Cancers最新文献

Approximately 15-20% of cancers are caused by viruses. Kaposi sarcoma-associated herpesvirus (KSHV), also known as human herpesvirus 8 (HHV8), is an oncogenic virus that is the etiologic agent of not only Kaposi sarcoma but also the lymphoproliferative disorders, primary effusion lymphoma (PEL) and multicentric Castleman disease (MCD). KSHV can infect a broad tropism of cells, including B lymphocytes, wherein KSHV encodes specific viral proteins that can transform the cell. KSHV infection precedes the progression of PEL and MCD. KSHV establishes lifelong infection and has two phases of its lifecycle: latent and lytic. During the latent phase, viral genomes are maintained episomally with limited gene expression. Upon sporadic reactivation, the virus enters its replicative lytic phase to produce infectious virions. KSHV relies on its viral products to modulate host factors to evade immune detection or to co-opt their function for KSHV persistence. These manipulations dysregulate normal cell pathways to ensure cell survival and inhibit antiviral immune responses, which in turn, contribute to KSHV-associated malignancies. Here, we highlight the known molecular mechanisms of KSHV that promote lymphomagenesis and how these findings identify potential therapeutic targets for KSHV-associated lymphomas.

Integrin α6β4 drives triple-negative breast cancer (TNBC) aggressiveness through the transcriptional regulation of key genes. Here, we investigated how integrin α6β4 regulates protein tyrosine phosphatase receptor type Z1 (PTPRZ1). Using stable re-expression of integrin β4 (ITGB4) in cells naturally devoid of integrin α6β4 or knockdown or knockout (KO) of ITGB4, we found that integrin α6β4 regulates PTPRZ1 expression. To gain mechanistic insight, we focused on Hif-1α due to the impact of integrin α6β4 on a hypoxia-associated signature. We found that nuclear localization of Hif-1α, but not Hif-2α, was substantially enhanced with integrin α6β4 signaling. Hif-1α knockdown by shRNA or chemical inhibition decreased PTPRZ1 expression, while chemical activation of Hif-1α increased it. Upstream of Hif-1α, integrin α6β4 upregulates UCHL1 to stabilize Hif-1α and ultimately regulate PTPRZ1. Inhibition of UCHL1 and PTPRZ1 dramatically decreases integrin α6β4-mediated cell migration and three-dimensional invasive growth. Finally, public breast cancer database analyses demonstrated that ITGB4 correlates with PTPRZ1 and that high expression of ITGB4, UCHL1, HIF1A, and PTPRZ1 associated with decreased overall survival, distant metastasis free survival, post progression survival, and relapse-free survival. In summary, these findings provide a novel function of integrin α6β4 in promoting tumor invasive phenotypes through UCHL1-Hif-1α-mediated regulation of PTPRZ1.

The purpose of this article is to provide a literature review of the epigenetic understanding of conjunctival melanoma (CM), with a primary focus on current gaps in knowledge and future directions in research. CM is a rare aggressive cancer that predominantly affects older adults. Local recurrences and distant metastases commonly occur in CM patients; however, their prediction and management remain challenging. Hence, there is currently an unmet need for useful biomarkers and more effective treatments to improve the clinical outcomes of these patients. Like other cancers, CM occurrence and prognosis are believed to be influenced by multiple genetic and epigenetic factors that contribute to tumor development/progression/recurrence/spread, immune evasion, and primary/acquired resistance to therapies. Epigenetic alterations may involve changes in chromatin conformation/accessibility, post-translational histone modifications or the use of histone variants, changes in DNA methylation, alterations in levels/functions of short (small) or long non-coding RNAs (ncRNAs), or RNA modifications. While recent years have witnessed a rapid increase in available epigenetic technologies and epigenetic modulation-based treatment options, which has enabled the development/implementation of various epi-drugs in the cancer field, the epigenetic understanding of CM remains limited due to a relatively small number of epigenetic studies published to date. These studies primarily investigated DNA methylation, ncRNA (e.g., miRNA or circRNA) expression, or RNA methylation. While these initial epigenetic investigations have revealed some potential biomarkers and/or therapeutic targets, they had various limitations, and their findings warrant replication in independent and larger studies/samples. In summary, an in-depth understanding of CM epigenetics remains largely incomplete but essential for advancing our molecular knowledge and improving clinical management/outcomes of this aggressive disease.

Background: The identification of reliable prognostic biomarkers is crucial for optimizing cancer treatment strategies, especially in the era of personalized medicine. This systematic review and meta-analysis evaluate the prognostic significance of the neutrophil-to-eosinophil ratio (NER) in various cancer types, with a focus on its association with overall survival (OS) and progression-free survival (PFS).

Methods: We conducted a systematic literature search across PubMed, Scopus, and Web of Science databases for studies published up to 28 July 2024. We performed the meta-analyses with the generic inverse variance method with a random effects model and reported hazard ratios (HR) with 95% confidence intervals (CI).

Results: The comprehensive literature search identified 10 studies comprising 2351 patients. Pooled analyses demonstrated that elevated pretreatment NER levels were significantly correlated with poorer OS (HR: 1.74, 95% CI: 1.28-2.36, p < 0.001) and PFS (HR: 1.53, 95% CI: 1.21-1.95, p < 0.001). Subgroup analyses confirmed a consistent adverse association between high NER and OS across various tumor types and geographic locations, although results from studies conducted in the Far East did not reach statistical significance.

Conclusions: This meta-analysis demonstrates that elevated NER is associated with poorer OS and PFS in cancer patients, suggesting its potential utility as a non-invasive prognostic marker. Further validation in large, prospective studies is warranted to establish NER's role in guiding personalized treatment strategies across diverse oncologic contexts.

Background: Sentinel lymph node (SLN) biopsy is recommended over systematic lymphadenectomy in early-stage endometrial cancer due to its lower morbidity and comparable detection rate. The objective of this study was to identify clinical factors associated with unsuccessful mapping.

Methods: Between April 2020 and June 2024, 120 patients over the age of 18 and diagnosed with early-stage endometrial cancer were enrolled in this prospective study at a single institution. Demographic, clinicopathologic, and treatment data were collected and analyzed using descriptive statistics. Univariate and multiple linear regressions were performed to identify predictors of failed mapping.

Results: The mean age of the patient cohort was 62.5 years (range 33 to 83), and the mean body mass index (BMI) was 32 kg/m² (range 18 to 50). Patients underwent intracervical injections with methylene blue (MB), indocyanine green (ICG), or a combination of both tracers, with 40 patients in each group. A total of 108 patients (90.0%) were diagnosed with endometrioid carcinoma and 12 (10.0%) with non-endometrioid cancers. Additionally, 110 patients (91.7%) were diagnosed in early stages of the disease. The overall SLN detection rate was 73.4%, with bilateral detection at 49.2% and unilateral detection at 24.2%. Univariate analysis showed that older age (p < 0.001), menopause (p = 0.001), the use of MB as the sole tracer (p = 0.006), a shorter tumor-to-serosa distance (p = 0.048), and bulky lymph nodes (p = 0.18) were associated with unsuccessful mapping. Multiple linear regression model analysis identified age (p = 0.007), tracer type (p = 0.013), and enlarged lymph nodes (p = 0.013) as independent predictors of SLN mapping failure.

Conclusions: Advanced age, tracer type, and intraoperative detection of enlarged lymph nodes were identified as independent risk factors for unsuccessful mapping in patients undergoing laparoscopic SLN mapping.

Prostate cancer progression is significantly affected by its tumor microenvironment, in which mesenchymal cells play a crucial role. Stromal cells are modified by cancer mutations, response to androgens, and lineage plasticity, and in turn, engage with epithelial tumor cells via a complex array of signaling pathways and ligand-receptor interactions, ultimately affecting tumor growth, immune interaction, and response to therapy. The metabolic rewiring and interplay in the microenvironment play an additional role in affecting the growth and progression of prostate cancer. Finally, therapeutic strategies and novel clinical trials with agents that target the stromal microenvironment or disrupt the interaction between cellular compartments are described. This review underscores cancer-associated fibroblasts as essential contributors to prostate cancer biology, emphasizing their potential as prognostic indicators and therapeutic targets.

Lynch syndrome (LS) is an autosomal dominant disorder characterized by increased risks of colorectal and endometrial cancers. LS is defined by pathogenic variants in mismatch repair (MMR) genes, including MLH1, MSH2, and MSH6. Data on the prevalence and associated cancer risks of LS in the Han Chinese population remain limited. In this study, using a broad biobank approach through the Taiwan Precision Medicine Initiative (TPMI), we identified LS-associated MMR gene variants within a cohort of 42,828 participants from a Taiwanese medical center. A total of 89 individuals were found to carry pathogenic MMR variants: MLH1 (n = 22, 25%), MSH2 (n = 47, 53%), and MSH6 (n = 20, 22%). The overall prevalence of MMR variants was calculated, and cancer incidence rates among carriers were determined. The prevalence of MMR variants in the study population was 1 in 481. The distribution of MLH1, MSH2, and MSH6 variants were 24.7%, 52.8%, and 22.5%, respectively. Cumulative cancer incidence rates of carriers were 40.9% for MLH1 carriers, 29.8% for MSH2, and 40% for MSH6. Among the 19 individuals who underwent colonoscopy screening, the prevalence of polyps was similar to that of the control group (adenoma detection rate: 32% vs 26%, p = 0.585). A meticulous analysis of the detected polyps in seven participants, considering factors such as location, size, morphology, and pathological features, showed no significant differences from controls. A significant cancer risk is associated with LS-related MMR variants in the Taiwanese population. The apparent under diagnosis of LS highlights the urgent need for enhanced surveillance and genetic counseling in this demographic. Our findings suggest that adjustments in the current screening protocols may be warranted to better identify and manage at-risk individuals.

Background: Cancer remains a leading cause of death worldwide. Progress in its effective treatment has been hampered by challenges in personalized therapy, particularly in patients with comorbid conditions. The integration of artificial intelligence (AI) into patient profiling offers a promising approach to enhancing individualized anticancer therapy. Objective: This narrative review explores the role of AI in refining anticancer therapy through personalized profiling, with a specific focus on cancer patients with comorbid migraine. Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Scopus, and Google Scholar. Studies were selected based on their relevance to AI applications in oncology and migraine management, with a focus on personalized medicine and predictive modeling. Key themes were synthesized to provide an overview of recent developments, challenges, and emerging directions. Results: AI technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), have become instrumental in the discovery of genetic and molecular biomarkers of cancer and migraine. These technologies also enable predictive analytics for assessing the impact of migraine on cancer therapy in comorbid cases, predicting outcomes and provide clinical decision support systems (CDSS) for real-time treatment adjustments. Conclusions: AI holds significant potential to improve the precision and effectiveness of the management and therapy of cancer patients with comorbid migraine. Nevertheless, challenges remain over data integration, clinical validation, and ethical consideration, which must be addressed to appreciate the full potential for the approach outlined herein.

Background/objectives: With breast cancer (BC) survival improving due to optimized therapy, enhancing quality of life has become increasingly important. Both diagnosis and treatment, with their potential side effects, pose risks to mental well-being. Our study aimed to analyze the incidence and potential risk factors for mental disorders in BC patients.

Methods: This retrospective analysis used claims data from AOK Baden-Wuerttemberg, including 11,553 BC patients diagnosed via ICD code C50 between 2010 and 2020 and 31,944 age-matched controls. Patients with mental disorders in the 12 months prior to diagnosis were excluded. Mental disorders were categorized into eight groups based on ICD codes: anxiety, obsessive compulsive disorder, adjustment disorder, dissociative disorder, hypochondriac disorder, affective disorder, mania, and other neuroses.

Results: Mental disorders were significantly more common in BC patients than in controls (64.2% vs. 38.1%, p < 0.01, OR 2.91, 95%CI [2.79, 3.04]). In particular, hypochondriac, anxiety, affective, and adjustment disorders occurred significantly more often in BC patients. No differences were found for mania, bipolar disease, other neuroses, obsessive compulsive-, or dissociative disorders. Furthermore, endocrine therapy was associated with psychological comorbidities (OR 1.69, p < 0.001, 95%CI [1.53, 1.86]), while primarily metastasized patients (stage C) had a lower risk than adjuvant patients in stage A (OR 0.55, p < 0.0001, 95%CI [0.49, 0.61]). Regarding surgical treatment, mastectomy patients showed lower rates of mental illnesses (61.2%) than those with breast-conserving treatment (71.6%), or especially breast reconstruction (78.4%, p < 0.01). Breast reconstruction was also associated with more hypochondriac (p < 0.01) and adjustment disorders (p < 0.01).

Conclusions: So, BC patients experience significantly more mental disorders than controls, particularly when treated with endocrine therapy and breast reconstructive surgery.

Background Parenchymal Enhancement (BPE) on breast MRI holds promise as an imaging biomarker for breast cancer risk and prognosis. The ability to identify those at greatest risk can inform clinical decisions, promoting early diagnosis and potentially guiding strategies for prevention such as risk-reduction interventions with the use of selective estrogen receptor modulators and aromatase inhibitors. Currently, the standard method of assessing BPE is based on the Breast Imaging-Reporting and Data System (BI-RADS), which involves a radiologist's qualitative categorization of BPE as minimal, mild, moderate, or marked on contrast-enhanced MRI. This approach can be subjective and prone to inter/intra-observer variability, and compromises accuracy and reproducibility. In addition, this approach limits qualitative assessment to 4 categories. More recently developed methods using machine learning/artificial intelligence (ML/AI) techniques have the potential to quantify BPE more accurately and objectively. This paper will review the current machine learning/AI methods to determine BPE, and the clinical applications of BPE as an imaging biomarker for breast cancer risk prediction and prognosis.