

We found that disulfidptosis regulators were dysregulated among cancers, which could be explained by aberrant DNA methylation and genomic mutation events. Disulfidptosis scores were depressed among cancers and negatively correlated with epithelial mesenchymal transition. Disulfidptosis regulators could satisfactorily stratify risk subgroups in ccRCC, and a novel subtype, DCS3, owning with disulfidptosis depression, insensitivity to immune therapy and aberrant genome instability were identified and verified. Moreover, treating DCS3 with NU1025 could significantly inhibit ccRCC malignancy.

Conclusion

This work provided a better understanding of disulfidptosis in cancers and new insights into individual management based on disulfidptosis.

An in vitro model of acute horizontal basal cell activation reveals gene regulatory networks underlying the nascent activation phase

While horizontal basal cells (HBCs) make minor contributions to olfactory epithelium (OE) regeneration during homeostatic conditions, they possess a potent, latent capacity to activate and subsequently regenerate the OE following severe injury. Activation requires, and is mediated by, the downregulation of the transcription factor (TF) TP63. In this paper, we describe the cellular processes that drive the nascent stages of HBC activation. The compound phorbol 12-myristate 13-acetate (PMA) induces a rapid loss in TP63 protein and rapid enrichment of HOPX and the nuclear translocation of RELA, previously identified as components of HBC activation. Using bulk RNA sequencing (RNA-seq), we find that PMA-treated HBCs pass through various stages of activation identifiable by transcriptional regulatory signatures that mimic stages identified in vivo. These temporal stages are associated with varying degrees of engraftment and differentiation potential in transplantation assays. Together, these data show that our in vitro HBC activation system models physiologically relevant features of in vivo HBC activation and identifies new candidates for mechanistic testing.

Loss of LPAR6 and CAB39L dysregulates the basal-to-luminal urothelial differentiation program, contributing to bladder carcinogenesis

We describe a strategy that combines histologic and molecular mapping that permits interrogation of the chronology of changes associated with cancer development on a whole-organ scale. Using this approach, we present the sequence of alterations around RB1 in the development of bladder cancer. We show that RB1 is not involved in initial expansion of the preneoplastic clone. Instead, we found a set of contiguous genes that we term "forerunner" genes whose silencing is associated with the development of plaque-like field effects initiating carcinogenesis. Specifically, we identified five candidate forerunner genes (ITM2B, LPAR6, MLNR, CAB39L, and ARL11) mapping near RB1. Two of these genes, LPAR6 and CAB39L, are preferentially downregulated in the luminal and basal subtypes of bladder cancer, respectively. Their loss of function dysregulates urothelial differentiation, sensitizing the urothelium to N-butyl-N-(4-hydroxybutyl)nitrosamine-induced cancers, which recapitulate the luminal and basal subtypes of human bladder cancer.

An in vitro neurogenetics platform for precision disease modeling in the mouse

The power and scope of disease modeling can be markedly enhanced through the incorporation of broad genetic diversity. The introduction of pathogenic mutations into a single inbred mouse strain sometimes fails to mimic human disease. We describe a cross-species precision disease modeling platform that exploits mouse genetic diversity to bridge cell-based modeling with whole organism analysis. We developed a universal protocol that permitted robust and reproducible neural differentiation of genetically diverse human and mouse pluripotent stem cell lines and then carried out a proof-of-concept study of the neurodevelopmental gene DYRK1A. Results in vitro reliably predicted the effects of genetic background on Dyrk1a loss-of-function phenotypes in vivo. Transcriptomic comparison of responsive and unresponsive strains identified molecular pathways conferring sensitivity or resilience to Dyrk1a1A loss and highlighted differential messenger RNA isoform usage as an important determinant of response. This cross-species strategy provides a powerful tool in the functional analysis of candidate disease variants identified through human genetic studies.

BHLHE40/41 regulate microglia and peripheral macrophage responses associated with Alzheimer's disease and other disorders of lipid-rich tissues

Genetic and experimental evidence suggests that Alzheimer's disease (AD) risk alleles and genes may influence disease susceptibility by altering the transcriptional and cellular responses of macrophages, including microglia, to damage of lipid-rich tissues like the brain. Recently, sc/nRNA sequencing studies identified similar transcriptional activation states in subpopulations of macrophages in aging and degenerating brains and in other diseased lipid-rich tissues. We collectively refer to these subpopulations of microglia and peripheral macrophages as DLAMs. Using macrophage sc/nRNA-seq data from healthy and diseased human and mouse lipid-rich tissues, we reconstructed gene regulatory networks and identified 11 strong candidate transcriptional regulators of the DLAM response across species. Loss or reduction of two of these transcription factors, BHLHE40/41, in iPSC-derived microglia and human THP-1 macrophages as well as loss of Bhlhe40/41 in mouse microglia, resulted in increased expression of DLAM genes involved in cholesterol clearance and lysosomal processing, increased cholesterol efflux and storage, and increased lysosomal mass and degradative capacity. These findings provide targets for therapeutic modulation of macrophage/microglial function in AD and other disorders affecting lipid-rich tissues.

Transcription Factor Regulation of Gene Expression Network by ZNF385D and HAND2 in Carotid Atherosclerosis

Carotid intima-media thickness (CIMT) is a surrogate indicator for atherosclerosis and has been shown to predict cardiovascular risk in multiple large studies. Identification of molecular markers for carotid atheroma plaque formation can be critical for early intervention and prevention of atherosclerosis. This study performed transcription factor (TF) network analysis of global gene expression data focusing on two TF genes, ZNF385D and HAND2, whose polymorphisms have been recently reported to show association with CIMT. Genome-wide gene expression data were measured from pieces of carotid endarterectomy collected from 34 hypertensive patients (atheroma plaque of stages IV and above according to the Stary classification) each paired with one sample of distant macroscopically intact tissue (stages I and II). Transcriptional regulation networks or the regulons were reconstructed for ZNF385D (5644 target genes) and HAND2 (781 target genes) using network inference. Their association with the progression of carotid atheroma was examined using gene-set enrichment analysis with extremely high statistical significance for regulons of both ZNF385D and HAND2 (p < 6.95 × 10-7) suggesting the involvement of expression quantitative loci (eQTL). Functional annotation of the regulon genes found heavy involvement in the immune system's response to inflammation and infection in the development of atherosclerosis. Detailed examination of the regulation and correlation patterns suggests that activities of the two TF genes could have high clinical and interventional impacts on impairing carotid atheroma plaque formation and preventing carotid atherosclerosis.

TRPS1 modulates chromatin accessibility to regulate estrogen receptor alpha (ER) binding and ER target gene expression in luminal breast cancer cells

Common genetic variants in the repressive GATA-family transcription factor (TF) TRPS1 locus are associated with breast cancer risk, and luminal breast cancer cell lines are particularly sensitive to TRPS1 knockout. We introduced an inducible degron tag into the native TRPS1 locus within a luminal breast cancer cell line to identify the direct targets of TRPS1 and determine how TRPS1 mechanistically regulates gene expression. We acutely deplete over 80 percent of TRPS1 from chromatin within 30 minutes of inducing degradation. We find that TRPS1 regulates transcription of hundreds of genes, including those related to estrogen signaling. TRPS1 directly regulates chromatin structure, which causes estrogen receptor alpha (ER) to redistribute in the genome. ER redistribution leads to both repression and activation of dozens of ER target genes. Downstream from these primary effects, TRPS1 depletion represses cell cycle-related gene sets and reduces cell doubling rate. Finally, we show that high TRPS1 activity, calculated using a gene expression signature defined by primary TRPS1-regulated genes, is associated with worse breast cancer patient prognosis. Taken together, these data suggest a model in which TRPS1 modulates the genomic distribution of ER, both activating and repressing transcription of genes related to cancer cell fitness.

Cross-species comparative hippocampal transcriptomics in Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial pathology, with most cases having a sporadic origin. Recently, knock-in (KI) mouse models, such as the novel humanized amyloid-β (hAβ)-KI, have been developed to better resemble sporadic human AD.

METHODS

Here, we compared hippocampal publicly available transcriptomic profiles of transgenic (5xFAD and APP/PS1) and KI (hAβ-KI) mouse models with early- (EOAD) and late- (LOAD) onset AD patients.

RESULTS

The three mouse models presented more Gene Ontology biological processes terms and enriched signaling pathways in common with LOAD than with EOAD individuals. Experimental validation of consistently dysregulated genes revealed five altered in mice (SLC11A1, S100A6, CD14, CD33, and C1QB) and three in humans (S100A6, SLC11A1, and KCNK). Finally, we identified 17 transcription factors potentially acting as master regulators of AD.

CONCLUSION

Our cross-species analyses revealed that the three mouse models presented a remarkable similarity to LOAD, with the hAβ-KI being the more specific one.

An in vitro model of acute horizontal basal cell activation reveals dynamic gene regulatory networks underlying the acute activation phase

Horizontal basal cells (HBCs) activate only in response to severe olfactory epithelium (OE) injury. This activation is mediated by the loss of the transcription factor TP63. Using the compound phorbol 12-myristate 13-acetate (PMA), we find that we can model the process of acute HBC activation. First, we find that PMA treatment induces a rapid loss in TP63 protein and induces the expression of HOPX and the nuclear translocation of RELA, previously identified to mediate HBC activation. Using bulk RNA sequencing, we find that PMA-treated HBCs pass through various stages of acute activation identifiable by transcriptional regulatory signatures that mimic stages identified in vivo . These temporal stages are associated with varying degrees of engraftment and differentiation potential in transplantation assays. Together, this data shows that our model can model physiologically relevant features of HBC activation and identifies new candidates for mechanistic testing.

TimeTalk uses single-cell RNA-seq datasets to decipher cell-cell communication during early embryo development

Early embryonic development is a dynamic process that relies on proper cell-cell communication to form a correctly patterned embryo. Early embryo development-related ligand-receptor pairs (eLRs) have been shown to guide cell fate decisions and morphogenesis. However, the scope of eLRs and their influence on early embryo development remain elusive. Here, we developed a computational framework named TimeTalk from integrated public time-course mouse scRNA-seq datasets to decipher the secret of eLRs. Extensive validations and analyses were performed to ensure the involvement of identified eLRs in early embryo development. Process analysis identified that eLRs could be divided into six temporal windows corresponding to sequential events in the early embryo development process. With the interpolation strategy, TimeTalk is powerful in revealing paracrine settings and studying cell-cell communication during early embryo development. Furthermore, by using TimeTalk in the blastocyst and blastoid models, we found that the blastoid models share the core communication pathways with the epiblast and primitive endoderm lineages in the blastocysts. This result suggests that TimeTalk has transferability to other bio-dynamic processes. We also curated eLRs recognized by TimeTalk, which may provide valuable clues for understanding early embryo development and relevant disorders.

Revealing metastatic castration-resistant prostate cancer master regulator through lncRNAs-centered regulatory network

BACKGROUND

Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive form of cancer unresponsive to androgen deprivation therapy (ADT) that spreads quickly to other organs. Despite reduced androgen levels after ADT, mCRPC development and lethality continues to be conducted by the androgen receptor (AR) axis. The maintenance of AR signaling in mCRPC is a result of AR alterations, androgen intratumoral production, and the action of regulatory elements, such as noncoding RNAs (ncRNAs). ncRNAs are key elements in cancer signaling, acting in tumor growth, metabolic reprogramming, and tumor progression. In prostate cancer (PCa), the ncRNAs have been reported to be associated with AR expression, PCa proliferation, and castration resistance. In this study, we aimed to reconstruct the lncRNA-centered regulatory network of mCRPC and identify the lncRNAs which act as master regulators (MRs).

METHODS

We used publicly available RNA-sequencing to infer the regulatory network of lncRNAs in mCRPC. Five gene signatures were employed to conduct the master regulator analysis. Inferred MRs were then subjected to functional enrichment and symbolic regression modeling. The latter approach was applied to identify the lncRNAs with greater predictive capacity and potential as a biomarker in mCRPC.

RESULTS

We identified 31 lncRNAs involved in cellular proliferation, tumor metabolism, and invasion-metastasis cascade. SNHG18 and HELLPAR were the highlights of our results. SNHG18 was downregulated in mCRPC and enriched to metastasis signatures. It accurately distinguished both mCRPC and primary CRPC from normal tissue and was associated with epithelial-mesenchymal transition (EMT) and cell-matrix adhesion pathways. HELLPAR consistently distinguished mCRPC from primary CRPC and normal tissue using only its expression.

CONCLUSION

Our results contribute to understanding the regulatory behavior of lncRNAs in mCRPC and indicate SNHG18 and HELLPAR as master regulators and potential new diagnostic targets in this tumor.

TRPS1 modulates chromatin accessibility to regulate estrogen receptor (ER) binding and ER target gene expression in luminal breast cancer cells

Breast cancer is the most frequently diagnosed cancer in women. The most common subtype is luminal breast cancer, which is typically driven by the estrogen receptor α (ER), a transcription factor (TF) that activates many genes required for proliferation. Multiple effective therapies target this pathway, but individuals often develop resistance. Thus, there is a need to identify additional targets that regulate ER activity and contribute to breast tumor progression. TRPS1 is a repressive GATA-family TF that is overexpressed in breast tumors. Common genetic variants in the TRPS1 locus are associated with breast cancer risk, and luminal breast cancer cell lines are particularly sensitive to TRPS1 knockout. However, we do not know how TRPS1 regulates target genes to mediate these breast cancer patient and cellular outcomes. We introduced an inducible degron tag into the native TRPS1 locus within a luminal breast cancer cell line to identify the direct targets of TRPS1 and determine how TRPS1 mechanistically regulates gene expression. We acutely deplete over eighty percent of TRPS1 from chromatin within 30 minutes of inducing degradation. We find that TRPS1 regulates transcription of hundreds of genes, including those related to estrogen signaling. TRPS1 directly regulates chromatin structure, which causes ER to redistribute in the genome. ER redistribution leads to both repression and activation of dozens of ER target genes. Downstream from these primary effects, TRPS1 depletion represses cell cycle-related gene sets and reduces cell doubling rate. Finally, we show that high TRPS1 activity, calculated using a gene expression signature defined by primary TRPS1-regulated genes, is associated with worse breast cancer patient prognosis. Taken together, these data suggest a model in which TRPS1 modulates the activity of other TFs, both activating and repressing transcription of genes related to cancer cell fitness.

Differential expression of Dusp1 and immediate early response genes in the hippocampus of rats, subjected to forced swim test

The forced swim test (FST) is widely used to screen for potential antidepressant drugs and treatments. Despite this, the nature of stillness during FST and whether it resembles "depressive-like behavior" are widely debated issues. Furthermore, despite being widely used as a behavioral assay, the effects of the FST on the brain transcriptome are rarely investigated. Therefore, in this study we have investigated changes in the transcriptome of the rat hippocampus 20 min and 24 h after FST exposure. RNA-Seq is performed on the hippocampus tissues of rats 20 min and 24 h after an FST. Differentially expressed genes (DEGs) were identified using limma and used to construct gene interaction networks. Fourteen differentially expressed genes (DEGs) were identified only in the 20-m group. No DEGs were identified 24 h after the FST. These genes were used for Gene Ontology term enrichment and gene-network construction. Based on the constructed gene-interaction networks, we identified a group of DEGs (Dusp1, Fos, Klf2, Ccn1, and Zfp36) that appeared significant based on multiple methods of downstream analysis. Dusp1 appears especially important, as its role in the pathogenesis of depression has been demonstrated both in various animal models of depression and in patients with depressive disorders.

Molecular signature of neutrophil extracellular trap mediating disease module in idiopathic inflammatory myopathy

The rarity and heterogeneity of idiopathic inflammatory myopathy (IIM) pose challenges for researching IIM in affected individuals. We analyzed integrated transcriptomic datasets obtained using muscle tissues from patients with five distinct IIM subtypes to investigate the shared and distinctive cellular and molecular characteristics. A transcriptomic dataset of muscle tissues from normal controls (n = 105) and patients with dermatomyositis (n = 89), polymyositis (n = 33), inclusion body myositis (n = 121), immune-mediated necrotizing myositis (n = 75), and anti-synthetase syndrome (n = 18) was used for differential gene-expression analysis, functional-enrichment analysis, gene set-enrichment analysis, disease-module identification, and kernel-based diffusion scoring. Damage-associated molecular pattern-associated pathways and neutrophil-mediated immunity were significantly enriched across different IIM subtypes, although their activities varied. Interferons-signaling pathways were differentially activated across all five IIM subtypes. In particular, neutrophil extracellular trap (NET) formation was significantly activated and correlated with Fcγ R-mediated signaling pathways. NET formation-associated genes were key for establishing disease modules, and FCGRs, C1QA, and SERPINE1 markedly perturbed the disease modules. Integrated transcriptomic analysis of muscle tissues identified NETs as key components of neutrophil-mediated immunity involved in the pathogenesis of IIM subtypes and, thus, has therapeutically targetable value.

FOXA2 Cooperates with Mutant KRAS to Drive Invasive Mucinous Adenocarcinoma of the Lung

The endoderm-lineage transcription factor FOXA2 has been shown to inhibit lung tumorigenesis in in vitro and xenograft studies using lung cancer cell lines. However, FOXA2 expression in primary lung tumors does not correlate with an improved patient survival rate, and the functional role of FOXA2 in primary lung tumors remains elusive. To understand the role of FOXA2 in primary lung tumors in vivo, here, we conditionally induced the expression of FOXA2 along with either of the two major lung cancer oncogenes, EGFRL858R or KRASG12D, in the lung epithelium of transgenic mice. Notably, FOXA2 suppressed autochthonous lung tumor development driven by EGFRL858R, whereas FOXA2 promoted tumor growth driven by KRASG12D. Importantly, FOXA2 expression along with KRASG12D produced invasive mucinous adenocarcinoma (IMA) of the lung, a fatal mucus-producing lung cancer comprising approximately 5% of human lung cancer cases. In the mouse model in vivo and human lung cancer cells in vitro, FOXA2 activated a gene regulatory network involved in the key mucous transcription factor SPDEF and upregulated MUC5AC, whose expression is critical for inducing IMA. Coexpression of FOXA2 with mutant KRAS synergistically induced MUC5AC expression compared with that induced by FOXA2 alone. ChIP-seq combined with CRISPR interference indicated that FOXA2 bound directly to the enhancer region of MUC5AC and induced the H3K27ac enhancer mark. Furthermore, FOXA2 was found to be highly expressed in primary tumors of human IMA. Collectively, this study reveals that FOXA2 is not only a biomarker but also a driver for IMA in the presence of a KRAS mutation.

SIGNIFICANCE

FOXA2 expression combined with mutant KRAS drives invasive mucinous adenocarcinoma of the lung by synergistically promoting a mucous transcriptional program, suggesting strategies for targeting this lung cancer type that lacks effective therapies.

Expression-based subtypes define pathologic response to neoadjuvant immune-checkpoint inhibitors in muscle-invasive bladder cancer

Checkpoint immunotherapy (CPI) has increased survival for some patients with advanced-stage bladder cancer (BCa). However, most patients do not respond. Here, we characterized the tumor and immune microenvironment in pre- and post-treatment tumors from the PURE01 neoadjuvant pembrolizumab immunotherapy trial, using a consolidative approach that combined transcriptional and genetic profiling with digital spatial profiling. We identify five distinctive genetic and transcriptomic programs and validate these in an independent neoadjuvant CPI trial to identify the features of response or resistance to CPI. By modeling the regulatory network, we identify the histone demethylase KDM5B as a repressor of tumor immune signaling pathways in one resistant subtype (S1, Luminal-excluded) and demonstrate that inhibition of KDM5B enhances immunogenicity in FGFR3-mutated BCa cells. Our study identifies signatures associated with response to CPI that can be used to molecularly stratify patients and suggests therapeutic alternatives for subtypes with poor response to neoadjuvant immunotherapy.

Evaluation of the Association between FGFR2 Gene Polymorphisms and Breast Cancer Risk in the Bangladeshi Population

Breast cancer is considered the most frequent cause of mortality from malignancy among females. Fibroblast growth factor receptor 2 (FGFR2) gene polymorphisms are highly related to the risk of breast cancer. However, no investigation has been carried out to determine the association of FGFR2 gene polymorphisms in the Bangladeshi population. Based on polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP), this study was performed to evaluate the association of FGFR2 (rs1219648, rs2420946, and rs2981582) variants in 446 Bangladeshi women (226 cases and 220 controls). A significant association of the FGFR2 rs1219648 variant with breast malignancy was reported in additive model 1 (aOR = 2.87, p < 0.0001), additive model 2 (aOR = 5.62, p < 0.0001), the dominant model (aOR = 2.87, p < 0.0001), the recessive model (aOR = 4.04, p < 0.0001), and the allelic model (OR = 2.16, p < 0.0001). This investigation also explored the significant association of the rs2981582 variant with the risk of breast cancer in additive model 2 (aOR = 2. 60, p = 0.010), the recessive model (aOR = 2.47, p = 0.006), and the allelic model (OR = 1.39, p = 0.016). However, the FGFR2 rs2420946 polymorphism showed no association with breast cancer except in the overdominant model (aOR = 0.62, p = 0.048). Furthermore, GTT (p < 0.0001) haplotypes showed a correlation with breast cancer risk, and all variants showed strong linkage disequilibrium. Moreover, in silico gene expression analysis showed that the FGFR2 level was upregulated in BC tissues compared to healthy tissues. This study confirms the association of FGFR2 polymorphisms with breast cancer risk.

A comparative study of COVID-19 transcriptional signatures between clinical samples and preclinical cell models in the search for disease master regulators and drug repositioning candidates

Coronavirus disease 2019 (COVID-19) is an acute viral disease with millions of cases worldwide. Although the number of daily new cases and deaths has been dropping, there is still a need for therapeutic alternatives to deal with severe cases. A promising strategy to prospect new therapeutic candidates is to investigate the regulatory mechanisms involved in COVID-19 progression using integrated transcriptomics approaches. In this work, we aimed to identify COVID-19 Master Regulators (MRs) using a series of publicly available gene expression datasets of lung tissue from patients which developed the severe form of the disease. We were able to identify a set of six potential COVID-19 MRs related to its severe form, namely TAL1, TEAD4, EPAS1, ATOH8, ERG, and ARNTL2. In addition, using the Connectivity Map drug repositioning approach, we identified 52 different drugs which could be used to revert the disease signature, thus being candidates for the design of novel clinical treatments. Furthermore, we compared the identified signature and drugs with the ones obtained from the analysis of nasopharyngeal swab samples from infected patients and preclinical cell models. This comparison showed significant similarities between them, although also revealing some limitations on the overlap between clinical and preclinical data in COVID-19, highlighting the need for careful selection of the best model for each disease stage.

BHLHE40/41 regulate macrophage/microglia responses associated with Alzheimer's disease and other disorders of lipid-rich tissues

Background

Genetic and experimental evidence strongly implicates myeloid cells in the etiology of AD and suggests that AD-associated alleles and genes may modulate disease risk by altering the transcriptional and cellular responses of macrophages (like microglia) to damage of lipid-rich tissues (like the brain). Specifically, recent single-cell/nucleus RNA sequencing (sc/nRNA-seq) studies identified a transcriptionally distinct state of subsets of macrophages in aging or degenerating brains (usually referred to as disease-associated microglia or DAM) and in other diseased lipid-rich tissues (e.g., obese adipose tissue, fatty liver, and atherosclerotic plaques). We collectively refer to these subpopulations as lipid-associated macrophages or LAMs. Importantly, this particular activation state is characterized by increased expression of genes involved in the phagocytic clearance of lipid-rich cellular debris (efferocytosis), including several AD risk genes.

Methods

We used sc/nRNA-seq data from human and mouse microglia from healthy and diseased brains and macrophages from other lipid-rich tissues to reconstruct gene regulatory networks and identify transcriptional regulators whose regulons are enriched for LAM response genes (LAM TFs) across species. We then used gene knock-down/knock-out strategies to validate some of these LAM TFs in human THP-1 macrophages and iPSC-derived microglia in vitro, as well as mouse microglia in vivo.

Results

We nominate 11 strong candidate LAM TFs shared across human and mouse networks (BHLHE41, HIF1A, ID2, JUNB, MAF, MAFB, MEF2A, MEF2C, NACA, POU2F2 and SPI1). We also demonstrate a strong enrichment of AD risk alleles in the cistrome of BHLHE41 (and its close homolog BHLHE40), thus implicating its regulon in the modulation of disease susceptibility. Loss or reduction of BHLHE40/41 expression in human THP-1 macrophages and iPSC-derived microglia, as well as loss of Bhlhe40/41 in mouse microglia led to increased expression of LAM response genes, specifically those involved in cholesterol clearance and lysosomal processing, with a concomitant increase in cholesterol efflux and storage, as well as lysosomal mass and degradative capacity.

Conclusions

Taken together, this study nominates transcriptional regulators of the LAM response, experimentally validates BHLHE40/41 in human and mouse macrophages/microglia, and provides novel targets for therapeutic modulation of macrophage/microglia function in AD and other disorders of lipid-rich tissues.

Steroidogenic Factor 1, a Goldilocks Transcription Factor from Adrenocortical Organogenesis to Malignancy

Steroidogenic factor-1 (SF-1, also termed Ad4BP; NR5A1 in the official nomenclature) is a nuclear receptor transcription factor that plays a crucial role in the regulation of adrenal and gonadal development, function and maintenance. In addition to its classical role in regulating the expression of P450 steroid hydroxylases and other steroidogenic genes, involvement in other key processes such as cell survival/proliferation and cytoskeleton dynamics have also been highlighted for SF-1. SF-1 has a restricted pattern of expression, being expressed along the hypothalamic-pituitary axis and in steroidogenic organs since the time of their establishment. Reduced SF-1 expression affects proper gonadal and adrenal organogenesis and function. On the other hand, SF-1 overexpression is found in adrenocortical carcinoma and represents a prognostic marker for patients' survival. This review is focused on the current knowledge about SF-1 and the crucial importance of its dosage for adrenal gland development and function, from its involvement in adrenal cortex formation to tumorigenesis. Overall, data converge towards SF-1 being a key player in the complex network of transcriptional regulation within the adrenal gland in a dosage-dependent manner.

Epigenome-wide association study of short-term temperature fluctuations based on within-sibship analyses in Australian females

BACKGROUND

Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation.

METHODS

Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant's home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0-1 to TV 0-7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied.

RESULTS

Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0-3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0-3).

CONCLUSIONS

Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations.

DriverMP enables improved identification of cancer driver genes

BACKGROUND

Cancer is widely regarded as a complex disease primarily driven by genetic mutations. A critical concern and significant obstacle lies in discerning driver genes amid an extensive array of passenger genes.

FINDINGS

We present a new method termed DriverMP for effectively prioritizing altered genes on a cancer-type level by considering mutated gene pairs. It is designed to first apply nonsilent somatic mutation data, protein‒protein interaction network data, and differential gene expression data to prioritize mutated gene pairs, and then individual mutated genes are prioritized based on prioritized mutated gene pairs. Application of this method in 10 cancer datasets from The Cancer Genome Atlas demonstrated its great improvements over all the compared state-of-the-art methods in identifying known driver genes. Then, a comprehensive analysis demonstrated the reliability of the novel driver genes that are strongly supported by clinical experiments, disease enrichment, or biological pathway analysis.

CONCLUSIONS

The new method, DriverMP, which is able to identify driver genes by effectively integrating the advantages of multiple kinds of cancer data, is available at https://github.com/LiuYangyangSDU/DriverMP. In addition, we have developed a novel driver gene database for 10 cancer types and an online service that can be freely accessed without registration for users. The DriverMP method, the database of novel drivers, and the user-friendly online server are expected to contribute to new diagnostic and therapeutic opportunities for cancers.

Integrative network analysis reveals subtype-specific long non-coding RNA regulatory mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3, were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC.

FOXA1 repression drives lineage plasticity and immune heterogeneity in bladder cancers with squamous differentiation

Cancers arising from the bladder urothelium often exhibit lineage plasticity with regions of urothelial carcinoma adjacent to or admixed with regions of divergent histomorphology, most commonly squamous differentiation. To define the biologic basis for and clinical significance of this morphologic heterogeneity, here we perform integrated genomic analyses of mixed histology bladder cancers with separable regions of urothelial and squamous differentiation. We find that squamous differentiation is a marker of intratumoral genomic and immunologic heterogeneity in patients with bladder cancer and a biomarker of intrinsic immunotherapy resistance. Phylogenetic analysis confirms that in all cases the urothelial and squamous regions are derived from a common shared precursor. Despite the presence of marked genomic heterogeneity between co-existent urothelial and squamous differentiated regions, no recurrent genomic alteration exclusive to the urothelial or squamous morphologies is identified. Rather, lineage plasticity in bladder cancers with squamous differentiation is associated with loss of expression of FOXA1, GATA3, and PPARG, transcription factors critical for maintenance of urothelial cell identity. Of clinical significance, lineage plasticity and PD-L1 expression is coordinately dysregulated via FOXA1, with patients exhibiting morphologic heterogeneity pre-treatment significantly less likely to respond to immune checkpoint inhibitors.

CRISPRi screens in human iPSC-derived astrocytes elucidate regulators of distinct inflammatory reactive states

Astrocytes become reactive in response to insults to the central nervous system by adopting context-specific cellular signatures and outputs, but a systematic understanding of the underlying molecular mechanisms is lacking. In this study, we developed CRISPR interference screening in human induced pluripotent stem cell-derived astrocytes coupled to single-cell transcriptomics to systematically interrogate cytokine-induced inflammatory astrocyte reactivity. We found that autocrine-paracrine IL-6 and interferon signaling downstream of canonical NF-κB activation drove two distinct inflammatory reactive signatures, one promoted by STAT3 and the other inhibited by STAT3. These signatures overlapped with those observed in other experimental contexts, including mouse models, and their markers were upregulated in human brains in Alzheimer's disease and hypoxic-ischemic encephalopathy. Furthermore, we validated that markers of these signatures were regulated by STAT3 in vivo using a mouse model of neuroinflammation. These results and the platform that we established have the potential to guide the development of therapeutics to selectively modulate different aspects of inflammatory astrocyte reactivity.

An integrated proteomic and transcriptomic signature of the failing right ventricle in monocrotaline induced pulmonary arterial hypertension in male rats

Aim: Pulmonary arterial hypertension (PAH) is an obstructive pulmonary vasculopathy that results in death from right ventricular failure (RVF). There is limited understanding of the molecular mechanisms of RVF in PAH. Methods: In a PAH-RVF model induced by injection of adult male rats with monocrotaline (MCT; 60 mg/kg), we performed mass spectrometry to identify proteins that change in the RV as a consequence of PAH induced RVF. Bioinformatic analysis was used to integrate our previously published RNA sequencing data from an independent cohort of PAH rats. Results: We identified 1,277 differentially regulated proteins in the RV of MCT rats compared to controls. Integration of MCT RV transcriptome and proteome data sets identified 410 targets that are concordantly regulated at the mRNA and protein levels. Functional analysis of these data revealed enriched functions, including mitochondrial metabolism, cellular respiration, and purine metabolism. We also prioritized 15 highly enriched protein:transcript pairs and confirmed their biological plausibility as contributors to RVF. We demonstrated an overlap of these differentially expressed pairs with data published by independent investigators using multiple PAH models, including the male SU5416-hypoxia model and several male rat strains. Conclusion: Multiomic integration provides a novel view of the molecular phenotype of RVF in PAH which includes dysregulation of pathways involving purine metabolism, mitochondrial function, inflammation, and fibrosis.

Comprehensive Characterization of the Regulatory Landscape of Adrenocortical Carcinoma: Novel Transcription Factors and Targets Associated with Prognosis

We reconstructed a transcriptional regulatory network for adrenocortical carcinoma (ACC) using transcriptomic and clinical data from The Cancer Genome Atlas (TCGA)-ACC cohort. We investigated the association of transcriptional regulatory units (regulons) with overall survival, molecular phenotypes, and immune signatures. We annotated the ACC regulons with cancer hallmarks and assessed single sample regulon activities in the European Network for the Study of Adrenal Tumors (ENSAT) cohort. We found 369 regulons associated with overall survival and subdivided them into four clusters: RC1 and RC2, associated with good prognosis, and RC3 and RC4, associated with worse outcomes. The RC1 and RC3 regulons were highly correlated with the 'Steroid Phenotype,' while the RC2 and RC4 regulons were highly correlated with a molecular proliferation signature. We selected two regulons, NR5A1 (steroidogenic factor 1, SF-1) and CENPA (Centromeric Protein A), that were consistently associated with overall survival for further downstream analyses. The CENPA regulon was the primary regulator of MKI-67 (a marker of proliferation KI-67), while the NR5A1 regulon is a well-described transcription factor (TF) in ACC tumorigenesis. We also found that the ZBTB4 (Zinc finger and BTB domain-containing protein 4) regulon, which is negatively associated with CENPA in our transcriptional regulatory network, is also a druggable anti-tumorigenic TF. We anticipate that the ACC regulons may be used as a reference for further investigations concerning the complex molecular interactions in ACC tumors.

Chromatin Variants Reveal the Genetic Determinants of Oncogenesis in Breast Cancer

Breast cancer presents as multiple distinct disease entities. Each tumor harbors diverse cell populations defining a phenotypic heterogeneity that impinges on our ability to treat patients. To date, efforts mainly focused on genetic variants to find drivers of inter- and intratumor phenotypic heterogeneity. However, these efforts have failed to fully capture the genetic basis of breast cancer. Through recent technological and analytical approaches, the genetic basis of phenotypes can now be decoded by characterizing chromatin variants. These variants correspond to polymorphisms in chromatin states at DNA sequences that serve a distinct role across cell populations. Here, we review the function and causes of chromatin variants as they relate to breast cancer inter- and intratumor heterogeneity and how they can guide the development of treatment alternatives to fulfill the goal of precision cancer medicine.

A transcriptional network of cell cycle dysregulation in noninvasive papillary urothelial carcinoma

Human cancers display a restricted set of expression profiles, despite diverse mutational drivers. This has led to the hypothesis that select sets of transcription factors act on similar target genes as an integrated network, buffering a tumor's transcriptional state. Noninvasive papillary urothelial carcinoma (NIPUC) with higher cell cycle activity has higher risk of recurrence and progression. In this paper, we describe a transcriptional network of cell cycle dysregulation in NIPUC, which was delineated using the ARACNe algorithm applied to expression data from a new cohort (n = 81, RNA sequencing), and two previously published cohorts. The transcriptional network comprised 121 transcription factors, including the pluripotency factors SOX2 and SALL4, the sex hormone binding receptors ESR1 and PGR, and multiple homeobox factors. Of these 121 transcription factors, 65 and 56 were more active in tumors with greater and less cell cycle activity, respectively. When clustered by activity of these transcription factors, tumors divided into High Cell Cycle versus Low Cell Cycle groups. Tumors in the High Cell Cycle group demonstrated greater mutational burden and copy number instability. A putative mutational driver of cell cycle dysregulation, such as homozygous loss of CDKN2A, was found in only 50% of High Cell Cycle NIPUC, suggesting a prominent role of transcription factor activity in driving cell cycle dysregulation. Activity of the 121 transcription factors strongly associated with expression of EZH2 and other members of the PRC2 complex, suggesting regulation by this complex influences expression of the transcription factors in this network. Activity of transcription factors in this network also associated with signatures of pluripotency and epithelial-to-mesenchymal transition (EMT), suggesting they play a role in driving evolution to invasive carcinoma. Consistent with this, these transcription factors differed in activity between NIPUC and invasive urothelial carcinoma.

Integrating cell cycle score for precise risk stratification in ovarian cancer

Background: Ovarian cancer (OC) is a highly heterogeneous disease, of which the mesenchymal subtype has the worst prognosis, is the most aggressive, and has the highest drug resistance. The cell cycle pathway plays a vital role in ovarian cancer development and progression. We aimed to screen the key cell cycle genes that regulated the mesenchymal subtype and construct a robust signature for ovarian cancer risk stratification.

Methods: Network inference was conducted by integrating the differentially expressed cell cycle signature genes and target genes between the mesenchymal and non-mesenchymal subtypes of ovarian cancer and identifying the dominant cell cycle signature genes.

Results: Network analysis revealed that two cell cycle signature genes (POLA2 and KIF20B) predominantly regulated the mesenchymal modalities of OC and used to construct a prognostic model, termed the Cell Cycle Prognostic Signature of Ovarian Cancer (CCPOC). The CCPOC-high patients showed an unfavorable prognosis in the GSE26712 cohort, consistent with the results in the seven public validation cohorts and one independent internal cohort (BL-OC cohort, qRT-PCR, n = 51). Functional analysis, drug-sensitive analysis, and survival analysis showed that CCPOC-low patients were related to strengthened tumor immunogenicity and sensitive to the anti-PD-1/PD-L1 response rate in pan-cancer (r = −0.47, OC excluded), which indicated that CCPOC-low patients may be more sensitive to anti-PD-1/PD-L1.

Conclusion: We constructed and validated a subtype-specific, cell cycle-based prognostic signature for ovarian cancer, which has great potential for predicting the response of anti-PD-1/PD-L1.

Development of a miRNA-based classifier for detection of colorectal cancer molecular subtypes

Previously, colorectal cancer (CRC) has been classified into four distinct molecular subtypes based on transcriptome data. These consensus molecular subtypes (CMSs) have implications for our understanding of tumor heterogeneity and the prognosis of patients. So far, this classification has been based on the use of messenger RNAs (mRNAs), although microRNAs (miRNAs) have also been shown to play a role in tumor heterogeneity and biological differences between CMSs. In contrast to mRNAs, miRNAs have a smaller size and increased stability, facilitating their detection. Therefore, we built a miRNA-based CMS classifier by converting the existing mRNA-based CMS classification using machine learning (training dataset of n = 271). The performance of this miRNA-assigned CMS classifier (CMS-miRaCl) was evaluated in several datasets, achieving an overall accuracy of ~ 0.72 (0.6329-0.7987) in the largest dataset (n = 158). To gain insight into the biological relevance of CMS-miRaCl, we evaluated the most important features in the classifier. We found that miRNAs previously reported to be relevant in microsatellite-instable CRCs or Wnt signaling were important features for CMS-miRaCl. Following further studies to validate its robustness, this miRNA-based alternative might simplify the implementation of CMS classification in clinical workflows.

Analysis of the genomic landscapes of Barbadian and Nigerian women with triple negative breast cancer

PURPOSE

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype that disproportionately affects women of African ancestry (WAA) and is often associated with poor survival. Although there is a high prevalence of TNBC across West Africa and in women of the African diaspora, there has been no comprehensive genomics study to investigate the mutational profile of ancestrally related women across the Caribbean and West Africa.

METHODS

This multisite cross-sectional study used 31 formalin-fixed paraffin-embedded (FFPE) samples from Barbadian and Nigerian TNBC participants. High-resolution whole exome sequencing (WES) was performed on the Barbadian and Nigerian TNBC samples to identify their mutational profiles and comparisons were made to African American, European American and Asian American sequencing data obtained from The Cancer Genome Atlas (TCGA). Whole exome sequencing was conducted on tumors with an average of 382 × coverage and 4335 × coverage for pooled germline non-tumor samples.

RESULTS

Variants detected at high frequency in our WAA cohorts were found in the following genes NBPF12, PLIN4, TP53 and BRCA1. In the TCGA TNBC cases, these genes had a lower mutation rate, except for TP53 (32% in our cohort; 63% in TCGA-African American; 67% in TCGA-European American; 63% in TCGA-Asian). For all altered genes, there were no differences in frequency of mutations between WAA TNBC groups including the TCGA-African American cohort. For copy number variants, high frequency alterations were observed in PIK3CA, TP53, FGFR2 and HIF1AN genes.

CONCLUSION

This study provides novel insights into the underlying genomic alterations in WAA TNBC samples and shines light on the importance of inclusion of under-represented populations in cancer genomics and biomarker studies.

The regulatory landscape of retinoblastoma: a pathway analysis perspective

Retinoblastoma (Rb) is a rare intraocular tumour in early childhood, with an approximate incidence of 1 in 18 000 live births. Experimental studies for Rb are complex due to the challenges associated with obtaining a normal retina to contrast with diseased tissue. In this work, we reanalyse a dataset that contains normal retina samples. We identified the individual genes whose expression is different in Rb in contrast with normal tissue, determined the pathways whose global expression pattern is more distant from the global expression observed in normal tissue, and finally, we identified which transcription factors regulate the highest number of differentially expressed genes (DEGs) and proposed as transcriptional master regulators (TMRs). The enrichment of DEGs in the phototransduction and retrograde endocannabinoid signalling pathways could be associated with abnormal behaviour of the processes leading to cellular differentiation and cellular proliferation. On the other hand, the TMRs nuclear receptor subfamily 5 group A member 2 and hepatocyte nuclear factor 4 gamma are involved in hepatocyte differentiation. Therefore, the enrichment of aberrant expression in these transcription factors could suggest an abnormal retina development that could be involved in Rb origin and progression.

A Novel Attention-Mechanism Based Cox Survival Model by Exploiting Pan-Cancer Empirical Genomic Information

Cancer prognosis is an essential goal for early diagnosis, biomarker selection, and medical therapy. In the past decade, deep learning has successfully solved a variety of biomedical problems. However, due to the high dimensional limitation of human cancer transcriptome data and the small number of training samples, there is still no mature deep learning-based survival analysis model that can completely solve problems in the training process like overfitting and accurate prognosis. Given these problems, we introduced a novel framework called SAVAE-Cox for survival analysis of high-dimensional transcriptome data. This model adopts a novel attention mechanism and takes full advantage of the adversarial transfer learning strategy. We trained the model on 16 types of TCGA cancer RNA-seq data sets. Experiments show that our module outperformed state-of-the-art survival analysis models such as the Cox proportional hazard model (Cox-ph), Cox-lasso, Cox-ridge, Cox-nnet, and VAECox on the concordance index. In addition, we carry out some feature analysis experiments. Based on the experimental results, we concluded that our model is helpful for revealing cancer-related genes and biological functions.

High-Throughput Profiling of Colorectal Cancer Liver Metastases Reveals Intra- and Inter-Patient Heterogeneity in the EGFR and WNT Pathways Associated with Clinical Outcome

Simple Summary

Tumor heterogeneity can greatly influence therapy outcome and patient survival. In this study, we aimed at unraveling inter- and intra-patient heterogeneity of colorectal cancer liver metastases (CRLM). To this end, we comprehensively characterized CRLM using state-of-the-art high-throughput technologies combined with bioinformatics analyses. We found a high degree of inter- and intra-patient heterogeneity among the metastases, in particular in genes of the WNT and EGFR pathways. Through analyzing the master regulators and effectors associated with the regulation of these genes, we identified a specific gene signature that was highly expressed in a large cohort of colorectal cancer patients and associated with clinical outcome.

Abstract

Seventy percent of patients with colorectal cancer develop liver metastases (CRLM), which are a decisive factor in cancer progression. Therapy outcome is largely influenced by tumor heterogeneity, but the intra- and inter-patient heterogeneity of CRLM has been poorly studied. In particular, the contribution of the WNT and EGFR pathways, which are both frequently deregulated in colorectal cancer, has not yet been addressed in this context. To this end, we comprehensively characterized normal liver tissue and eight CRLM from two patients by standardized histopathological, molecular, and proteomic subtyping. Suitable fresh-frozen tissue samples were profiled by transcriptome sequencing (RNA-Seq) and proteomic profiling with reverse phase protein arrays (RPPA) combined with bioinformatic analyses to assess tumor heterogeneity and identify WNT- and EGFR-related master regulators and metastatic effectors. A standardized data analysis pipeline for integrating RNA-Seq with clinical, proteomic, and genetic data was established. Dimensionality reduction of the transcriptome data revealed a distinct signature for CRLM differing from normal liver tissue and indicated a high degree of tumor heterogeneity. WNT and EGFR signaling were highly active in CRLM and the genes of both pathways were heterogeneously expressed between the two patients as well as between the synchronous metastases of a single patient. An analysis of the master regulators and metastatic effectors implicated in the regulation of these genes revealed a set of four genes (SFN, IGF2BP1, STAT1, PIK3CG) that were differentially expressed in CRLM and were associated with clinical outcome in a large cohort of colorectal cancer patients as well as CRLM samples. In conclusion, high-throughput profiling enabled us to define a CRLM-specific signature and revealed the genes of the WNT and EGFR pathways associated with inter- and intra-patient heterogeneity, which were validated as prognostic biomarkers in CRC primary tumors as well as liver metastases.

Introduction to Genomic Network Reconstruction for Cancer Research

High-throughput genomic technologies have revolutionized the study of cancer. Current research in oncology is now limited more for the capacity of analyzing and interpreting data, rather than the availability of data itself. Integrative approaches to obtain functional information from data are at the core of the disciplines gathered under the systems biology banner. In this context, network models have been used to study cancer, from the identification of key molecules involved in the disease to the discovery of functional alterations associated with specific manifestations of the disease.In this chapter, we describe the state of the art of network reconstruction from genomic data, with an emphasis in gene expression experiments. We explore the strengths and limitations of correlation, Bayesian, and information theoretic approaches to network reconstruction. We present tools that leverage the flexibility of network science to gain a deeper understanding of cancer biology.

Incidence of FGFR2 Amplification and FGFR2 Fusion in Patients with Metastatic Cancer Using Clinical Sequencing

Aberrations in the fibroblast growth factor receptor2 (FGFR2) gene, including genetic alterations and chromosomal rearrangements, lead to the development and progression of cancer with poor prognosis. However, the mechanisms underlying the FGFR2 signaling pathway to facilitate the development of FGFR2-targeted therapies have not been fully explored. Here, we examined the clinicopathological features of FGFR2 amplification and fusion in gastrointestinal tract/genitourinary tract cancers. FGFR2 amplification and fusion were identified in approximately 1.5% and 1.1% of all cancer types in 1,373 patients, respectively, with both FGFR2 amplification and fusion occurring together at a rate of approximately 0.6%. Of all cancer types screened, gastric cancer (GC) was the most common cancer type with FGFR2 amplification (87.5% of all FGFR2 amplification case) or fusion (46.7% of all cases). In addition, FGFR2 alteration had poorer overall survival (OS, 13.7 months vs. 50.2 months, P = 0.0001) and progression-free survival (PFS, 5.6 months vs. 11.4 months, P = 0.0005) than did those without FGFR2 alteration, respectively. Taken together, our data underscore to screen solid cancer patients for FGFR2 aberrations in oncology clinic.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

Background

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.

Results

In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.

Conclusions

Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01021-x.

Colorectal Cancer-Associated Microbiome Patterns and Signatures

The gut microbiome is dynamic and shaped by diet, age, geography, and environment. The disruption of normal gut microbiota (dysbiosis) is closely related to colorectal cancer (CRC) risk and progression. To better identify and characterize CRC-associated dysbiosis, we collected six independent cohorts with matched normal pairs (when available) for comparison and exploration of the microbiota and their interactions with the host. Comparing the microbial community compositions between cancerous and adjacent noncancerous tissues, we found that more microbes were depleted than enriched in tumors. Despite taxonomic variations among cohorts, consistent depletion of normal microbiota (members of Clostridia and Bacteroidia) and significant enrichment of oral-originated pathogens (such as Fusobacterium nucleatum and Parvimonas micra) were observed in CRC compared to normal tissues. Sets of hub and hub-connecting microbes were subsequently identified to infer microbe-microbe interaction networks in CRC. Furthermore, biclustering was used for identifying coherent patterns between patients and microbes. Two patient-microbe interaction patterns, named P0 and P1, can be consistently identified among the investigated six CRC cohorts. Characterization of the microbial community composition of the two patterns revealed that patients in P0 and P1 differed significantly in microbial alpha and beta diversity, and CRC‐associated microbiota changes consist of continuous populations of widespread taxa rather than discrete enterotypes. In contrast to the P0, the patients in P1 have reduced microbial alpha diversity compared to the adjacent normal tissues, and P1 possesses more oral-related pathogens than P0 and controls. Collectively, our study investigated the CRC-associated microbiome changes, and identified reproducible microbial signatures across multiple independent cohorts. More importantly, we revealed that the CRC heterogeneity can be partially attributed to the variety and compositional differences of microbes and their interactions to humans.

Stage-stratified molecular profiling of non-muscle-invasive bladder cancer enhances biological, clinical, and therapeutic insight

Understanding the molecular determinants that underpin the clinical heterogeneity of non-muscle-invasive bladder cancer (NMIBC) is essential for prognostication and therapy development. Stage T1 disease in particular presents a high risk of progression and requires improved understanding. We present a detailed multi-omics study containing gene expression, copy number, and mutational profiles that show relationships to immune infiltration, disease recurrence, and progression to muscle invasion. We compare expression and genomic subtypes derived from all NMIBCs with those derived from the individual disease stages Ta and T1. We show that sufficient molecular heterogeneity exists within the separate stages to allow subclassification and that this is more clinically meaningful for stage T1 disease than that derived from all NMIBCs. This provides improved biological understanding and identifies subtypes of T1 tumors that may benefit from chemo- or immunotherapy.

The enhanced cell cycle related to the response to adjuvant therapy in pancreatic ductal adenocarcinoma

A major clinical challenge for treating patients with pancreatic ductal adenocarcinoma (PDAC) is identifying those that may benefit from adjuvant chemotherapy versus those that will not. Thus, there is a need for a robust and convenient biomarker for predicting chemotherapy response in PDAC patients. In this study, network inference was conducted by integrating the differentially expressed cell cycle signatures and target genes between the basal-like subtype and classical subtype of PDAC. As a result from this statistical analysis, two dominant cell cycle genes, RASAL2 and ASPM, were identified. Based on the expression levels of these two genes, we constructed a "Enhanced Cell Cycle" scoring system (ECC score). Patients were given an ECC score, and respectively divided into ECC-high and ECC-low groups. Survival, pathway enrichment, immune environment characteristics, and chemotherapy response analysis' were performed between the two groups in a total of 891 patients across 5 cohorts. ECC-high patients exhibited shortened recurrence-free survival (RFS) and overall survival (OS) rates. In addition, it was found that adjuvant chemotherapy could significantly improve the outcome of the ECC-high patients while ECC-low patients did not benefit from adjuvant chemotherapy. It was also found that there was less CD8+ T cell, natural killer (NK) cell, M1 macrophage, and plasma cell infiltration in ECC-high patients when compared to ECC-low patients. Also, the expression of CD73, an immune suppressor gene, and it's related hypoxia pathway were elevated in the ECC-high group when compared to the ECC-low group. In conclusion, this study showed that patients characterized as ECC-high not only had reduced RFS and OS rates, but were also more sensitive to adjuvant chemotherapy and could potentially be less sensitive to immune checkpoint inhibitors. Being able to characterize patients by these parameters would allow doctors to make more informed decisions on patient treatment regimens.

Single-cell transcriptomics identifies master regulators of neurodegeneration in SOD1 ALS iPSC-derived motor neurons

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative condition characterized by the loss of motor neurons. We utilized single-cell transcriptomics to uncover dysfunctional pathways in degenerating motor neurons differentiated from SOD1 E100G ALS patient-derived induced pluripotent stem cells (iPSCs) and respective isogenic controls. Differential gene expression and network analysis identified activation of developmental pathways and core transcriptional factors driving the ALS motor neuron gene dysregulation. Specifically, we identified activation of SMAD2, a downstream mediator of the transforming growth factor β (TGF-β) signaling pathway as a key driver of SOD1 iPSC-derived motor neuron degeneration. Importantly, our analysis indicates that activation of TGFβ signaling may be a common mechanism shared between SOD1, FUS, C9ORF72, VCP, and sporadic ALS motor neurons. Our results demonstrate the utility of single-cell transcriptomics in mapping disease-relevant gene regulatory networks driving neurodegeneration in ALS motor neurons. We find that ALS-associated mutant SOD1 targets transcriptional networks that perturb motor neuron homeostasis.

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Single-cell transcriptomic analysis of SOD1 E100G ALS iPSC-derived motor neurons

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Mapping an ALS-relevant transcriptional network

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Upregulation of developmental programs in familial and sporadic ALS motor neurons

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Inhibition of TGFβ pathway improves SOD1 ALS iPSC-derived motor neuron survival

Early Pro-Inflammatory Signal and T-Cell Activation Associate With Vaccine-Induced Anti-Vaccinia Protective Neutralizing Antibodies

Both vaccine “take” and neutralizing antibody (nAb) titer are historical correlates for vaccine-induced protection from smallpox. We analyzed a subset of samples from a phase 2a trial of three DNA/HIV-1 primes and a recombinant Tiantan vaccinia virus-vectored (rTV)/HIV-1 booster and found that a proportion of participants showed no anti-vaccinia nAb response to the rTV/HIV-1 booster, despite successful vaccine “take.” Using a rich transcriptomic and vaccinia-specific immunological dataset with fine kinetic sampling, we investigated the molecular mechanisms underlying nAb response. Blood transcription module analysis revealed the downregulation of the activator protein 1 (AP-1) pathway in responders, but not in non-responders, and the upregulation of T-cell activation in responders. Furthermore, transcriptional factor network reconstruction revealed the upregulation of AP-1 core genes at hour 4 and day 1 post-rTV/HIV-1 vaccination, followed by a downregulation from day 3 until day 28 in responders. In contrast, AP-1 core and pro-inflammatory genes were upregulated on day 7 in non-responders. We speculate that persistent pro-inflammatory signaling early post-rTV/HIV-1 vaccination inhibits the nAb response.

Reverse Engineering of the Pediatric Sepsis Regulatory Network and Identification of Master Regulators

Sepsis remains a leading cause of death in ICUs all over the world, with pediatric sepsis accounting for a high percentage of mortality in pediatric ICUs. Its complexity makes it difficult to establish a consensus on genetic biomarkers and therapeutic targets. A promising strategy is to investigate the regulatory mechanisms involved in sepsis progression, but there are few studies regarding gene regulation in sepsis. This work aimed to reconstruct the sepsis regulatory network and identify transcription factors (TFs) driving transcriptional states, which we refer to here as master regulators. We used public gene expression datasets to infer the co-expression network associated with sepsis in a retrospective study. We identified a set of 15 TFs as potential master regulators of pediatric sepsis, which were divided into two main clusters. The first cluster corresponded to TFs with decreased activity in pediatric sepsis, and GATA3 and RORA, as well as other TFs previously implicated in the context of inflammatory response. The second cluster corresponded to TFs with increased activity in pediatric sepsis and was composed of TRIM25, RFX2, and MEF2A, genes not previously described as acting in a coordinated way in pediatric sepsis. Altogether, these results show how a subset of master regulators TF can drive pathological transcriptional states, with implications for sepsis biology and treatment.