Glioma classification based on histology and malignancy scale.
\r\n\t
",isbn:"978-1-80356-420-3",printIsbn:"978-1-80356-419-7",pdfIsbn:"978-1-80356-421-0",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"f188555eee4211fc24b6cca361983149",bookSignature:"Dr. Kim Ho Yeap",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11509.jpg",keywords:"Inductive Coupling, Resonant Inductive Coupling, Magnetic Coupling, Magnetic Resonance, Transmitter, Receiver, Rectenna, Antenna, Induction Coil, Stationery Charging, Dynamic Charging, Rectifier",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 25th 2022",dateEndSecondStepPublish:"May 6th 2022",dateEndThirdStepPublish:"July 5th 2022",dateEndFourthStepPublish:"September 23rd 2022",dateEndFifthStepPublish:"November 22nd 2022",remainingDaysToSecondStep:"11 days",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Dr. Kim Ho Yeap is a senior member of the IEEE, a Chartered Engineer registered with the UK Engineering Council, a Professional Engineer (PEng) registered with the Board of Engineers Malaysia, and an ASEAN Chartered Professional Engineer. In 2008 and 2015 he underwent research attachment at the University of Oxford (UK) and the Nippon Institute of Technology (Japan). Dr. Yeap has been given the university teaching excellence award and 21 research grants. He has published more than 100 research articles.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"126825",title:"Dr.",name:"Kim Ho",middleName:null,surname:"Yeap",slug:"kim-ho-yeap",fullName:"Kim Ho Yeap",profilePictureURL:"https://mts.intechopen.com/storage/users/126825/images/system/126825.jpeg",biography:"Dr. Kim Ho Yeap is an associate professor at Universiti Tunku Abdul Rahman, Malaysia. He is a senior member of the IEEE, a Chartered Engineer (CEng) registered with the UK Engineering Council, a Professional Engineer (PEng) registered with the Board of Engineers Malaysia, and an ASEAN Chartered Professional Engineer. He received his BEng (Hons) in Electrical and Electronics Engineering from Universiti Teknologi Petronas in 2004, his MSc in Microelectronics from Universiti Kebangsaan Malaysia in 2005, and his PhD from Universiti Tunku Abdul Rahman in 2011. In 2008 and 2015, respectively, he underwent research attachment at the University of Oxford (UK) and the Nippon Institute of Technology (Japan). He is the external examiner and external course assessor of Wawasan Open University. He is also the editor-in-chief of the i-manager’s Journal on Digital Signal Processing. He has also been a guest editor for the Journal of Applied Environmental and Biological Sciences and Journal of Fundamental and Applied Sciences. In addition, he has been given the university teaching excellence award and 21 research grants. He has published more than 100 research articles (including refereed journal papers, conference proceedings, books, and book chapters), which are mostly related to electromagnetics. Among his notable publications—and those of which he is most proud—are the report on the design of the receiver optics used in the Atacama Large Millimeter/Submillimeter Array telescope and the formulations that rigorously describe wave propagation in lossy waveguides.",institutionString:"Universiti Tunku Abdul Rahman",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Universiti Tunku Abdul Rahman",institutionURL:null,country:{name:"Malaysia"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"444315",firstName:"Karla",lastName:"Skuliber",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/444315/images/20013_n.jpg",email:"karla@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"7617",title:"Electromagnetic Fields and Waves",subtitle:null,isOpenForSubmission:!1,hash:"d87c09ddaa95c04479ffa2579e9f16d2",slug:"electromagnetic-fields-and-waves",bookSignature:"Kim Ho Yeap and Kazuhiro Hirasawa",coverURL:"https://cdn.intechopen.com/books/images_new/7617.jpg",editedByType:"Edited by",editors:[{id:"126825",title:"Dr.",name:"Kim Ho",surname:"Yeap",slug:"kim-ho-yeap",fullName:"Kim Ho Yeap"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10198",title:"Response Surface Methodology in Engineering Science",subtitle:null,isOpenForSubmission:!1,hash:"1942bec30d40572f519327ca7a6d7aae",slug:"response-surface-methodology-in-engineering-science",bookSignature:"Palanikumar Kayaroganam",coverURL:"https://cdn.intechopen.com/books/images_new/10198.jpg",editedByType:"Edited by",editors:[{id:"321730",title:"Prof.",name:"Palanikumar",surname:"Kayaroganam",slug:"palanikumar-kayaroganam",fullName:"Palanikumar Kayaroganam"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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Neurons function in synaptic interactions, whereas glial cells provide protective and structural support to the neurons. According to the 2020 GLOBOCAN, cancer of the brain and central nervous system rank at 19th and 12th, respectively [1]. The age-standardized incidence of these tumors is 3.9 per 100,000 in males and 3.0 in females globally. In comparison, the mortality is 3.5 per 100,000 in males vs. 2.8 in females worldwide. These cancers are prevalent in countries with a high human development index [1]. In 2020 alone, 308102 worldwide brain and central nervous system cases were reported. More than half were reported from Asia (54.2%) [1]. The number of deaths reported in the same year was 251329 worldwide, pushing the mortality rate to 81.57% [1]. The survival rate of gliomas vary based on their grade; the median survival time for high-grade glioma is 14 to 16 months. It ranges from 3–15 years for low-grade gliomas [2].
One of the only risk factors identified for the development of high-grade gliomas is exposure to high-dose of ionizing radiation [3]. However, environmental factors, toxins, infections, cell phone usage, or head trauma have not been correlated to the development of gliomas. Only 5% of cases of brain tumors have been linked to hereditary genetic syndromes [4]. Some of which are Li-Fraumeni cancer syndrome (associated with a germline mutation in the TP53 gene), neurofibromatosis, Turcot syndrome, and Lynch syndrome (constitutional mismatch repair deficiency), tuberous sclerosis, melanoma-neural system tumor syndrome, Ollier disease and Rubinstein-Taybi syndrome [4, 5, 6, 7].
Gliomas are diagnosed when the patients become symptomatic, exhibiting recurrent headaches, the onset of seizures, personality changes, weakness in limbs, or language disturbances [8]. Elevated intracranial pressure is also a common feature in gliomas [9]. Infantile spasms and seizures have also been noted in infants [9]. Gliomas are generally diagnosed by computed tomography (CT), and Magnetic Resonance Imaging (MRI) scans [10]. The current treatment regimen is based on the tumor grade and includes either or combinations of surgical resection, radiation, and chemotherapy [11]. The chemotherapeutic drugs used for glioma treatment fall under the category of alkylating agents that induce double-stranded breaks in the DNA, thereby inhibiting tumor proliferation [12]. The standard chemotherapeutic drug used for high-grade glioma is temozolomide (TMZ), and for low-grade gliomas are carmustine, procarbazine, and lomustine [13]. Metastasis of malignant gliomas is rare, primarily due to the low survival of the patients and also due to the blood–brain barriers [14]. However, in certain rare cases of high-grade gliomas, metastasis to the lung, pleura, lymph nodes, bone, and liver have been reported [15]. Recurrence post-treatment is reported in most gliomas and can be attributed mainly to surgical brain injury (SBI) and TMZ chemoresistance [16].
The following sections describe the glioma subtypes, their molecular characterization, and their deregulated signaling pathways. This chapter’s primary focus is on the DNA damage response (DDR) pathway, and noncoding RNAs in high-grade glioma called glioblastoma multiforme (GBM). The role of noncoding RNAs affecting chemosensitivity and other novel therapeutic drugs being developed for gliomas are also highlighted.
The Glial cells are classified as astrocytes, oligodendrocytes, and ependymal cells [17]. The astrocytes function in providing mechanical support to the neurons; oligodendrocytes are involved in myelin production, a component of the myelin sheath and ependymal cells play essential roles in the transport of CSF and brain homeostasis [18]. Based on the cellular origins, gliomas are classified as astrocytoma (derived from astrocytes), oligodendrogliomas (derived from oligodendrocytes), and ependymoma [2].
Until 2016, the World Health Organization (WHO) had categorized gliomas entirely based on histological features and graded them according to their malignancy profile [19]. Table 1 represents this WHO grading of gliomas where grades I and II are considered low-grade gliomas (LGGs) that are slow-growing with a better prognosis. The Grade I tumors are mainly diagnosed in children and curable with just surgical resection. On the contrary, the most aggressive tumors are referred to as high-grade gliomas (grade III and IV). Grade III tumors are termed ‘anaplastic’ as they have lost their characteristic cellular features to become malignant. The grade IV in this category, which accounts for 90% of gliomas, is GBM, the most aggressive and deadly tumor of all gliomas, with an abysmal survival rate. About 90% of GBM cases are de novo and develop in older patients [20]. On the contrary, secondary GBM, which arises from LGG, manifests mostly in younger patients and has a better prognosis [20].
WHO grade | Astrocytoma | Oligodendroglioma | Oligoastrocytoma | Prognosis | Incidence | |
---|---|---|---|---|---|---|
Low grade | I | Pilocytic astrocytoma, subependymal giant cell astrocytoma | Good | Predominant in children <1 year | ||
II | Low-grade astrocytoma | Low-grade oligoastrocytoma | Low-grade oligodendroglioma | Favorable | Median age of 35 | |
High grade | III | Anaplastic astrocytoma | Anaplastic oligoastrocytoma | Anaplastic oligodendroglioma | Poor | Predominant in adults |
IV | Glioblastoma | Very poor | Predominant in adults |
Glioma classification based on histology and malignancy scale.
A more recent WHO classification in 2016 includes genetic screening to histopathological analysis, which integrates the tumor’s morphological and genetic considerations [21]. The status of the following molecular alterations has been incorporated in this classification and are critical to diagnosis and further treatment.
IDH mutation: The most prevalent genetic mutation is the Isocitrate dehydrogenase (IDH) mutation accounting for a single point mutation in around 80% of glioma cases [22]. It is identified to be one of the earliest mutations for gliomagenesis and has been implemented primarily to classify gliomas as either IDH mutant or IDH wildtype. IDH mutation is considered to be a favorable prognostic marker with increased survival [23]. It is a metabolic enzyme that catalyzes the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG) and produces NADPH from NADP without the Kreb cycle’s involvement. This mutated IDH produces high levels of 2-hydroxyglutarate (2-HG) instead of the α-KG which is implicated in glioma invasion as well in epigenetic alterations leading to a glioma CpG island methylator (G-CIMP) phenotype (G-CIMP) [24].
Codeletion 1p19q: Post IDH mutation status, the gliomas are further classified based on this chromosomal co-deletion of 1p19q where the short arm chromosome 1 (1p) and the long arm of chromosome 19 (19q) are lost. It is observed in more than 70% oligodendrogliomas and 50% mixed oligoastrocytomas [25]. Clinically, IDH mutants with co-deletion 1p19q are linked to better prognosis and chemotherapy response [26].
TERT promoter mutations: Telomerase reverse transcriptase (TERT) promoter mutations are reported in several cancers leading to enhanced activity of TERT resulting in tumor cell survival and its progression [27]. It is present in 55% GBM and its prevalence is inversely correlated with IDH mutation [27, 28]. This TERT mutation serves as a prognostic biomarker and is associated with poor survival [29].
MGMT promoter methylation: MGMT (O[6]-methylguanine-DNA methyltransferase) is a DNA damage repair protein that removes alkyl groups added to nucleotides preventing mutation. Chemotherapeutic drugs like TMZ blocks cell growth by alkylating DNA. Hypermethylation of MGMT promoter regions renders this enzyme inactive and is reported in 40% GBM cases [30]. IDH mutant-MGMT promoter methylation cases are associated with increased PFS (Progression-free survival) whereas MGMT promoter methylation with TP53 mutation has favorable outcome irrespective of IDH status [31].
ATRX mutation: The alpha thalassemia/mental retardation syndrome X-linked (ATRX) is a chromatin remodeling enzyme involved in incorporating histone H3.3 at telomeres and pericentromeric heterochromatin. Loss of function mutations of ATRX is reported in gliomas which correspond to alternative lengthening of telomeres (ALT) phenotype [32]. ATRX and TERT mutations occur in 90% diffuse IDH mutant gliomas with both being mutually exclusive which confer better progression-free and overall survival [33].
H3K27M mutations: H3K27M (methionine substitution of lysine at residue 27 of histone H3) are mutations that occur in Histone 3 of H3F3A or HIST1H3B/C gene. These mutations are predominantly present in pediatric cases with IDH-wildtype and lack 1p/19q co-deletion and are associated with poor prognosis [34]. The H3K27M mutant protein has a dominant-negative effect on EZH2 protein, a histone methyltransferase impacting the epigenetic landscape of tumor genes [35].
Besides the above, other somatic and germline mutations are also reported in gliomas. More than 25 gene loci are linked to an increased risk of development of gliomas. Somatic mutations of cyclin-dependent kinase inhibitor 2A and B (CDKN2A, CDKN2B), epidermal growth factor receptor (EGFR), pleckstrin homology-like domain family B member 1 (PHLDB1), and regulator of telomere elongation helicase 1 (RTEL1) are reported in gliomas [36]. In case of GBM, the frequent genetic alterations in the decreasing order are LOH 10q (69%), EGFR amplification (34%), TP53 mutations (31%), p16INK4a deletions (31%) and PTEN mutations (24%) [37].
GBMs are the most fatal of all glial cancers. Secondary GBMs arising from LGG constitute 10% whereas the remaining 90% GBMs arise de novo. The genomic alterations of oncogenes and tumor suppressors are the fundamental cause of cancer development. These alterations further lead to deregulation of several signaling pathways aiding in tumor progression manifesting in metastasis and chemoresistant cancers. GBMs were one of the first tumors to be studied by the TCGA [38] and some of the key signaling pathways reported to be deregulated are as follows:
RTK/RAS/PI3K pathway: This pathway is majorly involved in growth and proliferation and is dysregulated in 88% of GBM cases. This dysregulation occurs by amplification and mutational activation of receptor tyrosine kinase (RTK) genes – EGFR, ERBB2, PDGFRA, MET. A variant of the protein – EGFRvIII that occurs due to intragenic deletions is also a common feature. Activation of the phosphatidylinositol 3-kinase (PI3K) pathway are achieved by PTEN deletion, activating mutations in PIK3CA or PIK3R, AKT3 amplification, NF1 mutation, RAS mutation, FOXO mutation.
p53 pathway: Inactivation of the p53 pathway occurs in about 87% of the GBM cases. TP53, termed as “the guardian of the genome”, is a tumor suppressor gene and is frequently mutated or deleted in most cancers [39, 40]. The pathway is involved in several processes like cell cycle arrest, DNA repair, apoptosis, autophagy, differentiation, senescence, and self-renewal [41]. Mutations in the TP53 gene lead to nonfunctional proteins. Several missense mutations, particularly in IDH-wildtype GBM (primary GBM), have been reported, resulting in accumulating the protein in the nucleus [42]. Additionally, deletions in ARF (ADP-ribosylation factor) at 55%, amplification of MDM2 (Mouse double minute 2 homolog)at 11%, and amplification of MDM4 (Double minute 4 protein) at 4% contribute to the inactivation of the P53 pathway [38]. TP53 is the most frequent and the earliest detectable alteration in the transition from low grade to high-grade [43].
Rb pathway: This retinoblastoma (Rb) pathway is dysregulated in 78% of GBM cases and is a vital regulator of the cell cycle and controls progression through the G1 to S phase of the cell cycle at the G1 checkpoint [44]. The Rb gene promoter is methylated frequently in secondary than primary GBMs and is associated with its low gene expression. There are two significant genetic alterations seen in the pathway– deletion of the CDKN2A/CDKN2B locus on chromosome 9p21 and the amplification of the CDK4 locus [38]. Such a loss of CDKN2A, RB or CDK4 amplification disrupts the p16INK4A-CDK4-RB tumor suppressor pathway. It has been shown to correlate with decreased expression and survival.
Recent studies have implicated the DNA damage response (DDR) pathway in modulating GBM chemoresistance. GBMs being the most aggressive gliomas with the least survival rate with treatment options being only radiation and chemotherapy using TMZ. These tumors ultimately gain resistance, leading to cancer relapse. This chemoresistant phenotype is attributed to enhanced DDR with alterations in DNA-repair and cell-cycle genes [12]. DNA repair mechanisms have evolved to counteract this damage based on the type of damage the DNA experiences (Figure 1). Some of the commonly observed damage and repair mechanisms are:
Methylated O6 or N7 Guanine is repaired directly by MGMT (O-6-Methylguanine-DNA Methyltransferase)
Oxidized/Deaminated bases by Base excision repair
Bulky DNA lesions or DNA-protein adducts by Nucleotide excision repair
Mismatched bases by Mismatch repair
Double-strand breaks by Homologous recombination or Nonhomologous end-joining or Alternate End Joining or Single-strand annealing
Inter-strand crosslinks by Fanconi Anemia pathway
Genes involved in the various types of DDR.
Besides mutations in IDH, TP53, and TERT promoter in GBMs, the mutation in genes that function in various DDR pathways have been reported:
MGMT-mediated DNA repair: As previously explained, MGMT is a DNA repair enzyme involved in DNA damage repair induced by alkylating drugs like TMZ. It is involved in the repair of DNA lesions. MGMT enzyme reverses O-alkylated DNA lesions of the alkylated bases [45]. MGMT is mostly hypermethylated in GBM; ~1.6% of the patient’s mutation is observed (The results are in whole or part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga).
Base excision repair: BER corrects base damage that does not cause significant distortions to the DNA helix. The enzymes involved in repair are DNA glycosylase, AP endonuclease, POL β, DNA ligase 1, or a complex of DNA ligase 3 and XRCC1 [46]. Unlike direct repair by MGMT, there are very few BER machinery components that showed a mutation in GBM.
Nucleotide excision repair: NER is the pathway chosen to remove bulky lesions. The damage is sensed by XPC complexed with RAD23B and CETN2. The other pathway proteins are the UV–DDB complex consisting of DDB1, DDB2, and TFIIH complex. Endonuclease XPF–ERCC1 and XPG, the replicative proteins PCNA, RFC, POL δ, POL ε or POL κ, and LIG1, XRCC1–LIG3 [47]. Of these genes, 5.6% of the cases had a mutation in POLE [48].
Mismatch repair (MMR): The mismatches incorporated during replication are recognized by MutSα heterodimer (MSH2/MSH6) or MutSβ heterodimer (MSH2/MSH3). The other proteins involved are POL δ, RFC, HMGB1, and LIG1 [49]. Of these, 3.8% of patients had a mutation in MSH6 and 1.6% in the MSH2 gene [48].
Double-strand breaks repair: The Double-Stranded Breaks (DSBs) are majorly repaired by nonhomologous end-joining (NHEJ) [50] and homologous recombination (HR) [51]. The alternate less-characterized pathway is microhomology-mediated end joining (MMEJ) or alternative end-joining (AEJ) [52]. While HR is restricted to the cell-cycle S and G2 phases, NHEJ and MMEJ are free to get employed in any cell cycle phase [53]. In response to DSBs, three proteins of the phosphoinositide 3-kinase-related kinase (PIKK) family are activated – ATM, ATR, and DNA-PK, downstream they phosphorylate other substrates, activating them [12]. The additional factors that are subsequently recruited include XRCC4, XLF, DNA ligase IV (LIG4), ARTEMIS, and PAXX which plays a key role in stabilizing the complex chromatin [54]. Other proteins that facilitate the pathway are DNA polymerases like POLM and POLL. Multiple proteins in this pathway are mutated in GBM. The ATR gene is mutated in 4.5% patients followed by 2.9% in PRKDC (DNA-PK), 2.5% in ATM, 1.9% ARTEMIS, 1.94% in XRCC5 (Ku80) and POLL [48].
The HR preferentially repairs the DSBs, which occur at the replication fork [55]. The pre-requisite for the homologous recombination repair pathway is the end-processing of DSBs by helicases and nucleases to produce single-stranded DNA. ATM, CtIP, MRN complex(MRE11-RAD50-NBS1) is involved in generating ssDNA [56]. This ssDNA binds with the RecA/RAD51 complex, stimulated by RPA, promotes DNA pairing and strand exchange in an ATP-dependent fashion [57]. Additionally, the tumor suppressor proteins – BRCA1, BRCA2, and PALB2 are involved in HR [58]. In GBM patients, 3.55% BRCA1, 1.86% MRE11A and RAD50, 1.4% NBN, and ~ 1% RPA1 mutations have been reported [48].
The MMEJ pathway is promoted by PARP-1, Ligase III, CtIP, and Mre11. It uses the same machinery as the HR pathway to form a 3′ single-stranded overhang at the region of DSB [52, 59]. Mutations in Ligase III (3.49%) PARP1 (3.33%) and CtIP (2.5%) have been reported in GBM patients [48].
Single strand annealing (SSBR): The single-strand breaks are detected by PARP1, followed by end-processing by PE1, PNKP, and APTX. FEN1 acts as an endonuclease to create a gap. POL β, in combination with POL δ/ε, fills the gap and is ligated by LIG1 [60]. Mutations, although at a much lower frequency, have been reported in all the components of SSBR, APTX (1.17%), FEN1 and PNKP (0.78%), and POLB (0.39%) [48].
Inter-strand crosslink repair (ICL): ICLs are resolved by complex FANCM and FAAP24. MFH stimulates the remodeling of the replication fork. The RPA protein binds to ssDNA and activates ATR, CHK1, FANCE, FANCD2, FANCI, and MRN consecutively. Further, excision is carried out by PF-ERCC1, MUS8-EME1, SLX4-SLX1, FAN1, SNM1A/SNM1B. The polymerase which acts to repair includes POL ι, POL κ, POL ν, and REV1 [61]. 4.42% mutations in FANCD2, 2.26% in FANCI, 1.61% in FANCE, 2.7% and 1.91% in SNM1A and SNM1B, respectively have been reported in GBM patients [48].
Depending on the type of damage a cell encounters, any of these pathways can be activated to restore the damage sites. One of the most deleterious repairs found in cancer cells is MMEJ which results in large deletions and translocations, destabilizing the genome. In GBM, HR and c-NHEJ have higher mutation rates than in MMEJ, making MMEJ the preferred pathway for DNA repair. Figure 2 represents the frequently mutated genes of the various DDR pathways along with their impact on overall survival obtained from NCI - GDC Database [62]. As can be observed, the mutations in these genes reduce patients’ survival in GBM (14–16 months).
Frequently mutated genes of DDR pathway in glioblastomas obtained from GEPIA database.
The various genomic mutations like the overexpression of oncogenes and under expression of tumor suppressor genes lead to altered genomic and epigenomic changes favoring cancer growth. In GBM several genes that encode proteins in the DNA repair pathway have altered expression. Figure 3 represents some of the altered gene expressions in the different DDR pathways in GBMs. This data is obtained from GEPIA database which compares normal patient samples with GBM tumor samples [63].
Altered gene expressions in the various DDR pathway in glioblastoma.
The DDR genes are significantly upregulated and include HR factors - RAD51 recombinase, the chromatin remodelers RAD54B and RAD54L, enzymes in the HOLLIDAY JUNCTION resolution (EME1/MUS81 complex), NER (ERCC3 (XPB), ERCC4 (XPF). Also, expression of genes encoding DNA glycosylase NEIL3, Fanconi Anemia factors (FANCD2, UBE2T), the ubiquitin-protein ligase UBE3B, and two specialized DNA polymerases POLM and POLQ in the NHEJ pathway are increased significantly [64]. Coincident with the least mutation, MMEJ transcripts show relatively higher expression than other pathways. Closer observation shows elevated MMR transcripts, but a higher mutation rate has been observed of some of the genes like MSH2 and MSH6 in GBM. Among HR gene expression, PDS5B is highly expressed, which is required for proper segregation.
Additionally, these signatures also suggest the sensitivity of the tumor to therapeutic drugs. Upregulation of the TOP2A gene, which encodes topoisomerase II, might be more sensitive to topoisomerase II inhibitors like etoposide. Similarly, the decreased expression of NER genes like ERCC3/XPB and ERCC4/XPF can be more sensitive to cisplatin. Cisplatin acts by causing inter-strand crosslinking, and its repair requires NER [64]. Targeting RAD51 is also a potential therapeutic option that can either target the HR pathway or sensitize the cancer cells to irradiation and chemotherapeutic agents that cause DSBs [65].
In tumors treated with DNA damaging agents, efficient DNA repair systems become the primary cause for treatment failure. GBM’s ability to resist DNA insults is directly attributable to its upregulation of DNA repair pathways. Hence, along with the standard care regimen, DDR kinase inhibitors are being investigated to overcome chemo- and radio-resistance. Table 2 represents inhibitors that are being developed to target kinases in the DNA damage response pathway.
Kinase | Inhibitor | Phase | Reference |
---|---|---|---|
ATM | KU60019 | Preclinical | [54] |
CP466722 | Pre-clinical +temozolomide | [66] | |
AZ32 | Preclinical + IR | [67] | |
AZD1390 | Phase-I + IR | [68] | |
ATR | VE-821 | Preclinical +cisplatin | [55] |
AZ20 | Preclinical | [56, 57] | |
DNA-PK | CC-115 | Phase-I + neratinib +temozolomide | [58] |
Chk2 | PV1019 | Pre-clinical - + IR + topotecan | [59] |
CCT241533 | Pre-clinical - bleomycin +olaparib +IR | [61] | |
Wee1 | MK-1775 | Phase-I monotherapy +IR + temozolomide | [60] |
PARP | Niraparib | Phase II monotherapy +temozolomide +bevacizumab +carboplatin | [69] |
Veliparib | Phase III + IR + temozolomide | [70] | |
Olaparib | Phase II monotherapy +bevacizumab +IR + temozolomide | [71] |
List of drugs developed targeting DDR kinases in gliomas.
MicroRNAs are a group of noncoding RNAs ~18–22 nucleotides in length. miRNA regulates gene expression at both transcriptional and post-transcriptional levels. It modulates transcription by binding to the 5’ UTR of the gene. The binding of miRNA at 3’ UTR regions (untranslated regions) reduces mRNA stability or inhibits translation [72, 73]. Dysregulated miRNA expression is one of the hallmarks of cancer. They have been shown to affect several crucial processes like proliferation, invasion, and metastasis [74]. Hence, they are potential biomarkers and targets for therapeutic intervention. The aberrant expression of miRNAs in GBM is well documented. 256 upregulated miRNAs and 95 downregulated miRNAs are reported in GBM compared to normal brain tissue [72]. Here, we focus on the deregulated miRNAs involved in DDR pathways leading to chemoresistant or chemosensitive phenotype (Table 3).
miRNA | Target | Activity | Reference |
---|---|---|---|
MiR-338-5p | Ndfip1, Rheb, ppp2R5a | Radio sensitivity | [75] |
MiR-10b | p-AKT | Decreases sensitivity to radiation | [76] |
miR-26a, miR-100 | ATM | Radio sensitivity | [77] |
miR-30b-3p | HIF1α, STAT3 | Chemo resistance | [78] |
miR-1193 | FEN1 | Chemo sensitivity | [79] |
miR-96 | PDCD4 | Radio resistance | [80] |
miR-17 | ATG7 | Chemo and radio sensitivity | [81] |
miR-21 | PDCD4, TPM1, PTEN | Chemoresistance | [82] |
miR-143 | N-RAS | Chemo sensitivity | [83] |
miR200a, miR-603, miR-181d, miRNA-370-3p, miR-198, miR-142-3p | MGMT | Chemo sensitivity | [84] |
miR195 | SIAH1,WEE1 RANBP3 | Chemoresistance | [85] |
miR-455-3p | LTBR, EI24, SMAD2 | Chemoresistance | |
miR-10a | EPHX1 and BRD7 | Chemoresistance | |
miR-222 | GAS5, MGMT | Increase the DNA damage effect induced by TMZ | [86] |
miR-29c | Sp1, MGMT | Chemo sensitivity | [87] |
miR-99 | SNF2H/SMARCA5 | Radio sensitivity | [88] |
miR210-3p | HIF1α/HIF2α | Chemo resistance | [89] |
miR-136 | AEG-1 | Chemo sensitivity | [90] |
miR-155 | p38 | Chemo sensitivity | [91] |
miR-181b | MEK1 | Chemo sensitivity | [92] |
miR-29b | STAT3 | Chemo sensitivity | [93] |
miR-101 | DNA-PKcs, ATM | Radio sensitivity | [94] |
miR-137 | CAR, MDR1 | Chemo sensitivity | [95] |
miR-204 | FAP-α | Reverses chemo resistance | [96] |
MiR-181a | Bcl-2 | Radio sensitivity | [97] |
miR-132 | TUSC3 | Chemo resistance | [98] |
miR-138 | BIM | Chemo resistance | [99] |
miR-221, miR-222 | DNA-PKcs | Radio resistance | [100] |
miR-1238 | CAV1 | Chemo resistance | [101] |
miR-26a | Bax, Bad, HIF-1α | Chemo resistance | [102] |
miR-9 | PTCH1 | Chemo resistance | [103] |
miR-124, miR-128, miR-137 | EZH2, BMI1, LSD1 | Chemo resistance | [104] |
miR-151a | XRCC4 | Chemo sensitivity | [105] |
Deregulated miRNAs involved in DNA damage response in GBM.
The noncoding RNAs are a diverse group of transcribed RNAs, with long-non coding RNA or lncRNA being the largest sub-type in this category [106]. Long noncoding RNA can regulate gene expression by binding to the gene’s promoter and recruiting activators or repressors, or chromatin modifiers and activating or repressing transcription, respectively [106, 107]. Alternatively, they can work as antisense and bind to the transcripts, thereby inhibiting translation or destabilizing the transcript. They can also act as miRNA sponges, altering gene expression post-transcriptionally [108]. LncRNA deregulation is involved in cancer development, progression, and metastasis. It is a potential target for therapeutic interventions. Their expression pattern in response to chemotherapeutic treatment has prognostic value and serves as predictive biomarkers [106, 107].
lncRNAs are abundantly expressed in the brain as compared to other parts of the body [109]. Glioma subclassification has also been done based on the lncRNA profile into three groups: (i) astrocytic tumor with high EGFR amplification (ii) neuronal-type tumor (iii) oligodendrocytic tumor enriched with an IDH-1 mutation and 1p19q co-deletion. Such a classification has been shown to correspond to patient survival where lncRNAs like PART1, MGC21881, MIAT, GAS5, and PAR5 were correlated with prolonged survival. At the same time, KIAA0495 was associated with poor survival [109]. Table 4 represents the lncRNAs studied in gliomas that are involved in chemoresistance or chemosensitivity.
lncRNA | Target | Activity | Reference |
---|---|---|---|
ADAMTS9-AS2 | FUS | Chemo-resistance | [110] |
AHIF | HIF1a, p53 | Radio-resistance | [111] |
CASC-2 | miR 181a, PTEN | Chemo-resistance | [112] |
CCAT2 | miR-424, CHK1 | Chemo-resistance | [113] |
H19 | MDR, MRP, and ABCG2 | Chemo-resistance, Stemness in GSCs | [114] |
HMMR-AS1 | HMMR mRNA stabilization, ATM, RAD51, BMI1 | Radio-resistance | [115] |
HOTAIR | miR-519a-3p, RRM1 | Chemo resistance | [116] |
LINC00174 | miR-138-5, SOX9 | Chemo resistance | [117] |
LINC01057 | IKKα | Radio resistance | [118] |
MALAT1 | miR-203, miR-101, Thymidylate synthase (TS) | Reduction of cell proliferation | [119, 120] |
MIR155HG | PTBP1 | Chemo-resistance | [121] |
NCK1-AS1 | miR-137, TRIM24 | Chemo-resistance | [122] |
PCAT1 | miR-129-5p, HMGB1 | Radio-resistance | [123] |
PSMB8-AS1 | MiRNA-22-3p, DDIT4 | Radio resistance | [124] |
RA1 | H2B | Radio resistance | [125] |
SBF2-AS1 | miR-151a-3p, XRCC4 | Chemo-resistance | [126] |
SNHG18 | Sema5A | Radio resistance | [127] |
SOX2OT | ALKBH5, SOX2, Wnt5a/β-catenin | Chemo-resistance | [128] |
TALC | miR-20b-3p, Stat3/p300 complex, MGMT | Chemo-resistance | [129] |
TALNEC2 | G1/S transition, mesenchymal transformation | Radio-resistance | [130] |
TP53TG1 | miR-524-5p, RAB5A | Radio-resistance | [131] |
TP73-AS1 | Metabolism related genes, ALDH1A1 | Chemo-resistance | [132] |
TPTEP1 | miR-106a-5p, MAPK14 | Radio-resistance | [133] |
TUSC7 | miR-10a MDR1 | Chemo resistance | [134] |
UCA1 | Wnt/β-catenin | Chemo-resistance | [135] |
Xist | miR-29c, SP1, MGMT | Chemo-resistance | [136] |
lncRNAs in glioma involved in chemoresistance or chemosensitivity.
Circular RNA is yet another group of noncoding RNA produced from pre-mRNA back-splicing [137]. They inhibit miRNA and upregulate the expression of genes at the transcriptional and post-transcriptional levels [138, 139]. CircRNAs have also been shown to bind to different proteins to form circRNA-protein complexes (circRNPs) that regulate the action of associated proteins, the subcellular localization of proteins, and the transcription of parental or related genes [140]. circRNAs play significant roles in tumor growth, metastasis, EMT transformation, and therapy resistance [141]. circRNAs are the most abundant in the brain and play a crucial role in the brain’s functioning [142]. In glioma, they are expressed aberrantly and play a key role in tumor initiation and progression [143]. In GBM, several studies have identified the upregulated and the down-regulated circRNAs. Identifying these circRNAs is valuable for further understanding the molecular mechanism of glioma and developing novel targeted treatments [144]. Table 5 represents the circRNAs studied in gliomas with their targets.
circRNA | Target | Activity | Reference |
---|---|---|---|
NFIX | miR-132 | Chemo resistance | [145] |
circ_0005198 | miR-198 TRIM14 | Chemo resistance | [146] |
CEP128 | miR-145-5p | Chemo resistance | [147] |
VCAN | miR-1183 | Radio resistance | [148] |
circPITX1 | MiR-329-3p NEK2 | Radio resistance | [149] |
CircATP8B4 | miR-766-5p | Radio resistance | [150] |
CDR1as | miR-7, p53 | Protects from DNA damage | [151] |
circRNAs involved in chemoresistance/chemosensitivity in gliomas.
The standard chemotherapeutic drugs used for gliomas are alkylating agents (TMZ, procarbazine, vincristine, carmustine). More recently, GLIADEL wafer containing carmustine is approved for GBM as an adjunct to surgery and radiation [152]. Humanized monoclonal IgG1 antibody Bevacizumab targeting VEGF is used for recurrent GBM [153]. Surpassing the blood–brain barrier makes treating gliomas difficult [154]. Several inhibitors targeting enzymes like topoisomerase II, [155], immunotherapeutic agents like α-type-1 dendritic cell vaccine [156], autologous cytokine-induced killer cell immunotherapy [157], autologous dendritic cell vaccine [158], and immunomodulatory drugs [159] are in clinical trials phases I and II. Additionally, many of these drugs in combination with the standard chemotherapeutic drug are also in trials, including Giladel wafers with dendritic cell vaccine [160], Lomustine-temozolomide [160, 161], Bevacizumab + radiation therapy + temozolomide [162], Irinotecan + bevacizumab + temozolomide [163]. The Table 6 lists some of the drugs which are in phase 3 trial for glioma treatment.
Drug | Status | Activity | Reference |
---|---|---|---|
Cilengitide | Did not improve outcomes | αvβ3 and αvβ5 integrin inhibitor | [164] |
Rindopepimut | Did not improve outcomes | Targets EGFRvIII | [165] |
DCVax®-L | Feasible and safe, May extend survival | Autologous tumor lysate-pulsed dendritic cell vaccine | [166] |
Nivolumab | Did not improve overall survival | PD-1 inhibitor | [167] |
Lomustine (CCNU) -temozolomide | Might improve survival | Nitrosourea Alkylating agent | [161] |
Tumor treating fields | Significantly improved OS and PFS (with TMZ) | Alternating electric fields targeting microtubules and septin fibers | [168] |
Sitimagene ceradenovec | Can increase time to death or re-intervention but did not improve overall survival | Adenovirus-mediated gene therapy | [169] |
CIK cell immunotherapy | Along with TMZ improves PFS, but not OS | Autologous cytokine-induced killer cell immunotherapy | [157] |
Novel drugs in clinical trials for glioma treatment.
Gliomas are the most common malignant brain cancers constituting 80% of all brain & central nervous system cancers. Even though gliomas represent a small percentage of all cancers, they account for disproportionally high morbidity and mortality. Despite the emphasis on new therapeutic interventions, the standard care regimen has not changed drastically. However, there has been more emphasis on understanding molecular pathogenesis and its clinical relevance. Emerging preclinical and clinical data points to a shift towards more personalized therapies, and targeting the DDR pathway and its related noncoding genes is on the horizon. Figure 4 summarizes the interplay of noncoding in DDR and drug resistance in gliomas.
Representative genes and non-coding RNAs in glioblastomas.
We acknowledge the support from the Department of Science and Technology Fund for Improvement of S&T Infrastructure in Higher Educational Institutions (Grant no. SR/FST/LSI-5361/2012), the Department of Biotechnology, India, Glue grant (BTIPR23078/MED/29/1253/2017), and the Departments Information Technology, Biotechnology and Science and Technology, Government of Karnataka, India.
In today’s world, rapid technology advancement and globalization seem to significantly influence the creation of a new knowledge-based economy. In other words, technology appears to be the critical factor in this knowledge-based economy for many nations across the globe [1, 2]. Most governments in the world, especially those in developing countries, have recognized that advancement in technology has an immense influence on the socio-economic development of their citizenry. Based on this development, some governments have invested heavily in technology developments to build the human resource base to address and conveniently cope with the demands and pressure of the current information and digital age [3, 4].
The concept “digital technology tools” was used since the post-World War II period in the United States of America to allow the integration of equipment such as audiotapes, television, and slide projectors in teaching [5, 6]. In our contemporary society, digital technology tools include computer-related hardware and software integrated into teaching and learning [7]. In this research, the use of digital technology tools refers to all electronic devices used in instructional delivery.
Digital technology has long been identified as a means to bridging the gap between access to higher education and improvements in learning outcomes, and university teachers have been recognized to play a leading role in the use of digital technology tools [8]. Many arguments posited for digital technology integration indicate that technology makes teaching and learning effective [9]. Trinidad et al. [10] explained teaching and learning effectiveness as “the degree to which a teaching tool contributes to students’ retention of learning or skills…Effectiveness is measured through students’ grades, acquired skills, transfer of knowledge, or retention of ideas” (p. 162).
In Ghana, the initiative to use digital technology devices to improve access, equity, and quality in education delivery was taken only a couple of years ago. In 2003, the country formulated a policy called Ghana ICT in Education Policy. The main aim of the policy was to integrate technology into education to promote teaching and learning, especially in the higher education sector. At the time, the policy framework recognized the essential role of technology in creating an opportunity for teachers to enhance their instructional delivery [11]. Although the policy document was timely because it served as a platform for the promotion of a systematic technology-driven education [12], our engagement with the literature revealed that there was a paucity of information as to whether teachers in the country, especially those teaching at the university level, saw themselves as digital leaders whose critical role was to promote the use of digital technology in teaching. Consequently, there appeared to be a knowledge gap as to the nature of digital technology tools used in instructional delivery at the university level in Ghana, and whether the tools effectively promoted teaching and learning.
The aim of the research was to use the context of Ghana to examine the extent to which university teachers in the developing world effectively used their digital leadership role to promote the use of digital technology in instructional delivery. Specifically, the research was to examine the kinds of digital technology tools university teachers in Ghana often used in their teaching. It was also to find out whether the tools were effective in promoting teaching and learning. Based on the objectives, we posed questions as follows:
What kinds of digital technology tools do university teachers in Ghana often apply in their instructional delivery as digital leaders?
How effective are digital technology tools in promoting academic work in Ghanaian universities?
The research was compelling because earlier studies by Boakye and Banini [13] and Mercader [14] claimed that despite the increasing number of research on digital technology integration in teaching, the concentration had been on the Western world, and little was known about the extent of the use of digital technology in the education system of the developing world.
Thus far, the Section 1 of this chapter has given the background, problem, objectives, and questions guiding the research. Next will be a review of the literature on the theoretical framework and the global use of digital technology tools in higher education. To be followed is the Section 4 detailing the processes involved in conducting the research. The findings and discussion will also be presented subsequently. The chapter will conclude by highlighting the implications of the research for global higher education, especially in the developing world.
Ghana has 180 higher education institutions (HEIs) out of which there are 99 public and 81 private universities [15]. Most of the public universities operate the collegiate system. According to NCTE, about 70% of students in the universities enroll to acquire a bachelor’s degree, while about 22% pursue diploma programs mostly by the distance education mode. The enrolment in graduate programs (masters’ and doctoral degrees) is, however, minimal, according to the NCTE.
Recruitment of teachers in Ghana’s HEIs is mainly based on the acquisition of a terminal degree (usually a Ph.D.) and a satisfactory publication record. Recruited teachers serve on a contract basis, usually 6 years with the opportunity for renewal. The promotion criteria for teachers vary from university to university. However, for promotion purposes, the universities commonly emphasize teaching, research, scholarly work (publications), and community service. After recruitment, university teachers in Ghana normally begin as Lecturers and may rise to Senior Lecturer, Associate Professor up to Professor. With regard to reporting lines, teachers and students are directly managed by Heads of Departments (HODs). The HOD’s are also supervised by Deans who manage Schools or Faculties. The Deans also report Provosts of Colleges in the collegiate system or directly to Pro Vice-Chancellors who also reports to Vice-Chancellors. The Vice-Chancellors are ultimately answerable to University Councils.
Roger’s [16] innovation-decision activities vividly define a framework on how people choose to accept or reject a particular technology. The four key ingredients in the framework depicted in Figure 1 concern innovation, communication, the context of the social system, and time. The four key components interrelate to describe how a person’s adoption represents diffusion. Beyond these components, Casmar [17] identified five critical characteristics of adoption decisions. These include the relative merits associated with the adoption of the technology (relative advantage), the complex nature of the technology (complexity), ability to access and try the technology (triability), the availability and visibility of the technology (observability), and compatibility [18].
Adoption decisions. Source: [
Chevers and Whyte [19], Shelton [20], and Tondeur et al. [21] argued that the most frequently applied technology in teaching and learning are projectors and laptops/computers for presentation. According to Farmery [22], most instructors integrate blogs, wikis, and podcasts in teaching and learning. Amory [23], Bagheri et al. [24], Bates and Sangra [25], and Cheung and Slavin [26] also reported that instructional technologies would modify how learners and instructors collect and gather information and collaborate.
Makewa et al.’s [27] study on instructor’s competence in integrating digital technologies into teaching and learning found that majority of the study participants disagreed with being knowledgeable in applying online technology tools such as the podcast, wikis, and blogs. Besides, Montrieux et al.’s [28] qualitative study revealed that mobile tools such as mobile quizzes, blogs, and podcasts were famous for their integration in classroom teaching and learning. However, lecturers tended to be more confident and knowledgeable in using projectors. Other researchers such as Makewa et al. [27], Shelton [20], and Farmery [22] also found projectors and computers as the most frequently used technology tools in teaching. For their part, Alkash and Al-Dersi [29], Rumble and Harry [30], and Rashid and Elahi [31] found that technology-related resources such as the Internet, e-mobile, and computers facilitate distance learning.
In another related research, Alqurashi [32] found that there was a statistically significant relationship between familiarity and proficiency in using digital technologies and integrating them in teaching. Kumar and Daniel’s [33] comparative study on the technology integration into instructional delivery at Fijian further established that 36.67% of the studied population indicated they were knowledgeable and skillful in incorporating digital technologies in teaching. In Fleischer’s [34] view, integrating digital technology tools in teaching enhances students’ creativity and inspires them to explore and learn new things independently. Fleischer’s study found that teachers and students used laptops for academic work for long hours.
According to Bozkurt [35], the breakdown of technology devices and inadequate wireless services, limited time for integration in lessons, unreliable Internet speed, the lack of computers, and inadequate accessibility to technology tools for effective integration are some institutional factors affecting digital technology integration in teaching and learning.
Chertovskikh’s [36] research also identified the following as barriers to technology integration: insufficient digital learning resources, insufficient pedagogical support, the lack of institutional policies for technology integration, insufficient technology equipment, poor connectivity, and insufficient technical support. In similar research, Adedokun-Shittu and Shittu [37] also found technical problems and constraints such as power failure, Internet interruption, and inadequate training for instructors as some of the critical challenges confronting technology integration in teaching and learning. Furthermore, Bagheri et al.’s [24] research rather found the challenges to include inadequate human resource capacity, low bandwidth for Internet connectivity, and poor penetration of technology in higher institutions.
Thus far, the literature reviewed highlighted the fact that there was scholarly information on various digital technology tools integrated into teaching in higher education institutions. It also revealed the fact that there were challenges confronting digital leaders in using the technologies in teaching. Conspicuously missing, however, was information on which of the digital technology tools were commonly used in the developing world, and whether or not they effectively promoted academic work. This was the gap this research intended to fill.
The study used the embedded/nested mixed-method design to concurrently collect both quantitative and qualitative data. However, the latter played a complementary role in supporting the former [38]. The choice of the design enabled us to give a holistic picture and broader perspective of the extent to which university teachers in the developing world effectively used their digital leadership role to promote the use of digital technology in instructional delivery. The study used the accidental sampling technique to select 252 university teachers across Ghana. The sample size was considered appropriate based on Krejcie and Morgan’s [39] standard criteria for determining sample size. Table 1 presents details of the demographic characteristics of the sample.
Variable | No. | % |
---|---|---|
Gender | ||
Male | 97 | 38.49 |
Female | 155 | 61.50 |
Total | 252 | 100.0 |
Age | ||
30–39 | 74 | 5.95 |
40–49 | 113 | 28.17 |
50–59 | 65 | 25.79 |
Total | 252 | 100.0 |
University teaching experience | ||
1–5 years | 121 | 48.02 |
6–10 years | 88 | 34.92 |
11 years+ | 43 | 17.06 |
Total | 252 | 100.0 |
Demographic characteristics of participants.
Source: Fieldwork (2021).
A self-developed questionnaire was used for the research. The instrument had three sections. The first section (“A”) was on the demographic background of respondents. The second section (“B”) dealt with kinds of digital technology tools university teachers often applied in their instructional delivery. The third and final section (“C”) also elicited responses on the effectiveness of the tools in promoting academic work. Although the instrument was mainly structured, the second and third sections gave respondents an opportunity to express their own qualitative opinions not captured in the structured items. The design of the items in the two sections was informed by the authoritative views expressed in the extant literature gleaned for this research. The items were put on a five-point Likert scale in both sections as follows: Section “B”: (1) never used; (2) rarely used; (3) occasionally used; (4) frequently used; and (5) more frequently used. Section “C”: (1) strongly disagree; (2) Disagree; (3) Unsure; (4) Agree; and (5) Strongly agree. Prior to using the instrument, a face validity test was conducted on it to ascertain the extent to which the items in the second and third sections met the objective of the research and the findings proved positive. Again, the instrument was piloted among accidentally selected 63 (i.e., a quarter of the sample size) university teachers in Ghana who were not part of the sample. A Cronbach’s alpha test yielded a reliability coefficient of 0.81 making the instrument undoubtedly reliable for use in the research.
The data collection exercise was done using the self-constructed questionnaire and took a period of 102 days to complete. As explained already, the accidental technique was used, and it allowed the distribution of the instrument among university teachers on the basis of availability and willingness to participate. Using the SPSS version 21, preliminary analyses were done by organizing the data according to the five-point Likert scale and subjecting them to frequency and percentage analyses. The same data were subsequently converted into means and standard deviations. The qualitative data were grouped into common themes to be analyzed using descriptive statistics. However, because the themes generated did not yield new issues remarkably different from the main items already captured in the questionnaire, the intention was shelved.
A written consent was obtained from the participants before their involvement in the study. To ensure confidentiality and to check that the rights of the participants are not disregarded and abused, ethical clearance with reference number ECH 101/19-20 was obtained from one of the universities’ ethics committees for the humanities. Besides, participation in the research process was voluntary, and participants could withdraw at any point in the research process. Participants’ identities were also concealed.
This section presents analyses of the field data obtained from our investigation on the extent to which university teachers in a developing country like Ghana effectively used their digital leadership role to promote the use of digital technology in instructional delivery. The presentation in this section is based on only the quantitative aspect of the embedded/nested mixed-method design because, as indicated in Section 4 (see Subsection 4.3), the qualitative data did not yield new issues remarkably different from the main quantitative data.
The first research question asks: What kinds of digital technology tools do university teachers in Ghana often apply in their instructional delivery as digital leaders?
Table 2 presents the means (
Digital technology tools | SD | Mean rank | ||
---|---|---|---|---|
Laptops | 252 | 4.28 | 1.32 | 1 |
Mobile phones | 252 | 3.94 | 1.42 | 2 |
Projectors | 252 | 3.75 | 1.27 | 3 |
Desktop computers | 252 | 3.03 | 1.48 | 4 |
Television sets | 252 | 2.99 | 1.63 | 5 |
IPads | 252 | 2.10 | 1.57 | 6 |
Smartboard | 252 | 1.81 | 1.19 | 8 |
Digital cameras | 252 | 1.61 | 1.08 | 7 |
Digital speakers | 252 | 1.52 | 1.11 | 9 |
Kinds digital technology tools frequently used by Ghanaian universities.
Source: Fieldwork (2021).
Having examined the measure of central tendencies on the table, it is equally important to also consider the measure of dispersion. From the table, two extreme measures of standard deviations (i.e., the most dispersed variable from its mean and the least dispersed variable from its mean) show that whereas responses for the variable “Television sets” are the farthest apart and most dispersed (SD = 1.63). On the opposite, responses for the variable “Digital cameras” are the closest and least dispersed (SD = 1.08).
The second research question also asks: How effective are digital technology tools in promoting academic work in Ghanaian universities?
Table 3 shows respondents’ opinions regarding the effectiveness of digital technology tools in promoting teaching and learning in Ghanaian universities. For the measure of central tendencies, an examination of only the extreme measures of the means gives the impression that while the responses for the variable contending that digital technology tools allowed students to easily retain and recollect learning concepts have the highest mean score (
Digital technology tools… | SD | |
---|---|---|
Allows students to easily retain and recollect learning concepts | 4.51 | 0.88 |
Allows students to access information at any time and place | 4.27 | 0.89 |
Motivates and sustains students’ interest in teaching | 3.68 | 1.22 |
Allows easy transfer of knowledge by students | 3.67 | 0.97 |
Helps students to explore opportunities for further learning | 3.51 | 1.06 |
Enhance the learning experience of students | 3.42 | 1.51 |
Leads to better acquisition of skills by students | 3.23 | 1.40 |
Enable students to obtain desirable findings | 3.12 | 1.39 |
Helps students to learn independently | 2.36 | 1.07 |
Makes it easy to attract students’ attention | 2.20 | 1.30 |
Effectiveness of digital technology tools in promoting instructional delivery.
Source: Fieldwork (2021).
In the case of the measure of dispersion, a perusal of the table also reveals two extreme measures of standard deviations showing that responses for the variable on the assertion that digital technology tools enhanced the learning experience of students are the farthest apart and most dispersed (SD = 1.51). On the contrary, responses for the variable on the view that digital technology tools enabled students to easily retain and recollect learning concepts are the closest and least dispersed (SD = 0.88).
The study found high average usage for laptops, mobile, and phones as the usually used educational technology for teaching by the participants in playing their roles as digital leaders. The study, however, revealed the speaker as the least used educational technology device by the teachers. The findings further show that although most of the participants used digital technology tools, only a few effectively applied the tools in their instructional delivery. This result is interesting, given that a burgeoning body of the literature such as Amory [23], Bagheri et al. [24], Bates and Sangra [25], and Cheung and Slavin [26] found their integration into instructional delivery of most higher education institutions in the world. These digital technology tools are common, easy to operate, accessible, and have numerous advantages [40]. These merits perhaps account for the reason most teachers would want to use them to teach. Alkash and Al-Dersi [29] and Chevers and Whyte [19] believed that these tools make teaching lively, less stressful, and flexible.
Another possible explanation could be that most of the university teachers owned laptops and mobile phones and used them for various social activities. Research has shown that most university teachers believe that the use of these technology tools enhances teaching and fosters collaboration between students and faculty members. For instance, Tondeur et al. [21] pointed out that educational technology integration in the instructional process has become common because technology has assumed a pivotal role in enhancing teaching and learning. It is therefore not surprising that the participants deployed the digital devices to teach. It is also believed that most students have laptops and mobile phones; therefore, the participants would naturally find it ideal to share information and educational resources with the students [5].
Again, the use of the digital tools in teaching by the participants as digital leaders appears to give credence to the finding that digital technology tools increase teachers’ ability to speedily search for information [2, 7] and library databases [1]. By implication, the findings mean that if university teachers in the developing world are assisted with technology devices, it would boost their morale and encourage them to integrate educational technology into teaching [41]. It would also enhance the quality of their instructional delivery and impact positively on students’ learning outcomes.
Comparing the findings of this research with previous studies reveals some consistencies. For example, the findings appear to confirm a key finding of Bozalek et al. [1] who revealed that educational technology devices are used in teaching in higher institutions in South Africa. Furthermore, Sife et al. [6] found that in Tanzania, higher institutions faculty members use educational technology for many educational purposes. The findings also corroborate Jackson and Chapman’s [4] research who reported that most lecturers were proficient in using PowerPoint and Word applications for teaching.
Arguing from the perspective of Roger’s [42] diffusion of innovation theory, which anchors this research, one would reason that if digital technology tools are not easy to use, not accessible, and do not offer relative advantages to university teachers in the developing world, they might decline their usage in teaching. It appears obvious that university teachers in Ghana, like all other teachers in the higher education sector in the developing world, may have positive attitudes toward the usage of digital technology tools in teaching but they need support to procure them.
This study aimed to use the context of Ghana to examine the kinds of digital technology tools university teachers in the developing world often used in their teaching as digital leaders, and whether the tools were effective in promoting academic work. The study mainly found laptops, mobile phones, and projectors as the commonest digital technology tools used in teaching by the participants, and they thought that the tools effectively promoted academic work.
The study has two major limitations. First, the accidental technique used to recruit participants from Ghanaian universities does not allow the findings to generalize beyond the present sample. Second, because the study used the cross-sectional survey design, it cannot offer causal interpretations. Based on the limitations, we recommend that future research should compare the experiences of university teachers playing digital leadership roles in different geographical contexts across several developing countries. Because the research found that digital technology tools were effective in promoting academic work, we wish to also suggest that universities in Ghana should provide allowances to teachers to assist them to procure digital technology tools needed for teaching.
Despite the limitations, substantially, the findings are original because, to the best of our knowledge, there has not been previous research that has focused on the same issue on HEIs in the developing world. The study is also novel because of its use of the Diffusion of Innovation (DoN) theory to discuss pertinent issues about digital technology use in higher education. Most importantly, because developing countries arguably have similar characteristics, the findings may apply favorably with other developing countries.
Again, the findings may have global implications because knowing the effectiveness of the use of digital technology in higher education teaching in Ghana as a developing country could serve as a source of information on measures HEIs in developing countries have put in place to deal with the negative impact of the Covid-19 pandemic on academic work. Finally, research also contributes to existing knowledge about how HEIs in the developing are using digital leadership to address the issue of large class size teaching bedeviling most universities.
The authors acknowledge the immense contributions of colleagues who read through the manuscript and provided the needed feedback to improve the quality of the paper.
There are no potential conflicts of interest/competing interests with respect to the research, authorship, and/or publication of this article.
The authors received no financial support for the research, authorship, and/or publication of this article.
The authors consent to the publication of the manuscript titled above in the journal “Australian Education Researcher.”
All data generated or analyzed during this research are included in this manuscript (and its supplementary file).
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