PCAF-Mediated Histone Acetylation Promotes Replication Fork Degradation by MRE11 and EXO1 in BRCA-Deficient Cells.

Stabilization of stalled replication forks is a prominent mechanism of PARP (Poly(ADP-ribose) Polymerase) inhibitor (PARPi) resistance in BRCA-deficient tumors. Epigenetic mechanisms of replication fork stability are emerging but remain poorly understood. Here, we report the histone acetyltransferase PCAF (p300/CBP-associated) as a fork-associated protein that promotes fork degradation in BRCA-deficient cells by acetylating H4K8 at stalled replication forks, which recruits MRE11 and EXO1. A H4K8ac binding domain within MRE11/EXO1 is required for their recruitment to stalled forks. Low PCAF levels, which we identify in a subset of BRCA2-deficient tumors, stabilize stalled forks, resulting in PARPi resistance in BRCA-deficient cells. Furthermore, PCAF activity is tightly regulated by ATR (ataxia telangiectasia and Rad3-related), which phosphorylates PCAF on serine 264 (S264) to limit its association and activity at stalled forks. Our results reveal PCAF and histone acetylation as critical regulators of fork stability and PARPi responses in BRCA-deficient cells, which provides key insights into targeting BRCA-deficient tumors and identifying epigenetic modulators of chemotherapeutic responses.

Integrative transcriptomic and genomic analyses unveil the IFI16 variants and expression as MASLD progression markers.

BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses a broad and continuous spectrum of liver diseases ranging from fatty liver to steatohepatitis. The intricate interactions of genetic, epigenetic, and environmental factors in the development and progression of MASLD remain elusive. Here, we aimed to achieve an integrative understanding of the genomic and transcriptomic alterations throughout the progression of MASLD. APPROACH AND RESULTS: RNA-Seq profiling (n = 146) and whole-exome sequencing (n = 132) of MASLD liver tissue samples identified 3 transcriptomic subtypes (G1-G3) of MASLD, which were characterized by stepwise pathological and molecular progression of the disease. Macrophage-driven inflammatory activities were identified as a key feature for differentiating these subtypes. This subtype-discriminating macrophage interplay was significantly associated with both the expression and genetic variation of the dsDNA sensor IFI16 (rs6940, A>T, T779S), establishing it as a fundamental molecular factor in MASLD progression. The in vitro dsDNA-IFI16 binding experiments and structural modeling revealed that the IFI16 variant exhibited increased stability and stronger dsDNA binding affinity compared to the wild-type. Further downstream investigation suggested that the IFI16 variant exacerbated DNA sensing-mediated inflammatory signals through mitochondrial dysfunction-related signaling of the IFI16-PYCARD-CASP1 pathway. CONCLUSIONS: This study unveils a comprehensive understanding of MASLD progression through transcriptomic classification, highlighting the crucial roles of IFI16 variants. Targeting the IFI16-PYCARD-CASP1 pathway may pave the way for the development of novel diagnostics and therapeutics for MASLD.

Integration of National Health Insurance claims data and animal models reveals fexofenadine as a promising repurposed drug for Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is a common and costly progressive neurodegenerative disease of unclear etiology. A disease-modifying approach that can directly stop or slow its progression remains a major unmet need in the treatment of PD. A clinical pharmacology-based drug repositioning strategy is a useful approach for identifying new drugs for PD. METHODS: We analyzed claims data obtained from the National Health Insurance Service (NHIS), which covers a significant portion of the South Korean population, to investigate the association between antihistamines, a class of drugs commonly used to treat allergic symptoms by blocking H1 receptor, and PD in a real-world setting. Additionally, we validated this model using various animal models of PD such as the 6-hydroxydopmaine (6-OHDA), α-synuclein preformed fibrils (PFF) injection, and Caenorhabditis elegans (C. elegans) models. Finally, whole transcriptome data and Ingenuity Pathway Analysis (IPA) were used to elucidate drug mechanism pathways. RESULTS: We identified fexofenadine as the most promising candidate using National Health Insurance claims data in the real world. In several animal models, including the 6-OHDA, PFF injection, and C. elegans models, fexofenadine ameliorated PD-related pathologies. RNA-seq analysis and the subsequent experiments suggested that fexofenadine is effective in PD via inhibition of peripheral immune cell infiltration into the brain. CONCLUSION: Fexofenadine shows promise for the treatment of PD, identified through clinical data and validated in diverse animal models. This combined clinical and preclinical approach offers valuable insights for developing novel PD therapeutics.

Molecular and radiopathologic spectrum between HCC and intrahepatic cholangiocarcinoma.

BACKGROUND AND AIMS: Primary liver cancers (LCs), including HCC and intrahepatic cholangiocarcinoma (iCCA), are derived from a common developmental lineage, conferring a molecular spectrum between them. To elucidate the molecular spectrum, we performed an integrative analysis of transcriptome profiles associated with patients' radiopathologic features. APPROACH AND RESULTS: We identified four LC subtypes (LC1-LC4) from RNA-sequencing profiles, revealing intermediate subtypes between HCC and iCCA. LC1 is a typical HCC characterized by active bile acid metabolism, telomerase reverse transcriptase promoter mutations, and high uptake of gadoxetic acid in MRI. LC2 is an iCCA-like HCC characterized by expression of the progenitor cell-like trait, tumor protein p53 mutations, and rim arterial-phase hyperenhancement in MRI. LC3 is an HCC-like iCCA, mainly small duct (SD) type, associated with HCC-related etiologic factors. LC4 is further subclassified into LC4-SD and LC4-large duct iCCAs according to the pathological features, which exhibited distinct genetic variations (e.g., KRAS , isocitrate dehydrogenase 1/2 mutation, and FGF receptor 2 fusion), stromal type, and prognostic outcomes. CONCLUSIONS: Our integrated view of the molecular spectrum of LCs can identify subtypes associated with transcriptomic, genomic, and radiopathologic features, providing mechanistic insights into heterogeneous LC progression.

Optimization of vision transformer-based detection of lung diseases from chest X-ray images.

BACKGROUND: Recent advances in Vision Transformer (ViT)-based deep learning have significantly improved the accuracy of lung disease prediction from chest X-ray images. However, limited research exists on comparing the effectiveness of different optimizers for lung disease prediction within ViT models. This study aims to systematically evaluate and compare the performance of various optimization methods for ViT-based models in predicting lung diseases from chest X-ray images. METHODS: This study utilized a chest X-ray image dataset comprising 19,003 images containing both normal cases and six lung diseases: COVID-19, Viral Pneumonia, Bacterial Pneumonia, Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), and Tuberculosis. Each ViT model (ViT, FastViT, and CrossViT) was individually trained with each optimization method (Adam, AdamW, NAdam, RAdam, SGDW, and Momentum) to assess their performance in lung disease prediction. RESULTS: When tested with ViT on the dataset with balanced-sample sized classes, RAdam demonstrated superior accuracy compared to other optimizers, achieving 95.87%. In the dataset with imbalanced sample size, FastViT with NAdam achieved the best performance with an accuracy of 97.63%. CONCLUSIONS: We provide comprehensive optimization strategies for developing ViT-based model architectures, which can enhance the performance of these models for lung disease prediction from chest X-ray images.

CGV: Cancer Genome Viewer, a web service for integrative cancer genome and pharmacogenomic data analysis.

MOTIVATION: Multi-omic profiling data, such as The Cancer Genome Atlas and pharmacogenomic data, facilitate research into cancer mechanisms and drug development. However, it is not easy for researchers to connect, integrate and analyze huge and heterogeneous data, which is a major obstacle to the utilization of cancer genomic data. RESULTS: We developed Cancer Genome Viewer (CGV), a user-friendly web service that provides functions to integrate and visualize cancer genome data and pharmacogenomic data. Users can easily select and customize the samples to be analyzed with the pre-defined selection options for patients' clinic-pathological features from multiple datasets. Using the customized dataset, users can perform subsequent data analyses comprehensively, including gene set analysis, clustering or survival analysis. CGV also provides pre-calculated drug response scores from pharmacogenomic data, which may facilitate the discovery of new cancer targets and therapeutics. AVAILABILITY AND IMPLEMENTATION: CGV web service is implemented with the R Shiny application at http://cgv.sysmed.kr and the source code is freely available at https://git.sysmed.kr/sysmed_public/cgv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Consensus subtypes of hepatocellular carcinoma associated with clinical outcomes and genomic phenotypes.

BACKGROUND AND AIMS: Although many studies revealed transcriptomic subtypes of HCC, concordance of the subtypes are not fully examined. We aim to examine a consensus of transcriptomic subtypes and correlate them with clinical outcomes. APPROACH AND RESULTS: By integrating 16 previously established genomic signatures for HCC subtypes, we identified five clinically and molecularly distinct consensus subtypes. STM (STeM) is characterized by high stem cell features, vascular invasion, and poor prognosis. CIN (Chromosomal INstability) has moderate stem cell features, but high genomic instability and low immune activity. IMH (IMmune High) is characterized by high immune activity. BCM (Beta-Catenin with high Male predominance) is characterized by prominent ß-catenin activation, low miRNA expression, hypomethylation, and high sensitivity to sorafenib. DLP (Differentiated and Low Proliferation) is differentiated with high hepatocyte nuclear factor 4A activity. We also developed and validated a robust predictor of consensus subtype with 100 genes and demonstrated that five subtypes were well conserved in patient-derived xenograft models and cell lines. By analyzing serum proteomic data from the same patients, we further identified potential serum biomarkers that can stratify patients into subtypes. CONCLUSIONS: Five HCC subtypes are correlated with genomic phenotypes and clinical outcomes and highly conserved in preclinical models, providing a framework for selecting the most appropriate models for preclinical studies.

The paradigm of immune escape by SARS-CoV-2 variants and strategies for repositioning subverted mAbs against escaped VOCs.

The perpetual emergence of SARS-CoV-2 variants is a serious issue that makes it difficult for the therapeutic antibodies and vaccines to end the COVID-19 pandemic. This article discusses the trend of increasing host fitness and immune escape by the virus and how to devise computational strategies for antibodies design and their affinity maturation against emerging SARS-CoV-2 variants.

Global spliceosome activity regulates entry into cellular senescence.

Cellular senescence is a state of permanent growth arrest that can ultimately contribute to aging. Senescence can be induced by various stressors and is associated with a myriad of cellular functions and phenotypic markers. Alternative splicing is emerging as a critical contributor to senescence and aging. However, it is unclear how the composition and function of the spliceosome are involved in senescence. Here, using replicative and oxidative stress-induced senescence models in primary human fibroblasts, we report a common shift in the expression of 58 spliceosomal genes at the pre-senescence stage, prior to the detection of senescence-associated ß-galactosidase (SA-ß-gal) activity. Spliceosomal perturbation, induced by pharmacologic and genetic inhibition of splicesomal genes, triggered cells to enter senescence, suggesting a key role as a gatekeeper. Association analysis of transcription factors based on the 58 splicesomal genes revealed Sp1 as a key regulator of senescence entry. Indeed, Sp1 depletion suppressed the expression of downstream spliceosomal genes (HNRNPA3, SRSF7, and SRSF4) and effectively induced senescence. These results indicate that spliceosomal gene sets, rather than a single spliceosomal gene, regulate the early transition into senescence prior to SA-ß-gal expression. Furthermore, our study provides a spliceosome signature that may be used as an early senescence marker.

Lung and lymph node metastases from hepatocellular carcinoma: Comparison of pathological aspects.

BACKGROUND & AIMS: Extrahepatic metastasis from hepatocellular carcinoma (HCC) is a catastrophic event, yet organ-specific pathological characteristics of metastatic HCC remain unclear. We aimed to characterize the pathological aspects of HCC metastases to various organs. METHODS: We collected intrahepatic HCC (cohort 1, n = 322) and extrahepatic metastatic HCC (cohort 2, n = 130) samples. Clinicopathological evaluation and immunostaining for K19, CD34, αSMA, fibroblast-associated protein (FAP), CAIX, VEGF, PD-L1, CD3, CD8, Foxp3, CD163 and epithelial-mesenchymal transition (EMT)-related markers were performed. RESULTS: Independent factors for extrahepatic metastasis included BCLC stage B-C, microvascular invasion (MVI), vessels encapsulating tumour clusters (VETC)-HCC, K19 and FAP expression, and CD163+ macrophage infiltration (cohort 1, P < .05 for all). Lung metastases (n = 63) had the highest proportion of VETC-HCC and macrotrabecular-massive (MTM)-HCC. Lymph node metastases (n = 19) showed significantly high rates of EMT-high features, K19 expression, fibrous tumour stroma with αSMA and FAP expression, high immune cell infiltration, PD-L1 expression (combined positive score), CD3+, CD8+, Foxp3+ T cell and CD163+ macrophage infiltration (adjusted P < .05 for all). In both cohorts, EMT-high HCCs showed higher rates of K19 expression, fibrous tumour stroma, high immune cell infiltration, PD-L1 expression and CD3+ T cell infiltration, whereas EMT-low HCCs were more frequent among VETC-HCCs (P < .05 for all). Overall phenotypic features were not significantly different between paired primary-metastatic HCCs (n = 32). CONCLUSIONS: Metastatic HCCs to various organs showed different pathological features. VETC and MTM subtypes were related to lung metastasis, whereas K19 expression, EMT-high features with fibrous tumour stroma and high immune cell infiltration were related to lymph node metastasis.

USO1 isoforms differentially promote liver cancer progression by dysregulating the ER-Golgi network.

Alternative splicing of RNA transcripts plays an important role in cancer development and progression. Recent advances in RNA-seq technology have made it possible to identify alternately spliced events in various types of cancer; however, research on hepatocellular carcinoma (HCC) is still limited. Here, by performing RNA-seq profiling of HCC transcripts at isoform level, we identified tumor-specific and molecular subtype-dependent expression of the USO1 isoforms, which we designated as a normal form USO1-N (XM_001290049) and a tumor form USO1-T (NM_003715). The expression of USO1-T, but not USO1-N, was associated with worse prognostic outcomes of HCC patients. We confirmed that the expression of USO1-T promoted an aggressive phenotype of HCC, both in vitro and in vivo. In addition, structural modeling analyses revealed that USO1-T lacks an ARM10 loop encoded by exon 15, which may weaken the dimerization of USO1 and its tethering to GM130. We demonstrated that USO1-T ensured unstacking of the Golgi and accelerated the vesicles trafficking from endoplasmic reticulum (ER) to Golgi and plasma membrane in multiple liver cancer cells. ERK and GRASP65 were found to be involved in the USO1-T-mediated Golgi dysfunction. Conclusively, we provide new mechanophysical insights into the USO1 isoforms that differentially regulate the ER-Golgi network, promoting the heterogeneous HCC progression.

scTyper: a comprehensive pipeline for the cell typing analysis of single-cell RNA-seq data.

BACKGROUND: Recent advances in single-cell RNA sequencing (scRNA-seq) technology have enabled the identification of individual cell types, such as epithelial cells, immune cells, and fibroblasts, in tissue samples containing complex cell populations. Cell typing is one of the key challenges in scRNA-seq data analysis that is usually achieved by estimating the expression of cell marker genes. However, there is no standard practice for cell typing, often resulting in variable and inaccurate outcomes. RESULTS: We have developed a comprehensive and user-friendly R-based scRNA-seq analysis and cell typing package, scTyper. scTyper also provides a database of cell type markers, scTyper.db, which contains 213 cell marker sets collected from literature. These marker sets include but are not limited to markers for malignant cells, cancer-associated fibroblasts, and tumor-infiltrating T cells. Additionally, scTyper provides three customized methods for estimating cell-type marker expression, including nearest template prediction (NTP), gene set enrichment analysis (GSEA), and average expression values. DNA copy number inference method (inferCNV) has been implemented with an improved modification that can be used for malignant cell typing. The package also supports the data preprocessing pipelines by Cell Ranger from 10X Genomics and the Seurat package. A summary reporting system is also implemented, which may facilitate users to perform reproducible analyses. CONCLUSIONS: scTyper provides a comprehensive and user-friendly analysis pipeline for cell typing of scRNA-seq data with a curated cell marker database, scTyper.db.

SEQprocess: a modularized and customizable pipeline framework for NGS processing in R package.

BACKGROUNDS: Next-Generation Sequencing (NGS) is now widely used in biomedical research for various applications. Processing of NGS data requires multiple programs and customization of the processing pipelines according to the data platforms. However, rapid progress of the NGS applications and processing methods urgently require prompt update of the pipelines. Recent clinical applications of NGS technology such as cell-free DNA, cancer panel, or exosomal RNA sequencing data also require appropriate customization of the processing pipelines. Here, we developed SEQprocess, a highly extendable framework that can provide standard as well as customized pipelines for NGS data processing. RESULTS: SEQprocess was implemented in an R package with fully modularized steps for data processing that can be easily customized. Currently, six pre-customized pipelines are provided that can be easily executed by non-experts such as biomedical scientists, including the National Cancer Institute's (NCI) Genomic Data Commons (GDC) pipelines as well as the popularly used pipelines for variant calling (e.g., GATK) and estimation of allele frequency, RNA abundance (e.g., TopHat2/Cufflink), or DNA copy numbers (e.g., Sequenza). In addition, optimized pipelines for the clinical sequencing from cell-free DNA or miR-Seq are also provided. The processed data were transformed into R package-compatible data type 'ExpressionSet' or 'SummarizedExperiment', which could facilitate subsequent data analysis within R environment. Finally, an automated report summarizing the processing steps are also provided to ensure reproducibility of the NGS data analysis. CONCLUSION: SEQprocess provides a highly extendable and R compatible framework that can manage customized and reproducible pipelines for handling multiple legacy NGS processing tools.

The Ubiquitin-like with PHD and Ring Finger Domains 1 (UHRF1)/DNA Methyltransferase 1 (DNMT1) Axis Is a Primary Regulator of Cell Senescence.

As senescence develops, cells sequentially acquire diverse senescent phenotypes along with simultaneous multistage gene reprogramming. It remains unclear what acts as the key regulator of the collective changes in gene expression at initiation of senescent reprogramming. Here we analyzed time series gene expression profiles obtained in two different senescence models in human diploid fibroblasts: replicative senescence and H2O2-induced senescence. Our results demonstrate that suppression of DNA methyltransferase 1 (DNMT1)-mediated DNA methylation activity was an initial event prior to the display of senescent phenotypes. We identified seven DNMT1-interacting proteins, ubiquitin-like with PHD and ring finger domains 1 (UHRF1), EZH2, CHEK1, SUV39H1, CBX5, PARP1, and HELLS (also known as LSH (lymphoid-specific helicase) 1), as being commonly down-regulated at the same time point as DNMT1 in both senescence models. Knockdown experiments revealed that, among the DNMT1-interacting proteins, only UHRF1 knockdown suppressed DNMT1 transcription. However, UHRF1 overexpression alone did not induce DNMT1 expression, indicating that UHRF1 was essential but not sufficient for DNMT1 transcription. Although UHRF1 knockdown effectively induced senescence, this was significantly attenuated by DNMT1 overexpression, clearly implicating the UHRF1/DNMT1 axis in senescence. Bioinformatics analysis further identified WNT5A as a downstream effector of UHRF1/DNMT1-mediated senescence. Senescence-associated hypomethylation was found at base pairs -1569 to -1363 from the transcription start site of the WNT5A gene in senescent human diploid fibroblasts. As expected, WNT5A overexpression induced senescent phenotypes. Overall, our results indicate that decreased UHRF1 expression is a key initial event in the suppression of DNMT1-mediated DNA methylation and in the consequent induction of senescence via increasing WNT5A expression.

Transcriptomic and histopathological analysis of cholangiolocellular differentiation trait in intrahepatic cholangiocarcinoma.

BACKGROUND & AIMS: Intrahepatic cholangiocarcinoma (iCCA) is a heterogeneous entity with diverse aetiologies, morphologies and clinical outcomes. Recently, histopathological distinction of cholangiolocellular differentiation (CD) of iCCA has been suggested. However, its genome-wide molecular features and clinical significance remain unclear. METHODS: Based on CD status, we stratified iCCAs into iCCA with CD (n=20) and iCCA without CD (n=102), and performed an integrative analysis using transcriptomic and clinicopathological profiles. RESULTS: iCCA with CD revealed less aggressive histopathological features compared to iCCA without CD, and iCCA with CD showed favourable clinical outcomes of overall survival and time to recurrence than iCCA without CD (P<.05 for all). Transcriptomic profiling revealed that iCCA with CD resembled an inflammation-related subtype, while iCCA without CD resembled a proliferation subtype. In addition, we identified a CD signature that can predict prognostic outcomes of iCCA (CD_UP, n=486 and CD_DOWN, n=308). iCCAs were subgrouped into G1 (positivity for CRP and CDH2, 7%), G3 (positivity for S100P and TFF1, 32%) and G2 (the others, 61%). Prognostic outcomes for overall survival (P=.001) and time to recurrence (P=.017) were the most favourable in G1-iCCAs, intermediate in G2-iCCAs and the worst in G3-iCCAs. Similar result was confirmed in the iCCA set from GSE26566 (n=68). CONCLUSIONS: CD signature was identified to predict the prognosis of iCCA. The combined evaluation of histology of CD and protein expression status of CRP, CDH2, TFF1 and S100P might help subtyping and predicting clinical outcomes of iCCA.

Pan-cancer analysis of systematic batch effects on somatic sequence variations.

BACKGROUND: The Cancer Genome Atlas (TCGA) is a comprehensive database that includes multi-layered cancer genome profiles. Large-scale collection of data inevitably generates batch effects introduced by differences in processing at various stages from sample collection to data generation. However, batch effects on the sequence variation and its characteristics have not been studied extensively. RESULTS: We systematically evaluated batch effects on somatic sequence variations in pan-cancer TCGA data, revealing 999 somatic variants that were batch-biased with statistical significance (P < 0.00001, Fisher's exact test, false discovery rate ≤ 0.0027). Most of the batch-biased variants were associated with specific sample plates. The batch-biased variants, which had a unique mutational spectrum with frequent indel-type mutations, preferentially occurred at sites prone to sequencing errors, e.g., in long homopolymer runs. Non-indel type batch-biased variants were frequent at splicing sites with the unique consensus motif sequence 'TTDTTTAGTT'. Furthermore, some batch-biased variants occur in known cancer genes, potentially causing misinterpretation of mutation profiles. CONCLUSIONS: Our strategy for identifying batch-biased variants and characterising sequence patterns might be useful in eliminating false variants and facilitating correct interpretation of sequence profiles.

Role of cysteinyl leukotriene signaling in a mouse model of noise-induced cochlear injury.

Noise-induced hearing loss is one of the most common types of sensorineural hearing loss. In this study, we examined the expression and localization of leukotriene receptors and their respective changes in the cochlea after hazardous noise exposure. We found that the expression of cysteinyl leukotriene type 1 receptor (CysLTR1) was increased until 3 d after noise exposure and enhanced CysLTR1 expression was mainly observed in the spiral ligament and the organ of Corti. Expression of 5-lipoxygenase was increased similar to that of CysLTR1, and there was an accompanying elevation of CysLT concentration. Posttreatment with leukotriene receptor antagonist (LTRA), montelukast, for 4 consecutive days after noise exposure significantly decreased the permanent threshold shift and also reduced the hair cell death in the cochlea. Using RNA-sequencing, we found that the expression of matrix metalloproteinase-3 (MMP-3) was up-regulated after noise exposure, and it was significantly inhibited by montelukast. Posttreatment with a MMP-3 inhibitor also protected the hair cells and reduced the permanent threshold shift. These findings suggest that acoustic injury up-regulated CysLT signaling in the cochlea and cochlear injury could be attenuated by LTRA through regulation of MMP-3 expression. This study provides mechanistic insights into the role of CysLTs signaling in noise-induced hearing loss and the therapeutic benefit of LTRA.

Identification of a mitochondrial defect gene signature reveals NUPR1 as a key regulator of liver cancer progression.

UNLABELLED: Many cancer cells require more glycolytic adenosine triphosphate production due to a mitochondrial respiratory defect. However, the roles of mitochondrial defects in cancer development and progression remain unclear. To address the role of transcriptomic regulation by mitochondrial defects in liver cancer cells, we performed gene expression profiling for three different cell models of mitochondrial defects: cells with chemical respiratory inhibition (rotenone, thenoyltrifluoroacetone, antimycin A, and oligomycin), cells with mitochondrial DNA depletion (Rho0), and liver cancer cells harboring mitochondrial defects (SNU354 and SNU423). By comparing gene expression in the three models, we identified 10 common mitochondrial defect-related genes that may be responsible for retrograde signaling from cancer cell mitochondria to the intracellular transcriptome. The concomitant expression of the 10 common mitochondrial defect genes is significantly associated with poor prognostic outcomes in liver cancers, suggesting their functional and clinical relevance. Among the common mitochondrial defect genes, we found that nuclear protein 1 (NUPR1) is one of the key transcription regulators. Knockdown of NUPR1 suppressed liver cancer cell invasion, which was mediated in a Ca(2+) signaling-dependent manner. In addition, by performing an NUPR1-centric network analysis and promoter binding assay, granulin was identified as a key downstream effector of NUPR1. We also report association of the NUPR1-granulin pathway with mitochondrial defect-derived glycolytic activation in human liver cancer. CONCLUSION: Mitochondrial respiratory defects and subsequent retrograde signaling, particularly the NUPR1-granulin pathway, play pivotal roles in liver cancer progression.

Molecular classification of basal cell carcinoma of skin by gene expression profiling.

Non-melanoma skin cancers (NMSC) including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are more common kinds of skin cancer. Although these tumors share common pathological and clinical features, their similarity and heterogeneity at molecular levels are not fully elaborated yet. Here, by performing comparative analysis of gene expression profiling of BCC, SCC, and normal skin tissues, we could classify the BCC into three subtypes of classical, SCC-like, and normal-like BCCs. Functional enrichment and pathway analyses revealed the molecular characteristics of each subtype. The classical BCC showed the enriched expression and transcription signature with the activation of Wnt and Hedgehog signaling pathways, which were well known key features of BCC. By contrast, the SCC-like BCC was enriched with immune-response genes and oxidative stress-related genes. Network analysis revealed the PLAU/PLAUR as a key regulator of SCC-like BCC. The normal-like BCC showed prominent activation of metabolic processes particularly the fatty acid metabolism. The existence of these molecular subtypes could be validated in an independent dataset, which demonstrated the three subgroups of BCC with distinct functional enrichment. In conclusion, we suggest a novel molecular classification of BCC providing insights on the heterogeneous progression of BCC.