Carcinoembryonic Antigen Levels Research Articles

The influence of knocking down the expression of low-density lipoprotein receptor associated proteins on the vascular abnormalities in hepatocellular carcinoma and its mechanisms

Objectives: To investigate the effect of the expression of low-density lipoprotein receptor associated protein (LDLR) on the vascular abnormalities in hepatocellular carcinoma (HCC) and its mechanisms. Methods: Based on the information of Oncomine Cancer GeneChip database, we analyzed the correlation between the expression level of LDLR and the expression level of carcinoembryonic antigen (CEA) and CD31 in hepatocellular carcinoma tissues. Lentiviral transfection of short hairpin RNA target genes was used to construct LDLR-knockdown MHCC-97H and HLE hepatocellular carcinoma cells. The differential genes and their expression level changes in LDLR-knockdown hepatocellular carcinoma cells were detected by transcriptome sequencing, real-time fluorescence quantitative polymerase chain reaction, and protein immunoblotting. The gene-related signaling pathways that involve LDLR were clarified by enrichment analysis. The effect of LDLR on CEA was assessed by the detection of CEA content in conditioned medium of hepatocellular carcinoma cells. Angiogenesis assay was used to detect the effect of LDLR on the angiogenic capacity of human umbilical vein endothelial cells, as well as the role of CEA in the regulation of angiogenesis by LDLR. Immunohistochemical staining was used to detect the expression levels of LDLR in 176 hepatocellular carcinoma tissues, and CEA and CD31 in 146 hepatocellular carcinoma tissues, and analyze the correlations between the expression levels of LDLR, CEA, and CD31 in the tissues, serum CEA, and alanine transaminase (ALT). Results: Oncomine database analysis showed that the expressions of LDLR and CEA in the tissues of hepatocellular carcinoma patients with portal vein metastasis were negatively correlated (r=-0.64, P=0.001), whereas the expressions of CEA and CD31 in these tissues were positively correlated ( r=0.46, P=0.010). The transcriptome sequencing results showed that there were a total of 1 032 differentially expressed genes in the LDLR-knockdown group and the control group of MHCC-97H cells, of which 517 genes were up-regulated and 515 genes were down-regulated. The transcript expression level of CEACAM5 was significantly up-regulated in the cells of the LDLR-knockdown group. The Gene Ontology (GO) function enrichment analysis showed that the differential genes were most obviously enriched in the angiogenesis function. The Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis showed that the relevant pathways involved mainly included the cellular adhesion patch, the extracellular matrix receptor interactions, and the interactions with the extracellular matrix receptors. The CEA content in the conditioned medium of the LDLR-knockdown group was 43.75±8.43, which was higher than that of the control group (1.15±0.14, P＜0.001). The results of angiogenesis experiments showed that at 5 h, the number of main junctions, the number of main segments, and the total area of the lattice formed by HUVEC cells cultured with the conditioned medium of MHCC-97H cells in the LDLR-knockdown group were 295.3±26.4, 552.5±63.8, and 2 239 781.0±13 8211.9 square pixels, which were higher than those of the control group (113.3±23.5, 194.8±36.5, and 660 621.0±280 328.3 square pixels, respectively, all P＜0.01).The number of vascular major junctions, the number of major segments, and the total area of the lattice formed by HUVEC cells cultured in conditioned medium with HLE cells in the LDLR-knockdown group were 245.3±42.4, 257.5±20.4, and 2 535 754.5±249 094.2 square pixels, respectively, which were all higher than those of the control group (113.3±23.5, 114.3±12.2, and 1 565 456.5±219 259.7 square pixels, respectively, all P＜0.01). In the conditioned medium for the control group of MHCC-97H cells,the number of main junctions, the number of main segments, and the total area of the lattice formed by the addition of CEA to cultured HUVEC cells were 178.9±12.0, 286.9±12.3, and 1 966 990.0±126 249.5 spixels, which were higher than those in the control group (119.7±22.1, 202.7±33.7, and 1 421 191.0±189 837.8 square pixels, respectively). The expression of LDLR in hepatocellular carcinoma tissues was not correlated with the expression of CEA, but was negatively correlated with the expression of CD31 (r=-0.167, P=0.044), the level of serum CEA (r=-0.061, P=0.032), and the level of serum ALT(r=-0.147,P=0.05). The expression of CEA in hepatocellular carcinoma tissues was positively correlated with the expression of CD31 (r=0.192, P=0.020). The level of serum CEA was positively correlated with the level of serum ALT (r=0.164, P=0.029). Conclusion: Knocking down LDLR can promote vascular abnormalities in HCC by releasing CEA.

A clinical-radiomics nomogram based on spectral CT multi-parameter images for preoperative prediction of lymph node metastasis in colorectal cancer.

To develop a clinical-radiomics nomogram based on spectral CT multi-parameter images for predicting lymph node metastasis in colorectal cancer. A total of 76 patients with colorectal cancer and 156 lymph nodes were included. The clinical data of the patients were collected, including gender, age, tumor location and size, preoperative tumor markers, etc. Three sets of conventional images in the arterial, venous, and delayed phases were obtained, and six sets of spectral images were reconstructed using the arterial phase spectral data, including virtual monoenergetic images (40keV, 70keV, 100keV), iodine density maps, iodine no water maps, and virtual non-contrast images. Radiomics features of lymph nodes were extracted from the above images, respectively. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select features. A clinical model was constructed based on age and carcinoembryonic antigen (CEA) levels. The radiomics featuresselected were used to generate a composedradiomics signature (Com-RS). A nomogram was developed using age, CEA, and theCom-RS. The models' prediction efficiency, calibration, and clinical application value were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis, respectively. The nomogram outperforms the clinical model and the Com-RS (AUC = 0.879, 0.824). It is well calibrated and has great clinical application value. This study developed a clinical-radiomics nomogram based on spectral CT multi-parameter images, which can be used as an effective tool for preoperative personalized prediction of lymph node metastasis in colorectal cancer.

Development of a CT-Based comprehensive model combining clinical, radiomics with deep learning for differentiating pulmonary metastases from noncalcified pulmonary hamartomas, a retrospective cohort study.

Clinical differentiation between pulmonary metastases and noncalcified pulmonary hamartomas (NCPH) often presents challenges, leading to potential misdiagnosis. However, the efficacy of a comprehensive model that integrates clinical features, radiomics, and deep learning (CRDL) for differential diagnosis of these two diseases remains uncertain. This study evaluated the diagnostic efficacy of a Clinical Features, Radiomics, and Deep Learning (CRDL) model in differentiating pulmonary metastases from noncalcified pulmonary hamartomas (NCPH). We retrospectively analyzed the clinical and imaging data of 256 patients from Hospital A and 85 patients from Hospital B, who were pathologically confirmed pulmonary hamartomas or pulmonary metastases after thoracic surgery. Employing Python 3.7 software suites, we extracted radiomic features and deep learning attributes from patient datasets. The cohort was divided into training set, internal validation set, and external validation set. The diagnostic performance of the constructed models was evaluated using receiver operating characteristic (ROC) curve analysis to determine their effectiveness in differentiating between pulmonary metastases and NCPH. Clinical features such as white blood cell count (WBC), platelet count (PLT), history of cancer, carcinoembryonic antigen (CEA) level, tumor marker status, lesion margin characteristics (smooth or blurred) and maximum diameter were found to have diagnostic value in differentiating between the two diseases. In the domains of radiomics and deep learning. Of the 1,130 radiomics features and 512 deep learning features, 24 and 7, respectively, were selected for model development. The area under the ROC curve (AUC) values for the four groups were 0.980, 0.979, 0.999, and 0.985 in the training set, 0.947, 0.816, 0.934, and 0.952 in the internal validation set, and 0.890, 0.904, 0.923, and 0.938 in the external validation set. This demonstrated that the CRDL model showed the greatest efficacy. The comprehensive model incorporating clinical features, radiomics, and deep learning shows promise for aiding in the differentiation between pulmonary metastases and hamartomas.

Colonic duplication in an adult with chronic constipation: a case report and review of its surgical management.

One of the possible causes of chronic constipation is colonic duplication. Although seldom asymptomatic, its diagnosis is important due to the risk of malignancy that it carries. We present a case of a young female patient with long-standing constipation who was referred to Kolorektal Cerrahi Clinic (Izmir, Turkey) after scans revealed tubular type of colonic duplication. We successfully performed a laparoscopic total colectomy, and she recovered well. Identifying the type of duplication is important to ensure adequate resection and treatment. A proper workup, including carcinoembryonic antigen levels, must be done as well. Multiple surgical techniques and procedures have been introduced for this condition, but resection of the duplicated colon with its native lumen should be the management of choice, especially in tubular type of duplications such as in our case. In centers where laparoscopic services are available, laparoscopy could be a better option, as it provides multiple benefits of minimally invasive surgery. Attention should also be paid to anatomical details during surgery to ensure better results and outcomes.

Combination of clinical and spectral-CT iodine concentration for predicting liver metastasis in gastric cancer: a preliminary study.

This study aimed to determine the diagnostic efficacy of various indicators and models for the prediction of gastric cancer with liver metastasis. Clinical and spectral computed tomography (CT) data from 80 patients with gastric adenocarcinoma who underwent surgical resection were retrospectively analyzed. Patients were divided into metastatic and non-metastatic groups based on whether or not to occur liver metastasis, and the region of interest (ROI) was measured manually on each phase iodine map at the largest level of the tumor. Iodine concentration (IC), normalized iodine concentration (nIC), and clinical data of the primary gastric lesions were analyzed. Logistic regression analysis was used to construct the clinical indicator (CI) and clinical indicator-spectral CT iodine concentration (CI-Spectral CT-IC) Models, which contained all of the parameters with statistically significant differences between the groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the accuracy of the models. The metastatic group showed significantly higher levels of Cancer antigen125 (CA125), carcinoembryonic antigen (CEA), IC, and nIC in the arterial phase, venous phase, and delayed phase than the non-metastatic group (all p < 0.05). Normalized iodine concentration Venous Phase (nICVP) exhibited a favorable performance among all IC and nIC parameters for forecasting gastric cancer with liver metastasis (area under the curve (AUC), 0.846). The combination model of clinical data with significant differences and nICVP showed the best diagnostic accuracy for predicting liver metastasis from gastric cancer, with an AUC of 0.897. nICVP showed the best diagnostic efficacy for predicting gastric cancer with liver metastasis. Clinical Indicators-normalized ICVP model can improve the prediction accuracy for this condition.

Evaluation of the value of combined detection of tumor markers CA724, carcinoembryonic antigen, CA242, and CA19-9 in gastric cancer.

Gastric cancer is a global health concern that poses a significant threat to human well-being. To detecting serum changes in carcinoembryonic antigen (CEA), carbohydrate antigens (CA) 724, CA242, and CA19-9 expression among patients with gastric cancer. Eighty patients diagnosed with gastric cancer between January 2020 and January 2023 were included in the observation group, while 80 patients with benign gastric diseases were included in the control group. Both groups were tested for tumor markers (CA724, CEA, CA242, and CA19-9]. Tumor marker indicators (CA724, CEA, CA242, and CA19-9) were compared between the two groups, assessing positive rates of tumor markers across various stages in the observation group. Additionally, single and combined detection of various tumor markers were examined. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value observed for the combined detection of CA724, CEA, CA242, and CA19-9 were higher than those of CA724, CEA, CA242, and CA19-9 individually. Therefore, the combined detection of CA724, CEA, CA242, and CA19-9 has a high diagnostic accuracy and could reduce the occurrence of missed or misdiagnosed cases, facilitating the early diagnosis and treatment of patients. CA724, CEA, CA242, and CA19-9 serum levels in gastric cancer patients significantly surpassed those in non-gastric cancer patients (P < 0.05). Their combined detection can improve the diagnostic accuracy for gastric cancer, warranting clinical promotion.

Hepatic hemangioma in a simple liver cyst mimicking biliary cystic neoplasm

BackgroundFollow-up is recommended for an asymptomatic unilocular hepatic cystic lesion without wall-thickness and nodular components. A few liver cystic lesions represent biliary cystic neoplasms, which are difficult to differentiate from simple cysts with benign mural nodules on imaging alone.Case presentationAn 84-year-old woman with a history of simple liver cyst diagnosed one year prior was admitted for evaluation of a developed mural nodule in the cystic lesion. She had no specific symptoms and no abnormalities in blood tests except for carcinoembryonic antigen (5.0 ng/mL) and carbohydrate antigen (43.5 U/mL) levels. Contrast-enhanced computed tomography revealed a well-defined, low-attenuation lesion without a septum that had enlarged from 41 to 47 mm. No dilation of the bile duct was observed. A gradually enhancing mural nodule, 14 mm in diameter, was confirmed. MRI revealed a uniform water-intense cystic lesion with a mural nodule. This was followed by T2-enhanced imaging showing peripheral hypointensity and central hyperintensity. Enhanced ultrasonography revealed an enhanced nodule with a distinct artery within it. A needle biopsy of the wall nodule or aspiration of intracystic fluid was not performed to avoid tumor cell spillage. The possibility of a neoplastic cystic tumor could not be ruled out, so a partial hepatectomy was performed with adequate margins. Pathologically, the cystic lesion contained a black 5 mm nodule consisting of a thin, whitish fibrous wall and dilated vessels lined by CD31 and CD34 positive endothelial cells. The final diagnosis was a rare cavernous hemangioma within a simple liver cyst.ConclusionsCavernous hemangiomas mimicking well-enhanced mural nodules can arise from simple liver cysts. In less malignant cases, laparoscopic biopsy or percutaneous targeted biopsy of the mural nodules, together with needle ablation, may be recommended to avoid unnecessary surgery.

The efficacy and safety of continuous intravenous infusion of rh-endostatin combined with platinum-based doublet chemotherapy for advanced non-small-cell lung cancer.

Platinum-based doublet chemotherapy is commonly used in the treatment of non-small cell lung cancer (NSCLC). A growing body of evidence indicates that incorporating antiangiogenic agents into platinum-based chemotherapy may enhance the survival outcomes for NSCLC patients. However, the optimal administration protocol for intravenous recombinant human endostatin (rh-endostatin), an antiangiogenic agent, remains uncertain at present. This study aims to investigate the efficacy and safety of 5-d continuous intravenous infusion of rh-endostatin in combination with chemotherapy for patients with advanced NSCLC. The predictive biomarkers for this treatment regimen were further probed. This prospective, single-arm multicenter study enrolled a total of 48 patients with advanced NSCLC who were histologically or cytologically confirmed but had not received any prior treatment from January 2021 to December 2022. Prior to the chemotherapy, these patients received a continuous intravenous infusion of rh-endostatin (210mg) over a period of 120h, using an infusion pump. The chemotherapy regimen included a combination of platinum with either pemetrexed or paclitaxel, given in 21-day cycles. The primary endpoint of the study was median progression-free survival (mPFS), and the secondary endpoints included median overall survival (mOS), objective response rate (ORR), disease control rate (DCR), and assessment of adverse events (AEs). The mPFS was 6.5 months (95% confidence interval (CI): 3.8-9.1m) while the mOS was 12.3 months (95% CI: 7.6-18.5m). The ORR and DCR was 52.1% and 75.0%, respectively. Leukopenia (52.1%), anemia (33.3%), and thrombocytopenia (20.8%) were the most common adverse effects and these toxicities were deemed acceptable and manageable. In addition, a correlation was noted between elevated serum carcinoembryonic antigen (CEA) levels and decreased PFS and OS. The incorporation of a 5-day continuous intravenous infusion of rh-endostatin into platinum-based doublet chemotherapy has demonstrated both safety and efficacy in the treatment of advanced NSCLC. Furthermore, the baseline serum levels of CEA may potentially function as a predictor for the efficacy of rh-endostatin when combined with chemotherapy in NSCLC patients. GOV: NCT05574998.

Elevated serum homocysteine levels associated with poor recurrence-free and overall survival in patients with colorectal cancer

This study aimed to evaluate the significance of homocysteine (HCY) levels in predicting recurrence-free survival (RFS) and overall survival (OS) in colorectal cancer (CRC) patients. This retrospective study involved 1272 CRC patients. The risk of mortality increased with increasing HCY levels in CRC patients. The optimal HCY cutoff value in CRC patients was 15.2 μmol/L. The RFS (45.8% vs. 60.5%, p < 0.001) and OS (48.2% vs. 63.2%, p < 0.001) of patients with high HCY levels were significantly lower than those of patients with low HCY levels. Patients with high HCY levels were older, male, had large tumours, high carcinoembryonic antigen (CEA) levels, and long hospital stays, and incurred high hospitalisation costs. Multivariate analysis showed that when HCY levels exceeded 15.2 μmol/L, the risk of adverse RFS and OS increased by 55.7% and 61.4%, respectively. Subgroup analysis showed that HCY levels could supplement CEA levels and pathological staging. We constructed HCY-based prognostic nomograms, which demonstrated feasible discrimination and calibration values better than the traditional tumour, node, metastasis staging system for predicting RFS and OS. Elevated serum HCY levels were strongly associated with poor RFS and OS in CRC patients. HCY-based prognostic models are effective tools for a comprehensive evaluation of prognosis.

Exploration of the application potential of serum multi-biomarker model in colorectal cancer screening

Analyzing blood lipid and bile acid profile changes in colorectal cancer (CRC) patients. Evaluating the integrated model's diagnostic significance for CRC. Ninety-one individuals with colorectal cancer (CRC group) and 120 healthy volunteers (HC group) were selected for comparison. Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and apolipoproteins (Apo) A1, ApoA2, ApoB, ApoC2, and ApoC3 were measured using immunoturbidimetric and colorimetric methods. Additionally, LC–MS/MS was employed to detect fifteen bile acids in the serum, along with six tumor markers: carcinoembryonic antigen (CEA), carbohydrate antigens (CA) 125, CA19-9, CA242, CA50, and CA72-4. Group comparisons utilized independent sample t-tests and Mann–Whitney U tests. A binary logistic regression algorithm was applied to fit the indicators and establish a screening model; the diagnostic accuracy of individual Indicators and the model was analyzed using receiver operating characteristic (ROC) curves. The CRC group showed significantly lower levels in eight serum lipid indicators and eleven bile acids compared to the HC group (P < 0.05). Conversely, serum levels of TG, CA19-9, and CEA were elevated (P < 0.05). Among the measured parameters, ApoA2 stands out for its strong correlation with the presence of CRC, showcasing exceptional screening efficacy with an area under the curve (AUC) of 0.957, a sensitivity of 85.71%, and a specificity of 93.33%. The screening model, integrating ApoA1, ApoA2, lithocholic acid (LCA), and CEA, attained an impressive AUC of 0.995, surpassing the diagnostic accuracy of individual lipids, bile acids, and tumor markers. CRC patients manifest noteworthy alterations in both blood lipids and bile acid profiles. A screening model incorporating ApoA1, ApoA2, LCA, and CEA provides valuable insights for detecting CRC.

Evaluation of serum levels of fibroblast growth factor-2 and carcinoembryonic antigen in patients with squamous cell carcinoma of the oral cavity

Evaluation of serum levels of fibroblast growth factor-2 and carcinoembryonic antigen in patients with squamous cell carcinoma of the oral cavity

Evaluation of serum levels of fibroblast growth factor-2 and carcinoembryonic antigen in patients with squamous cell carcinoma of the oral cavity

Evaluation of serum levels of fibroblast growth factor-2 and carcinoembryonic antigen in patients with squamous cell carcinoma of the oral cavity

Deep Neural Network for the Prediction of KRAS, NRAS and BRAF Genotypes in left-sided colorectal cancer based on histopathologic images

BackgroundThe KRAS, NRAS, and BRAF genotypes are critical for selecting targeted therapies for patients with metastatic colorectal cancer (mCRC). Here, we aimed to develop a deep learning model that utilizes pathologic whole-slide images (WSIs) to accurately predict the status of KRAS, NRAS, and BRAFV600E. Methods129 patients with left-sided colon cancer and rectal cancer from the Third Affiliated Hospital of Sun Yat-sen University were assigned to the training and testing cohorts. Utilizing three convolutional neural networks (ResNet18, ResNet50, and Inception v3), we extracted 206 pathological features from H&E-stained WSIs, serving as the foundation for constructing specific pathological models. A clinical feature model was then developed, with carcinoembryonic antigen (CEA) identified through comprehensive multiple regression analysis as the key biomarker. Subsequently, these two models were combined to create a clinical-pathological integrated model, resulting in a total of three genetic prediction models. Result103 patients were evaluated in the training cohort (1,782,302 image tiles), while the remaining 26 patients were enrolled in the testing cohort (489,481 image tiles). Compared with the clinical model and the pathology model, the combined model which incorporated CEA levels and pathological signatures, showed increased predictive ability, with an area under the curve (AUC) of 0.96 in the training and an AUC of 0.83 in the testing cohort, accompanied by a high positive predictive value (PPV 0.92). ConclusionThe combined model demonstrated a considerable ability to accurately predict the status of KRAS, NRAS, and BRAFV600E in patients with left-sided colorectal cancer, with potential application to assist doctors in developing targeted treatment strategies for mCRC patients, and effectively identifying mutations and eliminating the need for confirmatory genetic testing.

The Impact of Type 2 Diabetes Mellitus on Treatment Outcomes in Patients Operated for Stage III Rectal Adenocarcinoma

Introduction: Colorectal cancer (CRC) ranks as the world&amp;#39;s fourth most prevalent cancer and is the third leading cause of death globally. Stage III CRC indicates localized spread to nearby lymph nodes without metastasis to other body parts. While numerous studies have explored outcomes in CRC patients based on various predictive factors, a comprehensive literature review has identified a gap in research specifically investigating surgical outcomes for stage III rectal adenocarcinoma in individuals with type 2 diabetes mellitus (DM2).Aim: To explore the impact of DM2 on treatment outcomes in patients undergoing surgery for stage III rectal adenocarcinoma.Patients and methods: Our retrospective cohort study involved 95 patients who underwent elective radical anterior rectal resection with established mechanical colorectal anastomosis. Patients were categorized into two groups based on DM2 status.Results: Univariate regression analysis demonstrated that DM2 patients face a significantly higher risk of preoperatively elevated carcinoembryonic antigen levels and postoperative complications such as surgical site infection, urinary issues, and anastomotic leakage. Kaplan-Meier analysis indicated a shorter time to complication onset, particularly anastomotic leakage, and a diminished overall survival in DM2 patients.Conclusion: DM2 emerged as a significant prognostic factor influencing the treatment outcomes of patients undergoing surgery for stage III rectal adenocarcinoma.

Prognostic value of a nomogram model for postoperative liver metastasis of colon cancer.

Colon cancer is one of the most common malignant tumors of the digestive system. Liver metastasis after colon cancer surgery is the primary cause of death in patients with colon cancer. To construct a novel nomogram model including various factors to predict liver metastasis after colon cancer surgery. We retrospectively analyzed 242 patients with colon cancer who were admitted and underwent radical resection for colon cancer in Zhejiang Provincial People's Hospital from December 2019 to December 2022. Patients were divided into liver metastasis and non-liver metastasis groups. Sex, age, and other general and clinicopathological data (preoperative blood routine and biochemical test indexes) were compared. The risk factors for liver metastasis were analyzed using single-factor and multifactorial logistic regression. A predictive model was then constructed and evaluated for efficacy. Systemic inflammatory index (SII), C-reactive protein/albumin ratio (CAR), red blood cell distribution width (RDW), alanine aminotransferase, preoperative carcinoembryonic antigen level, and lymphatic metastasis were different between groups (P < 0.05). SII, CAR, and RDW were risk factors for liver metastasis after colon cancer surgery (P < 0.05). The area under the curve was 0.93 for the column-line diagram prediction model constructed based on these risk factors to distinguish whether liver metastasis occurred postoperatively. The actual curve of the column-line diagram predicting the risk of postoperative liver metastasis was close to the ideal curve, with good agreement. The prediction model curves in the decision curve analysis showed higher net benefits for a larger threshold range than those in extreme cases, indicating that the model is safer. Liver metastases after colorectal cancer surgery could be well predicted by a nomogram based on the SII, CAR, and RDW.

Limited prognostic role of routine serum markers (AP, CEA, LDH and NSE) in oligorecurrent prostate cancer patients undergoing PSMA-radioguided surgery

IntroductionWe evaluated the prognostic role of pre-salvage prostate-specific membrane antigen–radioguided surgery (PSMA-RGS) serum levels of alkaline phosphatase (AP), carcinoembryonic antigen (CEA), lactate dehydrogenase (LDH), and neuron-specific enolase (NSE).Materials and methodsPatients who consecutively underwent PSMA-RGS for prostate cancer (PCa) oligorecurrence between January 2019 and January 2022 were selected. Biomarkers were assessed one day before surgery. Cox regression and logistic regression models tested the relationship between biochemical recurrence-free survival (BFS), 6- and 12-month biochemical recurrence (BCR), and several independent variables, including biomarkers.Results153 consecutive patients were analyzed. In the univariable Cox regression analysis, none of the biomarkers achieved predictor status (AP: hazard ratio [HR] = 1.03, 95% CI 0.99, 1.01; p = 0.19; CEA: HR = 1.73, 95% CI 0.94, 1.21; p = 0.34; LDH: HR = 1.01, 95% CI 1.00, 1.01; p = 0.05; NSE: HR = 1.02, 95% CI 0.98, 1.06; p = 0.39). The only independent predictor of BFS was the number of positive lesions on PSMA PET (HR = 1.17, 95% CI 1.02, 1.30; p = 0.03).The number of positive lesions was confirmed as independent predictor for BCR within 6 and 12 months (BCR < 6 months: odds ratio [OR] = 1.1, 95% CI 1.0, 1.3; p = 0.04; BCR < 12 months: OR = 1.1, 95% CI 1.0, 1.3; p = 0.04).ConclusionThe assessment of AP, CEA, LDH, and NSE before salvage PSMA-RGS showed no prognostic impact. Further studies are needed to identify possible predictors that will optimize patient selection for salvage PSMA-RGS.

Implications of Pretreatment Serum Carcinoembryonic Antigen Levels and Perineural Invasion with Staging, Prognosis, and Management in Stage I-III Colon Cancer after Surgery: A Retrospective Cohort Study in the SEER Database.

Pretreatment levels of serum carcinoembryonic antigen (CEA) and perineural invasion (PNI) are related to poor prognosis in colon cancer. We analyzed the CEA and PNI (defined as incorporation of carcinoembryonic antigen and perineural invasion (CP)-stage), which are included in the Tumor-Node-Metastasis (TNM) staging system of the American Joint Committee on Cancer (AJCC), and evaluated the survival prognosis of patients treated with surgery in I-III stage colon carcinoma. We employed a retrospective study for eligible colon carcinoma patients obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. Kaplan-Meier curve and Multivariate Cox regression analysis were used to analyze different TNM-CP stages for the cancer-specific survival (CSS) probabilities in colon cancer. In our study, CEA levels and PNI were significant prognostic factors (p < 0.05), and the newly proposed CP-stage was an independent prognostic index in stage I-III colon carcinoma after surgery. Multivariate Cox regression analyses indicated that CP1-stage was related to a 63.9% increased risk of cancer-specific mortality (hazard ratio (HR): 1.639, 95% confidence interval (CI): 1.544-1.739, p < 0.001), compared with CP0-stage in colon cancer. In respective TNM stages, the CP0-stage had an advantage over the CP1-stage for CSS (p < 0.001). Moreover, CP1-stage patients with node-negative colon cancer were contacted with similar or worse survival in comparison to CP0-stage patients with node-positive. For postoperative patients with stage I-III colon cancer, our study indicated that the CP stage is a significant prognostic factor for CSS, which deserves more clinical attention. It's worth noting that including the CP stage in the AJCC TNM staging system of colon carcinoma is beneficial to the survival prediction and clinical treatment.

Presence of CD44v9-Expressing Cancer Stem Cells in Circulating Tumor Cells and Effects of Carcinoembryonic Antigen Levels on the Prognosis of Colorectal Cancer.

Circulating tumor cells (CTCs) are cancer cells released from the primary tumor into the bloodstream, and contain cancer stem cells that influence tumor survival, recurrence, and metastasis. Here, we investigated CD44v9 expression in CTCs and impact of preoperative carcinoembryonic antigen (CEA) levels on colorectal cancer (CRC) prognosis. We analyzed the expression of CD44v9 mRNA in CTCs using reverse transcription-polymerase chain reaction and preoperative CEA levels in blood samples obtained from 300 patients with CRC. Subsequently, we evaluated the association of CD44v9 expression and CEA levels with clinicopathological factors. CD44v9 mRNA was expressed in 31.3% of the patients, and was significantly associated with liver metastasis. Patients with positive CD44v9 expression had a lower 5-year survival rate (62.3%) than those with negative CD44v9 expression (82.8%, p < 0.001). Cox regression analysis identified CD44v9 expression and high CEA levels (≥5 ng/mL) as poor prognostic factors, while negative CD44v9 expression and low CEA levels (<5 ng/mL) were associated with favorable prognosis (hazard ratio = 0.285, p = 0.006). These results suggest that a combination of CD44v9 mRNA expression in CTCs and serum CEA levels could serve as a valuable prognostic marker for CRC, potentially enhancing the accuracy of prognosis predictions.

Machine learning for predicting colon cancer recurrence

Colorectal cancer (CRC) is a global public health concern, ranking among the most commonly diagnosed malignancies worldwide. Despite advancements in treatment modalities, the specter of CRC recurrence remains a significant challenge, demanding innovative solutions for early detection and intervention. The integration of machine learning into oncology offers a promising avenue to address this issue, providing data-driven insights and personalized care. This retrospective study analyzed data from 396 patients who underwent surgical procedures for colon cancer (CC) between 2010 and 2021. Machine learning algorithms were employed to predict CC recurrence, with a focus on demographic, clinicopathological, and laboratory characteristics. A range of evaluation metrics, including AUC (Area Under the Receiver Operating Characteristic), accuracy, recall, precision, and F1 scores, assessed the performance of machine learning algorithms. Significant risk factors for CC recurrence were identified, including sex, carcinoembryonic antigen (CEA) levels, tumor location, depth, lymphatic and venous invasion, and lymph node involvement. The CatBoost Classifier demonstrated exceptional performance, achieving an AUC of 0.92 and an accuracy of 88% on the test dataset. Feature importance analysis highlighted the significance of CEA levels, albumin levels, N stage, weight, platelet count, height, neutrophil count, lymphocyte count, and gender in determining recurrence risk. The integration of machine learning into healthcare, exemplified by this study's findings, offers a pathway to personalized patient risk stratification and enhanced clinical decision-making. Early identification of individuals at risk of CC recurrence holds the potential for more effective therapeutic interventions and improved patient outcomes. Machine learning has the potential to revolutionize our approach to CC recurrence prediction, emphasizing the synergy between medical expertise and cutting-edge technology in the fight against cancer. This study represents a vital step toward precision medicine in CC management, showcasing the transformative power of data-driven insights in oncology.

Analysis of risk factors for postoperative recurrence of stage I colorectal cancer: a retrospective analysis of a large population.

Colorectal cancer (CRC) is the third most common cancer worldwide. Patients diagnosed with stage I CRC typically do not require postoperative adjuvant treatment. However, postoperative recurrence is present in at least 40% of patients with CRC and often occurs in those with stage I disease. This study aimed to elucidate the current status of recurrence and clinicopathological characteristics in patients with stage I CRC. Data of indicated patients were obtained from 18 registries in Surveillance, Epidemiology, and End Results (SEER). The multivariable Fine-Gray regression model was used to identify the mortality risk of patients. Disparities in survival were analyzed using Kaplan-Meier curves. Logistic regression was employed to identify factors associated with recurrent risk overestimation. Our study indicated a recurrence rate of 15.04% (1,874/12,452) in stage I CRC cases. Notably, we identified race, age, T stage, and carcinoembryonic antigen (CEA) levels as independent risk factors for tumor recurrence, substantially impacting prognosis. Furthermore, gender, race (Black), age (>65 years), elevated CEA levels, and refusal or unknown status regarding radiotherapy significantly correlated with an adverse prognosis in patients with stage I CRC. We identified certain key clinicopathological features of patients with stage I CRC and demonstrated the survival benefits of radiotherapy, offering a new perspective on stage I CRC follow-up and treatment recommendations.