Senescence Score Research Articles

Identification of Cellular Senescence-Related Critical Genes and Molecular Classification and Revealing the Drug-Resistant Therapeutic Effect of IGFBP2 in Chronic Myeloid Leukemia.

The occurrence and development of hematologic tumors are closely linked to cellular senescence. However, the molecular characteristics associated with this phenomenon in chronic myeloid leukemia (CML) have not been thoroughly investigated. The cellular senescence score was calculated using gene set variation analysis. Consensus clustering algorithm was used to identify the molecular subtypes associated with cellular senescence. Clinical samples were collected for sequencing analysis to verify the expression of critical cellular senescence-related genes (CSRG). The effect of targeted inhibition of IGFBP2 on the malignant phenotype of CML-resistant cells was studied by cell experiments. The cellular senescence score in CML samples was significantly lower compared to normal samples. Higher expression of immune checkpoint markers correlated with increased cellular senescence scores. We identified two distinct molecular subtypes (C1 and C2) related to cellular senescence. The C1 subtype exhibited enhanced metabolic function and DNA damage repair capacity, while the C2 subtype showed higher infiltration of immune effector cells and activity in immune-related signaling pathways. We also discovered a group of drugs that displayed significant sensitivity differences between these two molecular subtypes, with the C2 subtype showing greater responsiveness to immunotherapy. Four critical cellular senescence-related genes (CSRGs), namely IGFBP2, IL7R, PLAU, and SUN1 demonstrated high diagnostic value for CML. We validated the expression levels of these four genes using clinical samples and confirmed through cell experiments that targeted inhibition of IGFBP2 effectively suppressed proliferation of resistant CML cells, promoted apoptosis, and enhanced therapeutic sensitivity to imatinib. Our study conducted a comprehensive analysis on CSRG expression characteristics in CML and explored potential correlations between cellular senescence and immune function. The identification of molecular subtypes provides valuable insights into assessing individual patients' biological characteristics for guiding clinical treatment decisions. Additionally, IGFBP2has emerged as a promising therapeutic target for therapy-resistant cases of CML.

P02.15.A INVESTIGATING THE ROLE OF CELLULAR SENESCENCE IN BRIDGING GLIOBLASTOMA AND ALZHEIMER’S DISEASE

Abstract BACKGROUND With changing demographics, age-related diseases like neurodegenerative disorders and cancer are becoming increasingly prevalent. We previously demonstrated that over 50% of glioblastoma (GB) patients show Alzheimer’s Disease (AD)-like changes in the tumor-adjacent cortex. However, whether these diseases are biologically linked remains unclear. Here, we investigate cellular senescence, a hallmark of aging, as a shared mechanism. MATERIAL AND METHODS We utilized single cell and single nucleus RNA sequencing datasets from 110 GB patients (GBmap core atlas) and 89 individuals with varying stages of AD (SEA-AD MTG atlas). Following data integration, we assessed senescent cells using three established gene lists, performed differential gene expression and conducted gene set enrichment analysis. Senescence scores were compared across different cell types and patients. Co-expression modules with senescence-associated genes were identified using weighted gene co-expression network analysis (WGCNA). Quantitative neuropathological analysis of published measurements (Iba1, AT8, 6E10) complemented the molecular findings. RESULTS Senescence was found in both GB and AD patient cells including cell types of the microenvironment. Notably, the variability in scores per patient was significantly higher in GB as compared to AD cell types, indicating greater inter-patient heterogeneity. Microglia were specifically enriched for senescence gene sets among glial cells. Subset analysis of microglia through data harmonization identified a proinflammatory GB microglia subtype that shared high similarity with AD microglia and had highest senescence scores. Notably, the increase in senescent microglia was associated with progression to advanced disease stages in both diseases. WGCNA identified 3 consensus modules of senescence-associated genes that were coexpressed with disease-specific genes, like PTEN implicated phosphorylation in the AD module and SPP1 for extracellular matrix remodeling in the GB module. All senescence associated modules showed increased expression in more advanced disease stages. Quantitative analysis of immunohistochemistry measurements in the AD dataset confirmed that samples with a high senescence score showed a significantly higher density of tau pathology and an altered microglia morphology. CONCLUSION Our study identifies cellular senescence as one connection between GB and AD pathology by utilizing atlas-level transcriptomic datasets. Particularly microglia upregulate senescence signatures with disease progression. The co-expression of senescence-associated genes within disease-specific modules underscores the complexity of senescence in this context.

The cellular senescence score (CSS) is a comprehensive biomarker to predict prognosis and assess senescence and immune characteristics in hepatocellular carcinoma (HCC)

Cellular senescence, an emerging hallmark of cancer, has garnered increasing attention in recent years. However, its role in hepatocellular carcinoma (HCC) is still not well understood. Furthermore, there is a lack of comprehensive biomarkers to predict prognosis and assess senescence and immune characteristics in HCC patients. To address these gaps, we conducted functional studies on bleomycin-induced senescent Hepa1-6 cells and developed the Cellular Senescence Score (CSS) based on four core cellular senescence-related genes. We found that the cellular senescence signaling pathway was enriched among the risk genes associated with unfavorable prognosis in HCC patients. The senescence associated secretory phenotype (SASP) derived from senescent Hepa1-6 cells induced an increase in CD3+ CD8+ CD279+ T cells. The senescent Huh7 cells expressed higher levels of pro-angiogenic genes compared to their immortal counterparts. The CSS was constructed on the basis of BMI1, EZH2, NPM1, and ME1. HCC Patients in the high-CSS group had significantly shorter overall survival compared to those in the low-CSS group. In contrast to the low-CSS group, the high-CSS group exhibited more senescence characteristics at both the overall tumor microenvironment and single-cell levels. Three distinct senescence patterns were identified in hepatoma cells: oxidative stress related senescence, metabolism related senescence, and immune related senescence. The high-CSS group showed elevated TP53 mutation rate, diminished immune cell infiltration, and enhanced expression levels of immune checkpoint molecules compared to the low-CSS group. Moreover, the high-CSS group displayed a greater proportion of patients responsive to immune checkpoint therapy compared to the low-CSS group. In summary, the impacts of cellular senescence on HCC are multifaceted, and the tumor-promoting effects may be caused by SASP remodeling the HCC microenvironment rather than by the senescent hepatoma cells themselves. The CSS is a promising biomarker capable of predicting prognosis and assessing senescence and immune characteristics in HCC.

Integrated analysis of single-cell and bulk RNA sequencing data reveals a cellular senescence-related signature in hepatocellular carcinoma.

The mortality of hepatocellular carcinoma (HCC) is on the rise globally, particularly in the Western world, with etiology gradually shifting from virus-related liver diseases to metabolic disorders such as non-alcoholic fatty liver disease. Early detection of HCC is challenging, and effective prognostic indicators are currently lacking, urgently necessitating reliable markers to assist in treatment planning and clinical management. Here, we introduce hepatocellular carcinoma senescence genes (HSG) to assess cellular senescence in HCC and devise a hepatocellular carcinoma senescence score (HSS) for prognostic prediction. Higher HSS levels signify poorer prognosis and increased tumor proliferation activity. Additionally, we observe alterations in the tumor immune microenvironment with higher HSS levels, such as increased infiltration of Treg, potentially providing a basis for immunotherapy. Furthermore, we identify key genes, such as PTTG1, within the senescence gene set and demonstrate their regulatory roles in HCC cells and Treg through experimentation. In summary, we establish a scoring system based on hepatocellular carcinoma senescence genes for prognostic prediction in HCC, potentially offering guidance for clinical treatment planning.

Targeting cellular senescence as a therapeutic vulnerability in gastric cancer

AimsCellular senescence (CS) represents an intracellular defense mechanism responding to stress signals and can be leveraged as a “vulnerability” in cancer treatment. This study aims to construct a CS atlas for gastric cancer (GC) and uncover potential therapeutics for GC patients. Materials and methods38 senescence-associated regulators with prognostic significance in GC were obtained from the CellAge database to construct Gastric cancer-specific Senescence Score (GSS). Using eXtreme Sum algorism, GSS-based drug repositioning was conducted to identify drugs that could antagonize GSS in CMap database. In vitro experiments were conducted to test the effect of combination of palbociclib and exisulind in eliminating GC cells. Key findingsPatients with high GSS exhibited CS-related features, such as CS markers upregulation, adverse clinical outcomes and hypomethylation status. scRNA-seq data showed malignant cells with high GSS exhibited enhanced senescence state and more immunosuppressive signals such as PVR-CD96 compared with malignant cells with low GSS. In addition, the GSS-High cancer associated fibroblasts might secrete cytokines and chemokines such as IL-6, CXCL1, CXCL12, and CCL2 to from an immunosuppressive microenvironment, and GSS could serve as an indicator for immunotherapy resistance. Exisulind exhibited the greatest potential to reverse GSS. In vitro experiments demonstrated that exisulind could induce apoptosis and suppress the proliferation of palbociclib-induced senescent GC cells. SignificanceOverall, GSS offers a framework for better understanding of correlation between senescence and GC, which might provide new insights into the development of novel therapeutics in GC.

Abstract 2955: HPV E6* and senescence-related gene expression in cervical cancer

Abstract Previous work in our lab found that increased expression of the E6* variant of the HPV E6 viral protein was significantly correlated with worse response to standard-of-care chemoradiation (CRT) and progression-free survival, independently of HPV genotype. In vitro validation showed that overexpression of E6* induces senescence in an HPV 16-positive cervical cancer cell line. Given these findings, we hypothesized that increased E6* expression mediates resistance to CRT by inducing a reversible state of tumor cell senescence. We created a senescence score using ten genes that have been consistently reported in the literature as associated with senescence. Using an institutional cohort of 68 patients with cervical cancer with prospectively collected clinical outcome data, we performed bulk RNA sequencing to assess senescence scores before CRT and determine whether there is an association between senescence scores and E6* expression. Using a second institutional cohort of 35 patients with cervical cancer treated with CRT with pre and posttreatment tumor biopsies, we performed bulk RNA sequencing to evaluate the same relationship and determine whether expression of senescence-related genes was affected by CRT. Nine cervical cancer cell lines stratified into low- and high-E6* expression groups will be assessed regarding their senescence score, beta-galactosidase staining, and SASP expression before and after CRT. In our first cohort, there was no correlation between E6*:E6 expression ratio and senescence score, regardless of HPV genotype. In our second cohort, CRT increased senescence score in CRT-treated samples (p < 0.01), but p16INK4a expression significantly decreased compared to pre-treatment samples (p < 0.01). Increased senescence score was not associated with cancer recurrence. There was no significant difference in senescence scores between different HPV genotypes before therapy. Tumors that were positive for HPV 16 or HPV 18 had significantly lower senescence scores compared to HPV negative tumors (p = 0.037 and p = 0.038, respectively) after CRT. Among HPV 16-positive tumors (n = 12), there was no correlation between E6*:E6 expression ratio and senescence score before or after CRT. We found no association between senescence score and E6* expression, and between senescence score and cancer recurrence after CRT in our dataset. Additionally, our results suggest that p16INK4a might not be an appropriate senescence marker in tumors that have intrinsically high p16INK4a expression, such as in cervical cancer, reinforcing the need for a cervical cancer-specific senescence signature. We are currently testing beta-galactosidase and SASP expression in vitro and in vivo before and after CRT. Citation Format: Louise Medina Bengtsson, Matthew Inkman, Naoshad Muhammad, Leahan Castillo, Naomi Msengi, Tyler McKinnish, Nishanth Gabriel, Jin Zhang, Julie Schwarz. HPV E6* and senescence-related gene expression in cervical cancer [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 2955.

Phenotypes and ontogeny of senescent hepatic stellate cells in metabolic dysfunction-associated steatohepatitis

Hepatic stellate cells (HSCs) are the key drivers of fibrosis in metabolic dysfunction-associated steatohepatitis (MASH), the fastest growing cause of hepatocellular carcinoma (HCC) worldwide. HSCs are heterogenous, and a senescent subset of HSCs is implicated in hepatic fibrosis and HCC. Administration of anti-uPAR (urokinase-type plasminogen activator receptor) CAR T cells has been shown to deplete senescent HSCs and attenuate fibrosis in murine models. However, the comprehensive features of senescent HSCs in MASH, as well as their cellular ontogeny have not been characterized; hence, we aimed to comprehensively characterize and define the origin of HSCs in human and murine MASH. To comprehensively characterize the phenotype and ontogeny of senescent HSCs in human and murine MASH, we integrated senescence-associated beta galactosidase activity with immunostaining, flow cytometry and single-nucleus RNA sequencing (snRNAseq). We integrated the immunohistochemical profile with a senescence score applied to snRNAseq data to characterize senescent HSCs and mapped the evolution of uPAR expression in MASH. Using pseudotime trajectory analysis, we establish that senescent HSCs arise from activated HSCs. While uPAR is expressed in MASH, the magnitude and cell-specificity of its expression evolve with disease stage. In early disease, uPAR is more specific to activated and senescent HSCs, while it is also expressed by myeloid-lineage cells, including Trem2+ macrophages and myeloid-derived suppressor cells, in late disease. Furthermore, we identify novel surface proteins expressed on senescent HSCs in human and murine MASH that could be exploited as therapeutic targets. These data define features of HSC senescence in human and murine MASH, establishing an important blueprint to target these cells as part of future antifibrotic therapies. Hepatic stellate cells (HSCs) are the primary drivers of scarring in chronic liver diseases. As injury develops, a subset of HSCs become senescent; these cells are non-proliferative and pro-inflammatory, thereby contributing to worsening liver injury. Here we show that senescent HSCs are expanded in MASH (metabolic dysfunction-associated steatohepatitis) in humans and mice, and we trace their cellular origin from the activated HSC subset. We further characterize expression of uPAR (urokinase plasminogen activated receptor), a protein that marks senescent HSCs, and report that uPAR is also expressed by activated HSCs in early injury, and in immune cells as liver injury advances. We have integrated high-resolution single-nucleus RNA sequencing with immunostaining and flow cytometry to identify five other novel proteins expressed by senescent HSCs, including mannose receptor CD206, which will facilitate future therapeutic development.

Detection of senescence using machine learning algorithms based on nuclear features

Cellular senescence is a stress response with broad pathophysiological implications. Senotherapies can induce senescence to treat cancer or eliminate senescent cells to ameliorate ageing and age-related pathologies. However, the success of senotherapies is limited by the lack of reliable ways to identify senescence. Here, we use nuclear morphology features of senescent cells to devise machine-learning classifiers that accurately predict senescence induced by diverse stressors in different cell types and tissues. As a proof-of-principle, we use these senescence classifiers to characterise senolytics and to screen for drugs that selectively induce senescence in cancer cells but not normal cells. Moreover, a tissue senescence score served to assess the efficacy of senolytic drugs and identified senescence in mouse models of liver cancer initiation, ageing, and fibrosis, and in patients with fatty liver disease. Thus, senescence classifiers can help to detect pathophysiological senescence and to discover and validate potential senotherapies.

Exploring the role of cellular senescence in cancer prognosis across multiple tumor types.

Cellular senescence is a common biological process with a well-established link to cancer. However, the impact of cellular senescence on tumor progression remains unclear. To investigate this relationship, we utilized transcriptomic data from a senescence gene set to explore the connection between senescence and cancer prognosis. We developed the senescence score by the Least Absolute Shrinkage and Selection Operator (LASSO) Cox model. We obtained transcriptomic information of the senescence gene set from The Cancer Genome Atlas (TCGA) program. Additionally, we created a nomogram that integrates these senescence scores with clinical characteristics, providing a more comprehensive tool for prognosis evaluation. We calculated the senescence score based on the expression level of 42 senescence-related genes. We established the nomogram based on the senescence score and clinical characteristics. The senescence score showed a positive correlation with epithelial-to-mesenchymal transition, cell cycle, and glycolysis, and a negative correlation with autophagy. Furthermore, we carried out Gene Ontology (GO) analysis to explore the signaling pathways and biological process in different senescence score groups. The senescence score, a novel tool constructed in this study, shows promise in predicting survival outcomes across various cancer types. These findings not only highlight the complex interplay between senescence and cancer but also indicate that cellular senescence might serve as a biomarker for tumor prognosis.

ELMO1 ameliorates intestinal epithelial cellular senescence via SIRT1/p65 signaling in inflammatory bowel disease-related fibrosis.

Intestinal fibrosis is a common complication in inflammatory bowel disease (IBD), which still lacks of reliable markers and therapeutic options. Cellular senescence has been considered an important mechanism of intestinal fibrosis, but the underlying molecular link remains elusive. Tissues were stained using α-smooth muscle actin (α-SMA), fibronectin, and collagen I as markers of myofibroblastic differentiation. Cellular senescence was confirmed through Lamin B1 staining, senescence-associated β-galactosidase staining, and the expression of senescence-associated secretory phenotype (SASP) factors. We explored the relationship between senescence of intestinal epithelial cells (IECs) and intestinal fibrosis, as well as the molecular mechanism underlying this interaction. The effects of irisin on cellular senescence and fibrosis were determined. Here, we identify engulfment and cell motility protein 1 (ELMO1) as a novel biomarker for intestinal cellular senescence and fibrosis. In fibrostrictured tissues from patients and murine models with IBD, significantly high levels of cellular senescence score and factors were noted, which positively correlated with the fibrotic regulator fibronectin. Senescent IECs, not fibroblast itself, released SASP factors to regulate fibroblast activation. Prolonging exposure to severe and persistent injurious stimuli decreased ELMO1 expression, which dampened SIRT1 deacetylase activity, enhanced NF-κB (p65) acetylation, and thereby accelerated cellular senescence. Deletion of ELMO1 led to senescent IECs accumulation and triggered premature fibrosis in murine colitis. Furthermore, irisin, inhibiting the degradation of ELMO1, could downregulate p65 acetylation, reduce IECs senescence, and prevent incipient intestinal fibrosis in murine colitis models. This study reveals ELMO1 downregulation is an early symbol of intestinal senescence and fibrosis, and the altered ELMO1-SIRT1-p65 pathway plays an important role in intestinal cellular senescence and IBD-related fibrosis.

Sixteen Cellular Senescence-associated DNA Methylation Signature Predicts Overall Survival in Patients with Head and Neck Squamous Cell Carcinoma.

To construct a cellular senescence-related DNA methylation model to act as an independent prognosis predictor for patients with head and neck squamous cell carcinoma (HNSCC). Methylome, transcriptome and clinical information for 499 HNSCC patients were received from The Cancer Genome Atlas (TCGA) as a training set. An extra independent methylation dataset of 54 patients with oral squamous cell carcinoma (OSCC) was downloaded from the NCBI Gene Expression Omnibus (GEO) database as the validation set. To assess the cellular senescence level of each sample, the senescence score (SS) of each patient was calculated using the transcriptome data via single-sample gene set enrichment analysis (ssGSEA). Least absolute shrinkage and selection operator (LASSO) Cox regression analyses were conducted to confirm Cytosine, phosphoric acid and Guanine (CpG) sites for the development of a cellular senescence-related DNA methylation signature. Based on the SS of each HNSCC patient in the TCGA cohort, the patients were divided into high- and low-SS subgroups. The high-SS group showed a better prognosis than the low-SS group. Moreover, 3,261 differentially methylated CpG sites (DMCs) were confirmed between the two groups. Among them, 16 DMCs were included to develop a 16-DNA methylation signature for evaluation of HNSCC prognosis using LASSO and multivariate Cox regression analysis. A novel cellular senescence-related 16-DNA methylation signature was determined, which can be used as an independent index to evaluate the prognosis of HNSCC patients and select appropriate treatment strategies.

IFNγ Signaling in Acute Myeloid Leukemia Mediates Immunomodulation and Reveals Therapeutic Strategies

Background: Interferon gamma (IFNγ) is a critical cytokine known for its diverse roles in immune regulation, inflammation, and tumor surveillance. Studies have reported the dichotomous nature of IFNγ signaling in both the pathogenesis of cancer and immunotherapy response. However, its complex interplay with acute myeloid leukemia (AML) remains insufficiently understood. Methods: Three independent RNA-seq datasets were integrated to disentangle the IFNγ signaling in AML. We also performed single cell RNA sequencing (scRNA) on 20 newly diagnosed AML patients to discern relative contribution of cells and cellular communications for IFNγ signaling. Results: Single-sample gene set enrichment analysis was used to examine the transcriptional programs linked to IFNγ signaling in 672 newly diagnosed adult AML patients. We observed higher IFNγ signaling score in subgroups of patients including diploid with monocytic differentiation, inv16 core-binding-factor AML, and del7/7q. Notably, sorted CD34 + cells from 17 healthy donors had markedly lower levels of IFNγ signaling scores than did those from AML patients, making it a predominant feature in AML. Additionally, we found significant positive correlations between IFNγ signaling score and expression of its downstream targets HLA class 1 and 2 as well as T cell dysfunction score, T cell exhaustion score, and T cell senescence score, consistent with the fact that chronic IFNγ can drive T cell dysfunction. In scRNA, we observed that AML cells in patients with diploid monocytic AML had the highest expression of IFNγ signaling followed by del7/7q, while the non-monocytic, diploid AML cells had the lowest (Figure 1A). We then explored whether IFNγ signaling is differentially activated across the AML hierarchies and found the spectrum along the hierarchy with the primitive cells displaying significant higher IFNγ signaling than GMP while reaching the highest in Mono-like state. Transcription factor analysis revealed high regulon activity of interferon regulator factors (IRFs) in AML cells, with elevated levels of IRF1 and IRF5 regulons in del7/7q and del5/5q, respectively and elevated IRF8 regulon in diploid AML cells with monocytic differentiation, consistent with its role as a lineage-determinant factor promoting monocytic differentiation. Cell-cell interactions revealed IFNγ from CD8 T cells and NK cells as a top interaction to AML cells. These observations indicate that the activation levels of IFNγ signaling in AML cells are associated with distinct cellular states and hierarchies, and that disparate regulons of IFNγ signaling characterize distinct patient subgroups. The high level of IFNγ signaling in monocytic patient prompted us to assess its correlation with drug response as monocytic subclones are suggested to have inherent resistance to venetoclax. In BEAT-AML ex vivo drug test data, we found a strong positive correlation between IFNγ signaling score and venetoclax resistance, indicating that IFNγ signaling confers venetoclax resistance. This correlation was validated in an independent cohort. However, the IFNγ signaling score did not predict survival outcomes in our bulk cohort. Therefore, we defined a light weighted IFNγ signature to improve the prognostic sensitivity using the least absolute shrinkage and selection operator model. After regression, 47 genes related to survival were retained, forming a parsimonious IFNγ signature. The new parsimonious IFNγ score revealed a tight positive correlation with HLA class 1 and 2 scores. Importantly, this parsimonious IFNγ score was able to predict patient outcomes in our bulk cohort, whereby a higher score predicted worse survival (Figure 1B). Ultimately, these results suggest that the IFNγ pathway activation is associated with resistance to venetoclax-based therapy and can predict patient outcomes independently of known risk factors, making it a promising target for therapeutic intervention. Conclusions: Characterization of inflammation in AML using independent bulk and scRNA profiling led to the identification of novel drug targets and mechanisms of resistance to targeted therapy. We identified monocytic AML as having a unique microenvironment characterized by high IFNγsignaling in AML cells and immunosuppressive features. IFNγ signaling scores correlated strongly with venetoclax resistance. A parsimonious IFNγ gene signature demonstrated robust prognostic value.

TRANSLATIONAL RESEARCH-02 THE KEYSTONE CYTOKINE, INTERLEUKIN-6, A KEY TARGET AND “ORGANIZING PRINCIPLE” FOR GLIOBLASTOMA THERAPY: A DECADE OF TRANSLATIONAL PROGRESS FROM GENOMICS TO THE LABORATORY AND TO A MULTICENTER CLINICAL TRIAL

Abstract Interleukin-6 (IL-6), the ‘keystone cytokine’, affects homeostatic processes, including innate and adaptive immunity, and is regarded as a prominent target for clinical intervention (Hunter, 2015). IL-6 is also a senescence-associated-gene (SAG), linked to cellular aging, the aging brain, and cancer pathogenesis. We hypothesized that SAGs, including IL-6, are overexpressed in older patients, in higher grades of glioma, portending a poor prognosis (Coppola, 2014). Indeed, in an analysis of 47 gliomas at the Moffitt Cancer Center, we found that the ‘senescence score’ composed of genes central to the pathogenesis of glioma, defined a novel signature, provided prognostic biomarkers as well as targets for drug discovery and immunotherapy (Coppola, 2014). We suggested that IL-6 could be linked to neoplastic transformation and could be predictive of glioma progression (US Patent #8741575). At the University of Pennsylvania, we found an inhibitor of IL-6 to be well-tolerated in patients with glioblastoma undergoing CAR T cell therapy (O’Rourke, 2017). Yi Fan’s team discovered (Wang, 2018) that targeting IL-6 led to a remarkable change in the tumor microenvironment (TME), with a “switch” from the M2 (immunosuppressive, pro-tumorigenic) macrophage phenotype to an immunostimulatory (M1) phenotype, resulting in a significant increase in survival. Adding CD40 agonist enhanced the activity of infiltrated T cells, and an almost complete cure in GBM models. The use of immune checkpoint inhibitors in these experiments and by others (Lamano, 2019) produced a significant increase in survival. These findings led to a multicenter trial (PI, Stephen Bagley; NCT 047299959), by NRG Oncology (BN010), combining IL-6 inhibition (tocilizumab), PD-L1 blockade (atezolizumab) and stereotactic radiotherapy to treat recurrent glioblastoma. More recently, a MDACC team discovered that IL-6 blockade not only promotes tumor immunity but also abrogates the toxicity of checkpoint blockade, decoupling the autoimmune toxicity while promoting tumor immunity through the IL-12 pathway (Hailemichael, 2022).

Transcriptional changes of the aging lung.

Aging is a natural process associated with declined organ function and higher susceptibility to developing chronic diseases. A systemic single-cell type-based study provides a unique opportunity to understand the mechanisms behind age-related pathologies. Here, we use single-cell gene expression analysis comparing healthy young and aged human lungs from nonsmoker donors to investigate age-related transcriptional changes. Our data suggest that aging has a heterogenous effect on lung cells, as some populations are more transcriptionally dynamic while others remain stable in aged individuals. We found that monocytes and alveolar macrophages were the most transcriptionally affected populations. These changes were related to inflammation and regulation of the immune response. Additionally, we calculated the LungAge score, which reveals the diversity of lung cell types during aging. Changes in DNA damage repair, fatty acid metabolism, and inflammation are essential for age prediction. Finally, we quantified the senescence score in aged lungs and found that the more biased cells toward senescence are immune and progenitor cells. Our study provides a comprehensive and systemic analysis of the molecular signatures of lung aging. Our LungAge signature can be used to predict molecular signatures of physiological aging and to detect common signatures of age-related lung diseases.

Integrated analysis of single-cell sequencing and weighted co-expression network identifies a novel signature based on cellular senescence-related genes to predict prognosis in glioblastoma.

Glioblastoma (GBM) is a highly aggressive cancer with heavy mortality rates and poor prognosis. Cellular senescence exerts a pivotal influence on the development and progression of various cancers. However, the underlying effect of cellular senescence on the outcomes of patients with GBM remains to be elucidated. Transcriptome RNA sequencing data with clinical information and single-cell sequencing data of GBM cases were obtained from CGGA, TCGA, and GEO (GSE84465) databases respectively. Single-sample gene set enrichment analysis (ssGSEA) analysis was utilized to calculate the cellular senescence score. WGCNA analysis was employed to ascertain the key gene modules and identify differentially expressed genes (DEGs) associated with the cellular senescence score in GBM. The prognostic senescence-related risk model was developed by least absolute shrinkage and selection operator (LASSO) regression analyses. The immune infiltration level was calculated by microenvironment cell populations counter (MCPcounter), ssGSEA, and xCell algorithms. Potential anti-cancer small molecular compounds of GBM were estimated by "oncoPredict" R package. A total of 150 DEGs were selected from the pink module through WGCNA analysis. The risk-scoring model was constructed based on 5 cell senescence-associated genes (CCDC151, DRC1, C2orf73, CCDC13, and WDR63). Patients in low-risk group had a better prognostic value compared to those in high-risk group. The nomogram exhibited excellent predictive performance in assessing the survival outcomes of patients with GBM. Top 30 potential anti-cancer small molecular compounds with higher drug sensitivity scores were predicted. Cellular senescence-related genes and clusters in GBM have the potential to provide valuable insights in prognosis and guide clinical decisions.

Senescence-based colorectal cancer subtyping reveals distinct molecular characteristics and therapeutic strategies.

Cellular senescence has been listed as a hallmark of cancer, but its role in colorectal cancer (CRC) remains unclear. We comprehensively evaluated the transcriptome, genome, digital pathology, and clinical data from multiple datasets of CRC patients and proposed a novel senescence subtype for CRC. Multi-omics data was used to analyze the biological features, tumor microenvironment, and mutation landscape of senescence subtypes, as well as drug sensitivity and immunotherapy response. The senescence score was constructed to better quantify senescence in each patient for clinical use. Unsupervised learning revealed three transcriptome-based senescence subtypes. Cluster 1, characterized by low senescence and activated proliferative pathways, was sensitive to chemotherapeutic drugs. Cluster 2, characterized by intermediate senescence and high immune infiltration, exhibited significant immunotherapeutic advantages. Cluster 3, characterized by high senescence, high immune, and stroma infiltration, had a worse prognosis and maybe benefit from targeted therapy. We further constructed a senescence scoring system based on seven senescent genes through machine learning. Lower senescence scores were highly predictive of longer disease-free survival, and patients with low senescence scores may benefit from immunotherapy. We proposed the senescence subtypes of CRC and our findings provide potential treatment interventions for each CRC senescence subtype to promote precision treatment.

Gene set variation analysis-based aging and senescence score as a prognostic indicator and therapeutic guide in lung adenocarcinoma.

Accumulating evidence suggests that aging and senescence play crucial roles in tumorigenesis, cancer progression, and treatment. However, the influence of aging and senescence-related genes (ASRGs) on clinical outcomes and treatment options in lung adenocarcinoma (LUAD) patients remains unknown. Here, we developed an aging and senescence-related scoring system, ASRS, by integrating bulk transcriptome data from 22 LUAD datasets. In 3,243 LUAD samples, higher ASRS scores were associated with poor tumor stage and pathological grade, as well as shorter overall survival, disease-free survival, and recurrence-free survival. Additionally, ASRS was associated with different immune patterns in the tumor microenvironment (TME). Importantly, ASRS was found to predict therapeutic efficacy, with patients having a low ASRS benefiting from immunotherapy and those with a high ASRS responding better to chemotherapy. Therefore, ASRS represents a previously overlooked characteristic of LUAD that can influence patient outcomes and treatment success.

Optimal combination of immune checkpoint and senescence molecule predicts adverse outcomes in patients with acute myeloid leukemia

Background High expression of immune checkpoints (ICs) and senescence molecules (SMs) contributes to T cell dysfunction, tumor escape, and progression, but systematic evaluation of them in co-expression patterns and prognosis in acute myeloid leukemia (AML) was lacking. Methods Three publicly available datasets (TCGA, Beat-AML, and GSE71014) were first used to explore the effect of IC and SM combinations on prognosis and the immune microenvironment in AML, and bone marrow samples from 68 AML patients from our clinical center (GZFPH) was further used to validate the findings. Results High expression of CD276, Bcl2-associated athanogene 3 (BAG3), and SRC was associated with poor overall survival (OS) of AML patients. CD276/BAG3/SRC combination, standard European Leukemia Net (ELN) risk stratification, age, and French-American-British (FAB) subtype were used to construct a nomogram model. Interestingly, the new risk stratification derived from the nomogram was better than the standard ELN risk stratification in predicting the prognosis for AML. A weighted combination of CD276 and BAG3/SRC positively corrected with TP53 mutation, p53 pathway, CD8+ T cells, activated memory CD4+ T cells, T-cell senescence score, and Tumor Immune Dysfunction and Exclusion (TIDE) score estimated by T-cell dysfunction. Conclusion High expression of ICs and SMs was associated with poor OS of AML patients. The co-expression patterns of CD276 and BAG3/SRC might be potential biomarkers for risk stratification and designing combinational immuno-targeted therapy in AML. Key Messages High expression of CD276, BAG3, and SRC was associated with poor overall survival of AML patients. The co-expression patterns of CD276 and BAG3/SRC might be potential biomarkers for risk stratification and designing combinational immuno-targeted therapy in AML.

Cellular senescence-related gene signature as a valuable predictor of prognosis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a lethal tumor. Its prognosis prediction remains a challenge. Meanwhile, cellular senescence, one of the hallmarks of cancer, and its related prognostic genes signature can provide critical information for clinical decision-making. Using bulk RNA sequencing and microarray data of HCC samples, we established a senescence score model via multi-machine learning algorithms to predict the prognosis of HCC. Single-cell and pseudo-time trajectory analyses were used to explore the hub genes of the senescence score model in HCC sample differentiation. A machine learning model based on cellular senescence gene expression profiles was identified in predicting HCC prognosis. The feasibility and accuracy of the senescence score model were confirmed in external validation and comparison with other models. Moreover, we analyzed the immune response, immune checkpoints, and sensitivity to immunotherapy drugs of HCC patients in different prognostic risk groups. Pseudo-time analyses identified four hub genes in HCC progression, including CDCA8, CENPA, SPC25, and TTK, and indicated related cellular senescence. This study identified a prognostic model of HCC by cellular senescence-related gene expression and insight into novel potential targeted therapies.

Identification and validation of BCL6 and VEGFA as biomarkers and ageing patterns correlating with immune infiltrates in OA progression

Osteoarthritis (OA), the most common type of arthritis, is a complex biological response caused by cartilage wear and synovial inflammation that links biomechanics and inflammation. The progression of OA correlates with a rise in the number of senescent cells in multiple joint tissues. However, the mechanisms by which senescent cells and their involvement with immune infiltration promote OA progression are not fully understood. The gene expression profiles and clinical information of OA and healthy control synovial tissue samples were retrieved from the Gene Expression Omnibus database, and then differential analysis of senescence regulators between OA and normal samples was performed. The random forest (RF) was used to screen candidate senescence regulators to predict the occurrence of OA. The reverse transcription quantitative real-time PCR experiments at tissue’s level was performed to confirm these biomarkers. Moreover, two distinct senescence patterns were identified and systematic correlation between these senescence patterns and immune cell infiltration was analyzed. The senescence score and senescence gene clusters were constructed to quantify senescence patterns together with immune infiltration of individual OA patient. 73 senescence differentially expressed genes were identified between OA patients and normal controls. The RF method was utilized to build an OA risk model based on two senescence related genes: BCL6 and VEGFA. Next, two distinct aging patterns were determined in OA synovial samples. Most patients from senescence cluster A were further classified into gene cluster B and high senescence score group correlated with a non-inflamed phenotype, whereas senescence cluster B were classified into gene cluster A and low senescence score group correlated with an inflamed phenotype. Our study revealed that senescence played an important role in in OA synovial inflammation. Evaluating the senescence patterns of individuals with OA will contribute to enhancing our cognition of immune infiltration characterization, providing novel diagnostic and prognostic biomarkers, and guiding more effective immunotherapy strategies.