High-Throughput Metabolic Pattern Screening Strategy for Early Colorectal and Gastric Cancers Based on Covalent Organic Frameworks-Assisted Laser Desorption/Ionization Mass Spectrometry.

Precise early diagnosis and staging are conducive to improving the prognosis of colorectal cancer (CRC) and gastric cancer (GC) patients. However, due to intrusive inspections and limited sensitivity, the prevailing diagnostic methods impede precisely large-scale screening. In this work, we reported a high-throughput serum metabolic patterns (SMP) screening strategy based on covalent organic frameworks-assisted laser desorption/ionization mass spectrometry (hf-COFsLDI-MS) for early diagnosis and staging of CRC and GC. Notably, 473 high-quality SMP were extracted without any tedious sample pretreatment and coupled with multiple machine learning algorithms; the area under the curve (AUC) value is 0.938 with 96.9% sensitivity for early CRC diagnosis, and the AUC value is 0.974 with 100% sensitivity for early GC diagnosis. Besides, the discrimination of CRC and GC is accomplished with an AUC value of 0.966 for the validation set. Also, the screened-out features were identified by MS/MS experiments, and 8 metabolites were identified as the biomarkers for CRC and GC. Finally, the corresponding disordered metabolic pathways were revealed, and the staging of CRC and GC was completed. This work provides an alternative high-throughput screening strategy for CRC and GC and highlights the potential of metabolic molecular diagnosis in clinical applications.

Blood-Based Multiomics-Guided Detection of a Precancerous Pancreatic Tumor.

Over a decade ago, longitudinal multiomics analysis was pioneered for early disease detection and individually tailored precision health interventions. However, high sample processing costs, expansive multiomics measurements along with complex data analysis have made this approach to precision/personalized medicine impractical. Here we describe in a case report, a more practical approach that uses fewer measurements, annual sampling, and faster decision making. We also show how this approach offers promise to detect an exceedingly rare and potentially fatal condition before it fully manifests. Specifically, we describe in the present case report how longitudinal multiomics monitoring (LMOM) helped detect a precancerous pancreatic tumor and led to a successful surgical intervention. The patient, enrolled in an annual blood-based LMOM since 2018, had dramatic changes in the June 2021 and 2022 annual metabolomics and proteomics results that prompted further clinical diagnostic testing for pancreatic cancer. Using abdominal magnetic resonance imaging, a 2.6 cm lesion in the tail of the patient's pancreas was detected. The tumor fluid from an aspiration biopsy had 10,000 times that of normal carcinoembryonic antigen levels. After the tumor was surgically resected, histopathological findings confirmed it was a precancerous pancreatic tumor. Postoperative omics testing indicated that most metabolite and protein levels returned to patient's 2018 levels. This case report illustrates the potentials of blood LMOM for precision/personalized medicine, and new ways of thinking medical innovation for a potentially life-saving early diagnosis of pancreatic cancer. Blood LMOM warrants future programmatic translational research with the goals of precision medicine, and individually tailored cancer diagnoses and treatments.

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

INTRODUCTION: We 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 METHODS: Patients 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. RESULTS: 153 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). CONCLUSION: The 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.

Increased level of serum leucine-rich-alpha-2-glycoprotein 1 in patients with clear cell renal cell carcinoma.

BACKGROUND: Currently, no useful serum markers exist for clear cell renal cell carcinoma (ccRCC), making early detection challenging as diagnosis relies solely on imaging tests. Radiation exposure is also a concern due to multiple required CT examinations during treatment. Renal cell carcinoma (RCC) histological types include ccRCC and non-clear cell RCC (non-ccRCC); however, treatment response to medications varies which necessitates accurate differentiation between the two. Therefore, we aimed to identify a novel serum marker of RCC. Increased LRG1 expression in the serum has been demonstrated in multiple cancer types. However, the expression of LRG1 expression in the serum and cancer tissues of patients with RCC has not been reported. Since ccRCC is a hypervascular tumor and LRG1 is capable of accelerating angiogenesis, we hypothesized that the LRG1 levels may be related to ccRCC. Therefore, we examined LRG1 expression in sera from patients with RCC. METHODS: Using an enzyme-linked immunosorbent assay, serum levels of leucine-rich-alpha-2-glycoprotein 1 (LRG1) were measured in 64 patients with ccRCC and 22 patients non-ccRCC who underwent radical or partial nephrectomy, as well as in 63 patients without cancer. RESULTS: Median values of serum LRG1 and their inter-quartile ranges were 63.2 (42.8-94.2) µg/mL in ccRCC, 23.4 (17.7-29.6) µg/mL in non-ccRCC, and 36.0 (23.7-56.7) µg/mL in patients without cancer, respectively (ccRCC vs. non-ccRCC or patients without cancer: P < 0.001). C-reactive protein (CRP) levels (P = 0.002), anemia (P = 0.037), hypercalcemia (P = 0.023), and grade (P = 0.031) were independent predictors of serum LRG1 levels in ccRCC. To assess diagnostic performance, the area under the receiver operating characteristic curve of serum LRG1 was utilized to differentiate ccRCC from non-cancer and non-ccRCC, with values of 0.73 (95% CI, 0.64-0.82) and 0.91 (95% CI, 0.82-0.96), respectively. CONCLUSIONS: LRG1 served as a serum marker associated with inflammation, indicated by CRP, anemia, hypercalcemia, and malignant potential in ccRCC. Clinically, serum LRG1 levels may assist in differentiating ccRCC from non-ccRCC with excellent diagnostic accuracy.

Clinical value of KiSS-1 and MMP-2 expression levels in breast cancer tissue in evaluating prognosis of elderly breast cancer patients after modified radical mastectomy.

We attempted to clarify clinical value of KiSS-1 and MMP-2 levels in breast cancer (BC) tissue in evaluating prognosis of elderly BC patients after modified radical mastectomy (MCM). The data of 192 elderly female BC patients receiving MCM in our hospital from January 2018 to December 2022 were collected. According to prognosis, patients received division into poor prognosis group (n = 43) and good prognosis group (n = 149). The serum CEA level and KiSS-1 and MMP-2 levels in BC tissue received measurement in both groups. The predictive value of KiSS-1 and MMP-2 alone and jointly in adverse prognosis of elderly BC patients after MCM received assessment. Results showed that No statistical significance was exhibited between both groups in general data (P > 0.05). The serum CEA level and MMP-2 expression in BC tissue in poor prognosis group exhibited elevation relative to those in good prognosis group, and KiSS-1 expression in BC tissue in poor prognosis group exhibited depletion relative to that in good prognosis group, indicating statistical significance (P < 0.05). The high-level KiSS-1 might be a protective element for adverse prognosis of elderly BC patients after MCM, and high-level CEA and MMP-2 might be an independent risk element for adverse prognosis of elderly BC patients after MCM (P < 0.05). KiSS-1 and MMP-2 alone and jointly predicted AUC of adverse prognosis in elderly BC patients after MCM were 0.93, 0.802 and 0.958, with certain predictive values; when cutoff values of KiSS-1 and MMP-2 were 6.15 and 2.26, the predictive value was the best. In conclusion, KiSS-1 and MMP-2 levels in BC tissue possess relation to adverse prognosis of MCM. KiSS-1 and MMP-2 levels in elderly BC patients before surgery may be detected in the future to assist in prognosis evaluation of elderly BC patients after MCM.

Application value of the automated machine learning model based on modified CT index combined with serological indices in the early prediction of lung cancer.

Background and objective: Accurately predicting the extent of lung tumor infiltration is crucial for improving patient survival and cure rates. This study aims to evaluate the application value of an improved CT index combined with serum biomarkers, obtained through an artificial intelligence recognition system analyzing CT features of pulmonary nodules, in early prediction of lung cancer infiltration using machine learning models. Patients and methods: A retrospective analysis was conducted on clinical data of 803 patients hospitalized for lung cancer treatment from January 2020 to December 2023 at two hospitals: Hospital 1 (Affiliated Changshu Hospital of Soochow University) and Hospital 2 (Nantong Eighth People's Hospital). Data from Hospital 1 were used for internal training, while data from Hospital 2 were used for external validation. Five algorithms, including traditional logistic regression (LR) and machine learning techniques (generalized linear models [GLM], random forest [RF], gradient boosting machine [GBM], deep neural network [DL], and naive Bayes [NB]), were employed to construct models predicting early lung cancer infiltration and were analyzed. The models were comprehensively evaluated through receiver operating characteristic curve (AUC) analysis based on LR, calibration curves, decision curve analysis (DCA), as well as global and individual interpretative analyses using variable feature importance and SHapley additive explanations (SHAP) plots. Results: A total of 560 patients were used for model development in the training dataset, while a dataset comprising 243 patients was used for external validation. The GBM model exhibited the best performance among the five algorithms, with AUCs of 0.931 and 0.99 in the validation and test sets, respectively, and accuracies of 0.857 and 0.955 in the validation and test groups, respectively, outperforming other models. Additionally, the study found that nodule diameter and average CT value were the most significant features for predicting lung cancer infiltration using machine learning models. Conclusion: The GBM model established in this study can effectively predict the risk of infiltration in early-stage lung cancer patients, thereby improving the accuracy of lung cancer screening and facilitating timely intervention for infiltrative lung cancer patients by clinicians, leading to early diagnosis and treatment of lung cancer, and ultimately reducing lung cancer-related mortality.

Comprehensive genomic profiling of pulmonary spindle cell carcinoma using tissue and plasma samples: insights from a real-world cohort analysis.

Pulmonary spindle cell carcinoma (PSCC) is a rare and aggressive non-small cell lung cancer (NSCLC) subtype with a dismal prognosis. The molecular characteristics of PSCC are largely unknown due to its rarity, which limits the diagnosis and treatment of this historically poorly characterized malignancy. We present comprehensive genomic profiling results of baseline tumor samples from 22 patients histologically diagnosed with PSCC, representing the largest cohort to date. Somatic genetic variant detection was compared between paired plasma samples and primary tumors from 13 patients within our cohort. The associations among genomic features, treatment, and prognosis were also analyzed in representative patient cases. TP53 (54.5%), TERT (36.4%), CDKN2A (27.3%), and MET (22.7%) were most frequently mutated. Notably, 81.8% of patients had actionable targets in their baseline tumors, including MET (22.7%), ERBB2 (13.6%), EGFR (9.1%), KRAS (9.1%), ALK (9.1%), and ROS1 (4.5%). The median tumor mutation burden (TMB) for PSCC tumors was 5.5 mutations per megabase (muts/Mb). TMB-high tumors (>10 muts/Mb) exhibited a significantly higher mutation frequency in genes such as KRAS, ARID2, FOXL2, and LRP1B, as well as within the DNA mismatch repair pathway. The detection rates for single nucleotide variants and structural variants were comparable between matched tumor and plasma samples, with 48.6% of genetic variants being mutually identified in both sample types. Additionally, a patient with a high mutation load and positive PD-L1 expression demonstrated a 7-month survival benefit from chemoimmunotherapy. Furthermore, a patient with an ALK-rearranged tumor achieved a remarkable 3-year progression-free survival following crizotinib treatment. Overall, our findings deepen the understanding of the complex genomic landscape of PSCC, revealing actionable targets amenable to tailored treatment of this poorly characterized malignancy.

Evaluation of the preoperative neutrophil-to-lymphocyte ratio as a predictor of the micropapillary component of stage IA lung adenocarcinoma.

OBJECTIVE: To assess the ability of markers of inflammation to identify the solid or micropapillary components of stage IA lung adenocarcinoma and their effects on prognosis. METHODS: We performed a retrospective study of clinicopathologic data from 654 patients with stage IA lung adenocarcinoma collected between 2013 and 2019. Logistic regression analysis was used to identify independent predictors of these components, and we also evaluated the relationship between markers of inflammation and recurrence. RESULTS: Micropapillary-positive participants had high preoperative neutrophil-to-lymphocyte ratios. There were no significant differences in the levels of markers of systemic inflammation between the participants with or without a solid component. Multivariate analysis showed that preoperative neutrophil-to-lymphocyte ratio (odds ratio [OR] = 2.094; 95% confidence interval [CI], 1.668-2.628), tumor size (OR = 1.386; 95% CI, 1.044-1.842), and carcinoembryonic antigen concentration (OR = 1.067; 95% CI, 1.017-1.119) were independent predictors of a micropapillary component. There were no significant correlations between markers of systemic inflammation and the recurrence of stage IA lung adenocarcinoma. CONCLUSIONS: Preoperative neutrophil-to-lymphocyte ratio independently predicts a micropapillary component of stage IA lung adenocarcinoma. Therefore, the potential use of preoperative neutrophil-to-lymphocyte ratio in the optimization of surgical strategies for the treatment of stage IA lung adenocarcinoma should be further studied.

Bridging horizons beyond CIRCULATE-Japan: a new paradigm in molecular residual disease detection via whole genome sequencing-based circulating tumor DNA assay.

Circulating tumor DNA (ctDNA) is the fraction of cell-free DNA in patient blood that originates from a tumor. Advances in DNA sequencing technologies and our understanding of the molecular biology of tumors have increased interest in exploiting ctDNA to facilitate detection of molecular residual disease (MRD). Analysis of ctDNA as a promising MRD biomarker of solid malignancies has a central role in precision medicine initiatives exemplified by our CIRCULATE-Japan project involving patients with resectable colorectal cancer. Notably, the project underscores the prognostic significance of the ctDNA status at 4 weeks post-surgery and its correlation to adjuvant therapy efficacy at interim analysis. This substantiates the hypothesis that MRD is a critical prognostic indicator of relapse in patients with colorectal cancer. Despite remarkable advancements, challenges endure, primarily attributable to the exceedingly low ctDNA concentration in peripheral blood, particularly in scenarios involving low tumor shedding and the intrinsic error rates of current sequencing technologies. These complications necessitate more sensitive and sophisticated assays to verify the clinical utility of MRD across all solid tumors. Whole genome sequencing (WGS)-based tumor-informed MRD assays have recently demonstrated the ability to detect ctDNA in the parts-per-million range. This review delineates the current landscape of MRD assays, highlighting WGS-based approaches as the forefront technique in ctDNA analysis. Additionally, it introduces our upcoming endeavor, WGS-based pan-cancer MRD detection via ctDNA, in our forthcoming project, SCRUM-Japan MONSTAR-SCREEN-3.

Association of Preoperative and Postoperative Plasma Syndecan-1 and Colorectal Cancer Outcome.

BACKGROUND/AIM: A three-dimensional network constructed using glycocalyx (GCX) extends throughout the cancer cell nest in human colorectal cancer (CRC). GCX was found to be closely related to cancer. We examined the prognostic correlation and potential of syndecan-1 (SDC1), a representative proteoglycan of GCX, as a biomarker. PATIENTS AND METHODS: We analyzed SDC1 in the transcriptomic profiles of a major publicly available CRC cohort from The Cancer Genome Atlas (TCGA) using a computational algorithm. We investigated serum SDC1 levels preoperatively and on postoperative day seven in 48 patients with stage I-III CRC who underwent surgery during July-December 2019 at Gifu University Hospital. RESULTS: For TCGA, no significant differences existed between the high and low SDC1 expression groups regarding disease-free, disease-specific, and overall survival for stage I-III, and only overall survival for stage IV was significantly different. In our study, among the 48 patients, 17 (no recurrence), 13 (1 recurrence), and 18 (10 recurrences) had stage I-III, respectively. Preoperative and postoperative day 7 SDC1 levels for patients with stage I-III were 10.7±2.3 and 9.9±3.1 ng/ml (p=0.40), 11.1±1.7 and 10.1±0.8 ng/ml (p=0.07), and 10.3±2.0 and 9.5±1.4 ng/ml (p=0.15), respectively. In stage II and III, patients were divided into two groups according to differences between preoperative and postoperative SDC1 levels (SDC1pre-pro). SDC1pre-pro ≤0 group significantly prolonged disease-free survival compared with SDC1pre-pro >0 group (p=0.048). CONCLUSION: Dynamic change in serum SDC1 levels serves as a prognostic biomarker for stage II and III colorectal cancer.

The Utility of Serum Alpha-fetoprotein for Monitoring for Relapse of Alpha-fetoprotein-Positive Hepatoblastoma.

Hepatoblastoma is the most common liver malignancy in children. Treatment typically involves surgery and cisplatin-based chemotherapy. After therapy completion, children undergo repetitive surveillance imaging to screen for relapse, which occurs in <12% of cases. Monitoring for relapse has gradually shifted to serial determination of serum alpha-fetoprotein (AFP) alone as most cases have AFP elevation at the time of relapse. Little primary data supports, such a practice, however, and herein we present both our institutional experience with relapsed hepatoblastoma and a careful review of published literature on this topic. While serial AFP monitoring may suffice for most patients, certain clinical characteristics should give pause to the practitioner, when considering posttreatment monitoring with serum AFP alone.

Clinical value of serum DJ-1 in lung adenocarcinoma.

Objective: DJ-1 is an oncoprotein secreted by cancer cells. However, the physiological and pathological significance of DJ-1 secretion is not clearly understood. This study investigated the clinical value of serum DJ-1 in lung adenocarcinoma (LUAD). Methods: The study involved 224 LUAD patients, 110 patients with benign pulmonary disease and 100 healthy controls from the First Affiliated Hospital of Nanjing Medical University. We detected the expression of DJ-1 in lung cell lines in vitro. Meanwhile, serum concentrations of DJ-1, carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), and cytokeratin 19 fragment (CYFRA21-1) were measured. The diagnostic performance of LUAD was obtained using receiver operating characteristic (ROC) curves. Kaplan-Meier, univariate and multivariate Cox regression analyses were performed for progression-free survival (PFS). Results: DJ-1 was highly expressed in LUAD cell lines. Serum DJ-1 levels were significantly higher in the LUAD group compared to the benign pulmonary disease group (5.04 vs. 3.66 ng/mL, P < 0.001) and healthy controls (5.04 vs. 3.51 ng/mL, P < 0.001). DJ-1 levels were associated with gender (P = 0.002), smoking history (P = 0.042) and lymph node metastasis (P = 0.040). ROC curve analysis of DJ-1 revealed an area under the curve (AUC) of 0.758 (95% CI [0.714-0.803], P < 0.001) with a sensitivity of 63.8% and specificity of 78.6% at a cutoff value of 4.62 ng/mL for the detection of LUAD. Univariate and multivariate analyses confirmed that the preoperative serum DJ-1 level, tumor stage and smoking history were independent prognostic factors of PFS. Conclusion: Our study is the first to explore the clinical value of serum DJ-1 in LUAD comprehensively. Serum DJ-1 could be a potential diagnostic and prognostic biomarker for LUAD.

Priming agents transiently reduce the clearance of cell-free DNA to improve liquid biopsies.

Liquid biopsies enable early detection and monitoring of diseases such as cancer, but their sensitivity remains limited by the scarcity of analytes such as cell-free DNA (cfDNA) in blood. Improvements to sensitivity have primarily relied on enhancing sequencing technology ex vivo. We sought to transiently augment the level of circulating tumor DNA (ctDNA) in a blood draw by attenuating its clearance in vivo. We report two intravenous priming agents given 1 to 2 hours before a blood draw to recover more ctDNA. Our priming agents consist of nanoparticles that act on the cells responsible for cfDNA clearance and DNA-binding antibodies that protect cfDNA. In tumor-bearing mice, they greatly increase the recovery of ctDNA and improve the sensitivity for detecting small tumors.

Prognostic Nutritional Index as a Prognostic Factor for Very Early-Stage Hepatocellular Carcinoma.

INTRODUCTION: Field factors play more important roles in predicting the outcomes of patients compared with tumor factors in early-stage hepatocellular carcinoma (HCC). However, the prognostic ability of noninvasive serum marker scores for hepatic fibrosis and liver functional reserve on very early-stage HCC is still not yet determined. We aimed to investigate the performance of these serum marker scores in predicting the prognoses of patients with very early-stage HCC. METHODS: A total of 446 patients with very early-stage HCC from 2012 to 2022 were retrospectively enrolled. Serum biomarkers and prognostic scores determining overall survival (OS) were analyzed by Cox proportional hazards model. We compared the Akaike information criterion among the prognostic nutritional index (PNI), aspartate aminotransferase-to-platelet ratio index, albumin-bilirubin (ALBI) score, EZ (easy)-ALBI score, modified ALBI score, fibrosis-4 score, and lymphocyte-to-monocyte ratio to determine the predictability on the OS. RESULTS: After a median follow-up of 41.0 months (interquartile range 36.9-45.1 months), 81 patients died, with a 5-year OS rate of 71.0%. Among the noninvasive serum marker scores, PNI had the best performance in predicting the OS with the lowest Akaike information criterion (846.407) compared with other scores. Moreover, we stratified the patients into high-risk (PNI <45) and low-risk (PNI ≥45) groups. It showed that the 5-year OS rates were 83.4% and 60.8% in the low-risk and high-risk PNI groups, respectively ( P < 0.001). DISCUSSION: PNI had the best performance in predicting the OS for patients with very early-stage HCC.

Surpassing sensitivity limits in liquid biopsy.

Attenuation of cell-free DNA clearance in vivo is an alternative strategy to maximize recovery.

Ag nanorod@PEI-Ag nanohybrid as an excellent signal label for sensitive and rapid detection of serum HER2.

The accurate detection of Human epidermal growth factor receptor-2 (HER2) as a critical breast cancer biomarker can be essential for the early selection of therapeutic approaches. HER2 is a prominent component of a signaling network. Overexpression of the HER2 protein due to amplification of its gene leads to the development of an aggressive subtype of breast cancer. Patients with tumors that overexpress HER2 are eligible for treatment that significantly reduces mortality rates. Herein, we present a fast and simple method for detecting serum HER2. A new electrochemical label has been developed using charged Ag nanorod@ polyethylenimine-Ag (Ag NR@ PEI-Ag) nanohybrid. The synthesized Ag NR@PEI-Ag nanohybrid simultaneously has the electroactive property of silver and the large surface area of the PEI, which results in the enhancement of the detection signal. So, using Ag NR@PEI-Ag nanohybrid as the electrochemical label, a simple, fast, and sensitive electrochemical biosensor was designed to detect HER2. This way, after immobilizing HER2 aptamer on the Au electrode surface, HER2 or human serum was exposed to the aptamer. Then, the positively charged Ag NR@PEI-Ag nanohybrid was adsorbed onto the negatively charged aptamer-HER2 complex, and the current that was produced due to the Ag/AgCl reaction was measured as the electrochemical signal. The aptasensor shows a broad linear response from 10-12 to 10-7 g, a low detection limit (LOD) of 10 pg, and a total assay time of ~ 30 min.

SPP1 is associated with adverse prognosis and predicts immunotherapy efficacy in penile cancer.

BACKGROUND: The effect of SPP1 in squamous cell carcinoma of the penis (PSCC) remained unknown. We attempted to clarify the function of the SPP1 gene in PSCC. METHOD: Eight paired penile cancer specimens (including penile cancer tissue, paracancerous tissue, and positive lymph node tissue) subjected to whole transcriptome sequencing were analysed to identify differentially expressed genes. We used immunohistochemistry to detect the expression of SPP1 protein and immune cell related proteins in penile cancer tissue. Then, we performed weighted gene coexpression network analysis (WGCNA) to identify the genes related to SPP1 in penile cancer tissue and positive lymph node tissue. Based on the GSE57955 dataset, the CIBERSORT and ssGSEA algorithms were carried out to investigate the immune environment of PSCC. GSVA analysis was conducted to identify the signaling pathways related to SPP1 subgroups. Enzyme-linked immunosorbent assay (ELISA) method was adopted to detect SPP1 level in the serum of 60 patients with penile cancer. RESULTS: Differential analysis indicated that SPP1 was the most differentially upregulated gene in both penile cancer tissues and positive lymph node tissues. Survival analysis suggested that the prognosis of the low-SPP1 group was significantly poorer than that of the high-SPP1 group. Subsequently, immune-related bioinformatics showed that SPP1 was significantly associated with B cells, CD8 + T cells, CD4 + T cells, macrophages, helper T cells, neutrophils and dendritic cells. The immunohistochemical results showed that the high-SPP1 group was characterized by relatively high expression of CD16 and relatively low expression of CD4. GSVA analysis indicated that high-SPP1 group was significantly associated with immune-related pathways such as PD-L1 expression and the PD-1 checkpoint pathway in cancer and the TNF signaling pathway. ELISA demonstrated that the serum level of SPP1 in patients with positive lymph node metastasis of penile cancer was significantly higher than that in patients with negative lymph node metastasis of penile cancer. CONCLUSION: Our study shows that the SPP1 gene might be an effective biomarker for predicting the prognosis and the efficacy of immunotherapy in PSCC patients.

D-dimer, Fibrinogen and Tumor Marker Levels in Patients with benign and Malignant Ovarian Tumors.

Limited studies have investigated the differences between the levels of plasma coagulants and tumor markers in ovarian cancer. Therefore, we conducted this study to determine and compare the level of coagulation, fibrinolysis and tumor markers in patients with benign and malignant ovarian tumors. This cross-sectional study was conducted between January 2022 and February 2023 in Imam Hossein Hospital on patients with ovarian mass. Laboratory tests included platelet count, PT, INR, PTT, fibrinogen and D-dimer were sent to the pathology laboratory to be examined by a pathologist. Based on histopathology, patients were divided into benign, borderline and malignant groups. Logistic regression was used for determine predictors of malignancy. Receiver operating characteristics (ROC) curves and their corresponding 95% CI were determined for the predictor value of the full model. From 141 investigated patients, tumor type in 124 (87.94%) patients were benign, in 12 (8.51%) was malignant and in 5 (3.55%) was borderline. D-dimer, Ca-125 and HE4 were significantly higher in the patients with malignant tumor type (P<0.001), whereas AFP was significantly higher in patients with borderline tumor type (P<0.001). With one-unit increase in D-dimer odds of borderline/malignant tumor 0.3% increases (OR=1.003, 95% CI: 1.001, 1.006) and with one-unit increase in Ca-125 odds of borderline/malignant tumor 1% increases (OR=1.01, 95% CI: 1.003, 1.02). We found that plasma fibrinogen, D-dimer and Ca-125 levels are independently associated with malignant ovarian tumors and combined use of these markers has the high discriminant power for distinction of benign and malignant ovarian masses.
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CPEB2 inhibit cell proliferation through upregulating p21 mRNA stability in glioma.

Glioma is the most common primary malignant brain tumor in adults and remains an incurable disease at present. Thus, there is an urgent need for progress in finding novel molecular mechanisms that control the progression of glioma which could be used as therapeutic targets for glioma patients. The RNA binding protein cytoplasmic polyadenylate element-binding protein 2 (CPEB2) is involved in the pathogenesis of several tumors. However, the role of CPEB2 in glioma progression is unknown. In this study, the functional characterization of the role and molecular mechanism of CPEB2 in glioma were examined using a series of biological and cellular approaches in vitro and in vivo. Our work shows CPEB2 is significantly downregulated in various glioma patient cohorts. Functional characterization of CPEB2 by overexpression and knockdown revealed that it inhibits glioma cell proliferation and promotes apoptosis. CPEB2 exerts an anti-tumor effect by increasing p21 mRNA stability and inducing G1 cell cycle arrest in glioma. Overall, this work stands as the first report of CPEB2 downregulation and involvement in glioma pathogenesis, and identifies CPEB2 as an important tumor suppressor gene through targeting p21 in glioma, which revealed that CPEB2 may become a promising predictive biomarker for prognosis in glioma patients.