Abstract
Introduction
Quality of life (QOL) is an essential component of care in people with HIV‐associated Kaposi sarcoma (HIV‐KS). Kaposi sarcoma herpes virus (KSHV) promotes cytokine expression and a dysfunctional inflammatory environment, contributing to KS pathogenesis and progression. However, disease‐related inflammatory factors influencing QOL and symptoms remain underexplored. This study examines the relationship between baseline QOL parameters and inflammatory cytokine biomarkers in treatment‐naïve Africans with HIV‐KS participating in the randomized controlled KAART study. We hypothesized that inflammatory cytokines are linked with reduced QOL and symptom burden.
Methods
Twenty‐eight cytokines were measured from stored baseline serum using the Milliplex® multiplex assay. QOL was assessed using the validated EORTC QLQ‐C30. Spearman Rho‐Rank correlation was used to assess relationships between cytokine levels and QOL parameters, with p ≤ 0.01 considered statistically significant.
Results
Paired cytokine and QOL data were available for 68 participants. IL‐8 showed significant negative correlations with summary scores, a reliable indicator of overall QOL (r s = −0.35, p = 0.005). Increased IL‐8 also correlated significantly with reduced emotional functioning scales (r s = −0.33, p = 0.01) and increased pain (r s = 0.32, p = 0.01). By contrast, increased IL‐10 correlated significantly with reduced pain (r s = −0.31, p = 0.01). VEGF and MCP‐1 levels correlated negatively with role functioning (r s = −0.32, p = 0.01; r s = −0.30, p = 0.01).
Conclusion
IL‐8 is a key cytokine affecting QOL in HIV‐KS. Elevations have a negative impact on pain, emotional functioning and overall QOL. IL‐10, VEGF and MCP‐1 perturbations also impact QOL. These findings enhance understanding of cytokine involvement in KS pathogenesis.
Keywords: biomarkers, cytokines, HIV‐associated Kaposi sarcoma, Kaposi sarcoma herpes virus, KS‐symptoms, quality of life
INTRODUCTION
Kaposi sarcoma herpes virus (KSHV) is causally associated with Kaposi sarcoma (KS) and is known to infect predominantly endothelial cells [1, 2]. KSHV encodes multiple viral proteins that modulate the host's cell signaling pathways, leading to the expression of many cytokines that induce inflammation and angiogenesis [3]. These cytokines are implicated in the pathogenesis and maintenance of KS [4]. Elevated levels of IL‐6, IL‐8, IL‐10, interferon‐gamma (IFN‐γ) and vascular endothelial growth factor (VEGF) have been found in KS lesions [5].
Inflammatory cytokines may contribute to cancer pathogenesis, and symptom development may be a result of this inflammatory response. The impact of cytokines as potential biomarkers for assessing symptoms and quality of life (QOL) in people with cancer is a relatively new field of study [6, 7]. Elevated levels of serum cytokines, interleukins (IL‐2, 6, 10, 12 and 18), tumour necrosis factor‐alpha (TNF‐α) and transforming growth factor‐β (TGF‐β) have been found in individuals with cancer [8]. Research indicates that cytokines may play a role in the pathophysiology of cancer symptoms. A recent systematic review of 20 studies showed multiple associations between 31 pro‐ and anti‐inflammatory cytokines and symptoms and quality of life in 1806 participants with mixed incurable cancers. Notable findings were seen with cytokines IL‐6, IL‐1 and TNF‐α, and common symptoms included depression, fatigue, pain and loss of appetite [6]. Symptoms of fatigue, anorexia, nausea and diarrhoea are common in KSHV‐associated diseases, with elevated serum levels of IL‐6 and IL‐10 [9].
There is a need to explore inflammatory associations with symptom generation and QOL to identify cytokine biomarkers that will contribute to understanding KS pathogenesis. To date, this is the first study to evaluate the correlation of cytokines with QOL and symptoms in people with KS. We hypothesised that elevated pro‐inflammatory cytokine levels would be linked to reduced QOL and increased cancer‐related symptoms in people with KS.
MATERIALS AND METHODS
A descriptive correlational cross‐sectional analysis was conducted using baseline QOL data and baseline serum cytokines from participants of the KAART trial (NCT00380770; clinicaltrials.gov), a prospective, controlled trial of 112 treatment‐naive adult HIV‐KS participants randomized to receive ART (anti‐retroviral therapy) with or without chemotherapy, followed for a period of 12 months (from 2002–2008). Details, including study design and initial QOL findings, were previously reported [10, 11]. Participants' sera were collected at routine monitoring and stored in 1 mL aliquots at −80°C until analysed. Full informed consent was taken, and approval was obtained from the University of KwaZulu‐Natal's biomedical research ethics committee (BE442/16).
Assessments
The validated, 30‐item, self‐reported cancer‐specific European Organization for Research and Treatment of Cancer QOL questionnaire (EORTC QLQ‐C30) was used to measure QOL data prospectively in all participants at baseline and 3‐monthly intervals. The questionnaire was translated into isiZulu. Domains include a global health scale (GHS), 6 single‐item measures, 5 functional (physical, role, emotional, cognitive and social), and 3 symptoms (fatigue, nausea/ vomiting and pain). Scores range from 0 to 100 [12]. The summary score is calculated as the mean of the combined scales (excluding GHS and financial impact) [13]. Higher scores indicate better QOL for the functional domains, GHS and summary score, as well as a higher symptom burden for the symptom domains [12].
Cytokine Measurements
A panel of cytokines and circulating factors hypothesized to have a role in KS pathogenesis was evaluated. Fibroblast growth factor 2 (FGF‐2), eotaxin, granulocyte colony‐stimulating factor (G‐CSF), granulocyte‐macrophage colony‐stimulating factor (GM‐CSF), interferon gamma (IFN‐γ), interleukin (IL) ‐10, IL‐2p70, IL‐13, IL‐15, IL‐17, IL‐9, IL‐1β, IL‐2, IL‐4, IL‐5, IL‐6, IL‐7, IL‐8, interleukin‐1 receptor antagonist (IL‐1RA), soluble CD40L (sCD40L), interferon gamma‐induced protein 10 (IP‐10), monocyte chemoattractant protein‐1 (MCP‐1), macrophage inflammatory protein 1‐alpha (MIP‐1α), macrophage inflammatory protein 1‐beta (MIP‐1β), tumour necrosis factor (TNF‐α), vascular endothelial growth factor (VEGF) and platelet‐derived growth factor (PDGF) were tested in duplicate with multiplex analysis, using the Milliplex® MAP Magnetic Bead Cytokine assay (#HCYTOMAG‐60 K, Merck, USA), as per the manufacturer's recommendations. Bead complexes were acquired on the MAGPIX® instrument using the xPONENT software and analyzed with the Merck Belysa Immunoassay Curve Fitting Software. The limit of detection (LOD) is the lowest concentration of an analyte that can be reliably detected from background noise. LOD is listed as “N/A” for standard curves without variation in their blanks [14]. Cytokines were selected based on previous relevant studies.
Statistical Analysis
Descriptive statistics were used to summarize participant characteristics, baseline QOL domain scores, and cytokine concentrations. Continuous variables were presented as medians with interquartile ranges (IQRs) due to non‐normal distributions, and categorical variables were summarized as frequencies and percentages. Spearman's rank correlation was used to evaluate the correlations between baseline serum cytokine concentrations and QOL domain scores. A total of 28 cytokines were assessed individually against each QOL domain. Further analysis was conducted to assess whether the T (tumour) status in KS: T0 (good risk) versus T1 (poor risk) could have confounded the observed correlations. Baseline cytokine concentrations and QOL domain scores were compared by T‐status using nonparametric tests, focusing specifically on cytokines that showed statistically significant correlations. Given the exploratory aim of this study and the multiple comparisons, a conservative significance threshold of p‐value ≤0.01 was used. Values below the LOD were replaced by the LOD value for statistical purposes. Analyses were performed using STATA version 16.
RESULTS
Participant characteristics
The baseline sera of 73 of the HIV‐KS participants were available for analysis. The median age was 33 years (IQR 28–39 years). Thirty‐nine (53.42%) were males and 34 (46.58%) were females. The majority were black Africans (71, 97.26%), one white, and the other mixed race. According to the AIDS Clinical Trials Group (ACTG) staging classification, 68 (93.15%) were considered poor risk; 67 (91.78%) participants had T1 tumour stage, 39 (53.42%) had I1 immune status with a CD4 count below 150 cells/μL, and 28 (33.36%) had systemic symptoms meeting poor risk criteria (S1). Visceral disease was found in 37 (50.68%) at baseline.
Baseline QOL data
Corresponding baseline QOL data was available for 68 subjects (Table 1). Overall, participants reported satisfactory QOL scores (median, IQR) apart from financial problems (100, 33.33–100), GHS (50, 41.67–66.67) and pain (50, 25–83.33).
TABLE 1.
Baseline quality of life scores.
| Quality of life domains | Scores | |
|---|---|---|
| Global health status | 50 (41.67–66.67) | |
| Summary score | 70.75 (57.12–85.85) | |
| Functional scales | Physical | 86.67 (86.67–93.33) |
| Role | 66.67 (33.33–83.33) | |
| Emotional | 75 (44.44–83.33) | |
| Cognitive | 83.33 (50–100) | |
| Social | 75 (33.33–100) | |
| Symptom scales/items | Fatigue | 44.44 (11.11–66.67) |
| Nausea/vomiting | 0 (0–25) | |
| Pain | 50 (25–83.33) | |
| Dyspnea | 0 (0–33.33) | |
| Insomnia | 33.33 (0–66.67) | |
| Appetite loss | 33.33 (0–66.67) | |
| Constipation | 0 (0–66.67) | |
| Diarrhoea | 0 (0–50) | |
| Financial problems | 100 (33.33–100) | |
Note: Data presented as medians (interquartile range).
Scores range from 0 to 100. Higher scores indicate better QOL for the functional domains, global health status and summary score, and a higher symptom burden for the symptom domains.
Global health status is a strong overall indicator of quality of life, but the novel summary score is thought to be more meaningful and reliable.
Cytokines
Median serum cytokine concentrations at baseline are shown in Table 2. Cytokine assays IL‐13 and IL‐9 yielded undetectable values for more than 50% of the samples and were excluded from analyses. Several potentially clinically important correlations were observed between individual cytokine biomarkers and the various QOL measures and symptoms (Table 3).
TABLE 2.
Baseline serum cytokine concentrations.
| Median (pg/ml) | Interquartile range | Limit of detection | |
|---|---|---|---|
| FGF2 | 45.88 | 38.59–56.62 | 21.47 |
| EOTAXIN | 76.86 | 60.54–116.58 | 2.63 |
| G‐CSG | 26.34 | 16.56–37.16 | 7.08 |
| GM‐CSF | 4.55 | 2.01–6.16 | 0.56 |
| IFN‐γ | 20.49 | 10.16–30.53 | 1.23 |
| IL‐10 | 25.51 | 13.97–51.11 | 0.5 |
| IL‐12p70 | 4.37 | 1.86–6.83 | 0.66 |
| IL‐13 | BDL | BDL‐1.62 | 0.06 |
| IL‐15 | 3.3 | 1.18–4.99 | 0.54 |
| sCD40L | 826.13 | 448.55–1316.88 | 43.09 |
| IL‐17 | 1.95 | 0.93–3.13 | 0.17 |
| IL‐1RA | 38.8 | 21.54–65.98 | N/A |
| IL‐9 | BDL | BDL‐0.58 | 0 |
| IL‐1β | 2.48 | 1.4–3.92 | N/A |
| IL‐2 | 2.29 | 1.49–3.17 | 0.13 |
| IL‐4 | 5.9 | BDL‐13.84 | 2.97 |
| IL‐5 | 2.62 | 1.77–4.31 | N/A |
| IL‐6 | 1.83 | 0.76–4.05 | 0.24 |
| IL‐7 | 4.67 | 3.33–6.24 | 0.7 |
| IL‐8 | 5.16 | 3.31–8.11 | N/A |
| IP‐10 | 1239.71 | 799.21–1852.44 | 2.24 |
| MCP‐1 | 268.86 | 171.76–352.76 | 0.81 |
| MIP‐1α | 7.21 | 4.98–9.53 | 1.38 |
| MIP‐1β | 20.53 | 16.11–26.64 | 0.72 |
| TNF‐α | 22.43 | 17.68–29.66 | 4.78 |
| VEGF | 54.89 | 34.12–104.77 | N/A |
| PDGF‐BB | 259.77 | 68.62–559.64 | 11.63 |
| RANTES | 859.97 | 467.54–1610.2 | 45.25 |
Abbreviations: BDL, Below the detection limit; N/A, Not available; ND, Response is below the limit of detection.
TABLE 3.
Spearman Rho–Rank correlation analyses of baseline symptoms and QOL parameters with serum cytokine levels.
| Functional scales | Symptoms | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| GHS | SS | PF | RF | EF | CF | SF | FA | PA | SL | AP | |
| FGF2 | 0.02 | −0.11 | −0.03 | −0.24 | −0.12 | 0.03 | −0.10 | 0.06 | 0.01 | 0.04 | 0.01 |
| EOTAXIN | −0.18 | −0.26 | −0.12 | −0.22 | −0.18 | −0.11 | −0.09 | 0.17 | 0.21 | 0.08 | 0.26 |
| G‐CSG | −0.08 | 0.03 | −0.09 | −0.10 | 0.03 | 0.02 | −0.03 | 0.07 | −0.03 | −0.00 | −0.00 |
| GM‐CSF | −0.09 | −0.06 | −0.12 | −0.18 | −0.05 | 0.15 | −0.05 | 0.01 | −0.05 | −0.04 | 0.10 |
| IFN‐γ | −0.22 | −0.13 | −0.17 | −0.26 | −0.11 | 0.06 | −0.02 | 0.22 | 0.15 | −0.05 | 0.10 |
| IL‐10 | −0.10 | 0.27 | 0.20 | 0.14 | 0.13 | 0.24 | 0.25 | −0.17 | −0.31* | −0.11 | −0.10 |
| IL‐12p70 | 0.03 | −0.00 | −0.15 | −0.18 | −0.03 | 0.18 | −0.01 | −0.00 | −0.01 | −0.12 | 0.07 |
| IL‐15 | −0.16 | −0.18 | −0.15 | −0.28 | −0.18 | −0.00 | −0.24 | 0.15 | 0.12 | 0.05 | 0.09 |
| sCD40L | 0.09 | 0.04 | −0.09 | −0.05 | 0.06 | 0.09 | 0.23 | −0.07 | 0.03 | −0.18 | 0.13 |
| IL‐17 | 0.05 | 0.01 | −0.09 | −0.05 | −0.10 | 0.09 | −0.01 | 0.01 | −0.08 | −0.04 | 0.02 |
| IL‐1RA | −0.03 | −0.07 | −0.17 | −0.17 | −0.15 | 0.13 | −0.06 | 0.09 | 0.10 | −0.06 | 0.08 |
| IL‐1β | −0.08 | −0.10 | −0.18 | −0.22 | −0.09 | 0.12 | −0.02 | 0.07 | 0.05 | 0.01 | 0.05 |
| IL‐2 | −0.19 | −0.06 | −0.11 | −0.28 | −0.11 | 0.07 | 0.00 | 0.08 | 0.08 | −0.07 | 0.04 |
| IL‐4 | −0.09 | −0.07 | −0.16 | −0.16 | −0.07 | 0.11 | −0.09 | −0.00 | 0.02 | 0.06 | 0.03 |
| IL‐5 | −0.16 | 0.01 | −0.14 | −0.15 | −0.02 | 0.17 | −0.03 | 0.01 | 0.03 | −0.08 | 0.05 |
| IL‐6 | −0.04 | −0.07 | −0.25 | −0.22 | −0.04 | 0.11 | −0.11 | 0.09 | 0.17 | −0.04 | 0.00 |
| IL‐7 | −0.05 | −0.10 | −0.08 | −0.25 | −0.01 | 0.13 | 0.04 | 0.06 | 0.04 | −0.07 | 0.13 |
| IL‐8 | −0.15 | −0.35* | −0.29 | −0.17 | −0.33* | −0.18 | −0.27 | 0.28 | 0.32* | 0.18 | 0.22 |
| IP‐10 | −0.21 | −0.06 | 0.06 | −0.02 | 0.05 | 0.11 | 0.03 | 0.15 | −0.02 | −0.12 | 0.03 |
| MCP‐1 | −0.16 | −0.25 | −0.02 | −0.30* | −0.20 | −0.08 | −0.08 | 0.19 | 0.23 | −0.05 | 0.23 |
| MIP‐1α | −0.13 | −0.23 | −0.01 | −0.27 | −0.21 | −0.01 | 0.02 | 0.18 | 0.14 | −0.02 | 0.12 |
| MIP‐1β | −0.06 | −0.07 | −0.02 | −0.14 | −0.03 | 0.01 | 0.01 | 0.03 | 0.03 | −0.04 | 0.00 |
| TNF‐α | −0.05 | 0.03 | 0.15 | 0.02 | 0.25 | 0.10 | −0.16 | −0.09 | −0.16 | −0.05 | −0.01 |
| VEGF | −0.14 | −0.21 | −0.20 | −0.32* | −0.18 | −0.04 | −0.07 | 0.16 | 0.09 | 0.04 | 0.20 |
| PDGF | 0.05 | 0.10 | −0.26 | −0.17 | −0.05 | 0.03 | 0.06 | 0.03 | 0.15 | −0.04 | 0.20 |
| RANTES | 0.02 | 0.06 | −0.17 | −0.16 | −0.01 | 0.03 | 0.05 | 0.01 | 0.07 | −0.04 | 0.10 |
Note: r indicates the linear correlation coefficient. The colour highlights the significant findings.
Abbreviations: AP, appetite loss; CF, cognitive functioning; EF, emotional functioning; FA, fatigue; GHS, global health scale; PA, pain; PF, physical functioning; QOL, quality of life; RF, role functioning; SF, social functioning; SL, Insomnia; SS, summary score.
Statistically significant at ≤0.01.
Functional scales
Spearman's rho correlation indicated statistically significant, moderate, negative correlations between role functioning and cytokine levels of VEGF (r s (63) = −0.32, p = 0.01), and MCP‐1 (r s (63) = −0.30, p = 0.01). There was a statistically significant, moderate, negative correlation between emotional functioning scales and IL‐8 (r s (66) = −0.33, p = 0.01). Findings suggest that cytokines play a role in influencing functional scales.
Symptom Scales
The symptom scores nausea/vomiting, dyspnoea, constipation and diarrhoea were excluded from the correlation analysis due to a lack of variability in the data. The symptoms of insomnia, fatigue and appetite loss did not show any significant correlations with cytokine levels. A statistically significant, positive moderate correlation was observed between pain and IL‐8 (r s (66) = 0.32, p = 0.01), and a moderate, negative correlation was observed with IL‐10 (r s (66) = −0.31, p = 0.01). Results indicate that serum cytokine levels are significantly correlated with pain (Tables A1 and A2).
Overall QOL
GHS scores did not show any significant correlations with any of the cytokine concentrations. However, the summary score, a better indicator of overall QOL, showed a statistically significant, moderate negative correlation with IL‐8 (r s (62) = −0.35, p = 0.005).
Cytokine levels and QOL scores by T(tumour)‐status
No statistically significant baseline differences in cytokine concentrations or QOL scores were found between the T0 and T1 groups (p‐values >0.25). These findings suggest that the tumour status is unlikely to confound the correlations observed.
DISCUSSION
This research provides novel observations about cytokine biomarkers and QOL and its associated symptoms in people with HIV‐KS. Findings contribute to our understanding of the role of inflammatory cytokines in KS pathogenesis. Several significant correlations were observed between inflammatory and angiogenic circulating factors and various QOL domains, including functional scales, symptoms and summary scores.
KSHV infection can induce the production of pro‐ and anti‐inflammatory cytokines through a complex activation and interaction of cellular pathways, resulting in the development and maintenance of KS, which may also lead to disease symptoms. Viral FLICE‐Inhibitory Protein (vFLIP) encoded by ORF71 of KSHV activates the NF‐kB pathway (linked to chronic inflammation), stimulating increased production of cytokines IL‐6 and IL‐8 [15]. Interestingly, many of the cytokines noted to be correlated with QOL/symptoms may be induced by viral G protein‐coupled receptor (vGPCR), a potent signaling molecule encoded by viral ORF74. vGPCR induces the mitogen‐activated protein kinase (MAPK) and p38 pathways, increasing the production of highly angiogenic cytokine VEGF, promoting angiogenesis and vascular permeability. vGPCR can also induce the activation of both AP‐1 and NF‐κB resulting in the expression of MCP‐1, IL‐8, IL‐1β, bFGF, PDGFβ, TNF‐α [16].
IL‐8
In our cohort, elevated levels of pro‐inflammatory cytokine IL‐8 correlated significantly with reduced summary score, reduced emotional functioning, and increased pain. The EORTC emotional functional scale, which consists of four items assessing feelings of tension, worry, depression and irritability, is used to assess the emotional burden experienced by people with cancer [12]. Increased IL‐8 may reflect biological correlates of that burden and identify those who may benefit from psychological support or intervention.
IL‐8 is a potent proinflammatory chemokine. Chemokines are the primary regulators of leukocyte migration to sites of inflammation or immune responses and may be responsible for the early histological changes associated with KSHV infection (massive inflammatory infiltrates of neutrophils, macrophages, lymphocytes and plasma cells) [17, 18]. IL‐8 has been found in significantly elevated levels in different tumours, and recent studies have linked it with poor cancer prognosis [19]. IL‐8 is crucial to the development of the angiogenic phenotype in KSHV‐infected endothelial cells in cell culture and when implanted into severe combined immunodeficient mice [20]. Besides its own angiogenic effect, IL‐8 also induces the expression of the potent angiogenic factor, VEGF [19]. The excessive angiogenesis and inflammation associated with KS could negatively impact QOL and account for the associated negative symptoms. In people with advanced lung cancer, genetic variations in IL‐8 and IL‐10 were associated with pain, depressed mood and fatigue [21]. In our cohort, increased levels of IL‐8 significantly correlated with worsening of pain symptoms and reduced summary score, a meaningful and reliable indicator of overall QOL [22]. To our knowledge, this is the first study to explore the relationship of cytokines with the novel summary score, and further research may identify key cytokines influencing QOL in cancers.
Anti‐IL‐8 agents may serve as potential therapeutic targets for treating HIV‐KS that could potentially improve KS symptoms and overall QOL. Anti‐IL‐8 antibodies appear promising for the treatment of advanced melanoma. Intravenous injection of the melanoma cell lines in nude mice showed a decrease in metastasis formation and a reduction in angiogenesis [23]. Anti‐IL‐8 agents appear well tolerated in ongoing trials of participants with advanced melanoma and in participants with metastatic or unresectable solid tumours [24].
IL‐10
In contrast to IL‐8, increased levels of IL‐10 correlated significantly with reduced pain. In animal studies and inflammatory pain models, the application of anti‐inflammatory cytokines such as IL‐10 is known to promote analgesia [25]. IL‐10 plays a crucial role in host homeostasis, regulating and suppressing proinflammatory cytokine production and downregulating the immune response, thereby minimizing inflammatory tissue damage [26]. Although IL‐10 is considered an anti‐inflammatory cytokine, its role in KSHV‐associated diseases is unclear. IL‐10, IL‐6, stromal cell‐derived factor 1, and VEGF promote the growth, survival and spread of primary effusion lymphoma (PEL) and multicentric Castleman's disease (MCD) in people with AIDS [27]. Higher baseline levels of IL‐10 also correlated with tumour progression in ART‐naïve individuals with limited‐stage KS [28]. Significantly elevated levels of IL‐10 were found in people with disseminated KS and KSHV inflammatory cytokine syndrome (KICS) [29, 30].
VEGF and MCP‐1
Significantly elevated levels of the highly angiogenic VEGF and MCP‐1 correlated with reduced role functioning. Role functioning comprises aspects of social and occupational roles. Thus, people with KS proliferation, oedema and pathological angiogenesis might be particularly susceptible to poor role functioning. VEGF increases vascular permeability and is implicated in KS tumour‐associated oedema, which can be an incapacitating disease symptom [31]. Humanized anti–VEGF–A monoclonal antibody, bevacizumab, has shown a response in a subset of people with KS and may benefit role functioning [32]. MCP‐1 is a key inflammatory chemokine that plays a crucial role in the development and progression of KS by promoting immune cell recruitment, chronic inflammation and indirectly stimulating angiogenesis [33, 34]. Research into the anti‐tumour effects of anti‐MCP‐1 therapy appears promising. MCP‐1 inhibitor (mNOX‐E36) therapy enhances bevacizumab therapy in glioblastoma rodent models, and MCP‐1 neutralizing Ab treatment inhibits tumour proliferation in vitro [35].
KS is a tumour largely driven by chronic inflammation and cytokine‐mediated signalling, primarily triggered by KSHV activity [36]. Our findings add to the understanding of the molecular mechanisms of KS as well as associated symptom pathogenesis and the identification of key cytokines and cellular pathways as potential targets for KS therapy.
STRENGTHS AND LIMITATIONS
This is the first study demonstrating the relationship between inflammation and QOL/symptoms in people with HIV‐KS. A large panel of cytokines was analysed. However, the study size was small, and only baseline correlations were assessed. Although no significant differences were noted between T1 and T0 in baseline QOL scores or cytokines, the findings are based on a cohort where only 6 participants (8.2%) had T0 disease, limiting the statistical power to detect modest differences between the groups. Further research with larger cohorts is needed to validate the results. Longitudinal studies are required to determine the effects of treatment and KS progression. Additionally, cytokine dysregulation may be associated with the time from HIV diagnosis [37]. The KAART study did not collect time to HIV diagnosis; therefore, this factor was not controlled in the RCT, nor was it adjusted for in the correlations. We did not account for the possible co‐diagnosis of other KSHV‐associated diseases, such as MCD or KICS, which may have been present in this cohort and impacted both the cytokines and QOL measures.
CONCLUSION
Improvement in QOL is a therapeutic priority, especially in advanced disease, where survival is limited. Identifying potentially clinically useful cytokine biomarkers allows for the development of personalized and targeted therapy via inflammatory cytokine pathways. Our findings suggest that the pro‐inflammatory IL‐8 is a key cytokine associated with reduced quality of life and worsening of symptoms in people with HIV‐KS. Increased understanding of the complex roles of cytokines, chemokines and angiogenic factors in the pathogenesis of KS and KS‐associated symptoms identifies potential therapeutic targets in KSHV‐associated diseases. Anti‐cytokine therapy may be a novel approach to symptom treatment, enhancement of QOL, and ultimately, care and outcome of people afflicted with HIV‐KS.
AUTHOR CONTRIBUTIONS
Conception and design: FS, TSU, MM, NG, AM. Collection and assembly of data: FS. Data analysis and interpretation: FS, TSU, MM, NG, AM. Manuscript writing: FS, TSU, MM, NG, AM. Final approval of manuscript: FS, TSU, MM, NG, AM.
FUNDING INFORMATION
The degree from which this study emanated was funded by the South African Medical Research Council under the SAMRC Clinician Researcher Development Scholarship PhD Programme (57029). The research reported in this publication was supported by the South African Medical Research Council under a Self‐Initiated Research Grant (SN383887). The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the South African Medical Research Council.
CONFLICT OF INTEREST STATEMENT
The authors declare that they have no competing interests.
ACKNOWLEDGEMENTS
The authors would like to thank the participants of the KAART study and Sister G. Ghanyile for her invaluable assistance. Our deepest gratitude is extended to Fazana Dessai for conducting the cytokine analysis and aiding with the interpretation of results. Thanks to Wided Kelmemi, Donovan Alho, and Lawrence Rentoul for assistance with the Belysa software and results. Finally, I sincerely acknowledge Alan Li for his invaluable assistance with the analysis and interpretation of the data.
APPENDIX A.
TABLE A1.
Spearman's rank correlation coefficient of baseline serum cytokine concentrations with quality of life scores.
| Global Health Status | Summary score | Functional Scales | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Physical | Role | Emotional | Cognitive | Social | ||||||||||
| r | p | r | p | r | p | r | p | r | p | r | p | r | p | |
| FGF2 |
0.02 |
0.85 | −0.11 | 0.37 | −0.03 | 0.81 | −0.24 |
0.05 |
−0.12 | 0.31 | 0.03 | 0.83 | −0.10 | 0.41 |
| EOTAXIN | −0.18 | 0.16 | −0.26 | 0.04 | −0.12 | 0.33 | −0.22 | 0.08 | −0.18 | 0.15 | −0.11 | 0.37 | −0.09 | 0.48 |
| G‐CSG | −0.08 | 0.50 | 0.03 | 0.84 | −0.09 | 0.46 | −0.10 | 0.43 | 0.03 | 0.83 | 0.02 | 0.85 | −0.03 | 0.79 |
| GM‐CSF | −0.09 | 0.48 | −0.06 | 0.62 | −0.12 | 0.35 | −0.18 | 0.15 | −0.05 | 0.66 | 0.15 | 0.22 | −0.05 | 0.66 |
| IFN‐γ | −0.22 | 0.08 | −0.13 | 0.30 | −0.17 | 0.17 | −0.26 | 0.04 | −0.11 | 0.38 | 0.06 | 0.65 | −0.02 | 0.89 |
| IL‐10 | −0.10 | 0.43 | 0.27 | 0.03 | 0.20 | 0.10 | 0.14 | 0.25 | 0.13 | 0.29 | 0.24 | 0.05 | 0.25 | 0.04 |
| IL‐12p70 | 0.03 | 0.83 | −0.00 | 0.99 | −0.15 | 0.21 | −0.18 | 0.15 | −0.03 | 0.79 | 0.18 | 0.13 | −0.01 | 0.94 |
| IL‐15 | −0.16 | 0.19 | −0.18 | 0.15 | −0.15 | 0.24 | −0.28 | 0.03 | −0.18 | 0.13 | −0.00 | 0.98 | −0.24 | 0.05 |
| sCD40L | 0.09 | 0.48 | 0.04 | 0.75 | −0.09 | 0.46 | −0.05 | 0.69 | 0.06 | 0.64 | 0.09 | 0.46 | 0.22 | 0.06 |
| IL‐17 | 0.05 | 0.70 | 0.01 | 0.96 | −0.09 | 0.46 | −0.05 | 0.69 | −0.10 | 0.42 | 0.09 | 0.48 | −0.01 | 0.95 |
| IL‐1RA | −0.03 | 0.80 | −0.07 | 0.57 | −0.17 | 0.18 | −0.17 | 0.17 | −0.15 | 0.22 | 0.13 | 0.28 | −0.06 | 0.64 |
| IL‐1β | −0.08 | 0.52 | −0.10 | 0.43 | −0.18 | 0.14 | −0.22 | 0.08 | −0.09 | 0.49 | 0.12 | 0.33 | −0.02 | 0.86 |
| IL‐2 | −0.19 | 0.13 | −0.06 | 0.65 | −0.11 | 0.36 | −0.28 | 0.03 | −0.11 | 0.39 | 0.07 | 0.57 | 0.00 | 0.99 |
| IL‐4 | −0.09 | 0.48 | −0.07 | 0.58 | −0.16 | 0.18 | −0.16 | 0.20 | −0.07 | 0.56 | 0.11 | 0.37 | −0.09 | 0.46 |
| IL‐5 | −0.16 | 0.20 | 0.01 | 0.92 | −0.14 | 0.25 | −0.15 | 0.22 | −0.02 | 0.84 | 0.17 | 0.16 | −0.03 | 0.80 |
| IL‐6 | −0.04 | 0.72 | −0.07 | 0.59 | −0.25 | 0.04 | −0.22 | 0.08 | −0.04 | 0.76 | 0.11 | 0.37 | −0.11 | 0.38 |
| IL‐7 | −0.05 | 0.72 | −0.10 | 0.41 | −0.08 | 0.49 | −0.25 | 0.04 | −0.01 | 0.94 | 0.13 | 0.30 | 0.04 | 0.77 |
| IL‐8 | −0.15 | 0.24 | −0.35 | 0.005* | −0.29 | 0.02 | −0.17 | 0.18 | −0.33 | 0.01* | −0.18 | 0.15 | −0.27 | 0.03 |
| IP‐10 | −0.21 | 0.10 | −0.06 | 0.65 | 0.06 | 0.63 | −0.02 | 0.89 | 0.05 | 0.70 | 0.11 | 0.38 | 0.03 | 0.78 |
| MCP‐1 | −0.16 | 0.21 | −0.25 | 0.05 | −0.02 | 0.89 | −0.30 | 0.01* | −0.20 | 0.10 | −0.08 | 0.49 | −0.08 | 0.53 |
| MIP‐1α | −0.13 | 0.29 | −0.23 | 0.06 | −0.01 | 0.93 | −0.27 | 0.03 | −0.21 | 0.09 | −0.01 | 0.97 | 0.02 | 0.90 |
| MIP‐1β | −0.06 | 0.61 | −0.07 | 0.60 | −0.02 | 0.86 | −0.14 | 0.27 | −0.03 | 0.81 | 0.01 | 0.92 | 0.01 | 0.94 |
| TNF‐α | −0.05 | 0.72 | 0.03 | 0.80 | 0.15 | 0.22 | 0.02 | 0.86 | 0.25 | 0.04 | 0.10 | 0.41 | −0.16 | 0.18 |
| VEGF | −0.14 | 0.26 | −0.21 | 0.09 | −0.20 | 0.10 | −0.32 | 0.01* | −0.18 | 0.14 | −0.04 | 0.78 | −0.07 | 0.58 |
| PDGF‐BB | 0.05 | 0.66 | 0.10 | 0.45 | −0.26 | 0.03 | −0.17 | 0.18 | −0.05 | 0.66 | 0.03 | 0.83 | 0.06 | 0.61 |
| RANTES | 0.02 | 0.90 | 0.06 | 0.65 | −0.17 | 0.16 | −0.16 | 0.21 | −0.01 | 0.95 | 0.03 | 0.81 | 0.05 | 0.69 |
| Symptom scales | ||||||||
|---|---|---|---|---|---|---|---|---|
| Fatigue | Pain | Insomnia | Appetite loss | |||||
| r | p | r | p | r | p | r | p | |
| FGF2 | 0.06 | 0.64 | 0.01 | 0.91 | 0.04 | 0.75 | 0.01 | 0.93 |
| EOTAXIN | 0.17 | 0.17 | 0.21 | 0.09 | 0.08 | 0.53 | 0.26 | 0.03 |
| G‐CSG | 0.07 | 0.60 | −0.03 | 0.83 | −0.00 | 0.98 | −0.00 | 0.99 |
| GM‐CSF | 0.01 | 0.94 | −0.05 | 0.70 | −0.04 | 0.72 | 0.10 | 0.42 |
| IFN‐γ | 0.22 | 0.08 | 0.15 | 0.24 | −0.05 | 0.70 | 0.10 | 0.42 |
| IL‐10 | −0.17 | 0.16 | −0.31 | 0.01* | −0.11 | 0.36 | −0.10 | 0.42 |
| IL‐12p70 | −0.00 | 0.98 | −0.01 | 0.91 | −0.12 | 0.34 | 0.07 | 0.58 |
| IL‐15 | 0.15 | 0.23 | 0.12 | 0.33 | 0.05 | 0.66 | 0.09 | 0.48 |
| sCD40L | −0.07 | 0.55 | 0.03 | 0.84 | −0.18 | 0.13 | 0.13 | 0.30 |
| IL‐17 | 0.01 | 0.96 | −0.08 | 0.54 | −0.04 | 0.73 | 0.02 | 0.85 |
| IL‐1RA | 0.09 | 0.48 | 0.10 | 0.44 | −0.06 | 0.64 | 0.08 | 0.52 |
| IL‐1β | 0.07 | 0.57 | 0.05 | 0.66 | 0.01 | 0.92 | 0.05 | 0.68 |
| IL‐2 | 0.08 | 0.52 | 0.08 | 0.51 | −0.07 | 0.58 | 0.04 | 0.73 |
| IL‐4 | −0.00 | 0.99 | 0.02 | 0.88 | 0.06 | 0.61 | 0.03 | 0.80 |
| IL‐5 | 0.01 | 0.93 | 0.03 | 0.80 | −0.08 | 0.52 | 0.05 | 0.70 |
| IL‐6 | 0.09 | 0.49 | 0.17 | 0.16 | −0.04 | 0.76 | 0.00 | 0.99 |
| IL‐7 | 0.06 | 0.64 | 0.04 | 0.74 | −0.07 | 0.58 | 0.13 | 0.30 |
| IL‐8 | 0.28 | 0.02 | 0.32 | 0.01* | 0.18 | 0.15 | 0.22 | 0.08 |
| IP‐10 | 0.15 | 0.23 | −0.02 | 0.86 | −0.12 | 0.32 | 0.03 | 0.80 |
| MCP‐1 | 0.19 | 0.13 | 0.23 | 0.06 | −0.05 | 0.66 | 0.23 | 0.06 |
| MIP‐1α | 0.18 | 0.15 | 0.14 | 0.26 | −0.02 | 0.86 | 0.12 | 0.34 |
| MIP‐1β | 0.03 | 0.83 | 0.03 | 0.80 | −0.04 | 0.76 | 0.00 | 0.97 |
| TNF‐α | −0.09 | 0.47 | −0.16 | 0.19 | −0.05 | 0.66 | −0.01 | 0.91 |
| VEGF | 0.16 | 0.20 | 0.09 | 0.48 | 0.04 | 0.73 | 0.20 | 0.10 |
| PDGF | 0.03 | 0.79 | 0.15 | 0.23 | −0.04 | 0.73 | 0.20 | 0.10 |
| RANTES | 0.01 | 0.96 | 0.07 | 0.56 | −0.04 | 0.73 | 0.10 | 0.41 |
Note: r indicates the linear correlation coefficient. The colour highlights the significant findings.
Abbreviations: AP, appetite loss; CF, cognitive functioning; EF, emotional functioning; FA, fatigue; GHS, global health scale; PA, pain; PF, physical functioning; RF, role functioning; SL, Insomnia; SF, social functioning; SS, summary score.
Statistically significant at ≤0.01.
TABLE A2.
Baseline participant characteristics (n = 73).
| n (%) | n (%) | ||||
|---|---|---|---|---|---|
| Sex | Male | 39 (53.42) | Treatment arm | HAART | 36 (49.32) |
| Female | 34 (46.58) | COMBI | 37 (50.68) | ||
| Race | Black | 71 (97.26) | TIS Status | T0 | 6 (8.22) |
| White | 1 (1.37) | T1 | 67 (91.78) | ||
| Mixed Race | 1 (1.37) | I0 | 34 (46.58) | ||
| I1 | 39 (53.42) | ||||
| Locale | Urban | 48 (65.75) | S0 | 45 (61.64) | |
| Rural | 25 (34.25) | S1 | 28 (38.36) | ||
| Educational Status | Primary | 16 (21.92) | ACTG Staging | Good risk | 5 (6.85) |
| Secondary | 45 (61.64) | Poor risk | 68 (93.15) | ||
| Tertiary | 9 (12.33) | ||||
| Unknown | 3 (4.11) | Visceral disease | Yes | 37 (50.68) | |
| No | 36 (49.32) | ||||
| Employment Status | Employed | 25 (34.25) | Age | 33 (28–39) years | |
| Unemployed | 44 (60.27) | ||||
| Other | 4 (5.48) |
Note: HAART: stavudine, lamivudine and nevirapine (Triomune®).
COMBI: HAART plus doxorubicin (20 mg/m3), bleomycin (10 U/m2), and vincristine (1.4 mg/m2). Oral etoposide (50–100 mg) was used as an alternative therapy.
Cancer Staging: TIS.
T0: Localized tumour, T1: Oedema or ulceration, extensive oral mucosa KS, or visceral KS.
I0: CD4 ≥ 150 cells/μLI1, I1: CD4 < 150 cells/μL.
S0: No opportunistic infection, S1: History of opportunistic infections or thrush, “B” symptoms present, Karnofsky <70%, other HIV related disease.
ACTG: AIDS Clinical Trials Group. ACTG poor risk = at least one T, I or S risk factor.
Shaik F, Uldrick TS, Mazinu M, Gwebushe N, Mosam A. Cytokine biomarkers and their relationship to symptoms and quality of life in people with HIV‐associated Kaposi sarcoma. HIV Med. 2025;26(12):1983‐1993. doi: 10.1111/hiv.70107
The content of any publications from any studies during this degree is solely the responsibility of the authors and does not necessarily represent the official views of the South African Medical Research Council.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.