3D Bioprinted cancer models: Revolutionizing personalized cancer therapy

After cardiovascular disease, cancer is the leading cause of death worldwide with devastating health and economic consequences, particularly in developing countries. Inter-patient variations in anti-cancer drug responses further limit the success of therapeutic interventions. Therefore, personalized medicines approach is key for this patient group involving molecular and genetic screening and appropriate stratification of patients to treatment regimen that they will respond to. However, the knowledge related to adequate risk stratification methods identifying patients who will respond to specific anti-cancer agents is still lacking in many cancer types. Recent advancements in three-dimensional (3D) bioprinting technology, have been extensively used to generate representative bioengineered tumor in vitro models, which recapitulate the human tumor tissues and microenvironment for high-throughput drug screening. Bioprinting process involves the precise deposition of multiple layers of different cell types in combination with biomaterials capable of generating 3D bioengineered tissues based on a computer-aided design. Bioprinted cancer models containing patient-derived cancer and stromal cells together with genetic material, extracellular matrix proteins and growth factors, represent a promising approach for personalized cancer therapy screening. Both natural and synthetic biopolymers have been utilized to support the proliferation of cells and biological material within the personalized tumor models/implants. These models can provide a physiologically pertinent cell–cell and cell–matrix interactions by mimicking the 3D heterogeneity of real tumors. Here, we reviewed the potential applications of 3D bioprinted tumor constructs as personalized in vitro models in anticancer drug screening and in the establishment of precision treatment regimens.     

Targeted therapy and immunotherapy: Emerging biomarkers in metastatic melanoma

Targeted therapy directed against oncogenic BRAF mutations and immune checkpoint inhibitors have transformed melanoma therapy over the past decade and prominently improved patient outcomes. However, not all patients will respond to targeted therapy or immunotherapy and many relapse after initially responding to treatment. This unmet need presents two major challenges. First, can we elucidate novel oncogenic drivers to provide new therapeutic targets? Second, can we identify patients who are most likely to respond to current therapeutic strategies in order to both more accurately select populations and avoid undue drug exposure in patients unlikely to respond? In an effort to evaluate the current state of the field with respect to these questions, we provide an overview of some common oncogenic mutations in patients with metastatic melanoma and ongoing efforts to therapeutically target these populations, as well as a discussion of biomarkers for response to immune checkpoint inhibitors—including tumor programmed death ligand 1 expression and the future use of neoantigens as a means of truly personalized therapy. This information is becoming important in treatment decision making and provides the framework for a treatment algorithm based on the current landscape in metastatic melanoma.     

Apoptosis signaling proteins as prognostic biomarkers in colorectal cancer: A review

Colorectal cancer is a leading cause of cancer related mortality in the Western world. In recent years, combination 5-fluorouracil based adjuvant chemotherapy as first line treatment of this disease has led to improved disease free and overall survival. However drug resistance, both innate and acquired, remains an obstacle in the effective treatment of this disease. Apoptotic pathways are frequently altered in both tumor progression and drug resistance; therefore proteins associated with this pathway may have potential as prognostic biomarkers for this disease. Identification of clinical biomarkers that are able to identify patients who are more likely to respond to specific chemotherapy will lead to more personalized, effective, and less toxic therapy. This review focuses on the current status of apoptosis related proteins as biomarkers for colorectal cancer and discusses the possible application of systems approaches in this context.     

Analysis of Chemopredictive Assay for Targeting Cancer Stem Cells in Glioblastoma Patients

Introduction: The prognosis of glioblastoma (GBM) treated with standard-of-care maximal surgical resection and concurrent adjuvant temozolomide (TMZ)/radiotherapy remains very poor (less than 15 months). GBMs have been found to contain a small population of cancer stem cells (CSCs) that contribute to tumor propagation, maintenance, and treatment resistance. The highly invasive nature of high-grade gliomas and their inherent resistance to therapy lead to very high rates of recurrence. For these reasons, not all patients with similar diagnoses respond to the same chemotherapy, schedule, or dose. Administration of ineffective anticancer therapy is not only costly but more importantly burdens the patient with unnecessary toxicity and selects for the development of resistant cancer cell clones. We have developed a drug response assay (ChemoID) that identifies the most effective chemotherapy against CSCs and bulk of tumor cells from of a panel of potential treatments, offering great promise for individualized cancer management. Providing the treating physician with drug response information on a panel of approved drugs will aid in personalized therapy selections of the most effective chemotherapy for individual patients, thereby improving outcomes. A prospective study was conducted evaluating the use of the ChemoID drug response assay in GBM patients treated with standard of care. Methods: Forty-one GBM patients (mean age 54 years, 59% male), all eligible for a surgical biopsy, were enrolled in an Institutional Review Board–approved protocol, and fresh tissue samples were collected for drug sensitivity testing. Patients were all treated with standard-of-care TMZ plus radiation with or without maximal surgery, depending on the status of the disease. Patients were prospectively monitored for tumor response, time to recurrence, progression-free survival (PFS), and overall survival (OS). Odds ratio (OR) associations of 12-month recurrence, PFS, and OS outcomes were estimated for CSC, bulk tumor, and combined assay responses for the standard-of-care TMZ treatment; sensitivities/specificities, areas under the curve (AUCs), and risk reclassification components were examined. Results: Median follow-up was 8 months (range 3-49 months). For every 5% increase in in vitro CSC cell kill by TMZ, 12-month patient response (nonrecurrence of cancer) increased two-fold, OR = 2.2 (P = .016). Similar but somewhat less supported associations with the bulk tumor test were seen, OR = 2.75 (P = .07) for each 5% bulk tumor cell kill by TMZ. Combining CSC and bulk tumor assay results in a single model yielded a statistically supported CSC association, OR = 2.36 (P = .036), but a much attenuated remaining bulk tumor association, OR = 1.46 (P = .472). AUCs and [sensitivity/specificity] at optimal outpoints (>40% CSC cell kill and >55% bulk tumor cell kill) were AUC = 0.989 [sensitivity = 100/specificity = 97], 0.972 [100/89], and 0.989 [100/97] for the CSC only, bulk tumor only, and combined models, respectively. Risk categorization of patients was improved by 11% when using the CSC test in conjunction with the bulk test (risk reclassification nonevent net reclassification improvement [NRI] and overall NRI = 0.111, P = .030). Median recurrence time was 20 months for patients with a positive (>40% cell kill) CSC test versus only 3 months for those with a negative CSC test, whereas median recurrence time was 13 months versus 4 months for patients with a positive (>55% cell kill) bulk test versus negative. Similar favorable results for the CSC test were observed for PFS and OS outcomes. Panel results across 14 potential other treatments indicated that 34/41 (83%) potentially more optimal alternative therapies may have been chosen using CSC results, whereas 27/41 (66%) alternative therapies may have been chosen using bulk tumor results. Conclusions: The ChemoID CSC drug response assay has the potential to increase the accuracy of bulk tumor assays to help guide individualized chemotherapy choices. GBM cancer recurrence may occur quickly if the CSC test has a low in vitro cell kill rate even if the bulk tumor test cell kill rate is high.     

Dynamics of targeted cancer therapy

Targeted cancer therapies offer renewed hope for an eventual 'cure for cancer'. At present, however, their success is often compromised by the emergence of resistant tumor cells. In many cancers, patients initially respond to single therapy treatment but relapse within months. Mathematical models of somatic evolution can predict and explain patterns in the success or failure of anticancer drugs. These models take into account the rate of cell division and death, the mutation rate, the size of the tumor, and the dynamics of tumor growth including density limitations caused by geometric and metabolic constraints. As more targeted therapies become available, mathematical modeling will provide an essential tool to inform the design of combination therapies that minimize the evolution of resistance.     

Advanced Cell Mapping Visualizations for Single Cell Functional Proteomics Enabling Patient Stratification

Highly multiplexed single‐cell functional proteomics has emerged as one of the next‐generation toolkits for a deeper understanding of functional heterogeneity in cell. Different from the conventional population‐based bulk and single‐cell RNA‐Seq assays, the microchip‐based proteomics at the single‐cell resolution enables a unique identification of highly polyfunctional cell subsets that co‐secrete many proteins from live single cells and most importantly correlate with patient response to a therapy. The 32‐plex IsoCode chip technology has defined a polyfunctional strength index (PSI) of pre‐infusion anti‐CD19 chimeric antigen receptor (CAR)‐T products, that is significantly associated with patient response to the CAR‐T cell therapy. To complement the clinical relevance of the PSI, a comprehensive visualization toolkit of 3D uniform manifold approximation and projection (UMAP) and t‐distributed stochastic neighbor embedding (t‐SNE) in a proteomic analysis pipeline is developed, providing more advanced analytical algorithms for more intuitive data visualizations. The UMAP and t‐SNE of anti‐CD19 CAR‐T products reveal distinct cytokine profiles between nonresponders and responders and demonstrate a marked upregulation of antitumor‐associated cytokine signatures in CAR‐T cells from responding patients. Using this powerful while user‐friendly analytical tool, the multi‐dimensional single‐cell data can be dissected from complex immune responses and uncover underlying mechanisms, which can promote correlative biomarker discovery, improved bioprocessing, and personalized treatment development.     

Inducing pluripotency in vitro: recent advances and highlights in induced pluripotent stem cells generation and pluripotency reprogramming

Induced pluripotent stem cells (iPSCs) are considered patient‐specific counterparts of embryonic stem cells as they originate from somatic cells after forced expression of pluripotency reprogramming factors Oct4, Sox2, Klf4 and c‐Myc. iPSCs offer unprecedented opportunity for personalized cell therapies in regenerative medicine. In recent years, iPSC technology has undergone substantial improvement to overcome slow and inefficient reprogramming protocols, and to ensure clinical‐grade iPSCs and their functional derivatives. Recent developments in iPSC technology include better reprogramming methods employing novel delivery systems such as non‐integrating viral and non‐viral vectors, and characterization of alternative reprogramming factors. Concurrently, small chemical molecules (inhibitors of specific signalling or epigenetic regulators) have become crucial to iPSC reprogramming; they have the ability to replace putative reprogramming factors and boost reprogramming processes. Moreover, common dietary supplements, such as vitamin C and antioxidants, when introduced into reprogramming media, have been found to improve genomic and epigenomic profiles of iPSCs. In this article, we review the most recent advances in the iPSC field and potent application of iPSCs, in terms of cell therapy and tissue engineering.     

Application of oncoproteomics to aberrant signalling networks in changing the treatment paradigm in acute lymphoblastic leukaemia

Oncoproteomics is an important innovation in the early diagnosis, management and development of personalized treatment of acute lymphoblastic leukaemia (ALL). As inherent factors are not completely known – e.g. age or family history, radiation exposure, benzene chemical exposure, certain viral exposures such as infection with the human T‐cell lymphoma/leukaemia virus‐1, as well as some inherited syndromes may raise the risk of ALL – each ALL patient may modify the susceptibility of therapy. Indeed, we consider these unknown inherent factors could be explained via coupling cytogenetics plus proteomics, especially when proteins are the ones which play function within cells. Innovative proteomics to ALL therapy may help to understand the mechanism of drug resistance and toxicities, which in turn will provide some leads to improve ALL management. Most important of these are shotgun proteomic strategies to unravel ALL aberrant signalling networks. Some shotgun proteomic innovations and bioinformatic tools for ALL therapies will be discussed. As network proteins are distinctive characteristics for ALL patients, unrevealed by cytogenetics, those network proteins are currently an important source of novel therapeutic targets that emerge from shotgun proteomics. Indeed, ALL evolution can be studied for each individual patient via oncoproteomics.     

Induced pluripotent stem cell‐derived myeloid cells expressing OX40 ligand amplify antigen‐specific T cells in advanced melanoma

Immune checkpoint inhibitors improved the survival rate of patients with unresectable melanoma. However, some patients do not respond, and variable immune‐related adverse events have been reported. Therefore, more effective and antigen‐specific immune therapies are urgently needed. We previously reported the efficacy of an immune cell therapy with immortalized myeloid cells derived from induced pluripotent stem cells (iPS‐ML). In this study, we generated OX40L‐overexpressing iPS‐ML (iPS‐ML‐Zsgreen‐OX40L) and investigated their characteristics and in vivo efficacy against mouse melanoma. We found that iPS‐ML‐Zsgreen‐OX40L suppressed the progression of B16‐BL6 melanoma, and prolonged survival of mice with ovalbumin (OVA)‐expressing B16 melanoma (MO4). The number of antigen‐specific CD8⁺ T cells was higher in spleen cells treated with OVA peptide‐pulsed iPS‐ML‐Zsgreen‐OX40L than in those without OX40L. The OVA peptide‐pulsed iPS‐ML‐Zsgreen‐OX40L significantly increased the number of tumor‐infiltrating T lymphocytes (TILs) in MO4 tumor. Flow cytometry showed decreased regulatory T cells but increased effector and effector memory T cells among the TILs. Although we plan to use allogeneic iPS‐ML in the clinical applications, iPS‐ML showed the tumorgenicity in the syngeneic mice model. Incorporating the suicide gene is necessary to ensure the safety in the future study. Collectively, these results indicate that iPS‐ML‐Zsgreen‐OX40L therapy might be a new method for antigen‐specific cancer immunotherapy.     

Therapeutic resistance resulting from mutations in Raf/MEK/ERK and PI3K/PTEN/Akt/mTOR signaling pathways

Chemotherapy remains a commonly used therapeutic approach for many cancers. Indeed chemotherapy is relatively effective for treatment of certain cancers and it may be the only therapy (besides radiotherapy) that is appropriate for certain cancers. However, a common problem with chemotherapy is the development of drug resistance. Many studies on the mechanisms of drug resistance concentrated on the expression of membrane transporters and how they could be aberrantly regulated in drug resistant cells. Attempts were made to isolate specific inhibitors which could be used to treat drug resistant patients. Unfortunately most of these drug transporter inhibitors have not proven effective for therapy. Recently the possibilities of more specific, targeted therapies have sparked the interest of clinical and basic researchers as approaches to kill cancer cells. However, there are also problems associated with these targeted therapies. Two key signaling pathways involved in the regulation of cell growth are the Ras/Raf/MEK/ERK and PI3K/PTEN/Akt/mTOR pathways. Dysregulated signaling through these pathways is often the result of genetic alterations in critical components in these pathways as well as mutations in upstream growth factor receptors. Furthermore, these pathways may be activated by chemotherapeutic drugs and ionizing radiation. This review documents how their abnormal expression can contribute to drug resistance as well as resistance to targeted therapy. This review will discuss in detail PTEN regulation as this is a critical tumor suppressor gene frequently dysregulated in human cancer which contributes to therapy resistance. Controlling the expression of these pathways could improve cancer therapy and ameliorate human health.     

MicroRNAs: key players of taxane resistance and their therapeutic potential in human cancers

The successful long‐term use of taxane for cancer therapy is often prevented by the development of drug resistance in clinic. Thus, exploring the mechanisms involved is a first step towards rational strategies to overcome taxane resistance. Taxane resistance‐related microRNA (miRNAs) are under investigation and miRNAs could induce the taxane resistance of tumour cells by regulating cell cycle distribution, survival and/or apoptosis pathways, drug transports, epithelial–mesenchymal transition and cancer stem cell. This article summarizes current research involving miRNAs as regulators of key target genes for tanxanxe chemoresistance and discusses the complex regulatory networks of miRNAs. Also, the authors will envisage future developments towards the potential use of targeting miRNAs as a novel strategy for improving response of tumour patients to taxane. miRNAs play critical roles in taxane chemoresistance and the miRNA‐based therapies will be helpful for overcoming drug resistance and developing more effective personalized anti‐cancer treatment strategies. Further research studies should be performed to promote therapeutic–clinical use of taxane resistance‐related miRNAs in cancer patients, especially in those patients with taxane‐resistant cancers.     

In silico drug combination discovery for personalized cancer therapy

Background

Drug combination therapy, which is considered as an alternative to single drug therapy, can potentially reduce resistance and toxicity, and have synergistic efficacy. As drug combination therapies are widely used in the clinic for hypertension, asthma, and AIDS, they have also been proposed for the treatment of cancer. However, it is difficult to select and experimentally evaluate effective combinations because not only is the number of cancer drug combinations extremely large but also the effectiveness of drug combinations varies depending on the genetic variation of cancer patients. A computational approach that prioritizes the best drug combinations considering the genetic information of a cancer patient is necessary to reduce the search space.

Results

We propose an in-silico method for personalized drug combination therapy discovery. We predict the synergy between two drugs and a cell line using genomic information, targets of drugs, and pharmacological information. We calculate and predict the synergy scores of 583 drug combinations for 31 cancer cell lines. For feature dimension reduction, we select the mutations or expression levels of the genes in cancer-related pathways. We also used various machine learning models. Extremely Randomized Trees (ERT), a tree-based ensemble model, achieved the best performance in the synergy score prediction regression task. The correlation coefficient between the synergy scores predicted by ERT and the actual observations is 0.738. To compare with an existing drug combination synergy classification model, we reformulate the problem as a binary classification problem by thresholding the synergy scores. ERT achieved an F1 score of 0.954 when synergy scores of 20 and -20 were used as the threshold, which is 8.7% higher than that obtained by the state-of-the-art baseline model. Moreover, the model correctly predicts the most synergistic combination, from approximately 100 candidate drug combinations, as the top choice for 15 out of the 31 cell lines. For 28 out of the 31 cell lines, the model predicts the most synergistic combination in the top 10 of approximately 100 candidate drug combinations. Finally, we analyze the results, generate synergistic rules using the features, and validate the rules through the literature survey.

Conclusion

Using various types of genomic information of cancer cell lines, targets of drugs, and pharmacological information, a drug combination synergy prediction pipeline is proposed. The pipeline regresses the synergy level between two drugs and a cell line as well as classifies if there exists synergy or antagonism between them. Discovering new drug combinations by our pipeline may improve personalized cancer therapy.

     

The avidity of tumor‐specific T cells amplified by a plasmacytoid dendritic cell‐based assay can predict the clinical evolution of melanoma patients

The advent of immune checkpoint blockers and targeted therapies has changed the outcome of melanoma. However, many patients experience relapses, emphasizing the need for predictive and prognostic biomarkers. We developed a strategy based on plasmacytoid dendritic cells (pDCs) loaded with melanoma tumor antigens that allows eliciting highly efficient antitumor T‐cell responses. We used it to investigate antitumor T‐cell functionality in peripheral blood mononuclear cells and tumor‐infiltrating lymphocytes from melanoma patients. The pDCs elicited tumor‐specific T cells in different proportions and displaying diverse functional features, dependent upon the stage of the disease, but independent of the histological parameters at diagnosis. Strikingly, the avidity of the MelA‐specific T cells triggered by the pDCs was found to predict patient relapse time and overall survival. Our findings highlighted unexplored aspects of antitumor T‐cell responsiveness in melanoma, and revealed for the first time the structural avidity of tumor‐specific T cells as a crucial feature for predicting clinical evolution.     

Potentials of single‐cell biology in identification and validation of disease biomarkers

Single‐cell biology is considered a new approach to identify and validate disease‐specific biomarkers. However, the concern raised by clinicians is how to apply single‐cell measurements for clinical practice, translate the message of single‐cell systems biology into clinical phenotype or explain alterations of single‐cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single‐cell gene sequencing in the identification and development of disease‐specific biomarkers, the definition and significance of single‐cell biology and single‐cell systems biology in the understanding of single‐cell full picture, the development and establishment of whole‐cell models in the validation of targeted biological function and the figure and meaning of single‐molecule imaging in single cell to trace intra‐single‐cell molecule expression, signal, interaction and location. We headline the important role of single‐cell biology in the discovery and development of disease‐specific biomarkers with a special emphasis on understanding single‐cell biological functions, e.g. mechanical phenotypes, single‐cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi‐dimensional, multi‐layer, multi‐crossing and stereoscopic single‐cell biology definitely benefits the discovery and development of disease‐specific biomarkers.     

Focus: Personalized Medicine: Value of Organoids from Comparative Epithelia Models

Organoids have tremendous therapeutic potential. They were recently defined as a collection of organ-specific cell types, which self-organize through cell-sorting, develop from stem cells, and perform an organ specific function. The ability to study organoid development and growth in culture and manipulate their genetic makeup makes them particularly suitable for studying development, disease, and drug efficacy. Organoids show great promise in personalized medicine. From a single patient biopsy, investigators can make hundreds of organoids with the genetic landscape of the patient of origin. This genetic similarity makes organoids an ideal system in which to test drug efficacy. While many investigators assume human organoids are the ultimate model system, we believe that the generation of epithelial organoids of comparative model organisms has great potential. Many key transport discoveries were made using marine organisms. In this paper, we describe how deriving organoids from the spiny dogfish shark, zebrafish, and killifish can contribute to the fields of comparative biology and disease modeling with future prospects for personalized medicine.     

Tissue-specific cancer stem/progenitor cells: Therapeutic implications

Surgical resection, chemotherapy, and radiation are the standard therapeutic modalities for treating cancer. These approaches are intended to target the more mature and rapidly dividing cancer cells. However, they spare the relatively quiescent and intrinsically resistant cancer stem cells (CSCs) subpopulation residing within the tumor tissue. Thus, a temporary eradication is achieved and the tumor bulk tends to revert supported by CSCs' resistant features. Based on their unique expression profile, the identification, isolation, and selective targeting of CSCs hold great promise for challenging treatment failure and reducing the risk of cancer recurrence. Yet, targeting CSCs is limited mainly by the irrelevance of the utilized cancer models. A new era of targeted and personalized anti-cancer therapies has been developed with cancer patient-derived organoids (PDOs) as a tool for establishing pre-clinical tumor models. Herein, we discuss the updated and presently available tissue-specific CSC markers in five highly occurring solid tumors. Additionally, we highlight the advantage and relevance of the three-dimensional PDOs culture model as a platform for modeling cancer, evaluating the efficacy of CSC-based therapeutics, and predicting drug response in cancer patients.     

Recent Development of the Second and Third Generation Irreversible Epidermal Growth Factor Receptor Inhibitors

Recent reports suggested that essential directions for new lung cancer, breast carcinoma therapies, as well as the roomier realm of targeted cancer therapies were provided through targeting the epidermal growth factor receptor (EGFR). Patients who carrying non‐small cell lung carcinoma (NSCLC) with activating mutations in EGFR initially respond well to the EGFR inhibitors erlotinib and gefitinib, which were located the active site of the EGFR kinase and designed to act as competitive inhibitors of combining with the ATP. However, patients who were treated with the erlotinib and gefitinib will relapse because of the emergence of drug‐resistant mutations, with T790M mutations accounting for approximately 60% of all resistance. In order to overcome drug resistance, Pharmaceutical chemistry experts recently devoted great endeavors to the development of second‐generation irreversible selective inhibitors which covalently modify Cys797 or Cys773 at the ATP binding cleft. Nevertheless, these inhibitors have not reached ideal effect of experts in patients with T790M positive mutation and apparently because of the dose‐limiting toxicities associated with inhibition of wild type EGFR. A novel class of ‘third generation’ EGFR TKIs have been developed that is sensitising and T790M mutant‐specific whilst sparing WT EGFR, representing a significant breakthrough in the treatment in NSCLC patients with acquired resistance harboring these genotypes. Herein, we provides an overview of the second and third generation inhibitors currently approved, in clinical trial and also encompasses novel structures of discovery. This review mainly focuses on drug resistance, their mechanisms of action, development of structure–activity relationships and binding modes.     

肿瘤类器官在药物筛选和个性化用药中的研究进展*

恶性肿瘤是影响人类生命健康的重大疾病之一,药物治疗是常见的治疗手段。近年来,“精准治疗”已经成为肿瘤治疗的趋势。要实现对恶性肿瘤有效、精准的药物治疗,药物筛选模型至关重要。肿瘤类器官是近年来新兴的一种三维细胞模型,具有经长期传代还保留亲本肿瘤的特征和异质性、培养成功率高、周期短和能够高通量筛选药物等优点,已被用于药物筛选、预测患者对治疗的反应以及为个性化用药提供指导等。重点介绍了肿瘤类器官在药物筛选及个性化用药中的研究进展和面临的挑战。