Unique Gene Expression Patterns Research Articles

Unlocking the genetic tapestry of autoimmune diseases: Unveiling common genes across multiple conditions.

This study aimed to unravel the complexities of autoimmune diseases by conducting a comprehensive analysis of gene expression data across 10 conditions, including systemic lupus erythematosus (SLE), psoriasis, Sjögren's syndrome, sclerosis, immune-associated diseases, osteoarthritis, cystic fibrosis, inflammatory bowel disease (IBD), type 1 diabetes, and Guillain-Barré syndrome. Gene expression profiles were rigorously examined to identify both upregulated and downregulated genes specific to each autoimmune disease. The study employed visual representation techniques such as heatmaps, volcano plots, and contour-MA plots to provide an intuitive understanding of the complex gene expression patterns in these conditions. Distinct gene expression profiles for each autoimmune condition were uncovered, with psoriasis and osteoarthritis standing out due to a multitude of both upregulated and downregulated genes, indicating intricate molecular interplays in these disorders. Notably, common upregulated and downregulated genes were identified across various autoimmune conditions, with genes like SELENBP1, MMP9, BNC1, and COL1A1 emerging as pivotal players. This research contributes valuable insights into the molecular signatures of autoimmune diseases, highlighting the unique gene expression patterns characterizing each condition. The identification of common genes shared among different autoimmune conditions, and their potential role in mitigating the risk of rare diseases in patients with more prevalent conditions, underscores the growing significance of genetics in healthcare and the promising future of personalized medicine.

Molecular Genealogy of Metabolic-associated Hepatocellular Carcinoma.

This review examines the latest epidemiological and molecular pathogenic findings of metabolic-associated hepatocellular carcinoma (HCC). Its increasing prevalence is a significant concern and reflects the growing burden of obesity and metabolic diseases, including metabolic dysfunction-associated steatotic liver disease, formerly known as nonalcoholic fatty liver disease, and type 2 diabetes. Metabolic-associated HCC has unique molecular abnormality and distinctive gene expression patterns implicating aberrations in bile acid, fatty acid metabolism, oxidative stress, and proinflammatory pathways. Furthermore, a notable frequency of single nucleotide polymorphisms in genes such as patatin-like phospholipase domain-containing 3, transmembrane 6 superfamily member 2, glucokinase regulator, and membrane-bound O-acyltransferase domain-containing 7 has been observed. The tumor immune microenvironment of metabolic-associated HCC is characterized by unique phenotypes of macrophages, neutrophils, and T lymphocytes. Additionally, the pathogenesis of metabolic-associated HCC is influenced by abnormal lipid metabolism, insulin resistance, and dysbiosis. In conclusion, deciphering the intricate interactions among metabolic processes, genetic predispositions, inflammatory responses, immune regulation, and microbial ecology is imperative for the development of novel therapeutic and preventative measures against metabolic-associated HCC.

Abstract 5540: Single cell multiomic analysis of human brain metastasis reveals conserved dormancy population

Abstract This study explores the complex realm of brain metastasis, pivotal in crafting effective anti-tumor strategies. Leveraging single-cell multi-omics sequencing, we profiled the transcriptomes and chromatin accessibility landscapes of tumor cells and their surrounding microenvironment in human brain metastases that originated from across a spectrum of primary cancers. Our investigations have identified distinct, yet uniformly present, tumor cell subpopulations, each defined by unique gene expression patterns, chromatin accessibility, and the interactions between tumor and stromal cells. Notably, one such subpopulation exhibits a dormancy signature, characterized by enhanced interferon response, oxidative phosphorylation, and upregulated HLA class molecules, alongside alterations in circadian rhythms. Our trajectory analysis charts a course from these dormant cells to rapidly proliferating ones, with notable shifts in circadian rhythm genes, underscoring their potential role in brain metastasis. This aligns with recent findings that disruptions in circadian rhythms can modify stem cell characteristics in glioblastomas. This insight led us to focus on a specific circadian rhythm gene, highly active in the dormant cells and located on the HER2 amplicon—an area linked to high brain metastasis relapse rates in patients. We've developed inducible models for both overexpression and knockdown to scrutinize this gene's impact in her2 positive breast cancer cell lines, examining gene expression and proliferation in vitro. Complementing this, we are conducting spatial transcriptomic analysis to evaluate the microenvironmental regulation of tumor dormancy in human brain metastases. This multi-omics approach reveals a nuanced regulatory landscape of brain metastasis, highlighting a novel and often overlooked factor in metastasis progression and brain tumor relapse: the interplay between circadian rhythms and tumor dormancy. This discovery not only deepens our understanding of brain metastases but also opens potential new avenues for therapeutic interventions. Citation Format: Remi Klotz, Yiru Wang, Anu Sunkara, Frank Attenelo, Min Yu. Single cell multiomic analysis of human brain metastasis reveals conserved dormancy population [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 5540.

Abstract 6883: Investigation of tumor-immune interactions in pediatric sarcomas using single-cell multi-omics

Abstract Background: Pediatric sarcoma represents the second most common solid tumor in children. Despite advances in multimodal therapies, one-third of sarcoma patients do not survive the disease. Over the past few decades, the development of novel therapeutic strategies for sarcoma has been impeded by an insufficient understanding of the tumor microenvironment (TME). In particular, the potential of immunotherapy remains constrained by the gap of knowledge about the molecular and functional phenotypes of the immune cells in the sarcoma TME. Methods: To address this knowledge gap, we collected treatment-naïve tumor samples from 32 patients with five pediatric sarcoma subtypes. We employed a single-nuclei RNA+ATAC-Seq multi-omics assay to comprehensively characterize the transcriptomic and epigenomic heterogeneity of tumor and immune cells within the sarcoma TME. Results: Our analysis revealed that tumor-associated macrophages (TAMs) were the most abundant immune cell type in the sarcoma TME. We identified seven distinct TAM subpopulations, each exhibiting unique gene expression and chromatin accessibility patterns. Among these, TAM subsets with higher expression of SPP1 and C1QC genes displayed the strongest immunosuppressive potential. Transcriptional regulatory network (TRN) analysis identified transcription factors that were most likely to drive the phenotypes of SPP1+ and C1QC+ TAMs, including ELF2, JUND and RUNX1. Through cell-cell communication analysis, we discovered that SPP1+ TAMs interact with T cells via SPP1-CD44 signaling, while C1QC+ TAMs interact with NK cells through HLA-E-KLRC1 signaling, suggesting the potential involvement of these signaling pathways in TAM-mediated suppression of these cytotoxic lymphocytes. We prioritized ligand-receptor gene pairs, such as SEMA3D-NRP1 and LTBP3-ITGB5, which likely mediate the interaction between malignant sarcoma cells and SPP1+/C1QC+ TAMs based on their dominance across sarcoma subtypes and association with poorer clinical outcomes. On the other hand, our analysis revealed that sarcoma subtype-specific interactions between TAMs and malignant cells are common, highlighting the heterogeneity of signaling events across sarcoma subtypes. Conclusion and Significance: Our study presents a comprehensive single-cell multi-omics characterization of pediatric sarcomas and sheds light on its tumor microenvironment. By identifying unique markers for immunosuppressive TAM subpopulations and elucidating intercellular interactions promoting tumor development, this study proposes potential therapeutic targets for sarcoma treatment based on the role of TAMs in sarcoma TME. Citation Format: Zhan Zhang, Kyung Jin Ahn, Changya Chen, Rumeysa Biyik Sit, Hesham Mohei, Brian Lockhart, Malay Haldar, Kathrin Bernt, Vinodh Pillai, Kai Tan. Investigation of tumor-immune interactions in pediatric sarcomas using single-cell multi-omics [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 6883.

Establishment and analysis of artificial neural network diagnosis model for coagulation-related molecular subgroups in coronary artery disease.

Background: Coronary artery disease (CAD) is the most common type of cardiovascular disease and cause significant morbidity and mortality. Abnormal coagulation cascade is one of the high-risk factors in CAD patients, but the molecular mechanism of coagulation in CAD is still limited. Methods: We clustered and categorized 352 CAD paitents based on the expression patterns of coagulation-related genes (CRGs), and then we explored the molecular and immunological variations across the subgroups to reveal the underlying biological characteristics of CAD patients. The feature genes between CRG-subgroups were further identified using a random forest model (RF) and least absolute shrinkage and selection operator (LASSO) regression, and an artificial neural network prediction model was constructed. Results: CAD patients could be divided into the C1 and C2 CRG-subgroups, with the C1 subgroup highly enriched in immune-related signaling pathways. The differential expressed genes between the two CRG-subgroups (DE-CRGs) were primarily enriched in signaling pathways connected to signal transduction and energy metabolism. Subsequently, 10 feature DE-CRGs were identified by RF and LASSO. We constructed a novel artificial neural network model using these 10 genes and evaluated and validated its diagnostic performance on a public dataset. Conclusion: Diverse molecular subgroups of CAD patients may each have a unique gene expression pattern. We may identify subgroups using a few feature genes, providing a theoretical basis for the precise treatment of CAD patients with different molecular subgroups.

Wnt/β-catenin signaling pathway in liver biology and tumorigenesis.

The Wnt/β-catenin pathway is an evolutionarily conserved signaling pathway that controls fundamental physiological and pathological processes by regulating cell proliferation and differentiation. The Wnt/β-catenin pathway enables liver homeostasis by inducing differentiation and contributes to liver-specific features such as metabolic zonation and regeneration. In contrast, abnormalities in the Wnt/β-catenin pathway promote the development and progression of hepatocellular carcinoma (HCC). Similarly, hepatoblastoma, the most common childhood liver cancer, is frequently associated with β-catenin mutations, which activate Wnt/β-catenin signaling. HCCs with activation of the Wnt/β-catenin pathway have unique gene expression patterns and pathological and clinical features. Accordingly, they are highly differentiated with retaining hepatocyte-like characteristics and tumorigenic. Activation of the Wnt/β-catenin pathway in HCC also alters the state of immune cells, causing "immune evasion" with inducing resistance to immune checkpoint inhibitors, which have recently become widely used to treat HCC. Activated Wnt/β-catenin signaling exhibits these phenomena in liver tumorigenesis through the expression of downstream target genes, and the molecular basis is still poorly understood. In this review, we describe the physiological roles of Wnt/b-catenin signaling and then discuss their characteristic changes by the abnormal activation of Wnt/b-catenin signaling. Clarification of the mechanism would contribute to the development of therapeutic agents in the future.

Alteration of functionality and differentiation directed by changing gene expression patterns in myeloid-derived suppressor cells (MDSCs) in tumor microenvironment and bone marrow through early to terminal phase of tumor progression.

Myeloid-derived suppressor cells are heterogenous immature myeloid lineage cells that can differentiate into neutrophils, monocytes, and dendritic cells as well. These cells have been characterized to have potent immunosuppressive capacity in neoplasia and a neoplastic chronic inflammatory microenvironment. Increased accumulation of myeloid-derived suppressor cells was reported with poor clinical outcomes in patients. They support neoplastic progression by abrogating antitumor immunity through inhibition of lymphocyte functions and directly by facilitating tumor development. Yet the shifting genetic signatures of this myeloid lineage cell toward immunosuppressive functionality in progressive tumor development remain elusive. We have attempted to identify the gene expression profile using lineage-specific markers of these unique myeloid lineage cells in a tumor microenvironment and bone marrow using a liquid transplantable mice tumor model to trace the changing influence of the tumor microenvironment on myeloid-derived suppressor cells. We analyzed the phenotype, functional shift, suppressive activity, differentiation status, and microarray-based gene expression profile of CD11b+Gr1+ lineage-specific cells isolated from the tumor microenvironment and bone marrow of 4 stages of tumor-bearing mice and compared them with control counterparts. Our analysis of differentially expressed genes of myeloid-derived suppressor cells isolated from bone marrow and the tumor microenvironment reveals unique gene expression patterns in the bone marrow and tumor microenvironment-derived myeloid-derived suppressor cells. It also suggests T-cell suppressive activity of myeloid-derived suppressor cells progressively increases toward the mid-to-late phase of the tumor and a significant differentiation bias of tumor site myeloid-derived suppressor cells toward macrophages, even in the presence of differentiating agents, indicating potential molecular characteristics of myeloid-derived suppressor cells in different stages of the tumor that can emerge as an intervention target.

Abstract C095: KRAS mutation subtypes are associated with clinical and phenotypic differences in pancreatic ductal adenocarcinoma

Abstract Background: KRAS is a significant driver gene for pancreatic ductal adenocarcinoma (PDAC) and is present in up to 90% of PDAC cases. KRAS mutant (mt) PDAC tends to have worse prognosis compared to KRAS wild-type (wt) PDAC. However, the clinical and biological impact of the KRAS mutation subtypes (e.g. G12D, G12R, G12V, G12C and Q61) remains unclear. We sought to explore the clinical and molecular characteristics of the KRAS mt subtypes. Methods: We performed a retrospective review of patients with KRAS mt PDAC who underwent next generation sequencing at our institution from December 1, 2018 to December 1, 2021. We collected patient demographics, disease characteristics, clinical outcomes, DNA and RNA sequencing results via chart review. Bulk RNA-seq was performed via Tempus and The Cancer Genome Atlas. Count data were processed and separated by KRAS mutation subtype using a custom python script. Differential gene expression was performed using the DifSeq2 R package. Results: A total of 158 KRAS mt patients (at diagnosis, average age 63.8 years, 57% male, 88 (56%) Stage IV) were included. 10% of patients had KRAS Q61 mutation, 14% G12R, 30% G12V and 46% G12D; only 1.1% had the potentially actionable G12C mutation. G12R had a longer overall survival (OS) compared to the others (median 24.8 vs 17.5 months (m), p=0.05). Among patients with de novo metastatic disease, G12V had the lowest OS (median 9.8 vs 12.4 m, p=0.02). Between the KRAS mt subtypes, there were no statistically significant differences in tumor mutation burden, location of PDAC or subsequent metastasis, lines of treatment (average 2.3), age at diagnosis, gender, or stage at diagnosis. One hundred thirty-seven (87%) patients had at least one pathogenic somatic variant, 14 of which had statistically significant differences between KRAS mt subtypes. 82 (52%) patients had at least one RNA expression variant and bulk RNA-seq showed that each KRAS G12 mutation subtype had unique gene expression patterns, including several oncogenes and tumor suppressor genes. Conclusions: Our data suggest that KRAS mt subtypes may confer different clinically significant phenotypes of PDAC. We found G12R to be associated with improved prognosis compared to other KRAS mt subtypes and that among patients with de novo metastatic disease, G12V had the worst prognostic implication. As there were no statistically significant differences in patient demographics between the KRAS mt subtypes, we hypothesize survival differences are driven by biological phenotype. This is supported by our RNA-seq findings, which demonstrated unique gene expression patterns for each KRAS mt subtype. Citation Format: Alexander Xiao, Jack Korleski, Ryan Carr. KRAS mutation subtypes are associated with clinical and phenotypic differences in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C095.

Bariatric surgery induces pancreatic cell transdifferentiation as indicated by single-cell transcriptomics in Zucker diabetic rats.

Bariatric surgery results in rapid recovery of glucose control in subjects with type 2 diabetes mellitus. However, the underlying mechanisms are still largely unknown. The present study aims to clarify how bariatric surgery modifies pancreatic cell subgroup differentiation and transformation in the single-cell RNA level. Male, 8-week-old Zucker diabetic fatty (ZDF) rats with obesity and diabetes phenotypes were randomized into sleeve gastrectomy (Sleeve, n = 9), Roux-en-Y gastric bypass (RYGB, n = 9), and Sham (n = 7) groups. Two weeks after surgery, the pancreas specimen was further analyzed using single-cell RNA-sequencing technique. Two weeks after surgery, compared to the Sham group, the metabolic parameters including fasting plasma glucose, plasma insulin, and oral glucose tolerance test values were dramatically improved after RYGB and Sleeve procedures (p < .05) as predicted. In addition, RYGB and Sleeve groups increased the proportion of pancreatic β cells and reduced the ratio of α cells. Two multiple hormone-expressing cells were identified, the Gcg+/Ppy + and Ins+/Gcg+/Ppy + cells. The pancreatic Ins+/Gcg+/Ppy + cells were defined for the first time, and further investigation indicates similarities with α and β cells, with unique gene expression patterns, which implies that pancreatic cell transdifferentiation occurs following bariatric surgery. For the first time, using the single-cell transcriptome map of ZDF rats, we reported a comprehensive characterization of the heterogeneity and differentiation of pancreatic endocrinal cells after bariatric surgery, which may contribute to the underlying mechanisms. Further studies will be needed to elucidate these results.

Single-cell sequencing of head and neck carcinoma: Transcriptional landscape and prognostic model based onmalignant epithelial cell features.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, and the development of novel therapeutic strategies for HNSCC requires a profound understanding of tumor cells and the tumor microenvironment (TME). Additionally, HNSCC has a poor prognosis, necessitating the use of genetic markers for predicting clinical outcomes in HNSCC. In this study, we performed single-cell sequencing analysis on tumor tissues from seven HNSCC patients, along with one adjacent normal tissue. Firstly, the analysis of epithelial cell clusters revealed two clusters of malignant epithelial cells, characterized by unique gene expression patterns and dysregulated signaling pathways compared to normal epithelial cells. Secondly, the examination of the TME unveiled extensive crosstalk between fibroblasts and malignant epithelial cells, potentially mediated through ligand-receptor interactions such as COL1A1-SDC1, COL1A1-CD44, and COL1A2-SDC1. Furthermore, transcriptional heterogeneity was observed in immune cells present in the TME, including macrophages and dendritic cells. Finally, leveraging the gene expression profiles of malignant epithelial cells, we developed a prognostic model comprising six genes, which we validated using two independent datasets. These findings shed light on the heterogeneity within HNSCC tumors and the intricate interplay between malignant cells and the TME. Importantly, the developed prognostic model demonstrates high efficacy in predicting the survival outcomes of HNSCC patients.

Expansion of CD4+ cytotoxic T lymphocytes with specific gene expression patterns may contribute to suppression of tumor immunity in oral squamous cell carcinoma: single-cell analysis and in vitro experiments.

Cancer immunotherapy targeting CD8+ T cells has made remarkable progress, even for oral squamous cell carcinoma (OSCC), a heterogeneous epithelial tumor without a substantial increase in the overall survival rate over the past decade. However, the therapeutic effects remain limited due to therapy resistance. Thus, a more comprehensive understanding of the roles of CD4+ T cells and B cells is crucial for more robust development of cancer immunotherapy. In this study, we examined immune responses and effector functions of CD4+ T cells, CD8+ T cells and B cells infiltrating in OSCC lesions using single-cell RNA sequencing analysis, T cell receptor (TCR) and B cell receptor (BCR) repertoire sequencing analysis, and multi-color immunofluorescence staining. Finally, two Kaplan-Meier curves and several Cox proportional hazards models were constructed for the survival analysis. We observed expansion of CD4+ cytotoxic T lymphocytes (CTLs) expressing granzymes, which are reported to induce cell apoptosis, with a unique gene expression patterns. CD4+ CTLs also expressed CXCL13, which is a B cell chemoattractant. Cell-cell communication analysis and multi-color immunofluorescence staining demonstrated potential interactions between CD4+ CTLs and B cells, particularly IgD- CD27- double negative (DN) B cells. Expansion of CD4+ CTLs, DN B cells, and their contacts has been reported in T and B cell-activated diseases, including IgG4-related disease and COVID-19. Notably, we observed upregulation of several inhibitory receptor genes including CTLA-4 in CD4+ CTLs, which possibly dampened T and B cell activity. We next demonstrated comprehensive delineation of the potential for CD8+ T cell differentiation towards dysfunctional states. Furthermore, prognostic analysis revealed unfavorable outcomes of patients with a high proportion of CD4+ CTLs in OSCC lesions. Our study provides a dynamic landscape of lymphocytes and demonstrates a systemic investigation of CD4+ CTL effects infiltrating into OSCC lesions, which may share some pathogenesis reported in severe T and B cell-activated diseases such as autoimmune and infectious diseases.

Characterization of glucose metabolism in high-growth performance Nile tilapia (Oreochromis niloticus)

Significant differences in growth performance have been observed in fish that have undergone the same culture cycle, even under identical conditions, including genetic background, water environment, and feeding strategy. These differences may adversely affect the harvesting and subsequent processing of commercial fish. We have previously demonstrated that the genes of glucose metabolism in high-growth performance tilapia (Oreochromis niloticus) showed significant upregulation at the transcriptome level. These findings suggested that the growth performance of tilapia may be closely related to their endogenous glucose metabolism capacity. To investigate the characteristics of glucose metabolism in high-growth performance tilapia, three full-sibling families were cultured under the same environmental and feeding conditions. The high-growth performance group (HG) and low-growth performance group (LG) were screened and compared at the biochemical and transcriptional levels during the postprandial period of 0 to 7 h. Based on biochemical analysis, HG had higher levels of intestinal lipase activity (0 to 1 h), serum triglyceride content (0 to 7 h), liver acetyl coenzyme A content (1 to 4 h), and liver glycogen content (0 to 1 h and 6 to 7 h) than LG. In contrast, HG had lower serum glucose content (0 h and 2 to 4 h), ATP content (4 to 7 h), and liver pyruvate content (3 to 4 h) than LG. There were no significant differences between HG and LG in liver ATP, intestinal α-amylase, and trypsin. We conducted a comprehensive analysis of gene expression within multiple metabolic pathways, namely the tricarboxylic acid cycle, glycolysis, pentose phosphate, glycogen metabolism, gluconeogenesis, and insulin signaling pathways, during three specific post-feeding periods: 0 to 1 h, 2–5 h, and 6 to 7 h, and revealed unique gene expression patterns related to glucose metabolic pathways in HG at different stages of post-feeding. We first revealed the endogenous glucose metabolism characteristics of high-growth performance tilapia. The findings will provide novel insights for further research on quality improvement related to growth performance in fish.

Hexagonal image segmentation on spatially resolved transcriptomics

Spatial transcriptomics is a rapidly evolving field that enables researchers to capture comprehensive molecular profiles while preserving information about the physical locations. One major challenge in this research area involves the identification of spatial domains, which are distinct regions characterized by unique gene expression patterns. However, current unsupervised methods have struggled to perform well in this regard due to the presence of high levels of noise and dropout events in spatial transcriptomic profiles. In this paper, we propose a novel hexagonal Convolutional Neural Network (hexCNN) for hexagonal image segmentation on spatially resolved transcriptomics. To address the problem of noise and dropout occurrences within spatial transcriptomics data, we first extend an unsupervised algorithm to a supervised learning method that can identify useful features and reduce noise hindrance. Then, inspired by the classical convolution in convolutional neural networks (CNNs), we designed a regular hexagonal convolution to compensate for the missing gene expression patterns from adjacent spots. We evaluated the performance of hexCNN by applying it to the DLPFC dataset. The results show that hexCNN achieves a classification accuracy of 86.8% and an average Rand index (ARI) of 77.1% (1.4% and 2.5% higher than those of GNNs). The results also demonstrate that hexCNN is capable of removing the noise caused by batch effect while preserving the biological signal differences.

Integrated analysis of single-cell transcriptome and structural biology approach reveals the dynamics changes of NP subtypes and roles of Menaquinone in attenuating intervertebral disc degeneration

Intervertebral disc degeneration (IDD) is a progressive and chronic disease, the mechanisms have been studied extensively as a whole, while the cellular heterogeneity of cells in nucleus pulposus (NP) tissues remained controversial for a long time. This study conducted integrated analysis through single-cell sequencing analysis, weighted gene co-expression network analysis (WGCNA), and differential expression analysis, to systematically decipher the longitudinal alterations of distinct NP subtypes, and also analyzed the most essential genes in the development of IDD. Then, this study further conducted structural biology method to discover the potential lead compounds through a suite of advanced approaches like high-throughput screening (HTVS), pharmaceutical characteristics assessment, CDOCKER module as well as molecular dynamics simulation, etc., aiming to ameliorate the progression of IDD. Totally 5 NP subpopulations were identified with distinct biological functions based on their unique gene expression patterns. The predominant dynamics changes mainly involved RegNPs and EffNPs, the RegNPs were mainly aggregated in normal NP tissues and drastically decreased in degenerative NP, while EffNPs, as pathogenic subtype, exhibited opposite phenomenon. Importantly, this study further reported the essential roles of Menaquinone in alleviating degenerative NP cells for the first time, which could provide solid evidence for the application of nutritional therapy in the treatment of IDD. This study combined scRNA-seq, bulk-RNA seq and HTVS techniques to systematically decipher the longitudinal changes of NP subtypes during IDD. EffNPs were considered to be ‘chief culprit’ in IDD progression, while the novel natural drug Menaquinone could reverse this phenomenon. Communicated by Ramaswamy H. Sarma

Caffeine enhances chemosensitivity to irinotecan in the treatment of colorectal cancer

Background: Colorectal cancer (CRC) is one of the most common types of cancer. This disease arises from gene mutations and epigenetic alterations that transform colonic epithelial cells into colon adenocarcinoma cells, which display a unique gene expression pattern compared to normal cells. Specifically, CRC cells exhibit significantly higher expression levels of genes involved in DNA repair or replication, which is attributed to the accumulation of DNA breakage resulting from rapid cell cycle progression.Purpose: This study aimed to investigate the in vivo effects of caffeine on CRC cells and evaluate its impact on the sensitivity of these cells to irinotecan, a topoisomerase I inhibitor widely used for CRC treatment.Methods: Two CRC cell lines, HCT116 and HT29, were treated with irinotecan and caffeine. Western blot analysis assessed protein expression levels in caffeine/irinotecan-treated CRC cells. Immunofluorescence staining determined protein localization, measured DNA breaks, and explored the effects of DNA damage reagents during cell cycle progression and flow cytometry analysis was used to measure cell viability. Fiber assays investigated DNA synthesis in DNA-damaged cells during S-phase, while the comet assay assessed DNA fragmentation caused by DNA breaks.Results: Our findings demonstrated that the combination of irinotecan and caffeine exhibits a synergistic effect in suppressing CRC cell proliferation and inducing cell death. Compared to treatment with only irinotecan or caffeine, the combined irinotecan and caffeine treatment was more effective in inducing DNA lesions by displacing RAD51 from DNA break sites and inhibiting DNA repair progression, leading to cell cycle arrest. This combination also resulted in more severe effects, including DNA fragmentation and mitotic catastrophe.Conclusion: Caffeine could enhance the effectiveness of an existing drug for CRC treatment despite having little impact on the cell survival rate of CRC cells. Our findings suggest that the beneficial adjuvant effects of caffeine may not only be applicable to CRC but also to various other types of cancers at different stages of development.

Advancing Breast Cancer Heterogeneity Analysis: Insights from Genomics, Transcriptomics and Proteomics at Bulk and Single-Cell Levels.

Breast cancer continues to pose a significant healthcare challenge worldwide for its inherent molecular heterogeneity. This review offers an in-depth assessment of the molecular profiling undertaken to understand this heterogeneity, focusing on multi-omics strategies applied both in traditional bulk and single-cell levels. Genomic investigations have profoundly informed our comprehension of breast cancer, enabling its categorization into six intrinsic molecular subtypes. Beyond genomics, transcriptomics has rendered deeper insights into the gene expression landscape of breast cancer cells. It has also facilitated the formulation of more precise predictive and prognostic models, thereby enriching the field of personalized medicine in breast cancer. The comparison between traditional and single-cell transcriptomics has identified unique gene expression patterns and facilitated the understanding of cell-to-cell variability. Proteomics provides further insights into breast cancer subtypes by illuminating intricate protein expression patterns and their post-translational modifications. The adoption of single-cell proteomics has been instrumental in this regard, revealing the complex dynamics of protein regulation and interaction. Despite these advancements, this review underscores the need for a holistic integration of multiple 'omics' strategies to fully decipher breast cancer heterogeneity. Such integration not only ensures a comprehensive understanding of breast cancer's molecular complexities, but also promotes the development of personalized treatment strategies.

Identification of cytokine-predominant immunosuppressive class and prognostic risk signatures in glioma.

The advent of immune checkpoint blockade (ICB) therapies this year has changed the way glioblastoma (GBM) is treated. Meanwhile, some patients with strong PD-L1 expression remain immune checkpoint resistant. To better understand the molecular processes that influence the immune environment, there is an urgent need to characterize the immunosuppressive tumor microenvironment and identify biomarkers to predict patient survival outcomes. Our study analyzed RNA-sequencing data from 178 GBM samples. Their unique gene expression patterns in the tumor microenvironment were analyzed by an unsupervised clustering algorithm. Through these expression patterns, a panel of T-cell exhaustion signatures, immunosuppressive cells, and clinical features correlates with immunotherapy response. The presence or absence of immune status and prognostic signatures was then validated with the test dataset. 38.2% of GBM patients showed increased expression of anti-inflammatory cytokines, significant enrichment of T cell exhaustion signals, higher proportion of immunosuppressive cells (macrophages and CD4 regulatory T cells) and nine inhibitory checkpoints (CTLA4, PDCD1, LAG3, BTLA, TIGIT, HAVCR2, IDO1, SIGLEC7, and VISTA). The immunodepleted class (IDC) was used to classify these immunocompromised individuals. Despite the high density of tumor-infiltrating lymphocytes shown by IDC, such patients have a poor prognosis. Although PD-L1 was highly expressed in IDC, it suggested that there might be ICB resistance. There are many IDC predictive signatures to discover. PD-1 is strongly expressed in a novel immunosuppressive class of GBM, but this cluster may be resistant to ICB therapy. A comprehensive description of this drug-resistant tumor microenvironment could provide new insights into drug resistance mechanisms and improved immunotherapy techniques.

Endothelial Cells Are Heterogeneous in Different Brain Regions and Are Dramatically Altered in Alzheimer's Disease.

Vascular endothelial cells play an important role in maintaining brain health, but their contribution to Alzheimer's disease (AD) is obscured by limited understanding of the cellular heterogeneity in normal aged brain and in disease. To address this, we performed single nucleus RNAseq on tissue from 32 human AD and non-AD donors (19 female, 13 male) each with five cortical regions: entorhinal cortex, inferior temporal gyrus, prefrontal cortex, visual association cortex, and primary visual cortex. Analysis of 51,586 endothelial cells revealed unique gene expression patterns across the five regions in non-AD donors. Alzheimer's brain endothelial cells were characterized by upregulated protein folding genes and distinct transcriptomic differences in response to amyloid β plaques and cerebral amyloid angiopathy. This dataset demonstrates previously unrecognized regional heterogeneity in the endothelial cell transcriptome in both aged non-AD and AD brain.SIGNIFICANCE STATEMENT In this work, we show that vascular endothelial cells collected from five different brain regions display surprising variability in gene expression. In the presence of Alzheimer's disease pathology, endothelial cell gene expression is dramatically altered with clear differences in regional and temporal changes. These findings help explain why certain brain regions appear to differ in susceptibility to disease-related vascular remodeling events that may impact blood flow.

Reactive astrogliosis in the era of single-cell transcriptomics.

Reactive astrogliosis is a reaction of astrocytes to disturbed homeostasis in the central nervous system (CNS), accompanied by changes in astrocyte numbers, morphology, and function. Reactive astrocytes are important in the onset and progression of many neuropathologies, such as neurotrauma, stroke, and neurodegenerative diseases. Single-cell transcriptomics has revealed remarkable heterogeneity of reactive astrocytes, indicating their multifaceted functions in a whole spectrum of neuropathologies, with important temporal and spatial resolution, both in the brain and in the spinal cord. Interestingly, transcriptomic signatures of reactive astrocytes partially overlap between neurological diseases, suggesting shared and unique gene expression patterns in response to individual neuropathologies. In the era of single-cell transcriptomics, the number of new datasets steeply increases, and they often benefit from comparisons and integration with previously published work. Here, we provide an overview of reactive astrocyte populations defined by single-cell or single-nucleus transcriptomics across multiple neuropathologies, attempting to facilitate the search for relevant reference points and to improve the interpretability of new datasets containing cells with signatures of reactive astrocytes.

Multi-omics-based analysis of high grade serous ovarian cancer subtypes reveals distinct molecular processes linked to patient prognosis.

Despite advancements in treatment, high-grade serous ovarian cancer (HGSOC) is still characterized by poor patient outcomes. To understand the molecular heterogeneity of this disease, which underlies the challenge in selecting optimal treatments for HGSOC patients, we have integrated genomic, transcriptomic, and epigenetic information to identify seven new HGSOC subtypes using a multiscale clustering method. These subtypes not only have significantly distinct overall survival, but also exhibit unique patterns of gene expression, microRNA expression, DNA methylation, and copy number alterations. As determined by our analysis, patients with similar clinical outcomes have distinct profiles of activated or repressed cellular processes, including cell cycle, epithelial-to-mesenchymal transition, immune activation, interferon response, and cilium organization. Furthermore, we performed a multiscale gene co-expression network analysis to identify subtype-specific key regulators and predicted optimal targeted therapies based on subtype-specific gene expression. In summary, this study provides new insights into the cellular heterogeneity of the HGSOC genomic, epigenetic, and transcriptomic landscapes and provides a basis for future studies into precision medicine for HGSOC patients.