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Aging Feb 2024Non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer. With the in-depth exploration of cell death manners, numerous studies found that...
Non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer. With the in-depth exploration of cell death manners, numerous studies found that anoikis is an important mechanism that associated with treatment. Therefore, we aimed to explore the prognostic value and treatment guidance of anoikis in NSCLC patients. In the current study, we first constructed a prognostic model based on the anoikis-related genes based on bulk RNA-sequencing and single-cell RNA-sequencing (scRNA-seq) dataset. Then, immuno-correlations of anoikis-related risk scores (ARGRS) were analyzed. In addition, HMGA1, a risky gene in ARGRS, was further explored to define its expression and immuno-correlation. Results showed that patients with higher ARGRS had worse clinical outcomes. Moreover, the five genes in the prognostic model were all highly expressed on tumor cells. Moreover, further analysis found that the ARGRS was negatively correlated with ImmuneScore, but positively with tumor purity. Besides, patients in the ARGRS-high group had lower levels of immunological characteristics, such as the immune-related signaling pathways and subpopulations. Additionally, in the immunotherapy cohorts, patients with the ARGRS-high phenotype were more resistant to immunotherapy and tended to not achieve remission after treatment. Last, HMGA1 was chosen as the representative biomarker, and analysis of the in-house cohort showed that HMGA1 was highly expressed in tumor tissues and correlated with decreased T cell infiltration. To sum up, ARGRS was correlated with a desert tumor microenvironment and identified immune-cold tumors, which can be a novel biomarker for the recognition of immunological characteristics and an immunotherapeutic response in NSCLC.
Topics: Humans; Carcinoma, Non-Small-Cell Lung; HMGA1a Protein; Lung Neoplasms; Anoikis; Prognosis; Biomarkers; RNA; Tumor Microenvironment
PubMed: 38329444
DOI: 10.18632/aging.205522 -
Aging Feb 2024Methods for predicting the outcome of lung adenocarcinoma (LUAD) in the clinic are limited. Anoikis is an important route to programmed cell death in LUAD, and the...
BACKGROUND
Methods for predicting the outcome of lung adenocarcinoma (LUAD) in the clinic are limited. Anoikis is an important route to programmed cell death in LUAD, and the prognostic value of a model constructed with anoikis-related lncRNAs (ARlncRNAs) in LUAD is unclear.
METHODS
Transcriptome and basic information for LUAD patients was obtained from the Cancer Genome Atlas. Coexpression and Cox regression analyses were utilized to identify prognostically significant ARlncRNAs and construct a prognostic signature. Furthermore, the signature was combined with clinical characteristics to create a nomogram. Finally, we performed principal component, enrichment, tumor mutation burden (TMB), tumor microenvironment (TME) and drug sensitivity analyses to evaluate the basic research and clinical merit of the signature.
RESULTS
The prognostic signature developed with eleven ARlncRNAs can accurately predict that high-risk group patients have a worse prognosis, as proven by the receiver operating characteristic (ROC) curve (AUC: 0.718). Independent prognostic analyses indicated that the risk score is a significant independent prognostic element for LUAD (P<0.001). In the high-risk group, enrichment analysis demonstrated that glucose metabolism and DNA replication were the main enrichment pathways. TMB analysis indicated that the high-risk group had a high TMB (P<0.05). Drug sensitivity analyses can recognize drugs that are sensitive to different risk groups. Finally, 11 ARlncRNAs of this signature were verified by RT-qPCR analysis.
CONCLUSIONS
A novel prognostic signature developed with 11 ARlncRNAs can accurately predict the OS of LUAD patients and offer clinical guidance value for immunotherapy and chemotherapy treatment.
Topics: Humans; Anoikis; Prognosis; RNA, Long Noncoding; Adenocarcinoma; Lung; Lung Neoplasms; Tumor Microenvironment
PubMed: 38319706
DOI: 10.18632/aging.205481 -
Cancer Cell International Feb 2024Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays...
Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples. Through the LASSO-Cox analysis, a 2-gene prognostic signature, namely AKT2, and DAPK1, was finally distinguished. We then demonstrated the promising prognostic value of the signature through the K-M survival analysis and time-dependent ROC curves (p-value < 0.05). Moreover, based on the signature and clinical features, we constructed and validated a nomogram model for 1-year, 3-year, and 5-year overall survival, with reliable prognostic values in both TCGA-OV training cohort (p-value < 0.001) and ICGC-OV validation cohort (p-value = 0.030). We evaluated the tumor immune landscape through the CIBERSORT algorithm, which indicated the upregulation of resting Myeloid Dendritic Cells (DCs), memory B cells, and naïve B cells and high expression of key immune checkpoint molecules (CD274 and PDCD1LG2) in the high-risk group. Interestingly, the high-risk group exhibited better sensitivity toward immunotherapy and less sensitivity toward chemotherapies, including Cisplatin and Bleomycin. Especially, based on the IHC of tissue microarrays among 125 OV patients at our institution, we reported that aberrant upregulation of DAPK1 was related to poor prognosis. Conclusively, the anoikis-related signature was a promising tool to evaluate prognosis and predict therapy responses, thus assisting decision-making in the realm of OV precision medicine.
PubMed: 38310291
DOI: 10.1186/s12935-023-03170-8 -
BMB Reports Feb 2024Gefitinib exerts anticancer effects on various types of cancer, such as lung, ovarian, breast, and colon cancers. However, the therapeutic effects of gefitinib on...
Gefitinib exerts anticancer effects on various types of cancer, such as lung, ovarian, breast, and colon cancers. However, the therapeutic effects of gefitinib on cervical cancer and the underlying mechanisms remain unclear. Thus, this study aimed to explore whether gefitinib can be used to treat cervical cancer and elucidate the underlying mechanisms. Results showed that gefitinib induced a caspase-dependent apoptosis of HeLa cells, which consequently became round and detached from the surface of the culture plate. Gefitinib induced the reorganization of actin cytoskeleton and downregulated the expression of p-FAK, integrin β1 and E-cadherin, which are important in cell-extracellular matrix adhesion and cell-cell interaction, respectively. Moreover, gefitinib hindered cell reattachment and spreading and suppressed interactions between detached cells in suspension, leading to poly (ADP-ribose) polymerase cleavage, a hallmark of apoptosis. It also induced detachment-induced apoptosis (anoikis) in C33A cells, another cervical cancer cell line. Taken together, these results suggest that gefitinib triggers anoikis in cervical cancer cells. Our findings may serve as a basis for broadening the range of anticancer drugs used to treat cervical cancer. [BMB Reports 2024; 57(2): 104-109].
Topics: Female; Humans; Anoikis; Gefitinib; HeLa Cells; Uterine Cervical Neoplasms; Apoptosis; Antineoplastic Agents; Cell Line, Tumor
PubMed: 38303562
DOI: 10.5483/BMBRep.2023-0225 -
Mathematical Biosciences and... Jan 2024As a type of programmed cell death, anoikis resistance plays an essential role in tumor metastasis, allowing cancer cells to survive in the systemic circulation and as a...
As a type of programmed cell death, anoikis resistance plays an essential role in tumor metastasis, allowing cancer cells to survive in the systemic circulation and as a key pathway for regulating critical biological processes. We conducted an exploratory analysis to improve risk stratification and optimize adjuvant treatment choices for patients with breast cancer, and identify multigene features in mRNA and lncRNA transcriptome profiles associated with anoikis. First, the variance selection method filters low information content genes in RNA sequence and then extracts the mRNA and lncRNA expression data base on annotation files. Then, the top ten key mRNAs are screened out through the PPI network. Pearson analysis has been employed to identify lncRNAs related to anoikis, and the prognosis-related lncRNAs are selected using Univariate Cox regression and machine learning. Finally, we identified a group of RNAs (including ten mRNAs and six lncRNAs) and integrated the expression data of 16 genes to construct a risk-scoring system for BRCA prognosis and drug sensitivity analysis. The risk score's validity has been evaluated with the ROC curve, Kaplan-Meier survival curve analysis and decision curve analysis (DCA). For the methylation data, we have obtained 169 anoikis-related prognostic methylation sites, integrated these sites with 16 RNA features and further used the deep learning model to evaluate and predict the survival risk of patients. The developed anoikis feature is demonstrated a consistency index (C-index) of 0.778, indicating its potential to predict the survival probability of breast cancer patients using deep learning methods.
Topics: Humans; Female; RNA, Long Noncoding; Breast Neoplasms; RNA, Messenger; Gene Expression Profiling; DNA Methylation; Anoikis; Gene Expression Regulation, Neoplastic
PubMed: 38303479
DOI: 10.3934/mbe.2024069 -
Frontiers in Pharmacology 2023Hepatocellular carcinoma (HCC) is responsible for approximately 90% of liver malignancies and is the third most common cause of cancer-related mortality worldwide....
Hepatocellular carcinoma (HCC) is responsible for approximately 90% of liver malignancies and is the third most common cause of cancer-related mortality worldwide. However, the role of anoikis, a programmed cell death mechanism crucial for maintaining tissue equilibrium, is not yet fully understood in the context of HCC. Our study aimed to investigate the expression of 10 anoikis-related genes (ARGs) in HCC, including BIRC5, SFN, UBE2C, SPP1, E2F1, etc., and their significance in the disease. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we discovered that these ARGs are involved in important processes such as tissue homeostasis, ion transport, cell cycle regulation, and viral infection pathways. Furthermore, we found a significant correlation between the prognostic value of five ARGs and immune cell infiltrates. Analysis of clinical datasets revealed a strong association between BIRC5 expression and HCC pathological progression, including pathological stage, T stage, overall survival (OS), and race. By constructing a competing endogenous RNA (ceRNA) network and using molecular docking, we identified ten bioactive compounds from traditional Chinese medicine (TCM) that could potentially modulate BIRC5. Subsequent experiments confirmed the influence of platycodin D, one of the identified compounds, on key elements within the ceRNA network. In conclusion, our study presents a novel framework for an anoikis-centered prognostic model and an immune-involved ceRNA network in HCC, revealing potential regulatory targets. These insights contribute to our understanding of HCC pathology and may lead to improved therapeutic interventions.
PubMed: 38283837
DOI: 10.3389/fphar.2023.1325992 -
Scientific Reports Jan 2024Sepsis is a common acute and severe medical condition with a high mortality rate. Anoikis, an emerging form of cell death, plays a significant role in various diseases....
Sepsis is a common acute and severe medical condition with a high mortality rate. Anoikis, an emerging form of cell death, plays a significant role in various diseases. However, the role of anoikis in sepsis remains poorly understood. Based on the datasets from Gene Expression Omnibus and anoikis-related genes from GeneCards, the differentially expressed anoikis-related genes (DEARGs) were identified. Based on hub genes of DEARGs, a novel prognostic risk model was constructed, and the pattern of immune infiltration was investigated by CIBERSORT algorithm. And small molecule compounds targeting anoikis in sepsis were analyzed using Autodock. Of 23 DEARGs, CXCL8, CFLAR, FASLG and TP53 were significantly associated with the prognosis of sepsis (P < 0.05). Based on the prognostic risk model constructed with these four genes, high-risk population of septic patients had significant lower survival probability than low-risk population (HR = 3.30, P < 0.001). And the level of CFLAR was significantly correlated with the number of neutrophils in septic patients (r = 0.54, P < 0.001). Moreover, tozasertib had low binding energy with CXCL8, CFLAR, FASLG and TP53, and would be a potential compound for sepsis. Conclusively, our results identified a new prognostic model and potential therapeutic molecular for sepsis, providing new insights on mechanism and treatment of sepsis.
Topics: Humans; Anoikis; Prognosis; Sepsis; Algorithms; Cell Death
PubMed: 38281996
DOI: 10.1038/s41598-024-52742-9 -
Major Stressful Life Events and the Risk of Pancreatic, Head and Neck Cancers: A Case-Control Study.Cancers Jan 2024Major stressful life events have been shown to be associated with an increased risk of lung cancer, breast cancer and the development of various chronic illnesses. The...
BACKGROUND
Major stressful life events have been shown to be associated with an increased risk of lung cancer, breast cancer and the development of various chronic illnesses. The stress response generated by our body results in a variety of physiological and metabolic changes which can affect the immune system and have been shown to be associated with tumor progression. In this study, we aim to determine if major stressful life events are associated with the incidence of head and neck or pancreatic cancer (HNPC).
METHODS
This is a matched case-control study. Cases (CAs) were HNPC patients diagnosed within the previous 12 months. Controls (COs) were patients without a prior history of malignancy. Basic demographic data information on major stressful life events was collected using the modified Holmes-Rahe stress scale. A total sample of 280 was needed (79 cases, 201 controls) to achieve at least 80% power to detect odds ratios (ORs) of 2.00 or higher at the 5% level of significance.
RESULTS
From 1 January 2018 to 31 August 2021, 280 patients were enrolled (CA = 79, CO = 201) in this study. In a multivariable logistic regression analysis after controlling for potential confounding variables (including sex, age, race, education, marital status, smoking history), there was no difference between the lifetime prevalence of major stressful event in cases and controls. However, patients with HNPC were significantly more likely to report a major stressful life event within the preceding 5 years when compared to COs ( = 0.01, OR = 2.32, 95% CI, 1.18-4.54).
CONCLUSIONS
Patients with head, neck and pancreatic cancers are significantly associated with having a major stressful life event within 5 years of their diagnosis. This study highlights the potential need to recognize stressful life events as risk factors for developing malignancies.
PubMed: 38275892
DOI: 10.3390/cancers16020451 -
World Journal of Oncology Feb 2024Ovarian cancer is an extremely deadly gynecological malignancy, with a 5-year survival rate below 30%. Among the different histological subtypes, serous ovarian cancer...
BACKGROUND
Ovarian cancer is an extremely deadly gynecological malignancy, with a 5-year survival rate below 30%. Among the different histological subtypes, serous ovarian cancer (SOC) is the most common. Anoikis significantly contributes to the progression of ovarian cancer. Therefore, identifying an anoikis-related signature that can serve as potential prognostic predictors for SOC is of great significance.
METHODS
We intersected 308 anoikis-related genes (ARGs) and identified those significantly associated with SOC prognosis using univariate Cox regression. A LASSO Cox regression model was constructed and evaluated using Kaplan-Meier and receiver operating characteristic (ROC) analyses in TCGA (The Cancer Genome Atlas) and GSE26193 cohorts. We conducted quantitative real-time polymerase chain reaction (qPCR) to assess mRNA levels and applied bioinformatics to investigate the correlation between risk groups and gene expression, mutations, pathways, tumor immune microenvironment (TIME), and drug sensitivity in SOC.
RESULTS
Among 308 ARGs, 28 were significantly associated with SOC prognosis. A 13-gene prognostic model was established through LASSO Cox regression in TCGA cohort. High-risk group had poorer prognosis than low-risk group (median overall survival (mOS): 34.2 vs. 57.1 months, hazard ratio (HR): 2.590, 95% confidence interval (CI): 0.159 - 6.00, P < 0.001). The area under the curve (AUC) values of 0.63, 0.65, and 0.74 reflected the predictive performance for 3-, 5-, and 8-year overall survival (OS) in GSE26193 validation cohort. Functional enrichment, pathway analysis, and TIME analysis identified distinct characteristics between risk groups. Drug sensitivity analysis revealed potential drug advantages for each group. Furthermore, qPCR validation once again confirmed the effectiveness of the risk model in SOC patients.
CONCLUSIONS
We developed and validated a robust ARG model, which could be used to predict OS in SOC patients. By systematically analyzing the correlation between the risk score of the ARGs signature model and various patterns, including the TIME and drug sensitivity, our findings suggest that this prognostic model contributes to the advancement of personalized and precise therapeutic strategies. Nevertheless, further validation studies and investigations into the underlying mechanisms are warranted.
PubMed: 38274727
DOI: 10.14740/wjon1714 -
JCI Insight Mar 2024High-grade serous carcinoma (HGSC) is the most lethal gynecological malignancy in the United States. Late diagnosis and the emergence of chemoresistance have prompted...
High-grade serous carcinoma (HGSC) is the most lethal gynecological malignancy in the United States. Late diagnosis and the emergence of chemoresistance have prompted studies into how the tumor microenvironment, and more recently tumor innervation, may be leveraged for HGSC prevention and interception. In addition to stess-induced sources, concentrations of the sympathetic neurotransmitter norepinephrine (NE) in the ovary increase during ovulation and after menopause. Importantly, NE exacerbates advanced HGSC progression. However, little is known about the role of NE in early disease pathogenesis. Here, we investigated the role of NE in instigating anchorage independence and micrometastasis of preneoplastic lesions from the fallopian tube epithelium (FTE) to the ovary, an essential step in HGSC onset. We found that in the presence of NE, FTE cell lines were able to survive in ultra-low-attachment (ULA) culture in a β-adrenergic receptor-dependent (β-AR-dependent) manner. Importantly, spheroid formation and cell viability conferred by treatment with physiological sources of NE were abrogated using the β-AR blocker propranolol. We have also identified that NE-mediated anoikis resistance may be attributable to downregulation of colony-stimulating factor 2. These findings provide mechanistic insight and identify targets that may be regulated by ovary-derived NE in early HGSC.
Topics: Female; Humans; Ovarian Neoplasms; Cystadenocarcinoma, Serous; Fallopian Tubes; Anoikis; Norepinephrine; Tumor Microenvironment
PubMed: 38271085
DOI: 10.1172/jci.insight.170961