Integration Of Transcriptomics Research Articles

Integrating Omics Approaches for Climate-Resilient Crops: A Comprehensive Review

Climate change is a looming threat to global agriculture, impacting temperature, rainfall patterns, pest dynamics, and soil quality. These challenges transcend numerous crops vital for global food security. Drought, soil acidity, and nutrient fluctuations induced by climate change impede crop productivity, necessitating the development of breeding strategies to produce climate-resilient varieties. This review delves into the integration of omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, to bolster breeding programs across diverse crops. By harnessing high-throughput technologies, researchers gain insights into the genetic and molecular mechanisms underlying traits such as stress resistance, yield, and disease tolerance. The cultivation of elite cultivars with enhanced stress tolerance is paramount for sustainable agriculture in the face of climate change. Various breeding approaches, encompassing functional genomics and mutagenomics, are explored alongside the application of genome editing tools like CRISPR/Cas9 and TALEN for targeted trait enhancement. Through the integration of multi-omics data, novel genetic targets are unearthed, facilitating the development of crop varieties resilient to climate-induced stressors beyond maize. This review underscores the significance of multi-omics in crop breeding and highlights strides made toward climate-resilient crop production. Understanding crop responses to abiotic stresses induced by climate change is imperative for the development of resilient varieties. The integration of modern genetics into classical breeding methods aims to cultivate stress-resistant cultivars, mitigating food security risks. Multi-omics approaches play pivotal roles in unraveling crop performance and stress tolerance mechanisms under diverse environmental conditions. Moving forward, the integration of multi-omics approaches will pinpoint candidate genes and pathways, enabling precision breeding to enhance crop performance amidst changing climates. These endeavors will propel the advancement of climate-resilient crops, safeguarding global food security in the face of climate change's challenges.

PLS-based integration of metabolomics and transcriptomics to reveal the effect of different growth years on Eurycoma longifolia roots and hairy root cultures

Growth years are important factors that affect the accumulation of secondary metabolites in Eurycoma longifolia roots. This study aimed to investigate the effect of different growth years on the metabolites and gene expression of E. longifolia roots and hairy root cultures. To achieve this, metabolite profiles and candidate transcripts of terpenoid backbone biosynthesis and sesquiterpenoid and triterpenoid pathways of 1- and 11-year old E. longifolia roots and hairy root cultures were obtained and integrated using partial least squares (PLS). Integration of eighty-two metabolites and forty-five selected candidate genes using PLS successfully differentiated 1-, 11-year-old E. longifolia roots and hairy root cultures, indicating significant metabolite-gene expression differences in response to different growth years and root types. Amino acids, 2-C-methyl-D-erythritol-4-phosphate cytidylyl-transferase (MCT) and acetyl-CoA C-acetyltransferase (AACT) were responsible for the discrimination of 1-year-old E. longifolia root. Quassinoids of eurycomanone and eurycomalactone and genes linked to the upstream synthesis in mevalonate (MVA) pathway contributed to the discrimination of the11-year-old E. longifolia root. 11-hydroxycanthin-6-one and genes that participate in the methylerythritol phosphate (MEP) pathway upstream of terpenoid biosynthesis were responsible for the discrimination of E. longifolia hairy root cultures.

Transcriptomics and metabolomics: Challenges of studying obesity in osteoarthritis

ObjectiveObesity is a leading risk factor for both the incidence and progression of osteoarthritis (OA). Omic technologies, including transcriptomics and metabolomics are capable of identifying RNA and metabolite profiles in tissues and biofluids of OA patients. The objective of this review is to highlight studies using transcriptomics and metabolomics that contribute to our understanding of OA pathology in relation to obesity. DesignWe conducted a targeted search of PUBMED for articles, and GEO for datasets, published up to February 13, 2024, screening for those using high-throughput transcriptomic and metabolomic techniques to study human or pre-clinical animal model tissues or biofluids related to obesity-associated OA. We describe relevant studies and discuss challenges studying obesity as a disease-related factor in OA. ResultsOf the 107 publications identified by our search criteria, only 15 specifically used transcriptomics or metabolomics to study joint tissues or biofluids in obesity-related OA. Specific transcriptomic and metabolomic signatures associated with obesity-related OA have been defined in select local joint tissues, biofluids and other biological material. However, considerable challenges exist in understanding contributions of obesity-associated modifications of transcriptomes and metabolomes related to OA, including sociodemographic, anthropometric, dietary and molecular redundancy-related factors. ConclusionsA number of additional transcriptomic and metabolomic studies are needed to comprehensively understand how obesity affects OA incidence, progression and outcomes. Integration of transcriptome and metabolome signatures from multiple tissues and biofluids, using network-based approaches will likely help to better define putative therapeutic targets that could enable precision medicine approaches to obese OA patients.

Abstract PO3-14-05: Integration of metabolomics and transcriptomics to Reveal Potential Biomarkers Associated with Treatment Response of Neoadjuvant Therapy in HER2+ Breast Cancer

Abstract Background: Neoadjuvant therapy (NAT) has become the standard treatment for early human epidermal growth factor receptor 2 positive (HER2+) breast cancer. For patients with HER2+ breast cancer, achieving a pathologic complete response (pCR) is highly indicative of their prognosis. However, not all HER2+ breast cancer patients could benefit from the NAT, about 40%-50% patients could not achieve pCR at surgery, even if they used the present standard neoadjuvant regime of TCbHP (taxane, carboplatin, trastuzumab and pertuzumab). This study was conducted to explore potential indicators associated with neoadjuvant efficacy of TCbHP in HER2+ breast cancer. Methods: Consecutive HER2+ breast cancer patients, who received and completed NAT with TCbHP regime and subsequent surgery at Chongqing University Cancer Hospital were prospectively enrolled. LC-MS and GC-MS platform-based untargeted metabolomics were performed to determine the metabolic profiles of plasma samples from these patients at different time points during treatment period. Random forest (RF) was used to establish predictive models based on pre-therapeutic metabolic traits. The potential monitors for the treatment response were obtained by time series analysis. Transcriptome analysis was performed in available samples to identify differentially expressed genes (DEGs) before treatment. qRT-pCR was used to detect DEGs in tastuzumab-sensitive and -resistant cell lines. Metabolic and transcriptomic data were integrated to explore substantially altered pathways that might be responsible for drug resistance. Results: From July 20, 2020 to May 28, 2021, a total of 40 HER2+ breast cancer patients with 120 plasma samples were eligible and recruited for this study. Of whom 21 (52.5%) patients achieved pCR and 19 (47.5%) achieved non-pCR, there are no significant difference in baseline clinicopathological features between pCR and non-pCR patients. There were significant differences in plasma metabolic profiles between non-pCR and pCR groups before and during treatment. A total of 100 differential metabolites were identified between pCR and non-pCR patients at pre-therapeutic period, which were markedly enriched in 40 metabolic pathways. Four key metabolites [sophorose, N-(2-acetamido)iminodiacetic acid, taurine and 6-hydroxy-2-aminohexanoic acid] were selected by RF analysis. The AUC value to discriminate pCR and non-PCR group to NAT of the single potential metabolite or combined panel of these metabolites were more than 0.910. 18 metabolites exhibit a potential for monitoring efficacy. Among 163 DEGs identified by RNA-seq, some genes might associate with trastuzumab resistance detected by qRT-PCR in cell lines. 39 altered pathways were found abnormally expressed at both the transcriptional and metabolic levels, including ABC transporters, protein digestion and absorption, mineral absorption, et al. Conclusion: By metabolomics analysis, we have both offered a road map of the molecular alterations underlying NAT of TCbHP regime in HER2+ breast cancer and a preliminary analysis of a unique metabolic signature that might be used to distinguish non-pCR from pCR patients. Metabolomics integrated with transcriptomics analysis could assist for gaining new insights into biochemical pathophysiology and might facilitate the development of new treatment targets for insensitive patients. Citation Format: Ningning Zhang, Yuxin Huang, Guanwen Wang, Yimei Xiang, Zhouhong Jing, Junjie Zeng, Feng Yu, Xianjun Pan, Wenqi Zhou, Xiaohua Zeng. Integration of metabolomics and transcriptomics to Reveal Potential Biomarkers Associated with Treatment Response of Neoadjuvant Therapy in HER2+ 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 PO3-14-05.

Integration of metabolomics and transcriptomics reveals the therapeutic mechanism underlying Chelidonium majus L. in the treatment of allergic asthma

BackgroundChelidonium majus is a well-known traditional Chinese medicine, and has been reported of the effect in relieving cough and asthma. However, the mechanism of action is still unknown.MethodsAsthmatic SD rats were first sensitized and established through ovalbumin (OVA) motivation. Subsequently, Hematoxylin and eosin (H&E) staining, Masson’s trichrome (Masson) staining, Periodic acid-Schiff (PAS) staining and inflammatory cytokines assay of interleukin (IL)-4, IL-6, IL-17 were implemented to evaluate the protective effects of Chelidonium majus on asthma. Then, the effects of Chelidonium majus and their molecular mechanisms of action on asthma were detected based on the integration of transcriptomics and metabolomics analyses.ResultsAfter administration with Chelidonium majus, the histological injuries of inflammation, collagen deposition and mucus secretion in lungs were attenuated and the serum inflammatory cytokines perturbations were also converted. Furthermore, integrated analysis revealed that after Chelidonium majus treatment, 7 different expression genes (DEGs) (Alox15, P4ha1, Pla2g16, Pde3a, Nme1, Entpd8 and Adcy9) and 9 metabolic biomarkers (ADP, Xanthosine, Hypoxanthine, Inosine, prostaglandin E2 (PGE2), prostaglandin F2a (PGF2a), phosphatidylserine, Creatine and LysoPC (10:0)) were discovered to be connected with the enrichment metabolic pathways, including Purine metabolism, Arachidonic acid metabolism, Arginine and proline metabolism and Glycerophospholipid metabolism. The obtained metabolic biomarkers and DEGs were mainly related to energy metabolism and inflammation, and may be potential therapeutic targets.ConclusionChelidonium majus relieved OVA-induced asthma in rats by regulating the Alox15, P4ha1, Pla2g16, Pde3a, Nme1, Entpd8 and Adcy9 genes expression to restore the disorders in energy metabolism and inflammation.

Exploring the Causal Role of Immune Cells in Cerebral Aneurysm Through Single-Cell Transcriptomics and Mendelian Randomization Analysis.

Cerebral aneurysm (CA) represent a significant clinical challenge, characterized by pathological dilation of cerebral arteries. Recent evidence underscores the crucial involvement of immune cells in CA pathogenesis. This study aims to explore the complex interplay between immune cells and CA formation. We analyzed single-cell RNA sequencing data from the GSE193533 dataset, focusing on unruptured CA and their controls. Comprehensive cell-type identification and pseudotime trajectory analyses were conducted to delineate the dynamic shifts in immune cell populations. Additionally, a two-sample Mendelian Randomization (MR) approach was employed to investigate the causal influence of various immunophenotypes on CA susceptibility and the reciprocal effect of CA formation on immune phenotypes. Single-cell transcriptomic analysis revealed a progressive loss of vascular smooth muscle cells (VSMCs) and an increase in monocytes/macrophages (Mo/MΦ) and other immune cells, signifying a shift from a structural to an inflammatory milieu in CA evolution. MR analysis identified some vital immunophenotypes, such as CD64 on CD14+ CD16+ monocytes (OR: 1.236, 95% CI: 1.064 to 1.435, p=0.006), as potential risk factors for CA development, while others, like CD28- CD8br %CD8br (OR: 0.883, 95% CI: 0.789 to 0.988, p=0.030), appeared protective. Reverse MR analysis demonstrated that CA formation could modulate specific immunophenotypic expressions, highlighting a complex bidirectional interaction between CA pathology and immune response. This study underscores the pivotal role of immune cells in this process through the integration of single-cell transcriptomics with MR analysis, offering a comprehensive perspective on CA pathogenesis, potentially guiding future therapeutic strategies targeting specific immune pathways.

The Integration of Transcriptome and Metabolome Analyses Provides Insights into the Determinants of the Wood Properties in Toona ciliata.

Toona ciliata, also known as Chinese mahogany, is a high-quality and fast-growing wood species with a high economic value. The wood properties of T. ciliata of different provenances vary significantly. In this study, we conducted comprehensive transcriptome and metabolome analyses of red and non-red T. ciliata wood cores of different provenances to compare their wood properties and explore the differential metabolites and genes that govern the variation in their wood properties. Through combined analyses, three differential genes and two metabolites were identified that are possibly related to lignin synthesis. The lignin content in wood cores from T. ciliata of different provenances shows significant variation following systematic measurement and comparisons. The gene Tci09G002190, one of the three differential genes, was identified as a member of the CAD (Cinnamyl alcohol dehydrogenase) gene family of T. ciliata, which is associated with lignin synthesis. Our data provide insights into the determinants of the wood properties in T. ciliata, providing a solid foundation for research into the subsequent mechanisms of the formation of T. ciliata wood.

Multi-tissue transcriptome profiling linked the association between tissue-specific circRNAs and the heterosis for feed intake and efficiency in chicken

Heterosis has been widely utilized in chickens. The nonadditive inheritance of genes contributes to this biological phenomenon. However, the role of circRNAs played in the heterosis is poorly determined. In this study, we observed divergent heterosis for residual feed intake (RFI) between 2 crossbreds derived from a reciprocal cross between White Leghorns and Beijing You chickens. Then, circRNA landscape for 120 samples covering the hypothalamus, liver, duodenum mucosa and ovary were profiled to elucidate the regulatory mechanisms of heterosis. We detected that a small proportion of circRNAs (7.83-20.35%) were additively and non-additively expressed, in which non-additivity was a major inheritance of circRNAs in the crossbreds. Tissue-specific expression of circRNAs was prevalent across 4 tissues. Weighted gene co-expression network analysis revealed circRNA-mRNA co-expression modules associated with feed intake and RFI in the hypothalamus and liver, and the co-expressed genes were enriched in oxidative phosphorylation pathway. We further identified 8 nonadditive circRNAs highly correlated with 16 nonadditive genes regulating negative heterosis for RFI in the 2 tissues. Circ-ITSN2 was validated in the liver tissue for its significantly positive correlation with PGPEP1L. Moreover, the bioinformatic analysis indicated that candidate circRNAs might be functioned by binding the microRNAs and interacting with the RNA binding proteins. The integration of multi-tissue transcriptome firstly linked the association between tissue-specific circRNAs and the heterosis for feed intake and efficiency in chicken, which provide novel insights into the molecular mechanism underlying heterosis for feed efficiency. The validated circRNAs can act as potential biomarkers for predicting RFI and its heterosis.

Metabolome and transcriptome integration reveals insights into petals coloration mechanism of three species in Sect. Chrysantha chang

Metabolome and transcriptome integration reveals insights into petals coloration mechanism of three species in Sect. <i>Chrysantha</i> chang

Integrating Multi-omics Data for Alzheimer's Disease to Explore Its Biomarkers Via the Hypergraph-Regularized Joint Deep Semi-Non-Negative Matrix Factorization Algorithm.

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disorder. Its etiology may be associated with genetic, environmental, and lifestyle factors. With the advancement of technology, the integration of genomics, transcriptomics, and imaging data related to AD allows simultaneous exploration of molecular information at different levels and their interaction within the organism. This paper proposes a hypergraph-regularized joint deep semi-non-negative matrix factorization (HR-JDSNMF) algorithm to integrate positron emission tomography (PET), single-nucleotide polymorphism (SNP), and gene expression data for AD. The method employs matrix factorization techniques to nonlinearly decompose the original data at multiple layers, extracting deep features from different omics data, and utilizes hypergraph mining to uncover high-order correlations among the three types of data. Experimental results demonstrate that this approach outperforms several matrix factorization-based algorithms and effectively identifies multi-omics biomarkers for AD. Additionally, single-cell RNA sequencing (scRNA-seq) data for AD were collected, and genes within significant modules were used to categorize different types of cell clusters into high and low-risk cell groups. Finally, the study extensively explores the differences in differentiation and communication between these two cell types. The multi-omics biomarkers unearthed in this study can serve as valuable references for the clinical diagnosis and drug target discovery for AD. The realization of the algorithm in this paper code is available at https://github.com/ShubingKong/HR-JDSNMF .

Integration of transcriptome, gut microbiota, and physiology reveals toxic responses of the red claw crayfish (Cherax quadricarinatus) to imidacloprid

Imidacloprid enters the water environment through rainfall and causes harm to aquatic crustaceans. However, the potential chronic toxicity mechanism of imidacloprid in crayfish has not been comprehensively studied. In this study, red claw crayfish (Cherax quadricarinatus) were exposed to 11.76, 35.27, or 88.17 μg/L imidacloprid for 30 days, and changes in the physiology and biochemistry, gut microbiota, and transcriptome of C. quadricarinatus and the interaction between imidacloprid, gut microbiota, and genes were studied. Imidacloprid induced oxidative stress and decreased growth performance in crayfish. Imidacloprid exposure caused hepatopancreas damage and decreased serum immune enzyme activity. Hepatopancreatic and plasma acetylcholine decreased significantly in the 88.17 μg/L group. Imidacloprid reduced the diversity of the intestinal flora, increased the abundance of harmful flora, and disrupted the microbiota function. Transcriptomic analysis showed that the number of up-and-down-regulated differentially expressed genes (DEGs) increased significantly with increasing concentrations of imidacloprid. DEG enrichment analyses indicated that imidacloprid inhibits neurotransmitter transduction and immune responses and disrupts energy metabolic processes. Crayfish could alleviate imidacloprid stress by regulating antioxidant and detoxification-related genes. A high correlation was revealed between GST, HSPA1s, and HSP90 and the composition of gut microorganisms in crayfish under imidacloprid stress. This study highlights the negative effects and provides detailed sequencing data from transcriptome and gut microbiota to enhance our understanding of the molecular toxicity of imidacloprid in crustaceans.

Elucidating ascorbate and aldarate metabolism pathway characteristics via integration of untargeted metabolomics and transcriptomics of the kidney of high-fat diet-fed obese mice.

Obesity is a major independent risk factor for chronic kidney disease and can activate renal oxidative stress injury. Ascorbate and aldarate metabolism is an important carbohydrate metabolic pathway that protects cells from oxidative damage. However the effect of oxidative stress on this pathway is still unclear. Therefore, the primary objective of this study was to investigate the ascorbate and aldarate metabolism pathway in the kidneys of high-fat diet-fed obese mice and determine the effects of oxidative stress. Male C57BL/6J mice were fed on a high-fat diet for 12 weeks to induce obesity. Subsequently, non-targeted metabolomics profiling was used to identify metabolites in the kidney tissues of the obese mice, followed by RNA sequencing using transcriptomic methods. The integrated analysis of metabolomics and transcriptomics revealed the alterations in the ascorbate and aldarate metabolic pathway in the kidneys of these high-fat diet-fed obese mice. The high-fat diet-induced obesity resulted in notable changes, including thinning of the glomerular basement membrane, alterations in podocyte morphology, and an increase in oxidative stress. Metabolomics analysis revealed 649 metabolites in the positive-ion mode, and 470 metabolites in the negative-ion mode. Additionally, 659 differentially expressed genes (DEGs) were identified in the obese mice, of which 34 were upregulated and 625 downregulated. Integrated metabolomics and transcriptomics analyses revealed two DEGs and 13 differential metabolites in the ascorbate and aldarate metabolic pathway. The expression levels of ugt1a9 and ugt2b1 were downregulated, and the ascorbate level in kidney tissue of obese mice was reduced. Thus, renal oxidative stress injury induced by high-fat diet affects metabolic regulation of ascorbate and aldarate metabolism in obese mice. Ascorbate emerged as a potential marker for predicting kidney damage due to high-fat diet-induced obesity.

Inhibition of hepatitis B virus via selective apoptosis modulation by Chinese patent medicine Liuweiwuling Tablet.

Liuweiwuling Tablet (LWWL) is a Chinese patent medicine approved for the treatment of chronic inflammation caused by hepatitis B virus (HBV) infection. Previous studies have indicated an anti-HBV effect of LWWL, specifically in terms of antigen inhibition, but the underlying mechanism remains unclear. To investigate the potential mechanism of action of LWWL against HBV. In vitro experiments utilized three HBV-replicating and three non-HBV-replicating cell lines. The in vivo experiment involved a hydrodynamic injection-mediated mouse model with HBV replication. Transcriptomics and metabolomics were used to investigate the underlying mechanisms of action of LWWL. In HepG2.1403F cells, LWWL (0.8 mg/mL) exhibited inhibitory effects on HBV DNA, hepatitis B surface antigen and pregenomic RNA (pgRNA) at rates of 51.36%, 24.74% and 50.74%, respectively. The inhibition rates of LWWL (0.8 mg/mL) on pgRNA/covalently closed circular DNA in HepG2.1403F, HepG2.2.15 and HepG2.A64 cells were 47.78%, 39.51% and 46.74%, respectively. Integration of transcriptomics and metabolomics showed that the anti-HBV effect of LWWL was primarily linked to pathways related to apoptosis (PI3K-AKT, CASP8-CASP3 and P53 pathways). Apoptosis flow analysis revealed that the apoptosis rate in the LWWL-treated group was significantly higher than in the control group (CG) among HBV-replicating cell lines, including HepG2.2.15 (2.92% ± 1.01% vs 6.68% ± 2.04%, P < 0.05), HepG2.A64 (4.89% ± 1.28% vs 8.52% ± 0.50%, P < 0.05) and HepG2.1403F (3.76% ± 1.40% vs 7.57% ± 1.35%, P < 0.05) (CG vs LWWL-treated group). However, there were no significant differences in apoptosis rates between the non-HBV-replicating HepG2 cells (5.04% ± 0.74% vs 5.51% ± 1.57%, P > 0.05), L02 cells (5.49% ± 0.80% vs 5.48% ± 1.01%, P > 0.05) and LX2 cells (6.29% ± 1.54% vs 6.29% ± 0.88%, P > 0.05). TUNEL staining revealed a significantly higher apoptosis rate in the LWWL-treated group than in the CG in the HBV-replicating mouse model, while no noticeable difference in apoptosis rates between the two groups was observed in the non-HBV-replicating mouse model. Preliminary results suggest that LWWL exerts a potent inhibitory effect on wild-type and drug-resistant HBV, potentially involving selective regulation of apoptosis. These findings offer novel insights into the anti-HBV activities of LWWL and present a novel mechanism for the development of anti-HBV medications.

Integration of single-cell transcriptome and chromatin accessibility and its application on tumor investigation

Abstract The advent of single-cell sequencing techniques has not only revolutionized the investigation of biological processes but also significantly contributed to unraveling cellular heterogeneity at unprecedented levels. Among the various methods, single-cell transcriptome sequencing stands out as the best established, and has been employed in exploring many physiological and pathological activities. The recently developed single-cell epigenetic sequencing techniques, especially chromatin accessibility sequencing, have further deepened our understanding of gene regulatory networks. In this review, we summarize the recent breakthroughs in single-cell transcriptome and chromatin accessibility sequencing methodologies. Additionally, we describe current bioinformatic strategies to integrate data obtained through these single-cell sequencing methods and highlight the application of this analysis strategy on a deeper understanding of tumorigenesis and tumor progression. Finally, we also discuss the challenges and anticipated developments in this field.

Abstract 4940: Unraveling ctDNA features in high-grade serous ovarian carcinoma and insights from genomic and transcriptomic integration

Abstract High-grade serous carcinoma (HGSC) is often diagnosed at advanced stages with less than 40% of patients surviving for five years after diagnosis. Circulating tumor DNA (ctDNA) is a minimally invasive technology that can provide crucial insights into tumor biology. Unique features from ctDNA, fragment patterns and nucleosome footprints at transcription start sites (TSS), complement genomic variants. Our study explored ctDNA features in HGSC, integrating with tumor biopsies' genomic and transcriptomic profiles. We focus on two aspects in HGSC: understanding how ctDNA features assist genomic profiling and track dynamic changes during treatment and exploring the biological factors impacting ctDNA release. We used 500+ longitudinal plasma and 400+ pretreatment tissue samples from HGSC patients in the DECIDER study (NCT04846933). Shallow whole-genome sequencing (sWGS) with 0.4x average coverage was conducted on plasma. Integration of DNA and RNA pretreatment tissue data was performed for 98 and 91 patients with available plasma before treatment, respectively. Plasma samples underwent analysis for fragment patterns and TSS signals. Somatic mutations and mutational signatures were retrieved for patients with available WGS tissue data. Pathway enrichment analysis was applied to diverse gene expression profiles. WGS data from 29 healthy individuals (Zhu, G. et al. (2023)) served as controls. DNA fragment profiles and TSS signals distinguish ctDNA from healthy samples. The ability to cluster sample phases based on ctDNA features facilitates tracking longitudinal changes. Integrating tissue DNA and RNA data reveals a positive correlation between high ctDNA release and mutational burden, single-base substitution signature SBS1 as a marker for cell division/mitotic clock and doublet-base substitution signatures linked to late replication. These mechanisms help explain why high ctDNA release group (n=40) is associated with a shorter progression-free survival. Additionally, transcriptomics data indicates associations with proliferation pathways in cancer cells and ctDNA release. The concordance in results from DNA and RNA points to a higher proliferation rate in patients with high ctDNA release, suggesting the need for alternative treatment compared to those with low ctDNA release. In conclusion, our results provide a multifaceted perspective on ctDNA in HGSC. The identification of longitudinal ctDNA features signifies the capability to stratify sample states and show the potential findings through fragment profiles and the discernment of key TSS regions. The proposed aetiologies and enriched pathways associated with ctDNA release, mutation burden and proliferation, shed light on potential treatment avenues. These findings contribute to our understanding of ctDNA in HGSC and offer insights for personalized treatment strategies and monitoring approaches. Citation Format: Mai TN Nguyen, Jaana Oikkonen, Yilin Li, Daria Afentave, Johanna Hynninen, Sampsa K. Hautaniemi. Unraveling ctDNA features in high-grade serous ovarian carcinoma and insights from genomic and transcriptomic integration [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 4940.

Abstract 3988: Deep spatial immunophenotyping of lymphoid aggregates in pancreatic cancer using multi-omic integration of ultra high-plex proteomics and transcriptomics

Abstract The most well-described mechanism of immune evasion in PDAC is exclusion of immune cells by a desmoplastic stroma, but such immune exclusion is not uniform. Through single-nucleus RNA-seq and whole-transcriptome digital spatial profiling of patient tumors, we previously reported marked heterogeneity in the immune composition of PDAC. Here, we developed a novel multi-omics workflow integrating single cell spatial proteomics (96-plex, Akoya Phenocycler®-Fusion) and transcriptomics (990-plex, Nanostring CosMx) in primary patient PDAC tumors to systematically study spatial relationships and functional states of malignant, stromal, and immune cells. Consecutive sections from four independent tumors enabled whole slide proteomic assessment of &amp;gt;3.5M cells, and transcriptomic assessment of &amp;gt;200K cells. Strikingly, we observed an abundance of immune cell aggregates in all tissue sections, up to 57 within a 1 cm2 tumor section. Aggregates were diverse in composition with representation of myeloid cells, CD8+ T cells, and stromal cells, including fibroblasts and nerves. B/T lymphoid aggregates were well vascularized with co-localized CD31+CD34+ endothelial cells and appeared at various phases of maturation towards putative tertiary lymphoid structures (TLSs) containing CD38+ B cells, CD4+ T cells, and CD21+ follicular DCs. These tissues were enriched for interferon stimulated genes in T cells and type 1 interferon response signatures in malignant cells and cancer associated fibroblasts (CAFs) forming inflammatory multicellular hubs that have been associated with improved response to immune checkpoint blockade. Surprisingly, B cells, in addition to macrophages and CD8+ T cells, were major producers of interferon gamma (B cells: 13.7%, macrophages: 36.6%, CD8+ T cells: 12.1% of IFNG+ cells). Finally, to gain insight into the necessary factors for TLS formation in PDAC, we quantified the expression of chemokines and adhesion molecules associated with TLS initiation. Activated dendritic cells expressed CCL19 and CCL21, endothelial cells expressed CCL21, and in concert with inflammatory CAFs (iCAFs), CXCL12. Malignant cells expressed CXCL13 and CCL20 and displayed high levels of cell adhesion molecules ICAM1, VCAM1, and ICAM2. Together, our data suggests that the functions of lymphoid tissue organizer cells can be substituted by endothelial cells, dendritic cells, iCAFs, and, surprisingly, malignant cells. Our spatial immunophenotyping study of pancreatic cancer thus highlights the marked immune heterogeneity of the disease and suggests a central role for malignant and stromal cells in mediating diverse mechanisms of immune evasion and engagement. Functional studies will be conducted to investigate these mechanisms of tumor-immune crosstalk and identify novel immunotherapeutic vulnerabilities for this deadly disease. Citation Format: Dennis Gong, Jingyi Cao, Peter Wang, Niyati Jhaveri, Yue Hou, Bassem B. Cheikh, HaYeun Ji, Mark Gregory, Jason Reeves, Michael Patrick, Carina Shiau, Jennifer Su, Jimmy A. Guo, Joseph M. Beechem, Martin Hemberg, William L. Hwang, Ryan Park. Deep spatial immunophenotyping of lymphoid aggregates in pancreatic cancer using multi-omic integration of ultra high-plex proteomics and transcriptomics [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 3988.

Abstract 109: Identification of tumor-intrinsic and extrinsic mechanisms of T cell exclusion in estrogen receptor-positive (ER+) breast cancer through integration of bulk and single-cell transcriptome and spatial analysis

Abstract T cells are generally present in low numbers in estrogen receptor-positive (ER+) breast cancer (BC) potentially due to limited antigens or impaired antigen presentation, however defined mechanisms are not fully understood. This study explores the interplay between estrogen receptor signaling (ERS), antigen presentation machinery (APM), and T cell signaling (TC) using diverse datasets, including BC cell lines, TCGA, METABRIC, and clinical trial bulk transcriptomes, single-cell RNA-sequencing of ER+ primary BC, and single-cell spatial multi-plex cyclic immunofluorescence (CyCIF) of primary BC patients. Co-expression analysis of both computationally and manually curated genes in TCGA and METABRIC data unveiled distinct 29-gene ERS and 225-gene combined APM/TC modules with strong inverse correlations in ER+ BC. This inverse correlation was confirmed in independent cohorts. ERS and APM/TC modules were down- and up-regulated, respectively, in response to aromatase inhibitor therapy in ER+ BC patients from the ACOSOG Z1301B trial who demonstrated clinical benefit. Analysis of published single-cell RNA-sequencing data of 20 primary ER+ BC was performed to elucidate cell types that express individual genes in the modules. It confirmed that high ERS activity is associated with reduced T cells, and identified distinct cell types contributing to each module, showing higher ERS activity in tumor cells and higher APM/TC activity in stromal and immune cells. At the cell type level, we found distinct contributions and precise insights of individual genes. The prevalence of ERS activity in tumor cells prompted investigation to determine if the ERS and APM/TC modules were preserved as tumor-intrinsic signaling. Analysis of 54 BC cell lines indicated partially preserved module correlations in cancer cell lines and revealed that the APM/TC module is a contribution of both tumor-intrinsic (e.g., complement and type-I IFN-response), and tumor-extrinsic (e.g., lymphocyte activation) factors. CyCIF analysis of 29 ER+ BC samples was performed to bridge gene signatures with spatial biology and validated that higher ERS activity correlates with lower T cell infiltration. The spatial pattern of T cells varied from immune desert to stromally bound to fully inflamed tumors. Neighborhood analysis revealed increased frequency of CD8 T cells around a tumor cell is associated with elevated MHC I and II in broad immune cells and macrophage subsets, respectively. pTBK1+ macrophages inversely correlated with CD8 T cell frequency and MHC expression in neighboring cells, suggesting an immunosuppressive role. This study uncovers robust and tightly regulated ERS and APM/TC signaling in ER+ patients, unraveling molecular intricacies and offering potential insights for targeted therapeutic interventions. Citation Format: Kenichi Shimada, Yvonne X. Cui, Daniel Michaud, Kelly F. Zheng, Jonathan Goldberg, Ricardo Pastorello, Lukas Kania, Sandra S. McAllister, Sara M. Tolaney, Adrienne Waks, Rinath Jeselsohn, Peter K. Sorger, Judith Agudo, Jennifer L. Guerriero, Elizabeth A. Mittendorf. Identification of tumor-intrinsic and extrinsic mechanisms of T cell exclusion in estrogen receptor-positive (ER+) breast cancer through integration of bulk and single-cell transcriptome and spatial analysis [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 109.

Abstract 1492: Unveiling the re-programming of choroid plexus and leptomeningeal metastasis

Abstract Leptomeningeal metastasis (LM) is an increasingly common, fatal complication of breast and lung cancer. Despite aggressive treatment, neurologic deficits accumulate rapidly, and patients generally succumb to LM within months. We must expand our limited mechanistic knowledge of this disease. Under homeostatic conditions, choroid plexus (ChP), highly vascularized structures within the brain ventricles, restrict the entry of macromolecules and cells into the leptomeninges; however, select cancer cells can cross this barrier and grow within the leptomeningeal space. We hypothesize that interactions between cancer and ChP niche cells alter both the niche and the cancer cells, ultimately supporting LM.During neurogenesis, the ChP display substantial extracellular matrix (ECM) remodeling, which is elegantly modulated by dynamic spatiotemporal regulation of MMPs, Wnt signaling, among other effector proteins. Similarly, 2-photon imaging of ChP collected from mice harboring LM revealed a profound ECM remodeling of the ChP when compared with naïve mice. This remodeling was accompanied by increased levels of MMP2 and MMP9 in LM mice. Upon pharmacological inhibition of MMP2 and MMP9 in vivo, we observed a decrease in LM burden and increase in overall survival, which correlates with a decrease in ChP permeability. Interestingly, human CSF from patients with leptomeningeal metastases is also enriched in collagen 1 fragments, MMP2, MMP9 and TIMP1. TIMP1, a MMP9 natural inhibitor, is not present in complex with MMP9, suggesting a role of TIMP1 as a cytokine in LM progression. TIMP1 neutralization and knockout from the cancer cells leads to a decrease in LM burden and increase in overall survival. Together, these data suggest a provocative link between proteolysis and inflammation in LM progression. The use of clinically-annotated human samples and mouse models of LM, and the integration of transcriptomics and proteomics enabled us to identify key signaling pathways, and capture the re-programming of ChP niche and cancer cells that unlock the leptomeningeal space to cancer cells. The timeframe for this evolution will be further revealed by analysis of mouse and human samples at different stages of cancer progression. Citation Format: Ana Rita Nobre, Helen Wang, Rachel Estrera, Isaiah Osei-Gyening, Adrienne Boire. Unveiling the re-programming of choroid plexus and leptomeningeal 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 1492.

Abstract 1587: Multimodal spatial transcriptomics uncover distinct tumor microenvironment states and cell-cell communication networks in molecular pancreatic cancer subtypes

Abstract The tumor microenvironment (TME) presents a complex ecosystem comprising a diversity of immune and stromal cell populations that influence tumor progression, drug delivery and therapy outcome. High levels of inter- and intra-tumor heterogeneity in TME state are driven by molecular tumor phenotypes. Pancreatic ductal adenocarcinoma (PDAC), one of the most lethal cancer types, displays a high genetic heterogeneity along with an immunosuppressive TME. However, it remains largely elusive how distinct TME states are mechanistically influenced, and which molecular processes dictate the emergence of different modes of immunosuppression within the TME of molecular PDAC subtypes.Here, we performed a systematic analysis of functional associations between the major molecular PDAC subtypes, the classical and mesenchymal subtype, and their TME states. We describe the TME composition and complex cell-cell communication networks within PDAC subtypes using a multimodal integration of spatial transcriptomics (ST) with complementary approaches, such as scRNA-seq, MS-based Secretomics and multiplexed histocytometry. We generated ST data sets (Visium) of a tumor cohort derived from a Kras-driven PDAC mouse model. To analyze TME composition as well as spatial niches and cell type communities, we computationally enhanced the spot-resolution of ST datasets, followed by cell type deconvolution and cell-cell communication analysis to identify subtype-specific TME communities and communication networks.To this end, we generated a large resource of PDAC mouse models which represent molecular subtypes of the disease and mimic the heterogeneity of TME states found in human PDAC cohorts. This analysis revealed that a set of subtype-specific secreted factors shape the immunosuppressive PDAC TME via direct and indirect communication networks with immunosuppressive myeloid and T cells in molecular PDAC subtypes. Multimodal ST analysis delineated spatial subtype-specific TME communities as well as spatial communication patterns. We functionally investigate the tumor cell intrinsic regulation of the identified subtype-specific secreted factors, providing potential therapeutic vulnerabilities for more effective combinatorial subtype-specific therapies including immunotherapeutic approaches. Citation Format: Stefanie Baerthel, Chiara Falcomatà, Vanessa Goelling, Daniele Lucarelli, Rushin Gindra, Constantin Schmitt, Jonathan Swietlik, Felix Meissner, Marc Schmidt-Supprian, Dieter Saur. Multimodal spatial transcriptomics uncover distinct tumor microenvironment states and cell-cell communication networks in molecular pancreatic cancer 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 1587.

The exon junction complex is required for DMD gene splicing fidelity and myogenic differentiation

Deposition of the exon junction complex (EJC) upstream of exon-exon junctions helps maintain transcriptome integrity by preventing spurious re-splicing events in already spliced mRNAs. Here we investigate the importance of EJC for the correct splicing of the 2.2-megabase-long human DMD pre-mRNA, which encodes dystrophin, an essential protein involved in cytoskeletal organization and cell signaling. Using targeted RNA-seq, we show that knock-down of the eIF4A3 and Y14 core components of EJC in a human muscle cell line causes an accumulation of mis-splicing events clustered towards the 3′ end of the DMD transcript (Dp427m). This deregulation is conserved in the short Dp71 isoform expressed ubiquitously except in adult skeletal muscle and is rescued with wild-type eIF4A3 and Y14 proteins but not with an EJC assembly-defective mutant eIF4A3. MLN51 protein and EJC-associated ASAP/PSAP complexes independently modulate the inclusion of the regulated exons 71 and 78. Our data confirm the protective role of EJC in maintaining splicing fidelity, which in the DMD gene is necessary to preserve the function of the critical C-terminal protein–protein interaction domain of dystrophin present in all tissue-specific isoforms. Given the role of the EJC in maintaining the integrity of dystrophin, we asked whether the EJC could also be involved in the regulation of a mechanism as complex as skeletal muscle differentiation. We found that eIF4A3 knockdown impairs myogenic differentiation by blocking myotube formation. Collectively, our data provide new insights into the functional roles of EJC in human skeletal muscle.