Gastroenteropancreatic neuroendocrine neoplasms: current development, challenges, and clinical perspectives.

Neuroendocrine neoplasms (NENs) are highly heterogeneous and potentially malignant tumors arising from secretory cells of the neuroendocrine system. Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are the most common subtype of NENs. Historically, GEP-NENs have been regarded as infrequent and slow-growing malignancies; however, recent data have demonstrated that the worldwide prevalence and incidence of GEP-NENs have increased exponentially over the last three decades. In addition, an increasing number of studies have proven that GEP-NENs result in a limited life expectancy. These findings suggested that the natural biology of GEP-NENs is more aggressive than commonly assumed. Therefore, there is an urgent need for advanced researches focusing on the diagnosis and management of patients with GEP-NENs. In this review, we have summarized the limitations and recent advancements in our comprehension of the epidemiology, clinical presentations, pathology, molecular biology, diagnosis, and treatment of GEP-NETs to identify factors contributing to delays in diagnosis and timely treatment of these patients.

Conditional survival nomogram for patients with colon mucinous adenocarcinoma to predict prognosis: a dynamic survival analysis.

The aim was to assess conditional survival for colon mucinous adenocarcinoma (MAC) patients, and to construct nomograms to predict conditional survival probability. Survival analysis was done using conditional survival, which was defined as the probability of surviving additional y years for patients who have survived for x years. The mathematical definition was express as: CS (y|x) = S (x + y)/S (x). Cox regression analyses were used to identify prognostic factors. A nomogram is constructed to predict conditional disease-free survival (DFS) and overall survival (OS) probability according to years that already survive. A total of 179 colon MAC patients were included. The 5-year DFS was 67% after surgery, and the 5-year survival probability of patients, who already survived 1, 2, 3, and 4 years were 75%, 87%, 95%, and 98%, respectively. The 5-year OS was 73% after surgery and increased to 76%, 82%, 88%, and 92% at 1, 2, 3, and 4 years, respectively. Subgroup analyses demonstrated the superiority of conditional survival was more pronounced in advanced stages than in stage I. And pT stage, pN stage, and lymphovascular invasion were significantly associated with DFS and OS. Conditional survival nomograms were constructed to predict the 5-year conditional DFS and OS probability given survival for 1, 2, 3, 4 years after surgery. Conditional survival can provide dynamic survival probability according to years that already survive, especially for patients with advanced stages. Taking into account the years already survived accounted for, novel nomograms contributed to effectively predicting conditional survival.

The prognostic model and immune landscape based on cancer-associated fibroblast features for patients with locally advanced rectal cancer.

Background: This study aimed to construct a nomogram based on CAF features to predict the cancer-specific survival (CSS) rates of locally advanced rectal cancer (LARC) patients. Methods: The EPIC algorithm was employed to calculate the proportion of CAFs. based on the differentially expressed genes between the high and low CAF proportion subgroups, prognostic genes were identified via LASSO and Cox regression analyses. They were then used to construct a prognostic risk signature. Moreover, the GSE39582 and GGSE38832 datasets were used for external validation. Lastly, the level of immune infiltration was evaluated using ssGSEA, ESTIMATE, CIBERSORTx, and TIMER. Results: A higher level of CAF infiltration was associated with a worse prognosis. Additionally, the number of metastasized lymph nodes and distant metastases, as well as the level of immune infiltration were higher in the high CAF proportion subgroup. Five prognostic genes (SMOC2, TUBAL3, C2CD4A, MAP1B, BMP8A) were identified and subsequently incorporated into the prognostic risk signature to predict the 1-, 3-, and 5-year CSS rates in the training and validation sets. Differences in survival rates were also determined in the external validation cohort. Furthermore, independent prognostic factors, including TNM stage and risk score, were combined to established a nomogram. Notably, our results revealed that the proportions of macrophages and neutrophils and the levels of cytokines secreted by M2 macrophages were higher in the high-risk subgroup. Finally, the prognostic genes were significantly associated with the level of immune cell infiltration. Conclusion: Herein, a nomogram based on CAF features was developed to predict the CSS rate of LARC patients. The risk model was capable of reflecting differences in the level of immune cell infiltration.

The prognostic role of the change in albumin-derived neutrophil-to-lymphocyte ratio during neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer.

The prognosis of patients with locally advanced rectal cancer (LARC) has improved with the adoption of a multidisciplinary treatment approach combining neoadjuvant chemoradiotherapy (nCRT) and total mesorectal excision (TME). Developing real-time, sensitive biomarkers to monitor systemic changes during nCRT is of paramount importance. Although the association between albumin-derived neutrophil-to-lymphocyte ratio (Alb-dNLR) and prognosis in various cancers is established, its prognostic value in LARC patients undergoing nCRT is not well-studied. This study enrolled a cohort of 618 LARC patients, stratifying them into two groups according to their change in Alb-dNLR (∆Alb-dNLR) values, using an optimal cut-off point: a low ∆Alb-dNLR group (≤ 0.90) and a high ∆Alb-dNLR group (> 0.90). The prognostic significance of ∆Alb-dNLR was evaluated using a Cox proportional hazards model. The 5-year overall survival (OS) rates were 75.2% in the low ∆Alb-dNLR group (≤ 0.90) and 85.9% in the high ∆Alb-dNLR group (>0.90) (P < 0.001). The 5-year disease-free survival (DFS) rates were 71.2% and 80.6%, respectively (P = 0.016). Multivariate analyses demonstrated that both ∆Alb-dNLR and pre-Alb-dNLR were independent prognostic factors for OS (P ≤ 0.001), while ∆Alb-dNLR was demonstrated as an independent prognostic factor for DFS (P = 0.016). A predictive nomogram, incorporating the ∆Alb-dNLR subgroup, demonstrated enhanced performance (concordance index [C-index] of 0.720 for OS and 0.690 for DFS) compared to the pre-treatment Alb-dNLR subgroup (C-index of 0.700 for OS and of 0.680 for DFS). Therefore, ∆Alb-dNLR shows significant potential as a usable and prognostic biomarker for predicting OS and DFS in LARC patients undergoing nCRT.

Background-oriented Schlieren tomography using gated recurrent unit.

Current Background-oriented schlieren tomography (BOST) methods rely primarily on iterative algorithms for reconstruction. Before reconstruction, a weight projection matrix was generated by performing 3D ray tracing using the projection relationship between the cameras, depending on the camera calibration parameters and large weight projection matrix which introduce artifacts and greatly reduce computational efficiency in the reconstruction. Considering that CT reconstruction uses spatial projection sequences from multiple directions, this study draws inspiration from the Recurrent Neural network(RNN) and utilizes spatial correlation between adjacent projection data to propose a background-oriented schlieren reconstruction method based on a gated recurrent unit (GRU) neural network. First, the model architecture is designed and implemented. Subsequently, numerical simulations were conducted using a methane combustion model to evaluate the proposed method, which achieved an average mean relative error (MRE) of 0.23%. Finally, reconstruction experiments were performed on the actual flow-field data above a candle flame, with a reprojection correlation coefficient of 89% and an average reconstruction time of only 1.04 s per frame. The results demonstrate that the proposed method outperforms traditional iterative reconstruction methods in terms of reconstruction speed and accuracy. This provides a feasible solution for the real-time reconstruction of three-dimensional instantaneous flow fields.

Displacement extraction of background-oriented schlieren images using Swin Transformer.

Displacement extraction of background-oriented schlieren (BOS) is an essential step in BOS reconstruction, which directly determines the accuracy of the results. Typically, the displacement is calculated from the background images with and without inhomogeneous flow using the cross-correlation (CC) or optical flow (OF) method. This paper discusses the disadvantages of the CC and OF methods, and an end-to-end deep neural network was designed to estimate the BOS displacement. The proposed network is based on a Swin Transformer, which can build long-range correlations. A synthetic dataset used for training was generated using the simulated flow field by computational fluid dynamics. After training, the displacement can be obtained using the BOS image pair without additional parameters. Finally, the effectiveness of the proposed network was verified through experiments. The experiments illustrate that the proposed method performs stably on synthetic and real experimental images and outperforms conventional CC or OF methods and classic convolutional neural networks for OF tasks.

A good preoperative immune prognostic index is precits a better prognosis for locally advanced rectal cancer patients with ypTNM stage II who underwent radical resection after neoadjuvant chemoradiotherapy.

BACKGROUND: No studies have investigated the role of IPI in assessing the prognosis of locally advanced rectal cancer (LARC) patients undergoing nCRT. OBJECTIVE: We attempted to combine neutrophil-to-lymphocyte ratio (NLR) and serum lactate dehydrogenase (sLDH) to generate a new rectal immune prognostic index (RIPI) to explore whether RIPI is associated with LARC prognosis. We aimed to identify whether there is a population that might benefit from RIPI in LARC. METHODS: LARC patients who underwent radical surgery after Neoadjuvant chemoradiotherapy (nCRT) were enrolled between February 2012 and May 2017. Based on the best cut-off points of NLR and sLDH, we developed RIPI. The patients were grouped as follows: (1) good, RIPI = 0, good, 0 factors; (2) poor, RIPI = 1, 1 or 2 factors. RESULTS: This study enrolled 642 patients. In yp TNM stage II patients, 5-year disease-free survival (DFS) differed significantly between the RIPI = 1 and RIPI = 0 groups (p = 0.03). Five-year DFS did not differ significantly between IPI = 0 and IPI = 1 groups in ypCR, stage I, stage II, and stage III. In multivariate analysis, the significant factor predicting DFS was pre-nCRT RIPI score (p = 0.035). CONCLUSION: The pre-nCRT RIPI was closely related to the prognosis of LARC patients undergoing nCRT. Particularly, RIPI is significant in evaluating the prognosis of ypTNM stage II LARC patients who underwent radical resection after nCRT.

A modified mTNM staging system based on lymph node ratio for colon neuroendocrine tumors: A recursive partitioning analysis.

Background: In the current tumor-lymph node-metastasis (TNM) staging system for colon neuroendocrine tumors, lymph node status is divided into N1 and N0. An assessment of the lymph node ratio (LNR) and a proposal for a modified mTNM staging system were the objectives of this study. Methods: Selecting the optimal cut-off value of LNR was done using X-tile. A Cox regression model and the Kaplan-Meier method were performed to calculate patient cancer-specific survival in the Surveillance, Epidemiology and End Results cohort. Recursive partitioning analysis was used to improve TNM staging. Results: The study included 674 patients. The current TNM staging system showed inadequate discriminatory power between stage I and stage II patients (p = 0.088). The optimal cut-off value was determined as 0.6 for LNR. Based on multivariate Cox regression analysis, the modified mN classification could be classified into mN 0 (LNR = 0.00), mN 1 (LNR = 0.01-0.60), and mN 2 (LNR > 0.60), and was found to be an independent factor affecting prognosis (p < 0.001). Using the American Joint Committee on Cancer T and modified mN classifications, the modified mTNM system was constructed, and it exhibited better prognostic discriminatory power ability than the traditional TNM system (C-index: 0.587 vs. 0.665). Conclusions: Our study determined that LNR is a prognostic factor in colon NET patients. In addition, to more accurately assess the prognosis of colon NET patients, we proposed a modified mTNM staging system.

Direct background-oriented schlieren tomography using radial basis functions.

Background-oriented schlieren tomography (BOST) is effective for flow field measurement; however, different from general computed tomography (CT), the BOST utilizes the deflection of rays passing through an inhomogeneous field for measurement. It is sensitive to the refractive index gradient. Therefore, an additional integration step is typically employed to obtain the refractive index. In this article, a calculation method of projection matrix is proposed based on the radial basis function (RBF). The 3D distribution of the refractive index can be reconstructed directly. This method was first verified by numerical simulation. Then, the 3D instantaneous refractive index field above a candle flame was measured. The reprojection error was calculated by ray tracing. The results illustrate the accuracy and stability of the proposed method. This research provides a new and complete solution for the 3D instantaneous flow field (refractive index, density, or temperature) measurement.

The prognostic significance of different proportion of signet-ring cells of colorectal carcinoma.

While the prognosis of patients with partial SRCC (PSRCC) has been rarely reported, colorectal signet-ring cell carcinoma (SRCC) has been associated with poor prognosis. The aim of this study was to analyze the prognosis of patients with different SRCC composition and establish a prediction model. A total of 91 patients with SRC component were included in the study. These patients were divided into two groups: SRCC group (SRC composition > 50%; n=41) and partial SRCC (PSRCC) group (SRC composition ≤ 50%; n=50). COX regression model was used to identify independent prognostic factors for overall survival (OS). A predictive nomogram was established and compared with the 7th AJCC staging system. After a median follow-up of 16 months, no significant difference in OS was observed in either group. Preoperative carcinoembryonic antigen (CEA) level, pN stage, M stage, preoperative ileus, and adjuvant chemotherapy were independent prognostic risk factors for OS (p<0.05). A nomogram for predicting the overall survival of colorectal SRCC was established with a C-index of 0.800, and it showed better performance than that of the 7th AJCC staging system (p<0.001). In summary, the ratio of SRC component was not an independent prognostic factor of the OS. Those patients with less than 50% of SRC component should be given the same clinical attention. A predictive nomogram for survival based on five independent prognostic factors was developed and showed better performance than the 7th AJCC staging system. This resulted to be helpful for individualized prognosis prediction and risk assessment.

Delineation of colorectal cancer ligand-receptor interactions and their roles in the tumor microenvironment and prognosis.

BACKGROUND: Immunotherapies targeting ligand-receptor interactions (LRIs) are advancing rapidly in the treatment of colorectal cancer (CRC), and LRIs also affect many aspects of CRC development. However, the pattern of LRIs in CRC and their effect on tumor microenvironment and clinical value are still unclear. METHODS: We delineated the pattern of LRIs in 55,539 single-cell RNA sequencing (scRNA-seq) samples from 29 patients with CRC and three bulk RNA-seq datasets containing data from 1411 CRC patients. Then the influence of tumor microenvironment, immunotherapy and prognosis of CRC patients were comprehensively investigated. RESULTS: We calculated the strength of 1893 ligand-receptor pairs between 25 cell types to reconstruct the spatial structure of CRC. We identified tumor subtypes based on LRIs, revealed the relationship between the subtypes and immunotherapy efficacy and explored the ligand-receptor pairs and specific targets affecting the abundance of tumor-infiltrating lymphocytes. Finally, a prognostic model based on ligand-receptor pairs was constructed and validated. CONCLUSION: Overall, through the comprehensive and in-depth investigation of the existing ligand-receptor pairs, this study provides new ideas for CRC subtype classification, a new risk screening tool for CRC patients, and potential ligand-receptor pair targets and pathways for CRC therapy.

Development and Validation of a Robust Pyroptosis-Related Signature for Predicting Prognosis and Immune Status in Patients with Colon Cancer.

BACKGROUND: Pyroptosis has been confirmed as a type of inflammatory programmed cell death in recent years. However, the prognostic role of pyroptosis in colon cancer (CC) remains unclear. METHODS: Dataset TCGA-COAD which came from the TCGA portal was taken as the training cohort. GSE17538 from the GEO database was treated as validation cohorts. Differential expression genes (DEGs) between normal and tumor tissues were confirmed. Patients were classified into two subgroups according to the expression characteristics of pyroptosis-related DEGs. The LASSO regression analysis was used to build the best prognostic signature, and its reliability was validated using Kaplan-Meier, ROC, PCA, and t-SNE analyses. And a nomogram based on the multivariate Cox analysis was developed. The enrichment analysis was performed in the GO and KEGG to investigate the potential mechanism. In addition, we explored the difference in the abundance of infiltrating immune cells and immune microenvironment between high- and low-risk groups. And we also predicted the association of common immune checkpoints with risk scores. Finally, we verified the expression of the pyroptosis-related hub gene at the protein level by immunohistochemistry. RESULTS: A total of 23 pyroptosis-related DEGs were identified in the TCGA cohort. Patients were classified into two molecular clusters (MC) based on DEGs. Kaplan-Meier survival analysis indicated that patients with MC1 represented significantly poorer OS than patients with MC2. 13 overall survival- (OS-) related DEGs in MCs were used to construct the prognostic signature. Patients in the high-risk group exhibited poorer OS compared to those in the low-risk group. Combined with the clinical features, the risk score was found to be an independent prognostic factor of CC patients. The above results are verified in the external dataset GSE17538. A nomogram was established and showed excellent performance. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the varied prognostic performance between high- and low-risk groups may be related to the immune response mediated by local inflammation. Further analysis showed that the high-risk group has stronger immune cell infiltration and lower tumor purity than the low-risk group. Through the correlation between risk score and immune checkpoint expression, T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3) was predicted as a potential therapeutic target for the high-risk group. CONCLUSION: The 13-gene signature was associated with OS, immune cells, tumor purity, and immune checkpoints in CC patients, and it could provide the basis for immunotherapy and predicting prognosis and help clinicians make decisions for individualized treatment.

Value of the log odds of positive lymph nodes for prognostic assessment of colon mucinous adenocarcinoma: Analysis and external validation.

PURPOSE: To evaluate the impact of the log odds of positive lymph nodes (LODDS) on cancer-specific survival (CSS) in colon mucinous adenocarcinoma (MAC) patients, compared with pN stage and the lymph nodes ratio (LNR). METHODS: A total of 10,182 colon MAC patients from the Surveillance, Epidemiology, and End Results database were divided into the training group. The external validation group included 153 patients from Fujian Medical University Union Hospital. The Cox regression method was used to identify prognostic risk factors. Nomograms were evaluated by Harrell's concordance index (C-index) and calibration curves. Recursive partitioning analysis (RPA) was used to develop a novel staging system. RESULTS: Time-dependent receiver operating characteristic curves (ROC) to predict CSS showed the areas under the ROC curve of LODDS were always higher than pN stage and LNR. LNR and LODDS classifications can well distinguish the prognosis of patients with the same pN stage. Cox analyses indicated that age, tumor size, pT stage, pN stage, LNR, and LODDS were independent predictors of CSS (p < 0.05). Based on three lymph nodes classifications, we constructed three prognostic nomograms models for CSS. The C-index of the pN, LNR, and LODDS classification nomograms were 0.746 (95% confidence interval [95% CI]: 0.736-0.756), 0.750 (95% CI: 0.740-0.760), and 0.758 (95% CI: 0.748-0.768), respectively. In external validation, we observed the C-index of LODDS classification nomograms was 0.787 (95% CI: 0.648-0.926). RPA stage, including four stages, was constructed successfully based on pT stage and LNR or LODDS, respectively. The 3-, 5-, and 8-year areas under the ROC curve of LNR-RPA stage and LODDS-RPA stage were superior to tumor-node-metastasis stage. CONCLUSION: LODDS to be a better prognostic factor of CSS for colon MAC patients than pN stage and LNR. A nomogram and RPA stage base on LODDS can provide accurate information for personalized cancer treatment.

Development and validation of a ferroptosis-related lncRNAs prognosis signature in colon cancer.

Ferroptosis is a form of iron-dependent programmed cell death. Regulation of ferroptosis in tumor cells is a novel treatment modality. The present study aimed to investigate ferroptosis-related long non-coding RNAs (lncRNAs) and construct a prognostic model for colon adenocarcinoma (COAD). RNA- sequencing data and ferroptosis-related genes were obtained from The Cancer Genome Atlas database and FerrDb database. COAD patients were randomly assigned to training- and validation groups. The Least Absolute Shrinkage and Selection Operator regression and Cox regression model were used to determine and develop a predictive model. The model was corroborated using the validation group and the entire group. In total, 259 ferroptosis-related genes and 905 ferroptosis-related LncRNAs were obtained. Cox model revealed and constructed seven ferroptosis-related LncRNAs signature (LINC01503, AC004687.1, AC010973.2, AP001189.3, ARRDC1-AS1, OIP5-AS1, and NCK1-DT). Patients were assigned into two groups according to the median risk score. Kaplan-Meier survival curves showed that overall survival between high- and low-risk groups was statistically significant (P<0.01). Cox multivariate analysis seven ferroptosis-related LncRNAs signature was an independent risk factor for COAD outcomes (P<0.05). The relationship between seven ferroptosis-related LncRNAs and clinicopathological features was also examined. The principal component analysis showed a difference between high- and low-risk groups intuitively. With the aid of gene set enrichment analysis, the underlying mechanisms of seven ferroptosis-related LncRNAs were uncovered, including the MAPK signaling pathway, mTOR signaling pathway, and glutathione metabolism pathway. Finally, we established and validated seven ferroptosis-related lncRNAs signature for COAD patients to predict survival. These results may provide meaningful targets for future study.

Association of age and cause-special mortality in patients with stage I/ II colon cancer: A population-based competing risk analysis.

PURPOSE: This study aimed to determine the probability and prognostic factors of colon cancer-specific mortality (CCSM) and noncancer-specific mortality (NCSM) for patients with stage I/II colon cancer and evaluate the association of age on cause-specific mortality. MATERIALS AND METHODS: From Surveillance, Epidemiology, and End Results (SEER) database, we identified 33152 patients with stage I/II colon cancer undergoing surgery between 2004 and 2011. The cumulative incidence of CCSM and NCSM was calculated, and competing risk analysis was performed to investigate prognostic factors for cause-specific mortality. RESULTS: In patients <50, 50-75, and >75 years of age, 5-year cumulative incidence of CCSM was 5.7%, 7.8%, and 16.1%, respectively (overall, 10.6%); 5-year cumulative incidence of NCSM was 2.2%, 7.1%, and 26.9%, respectively (overall, 13.8%). The probability of CCSM and NCSM increased with advanced age. The 5-year cumulative incidence of CCSM was higher than NCSM in patients <50 years of age, whereas lower in patients >75 years of age. The probability of CCSM and NCSM was similar in patients 50-75 years of age. Competing-risk multivariable analysis demonstrated that increasing age was a strong predictor of CCSM (per year increase, SHR 1.03,95% confidence interval [CI]: 1.03-1.04). Age was most predictive of NCSM: (per year increase, SHR 1.08, 95% CI: 1.08-1.08). CONCLUSION: Age was significantly associated with an increased cumulative incidence of CCSM and NCSM of patients with stage I/II colon cancer underwent surgery. NCSM was a significant competing event and should be adequately considered when performing survival analysis.

Flexible multicamera calibration method with a rotating calibration plate.

Camera calibration is necessary for accurate image measurements, particularly in multicamera systems. The calibration process involves corresponding the coordinates of 3D calibration points with a 2D image and requires the establishment of a reliable 3D world coordinate system. This paper presents a convenient multicamera calibration method that uses a rotating calibration plate and multi-view stereo vision to calculate 3D points and their relationship with the image coordinates. Despite simple implementation, the rotation of the calibration plate presents numerous calibration points from various planes, increasing the stability of the solution and the noise reduction. The relocation accuracy and reprojection error are experimentally verified.

Gold-catalyzed intermolecular hydroamination of allenes with sulfonamides.

A co-catalyst of (PPh3)AuCl/AgOTf for the intermolecular hydroamination of allenes with sulfonamides is shown. The reaction proceeded smoothly under mild conditions for differently substituted allenes giving N-allylic sulfonamides in good yields with high regioselectivity and E-selectivity.