Pro-gastrin-releasing Peptide Research Articles

Human epididymal protein 4 and its combined detection show good diagnostic value in lung cancer: A retrospective study.

This study aimed to assess the diagnostic value of human epididymal protein 4 (HE4), a potential novel biomarker for lung cancer, and its combined detection with five other conventional biomarkers in lung cancer diagnosis and subtyping. In this retrospective study, 115 lung cancer patients, 50 patients with benign pulmonary disease, and 50 healthy controls were included. Serum HE4, progastrin-releasing peptide (ProGRP), squamous cell carcinoma (SCC) antigen, cytokeratin-19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and carcinoembryonic antigen (CEA) were analyzed using the electrochemiluminescence immunoassay and chemiluminescence immunoassay. The receiver operating characteristic curve was performed to analyze the diagnostic efficacy of individual biomarkers in identifying both lung cancer and its histologic subtypes. All six biomarkers showed significantly elevated levels in the lung cancer group compared to both benign pulmonary disease and control groups (P < 0.05). Among the biomarkers evaluated, HE4 exhibited the highest diagnostic performance for lung cancer, lung adenocarcinoma, and lung squamous cell carcinoma with area under the curve (AUC) values of 0.921, 0.891, and 0.937, respectively. ProGRP was the optimal biomarker for small cell lung cancer with an AUC of 0.973. The combination of all six biomarkers yielded the largest AUCs in the diagnosis of lung cancer subtypes (0.937 for lung adenocarcinoma, 0.998 for lung squamous cell carcinoma, and 0.985 for small cell lung cancer). Furthermore, specific combinations, such as HE4 + CEA, HE4 + SCC, and ProGRP + HE4 + NSE, showed strong diagnostic performance in lung cancer. HE4 and its combined detection held substantial clinical significance in the diagnosis of lung cancer and its histologic subtyping, especially for lung adenocarcinoma and lung squamous cell carcinoma.

Identification of risk factors of EGFR-TKIs primary resistance in lung adenocarcinoma patients and construction of a risk predictive model: a case-control study.

Lung cancer is one of the malignancies with the highest incidence and mortality rates. Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are recommended as the first-line treatment for patients with EGFR-mutated lung adenocarcinoma (LUAD). However, some patients with EGFR-sensitive mutations develop primary resistance to EGFR-TKIs. This study aims to analyze the clinical characteristics of LUAD patients with primary resistance to EGFR-TKIs, identify independent risk factors for primary resistance, and establish a risk predictive model to provide reference for clinical decision-making. We collected data from LUAD patients with EGFR-sensitive mutations (19del/21L858R) who were hospitalized in our institution between 2020 and 2022 and received first-generation EGFR-TKIs with follow-up exceeding 6 months. These patients were categorized into primary resistance and sensitive groups based on treatment outcomes. We compared general clinical data, laboratory tests, and tumor-related characteristics between the two groups, analyzed risk factors for primary resistance to EGFR-TKIs, and constructed a risk predictive model. The model's predictive value was comprehensively assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Serum neuron-specific enolase (NSE) concentration (P=0.03), serum pro-gastrin-releasing peptide (ProGRP) concentration (P=0.01), and Ki67 expression (P<0.001) were identified as independent risk factors for primary resistance to EGFR-TKIs in LUAD. The combined presence of these three risk factors had the highest predictive value [area under the curve (AUC) =0.975, P<0.001]. We constructed a predictive model for the risk of primary resistance to EGFR-TKIs in LUAD patients, incorporating these three parameters, and represented it through a visually interpretable nomogram. The calibration curve of the nomogram demonstrated its strong predictive ability. Further decision curve analysis indicated the model's clinical utility. Based on a single-center retrospective case-control study, we identified serum NSE concentration, ProGRP concentration, and Ki67 expression as independent risk factors for primary resistance to EGFR-TKIs in LUAD patients. We constructed and validated a risk predictive model based on these findings. This predictive model holds promise for clinical application, aiding in the development of personalized treatment strategies and providing a scientific basis for early identification of primary resistance patients.

Prognostic value of tumor markers ProGRP, NSE and CYFRA 21-1 in patients with small cell lung cancer and chemotherapy-induced remission.

Despite successful response to first line therapy, patients with small-cell lung cancer (SCLC) often suffer from early relapses and disease progression. To investigate the relevance of serum tumor markers for estimation of prognosis at several time points during the course of disease. In a prospective, single-center study, serial assessments of progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), cytokeratin-19 fragments (CYFRA 21-1) and carcino-embryogenic antigen (CEA) were performed during and after chemotherapy in 232 SCLC patients, and correlated with therapy response and overall survival (OS). ProGRP, NSE and CYFRA 21-1 levels decreased quickly after the first chemotherapy cycle and correlated well with the radiological response. Either as single markers or in combination they provided valuable prognostic information regarding OS at all timepoints investigated: prior to first-line therapy, after two treatment cycles in patients with successful response to first-line therapy, and prior to the start of second-line therapy. Furthermore, they were useful for continuous monitoring during and after therapy and often indicated progressive disease several months ahead of radiological changes. The results indicate the great potential of ProGRP, NSE and CYFRA 21-1 for estimating prognosis and monitoring of SCLC patients throughout the course of the disease.

Improved diagnostic accuracy with three lung tumor markers compared to six-marker panel.

Combining multiple tumor markers increases sensitivity for lung cancer diagnosis in the cost of false positive. However, some would like to check as many as tumor markers in the fear of missing cancer. We though to propose a panel of fewer tumor markers for lung cancer diagnosis. Patients with suspected lung cancer who simultaneously underwent all six tests [carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA), squamous cell carcinoma-associated antigen (SCC), neuron-specific enolase (NSE), pro-gastrin-releasing peptide (ProGRP), and sialyl Lewis-X antigen (SLX)] were included. Tumor markers with significant impact on the lung cancer in a logistic regression model were included in our panel. Area under the curve (AUC) was compared between our panel and the panel of all six. We included 1,733 [median 72 years, 1,128 men, 605 women, 779 (45%) confirmed lung cancer]. Logistic regression analysis suggested CEA, CYFRA, and NSE were independently associated with the lung cancer diagnosis. The panel of these three tumor markers [AUC =0.656, 95% confidence interval (CI): 0.630-0.682, sensitivity 0.650, specificity 0.662] had better (P<0.001) diagnostic performance than six tumor markers (AUC =0.575, 95% CI: 0.548-0.602, sensitivity 0.829, specificity 0.321). Compared to applying all six markers (at least one marker above the upper limit of normal), the panel with three markers (at least one marker above the upper limit of normal) led to a better predictive value by lowering the risk of false positives.

Prognostic Factors and Construction of Nomogram Prediction Model of Lung Cancer Patients Using Clinical and Blood Laboratory Parameters.

This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model. A total of 322 LC patients were taken as the study subjects. They were randomly divided into a training set (n = 202) and a validation set (n = 120). Basic information and laboratory indicators were collected, and the progression-free survival (PFS) and overall survival (OS) were followed up. Single-factor and cyclooxygenase (COX) multivariate analyses were performed on the training set to construct a Nomogram prediction model, which was validated with 120 patients in the validation set, and Harrell's consistency was analyzed. Single-factor analysis revealed significant differences in PFS (P<0.05) between genders, body mass index (BMI), carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), treatment methods, treatment response evaluation, smoking status, presence of pericardial effusion, and programmed death ligand 1 (PD-L1) at 0 and 1-50%. Significant differences in OS (P<0.05) were observed for age, tumor location, treatment methods, White blood cells (WBC), uric acid (UA), CA125, pro-gastrin-releasing peptide (ProGRP), SCCA, cytokeratin fragment 21 (CYFRA21), and smoking status. COX analysis identified male gender, progressive disease (PD) as treatment response, and SCCA > 1.6 as risk factors for LC PFS. The consistency indices of the line chart models for predicting PFS and OS were 0.782 and 0.772, respectively. Male gender, treatment response of PD, and SCCA > 1.6 are independent risk factors affecting the survival of LC patients. The PFS line chart model demonstrates good concordance.

Sensitive electrochemiluminescence immunosensor based on a novel luminescent europium metal–organic framework and antenna effect for detecting pro-gastrin-releasing peptide

Sensitive detection of pro-gastrin-releasing peptide (Pro-GRP) is crucial because it is a highly sensitive and specific tumor marker for small cell lung cancer. Herein, we synthesized an efficient luminescent europium metal–organic framework and developed a sandwich ECL immunosensor for the sensitive detection of Pro-GRP, which used Eu3+ as the central ion and 2,4,6-tri (4-carboxyphenyl)-1,3,5-triazine (H3TATB) as the organic ligand. H3TATB acted as a strong absorbing reagent and transferred its energy to Eu3+ via the antenna effect to enhance the ECL response signal of Eu3+. As per calculations, the ECL efficiency of Eu-TATB, which was a promising ECL luminophore, was up to 130 %. The Cu2O cube worked as a substrate to assist the electron transfer and was used as a co-reaction accelerator to catalyze S2O82− to produce more SO4•− and then enhance the ECL intensity of Eu-TATB. Under optimal experimental conditions, the ECL immunosensor had a linear range of 5 fg mL−1–50 ng mL−1 for detecting Pro-GRP with a detection limit of 1.6 fg mL−1; moreover, it demonstrated excellent stability and specificity and has been successfully applied for detecting Pro-GRP in the human serum.

Exploring the application value of pro-gastrin-releasing peptide in the clinical diagnosis and surgical treatment of medullary thyroid carcinoma.

To investigate the relationship between pro-gastrin-releasing peptide (ProGRP) and the clinical characteristics of patients with medullary thyroid carcinoma (MTC) and the value of ProGRP in surgical treatment monitoring. A total of 347 patients with MTC and non-MTC malignant and benign thyroid diseases were enrolled. The concentrations of neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), calcitonin (CT), and ProGRP were determined by Elecsys® assays. The NSE, CEA, CT, and ProGRP levels in different thyroid disease groups were compared, and ProGRP levels in different clinicopathological feature groups pre and postoperatively were further compared. The CT, CEA, NSE, and ProGRP levels were upregulated in the MTC group compared to those in the non-MTC malignant and benign thyroid disease groups. The area under the receiver operating characteristic curve (AUC) of ProGRP for the diagnosis of MTC was 0.832(0.787-0.871), similar to that of CT and CEA. The sensitivity and specificity were 71.4% and 92.7%, respectively, and the optimal cut-off value was 61.8 pg/mL. The AUC of ProGRP combined with CT or CEA for the diagnosis of MTC was 0.933 (0.900-0.958) and 0.922 (0.886-0.949), respectively, which were higher than those of a single index. ProGRP levels were higher in patients with lymph nodes and distant metastases than in patients without metastases. The postoperative level of ProGRP was lower than that before treatment. ProGRP is comparable to CEA and CT as an MTC biomarker with broad prospects. It has potential application value in the progression of MTC assessment and the evaluation of surgical intervention effects.

Construction of a Diagnostic Model for Small Cell Lung Cancer Combining Metabolomics and Integrated Machine Learning.

To date, no study has systematically explored the potential role of serum metabolites and lipids in the diagnosis of small cell lung cancer (SCLC). Therefore, we aimed to conduct a case-cohort study that included 191 cases of SCLC, 91 patients with lung adenocarcinoma, 82 patients with squamous cell carcinoma, and 97 healthy controls. Metabolomics and lipidomics were applied to analyze different metabolites and lipids in the serum of these patients. The SCLC diagnosis model (d-model) was constructed using an integrated machine learning technology and a training cohort (n = 323) and was validated in a testing cohort (n=138). Eight metabolites, including 1-mristoyl-sn-glycero-3-phosphocholine, 16b-hydroxyestradiol, 3-phosphoserine, cholesteryl sulfate, D-lyxose, dioctyl phthalate, DL-lactate and Leu-Phe, were successfully selected to distinguish SCLC from controls. The d-model was constructed based on these 8 metabolites and showed improved diagnostic performance for SCLC, with the area under curve (AUC) of 0.933 in the training cohort and 0.922 in the testing cohort. Importantly, the d-model still had an excellent diagnostic performance after adjusting the stage and related clinical variables and, combined with the progastrin-releasing peptide (ProGRP), showed the best diagnostic performance with 0.975 of AUC for limited-stage patients. This study is the first to analyze the difference between metabolomics and lipidomics and to construct a d-model to detect SCLC using integrated machine learning. This study may be of great significance for the screening and early diagnosis of SCLC patients.

Ribonucleotide reductase regulatory subunit M2 (RRM2) as a potential sero-diagnostic biomarker in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is a major cause of cancer-related death worldwide. Most cases are diagnosed at an advanced stage using current tumor markers. Here, we aimed to identify potential novel potential biomarkers for NSCLC. Four independent datasets from the Gene Expression Omnibus database were analyzed. The relative expression of ribonucleotide reductase regulatory subunit M2 (RRM2) mRNA in 30 paired of NSCLC paired tissues was measured by reverse transcription quantitative PCR. Serum levels of cytokeratin fragment 21-1 (CYFRA21-1), pro-gastrin-releasing peptide (ProGRP), carcinoembryonic antigen (CEA), and neuron-specific enolase (NSE) were measured using electrochemiluminescence immunoassays, and serum RRM2 levels were evaluated by an enzyme-linked immunosorbent assay. The mRNA expression level of RRM2 was significantly increased in most NSCLC lesions compared to para-adjacent tissues. Serum RRM2 levels in NSCLC patients were significantly elevated compared to healthy controls and were also associated with distant metastasis and histological type, but not with tumor size or lymph node metastasis. Receiver operating characteristic curve analysis showed a higher diagnostic ratio for NSCLC using RRM2 alone compared to other traditional tumor markers. RRM2 is a potential sero-diagnostic biomarker for NSCLC.

Clinical utility of six serum tumor markers for the diagnosis of lung cancer

AbstractBackgroundWith the increasing prevalence of lung cancer, it has become imperative to identify reliable biomarkers that can aid in early detection and prognosis assessment. Therefore, we sought to investigate the potential utility of six serum tumor markers as diagnostic and prognostic tools for lung cancer patients. By analyzing a large cohort of patients with different stages and subtypes of lung cancer, we hoped to shed light on the predictive value and accuracy of each marker individually, as well as their combined performance. This study should not only provide valuable insights into the biology and pathogenesis of lung cancer but also pave the way for personalized treatment strategies based on individual patient profiles.MethodsThe serum levels of the tumor markers progastrin‐releasing peptide (ProGRP), carcinoembryonic antigen (CEA), neuron‐specific enolase (NSE), cytokeratin 19 fragment (CYFRA21‐1), carbohydrate antigen 19‐9 (CA19‐9) and squamous cell carcinoma antigen (SCCA) were meticulously assessed in a cohort comprising 324 individuals diagnosed with lung cancer and an additional 51 patients with benign lung disease. The measurements were conducted using cutting‐edge techniques such as ELISA, electrochemical luminescence, and chemiluminescence methods. Differences between groups and the impact of these markers on lung cancer diagnosis were analyzed.ResultsThe serum levels of ProGRP, NSE, and CEA were significantly higher in lung cancer patients than in patients with benign lung disease (p &lt; 0.01). NSE had the highest sensitivity for squamous cell carcinomas (SC), while CEA had the highest sensitivity for adenocarcinomas (AC). ProGRP and NSE had higher sensitivities than other markers for small cell carcinomas (SCC). Combining the six tumor markers resulted in higher sensitivities for SC (70.6%), AC (77.4%), and SCC (80%) compared with any single test. Receiver operator characteristic analysis showed that ProGRP and NSE had a greater area under the curve (AUC) in SCC (0.886 and 0.775) than SC and AC, while CEA had a higher AUC in AC (0.716), and NSE had a higher AUC than other markers in SC (0.719).ConclusionsProGRP and NSE are effective serum tumor markers for SCC, whereas CEA and NSE may aid in the diagnosis of AC and SC. Combining the detection of ProGRP, NSE, CYFRA21‐1, CEA, and SCCA significantly improves sensitivity when diagnosing lung cancer.

Clinical Efficacy and Safety of First- or Second-Generation EGFR-TKIs after Osimertinib Resistance for EGFR Mutated Lung Cancer: A Prospective Exploratory Study.

Osimertinib monotherapy is a common treatment for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC); however, standard treatment strategies for acquired resistance to this drug have not been established. In addition, the clinical significance of first-generation (1G) or second-generation (2G) EGFR-tyrosine kinase inhibitors (TKI) in patients with EGFR-mutant NSCLC and osimertinib resistance has not yet been fully evaluated. We aimed to conduct a prospective multicenter observational study to evaluate the efficacy and safety of 1G and 2G EGFR-TKIs after the development of osimertinib resistance. Patients with EGFR-mutant NSCLC who received 1G or 2G EGFR-TKIs after developing resistance to osimertinib monotherapy were prospectively assessed at eight institutions in Japan. The primary endpoint was progression-free survival (PFS). A total of 29 patients with advanced or recurrent EGFR-mutant NSCLC were analyzed. The objective response and disease control rates were 6.9% (2/29) and 58.6% (17/29), respectively. The median PFS was 1.9 months [95% confidence interval (CI): 1.3-5.3]. There was no significant difference in PFS between the 1G and 2G EGFR-TKI groups (3.7 versus 1.5 months, log-rank test p = 0.20). However, patients with normal cytokeratin 19 fragment (CYFRA 21-1) and pro-gastrin-releasing peptide (ProGRP) levels experienced longer PFS than those with elevated CYFRA 21-1 and/or ProGRP (5.5 versus 1.3 months, log-rank test p < 0.001). Administration of 1G or 2G EGFR-TKIs after the development of osimertinib resistance has limited efficacy in patients with EGFR-mutant NSCLC. Moreover, normal CYFRA 21-1 and ProGRP levels could be promising indicators for 1G and 2G EGFR-TKI administration after osimertinib resistance development. UMIN000044049.

Association of immunotoxicological indices with lung cancer biomarkers in poultry, grape, and rose farming workers.

Exposure to occupational hazards like dust, pesticides, diesel emission particles, or physical hazards in the agricultural sector is known to cause adverse health effects on farm workers. Our study aimed at addressing the association of immunomodulatory status with plasma levels of lung cancer biomarkers in farming population, attempting to recognition of vulnerable farming group. Blood samples from apparently healthy 51 chicken husbandry, 19 grape orchard, and 21 rose greenhouse workers were subjected to evaluate plasma levels of two representative lung cancer biomarkers, pro-gastrin releasing peptide (Pro-GRP) and cytokeratin fragment 19 (CYFRA 21-1). Peripheral blood mononuclear cells obtained from farmers were used for natural killer (NK) cell phenotyping and cytokines (interferon-gamma, IFN-γ and interleukin-13, IL-13) profiling in the culture supernatant. Compared to the rose greenhouse farmers, the grape orchard and chicken husbandry workers revealed a significantly upregulated plasma Pro-GRP and CYFRA 21-1 level. A low proportion of NK cells was observed among the female grape orchard workers and a lowered IFN- γ:IL-13 ratio was seen in the grape and chicken husbandry workers than the rose workers. Our findings imply that grape orchard and chicken husbandry workers have more disturbed immune homeostasis implicated with augmentation in the levels of lung cancer biomarkers than the rose greenhouse workers.

Pro-Gastrin-Releasing Peptide as a Biomarker in Lung Neuroendocrine Neoplasm.

There is a lack of effective biomarkers for diagnosing lung neuroendocrine neoplasms (LNENs). A known small cell lung cancer (SCLC) biomarker is a pro-gastrin-releasing peptide (ProGRP), but not for all LNENs, especially for bronchopulmonary carcinoids. This study aimed to evaluate the diagnostic value of ProGRP and chromogranin A (CgA) in diagnosing LNENs. The ProGRP and CgA levels in 290 cases of LNENs and 54 healthy controls (HCs) were measured. The median ProGRP concentration in the group of LNEN patients was 136.4 pg/mL, higher than that of HCs at 6.5 pg/mL. Most of the LNEN cohort was well-differentiated tumors (typical and atypical carcinoids, n = 262, 91.7% of all LNENs). The sensitivity, specificity, and area under the curve (AUC) of ProGRP when distinguishing LNENs vs. HCs were 94.8%, 100%, and 0.995. CgA (AUC = 0.375) could not determine LNENs vs. HCs. Therefore, based on these results, ProGRP may be considered as an effective marker for diagnosing LNENs.

Extracellular Vesicles Derived circSH3PXD2A Inhibits Chemoresistance of Small Cell Lung Cancer by miR-375-3p/YAP1.

Small cell lung cancer (SCLC) is a subtype of lung cancer with high malignancy and poor prognosis. Rapid acquisition of chemoresistance is one of the main reasons leading to clinical treatment failure of SCLC. Studies have indicated that circRNAs participate in multiple processes of tumor progression, including chemoresistance. However, the molecular mechanisms of circRNAs driving the chemoresistance of SCLC are not well specified. The differentially expressed circRNAs were screened by transcriptome sequencing of chemoresistant and chemosensitive SCLC cells. The EVs of SCLC cells were isolated and identified by ultracentrifugation, Western blotting, transmission electron microscopy, nanoparticle tracking analysis and EVs uptake assays. The expression levels of circSH3PXD2A in serum and EVs of SCLC patients and healthy individuals were detected by qRT‒PCR. The characteristics of circSH3PXD2A were detected by Sanger sequencing, RNase R assay, nuclear-cytoplasmic fraction assay, and fluorescence in situ hybridization assay. The mechanisms of circSH3PXD2A inhibiting SCLC progression were studied by bioinformatics analysis, chemoresistance assay, proliferation assay, apoptosis assay, transwell assay, pull-down assay, luciferase reporting assay, and mouse xenograft assay. It was identified that the circSH3PXD2A was a prominently downregulated circRNA in chemoresistant SCLC cells. The expression level of circSH3PXD2A in EVs of SCLC patients was negatively associated with chemoresistance, and the combination of EVs-derived circSH3PXD2A and serum ProGRP (Progastrin-releasing peptide) levels had better indications for DDP-resistant SCLC patients. CircSH3PXD2A inhibited the chemoresistance, proliferation, migration, and invasion of SCLC cells through miR-375-3p/YAP1 axis in vivo and in vitro. SCLC cells cocultured with EVs secreted by circSH3PXD2A-overexpressing cells exhibited decreased chemoresistance and cell proliferation. Our results manifest that EVs-derived circSH3PXD2A inhibits the chemoresistance of SCLC through miR-375-3p/YAP1 axis. Moreover, EVs-derived circSH3PXD2A may serve as a predictive biomarker for DDP-resistant SCLC patients.

Biomarkers for Prostate Cancer Bone Metastasis Detection and Prediction.

Prostate cancer (PCa) causes deaths worldwide, ranking second after lung cancer. Bone metastasis (BM) frequently results from advanced PCa, affecting approximately 90% of patients, and it also often results in severe skeletal-related events. Traditional diagnostic methods for bone metastases, such as tissue biopsies and imaging, have substantial drawbacks. This article summarizes the significance of biomarkers in PCa accompanied with BM, including (1) bone formation markers like osteopontin (OPN), pro-collagen type I C-terminal pro-peptide (PICP), osteoprotegerin (OPG), pro-collagen type I N-terminal pro-peptide (PINP), alkaline phosphatase (ALP), and osteocalcin (OC); (2) bone resorption markers, including C-telopeptide of type I collagen (CTx), N-telopeptide of type I collagen (NTx), bone sialoprotein (BSP), tartrate-resistant acid phosphatase (TRACP), deoxypyridinoline (D-PYD), pyridoxine (PYD), and C-terminal pyridinoline cross-linked telopeptide of type I collagen (ICTP); (3) prostate-specific antigen (PSA); (4) neuroendocrine markers, such as chromogranin A (CgA), neuron-specific enolase (NSE), and pro-gastrin releasing peptide (ProGRP); (5) liquid biopsy markers, such as circulating tumor cells (CTCs), microRNA (miRNA), circulating tumor DNA (ctDNA), and cell-free DNA (cfDNA) and exosomes. In summary, some of these markers are already in widespread clinical use, while others still require further laboratory or clinical studies to validate their value for clinical application.

Evaluating the diagnostic and prognostic value of serum TuM2-PK, NSE, and ProGRP in small cell lung cancer.

The aim of this study was to explore the diagnostic and prognostic value of serum tumor M2-pyruvate kinase (TuM2-PK), neuron-specific enolase (NSE), and progastrin-releasing peptide (ProGRP) levels in patients with small cell lung cancer (SCLC). The levels of serum TuM2-PK, NSE, and ProGRP in 102 patients with SCLC, 60 patients with benign lung disease (BLD), and 90 healthy controls were detected. The serum TuM2-PK, NSE, and ProGRP levels in the SCLC group were higher than those in BLD group (p < 0.05) and healthy control group (p < 0.05). The sensitivity of TuM2-PK, NSE, and ProGRP detection in SCLC was 82.35%, 60.78%, and 77.45% respectively, and specificity was 91.11%, 81.11%, and 86.67%, respectively. The area under the curve (AUC) of SCLC resulting from TuM2-PK was significantly better than that of NSE and ProGRP. The application of TuM2-PK combined with NSE and ProGRP improved the diagnostic yield of SCLC patients and had better diagnostic value than TuM2-PK alone. Univariate and multivariate analysis indicated that an elevated TuM2-PK level was an independent prognostic factor for shorter survival in SCLC. These results suggest that TuM2-PK levels in the serum could be an effective biomarker for the diagnosis and prognosis of SCLC.

Development and validation of a nomogram model for lung cancer based on radiomics artificial intelligence score and clinical blood test data.

Artificial intelligence (AI) discrimination models using single radioactive variables in recognition algorithms of lung nodules cannot predict lung cancer accurately. Hence, we developed a clinical model that combines AI with blood test variables to predict lung cancer. Between 2018 and 2021, 584 individuals (358 patients with lung cancer and 226 individuals with lung nodules other than cancer as control) were enrolled prospectively. Machine learning algorithms including lasso regression and random forest (RF) were used to select variables from blood test data, Logistic regression analysis was used to reconfirm the features to build the nomogram model. The predictive performance was assessed by performing the receiver operating characteristic (ROC) curve analysis as well as calibration, clinical decision and impact curves. A cohort of 48 patients was used to independently validate the model. The subgroup application was analyzed by pathological diagnosis. A total of 584 patients were enrolled (358 lung cancers, 61.30%,226 patients for the control group) to establish the model. The integrated model identified eight potential factors including carcinoembryonic antigen (CEA), AI score, Pro-Gastrin Releasing Peptide (ProGRP), cytokeratin 19 fragment antigen21-1(CYFRA211), squamous cell carcinoma antigen(SCC), indirect bilirubin(IBIL), activated partial thromboplastin time(APTT) and age. The area under the curve (AUC) of the nomogram was 0.907 (95% CI, 0.881-0.929). The decision and clinical impact curves showed good predictive accuracy of the model. An AUC of 0.844 (95% CI, 0.710 - 0.932) was obtained for the external validation group. The nomogram model integrating AI and clinical data can accurately predict lung cancer, especially for the squamous cell carcinoma subtype.

A case of atypical carcinoid of the lung with abnormal elevation of plasma progastrin-releasing peptide (ProGRP)

症例は87歳女性．健診の胸部X線写真で緩徐な増大傾向を示す肺腫瘤影を主訴に当院を受診．胸部CTにて右肺S7に40 mm大の腫瘤影を認めた．腫瘍マーカーでは，ProGRPが3650 pg/mLと異常高値を示した．気管支鏡下生検で肺カルチノイドと診断した．高齢であることから消極的縮小手術として胸腔鏡下右肺S7区域切除を施行した．摘出標本の病理検査で最終的に異型カルチノイドと診断した．ProGRPは術後基準値範囲内まで低下を認め，術後18ヵ月経過して無再発生存中である．肺カルチノイドでProGRP高値症例は報告されているが，検索した限りでは自験例は報告例のうち最も高値であった．さらに肺カルチノイドにおいてProGRPが治療効果判定に有用である可能性が示唆された．

Clinicopathological features and prognosis of primary pulmonary rhabdomyosarcoma in middle-aged and elderly patients: a case report and literature review

To date, only 34 cases of primary pulmonary rhabdomyosarcoma (PPRMS) in the middle-aged and elderly population have been published. However, analyses of the clinicopathological characteristics and prognosis of PPRMS in this population have not been performed. A 75-year-old man visited our hospital because of abdominal pain and discomfort. His serum lactate dehydrogenase, neuron specific enolase, and progastrin-releasing peptide levels were elevated. Positron emission tomography-computed tomography revealed a lobulated mass of 7.6 × 5.5 cm2 in the lower lobe of the left lung with abnormally high fluoro-2-deoxy-d-glucose metabolism. Histologically, the tumor cells were small with little cytoplasm, deep nuclear staining, and heavily stained nuclear chromatin. Immunohistochemically, the tumor cells were positive for desmin, MyoD1 myogenin, synaptophysin, and CD56. Cytogenetic analysis for FOXO1A translocation was negative. Finally, the patient was diagnosed with PPRMS. He received combined chemotherapy with vincristine 1 mg, actinomycin 0.4 mg, cyclophosphamide 0.8 mg; however, only one course of chemotherapy was completed, and the patient died 2 months after diagnosis. PPRMS in middle-aged and elderly people is a highly malignant soft tissue tumor with significant clinicopathological characteristics.

Detection of Changes in CEA and ProGRP Levels in BALF of Patients with Peripheral Lung Cancer and the Relationship with CT Signs.

To investigate the relationship between the detection of changes in the levels of carcinoembryonic antigen (CEA) and progastrin-releasing peptide (ProGRP) in bronchoalveolar lavage fluid (BALF) and CT signs in patients with peripheral lung cancer. Retrospective analysis of 108 patients with perihilar lung cancer who attended our hospital from January 2019 to January 2022, 54 cases were randomly selected as the observation group and 50 cases as the control group. Patients in both groups received CT examination and BALF test at the same time to observe and compare the differences in serum levels, the relationship between CT signs and serum indices, and the diagnostic value of peripheral lung cancer between the two groups. The serum levels of ProGrp, CEA, CA211, and NSE in the observation group were significantly higher than those in the control group, and the difference was statistically significant (P < 0.05). The morphology, density, mass enhancement pattern, bronchial morphology, obstructive signs, and lymph node fusion of CT signs were compared between the observation group and the control group, indicating that CT signs were more helpful for the localization, diagnosis, and staging of lung cancer. The results of ROC curve analysis showed that the AUC value of low-dose CT combined with serum ProGrp, CEA, CA211, and NSE was 0.892, sensitivity was 96.21%, and specificity of 90.05%, which were significantly higher than those of the single tests, respectively. The positive likelihood ratio was 84.41% and the negative likelihood ratio was 87.11%. The combination of CT signs and serum tumour markers helps to improve the detection rate, sensitivity, and specificity of lung cancer, which has a high diagnostic rate for lung cancer and may provide evidence for the early diagnosis of lung cancer.