Identification and validation of a novel senescence-related biomarker for thyroid cancer to predict the prognosis and immunotherapy

PRDM1 promotes the ferroptosis and immune escape of thyroid cancer by regulating USP15-mediated SELENBP1 deubiquitination

BACKGROUND

The deubiquitinating enzyme Ubiquitin-specific peptidase 15 (USP15) is upregulated in various cancers and promotes tumor progression by increasing the expression of several oncogenes. This project is designed to explore the role and mechanism of USP15 in thyroid cancer (TC) progression.

METHODS

Selenium-binding protein 1 (SELENBP1), USP15, CCL2/5, CXCL10/11, IL-4, and TGF-β1 mRNA levels were detected using real-time quantitative polymerase chain reaction (RT-qPCR). SELENBP1, USP15, GPX4, IL-10, Arg-1, Granzyme B, TNF-α, and PR domain zinc finger protein 1 (PRDM1) protein levels were examined by western blot assay. Fe+ level, malondialdehyde (MDA), and lipid-ROS levels were determined using special kits. The proportion of CD11b+CD206+ positive cells was detected using a flow cytometry assay. The role of SELENBP1 on TC cell growth was examined using a xenograft tumor model in vivo. After GeneMANIA prediction, the interaction between USP15 and SELENBP1 was verified using Co-immunoprecipitation (CoIP) assay. The binding between PRDM1 and USP15 promoter was predicted by JASPAR and validated using Chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays.

RESULTS

SELENBP1 was increased in TC subjects and cell lines, and its knockdown repressed TC cell proliferation, migration, invasion, immune escape, and induced ferroptosis in vitro, as well as blocked tumor growth in vivo. In mechanism, USP15 interacted with SELENBP1 and maintained its stabilization by removing ubiquitin. Meanwhile, the upregulation of USP15 was induced by the transcription factor PRDM1.

CONCLUSION

USP15 transcriptionally mediated by PRDM1 might boost TC cell malignant behaviors through deubiquitinating SELENBP1, providing a promising therapeutic target for TC treatment.

Development and verification of a novel risk model related to ubiquitination linked with prognosis and therapeutic response in clear cell renal cell carcinoma

Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC.

Serum CHI3L1 Levels Predict Overall Survival of Hepatocellular Carcinoma Patients after Hepatectomy

Objective: The Chitinase 3-like protein 1 (CHI3L1) is currently used as a biomarker for the diagnosis of liver fibrosis. However, its prognostic value for hepatocellular carcinoma (HCC) patients remains controversial. In this study, we aimed to investigate the prognostic value of the CHI3L1 in HCC patients after hepatectomy. Methods: In total, 753 HCC patients who underwent curative hepatectomy between January 2017 to August 2021 were retrospectively recruited. The probability of overall survival (OS) was evaluated by the Kaplan-Meier method and compared between groups using the log-rank test. Cox proportional hazard regression analysis was used to determine the independent prognostic factors. A prognostic nomogram was constructed for further examine the clinical utility of CHI3L1 in HCC. Results: Kaplan-Meier analysis revealed that elevated serum CHI3L1 levels were associated with worse overall survival of HCC patients. Multivariate Cox regression analysis showed that the high-CHI3L1 group (≥198.94 ng/ml) was associated with a shorter survival time compared with that in the low-CHI3L1 group (< 198.94 ng/ml) after adjustment for potential confounding factors (HR =1.43, 95% CI = 1.05-1.94, P = 0.024). Additionally, the nomogram had sufficient calibration and discriminatory power in the training cohort, with C-indexes of 0.723 (95% CI: 0.673-0.772). The validation cohort showed similar results. Finally, we demonstrated that the AUC of the nomogram was 0.752 (95% CI: 0.683-0.821), which had better predictive ability than AFP (AUC: 0.644, 95% CI: 0.577-0.711). Conclusion: Our results confirmed that the CHI3L1 could serve as an independent predictor for OS in HCC patients after hepatectomy. The nomogram showed a good performance in prognosis prediction of HCC.

Development and validation of a prognostic signature of breast cancer based on drug absorption, distribution, metabolism and excretion (ADME)-related genes

The individual variation of carcinogenesis and drug response is influenced by the absorption, distribution, metabolism, and excretion (ADME) of drugs. The utilization of signatures derived from ADME-related genes holds potential for predicting prognosis and treatment response across diverse cancer types. Further investigation is required to completely understand the role of ADME-associated genes in breast cancer. A signature was constructed through the application of a least absolute shrinkage and selection operator regression model, employing prognostic differentially expressed genes found in both cancer tissue and normal tissue. To assess the robustness of the signature, verification analyses were carried out. RT-qPCR was utilized for the validation of gene expression related to risk. Subsequently, a nomogram was developed to enhance the clinical utility of our prognostic tool. The ADME signature, comprising four genes, was established and exhibited a robust association with the prognoses of individuals diagnosed with breast cancer. The nomogram was created by fusing the clinicopathological characteristics with the ADME signature. The ADME signature demonstrated remarkable superiority when compared to the performance of the other individual predictors. Additionally, the analysis of the immune microenvironment revealed that the ImmuneScores of the low-risk group were elevated. The variation in both the infiltration of immune cells and the expression of immune-related genes in the tissues differed among the two groups. For patients with breast cancer, the utilization of ADME signatures as biomarkers presents a significant reference point for prognosis and individualized treatment strategies.

Transcriptomic analysis reveals oxidative stress-related signature and molecular subtypes in cholangio carcinoma

Cholangiocarcinoma (CCA) is a heterogeneous and aggressive malignancy with limited therapeutic options and poor prognosis. The identification of reliable prognostic biomarkers and a deeper understanding of the molecular subtypes are critical for the development of targeted therapies and improvement of patient outcomes. This study aims to uncover oxidative stress-related genes (ORGs) in CCA and develop a prognostic risk model using comprehensive transcriptomic analysis from The Cancer Genome Atlas (TCGA). Through LASSO regression analysis, we identified prognosis-related ORGs and constructed a prognostic signature consisting of six ORGs. This signature demonstrated strong predictive performance in survival analysis and ROC curve assessment. Functional enrichment and GSEA analyses revealed significant enrichment of immune-related pathways among different risk groups. GSVA analysis indicated reduced activity in inflammation and oxidative stress pathways in the high-risk subgroup, and xCell results showed lower immune cell infiltration levels in this group. Additionally, immune checkpoint genes and immune-related pathways were downregulated in the high-risk subgroup. Our research has developed a unique prognostic model focusing on oxidative stress, enabling accurate forecasting of patient outcomes and providing crucial insights and recommendations for the prognosis of individuals with CCA. Future studies should aim to validate these findings in clinical settings and further explore therapeutic targets within oxidative stress pathways.

Cancer-associated fibroblasts-secreted exosomal miR-92a-3p promotes tumor growth and stemness in hepatocellular carcinoma through activation of Wnt/β-catenin signaling pathway by suppressing AXIN1

Cancer-associated fibroblasts (CAFs) are a major cellular component in the tumor microenvironment and have been shown to exhibit protumorigenic effects in hepatocellular carcinoma (HCC). This study aimed to delve into the mechanisms underlying the tumor-promoting effects of CAFs in HCC. Small RNA sequencing was conducted to screen differential expressed microRNAs in exosomes derived from CAFs and normal fibroblasts (NFs). The miR-92a-3p expression was then measured using reverse transcriptase quantitative real-time PCR in CAFs, NFs, CAFs-derived exosomes (CAFs-Exo), and NF-derived exosomes (NFs-Exo). Compared to NFs or NF-Exo, CAFs and CAFs-Exo significantly promoted HCC cell proliferation, migration, and stemness. Additionally, compared to NFs or NF-Exo, miR-92a-3p level was notably higher in CAFs and CAFs-Exo, respectively. Exosomal miR-92a-3p was found to enhance HCC cell proliferation, migration, and stemness. Meanwhile, AXIN1 was targeted by miR-92a-3p. Exosomal miR-92a-3p could activate β-catenin/CD44 signaling in HCC cells by inhibiting AXIN1 messenger RNA. Furthermore, in vivo studies verified that exosomal miR-92a-3p notably promoted tumor growth and stemness through targeting AXIN1/β-catenin axis. Collectively, CAFs secreted exosomal miR-92a-3p was capable of promoting growth and stemness in HCC through activation of Wnt/β-catenin signaling pathway by suppressing AXIN1. Therefore, targeting CAFs-derived miR-92a-3p may be a potential strategy for treating HCC.

Identification of signature genes and immune infiltration analysis in thyroid cancer based on PANoptosis related genes

Background

Thyroid cancer is the most common malignancy of the endocrine system. PANoptosis is a specific form of inflammatory cell death. It mainly includes pyroptosis, apoptosis and necrotic apoptosis. There is increasing evidence that PANoptosis plays a crucial role in tumour development. However, no pathogenic mechanism associated with PANoptosis in thyroid cancer has been identified.

Methods

Based on the currently identified PANoptosis genes, a dataset of thyroid cancer patients from the GEO database was analysed. To screen the common differentially expressed genes of thyroid cancer and PANoptosis. To analyse the functional characteristics of PANoptosis-related genes (PRGs) and screen key expression pathways. The prognostic model was established by LASSO regression and key genes were identified. The association between hub genes and immune cells was evaluated based on the CIBERSORT algorithm. Predictive models were validated by validation datasets, immunohistochemistry as well as drug-gene interactions were explored.

Results

The results showed that eight key genes (NUAK2, TNFRSF10B, TNFRSF10C, TNFRSF12A, UNC5B, and PMAIP1) exhibited good diagnostic performance in differentiating between thyroid cancer patients and controls. These key genes were associated with macrophages, CD4+ T cells and neutrophils. In addition, PRGs were mainly enriched in the immunomodulatory pathway and TNF signalling pathway. The predictive performance of the model was confirmed in the validation dataset. The DGIdb database reveals 36 potential therapeutic target drugs for thyroid cancer.

Conclusion

Our study suggests that PANoptosis may be involved in immune dysregulation in thyroid cancer by regulating macrophages, CD4+ T cells and activated T and B cells and TNF signalling pathways. This study suggests potential targets and mechanisms for thyroid cancer development.

Human serum proteomics reveals a molecular signature after one night of sleep deprivation

Study Objectives

Sleep deprivation is highly prevalent and caused by conditions such as night shift work or illnesses like obstructive sleep apnea. Compromised sleep affects cardiovascular-, immune-, and neuronal systems. Recently, we published human serum proteome changes after a simulated night shift. This pilot proteomic study aimed to further explore changes in human blood serum after 6 hours of sleep deprivation at night.

Methods

Human blood serum samples from eight self-declared healthy females were analyzed using Orbitrap Eclipse mass spectrometry (MS-MS) and high-pressure liquid chromatography. We used a within-participant design, in which the samples were taken after 6 hours of sleep at night and after 6 hours of sleep deprivation the following night. Systems biological databases and bioinformatic software were used to analyze the data and comparative analysis were done with other published sleep-related proteomic datasets.

Results

Out of 494 proteins, 66 were found to be differentially expressed proteins (DEPs) after 6 hours of sleep deprivation. Functional enrichment analysis revealed the associations of these DEPs with several biological functions related to the altered regulation of cellular processes such as platelet degranulation and blood coagulation, as well as associations with different curated gene sets.

Conclusions

This study presents serum proteomic changes after 6 hours of sleep deprivation, supports previous findings showing that short sleep deprivation affects several biological processes, and reveals a molecular signature of proteins related to pathological conditions such as altered coagulation and platelet function, impaired lipid and immune function, and cell proliferation. Data are available via ProteomeXchange with identifier PXD045729. This paper is part of the Genetic and other molecular underpinnings of sleep, sleep disorders, and circadian rhythms including translational approaches Collection.

Glycometabolism and lipid metabolism related genes predict the prognosis of endometrial carcinoma and their effects on tumor cells

BACKGROUND

Glycometabolism and lipid metabolism are critical in cancer metabolic reprogramming. The primary aim of this study was to develop a prognostic model incorporating glycometabolism and lipid metabolism-related genes (GLRGs) for accurate prognosis assessment in patients with endometrial carcinoma (EC).

METHODS

Data on gene expression and clinical details were obtained from publicly accessible databases. GLRGs were obtained from the Genecards database. Through nonnegative matrix factorization (NMF) clustering, molecular groupings with various GLRG expression patterns were identified. LASSO Cox regression analysis was employed to create a prognostic model. Use rich algorithms such as GSEA, GSVA, xCELL ssGSEA, EPIC,CIBERSORT, MCPcounter, ESTIMATE, TIMER, TIDE, and Oncoppredict to analyze functional pathway characteristics of the forecast signal, immune status, anti-tumor therapy, etc. The expression was assessed using Western blot and quantitative real-time PCR techniques. A total of 113 algorithm combinations were combined to screen out the most significant GLRGs in the signature for in vitro experimental verification, such as colony formation, EdU cell proliferation, wound healing, apoptosis, and Transwell assays.

RESULTS

A total of 714 GLRGs were found, and 227 of them were identified as prognostic-related genes. And ten GLRGs (AUP1, ESR1, ERLIN2, ASS1, OGDH, BCKDHB, SLC16A1, HK2, LPCAT1 and PGR-AS1) were identified to construct the prognostic model of patients with EC. Based on GLRGs, the risk model's prognosis and independent prognostic value were established. The signature of GLRGs exhibited a robust correlation with the infiltration of immune cells and the sensitivity to drugs. In cytological experiments, we selected HK2 as candidate gene to verify its value in the occurrence and development of EC. Western blot and qRT-PCR revealed that HK2 was substantially expressed in EC cells. According to in vitro experiments, HK2 knockdown can increase EC cell apoptosis while suppressing EC cell migration, invasion, and proliferation.

CONCLUSION

The GLRGs signature constructed in this study demonstrated significant prognostic value for patients with endometrial carcinoma, thereby providing valuable guidance for treatment decisions.

Development of a novel senescence-related gene signature to predict clinical outcomes, immune landscape, and chemotherapeutic sensitivity in oral squamous cell carcinoma

BACKGROUND

Cellular senescence significantly associates with tumor initiation, progression, and therapeutic response across multiple cancers. Here, we sought to develop a novel senescence-related genes (SRGs)-derived signature for oral squamous cell carcinoma (OSCC) prognostication and therapeutic response prediction.

METHODS

OSCC-specific SRG prognostic signature was established with univariate Cox regression, Kaplan-Meier survival, and LASSO-penalized multivariate Cox regression analyses. A SRG nomogram integrating this signature and selected clinicopathological parameters were constructed by multivariate Cox regression. SiRNA-mediated gene knockdown was exploited to validate its function in vitro. The utilities of SRG signature in predicting immune status and chemotherapeutic sensitivities were analyzed.

RESULTS

The prognostic performance of SRG signature/nomogram was satisfactory in multiple independent cohorts. CDK1 knockdown induced senescence phenotype in vitro. Moreover, SRG signature scores negatively correlated with tumor-infiltrating immune cells and associated with multiple chemotherapeutic drug sensitivities.

CONCLUSIONS

Our results established SRG-derived signature/nomogram as powerful predictors for prognosis and chemotherapeutic response for OSCC.

Correlation analysis of disulfidptosis-related gene signatures with clinical prognosis and immunotherapy response in sarcoma

Disulfidptosis, a newly discovered type of programmed cell death, could be a mechanism of cell death controlled by SLC7A11. This could be closely associated with tumor development and advancement. Nevertheless, the biological mechanism behind disulfidptosis-related genes (DRGs) in sarcoma (SARC) is uncertain. This study identified three valuable genes (SLC7A11, RPN1, GYS1) associated with disulfidptosis in sarcoma (SARC) and developed a prognostic model. The multiple databases and RT-qPCR data confirmed the upregulated expression of prognostic DRGs in SARC. The TCGA internal and ICGC external validation cohorts were utilized to validate the predictive model capacity. Our analysis of DRG riskscores revealed that the low-risk group exhibited a more favorable prognosis than the high-risk group. Furthermore, we observed a significant association between DRG riskscores and different clinical features, immune cell infiltration, immune therapeutic sensitivity, drug sensitivity, and RNA modification regulators. In addition, two external independent immunetherapy datasets and clinical tissue samples were collected, validating the value of the DRGs risk model in predicting immunotherapy response. Finally, the SLC7A11/hsa-miR-29c-3p/LINC00511, and RPN1/hsa-miR-143-3p/LINC00511 regulatory axes were constructed. This study provided DRG riskscore signatures to predict prognosis and response to immunotherapy in SARC, guiding personalized treatment decisions.

Advances in targeted therapy and biomarker research in thyroid cancer

Driven by the intricacy of the illness and the need for individualized treatments, targeted therapy and biomarker research in thyroid cancer represent an important frontier in oncology. The variety of genetic changes associated with thyroid cancer demand more investigation to elucidate molecular details. This research is clinically significant since it can be used to develop customized treatment plans. A more focused approach is provided by targeted therapies, which target certain molecular targets such as mutant BRAF or RET proteins. This strategy minimizes collateral harm to healthy tissues and may also reduce adverse effects. Simultaneously, patient categorization based on molecular profiles is made possible by biomarker exploration, which allows for customized therapy regimens and maximizes therapeutic results. The benefits of targeted therapy and biomarker research go beyond their immediate clinical impact to encompass the whole cancer landscape. Comprehending the genetic underpinnings of thyroid cancer facilitates the creation of novel treatments that specifically target aberrant molecules. This advances the treatment of thyroid cancer and advances precision medicine, paving the way for the treatment of other cancers. Taken simply, more study on thyroid cancer is promising for better patient care. The concepts discovered during this investigation have the potential to completely transform the way that care is provided, bringing in a new era of personalized, precision medicine. This paradigm shift could improve the prognosis and quality of life for individuals with thyroid cancer and act as an inspiration for advances in other cancer types.

Cell Senescence-Related Genes as Biomarkers for Prognosis and Immunotherapeutic Response in Colon Cancer

Colon adenocarcinoma (COAD) stands out as the most prevalent malignancy diagnosed within the gastrointestinal tract, bearing substantial incidence and mortality rates. The processes of ageing and senescence intricately intertwine with tumorigenesis and immune regulation, concurrently exerting influence on the remodelling of the tumor microenvironment (TME). This phenomenon, in turn, significantly impacts the efficacy of immunotherapeutic interventions. Despite this awareness, the comprehensive understanding of the intricate interplay between cellular senescence and TME in the context of COAD remains elusive. Further inquiry is imperative to comprehensively gauge the relevance of cellular senescence-related genes (CSGs) in the realms of immune infiltration and the prognostication of COAD. Differentially expressed cell senescence-related genes (DE-CSGs) within COAD tumors and normal specimens were discerned through analysis of the TCGA-COAD dataset. Leveraging univariate, LASSO, and multivariate Cox regression analyses, we formulated a prognostic risk signature. Subsequent validation utilised two independent GEO datasets. Furthermore, a nomogram was devised to gauge the prognostic significance of this signature. Additionally, the immune landscape of the Cell Senescence-related Signature (CSS) was characterised using CIBERSORT and TIMER algorithms. The expression levels of CSGs were quantified through RT-PCR in COAD specimens. Drawing upon mRNA expression profiles of 191 DE-CSGs, we successfully established a 9-gene CSS, demonstrating its autonomy as a prognostic determinant for COAD patients. Those assigned high-risk scores exhibited an immunosuppressive phenotype, marked by elevated proportions of resting CD4+memory T cells and macrophages M0, correlating with diminished overall survival. Subsequent analyses uncovered that the amalgamation of CSS with the expression profiles of immune checkpoint key genes effectively predicted patient prognosis. Furthermore, patients with low-risk scores demonstrated a potential association with more favourable therapeutic outcomes in the context of immunotherapy. This study has culminated in the development of a prognostic risk signature grounded in cell senescence-related genes for COAD. We posit that the CSS plays a regulatory role in immune infiltration, emerging as a robust biomarker for prognosis and a predictive indicator for immunotherapeutic responsiveness within the COAD landscape.

Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy

Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments. Programmed cell death (PCD) pathways play a pivotal role in the development and progression of various cancers, offering potential as prognostic indicators and drug sensitivity markers for LUAD patients. The development and validation of predictive models were conducted by integrating 13 PCD patterns with comprehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizing the machine learning algorithms, we identified ten critical differentially expressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a programmed cell death index (PCDI) based on these genes across the aforementioned cohorts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation between the PCDI and immune features in LUAD, including immune cell infiltration and the expression of immune checkpoint molecules. Additionally, we found that patients with a high PCDI score may exhibit resistance to immunotherapy and standard adjuvant chemotherapy regimens; however, they may benefit from other FDA-supported drugs such as docetaxel and dasatinib. In conclusion, the PCDI holds potential as a prognostic signature and can facilitate personalized treatment for LUAD patients.

Characteristics and immune checkpoint status of radioiodine-refractory recurrent papillary thyroid carcinomas from Ukrainian Chornobyl Tissue Bank donors

Introduction

The radioiodine-refractory (RAI-R) recurrent papillary thyroid carcinomas (PTCs) are more frequent in elderly patients and have an unfavorable prognosis. Data on the prevalence and characteristics of RAI-R recurrent PTCs in patients of young and middle age with or without a history of radiation exposure in childhood are poorly described. The aim of the current study was: i) to determine the frequency of RAI-R recurrent PTCs among donors of the Chornobyl Tissue Bank (CTB) and analyze the clinicopathological features of primary tumors (PTs), primary metastases (PMTSs), recurrent metastases (RMTSs) and risk factors for RMTS, and ii) to determine the immune checkpoint status (ICS) of the RAI-R recurrent PTCs and to assess the factors associated with ICS positivity.

Methods

Sixty RAI-R recurrent PTCs (46 exposed to radiation and 14 non-exposed, 2.5% of all cases registered with the CTB) from the Ukrainian patients aged up to 48 years were identified.

Results

The clinicopathological characteristics of the PTs moderately to weakly resembled those of the PMTS and RMTS from the same patients while the metastatic tissues were highly similar. The multivariate model of RMTS included the dominant solid-trabecular growth pattern of the PT, cystic changes, N1b metastases, and the probability of a causation (POC) of PTC by radiation as risk factors. Among these factors, the lateral PMTS (N1b) had the strongest effect. The longer period of latency (a POC component) was the second statistically significant characteristic. ICS percent agreement between the PT and RAI-R RMTS was 91.5%; 23.7% of PTs and 28.8% of RMTSs had positive ICS (positive PD-L1 tumor epithelial cells (TECs) and positive PD-L1/PD1 tumor-associated immune cells). ICS positivity of PTs was associated with pronounced oncocytic changes and high density of the p16INK4A-positive TECs in the invasive areas of PTs. In RMTSs, ICS positivity was associated with pronounced oncocytic changes and Ki-67 labeling index ≥ 4.5% of PTs, and the dominant solid-trabecular growth pattern, Ki-67 labeling index ≥ 7.6% and p16INK4A-positivity of RMTS.

Discussion

The findings are of clinical relevance and may be useful for developing individual treatment approaches for patients with RAI-R recurrent PTCs possibly involving immunotherapy.

A prognostic signature associated with cell senescence predicts survival outcomes and strongly associates with immunotherapy and chemotherapy response in breast cancer

The objective of this study is to assess the predictive potency of cell senescence-related genes (CSRGs) in breast cancer (BC) and establish a risk signature. Trascriptome data of CSRGs were obtained from the TCGA and GEO databases. Consensus clustering was used to generate CSRGs-based molecular clusters for BC patients. A CSRGs-derived risk signature was built using multiple Cox regression analyses of differentially expressed genes (DEGs) between clusters. The prognosis, immune infiltration, chemotherapy and immunotherapy response between different risk groups were analyzed and compared. Two molecular clusters of BC patients were generated on the basis of 79 differentially expressed CSRGs, which showed distinct prognosis and immune infiltration. A total of 1403 DEGs between the CSRGs-derived clusters were found, and 10 of them were independent prognostic genes that used to construct a risk signature. The results demonstrated that patients with older age and advanced stage presented with a higher risk scores. In addition, the risk signature was found to be associated with outcomes, immune infiltration, chemotherapy and immunotherapy response. Patients in the low-risk group showed a favorable prognosis and higher immunotherapy response than those in the high-risk group. Finally, we developed a highly stable nomogram that incorporates risk signature, chemotherapy, radiotherapy, and stage variables, enabling accurate prediction of the overall survival (OS) of individual patients. To conclude, the signature derived from CSRGs holds great promise as a biomarker for prognostic assessment of BC and may serve as a valuable tool in guiding immunotherapy.