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BackgroundCervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most prevalent gynecologic malignancies globally. The prognosis is abysmal once cervical cancer progresses to lymphatic metastasis. Anoikis, a specialized form of apoptosis induced by loss of cell adhesion to the extracellular matrix, plays a critical role. The prediction model based on anoikis-related genes (ARGs) expression and clinical data could greatly aid clinical decision-making. However, the relationship between ARGs and CESC remains unclear.MethodsARGs curated from the GeneCards and Harmonizome portals were instrumental in delineating CESC subtypes and in developing a prognostic framework for patients afflicted with this condition. We further delved into the intricacies of the immune microenvironment and pathway enrichment across the identified subtypes. Finally, our efforts culminated in the creation of an innovative nomogram that integrates ARGs. The utility of this prognostic tool was underscored by Decision Curve Analysis (DCA), which illuminate its prospective benefits in guiding clinical interventions.ResultsIn our study, We discerned a set of 17 survival-pertinent, anoikis-related differentially expressed genes (DEGs) in CESC, from which nine were meticulously selected for the construction of prognostic models. The derived prognostic risk score was subsequently validated as an autonomous prognostic determinant. Through comprehensive functional analyses, we observed distinct immune profiles and drug response patterns among divergent prognostic stratifications. Further, we integrated the risk scores with the clinicopathological characteristics of CESC to develop a robust nomogram. DCA corroborated the utility of our model, demonstrating its potential to enhance patient outcomes through tailored clinical treatment strategies.ConclusionThe predictive signature, encompassing nine pivotal genes, alongside the meticulously constructed nomogram developed in this research, furnishes clinicians with a sophisticated tool for tailoring treatment strategies to individual patients diagnosed with CESC.

BackgroundDepression increases the risk of breast cancer recurrence and metastasis. However, there lacks potential biomarkers for predicting prognosis in breast cancer. 5-hydroxytryptamine (5-HT) plays a key role in the pathogenesis and treatment of depression. In this study, we developed a prognostic signature based on 5-HT receptors (5-HTRs) and elucidated its potential immune regulatory mechanisms for breast cancer prognosis.MethodsOncomine, GEPIA, UALCAN, cBioPortal, Kaplan-Meier plotter, and TIMER were used to analyze differential expression, prognostic value, genetic alteration, and immune cell infiltration of HTRs in breast cancer patients. The model training and validation assays were based on the analyses of GSE1456 and GSE86166. A risk signature was established by univariate and multivariate Cox regression analyses. The transwell assay was utilized to verify the effect of the 5-HTRs expression on breast cancer invasion. Effects of HTR2A/2B inhibitor on CD8+ T cell proliferation and infiltration as well as apoptosis of 4T1 cells in the tumor microenvironment were detected by flow cytometry and TUNEL assay. Zebrafish and mouse breast cancer xenografts were used to determine the effect of HTR2A/2B inhibitor on breast cancer metastasis.ResultsThe expression levels of HTR1A, HTR1B, HTR2A, HTR2B, HTR2C, HTR4, and HTR7 were significantly downregulated in highly malignant breast cancer types. 5-HTRs were significantly associated with recurrence-free survival (RFS) in breast cancer patients. The genetic alteration of HTR1D, HTR3A, HTR3B, and HTR6 in breast cancer patients was significantly associated with shorter overall survival (OS). Finally, HTR2A and HTR2B were determined to construct the risk signature. The expression of HTR2A/2B was positively correlated with the infiltration of immune cells such as CD8+ T cells and macrophages. Furthermore, inhibition of HTR2A expression could suppress CD8+ T cell proliferation and enhance invasion and metastasis of breast cancer cells in both zebrafish and mice model.ConclusionsThe HTR2A/2B risk signature not only highlights the significance of HTRs in breast cancer prognosis by modulating cancer immune microenvironment, but also provides a novel gene-testing tool for early prevention of depression in breast cancer patients and lead to an improved prognosis and quality of life.

BackgroundCyclin-dependent kinase 4/6 inhibitor (CDK4/6i) has become the commonest first-line treatment of hormonal receptor positive and human epidermal growth factor receptor 2 negative (HR+/HER2-) metastatic breast cancer (MBC). However, therapy is quite individualized after progression of disease (PD) when CDK4/6i fails. Estrogen receptor (ER) status of metastatic lesions of bone, lung or liver might be different from the primary tumor and biopsy of metastatic lesions was invasive and not always available. Prediction of treatment response after PD of CDK4/6i remains unsolved. 18F-fluoroestradiol (FES) PET/CT could non-invasively reveal ER expression both in primary and metastatic breast cancer and recognize heterogeneity of ER status.Case presentationA 70-year-old woman with Parkinson’s disease, osteoporosis and cardiovascular co-morbidity was diagnosed with HR+/HER2- breast cancer (pT2N2M0, stage IIIa). Three years later, she developed metastases in right lung and pleura with pleural effusion and received palbociclib + letrozole. After 8 months the disease progressed, and 18F-FES PET/CT revealed multiple ER-positive pleural lesions and ER-negative pulmonary nodules after PD and the progression-free survival (PFS) of first-line CDK4/6i was 8 months. Since most of the metastatic lesions were ER-positive, abemaciclib + fulvestrant were chosen as the second-line CDK4/6i treatment and the PFS was 15 months. Another 18F-FES PET/CT showed a new ER-positive pleural mass with multiple ER-negative pulmonary nodules. Since 18F-FES PET/CT revealed that the dominant lesions were still ER-positive, dalpiciclib + exemestane + fulvestrant were prescribed as the third-line CDK4/6i treatment. Currently the patient’s disease had been stable for 2 months.ConclusionThis case demonstrated that 18F-FES PET/CT could show ER heterogeneity non-invasively and reveal the treatment responses a predictive imaging tool of serial second- and third-line of CDK4/6i treatments when first-line CDK4/6i failed in HR+/HER2- MBC. So long as the dominant or newly-developed metastatic lesion was ER-positive on 18F-FES PET after first-line CDK4/6i, the patient might show certain therapeutic response towards endocrine-based treatment including second- and third-line of CDK4/6i, and thus increased the time to chemotherapy (TTC).

BackgroundDepression plays a significant role in mediating breast cancer recurrence and metastasis. However, a precise risk model is lacking to evaluate the potential impact of depression on breast cancer prognosis. In this study, we established a depression-related gene (DRG) signature that can predict overall survival (OS) and elucidate its correlation with pathological parameters and sensitivity to therapy in breast cancer.MethodsThe model training and validation assays were based on the analyses of 1,096 patients from The Cancer Genome Atlas (TCGA) database and 2,969 patients from GSE96058. A risk signature was established through univariate and multivariate Cox regression analyses.ResultsTen DRGs were determined to construct the risk signature. Multivariate analysis revealed that the signature was an independent prognostic factor for OS. Receiver operating characteristic (ROC) curves indicated good performance of the model in predicting 1-, 3-, and 5-year OS, particularly for patients with triple-negative breast cancer (TNBC). In the high-risk group, the proportion of immunosuppressive cells, including M0 macrophages, M2 macrophages, and neutrophils, was higher than that in the low-risk group. Furthermore, low-risk patients responded better to chemotherapy and endocrine therapy. Finally, a nomogram integrating risk score, age, tumor-node-metastasis (TNM) stage, and molecular subtypes were established, and it showed good agreement between the predicted and observed OS.ConclusionThe 10-gene risk model not only highlights the significance of depression in breast cancer prognosis but also provides a novel gene-testing tool to better prevent the potential adverse impact of depression on breast cancer prognosis.

Keratin 8 (KRT8) is the major component of the intermediate filament cytoskeleton and aberrant expression in multiple tumors. However, the role of KRT8 in lung adenocarcinoma (LUAD) remains unclear. In the present study, KRT8 expression was found to be upregulated along with prognosis and metastasis in LUAD. Kaplan–Meier analysis presented that the 5-year OS and DSS rates were significantly better among patients with low KRT8 expression compared to those with high expression. Correlation analysis showed that KRT8 expression was significantly associated with gender (P = 0.027), advanced T stage (P = 0.001), advanced N stage (P = 0.048), and advanced pathologic stage (P = 0.025). Univariate Cox analysis demonstrated that KRT8 was a predictor of OS [hazard ratio (HR) = 1.526; 95% confidence interval (CI) 1.141–2.040; P = 0.004] and DSS (HR = 1.625; 95% CI 1.123–2.353; P = 0.010) in the TCGA database. Importantly, downregulation of KRT8 obviously suppressed cell proliferation, cell migration, invasion, and EMT as well as induced cell apoptosis. KRT8 knockdown significantly inhibited NF-κB signaling, suggesting a potential mechanism. Overall, our results indicated that KRT8 could regulate lung carcinogenesis and may serve as a potential target for antineoplastic therapies.

Breast cancer remains the most common malignancy and the leading causality of cancer-associated mortality among women worldwide. With proven efficacy, Oldenlandia diffusa has been extensively applied in breast cancer treatment in Traditional Chinese Medicine (TCM) for thousands of years. However, the bioactive compounds of Oldenlandia diffusa accounting for its anti-breast cancer activity and the underlying biological mechanisms remain to be uncovered. Herein, bioactivity-guided fractionation suggested ursolic acid as the strongest anti-breast cancer compound in Oldenlandia diffusa. Ursolic acid treatment dramatically suppressed the proliferation and promoted mitochondrial-mediated apoptosis in breast cancer cells while brought little cytotoxicities in nonmalignant mammary epithelial cells in vitro. Meanwhile, ursolic acid dramatically impaired both the glycolytic metabolism and mitochondrial respiration function of breast cancer cells. Further investigations demonstrated that ursolic acid may impair the glycolytic metabolism of breast cancer cells by activating Caveolin-1 (Cav-1) signaling, as Cav-1 knockdown could partially abrogate the suppressive effect of ursolic acid on that. Mechanistically, ursolic acid could activate SP1-mediated CAV1 transcription by promoting SP1 expression as well as its binding with CAV1 promoter region. More meaningfully, ursolic acid administration could dramatically suppress the growth and metastasis of breast cancer in both the zebrafish and mouse xenotransplantation models of breast cancer in vivo without any detectable hepatotoxicity, nephrotoxicity or hematotoxicity. This study not only provides preclinical evidence supporting the application of ursolic acid as a promising candidate drug for breast cancer treatment but also sheds novel light on Cav-1 as a druggable target for glycolytic modulation of breast cancer.

Background: Cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) has become the commonest first-line treatment of hormonal receptor positive and human epidermal growth factor receptor 2 negative (HR+/HER2-) metastatic breast cancer (MBC). However, therapy is quite individualized after progression of disease (PD) when CDK4/6i fails. Estrogen receptor (ER) status of metastatic lesions of bone, lung or liver might be different from the primary tumor and biopsy of metastatic lesions was invasive and not always available. Prediction of treatment response after PD of CDK4/6i remains unsolved. 18F-fluoroestradiol (FES) PET/CT could non-invasively reveal ER expression both in primary and metastatic breast cancer and recognize heterogeneity of ER status. Case presentation: A 70-year-old woman with Parkinson's disease, osteoporosis and cardiovascular co-morbidity was diagnosed with HR+/HER2- breast cancer (pT2N2M0, stage IIIa). Three years later, she developed metastases in right lung and pleura with pleural effusion and received palbociclib + letrozole. After 8 months the disease progressed, and 18F-FES PET/CT revealed multiple ER-positive pleural lesions and ER-negative pulmonary nodules after PD and the progression-free survival (PFS) of first-line CDK4/6i was 8months. Sincemost of the metastatic lesions were ER-positive, abemaciclib + fulvestrant were chosen as the second-line CDK4/6i treatment and the PFS was 15 months. Another 18FFES PET/CT showed a new ER-positive pleural mass with multiple ER-negative pulmonary nodules. Since 18F-FES PET/CT revealed that the dominant lesions were still ER-positive, dalpiciclib + exemestane + fulvestrant were prescribed as the third-line CDK4/6i treatment. Currently the patient's disease had been stable for 2 months. Conclusion: This case demonstrated that 18F-FES PET/CT could show ER heterogeneity non-invasively and reveal the treatment responses a predictive imaging tool of serial second- and third-line of CDK4/6i treatments when first-line CDK4/6i failed in HR+/HER2- MBC. So long as the dominant or newly-developed metastatic lesion was ER-positive on 18F-FES PET after first-line CDK4/6i, the patient might show certain therapeutic response towards endocrine-based treatment including second- and third-line of CDK4/6i, and thus increased the time to chemotherapy (TTC). [ABSTRACT FROM AUTHOR]

BackgroundAs a malignant digestive system tumor, pancreatic cancer has unique metabolic characteristics. In recent years, the study of pancreatic cancer metabolism is in full swing, which provides a new direction for the treatment of pancreatic cancer patients. However, there is no systematic report of pancreatic cancer metabolism. In this paper, bibliometrics and visualization methods were used to analyze the number of publications, countries/regions, authors, institutions, journals, co-cited references, and keywords of pancreatic cancer metabolism articles, to summarize the research trends and predict research hotspots.MethodsWe searched, screened and downloaded articles on pancreatic cancer metabolism through the Web of Science Core Collection (WoSCC). Using CiteSpace, VOSviewer and Bibliometrix Package to analyze publications, countries/regions, authors, institutions, journals, co-cited references, and keywords of pancreatic cancer metabolism to identify research trends and predict research hotspots.ResultsAccording to the inclusion and exclusion criteria, a total of 5,255 articles were retrieved during the period 1943-2022. The number of publications on pancreatic cancer metabolism is increasing year by year. The United States (n=1602, 30.49%), China (n=1074, 20.44%), and Italy (n=313, 5.96%) are the three countries with the largest number of publications and citations, and there is close cooperation between countries. LI J (n=55) is the most prolific author. FUDAN UNIV (n=348) is the most published institution. CANCERS (n=118), PLOS ONE (n=93), and CANCER RESEARCH (n=80) are the most popular journals in this field. “Nutriment-deficient environment”, “cancer chemoprevention” and “targeting cancer stem cell” are the main areas of focus. “immunotherapy”, “ferroptosis” and “targeted therapy” are hot keywords in recent years. Taking pancreatic cancer metabolism as an entry point to study the role of traditional Chinese medicine (TCM) mainly focuses on curcumin and resveratrol, lack of broader and deeper research on TCM.ConclusionsThe number of publications on pancreatic cancer metabolism has generally increased, and scholars have generally paid more attention to this field. “immunotherapy”, “ferroptosis” and “targeted therapy” are the current research hotspots. The in-depth study of pancreatic cancer metabolism will provide new ideas for the treatment of pancreatic cancer.

ObjectiveUnderstanding the characteristics of tumor suppressor genes (TSGs) is of great significance for the development of new targeted treatment strategies for non-small cell lung cancer (NSCLC). Therefore, this present article is to explore the underlying molecular mechanism of ZFN24 inhibiting the development of NSCLC.MethodsWe performed RT-PCR and Western blotting for evaluating associated RNA and protein expression. CCK8, colony forming and sphere-forming assays were used to evaluate the proliferation and stemness of NSCLC cells. NSCLC cell senescence was examined by β-galactosidase staining assay. Luciferase assay was performed to evaluate β-catenin transcriptional activity. The effect of ZNF24 on NSCLC cells in vivo was evaluated by the xenograft tumor experiment.ResultsEctopic expression of ZNF24 significantly inhibited cell viability, colony forming ability, and stemness of NSCLC cells. WNT signaling pathway was inhibited by ZNF24 resulting in NSCLC cell senescence. β-catenin transcriptional activity was significantly inhibited by ZNF24 (P < 0.05). Ectopic expression of ZNF24 significantly inhibited xenotransplant tumors growth in vivo (P < 0.05).ConclusionZNF24 could notably inhibit the development of NSCLC by inhibiting the WNT signaling pathway.

The current histologically based grading system for glioma does not accurately predict which patients will have better outcomes or benefit from adjuvant chemotherapy. We proposed that combining the expression profiles of multiple long non-coding RNAs (lncRNAs) into a single model could improve prediction accuracy. We included 1,094 glioma patients from three different datasets. Using the least absolute shrinkage and selection operator (LASSO) Cox regression model, we built a multiple-lncRNA-based classifier on the basis of a training set. The predictive and prognostic accuracy of the classifier was validated using an internal test set and two external independent sets. Using this classifier, we classified patients in the training set into high- or low-risk groups with significantly different overall survival (OS, HR = 8.42, 95% CI = 4.99–14.2, p < 0.0001). The prognostic power of the classifier was then assessed in the other sets. The classifier was an independent prognostic factor and had better prognostic value than clinicopathological risk factors. The patients in the high-risk group were found to have a favorable response to adjuvant chemotherapy (HR = 0.4, 95% CI = 0.25–0.64, p < 0.0001). We built a nomogram that integrated the 10-lncRNA-based classifier and four clinicopathological risk factors to predict 3 and 5 year OS. Gene set variation analysis (GSVA) showed that pathways related to tumorigenesis, undifferentiated cancer, and epithelial–mesenchymal transition were enriched in the high-risk groups. Our classifier built on 10-lncRNAs is a reliable prognostic and predictive tool for OS in glioma patients and could predict which patients would benefit from adjuvant chemotherapy.

Background: There existed limited evidence about prognosis of young-onset early colorectal cancer (ECRC). In the present study, we aimed to compare prognosis between patients with young-onset ECRCs and patients with conventional ECRCs.Method: Patients with surgically resected, histologically diagnosed ECRCs were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Young-onset ECRC was defined as ECRC occurring in patients aged