Refining Classification of Cholangiocarcinoma Subtypes via Proteogenomic Integration Reveals New Therapeutic Prospects.

BACKGROUND & AIMS: Intrahepatic cholangiocarcinomas (iCCs) are characterized by their rarity, difficult diagnosis, and overall poor prognosis. The iCC molecular classification for developing precision medicine strategies was investigated. METHODS: Comprehensive genomic, transcriptomic, proteomic, and phosphoproteomic analyses were performed on treatment-naïve tumor samples from 102 patients with iCC who underwent surgical resection with curative intent. An organoid model was constructed for testing therapeutic potential. RESULTS: Three clinically supported subtypes (stem-like, poorly immunogenic, and metabolism) were identified. NCT-501 (aldehyde dehydrogenase 1 family member A1 [ALDH1A1] inhibitor) exhibited synergism with nanoparticle albumin-bound-paclitaxel in the organoid model for the stem-like subtype. The oncometabolite dysregulations were associated with different clinical outcomes in the stem-like and metabolism subtypes. The poorly immunogenic subtype harbors the non-T-cell tumor infiltration. Integrated multiomics analysis not only reproduced the 3 subtypes but also showed heterogeneity in iCC. CONCLUSIONS: This large-scale proteogenomic analysis provides information beyond that obtained with genomic analysis, allowing the functional impact of genomic alterations to be discerned. These findings may assist in the stratification of patients with iCC and in developing rational therapeutic strategies.

The Gata1low murine megakaryocyte-erythroid progenitor cells expand robustly and alter differentiation potential.

GATA1 is a master transcription factor of megakaryopoiesis and erythropoiesis, and loss-of-function mutation can induce accumulation of megakaryocyte-erythroid progenitors (MEPs) in mice and humans. Accordingly, the murine MEP cell line (termed G1ME2 cells) encoding doxycycline (dox)-inducible anti-Gata1 shRNA on Hprt locus has been developed. The cells were CD41+CD71+KIT+, expand under dox, stem cell factor, and thrombopoietin (TPO), and terminally differentiate into erythroid cells or megakaryocytes upon removal of dox. Surprisingly, in this study, these Gata1low murine MEPs displayed accelerated growth from around 90-100 days after cell culture, impeded megakaryocytic potential, and maintained erythropoiesis. We specified them as late G1ME2 cells and discovered that increased CD41-KIT+ population during long-term culture was the main reason for the delayed megakaryopoiesis. The CD41 expression level was partially de-repressed by PI3K/AKT inhibitors, suggesting that TPO-mediated cell survival signaling pathway might have impacted on CD41 in the late G1ME2 cells. Nevertheless, among the late cells, the CD41+KIT+ cells could still generate megakaryocytes on dox withdrawal. Taken together, G1ME2 cells could provide a good model to study molecular mechanism of hematopoiesis because of their ability to expand excessively without artificial immortalization.

ASpedia: a comprehensive encyclopedia of human alternative splicing.

Alternative splicing confers the human genome complexity by increasing the diversity of expressed mRNAs. Hundreds or thousands of splicing regions have been identified through differential alternative splicing analysis of high-throughput datasets. However, it is hard to explain the functional impact of each splicing event. Protein domain formation and nonsense-mediated decay are considered the main functional features of splicing. However, other functional features such as miRNA target sites, phosphorylation sites and single-nucleotide variations are directly affected by alternative splicing and affect downstream function. Hence, we established ASpedia: a comprehensive database for human alternative splicing annotation, which encompasses a range of functions, from genomic annotation to isoform-specific function (ASpedia, http://combio.snu.ac.kr/aspedia). The database provides three features: (i) genomic annotation extracted from DNA, RNA and proteins; (ii) transcription and regulation elements analyzed from next-generation sequencing datasets; and (iii) isoform-specific functions collected from known and published datasets. The ASpedia web application includes three components: an annotation database, a retrieval system and a browser specialized in the identification of human alternative splicing events. The retrieval system supports multiple AS event searches resulting from high-throughput analysis and the AS browser comprises genome tracks. Thus, ASpedia facilitates the systemic annotation of the functional impacts of multiple AS events.

Integrative molecular profiling identifies a novel cluster of estrogen receptor-positive breast cancer in very young women.

Very young breast cancer patients are more common in Asian countries than Western countries and are thought to have worse prognosis than older patients. The aim of the current study was to identify molecular characteristics of young patients with estrogen receptor (ER)-positive breast cancer by analyzing mutations and copy number variants (CNV), and by applying expression profiling. The whole exome and transcriptome of 47 Korean young breast cancer (KYBR) patients (age <35) were analyzed. Genomic profiles were constructed using mutations, CNV and differential gene expression from sequencing data. Pathway analyses were also performed using gene sets to identify biological processes. Our data were compared with young ER+ breast cancer patients in The Cancer Genome Atlas (TCGA) dataset. TP53, PIK3CA and GATA3 were highly recurrent somatic mutation genes. APOBEC-associated mutation signature was more frequent in KYBR compared with young TCGA patients. Integrative profiling was used to classify our patients into 3 subgroups based on molecular characteristics. Group A showed luminal A-like subtype and IGF1R signal dysregulation. Luminal B patients were classified into groups B and C, which showed chromosomal instability and enrichment for APOBEC3A/B deletions, respectively. Group B was characterized by 11q13 (CCND1) amplification and activation of the ubiquitin-mediated proteolysis pathway. Group C showed 17q12 (ERBB2) amplification and lower ER and progesterone receptor expression. Group C was also distinguished by immune activation and lower epithelial-mesenchyme transition (EMT) degree compared with group B. This study showed that integrative genomic profiling could classify very young patients with breast cancer into molecular subgroups that are potentially linked to different clinical characteristics.

Integrated molecular characterization of adult soft tissue sarcoma for therapeutic targets.

BACKGROUND: Several studies have investigated the molecular drivers and therapeutic targets in adult soft tissue sarcomas. However, such studies are limited by the genomic heterogeneity and rarity of sarcomas, particularly in those with complex and unbalanced karyotypes. Additional biomarkers are needed across sarcoma types to improve therapeutic strategies. To investigate the molecular characteristics of complex karyotype sarcomas (CKSs) for therapeutic targets, we performed genomic profiling. RESULTS: The mutational landscape showed that TP53, ATRX, and PTEN genes were highly mutated. CKS samples were categorized into three groups based on copy number variations that were associated with CDK4 and RB1 signatures. Integrated analysis of genomic and transcriptomic data revealed several pathways related to PDGFR, which could be a strategic target for anti-sarcoma therapy. CONCLUSIONS: This study provides a detailed molecular classification of CKSs and proposes several therapeutic targets. Targeted or combinational therapies for treating CKS should be considered before chemotherapy.

Programming of Plant Leaf Senescence with Temporal and Inter-Organellar Coordination of Transcriptome in Arabidopsis.

Plant leaves, harvesting light energy and fixing CO2, are a major source of foods on the earth. Leaves undergo developmental and physiological shifts during their lifespan, ending with senescence and death. We characterized the key regulatory features of the leaf transcriptome during aging by analyzing total- and small-RNA transcriptomes throughout the lifespan of Arabidopsis (Arabidopsis thaliana) leaves at multidimensions, including age, RNA-type, and organelle. Intriguingly, senescing leaves showed more coordinated temporal changes in transcriptomes than growing leaves, with sophisticated regulatory networks comprising transcription factors and diverse small regulatory RNAs. The chloroplast transcriptome, but not the mitochondrial transcriptome, showed major changes during leaf aging, with a strongly shared expression pattern of nuclear transcripts encoding chloroplast-targeted proteins. Thus, unlike animal aging, leaf senescence proceeds with tight temporal and distinct interorganellar coordination of various transcriptomes that would be critical for the highly regulated degeneration and nutrient recycling contributing to plant fitness and productivity.

Deregulation of immune response genes in patients with Epstein-Barr virus-associated gastric cancer and outcomes.

BACKGROUND & AIMS: Patients with Epstein-Barr virus-associated gastric carcinoma (EBVaGC) have a better prognosis than those with gastric cancer not associated with EBV infection (EBVnGC). This is partly because EBV infection recruits lymphocytes, which infiltrate the tumor. A high degree of tumor heterogeneity is likely to be associated with poor response. We investigated differences in gene expression patterns between EBVaGC and EBVnGC. METHODS: We used gene expression profile analysis to compare tumor and nontumor gastric tissues from 12 patients with EBVaGC and 14 patients with EBVnGC. Findings were validated by whole transcriptome RNAseq and real-time quantitative polymerase chain reaction analyses. CD3(+) primary T cells were isolated from human blood samples; migration of these cells and of Jurkat cells were measured in culture with EBV-infected and uninfected gastric cancer cells. RESULTS: Based on Pearson correlation matrix analysis, EBVaGCs had a higher degree of homogeneity than EBVnGCs. Although 4550 genes were differentially expressed between tumor and nontumor gastric tissues of patients with EBVnGC, only 186 genes were differentially expressed between tumor and nontumor gastric tissues of patients with EBVaGC (P < .001). This finding supports the concept that EBVaGCs have fewer genetic and epigenetic alterations than EBVnGCs. Expression of major histocompatibility complex class II genes and genes that regulate chemokine activity were more often deregulated in EBVaGCs compared with nontumor tissues. In culture, more T cells migrated to EBV-infected gastric cancer cells than to uninfected cells; migration was blocked with a neutralizing antibody against CXCR3 (a receptor for many chemokines). CONCLUSIONS: Fewer genes are deregulated in EBVaGC than in EBVnGC. Most changes in EBVaGCs occur in immune response genes. These changes might allow EBVaGC to recruit reactive immune cells; this might contribute to the better outcomes of these patients compared with those with EBVnGC.

lncRNAtor: a comprehensive resource for functional investigation of long non-coding RNAs.

MOTIVATION: A number of long non-coding RNAs (lncRNAs) have been identified by deep sequencing methods, but their molecular and cellular functions are known only for a limited number of lncRNAs. Current databases on lncRNAs are mostly for cataloging purpose without providing in-depth information required to infer functions. A comprehensive resource on lncRNA function is an immediate need. RESULTS: We present a database for functional investigation of lncRNAs that encompasses annotation, sequence analysis, gene expression, protein binding and phylogenetic conservation. We have compiled lncRNAs for six species (human, mouse, zebrafish, fruit fly, worm and yeast) from ENSEMBL, HGNC, MGI and lncRNAdb. Each lncRNA was analyzed for coding potential and phylogenetic conservation in different lineages. Gene expression data of 208 RNA-Seq studies (4995 samples), collected from GEO, ENCODE, modENCODE and TCGA databases, were used to provide expression profiles in various tissues, diseases and developmental stages. Importantly, we analyzed RNA-Seq data to identify coexpressed mRNAs that would provide ample insights on lncRNA functions. The resulting gene list can be subject to enrichment analysis such as Gene Ontology or KEGG pathways. Furthermore, we compiled protein-lncRNA interactions by collecting and analyzing publicly available CLIP-seq or PAR-CLIP sequencing data. Finally, we explored evolutionarily conserved lncRNAs with correlated expression between human and six other organisms to identify functional lncRNAs. The whole contents are provided in a user-friendly web interface. AVAILABILITY AND IMPLEMENTATION: lncRNAtor is available at http://lncrnator.ewha.ac.kr/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prediction of miRNA-mRNA associations in Alzheimer's disease mice using network topology.

BACKGROUND: Little is known about the relationship between miRNA and mRNA expression in Alzheimer's disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA. RESULTS: In total, 8 cluster modules were predicted by the transcriptome data for co-expression networks of AD pathology. In total, 54 miRNAs were identified as being differentially expressed in AD. Among these, 50 significant miRNA-mRNA interactions were predicted by integrating sequence target prediction, expression analysis, and the PageRank algorithm. We identified a set of miRNA-mRNA interactions that were changed in the hippocampus of Tg6799 AD model mice. We determined the expression levels of several candidate genes and miRNA. For functional validation in primary cultured neurons from Tg6799 mice (MT) and littermate (LM) controls, the overexpression of ARRDC3 enhanced PPP1R3C expression. ARRDC3 overexpression showed the tendency to decrease the expression of miR139-5p and miR3470a in both LM and MT primary cells. Pathological environment created by Aß treatment increased the gene expression of PPP1R3C and Sfpq but did not significantly alter the expression of miR139-5p or miR3470a. Aß treatment increased the promoter activity of ARRDC3 gene in LM primary cells but not in MT primary cells. CONCLUSIONS: Our results demonstrate AD-specific changes in the miRNA regulatory system as well as the relationship between the expression levels of miRNAs and their targets in the hippocampus of Tg6799 mice. These data help further our understanding of the function and mechanism of various miRNAs and their target genes in the molecular pathology of AD.

ASpedia-R: a package to retrieve junction-incorporating features and knowledge-based functions of human alternative splicing events.

Motivation: Alternative splicing (AS) is a key regulatory mechanism that confers genetic diversity and phenotypic plasticity of human. The exons and their flanking regions include comprehensive junction-incorporating sequence features like splicing factor-binding sites and protein domains. These elements involve in exon usage and finally contribute to isoform-specific biological functions. Splicing-associated sequence features are involved in the multilayered regulation encompassing DNA and proteins. However, most analysis applications have investigated limited sequence features, like protein domains. It is insufficient to explain the comprehensive cause and effect of exon-specific biological processes. Results: With the advent of RNA-seq technology, global AS event analysis has deduced more precise results. As accumulating analysis results, it could be a challenge to identify multi-omics sequence features for AS events. Therefore, application to investigate multi-omics sequence features is useful to scan critical evidence. ASpedia-R is an R package to interrogate junction-incorporating sequence features for human genes. Our database collected the heterogeneous profile encompassed from DNA to protein. Additionally, knowledge-based splicing genes were collected using text-mining to test the association with specific pathway terms. Our package retrieves AS events for high-throughput data analysis results via AS event ID converter. Finally, result profile could be visualized and saved to multiple formats: sequence feature result table, genome track figure, protein-protein interaction network, and gene set enrichment test result table. Our package is a convenient tool to understand global regulation mechanisms by splicing. Availability and implementation: The package source code is freely available to non-commercial users at https://github.com/ncc-bioinfo/ASpedia-R.

Tumor Microenvironment Modulation by Neoadjuvant Erlotinib Therapy and Its Clinical Impact on Operable EGFR-Mutant Non-Small Cell Lung Cancer.

PURPOSE: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors have greatly improved survival in EGFR-mutant (EGFRm) non-small cell lung cancer (NSCLC); however, their effects on the tumor microenvironment (TME) are unknown. We assessed the changes induced by neoadjuvant erlotinib therapy (NE) in the TME of operable EGFRm NSCLC. MATERIALS AND METHODS: This was a single-arm phase II trial for neoadjuvant/adjuvant erlotinib therapy in patients with stage II/IIIA EGFRm NSCLC (EGFR exon 19 deletion or L858R mutations). Patients received up to 2 cycles of NE (150 mg/day) for 4 weeks, followed by surgery and adjuvant erlotinib or vinorelbine plus cisplatin therapy depending on observed NE response. TME changes were assessed based on gene expression analysis and mutation profiling. RESULTS: A total of 26 patients were enrolled; the median age was 61, 69% were female, 88% were stage IIIA, and 62% had L858R mutation. Among 25 patients who received NE, the objective response rate was 72% (95% confidence interval [CI], 52.4 to 85.7). The median disease-free and overall survival (OS) were 17.9 (95% CI, 10.5 to 25.4) and 84.7 months (95% CI, 49.7 to 119.8), respectively. Gene set enrichment analysis in resected tissues revealed upregulation of interleukin, complement, cytokine, transforming growth factor ß, and hedgehog pathways. Patients with upregulated pathogen defense, interleukins, and T-cell function pathways at baseline exhibited partial response to NE and longer OS. Patients with upregulated cell cycle pathways at baseline exhibited stable/progressive disease after NE and shorter OS. CONCLUSION: NE modulated the TME in EGFRm NSCLC. Upregulation of immune-related pathways was associated with better outcomes.

Deficiency of thioredoxin-interacting protein results in age-related thrombocytopenia due to megakaryocyte oxidative stress.

BACKGROUND: Platelets are generated from megakaryocytes (MKs), mainly located in the bone marrow (BM). Megakaryopoiesis can be affected by genetic disorders, metabolic diseases, and aging. The molecular mechanisms underlying platelet count regulation have not been fully elucidated. OBJECTIVES: In the present study, we investigated the role of thioredoxin-interacting protein (TXNIP), a protein that regulates cellular metabolism in megakaryopoiesis, using a Txnip-/- mouse model. METHODS: Wild-type (WT) and Txnip-/- mice (2-27-month-old) were studied. BM-derived MKs were analyzed to investigate the role of TXNIP in megakaryopoiesis with age. The global transcriptome of BM-derived CD41+ megakaryocyte precursors (MkPs) of WT and Txnip-/- mice were compared. The CD34+ hematopoietic stem cells isolated from human cord blood were differentiated into MKs. RESULTS: Txnip-/- mice developed thrombocytopenia at 4 to 5 months that worsened with age. During ex vivo megakaryopoiesis, Txnip-/- MkPs remained small, with decreased levels of MK-specific markers. Critically, Txnip-/- MkPs exhibited reduced mitochondrial reactive oxygen species, which was related to AKT activity. Txnip-/- MkPs also showed elevated glycolysis alongside increased glucose uptake for ATP production. Total RNA sequencing revealed enrichment for oxidative stress- and apoptosis-related genes in differentially expressed genes between Txnip-/- and WT MkPs. The effects of TXNIP on MKs were recapitulated during the differentiation of human cord blood-derived CD34+ hematopoietic stem cells. CONCLUSION: We provide evidence that the megakaryopoiesis pathway becomes exhausted with age in Txnip-/- mice with a decrease in terminal, mature MKs that response to thrombocytopenic challenge. Overall, this study demonstrates the role of TXNIP in megakaryopoiesis, regulating mitochondrial metabolism.

Drug Response of Patient-Derived Lung Cancer Cells Predicts Clinical Outcomes of Targeted Therapy.

Intratumor heterogeneity leads to different responses to targeted therapies, even within patients whose tumors harbor identical driver oncogenes. This study examined clinical outcomes according to a patient-derived cell (PDC)-based drug sensitivity test in lung cancer patients treated with targeted therapies. From 487 lung cancers, 397 PDCs were established with a success rate of 82%. In 139 PDCs from advanced non-small-cell lung cancer (NSCLC) patients receiving targeted therapies, the standardized area under the curve (AUC) values for the drugs was significantly correlated with their tumor response (p = 0.002). Among 59 chemo-naive EGFR/ALK-positive NSCLC patients, the PDC non-responders showed a significantly inferior response rate (RR) and progression-free survival (PFS) for the targeted drugs than the PDC responders (RR, 25% vs. 78%, p = 0.011; median PFS, 3.4 months [95% confidence interval (CI), 2.8-4.1] vs. 11.8 months [95% CI, 6.5-17.0], p < 0.001). Of 25 EGFR-positive NSCLC patients re-challenged with EGFR inhibitors, the PDC responder showed a higher RR than the PDC non-responder (42% vs. 15%). Four patients with wild-type EGFR or uncommon EGFR-mutant NSCLC were treated with EGFR inhibitors based on their favorable PDC response to EGFR inhibitors, and two patients showed dramatic responses. Therefore, the PDC-based drug sensitivity test results were significantly associated with clinical outcomes in patients with EGFR- or ALK-positive NSCLC. It may be helpful for predicting individual heterogenous clinical outcomes beyond genomic alterations.

miRGator v2.0: an integrated system for functional investigation of microRNAs.

miRGator is an integrated database of microRNA (miRNA)-associated gene expression, target prediction, disease association and genomic annotation, which aims to facilitate functional investigation of miRNAs. The recent version of miRGator v2.0 contains information about (i) human miRNA expression profiles under various experimental conditions, (ii) paired expression profiles of both mRNAs and miRNAs, (iii) gene expression profiles under miRNA-perturbation (e.g. miRNA knockout and overexpression), (iv) known/predicted miRNA targets and (v) miRNA-disease associations. In total, >8000 miRNA expression profiles, ∼300 miRNA-perturbed gene expression profiles and ∼2000 mRNA expression profiles are compiled with manually curated annotations on disease, tissue type and perturbation. By integrating these data sets, a series of novel associations (miRNA-miRNA, miRNA-disease and miRNA-target) is extracted via shared features. For example, differentially expressed genes (DEGs) after miRNA knockout were systematically compared against miRNA targets. Likewise, differentially expressed miRNAs (DEmiRs) were compared with disease-associated miRNAs. Additionally, miRNA expression and disease-phenotype profiles revealed miRNA pairs whose expression was regulated in parallel in various experimental and disease conditions. Complex associations are readily accessible using an interactive network visualization interface. The miRGator v2.0 serves as a reference database to investigate miRNA expression and function (http://miRGator.kobic.re.kr).

Splicing signature database development to delineate cancer pathways using literature mining and transcriptome machine learning.

Alternative splicing (AS) events modulate certain pathways and phenotypic plasticity in cancer. Although previous studies have computationally analyzed splicing events, it is still a challenge to uncover biological functions induced by reliable AS events from tremendous candidates. To provide essential splicing event signatures to assess pathway regulation, we developed a database by collecting two datasets: (i) reported literature and (ii) cancer transcriptome profile. The former includes knowledge-based splicing signatures collected from 63,229 PubMed abstracts using natural language processing, extracted for 202 pathways. The latter is the machine learning-based splicing signatures identified from pan-cancer transcriptome for 16 cancer types and 42 pathways. We established six different learning models to classify pathway activities from splicing profiles as a learning dataset. Top-ranked AS events by learning model feature importance became the signature for each pathway. To validate our learning results, we performed evaluations by (i) performance metrics, (ii) differential AS sets acquired from external datasets, and (iii) our knowledge-based signatures. The area under the receiver operating characteristic values of the learning models did not exhibit any drastic difference. However, random-forest distinctly presented the best performance to compare with the AS sets identified from external datasets and our knowledge-based signatures. Therefore, we used the signatures obtained from the random-forest model. Our database provided the clinical characteristics of the AS signatures, including survival test, molecular subtype, and tumor microenvironment. The regulation by splicing factors was additionally investigated. Our database for developed signatures supported retrieval and visualization system.

Molecular Subtypes and Tumor Microenvironment Characteristics of Small-Cell Lung Cancer Associated with Platinum-Resistance.

Although molecular subtypes of small-cell lung cancer (SCLC) have been proposed, their clinical relevance and therapeutic implications are not fully understood. Thus, we aimed to refine molecular subtypes and to uncover therapeutic targets. We classified the subtypes based on gene expression (n = 81) and validated them in our samples (n = 87). Non-SCLC samples were compared with SCLC subtypes to identify the early development stage of SCLC. Single-cell transcriptome analysis was applied to dissect the TME of bulk samples. Finally, to overcome platinum resistance, we performed drug screening of patient-derived cells and cell lines. Four subtypes were identified: the ASCL1+ (SCLC-A) subtype identified as TP53/RB-mutated non-SCLC representing the early development stage of SCLC; the immune activation (SCLC-I) subtype, showing high CD8+/PD-L1+ T-cell infiltration and endothelial-to-mesenchymal transition (EndMT); the NEUROD1 (SCLC-N) subtype, which showed neurotransmission process; and the POU2F3+ (SCLC-P) subtype with epithelial-to-mesenchymal transition (EMT). EndMT was associated with the worst prognosis. While SCLC-A/N exhibited platinum sensitivity, the EndMT signal of SCLC-I conferred platinum resistance. A BET inhibitor suppressed the aggressive angiogenesis phenotype of SCLC-I. We revealed that EndMT development contributed to a poor outcome in SCLC-I. Moreover, heterogenous TME development facilitated platinum resistance. BET inhibitors are novel candidates for overcoming platinum resistance.

Patient-derived cell-based pharmacogenomic assessment to unveil underlying resistance mechanisms and novel therapeutics for advanced lung cancer.

BACKGROUND: A pharmacogenomic platform using patient-derived cells (PDCs) was established to identify the underlying resistance mechanisms and tailored treatment for patients with advanced or refractory lung cancer. METHODS: Drug sensitivity screening and multi-omics datasets were acquired from lung cancer PDCs (n = 102). Integrative analysis was performed to explore drug candidates according to genetic variants, gene expression, and clinical profiles. RESULTS: PDCs had genomic characteristics resembled with those of solid lung cancer tissues. PDC molecular subtyping classified patients into four groups: (1) inflammatory, (2) epithelial-to-mesenchymal transition (EMT)-like, (3) stemness, and (4) epithelial growth factor receptor (EGFR)-dominant. EGFR mutations of the EMT-like subtype were associated with a reduced response to EGFR-tyrosine kinase inhibitor therapy. Moreover, although RB1/TP53 mutations were significantly enriched in small-cell lung cancer (SCLC) PDCs, they were also present in non-SCLC PDCs. In contrast to its effect in the cell lines, alpelisib (a PI3K-AKT inhibitor) significantly inhibited both RB1/TP53 expression and SCLC cell growth in our PDC model. Furthermore, cell cycle inhibitors could effectively target SCLC cells. Finally, the upregulation of transforming growth factor-ß expression and the YAP/TAZ pathway was observed in osimertinib-resistant PDCs, predisposing them to the EMT-like subtype. Our platform selected XAV939 (a WNT-TNKS-ß-catenin inhibitor) for the treatment of osimertinib-resistant PDCs. Using an in vitro model, we further demonstrated that acquisition of osimertinib resistance enhances invasive characteristics and EMT, upregulates the YAP/TAZ-AXL axis, and increases the sensitivity of cancer cells to XAV939. CONCLUSIONS: Our PDC models recapitulated the molecular characteristics of lung cancer, and pharmacogenomics analysis provided plausible therapeutic candidates.

Nivolumab after Induction Chemotherapy in Previously Treated Non-Small-Cell Lung Cancer Patients with Low PD-L1 Expression.

This study aimed to investigate whether cyclophosphamide (C) and adriamycin (A) induction therapy (IT) prior to nivolumab could enhance the efficacy of nivolumab in previously treated patients with non-squamous (NSQ) non-small-cell lung cancer (NSCLC) with less than 10% programmed death-ligand 1 (PD-L1) expression. Twenty-two enrolled patients received four cycles of CA-IT every 3 weeks. Nivolumab was given 360 mg every 3 weeks from the second cycle and 480 mg every 4 weeks after four cycles of CA-IT. The median progression-free survival (PFS) and overall survival (OS) were 2.4 months and 11.6 months, respectively. Fluorescence-activated cell sorting revealed the lowest ratio of myeloid-derived suppressor cells (MDSCs) to CD8+T-cells in the responders. Proteomic analysis identified a consistent upregulation of extracellular matrix-receptor interactions and phagosome pathways in the responders. Among the differentially expressed proteins, the transferrin receptor protein (TFRC) was higher in the responders before treatment (fold change > 1.2). TFRC validation with an independent cohort showed the prognostic significance of either OS or PFS in patients with low PD-L1 expression. In summary, CA-IT did not improve nivolumab efficacy in NSQ-NSCLCs with low PD-L1 expression; however, it induced decreasing MDSC, resulting in a durable response. Higher baseline TFRC levels predicted a favorable response to nivolumab in NSCLC with low PD-L1 expression.

ASpediaFI: Functional Interaction Analysis of Alternative Splicing Events.

Alternative splicing (AS) regulates biological processes governing phenotypes and diseases. Differential AS (DAS) gene test methods have been developed to investigate important exonic expression from high-throughput datasets. However, the DAS events extracted using statistical tests are insufficient to delineate relevant biological processes. In this study, we developed a novel application, Alternative Splicing Encyclopedia: Functional Interaction (ASpediaFI), to systemically identify DAS events and co-regulated genes and pathways. ASpediaFI establishes a heterogeneous interaction network of genes and their feature nodes (i.e., AS events and pathways) connected by co-expression or pathway gene set knowledge. Next, ASpediaFI explores the interaction network using the random walk with restart algorithm and interrogates the proximity from a query gene set. Finally, ASpediaFI extracts significant AS events, genes, and pathways. To evaluate the performance of our method, we simulated RNA sequencing (RNA-seq) datasets to consider various conditions of sequencing depth and sample size. The performance was compared with that of other methods. Additionally, we analyzed three public datasets of cancer patients or cell lines to evaluate how well ASpediaFI detects biologically relevant candidates. ASpediaFI exhibits strong performance in both simulated and public datasets. Our integrative approach reveals that DAS events that recognize a global co-expression network and relevant pathways determine the functional importance of spliced genes in the subnetwork. ASpediaFI is publicly available at https://bioconductor.org/packages/ASpediaFI.

Single-cell analysis of gastric pre-cancerous and cancer lesions reveals cell lineage diversity and intratumoral heterogeneity.

Single-cell transcriptomic profiles analysis has proposed new insights for understanding the behavior of human gastric cancer (GC). GC offers a unique model of intratumoral heterogeneity. However, the specific classes of cells involved in carcinogenetic passage, and the tumor microenvironment of stromal cells was poorly understood. We characterized the heterogeneous cell population of precancerous lesions and gastric cancer at the single-cell resolution by RNA sequencing. We identified 10 gastric cell subtypes and showed the intestinal and diffuse-type cancer were characterized by different cell population. We found that the intestinal and diffuse-type cancer cells have the differential metaplastic cell lineages: intestinal-type cancer cells differentiated along the intestinal metaplasia lineage while diffuse-type cancer cells resemble de novo pathway. We observed an enriched CCND1 mutation in premalignant disease state and discovered cancer-associated fibroblast cells harboring pro-stemness properties. In particular, tumor cells could be categorized into previously proposed molecular subtypes and harbored specific subtype of malignant cell with high expression level of epithelial-myofibroblast transition which was correlated with poor clinical prognosis. In addition to intratumoral heterogeneity, the analysis revealed different cellular lineages were responsible for potential carcinogenetic pathways. Single-cell transcriptomes analysis of gastric pre-cancerous lesions and cancer may provide insights for understanding GC cell behavior, suggesting potential targets for the diagnosis and treatment of GC.