Clinical Evaluation of Serum Tumor Markers in the Diagnosis of Gastric Adenocarcinoma Staging and Grading. J Gastrointest Cancer. 2019;50:525-529. [PMID: 29806060 DOI: 10.1007/s12029-018-0091-6]

PG I and PG II show unique value in diagnosing postoperative biochemical recurrence in patients with gastric cancer after total gastrectomy

OBJECTIVE

To investigate the potential of group I pepsinogen (PG I) and group II pepsinogen (PG II) as diagnostic markers for recurrence in gastric cancer (GC) patients post-total gastrectomy.

METHODS

Ninety-six patients who underwent total gastrectomy for GC between June 2022 and June 2023 were included in this study. Clinical data, serum samples, and ascites samples were collected. Patients were categorized based on recurrence status at the time of sample collection and the primary tumor site. PG I and PG II levels were determined using a chemiluminescent immunoassay, and their clinical utility following total gastrectomy for GC was evaluated via receiver operating characteristic (ROC) curve analysis.

RESULTS

This study included 96 GC patients who underwent total gastrectomy, 55 of whom experienced postoperative recurrence (57.29%). The levels of serum PG I (27.86 (27.04, 30.97) vs. 26.05 (24.16, 27.09) ng/mL; P < 0.0001) and PG II (1.95 (1.23, 3.05) vs. 0.63 (0.47, 0.90) ng/mL; P < 0.0001) were significantly greater in the recurrent group compared to the non-recurrent group. The secretion of PG I and/or PG II by metastatic cancer cells correlated with the primary lesion site. When the cut-off value for serum PG I was 26.93 ng/mL, the area under the curve (AUC) for PG I was 0.77. When the cut-off value for serum PG II was 0.96 ng/mL, the AUC reached 0.90. The combined AUC was 0.97.

CONCLUSION

These findings suggest that serum PG I and PG II are valuable biomarkers for identifying GC patients with biochemical recurrence post-total gastrectomy.

Quantitative Detection of Gastrointestinal Tumor Markers Using a Machine Learning Algorithm and Multicolor Quantum Dot Biosensor

This work was to explore the application value of gastrointestinal tumor markers based on gene feature selection model of principal component analysis (PCA) algorithm and multicolor quantum dots (QDs) immunobiosensor in the detection of gastrointestinal tumors. Based on the PCA method, the neighborhood rough set algorithm was introduced to improve it, and the tumor gene feature selection model (OPCA) was established to analyze its classification accuracy and accuracy. Four kinds of coupled biosensors were fabricated based on QDs, namely, 525 nm Cd Se/Zn S QDs-carbohydrate antigen 125 (QDs525-CA125 McAb), 605 nm Cd Se/Zn S QDs-cancer antigen 19-9 (QDs605-CA19-9 McAb), 645 nm Cd Se/Zn S QDs-anticancer embryonic antigen (QDs 645-CEA McAb), and 565 nm Cd Se/Zn S QDs-anti-alpha-fetoprotein (QDs565-AFP McAb). The quantum dot-antibody conjugates were identified and quantified by fluorescence spectroscopy and ultraviolet absorption spectroscopy. The results showed that the classification precision of OPCA model in colon tumor and gastric cancer datasets was 99.52% and 99.03%, respectively, and the classification accuracy was 94.86% and 94.2%, respectively, which were significantly higher than those of other algorithms. The fluorescence values of AFP McAb, CEA McAb, CA19-9 McAb, and CA125 McAb reached the maximum when the conjugation concentrations were 25 µg/mL, 20 µg/mL, 30 µg/mL, and 30 µg/m, respectively. The highest recovery rate of AFP was 98.51%, and its fluorescence intensity was 35.78 ± 2.99, which was significantly higher than that of other antigens (P < 0.001). In summary, the OPCA model based on PCA algorithm can obtain fewer feature gene sets and improve the accuracy of sample classification. Intelligent immunobiosensors based on machine learning algorithms and QDs have potential application value in gastrointestinal gene feature selection and tumor marker detection, which provides a new idea for clinical diagnosis of gastrointestinal tumors.

Application of Surface-Enhanced Raman Spectroscopy in the Screening of Pulmonary Adenocarcinoma Nodules

This study is aimed at evaluating the feasibility of a screening method for the pulmonary adenocarcinoma nodules through surface-enhanced Raman spectroscopy (SERS). Objective. Using SERS to measure serum from pulmonary nodules and healthy subjects, intraoperative biopsy pathological diagnosis was regarded as the gold standard for labeling serum samples. To explore the application value of SERS in the differential diagnosis of pulmonary adenocarcinoma nodules, benign nodules, and healthy, we build a machine learning model. Method. We collected 116 serum samples from patients. Radiographically confirmed nodules less than 3 cm in maximum diameter in all patients, including 58 cancer (pathologic diagnosis: adenocarcinoma nodules, labeled as cancer) patients, 58 pathologic diagnoses as benign nodule (labeled as benign) patients, and 63 healthy (labeled as normal) people from the clinical laboratory of Sichuan Cancer Hospital. Gold nanorods were employed as SERS substrates. Support vector machine (SVM) was used to classify the normal, benign, and cancer sample groups, and SVM model evaluated using cross-validation. Results. The average SERS spectra of serum were significantly different between the normal group and the cancer/benign group. While the average SERS spectra of the cancer group and the benign group differed slightly, for the cancer, benign, and normal groups, SVM models can predict with 93.33% accuracy. Conclusion. This exploratory study demonstrates that the SERS technique based on nanoparticles in conjunction with SVM has great potential as a clinical auxiliary diagnosis and screening for pulmonary adenocarcinoma nodules.

An Immaculate Deception: Persistently Elevated Serum β-Hcg in Metastatic Signet Ring Cell Gastric Adenocarcinoma

BACKGROUND

Persistent elevations in beta-human chorionic gonadotropin (β-hCG) can be an ominous sign of both trophoblastic and non-trophoblastic malignancies. The absence of a clearly identified etiology of β-hCG elevation warrants pursuit of further diagnostic testing to determine the source of ectopic β-hCG.

CASE REPORT

A virginal 26-year-old woman with past medical history significant for persistently elevated β-hCG presented to our Emergency Department with shortness of breath, pleuritic chest pain, nausea, and vomiting, and was found to have widely metastatic gastric signet ring cell adenocarcinoma. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Although elevated serum β-hCG is a generally a marker of pregnancy, β-hCG elevation without clear etiology necessitates ruling out other insidious processes. Failure to maintain and pursue a broad differential in the context of unexplained elevations of β-hCG can result in catastrophic missed or delayed diagnosis.

A presumed extragonadal germ cell tumor that turned out to be a gastric cancer-a case report

A solely retroperitoneal mass in males in combination with elevated serum Alpha-Fetoprotein (AFP) and beta-human choriogonadotropin (β-HCG) levels is highly indicative of a metastatic testicular cancer. Although testicular cancers are rare, they represent the most common diagnosed cancer in males between 14 and 40 years. However, in cases without evidence of a primary testicular tumor, the rare diagnosis of a retroperitoneal extragonadal germ cell tumor (EGCT) must be assumed. Here, we describe the first published case of a 66-year-old man presenting with this typical clinical picture and the diagnosis of an AFP and β-HCG producing advanced gastric cancer with retroperitoneal lymph node metastases mimicking a primary retroperitoneal EGCT. The final diagnosis was only made by gastroscopy performed after a CT-guided retroperitoneal lymph node biopsy revealed an adenocarcinoma, suggesting an upper gastrointestinal tract primary origin. However, a specific initial anamnesis and also in the primary staging, including a full-body CT-scan there was no hint for another primary tumor. Only the slightly unusual extension of the retroperitoneal mass up to the ligamentum hepatoduodenale and the pylorus, as well as the atypical age made us question our initial diagnosis. This extraordinary case is of special clinical interest to all practising physicians and once again highlights the importance of keeping rare differential diagnosis such as AFP-producing gastrointestinal tumors in mind.

Establishment and validation of a nomogram to predict the risk of ovarian metastasis in gastric cancer: Based on a large cohort

BACKGROUND

Ovarian metastasis is a special type of distant metastasis unique to female patients with gastric cancer. The pathogenesis of ovarian metastasis is incompletely understood, and the treatment options are controversial. Few studies have predicted the risk of ovarian metastasis. It is not clear which type of gastric cancer is more likely to metastasize to the ovary. A prediction model based on risk factors is needed to improve the rate of detection and diagnosis.

AIM

To analyze risk factors of ovarian metastasis in female patients with gastric cancer and establish a nomogram to predict the probability of occurrence based on different clinicopathological features.

METHODS

A retrospective cohort of 1696 female patients with gastric cancer between January 2006 and December 2017 were included in a single center, and patients with distant metastasis other than ovary and peritoneum metastasis were excluded. Potential risk factors for ovarian metastasis were analyzed using univariate and multivariable logistic regression. Independent risk factors were chosen to construct a nomogram which received internal validation.

RESULTS

Ovarian metastasis occurred in 83 of 1696 female patients. Univariate analysis showed that age, Lauren type, whether the primary lesion contained signet-ring cells, vascular tumor emboli, T stage, N stage, the expression of estrogen receptor, the expression of progesterone receptor, serum carbohydrate antigen 125 and the neutrophil-to-lymphocyte ratio were risk factors for ovarian metastasis of gastric cancer (all P < 0.05). Multivariate analysis showed that age ≤ 50 years, Lauren typing of non-intestinal, gastric cancer lesions containing signet-ring cell components, N stage > N2, positive expression of estrogen receptor, serum carbohydrate antigen 125 > 35 U/mL, and a neutrophil-to-lymphocyte ratio > 2.16 were independent risk factors (all P < 0.05). The independent risk factors were constructed into a nomogram model using R language software. The consistency index after continuous correction was 0.840 [95% confidence interval: (0.774-0.906)]. After the internal self-sampling (Bootstrap) test, the calibration curve of the model was obtained with an average absolute error of 0.007. The receiver operating characteristic curve of the obtained model was drawn. The area under the curve was 0.867, the maximal Youden index was 0.613, the corresponding sensitivity was 0.794, and the specificity was 0.819.

CONCLUSION

The nomogram model performed well in the prediction of ovarian metastasis. Attention should be paid to the possibility of ovarian metastasis in high-risk populations during re-examination, to ensure early detection and treatment.