Predicting Survival for Hepatic Arterial Infusion Chemotherapy of Unresectable Colorectal Liver Metastases: Radiomics Analysis of Pretreatment Computed Tomography

Predictive factors and prognostic models for Hepatic arterial infusion chemotherapy in Hepatocellular carcinoma: a comprehensive review

Hepatocellular carcinoma (HCC) is a prevalent and lethal cancer, often diagnosed at advanced stages where traditional treatments such as surgical resection, liver transplantation, and locoregional therapies provide limited benefits. Hepatic arterial infusion chemotherapy (HAIC) has emerged as a promising treatment modality for advanced HCC, enhancing anti-tumor efficacy through targeted drug delivery while minimizing systemic side effects. However, the heterogeneous nature of HCC leads to variable responses to HAIC, highlighting the necessity for reliable predictive indicators to tailor personalized treatment strategies. This review explores the factors influencing HAIC success, including patient demographics, tumor characteristics, biomarkers, genomic profiles, and advanced imaging techniques such as radiomics and deep learning models. Additionally, the synergistic potential of HAIC combined with immunotherapy and molecular targeted therapies is examined, demonstrating improved survival outcomes. Prognostic scoring systems and nomograms that integrate clinical, molecular, and imaging data are discussed as superior tools for individualized prognostication compared to traditional staging systems. Understanding these predictors is essential for optimizing HAIC efficacy and enhancing survival and quality of life for patients with advanced HCC. Future research directions include large-scale prospective studies, integration of multi-omics data, and advancements in artificial intelligence to refine predictive models and further personalize treatment approaches.

N-glycosylation of ACTRIIB enhances protein stability leading to rapid cell proliferation and strong resistance to docetaxel in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant tumor predominantly influenced by Epstein-Barr virus infection and genetic factors. The transforming growth factor-beta (TGF-β) superfamily is implicated in various cellular processes, including tumorigenesis. This study aimed to detect the role of one TGF-β superfamily member activin receptor type IIB (ACTRIIB) in NPC. This study analyzed NPC datasets, including GSE12452, GSE102349, and GSE53819. ACTRIIB expression and N-glycosylation levels were assessed by western blot, real-time PCR, immunofluorescence, and immunohistochemistry in NPC cells and tissues. As indicated by the datasets, ACTRIIB was significantly upregulated in NPC tissues, and the up-regulation was associated with poor prognosis. This study confirmed the N-glycosylation of ACTRIIB primarily at the forty-second amino acid, an asparagine. The N-glycosylation of ACTRIIB promoted the localization of ACTRIIB to the cell membrane and prevented the degradation of the protein by lysosomes, through which ACTRIIB activated the downstream Smard1/2 to promote tumor cell proliferation and invasion. Inhibition of N-glycosylation or knockdown of ACTRIIB resulted in reduced cell proliferation and invasion and increased the cell sensitivity to docetaxel. In conclusion, N-glycosylation of ACTRIIB was a critical post-translational modification that enhanced protein stability and induced membrane localization, which facilitates the functions of ACTRIIB in cell proliferation and invasion in NPC. Inhibition of ACTRIIB N-glycosylation could potentially serve as a therapeutic strategy to improve the efficacy of chemotherapy in NPC.

Clinical value of circulating tumour cells in evaluating the efficacy of continuous hepatic arterial infusion among colorectal cancer patients

Few studies have been conducted to evaluate the efficacy of HAIC using circulating tumour cells (CTCs). In this study, a total of 100 patients who received HAIC treatment and CTC detection were selected. The results showed that after HAIC treatment, the levels of CTC, carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) decreased. Postoperative progression-free survival (PFS) rates between patients with positive and negative preoperative CTC results, and for CA19-9, CEA were significantly different. The positive rate of CTCs was 61% before chemotherapy and 23% after chemotherapy, and the correlation coefficient between the two was 0.385. Those whose CTC values increased after chemotherapy had shorter PFS rates. CTCs are an independent predictor of recurrence. Patients with CTC-positive results are more susceptible to recurrence. The CTC count in peripheral blood has a close bearing on the postoperative chemotherapy efficacy of patients with CRC and affects patients' PFS.

Deep learning-based CT radiomics predicts prognosis of unresectable hepatocellular carcinoma treated with TACE-HAIC combined with PD-1 inhibitors and tyrosine kinase inhibitors

OBJECTIVE

To develop and validate a computed tomography (CT)-based deep learning radiomics model to predict treatment response and progression-free survival (PFS) in patients with unresectable hepatocellular carcinoma (uHCC) treated with transarterial chemoembolization (TACE)-hepatic arterial infusion chemotherapy (HAIC) combined with PD-1 inhibitors and tyrosine kinase inhibitors (TKIs).

METHODS

This retrospective study included 172 patients with uHCC who underwent combination therapy of TACE-HAIC with TKIs and PD-1 inhibitors. Among them, 122 were from the Interventional Department of the Harbin Medical University Cancer Hospital, with 92 randomly assigned to the training cohort and 30 cases randomly assigned to the testing cohort. The remaining 50 cases were from the Interventional Department of the Affiliated Fourth Hospital of Harbin Medical University and were used for external validation. All patients underwent liver enhanced CT examination before treatment. Residual convolutional neural network (ResNet) technology was used to extract image features. A predictive model for treatment response of combination therapy and PFS was established based on image features and clinical features. Model effectiveness was evaluated using metrics such as the area under the receiver operating characteristic (ROC) curve (AUC), concordance index (C-index), accuracy, precision, and F1-score.

RESULTS

All patients had a median follow-up of 25.2 months (95% CI 24.4-26.0), with a median PFS of 14.0 months (95% CI 8.5-19.4) and a median overall survival (OS) of 26.2 months (95% CI 15.9-36.4) achieved. Objective response rate (ORR) and disease control rate (DCR) was 41.0% and 55.7%, respectively. In the treatment response prediction model, the AUC for the training cohort reached 0.96, with an accuracy of 89.5%, precision of 85.6%, and F1-score of 0.896; the AUC for the testing cohort was 0.87, with an accuracy of 80.4%, precision of 74.5%, and F1-score of 0.802. The AUC of the external validation cohort was 0.85, with accuracy of 79.1%, precision of 73.6%, and f1-score of 0.784. In the PFS prediction model, the predicted AUC for 12 months, 18 months, and 24 months-PFS in the training cohort were 0.874, 0.809, 0.801, respectively. The AUC of testing cohort were 0.762, 0.804, 0.792. The AUC of external validation cohort were 0.764, 0.796, 0.773. The C-index of the combination model, radiomics model, and clinical model were 0.75, 0.591, and 0.655, respectively. The calibration curve demonstrated that the combination model was significantly superior to both the radiomics and clinical models.

CONCLUSIONS

The study provides a CT-based radiomics model that can predict PFS for patients with uHCC treated with TACE-HAIC combined with PD-1 and TKIs.

TOM40 as a prognostic oncogene for oral squamous cell carcinoma prognosis

BACKGROUND

To investigate the role of the translocase of the outer mitochondrial membrane 40 (TOM40) in oral squamous cell carcinoma (OSCC) with the aim of identifying new biomarkers or potential therapeutic targets.

METHODS

TOM40 expression level in OSCC was evaluated using datasets downloaded from The Cancer Genome Atlas (TCGA), as well as clinical data. The correlation between TOM40 expression level and the clinicopathological parameters and survival were analyzed in TCGA. The signaling pathways associated with TOM40 were identified through gene set enrichment analysis. A network of genes co-expressed with TOM40 was constructed and functionally annotated by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The immune infiltration pattern in OSCC was analyzed in the TCGA-OSCC cohort using the CIBERSORT algorithm. Clinically significant factors of OSCC were screened through the expression levels of TOM40 and a clinically relevant nomogram was constructed. The TCGA-OSCC cohort was divided into the TOM40high and TOM40low groups and the correlation between TOM40 expression level and the sensitivity to frequently used chemotherapeutic drugs was evaluated. CCK-8 and colony formation assays were applied to determine the cell growth.

RESULTS

TOM40 was highly expressed in OSCC tissues and correlated negatively with the overall survival (P < 0.05). Patients with high TOM40 expression level showed worse prognosis. Furthermore, GO and KEGG enrichment analyses of the differentially expressed genes related to TOM40 showed that these genes are mainly associated with immunity and tumorigenesis. Immunological infiltration analysis has found that the expression levels of TOM40 are correlated with the proportions of several immune cells. Moreover, we found that TOM40 knockdown inhibited cell growth in OSCC cell lines.

CONCLUSIONS

Our results uncovered that TOM40 is a reliable prognostic marker and therapeutic target in OSCC.

Development and validation of web-based risk score predicting prognostic nomograms for elderly patients with primary colorectal lymphoma: A population-based study

Background and Objectives

Primary colorectal lymphoma (PCL) is an infrequently occurring form of cancer, with the elderly population exhibiting an increasing prevalence of the disease. Furthermore, advanced age is associated with a poorer prognosis. Accurate prognostication is essential for the treatment of individuals diagnosed with PCL. However, no reliable predictive survival model exists for elderly patients with PCL. Therefore, this study aimed to develop an individualized survival prediction model for elderly patients with PCL and stratify its risk to aid in the treatment and monitoring of patients.

Methods

Patients aged 60 or older with PCL from 1975 to 2013 in the Surveillance, Epidemiology, and End Results database were selected and randomly divided into a training cohort (n = 1305) and a validation cohort (n = 588). The patients from 2014-2015 (n = 207) were used for external validation. The research team utilized both Cox regression and the least absolute shrinkage and selection operator (LASSO) regression to analyze potential predictors, in order to identify the most suitable model for constructing an OS-nomogram and an associated network version. The risk stratification is constructed on the basis of this model. The performance of the model was evaluated based on the consistency index (C-index), calibration curve, and decision curve analysis (DCA) to determine its resolving power and calibration capability.

Results

Age, gender, marital status, Ann Arbor staging, primary site, surgery, histological type, and chemotherapy were independent predictors of Overall Survival (OS) and were therefore included in our nomogram. The Area Under the Curve (AUC) of the 1, 3, and 5-year OS in the training, validation, and external validation sets ranged from 0.732 to 0.829. The Receiver Operating Characteristic (ROC) curves showed that the nomogram model outperformed the Ann Arbor stage system when predicting elderly patients with PCL prognosis at 1, 3, and 5 years in the training set, validation dataset, and external validation cohort. The Concordance Index (C-index) also demonstrated that the nomogram had excellent predictive accuracy and robustness. The calibration curves demonstrated a strong agreement between observed and predicted values. In the external validation cohort, the C-index (0.769, 95%CI: 0.712-0.826) and calibration curves of 1000 bootstrap samples also indicated a high level of concordance between observed and predicted values. The nomogram-related DCA curves exhibited superior clinical utility when compared to Ann Arbor stage. Furthermore, an online prediction tool for overall survival has been developed: https://medkuiwang.shinyapps.io/DynNomapp/.

Conclusion

This was the first study to construct and validate predictive survival nomograms for elderly patients with PCL, which is better than the Ann Arbor stage. It will help clinicians manage elderly patients with PCL more accurately.

Bridging Chronic Inflammation and Digestive Cancer: The Critical Role of Innate Lymphoid Cells in Tumor Microenvironments

The incidence and mortality of digestive system-related cancers have always been high and attributed to the heterogeneity and complexity of the immune microenvironment of the digestive system. Furthermore, several studies have shown that chronic inflammation in the digestive system is responsible for cancer incidence; therefore, controlling inflammation is a potential strategy to stop the development of cancer. Innate Lymphoid Cells (ILC) represent a heterogeneous group of lymphocytes that exist in contrast to T cells. They function by interacting with cytokines and immune cells in an antigen-independent manner. In the digestive system cancer, from the inflammatory phase to the development, migration, and metastasis of tumors, ILC have been found to interact with the immune microenvironment and either control or promote these processes. The conventional treatments for digestive tumors have limited efficacy, therefore, ILC-associated immunotherapies are promising strategies. This study reviews the characterization of different ILC subpopulations, how they interact with and influence the immune microenvironment as well as chronic inflammation, and their promotional or inhibitory role in four common digestive system tumors, including pancreatic, colorectal, gastric, and hepatocellular cancers. In particular, the review emphasizes the role of ILC in associating chronic inflammation with cancer and the potential for enhanced immunotherapy with cytokine therapy and adoptive immune cell therapy.

The role of coagulopathy and subdural hematoma thickness at admission in predicting the prognoses of patients with severe traumatic brain injury: a multicenter retrospective cohort study from China

BACKGROUND

Traumatic brain injury (TBI) is one of the diseases with high disability and mortality worldwide. Recent studies have shown that TBI-related factors may change the complex balance between bleeding and thrombosis, leading to coagulation disorders. The aim of this retrospective study was to investigate the prediction of coagulopathy and subdural hematoma thickness at admission using the Glasgow Outcome Scale (GOS) in patients with severe TBI at 6 months after discharge.

METHODS

In this retrospective cohort study, a total of 1006 patients with severe TBI in large medical centers in three different provinces of China from June 2015 to June 2021 were enrolled after the exclusion criteria, and 800 patients who met the enrollment criteria were included. A receiver operating characteristic (ROC) curve was used to determine the best cut-off values of platelet (PLT), international normalized ratio (INR), activated partial thromboplastin time (APTT), and subdural hematoma (SDH) thickness. The ROC curve, nomogram, calibration curve, and the decision curve were used to evaluate the predictive effect of the coagulopathy and Coagulopathy-SDH(X1) models on the prognoses of patients with severe TBI, and the importance of predictive indicators was ranked by machine learning.

RESULTS

Among the patients with severe TBI on admission, 576/800 (72%) had coagulopathy, 494/800 (61%) had SDH thickness ≥14.05 mm, and 385/800 (48%) had coagulopathy combined with SDH thickness ≥14.05 mm. Multivariate logistic regression analyses showed that age, pupil, brain herniation, WBC, CRP, SDH, coagulopathy, and X1 were independent prognostic factors for GOS after severe TBI. Compared with other single indicators, X1 as a predictor of the prognosis of severe TBI was more accurate. The GOS of patients with coagulopathy and thick SDH (X1, 1 point) at 6 months after discharge was significantly worse than that of patients with coagulopathy and thin SDH (X1, 2 points), patients without coagulopathy and thick SDH (X1, 3 point), and patients without coagulopathy and thin SDH (X1, 4 points). In the training group, the C-index based on the coagulopathy nomogram was 0.900. The C-index of the X1-based nomogram was 0.912. In the validation group, the C-index based on the coagulopathy nomogram was 0.858. The C-index of the X1-based nomogram was 0.877. Decision curve analysis also confirmed that the X1-based model had a higher clinical net benefit of GOS at 6 months after discharge than the coagulopathy-based model in most cases, both in the training and validation groups. In addition, compared with the calibration curve based on the coagulopathy model, the prediction of the X1 model-based calibration curve for the probability of GOS at 6 months after discharge showed better agreement with actual observations. Machine learning compared the importance of each independent influencing factor in the evaluation of GOS prediction after TBI, with results showing that the importance of X1 was better than that of coagulopathy alone.

CONCLUSION

Coagulopathy combined with SDH thickness could be used as a new, accurate, and objective clinical predictor, and X1, based on combining coagulopathy with SDH thickness could be used to improve the accuracy of GOS prediction in patients with TBI, 6 months after discharge.

Prognostication of colorectal cancer liver metastasis by CE-based radiomics and machine learning

The liver is the most common organ for the formation of colorectal cancer metastasis. Non-invasive prognostication of colorectal cancer liver metastasis (CRLM) may better inform clinicians for decision-making. Contrast-enhanced computed tomography images of 180 CRLM cases were included in the final analyses. Radiomics features, including shape, first-order, wavelet, and texture, were extracted with Pyradiomics, followed by feature engineering by penalized Cox regression. Radiomics signatures were constructed for disease-free survival (DFS) by both elastic net (EN) and random survival forest (RSF) algorithms. The prognostic potential of the radiomics signatures was demonstrated by Kaplan-Meier curves and multivariate Cox regression. 11 radiomics features were selected for prognostic modelling for the EN algorithm, with 835 features for the RSF algorithm. Survival heatmap indicates a negative correlation between EN or RSF risk scores and DFS. Radiomics signature by EN algorithm successfully separates DFS of high-risk and low-risk cases in the training dataset (log-rank test: p < 0.01, hazard ratio: 1.45 (1.07-1.96), p < 0.01) and test dataset (hazard ratio: 1.89 (1.17-3.04), p < 0.05). RSF algorithm shows a better prognostic implication potential for DFS in the training dataset (log-rank test: p < 0.001, hazard ratio: 2.54 (1.80-3.61), p < 0.0001) and test dataset (log-rank test: p < 0.05, hazard ratio: 1.84 (1.15-2.96), p < 0.05). Radiomics features have the potential for the prediction of DFS in CRLM cases.

Understanding the heterogeneity in liver hepatocellular carcinoma with a special focus on malignant cell through single-cell analysis

INTRODUCTION

Hepatocellular carcinoma (HCC) is the most common form of liver cancer globally and remains a major cause of cancer-related deaths. HCC exhibits significant intra-tumoral and interpatient heterogeneity, impacting treatment efficacy and patient prognosis.

METHODS

We acquired transcriptome data from the TCGA and ICGC databases, as well as liver cancer chip data from the GEO database, and processed the data for subsequent analysis. We also obtained single cell data from the GEO database and performed data analysis using the Seurat package. To further investigate epithelial cell subgroups and their copy number variations, we used the Seurat workflow for subgroup classification and the InferCNV software for CNV analysis, utilizing endothelial cells as a reference. Pseudo-time analysis and transcription factor analysis of epithelial cells were performed using the monocle2 and SCENIC software, respectively. To assess intercellular communication, we employed the CellChat package to identify potential ligand-receptor interactions. We also analyzed gene expression differences and conducted enrichment analysis using the limma and clusterProfiler packages. Additionally, we established tumor-related risk characteristics using Cox analysis and Lasso regression, and predicted immunotherapy response using various datasets.

RESULTS

The samples were classified into 23 clusters, with malignant epithelial cells being the majority. Trajectory analysis revealed the differentiation states of the malignant epithelial cells, with cluster 1 being in the terminal state. Functional analysis revealed higher aggressiveness and epithelial-mesenchymal transition (EMT) scores in cluster 1, indicating a higher propensity for metastasis. RBP4+ tumor cells were highly enriched with hypoxia process and intensive cell-to-cell communication. A prognostic model was established, and immune infiltration analysis showed increased infiltration in the high-risk group. TP53 demonstrated significant differences in mutation rate between the two risk groups. Validation analysis confirmed the up-regulation of model genes, including AKR1B10, ARL6IP4, ATP6V0B, and BSG in tumor tissues.

CONCLUSION

A prognostic model was established based on HCC malignant cell associated gene signature, displaying decent prognosis guiding effectiveness in the multiple cohorts. The study provided comprehensive insights into the heterogeneity and potential therapeutic targets of LIHC.

Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma

Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.

Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma

Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.

Qualitative exploration of home life experiences and care needs among elderly patients with temporary intestinal stomas

BACKGROUND

This study employed a phenomenological research approach within qualitative research to explore the challenges encountered by elderly individuals with temporary colostomies in managing their daily lives and care needs. Protecting the anus surgery combined with temporary colostomy has emerged as a prevalent treatment modality for low rectal cancer. However, the ileostomy is susceptible to peri-stoma skin complications, as well as fluid, electrolyte, and nutritional imbalances, posing challenges to effective management. The successful self-management of patients is intricately linked to their adjustment to temporary colostomy; nonetheless, there remains a dearth of research examining the factors influencing self-care among temporary colostomy patients and the obstacles they confront.

AIM

To investigate the lived experiences, perceptions, and care requirements of temporary colostomy patients within their home environment, with the ultimate goal of formulating a standardized management protocol.

METHODS

Over the period of June to August 2023, a purposive sampling technique was utilized to select 12 patients with temporary intestinal stomas from a tertiary hospital in Shanghai, China. Employing a phenomenological research approach, a semi-structured interview guide was developed, and qualitative interviews were conducted using in-depth interview techniques. The acquired data underwent coding, analysis, organization, and summarization following Colaizzi's seven-step method.

RESULTS

The findings of this study revealed that the experiences and needs of patients with temporary intestinal stomas can be delineated into four principal themes: Firstly, Temporary colostomy patients bear various burdens and concerns about the uncertainty of disease progression; secondly, patients exhibit limited self-care capabilities and face information deficits, resulting in heightened reliance on healthcare professionals; thirdly, patients demonstrate the potential for internal motivation through proactive self-adjustment; and finally, patients express a significant need for emotional and social support.

CONCLUSION

Home-living patients with temporary intestinal stomas confront multifaceted challenges encompassing burdens, inadequate self-care abilities, informational deficits, and emotional needs. Identifying factors influencing patients' self-care at home and proposing strategies to mitigate barriers can serve as a foundational framework for developing and implementing nursing interventions tailored to the needs of patients with temporary intestinal stomas.

Integrating transcriptomics and machine learning for immunotherapy assessment in colorectal cancer

Colorectal cancer (CRC) is a highly prevalent and lethal malignancy worldwide. Although immunotherapy has substantially improved CRC outcomes, intolerance remains a major concern among most patients. Considering the pivotal role of the tumor microenvironment (TME) in tumor progression and treatment outcomes, profiling the TME at the transcriptomic level can provide novel insights for developing CRC treatment strategies. Seventy-seven TME-associated signatures were acquired from previous studies. To elucidate variations in prognosis, clinical features, genomic alterations, and responses to immunotherapy in CRC, we employed a non-negative matrix factorization algorithm to categorize 2595 CRC samples of 27 microarrays from the Gene Expression Omnibus database. Three machine learning techniques were employed to identify a signature specific to immunotherapy. Subsequently, the mechanisms by which this signature interacts with TME subtypes and immunotherapy were investigated. Our findings revealed five distinct TME subtypes (TMESs; TMES1-TMES5) in CRC, each exhibiting a unique pattern of immunotherapy response. TMES1, TMES4, and TMES5 had relatively inferior outcomes, TMES2 was associated with the poorest prognosis, and TMES3 had a superior outcome. Subsequent investigations revealed that activated dendritic cells could enhance the immunotherapy response rate, with their augmentation effect closely associated with the activation of CD8+T cells. We successfully classified CRC into five TMESs, each demonstrating varying response rates to immunotherapy. Notably, the application of machine learning to identify activated dendritic cells helped elucidate the underlying mechanisms contributing to these differences. We posit that these TMESs hold promising clinical implications for prognostic evaluation and guidance of immunotherapy strategies, thereby providing valuable insights to inform clinical decision-making.

Epidemiology and early screening strategies for colorectal cancer in China

China ranks the first worldwide in the number of new colorectal cancer (CRC) cases and CRC-related deaths. The increasing incidence of early-onset CRC in recent years highlights the challenges related to CRC screening and prevention. High-quality colonoscopy is the universally used gold standard for CRC screening. Risk assessment combined with a two-step screening strategy based on colonoscopy and non-invasive examinations was proven to be highly effective. However, systematic use of well-established risk factors associated with CRC, beyond age, could better identify those who might harbor advanced colorectal neoplasia, improve the diagnostic yield of current screening modalities, and optimize the selection of individuals who might benefit most from preventive strategies. "Personalization" and "Standardization" are the future development directions of CRC screening, from the initiation of screening in those at high risk for CRC to follow-up after treatment, which are the key to ensure the screening efficiency.

Predicting cutaneous malignant melanoma patients' survival using deep learning: a retrospective cohort study

BACKGROUND

Cutaneous malignant melanoma (CMM) has the worst prognosis among skin cancers, especially metastatic CMM. Predicting its prognosis accurately could direct clinical decisions.

METHODS

The Surveillance, Epidemiology, and End Results database was screened to collect CMM patients' data. According to diagnosed time, patients were subdivided into three cohorts, train cohort (diagnosed between 2010 and 2013), validation cohort (diagnosed in 2014), and test cohort (diagnosed in 2015). Train cohort was used to train deep learning survival model for cutaneous malignant melanoma (DeepCMM). DeepCMM was then evaluated in train cohort and validation cohort internally, and validated in test cohort externally.

RESULTS

DeepCMM showed 0.8270 (95% CI, confidence interval, CI 0.8260-0.8280) as area under the receiver operating characteristic curve (AUC) in train cohort, 0.8274 (95% CI 0.8286-0.8298) AUC in validation cohort, and 0.8303 (95% CI 0.8289-0.8316) AUC in test cohort. Then DeepCMM was packaged into a Windows 64-bit software for doctors to use.

CONCLUSION

Deep learning survival model for cutaneous malignant melanoma (DeepCMM) can offer a reliable prediction on cutaneous malignant melanoma patients' overall survival.

Mucosal esophageal carcinoma following endoscopic submucosal dissection with giant gastric metastasis: A case report and review of literature

BACKGROUND

Esophageal carcinoma is a highly aggressive digestive cancer responsible for a notable proportion of cancer-related deaths worldwide. Its elevated metastatic rate contributes to a poor prognosis in affected patients. In this case review, we aim to summarize the metastatic characteristics of intramural gastric metastasis (IGM) in mucosal esophageal squamous carcinoma.

CASE SUMMARY

A 56-year-old man was admitted to our hospital because of a dry cough with an esophageal sensation for one year. Endoscopic examination revealed a 2.0 cm 1.0 cm, superficial esophageal squamous cell carcinoma, and the patient underwent endoscopic submucosal dissection (ESD). Fifteen months after ESD, positron emission tomography/computed tomography revealed that the metabolism of the stomach cardia wall had increased slightly. However, the mucosa of the gastric cardia was smooth under gastroendoscopy. Two years after ESD, endoscopic examination revealed a giant gastric cardia carcinoma, while the esophageal mucosa was smooth, and no advanced cancer was found. A biopsy of the gastric cardia indicated squamous-cell carcinoma. The patient received immunochemotherapy and radiotherapy for esophageal cancer for 8 mo and is currently under follow-up.

CONCLUSION

Early-stage esophageal carcinoma with IGM is rare. Despite the ESD of the primary lesion, IGM may still occur and should be closely monitored after ESD.

Circulating tumor cells as potential prognostic biomarkers for early-stage pancreatic cancer: A systematic review and meta-analysis

BACKGROUND

Pancreatic cancer is difficult to be diagnosed early clinically, while often leads to poor prognosis. If optimal personalized treatment plan can be provided to pancreatic cancer patient at an earlier stage, this can greatly improve overall survival (OS). Circulating tumor cells (CTCs) are a collective term for various types of tumor cells present in the peripheral blood (PB), which are formed by detachment during the development of solid tumor lesions. Most CTCs undergo apoptosis or are phagocytosed after entering the PB, whereas a few can escape and anchor at distal sites to develop metastasis, increasing the risk of death for patients with malignant tumors.

AIM

To investigate the significance of CTCs in predicting the prognosis of early pancreatic cancer patients.

METHODS

The PubMed, EMBASE, Web of Science, Cochrane Library, China National Knowledge Infrastructure, China Biology Medicine, and ChinaInfo databases were searched for articles published through December 2022. Studies were considered qualified if they included patients with early pancreatic cancer, analyzed the prognostic value of CTCs, and were full papers reported in English or Chinese. Researches were selected and assessed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol and the Newcastle-Ottawa Scale criteria. We used a funnel plot to assess publication bias.

RESULTS

From 1595 publications, we identified eight eligible studies that collectively enrolled 355 patients with pancreatic cancer. Among these original studies, two were carried out in China; three in the United States; and one each in Italy, Spain, and Norway. All eight studies analyzed the relevance between CTCs and the prognosis of patients with early-stage pancreatic cancer after surgery. A meta-analysis showed that the patients that were positive pre-treatment or post-treatment for CTCs were associated with decreased OS [hazard ratio (HR) = 1.93, 95% confidence interval (CI): 1.197-3.126, P = 0.007] and decreased relapse-free/disease-free/progression-free survival (HR = 1.27, 95%CI: 1.137-1.419, P < 0.001) in early-stage pancreatic cancer. Additionally, the results suggest no statistically noticeable publication bias for overall, disease-free, progression-free, and recurrence-free survival.

CONCLUSION

This pooled meta-analysis shows that CTCs, as biomarkers, can afford reliable prognostic information for patients with early-stage pancreatic cancer and help develop individualized treatment plans.

Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment

OBJECTIVE

The aim of this study was the evaluation radiomics analysis efficacy performed using computed tomography (CT) and magnetic resonance imaging in the prediction of colorectal liver metastases patterns linked to patient prognosis: tumor growth front; grade; tumor budding; mucinous type. Moreover, the prediction of liver recurrence was also evaluated.

METHODS

The retrospective study included an internal and validation dataset; the first was composed by 119 liver metastases from 49 patients while the second consisted to 28 patients with single lesion. Radiomic features were extracted using PyRadiomics. Univariate and multivariate approaches including machine learning algorithms were employed.

RESULTS

The best predictor to identify tumor growth was the Wavelet_HLH_glcm_MaximumProbability with an accuracy of 84% and to detect recurrence the best predictor was wavelet_HLH_ngtdm_Complexity with an accuracy of 90%, both extracted by T1-weigthed arterial phase sequence. The best predictor to detect tumor budding was the wavelet_LLH_glcm_Imc1 with an accuracy of 88% and to identify mucinous type was wavelet_LLH_glcm_JointEntropy with an accuracy of 92%, both calculated on T2-weigthed sequence. An increase statistically significant of accuracy (90%) was obtained using a linear weighted combination of 15 predictors extracted by T2-weigthed images to detect tumor front growth. An increase statistically significant of accuracy at 93% was obtained using a linear weighted combination of 11 predictors by the T1-weigthed arterial phase sequence to classify tumor budding. An increase statistically significant of accuracy at 97% was obtained using a linear weighted combination of 16 predictors extracted on CT to detect recurrence. An increase statistically significant of accuracy was obtained in the tumor budding identification considering a K-nearest neighbors and the 11 significant features extracted T1-weigthed arterial phase sequence.

CONCLUSIONS

The results confirmed the Radiomics capacity to recognize clinical and histopathological prognostic features that should influence the choice of treatments in colorectal liver metastases patients to obtain a more personalized therapy.

Dextran-based micelles for combinational chemo-photodynamic therapy of tumors via in vivo chemiluminescence

Natural polysaccharides, represented by dextran, chitosan, and hyaluronic acid, are widely approved for use as pharmaceutical excipients and are important carrier materials for the design of advanced drug delivery systems, particularly in the field of anticancer drug delivery. The combination of stimuli-activable prodrug based chemotherapy and photodynamic therapy (PDT) has attracted increasing attention. Recent studies have verified the effectiveness of this strategy in the treatment of multiple aggressive cancers. However, in such combination, the stimuli-responsive chemotherapy and PDT have their own problems that need to be overcome. The uneven distribution of endogenous stimuli within tumor tissues makes it difficult for prodrug to be completely activated. And the inadequate tissue penetration depth of external light results in low efficiency of PDT. Aiming at these two bottlenecks, we designed a biocompatible dextran based - multi-component nanomedicine (PCL-NPs) that integrate a chemiluminescence agent luminol, a photosensitizer chlorine e6 (Ce6), and a reactive oxygen species (ROS)-activable thioketal-based paclitaxel (PTX) prodrug. The presence of overexpressed hydrogen peroxide (H2O2) inside tumor oxidizes the luminol moiety to generate in-situ light for PDT through chemiluminescence resonance energy transfer (CRET). The singlet oxygen (1O2) produced in this process not only directly kills tumor cells but also amplifies oxidative stress to accelerate the activation of PTX prodrug. We propose that the PCL-NPs have great therapeutic potential by simultaneously enhancing chemotherapy and PDT in a combination therapy.

Does the use of computed tomography scenogram alone enable diagnosis in cases of bowel obstruction?

BACKGROUND

Ileus is a pathological condition of the abdomen that presents as a medical emergency. It is characterized by potential complications such as perforation and ischemia, which can lead to significant morbidity and mortality if not promptly addressed. The successful management of ileus relies heavily on the timely and precise identification of the condition. While conventional radiography (CR) is commonly used as the primary diagnostic tool, its accuracy in identifying obstructions ranges from 46% to 80%. Furthermore, the diagnostic accuracy of identifying the location and etiology of intestinal obstruction by CR is limited, therefore making computed tomography (CT) the ideal imaging modality in this regard.

AIM

To determine the presence of acute bowel obstruction (BO) on abdominal CT scenogram images and the accuracy of determining its possible location, taking into account the experience of the observers.

METHODS

A retrospective screening was conducted on an ensemble of 46 individuals who presented to the emergency department between January 2021 and January 2022 with severe abdominal pain and were subsequently monitored for suspected ileus. The abdominal CT scans of these patients were assessed by three radiologists with varying levels of experience (1, 3, and 10 years) at different intervals (1 mo apart). The evaluation focused on determining the presence or absence of BO, as well as identifying the potential location of the obstruction (small bowel or large bowel). The study employed Kappa statistics to assess inter-observer variances, while the McNamer test was used to evaluate obstruction and segmentation discrepancies between observations. A significance level of P < 0.05 was determined to indicate statistical significance.

RESULTS

Out of the total sample size of 46 patients, 15 individuals (32.6%) were identified as female, while the remaining 31 individuals (67.4%) were identified as male. The ultimate diagnosis of 42 instances (91.3%) indicated ileus resulting from mechanical obstruction (MO). Among these patients, 14 (33%) experienced obstruction in the large bowel (LB), while 28 (66%) experienced obstruction in the small bowel (SB). The initial evaluation yielded sensitivity rates of 76.19%, 83.31%, and 83.33%, and diagnostic accuracy rates of 69.56%, 76.08%, and 80.43% for the detection of BO among the three observers. The initial study revealed that the average sensitivity of three observers in detecting the presence of ileus caused by MO was 80.94%, while the diagnostic accuracy was 75.35%. Based on the first evaluation, the senior observer demonstrated the highest sensitivity (85.71%), negative predictive value (92.60%), and diagnostic accuracy (80.43%) when accurately estimating the thick and thin segmentation, as per the final diagnosis. There was no statistically significant disparity observed in the sensitivities pertaining to the identification of ileus during the second assessment, as well as the precise determination of the segment level inside the LB or SB, when comparing the second and third observers. Nevertheless, although there was no statistically significant alteration in the detection rate of ileus by the first observer, there was a notable rise in the accuracy rate of segment estimating (73.91%). The senior assessor had a higher level of accuracy in assessing the existence of ileus and segmentation compared to the other evaluators in both evaluations.

CONCLUSION

The findings of our study indicate that the sensitivity and accuracy rates of abdominal CT scenogram scans in diagnosing acute MOs are similar to or greater than those of CR. Additionally, the study revealed that radiologists with more experience demonstrated a higher likelihood of accurately predicting the existence and potential localization of MO compared to their less experienced counterparts.

Exosomes-mediated transfer of LINC00691 regulates the formation of CAFs and promotes the progression of gastric cancer

OBJECTIVE

Gastric cancer (GC) is one of the malignant tumors with the highest mortality worldwide. Our previous studies have revealed that LINC00691 is up-regulated in serum of GC patients as a novel potential biomarker for GC diagnosis and prognosis. However, the roles of serum exosomal LINC00691 in GC has not been clarified. This study aimed to find the expression pattern of serum exosomal LINC00691 in GC patients and the correlation between the level of serum exosomal LINC00691 and the pathology of gastric cancer patients.

METHODS

We collected the serum of 94 GC patients before surgery and extracted exosomes to detect the expression level of exosomal LINC00691, with 21 healthy volunteers and 17 patients with benign gastric diseases as controls. Surgical GC tissues and paired healthy tissues were collected to culture primary cancer-associated fibroblasts (CAFs) and normal fibroblasts (NFs). We then treated NFs with LINC00691-rich GC cell culture supernatant or exosomes and detected the activation markers and biological functions of the fibroblasts.

RESULTS

The results of real-time qPCR indicated that the serum exosomal LINC00691 of GC patients was significantly higher than that of healthy subjects and patients with benign gastric diseases, and was associated with the clinicopathology of GC patients. More interestingly, when the NFs were treated with GC exosomes, the level of LINC00691 was significantly increased, the cell proliferation and migration were noticeably enhanced, and the ability to accelerate GC cell proliferation and invasion was promoted, which means that the induced fibroblasts gained the properties of CAFs. In addition, we found that knockdown of LINC00691 and the use of the JAK2/STAT3 signaling pathway inhibitor ruxolitinib effectively deprived exosome-containing GC cell supernatants of the effects on NFs.

CONCLUSION

Our study suggested that exosomal LINC00691 promoted NFs to gained the properties of CAFs depending on JAK2/STAT3 signaling pathway as a potential diagnostic biomarker for GC.

Research progress on drug delivery systems for curcumin in the treatment of gastrointestinal tumors

Curcumin is a natural compound with a diketone structure, which can control the growth, metastasis, recurrence, neovascularization, invasion, and drug resistance of gastrointestinal tumors by inhibiting nuclear factor κB, overexpression of tumor cells, vascular endothelial growth factor, etc. However, due to the low bioavailability of curcumin formulation, it did not fully exert its pharmacological effects, and its application and development in the treatment of various malignant tumors are still limited. This review summarizes the research on drug delivery systems of curcumin combating digestive tract tumors in order to further reduce the toxic side effects of curcumin-containing drugs and fully exert their pharmacological activities, and improve their bioavailability and clinical value.

Progress of PD-1/PD-L1 signaling in immune response to liver transplantation for hepatocellular carcinoma

Primary liver cancer is one of the most common malignant tumors in China. The vast majority of primary liver cancer are hepatocellular carcinoma. Due to its high incidence and mortality from HCC, HCC has always been a feared type of cancer. Liver transplantation, as one of the important means to treat advanced liver cancer, has brought new hope to patients. However, as patients have been in a state of immunosuppression after liver transplantation, these patients face new problems of HCC recurrence and metastasis. A increasing number of studies have proved that blocking the PD-1/PD-L1 signaling pathway and restoring the immune killing inhibition of T cells can produce better therapeutic effects on tumors and chronic infectious diseases. As a promising treatment in the field of tumor immunotherapy, PD-1/PD-L1 inhibitors have achieved important results in liver cancer patients, but their application in liver transplantation patients is still highly controversial. This paper will introduce the mechanism of action of PD-1/PD-L1 signaling pathway and the current basic and clinical studies of PD-1/PD-L1 signaling pathway associated with immune response in HCC transplantation.

Emerging role of autophagy in colorectal cancer: Progress and prospects for clinical intervention

Autophagy is a physiological mechanism in which cells degrade themselves and quickly recover the degraded cell components. Recent studies have shown that autophagy plays an important role in the occurrence, development, treatment, and prognosis of colorectal cancer. In the early stages of colorectal cancer, autophagy can inhibit the production and development of tumors through multiple mechanisms such as maintaining DNA stability, inducing tumor death, and enhancing immune surveillance. However, as colorectal cancer progresses, autophagy may mediate tumor resistance, enhance tumor metabolism, and other pathways to promote tumor development. Therefore, intervening in autophagy at the appropriate time has broad clinical application prospects. This article summarizes the recent research progress of autophagy and colorectal cancer and is expected to provide new theoretical basis and reference for clinical treatment of colorectal cancer.

Endoscopic and pathological characteristics of de novo colorectal cancer: Retrospective cohort study

BACKGROUND

Endoscopy has rapidly developed in recent years and has enabled further investigation into the origin and features of intestinal tumors. The small size and concealed position of these tumors make it difficult to distinguish them from nonneoplastic polyps and carcinoma in adenoma (CIA). The invasive depth and metastatic potential determine the operation regimen, which in turn affects the overall survival and distant prognosis. The previous studies have confirmed the malignant features and clinicopathological features of de novo colorectal cancer (CRC).

AIM

To provide assistance for diagnosis and treatment, but the lack of a summary of endoscopic features and assessment of risk factors that differ from the CIA prompted us to conduct this retrospective study.

METHODS

In total, 167 patients with small-sized CRCs diagnosed by endoscopy were reviewed. The patients diagnosed as advanced CRCs and other malignant cancers or chronic diseases that could affect distant outcomes were excluded. After screening, 63 cases were excluded, including 33 de novo and 30 CIA cases. Patient information, including their follow-up information, was obtained from an electronic His-system. The characteristics between two group and risk factors for invasion depth were analyzed with SPSS 25.0 software.

RESULTS

Nearly half of the de novo CRCs were smaller than 1 cm (n = 16, 48.5%) and the majority were located in the distal colon (n = 26, 78.8%). The IIc type was the most common macroscopic type of de novo CRC. In a Pearson analysis, the differential degree, Sano, JNET, and Kudo types, surrounding mucosa, and chicken skin mucosa (CSM) were correlated with the invasion depth (P < 0.001). CSM was a significant risk factor for deep invasion and disturbed judgment of endoscopic ultrasound. A high degree of tumor budding and tumor-infiltrating lymphocytes are accompanied by malignancy. Finally, de novo CRCs have worse outcomes than CIA CRCs.

CONCLUSION

This is the first comprehensive study to analyze the features of de novo CRCs to distinguish them from nonneoplastic polyps. It is also the first study paying attention to CSM invasive depth measurement. This study emphasizes the high metastatic potential of de novo CRCs and highlights the need for more research on this tumor type.

Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics

In this narrative review, we reported un up-to-date on the role of radiomics to assess prognostic features, which can impact on the liver metastases patient treatment choice. In the liver metastases patients, the possibility to assess mutational status (RAS or MSI), the tumor growth pattern and the histological subtype (NOS or mucinous) allows a better treatment selection to avoid unnecessary therapies. However, today, the detection of these features require an invasive approach. Recently, radiomics analysis application has improved rapidly, with a consequent growing interest in the oncological field. Radiomics analysis allows the textural characteristics assessment, which are correlated to biological data. This approach is captivating since it should allow to extract biological data from the radiological images, without invasive approach, so that to reduce costs and time, avoiding any risk for the patients. Several studies showed the ability of Radiomics to identify mutational status, tumor growth pattern and histological type in colorectal liver metastases. Although, radiomics analysis in a non-invasive and repeatable way, however features as the poor standardization and generalization of clinical studies results limit the translation of this analysis into clinical practice. Clear limits are data-quality control, reproducibility, repeatability, generalizability of results, and issues related to model overfitting.

Dynamic radiomics for predicting the efficacy of antiangiogenic therapy in colorectal liver metastases

Background and objective

For patients with advanced colorectal liver metastases (CRLMs) receiving first-line anti-angiogenic therapy, an accurate, rapid and noninvasive indicator is urgently needed to predict its efficacy. In previous studies, dynamic radiomics predicted more accurately than conventional radiomics. Therefore, it is necessary to establish a dynamic radiomics efficacy prediction model for antiangiogenic therapy to provide more accurate guidance for clinical diagnosis and treatment decisions.

Methods

In this study, we use dynamic radiomics feature extraction method that extracts static features using tomographic images of different sequences of the same patient and then quantifies them into new dynamic features for the prediction of treatmentefficacy. In this retrospective study, we collected 76 patients who were diagnosed with unresectable CRLM between June 2016 and June 2021 in the First Hospital of China Medical University. All patients received standard treatment regimen of bevacizumab combined with chemotherapy in the first-line treatment, and contrast-enhanced abdominal CT (CECT) scans were performed before treatment. Patients with multiple primary lesions as well as missing clinical or imaging information were excluded. Area Under Curve (AUC) and accuracy were used to evaluate model performance. Regions of interest (ROIs) were independently delineated by two radiologists to extract radiomics features. Three machine learning algorithms were used to construct two scores based on the best response and progression-free survival (PFS).

Results

For the task that predict the best response patients will achieve after treatment, by using ROC curve analysis, it can be seen that the relative change rate (RCR) feature performed best among all features and best in linear discriminantanalysis (AUC: 0.945 and accuracy: 0.855). In terms of predicting PFS, the Kaplan-Meier plots suggested that the score constructed using the RCR features could significantly distinguish patients with good response from those with poor response (Two-sided P<0.0001 for survival analysis).

Conclusions

This study demonstrates that the application of dynamic radiomics features can better predict the efficacy of CRLM patients receiving antiangiogenic therapy compared with conventional radiomics features. It allows patients to have a more accurate assessment of the effect of medical treatment before receiving treatment, and this assessment method is noninvasive, rapid, and less expensive. Dynamic radiomics model provides stronger guidance for the selection of treatment options and precision medicine.

Ultrasound Assessment of the Rectus Femoris in Patients with Chronic Obstructive Pulmonary Disease Predicts Sarcopenia

PURPOSE

Sarcopenia, an age-related loss of skeletal muscle mass and function, is frequent in patients with chronic obstructive pulmonary disease (COPD) and is linked to a poor prognosis. The diagnosis of sarcopenia requires specific equipment and is inconvenient to introduce into clinical practice. Ultrasound is an innovative method to assess muscle quantity. The objective of this research was to evaluate the use of ultrasound for prospectively screening for sarcopenia in COPD patients.

PATIENTS AND METHODS

A total of 235 stable patients with COPD were included in this observational study and divided into development and validation sets. The Asian Working Group for Sarcopenia standards were used to define sarcopenia. The thickness (RF_thick) and cross-sectional area (RF_csa) of the rectus femoris were measured using ultrasound. Receiver operating characteristic curve analysis of RF_thick and RF_csa was used to predict sarcopenia. Nomogram models were constructed based on RF_thick, RF_csa, age and body mass index to identify sarcopenia.

RESULTS

Sarcopenia was present in 83 (35.32%) patients. Patients with sarcopenia had advanced age, decreased pulmonary function, decreased physical function and poor clinical outcomes. RF_thick and RF_csa showed good predictive ability for sarcopenia in the development and validation sets. The nomogram based on RF_thick and RF_csa could detect sarcopenia in COPD patients, and all had significant predictive performance in the development and validation sets. The calibration plot showed good agreement between the nomogram predictions and actual observations.

CONCLUSION

The ultrasound measurement of the rectus femoris has potential for the clinical assessment of sarcopenia in patients with COPD.