Search Results (1,108)

Globally, the mutations around forest landscapes continue to draw significant scientific interest, despite fragmented evidence on the socio-ecological outcomes linked to this process. This knowledge gap is evident in the Congo Basin—one of the world’s major ecosystems. To contribute towards addressing the knowledge gap, this study analyzed two decades of forest landscape mutations and the socio-ecological transformation-cum-outcomes linked to the process in Cameroon. A mixed-methods approach was employed, combining remote sensing-based land use/land cover (LULC) analysis (using multi-date Landsat imagery at 30 m resolution) with household surveys involving 100 randomly selected forest-dependent households across three forest blocks: Ebo, Ndokbou, and Makombé for ground truthing. Survey data were analyzed using descriptive statistics and combined spatial analysis to reveal the following. Firstly, forest cover has significantly increased within the 20-year period; this involved a 104.01% increase between 2004 and 2014, and an additional 47.27% between 2014 and 2024. In that vein, agricultural land declined by more than 20%, whereas settlement and water bodies increased by 226.4% and 376.2%, respectively. Secondly, forest landscape mutations in the Yabassi Forest Area were primarily driven by a convergence of social (notably population growth at 57% and livelihood diversification), economic (agricultural expansion and timber exploitation), political (tenure ambiguity and development-driven land conversion), and environmental (climate variability at 36% and ecological restoration efforts) forces. These interwoven drivers shaped the land use change process, revealing how the human-environment feedback defines landscape trajectories in complex and non-linear ways. Thirdly, while the ecological outcomes of forest mutations were largely positive—with significant gains in forest cover, the social outcomes were skewed towards the negative. Communities experienced both improvements in livelihoods and infrastructure (66%), but also faced land conflicts (67%), the loss of traditional access (69%), and resource-based insecurity. By applying the socio-ecological systems (SES) framework, this study provides novel insights on how governance, ecological processes, and human behavior co-evolve in forest landscapes. The findings do not only edify the SES framework but also challenge the mainstream position about forest decline by highlighting areas of recovery. The evidence informs adaptive forest governance processes in the Congo Basin and similar contexts. Further research should investigate the institutional and adaptive mechanisms that influence these dynamics across the Congo Basin. Full article

Pancreatic neuroendocrine tumors (pNETs) are rare malignancies, accounting for 1–2% of pancreatic cancers, with an incidence of ≤1 case per 100,000 individuals annually. Originating from pancreatic endocrine cells, pNETs display significant clinical and biological heterogeneity. Traditional classification based on proliferative grading does not fully capture the complex mechanisms involved, such as oxidative stress, mitochondrial dysfunction, and tumor-associated macrophage infiltration. Recent advances in molecular profiling have revealed key oncogenic drivers, including MEN1 (menin 1), DAXX (death domain–associated protein), ATRX (alpha thalassemia/mental retardation syndrome X-linked), CDKN1B (cyclin-dependent kinase inhibitor 1B) mutations, chromatin remodeling defects, and dysregulation of the mTOR pathway. Somatostatin receptors, particularly SSTR2, play a central role in tumor biology and serve as important prognostic markers, enabling the use of advanced diagnostic imaging (e.g., Gallium-68 DOTATATE PET/CT) and targeted therapies like somatostatin analogs and peptide receptor radionuclide therapy (PRRT). Established biomarkers such as Chromogranin A and the Ki-67 proliferation index remain vital for diagnosis and prognosis, while emerging markers, like circulating tumor DNA and microRNAs, show promise for enhancing disease monitoring and diagnostic accuracy. This review summarizes the molecular landscape of pNETs and highlights genomic, transcriptomic, proteomic, and epigenomic factors that support the identification of novel diagnostic, prognostic, and therapeutic biomarkers, ultimately advancing personalized treatment strategies. Full article

Lung cancer (LC), with non-small-cell lung cancer (NSCLC) as its predominant subtype, remains the leading cause of cancer-related mortality worldwide. While immune checkpoint inhibitors (ICIs) have redefined the therapeutic paradigm in advanced NSCLC, durable responses are confined to a limited subset of patients. A major clinical challenge persists: the inability to accurately predict which patients will derive meaningful benefit, which will exhibit primary resistance, and which are at risk for severe immune-related toxicities. The imperative to individualize ICI therapy necessitates robust, dynamic, and accessible biomarkers. Liquid biopsy has emerged as a transformative, minimally invasive tool that enables real-time molecular and immunologic profiling. Through analysis of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, and peripheral blood immune components, liquid biopsy offers a window into both tumor intrinsic and host-related determinants of ICI response. These biomarkers not only hold promise for identifying predictive signatures—such as tumor mutational burden, neoantigen landscape, or immune activation states—but also for uncovering mechanisms of acquired resistance and guiding treatment adaptation. Beyond immunotherapy, liquid biopsy plays an increasingly central role in the landscape of targeted therapies, allowing early detection of actionable driver mutations and resistance mechanisms (e.g., EGFR T790M, MET amplification, and ALK fusion variants). Importantly, serial sampling via liquid biopsy facilitates longitudinal disease monitoring and timely therapeutic intervention without the need for repeated tissue biopsies. By guiding therapy selection, monitoring response, and detecting resistance early, liquid biopsy has the potential to significantly improve outcomes in NSCLC. Full article

Targeted therapies against specific driver gene mutations have become the standard first-line treatment for most patients with advanced non-small cell lung cancer (NSCLC). While these therapies significantly prolong survival, the entire cancer treatment journey remains challenging and distressing. To better understand these experiences, this study employed a qualitative descriptive approach, conducting semi-structured interviews with 18 advanced NSCLC patients receiving targeted therapy, supplemented by patient journey logs. The resulting journey map delineated five stages: diagnosis, initial treatment, maintenance therapy, disease progression, and end-of-life. The analysis identified four key themes characterizing patient experiences at each stage. These findings enable healthcare professionals to identify risk situations and determine optimal timing for support interventions. Similarly, preparing patients for the processes they must undergo and the side effects of medical treatment helps reduce their uncertainty and anxiety, thereby improving their quality of life. Full article

Oxidative stress is a defining and pervasive driver of neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). As a molecular accelerant, reactive oxygen species (ROS) and reactive nitrogen species (RNS) compromise mitochondrial function, amplify lipid peroxidation, induce protein misfolding, and promote chronic neuroinflammation, creating a positive feedback loop of neuronal damage and cognitive decline. Despite its centrality in promoting disease progression, attempts to neutralize oxidative stress with monotherapeutic antioxidants have largely failed owing to the multifactorial redox imbalance affecting each patient and their corresponding variation. We are now at the threshold of precision redox medicine, driven by advances in syndromic multi-omics integration, Artificial Intelligence biomarker identification, and the precision of patient-specific therapeutic interventions. This paper will aim to reveal a mechanistically deep assessment of oxidative stress and its contribution to diseases of neurodegeneration, with an emphasis on oxidatively modified proteins (e.g., carbonylated tau, nitrated α-synuclein), lipid peroxidation biomarkers (F2-isoprostanes, 4-HNE), and DNA damage (8-OHdG) as significant biomarkers of disease progression. We will critically examine the majority of clinical trial studies investigating mitochondria-targeted antioxidants (e.g., MitoQ, SS-31), Nrf2 activators (e.g., dimethyl fumarate, sulforaphane), and epigenetic reprogramming schemes aiming to re-establish antioxidant defenses and repair redox damage at the molecular level of biology. Emerging solutions that involve nanoparticles (e.g., antioxidant delivery systems) and CRISPR (e.g., correction of mutations in SOD1 and GPx1) have the potential to transform therapeutic approaches to treatment for these diseases by cutting the time required to realize meaningful impacts and meaningful treatment. This paper will argue that with the connection between molecular biology and progress in clinical hyperbole, dynamic multi-targeted interventions will define the treatment of neurodegenerative diseases in the transition from disease amelioration to disease modification or perhaps reversal. With these innovations at our doorstep, the future offers remarkable possibilities in translating network-based biomarker discovery, AI-powered patient stratification, and adaptive combination therapies into individualized/long-lasting neuroprotection. The question is no longer if we will neutralize oxidative stress; it is how likely we will achieve success in the new frontier of neurodegenerative disease therapies. Full article

Coronavirus disease 2019 (COVID-19) causes cardiovascular complications, which contributes to the high mortality rate of the disease. Emerging evidence indicates that aberrant vascular smooth muscle cell (SMC) function is a key driver of vascular disease in COVID-19. While antivirals alleviate the symptoms of COVID-19, it is not known whether these drugs directly affect SMCs. Accordingly, the present study investigated the ability of three approved COVID-19 antiviral drugs to influence SMC function. Treatment of SMCs with remdesivir (RDV), but not molnupiravir or nirmatrelvir, inhibited cell proliferation, DNA synthesis, and migration without affecting cell viability. RDV also stimulated an increase in heme oxygenase-1 (HO-1) expression that was not observed with molnupiravir or nirmatrelvir. The induction of HO-1 by RDV was abolished by mutating the antioxidant responsive element of the promoter, overexpressing dominant-negative NF-E2-related factor-2 (Nrf2), or treating cells with an antioxidant. Finally, silencing HO-1 partly rescued the proliferative and migratory response of RDV-treated SMCs, and this was reversed by carbon monoxide and bilirubin. In conclusion, the induction of HO-1 via the oxidant-sensitive Nrf2 signaling pathway contributes to the antiproliferative and antimigratory actions of RDV by generating carbon monoxide and bilirubin. These pleiotropic actions of RDV may prevent occlusive vascular disease in COVID-19. Full article

Background/Objectives: Hepatic cancers, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are major global health concerns due to rising incidence and limited therapeutic success. While traditional risk factors include chronic liver disease and environmental exposures, recent evidence underscores the significance of genetic alterations and gut microbiota in liver cancer development and progression. This review aims to integrate emerging knowledge on the interplay between host genomic changes and gut microbial dynamics in the pathogenesis and treatment of hepatic cancers. Methods: We conducted a comprehensive review of current literature on genetic and epigenetic drivers of HCC and CCA, focusing on commonly mutated genes such as TP53, CTNNB1, TERT, IDH1/2, and FGFR2. In parallel, we evaluated studies addressing the gut–liver axis, including the roles of dysbiosis, microbial metabolites, and immune modulation. Key clinical and preclinical findings were synthesized to explore how host–microbe interactions influence tumorigenesis and therapeutic response. Results: HCC and CCA exhibit distinct but overlapping genomic landscapes marked by recurrent mutations and epigenetic reprogramming. Alterations in the gut microbiota contribute to hepatic inflammation, genomic instability, and immune evasion, potentially enhancing oncogenic signaling pathways. Furthermore, microbiota composition appears to affect responses to immune checkpoint inhibitors. Emerging therapeutic strategies such as probiotics, fecal microbiota transplantation, and precision oncology based on mutational profiling demonstrate potential for personalized interventions. Conclusions: The integration of host genomics with microbial ecology provides a promising paradigm for advancing diagnostics and therapies in liver cancer. Targeting the gut–liver axis may complement genome-informed strategies to improve outcomes for patients with HCC and CCA. Full article

Replication timing (RT), the temporal order of DNA replication during S phase, influences regional mutation rates, yet the mechanistic basis for RT-associated mutagenesis remains incompletely defined. To identify drivers of RT-dependent mutation biases, we analyzed whole-genome sequencing data from cells with disruptions in DNA replication/repair genes or exposed to mutagenic compounds. Mutation distributions between early- and late-replicating regions were compared using bootstrapping and statistical modeling. We identified 14 genes that exhibit differential effects in early- or late-replicating regions, encompassing multiple DNA repair pathways, including mismatch repair (MLH1, MSH2, MSH6, PMS1, and PMS2), trans-lesion DNA synthesis (REV1) and double-strand break repair (DCLRE1A and PRKDC), DNA polymerases (POLB, POLE3, and POLE4), and other genes central to genomic instability (PARP1 and TP53). Similar analyses of mutagenic compounds revealed 19 compounds with differential effects on replication timing. These results establish replication timing as a critical modulator of mutagenesis, with distinct DNA repair pathways and exogenous agents exhibiting replication timing-specific effects on genomic instability. Our systematic bioinformatics approach identifies new DNA repair genes and mutagens that exhibit differential activity during the S phase. These findings pave the way for further investigation of factors that contribute to genome instability during cancer transformation. Full article

Osteosarcoma (OS), the most common primary bone cancer of mesenchymal origin in children and young adolescents, remains a challenge due to metastasis and resistance to chemotherapy. It displays severe aneuploidy and a high mutation frequency which drive tumor initiation and progression; however, recent studies have highlighted the role of epigenetic modifications as a key driver of OS pathogenesis, independent of genetic mutations. DNA and RNA methylation, histone modifications and non-coding RNAs are among the major epigenetic modifications which can modulate the expression of oncogenes. Abnormal activity of these mechanisms contributes to gene dysregulation, metastasis and immune evasion. Therapeutic targeting against these epigenetic mechanisms, including inhibitors of DNA and RNA methylation as well as regulators of RNA modifications, can enhance tumor suppressor gene activity. In this review, we examine recent studies elucidating the role of epigenetic regulation in OS pathogenesis and discuss emerging drugs or interventions with potential clinical utility. Understanding of tumor- specific epigenetic alterations, coupled with innovative therapeutic strategies and AI-driven biomarker discovery, could pave the way for personalized therapies based on the molecular profile of each tumor and improve the management of patients with OS. Full article

Background/Objectives: The RTK-RAS signaling cascade is a central axis in colorectal cancer (CRC) pathogenesis, governing cellular proliferation, survival, and therapeutic resistance. Somatic alterations in key pathway genes—including KRAS, NRAS, BRAF, and EGFR—are pivotal to clinical decision-making in precision oncology. However, the integration of these genomic events with clinical and demographic data remains hindered by fragmented resources and a lack of accessible analytical frameworks. To address this challenge, we developed AI-HOPE-RTK-RAS, a domain-specialized conversational artificial intelligence (AI) system designed to enable natural language-based, integrative analysis of RTK-RAS pathway alterations in CRC. Methods: AI-HOPE-RTK-RAS employs a modular architecture combining large language models (LLMs), a natural language-to-code translation engine, and a backend analytics pipeline operating on harmonized multi-dimensional datasets from cBioPortal. Unlike general-purpose AI platforms, this system is purpose-built for real-time exploration of RTK-RAS biology within CRC cohorts. The platform supports mutation frequency profiling, odds ratio testing, survival modeling, and stratified analyses across clinical, genomic, and demographic parameters. Validation included reproduction of known mutation trends and exploratory evaluation of co-alterations, therapy response, and ancestry-specific mutation patterns. Results: AI-HOPE-RTK-RAS enabled rapid, dialogue-driven interrogation of CRC datasets, confirming established patterns and revealing novel associations with translational relevance. Among early-onset CRC (EOCRC) patients, the prevalence of RTK-RAS alterations was significantly lower compared to late-onset disease (67.97% vs. 79.9%; OR = 0.534, p = 0.014), suggesting the involvement of alternative oncogenic drivers. In KRAS-mutant patients receiving Bevacizumab, early-stage disease (Stages I–III) was associated with superior overall survival relative to Stage IV (p = 0.0004). In contrast, BRAF-mutant tumors with microsatellite-stable (MSS) status displayed poorer prognosis despite higher chemotherapy exposure (OR = 7.226, p < 0.001; p = 0.0000). Among EOCRC patients treated with FOLFOX, RTK-RAS alterations were linked to worse outcomes (p = 0.0262). The system also identified ancestry-enriched noncanonical mutations—including CBL, MAPK3, and NF1—with NF1 mutations significantly associated with improved prognosis (p = 1 × 10⁻⁵). Conclusions: AI-HOPE-RTK-RAS exemplifies a new class of conversational AI platforms tailored to precision oncology, enabling integrative, real-time analysis of clinically and biologically complex questions. Its ability to uncover both canonical and ancestry-specific patterns in RTK-RAS dysregulation—especially in EOCRC and populations with disproportionate health burdens—underscores its utility in advancing equitable, personalized cancer care. This work demonstrates the translational potential of domain-optimized AI tools to accelerate biomarker discovery, support therapeutic stratification, and democratize access to multi-omic analysis. Full article

Sub-Saharan Africa is experiencing the highest mortality rates for several cancer types. While cancer research globally has entered the genomic era and advanced the deployment of precision oncology, Africa has largely been excluded and has received few benefits from tumour profiling. Through a thorough literature review, we identified only five whole cancer genome databases that include patients from Sub-Saharan Africa, covering four cancer types (breast, esophageal, prostate, and Burkitt lymphoma). Irrespective of cancer type, these studies report higher tumour genome instability, including African-specific cancer drivers and mutational signatures, suggesting unique contributory mechanisms at play. Reviewing bioinformatic tools applied to African databases, we carefully select a workflow suitable for large-scale African resources, which incorporates cohort-level data and a scalable design for time and computational efficiency. Using African genomic data, we demonstrate the scalability achieved by high-level parallelism through physical data or genomic interval chunking strategies. Furthermore, we provide a rationale for improving current workflows for African data, including the adoption of more genomic techniques and the prioritisation of African-derived datasets for diverse applications. Together, these enhancements and genomic scaling strategies serve as practical computational guidance, lowering technical barriers for future large-scale African-inclusive research and ultimately helping to reduce the disparity gap in cancer mortality rates across Sub-Saharan Africa. Full article

DNA polymerase epsilon (POLe) is the leading strand replicative polymerase. POLe mutations located primarily in the proofreading domain cause replication errors and increase mutation burden in cancer cells. Consequently, POLe has been classified as a cancer driver gene. Certain POLe frameshift mutations that affect the proofreading domain are purified in cancer cells, but point mutations in other domains have also been reported. Here we use an artificial intelligence algorithm to determine what other mutations co-occur with POLe mutations in colorectal cancers. We partitioned POLe mutations into driver, passenger, and WT (no mutation), then assessed mutations in other genes in these three groups. We found that a driver POLe mutation is not likely to associate with driver mutations in other genes. Thus, driver mutations in colorectal cancers appear to purify in a manner that is independent of POLe. Mutations that affect POLe function do not necessarily increase the frequency of driver mutations in other genes. Structural analysis shows that many POLe driver mutations affect coordination of the Mg²⁺ ion in the active site. Our data show that the accumulation of colorectal cancer mutations is driven by complex factors. Full article

Sporadic colorectal cancer (CRC), the third leading cause of cancer-related death globally, arises through a continuum from normal tissue to adenomas, progressing from low-grade (LGD) to high-grade dysplasia (HGD); yet, the early epigenetic drivers of this transition remain unclear. To investigate these events, we profiled LGD and HGD adenomas using EM-seq, and identified a consensus differential methylation signature (DMS) of 626 regions through two independent bioinformatics pipelines. This signature effectively distinguished LGD from HGD in both tissue and plasma-derived cell-free DNA (cfDNA), highlighting specific methylation patterns. Functional annotation indicated enrichment for regulatory elements associated with transcription factor activity and cell signaling. Applying the DMS to the TCGA CRC dataset revealed three tumor subtypes with increasing hypermethylation and one normal cluster. The most hypermethylated subtype exhibited poor survival, high mutation burden, and disrupted transcriptional networks. While overlapping with classical CpG Island Methylator Phenotype (CIMP) categories, the DMS captured a broader spectrum of methylation alterations. These findings suggest that the DMS captures functionally relevant, antecedent epigenetic alterations in CRC progression, enabling the robust stratification of dysplasia severity and tumor subtypes. This signature holds promise for enhancing preclinical detection and molecular classification, and warrants further evaluation in larger prospective cohorts. Full article

Lung adenocarcinoma exhibits a heterogeneous molecular landscape shaped by key oncogenic drivers and tumor suppressor gene alterations. Mutation frequencies vary geographically, influenced by genetic ancestry and environmental factors. However, the molecular profile of lung adenocarcinoma in Bulgarian patients remains largely uncharacterized. We conducted a prospective study of 147 Bulgarian patients with metastatic lung adenocarcinoma, analyzing clinicopathologic features and somatic mutation frequencies using next-generation sequencing. Key mutations and their prevalence were assessed and compared with published data from other populations. The cohort included predominantly male patients (68.0%) with a median age of 67 years. TP53 mutations were most frequent (41.5%), followed by EGFR alterations (19.0%) and KRAS c.34G>T (p.Gly12Cys) (17.0%). Over half of the patients (51.0%) harbored two or more gene mutations. Mutation frequencies aligned closely with European cohorts, exhibiting a lower prevalence of EGFR mutations compared to East Asian populations. This study characterizes the molecular landscape of lung adenocarcinoma in Bulgaria, highlighting the predominance of TP53 and KRAS mutations. The findings emphasize the need for comprehensive molecular profiling to inform targeted therapies and support precision oncology approaches tailored to the Bulgarian population. Further research is needed to validate these results and improve clinical outcomes. Full article

Fusobacterium nucleatum and activating mutations in the Kirsten rat sarcoma virus oncogene homolog (KRAS) are increasingly recognized as cooperative drivers of colorectal cancer (CRC). F. nucleatum promotes tumorigenesis via adhesion to epithelial cells, modulation of the immune microenvironment, and delivery of virulence factors, while KRAS mutations—present in 60% of CRC cases—amplify proliferative signaling and inflammatory pathways. Here, we review the molecular interplay by which F. nucleatum enhances KRAS-driven oncogenic cascades and, conversely, how KRAS mutations reshape the tumor niche to favor bacterial colonization. We further discuss the use of KRAS as a prognostic biomarker and explore promising non-antibiotic interventions—such as phage therapy, antimicrobial peptides, and targeted small-molecule inhibitors—aimed at selectively disrupting F. nucleatum colonization and virulence. This integrated perspective on microbial–genetic crosstalk offers novel insights for precision prevention and therapy in CRC. Full article