Anticancer Response Research Articles

Antibody-targeted T cells and natural killer cells for cancer immunotherapy

BackgroundAdoptive cell cancer therapies aim to re-engineer a patient’s immune cells to mount an anti-cancer response. Chimeric antigen receptor T and natural killer cells have been engineered and proved successful in treating some cancers; however, the genetic methods for engineering are laborious, expensive, and inefficient and can cause severe toxicities when they over-proliferate.ResultsWe examined whether the cell-killing capacity of activated T and NK cells could be targeted to cancer cells by anchoring antibodies to their cell surface. Using metabolic glycoengineering to introduce azide moieties to the cellular surface, we covalently attached a dibenzocyclooctyne-modified antibody using the strain-promoted alkyne azide cycloaddition reaction, creating antibody-conjugated T and NK cells. We targeted the immune cells to tumors possessing the xenoantigen, N-glycolyl neuraminic acid GM3 ganglioside, using the 14F7hT antibody. These activated T and NK cells are “armed” with tumour-homing capabilities that specifically lyses antigen-positive cancer cells without off-target toxicities. Moreover, when exposed to target cells, 14F7hT-conjugated T cells that are not preactivated exhibit increased perforin, granzyme, CD69, and CD25 expression and specific cell killing.ConclusionsThis research shows the potential for a non-genetic method for redirecting cytotoxic immune cells as a feasible and effective approach for tumor-targeted cell immunotherapy.Graphical

Study on the Recombinant Human Interferon α1b, α2b, and Gamma Transient Expression and in Vitro Activities in Tobacco.

Interferons (IFNs) are universally acknowledged for their pivotal role in antiviral and anticancer responses. Thus, the primary aim of our study was to explore the expressions of IFN-α1b, α2b, and gamma in tobacco leaves via agrobacterium-mediated transient transformation and investigate their possible activities. Briefly, fusion with green fluorescent protein tags aided in detecting the expressed IFN proteins in the foliar tissues. The genetic constructs encoding these fusion proteins were inserted into the MagnICON plant transient expression vector, followed by transformation into the Agrobacterium strain GV3101. The transformed bacteria were then used to infiltrate tobacco leaves. After post-infiltration, protein expression was confirmed within 72 h via sodium dodecyl sulfate polyacrylamide gel electrophoresis, and the fusion proteins were subsequently purified using high-performance liquid chromatography for identification. Both the antiviral and anticancer potencies of these IFN fusion proteins were evaluated using the WISH/VSV (WISH cells/Vesicular stomatitis virus) microneutralization and MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assays, respectively. Results indicated robust expression of the targeted IFN genes in plant tissues and significant biological activities against pathogens and cancer cells. Consequently, this study substantiated the viability of producing these therapeutic proteins in plants, potentially revolutionizing the manufacture of interferons biologically.

Anaerobic bacterial metabolism responsive microspheres for bacterial embolization cancer therapy

Anaerobic bacteriolytic cancer therapy, whether delivered locally or systemically, frequently encounters challenges related to limited colonization within hypoxic pockets of central tumors and activation of innate immunity. Herein we have developed trans-arterial bacteria embolization therapy using bacterial embolic microspheres. C. novyi-NT spores loaded calcium alginate embolic microspheres demonstrated C. novyi-NT metabolites-mediated microsphere degradation, releasing vegetative C. novyi-NT bacterial in hypoxic condition. Transcatheter directed bacterial microsphere embolization therapy occludes tumor feeding vessels with infused bacterial embolic microspheres and enhances tumoral hypoxia. Notably, anaerobic bacterial metabolism responsive microsphere-bacterial embolization therapy achieved a complete tumor response with enhanced tumor-specific bacterial delivery and colonization, resulting in cancer cell killing across the entire tumor. In vivo tumor response and immunological profiling revealed that bacterial embolization uniquely enhances anti-cancer response, effectively engaging direct anaerobic bacterial oncolysis and adaptive and innate immune responses in a cooperative manner.

Therapeutic Responses to Two New SN-38 Derivatives in Colorectal Cancer Patient-Derived Xenografts and Respective 3D In Vitro Cultures.

SN-38, an active metabolite of irinotecan, exhibits toxicity to all proliferating cells, causing dose-limiting and potentially life-threatening side effects. Newly established water-soluble derivatives of SN-38, 7-ethyl-9-(N-morpholinyl)methyl-10-hydroxycamptothecin (BN-MOA) and 7-ethyl-9-(N-methylamino)methyl-10-hydroxycamptothecin (BN-NMe), exhibit a unique mechanism of spontaneous alkylation of aromatic bases in DNA and show greater in vitro activity on cancer cell lines than SN-38. The aim of this study was to compare the therapeutic responses to irinotecan, BN-MOA and BN-NMe in vivo and in vitro in 3D cultures using colorectal cancer (CRC) patient derived xenografts (PDX). Seven established PDX tissues were subcutaneously grown on the flanks of NSG or NSG-SGM3 mice and tumor diameters were measured with a caliper. Compounds were administrated intraperitoneally at 40 mg/kg every five days. 3D PDX cultures were performed on 96-well LifeGel plates and cell viability was determined with the CellTiter Glo 3D reagent. Treatment with irinotecan significantly delayed or stopped the growth of 5 out of 7 PDXs, with a greater level of inhibition from BN-MOA compared to irinotecan and BN-NMe. In vitro studies exhibited the same trends in SN-38 and BN-NMe but not in BN-MOA. The new SN-38 derivatives, BN-MOA and BN-NMe, showed enhanced therapeutic effects compared to irinotecan in CRC models. BN-MOA demonstrated superior tumor inhibition in vivo, while BN-NMe had similar in vitro activity to SN-38. These findings highlight the potential of BN-MOA for greater antitumor efficacy in vivo, with BN-NMe showing comparable effectiveness to SN-38 in vitro. Future studies should optimize growth models to better predict anticancer drug responses.

Improving tumor microenvironment assessment in chip systems through next-generation technology integration.

The tumor microenvironment (TME) comprises a diverse array of cells, both cancerous and non-cancerous, including stromal cells and immune cells. Complex interactions among these cells play a central role in driving cancer progression, impacting critical aspects such as tumor initiation, growth, invasion, response to therapy, and the development of drug resistance. While targeting the TME has emerged as a promising therapeutic strategy, there is a critical need for innovative approaches that accurately replicate its complex cellular and non-cellular interactions; the goal being to develop targeted, personalized therapies that can effectively elicit anti-cancer responses in patients. Microfluidic systems present notable advantages over conventional in vitro 2D co-culture models and in vivo animal models, as they more accurately mimic crucial features of the TME and enable precise, controlled examination of the dynamic interactions among multiple human cell types at any time point. Combining these models with next-generation technologies, such as bioprinting, single cell sequencing and real-time biosensing, is a crucial next step in the advancement of microfluidic models. This review aims to emphasize the importance of this integrated approach to further our understanding of the TME by showcasing current microfluidic model systems that integrate next-generation technologies to dissect cellular intra-tumoral interactions across different tumor types. Carefully unraveling the complexity of the TME by leveraging next generation technologies will be pivotal for developing targeted therapies that can effectively enhance robust anti-tumoral responses in patients and address the limitations of current treatment modalities.

BANDRP: a bilinear attention network for anti-cancer drug response prediction based on fingerprint and multi-omics.

Predicting anti-cancer drug response can help with personalized cancer treatment and is an important topic in modern oncology research. Although some methods have been used for anti-cancer drug response prediction, how to effectively integrate various features related to cancer cell lines, drugs, and their known responses is still affected by the redundant information of input features and the complex interactions between features. In this study, we propose a bilinear attention model, named BANDRP, based on multiple omics data of cancer cell lines and multiple molecular fingerprints of drugs to predict potential anti-cancer drug responses. Compared with existing models, BANDRP uses gene expression data to calculate pathway enrichment scores to enrich the features of cancer cell lines and can automatically learn the interactive information of cancer cell lines and drugs through bilinear attention networks. Benchmarking and independent tests demonstrate that BANDRP surpasses baseline models and exhibits robust generalization performance. Ablation experiments affirm the optimality of the current model architecture and feature selection scheme for our prediction task. Furthermore, analytical experiments and case studies on unknown anti-cancer drug response predictions underscore BANDRP's potential as a potent and reliable framework for predicting anti-cancer drug response.

Sustained antiviral response against in vitro HIV-1 infection in peripheral blood mononuclear cells from people with chronic myeloid leukemia treated with ponatinib.

HIV-1 infection cannot be cured due to long-lived viral reservoirs formed by latently infected CD4+ T cells. "Shock and Kill" strategy has been considered to eliminate the viral reservoir and achieve a functional cure but the stimulation of cytotoxic immunity is necessary. Ponatinib is a tyrosine kinase inhibitor (TKI) clinically used against chronic myeloid leukemia (CML) that has demonstrated to be effective against HIV-1 infection in vitro. Several TKIs may induce a potent cytotoxic response against cancer cells that makes possible to discontinue treatment in people with CML who present long-term deep molecular response. In this longitudinal study, we analyzed the capacity of ponatinib to induce an antiviral response against HIV-1 infection in peripheral blood mononuclear cells (PBMCs) obtained from people with CML previously treated with imatinib for a median of 10years who changed to ponatinib for 12months to boost the anticancer response before discontinuing any TKI as part of the clinical trial NCT04043676. Participants were followed-up for an additional 12months in the absence of treatment. PBMCs were obtained at different time points and then infected in vitro with HIV-1. The rate of infection was determined by quantifying the intracellular levels of p24-gag in CD4+ T cells. The levels of p24-gag+ CD4+ T-cells were lower when these cells were obtained during and after treatment with ponatinib in comparison with those obtained during treatment with imatinib. Cytotoxicity of PBMCs against HIV-infected target cells was significantly higher during treatment with ponatinib than during treatment with imatinib, and it was maintained at least 12months after discontinuation. There was a significant negative correlation between the lower levels of p24-gag+ CD4+ T-cells and the higher cytotoxicity induced by PBMCs when cells were obtained during and after treatment with ponatinib. This cytotoxic immunity was mostly based on higher levels of Natural Killer and Tγδ cells seemingly boosted by ponatinib. In conclusion, transient treatment with immunomodulators like ponatinib along with ART could be explored to boost the antiviral activity of cytotoxic cells and contribute to the elimination of HIV-1 reservoir.

Modeling different strategies towards control of lung cancer: leveraging early detection and anti-cancer cell measures

The global population has encountered significant challenges throughout history due to infectious diseases. To comprehensively study these dynamics, a novel deterministic mathematical model, TCD I L 2 Z, is developed for the early detection and treatment of lung cancer. This model incorporates I L 2 cytokine and anti-PD-L1 inhibitors, enhancing the immune system’s anticancer response within five epidemiological compartments. The TCD I L 2 Z model is analyzed qualitatively and quantitatively, emphasizing local stability given the limited data-a critical component of epidemic modeling. The model is systematically validated by examining essential elements such as equilibrium points, the reproduction number ( R 0 ), stability, and sensitivity analysis. Next-generation techniques based on R 0 that track disease transmission rates across the sub-compartments are fed into the system. At the same time, sensitivity analysis helps model how a particular parameter affects the dynamics of the system. The stability on the global level of such therapy agents retrogrades individuals with immunosuppression or treated with I L 2 and anti-PD-L1 inhibitors admiring the Lyapunov functions’ applications. NSFD scheme based on the implicit method is used to find the exact value and is compared with Euler’s method and RK4, which guarantees accuracy. Thus, the simulations were conducted in the MATLAB environment. These simulations present the general symptomatic and asymptomatic consequences of lung cancer globally when detected in the middle and early stages, and measures of anticancer cells are implemented including boosting the immune system for low immune individuals. In addition, such a result provides knowledge about real-world control dynamics with I L 2 and anti-PD-L1 inhibitors. The studies will contribute to the understanding of disease spread patterns and will provide the basis for evidence-based intervention development that will be geared toward actual outcomes.

Machine Learning-Driven Phenogrouping and Cardiorespiratory Fitness Response in Metastatic Breast Cancer.

The magnitude of cardiorespiratory fitness (CRF) impairment during anticancer treatment and CRF response to aerobic exercise training (AT) are highly variable. The aim of this ancillary analysis was to leverage machine learning approaches to identify patients at high risk of impaired CRF and poor CRF response to AT. We evaluated heterogeneity in CRF among 64 women with metastatic breast cancer randomly assigned to 12 weeks of highly structured AT (n = 33) or control (n = 31). Unsupervised hierarchical cluster analyses were used to identify representative variables from multidimensional prerandomization (baseline) data, and to categorize patients into mutually exclusive subgroups (ie, phenogroups). Logistic and linear regression evaluated the association between phenogroups and impaired CRF (ie, ≤16 mL O2·kg-1·min-1) and CRF response. Baseline CRF ranged from 10.2 to 38.8 mL O2·kg-1·min-1; CRF response ranged from -15.7 to 4.1 mL O2·kg-1·min-1. Of the n = 120 candidate baseline variables, n = 32 representative variables were identified. Patients were categorized into two phenogroups. Compared with phenogroup 1 (n = 27), phenogroup 2 (n = 37) contained a higher number of patients with none or >three lines of previous anticancer therapy for metastatic disease and had lower resting left ventricular systolic and diastolic function, cardiac output reserve, hematocrit, lymphocyte count, patient-reported outcomes, and CRF (P < .05) at baseline. Among patients allocated to AT (phenogroup 1, n = 12; 44%; phenogroup 2, n = 21; 57%), CRF response (-1.94 ± 3.80 mL O2·kg-1·min-1 v 0.70 ± 2.22 mL O2·kg-1·min-1) was blunted in phenogroup 2 compared with phenogroup 1. Phenotypic clustering identified two subgroups with unique baseline characteristics and CRF outcomes. The identification of CRF phenogroups could help improve cardiovascular risk stratification and guide investigation of targeted exercise interventions among patients with cancer.

Computational Modeling of Drug Response Identifies Mutant-Specific Constraints for Dosing panRAF and MEK Inhibitors in Melanoma.

This study explores the potential of pre-clinical in vitro cell line response data and computational modeling in identifying the optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. In a drug combination screen of 43 melanoma cell lines, we identified specific dosage landscapes of panRAF and MEK inhibitors for NRAS vs. BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma (mean Bliss score of 0.27 in NRAS vs. 0.1 in BRAF mutants). Computational modeling and follow-up molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated the in vivo translatability of in vitro dose-response maps by predicting tumor growth in xenografts with high accuracy in capturing cytostatic and cytotoxic responses. We analyzed the pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range. Overall, this work presents a framework to aid dose selection in drug combinations.

Computational modeling of drug response identifies mutant-specific constraints for dosing panRAF and MEK inhibitors in melanoma.

This study explores the potential of preclinical in vitro cell line response data and computational modeling in identifying optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. In a drug combination screen of 43 melanoma cell lines, we identified unique dosage landscapes of panRAF and MEK inhibitors for NRAS vs BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma. Computational modeling and molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated in vivo translatability of in vitro dose-response maps by accurately predicting tumor growth in xenografts. Then, we analyzed pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range.

Design and synthesis of TH19P01-Camptothecin based hybrid peptides inducing effective anticancer responses on sortilin positive cancer cells

Recently, the sortilin receptor (SORT1) was found to be preferentially over-expressed on the surface of many cancer cells, which makes SORT1 a novel anticancer target. The SORT1 binding proprietary peptide TH19P01 could achieve the SORT1-mediated cancer cell binding and subsequent internalization. Inspired by the peptide-drug conjugate (PDC) strategy, the TH19P01-camptothecin (CPT) conjugates were designed, efficiently synthesized, and evaluated for their anticancer potential in this study. The water solubility, in vitro anticancer activity, time-kill kinetics, cellular uptake, anti-migration activity, and hemolysis effects were systematically estimated. Besides, in order to monitor the release of CPT from conjugates in real-time, the CPT/Dnp-based “turn on” hybrid peptide was designed, which indicted that CPT could be sustainably released from the hybrid peptide in both human serum and cancer cellular environments. Strikingly, compared with free CPT, the water solubility, cellular uptake, and selectivity towards cancer cells of hybrid peptide LYJ-2 have all been significantly enhanced. Moreover, unlike free CPT or TH19P01, LYJ-2 exhibited selective anti-proliferative and anti-migration effects against SORT1-positive MDA-MB-231 cells. Collectively, this study not only established efficient strategies to improve the solubility and anticancer potential of chemotherapeutic agent CPT, but also provided important references for the future development of TH19P01 based PDCs targeting SORT1.

Exploring the Dark Matter of Human Proteome: The Emerging Role of Non-Canonical Open Reading Frame (ncORF) in Cancer Diagnosis, Biology, and Therapy.

Cancer develops from abnormal cell growth in the body, causing significant mortalities every year. To date, potent therapeutic approaches have been developed to eradicate tumor cells, but intolerable toxicity and drug resistance can occur in treated patients, limiting the efficiency of existing treatment strategies. Therefore, searching for novel genes critical for cancer progression and therapeutic response is urgently needed for successful cancer therapy. Recent advances in bioinformatics and proteomic techniques have allowed the identification of a novel category of peptides encoded by non-canonical open reading frames (ncORFs) from historically non-coding genomic regions. Surprisingly, many ncORFs express functional microproteins that play a vital role in human cancers. In this review, we provide a comprehensive description of different ncORF types with coding capacity and technological methods in discovering ncORFs among human genomes. We also summarize the carcinogenic role of ncORFs such as pTINCR and HOXB-AS3 in regulating hallmarks of cancer, as well as the roles of ncORFs such as HOXB-AS3 and CIP2A-BP in cancer diagnosis and prognosis. We also discuss how ncORFs such as AKT-174aa and DDUP are involved in anti-cancer drug response and the underestimated potential of ncORFs as therapeutic targets.

Immune-related encephalitis after immune checkpoint inhibitor therapy.

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment but can trigger immune-related encephalitis. We report one of the largest case series of patients with immune-related encephalitis and review of the literature. Retrospective series of patients with immune-related encephalitis and literature review. Fourteen patients with cancer treated with ICI (50% combination therapy) developed immune-related encephalitis. Diagnostic testing revealed cerebral spinal fluid (CSF) lymphocytic pleocytosis (85%) and elevated protein (69%), abnormal brain magnetic resonance imaging(MRI) (33%) or brain FDG-PET (25%), electroencephalogram (EEG) abnormalities (30%), and autoantibodies (31%). Encephalitis treatment included: corticosteroids (86%), intravenous immunoglobulin (IVIg) (36%), plasmapheresis (7%), and rituximab (29%). There were no deaths and 12 patients had significant recovery, although long-term complications were observed. All patients discontinued ICI. Longitudinal follow-up demonstrated anti-cancer response to ICI at 3 months (85%) and 6 months post-ICI initiation (77%). A literature review identified 132 patients with immune-related encephalitis. Most were treated with PD-1 inhibitors (18% combination). Common abnormalities included elevated CSF protein (84%) or pleocytosis (77%), abnormal brain MRI (65%), or autoantibodies (47%). Nearly all were treated with corticosteroids, many required additional therapy with IVIg (26%) or rituximab (12%). Most patients had clinical improvement (81%) but a minority (10%) had a clinical relapse after completing corticosteroid taper. ICIs were resumed in 7 patients (5%), with relapse in 3. Immune-related encephalitis is treatable and improves with corticosteroids in most cases but may require additional immunosuppression. Re-emergence of encephalitis is rare and does not typically result in adverse outcomes, and this should be considered in neurological immune-related adverse event management guidelines.

Malignancy progression and treatment efficacy estimation of osteosarcoma patients based on in vitro cell culture model and analysis

BackgroundOsteosarcoma (OS) usually happens in patients under 20 years old and is notorious for its low survivorship and limb loss. Personalized medicine is a viable approach to increase the efficiency of chemotherapy which is the main prognostic factor for survivorship after surgical treatment. MethodsIn this five-year prospective observational study, we collected primary cells of osteosarcoma from 15 patients, and examined the correlation between clinical characters of patients and cell properties characterized using various in vitro assays. The properties including genes expression, pro-angiogenic capability and anti-cancer drug response are characterized respectively by using RT-PCR, tube formation assay, osteogenesis assay and drug testing on 3D tumor spheroid model. ResultThe results suggest that OS patients with higher MMP9 expression levels have higher probability to develop skip metastasis (p = 0.041). The 3D tumor spheroid test based on the median lethal dose from 2D culture provides some prognostic value. Patients do not response well to methotrexate (MTX) show higher percentage of high pathology grade (p = 0.009) and lung metastasis (p = 0.044). Also, patients respond well to ifosfamide (IFO) have higher probability to achieve high tumor necrosis rate (p = 0.007). ConclusionThe association between cell properties and clinical characters of patients provided by our data can act as potential prognostic factors to help physicians to develop effective personalized chemotherapy for osteosarcoma treatments.

Gut-derived metabolite 3-methylxanthine enhances cisplatin-induced apoptosis via dopamine receptor D1 in a mouse model of ovarian cancer.

Platinum-based chemotherapy failure represents a significant challenge in the management of ovarian cancer (OC) and contributes to disease recurrence and poor prognosis. Recent studies have shed light on the involvement of the gut microbiota in modulating anticancer treatments. However, the precise underlying mechanisms, by which gut microbiota regulates the response to platinum-based therapy, remain unclear. Here, we investigated the role of gut microbiota on the anticancer response of cisplatin and its underlying mechanisms. Our results demonstrate a substantial improvement in the anticancer efficacy of cisplatin following antibiotic-induced perturbation of the gut microbiota in OC-bearing mice. 16S rRNA sequencing showed a pronounced alteration in the composition of the gut microbiome in the cecum contents following exposure to cisplatin. Through metabolomic analysis, we identified distinct metabolic profiles in the antibiotic-treated group, with a notable enrichment of the gut-derived metabolite 3-methylxanthine in antibiotic-treated mice. Next, we employed a strategy combining transcriptome analysis and chemical-protein interaction network databases. We identified metabolites that shared structural similarity with 3-methylxanthine, which interacted with genes enriched in cancer-related pathways. It is identified that 3-methylxanthinesignificantly enhances the effectiveness of cisplatin by promoting apoptosis both in vivo and in vitro. Importantly, through integrative multiomics analyses, we elucidated the mechanistic basis of this enhanced apoptosis, revealing a dopamine receptor D1-dependent pathway mediated by 3-methylxanthine. This study elucidated the mechanism by which gut-derived metabolite 3-methylxanthine mediated cisplatin-induced apoptosis. Our findings highlight the potential translational significance of 3-methylxanthine as a promising adjuvant in conjunction with cisplatin, aiming to improve treatment outcomes for OC patients.IMPORTANCEThe precise correlation between the gut microbiota and the anticancer effect of cisplatin in OC remains inadequately understood. Our investigation has revealed that manipulation of the gut microbiota via the administration of antibiotics amplifies the efficacy of cisplatin through the facilitation of apoptosis in OC-bearing mice. Metabolomic analysis has demonstrated that the cecum content from antibiotic-treated mice exhibits an increase in the levels of 3-methylxanthine, which has been shown to potentially enhance the therapeutic effectiveness of cisplatin by an integrated multiomic analysis. This enhancement appears to be attributable to the promotion of cisplatin-induced apoptosis, with 3-methylxanthine potentially exerting its influence via the dopamine receptor D1-dependent pathway. These findings significantly contribute to our comprehension of the impact of the gut microbiota on the anticancer therapy in OC. Notably, the involvement of 3-methylxanthine suggests its prospective utility as a supplementary component for augmenting treatment outcomes in patients afflicted with ovarian cancer.

CCL2 promotes EGFR-TKIs resistance in non-small cell lung cancer via the AKT-EMT pathway.

Acquired resistance to EGFR tyrosine kinase inhibitors (EGFR-TKIs) represents a primary cause of treatment failure in non-small cell lung cancer (NSCLC) patients. Chemokine (C-C motif) ligand 2 (CCL2) is recently found to play a pivotal role in determining anti-cancer treatment response. However, the role and mechanism of CCL2 in the development of EGFR-TKIs resistance have not been fully elucidated. In the present study, we focus on the function of CCL2 in the development of acquired resistance to EGFR-TKIs in NSCLC cells. Our results show that CCL2 is aberrantly upregulated in EGFR-TKIs-resistant NSCLC cells and that CCL2 overexpression significantly diminishes sensitivity to EGFR-TKIs. Conversely, CCL2 suppression by CCL2 synthesis inhibitor, bindarit, or CCL2 knockdown can reverse this resistance. CCL2 upregulation can also lead to enhanced migration and increased expressions of epithelial-mesenchymal transition (EMT) markers in EGFR-TKI-resistant NSCLC cells, which could also be rescued by CCL2 knockdown or inhibition. Furthermore, our findings suggest that CCL2-dependent EGFR-TKIs resistance involves the AKT-EMT signaling pathway; inhibition of this pathway effectively attenuates CCL2-induced cell migration and EMT marker expression. In summary, CCL2 promotes the development of acquired EGFR-TKIs resistance and EMT while activating AKT signaling in NSCLC. These insights suggest a promising avenue for the development of CCL2-targeted therapies that prevent EGFR-TKIs resistance in NSCLC.

Assessing the implications of sentinel lymph node removal in cervical cancer: an immunogenetic perspective – a SENTICOL ancillary study

BackgroundCervical cancer’s lymphatic spread primarily begins from the sentinel lymph nodes (SLNs), underlining their pivotal role in disease metastasis. However, these nodes’ immune gene expression profiles and immunoregulation mechanisms have...

Unveiling Nanoparticles: Recent Approaches in Studying the Internalization Pattern of Iron Oxide Nanoparticles in Mono- and Multicellular Biological Structures.

Nanoparticle (NP)-based solutions for oncotherapy promise an improved efficiency of the anticancer response, as well as higher comfort for the patient. The current advancements in cancer treatment based on nanotechnology exploit the ability of these systems to pass biological barriers to target the tumor cell, as well as tumor cell organelles. In particular, iron oxide NPs are being clinically employed in oncological management due to this ability. When designing an efficient anti-cancer therapy based on NPs, it is important to know and to modulate the phenomena which take place during the interaction of the NPs with the tumor cells, as well as the normal tissues. In this regard, our review is focused on highlighting different approaches to studying the internalization patterns of iron oxide NPs in simple and complex 2D and 3D in vitro cell models, as well as in living tissues, in order to investigate the functionality of an NP-based treatment.

Aptamer-Drug conjugates for a targeted and synergistic anticancer Response: Exploiting T30923-5-fluoro-2′-deoxyuridine (INT-FdU) derivatives

One of the most appealing approaches for cancer treatment is targeted therapy, which is based on the use of drugs able to target cancer cells without affecting normal ones. This strategy lets to overcome the major limitation of conventional chemotherapy, namely the lack of specificity of anticancer drugs, which often leads to severe side effects, decreasing the therapy effectiveness. Delivery of cell-killing substances to tumor cells is one-way targeted drug therapy can work. Generally, monoclonal antibodies are combined with chemotherapeutic drugs, allowing cellular uptake through the binding to their targets on the surface of cancer cells. Aptamer-drug conjugates represent a promising alternative solution to antibodies to minimize off-target effects, considering the remarkable selective binding capabilities of aptamers. In this study, to enhance the therapeutic efficacy of the antineoplastic agent 5-fluoro-2′-deoxyuridine (FdU) in various cancer cells, we focused on the development of a novel conjugate using the antiproliferative aptamer T30923 (INT) as a drug vehicle. Three derivatives composed of T30923 conjugated with a different number of FdU units were synthesized, and their structural and biological properties were thoroughly characterized, highlighting their potential for targeted and synergistic anticancer responses.