Cancers

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.

Minerals constitute only 5% of the typical human diet but are vital for health and functionality. Copper, a trace element, is absorbed by the human gut at 30–40% from diets typical of industrialized countries. The liver produces metallothioneins, which store copper. Copper is crucial for mitochondrial respiration, pigmentation, iron transport, antioxidant defense, hormone production, and extracellular matrix biosynthesis. Copper deficiency, often caused by mutations in the ATP7A gene, results in Menkes disease, an X-linked recessive disorder. On the contrary, Wilson disease is characterized by toxic copper accumulation. Cuproptosis, a unique form of cell death regulated by copper, is a subtype of necrosis induced by enhanced mitochondrial metabolism and intracellular copper accumulation. This process can reduce the malignant potential of tumor cells by inhibiting glucose metabolism. Therapeutically, copper and its complexes have shown efficacy in malignancy treatments. The disruption of copper homeostasis and excessive cuproplasia are significant in colorectal cancer development and metastasis. Therefore, manipulating copper status presents a potential therapeutic target for colorectal cancer, using copper chelators to inhibit copper formation or copper ion carriers to promote cuproptosis. This review highlights the role of copper in human physiology and pathology, emphasizing its impact on colorectal cancer and potential therapeutic strategies. Future AI-based approaches are anticipated to accelerate the development of new compounds targeting cuproptosis and copper disruption in colorectal cancer.

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.

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.

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.

Brain and leptomeningeal metastases are complications of breast cancer with high rates of morbidity and mortality and have an estimated incidence of up to 30%. While National Comprehensive Cancer Network (NCCN) guidelines recommend screening for central nervous system metastasis in other neurotropic cancers such as non-small cell lung cancer, there are no such recommendations for asymptomatic breast cancer patients at any stage of disease. This review highlights ongoing studies into screening and diagnostics for breast cancer with brain and leptomeningeal metastasis (BCBLM) as they relate to patient outcomes and prognostication. These include imaging methods such as MRI with novel contrast agents with or without PET/CT, as well as ‘liquid biopsy’ testing of the cerebrospinal fluid and serum to analyze circulating tumor cells, genomic material, proteins, and metabolites. Given recent advances in radiation, neurosurgery, and systemic treatments for BCBLM, screening for CNS involvement should be considered in patients with advanced breast cancer as it may impact treatment decisions and overall survival.

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/Objectives: Early and aggressive metastasis is a major feature of pancreatic ductal adenocarcinoma. Understanding the processes underlying metastasis is crucial for making a difference to disease outcome. Towards these ends, we looked in a comprehensive manner for genes that are metastasis-specific. Methods: A genome-wide CRISPR-Cas9 gene knockout screen with 259,900 single guide RNA constructs was performed on pancreatic cancer cell lines with very high or very low metastatic capacity, respectively. Functional aspects of some of the identified genes were analysed in vitro. The injection of tumour cells with or without a gene knockout into mice was used to confirm the effect on metastasis. Results: The knockout of 590 genes—and, with higher analysis stringency, 67 genes—affected the viability of metastatic cells substantially, while these genes were not vital to non-metastasizing cells. Further evaluations identified different molecular processes related to this observation. One of the genes was MYBL2, encoding for a well-known transcription factor involved in the regulation of cell survival, proliferation, and differentiation in cancer tissues. In our metastasis-focussed study, no novel functional activity was detected for MYBL2, however. Instead, a metastasis-specific transformation of its genetic interaction with FOXM1 was observed. The interaction was synergistic in cells of low metastatic capacity, while there was a strong switch to a buffering mode in metastatic cells. In vivo analyses confirmed the strong effect of MYBL2 on metastasis. Conclusions: The genes found to be critical for the viability of metastatic cells form a basis for further investigations of the processes responsible for triggering and driving metastasis. As shown for MYBL2, unexpected processes of regulating metastasis might also be involved.

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 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.