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Anoikis is a distinct type of programmed cell death and a unique mechanism for tumor progress. However, its exact function in gastric cancer (GC) remains unknown. This study aims to investigate the function of anoikis-related lncRNA (ar-lncRNA) in the prognosis of GC and its immunological infiltration. The ar-lncRNAs were derived from RNA sequencing data and associated clinical information obtained from The Cancer Genome Atlas. Pearson correlation analysis, differential screening, LASSO and Cox regression were utilized to identify the typical ar-lncRNAs with prognostic significance, and the corresponding risk model was constructed, respectively. Comprehensive methods were employed to assess the clinical characteristics of the prediction model, ensuring the accuracy of the prediction results. Further analysis was conducted on the relationship between immune microenvironment and risk features, and sensitivity predictions were made about anticancer medicines. A risk model was built according to seven selected ar-lncRNAs. The model was validated and the calibration plots were highly consistent in validating nomogram predictions. Further analyses revealed the great accuracy of the model and its ability to serve as a stand-alone GC prognostic factor. We subsequently disclosed that high-risk groups display significant enrichment in pathways related to tumors and the immune system. Additionally, in tumor immunoassays, notable variations in immune infiltrates and checkpoints were noted between different risk groups. This study proposes, for the first time, that prognostic signatures of ar-lncRNA can be established in GC. These signatures accurately predict the prognosis of GC and offer potential biomarkers, suggesting new avenues for basic research, prognosis prediction and personalized diagnosis and treatment of GC. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is the second-most common cancer among men. Both active surveillance or watchful waiting (AS/WW) and focal laser ablation (FLA) can avoid the complications caused by radical treatment. How to make the choice between these options in clinical practice needs further study. Therefore, this study aims to compare and analyze their effects based on overall survival (OS) and cancer-specific survival (CSS) to obtain better long-term benefits. We included patients with low-risk PCa from the Surveillance Epidemiology and End Results database of 2010–2016. Multivariate Cox proportional hazard analyses were conducted for OS and CSS in the two groups. To eliminate bias, this study applied a series of sensitivity analyses. Moreover, Kaplan–Meier curves were plotted to obtain survival status. A total of 18 841 patients with low-risk PCa were included, with a median of 36-month follow-up. According to the multivariate Cox proportional hazard regression, the FLA group presented inferior survival benefits in OS than the AS/WW group (hazard ratio [HR]: 2.13, 95% confidence interval [CI]: 1.37–3.33, P < 0.05). After adjusting for confounders, the result persisted (HR: 1.69, 95% CI: 1.02–2.81, P < 0.05). According to the results of the sensitivity analysis, the inverse probability of the treatment weighing model indicated the same result in OS. In conclusion, AS/WW and FLA have the advantage of fewer side effects and the benefit of avoiding overtreatment compared with standard treatment. Our study suggested that AS/WW provides more survival benefits for patients with low-risk PCa. More relevant researches and data will be needed for further clarity. [ABSTRACT FROM AUTHOR]

Biochemical recurrence (BCR) is important for measuring the oncological outcomes of patients who undergo radical prostatectomy (RP). Whether transurethral resection of the prostate (TURP) has negative postoperative effects on oncological outcomes remains controversial. The primary aim of our retrospective study was to determine whether a history of TURP could affect the postoperative BCR rate. We retrospectively reviewed patients with prostate cancer (PCa) who had undergone RP between January 2009 and October 2017. Clinical data on age, prostate volume, serum prostate-specific antigen levels (PSA), biopsy Gleason score (GS), metastasis stage (TNM), D'Amico classification, and American Society of Anesthesiologists (ASA) classification were collected. Statistical analyses including Cox proportional hazard models and sensitivity analyses which included propensity score matching, were performed, and the inverse-probability-of-treatment-weighted estimator and standardized mortality ratio-weighted estimator were determined. We included 1083 patients, of which 118 had a history of TURP. Before matching, the non-TURP group differed from the TURP group with respect to GS (P= 0.047), prostate volume (mean: 45.19 vs 36.00 ml, P < 0.001), and PSA level (mean: 29.41 vs 15.11 ng ml−1, P= 0.001). After adjusting for age, PSA level, T stage, N stage, M stage, and GS, the TURP group showed higher risk of BCR (hazard ratio [HR]: 2.27, 95% confidence interval [CI]: 1.13–3.94, P= 0.004). After matching (ratio 1:4), patients who underwent TURP were still more likely to develop BCR according to the adjusted propensity score (HR: 2.00, 95% CI: 1.05–3.79, P= 0.034). Among patients with PCa, those with a history of TURP were more likely to develop BCR after RP. [ABSTRACT FROM AUTHOR]

Background: Patients with resectable esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant immunotherapy (NIT) display variable treatment responses. The purpose of this study is to establish and validate a radiomics based on enhanced computed tomography (CT) and combined with clinical data to predict the major pathological response to NIT in ESCC patients., Methods: This retrospective study included 82 ESCC patients who were randomly divided into the training group (n = 57) and the validation group (n = 25). Radiomic features were derived from the tumor region in enhanced CT images obtained before treatment. After feature reduction and screening, radiomics was established. Logistic regression analysis was conducted to select clinical variables. The predictive model integrating radiomics and clinical data was constructed and presented as a nomogram. Area under curve (AUC) was applied to evaluate the predictive ability of the models, and decision curve analysis (DCA) and calibration curves were performed to test the application of the models., Results: One clinical data (radiotherapy) and 10 radiomic features were identified and applied for the predictive model. The radiomics integrated with clinical data could achieve excellent predictive performance, with AUC values of 0.93 (95% CI 0.87-0.99) and 0.85 (95% CI 0.69-1.00) in the training group and the validation group, respectively. DCA and calibration curves demonstrated a good clinical feasibility and utility of this model., Conclusion: Enhanced CT image-based radiomics could predict the response of ESCC patients to NIT with high accuracy and robustness. The developed predictive model offers a valuable tool for assessing treatment efficacy prior to initiating therapy, thus providing individualized treatment regimens for patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Tang, Zhong, Wang, Feng, Zhang and Liu.)

Objectives: Carcinosarcoma (CS) is a rare and biphasic malignancy characterised by a highly invasive biological nature and poor prognosis. This study explored the epidemiology, site-specific characteristics and survival outcome of CS., Design: We conducted a retrospective study in the Surveillance, Epidemiology and End Results (SEER) database (1975-2018) for primary CS., Setting and Participants: SEER database includes publicly available information from regional and state cancer registries in the US centres. A total of 5042 CS patients were identified. We selected the top five anatomic CS (uterus, double adnexa, lung, bladder and breast) patients for further analysis., Primary Outcome Measures: Incidence was estimated by geographical region, age, sex, race, stage and primary site. Trends were calculated using joinpoint regression. The cancer-specific survival (CSS) rate and initial treatment were summarised., Results: Nearly 80% of CS occurred in the uterus and double adnexa, followed by lung, bladder and breast. The elderly and black population presented the highest age-adjusted rate of CS. The rates of distant metastasis in CS progressively increased from 1989 to 2018. Atlanta was the area with the highest incidence at 0.7 per 100 000. Pulmonary and bladder CS more frequently occurred in men and were diagnosed with regional stage. Distant metastasis was mostly found in ovary/fallopian tube CS. Radiotherapy was more commonly applied in uterine CS, while adnexa CS cases were more likely to receive chemotherapy. Multiple treatments were more used in breast CS. Pulmonary CS seemed to suffer worse CSS (median: 9.92 months), for which radiotherapy might not provide survival benefits (HR 0.60, 95% CI 0.42 to 0.86). Compared with the common histological types in each site, CS had the shortest survival., Conclusions: CS has unique clinical features in each primary site. Substantial prognosis variances exist based on tumour locations. The aggressive course is the common feature in CS at all sites., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)