Clinical & Experimental Metastasis最新文献

Although the incidence of cutaneous melanoma (CM) has been increasing annually, the mortality rate has been decreasing, likely due to better prevention, earlier detection, improved surveillance, and the development of new therapies. Current clinical management guidelines by the National Comprehensive Cancer Network (NCCN) are based on patient risk assignment using staging criteria established by the American Joint Committee on Cancer (AJCC). However, some patients with localized disease (stage I–II), generally considered to have a good prognosis, will develop metastatic disease and die, whereas some patients with later stage disease (stage III–IV) will be cured by surgery, adjuvant therapy, and/or systemic therapy. These results emphasize the importance of identifying patients whose risk may be over or underestimated with standard staging. Gene expression profile (GEP) tests are noninvasive molecular tests that assess the expression levels of a panel of validated genes, providing information about tumor prognosis, including the risk of recurrence, metastasis, and cancer-specific death. GEP tests can provide prognostic information beyond standard staging that may aid clinicians and patients in treatment and surveillance management decisions. This review describes how combining clinicopathologic staging with a robust assessment of tumor biology may provide information that will allow more refined intervention and long-term management.

Large cell neuroendocrine carcinoma (LCNEC) of the lung is an aggressive malignancy, with brain metastases (BM) occurring in approximately 20% of cases. There are currently no therapy guidelines for this population as only few data on the management of LCNEC and BM have been published. For this retrospective single center study, patients with LCNEC and BM were identified from the Vienna Brain Metastasis Registry. Data on clinicopathological features, BM-specific characteristics, treatment, and outcome were extracted. In total, 52/6083 (0.09%) patients in the dataset had a diagnosis of LCNEC and radiologically verified BM. Median age at diagnosis of LCNEC and BM was 59.1 and 60.1 years, respectively. Twenty-seven (51.9%) presented with single BM, while 12 (23%) exhibited > 3 BM initially. Neurologic symptoms due to BM were present in n = 40 (76.9%), encompassing neurologic deficits (n = 24), increased intracranial pressure (n = 18), and seizures (n = 6). Initial treatment of BM was resection (n = 13), whole brain radiation therapy (n = 19), and/or stereotactic radiosurgery (n = 25). Median overall survival (mOS) from LCNEC diagnosis was 16 months, and mOS after BM diagnosis was 7 months. Patients with synchronous BM had reduced mOS from LCNEC diagnosis versus patients with metachronous BM (11 versus 27 months, p = 0.003). Median OS after BM diagnosis did not differ between LCNEC patients and a control group of small cell lung cancer patients with BM (7 versus 6 months, p = 0.17). Patients with LCNEC and BM have a poor prognosis, particularly when synchronous BM are present. Prospective trials are required to define optimal therapeutic algorithms.

Cancer is a disease that undergoes selective pressure to evolve during its progression, becoming increasingly heterogeneous. Tumoral heterogeneity can dictate therapeutic response. Transcriptomics can be used to uncover complexities in cancer and reveal phenotypic heterogeneity that affects disease response. This is especially pertinent in the immune microenvironment, which contains diverse populations of immune cells, and whose dynamic properties influence disease response. The recent development of immunotherapies has revolutionized cancer therapy, with response rates of up to 50% within certain cancers. However, despite advances in immune checkpoint blockade specifically, there remains a significant population of non-responders to these treatments. Transcriptomics can be used to profile immune and other cell populations following immune-checkpoint inhibitor (ICI) treatment, generate predictive biomarkers of resistance or response, assess immune effector function, and identify potential immune checkpoints. Single-cell RNA sequencing has offered insight into mRNA expression within the complex and heterogeneous tumor microenvironment at single-cell resolution. Spatial transcriptomics has enabled measurement of mRNA expression while adding locational context. Here, we review single-cell sequencing and spatial transcriptomic research investigating ICI response within a variety of cancer microenvironments.

Diagnosing malignant pleural effusions (MPE) is challenging when patients lack a history of cancer and cytopathology does not detect malignant cells in pleural effusions (PE). We investigated whether a systematic analysis of PE by flow cytometry immunophenotyping (FCI) had any impact on the diagnostic yield of MPE. Over 7 years, 570 samples from patients with clinical suspicion of MPE were submitted for the FCI study. To screen for epithelial malignancies, a 3-color FCI high sensitivity assay was used. The FCI results, qualified as "malignant" (FCI+) or "non-malignant" (FCI-), were compared to integrated definitive diagnosis established by clinicians based on all available information. MPE was finally diagnosed in 182 samples and FCI detected 141/182 (77.5%). Morphology further confirmed FCI findings by cytopathology detection of malignant cells in PE (n = 91) or histopathology (n = 29). Imaging tests and clinical history supported the diagnosis in the remaining samples. The median percentage of malignant cells was 6.5% for lymphoma and 0.23% for MPE secondary to epithelial cell malignancies. FCI identified a significantly lower percentage of EpCAM⁺ cells in cytopathology-negative MPE than in cytopathology-positive cases (0.02% vs. 1%; p < 0.0001). Interestingly, 29/52 MPE (55.8%) where FCI alerted of the presence of malignant cells were new diagnosis of cancer. Overall, FCI correctly diagnosed 456/522 samples (87.4%) suitable for comparison with cytopathology. These findings show that high sensitivity FCI significantly increases the diagnostic yield of MPE. Early detection of FCI + cases accelerates the diagnostic pathway of unsuspected MPE, thus supporting its implementation in clinical diagnostic work-up as a diagnostic tool.

Peritoneal metastasis (PM) is a frequent manifestation of advanced abdominal malignancies. Accurately assessing the extent of PM before surgery is essential for patients to receive optimal treatment. Therefore, we propose to construct a deep learning (DL) model based on enhanced computed tomography (CT) images to stage PM preoperatively in patients. All 168 patients with PM underwent contrast-enhanced abdominal CT before either open surgery or laparoscopic exploration, and peritoneal cancer index (PCI) was used to evaluate patients during the surgical procedure. DL features were extracted from portal venous-phase abdominal CT scans and subjected to feature selection using the Spearman correlation coefficient and LASSO. The performance of models for preoperative staging was assessed in the validation cohort and compared against models based on clinical and radiomics (Rad) signature. The DenseNet121-SVM model demonstrated strong patient discrimination in both the training and validation cohorts, achieving AUC was 0.996 in training and 0.951 validation cohort, which were both higher than those of the Clinic model and Rad model. Decision curve analysis (DCA) showed that patients could potentially benefit more from treatment using the DL-SVM model, and calibration curves demonstrated good agreement with actual outcomes. The DL model based on portal venous-phase abdominal CT accurately predicts the extent of PM in patients before surgery, which can help maximize the benefits of treatment and optimize the patient's treatment plan.

The Graded Prognostic Assessment (GPA) score has the best accuracy among prognostic scales for patients with brain metastases (BM). A wide range of GPA-derived scales have been established to different types of primary tumor BM. However, there is a high variability between them, and their characteristics have not been described altogether yet. We aim to summarize the features of the existent GPA-derived scales and to compare their predictor factors and their uses in clinical setting. Medline was searched from inception until January 2023 to identify studies related to the development, update, or validation of GPA. The initial search yielded 1,083 results. 16 original studies and 16 validation studies were included, comprising a total of 33,348 patients. 13 different scales were assessed, including: GPA, Diagnosis-Specific GPA, Extracranial Score, Lung-molGPA, Updated Renal GPA, Updated Gastrointestinal GPA, Modified Breast GPA, Integrated Melanoma GPA, Melanoma Mol GPA, Sarcoma GPA, Hepatocellular Carcinoma GPA, Colorectal Cancer GPA, and Uterine Cancer GPA. The most prevalent prognostic predictors were age, Karnofsky Performance Status, number of BM, and presence or absence of extracranial metastases. Treatment modalities consisted of whole brain radiation therapy, stereotactic radiosurgery, surgery, cranial radiotherapy, gamma knife radiosurgery, and BRAF inhibitor therapy. Median survival rates with no treatment and with a specific treatment ranged from 6.1 weeks to 33 months and from 3.1 to 21 months, respectively. Original GPA and GPA-derived scales are valid prognostic tools, but with heterogeneous survival results when compared to each other. More studies are needed to improve scientific evidence of these scales.

Approximately 25% of those who are diagnosed with colorectal cancer will develop colorectal liver metastases (CRLM) as their illness advances. Despite major improvements in both diagnostic and treatment methods, the prognosis for patients with CRLM is still poor, with low survival rates. Accurate employment of imaging methods is critical in identifying the most effective treatment approach for CRLM. Different imaging modalities are used to evaluate CRLM, including positron emission tomography (PET)/computed tomography (CT). Among the PET radiotracers, fluoro-18-deoxyglucose (¹⁸F-FDG), a glucose analog, is commonly used as the primary radiotracer in assessment of CRLM. As the importance of ¹⁸F-FDG-PET/CT continues to grow in assessment of CRLM, developing a comprehensive understanding of this subject becomes imperative for healthcare professionals from diverse disciplines. The primary aim of this article is to offer a simplified and comprehensive explanation of PET/CT in the evaluation of CRLM, with a deliberate effort to minimize the use of technical nuclear medicine terminology. This approach intends to provide various healthcare professionals and researchers with a thorough understanding of the subject matter.

Cancer cell invasion, intravasation and survival in the bloodstream are early steps of the metastatic process, pivotal to enabling the spread of cancer to distant tissues. Circulating tumor cells (CTCs) represent a highly selected subpopulation of cancer cells that tamed these critical steps, and a better understanding of their biology and driving molecular principles may facilitate the development of novel tools to prevent metastasis. Here, we describe key research advances in this field, aiming at describing early metastasis-related processes such as collective invasion, shedding, and survival of CTCs in the bloodstream, paying particular attention to microenvironmental factors like hypoxia and mechanical stress, considered as important influencers of the metastatic journey.