abcArchives of Breast CancerArch Breast Cancer2383-0433Archives of Breast Cancer10.32768/abc.1938574206-1951110Original ArticleCorrelation Between miR-143-5p/miR-744-5p and HIF1A Expression Across Breast Cancer Grades and Treatments in Iraqi WomenHadeedHatem M.RasheedMaarib N.SuleimanAhmed AbdulJabbarDepartment of Clinical Laboratories Sciences, College of Pharmacy, University of AnbarRamadiIraqInstitute of Genetic Engineering and Biotechnology for Postgraduate Studies, University of BaghdadBaghdadIraqDepartment of Biotechnology, College of Science, University of AnbarRamadiIraqDepartment of Biotechnology, College of Science, University of Anbar, Ramadi, Iraqahmed.suleiman@uoanbar.edu.iq
The authors declare that they have no known competing financial interests.
Breast cancer (BC) accounts for 25% of all cancer cases and 15% of all cancer-related deaths among women. Hypoxia-inducible factor-1alpha (HIF1A) is a crucial regulator of cellular responses to hypoxia. This study aimed to evaluate the expression of miR-143-5p and miR-744-5p as potential molecular markers and their association with HIF1A in BC.
Methods
The study included 100 newly diagnosed cases of BC who attended the Oncology Center in Al-Anbar, Iraq, from July 2024 to January 2025. After RNA extraction and cDNA synthesis, real-time polymerase chain reaction was used to determine microRNA (miR) expression levels for women with BC and healthy controls.
Results
The results showed that miR-143-5p exhibited significantly higher expression levels in high-grade after treatment (HAT) and low-grade before treatment (LBT) samples compared with control, high-grade before treatment (HBT), and low-grade after treatment (LAT) samples. miR-744-5p did not show significant differences in expression across the different cohorts. HIF1A showed no statistically significant correlations with any of the other measured molecules in either the control group (miR-143-5p: r = -0.25, P = 0.32; miR-744-5p: r = -0.32, P = 0.23) or any of the experimental groups (all P values > 0.05). miR-744-5p showed moderate potential (area under the curve [AUC] = 0.629). HIF1A exhibited high diagnostic potential in the HBT group with an AUC value of 0.774 and moderate diagnostic potential in the HAT group with an AUC value of 0.647, indicating that the HIF1A gene may be a good diagnostic marker for certain subgroups of BC.
Conclusion
The findings suggest that miR-143-5p may serve as a potential biomarker for BC.
breast neoplasmsmiR-143-5pmiR-744-5pHIF1AhypoxiaRT-qPCRThe research is self-funded.How to CiteHadeed HM, Rasheed MN, Suleiman AA. Correlation Between miR-143-5p/miR-744-5p and HIF1A Expression Across Breast Cancer Grades and Treatments in Iraqi Women. Arch Breast Cancer. 2025;12(4):410-418. Available from: View ArticleINTRODUCTION
Breast cancer (BC) is a complex disease and the most commonly diagnosed cancer in women worldwide. BC is the primary cause of cancer among women and the leading cause of cancer-related mortality in women in Iraq.1,2 Additionally, BC is a multifactorial heterogeneous disease.3,4 MicroRNAs (miRs) are endogenous noncoding RNAs with 21 to 23 nucleotides. They function in posttranscriptional gene regulation through degradation and translational repression of target mRNAs harboring substantial complementarity with miRs.5 MicroRNAs are involved in several cellular processes, such as development, differentiation, growth, proliferation, and apoptosis.6 They play a significant role as oncogenes and tumor suppressor genes.7 The role of miR-143-5p and its seed region specificity in estrogen receptor-positive BC remains poorly understood.8 Mechanistically, miR-143-5p acts by targeting specific genes in BC cells.9 miR-744-5p, on the other hand, acts as a tumor suppressor as it is able to inhibit BC cell migration and invasion in vitro. Hypoxia is defined as an imbalance between rapid tumor growth and inadequate O2 delivery.10 The microenvironment of solid tumors, such as BC, can be acidic, causing aggressiveness and treatment resistance. Hypoxia-inducible factor-1alpha (HIF1A) is a key transcription factor that regulates cellular responses to hypoxia, a common feature in solid tumors, including BC.11 Under hypoxic conditions, HIF1A stabilizes and activates the transcription of genes involved in angiogenesis, metabolic reprogramming, and cell survival, which are critical for tumor progression and metastasis.12 HIF1A is significantly upregulated in the majority of BC cases but is downregulated in a few cases.13 The aim of this study is to investigate the role of miR-143-5p and miR-744-5p in HIF1A gene expression in patients with BC.
METHODSSamples and data collection
This study was approved by the Council of the Institute of Genetic Engineering and Biotechnology for Postgraduate Studies at the University of Baghdad, and the study protocol was approved by the Ethics Committee of the Ministry of Health and Environment- Al-Anbar Directorate of Health (AO No. 1812). All procedures of this research, including sample collection, were conducted at the Oncology Center in Al-Anbar Province from July 2024 to January 2025. The study design was cross-sectional, as biomarkers and gene expression were measured simultaneously through convenience sampling. In this research, 100 Iraqi women participated, all of whom were confirmed as newly diagnosed patients with BC aged 30-70 years. All patients with breast cancer underwent all required assessments, including measurement of weight and height and collection of detailed family medical history, which were documented in a dedicated patient admission form at the oncology center. Participants were classified as overweight or obese based on their body mass index (BMI), calculated as weight in kilograms divided by height in meters squared (kg/m2). Participants were classified as overweight (BMI, 25.0-29.9) or obese (BMI, ≥ 30.0) based on standard World Health Organization (WHO) criteria. The selected patients were grouped according to specific criteria into 4 groups, each with 25 patients. There were 25 patients with low-grade BC before treatment (LBT) and 25 patients with low-grade BC after treatment (LAT). The remaining 25 patients had high-grade BC before treatment (HBT) and 25 patients had high-grade BC after treatment (HAT). There were 25 healthy individuals who had no history or clinical evidence of BC and no chronic diseases, such as hypertension or diabetes, in the control group. The blood samples were taken before chemotherapy and 6 weeks after treatment for all patients who attended Al-Anbar Oncology Center. A volume of 1.5 mL of blood was collected and transferred into an EDTA anticoagulant tube. After gentle mixing, 0.5 mL of whole blood was placed directly into TRIzol for preservation for the extraction of RNA and kept at -70°C for molecular analysis.
Inclusion criteria
The study included women with a first-time diagnosis of BC, classified as low or high grade by immunohistochemistry (IHC) and biopsy, who were treatment-naive and without chronic comorbidities (e.g., hypertension or diabetes).
Exclusion criteria
Women previously treated with any cancer therapy (e.g., chemotherapy), those with other cancers, prior BC diagnoses, or chronic conditions such as hypertension or diabetes were excluded from the study.
Molecular assaysProtocol of RNA extraction
Total RNA, including microRNA, was extracted from patient samples using TRIzol Reagent according to the manufacturer's protocol. Briefly, 200 μL of chloroform was added to homogenized samples to separate the aqueous phase. After centrifugation, the aqueous phase was transferred to a new tube, and 500 μL of isopropanol was added to precipitate the RNA. Then, 500 μL of 70% ethanol was used for RNA washing. Finally, the supernatant was discarded, the pellet was resuspended in 50 μL of nuclease-free water, and the RNA was kept at -70°C until the RT-qPCR reaction.
Reverse transcription for complementary DNA (cDNA) synthesis
Reverse transcription was performed using RNA extracted from blood. The quantification of miRs by quantitative real-time polymerase chain reaction (qRT-PCR) requires the extension of mature miRs' length by adding poly(A) tails, due to their short sequence. To reverse transcribe miR, the total RNA was first polyadenylated using a Poly(A) Tailing Kit from Tinzyme Company, China. The cDNA synthesis was carried out using a reverse transcriptase kit (ELK Biotechnology, China). The reverse transcription master mix was placed in a 0.2-mL PCR tube, and the template RNA and cDNA primers were added and gently mixed. For reverse transcription, the thermal cycle settings were 25°C for 5 minutes, 42°C for 60 minutes, and 70°C for 1 minute.
Following the manufacturer's instructions, the SYBR Green PCR Kit (Bioer LineGene, China) was used to perform RT-qPCR. The reaction was carried out using a real-time PCR instrument and had a total volume of 20 μL. It contained 10 μL of SYBR Green Master Mix, 1 μL of each specific forward and reverse primer, 3 μL of cDNA, and 6 μL of RNase-free water. The following were the cycling conditions: an initial cycle of 95°C for 1 minute, followed by 45 cycles of 95°C for 20 s and 60°C for 30 s. The relative expression levels of the miRs (normalized to U6) and HIF1A mRNA (normalized to glyceraldehyde-3-phosphate dehydrogenase [GAPDH]) were calculated using the formula 2-ΔΔCt, presented as fold change. The primer sets used in the current study are listed in Table 1.
Primer Sequences Used in This Research
Primer name
Sequence 5'-3'
HIF1A
GTCTCAGAGTAGCAGCCAGATCCTCACACGCAATAGCTGA
GAPDH (Housekeeping gene)
TGCCACCCAGAAGACTGTGGTTCAGCTCAGGGATGACCTTT
miR-143-5p
AACAGAGGTGCAGTGCTGC
miR-744-5p
AACAAGTGCGGGGCTAGGGCR
Universal Reverse
CAGTGCAGGGTCCGAGGT
U6 (Housekeeping gene)
GTGCTCGCTTCGGCAGCACAAAATATGGAACGCTTC
GAPDH, glyceraldehyde 3-phosphate dehydrogenase; HIF1A, hypoxia-inducible factor 1-alpha; miR, microRNA; U6, U6 small nuclear RNA. Primers were designed by the researcher in the current study.
Statistical analysis
Data were analyzed using IBM SPSS Statistics (version 26.0) to determine the effect of different factors on the study parameters. The relationship between the variables was assessed using the Pearson correlation coefficient. Categorical data were expressed as numbers and percentages, whereas the quantitative variables were expressed as the median and interquartile range (IQR). Receiver operating characteristic (ROC) curve analysis was employed to calculate the area under the curve (AUC).
RESULTS
The RT-qPCR results for miRs and HIF1A were analyzed using the relative quantification of gene expression levels (fold change) based on the cycle threshold (Ct) values. The analyses revealed distinct patterns of miR-143-5p, miR-744-5p, and HIF1A expression in relation to age and BMI and highlighted potential links between these molecules, aging, obesity, and cancer stage-specific factors.
The analysis of the dataset revealed notable distributional disparities across several variables. Family history was unevenly distributed, with the majority of observations (78%) reporting no history of disease compared with 22% with a history. Table 2 presents the demographic and clinical characteristics of the patients in different BC cohorts and the participants in the control group.
The distribution of samples was uneven across categories of family history and other diseases. The control group showed the lowest counts in some clinical categories, such as family history and comorbidities, but not consistently across all variables. Upon analysis of BMI and age across 5 different sample groups, including a control group and 4 cancer-related groups (HAT, HBT, LAT, and LBT), the control group was found to exhibit a median BMI similar to that of the LAT and LBT groups, but it had the narrowest IQR, indicating both a lower median BMI and less variability within this group compared with the cancer-related groups. Compared with the control group (younger, lower BMI, narrower age range), all cancer groups exhibited higher median ages and wider age distributions. The trend of increasing median age from HAT to LBT suggests an association between age, cancer grade, and/or treatment status.
Biomarker expression analysis across age and cancer grades
The study categorized samples into 2 age groups: adult and older adult. The age groups were defined as follows: young adults (18-24 years), adults (25-59 years), and older adults (≥ 60 years), in alignment with WHO and commonly accepted epidemiological classifications.
We analyzed multiple biomarkers across different groups (i.e., control, HAT, HBT, LAT, and LBT). The biomarkers examined consisted of microRNAs (miR-143-5p, miR-744-5p) and HIF1A.
Demographic and Clinical Characteristics of the Participants
Variables
LBT(n = 25, 20.0%)
LAT(n = 25, 20.0%)
HBT(n = 25, 20.0%)
HAT(n = 25, 20.0%)
Control(n = 25, 20.0%)
Age, y
<50
10 (40%)
7 (28%)
8 (32%)
8 (32%)
20 (80%)
>50
15 (60%)
18 (72%)
17 (68%)
17 (68%)
5 (20%)
BMI, median (IQR)
32.7 (31.2–34.2)
32.7 (31.2–34.2)
33.5 (32.4–34.2)
33.8 (32.6–34.3)
32.7 (31.8–34.2)
Family history
Yes
9 (36%)
8 (32%)
4 (16%)
4 (16%)
0 (0%)
No
16 (64%)
17 (68%)
21 (84%)
21 (84%)
25 (100%)
Other diseases
Yes
0 (0%)
0 (0%)
2 (8%)
2 (8%)
0 (0%)
No
25 (100%)
25 (100%)
23 (92%)
23 (92%)
25 (100%)
BMI, body mass index; HAT, high-grade after treatment; HBT, high-grade before treatment; IQR, interquartile range; LAT, low-grade after treatment; LBT, low-grade before treatment.
Analysis of miR-143-5p revealed a general trend of decreased expression with age, particularly in HAT and LBT groups. The participants in the control group exhibited relatively low expression levels across both age groups, while HBT and LAT samples showed greater variability, with some instances of high expression in the adult group. The participants in the control group displayed consistently low expression levels across the entire age spectrum. This suggests a potential age-dependent downregulation of miR-143-5p, particularly within specific sample types. For HIF1A, levels remained relatively stable across age groups in control, HAT, and LBT groups. However, HBT and LAT exhibited greater variability, with some instances of high expression in the adult group, possibly indicative of varying levels of cellular stress or hypoxia. The observed age-related changes in miR-143-5p and miR-744-5p levels indicate possible dysregulation of these regulatory RNAs, which play crucial roles in gene expression and cellular function. MiR-744-5p displayed a more heterogeneous pattern, with some groups showing a slight decrease with age, while others exhibited a slight increase. The LBT and control groups remained relatively stable across the age groups, indicating a more complex and nuanced relationship between age and miR-744-5p expression, likely influenced by sample-specific factors (Table 3).
Age-Stratified Expression of miR-143-5p, miR-744-5p, and HIF1A in Patients With BC and the Participants in the Control Group
Sample type
Age group
miR-143-5p
miR-744-5p
HIF1A
Control
Adult
1.00 (1.00–1.00)
1.00 (1.00–1.00)
1.00 (1.00–1.00)
Old
1.00 (1.00–1.00)
1.00 (1.00–1.00)
1.00 (1.00–1.00)
HAT
Adult
0.65 (0.37–2.89)
0.56 (0.10–1.08)
2.10 (1.46–3.39)
Old
0.52 (0.19–2.16)
0.52 (0.31–3.07)
2.17 (1.31–2.71)
HBT
Adult
0.48 (0.13–1.01)
0.16 (0.07–0.54)
2.77 (2.01–2.99)
Old
0.11 (0.05–0.34)
0.10 (0.01–0.16)
2.87 (2.43–3.23)
LAT
Adult
0.63 (0.08–0.85)
0.08 (0.07–0.79)
1.10 (0.85–1.48)
Old
0.04 (0.01–0.10)
0.08 (0.02–0.26)
0.86 (0.73–1.19)
LBT
Adult
18.92 (0.55–37.90)
0.48 (0.08–6.84)
0.60 (0.55–0.70)
Old
3.43 (0.86–21.71)
0.22 (0.04–3.63)
0.78 (0.66–0.82)
BC, breast cancer; HAT, high-grade after treatment; HBT, high-grade before treatment; HIF1A, hypoxia-inducible factor 1-alpha; IQR, interquartile range; LAT, low-grade after treatment; LBT, low-grade before treatment; miR, microRNA. Data are presented as median (IQR).
Biomarker expression analysis across BMI and cancer grades
This study examined biomarker expression levels, which included 2 microRNAs (miR-143-5p, miR-744-5p) and HIF1A in individuals classified by BMI as either overweight or obese, with further stratification by sample type: control, HAT, HBT, LAT, and LBT. BMI was categorized based on the WHO criteria: underweight (BMI < 18.5), normal weight (18.5-24.9), overweight (25.0-29.9), and obese (≥ 30.0). Analysis of miR-143-5p expression revealed higher levels in obese compared with overweight participants, particularly in HAT and LBT groups, while control samples showed consistently low expression. In contrast, miR-744-5p exhibited a complex pattern: expression was higher in obese participants for HBT and LAT groups but lower in HAT groups, with controls consistently low. These nuanced patterns suggest a variable relationship with BMI. HIF1A expression was elevated in obese participants, most notably in HBT and LAT groups, with low expression in controls (Figures 1 and 2).
miR-143-5p showed substantially elevated expression levels in HAT and LBT samples compared with control, HBT, and LAT samples. This observation suggests a potential role for miR-143-5p in the biological processes or characteristics specific to HAT and LBT. In contrast, miR-744-5p did not show discernible differences in expression across the different groups. This suggests that the expression of miR-744-5p is likely not influenced by the factors that differentiate these sample groups. HIF1A exhibited markedly higher expression in HBT samples compared with control and LAT samples. While HBT and LBT samples also showed higher HIF1A levels compared with the control group, these differences did not reach statistical significance.
Biomarker expression across BMI values and cancer grades
Scatter plot showing biomarker expression across BMI values and cancer grades.
Expression of biomarkers across different sample types, categorized by BMI. Panel A shows the expression of miR-143-5p, Panel B shows miR-744-5p, Panel C shows HIF-1A
Bar charts illustrating the expression of miR-143-5p, miR-744-5p, and HIF-1A across different sample types, categorized by BMI.Correlation analysis of biomarkers across BC cohorts
In the LBT group, the correlation between miR-143-5p and HIF1A was -0.52, suggesting a negative correlation between them. In the control group, miR-143-5p exhibited a strong, highly significant positive correlation with miR-744-5p (r = 0.88, P < 0.001) suggesting co-expression. However, no significant correlations were found with HIF1A (control: r = -0.32, P = 0.23). Correlation analysis within the LAT group revealed a moderate positive correlation between miR-143-5p and miR-744-5p (r = 0.22). The correlations between miR-143-5p and HIF1A (r = 0.01) and between miR-744-5p and HIF1A (r = -0.03) were negligible and not statistically significant (P = 0.89). In contrast, a strong positive correlation was observed between miR-143-5p and miR-744-5p in the HBT group (r = 0.835). A strong positive correlation was observed between miR-143-5p and miR-744-5p in the HAT group (r = 0.83) indicating that their expression levels tend to change in the same direction. In contrast, correlations between HIF1A and both miRNAs were negligible and not statistically significant in all groups analyzed (HAT group: miR-143-5p vs HIF1A, r = 0.10; miR-744-5p vs HIF1A, r = -0.03, P = 0.89; control group: miR-143-5p vs HIF1A, r = -0.25, P = 0.32; miR-744-5p vs HIF1A, r = -0.32, P = 0.23).
Diagnostic Performance of BC Biomarkers
Our analysis revealed strong diagnostic performance for specific biomarkers in distinct patient subgroups. miR-143-5p in the LBT group demonstrated exceptional potential as a standalone diagnostic test (AUC = 0.83). HIF1A in the HBT group also showed reliable performance (AUC = 0.77). While slightly lower than the top biomarkers in Table 4, its strength suggests it would be a valuable contributor to a multi-biomarker panel for BC diagnosis.
miR-143-5p (AUC = 0.66) and HIF1A (AUC = 0.65) in the HAT group, along with miR-744-5p in the LBT and HAT groups (AUC = 0.63 and 0.60, respectively), demonstrated only moderate discriminatory power. Clinically, such markers are generally not suitable for standalone diagnosis. However, they should not be dismissed entirely, as they could still contribute valuable information to a multivariate diagnostic algorithm where the combination of several moderate markers can achieve high overall accuracy.
Comparative Evaluation of miR-143-5p, miR744-5p, and HIF1A in BC
Comparison
Biomarker
AUC
95% CI
LBT vs Control
miR-143-5p
0.83
0.68–0.94
LAT vs Control
miR-744-5p
0.63
0.44–0.80
HIF1A
0.15
0.04–0.31
All
<0.40
NA
HBT vs Control
miR-143-5p
0.44
0.26–0.62
miR-744-5p
0.33
0.16–0.52
HAT vs Control
HIF1A
0.77
0.61–0.91
miR-143-5p
0.66
0.47–0.82
miR-744-5p
0.60
0.41–0.78
HIF1A
0.65
0.46–0.81
AUC, area under the curve; BC, breast cancer; CI, confidence interval; HAT, high-grade after treatment; HBT, high-grade before treatment; HIF1A, hypoxia-inducible factor 1-alpha; LAT, low-grade after treatment; LBT, low-grade before treatment; miR, microRNA; NA, not applicable.
DISCUSSION
This study aimed to analyze the expression of a panel of biomarkers, including miR-143-5p, miR-744-5p, and HIF1A, across different BC cohorts (HAT, HBT, LAT, and LBT) and to identify potential associations between these biomarkers and specific cancer grades. Crucially, miRNA expression patterns are not uniform across different breast tumor stages (luminal A, luminal B, basal-like, and HER2+), highlighting the importance of cancer stage classification in miRNA studies.14 Histological grade has also been identified as a major source of variation in BC miRNA expression, potentially even more influential than other factors.15 Our findings revealed distinct patterns of expression for these biomarkers in relation to age, BMI, and cancer grade, suggesting complex regulatory mechanisms and potential roles in the biological characteristics of each subgroup. miR-143-5p expression revealed higher levels in the obese group, particularly in the HAT and LBT sample types. In contrast, the control samples exhibited consistently low expression. This suggests a potential positive correlation between BMI and miR-143-5p expression.16 miR-744-5p exhibited higher expression in specific sample types (HBT and LAT) within the obese group, while other samples (HAT) and the control group showed lower expression levels. Previous studies have reported alterations in microRNA expression in several diseases, including BC and obesity.17
Regarding BMI and age, the control group had the lowest median BMI and age, with narrower IQRs, while BC cohorts showed higher median BMIs and ages with broader IQRs. The age distribution of patients with BC in this study is comparable to previous Iraqi research18,19, which identified age ≥ 50 years as a significant risk factor. According to these findings20,21, the risk of BC can occur at any age, but it increases in middle age and beyond the age of 50. HIF1A exhibited higher expression in the obese group, most notably in HBT and LAT samples, suggesting a potential link between hypoxia and this specific cohort (high-grade before treatment). This is a crucial finding, as it suggests HBT tumors may possess a more hypoxic microenvironment, potentially driving their aggressive behavior. In contrast, HIF1A levels were stable in control, HAT, and LBT samples but exhibited greater variability in HBT and LAT groups. Obesity-related increased expression of HIF1A in HBT and LAT samples suggests a potential link between obesity and increased cellular stress or hypoxia. In this study, HIF1A expression showed moderate significance with (AUC > 0.60) in high-grade cancer before and after treatment. This partially agrees with the results of another study22, which indicated that the HIF1A gene can be a good diagnostic marker. Our analysis showed significant distributional disparities. Family history was found to be imbalanced, with 78% reporting no disease history and 22% reporting a disease history. The "other diseases" variable was similarly skewed, with 97% indicating no comorbidities. The noticeable difference in counts between family history categories suggested that family history plays a significant role in diagnosis and treatment of BC.23
Our correlation analysis revealed distinct co-expression patterns for miR-143-5p, miR-744-5p, and HIF1A across patient subgroups, suggesting differential regulatory mechanisms based on disease state and treatment. Notably, we observed a very strong, significant positive correlation between miR-143-5p and miR-744-5p in the control (r = 0.80, P < 0.001), HBT (r = 0.835), and HAT (r = 0.83) groups. This consistent synchrony suggests a potential co-regulation or shared regulatory pathway for these 2 miRNAs in the absence of advanced disease or following certain treatments. In stark contrast, these relationships were attenuated in the LAT group (r = 0.22), implying that treatment and/or tumor grade may disrupt this coordinated expression. Furthermore, correlations between the miRNAs and HIF1A were consistently negligible or very weak across all groups (e.g., r = 0.01 to 0.10) and were not statistically significant. The lack of a strong linear relationship suggests that HIF1A expression is likely independent of these specific miRNAs in this cohort or that its regulation involves more complex, nonlinear interactions.
Significantly higher levels of miR-143-5p observed in LBT (low-grade before treatment) and HAT (high-grade after treatment) point to a possible function in the pretreatment condition or in response to treatment. miR-744-5p demonstrated a moderate diagnostic potential in LBT and HAT comparisons, with AUC values exceeding 0.60, suggesting potential diagnostic utility when combined with other markers. Increasing evidence has shown that miRNAs function as oncogenes or anti-oncogenes and are involved in all types of important physiological processes in cancer initiation, progression, treatment, and drug resistance.24 MicroRNAs have emerged as important posttranscriptional regulators of HIF1A. Several studies have demonstrated that specific miRNAs can directly target the 3' untranslated region (3' UTR) of HIF1A mRNA, thereby modulating its expression and activity. Among these, miR-143-5p has been shown to function as a tumor suppressor by downregulating HIF1A. Previous studies have suggested that certain miRNAs may influence hypoxia responses through posttranscriptional regulation of HIF1A.
Analysis of AUC values revealed significant differences in the diagnostic potential of 3 biomarkers across 4 sample comparisons in each cancer group compared with controls. miR-143-5p showed high diagnostic accuracy, with an AUC value of 0.83 in the LBT group (AUC > 0.70 indicates good diagnostic accuracy). MiR-744-5p showed a moderate potential in the LBT vs control comparison (an AUC of 0.63). HIF1A exhibited a high diagnostic potential in the HBT group with an AUC value of 0.774 and a moderate diagnostic potential in the HAT group with an AUC value of 0.647.
The remaining measurements of biomarkers across the other sample comparisons displayed a low diagnostic accuracy, with AUC values below 0.50, indicating poor discriminatory ability.
CONCLUSION
The current study showed the importance of evaluating different miRNAs and HIF1A expression as potential predictive diagnostic markers for the early detection of BC. In addition, we evaluated the role of these biomarkers in different grades and treatments. Relative gene expression analysis (fold change) suggested that miR-143-5p, miR-744-5p, and HIF1A could potentially form reliable diagnostic panels for BC, particularly when combined with other biomarkers.
ACKNOWLEDGMENTS
The authors appreciate the staff of the Department of Biotechnology, College of Science, University of Anbar, for facilitating this work.
FUNDING
The research is self-funded.
ETHICAL CONSIDERATIONS
This study was approved by the Council of the Institute of Genetic Engineering and Biotechnology for Postgraduate Studies at the University of Baghdad, and the study protocol was approved by the Ethics Committee of the Ministry of Health and Environment- Al-Anbar Directorate of Health (AO No. 1812).
DATA AVAILABILITY
The data related to the study are presented in the article.
AI DISCLOSURE
No AI tool was used for preparing the manuscript of this study.
RasheedMNEvaluation of DNA methylation of MAP9 gene in breast cancer as epigenetic biomarker.Biomedicine2022422227229SalihAMAzizIHMohsinFYRole of miRNA 199a-5p expression in Iraqi women with breast cancer.Al-Rafidain J Med Sci202351SS94S9910.54133/ajms.v5i1S.308HashimHTRamadhanMAThebanKMBcharaJEl-Abed-El-RassoulAShahJAssessment of breast cancer risk among Iraqi women in 2019.BMC Womens Health202121141241210.1186/s12905-021-01557-1AlwanNASBreast cancer among Iraqi women: preliminary findings from a regional comparative breast cancer research project.J Glob Oncol20162525525810.1200/JGO.2015.003087GandelliniPDoldiVZaffaroniNmicroRNAs as players and signals in the metastatic cascade: implications for the development of novel anti-metastatic therapies.Semin Cancer Biol20174413214010.1016/j.semcancer.2017.03.005KimJYaoFXiaoZSunYMaLMicroRNAs and metastasis: small RNAs play big roles.Cancer Metastasis Rev201837151510.1007/s10555-017-9712-yXuJLiXZhangPLuoJMouELiuSmiR-143-5p suppresses breast cancer progression by targeting the HIF-1α-related GLUT1 pathway.Oncol Lett202223514714710.3892/ol.2022.13268MansooriBKianiSMezajinAAZandiPBanaieHRostamzadehDMicroRNA-143-5p suppresses ER-positive breast cancer development by targeting oncogenic HMGA2.Clin Breast Cancer2023237e480e49010.1016/j.clbc.2023.07.011PengXGaoHXuRWangHMeiJLiuCThe interplay between HIF-1α and noncoding RNAs in cancer.J Exp Clin Cancer Res2020391272710.1186/s13046-020-1535-yEngstromMJOpdahlSHagenAIRomundstadPRAkslenLAHaugenOAMolecular cohorts, histopathological grade and survival in a historic cohort of breast cancer patients.Breast Cancer Res Treat2013140346347310.1007/s10549-013-2647-2SemenzaGLHypoxia-inducible factors: mediators of cancer progression and targets for cancer therapy.Trends Pharmacol Sci201233420721410.1016/j.tips.2012.01.005BuiBPNguyenPLLeeKChoJHypoxia-inducible factor-1: a novel therapeutic target for the management of cancer, drug resistance, and cancer-related pain.Cancers (Basel)202214246054605410.3390/cancers14246054ShihJWKungHJLong non-coding RNA and tumor hypoxia: new players ushered toward an old arena.J Biomed Sci2017241535310.1186/s12929-017-0358-4UvaPCossu-RoccaPLoiFPiraGMurgiaLOrruSmiRNA-135b contributes to triple negative breast cancer molecular heterogeneity: different expression profile in basal-like versus non-basal-like phenotypes.Int J Med Sci2018156536548SalesACVGomes da SilvaIIFLeiteMCBCoutinhoLLReisRBACCastoldiAMirna21 expression in the breast cancer tumor tissue is independent of neoadjuvant chemotherapy.Breast Cancer (Dove Med Press)20201214115110.2147/BCTT.S269519ChanDSMVieiraARAuneDBanderaEVGreenwoodDCMcTiernanABody mass index and survival in women with breast cancer: systematic literature review and meta-analysis of 82 follow-up studies.Ann Oncol201425101901191410.1093/annonc/mdu042KasiappanRRajarajanDRole of microRNA regulation in obesity-associated breast cancer: nutritional perspectives.Adv Nutr20178686888810.3945/an.117.015800AbdelrahmanSAliBAl-KhalidyNAl-HashimiARisk factors of breast cancer among Iraqi women.J Contemp Med Sci201951510.22317/jcms.v5i3.609Al-KhafajiASKHadeIMAl-NaqqashMAAlnefaieGOPotential effects of miR-146 expression in relation to malondialdehyde as a biomarker for oxidative damage in patients with breast cancer.World Acad Sci J2023511910.3892/wasj.2023.187MakkiJDiversity of breast carcinoma: histological cohorts and clinical relevance.Clin Med Insights Pathol20158CPath-S31563OzmenVBreast cancer in Turkey: clinical and histopathological characteristics (analysis of 13,240 patients).J Breast Health20141029810510.5152/tjbh.2014.1988HayesDFIsaacsCStearnsVPrognostic factors in breast cancer: current and new predictors of metastasis.J Mammary Gland Biol Neoplasia20016437539210.1023/a:1014778713034LiuLHaoXSongZZhiXZhangSZhangJCorrelation between family history and characteristics of breast cancer.Sci Rep20211116360636010.1038/s41598-021-85899-8LiXZengZWangJWuYChenWZhengLMicroRNA-9 and breast cancer.Biomed Pharmacother202012210968710968710.1016/j.biopha.2019.109687