Tumor Heterogeneity, Single-Cell Sequencing, and Drug Resistance

A novel method for the isolation of single cells mimicking circulating tumour cells adhered on Smart Bio Surface slides by Laser Capture Microdissection

In recent years, the importance of isolating single cells from blood circulation for several applications, such as non-invasive tumour diagnosis, the monitoring of minimal residual disease, and the analysis of circulating fetal cells for prenatal diagnosis, urged the need to set up innovative methods. For such applications, different methods were developed. All show some weaknesses, especially a limited sensitivity, and specificity. Here we present a new method for isolating a single or a limited number of cells adhered to SBS slides (Tethis S.p.a.) (a glass slide coated with Nanostructured Titanium Dioxide) by Laser Capture Microdissection (LCM) and subsequent Whole Genome Amplification. SBS slides have been shown to have an optimal performance in immobilizing circulating tumour cells (CTCs) from early breast cancer patients. In this work, we spiked cancer cells in blood samples to mimic CTCs. By defining laser parameters to cut intact samples, we were able to isolate genetically intact single cells. We demonstrate that SBS slides are optimally suited for isolating cells using LCM and that this method provides high-quality DNA, ideal for gene-specific assays such as PCR and Sanger sequencing for mutation analysis.

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

Single-Cell Proliferation Microfluidic Device for High Throughput Investigation of Replicative Potential and Drug Resistance of Cancer Cells

Introduction

Cell proliferation represents a major hallmark of cancer biology, and manifests itself in the assessment of tumor growth, drug resistance and metastasis. Tracking cell proliferation or cell fate at the single-cell level can reveal phenotypic heterogeneity. However, characterization of cell proliferation is typically done in bulk assays which does not inform on cells that can proliferate under given environmental perturbations. Thus, there is a need for single-cell approaches that allow longitudinal tracking of the fate of a large number of individual cells to reveal diverse phenotypes.

Methods

We fabricated a new microfluidic architecture for high efficiency capture of single tumor cells, with the capacity to monitor cell divisions across multiple daughter cells. This single-cell proliferation (SCP) device enabled the quantification of the fate of more than 1000 individual cancer cells longitudinally, allowing comprehensive profiling of the phenotypic heterogeneity that would be otherwise masked in standard cell proliferation assays. We characterized the efficiency of single cell capture and demonstrated the utility of the SCP device by exposing MCF-7 breast tumor cells to different doses of the chemotherapeutic agent doxorubicin.

Results

The single cell trapping efficiency of the SCP device was found to be ~ 85%. At the low doses of doxorubicin (0.01 µM, 0.001 µM, 0.0001 µM), we observed that 50-80% of the drug-treated cells had undergone proliferation, and less than 10% of the cells do not proliferate. Additionally, we demonstrated the potential of the SCP device in circulating tumor cell applications where minimizing target cell loss is critical. We showed selective capture of breast tumor cells from a binary mixture of cells (tumor cells and white blood cells) that was isolated from blood processing. We successfully characterized the proliferation statistics of these captured cells despite their extremely low counts in the original binary suspension.

Conclusions

The SCP device has significant potential for cancer research with the ability to quantify proliferation statistics of individual tumor cells, opening new avenues of investigation ranging from evaluating drug resistance of anti-cancer compounds to monitoring the replicative potential of patient-derived cells.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-023-00773-z.

Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs across hundreds of fluconazole-resistant yeast strains

There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into 6 classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, and some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings empower multidrug strategies that leverage tradeoffs to combat resistance. Finally, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.

Inferring therapeutic vulnerability within tumors through integration of pan-cancer cell line and single-cell transcriptomic profiles

Single-cell RNA sequencing greatly advanced our understanding of intratumoral heterogeneity through identifying tumor subpopulations with distinct biologies. However, translating biological differences into treatment strategies is challenging, as we still lack tools to facilitate efficient drug discovery that tackles heterogeneous tumors. One key component of such approaches tackles accurate prediction of drug response at the single-cell level to offer therapeutic options to specific cell subpopulations. Here, we present a transparent computational framework (nicknamed scIDUC) to predict therapeutic efficacies on an individual-cell basis by integrating single-cell transcriptomic profiles with large, data-rich pan-cancer cell line screening datasets. Our method achieves high accuracy, with predicted sensitivities easily able to separate cells into their true cellular drug resistance status as measured by effect size (Cohen's d > 1.0). More importantly, we examine our method's utility with three distinct prospective tests covering different diseases (rhabdomyosarcoma, pancreatic ductal adenocarcinoma, and castration-resistant prostate cancer), and in each our predicted results are accurate and mirrored biological expectations. In the first two, we identified drugs for cell subpopulations that are resistant to standard-of-care (SOC) therapies due to intrinsic resistance or effects of tumor microenvironments. Our results showed high consistency with experimental findings from the original studies. In the third test, we generated SOC therapy resistant cell lines, used scIDUC to identify efficacious drugs for the resistant line, and validated the predictions with in-vitro experiments. Together, scIDUC quickly translates scRNA-seq data into drug response for individual cells, displaying the potential as a first-line tool for nuanced and heterogeneity-aware drug discovery.

Using picoliter droplet deposition to track clonal competition in adherent and organoid cancer cell cultures

Clonal growth and competition underlie processes of key relevance in etiology, progression and therapy response across all cancers. Here, we demonstrate a novel experimental approach, based on multi-color, fluorescent tagging of cell nuclei, in combination with picoliter droplet deposition, to study the clonal dynamics in two- and three-dimensional cell cultures. The method allows for the simultaneous visualization and analysis of multiple clones in individual multi-clonal colonies, providing a powerful tool for studying clonal dynamics and identifying clonal populations with distinct characteristics. Results of our experiments validate the utility of the method in studying clonal dynamics in vitro, and reveal differences in key aspects of clonal behavior of different cancer cell lines in monoculture conditions, as well as in co-cultures with stromal fibroblasts.

Optimization of method for achieving a single-cell suspension from mouse corneas

The single-cell RNA-sequencing (scRNA-seq) technique is used to explore the biological characteristics of tissues under pathological and physiological conditions that include certain chronic eye diseases. Harvesting of single-cell suspensions is one challenge inherent to scRNA-seq procedures. This study aimed to use an optimized method to digest a whole mouse cornea to harvest single-cell suspensions. We utilized five different mouse cornea digestion methods to obtain single-cell suspensions: (1) 5 dissected mouse corneas were cut into pieces (∼0.5 mm) and digested in trypsin for 10 min, and this digestion was repeated for 10 cycles; (2) 5 dissected mouse corneas were cut into pieces and incubated with 5 mg/ml collagenase A at 37 °C for 1h and then further digested in trypsin at 37 °C for 10 min; (3) used the same approach as that used in method 2, but the second digestion step was performed in TrypLE for 20 min; (4) used the same approach as that used in method 2, but the concentration of collagenase A was 2 mg/ml and the incubation time was 2h; (5) used the same approach as that used in method 3, but the corneas were incubated in 2 mg/ml collagenase A at 37 °C for 2h. Trypan blue staining was used to calculate the cell viability and agglomeration rate. The cell types and percentages were determined using immunofluorescence staining. RNA integrity number (RIN) was measured by Agilent 2100. Method 1 showed the lowest cell yield (0.375 × 10⁵), epithelial cell percentage, and less than 70% cell viability, thus not a proper protocol. Method 2 showed the highest cell viability (over 90%), percentage of single-cell (89.53%), and high cell quantity (1.05 × 10⁵). Method 3 had a significantly lower cell viability (55.30%). Cell agglomeration rates of method 4 and 5 reached up to 20% and 13%, and with lower cell viability (72.51%, 59.87%, respectively) and decreased epithelial cell rate compared to method 2 and 3. The results suggest that method 2 (5 mg/ml collagenase A and trypsin) is a preferred protocol for digesting mouse cornea to obtain single-cell suspension which achieves the criterion of single-cell RNA sequencing.

Red-Shifted Coumarin Luciferins for Improved Bioluminescence Imaging

Multicomponent bioluminescence imaging in vivo requires an expanded collection of tissue-penetrant probes. Toward this end, we generated a new class of near-infrared (NIR) emitting coumarin luciferin analogues (CouLuc-3s). The scaffolds were easily accessed from commercially available dyes. Complementary mutant luciferases for the CouLuc-3 analogues were also identified. The brightest probes enabled sensitive imaging in vivo. The CouLuc-3 scaffolds are also orthogonal to popular bioluminescent reporters and can be used for multicomponent imaging applications. Collectively, this work showcases a new set of bioluminescent tools that can be readily implemented for multiplexed imaging in a variety of biological settings.

Identification of Prognostic and Predictive Biomarkers and Druggable Targets among 205 Antioxidant Genes in 21 Different Tumor Types via Data-Mining

(1) Background: Oxidative stress is crucial in carcinogenesis and the response of tumors to treatment. Antioxidant genes are important determinants of resistance to chemotherapy and radiotherapy. We hypothesized that genes involved in the oxidative stress response may be valuable as prognostic biomarkers for the survival of cancer patients and as druggable targets. (2) Methods: We mined the KM Plotter and TCGA Timer2.0 Cistrome databases and investigated 205 antioxidant genes in 21 different tumor types within the context of this investigation. (3) Results: Of 4347 calculations with Kaplan-Meier statistics, 84 revealed statistically significant correlations between high gene expression and worse overall survival (p < 0.05; false discovery rate ≤ 5%). The tumor types for which antioxidant gene expression was most frequently correlated with worse overall survival were renal clear cell carcinoma, renal papillary cell carcinoma, and hepatocellular carcinoma. Seventeen genes were clearly overexpressed in tumors compared to their corresponding normal tissues (p < 0.001), possibly qualifying them as druggable targets (i.e., ALOX5, ALOX5AP, EPHX4, G6PD, GLRX3, GSS, PDIA4, PDIA6, PRDX1, SELENOH, SELENON, STIP1, TXNDC9, TXNDC12, TXNL1, TXNL4A, and TXNRD1). (4) Conclusions: We concluded that a sub-set of antioxidant genes might serve as prognostic biomarkers for overall survival and as druggable targets. Renal and liver tumors may be the most suitable entities for this approach.

Cpt1c Downregulation Causes Plasma Membrane Remodelling and Anthracycline Resistance in Breast Cancer

Breast cancer (BC) is the most common malignancy in women worldwide. While the main systemic treatment option is anthracycline-containing chemotherapy, chemoresistance continues to be an obstacle to patient survival. Carnitine palmitoyltransferase 1C (CPT1C) has been described as a poor-prognosis marker for several tumour types, as it favours tumour growth and hinders cells from entering senescence. At the molecular level, CPT1C has been associated with lipid metabolism regulation and important lipidome changes. Since plasma membrane (PM) rigidity has been associated with reduced drug uptake, we explored whether CPT1C expression could be involved in PM remodelling and drug chemoresistance. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) lipid analysis of PM-enriched fractions of MDA-MB-231 BC cells showed that CPT1C silencing increased PM phospholipid saturation, suggesting a rise in PM rigidity. Moreover, CPT1C silencing increased cell survival against doxorubicin (DOX) treatment in different BC cells due to reduced drug uptake. These findings, further complemented by ROC plotter analysis correlating lower CPT1C expression with a lower pathological complete response to anthracyclines in patients with more aggressive types of BC, suggest CPT1C as a novel predictive biomarker for BC chemotherapy.

Destroying the Shield of Cancer Stem Cells: Natural Compounds as Promising Players in Cancer Therapy

In a scenario where eco-sustainability and a reduction in chemotherapeutic drug waste are certainly a prerogative to safeguard the biosphere, the use of natural products (NPs) represents an alternative therapeutic approach to counteract cancer diseases. The presence of a heterogeneous cancer stem cell (CSC) population within a tumor bulk is related to disease recurrence and therapy resistance. For this reason, CSC targeting presents a promising strategy for hampering cancer recurrence. Increasing evidence shows that NPs can inhibit crucial signaling pathways involved in the maintenance of CSC stemness and sensitize CSCs to standard chemotherapeutic treatments. Moreover, their limited toxicity and low costs for large-scale production could accelerate the use of NPs in clinical settings. In this review, we will summarize the most relevant studies regarding the effects of NPs derived from major natural sources, e.g., food, botanical, and marine species, on CSCs, elucidating their use in pre-clinical and clinical studies.

Biomimetic antimicrobial polymers—Design, characterization, antimicrobial, and novel applications

Biomimetic antimicrobial polymers have been an area of great interest as the need for novel antimicrobial compounds grows due to the development of resistance. These polymers were designed and developed to mimic naturally occurring antimicrobial peptides in both physicochemical composition and mechanism of action. These antimicrobial peptide mimetic polymers have been extensively investigated using chemical, biophysical, microbiological, and computational approaches to gain a deeper understanding of the molecular interactions that drive function. These studies have helped inform SARs, mechanism of action, and general physicochemical factors that influence the activity and properties of antimicrobial polymers. However, there are still lingering questions in this field regarding 3D structural patterning, bioavailability, and applicability to alternative targets. In this review, we present a perspective on the development and characterization of several antimicrobial polymers and discuss novel applications of these molecules emerging in the field. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease.

Network Pharmacology of Adaptogens in the Assessment of Their Pleiotropic Therapeutic Activity

The reductionist concept, based on the ligand–receptor interaction, is not a suitable model for adaptogens, and herbal preparations affect multiple physiological functions, revealing polyvalent pharmacological activities, and are traditionally used in many conditions. This review, for the first time, provides a rationale for the pleiotropic therapeutic efficacy of adaptogens based on evidence from recent gene expression studies in target cells and where the network pharmacology and systems biology approaches were applied. The specific molecular targets and adaptive stress response signaling mechanisms involved in nonspecific modes of action of adaptogens are identified.

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.

Drug resistance in cancer therapy: the Pandora's Box of cancer stem cells

Drug resistance is the main culprit of failure in cancer therapy that may lead to cancer relapse. This resistance mostly originates from rare, but impactful presence of cancer stem cells (CSCs). Ability to self-renewal and differentiation into heterogeneous cancer cells, and harboring morphologically and phenotypically distinct cells are prominent features of CSCs. Also, CSCs substantially contribute to metastatic dissemination. They possess several mechanisms that help them to survive even after exposure to chemotherapy drugs. Although chemotherapy is able to destroy the bulk of tumor cells, CSCs are left almost intact, and make tumor entity resistant to treatment. Eradication of a tumor mass needs complete removal of tumor cells as well as CSCs. Therefore, it is important to elucidate key features underlying drug resistance raised by CSCs in order to apply effective treatment strategies. However, the challenging point that threatens safety and specificity of chemotherapy is the common characteristics between CSCs and normal peers such as signaling pathways and markers. In the present study, we tried to present a comprehensive appraisal on CSCs, mechanisms of their drug resistance, and recent therapeutic methods targeting this type of noxious cells.

Cancer Stem Cells in Ovarian Cancer-A Source of Tumor Success and a Challenging Target for Novel Therapies

Ovarian cancer is the most lethal neoplasm of the female genital organs. Despite indisputable progress in the treatment of ovarian cancer, the problems of chemo-resistance and recurrent disease are the main obstacles for successful therapy. One of the main reasons for this is the presence of a specific cell population of cancer stem cells. The aim of this review is to show the most contemporary knowledge concerning the biology of ovarian cancer stem cells (OCSCs) and their impact on chemo-resistance and prognosis in ovarian cancer patients, as well as to present the treatment options targeted exclusively on the OCSCs. The review presents data concerning the role of cancer stem cells in general and then concentrates on OCSCs. The surface and intracellular OCSCs markers and their meaning both for cancer biology and clinical prognosis, signaling pathways specifically activated in OCSCs, the genetic and epigenetic regulation of OCSCs function including the recent studies on the non-coding RNA regulation, cooperation between OCSCs and the tumor microenvironment (ovarian cancer niche) including very specific environment such as ascites fluid, the role of shear stress, autophagy and metabolic changes for the function of OCSCs, and finally mechanisms of OCSCs escape from immune surveillance, are described and discussed extensively. The possibilities of anti-OCSCs therapy both in experimental settings and in clinical trials are presented, including the recent II phase clinical trials and immunotherapy. OCSCs are a unique population of cancer cells showing a great plasticity, self-renewal potential and resistance against anti-cancer treatment. They are responsible for the progression and recurrence of the tumor. Several completed and ongoing clinical trials have tested different anti-OCSCs drugs which, however, have shown unsatisfactory efficacy in most cases. We propose a novel approach to ovarian cancer diagnosis and therapy.

Detecting spatially co-expressed gene clusters with functional coherence by graph-regularized convolutional neural network

MOTIVATION

Clustering spatial-resolved gene expression is an essential analysis to reveal gene activities in the underlying morphological context by their functional roles. However, conventional clustering analysis does not consider gene expression co-localizations in tissue for detecting spatial expression patterns or functional relationships among the genes for biological interpretation in the spatial context. In this article, we present a convolutional neural network (CNN) regularized by the graph of protein-protein interaction (PPI) network to cluster spatially resolved gene expression. This method improves the coherence of spatial patterns and provides biological interpretation of the gene clusters in the spatial context by exploiting the spatial localization by convolution and gene functional relationships by graph-Laplacian regularization.

RESULTS

In this study, we tested clustering the spatially variable genes or all expressed genes in the transcriptome in 22 Visium spatial transcriptomics datasets of different tissue sections publicly available from 10× Genomics and spatialLIBD. The results demonstrate that the PPI-regularized CNN constantly detects gene clusters with coherent spatial patterns and significantly enriched by gene functions with the state-of-the-art performance. Additional case studies on mouse kidney tissue and human breast cancer tissue suggest that the PPI-regularized CNN also detects spatially co-expressed genes to define the corresponding morphological context in the tissue with valuable insights.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/kuanglab/CNN-PReg.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multi-ligand modified PC@DOX-PA/EGCG micelles effectively inhibit the growth of ER+, PR+ or HER2+ breast cancer

Breast cancer is one of the most common cancers in the world with tumor heterogeneity. Currently, cancer treatment mainly relies on surgical intervention, chemotherapy, and radiotherapy, for which the side effects, drug resistance and cost need to be resolved. In this study, we develop a natural medicine targeted therapy system. Phosphatidylcholine (PC), doxorubicin (DOX), procyanidin (PA), and epigallocatechin gallate (EGCG) are assembled and PC@DOX-PA/EGCG nanoparticles (NPs) are obtained. In addition, the HER2, ER and PR ligands were grafted on the surface of the NPs to acquire the targeted nanoparticles NP-ER, NP-ER-HER2, and NP-ER-HER2-PR. The physicochemical properties of the nanoparticles were detected and it was found that the nanoparticles are spherical and less than 200 nm in diameter. Furthermore, in vitro and in vivo results indicate that the nanoparticles can target BT-474, MCF-7, EMT-6, and MDA-MB-231 breast cancer cells, effectively inhibiting the growth of the breast cancer cells. In short, this research will provide some strategies for the treatment of heterogeneous breast cancer.

The Role of Sphingolipids Metabolism in Cancer Drug Resistance

Drug resistance continues to be one of the major challenges to cure cancer. As research in this field evolves, it has been proposed that numerous bioactive molecules might be involved in the resistance of cancer cells to certain chemotherapeutics. One well-known group of lipids that play a major role in drug resistance are the sphingolipids. Sphingolipids are essential components of the lipid raft domains of the plasma membrane and this structural function is important for apoptosis and/or cell proliferation. Dysregulation of sphingolipids, including ceramide, sphingomyelin or sphingosine 1-phosphate, has been linked to drug resistance in different types of cancer, including breast, melanoma or colon cancer. Sphingolipid metabolism is complex, involving several lipid catabolism with the participation of key enzymes such as glucosylceramide synthase (GCS) and sphingosine kinase 1 (SPHK1). With an overview of the latest available data on this topic and its implications in cancer therapy, this review focuses on the main enzymes implicated in sphingolipids metabolism and their intermediate metabolites involved in cancer drug resistance.

Cancer Stem Cells: An Ever-Hiding Foe

Cancer stem cells are a population of cells enable to reproduce the original phenotype of the tumor and capable to self-renewal, which is crucial for tumor proliferation, differentiation, recurrence, and metastasis, as well as chemoresistance. Therefore, the cancer stem cells (CSCs) have become one of the main targets for anticancer therapy and many ongoing clinical trials test anti-CSCs efficacy of plenty of drugs. This chapter describes CSCs starting from general description of this cell population, through CSCs markers, signaling pathways, genetic and epigenetic regulation, role of epithelial-mesenchymal transition (EMT) transition and autophagy, cooperation with microenvironment (CSCs niche), and finally role of CSCs in escaping host immunosurveillance against cancer.

Photoactivatable Reporter to Perform Multiplexed and Temporally Controlled Measurements of Kinase and Protease Activity in Single Cells

Peptide bioreporters were developed to perform multiplexed measurements of the activation of epidermal growth factor receptor kinase (EGFR), Akt kinase (Akt/protein kinase B), and proteases/peptidases in single cells. The performance characteristics of the three reporters were assessed by measuring the reporter's proteolytic stability, kinetic constants for EGFR and Akt, and dephosphorylation rate. The reporter displaying optimal performance was composed of 6-carboxyfluorescein (6-FAM) on the peptide N-terminus, an Akt substrate sequence employing a threonine phosphorylation site for Akt, followed by a tri-D arginine linker, and finally an EGFR substrate sequence bearing a phosphatase-resistant 7-(S)-hydroxy-1,2,3,4-tetrahydroisoquinoline-3-carboxylic acid (L-htc) residue as the EGFR phosphorylation site. Importantly, use of a single electrophoretic condition separated the mono- and diphosphorylated products as well as proteolytic forms permitting the quantitation of multiple enzyme activities simultaneously using a single reporter. Because the Akt and EGFR substrates were linked, a known ratio (EGFR/Akt) of the reporter was loaded into cells. A photoactivatable version of the reporter was synthesized by adding two 4,5-dimethoxy-2-nitrobenzyl (DMNB) moieties to mask the EGFR and Akt phosphorylation sites. The DMNB moieties were readily photocleaved following exposure to 360 nm light, unmasking the phosphorylation sites on the reporter. The new photoactivatable reporter permitted multiplexed measurements of kinase signaling and proteolytic degradation in single cells in a temporally controlled manner. This work will facilitate the development of a new generation of multiplexed activity-based reporters capable of light-initiated measurement of enzymatic activity in single cells.

Single-Cell Microgels for Diagnostics and Therapeutics

Cell encapsulation within hydrogel droplets is transforming what is feasible in multiple fields of biomedical science such as tissue engineering and regenerative medicine, in vitro modeling, and cell-based therapies. Recent advances have allowed researchers to miniaturize material encapsulation complexes down to single-cell scales, where each complex, termed a single-cell microgel, contains only one cell surrounded by a hydrogel matrix while remaining <100 μm in size. With this achievement, studies requiring single-cell resolution are now possible, similar to those done using liquid droplet encapsulation. Of particular note, applications involving long-term in vitro cultures, modular bioinks, high-throughput screenings, and formation of 3D cellular microenvironments can be tuned independently to suit the needs of individual cells and experimental goals. In this progress report, an overview of established materials and techniques used to fabricate single-cell microgels, as well as insight into potential alternatives is provided. This focused review is concluded by discussing applications that have already benefited from single-cell microgel technologies, as well as prospective applications on the cusp of achieving important new capabilities.

Tumor-suppressive function of EZH2 is through inhibiting glutaminase

Tumors can use metabolic reprogramming to survive nutrient stress. Epigenetic regulators play a critical role in metabolic adaptation. Here we screened a sgRNA library to identify epigenetic regulators responsible for the vulnerability of colorectal cancer (CRC) cells to glucose deprivation and found that more EZH2-knockout cells survived glucose deprivation. Then, we showed that EZH2 expression was significantly downregulated in response to glucose deprivation in a glucose-sensitive CRC cell line, and EZH2-knockdown cells were more resistant to glucose deprivation. Mechanistically, EZH2 deficiency upregulated the expression of glutaminase (GLS) and promoted the production of glutamate, which in turn led to increased synthesis of intracellular glutathione (GSH) and eventually attenuated the reactive oxygen species (ROS)-mediated cell death induced by glucose deprivation. Although EZH2 functioned as an oncogene in cancer progression and EZH2 knockout abolished colorectal cancer development in a mouse model, here we revealed a mechanistic link between EZH2 and metabolic reprogramming via the direct regulation of GLS expression and observed a negative correlation between EZH2 and GLS expression in colorectal cancer tissues. These findings further confirmed the importance of heterogeneity, provided an explanation for the clinical tolerance of cancer cells to EZH2 inhibitors from the perspective of metabolism, and proposed the possibility of combining EZH2 inhibitors and glutamine metabolism inhibitors for the treatment of cancer.

On-chip rapid drug screening of leukemia cells by acoustic streaming

Rapid and personalized single-cell drug screening testing plays an essential role in acute myeloid leukemia drug combination chemotherapy. Conventional chemotherapeutic drug screening is a time-consuming process because of the natural resistance of cell membranes to drugs, and there are still great challenges related to using technologies that change membrane permeability such as sonoporation in high-throughput and precise single-cell drug screening with minimal damage. In this study, we proposed an acoustic streaming-based non-invasive single-cell drug screening acceleration method, using high-frequency acoustic waves (>10 MHz) in a concentration gradient microfluidic device. High-frequency acoustics leads to increased difficulties in inducing cavitation and generates acoustic streaming around each single cell. Therefore, single-cell membrane permeability is non-invasively increased by the acoustic pressure and acoustic streaming-induced shear force, which significantly improves the drug uptake process. In the experiment, single human myeloid leukemia mononuclear (THP-1) cells were trapped by triangle cell traps in concentration gradient chips with different cytarabine (Ara-C) drug concentrations. Due to this dual acoustic effect, the drugs affect cell viability in less than 30 min, which is faster than traditional methods (usually more than 24 h). This dual acoustic effect-based drug delivery strategy has the potential to save time and reduce the cost of drug screening, when combined with microfluidic technology for multi-concentration drug screening. This strategy offers enormous potential for use in multiple drug screening or efficient drug combination screening in individualized/personalized treatments, which can greatly improve efficiency and reduce costs.

Current understanding of epigenetics mechanism as a novel target in reducing cancer stem cells resistance

At present, after extensive studies in the field of cancer, cancer stem cells (CSCs) have been proposed as a major factor in tumor initiation, progression, metastasis, and recurrence. CSCs are a subpopulation of bulk tumors, with stem cell-like properties and tumorigenic capabilities, having the abilities of self-renewal and differentiation, thereby being able to generate heterogeneous lineages of cancer cells and lead to resistance toward anti-tumor treatments. Highly resistant to conventional chemo- and radiotherapy, CSCs have heterogeneity and can migrate to different organs and metastasize. Recent studies have demonstrated that the population of CSCs and the progression of cancer are increased by the deregulation of different epigenetic pathways having effects on gene expression patterns and key pathways connected with cell proliferation and survival. Further, epigenetic modifications (DNA methylation, histone modifications, and RNA methylations) have been revealed to be key drivers in the formation and maintenance of CSCs. Hence, identifying CSCs and targeting epigenetic pathways therein can offer new insights into the treatment of cancer. In the present review, recent studies are addressed in terms of the characteristics of CSCs, the resistance thereof, and the factors influencing the development thereof, with an emphasis on different types of epigenetic changes in genes and main signaling pathways involved therein. Finally, targeted therapy for CSCs by epigenetic drugs is referred to, which is a new approach in overcoming resistance and recurrence of cancer.

Imputation of spatially-resolved transcriptomes by graph-regularized tensor completion

High-throughput spatial-transcriptomics RNA sequencing (sptRNA-seq) based on in-situ capturing technologies has recently been developed to spatially resolve transcriptome-wide mRNA expressions mapped to the captured locations in a tissue sample. Due to the low RNA capture efficiency by in-situ capturing and the complication of tissue section preparation, sptRNA-seq data often only provides an incomplete profiling of the gene expressions over the spatial regions of the tissue. In this paper, we introduce a graph-regularized tensor completion model for imputing the missing mRNA expressions in sptRNA-seq data, namely FIST, Fast Imputation of Spatially-resolved transcriptomes by graph-regularized Tensor completion. We first model sptRNA-seq data as a 3-way sparse tensor in genes (p-mode) and the (x, y) spatial coordinates (x-mode and y-mode) of the observed gene expressions, and then consider the imputation of the unobserved entries or fibers as a tensor completion problem in Canonical Polyadic Decomposition (CPD) form. To improve the imputation of highly sparse sptRNA-seq data, we also introduce a protein-protein interaction network to add prior knowledge of gene functions, and a spatial graph to capture the the spatial relations among the capture spots. The tensor completion model is then regularized by a Cartesian product graph of protein-protein interaction network and the spatial graph to capture the high-order relations in the tensor. In the experiments, FIST was tested on ten 10x Genomics Visium spatial transcriptomic datasets of different tissue sections with cross-validation among the known entries in the imputation. FIST significantly outperformed the state-of-the-art methods for single-cell RNAseq data imputation. We also demonstrate that both the spatial graph and PPI network play an important role in improving the imputation. In a case study, we further analyzed the gene clusters obtained from the imputed gene expressions to show that the imputations by FIST indeed capture the spatial characteristics in the gene expressions and reveal functions that are highly relevant to three different kinds of tissues in mouse kidney.

Biological tissues are composed of different types of structurally organized cell units playing distinct functional roles. The exciting new spatial gene expression profiling methods have enabled the analysis of spatially resolved transcriptomes to understand the spatial and functional characteristics of these cells in the context of eco-environment of tissue. Due to the technical limitations, spatial transcriptomics data suffers from only sparsely measured mRNAs by in-situ capture and possibly missing spots in tissue regions that entirely failed fixing and permeabilizing RNAs. Our method, FIST (Fast Imputation of Spatially-resolved transcriptomes by graph-regularized Tensor completion), focuses on the spatial and high-sparsity nature of spatial transcriptomics data by modeling the data as a 3-way gene-by-(x, y)-location tensor and a product graph of a spatial graph and a protein-protein interaction network. Our comprehensive evaluation of FIST on ten 10x Genomics Visium spatial genomics datasets and comparison with the methods for single-cell RNA sequencing data imputation demonstrate that FIST is a better method more suitable for spatial gene expression imputation. Overall, we found FIST a useful new method for analyzing spatially resolved gene expressions based on novel modeling of spatial and functional information.

Single- versus Dual-Targeted Nanoparticles with Folic Acid and Biotin for Anticancer Drug Delivery

Cancer is one of the major causes of death worldwide and its treatment remains very challenging. The effectiveness of cancer therapy significantly depends upon tumour-specific delivery of the drug. Nanoparticle drug delivery systems have been developed to avoid the side effects of the conventional chemotherapy. However, according to the most recent recommendations, future nanomedicine should be focused mainly on active targeting of nanocarriers based on ligand-receptor recognition, which may show better efficacy than passive targeting in human cancer therapy. Nevertheless, the efficacy of single-ligand nanomedicines is still limited due to the complexity of the tumour microenvironment. Thus, the NPs are improved toward an additional functionality, e.g., pH-sensitivity (advanced single-targeted NPs). Moreover, dual-targeted nanoparticles which contain two different types of targeting agents on the same drug delivery system are developed. The advanced single-targeted NPs and dual-targeted nanocarriers present superior properties related to cell selectivity, cellular uptake and cytotoxicity toward cancer cells than conventional drug, non-targeted systems and single-targeted systems without additional functionality. Folic acid and biotin are used as targeting ligands for cancer chemotherapy, since they are available, inexpensive, nontoxic, nonimmunogenic and easy to modify. These ligands are used in both, single- and dual-targeted systems although the latter are still a novel approach. This review presents the recent achievements in the development of single- or dual-targeted nanoparticles for anticancer drug delivery.

Activity of Cordycepin From Cordyceps sinensis Against Drug-Resistant Tumor Cells as Determined by Gene Expression and Drug Sensitivity Profiling

Cordycepin is one of the substantial components of the parasitic fungus Cordyceps sinensis as well as other Cordyceps species. It exerts various effects such as antimetastatic, antiinflammatory, antioxidant, and neuroprotective activities. Assorted studies revealed in vitro and in vivo anticancer influence of cordycepin and put forward its potential for cancer therapy. However, the role of multidrug resistance-associated mechanisms for the antitumor effect of cordycepin has not been investigated in great detail thus far. Therefore, we searched cordycepin’s cytotoxicity with regard to well-known anticancer drug resistance mechanisms, including ABCB1, ABCB5, ABCC1, ABCG2, EGFR, and TP53, and identified putative molecular determinants related to the cellular responsiveness of cordycepin. Bioinformatic analyses of NCI microarray data and gene promoter transcription factor binding motif analyses were performed to specify the mechanisms of cordycepin towards cancer cells. COMPARE and hierarchical analyses led to the detection of the genes involved in cordycepin’s cytotoxicity and sensitivity and resistance of cell lines towards cordycepin. Tumor-type dependent response and cross-resistance profiles were further unravelled. We found transcription factors potentially involved in the common transcriptional regulation of the genes identified by COMPARE analyses. Cordycepin bypassed resistance mediated by the expression of ATP-binding cassete (ABC) transporters (P-gp, ABCB5, ABCC1 and BCRP) and mutant epidermal growth factor receptor (EGFR). The drug sensitivity profiles of several DNA Topo I and II inhibitors were significantly correlated with those of cordycepin’s activity. Among eight different tumor types, prostate cancer was the most sensitive, whereas renal carcinoma was the most resistant to cordycepin. NF-κB was discovered as a common transcription factor. The potential of cordycepin is set forth as a potential new drug lead by bioinformatic evaluations. Further experimental studies are warranted for better understanding of cordycepin’s activity against cancer.

The Chemosensitizing Role of Metformin in Anti-Cancer Therapy

Chemoresistance, which leads to the failure of chemotherapy and further tumor recurrence, presents the largest hurdle for the success of anti-cancer therapy. In recent years, metformin, a widely used first-line antidiabetic drug, has attracted increasing attention for its anti-cancer effects. A growing body of evidence indicates that metformin can sensitize tumor responses to different chemotherapeutic drugs, such as hormone modulating drugs, anti-metabolite drugs, antibiotics, and DNA-damaging drugs via selective targeting of Cancer Stem Cells (CSCs), improving the hypoxic microenvironment, and by suppressing tumor metastasis and inflammation. In addition, metformin may regulate metabolic programming, induce apoptosis, reverse Epithelial to Mesenchymal Transition (EMT), and Multidrug Resistance (MDR). In this review, we summarize the chemosensitization effects of metformin and focus primarily on its molecular mechanisms in enhancing the sensitivity of multiple chemotherapeutic drugs, through targeting of mTOR, ERK/P70S6K, NF-κB/HIF-1 α, and Mitogen- Activated Protein Kinase (MAPK) signaling pathways, as well as by down-regulating the expression of CSC genes and Pyruvate Kinase isoenzyme M2 (PKM2). Through a comprehensive understanding of the molecular mechanisms of chemosensitization provided in this review, the rationale for the use of metformin in clinical combination medications can be more systematically and thoroughly explored for wider adoption against numerous cancer types.>.

Organotypic Models in Drug Development "Tumor Models and Cancer Systems Biology for the Investigation of Anticancer Drugs and Resistance Development"

The landscape of cancer treatment has improved over the past decades, aiming to reduce systemic toxicity and enhance compatibility with the quality of life of the patient. However, at the therapeutic level, metastatic cancer remains hugely challenging, based on the almost inevitable emergence of therapy resistance. A small subpopulation of cells able to survive drug treatment termed the minimal residual disease may either harbor resistance-associated mutations or be phenotypically resistant, allowing them to regrow and become the dominant population in the therapy-resistant tumor. Characterization of the profile of minimal residual disease represents the key to the identification of resistance drivers that underpin cancer evolution. Therapeutic regimens must, therefore, be dynamic and tailored to take into account the emergence of resistance as tumors evolve within a complex microenvironment in vivo. This requires the adoption of new technologies based on the culture of cancer cells in ways that more accurately reflect the intratumor microenvironment, and their analysis using omics and system-based technologies to enable a new era in the diagnostics, classification, and treatment of many cancer types by applying the concept "from the cell plate to the patient." In this chapter, we will present and discuss 3D model building and use, and provide comprehensive information on new genomic techniques that are increasing our understanding of drug action and the emergence of resistance.

Tumor heterogeneity in muscle-invasive bladder cancer

Muscle-invasive bladder cancer (MIBC), a highly heterogeneous disease, shows genomic instability and a high mutation rate. Clinical outcomes are variable and responses to conventional chemotherapy differ among patients (due to inter-patient tumor heterogeneity and inter-tumor heterogeneity) and even within each individual tumor (intra-tumor heterogeneity). Emerging evidence indicates that tumor heterogeneity may play an important role in cancer progression, resistance to therapy, and metastasis. Comprehensive molecular subtyping classifies MIBC into distinct categories that have potential to guide prognosis, patient stratification, and treatment. Genomic characterization of time-series analyses at the single cell level, and of cell-free circulating tumor DNA or circulating tumor cells, are emerging technologies that enable dissection of the complex clonal architecture of MIBC. This review provides insight into the clinical significance of the molecular mechanisms underlying heterogeneity, focusing on inter- and intra-tumor heterogeneity, with special emphasis on molecular classification and methods used to analyze the complex patterns involved.

The Effects of Single Nucleotide Polymorphisms in Cancer RNAi Therapies

Simple Summary

Despite the recent progress in RNAi delivery of siRNA-based therapeutics for cancer therapy, the presence of single nucleotide polymorphisms (SNPs) in the general population could dramatically reduce the effectiveness of RNAi therapy. Their ubiquitous presence can also lead to unpredictable and adverse side effects. Because both SNPs and somatic mosaicisms have also been implicated in a number of human diseases including cancer, however, these specific changes offer the ability to selectively and efficiently target cancer cells. Here, we discuss how SNPs influence the development and success of novel anticancer RNAi therapies.

Abstract

Tremendous progress in RNAi delivery methods and design has allowed for the effective development of siRNA-based therapeutics that are currently under clinical investigation for various cancer treatments. This approach has the potential to revolutionize cancer therapy by providing the ability to specifically downregulate or upregulate the mRNA of any protein of interest. This exquisite specificity, unfortunately, also has a downside. Genetic variations in the human population are common because of the presence of single nucleotide polymorphisms (SNPs). SNPs lead to synonymous and non-synonymous changes and they occur once in every 300 base pairs in both coding and non-coding regions in the human genome. Much less common are the somatic mosaicism variations associated with genetically distinct populations of cells within an individual that is derived from postzygotic mutations. These heterogeneities in the population can affect the RNAi’s efficacy or more problematically, which can lead to unpredictable and sometimes adverse side effects. From a more positive viewpoint, both SNPs and somatic mosaicisms have also been implicated in human diseases, including cancer, and these specific changes could offer the ability to effectively and, more importantly, selectively target the cancer cells. In this review, we discuss how SNPs in the human population can influence the development and success of novel anticancer RNAi therapies and the importance of why SNPs should be carefully considered.

Putative molecular determinants mediating sensitivity or resistance towards carnosic acid tumor cell responses

BACKGROUND

Carnosic acid (CA) is one of the main constituents in rosemary extract. It possesses valuable pharmacological properties, including anti-oxidant, anti-inflammatory, anti-microbial and anti-cancer activities. Numerous in vitro and in vivo studies investigated the anticancer profile of CA and emphasized its potentiality for cancer treatment. Nevertheless, the role of multidrug-resistance (MDR) related mechanisms for CA's anticancer effect is not yet known.

PURPOSE

We investigated the cytotoxicity of CA against known mechanisms of anticancer drug resistance (P-gp, ABCB5, BCRP, EGFR and p53) and determined novel putative molecular factors associated with cellular response towards CA.

STUDY DESIGN

Cytotoxicity assays, bioinformatic analysis, flow cytometry and western blotting were performed to identify the mode of action of CA towards cancer cells.

METHODS

The cytotoxicity to CA was assessed using the resazurin assays in cell lines expressing the mentioned resistance mechanisms. A pharmacogenomic characterization of the NCI 60 cell line panel was applied via COMPARE, hierarchical cluster and network analyses. Flow cytometry was used to detect cellular mode of death and ROS generation. Changes in proteins-related to apoptosis were determined by Western blotting.

RESULTS

Cell lines expressing ABC transporters (P-gp, BCRP or ABCB5), mutant EGFR or p53 were not cross-resistant to CA compared to their parental counterparts. By pharmacogenomic approaches, we identified genes that belong to different functional groups (e.g. signal transduction, regulation of cytoskeleton and developmental regulatory system). These genes were predicted as molecular determinants that mediate CA tumor cellular responses. The top affected biofunctions included cellular development, cellular proliferation and cellular death and survival. The effect of CA-mediated apoptosis in leukemia cells, which were recognized as the most sensitive tumor type, was confirmed via flow cytometry and western blot analysis.

CONCLUSION

CA may provide a novel treatment option to target refractory tumors and to effectively cooperate with established chemotherapy. Using pharmacogenomic approaches and network pharmacology, the relationship between cancer complexity and multi-target potentials of CA was analyzed and many putative molecular determinants were identified. They could serve as novel targets for CA and further studies are needed to translate the possible implications to clinical cancer treatment.

Counteracting Chemoresistance with Metformin in Breast Cancers: Targeting Cancer Stem Cells

Despite the leaps and bounds in achieving success in the management and treatment of breast cancers through surgery, chemotherapy, and radiotherapy, breast cancer remains the most frequently occurring cancer in women and the most common cause of cancer-related deaths among women. Systemic therapeutic approaches, such as chemotherapy, although beneficial in treating and curing breast cancer subjects with localized breast tumors, tend to fail in metastatic cases of the disease due to (a) an acquired resistance to the chemotherapeutic drug and (b) the development of intrinsic resistance to therapy. The existence of cancer stem cells (CSCs) plays a crucial role in both acquired and intrinsic chemoresistance. CSCs are less abundant than terminally differentiated cancer cells and confer chemoresistance through a unique altered metabolism and capability to evade the immune response system. Furthermore, CSCs possess active DNA repair systems, transporters that support multidrug resistance (MDR), advanced detoxification processes, and the ability to self-renew and differentiate into tumor progenitor cells, thereby supporting cancer invasion, metastasis, and recurrence/relapse. Hence, current research is focusing on targeting CSCs to overcome resistance and improve the efficacy of the treatment and management of breast cancer. Studies revealed that metformin (1, 1-dimethylbiguanide), a widely used anti-hyperglycemic agent, sensitizes tumor response to various chemotherapeutic drugs. Metformin selectively targets CSCs and improves the hypoxic microenvironment, suppresses the tumor metastasis and inflammation, as well as regulates the metabolic programming, induces apoptosis, and reverses epithelial-mesenchymal transition and MDR. Here, we discuss cancer (breast cancer) and chemoresistance, the molecular mechanisms of chemoresistance in breast cancers, and metformin as a chemo-sensitizing/re-sensitizing agent, with a particular focus on breast CSCs as a critical contributing factor to acquired and intrinsic chemoresistance. The review outlines the prospects and directions for a better understanding and re-purposing of metformin as an anti-cancer/chemo-sensitizing drug in the treatment of breast cancer. It intends to provide a rationale for the use of metformin as a combinatory therapy in a clinical setting.

A guide for bioinformaticians: 'omics-based drug discovery for precision oncology

Bioinformatics-centric drug development is inevitable in the era of precision medicine. Clinical 'omics information, including genomics, epigenomics, transcriptomics, and proteomics, provides the most comprehensive molecular landscape in which each patient's pathological history is delineated. Hence, the capability of bioinformaticians to manage integrative 'omics data is crucial to current drug development. Bioinformatics can accelerate drug development from initial time-consuming discoveries to the clinical stage by providing information-guided solutions. However, many bioinformaticians do not have opportunities to participate in drug discovery programs. As a starting point for bioinformaticians with no prior drug development experience, here we discuss bioinformatics applications during drug development with a focus on working-level omics-based methodologies.

Indirect co-culture of lung carcinoma cells with hyperthermia-treated mesenchymal stem cells influences tumor spheroid growth in a collagen-based 3-dimensional microfluidic model

BACKGROUND

Mesenchymal stem cells (MSCs) have paradoxically been reported to exert either pro- or anti-tumor effects in vitro. Hyperthermia, in combination with chemotherapy, has tumor-inhibiting effects; however, its role, together with MSCs, so far is not well understood. Furthermore, a lot of research is conducted using conventional 2-dimensional in vitro models that do not mimic the actual tumor microenvironment.

AIM

In light of this fact, an indirect method of co-culturing human amniotic membrane-derived MSCs (AMMSCs) with collagen-encapsulated human lung carcinoma cells (A549) was performed using a 3-dimensional (3D) tumor-on-chip device.

METHODS

The conditioned medium of AMMSCs (AMMSC-CM) or heat-treated AMMSCs (heat-AMMSC-CM) was utilized to create indirect co-culture conditions. Tumor spheroid growth characterization, immunocytochemistry and cytotoxicity assays, and anti-cancer peptide (P1) screening were performed to determine the effects of the conditioned medium.

RESULTS

The A549 cells cultured inside the 3D microfluidic chip developed into multicellular tumor spheroids over five days of culture. The AMMSC-CM, contrary to previous reports claiming its tumor-inhibiting potential, led to significant proliferation of tumor spheroids. Heat-AMMSC-CM led to reductions in both spheroid diameter and cell proliferation. The medium containing the P1 peptide was found to be the least cytotoxic to tumor spheroids in co-culture compared with the monoculture and heat-co-culture groups.

CONCLUSIONS

Hyperthermia, in combination with the anticancer peptide, exhibited highest cytotoxic effects. This study highlights the growing importance of 3D microfluidic tumor models for testing stem-cell-based and other anti-cancer therapies.

Single-cell sequencing of miRNAs: A modified technology

The recent development of next-generation sequencing technologies has offered valuable insights into individual cells. This technology is centered on the characterization of single cells for epigenomics, genomics, and transcriptomics. Ever since the first report appeared in 2009, the single-cell RNA-sequencing saga started to explore deeper into the mechanics intrigued within a single cell. microRNA (miRNA) has been increasingly recognized as an essential molecule triggering an additional layer for gene regulation. Therefore, single-cell sequencing of miRNAs is crucial to explore the logical riddles surrounding the epigenomics, genomics, and transcriptomics of an individual cell. Scientists from the Vienna Biocenter Campus have lately performed single-cell sequencing of miRNAs in the fly, Drosophila, and nematode, Caenorhabditis elegans. In this review, we present the latest scientific explorations supported by all-inclusive data on this novel subject matter of next-generation sequencing.

8,8-bis-(Dihydroconiferyl)-diferulate displayed impressive cytotoxicity towards a panel of human and animal cancer cells

BACKGROUND

Recalcitrant cancers appear as a major obstacle to chemotherapy, prompting scientists to intensify the search for novel drugs to tackle the cell lines expressing multi-drug resistant (MDR) phenotypes.

PURPOSE

The purpose of this study was to evaluate the antiproliferative potential of a ferrulic acid derivative, 8,8-bis-(dihydroconiferyl)-diferulate (DHCF2) on a panel of 18 cancer cell lines, including various sensitive and drug-resistant phenotypes, belonging to human and animals. The mode of induction of cell death by this compound was further studied.

METHODS

The antiproliferative activity, autophagy, ferroptotic and necroptotic cell death were evaluated by the resazurin reduction assay (RRA). CCRF-CEM leukemia cells were used for all mechanistic studies. A caspase-Glo assay was applied to evaluate the activity of caspases. Cell cycle analysis (PI staining), apoptosis (annexin V/PI staining), mitochondrial membrane potential (MMP) (JC-1) and reactive oxygen species (ROS) (H₂DCFH-DA) were assessed by flow cytometry.

RESULTS

DHCF2 demonstrated impressive cytotoxic effects towards the 18 cancer cell lines tested, with IC₅₀ values all below 6.5 µM. The obtained IC₅₀ values were in the range of 1.17 µM (towards CCRF-CEM leukemia cells) to 6.34 µM (towards drug-resistant HCT116 p53^-/- human colon adenocarcinoma cells) for DHCF2 and from 0.02 µM (against CCRF-CEM cells) to 122.96 µM (against multidrug-resistant CEM/ADR5000 leukemia cells) for the reference drug, doxorubicin. DHCF2 had IC₅₀ values lower than those of doxorubicin, against CEM/ADR5000 cells and on some melanoma cell lines, such as MaMel-80a cells, Mel-2a cells, MV3 cells and SKMel-505 cells. DHCF2 induced autophagy as well as apoptosis in CCRF-CEM cells though caspases activation, MMP alteration and increase of ROS production.

CONCLUSION

The studied diferulic acid, DHCF2, is a promising antiproliferative compound. It deserves further indepth investigations with the ultimate aim to develop a novel drug to fight cancer drug resistance.

Alleviation of Multidrug Resistance by Flavonoid and Non-Flavonoid Compounds in Breast, Lung, Colorectal and Prostate Cancer

The aim of the manuscript is to discuss the influence of plant polyphenols in overcoming multidrug resistance in four types of solid cancers (breast, colorectal, lung and prostate cancer). Effective treatment requires the use of multiple toxic chemotherapeutic drugs with different properties and targets. However, a major cause of cancer treatment failure and metastasis is the development of multidrug resistance. Potential mechanisms of multidrug resistance include increase of drug efflux, drug inactivation, detoxification mechanisms, modification of drug target, inhibition of cell death, involvement of cancer stem cells, dysregulation of miRNAs activity, epigenetic variations, imbalance of DNA damage/repair processes, tumor heterogeneity, tumor microenvironment, epithelial to mesenchymal transition and modulation of reactive oxygen species. Taking into consideration that synthetic multidrug resistance agents have failed to demonstrate significant survival benefits in patients with different types of cancer, recent research have focused on beneficial effects of natural compounds. Several phenolic compounds (flavones, phenolcarboxylic acids, ellagitannins, stilbens, lignans, curcumin, etc.) act as chemopreventive agents due to their antioxidant capacity, inhibition of proliferation, survival, angiogenesis, and metastasis, modulation of immune and inflammatory responses or inactivation of pro-carcinogens. Moreover, preclinical and clinical studies revealed that these compounds prevent multidrug resistance in cancer by modulating different pathways. Additional research is needed regarding the role of phenolic compounds in the prevention of multidrug resistance in different types of cancer.

Preserving Single Cells in Space and Time for Analytical Assays

Analytical assays performed within clinical laboratories influence roughly 70% of all medical decisions by facilitating disease detection, diagnosis, and management. Both in clinical and academic research laboratories, single-cell assays permit measurement of cell diversity and identification of rare cells, both of which are important in the understanding of disease pathogenesis. For clinically utility, the single-cell assays must be compatible with the clinical workflow steps of sample collection, sample transportation, pre-analysis processing, and single-cell assay; therefore, it is paramount to preserve cells in a state that resembles that in vivo rather than measuring signaling behaviors initiated in response to stressors such as sample collection and processing. To address these challenges, novel cell fixation (and more broadly, cell preservation) techniques incorporate programmable fixation times, reversible bond formation and cleavage, chemoselective reactions, and improved analyte recovery. These technologies will further the development of individualized, precision therapies for patients to yield improved clinical outcomes.

Repurposing of plant alkaloids for cancer therapy: Pharmacology and toxicology

Drug repurposing (or repositioning) is an emerging concept to use old drugs for new treatment indications. Phytochemicals isolated from medicinal plants have been largely neglected in this context, although their pharmacological activities have been well investigated in the past, and they may have considerable potentials for repositioning. A grand number of plant alkaloids inhibit syngeneic or xenograft tumor growth in vivo. Molecular modes of action in cancer cells include induction of cell cycle arrest, intrinsic and extrinsic apoptosis, autophagy, inhibition of angiogenesis and glycolysis, stress and anti-inflammatory responses, regulation of immune functions, cellular differentiation, and inhibition of invasion and metastasis. Numerous underlying signaling processes are affected by plant alkaloids. Furthermore, plant alkaloids suppress carcinogenesis, indicating chemopreventive properties. Some plant alkaloids reveal toxicities such as hepato-, nephro- or genotoxicity, which disqualifies them for repositioning purposes. Others even protect from hepatotoxicity or cardiotoxicity of xenobiotics and established anticancer drugs. The present survey of the published literature clearly demonstrates that plant alkaloids have the potential for repositioning in cancer therapy. Exploitation of the chemical diversity of natural alkaloids may enrich the candidate pool of compounds for cancer chemotherapy and -prevention. Their further preclinical and clinical development should follow the same stringent rules as for any other synthetic drug as well. Prospective randomized, placebo-controlled clinical phase I and II trials should be initiated to unravel the full potential of plant alkaloids for drug repositioning.

Editorial focus: understanding off-target effects as the key to successful RNAi therapy

With the first RNA interference (RNAi) drug (ONPATTRO (patisiran)) on the market, we witness the RNAi therapy field reaching a critical turning point, when further improvements in drug candidate design and delivery pipelines should enable fast delivery of novel life changing treatments to patients. Nevertheless, ignoring parallel development of RNAi dedicated in vitro pharmacological profiling aiming to identify undesirable off-target activity may slow down or halt progress in the RNAi field. Since academic research is currently fueling the RNAi development pipeline with new therapeutic options, the objective of this article is to briefly summarize the basics of RNAi therapy, as well as to discuss how to translate basic research into better understanding of related drug candidate safety profiles early in the process.

Moonshot Objectives: Catalyze New Scientific Breakthroughs-Proteogenomics

Breaking down the silos between disciplines to accelerate the pace of cancer research is a key paradigm for the Cancer Moonshot. Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids-DNA, RNA, and their modifications-and a focus on proteins and protein function. Proteogenomics represents a fusion of those two approaches, leveraging the strengths of each to provide a more integrated vision of the flow of information from DNA to RNA to protein and eventually function at the molecular level. Proteogenomic studies have been incorporated into multiple activities associated with the Cancer Moonshot, demonstrating substantial added value. Innovative study designs integrating genomic, transcriptomic, and proteomic data, particularly those using clinically relevant samples and involving clinical trials, are poised to provide new insights regarding cancer risk, progression, and response to therapy.

Intratumor heterogeneity inferred from targeted deep sequencing as a prognostic indicator

Tumor genetic heterogeneity may underlie poor clinical outcomes because diverse subclones could be comprised of metastatic and drug resistant cells. Targeted deep sequencing has been used widely as a diagnostic tool to identify actionable mutations in cancer patients. In this study, we evaluated the clinical utility of estimating tumor heterogeneity using targeted panel sequencing data. We investigated the prognostic impact of a tumor heterogeneity (TH) index on clinical outcomes, using mutational profiles from targeted deep sequencing data acquired from 1,352 patients across 8 cancer types. The TH index tended to be increased in high pathological stage disease in several cancer types, indicating clonal expansion of cancer cells as tumor progression proceeds. In colorectal cancer patients, TH index values also correlated significantly with clinical prognosis. Integration of the TH index with genomic and clinical features could improve the power of risk prediction for clinical outcomes. In conclusion, deep sequencing to determine the TH index could serve as a promising prognostic indicator in cancer patients.

Biopiracy versus One-World Medicine-From colonial relicts to global collaborative concepts

BACKGROUND

Practices of biopiracy to use genetic resources and indigenous knowledge by Western companies without benefit-sharing of those, who generated the traditional knowledge, can be understood as form of neocolonialism.

HYPOTHESIS

The One-World Medicine concept attempts to merge the best of traditional medicine from developing countries and conventional Western medicine for the sake of patients around the globe.

STUDY DESIGN

Based on literature searches in several databases, a concept paper has been written. Legislative initiatives of the United Nations culminated in the Nagoya protocol aim to protect traditional knowledge and regulate benefit-sharing with indigenous communities. The European community adopted the Nagoya protocol, and the corresponding regulations will be implemented into national legislation among the member states. Despite pleasing progress, infrastructural problems of the health care systems in developing countries still remain. Current approaches to secure primary health care offer only fragmentary solutions at best. Conventional medicine from industrialized countries cannot be afforded by the impoverished population in the Third World. Confronted with exploding costs, even health systems in Western countries are endangered to burst. Complementary and alternative medicine (CAM) is popular among the general public in industrialized countries, although the efficacy is not sufficiently proven according to the standards of evidence-based medicine. CAM is often available without prescription as over-the-counter products with non-calculated risks concerning erroneous self-medication and safety/toxicity issues. The concept of integrative medicine attempts to combine holistic CAM approaches with evidence-based principles of conventional medicine.

CONCLUSION

To realize the concept of One-World Medicine, a number of standards have to be set to assure safety, efficacy and applicability of traditional medicine, e.g. sustainable production and quality control of herbal products, performance of placebo-controlled, double-blind, randomized clinical trials, phytovigilance, as well as education of health professionals and patients.

Profiling Single Cancer Cells with Volatolomics Approach

Single-cell analysis is a rapidly evolving to characterize molecular information at the individual cell level. Here, we present a new approach with the potential to overcome several key challenges facing the currently available techniques. The approach is based on the identification of volatile organic compounds (VOCs), viz. organic compounds having relatively high vapor pressure, emitted to the cell's headspace. This concept is demonstrated using lung cancer cells with various p53 genetic status and normal lung cells. The VOCs were analyzed by gas chromatography combined with mass spectrometry. Among hundreds of detected compounds, 18 VOCs showed significant changes in their concentration levels in tumor cells versus control. The composition of these VOCs was found to depend, also, on the sub-molecular structure of the p53 genetic status. Analyzing the VOCs offers a complementary way of querying the molecular mechanisms of cancer as well as of developing new generation(s) of biomedical approaches for personalized screening and diagnosis.

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Measurement of VOCs was achieved at the single-cell level

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Genetic changes influence the emitted volatiles of single and bulk cancer cells

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Single-cell VOC analysis measures population heterogeneity in initial stage of tumors

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Volatolomics research can promote non-invasive, simple, and cost-effective diagnostics