Dynamic Cancer Cell Heterogeneity: Diagnostic and Therapeutic Implications

Effective Strategies in Designing Chitosan-hyaluronic Acid Nanocarriers: From Synthesis to Drug Delivery Towards Chemotherapy

The biomedical field faces an ongoing challenge in developing more effective anti-cancer medication due to the significant burden that cancer poses on human health. Extensive research has been conducted on the utilization of natural polysaccharides in nanomedicine owing to their properties of biocompatibility, biodegradability, non-immunogenicity, and non-toxicity. These characteristics make them a potent drug delivery system for cancer therapy. The chitosan hyaluronic acid nanoparticle (CSHANp) system, consisting of chitosan and hyaluronic acid nanoparticles, has exhibited considerable potential as a nanocarrier for various cancer drugs, rendering it one of the most auspicious systems presently accessible. The CSHANps demonstrate remarkable drug loading capacity, precise control over drug release, and exceptional selectivity towards cancer cells. These properties enhance the therapeutic effectiveness against cancerous cells. This article aims to provide a comprehensive analysis of CSHANp, focusing on its characteristics, production techniques, applications, and future prospects.

MetaPhenotype: A Transferable Meta-Learning Model for Single-Cell Mass Spectrometry-Based Cell Phenotype Prediction Using Limited Number of Cells

Single-cell mass spectrometry (SCMS) is an emerging tool for studying cell heterogeneity according to variation of molecular species in single cells. Although it has become increasingly common to employ machine learning models in SCMS data analysis, such as the classification of cell phenotypes, the existing machine learning models often suffer from low adaptability and transferability. In addition, SCMS studies of rare cells can be restricted by limited number of cell samples. To overcome these limitations, we performed SCMS analyses of melanoma cancer cell lines with two phenotypes (i.e., primary and metastatic cells). We then developed a meta-learning-based model, MetaPhenotype, that can be trained using a small amount of SCMS data to accurately classify cells into primary or metastatic phenotypes. Our results show that compared with standard transfer learning models, MetaPhenotype can rapidly predict and achieve a high accuracy of over 90% with fewer new training samples. Overall, our work opens the possibility of accurate cell phenotype classification based on fewer SCMS samples, thus lowering the demand for sample acquisition.

Lectin-modified drug delivery systems - Recent applications in the oncology field

Chemotherapy with cytotoxic drugs remains the core treatment for cancer but, due to the difficulty to find general and usable biochemical differences between cancer cells and normal cells, many of these drugs are associated with lack of specificity, resulting in side effects and collateral cytotoxicity that impair patients' adherence to therapy. Novel cancer treatments in which the cytotoxic effect is maximized while adverse effects are reduced can be implemented by developing targeted therapies that exploit the specific features of cancer cells, such as the typical expression of aberrant glycans. Modification of drug delivery systems with lectins is one of the strategies to implement targeted chemotherapies, as lectins are able to specifically recognize and bind to cancer-associated glycans expressed at the surface of cancer cells, guiding the drug treatment towards these cells and not affecting healthy ones. In this paper, recent advances on the development of lectin-modified drug delivery systems for targeted cancer treatments are thoroughly reviewed, with a focus on their properties and performance in diverse applications, as well as their main advantages and limitations. The synthesis and analytical characterization of the cited lectin-modified drug delivery systems is also briefly described. A comparison with free-drug treatments and with antibody-modified drug delivery systems is presented, emphasizing the advantages of lectin-modified drug delivery systems. Main constraints and potential challenges of lectin-modified drug delivery systems, including key difficulties for clinical translation of these systems, and the required developments in this area, are also signalled.

Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.

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.

Susceptibility of Melanoma Cells to Targeted Therapy Correlates with Protection by Blood Neutrophils

Elevated levels of peripheral blood and tumor tissue neutrophils are associated with poorer clinical response and therapy resistance in melanoma. The underlying mechanism and the role of neutrophils in targeted therapy is still not fully understood. Serum samples of patients with advanced melanoma were collected and neutrophil-associated serum markers were measured and correlated with response to targeted therapy. Blood neutrophils from healthy donors and patients with advanced melanoma were isolated, and their phenotypes, as well as their in vitro functions, were compared. In vitro functional tests were conducted through nonadherent cocultures with melanoma cells. Protection of melanoma cell lines by neutrophils was assessed under MAPK inhibition. Blood neutrophils from advanced melanoma patients exhibited lower CD16 expression compared to healthy donors. In vitro, both healthy-donor- and patient-derived neutrophils prevented melanoma cell apoptosis upon dual MAPK inhibition. The effect depended on cell-cell contact and melanoma cell susceptibility to treatment. Interference with protease activity of neutrophils prevented melanoma cell protection during treatment in cocultures. The negative correlation between neutrophils and melanoma outcomes seems to be linked to a protumoral function of neutrophils. In vitro, neutrophils exert a direct protective effect on melanoma cells during dual MAPK inhibition. This study further hints at a crucial role of neutrophil-related protease activity in protection.

Recent Trends and Innovations in Bead-Based Biosensors for Cancer Detection

Demand is strong for sensitive, reliable, and cost-effective diagnostic tools for cancer detection. Accordingly, bead-based biosensors have emerged in recent years as promising diagnostic platforms based on wide-ranging cancer biomarkers owing to the versatility, high sensitivity, and flexibility to perform the multiplexing of beads. This comprehensive review highlights recent trends and innovations in the development of bead-based biosensors for cancer-biomarker detection. We introduce various types of bead-based biosensors such as optical, electrochemical, and magnetic biosensors, along with their respective advantages and limitations. Moreover, the review summarizes the latest advancements, including fabrication techniques, signal-amplification strategies, and integration with microfluidics and nanotechnology. Additionally, the challenges and future perspectives in the field of bead-based biosensors for cancer-biomarker detection are discussed. Understanding these innovations in bead-based biosensors can greatly contribute to improvements in cancer diagnostics, thereby facilitating early detection and personalized treatments.

Cancer cell plasticity, stem cell factors, and therapy resistance: how are they linked?

Cellular plasticity can occur naturally in an organism and is considered an adapting mechanism during the developmental stage. However, abnormal cellular plasticity is observed in different diseased conditions, including cancer. Cancer cell plasticity triggers the stimuli of epithelial-mesenchymal transition (EMT), abnormal epigenetic changes, expression of stem cell factors and implicated signaling pathways, etc., and helps in the maintenance of CSC phenotype. Conversely, CSC maintains the cancer cell plasticity, EMT, and epigenetic plasticity. EMT contributes to increased cell migration and greater diversity within tumors, while epigenetic changes, stem cell factors (OCT4, NANOG, and SOX2), and various signaling pathways allow cancer cells to maintain various phenotypes, giving rise to intra- and inter-tumoral heterogeneity. The intricate relationships between cancer cell plasticity and stem cell factors help the tumor cells adopt drug-tolerant states, evade senescence, and successfully acquire drug resistance with treatment dismissal. Inhibiting molecules/signaling pathways involved in promoting CSCs, cellular plasticity, EMT, and epigenetic plasticity might be helpful for successful cancer therapy management. This review discussed the role of cellular plasticity, EMT, and stem cell factors in tumor initiation, progression, reprogramming, and therapy resistance. Finally, we discussed how the intervention in this axis will help better manage cancers and improve patient survivability.

Single-cell analysis reveals ADGRL4+ renal tubule cells as a highly aggressive cell type in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a highly heterogeneous cancer that poses great challenge to clinical treatment and prognostic prediction. Characterizing the cellular landscape of ccRCC in a single-cell dimension can help better understand the tumor heterogeneity and molecular mechanisms of ccRCC. This study analyzed single-cell profiles in ccRCC samples and para-tumor samples from Gene Expression Omnibus and identified a highly heterogeneous subcluster of renal tubule cells. Single-cell regulatory network inference and clustering analyses and cell communication analysis were performed to develop transcription factor-target gene regulatory networks and cell-cell interactions. Additionally, the distribution and prognostic risk of renal tubule cells from spatial transcriptome data (GSM6415706) and The Cancer Genome Atlas-Kidney Clear Cell Carcinoma data were analyzed. A total of 10 cell types were identified in ccRCC and para-tumor samples. The ccRCC renal tubule cells showed a high expression of the oncogene nicotinamide N-methyltransferase and a significantly high degree of tumor heterogeneity. We further identified 6 cell subclusters with specific expression of BEX2, PTHLH, SFRP2, KLRB1, ADGRL4, and HGF from the ccRCC renal tubule cells. ADGRL4+ renal tubule cells had highly metastatic and angiogenesis-inducing characteristics, with more ADGRL4+ renal tubule cells indicating a worse survival. ADGRL4+ renal tubule cells regulated the metastasis of other renal tubule cells through metastasis-related receptor-ligand communication. We also found that ADGRL4+ renal tubule cells clustered around the glomeruli but the rest of the renal tubule cell subclusters rarely localized in ccRCC tissues. ETS1 and ELK3 -dominant GRNs were remarkably activated in ADGRL4+ renal tubule cells, functionally, knockdown of ELK3 in A498 significantly disturbedaffected the cell migration and invasion. ADGRL4+ renal tubule cells, which were highly metastatic and invasive, might be an essential cell subcluster for ccRCC, and ADGRL4 could be used a novel therapeutic target.

Adhesion, metastasis, and inhibition of cancer cells: a comprehensive review

This comprehensive review delves into cancer's complexity, focusing on adhesion, metastasis, and inhibition. It explores the pivotal role of these factors in disease progression and therapeutic strategies. This review covers cancer cell migration, invasion, and colonization of distant organs, emphasizing the significance of cell adhesion and the intricate metastasis process. Inhibition approaches targeting adhesion molecules, such as integrins and cadherins, are discussed. Overall, this review contributes significantly to advancing cancer research and developing targeted therapies, holding promise for improving patient outcomes worldwide. Exploring different inhibition strategies revealed promising therapeutic targets to alleviate adhesion and metastasis of cancer cells. The effectiveness of integrin-blocking antibodies, small molecule inhibitors targeting Focal adhesion kinase (FAK) and the Transforming Growth Factor β (TGF-β) pathway, and combination therapies underscores their potential to disrupt focal adhesions and control epithelial-mesenchymal transition processes. The identification of as FAK, Src, β-catenin and SMAD4 offers valuable starting points for further research and the development of targeted therapies. The complex interrelationships between adhesion and metastatic signaling networks will be relevant to the development of new treatment approaches.

Analysis of the potential biological value of pyruvate dehydrogenase E1 subunit β in human cancer

BACKGROUND

The pyruvate dehydrogenase E1 subunit β (PDHB) gene which regulates energy metabolism is located in mitochondria. However, few studies have elucidated the role and mechanism of PDHB in different cancers.

AIM

To comprehensive pan-cancer analysis of PDHB was performed based on bioinformatics approaches to explore its tumor diagnostic and prognostic value and tumor immune relevance in cancer. In vitro experiments were performed to examine the biological regulation of PDHB in liver cancer.

METHODS

Pan-cancer data related to PDHB were obtained from the Cancer Genome Atlas (TCGA) database. Analysis of the gene expression profiles of PDHB was based on TCGA and Genotype Tissue Expression Dataset databases. Cox regression analysis and Kaplan-Meier methods were used to assess the correlation between PDHB expression and survival prognosis in cancer patients. The correlation between PDHB and receiver operating characteristic diagnostic curve, clinicopathological staging, somatic mutation, tumor mutation burden (TMB), microsatellite instability (MSI), DNA methylation, and drug susceptibility in pan-cancer was also analyzed. Various algorithms were used to analyze the correlation between PDHB and immune cell infiltration and tumor chemotaxis environment, as well as the co-expression analysis of PDHB and immune checkpoint (ICP) genes. The expression and functional phenotype of PDHB in single tumor cells were studied by single-cell sequencing, and the functional enrichment analysis of PDHB-related genes was performed. The study also validated the level of mRNA or protein expression of PDHB in several cancers. Finally, in vitro experiments verified the regulatory effect of PDHB on the proliferation, migration, and invasion of liver cancer.

RESULTS

PDHB was significantly and differently expressed in most cancers. PDHB was significantly associated with prognosis in patients with a wide range of cancers, including kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, breast invasive carcinoma, and brain lower grade glioma. In some cancers, PDHB expression was clearly associated with gene mutations, clinicopathological stages, and expression of TMB, MSI, and ICP genes. The expression of PDHB was closely related to the infiltration of multiple immune cells in the immune microenvironment and the regulation of tumor chemotaxis environment. In addition, single-cell sequencing results showed that PDHB correlated with different biological phenotypes of multiple cancer single cells. This study further demonstrated that down-regulation of PDHB expression inhibited the proliferation, migration, and invasion functions of hepatoma cells.

CONCLUSION

As a member of pan-cancer, PDHB may be a novel cancer marker with potential value in diagnosing cancer, predicting prognosis, and in targeted therapy.

From Chaos to Opportunity: Decoding Cancer Heterogeneity for Enhanced Treatment Strategies

Cancer manifests as a multifaceted disease, characterized by aberrant cellular proliferation, survival, migration, and invasion. Tumors exhibit variances across diverse dimensions, encompassing genetic, epigenetic, and transcriptional realms. This heterogeneity poses significant challenges in prognosis and treatment, affording tumors advantages through an increased propensity to accumulate mutations linked to immune system evasion and drug resistance. In this review, we offer insights into tumor heterogeneity as a crucial characteristic of cancer, exploring the difficulties associated with measuring and quantifying such heterogeneity from clinical and biological perspectives. By emphasizing the critical nature of understanding tumor heterogeneity, this work contributes to raising awareness about the importance of developing effective cancer therapies that target this distinct and elusive trait of cancer.

Tumor matrix stiffness provides fertile soil for cancer stem cells

Matrix stiffness is a mechanical characteristic of the extracellular matrix (ECM) that increases from the tumor core to the tumor periphery in a gradient pattern in a variety of solid tumors and can promote proliferation, invasion, metastasis, drug resistance, and recurrence. Cancer stem cells (CSCs) are a rare subpopulation of tumor cells with self-renewal, asymmetric cell division, and differentiation capabilities. CSCs are thought to be responsible for metastasis, tumor recurrence, chemotherapy resistance, and consequently poor clinical outcomes. Evidence suggests that matrix stiffness can activate receptors and mechanosensor/mechanoregulator proteins such as integrin, FAK, and YAP, modulating the characteristics of tumor cells as well as CSCs through different molecular signaling pathways. A deeper understanding of the effect of matrix stiffness on CSCs characteristics could lead to development of innovative cancer therapies. In this review, we discuss how the stiffness of the ECM is sensed by the cells and how the cells respond to this environmental change as well as the effect of matrix stiffness on CSCs characteristics and also the key malignant processes such as proliferation and EMT. Then, we specifically focus on how increased matrix stiffness affects CSCs in breast, lung, liver, pancreatic, and colorectal cancers. We also discuss how the molecules responsible for increased matrix stiffness and the signaling pathways activated by the enhanced stiffness can be manipulated as a therapeutic strategy for cancer.

The prognostic value of radiomic features from pre- and post-treatment 18F-FDG PET imaging in patients with nasopharyngeal carcinoma

Positron emission tomography/computed tomography (PET/CT) with ¹⁸F-fluorodeoxyglucose (FDG) is widely used for management of nasopharyngeal carcinoma (NPC). Combining the radiomic features of pre- and post-treatment FDG PET images may improve tumor characterization and prognostic predication. We investigated prognostic value of radiomic features from pre- and post-radiotherapy FDG PET images in patients with NPC. Quantitative radiomic features of primary tumors were extracted from the FDG PET images of 145 NPC patients and the delta values were also calculated. The study population was divided randomly into two groups, the training and test sets (7:3). A random survival forest (RSF) model was adopted to perform analyses of progression-free survival (PFS) and overall survival (OS). There were 37 (25.5%) cases of recurrence and 16 (11.0%) cases of death during a median follow-up period of 54.5 months. Both RSF models with clinical variables and radiomic PET features for PFS and OS showed comparable predictive performance to RSF models with clinical variables and conventional PET parameters. Tumoral radiomic features of pre- and post-treatment FDG PET and the corresponding delta values may predict PFS and OS in patients with NPC.

From the Catastrophic Objective Irreproducibility of Cancer Research and Unavoidable Failures of Molecular Targeted Therapies to the Sparkling Hope of Supramolecular Targeted Strategies

The unprecedented non-reproducibility of the results published in the field of cancer research has recently come under the spotlight. In this short review, we try to highlight some general principles in the organization and evolution of cancerous tumors, which objectively lead to their enormous variability and, consequently, the irreproducibility of the results of their investigation. This heterogeneity is also extremely unfavorable for the effective use of molecularly targeted medicine. Against the seemingly comprehensive background of this heterogeneity, we single out two supramolecular characteristics common to all tumors: the clustered nature of tumor interactions with their microenvironment and the formation of biomolecular condensates with tumor-specific distinctive features. We suggest that these features can form the basis of strategies for tumor-specific supramolecular targeted therapies.

Resveratrol, Epigallocatechin Gallate and Curcumin for Cancer Therapy: Challenges from Their Pro-Apoptotic Properties

Plant-derived bioactive compounds are gaining wide attention for their multiple health-promoting activities and in particular for their anti-cancer properties. Several studies have highlighted how they can prevent cancer initiation and progression, improve the effectiveness of chemotherapy, and, in some cases, limit some of the side effects of chemotherapy agents. In this paper, we provide an update of the literature on the anti-cancer effects of three extensively studied plant-derived compounds, namely resveratrol, epigallocatechin gallate, and curcumin, with a special focus on the anti-cancer molecular mechanisms inducing apoptosis in the major types of cancers globally.