Open access peer-reviewed chapter

Two-Dimensional and Three-Dimensional Cell Culture and Their Applications

Written By

Sangeeta Ballav, Ankita Jaywant Deshmukh, Shafina Siddiqui, Jyotirmoi Aich and Soumya Basu

Submitted: 13 August 2021 Reviewed: 09 September 2021 Published: 13 October 2021

DOI: 10.5772/intechopen.100382

From the Edited Volume

Cell Culture - Advanced Technology and Applications in Medical and Life Sciences

Edited by Xianquan Zhan

Chapter metrics overview

1,042 Chapter Downloads

View Full Metrics

Abstract

Cell culture is one of the most important and commonly used in vitro tools to comprehend various aspects of cells or tissues of a living body such as cell biology, tissue morphology, mechanism of diseases, cell signaling, drug action, cancer research and also finds its great importance in preclinical trials of various drugs. There are two major types of cell cultures that are most commonly used- two-dimensional (2D) and three-dimensional culture (3D). The former has been used since the 1900s, owing to its simplicity and low-cost maintenance as it forms a monolayer, while the latter being the advanced version and currently most worked upon. This chapter intends to provide the true meaning and significance to both cultures. It starts by making a clear distinction between the two and proceeds further to discuss their different applications in vitro. The significance of 2D culture is projected through different assays and therapeutic treatment to understand cell motility and treatment of diseases, whereas 3D culture includes different models and spheroid structures consisting of multiple layers of cells, and puts a light on its use in drug discovery and development. The chapter is concluded with a detailed account of the production of therapeutic proteins by the use of cells.

Keywords

  • Cell culture
  • 2D culture
  • 3D culture
  • drug action
  • therapeutics

1. Introduction

The growth of cells in a controlled artificial environment isolated from their natural habitat is referred to as cell culture [1]. It is a significant tool used widely to study cell and molecular biology, screening drugs and toxicity analysis, the role of a particular gene in a disease, and cancer research. Due to their unique properties, they also have been tuned for screening and developing biopharmaceutical compounds such as vaccines and recombinant proteins. One of the major advantages of using cell culture is the homogenous and reproducible data generated [2].

Drug discovery is a lengthy and time-consuming process that undergoes several stages of testing and optimization. This encompasses identification of the target, lead discovery, pre-clinical validation, and clinical trials [3]. Therefore, it is very pertinent to obtain information about the biological activity, biochemical mechanisms, toxicity, and off-target interactions of drug molecules leading to the early stages of drug discovery. In vitro, cell-based assays prove futile to understand the effects of drugs on the cells at an early stage of drug discovery which attributes an increased chance of development of drugs with good efficacy and safety [4].

Two-dimensional (2D) cell culture was introduced many decades ago that has been the major type of cell culture technique in numerous fields. This traditional approach has been extensively used for drug screening due to its relatively inexpensive feature and convenience to use. However, the issue of mimicking the in vivo environment restricts its use [5]. The 2D cell cultures grow as a monolayer in controlled flat environments, such as a glass or polystyrene flask that comprises live proliferating cells because of the detachment of dead cells from the surface (Figure 1). As a result, this leads to uniformity in nutrients and growth factors present in the medium to which the cells get access and proliferate at a faster rate than they would in vivo [6]. Thus, the morphology of the cells is completely changed as they appear flattered and stretched as compared to the in vivo environment. Besides this, the cell–cell interactions and cell-extracellular interactions become different in comparison to the tumor [7].

Figure 1.

Simplified sketch of 2D cell culture (a) and 3D cell culture (b).

Recently there has been an upsurge of interest towards three-dimensional (3D) cell culture in biomedical research and drug development processes due to its high-throughput accuracy and refined in vitro models [8]. They have been broadly used in understanding the cell shape, cell–cell interaction, and the cellular environment that efficiently mimics the in vivo environment. 3D cultures grow as clusters or aggregates called spheroids either with a matrix or without a matrix [9] (Figure 1). There is a gradient of nutrients across these spheroids due to which the cells at the surface of spheroids proliferate more as compared to the cells that are present in the interior [10]. As a result of the difference in the proliferation rate, the cells in the spheroids are usually in different stages of the cell cycle such as proliferating, quiescent, hypoxic, and necrotic cells. In the 3D culture, the cells have uniform access to nutrients as in the case of a tumor. Also, the shape of the cells, cell–cell interactions, and cell-environment interactions are well defined in 3D culture [7]. It has also been observed that 2D cell cultures are more sensitive to drugs as compared to 3D cells [11]. This chapter intends to provide the true meaning and significance of both cultures. It starts by making a clear distinction between the two and proceeds further to discuss their different applications in vitro. The significance of 2D culture is projected through different assays and therapeutic treatment to understand cell motility and treatment of diseases, while 3D culture includes different models and spheroid structures consisting of multiple layers of cells, and puts a light on its use in drug discovery and development. The chapter is concluded with a detailed account of the production of therapeutic proteins by the use of cells.

Advertisement

2. In vitro applications of 2D culture

2.1 In vitro cytotoxicity assays and tissue-engineered tissue models

Cytotoxicity assays are commonly used for in vitro toxicology and pharmacology studies for the screening the effect of chemicals and drugs on the cultured cells. There are different assays available for measuring cytotoxicity namely- the colony-forming assay and dye inclusion or exclusion such as neutral red and trypan blue assay is the most significantly used. Cytotoxicity assays can be broadly divided into the following categories– (i) Assays based on metabolism, (ii) Adenosine triphosphate (ATP) Bioluminescence Assay and (iii) Assays based on the release of enzymes.

Assays based on metabolism generally include the 3-(4,5-dimethythiazol2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay and its alternatives such as 2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide (XTT),3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium(MTS) and sulforhodamine B (SRB) assay. Due to rapid, quantitative, versatile, and highly reproducibility of MTT, it is widely used in large-scale, anti-tumor drug-screening program. MTT is a quantitative colorimetric assay that quantifies the reduction of yellow tetrazolium dye by mitochondrial succinate dehydrogenase to purple insoluble formazan crystals by the NADPH dependent cellular oxidoreductase enzymes [12]. The crystals are dissolved in an appropriate solvent. The absorbance is then recorded using a spectrophotometer to analyze the cell viability wherein the crystals get accumulated in the viable cells due to their impermeability to the cell membrane.

ATP Bioluminescence Assay is used to measure the ATP level that is well regulated in the metabolically active live eukaryotic cells as compared to the dead cells wherein the ATP level falls due to the activity of ATPases. This assay includes a luciferase enzyme that utilizes energy from ATP that converts luciferin into oxyluciferin and thus produces luminescence. Therefore, luminescence could be used to measure the ATP level. Assays based on the release of enzymes are more significant as they measure the products released by the dead cells [13].

Assays based on the release of enzymes include Lactate dehydrogenase(LDH) leakage assay involving the formation of pyruvate from lactate in the presence of LDH with simultaneous reduction of NAD to NADH that alters the absorbance at 340 nm [14]. Research in cancer and cell biology is greatly dependent on in vitro assays and models. This help in understanding the various responses of the cultured cells when exposed to different conditions. Tissue-engineered in vitro tissue models serve as an alternative to in vivo animal studies to study the physiology of various diseases. Example of tissue-engineered in vitro models includes Skeletal Muscle Models [15], blood–brain barrier model [16], aneurysm models [17] and the Pre-vascularized Human Vaginal Mucosa model [18].

2.2 Cell migration assay

Cell migration is well known for its significant role in embryonic morphogenesis, cancer invasion and metastasis, immune responses, tissue formation, and angiogenesis [19]. Mainly, cell migration is of two types; single-cell migration and collective cell migration. Single-cell migration is regulated by cytoskeletal activity without cell-to-cell interactions with neighboring cells. This type of migration is important for embryonic development, immune response, and in the early stages of metastasis. On the other hand in the collective cell migration, the group of cells retains their cell to cell interactions as well as collective polarity. Wound healing assay or scratch assay is a 2D in vitro technique used to study collective cell migration. In this assay, a scratch is made on the confluent cell monolayer resulting in the formation of a gap or wound which is monitored by taking pictures of the migrating cells at regular intervals of time. These pictures are then used to measure the speed of wound closure and thus quantify migration. Live-cell imaging using Time-lapse microscopy can be used for a more detailed study of cell migration behavior [20]. In order to reduce the effect of cell proliferation on gap filling, the readings are taken for a time period of 24 hours but this may vary depending on the cell line.

Another assay involving the response of single cells to various chemo-attractants is the transwell assay or the Boyden Chamber assay. This assay can be used for both adherent and non-adherent cells wherein the cells are placed in a serum-free medium on one side of a porous membrane and analyzed on the basis of the cell’s ability to migrate through the pores to the other side. Cell migration can be quantified by counting the cells that have traversed through the membrane towards the higher concentration of chemoattractant [21]. A drawback of this assay is visualizing the cells and their morphology while migrating through pores due to the transitive state of cells [22].

2.3 In vitro tumorigenicity assay

Cancer is one of the most frightful diseases in both developing and developed countries and imparts a major health burden to the society. Tumorigenicity is the tendency of the cultured cells to form tumors. The two common in vitro tumorigenicity assays are - Colony-forming assay and Tumorsphere assay. The colony-forming assay is also referred to as clonogenic assay that analyzes the potentiality of a single cell to undergo a clonal expansion to form a colony composed of a minimum of 50 cells [23]. This assay is usually used to distinguish there productive viability of untreated cells from the cells that are treated with ionizing radiation or cytotoxic agents. It is also used to study the stemness and the clonogenicity of stem cells [24].

Colony forming assay is performed using the soft agar method. The basic steps involved in this assay are treating the cell monolayer in the flask, seeding the required number of cells on the agar and incubate for 1–3 weeks, fixing and staining the colonies and finally observing the colonies under the stereomicroscope [23]. Another in vitro tumorigenicity assay is tumorsphere assay which analyzes the potential of cancer stem cells (CSCs), a major cause of tumor initiation, progression, and recurrence after treatment. This assay is carried out under non-adherent conditions and serum-free medium supplied with growth factors of choice leading to the proliferation of CSCs and formation of spheres whereas the non-CSCs undergo apoptosis due to loss of adherence and abundant nutrients [25].

2.4 Cell invasion assay

Cell migration is an important process in biology where the cells changes and reaches their destination within a proper environment, in order to execute their respective function. It is a normal physiological process that takes place in nearly all forms of organisms. However, changes or deregulation of any kind in the pattern of cell migration or invasion are an indication of pathological conditions including inflammatory diseases and cancer metastasis, with the latter being the most explored one [21]. There are various biological methods that are commonly employed in the scientific community to study the above-mentioned events in depth namely, the cell culture wound-healing assay, the transwell migration, and invasion assay, individual cell-tracking assay, and spreading assay. These assays aim to provide relevant information pertaining to the pattern of cell migration or its response to chemoattractant(s).

2.4.1 The cell culture wound-closure assay

It is the simplest of all methods in determining the migration of whole-cell masses altogether. Going further in detail, it can be used to interpret individual cell’s morphological characteristics and phenotypes during migration. Measuring the closed distance compared to the control over regular intervals of time shows specific migration changes or phenotype that was unknown in the past [26].

2.4.2 The transwell migration and invasion assay

The transwell migration and invasion assay are used to determine the capability of single cells to respond to various chemoattractant(s) including chemokines, growth factors, lipids, or nucleotides. It also contributes to assessing differential cell migration due to the over-expression of a receptor. It also identifies and characterizes the key regulators participating in cell migration [26].

2.4.3 Individual cell-tracking assay or single-cell tracking assay

Conducting single-cell tracking and its live imaging under appropriate conditions adds to the overall advantage of cell migration assay. The software includes a time-lapse video-microscopy protocol comprising of post-processing tracks of the cell populations with single-cell resolution. It greatly helps to understand the cell biology and lineage progression of distinct cell populations [27].

2.4.4 Cell spreading assay

In this type of assay, the spreading process of individual cells is seen and recorded with the help of Differential Interference Contrast microscopy (DIC). The spreading state is recorded every 5 seconds with a Charge-Coupled Device (CCD) of the camera, producing high-quality grayscale images. The process of taking images could extend to several hours [28].

2.5 Hybridoma technology and monoclonal antibodies

Antibodies, one of the major elements of the immune system are the glycoproteins produced by the immunoglobulins; B-cells provide protection against invading pathogens. The antibodies are highly specific and selective, thus have been used as an extraordinary tool in bioengineering and biomedical research for many years. The antibodies are majorly classified into two categories, Monoclonal Antibodies (mAbs) and Polyclonal Antibodies (pAbs) are based on their origin from the lymphocytes. mAbs are produced by only B lymphocyte or B cells and are monospecific. Due to this property, they possess high specificity and affinity towards a single epitope of an antigen whereas pAbs are produced by different B-cells and possess different affinities for multiple epitopes of a specific antigen. Since mAbs are highly specific, they are produced on a large scale through culturing of antibodies-producing cells widely known as ‘Hybridomas’, which are commonly derived from mice, and the method is known as ‘Hybridoma Technology [29].

Hybridoma technology was discovered and developed by two eminent scientists, Georges Kohler and Cesar Milstein in 1975 and is considered to be one of the biggest breakthroughs. It has proved to be a robust, effective, and successful methodology employed in the field of biotechnology and biomedical research that solely deals with mAb isolation. The B cells go through the antibody maturation process in the germinal centers of secondary lymphoid tissues (for example, lymph nodes, spleen, tonsils, and Peyer’s patches). Upon proliferation, certain mutations are experienced by the B cells, specifically in the genes encoding the variable region of the antibodies that helps in the selection for high-affinity tight binding to the corresponding antigen. The overall resulting antibodies by B cells consist of a natural pairing of the light chain and variable heavy chain genes with constant region genes. This region contains Class Switch Recombination (CSR) differentiates from the hybridoma technology in which CSR is absent [29].

Following are the steps employed for the production of monoclonal antibody by hybridoma technology.

2.5.1 Isolation of antibody-producing B lymphocyte

The mouse/mice is/are immunized every 2–3 weeks with red blood cells taken from sheep in order to produce the B cells. These antibodies are isolated from the spleen cells of mice.

2.5.2 Screening of mouse for production of antibody

After the process of immunization, the blood samples are taken from the mouse to determine the serum antibody titer. When the titer reaches the optimal level, the mouse is boosted by injecting antigen 3 days prior to fusion with myeloma cells [30].

2.5.3 Fusion of B cells with myeloma cells

Fusion of isolated spleen cells (limited life span) with tumor lymphocytes (immortal) with the help of PEG (Polyethylene Glycol) leads to the development of hybridomas with an unlimited life span.

2.5.4 Culturing of hybridomas

Hybridomas are grown in a selective medium containing Hypoxanthine, Aminopterin and Thymidine (HAT). Aminopterin present in the media blocks pathway for nucleotide synthesis, making the cells dependent on the alternative pathway which is not evident in myeloma cells.

2.5.5 Screening and selection of the desired colony

The cells are screened and chosen or selected for production of antibodies with the desired specificity.

2.5.6 Culturing of the selected hybridoma cells on large scale

The cells are cultured and used for the production of large quantities of antibodies [31].

2.5.7 Storage for future use

The cells are frozen and stored for future use in therapeutics.

2.6 Gene therapy

Gene, the fundamental biological unit of heredity that constitutes an ordered sequence of nucleotides present in chromosomes. The functional aspect of a gene is to encode a protein or RNA molecule inherited from parents such as texture and color of the hair and eyes. Any kind of alterations/mutations in a gene sequence can lead to abnormal functionality of the genes. Gene therapy is a modern type of experimental technique in the medical field which involves rectifying the non-functional or malfunctioning of genes by replacing them with healthy and functional genes. Several approaches have been implemented by researchers in terms of correcting a mutated gene with a healthy copy of the gene or by inactivating the mutated gene causing disease. It has been widely studied for various diseases such as immune deficiency, blood disorders, eye problems, metabolic disorders, regeneration of nerve cells, and cancer [32]. The first case of gene therapy was discovered in the 1990s whereby a functional Adenosine Deaminase (ADA) gene was incorporated in the white blood cells of the patient, replacing the non-functional ADA [33]. This application led to interesting results with the immune systems and hence, was considered the most reliable technique.

There are two main methods for gene therapy such as- Ex-vivo gene therapy and In-vivo gene therapy. The former is the transfer of genes into patient cells outside the body and the latter one is the transfer of genes directly to cells inside the body. To carry this, several techniques are used like- direct or liposome-mediated injection of DNA, calcium phosphate transfection, electroporation, dendrimers, hybrid methods, retrovirus, and other viral vectors. Clinical conditions on which gene therapy has been applied are as follows:

2.6.1 Parkinson’s disease (PD)

The strategy of gene therapy has been applied to this disease in order to improve the advanced symptoms of PD. Gene therapy was applied to transfer ‘Glutamic Acid Decarboxylase (GAD), a chemical produced by a gene into the basal ganglia. GAD showed an increased amount of a neurotransmitter called as Gamma-Aminobutyric Acid (GABA), responsible for inhibiting brain signals and decreasing activity in the nervous system Decreased GABA activity leads to certain brain-related disorders [34].

2.6.2 Alzheimer’s disease (AD)

AD and other frontotemporal dementias (FTDs) are caused by the accumulation of amyloid-β peptide (Aβ) and protein tau in the brain. It is characterized by having memory loss, difficulty in learning and communicating along with the inability to organize things. The use of recombinant Adeno-Associated Viruses (rAAVs) has provided new ways for studying AD and other related neurological disorders [35]. Such strategies or approaches have added novel dimensions to medical treatments.

2.6.3 Cystic fibrosis

Cystic fibrosis is a disease known to affect the lungs primarily. Its symptoms include inflammation, airway obstruction leading to respiratory tract infection and deformity. Insertion of the Cystic Fibrosis Transmembrane Regulator (CFTR) gene directly into the epithelium cells of the respiratory tract bear the capability to lessen the symptoms but not totally cure the disease in patients suffering from cystic fibrosis [36].

2.7 Cell therapy

Cell-based therapy is one of the most important and well-known forms of all treatments in the fields of modern science & medicine. It is not only a curative option for treating deadly or threatening diseases but is also making ‘Regenerative Medicine’ the most vital technique in health care with the specific goal of replacing diseased cells, tissues or organs and thereby restoring their normal function(s) [4]. Over the years, there has been a gush of interests and work done in understanding the potential of stem cells. They are the cells found naturally in the living bodies, characterized by two defining properties of eternal self-renewal and the propensity to differentiate into an adult cell type. There are three main types of stem cells: Totipotent (a cell developing into a healthy organism independent of the permissive environment), Pluripotent (a cell developing into any type of adult cell) and Multipotent (a cell developing into a limited type of cell) [37].

Following is the account of different stem cells used for the treatment of various diseases:-

2.7.1 Pluripotent stem cells

Reportedly, pluripotent cells have been used successfully to treat animals per se. Animals diagnosed with diabetes are incorporated with cells containing insulin responsive to glucose levels. Additionally, the treatment of the animals suffering from acute spinal cord injury and visual impairment is performed with myelinated neurons and retinal epithelial cells, respectively. Researchers are still conducting studies with the use of pluripotent stem cells to cure several disorders such as Parkinson’s disease, muscular dystrophy and heart failure.

2.7.2 Induced pluripotent stem cells

The stem cells created artificially from normal adult somatic cells through co-expression of genes and factors are known as Induced Pluripotent Stem Cells (iPSCs). These are important for maintaining the characteristic properties of Embryonic Stem (ES) cells. Some reports have stated the successful use of iPSCs in conditions like Parkinson’s disease, spinal muscular atrophy, cardiac diseases, blood disorders, diabetes, amyotrophic lateral sclerosis, Huntington’s disease, and familial dysautonomia.

2.7.3 Multipotent stem cells

The multipotent stem cells derived from bone marrow (Hematopoietic stem cells) have been used in the 1960s to treat cancer conditions like leukemia, myeloma and lymphoma. Mesenchymal stem cells with the capability of forming whole joints in mouse models have been used regenerating bone and cartilages form. Curing heart ailments are still under clinical trial.

Advertisement

3. Applications of 3D cultures in vitro

Spurred by the recent advent in cell culture technologies, three-dimensional (3D) cell culture is paving the way in promoting tissue organization and cell differentiation by triggering tissue-based diseased microenvironment. An ideal 3D cell culture system generally composed of tightly bound tissues that involve cell–cell fluent interaction almost mimicking the extracellular matrix (ECM) that is highly dynamic and includes scaffolds of cells in a fluid that enhances them to differentiate (Table 1). The key parameter of a 3D culture environment is the ability to organize the spatial arrangement of cells with other surrounding cells along with physical constraints [8]. This significant approach has gardened great focus on understanding complex cellular biology and their responses by validating mammalian tissue studies via linking the gap between in vitro and in vivo environments. The two-dimensional (2D) cell cultures lack several features that 3D cultures impart such as tissue-specific architecture and complex cellular interactions that make them poor models for complex diseases. Based on the process of preparation, 3D techniques are categorized into (i) scaffold-based, (ii) scaffold-free culture systems. Scaffold-based technique efficiently is more responsive towards cell-to-ECM connection because of their potentiality of mimicking ECM whilst scaffold-free technique persuades physiological and cellular gradients. Scaffold or matrix is designed according to the tissue of interest, higher is the complexity of the scaffold, and the higher is the difficulty to extract the cells for analysis [9]. Majorly, the scaffolds manufactured are polymeric hard material-based support, microfluidic-based assembly, hydrophilic glass fiber, and organoids. In contrast, scaffold-free systems form cellular aggregates called spheroids that have evolved with improvement in their techniques such as magnetic levitation, liquid overlay (low adhesion plates), hanging drop microplates, and spheroid microplates yet the demand for 3D scaffolds preferentially increased due to their immense property of modulating the behavior of cultured cells according to the matrix in which they are cultured.

  1. 3.1 3D Spheroids

ApproachMeritsDemerits
3D Spheroids
  • High reproducibility

  • Expensive to prepare

  • Therapeutic inhibition to drug exposure can be easily evaluated through image analysis

  • Optimization protocols for each cell line is required

  • Constant perfusion

  • Difficult light matter interactions for large spheroids

  • Lower consumption of reagents

  • Differences in spheroids’ diameters,

  • Control of shear stress and pressure on cells

  • Low-throughput

  • Capable of imbibing large amount of water or biological fluid

  • Labour intensity

Hydrogels
  • Ease of maintenance

  • Low mechanical strength

  • Amenable of controlling the micro-tissue size and large amount of micro-tissues per plate

  • Difficult to handle

  • Expensive

Organoids
  • Amenable to high-throughput screening

  • Absence of microenvironment

  • Long lived organoid production from single cells

  • Optimization protocols are not globally standardized.

  • Organoid cultures rapidly die due to contamination

Cancer co-culture Models
  • Easily evaluate cell–cell interactions of cancer microenvironment

  • Microbial contamination

  • Provide fluid flow

  • Static condition

  • Easy to handle and quantify

  • Relevant mechanical cues

Organ-on-a-chip
  • Enable stable co-culture of living human cells

  • Architectural complexity of developing human tissues and organs

  • Good control over microenvironment

  • Difficulty in standardization and scale-up

Table 1.

Merits and demerits of different 3D cell culture techniques.

Organ typeIncorporated cell typesOrgan-specific propertiesRef.
LungPrimary lung alveolar epithelial cells
  • Breathing movements

[76, 77]
Primary lung endothelial cells
  • In vivo functionality array of tiny alveoli

  • Human lung parenchyma (lung alveoli and ultrathin air–blood barrier)

  • Recreates the native viscoelastic microenvironment of the cells

Human vascular endothelial cells
  • Alveolar capillary barrier in the human lung

[78]
Human alveolar epithelial cells
SkinPeripheral perfusion fluid (PPF)
  • Franz diffusion cell system

[79]
  • Drug absorption across the dermal barrier

  • Microfluidic Diffusion Chamber (MDC)

LiverHepatic cell lines
  • Hepatoprotective effect assessment

[80]
  • Hepatic activity (cell viability, albumin synthesis, urea secretion, and cytochrome P450 enzyme activities)

  • Drug Screening and Toxicity Testing

KidneyHuman podocytes
Glomerular endothelial cells
  • Human glomerular filtration barrier

[81]
  • Functions and structure of the glomerulus

Human-derived renal proximal tubule epithelial cells
  • Cell Polarization-Dependent Cisplatin Toxicity

[82]
  • Proximal tubule

HeartCardiomyocytes
  • Contractile behavior (contraction force, frequency, and synchronization) of a 3D cardiac tissue construct

  • Three-dimensional beating tissue from human cardiomyocytes

[83, 84]
PancreasHuman pancreatic beta-cell line
  • Human pseudo-islets in biomechanical flow conditions

[85]

Table 2.

Summary of recent organ-on-a-chip models.

3Dspheroids or multi-cellular aggregates are spherical micro-sized cellular constructs that are produced from numerous gamuts of cell types, originally from scaffold-free systems. The most characteristic features of 3D spheroids are the ability to recapitulate a cell’s typical physiological behavior, cellular heterogeneity, gene expression, cell–cell signaling, and structural architecture with respect to cell–cell contact [10]. Various types of 3Dspheroids include embryonic bodies, tumor spheroids (spheres of different tumorcells), hepatospheres (spheres of hepatic cells), neurospheres (spheres of different cell types of the central nervous system (CNS)) and mammospheres (spheres of mammary glands) [38]. An ideal 3D spheroid constitute ECM components such as proteoglycans, laminin, collagen, fibronectin, tenascin, and glycosaminoglycans [39] which tightens the spheroid density with close ECM-cell and cell–cell anchors eventually increase interstitial fluid pressure (IFP). Depending on the primary amount of cells seeded, the size of spheroid increases with an elevation in cell number, oxygen, and nutrient gradients equivalent to the tissue of interest [5]. Alongside, the different techniques enabling spheroid cultures are illustrated further.

Hanging drop technique is a non-scaffold method wherein a drop of media containing cells are suspended inversely on the lid of the culture dish (bottom-less and open) such that there is no surface provided for the cells and tend to hang. This attempt forms a cluster called spheroid at the tip of the droplet when cultured for a longer period [40]. Spheroids formed through hanging drop cultures have fetched considerable stance in cell culture technology with 100% reproducibility owing to ubiquitous applications in cancer research [41], toxicity testing in hepatocytes [42], and constructing cardiac spheroids [43]. Another method involves the use of a liquid overlay that eases the formation of aggregates and commercially produced as low adhesion plates. These spheroid microplates contain either hydrophilic or hydrophobic coating with V-shaped bottom and allow mild attachment to the surface such that the cells tend to self-aggregate and form spheroid. Unlike the hanging drop technique, low adhesion plates generate one spheroid per plate that signifies its importance for multicellular culture. This ensures a medium-throughput screening that requires no modification in spheroid formation [44]. Spheroids can also be cultured with the use of magnetic nanoparticles with the application of the magnetic field. The process is called magnetic cell levitation that is highly applied to produce spheroids of mesenchymal stem cells and tissue engineering [45, 46]. An in vivo study showed that human glioblastoma cells levitated by a magnetic approach closely mimicked the protein expression of human glioblastoma tumor xenografts [47].

3.2 Organoids

Organoids refer to the primary cultures derived from cell aggregates through in vitro process that is grown in 3D gels containing ECM to produce organ-like buds with the application of either physical support (cell adherence) or biochemical cues (signaling pathway modulation). Various types of cells such as embryonic, adult, primary, and stem cells are utilized for the development of organoids. Based on organ-like structures formed, organoids are classified into tissue and stem cell organoids. The application of organoids has helped in producing numerous in vitro organoids such as rectal [48], gastric [49], lung [50], liver [51], pancreas [52], retina [53], thyroid [54], kidney [55] and intestine [56] that had successfully recapitulated the structural and functional motif of real organs. 3D organoids are extensively used by researchers to decipher the toxicity analysis, examine the genetic pathologies and investigate the local immune responses to infections. In addition to this, current reports have suggested the promiscuous application of organoids in platforms like transcriptomics and proteomics technologies. One such example illustrates the interaction study between Zika virus and Toll-like receptor 3 is performed by the generation of cerebral organoids from embryonic stem cells [57]. They have been also used as models for distinct genetic diseases. For instance, a study applied the rectal organoid model of cystic fibrosis for the investigation of the potency of transmembrane regulator-modulating compounds [48]. Besides, the tubular organoids model of polycystic kidney disease was also used to unravel the cause for cyst formation [55]. Apart from this, organoids have been an excellent source of models to understand the depth of neurodegenerative diseases viz.; Alzheimer, Parkinson’s, HIV, diabetes, or cancer.

3.3 Cancer co-culture models

Cancer cell lines have emerged as an eminent tool for comprehending complex physiology of cancers. The cell cultures have eased the outlook in preclinical research to understand the process of disease, morphological changes occurring in tissue, gene function, cell biology and tissue engineering [58]. They have evolved with immense features of offering homogenous samples without any sort of modification and variations. However, a big leap was noted when monolayer cell cultures (2D) obtained from solid tumors were incapable of mimicking the structural elements of tumor microenvironment. Thusly, 3D cancer cell culture models have placed an enduring platform recently whereby ECM in 3D construct is same as that of original cell culture and imparted knowledge of predicting tumor response to treatment [59]. The application of 3D cell culture models of tumors have ought to manifest typical properties of tumor microenvironment such as gene and protein expressions, morphology, angiogenesis, malignancy and invasiveness. From this standpoint, 3D tumor cell culture models scintillate anticancer therapeutics and cancer drug discovery. To date, a vast content of literature owes the significance of these 3D co-cultures models in varying applications. In a study, tumor-associated macrophages (TAM) or cancer-associated fibroblasts (CAF) and gelatin hydrogel microspheres (GM) have been applied to produce cancer co-culture models from different cancer cells including HepG2 (liver), MCF-7 (breast) and WA-hT (lung) in order to inspect sustained release of drugs. They induced metastatic proteins involved in epithelial-mesenchymal transition (EMT) with transforming growth factor-β1 (TGF-β1) and reported elevation in N-cadherin and Vimentin proteins with deceleration in E-cadherin protein [58]. Recently, cancer co-culture models evinced interest in numerous approaches such as 3D breast cancer co-culture models obtained from MCF-7, MRC-5 and MDA-MB-231 tumor cells were used in investigating radiation-induced fibrosis [59], tumor-associated fibroblast differentiation [60] and development of immunotherapies [61], 3D lung cancer co-culture models derived lung squamous carcinoma and Non-Small Cell Lung Cancer Cells (NSCLC)fromTUM622, A549 and Colo699 tumor cells were utilized to explore tumor-stroma interactions [62, 63], 3D renal cancer co-culture models formed from Caki 1 (skin metastasis derived) and ACHN (pleural effusion derived) were sought for determining the efficacy of produced 3D models in stem cell physiology research and drug toxicity screening [64]. 3D colon cancer co-culture models acquired from LS 174 T, HCT 116, Colo205, MCF7, SW480, SW620, CCD-18Co, Caco-2, HT-29, and H446 have also been used to explore tumor-stroma interactions [65].

3.4 Tissue co-culture models

In vitro tissue models with the use of co-culture cells have emphasized greater applications to represent varying mechanisms of human body which is a daunting task. These models have served a vital role over several animal models that once were used to examine human physiology and pathophysiology. The major limitation of animal models was the failure of mimicking true human facets and their ethical constraints. This led to fetch insights into development of tissue models as a research tool from co-cultures such that the created models would possibly recapitulate the natural microenvironment of cells and examine the pathophysiological bases of diseases. Distinct in vitro 3D tissue models have been achieved with the approach of tissue engineering comprising human characteristics with increased complexity as compared to the 2D monolayers. Some of the examples of 3D models constructed from tissue co-cultures include kidney [66], neuro-glia [67], lung [68], liver [69], ovary [70] and intestine [71] that have potentially predicted and represented physiological responses of the original culture of cells. Most probably, primary cells are used as they possess feasible in vivo features of not being immortal, incapable of getting transformed and consist of limited survival time in culture. Pertaining to these advantages, they have been applied to develop models that would combat various disease and physiological studies. Reportedly, tissue models have been revolutionized in terms of investigating multiple changes in real-time processes. A pulmonary endothelium model was constructed to investigate massive inflammation in patients with acute respiratory disease syndrome (ARDS). The authors performed this study using lavage samples of the patients for determining the etiology of ARDS that took place during the process of disease [72]. In addition, endothelial cells have also played a key role in constructing 3D tissue models with their fascinating physiological roles. For instance, in vitro gastrointestinal epithelial cell cultures derived from adult murine colon allowed the authors to analyze epithelial cell–cell interactions, microbiological infections and cellular signaling [73]. Another instance showed the potential of hepatocyte tissue cultures in maintaining the cancer cell hierarchy in human hepatocellular carcinoma [74].

3.5 Organ-on-a-chip

Organ-on-a-chip is a biomimetic system that uses fabrication of computerized microchips and microfluids consisting of living cells, mimicking the natural environment of organs from which it is been created. There are several factors that made organ chips be listed in “Top Ten Emerging Technologies” in the World Economic Forum [75] such as shear force, tissue-boundaries, concentration gradients, tissue–organ interactions and cell patterning. Organ chips have intensified in the field of drug therapeutics for their ability of high throughput screening. Table 2 summarizes the recent researches carried out using various organ chips. These organ chips use microtechnology that provides nutrients to the cells for their better growth and proliferation. Microfluids are one such component that has been used in various studies for efficient treatment in drug sensitivity testing [86]. Talking of this notion, a microfluidic chip was produced in order to monitor and document real-time impedimetric biosensor changes. Other organ-on-a-chip models such as blood–brain barrier chips have been developed to represent the in vivo architecture of brain involving micro blood vessels by using type 1 collagen hydrogel. Another model entails the significance of human-on-a-chip that depicts the normal human physiology in combination with single organ chip within a microfluidic system that ultimately forms multi-organ chip [87]. One study dealt with an in vitro 3D-tumor-on-a-chip device that illustrated its importance in quorum sensing phenomenon in tumor cells activated by salmonella [88]. Hence, organ-on-a-chip has been diversified in many scientific platforms due to their efficient physiological bio-mimicry.

3.6 Patient-derived cells

Animal models used in laboratories have been greatly avoided due to the fact that they are costly and require a large number of laborers. This approach was replaced by the use of in vitro models wherein despite having several advantages; still, the application is constrained due to poor cell-to-cell and cell-to-matrix interactions. In vitro culture of cells has been observed to acquire multiple genetic and epigenetic variations that eventually make the cells lose their originality. The above-listed models comprise their own merits and demerits in respect of cellular response, cellular composition, and structural features. The above-mentioned models consist of a few advantages and disadvantages with respect to cellular composition, mimicking the in vivo physiology of original tumor architecture, tumor microenvironment (TME) and the response to different exogenous stimuli. Therefore, patient-derived cells have come into the picture which is generally a co-culture-based technology that is grown in a culture medium supplemented with all sorts of nutrients [89]. Different studies have exemplified the use of patient-derived cells as a preclinical model in drug discovery (screening and responses) in several types of cells. Patient-derived xenograft (PDX)models are made of minute pieces of tumor tissue of the surgical patients, utilized for implantation into an immune-deficient mouse. In a study, Fong et al. used PDX models from prostate cancer to investigate tumor-stromal interactions via the use of a 3D hydrogel system [90]. Likewise, in another study, Liu et al. demonstrated the establishment of patient-derived cell cultures from colorectal cancer cells of biopsies of cancerous and non-cancerous tissue that could grow in in vitro culture indefinitely by recapitulating exactly the same phenotypic and genotypic features of the original tissue [91]. Some of the researchers have also elaborated patient-derived 3D culture using a scaffold-based organoid culture that is prepared to preserve the genomic features of the original tissue [92].

Advertisement

4. Three-dimensional cell culture in drug discovery and development

Drug discovery is a lengthy and time-consuming process that undergoes several stages of testing and optimization. This encompasses identification of the target, lead discovery, pre-clinical validation, and clinical trials [3]. Due to the constant failure of drugs in Phase II and Phase III clinical trials, there has been constant pressure on the pharmaceutical industry to seek more novel drugs with lower side effects and cost-effectiveness. 3D cell culture has emerged as a significant high-throughput system that has uplifted the standards of cell culture [93]. Specifically, spheroids are considered the most reliable model for testing drugs in various diseases because of their capability of resembling the natural environment of original tissue [93]. The spatial organization of spheroids in different layers of cells leads to cellular death by forming reactive oxygen species [94]. In the case of investigating the effect in 3D spheroids, fluorescence microscopy plays a key role in determining pharmaceutical dispersion within spheroids (eg-doxorubicin and epirubicin) [95]. The capital importance of any drug testing involves cell-based assays that are efficient enough and easily reproducible compared to expensive animal models. Cell-based assays have shaped the physiological relevance of 2D cultures [96]. While the reaction may vary from technique to technique such as cell viability, proliferation, signaling and migration and drug to drug for achieving better sensitivity. It is now broadly accepted that compared to 2D cultures, 3D models serve the resemblance of the natural environment of original tissue efficiently and differently in 3D environments. Research has nested stance on novel 3D culture technologies that impart functional basis of tissues such as spheroids and organoids [97]. A study used 3D hydrogel-based model for the determination of drug sensitivity in HepG2 cell lines by comparing cytotoxicity effect with cytotoxicity (CT50) and lethal dose (LD50) values [98]. Organoid 3D models also aid as a resourceful tool for modeling neurodevelopmental disorders [98]. Microfluidic chips have also been utilized in drug sensitivity testing whereby a study elaborated its efficacy in lung cancer which was in combination with stromal cell lines [98]. Evaluation of absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the drug is primarily examined in in vitro cell culture experiments. 3D cell cultures have fostered drug pharmacokinetics in several studies with the implementation of various types of cell culture models.

Advertisement

5. Cell based manufacturing of therapeutic proteins

Therapeutic proteins production using human cell lines has greatly influenced different medical areas including biopharmaceutical research and vaccine production. Mammalian cell lines prove futile in protein production due to their likelihood of possessing post-translational modifications (PTMs) achieved from recombinant proteins that are in accordance with the endogenous human proteins. These cell lines show exquisite specificity to produce similar proteins to those in humans naturally synthesized, an advantage over mammalian expression systems [99]. One of the most routinely and high yields of proteins production is performed by using cell-based expression systems such as Chinese hamster ovary (CHO) a cell line that constitutes major advances such as accomplishment of gene amplification, specific productivity, better selection strategies, and devising greater expression units and advanced hosts. CHO cells have established their safety profile for 20 years from the production of its first recombinant biotherapeutic protein in 1986 [100]. Other human cell lines such as BHK-21 cells are used for the generation of few coagulation factors such as factor VIII [101]. There are two vital human cell lines namely, HEK293 and HT-1080 that are used to manufacture licensed products of human PTMs. The advancement in protein-based drug development and technologies has driven more towards the therapeutic proteins market that comprises of sales of these therapeutic proteins. The methods that are involved in the production of these proteins are pegylation, glycoengineering, albumin fusion, Fc-fusion, product purity, targeting, and functionality of therapeutic protein drugs. Few examples of therapeutic protein drugs which has been produced using protein engineering technologies and approved by the Food and Drug Administration (FDA) from the past five years are imiglucerase, Belimumab, alfa, coagulation factor IX recombinant human and albiglutide [102]. A French pharmaceutical company named Sanofi accomplished a great achievement of strengthening its R&D strategy with the best proprietary therapeutic proteins production pharmaceutical company, Ablynx, for a nanobody technology platform.

Advertisement

6. Conclusion

In particular, a plethora of research studies have shed light on the fact that in spite of the availability of advanced organ-on-chip technologies and bioengineered 3D models, the application is limited by drug companies due to their relatively novel approach which is more likely requires to undergo further validation and characterization. Moreover, 3D cell culture models with high-throughput screening in combination with high-content leads to the identification of clinically relevant compounds. However, still many difficulties are being faced as 3D cell cultures do not meet certain criteria in the drug discovery process with regard to size, morphology, complexity, and protocol for assaying. It requires ample standardization and optimization to extract successful specific phenotypes for drug screening. Thus, there are few 3D models that are constrained for their restricted access due to limited permeability. Following the advances in protein therapeutics, more improvements in generating sophisticated therapeutic protein products will be developed for better futuristic research.

Advertisement

Acknowledgments

Authors thanks, Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Tathawade, Pune, for providing necessary facilities. This work was supported by Dr. D. Y. Patil Vidyapeeth seed grant (DPU/14/2016, dated 06/01/2016).

Advertisement

Conflict of interest

There are no conflicts of interest.

Advertisement

Abbreviations

2DTwo-dimensional
3DThree-dimensional culture
Amyloid-β peptide
ADMETAbsorption, distribution, metabolism, excretion and toxicity
ADAAdenosine Deaminase
ADAlzheimer’s disease
ARDSAcute respiratory disease syndrome
CAFCancer-associated fibroblasts
CCDCharge-Coupled Device
CFTRCystic fibrosis transmembrane regulator
CHOChinese hamster ovary
CNSCentral nervous system
CSCsCancer stem cells
CT50Cytotoxicity 50 percent
CSRClass Switch Recombination
DICDifferential Interference Contrast microscopy
ECMExtracellular matrix
ESEmbryonic Stem
EMTEpithelial-mesenchymal transition
FTDsFrontotemporal dementias
GABAGamma-Aminobutyric Acid
GADGlutamic Acid Decarboxylase
GMGelatin hydrogel microspheres
HATHypoxanthine, Aminopterin, Thymidine
IFPInterstitial fluid pressure
iPSCsInduced pluripotent stem cells
LDHLactate dehydrogenase
LD50Lethal dose 50 percent
MTT3-(4,5-dimethythiazol2-yl)-2,5-diphenyl tetrazolium bromide
MTS3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium
MDCMicrofluidic Diffusion Chamber
mAbsMonoclonal Antibodies
NADNicotinamide adenine dinucleotide
NADHReduced nicotinamide adenine dinucleotide
NADPHNicotinamide adenine dinucleotide phosphate
NSCLCNon-Small Cell Lung Cancer Cells
pAbsPolyclonal Antibodies
PDXPatient-derived xenograft
PDParkinson’s Disease
PPFPeripheral perfusion fluid
PTMsPost-translational modifications
rAAVsAdeno-Associated Viruses
SRBSulforhodamine B
TAMTumor-associated macrophages
TGF-β1Transforming growth factor-β1
TMETumor microenvironment
XTT2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide.

References

  1. 1. Hudu SA, Alshrari AS, Syahida A, Sekawi Z. Cell Culture, Technology: Enhancing the Culture of Diagnosing Human Diseases. J ClinDiagn Res. 2016;10(3):DE01-DDE5. DOI:10.7860/JCDR/2016/15837.7460
  2. 2. Verma A, Verma M, Singh A. Animal tissue culture principles and applications. Animal Biotechnology. 2020;269-293. DOI:10.1016/B978-0-12-811710-1.00012-4
  3. 3. Smith SC, Baras AS, Lee JK, Theodorescu D. The COXEN principle: translating signatures of in vitro chemosensitivity into tools for clinical outcome prediction and drug discovery in cancer. Cancer Res. 2010; 70,1753-1758. DOI: 10.1158/0008-5472.CAN-09-3562
  4. 4. Michelini E, Cevenini L, Mezzanotte L, Coppa A, Roda A. Cell-based assays: fuelling drug discovery. Anal Bioanal Chem. 2010; 398(1):227-238. DOI: 10.1007/s00216-010-3933-z
  5. 5. Kapałczyńska M, Kolenda T, Przybyła W, Zajączkowska M, Teresiak A, Filas V, Ibbs M, Bliźniak R, Łuczewski Ł, Lamperska K. 2D and 3D cell cultures - a comparison of different types of cancer cell cultures. Arch Med Sci. 2018;14(4):910-919. DOI:10.5114/aoms.2016.63743
  6. 6. Verma A, Verma M, Singh A. Animal tissue culture principles and applications. Animal Biotechnology. 2020; 269-293. DOI:10.1016/B978-0-12-811710-1.00012-4
  7. 7. Kamińska K, Szczylik C, Bielecka ZF, Bartnik E, Porta C, Lian F, Czarnecka AM. The role of the cell-cell interactions in cancer progression. Journal of cellular and molecular medicine. 2015; 19(2), 283-296. DOI: 10.1111/jcmm.12408
  8. 8. Ravi M, Paramesh V, Kaviya SR, Anuradha E, Solomon FDP. 3D cell culture systems: Advantages and applications. Journal of Cellular Physiology. 2015;230(1):16-26. DOI: 10.1002/jcp.24683
  9. 9. Fennema E, Rivron N, Rouwkema J, van Blitterswijk C, de Boer J. Spheroid culture as a tool for creating 3D complex tissues. Trends in Biotechnology. 2013;31(2):108-115. DOI: 10.1016/j.tibtech.2012
  10. 10. Zanoni M, Piccinini F, Arienti C, Zamagni A, Santi S, Polico R, Bevilacqua A, Tesei A. 3D tumor spheroid models for in vitro therapeutic screening: A systematic approach to enhance the biological relevance of data obtained. Sci. Rep. 2016;6:19103. DOI: 10.1038/srep19103
  11. 11. Duval K, Grover H, Han LH, Mou Y, Pegoraro AF, Fredberg J, Chen Z. Modeling Physiological Events in 2D vs. 3D Cell Culture. Physiology (Bethesda). 2017;32(4):266-277. DOI: 10.1152/physiol.00036.2016
  12. 12. Freimoser FM, Jakob CA, Aebi M, Tuor U. The MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay is a fast and reliable method for colorimetric determination of fungal cell densities. Appl Environ Microbiol. 1999;65(8):3727-3729. DOI:10.1128/AEM.65.8.3727-3729.1999
  13. 13. Lomakina GY, Modestova YA, Ugarova NN. Bioluminescence assay for cell viability. Biochemistry (Mosc). 2015;80(6):701-713. DOI:10.1134/S0006297915060061
  14. 14. Kumar P, Nagarajan A, Uchil PD. Analysis of Cell Viability by the Lactate Dehydrogenase Assay. Cold Spring HarbProtoc. 2018; 2018(6). DOI:10.1101/pdb.prot095497
  15. 15. Khodabukus A, Prabhu N, Wang J, Bursac N. In Vitro Tissue-Engineered Skeletal Muscle Models for Studying Muscle Physiology and Disease. AdvHealthc Mater. 2018; 7(15):e1701498. doi:10.1002/adhm.201701498
  16. 16. DeStefano JG, Jamieson JJ, Linville RM, Searson PC. Benchmarking in vitro tissue-engineered blood-brain barrier models. Fluids Barriers CNS. 2018; 15(1):32. DOI:10.1186/s12987-018-0117-2
  17. 17. Shen TW, Puccini B, Temnyk K, Herting S, Cardinal KO. Tissue-engineered aneurysm models for in vitro assessment of neurovascular devices. Neuroradiology. 2019; 61(6):723-732. DOI:10.1007/s00234-019-02197-x
  18. 18. Jakubowska W, Chabaud S, Saba I, Galbraith T, Berthod F, Bolduc S. Prevascularized Tissue-Engineered Human Vaginal Mucosa: In Vitro Optimization and In Vivo Validation. Tissue Eng Part A. 2020; 26(13-14):811-822. DOI:10.1089/ten.tea.2020.0036
  19. 19. Winkler J, Abisoye-Ogunniyan A, Metcalf KJ,Zena W. Concepts of extracellular matrix remodelling in tumour progression and metastasis. Nat Commun. 2020; 11(1), 5120. DOI:10.1038/s41467-020-18794-x
  20. 20. Grada A, Otero-Vinas M, Prieto-Castrillo F, Obagi Z, Falanga V. Research Techniques Made Simple: Analysis of Collective Cell Migration Using the Wound Healing Assay. J Invest Dermatol. 2017; 137(2):e11-e16. DOI:10.1016/j.jid.2016.11.020
  21. 21. Pijuan J, Barceló C, Moreno DF, Maiques O, Sisó P, Marti RM, Macià A, Panosa A. In vitro Cell Migration, Invasion, and Adhesion Assays: From Cell Imaging to Data Analysis. Frontiers in cell and developmental biology, 2019; 7, 107. DOI: 10.3389/fcell.2019.00107
  22. 22. Gau DM, Roy P. Single Cell Migration Assay Using Human Breast Cancer MDA-MB-231 Cell Line. Bio Protoc. 2020; 10(8):e3586. DOI:10.21769/bioprotoc.3586
  23. 23. Franken NA, Rodermond HM, Stap J, Haveman J, van Bree C. Clonogenic assay of cells in vitro. Nat Protoc. 2006; 1(5):2315-2319. DOI:10.1038/nprot.2006.339
  24. 24. Rajendran V, Jain MV. In Vitro Tumorigenic Assay: Colony Forming Assay for Cancer Stem Cells. Methods Mol Biol. 2018; 1692:89-95. DOI:10.1007/978-1-4939-7401-6_8
  25. 25. Wang H, Paczulla AM, Konantz M, Lengerke C. In Vitro Tumorigenic Assay: The Tumor Spheres Assay. Methods Mol Biol. 2018; 1692:77-87. DOI:10.1007/978-1-4939-7401-6_7
  26. 26. Justus CR, Leffler N, Ruiz-Echevarria M, Yang LV. In vitro cell migration and invasion assays. J Vis Exp. 2014; (88):51046. DOI:10.3791/51046
  27. 27. Gómez-Villafuertes R, Paniagua-Herranz L, Gascon S, de Agustín-Durán D, Ferreras M O, Gil-Redondo JC, Queipo MJ, Menendez-Mendez A, Pérez-Sen R, Delicado EG, Gualix J, Costa MR, Schroeder T, Miras-Portugal MT, Ortega F. Live Imaging Followed by Single Cell Tracking to Monitor Cell Biology and the Lineage Progression of Multiple Neural Populations. J Vis Exp. 2017; (130):56291. DOI:10.3791/56291
  28. 28. Fardin MA, Rossier OM, Rangamani P, Avigan PD, Gauthier NC, Vonnegut W, Mathur A, Hone J, Iyengar R, Sheetz MP. Cell spreading as a hydrodynamic process. Soft Matter. 2010; 6(19), 4788. DOI:10.1039/c0sm00252f
  29. 29. Parray HA, Shukla S, Samal S, Shrivastava T, Ahmed S, Sharma C, Kumar R. Hybridoma technology a versatile method for isolation of monoclonal antibodies, its applicability across species, limitations, advancement and future perspectives. IntImmunopharmacol. 2020; 85:106639. DOI:10.1016/j.intimp.2020.106639
  30. 30. Holzlöhner P, Hanack K. Generation of Murine Monoclonal Antibodies by Hybridoma Technology. J Vis Exp. 2017; (119):54832. DOI:10.3791/54832
  31. 31. Carvalho LS, Bravim da Silva O, Carneiro de Almeida G, Davies de Oliveira J, ParachinNS,Carmo TS. Production Processes for Monoclonal Antibodies. Intechopen; 2017. DOI:10.5772/61924(Chapter 10)
  32. 32. Gonçalves GAR, Paiva RMA. Gene therapy: advances, challenges and perspectives. Einstein (Sao Paulo). 2017;15(3):369-375. DOI:10.1590/S1679-45082017RB4024
  33. 33. Aiuti A, Roncarolo MG, Naldini L. Gene therapy for ADA-SCID, the first marketing approval of an ex vivo gene therapy in Europe: paving the road for the next generation of advanced therapy medicinal products. EMBOMol Med. 2017; 9(6):737-740. DOI:10.15252/emmm.201707573
  34. 34. Axelsen TM, Woldbye DPD. Gene Therapy for Parkinson's Disease, An Update. J Parkinsons Dis. 2018; 8(2):195-215. DOI:10.3233/JPD-181331
  35. 35. Combs B, Kneynsberg A, Kanaan NM. Gene Therapy Models of Alzheimer's Disease and Other Dementias. Methods Mol Biol. 2016; 1382:339-366. DOI:10.1007/978-1-4939-3271-9_25
  36. 36. Marquez Loza LI, Cooney AL, Dong Q, Randak CO, Rivella S, Sinn PL, McCray PB. Increased CFTR expression and function from an optimized lentiviral vector for cystic fibrosis gene therapy. MolTher Methods Clin Dev. 2021;21:94-106. DOI:10.1016/j.omtm.2021.02.020
  37. 37. Aly RM. Current state of stem cell-based therapies: an overview. Stem Cell Investig. 2020;7:8. DOI:10.21037/sci-2020-001
  38. 38. Edmondson R, Broglie JJ, Adcock AF, Yang L. Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors. Assay Drug DevTechnol. 2014;12(4):207-218. DOI:10.1089/adt.2014.573
  39. 39. Yeon SE, No da Y, Lee SH, Nam SW, Oh IH, Lee J, Kuh HJ. Application of concave microwells to pancreatic tumor spheroids enabling anticancer drug evaluation in a clinically relevant drug resistance model. PLoS One. 2013;8(9):e73345. DOI:10.1371/journal.pone.0073345
  40. 40. Tung YC, Hsiao AY, Allen SG, Torisawa YS, Ho M, Takayama S. High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array. Analyst. 2011;136(3):473-478. DOI: 10.1039/c0an00609b
  41. 41. Zhao L, Xiu J, Liu Y,Zhang T, Pan W, Zheng X, Zhang X. A 3D Printed Hanging Drop Dripper for Tumor Spheroids Analysis Without Recovery. Sci Rep 2019; 9, 19717. DOI: 10.1038/s41598-019-56241-0
  42. 42. Hurrell T, Ellero AA, Masso ZF, Cromarty AD. Characterization and reproducibility of HepG2 hanging drop spheroids toxicology in vitro. Toxicol In Vitro. 2018;50:86-94. DOI: 10.1016/j.tiv.2018.02.013
  43. 43. Bai Y, Yeung E, Lui C, Ong CS, Pitaktong I, Huang C, Inoue T, Matsushita H, Ma C, Hibino NA. Net Mold-based Method of Scaffold-free Three-Dimensional Cardiac Tissue Creation. J. Vis. Exp. 2018; 138, e58252. DOI:10.3791/58252
  44. 44. Raghavan S, Mehta P, Horst EN, Ward MR, Rowley KR, Mehta G. Comparative analysis of tumor spheroid generation techniques for differential in vitro drug toxicity. Oncotarget. 2016;7(13):16948-61. DOI: 10.18632/oncotarget.7659
  45. 45. Lewis EEL, Wheadon H, Lewis N, Yang J, Mullin M, Hursthouse A, Stirling D, Dalby MJ, Berry CC. A Quiescent, Regeneration-Responsive Tissue Engineered Mesenchymal Stem Cell Bone Marrow Niche Model via Magnetic Levitation. ACS Nano. 2016; 10, 9, 8346-8354. DOI:10.1021/acsnano.6b02841
  46. 46. Lewis NS, Lewis EE, Mullin M, Wheadon H, Dalby MJ, Berry CC. Magnetically levitated mesenchymal stem cell spheroids cultured with a collagen gel maintain phenotype and quiescence. J Tissue Eng. 2017; 8:2041731417704428. DOI: 10.1177/2041731417704428
  47. 47. Souza GR, Molina JR, Raphael RM, Ozawa MG, Stark DJ, Levin CS, Bronk LF, Ananta JS, Mandelin J, Georgescu MM, Bankson JA, Gelovani JG, Killian TC, Arap W, Pasqualini R. Three-dimensional tissue culture based on magnetic cell levitation. Nat Nanotechnol. 2010; (4):291-296. DOI: 10.1038/nnano.2010.23
  48. 48. Dekkers J, Berkers G, Kruisselbrink E, Vonk A, de Jonge H, Janssens HM, Bronsveld, I., van de Graaf EA, Nieuwenhuis EE, Houwen RH, Vleggaar FP, Escher JC, de Rijke YB, Majoor CJ, Heijerman HG, de Winter-de Groot KM, Clevers H, van der Ent CK, Beekman JM. Characterizing responses to CFTR-modulating drugs using rectal organoids derived from subjects with cystic fibrosis. SciTransl Med. 2016; 8:344ra84. DOI:10.1126/scitranslmed.aad8278
  49. 49. Seidlitz T, Koo BK,Stange DE. Gastric organoids—an in vitro model system for the study of gastric development and road to personalized medicine. Cell Death Differ. 2021; 28, 68-83. DOI: 10.1038/s41418-020-00662-2
  50. 50. Cunniff B, Druso JE, van der Velden JL. Lung organoids: advances in generation and 3D-visualization. HistochemCell Biol. 2021; 155, 301-308. DOI: org/10.1007/s00418-020-01955-w
  51. 51. Prior N, Inacio P, Huch M. Liver organoids: from basic research to therapeutic applications. Gut. 2019; 68(12):2228-2237. DOI:10.1136/gutjnl-2019-319256
  52. 52. Wills ES, Drenth JP. Building pancreatic organoids to aid drug development. Gut. 2017; 66(3):393-394. DOI:10.1136/gutjnl-2016-312865
  53. 53. Cowan CS, Renner M, De Gennaro M, Gross-Scherf B, Goldblum D, Hou Y, Munz M, Rodrigues TM, Krol J, Szikra T, Cuttat R, Waldt A, Papasaikas P, Diggelmann R, Patino-Alvarez CP, Galliker P, Spirig SE, Pavlinic D, Gerber-Hollbach N, Schuierer S, Aldin Srdanovic 8, Marton Balogh 3, Riccardo Panero 3, Akos Kusnyerik, Arnold Szabo A, Michael B Stadler MB, Selim Orgül S, Simone Picelli S, Pascal W Hasler PW, Andreas Hierlemann A, Scholl HPN, Roma G, Nigsch F, Roska B. Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution. Cell. 2020; 182(6),1623-1640.e34. DOI: 10.1016/j.cell.2020.08.0
  54. 54. Saito Y, Onishi N, Takami, H, Seishima R, Inoue H, Hirata Y, Kameyama K, Tsuchihashi K, Sugihara E, Uchino S, Ito K, Kawakubo H, Takeuchi H, Kitagawa Y, Saya H, Nagano O. (). Development of a functional thyroid model based on an organoid culture system. Biochemical and biophysical research communications. 2018; 497(2), 783-789. DOI:10.1016/j.bbrc.2018.02.154
  55. 55. Cruz NM, Song X, Czerniecki SM, Gulieva RE, Churchill AJ, Kim YK, Winston K, Tran LM, Diaz MA, Fu H, Finn LS, Pei Y, Himmelfarb J, Freedman BS. (). Organoid cystogenesis reveals a critical role of microenvironment in human polycystic kidney disease. Nature materials. 2017; 16(11), 1112-1119. DOI: 10.1038/nmat4994
  56. 56. Bareiss PM, Metzger M, Sohn K, Rupp S, Frick JS, Autenrieth IB, Lang F, Schwarz H, Skutella T, Just L. Organotypical tissue cultures from adult murine colon as an in vitro model of intestinal mucosa. Histochemistry and cell biology. 2008; 129(6), 795-804. DOI: 10.1007/s00418-008-0405-z
  57. 57. Qian X, Nguyen HN, Jacob F, Song H, Ming GL. Using brain organoids to understand Zika virus-induced microcephaly. Development. 2017; 144(6):952-957. DOI:10.1242/dev.140707
  58. 58. Yakavets I, Francois A, Benoit A, Merlin JL, Bezdetnaya L, Guillaume Vogin G. Advanced co-culture 3D breast cancer model for investigation of fibrosis induced by external stimuli: optimization study. Sci Rep. 2020; 10,21273. DOI:10.1038/s41598-020-78087-7
  59. 59. Kunz-Schughart LA, Heyder P, Schroeder J, Knuechel R. A heterologous 3-D coculture model of breast tumor cells and fibroblasts to study tumor-associated fibroblast differentiation. ExpCell Res. 2001; 266(1):74-86. DOI:10.1006/excr.2001.5210
  60. 60. Saraiva DP, Matias AT, Braga S, Jacinto A, Cabral MG. Establishment of a 3D Co-culture With MDA-MB-231 Breast Cancer Cell Line and Patient-Derived Immune Cells for Application in the Development of Immunotherapies. Front Oncol. 2020; 10:1543. DOI:10.3389/fonc.2020.01543
  61. 61. Chen S, Giannakou A, Golas J, Geles KG. Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression. J. Vis. Exp. 2020; (157), e60644, DOI:10.3791/60644
  62. 62. Amann A, Zwierzina M, Gamerith G, Bitsche M, Huber J M, Vogel GF, Blumer M, Koeck S, Pechriggl EJ, Kelm JM, Hilbe W, Zwierzina H. Development of an Innovative 3D Cell Culture System to Study Tumour - Stroma Interactions in Non-Small Cell Lung Cancer Cells. PLoS ONE. 2014; 9(3), e92511. DOI:10.1371/journal.pone.0092511
  63. 63. Brodaczewska KK, Bielecka ZF, Maliszewska Olejniczak K, Szczylik C, Porta C, Bartnik E, Czarnecka AM. Metastatic renal cell carcinoma cells growing in 3D on poly-D-lysine or laminin present a stem-like phenotype and drug resistance. Oncol Rep. 2019;42(5):1878-1892. DOI:10.3892/or.2019.7321
  64. 64. Dolznig H, Rupp C, Puri C, Haslinger C, Schweifer N, Wieser E, Kerjaschki D, Garin-Chesa P. Modeling colon adenocarcinomas in vitro a 3D co-culture system induces cancer-relevant pathways upon tumor cell and stromal fibroblast interaction. Am J Pathol. 2011; 179(1):487-501. DOI:10.1016/j.ajpath.2011.03.015
  65. 65. Dolznig H, Rupp C, Puri C, Haslinger C, Schweifer N, Wieser E, Kerjaschki D, Garin-Chesa P. Modeling colon adenocarcinomas in vitro a 3D co-culture system induces cancer-relevant pathways upon tumor cell and stromal fibroblast interaction. The American journal of pathology. 2011; 179(1), 487-501. DOI:10.1016/j.ajpath.2011.03.015
  66. 66. Takasato M, Little MH. Making a Kidney Organoid Using the Directed Differentiation of Human Pluripotent Stem Cells. Methods Mol Biol. 2017; 1597:195-206. DOI:10.1007/978-1-4939-6949-4_14
  67. 67. Skaper SD, Facci L. Central Nervous System Neuron-Glia co-Culture Models and Application to Neuroprotective Agents. Methods Mol Biol. 2018; 1727:63-80. DOI:10.1007/978-1-4939-7571-6_5
  68. 68. Strikoudis A, Cieślak A, Loffredo L, Chen YW, Patel N, Saqi A, Lederer DJ, Snoeck HW. Organoids Derived from Human Pluripotent Stem Cells. Cell Rep. 2019; 27(12):3709-3723.e5. DOI:10.1016/j.celrep.2019.05.077
  69. 69. Coll M, Perea L, Boon R, Leite SB, Vallverdú J, Mannaerts I, Smout A, El Taghdouini, A, Blaya D, Rodrigo-Torres D, Graupera I, Aguilar-Bravo B, Chesne C, Najimi M, Sokal E, Lozano JJ, van Grunsven LA, Verfaillie CM, Sancho-Bru P. Generation of Hepatic Stellate Cells from Human Pluripotent Stem Cells Enables In Vitro Modeling of Liver Fibrosis. Cell Stem Cell. 2018; 23(1):101-113.e7. DOI:10.1016/j.stem.2018.05.027
  70. 70. Saadeldin IM, Kim SJ, Choi YB, Lee BC. Improvement of cloned embryos development by co-culturing with parthenotes: a possible role of exosomes/microvesicles for embryos paracrine communication. Cell Reprogram. 2014; 16(3):223-234. DOI:10.1089/cell.2014.0003
  71. 71. Jalili-Firoozinezhad S, Gazzaniga FS, Calamari EL, Camacho DM, Fadel CW, Bein A, Swenor B, Nestor B, Cronce MJ, Tovaglieri A, Levy O, Gregory KE, Breault DT, Cabral J, Kasper DL, Novak R, Ingber DE. A complex human gut microbiome cultured in an anaerobic intestine-on-a-chip. Nat Biomed Eng. 2019; 3(7):520-531. DOI:10.1038/s41551-019-0397-0
  72. 72. Murphy LS, Wickersham N, McNeil JB, Shaver CM, May AK, Bastarache JA, Ware LB. Endothelial glycocalyx degradation is more severe in patients with non-pulmonary sepsis compared to pulmonary sepsis and associates with risk of ARDS and other organ dysfunction. Ann Intensive Care. 2017; 7(1):102. DOI:10.1186/s13613-017-0325-y
  73. 73. Krump-Konvalinkova V, Bittinger F, Unger RE, Peters K, Lehr HA, Kirkpatrick CJ. Generation of human pulmonary microvascular endothelial cell lines. Lab Invest. 2001; 81(12):1717-1727. DOI:10.1038/labinvest.3780385
  74. 74. Kosuge M, Takizawa H, Maehashi H, Matsuura T, Matsufuji S. A comprehensive gene expression analysis of human hepatocellular carcinoma cell lines as components of a bioartificial liver using a radial flow bioreactor. Liver Int. 2007; 27(1):101-108. DOI:10.1111/j.1478-3231.2006.01410.x
  75. 75. World Economic Forum. Top Ten Emerging Technologies [Internet]. 2016. Available from:https://www.weforum.org/agenda/2016/06/top-10-emerging-technologies-2016/ [Accessed: 2016-06-23]
  76. 76. Stucki JD, Hobi N, Galimov A, Stucki AO, Schneider-Daum N, Lehr CM, Huwer H, Frick M, Funke-Chambour M, Geiser T, Guenat OT. Medium throughput breathing human primary cell alveolus-on-chip model. Scientific reports 8(1), 2018; 14359. DOI: 10.1038/s41598-018-32523-x
  77. 77. Zhang M, Xu C, Jiang L, Qin J. A 3D human lung-on-a-chip model for nanotoxicity testing. Toxicol Res (Camb). 2018;11;7(6):1048-1060. DOI: 10.1039/c8tx00156a
  78. 78. Zamprogno P, Wüthrich S, Achenbach S,Zamprogno P, Wüthrich S, Achenbach S, Thoma G, Stucki JD, Hobi N, Schneider-Daum N, Lehr CM, Huwer H, Geiser T, Schmid RA, Guenat OT. Second-generation lung-on-a-chip with an array of stretchable alveoli made with a biological membrane. Commun Biol. 2021;4(1):168. DOI:10.1038/s42003-021-01695-0
  79. 79. Lukács B., Bajza Á, Kocsis D, Csorba A, Antal I, Iván K, Laki A J, Erdő F. Skin-on-a-Chip Device for Ex Vivo Monitoring of Transdermal Delivery of Drugs-Design, Fabrication, and Testing. Pharmaceutics. 2019; 11(9), 445. DOI:10.3390/pharmaceutics11090445
  80. 80. Deng J, Cong Y, Han X, Wei W, Lu Y, Liu T, Zhao W, Lin B, Luo Y, Zhang X. A liver-on-a-chip for hepatoprotective activity assessment. Biomicrofluidics. 2020; 14(6):064107. DOI:10.1063/5.0024767
  81. 81. Petrosyan A, Cravedi P, Villani V, Angeletti A, Manrique J, Renieri AR, DeFilippo RE, Perin LP, Da Sacco SA. Glomerulus-on-a-chip to recapitulate the human glomerular filtration barrier. Nat Commun. 2019; 10, 3656. Doi:10.1038/s41467-019-11577-z
  82. 82. Nieskens TTG, Persson M, Kelly EJ, Sjögren AK. A Multicompartment Human Kidney Proximal Tubule-on-a-Chip Replicates Cell Polarization-Dependent Cisplatin Toxicity. Drug MetabDispos. 2020; 48(12):1303-1311. DOI:10.1124/dmd.120.000098
  83. 83. Sakamiya M, Fang Y, Mo X, Shen J, Zhang T. A heart-on-a-chip platform for online monitoring of contractile behavior via digital image processing and piezoelectric sensing technique. Med Eng Phys. 2020; 75:36-44. DOI:10.1016/j.medengphy.2019.10.001
  84. 84. Zhao Y, Rafatian N, Wang EY, Feric NT, Lai B, Knee-Walden EJ, Backx PH, Radisic M. Engineering microenvironment for human cardiac tissue assembly in heart-on-a-chip platform. Matrix Biol. 2020; 85-86:189-204. DOI:10.1016/j.matbio.2019.04.001
  85. 85. Zbinden A, Marzi J, Schlünder K, Probst C, Urbanczyk M, Black S, Brauchle EM, Layland SL, Kraushaar U, Duffy G, Schenke-Layland K, Loskill P. Non-invasive marker-independent high content analysis of a microphysiological human pancreas-on-a-chip model. Matrix Biol. 2020; 85-86:205-220. DOI:10.1016/j.matbio.2019.06.008
  86. 86. Zhiyun X, Yanghui G, YuanyuanH, Encheng L, Yan W, Jianing Z. Application of a microfluidic chip-based 3D co-culture to test drug sensitivity for individualized treatment of lung cancer. Biomaterials. 2013; 34:4109-17. DOI:10.1016/j.biomaterials.2013.02.045
  87. 87. Huh D, Hamilton GA, Ingber DE. From 3D cell culture to organs-on-chips. Trends Cell Biol. 2011;21(12):745-754. DOI:10.1016/j.tcb.2011.09.005
  88. 88. Swofford CA, Van Dessel N, Forbes NS. Quorum-sensing Salmonella selectively trigger protein expression within tumors. Proc. Natl. Acad. Sci. U S A. 2015; 112:3457-3462. DOI: 10.1073/pnas.1414558112
  89. 89. Ramzy GM, Koessler T, Ducrey E, McKee T, Ris F, Buchs N, Rubbia-Brandt L, Dietrich PY, Nowak-Sliwinska P. (2020). Patient-Derived In Vitro Models for Drug Discovery in Colorectal Carcinoma. Cancers (Basel). 2020; 12(6):1423. DOI:10.3390/cancers12061423
  90. 90. Fong EL, Wan X, Yang J, Morgado M, Mikos AG, Harrington DA, Navone NM, Farach-Carson MCA. A 3D in vitro model of patient-derived prostate cancer xenograft for controlled interrogation of in vivo tumor-stromal interactions. Biomaterials. 2016; 77:164-172. DOI:10.1016/j.biomaterials.2015.10.059
  91. 91. Liu X, Krawczyk E, A Suprynowicz F, Palechor-Ceron N, Yuan H, Dakic A, Simic V, Zheng YL, Sripadhan P, Chen C, Lu J, Hou TW, Choudhury S, Kallakury B, Tang DG, Darling T, Thangapazham R, Timofeeva O, Dritschilo A, Randell SH, … Schlegel R. Conditional reprogramming and long-term expansion of normal and tumor cells from human biospecimens. Nat Protoc. 2017;12(2):439-451. doi:10.1038/nprot.2016.174
  92. 92. Beshiri ML, Tice CM, Tran C, Nguyen HM, Sowalsky AG, Agarwal S, Jansson KH, Yang Q, McGowen KM, Yin J, Alilin AN, Karzai FH, Dahut WL, Corey E, Kelly K. A PDX/Organoid Biobank of Advanced Prostate Cancers Captures Genomic and Phenotypic Heterogeneity for Disease Modeling and Therapeutic Screening. Clin Cancer Res. 2018; 24(17):4332-4345. DOI:10.1158/1078-0432.CCR-18-0409
  93. 93. Aparicio S, Hidalgo M, Kung AL. Examining the utility of patient-derived xenograft mouse models. Nat Rev Cancer. 2015;15(5):311-316. DOI:10.1038/nrc3944
  94. 94. Wartenberg M, Hoffmann E, Schwindt H, Grünheck F, Petros J, Arnold JRS, Hescheler J, Sauer H. Reactive oxygen species-linked regulation of the multidrug resistance transporter P-glycoprotein in Nox-1 overexpressing prostate tumor spheroids. FEBS Lett. 2005; 579(20):4541-4549. DOI:10.1016/j.febslet.2005.06.078
  95. 95. Gaspar VM, Costa EC, Queiroz JA, Pichon C, Sousa F, Correia IJ. Folate-targeted multifunctional amino acid-chitosan nanoparticles for improved cancer therapy. Pharm Res. 2015; 32(2):562-577. DOI:10.1007/s11095-014-1486-0
  96. 96. Turley SJ, Cremasco V, Astarita JL. Immunological hallmarks of stromal cells in the tumour microenvironment. Nat Rev Immunol. 2015;15(11):669-682. DOI:10.1038/nri3902
  97. 97. Liu F, Huang J, Ning B, Liu Z, Chen S, Zhao W. Drug Discovery via Human-Derived Stem Cell Organoids. Front Pharmacol. 2016;7:334. DOI:10.3389/fphar.2016.00334
  98. 98. Zhiyun X, Yanghui G, Yuanyuan H, Encheng L, Yan W, Jianing Z. Application of a microfluidic chip-based 3D co-culture to test drug sensitivity for individualized treatment of lung cancer. Biomaterials. 2013;34(16):4109-4117. DOI:10.1016/j.biomaterials.2013.02.045
  99. 99. Ghaderi D, Zhang M, Hurtado-Ziola N, Varki A. Production platforms for biotherapeutic glycoproteins. Occurrence, impact, and challenges of non-human sialylation. Biotechnol Genet Eng Rev. 2012; 28:147-175. DOI:10.5661/bger-28-147
  100. 100. Kim JY, Kim YG, Lee GM. CHO cells in biotechnology for production of recombinant proteins: current state and further potential. ApplMicrobiolBiotechnol. 2012;93(3):917-930. DOI:10.1007/s00253-011-3758-5
  101. 101. Wurm FM. Production of recombinant protein therapeutics in cultivated mammalian cells. Nat Biotechnol. 2004;22(11):1393-1398. DOI:10.1038/nbt1026
  102. 102. Dumont J, Euwart D, Mei B, Estes S, Kshirsagar R. Human cell lines for biopharmaceutical manufacturing: history, status, and future perspectives. Crit Rev Biotechnol. 2016;36(6):1110-1122. DOI:10.3109/07388551.2015.1084266

Written By

Sangeeta Ballav, Ankita Jaywant Deshmukh, Shafina Siddiqui, Jyotirmoi Aich and Soumya Basu

Submitted: 13 August 2021 Reviewed: 09 September 2021 Published: 13 October 2021