Single-cell transcriptomic analysis reveals circadian rhythm disruption associated with poor prognosis and drug-resistance in lung adenocarcinoma

Dysregulation of R-loop homeostasis shapes the immunosuppressive microenvironment and induces malignant progression in melanoma

Dysregulated R-loop homeostasis leads to DNA replication stress and genomic instability, a major driver of cancer. However, the role of R-loops in melanoma development remains unclear. We established an R-loop scoring model based on a single-cell RNA sequencing dataset and evaluated the association between the R-loop score with the melanoma immune microenvironment and treatment response. We explored the role of CENPA-mediated changes in R-loop distribution during melanoma progression by DNA/RNA immunoprecipitation and sequencing and a series of functional experiments. We found that malignant cells with high R-loop scores may be involved in melanoma progression by modulating immune evasion, metabolic reprogramming, and cancer-related pathways. A cell communication analysis revealed that high-score R-loops play an important role in altering cell-cell interactions and limiting the CD8 + cytotoxic T cell response and T cell accumulation. CENPA silencing induced changes in R-loop distribution, upregulated Hippo signaling activity, and inhibited tumor cell proliferation and migration. Moreover, the R-loop score can predict the prognosis and immunotherapy effect of melanoma patients. Our work reveals the potential molecular mechanism by which abnormal R-loops promote melanoma progression, which may help develop anticancer therapies based on R-loops or R-loop regulators.

Multi-stage mechanisms of tumor metastasis and therapeutic strategies

The cascade of metastasis in tumor cells, exhibiting organ-specific tendencies, may occur at numerous phases of the disease and progress under intense evolutionary pressures. Organ-specific metastasis relies on the formation of pre-metastatic niche (PMN), with diverse cell types and complex cell interactions contributing to this concept, adding a new dimension to the traditional metastasis cascade. Prior to metastatic dissemination, as orchestrators of PMN formation, primary tumor-derived extracellular vesicles prepare a fertile microenvironment for the settlement and colonization of circulating tumor cells at distant secondary sites, significantly impacting cancer progression and outcomes. Obviously, solely intervening in cancer metastatic sites passively after macrometastasis is often insufficient. Early prediction of metastasis and holistic, macro-level control represent the future directions in cancer therapy. This review emphasizes the dynamic and intricate systematic alterations that occur as cancer progresses, illustrates the immunological landscape of organ-specific PMN creation, and deepens understanding of treatment modalities pertinent to metastasis, thereby identifying some prognostic and predictive biomarkers favorable to early predict the occurrence of metastasis and design appropriate treatment combinations.

Complement Factor B (CFB) inhibits the malignant progression of lung adenocarcinoma by downregulating the Ras/MAPK signaling pathway

Lung adenocarcinoma (LUAC) as the most common lung cancer, and its incidence is increasing. Complement factor B (CFB) is an important factor in the alternative complement pathway. CFB has been reported to be involved in the progression of many cancers, including in pancreatic cancer, cutaneous squamous cell carcinoma, and nasopharyngeal carcinoma, but the function and molecular mechanism of CFB in LUAC remains unclear. The present study aimed to explore the role of CFB in LUAC malignant progression. In our previous study, we found that CFB was downregulated expression in LUAC clinical samples. Here, we firstly detected the cell function in vitro. Cell proliferation and migration were increased, while cell apoptosis and cell cycle arrest were suppressed after CFB knockdown. Overexpression of CFB repressed the malignant progression of LUAC in vitro. Besides, in vivo experiments revealed that upregulation of CFB inhibited tumor growth and Ki67 expression. Additionally, our data indicated that CFB negatively regulated Ras/mitogen-activated protein kinase (MAPK) signaling pathway. Furthermore, upregulation of CFB inhibited the progression of LUAC was reversed by Ras/MAPK pathway activators (ML-098 or C16-PAF). Our study uncovered that CFB acts as a tumor suppressor repressed tumorigenesis of LUAC through inhibiting the Ras/MAPK pathway, suggesting that CFB may be a potential biomarker and therapeutic target for LUAC.

Melatonin reverses EGFR-TKI therapeutic resistance by modulating crosstalk between circadian-related gene signature and immune infiltration patterns in patients with COVID-19 and lung adenocarcinoma

BACKGROUND

Patients with lung cancer exhibit the poorest outcomes when infected with coronavirus disease 2019 (COVID-19). However, the potential impact of COVID-19 on the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) remains unknown.

METHODS

Expression data and clinical information were sourced from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Prognostic, differentially expressed circadian-related genes (CRGs) were identified using multivariate Cox regression and LASSO regression analyses to establish an immune-related gene signature. The clinical value, immune landscape, somatic mutations, and drug sensitivity of high- and low-risk groups were assessed using Kaplan-Meier curves and immunotherapy cohorts. Finally, in vitro and in vivo experiments were conducted to elucidate the molecular function of melatonin in regulating the immune microenvironment and therapeutic resistance.

RESULTS

Three circadian-related patterns and distinct CRGs clusters were identified based on the abnormal expression of 13 CRGs. Circadian genomic phenotypes were identified based on 13 circadian phenotype-related differentially expressed genes (DEGs). A CRGs risk signature was constructed; the high CRGs risk group displayed an immunosuppressive TME, poor survival, and therapy resistance. Melatonin reversed EGFR-tyrosine kinase inhibitor (EGFR-TKI) resistance by regulating immune cell infiltration into the TME, both in vitro and in vivo.

CONCLUSIONS

The investigation revealed crosstalk between CRGs signatures and immune infiltration patterns in LUAD and COVID-19. Melatonin acted as a promising agent to suppress the malignant features of lung cancer and enhance treatment sensitivity by modulating the TME.

Disruption of Circadian Clock Induces Abnormal Mammary Morphology and Aggressive Basal Tumorigenesis by Enhancing LILRB4 Signaling

Epidemiological studies have shown that circadian rhythm disruption (CRD) is associated with the risk of breast cancer. However, the role of CRD in mammary gland morphology and aggressive basal mammary tumorigenesis and the molecular mechanisms underlying CRD and cancer risk remain unknown. To investigate the effect of CRD on aggressive tumorigenesis, a genetically engineered mouse model that recapitulates the human basal type of breast cancer was used for this study. The effect of CRD on mammary gland morphology was investigated using wild-type mice model. The impact of CRD on the tumor microenvironment was investigated using the tumors from LD12:12 and CRD mice via scRNA seq. ScRNA seq was substantiated by multiplexing immunostaining, flow cytometry, and realtime PCR. The effect of LILRB4 immunotherapy on CRD-induced tumorigenesis was also investigated. Here we identified the impact of CRD on basal tumorigenesis and mammary gland morphology and identified the role of LILRB4 on CRD-induced lung metastasis. We found that chronic CRD disrupted mouse mammary gland morphology and increased tumor burden, and lung metastasis and induced an immunosuppressive tumor microenvironment by enhancing LILRB4a expression. Moreover, CRD increased the M2-macrophage and regulatory T-cell populations but decreased the M1-macrophage, and dendritic cell populations. Furthermore, targeted immunotherapy against LILRB4 reduced CRD-induced immunosuppressive microenvironment and lung metastasis. These findings identify and implicate LILRB4a as a link between CRD and aggressive mammary tumorigenesis. This study also establishes the potential role of the targeted LILRB4a immunotherapy as an inhibitor of CRD-induced lung metastasis.

NPAS2, transcriptionally activated by ARRB1, promotes the malignant behaviours of lung adenocarcinoma cells and regulates the reprogramming of glucose metabolism

Lung adenocarcinoma (LUAD) is a serious threat to public health and is accompanied by increased morbidity and mortality worldwide. Neuronal PAS domain protein2 (NPAS2) has been confirmed as an oncogene in LUAD; however, little is known about its molecular mechanism. Here, the expression level of NPAS2 was detected in LUAD cell lines and 16HBE cells. Gain- and loss-of-function experiments were performed. Cell Counting Kit-8, colony formation, flow cytometry, wound-healing and Transwell assays were conducted to assess cell proliferation, apoptosis, migration and invasion, respectively. Reprogramming of glucose metabolism was evaluated via oxygen consumption rate (OCR), complexes activities, lactic production and glucose consumption. The expression of critical proteins was examined by western blot. We demonstrated aberrant upregulation of NPAS2 and β-arrestin-1 (ARRB1) in LUAD cell lines. ARRB1 was found to be a critical transcription factor of NPAS2 with binding sites within the promoter region of NPAS2, thereby causing its transcriptional activation. Functional experiments revealed that NPAS2 depletion significantly inhibited the malignant behaviours of A549 cells by suppressing cell proliferation, migration, invasion and epithelial-mesenchymal transition and promoting cell apoptosis. Meanwhile, NPAS2 depletion increased OCR and activities of complexes (I, II, III and V), and reduced lactic acid production and glucose uptake in A549 cells, indicating that NPAS2 depletion inhibited aerobic glycolysis, accompanied by reduced expression of glycolytic enzymes. However, the changes caused by NPAS2 knockdown were partly restored by ARRB1 overexpression. In conclusion, our study suggests that ARRB1 could transcriptionally activate NPAS2, facilitating malignant activities and glycolysis, and ultimately promoting the progression of LUAD, proving a novel therapeutic strategy for the treatment of LUAD.

Circadian rhythm regulates the function of immune cells and participates in the development of tumors

Circadian rhythms are present in almost all cells and play a crucial role in regulating various biological processes. Maintaining a stable circadian rhythm is essential for overall health. Disruption of this rhythm can alter the expression of clock genes and cancer-related genes, and affect many metabolic pathways and factors, thereby affecting the function of the immune system and contributing to the occurrence and progression of tumors. This paper aims to elucidate the regulatory effects of BMAL1, clock and other clock genes on immune cells, and reveal the molecular mechanism of circadian rhythm's involvement in tumor and its microenvironment regulation. A deeper understanding of circadian rhythms has the potential to provide new strategies for the treatment of cancer and other immune-related diseases.

Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing

Tumor immune microenvironment (TIME) and its indications for lung cancer patient prognosis and therapeutic response have become new hotspots in cancer research in recent years. Tumor cells, immune cells, various regulatory factors, and their interactions in the TIME have been suggested to commonly influence lung cancer development and therapeutic outcome. The heterogeneity of TIME is composed of dynamic immune-related components, including various cancer cells, immune cells, cytokine/chemokine environments, cytotoxic activity, or immunosuppressive factors. The specific composition of cell subtypes may facilitate or hamper the response to immunotherapy and influence patient prognosis. Various markers have been found to stratify the patient prognosis or predict the therapeutic outcome. In this article, we systematically reviewed the recent advancement of TIME studies in lung adenocarcinoma (LUAD) using single-cell RNA sequencing (scRNA-seq) techniques, with specific focuses on the roles of TIME in LUAD development, TIME heterogeneity, indications of TIME in patient prognosis and therapeutic response during immunotherapy and drug resistance. The main findings in TIME heterogeneity and relevant markers or models for prognosis stratification and response prediction have been summarized. We hope that this review provides an overview of TIME status in LUAD and an inspiration for future development of strategies and biomarkers in LUAD treatment.

A signature based on circadian rhythm-associated genes for the evaluation of prognosis and the tumour microenvironment in HNSCC

The morbidity and mortality rates of head and neck squamous cell carcinoma (HNSCC) remain high worldwide. Therefore, there is an urgent need to identify a new prognostic biomarker to guide the personalized treatment of HNSCC patients. Increasing evidence suggests that circadian rhythm genes play an important role in the development and progression of cancer. We aimed to explore the value of circadian rhythm genes in predicting prognosis and guiding the treatment of HNSCC. We first obtained a list of circadian rhythm genes from previous research. The sequencing data were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Finally, univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox proportional hazard analysis were performed to develop a prognostic signature (Circadian Rhythm-Related Gene Prognostic Index, CRRGPI) consisting of nine circadian rhythm genes. The signature exhibited good performance in predicting overall survival. Patients with low CRRGPI scores had lower metabolic activities and an active antitumour immunity ability. Additionally, a clinical cohort was used to further evaluate the ability of the CRRGPI to predict the efficacy of immune checkpoint inhibitors. In conclusion, the novel circadian rhythm-related gene signature can provide a precise prognostic evaluation with the potential capacity to guide individualized treatment regimens for HNSCC patients.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma

BACKGROUND

Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD).

METHODS

Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS).

RESULTS

This study identified TIME-related lncRNAs from integrated analysis of single‑cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy.

CONCLUSIONS

This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Melatonin and Its Role in the Epithelial-to-Mesenchymal Transition (EMT) in Cancer

The epithelial-to-mesenchymal transition (EMT) is a cell-biological program that occurs during the progression of several physiological processes and that can also take place during pathological situations such as carcinogenesis. The EMT program consists of the sequential activation of a number of intracellular signaling pathways aimed at driving epithelial cells toward the acquisition of a series of intermediate phenotypic states arrayed along the epithelial-mesenchymal axis. These phenotypic features include changes in the motility, conformation, polarity and functionality of cancer cells, ultimately leading cells to stemness, increased invasiveness, chemo- and radioresistance and the formation of cancer metastasis. Amongst the different existing types of the EMT, type 3 is directly involved in carcinogenesis. A type 3 EMT occurs in neoplastic cells that have previously acquired genetic and epigenetic alterations, specifically affecting genes involved in promoting clonal outgrowth and invasion. Markers such as E-cadherin; N-cadherin; vimentin; and transcription factors (TFs) like Twist, Snail and ZEB are considered key molecules in the transition. The EMT process is also regulated by microRNA expression. Many miRNAs have been reported to repress EMT-TFs. Thus, Snail 1 is repressed by miR-29, miR-30a and miR-34a; miR-200b downregulates Slug; and ZEB1 and ZEB2 are repressed by miR-200 and miR-205, respectively. Occasionally, some microRNA target genes act downstream of the EMT master TFs; thus, Twist1 upregulates the levels of miR-10b. Melatonin is an endogenously produced hormone released mainly by the pineal gland. It is widely accepted that melatonin exerts oncostatic actions in a large variety of tumors, inhibiting the initiation, progression and invasion phases of tumorigenesis. The molecular mechanisms underlying these inhibitory actions are complex and involve a great number of processes. In this review, we will focus our attention on the ability of melatonin to regulate some key EMT-related markers, transcription factors and micro-RNAs, summarizing the multiple ways by which this hormone can regulate the EMT. Since melatonin has no known toxic side effects and is also known to help overcome drug resistance, it is a good candidate to be considered as an adjuvant drug to conventional cancer therapies.

Prognostic stratification of sepsis through DNA damage response based RiskScore system: insights from single-cell RNA-sequencing and transcriptomic profiling

Background

A novel risk scoring system, predicated on DNA damage response (DDR), was developed to enhance prognostic predictions and potentially inform the creation of more effective therapeutic protocols for sepsis.

Methods

To thoroughly delineate the expression profiles of DDR markers within the context of sepsis, an analytical approach utilizing single-cell RNA-sequencing (scRNA-seq) was implemented. Our study utilized single-cell analysis techniques alongside weighted gene co-expression network analysis (WGCNA) to pinpoint the genes that exhibit the most substantial associations with DNA damage response (DDR). Through Cox proportional hazards LASSO regression, we distinguished DDR-associated genes and established a risk model, enabling the stratification of patients into high- and low-risk groups. Subsequently, we carried out an analysis to determine our model's predictive accuracy regarding patient survival. Moreover, we examined the distinct biological characteristics, various signal transduction routes, and immune system responses in sepsis patients, considering different risk categories and outcomes related to survival. Lastly, we conducted experimental validation of the identified genes through in vivo and in vitro assays, employing RT-PCR, ELISA, and flow cytometry.

Results

Both single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses have demonstrated a strong correlation between DNA damage response (DDR) levels and sepsis prognosis. Specific cell subtypes, including monocytes, megakaryocytes, CD4+ T cells, and neutrophils, have shown elevated DDR activity. Cells with increased DDR scores exhibited more robust and numerous interactions with other cell populations. The weighted gene co-expression network analysis (WGCNA) and single-cell analyses revealed 71 DDR-associated genes. We developed a four-gene risk scoring system using ARL4C, CD247, RPL7, and RPL31, identified through univariate COX, LASSO COX regression, and log-rank (Mantel-Cox) tests. Nomograms, calibration plots, and decision curve analyses (DCA) regarding these specific genes have provided significant clinical benefits for individuals diagnosed with sepsis. The study suggested that individuals categorized as lower-risk demonstrated enhanced infiltration of immune cells, upregulated expression of immune regulators, and a more prolific presence of immune-associated functionalities and pathways. RT-qPCR analyses on a sepsis rat model revealed differential gene expression predominantly in the four targeted genes. Furthermore, ARL4C knockdown in sepsis model in vivo and vitro caused increased inflammatory response and a worse prognosis.

Conclusion

The delineated DDR expression landscape offers insights into sepsis pathogenesis, whilst our riskScore model, based on a robust four-gene signature, could underpin personalized sepsis treatment strategies.

Deciphering the immune modulation through deep transcriptomic profiling and therapeutic implications of DNA damage repair pattern in hepatocellular carcinoma

AIMS

DNA damage repair (DDR) plays a pivotal role in hepatocellular carcinoma (HCC), driving oncogenesis, progression, and therapeutic response. However, the mechanisms of DDR mediated immune cells and immuno-modulatory pathways in HCC are yet ill-defined.

METHODS

Our study introduces an innovative deep machine learning framework for precise DDR assessment, utilizing single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data. Single-cell RNA sequencing data were obtained and in total 85,628 cells of primary or post-immunotherapy cases were analyzed. Large-scale HCC datasets, including 1027 patients in house together with public datasets, were used for 101 machine-learning models and a novel DDR feature was derived at single-cell resolution (DDRscore). Druggable targets were predicted using the reverse phase protein array (RPPA) proteomic profiling of 169 HCC patients and RNA-seq data from 22 liver cancer cell lines.

RESULTS

Our investigation reveals a dynamic interplay of DDR with natural killer cells and B cells in the primary HCC microenvironment, shaping a tumor-promoting immune milieu through metabolic programming. Analysis of HCC post-immunotherapy demonstrates elevated DDR levels that induces epithelial-mesenchymal transition and fibroblast-like transformation, reshaping the fibrotic tumor microenvironment. Conversely, attenuated DDR promotes antigen cross-presentation by dendritic cells and CD8+ T cells, modulating the inflammatory tumor microenvironment. Regulatory network analysis identifies the CXCL10-CXCR3 axis as a key determinant of immunotherapeutic response in low DDR HCC, potentially regulated by transcription factors GATA3, REL, and TBX21. Using machine learning techniques by combining bulk RNA-seq data in house together with public datasets, we introduce DDRscore, a robust consensus DDR scoring system to predict overall survival and resistance to PD-1 therapy in HCC patients. Finally, we identify BRAF as a potential therapeutic target for high DDRscore patients.

CONCLUSION

Our comprehensive findings advance our understanding of DDR and the tumor microenvironment in HCC, providing insights into immune regulatory mechanisms mediated via DDR pathways.

Aberrant R-loop-mediated immune evasion, cellular communication, and metabolic reprogramming affect cancer progression: a single-cell analysis

Dysregulation of R-loop homeostasis is closely related to various human diseases, including cancer. However, the causality of aberrant R-loops in tumor progression remains unclear. In this study, using single-cell RNA-sequencing datasets from lung adenocarcinoma (LUAD), we constructed an R-loop scoring model to characterize the R-loop state according to the identified R-loop regulators related to EGFR mutations, tissue origins, and TNM stage. We then evaluated the relationships of the R-loop score with the tumor microenvironment (TME) and treatment response. Furthermore, the potential roles of FANCI-mediated R-loops in LUAD were explored using a series of in vitro experiments. Results showed that malignant cells with low R-loop scores displayed glycolysis and epithelial-mesenchymal transition pathway activation and immune escape promotion, thereby hampering the antitumor therapeutic effects. Cell communication analysis suggested that low R-loop scores contributed to T cell exhaustion. We subsequently validated the prognostic value of R-loop scores by using bulk transcriptome datasets across 33 tumor types. The R-loop scoring model well predicted patients' therapeutic response to targeted therapy, chemotherapy, or immunotherapy in 32 independent cohorts. Remarkably, changes in R-loop distribution mediated by FANCI deficiency blocked the activity of Ras signaling pathway, suppressing tumor-cell proliferation and dissemination. In conclusion, this study reveals the underlying molecular mechanism of metabolic reprogramming and T cell exhaustion under R-loop score patterns, and the changes in R-loops mediated by R-loop regulators resulting in tumor progression. Therefore, incorporating anticancer methods based on R-loop or R-loop regulators into the treatment schemes of precision medicine may be beneficial.

Multi-omics and single-cell sequencing analyses reveal the potential significance of circadian pathways in cancer therapy

BACKGROUND

Circadian rhythm disturbance is an independent risk factor for cancer. However, few studies have been reported on circadian rhythm related genes (CRGs) in cancer, so it is important to further explore the impact of CRGs in pan-cancer.

RESEARCH DESIGN AND METHODS

The Cancer Genome Atlas database was used to collect cancer-related data such as copy number variation, single nucleotide variants, methylation, and survival differences. Immunohistochemistry (IHC) was used to verify the expression of circadian rhythm hub genes. The circadian pathway scores (CRS) were calculated using single-sample gene enrichment analysis. TIMER and GEPIA databases were used for immune-cell integration and assessment. Single-cell sequencing data was used to evaluate the abundance of CRS in tumor microenvironment cells.

RESULTS

In this study, we found that the expression of circadian pathway varies between tumors. CSNK1E was significantly up-regulated in most tumors and CRY2 was significantly down-regulated in most tumors. The protein interaction network suggested CRY2 as the core gene and IHC verified its significant low expression in KIRC. In addition, CRGs were found to be protective factors in most tumors and have the potential to act as specific immune markers in different tumors. CRS was significantly lower in abundance in most tumors. CRS was significantly associated with overall survival in tumor patients and associated with the expression of many immune cells in the tumor immune microenvironment. CRS is significantly associated with tumor mutational burden and microsatellite instability scores in most tumors and may serve as a potential immunotherapeutic marker.

CONCLUSIONS

The circadian rhythm pathway may be a breakthrough point in regulating the tumor microenvironment meanwhile a suitable immunotherapy method in the future.

Neutrophil extracellular traps regulating tumorimmunity in hepatocellular carcinoma

As a component of the innate immune system, there is emerging evidence to suggest that neutrophils may play a critical role in the initiation and progression of hepatocellular carcinoma (HCC). Neutrophil extracellular traps (NETs) are web-like chromatin structures that protrude from the membranes during neutrophil activation. Recent research has shown that NETs, which are at the forefront of the renewed interest in neutrophil studies, are increasingly intertwined with HCC. By exploring the mechanisms of NETs in HCC, we aim to improve our understanding of the role of NETs and gain deeper insights into neutrophil biology. Therefore, this article provides a summary of key findings and discusses the emerging field of NETs in HCC.

Leveraging a KRAS-based signature to predict the prognosis and drug sensitivity of colon cancer and identifying SPINK4 as a new biomarker

KRAS is one of the leading mutations reported in colon cancer. However, there are few studies on the application of KRAS related signature in predicting prognosis and drug sensitivity of colon cancer patient. We identified KRAS related differentially expressed genes (DEGs) using The Cancer Genome Atlas (TCGA) database. A signature closely related to overall survival was recognized with Kaplan-Meier survival analysis and univariate cox regression analysis. Then we validated this signature with overall expression score (OE score) algorithm using both scRNA-seq and bulk RNA-seq data. Based on this signature, we performed LASSO cox regression to establish a prognostic model, and corresponding scores were calculated. Differences in genomic alteration, immune microenvironment, drug sensitivity between high- and low-KRD score groups were investigated. A KRAS related signature composed of 80 DEGs in colon cancer were recognized, among which 19 genes were selected to construct a prognostic model. This KRAS related signature was significantly correlated with worse prognosis. Furthermore, patients who scored lower in the prognostic model presented a higher likelihood of responding to chemotherapy, targeted therapy and immunotherapy. Furthermore, among the 19 selected genes in the model, SPINK4 was identified as an independent prognostic biomarker. Further validation in vitro indicated the knockdown of SPINK4 promoted the proliferation and migration of SW48 cells. In conclusion, a novel KRAS related signature was identified and validated based on clinical and genomic information from TCGA and GEO databases. The signature was proved to regulate genomic alteration, immune microenvironment and drug sensitivity in colon cancer, and thus might serve as a predictor for individual prognosis and treatment.

A three-gene random forest model for diagnosing idiopathic pulmonary fibrosis based on circadian rhythm-related genes in lung tissue

BACKGROUND

The disorder of circadian rhythm could be a key factor mediating fibrotic lung disease Therefore, our study aims to determine the diagnostic value of circadian rhythm-related genes (CRRGs) in IPF.

METHODS

We retrieved the data on CRRGs from previous studies and the GSE150910 dataset. The participants from the GSE150910 dataset were divided into training and internal validation sets. Next, we used several various bioinformatics methods and machine learning algorithms to screen genes. Next, we identified SEMA5A, COL7A1, and TUBB3, which were included in the random forest (RF) diagnostic model. Finally, external validation was conducted on data retrieved from the GSE184316 datasets.

RESULTS

The results revealed that the RF diagnostic model could diagnose patients with IPF in the internal validation set with the area under the ROC curve (AUC) value of 0.905 and in the external validation with the AUC value of 0.767. Furthermore, real-time quantitative PCR and western blotting results revealed a significant decrease in SEMA5A (p < 0.05) expression level and an increase in COL7A1 and TUBB3 expression levels in TGF-β1-treated normal human lung fibroblasts.

CONCLUSION

We constructed an RF diagnostic model based on SEMA5A, COL7A1, and TUBB3 expression in lung tissue for diagnosing patients with IPF.

Time-restricted feeding affects the fecal microbiome metabolome and its diurnal oscillations in lung cancer mice

The homeostasis of the gut microbiota and circadian rhythm is critical to host health, and both are inextricably intertwined with lung cancer. Although time-restricted feeding (TRF) can maintain circadian synchronization and improve metabolic disorders, the effects of TRF on the fecal microbiome, metabolome and their diurnal oscillations in lung cancer have not been discussed. We performed 16S rRNA sequencing and untargeted metabonomic sequencing of the feces prepared from models of tumor-bearing BALB/c nude mice and urethane-induced lung cancer. We demonstrated for the first time that TRF significantly delayed the growth of lung tumors. Moreover, TRF altered the abundances of the fecal microbiome, metabolome and circadian clocks, as well as their rhythmicity, in lung cancer models of tumor-bearing BALB/c nude mice and/or urethane-induced lung cancer C57BL/6J mice. The results of fecal microbiota transplantation proved that the antitumor effects of TRF occur by regulating the fecal microbiota. Notably, Lactobacillus and Bacillus were increased upon TRF and were correlated with most differential metabolites. Pathway enrichment analysis of metabolites revealed that TRF mainly affected immune and inflammatory processes, which might further explain how TRF exerted its anticancer benefits. These findings underscore the possibility that the fecal microbiome/metabolome regulates lung cancer following a TRF paradigm.

Hsa-miR-503-5p regulates CTDSPL to accelerate cisplatin resistance and angiogenesis of lung adenocarcinoma cells

The study aimed to assess the role of hsa-miR-503-5p in cisplatin resistance and angiogenesis in LUAD and its underlying mechanisms. Hsa-miR-503-5p expression in LUAD and the target gene downstream of hsa-miR-503-5p was predicted by bioinformatics analysis. Binding relationship between the two genes was verified by dual-luciferase reporter assay. qRT-PCR was conducted for detecting gene expression in cells, CCK-8 for IC50 value, angiogenesis assay for human umbilical vein endothelial cell (HUVEC) angiogenic ability, flow cytometry for apoptosis ability, transwell assay for migration ability, and western blot for detecting the protein expression of vascular endothelial growth factor receptor 1 (VEGFR1), VEGFR2, and CTD small phosphatase like (CTDSPL). The results showed that hsa-miR-503-5p showed high expression, while its target gene CTDSPL presented decreased expression in LUAD. Hsa-miR-503-5p also had high expression in cisplatin-resistant LUAD cells. Knockdown of hsa-miR-503-5p resensitized LUAD cells to cisplatin, inhibited angiogenesis of drug-resistant cells, and reduced the protein expression of VEGFR1, VEGFR2, and EMT-related targets in cisplatin-resistant LUAD cells, but promoted the apoptosis ability. Hsa-miR-503-5p bound to CTDSPL gene and promoted cisplatin resistance and malignant progression of LUAD cells by negatively regulating CTDSPL. Our results revealed that hsa-miR-503-5p and CTDSPL may be novel targets for overcoming cisplatin resistance in LUAD.

Functional status analysis of RNH1 in bladder cancer for predicting immunotherapy response

Bladder cancer (BLCA) typically has a poor prognosis due to high rates of relapse and metastasis. Although the emergence of immunotherapy brings hope for patients with BLCA, not all patients will benefit from it. Identifying some markers to predict treatment response is particularly important. Here, we aimed to determine the clinical value of the ribonuclease/angiogenin inhibitor 1 (RNH1) in BLCA therapy based on functional status analysis. First, we found that RNH1 is aberrantly expressed in multiple cancers but is associated with prognosis in only a few types of cancer. Next, we determined that low RNH1 expression was significantly associated with enhanced invasion and metastasis of BLCA by assessing the relationship between RNH1 and 17 functional states. Moreover, we identified 95 hub genes associated with invasion and metastasis among RNH1-related genes. Enrichment analysis revealed that these hub genes were also significantly linked with immune activation. Consistently, BLCA can be divided into two molecular subtypes based on these hub genes, and the differentially expressed genes between the two subtypes are also significantly enriched in immune-related pathways. This indicates that the expression of RNH1 is also related to the tumour immune response. Subsequently, we confirmed that RNH1 shapes an inflammatory tumour microenvironment (TME), promotes activation of the immune response cycle steps, and has the potential to predict the immune checkpoint blockade (ICB) treatment response. Finally, we demonstrated that high RNH1 expression was significantly associated with multiple therapeutic signalling pathways and drug targets in BLCA. In conclusion, our study revealed that RNH1 could provide new insights into the invasion of BLCA and predict the immunotherapy response in patients with BLCA.

Integrative analysis of circadian clock with prognostic and immunological biomarker identification in ovarian cancer

Objective: To identify circadian clock (CC)-related key genes with clinical significance, providing potential biomarkers and novel insights into the CC of ovarian cancer (OC). Methods: Based on the RNA-seq profiles of OC patients in The Cancer Genome Atlas (TCGA), we explored the dysregulation and prognostic power of 12 reported CC-related genes (CCGs), which were used to generate a circadian clock index (CCI). Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were used to identify potential hub genes. Downstream analyses including differential and survival validations were comprehensively investigated. Results: Most CCGs are abnormally expressed and significantly associated with the overall survival (OS) of OC. OC patients with a high CCI had lower OS rates. While CCI was positively related to core CCGs such as ARNTL, it also showed significant associations with immune biomarkers including CD8⁺ T cell infiltration, the expression of PDL1 and CTLA4, and the expression of interleukins (IL-16, NLRP3, IL-1β, and IL-33) and steroid hormones-related genes. WGCNA screened the green gene module to be mostly correlated with CCI and CCI group, which was utilized to construct a PPI network to pick out 15 hub genes (RNF169, EDC4, CHCHD1, MRPL51, UQCC2, USP34, POM121, RPL37, SNRPC, LAMTOR5, MRPL52, LAMTOR4, NDUFB1, NDUFC1, POLR3K) related to CC. Most of them can exert prognostic values for OS of OC, and all of them were significantly associated with immune cell infiltration. Additionally, upstream regulators including transcription factors and miRNAs of key genes were predicted. Conclusion: Collectively, 15 crucial CC genes showing indicative values for prognosis and immune microenvironment of OC were comprehensively identified. These findings provided insight into the further exploration of the molecular mechanisms of OC.

Construction of a CCL20-centered circadian-signature based prognostic model in cervical cancer

BACKGROUND

Rather low vaccination rates for Human papillomavirus (HPV) and pre-existing cervical cancer patients with limited therapeutic strategies ask for more precise prognostic model development. On the other side, the clinical significance of circadian clock signatures in cervical cancer lacks investigation.

METHODS

Subtypes classification based upon eight circadian clock core genes were implemented in TCGA-CESC through k-means clustering methods. Afterwards, KEGG, GO and GSEA analysis were conducted upon differentially expressed genes (DEGs) between high and low-risk groups, and tumor microenvironment (TME) investigation by CIBERSORT and ESTIMATE. Furthermore, a prognostic model was developed by cox and lasso regression methods, and verified in GSE44001 by time-dependent receiver-operating characteristic curve (ROC) analysis. Lastly, FISH and IHC were used for validation of CCL20 expression in patients' specimens and U14 subcutaneous tumor models were built for TME composition.

RESULTS

We successfully classified cervical patients into high-risk and low-risk groups based upon circadian-oscillation-signatures. Afterwards, we built a prognostic risk model composed of GJB2, CCL20 and KRT24 with excellent predictive value on patients' overall survival (OS). We then proposed metabolism unbalance, especially for glycolysis, and immune related pathways to be major enriched signatures between the high-risk and low-risk groups. Then, we proposed an 'immune-desert'-like suppressive myeloid cells infiltration pattern in high-risk group TME and verified its resistance to immunotherapies. Finally, CCL20 was proved positively correlated with real-world patients' stages and induced significant less CD8⁺ T cells and more M2 macrophages infiltration in mouse model.

CONCLUSIONS

We unraveled a prognostic risk model based upon circadian oscillation and verified its solidity. Specifically, we unveiled distinct TME immune signatures in high-risk groups.

Combined analysis of single-cell and bulk RNA sequencing reveals the expression patterns of circadian rhythm disruption in the immune microenvironment of Alzheimer's disease

Background

Circadian rhythm disruption (CRD) represents a critical contributor to the pathogenesis of Alzheimer's disease (AD). Nonetheless, how CRD functions within the AD immune microenvironment remains to be illustrated.

Methods

Circadian rhythm score (CRscore) was utilized to quantify the microenvironment status of circadian disruption in a single-cell RNA sequencing dataset derived from AD. Bulk transcriptome datasets from public repository were employed to validate the effectiveness and robustness of CRscore. A machine learning-based integrative model was applied for constructing a characteristic CRD signature, and RT-PCR analysis was employed to validate their expression levels.

Results

We depicted the heterogeneity in B cells, CD4⁺ T cells, and CD8⁺ T cells based on the CRscore. Furthermore, we discovered that CRD might be strongly linked to the immunological and biological features of AD, as well as the pseudotime trajectories of major immune cell subtypes. Additionally, cell-cell interactions revealed that CRD was critical in the alternation of ligand-receptor pairs. Bulk sequencing analysis indicated that the CRscore was found to be a reliable predictive biomarker in AD patients. The characteristic CRD signature, which included 9 circadian-related genes (CRGs), was an independent risk factor that accurately predicted the onset of AD. Meanwhile, abnormal expression of several characteristic CRGs, including GLRX, MEF2C, PSMA5, NR4A1, SEC61G, RGS1, and CEBPB, was detected in neurons treated with Aβ1-42 oligomer.

Conclusion

Our study revealed CRD-based cell subtypes in the AD microenvironment at single-cell level and proposed a robust and promising CRD signature for AD diagnosis. A deeper knowledge of these mechanisms may provide novel possibilities for incorporating "circadian rhythm-based anti-dementia therapies" into the treatment protocols of individualized medicine.

CRS: a circadian rhythm score model for predicting prognosis and treatment response in cancer patients

BACKGROUND

Circadian rhythm regulates complex physiological activities in organisms. A strong link between circadian dysfunction and cancer has been identified. However, the factors of dysregulation and functional significance of circadian rhythm genes in cancer have received little attention.

METHODS

In 18 cancer types from The Cancer Genome Atlas (TCGA), the differential expression and genetic variation of 48 circadian rhythm genes (CRGs) were examined. The circadian rhythm score (CRS) model was created using the ssGSEA method, and patients were divided into high and low groups based on the CRS. The Kaplan-Meier curve was created to assess the patient survival rate. Cibersort and estimate methods were used to identify the infiltration characteristics of immune cells between different CRS subgroups. Gene Expression Omnibus (GEO) dataset is used as verification queue and model stability evaluation queue. The CRS model's ability to predict chemotherapy and immunotherapy was assessed. Wilcoxon rank-sum test was used to compare the differences of CRS among different patients. We use CRS to identify potential "clock-drugs" by the connective map method.

RESULTS

Transcriptomic and genomic analyses of 48 CRGs revealed that most core clock genes are up-regulated, while clock control genes are down-regulated. Furthermore, we show that copy number variation may affect CRGs aberrations. Based on CRS, patients can be classified into two groups with significant differences in survival and immune cell infiltration. Further studies showed that patients with low CRS were more sensitive to chemotherapy and immunotherapy. Additionally, we identified 10 compounds (e.g. flubendazole, MLN-4924, ingenol) that are positively associated with CRS, and have the potential to modulate circadian rhythms.

CONCLUSIONS

CRS can be utilized as a clinical indicator to predict patient prognosis and responsiveness to therapy, and identify potential "clock-drugs".

Anterior gradient-2 regulates cell communication by coordinating cytokine-chemokine signaling and immune infiltration in breast cancer

Anterior gradient-2 (AGR2) is crucial to breast cancer progression. However, its role in the tumor immune microenvironment remains unclear. RNA sequencing expression profiles and associated clinical information were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. The AGR2 expression patterns were verified using clinical samples of breast cancer. Based on single-cell transcriptomic data, AGR2 expression patterns were identified and cell communication analysis was carried out. Furthermore, the roles of AGR2 in breast tumor progression were explored by a series of functional experiments. We found that DNA methylation was an important mechanism for regulating the expression patterns of AGR2. Patients with AGR2 low expression displayed an immune "hot" and immunosuppressive phenotype characterized by high abundance of tumor immune cell infiltration and increased enrichment scores for transforming growth factor-β (TGF-β) and epithelial-mesenchymal transition pathways, whereas patients with AGR2 high expression showed an opposite immunologic feature with a lack of immune cell infiltration, suggestive of an immune "cold" and desert phenotype. Moreover, single-cell analysis further revealed that AGR2 in malignant cells alters cell-cell interactions by coordinating cytokine-chemokine signaling and immune infiltration. Notably, two immunotherapy cohorts revealed that AGR2-coexpressed genes could serve as prognostic indicators of patient survival. In conclusion, AGR2 could promote breast cancer progression by affecting the tumor immune microenvironment. Patients with AGR2 low expression could be suitable for combination treatment with immune checkpoint inhibitor agents and TGF-β blockers. Therefore, this study provides a theoretical foundation for developing a strategy for personalized immunotherapy to patients with breast cancer.

A circadian rhythm-related biomarker for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains a major reason of cancer-associated mortality globally, and there exists a lack of indicators for survival in LUAD patients. Therefore, it is clinically required to obtain a novel prognostically indicator for guiding clinical management. In this study, we established a circadian rhythm (CR) related signature by a combinative investigation of multiple datasets. The newly-established signature showed an acceptable ability to predict survival and could serve as an independent indicator for prognosis. Moreover, the newly-established signature was critically associated with tumor malignancy, including proliferation, invasion, EMT and metastasis. The newly-established signature was predictive of response to immune checkpoint blockade. Collectively, we established a CR-related gene signature that could forecast survival, tumor malignancy and therapeutic response; our findings could help guiding clinical management.