BackgroundIt is unclear what proportion of the population cancer burden is covered by current implementation of USPSTF A/B screening recommendations.ObjectiveWe estimated the proportion of all US cancer deaths caused by cancer types not covered by screening recommendations or cancer types covered but unaddressed by current implementation.MethodsWe used 2018-2019 National Center for Health Statistics mortality data, Surveillance, Epidemiology, and End Results registries incidence-based mortality data, and published estimates of screening eligibility and receipt.ResultsOf approximately 600,000 annual cancer deaths in the US, 31.4% were from screenable cancer types, including colorectal, female breast, cervical, and smoking-associated lung cancers. Further accounting for the low receipt of lung cancer screening reduced the proportion to 17.4%; accounting for receipt of other screening reduced it to 12.8%. Thus, we estimated that current implementation of recommended screening may not address as much as 87.2% of cancer deaths-including 30.4% from individually uncommon cancer types unlikely ever to be covered by dedicated screening.ConclusionsThe large proportion of cancer deaths unaddressed by current screening represents a major opportunity for improved implementation of current approaches, as well as new multi-cancer screening technologies.

Lung cancer is the leading cause of cancer death world-wide. Along the entire timeline of lung cancer identification, diagnosis and treatment, clinicians and patients face challenges in clinical decision-making that could be aided by useful biomarkers. In this review, we discuss the development of biomarkers and qualities that are ideal in a biomarker candidate, types of biospecimens that can be utilized for biomarker development in lung cancer, and how biomarkers could be clinically useful at various points along lung cancer timeline. We then review biomarkers that have been validated and are clinically available to assist with the management of lung nodules and diagnosis of lung cancer, which includes blood-based biomarkers to assist with decision-making prior to an invasive diagnostic procedure, as well as specimens obtained during a bronchoscopy and applied in cases of an inconclusive biopsy result. Finally, we discuss challenges in biomarker application and recent publications relevant to future lung cancer biomarker development.

BackgroundDoublecortin-like kinase 1 (DCLK1) isoforms play distinct roles in the progression of gastrointestinal cancers. For the first time ever, the current study aimed to generate DCLK1-S-specific monoclonal antibodies (mAbs) to evaluate the clinical value of DCLK1-S (short isoform) in gastric cancer (GC).Materials and methodsMice were immunized with a unique 7-mer synthetic peptide of DCLK1-S conjugated with keyhole limpet hemocyanin (KLH). Immunoreactivity of hybridomas and mAbs was determined by ELISA assays and immunohistochemistry (IHC). DCLK1-S expression in two GC cell lines was assessed by flow cytometry. After characterization, the expression pattern of DCLK1-S was investigated in different histological subtypes of GC (n=217) and adjacent normal tissues (n=28) using IHC on tissue microarrays. The association of clinical prognostic values with DCLK1-S expression was also investigated.ResultsELISA findings demonstrated that the generated monoclonal antibody (mAb) exhibited strong immunoreactivity towards the immunizing peptide. Positive control tissues, including GC and colorectal cancer, showed strong positive immunoreactivity with anti-DCLK1-S mAb whereas negative reagent control sections represented no staining, demonstrating the specificity of produced mAb. Flow cytometry analysis confirmed that the newly developed mAbs effectively recognized DCLK1-S on the cell surface. A mixture pattern of membranous, cytoplasmic, and nuclear DCLK1-S expression in the GC cells was observed. A significant and inverse association was identified between the expression DCLK1-S in the cell membrane and cytoplasm and PT stage, muscolarispropia, subserosa, and perineural invasion in intestinal subtype, respectively. In signet ring cell type, however, nuclear DCLK1-S expression was adversely associated with tumor size and PT stage. Furthermore, patients with low DCLK1-S expression had a shorter survival than patients with high expression, however, without a statistically significant association.ConclusionAn efficient and precise tool for detecting DCLK1-S in cancer tissues has been developed. Moreover, DCLK1-S overexpression might be considered a favorable clinical factor in GC patients.

ObjectiveStudy aims to develop diagnostic and prognostic models for lung adenocarcinoma (LUAD) using Machine learning（ML）algorithms, aiming to enhance clinical decision-making accuracy.MethodsData from The Cancer Genome Atlas (TCGA) for LUAD patients were split into training (n = 196) and test sets (n = 133). Feature selection (Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Support Vector Machine (SVM)) identified miRNAs distinguishing stage I LUAD. Six ML algorithms predicted pulmonary node classification. Model performance was evaluated using Receiver Operating Characteristic (ROC) curve, Precision-Recall (PR) curves, and Error Rates (CE). A prognostic model was constructed using Lasso Cox regression. Risk score plots were generated, and model performance was assessed using Kaplan-Meier (K-M) and time-dependent ROC curves. Functional enrichment analyses investigated miRNA function and mechanism.ResultsThe feature selection results identified five miRNA molecules as distinguishing characteristics between early-stage LUAD and adjacent non-cancerous tissues. A prognostic model using 13 miRNAs predicted poorer outcomes for patients with higher risk scores, supported by time-dependent ROC curves and a nomogram. Functional enrichment analysis identified cancer-related signaling pathways for the biomarkers.ConclusionML identified a diagnostic five-miRNA signature and a prognostic 13-miRNA model for LUAD, both robust and reliable.

Background and Aim: Malignant pleural effusion (MPE) is a common clinical problem. Management options are mainly pleurodesis and drainage, and have remained unchanged for years. Novel therapies that target the molecules responsible for fluid formation are needed to reduce the need for invasive procedures. The aim of this study is to investigate the potential role of MCP-1 in the development of MPE in patients with metastatic pleural malignancies. Methods: Pleural effusion samples (8-10 ml) were collected from 100 patients who were divided into three groups: Group 1 (MPE, n = 56), Group 2 (benign exudate, n = 27) and Group 3 (transudate, n = 17). The collected effusions were promptly centrifuged at 4°C, and the supernatants were stored at -80°C. MCP-1 levels were determined by ELISA kit (USCN, Wuhan). Results: Median MCP-1 levels were found to be significantly different between the three groups (Group 1: 1303 pg/ml, Group 2: 926 pg/ml, Group 3: 211 pg/ml) (p < 0.001). MCP-1 levels were markedly higher but similar in Group 1 and Group 2, as compared to Group 3. When patients from Group 1 and Group 2 were combined, a positive correlation was observed between pleural fluid MCP-1 and LDH levels (r = 0.38; p = 0.001). Additionally, MCP-1 levels were observed to increase significantly as the volume of pleural fluid increased (p = 0.007). Conclusion: MCP-1 levels were found to be similarly high in both Group 1 (MPE) and Group 2 (Benign exudate), indicating that inflammation accompanying the tumor could play a role in the formation of pleural effusion. This suggests that the development of biological therapies targeting MCP-1 could be a promising approach in the future management of MPE.

Background:The limited diagnostic accuracy of prostate-specific antigen screening for prostate cancer (PCa) has prompted innovative solutions, such as the state-of-the-art 18-gene urine test for clinically-significant PCa (MyProstateScore2.0 (MPS2)).Objective:We aim to develop a non-invasive biomarker test, the simplified MPS2 (sMPS2), which achieves similar state-of-the-art accuracy as MPS2 for predicting high-grade PCa but requires substantially fewer genes than the 18-gene MPS2 to improve its accessibility for routine clinical care.Methods:We grounded the development of sMPS2 in the Predictability, Computability, and Stability (PCS) framework for veridical data science. Under this framework, we stress-tested the development of sMPS2 across various data preprocessing and modeling choices and developed a stability-driven PCS ranking procedure for selecting the most predictive and robust genes for use in sMPS2.Results:The final sMPS2 model consisted of 7 genes and achieved a 0.784 AUROC (95% confidence interval, 0.742–0.825) for predicting high-grade PCa on a blinded external validation cohort. This is only 2.3% lower than the 18-gene MPS2, which is similar in magnitude to the 1–2% in uncertainty induced by different data preprocessing choices.Conclusions:The 7-gene sMPS2 provides a unique opportunity to expand the reach and adoption of non-invasive PCa screening.

BackgroundThe status of carbohydrate antigen 19-9 (CA19-9) in metabolic syndrome (MetS) is unknown.ObjectiveTo investigate the association between serum CA19-9 levels and incident metabolic syndrome in obese middle-aged and older men.MethodsFrom 2007 to 2015, 1,750 participants were retrospectively reviewed. Health checkup data were obtained, and participants were divided into three groups based on CA19-9 levels. Various parameters including BMI, waist circumference, blood pressure, and biochemical parameters were measured. Cox regression analysis was used to assess the association between CA19-9 levels and incident MetS. The MetS diagnostic criteria were based on the National Cholesterol Education Program Adult Treatment Panel III guidelines.ResultsThe highest CA19-9 tertile was associated with an increased risk of incident MetS, high systolic blood pressure, high waist circumference, high fasting plasma glucose, low high-density lipoprotein, and high triglyceride levels. The observation period was 9 years, during which 328 (18.7%) new-onset MetS cases were identified. Subgroup analysis showed increased risk among individuals in the highest CA19-9 tertile who were obese, male, and ≥ 50 years old.ConclusionsThere is a positive correlation between serum CA19-9 levels and incident metabolic syndrome in obese middle-aged and older men.

BackgroundBreast cancer is the leading malignancy among women and the lack of ideal early biomarkers hampers diagnosis and treatment monitoring. Genomic instability, central to breast cancer development, makes DNA damage a potential biomarker for these purposes.ObjectiveThis study aims to evaluate the predictive value of DNA damage for diagnosis, and treatment monitoring in breast cancer, with CA 15-3, a conventional cancer biomarker, included for comparison to assess the added value of DNA damage measurement.MethodsDNA damage was measured in peripheral blood lymphocytes of 58 breast cancer patients, and 31 healthy controls, employing comet assay, both before and after treatment. Serum CA 15-3 levels were assessed at the same time points for comparison.ResultsDNA damage levels were significantly higher in cancer patients compared to healthy controls, with the most elevated levels observed in patients with advanced-stage disease, irrespective of age, sex, lifestyle, or genetic status. Post-treatment assessments showed a significant rise in DNA damage. In comparison, CA 15-3 showed less consistent relevance for diagnostic and monitoring.ConclusionsThis study underscores the greater potential of DNA damage as a consistent and reliable biomarker for breast cancer, with CA 15-3 providing complementary but less consistent data for clinical decision-making.

BackgroundApolipoprotein C1 (APOC1) and Apoprotein E (APOE) play important roles in lipid transport and metabolism. In recent years, APOC1 and APOE have been shown to play key roles in the occurrence and development of various cancers. However, the expression levels, gene regulatory networks, prognostic values, and target predictions of APOC1 and APOE in adrenocortical carcinoma (ACC) remain unclear.MethodsVarious bioinformatics analysis methods were used, including gene expression profiling interactive analysis, the University of Alabama at Birmingham cancer data analysis portal, biomarker exploration of solid tumors software, the BioPortal for Cancer Genomics, search tool for the retrieval of interacting genes/proteins, gene multiple association network integration algorithm, Metascape, transcriptional regulatory relationships unraveled by sentence-based text-mining, LinkedOmics, and genomics of drug sensitivity in cancer analysis.ResultsAPOC1 and APOE expression were strongly downregulated in patients with ACC. APOC1 and APOE expression levels were lower in male patients with ACC than those in female patients. Furthermore, APOC1 and APOE expression levels affected the prognosis of patients with ACC. The main functions of APOC1 and its altered neighboring genes (ANG) were organophosphate ester transport, rRNA processing, and positive regulation of cytokine production. Cytolysis, protein ubiquitination, and histone modification were the main functions of APOE and its ANGs. The transcription factor E2F1, tumor protein p53, miR-182, miR-493, Erb-B2 receptor tyrosine kinase 2, and cyclin dependent kinase 1 were key regulatory targets of APOC1, APOE, and the ANGs. APOC1 and APOE expression in patients with ACC were positively associated with immune cell infiltration. Furthermore, anti-programmed cell death protein 1 immunotherapy strongly downregulated the expression of APOC1 in patients with ACC. Both pilaralisib and elesclomol strongly inhibited SW13 cell growth.ConclusionsThis study preliminarily clarified that APOC1 and APOE might be potential therapeutic and prognostic targets for ACC, and identified new targets and treatment strategies for ACC.

BackgroundOropharyngeal cancer rates continue to rise with no effective screening method. Persistent oral oncogenic human papillomavirus (HPV), antibodies to HPV16 early (E) oncoproteins, and circulating tumor HPV DNA (ctHPVDNA) are biomarkers that show promise for use in HPV-related cancer screening.ObjectiveTo assess the prevalence of biomarkers for HPV-related cancer and their agreement in middle-aged men.MethodsMen aged 50-64 years from the general population provided oral rinse and blood samples as well as information about demographics, tobacco/alcohol exposure, sexual behavior, and HPV-related disease history. Oral rinse was tested for HPV16 DNA and plasma was tested for HPV16 E antibodies and ctHPVDNA using a droplet digital PCR (ddPCR)-based assay that measures circulating tumor tissue modified viral (TTMV)-HPV DNA (NavDx, Naveris, Inc.). We calculated frequency distributions of variables of interest and agreement between the biomarkers.ResultsWe enrolled 1045 subjects between April 2017 and April 2024. The 954 subjects with results for all three biomarkers were included in the analysis. The prevalence was 4.9% for oral HPV16 DNA, 0.7% for HPV16 E antibodies, and 0.5% for TTMV-HPV DNA.ConclusionsThe low prevalence of all three biomarkers shows their potential to identify high-risk individuals eligible for further clinical HPV-related cancer screening.