Teriflunomide/leflunomide synergize with chemotherapeutics by decreasing mitochondrial fragmentation via DRP1 in SCLC.

Although up to 80% small cell lung cancer (SCLC) patients' response is good for first-line chemotherapy regimen, most patients develop recurrence of the disease within weeks to months. Here, we report cytostatic effect of leflunomide (Leflu) and teriflunomide (Teri) on SCLC cell proliferation through inhibition of DRP1 phosphorylation at Ser616 and decreased mitochondrial fragmentation. When administered together, Teri and carboplatin (Carbo) act synergistically to significantly inhibit cell proliferation and DRP1 phosphorylation, reduce abundance of intermediates in pyrimidine de novo pathway, and increase apoptosis and DNA damage. Combination of Leflu&Carbo has anti-tumorigenic effect in vivo. Additionally, lurbinectedin (Lur) and Teri potently and synergistically inhibited spheroid growth and depleted uridine and DRP1 phosphorylation in mouse tumors. Our results suggest combinations of Carbo and Lur with Teri or Leflu are efficacious and underscore how the relationship between DRP1/DHODH and mitochondrial plasticity serves as a potential therapeutic target to validate these treatment strategies in SCLC clinical trials.

Emerging Therapeutic Strategies to Overcome Drug Resistance in Cancer Cells.

The rise of drug resistance in cancer cells presents a formidable challenge in modern oncology, necessitating the exploration of innovative therapeutic strategies. This review investigates the latest advancements in overcoming drug resistance mechanisms employed by cancer cells, focusing on emerging therapeutic modalities. The intricate molecular insights into drug resistance, including genetic mutations, efflux pumps, altered signaling pathways, and microenvironmental influences, are discussed. Furthermore, the promising avenues offered by targeted therapies, combination treatments, immunotherapies, and precision medicine approaches are highlighted. Specifically, the synergistic effects of combining traditional cytotoxic agents with molecularly targeted inhibitors to circumvent resistance pathways are examined. Additionally, the evolving landscape of immunotherapeutic interventions, including immune checkpoint inhibitors and adoptive cell therapies, is explored in terms of bolstering anti-tumor immune responses and overcoming immune evasion mechanisms. Moreover, the significance of biomarker-driven strategies for predicting and monitoring treatment responses is underscored, thereby optimizing therapeutic outcomes. For insights into the future direction of cancer treatment paradigms, the current review focused on prevailing drug resistance challenges and improving patient outcomes, through an integrative analysis of these emerging therapeutic strategies.

Leveraging Cancer Phenotypic Plasticity for Novel Treatment Strategies.

Cancer cells, like all other organisms, are adept at switching their phenotype to adjust to the changes in their environment. Thus, phenotypic plasticity is a quantitative trait that confers a fitness advantage to the cancer cell by altering its phenotype to suit environmental circumstances. Until recently, new traits, especially in cancer, were thought to arise due to genetic factors; however, it is now amply evident that such traits could also emerge non-genetically due to phenotypic plasticity. Furthermore, phenotypic plasticity of cancer cells contributes to phenotypic heterogeneity in the population, which is a major impediment in treating the disease. Finally, plasticity also impacts the group behavior of cancer cells, since competition and cooperation among multiple clonal groups within the population and the interactions they have with the tumor microenvironment also contribute to the evolution of drug resistance. Thus, understanding the mechanisms that cancer cells exploit to tailor their phenotypes at a systems level can aid the development of novel cancer therapeutics and treatment strategies. Here, we present our perspective on a team medicine-based approach to gain a deeper understanding of the phenomenon to develop new therapeutic strategies.

Spatial iTME analysis of KRAS mutant NSCLC and immunotherapy outcome.

We conducted spatial immune tumor microenvironment (iTME) profiling using formalin-fixed paraffin-embedded (FFPE) samples of 25 KRAS-mutated non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), including 12 responders and 13 non-responders. An eleven-marker panel (CD3, CD4, CD8, FOXP3, CD68, arginase-1, CD33, HLA-DR, pan-keratin (PanCK), PD-1, and PD-L1) was used to study the tumor and immune cell compositions. Spatial features at single cell level with cellular neighborhoods and fractal analysis were determined. Spatial features and different subgroups of CD68+ cells and FOXP3+ cells being associated with response or resistance to ICIs were also identified. In particular, CD68+ cells, CD33+ and FOXP3+ cells were found to be associated with resistance. Interestingly, there was also significant association between non-nuclear expression of FOXP3 being resistant to ICIs. We identified CD68dim cells in the lung cancer tissues being associated with improved responses, which should be insightful for future studies of tumor immunity.

Nanoengineering Solutions for Cancer Therapy: Bridging the Gap between Clinical Practice and Translational Research.

Nanoengineering has emerged as a progressive method in cancer treatment, offering precise and targeted delivery of therapeutic agents while concurrently reducing overall toxicity. This scholarly article delves into the innovative strategies and advancements in nanoengineering that bridge the gap between clinical practice and research in the field of cancer treatment. Various nanoengineered platforms such as nanoparticles, liposomes, and dendrimers are scrutinized for their capacity to encapsulate drugs, augment drug efficacy, and enhance pharmacokinetics. Moreover, the article investigates research breakthroughs that drive the progression and enhancement of nanoengineered remedies, encompassing the identification of biomarkers, establishment of preclinical models, and advancement of biomaterials, all of which are imperative for translating laboratory findings into practical medical interventions. Furthermore, the integration of nanotechnology with imaging modalities, which amplify cancer detection, treatment monitoring, and response assessment, is thoroughly examined. Finally, the obstacles and prospective directions in nanoengineering, including regulatory challenges and issues related to scalability, are examined. This underscores the significance of fostering collaboration among various entities in order to efficiently translate nanoengineered interventions into enhanced cancer therapies and patient management.

Emerging biomarkers and molecular targets for precision medicine in cervical cancer.

Cervical cancer remains a significant global health burden, necessitating innovative approaches for improved diagnostics and personalized treatment strategies. Precision medicine has emerged as a promising paradigm, leveraging biomarkers and molecular targets to tailor therapy to individual patients. This review explores the landscape of emerging biomarkers and molecular targets in cervical cancer, highlighting their potential implications for precision medicine. By integrating these biomarkers into comprehensive diagnostic algorithms, clinicians can identify high-risk patients at an earlier stage, enabling timely intervention and improved patient outcomes. Furthermore, the identification of specific molecular targets has paved the way for the development of targeted therapies aimed at disrupting key pathways implicated in cervical carcinogenesis. In conclusion, the evolving landscape of biomarkers and molecular targets presents exciting opportunities for advancing precision medicine in cervical cancer. By harnessing these insights, clinicians can optimize treatment selection, enhance patient outcomes, and ultimately transform the management of this devastating disease.

Comprehending phenotypic plasticity in cancer and evolution.

Organisms as well as cancer cells are adept at adapting to changes in the environment in which they find themselves, by actively adjusting their phenotype. Phenotypic plasticity is a quantitative trait that confers a fitness advantage to the organism by tailoring its phenotype to environmental circumstances. While it is generally held that new traits arise solely from genetic factors, emerging evidence indicates that phenotypic plasticity also plays a critical role both in cancer and evolution. Thus, understanding the mechanisms that underlie phenotypic plasticity can not only provide new insights into organismal evolution and the origin of novelty but can also result in novel strategies and therapeutics to treat cancer.

Interplay of mitochondria-associated membrane proteins and autophagy: Implications in neurodegeneration.

Since the discovery of membrane contact sites between ER and mitochondria called mitochondria-associated membranes (MAMs), several pieces of evidence identified their role in the regulation of different cellular processes such as Ca2+ signalling, mitochondrial transport, and dynamics, ER stress, inflammation, glucose homeostasis, and autophagy. The integrity of these membranes was found to be essential for the maintenance of these cellular functions. Accumulating pieces of evidence suggest that MAMs serve as a platform for autophagosome formation. However, the alteration within MAMs structure is associated with the progression of neurodegenerative diseases. Dysregulated autophagy is a hallmark of neurodegeneration. Here, in this review, we highlight the present knowledge on MAMs, their structural composition, and their roles in different cellular functions. We also discuss the association of MAMs proteins with impaired autophagy and their involvement in the progression of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease.

A Nexus between Genetic and Non-Genetic Mechanisms Guides KRAS Inhibitor Resistance in Lung Cancer.

Several studies in the last few years have determined that, in contrast to the prevailing dogma that drug resistance is simply due to Darwinian evolution-the selection of mutant clones in response to drug treatment-non-genetic changes can also lead to drug resistance whereby tolerant, reversible phenotypes are eventually relinquished by resistant, irreversible phenotypes. Here, using KRAS as a paradigm, we illustrate how this nexus between genetic and non-genetic mechanisms enables cancer cells to evade the harmful effects of drug treatment. We discuss how the conformational dynamics of the KRAS molecule, that includes intrinsically disordered regions, is influenced by the binding of the targeted therapies contributing to conformational noise and how this noise impacts the interaction of KRAS with partner proteins to rewire the protein interaction network. Thus, in response to drug treatment, reversible drug-tolerant phenotypes emerge via non-genetic mechanisms that eventually enable the emergence of irreversible resistant clones via genetic mutations. Furthermore, we also discuss the recent data demonstrating how combination therapy can help alleviate KRAS drug resistance in lung cancer, and how new treatment strategies based on evolutionary principles may help minimize or even preclude the emergence of drug resistance.

Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers.

Gynecological cancers including breast, cervical, ovarian, uterine, and vaginal, pose the greatest threat to world health, with early identification being crucial to patient outcomes and survival rates. The application of machine learning (ML) and artificial intelligence (AI) approaches to the study of gynecological cancer has shown potential to revolutionize cancer detection and diagnosis. The current review outlines the significant advancements, obstacles, and prospects brought about by AI and ML technologies in the timely identification and accurate diagnosis of different types of gynecological cancers. The AI-powered technologies can use genomic data to discover genetic alterations and biomarkers linked to a particular form of gynecologic cancer, assisting in the creation of targeted treatments. Furthermore, it has been shown that the potential benefits of AI and ML technologies in gynecologic tumors can greatly increase the accuracy and efficacy of cancer diagnosis, reduce diagnostic delays, and possibly eliminate the need for needless invasive operations. In conclusion, the review focused on the integrative part of AI and ML based tools and techniques in the early detection and exclusion of various cancer types; together with a collaborative coordination between research clinicians, data scientists, and regulatory authorities, which is suggested to realize the full potential of AI and ML in gynecologic cancer care.

Acquired resistance to KRAS G12C small-molecule inhibitors via genetic/nongenetic mechanisms in lung cancer.

Inherent or acquired resistance to sotorasib poses a substantialt challenge for NSCLC treatment. Here, we demonstrate that acquired resistance to sotorasib in isogenic cells correlated with increased expression of integrin ß4 (ITGB4), a component of the focal adhesion complex. Silencing ITGB4 in tolerant cells improved sotorasib sensitivity, while overexpressing ITGB4 enhanced tolerance to sotorasib by supporting AKT-mTOR bypass signaling. Chronic treatment with sotorasib induced WNT expression and activated the WNT/ß-catenin signaling pathway. Thus, silencing both ITGB4 and ß-catenin significantly improved sotorasib sensitivity in tolerant, acquired, and inherently resistant cells. In addition, the proteasome inhibitor carfilzomib (CFZ) exhibited synergism with sotorasib by down-regulating ITGB4 and ß-catenin expression. Furthermore, adagrasib phenocopies the combination effect of sotorasib and CFZ by suppressing KRAS activity and inhibiting cell cycle progression in inherently resistant cells. Overall, our findings unveil previously unrecognized nongenetic mechanisms underlying resistance to sotorasib and propose a promising treatment strategy to overcome resistance.

Regression of ovarian cancer xenografts by depleting or inhibiting RLIP.

Ovarian cancer (OC) is the most prevalent and deadly cancer of the female reproductive system. Women will continue to be impacted by OC-related morbidity and mortality. Despite the fact that chemotherapy with cisplatin is the main component as the first-line anticancer treatment for OC, chemoresistance and unfavorable side effects are important obstacles to effective treatment. Targets for effective cancer therapy are required for cancer cells but not for non-malignant cells because they are expressed differently in cancer cells compared to normal cells. Targets for cancer therapy should preferably be components that already exist in biochemical and signalling frameworks and that significantly contribute to the development of cancer or regulate the response to therapy. RLIP is an important mercapturic acid pathway transporter that is crucial for survival and therapy resistance in cancers, therefore, we examined the role of RLIP in regulating essential signalling proteins involved in relaying the inputs from upstream survival pathways and mechanisms contributing to chemo-radiotherapy resistance in OC. The findings of our research offer insight into a novel anticancer effect of RLIP depletion/inhibition on OC and might open up new therapeutic avenues for OC therapy.

On the Virtues of "Team Medicine"-A City of Hope Perspective.

Our first Special Issue of the Journal of Clinical Medicine, entitled 'Integrating Clinical and Translational Research Networks-Building Team Medicine,' highlighted the collective experience of the City of Hope and was a tremendous success [...].

Targeting ITGB4/SOX2-driven lung cancer stem cells using proteasome inhibitors.

This study investigates the role of integrin ß4 (ITGB4) and stemness-associated factor SOX2 in platinum resistance in lung squamous cell carcinoma (LUSC). The expression of SOX2 and ITGB4 is found to be high in all LUSC subtypes, but the impact of ITGB4 expression on overall patient survival varies by subtype. Cancer stem cells (CSCs) isolated from LUSC patients were found to be resistant to cisplatin, but knocking down ITGB4 or SOX2 sensitized them to cisplatin. Carfilzomib (CFZ) synergized with cisplatin and suppressed CSC growth by inhibiting ITGB4 and SOX2 expression. Additionally, CFZ was found to inhibit SOX2 expression epigenetically by inhibiting histone acetylation at the SOX2 promoter site. CFZ also suppressed the growth of SOX2-dependent small cell lung cancer cells in vitro and in vivo. The study highlights the unique function of CFZ as a transcriptional suppressor of SOX2, independent of its proteasome inhibitory function.

Clinical Network Systems Biology: Traversing the Cancer Multiverse.

In recent decades, cancer biology and medicine have ushered in a new age of precision medicine through high-throughput approaches that led to the development of novel targeted therapies and immunotherapies for different cancers. The availability of multifaceted high-throughput omics data has revealed that cancer, beyond its genomic heterogeneity, is a complex system of microenvironments, sub-clonal tumor populations, and a variety of other cell types that impinge on the genetic and non-genetic mechanisms underlying the disease. Thus, a systems approach to cancer biology has become instrumental in identifying the key components of tumor initiation, progression, and the eventual emergence of drug resistance. Through the union of clinical medicine and basic sciences, there has been a revolution in the development and approval of cancer therapeutic drug options including tyrosine kinase inhibitors, antibody-drug conjugates, and immunotherapy. This 'Team Medicine' approach within the cancer systems biology framework can be further improved upon through the development of high-throughput clinical trial models that utilize machine learning models, rapid sample processing to grow patient tumor cell cultures, test multiple therapeutic options and assign appropriate therapy to individual patients quickly and efficiently. The integration of systems biology into the clinical network would allow for rapid advances in personalized medicine that are often hindered by a lack of drug development and drug testing.

Intrinsically disordered proteins and conformational noise: The hypothesis a decade later.

Phenotypic plasticity is the ability of individual genotypes to produce different phenotypes in response to environmental perturbations. We previously postulated how conformational noise emanating from conformational dynamics of intrinsically disordered proteins (IDPs) which is distinct from transcriptional noise, can contribute to phenotypic switching by rewiring the cellular protein interaction network. Since most transcription factors are IDPs, we posited that conformational noise is an integral component of transcriptional noise implying that IDPs may amplify total noise in the system either stochastically or in response to environmental changes. Here, we review progress in elucidating the details of the hypothesis. We highlight empirical evidence supporting the hypothesis, discuss conceptual advances that underscore its fundamental importance and implications, and identify areas for future investigations.

Recent Advancement in Breast Cancer Research: Insights from Model Organisms-Mouse Models to Zebrafish.

Animal models have been utilized for decades to investigate the causes of human diseases and provide platforms for testing novel therapies. Indeed, breakthrough advances in genetically engineered mouse (GEM) models and xenograft transplantation technologies have dramatically benefited in elucidating the mechanisms underlying the pathogenesis of multiple diseases, including cancer. The currently available GEM models have been employed to assess specific genetic changes that underlay many features of carcinogenesis, including variations in tumor cell proliferation, apoptosis, invasion, metastasis, angiogenesis, and drug resistance. In addition, mice models render it easier to locate tumor biomarkers for the recognition, prognosis, and surveillance of cancer progression and recurrence. Furthermore, the patient-derived xenograft (PDX) model, which involves the direct surgical transfer of fresh human tumor samples to immunodeficient mice, has contributed significantly to advancing the field of drug discovery and therapeutics. Here, we provide a synopsis of mouse and zebrafish models used in cancer research as well as an interdisciplinary 'Team Medicine' approach that has not only accelerated our understanding of varied aspects of carcinogenesis but has also been instrumental in developing novel therapeutic strategies.

Per Aspera ad Chaos: Vladimir Uversky's Odyssey through the Strange World of Intrinsically Disordered Proteins.

Until the late 1990s, we believed that protein function required a unique, well-defined 3D structure encrypted in the amino acid sequence [...].

Radiation Sensitivity: The Rise of Predictive Patient-Derived Cancer Models.

Patient-derived cancer models have been used for decades to improve our understanding of cancer and test anticancer treatments. Advances in radiation delivery have made these models more attractive for studying radiation sensitizers and understanding an individual patient's radiation sensitivity. Advances in the use of patient-derived cancer models lead to a more clinically relevant outcome, although many questions remain regarding the optimal use of patient-derived xenografts and patient-derived spheroid cultures. The use of patient-derived cancer models as personalized predictive avatars through mouse and zebrafish models is discussed, and the advantages and disadvantages of patient-derived spheroids are reviewed. In addition, the use of large repositories of patient-derived models to develop predictive algorithms to guide treatment selection is discussed. Finally, we review methods for establishing patient-derived models and identify key factors that influence their use as both avatars and models of cancer biology.

DNA Methylation-Mediated Mfn2 Gene Regulation in the Brain: A Role in Brain Trauma-Induced Mitochondrial Dysfunction and Memory Deficits.

Repeated mild traumatic brain injuries (rMTBI) affect mitochondrial homeostasis in the brain. However, mechanisms of long-lasting neurobehavioral effects of rMTBI are largely unknown. Mitofusin 2 (Mfn2) is a critical component of tethering complexes in mitochondria-associated membranes (MAMs) and thereby plays a pivotal role in mitochondrial functions. Herein, we investigated the implications of DNA methylation in the Mfn2 gene regulation, and its consequences on mitochondrial dysfunction in the hippocampus after rMTBI. rMTBI dramatically reduced the mitochondrial mass, which was concomitant with decrease in Mfn2 mRNA and protein levels. DNA hypermethylation at the Mfn2 gene promoter was observed post 30 days of rMTBI. The treatment of 5-Azacytidine, a pan DNA methyltransferase inhibitor, normalized DNA methylation levels at Mfn2 promoter, which further resulted into restoration of Mfn2 function. The normalization of Mfn2 function was well correlated with recovery in memory deficits in rMTBI-exposed rats. Since, glutamate excitotoxicity serves as a primary insult after TBI, we employed in vitro model of glutamate excitotoxicity in human neuronal cell line SH-SY5Y to investigate the causal epigenetic mechanisms of Mfn2 gene regulation. The glutamate excitotoxicity reduced Mfn2 levels via DNA hypermethylation at Mfn2 promoter. Loss of Mfn2 caused significant surge in cellular and mitochondrial ROS levels with lowered mitochondrial membrane potential in cultured SH-SY5Y cells. Like rMTBI, these consequences of glutamate excitotoxicity were also prevented by 5-AzaC pre-treatment. Therefore, DNA methylation serves as a vital epigenetic mechanism involved in Mfn2 expression in the brain; and this Mfn2 gene regulation may play a pivotal role in rMTBI-induced persistent cognitive deficits. Closed head weight drop injury method was employed to induce repeated mild traumatic brain (rMTBI) in jury in adult, male Wistar rats. rMTBI causes hyper DNA methylation at the Mfn2 promoter and lowers the Mfn2 expression triggering mitochondrial dysfunction. However, the treatment of 5-azacytidine normalizes DNA methylation at the Mfn2 promoter and restores mitochondrial function.