Identification of prognostic aging-related genes associated with immunosuppression and inflammation in head and neck squamous cell carcinoma

An Aging-Related lncRNA Signature Establishing for Breast Cancer Prognosis and Immunotherapy Responsiveness Prediction

Purpose

Emerging evidence demonstrates the vital role of aging and long non-coding RNAs (lncRNAs) in breast cancer (BC) progression. Our study intended to develop a prognostic risk model based on aging-related lncRNAs (AG-lncs) to foresee BC patients' outcomes.

Patients and Methods

307 aging-related genes (AGs) were sequenced from the TCGA project. Then, 697 AG-lncs were identified by the co-expression analysis with AGs. Using multivariate and univariate Cox regression analysis, and LASSO, 6 AG-lncs, including al136531.1, mapt-as1, al451085.2, otud6b-as1, tnfrsf14-as1, and linc01871, were validated to compute the risk score and establish a risk signature. Expression levels of al136531.1, mapt-as1, al451085.2, tnfrsf14-as1, and linc01871 were higher in low-risk BC patients, whereas otud6b-as1 expression was higher in high-risk BC patients. In the training and testing set, high-risk patients performed shorter PFI, OS, and DFS than low-risk patients.

Results

Our risk signature had the highest concordance index among other established prognostic signatures and displayed ideal predictive ability for 1-, 3- and 5-year patient OS in the nomogram. Additionally, BC patients with different risk score levels showed different immune statuses and responses to immunotherapy via GSEA, ssGSEA, ESTIMATE algorithm, and TIDE algorithm analysis. Of note, the qRT-PCR analysis validated that these 6 AG-lncs expressed quite differentially in BC tissues at various clinical stages.

Conclusion

The risk signature of 6 AG-lncs might offer a novel prognostic biomarker and promisingly enhance BC immunotherapy's effectiveness.

The significance of elective neck dissection for patients with T2N0M0 OSCC at different ages

BACKGROUND

The aim of this study was to determine the significance of elective neck dissection (END) for patients of different ages with T2N0M0 oral squamous cell carcinoma (OSCC) and sought to analyze the reasons behind it and its value for clinical guidance.

METHODS

This study enrolled 391 patients with T2N0M0 OSCC who were surgically treated in our hospital and were divided into young-, moderate-, and advanced-age groups according to our previous study. The Chi-square test and Kaplan-Meier analysis were performed for statistical analysis.

RESULTS

Compared with moderate- and advanced-age patients, young patients with T2N0M0 OSCC had higher lymph node metastasis rates and lymph node ratios. Therefore, END significantly improved the recurrence (p = 0.001) and survival (p = 0.001) for young patients, but not for moderate-age patients. Advanced-age patients even benefit from watchful waiting. END significantly improved recurrence and survival in young patients with smoking or alcohol consumption habits.

CONCLUSIONS

END improved the prognosis of young patients, and it was related to their higher metastasis rate. However, advanced-age patients benefited from the wait-and-see policy. END is essential for the young patients with smoking or drinking habit, it is also highly recommended for nonsmokers and nondrinkers.

Aging-related biomarker discovery in the era of immune checkpoint inhibitors for cancer patients

Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.

Construction of a prognosis model of head and neck squamous cell carcinoma pyroptosis and an analysis of immuno-phenotyping based on bioinformatics

Background

Head and neck squamous cell carcinoma (HNSCC) is currently the sixth most common cancer worldwide, and its prevalence and recurrence rates are gradually increasing. To study the relationship between HNSCC and cell pyroptosis and provide new treatment options for HNSCC, a prognostic model of pyroptosis-related genes (PRGs) was established to predict the prognosis of patients with HNSCC, and an immune correlation analysis was performed.

Methods

A total of 53 PRGs were selected. We comprehensively analyzed the role of these PRGs in HNSCC through multiple omics data-set integration. We then identified two different molecular subtypes and found that changes in multi-layer PRGs were associated with clinicopathological characteristics, prognosis, and tumor microenvironment cell-infiltration characteristics in patients. Next, prognostic models were generated for nine PRGs; that is, cytotoxic T lymphocyte antigen 4 (CTLA4), V-set and immunoglobulin domain containing 4 (VSIG4), heparin-binding-epidermal growth factor (HBEGF), aquaporin-1 (AQP1), sodium channel epithelial 1 subunit delta (SCNN1D), argininosuccinate synthase 1 (ASS1), family with sequence similarity 83 member (FAM83), cyclin dependent kinase inhibitor 2A (CDKN2A), and serine protease inhibitor Kazal 6 (SPINK6). Finally, a risk-score model was constructed, and the Kaplan-Meier method was used to evaluate overall survival. In addition, the immune environment and drug sensitivity were analyzed.

Results

This study showed that pyroptosis is closely related to HNSCC. The scores generated by the risk markers based on the new nine PRGs were identified as independent risk factors for predicting HNSCC. The differentially expressed genes between the low- and high-risk groups were further found to be related to the tumor immune cells and pathways. In addition, the risk score was found to be significantly correlated with chemosensitivity.

Conclusions

Our comprehensive analysis of PRGs revealed their potential role in the tumor immune microenvironment, clinicopathological characteristics, and prognosis. These findings may improve our understanding of pyroptosis in HNSCC and may provide new ideas for evaluating prognosis and developing more effective immunotherapy strategies.

Geroscience: Aging and Oral Health Research

Research in aging has significantly advanced; scientists are now able to identify interventions that slow the biologic aging processes (i.e., the "hallmarks of aging"), thus delaying the onset and progression of multiple diseases, including oral conditions. Presentations given during the 3-part session "Geroscience: Aging and Oral Health Research," held during the 2023 American Association for Dental, Oral, and Craniofacial Research meeting, are summarized in this publication. Speakers' topics spanned the translational research spectrum. Session 1 provided an overview of the geroscience and health span (disease-free and functional health throughout life) concepts. The common molecular mechanisms between oral cancer and aging were discussed, and research was presented that showed periodontal microflora as a potential factor in Alzheimer's disease progression. Session 2 focused on behavioral and social science aspects of aging and their oral health significance. The keynote provided evidence that loneliness and isolation can have major health effects. These social conditions, along with poor oral health, tooth loss, and cognitive decline, could potentially affect healthy eating ability and systemic health in older adults. Research could help elucidate the directions and pathways connecting these seemingly disparate conditions. Session 3 focused on the delivery of oral care in different settings and the many barriers to access care faced by older adults. Research is needed to identify and implement effective technology and strategies to improve access to dental care, including new delivery and financing mechanisms, workforce models, interprofessional provider education and practice, and use of big data from medical-dental integration of electronic health records. Research to improve the "oral health span," reduce oral health disparities, and increase health equity must be tackled at all levels from biologic pathways to social determinants of health and health policies.

Identifying Crucial Biomarkers in Osteoporosis and Ulcerative Colitis Through Bioinformatics Analysis of Co-expressed Genes

Osteoporosis (OP) and ulcerative colitis (UC), prevalent immune diseases, exert a substantial socioeconomic impact globally. This study identifies biomarkers for these diseases, paving the way for in-depth research. Initially, the Gene Expression Omnibus (GEO) database was employed to analyze datasets GSE35958 and GSE87466. This analysis aimed to pinpoint co-expression differential genes (DEGs) between OP and UC. Subsequently, the Metascape database facilitated the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of these DEGs' co-expression. For network construction and visualization, the STRING11.5 database along with Cytoscape 3.7.2 (Cytoscape Team, USA) were utilized to create a protein-protein interaction (PPI) network. Moreover, Cytoscape's cytoHubba plugin was instrumental in identifying the central genes, known as hub genes. In the datasets GSE35958 and GSE87466, 156 co-expressed DEGs were discovered. The PPI network, constructed using STRING11.5 and Cytoscape 3.7.2, comprises 96 nodes and 222 connections. Notably, seven hub genes were identified, namely COL6A1, COL6A2, BGN, NID1, PLAU, TGFB1, and PLAUR. These DEGs were predominantly enriched in pathways such as extracellular matrix organization and collagen-containing extracellular matrix, as per GO analysis. For diagnostic model construction and hub gene validation, datasets GSE56815 and GSE107499 from the GEO database were employed. The top five hub genes were validated. In conclusion, the hub genes identified in this study played a significant role in the early diagnosis, prevention, and treatment of OP and UC. Furthermore, they provide fresh insights into the underlying mechanisms of these diseases' development and progression.

Bioinformatics identification and validation of aging‑related molecular subtype and prognostic signature in breast cancer

Patients with metastatic breast cancer have a poor clinical outcome, accounting for more than 90 percent of breast cancer-related deaths. Aging could regulate many biological processes in malignancies by regulating cell senescence. The role of aging has not been fully clarified. Consensus cluster analysis was performed to differentiate The Cancer Genome Atlas (TCGA) breast cancer cases. Least absolute shrinkage and selection operator (LASSO) cox regression analysis was performed to construct an aging-related prognostic signature. A total of 118 differentially expressed aging-related genes (ARGs) was obtained in breast cancer. Consensus clustering analysis identified 3 categories of TCGA-breast cancer with significant difference in prognosis and immune infiltration. We also constructed an aging-related prognostic signature for breast cancer, which had a good performance in predicting the 1-year, 3-year and 5-year OS and disease specific survival (DSS) of breast cancer patients. Further single gene analysis revealed that the expression of PIK3R1 was significantly different in different pT and pN stages of breast cancer. Moreover, low expression of PIK3R1 showed resistance to many drugs based on the data of Genomics of Drug Sensitivity in Cancer (GDSC) and Genomics of Therapeutics Response Portal (CTRP). PIK3R1 played a vital role in many well-known cancer-related pathways. The current study identified 3 clusters of TCGA-breast cancer cases with significant differences in prognosis and immune infiltration. We also constructed an aging-related prognostic signature for breast cancer. However, further in vivo and in vitro studies should be conducted to verify these results.

Bioinformatics identification and validation of aging-related molecular subtype and prognostic signature in sarcoma

Aging could regulate many biological processes in malignancies by regulating cell senescence. Consensus cluster analysis was conducted to differentiate TCGA sarcoma cases. LASSO cox regression analysis was performed to construct an aging-related prognostic signature. We identified two categories of TCGA-sarcoma with significant difference in prognosis, immune infiltration and chemotherapy and targeted therapy. Moreover, an aging-related prognostic signature was constructed for sarcoma, which had a good performance in predicting the 3-year and 5-year overall survival of sarcoma patients. We also identified a lncRNA MALAT1/miR-508-3p/CCNA2 regulatory axis for sarcoma. This stratification could provide more evidence for estimating prognosis and immunotherapy of sarcoma.

Construction and validation of an aging-related gene signature predicting the prognosis of pancreatic cancer

Background: Pancreatic cancer is a malignancy with a high mortality rate and worse prognosis. Recently, public databases and bioinformatics tools make it easy to develop the prognostic risk model of pancreatic cancer, but the aging-related risk signature has not been reported. The present study aimed to identify an aging-related risk signature with potential prognostic value for pancreatic cancer patients. Method: Gene expression profiling and human clinical information of pancreatic cancer were derived from The Cancer Genome Atlas database (TCGA). Aging-related gene sets were downloaded from The Molecular Signatures Database and aging-related genes were obtained from the Human Ageing Genomic Resources database. Firstly, Gene set enrichment analysis was carried out to investigate the role of aging process in pancreatic cancer. Secondly, differentially expressed genes and aging-related prognostic genes were screened on the basis of the overall survival information. Then, univariate COX and LASSO analysis were performed to establish an aging-related risk signature of pancreatic cancer patients. To facilitate clinical application, a nomogram was established to predict the survival rates of PCa patients. The correlations of risk score with clinical features and immune status were evaluated. Finally, potential therapeutic drugs were screened based on the connectivity map (Cmap) database and verified by molecular docking. For further validation, the protein levels of aging-related genes in normal and tumor tissues were detected in the Human Protein Atlas (HPA) database. Result: The genes of pancreatic cancer were markedly enriched in several aging-associated signaling pathways. We identified 14 key aging-related genes related to prognosis from 9,020 differentially expressed genes and establish an aging-related risk signature. This risk model indicated a strong prognostic capability both in the training set of TCGA cohort and the validation set of PACA-CA cohort and GSE62452 cohort. A nomogram combining risk score and clinical variables was built, and calibration curve and Decision curve analysis (DCA) have proved that it has a good predictive value. Additionally, the risk score was tightly linked with tumor immune microenvironment, immune checkpoints and proinflammatory factors. Moreover, a candidate drug, BRD-A47144777, was screened and verified by molecular docking, indicating this drug has the potential to treat PCa. The protein expression levels of GSK3B, SERPINE1, TOP2A, FEN1 and HIC1 were consistent with our predicted results. Conclusion: In conclusion, we identified an aging-related signature and nomogram with high prediction performance of survival and immune cell infiltration for pancreatic cancer. This signature might potentially help in providing personalized immunotherapy for patients with pancreatic cancer.

Identification and Analysis of Senescence-Related Genes in Head and Neck Squamous Cell Carcinoma by a Comprehensive Bioinformatics Approach

Head and neck cancer is the sixth most frequent cancer all over the world, with the majority of subtypes of head and neck squamous cell carcinoma (HNSCC). Cellular senescence-associated genes have been confirmed to play a critical role in cancer and have the potential to be prognostic biomarkers for cancer. Clinical information of HNSCC samples and expression data were acquired from public databases. Expression profiles of genes related to cellular senescence were used to identify molecular subtypes by consensus clustering. To screen differentially expressed genes (DEGs) between different subtypes, differential analysis was performed. We used the univariate Cox regression to identify prognostic DEGs and performed least absolute shrinkage and selection operator (LASSO) to optimize and construct a prognostic model. CIBERSORT, ESTIMATE, and TIDE tools were applied to estimate immune characteristics. Four molecular subtypes were established based on cellular senescence-associated genes. Differential prognosis was observed among different subtypes with C4 having the longest overall survival and C1 having the worst prognosis. C4 subtype also showed the highest immune infiltration. We screened a total of eight cellular senescence prognosis-related genes and established a cellular senescence-related signature score (CSRS.Score) that could stratify samples into high-CSRS.Score and low-CSRS.Score groups. The high-CSRS.Score group had worse prognosis, lower immune infiltration, and lower response to immunotherapy. We further improved the prognostic model and survival prediction by combining CSRS.Score with clinicopathological features using a decision tree model, which had high predictive accuracy and survival prediction. This study demonstrated an important role of cellular senescence in HNSCC. The identified eight cellular senescence-associated genes have the potential to provide ideas for adjuvant treatment and personalized treatment of HNSCC patients.

The Aging-Related Prognostic Signature Reveals the Landscape of the Tumor Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

Background

Numerous studies have shown that the aging microenvironment played a huge impact on tumor progression. However, the clinical prognostic value of aging-related risk signatures and their effects on the tumor immune microenvironment (TIME) in head and neck squamous cell carcinoma (HNSCC) remains largely unclear. This study aimed to identify novel prognostic signatures based on aging-related genes (AGs) and reveal the landscape of the TIME in HNSCC.

Methods

Differentially expressed AGs were identified using the gene set enrichment analysis (GSEA). The prognostic risk model of AGs was established by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. The independent prognostic value of the risk model and the correlations of the prognostic signature with immune score, tumor immune cell infiltration, and immune checkpoints were systematically analyzed.

Results

A prognostic risk model of four AGs (BAK1, DKK1, CDKN2A, and MIF) was constructed and validated in the training and testing datasets. Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed that the four-AG risk signature possessed an accurate predictive value for the prognosis of patients with HNSCC. Correlation analysis revealed that the risk score was negatively associated with immune score and immune cell infiltration level while positively correlated with immune checkpoint blockade (ICB) response score. Patients of the high-risk subtype contained higher infiltration levels of resting natural killer (NK) cells, M0 macrophages, M2 macrophages, and resting mast cells while having lower infiltration levels of memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells (Tregs), and activated mast cells than did those of the low-risk subtype. The expressions of CTLA4, PDCD1, and TIGIT were downregulated while the PDCD1LG2 expression was upregulated in the high-risk subtype compared to those in the low-risk subtype. Furthermore, the four selected AGs in the risk model were demonstrated to possess important functions in immune cell infiltration and ICB response of HNSCC.

Conclusions

The aging-related risk signature is a reliable prognostic model for predicting the survival of HNSCC patients and provides potential targets for improving outcomes of immunotherapy.

An Update on the Immunotherapy for Oropharyngeal Squamous Cell Carcinoma

Oropharyngeal squamous cell carcinoma (OPSCC) is an uncommon malignancy worldwide. Remarkably, the rising incidence of OPSCC has been observed in many developed countries over the past few decades. On top of tobacco smoking and alcohol consumption, human papillomavirus (HPV) infection has become a major etiologic factor for OPSCC. The radiotherapy-based or surgery-based systemic therapies are recommended equally as first-line treatment, while chemotherapy-based strategy is applied to advanced diseases. Immunotherapy in head and neck squamous cell carcinoma (HNSCC) is currently under the spotlight, especially for patients with advanced diseases. Numerous researches on programmed death-1/programmed death-ligand 1 checkpoint inhibitors have proven beneficial to patients with metastatic HNSCC. In 2016, nivolumab and pembrolizumab were approved as the second-line treatment for advanced metastatic HNSCC by the USA Food and Drug Administration. Soon after, in 2019, the USA Food and Drug Administration approved pembrolizumab as the first-line treatment for patients with unresectable, recurrent, and metastatic HNSCC. It has been reported that HPV-positive HNSCC patients were associated with increased programmed death-ligand 1 expression; however, whether HPV status indicates different treatment outcomes among HNSCC patients treated with immunotherapy has contradicted. Notably, HPV-positive OPSCC exhibits a significantly better clinical response to primary treatment (i.e., radiotherapy, surgery, and chemotherapy) and a more desirable prognosis compared to the HPV-negative OPSCC. This review summarizes the current publications on immunotherapy in HNSCC/OPSCC patients and discusses the impact of HPV infection in immunotherapeutic efficacy, providing an update on the immune landscape and future perspectives in OPSCC.

Characterization of Aging-Related Genes to Predict Prognosis and Evaluate the Tumor Immune Microenvironment in Malignant Melanoma

Objective. Malignant melanoma (MM) is one of the most malignant types of skin cancer and its incidence and mortality rates are increasing worldwide. Aging is well recognized as a significant risk factor for cancer. However, few studies have analyzed in depth the association between aging-related genes (AGs) and malignant melanoma prognosis with tumor immune microenvironment. Methods. Here, we downloaded 471 MM patients from The Cancer Genome Atlas (TCGA) with RNA sequence and clinicopathological data. 58 AGs from the TCGA dataset were examined using Cox regression and the LASSO assay. As a result, a gene signature for aging-related genes was created. The time-dependent ROC curve and Kaplan–Meier analysis were calculated to determine its predictive capability. Moreover, we created a nomogram for the clinicopathologic variables and the AGs gene signature to determine overall survival (OS). We also explored the association between three immune checkpoints, immune cell infiltration, and the aging-related gene signature. Results. We established an aging risk model to identify and predict the immune microenvironment in malignant melanoma. Then we developed and validated a prognosis risk model using three AGs (CSNK1E, C1QA, and SOD-2) in the GSE65904 dataset. The aging signature was positively associated with clinical and molecular characteristics and can be used as a prognostic factor for malignant melanoma. The low aging risk score was associated with a poor prognosis and indicated an immunosuppressive microenvironment. Conclusions. To summarize, we established and validated a model of aging risk based on three aging-related genes that acted as an independent prognostic predictor of overall survival. Besides, it also characterized the immune response in the malignant melanoma microenvironment and could provide a potential indicator of individualized immunotherapy in malignant melanoma.

Comprehensive Characterization of Ageing-Relevant Subtypes Associated With Different Tumorigenesis and Tumor Microenvironment in Prostate Cancer

Objective: Accumulated evidence demonstrates that ageing is a robust risk factor of prostate cancer prognosis. Herein, we conducted a systematic analysis about ageing-relevant molecules and relevant tumor microenvironment features in prostate cancer.

Methods: Transcriptome data, clinical information, and mutational data of prostate cancer patients were retrospectively collected from the Cancer Genome Atlas cohort. In accordance with the expression of specific ageing-relevant genes, prostate cancer patients were clustered with consensus clustering analyses. WGCNA was adopted for determination of subtype-associated co-expression modules and genes. Thereafter, characteristic genes were further screened with random forest algorithm and a prognostic model was conducted with multivariate cox regression analyses. Tumor microenvironment-infiltrating immune cells were estimated with ssGSEA and ESTIMATE. Activities of the cancer immunity cycle and expressions of HLA and immune checkpoint molecules were then quantified across prostate cancer cases. A serious experiment was conducted to investigate the roles of EIF2S2 in prostate tumorigenesis.

Results: This study characterized three ageing-relevant subtypes (C1, C2, and C3) with diverse clinical prognosis. Subtype C1 presented the features of low mutational frequency and immune activation; C2 was characterized by stromal and immune activation; and C3 showed immune suppression. An ageing-derived gene signature was conducted, which independently and robustly predicted patients’ prognosis. Additionally, this signature was in relation to immune inactivation. Among the genes in the signature, EIF2S2 triggered proliferation, invasion, and migration of LNCaP and PC-3 cells.

Conclusion: Collectively, ageing-relevant molecular subtypes and gene signature might be of great significance to determine clinical outcomes and tumor microenvironment features and immunotherapeutic responses in prostate cancer.

Depiction of Aging-Based Molecular Phenotypes With Diverse Clinical Prognosis and Immunological Features in Gastric Cancer

Objective

Aging acts as a dominating risk factor for human cancers. Herein, we systematically dissected the features of transcriptional aging-relevant genes in gastric cancer from multiple perspectives.

Methods

Based on the transcriptome profiling of prognostic aging-relevant genes, patients with gastric cancer in The Cancer Genome Atlas (TCGA) stomach adenocarcinoma (TCGA-STAD) cohort were clustered with a consensus clustering algorithm. Mutational landscape and chemotherapeutic responses were analyzed and immunological features (immunomodulators, immune checkpoint molecules, cancer immunity cycle, and tumor-infiltrating immune cells) were systematically evaluated across gastric cancer. Weighted gene co-expression network (WGCNA) was conducted for screening aging molecular phenotype-relevant genes, and key genes were identified with Molecular Complex Detection (MCODE) analyses. Expressions of key genes were examined in 20 paired tumors and controls with RT-qPCR and Western blotting. Proliferation and apoptosis were investigated in two gastric cancer cells under MYL9 deficiency.

Results

Three aging-based molecular phenotypes (namely, C1, C2, and C3) were conducted in gastric cancer. Phenotype C1 presented the most prominent survival advantage and highest mutational frequencies. Phenotype C2 indicated low responses to sorafenib and gefitinib, while C3 indicated low responses to vinorelbine and gemcitabine. Additionally, phenotype C2 was characterized by enhanced immune and stromal activation and an inflamed tumor microenvironment. Seven aging molecular phenotype-relevant key genes (ACTA2, CALD1, LMOD1, MYH11, MYL9, MYLK, and TAGLN) were identified, which were specifically upregulated in tumors and in relation to dismal prognosis. Among them, MYL9 deficiency reduced proliferation and enhanced apoptosis in gastric cancer cells.

Conclusion

Collectively, aging-based molecular subtypes may offer more individualized therapy recommendations and prognosis assessment for patients in distinct subtypes.

Development of an Aging-Related Gene Signature for Predicting Prognosis, Immunotherapy, and Chemotherapy Benefits in Rectal Cancer

Objective: Aging is the major risk factor for human cancers, including rectal cancer. Targeting the aging process provides broad-spectrum protection against cancers. Here, we investigate the clinical implications of aging-related genes in rectal cancer.

Methods: Dysregulated aging-related genes were screened in rectal cancer from TCGA project. A LASSO prognostic model was conducted, and the predictive performance was evaluated and externally verified in the GEO data set. Associations of the model with tumor-infiltrating immune cells, immune and stromal score, HLA and immune checkpoints, and response to chemotherapeutic agents were analyzed across rectal cancer. Biological processes underlying the model were investigated through GSVA and GSEA methods. Doxorubicin (DOX)-induced or replicative senescent stromal cells were constructed, and AGTR1 was silenced in HUVECs. After coculture with conditioned medium of HUVECs, rectal cancer cell growth and invasion were investigated.

Results: An aging-related model was established, consisting of KL, BRCA1, CLU, and AGTR1, which can stratify high- and low-risk patients in terms of overall survival, disease-free survival, and progression-free interval. ROC and Cox regression analyses confirmed that the model was a robust and independent predictor. Furthermore, it was in relation to tumor immunity and stromal activation as well as predicted the responses to gemcitabine and sunitinib. AGTR1 knockdown ameliorated stromal cell senescence and suppressed senescent stromal cell-triggered rectal cancer progression.

Conclusion: Our findings suggest that the aging-related gene signature was in relation to tumor immunity and stromal activation in rectal cancer, which might predict survival outcomes and immuno- and chemotherapy benefits.

Coagulome and the tumor microenvironment: an actionable interplay

Human tumors often trigger a hypercoagulable state that promotes hemostatic complications, including venous thromboembolism. The recent application of systems biology to the study of the coagulome highlighted its link to shaping the tumor microenvironment (TME), both within and outside of the vascular space. Addressing this link provides the opportunity to revisit the significance of biomarkers of hemostasis and assess the communication between vasculature and tumor parenchyma, an important topic considering the advent of immune checkpoint inhibitors and vascular normalization strategies. Understanding how the coagulome and TME influence each other offers exciting new prospects for predicting hemostatic complications and boosting the effectiveness of cancer treatment.

Gene Therapy Strategies Targeting Aging-Related Diseases

Rapid advancements have taken place in gene therapy technology. However, effective methods for treating aging- or age-related chronic diseases, which are often closely related to genes or even multiple genes, are still lacking. The path to developing cures is winding, while gene therapy that targets genes related to aging represents an exciting research direction with tremendous potential. Among aging-related genes, some candidates have been studied at different levels, from cell to organismal levels (e.g., mammalian models) with different methods, from overexpression to gene editing. The TERT and APOE have even entered the stage of clinical trials. Even those displaying only a preliminary association with diseases have potential applications. This article discusses the foundations and recent breakthroughs in the field of gene therapy, providing a summary of current mainstream strategies and gene therapy products with clinical and preclinical applications. Finally, we review representative target genes and their potential for treating aging or age-related diseases.

Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer

Breast cancer (BC) is the most commonly diagnosed malignancy accompanied by high invasion and metastasis features. Importantly, emerging studies have supported that aging is a key clue that participates in the immune state and development of BC. Nevertheless, there are no studies concerning the aging-related genes (AGs) in constructing the prognosis signature of BC. Here, to address this issue, we initially performed a systematic investigation of the associations between AGs and BC prognosis and accordingly constructed a prognosis risk model with 10 AGs including PLAU, JUND, IL2RG, PCMT1, PTK2, HSPA8, NFKBIA, GCLC, PIK3CA, and DGAT1 by using the least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis. Meanwhile, our analysis further confirmed that the nomogram possessed a robust performance signature for predicting prognosis compared to clinical characteristics of BC patients, including age, clinical stage, and TNM staging. Moreover, the risk score was confirmed as an independent prognostic index of BC patients and was potentially correlated with immune scores, estimate score, immune cell infiltration level, tumor microenvironment, immunotherapy effect, and drug sensitivity. Furthermore, in the external clinical sample validation, AGs were expressed differentially in patients from different risk groups, and tumor-associated macrophage markers were elevated in high-risk BC tissues with more co-localization of AGs. In addition, the proliferation, transwell, and wound healing assays also confirmed the promoting effect of DGAT1 in BC cell proliferation and migration. Therefore, this well-established risk model could be used for predicting prognosis and immunotherapy in BC, thus providing a powerful instrument for combating BC.

Derivation and Comprehensive Analysis of Aging Patterns in Patients with Bladder Cancer

Background

Aging is an essential risk factor for cancer. However, aging-related genes (ARGs) have not been comprehensively analyzed in bladder cancer (BC). Therefore, the study is aimed at derivating a risk stratification system for BC patients based on ARGs.

Methods

Public databases were used to acquire ARGs sets, transcriptome files, and clinical data. The “limma” package was then used to screen for differential ARGs while also using univariate Cox regression analysis to explore for prognostic ARGs. The “ConsensusClusterPlus” package was used to perform aging patterns in BC patients based on the above prognostic ARGs. Subsequently, aging patterns were investigated in survival prediction, mutation landscape, immunotherapy, immunological checkpoints, and immune microenvironment. We likewise utilized gene enrichment analysis to explore the biological functions that were behind the findings. To construct a risk signature and nonogram for prognostic prediction, we used LASSO and Cox regression analysis based on differential genes in aging patterns. In addition, we plotted a nomogram and validate the accuracy of the risk signature in GEO and TCGA cohorts. We explored the possible biological mechanism using GSEA analysis and preliminarily identified a hub gene using PPI network. Finally, we validated the expression of hub gene in BC cell lines.

Results

We screened 84 downregulated ARGs, 74 upregulated ARGs, and 32 prognostic ARGs in the human aging genome resource. The aging patterns based on prognostic genes had excellent survival prediction (p < 0.001) and discriminatory ability in 405 BC patients. In addition, we found no significant differences in aging patterns in mutation analysis, which were all characterized by TP53, TTN, and KMT2D mutations. It is worth noting that cluster B in the aging patterns has a better response to immunotherapy and a more active immune microenvironment (p < 0.05). In addition, gene enrichment analysis showed that aging patterns may be related to biological processes such as Staphylococcus aureus infection, phagosome, and cytokine-cytokine receptor interaction. Subsequently, we constructed a risk signature based on 16 differential genes from different aging patterns and had good survival prediction ability in both GEO and TCGA cohort. Specifically, survival analysis revealed a significantly shorter survival time in the high-risk group than in the low-risk group (TCGA and GEO, p < 0.001). In addition, AUC values in the ROC analysis predicted 1, 3, and 5 years in TCGA cohort that are 0.713, 0.714, and 0.738, respectively. AUC values predicted 1, 3, and 5 years in GEO cohort that are 0.606, 0.663, and 0.718, respectively. There is no doubt that risk score was an independent prognostic factor from results of multivariate Cox regression analysis in BC patients (p < 0.001). There were also significant differences in immune cell infiltration, immune checkpoint, and immune score between the two groups (p < 0.05), but it should not be ignored that the correlation with the HLA expression was weak. Finally, we identified and validated CLIC3 as a hub gene that may be involved in the Wnt signaling pathway, etc.

Conclusion

We provided robust evidences that aging patterns based on ARGs can guide targeted therapy and survival prediction in BC patients.

Development and Validation of a Novel Gene Signature for Predicting the Prognosis by Identifying m5C Modification Subtypes of Cervical Cancer

Background: 5-Methylcytidine (m5C) is the most common RNA modification and plays an important role in multiple tumors including cervical cancer (CC). We aimed to develop a novel gene signature by identifying m5C modification subtypes of CC to better predict the prognosis of patients. Methods: We obtained the expression of 13 m5C regulatory factors from The Cancer Genome Atlas (TCGA all set, 257 patients) to determine m5C modification subtypes by the "nonnegative matrix factorization" (NMF). Then the "limma" package was used to identify differentially expressed genes (DEGs) between different subtypes. According to these DEGs, we performed Cox regression and Kaplan-Meier (KM) survival analysis to establish a novel gene signature in TCGA training set (128 patients). We also verified the risk prediction effect of gene signature in TCGA test set (129 patients), TCGA all set (257 patients) and GSE44001 (300 patients). Furthermore, a nomogram including this gene signature and clinicopathological parameters was established to predict the individual survival rate. Finally, the expression and function of these signature genes were explored by qRT-PCR, immunohistochemistry (IHC) and proliferation, colony formation, migration and invasion assays. Results: Based on consistent clustering of 13 m5C-modified genes, CC was divided into two subtypes (C1 and C2) and the C1 subtype had a worse prognosis. The 4-gene signature comprising FNDC3A, VEGFA, OPN3 and CPE was constructed. In TCGA training set and three validation sets, we found the prognosis of patients in the low-risk group was much better than that in the high-risk group. A nomogram incorporating the gene signature and T stage was constructed, and the calibration plot suggested that it could accurately predict the survival rate. The expression levels of FNDC3A, VEGFA, OPN3 and CPE were all high in cervical cancer tissues. Downregulation of FNDC3A, VEGFA or CPE expression suppressed the proliferation, migration and invasion of SiHa cells. Conclusions: Two m5C modification subtypes of CC were identified and then a 4-gene signature was established, which provide new feasible methods for clinical risk assessment and targeted therapies for CC.

A Novel Immune-Related Prognostic Signature in Head and Neck Squamous Cell Carcinoma

The immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, very limited robust and reliable immunological biomarkers have been developed that are capable of estimating prognosis in HNSCC patients. In this study, we aimed to identify the effects of novel immune-related gene signatures (IRGs) that can predict HNSCC prognosis. Based on gene expression profiles and clinical data of HNSCC patient cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, a total of 439 highly variable expressed immune-related genes (including 239 upregulated and 200 downregulated genes) were identified by using differential gene expression analysis. Pathway enrichment analysis indicated that these immune-related differentially expressed genes were enriched in inflammatory functions. After process screening in the training TCGA cohort, six immune-related genes (PLAU, STC2, TNFRSF4, PDGFA, DKK1, and CHGB) were significantly associated with overall survival (OS) based on the LASSO Cox regression model. Integrating these genes with clinicopathological features, a multivariable model was built and suggested better performance in determining patients’ OS in the testing cohort, and the independent validation cohort. In conclusion, a well-established model encompassing both immune-related gene signatures and clinicopathological factors would serve as a promising tool for the prognostic prediction of HNSCC.