|Year : 2022 | Volume
| Issue : 2 | Page : 74-80
Study of serum cytokines (interleukin-6 and tumor necrosis factor-alpha) in acute leukemias
Divita Saxena1, Leelavathi Dawson1, Rani Gera2
1 Department of Pathology, VMMC and Safdarjung Hospital, New Delhi, India
2 Department of Paediatrics, VMMC and Safdarjung Hospital, New Delhi, India
|Date of Submission||18-Oct-2021|
|Date of Decision||29-Jan-2022|
|Date of Acceptance||31-Jan-2022|
|Date of Web Publication||28-Feb-2022|
Dr. Divita Saxena
Department of Pathology, VMMC and Safdarjung Hospital, New Delhi
Source of Support: None, Conflict of Interest: None
Objectives: The objectives of this study were to assess the cutoff levels of interleukin (IL)-6 and tumor necrosis factor-alpha (TNF-alpha) for predicting acute leukemia with special attention to their correlation with blast counts in leukemia subtypes of acute lymphoblastic leukemia (ALL), acute myeloid leukemia, and mixed phenotypic acute leukemia. Methods: This observational cross-sectional case–control study was done from September 2018 to March 2020. A total of 35 newly diagnosed patients of acute leukemia were taken as cases and compared with 140 healthy controls. Complete phenotyping and blood film analysis was done for the cases. The serum levels of IL-6 and TNF-alpha levels were assessed and compared among cases and controls. The levels of IL-6 and TNF-alpha were correlated with blast counts of subtypes of acute leukemia. P < 0.05 was considered statistically significant. Results: Compared to controls, acute leukemia cases had significantly higher levels of IL-6 median interquartile range value (12.39 [8.056–136.894] vs. 8.27 [6.477–10.849]) and TNF-alpha (192.48 ± 633.01 vs. [20.63 ± 8.17]) with P < 0.05. TNF-alpha was found to be the better predictor of acute leukemias at cutoff of >24.906 with sensitivity of 71.43% as compared to IL-6 (Sn of 48.57%). Only TNF-alpha had a significant correlation with absolute blast count in ALL cases (r = 0.579, P = 0.0118). Conclusion: It can be concluded that an aberrant increased production of the pro-inflammatory cytokines IL-6 and TNF-alpha is shown in the acute leukemia patients as compared to the healthy controls. TNF-alpha is a better marker among both the cytokines for predicting acute leukemia with significant correlation with blast counts in ALL.
Keywords: Acute leukemias, cytokines, interleukin-6, tumor necrosis factor-alpha
|How to cite this article:|
Saxena D, Dawson L, Gera R. Study of serum cytokines (interleukin-6 and tumor necrosis factor-alpha) in acute leukemias. J Radiat Cancer Res 2022;13:74-80
|How to cite this URL:|
Saxena D, Dawson L, Gera R. Study of serum cytokines (interleukin-6 and tumor necrosis factor-alpha) in acute leukemias. J Radiat Cancer Res [serial online] 2022 [cited 2022 Aug 17];13:74-80. Available from: https://www.journalrcr.org/text.asp?2022/13/2/74/338799
| Introduction|| |
Acute leukemias are a heterogeneous group of malignancies with varying clinical, morphological, immunogenic, and molecular characterization. The age-adjusted acute myeloid leukemia (AML) incidence in the United States is 4.3 per 100,000 per annum. An increase in the incidence is observed with age, and the median age at diagnosis was 68 years in the US. Within the United States, the incidence of acute lymphoblastic leukemia (ALL) is estimated at 1.6 per 100 000 population.
The unrestricted growth and maturation arrest of hematopoietic precursor cells in leukemias have been found with a potential mechanism of abnormal cytokine production or abnormal cytokine receptor expression.
Previous studies have suggested that pro-inflammatory mediators such as interleukin (IL)-1 β, tumor necrosis factor-alpha (TNF-alpha), and IL-6 tend to increase AML aggressiveness, and anti-inflammatory mediators such as transforming growth factor-β and IL-10 appear to impede AML progression. Dysregulation of the complex interactions between pro- and anti-inflammatory cytokines in leukemia creates a pro-tumorigenic microenvironment and affects leukemic cell proliferation and survival.,
Among the plethora of cytokines which regulate leukemogenesis, TNF-alpha and IL-6 are two of the most common pro-inflammatory cytokines being studied.
IL-6 is a dominant prognostic factor in chronic lymphocytic leukemia, large cell lymphoma, and aids in the development of AML blast cell, in addition to inspiration and maintenance of their progression throughout the IL-6/IL-6 receptor signaling arrangement. IL-6 plays an important role in the angiogenesis, migration, and cancer development, and its role during carcinogenesis is very vital. In many cancer types, IL-6 does not perform a role in cancer defense; on the contrary, it is concerned in cancer development.
TNF-α plays a significant role in promoting the development and progression of malignant disease. TNF-α is involved in all steps of leukemogenesis, including cellular transformation, proliferation, angiogenesis, as well as extramedullary infiltration. TNF-α is also an important factor in the tumor microenvironment and helps leukemia cells in immune evasion, survival, and resistance to chemotherapy. TNF-α can be a potent target for leukemia therapy.
Among the plethora of cytokines and inflammatory markers, IL-6 and TNF-α are the most common employed markers in the practice of medicine. Their application has increased further in the times of pandemic of COVID-19. The present study holds utility in this regard since it determines the cutoff values of these two markers among the patients with leukemia in comparison to the healthy population which may help in defining their levels in relation to leukemia with differentiation from the inflammatory diseases.
We did this study to assess the cutoff levels of IL-6 and TNF-alpha for predicting acute leukemia with special attention to their correlation with blast counts in leukemia subtypes of ALL, AML, and mixed phenotypic acute leukemia (MPAL).
| Methods|| |
This observational cross-sectional case–control comparative study was conducted in the Department of Pathology and Department of Paediatrics from September 2018 to March 2020 in Safdarjung Hospital, New Delhi. The ethical clearance was taken from the Institutional Ethical Committee before conducting the study. Newly diagnosed cases of acute leukemias in whom therapy was not yet initiated were consecutively selected for the study and were compared against the healthy normal donors from the blood bank. Any patients with acute leukemias who were already on therapy, patients with lymphoma spill, chronic leukemias in blast crisis, and cases of relapse were excluded from the study.
Sample size calculation
The sample size was calculated using OpenEpi software. For confidence interval (CI) 95% and power of 80%, sample size was calculated using the following mean and standard deviation (SD).
Group 1 (cases) – 35.30 mean and SD – 0.75.
Group 2 (controls) – 28.60 mean and SD – 0.6.
Ratio of sample size in Group 2: Group 1, i.e., control: Case was taken as 4 and the minimum sample size that was arrived at was cases = 1 and control = 4.
However, as per statistics in our pathology department, approximately 2–3 cases of acute leukemias were being received per month. Based on this, the study included 35 cases of acute leukemia and compared against 140 healthy controls.
Data collection methods and protocols
All the newly diagnosed acute leukemia cases were included in the study. Relevant data about the demography, diagnosis of leukemia subtype (lymphoid, myeloid, mixed lineage), and myeloperoxidase (MPO)/periodic acid–Schiff's (PAS) cytochemistry results were collected through a predesigned study pro forma. Consent was obtained from all patients who were included in the study after explaining them in detail about the study. IL-6 and TNF-alpha levels were assessed and recorded for all the leukemia cases. No treatment modifications were done during the study.
Sample collection and processing
Under strict aseptic conditions, 2-ml blood sample was taken in ethylenediaminetetraacetic acid (EDTA) vacutainer and plain vacutainer (red cap) from the cases of acute leukemia. From the healthy controls, only 2-ml blood sample in plain vacutainer was taken. From EDTA blood sample, peripheral blood film was made and stained with Giemsa stain to know the morphology and blast count. Cytochemistry using MPO and PAS was done.
Diagnosis of leukemia subtype was made based on flow cytometry. The machine used was Cytomics FC 500 with 488 nm blue laser/AYO4213, Company Beckman Coulter (United States).
The panel of flow cytometry comprised Beckman Coulter Flow Cytometer FC 500 antibodies (United States).
- Myeloid lineage markers – cyMPO, CD33, CD16, and CD13
- Monocytic lineage markers – CD64, CD14, and CD11c
- B-cell markers – CD10, CD19, CD20, and cyCD79a
- T-cell markers – cyCD3, CD5, and CD7
- Immature lineage markers – CD34, CD38, CD117, and HLADR
- Aberrant markers – CD123, CD56, CD15, and CD45.
The specific markers based on the morphology of the leukemia smears were used for the individual cases, and the final diagnosis was made. The cutoffs for flow cytometry markers and positivity were taken from Chiaretti et al.
From the second sample in the plain vacutainer, IL-6 and TNF-alpha was measured in cases as well as controls by ELISA technique and ELISA microplate reader.
Determination of circulating tumor necrosis factor-alpha levels
Blood sample collected in the plain tubes were centrifuged for around 10 min at ×1500 g which was followed by serum extraction. TNF-α levels were estimated by using a human “ELISA kit (Diaclone, Besancon Cedex, France) in accordance with the manufacturer's protocol.”
Determination of circulating levels of interleukin-6
IL-6 levels were determined from the serum samples extracted by centrifuging the blood collected in the plain vial at ×1500 g for 10 min by using a commercially available human IL-16 ELISA kit from Krishgen Biosystems (United Kingdom) following manufacturer's instructions.
Categorical variables were presented in number and percentage (%) and continuous variables were presented as mean ± SD and median. Normality of data was tested by Kolmogorov–Smirnov test. If the normality was rejected, then nonparametric test was used. The data were entered in MS EXCEL spreadsheet, and analysis was done using the Statistical Package for the Social Sciences (SPSS) version 21.0, IBM manufacturer, Chicago, Illinois, USA. P < 0.05 was considered statistically significant.
Quantitative variables were compared using Mann–Whitney test (as the data sets were not normally distributed) between the two groups, and Kruskal–Wallis test was used for comparison between three groups. Receiver operating characteristic (ROC) curve were used to find out the cutoff point of IL-6 levels and TNF-α levels for predicting leukemia cases. Spearman rank correlation coefficient was used to find out the correlation of absolute blast count with IL-6 levels and TNF-α levels and between IL-6 levels and TNF-α levels.
| Results|| |
Demographic and clinical characteristics of the study population
In the present study, majority 13 (37.14%) of patients belonged to age group <=10 years. There were 23 (65.71%) males and 12 (34.29%) females. The mean value of age in years of study subjects was 19.66 ± 15.2 years with median interquartile range (IQR) of 16 (8.25–30.5). The mean hemoglobin was 7.53 ± 2.08 g/dL with a mean total leucocyte count (TLC) of 96711.43 cells/cumm. A mean blast % of 83.66 ± 11.13 (mean blast count 84027.66 cells/cumm) was observed with median granulocyte, lymphocyte, and monocyte % of 8, 6, and 0, respectively [Table 1].
|Table 1: Distribution of sociodemographic characteristics of study subjects|
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The most common signs and symptoms of leukemia observed among patients were fever in 97% of the patients followed by splenomegaly in 60%, hepatosplenomegaly in 54% of patients, and other symptoms such as generalized weakness (46%), epistaxis (14%), generalized body aches (14%), abdominal pain/distention (17%), headache (3%), lymphadenopathy (37%), pallor, rashes, melena, vomiting, chest pain, and shortness of breath, as shown [Supplementary Figure 1].
PAS was positive for 14 out of 18 cases of ALL which were pre-B-ALL. MPO positivity was seen in all cases of AML. MPAL was negative for both MPO and PAS. On flow cytometry, ALL was positive for CD19, HLADR, cyCD79a, cyCD3, CD10, and CD7. AML was positive for MPO, CD13, CD14, CD11c, CD117, CD64, and CD33. MPAL was positive for MPO, CD3, CD19, cyCD79a, CD10, and CD7.
Interleukin-6 and tumor necrosis factor-alpha
As compared to controls, the cases had significantly higher median levels of IL-6 (12.39 vs. 8.27, P = 0.0002) and TNF-α levels (35.91 vs. 20.19, P < 0.0001), as shown in [Table 2].
|Table 2: Comparison of interleukin-6 levels (pg/mL) and tumor necrosis factor-alpha levels (pg/mL) between cases and controls|
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Among subtypes of leukemia, median (IQR) of IL-6 levels (pg/mL) in ALL was 11.6 (9.601–19.028), AML was 83.32 (7.884–213.569), and mixed lineage was 7.84 (4.685–16.476) with no significant difference between them. Similarly, median (IQR) of TNF-α levels (pg/mL) in ALL was 29.76 (23.617–66.204), AML was 32.07 (23.319–65.821), and mixed lineage was 57.61 (37.986–75.96) with no significant difference between them [Table 3].
|Table 3: Comparison of interleukin-6 levels (pg/mL) and tumor necrosis factor-alpha levels (pg/mL) between subtypes of leukemia|
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Cutoff values for predicting acute leukemia
On ROC, both the parameters had significant discriminatory power to predict leukemia cases. Discriminatory power of TNF-α levels (pg/mL) (area under the curve [AUC]: 0.838; 95% CI: 0.775–0.889) was excellent and discriminatory power of IL-6 levels (pg/mL) (AUC: 0.704; 95% CI: 0.630–0.770) was acceptable. Among both the parameters, TNF-α level (pg/mL) was the best predictor of leukemia cases at cutoff point of >24.906 with 83.80% chances of correctly predicting leukemia cases [Table 4] and [Supplementary Figure 2.1] and [Supplementary Figure 2.2].
|Table 4: Receiver operating characteristic curve to find out the cutoff point of interleukin-6 levels and tumor necrosis factor-alpha levels for predicting leukemia cases|
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Correlation of interleukin-6 and tumor necrosis factor-alpha with blast counts
With blast counts, TNF-alpha showed a significant positive correlation in cases of ALL (r = 0.579, P = 0.0118) but a nonsignificant correlation in AML and MPAL cases. On the other hand, IL-6 showed no significant correlation with blast counts in various subtypes of leukemia [Table 5].
|Table 5: Correlation of interleukin-6 levels and tumor necrosis factor-alpha levels with absolute blast count in subtypes of leukemia|
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Overall, there was a nonsignificant moderate negative correlation between IL-6 levels (pg/mL) with TNF-α levels (pg/mL) in ALL cases (r = −0.325, P > 0.05) and mixed lineage (r = −0.8, P > 0.05) and nonsignificant moderate positive correlation (r = 0.301, P > 0.05) in AML cases [Table 6].
|Table 6: Correlation of interleukin-6 levels with tumor necrosis factor-alpha levels in subtypes of leukemia|
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| Discussion|| |
In our study on acute leukemia patients, with mean age of 19.66 ± 15.2 and male: female ratio of 2:1, a significant difference was seen in IL-6 median levels (pg/mL) (12.39 vs. 8.27, P = 0.0002) and TNF-α mean levels (pg/mL) (192.48 vs. 20.63, P < 0.0001) between cases and control population. Our findings were in line with a Chinese study by Luo et al., who determined a similar higher value of IL-6 and TNF-alpha in cases with acute leukemia as compared to control population (P < 0.05).
The more elaborated cytokine profile studies have been done by Sanchez-Correa et al. among 42 newly diagnosed AML patients (27 males, 15 females) with an age range of 21–86 years (median age, 62 ± 16 years). The authors found that in addition to the elevated levels of IL-6 and TNF-alpha, IL-4, IL-5, IL-8, and IL-12p70 levels were also significantly higher in AML patients compared to their age-matched healthy volunteers (P = 0.048, P = 0.002, P = 0.006, and P = 0.018, respectively). In another study, Potapnev et al. evaluated the cytokine levels among 49 childhood B-lineage ALL with age range of 3–17 years and 30 healthy children (age-related control). The mean value of TNF-alpha was significantly higher among the ALL cases as compared to the controls (43.4 ± 8.1 pg/ml vs. 30.7 ± 3 pg/ml, P < 0.05), as was seen in our study.
It must be stressed here that our study is one of the few studies, that included all cases of acute leukemias, comprising 18 (51.43%) ALL cases, 12 (34.29%) AML cases, and 5 other cases of mixed lineage. Most of the other studies have included mainly either only ALL cases,, or only AML cases.,,
Overall, the results indicated that IL-6 and TNF-alpha are increased among the patients with acute leukemia as compared to the healthy controls which may be probably related to the pathogenesis of acute leukemia. On ROC, both the parameters had significant discriminatory power to predict leukemia cases (P < 0.05). Among both the parameters, TNF-α level (pg/mL) was the best predictor of leukemia cases at cutoff point of >24.906 with 83.80% chances of correctly predicting leukemia cases.
TNF and IL-6 are both pro-inflammatory cytokines that act by NF-κB and/or STAT3 and influence leukemic progression. The intricate association between the various cytokines and the bone marrow microenvironment suggests a link between them. It has been suggested that the blast cells produce IL-6 and other cytokines such as colony-stimulating factors (cerebrospinal fluid [CSF]: G-CSF, M-CSF, and GM-CSF), TNF-alpha, and IL-1 to form autonomous colonies. The role of IL-6 is a co-stimulator to enhance CSF-induced clonogenicity of the blast cells. TNF-alpha and IL-1 that are produced from the blast cells may also stimulate the growth of the blast cells by inducing production of CSF in bone marrow stromal cells or in the blast cell population itself.
Thus theoretically, the levels of IL-6 and TNF-alpha must go hand in hand in acute leukemia, however, we found no statistically significant correlation between IL-6 and TNF-alpha. Rather, it was a nonsignificant moderate negative correlation between IL-6 levels (pg/mL) with TNF-α levels (pg/mL) in ALL cases (r = −0.325, P > 0.05) and mixed lineage (r = −0.8, P > 0.05) and nonsignificant moderate positive correlation (r = 0.301, P > 0.05) in AML cases. This can be explained from the mRNA expression analysis of IL-6 and its related genes in AML and acute lymphoid leukemia (ALL) by reverse transcriptase-polymerase chain reaction done by Sugiyama et al. It was noted that IL-6 mRNA expression was common in AML, but rare in ALL, and thus its expression may not go in sync with TNF-alpha. Wu et al. showed that a complex interaction of TNF-a, IL-1b, and IL-17 induces IL-6 production and IL-6 levels correlate positively with Th17 frequencies rather than with TNF-alpha. In addition, as the IL-6 and TNF-alpha correlation findings of our study were statistically not significant, future research in this field is recommended.
On the peripheral smear while estimating TLC, the determination of the blast count holds a significant importance in assessing the progression of the disease. The changes in cytokines levels may play a role in the dynamic leukemic marrow environment. Statistically, we found a significant association of TNF-alpha with the blast counts only in ALL. Like our study, Potapnev et al. found that the level of TNF-alpha positively correlated with blast cell count in peripheral blood of ALL patients (R = + 0.432; P = 0.008). Patients with TNF-alpha level above the median value were characterized by higher white blood cell count (P = 0.025), as compared to those with TNF-alpha level below the median value. Although Potapnev et al. determined a positive correlation of TNF-alpha with the blast counts, no significant association of the level of TNF-alpha was seen with the treatment response at days 8 and 15 or 3-year overall survival. Thus, it can be said that although the elevated plasma level of TNF-alpha can be a useful marker to assess disease activity/progression, the prognostic association needs further research.
Limitations of the study
The study results must be interpreted in view of the small sample size of individual acute leukemia subtype. Second, as the study was observational cross-sectional in design, the treatment follow-up of the patients was not done and thus the prognostication value of IL-6 and TNF-alpha could not be assessed.
| Conclusion|| |
It can be concluded that an aberrant increased production of the pro-inflammatory cytokines IL-6 and TNF-alpha is shown in the acute leukemia patients as compared to the healthy controls. The cutoff levels of TNF-α >24.906 and IL-6 >13.218 can be used with good discriminatory powers to predict cases of acute leukemia. Among the two markers, TNF-alpha was a better predictor of acute leukemia owning 83.8% accuracy, with a significant positive correlation with blast counts in ALL. It can be recommended that these markers can be routinely applied in the medicine and hematology as an adjunct while diagnosing the cases with acute leukemia.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]