Serum Tumor Markers and Outcomes in Patients With Appendiceal Adenocarcinoma

Defining a 'cells to society' research framework for appendiceal tumours

Tumours of the appendix - a vestigial digestive organ attached to the colon - are rare. Although we estimate that around 3,000 new appendiceal cancer cases are diagnosed annually in the USA, the challenges of accurately diagnosing and identifying this tumour type suggest that this number may underestimate true population incidence. In the current absence of disease-specific screening and diagnostic imaging modalities, or well-established risk factors, the incidental discovery of appendix tumours is often prompted by acute presentations mimicking appendicitis or when the tumour has already spread into the abdominal cavity - wherein the potential misclassification of appendiceal tumours as malignancies of the colon and ovaries also increases. Notwithstanding these diagnostic difficulties, our understanding of appendix carcinogenesis has advanced in recent years. However, there persist considerable challenges to accelerating the pace of research discoveries towards the path to improved treatments and cures for patients with this group of orphan malignancies. The premise of this Expert Recommendation article is to discuss the current state of the field, to delineate unique challenges for the study of appendiceal tumours, and to propose key priority research areas that will deliver a more complete picture of appendix carcinogenesis and metastasis. The Appendix Cancer Pseudomyxoma Peritonei (ACPMP) Research Foundation Scientific Think Tank delivered a consensus of core research priorities for appendiceal tumours that are poised to be ground-breaking and transformative for scientific discovery and innovation. On the basis of these six research areas, here, we define the first 'cells to society' research framework for appendix tumours.

Overview: Challenges of Treating Peritoneal Surface Malignancies

Peritoneal surface malignancies (PSM) includes an expansive disease spectrum, ranging from low-grade appendiceal mucinous neoplasm to metastatic processes from invasive adenocarcinomas of the gastrointestinal tract. Management of PSM faces numerous challenges, from diagnosis to delivery of care, both from a treatment and navigational standpoint. This article outlines the various hurdles faced at different branch points and current management recommendations.

BRAF mutant appendiceal adenocarcinoma differs from colorectal cancer but responds to BRAF-targeted therapy

Appendiceal Adenocarcinoma (AA) is a rare gastrointestinal cancer with no FDA-approved targeted therapies. Here, we retrospectively compare BRAF-mutant AA and colorectal cancer (CRC). BRAF mutation is rare in AA (3%). Unlike CRC, BRAFV600E AA is not associated with poor prognosis, female sex, microsatellite instability, mucinous histology, or poor differentiation. In both cancers, BRAFV600E but not atypical BRAF mutations are mutually exclusive with other Ras-activating mutations. BRAFV600E + EGFR inhibition shows efficacy in BRAFV600E AA (disease control rate = 80%, median progression-free survival = 7.1 months).

Caring for a patient with appendiceal cancer

ABSTRACT

Appendiceal cancer (AC) is a rare malignancy, occurring in 1 to 2 individuals per million annually in the US. It is often diagnosed incidentally during appendectomies or imaging for unrelated conditions. This article explores the risk factors, clinical presentation, diagnostic methods, pathology, staging, and treatment options for AC, highlighting disparities in access to care across different demographics. This article also emphasizes the importance of early detection and tailored management strategies to enhance nurses' understanding and improve outcomes for patients with this uncommon but significant disease.

cGAS/STING pathway and gastrointestinal cancer: Mechanisms and diagnostic and therapeutic targets (Review)

The health of individuals is seriously threatened by intestinal cancer, which includes pancreatic, colorectal, esophageal, gastric and gallbladder cancer. Most gastrointestinal cancers do not have typical and specific early symptoms, and lack specific and effective diagnostic markers and treatment methods. It is critical to understand the etiology of gastrointestinal cancer and develop more efficient methods of diagnosis and treatment. The cyclic GMP‑AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway serves a crucial role in the occurrence, progression and treatment of gastrointestinal cancer. The present review focuses on the latest progress regarding the role and mechanism of the cGAS/STING pathway in gastrointestinal cancer, and discusses treatment approaches and related applications based on the cGAS/STING signaling pathway. In order to improve the knowledge of the connection between the cGAS/STING pathway and gastrointestinal cancer, aid the diagnosis and treatment of gastrointestinal cancer, and lessen the burden on patients and society, the present review also discusses future research directions and existing challenges regarding cGAS/STING in the study of gastrointestinal cancer.

Investigation of Programmed Death Ligand-1 as a New Prognostic Biomarker in Pancreatic Cancer Patients

Pancreatic cancer is one of the most lethal and fast-growing cancers with a poor prognosis. Herein, we report the expression of programmed death ligand 1 (PD-L1) as a new prognostic biomarker in pancreatic cancer progression analysis at the clinical level. Immunohistochemistry was performed on 86 clinically proven cases of pancreatic cancer tissue microarrays (TMAs) using anti-PD-L1 antibodies. Histoscore was done, and a variety of cutoffs were identified for analyses of the results. The chi-square test and Kaplan-Meier method were used to find the association between pancreatic cancer and various clinicopathological variables and the overall survival of the patients. PD-L1 expression was associated with histological grade and recurrence of the disease for epithelial and stromal staining at 10 histoscores. In addition, PD-L1 expression was strongly associated with lymph node involvement at the stromal 20 histoscore. The tumor stage of pancreatic cancer had an association with PD-L1 expression with epithelial and stromal 20 histoscores for all comparisons. At a stromal 20 histoscore, overall survival in high-low expression of PD-L1 was 7-19 months, and at a nuclear/cytoplasmic 10 histoscore, it was 9-28 months (p = 0.0001), respectively. Overall, PD-L1 overexpression in subcellular compartments was associated with disease aggression phenotypes and poor patient survival. Overexpression of PD-L1 was directly linked to pancreatic cancer progression and a poor survival rate. Therefore, PD-L1 may be used as a prognostic biomarker in the diagnosis, treatment, and management of pancreatic cancer patients.

Prediction of Neoadjuvant Chemoradiotherapy Sensitivity in Patients With Esophageal Squamous Cell Carcinoma Using CT-Based Radiomics Combined With Clinical Features

Background: For patients with resectable locally advanced esophageal squamous cell carcinoma (ESCC), the current standard treatment is neoadjuvant chemoradiotherapy (nCRT) plus radical surgery. Objective: This study aimed to establish a predictive model, based on computed tomography (CT) radiomics features and clinical parameters, to predict sensitivity to nCRT in patients with ESCC pre-treatment. The goal was to provide risk stratification and decision-making recommendations for clinical treatments and offer more valuable information for developing personalized therapies. Methods: This retrospective study involved 102 patients diagnosed with ESCC through biopsy who underwent nCRT. To select radiomics features, we used the least absolute shrinkage and selection operator (LASSO) algorithm. A combined model was constructed, integrating the selected clinically relevant parameters with the Rad-Score. To assess the performance of this combined model, we utilized calibration curves and receiver operating characteristic (ROC) curves. Results: Nine optimal radiomics features were selected using the LASSO algorithm. The support vector machine (SVM) classifier was identified as having the best predictive performance. The area under the curve (AUC) of the SVM training group was 0.937 (95% CI: 0.856-1.000), and of the validation group was 0.831 (95% CI: 0.679-0.983). Smoking and alcohol history, neutrophil to lymphocyte ratio, serum aspartate aminotransferase to alanine aminotransferase ratio, and carcinoembryonic antigen and fibrinogen levels were independent predictors of sensitivity to nCRT in patients with ESCC. The AUCs of the combined model for the training and validation groups were 0.870 (95% CI: 0.774-0.964) and 0.821 (95% CI: 0.669-0.972), respectively. The calibration curve showed that the nomogram's predictions were close to the actual clinical observations, indicating that the model exhibited good predictive performance. Conclusion: Our combined model based on Rad-Score and clinical characteristics showed high predictive performance for predicting sensitivity to nCRT in patients with ESCC. It may be useful for predicting treatment effects in clinical practice and demonstrates the significant potential of radiomics in predicting and optimizing treatment decisions.

A radiomics-boosted deep-learning for risk assessment of synchronous peritoneal metastasis in colorectal cancer

OBJECTIVES

Synchronous colorectal cancer peritoneal metastasis (CRPM) has a poor prognosis. This study aimed to create a radiomics-boosted deep learning model by PET/CT image for risk assessment of synchronous CRPM.

METHODS

A total of 220 colorectal cancer (CRC) cases were enrolled in this study. We mapped the feature maps (Radiomic feature maps (RFMs)) of radiomic features across CT and PET image patches by a 2D sliding kernel. Based on ResNet50, a radiomics-boosted deep learning model was trained using PET/CT image patches and RFMs. Besides that, we explored whether the peritumoral region contributes to the assessment of CRPM. In this study, the performance of each model was evaluated by the area under the curves (AUC).

RESULTS

The AUCs of the radiomics-boosted deep learning model in the training, internal, external, and all validation datasets were 0.926 (95% confidence interval (CI): 0.874-0.978), 0.897 (95% CI: 0.801-0.994), 0.885 (95% CI: 0.795-0.975), and 0.889 (95% CI: 0.823-0.954), respectively. This model exhibited consistency in the calibration curve, the Delong test and IDI identified it as the most predictive model.

CONCLUSIONS

The radiomics-boosted deep learning model showed superior estimated performance in preoperative prediction of synchronous CRPM from pre-treatment PET/CT, offering potential assistance in the development of more personalized treatment methods and follow-up plans.

CRITICAL RELEVANCE STATEMENT

The onset of synchronous colorectal CRPM is insidious, and using a radiomics-boosted deep learning model to assess the risk of CRPM before treatment can help make personalized clinical treatment decisions or choose more sensitive follow-up plans.

KEY POINTS

Prognosis for patients with CRPM is bleak, and early detection poses challenges. The synergy between radiomics and deep learning proves advantageous in evaluating CRPM. The radiomics-boosted deep-learning model proves valuable in tailoring treatment approaches for CRC patients.

Analysis of causes and prognostic impact of tube occlusion during hyperthermic intraperitoneal chemotherapy for appendiceal pseudomyxoma peritonei

BACKGROUND

Appendiceal pseudomyxoma peritonei (PMP), a rare tumor from mucinous appendiceal origins, is treated with Cytoreductive Surgery (CRS) and Hyperthermic Intraperitoneal Chemotherapy (HIPEC). However, tubing blockages during HIPEC treatment pose a common challenge, impeding the smooth progression of therapy. Few studies to date have explored the incidence and risk factors of tube occlusion during HIPEC in patients with appendiceal PMP, as well as its adverse impact on postoperative complications.

METHODS

From October 2017 to June 2023, a total of 80 patients with appendiceal PMP undergoing combined CRS and HIPEC were included in this study. Tubing blockage events were strictly defined, with patients experiencing blockages during HIPEC treatment allocated to the study group, while those with unobstructed perfusion were assigned to the control group. A comparative analysis was conducted between the two groups regarding post-HIPEC health assessments and occurrence of complications. Risk factors for luminal occlusion during closed HIPEC procedures were identified through univariate and multivariate analysis of data from 303 HIPEC treatments.

RESULTS

Tubing blockages occurred in 41 patients (51.3%). The study group experienced prolonged gastrointestinal decompression time (4.1 ± 3.0 vs. 2.5 ± 1.7 days, P = 0.003) and prolonged time to bowel movement (6.1 ± 2.3 vs. 5.1 ± 1.8 days, P = 0.022) compared to the control group. There was no significant difference in the incidence of complications between the two groups. The 1-year survival rate postoperatively was 97%, and the 3-year survival rate was 81%, with no association found between tubing blockage and poorer survival. Additionally, In 303 instances of HIPEC treatment among these 80 patients, tube occlusion occurred in 89 cases (89/303, 29.4%). Multivariable logistic regression analysis revealed age, diabetes, hypertension, and pathology as independent risk factors for tube occlusion.

CONCLUSION

Tubing blockages are a common occurrence during HIPEC treatment, leading to prolonged postoperative gastrointestinal functional recovery time. When patients are elderly and have concomitant hypertension and diabetes, along with a histological type of low-grade mucinous tumor, the risk of tube occlusion increases. However, this study did not find a significant correlation between tubing blockage and the incidence of postoperative complications or overall patient survival.