Medical Oncology最新文献

Multidrug resistance (MDR) still constitutes a significant barrier to the effective treatment of lung cancer and makes a significant contribution to the poor clinical results. MDR is explained by a set of mechanisms; increase of drug efflux, metabolism, increase of DNA repair potential, inhibition of apoptotic signals, mutation or post-translational modification of drug targets. These cell intrinsic mechanisms are even aggravated by tumour-microenvironment-induced factors, epigenetics dysregulation, survival of cancer stem cells and intratumour heterogeneity, which has made resistance highly adaptive and multifactorial. In order to address this complexity emerging therapeutic strategy is dual. The former element deals with new targeted agents which are able to counter an oncogene-mediated resistance. These include next-generation tyrosine kinase inhibitors (TKIs), KRAS12C inhibitors, bispecific antibodies including ivonescimab, and they all are specific to inhibit predominant signalling cascades that promote tumoral proliferation and resistance. The second element is drug repurposing whereby it exploits already established pharmacological drugs with already a clear safety record to attack non-oncogenic vulnerabilities linked with MDR. Pharmacological modulators of autophagy including statins, disulfiram, and lysosomotropic agents (e.g., chloroquine) target metabolic vulnerabilities such as mitochondrial bioenergetics and redox homeostasis. By mitigating oxidative stress and immune evasion, these compounds act as chemo sensitizers that potentiate the efficacy of tyrosine kinase inhibitors (TKIs) and immunotherapies, effectively overcoming adaptive drug resistance. Real-time monitoring of resistance evolution can be achieved with liquid biopsies, such as circulating tumor DNA and exosomal cargo, whereas MDR-related biomarkers can be used to stratify a patient. Analytical models that are built using artificial-intelligence also guide rational combination-therapy design and the chosen selection of treatments that are personalized. Also, inhalable nano formulations and targeted drug-delivery systems optimize the bioavailability of the formulation by pulmonary determination and ameliorates the systemic toxicity. A combination of these therapeutic approaches will provide a more accurate and flexible way of conquering MDR in lung cancer.

The current investigation evaluated the antitumor efficacy of a standardized hydroalcoholic extract of Cleome gynandra leaves (HAECG) using the Ehrlich ascites carcinoma (EAC) model in Swiss albino mice. Administration of HAECG produced a significant and dose-dependent suppression of tumor progression, as evidenced by a marked reduction in tumor volume (3.1 ± 0.20 mm vs. 5.4 ± 0.25 mm; p < 0.001), viable tumor cell count, and lipid peroxidation levels (0.58 ± 0.03 vs. 0.95 ± 0.05 mg/g; p < 0.001) when compared with the EAC control group. Elevated glycoprotein markers, including hexose, hexosamine, and sialic acid, commonly associated with increased membrane turnover and malignancy, were substantially reduced following treatment, demonstrating effective biochemical normalization. HAECG also restored serum protein levels (11.5 ± 0.98 g/dL vs. 8.9 ± 0.5 g/dL), suggesting a protective effect against tumour-induced hepatic dysfunction. Phytochemical screening identified phenolics, flavonoids, alkaloids, and other secondary metabolites, which are well recognized for their antioxidant, pro-apoptotic, and cytotoxic properties. The combined reduction in oxidative stress and normalization of tumour-associated biochemical parameters indicate that HAECG exerts its antitumor activity through both antioxidant and metabolic regulatory mechanisms. Collectively, these findings highlight C. gynandra as a promising natural candidate for the development of novel anticancer therapeutics.

Breast cancer often carries a poor short-term prognosis because of its strong tendency for early distant metastasis and recurrence. Effective treatment requires strategies that disrupt the anabolic pathways cancer cells use to overcome therapeutic resistance. In this study, we explored a synergistic combination of a well-tolerated anti-diabetic drug, Metformin, which is in a phase III clinical trial, and dendrosomal curcumin, DNC, to induce cell death in breast cancer MDA-MB-231 and MCF-7 cells. Intriguingly, Metformin and DNC exhibited positive synergistic effects, increased anticancer toxicity through S-phase cell growth arrest, enhanced activation of caspases, reduced expression of Bcl-2, cIAP1, cIAP2, and XIAP proteins, and morphological and biological changes consistent with apoptosis. The mechanism behind this synergism in MDA-MB-231 and MCF-7 cells was the result of a significantly higher ratio of Bax to Bcl-2 and the dramatic upregulation of active caspase-3, concomitant with the downregulation of XIAP. In addition to downregulation of anti-apoptotic proteins and upregulation of pro-apoptotic proteins, mTORC1 signaling was effectively hindered in the cells exposed to the drugs. Thus, induction of apoptosis by a combination of Metformin and DNC in MDA-MB-231 and MCF-7 cells is accompanied by the inhibition of anabolic pathways mediated by mTOR complex I.

The role of Insulin-like growth factor 1 (IGF-1) in promoting cancer proliferation has been identified, yet its potential role in metastasis has not been fully elucidated. Autophagy plays a pivotal, yet controversial, role in regulating cancer cell behaviour. Our previous transcriptomic analysis identified autophagy-related genes and insulin-like growth factor 1 receptor (IGF-1R) among the most differentially expressed in advanced versus early-stage colorectal cancer (CRC). In this study, we investigated the functional interplay between IGF-1R signalling and autophagy in CRC progression and metastasis, using a panel of CRC cell lines, including HCT116 cells with targeted CRISPR-Cas9 knockout of ATG5 and ATG7. Our results demonstrate that stimulation with IGF-1 enhances autophagic flux, whereas IGF-1R knockdown suppresses autophagic activity. Notably, dual inhibition of IGF-1R and autophagy led to a marked reduction in CRC cell migration and invasion. In ATG5-/- and ATG7-/- cells, IGF-1R silencing significantly downregulated mesenchymal markers Vimentin, Slug, and Snail, while upregulating the epithelial marker E-cadherin. Additionally, combined inhibition resulted in increased size and number of focal adhesion molecules, such as paxillin and zyxin. Collectively, these findings highlight the synergistic effect of IGF-1R and autophagy inhibition in suppressing EMT and metastatic potential in CRC cells, suggesting that this combinatorial approach may represent a promising therapeutic strategy for metastatic CRC.

The integration of artificial intelligence (AI) into hepatocellular carcinoma (HCC) management introduces significant ethical challenges, which are shaped by the disease's unique epidemiology and clinical complexity. In this review, we systematically analyze these challenges through the lens of the World Health Organization (WHO)'s ethical principles. To address them, we discuss practical strategies including federated learning (FL) for privacy-preserving model training, differential privacy for sensitive genomic data, interpretable AI method to enhance transparency, and adherence to standardized reporting frameworks. Furthermore, we examine global governance approaches and their implications for HCC care. Embedding ethics-by-design and promoting equity-driven AI deployment are essential to ensure that technological innovation enhances patient safety and fairness without compromising autonomy or trust.

LIM kinases (LIMK1 and LIMK2) serve as critical regulators of microtubule dynamics and mitotic progression, positioning them as promising targets for cancer therapy. However, most existing LIMK inhibitors lack specificity and cause toxic side effects due to the high sequence conservation between LIMK isoforms. Notably, no peptide-based inhibitors targeting the conserved ATP-binding pocket of LIMKs have been systematically investigated to date. To address this, an integrative structural bioinformatics approach, such as virtual screening of oligopeptide libraries, molecular dynamics simulations (MDS), and binding free energy analyses, was implemented to identify selective and less toxic peptide inhibitors. Among the top candidates, peptides with known anti-cancer, anti-inflammatory, and anti-angiogenic properties were prioritized. Interaction profiling revealed four and five tetrapeptides that closely mimicked interactions of LIMKi3 (BMS-5), a known Type-I inhibitor, with LIMK1 and LIMK2, respectively were shortlisted. Notably, MD and binding free energy analyses identified WRHF as a potent LIMK1 inhibitor with greater affinity than LIMKi3, while YYRW and WWHW exhibited superior stability and binding strength toward LIMK2. Overall, WRHF (LIMK1), YYRW, and WWHW (LIMK2) emerged as stable and high-affinity tetrapeptide inhibitors, demonstrating strong potential as selective, low-toxicity therapeutics for LIMK-targeted cancer treatment. However, in vitro and in vivo validation are essential to confirm their inhibitory efficacy and therapeutic potential, paving the way for the development of next-generation anti-cancer agents with reduced off-target effects.

Exosomal long non-coding RNAs (lncRNAs) have emerged as critical regulators in the pathogenesis, progression, and metastasis of head, neck, and thyroid cancers. These molecules, encapsulated within exosomes and released into biological fluids, mediate intercellular communication and influence various oncogenic processes including epithelial-mesenchymal transition (EMT), angiogenesis, immune evasion, and therapy resistance. Recent studies have demonstrated that specific exosomal lncRNAs are differentially expressed in cancer patients compared to healthy individuals, making them promising candidates for non-invasive biomarkers in early diagnosis, prognosis assessment, and treatment monitoring. In addition, several exosomal lncRNAs actively participate in modulating the tumor microenvironment, supporting cancer cell proliferation, migration, and metastatic potential. Therapeutically, targeting oncogenic lncRNAs or restoring tumor-suppressive ones offers new strategies for overcoming drug resistance and enhancing treatment efficacy. However, there are some areas of ambiguity and conflicting data in this topic. Thus, despite their promise, further large-scale and longitudinal studies are needed to validate their clinical utility of exosomal lncRNAs. This review summarizes the current knowledge on the biological functions and clinical applications of exosomal lncRNAs in head, neck, and thyroid cancers, highlighting their potential as biomarkers and therapeutic targets in modern oncology.

Cisplatin remains one of the most widely used chemotherapeutic agents, yet its clinical efficacy is limited by poor tumor selectivity, dose-dependent toxicity, and the development of resistance. Silibinin, a hydrophobic natural compound with antioxidant and anticancer activity, has been proposed as a complementary agent capable of enhancing therapeutic responses. In this study, poly(lactic-co-glycolic acid) (PLGA) nanoparticles were developed to encapsulate cisplatin and silibinin individually, aiming to improve their stability, sustain release, and enhance cytotoxic activity against HeLa cervical cancer cells. Nanoparticles were synthesized using a modified double-emulsion (W/O/W) solvent evaporation method and characterized for particle size, zeta potential, morphology, encapsulation efficiency, and in vitro release. Silibinin-loaded nanoparticles (F4) and cisplatin-loaded nanoparticles (F7) demonstrated optimal physicochemical properties, with encapsulation efficiencies of 81.2% and 59.4%, respectively. TEM imaging confirmed spherical morphology, and DLS analysis showed particle sizes of 144 nm (silibinin) and 164 nm (cisplatin). In vitro drug release studies performed under physiological (pH 7.4, 37 °C) and tumor-mimicking conditions (pH 5.2, 42 °C) revealed accelerated release at acidic and hyperthermic conditions. Silibinin release increased from 53.77% to 81.95%, while cisplatin release increased from 57.18% to 73.41% under tumor-like conditions. Both formulations exhibited biphasic release behavior consistent with diffusion-controlled kinetics. Cytotoxicity assessment using the MTT assay demonstrated a significant reduction in HeLa cell viability for both optimized formulations, with the combined treatment showing enhanced inhibitory effects compared to individual drugs. Overall, the findings indicate that PLGA nanoparticles can effectively enhance the controlled release and anticancer activity of cisplatin and silibinin, supporting their potential application as a more efficient and less toxic therapeutic strategy for cervical cancer.

The occurrence and advancement of skin cutaneous melanoma (SKCM) is closely associated with tumor microenvironment (TME). Evaluating the condition of immune cell infiltration is pivotal to the comprehension regarding the features of TME in SKCM. Baicalin has been demonstrated to have anti-tumor effects by regulating the TME in tumors. However, its pharmacological potential in melanoma still needs to be elucidated. In this study, through unsupervised clustering analysis and network pharmacology, 32 potential baicalin targets have been identified. The prognostic model effectively stratifies patients, and an individualized clinical prediction model can be developed from it. Single-cell analysis demonstrated the expression of prognostic targets was associated with TME and mainly accumulated in mono/macro subset. Finally, in vitro experiments demonstrated that baicalin significantly reduced the viability, proliferation, and migration capabilities of melanoma cells. Additionally, baicalin promoted pro-inflammatory polarization of macrophages under co-culture with melanoma cells and baicalin exerted relatively high biological safety. In conclusion, this study demonstrates that baicalin inhibits melanoma by modulating the TME and establishes a prognostic model with predictive potential. These findings expand the therapeutic potential of baicalin and provide novel insights for melanoma treatment strategies.

Collagen prolyl 4-hydroxylase (C-P4H) is a critical enzyme involved in collagen biosynthesis, mediating the hydroxylation of proline residues to ensure the stability of collagen and its integration into the extracellular matrix (ECM). Within the tumor microenvironment (TME), aberrant ECM remodeling, characterized by excessive collagen deposition, contributes to tumor progression, metastasis, and resistance to therapy. C-P4H operates as an α2β2 tetramer, comprising three isoenzymes distinguished by their catalytic α-subunits (P4HA1, P4HA2, P4HA3) and a common β-subunit (P4HB). Both P4HAs and P4HB are frequently overexpressed in various cancers, where they facilitate ECM remodeling, cancer cell invasion, and metastasis. Inhibitors targeting P4HAs or P4HB have demonstrated promising anti-tumor effects, highlighting its potential as a therapeutic target. This review consolidates recent advancements in the comprehension of the roles and regulatory mechanisms of C-P4H in cancer progression and evaluates the development of C-P4H targeted therapies for prospective cancer treatment.