Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma.

BACKGROUND: The metastatic vascular patterns of hepatocellular carcinoma (HCC) are mainly microvascular invasion (MVI) and vessels encapsulating tumor clusters (VETC). However, most existing VETC-related radiological studies still focus on the prediction of VETC status. PURPOSE: This study aimed to build and compare VETC-MVI related models (clinical, radiomics, and deep learning) associated with recurrence-free survival of HCC patients. STUDY TYPE: Retrospective. POPULATION: 398 HCC patients (349 male, 49 female; median age 51.7 years, and age range: 22-80 years) who underwent resection from five hospitals in China. The patients were randomly divided into training cohort (n = 358) and test cohort (n = 40). FIELD STRENGTH/SEQUENCE: 3-T, pre-contrast T1-weighted imaging spoiled gradient recalled echo (T1WI SPGR), T2-weighted imaging fast spin echo (T2WI FSE), and contrast enhanced arterial phase (AP), delay phase (DP). ASSESSMENT: Two radiologists performed the segmentation of HCC on T1WI, T2WI, AP, and DP images, from which radiomic features were extracted. The RFS related clinical characteristics (VETC, MVI, Barcelona stage, tumor maximum diameter, and alpha fetoprotein) and radiomic features were used to build the clinical model, clinical-radiomic (CR) nomogram, deep learning model. The follow-up process was done 1 month after resection, and every 3 months subsequently. The RFS was defined as the date of resection to the date of recurrence confirmed by radiology or the last follow-up. Patients were followed up until December 31, 2022. STATISTICAL TESTS: Univariate COX regression, least absolute shrinkage and selection operator (LASSO), Kaplan-Meier curves, log-rank test, C-index, and area under the curve (AUC). P < 0.05 was considered statistically significant. RESULTS: The C-index of deep learning model achieved 0.830 in test cohort compared with CR nomogram (0.731), radiomic signature (0.707), and clinical model (0.702). The average RFS of the overall patients was 26.77 months (range 1-80 months). DATA CONCLUSION: MR deep learning model based on VETC and MVI provides a potential tool for survival assessment. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Analysis of the metastatic mechanism and progress in the treatment of breast cancer liver metastasis: a narrative review.

Background and Objective: Breast cancer is the most common malignancy in women, and metastasis to other target organs is one of the main causes of death. Breast cancer liver metastasis (BCLM) has long been a research focus. Enhancing therapeutic effects, optimizing treatment plans and improving the prognosis of patients are major clinical challenges at present. Methods: We performed a comprehensive, nonsystematic review of the latest literature to define the current metastatic mechanism and related treatment advances of BCLM. Key Content and Findings: Due to the lack of research on the mechanism of BCLM, present treatment programs still have limited benefits, and the prognosis of patients is generally poor. New research directions and treatment ideas for BCLM are urgently needed. In this article, we indicated the specific procedures of the BCLM mechanism from the microenvironment to metastasis formation and progress in treatment, including drug therapies such as targeted therapy, surgery, intervention therapy and radiotherapy. Research on the molecular mechanism plays a crucial role in the development of BCLM-related therapies. Based on the metastasis process, we are able to propel new findings and further progression of antineoplastic drugs. Conclusions: The process of BCLM is multistep, and various factors are involved in it, which provides a powerful theoretical basis for the development of therapeutic methods for treatment of this disease. Further understanding of the mechanism of BCLM is essential to guide clinical management.

Nanotechnology-integrated ovarian cancer metastasis therapy: Insights from the metastatic mechanisms into administration routes and therapy strategies.

Ovarian cancer is a kind of malignant tumour which locates in the pelvic cavity without typical clinical symptoms in the early stages. Most patients are diagnosed in the late stage while about 60 % of them have suffered from the cancer cells spreading in the abdominal cavity. The high recurrence rate and mortality seriously damage the reproductive needs and health of women. Although recent advances in therapeutic regimes and other adjuvant therapies improved the overall survival of ovarian cancer, overcoming metastasis has still been a challenge and is necessary for achieving cure of ovarian cancer. To present potential targets and new strategies for curbing the occurrence of ovarian metastasis and the treatment of ovarian cancer after metastasis, the first section of this paper explained the metastatic mechanisms of ovarian cancer comprehensively. Nanomedicine, not limited to drug delivery, offers opportunities for metastatic ovarian cancer therapy. The second section of this paper emphasized the advantages of various administration routes of nanodrugs in metastatic ovarian cancer therapy. Furthermore, the third section of this paper focused on advances in nanotechnology-integrated strategies for targeting metastatic ovarian cancer based on the metastatic mechanisms of ovarian cancer. Finally, the challenges and prospects of nanotherapeutics for ovarian cancer metastasis therapy were evaluated. In general, the greatest emphasis on using nanotechnology-based strategies provides avenues for improving metastatic ovarian cancer outcomes in the future.

Molecular Alterations in Metastatic Ovarian Cancer From Gastrointestinal Cancer.

Reports indicate that most metastatic ovarian cancer (MOC) originates from gastrointestinal cancer (GIC). Notably, GICs metastasize to the ovary frequently via 3 main routes including hematogenous spread, lymphogenous spread, and transcoelomic spread. Nonetheless, the mechanism of the progression remains unknown, and only a handful of literature exists on the molecular alteration implicated in MOC from GIC. This work collected existing evidence and literature on the vital molecules of the metastatic pathway and systematically analyzed them geared toward exploring the mechanism of the metastatic pathway of MOC. Further, this review described dominating molecular alteration in the metastatic process from cancer cells detaching away from lesions to arrive at the ovary, including factors for regulating signaling pathways in epithelial-interstitial transformation, invading, and surviving in the circulatory system or abdominal cavity. We interrogated the basis of the ovary as a distant metastatic site. This article provides new insights into the metastatic pathway and generates novel therapeutic targets for effective treatment and satisfactory outcomes in GIC patients.

Oligometastatic Gastroesophageal Adenocarcinoma: Molecular Pathophysiology and Current Therapeutic Approach.

Gastric and esophageal cancers are dreaded malignancies, with a majority of patients presenting in either a locally advanced or metastatic state. Global incidences are rising and the overall prognosis remains poor. The concept of oligometastasis has been established for other tumor entities and is also proposed for upper gastrointestinal tract cancers. This review article explores metastasis mechanisms on the molecular level, specific to esophageal and gastric adenocarcinoma. Existing data and recent studies that deal with upper gastrointestinal tumors in the oligometastatic state are reviewed. Furthermore, current therapeutic targets in gastroesophageal cancers are presented and discussed. Finally, a perspective about future diagnostic and therapeutic strategies is given.

Synchronous peritoneal carcinomatosis from a buccal squamous cell carcinoma: a case report focusing on possible metastatic mechanisms and novel therapeutic modalities.

A 53-year-old male patient was diagnosed with squamous cell carcinoma of buccal mucosa with synchronous diffuse peritoneal carcinomatosis, a very rare presentation for oral cancer. His disease was highly resistant to intensive systemic chemotherapy and progressed rapidly. So far as we know, there were only five cases with peritoneal involvement by metastatic head and neck cancer reported prior to this patient in the English literature. Immunohistochemistry study revealed that tumour specimens from both oral cavity and peritoneum were negative for tumour necrosis factor alpha and CD24 but positive for CD44 and CD36. These four molecules have been disclosed to be involved in the process of peritoneal metastasis from ovarian cancer. Their roles in the metastatic pathway and possible therapeutic policy targeting at them will be thoroughly discussed.

NUP58 facilitates metastasis and epithelial-mesenchymal transition of lung adenocarcinoma via the GSK-3ß/Snail signaling pathway.

The NUP58 gene encodes a nucleus-pore protein that is a component of nuclear pore complex (NPC). NPC facilitates the transportation of macromolecules (ions and other substances) into the nuclei of eukaryotic cells. However, there are no relevant reports about the NUP58 gene in human lung cancer. In this study, we demonstrated that NUP58 was highly expressed in the primary and metastatic foci of lung adenocarcinoma, with low expression in adjacent tissues and normal lung tissue. In patients with lung adenocarcinoma, the NUP58 gene was highly expressed in patients with stage IV disease (P < 0.05); NUP58 knockdown using a lentiviral vector-mediated shRNA inhibited metastasis and invasion of lung adenocarcinoma cell lines A549 and H1299 in vivo and in vitro. Furthermore, silencing of NUP58 resulted in altered expression of EMT markers, associated GSK-3ß/Snail pathways, tumor metastasis and invasion factors. In conclusion, these findings demonstrated that NUP58 can promote the metastasis and invasion of lung adenocarcinoma, which can be partially attributed to the GSK-3ß/Snail signaling pathway.