Search Results (1,548)

KRAS is one of the most frequently mutated genes in all human cancers, and its oncogenic mutation hotspots are glycine 12 (G12), glycine 13 (G13), glutamine 61 (Q61) and alanine 146 (A146). Among these hotspot mutations, A146 substitution mutations (A146X) occur relatively infrequently, except for haematopoietic and lymphoid cancers, suggesting that A146X causes intrinsically distinct KRAS signalling compared to other KRAS oncogenic alleles. However, due to the absence of model A146X cell lines derived from haematopoietic sources, the cellular mechanisms that cause the differences between KRAS.A146X and other common KRAS mutants, such as KRAS.G12X, remain largely unexplored. In this study, we developed a set of isogenic model haematopoietic cell lines expressing KRAS.A146T, KRAS.G12V and KRAS.G12G (non-mutated) from the endogenous locus by genetically modifying the human lymphoblastoid TK6 cell line. We found that TK6 cells carrying KRAS^A146T/+ or KRAS^G12V/+ exhibited increased replication stress compared to KRAS wild-type cells. Strikingly, KRAS^A146T/+ cells strongly rely on PrimPol for maintaining cellular survival upon replication stress. In contrast, KRAS^G12V/+ cells exhibited hypersensitivity to inhibitors for the ATR-Chk1 checkpoint signalling axis and to nucleoside analogues commonly used to treat cancers and viral infections. Our findings demonstrate that the endogenously expressed oncogenic KRAS mutations exacerbate the replication stress and reveal KRAS allele-specific replication phenotypes, facilitating the development of effective chemotherapies tailored to specific oncogenic KRAS mutation alleles and types of cancer. Moreover, our study offers valuable model cell lines for investigating mechanisms underlying replication vulnerability in cancers harbouring oncogenic KRAS mutations. Full article

Background/Objectives: Despite the clinical success of immune checkpoint blockade (ICB), its efficacy remains limited in immunologically “cold” tumors, primarily due to poor immunogenicity and an immunosuppressive tumor microenvironment (TME). Chemo-immunotherapy offers a potential strategy to enhance ICB response, yet its application is often hindered by inadequate tumor-targeted delivery and systemic immunosuppressive side effects. Biomimetic nanotechnology represents a promising approach to overcoming these limitations by improving drug delivery and facilitating effective combination regimens. Methods: We developed a biomimetic nanosystem (NVs@DOX) through genetic engineering of cellular membranes and optimized nanoformulation techniques, enabling co-delivery of doxorubicin (DOX) and ICB agents. This design aims to maximize synergistic antitumor effects while minimizing adverse impacts. Results: In vitro studies demonstrated the potent cytotoxicity of NVs@DOX, including significant inhibition of cancer cell proliferation and complete suppression of colony formation. In a 4T1 murine breast cancer model, NVs@DOX treatment led to substantial tumor growth inhibition (approximately 72%) without notable body weight loss, underscoring a favorable safety profile alongside enhanced therapeutic efficacy. Conclusions: The NVs@DOX platform effectively integrates doxorubicin with ICB within a biomimetic nanocarrier, significantly improving chemo-immunotherapy outcomes. This strategy highlights the potential of genetically engineered cellular nanoparticles as a promising combinatorial approach for the treatment of breast cancer. Full article

Cancer patients are highly vulnerable to severe COVID-19, requiring models that capture tumor–virus interactions. We investigated tumor- and variant-specific effects of SARS-CoV-2 Gamma and Delta infections using patient-derived organoids (PDOs) from metastatic breast, lung, and colorectal cancers. Viral infection was quantified by Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) 24 h post-infection, and morphological changes and immune mediators were profiled. Genomic analysis using whole-exome sequencing was performed to identify contributing host-related gene alterations. The Delta variant produced consistently higher viral loads in lung and breast PDOs, while colorectal PDOs showed variable susceptibility. Infection led to reduced area and perimeter and increased circularity across all tumor types. Immune profiling revealed distinct responses: Gamma decreased Interferon alpha (IFNα) in lung PDOs and increased E-selectin in colorectal PDOs. Delta broadly reduced inflammatory mediators in lung [10 kDa interferon gamma-induced protein (IP-10) and Intercellular adhesion molecule 1 (ICAM-1)] and breast [Interleukin-6 (IL-6), Interleukin-13 (IL-13), and Interleukin-17A (IL-17A)] PDOs, while increasing Macrophage inflammatory protein 1-beta (MIP-1β) in colorectal PDOs. Host gene variants involved in trafficking (FYCO1 and RAB7A) and immune signaling (FOXA2, SFTPD, STAT3, and TET2) were associated with differential infection profiles. These findings show that SARS-CoV-2 induces variant- and tumor-specific morphological and immunological changes in cancer PDOs, highlighting the potential of this model to unravel host–virus interactions and identify genetic factors that shape infection outcomes in cancer. Full article

Cancer and Alzheimer’s disease (AD) display an inverse relationship, and there is a need to further explore this interplay. One key genetic contributor to AD is SORL1, the loss of which is thought to be causally related to AD development. SORL1 also appears to be implicated in cancer. To examine SORL1 and its network, this article simulated SORL1 and its interactions via signal-flow Boolean modelling, including in silico knockouts (mirroring in vivo loss-of-function mutations). This model (SKM034) predicted a total of 29 key changes in molecular relationships following the loss of SORL1 or another highly connected protein (ERBB2). Literature validation demonstrated that 2 of these predictions were at least partially validated experimentally, whilst 27 were Potentially Novel Predictions (PNPs). Complementing the in-depth relationship analyses was signal flow analysis through the network’s structure, validated using cell line and cancer patient RNA-seq data. Correct prediction rates for these analyses reached 60% (statistically significant relative to a random model). This article demonstrates the clinical relevance of this Alzheimer’s-related network in a cancer context and, through the PNPs, provides a strong starting point for in vitro experimental validation. As with previously published models using similar methods, the model may be reanalysed in different contexts for further discoveries. Full article

The gut microbiome is defined as the collective assembly of microbial communities inhabiting the gut, along with their genes and metabolic products. The gut microbiome systematically regulates host metabolism, immunity, and neuroendocrine homeostasis via interspecies interaction networks and inter-organ axes. Given the importance of the gut microbiome to the host, this review integrates the composition, function, and genetic basis of the gut microbiome with host genomics to provide a systematic overview of recent advances in microbiome–host interactions. This encompasses a complete technological pipeline spanning from in vitro to in vivo models to translational medicine. This technological pipeline spans from single-bacterium CRISPR editing, organoid–microbiome co-culture, and sterile/humanized animal models to multi-omics integrated algorithms, machine learning causal inference, and individualized probiotic design. It aims to transform microbiome associations into precision intervention strategies that can be targeted and predicted for clinical application through interdisciplinary research, thereby providing the cornerstone of a new generation of precision treatment strategies for cancer, metabolic, and neurodegenerative diseases. Full article

The gut microbiome is a modifiable factor in cancer survivorship. Diet represents the most practical intervention for modulating the gut microbiome. However, diet–microbiome relationships in prostate-cancer survivors remain poorly characterized. We conducted a comprehensive analysis of diet–microbiome associations in 79 prostate-cancer survivors (ages 62–81) enrolled in a randomized exercise intervention trial, 59.5% of whom still have active metastatic disease. Dietary intake was assessed using the Diet History Questionnaire (201 variables) and analyzed using three validated dietary pattern scores: Mediterranean Diet Adherence Score (MEDAS), Healthy Eating Index-2015 (HEI-2015), and the Mediterranean-Dash Intervention for Neurodegenerative Delay (MIND) diet score. Gut microbiome composition was characterized via 16S rRNA sequencing. Dimensionality reduction strategies, including theory-driven diet scores and data-driven machine learning (Random Forest, and Least Absolute Shrinkage and Selection Operator (LASSO)), were used. Statistical analyses included beta regression for alpha diversity, Permutational Multivariate Analysis of Variance (PERMANOVA) for beta diversity (both Bray–Curtis and Sørensen metrics), and Microbiome Multivariable Associations with Linear Models (MaAsLin2) with negative binomial regression for taxa-level associations. All models tested interactions with exercise intervention, APOLIPOPROTEIN E (APOE) genotype, and testosterone levels. There was an interaction between MEDAS and exercise type on gut alpha diversity (Shannon: p = 0.0022), with stronger diet–diversity associations in strength training and Tai Chi groups than flexibility controls. All three diet-quality scores predicted beta diversity (HEI p = 0.002; MIND p = 0.025; MEDAS p = 0.034) but not Bray–Curtis (abundance-weighted) distance, suggesting diet shapes community membership rather than relative abundances. Taxa-level analysis revealed 129 genera with diet associations or diet × host factor interactions. Among 297 dietary variables tested for cognitive outcomes, only caffeine significantly predicted Montreal Cognitive Assessment (MoCA) scores after False Discovery Rate (FDR) correction (p = 0.0009, q = 0.014) through direct pathways beneficial to cognitive performance without notable gut microbiome modulation. In cancer survivors, dietary recommendations should be tailored to exercise habits, genetic background, and hormonal status. Full article

Objective: To develop and validate a genetic diagnostic model for colorectal cancer (CRC). Methods: First, differential expression genes (DEGs) between colorectal cancer and normal groups were screened using the TCGA database. Subsequently, a two-sample Mendelian randomization analysis was performed using the eQTL genomic data from the IEU OpenGWAS database and colorectal cancer outcomes from the R12 Finnish database to identify associated genes. The intersecting genes from both methods were selected for the development and validation of the CRC genetic diagnostic model using nine machine learning algorithms: Lasso Regression, XGBoost, Gradient Boosting Machine (GBM), Generalized Linear Model (GLM), Neural Network (NN), Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Random Forest (RF), and Decision Tree (DT). Results: A total of 3716 DEGs were identified from the TCGA database, while 121 genes were associated with CRC based on the eQTL Mendelian randomization analysis. The intersection of these two methods yielded 27 genes. Among the nine machine learning methods, XGBoost achieved the highest AUC value of 0.990. The top five genes predicted by the XGBoost method—RIF1, GDPD5, DBNDD1, RCCD1, and CLDN5—along with the five most significantly differentially expressed genes (ASCL2, IFITM3, IFITM1, SMPDL3A, and SUCLG2) in the GSE87211 dataset, were selected for the construction of the final colorectal cancer (CRC) genetic diagnostic model. The ROC curve analysis revealed an AUC (95% CI) of 0.9875 (0.9737–0.9875) for the training set, and 0.9601 (0.9145–0.9601) for the validation set, indicating strong predictive performance of the model. SHAP model interpretation further identified IFITM1 and DBNDD1 as the most influential genes in the XGBoost model, with both making positive contributions to the model’s predictions. Conclusions: The gene expression profile in colorectal cancer is characterized by enhanced cell proliferation, elevated metabolic activity, and immune evasion. A genetic diagnostic model constructed based on ten genes (RIF1, GDPD5, DBNDD1, RCCD1, CLDN5, ASCL2, IFITM3, IFITM1, SMPDL3A, and SUCLG2) demonstrates strong predictive performance. This model holds significant potential for the early diagnosis and intervention of colorectal cancer, contributing to the implementation of third-tier prevention strategies. Full article

Background/Objectives: The COVID-19 pandemic profoundly disrupted gastric cancer care, reducing access to screening, delaying diagnosis, and altering therapeutic pathways worldwide. Beyond clinical challenges, it exposed structural weaknesses in healthcare systems but also accelerated innovation. Methods: We conducted a narrative review supported by a structured literature search (PubMed/MEDLINE, Scopus, Web of Science; 1 January 2014–30 November 2025), with a narrative synthesis of observational studies, registry analyses, and meta-analyses addressing COVID-19–related changes in gastric cancer epidemiology, diagnosis, treatment, vaccination, and telemedicine. A PRISMA-style flow diagram was used to illustrate study selection. Results: Elective endoscopy volumes fell by up to 80%, leading to diagnostic backlogs and increased proportions of advanced-stage gastric cancer. Surgical postponements, modified chemotherapy and radiotherapy schedules, and reduced molecular/genetic testing further compromised outcomes. Conversely, vaccination, telemedicine, capsule endoscopy, and adaptive triage frameworks enabled partial recovery of services. Geographical variations were observed in the recovery of gastric cancer care services, with regions that had established screening infrastructure generally resuming activity more rapidly, whereas others experienced ongoing delays and diagnostic backlogs. Conclusions: This review integrates epidemiological, diagnostic, and therapeutic evidence to demonstrate how COVID-19 redefined gastric cancer care. By highlighting regional disparities and outlining a conceptual model for oncologic resilience, it provides an innovative framework for future crisis preparedness. The lessons of the pandemic—digital health integration, flexible treatment protocols, and international collaboration—represent a foundation for more robust, equitable gastric cancer management in the post-pandemic era. Full article

Colorectal cancer (CRC) develops through evolutionary processes involving genomic alterations, epigenetic regulation, and microenvironmental interactions. While traditionally explained by the stepwise accumulation of driver mutations, contemporary evidence supports a ‘Big Bang’ model in which many early-arising clones expand simultaneously to establish extensive heterogeneity. We reviewed recent studies employing spatially resolved multi-omic sequencing of tumour glands combined with computational modelling. These approaches enable high-resolution reconstruction of clonal architecture, transcriptional states, and chromatin accessibility. Findings show that although early clonal mutations shape tumour expansion, gene expression variability can be independent of genetic ancestry and instead reflects phenotypic plasticity driven by microenvironmental cues. Epigenomic analyses identified recurrent somatic chromatin accessibility alterations in promotors and enhancers of oncogenic pathways, frequently in the absence of DNA mutations, suggesting alternative mechanisms of gene regulation. Immune-focused studies demonstrated that early silencing of antigen-presenting genes and loss of neoantigens facilitate immune escape despite active surveillance. CRC is shaped by an interplay of genome, epigenome, and immune evolution, with non-genetic mechanisms and tumour plasticity emerging as important drivers of progression and therapeutic resistance. Full article

Background/Objectives: Cancer pain affects 55–95% of patients with advanced malignancy, representing a complex syndrome involving nociceptive, neuropathic and nociplastic mechanisms. Despite therapeutic advances, two-thirds of patients with metastatic cancer experience inadequate pain control. This scoping review synthesizes recent advances in cancer pain pathophysiology and management, focusing on molecular and cellular mechanisms, emerging pharmacological, interventional and technological therapies and key evidence gaps to inform future precision-based pain management strategies. Methods: Following PRISMA-ScR methodology, we searched PubMed, Embase, Scopus, and Web of Science for studies published between January 2022 and September 2025. After screening 3412 records, 278 studies were included and analyzed across different domains: biological mechanisms, pharmacological management, interventional and neuromodulatory approaches, radiotherapy developments, and digital health innovations. Results: Recent mechanistic research reveals cancer pain arises from tumor–neuron–immune crosstalk, with malignant cells secreting neurotrophic factors that promote axonal sprouting and nociceptor sensitization. Genetic polymorphisms and epigenetic modifications contribute to inter-individual pain variability. Management strategies are evolving toward multimodal precision medicine: NSAIDs and opioids remain foundational, complemented by adjuvant agents and interventional procedures including nerve blocks, intrathecal delivery, and neuromodulation (spinal cord and dorsal root ganglion stimulation). Stereotactic body radiotherapy demonstrates superior analgesic durability versus conventional approaches. Digital health innovations, such as mobile applications, remote monitoring, wearables, and AI-enabled predictive models, enable continuous assessment and personalized treatment optimization. Conclusions: Cancer pain management is transitioning toward mechanism-based precision medicine integrating biological insights, advanced interventional techniques, and digital technologies. However, implementation challenges persist, including limited randomized trials for interventional approaches, the incomplete external validation of AI tools, and digital health equity concerns. Future research must prioritize prospective controlled studies and equitable integration into routine care. Full article

The mammalian lung operates under a biological paradox, requiring architectural fragility for gas exchange while maintaining robust regenerative plasticity to withstand injury. The Hippo signaling pathway has emerged as a central “rheostat” in orchestrating these opposing needs, yet the distinct roles of its downstream effectors remain underappreciated. This review synthesizes recent genetic and mechanobiological advances to propose a “Tale of Two Effectors” model, arguing for the functional non-redundancy of YAP and TAZ. We posit that YAP functions to drive airway progenitor expansion, mechanical force generation, and maladaptive remodeling. Conversely, TAZ—regulated uniquely via transcriptional mechanisms and mechanotransduction—acts as an obligate driver of alveolar differentiation and adaptive repair through an NKX2-1 feed-forward loop. Furthermore, we introduce the “See-Saw” model of tissue fitness, where mesenchymal niche collapse releases the mechanical brake on the epithelium, triggering the bronchiolization characteristic of pulmonary fibrosis. Finally, we extend this framework to malignancy, illustrating how Small Cell Lung Cancer (SCLC) subtypes mirror these developmental and regenerative states. This integrated framework offers new therapeutic distinct targets for modulating tissue fitness and resolving fibrosis. Full article

Bone metastasis in breast cancer remains a major therapeutic challenge because current osteoclast-targeted therapies do not fully disrupt the tumor–bone vicious cycle. Osteocytes, the most abundant bone cells, are increasingly recognized as key regulators of bone–tumor crosstalk. Previous work has shown that osteocyte-specific overexpression of the Wnt co-receptor LRP5 inhibits breast cancer-induced osteolysis and generates conditioned medium (CM) with tumor-suppressive activity. Proteomic analysis identified LIM domain and actin-binding protein 1 (LIMA1) as a central mediator that interacts with Myosin Vb (MYO5B), suggesting the role of the LIMA1/MYO5B regulatory axis. This study demonstrates that CM derived from LRP5-overexpressing osteocytes suppresses EO771 breast cancer cell proliferation, migration, and invasion, and downregulates tumor-promoting proteins, including MMP9, Snail, IL-6, and TGF-β1, while upregulating the apoptosis-related protein cleaved caspase-3. These effects were largely reversed by knockdown of LIMA1 or MYO5B. In syngeneic mouse models of mammary tumors and bone metastasis, systemic administration of LRP5-overexpressing osteocyte-derived CM reduced tumor burden and osteolytic bone destruction, whereas genetic knockdown of LIMA1 in osteocytes or MYO5B in tumor cells abrogated these protective effects. Collectively, these findings indicate that LRP5 activation in osteocytes engages the LIMA1/MYO5B signaling axis that inhibits breast cancer progression and osteolysis, disrupts tumor–stromal interactions, and restores bone–tumor homeostasis, thereby providing a potential therapeutic strategy to break the vicious cycle of bone metastasis in breast cancer. Full article

Background: Colorectal cancer (CRC) is a malignancy that ranks among the top three in terms of both global mortality and incidence. Although numerous studies have demonstrated that gut microbes are implicated in CRC pathogenesis, the precise mechanisms underlying host–microbiota metabolic crosstalk remain poorly understood. Objective: This study aims to identify and delineate key co-metabolites and their associated metabolic pathways that modulate the biomass of CRC-related gut bacteria within healthy individuals, through the construction of host–gut microbiota co-metabolic network models. We seek to elucidate the underlying mechanisms of metabolic interplay between the host and CRC-related gut microbiota, thereby offering novel perspectives on the microbial involvement in the initiation and progression of CRC. Methods: We coupled a colon tissue-specific host Genome-Scale Metabolic Model (GEM), which utilized transcriptomic data from healthy human colon tissues, with 12 CRC-associated pro-/anti-carcinogenic gut bacterial GEMs to construct a co-metabolic network. Through a comparative analysis of the network structure and systemic methods (including Flux Sampling and metabolic difference analysis), we simulated scenarios of constrained host co-metabolite supply. Finally, metabolic subsystem enrichment analysis was employed to elucidate the specific molecular mechanisms by which key co-metabolites affect microbial function. Results: The 17 key co-metabolites identified include chloride ions, zinc ions, and acetate. Among these, thirteen metabolites (e.g., ferric iron, succinate, and acetate) were confirmed by literature to be associated with CRC. All 17 key co-metabolites were found to significantly modulate the biomass of CRC-associated gut bacteria. These regulatory effects primarily influence microbial function through core pathways such as glycerophospholipid metabolism and folate metabolism. Conclusion: This research provides a systemic perspective for elucidating the mechanisms of host–gut microbiota metabolic interplay in CRC, thereby complementing the existing theoretical framework concerning microbial regulation by the host genetic background. Full article

Patient-derived organoids (PDOs) have emerged as promising preclinical models for studying tumor biology and testing therapeutic strategies in oncology. These three-dimensional culture systems retain key histological, genetic, and functional characteristics of the original tumors, offering a unique opportunity to advance personalized medicine approaches in liver cancer. In this study, we present the methodological framework and preliminary findings of a prospective study aimed at generating and characterizing PDOs from patients with hepatocellular carcinoma (HCC) undergoing surgical resection. Tumor specimens were processed using an optimized protocol for organoid derivation, expansion, and cryopreservation. We evaluated the success rate of organoid establishment and the histo-molecular fidelity to the parental tumor. These early results demonstrate promising engraftment efficiency and maintenance of tumor-specific markers across passages. Our work highlights the potential of PDOs as a reliable and scalable platform for translational research in HCC, setting the stage for future applications in drug screening and biomarker discovery. Full article

Background and Rationale: Tinospora crispa (L.) Hook.f. & Thomson (T. crispa) is a climbing medicinal plant with long-standing ethnopharmacological use, particularly in inflammatory and hepatic disorders and cancer-related conditions. There is a knowledge gap regarding how wild versus cultivated ecotypes differ in chemotype, bioactivity, and safety, and how this might support or refine traditional use. Study Objectives: This study aimed to compare wild and cultivated ecotypes of T. crispa from the Nile Delta (Egypt) in terms of quantitative and qualitative phytochemical profiles; selected in vitro biological activities (especially antioxidant and cytotoxic actions); genetic markers potentially associated with metabolic variation; and short-term oral safety in an animal model. Core Methodology: Standardized extraction of plant material from wild and cultivated ecotypes. Determination of total phenolics, total flavonoids, and major phytochemical classes (alkaloids, tannins, terpenoids). Metabolomic characterization using UHPLC-ESI-QTOF-MS, supported by NMR, to confirm key compounds such as berberine, palmatine, chlorogenic acid, rutin, and borapetoside C. In vitro bioassays including: Antioxidant activity (e.g., radical-scavenging assay with EC₅₀ determination). Cytotoxicity against human cancer cell lines, with emphasis on HepG2 hepatoma cells and calculation of IC₅₀ values. Targeted genetic analysis to detect single-nucleotide polymorphisms (SNPs) in the gen1 locus that differentiate ecotypes. A 14-day oral toxicity study in rats, assessing liver and kidney function markers and performing histopathology of liver and kidney tissues. Principal Results: The wild ecotype showed a 43–65% increase in total flavonoid and polyphenol content compared with the cultivated ecotype, as well as substantially higher levels of key alkaloids, particularly berberine (around 12.5 ± 0.8 mg/g), along with elevated chlorogenic acid and borapetoside C. UHPLC-MS and NMR analyses confirmed the identity of the main bioactive constituents and defined a distinct chemical fingerprint for the wild chemotype. Bioassays demonstrated stronger antioxidant activity of the wild extract than the cultivated one and selective cytotoxicity of the wild extract against HepG2 cells (IC₅₀ ≈ 85 µg/mL), being clearly more potent than extracts from cultivated plants. Genetic profiling detected a C → T SNP within the gen1 region that differentiates the wild ecotype and may be linked to altered biosynthetic regulation. The 14-day oral toxicity study (up to 600 mg/kg) revealed no evidence of hepatic or renal toxicity, with biochemical markers remaining within physiological limits and normal liver and kidney histology. Conclusions and Future Perspectives: The wild Nile-Delta ecotype of T. crispa appears to be a stress-adapted chemotype characterized by enriched levels of multiple bioactive metabolites, superior in vitro bioactivity, and an encouraging preliminary safety margin. These findings support further evaluation of wild T. crispa as a candidate source for standardized botanical preparations targeting oxidative stress-related and hepatic pathologies, while emphasizing the need for: More comprehensive in vivo efficacy studies. Cultivation strategies that deliberately maintain or mimic beneficial stress conditions to preserve phytochemical richness. Broader geographical and genetic sampling to assess how generalizable the present chemotypic and bioactivity patterns are across the species. Full article