Early detection and stratification of colorectal cancer using plasma cell-free DNA fragmentomic profiling.

Timely accurate and cost-efficient detection of colorectal cancer (CRC) is of great clinical importance. This study aims to establish prediction models for detecting CRC using plasma cell-free DNA (cfDNA) fragmentomic features. Whole-genome sequencing (WGS) was performed on cfDNA from 620 participants, including healthy individuals, patients with benign colorectal diseases and CRC patients. Using WGS data, three machine learning methods were compared to build prediction models for the stratification of CRC patients. The optimal model to discriminate CRC patients of all stages from healthy individuals achieved a sensitivity of 92.31% and a specificity of 91.14%, while the model to separate early-stage CRC patients (stage 0-II) from healthy individuals achieved a sensitivity of 88.8% and a specificity of 96.2%. Additionally, the cfDNA fragmentation profiles reflected disease-specific genomic alterations in CRC. Overall, this study suggests that cfDNA fragmentation profiles may potentially become a noninvasive approach for the detection and stratification of CRC.

Imaging features and deep learning for prediction of pulmonary epithelioid hemangioendothelioma in CT images.

Background: Pulmonary epithelioid hemangioendothelioma (PEH) is a rare vascular tumour, and its early diagnosis remains challenging. This study aims to comprehensively analyse the imaging features of PEH and develop a model for predicting PEH. Methods: Retrospective and pooled analyses of imaging findings were performed in PEH patients at our center (n=25) and in published cases (n=71), respectively. Relevant computed tomography (CT) images were extracted and used to build a deep learning model for PEH identification and differentiation from other diseases. Results: In this study, bilateral multiple nodules/masses (n=19) appeared to be more common with most nodules less than 2 cm. In addition to the common types and features, the pattern of mixed type (n=4) and isolated nodules (n=4), punctate calcifications (5/25) and lymph node enlargement were also observed (10/25). The presence of pleural effusion is associated with a poor prognosis in PEH. The deep learning model, with an area under the receiver operating characteristic curve (AUC) of 0.71 [95% confidence interval (CI): 0.69-0.72], has a differentiation accuracy of 100% and 74% for the training and test sets respectively. Conclusions: This study confirmed the heterogeneity of the imaging findings in PEH and showed several previously undescribed types and features. The current deep learning model based on CT has potential for clinical application and needs to be further explored in the future.

Causal role of lipid metabolism in pulmonary alveolar proteinosis: an observational and mendelian randomisation study.

BACKGROUND: Pulmonary alveolar proteinosis (PAP) is a rare interstitial lung disease characterised by the accumulation of lipoprotein material in the alveoli. Although dyslipidaemia is a prominet feature, the causal effect of lipid traits on PAP remains unclear. This study aimed to explore the role of lipid traits in PAP and evaluate the potential of lipid-lowering drug targets in PAP. METHODS: Clinical outcomes, lipid profiles and lung function tests were analysed in a clinical cohort of diagnosed PAP patients and propensity score-matched healthy controls. Genome-wide association study data on PAP, lipid metabolism, blood cells and variants of genes encoding potential lipid-lowering drug targets were obtained for Mendelian randomisation (MR) and mediation analyses. FINDINGS: Observational results showed that higher levels of total cholesterol (TC), triglycerides and low-density lipoprotein (LDL) were associated with increased risks of PAP. Higher levels of TC and LDL were also associated with worse PAP severity. In MR analysis, elevated LDL was associated with an increased risk of PAP (OR: 4.32, 95% CI: 1.63 to 11.61, p=0.018). Elevated monocytes were associated with a lower risk of PAP (OR 0.34, 95% CI: 0.18 to 0.66, p=0.002) and mediated the risk impact of LDL on PAP. Genetic mimicry of PCSK9 inhibition was associated with a reduced risk of PAP (OR 0.03, p=0.007). INTERPRETATION: Our results support the crucial role of lipid and metabolism-related traits in PAP risk, emphasising the monocyte-mediated, causal effect of elevated LDL in PAP genetics. PCSK9 mediates the development of PAP by raising LDL. These finding provide evidence for lipid-related mechanisms and promising lipid-lowering drug target for PAP.

T Cells in Colorectal Cancer: Unravelling the Function of Different T Cell Subsets in the Tumor Microenvironment.

Therapeutic options for metastatic colorectal cancer (mCRC) are very limited, and the prognosis using combination therapy with a chemotherapeutic drug and a targeted agent, e.g., epidermal growth factor receptor or tyrosine kinase, remains poor. Therefore, mCRC is associated with a poor median overall survival (mOS) of only 25-30 months. Current immunotherapies with checkpoint inhibitor blockade (ICB) have led to a substantial change in the treatment of several cancers, such as melanoma and non-small cell lung cancer. In CRC, ICB has only limited effects, except in patients with microsatellite instability-high (MSI-H) or mismatch repair-deficient (dMMR) tumors, which comprise about 15% of sporadic CRC patients and about 4% of patients with metastatic CRC. The vast majority of sporadic CRCs are microsatellite-stable (MSS) tumors with low levels of infiltrating immune cells, in which immunotherapy has no clinical benefit so far. Immunotherapy with checkpoint inhibitors requires the presence of infiltrating T cells into the tumor microenvironment (TME). This makes T cells the most important effector cells in the TME, as evidenced by the establishment of the immunoscore-a method to estimate the prognosis of CRC patients. The microenvironment of a tumor contains several types of T cells that are anti-tumorigenic, such as CD8+ T cells or pro-tumorigenic, such as regulatory T cells (Tregs) or T helper 17 (Th17) cells. However, even CD8+ T cells show marked heterogeneity, e.g., they can become exhausted, enter a state of hyporesponsiveness or become dysfunctional and express high levels of checkpoint molecules, the targets for ICB. To kill cancer cells, CD8+ T cells need the recognition of the MHC class I, which is often downregulated on colorectal cancer cells. In this case, a population of unconventional T cells with a γδ T cell receptor can overcome the limitations of the conventional CD8+ T cells with an αßT cell receptor. γδ T cells recognize antigens in an MHC-independent manner, thus acting as a bridge between innate and adaptive immunity. Here, we discuss the effects of different T cell subsets in colorectal cancer with a special emphasis on γδ T cells and the possibility of using them in CAR-T cell therapy. We explain T cell exclusion in microsatellite-stable colorectal cancer and the possibilities to overcome this exclusion to enable immunotherapy even in these "cold" tumors.

The regulating role of miR-494 on HCCR1 in cervical cancer cells.

This study focused on miR-494 inhibiting the proliferation, migration and invasion of cervical cancer cells by regulating HCCR1. During the study, 30 pairs of primary cervical cancer tissues and adjacent tissues diagnosed by pathology were collected, and then placed in a cryopreservation tube, immediately placed in liquid nitrogen to freeze, and then moved to a -80 °C refrigerator for storage until use. They were dipped with crystal violet staining solution for 20 minutes, washed 3 times with PBS, and dried at room temperature. The polycarbonate film on the chamber was gently cut, placed on a glass slide, and covered with neutral resin. The number of cells in 5 random fields was counted under a microscope, and the differences between the groups were compared. The qRT-PCR results showed that compared with the normal cervical tissue cell line HCCR1, the expression levels of miR-494 in cervical cancer cell lines HCCR1 and C-33A were significantly reduced. Compared with the transfection of mimics NC, the level of HCCR1mRNA and protein decreased significantly when transfected with miRNA-494mimics (P <0.05); compared with the transfection of inhibitor NC, the level of HCCR1 mRNA and protein increased significantly when transfected with miRNA-494 inhibitor (P <0.05).

Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center study.

PURPOSE Knowing the genetic phenotype of gastrointestinal stromal tumors (GISTs) is essential for patients who receive therapy with tyrosine kinase inhibitors. The aim of this study was to develop a radiomic algorithm for predicting GISTs with KIT exon 11 mutation. METHODS We enrolled 106 patients (80 in the training set, 26 in the validation set) with clinicopathologically confirmed GISTs from two centers. Preoperative and postoperative clinical characteristics were selected and analyzed to construct the clinical model. Arterial phase, venous phase, delayed phase, and tri-phase combined radiomics algorithms were generated from the training set based on contrast-enhanced computed tomography (CE-CT) images. Various radiomics feature selection methods were used, namely least absolute shrinkage and selection operator (LASSO); minimum redundancy maximum relevance (mRMR); and generalized linear model (GLM) as a machine-learning classifier. Independent predictive factors were determined to construct preoperative and postoperative radiomics nomograms by multivariate logistic regression analysis. The performances of the clinical model, radiomics algorithm, and radiomics nomogram in distinguishing GISTs with the KIT exon 11 mutation were evaluated by area under the curve (AUC) of the receiver operating characteristics. RESULTS Of 106 patients who underwent genetic analysis, 61 had the KIT exon 11 mutation. The combined radiomics algorithm was found to be the best prediction model for differentiating the expression status of the KIT exon 11 mutation (AUC = 0.836; 95% confidence interval [CI], 0.640-0.951) in the validation set. The clinical model, and preoperative and postoperative radiomics nomograms had AUCs of 0.606 (95% CI, 0.397-0.790), 0.715 (95% CI, 0.506-0.873), and 0.679 (95% CI, 0.468-0.847), respectively, with the validation set. CONCLUSION The radiomics algorithm could distinguish GISTs with the KIT exon 11 mutation based on CE-CT images and could potentially be used for selective genetic analysis to support the precision medicine of GISTs.

Radiomics Nomogram Based on Contrast-enhanced CT to Predict the Malignant Potential of Gastrointestinal Stromal Tumor: A Two-center Study.

RATIONALE AND OBJECTIVES: Contrast-enhanced computed tomography (CE-CT) was used to establish radiomics nomogram to evaluate the malignant potential of gastrointestinal stromal tumors (GISTs). MATERIALS AND METHODS: A total of 500 GIST patients were enrolled in this study and divided into training cohort (n = 346, our center) and validation cohort (n = 154, another center). Minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) algorithms were used to select the feature subset with the best discriminant features from the three phases image, and five classifiers were used to establish four radiomics signatures. Preoperative radiomics nomogram was constructed by adding the clinical features determined by multivariate logistic regression analysis. The performance of radiomics signatures and nomogram were evaluated by area under the curve (AUC) of the receiver operating characteristic (ROC). The calibration of nomogram was appraised by calibration curve. RESULTS: A total of 13 radiomic features were extracted from tri-phase combined CE-CT images. Tri-phase combined CE-CT features + Support Vector Machine (SVM) was the best combination at predicting the malignant potential of GIST, with an AUC of 0.895 (95% CI 0.858-0.931) in the training cohort and 0.847 (95% CI 0.778-0.917) in the validation cohort. The nomogram also had good calibration. In the training cohort and the validation cohort, preoperative radiomics nomogram reached AUCs of 0.927 and 0.905, respectively, which were higher than clinical. CONCLUSION: The radiomics nomogram had a good predictive effect and generalization on the malignant potential of GIST, which could effectively help guide preoperative clinical decision.

Prognostic value of HPV 16/18 genotyping and geminin mRNA quantification in low-grade cervical squamous intraepithelial lesion.

Low-grade cervical squamous intraepithelial lesion is a precancerous neoplasia that has appreciable probability to evolve into malignancy. To explore the prognostic value of HPV 16/18 genotyping and geminin mRNA quantification in predicting the progressiveness of LSIL. We recruited 212 participants who were negative for intraepithelial lesion or malignancy (NILM 76), low-grade squamous intraepithelial lesion (LSIL 85), high-grade squamous intraepithelial lesion (HSIL 36) and cervical intraepithelial neoplasia grade cervical cancer grade 3, (CIN3 15) patients. Tissues were obtained during excisional treatment. HPV 16/18 genotyping and geminin mRNA qRT-PCR were performed. HPV 16/18 positivity rate and geminin mRNA level were integrated with the clinical parameters into a multivariate logistic model. Area under curve was yielded based on receiver operation curve derived from this multivariate logistic model. Follow-up visits were performed to LSIL patients with progression. HSIL patients have higher HPV 16/18 positivity rate and geminin mRNA levels than LSIL. Among HSIL, CIN3 have higher HPV 16/18 positivity rate and geminin mRNA levels. Multivariate logistic analysis showed that HPV 16/18 positivity and geminin mRNA expression status are independent factors for differentiating HSIL and LSIL. The baseline HPV 16/18 positivity rate and geminin mRNA levels of 18 LSIL patients who developed HSIL are significantly higher than non-progressive LSIL patients. The values examined at follow-up timepoints were also higher than baseline. These results suggest that geminin is implicated in the progression of LSIL and combining HPV 16/18 genotyping and geminin mRNA qRT-PCR could potentially differentiating the progressive LSIL and improve the efficacy of clinical intervention.

Downregulation of DEC1 inhibits proliferation, migration and invasion, and induces apoptosis in ovarian cancer cells via regulation of Wnt/ß-catenin signaling pathway.

DEC1 has been reported to regulate the expression of multiple target genes, participate in cell differentiation, apoptosis, aging and the development and progression of numerous tumors, but the detailed effects and possible mechanisms of DEC1 in ovarian cancer (OC) remain unknown. The present study aimed to investigate the expression and mechanism of function of DEC1 in OC. The present results demonstrated that DEC1 was highly expressed in OC tissues and cell lines using reverse transcription-quantitative PCR, western blotting and immunohistochemistry, and high expression of DEC1 was negatively associated with the prognosis of patients with OC. In addition, knockdown of DEC1 significantly inhibited proliferation in SKOV3 and OVCAR3 cells compared with control. DEC1 knockdown also induced apoptosis and increased the expression of apoptosis-related proteins in OC cells. The results suggested that knockdown of DEC1 inhibited OC cell migration and invasion via regulation of epithelial-mesenchymal transition-related protein. It was also found that DEC1 knockdown significantly inhibited the Wnt/ß-catenin pathway. Collectively, the current results indicated that knockdown of DEC1 inhibited proliferation, migration and invasion, and induced apoptosis in OC cells via modulating the Wnt/ß-catenin signaling pathway. Thus, DEC1 may participate in malignant progression of OC, and may be a target for treatment and diagnosis of OC.

Bioinformatic analysis of potential hub genes in gastric adenocarcinoma.

Gastric adenocarcinoma is the most common histologic type of gastric cancer; however, the pathogenic mechanisms remain unclear. To improve mechanistic understanding and identify new treatment targets or diagnostic biomarkers, we used bioinformatic tools to predict the hub genes related to the process of gastric adenocarcinoma development from public datasets, and explored their prognostic significance. We screened differentially expressed genes between gastric adenocarcinoma and normal gastric tissues in Gene Expression Omnibus datasets (GSE79973, GSE118916, and GSE29998) using the GEO2R tool, and their functions were annotated with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes signaling pathway enrichment analyses in the DAVID database. Hub genes were identified based on the protein-protein network constructed in the STRING database with Cytoscape software. A total of 10 hub genes were selected for further analysis, and their expression patterns in gastric adenocarcinoma patients were investigated using the Oncomine GEPIA database. The expression levels of ATP4A, CA9, FGA, ALDH1A1, and GHRL were reduced, whereas those of TIMP1, SPP1, CXCL8, THY1, and COL1A1 were increased in gastric adenocarcinoma. The Kaplan-Meier online plotter tool showed associations of all hub genes except for CA9 with prognosis in gastric adenocarcinoma patients; CXCL8 and ALDH1A1 were positively correlated with survival, and the other genes were negatively correlated with survival. These 10 hub genes may be involved in important processes in gastric adenocarcinoma development, providing new directions for research to clarify the role of these genes and offer insight for improved treatment.

Construction of a clinical survival prognostic model for middle-aged and elderly patients with stage III rectal adenocarcinoma.

BACKGROUND: Nomograms for prognosis prediction in colorectal cancer patients are few, and prognostic indicators differ with age. AIM: To construct a new nomogram survival prediction tool for middle-aged and elderly patients with stage III rectal adenocarcinoma. METHODS: A total of 2773 eligible patients were divided into the training cohort (70%) and the validation cohort (30%). Optimal cutoff values were calculated using the X-tile software for continuous variables. Univariate and multivariate Cox proportional hazards regression analyses were used to determine overall survival (OS) and cancer-specific survival (CSS)-related prognostic factors. Two nomograms were successfully constructed. The discriminant and predictive ability and clinical usefulness of the model were also assessed by multiple methods of analysis. RESULTS: The 95%CI in the training group was 0.719 (0.690-0.749) and 0.733 (0.702-0.74), while that in the validation group was 0.739 (0.696-0.782) and 0.750 (0.701-0.800) for the OS and CSS nomogram prediction models, respectively. In the validation group, the AUC of the three-year survival rate was 0.762 and 0.770, while the AUC of the five-year survival rate was 0.722 and 0.744 for the OS and CSS nomograms, respectively. The nomogram distinguishes all-cause mortality from cancer-specific mortality in patients with different risk grades. The time-dependent AUC and decision curve analysis showed that the nomogram had good clinical predictive ability and decision efficacy and was significantly better than the tumor-node-metastases staging system. CONCLUSION: The survival prediction model constructed in this study is helpful in evaluating the prognosis of patients and can aid physicians in clinical diagnosis and treatment.

Application of three-dimensional reconstruction with a Hisense computer-assisted system in upper pancreatic lymph node dissection during laparoscopic-assisted radical gastrectomy.

BACKGROUND/OBJECTIVE: To investigate the feasibility of three-dimensional (3D) reconstruction with an interactive Hisense computer-assisted system (CAS) for preoperative planning and intraoperative guidance during laparoscopic-assisted upper pancreatic lymph node dissection in distal gastrectomy for gastric cancer. METHODS: This study included 28 patients who underwent preoperative 3D reconstruction of the upper border of the pancreas using Hisense CAS (3D reconstruction group) for preoperative planning and intraoperative navigation. To determine its efficacy, the clinical data of these patients were compared with those of 28 patients who did not undergo 3D reconstruction (control group). RESULTS: Fifty-six cases of laparoscopic-assisted distal gastrectomy were performed. Three-dimensional reconstruction was successful in all the patients in the 3D reconstruction group, and real-time navigation was performed during the operation. The rate of correspondence between the 3D reconstruction images and intraoperative findings was 100%. The time taken for upper pancreatic lymph node dissection, number of upper pancreatic lymph node dissections, and number of unnecessary injuries during surgery were superior in the 3D reconstruction group than in the control group. The results of the remaining parameters were not statistically significant. CONCLUSION: Preoperative planning with interactive Hisense CAS 3D reconstruction technology can improve surgeons' understanding of each patient's individual anatomy and can reveal anatomical variations, which is helpful for accurate preoperative planning and intraoperative navigation. This technique is helpful for the implementation of the precise dissection of lymph nodes at the upper edge of the pancreas and improves the quality and safety of the surgery.

Evaluation of human-papillomavirus screening for cervical cancer in China's rural population.

BACKGROUND AND OBJECTIVE: Human papillomavirus (HPV) testing has become a preferred cervical cancer screening. However, most HPV infections are harmless and additional tests are required to screen HPV positive women. The objective of this study is to determine the optimal triage strategies for HPV positive women in China's rural population. METHODS: A population-based screening was performed at seven rural counties of Jiangxi province, between October 2014 to January 2016. A total of 18,000 women aged 35-64 years were enrolled in this study. The primary screening was performed using CareHPV, HC-2, Cobas ®4,800 or HybriMax. Positive women were further screened with five triage tests: (1) Liquid-based cytology test (LBC); (2) conventional Pap cytology test (Pap smear); (3) HPV16, 18 detection; (4) viral load; and (5) visual inspection with acetic acid and Lugol's iodine (VIA/VILI). Women who were tested positive were referred for colposcopy. The five triage tests were compared with respect to sensitivity, specificity, referral rate, cost and diagnostic time. RESULTS: Complete data were available for 17,782 women. The HPV prevalence was 13.6%. Referral rates for colposcopy were 4.5%, 2.8%, 2.8%, 6.6%, and 3.7% with LBC, Pap smear, HPV16/18, viral load, and VIA/VILI, respectively. The sensitivity of the above triage tests was 65.8%, 51.9%, 86.8%, 73.3%, and 41.7%, respectively. The specificity was 69.8%, 81.0%, 85.8%, 52.2% and 65.3%, respectively. The average time to diagnosis was significantly lower with HPV16/18, viral load and VIA/VILI than LBC and Pap smear. In addition, screening cost that leads to identify one HSIL+ woman was the lowest with viral load. CONCLUSION: Our data indicate that HPV16/18 and viral load are the optimal triage strategies for HPV screening in China's rural population.