Cross-species regulatory network analysis identifies a synergistic interaction between FOXM1 and CENPF that drives prostate cancer malignancy

Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium

The Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have leveraged a microfluidics-based Plate-Seq technology to survey drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Built on this dataset, we implemented an efficient computational framework to define a tissue-specific protein activity landscape of these drugs and reported almost 50 million differential protein activities derived from drug perturbations vs. vehicle controls. These analyses revealed thousands of highly reproducible and novel, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide drug functional network, characterization of MoA-related drug clusters and off-target effects, dramatical expansion of druggable human proteome, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins, most never reported before. The drug perturbation profile resource described here represents the first, large-scale, whole-genome-wide, RNA-Seq based dataset assembled to date, with the proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, facilitates mechanistic exploration of drug functions, supports systematic and quantitative approaches to precision oncology, and serves as a rich data foundation for drug discovery.

Ras-dependent activation of BMAL2 regulates hypoxic metabolism in pancreatic cancer

To identify drivers of malignancy in human pancreatic ductal adenocarcinoma (PDAC), we performed regulatory network analysis on a large collection of expression profiles from laser capture microdissected samples of PDAC and benign precursors. We discovered that BMAL2 plays a role in the initiation, progression, post resection survival, and KRAS activity in PDAC. Functional analysis of BMAL2 target genes led us to hypothesize that it plays a role in regulating the response to hypoxia, a critical but poorly understood feature of PDAC physiology. Knockout of BMAL2 in multiple human PDAC cell lines revealed effects on viability and invasion, particularly under hypoxic conditions. Loss of BMAL2 also affected glycolysis and other metabolic processes. We found that BMAL2 directly regulates hypoxia-responsive target genes. We also found that BMAL2 is necessary for the stabilization of HIF1A upon exposure to hypoxia, but destabilizes HIF2A under hypoxia. These data demonstrate that BMAL2 is a master transcriptional regulator of hypoxia responses in PDAC and may serve as a long-sought molecular switch that distinguishes HIF1A- and HIF2A-dependent modes of hypoxic metabolism.

Predicting transcriptional outcomes of novel multigene perturbations with GEARS

Understanding cellular responses to genetic perturbation is central to numerous biomedical applications, from identifying genetic interactions involved in cancer to developing methods for regenerative medicine. However, the combinatorial explosion in the number of possible multigene perturbations severely limits experimental interrogation. Here, we present graph-enhanced gene activation and repression simulator (GEARS), a method that integrates deep learning with a knowledge graph of gene-gene relationships to predict transcriptional responses to both single and multigene perturbations using single-cell RNA-sequencing data from perturbational screens. GEARS is able to predict outcomes of perturbing combinations consisting of genes that were never experimentally perturbed. GEARS exhibited 40% higher precision than existing approaches in predicting four distinct genetic interaction subtypes in a combinatorial perturbation screen and identified the strongest interactions twice as well as prior approaches. Overall, GEARS can predict phenotypically distinct effects of multigene perturbations and thus guide the design of perturbational experiments.

Stem-cell states converge in multistage cutaneous squamous cell carcinoma development

Stem cells play a critical role in cancer development by contributing to cell heterogeneity, lineage plasticity, and drug resistance. We created gene expression networks from hundreds of mouse tissue samples (both normal and tumor) and integrated these with lineage tracing and single-cell RNA-seq, to identify convergence of cell states in premalignant tumor cells expressing markers of lineage plasticity and drug resistance. Two of these cell states representing multilineage plasticity or proliferation were inversely correlated, suggesting a mutually exclusive relationship. Treatment of carcinomas in vivo with chemotherapy repressed the proliferative state and activated multilineage plasticity whereas inhibition of differentiation repressed plasticity and potentiated responses to cell cycle inhibitors. Manipulation of this cell state transition point may provide a source of potential combinatorial targets for cancer therapy.

Contribution of CENP-F to FOXM1-Mediated Discordant Centromere and Kinetochore Transcriptional Regulation

Proper chromosome segregation is required to ensure chromosomal stability. The centromere (CEN) is a unique chromatin domain defined by CENP-A and is responsible for recruiting the kinetochore (KT) during mitosis, ultimately regulating microtubule spindle attachment and mitotic checkpoint function. Upregulation of many CEN/KT genes is commonly observed in cancer. Here, we show that although FOXM1 occupies promoters of many CEN/KT genes with MYBL2, FOXM1 overexpression alone is insufficient to drive the FOXM1-correlated transcriptional program. CENP-F is canonically an outer kinetochore component; however, it functions with FOXM1 to coregulate G2/M transcription and proper chromosome segregation. Loss of CENP-F results in altered chromatin accessibility at G2/M genes and reduced FOXM1-MBB complex formation. We show that coordinated CENP-FFOXM1 transcriptional regulation is a cancer-specific function. We observe a small subset of CEN/KT genes including CENP-C, that are not regulated by FOXM1. Upregulation of CENP-C in the context of CENP-A overexpression leads to increased chromosome missegregation and cell death suggesting that escape of CENP-C from FOXM1 regulation is a cancer survival mechanism. Together, we show that FOXM1 and CENP-F coordinately regulate G2/M genes, and this coordination is specific to a subset of genes to allow for maintenance of chromosome instability levels and subsequent cell survival.

Comprehensive data mining reveals RTK/RAS signaling pathway as a promoter of prostate cancer lineage plasticity through transcription factors and CNV

Prostate cancer lineage plasticity is a key driver in the transition to neuroendocrine prostate cancer (NEPC), and the RTK/RAS signaling pathway is a well-established cancer pathway. Nevertheless, the comprehensive link between the RTK/RAS signaling pathway and lineage plasticity has received limited investigation. In particular, the intricate regulatory network governing the interplay between RTK/RAS and lineage plasticity remains largely unexplored. The multi-omics data were clustered with the coefficient of argument and neighbor joining algorithm. Subsequently, the clustered results were analyzed utilizing the GSEA, gene sets related to stemness, multi-lineage state datasets, and canonical cancer pathway gene sets. Finally, a comprehensive exploration of the data based on the ssGSEA, WGCNA, GSEA, VIPER, prostate cancer scRNA-seq data, and the GPSAdb database was conducted. Among the six modules in the clustering results, there are 300 overlapping genes, including 3 previously unreported prostate cancer genes that were validated to be upregulated in prostate cancer through RT-qPCR. Function Module 6 shows a positive correlation with prostate cancer cell stemness, multi-lineage states, and the RTK/RAS signaling pathway. Additionally, the 19 leading-edge genes of the RTK/RAS signaling pathway promote prostate cancer lineage plasticity through a complex network of transcriptional regulation and copy number variations. In the transcriptional regulation network, TP63 and FOXO1 act as suppressors of prostate cancer lineage plasticity, whereas RORC exerts a promoting effect. This study provides a comprehensive perspective on the role of the RTK/RAS pathway in prostate cancer lineage plasticity and offers new clues for the treatment of NEPC.

Elucidation and Pharmacologic Targeting of Master Regulator Dependencies in Coexisting Diffuse Midline Glioma Subpopulations

Diffuse Midline Gliomas (DMGs) are universally fatal, primarily pediatric malignancies affecting the midline structures of the central nervous system. Despite decades of clinical trials, treatment remains limited to palliative radiation therapy. A major challenge is the coexistence of molecularly distinct malignant cell states with potentially orthogonal drug sensitivities. To address this challenge, we leveraged established network-based methodologies to elucidate Master Regulator (MR) proteins representing mechanistic, non-oncogene dependencies of seven coexisting subpopulations identified by single-cell analysis-whose enrichment in essential genes was validated by pooled CRISPR/Cas9 screens. Perturbational profiles of 372 clinically relevant drugs helped identify those able to invert the activity of subpopulation-specific MRs for follow-up in vivo validation. While individual drugs predicted to target individual subpopulations-including avapritinib, larotrectinib, and ruxolitinib-produced only modest tumor growth reduction in orthotopic models, systemic co-administration induced significant survival extension, making this approach a valuable contribution to the rational design of combination therapy.

Prostate cancer: Novel genetic and immunologic biomarkers

Prostate cancer (PCa) is considered one of the most prevalent male malignancies worldwide with a global burden estimated to increase over the next two decades. Due to significant mortality and debilitation of survival, early diagnosis has been described as key. Unfortunately, current diagnostic serum-based strategies have low specificity and sensitivity. Histologic examination is invasive and not useful for treatment and monitoring purposes. Hence, a plethora of studies have been conducted to identify and validate an efficient noninvasive approach in the diagnosis, staging, and prognosis of PCa. These investigations may be categorized as genetic (non-coding biomarkers and gene markers), immunologic (immune cells, interleukins, cytokines, antibodies, and auto-antibodies), and heterogenous (PSA-related markers, PHI-related indices, and urinary biomarkers) subgroups. This review examines current approaches and potential strategies using biomarker panels in PCa.

Tumor Explants Elucidate a Cascade of Paracrine SHH, WNT, and VEGF Signals Driving Pancreatic Cancer Angiosuppression

The sparse vascularity of pancreatic ductal adenocarcinoma (PDAC) presents a mystery: What prevents this aggressive malignancy from undergoing neoangiogenesis to counteract hypoxia and better support growth? An incidental finding from prior work on paracrine communication between malignant PDAC cells and fibroblasts revealed that inhibition of the Hedgehog (HH) pathway partially relieved angiosuppression, increasing tumor vascularity through unknown mechanisms. Initial efforts to study this phenotype were hindered by difficulties replicating the complex interactions of multiple cell types in vitro. Here we identify a cascade of paracrine signals between multiple cell types that act sequentially to suppress angiogenesis in PDAC. Malignant epithelial cells promote HH signaling in fibroblasts, leading to inhibition of noncanonical WNT signaling in fibroblasts and epithelial cells, thereby limiting VEGFR2-dependent activation of endothelial hypersprouting. This cascade was elucidated using human and murine PDAC explant models, which effectively retain the complex cellular interactions of native tumor tissues.

SIGNIFICANCE

We present a key mechanism of tumor angiosuppression, a process that sculpts the physiologic, cellular, and metabolic environment of PDAC. We further present a computational and experimental framework for the dissection of complex signaling cascades that propagate among multiple cell types in the tissue environment. This article is featured in Selected Articles from This Issue, p. 201.

Mechanism-centric regulatory network identifies NME2 and MYC programs as markers of Enzalutamide resistance in CRPC

Heterogeneous response to Enzalutamide, a second-generation androgen receptor signaling inhibitor, is a central problem in castration-resistant prostate cancer (CRPC) management. Genome-wide systems investigation of mechanisms that govern Enzalutamide resistance promise to elucidate markers of heterogeneous treatment response and salvage therapies for CRPC patients. Focusing on the de novo role of MYC as a marker of Enzalutamide resistance, here we reconstruct a CRPC-specific mechanism-centric regulatory network, connecting molecular pathways with their upstream transcriptional regulatory programs. Mining this network with signatures of Enzalutamide response identifies NME2 as an upstream regulatory partner of MYC in CRPC and demonstrates that NME2-MYC increased activities can predict patients at risk of resistance to Enzalutamide, independent of co-variates. Furthermore, our experimental investigations demonstrate that targeting MYC and its partner NME2 is beneficial in Enzalutamide-resistant conditions and could provide an effective strategy for patients at risk of Enzalutamide resistance and/or for patients who failed Enzalutamide treatment.

Oncogenic role of FOXM1 in human prostate cancer (Review)

Prostate cancer is the leading cause of cancer‑related mortality among men worldwide. In particular, castration‑resistant prostate cancer presents a formidable clinical challenge and emphasizes the need to develop novel therapeutic strategies. Forkhead box M1 (FOXM1) is a multifaceted transcription factor that is implicated in the acquisition of the multiple cancer hallmark capabilities in prostate cancer cells, including sustaining proliferative signaling, resisting cell death and the activation of invasion and metastasis. Elevated FOXM1 expression is frequently observed in prostate cancer, and in particular, FOXM1 overexpression is closely associated with poor clinical outcomes in patients with prostate cancer. In the present review, recent advances in the understanding of the oncogenic role of deregulated FOXM1 expression in prostate cancer were highlighted. In addition, the molecular mechanisms by which FOXM1 regulates prostate cancer development and progression were described, thereby providing knowledge and a conceptual framework for FOXM1. The present review also provided valuable insight into the inherent challenges associated with translating biomedical knowledge into effective therapeutic strategies for prostate cancer.

A review on gene regulatory network reconstruction algorithms based on single cell RNA sequencing

BACKGROUND

Understanding gene regulatory networks (GRNs) is essential for unraveling the molecular mechanisms governing cellular behavior. With the advent of high-throughput transcriptome measurement technology, researchers have aimed to reverse engineer the biological systems, extracting gene regulatory rules from their outputs, which represented by gene expression data. Bulk RNA sequencing, a widely used method for measuring gene expression, has been employed for GRN reconstruction. However, it falls short in capturing dynamic changes in gene expression at the level of individual cells since it averages gene expression across mixed cell populations.

OBJECTIVE

In this review, we provide an overview of 15 GRN reconstruction tools and discuss their respective strengths and limitations, particularly in the context of single cell RNA sequencing (scRNA-seq).

METHODS

Recent advancements in scRNA-seq break new ground of GRN reconstruction. They offer snapshots of the individual cell transcriptomes and capturing dynamic changes. We emphasize how these technological breakthroughs have enhanced GRN reconstruction.

CONCLUSION

GRN reconstructors can be classified based on their requirement for cellular trajectory, which represents a dynamical cellular process including differentiation, aging, or disease progression. Benchmarking studies support the superiority of GRN reconstructors that do not require trajectory analysis in identifying regulator-target relationships. However, methods equipped with trajectory analysis demonstrate better performance in identifying key regulatory factors. In conclusion, researchers should select a suitable GRN reconstructor based on their specific research objectives.

CENPF Upregulation is Associated with Immunosuppressive Status and Poor Clinical Outcomes in Lung Adenocarcinoma Validated by qRT-PCR

OBJECTIVE

CENPF-differentially expressed in various types of cancers-is a marker of poor prognosis. However, studies on the impact of CENPF on patient prognosis in lung adenocarcinoma regarding immune infiltration are lacking.

METHODS

CENPF expression profiles were analyzed in the GEO and TCGA databases. qRT-PCR was used to verify CENPF mRNA expression in lung adenocarcinoma cell lines. The prognostic value of CENPF was evaluated by combining data from clinical samples in the GEPIA2 and TCGA databases. Metascape and WebGestalt were used for enrichment analysis of gene sets most positively associated with CENPF. Immune cell infiltration score data were retrieved from TCGA and the correlation between CENPF expression and immune cell infiltration was analyzed.

RESULTS

CENPF expression was elevated in 29 types of cancer. CENPF was highly expressed and increased with tumor grade in lung adenocarcinoma. Immunohistochemical and qRT-PCR analyses revealed that CENPF expression was upregulated in lung adenocarcinoma tissues and cells. High expression of CENPF significantly worsened prognoses in patients with multiple malignancies, including lung adenocarcinoma. Results from gene set enrichment analysis indicated significant enrichment of the progesterone-mediated oocyte maturation pathway. Immune infiltration analysis revealed that CD4+ Th2 cell infiltration was significantly higher in the high CENPF expression group.

CONCLUSION

Upregulation of CENPF expression was related to poor progression-free survival, disease- free survival, and overall survival in patients with lung adenocarcinoma. High expression of CENPF was markedly related to genes associated with the immune checkpoint. Lung adenocarcinoma samples with high CENPF expression had increased CD4+ Th2 cell infiltration. Our findings indicate that CENPF promotes CD4+ Th2 cell infiltration through oncogenic activity and may be used as a biomarker for predicting patient outcomes in lung adenocarcinoma.

Contribution of CENP-F to FOXM1-mediated discordant centromere and kinetochore transcriptional regulation

Proper chromosome segregation is required to ensure genomic and chromosomal stability. The centromere is a unique chromatin domain present throughout the cell cycle on each chromosome defined by the CENP-A nucleosome. Centromeres (CEN) are responsible for recruiting the kinetochore (KT) during mitosis, ultimately regulating spindle attachment and mitotic checkpoint function. Upregulation of many genes that encode the CEN/KT proteins is commonly observed in cancer. Here, we show although that FOXM1 occupies the promoters of many CEN/KT genes with MYBL2, occupancy is insufficient alone to drive the FOXM1 correlated transcriptional program. We show that CENP-F, a component of the outer kinetochore, functions with FOXM1 to coregulate G2/M transcription and proper chromosome segregation. Loss of CENP-F results in alteration of chromatin accessibility at G2/M genes, including CENP-A, and leads to reduced FOXM1-MBB complex formation. The FOXM1-CENP-F transcriptional coordination is a cancer-specific function. We observed that a few CEN/KT genes escape FOXM1 regulation such as CENP-C which when upregulated with CENP-A, leads to increased chromosome misegregation and cell death. Together, we show that the FOXM1 and CENP-F coordinately regulate G2/M gene expression, and this coordination is specific to a subset of genes to allow for proliferation and maintenance of chromosome stability for cancer cell survival.

Master Transcription Factor Reprogramming Unleashes Selective Translation Promoting Castration Resistance and Immune Evasion in Lethal Prostate Cancer

Signaling rewiring allows tumors to survive therapy. Here we show that the decrease of the master regulator microphthalmia transcription factor (MITF) in lethal prostate cancer unleashes eukaryotic initiation factor 3B (eIF3B)-dependent translation reprogramming of key mRNAs conferring resistance to androgen deprivation therapy (ADT) and promoting immune evasion. Mechanistically, MITF represses through direct promoter binding eIF3B, which in turn regulates the translation of specific mRNAs. Genome-wide eIF3B enhanced cross-linking immunoprecipitation sequencing (eCLIP-seq) showed specialized binding to a UC-rich motif present in subsets of 5' untranslated regions. Indeed, translation of the androgen receptor and major histocompatibility complex I (MHC-I) through this motif is sensitive to eIF3B amount. Notably, pharmacologic targeting of eIF3B-dependent translation in preclinical models sensitizes prostate cancer to ADT and anti-PD-1 therapy. These findings uncover a hidden connection between transcriptional and translational rewiring promoting therapy-refractory lethal prostate cancer and provide a druggable mechanism that may transcend into effective combined therapeutic strategies.

SIGNIFICANCE

Our study shows that specialized eIF3B-dependent translation of specific mRNAs released upon downregulation of the master transcription factor MITF confers castration resistance and immune evasion in lethal prostate cancer. Pharmacologic targeting of this mechanism delays castration resistance and increases immune-checkpoint efficacy. This article is featured in Selected Articles from This Issue, p. 2489.

FOXM1 and CENPF are associated with a poor prognosis through promoting proliferation and migration in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a clinically challenging disease due to its poor prognosis and limited therapeutic methods. The aim of the present study was to identify prognosis-related genes and therapeutic targets for LUAD. Raw data from the GSE32863, GSE41271 and GSE42127 datasets were downloaded from the Gene Expression Omnibus database. Following normalization, the data were merged into a matrix, which was first used to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and survival analysis were performed to screen potential prognosis-related genes. Gene overlaps among DEGs, survival-related genes and WGCNA genes were finally constructed to obtain candidate genes. An analysis with the STRING database was performed to construct a protein-protein interaction network and hub genes were selected using Cytoscape. The candidate genes were finally identified by univariate and multivariate Cox regression analysis. Furthermore, in vivo and in vitro experiments, including immunohistochemistry, immunofluorescence, Cell Counting Kit-8, colony-formation and migration assays, were performed to validate the potential mechanism of these genes in LUAD. Two genes, namely forkhead box M1 (FOXM1) and centromere protein F (CENPF), were identified as unfavorable indicators of prognosis in patients with LUAD. High expression of FOXM1 and CENPF were associated with poor survival. Furthermore, LUAD cells with FOXM1 and CENPF knockdown showed a significant reduction in proliferation and migration (P<0.05). FOXM1 and CENPF may have an essential role in the prognosis of patients with LUAD by influencing cell proliferation and migration, and they provide potential molecular targets for LUAD therapy.

Tissue-specific biological aging predicts progression in prostate cancer and acute myeloid leukemia

Introduction

Chronological aging is a well-recognized diagnostic and prognostic factor in multiple cancer types, yet the role of biological aging in manifesting cancer progression has not been fully explored yet.

Methods

Given the central role of chronological aging in prostate cancer and AML incidence, here we investigate a tissue-specific role of biological aging in prostate cancer and AML progression. We have employed Cox proportional hazards modeling to associate biological aging genes with cancer progression for patients from specific chronological aging groups and for patients with differences in initial cancer aggressiveness.

Results

Our prostate cancer-specific investigations nominated four biological aging genes (CD44, GADD45B, STAT3, GFAP) significantly associated with time to disease progression in prostate cancer in Taylor et al. patient cohort. Stratified survival analysis on Taylor dataset and validation on an independent TCGA and DKFZ PRAD patient cohorts demonstrated ability of these genes to predict prostate cancer progression, especially for patients with higher Gleason score and for patients younger than 60 years of age. We have further tested the generalizability of our approach and applied it to acute myeloid leukemia (AML). Our analysis nominated three AML-specific biological aging genes (CDC42EP2, CDC42, ALOX15B) significantly associated with time to AML overall survival, especially for patients with favorable cytogenetic risk score and for patients older than 56 years of age.

Discussion

Comparison of the identified PC and AML markers to genes selected at random and to known markers of progression demonstrated robustness of our results and nominated the identified biological aging genes as valuable markers of prostate cancer and AML progression, opening new avenues for personalized therapeutic management and potential novel treatment investigations.

Pan-glioma analyses reveal species- and tumor-specific regulation of neuron-glioma synapse genes by lncRNAs

Gliomas are highly heterogeneous and aggressive. Malignant cells in gliomas can contact normal neurons through a synapse-like structure (called neuron-to-glioma synapse, NGS) to promote their proliferation, but it is unclear whether NGS gene expression and regulation show species- and tumor-specificity. This question is important in that many anti-cancer drugs are developed upon mouse models. To address this question, we conducted a pan-glioma analysis using nine scRNA-seq datasets from humans and mice. We also experimentally validated the key element of our methods and verified a key result using TCGA datasets of the same glioma types. Our analyses revealed that NGS gene expression and regulation by lncRNAs are highly species- and tumor-specific. Importantly, simian-specific lncRNAs are more involved in NGS gene regulation than lncRNAs conserved in mammals, and transgenic mouse gliomas have little in common with PDX mouse models and human gliomas in terms of NGS gene regulation. The analyses suggest that simian-specific lncRNAs are a new and rich class of potential targets for tumor-specific glioma treatment, and provide pertinent data for further experimentally and clinically exmining the targets.

Immune mechanisms shape the clonal landscape during early progression of prostate cancer

Understanding the role of the immune microenvironment in modulating intratumor heterogeneity is essential for effective cancer therapies. Using multicolor lineage tracing in genetically engineered mouse models and single-cell transcriptomics, we show that slowly progressing tumors contain a multiclonal landscape of relatively homogeneous subpopulations within a well-organized tumor microenvironment. In more advanced and aggressive tumors, however, the multiclonal landscape develops into competing dominant and minor clones accompanied by a disordered microenvironment. We demonstrate that this dominant/minor landscape is associated with differential immunoediting, in which minor clones are marked by an increased expression of IFNγ-response genes and the T cell-activating chemokines Cxcl9 and Cxcl11. Furthermore, immunomodulation of the IFNγ pathway can rescue minor clones from elimination. Notably, the immune-specific gene signature of minor clones exhibits a prognostic value for biochemical recurrence-free survival in human prostate cancer. These findings suggest new immunotherapy approaches for modulating clonal fitness and tumor progression in prostate cancer.

A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies

Predicting in vivo response to antineoplastics remains an elusive challenge. We performed a first-of-kind evaluation of two transcriptome-based precision cancer medicine methodologies to predict tumor sensitivity to a comprehensive repertoire of clinically relevant oncology drugs, whose mechanism of action we experimentally assessed in cognate cell lines. We enrolled patients with histologically distinct, poor-prognosis malignancies who had progressed on multiple therapies, and developed low-passage, patient-derived xenograft models that were used to validate 35 patient-specific drug predictions. Both OncoTarget, which identifies high-affinity inhibitors of individual master regulator (MR) proteins, and OncoTreat, which identifies drugs that invert the transcriptional activity of hyperconnected MR modules, produced highly significant 30-day disease control rates (68% and 91%, respectively). Moreover, of 18 OncoTreat-predicted drugs, 15 induced the predicted MR-module activity inversion in vivo. Predicted drugs significantly outperformed antineoplastic drugs selected as unpredicted controls, suggesting these methods may substantively complement existing precision cancer medicine approaches, as also illustrated by a case study.

SIGNIFICANCE

Complementary precision cancer medicine paradigms are needed to broaden the clinical benefit realized through genetic profiling and immunotherapy. In this first-in-class application, we introduce two transcriptome-based tumor-agnostic systems biology tools to predict drug response in vivo. OncoTarget and OncoTreat are scalable for the design of basket and umbrella clinical trials. This article is highlighted in the In This Issue feature, p. 1275.

N6-methyladenosine modification of CENPF mRNA facilitates gastric cancer metastasis via regulating FAK nuclear export

BACKGROUND

N6-methyladenosine (m⁶ A) modification is the most common modification that occurs in eukaryotes. Although substantial effort has been made in the prevention and treatment of gastric cancer (GC) in recent years, the prognosis of GC patients remains unsatisfactory. The regulatory mechanism between m⁶ A modification and GC development needs to be elucidated. In this study, we examined m⁶ A modification and the downstream mechanism in GC.

METHODS

Dot blotting assays, The Cancer Genome Atlas analysis, and quantitative real-time PCR (qRT-PCR) were used to measure the m⁶ A levels in GC tissues. Methylated RNA-immunoprecipitation sequencing and RNA sequencing were performed to identify the targets of m⁶ A modification. Western blotting, Transwell, wound healing, and angiogenesis assays were conducted to examine the role of centromere protein F (CENPF) in GC in vitro. Xenograft, immunohistochemistry, and in vivo metastasis experiments were conducted to examine the role of CENPF in GC in vivo. Methylated RNA-immunoprecipitation-qPCR, RNA immunoprecipitation-qPCR and RNA pulldown assays were used to verify the m⁶ A modification sites of CENPF. Gain/loss-of-function and rescue experiments were conducted to determine the relationship between CENPF and the mitogen-activated protein kinase (MAPK) signaling pathway in GC cells. Coimmunoprecipitation, mass spectrometry, qRT-PCR, and immunofluorescence assays were performed to explore the proteins that interact with CENPF and elucidate the regulatory mechanisms between them.

RESULTS

CENPF was upregulated in GC and facilitated the metastasis of GC both in vitro and in vivo. Mechanistically, increased m⁶ A modification of CENPF was mediated by methyltransferase 3, and this modified molecule could be recognized by heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1), thereby promoting its mRNA stability. In addition, the metastatic phenotype of CENPF was dependent on the MAPK signaling pathway. Furthermore, CENPF could bind to FAK and promote its localization in the cytoplasm. Moreover, we discovered that high expression of CENPF was related to lymphatic invasion and overall survival in GC patients.

CONCLUSIONS

Our findings revealed that increased m⁶ A modification of CENPF facilitates the metastasis and angiogenesis of GC through the CENPF/FAK/MAPK and epithelial-mesenchymal transition axis. CENPF expression was correlated with the clinical features of GC patients; therefore, CENPF may serve as a prognostic marker of GC.

Integrated pan-cancer analysis of centromere protein F and experimental verification of its role and clinical significance in cholangiocarcinoma

Centromere protein F (CENPF), a protein related to the cell cycle, is a key part of the kinetochore-centromere complex involved in cell division, differentiation, and proliferation. CENPF expression is upregulated in various types of cancer and plays a role in oncogenesis and tumor progression. However, the expression pattern, prognostic significance, and biological role of CENPF in these cancer types are poorly understood. Therefore, in this study, we conducted a pan-cancer analysis of the role of CENPF, which we considered a cut point, to investigate its utility as a prognostic and immunological indicator for malignancies, especially cholangiocarcinoma (CCA). Using systematic bioinformatics analysis, we investigated the expression patterns, prognostic relevance, molecular function, signaling pathways, and immune infiltration patterns of CENPF in the pan-cancer analysis. Western blot and immunohistochemistry staining assays were performed to evaluate the expression profiles of CENPF in CCA tissues and cell lines. Furthermore, Cell Counting Kit-8, colony formation, wound healing, and Transwell assays, as well as CCA xenograft mouse models, were employed to determine the role and function of CENPF in CCA. The results showed that CENPF expression was upregulated and strongly linked to a worse prognosis in most cancer types. CENPF expression was substantially associated with immune cell infiltration, tumor microenvironment, genes related to immune checkpoints, tumor mutational burden, microsatellite instability, and immunotherapy response in diverse malignancies. CENPF was considerably overexpressed in CCA tissues and cells. Functionally, inhibiting CENPF expression significantly reduced the proliferating, migrating, and invading abilities of CCA cells. CENPF expression also affects the prognosis of multiple malignancies, which is highly associated with immunotherapy response and tumor immune cell infiltration. In conclusion, CENPF may act as an oncogene and an immune infiltration-related biomarker and can accelerate tumor development in CCA.

Gene networks reveal stem-cell state convergence during preneoplasia and progression to malignancy in multistage skin carcinogenesis

Adult mammalian stem cells play critical roles in normal tissue homeostasis, as well as in tumor development, by contributing to cell heterogeneity, plasticity, and development of drug resistance. The relationship between different types of normal and cancer stem cells is highly controversial and poorly understood. Here, we carried out gene expression network analysis of normal and tumor samples from genetically heterogeneous mice to create network metagenes for visualization of stem-cell networks, rather than individual stem-cell markers, at the single-cell level during multistage carcinogenesis. We combined this approach with lineage tracing and single-cell RNASeq of stem cells and their progeny, identifying a previously unrecognized hierarchy in which Lgr6+ stem cells from tumors generate progeny that express a range of other stem-cell markers including Sox2, Pitx1, Foxa1, Klf5, and Cd44. Our data identify a convergence of multiple stem-cell and tumor-suppressor pathways in benign tumor cells expressing markers of lineage plasticity and oxidative stress. This same single-cell population expresses network metagenes corresponding to markers of cancer drug resistance in human tumors of the skin, lung and prostate. Treatment of mouse squamous carcinomas in vivo with the chemotherapeutic cis-platin resulted in elevated expression of the genes that mark this cell population. Our data have allowed us to create a simplified model of multistage carcinogenesis that identifies distinct stem-cell states at different stages of tumor progression, thereby identifying networks involved in lineage plasticity, drug resistance, and immune surveillance, providing a rich source of potential targets for cancer therapy.

Systematic elucidation and pharmacological targeting of tumor-infiltrating regulatory T cell master regulators

Due to their immunosuppressive role, tumor-infiltrating regulatory T cells (TI-Tregs) represent attractive immuno-oncology targets. Analysis of TI vs. peripheral Tregs (P-Tregs) from 36 patients, across four malignancies, identified 17 candidate master regulators (MRs) as mechanistic determinants of TI-Treg transcriptional state. Pooled CRISPR-Cas9 screening in vivo, using a chimeric hematopoietic stem cell transplant model, confirmed the essentiality of eight MRs in TI-Treg recruitment and/or retention without affecting other T cell subtypes, and targeting one of the most significant MRs (Trps1) by CRISPR KO significantly reduced ectopic tumor growth. Analysis of drugs capable of inverting TI-Treg MR activity identified low-dose gemcitabine as the top prediction. Indeed, gemcitabine treatment inhibited tumor growth in immunocompetent but not immunocompromised allografts, increased anti-PD-1 efficacy, and depleted MR-expressing TI-Tregs in vivo. This study provides key insight into Treg signaling, specifically in the context of cancer, and a generalizable strategy to systematically elucidate and target MR proteins in immunosuppressive subpopulations.

hSSB1 (NABP2/OBFC2B) modulates the DNA damage and androgen-induced transcriptional response in prostate cancer

BACKGROUND

Activation and regulation of androgen receptor (AR) signaling and the DNA damage response impact the prostate cancer (PCa) treatment modalities of androgen deprivation therapy (ADT) and radiotherapy. Here, we have evaluated a role for human single-strand binding protein 1 (hSSB1/NABP2) in modulation of the cellular response to androgens and ionizing radiation (IR). hSSB1 has defined roles in transcription and maintenance of genome stability, yet little is known about this protein in PCa.

METHODS

We correlated hSSB1 with measures of genomic instability across available PCa cases from The Cancer Genome Atlas (TCGA). Microarray and subsequent pathway and transcription factor enrichment analysis were performed on LNCaP and DU145 prostate cancer cells.

RESULTS

Our data demonstrate that hSSB1 expression in PCa correlates with measures of genomic instability including multigene signatures and genomic scars that are reflective of defects in the repair of DNA double-strand breaks via homologous recombination. In response to IR-induced DNA damage, we demonstrate that hSSB1 regulates cellular pathways that control cell cycle progression and the associated checkpoints. In keeping with a role for hSSB1 in transcription, our analysis revealed that hSSB1 negatively modulates p53 and RNA polymerase II transcription in PCa. Of relevance to PCa pathology, our findings highlight a transcriptional role for hSSB1 in regulating the androgen response. We identified that AR function is predicted to be impacted by hSSB1 depletion, whereby this protein is required to modulate AR gene activity in PCa.

CONCLUSIONS

Our findings point to a key role for hSSB1 in mediating the cellular response to androgen and DNA damage via modulation of transcription. Exploiting hSSB1 in PCa might yield benefits as a strategy to ensure a durable response to ADT and/or radiotherapy and improved patient outcomes.

Deciphering the Prognostic and Therapeutic Significance of Cell Cycle Regulator CENPF: A Potential Biomarker of Prognosis and Immune Microenvironment for Patients with Liposarcoma

Liposarcoma (LPS) is one of the most common subtypes of sarcoma with a high recurrence rate. CENPF is a regulator of cell cycle, differential expression of which has been shown to be related with various cancers. However, the prognostic value of CENPF in LPS has not been deciphered yet. Using data from TCGA and GEO datasets, the expression difference of CENPF and its effects on the prognosis or immune infiltration of LPS patients were analyzed. As results show, CENPF was significantly upregulated in LPS compared to normal tissues. Survival curves illustrated that high CENPF expression was significantly associated with adverse prognosis. Univariate and multivariate analysis suggested that CENPF expression could be an independent risk factor for LPS. CENPF was closely related to chromosome segregation, microtubule binding and cell cycle. Immune infiltration analysis elucidated a negative correlation between CENPF expression and immune score. In conclusion, CENPF not only could be considered as a potential prognostic biomarker but also a potential malignant indicator of immune infiltration-related survival for LPS. The elevated expression of CENPF reveals an unfavorable prognostic outcome and worse immune score. Thus, therapeutically targeting CENPF combined with immunotherapy might be an attractive strategy for the treatment of LPS.

A hotspot for posttranslational modifications on the androgen receptor dimer interface drives pathology and anti-androgen resistance

Mutations of the androgen receptor (AR) associated with prostate cancer and androgen insensitivity syndrome may profoundly influence its structure, protein interaction network, and binding to chromatin, resulting in altered transcription signatures and drug responses. Current structural information fails to explain the effect of pathological mutations on AR structure-function relationship. Here, we have thoroughly studied the effects of selected mutations that span the complete dimer interface of AR ligand-binding domain (AR-LBD) using x-ray crystallography in combination with in vitro, in silico, and cell-based assays. We show that these variants alter AR-dependent transcription and responses to anti-androgens by inducing a previously undescribed allosteric switch in the AR-LBD that increases exposure of a major methylation target, Arg⁷⁶¹. We also corroborate the relevance of residues Arg⁷⁶¹ and Tyr⁷⁶⁴ for AR dimerization and function. Together, our results reveal allosteric coupling of AR dimerization and posttranslational modifications as a disease mechanism with implications for precision medicine.

High intratumoral plasma cells content in primary prostate cancer defines a subset of tumors with potential susceptibility to immune-based treatments

BACKGROUND

Data on advanced prostate cancer (PCa) suggest more prior systemic therapies might reduce tumor immune responsiveness. In treatment-naïve primary PCa, recent work correlated intratumoral plasma cell content with enhanced tumor immune-responsiveness. We sought to identify features of localized PCa at a high risk of recurrence following local treatment with high plasma cell content to help focus future immune-based neoadjuvant trials.

METHODS

We performed retrospective analyses of molecular profiles from three independent cohorts of over 1300 prostate tumors. We used Wilcoxon Rank Sum to compare molecular pathways between tumors with high and low intratumoral plasma cell content and multivariable Cox proportional hazards regression analyses to assess metastasis-free survival.

RESULTS

We validated an expression-based signature for intratumoral plasma cell content in 113 primary prostate tumors with both RNA-expression data and digital image quantification of CD138+ cells (plasma cell marker) based on immunohistochemisty. The signature showed castration-resistant tumors (n = 101) with more prior systemic therapies contained lower plasma cell content. In high-grade primary PCa, tumors with high plasma cell content were associated with increased predicted response to immunotherapy and decreased response to androgen-deprivation therapy. Master regulator analyses identified upregulated transcription factors implicated in immune (e.g. SKAP1, IL-16, and HCLS1), and B-cell activity (e.g. VAV1, SP140, and FLI-1) in plasma cell-high tumors. Master regulators overactivated in tumors with low plasma cell content were associated with shorter metastasis-free survival following radical prostatectomy.

CONCLUSIONS

Markers of plasma cell activity might be leveraged to augment clinical trial targeting and selection and better understand the potential for immune-based treatments in patients with PCa at a high risk of recurrence following local treatment.

CENPF promotes the proliferation of renal cell carcinoma in vitro

Background

Metastasis and drug resistance are the main causes of renal cell carcinoma (RCC) mortality. Currently, there are still a limited number of targeted therapies against advanced RCC. It is critical to develop new effective clinical biomarkers and drug targets in RCC. Several studies have shown that centromere protein F (CENPF), a microtubule binding protein, promotes cancer progression in various types of cancer. The purpose of this study was to explore the role of CENPF in RCC.

Methods

Peripheral blood and corresponding tissue samples of 23 RCC patients and 23 normal physical examination patients who were treated in our hospital from 2018 to 2020 were collected, and CENPF expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR), western blot, and immunohistochemical (IHC) methods. The expression of CENPF was downregulated by small interfering RNA (siRNA) transfection, and the proliferation of the corresponding RCC cells and the corresponding cell cycle were detected.

Results

According to The Cancer Genome Atlas (TCGA) data analysis, CENPF is highly expressed in RCC, and its expression level is significantly related to the overall survival (OS) and recurrence-free survival (RFS) of RCC. In addition, high expression of CENPF was found in the tissues of RCC patients in our hospital. Knockdown of CENPF significantly reduced the proliferation of RCC cells in vitro, and knockdown of CENPF regulated the cell cycle by inhibiting the expression of cyclins such as CDK4, CDK6, and CyclinD1.

Conclusions

CENPF can be used as an independent prognostic factor of RCC and regulate the proliferation ability and cell cycle of RCC cells. CENPF is a potential oncogene and prognostic marker in RCC.

A luminal intermediate cell state maintains long-term prostate homeostasis and contributes to tumorigenesis

Cellular heterogeneity poses tremendous challenges for developing cell-targeted therapies and biomarkers of clinically significant prostate cancer. The origins of this heterogeneity within normal adult and aging tissue remain unknown, leaving cellular states and transcriptional programs that allow expansions of malignant clones unidentified. To define cell states that contribute to early cancer development, we performed clonal analyses and single cell transcriptomics of normal prostate from genetically-engineered mouse models. We uncovered a luminal transcriptional state with a unique "basal-like" Wnt/p63 signaling ( luminal intermediate , LumI) which contributes to the maintenance of long-term prostate homeostasis. Moreover, LumI cells greatly expand during early stages of tumorigenesis in several mouse models of prostate cancer. Genetic ablation of p63 in vivo in luminal cells reduced the formation of aggressive clones in mouse prostate tumor models. Finally, the LumI cells and Wnt signaling appear to significantly increase in human aging prostate and prostate cancer samples, highlighting the importance of this hybrid cell state for human pathologies with potential translational impact.

OncoLoop: A Network-Based Precision Cancer Medicine Framework

Prioritizing treatments for individual patients with cancer remains challenging, and performing coclinical studies using patient-derived models in real time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework that predicts drug sensitivity in human tumors and their preexisting high-fidelity (cognate) model(s) by leveraging drug perturbation profiles. As a proof of concept, we applied OncoLoop to prostate cancer using genetically engineered mouse models (GEMM) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of human prostate cancer cohorts by Master Regulator (MR) conservation analysis revealed that most patients with advanced prostate cancer were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated in allograft, syngeneic, and patient-derived xenograft (PDX) models of tumors and metastasis. Furthermore, OncoLoop-predicted drugs enhanced the efficacy of clinically relevant drugs, namely, the PD-1 inhibitor nivolumab and the AR inhibitor enzalutamide.

SIGNIFICANCE

OncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround coclinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. This article is highlighted in the In This Issue feature, p. 247.

SR9009 inhibits lethal prostate cancer subtype 1 by regulating the LXRα/FOXM1 pathway independently of REV-ERBs

Perturbations of the circadian clock are linked to multiple diseases, including cancers. Pharmacological activation of REV-ERB nuclear receptors, the core components of the circadian clock, has antitumor effects on various malignancies, while the impact of SR9009 on prostate cancer (PCa) remains unknown. Here, we found that SR9009 was specifically lethal to PCa cell lines but had no cytotoxic effect on prostate cells. SR9009 significantly inhibited colony formation, the cell cycle, and cell migration and promoted apoptosis in PCa cells. SR9009 treatment markedly inhibited prostate cancer subtype 1 (PCS1), the most lethal and aggressive PCa subtype, through FOXM1 pathway blockade, while it had no impacts on PCS2 and PCS3. Seven representative genes, including FOXM1, CENPA, CENPF, CDK1, CCNB1, CCNB2, and BIRC5, were identified as the shared genes involved in the FOXM1 pathway and PCS1. All of these genes were upregulated in PCa tissues, associated with worse clinicopathological outcomes and downregulated after SR9009 treatment. Nevertheless, knockdown or knockout of REV-ERB could not rescue the anticancer effect of SR9009 in PCa. Further analysis confirmed that it was LXRα rather than REV-ERBs which has been activated by SR9009. The expression levels of these seven genes were changed correspondingly after LXRα knockdown and SR9009 treatment. An in vivo study validated that SR9009 restrained tumor growth in 22RV1 xenograft models and inhibited FOXM1 and its targeted gene expression. In summary, SR9009 can serve as an effective treatment option for highly aggressive and lethal PCS1 tumors through mediating the LXRα/FOXM1 pathway independently of REV-ERBs.

An Integrative Multi-Omics Analysis Based on Nomogram for Predicting Prostate Cancer Bone Metastasis Incidence

Background

The most common site of prostate cancer metastasis is bone tissue with many recent studies having conducted genomic and clinical research regarding bone metastatic prostate cancer. However, further work is needed to better define those patients that are at an elevated risk of such metastasis.

Methods

SEER and TCGA databases were searched to develop a nomogram for predicting prostate cancer bone metastasis.

Results

Herein, we leveraged the Surveillance, Epidemiology, and End Results (SEER) database to construct a predictive nomogram capable of readily and accurately predicted the odds of bone metastasis in prostate cancer patients. This nomogram was utilized to assign patients with prostate cancer included in The Cancer Genome Atlas (TCGA) to cohorts at a high or low risk of bone metastasis (HRBM and LRBM, respectively). Comparisons of these LRBM and HRBM cohorts revealed marked differences in mutational landscapes between these patient cohorts, with increased frequencies of gene fusions, somatic copy number variations (CNVs), and single nucleotide variations (SNVs), particularly in the P53 gene, being evident in the HRBM cohort. We additionally identified lncRNAs, miRNAs, and mRNAs that were differentially expressed between these two patient cohorts and used them to construct a competing endogenous RNA (ceRNA) network. Moreover, three weighted gene co-expression network analysis (WGCNA) modules were constructed from the results of these analyses, with KIF14, MYH7, and COL10A1 being identified as hub genes within these modules. We further found immune response activity levels in the HRBM cohort to be elevated relative to that in the LRBM cohort, with single sample gene enrichment analysis (ssGSEA) scores for the immune checkpoint signature being increased in HRBM patient samples relative to those from LRBM patients.

Conclusion

We successfully developed a nomogram capable of readily detecting patients with prostate cancer at an elevated risk of bone metastasis.

Deciphering the dynamic niches and regeneration-associated transcriptional program of motoneurons following peripheral nerve injury

Robust axon regeneration of motoneurons (MNs) occurs in rodent models upon peripheral nerve injury (PNI). However, genome-wide dynamic molecules and permissive microenvironment following insult in MNs remain largely unknown. Here, we firstly tackled by high-coverage and massive sequencing of laser-dissected individual ChAT⁺ cells to uncover molecules and pro-regenerative programs of MNs from injury to the regenerating phase after PNI. "Injured" populations at 1d∼7d were well distinguished and three response phases were well defined by elucidating with several clues (Gap43, etc). We found remarkable changes of genes expressed by injured motoneurons to activate and enhance intrinsic axon regrowth or crosstalk with other cellular or non-cellular counterpart in the activated regenerative microenvironment, specifically microglia/macrophage. We also identified an injury and regeneration-associated module and critical regulators including core transcription factors (Atf3, Arid5a, Klf6, Klf7, Jun, Stat3, and Myc). This study provides a vital resource and critical molecules for studying neural repair of axotomized motoneurons.

A Patient-to-Model-to-Patient (PMP) Cancer Drug Discovery Protocol for Identifying and Validating Therapeutic Agents Targeting Tumor Regulatory Architecture

The current Achilles heel of cancer drug discovery is the inability to forge precise and predictive connections among mechanistic drivers of the cancer cell state, therapeutically significant molecular targets, effective drugs, and responsive patient subgroups. Although advances in molecular biology have helped identify molecular markers and stratify patients into molecular subtypes, these associational strategies typically fail to provide a mechanistic rationale to identify cancer vulnerabilities. Recently, integrative systems biology methodologies have been used to reverse engineer cellular networks and identify master regulators (MRs), proteins whose activity is both necessary and sufficient to implement phenotypic states under physiological and pathological conditions, which are organized into highly interconnected regulatory modules called tumor checkpoints. Because of their functional relevance, MRs represent ideal pharmacological targets and biomarkers. Here, we present a six-step patient-to-model-to-patient protocol that employs computational and experimental methodologies to reconstruct and interrogate the regulatory logic of human cancer cells for identifying and therapeutically targeting the tumor checkpoint with novel as well as existing pharmacological agents. This protocol systematically identifies, from specific patient tumor samples, the MRs that comprise the tumor checkpoint. Then, it identifies in vitro and in vivo models that, by recapitulating the patient's tumor checkpoint, constitute the appropriate cell lines and xenografts to further elucidate the tissue context-specific drug mechanism of action (MOA) and permit precise, biomarker-based preclinical validations of drug efficacy. The combination of determination of a drug's context-specific MOA and precise identification of patients' tumor checkpoints provides a personalized, mechanism-based biomarker to enrich prospective clinical trials with patients likely to respond. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

A model for network-based identification and pharmacological targeting of aberrant, replication-permissive transcriptional programs induced by viral infection

SARS-CoV-2 hijacks the host cell transcriptional machinery to induce a phenotypic state amenable to its replication. Here we show that analysis of Master Regulator proteins representing mechanistic determinants of the gene expression signature induced by SARS-CoV-2 in infected cells revealed coordinated inactivation of Master Regulators enriched in physical interactions with SARS-CoV-2 proteins, suggesting their mechanistic role in maintaining a host cell state refractory to virus replication. To test their functional relevance, we measured SARS-CoV-2 replication in epithelial cells treated with drugs predicted to activate the entire repertoire of repressed Master Regulators, based on their experimentally elucidated, context-specific mechanism of action. Overall, 15 of the 18 drugs predicted to be effective by this methodology induced significant reduction of SARS-CoV-2 replication, without affecting cell viability. This model for host-directed pharmacological therapy is fully generalizable and can be deployed to identify drugs targeting host cell-based Master Regulator signatures induced by virtually any pathogen.

Investigation of Functional Synergism of CENPF and FOXM1 Identifies POLD1 as Downstream Target in Hepatocellular Carcinoma

Background

Lines of evidence implicate CENPF and FOXM1 may have novel co-operative roles in driving hepatocellular carcinoma (HCC).

Objective

We investigated the clinicopathological correlation, functional characterization, molecular mechanism and translational significance of CENPF and FOXM1.

Methods

We carried out integrative studies investigating functional synergism of CENPF and FOXM1 in HCC and its metastasis. Human HCC samples, HCC cell lines and mouse model were used in the studies. Stable knockdown, q-PCR, Western blotting, whole-transcriptomic sequencing (RNA-seq), as well as cell and mouse assays were performed.

Results

Upon clinicopathological correlation, we found that co-overexpression of CENPF and FOXM1 in human HCCs was associated with more aggressive tumor behavior including presence of venous invasion, tumor microsatellite formation, and absence of tumor encapsulation. Moreover, co-silencing FOXM1 and CENPF using shRNA approach in HCC cell lines resulted in significantly reduced cell proliferation. Furthermore, our RNA-seq and differential gene expression analysis delineated that CENPF and FOXM1 co-regulated a specific set of target genes in various metabolic processes and oncogenic signaling pathways. Among them, POLD1, which encodes the catalytic subunit of DNA polymerase δ, was ranked as the top downstream target co-regulated by CENPF and FOXM1. POLD1 expression was positively correlated with that of FOXM1 and CENPF in HCCs. In addition, POLD1 expression was significantly upregulated in HCC tumors. Functionally, in vivo orthotopic injection model showed that stable knockdown of POLD1 in HCC cells suppressed tumor incidence and tumorigenicity and had a trend of diminished lung metastasis.

Conclusion

Taken together, our data suggest that CENPF and FOXM1 could synergistically support hepatocarcinogenesis via the regulation of POLD1. CENPF and FOXM1 may represent new vulnerabilities to novel drug-based therapy in HCC.

The genes controlling normal function of citrate and spermine secretion are lost in aggressive prostate cancer and prostate model systems

High secretion of the metabolites citrate and spermine is a unique hallmark for normal prostate epithelial cells, and is reduced in aggressive prostate cancer. However, the identity of the genes controlling this biological process is mostly unknown. In this study, we have created a gene signature of 150 genes connected to citrate and spermine secretion in the prostate. We have computationally integrated metabolic measurements with multiple transcriptomics datasets from the public domain, including 3826 tissue samples from prostate and prostate cancer. The accuracy of the signature is validated by its unique enrichment in prostate samples and prostate epithelial tissue compartments. The signature highlights genes AZGP1, ANPEP and metallothioneins with zinc-binding properties not previously studied in the prostate, and the expression of these genes are reduced in more aggressive cancer lesions. However, the absence of signature enrichment in common prostate model systems can make it challenging to study these genes mechanistically.

•

Novel 150 gene signature reflecting prostatic citrate and spermine secretion

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Identified several zinc-binding proteins not previously investigated in the prostate

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The signature is absent in prostate model systems

Single-cell analysis reveals Comma-1D as a unique cell model for mammary gland development and breast cancer

The mammary epithelial tree contains two distinct populations, luminal and basal. The investigation of how this heterogeneity is developed and how it influences tumorigenesis has been hampered by the need to perform these studies using animal models. Comma-1D is an immortalized mouse mammary epithelial cell line that has unique morphogenetic properties. By performing single-cell RNA-seq studies we found that Comma-1D cultures consist of two main populations with luminal and basal features and a smaller population with mixed lineage and bipotent characteristics. We demonstrated that multiple transcription factors associated with the differentiation of the mammary epithelium in vivo also modulate this process in Comma-1D cultures. Additionally, we found that only cells with luminal features were able to acquire transformed characteristics after an oncogenic HER2 mutant was introduced in their genomes. Overall, our studies characterize at a single-cell level the heterogeneity of the Comma-1D cell line and illustrate how Comma-1D cells can be used as an experimental model to study both the differentiation and the transformation processes in vitro.

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.

Long noncoding RNA SH3PXD2A-AS1 promotes NSCLC proliferation and accelerates cell cycle progression by interacting with DHX9

As the most commonly diagnosed lung cancer, non-small cell lung carcinoma (NSCLC) is regulated by many long noncoding RNAs (lncRNAs). In the present study, we found that SH3PXD2A-AS1 expression in NSCLC tissues was upregulated compared with that in normal lung tissues in The Cancer Genome Atlas (TCGA) database by using the GEPIA website. K-M analysis was performed to explore the effects of this molecule on the survival rate in NSCLC. The results demonstrated that SH3PXD2A-AS1 expression was increased in human NSCLC, and high SH3PXD2A-AS1 expression was correlated with poor overall survival. SH3PXD2A-AS1 promotes lung cancer cell proliferation and accelerates cell cycle progression in vitro. Animal studies validated that knockdown of SH3PXD2A-AS1 inhibits NSCLC cell proliferation in vivo. Mechanically, SH3PXD2A-AS1 interacted with DHX9 to enhance FOXM1 expression, promote tumour cell proliferation and accelerate cell cycle progression. Altogether, SH3PXD2A-AS1 promoted NSCLC growth by interacting with DHX9 to enhance FOXM1 expression. SH3PXD2A-AS1 may serve as a promising predictive biomarker for the diagnosis and prognosis of patients with NSCLC.

Topological ranks reveal functional knowledge encoded in biological networks: a comparative analysis

MOTIVATION

Biological networks topology yields important insights into biological function, occurrence of diseases and drug design. In the last few years, different types of topological measures have been introduced and applied to infer the biological relevance of network components/interactions, according to their position within the network structure. Although comparisons of such measures have been previously proposed, to what extent the topology per se may lead to the extraction of novel biological knowledge has never been critically examined nor formalized in the literature.

RESULTS

We present a comparative analysis of nine outstanding topological measures, based on compact views obtained from the rank they induce on a given input biological network. The goal is to understand their ability in correctly positioning nodes/edges in the rank, according to the functional knowledge implicitly encoded in biological networks. To this aim, both internal and external (gold standard) validation criteria are taken into account, and six networks involving three different organisms (yeast, worm and human) are included in the comparison. The results show that a distinct handful of best-performing measures can be identified for each of the considered organisms, independently from the reference gold standard.

AVAILABILITY

Input files and code for the computation of the considered topological measures and K-haus distance are available at https://gitlab.com/MaryBonomo/ranking.

CONTACT

simona.rombo@unipa.it.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Briefings in Bioinformatics online.

Construction of Bone Metastasis-Specific Regulation Network Based on Prognostic Stemness-Related Signatures in Prostate Cancer

Background

We planned to uncover the cancer stemness-related genes (SRGs) in prostate cancer (PCa) and its underlying mechanism in PCa metastasis.

Methods

We acquired the RNA-seq data of 406 patients with PCa from the TCGA database. Based on the mRNA stemness index (mRNAsi) calculated by one-class logistic regression (OCLR) algorithm, SRGs in PCa were extracted by WGCNA. Univariate and multivariate regression analyses were applied to uncover OS-associated SRGs. Gene Set Variation Analysis (GSVA), Gene Set Enrichment Analysis (GSEA), and Pearson's correlation analysis were performed to discover the possible mechanism of PCa metastasis. The significantly correlated transcription factors of OS-associated SRGs were also identified by Pearson's correlation analysis. ChIP-seq was applied to validate the binding relationship of TFs and OS-associated SRGs and spatial transcriptome and single-cell sequencing were performed to uncover the location of key biomarkers expression. Lastly, we explored the specific inhibitors for SRGs using CMap algorithm.

Results

We identified 538 differentially expressed genes (DEGs) between non-metastatic and metastatic PCa. Furthermore, OS-associated SRGs were identified. The Pearson correlation analysis revealed that FOXM1 was significantly correlated with NEIL3 (correlation efficient =0.89, p < 0.001) and identified hallmark_E2F_targets as the potential pathway mechanism of NEIL3 promoting PCa metastasis (correlation efficient =0.58, p < 0.001). Single-cell sequencing results indicated that FOXM1 regulating NEIL3 may get involved in the antiandrogen resistance of PCa. Rottlerin was discovered to be a potential target drug for PCa.

Conclusion

We constructed a regulatory network based on SRGs associated with PCa metastasis and explored possible mechanism.

Ageing induces tissue‐specific transcriptomic changes in Caenorhabditis elegans

Ageing is a complex process with common and distinct features across tissues. Unveiling the underlying processes driving ageing in individual tissues is indispensable to decipher the mechanisms of organismal longevity. Caenorhabditis elegans is a well‐established model organism that has spearheaded ageing research with the discovery of numerous genetic pathways controlling its lifespan. However, it remains challenging to dissect the ageing of worm tissues due to the limited description of tissue pathology and access to tissue‐specific molecular changes during ageing. In this study, we isolated cells from five major tissues in young and old worms and profiled the age‐induced transcriptomic changes within these tissues. We observed a striking diversity of ageing across tissues and identified different sets of longevity regulators therein. In addition, we found novel tissue‐specific factors, including irx‐1 and myrf‐2, which control the integrity of the intestinal barrier and sarcomere structure during ageing respectively. This study demonstrates the complexity of ageing across worm tissues and highlights the power of tissue‐specific transcriptomic profiling during ageing, which can serve as a resource to the field.

CENPF/CDK1 signaling pathway enhances the progression of adrenocortical carcinoma by regulating the G2/M-phase cell cycle

Background

Adrenocortical carcinoma (ACC) is an aggressive and rare malignant tumor and is prone to local invasion and metastasis. And, overexpressed Centromere Protein F (CENPF) is closely related to the oncogenesis of various neoplasms, including ACC. However, the prognosis and exact biological function of CENPF in ACC remains largely unclear.

Methods

In the present essay, the expression patterns and prognostic value of CENPF in ACC were investigated in clinical specimens and public cancer databases, including GEO and TCGA. The potential signaling mechanism of CENPF in ACC was studied based on gene-set enrichment analysis (GSEA). Furthermore, a small RNA interference experiment was conducted to probe the underlying biological function of CENPF in the human ACC cell line, SW13 cells. Lastly, two available therapeutic strategies, including immunotherapy and chemotherapy, have been further explored.

Results

The expression of CENPF in human ACC samples, GEO, and TCGA databases depicted that CENPF was overtly hyper-expressed in ACC patients and positively correlated with tumor stage. The aberrant expression of CENPF was significantly correlated with unfavorable overall survival (OS) in ACC patients. Then, the GSEA analysis declared that CENPF was mainly involved in the G2/M-phase mediated cell cycle and p53 signaling pathway. Further, the in vitro experiment demonstrated that the interaction between CENPF and CDK1 augmented the G2/M-phase transition of mitosis, cell proliferation and might induce p53 mediated anti-tumor effect in human ACC cell line, SW13 cells. Lastly, immune infiltration analysis highlighted that ACC patients with high CENPF expression harbored significantly different immune cell populations, and high TMB/MSI score. The gene-drug interaction network stated that CENPF inhibitors, such as Cisplatin, Sunitinib, and Etoposide, might serve as potential drugs for the therapy of ACC.

Conclusion

The result points out that CENPF is significantly overexpressed in ACC patients. The overexpressed CENPF predicts a poor prognosis of ACC and might augment the progress of ACC. Thus, CENPF and related genes might serve as a novel prognostic biomarker or latent therapeutic target for ACC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03277-y.

A Novel Prognostic Signature for Survival Prediction and Immune Implication Based on SARS-CoV-2–Related Genes in Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) is a common aggressive malignancy of the urinary system. COVID-19, a highly infectious and severe disease caused by SARS-CoV-2, has become a significant challenge for global public health. Cancer patients have been reported to be more vulnerable to SARS-CoV-2 infection and have a higher risk for serious complications than the general population. However, the correlation between KIRC and COVID-19 remains incompletely elucidated. In this study, we comprehensively investigated the expression and prognostic significance of 333 SARS-CoV-2 infection–related genes in KIRC using the TCGA dataset and identified 31 SARS-CoV-2–related differently expressed genes between KIRC and normal renal tissues. Based on these genes, we constructed and validated a 5-gene prognostic signature (including ACADM, CENPF, KDELC1, PLOD2, and TRMT1) to distinguish low- and high-risk KIRC patients of poor survival in TCGA and E-MTAB-1980 cohorts. Gene set enrichment analysis (GSEA) showed that some inflammatory/immune-related pathways were significantly enriched in the high-risk group. The ESTIMATE analysis indicated that patients in the high-risk group had higher stromal and immune cell scores, therefore lower tumor purity. Moreover, they presented higher proportions of macrophages M0, regulatory T cells (Tregs), and T follicular helper cells and higher expression of immune checkpoints CTLA-4, LAG-3, TIGIT, and PDCD1 than low-risk patients. Besides, we also developed a nomogram to expand clinical applicability, which exhibits excellent predictive accuracy for survival. In conclusion, we identified a novel prognostic signature and nomogram based on SARS-CoV-2–related genes as reliable prognostic predictors for KIRC patients and provided potential therapeutic targets for KIRC and COVID-19.

MicroRNA-383: A tumor suppressor miRNA in human cancer

Downregulated expression of anti-tumor miR-383 has been found in many kinds of cancer. MiR-383 family members can directly target the 3'-untranslated region (3'-UTR) of the mRNA of some pro-tumor genes to attenuate several cancer-related processes, including cell proliferation, invasion, migration, angiogenesis, immunosuppression, epithelial-mesenchymal transition, glycolysis, chemoresistance, and the development of cancer stem cells, whilst promoting apoptosis. Functionally, miR-383 operates as a tumor inhibitor miRNA in many types of cancer, including breast cancer, hepatocellular carcinoma, gastric cancer, pancreatic cancer, colorectal cancer, esophageal cancer, lung cancer, head and neck cancer, glioma, medulloblastoma, melanoma, prostate cancer, cervical cancer, oral squamous cell carcinoma, thyroid cancer, and B-cell lymphoma. Both pro-tumor and anti-tumor effects have been attributed to miR-383 in ovarian cancer. However, only the pro-tumor effects of miR-383 were reported in cholangiocarcinoma. The restoration of miR-383 expression could be considered a possible treatment for cancer. This review discusses the anti-tumor effects of miR-383 in human cancers, emphasizing their downstream target genes and potential treatment approaches.

Pre-existing Castration-resistant Prostate Cancer–like Cells in Primary Prostate Cancer Promote Resistance to Hormonal Therapy

BACKGROUND

Hormonal therapy targeting the androgen receptor inhibits prostate cancer (PCa), but the tumor eventually recurs as castration-resistant prostate cancer (CRPC).

OBJECTIVE

To understand the mechanisms by which subclones within early PCa develop into CRPC.

DESIGN, SETTING, AND PARTICIPANTS

We isolated epithelial cells from fresh human PCa cases, including primary adenocarcinoma, locally recurrent CRPC, and metastatic CRPC, and utilized single-cell RNA sequencing to identify subpopulations destined to become either CRPC-adeno or small cell neuroendocrine carcinoma (SCNC).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We revealed dynamic transcriptional reprogramming that promotes disease progression among 23226 epithelial cells using single-cell RNA sequencing, and validated subset-specific progression using immunohistochemistry and large cohorts of publically available genomic data.

RESULTS AND LIMITATIONS

We identified a small fraction of highly plastic CRPC-like cells in hormone-naïve early PCa and demonstrated its correlation with biochemical recurrence and distant metastasis, independent of clinical characteristics. We show that progression toward castration resistance was initiated from subtype-specific lineage plasticity and clonal expansion of pre-existing neuroendocrine and CRPC-like cells in early PCa.

CONCLUSIONS

CRPC-like cells are present early in the development of PCa and are not exclusively the result of acquired evolutionary selection during androgen deprivation therapy. The lethal CRPC and SCNC phenotypes should be targeted earlier in the disease course of patients with PCa.

PATIENT SUMMARY

Here, we report the presence of pre-existing castration-resistant prostate cancer (CRPC)-like cells in primary prostate cancer, which represents a novel castration-resistant mechanism different from the adaptation mechanism after androgen deprivation therapy (ADT). Patients whose tumors harbor increased pre-existing neuroendocrine and CRPC-like cells may become rapidly resistant to ADT and may require aggressive early intervention.