Construction of a novel cancer-associated fibroblast-related signature to predict clinical outcome and immune response in cervical cancer.

This study developed a prognostic signature for cervical cancer using transcriptome profiling and clinical data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and TISCH database, focusing on cancer-associated fibroblasts (CAFs). Through LASSO Cox regression and integrated bioinformatics analyses, we identified 144 differentially expressed genes (DEGs) related to CAFs, from which an 11-gene CAF-related signature (CAFRSig) was constructed. The CAFRSig effectively stratified patients into high- and low-risk categories, demonstrating significant prognostic capability in predicting overall survival. Gene ontology (GO) and gene set variation analysis (GSVA) linked the DEGs to crucial pathways in tumor malignancy, immune response, and fatty acid metabolism. The immune landscape analysis, utilizing the TIMER platform and CIBERSORT algorithm, revealed a positive correlation between immune cell effector functions and CAFRSig scores, highlighting the model's potential to identify patients likely to respond to immune checkpoint blockade (ICB) therapies. Furthermore, neuropilin 1 (NRP1), a key gene in the CAFRSig, was upregulated in cervical cancer tissues and associated with disease progression and differentiation. The downregulation of NRP1 curbed cell proliferation and influenced the epithelial-mesenchymal transition (EMT), implicating the PI3K/AKT pathway and modulating PD-L1 expression. This comprehensive analysis establishes a robust prognostic signature based on CAF-related genes, offering valuable insights for optimizing therapeutic strategies in cervical cancer management.

STUB1 is acetylated by KAT5 and alleviates myocardial ischemia-reperfusion injury through LATS2-YAP-ß-catenin axis.

Myocardial ischemia-reperfusion injury (MIRI) is involved in the pathogenesis of multiple cardiovascular diseases. This study elucidated the biological function of lysine acetyltransferase 5 (KAT5) in cardiomyocyte pyroptosis during MIRI. Oxygen-glucose deprivation/reoxygenation and left anterior descending coronary artery ligation were used to establish MIRI models. Here we show, KAT5 and STIP1 homology and U-box-containing protein 1 (STUB1) were downregulated, while large tumor suppressor kinase 2 (LATS2) was upregulated in MIRI models. KAT5/STUB1 overexpression or LATS2 silencing repressed cardiomyocyte pyroptosis. Mechanistically, KAT5 promoted STUB1 transcription via acetylation modulation, and subsequently caused ubiquitination and degradation of LATS2, which activated YAP/ß-catenin pathway. Notably, the inhibitory effect of STUB1 overexpression on cardiomyocyte pyroptosis was abolished by LATS2 overexpression or KAT5 depletion. Our findings suggest that KAT5 overexpression inhibits NLRP3-mediated cardiomyocyte pyroptosis to relieve MIRI through modulation of STUB1/LATS2/YAP/ß-catenin axis, providing a potential therapeutic target for MIRI.

PANoptosis-related long non-coding RNA signature to predict the prognosis and immune landscapes of pancreatic adenocarcinoma.

Background: Cancer growth is significantly influenced by processes such as pyroptosis, apoptosis, and necroptosis that underlie PANoptosis, a proinflammatory programmed cell death. Several studies have examined the long non-coding RNAs (lncRNAs) associated with pancreatic adenocarcinoma (PAAD). However, the predictive value of lncRNAs related to PANoptosis for PAAD has not been established. Methods: The Clinical Genome Atlas database was used to obtain the transcriptome 、clinical data and the corresponding mutation data of the patients with PAAD in this study. The least absolute shrinkage and selection operator regression analysis was employed to obtain prognosis-related lncRNAs for constructing a risk signature. According to the median risk score of the signature, patients with PAAD were grouped into low- and high-risk groups to further compare the survival prognosis of different risk groups. Time-dependent receiver operating characteristic curves, c-index analysis, nomograms, principal component analysis and univariate Cox and multivariate Cox regression were performed for the internal validation of the signature. In addition, enrichment analysis of different genes was performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Lastly, differences in tumor mutation burden (TMB), immune function, tumor immune dysfunction and rejection (TIDE), and drug response were determined for the two risk groups. Results: The signature was constructed with six PANoptosis-related lncRNAs (AC067817.2、LINC02004、AC243829.1、AC092171.5、AP005233.2、AC004687.1) that predicted the prognosis of the patients with PAAD. Survival curves showed that patients in the two risk groups had statistically significant differences in prognosis (P < 0.05), and multi-cox regression analysis identified risk score as an independent risk factor for PAAD prognosis, and internal validation of nomograms showed high confidence in the signature. GO and KEGG enrichment analysis showed functional and pathway differences between the high- and low-risk groups. TMB evaluation demonstrated that patients in the high-risk group had a higher frequency of mutations. The TIDE score indicated that the high-risk group had a lower risk of immunotherapy escape and better immunotherapy outcomes. Additionally, the two risk groups revealed significantly different responses to 11 anticancer drugs. Conclusion: We identified a novel risk signature for PANoptosis-related lncRNAs, which is a standalone prognostic indicator for PAAD. The PANoptosis-related lncRNA risk signature may be relevant for immunotherapy and a therapeutic target for PAAD.

Identification of a cancer associated fibroblasts-related index to predict prognosis and immune landscape in ovarian cancer.

Cancer-associated fibroblasts (CAFs) play a role in ovarian cancer (OV) evolution, immunosuppression and promotion of drug resistance. Exploring the value of CAFs-related biomarker in OV is of great importance. In the present work, we developed a CAFs-related index (CAFRI) based on an integrated analysis of single-cell and bulk RNA-sequencing and highlighted the value of CAFRI in predicting clinical outcomes in individuals with OV, tumour immune microenvironment (TIME) and response to immune checkpoint inhibitors (ICIs). The GSE151214 cohort was used for cell subpopulation localization and analysis, the TCGA-OV patients as a training set. Moreover, the ICGC-OV, GSE26193, GSE26712 and GSE19829 cohorts were used for the validation of CAFRI. The TIMER 2.0, CIBERSORT and ssGSEA algorithms were used for analysis of TIME characteristics based on the CAFRI. The GSVA, GSEA, GO, KEGG and tumour mutation burden (TMB) analyses were used for mechanistic exploration. Additionally, the IMvigor210 cohort was conducted to validate the predictive value of CAFRI on the efficacy of ICIs. Finally, CAFRI-based antitumour drug sensitivity was analysed. The findings demonstrate that the CAFRI can served as an excellent predictor of prognosis for individuals with OV, as well as identifying patients with different TIME characteristics, differentiating between immune 'hot' and 'cold' tumour populations, and providing new insights into the selection of ICIs and personalised treatment regimens. CAFRI provides new perspectives for the development of novel prognostic and immunotherapy efficacy predictive biomarkers for OV.

Construction of a novel cancer-associated fibroblast-related signature to predict clinical outcome and immune response in colon adenocarcinoma.

The interaction between the tumour and the surrounding microenvironment determines the malignant biological behaviour of the tumour. Cancer-associated fibroblasts (CAFs) coordinate crosstalk between cancer cells in the tumour immune microenvironment (TIME) and are extensively involved in tumour malignant behaviours, such as immune evasion, invasion and drug resistance. Here, we performed differential and prognostic analyses of genes associated with CAFs and constructed CAF-related signatures (CAFRs) to predict clinical outcomes in individuals with colon adenocarcinoma (COAD) based on machine learning algorithms. The CAFRs were further validated in an external independent cohort, GSE17538. Additionally, Cox regression, receiver operating characteristic (ROC) and clinical correlation analysis were utilised to systematically assess the CAFRs. Moreover, CIBERSORT, single sample Gene Set Enrichment Analysis (ssGSEA) and Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) analysis were utilised to characterise the TIME in patients with COAD. Microsatellite instability (MSI) and tumour mutation burden were also analysed. Furthermore, Gene Set Variation Analysis (GSVA), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) elucidated the biological functions and signalling pathways involved in the CAFRs. Consensus clustering analysis was used for the immunological analysis of patients with COAD. Finally, the pRRophic algorithm was used for sensitivity analysis of common drugs. The CAFRs constructed herein can better predict the prognosis in COAD. The cluster analysis based on the CAFRs can effectively differentiate between immune 'hot' and 'cold' tumours, determine the beneficiaries of immune checkpoint inhibitors (ICIs) and provide insight into individualised treatment for COAD.

Knowledge mapping of early-onset colorectal cancer from 2000 to 2022: A bibliometric analysis.

The incidence of early-onset colorectal cancer (EO-CRC), diagnosed in patients younger than 50 years, has increased in incidence alarmingly over the past few decades, while overall incidence and mortality of colorectal cancer are stabilizing or declining in many high-income countries. These unfavorable changes have raised significant concerns and led to extensive research, resulting in a surge in studies on EO-CRC. Our aim was to obtain a more comprehensive understanding of the current state of this field and to identify prospective research directions by performing a bibliometric analysis of EO-CRC. A total of 1952 papers on EO-CRC published from 2000 to 2022 were identified after a thorough search of the Web of Science Core Collection. The United States dominated this field, with Harvard University contributing the greatest number of papers, while the journal Familial Cancer (n = 52) published the most articles. Cooperation network analysis revealed close internal cooperation among countries, institutions and authors. Based on reference and keyword analysis, high-frequency keywords showed several popular research directions, including epidemiology (incidence, young patients, age of onset, etc.), risk factors (obesity, family history, lynch syndrome, etc.) and molecular characterization (germline mutation, genome wide association, MLH1, etc.). Overall, our research provides an overview of the current status in this field, which we hope will give researchers a comprehensive perspective on the present trends within this domain.

Identification and validation of a novel anoikis-related long non-coding RNA signature for pancreatic adenocarcinoma to predict the prognosis and immune response.

OBJECTIVE: To provide more precise treatment options for pancreatic adenocarcinoma (PAAD) patients and improve their prognosis,we established a novel anoikis-related long non-coding RNA signature (ARLSig) to predict the prognosis and immune response for PAAD patients. METHODS: We downloaded information on PAAD from The Cancer Genome Atlas (TCGA) database, and screened long non-coding RNA (lncRNA) linked with anoikis, and prognostic signatures with these lncRNAs. After that, ARLSig was verified using receiver operating characteristic (ROC) and C-index curves. To further investigate the role of ARLSig, we also performed enrichment analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). Additionally, using immunological correlation analysis and single-sample genetic enrichment analysis, we investigated the effectiveness of PAAD immunotherapy. RESULTS: We screened 7 lncRNAs to construct a novel ARLSig and utilized it to predict the efficacy of immunotherapy and the prognosis of PAAD patients. CONCLUSION: ARLSig can identify patients who will benefit from immunotherapy and improve the prediction of PAAD patient prognosis.

Esophageal stenosis as an independent factor of poor prognosis in patients with ESCC treated with definitive chemoradiotherapy.

Aim: To evaluate the clinical outcome and elucidate the prognostic factors in patients with esophageal squamous cell carcinoma (ESCC) treated with definitive chemoradiotherapy (CRT). Patients: Data for patients newly diagnosed with ESCC receiving definitive CRT at our institution between 2012 and 2018 were retrospectively reviewed. Results: A total of 201 patients were included. Severe stenosis after radiotherapy was an independent factor relevant to prognosis. Maximal esophageal wall thickness, short-term responses, severe stenosis at diagnosis and a high neutrophil-to-lymphocyte ratio were independent risk factors for the occurrence of severe stenosis after radiotherapy. Conclusion: Severe stenosis after radiotherapy is a useful predictive indicator in patients with ESCC receiving definitive CRT. Further studies are needed to verify these findings.

This study aimed to identify valuable factors as predictive diagnostic markers for patients diagnosed with esophageal squamous cell carcinoma receiving chemoradiotherapy. In this retrospective study with patients, we have found that severe stenosis after radiotherapy has an independent predictive value for survival. Survival was also associated with maximal esophageal wall thickness, short-term responses, severe stenosis at diagnosis and a high neutrophil-to-lymphocyte ratio. Stenosis could be used as a parameter to predict survival in esophageal squamous cell carcinoma patients after chemoradiotherapy.

A Nomogram for Predicting the Risk of Radiotherapy-Related Esophageal Fistula in Esophageal Cancer Patients.

BACKGROUND: To construct and validate a nomogram for predicting the risk of esophageal fistula in esophageal cancer patients receiving radiotherapy. METHODS: A retrospective nested case-control study was performed, in which a total of 81 esophageal fistula patients and 243 controls from 2014 to 2020 in the First Affiliated Hospital of Anhui Medical University were enrolled. Factors included in the nomogram were determined by univariate and multiple logistic regression analysis. The following methods including ROC curve, C-index, calibration curves, Brier score, and decision curve analysis (DCA) were adopted to evaluate this nomogram. RESULTS: Multivariate logistic regression analysis showed that T4 stage, level 4 stenosis, ulcerative esophageal cancer, prealbumin, and maximum diameters of GTV and NLR were the independent risk factors of esophageal fistula. Accordingly, a nomogram incorporating the aforementioned six parameters was constructed. The AUC was 0.848 (95% CI 0.901-0.895), indicating a high prediction accuracy of this nomogram. Further evaluation of this model showed that the C-index was 0.847, while the bias-corrected C-index after internal validation was 0.833. The Brier score was 0.127. The calibration curves presented good concordance, and the DCA revealed promising clinical application. CONCLUSIONS: The nomogram presents accurate and applicable prediction for the esophageal fistula risk in esophageal cancer patients receiving radiotherapy.

Preventable lifestyle and eating habits associated with gastric adenocarcinoma: A case-control study.

Background: Besides the well-established risk factors for gastric adenocarcinoma (GaC), many other etiological factors remain largely unexplored. This large comprehensive case-control study aimed to investigate the preventable lifestyle and eating habits associated with GaC. Methods: Consecutive patients with primary microscopically-confirmed GaC diagnosed in 2016-2018 were matched by sex, age, height, and socioeconomic status at a 1:1 ratio with healthy controls. Association of GaC versus control with investigated factors was assessed using the multivariable-adjusted conditional logistic regression for paired samples. Results: Together 302 GaC patients and 302 healthy controls were investigated. Participants receiving higher education and those eating majorly vegetables had less frequently GaC. The majorly frying cooking habit was associated with a higher incidence of GaC. People complaining about poor sleep quality had more often GaC. The more often one smoked, the more often he/she had GaC. A higher frequency for having pickled food was associated with more frequent GaC, while having more frequently vegetables/fruit, beans, or kelps was associated with less often GaC. A greater preference for sour or bitter taste was associated with less frequent GaC. The frequencies of thin liquid intake after meal, swallowing hot food without adequate cooling, doing other things while eating, eating overnight food, and eating midnight snack were all positively associated with GaC, while going to bed regularly was associated with less often GaC. Conclusions: Education level, sleep quality, smoking, the frequencies of use of several foods and seasonings, the preference for specific tastes, and various eating and living habits were associated with GaC. The findings offer important hints for further prospective investigations and for easy effective GaC-preventative strategy-making.