DHX33 mediates p53 to regulate mevalonate pathway gene transcription in human cancers.

Tumor suppressor p53 is frequently null or mutated in human cancers. Here in this study, DHX33 protein was found to be induced in p53 null cells in vitro, and in p53 mutant lung tumorigenesis in vivo. Cholesterol metabolism through mevalonate pathway is pivotal for cell proliferation and is frequently altered in human cancers. Mice carrying mutant p53 and KrasG12D alleles showed upregulation of mevalonate pathway gene expression. However upon DHX33 loss, their upregulation was significantly debilitated. Additionally, in many human cancer cells, DHX33 knockdown caused inhibition of mavelonate pathway gene transcription. We propose DHX33 locates downstream of mutant p53 and Ras to regulate mevalonate pathway gene transcription and thereby supports cancer development in vivo.

Predicting lymph node metastasis in colorectal cancer: An analysis of influencing factors to develop a risk model.

BACKGROUND: Colorectal cancer (CRC) is a significant global health issue, and lymph node metastasis (LNM) is a crucial prognostic factor. Accurate prediction of LNM is essential for developing individualized treatment strategies for patients with CRC. However, the prediction of LNM is challenging and depends on various factors such as tumor histology, clinicopathological features, and molecular characteristics. The most reliable method to detect LNM is the histopathological examination of surgically resected specimens; however, this method is invasive, time-consuming, and subject to sampling errors and interobserver variability. AIM: To analyze influencing factors and develop and validate a risk prediction model for LNM in CRC based on a large patient queue. METHODS: This study retrospectively analyzed 300 patients who underwent CRC surgery at two Peking University Shenzhen hospitals between January and December 2021. A deep learning approach was used to extract features potentially associated with LNM from primary tumor histological images while a logistic regression model was employed to predict LNM in CRC using machine-learning-derived features and clinicopathological variables as predictors. RESULTS: The prediction model constructed for LNM in CRC was based on a logistic regression framework that incorporated machine learning-extracted features and clinicopathological variables. The model achieved high accuracy (0.86), sensitivity (0.81), specificity (0.87), positive predictive value (0.66), negative predictive value (0.94), area under the curve for the receiver operating characteristic (0.91), and a low Brier score (0.10). The model showed good agreement between the observed and predicted probabilities of LNM across a range of risk thresholds, indicating good calibration and clinical utility. CONCLUSION: The present study successfully developed and validated a potent and effective risk-prediction model for LNM in patients with CRC. This model utilizes machine-learning-derived features extracted from primary tumor histology and clinicopathological variables, demonstrating superior performance and clinical applicability compared to existing models. The study provides new insights into the potential of deep learning to extract valuable information from tumor histology, in turn, improving the prediction of LNM in CRC and facilitate risk stratification and decision-making in clinical practice.

Glutathione Peroxidase 4 as a Therapeutic Target for Anti-Colorectal Cancer Drug-Tolerant Persister Cells.

Background: Despite the effectiveness of chemotherapy and targeted therapy for colorectal cancer, drug resistance drives therapy failure and tumor relapse. Increasing evidence has suggested that cancer cells can enter a reversible drug-tolerant persister state to survive chemotherapy or targeted agents. However, the traits and treatable vulnerabilities of anti-colorectal cancer drug-tolerant persister cells is not yet known. Methods: In this study, we established 5-fluorouracil and AZ628-tolerant persister cell models in two colorectal cancer cell lines, namely HCT116 and SW620, and revealed the characteristics of colorectal cancer persister cells by cell viability assay and flow cytometry. We investigated the efficacy and mechanism of ferroptosis inducers RSL3 and FIN56 on persister cells, which are glutathione peroxidase 4 inhibitors. In the xenograft mouse model, we further evaluated the inhibitory effect of RSL3 on tumor regrowth. Results: Colorectal cancer persister cells, which were enriched in the residual cancer cell population, exhibited reduced drug sensitivity, were largely quiescent and expressed high levels of stem cell-related genes and mesenchymal markers but not epithelial markers. The persister cells were more sensitive and underwent ferroptosis induced by glutathione peroxidase 4 inhibitors. Mechanistically, glutathione peroxidase 4 and ferrous iron, which are pivotal ferroptosis regulators, were upregulated in residual cells or tumors, and were hence potential therapeutic targets of persister cells. In the xenograft model, we confirmed that inhibition of glutathione peroxidase 4 restrained tumor regrowth after discontinuation of anti-cancer drug treatment. Moreover, biopsies obtained from patients with colorectal cancer undergoing neoadjuvant chemoradiotherapy revealed upregulated glutathione peroxidase 4 and ferritin heavy chain 1. High glutathione peroxidase 4 expression correlates with a worse prognosis in colorectal cancer patients. Conclusions: Our work reveals that the upregulated glutathione peroxidase 4 and ferrous iron in anti-colorectal cancer drug-tolerant persister cells were potential therapeutic targets. Glutathione peroxidase 4 inhibition combined with chemotherapy or targeted therapy may be a promising therapy for colorectal cancer.

Current status and future perspectives on neoadjuvant therapy in gastric cancer.

Gastric cancer, with high morbidity and mortality rates, is one of the most heterogeneous tumors. Radical gastrectomy and postoperative chemotherapy are the standard treatments. However, the safety and efficacy of neoadjuvant therapy (NAT) need to be confirmed by many trials before implementation, creating a bottleneck in development. Although clinical benefits of NAT have been observed, a series of problems remain to be solved. Before therapy, more contributing factors should be offered for choice in the intended population and ideal regimens. Enhanced computed tomography (CT) scanning is usually applied to evaluate effectiveness according to Response Evaluation Criteria in Solid Tumors (RECIST), yet CT scanning results sometimes differ from pathological responses. After NAT, the appropriate time for surgery is still empirically defined. Our review aims to discuss the abovementioned issues regarding NAT for GC, including indications, selection of regimens, lesion assessment and NAT-surgery interval time.

Mutations in ALK and TSC1 in a gastrointestinal stromal tumor: a case report.

BACKGROUND: Gastrointestinal stromal tumors rarely occur in children, but when they do, their biological behavior and histopathological patterns differ from those of adults. CASE PRESENTATION: A 13-year-old boy with a gastrointestinal stromal tumor was characterized by a rare genetic mutation. The patient complained of "fatigue with intermittent abdominal pain for 1 month". According to the preoperative imaging examination, gastroscopy, and gastroscopic biopsy, the patient was diagnosed with a gastric stromal tumor. Postoperative pathology showed that the tumor cells were fusiform and ovoid, and mitotic figures were easily seen. Immunohistochemistry revealed that the tumor was S-100(+), SOX10(-), CD34(+), SMA(partially+), DOG-1(+), CD117(+), KI-67 (positive for 20% + of the subjects and 40% + of the hotspots), and SDHB(-). Genetic tests showed missense mutations in ALK and TSC1. With surgical treatment, the tumor was completely removed. The patient recovered well and was discharged on the ninth day after the operation. He is currently under follow-up. CONCLUSIONS: In this case involving a patient with a gastrointestinal stromal tumor, immunohistochemistry indicated that the tumor was an "SDH-deficient type", and gene detection showed no KIT or PDGFRA mutation but rare ALK and TSC1 mutations, which adds to the knowledge of the types of gene mutations in children with gastrointestinal stromal tumors.