HIV-Associated Cancer Biomarkers: History
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Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor:
Zodwa Dlamini
,
Mzwandile Mbele
,
Tshepiso J. Makhafola
,
Rodney Hull
,
Rahaba Marima

Biomarkers are classified based on certain parameters such as functions and characteristics such as Type 0, Type I and Type II.

  • cancer
  • HIV/AIDS
  • biomarkers
  • diagnosis
  • prognosis
  • HAART

1. Classification of Cancer Biomarker

Biomarkers are classified based on certain parameters such as functions and characteristics such as Type 0, Type I and Type II [1][2][3]. Type 0 biomarkers are used to measure the natural history of diseases. These biomarkers are associated with known clinical indicators. Type I biomarkers correlate with the efficacy of pharmacologic agents. Type II biomarkers are surrogate endpoint biomarkers that are intended to substitute for clinical endpoints [2][4]. Recently, tumour biomarkers are grouped into certain categories such as proteins, glycoproteins, hormones, receptors, oncofetal antigens, genetic markers and RNA molecules [5]. Cancer biomarkers are also known to be classified into diagnostic, predictive, prognostic and pharmacodynamic biomarkers [6][7][8][9][10]. Prediction biomarkers, also known as response markers, are used to assess the effect of a specific drug to allow the clinicians to select chemotherapeutic agents which will have the best positive response on the patient [10][11]. Prognostic biomarkers are used to analyse the overall outcome of the disease [12][13]. Lastly, pharmacodynamic biomarkers are utilised to select chemotherapeutic agents’ doses in a given set of tumour–patient conditions. These biomarkers are also used to assess the impending treatment effects of a drug. During cancer development, the diagnostic markers may be present at any stage [14][15].

2. Biomarkers Used in HIV-Associated Cancer Diagnosis and Prognosis

Compared to the broad spectrum of the NADCs, ADCs that include Kaposi’s Sarcoma, cervical cancer and NHL are on the decline since the introduction of HAART. The diagnostic and prognostic challenges of these HIV-associated cancers are discussed below [16].

2.1. Diagnosis and Prognosis Challenges of HIV-Associated Cervical Cancer

Cervical cancer is a disease that develops as a result of a persistent infection with high-risk human papillomavirus (hrHPV) types, resulting in premalignant precursor lesions also known as cervical intraepithelial neoplasia (CIN) [9][17]. Human papilloma virus (HPV) is defined as the cause of cervical cancer, although only 2% of cervical HPV are known to result in cervical cancer [18]. Cervical cancers have two common histologic types, namely, squamous cell carcinoma (SCC), accounting for 70% of all adenocarcinomas [19][20]. In 2018, new diagnosed cervical cancer cases worldwide were ~569,000. Furthermore, ~311,000 deaths were associated with cervical cancer. The low-to-middle income countries (LMICs) such as South Africa accounted for ~90% of these deaths [19]. Abnormalities in cellular proliferation, maturation and nuclear atypia are characteristics of CIN [21]. According to Flepitsi et al. (2014), CIN may regress to normal or progress to invasive cervical cancer if untreated [22]. It is reported that approximately one-third to one-half of the CIN I and CIN II cases regress without treatment; including when the abnormality of the lesions is more severe, and they are less likely to regress [22]. Grading of CIN lesions is vital for clinical management of patients and specific biomarkers are required for grading and accurate diagnosis. The inaccurate grading results in inaccurate diagnosis and, therefore, ineffective treatment of CIN.
A whole host of novel biomarkers for the diagnosis of cervical cancer have been identified. These include the presence of HPV E6/E7 mRNA, miR-9 and patterns of DNA methylation. Protein expression biomarkers include p16INK4a/ki-67, SCC-Ag, M-CSF and VEGF. However, not all these biomarkers are suitable for the diagnosis of HIV-associated cervical cancer [23][24][25].
Cervical cancer diagnosis is achieved by the detection of HPV DNA in cervical tumour cells, which has proven to be a good diagnostic and risk predictor tool (Table 1) [26]. The initiation and mediation of the oncogenic process of cervical cancer occurs by the upregulation of HPV E6/E7 oncoproteins. The overexpression of these oncoproteins serves as a biomarker for increased cervical cancer risk [27][28][29]. The hrHPV 16 and 18 subtypes have a vital role in malignant transformation of cells by developing E6 and E7 viral regulatory proteins [30]. The viral regulatory proteins, E6 and E7, are involved in cell proliferation and survival. The microRNA miRNA9 has been shown to be an accurate prognostic and diagnostic biomarker for cervical cancer [31]. This miRNA is known to play a role in neurogenesis, which is a process that also plays a role in the progression of many cancers [31]. Changes in DNA methylation is a major epigenetic mechanism that regulates gene expression, genomic imprinting, cell differentiation, development and inflammation [32]. These epigenetic changes also play a role in the early diagnosis of cervical cancer.
The most vital biomarkers implicated in cervical cancer are HPV and oncogene E6 and E7 [28]. Another protein, the Ki-67 is the cell proliferation biomarker which plays an important role in confirming the diagnosis and CIN grading [33]. This biomarker is known to detect a nuclear antigen found only in cell proliferation but not in other cells [34]. Furthermore, Ki-67 is known to be more intensely stained in HPV-positive than HPV-negative epithelium. The p16 protein, a cyclin-dependent kinase (CDK) inhibitor has a specific biomarker functions used to identify squamous and glandular dysplastic cervical epithelium. In cervical epithelial cells that are transformed due to the hrHPV E7 oncoprotein expression, the overexpression of p16 has been observed [17]. In a study performed by Carozzi and colleagues (2013), p16 has been shown to be a biomarker for CIN II or for the development of CIN II within 3 years in HPV-positive women [35]. It has been reported that p16 alternatively complements Ki-67 for HPV-related neoplasia [29][36][37]. Ki67 and p16 are better used in combination that alone, in the diagnosis of cervical cancer. Cytokeratin (CK) 17, a biomarker for endocervical reserve stem cells, plays an important role in the differentiation between immature squamous metaplasia and high-grade CIN III. CK-17 is a biomarker that is not expressed in cervical glandular epithelial cells, squamous cells, or mature squamous metaplastic cells. However, they are known to be specific for immature metaplastic cells and reserve cells (Mockler et al., 2017) [37][38]. The important tumour suppressor protein p53 is a known nuclear phosphoprotein encoded by the p53 gene and responsible for cell proliferation and apoptosis control. Alterations in the p53 gene are closely associated with invasive cancers as a result of loss of tumour suppressor function. The overexpression of p53 biomarker have been shown in cervical cancers [39][40]. Table 1 outlines HIV-associated cancer biomarkers.
The measurement of serum levels of squamous cell carcinoma antigen (SCC-Ag), which is a serine protease inhibitor (Serpin), is a good indicator of the presence of cervical cancer, or additionally, as a prognostic indicator. SCC-Ag levels are elevated in cervical cancer [41]. The macrophage colony-stimulating factor (M-CSF) is a hematopoietic growth factor and can serve as a biomarker in multiple cancers [41]. The vascular endothelial growth factor is used as a diagnostic biomarker in not only cervical, cancer but also in breast and endometrial cancer [42].
Table 1. Identified biomarkers and the related changes in HIV-associated cervical cancer.
HIV-Associated Cervical Cancer Changes in HIV-Cervical Cancer References
HPV DNA Elevated [17][43]
HPVE6/E7 Elevated [26][29][44]
Ki-67 Elevated [45][46]
P16 Elevated [17][45]
CK17 Elevated [17][47]
MCM Elevated [48][49]
CDC6 Elevated [50][51]
Ribosomal protein S12 Elevated [52]
P53 Elevated [21][53]
PCNA Elevated [54][55]
MIB-1 Elevated [55]
P63 Suppressed [17][56]
CD44 Elevated [57]

2.2. Diagnosis/Prognosis Challenges of HIV-Associated Non-Hodgkin Lymphoma

NHL is reported as the second most common malignancy in HIV-infected patients and is characterised by diffused large B-cell lymphoma (DLBCL) [58]. NHL cases are believed to arise from B-cell progenitors and develop into various entities that are grouped into three, the low, intermediate and high-grade NHL [59]. Heterogeneous diseases such as DLBCL differ in genetic abnormality, morphology nature and clinical features, and patients vary in prognosis and respond differently to treatment [60][61]. DLBCL develops from normal antigen-exposed B-cells that have moved to or through germinal centres [9][61]. There are two subgroups identified by gene expression profiling: (i) germinal centre B-cell-like (GCB) lymphomas (typically CD10+ and BCL6+), and (ii) non-GCB lymphomas that are developed from cells resembling activated B-cell-like lymphomas [6][8][62][63]. Patients with GCB DLBCL display a better progression and overall survival than patients with non-GCB DLBCL, regardless of the international prognostic index score (IPI) [9][64][65]. IPI is a useful clinical tool that aids in prognostic prediction of patients with aggressive NHL [66]. It has been also suggested that the sub-classifications of DLBCL into GCB and non-GCB may be a vital prognostic factor.
The quality and quantity of affected lymph nodes for assessing morphology and architecture are the first requirement in the diagnosis of NHL [67][68][69]. Blood count, differentiation of white blood cells, count of platelet and examination of peripheral smear for the presence of atypical cells are performed to detect the involvement of peripheral blood and bone marrow [70]. These tests are followed by pathological tests such flow cytometry or immunohistochemically staining for immunophenotype [70]; Ki-67 or MIB-1 staining (an antibody against Ki-67) are used to identify aggressive lymphomas as these may be indicating a high growth fraction of tumours [70]. Ki-67 expression in DLBCL patients is associated with poor outcome and survival [71][72][73]. B-cell biomarkers such as CD19, CD20, CD22, CD79a and PAX-5 that play an important role in immunophenotypic expression patterns of DLBCL and flow cytometry have shown surface immunoglobulin light chain restriction in a majority of cases (Table 2) [9][74]. Since PAX-5 is a B-cell restricted transcription factor, positive PAX-5 immunostaining indicates a strong association with B-cell differentiation [9], while positive staining of biomarkers such as CD10, bcl-6 and MUM-1 distinguish GCB from non-GCB DLBCL [9][22]. Fork box protein P1 (FOXP1) is a transcriptional regulator of the B-cell development and has been found to be overexpressed in non-GCB DLBCL than in GCB DLBCL [69][74][75]. The poor survival and prognosis have been associated with FOXP1 [76]. For this reason, it has been recommended that FOXP1 should be used to distinguish non-GCB from GCB DLBCL to improve the diagnosis and predict prognosis of DLBCL.
In some studies, fluorescence in situ hybridisation (FISH) analysis of cMYC, a transcription factor that functions in regulating cell growth and cell cycle, has shown to occur in 10–15% of DLBCL lymphomas and is associated with worse prognosis outcomes [77]. Furthermore, the translocations of MYC confers poor prognosis in patients treated with cyclophosphamide, hydroxydaunorubicin, oncovin and prednisone (CHOP) regime [22]. Modified immune mechanisms play a critical role in the pathogenesis of NHL. Increased prevalence of NHL has been reported among HIV-positive patients, patients with autoimmune disease and transplant recipients [11][78]. B-cell activation is commonly shown in HIV infection, which is caused by the overproduction of B-cell stimulatory cytokines, such as IL-6 and IL-10. This also applies for the stimulation of B-cells by HIV and other microbial antigens [62][73]. HIV also induces the production of inflammatory cytokines that cause B-cell stimulation, activation and proliferation. Cell lines derived from HIV-NHL show the expression of cytokines including interleukin 6, 10 and tumour necrosis factor-α [79][80][81][82]. B-cell activation is characterised by the proliferation lymphocyte, class switch recombination (CSR) and somatic hyper-mutation, all of which are prone to result in DNA replication errors that may lead to lymphomagenesis. Table 2 outlines HIV-associated NHL biomarkers.
Table 2. Identified biomarkers and the related changes in HIV-associated Non-Hodgkin lymphoma.
HIV-Associated NHL Biomarkers Changes in HIV-NHL References
LDH Elevated [75][83][84]
Ki-67/MIB-1 Elevated [85][86]
CD19, CD20, CD22 Elevated [60][87]
PAX-5 Elevated [60][87]
CD10 Elevated [58][85]
bcl6 Elevated [22][88]
MUM-1 Elevated [58][85]
cMYC Elevated [89][90]
IL-6 Elevated [15][91]
IL-10 Elevated [15][91][92]
TNF-α Elevated [15][93]
CRP Elevated [75][91]
sCD23, sCD27, sCD30, sCD44 Elevated [74][76]
EBV DNA Elevated [77]
CXCL13 Elevated [15][76]
FLC Elevated [15][94]
FOXP1 Elevated [22][95]
B2M Elevated [22][83]

2.3. Diagnosis/Prognosis Challenges of HIV-Associated Kaposi’s Sarcoma

KS is defined as an endothelial neoplasia that is located in cutaneous lesions and is known as a common malignancy in HIV patients [1]. HIV-associated KS (HIV-KS) is reported as a low-grade vascular tumour which is associated with human herpesvirus-8 (HHV8)/KS-associated herpes virus (KSHV) infection and is the most frequent and aggressive type [10][59]. The primary target for KS involves the skin [11][96]. Multiple mucocutaneous lesions from early or patch stage into plague stage and then tumour or nodular stage contain spindle-shaped tumour cells. KS has a variable clinical course, and this can pose challenges in histologic diagnosis [7]. KS differs in characteristic features from other benign or malignant vascular tumours and other nonvascular spindle tissue neoplasms. This is a vital challenge and require great investigations [8]. In its early stages, lesions may either regress or progress. Progression represents the expression of HHV8 latency that include latent nuclear antigen-1 (LANA-1) [1], cyclin-D1 [9][10] and bcl-2 (Table 3) [11]. Receptor tyrosine c-kit gene expression profiling in cultured endothelial cells has a functional role in KS tumourigenesis-activated HHV8-related induction [12][13]. Table 3 outlines HIV-associated KS biomarkers.
Table 3. Identified biomarkers and the related changes in HIV-associated Kaposi’s Sarcoma.
HIV-Associated KS Biomarkers Changes in HIV-KS References
HHV8/LANA-1 Elevated [22][97][98][99]
Cyclin D1 Elevated [97][100][101]
bcl2 Elevated [79][80][82]
c-kit Elevated [81][102]
K12 Elevated [30][103]
K13/vFLIP Elevated [30][104][105]
vCyclin Elevated [80][106][107]
P53 Suppressed [108][109]
pRb Suppressed [30][100]
D2–40 Elevated [10][98][110]
CD31 Elevated [99][111]
CD34 Elevated [111][112][113]
FLI1 Elevated [22][112]
vIL-6 Elevated [30][114][115]
Tat Elevated [74]
bFGF Elevated [116]
TNF-α Elevated [22][116]
IL-1 Elevated [117]
Oncostatin M Elevated [116][118][119]
There are eight variable diagnoses of KS. These include cutaneous angiosarcoma, spindle cell haemangioma, pyogenic granuloma and spindled melanoma. vascular transformation of lymph nodes, dermatofibrosarcoma protuberans, pilar leiomyoma and stasis dermatitis [8]. KS histology indicates the progressive proliferation of spindle-shaped cells which are associated with KSHV/HHV8 [15]. The immunohistochemical detection of HHV8 of fixed tissues might be a diagnostic tool to differentiate KS. HHV8 encodes for numerous proteins used to induce or maintain KS lesions, such as K12, K13/viral FADD-like interferon converting enzyme inhibitory protein (vFLIP), vCyclin and the LANA-1 that is required for cellular transcription [17][18][20]. In the viral genome, the open reading frame encodes for the HHV8 LANA-1 protein which reveals its expression during viral latency and its functional role in viral integration into the host genome. The HHV8 LANA-1 protein has been reported to have an interference involvement in apoptosis through interactions with p53 [21]. The antibodies such as platelet/endothelial cell adhesion molecules, PECAM1 (D2-40, CD31), a hematopoietic progenitor cell surface protein and Friend leukaemia virus integration 1 are used in immunohistochemical staining to distinguish cutaneous KS from other diseases [4][28].
There are a number of peptide growth factors of HIV that encode Tat protein, inflammatory cytokines and KSHV/HHV8 gene products involved in KS cell growth and development [35]. The antigens for HHV8 affect cell signaling pathways and deregulate immune response and apoptosis through vCyclin, vFLIP, bcl2 oncogene, viral interferon regulatory factor and vIL-6 [22]. The mutations in immune cells may play a vital function in the neoplastic process [17][120]. Immune activation has a cooperative function with growth factors and HIV-1 Tat protein in KS development [45]. HIV-KS cells produce cytokines and angiogenic growth factors such as fibroblast growth factors (FGFs), tumour necrosis factor-α (TNF-α), interleukin-1 (IL-1), IL-6, Tat and oncostatin M. They express high affinity receptors for some cytokines [46][47].

This entry is adapted from the peer-reviewed paper 10.3390/ijms22158127

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