Correlation and Survival Analysis of Distant Metastasis Site and Prognosis in Patients With Hepatocellular Carcinoma

Metabolomics Analysis of Functional Activity Changes in Residual Tumour Cells After IOCS Treatment

Hepatocellular carcinoma (HCC) is a serious and often lethal cancer, particularly in patients with chronic liver disease. Currently, no specific treatment has been utilised to prevent HCC. The detailed mechanism of HCC is still elusive, and this study aims to identify and characterise the functional activity changes in residual tumour cells following intraoperative cell salvage (IOCS) treatment during HCC surgery. This research is a retrospective case-control study, involving the selection of 60 patients with HCC who underwent radical surgery; then blood and tumour tissue were collected for further testing. GC-MS assay, immunofluorescence, Western blot and qRT-PCR techniques were employed. Our study found comparable demographic and baseline clinical characteristics between the experimental group (n = 30), which received IOCS treatment during surgery, and the control group (n = 30), which did not receive IOCS treatment, validating subsequent analyses. Metabolomic analysis revealed six key metabolites differing between groups, indicating improvement in liver tumours in the experimental group. TP53 expression was significantly upregulated, potentially mediating therapeutic effects. The intervention reduced HCC cell migration and apoptosis, decreased E2F1 and MDM2 protein and mRNA levels, and increased TP53 and CTNNB1 levels. These findings support the potential clinical application of the intervention in improving treatment outcomes for HCC patients, warranting further investigation to elucidate the underlying mechanisms and optimise therapeutic strategies.

Betaine inhibits the stem cell-like properties of hepatocellular carcinoma by activating autophagy via SAM/m6A/YTHDF1-mediated enhancement on ATG3 stability

Background: Stem cell-like properties are known to promote the recurrence and metastasis of hepatocellular carcinoma (HCC), contributing to a poor prognosis for HCC patients. Betaine, an important phytochemical and a methyl-donor related substance, has shown protective effects against liver diseases. However, its effect on HCC stem cell-like properties and the underlying mechanisms remains uninvestigated. Methods: We measured the effects of betaine on the stem cell-like properties and malignant progression of HCC using patient-derived xenografts, cell-derived xenografts, tail vein-lung metastasis models, in vitro limiting dilution, tumor sphere formation, colony formation, and transwell assays. Mechanistic exploration was conducted using western blots, dot blots, methylated RNA immunoprecipitation-qPCR, RNA stability assays, RNA immunoprecipitation-qPCR, RNA pull-down, and gene mutation assays. Results: A cohort study of HCC found that a higher serum concentration of betaine was associated with decreased levels of stemness-related markers. Furthermore, in HCC cells and xenograft mice, betaine suppressed the stem cell-like properties of HCC by activating autophagy. Mechanistically, betaine increased the m6A modification in HCC by producing S-adenosylmethionine (SAM) via betaine-homocysteine S-methyltransferase (BHMT). This increase in SAM subsequently triggered autophagy by enhancing the stability of autophagy-related protein 3 (ATG3) via YTHDF1 in an m6A-dependent manner, thereby inhibiting the stem cell-like properties of HCC cells. Conclusions: These findings indicate that betaine inhibits the stem cell-like properties of HCC via the SAM/m6A/YTHDF1/ATG3 pathway. This study underscores the potential anti-tumor effects of betaine on HCC and offers novel therapeutic prospects for HCC patients.

Prevalence, management and outcomes of pulmonary metastases in hepatocellular carcinoma: a systematic review and meta-analysis

BACKGROUND

Hepatocellular carcinoma (HCC) presents a significant global health burden, with varying survival rates across regions. The presence of pulmonary metastases (PM) in HCC predicts a poorer prognosis, yet the global understanding of the progression and management is limited.

METHODS

This study aims to systematically review the burden of PM in HCC, document current treatment approaches, and evaluate treatment effectiveness through meta-analysis. A comprehensive literature search was conducted across multiple databases. Articles were screened, and data extraction was performed independently by two reviewers. Statistical analyses were conducted to synthesise data and assess treatment outcomes.

RESULTS

A total of 82 articles were included, comprising a population of 3241 participants with documented PM. Our analysis revealed a linear relationship between the HCC population size and the occurrence of PM (p < 0.005). Surgical intervention demonstrated the lowest hazard ratio (0.128) and significantly improved survival rates compared to other treatment modalities. However, data quality limitations underscore the need for further research to delineate patient subsets benefitting from surgical intervention for PM.

CONCLUSION

Our findings advocate for continued investigation into PM management strategies, notably the role of surgical resection alongside systemic therapies, to improve outcomes in HCC patients with PM.

Predictive models and treatment efficacy for liver cancer patients with bone metastases: A comprehensive analysis of prognostic factors and nomogram development

Background

Bone metastasis considerably undermines the prognosis of advanced primary liver cancer patients. Though its impact is well-recognized, the clinical field still lacks robust predictive models that can accurately forecast patient outcomes and aid in treatment effectiveness evaluation. Addressing this gap is paramount for improving patient management and survival.

Materials and methods

We conducted an extensive analysis using data from the SEER database (2010-2020). COX regression analysis was applied to identify prognostic factors for primary liver cancer with bone metastasis (PLCBM). Nomograms were developed and validated to predict survival outcomes in PLCBM patients. Additionally, propensity score matching and Kaplan-Meier survival analyses lent additional insight by dissecting the survival advantage conferred by various treatment strategies.

Results

A total of 470 patients with PLCBM were included in our study. The median overall survival (OS) and cancer-specific survival (CSS) for these patients were both 5 months. We unveiled several independent prognosticators for OS and CSS, spanning demographic to therapeutic parameters like marital status, cancer grade, histological type, and treatments received. This discovery enabled the formulation of two novel nomograms-now verified to eclipse the predictive prowess of the traditional TNM staging system regarding discrimination and clinical utility. Additionally, propensity score matching analysis showed the effectiveness of surgeries, radiotherapy, and chemotherapy in improving OS and CSS outcomes for PLCBM patients.

Conclusions

Our investigation stands out by introducing pioneering nomograms for prognostic evaluation in PLCBM, a leap forward compared to existing tools. Far exceeding mere academic exercise, these nomograms hold immense clinical value, serving as a foundation for nuanced risk stratification systems and delivering dynamic, interactive guides, allowing healthcare professionals and patients to assess individual bone metastasis survival probabilities and personalize treatment selection.

Leveraging SEER data through machine learning to predict distant lymph node metastasis and prognosticate outcomes in hepatocellular carcinoma patients

OBJECTIVES

This study aims to develop and validate machine learning-based diagnostic and prognostic models to predict the risk of distant lymph node metastases (DLNM) in patients with hepatocellular carcinoma (HCC) and to evaluate the prognosis for this cohort.

DESIGN

Utilizing a retrospective design, this investigation leverages data extracted from the Surveillance, Epidemiology, and End Results (SEER) database, specifically the January 2024 subset, to conduct the analysis.

PARTICIPANTS

The study cohort consists of 15,775 patients diagnosed with HCC as identified within the SEER database, spanning 2016 to 2020.

METHOD

In the construction of the diagnostic model, recursive feature elimination (RFE) is employed for variable selection, incorporating five critical predictors: age, tumor size, radiation therapy, T-stage, and serum alpha-fetoprotein (AFP) levels. These variables are the foundation for a stacking ensemble model, which is further elucidated through Shapley Additive Explanations (SHAP). Conversely, the prognostic model is crafted utilizing stepwise backward regression to select pertinent variables, including chemotherapy, radiation therapy, tumor size, and age. This model culminates in the development of a prognostic nomogram, underpinned by the Cox proportional hazards model.

MAIN OUTCOME MEASURES

The outcome of the diagnostic model is the occurrence of DLNM in patients. The outcome of the prognosis model is determined by survival time and survival status.

RESULTS

The integrated model developed based on stacking demonstrates good predictive performance and high interpretative variability and differentiation. The area under the curve (AUC) in the training set is 0.767, while the AUC in the validation set is 0.768. The nomogram, constructed using the Cox model, also demonstrates consistent and strong predictive capabilities. At the same time, we recognized elements that have a substantial impact on DLNM and the prognosis and extensively discussed their significance in the model and clinical practice.

CONCLUSION

Our study identified key predictive factors for DLNM and elucidated significant prognostic indicators for HCC patients with DLNM. These findings provide clinicians with valuable tools to accurately identify high-risk individuals for DLNM and conduct more precise risk stratification for this patient subgroup, potentially improving management strategies and patient outcomes.

Analysis of Factors Predicting the Real-World Efficacy of Atezolizumab and Bevacizumab in Patients with Advanced Hepatocellular Carcinoma

Background/Aims

Atezolizumab and bevacizumab have shown promising results for the treatment of advanced hepatocellular carcinoma (HCC) in clinical trials. In this study, the real-world efficacy and safety of atezolizumab and bevacizumab in treating advanced HCC were evaluated.

Methods

In this retrospective study of patients at a Korean tertiary cancer center, 111 patients with Barcelona Clinic Liver Cancer stage B or C HCC received atezolizumab and bevacizumab as first-line therapy from May 2022 to June 2023. We assessed the progression-free survival (PFS), overall response rate (ORR), disease control rate (DCR), and adverse events.

Results

Patients with Barcelona Clinic Liver Cancer stage C HCC and Child-Pugh class A liver function were included in the study. The median PFS was 6.5 months, with an ORR of 27% and a DCR of 63%. Several factors, including the albumin-bilirubin grade, age, C-reactive protein and α-fetoprotein in immunotherapy score, macrovascular invasion, lung metastases, and combined radiotherapy, were found to significantly influence PFS (p<0.05). Patients with peritoneal seeding showed an higher ORR. The safety profile was consistent with that observed in clinical trials.

Conclusions

Atezolizumab and bevacizumab demonstrated real-world efficacy in the treatment of advanced HCC, with ORRs and DCRs aligning with those observed in clinical trials. Variations in PFS and ORR based on specific risk factors highlight the potential of atezolizumab and bevacizumab in precision medicine for advanced HCC.

Nomogram predicting survival in patients with lymph node-negative hepatocellular carcinoma based on the SEER database and external validation

BACKGROUND

The relationship between lymph node (LN) status and survival outcome in hepatocellular carcinoma (HCC) is a highly controversial topic. The aim of this study was to investigate the prognostic factors in patients without LN metastasis (LNM) and to construct a nomogram to predict cancer-specific survival (CSS) in this group of patients.

METHODS

We screened 6840 eligible HCC patients in the Surveillance, Epidemiology and End Results（SEER）database between 2010 and 2019 and randomized them into a training cohort and an internal validation cohort, and recruited 160 patients from Zhongnan Hospital of Wuhan University as an external validation cohort. Independent prognostic factors obtained from univariate and multivariate analysis were used to construct a nomogram prediction model. The concordance index (C-index), area under curve (AUC), calibration plots and decision curve analysis (DCA) were used to assess the predictive power and clinical application of the model.

RESULTS

Univariate and multivariate analysis revealed age, gender, bone metastasis, lung metastasis, AFP, T stage, surgery and chemotherapy as independent prognostic factors. The C-index of the constructed nomogram for the training cohort, internal validation cohort and external validation cohort are 0.746, 0.740, and 0.777, respectively. In the training cohort, the AUC at 1-, 3-, and 5-year were 0.81, 0.800, and 0.800, respectively. Calibration curves showed great agreement between the actual observations and predictions for the three cohorts. The DCA results suggest that the nomogram model has more clinical application potential.

CONCLUSION

We constructed a nomogram to predict CSS in HCC patients without LNM. The model has been internally and externally validated to have excellent predictive performance and can help clinicians determine prognosis and make treatment decisions.

Pediatric hepatocellular carcinoma in a 14-year-old boy: A rare case report

ABSTRACT

Hepatocellular carcinoma (HCC) is much rarer in children and adolescents in comparison to adults with an incidence of 0.7/1,000,000 per year. Hepatitis B virus, a known carcinogen increases the chances of HCC at a young age. Very few case reports of HCC developing in HBV-positive male children have been published.We present a case of a 14-year-old Hepatitis B-positive boy who presented with abdominal distension and jaundice. Contrast enhanced computerized tomography (CECT) whole abdomen suggested a diagnosis of multinodular HCC with no evidence of metastasis on FDG PET-CECT. Histopathology with immunohistochemistry confirmed the diagnosis of moderately differentiated HCC.Clinical presentation of HCC in children is similar to adults. Viral hepatitis, metabolic disorders, and male gender increase the risk of HCC. In our case, boy never had any prior history of jaundice, abdominal pain/distension, or any other illness suggestive of liver dysfunction. When the boy was found to be HBV positive, his mother was also screened and turned out to be Hepatitis B virus positive. Histopathology along with a panel of immunohistochemical markers clinched the final diagnosis.

Development and evaluation of nomograms and risk stratification systems to predict the overall survival and cancer-specific survival of patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and patients with HCC have a poor prognosis and low survival rates. Establishing a prognostic nomogram is important for predicting the survival of patients with HCC, as it helps to improve the patient's prognosis. This study aimed to develop and evaluate nomograms and risk stratification to predict overall survival (OS) and cancer-specific survival (CSS) in HCC patients. Data from 10,302 patients with initially diagnosed HCC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Patients were randomly divided into the training and validation set. Kaplan-Meier survival, LASSO regression, and Cox regression analysis were conducted to select the predictors of OS. Competing risk analysis, LASSO regression, and Cox regression analysis were conducted to select the predictors of CSS. The validation of the nomograms was performed using the concordance index (C-index), the Akaike information criterion (AIC), the Bayesian information criterion (BIC), Net Reclassification Index (NRI), Discrimination Improvement (IDI), the receiver operating characteristic (ROC) curve, calibration curves, and decision curve analyses (DCAs). The results indicated that factors including age, grade, T stage, N stage, M stage, surgery, surgery to lymph node (LN), Alpha-Fetal Protein (AFP), and tumor size were independent predictors of OS, whereas grade, T stage, surgery, AFP, tumor size, and distant lymph node metastasis were independent predictors of CSS. Based on these factors, predictive models were built and virtualized by nomograms. The C-index for predicting 1-, 3-, and 5-year OS were 0.788, 0.792, and 0.790. The C-index for predicting 1-, 3-, and 5-year CSS were 0.803, 0.808, and 0.806. AIC, BIC, NRI, and IDI suggested that nomograms had an excellent predictive performance with no significant overfitting. The calibration curves showed good consistency of OS and CSS between the actual observation and nomograms prediction, and the DCA showed great clinical usefulness of the nomograms. The risk stratification of OS and CSS was built that could perfectly classify HCC patients into three risk groups. Our study developed nomograms and a corresponding risk stratification system predicting the OS and CSS of HCC patients. These tools can assist in patient counseling and guiding treatment decision making.

Progression-free survival, disease-free survival and other composite end points in oncology: improved reporting is needed

Composite outcome measures such as progression-free survival and disease-free survival are increasingly used as surrogate end points in oncology research, frequently serving as the primary end point of pivotal trials that form the basis for FDA and EMA approvals. Such outcome measures combine two or more distinct events (for example, tumour (re)growth, new lesions and/or death) into a single, time-to-event end point. The use of a composite end point can increase the statistical power of a clinical trial and decrease the follow-up period required to demonstrate efficacy, thus lowering costs; however, these end points have a number of limitations. Composite outcomes are often vaguely defined, with definitions that vary greatly between studies, complicating comparisons of results across trials. Altering the makeup of events included in a composite outcome can alter study conclusions, including whether treatment effects are statistically significant. Moreover, the events included in a composite outcome often vary in clinical significance, reflect distinct biological pathways and/or are affected differently by treatment. Therefore, knowing the precise breakdown of the component events is essential to accurately interpret trial results and gauge the true benefit of an intervention. In oncology clinical trials, however, such information is rarely provided. In this Perspective, we emphasize this deficiency through a review of 50 studies with progression-free survival as an outcome published in five top oncology journals, discuss the advantages and challenges of using composite end points, and highlight the need for transparent reporting of the component events.

Conditional survival probability of distant-metastatic hepatocellular carcinoma: A population-based study

BACKGROUND

The prognosis of many patients with distant metastatic hepatocellular carcinoma (HCC) improved after they survived for several months. Compared with traditional survival analysis, conditional survival (CS) which takes into account changes in survival risk could be used to describe dynamic survival probabilities.

AIM

To evaluate CS of distant metastatic HCC patients.

METHODS

Patients diagnosed with distant metastatic HCC between 2010 and 2015 were extracted from the Surveillance, Epidemiology and End Results database. Univariate and multivariate Cox regression analysis were used to identify risk factors for overall survival (OS), while competing risk model was used to identify risk factors for cancer-specific survival (CSS). Six-month CS was used to calculate the probability of survival for an additional 6 mo at a specific time after initial diagnosis, and standardized difference (d) was used to evaluate the survival differences between subgroups. Nomograms were constructed to predict CS.

RESULTS

Positive α-fetoprotein expression, higher T stage (T3 and T4), N1 stage, non-primary site surgery, non-chemotherapy, non-radiotherapy, and lung metastasis were independent risk factors for actual OS and CSS through univariate and multivariate analysis. Actual survival rates decreased over time, while CS rates gradually increased. As for the 6-month CS, the survival difference caused by chemotherapy and radiotherapy gradually disappeared over time, and the survival difference caused by lung metastasis reversed. Moreover, the influence of age and gender on survival gradually appeared. Nomograms were fitted for patients who have lived for 2, 4 and 6 mo to predict 6-month conditional OS and CSS, respectively. The area under the curve (AUC) of nomograms for conditional OS decreased as time passed, and the AUC for conditional CSS gradually increased.

CONCLUSION

CS for distant metastatic HCC patients substantially increased over time. With dynamic risk factors, nomograms constructed at a specific time could predict more accurate survival rates.

Construction and validation of a SEER-based prognostic nomogram for young and middle-aged males patients with hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common digestive tumor, and we aimed to develop and validate nomogram models, predicting the overall survival (OS) of young and middle-aged male patients with HCC.

METHODS

We extracted eligible data from relevant patients between 2000 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database. In addition, randomly divided all patients into two groups (training and validation = 7:3). The nomogram was established using effective risk factors based on univariate and multivariate analysis. The area under the time-dependent curve, calibration plots, and decision curve analysis (DCA) were used to evaluate the effective performance of the nomogram. The risk stratifications of the nomogram and the AJCC criteria-based tumor stage were compared.

RESULTS

11 variables were selected by univariate and multivariate analysis to establish the nomogram of HCC. The AUC values of 3, 4, and 5 years of the time-ROC curve are 0.858, 0.862 and 0.859 for the training cohort, and 0.858, 0.877 and 0.869 for the validation cohort, respectively, indicating that the nomogram has a good ability of discrimination. The calibration plots showed favorable consistency between the prediction of the nomogram and actual observations in both the training and validation cohorts. In addition, the decision curve DCA showed that the nomogram was clinically useful and had better discriminative ability to recognize patients at high risk than the AJCC criteria-based tumor stage.

CONCLUSION

Prognostic nomogram of young and middle-aged male patients with HCC was developed and validated to help clinicians evaluate the prognosis of patients.

Predictors of poor outcome following liver biopsy for the investigation of new hepatic space occupying lesion/s

BACKGROUND

Ultrasound-guided percutaneous liver biopsy (UPLB) is currently performed mainly to determine if new hepatic space occupying lesions (SOL) represent benign, primary malignant, or metastatic disease. This study sought to investigate the outcome of UPLB in this setting.

METHODS

In a retrospective study, patients with a new hepatic SOL who underwent UPLB during 1/2006-12/2016 were included and followed to 12/2018. Clinical data and pathology reports were reviewed. Mortality within 60 days and no change in patients' management following UPLB were defined as medically futile.

RESULTS

Included 140 patients, 50% male, mean age 68.8 ± 11.5 years; 112 patients died, all of malignant disease. 32 patients (23%) died within 60 days of UPLB. Median post-UPLB survival was 151 days. Survival was significantly shorter in patients with >1 hepatic lesion (n = 108) or an extrahepatic malignant lesion (n = 77) (p = 0.0082, p = 0.0301, respectively). On Cox Proportional Hazards analysis, significant predictors of mortality within 60 days of UPLB were: age as a continuous variable, (HR 1.070, 95% CI 1.011-1.131, p = 0.018), serum albumin <2.9 g/dL, (HR 4.822 95% CI 1.335-17.425, p = 0.016) and serum LDH >1500 U/L (HR 9.443, 95% CI 3.404-26.197, p < 0.0001).

CONCLUSIONS

In patients with these features or with disseminated disease, liver biopsy should be carefully reconsidered.

HMGB1/GPC3 dual targeting vaccine induces dendritic cells-mediated CD8+T cell immune response and elicits potential therapeutic effect in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a fatal malignant tumor, but effective clinical interventions are limited. PLGA/PEI-mediated DNA vaccine encoding the dual targets of high-mobility group box 1 (HMGB1) or GPC3 was developed for HCC treatment. Compared with PLGA/PEI-GPC3 immunization, PLGA/PEI-HMGB1/GPC3 co-immunization significantly inhibited the subcutaneous tumor growth, while increasing the infiltration of CD8⁺T cells and DCs. Furthermore, the PLGA/PEI-HMGB1/GPC3 vaccine induced a strong CTL effect and promoted functional CD8⁺T cell proliferation. Intriguingly, the depletion assay proved that the therapeutic effect PLGA/PEI-HMGB1/GPC3 vaccine was dependent on antigen-specific CD8⁺T cell immune responses. In the rechallenge experiment, PLGA/PEI-HMGB1/GPC3 vaccine provided a long-lasting resistance to the growth of the contralateral tumor by inducing the memory CD8⁺T cell responses. Collectively, PLGA/PEI-HMGB1/GPC3 vaccine could induce a strong and long-lasting CTL effect and inhibit the tumor progression or re-attack. Therefore, the combined co-immunization of PLGA/PEI-HMGB1/GPC3 might be served as an effective anti-tumor strategy against HCC.

Prognostic Impact of Metastatic Site in Patients Receiving First-Line Sorafenib Therapy for Advanced Hepatocellular Carcinoma

Extrahepatic spread is a well-known negative prognostic factor in patients with advanced hepatocellular carcinoma (HCC). The prognostic role of different metastatic sites and their response rate to systemic treatment is still being debated. We considered 237 metastatic HCC patients treated with sorafenib as first-line therapy in five different Italian centers from 2010 to 2020. The most common metastatic sites were lymph nodes, lungs, bone and adrenal glands. In survival analysis, the presence of dissemination to lymph nodes (OS 7.1 vs. 10.2 months; p = 0.007) and lungs (OS 5.9 vs. 10.2 months; p < 0.001) were significantly related to worse survival rates compared with all other sites. In the subgroup analysis of patients with only a single metastatic site, this prognostic effect remained statistically significant. Palliative radiation therapy on bone metastases significantly prolonged survival in this cohort of patients (OS 19.4 vs. 6.5 months; p < 0.001). Furthermore, patients with lymph node and lung metastases had worse disease control rates (39.4% and 30.5%, respectively) and shorter radiological progression-free survival (3.4 and 3.1 months, respectively). In conclusion, some sites of an extrahepatic spread of HCC have a prognostic impact on survival in patients treated with sorafenib; in particular, lymph nodes and lung metastases have worse prognosis and treatment response rate.

A population-based study of synchronous distant metastases and prognosis in patients with PDAC at initial diagnosis

Objective

Cancer of the pancreas is a life-threatening condition and has a high distant metastasis (DM) rate of over 50% at diagnosis. Therefore, this study aimed to determine whether patterns of distant metastases correlated with prognosis in pancreatic ductal adenocarcinoma (PDAC) with metastatic spread, and build a novel nomogram capable of predicting the 6, 12, 18-month survival rate with high accuracy.

Methods

We analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database for cases of PDAC with DM. Kaplan-Meier analysis, log-rank tests and Cox-regression proportional hazards model were used to assess the impact of site and number of DM on the cancer-specific survival (CSS) and over survival (OS). A total of 2709 patients with DM were randomly assigned to the training group and validation group in a 7:3 ratio. A nomogram was constructed by the dependent risk factors which were determined by multivariate Cox-regression analysis. An assessment of the discrimination and ability of the prediction model was made by measuring AUC, C-index, calibration curve and decision curve analysis (DCA). In addition, we collected 98 patients with distant metastases at the time of initial diagnosis from Ningbo University Affiliated LiHuili Hospital to verify the efficacy of the prediction model.

Results

There was a highest incidence of liver metastases from pancreatic cancer (2387,74.36%), followed by lung (625,19.47%), bone (190,5.92%), and brain (8,0.25%). The prognosis of liver metastases differed from that of lung metastases, and the presence of multiple organ metastases was associated with poorer prognosis. According to univariate and multivariate Cox-regression analyses, seven factors (i.e., diagnosis age, tumor location, grade of tumor differentiation, T-stage, receipt of surgery, receipt of chemotherapy status, presence of multiple organ metastases) were included in our nomogram model. In internal and external validation, the ROC curves, C-index, calibration curves and DCA were calculated, which confirmed that this nomogram can precisely predict prognosis of PDAC with DM.

Conclusion

Metastatic PDAC patients with liver metastases tended to have a worse prognosis than those with lung metastases. The number of DM had significant effect on the overall survival rate of metastatic PDAC. This study had a high prediction accuracy, which was helpful clinicians to analyze the prognosis of PDAC with DM and implement individualized diagnosis and treatment.

Prognostic impact of tumor size on isolated hepatocellular carcinoma without vascular invasion may have age variance

Background

Previous studies suggested that tumor size was an independent risk factor of prognosis for hepatocellular carcinoma (HCC). However, the general prognostic analysis did not consider the interaction between variables. The purpose of this study was to investigate whether the effect of tumor size on the prognosis of isolated HCC without vascular invasion varies according to covariates.

Methods

Patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database to investigate whether there was an interaction between age and tumor size on the prognosis. Then the trend test and the value of per 1 SD of tumor size were calculated. In addition, the data of Zhejiang Provincial People's Hospital meeting the requirements were selected to verify the obtained conclusions.

Results

Multivariable Cox regression analysis of the database cohort showed that age, gender, tumor size, pathological grade and marital status were independent risk factors for prognosis. Interaction test showed that there was an interaction between age and tumor size (P for interaction < 0.05). Stratified analysis by age showed that tumor size was an independent risk factor for prognosis when age ≤65 years old (HR:1.010,95%CI1.007-1.013 P < 0.001), while tumor size was not an independent risk factor for prognosis when age >65 years old. This result was confirmed by trend analysis (P for trend < 0.001), and the prognostic risk increased by 42.1% for each standard deviation increase of tumor size among patients age ≤65 years. Consistent conclusion was obtained by multivariable cox regression analysis and interaction test on the verification cohort. In the validation cohort, for each standard deviation increase of tumor size in patients ≤65 years old, the risk of prognosis increased by 52.4%.

Conclusion

Tumor size is not an independent risk factor for the prognosis of isolated HCC without vascular invasion when patient's age >65 years. Therefore, when analyzing the relationship between tumor size and prognosis, stratified analysis should be performed according to age.

Evaluation of the Clinical Efficacy of Intensity-Modulated Radiotherapy Combined with Transcatheter Arterial Chemoembolization for Hepatocellular Carcinoma with Extrahepatic Oligometastasis and Prognostic Factors for Patient Survival

Objective

To investigate the clinical efficacy of intensity-modulated radiotherapy (IMRT) combined with transcatheter arterial chemoembolization (TACE) in hepatocellular carcinoma (HCC) patients with extrahepatic oligometastasis and the prognosis of patients receiving this treatment.

Patients and Methods

Twenty-one HCC patients with extrahepatic oligometastasis were retrospectively analyzed; seven patients received IMRT only, and 14 received IMRT plus TACE. TACE treatment was administered before IMRT (50 mg epirubicin, oxaliplatin 100 mg, and mitomycin 10 mg). The short-term efficacy of this treatment and patient prognosis were evaluated.

Results

Complete response (CR) and partial response (PR) in the intrahepatic region were achieved in three and 14 patients, respectively. The objective response rate (ORR) approached 81%. CR and PR were achieved in six and 10 patients with extrahepatic metastases, respectively, for an ORR of 100%. Pain was completely relieved in all patients with bone metastases. The median overall survival (OS) and progression-free survival (PFS) were 21 months and 9.1 months, respectively. The 1-year PFS rate was 43%, and the 1-, 2-, 3-, and 4-year OS rates were 83%, 35%, 9%, and 4%, respectively. Univariate analysis showed that the prognostic factors for patient survival included Child-Pugh class, vascular thrombus, Karnofsky performance status (KPS), radiotherapy dose, ascites, combination therapy, and pattern of progression. Multivariate analysis showed that vascular thrombus, combination therapy, and pattern of failure were prognostic factors for PFS, and the KPS was the only prognostic factor for OS. No grade 3-4 adverse reactions were observed.

Conclusion

IMRT combined with TACE is safe and feasible without major toxicities for the treatment of advanced HCC patients with extrahepatic oligometastasis and results in excellent objective efficacy and a potential survival benefit. The KPS is the only predictive factor for OS. This approach is expected to be a useful palliative option for selected HCC patients with extrahepatic metastases.

Development and validation of an ensemble machine-learning model for predicting early mortality among patients with bone metastases of hepatocellular carcinoma

Purpose

Using an ensemble machine learning technique that incorporates the results of multiple machine learning algorithms, the study's objective is to build a reliable model to predict the early mortality among hepatocellular carcinoma (HCC) patients with bone metastases.

Methods

We extracted a cohort of 124,770 patients with a diagnosis of hepatocellular carcinoma from the Surveillance, Epidemiology, and End Results (SEER) program and enrolled a cohort of 1897 patients who were diagnosed as having bone metastases. Patients with a survival time of 3 months or less were considered to have had early death. To compare patients with and without early mortality, subgroup analysis was used. Patients were randomly divided into two groups: a training cohort (n = 1509, 80%) and an internal testing cohort (n = 388, 20%). In the training cohort, five machine learning techniques were employed to train and optimize models for predicting early mortality, and an ensemble machine learning technique was used to generate risk probability in a way of soft voting, and it was able to combine the results from the multiply machine learning algorithms. The study employed both internal and external validations, and the key performance indicators included the area under the receiver operating characteristic curve (AUROC), Brier score, and calibration curve. Patients from two tertiary hospitals were chosen as the external testing cohorts (n = 98). Feature importance and reclassification were both operated in the study.

Results

The early mortality was 55.5% (1052/1897). Eleven clinical characteristics were included as input features of machine learning models: sex (p = 0.019), marital status (p = 0.004), tumor stage (p = 0.025), node stage (p = 0.001), fibrosis score (p = 0.040), AFP level (p = 0.032), tumor size (p = 0.001), lung metastases (p < 0.001), cancer-directed surgery (p < 0.001), radiation (p < 0.001), and chemotherapy (p < 0.001). Application of the ensemble model in the internal testing population yielded an AUROC of 0.779 (95% confidence interval [CI]: 0.727-0.820), which was the largest AUROC among all models. Additionally, the ensemble model (0.191) outperformed the other five machine learning models in terms of Brier score. In terms of decision curves, the ensemble model also showed favorable clinical usefulness. External validation showed similar results; with an AUROC of 0.764 and Brier score of 0.195, the prediction performance was further improved after revision of the model. Feature importance demonstrated that the top three most crucial features were chemotherapy, radiation, and lung metastases based on the ensemble model. Reclassification of patients revealed a substantial difference in the two risk groups' actual probabilities of early mortality (74.38% vs. 31.35%, p < 0.001). Patients in the high-risk group had significantly shorter survival time than patients in the low-risk group (p < 0.001), according to the Kaplan-Meier survival curve.

Conclusions

The ensemble machine learning model exhibits promising prediction performance for early mortality among HCC patients with bone metastases. With the aid of routinely accessible clinical characteristics, this model can be a trustworthy prognostic tool to predict the early death of those patients and facilitate clinical decision-making.

Not all Rectal Cancer Patients Could Benefit From the Surgery on the Primary Site

AIM

Previous studies have provided evidence that primary site surgery can improve the prognosis of rectal cancer patients, even in those with advanced age and distant metastasis, though results have been inconsistent. The current study aims to determine if all rectal cancer patients are likely to benefit from surgery in terms of overall survival.

METHODS

This study examined the impact of primary site surgery on the prognosis of rectal cancer patients diagnosed between 2010 and 2019 using multivariable Cox regression analysis. The study also stratified patients by age group, M stage, chemotherapy, radiotherapy, and number of distant metastatic organs. The propensity score matching method was used to balance observed covariates between patients who received and did not receive surgery. The Kaplan-Meier method was used to analyze the data, and the log-rank test was used to determine differences between patients who did and did not undergo surgery.

RESULTS

The study included 76,941 rectal cancer patients, with a median survival of 81.0 months (95% CI: 79.2-82.8 months). Of these patients, 52,360 (68.1%) received primary site surgery, and they tended to be younger, have higher differentiated grade, earlier T, N, M stage, and lower rates of bone, brain, lung, and liver metastasis, chemotherapy, and radiotherapy than those without surgery. Multivariable Cox regression analysis revealed that surgery had a protective effect on the prognosis of rectal cancer patients, including those with advanced age, distant metastasis, and multiple organ metastasis, but not in patients with four organ metastases. The results were also confirmed using propensity score matching.

CONCLUSION

Not all rectal cancer patients could benefit from the surgery on the primary site, especially the patients with more than four distant metastases. The results could help the clinicians to tailor targeted treatment regimens and provide a guideline for making surgical decisions.

CAF-Released Exosomal miR-20a-5p Facilitates HCC Progression via the LIMA1-Mediated β-Catenin Pathway

Currently, exosomes derived from Cancer-associated fibroblast (CAF) have reportedly been involved in regulating hepatocellular carcinoma (HCC) tumour microenvironment (TME). LIM domain and actin binding 1 (LIMA1) is an actin-binding protein that is involved in controlling the biological behaviour and progression of specific solid tumours. We aimed to determine the effect of LIMA1 and exosome-associated miR-20a-5p in HCC development. LIMA1 and miR-20a-5p expression levels were examined by real-time quantitative PCR (qRT-PCR), western blotting or immunohistochemistry (IHC). Functional experiments, including Cell Counting Kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU) assays, colony formation assays, wound healing assays, and Transwell invasion assays, were performed to investigate the effect of LIMA1 and miR-20a-5p. A dual-luciferase reporter gene assay was performed to confirm the interaction of miR-20a-5p and LIMA1. Exosomes were characterised by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blotting. We noted that LIMA1 was downregulated in human HCC tissues and cells and remarkably correlated with overall survival (OS) and recurrence-free survival (RFS). LIMA1 overexpression suppressed HCC cell proliferation and metastasis in vitro and in vivo, while LIMA1 knockdown had the opposite effects. A mechanistic investigation showed that LIMA1 inhibited the Wnt/β-catenin signalling pathway by binding to BMI1 and inducing its destabilisation. Additionally, we found that LIMA1 expression in HCC cells could be suppressed by transferring CAF-derived exosomes harbouring oncogenic miR-20a-5p. In summary, LIMA1 is a tumour suppressor that inhibits the Wnt/β-catenin signalling pathway and is downregulated by CAF-derived exosomes carrying oncogenic miR-20a-5p in HCC.

Short-term prognosis for hepatocellular carcinoma patients with lung metastasis: A retrospective cohort study based on the SEER database

Our study aimed to develop a prediction model to predict the short-term mortality of hepatocellular carcinoma (HCC) patients with lung metastasis. The retrospective data of HCC patients with lung metastasis was from the Surveillance, Epidemiology, and End Results registration database between 2010 and 2015. 1905 patients were randomly divided into training set (n = 1333) and validation set (n = 572). There were 1092 patients extracted from the Surveillance, Epidemiology, and End Results database 2015 to 2019 as the validation set. The variable importance was calculated to screen predictors. The constructed prediction models of logistic regression, random forest, broad learning system, deep neural network, support vector machine, and naïve Bayes were compared through the predictive performance. The mortality of HCC patients with lung metastasis was 51.65% within 1 month. The screened prognostic factors (age, N stage, T stage, tumor size, surgery, grade, radiation, and chemotherapy) and gender were used to construct prediction models. The area under curve (0.853 vs. 0.771) of random forest model was more optimized than that of logistic regression model in the training set. But, there were no significant differences in testing and validation sets between random forest and logistic regression models. The value of area under curve in the logistic regression model was significantly higher than that of the broad learning system model (0.763 vs. 0.745), support vector machine model (0.763 vs. 0.689) in the validation set, and higher than that of the naïve Bayes model (0.775 vs. 0.744) in the testing model. We further chose the logistic regression prediction model and built the prognostic nomogram. We have developed a prediction model for predicting short-term mortality with 9 easily acquired predictors of HCC patients with lung metastasis, which performed well in the internal and external validation. It could assist clinicians to adjust treatment strategies in time to improve the prognosis.

A Novel circRNA hsa_circRNA_002178 as a Diagnostic Marker in Hepatocellular Carcinoma Enhances Cell Proliferation, Invasion, and Tumor Growth by Stabilizing SRSF1 Expression

BACKGROUND

Previous research studies have shown that the elevation of circular RNA (circRNA), hsa_circRNA_002178, was associated with the poor prognosis of breast cancer and colorectal cancer, while its molecular mechanisms underlying the effects on hepatocellular carcinoma (HCC) are still elusive.

METHODS

The microarray dataset GSE97332 was obtained from the Gene Expression Omnibus (GEO) database and calculated by using the GEO2R tool to identify differentially expressed circRNAs. Differentially expressed hsa_circRNA_002178, in 7 HCC tissue samples and paracancerous tissues, as well as in HCC cell lines and normal hepatocytes, was checked by RT-qPCR. Cell proliferation, invasion, migration, and epithelial-to-mesenchymal transition (EMT)-related proteins were tested in hsa_circRNA_002178-overexpressed or hsa_circRNA_002178-knocked down HCC cells. Subsequently, we identified whether hsa_circRNA_002178 binds to serine- and arginine-rich splicing factor 1 (SRSF1) and then analyzed their function in regulating HCC cell behavior. The effect on HCC cell xenograft tumor growth was observed by the knockdown of hsa_circRNA_002178 in vivo.

RESULTS

GEO2R-based analysis displayed that hsa_circRNA_002178 was upregulated in HCC tissues. Overexpression or knockdown of hsa_circRNA_002178 encouraged or impeded HCC cell proliferation, migration, invasion, and EMT program. Mechanically, hsa_circRNA_002178 bound to SRSF1 3'-untranslated region (UTR) and stabilized its expression. SRSF1 weakening eliminated the effects of pcDNA-hsa_circRNA_002178 on cell malignant behavior. Finally, the knockdown of hsa_circRNA_002178 was confirmed to prevent xenograft tumor growth.

CONCLUSIONS

hsa_circRNA_002178 overexpression encouraged the stability of SRSF1 mRNA expression, and it may serve as an upstream factor of SRSF1 for the diagnosis of HCC.

Oral metastasis as the first indication of undiscovered malignancy at a distant site: A systematic review of 413 cases

This systematic review is the first to provide evidence regarding demographic, clinical, and imaging characteristics, as well as information related to survival, of patients with oral and maxillofacial metastases of occult primary tumors. Case reports, case series, and cross-sectional studies were included. Ten databases were searched. The risk of bias was assessed using the Joanna Briggs Institute appraisal tools. Overall, 353 articles (413 patients) were included. Statistically significant associations between survival and multiplicity of metastatic foci, and between each of the main primary sites and some features of the oral lesions were observed. Some clinical and imaging characteristics can help dentists in raising diagnostic suspicions and also in relating to plausible primary sites. Early diagnosis of oral and maxillofacial metastases can positively affect the survival rate when they are the only focus of dissemination, conferring an important role on the dentist.

Gingival metastasis from primary hepatocellular carcinoma: a case report

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide; however, cases with metastasis to the oral cavity are extremely rare. Herein, we report a 68-year-old man who was diagnosed with HCC. Ten months after surgical removal of the right half of his liver, the patient developed gingival metastasis. Unfortunately, the patient died 4 months after the diagnosis. We discuss treatment options, pathological results, and disease prognosis. When a mandibular gingival mass is found, metastatic tumors should be considered in the differential diagnosis. In this regard, the patient’s medical history and physical examination are valuable indicators for the diagnosis of mandibular gingival metastasis. This case provides a basis for the clinical diagnosis of metastatic HCC involving the oral cavity.

PA2G4 promotes the metastasis of hepatocellular carcinoma by stabilizing FYN mRNA in a YTHDF2-dependent manner

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with high mortality. Advanced stage upon diagnosis and cancer metastasis are the main reasons for the dismal prognosis of HCC in large part. The role of proliferation associated protein 2G4 (PA2G4) in tumorigenesis and cancer progression has been widely investigated in various cancers. However, whether and how PA2G4 participates in HCC metastasis is still underexplored.

RESULTS

We found that the mRNA and protein levels of PA2G4 were higher in HCC samples than in normal liver tissues, and high expression of PA2G4 in HCC was correlated with a poor prognosis, by an integrative analysis of immunohistochemistry (IHC), western blot and bioinformatic approach. Moreover, the expression of PA2G4 was elevated in HCC patients with metastases than those metastasis-free. Cell migration, invasion, phalloidin staining and western blot analyses demonstrated that PA2G4 promoted epithelial to mesenchymal transition (EMT) of HCC cells in vitro. And a lung metastasis animal model exhibited that PA2G4 enhanced metastatic ability of HCC cells in vivo. RNA-sequencing combined with dual luciferase reporter assay and evaluation of mRNA half-time indicated that PA2G4 increased FYN expression by stabilizing its mRNA transcript. Recovering the impaired FYN level induced by PA2G4 knockdown rescued the impeded cell mobilities. Furthermore, endogenous immunoprecipitation (IP) and in-situ immunofluorescence (IF) showed that YTH N6-methyladenosine RNA binding protein 2 (YTHDF2) was the endogenous binding patterner of PA2G4. In addition, RNA binding protein immunoprecipitation (RIP) and anti- N6-methyladenosine immunoprecipitation (MeRIP) assays demonstrated that FYN mRNA was N6-methyladenosine (m6A) modified and bound with PA2G4, as well as YTHDF2. Moreover, the m6A catalytic ability of YTHDF2 was found indispensable for the regulation of FYN by PA2G4. At last, the correlation of expression levels between PA2G4 and FYN in HCC tissues was verified by IHC and western blot analysis.

CONCLUSIONS

These results indicate that PA2G4 plays a pro-metastatic role by increasing FYN expression through binding with YTHDF2 in HCC. PA2G4 may become a reliable prognostic marker or therapeutic target for HCC patients.

Conventional Therapies Do Not Prolong the Prognosis of Hepatocellular Carcinoma Patients with Extrahepatic Metastases under Receiving of Tyrosine Kinase Inhibitors

Simple Summary

Tyrosine kinase inhibitors (TKIs), including sorafenib and lenvatinib, have been the current standard treatment for advanced hepatocellular carcinoma (HCC) in cases where an immune checkpoint inhibitor cannot be used. The SHARP study showed that sorafenib tended to be less effective for extrahepatic metastases than for vascular invasion. Moreover, lenvatinib showed a response similar to that of sorafenib in such patients. The aforementioned data suggested that the addition of conventional therapies, including chemoembolization and radiation therapy, may improve the prognosis of such patients. Our retrospective study found that TKI promoted a longer overall survival in patients with extrahepatic metastases compared to conventional therapies. TKI plus conventional therapies did not promote a better prognosis compared to TKI alone. Thus, conventional therapies can be an option when events that worsen the quality of life occur in HCC patients with extrahepatic metastases.

Abstract

Background: Conventional therapies, including chemoembolization and radiation therapy, have been expected to prolong the prognosis of hepatocellular carcinoma (HCC) patients with extrahepatic metastases, which remains poor. However, little information is available on the efficacy of conventional therapies for such patients under tyrosine kinase inhibitor (TKI) treatment. Methods: We retrospectively investigated 127 HCC patients with extrahepatic metastases, who were divided into the non-TKI (conventional therapies) and TKI groups and further subdivided into the TKI alone and TKI plus conventional therapies groups. Conventional therapies included transcatheter arterial chemoembolization, cisplatin-based chemotherapy, radiation, surgery, and UFT, an oral chemotherapeutic agent. Results: The median of the overall survival (OS) of the 127 patients with extrahepatic metastases was 7.0 months. Meanwhile, the median OS of the TKI and non-TKI groups was 12.1 and 4.1 months, respectively. Imitating TKI after diagnosing metastases promoted a favorable increase in OS. Among the TKI group, the median OS in the TKI alone group was 8.9 months. TKI plus conventional therapies promoted no improvement in OS after adjusting for the patients’ background data. Conclusion: TKI promoted a better OS in HCC patients with extrahepatic metastases compared to conventional therapies. However, TKI plus conventional therapies promoted no improvement in the prognosis of such patients.

Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics

Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of 10%. The occurrence of metastasis, among other hallmarks, is the main contributor to its poor prognosis. Consequently, the elucidation of metastatic genes involved in the aggressive nature of the disease and its poor prognosis will result in the development of new treatment modalities for improved management of PC. There is a deep interest in understanding underlying disease pathology, identifying key prognostic genes, and genes associated with metastasis. Computational approaches, which have become increasingly relevant over the last decade, are commonly used to explore such interests. This review aims to address global studies that have employed global approaches to identify prognostic and metastatic genes, while highlighting their methods and limitations. A panel of 48 prognostic genes were identified across these studies, but only five, including ANLN, ARNTL2, PLAU, TOP2A, and VCAN, were validated in multiple studies and associated with metastasis. Their association with metastasis has been further explored here, and the implications of these genes in the metastatic cascade have been interpreted.