Expression Landscape Research Articles

Integrated whole-exome and bulk transcriptome sequencing delineates the dynamic evolution from preneoplasia to invasive lung adenocarcinoma featured with ground-glass nodules.

The genomic and molecular ecology involved in the stepwise continuum progression of lung adenocarcinoma (LUAD) from adenocarcinoma insitu (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) remains unclear and requires further elucidation. We aimed to characterize gene mutations and expression landscapes, and explore the association between differentially expressed genes (DEGs) and significantly mutated genes (SMGs) during the dynamic evolution from AIS to IAC. Thirty-five patients with ground-glass nodules (GGNs) lung adenocarcinomas were enrolled. Whole-exome sequencing (WES) and transcriptome sequencing (RNA-Seq) were conducted on all patients, encompassing both tumor samples and corresponding noncancerous tissues. Data obtained from WES and RNA-Seq were subsequently analyzed. The findings from WES delineated that the predominant mutations were observed in EGFR (49%) and ANKRD36C (17%). SMGs, including EGFR and RBM10, were associated with the dynamic evolution from AIS to IAC. Meanwhile, DEGs, including GPR143, CCR9, ADAMTS16, and others were associated with the entire process of invasive LUAD. We found that the signaling pathways related to cell migration and invasion were upregulated, and the signaling pathways of angiogenesis were downregulated across the pathological stages. Furthermore, we found that the messenger RNA (mRNA) levels of FAM83A, MAL2, DEPTOR, and others were significantly correlated with CNVs. Gene set enrichment analysis (GSEA) showed that heme metabolism and cholesterol homeostasis pathways were significantly upregulated in patients with EGFR/RBM10 co-mutations, and these patients may have poorer overall survival than those with EGFR mutations. Based on the six calculation methods for the immune infiltration score, NK/CD8+ T cells decreased, and Treg/B cells increased with the progression of early LUAD. Our findings offer valuable insights into the unique genomic and molecular features of LUAD, facilitating the identification and advancement of precision medicine strategies targeting the invasive progression of LUAD from AIS to IAC.

Haplotype-resolved T2T genome assemblies and pangenome graph of pear reveal diverse patterns of allele-specific expression and the genomic basis of fruit quality traits

Hybrid crops often exhibit increased yield and greater resilience, yet the genomic mechanism(s) underlying hybrid vigor or heterosis remain unclear, hindering our ability to predict the expression of phenotypic traits in hybrid breeding. Here, we generated haplotype-resolved T2T genome assemblies of two pear hybrid varieties, ‘Yuluxiang’ (YLX) and ‘Hongxiangsu’ (HXS), which share the same maternal parent but differ in their paternal parents. We then used these assemblies to explore the genome-scale landscape of allele-specific expression (ASE) and create a pangenome graph for pear. ASE was observed for close to 6000 genes in both hybrid cultivars. A subset of ASE genes related to aspects of fruit quality such as sugars, organic acids, and cuticular wax were identified, suggesting their important contributions to heterosis. Specifically, Ma1, a gene regulating fruit acidity, is absent in the paternal haplotypes of HXS and YLX. A pangenome graph was built based on our assemblies and seven published pear genomes. Resequencing data for 139 cultivated pear genotypes (including 97 genotypes sequenced here) were subsequently aligned to the pangenome graph, revealing numerous structural variant hotspots and selective sweeps during pear diversification. As predicted, the Ma1 allele was found to be absent in varieties with low organic acid content, and this association was functionally validated by Ma1 overexpression in pear fruit and calli. Overall, these results reveal the contributions of ASE to fruit-quality heterosis and provide a robust pangenome reference for high-resolution allele discovery and association mapping.

A programmable CRISPR/dCas9-based epigenetic editing system enabling loci-targeted histone citrullination and precise transcription regulation

Histone citrullination, an important post-translational modification mediated by peptidyl arginine deiminases, is essential for many physiological processes and epigenetic regulation. However, the causal relationship between histone citrullination and specific gene regulation remains unresolved. In this study, we develop a programmable epigenetic editor by fusing the peptidyl arginine deiminase PPAD from Porphyromonas gingivalis with dCas9. With the assistance of gRNA, PPAD-dCas9 can recruit peptidyl arginine deiminases to specific genomic loci, enabling direct manipulation of the epigenetic landscape and regulation of gene expression. Our citrullination editor allows for site-specific manipulation of histone H3R2,8,17 and 26 at target human gene loci, resulting in the activation or suppression of different genes in a locus-specific manner. Moreover, the epigenetic effects of the citrullination editor are specific and sustained. This epigenetic editor offers an accurate and efficient tool for exploring gene regulation of histone citrullination.

Granuloma Annulare Exhibits Mixed Immune and Macrophage Polarization Profiles with Spatial Transcriptomics

Granuloma annulare (GA) is an idiopathic condition characterized by granulomatous inflammation in the skin. Prior studies have suggested that GA develops from various triggers, leading to a complex interplay involving innate and adaptive immunity, tissue remodeling, and fibrosis. Macrophages are the major immune cells comprising GA granulomas; however, the molecular drivers and inflammatory signaling cascade behind macrophage activation are poorly understood. Histologically, GA exhibits both palisaded and interstitial patterns on histology; however, the molecular composition of GA at the spatial level remains unexplored. GA is a condition without Food and Drug Administration-approved therapies despite the significant impact of GA on QOL. Spatial transcriptomics is a valuable tool for profiling localized, genome-wide gene expression changes across tissues, with emerging applications in clinical medicine. To improve our understanding of the spatially localized gene expression patterns underlying GA, we profiled the spatial gene expression landscape from 6 patients with GA. Our findings revealed mixed T helper 1 and T helper 2 signals comprising the GA microenvironment and spatially distinct M1 and M2 macrophage polarization characteristics. IFN-γ and TNF signals emerged as important regulators of GA granulomatous inflammation, and IL-32 emerged as a key driver of granulomatous inflammation. Overall, our spatial transcriptomics data indicate that GA exhibits mixed immune and macrophage polarization.

Comprehensive analysis and experimental verification reveal the molecular characteristics of EGLN3 in pan-cancer and its relationship with the proliferation and apoptosis of lung cancer

BackgroundEgl-9 family hypoxia-inducible factor 3 (EGLN3) is involved in the regulation of tumor microenvironment and tumor progression. However, its biological function and clinical significance in various cancers remain unclear. MethodsRNA-seq, immunofluorescence, and single-cell sequencing were used to investigate the expression landscape of EGLN3 in pan-cancer. The TISCH2 and CancerSEA databases were used for single-cell function analysis of EGLN3 in tumors. TIMER2.0 database was used to explain the relationship between EGLN3 expression and immune cell infiltration. In addition, the LinkedOmics database was used to perform KEGG enrichment analysis of EGLN3 in pan-cancer. siRNA was used to silence gene expression. CCK8, transwell migration assay, flow cytometry analysis, RT-PCR, and western blotting were used to explore biological function of EGLN3. ResultsThe results showed that EGLN3 was highly expressed in a variety of tumors, and was mainly localized to the cytosol. EGLN3 expression is associated with immunoinfiltration of a variety of immune cells, including macrophages in the tumor immune microenvironment and tumor-associated fibroblasts. Functional experiments revealed that EGLN3 knockdown could inhibit cell proliferation, migration, and promote cell apoptosis. In addition, we found that Bax expression was up-regulated and Bcl-2 expression was down-regulated in the si-EGLN3 group. Taken together, as a potential oncogene, EGLN3 is involved in the regulation of tumor malignant process, especially tumor cell apoptosis. ConclusionWe comprehensively investigated the expression pattern, single-cell function, immune infiltration level and regulated signaling pathway of EGLN3 in pan-cancer. We found that EGLN3 is an important hypoxia and immune-related gene that may serve as a potential target for tumor immunotherapy.

Nectin-4 expression in primary breast cancer and associated clinical outcomes.

570 Background: Antibody-drug conjugates (ADC) selectively deliver chemotherapy to tumor cells expressing a target antigen. Currently approved ADCs in breast cancer target HER2 or Trop-2. Enfortumab vedotin, an ADC targeting Nectin-4, a cell adhesion molecule, is approved in advanced/metastatic urothelial cancer. This study evaluated the expression landscape of Nectin-4 in breast cancer and its association with clinical outcomes. Methods: Processed mRNAseq data was assessed for expression of the gene encoding Nectin-4 in primary breast cancer tissue and adjacent normal breast tissue from The Cancer Genome Atlas (TCGA), and normal tissue from the Genotype-Tissue Expression (GTEx) Project. Low gene expression was determined as <100 transcripts per million (TPM). TCGA samples had been annotated for putative copy-number alterations using GISTIC 2.0; genes with a score of 2 were marked as amplified. Multivariable Cox regression analysis was used to analyze the association of low vs medium/high gene expression with disease-free survival (DFS) and overall survival (OS), adjusting for age, stage, and subtype. Results: RNA-Seq data was available for 1086 patients with primary breast cancer, including known hormone receptor positive (HR+)/HER2- (n=530), HER2+ (n=112), and triple negative breast cancer (TNBC) (n=120). NECTIN4was amplified in 15% of cases (n=165): 15% (n=78) in HR+, 15% (n=17) in HER2+ and 21% (n=25) in TNBC. NECTIN4 expression was medium/high in 356 (33%) patients: 149 (28%) HR+/HER2- (median 77.8 TPM, IQR 50.1-116.5), 32 (29%) HER2+ (median 73.7 TPM, IQR 51.9-107.8), and 59 (49%) TNBC (median 99.7 TPM, IQR 57.8-148.3). Median expression in normal breast tissue was 47 TPM (TCGA) & 16.74 TPM (GTEx), and highest in normal skin at 205 TPM. In multivariable analysis, medium/high NECTIN4 expression was associated with worse OS (HR 1.96, 95% CI 1.32-2.99, p<0.001). As a continuous variable, increasing NECTIN4 expression levels were associated with worse OS. After correcting for age, stage and subtype, for each 10-unit increase in NECTIN4TPM, the risk of death increased by 5% (HR 1.0050, 95% CI 1.0028 - 1.0072, p < 0.001). Conclusions: NECTIN4 expression was higher in TNBC and associated with worse overall survival. The high expression level in normal skin possibly contributes to the cutaneous toxicity associated with enfortumab vedotin approval and requires careful consideration as ADCs targeting Nectin-4 are developed to target breast cancer.

Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation.

Recent advances in spatial transcriptomics allow spatially resolved gene expression measurements with cellular or even sub-cellular resolution, directly characterizing the complex spatiotemporal gene expression landscape and cell-to-cell interactions in their native microenvironments. Due to technology limitations, most spatial transcriptomic technologies still yield incomplete expression measurements with excessive missing values. Therefore, gene imputation is critical to filling in missing data, enhancing resolution, and improving overall interpretability. However, existing methods either require additional matched single-cell RNA-seq data, which is rarely available, or ignore spatial proximity or expression similarity information. To address these issues, we introduce Impeller, a path-based heterogeneous graph learning method for spatial transcriptomic data imputation. Impeller has two unique characteristics distinct from existing approaches. First, it builds a heterogeneous graph with two types of edges representing spatial proximity and expression similarity. Therefore, Impeller can simultaneously model smooth gene expression changes across spatial dimensions and capture similar gene expression signatures of faraway cells from the same type. Moreover, Impeller incorporates both short- and long-range cell-to-cell interactions (e.g. via paracrine and endocrine) by stacking multiple GNN layers. We use a learnable path operator in Impeller to avoid the over-smoothing issue of the traditional Laplacian matrices. Extensive experiments on diverse datasets from three popular platforms and two species demonstrate the superiority of Impeller over various state-of-the-art imputation methods. The code and preprocessed data used in this study are available at https://github.com/aicb-ZhangLabs/Impeller and https://zenodo.org/records/11212604.

The diagnostic potential role of thioredoxin reductase and TXNRD1 in early lung adenocarcinoma: A cohort study

BackgroundLung adenocarcinoma (LUAD) is the primary form of lung cancer, yet the reliable biomarkers for early diagnosis remain insufficient. Thioredoxin reductase (TrxR) is strongly linked to the occurrence, development, and drug resistance of lung cancer, making it a potential biomarker. However, further research is required to assess its diagnostic value in LUAD. MethodsA retrospective analysis was performed on patients who underwent pulmonary nodule resection at our center from 2018 to 2022. Clinical data, including preoperative TrxR levels, imaging, and laboratory characteristics, were identified as study variables. Two prediction models were constructed using multiple logistic regression, and their prediction performance was evaluated comprehensively. Besides, bioinformatics analyses of TrxR coding genes including differential expression, functional enrichment, immune infiltration, drug sensitivity, and single-cell landscape were performed based on TCGA database, which were subsequently validated by Human Protein Atlas. ResultsA total of 506 eligible patients (72 benign lesions, 77 AISs, 185 MIAs and 172 IACs) were identified in the clinical cohort. Two TrxR-based models were developed, which were able to distinguish between benign and malignant pulmonary nodules, as well as pathological subtypes of LUAD, respectively. The models exhibited good predictive ability with all AUC values ranging from 0.7 to 0.9. Based on calibration curves and clinical decision analysis, the nomogram models showed high reliability. Functional analysis indicated that TXNRD1 primarily participated in cell cycle and lipid metabolism. Immune infiltration analysis showed that TXNRD1 has a strong association with immune cells and could impact immunotherapy. Then, we identified small molecular compounds that inhibit TXNRD1 and confirmed TXNRD1 expression by single-cell landscape and immunohistochemistry. ConclusionThis study validated the diagnostic value of TrxR and TXNRD1 in clinical cohorts and transcriptional data, respectively. TrxR and TXNRD1 could be used in the risk diagnosis of early LUAD and facilitate personalized treatment strategies.

Determinants of gastric cancer immune escape identified from non-coding immune-landscape quantitative trait loci

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3′ untranslated region (3′-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3′-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3′-UTR eQTLs in immune-related genes. Our approach identifies numerous 3′-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer.

Assessment of TROP2, CEACAM5 and DLL3 in metastatic prostate cancer: Expression landscape and molecular correlates

Therapeutic approaches targeting proteins on the surface of cancer cells have emerged as an important strategy for precision oncology. To capitalize on the potential impact of drugs targeting surface proteins, detailed knowledge about the expression patterns of the target proteins in tumor tissues is required. In castration-resistant prostate cancer (CRPC), agents targeting prostate-specific membrane antigen (PSMA) have demonstrated clinical activity. However, PSMA expression is lost in a significant number of CRPC tumors. The identification of additional cell surface targets is necessary to develop new therapeutic approaches. Here, we performed a comprehensive analysis of the expression heterogeneity and co-expression patterns of trophoblast cell-surface antigen 2 (TROP2), delta-like ligand 3 (DLL3), and carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) in CRPC samples from a rapid autopsy cohort. We show that DLL3 and CEACAM5 exhibit the highest expression in neuroendocrine prostate cancer (NEPC), while TROP2 is expressed across different CRPC molecular subtypes, except for NEPC. We further demonstrated that AR alterations were associated with higher expression of PSMA and TROP2. Conversely, PSMA and TROP2 expression was lower in RB1-altered tumors. In addition to genomic alterations, we show a tight correlation between epigenetic states, particularly histone H3 lysine 27 methylation (H3K27me3) at the transcriptional start site and gene body of TACSTD2 (encoding TROP2), DLL3, and CEACAM5, and their respective protein expression in CRPC patient-derived xenografts. Collectively, these findings provide insights into patterns and determinants of expression of TROP2, DLL3, and CEACAM5 with implications for the clinical development of cell surface targeting agents in CRPC.

Transcriptomic analysis of N-terminal mutated Trypanosoma cruzi UBP1 knockdown underlines the importance of this RNA-binding protein in parasite development.

During its life cycle, the human pathogen Trypanosoma cruzi must quickly adapt to different environments, in which the variation in the gene expression of the regulatory U-rich RNA-binding protein 1 (TcUBP1) plays a crucial role. We have previously demonstrated that the overexpression of TcUBP1 in insect-dwelling epimastigotes orchestrates an RNA regulon to promote differentiation to infective forms. In an attempt to generate TcUBP1 knockout parasites by using CRISPR-Cas9 technology, in the present study, we obtained a variant transcript that encodes a protein with 95% overall identity and a modified N-terminal sequence. The expression of this mutant protein, named TcUBP1mut, was notably reduced compared to that of the endogenous form found in normal cells. TcUBP1mut-knockdown epimastigotes exhibited normal growth and differentiation into infective metacyclic trypomastigotes and were capable of infecting mammalian cells. We analyzed the RNA-Seq expression profiles of these parasites and identified 276 up- and 426 downregulated genes with respect to the wildtype control sample. RNA-Seq comparison across distinct developmental stages revealed that the transcriptomic profile of these TcUBP1mut-knockdown epimastigotes significantly differs not only from that of epimastigotes in the stationary phase but also from the gene expression landscape characteristic of infective forms. This is both contrary to and consistent with the results of our recent study involving TcUBP1-overexpressing cells. Together, our findings demonstrate that the genes exhibiting opposite changes under overexpression and knockdown conditions unveil key mRNA targets regulated by TcUBP1. These mostly encompass transcripts that encode for trypomastigote-specific surface glycoproteins and ribosomal proteins, supporting a role for TcUBP1 in determining the molecular characteristics of the infective stage.

Differential Epigenetic Regulation in Uninfected and Tuberculosis-Human Immunodeficiency Virus Co-Infected Patients.

This study aimed to compare the degree of epigenetic modifications between a TB-HIV co-infected cohort and uninfected subjects. Formalin-fixed paraffin-embedded (FFPE) tissues were retrieved from 45 TB-HIV co-infected and 45 control individuals. Real-time PCR was applied to compare the level of expression of genes involved in epigenetic regulation. The protein multiplex assay was used to assess the degree of protein modification. DNA sequencing was used to determine the evolutionary relationships between the infecting HIV and Mtb strains. Our results indicated a significant increase in the expression of the five candidate genes in the patients with TB-HIV relative to the control cohort. A sharp increase in the degree of histone methylation, acetylation and phosphorylation was observed in TB-HIV co-infected patients. The phylogenetic analysis classified the strains into three distinct HIV clusters and five Mtb clusters. The disparities in the expression profiles of our candidate genes between the TB-HIV cohort and non-TB-HIV group highlights the important role played by various TB and HIV strains in regulating the host gene expression landscape.

RNA isoform expression landscape of the human dorsal root ganglion generated from long-read sequencing.

Splicing is a posttranscriptional RNA processing mechanism that enhances genomic complexity by creating multiple isoforms from the same gene. We aimed to characterize the isoforms expressed in the human peripheral nervous system, with the goal of creating a resource to identify novel isoforms of functionally relevant genes associated with somatosensation and nociception. We used long-read sequencing to document isoform expression in the human dorsal root ganglia from 3 organ donors and validated in silico by confirming expression in short-read sequencing from 3 independent organ donors. Nineteen thousand five hundred forty-seven isoforms of protein-coding genes were detected and validated. We identified 763 isoforms with at least one previously undescribed splice junction. Previously unannotated isoforms of multiple pain-associated genes, including ASIC3 , MRGPRX1 , and HNRNPK , were identified. In the novel isoforms of ASIC3 , a region comprising approximately 35% of the 5'UTR was excised. By contrast, a novel splice junction was used in isoforms of MRGPRX1 to include an additional exon upstream of the start codon, consequently adding a region to the 5'UTR. Novel isoforms of HNRNPK were identified, which used previously unannotated splice sites to both excise exon 14 and include a sequence in the 3' end of exon 13. This novel insertion is predicted to introduce a tyrosine phosphorylation site potentially phosphorylated by SRC. We also independently confirm a recently reported DRG-specific splicing event in WNK1 that gives insight into how painless peripheral neuropathy occurs when this gene is mutated. Our findings give a clear overview of mRNA isoform diversity in the human dorsal root ganglia obtained using long-read sequencing.

Transcriptional Profiling Underscores the Role of Preprocurement Allograft Metabolism and Innate Immune Status on Outcomes in Human Liver Transplantation.

The adverse effects of ischemia-reperfusion injury (IRI) remain a principal barrier to a successful outcome after lifesaving orthotopic liver transplantation (OLT). Gene expression during different phases of IRI is dynamic and modified by individual exposures, making it attractive for identifying potential therapeutic targets for improving the number of suitable organs for transplantation and patient outcomes. However, data remain limited on the functional landscape of gene expression during liver graft IRI, spanning procurement to reperfusion and recovery. Therefore, we sought to characterize transcriptomic profiles of IRI during multiple phases in human OLT. We conducted clinical data analyses, histologic evaluation, and RNA sequencing of 17 consecutive human primary OLT. We performed liver allograft biopsies at 4 time points: baseline (B, before donor cross-clamp), at the end of cold ischemia (CI), during early reperfusion (ER, after revascularization), and during late reperfusion (LR). Data were generated and then recipients grouped by post-OLT outcomes categories: immediate allograft function (IAF; n = 11) versus early allograft dysfunction (EAD; n = 6) groups. We observed that CI (vs B) modified a transcriptomic landscape enriched for a metabolic and immune process. Expression levels of hallmark inflammatory response genes were higher transitioning from CI to ER and decreased from ER to LR. IAF group predominantly showed higher bile and fatty acid metabolism activity during LR compared with EAD group, while EAD group maintained more immunomodulatory activities. Throughout all time points, EAD specimens exhibited decreased metabolic activity in both bile and fatty acid pathways. We report transcriptomic profiles of human liver allograft IRI from prepreservation in the donor to posttransplantation in the recipient. Immunomodulatory and metabolic landscapes across ER and LR phases were different between IAF and EAD allografts. Our study also highlights marker genes for these biological processes that we plan to explore as novel therapeutic targets or surrogate markers for severe allograft injury in clinical OLT.

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections.

A crucial feature of life is its spatial organization and compartmentalization on the molecular, cellular, and tissue levels. Spatial transcriptomics (ST) technology has opened a new chapter of the sequencing revolution, emerging rapidly with transformative effects across biology. This technique produces extensive and complex sequencing data, raising the need for computational methods for their comprehensive analysis and interpretation. We developed the ST browser web tool for the interactive discovery of ST images, focusing on different functional aspects such as single gene expression, the expression of functional gene sets, as well as the inspection of the spatial patterns of cell-cell interactions. As a unique feature, our tool applies self-organizing map (SOM) machine learning to the ST data. Our SOM data portrayal method generates individual gene expression landscapes for each spot in the ST image, enabling its downstream analysis with high resolution. The performance of the spatial browser is demonstrated by disentangling the intra-tumoral heterogeneity of melanoma and the microarchitecture of the mouse brain. The integration of machine-learning-based SOM portrayal into an interactive ST analysis environment opens novel perspectives for the comprehensive knowledge mining of the organization and interactions of cellular ecosystems.

Expression of Anoikis-Related Genes and Potential Biomarkers in Colon Cancer Based on RNA-seq and scRNA-seq.

Colon cancer (CC) is a malignant tumor in the colon. Despite some progress in the early detection and treatment of CC in recent years, some patients still experience recurrence and metastasis. Therefore, it is urgent to better predict the prognosis of CC patients and identify new biomarkers. Recent studies have shown that anoikis-related genes (ARGs) play a significant role in the progression of many tumors. Hence, it is essential to confirm the role of ARGs in the development and treatment of CC by integrating scRNA-seq and transcriptome data. This study integrated transcriptome and single-cell sequencing (scRNA-seq) data from CC samples to evaluate patient stratification, prognosis, and ARG expression in different cell types. Specifically, differential expression of ARGs was identified through consensus clustering to classify CC subtypes. Subsequently, a CC risk model composed of CDKN2A, NOX4, INHBB, CRYAB, TWIST1, CD36, SERPINE1, and MMP3 was constructed using prognosis-related ARGs. Finally, using scRNA-seq data of CC, the expression landscape of prognostic genes in different cell types and the relationship between important immune cells and other cells were explored. Through the above analysis, two CC subtypes were identified, showing significant differences in prognosis and clinical factors. Subsequently, a risk model comprising aforementioned genes successfully categorized all CC samples into two risk groups, which also exhibited significant differences in prognosis, clinical factors, involved pathways, immune landscape, and drug sensitivity. Multiple pathways (cell adhesion molecules (CAMs), and extracellular matrix (ECM) receptor interaction) and immune cells/immune functions (B cell naive, dendritic cell activate, plasma cells, and T cells CD4 memory activated) related to CC were identified. Furthermore, it was found that prognostic genes were highly expressed in various immune cells, and B cells exhibited more and stronger interaction pathways with other cells. The results of this study may provide references for personalized treatment and potential biomarker identification in CC.

Abstract PO1-07-04: Multiomics analysis reveals the landscape of PD-L1 expression in triple-negative breast cancer

Abstract Background: Tumor-infiltrating lymphocytes (TILs) and programmed death ligand 1 (PD-L1) remain controversial in predicting clinical outcomes of triple-negative breast cancer (TNBC), as outcomes do not always correlate with the expression of these biomarkers. Genomic and transcriptomic alterations that might contribute to the expression of these biomarkers remain incompletely uncovered. Methods: We evaluated PD-L1 immunohistochemistry (IHC) scores (SP142 and 28-8) and TILs in our TNBC multiomics dataset and two immunotherapy clinical trial cohorts. Then, we analyzed genomic and transcriptomic alterations correlated with TILs, PD-L1 expression and patient outcomes. Results: Despite TILs serving as a decent predictor for TNBC clinical outcomes, there remained exceptions. Our study revealed that several genomic alterations were correlated with unexpected events. Particularly, PD-L1 expression may cause a paradoxical relationship between TILs and prognosis in certain patients. Consequently, we classified TNBCs into four groups based on PD-L1 and TIL levels. The TIL-PD-L1+ and TIL+PD-L1- groups were not typical “hot” tumors; both were associated with worse prognoses and lower immunotherapy efficacy than TIL+PD-L1+ tumors. Copy number variation of PD-L1 and oncogenic signaling activation were correlated with PD-L1 expression in the TIL-PD-L1+ group, whereas GSK3B-induced degradation might cause undetectable PD-L1 expression in the TIL+PD-L1- group. These factors have the potential to affect the predictive function of both PD-L1 and TILs. Conclusions: Several genomic and transcriptomic alterations may cause paradoxical effects among TILs, PD-L1 expression and prognosis in TNBC. Investigating and targeting these factors will advance precision immunotherapy for TNBC patients. Keywords: Triple-negative breast cancer, PD-L1 expression, Tumor-infiltrating lymphocytes, Multiomics, Immunotherapy Citation Format: Han Wang, Xiao-Hong Ding, Cheng-Lin Liu, Yi Xiao, Ruo-Hong Shui, Yan-Ping Li, Chen Chen, Wen-Tao Yang, Zhi-Ming Shao, Yi-Zhou Jiang. Multiomics analysis reveals the landscape of PD-L1 expression in triple-negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-04.

Abstract PO5-16-07: Unveiling the Landscape of PD-L1 Expression and Tumor-Infiltrating Lymphocyte Subtypes in Advanced Triple-Negative Breast Cancer

Abstract Background: Triple-negative breast cancer (TNBC) is known for its aggressive behavior with poor survival outcomes. Influenced by different expression levels of Programmed Death-Ligand 1 (PD-L1) and several subtypes of tumor-infiltrating lymphocytes (TILs), tumor microenvironment (TME) plays a crucial role in TNBC response to treatment and progression. Objective: To assess the prevalence and prognostic role of PD-L1 expression in advanced TNBC, defined as unresectable stage III or stage IV disease, in patients treated with a standard cytotoxic chemotherapy regimen. TILs composition was also evaluated as an exploratory objective. Methods: The internal database of the Brazilian National Cancer Institute was queried out for women diagnosed and treated with advanced TNBC from January 2018 to December 2022. Formalin-fixed paraffin-embedded samples of a maximum of four years old were analyzed. PD-L1 expression using 22C3 pharmDX assay was estimated through combined positive score (CPS) dichotomization (CPS < 10 vs. CPS≥10). Tissue microarrays comprising the samples of biopsies were subjected to immunohistochemistry, targeting specific markers including CD3, CD4, CD8, CD56, CD68, CD117, FOXP3, PD-1, the immune cell profiles were carefully examined and their correlation with the PD-L1 CPS was determined. Results: A total of 150 patients were included. The expression of PD-L1 was undetermined in 2 cases. The median age was 51.5 years (IQR 41.8-60.2) and 20.9% of the cases had CPS≥10. Most patients were < 65 years (73.0%), were postmenopausal (56.8%) and belonged to non-white ethnicity (70.3%). Postmenopausal women predominated in the CPS≥10 subgroup (74.2%) (Table 1). No significant differences in demographic characteristics and clinicopathological variables were observed based on PD-L1 subgroups, 117 patients (79.1%) had CPS < 10, with 91 (77.8%) being de novo stage IV metastatic disease. CD3+ (p=0.037), CD4+ (p=0.005) and CD8+ (p=0.001) TILs had higher expression in tumors with PD-L1 CPS≥10 (Table 2). According to the treatment received, almost half of the patients only received first-line chemotherapy (47%), as the following second line was applied to 28.8% of the total group. The third and fourth lines were administered in 12.9% and 9.1% of patients, respectively. Only 2 patients went through five palliative chemotherapy lines, and only one received up to 6 treatment lines. Between the subgroups CPS≥10 versus CPS < 10 no statistically significant differences were observed in the median progression-free survival (PFS) (5.1 vs. 5.0 months, p=0.89) and overall survival (OS) (8.7 vs. 8.8 months, p=0.6). Conclusion: This study offers insights into the expression patterns of PD-L1 and TILs subtypes in advanced TNBC cases in Brazil. PD-L1 CPS did not influence survival outcomes for this cohort of patients treated with cytotoxic chemotherapy only. The composition of TILs subtypes within the TME appears to vary based on PD-L1 CPS. Table 1. Advanced TNBC population characteristic by CPS (Nf148). Table 2. Tumor Infiltrating Lymphocytes characterization (CD3, CD4, CD8, CD56, CD68, CD 117, FOXP3 and PD-1) and its correlation with CPS status. Citation Format: Alexssandra Lima Siqueira dos Santos, Jesse Lopes da Silva, Lucas Zanetti de Albuquerque, Antônio Lucas Araújo Neto, Cecília Ferreira da Silva, Luana Aguiar Mesquita Cerva, Isabele Ávila Small, Cicera Pimenta Marcelino, Paula de Mendonça Batista, Maria Aparecida do Carmo Rego, Maria Amélia Carlos Souto Maior Borba, Andreia Cristina de Melo. Unveiling the Landscape of PD-L1 Expression and Tumor-Infiltrating Lymphocyte Subtypes in Advanced Triple-Negative Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-16-07.

Impacts of in-vitro zebularine treatment on genome-wide DNA methylation and transcriptomic profiles in Salix purpurea L.

Renewable energy resources such as biomass are crucial for a sustainable global society. Trees are a major source of lignocellulosic biomass, which can vary in response to different environmental factors owing to epigenetic regulation, such as DNA C-methylation. To investigate the effects of DNA methylation on plant development and wood formation, and its impacts on gene expression, with a focus on secondary cell wall (SCW)-associated genes, Salix purpurea plantlets were cloned from buds derived from a single hybrid tree for both treatment and control conditions. For the treatment condition, buds were exposed to 50 μM zebularine in vitro and a combined strategy of whole-genome bisulfite sequencing (WGBS) and RNA-seq was employed to examine the methylome and transcriptome profiles of different tissues collected at various time points under both conditions. Transcriptomic and methylome data revealed that most of the promoter and gene body demethylation had no marked effects on the expression profiles of genes. Nevertheless, gene expression tended to decrease with the increased methylation levels of genes with highly methylated promoters. Results indicated that demethylation is less evident in centromeric regions and sex chromosomes. Promoters of secondary cell wall-associated genes, such as 4-coumarate-CoA ligase-like and Rac-like GTP-binding protein RHO, were differentially methylated in the secondary xylem samples collected from two-month potted treated plants compared to control samples. Our results provide novel insights into DNA methylation and gene expression landscapes and a basis for investigating the epigenetic regulation of wood formation in S. purpurea as a model plant for bioenergy species.

Optimizing Color Matching and Color Effects in Oil Painting Using Computer Vision Technology

The fusion of traditional oil painting techniques with computer vision technology presents an exciting frontier in the realm of artistic expression. This paper explores the intersection of these disciplines, focusing specifically on optimizing color matching and manipulating color effects in oil painting through computational means. By leveraging algorithms and image processing techniques, artists can enhance their creative process, enabling precise color measurement, nuanced color analysis, and predictive modelling of color combinations' visual impact. Through a comprehensive review of relevant literature, case studies, and practical applications, this paper elucidates the methodologies and advancements driving this convergence. Furthermore, it examines the implications of integrating computer vision into oil painting, offering insights into its transformative potential for artistic practice and aesthetic outcomes. By fostering a deeper understanding of this interdisciplinary intersection, this paper aims to inspire further exploration and innovation at the nexus of art and technology, ultimately enriching the landscape of contemporary artistic expression.