Construction and experimental validation of a B cell senescence-related gene signature to evaluate prognosis and immunotherapeutic sensitivity in bladder cancer

Molecular signatures of cellular senescence in cancer: a critical review of prognostic implications and therapeutic opportunities

Cellular senescence is a state of permanent loss of proliferative capacity. Therefore, cells that reach a senescent state prevent tumor initiation, acting as an anti-tumor mechanism. However, despite not being proliferative, senescent cells have high secretory activity, constituting the Senescence-Associated Secretory Phenotype (SASP). SASP includes thousands of soluble molecules and extracellular vesicles, through which senescent cells can affect other cells and the extracellular matrix. In advanced tumors, the enrichment of senescent cells can have anti- or pro-tumor effects depending on features like SASP composition, tumor microenvironment (TME) composition, the anatomic site, histopathologic characteristics of malignancy, and tumor molecular background. We reviewed the studies assessing the impact of the senescence status, measured by mRNA or lncRNA molecular signatures, in the prognosis and other clinically relevant information in cancer, including anti-tumor immunity and response to therapy. We discussed the pros and cons of different strategies to define those molecular signatures and the main limitations of the studies. Finally, we also raised clinical challenges regarding the crossroad between cellular senescence and cancer prognosis, including some therapeutic opportunities in the field.

Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer

BACKGROUND

The prevalence and mortality of bladder cancer (BLCA) present a significant medical challenge. While the function of senescence-related genes in tumor development is recognized, their prognostic significance in BLCA has not been thoroughly explored.

METHODS

BLCA transcriptome datasets were sourced from the TCGA and GEO repositories. Gene groupings were determined through differential gene expression and non-negative matrix factorization (NMF) methodologies. Key senescence-linked genes were isolated using singular and multivariate Cox regression analyses, combined with lasso regression. Validation was undertaken with GEO database information. Predictive models, or nomograms, were developed by merging risk metrics with clinical records, and their efficacy was gauged using ROC curve methodologies. The immune response's dependency on the risk metric was assessed through the immune phenomenon score (IPS). Additionally, we estimated IC50 metrics for potential chemotherapeutic agents.

RESULTS

Reviewing 406 neoplastic and 19 standard tissue specimens from the TCGA repository facilitated the bifurcation of subjects into two unique clusters (C1 and C2) according to senescence-related gene expression. After a stringent statistical evaluation, a set of ten pivotal genes was discerned and applied for risk stratification. Validity tests for the devised nomograms in forecasting 1, 3, and 5-year survival probabilities for BLCA patients were executed via ROC and calibration plots. IC50 estimations highlighted a heightened responsiveness in the low-risk category to agents like cisplatin, cyclopamine, and sorafenib.

CONCLUSIONS

In summation, our research emphasizes the prospective utility of risk assessments rooted in senescence-related gene signatures for enhancing BLCA clinical oversight.

Investigating the impact of regulatory B cells and regulatory B cell-related genes on bladder cancer progression and immunotherapeutic sensitivity

BACKGROUND

Regulatory B cells (Bregs), a specialized subset of B cells that modulate immune responses and maintain immune tolerance in malignant tumors, have not been extensively investigated in the context of bladder cancer (BLCA). This study aims to elucidate the roles of Bregs and Breg-related genes in BLCA.

METHODS

We assessed Breg infiltration levels in 34 pairs of BLCA and corresponding paracancerous tissues using immunohistochemical staining. We conducted transwell and wound healing assays to evaluate the impact of Bregs on the malignant phenotype of SW780 and T24 cells. Breg-related genes were identified through gene sets and transcriptional analysis. The TCGA-BLCA cohort served as the training set, while the IMvigor210 and 5 GEO cohorts were used as external validation sets. We employed LASSO regression and random forest for feature selection and developed a risk signature using Cox regression. Primary validation of the risk signature was performed through immunohistochemical staining and RT-qPCR experiments using the 34 local BLCA samples. Additionally, we employed transfection assays and flow cytometry to investigate Breg expansion ability and immunosuppressive functions.

RESULTS

Breg levels in BLCA tissues were significantly elevated compared to paracancerous tissues (P < 0.05) and positively correlated with tumor malignancy (P < 0.05). Co-incubation of SW780 and T24 cells with Bregs resulted in enhanced invasion and migration abilities (all P < 0.05). We identified 27 Breg-related genes, including CD96, OAS1, and CSH1, which were integrated into the risk signature. This signature demonstrated robust prognostic classification across the 6 cohorts (pooled HR = 2.25, 95% CI = 1.52-3.33). Moreover, the signature exhibited positive associations with advanced tumor stage (P < 0.001) and Breg infiltration ratios (P < 0.05) in the local samples. Furthermore, the signature successfully predicted immunotherapeutic sensitivity in three cohorts (all P < 0.05). Knockdown of CSH1 in B cells increased Breg phenotype and enhanced suppressive ability against CD8 + T cells (all P < 0.05).

CONCLUSIONS

Bregs play a pro-tumor role in the development of BLCA. The Breg-related gene signature established in this study holds great potential as a valuable tool for evaluating prognosis and predicting immunotherapeutic response in BLCA patients.

Alfalfa xenomiR-162 targets G protein subunit gamma 11 to regulate milk protein synthesis in bovine mammary epithelial cells

OBJECTIVE

It was shown that microRNAs (miRNAs) play an important role in milk protein synthesis. However, the post-transcriptional regulation of casein expression by exogenous miRNA (xeno-miRNAs) in ruminants remains unclear. This study explores the regulatory roles of alfalfa xeno-miR162 on casein synthesis in bovine mammary epithelial cells (bMECs).

METHODS

The effects of alfalfa xenomiR-162 and G protein subunit gamma 11 (GNG11) on proliferation and milk protein metabolism of bMECs were detected by 5-Ethynyl-2'-Deoxyuridine (EdU) staining, flow cytometry, cell counting kit-8 (CCK-8), enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blot. Dual-luciferase reporter assay was used to verify the targeting relationship between GNG11 and xenomiR-162.

RESULTS

Results showed that over-expression of xenomiR-162 inhibited cell proliferation but promoted apoptosis, which also up-regulated the expression of several casein coding genes, including CSN1S1, CSN1S2, and CSN3, while decreasing the expression of CSN2. Furthermore, the targeting relationship between GNG11 and xenomiR-162 was determined, and it was confirmed that GNG11 silencing also inhibited cell proliferation but promoted apoptosis and reduced the expression of casein coding genes and genes related to the mammalian target of rapamycin (mTOR) pathway.

CONCLUSION

Alfalfa xenomiR-162 appears to regulate bMECs proliferation and milk protein synthesis via GNG11 in the mTOR pathway, suggesting that this xeno-miRNA could be harnessed to modulate CSN3 expression in dairy cows, and increase κ-casein contents in milk.

Unlocking the potential of senescence-related gene signature as a diagnostic and prognostic biomarker in sepsis: insights from meta-analyses, single-cell RNA sequencing, and in vitro experiments

Cellular senescence is closely associated with the pathogenesis of sepsis. However, the diagnostic and prognostic value of senescence-related genes remain unclear. In this study, 866 senescence-related genes were collected from CellAge. The training cohort, GSE65682, which included 42 control and 760 sepsis samples, was obtained from the Gene Expression Omnibus (GEO). Feature selection was performed using gene expression difference detection, LASSO analysis, random forest, and Cox regression. TGFBI and MAD1L1 were ultimately selected for inclusion in the multivariate Cox regression model. Clustering based on the expressions of TGFBI and MAD1L1 was significantly associated with sepsis characteristics and prognoses (all P < 0.05). The risk signature served as a reliable prognostic predictor across the GSE65682, GSE95233, and GSE4607 cohorts (pooled hazard ratio = 4.27; 95% confidence interval [CI] = 1.63-11.17). Furthermore, it also served as a robust classifier to distinguish sepsis samples from control cases across 14 cohorts (pooled odds ratio = 5.88; 95% CI = 3.54-9.77). Single-cell RNA sequencing analyses from five healthy controls and four sepsis subjects indicated that the risk signature could reflect the senescence statuses of monocytes and B cells; this finding was then experimentally validated in THP-1 and IM-9 cells in vitro (both P < 0.05). In all, a senescence-related gene signature was developed as a prognostic and diagnostic biomarker for sepsis, providing cut-in points to uncover underlying mechanisms and a promising clinical tool to support precision medicine.

Construction and experimental validation of a macrophage cell senescence-related gene signature to evaluate the prognosis, immunotherapeutic sensitivity, and chemotherapy response in bladder cancer

Tumor-associated macrophages (TAMs) are pivotal components of tumor microenvironment (TME), and senescent TAMs contribute to the alternation of the profiles of TME. However, the potential biological mechanisms and the prognosis value of senescent macrophages are largely unknown, especially in bladder cancer (BLCA). Based on the single-cell RNA sequencing of a primary BLCA sample, 23 macrophage-related genes were identified. Genomic difference analysis, LASSO, and Cox regression were used to develop the risk model. TCGA-BLCA cohort (n = 406) was utilized as the training cohort, and then, three independent cohorts (n = 90, n = 221, n = 165) from Gene Expression Omnibus, clinical samples from the local hospital (n = 27), and in vitro cell experiments were used for external validation. Aldo-keto reductase family 1 member B (AKR1B1), inhibitor of DNA binding 1 (ID1), and transforming growth factor beta 1 (TGFB1I1) were determined and included in the predictive model. The model serves as a promising tool to evaluate the prognosis in BLCA (pooled hazard ratio = 2.51, 95% confidence interval = [1.43; 4.39]). The model was also effective for the prediction of immunotherapeutic sensitivity and chemotherapy treatment outcomes, which were further confirmed by IMvigor210 cohort (P < 0.01) and GDSC dataset, respectively. Twenty-seven BLCA samples from the local hospital proved that the risk model was associated with the malignant degree (P < 0.05). At last, the human macrophage THP-1 and U937 cells were treated with H2O2 to mimic the senescent process in macrophage, and the expressions of these molecules in the model were detected (all P < 0.05).Overall, a macrophage cell senescence-related gene signature was constructed to predict the prognosis, immunotherapeutic response, and chemotherapy sensitivity in BLCA, which provides novel insights to uncover the underlying mechanisms of macrophage senescence.

Unraveling the potential of senescence-related genes in guiding clinical therapy of lung adenocarcinoma patients

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer. In recent years, cell senescence emerges as a potential therapeutic target of cancer therapy. However, the role of cell senescence in LUAD has not been comprehensively unveiled. One single cell RNA sequencing (scRNA-seq) dataset (GSE149655) and two bulk RNA-seq datasets (TCGA and GSE31210) of LUAD were included. Seurat R package was used to process scRNA-seq data and identify immune cell subgroups. Single sample gene set enrichment analysis (ssGSEA) was performed to calculate enrichment score of senescence-related pathways. Senescence-based molecular subtyping for LUAD samples was conducted through unsupervised consensus clustering. pRRophetic package was introduced to analysis drug sensitivity. The senescence-associated risk model was established using univariate regression and stepAIC methods. Western blot, RT-qPCR, immunofluorescence assay and CCK-8 were used to explore the effect of CYCS in LUAD cell lines. Malignant immune cells had remarkedly higher enrichment of senescence-related pathways than non-malignant cells. P53 signaling and DNA damage telomere stress induced senescence pathways were found to be significantly activated in LUAD samples compared with normal samples. We identified two clusters (clust1 and clust2) based on senescence-related genes. Clust1 had severe genomic instability, aggravated senescent features, and low immune and stromal infiltration. The senescence-associated risk model including CASP9, CHEK1, CYCS, SERPINE1, SESN2, TP53I3, LMNB1, RAD50 and TERF2IP, was effective to distinguish high- and low-risk groups. Moreover, low-risk group exhibited sensitive responses to immunotherapy and chemotherapeutic drugs. In vitro experiments results showed that CYCS expression was increased and promoted cell viability in LUAD cell lines. This study explored the important role of senescence in LUAD progression, and confirmed the potential of senescence-related genes in predicting LUAD prognosis and response to immunotherapy and chemotherapy.