OBJECTIVE: To use circulating tumor cells (CTC) from the first drainage vein (FDV) of the primary lesion and other clinically relevant parameters to construct a nomogram for predicting liver metastasis in colorectal cancer (CRC) patients, and to provide a theoretical basis for clinical diagnosis and treatment.
METHODS: Information from 343 CRC patients was collected and a database was established. Multivariate logistic analysis was used to identify independent factors for colorectal cancer liver metastasis(mCRC) and nomograms were constructed. Receiver operating characteristic curves(ROC), calibration plots, and decision curve analysis (DCA) were used to assess discrimination, agreement with actual risk, and the clinical utility of the prediction model, respectively.
RESULTS: CTC levels in FDV were significantly higher in patients with liver metastasis than in those without liver metastasis. Logistic multivariate analysis showed that vascular invasion, T stage, carcinoembryonic antigen (CEA), CA19-9, and CTC could be used as predictors to construct nomograms. The nomograms showed good discriminatory ability in predicting mCRC, with area under the curve (AUC) values of 0.871 [95 % CI: 0.817-0.924) and 0.891 (95 % CI: 0.817-0.964) for the training and validation sets, respectively.] The calibration curves of both the training and validation sets showed that the model was effective in predicting the probability of mCRC. DCA was used to evaluate this predictive model and showed good net clinical benefit.
CONCLUSIONS: We developed and validated a nomogram model based on the combination of CTC in the FDV with other clinical parameters to better predict the occurrence of mCRC.

Liver metastases occur commonly in many solid malignancies. With advances in systemic therapies and increased life expectancy, the role of using local therapies in oligo-metastases is rapidly increasing. Stereotactic body radiotherapy (SBRT) is an emerging precision therapy that is being used more frequently in the treatment for unresectable liver metastases. This review focuses on the role of SBRT for liver metastases, principles of treatment, clinical outcomes, toxicity, and optimal patient selection.

OBJECTIVE: The purpose of the study is to construct meaningful nomogram models according to the independent prognostic factor for metastatic pancreatic cancer receiving chemotherapy.
METHODS: This study is retrospective and consecutively included 143 patients from January 2013 to June 2021. The receiver operating characteristic (ROC) curve with the area under the curve (AUC) is utilized to determine the optimal cut-off value. The Kaplan-Meier survival analysis, univariate and multivariable Cox regression analysis are exploited to identify the correlation of inflammatory biomarkers and clinicopathological features with survival. R software are run to construct nomograms based on independent risk factors to visualize survival. Nomogram model is examined using calibration curve and decision curve analysis (DCA).
RESULTS: The best cut-off values of 966.71, 0.257, and 2.54 for the systemic immunological inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-lymphocyte ratio (NLR) were obtained by ROC analysis. Cox proportional-hazards model revealed that baseline SII, history of drinking and metastasis sites were independent prognostic indices for survival. We established prognostic nomograms for primary endpoints of this study. The nomograms\' predictive potential and clinical efficacy have been evaluated by calibration curves and DCA.
CONCLUSIONS: We constructed nomograms based on independent prognostic factors, these models have promising applications in clinical practice to assist clinicians in personalizing the management of patients.

With the widespread use of anti-androgen therapy, such as abiraterone and enzalutamide, the incidence of neuroendocrine prostate cancer (NEPC) is increasing. NEPC is a lethal form of prostate cancer (PCa), with a median overall survival of less than one year after diagnosis. In addition to the common bone metastases seen in PCa, NEPC exhibits characteristics of visceral metastases, notably liver metastasis, which serves as an indicator of a poor prognosis clinically. Key factors driving the neuroendocrine plasticity of PCa have been identified, yet the underlying mechanism behind liver metastasis remains unclear. In this study, we identified PROX1 as a driver of neuroendocrine plasticity in PCa, responsible for promoting liver metastases. Mechanistically, anti-androgen therapy alleviates transcriptional inhibition of PROX1. Subsequently, elevated PROX1 levels drive both neuroendocrine plasticity and liver-specific transcriptional reprogramming, promoting liver metastases. Moreover, liver metastases in PCa induced by PROX1 depend on reprogrammed lipid metabolism, a disruption that effectively reduces the formation of liver metastases.

OBJECTIVE: This meta-analysis aimed to compare the diagnostic effectiveness of [18F]FDG PET/CT with that of [18F]FDG PET/MRI in terms of identifying liver metastasis in patients with primary cancer.
METHODS: PubMed, Embase, Web of Science, and the Cochrane Library were searched, and studies evaluating the diagnostic efficacy of [18F]FDG PET/CT and [18F]FDG PET/MRI in patients with liver metastasis of primary cancer were included. We used a random effects model to analyze their sensitivity and specificity. Subgroup analyses and corresponding meta-regressions focusing on race, image analysis, study design, and analysis methodologies were conducted. Cochrane Q and I2 statistics were used to assess intra-group and inter-group heterogeneity.
RESULTS: Seven articles with 343 patients were included in this meta-analysis. The sensitivity of [18F]FDG PET/CT was 0.82 (95 % CI: 0.63-0.96), and that of [18F]FDG PET/MRI was 0.91 (95 % CI: 0.82-0.98); there was no significant difference between the two methods (P = 0.32). Similarly, both methods showed equal specificity: 1.00 (95 % CI: 0.95-1.00) for [18F]FDG PET/CT and 1.00 (95 % CI: 0.96-1.00) for [18F]FDG PET/MRI, and thus, there was no significant difference between the methods (P = 0.41). Furthermore, the subgroup analyses revealed no differences. Meta-regression analysis revealed that race was a potential source of heterogeneity for [18F]FDG PET/CT (P = 0.01), while image analysis and contrast agent were found to be potential sources of heterogeneity for [18F]FDG PET/MRI (P = 0.02).
CONCLUSIONS: [18F]FDG PET/MRI has similar sensitivity and specificity to [18F]FDG PET/CT for detecting liver metastasis of primary cancer in both the general population and in subgroups. [18F]FDG PET/CT may be a more cost-effective option. However, the conclusions of this meta-analysis are tentative due to the limited number of studies included, and further research is necessary for validation.

UNASSIGNED: Long noncoding RNAs (lncRNAs) have emerged as critical regulators of colorectal cancer (CRC) progression, but their roles and underlying mechanisms in colorectal cancer liver metastases (CRLMs) remain poorly understood.
UNASSIGNED: To explore the expression patterns and functions of lncRNAs in CRLMs, we analyzed the expression profiles of lncRNAs in CRC tissues using the TCGA database and examined the expression patterns of lncRNAs in matched normal, CRC, and CRLM tissues using clinical samples. We further investigated the biological roles of LINC02257 in CRLM using in vitro and in vivo assays, and verified its therapeutic potential in a mouse model of CRLM.
UNASSIGNED: Our findings showed that LINC02257 was highly expressed in metastatic CRC tissues and its expression was negatively associated with overall survival. Functionally, LINC02257 promoted CRC cell growth, migration, metastasis, and inhibited cell apoptosis in vitro, and enhanced liver metastasis in vivo. Mechanistically, LINC02257 up-regulated phosphorylated c-Jun N-terminal kinase (JNK) to promote CRLM.
UNASSIGNED: Our study revealed that LINC02257 played a key role in the proliferation and metastasis of CRC cells through the LINC02257/JNK axis. Targeting this axis may represent a promising therapeutic strategy for the treatment of liver metastases in patients with CRC.

BACKGROUND: Ovarian clear cell carcinoma (OCCC) is a rare pathological histotype in ovarian cancer, while the survival rate of advanced OCCC (Stage III-IV) is substantially lower than that of the advanced serous ovarian cancer (OSC), which is the most common histotype. The goal of this study was to identify high-risk OCCC by comparing OSC and OCCC, with investigating potential risk and prognosis markers.
METHODS: Patients diagnosed with ovarian cancer from 2009 to 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) Program. Logistic and Cox regression models were used to identify risk and prognostic factors in high-risk OCCC patients. Cancer-specific survival (CSS) and overall survival (OS) were assessed using Kaplan-Meier curves. Furthermore, Cox analysis was employed to build a nomogram model. The performance evaluation results were displayed using the C-index, calibration plots, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Immunohistochemically approach was used to identify the expression of the novel target (GPC3).
RESULTS: In the Cox analysis for advanced OCCC, age (45-65 years), tumor numbers (total number of in situ/malignant tumors for patient), T3-stage, bilateral tumors, and liver metastases could be defined as prognostic variables. Nomogram showed good predictive power and clinical practicality. Compared with OSC, liver metastases had a stronger impact on the prognosis of patients with OCCC. T3-stage, positive distant lymph nodes metastases, and lung metastases were risk factors for developing liver metastases. Chemotherapy was an independent prognostic factor for patient with advanced OCCC, but had no effect on CSS in patients with liver metastases (p = 0.0656), while surgery was significantly related with better CSS in these patients (p < 0.0001) (p = 0.0041). GPC3 expression was detected in all tissue sections, and GPC3 staining was predominantly found in the cytoplasm and membranes.
CONCLUSIONS: Advanced OCCC and OCCC with liver metastases are two types of high-risk OCCC. The constructed nomogram exhibited a satisfactory survival prediction for patients with advanced OCCC. GPC3 immunohistochemistry is expected to accumulate preclinical evidence to support the inclusion of GPC3 in OCCC targeted therapy.

UNASSIGNED: Although immune checkpoint inhibitor treatment for advanced thymic carcinoma exhibits promising efficacy, factors that affect the efficacy and prognosis, including metastases sites, remain uncertain.
UNASSIGNED: Our study aimed to investigate the determinants of survival among patients with advanced thymic carcinoma who underwent immunotherapy in real-world settings, with implications for clinical practice.
UNASSIGNED: Different therapy regimens of immunotherapy were produced to analyze the influence of liver metastases on survival and prognosis for advanced thymic carcinoma patients.
UNASSIGNED: Data for advanced thymic carcinoma patients receiving immunotherapy and their metastases sites were collected for analysis from seven different hospitals between January 2015 and January 2023. Progression-free survival (PFS) and overall survival (OS) analyses were performed using the Kaplan-Meier method. Cox analysis was used to evaluate factors influencing survival.
UNASSIGNED: The present study analyzed 136 advanced thymic carcinoma patients from seven different hospitals.The PFS for all patients receiving immunotherapy was 6.4 months, while the OS was 24.0 months. The objective response rate was different for patients with liver and non-liver metastases (11.9% versus 37.2%, p = 0.003). The disease control rate values were also different between the two groups (47.6% versus 80.9%, p = 0.037). The PFS for patients with liver metastases demonstrated poor immunotherapy efficacy compared to patients with non-liver metastases (3.0 versus 8.0 months, p < 0.0001). The OS was also significantly different between these two patient groups (16.1 versus 29.1 months, p = 0.009).
UNASSIGNED: Immunotherapy had poor efficacy in advanced thymic carcinoma patients with liver metastases.

BACKGROUND: Liver metastases (LM) is the primary factor contributing to unfavorable outcomes in patients diagnosed with gastric cancer (GC). The objective of this study is to analyze significant prognostic risk factors for patients with GCLM and develop a reliable nomogram model that can accurately predict individualized prognosis, thereby enhancing the ability to evaluate patient outcomes.
OBJECTIVE: To analyze prognostic risk factors for GCLM and develop a reliable nomogram model to accurately predict individualized prognosis, thereby enhancing patient outcome assessment.
METHODS: Retrospective analysis was conducted on clinical data pertaining to GCLM (type III), admitted to the Department of General Surgery across multiple centers of the Chinese PLA General Hospital from January 2010 to January 2018. The dataset was divided into a development cohort and validation cohort in a ratio of 2:1. In the development cohort, we utilized univariate and multivariate Cox regression analyses to identify independent risk factors associated with overall survival in GCLM patients. Subsequently, we established a prediction model based on these findings and evaluated its performance using receiver operator characteristic curve analysis, calibration curves, and clinical decision curves. A nomogram was created to visually represent the prediction model, which was then externally validated using the validation cohort.
RESULTS: A total of 372 patients were included in this study, comprising 248 individuals in the development cohort and 124 individuals in the validation cohort. Based on Cox analysis results, our final prediction model incorporated five independent risk factors including albumin levels, primary tumor size, presence of extrahepatic metastases, surgical treatment status, and chemotherapy administration. The 1-, 3-, and 5-years Area Under the Curve values in the development cohort are 0.753, 0.859, and 0.909, respectively; whereas in the validation cohort, they are observed to be 0.772, 0.848, and 0.923. Furthermore, the calibration curves demonstrated excellent consistency between observed values and actual values. Finally, the decision curve analysis curve indicated substantial net clinical benefit.
CONCLUSIONS: Our study identified significant prognostic risk factors for GCLM and developed a reliable nomogram model, demonstrating promising predictive accuracy and potential clinical benefit in evaluating patient outcomes.

OBJECTIVE: To explore the efficacy of serplulimab plus chemotherapy in esophageal squamous cell carcinoma (ESCC) patients with liver metastases.
METHODS: A post hoc exploratory analysis of ASTRUM-007 study was performed, focusing on the association between the liver metastases status and the clinical outcomes. A systematic literature search of electronic databases was conducted to identify eligible randomized controlled trials for the meta-analysis. Study-level pooled analyses of hazard ratios (HRs) for PFS according to liver metastases were performed.
RESULTS: The post hoc analysis of ASTRUM-007 showed that although patients with liver metastases had a worse prognosis comparing with the non-liver metastases patients in both treatment arms (serplulimab plus chemotherapy arm: median PFS, 5.7 vs. 6.6 months, HR 1.57 [95% CI, 1.15-2.13]; median OS, 13.7 vs. 15.3 months, HR 1.48 [95% CI, 1.09-1.98]; placebo plus chemotherapy arm: median PFS, 4.3 vs. 5.5 months, HR 1.58 [95% CI, 1.01-2.39]; median OS, 10.3 vs. 11.2 months, HR 1.32 [95% CI, 0.84-2.00]), OS and PFS benefits derived from serplulimab plus chemotherapy versus placebo plus chemotherapy in this study were observed in both patients with liver metastases (HR of PFS: 0.60; 95% CI, 0.37-0.97; HR of OS: 0.68; 95% CI, 0.43-1.11) and the non-liver metastases patients (HR of PFS: 0.62; 95% CI, 0.49-0.80; HR of OS: 0.69; 95% CI, 0.55-0.87) with similar magnitude. Three randomized controlled trials were included in the meta-analysis. Pooled HRs demonstrated that the addition of anti-PD-1 antibodies significantly improved PFS compared to chemotherapy alone regardless of liver metastases status.
CONCLUSIONS: This study reveals that the presence of liver metastases is a poor prognostic factor but does not affect the improvements in both PFS and OS brought by adding PD-1 blockade to chemotherapy in ESCC patients. Predictive biomarkers for survival in these patients warrant further investigation.