Tyrosine Kinase Inhibitors Play an Antiviral Action in Patients Affected by Chronic Myeloid Leukemia: A Possible Model Supporting Their Use in the Fight Against SARS-CoV-2
Abstract
SARS-CoV-2 is the viral agent responsible for the pandemic that in the first months of 2020 caused about 400,000 deaths. Among compounds proposed to fight the SARS-CoV-2-related disease (COVID-19), tyrosine kinase inhibitors (TKIs), already effective in Philadelphia-positive acute lymphoblastic leukemia (Ph+ ALL) and chronic myeloid leukemia (CML), have been proposed on the basis of their antiviral action already demonstrated against SARS-CoV-1. Very few cases of COVID-19 have been reported in Ph+ ALL and in CML Italian cohorts; authors suggested that this low rate of infections might depend on the use of TKIs, but the biological causes of this phenomenon remain unknown. In this study, the CML model was used to test if TKIs would sustain or not the viral replication and if they could damage patient immunity. Firstly, the infection and replication rate of torquetenovirus (TTV), whose load is inversely proportional to the host immunological control, have been measured in CML patients receiving nilotinib. A very low percentage of subjects were infected at baseline, and TTV did not replicate or at least showed a low replication rate during the follow-up, with a mean load comparable to the measured one in healthy subjects. Then, after gene expression profiling experiments, we found that several “antiviral” genes, such as CD28 and IFN gamma, were upregulated, while genes with “proviral” action, such as ARG-1, CEACAM1, and FUT4, were less expressed during treatment with imatinib, thus demonstrating that TKIs are not detrimental from the immunological point of view. To sum up, our data could offer some biological explanations to the low COVID-19 occurrence in Ph+ ALL and CML patients and sustain the use of TKIs in COVID-19, as already proposed by several international ongoing studies.
Patients
Nilotinib Cohort
TTV load was measured by quantitative real-time PCR in 60 peripheral blood samples from 10 CML patients in the chronic phase receiving nilotinib as a first-line therapy. The clinical features and outcomes of these subjects are reported in Table 1. In particular, six patients were male and four female; their median age was 46 years; the Sokal risk score was high in three cases, intermediate in six, and low in one. All except one achieved an early molecular response (BCR-ABL1/ABL1 ratio ≤ 10% IS after 3 months of treatment), and 9/10 achieved MR3 (BCR-ABL1/ABL1 ratio ≤ 0.1% IS) at 12 months.
Table 1
Feature | Number (%) |
---|---|
Total patients number (nilotinib) | 10 |
Sex | |
Male | 6 (60%) |
Female | 4 (40%) |
Age, median (range) | 46 (27–63) |
Sokal Risk | |
Low | 3 (30%) |
Intermediate | 6 (60%) |
High | 1 (10%) |
EMR (BCR-ABL1/ABL1 ≤ 10% at 3 months) | 9 (90%) |
CCyR (no Philadelphia) at 6 months | 9 (90%) |
MR3 at 12 months (BCR-ABL1/ABL1 ≤ 0.1%) | 9 (90%) |
Imatinib Cohort
A possible deregulation of 770 mRNAs caused by imatinib was measured by NanoString technology in peripheral blood samples of five CML patients in the chronic phase after 6 months of 400 mg/day of this TKI with respect to the diagnosis. Clinical features and outcomes of these subjects are reported in Table 2. In particular, three patients were male and two female; their median age was 55 years; the Sokal risk score was high in one case, intermediate in three, and low in another one. In this cohort, two patients were resistant to imatinib, while the other three became optimal responders, according to the ELN 2013 guidelines (26). Before participating in the study, all patients signed an informed consent approved by the Ethical Committee of the AOUP where they declared to donate leftover samples used for diagnostics for further scientific non-profit purposes.
Table 2
Feature | Number (%) |
---|---|
Total patients number (imatinib) | 5 |
Sex | |
Male | 3 (60%) |
Female | 2 (40%) |
Age, median (range) | 55 (55–72) |
Sokal Risk | |
Low | 1 (20%) |
Intermediate | 3 (60%) |
High | 1 (20%) |
EMR (BCR-ABL1/ABL1 ≤ 10% at 3 months) | 3 (60%) |
CCyR (no Philadelphia) at 6 months | 3 (60%) |
MR3 at 12 months (BCR-ABL1/ABL1 ≤ 0.1%) | 3 (60%) |
Nilotinib Cohort
TTV load was measured by quantitative real-time PCR in 60 peripheral blood samples from 10 CML patients in the chronic phase receiving nilotinib as a first-line therapy. The clinical features and outcomes of these subjects are reported in Table 1. In particular, six patients were male and four female; their median age was 46 years; the Sokal risk score was high in three cases, intermediate in six, and low in one. All except one achieved an early molecular response (BCR-ABL1/ABL1 ratio ≤ 10% IS after 3 months of treatment), and 9/10 achieved MR3 (BCR-ABL1/ABL1 ratio ≤ 0.1% IS) at 12 months.
Table 1
Feature | Number (%) |
---|---|
Total patients number (nilotinib) | 10 |
Sex | |
Male | 6 (60%) |
Female | 4 (40%) |
Age, median (range) | 46 (27–63) |
Sokal Risk | |
Low | 3 (30%) |
Intermediate | 6 (60%) |
High | 1 (10%) |
EMR (BCR-ABL1/ABL1 ≤ 10% at 3 months) | 9 (90%) |
CCyR (no Philadelphia) at 6 months | 9 (90%) |
MR3 at 12 months (BCR-ABL1/ABL1 ≤ 0.1%) | 9 (90%) |
Imatinib Cohort
A possible deregulation of 770 mRNAs caused by imatinib was measured by NanoString technology in peripheral blood samples of five CML patients in the chronic phase after 6 months of 400 mg/day of this TKI with respect to the diagnosis. Clinical features and outcomes of these subjects are reported in Table 2. In particular, three patients were male and two female; their median age was 55 years; the Sokal risk score was high in one case, intermediate in three, and low in another one. In this cohort, two patients were resistant to imatinib, while the other three became optimal responders, according to the ELN 2013 guidelines (26). Before participating in the study, all patients signed an informed consent approved by the Ethical Committee of the AOUP where they declared to donate leftover samples used for diagnostics for further scientific non-profit purposes.
Table 2
Feature | Number (%) |
---|---|
Total patients number (imatinib) | 5 |
Sex | |
Male | 3 (60%) |
Female | 2 (40%) |
Age, median (range) | 55 (55–72) |
Sokal Risk | |
Low | 1 (20%) |
Intermediate | 3 (60%) |
High | 1 (20%) |
EMR (BCR-ABL1/ABL1 ≤ 10% at 3 months) | 3 (60%) |
CCyR (no Philadelphia) at 6 months | 3 (60%) |
MR3 at 12 months (BCR-ABL1/ABL1 ≤ 0.1%) | 3 (60%) |
Methods
TTV Load Measure
Viral DNA was extracted from 200 μl whole peripheral blood anticoagulated with EDTA using QIAamp DNA minikit (Qiagen, Chatsworth, CA, USA) and stored at −20°C. Presence and load of TTV genome were determined by single-step quantitative real-time PCR, as described elsewhere (27). The method showed high sensitivity, being able to identify as positive samples those containing ≥10 viral genomes per milliliter; the specificity had been previously demonstrated, since this technique does not detect other human anelloviruses.
BCR-ABL1/ABL1 Ratio IS Detection
The BCR-ABL1/ABL1 ratio was measured by quantitative PCR on the concomitantly harvested peripheral blood, according to the standardized operative procedures of the Italian cooperative group GIMEMA LabNet (www.gimema.it/labnet-cml/). A minimum of 20,000 ABL1 copies was necessary for considering a sample as “evaluable”; 32,000 ABL1 copies were necessary for defining MR4.5 or 100,000 ABL1 copies for MR5, according to the ELN guidelines (28).
NanoString Assays
NanoString technology (NanoString, Seattle, USA) has been employed for analyzing the immune transcriptome profile of five CML patients after 6 months of treatment with imatinib in comparison with diagnosis. The “Human nCounter Myeloid Innate Immunity panel” that measures the expression of 770 genes involved in 19 different pathways, fundamental for the innate immune response, has been adopted.
TTV Load Measure
Viral DNA was extracted from 200 μl whole peripheral blood anticoagulated with EDTA using QIAamp DNA minikit (Qiagen, Chatsworth, CA, USA) and stored at −20°C. Presence and load of TTV genome were determined by single-step quantitative real-time PCR, as described elsewhere (27). The method showed high sensitivity, being able to identify as positive samples those containing ≥10 viral genomes per milliliter; the specificity had been previously demonstrated, since this technique does not detect other human anelloviruses.
BCR-ABL1/ABL1 Ratio IS Detection
The BCR-ABL1/ABL1 ratio was measured by quantitative PCR on the concomitantly harvested peripheral blood, according to the standardized operative procedures of the Italian cooperative group GIMEMA LabNet (www.gimema.it/labnet-cml/). A minimum of 20,000 ABL1 copies was necessary for considering a sample as “evaluable”; 32,000 ABL1 copies were necessary for defining MR4.5 or 100,000 ABL1 copies for MR5, according to the ELN guidelines (28).
NanoString Assays
NanoString technology (NanoString, Seattle, USA) has been employed for analyzing the immune transcriptome profile of five CML patients after 6 months of treatment with imatinib in comparison with diagnosis. The “Human nCounter Myeloid Innate Immunity panel” that measures the expression of 770 genes involved in 19 different pathways, fundamental for the innate immune response, has been adopted.
Statistical Analysis
Results from the NanoString were analyzed by the nCounter Advanced Analysis 2.0 software that allows us to identify genes significantly upregulated or downregulated, design volcano plots, and perform principal component analysis. For the remaining data, SPSS software version 22 (IBM, Bologna, Italy) was used. Viral load variable was used after transformation of TTV load in log format. Fisher's exact test has been applied to the contingency tables. Differences between distributions were calculated by a non-parametric Mann–Whitney U test. The association among variables was evaluated by the Kruskal–Wallis test. Correlations between variables were assessed using the Spearman r correlation coefficient and Student's t-test. Regression analyses were conducted to evaluate the association between the dependent variable TTV viremia and BCR-ABL1/ABL1 ratio. All p-values presented are based on two-tailed tests, and p ≤ 0.05 was considered as statistically significant.
TTV Infection and Replication Rates in CML Patients
TTV load was measured by quantitative real-time PCR in 60 peripheral blood samples from 10 CML patients in the chronic phase receiving nilotinib 600 mg/day as a first-line therapy. At diagnosis, only two patients showed detectable TTV genome; both TTV-positive patients were male, aged 40 and 53 years; no correlation with any of their clinical features and TTV presence was found. Because a correlation between age and sex with TTV replication has been previously reported in healthy subjects (29), we tested if this observation would be reproducible also in our series. Even if our cohort was very small, no correlation between age or sex and TTV infection rate was found.
Then, we analyzed the TTV load at different time points in order to test if in the TTV-negative cases, the virus started to replicate during treatment with nilotinib and if and how TTV load eventually would change during follow-up. Eleven patients were tested after 3, 6, and 9 months; 9 cases were also tested at 12 months, 15 at 18 months, and 3 patients also after 21 months of therapy.
Overall, during follow-up, 41 samples (68%) were TTV negative, while 19 (32%) presented a TTV quantifiable load. The mean TTV load in positive cases was 2.8 log copies per milliliter (95% confidence interval: 2.5–3.1 log copies per milliliter). It is worth remembering that in different series of immunocompromised patients, the mean TTV load was 4.1 log copies per milliliter (95% confidence interval: 3.9–4.3 log copies per milliliter) (25, 26, 29–32) and that the mean TTV load in healthy blood donors was 2.3 log copies per milliliter (95% confidence interval: 1.7–2.9 log copies per milliliter) (24).
When TTV load was measured at the last time points of follow-up, 9 of the 10 treated CML patients showed either unchanged or slightly increased values (<0.4 log copies per milliliter of variation) relative to baseline. In particular, in one of the two initially TTV-positive patients, TTV did not replicate already at the first time point (after 3 months of therapy), while in the second case, the mean value of TTV load measured at six different time points was the same as that measured baseline (2.7 log copies per milliliter). In the subgroup of cases who were initially TTV negative, four out of eight remained TTV negative during the whole follow-up; in the other four, TTV load was detectable in half of the occasions, but with a maximum increase value of 0.4 log copies per milliliter. When we analyzed TTV load with respect to molecular response assessed by the BCR-ABL1/ABL1 ratio measured by real-time PCR at the same time point, a statistically significant correlation between genome TTV detection and absence of optimal response was found. Indeed, according to the ELN 2013 classification (28), we counted seven failing time points: in all these occasions, the TTV genome was detectable. On the other hand, we had 53 time points where molecular response was optimal or a warning: in 33 of these occasions, TTV was not detectable (p = 0.02).
In conclusion, this first part of the study showed that nilotinib does not sustain the viral replication, even with a medium-term follow-up.
Deregulation of Immunity-Related Genes in CML Patients
In the second phase of our study, we employed the NanoString technology for analyzing the expression of 770 inflammation- and immunity-related genes in five CML patients before and after 6 months of treatment with imatinib, with the aim of testing the impact of this TKI on the possible immunological control of viral infection.
Overall, 58 genes were deregulated by imatinib, with 18 genes being upregulated and 40 downregulated. We previously reported that some genes involved in several different autoimmune/inflammatory conditions were downregulated by imatinib (25), which might have a positive impact on COVID-19. Interestingly, 20 out of these 58 deregulated genes were strictly correlated with immune or antiviral response, so representing the focus of the present study (see Supplemental File 1 for the original raw data).
Among these 20 genes, 11 appeared upregulated and 9 downregulated during treatment with imatinib (see Table 3). In more detail, we found a reduced expression of Arginase 1 (ARG-1) (44), Complement C3a Receptor 1 (C3AR1) (46), Carcinoembryonic antigen-related cell adhesion molecule-1 (CEACAM1) (45), Gelsolin (GSN) (49), Nectin 1 (50), and Fucosyltransferase 4 (FUT4) (48), all genes that usually play a “proviral” role. Indeed, ARG-1 displays a negative effect on immunity in several contexts, including hematological neoplasms: by depleting the microenvironment of arginine, which is essential for T-lymphocyte function, arginase makes them anergic. In CML, ARG-1 has been shown to be highly expressed at diagnosis, when myeloid-derived suppressor cells are very active against T-cell activity (53). CEACAM1 is an important regulator of virus-specific CD8+ T-cell functions. In an in vitro model, treatment with anti-CEACAM1 antibody prevented CD8+ T-cell exhaustion, thus improving the control of viral infections (54). FUT4 is a gene strictly involved in the PD1 axis, whose overexpression has been associated with a shorter survival in lung adenocarcinoma (48). Consequently, FUT4 downregulation could contribute to the inhibition of the PD1–PDL1 axis, with consequent recovery of the immune disease control.
Table 3
GENE ID | Function | Final effect | References |
---|---|---|---|
CCL5 | Activates NK | Anti-infective | (33) |
CCR5 | Activates NK | Anti-infective | (34) |
CD28 | Low in severe COVID-19 | Anti-infective | (35) |
CD74 | Blocks macrophage activation | Pro-infective | (36) |
CX3CR1 | High in antifungal resp | Anti-infective | (37) |
CXCL16 | High in antiviral resp | Anti-infective | (38) |
CXCR3 | High in T effector | Anti-infective | (39) |
HAVCR2 | NK mature marker | Anti-infective | (40) |
IFNG | Antiviral | Anti-infective | (41) |
NFATC2 | Increases T cells | Anti-infective | (42) |
TLR3 | Antiviral | Anti-infective | (43) |
ARG1 | Immunosuppressive | Pro immune | (44) |
CEACAM1 | Inhibits T lynf | Pro-infective | (45) |
C3AR1 | Neutrophil chemotaxis antagonist | Anti-infective | (46) |
COL17A1 | Induces IL7 that sustains T and B lynf | Anti-inflammation | (47) |
FUT4 | Increases bacterial infections | Anti-infective | (48) |
GSN | Increases NK apoptosis | Anti-infective | (49) |
NECTIN1 | High in chlamydial infection | Anti-infective | (50) |
RNASE2 | Antiviral | Pro-infective | (51) |
RNASE3 | Antiviral | Pro-infective | (52) |
For each gene, the respective functions and the final effect after deregulation done by this TKI are indicated. In violet are the effects that could sustain a possible virus replication.
On the other hand, imatinib upregulated some genes that could finally exert an “antiviral” action by sustaining the host immunological control of the viral attack, such as CD28 (35), Interferon gamma (IFN gamma) (41), C-C Motif Chemokine Ligand 5 (CCL5) (33), C-C chemokine receptor type 5 (CCR5) (34), and Toll-like receptor 3 (TLR3) (43). Particularly interesting is CD28, a co-stimulatory molecule also used for CAR-T production (55). CD28 is located immediately downstream of PD1, thus participating in the PD1-derived T-cell suppression (56). The role of CD28 in COVID-19 has been recently investigated: its expression on CD8+ T cells seems to be lower in patients with severe relative to those with mild COVID-19 (57); consequently, its overexpression induced by imatinib might be not detrimental. CCL5 is another interesting chemokine with antiviral action: indeed, in a murine model, CCL5-overexpressing NK cells were hyperactivated and made animals resistant to the viral infection (33). The pro-immune action of IFN gamma is well-known (41); in CML, interferon has a long history of successes, and it seems to be able to delete ABL1 mutations when added to TKIs, hence making patients sensitive again to treatment (58). Finally, also, the increased expression of TLR3 might be positively translated into the COVID-19 context: indeed, it has been previously reported that its overexpression protects neutropenic mice from meningoencephalitis (59).
In conclusion, even if performed on a small series of cases, results from our experiments might support the idea that imatinib could sustain the immunological control of infected subjects (Figure 1). These findings, translated in the coronavirus scenario, could help to explain why very few patients affected by Ph+ ALL and CML developed COVID-19 symptoms.
Acknowledgments
We thank all our CML patients, our nurse C. Baroni for her daily precious help, and our English lecturer I. Di Vita.
Footnotes
Funding. This work was supported by the University of Pisa, Italy, with the PRA 2018 grant, MP.
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