Independent Drug Action in Combination Therapy: Implications for Precision Oncology

The current landscape of aromatase inhibitors for the treatment of estrogen receptor-positive breast carcinoma

Estrogen receptor-positive (ER+) breast carcinoma represents a significant portion of breast cancer cases and is characterized by the presence of estrogen receptors that promote tumor growth upon estrogen binding. ER + breast cancer progression involves hormonal influences, interactions within the tumor microenvironment, and genetic mutations that may lead to treatment resistance. Successful therapeutic options include hormonal therapies, particularly aromatase inhibitors (AIs), which aim to block the effects of estrogen or reduce its synthesis. With higher efficacy than tamoxifen, AIs such as anastrozole, letrozole, and exemestane have become widely employed in adjuvant and first-line treatments for advanced breast cancer. AIs function by inhibiting the enzyme aromatase, which converts androgens into estrogens in the peripheral tissues. Because too much estrogen might promote tumor growth, this decrease in estrogen levels is essential for treating ER+ malignancies. To provide a comprehensive overview of AIs in the treatment of ER+ breast cancer, this study examined the pharmacokinetics, clinical uses, mechanisms of action, and problems with treatment resistance. To maximize therapeutic approaches and enhance patient outcomes in the treatment of ER breast cancer, it is imperative to understand these characteristics.

Combination Therapies in Drug Repurposing: Personalized Approaches to Combatting Leukaemia and Multiple Myeloma

Despite advances in cancer research, treating malignancies remains challenging due to issues like drug resistance, disease heterogeneity, and the limited efficacy of current therapies, particularly in relapsed or refractory cases. In recent years, several drugs originally approved for non-cancer indications have shown potential in cancer treatment, demonstrating anti-proliferative, anti-metastatic, and immunomodulatory effects. Drug repurposing has shown immense promise due to well-established safety profiles and mechanisms of action of the compounds. However, the implementation is fraught with clinical, logistical, regulatory, and ethical challenges, especially in diseases such as leukaemia and multiple myeloma. This chapter examines the treatment challenges in leukaemia and multiple myeloma, focusing on the role of drug repurposing in addressing therapeutic resistance and disease variability. It highlights the potential of personalized, tailored combination therapies, using repurposed drug components, to offer more effective, targeted, and cost-efficient treatment strategies, overcoming resistance and improving patient outcomes.

Steroid-Modulated Transcription Synergistically Forms DNA Double-Strand Breaks With Topoisomerase II Inhibitor

The synergistic effects of drug combinations have emerged as a promising approach for achieving efficient cancer treatment. Through our exploration of drug combinations, we found that medroxyprogesterone acetate (MPA), a steroid, induced a synergistic antitumor effect in combination with the topoisomerase II inhibitor etoposide (ETP). In this study, we investigated the mechanisms underlying this synergistic effect for potential clinical applications. To elucidate the relevant mechanisms, we performed a cell viability assay, cell cycle analysis, DNA repair assays, detection of DNA double-strand breaks (DSBs) and the nuclear localization of topoisomerase II (Top2), and genome-wide detection of DSBs. MPA synergistically increased ETP-induced DSBs, resulting in cell cycle arrest in the G2/M phase. Interestingly, this effect was not due to the inhibition of DSB repair but to a specific increase in the Top2-DNA covalent complex formed by ETP. A genome-wide search for DSB locations revealed that DSB formation was promoted near promoter regions, suggesting the involvement of MPA transcriptional modulation in this mechanism. We also found that various steroids promoted DSB formation when combined with ETP, strongly supporting our synergistic model. Therefore, this synergistic effect is based on an innovative mechanism that differs from conventional strategies targeting the DNA damage response and is expected to contribute toward novel therapeutic options.

PI3 expression predicts recurrence after chemotherapy with DNA-damaging drugs in gastric cancer

Despite recent advances in gastric cancer therapy, chemotherapy resistance and lack of methods for selecting combination regimens remain major problems. Organoids, which provide a culture system that more closely resembles tumor cell organization than traditional cell lines, can be established from surgical specimens with a high success rate and are widely used for drug sensitivity assays. In this study, we aimed to identify a novel biomarker for predicting multidrug resistance using gastric cancer organoids (GCOs). We evaluated 5-fluorouracil or oxaliplatin-resistant GCOs to find novel biomarkers that reflect multidrug resistance in gastric cancer. To examine the resistance mechanisms, RNA-sequencing analysis and ex vivo drug sensitivity testing were performed. The association of biomarkers with patient prognosis and chemotherapy efficacy was evaluated using three original cohorts with a total of 230 cases. The results were also validated with two independent public cohorts and single-cell RNA sequence data. Increased expression of peptidase inhibitor 3 (PI3) was detected in all 5-fluorouracil or oxaliplatin-resistant GCOs. Our findings suggest a potential association of PI3 expression with ribosome biosynthesis and RNA metabolism under organoid conditions. We also found that PI3 overexpression promoted 5-fluorouracil/oxaliplatin/cisplatin resistance but not paclitaxel resistance. Immunohistochemical evaluation of PI3 expression revealed that the PI3-positive gastric cancer group had a poorer outcome, especially in terms of time to recurrence. PI3 positivity was also an independent predictor of relapse after chemotherapy with DNA-damaging agents. PI3 promotes DNA-damaging drug resistance through multiple downstream regulations related to RNA and ribosomal metabolism. PI3 may be useful as a biomarker for the therapeutic selection of non-DNA-damaging agents. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Overcoming matrix barriers for enhanced immune infiltration using siRNA-coated metal-organic frameworks

The extracellular matrix (ECM) of solid tumor constitutes a formidable physical barrier that impedes immune cell infiltration, contributing to immunotherapy resistance. Breast cancer, particularly triple-negative breast cancer (TNBC), is characterized by a collagen-rich tumor microenvironment, which is associated with T cell exclusion and poor therapeutic outcomes. Discoidin domain receptor 2 (DDR2) and integrins, key ECM regulatory receptors on cancer cells, play pivotal role in maintaining this barrier. In this study, we developed a dual-receptor-targeted strategy using metal-organic frameworks (MOFs) to deliver DDR2-specific siRNA (siDDR2) and ITGAV-specific siRNA (siITGAV) to disrupt the ECM barrier. siDDR2 modulates immune infiltration by regulating collagen-cell interactions, while siITGAV suppresses TGF-β1 activation. The MOF@siDDR2+siITGAV complex significantly reduced collagen deposition, enhanced CD8+ T cell infiltration, and downregulated programmed cell death ligand 1 (PD-L1) expression in TNBC. Consequently, this approach markedly inhibited tumor growth. Our findings demonstrate that dual-receptor-targeted MOF-based nanocarriers (MOF@siDDR2+siITGAV) can effectively reprogram the tumor ECM to enhance immune cell access, offering a promising prospect for synergistic cancer immunotherapy. STATEMENT OF SIGNIFICANCE: A dual-receptor-targeted MOF nanocarrier is developed to improve immune accessibility in tumors. Concurrent blockade of DDR2 and ITGAV effectively decreases collagen deposition, increases CD8+ T cell infiltration, and suppresses PD-L1 expression. Modulating the mechanical properties of the extracellular matrix (ECM) to enhance immune accessibility offers an innovative strategy for cancer treatment.

Innovative applications and future perspectives of chromatography-mass spectrometry in drug research

Chromatography coupled with mass spectrometry (MS) has emerged as a cornerstone analytical technique in drug research. Over the years, advancements in chromatography-MS have significantly enhanced its capabilities, leading to improved sensitivity, specificity, and throughput. This review explores the innovative applications of chromatography-MS in drug research, particularly focusing on its role in drug absorption, distribution, metabolism, excretion (ADME), toxicity evaluation, and personalized medicine. It also addresses the future perspectives of this powerful technique, including challenges and potential solutions, and highlights how emerging trends such as high spatial resolution imaging and multimodal integration could revolutionize drug discovery and development. Through these innovations, chromatography-MS promises to contribute substantially to the development of more effective, safer, and personalized therapeutic interventions.

Methodology for Assessing Drug Efficacy: Protocol for Single and Combination Drug Screening Using HeLa Cell Cultures

This protocol outlines a detailed method for performing drug sensitivity testing (DST) on HeLa cells, focusing on both single-drug and combination-drug screening to assess cell viability. DST is integral to cancer research and functional precision medicine, providing insight into individual drug responses and facilitating the optimization of drug combinations. The protocol includes preparing and maintaining HeLa cell cultures, seeding in 96-well plates, and performing single and combination drug treatments using a low-throughput screening approach. These drug treatments aim to evaluate therapeutic effectiveness, enhance understanding of synergistic interactions, and identify optimal combinations that could minimize toxicity while overcoming resistance. Data analysis uses open-source tools, including the BREEZE pipeline and Synergy-Finder, allowing for precise analysis of cell viability and drug interactions. This protocol provides a robust, reproducible framework for DST in cancer research, applicable to other cell lines, patient samples, and various drug types/classes. The critical role of DST in improving clinical treatment strategies through precise, scalable drug response analysis is demonstrated.

Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial

Anti-angiogenic (AA) therapy is a cornerstone of metastatic clear cell renal cell carcinoma (ccRCC) treatment, but not everyone responds, and predictive biomarkers are lacking. CD31, a marker of vasculature, is insufficient, and the Angioscore, an RNA-based angiogenesis quantification method, is costly, associated with delays, difficult to standardize, and does not account for tumor heterogeneity. Here, we developed an interpretable deep learning (DL) model that predicts the Angioscore directly from ubiquitous histopathology slides yielding a visual vascular network (H&E DL Angio). H&E DL Angio achieves a strong correlation with the Angioscore across multiple cohorts (spearman correlations of 0.77 and 0.73). Using this approach, we found that angiogenesis inversely correlates with grade and stage and is associated with driver mutation status. Importantly, DL Angio expediently predicts AA response in both a real-world and IMmotion150 trial cohorts, out-performing CD31, and closely approximating the Angioscore (c-index 0.66 vs 0.67) at a fraction of the cost.

Scaling up drug combination surface prediction

Drug combinations are required to treat advanced cancers and other complex diseases. Compared with monotherapy, combination treatments can enhance efficacy and reduce toxicity by lowering the doses of single drugs-and there especially synergistic combinations are of interest. Since drug combination screening experiments are costly and time-consuming, reliable machine learning models are needed for prioritizing potential combinations for further studies. Most of the current machine learning models are based on scalar-valued approaches, which predict individual response values or synergy scores for drug combinations. We take a functional output prediction approach, in which full, continuous dose-response combination surfaces are predicted for each drug combination on the cell lines. We investigate the predictive power of the recently proposed comboKR method, which is based on a powerful input-output kernel regression technique and functional modeling of the response surface. In this work, we develop a scaled-up formulation of the comboKR, which also implements improved modeling choices: we (1) incorporate new modeling choices for the output drug combination response surfaces to the comboKR framework, and (2) propose a projected gradient descent method to solve the challenging pre-image problem that is traditionally solved with simple candidate set approaches. We provide thorough experimental analysis of comboKR 2.0 with three real-word datasets within various challenging experimental settings, including cases where drugs or cell lines have not been encountered in the training data. Our comparison with synergy score prediction methods further highlights the relevance of dose-response prediction approaches, instead of relying on simple scoring methods.

Role of liposomes in chemoimmunotherapy of breast cancer

In the dynamic arena of cancer therapeutics, chemoimmunotherapy has shown tremendous promise, especially for aggressive forms of breast cancer like triple-negative breast cancer (TNBC). This review delves into the significant role of liposomes in enhancing the effectiveness of chemoimmunotherapy by leveraging breast cancer-specific mechanisms such as the induction of immunogenic cell death (ICD), reprogramming the tumour microenvironment (TME), and enabling sequential drug release. We examine innovative dual-targeting liposomes that capitalise on tumour heterogeneity, as well as pH-sensitive formulations that offer improved control over drug delivery. Unlike prior analyses, this review directly links advancements in preclinical research-such as PAMAM dendrimer-based nanoplatforms and RGD-decorated liposomes-to clinical trial results, highlighting their potential to revolutionise TNBC treatment strategies. Additionally, we address ongoing challenges related to scalability, toxicity, and regulatory compliance, and propose future directions for personalised, immune-focused nanomedicine. This work not only synthesises the latest research but also offers a framework for translating liposomal chemoimmunotherapy from laboratory research to clinical practice.

Enhancer reprogramming: critical roles in cancer and promising therapeutic strategies

Transcriptional dysregulation is a hallmark of cancer initiation and progression, driven by genetic and epigenetic alterations. Enhancer reprogramming has emerged as a pivotal driver of carcinogenesis, with cancer cells often relying on aberrant transcriptional programs. The advent of high-throughput sequencing technologies has provided critical insights into enhancer reprogramming events and their role in malignancy. While targeting enhancers presents a promising therapeutic strategy, significant challenges remain. These include the off-target effects of enhancer-targeting technologies, the complexity and redundancy of enhancer networks, and the dynamic nature of enhancer reprogramming, which may contribute to therapeutic resistance. This review comprehensively encapsulates the structural attributes of enhancers, delineates the mechanisms underlying their dysregulation in malignant transformation, and evaluates the therapeutic opportunities and limitations associated with targeting enhancers in cancer.

Formononetin: a review of its source, pharmacology, drug combination, toxicity, derivatives, and drug delivery systems

Formononetin (FMN) is a common natural metabolite that can be extracted and isolated from some common botanical drugs. In recent years, FMN has garnered increasing attention due to its beneficial biological activities. In this paper, we systematically summarize the sources of FMN and provide a comprehensive review of its pharmacological activities and molecular mechanisms, co-administration, toxicity, derivatives, and drug delivery systems in the last 5 years. The study results found that FMN has a wide range of pharmacological activities in neurological disorders, organ damage and cancer, showing great potential for clinical application and broad prospects. Researchers are exploring various types of delivery systems, including nanoparticle carriers, ligand modifications and polymer microspheres. These advanced delivery systems can enhance the stability of FMN, prolong its release time in vivo, and improve targeting, thereby optimizing its therapeutic efficacy and reducing side effects, and greatly improving its bioavailability. In conclusion, FMN is a natural metabolite with considerable research value, and its diverse biological activities make it a promising candidate for drug development and medical research.

Discoidin domain receptor inhibitor DDR1-IN-1 induces autophagy and necroptotic cell death in malignant peripheral nerve sheath tumor

Malignant peripheral nerve sheath tumor (MPNST) is a soft tissue sarcoma commonly associated with the tumor-predisposition disorder neurofibromatosis 1. The extracellular matrix collagens contribute to many fibrotic tumors; however, the role of collagen signaling in MPNST was unclear. This study investigated the effects of blocking the interaction between collagens and their receptors in MPNST. We first analyzed the expressions of collagen family proteins in MPNSTs and found an overall increase compared to neurofibroma. Treatment of DDR1-IN-1, a small molecule inhibitor for the collagen receptor discoidin domain receptor, induced a robust MPNST cell death, highlighting the dependence of MPNST survival on collagen signaling. DDR1-IN-1 induced MPNST cell death by activating autophagy and necroptosis signaling. Treatment of necroptosis inhibitors necrostatin-1 or necrosulfonamide reduced the numbers of DDR1-IN-1-induced necrotic cells and autolysosomes, suggesting that the autophagic process depends on necroptosis activation. Combinations of DDR1-IN-1 with other anti-MPNST agents revealed synergistic activities against MPNST. In summary, this study discovered a critical MPNST death signaling induced by the small molecule DDR1-IN-1, which might shed light on future MPNST therapeutic strategies.

Resistance to immunotherapy in non-small cell lung cancer: Unraveling causes, developing effective strategies, and exploring potential breakthroughs

Over the last two decades, advancements in deciphering the intricate interactions between oncology and immunity have fueled a meteoric rise in immunotherapy for non-small cell lung cancer, typified by an explosive growth of immune checkpoint inhibitors. However, resistance to immunotherapy remains inevitable. Herein we unravel the labyrinthine mechanisms of resistance to immunotherapy, characterized by their involvement of nearly all types of cells within the body, beyond the extrinsic cancer cells, and importantly, such cells are not only (inhibitory or excitatory, or both) signal recipients but also producers, acting in a context-dependent manner. At the molecular level, these mechanisms underlie genetic and epigenetic aberrations, which are regulated by or regulate various protein kinases, growth factors, and cytokines with inherently dynamic and spatially heterogeneous properties. Additionally, macroscopic factors such as nutrition, comorbidities, and the microbiome within and around organs or tumor cells are involved. Therefore, developing therapeutic strategies combined with distinct action informed by preclinical, clinical, and real-world evidence, such as radiotherapy, chemotherapy, targeted therapy, antibody-drug conjugates, oncolytic viruses, and cell-based therapies, may stand as a judicious reality, although the ideality is to overcome resistance point-by-point through a novel drug. Notably, we highlight a realignment of treatment aims, moving the primary focus from eliminating cancer cells -- such as through chemotherapy and radiotherapy -- to promoting immune modulation and underscore the value of regulating various components within the host macro- or micro-environment, as their effects, even if seemingly minimal, can cumulatively contribute to visible clinical benefit when applied in combination with ICIs. Lastly, this review also emphasizes the current hurdles scattered throughout preclinical and clinical studies, and explores evolving directions in the landscape of immunotherapy for NSCLC.

Advancements in cellular immunotherapy: overcoming resistance in lung and colorectal cancer

Immunotherapy has revolutionized cancer treatment, offering hope for patients with otherwise treatment-resistant tumors. Among the most promising approaches are cellular therapies, particularly chimeric antigen receptor T-cell (CAR-T) therapy, which has shown remarkable success in hematologic malignancies. However, the application of these therapies to solid tumors, such as lung and colorectal cancers, has faced significant challenges. Tumor resistance mechanisms-ranging from immune evasion, antigen loss, and immune checkpoint upregulation, to tumor microenvironment immunosuppression-remain major obstacles. This mini-review highlights the latest advancements in tumor immunotherapy, with a focus on cellular therapies, and addresses the resistance mechanisms that hinder their effectiveness in lung and colorectal cancers. We examine the evolution of CAR-T cell therapy, as well as the potential of engineered natural killer (NK) cells and macrophages in solid tumor treatment. The review also explores cutting-edge strategies aimed at overcoming resistance, including combination therapies, gene editing technologies, and nanotechnology for targeted drug delivery. By discussing the molecular, cellular, and microenvironmental factors contributing to resistance, we aim to provide a comprehensive overview of how these challenges can be overcome, paving the way for more effective, personalized immunotherapies in lung and colorectal cancer treatment.

Roflumilast attenuates doxorubicin and cyclophosphamide combination-induced chemobrain in rats through modulation of NLRP3/ASC/caspase-1/GSDMD axis

AIM

The aim of this study is to investigate the neuroprotective effect of roflumilast, a phosphodiesterase-4 (PDE-4) inhibitor on cognitive impairment induced by doxorubicin (DOX)/cyclophosphamide (CP) combination therapy and to elucidate its modulatory effect on the pyroptosis pathway.

MATERIALS AND METHODS

Rats were allocated into five groups: a control group, a DOX/CP-intoxicated group, two groups receiving DOX/CP plus low-dose (0.5 mg/kg/day) or high-dose (1 mg/kg/day) roflumilast, and a roflumilast-only group. Behavioral assessments and brain tissue analyses were conducted, including histopathological staining and the measurement of inflammatory and oxidative stress markers.

FINDINGS

DOX/CP treatment resulted in cognitive impairment, abnormal brain histology. It significantly elevated the levels of tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and malondialdehyde (MDA). Concurrently, superoxide dismutase (SOD) activity was reduced. Pyroptosis-associated markers, including nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3), apoptosis-associated speck-like protein (ASC), caspase-1, gasdermin-D (GSDMD), and interleukin-18 (IL-18) were upregulated. Apoptotic marker caspase-3 also exhibited increased expression. Conversely, administration of roflumilast (1 mg/kg/day) for four weeks ameliorated these pathological changes. Roflumilast improved cognitive function, reduced oxidative stress, and modulated inflammatory signaling. Additionally, it suppressed pyroptotic and apoptotic pathways within hippocampal tissue.

SIGNIFICANCE

These results suggest that roflumilast exerts neuroprotective effects against chemotherapy-induced cognitive dysfunction and neurodegeneration through inhibition of the NLRP3/ASC/caspase-1/GSDMD pyroptosis pathway.

Napabucasin deactivates STAT3 and promotes mitoxantrone-mediated cGAS-STING activation for hepatocellular carcinoma chemo-immunotherapy

The immune resistance of tumor microenvironment (TME) causes immune checkpoint blockade therapy inefficient to hepatocellular carcinoma (HCC). Emerging strategies of using chemotherapy regimens to reverse the immune resistance provide the promise for promoting the efficiency of immune checkpoint inhibitors. The induction of cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) in tumor cells evokes the adaptive immunity and remodels the immunosuppressive TME. In this study, we report that mitoxantrone (MIT, a chemotherapeutic drug) activates the cGAS-STING signaling pathway of HCC cells. We provide an approach to augment the efficacy of MIT using a signal transducer and activator of transcription 3 (STAT3) inhibitor called napabucasin (NAP). We prepare an aminoethyl anisamide (AEAA)-targeted polyethylene glycol (PEG)-modified poly (lactic-co-glycolic acid) (PLGA)-based nanocarrier for co-delivery of MIT and NAP. The resultant co-nanoformulation can elicit the cGAS-STING-based immune responses to reshape the immunoresistant TME in the mice orthotopically grafted with HCC. Consequently, the resultant co-nanoformulation can promote anti-PD-1 antibody for suppressing HCC development, generating long-term survival, and inhibiting tumor recurrence. This study reveals the potential of MIT to activate the cGAS-STING signaling pathway, and confirms the feasibility of nano co-delivery for MIT and NAP on achieving HCC chemo-immunotherapy.

Coupling of response biomarkers between tumor and peripheral blood in patients undergoing chemoimmunotherapy

Platinum-based chemotherapy in combination with anti-PD-L1 antibodies has shown promising results in mesothelioma. However, the immunological mechanisms underlying its efficacy are not well understood and there are no predictive biomarkers to guide treatment decisions. Here, we combine time course RNA sequencing (RNA-seq) of peripheral blood mononuclear cells with pre-treatment tumor transcriptome data from the single-arm, phase 2 DREAM trial (N = 54). Single-cell RNA-seq and T cell receptor sequencing (TCR-seq) reveal that CD8+ T effector memory (TEM) cells with stem-like properties are more abundant in peripheral blood of responders and that this population expands upon treatment. These peripheral blood changes are linked to the transcriptional state of the tumor microenvironment. Combining information from both compartments, rather than individually, is most predictive of response. Our study highlights complex interactions between the tumor and immune cells in peripheral blood during objective tumor responses to chemoimmunotherapy. This trial is registered with the Australian New Zealand Clinical Trials Registry, number ACTRN12616001170415.

Anti-correlation of KLRG1 and PD-1 expression in human tumor CD8 T cells

Recently, combination checkpoint therapy of cancer has been recognized as producing additive as opposed to synergistic benefit due in part to positively correlated effects. The potential for uncorrelated or negatively correlated therapies to produce true synergistic benefits has been noted. Whereas the inhibitory receptors PD-1, CTLA-4, TIM-3, LAG-3, and TIGIT have been collectively characterized as exhaustion receptors, another inhibitory receptor KLRG1 was historically characterized as a senescent receptor and received relatively little attention as a potential checkpoint inhibitor target. The anti-tumor effects of KLRG1 blockade has relatively recently been demonstrated in preclinical in vivo studies. Here, expression of the inhibitory receptors PD-1, CTLA-4, TIM-3, LAG-3, TIGIT, and KLRG1 was studied in publicly available gene expression datasets. Bulk RNA microarray and RNAseq, and single cell RNAseq data from healthy blood and tumor tissue samples were analyzed for Pearson correlation. CD8 T cell differentiation of memory T cells from the TEM to TEMRA states is characterized by PD-1/KLRG1 anti-correlation, with decreased PD-1 expression but increased KLRG1 expression. Single cell RNAseq analysis of tumor infiltrating CD8 T cells shows positive correlation of CTLA-4, TIM-3, LAG-3, TIGIT, GITR, 4-1BB, and OX40 with PD-1 but negative correlation of KLRG1 with PD-1. The anti-correlation of PD-1 and KLRG1 expression in human tumor infiltrating CD8 T cells suggests the potential for combination therapy supra-additive benefits of anti-PD-1 and anti-KLRG1 therapies.

Evolutionary rescue model informs strategies for driving cancer cell populations to extinction

Cancers exhibit a remarkable ability to develop resistance to a range of treatments, often resulting in relapse following first-line therapies and significantly worse outcomes for subsequent treatments. While our understanding of the mechanisms and dynamics of the emergence of resistance during cancer therapy continues to advance, questions remain about how to minimize the probability that resistance will evolve, thereby improving long-term patient outcomes. Here, we present an evolutionary simulation model of a clonal population of cells that can acquire resistance mutations to one or more treatments. We leverage this model to examine the efficacy of a two-strike "extinction therapy" protocol, in which two treatments are applied sequentially to first contract the population to a vulnerable state and then push it to extinction, and compare it to a combination therapy protocol. We investigate how factors such as the timing of the switch between the two strikes, the rate of emergence of resistant mutations, the doses of the applied drugs, the presence of cross-resistance, and whether resistance is a binary or a quantitative trait affect the outcome. Our results show that the timing of switching to the second strike has a marked effect on the likelihood of driving the cancer to extinction, and that extinction therapy outperforms combination therapy when cross-resistance is present. We conduct an in silico trial that reveals when and why a second strike will succeed or fail. Finally, we demonstrate that our conclusions hold whether we model resistance as a binary trait or as a quantitative, multi-locus trait.

Integrated multi-omics demonstrates enhanced antitumor efficacy of donafenib combined with FADS2 inhibition in hepatocellular carcinoma

Pharmacotherapy is crucial for advanced hepatocellular carcinoma (HCC). The multi-kinase inhibitor donafenib offers superior survival benefits over sorafenib. Donafenib has first-line status, but there is limited research for combination therapies with this anticancer agent. This study aimed to delineate donafenib's antitumor effects, including transcriptomics and proteomics to characterize gene expression changes in donafenib-treated HCC cell lines. In vitro and in vivo tumorigenicity studies were conducted to evaluate the combined antitumor effects of donafenib. Proteomic and transcriptomic analyses identified that donafenib downregulated fatty acid desaturase 2 (FADS2) at the protein and mRNA levels. In vitro and in vivo assays revealed an inhibitory effect of FADS2 blockade on HCC cell malignancy. The combination of donafenib and the FADS2 inhibitor sc-26,196 produced synergistic antitumor action, enhancing therapeutic efficacy in HCC cell lines and xenografted tumors in nude mice. These findings highlight the potential of FADS2 as a biomarker for HCC and show a promising combinatorial therapy for its treatment. Thus, we provide a theoretical basis for translating laboratory research into clinical applications.

Subsequent Indications in Oncology Drugs: Pathways, Timelines, and the Inflation Reduction Act

INTRODUCTION

Recent research has raised questions about potential unintended consequences of the Inflation Reduction Act's Drug Price Negotiation Program (DPNP), suggesting that the timelines introduced by the law may reduce manufacturer incentives to invest in post-approval research towards additional indications. Given the role of multiple indications in expanding treatment options in patients with cancer, IRA-related changes to development incentives are especially relevant in oncology. This study aimed to describe heterogeneous drug-level trajectories and timelines of subsequent indications in a cohort of recently approved, multi-indication oncology drugs, including overall, across subgroups of drugs characterized by the timing and pace of additional indications, and by drug type (i.e., small molecule vs. biologic).

METHODS

This cross-sectional study evaluated oncology drugs first approved by the FDA from 2008 to 2018 and later approved for one or more additional indications. Numbers, types, and approval timelines of subsequent indications were recorded at the drug level, with drugs grouped by quartile based on the pacing of post-approval development (i.e., "rapid pace" to "measured pace").

RESULTS

Multi-indication oncology drugs (N = 56/86, 65.1%) had one or more subsequent indication approved in a new: cancer type (60.7%), line of treatment (50.0%), combination (41.1%), mutation (32.1%), or stage (28.6%). The median time between FDA approvals for indications increased from 0.6 years (IQR: 0.48, 0.74) in the "rapid pace" group to 1.6 years (IQR: 1.32, 1.66), 2.4 years (IQR: 2.29, 2.61), and 4.9 years (IQR: 3.43, 6.23) in the "moderate," "measured-moderate," and "measured" pace groups, respectively. Drugs in the "rapid pace" group often received their first subsequent indication approval within 9 months of initial approval (median: 0.7 years; IQR: 0.54, 1.59), whereas the "measured pace" group took a median of 5.7 years (IQR: 3.43, 6.98). Across all multi-indication drugs, the median time to the most recent approval for a subsequent indication was 5.5 years (IQR: 3.18, 7.95). One quarter (25%) of drugs were approved for their most recent subsequent indication after the time at which they would be DPNP-eligible.

CONCLUSION

Approval histories of new oncology drugs demonstrate the role of post-approval indications in expanding treatment options towards new cancer types, stages, lines, combinations, and mutations. Heterogeneous clinical development pathways provide insights into potential unintended consequences of IRA-related changes surrounding post-approval research and development.

How the Versatile Self-Assembly in Drug Delivery System to Afford Multimodal Cancer Therapy?

The rapid development of self-assembly technology during the past few decades has effectively addressed plenty of the issues associated with carrier-based drug delivery systems, such as low loading efficiency, complex fabrication processes, and inherent toxicity of carriers. The integration of nanoscale delivery systems with self-assembly techniques has enabled efficient and targeted self-administration of drugs, enhanced bioavailability, prolonged circulation time, and controllable drug release. Concurrently, the limitations of single-mode cancer treatment, including low bioavailability, poor therapeutic outcomes, and significant side effects, have highlighted the urgent need for multimodal combined antitumor therapies. Set against the backdrop of multimodal cancer therapy, this review summarizes the research progress and applications of a large number of self-assembled drug delivery platforms, including natural small molecule self-assembled, carrier-free self-assembled, amphiphilic polymer-based self-assembled, peptide-based self-assembled, and metal-based self-assembled nano drug delivery systems. This review particularly analyzes the latest advances in the application of self-assembled nano drug delivery platforms in combined antitumor therapies mediated by chemotherapy, phototherapy, radiotherapy, sonodynamic therapy, and immunotherapy, providing innovative research insights for further optimization and expansion of self-assembled nano drug delivery systems in the clinical translation and development of antitumor combined therapy.

SDDSynergy: Learning Important Molecular Substructures for Explainable Anticancer Drug Synergy Prediction

Drug combination therapies are well-established strategies for the treatment of cancer with low toxicity and fewer adverse effects. Computational drug synergy prediction approaches can accelerate the discovery of novel combination therapies, but the existing methods do not explicitly consider the key role of important substructures in producing synergistic effects. To this end, we propose a significant substructure-aware anticancer drug synergy prediction method, named SDDSynergy, to adaptively identify critical functional groups in drug synergy. SDDSynergy splits the task of predicting drug synergy into predicting the effect of individual substructures on cancer cell lines and highlights the impact of important substructures through a novel drug-cell line attention mechanism. And a substructure pair attention mechanism is incorporated to capture the information on internal substructure pairs interaction in drug combinations, which aids in predicting synergy. The substructures of different sizes and shapes are directly obtained from the molecular graph of the drugs by multilayer substructure information passing networks. Extensive experiments on three real-world data sets demonstrate that SDDSynergy outperforms other state-of-the-art methods. We also verify that many of the novel drug combinations predicted by SDDSynergy are supported by previous studies or clinical trials through an in-depth literature survey.

Cancer Cell's Achilles Heels: Considerations for Design of Anti-Cancer Drug Combinations

Loss of function screens using shRNA (short hairpin RNA) and CRISPR (clustered regularly interspaced short palindromic repeats) are routinely used to identify genes that modulate responses of tumor cells to anti-cancer drugs. Here, by integrating GSEA (Gene Set Enrichment Analysis) and CMAP (Connectivity Map) analyses of multiple published shRNA screens, we identified a core set of pathways that affect responses to multiple drugs with diverse mechanisms of action. This suggests that these pathways represent "weak points" or "Achilles heels", whose mild disturbance should make cancer cells vulnerable to a variety of treatments. These "weak points" include proteasome, protein synthesis, RNA splicing, RNA synthesis, cell cycle, Akt-mTOR, and tight junction-related pathways. Therefore, inhibitors of these pathways are expected to sensitize cancer cells to a variety of drugs. This hypothesis was tested by analyzing the diversity of drugs that synergize with FDA-approved inhibitors of the proteasome, RNA synthesis, and Akt-mTOR pathways. Indeed, the quantitative evaluation indicates that inhibitors of any of these signaling pathways can synergize with a more diverse set of pharmaceuticals, compared to compounds inhibiting targets distinct from the "weak points" pathways. Our findings described here imply that inhibitors of the "weak points" pathways should be considered as primary candidates in a search for synergistic drug combinations.

Probabilistic analysis of tumor growth inhibition models to Support trial design

A large enough sample size of patients is required to statistically show that one treatment is better than another. However, too large a sample size is expensive and can also result in findings that are statistically significant, but not clinically relevant. How sample sizes should be chosen is a well-studied problem in classical statistics and analytical expressions can be derived from the appropriate test statistic. However, these expressions require information regarding the efficacy of the treatment, which may not be available, particularly for newly developed drugs. Tumor growth inhibition (TGI) models are frequently used to quantify the efficacy of newly developed anticancer drugs. In these models, the tumor growth dynamics are commonly described by a set of ordinary differential equations containing parameters that must be estimated using experimental data. One widely used endpoint in clinical trials is the proportion of patients in different response categories determined using the Response Evaluation Criteria In Solid Tumors (RECIST) framework. From the TGI model, we derive analytical expressions for the probability of patient response to combination therapy. The probabilistic expressions are used together with classical statistics to derive a parametric model for the sample size required to achieve a certain significance level and test power when comparing two treatments. Furthermore, the probabilistic expressions are used to generalize the Tumor Static Exposure concept to be more suitable for predicting clinical response. The derivatives of the probabilistic expressions are used to derive two additional expressions characterizing the exposure and its sensitivity. Finally, our results are illustrated using parameters obtained from calibrating the model to preclinical data.

Doxorubicin and 4-nitrochalcone loaded in beeswax-based nanostructured lipid carriers: In vitro antitumoral screening and evaluation of synergistic effect on HepG-2 cells

Cancer is the second most deadly disease worldwide, and the most traditional approaches such as chemotherapy still face limitations associated to drug dosage and off-target side effects. To address these issues, we propose the simultaneous administration of 4-Nitrochalcone (4NC) and Doxorubicin (DOX) using beeswax based nanostructured lipid carriers (NLCs). The co-encapsulation of 4NC and DOX in the beeswax based NLCs was performed using the water/oil/water double emulsion technique in association with the melt dispersion approach. The system composed by semi-spherical NLCs with an average diameter around 200 nm and narrow size distribution, displayed colloidal stability before and after redispersion, keeping the zeta potential below -30 mV. The antitumor activity of the nanoparticles was screened on different tumor cell lines, and the induced cellular death and internal ROS levels were analyzed on hepatocarcinoma cells, which were found to be more affected by the combination of 4NC and DOX. The results indicated that 4NC + DOX-NCLs could promote cytotoxicity and oxidative damage-mediated apoptosis in a HepG-2 cell line.

Nanomedicine based on chemotherapy-induced immunogenic death combined with immunotherapy to enhance antitumor immunity

Introduction

Chemo-immunotherapy based on inducing tumor immunogenic cell death (ICD)with chemotherapy drugs has filled the gaps between traditional chemotherapy and immunotherapy. It is verified that paclitaxel (PTX) can induce breast tumor ICD. From this basis, a kind of nanoparticle that can efficiently deliver different drug components simultaneously is constructed. The purpose of this study is for the sake of exploring the scheme of chemotherapy-induced ICD combined with other immunotherapy to enhance tumor immunogenicity and inhibit the growth, metastasis, and recurrence of breast tumors, so as to provide a research basis for solving the tough problem of breast cancer treatment.

Methods

Nanomedicine loaded with PTX, small interference RNA that suppresses CD47 expression (CD47siRNA, siCD47), and immunomodulator R848 were prepared by the double emulsification method. The hydrodynamic diameter and zeta potential of NP/PTX/siCD47/R848 were characterized. Established the tumor-bearing mice model of mouse breast cancer cell line (4T1) in situ and observed the effect of intravenous injection of NP/PTX/siCD47/R848 on the growth of 4T1 tumor in situ. Flow cytometry was used to detect the effect of drugs on tumor immune cells.

Results

NP/PTX/siCD47/R848 nano-drug with tumor therapeutic potential were successfully prepared by double emulsification method, with particle size of 121.5 ± 4.5 nm and surface potential of 36.1 ± 2.5 mV. The calreticulin on the surface of cell membrane and extracellular ATP or HMGB1 of 4T1 cells increased through treatment with NPs. NP/PTX-treated tumor cells could cause activation of BMDCs and BMDMs. After intravenous injection, NP/PTX could quickly reach the tumor site and accumulate for 24 h. The weight and volume of tumor in situ in the breast cancer model mice injected with nanomedicine through the tail vein were significantly lower than those in the PBS group. The ratio of CD8+/CD4+ T cells in the tumor microenvironment and the percentage of dendritic cells in peripheral blood increased significantly in breast cancer model mice injected with nano-drugs through the tail vein.

Discussion

Briefly, the chemotherapeutic drug paclitaxel can induce breast cancer to induce ICD. The nanomedicine which can deliver PTX, CD47siRNA, and R848 at the same time was prepared by double emulsification. NP/PTX/siCD47/R848 nano-drug can be enriched in the tumor site. The experiment of 4T1 cell tumor-bearing mice shows that the nano-drug can enhance tumor immunogenicity and inhibit breast tumor growth, which provides a new scheme for breast cancer treatment. (Graphical abstract).

Analyzing the distribution of progression-free survival for combination therapies: A study of model-based translational predictive methods in oncology

Progression-free survival (PFS) is an important clinical metric in oncology and is typically illustrated and evaluated using a survival function. The survival function is often estimated post-hoc using the Kaplan-Meier estimator but more sophisticated techniques, such as population modeling using the nonlinear mixed-effects framework, also exist and are used for predictions. However, depending on the choice of population model PFS will follow different distributions both quantitatively and qualitatively. Hence the choice of model will also affect the predictions of the survival curves. In this paper, we analyze the distribution of PFS for a frequently used tumor growth inhibition model with and without drug-resistance and highlight the translational implications of this. Moreover, we explore and compare how the PFS distribution for combination therapy differs under the hypotheses of additive and independent-drug action. Furthermore, we calibrate the model to preclinical data and use a previously calibrated clinical model to show that our analytical conclusions are applicable to real-world setting. Finally, we demonstrate that independent-drug action can effectively describe the tumor dynamics of patient-derived xenografts (PDXs) given certain drug combinations.

Lessons learned from 20 years of preclinical testing in pediatric cancers

Programs for preclinical testing of targeted cancer agents in murine models of childhood cancers have been supported by the National Cancer Institute (NCI) since 2004. These programs were established to work collaboratively with industry partners to address the paucity of targeted agents for pediatric cancers compared with the large number of agents developed and approved for malignancies primarily affecting adults. The distinctive biology of pediatric cancers and the relatively small numbers of pediatric cancer patients are major challenges for pediatric oncology drug development. These factors are exacerbated by the division of cancers into multiple subtypes that are further sub-classified by their genomic properties. The imbalance between the large number of candidate agents and small patient populations requires careful prioritization of agents developed for adult cancers for clinical evaluation in children with cancer. The NCI-supported preclinical pediatric programs have published positive and negative results of efficacy testing for over 100 agents to aid the pediatric research community in identifying the most promising candidates to move forward for clinical testing in pediatric oncology. Here, we review and summarize lessons learned from two decades of experience with the design and execution of preclinical trials of antineoplastic agents in murine models of childhood cancers.

Resistance Management for Cancer: Lessons from Farmers

One of the main reasons we have not been able to cure cancers is that treatments select for drug-resistant cells. Pest managers face similar challenges with pesticides selecting for pesticide-resistant insects, resulting in similar mechanisms of resistance. Pest managers have developed 10 principles that could be translated to controlling cancers: (i) prevent onset, (ii) monitor continuously, (iii) identify thresholds below which there will be no intervention, (iv) change interventions in response to burden, (v) preferentially select nonchemical control methods, (vi) use target-specific drugs, (vii) use the lowest effective dose, (viii) reduce cross-resistance, (ix) evaluate success based on long-term management, and (x) forecast growth and response. These principles are general to all cancers and cancer drugs and so could be employed broadly to improve oncology. Here, we review the parallel difficulties in controlling drug resistance in pests and cancer cells. We show how the principles of resistance management in pests might be applied to cancer. Integrated pest management inspired the development of adaptive therapy in oncology to increase progression-free survival and quality of life in patients with cancers where cures are unlikely. These pest management principles have the potential to inform clinical trial design.

A Brief Chronicle of Antibody Research and Technological Advances

This review briefly traces the historical development of antibody research and related technologies. The path from early perceptions of immunity to the emergence of modern immunotherapy has been marked by pivotal discoveries and technological advances. Early insights into immunity led to the development of vaccination and serotherapy. The elucidation of antibody structure and function paved the way for monoclonal antibody technology and its application in diagnosis and therapy. Breakthroughs in genetic engineering have enabled the production of humanized antibodies and the advances in Fc engineering, thereby increasing therapeutic efficacy. The discovery of immune checkpoints and cytokines revolutionized the treatment of cancer and autoimmune diseases. The field continues to evolve rapidly with the advent of antibody-drug conjugates, bispecific antibodies, and CAR T-cell therapies. As we face global health challenges, antibody research remains at the forefront of medical innovation and offers promising solutions for the future.

Synergism of salvianolic acid B and ginsenoside Rg1 magnifies the therapeutic potency against ischemic stroke

Even though considerable progress has been made to reduce insult, ischemic stroke is still a significant cause of mortality and morbidity in the world, and new therapeutic strategies are urgently needed. In the present study, the magnesium salt of salvianolic acid B (SalB) and ginsenoside Rg1 (Rg1) combination as a multicomponent strategy against stroke was evaluated. The synergistic effect of Sa1B and Rg1 was evaluated by Bliss independence analysis on the middle cerebral artery occlusion model. The infarct volume, neuroethology, cerebral structure, and neurocyte number were evaluated by 3,5-triphenyltetrazolium chloride staining, Longa score, Garcia score, hematoxylin-eosin staining, and Nissl staining, respectively. Metabolomics was used to search for potential biomarkers and explore the mechanism of Sa1B/Rg1. First, the superior effects of SalB/Rg1 than SalB or Rg1 at the same dose were evaluated. Compared with SalB ( P  < 0.001) or Rg1 ( P  < 0.01), SalB/Rg1 significantly decreased infarct volume through 3,5-triphenyltetrazolium chloride staining and protected the structural integrity of cortex and striatum. The superior effect of SalB/Rg1 on neurological behavior was also detected compared with SalB or Rg1 significantly. Accompanying behavioral improvement, a considerable increase of SalB/Rg1 on neurons detected by Nissl staining was found on the cortex compared with SalB ( P  < 0.05) or Rg1 ( P  < 0.01). Second, the synergistic effect between SalB and Rg1 was strictly verified by Bliss independence analysis ( P  < 0.01) based on infarct volume. Finally, alleviation of cerebral metabolic disorders may be the possible mechanism of SalB/Rg1. Our study provided a multicomponent strategy against ischemic stroke, with not only dose reduction but also improved efficacy relative to single agents.

Matrix metalloproteinase 2-responsive dual-drug-loaded self-assembling peptides suppress tumor growth and enhance breast cancer therapy

Conventional chemotherapeutic agents are limited by their lack of targeting and penetration and their short retention time, and chemotherapy might induce an immune suppressive environment. Peptide self-assembly can result in a specific morphology, and the resulting morphological changes are stimuli responsive to the external environment, which is important for drug permeation and retention of encapsulated chemotherapeutic agents. In this study, a polypeptide (Pep1) containing the peptide sequences PLGLAG and RGD that is responsive to matrix metalloproteinase 2 (MMP-2) was successfully developed. Pep1 underwent a morphological transformation from a spherical structure to aggregates with a high aspect ratio in response to MMP-2 induction. This drug delivery system (DI/Pep1) can transport doxorubicin (DOX) and indomethacin (IND) simultaneously to target tumor cells for subsequent drug release while extending drug retention within tumor cells, which increases immunogenic cell death and facilitates the immunotherapeutic effect of CD4+ T cells. Ultimately, DI/Pep1 attenuated tumor-associated inflammation, enhanced the body's immune response, and inhibited breast cancer growth by combining the actions of DOX and IND. Our research offers an approach to hopefully enhance the effectiveness of cancer treatment.

Impact of combinatorial immunotherapies in breast cancer: a systematic review and meta-analysis

BACKGROUND

Breast cancer has the highest mortality rate among all cancers affecting females worldwide. Several new effective therapeutic strategies are being developed to minimize the number of breast cancer-related deaths and improve the quality of life of breast cancer patients. However, resistance to conventional therapies in breast cancer patients remains a challenge which could be due to several reasons, including changes in the tumor microenvironment. Attention is being diverted towards minimizing the resistance, toxicity, and improving the affordability of therapeutics for better breast cancer management. This includes personalized medicine, target-specific drug delivery systems, combinational therapies and artificial intelligence based screening and disease prediction. Nowadays, researchers and clinicians are also exploring the use of combinatorial immunotherapies in breast cancer patients, which have shown encouraging results in terms of improved survival outcomes. This study attempts to analyze the role of combinational immunotherapies in breast cancer patients, and offer insights into their effectiveness in breast cancer management.

METHODOLOGY

We conducted a systematic review and meta-analysis for which we selected the randomized clinical trials (RCTs) focused on completed Phase I/II/III/IV clinical trials investigating combination immunotherapies for breast cancer. The analysis aimed to assess the efficacy of combination therapies in comparison to mono-therapies, focusing on overall survival (OS), and progression-free survival (PFS).

RESULTS

We observed that, combination immunotherapies significantly (P<0.05) improved OS as compared to single-drug therapies in the Phase I with overall Risk ratio (RR) of 16.17 (CI 2.23,117.50), Phase II with an overall RR of 19.19 (CI 11.76,31.30) and for phase III overall RR 22.27 (CI 13.60,36.37). In the case of PFS, it was significant with RR: 12.35 (CI 2.14, 71.26) in Phase I RR 6.10 (CI 4.31, 8.64) in phase II, RR 8.95 (CI 6.09, 13.16) in phase III and RR 14.82 (CI 6.49, 33.82) in Phase IV of clinical trials.

CONCLUSION

The observed improvements in overall survival and progression-free survival suggest that combination immunotherapies could serve as a better approach to breast cancer management.

Towards unbiased interpretations of interactive effects in ecotoxicological studies

Ecotoxicological research has increasingly focused on the interactive effects of chemical mixtures on biological models, emphasising additive, synergistic, or antagonistic interactions. However, these combination studies often test chemicals at unique concentrations (e.g. x:y), limiting our understanding of the effects across the full spectrum of possible combinations. Evidence from human toxicology suggests that interactive effects among chemicals can vary significantly with total concentration (e.g. x:y vs. 2x:2y), their ratio (e.g. x:2y vs. 2x:y), and the magnitude of the tested effect (e.g. LC10vs. LC50). Our non-exhaustive review of studies on binary mixtures in bee ecotoxicology reveals that such parameters are frequently neglected. Of the 60 studies we examined, only two utilised multiple total concentrations and ratios, thus exploring a broad range of possible combinations. In contrast, 26 studies tested only a single concentration of each chemical, resulting in incomplete interpretations of the potential interactive effects. Other studies utilised various concentrations and/or ratios but failed to capture a broad spectrum of possible combinations. We also discuss potential discrepancies in interactive effects based on different metrics and exposure designs. We advocate for future ecotoxicological studies to investigate a wider spectrum of chemical combinations, including various concentrations and ratios, and to address different levels of effects.

Don't fear the reaper: The role of regulated cell death in tumorigenesis and BH3-mimetics for cancer therapy

From its earliest characterization, it has been recognized that there is a role for regulated (programmed) cell death in cancer. As our understanding of the different types of programmed cell death processes and their molecular control has advanced, so have the technologies that allow us to manipulate these processes to, for example, fight against cancer. In this review, we describe the roles of the different forms of regulated cell death in the development of cancer as well as their potential therapeutic exploitation. In that vein, we explore the development and use of BH3-mimetics, a unique class of drugs that can directly activate the apoptotic cell death machinery to treat cancer. Finally, we address key challenges that face the field to improve the use of these therapeutics and the efforts that are being undertaken to do so.

An Antagonist Antibody That Inhibits Cancer Cell Growth In Vitro through RACK1

BACKGROUND/OBJECTIVES

Our research introduces a novel screening method to identify antibodies that can suppress cell proliferation and induce apoptosis.

METHODS

By using an autocrine signaling system with lentivirus, we developed an antibody screening method based on FACS sorting assays and cell cycle analysis to inhibit tumor growth in vitro. This approach is particularly well suited for studying tumor suppressors. Inducing the G0 phase in tumor cells with specific antibodies may arrest their growth permanently or trigger apoptosis. The cell cycle is composed of tightly regulated phases for cell growth and division, with tumorigenesis or apoptosis occurring when these regulatory mechanisms fail.

RESULTS

In our study, we identified RACK1 as a key regulator of cancer cell growth. The H9 antibody against RACK1 selected from a human antibody library effectively suppressed cell proliferation by inhibiting RACK1 function.

CONCLUSIONS

These findings suggest that RACK1 plays a crucial role in tumor cell cycling and could represent a novel therapeutic target for cancer treatment. Although RACK1 is recognized as a significant target protein in various tumors, no commercial therapeutic agents currently exist. Our results suggest that the H9 antibody could be a promising candidate for the development of novel cancer therapies.

An integrated framework for the study of exercise across the postdiagnosis cancer continuum

Exercise plays many important roles across the entire cancer continuum that have been described in previous frameworks. These frameworks, however, have generally provided a simplified description of the roles of exercise postdiagnosis. The modern cancer treatment landscape has become complex and often consists of multiple lines of multimodal treatments combined concurrently and/or sequentially and delivered over many months or years. This complexity requires a more multifaceted and targeted approach to the study of exercise after a cancer diagnosis. Here, we propose a new integrated framework-Exercise Across the Postdiagnosis Cancer Continuum (EPiCC)-that highlights the distinct roles of exercise for disease treatment and supportive care from diagnosis until death. We also propose new terminology to clarify the distinct roles of exercise that emerge in the context of the modern cancer treatment landscape. The EPiCC Framework is structured around multiple sequential cancer treatments that highlight six distinct cancer treatment-related time periods for exercise-before treatments, during treatments, between treatments, immediately after successful treatments, during longer term survivorship after successful treatments, and during end of life after unsuccessful treatments. The EPiCC Framework proposes that the specific roles of exercise as a disease treatment and supportive care intervention will vary depending on its positioning within different cancer treatment combinations. As a cancer treatment, exercise may serve as a "priming therapy", primary therapy, neoadjuvant therapy, induction therapy, "bridging therapy", adjuvant therapy, consolidation therapy, maintenance therapy, and/or salvage therapy. As a supportive care intervention, exercise may serve as prehabilitation, intrahabilitation, interhabilitation, rehabilitation, "perihabilitation", health promotion/disease prevention, and/or palliation. To date, exercise has been studied during all of the cancer treatment-related time periods but only in relation to some cancer treatments and combinations. Moreover, fewer studies have examined exercise across multiple cancer treatment-related time periods within any cancer treatment combination. Future research is needed to study exercise as a disease treatment and supportive care intervention within and across the distinct cancer treatment-related time periods contained within different cancer treatment combinations. The aim of the EPiCC Framework is to stimulate a more targeted, integrated, and clinically-informed approach to the study of exercise after a cancer diagnosis.

Strategic Advances in Combination Therapy for Metastatic Castration-Sensitive Prostate Cancer: Current Insights and Future Perspectives

The contemporary treatment for metastatic castration-sensitive prostate cancer (mCSPC) has evolved significantly, building on successes in managing metastatic castration-resistant prostate cancer (mCRPC). Although androgen deprivation therapy (ADT) alone has long been the cornerstone of mCSPC treatment, combination therapies have emerged as the new standard of care based on recent advances, offering improved survival outcomes. Landmark phase 3 trials demonstrated that adding chemotherapy (docetaxel) and androgen receptor pathway inhibitors to ADT significantly enhances overall survival, particularly for patients with high-volume, high-risk, or de novo metastatic disease. Despite these advancements, a concerning gap between evidence-based guidelines and real-world practice remains, with many patients not receiving recommended combination therapies. The challenge in optimizing therapy sequences, considering both disease control and treatment burdens, and identifying clinical and biological subgroups that could benefit from personalized treatment strategies persists. The advent of triplet therapy has shown promise in extending survival, but the uro-oncology community must narrow the gap between evidence and practice to deliver the most effective care. Current research is focused on refining treatment approaches and utilizing biomarkers to guide therapy selection, aiming to offer more personalized and adaptive strategies for mCSPC management. Thus, aligning clinical practices with the evolving evidence is urgently needed to improve outcomes for patients facing this incurable disease.

Targeting NAT10 inhibits osteosarcoma progression via ATF4/ASNS-mediated asparagine biosynthesis

Despite advances in treatment, the prognosis of patients with osteosarcoma remains unsatisfactory, and searching for potential targets is imperative. Here, we identify N4-acetylcytidine (ac4C) acetyltransferase 10 (NAT10) as a candidate therapeutic target in osteosarcoma through functional screening. NAT10 overexpression is correlated with a poor prognosis, and NAT10 knockout inhibits osteosarcoma progression. Mechanistically, NAT10 enhances mRNA stability of activating transcription factor 4 (ATF4) through ac4C modification. ATF4 induces the transcription of asparagine synthetase (ASNS), which catalyzes asparagine (Asn) biosynthesis, facilitating osteosarcoma progression. Utilizing virtual screening, we identify paliperidone and AG-401 as potential NAT10 inhibitors, and both inhibitors are found to bind to NAT10 proteins. Inhibiting NAT10 suppresses osteosarcoma progression in vivo. Combined treatment using paliperidone and AG-401 produces synergistic inhibition for osteosarcoma in patient-derived xenograft (PDX) models. Our findings demonstrate that NAT10 facilitates osteosarcoma progression through the ATF4/ASNS/Asn axis, and pharmacological inhibition of NAT10 may be a feasible therapeutic approach for osteosarcoma.

Three-dimensional analysis of mitochondria in a patient-derived xenograft model of triple negative breast cancer reveals mitochondrial network remodeling following chemotherapy treatments

Mitochondria are hubs of metabolism and signaling and play an important role in tumorigenesis, therapeutic resistance, and metastasis in many cancer types. Various laboratory models of cancer demonstrate the extraordinary dynamics of mitochondrial structure, but little is known about the role of mitochondrial structure in resistance to anticancer therapy. We previously demonstrated the importance of mitochondrial structure and oxidative phosphorylation in the survival of chemotherapy-refractory triple negative breast cancer (TNBC) cells. As TNBC is a highly aggressive breast cancer subtype with few targeted therapy options, conventional chemotherapies remain the backbone of early TNBC treatment. Unfortunately, approximately 45% of TNBC patients retain substantial residual tumor burden following chemotherapy, associated with abysmal prognoses. Using an orthotopic patient-derived xenograft mouse model of human TNBC, we compared mitochondrial structures between treatment-naïve tumors and residual tumors after conventional chemotherapeutics were administered singly or in combination. We reconstructed 1,750 mitochondria in three dimensions from serial block-face scanning electron micrographs, providing unprecedented insights into the complexity and intra-tumoral heterogeneity of mitochondria in TNBC. Following exposure to carboplatin or docetaxel given individually, residual tumor mitochondria exhibited significant increases in mitochondrial complexity index, area, volume, perimeter, width, and length relative to treatment-naïve tumor mitochondria. In contrast, residual tumors exposed to those chemotherapies given in combination exhibited diminished mitochondrial structure changes. Further, we document extensive intra-tumoral heterogeneity of mitochondrial structure, especially prior to chemotherapeutic exposure. These results highlight the potential for structure-based monitoring of chemotherapeutic responses and reveal potential molecular mechanisms that underlie chemotherapeutic resistance in TNBC.

Pediatric Leukemia Roadmaps Are a Guide for Positive Metastatic Bone Sarcoma Trials

ALL cures require many MRD therapies. This strategy should drive experiments and trials in metastatic bone sarcomas.

Phytochemicals in Drug Discovery-A Confluence of Tradition and Innovation

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. An emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

Nanoscaled metal-organic frameworks: charting a transformative path for cancer therapeutics and beyond

Through this inspirational note, we would like to highlight the potential of nanoscaled metal-organic frameworks within the biomedical field. The unique properties of these materials that make them promising candidates for new nanomedicines are assessed here as well as the progression reached so far for combinational cancer therapies and theranostic, along with its most recent advances in nanomedicine. Finally, the perspective and challenges of these materials within this field is discussed.

Synergistic effects of the KDM4C inhibitor SD70 and the menin inhibitor MI-503 against MLL::AF9-driven acute myeloid leukaemia

MLL-rearranged (MLL-r) leukaemia is observed in approximately 10% of acute myeloid leukaemia (AML) and is associated with a relatively poor prognosis, highlighting the need for new treatment regimens. MLL fusion proteins produced by MLL rearrangements recruit KDM4C to mediate epigenetic reprogramming, which is required for the maintenance of MLL-r leukaemia. In this study, we used a combinatorial drug screen to selectively identify synergistic treatment partners for the KDM4C inhibitor SD70. The results showed that the drug combination of SD70 and MI-503, a potent menin-MLL inhibitor, induced synergistically enhanced apoptosis in MLL::AF9 leukaemia cells without affecting normal CD34+ cells. In vivo treatment with SD70 and MI-503 significantly prolonged survival in AML xenograft models. Differential gene expression analysis by RNA-seq following combined pharmacological inhibition of SD70 and MI-503 revealed changes in numerous genes, with MYC target genes being the most significantly downregulated. Taken together, these data provide preclinical evidence that the combination of SD70 and MI-503 is a potential dual-targeted therapy for MLL::AF9 AML.

Chemotherapeutic Potential of Chlorambucil-Platinum(IV) Prodrugs against Cisplatin-Resistant Colorectal Cancer Cells

Chlorambucil-platinum(IV) prodrugs exhibit multi-mechanistic chemotherapeutic activity with promising anticancer potential. The platinum(II) precursors of the prodrugs have been previously found to induce changes in the microtubule cytoskeleton, specifically actin and tubulin of HT29 colon cells, while chlorambucil alkylates the DNA. These prodrugs demonstrate significant anticancer activity in 2D cell and 3D spheroid viability assays. A notable production of reactive oxygen species has been observed in HT29 cells 72 h post treatment with prodrugs of this type, while the mitochondrial membrane potential was substantially reduced. The cellular uptake of the chlorambucil-platinum(IV) prodrugs, assessed by ICP-MS, confirmed that active transport was the primary uptake mechanism, with platinum localisation identified primarily in the cytoskeletal fraction. Apoptosis and necrosis were observed at 72 h of treatment as demonstrated by Annexin V-FITC/PI assay using flow cytometry. Immunofluorescence measured via confocal microscopy showed significant changes in actin and tubulin intensity and in architecture. Western blot analysis of intrinsic and extrinsic pathway apoptotic markers, microtubule cytoskeleton markers, cell proliferation markers, as well as autophagy markers were studied post 72 h of treatment. The proteomic profile was also studied with a total of 1859 HT29 proteins quantified by mass spectroscopy, with several dysregulated proteins. Network analysis revealed dysregulation in transcription, MAPK markers, microtubule-associated proteins and mitochondrial transport dysfunction. This study confirms that chlorambucil-platinum(IV) prodrugs are candidates with promising anticancer potential that act as multi-mechanistic chemotherapeutics.

GLUT1 inhibitor BAY-876 induces apoptosis and enhances anti-cancer effects of bitter receptor agonists in head and neck squamous carcinoma cells

Head and neck squamous cell carcinomas (HNSCCs) are cancers that arise in the mucosa of the upper aerodigestive tract. The five-year patient survival rate is ~50%. Treatment includes surgery, radiation, and/or chemotherapy and is associated with lasting effects even when successful in irradicating the disease. New molecular targets and therapies must be identified to improve outcomes for HNSCC patients. We recently identified bitter taste receptors (taste family 2 receptors, or T2Rs) as a novel candidate family of receptors that activate apoptosis in HNSCC cells through mitochondrial Ca2+ overload and depolarization. We hypothesized that targeting another component of tumor cell metabolism, namely glycolysis, may increase the efficacy of T2R-directed therapies. GLUT1 (SLC2A1) is a facilitated-diffusion glucose transporter expressed by many cancer cells to fuel their increased rates of glycolysis. GLUT1 is already being investigated as a possible cancer target, but studies in HNSCCs are limited. Examination of immortalized HNSCC cells, patient samples, and The Cancer Genome Atlas revealed high expression of GLUT1 and upregulation in some patient tumor samples. HNSCC cells and tumor tissue express GLUT1 on the plasma membrane and within the cytoplasm (perinuclear, likely co-localized with the Golgi apparatus). We investigated the effects of a recently developed small molecule inhibitor of GLUT1, BAY-876. This compound decreased HNSCC glucose uptake, viability, and metabolism and induced apoptosis. Moreover, BAY-876 had enhanced effects on apoptosis when combined at low concentrations with T2R bitter taste receptor agonists. Notably, BAY-876 also decreased TNFα-induced IL-8 production, indicating an additional mechanism of possible tumor-suppressive effects. Our study demonstrates that targeting GLUT1 via BAY-876 to kill HNSCC cells, particularly in combination with T2R agonists, is a potential novel treatment strategy worth exploring further in future translational studies.

Anticancer Effect of PtIIPHENSS, PtII5MESS, PtII56MESS and Their Platinum(IV)-Dihydroxy Derivatives against Triple-Negative Breast Cancer and Cisplatin-Resistant Colorectal Cancer

Development of resistance to cisplatin, oxaliplatin and carboplatin remains a challenge for their use as chemotherapies, particularly in breast and colorectal cancer. Here, we compare the anticancer effect of novel complexes [Pt(1,10-phenanthroline)(1S,2S-diaminocyclohexane)](NO3)2 (PtIIPHENSS), [Pt(5-methyl-1,10-phenanthroline)(1S,2S-diaminocyclohexane)](NO3)2 (PtII5MESS) and [Pt(5,6-dimethyl-1,10-phenanthroline)(1S,2S-diaminocyclohexane)](NO3)2 (PtII56MESS) and their platinum(IV)-dihydroxy derivatives with cisplatin. Complexes are greater than 11-fold more potent than cisplatin in both 2D and 3D cell line cultures with increased selectivity for cancer cells over genetically stable cells. ICP-MS studies showed cellular uptake occurred through an active transport mechanism with considerably altered platinum concentrations found in the cytoskeleton across all complexes after 24 h. Significant reactive oxygen species generation was observed, with reduced mitochondrial membrane potential at 72 h of treatment. Late apoptosis/necrosis was shown by Annexin V-FITC/PI flow cytometry assay, accompanied by increased sub-G0/G1 cells compared with untreated cells. An increase in S and G2+M cells was seen with all complexes. Treatment resulted in significant changes in actin and tubulin staining. Intrinsic and extrinsic apoptosis markers, MAPK/ERK and PI3K/AKT activation markers, together with autophagy markers showed significant activation of these pathways by Western blot. The proteomic profile investigated post-72 h of treatment identified 1597 MDA-MB-231 and 1859 HT29 proteins quantified by mass spectroscopy, with several differentially expressed proteins relative to no treatment. GO enrichment analysis revealed a statistically significant enrichment of RNA/DNA-associated proteins in both the cell lines and specific additional processes for individual drugs. This study shows that these novel agents function as multi-mechanistic chemotherapeutics, offering promising anticancer potential, and thereby supporting further research into their application as cancer therapeutics.