Frequency and clinicopathological features of metastasis to liver, lung, bone, and brain from gastric cancer: A SEER-based study

A Nomogram Based on Clinicopathological Characteristics for Estimating the Risk of Brain Metastasis from Advanced Gastric Cancer: A Multi-Center Retrospective Clinical Study

Purpose

Although brain metastasis (BM) from gastric cancer (GC) is relatively uncommon, its incidence has been increasing owing to advancements in treatment modalities. Unfortunately, patients diagnosed with BM from gastric cancer have poor life expectancy. Our study aims to establish a predictive model for brain metastasis in advanced gastric cancer patients, thus enabling the timely diagnosis of brain metastasis.

Patients and Methods

The clinicopathological features of a cohort which included 40 GC patients with brain metastasis, 32 of whom from the First Affiliated Hospital of Nanchang University, 2 from Gaoxin Branch of the First Affiliated Hospital of Nanchang University, remaining 6 from Anyang District Hospital, and 80 non-metastatic advanced GC patients from the First Affiliated Hospital of Nanchang University between 2018 and 2022. Data were retrospectively analyzed.

Results

Age, tumor size, differentiation, lymph node grade, tumor location, Lauren classification, liver metastasis, carbohydrate antigen 199 (CA199), lactate dehydrogenase (LDH), and human epidermal growth factor receptor 2 (Her-2) were associated with BM. A nomogram integrated with nine risk factors (tumor size, differentiation, lymph node grade, tumor location, Lauren classification, liver metastasis, CA-199, LDH, and Her-2) showed good performance (Area Under Curve 0.95, 95% CI: 0.91-0.98).

Conclusion

We developed and validated a nomogram that achieved individualized prediction of the possibility of BM from GC. This model enables personalized imaging review schedules for timely brain metastasis detection in advanced gastric cancer patients.

A novel nomogram and prognostic factor for metastatic soft tissue sarcoma survival

Background

This study represented the inaugural effort to develop predictive survival nomograms for metastatic soft tissue sarcoma (mSTS) patients in the era of immune checkpoint inhibitors.

Method

From the Surveillance, Epidemiology, and End Results (SEER) program database, we extracted 3078 eligible patients with mSTS between 2016 and 2022. Kaplan-Meier survival analysis, univariate and multivariable Cox analyses, and univariate and multivariable logistic analyses were conducted. Subsequently, predictive nomograms were constructed. Clinical effectiveness was validated using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA) methods.

Results

We used the SEER database to include 3078 eligible patients with mSTS between 2016 and 2022. All the eligible patients were randomly allocated in a ratio of 6:4 and stratified into a training group (n = 1846) and a validation group (n = 1232). In the multivariate Cox analysis, age, race, marital status, pathological grade, histologic subtype, surgery, and chemotherapy were identified as independent prognostic factors. These factors were used to construct the nomogram to predict the 1-, 3-, and 5-year OS of mSTS patients. The C-index for the training cohort and the validation cohort was 0.722(95% confidence interval [CI]: 0.708-0.736), and 0.716(95% CI: 0.698-0.734), respectively. The calibration curves for 1-, 3-, and 5-year OS probability demonstrated excellent calibration between the predicted and the actual survival. The AUC values of the nomogram at 1-, 3-, and 5-year were 0.785, 0.767, and 0.757 in the training cohort, 0.773, 0.754, and 0.751 in the validation cohort, respectively. Furthermore, DCA indicated the favorable clinical utility of the nomogram in both cohorts. The risk stratification system was constructed using the established nomogram, which enhanced prediction accuracy, aided clinicians in identifying high-risk patients and informing treatment decisions.

Conclusion

This study marked the inaugural effort in constructing predictive survival nomograms mSTS patients in the era of immune checkpoint inhibitors. The robustly constructed nomograms, alongside actual outcomes, offered valuable insights to inform follow-up management strategies.

Establishment and evaluation of a prognostic model for patients with unresectable gastric cancer 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.

AIM

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.

CONCLUSION

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.

Metastasis patterns and prognosis in young gastric cancer patients: A propensity score‑matched SEER database analysis

BACKGROUND

Whether young patients with metastatic gastric cancer (GC) had distinct metastasis patterns and survival outcomes from older patients remains controversial. The aim of the present study was to explore the metastasis patterns and prognostic factors in young patients and evaluate the survival outcome in comparison to their older counterparts.

MATERIALS AND METHODS

We identified patients with metastatic GC in the surveillance, epidemiology, and end results (SEER) database from 2010 to 2015. The patients were divided into two groups based on age at diagnosis: younger (≤40 years old) and older (>40 years old). We employed the chi-squared test to compare the clinicopathological characteristics between the two age groups. Furthermore, we conducted survival analyses using Kaplan-Meier and Cox regression analyses. To balance disparities in baseline characteristics, we employed propensity score matching (PSM).

RESULTS

We identified 5,580 metastatic GC patients from the SEER database, with 237 (4.2%) classified as younger and 5343 (95.8%) as older patients. A total of 237 pairs of patients were generated after adjustment by PSM. Patients in the younger group exhibited a higher proportion of bone-only metastases and a lower proportion of liver-only metastases compared with patients in the older group. Multivariate Cox regression analysis demonstrated that youth was an independent protective factor for overall survival (OS) before and after PSM, but not for gastric cancer-specific survival (GCSS). Among the younger group, patients with liver-only metastasis demonstrated the best prognosis, whereas patients with lung-only metastasis exhibited significantly worse survival outcomes compared with liver-only metastases, even comparable to that of bone metastasis.

CONCLUSIONS

Compared with the older group, the metastatic GC patients in the younger group exhibited more aggressive tumors but better prognoses. The metastasis pattern and its effect on the prognosis of GC varied by age group.

Gastric cancer with brain metastasis: from molecular characteristics and treatment

Gastric cancer is one of the cancers with increasing incidence and ranks fourth globally among the most frequent causes of cancer-related mortality. Early gastric cancer is often asymptomatic or presents with atypical symptoms, and the majority of patients present with advanced disease upon diagnosis. Brain metastases are present in approximately 1% of gastric cancer patients at the time of diagnosis, which significantly contributed to the overall mortality of the disease worldwide. Conventional therapies for patients with brain metastases remain limited and the median overall survival of patients is only 8 months in advanced cases. Recent studies have improved our understanding of the molecular mechanisms underlying gastric cancer brain metastases, and immunotherapy has become an important treatment option in combination with radiotherapy, chemotherapy, targeted therapy and surgery. This review aims to provide insight into the cellular processes involved in gastric cancer brain metastases, discuss diagnostic approaches, evaluate the integration of immune checkpoint inhibitors into treatment and prognosis, and explore the predictive value of biomarkers in immunotherapy.

The relationship between brain metastasis and HER2 expression status in gastric cancer

BACKGROUND

Brain metastasis (BM) in gastric cancer (GC) is underestimated, and human epidermal growth factor receptor 2 (HER2) overexpression is a durable poor prognostic factor. We explored the relationship between the two and made a survival analysis.

METHODS

HER2 expression and BM status were collected from GC patients who were diagnosed between December 2009 and May 2021. We collected GC patients diagnosed between 2010 and 2016 from the SEER database. The primary endpoint was survival from the diagnosis of BM. Multivariable logistic regression was used to determine potential risk factors of BM at diagnosis in SEER database. Survival analysis was performed using the Kaplan-Meier method.

RESULT

There were 513 HER2-positive GC patients, including 16 (3.1%) with BM. Among 38 brain metastasis GC patients we collected, 16 (42.1%) patients were HER2 positive. We collected 34,199 GC patients from the SEER database and there were 260 (0.76%) patients with BM at diagnosis. GC patients that are male, white, of younger age, with primary lesions located in the proximal stomach or with distant lymph nodes, liver, bone, or lung metastasis are more likely to develop BM. The median overall survival time from diagnosis of BM was 12.73 months, and the survival time from brain metastasis of HER2-positive patients was numerically shorter, though the difference was not significant (5.30 months vs.16.13 months, P = 0.28.) CONCLUSION: The incidence of BM in patients with HER2-positive gastric cancer is 4.08 times higher than that in general patients. The median overall survival time from BM is shorter for HER2-positive patients.

Bone metastasis is a late-onset and unfavorable event in survivors of gastric cancer after radical gastrectomy: Results from a clinical observational cohort

Background

The timing and incidence of recurrent bone metastasis (BM) after radical gastrectomy in patients with gastric cancer (GC) as well as the survival of these patients were not fully understood. The aim of this study was to analyze the data of an observational GC cohort and identify patients who underwent curative gastrectomy and had recurrent BM to describe and clarify the pattern and profile of BM evolution after surgery.

Methods

Data were retrieved from a hospital-based GC cohort, and patients who underwent upfront radical gastrectomy were selected. The time points of specific organ metastatic events were recorded, and the person-year incidence rate of metastatic events was calculated. The latency period of BM events after gastrectomy was measured and compared with that of the other two most common metastatic events, liver metastasis (LM) and distant lymph node metastasis (LNM), using analysis of variance. Propensity score matching and subgroup analysis were used for sensitivity analysis.

Results

A total of 1324 GC cases underwent radical gastrectomy between January 2011 and December 2021. Of these, 67 BM, 218 LM, and 248 LNM occurred before the last follow-up. The incidence of BM events was 1.7/100 person-years, which was approximately 3-fold lower than that of LM and distant LNM events (5.5 and 6.3 per 100 person-years, respectively). BM events had a significantly longer latency (median time, 16.5 months) than LM and LNM events (11.1 and 12.0 months, respectively). Recurrent BM led to a worse prognosis (median survival, 4.5 months) than those of LM and LNM events (median survival, 7.7 and 7.1 months, respectively). However, no difference in overall survival after gastrectomy was observed among the groups.

Conclusions

Compared with other common metastatic events, BM in GC after gastrectomy is a late-onset event indicating poor survival.

Trial registration

No. ChiCTR1800019978; http://www.chictr.org.cn/.

Prognostic Impact of Visceral Pleural Invasion in Resected Solitary Lung Metastases from Gastric Cancer

PURPOSE

Pulmonary resection of metastases from gastric cancer is extremely rare because gastric cancer metastasis to the lungs or thoracic cavity occurs as multiple pulmonary metastases, carcinomatous lymphangitis, or carcinomatous pleurisy. Therefore, the significance of surgery for pulmonary metastasis of gastric cancer remains unclear. This study aimed to investigate the surgical outcomes and prognostic factors for survival after the resection of pulmonary metastases from gastric cancer.

METHODS

From 2007 to 2019, 13 patients with pulmonary metastasis of gastric cancer underwent metastasectomy. Surgical outcomes were analyzed to determine the prognostic factors for recurrence and overall survival (OS).

RESULTS

All the patients underwent pulmonary resection for solitary metastases. At the median follow-up time of 45.6 months (range, 4.8-106.8 months), five patients experienced a recurrence of gastric cancer after metastasectomy. The 5-year recurrence-free survival rate was 44.4%, and the 5-year OS rate after pulmonary resection was 45.3%. Univariate analysis revealed that visceral pleural invasion (VPI) was an unfavorable prognostic factor for both recurrence-free and OS.

CONCLUSION

Pulmonary resection of solitary metastases from gastric cancer may be an effective therapeutic option to improve survival. VPI in gastric cancer metastasis is a negative prognostic factor.

Analysis of Related Risk Factors and Prognostic Factors of Gastric Cancer with Liver Metastasis: A SEER and External Validation Based Study

Background

Gastric cancer (GC) has a poor prognosis, particularly in patients with liver metastasis (LM). This study aims to identify relevant factors associated with the occurrence of LM in GC patients and factors influencing the prognosis of gastric cancer with liver metastasis (GCLM) patients, in addition to developing diagnostic and prognostic nomograms specifically.

Patients and Methods

Overall, 6184 training data were from the Surveillance, Epidemiology, and End Results (SEER) database from 2011 to 2015. 1527 validation data were from our hospital between January 2018 and December 2022. Logistic regression was used to identify the risk factors associated with the occurrence of LM in GC patients, Cox regression was used to confirm the prognostic factors of GCLM patients. Two nomogram models were established to predict the risk and overall survival (OS) of patients with GCLM. The performance of the two models was evaluated using the area under the curve (AUC), concordance index (C-index), and calibration curves.

Results

A nomogram included five independent factors from multivariate logistic regression: sex, lymph node removal, chemotherapy, T stage and N stage were constructed to calculate the possibility of LM. Internal and external verifications of AUC were 0.786 and 0.885, respectively. The other nomogram included four independent factors from multivariate Cox regression: surgery at primary site, surgery at other site, chemotherapy, and N stage were constructed to predict OS. C-index for internal and external validations were 0.714 and 0.702, respectively, and the calibration curves demonstrated the robust discriminative ability of the models.

Conclusion

Based on the SEER database and validation data, we defined effective nomogram models to predict risk and OS in patients with GCLM. They have important value in clinical decision-making and personalized treatment.

Analysis of risk factors and prognostic factors of brain metastasis in gastric cancer: a surveillance, epidemiology and end-results database study

Brain metastasis in gastric cancer (GC) patients is a rare phenomenon that is associated with adverse clinical outcomes and poor survival rates. We conducted a retrospective cohort study to investigate the incidence, risk factors and prognostic factors of brain metastasis in GC patients. Data on sociodemographic and tumor characteristics of GC patients from 2010 to 2019 was extracted from the Surveillance, Epidemiology and End-Results (SEER) database. Descriptive statistics, multivariable logistic and Cox regression were applied on SPSS. Kaplan-Meier-Survival curves and ROC curves were constructed. A total of 59,231 GC patients, aged 66.65 ± 13.410 years were included. Brain metastasis was reported in 368 (0.62%) patients. On logistic regression, the risk of brain metastasis was significantly greater in males, patients aged < 60 years and patients having concurrent bone and lung metastasis. High grade and high N stage were significant risk factors for development of brain metastasis. Patients who had undergone surgery for the primary tumor were at reduced risk for brain metastasis (adjusted odds ratio 0.210, 95% CI 0.131-0.337). The median OS was 3 months in patients with brain metastasis and 17 months in patients without brain metastasis (p < 0.05). On Cox regression, Grade IV tumors and primary antral tumors were significant predictable parameters for poor prognosis. Overall Survival (OS) and Cancer-Specific Survival (CSS) were prolonged in patients who had undergone surgery. Brain metastasis in gastric cancer is associated with significantly worse survival. Employing large-scale screening for high-risk patients holds a promising impact to improve survival rates, but it must be accurately balanced with a comprehensive understanding of clinicopathological aspects for accurate diagnosis and treatment.

Incidence, clinicopathological characteristics, and therapeutic strategy for gastric cancer patients with metastasis to the central nervous system

AIM

This study aimed to analyze the clinicopathologic features and treatment outcomes of central nervous system (CNS) metastasis from gastric cancer.

METHODS

A total of 419 patients diagnosed with unresectable advanced or recurrent gastric cancer at Kochi Medical School between January 2007 and December 2021 were evaluated. Data of patients were reviewed, and clinicopathological information and survival outcomes of those with CNS metastases were compared to patients without CNS metastases.

RESULTS

In total, 12/419 (2.9%) patients (median age: 66.5 years [range, 41-82 years]) were diagnosed with CNS metastasis from gastric cancer. Eleven had diffuse-type gastric cancer which was significantly more common than in those without CNS metastasis (91% vs. 61%, p = .034). Human epidermal growth factor receptor 2 status was positive in one of the 12 patients. The median survival time was significantly lower for patients with CNS metastasis than for those without CNS metastasis (1.8 months vs. 11.4 months, p < .001). The median survival time for patients who underwent surgical resection, radiation, or chemotherapy for CNS metastasis was significantly higher than those who received only best supportive care (3.5 months vs. .6 months; p = .007).

CONCLUSIONS

CNS metastasis was found in 2.9% (12/419) of patients with unresectable advanced or recurrent gastric cancer. Diffuse-type histology was a risk factor for CNS metastasis. Multidisciplinary treatment, including surgical resection, radiation treatment, or chemotherapy, for CNS metastasis from gastric cancer may benefit selected patients.

Rectal metastasis of gastric cancer: a case report

The most common metastatic sites of gastric cancer include the liver, peritoneum, lung, and bone. However, there is a lack of relevant clinical reports regarding rectal metastasis. Herein, we report the rare case of a patient with gastric cancer who developed rectal metastasis. A 57-year-old male patient was diagnosed with gastric cancer and underwent a radical gastrectomy in January 2016, followed by eight cycles of adjuvant chemotherapy. The patient subsequently developed a rectal mass in March 2021. He was diagnosed with rectal adenocarcinoma and underwent surgical resection of the rectal tumor. A mass was then found in the abdominal wall in September 2021 and was resected. Specimens obtained from the three surgeries were reviewed, and the rectal tumor and the mass in the abdominal wall were both found to be metastatic tumors from the gastric cancer. Metastasis of gastric cancer to the rectum is rare, but it is important to differentiate between rectal metastasis and primary rectal cancer to help avoid unnecessary treatment.

Prediction model of liver metastasis risk in patients with gastric cancer: A population-based study

Liver was the most common site of distant metastasis in patients with gastric cancer (GC). The prediction model of the risk of liver metastasis was rarely proposed. Therefore, we aimed to establish a prediction model for liver metastasis in patients with GC. In this retrospective cohort study, we extracted demographic and clinical data of all the GC patients from the Surveillance, Epidemiology, and End Results registration database from 2010 to 2015. Patients were divided into training set (n = 1691) for model development and testing set (n = 3943) for validation. Univariable and multivariable logistic regression analyses were carried out on the training set to screen potential predictors of liver metastasis and constructed a prediction model. The receiver operator characteristics curves with the area under curve values were used to assess the predictive performance of the liver metastasis prediction model. And a nomogram of the prediction model was also constructed. Of the total 5634 GC patients, 444 (7.88%) had liver metastasis. Variables including age, gender, N stage, T stage, Lauren classification, tumor size, histological type, and surgery were included in the liver metastasis prediction model. The study results indicated that the model had excellent discriminative ability with an area under curve of 0.851 (95% confidence interval: 0.829-0.873) in the training set, and that of 0.849 (95% confidence interval: 0.813-0.885) in the testing set. We have developed an effective prediction model with 8 easily acquired predictors of liver metastasis. The prediction model could predict the risk of liver metastasis in GC patients and performed well, which would assist clinicians to make individualized prediction of liver metastasis in GC patients and adjust treatment strategies in time to improve the prognosis.

Clinical association between coagulation indicators and bone metastasis in patients with gastric cancer

BACKGROUND

Bones are one of the most common target organs for cancer metastasis. Early evaluation of bone metastasis (BM) status is clinically significant. Cancer patients often experience a hypercoagulable state.

AIM

To evaluate the correlation between coagulation indicators and the burden of BM in gastric cancer (GC).

METHODS

We conducted a single-center retrospective study and enrolled 454 patients. Clinical information including routine blood examination and coagulation markers were collected before any treatment. Patients were grouped according to the status of BM. Receiver operating characteristic curves were used to assess diagnostic performance and determine the optimal cutoff values of the above indicators. Cutoff values, sensitivity and specificity were based on the maximum Youden index. Univariate and multivariate logistic regression analyses were used to evaluate the relationships between biomarkers and BM.

RESULTS

Of the 454 enrolled patients, 191 patients were diagnosed with BM. The receiver operating characteristic curve analysis suggested that prothrombin time (PT) [cutoff: 13.25; sensitivity: 0.651; specificity: 0.709; area under receiver operating characteristic curve (AUC) = 0.738], activated partial thromboplastin time (aPTT) (cutoff: 35.15; sensitivity: 0.640; specificity: 0.640; AUC = 0.678) and fibrin degradation products (FDP) (cutoff: 2.75; sensitivity: 0.668; specificity: 0.801; AUC = 0.768) act as novel predictors for BM. Based on multivariate logistic regression analysis, the results showed the independent correlation between PT [odds ratio (OR): 3.16; 95% confidence interval (CI): 1.612-6.194; P = 0.001], aPTT (OR: 2.234; 95%CI: 1.157-4.313; P = 0.017) and FDP (OR: 3.17; 95%CI: 1.637-6.139; P = 0.001) and BM in patients with GC. Moreover, age, carcinoembryonic antigen, erythrocyte and globulin were found to be significantly associated with BM.

CONCLUSION

Coagulation markers, namely PT, aPTT and FDP, might be potential predictors for screening BM in patients with GC.

Two web-based dynamic prediction models for the diagnosis and prognosis of gastric cancer with bone metastases: evidence from the SEER database

Purpose

Our aim was to identify the clinical characteristics and develop and validate diagnostic and prognostic web-based dynamic prediction models for gastric cancer (GC) with bone metastasis (BM) using the SEER database.

Method

Our study retrospectively analyzed and extracted the clinical data of patients aged 18-85 years who were diagnosed with gastric cancer between 2010 and 2015 in the SEER database. We randomly divided all patients into a training set and a validation set according to the ratio of 7 to 3. Independent factors were identified using logistic regression and Cox regression analyses. Furthermore, we developed and validated two web-based clinical prediction models. We evaluated the prediction models using the C-index, ROC, calibration curve, and DCA.

Result

A total of 23,156 patients with gastric cancer were included in this study, of whom 975 developed bone metastases. Age, site, grade, T stage, N stage, brain metastasis, liver metastasis, and lung metastasis were identified as independent risk factors for the development of BM in GC patients. T stage, surgery, and chemotherapy were identified as independent prognostic factors for GC with BM. The AUCs of the diagnostic nomogram were 0.79 and 0.81 in the training and test sets, respectively. The AUCs of the prognostic nomogram at 6, 9, and 12 months were 0.93, 0.86, 0.78, and 0.65, 0.69, 0.70 in the training and test sets, respectively. The calibration curve and DCA showed good performance of the nomogram.

Conclusions

We established two web-based dynamic prediction models in our study. It could be used to predict the risk score and overall survival time of developing bone metastasis in patients with gastric cancer. In addition, we also hope that these two web-based applications will help physicians comprehensively manage gastric cancer patients with bone metastases.

Assessment of experimental OpenCV tracking algorithms for ultrasound videos

This study aims to compare the tracking algorithms provided by the OpenCV library to use on ultrasound video. Despite the widespread application of this computer vision library, few works describe the attempts to use it to track the movement of liver tumors on ultrasound video. Movements of the neoplasms caused by the patient`s breath interfere with the positioning of the instruments during the process of biopsy and radio-frequency ablation. The main hypothesis of the experiment was that tracking neoplasms and correcting the position of the manipulator in case of using robotic-assisted surgery will allow positioning the instruments more precisely. Another goal of the experiment was to check if it is possible to ensure real-time tracking with at least 25 processed frames per second for standard definition video. OpenCV version 4.5.0 was used with 7 tracking algorithms from the extra modules package. They are: Boosting, CSRT, KCF, MedianFlow, MIL, MOSSE, TLD. More than 5600 frames of standard definition were processed during the experiment. Analysis of the results shows that two algorithms-CSRT and KCF-could solve the problem of tumor tracking. They lead the test with 70% and more of Intersection over Union and more than 85% successful searches. They could also be used in real-time processing with an average processing speed of up to frames per second in CSRT and 100 + frames per second for KCF. Tracking results reach the average deviation between centers of neoplasms to 2 mm and maximum deviation less than 5 mm. This experiment also shows that no frames made CSRT and KCF algorithms fail simultaneously. So, the hypothesis for future work is combining these algorithms to work together, with one of them-CSRT-as support for the KCF tracker on the rarely failed frames.

Distinct Differences in Gastroesophageal Junction and Gastric Adenocarcinoma in 2194 Patients: In Memory of Rebecca A. Carr, February 24, 1988-January 19, 2021

OBJECTIVE

We sought to compare gastroesophageal junction (GEJ) cancer and gastric cancer (GC) and identify clinicopathological and oncological differences.

SUMMARY BACKGROUND DATA

GEJ cancer and GC are frequently studied together. Although the treatment approach for each often differs, clinico-pathological and oncological differences between the 2 have not been fully evaluated.

METHODS

We retrospectively identified patients with GEJ cancer or GC who underwent R0 resection at our center between January 2000 and December 2016. Clinicopathological characteristics, disease-specific survival (DSS), and site of first recurrence were compared.

RESULTS

In total, 2194 patients were analyzed: 1060 (48.3%) with GEJ cancer and 1134 (51.7%) with GC. Patients with GEJ cancer were younger (64 vs 66 years; P < 0.001), more often received neoadjuvant treatment (70.9% vs 30.2%; P < 0.001), and had lower pathological T and N status. Five-year DSS was 62.2% in patients with GEJ cancer and 74.6% in patients with GC ( P < 0.001). After adjustment for clinicopathological factors, DSS remained worse in patients with GEJ cancer (hazard ratio, 1.78; 95% confidence interval, 1.40-2.26; P < 0.001). The cumulative incidence of recurrence was approximately 10% higher in patients with GEJ cancer ( P < 0.001). The site of first recurrence was more likely to be hematogenous in patients with GEJ cancer (60.1% vs 31.4%; P < 0.001) and peritoneal in patients with GC (52.9% vs 12.5%; P < 0.001).

CONCLUSIONS

GEJ adenocarcinoma is more aggressive, with a higher incidence of recurrence and worse DSS, compared with gastric adenocarcinoma. Distinct differences between GEJ cancer and GC, especially in patterns of recurrence, may affect evaluation of optimal treatment strategies.

Development and validation of prognostic nomogram for patients with metastatic gastric adenocarcinoma based on the SEER database

The aim of this study was to investigate the prognostic factors affecting overall survival in patients with metastatic gastric adenocarcinoma and to establish a nomogram prediction model for comprehensive clinical application. Data from 2370 patients with metastatic gastric adenocarcinoma between 2010 and 2017 were retrieved from the surveillance, epidemiology, and end results database. They were randomly divided into a training set (70%) and a validation set (30%), univariate and multivariate Cox proportional hazards regressions were used to screen important variables that may affect overall survival and to establish the nomogram. The nomogram model was evaluated using a receiver operating characteristic curve, calibration plot, and decision curve analysis. Internal validation was performed to test the accuracy and validity of the nomogram. Univariate and multivariate Cox regression analyses revealed that, age, primary site, grade, and American joint committee on cancer. T, bone metastasis, liver metastasis, lung metastasis, tumor Size, and chemotherapy were identified as independent prognostic factors for overall survival and were included in the prognostic model to construct a nomogram. The prognostic nomogram showed good overall survival risk stratification ability for the area under the curve, calibration plots, and decision curve analysis in both the training and validation sets. Kaplan-Meier curves further showed that patients in the low-risk group had better overall survival. This study synthesizes the clinical, pathological, therapeutic characteristics of patients with metastatic gastric adenocarcinoma, establishes a clinically effective prognostic model, and that can help clinicians to better evaluate the patient's condition and provide accurate treatment.

Zoledronic acid-associated osteonecro sis of the jaw in patients with EGFR-sensitive mutant lung cancer: two case reports

Bone metastasis from lung cancer predicts a decrease in the quality of life and a shortening of survival for patients. While controlling the primary disease, active prevention and treatment of skeletal-related events (SREs) are crucial. The use of bisphosphonates as a basic drug for bone metastases from lung cancer has been increasing; also, the corresponding adverse effects have emerged. The case is here reported of two cases of osteonecrosis of the jaw associated with zoledronic acid treatment were reported in patients with epidermal growth factor receptor -sensitive mutation non-small-cell lung cancer(NSCLC) and discussed the clinical features, early recognition and interventions.

Dynamic Nomogram for Predicting Long-Term Survival in Terms of Preoperative and Postoperative Radiotherapy Benefits for Advanced Gastric Cancer

Studies on the prognostic significance of preoperative radiotherapy (PERT) and postoperative radiotherapy (PORT) in patients with advanced gastric cancer (GC) remain elusive. The aim of the study was to evaluate the survival advantage of preoperative and postoperative radiotherapy and construct a dynamic nomogram model to provide customized prediction of the probability of prognostic events for advanced GC patients. We collected clinical records from 2010 to 2015 from the Surveillance, Epidemiology, and End Results (SEER) database with a specific target for stage II-IV GC patients treated with PERT or PORT. We used the least absolute shrinkage and selection operator (LASSO) regression model to identify factors that contribute to the overall survival (OS) of GC patients. The dynamic nomogram infographic was constructed based on the prognostic factors of tumor-specific survival. Out of the 3215 total patients (2271 [70.6%] male; median age, 61 [SD = 12] years), 1204 were in the PERT group and 2011 in the PORT group. Receiving PORT was associated with a survival advantage over PERT for stage II GC patients (HR = 0.791, 95% CI= 0.712-0.879, p < 0.001). The 1-, 3-, and 5-year OS rates were 89.9%, 63.8%, and 53.8% in the PORT group, whereas the corresponding rates were significantly lower in the PERT group (86.4%, 57.1%, and 44.3%, respectively, all p < 0.05). The survival prediction model demonstrated that patients aged > 65 years, with an advanced cancer development stage and tumor size >3 were independent risk factors for poor prognosis (all HR > 1, p < 0.05). In this study, a dynamic nomogram was established based on the LASSO model to provide a statistical basis for the clinical characteristics and predictive factors of advanced GC in a large population. PORT demonstrated significantly better treatment advantages than PERT for stage II GC patients.

Homogeneous Adaboost Ensemble Machine Learning Algorithms with Reduced Entropy on Balanced Data

Today's world faces a serious public health problem with cancer. One type of cancer that begins in the breast and spreads to other body areas is breast cancer (BC). Breast cancer is one of the most prevalent cancers that claim the lives of women. It is also becoming clearer that most cases of breast cancer are already advanced when they are brought to the doctor's attention by the patient. The patient may have the evident lesion removed, but the seeds have reached an advanced stage of development or the body's ability to resist them has weakened considerably, rendering them ineffective. Although it is still much more common in more developed nations, it is also quickly spreading to less developed countries. The motivation behind this study is to use an ensemble method for the prediction of BC, as an ensemble model aims to automatically manage the strengths and weaknesses of each of its separate models, resulting in the best decision being made overall. The main objective of this paper is to predict and classify breast cancer using Adaboost ensemble techniques. The weighted entropy is computed for the target column. Taking each attribute's weights results in the weighted entropy. Each class's likelihood is represented by the weights. The amount of information gained increases with a decrease in entropy. Both individual and homogeneous ensemble classifiers, created by mixing Adaboost with different single classifiers, have been used in this work. In order to deal with the class imbalance issue as well as noise, the synthetic minority over-sampling technique (SMOTE) was used as part of the data mining pre-processing. The suggested approach uses a decision tree (DT) and naive Bayes (NB), with Adaboost ensemble techniques. The experimental findings shown 97.95% accuracy for prediction using the Adaboost-random forest classifier.

A novel nomogram and prognostic factor for metastatic renal cell carcinoma survival in the era of immune checkpoint inhibitors (ICIs)

Patients with metastatic renal cell cancer (mRCC) for whom surgery is ineffective may experience a poor prognosis. The different sites where cancer has spread, and the different ways to treat it in the immune checkpoint inhibitors era could help clinical decision-making. In this study, individuals with mRCC were selected from the SEER database between 2015 and 2016 based on the Food and Drug Administration (FDA) approval of ICIs. A total of 4011 mRCC patients were studied (2239 with lung metastasis vs. 797 with liver metastasis in the immune checkpoint inhibitors period). The age ≤ 64 years and male were the majority in all cases of mRCC. When the two groups (lung metastasis and liver metastasis) were compared, the liver metastasis group had more bone metastasis than the lung metastasis group (41.8% vs. 34.1%, p < 0.001), but the lung metastasis group had more brain metastasis (8.9% vs. 11.5%) (p = 0.023). In a study of overall survival (OS) in the ICI era for mRCC, we found that lung metastasis was significantly associated with improved survival compared to liver metastasis (p < 0.001: 7 months vs. 4 months). This survival advantage restricted in lung metastasis group of mRCC after adjusting age, sex, race, marital status, histological type, metastasis to bone, and brain, origin, radiotherapy record chemotherapy record, surgery on multivariable using Cox proportional hazard model (HR = 1.407; 95% CI = 1. 269-1.560; p < 0.001). The overall survival difference between the variables of the lung metastasis and liver metastasis was noted among most of the variables, with survival benefits restricted to patients in lung metastasis in the ICI era. Patients who had undergone chemotherapy and surgery were strongly positive predictors for better OS (HR = 0.427; 95% CI = 0.379-0.481; p < 0.001) (HR = 0.371; 95% CI = 0.311-0.444; p=< 0.001), and (HR = 0.313; 95% CI = 0.264-0.372; p < 0.001), (HR = 0.427; 95% CI = 0.320-0.568; p < 0.001) in lung metastasis group and liver metastasis group. The c-index of the prognostic nomogram for OS prediction was 0.74 and 0.73. This study found that patients with lung metastasis who received ICI had better survival than those with liver metastasis. Chemotherapy and surgery enhanced survival in kidney cancer patients, whereas radiation had little impact. We developed a complete and realistic nomogram for mRCC patients based on distant metastases to the lung and liver.

Safety and Efficacy of Simultaneous Resection of Gastric Carcinoma and Synchronous Liver Metastasis-A Western Center Experience

Background and objectives: Gastric cancer (GC) is often diagnosed in the metastatic stage. Palliative systemic therapy is still considered the gold standard, even for patients with resectable oligometastatic disease. The aim of the current study is to assess the potential benefit of up-front gastric and liver resection in patients with synchronous resectable liver-only metastases from GC (LMGC) in a Western population. Materials and Methods: All patients with GC and synchronous LMGC who underwent gastric resection with or without simultaneous resection of LMs between January 1997 and December 2016 were selected from the institutional records. Those with T4b primary tumors or with unresectable or more than three LMs were excluded from the analysis. All patients who underwent emergency surgery for hemorrhagic shock or gastric perforation were also excluded. Results: Out of 28 patients fulfilling the inclusion criteria, 16 underwent simultaneous gastric and liver resection (SR group), while 12 underwent palliative gastric resection (GR group). The median overall survival (OS) of the entire cohort was of 18.81 months, with 1-, 3- and 5-year OS rates of 71.4%, 17.9% and 14.3%, respectively. The 1-, 3- and 5-year OS rates in SR group (75%, 31.3% and 25%, respectively) were significantly higher than those achieved in GR group (66.7%, 0% and 0%, respectively; p = 0.004). Multivariate analysis of the entire cohort revealed that the only independent prognostic factor associated with better OS was liver resection (HR = 3.954, 95% CI: 1.542-10.139; p = 0.004). Conclusions: In a Western cohort, simultaneous resection of GC and LMGC significantly improved OS compared to patients who underwent palliative gastric resection.

Clinicopathologic and genomic characterizations of brain metastases using a comprehensive genomic panel

Central nervous system (CNS) metastasis is the most common brain tumor type in adults. Compared to their primary tumors, these metastases undergo a variety of genetic changes to be able to survive and thrive in the complex tissue microenvironment of the brain. In clinical settings, the majority of traditional chemotherapies have shown limited efficacy against CNS metastases. However, the discovery of potential driver mutations, and the development of drugs specifically targeting affected signaling pathways, could change the treatment landscape of CNS metastasis. Genetic studies of brain tumors have so far focused mainly on common cancers in western populations. In this study, we performed Next Generation Sequencing (NGS) on 50 pairs of primary tumors, including but not limited to colorectal, breast, renal and thyroid tumors, along with their brain metastatic tumor tissue counterparts, from three different local tertiary centers in Saudi Arabia. We identified potentially clinically relevant mutations in brain metastases that were not detected in corresponding primary tumors, including mutations in the PI3K, CDK, and MAPK pathways. These data highlight the differences between primary cancers and brain metastases and the importance of acquiring and analyzing brain metastatic samples for further clinical management.

Molecular mechanism and potential therapeutic targets of liver metastasis from gastric cancer

Gastric cancer (GC) is characterized by high invasion and poor prognosis. The occurrence of liver metastasis seriously affects advanced GC prognosis. In recent years, great progress has been made in the field of GC liver metastasis. The abnormal expression of related genes leads to the occurrence of GC liver metastasis through metastasis cascades. The changes in the liver microenvironment provide a pre-metastasis condition for GC cells to colonize and grow. The development of several potential therapeutic targets might provide new therapeutic strategies for its treatment. Therefore, we reviewed the regulatory mechanism of abnormal genes mediating liver metastasis, the effect of liver resident cells on liver metastasis, and potential therapeutic targets, hoping to provide a novel therapeutic option to improve the quality of life and prognosis of GC patients with liver metastasis.

Tumor Microenvironment, Clinical Features, and Advances in Therapy for Bone Metastasis in Gastric Cancer

Gastric cancer (GC) is one of the most malignant neoplasms worldwide, accounting for about 770,000 deaths in 2020. The incidence of gastric cancer bone metastasis (GC-BM) is low, about 0.9–13.4%, and GC patients develop GC-BM because of a suitable bone microenvironment. Osteoblasts, osteoclasts, and tumor cells interact with each other, secreting cytokines such as PTHrP, RANK-L, IL-6, and other growth factors that disrupt the normal bone balance and promote tumor growth. The functions and numbers of immune cells in the bone microenvironment are continuously inhibited, resulting in bone balance disorder due to the cytokines released from destroyed bone and growing tumor cells. Patients with GC-BM are generally younger than 65 years old and they often present with a later stage of the disease, as well as more aggressive tumors. They usually have shorter overall survival (OS) because of the occurrence of skeletal-related events (SREs) and undetected bone destruction due to the untimely bone inspection. Current treatments of GC-BM focus mainly on gastric cancer and SRE-related treatment. This article reviews the clinical features, possible molecular pathogeneses, and the most commonly used diagnostic methods and treatments of bone metastasis in gastric cancer.

Prognostic characteristics and clinical response to immunotherapy targeting programmed cell death 1 for patients with advanced gastric cancer with liver metastases

Background

The specific efficacy of immunotherapy for patients with liver metastases of gastric cancer is unclear. This study set out to explore the treatment response and related prognostic factors for patients with liver metastases of gastric cancer treated with immunotherapy.

Patients and methods

This retrospective cohort study included 135 patients with unresectable advanced gastric cancer. According to the presence of liver metastases and/or first-line treatment with immunotherapy, patients were divided into the following three groups: I-LM(-) group(patients without liver metastases treated with immunotherapy, n=66), I-LM(+) group(patients with liver metastases treated with immunotherapy, n=36), C-LM(+) group(patients with liver metastases treated with chemotherapy and/or target therapy, n=33). Cox regression analyses were used to identify factors associated with survival in all patients and the three groups, respectively.

Results

For the patients with liver metastases treated with immunotherapy, multivariate analysis showed that only the presence of peritoneal metastases was significantly associated with shorter PFS [hazard ratios (HR), 3.23; 95% CI, 1.12-9.32; P=0.030] and the patients with peritoneal metastases had shorter median PFS than patients without peritoneal metastases(3.1 vs 18.4 months; P=0.004), while the objective response rate was 100% in patients with HER2-positive (2 complete radiographic responses and 2 partial responses; 3 of 4 patients were still ongoing benefits [median follow-up time, 15.3 months ; interquartile range(IQR), 6.3-17.9 months]).

Conclusions

The findings suggest that patients with various types of gastric cancer liver metastases respond differently to immune checkpoint inhibitors, HER2-positive patients may derive clinical benefits from immune checkpoint inhibitors, while the presence of peritoneal metastases is associated with resistance.

Incorporation of liver chemistry score in predicting survival of liver-involved advanced gastric cancer patients who received palliative chemotherapy

BACKGROUND

Gastric cancer liver metastasis (GCLM) patients usually accompany by abnormal serum liver function tests (LFTs) more or less; however, the prognostic value of LFTs is not fully understood. This study aimed to develop a liver chemistry score (LCS) based on LFTs and incorporate it into prognosis determination for GCLM patients who received palliative chemotherapy.

METHODS

Data were derived from hospitalized GCLM patients in two general hospitals in China. LCS was generated based on the results of LFTs by LASSO regression. Cutoff value of the score was determined by restricted cubic spline. The score was then incorporated into Cox regression analysis to construct a predictive nomogram; the model was then evaluated internally and externally by AUC of time-dependent receiver operating characteristic curves (ROC) and calibration curves.

RESULTS

Three hundred and thirty-six and 72 patients were included in development and validation cohort, respectively. LASSO regression analysis in development cohort finally reached a two-parametric LCS calculated on AST and ALP levels as 0.03343515 × ln (AST, U/L) + 0.02687997 × ln (ALP, U/L), and 0.232 was set as optimal cutoff value. Patients in low (LCS < 0.232) or high (LCS ≥ 0.232) score group experienced different survival times; median OS was 13.54 (95% CI: 11.1-15.6) months in the low LCS group and 7.3 (6.6-9.3) months in the high LCS group (p < 0.001). A nomogram including LCS and other clinical parameters was constructed and showed superior performance than model not including LCS. AUC of 6-month ROC improved from 0.647 (95% CI: 0.584-0.711) to 0.699 (0.638-0.759) in internal validation, and 0.837 (0.734-0.940) to 0.875 (0.784-0.966) in external validation.

CONCLUSIONS

Liver chemistry score is useful in determining the prognosis of gastric cancer patients with liver metastasis and may be helpful to clinicians in decision-making.

Peimine-induced apoptosis and inhibition of migration by regulating reactive oxygen species-mediated MAPK/STAT3/NF-κB and Wnt/β-catenin signaling pathways in gastric cancer MKN-45 cells

Peimine (PM), a natural product extracted from Fritillaria, has anti-inflammatory, drug resistance reversal, and other pharmacological effects. The purpose of this study was to investigate the antitumor effects and the molecular mechanisms of PM using gastric cancer MKN-45 cells. Cell counting kit-8 assays were used to evaluate the viability of gastric cancer cells after treatment with PM. The results showed that PM significantly reduced the activity of gastric cancer cells, and the effect was most obvious in MKN-45 cells. Annexin V-FITC/propidium iodide staining and flow cytometry were used to assess apoptosis of MKN-45 cells after PM treatment. Our results showed that PM-induced apoptosis of MKN-45 cells. Flow cytometry was also used to determine the mitochondrial membrane potential and reactive oxygen species (ROS) levels, and to assess PM-induced cell-cycle arrest. Additionally, Western blot was used to analyze the expression of signaling pathway proteins and the relationship between apoptosis and ROS accumulation. Our findings showed that PM destroyed the mitochondria by diminishing the mitochondrial membrane potential. In addition, PM regulated the mitogen-activated protein kinase (MAPK), signal transducer and activator of transcription 3, and nuclear factor kappa-B signaling pathways by promoting the accumulation of ROS in MKN-45 cells. PM also caused cell-cycle arrest in the G2/M phase by increasing ROS accumulation. Furthermore, PM inhibited cell migration by regulating the Wnt/β-catenin pathway. In conclusion, PM plays an anticancer role through endogenous apoptosis pathways and by inhibiting cell migration, and it has the potential to be a useful treatment for gastric cancers.

A predictive model for early death in elderly patients with gastric cancer: A population-based study

Background

The mean age of gastric cancer (GC) patients has increased due to the aging society. Elderly GC patients with poor physical status tend to develop complications during the treatment courses, which cause early death. This study aimed to identify risk factors and establish nomograms for predicting total early death and cancer-specific early death in elderly GC patients.

Methods

Data for elderly GC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. These patients were randomly assigned to a training cohort and a validation cohort. The univariate logistic regression model and backward stepwise logistic regression model were used to identify independent risk factors for early death. Nomograms were constructed to predict the overall risk of early death and their performance was validated by receiver operating characteristic (ROC) curve, calibration curve, decision curve analyses (DCA), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) in both training and validation cohorts.

Results

Among the 3102 enrolled patients, 1114 patients died within three months from the first diagnosis and 956 of them died due to cancer-specific causes. Non-Asian or Pacific Islander (API) race, non-cardia/fundus or lesser/greater curvature, higher AJCC stage, no surgery and no chemotherapy were all related to a high risk of both all-cause early death and cancer-specific early death. Higher T stage and N0 stage were only positively related to total early mortality, while liver metastasis was only positively related to cancer-specific early mortality. Based on these identified factors, two nomograms were developed for predicting the risk of all-cause and cancer-specific early death, which showed good performance with the AUC of the nomograms were 0.775 and 0.766, respectively. The calibration curves, DCAs, NRI, and IDI also confirmed the value of these nomograms.

Conclusions

These nomogram models were considered a practical tool to identify the early death of elderly GC patients and help provide a more individualized treatment strategy.

Prognostic microRNAs associated with phosphoserine aminotransferase 1 in gastric cancer as markers of bone metastasis

This study analyzed PSAT1-targeted miRNAs as a prognostic predictor for gastric cancer. The relationship between the clinical manifestations of gastric cancer in patients and phosphoserine aminotransferase 1 (PSAT1) was analyzed using correlation analysis. PSAT1 was highly expressed in gastric cancer, and its low expression was associated with a poor prognosis. By pan-cancer analysis, PSAT1 could affect the tumor immune microenvironment by immune infiltration analysis. Nine microRNAs targeting PSAT1 and associated with gastric cancer were screened by miRwalk and microRNA expression in TCGA tumor tissues. Six microRNAs were obtained by survival curve analysis, including hsa-miR-1-3p, hsa-miR-139-5p, hsa-miR-145-5p, hsa-miR-195-5p, hsa-miR-218-5p, and hsa-miR-497-5p. Based on the above six microRNAs, a model for bone metastasis prediction in gastric cancer prediction was constructed. An analysis of a decision curve was performed based on the microRNAs obtained to predict bone metastasis from gastric cancer. It had a positive area under the curve (AUC) value of 0.746, and the decision curve analysis (DCA) indicated that it was clinically significant. Dual-luciferase reporter genes indicated that hsa-miR-497-5p and PSAT1 were targeted, and qRT-PCR results confirmed that hsa-miR-497-5p could down-regulate PSAT1 expression. MicroRNAs targeting the regulation of PSAT1 expression can well predict the prognosis of gastric cancer.

Importance of tumor subtypes in cancer imaging

Cancer therapy has evolved from being broadly directed towards tumor types, to highly specific treatment protocols that target individual molecular subtypes of tumors. With the ever-increasing data on imaging characteristics of tumor subtypes and advancements in imaging techniques, it is now often possible for radiologists to differentiate tumor subtypes on imaging. Armed with this knowledge, radiologists may be able to provide specific information that can obviate the need for invasive methods to identify tumor subtypes. Different tumor subtypes also differ in their patterns of metastatic spread. Awareness of these differences can direct radiologists to relevant anatomical sites to screen for early metastases that may otherwise be difficult to detect during cursory inspection. Likewise, this knowledge will help radiologists to interpret indeterminate findings in a more specific manner.

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Tumor subtypes can be identified based on their different imaging characteristics.

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Awareness of tumor subtype can help radiologists chose the appropriate modality for additional imaging workup.

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Awareness of differences in metastatic pattern between tumor subtypes can be helpful to identify early metastases.

Liver Metastasis Formation Is Defined by AMIGO2 Expression via Adhesion to Hepatic Endothelial Cells in Human Gastric and Colorectal Cancer Cells

The adhesion of circulating cancer cells to vascular endothelial cells is an initial and critical step in distant metastases. Amphoterin-induced gene and open reading frame 2 (AMIGO2) was found to regulate tumor cell adhesion to hepatic endothelial cells and act as a driver gene for liver metastasis in mouse cell lines. However, whether the role of AMIGO2 observed in mouse tumor cells can be extrapolated to human cancer cells in vivo has not been verified. In this study, AMIGO2 expression in various human gastric and colorectal cancer cells was found to be closely associated with their adhesion to human hepatic sinusoidal endothelial cells (HHSECs). Constitutive AMIGO2-knockdown clones of human gastric (MKN-45) and colorectal cancer cell lines (DLD-1) were established to examine whether AMIGO2 expression in cancer cells is involved in the adhesion to HHSECs in vitro and the formation of liver metastasis in vivo. All AMIGO2-knockdown cells showed significantly attenuated adhesion to HHSECs. In vivo analysis revealed that intrasplenic inoculation of AMIGO2-knockdown clones could engraft in the spleen but significantly suppressed liver metastasis in nude mice. This study demonstrated that the role of AMIGO2 as a driver gene of liver metastasis in mouse tumor cells can be extrapolated to human cancer cells.

Patients with brain metastases from gastric cancer

INTRODUCTION

The aim of this study was to retrospectively evaluate the treatment strategies and possible prognostic factors in patients with brain metastases from gastric cancers.

METHODS

We retrospectively reviewed 24 patients with brain metastases from gastric cancer who were treated at our center between January 2014 and March 2020. Clinicopathological characteristics and clinical outcomes were analyzed.

RESULTS

The median follow-up time was six months (range, 1-40). The median survival time after diagnosis of brain metastases was six months (95% confidence interval: 1.33-10.66). The one- and two-year survival rates were 30.7% and 5.1%, respectively. On univariate analyses, absence of extracranial metastases was significantly associated with better overall survival (OS) but not intracranial progression-free survival (iPFS), while Eastern Cooperative Oncology Group performance status (ECOG PS), whole brain radiotherapy (WBRT) and systemic treatments were significantly associated with better iPFS and OS. Multivariate analysis showed that ECOG PS, extracranial disease and systemic treatments were independent prognostic factors, while only systemic treatment influenced the iPFS. Two patients achieved partial response, 12 patients had progressive disease, and 10 patients remained stable. Local tumor control in our series was achieved in 50%. One patient, who received a combination of camrelizumab and apatinib therapy following whole brain radiotherapy, achieved an obvious partial response.

CONCLUSIONS

ECOG PS, extracranial disease and systemic treatments were independent prognostic factors for gastric cancer patients with brain metastases. The present best treatment for this group of patients was individual comprehensive therapy according to the different situation of each patient.

Tumor-Derived Exosomes Modulate Primary Site Tumor Metastasis

Tumor-derived exosomes (TDEs) are actively produced and released by tumor cells and carry messages from tumor cells to healthy cells or abnormal cells, and they participate in tumor metastasis. In this review, we explore the underlying mechanism of action of TDEs in tumor metastasis. TDEs transport tumor-derived proteins and non-coding RNA to tumor cells and promote migration. Transport to normal cells, such as vascular endothelial cells and immune cells, promotes angiogenesis, inhibits immune cell activation, and improves chances of tumor implantation. Thus, TDEs contribute to tumor metastasis. We summarize the function of TDEs and their components in tumor metastasis and illuminate shortcomings for advancing research on TDEs in tumor metastasis.

Intense 68Ga-DOTA-FAPI-04 Uptake in Diffuse Sclerotic Skeletal Metastases of Gastric Cancer

ABSTRACT

Diffuse sclerotic metastases of the bone as initial presentation at gastric carcinoma are very rare. We present a 48-year-old man who was examined for pancytopenia and diagnosed with gastric cancer. 18F-FDG PET/CT showed moderate uptake in the primary gastric tumor and mild uptake in diffuse sclerotic metastatic lesions in the bone matrix, whereas 68Ga-DOTA-FAPI-04 showed mild uptake in the gastric lesion and intense uptake at the whole skeleton.

Analysis of Related Risk Factors and Prognostic Factors of Gastric Cancer with Bone Metastasis: A SEER-Based Study

Background

Gastric cancer is among the most common malignant tumors at home and abroad, because its early symptoms are mostly insidious, which leads to distant metastasis when gastric cancer is first diagnosed. The common metastatic sites of gastric cancer are mainly the liver, lung, and peritoneum, but bone metastasis is relatively rare, and the prognosis of gastric cancer bone metastasis is very poor. Therefore, this study is built on the SEER database to analyze the related risk factors of gastric cancer bone metastasis and related factors affecting the prognosis of gastric cancer patients, aiming at improving clinicians' understanding of clinical diagnosis and prognosis of bone metastasis of gastric cancer, thus reducing misdiagnosis and missed diagnosis.

Methods

The SEER database was collected to screen out patients with gastric cancer bone metastases and nonbone metastases matched with them from 2010 to 2016, and the Kaplan-Meier method was used to draw survival curves, and the comparison between survival curves was performed by Log-rank test to analyze the overall survival of the two groups of patient's time. Logistic regression analysis was used to analyze the related risk factors of gastric cancer bone metastasis, and the Cox regression proportional hazard model was used to analyze the relationship between gastric cancer bone metastasis and patient prognosis.

Results

Using Kaplan-Meier survival curve to analyze the 1, 3, and 5-year survival rates of gastric cancer patients with bone metastasis and non-metastasis groups were 14.2%, 1.8%, 0.6% and 71.4%, 44.3%, 36.4%, respectively; the average survival rate of the metastatic group was The time was 4.0 months (95%CI: 3.475~4.525), and the average survival time of the non-metastatic group was 30.0 months (95%CI: 26.778~33.222). The difference between the two groups was statistically significant (χ² = 1076.866, P < 0.001). Multivariate logistic regression analysis showed that race (P = 0.007, OR = 1.296), grade (P < 0.001, OR = 0.575), marital status (P < 0.001, OR = 0.040), tumor size (P = 0.006, OR = 0.752), TNM stage (P < 0.001), T stage (P = 0.023, OR = 0.882), and M stage (P < 0.001, OR = 44.958) are independent risk factors for gastric cancer bone metastasis. The Cox univariate analysis suggests that gastric cancer bone metastasis is a risk factor for the prognosis of gastric cancer patients. The Cox multivariate analysis validates that gastric cancer bone metastasis (HR = 0.584, 95% CI: 0.497~0.688, P < 0.001) is independent of the overall survival rate of gastric cancer patients.

Conclusions

Race, grade, marital status, tumor size, TNM stage, T stage, and M stage are independent risk factors for gastric cancer bone metastasis; and gastric cancer bone metastasis is an independent risk factor that affects the prognosis of gastric cancer patients. Therefore, for such high-risk groups, large range screening of the above indicators can effectively improve the prognosis of gastric cancer patients to a certain extent.

A Diagnostic Nomogram Based on 18F-FDG PET/CT for Bone Metastasis of Gastric Cancer

Purpose: To develop an effective diagnostic model for bone metastasis of gastric cancer by combining ¹⁸F-FDG PET/CT and clinical data.

Materials and Methods: A total of 212 gastric cancer patients with abnormal bone imaging scans based on ¹⁸F-FDG PET/CT were retrospectively enrolled between September 2009 and March 2020. Risk factors for bone metastasis of gastric cancer were identified by multivariate logistic regression analysis and used to create a nomogram. The performance of the nomogram was evaluated by using receiver operating characteristic curves and calibration plots.

Results: The diagnostic power of the binary logistic regression model incorporating skeleton-related symptoms, anemia, the SUVmax of bone lesions, bone changes, the location of bone lesions, ALP, LDH, CEA, and CA19-9 was significantly higher than that of the model using only clinical factors (p = 0.008). The diagnostic model for bone metastasis of gastric cancer using a combination of clinical and imaging data showed an appropriate goodness of fit according to a calibration test (p = 0.294) and good discriminating ability (AUC = 0.925).

Conclusions: The diagnostic model combined with the ¹⁸F-FDG PET/CT findings and clinical data showed a better diagnosis performance for bone metastasis of gastric cancer than the other studied models. Compared with the model using clinical factors alone, the additional ¹⁸F-FDG PET/CT findings could improve the diagnostic efficacy of identifying bone metastases in gastric cancer.

Machine learning algorithm of ultrasound-mediated intestinal function recovery and nursing efficacy analysis of lower gastrointestinal malignant tumor after surgery

Objectives:

In this paper, machine learning algorithms was used to explore the application value of ultrasound contrast in the early evaluation of neoadjuvant chemotherapy in patients with gastrointestinal malignant liver metastases, and analyzes the effect of sports nursing methods on intestinal function recovery.

Methods:

Forty-seven patients with gastrointestinal malignancies were divided into 25 patients (combined chemotherapy group) and 22 cases (chemotherapy group) from April 2018 to April 2019. Two groups of patients were treated with CEUS. The effective lesion patients and invalid quantitative parameters were compared between the two groups before and after treatment, and the postoperative routine nursing was implemented.

Results:

Chemotherapy group effective in 18 cases, accounting for 81.82%; 4 cases, 18.18%. Combination chemotherapy patients 21 cases, accounting for 84.00%; 4 cases, accounting for 16.00%.

Conclusion:

Based on early is important to assess the efficacy of neoadjuvant chemotherapy in patients with liver metastases peak intensity ultrasound contrast parameters of the machine learning algorithms malignant tumors in the gastrointestinal tract, post-operative care movement helps to restore bowel function.

Clinicopathological Characteristics and Prognosis of Signet Ring Gastric Cancer: A Population-Based Study

Background

To better define the clinicopathologic characteristics of signet ring cell (SRC) gastric cancer and build a prognostic model for it.

Methods

SRC patient information from 2010 to 2015 were identified using Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier method and log-rank test were used to estimate Overall survival (OS) and to determine associations with histologic subtypes. In COX proportional hazards regression model–based univariate and multivariate analyses, significant variables for construction of a nomogram were screened out. The nomogram was validated by means of the concordance index (CI), calibration plots, and receiver operating characteristics (ROCs) curves.

Results

A total of 11,363 gastric cancer patients were enrolled. On dividing the patients into SRC, well-to-moderately differentiated (WMD) adenocarcinoma, and poorly differentiated (PD) adenocarcinoma, differences among these subgroups emerged. SRC patients were more likely to occur in female and young patients than other histologic subtypes. Larger tumors, stage T4, and node stage N3 were more likely to be found in the SRC group. The survival for SRC patients was better than non-SRC patients in stage I. Univariate and multivariate analyses identified age, tumor site, larger tumor size, advanced T classification, advanced N classification, advanced TNM stage, and surgery of primary site as independent prognostic indicators. Then an OS nomogram was formulated.

Conclusions

SRC had distinct clinicopathological characteristics. The nomogram provided an accurate tool to evaluate the prognosis of SRC.

The prognosis and clinicopathological features of different distant metastases patterns in renal cell carcinoma: analysis based on the SEER database

Existing data on the prognosis and clinicopathological features of patients with metastatic renal cell carcinoma (mRCC) are limited. This study aims to investigate the prognostic value and clinicopathological features of different metastatic sites in patients with mRCC. A dataset from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database consisting of 18 registries (1973–2015) was selected for a retrospective mRCC cohort study. Information was included on the metastatic sites in lung, bone, liver, and brain. Kaplan–Meier analysis was applied to compare the survival distribution. Univariate and multivariate Cox regression models were used to analyze survival outcomes. From the SEER database, a total of 10,410 patients with primary mRCC from 2010 to 2015 were enrolled in this cohort study. Analysis indicated that 54.9%, 37.7%, 19.5%, and 10.4% of patients were found to have lung, bone, liver, and brain metastasis, respectively. There was a significantly higher risk for sarcomatoid RCC patients to develop liver metastasis as compared to patients with clear cell RCC. The median survival for patients with lung, bone, liver, or brain metastasis was 7 months, 7 months, 4 months, and 5 months, respectively. Various clinicopathological features and prognostic values are associated with different metastatic sites. Understanding these differences may enable targeted pre-treatment assessment of primary mRCC and personalized curative intervention for patients.

The incidence, risk factors and predictive nomograms for early death of lung cancer with synchronous brain metastasis: a retrospective study in the SEER database

BACKGROUND

The prognosis of lung cancer with synchronous brain metastasis (LCBM) is very poor, and patients often die within a short time. However, little is known about the early mortality and related factors in patients with LCBM.

METHODS

Patients diagnosed with LCBM between 2010 and 2016 were enrolled from the Surveillance, Epidemiology, and End Result (SEER) database. Univariate and multivariate logistic regression analysis were used to identify significant independent prognostic factors, which were used to construct nomograms of overall and cancer-specific early death. Then, the prediction ability of the model was verified by receiver operating characteristic (ROC) curve. At last, the clinical application value of the model was tested through decision curve analysis (DCA).

RESULTS

A total of 29,902 patients with LCBM were enrolled in this study. Among them, 13,275 (44.4%) patients had early death, and 11,425 (38.2%) cases died of lung cancer. The significant independent risk factors for overall and cancer-specific early death included age, race, gender, Gleason grade, histological type, T stage, N stage, bone metastasis, liver metastasis and marital status, which were used to construct the nomogram. The ROC curve demonstrated good predictive ability and clinical application value. The areas under the curve (AUC) of the training group was 0.793 (95% CI: 0.788-0.799) and 0.794 (95% CI: 0.788-0.799), in the model of overall and cancer-specific early death respectively. And the AUC of the validation group were 0.803 (95% CI: 0.788-0.818) and 0.806 (95% CI: 0.791-0.821), respectively. The calibration plots of the model showed that the predicted early death is consistent with the actual value. The DCA analysis indicated a good clinical application value of this model.

CONCLUSIONS

We established a comprehensive nomogram to predict early death in lung cancer patients with synchronous brain metastases. Nomograms may help oncologists develop better treatment strategies, such as clinical trials and hospice care.

Advanced esophagogastric junction cancer with brain, bone and gastric intramural metastases responding to combined modality therapy

A 63-year-old man was admitted to our hospital in March 2017 with dysphagia and right homonymous hemianopsia. We diagnosed him with esophagogastric junction cancer (adenocarcinoma) with metastases to the cerebral occipital lobe, bone, and lymph nodes. After one cycle of 5FU + cisplatin (FP), the brain metastasis was resected because of the hemiplegic symptoms he developed. Histology of the resected tissue showed no viable tumor cells. After three cycles of FP, the primary lesion and metastases were resolved. Upper gastrointestinal endoscopy revealed a scar at the primary site. This was considered a complete response (CR). In April 2018, CT revealed a mass at the cardia, which was considered as lymph node metastases with gastric wall invasion. Although two additional cycles of FP were administered for recurrent tumors, the efficacy was progressive. In August 2018, proximal gastrectomy and D1 + lymph node dissection were performed. The pathological diagnosis was gastric intramural metastases and lymph node metastases (ypN1 [2/22]). Weekly paclitaxel therapy was administered for three months after surgery. Two years have passed since the last surgery without recurrence. We report a rare case of esophagogastric junction cancer with brain, bone, and gastric intramural metastases that responded to combined modality therapy.

Metastasis pattern and prognosis in men with esophageal cancer patients: A SEER-based study

Esophageal cancer (EC) is relatively common; at the time of diagnosis, 50% of cases present with distant metastases, and most patients are men. This study aimed to examine and compare the clinicopathological characteristics and metastatic patterns of male EC (MEC) and female EC (FEC). In addition, risk factors associated with MEC prognosis were evaluated.The present study population was extracted from the Surveillance Epidemiology and End Results database. MEC characteristics and factors associated with prognosis were evaluated using descriptive analysis, the Kaplan-Meier method, and the Cox regression model.A total of 12,558 MEC cases were included; among them, 3454 cases had distant organ metastases. Overall, 27.5% of the entire cohort were patients with distant organ metastases. Compared with patients with non-metastatic MEC, patients with metastatic MEC were more likely to be aged ≤60 years, of Black and White race, have a primary lesion in the overlapping esophagus segments, and have a diagnosis of adenocarcinoma of poorly differentiated and undifferentiated grade that was treated with radiotherapy and chemotherapy rather than surgery; moreover, they were also more likely to be married and insured. In addition, patients with MEC were more likely to be aged ≤60 years, White race, and diagnosed with a primary lesion in the lower third of the esophagus and overlapping esophagus segments, and treated without chemotherapy, compared with those with FEC. Patients in the former group were also more likely than those in the latter group to be unmarried and have bone metastasis only and lung metastasis only. Liver, lung, and bone metastases separately, and simultaneous liver and lung metastases were associated with poor survival in MEC patients.Metastatic MEC is associated with clinicopathological characteristics and metastatic patterns different from those associated with non-metastatic MEC and metastatic FEC. Metastatic MEC and FEC patients may have similar prognoses. Distant organ metastasis may be associated with poor prognosis in patients with MEC and FEC.

Bone Metastases from Gastric Cancer: What We Know and How to Deal with Them

Gastric cancer (GC) is the third cause of cancer-related death worldwide; the prognosis is poor especially in the case of metastatic disease. Liver, lymph nodes, peritoneum, and lung are the most frequent sites of metastases from GC; however, bone metastases from GC have been reported in the literature. Nevertheless, it is unclear how the metastatic sites may affect the prognosis. In particular, knowledge about the impact of bone metastases on GC patients’ outcome is scant, and this may be related to the rarity of bone lesions and/or their underestimation at the time of diagnosis. In fact, there is still a lack of specific recommendation for their detection at the diagnosis. Then, the majority of the evidences in this field came from retrospective analysis on very heterogeneous study populations. In this context, the aim of this narrative review is to delineate an overview about the evidences existing about bone metastases in GC patients, focusing on their incidence and biology, the prognostic role of bone involvement, and their possible implication in the treatment choice.

Primary tumor resection benefited the survival of patients with distant metastatic gastric cancer

Background:

The role of surgery in the treatment of patients with distant metastatic (M1) gastric cancer (GC) remains controversial currently. This study aimed to clarify the impact of primary tumor resection (PTR) on the survival of such patients.

Materials and Methods:

The surveillance, epidemiology, and end results database was adopted to extract eligible patients. We designed a retrospective case–control study. The patients were divided into two groups according to whether they received PTR. The 1:1 propensity score matching (PSM) analysis was performed to balance the confounding factors between no-surgery and surgery groups. The categorical variables were described with Chi-square tests. Cancer-specific survival (CSS) and overall survival (OS) were evaluated by Kaplan–Meier method with log-rank test. Cox proportional hazard models were utilized to identify prognostic factors of CSS.

Results:

A total of 1716 patients were included, including 1108 (64.6%) patients without surgery and 608 (35.4%) patients with surgery. After PSM, most confounders were well balanced between the two comparison groups. Survival analysis in matched cohorts indicated that surgery exerted significant survival advantages in both CSS and OS curves. The median CSS was 11.0 (9.8–12.2) months in the surgery group versus 9.0 (8.0–10.0) months in the no-surgery group (P < 0.001). Multivariable Cox regression analysis identified surgery as an independent prognostic factor for favorable prognosis (hazard ratio: 0.689, 95% confidence interval: 0.538–0.881, P = 0.003).

Conclusion:

Surgery showed significant survival benefits for the patients with M1 stage GC. Our study has provided additional evidence to support PTR for these patients.

A clinical model to predict distant metastasis in patients with superficial gastric cancer with negative lymph node metastasis and a survival analysis for patients with metastasis

BACKGROUND

Distant metastasis (DM) is relatively rare in superficial gastric cancer (SGC), especially in patients without lymph node metastasis. This study aimed to explore the main clinical risk factors for DM in patients with superficial gastric cancer-no lymph node metastasis (SGC-NLNM) and the prognostic factors for patients with DM.

METHODS

Records of patients with SGC-NLNM between 2004 and 2015 were collected from the public Surveillance, Epidemiology, and End Results (SEER) database. Both univariate and multivariate logistic regressions were performed to analyze the clinical risk factors for DM. The Kaplan-Meier method and Cox regression model were used to identify prognostic factors for patients with DM. A nomogram was built based on multivariate logistic regression and evaluated by the C-index, the calibration, and the area under the receiver operating characteristic curve (AUC).

RESULTS

We developed and validated a nomogram to predict DM in patients with SGC-NLNM, showing that race, age, primary site, depth, size, and grade were independent risk factors. The built nomogram had a good discriminatory performance, with a C-index of 0.836 (95% confidence interval [CI]: 0.813-0.859). Calibration plots showed that the predicted DM probability was identical to the actual observations in both the training and validation sets. AUC was 0.846 (95% CI: 0.820-0.871) and 0.801 (95% CI: 0.751-0.850) in the training and validation sets, respectively. The results of the survival analysis revealed that surgery (hazard ratio [HR] = 0.249; 95% CI, 0.125-0.495), chemotherapy (HR = 0.473; 95% CI, 0.353-0.633), and grade (HR = 1.374; 95% CI, 1.018-1.854) were independent prognostic factors associated with cancer-specific survival (CSS), but radiotherapy was not (log-rank test, p = 0.676).

CONCLUSIONS

We constructed a sensitive and discriminative nomogram to identify high-risk patients with SGC-NLNM who may harbor dissemination at initial diagnosis. The tumor size and primary site were the largest contributors to DM prediction. Compared with radiotherapy, aggressive surgery, and chemotherapy may be better options for patients with DM.