Molecular and Phylogenetic Characterization of HTLV‐1 Infection in Patients With Hematological Malignancies in the State of Pará, Northern Brazil

ABSTRACT

Human T‐lymphotropic viruses 1 and 2 (HTLV‐1 and HTLV‐2) were first isolated from patients with hematological malignancies. This study was the first to investigate the frequency of HTLV‐1 and its molecular diversity among patients with hematolymphoid cancers who were treated at a leading reference hospital in Pará, northern Brazil. For this purpose, information from the International Classification of Diseases (ICD), laboratory test records, and peripheral blood samples were obtained. Patients with confirmed diagnosis of leukemia/lymphoma, myeloma, other hematological malignancies, and those under diagnostic investigation were included in the study. Serological screening for anti‐HTLV‐1/2 antibodies was carried out by ELISA, and infection was confirmed by real‐time PCR. PCR‐positive samples were sequenced for phylogenetic analysis. Of 329 people assessed, 47.7% were men (157) and 52.3% were women (172). The overall prevalence of HTLV‐1 was 1.82% (6/329), with 2.5% (n = 4) in men and 1.2% (n = 2) in women. Phylogenetic analysis of the 5′LTR region (715 bp) of HTLV‐1 indicated that the isolates belonged to the Cosmopolitan subtype, Transcontinental subgroup. Positivity among patients with lymphoma was 6.56% (4/61), with one patient diagnosed with Hodgkin lymphoma. Among patients under clinical investigation and with other types of cancer, the prevalence of infection was 1.19% (1/84) and 2.38% (1/42), respectively. A decrease in red blood cell count, hemoglobin, and hematocrit was identified in cancer patients with a negative HTLV diagnosis compared to HTLV‐positive patients. Our results highlight the importance of including HTLV‐1/2 testing in the routine follow‐up of cancer patients, for the sake of existing successful treatment protocols.

1. Introduction

Cancer comprises a heterogeneous group of diseases characterized primarily by uncontrolled cell proliferation, resulting in the formation of a malignancy [1]. Malignant neoplasms represent one of the greatest public health challenges globally and are among the leading causes of morbidity and mortality in children and adults [2].

The etiology of cancer is multifactorial, involving the interaction between genetic, environmental, and infectious factors. Among the environmental agents, exposure to toxic substances, ionizing radiation, and other mutagenic compounds stand out [3]. Among the infectious agents, viruses play an important role in carcinogenesis, being implicated in the induction of various tumors in humans and in experimental models. Among the main recognized human oncoviruses are human papillomavirus (HPV), hepatitis B virus (HBV), hepatitis C virus (HCV), Epstein‐Barr virus (EBV), Kaposi's sarcoma‐associated herpesvirus (KSHV), Merkel cell polyomavirus (MCPyV), and human T‐lymphotropic virus 1 (HTLV‐1) [4].

HTLV was the first human oncogenic retrovirus discovered in the 1980s [5, 6]. In Brazil, infection with the virus is endemic and is heterogeneously distributed among the different regions and states of Brazil, with an estimated 2.5 million people living with this virus [7]. Brazil is considered the country with the highest absolute number of HTLV‐1/2 seropositive individuals in the world [8] and the North and Northeast regions are endemic, with the states of Bahia, Maranhão, and Pará registering the highest prevalence rates in Brazil [8, 9, 10, 11].

HTLV‐1 exhibits tropism for CD4⁺ T lymphocytes and is the causative agent of a neoplasm of CD4⁺ and CD25⁺ T cells, known as adult T‐cell leukemia/lymphoma (ATLL), that is classified according to its pathogenicity into: latent, chronic, acute, and lymphoma [12, 13]. Latent and chronic forms of ATLL are the mildest forms of the disease, while acute and lymphoma are the most aggressive forms of the disease [14, 15].

The oncogenicity of HTLV‐1 is intrinsically related to the viral proteins HBZ and Tax. Tax is a pleiotropic transactivator protein expressed from viral RNA that can trigger the activation of signaling pathways, including the aberrant NF‐κB overstimulation, that drives T cell proliferation, survival, and transformation; and the modulation and interference with the cell cycle, triggering persistent phosphorylation, inducing the transcription of anti‐apoptotic proteins that can lead to cell immortalization and transformation [16, 17]. Tax protein can also alter physiological functions, such as cell proliferation and apoptosis, as well as induce the accumulation of gene alterations that can lead to the development of tumor malignancy [18].

The role of HTLV‐1 in hematological malignancies other than adult T‐cell leukemia/lymphoma (ATLL) remains poorly understood, and its detection outside the context of ATLL is rarely documented, limiting our understanding of the virus's oncogenic potential in other lymphoid subtypes. Research on HTLV‐1 has focused predominantly on ATLL; this, coupled with a lack of routine screening and methodological challenges, has resulted in a significant knowledge gap. In this study, we describe, for the first time, the prevalence and molecular characterization of HTLV‐1 in oncohematological patients treated at a reference center in the northern region of Brazil, highlighting the importance of investigating the infection as part of the routine protocol for monitoring and diagnosing patients with suspected hematological cancer.

2. Materials and Methods

2.1. Study Design

This is a primary, observational, analytical, and cross‐sectional study, conducted both on patients treated at a reference oncology hospital in the State of Pará (Figure 1), and on those referred from other services to the Support Service for People Living with HTLV (SAPEVH). The study population consisted of individuals diagnosed with hematological neoplasms, including Hodgkin's lymphoma, non‐Hodgkin lymphoma, multiple myeloma, and leukemias, as well as patients undergoing diagnostic investigation for hematological cancers. Eligible patients were adults of both sexes who provided biological samples that confirmed HTLV infection. Those diagnosed with other non‐hematolymphoid neoplasms and/or those without biological material available for analysis were excluded.

Figure 1.

Geographic location of the study area. Map of Brazil highlighting the state of Pará, located in the North region of the country, where the reference hospital for oncology and the virology laboratory are located.

2.2. Ethical Aspects

This project was approved by the Research Ethics Committees of the Ophir Loyola Hospital (CAAE: 23160619.1.0000.5550) and the Federal University of Pará (CAAE: 71261523.1.0000.0018) in accordance with Resolution No. 466/12 of the Brazilian Ministry of Health, which regulates research involving human beings.

Access to the clinical‐laboratory database and patient samples from the oncology hospital was made possible through approval from the local research committee, formalized in the Data Use Commitment Agreement (DUCA or TCUD), and by the addendum releasing residual samples from the hospital laboratory, respectively.

2.3. Data Collection and Biological Sample

The information collected from the secondary database included: International Classification of Diseases (ICD) codes; sex; age; and laboratory data from blood counts and biochemical tests: lactate dehydrogenase, Gamma GT, and C‐reactive protein.

Patients attending SAPEVH signed an Informed Consent Form (ICF or TCLE) and answered epidemiological and clinical questionnaires. The data were tabulated in Microsoft Excel for subsequent statistical analysis.

Peripheral venous blood samples were collected in tubes containing EDTA (4 mL). Samples were centrifuged at 4000 rpm (2250g) to separate plasma and cells (erythrocytes and leukocytes). Plasma and leukocytes were aliquoted separately and stored at −20°C until serological and molecular tests were performed at the Virology Laboratory of UFPA.

2.4. Serological Screening

Serological screening for anti‐HTLV‐1/2 antibodies (anti‐gp46 and anti‐gp21) was performed in plasma, using an enzyme‐linked immunosorbent assay (ELISA) method (Murex HTLV I + II Elisa, Diasorin, Dietzenbach, Germany), according to the manufacturer's protocol.

2.5. Genomic DNA Extraction

Serological reactive samples were confirmed by Real‐Time Polymerase Chain Reaction (qPCR). Total genomic DNA was extracted from 200 μL of leukocytes using the QIAamp DNA Mini Kit (Qiagen, Germany), following the manufacturer's protocol. After extraction, DNA samples were quantified using the BioDrop µLite+ Microvolume Spectrophotometer (Harvard Bioscience Inc.), following the manufacturer's recommended protocol.

2.6. Molecular Procedures

qPCR was performed using the TaqMan Universal Master Mix system (Applied Biosystems, Foster City, CA, USA) with three target sequences: the albumin gene (141 bp) as an endogenous control, the HTLV‐1 pol gene (108 bp), and the HTLV‐2 pol gene (91 bp) for confirmation and molecular differentiation of HTLV‐1/2. Each reaction contained 12.5 μL of TaqMan Universal PCR Master Mix (2X) (Applied Biosystems, Foster City, USA), 6.0 μL of ultrapure water, 0.5 μL of each primer, 0.5 μL of each probe, and 5.0 μL of DNA, resulting in a total volume of 25 μL. The following temperature cycles were used: 95°C for 10 min, followed by 45 cycles of 95°C for 15 s and 60°C for 1 min for primer and probe binding.

The primer sequences used were: 5′‐GAACGCTCTAATGGCATTCTTAAAACC‐3′ (HTLV−1F); 5′‐GTGGTTGATTGTCCATAGGGCTAT‐3′ (HTLV−1R), 5′‐CAACCCCACCAGCTCAGG‐3′ (HTLV−2F); 5′‐GGGAAGGTTAGGACAGTCTAGTAGATA‐3′ (HTLV−2R); 5′‐GCTCAACTCCCTATTGCTATCACA‐3′ (Albumin F); 5′‐GGGCATGACAGGTTTTGCAATATTA‐3′ (Albumin R). The probe sequences used were: FAM‐5′‐ACAAACCCGACCTACCC‐3′‐NFQ (HTLV‐1); FAM‐5′‐TCGAGAGAACCAATGGTATAAT‐3′‐NFQ (HTLV‐2); FAM‐5′‐TTGTGGGCTGTAATCAT‐3′‐NFQ (Albumin).

2.7. Proviral Load

HTLV‐1 proviral load (PVL) is the best marker of risk, pathogenesis, and disease potential, reflecting the integration of the virus, the clonal expansion of infected cells, and the failure of immune control—much more than just “virus quantity.” Proviral load was quantified from the ratio of Ct of the pol and albumin genes and the total leukocyte count, according to the protocol of Tamegão‐Lopes et al. [19], expressing the calculation by the following formula:

$$\frac{2^{ˆ}-CTTarget}{2^{ˆ}-CTAlbumin}xLeukocytesx2=proviralDNAcopies/m{m}^3.$$

2.8. Nested PCR

Samples confirmed as positive for HTLV‐1 by qPCR were subjected to molecular subtyping identification by nested PCR of the 5′ LTR‐1 region (788 bp) followed by nucleotide base sequencing and phylogenetic analysis. For the first reaction, 15.95 μL of ultrapure water (H₂O), 1.25 μL of buffer (10×), 1.5 μL of MgCl₂ (50 mM), 3.0 μL of dNTPs (10 mM), 0.5 μL of each primer (20 pmol), 0.3 μL of Taq DNA polymerase (1 U/μL), and 2.0 μL of DNA were combined.

The following HTLV‐1 primer sequences were used: LTR‐I.01, 5′‐TGACAATGACCATGAGCCCCAA‐3′ and LTR‐I.02, 5′‐CGCGGAATAGGGCTAGCGCT‐3′. The second reaction followed the same protocol using primers LTR‐I.03 (5′‐GGCTTAGAGCCTCCCAGTGA‐3′) and LTR‐I.04 (5′‐GCTAGGGAATAAAGGGGCGC‐3′) and 2.0 μL of the PCR product from the first reaction. Both reactions followed the same temperature cycle: 94°C for 5 min; 35 cycles at 94°C for 30 s, 61°C for 30 s, and 72°C for 40 s; and finally, 72°C for 10 min. The final product of the amplification was purified using the commercial QIAquick PCR Purification Kit (QIAGEN), following the manufacturer's instructions.

2.9. DNA Sequencing and Phylogenetic Analysis

After purification, both strands of the amplified products were sequenced using the Sanger chain termination method with fluorescence‐labeled base technology using the BigDye Terminator v3.1 kit (Thermo Fisher, Waltham, MA, USA). After precipitation of the reaction product, the samples were sequenced using the 3130Ixl Genetic Analyzers platform (Applied Biosystems).

The obtained sequences were analyzed using the Chromas 2.6.6 v program (Technelysium‐DNA Sequencing Software). The quality of each sequence was analyzed with the Phred algorithm, defined as a base value above 30, which represents 99.9% sequencing accuracy. Contig assembly (a combination of sense and antisense sequences) was performed using BioEdit 7.2.5 v software (Biological Sequence Alignment Editor). LTR sequence alignment was performed using Geneious Prime 2024.0.2 v software (www.genious.com, Biomatters, Auckland, New Zealand, accessed on 2025).

Phylogenetic analysis was performed using reference lineage sequences published in GenBank representing HTLV‐1 subtypes and subgroups with worldwide distribution, including lineages from different regions of Brazil. A maximum likelihood (ML) tree was constructed in MEGA 11.0.13 v using initial neighbor clustering (NJ) trees and the Tamura‐Nei (TN) model, including replacements, transitions, transversions, gamma distribution rates between locations with a gamma parameter, homogeneous patterns between lineages, and partial deletions with a 95% cutoff as initial trees. ML trees were constructed using TN G + I with five discrete gamma categories, and gaps were treated with partial deletion with a 95% cutoff. The heuristic method included extensive pruning of subtrees and moderate branch grafting. To infer bootstrap values, 1000 bootstrap‐tree interactions were performed. Layout changes were made in FigTree 1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/; accessed on 2025).

The following strains and GenBank access codes were used to construct the tree.: FNN100 (DQ005547.1); TSP12705 A (DQ897684.1); FNN153 A (DQ005550.1); BBD 3110 (FJ911637.1) BBD 2420 (FJ911628.1) TSP12481 A (DQ897683.1); SNT92 A (DQ070892.1); SNT43 A (DQ070891.1); Me2 Peru (Y16479.2); Qu1 Peru (Y16475.1); 2472LE A (AY818430.1); AINU (D23694.1); BOI (L36905.1); ATK (J02029.1); H5 (M37299.1); JPNBr177 (AY499187.1); TA6 (U53074.1); TA7 (U53075.1); 0D (U12805.1); BD89112 S (DQ235698.1); Bo (U12804.1); GH78 (D23693.1); PH906 C (AY342303.1); PH907 C (AY342304.1); 2656ND G (AY818431.1); H23 (L76312.1); 1259NG (AY818424.1); 1127MO B (AY818433.1); 1842LE D (AY818429.1); 2810YI G (AY818432.1); 979MO B (Y818423.1); StDen (L76306.1); 1380MV B (AY818425.1); рн236А (L76307.1) (1443MV B AY818426.1); Lib2 (Y17017.1); 1503MV B (AY818427.1); Lib1 (Y17016.1); Efe1 (Y17014.1); and Mel5 (L02534.1).

2.10. Statistical Analysis

Statistical analyses were performed using BioEstat 5.3 [20] and GraphPad Prism 6.0 (GraphPad Software, 2018) [21], software to identify possible associations. Initially, the normality of the data was assessed to select the statistical tests that best suited the numerical variables using the Shapiro‐Wilk test. Additionally, for categorical variables, frequency analyses were performed using Fisher's exact test, G‐test, and linear trend test to identify epidemiological characteristics associated with HTLV infection, adopting a significance level of 95% (p < 0.05).

For comparison with laboratory data from cancer patients infected or not with HTLV‐1, clinical and laboratory information from patients followed by SAPEVH (without a cancer diagnosis) was analyzed, in which an analysis of variance was performed using Dunn's multiple comparisons test. These patients were classified according to the result of the HTLV laboratory test, distinguishing between those with a confirmed diagnosis of infection and negative cases.

3. Results

3.1. Population Description

The study included a total of 329 patients treated at the reference oncology hospital or referred to SAPEVH. Regarding demographic characteristics, 157 (47.7%) were men and 172 (52.3%) were women. The mean age of the study population was 56.5 years (SD ± 17.0), and the median age was 59 years (ranging from 22 to 95 years). Most of the individuals were concentrated in the age groups of 50–59 years and 60–69 years, reflecting an older adult profile. The detailed demographic and clinical compositions of the study population are summarized in Table 1.

Table 1.

Demographic and clinical characteristics of the study population.

Characteristic	n (%)
Gender
Male	157 (47.7%)
Female	172 (52.3%)
Age (years)
Mean ± SD	56.5 ± 17.0
Median (Range)	59.0 (22 – 95)
Age Groups
20–29 years	24 (7.3%)
30–39 years	46 (14.0%)
40–49 years	40 (12.2%)
50–59 years	66 (20.1%)
60–69 years	73 (22.2%)
70–79 years	54 (16.4%)
≥ 80 years	26 (7.9%)
Clinical diagnosis (ICD‐10)
Leukemia	105 (31.9%)
Lymphoma	61 (18.5%)
Myeloma	30 (9.1%)
Other hematological malignancies	7 (2.1%)
Other neoplasms	42 (12.8%)
Undergoing Investigation for diagnostic	84 (25.5%)

From a clinical perspective, the study population included a diverse spectrum of hematolymphoid neoplasms. The most prevalent diagnosis was leukemia (n = 105; 31.91%), followed by lymphomas—both Hodgkin and non‐Hodgkin subtypes (n = 61; 18.54%)—and multiple myeloma (n = 30; 9.12%). Patients with other hematological malignancies and other types of neoplasms represented 2.13% (n = 7) and 12.77% (n = 42) of the cohort, respectively. Additionally, 84 patients (25.53%) were still undergoing diagnostic investigation to define their hematological classification at the time of sampling.

3.2. Prevalence of HTLV‐1 and Molecular Confirmation

The diagnostic investigation adhered to a two‐step protocol. Initially, all 329 participants underwent serological screening for anti‐HTLV‐1/2 antibodies using ELISA. This screening identified 6 reactive samples, which were subsequently subjected to molecular confirmation and differentiation via real‐time PCR (qPCR). The results confirmed HTLV‐1 infection in 6 individuals, with no cases of HTLV‐2 detected.

The confirmed prevalence of HTLV‐1 in the study population was 1.82% (6/329). Analysis by gender indicated a prevalence of 2.5% (n = 4) among men and 1.2% (n = 2) among women, with no statistically significant difference observed between sexes (p = 0.68). HTLV‐1 infection was most common in individuals over 60 years of age (2.83%) and was detected in males ranging from 30 to 79 years old. The distribution of confirmed infection across the different clinical groups is presented in Table 2.

Table 2.

Distribution of HTLV‐1 infected patients, according to their international classification of diseases (ICD).

Distribution according to ICD‐10	Study population
	Total n (%)		Negative HTLV n (%)		Positive HTLV‐1 n (%)		p‐value
Prevalence	329	(100.00)	323	(98.17)	6	(1.83)
ICD‐10
Leukemia	105	(31.91)	105	(32.51)	0	(0.00)	0.99
C90.1—Plasma cell leukemia	1	(0.30)	1	(0.31)	0	(0.00)
C90.2—Plasmacytoma	1	(0.30)	1	(0.31)	0	(0.00)
C91.0—Acute lymphocytic leukemia	26	(7.90)	26	(8.05)	0	(0.00)
C91.1—Chronic lymphocytic leukemia	9	(2.74)	9	(2.79)	0	(0.00)
C92.0—Acute myeloid leukemia	30	(9.12)	30	(9.29)	0	(0.00)
C92.1—Chronic myeloid leukemia	29	(8.81)	29	(8.98)	0	(0.00)
C92.4—Acute promyelocytic leukemia	3	(0.91)	3	(0.93)	0	(0.00)
C95—Leukemia of unspecified cell type.	3	(0.91)	3	(0.93)	0	(0.00)
C950—Acute leukemia of unspecified cell type	1	(0.30)	1	(0.31)	0	(0.00)
C959—Unspecified leukemia.	2	(0.61)	2	(0.62)	0	(0.00)
Lymphoma	61	(18.54)	57	(17.65)	4	(66.67)
C81—Hodgkin Lymphoma	19	(5.78)	18	(5.57)	1	(16.67)
C82—NHL (Follicular)	8	(2.43)	8	(2.48)	0	(0.00)
C83—NHL (Diffuse)	5	(1.52)	4	(1.24)	1	(16.67)
C84—Cutaneous and peripheral T‐cell lymphomas.	3	(0.91)	3	(0.93)	0	(0.00)
C84.1—Sézary disease	1	(0.30)		(0.00)	1	(16.67)
C84.4—Peripheral T‐cell lymphoma	1	(0.30)		(0.00)	1	(16.67)
C85—Non‐Hodgkin lymphoma of other types and of unspecified type.	24	(7.29)	24	(7.43)	0	(0.00)
Myeloma	30	(9.12)	30	(9.29)	0	(0.00)
C90.0—Multiple myeloma	30	(9.12)	30	(9.29)	0	(0.00)
Other hematological malignancies	7	(2.13)	7	(2.17)	0	(0.00)
C77—Unspecified secondary malignant neoplasm of lymph nodes	1	(0.30)	1	(0.31)	0	(0.00)
C96—Other malignant and unspecified neoplasms of lymphatic, hematopoietic and related tissues.	1	(0.30)	1	(0.31)	0	(0.00)
D47—Other neoplasms of uncertain or unknown behavior of lymphatic, hematopoietic and related tissues.	5	(1.52)	5	(1.55)	0	(0.00)
Other neoplasms	42	(12.77)	41	(12.69)	1	(16.67)
Undergoing investigation for diagnostic	84	(25.53)	83	(25.70)	1	(16.67)

The prevalence of HTLV‐1 among patients with a confirmed diagnosis of hematological malignancy was 1.97% (4/203). HTLV‐1/2 was investigated among 105 patients presenting leukemia subtypes, including Acute Lymphocytic Leukemia (ALL), Chronic Lymphocytic Leukemia (CLL), Acute Myeloid Leukemia (AML), and Chronic Myeloid Leukemia (CML), among others. They were all negative for the presence of antibodies against HTLV‐1/2.

Conversely, lymphomas, including both Hodgkin and non‐Hodgkin lymphomas (NHL), represented another important group (n = 61; 18.54%) and showed a significantly higher prevalence of 6.56% (4/61). Specifically, HTLV‐1 was present in one patient with Hodgkin lymphoma, and three with NHL (diffuse NHL, Sézary disease, and peripheral T‐cell lymphoma). Patients with multiple myeloma, totaling 30 cases (9.12%), and seven patients (2.13%) with other types of hematological neoplasms, were not infected with HTLV‐1/2.

Forty‐two patients (12.77%) with other types of neoplasia were investigated, and one was positive for HTLV‐1. Additionally, patients still undergoing diagnostic investigation for hematological neoplasia were included, totaling 84 patients (25.53%), and one was found to be positive for HTLV‐1. While there was a significant association for the lymphoma group as a broad category, statistical analysis did not show any significant association between HTLV‐1 infection and the different specific sub‐classifications of hematological malignancies (p > 0.5) (Table 2).

When comparing the major groups of malignancies (Figure 2), patients with lymphomas showed a significantly higher prevalence of 6.56% (4/61) compared to the leukemia and myeloma groups (p = 0.02). In patients still under diagnostic investigation, the prevalence was 1.19% (1/84), and among those with other types of cancer, it was 2.38% (1/42).

Figure 2.

Distribution of the study population according to the International Classification of Diseases (ICD‐10). The bar chart illustrates the stratification of the 329 patients included in the study based on their primary diagnosis. The clinical categories encompass specific leukemia subtypes (e.g., Acute Lymphoblastic Leukemia [ALL], Chronic Lymphocytic Leukemia [CLL], Acute Myeloid Leukemia [AML], Chronic Myeloid Leukemia [CML]), lymphomas (Hodgkin and non‐Hodgkin subtypes), multiple myeloma, and other specified or unspecified neoplasms.

3.3. Laboratory Findings

Laboratory data for patients positive for HTLV‐1 are presented in Table 2. These results include complete blood count, biochemical parameters, and some inflammatory markers. Proviral load was also quantified in all HTLV‐1‐infected patients (Table 3)

Table 3.

Laboratory assessments for each patient testing positive for HTLV‐1.

Patients/Clinical diagnosis
	ONC‐326	ONC‐262	ONC‐1181	ONC‐955	ONC‐100	ONC‐110
EXAMS	Hodgkin lymphoma	Diffuse NHL	Peripheral T‐cell lymphomas	Sézary disease	Other neoplasm	UID	Reference values
Red blood cells ‐ millions/mm 3	4.7	4	4.35	4	2.9	4.1	3.9 a 5.3
Hemoglobin g/dl	13.5	11.6	13.50	12.30	9.6	12.6	12.00 a 16.00
Hematócrit %	40.4	35.1	33.70	37.9	29.5	38.5	36 a 48
MCV fl	86.2	89	77.50	94.8	102	95	80 a 100
MCH pg	28.7	29.5	31	30.7	33.3	31.2	27 a 33
MCHC g/dl	33.4	33.1	40	32.4	32.7	32.9	31 a 36
RDW %	14.8	21.1	*	*	11.9	14.4	11.00 a 14.15
Leukocytes/mm 3	7900	9000	125 000	189 000	6538	6697	3600 a 11 000
Rod cells/mm 3	0	0	*	*	261	0	0 a 410
Neutrophils/mm 3	2701	6002	*	3723.30	4184	375	1700 a 8200
Lymphocytes/mm3	4166	1918	*	1 202 040	1440	2018	1000 a 4500
Reactive Lymphocytes/mm3	0	0	*	*	0	0	0
Monocytes/mm 3	734	927	*	*	392	669	100 a 1000
Eosinophils/mm 3	252	90	*	*	261	200	20 a 500
Basophils/mm 3	47	63	*	*	0	60	0 a 200
Platelets/mm 3	229 000	166 000	126 900	229 000	157 400	357 400	140 000 a 400 000
Urea mg/dL	31	79	*	55.00	25	31	13 a 43
Creatinine mg/dL	0.95	1.34	*	1.24	1.35	0.54	0.80 a 1.30
Gamma‐glutamyl transferase u/l	15	60	*	18	*	25	9 a 64
Lactic dehydrogenase (ldh) u/l	169	180	*	*	*	167	Inferior a 250
C‐reactive protein mg/l	*	99	162	229	25	*	**
Alkaline phosphatase u/l	105	87	113.90	*	*	49	34 a 104
Proviral load DNA copies/mm 3	25 379.53	20 127.34	34 779.65	37 654.96	23 516.41	19 688.38

Abbreviations: MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; MCV, mean corpuscular volume; RDW, red cell distribution width; UID, undergoing investigation for diagnostic.

^*Data missing from medical record. Gray cells—values within reference ranges; Blue cells—values below reference ranges; Orange cells—values above reference ranges.

^**Above 10 mg/L: indicates a serious or significant infection.

When analyzing the main hematological and biochemical parameters with different types of hematological neoplasms, it was observed that the patient with Hodgkin Lymphoma, presented a slightly increased Red Cell Distribution Width (RDW), and the individual with diffuse NHL showed altered hemoglobin and hematocrit levels, indicating mild to moderate anemia, in addition to the elevation of RDW (21.1%), urea (79 mg/dL), creatinine (1.34 mg/dL), and C‐reactive protein.

Among patients with Peripheral T‐cell Lymphoma and Sézary disease, the most striking findings included leukocytosis, more pronounced in the patient with Sézary disease (exceeding 15 000/mm³). Both cases presented elevated levels of C‐reactive protein. In addition, there was thrombocytopenia (platelets below 150 000/mm³) in the patient with peripheral T‐cell lymphoma.

In patients with other neoplasms and patients undergoing diagnostic investigation, signs of significant anemia were observed, with reduced hemoglobin (9.6 g/dL) and hematocrit.

Hematological parameters of patients with hematological malignancies who were positive and negative for HTLV‐1 infection were compared with cancer‐free patients (both infected and uninfected with HTLV‐1, attending the SAPEVH), and are presented in Figure 3.

Figure 3.

Comparative panel of mean values of hematological parameters among different clinical groups. The bar graphs represent the mean and respective standard deviations for: (a) red blood cell count (millions/mm³), (b) hemoglobin concentration (g/dL), (c) hematocrit (%), (d) white blood cell count (thousand/mm³) and (e) platelet count (thousand/mm³), distributed among the groups of patients diagnosed with hematological cancer with and without HTLV‐1 infection and non‐oncological patients with and without HTLV‐1 infection.

Regarding red blood cell counts, HTLV‐1‐negative cancer patients showed an average of 3.59 million/mm³, in contrast to 4.23 million/mm³ among HTLV‐1‐positive cancer patients. When compared to individuals without cancer, with or without HTLV‐1 infection (both with an average of 4.35 million/mm³), it is observed that HTLV‐negative cancer patients have reduced values. HTLV‐positive cancer patients exhibited red blood cell counts similar to those observed in individuals without cancer (Figure 3a).

Hemoglobin levels followed a similar trend. Cancer patients not infected with HTLV‐1 showed an average of 10 g/dL, while HTLV‐1‐positive cancer patients presented an average of 12.7 g/dL. In comparison, patients without cancer showed higher hemoglobin levels, with average counts of 13.92 g/dL (HTLV‐1 negative) and 13.29 g/dL (HTLV‐1 positive) (Figure 3b). Hematocrit also showed similar variation. HTLV‐1‐negative cancer patients showed a mean hematocrit of 31%, considerably lower than the 37.12% observed in HTLV‐1‐positive cancer patients. Patients without cancer showed higher values, with average counts of 41.53% (HTLV‐1 negative) and 40.42% (HTLV‐1 positive) (Figure 3c).

HTLV‐1‐negative cancer patients showed an average count of 5004/mm³, while HTLV‐1‐positive cancer patients presented a higher count, with an average of 10 999/mm³. In contrast, patients without cancer showed more moderate counts, with average counts of 6396/mm³ (HTLV‐1 negative) and 7377/mm³ (HTLV‐1 positive) (Figure 3d). Platelet counts also showed notable differences. HTLV‐1‐negative cancer patients showed an average of 174 042/mm³, while HTLV‐1‐positive cancer patients showed a count of 221 660/mm³. Patients without cancer presented the highest platelet counts, with averages of 245 609/mm³ (HTLV‐1 negative) and 239 590/mm³ (HTLV‐1 positive) as shown in Figure 3e.

Lactate dehydrogenase (LDH) levels were considerably higher in HTLV‐1‐negative cancer patients (274.71 U/L) compared to HTLV‐1‐positive cancer patients (181.4 U/L). Levels of C‐reactive protein showed HTLV‐1 positive cancer patients with an average count of 106.45 mg/L, higher than the 71.37 mg/L observed in HTLV‐1 negative cancer patients. Gamma‐glutamyltransferase (Gamma GT) was detected in lower levels in HTLV‐1 positive cancer patients (29 U/L) compared to HTLV‐negative patients (124.84 U/L). Alkaline phosphatase, another enzyme marker associated with liver function and bone activity, followed the same pattern and was found in higher levels in HTLV‐1 negative cancer patients (122.72 U/L) compared to HTLV‐1 positive cancer patients (80.33 U/L).

The PVL of patients with hematological malignancies was compared to that of individuals infected with HTLV‐1 but without cancer (asymptomatic and symptomatic) attending the SAPEVH. The average proviral load in patients with hematological cancer was significantly higher (29 485.38 copies of proviral DNA/mm³) compared to the non‐oncological groups, whose average counts were 10 991.89 copies/mm³ (asymptomatic) and 9832.89 copies/mm³ (symptomatic), as shown in Figure 4.

Figure 4.

HTLV‐1 proviral load (proviral DNA copies per mm³) among three different groups of people living with HTLV‐1: HTLV‐1 infected cancer patients, asymptomatic individuals, and symptomatic individuals. Each point represents an individual, and the dashed lines indicate the median of each group. ** Shows the statistically significant difference between the groups.

Variability in proviral load levels was more pronounced among patients with hematological malignancies, as demonstrated by the high standard deviation (SD = 8148.68), indicating a wide dispersion of values in this group. In contrast, asymptomatic and symptomatic individuals showed less variability, with standard deviations of 3768.86 and 3340.32, respectively, showing a more homogeneous distribution of proviral load among these patients.

Analysis of variance indicated a significant difference in mean proviral loads among the three groups (oncology patients, asymptomatic, and symptomatic) (p = 0.005). Dunn's multiple comparisons test was applied. The results showed that proviral load of oncology patients was significantly higher compared to asymptomatic individuals (p = 0.0318) and also compared to symptomatic individuals (p = 0.0034). However, no statistically significant difference was observed between the asymptomatic and symptomatic groups (p > 0.9999).

3.4. Molecular Epidemiology

Phylogenetic analysis of the 5′LTR region of HTLV‐1 was successfully performed on four isolates. The resulting sequences were deposited in GenBank with the following accession numbers: PX704688 (Isolate 110_ONCO), PX704689 (Isolate 262_ONCO), PX704690 (Isolate 326_ONCO), and PX704691 (Isolate 955_ONCO). Figure 5 shows the presence of five main phylogenetic clusters. The viral isolates obtained from patients with hematological cancer clustered in the HTLV‐1 Cosmopolitan subtype, Transcontinental subgroup cluster, with high bootstrap support (90%).

Figure 5.

Phylogenetic analysis of HTLV‐1 5′ LTR sequences. The tree was constructed using the maximum likelihood method, utilizing sequences from the LTR region of HTLV‐1 (715 bp). The Mel5 and Efe1 sequences were included as an outgroup. Red circles indicate samples sequenced in this study. The analysis allowed the formation of different clusters within the Cosmopolitan Subtype belonging to the Transcontinental Subgroup.

4. Discussion

HTLV‐1 is a retrovirus endemic in several regions of the world, and although the epidemiological scenario of HTLV‐1 infections among different populations and social groups has been explored (pregnant women, illicit drug users, urban and rural populations, among others), the prevalence of this virus in patients with other hematological neoplasms not related to ATLL remains underestimated [22, 23, 24].

In this study, we provided primary information on the prevalence of HTLV‐1 infection, clinical, laboratory and genotyping of the infecting virus in patients with hematological malignancies in the state of Pará. Since adequate representativeness was ensured, with the final sample exceeding the previously calculated sample size (calculated size = 322 vs. final size > 326), it was possible to show that the dynamics of HTLV‐1 infection in this cohort differ from prevalence patterns observed in the general population.

The prevalence of HTLV‐1 was similar in men and women with hematological cancer, differing from other studies that indicate a higher frequency in women, suggesting a clear difference from the general population in relation to sex. The age distribution showed a higher proportion of HTLV‐1‐positive infected elderly (> 60 years) individuals, corroborating the literature that associates prevalence with the accumulation of exposures throughout life [7]. The trend may be influenced by the type of neoplasm, prior use of blood transfusions, and other specific risk factors, highlighting the need for continuous surveillance in advanced age groups to guide prevention actions.

According to the subtypes of neoplasms, there was heterogeneity in the infection with HTLV. Patients with lymphoma, especially non‐Hodgkin lymphoma (NHL) and peripheral T‐cell lymphoma, presented the highest rates of HTLV‐1, while acute leukemias and multiple myeloma did not show positive cases. This distribution is consistent with the restricted oncogenic role of the virus, which is a classic cause of ATLL, and reinforces its strong association with T‐cell lymphoid neoplasms [25].

Finding a case of HTLV‐1 in a patient with Hodgkin lymphoma (HL) deserves attention, as this association is uncommon and poorly documented. Adedayo and Shehu [26], also reported cases of HTLV‐1 infection in patients with HL, suggesting that this virus may act as a cofactor in lymphoid oncogenesis, although this relationship is not yet fully elucidated. The possibility of misdiagnosis between HL and HTLV‐1‐associated lymphomas should be stressed, as the virus can trigger ATLL subtypes with histopathological characteristics similar to those of classic Hodgkin lymphoma; it is worth mentioning the need to perform specific tests, such as the detection of HTLV‐1 proviral integration and TCR Cb1 gene rearrangement, for diagnostic confirmation [27]. It has been previously reported by Sandival‐Ampuero et al. [28] that HTLV‐1‐infected patients with HL showed a reduced success response to treatment and reduced overall survival (55%) compared to the control group (67%), although without a statistically significant difference in the long term. These findings reinforce the relevance of accurate diagnosis of the infection and the investigation of the possible influence of HTLV‐1 on the prognosis and therapeutic response of patients with Hodgkin lymphoma.

The identification of HTLV‐1‐positive patients who are undergoing diagnostic investigation for malignancies highlights the relevance of including HTLV‐1 testing in the initial protocol for lymphomas and leukemias. The Clinical Management Guide for HTLV Infection of the Brazilian Ministry of Health [29] clearly recommends adding the testing to the initial approach; but it is not mandatory, delaying differential diagnosis and starting the appropriate treatment, especially in ATLL, where early detection is crucial for survival [30].

From a clinical‐laboratory perspective, HTLV‐1‐positive patients maintained LDH and alkaline phosphatase values within the reference range, whereas negative patients showed elevations, suggesting lower cellular turnover or distinct pathophysiological mechanisms in the presence of the virus. Furthermore, seropositive individuals presented hematimetric index values (red blood cells, hemoglobin, hematocrit, and platelets) within the reference range, compared to seronegative individuals.

Tax1 protein can suppress hematopoiesis in CD34+ progenitors and simultaneously inhibit apoptosis in these cells, creating a scenario of atypical proliferation over time [31, 32]. Dysregulation of miRNAs and activation of NF‐κB, AP‐1, and JAK‐STAT pathways can also interfere with hematopoietic proliferation and differentiation [33, 34, 35]. These mechanisms could explain the duality observed in the HTLV‐1‐positive patients, characterized by the preservation of hematological indices and normalization of cell destruction markers.

Proviral load was found to be significantly higher in patients with hematologic cancer compared to individuals without neoplasia (symptomatic and asymptomatic), reinforcing its role as a biomarker of infection progression [36]. However, there was no significant difference between asymptomatic and symptomatic individuals positive HTLV‐1 without neoplasia, highlighting that proviral load is only one of the determinants in the clinical course. Host factors such as age, sex, immune status, and genetic predisposition also modulate disease progression [37].

Phylogenetic analysis based on the LTR region confirmed the predominance of the Cosmopolitan subtype, Transcontinental subgroup in Brazil, indicating a strong evolutionary relationship between the samples and this specific viral subgroup, with genetic similarity to other samples from individuals from the state of Pará (BBD_3110; SNT43_A; STN92_A; TSP12481_A) evidencing homogeneous groupings that may be related to the history of the virus's introduction into Brazil from human migratory flows and consequent viral dissemination [38, 39].

The study was slightly limited due to the absence of complete medical records, restricting detailed clinical characterization, and the cross‐sectional design, which prevents definitive causal inferences. Nevertheless, the results support evidence to propose a relevant question, regarding the capability of HTLV‐1 modulate immune responses protectively in certain oncological contexts and influence hematological parameters through direct effects on hematopoietic progenitors or indirectly via chronic inflammation.

Future investigations need to integrate comprehensive clinical data, gene expression analysis, and longitudinal assessment of proviral load. Furthermore, exploring the interaction between viral variability in regulatory regions (LTRs) and host factors (HLA, cytokines, miRNAs) may elucidate mechanisms of oncogenesis and differentiated pathogenesis.

In terms of public health policies, the systematic incorporation of HTLV‐1 testing into oncology protocols would allow mapping the actual prevalence, monitoring the incidence of ATLL, guiding contact tracing and genetic counseling [40], as well as providing a basis for prevention and control policies towards the elimination of the virus in hospital and community settings, reducing disparities between recommendations and clinical practice, and strengthening prevention policies.

5. Conclusions

This study provides the first evidence of HTLV‐1 infection among patients with hematological malignancies in the state of Pará, revealing an overall prevalence of 1.82% and a notable positivity (6.56%) among patients with lymphomas. Our results expand current knowledge regarding the relationship between HTLV‐1 infection and hematological cancer and underscore the importance of incorporating HTLV testing into routine screening and follow‐up protocols for patients with hematological malignancies. This approach facilitates a more comprehensive assessment of viral presence and its clinical implications. Finally, the results suggest that the design of cohorts with clinical and laboratory follow‐up, combined with host genomic approaches, would be essential to unravel the complex interactions between the virus and hematological cancer.

Author Contributions

Gabriel dos Santos Pereira Neto contributed to conceptualization, methodology, formal analysis, investigation, and writing of the original draft. Ana Vilhena Alves and Bruno José Sarmento Botelho contributed to methodology and investigation. Andrio Silva da Silva, Debora Monteiro Carneiro, and Rommel Mario Rodriguez Burbano were responsible for data curation and resources. Ricardo Ishak contributed to validation and article review and editing. Antonio Carlos Rosário Vallinoto contributed to conceptualization, funding acquisition, supervision, and article review and editing. Izaura Maria Vieira Cayres Vallinoto contributed to conceptualization, project administration, supervision, and article review and editing. All authors have read and approved the published version of the article.

Ethics Statement

This study was conducted in accordance with all applicable ethical guidelines for research involving human subjects. The project was approved by the Research Ethics Committees of the Ophir Loyola Hospital (CAAE: 23160619.1.0000.5550) and the Federal University of Pará (CAAE: 71261523.1.0000.0018), in compliance with Resolution No. 466/12 of the Brazilian Ministry of Health.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.