Lung cancer (LC) remains the leading cause of cancer-related deaths worldwide, characterized by high mortality rates and limited treatment options. MicroRNAs (miRNAs) are critical regulators of gene expression and play significant roles in the development of LC. This review aimed to provide a comprehensive analysis of oncogenic miRNAs involved in LC, focusing on their dysregulation, functional roles, and potential implications for diagnosis and therapy. In this review, we collected data from published literature, specifically selecting English articles closely related to the topic. We conducted a thorough review of studies published between 2013 and 2023, utilizing prominent academic databases such as PubMed, Scopus, and Google Scholar to gather relevant data. Our investigation highlights several oncogenic miRNAs that have been shown to play critical roles in lung cancer biology, including miR-9-5p, miR-21, and miR-31. These miRNAs are known to facilitate various key processes, such as tumor cell proliferation, enhanced migratory capabilities, and the development of resistance to chemotherapeutic agents. Additionally, miRNAs present significant diagnostic and therapeutic potential. In conclusion, the unique roles and regulatory networks of miRNAs in LC warrant extensive further research. Further research is essential to uncover the complex networks of miRNAs and to develop innovative miRNA-based therapies for lung cancer.

Reprogramming of lipid metabolism has emerged as a significant characteristic of malignancy during tumor development. Research indicates a critical link between lipid metabolism and the tumor immune microenvironment. This relationship not only facilitates cancer progression by remodeling the tumor microenvironment but also influences the functionality of immune cells. Alterations in lipid metabolism regulate the function and status of immune cells within the microenvironment, impacting immune evasion and the therapeutic efficacy of tumors. Consequently, targeting lipid metabolism is a viable strategy for intervening in tumorigenesis and tumor development. This review examines the roles of key lipid molecules, such as fatty acids and cholesterol, within the tumor microenvironment, highlighting how aberrant lipid metabolism can alter immune cell function. By investigating the interactions between lipid metabolism and immune cells in this setting, the review offers novel insights into early diagnosis, screening, and immunotherapy of malignant tumors. Furthermore, lipid metabolic reprogramming may act as a biomarker for monitoring early immune escape from tumors and predicting therapeutic outcomes, thereby enhancing early diagnosis and personalized cancer treatment.

Amyotrophic lateral sclerosis (ALS) and other motor neuron diseases (MNDs) are major global causes of death. However, their global incidence, mortality, and disability-adjusted life years remain largely unknown, despite their importance for disease prevention and resource allocation. We therefore examined the global epidemiology of ALS/MNDs.

This study analyzed data from the Global Burden of Disease 2021 database for 204 regions (1990–2021), focusing on ALS/MNDs. Data from the world, China, and the G8 countries were analyzed separately. Age-standardized incidence rates were reported for the 1990s, 2000s, 2010s, and 2020s.

A rising global burden of ALS/MNDs, with significant variations across regions and levels of the social development index, was observed in the Global Burden of Disease database. A significant overlap of etiology between neurological diseases and ALS was also identified. Among the G8 countries and China, China and the USA exhibited the highest prevalence rates in the 1990s, 2000s, 2010s, and 2020s, with China showing 3.3 per 10,000 and the USA 4.0 per 10,000 in the 2020s.

Understanding the common etiologies of ALS/MNDs is key to their effective control. Recommended strategies include pollution control, chemical and radiation safety management, disease monitoring, public health education, multi-departmental collaboration, and scientific research.

Recent studies have highlighted a link between amyotrophic lateral sclerosis (ALS) and gut microbiota. This prospective study aimed to evaluate the effects of electroacupuncture combined with Chinese herbal medicine on gut microbiota and metabolomics in ALS patients.

Ten ALS patients were randomly assigned to either a treatment group (electroacupuncture with Chinese herbal medicine, n = 6) or a control group (waiting treatment, n = 4). Healthy controls (age- and sex-matched, n = 10) were also included. Data were collected after 12 sessions of electroacupuncture and follow-ups at three and six months. ALS functional rating scale scores were documented pre- and post-treatment. Stool samples were collected at two time points (T0 and T4 weeks) and analyzed, and metabolomic profiles from urine samples were analyzed post-treatment. Heatmap correlation analysis was used to explore relationships between microbiota, metabolomics, and clinical outcomes.

Treatment with electroacupuncture reduced Eisenbergiella abundance in the treatment group. A significant positive correlation was found between Lachnospiraceae and ALS functional rating scale scores (P < 0.005 and P < 0.001, respectively). Differential expression of purine metabolism was observed in ALS patients (P = 0.0017).

Imbalances in the gut microbiome and metabolic disorders have been found among patients with ALS. These imbalances appear to be partially mitigated by treatment with electroacupuncture combined with Chinese herbal medicine. Our research suggests that Eisenbergiella might be a diagnostic biomarker and a potential therapeutic target for ALS.

Intrahepatic cholangiocarcinoma (iCCA) is the second most prevalent primary liver cancer, characterized by insidious onset and high malignancy. Many patients are diagnosed at an inoperable stage, and the effectiveness of chemotherapy and radiotherapy remains limited. This study aimed to provide a comprehensive review of the histological classification, genetic alterations, molecular subtypes, and corresponding imaging signatures of iCCA, highlighting its heterogeneity and offering insights into targeted therapy and personalized treatment. The heterogeneity of iCCA poses significant challenges to both targeted therapy and immunotherapy, necessitating in-depth exploration at the molecular and subtyping levels. Investigating genetic variations, signaling pathway alterations, and molecular subtypes can aid in patient stratification. Stratifying iCCA patients allows for more precise treatment selection, ultimately improving survival outcomes. Imaging, as a non-invasive tool, holds substantial potential for predicting subtypes and molecular profiles. It is possible to infer histological and molecular features from imaging, or to interpret imaging signatures in light of known histological and molecular data. This integrative approach, combining external imaging with internal molecular insights, fosters a comprehensive understanding of iCCA’s characteristics and enhances clinical management.

Chronic liver cirrhosis (LC) and acute-on-chronic liver failure (ACLF) are interconnected hepatic disorders associated with substantial morbidity and mortality. Despite their distinct clinical characteristics, both conditions share common pathogenic pathways that remain inadequately understood. This study aimed to identify shared gene signatures and elucidate underlying molecular mechanisms.

In this study, we employed Weighted Gene Co-Expression Network Analysis to explore transcriptomic data from the Gene Expression Omnibus for LC and ACLF.

Key co-expression modules enriched with genes involved in glycolysis and gluconeogenesis pathways were identified, implicating metabolic dysfunction as a central feature in both conditions. Furthermore, microRNA analysis revealed that hsa-miR-122 and hsa-miR-194 play pivotal roles in regulating these metabolic pathways, potentially contributing to immune dysregulation.

Our findings indicate that these shared molecular mechanisms are critical in the progression from LC to ACLF, providing novel insights into potential therapeutic targets for mitigating disease severity and improving clinical outcomes.

Tumors are complex systems characterized by variations across genetic, transcriptomic, phenotypic, and microenvironmental levels. This study introduced a novel framework for quantifying cancer cell heterogeneity using single-cell RNA sequencing data. The framework comprised several scores aimed at uncovering the complexities of key cancer traits, such as metastasis, tumor progression, and recurrence.

This study leveraged publicly available single-cell transcriptomic data from three human breast cancer subtypes: estrogen receptor-positive, human epidermal growth factor receptor 2-positive, and triple-negative. We employed a quantitative approach, analyzing copy number alterations (CNAs), entropy, transcriptomic heterogeneity, and diverse protein-protein interaction networks (PPINs) to explore critical concepts in cancer biology.

We found that entropy and PPIN activity related to the cell cycle could distinguish cell clusters with elevated mitotic activity, particularly in aggressive breast cancer subtypes. Additionally, CNA distributions varied across cancer subtypes. We also identified positive correlations between the CNA score, entropy, and the activities of PPINs associated with the cell cycle, as well as those linked to basal and mesenchymal cell lines.

This study addresses a gap in the current understanding of breast cancer heterogeneity by presenting a novel quantitative approach that offers deeper insights into tumor biology, surpassing traditional marker-based methods.

Breast cancer is the most common cancer among women, with hormone receptors playing a crucial role, not only in cancer cell growth but also as primary targets in breast cancer treatment. This systematic literature review aimed to summarize the current evidence on estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) discordance rates between primary and recurrent breast cancer. Additionally, it seeks to identify how discordance affects prognosis, metastasis, and the potential evidence of primary tumor heterogeneity.

The databases Web of Science, Scopus, MEDLINE, and PubMed were searched for publications of original research in English from 2013 to 2023. Studies with paired histopathology from primary and recurrent breast cancer that employed immunohistochemistry and fluorescence in situ hybridization were included. Ten studies were deemed eligible for inclusion.

Concordance between primary and recurrent breast cancer was high for ER (80%), PR (65%), and HER2 (85%). Average discordance rates were: ER 19%, PR 34%, and HER2 15%, with PR discordance consistently being the highest. Loss of ER and PR receptors was observed more frequently than gain, while the opposite trend was noted for HER2. Loss of ER and PR was associated with a worse prognosis. Discordance was also observed in cases of tumor metastasis.

Discordance in receptor expression between primary and recurrent breast cancer was common, highlighting the importance of re-biopsy in recurrent or metastatic breast cancer, if possible. Patients who lost hormone receptors experienced worse outcomes, suggesting the development of treatment-resistant tumor clones.

Waist circumference (WC) is closely associated with metabolic diseases, including diabetes mellitus (DM), metabolic syndrome, and mortality. However, the correlation between WC and mortality varies across populations and has rarely been examined specifically in patients with DM. In this study, we explored the relationships between WC and both all-cause and cardiovascular mortalities among individuals with DM.

Participants from the National Health and Nutrition Examination Survey 2003–2018 included 3,151 women and 3,473 men with DM who had baseline WC measurements. Survival data were collected from enrollment until December 31, 2019. Cox proportional hazard models were adjusted for demographic features and other confounders. Restricted cubic spline curves and threshold effect analyses were performed separately for men and women. Sensitivity analyses were conducted to minimize reverse causality.

Among 6,624 participants with DM, 621 women and 871 men died during median follow-ups of 6.8 and 6.3 years, respectively. WC demonstrated a U-shaped association with all-cause and cardiovascular mortalities in women, and a J-shaped trend in men. The optimal WC thresholds for minimizing mortality risk were 107.0 cm for women and 89.0 cm for men. For women, adjusted hazard ratios for all-cause mortality were 0.97 (95% confidence interval (CI): 0.96–0.98, P < 0.001) for WC below 107.0 cm and 1.04 (95% CI: 1.02–1.05, P < 0.001) for WC above 107.0 cm. In men, the corresponding ratios were 0.94 (95% CI: 0.90–0.97, P < 0.001) for WC below 89.0 cm and 1.03 (95% CI: 1.02–1.05, P < 0.001) for WC above 89.0 cm.

WC showed a U-shaped association with all-cause and cardiovascular mortalities in women and a J-shaped association in men among U.S. adults with DM from the National Health and Nutrition Examination Survey. Further research is needed to explore the underlying mechanisms rather than promoting preconceived notions about an optimal WC.