FBXL18 increases cell proliferation and reduces cell radiosensitivity in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common malignant tumors worldwide. In this study, we aimed to investigate the pathophysiological mechanism through which F‑box and leucine-rich repeat protein 18 (FBXL18) promotes the progression of ESCC.

METHODS

ESCC cell lines KYSE150 and TE‑1 were infected with PLVX-FBXL18 or shFBXL18-derived lentivirus to overexpress or knock down FBXL18. A Cell-Counting Kit 8 and colony-forming assay were used to assess cell viability and proliferation. Cells were irradiated with varying doses of X‑ray (IR) to determine whether FBXL18 influenced the radiosensitivity of ESCC cells. KYSE450 cells, stably transduced with shNC or shFBXL18-derived lentivirus, were injected into nude mice to assess whether FBXL18 affected ESCC tumor growth. KYSE150 and TE-1 cells overexpressing FBXL18 were lysed for Western blot analysis to evaluate protein expression.

RESULTS

FBXL18 overexpression enhanced cell viability and colony formation, and proliferation of ESCC cells. In contrast, FBXL18 knockdown inhibited tumor growth in vivo. Additionally, FBXL18 overexpression reduced the radiosensitivity of ESCC cells. Mechanistically, FBXL18 was found to exert its effects by suppressing the expression of FBXL7 in ESCC cells.

CONCLUSION

FBXL18 promotes cell proliferation and diminishes radiosensitivity in ESCC cells. Most likely, it exerts its pro-tumorigenic effects by downregulating FBXL7.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experiments

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through in vitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration in vitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

Machine learning discrimination of Gleason scores below GG3 and above GG4 for HSPC patients diagnosis

This study aims to develop machine learning (ML)-assisted models for analyzing datasets related to Gleason scores in prostate cancer, conducting statistical analyses on the datasets, and identifying meaningful features. We retrospectively collected data from 717 hormone-sensitive prostate cancer (HSPC) patients at Yunnan Cancer Hospital. Of these, data from 526 patients were used for modeling. Seven auxiliary models were established using Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Extreme gradient boosting tree (XGBoost), Adaptive Boosting (Adaboost), and artificial neural network (ANN) based on 21 clinical biochemical indicators and features. Evaluation metrics included accuracy (ACC), precision (PRE), specificity (SPE), sensitivity (SEN) or regression rate(Recall), and f1 score. Evaluation metrics for the models primarily included ACC, PRE, SPE, SEN or Recall, f1 score, and area under the curve(AUC). Evaluation metrics were visualized using confusion matrices and ROC curves. Among the ensemble learning methods, RF, XGBoost, and Adaboost performed the best. RF achieved a training dataset score of 0.769 (95% CI: 0.759-0.835) and a testing dataset score of 0.755 (95% CI: 0.660-0.760) (AUC: 0.786, 95%CI: 0.722-0.803), while XGBoost achieved a training dataset score of 0.755 (95% CI: 95%CI: 0.711-0.809) and a testing dataset score of 0.745 (95% CI: 0.660-0.764) (AUC: 0.777, 95% CI: 0.726-0.798). Adaboost scored 0.789 on the training dataset (95% CI: 0.782-0.857) and 0.774 on the testing dataset (95% CI: 0.651-0.774) (AUC: 0.799, 95% CI: 0.703-0.802). In terms of feature importance (FI) in ensemble learning, Bone metastases at first visit, prostatic volume, age, and T1-T2 have significant proportions in RF's FI. fPSA, TPSA, and tumor burden have significant proportions in Adaboost's FI, while f/TPSA, LDH, and testosterone have the highest proportions in XGBoost. Our findings indicate that ensemble learning methods demonstrate good performance in classifying HSPC patient data, with TNM staging and fPSA being important classification indicators. These discoveries provide valuable references for distinguishing different Gleason scores, facilitating more accurate patient assessments and personalized treatment plans.

LRRC75A-AS1 Drives the Epithelial-Mesenchymal Transition in Cervical Cancer by Binding IGF2BP1 and Inhibiting SYVN1-Mediated NLRP3 Ubiquitination

Cervical cancer severely affects women's health with increased incidence and poor survival for patients with metastasis. Our study aims to investigate the mechanism by which lncRNA LRRC75A-AS1 regulates the epithelial-mesenchymal transition (EMT) of cervical cancer through modulating m6A and ubiquitination modification. In this study, tumor tissues were collected from patients to analyze the expression of LRRC75A-AS1 and SYVN1. Migratory and invasive capacities of HeLa and CaSki cells were evaluated with wound healing and transwell assays. CCK-8 and EdU incor-poration assays were employed to examine cell proliferation. The interaction between LRRC75A-AS1, IGF2BP1, SYVN1, and NLRP3 was evaluated through RNA immunoprecipitation, RNA pull-down, FISH, and coimmunoprecipitation assays, respectively. MeRIP-qPCR was applied to analyze the m6A modification of SYVN1 mRNA. A subcutaneous tumor model of cervical cancer was established. We showed LRRC75A-AS1 was upregulated in tumor tissues, and LRRC75A-AS1 enhanced EMT through activating NLRP3/IL1β/Smad2/3 signaling in cervical cancer. Furthermore, LRRC75A-AS1 inhibited SYVN1-mediated NLRP3 ubiquitination by destabilizing SYVN1 mRNA. LRRC75A-AS1 competitively bound to IGF2BP1 protein and subsequently impaired the m6A modification of SYVN1 mRNA and its stability. Knockdown of LRRC75A-AS1 repressed EMT and tumor growth via inhibiting NLRP3/IL-1β/Smad2/3 signaling in mice. In conclusion, LRRC75A-AS1 competitively binds to IGF2BP1 protein to destabilize SYVN1 mRNA, subsequently suppresses SYVN1-mediated NLRP3 ubiquitination degradation and activates IL1β/Smad2/3 signaling, thus promoting EMT in cervical cancer. Implication: LRRC75A-AS1 promotes cervical cancer progression, and this study suggests LRRC75A-AS1 as a new therapeutic target for cervical cancer.

The role of intestinal flora on tumorigenesis, progression, and the efficacy of PD-1/PD-L1 antibodies in colorectal cancer

Intestinal flora affects the maturation of the host immune system, serves as a biomarker and efficacy predictor in the immunotherapy of several cancers, and has an important role in the development of colorectal cancer (CRC). Anti-PD-1/PD-L1 antibodies have shown satisfactory results in MSI-H/dMMR CRC but performed poorly in patients with MSS/pMMR CRC. In recent years an increasing number of studies have shown that intestinal flora has an important impact on anti-PD-1/PD-L1 antibody efficacy in CRC patients. Preclinical and clinical evidence have suggested that anti-PD-1/PD-L1 antibody efficacy can be improved by altering the composition of the intestinal flora in CRC. Herein, we summarize the studies related to the influence of intestinal flora on anti-PD-1/PD-L1 antibody efficacy in CRC and discuss the potential underlying mechanism(s). We have focused on the impact of the intestinal flora on the efficacy and safety of anti-PD-1/PD-L1 antibodies in CRC and how to better utilize the intestinal flora as an adjuvant to improve the efficacy of anti-PD-1/PD-L1 antibodies. In addition, we have provided a basis for the potential of the intestinal flora as a new treatment modality and indicator for determining patient prognosis.

Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points

BACKGROUND AND PURPOSE

Recently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients.

METHODS

This research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients' overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell's C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan-Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26.

RESULTS

This study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell's C-index in the training and validation sets of the model was 0.85 (95% CI 0.76-0.93) and 0.88 (95% CI 0.76-0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy.

CONCLUSION

This study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.

Self-disclosure and reproductive concerns among breast cancer female patients: the chain mediation model of couples' cancer-related communication problems and relationship intimacy

PURPOSE

Reproductive concerns are prevalent in the female breast cancer patient population and increase existential distress. Although self-disclosure significantly correlated reproductive concerns, the exact mechanism of action is unknown. Based on previous theoretical studies on couples' cancer-related communication problems and intimacy in couples, this study constructed a chain mediation model to investigate whether the two variables mediate the relationship between self-disclosure and reproductive concerns.

METHODS

A cross-sectional survey was conducted from August 2023 to July 2024 at Jiangxi Cancer Hospital. A total of 280 female breast cancer patients completed the Distress Disclosure Index, Couples' Cancer-Related Communication Problems Scale, Quality Relationship Index, and Reproductive Concerns After Cancer Scale. Data description and Pearson's correlation analysis were performed through SPSS 26.0 software. Serial mediation effect analysis and testing were performed through Hayes' Process 4.1 program.

RESULTS

Self-disclosure was found to be negatively associated with reproductive concerns and couples' cancer-related communication problems, but positively associated with intimacy. After controlling for sociodemographic variables, including age, matrimonial, number of children, and hormone receptor, the direct effect of self-disclosure on reproductive concerns was significant (Effect =  - 0.320; 95% CI, - 0.465 to - 0.178). In addition, three other indirect pathways of action were also significant: (1) through couples' cancer-related communication problems (Effect =  - 0.113; 95% CI, - 0.181 to - 0.045), (2) through intimate relationships (Effect =  - 0.110, 95% CI - 0.187 to - 0.043), and (3) through the chain-mediated effects of couples' cancer-related communication problems and intimacy (Effect =  - 0.025; 95% CI, - 0.054 to - 0.007). The total indirect effect of the three pathways of action was 43.66%.

CONCLUSIONS

Self-disclosure not only directly affects reproductive concerns in female breast cancer patients, but also indirectly through couples' cancer-related communication problems and intimacy, as well as sequential mediation of the two. Interventions targeting the above factors can help promote self-disclosure in female breast cancer patients, reduce couples' cancer-related communication problems, and improve intimacy, thereby alleviating reproductive concerns after cancer.