Bulk RNA-seq Data Research Articles

Integrated Analysis Construct a Tumor-Associated Macrophage Novel Signature with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Gastric Cancer Patients.

Gastric cancer (GC) remains one of the most prevalent malignant tumors worldwide. At present, tumor-associated macrophages (TAMs) are essential in the progression, metastasis, and drug resistance of tumors. Therefore, TAMs can be a crucial target for tumor treatment. We intended to investigate the TAM characteristics in GC and develop a risk signature based on TAM to predict the prognosis of GC patients. The single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data were acquired from a publicly available database. We utilized the Seurat pipeline to process the scRNA-seq data and determine TAM cell types using marker genes. Univariate Cox regression analysis was utilized to examine TAM-related prognostic genes, and then we employed Lasso-Cox regression analysis, and Multivariate Cox regression analysis established a novel risk profile to forecast the clinical value of the model with a new nomogram combining risk profiles and clinicopathological characteristics. The current study employed scRNA-seq data to identify five TAM clusters in GC, among which four were significantly associated with GC prognosis. Accordingly, we further developed a TAM-related risk signature utilizing nine genes. After evaluation, our model accurately predicted the prognosis of gastric cancer. Generally, GC patients with low TAMS scores exhibited a more favorable prognosis, greater benefits from immunotherapy, and higher levels of immune cell infiltration. The prognosis of GC can be effectively predicted by TAM-based risk signatures, and the signature may provide a new perspective for comprehensively guiding clinical diagnosis, prediction, and immunotherapy for gastric cancer.

Pan-Cancer Single-Cell and Spatial-Resolved Profiling Reveals the Immunosuppressive Role of APOE+ Macrophages in Immune Checkpoint Inhibitor Therapy.

The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single-cell RNA sequencing (scRNA-seq) and machine learning methods. The scRNA-seq and bulk RNA-seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single-cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan-cancer patients. The proportion of APOE+ macrophages is higher in ICI non-responders of triple-negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor-bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real-world immunotherapy data accurately predicts the ICI response of pan-cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

Targeting nucleotide metabolic pathways in colorectal cancer by integrating scRNA-seq, spatial transcriptome, and bulk RNA-seq data

BackgroundColorectal cancer is a malignant tumor of the digestive system originating from abnormal cell proliferation in the colon or rectum, often leading to gastrointestinal symptoms and severe health issues. Nucleotide metabolism, which encompasses the synthesis of DNA and RNA, is a pivotal cellular biochemical process that significantly impacts both the progression and therapeutic strategies of colorectal cancerMethodsFor single-cell RNA sequencing (scRNA-seq), five functions were employed to calculate scores related to nucleotide metabolism. Cell developmental trajectory analysis and intercellular interaction analysis were utilized to explore the metabolic characteristics and communication patterns of different epithelial cells. These findings were further validated using spatial transcriptome RNA sequencing (stRNA-seq). A risk model was constructed using expression profile data from TCGA and GEO cohorts to optimize clinical decision-making. Key nucleotide metabolism-related genes (NMRGs) were functionally validated by further in vitro experiments.ResultsIn both scRNA-seq and stRNA-seq, colorectal cancer (CRC) exhibited unique cellular heterogeneity, with myeloid cells and epithelial cells in tumor samples displaying higher nucleotide metabolism scores. Analysis of intercellular communication revealed enhanced signaling pathways and ligand-receptor interactions between epithelial cells with high nucleotide metabolism and fibroblasts. Spatial transcriptome sequencing confirmed elevated nucleotide metabolism states in the core region of tumor tissue. After identifying differentially expressed NMRGs in epithelial cells, a risk prognostic model based on four genes effectively predicted overall survival and immunotherapy outcomes in patients. High-risk group patients exhibited an immunosuppressive microenvironment and relatively poorer prognosis and responses to chemotherapy and immunotherapy. Finally, based on data analysis and a series of cellular functional experiments, ACOX1 and CPT2 were identified as novel therapeutic targets for CRC.ConclusionIn this study, a comprehensive analysis of NMRGs in CRC was conducted using a combination of single-cell sequencing, spatial transcriptome sequencing, and high-throughput data. The prognostic model constructed with NMRGs shows potential as a standalone prognostic marker for colorectal cancer patients and may significantly influence the development of personalized treatment approaches for CRC.

Multi-Omics Profiling Reveals Phenotypic and Functional Heterogeneity of Neutrophils in COVID-19.

Accumulating evidence has revealed unexpected phenotypic heterogeneity and diverse functions of neutrophils in several diseases. Coronavirus disease (COVID-19) can alter the leukocyte phenotype based on disease severity, including neutrophil activation in severe cases. However, the plasticity of neutrophil phenotypes and their relative impact on COVID-19 pathogenesis has not been well addressed. This study aimed to identify and validate the heterogeneity of neutrophils in COVID-19 and evaluate the functions of each subpopulation. We analyzed public single-cell RNA-seq, bulk RNA-seq, and proteome data from healthy donors and patients with COVID-19 to investigate neutrophil subpopulations and their response to disease pathogenesis. We identified eight neutrophil subtypes: pro-neutrophil, pre-neutrophil, immature neutrophil, and five mature neutrophil subpopulations. The subtypes exhibited distinct features, including diverse activation signatures and multiple enriched pathways. The pro-neutrophil subtype was associated with severe and fatal disease, while the pre-neutrophil subtype was particularly abundant in mild/moderate disease. One of the mature neutrophil subtypes showed consistently large fractions in patients with different disease severity. Bulk RNA-seq dataset analyses using a cellular deconvolution approach validated the relative abundances of neutrophil subtypes and the expansion of pro-neutrophils in severe COVID-19 patients. Cell-cell communication analysis revealed representative ligand-receptor interactions among the identified neutrophil subtypes. Further investigation into transcription factors and differential protein abundance revealed the regulatory network differences between healthy donors and patients with severe COVID-19. Overall, we demonstrated the complex interactions among heterogeneous neutrophil subtypes and other blood cell types during COVID-19 disease. Our work has great value in terms of both clinical and public health as it furthers our understanding of the phenotypic and functional heterogeneity of neutrophils and other cell populations in multiple diseases.

ScINRB: single-cell gene expression imputation with network regularization and bulk RNA-seq data.

Single-cell RNA sequencing (scRNA-seq) facilitates the study of cell type heterogeneity and the construction of cell atlas. However, due to its limitations, many genes may be detected to have zero expressions, i.e. dropout events, leading to bias in downstream analyses and hindering the identification and characterization of cell types and cell functions. Although many imputation methods have been developed, their performances are generally lower than expected across different kinds and dimensions of data and application scenarios. Therefore, developing an accurate and robust single-cell gene expression data imputation method is still essential. Considering to maintain the original cell-cell and gene-gene correlations and leverage bulk RNA sequencing (bulk RNA-seq) data information, we propose scINRB, a single-cell gene expression imputation method with network regularization and bulk RNA-seq data. scINRB adopts network-regularized non-negative matrix factorization to ensure that the imputed data maintains the cell-cell and gene-gene similarities and also approaches the gene average expression calculated from bulk RNA-seq data. To evaluate the performance, we test scINRB on simulated and experimental datasets and compare it with other commonly used imputation methods. The results show that scINRB recovers gene expression accurately even in the case of high dropout rates and dimensions, preserves cell-cell and gene-gene similarities and improves various downstream analyses including visualization, clustering and trajectory inference.

Integration of Single-Cell and Bulk RNA-seq Data to Identify the Cancer-Associated Fibroblast Subtypes and Risk Model in Glioma.

Cancer-associated fibroblasts (CAFs) are an important component of the stroma. Studies showed that CAFs were pivotally in glioma progression which have long been considered a promising therapeutic target. Therefore, the identification of prognostic CAF markers might facilitate the development of novel diagnostic and therapeutic approaches. A total of 1333 glioma samples were obtained from the TCGA and CGGA datasets. The EPIC, MCP-counter, and xCell algorithms were used to evaluate the relative proportion of CAFs in glioma. CAF markers were identified by the single-cell RNA-seq datasets (GSE141383) from the Tumor Immune Single-Cell Hub database. Unsupervised consensus clustering was used to divide the glioma patients into different distinct subgroups. The least absolute shrinkage and selection operator regression model was utilized to establish a CAF-related signature (CRS). Finally, the prognostic CAF markers were further validated in clinical specimens by RT‒qPCR. Combined single-cell RNA-seq analysis and differential expression analysis of samples with high and low proportions of CAFs revealed 23 prognostic CAF markers. By using unsupervised consensus clustering, glioma patients were divided into two distinct subtypes. Subsequently, based on 18 differentially expressed prognostic CAF markers between the two CAF subtypes, we developed and validated a new CRS model (including PCOLCE, TIMP1, and CLIC1). The nomogram and calibration curves indicated that the CRS was an accurate prognostic marker for glioma. In addition, patients in the high-CRS score group had higher immune infiltration and tumor mutation burden levels. Moreover, the CRS score had the potential to predict the response to immune checkpoint blockade (ICB) therapy and chemotherapy. Finally, the expression profiles of three CAF markers were verified by RT‒qPCR. In general, our study classified glioma patients into distinct subgroups based on CAF markers, which will facilitate the development of individualized therapy. We also provided insights into the role of the CRS in predicting the response to ICB and chemotherapy in glioma patients.

Deconvolution of synovial myeloid cell subsets across pathotypes and role of COL3A1+ macrophages in rheumatoid arthritis remission.

Monocyte/macrophage (Mo/Mp) is a critical cell population involved in immune modulation of rheumatoid synovitis (RA) across different pathotypes. This study aims to investigate the contribution of Mo/Mp clusters to RA activity, and the biological function of particular subtypes in RA remission. We integrated single-cell RNA sequencing datasets from 4 published and 1 in-house studies using Liger selected by comparison. We estimated the abundance of Mo/Mp subtypes in bulk RNA-seq data from the 81 patients of the Pathobiology of Early Arthritis Cohort (PEAC) using deconvolution analysis. Correlations between Mo/Mp subtypes and RA clinical metrics were assessed. A particular cell type was identified using multicolor immunofluorescence and flow cytometry in vivo and successfully induced from a cell line in vitro. Potential immune modulation function of it was performed using immunohistochemical staining, adhesion assay, and RT-qPCR. We identified 8 Mo/Mp clusters. As a particular subtype among them, COL3A1+ Mp (CD68+, COL3A1+, ACTA2-) enriched in myeloid pathotype and negatively correlated with RA severity metrics in all pathotypes. Flow cytometry and multicolor immunofluorescence evidenced the enrichment and M2-like phenotype of COL3A1+ Mp in the myeloid pathotype. Further assays suggested that COL3A1+ Mp potentially attenuates RA severity via expressing anti-inflammatory cytokines, enhancing Mp adhesion, and forming a physical barrier at the synovial lining. This study reported unexplored associations between different pathologies and myeloid cell subtypes. We also identified a fibroblast-and-M2-like cluster named COL3A1+ Mp, which potentially contributes to synovial immune homeostasis. Targeting the development of COL3A1+ Mp may hold promise for inducing RA remission.

SFXN1-mediated immune cell infiltration and tumorigenesis in lung adenocarcinoma: A potential therapeutic target

BackgroundSideroflexin 1 (SFXN1), a mitochondrial serine transporter implicated in one-carbon metabolism, is a prognostic biomarker in lung adenocarcinoma (LUAD). However, its role in LUAD progression remains elusive. This study aimed to investigate the functional significance of SFXN1 in LUAD and evaluate its potential as a therapeutic target. MethodsWe analyzed SFXN1 expression and its diagnostic and prognostic value in LUAD using the Pan-cancer TCGA dataset. In vitro assays (CCK-8, cell cycle, EDU, wound-healing, and transwell) were employed to assess the role of SFXN1, complemented by in vivo experiments. RNA sequencing elucidated SFXN1-mediated cellular functions and potential mechanisms. Bulk RNA-seq and scRNA-seq data from TCGA and GEO were used to investigate the correlation between SFXN1 and the tumor immune microenvironment. RT-qPCR, Western blot, and IHC assays validated SFXN1 expression and its impact on the immune microenvironment in LUAD. ResultsSFXN1 was upregulated in LUAD tissues and associated with poor prognosis. RNA-seq and scRNA-seq analyses revealed increased SFXN1 expression in tumor cells, accompanied by decreased infiltration of NK and cytotoxic T cells. SFXN1 knockdown significantly reduced cell proliferation and migration, and the inhibition of ERK phosphorylation and CCL20 expression may be the molecular mechanism involved. In vivo, targeting SFXN1 decreased Tregs infiltration and inhibited tumor growth. ConclusionsOur findings suggest that SFXN1 may be a potential therapeutic target for LUAD treatment.

Histone modification-linked prognostic model for ovarian cancer reveals LBX2 as a novel growth promoter.

Ovarian cancer (OC) is a deadly disease with limited treatment options and poor overall survival rates. This study aimed to investigate the role of histone modification-related genes in predicting the prognosis of OC patients. Transcriptome data from multiple cohorts, including bulk RNA-Seq data and single-cell scRNA-Seq data, were collected. Gene set enrichment analysis was used to identify enriched gene sets in the histone modification pathway. Differentially expressed genes (DEGs) between histone modification-high and histone modification-low groups were identified using Lasso regression. A prognostic model was constructed using five selected prognostic genes from the DEGs in the TCGA-OV cohort. The study found enrichment of gene sets in the histone modification pathway and identified five prognostic genes associated with OC prognosis. The constructed risk score model based on histone modification-related genes was correlated with immune infiltration of T cells and M1 macrophages. Mutations are more prevalent in the high-risk group compared to the low-risk group. Several drugs were screened against the model genes. Through invitro experiments, we confirmed the expression patterns of the model genes. LBX2 facilitates the proliferation of OC. Histone modification-related genes have the potential to serve as biomarkers for predicting OC prognosis. Targeting these genes may lead to the development of more effective therapies for OC. Additionally, LBX2 represents a novel cell proliferation promoter in OC carcinogenesis.

Abstract 5459: Inflammatory gene-based subtyping of osteosarcoma patients reveals the association of inflammation in tumor microenvironment with better survival

Abstract Introduction:Inflammation has a significant impact on the tumor microenvironment (TME) of osteosarcoma (OS). Nevertheless, due to the high heterogenecity and variable inflammatory characteristics among OS patients, it is still unclear which inflammatory factors or immune/stroma cell types are crucially associated with OS prognosis. Therefore, it is essential to explore the immune infiltration pattern and the related core inflammatory genes in OS. Method:We combined bulk RNA-seq data of 88 osteosarcoma (OS) patients from the TARGET database and single cell RNA-seq data in GSE152048 from the NCBI Gene Expression Omnibus. Firstly, we calculated the inflammatory gene expression matrix of bulk RNA-seq data by combining 80 inflammatory gene sets (3427 genes in total) from the MSigDB using the gene set variation analysis (GSVA). Secondly, consensus clustering was executed to evaluate the stability of clustering for the above matrix. Furthermore, the overall survival and differential expression analyses were used to screen for core inflammatory genes. Immune infiltration patterns among groups were profiled with CIBERSORT. Finally, we employed the scRNA-seq series to evaluate cell-level information to identify the survival-associated cell subpopulations using the Seurat package. The t-SNE was used for dimensionality reduction and cluster identification. Results:88 osteosarcoma (OS) patients were clustered into two distinct groups according to the consensus clustering of our formed GSVA inflammatory gene expression matrix. Group 1 (43 patients) exhibited evident inflammation features, while Group 2 (45 patients) displayed limited inflammation features. Patients from Group 1 had significantly better overall survival than those from Group 2. The difference in immune infiltration pattern of two groups were examined using bulk RNA-seq data. Group 1 showed a higher population of macrophages and CD8+ T cells compared to Group 2, implying high inflammatory features might lead to a better immune activation of TME in patients. To explore the factors and cell types that contributes to restricted immune infiltration and activation in OS TME, scRNA-seq data of 11 OS patient tissues were analyzed. Consistently with bulk RNA seq analysis, the 338 up-regulated genes from Group 1 were mainly expressed in immune cells including macrophages and myeloid cells. Interestingly, the 64 up-regulated genes from Group 2 were found nearly uniformly expressed in two type of non-immune cells: myoblasts and chondroblastic cells. Conclusion:Inflammatory gene-based subtyping of osteosarcoma (OS) patients reveals that the inflammation in TME led by myeloid-derived immune cells including macrophage is associated with better prognosis. Furthermore, myoblasts and chondroblastic cells might contribute to the limited inflammation response in OS TME. Citation Format: Liu Yang, Yalan Sheng, Shuangying Qiao, Desheng Hu, Debajyoti Chowdhury, Hiu Fung Yip, Zheng Chen, Yun He, Aiping Lu, Fangfei Li. Inflammatory gene-based subtyping of osteosarcoma patients reveals the association of inflammation in tumor microenvironment with better survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5459.

Abstract 6134: The Latino Colorectal Cancer Consortium: A resource for colorectal cancer disparities research

Abstract Purpose: The Latino Colorectal Cancer Consortium (LC3) was established to fill a gap in representation of the diverse Hispanic/Latino/a/x community in cancer genomic research and to enhance understanding of determinants of disparities in the burden of colorectal cancer (CRC). Methods: The LC3 joins together three established studies with deeply-annotated clinical, epidemiologic, and biologic data available for a heterogenous group of Hispanic/Latino/a/x men and women diagnosed with primary colorectal adenocarcinoma: the Hispanic Colorectal Cancer Study (California), the Total Cancer Care Protocol at Moffitt Cancer Center (Florida), and the Puerto Rico Biobank (southern Puerto Rico). Each contributing study collected data on demographics, medical history, family history, and lifestyle factors. Vital status, cause of death, treatment, and clinical characteristics were obtained through medical chart abstraction and/or linkage to cancer registries. Blood, saliva, or normal colonic tissues were used to extract and genotype germline DNA for a subset of participants. Tumor tissues (snap frozen or formalin-fixed paraffin-embedded) were evaluated by pathologists for diagnosis, tissue content, tumor cellularity, necrosis, immune infiltration, and additional histopathologic characteristics. Results: The LC3 has assembled 2,041 participants across the three studies to date, with recruitment ongoing. Median age at diagnosis is 57 (range: 19-93), 54% of participants are male, and 63% are colon cancer cases (vs. rectal cancer). Participants were diagnosed between 1999 and 2022. The target is to generate comprehensive multi-omic data on 600 LC3 participants. To date, 243 have genome-wide germline genotyping, 323 have paired tumor/normal whole exome sequencing, and 257 have T cell receptor immunosequencing (immunoSEQ, Adaptive Biotechnologies). Further, 206 cases are represented on a set of tissue microarray blocks (target N=281). Bulk RNA-seq data are to be generated on 250 tumors. Conclusions: The LC3 fills an important gap in research infrastructure for the scientific community. Key strengths of this unique consortium are its ability to capture a diversity of Latino CRC patients with respect to nativity and cultural heritage and to represent the spectrum of stages from early to metastatic. Ultimately, research from the LC3 will inform development of equitable precision medicine approaches and predictive models to improve the health of the rapidly-growing, heterogeneous Hispanic/Latino/a population. Citation Format: Nicole C. Loroña, Marco Matejcic, Daniel Sobieski, Nathalie T. Nguyen, Hannah J. Hoehn, Diana B. Diaz, Kritika Shankar, Esther Jean-Baptiste, Domenico Coppola, Clifton Fulmer, Ozlen Saglam, Kun Jiang, Teresita Muñoz-Antonia, Idhaliz Flores, Edna Gordian, José A. Oliveras Torres, Seth I. Felder, Julian A. Sanchez, Jason Fleming, Erin M. Siegel, Douglas Cress, Mariana C. Stern, Jamie K. Teer, Stephanie L. Schmit, Jane C. Figueiredo. The Latino Colorectal Cancer Consortium: A resource for colorectal cancer disparities research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6134.

Abstract 4946: ssTimiGP: Equip the TimiGP system with a single-sample module, facilitating the cell-cell interaction inference of the tumor microenvironment in any sample

Abstract Understanding the tumor microenvironment (TME) is essential in cancer treatment and risk assessment. While single-cell RNA-seq (scRNA-seq) offers in-depth insights into the TME, its expensive cost results in limited data sets and size. In contrast, microarray and RNA-seq provide rich datasets from larger cohorts, but they yield bulk data with lower resolution. To leverage the strengths of both approaches and comprehensively study the TME, we developed the computational framework TimiGP (Tumor Immune Microenvironment Illustration through Gene Pairs). It is inspired by the dynamic balance of the immune system and extended to the entire TME. TimiGP utilizes scRNA-seq to define cell type of interest, and bulk transcriptomic profiles to deduce clinically relevant cell-cell interaction networks and cell functions. Our recent release includes both prognosis and response modules to study the association between TME and the corresponding clinical outcomes. However, their applicability is constrained by the necessity for paired clinical information. In response to this limitation, we present a significant enhancement, a single sample module slightly modified from the TimiGP framework (ssTimiGP). This upgraded version enables TME analysis in any individual sample, requiring only bulk RNA-seq data and cell-type markers. It exports a cell-cell interaction network representing the relative expression of functional markers and the abundance of cells. This optimization expands the utility of TimiGP, making it more accessible across diverse samples and species. We have further expanded the application of ssTimiGP from solid tumors to liquid samples (e.g., peripheral blood). To validate its performance, we conducted a comparative analysis between the interactions of eight immune cell types observed in experimental results using FACS and the computational results derived from ssTimiGP based on paired RNA-seq data. As a result, ssTimiGP not only successfully identified interactions between different cell types that exhibited a significant correlation with experimental findings (e.g., CD4+ naïve T cells → Monocyte, R=0.75, p< 0.001, accuracy = 0.8), but also demonstrated its capability to achieve higher resolution in capturing interactions between immune cell subpopulations (e.g., CD4 naïve T cells → activated CD4+ memory T cells, R=0.57, p=0.008, accuracy = 1.0). In our benchmark analysis, ssTimiGP demonstrated superior performance compared to CIBERSORTx (e.g., CD4+ naïve T cells → Monocyte, R=0, Accuracy=0.3). In summary, ssTimiGP signifies an expansion of the TimiGP system, enabling the inference of the TME in individual solid tumors and liquid samples at various resolutions by integrating the strengths of both scRNA-seq and bulk RNA-seq. This approach offers substantial potential for advancing personalized cancer treatment. Citation Format: Chenyang Li, Jianjun Zhang, Chao Cheng. ssTimiGP: Equip the TimiGP system with a single-sample module, facilitating the cell-cell interaction inference of the tumor microenvironment in any sample [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4946.

Abstract 6222: Exposing the heterogeneity of the lipidome in the TME of cutaneous melanoma following treatment with NUC-7738 in combination with anti-PD-1 therapy

Abstract Background. Malignant melanoma exhibits distinct lipid profiles compared to normal tissue and changes in the lipidome influence multiple aspects of tumor biology. Lipidomic alterations within the tumor microenvironment (TME) may influence the efficacy of anti-PD-1 therapy. In combination with anti-PD-1 agent pembrolizumab, NUC-7738 (3'-deoxyadenosine [3’-dA] which is phosphorylated and protected with a phosphoramidate moiety attached at the 5’-position) has shown promising activity in anti-PD-1 refractory melanoma (Phase 2; NCT03829254). NUC-7738 generates sustained intracellular levels of 3’-dATP, which profoundly alters RNA regulatory processes in tumor cells, resulting in impaired cellular responses and changes in expression of proteins related to lipid biosynthesis. To interrogate components of the TME before and after NUC-7738 + pembrolizumab treatment, we developed a novel workflow incorporating Mass Spectrometry Imaging (MSI) to co-register lipidomic changes with molecular markers. Machine learning accelerated the interpretation of complex data obtained from paired patient biopsies. Methods. Snap frozen paired biopsies from patients with advanced cutaneous melanoma treated with NUC-7738 ±pembrolizumab were analyzed by desorption electrospray ionization (DESI)-MSI. Specific metabolic (e.g., ASAH1) and immune (e.g., CD8, CD20) markers were investigated by multiplex immunofluorescence (mIF) post DESI-MSI. Target selection was guided by bulk RNA-seq data. Raw MSI data was visualized using Waters HDI® software. Data extracted from selected regions of interest was exported into MetaboAnalyst 5.0 for statistical analysis. LIPID MAPS® Structure Database was used to assign lipid species. mIF/mIHC images were analyzed by HALO® AI. Results. Single 10 µm tissue sections allowed co-registered DESI-MSI and mIF, suitable for further informatic and AI-enabled image analysis. This facilitated direct comparison of lipids, cells, and protein expression in the TME, before and after treatment with NUC-7738, a compound known to cause profound changes in poly(A) tail regulation. MSI data analyses of the TME uncovered intra-tumoral heterogeneity of the lipidome and demonstrated changes following treatment. Conclusion. This platform provides a powerful investigative tool to simultaneously explore the myriad of factors in the TME that contribute to tumorigenesis and therapeutic response. Further analyses of the role of the lipidome in the TME and intra-tumoral heterogeneity will be explored in paired biopsies from patients with PD-1 inhibitor refractory melanoma. Citation Format: Alison L. Dickson, Greice M. Zickuhr, In Hwa Um, Ying Zhang, Ruth Plummer, Sarah P. Blagden, Stefan N. Symeonides, Natalie Cook, T.R. Jeffry Evans, Mustafa Elshani, David J. Harrison. Exposing the heterogeneity of the lipidome in the TME of cutaneous melanoma following treatment with NUC-7738 in combination with anti-PD-1 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6222.

Abstract 3607: Case study: Efficacy and persistence of autologous T cell therapy targeting SLC45A2 in uveal melanoma

Abstract Background: Metastatic uveal melanoma (UM) is an aggressive cancer, with a 1-year overall survival of < 50%. While the bispecific T-cell engager tabentafusp is approved for HLA-A2+ patients with gp100+ UM, there are limited treatment options for patients who do not express HLA-A2. We present a strategy and proof-of-concept for designing and manufacturing a tumor-selective endogenous T-cell therapy (ETC) for a patient with metastatic UM. Methods: PBMC were collected by apheresis in 2013 upon first diagnosis with uveal melanoma; 8 years later, following progression, cryopreserved PBMC were used to generate autologous antigen-specific T cells for adoptive therapy. The validated tumor antigen SLC45A2 was found to be overexpressed in the patient’s metastatic tumor based on RNA expression profiling. Peripheral blood derived SLC45A2-specific HLA-A2402-restricted central memory CD8+ T cells were generated via a process of in vitro priming, IL-21 treatment, tetramer-guided sorting and cell expansion. Clinical response was assessed via longitudinal CT imaging and ctDNA-based MRD monitoring. Persistence of transferred T cells was measured via serial flow cytometry and RNA-sequencing of PBMCs, along with TCR and RNA sequencing of tumor tissue collected post infusion. Results: A 39 year old male received SLC45A2-specific ETC therapy and checkpoint inhibitor treatment for advanced metastatic UM (GNAQ (Q209P), BAP1 (E398*, LOF). Bulk RNAseq data from baseline biopsies were queried for known tumor-associated antigens, and SLC45A2 was expressed at high levels. The patient experienced widespread disease stabilization with minimal toxicity. SLC45A2-specific CD8+ T cells persisted in circulation up to 181 days after the first infusion and 43 days after the second infusion, ranging from 6.7% - 1.5% of total circulating CD3 T cells. T cell clones from the infusion product included the dominating TCR subclone in tumor tissue collected 6 weeks post infusion, comprising 33% of the TCRá and 26% of TCRâ population. SLC45A2-specific T cells were identified in the tumor infiltrating lymphocytes in a separate lesion collected 10 months after the first infusion. A duodenum lesion progressed during treatment, and RNAseq demonstrated reduced expression of genes associated with HLA presentation and SLC45A2 and reduced TIL infiltration, suggesting tissue-specific immune editing of the tumor cell population. Conclusions: 1. Tumor-reactive antigen-specific T cells can be isolated and expanded for adoptive therapy using PBMCs cryopreserved for > 8 years. 2. Following infusion, peripheral blood and tumor profiling support the persistence of transferred T cells in a patient with metastatic uveal melanoma. 3. Disease stabilization in aggressive metastatic UM was achieved with minimal toxicity. Overall, our study provides evidence and rationale for utilizing autologous antigen-specific T cells for treating rare cancers. Citation Format: Shailbala Singh, Esther Ryu, Katie M. Campbell, Amber Smith, Suzanne Phillips, Luisa Soto, Ivy Lai, Gregory Lizee, Benjamin Vincent, Marshall Thompson, William Hoos, Sapna Patel, Cassian Yee. Case study: Efficacy and persistence of autologous T cell therapy targeting SLC45A2 in uveal melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3607.

Abstract 6213: Determination of permissive and restraining cancer-associated fibroblast (DeCAF) subtypes

Abstract Cancer-associated fibroblasts (CAFs) in pancreatic adenocarcinoma (PDAC) are known to play a significant role in regulating tumor progression, invasion, and metastasis. Multiple studies using experimental strategies, as well as single-cell RNA-sequencing (scRNAseq) technology, have shown the existence of subpopulations of PDAC CAFs, with divergent physical and biological characteristics. However, how these CAF subpopulations translate to clinical practice remains unclear. Using a combination of sc- and bulk RNAseq data, we present two CAF subtypes with permissive (permCAF) and restraining (restCAF) characteristics in patients, and developed a clinically usable single-sample classifier (DeCAF) using using 11 independent datasets with high reproducibility (AUC = 0.961). We found that the permCAF patients tend to be associated with a “myxoid” histological features, while restCAF samples were more “collagenized” (p = 0.018). Patients with permCAF tumors had a median overall survival (OS) of 18.5 m compared to 30.2 m for restCAF tumors, with a stratified HR = 1.66 (p < 0.001) for patients with permCAF tumors. Basal-like tumors were found to be associated permCAF subtype (p < 0.001). DeCAF and PurIST (basal-like/classical) subtypes were independently associated with OS (p < 0.001). Analysis of a phase Ib trial FOLFIRINOX in combination with a CCR2 inhibitor (PF-04136309; NCT01413022) , we found that in patients with classical tumors, increasing permCAF probability was associated with response (r = -0.688, p<0.001). Tumors with permCAF subtype are enriched in neutrophils using CIBERSORT and may explain the positive response to CCR2 inhibition. More intriguingly, we found similar associations with OS in kidney renal clear cell carcinoma (KIRC, p = 0.001) and mesothelioma (MESO, p = 0.019). DeCAF subtypes are associated with histological subtype in MESO (p = 0.021) and grade in KIRC (p = 0.056). Taken together, DeCAF subtypes explain the role of CAF subtypes in patients, provide a foundation for the translation of preclinical studies, and facilitate the design of future therapeutic approaches and clinical trials. Citation Format: Xianlu Laura Peng, Elena Kharitonova, Joseph Kearney, Yi Xu, Priscilla Chan, Changfei Luan, Brian Belt, Roheena Panni, Arthi Hariharan, Ian McCabe, Ashley Morrison, Ashley Cliff, David C. Linehan, Alina Iuga, Naim U. Rashid, Jen Jen Yeh. Determination of permissive and restraining cancer-associated fibroblast (DeCAF) subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6213.

Abstract 151: BMP signaling determines neuroblastoma cell fate and sensitivity to retinoic acid

Abstract While retinoic acid (RA) has been successfully used for leukemia treatment for decades, the attempt to treat solid tumors with RA remains challenging, with less than 10% of neuroblastoma (NB) patients achieving complete remission when treated with RA alone. It has been believed the anti-cancer activity of retinoids is due to retinoid-induced terminal differentiation, however, what determines cell response or whether differentiation is the main effect of RA has never been fully understood. To better understand RA’s activity, we conducted genome-wide CRISPR modifier screens in RA-treated hyper-sensitive NB cell lines. Surprisingly, we found that, in these cells, RA primarily decreased cell viability via apoptosis or senescence, rather than differentiation—activities in which the CRISPR screens strongly implicated bone morphogenetic protein (BMP) signaling. BMP activation promoted apoptosis/senescence and sensitized cells to RA. Conversely, BMP inhibitors and SMAD9 (a critical transcription factor of the BMP pathway) knockout enhanced RA’s ability to induce differentiation but reduced cell sensitivity to RA. Our ChIP-seq and RNA-seq data showed these behaviors were mediated by the coordinated gene regulatory actions of RARA and BMP-family SMAD transcription factors. Furthermore, in a panel of 19 cell lines we screened with RA, we assessed the correlations between RA IC50 and the expression of all (~20,000) genes (publicly available data from the GDSC and Depmap). Remarkably, SMAD9 was the number 1 and number 10 most correlated gene, respectively, with RA IC50 (ranked by Pearson correlation coefficient; GDSC R = -0.92, P = 4.2 × 10−6; Depmap R = -0.81, P = 4.8 × 10−4). We also performed comprehensive large-scale drug screens in these cell lines with combinations of RA and a BMP activator FK506. RA exhibited a synergistic effect with FK506 in all the NB cell lines, very strikingly in some cell lines. All these data suggest BMP signaling is generally required for RA sensitivity and BMP activators are promising candidates in combination with RA to treat NB. Using published bulk and single cell RNA-seq data from NB patient samples, we found BMP signaling activity is relatively low in primary tumors, but well maintained in disseminated NB cells derived from bone marrow. This explains why RA is clinically used as a maintenance therapy and can only successfully treat the minimal residual disease and suggests that tumor microenvironment is a critical factor in determining cell response to RA. Overall, our study revealed that BMP controls NB cell fate and sensitivity in RA treatment. Notably, interactions between BMP signaling and RA are well established in developmental biology, where BMP signaling can tip cell fate decisions between differentiation, apoptosis, and senescence upon exposure to endogenous RA. Our data suggest that this developmental process can be maintained in NB cells, unveiling a novel mode of anti-neoplastic action. Citation Format: Min Pan, Yinwen Zhang, William C. Wright, Hyeong-Min Lee, Richard H. Chapple, Xueying Liu, Jonathan Low, Duane Currier, Allister J. Loughran, Dyer A. Dyer, Shondra M. Pruett, Burgess Freeman, Taosheng Chen, Brian J. Abraham, Elizabeth Stewart, John Easton, Paul Geeleher. BMP signaling determines neuroblastoma cell fate and sensitivity to retinoic acid [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 151.

Abstract 1773: Deciphering the roles of germline predisposition variants and somatic mutations on breast cancer cells and the tumor microenvironment

Abstract While great progress has been made in the understanding and treatment of cancer, tumor heterogeneity remains a diagnostic and prognostic challenge. Single-cell sequencing techniques and high-resolution cellular imaging now afford researchers the ability to investigate the effects of germline variants (especially when compared to somatic mutations) on molecular characteristics of cancer cells and non-cancer cells in the tumor microenvironment (TME). Here, we investigated a breast cancer (BRCA) cohort of over 100 individuals, for which we have generated sc/sn RNA-seq, snATAC-seq, and CODEX imaging data as well as bulk whole exome sequencing and RNA-seq data. We identified 21 BRCA cases carrying pathogenic and likely pathogenic rare germline variants in known cancer predisposition genes, such as BRCA2, BRIP1, ATM, and TP53. These predisposition genes showed diverse expression patterns across stromal and immune cell types, indicating roles in cell types beyond breast epithelia. For cases carrying pathogenic germline variants in such genes, we use snRNA-seq/snATAC-seq to assess gene expression changes and pathway alterations (e.g.,HRD and apoptosis) across all cell types and investigate phenotypic changes associated with pathogenic germline variants in cancer cells compared to stroma and immune cells in the TME. By evaluating chromatin accessibility changes and allele-specific expression, we reveal the connection between epigenetic regulators and differential roles of germline variants across cell types. Finally, the integrated analysis of germline variants and somatic mutations from predisposition genes at single cell resolution broadened our understanding of the role of germline variants in TME during tumorigenesis. Citation Format: Fernanda Martins Rodrigues, Kelsey Gallant, Reyka Jayasinghe, Michael Iglesia, Andrew Houston, Siqi Chen, Preet Lal, Ryan Fields, William Gillanders, Feng Chen, Li Ding. Deciphering the roles of germline predisposition variants and somatic mutations on breast cancer cells and the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1773.

Abstract 2758: Stemness subtype gastric cancer accelerate hematogenous metastasis

Abstract Oncogenic progression and metastasis correlate with the acquisition of stem cell-like characteristics and the loss of differentiated phenotype. Poorly differentiated primary tumors often lead to unfavorable oncologic outcomes due to a heightened likelihood of metastasis to distant organs across various cancers. However, the relationship between stemness traits and metastasis in gastric cancer (GC) remains insufficiently explored. In this investigation, we analyzed bulk RNA-sequencing from microdissected primary tumor specimens and clinical data to pinpoint molecular subtypes linked to distant organ metastasis. Transcriptomic data from patient-derived xenograft (PDX) samples and available single-cell RNA datasets validated our bulk RNAseq findings. Comprehensive analysis highlighted the molecular traits of GC tied to hematogenous metastasis. Microdissection of primary tumor FFPE samples facilitated bulk RNA sequencing, encompassing samples from 33 metastatic and 31 metastasis-free patients, with 8 paired normal samples. Most samples contained less than 10% of tumor microenvironment (TME) components like fibroblasts, endothelial cells, and immune cells. Using non-negative matrix factorization (NMF) clustering, we achieved unsupervised subtyping of the gastric cancer gene expression matrix. Permutation tests based on subsampling indicated consistent high-level cophenetic coefficients at k=2, suggesting robust bifurcation of transcriptomic data into two clusters. One showed augmented stemness traits while the other emphasized differentiated mucosal genes, labeled as stemness and differentiated subtypes, respectively. GSEA highlighted a significant boost in the Hallmark angiogenesis score in the stemness subtype, not attributed to endothelial cell infiltration as verified by CIBERSORTx. This subtype also exhibited a marked decrease in hematogenous metastasis-free survival (HMFS) (p=0.008, log-rank test). Further, PDX samples were scrutinized. Post classification of the PDX graft expression matrix via logistic regression, we examined the endothelial cell fraction, determined by CIBERSORTx. Stemness subtype PDX grafts revealed a significant elevation in the host (mouse) endothelial cell fraction (p<0.05). In addition, stemness PDX patient showed significant decreased HMFS (p = 0.03). We also categorized the pseudobulk expression matrix of malignant cells into stemness or differentiated subtypes using GSE183904 scRNA cohort. scRNA sample analysis consistently presented an elevated endothelial cell fraction in the stemness GC subtype. The outcomes suggest a propensity for angiogenesis in the TME of the stemness subtype of GC. In conclusion, our findings demonstrate that the stemness subtype of GC accelerates hematogenous metastasis, as evidenced through clinical data, bulk RNAseq, PDX, and scRNAseq data. Citation Format: Seungho Lee, Jaeun Yoo, Seungbok Lee, Hyun Myong Kim, Kyoungyun Jeong, Yie-Ri Yoo, Ji-Yeon Shin, Kyoung Un Park, Hye Seung Lee, Seong-Ho Kong, Do Joong Park, Hyuk-Joon Lee, Han-Kwang Yang. Stemness subtype gastric cancer accelerate hematogenous metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2758.

Abstract 2265: Distinct alternative splicing patterns in genetic subtypes of diffuse large B-cell lymphoma

Abstract Advances in sequencing techniques have made molecular subgrouping of Diffuse Large B-cell Lymphoma (DLBCL) based on DNA cahnges, which has led to the development of Lymphgen classification. By the way, although alternative splicing (AS) in cancer cells contributes to proliferation, invasion and metastasis, and immune escape, their role and association with DLBCL molecular subtypes are unknown. Therefore, we analyzed whole-exome sequencing (WES) and bulk RNA-Seq data paired in the public EGA dataset (EGAD00001003600) to explore the patterns of AS events that differ between Lymphgene subtypes. The WES data of 620 DLBCL samples that passed quality control were aligned to the reference using BWA-MEM, and variants were called with Mutect2. We used the information of copy number variants provided by cBioPortal. The RNA-Seq analysis was performed using the STAR-RSEM pipeline and differential splicing events were detected using rMATS to compare subtypes. Among 620 DLBCL samples, there were 19 MCDs, 95 EZBs, 22 BN2s, and 137 ST2s (50 samples with multiple genetic classes, and 291 samples unclassified). Mutations in spliceosome complex genes (ZRSR2 and SF1) were found in 14 and 27 samples, respectively. In BN2 and MCD subtypes, splicing events with significantly different exon inclusion levels were observed at a high frequency of 29 and 16 occurrences, respectively, compared to other subtypes. (P-value < 0.05). In contrast, retained intron is the only event observed in the EZB subtype (Table 1). Samples with mutations in ZRSR2 and SF1 showed four and two aberrant events, respectively, compared to samples without these mutations. Of note, rMATS detected an alternative 3’ splice site event in exon 6 of CD37 in the MCD. CD37 is involved in tumorigenesis in leukocytes and has been suggested as a potential biomarker in blood cancer, and its dysregulation may have influenced the poor prognosis of MCD. In summary, molecular subtypes of DLBCL had unique features in terms of alternative splicing. Functional consequences of these selective exon usages for each DLBCL subtype are being warranted. Citation Format: Sanyeowool An, Youngil Koh, Sung-Soo Yoon. Distinct alternative splicing patterns in genetic subtypes of diffuse large B-cell lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2265.

Abstract 6767: Multivariate analysis of ex vivo kidney 3D immune-microtumors for functional precision medicine

Abstract Immuno-oncology (IO) represents a significant paradigm shift in cancer treatment, focused on leveraging and mobilizing a patient’s own immune response and anti-tumor capabilities. Despite accounting for the majority of available treatment options, there are currently no diagnostic tests capable of predicting combination immunotherapy response in kidney cancer. We have developed a fully human 3D IO model for clinical drug efficacy prediction through multivariate analysis of the tumor-immune microenvironment (TiME) combining functional assays, artificial intelligence and multi-omics. These immune-microtumors recapitulate a patient’s unique pathophysiology and allow 3D spatio-temporal analyses of functional metrics at both bulk and single-cell resolutions. Renal cell carcinoma (RCC) resections and matched blood were collected and processed for single cell isolation of tumor and PBMCs (N=20, ISRCTN10001405). Flow cytometry (FC) and immunofluorescence (IF) were used to characterize TiME cell subpopulations (cancer, immune, stromal etc.) in pellets and 3D cultures, and to deconvolute bulk RNAseq data. Target (tumor) and effector cells (PBMCs and CD8+) were stained with fluorescent probes, activated using ɑCD3 and encapsulated in TiME-mimicking 3D matrices. 3D immune-microtumors were treated with FDA-approved regimens including immunotherapies (ipilimumab, nivolumab, pembrolizumab) and receptor-tyrosine kinase inhibitors (TKIs)(cabozantinib, lenvatinib, axitinib) as monotherapies or combination therapies. Differential drug efficacies were functionally quantified over 4 days using 3D confocal microscopy and computer vision pipelines to extract cell behavior metrics such as immune cell infiltration, immune/tumor cell migration speed, and tumor killing/viability. We devised a specialized RCC hydrogel formulation with superior viability compared to MatrigelTM alone (N=7). FC/IF/RNAseq were used to quantify relative cell subpopulations after isolation and show protein/transcriptional signature retention after 3D culture (N=7). The platform was conducive to the testing of various drugs with varying MoAs including immunotherapies, TKIs, targeted therapies and cell therapies. Treatment with pembrolizumab led to 26% higher PBMC infiltration, 14% higher CD8+ infiltration and 15% increased tumor cell death compared to control. When in combination, pembrolizumab reduced cell viability by 10% and 19% with lenvatinib and axitinib respectively (N=1). Population analyses revealed intra-patient response heterogeneity (N=7). In conclusion, we showed MoA-agnostic, patient-dependent responses to FDA-approved clinical treatment regimens via molecular and functional spatio-temporal analyses. Clinical outcome correlation is currently underway in our advanced RCC study PEAR-TREE2 as well as in breast NCT05435352 and brain NCT06038760 tumors. Citation Format: Eleonora Peerani, Keqian Nan, Demi A. Wiskerke, Thomas D. Richardson, Polina Maximchick, Jay Kearney, George R. de Fraine, Kerrie L. Loughrey, Jonathan Ient, Jessica A. Hudson, Andreas Kaffa, Aston M. Crawley, Nourdine K. Bah, Edgar G. Lopez Molina, Elli Tham, Francesco Iori, Matthew H. Williams, Maxine G. Tran, Duleek N. Ranatunga. Multivariate analysis of ex vivo kidney 3D immune-microtumors for functional precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6767.