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Transcriptomic Plasticity Is a Hallmark of Metastatic Pancreatic Cancer.
UNLABELLED: Metastasis is the leading cause of cancer deaths. To develop strategies for intercepting metastatic progression, a better understanding of how tumor cells adapt to vastly different organ contexts is needed. To investigate this question, a single-cell transcriptomic atlas of primary tumors and diverse metastatic samples (liver, omentum, peritoneum, stomach wall, lymph node, and diaphragm) from a patient with pancreatic ductal adenocarcinoma who underwent rapid autopsy was generated. Using unsupervised archetype analysis, both shared and site-specific gene programs were identified, including lipid metabolism and gastrointestinal programs prevalent in peritoneal and stomach wall lesions, respectively. We developed phylogenetic inference from copy-number alterations in single-cell sequencing observations (PICASSO) as a probabilistic approach for inferring clonal phylogeny from single-cell and matched whole-exome sequencing data. Comparison of PICASSO-generated clonal structure with phenotypic signatures revealed that pancreatic cancer cells adapted to local environments with minimal contribution from clonal genotype. Our results suggest a paradigm whereby strong environmental effects are imposed on highly plastic cancer cells during metastatic dissemination. SIGNIFICANCE: Single-cell transcriptional profiling of primary tumor and metastases from rapid autopsy samples of an individual with pancreatic cancer, combined with probabilistic clonal inference by PICASSO, reveals substantial transcriptomic plasticity in metastatic cells. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI .
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Epigallocatechin gallate is associated with PDGFRB downregulation and altered PI3K-AKT signaling in gastric cancer.
BACKGROUND: Gastric cancer (GC) remains a major cause of cancer-related mortality worldwide. Epigallocatechin gallate (EGCG), a natural polyphenol derived from green tea, exhibits anticancer properties; however, its molecular targets and regulatory mechanisms in GC are not fully elucidated. This study aimed to identify candidate EGCG-associated genes in GC and generate a hypothesis for future mechanistic investigation. METHODS: Differentially expressed genes (DEGs) in GC were identified and intersected with EGCG-associated targets retrieved from The Cancer Genome Atlas (TCGA) and GeneCards public databases. Least absolute shrinkage and selection operator (LASSO) regression and Cox proportional hazards analyses were performed to screen prognostically relevant genes. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Functional enrichment analysis was conducted to explore biological significance. Public single-cell RNA sequencing datasets were analyzed to determine the cellular localization of platelet-derived growth factor receptor beta (PDGFRB), while DepMap transcriptomic data were used to assess its expression across GC cell lines. In vitro assays, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), Transwell migration, and Western blotting, were performed to evaluate the biological effects of EGCG on GC-associated signaling pathways. RESULTS: Thirty-eight EGCG-associated DEGs were identified. Enrichment analysis revealed these genes were involved in cancer-associated pathways. LASSO-Cox modelling identified four candidate genes. Among them, PDGFRB was selected for further investigation based on its prognostic relevance and favorable diagnostic performance. PDGFRB expression was significantly higher in the TCGA genomically stable (GS) subtype than in the other molecular subtypes and was predominantly localized to cancer-associated fibroblasts (CAFs) and pericytes in single-cell RNA sequencing analysis. DepMap data demonstrated heterogeneous PDGFRB expression across GC cell lines. In vitro experiments showed that EGCG inhibited proliferation, migration, and invasion, reduced PDGFRB protein expression, and was associated with apoptosis-related protein changes and altered PI3K-AKT signaling. CONCLUSIONS: Our findings suggest that EGCG treatment was associated with reduced PDGFRB expression and altered PI3K-AKT signaling in GC cells. These findings identify PDGFRB as a candidate EGCG-associated gene and provide a hypothesis for future mechanistic investigation.
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The Medicago sativa gene index 1.2: a web-accessible gene expression atlas for investigating expression differences between Medicago sativa subspecies.
BACKGROUND: Alfalfa (Medicago sativa L.) is the primary forage legume crop species in the United States and plays essential economic and ecological roles in agricultural systems across the country. Modern alfalfa is the result of hybridization between tetraploid M. sativa ssp. sativa and M. sativa ssp. falcata. Due to its large and complex genome, there are few genomic resources available for alfalfa improvement. RESULTS: A de novo transcriptome assembly from two alfalfa subspecies, M. sativa ssp. sativa (B47) and M. sativa ssp. falcata (F56) was developed using Illumina RNA-seq technology. Transcripts from roots, nitrogen-fixing root nodules, leaves, flowers, elongating stem internodes, and post-elongation stem internodes were assembled into the Medicago sativa Gene Index 1.2 (MSGI 1.2) representing 112,626 unique transcript sequences. Nodule-specific and transcripts involved in cell wall biosynthesis were identified. Statistical analyses identified 20,447 transcripts differentially expressed between the two subspecies. Pair-wise comparisons of each tissue combination identified 58,932 sequences differentially expressed in B47 and 69,143 sequences differentially expressed in F56. Comparing transcript abundance in floral tissues of B47 and F56 identified expression differences in sequences involved in anthocyanin and carotenoid synthesis, which determine flower pigmentation. Single nucleotide polymorphisms (SNPs) unique to each M. sativa subspecies (110,241) were identified. CONCLUSIONS: The Medicago sativa Gene Index 1.2 increases the expressed sequence data available for alfalfa by ninefold and can be expanded as additional experiments are performed. The MSGI 1.2 transcriptome sequences, annotations, expression profiles, and SNPs were assembled into the Alfalfa Gene Index and Expression Database (AGED) at http://plantgrn.noble.org/AGED/ , a publicly available genomic resource for alfalfa improvement and legume research.
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The role of IQCB1 in liver cancer: a bioinformatics analysis.
BACKGROUND: Liver hepatocellular carcinoma (LIHC) is a prevalent malignancy globally, exhibiting substantial incidence and mortality rates. Early diagnosis and prevention of metastasis are crucial for the benefit of patients with liver cancer. The present study aimed to elucidate the involvement of IQCB1 in liver cancer through the utilization of bioinformatics. METHODS: The samples utilized in this study were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Initially, the TCGA-LIHC dataset was employed to examine the expression of IQCB1, and its validation was performed on the GSE25097 dataset. Subsequently, Kaplan-Meier (KM) analysis was conducted to evaluate the prognostic significance of IQCB1 in LIHC, and its correlation with clinical pathological features was also investigated. Furthermore, a protein-protein interaction (PPI) network consisting of 20 proteins associated with IQCB1 was constructed using data from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out. A risk model was formulated to assess the prognostic significance and its prognostic value was compared to that of IQCB1 in isolation. Furthermore, an examination was conducted to explore the correlation between IQCB1 and immune infiltration, along with the involvement of immunological checkpoints. A drug sensitivity assessment of IQCB1 was performed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Additionally, the Tumor Immune Single-cell Hub (TISCH) database was utilized to investigate the association between IQCB1 and the tumor microenvironment (TME). RESULTS: The expression of IQCB1 was observed to be significantly elevated in tumor samples. Furthermore, patients with high expression levels of IQCB1 demonstrated a poorer prognosis. Additionally, IQCB1 exhibited significant correlations with MKI67, hepatitis B virus (HBV), hepatitis C virus (HCV), and alpha-fetoprotein (AFP). GO and KEGG analyses revealed enrichment of multiple signaling pathways. Subsequently, an investigation was conducted to examine the association between IQCB1 and the activity of ten signaling pathways related to tumor development. A positive correlation was observed between IQCB1 expression and T-helper 2 (Th2) cells, whereas a negative correlation was observed between IQCB1 expression and Th17 cells. Furthermore, a positive association was found between IQCB1 and immune checkpoints, particularly with CD276. Analysis of single-cell data from the TISCH database revealed widespread expression of IQCB1 in the TME. Additionally, screening revealed that among 12 drugs related to IQCB1, a subset of 10 drugs demonstrated negative correlations, whereas two drugs exhibited positive correlations. CONCLUSIONS: IQCB1 has the potential to function as a diagnostic and prognostic molecular marker, and its association with immune infiltration and checkpoint mechanisms has been observed.
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Distinct identities of leaf phloem cells revealed by single cell transcriptomics.
The leaf vasculature plays a key role in solute translocation. Veins consist of at least seven distinct cell types, with specific roles in transport, metabolism, and signaling. Little is known about leaf vascular cells, in particular the phloem parenchyma (PP). PP effluxes sucrose into the apoplasm as a basis for phloem loading, yet PP has been characterized only microscopically. Here, we enriched vascular cells from Arabidopsis leaves to generate a single-cell transcriptome atlas of leaf vasculature. We identified at least 19 cell clusters, encompassing epidermis, guard cells, hydathodes, mesophyll, and all vascular cell types, and used metabolic pathway analysis to define their roles. Clusters comprising PP cells were enriched for transporters, including SWEET11 and SWEET12 sucrose and UmamiT amino acid efflux carriers. We provide evidence that PP development occurs independently from ALTERED PHLOEM DEVELOPMENT, a transcription factor required for phloem differentiation. PP cells have a unique pattern of amino acid metabolism activity distinct from companion cells (CCs), explaining differential distribution/metabolism of amino acids in veins. The kinship relation of the vascular clusters is strikingly similar to the vein morphology, except for a clear separation of CC from the other vascular cells including PP. In summary, our single-cell RNA-sequencing analysis provides a wide range of information into the leaf vasculature and the role and relationship of the leaf cell types.
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LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.
Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-κB) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.
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Hepatitis B virus X protein (HBx)-mediated immune modulation and prognostic model development in hepatocellular carcinoma.
Hepatitis B virus (HBV) X protein (HBx) is critical in hepatocellular carcinoma (HCC) development, but its influence on tumor immunity and the tumor microenvironment (TME) remains unclear. This study aimed to construct a prognostic model based on HBx-related genes and explore their relationship with immune infiltration and immunotherapy response. Through transcriptome sequencing of our HBx-expressing HepG2 cells and analysis of HCC patient data from the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx), we identified seven HBx-related genes, nuclear VCP-like (NVL), WD repeat domain 75 (WDR75), NOP58 nucleolar protein (NOP58), Brix domain-containing protein 1 (BRIX1), deoxynucleotidyltransferase terminal interacting protein 2 (DNTTIP2), MKI67 FHA domain interacting nucleolar phosphoprotein (NIFK), and ribosome production factor 2 (RPF2), associated with poor prognosis. LASSO Cox regression narrowed these to four key genes (BRIX1, RPF2, DNTTIP2, and WDR75), which were used to develop a prognostic riskscore signature. High-risk patients exhibited lower survival rates, decreased infiltration of anti-tumor immune cells, poorer responses to immunotherapy, and increased immune evasion. Among the four genes, DNTTIP2 showed higher expression in single-cell data, was linked to migration inhibitory factor (MIF) signaling, and may play a pivotal role in shaping an immunosuppressive TME. Elevated DNTTIP2 expression was confirmed in HBx-expressing HepG2 cells and HBV-infected HCC samples. This study highlights a novel HBx-related four-gene prognostic model that predicts clinical outcomes, immune infiltration, and immunotherapy response, offering insights into HCC progression and potential therapeutic targets.
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CD90 Marks a Mesenchymal Program in Human Thymic Epithelial Cells In Vitro and In Vivo.
Thymic epithelium is critical for the structural integrity of the thymus and for T cell development. Within the fully formed thymus, large numbers of hematopoietic cells shape the thymic epithelium into a scaffold-like structure which bears little similarity to classical epithelial layers, such as those observed in the skin, intestine or pancreas. Here, we show that human thymic epithelial cells (TECs) possess an epithelial identity that also incorporates the expression of mesenchymal cell associated genes, whose expression levels vary between medullary and cortical TECs (m/cTECs). Using pluripotent stem cell (PSC) differentiation systems, we identified a unique population of cells that co-expressed the master TEC transcription factor FOXN1, as well as the epithelial associated marker EPCAM and the mesenchymal associated gene CD90. Using the same serum free culture conditions, we also observed co-expression of EPCAM and CD90 on cultured TECs derived from neonatal human thymus in vitro. Single cell RNA-sequencing revealed these cultured TECs possessed an immature mTEC phenotype and expressed epithelial and mesenchymal associated genes, such as EPCAM, CLDN4, CD90 and COL1A1. Importantly, flow cytometry and single cell RNA-sequencing analysis further confirmed the presence of an EPCAM+CD90+ population in the CD45- fraction of neonatal human thymic stromal cells in vivo. Using the human thymus cell atlas, we found that cTECs displayed more pronounced mesenchymal characteristics than mTECs during embryonic development. Collectively, these results suggest human TECs possess a hybrid gene expression program comprising both epithelial and mesenchymal elements, and provide a basis for the further exploration of thymus development from primary tissues and from the in vitro differentiation of PSCs.
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Data Mining for Identification of Targets and Repurposed Drugs to Eliminate Persistent Chronic Myeloid Leukaemia Stem Cells: Targeting RAS/RAF Signalling.
BACKGROUND: Persistent leukaemic stem cells (LSCs) in chronic myeloid leukaemia (CML) are insensitive to targeted tyrosine kinase inhibitors (TKIs). Identifying alternative molecular vulnerabilities may offer new therapeutic opportunities. This study aimed to identify active RAS/RAF signalling pathway components in persistent CML-LSCs using publicly available datasets to propose a novel drug combination that could synergise with TKI therapy. METHODS: EMBL-EBI Single Cell Expression Atlas and Stemformatics were used to analyse gene expression within the chosen signalling pathway using DESeq2 analysis in R Studio. Genes that showed statistically significant differences across three comparisons (CML vs. normal; post vs. pre TKI; post TKI vs. normal) were evaluated for gene dependency (Chronos scores), expression profiles, and inhibitor sensitivity using the DepMap platform, with a focus on CML cell lines. Candidate inhibitors were identified using DrugBank. RESULTS: PPP2CA demonstrated broad essentiality with negative Chronos scores consistent with strong gene dependency. Its expression was consistently high, reinforcing its biological relevance in CML. LB-100 was found as a PP2A inhibitor under trial. Sensitivity analysis revealed LB-100 affected 548 cancer cell lines broadly. CONCLUSION: PPP2CA represents a promising therapeutic vulnerability in CML, supported by both strong dependency and consistent expression in myeloid models, while BRAF showed limited relevance outside mutation-driven cancers. Variation in experimental platforms, sample representation, and data integration across public datasets is a recognised study limitation. Nonetheless, LB-100 may provide a novel therapeutic avenue in CML, provided further preclinical functional and clinical validation is performed in patient-derived samples to confirm translational applicability of the findings.
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Prognostic and Immunological Value of CTNNB1 in Pancreatic Adenocarcinoma: A Comprehensive NGS and Multicomponent Analysis.
BACKGROUND: To explore the prognostic value and immunomodulatory role of CTNNB1 in pancreatic ductal adenocarcinoma (PDAC), so as to provide evidence for the diagnosis and individualized treatment of PDAC. METHODS: Next-generation sequencing (NGS) was performed to detect 425 cancer-associated genes in PDAC specimens and matched normal pancreatic tissues. Integrative transcriptome analysis based on TCGA, GTEx, and multiple GEO datasets was conducted to identify the differential expression of CTNNB1 between PDAC and normal pancreatic tissues. The Human Protein Atlas (HPA, https://www.proteinatlas.org/) database was used to verify the protein expression and subcellular localization of CTNNB1 in normal pancreatic tissues and pancreatic ductal adenocarcinoma (PDAC) tissues. Single-cell RNA-sequencing and spatial transcriptomic data were further supplemented to delineate its cellular expression landscape. Forest plot, Kaplan-Meier survival analysis, and ROC curve analysis were applied to evaluate the correlations between CTNNB1 expression and prognostic and to verify its prognostic accuracy. The prognostic reliability was further validated using the independent cohort GSE57495. Immune cell infiltration and immune regulatory factors were quantified via TIMER, EPIC, MCPcounter, CIBERSORT, and xCell algorithms, and TMEscore was calculated to predict the responsiveness to immune checkpoint blockade (ICB). Pharmacogenomic datasets including GDSC1, GDSC2, PRISM, and CTRP were utilized to screen optimal candidate drugs for CTNNB1-high PDAC patients. RESULTS: CTNNB1 was significantly overexpressed in PDAC compared with normal pancreatic tissues. HPA immunohistochemistry confirmed CTNNB1 shifts from membranous to cytoplasmic localization in PDAC, indicating activated Wnt signaling and concordant dysregulation at mRNA and protein levels. CTNNB1 protein was mainly localized in malignant epithelial cells of PDAC, with elevated expression also observed in partial immune cell subsets by single-cell sequencing and spatial transcriptome assessment. Upregulated CTNNB1 was significantly linked to unfavorable clinical prognosis in PDAC. ROC analysis verified its good diagnostic efficiency for distinguishing PDAC from peritumoral tissues with favorable sensitivity and specificity. CTNNB1 expression was closely correlated with multiple immune biomarker molecules and ICB therapeutic efficacy; patients with low CTNNB1 expression tended to be more responsive to ICB treatment. Pharmacological prediction revealed that PDAC patients with high CTNNB1 expression exhibited enhanced sensitivity to clofibrate and several other small-molecule compounds. CONCLUSION: CTNNB1 may be remarkably effective as a suitable biomarker for the prognosis prediction of PDAC patients and is closely related to the tumor immune microenvironment. Such an association could provide novel thoughts for the therapy tactics and mechanistic studies toward PDAC.