Circulating muscle- and inflammation-related microRNAs in breast cancer survivorship: associations with treatment, timing, and age

Circulating muscle- and inflammation-related microRNAs in breast cancer survivorship: associations with treatment, timing, and age | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Circulating muscle- and inflammation-related microRNAs in breast cancer survivorship: associations with treatment, timing, and age Yanping Jiang, Heidi Annuk, Nicola Miller, Kerin Michael, Sanjeev Gupta, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9039383/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Purpose Cancer and its treatments often lead to inflammation, muscle problems, and ongoing loss of physical function, as reflected by alterations of circulating microRNAs. In this study, we measured levels of selected muscle- (miR-1, miR-133, miR-208, miR-486, miR-499) and inflammation-related (miR-21, miR-126, miR-146, miR-155) miRNAs in breast cancer patients, and aimed to explore, using a stratifies analysis, how their levels relate to cancer subtype, treatment type, treatment duration, and age. Methods We collected 77 plasma samples from pre-treated and post-treated breast cancer patients, and healthy controls. Circulating miRNA levels were measured using quantitative RT-PCR. We compared miRNA levels across different breast cancer subtypes, treatment types, treatment duration, and age groups. Results Pre-treated breast cancer patients did not show significant changes in the selected miRNAs compared to healthy controls. However, different breast cancer subtypes showed distinct patterns: Luminal A predominantly affected muscle-related miRNAs, and Luminal B inflammation-related miRNAs. Cancer treatment, especially surgery and chemotherapy, led to significant changes in miR-21 and miR-486, mainly within the first 91 days after diagnosis. Increases in miR-133 and miR-486 after treatment were mostly seen in patients over 50 years old. Conclusions Circulating muscle- and inflammation-related miRNAs display distinct expression patterns associated with breast cancer subtype and treatment. Specifically, miR-21, miR-133, and miR-486 demonstrate sensitivity to cancer treatment exposure, timing, and patient age. Implications for cancer survivors: Our findings support further investigation of these miRNAs as candidate biomarkers in prospective studies, including their potential use for monitoring physiological responses during exercise-based cancer rehabilitation. miRNA muscle inflammation breast cancer survivorship Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction In 2022, breast cancer has surpassed lung cancer as the most frequently diagnosed malignancy in female, with more than 2.3 million cancer cases. The advances in multimodal therapy have given rise to an increased chance of cure in 70–80% of patients [ 1 – 2 ]. However, cancer- and cancer treatment-induced complications can exert negative effects on treatment efficacy, and even significantly increase morbidity and mortality. Sarcopenia refers to the loss of muscle mass and strength, and is one of the severe complications that breast cancer survivors face during and after treatment. Research has shown that the prevalence of sarcopenia ranges from 30% to 55% in breast cancer patients, and it is linked to a higher chance of chemotoxicity, functional decline, and poorer quality of survivorship [ 3 ]. Sarcopenic survivors have a 2.86-fold greater all-cause mortality compared to their non-sarcopenic counterparts [ 4 ]. The mechanisms for cancer- and cancer treatment-induced sarcopenia are complex, and one of these mechanisms may be involved in inflammation [ 5 – 6 ]. Inflammation can over-stimulate the immune system, which fuels energy expenditure, thus leading to a shortage of stored reserves and affecting general metabolism. Such a dynamic shift may result in skeletal homeostasis toward muscle loss [ 7 ]. MicroRNAs (miRNAs) are a group of short, non-coding RNAs, with 20–22 nucleotides, and evidence has demonstrated miRNAs play an important role in modulating the pathway of skeletal muscle turnover and inflammation[ 8 – 9 ]. For example, Narasimhan et al [ 10 ] found eight upregulated miRNAs in cachectic cancer patients compared to their non-cachectic counterparts by next-generation sequencing. Ingenuity pathway analysis showed that the targets of these miRNAs were known to engage in myogenesis, inflammation, and immune response. These results indicated that miRNA may directly or indirectly be involved in muscle development and function and the abnormal expression of miRNAs may imply muscle loss and dysfunction during cancer survivorship. While research has shown that exercise can restore muscle loss and strength by improving systemic inflammation and this process is accompanied by the alterations of miRNAs. In our previous work, we reviewed the role of miRNA in both cancer- or cancer treatment-induced muscle loss and exercise. Generally, cancer itself and cancer treatment can cause muscle damage and inflammation, thus leading to physical inability and poor quality of life, while exercise can trigger adaptive responses and facilitate organ recovery, reflected by altered miRNA expression in damaged organs. This indicates that muscle- and inflammation-related miRNAs may be potential molecular biomarkers to monitor the progress of exercise-based cancer rehabilitation during cancer survivorship [ 11 ]. However, given the heterogeneity of breast cancer biology and its treatment, initial exploratory studies are needed to determine the association between miRNAs expression profiles and specific cancer subtypes or cancer treatment. Therefore, based on our previous work, we selected a panel of muscle-specific (miR-1, miR-133, miR-208, miR-486, miR-499) and inflammation-related (miR-21, miR-126, miR-146, and miR-155) miRNAs to conduct exploratory research on their associations with breast cancer subtypes, treatment, timing, and age during cancer survivorship. 2. Methods 2.1 Ethics approval and plasma sample information This study was performed in line with the principles of the Declaration of Helsinki and the Clinical Research Ethics Committee of the University Hospital of Galway approved the use of archived human plasma samples (ethical approval number: Ref: C.A. 2828). The commercial healthy plasma pool was purchased from Amsbio company, characterized by one African American and one Hispanic American, with an average age of 52. All archived plasma samples were obtained from the Cancer Biobank, Discipline of Surgery, University of Galway: 5 healthy archived samples were from healthy controls, with a median age of 52.2 (ranging from 51 to 55 years old). The archived samples from breast cancer patients were included when their donors met the following criteria: 1) aged over 18 years old and 2) diagnosed with breast cancer. However, samples were excluded if their donors had: 1) breast cancer with rare subtypes or 2) confirmed to have other cancer history in addition to breast cancer. A total of 71 archived samples from breast cancer patients were obtained. These samples came from breast cancer patients aged from 24 to 88 years old, with a median age of 59. Among these 71 plasma samples, there were 29 pre-treated samples (from patients who did not receive any treatment when the samples were collected) and 42 post-treated samples (from patients who received cancer treatment when the samples were collected). Among these samples, there were 14 paired samples where pre-treated and post-treated samples were obtained from the same patients. There were also 15 pre-treated samples and 28 post-treated samples obtained from different patients, classified as non-paired samples. Patients’ characteristics are shown in Table 1 . Table 1 Patients’ characteristics of included samples Characteristics Healthy Pre-treatment Post-treatment Number of Samples (N) 6 29 42 Age Median (year) 52 50 62 50 - 14 30 Subtypes (N) Luminal A - 15 25 Luminal B - 5 6 HER2+ - 5 5 Basal-like - 4 6 Treatment received Surgery - - 6 Chemotherapy - - 27 Endocrine therapy - - 4 Combined therapy - - 5 HER2+: human epidermal growth factor receptor 2 positive 2.2 RNA isolation Archived plasma samples were stored at -80℃, and thawed at 37℃ water bathing before RNA isolation. Plasma miRNA was isolated using plasma/serum miReasy Kit (Qiagen, Germany) according to the manufacturer’s instructions. The plasma aliquot was transferred to a new microcentrifuge tube with five times a Qiazol mixture without spike-ins as RNU6B was used as a reference miRNA in quantitative reverse transcription polymerase chain reaction (qRT-PCR). RNA concentration was measured by NanoDrop spectrophotometry (NanoDrop ND-100 Technologies Inc., DE USA). 2.3 Quantification of miRNA expression by qRT-PCR The reverse transcription (RT) was performed by using the TaqMan microRNA reverse transcription kit (applied biosystem) with 50 nanograms of miRNA in a 15µL reaction system (RNA: 5µL, RT master mix: 7µL, primer: 3µL) according to the manufacturer’s instruction. The reaction conditions in the thermal cycler for miRNA-specific RT reaction were as follows: 16℃ for 30 min, 42℃ for 30 min, 85℃ for 5 min, and 4℃ for hold. All primers’ information was shown in Table S1 . qRT-PCR was then performed on MicroAmp® Fast 96-Well Reaction Plate (applied biosystem) with a condition of holding at 50℃ for 2 min, further holding at 95℃ for 10 min, and then running 40 cycles for 0.15 min followed by holding at 60℃ for 1 min. All assays were conducted in triplicates. A comparative cycle (Ct) threshold was used to calculate the miRNA expression level, and the relative expression level of selected miRNAs in each plasma was normalized to that of RNU6B, and calculated as (2^ −ΔCt ). 2.4 Statistical analysis Statistical analysis was performed by using SPSS 25.0 and GraphPad Prism 8.0. Considering the characteristics of relative miRNA expression levels, miRNA data were log10-transformed (Log10) for analysis. The expression of miRNA data was presented with Mean ± standard deviation (SD). The student’s t-test or ANOVA were performed when data were normally distributed; the Mann-Whitney U test or Kruskal-Wallis test was performed when data were not normally distributed. For multiple groups’ comparison, significance values have been adjusted by the Bonferroni correction. Paired t-test or Wilcoxon signed-rank test was performed for paired sample analysis. All p values were two-sided and the significance level is 0.05. 3. Results 3.1 Circulating miRNA profiles in healthy controls and pre-treated breast cancer patients We first measured circulating levels of selected muscle-specific and inflammation-related miRNAs in healthy controls (including a healthy plasma pool and five healthy plasma samples) and pre-treated breast cancer patients. Muscle-related miRNAs such as miR-1, miR-133, miR-486, and miR-499 were found at low levels in healthy individuals (Fig. S1 ), while miR-208 was not detected in most samples (data not shown). Comparison of pre-treated breast cancer patients (n = 29) with healthy controls (n = 6) revealed no statistically significant differences in the expression of any selected miRNAs, despite trends toward increased miR-21 and miR-499, and decreased miR-133, miR-486, and miR-155 (Table 2 ). These results indicate that, at the group level, breast cancer alone was not associated with substantial alterations in circulating muscle- or inflammation-related miRNAs prior to treatment. In this study, miR-451 was included as the biomarker monitoring hemolysis in plasma samples based on literature [ 12 ]. Although we used clear and transparent plasma samples, miR-451 showed some significance in our results. This may be in part explained by that miR-451 can be influenced by cancer and cancer therapy [ 13 – 14 ], and may not be a reliable biomarker for hemolysis in this context. Therefore, the results of miR-451 were presented in the following Tables and Figures without interpretation. 3.2 Association between breast cancer subtype and circulating miRNA expression Because breast cancer is biologically diverse, we examined circulating miRNA levels across different molecular subtypes using only pre-treated samples. Luminal A breast cancer was associated with lower circulating levels of muscle-related miRNAs compared to healthy controls, particularly miR-486 (0.68-fold, p = 0.047, Fig. 1 , Table S2). MiR-133 (0.06-fold, p = 0.081) was also lower in Luminal A patients, though this was not quite significant. In Luminal B breast cancer, inflammation-related miRNAs were more affected. MiR-21 (19.32-fold, p = 0.008), miR-126 (1.27-fold, p = 0.062), and miR-146 (1.31-fold, p = 0.065) were increased in Luminal B patients. In human epidermal growth factor receptor 2 positive (HER2+) subtype, miR-21 (14.10-fold, p = 0.042) was significantly increased, but this trend was not seen in other inflammation-related miRNAs. No significant differences were observed for the Basal-like subtype. These findings indicate that muscle- and inflammation-related circulating miRNAs may display subtype-specific expression patterns prior to treatment. However, since the healthy controls used in this study is mixed sources and sample sizes in controls and each subtype are relatively small, these results are more descriptive rather than definitive, and should be interpreted cautiously. The Student’s t-test or Mann-Whitney U test was performed to compare different cancer subtypes to healthy controls. ANOVA or Kruskal-Wallis test was performed to compare the expression levels of selected miRNAs among different cancer subtypes, p values for within-group comparisons have been adjusted by the Bonferroni correction. *represents p < 0.05; **represents p < 0.01; ***represents p < 0.001. Table 2 The expression of selected miRNAs in plasma samples from healthy controls and breast cancer patients miRNAs Healthy vs pre-treated Paired samples Non-paired samples Healthy plasma samples (N = 6) Pre-treated plasma samples (N = 29) Fold change P value Pre-treated samples (N = 14) Post-treated samples (N = 14) Fold change P value Pre-treated samples (N = 15) Post-treated samples (N = 28) Fold change P value miR-451 3.05 (0.69) 3.25 (1.33) 1.07 0.718 0.24(1.13) 1.07(1.32) 4.46 0.062 3.21(1.53) 3.66(1.29) 1.14 0.320 miR-1 0.37 (0.85) 0.35 (0.60) 0.95 0.927 -0.31(0.60) 0.12(0.78) - 0.125 0.46(0.59) 0.53(0.68) 1.15 0.725 miR-21 0.05 (0.43) 0.51 (0.70) 10.2 0.174 0.30(0.70) 1.03(0.4) 3.43 0.002 3.20(0.65) 3.14(0.58) 0.98 0.752 miR-126 2.79 (0.62) 3.10 (0.65) 1.11 0.295 0.21(0.66) 0.76(0.73) 3.62 0.038 0.59(1.12) 1.17(0.80) 1.98 0.059 miR-133 1.01 (0.81) 0.60 (1.07) 0.59 0.375 -0.40(1.05) 0.26(0.94) - 0.053 2.97(0.90) 2.81(1.07) 0.95 0.541 miR-146 2.61 (0.68) 2.70 (1.18) 1.03 0.535 -0.21(1.41) 0.53(1.3) - 0.083 1.36(0.81) 1.27(0.68) 0.93 0.715 miR-155 1.41 (0.67) 1.14 (0.97) 0.81 0.881 -0.51(1.10) -0.02(0.96) - 0.152 0.64(0.66) 0.71(0.60) 1.11 0.739 miR-486 3.25 (0.61) 2.80 (1.37) 0.86 0.782 -0.35(1.37) 0.61(1.06) - 0.002 2.70(1.42) 3.51(1.09) 1.30 0.037 miR-499 -0.66(0.70) -0.19(0.85) 3.74 0.342 0.50(1.12) 0.91(0.72) 1.82 0.239 -0.27(0.62) -0.07(0.64) - 0.335 For paired samples, paired t-test or Wilcoxon signed-rank test was applied. For unpaired comparisons, Student’s t-test or Mann–Whitney U test was applied. 3.3 Impact of cancer treatment on circulating miRNA expression To assess how cancer treatment affects circulating miRNA levels, we compared post-treated and pre-treated samples using both unpaired and paired analyses. In unpaired analyses, post-treated patients had significantly higher levels of miR-486 than pre-treated patients (Table 2 ). Paired analyses showed similar results of miR-486. Besides, paired analyses also found significant increases in miR-21 and miR-126 after treatment, which were not seen in unpaired comparisons. Other miRNAs, such as miR-133 and miR-146, showed similar trends toward change after treatment but were not statistically significant. These results suggest that changes in circulating miRNA profiles are mainly linked to cancer treatment, not just the diagnosis itself. 3.4 Treatment modality–specific miRNA responses We then looked at how different treatment types affected circulating miRNAs. Both surgery and chemotherapy led to significant increases in miR-21 and miR-486 when comparing samples before and after treatment (Fig. 2 A-C). These trends were seen in both paired and unpaired analyses, but were more often significant in paired comparisons. Endocrine therapy was not associated with significant changes in any of the examined miRNAs (Fig. 2 D). In patients receiving combined therapy, which most commonly included surgery and chemotherapy, miR-486 again demonstrated a significant increase compared with pre-treated samples (Fig. 2 E). Across treatment modalities, miR-21 exhibited a consistent tendency toward increased expression following treatment exposure, supporting its sensitivity to treatment-related physiological changes. 3.5 Subtype-specific treatment-associated miRNA changes We also looked at treatment-related miRNA changes within each breast cancer subtype. In Luminal A, treatment led to significant increases in miR-486 and miR-21 in paired analyses (Fig. 3 A), and an increase in miR-133 in unpaired analyses (Fig. 3 B). Although there were some differences between paired and unpaired results, the overall pattern was similar. In Luminal B breast cancer, inflammation-related miRNAs miR-146 and miR-155 demonstrated significant decreases following treatment, despite modest elevations in pre-treated patients relative to healthy controls (Fig. 3 C). In HER2 + breast cancer, treatment exposure was associated with increased circulating miR-133 and miR-155 (Fig. 3 D). No statistically significant treatment-associated changes were observed in the Basal-like subtype (Fig. 3 E). These results show that the way circulating miRNAs respond to cancer treatment depends on the breast cancer subtype, likely due to differences in tumor biology and treatment approaches. (A) paired surgery group: 5 pre-treated vs 5 post-treated; (B) paired chemotherapy group: 8 vs 8, and (C)non-paired chemotherapy group (15 vs 19); (D) endocrine therapy:15 vs 4; (E) combined therapy: 15 vs 5 (one paired), and the paired samples in this group were regarded as independent samples. Paired t-test or Wilcoxon signed-rank test was performed for paired samples, Student’s t-test or Mann-Whitney U test was performed for non-paired samples. *represents p < 0.05; **represents p < 0.01; ***represents p < 0.001. (A) paired Luminal A: 10 vs 10; (B) non-paired Luminal A: 5 vs 15; (C)Luminal B: 5 vs 6 (one paired); (D) HER2+: 5 vs 5 (two paired); (E) Basal-like: 4 vs 6 (1 paired). Due to the small number of paired samples, the paired samples in these groups were regarded as independent samples. Paired t-test or Wilcoxon signed-rank test was performed for paired samples, Student’s t-test or Mann-Whitney U test was performed for non-paired samples. *represents p < 0.05; **represents p < 0.01; ***represents p < 0.001. 3.6 Association between treatment duration and circulating miRNA expression To examine temporal patterns, post-treated samples were stratified by time from diagnosis to blood collection (Table S3). Circulating miRNA changes were most pronounced within the first 91 days following diagnosis (Fig. 4 ). During this early period, miR-133, and miR-486 were significantly elevated compared to pre-treated samples. After 91 days, circulating miRNA levels mostly returned to pre-treatment values, and there were no significant differences at later time points. Most samples from the first 91 days came from patients having surgery or neoadjuvant chemotherapy, showing that the early treatment phase is a time of greater physiological change. We also looked at miRNA levels by age group (age distribution in Table S4). In patients 50 years or younger, there were no significant differences between pre-treated and treated groups (Fig. 5 ). In patients over 50, treatment led to significant increases in miR-133 and miR-486. These results suggest that age affects how circulating miRNAs respond to cancer treatment, especially for muscle-related miRNAs that are important for physical function and recovery. The bracket represents the p value from ANOVA or the Kruskal-Wallis test; the solid line represents the p value from within groups comparison, and significance values have been adjusted by the Bonferroni correction. *represents p < 0.05; **represents p < 0.01; ***represents p < 0.001. Student t-test or Mann-Whitney U test was performed. *represents p < 0.05; **represents p < 0.01; ***represents p < 0.001. 4. Discussion 4.1 Muscle- and inflammation-related miRNAs have different expression patterns among breast cancer subtypes The expression of miRNA was influenced by multiple factors. Research has demonstrated that the miRNAs expression profile in tumor tissue is different from that in circulation, and some of the differentially expressed circulating miRNAs are novel, denoting that miRNAs may be selectively released into circulation, and this may be one of the factors affecting miRNA expression in circulation [ 15 – 16 ]. Similarly, our results showed that muscle-enriched miRNAs such as miR-1, miR-133, miR-486, and miR-499 had a low expression in the plasma of healthy controls, and this may support their property of selective release into circulation. Blenkiron et al. [ 17 ] profiled miRNA expression in 93 breast cancer patients, and identified 133 differentially expressed miRNAs between healthy breast tissue and breast cancer tissue. Furthermore, a body of miRNAs was differentially expressed among these cancer subtypes, and certain miRNAs were implicated in clinicopathological factors, indicating that the cancer subtype may influence miRNA expression in breast cancer. Nevertheless, whether the selected inflammation- and muscle-related miRNAs are affected by cancer subtypes remains to be unclear. In this exploratory study, comparisons of healthy controls and pre-treated samples showed that none of these select miRNAs were significantly different. However, this changed when stratified analyses were performed across cancer subtypes: muscle-related miRNA miR-486 (p = 0.047) and miR-133 (p = 0.081, close to significance level) was decreased in Luminal A; inflammation-related miR-21 (p = 0.008) in Luminal B was 19-fold greater than that in healthy controls, miR-126 (p = 0.062) and miR-146 (p = 0.065) increased by about 30% in cancer patients, and it almost reached the statistical significance. These results revealed that Luminal A may have a greater impact on changes in muscle-related miRNAs, while Luminal B may have a greater impact on inflammation-related miRNAs. 4.2 miRNAs have different responses to cancer treatment in breast cancer Since miRNA signature was different among breast cancer subtypes and each subtype might have different treatment strategies, it is therefore assumed that miRNA signature may have different responses to different cancer treatments [ 18 ]. Research has shown that miR-30a-3p, miR-30c, and miR-182 can predict the clinical benefit of tamoxifen in estrogen receptor positive breast cancer; miR-21, miR-125b, and miR-331, may be associated with the response to HER2-targeted therapy or the modulation of HER2 expression [ 18 ]. In our study, cancer treatment changed the expression of muscle- and inflammation-related miRNAs. Compared to pre-treated samples, miR-486 significantly increased following treatment; however, miR-486 had decreased expression in post-treated samples when compared to healthy controls. This may be explained that treatment rescued the damage caused by cancer itself. MiR-21 and miR-126 significantly increased after cancer treatment in paired samples analysis, indicating their potential role as biomarkers monitoring cancer treatment-induced inflammation. In addition, miR-21 and miR-486 showed significant sensitivity to surgery and chemotherapy. In Luminal A breast cancer, miR-21, miR-133, and miR-486 significantly responded to treatment; miR-146 and miR-155 responded to treatment in Luminal B and HER2 + breast cancer, but their tendency to treatment was opposite in these two cancer subtypes. These results may imply that the changes of miRNAs were likely to be treatment modality-specific or subtype-specific. However, given the small sample size in each subgroup, the interpretation should be cautious and confirmatory studies with larger sample size are needed. 4.3 The implication of miR-486, miR-133, and miR-21 during cancer survivorship MiR-486 and miR-133 are muscle-enriched miRNAs, and play an important role in muscle development and function. Studies showed mice with Duchenne muscular dystrophy had a lower expression of miR-486 in muscle compared to their healthy counterparts; miR-486 knockout mice were likely to develop dysfunctional muscular structure in skeletal muscle, including disrupted myofiber architecture and decreased myofiber size, thus leading to exacerbated locomotor activity and metabolic defects, indicating its crucial role in maintaining muscle function [ 19 ]. In a recently published research, Wang et al[ 20 ] investigated the role of miR-486 in muscle function in breast cancer mouse models and found that miR-486 significantly prevented a cancer-induced reduction in muscle contraction force, grip strength, and rotarod performance. Besides, overexpression of miR-486 could reverse cancer-induced muscle change by modulating the miR-486-PTEN-AKT signaling axis. Our research showed that except for a slight increase in Luminal B, plasma miR-486 generally decreased in breast cancer patients compared to its healthy controls despite a significant difference only in Luminal A, and this is in line with previous reports both in patients and mouse models [ 20 – 21 ]. Additionally, the expression of miR-486 was linked to cancers and cancer treatment. Research has shown that circulating miR-486 in non-small lung cancer and cervical cancer was higher in cancer patients than in healthy controls [ 22 – 23 ]. Besides, plasma miR-486 in small lung cancer significantly increased after surgical resection, and such an increase could persist up to one year after surgery [ 22 ]. In our results, miR-486 significantly increased after treatment regardless of surgery and chemotherapy, and such an increase is more prominent in Luminal A and Luminal B. Normally, muscle-related miRNAs have a very low expression in circulation in healthy people, which was also confirmed in our study [ 24 ]; in this case, the high expression of circulating miR-486 is likely to be a stress response to treatment, which is contradictory to the aforementioned findings that overexpressed miR-486 in muscle tissue improve muscle function. One of possible explanation for this contradiction is that muscle cells were damaged, died, or even broken down following treatment, thus releasing miR-486 into the circulating system. In the context of exercise, research has shown that circulating miR-486 significantly decreases regardless of acute or chronic exercise, and the changes of miR-486 are negatively associated with maximal oxygen consumption [ 25 ]. These results suggested that miR-486 may be a promising candidate biomarker for exercise-based cancer rehabilitation, but further prospective studies are needed. Nie et al [ 26 ] demonstrated that miR-133 deficient mice had a low maximal exercise capacity, and such a compromised exercise capacity was impaired via depressing the transcription of mitochondrial biogenesis regulators. In addition, instead of in miR-133a-deficient mice, endurance exercise only elevated the transcriptional level of miR-133a as well as mitochondrial biogenesis in wild-type mice. In a case-control study, high expression of serum miR-133 was reported in breast cancer patients with doxorubicin-induced cardiotoxicity [ 27 ]. These results suggest that miR-133 may be a potential biomarker for cardiovascular function during treatment. However, miR-133 is not as sensitive to cancer and cancer treatment as miR-486 was in our research. This may be explained by their different roles in muscle: miR-486 is more engaged in maintaining muscle function, while miR-1 and miR-133 are more involved in muscle cell proliferation and differentiation, which are not commonly seen in adult patients [ 28 ]. In addition, we observed that miR-133 did not change between pre-treated and post-treated samples in non-paired analysis but almost reached statistical significance in paired samples analysis, implying that the sample variability and small sample size in subgroups may be attributed to such insensitivity. In the time course analysis, miR-133 and miR-486 were significantly increased in the 0–91 days group and remained at a high level despite being insignificant onwards. This indicated that muscle damage may be most susceptible in the first three months of cancer treatment. Of note, four out of these seven samples in the 0–91 days group were from patients who received surgery and the other were from patients who received neoadjuvant chemotherapy, and this again emphasized the huge impact of surgery and chemotherapy on muscle-related miRNA. Besides, higher expression of miR-486 and miR-133 in the older post-treated group may suggest the effect of age on muscle. MiR-21 was implicated in multiple activities in breast cancer. Research has shown that the high expression of miR-21 was not only involved in promotion and invasion but also mediated drug resistance as well as poor cancer prognosis [ 29 – 31 ]. Inflammation-related miR-21 plays a negative role in breast cancer patients. Muller et al. [ 32 ] reported a higher expression level of serum miR-21 in HER2 + breast cancer compared to healthy controls, and miR-21 increased further after chemotherapy combined with either trastuzumab or lapatinib. In our work, miR-21 was significantly higher in breast cancer patients, especially in Luminal B and HER2+, than that of healthy controls, and increased further after surgery and chemotherapy. Such an increasing trend was consistent with the findings of Muller et al. [ 32 ]. While Khalighfard et al. [ 33 ] found that plasma miR-21 was significantly increased in Luminal A breast cancer patients, but it was significantly down-regulated after surgery, chemotherapy, and radiotherapy compared to pre-treatment. These results again underscored miR-21 was treatment modality- and subtype-specific. Taken together, in this exploratory study, miR-486, miR-133, and miR-21 showed different responses to subtypes, treatment, timing, or age. These properties should be taken into consideration when exploring their potential as biomarkers to monitor exercise progress in cancer rehabilitation. Conclusions This exploratory study describes how selected muscle-specific and inflammation-related miRNAs are expressed in breast cancer patients, taking into account cancer subtype, treatment type, treatment duration, and age. While breast cancer itself did not cause major changes in these miRNAs overall, we found differences based on subtype and treatment. Of the miRNAs studied, miR-21 and miR-486 consistently changed in response to surgery and chemotherapy, especially early in treatment. miR-133 was more sensitive to treatment in older patients. These results show that circulating miRNAs reflect changes in the body during cancer treatment, rather than just the presence of disease. This study has some limitations, including its retrospective design and small subgroup sizes. However, our results suggest that circulating miR-21, miR-133, and miR-486 could be useful biomarkers for tracking inflammation and muscle changes related to cancer treatment. Future studies should follow patients over time and include measures of physical function and recovery to see if these miRNAs can help monitor adaptation and guide exercise-based rehabilitation in breast cancer survivors. Declarations Ethical approval and consent to participate Ethics approval for the current study was obtained from the Clinical Research Ethics committee of University hospital Galway https://hseresearch.ie/research-ethics/research-ethics-committees-cho-based-research/galwayuniversity-hospital-research-ethics-committee/ (Ref: C.A. 2828 – Identification and characterisation of biomarkers that determine the quality of life of cancer survivors). The Clinical Research Ethics Committee at the University of Galway operates in accordance with the World Medical Association Declaration of Helsinki, which provides the core ethical principles for medical research involving human subjects. The committee reviews applications to ensure they meet the Declaration of Helsinki, EU Directives, and national legislation regarding ethical research conduct. All experiments were conducted in line with the approved ethics and were carried out in accordance with clinical research ethics committee guidelines. All experimental protocols were approved by the clinical research ethics committee prior to the start of the study. A written informed consent was obtained from all participants ensuring participants voluntarily agree, are fully informed, and can withdraw at any time. All data was collected, stored and managed adhering to GDPR 2016 and Data Protection Act 2018 for data processing. Competing interests The authors declare no competing interest. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Clinical Research Ethics Committee of the University Hospital of Galway (ethical approval number: Ref: C.A. 2828). Funding This research was supported by a joint grant from the China Scholarship Council and the University of Galway. Financial Support for the Cancer Biobank was provided by the National Breast Cancer Research Institute under grant number FY23001. Author Contribution Yanping Jiang conducted the experiment and drafted the manuscript; Heidi Annuk. provided archived plasma samples and sample information; Nicola Miller and Kerin Michael provided technical support; Sai Zhang provided statistical instruction, Sanjeev Gupta and Ananya Gupta supervised this experiment. All authors read and approved the final manuscript. Acknowledgement We would like to express our great thanks to Cancer Biobank, Discipline of Surgery, University Hospital of Galway for providing their precious archived plasma samples. 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Int. , vol. 2014. 10.1155/2014/168407 Diakos CI, Charles KA, McMillan DC, Clarke SJ (Oct. 2014) Cancer-related inflammation and treatment effectiveness. Lancet Oncol 15(11):e493–e503. 10.1016/S1470-2045(14)70263-3 Pérez-Baos S, Prieto-Potin I, Román-Blas JA, Sánchez-Pernaute O, Largo R, Herrero-Beaumont G (2018) Mediators and patterns of muscle loss in chronic systemic inflammation, Front. Physiol. , vol. 9, no. APR, p. 409, Apr. 10.3389/FPHYS.2018.00409/BIBTEX Santos JMO, Da Silva SP, R. M. Gil Da Costa, and, Medeiros R (2020) The emerging role of micrornas and other non-coding rnas in cancer cachexia, Cancers (Basel). , vol. 12, no. 4, pp. 1–14. 10.3390/cancers12041004 Freire PP et al (1962) The Pathway to Cancer Cachexia: MicroRNA-Regulated Networks in Muscle Wasting Based on Integrative Meta-Analysis, International Journal of Molecular Sciences 2019, Vol. 20, Page 1962 , vol. 20, no. 8, p. Apr. 2019. 10.3390/IJMS20081962 Narasimhan A et al (2017) Small RNAome profiling from human skeletal muscle: novel miRNAs and their targets associated with cancer cachexia, J. Cachexia Sarcopenia Muscle , vol. 8, no. 3, pp. 405–416, Jun. 10.1002/jcsm.12168 Jiang Y, Ghias K, Gupta S, Gupta A (Dec. 2021) MicroRNAs as Potential Biomarkers for Exercise-Based Cancer Rehabilitation in Cancer Survivors. Life 2021 11(12):1439. 10.3390/LIFE11121439 Kirschner MB et al (2011) Sep., Haemolysis during Sample Preparation Alters microRNA Content of Plasma, PLoS One , vol. 6, no. 9, p. e24145. 10.1371/JOURNAL.PONE.0024145 Pan X, Wang R, Wang ZX (Jul. 2013) The potential role of miR-451 in cancer diagnosis, prognosis, and therapy. Mol Cancer Ther 12(7):1153–1162. 10.1158/1535-7163.MCT-12-0802/93940/ . P/THE-POTENTIAL-ROLE-OF-MIR-451-IN-CANCER-DIAGNOSIS Woo JW, Choi HY, Kim M, Chung YR, Park SY (2022) miR-145, miR-205 and miR-451: potential tumor suppressors involved in the progression of in situ to invasive carcinoma of the breast, Breast Cancer , vol. 29, no. 5, pp. 814–824, Sep. 10.1007/S12282-022-01359-9/FIGURES/4 Zhu J et al (2014) Different miRNA expression profiles between human breast cancer tumors and serum, Front. Genet. , vol. 5, no. MAY, p. 149, May 10.3389/FGENE.2014.00149/ABSTRACT Chan M et al (Aug. 2013) Identification of circulating microRNA signatures for breast cancer detection. Clin Cancer Res 19(16):4477–4487. 10.1158/1078-0432.CCR-12-3401/85841/ . AM/IDENTIFICATION-OF-CIRCULATING-MICRORNA-SIGNATURES Blenkiron C et al (Oct. 2007) MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype. Genome Biol 8(10):1–16. 10.1186/GB-2007-8-10-R214/FIGURES/6 Andorfer CA, Necela BM, Thompson EA, Perez EA (2011) MicroRNA signatures: clinical biomarkers for the diagnosis and treatment of breast cancer, Trends Mol. Med. , vol. 17, no. 6, pp. 313–319, Jun. 10.1016/J.MOLMED.2011.01.006 Samani A et al (Sep. 2022) miR-486 is essential for muscle function and suppresses a dystrophic transcriptome. Life Sci Alliance 5(9). 10.26508/LSA.202101215 Wang R et al (Jun. 2022) Skeletal muscle-specific overexpression of miR-486 limits mammary tumor-induced skeletal muscle functional limitations. Mol Ther Nucleic Acids 28:231–248. 10.1016/J.OMTN.2022.03.009 Rask L et al (Jul. 2014) Differential expression of miR-139, miR-486 and miR-21 in breast cancer patients sub-classified according to lymph node status. Cell Oncol 37(3):215–227. 10.1007/S13402-014-0176-6/FIGURES/5 Sromek M et al (Oct. 2017) Changes in plasma miR-9, miR-16, miR-205 and miR-486 levels after non-small cell lung cancer resection. Cell Oncol 40(5):529–536. 10.1007/S13402-017-0334-8/FIGURES/4 Li C, Zheng X, Li W, Bai F, Lyu J, Meng QH (Jan. 2018) Serum miR-486-5p as a diagnostic marker in cervical cancer: With investigation of potential mechanisms. BMC Cancer 18(1):1–10. 10.1186/S12885-017-3753-Z/FIGURES/7 Aoi W et al (2013) Muscle-enriched micro RNA miR-486 decreases in circulation in response to exercise in young men, Front. Physiol. , vol. 4 APR, p. 80, Apr. 10.3389/FPHYS.2013.00080/BIBTEX Domańska-Senderowska D, Laguette MJN, Jegier A, Cieszczyk P, September AV, Brzeziańska-Lasota E (2019) MicroRNA Profile and Adaptive Response to Exercise Training: A Review. Int J Sports Med 40(4):227–235. 10.1055/a-0824-4813 Nie Y, Sato Y, Wang C, Yue F, Kuang S, Gavin TP (Nov. 2016) Impaired exercise tolerance, mitochondrial biogenesis, and muscle fiber maintenance in miR-133a-deficient mice. FASEB J 30(11):3745–3758. 10.1096/FJ.201600529R/-/DC1 Alves MT et al (Jul. 2022) microRNA miR-133a as a Biomarker for Doxorubicin-Induced Cardiotoxicity in Women with Breast Cancer: A Signaling Pathway Investigation. Cardiovasc Toxicol 22(7):655–662. 10.1007/S12012-022-09748-4/FIGURES/4 Chen JF et al (2005) The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation, Nature Genetics 2005 38:2 , vol. 38, no. 2, pp. 228–233, Dec. 10.1038/ng1725 Petrovic´1 N, Petrovic´1 P (2016) miR-21 Might be Involved in Breast Cancer Promotion and Invasion Rather than in Initial Events of Breast Cancer Development, Molecular Diagnosis & Therapy 2016 20:2 , vol. 20, no. 2, pp. 97–110, Feb. 10.1007/S40291-016-0186-3 Qian B et al (Sep. 2009) High miR-21 expression in breast cancer associated with poor disease-free survival in early stage disease and high TGF-β1. Breast Cancer Res Treat 117(1):131–140. 10.1007/S10549-008-0219-7/TABLES/4 Najjary S, Mohammadzadeh R, Mokhtarzadeh A, Mohammadi A, Kojabad AB, Baradaran B (May 2020) Role of miR-21 as an authentic oncogene in mediating drug resistance in breast cancer. Gene 738:144453. 10.1016/J.GENE.2020.144453 Müller V et al (Aug. 2014) Changes in serum levels of miR-21, miR-210, and miR-373 in HER2-positive breast cancer patients undergoing neoadjuvant therapy: A translational research project within the Geparquinto trial. Breast Cancer Res Treat 147(1):61–68. 10.1007/S10549-014-3079-3/FIGURES/3 Khalighfard S, Alizadeh AM, Irani S, Omranipour R (2018) Plasma miR-21, miR-155, miR-10b, and Let-7a as the potential biomarkers for the monitoring of breast cancer patients, Scientific Reports 2018 8:1 , vol. 8, no. 1, pp. 1–11, Dec. 10.1038/s41598-018-36321-3 Additional Declarations No competing interests reported. Supplementary Files 03Supplementaryfiles.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 Mar, 2026 Editor assigned by journal 06 Mar, 2026 Submission checks completed at journal 06 Mar, 2026 First submitted to journal 05 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9039383","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":602374591,"identity":"80ce6099-fcb9-420e-a622-6e4afe02d2c6","order_by":0,"name":"Yanping Jiang","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Yanping","middleName":"","lastName":"Jiang","suffix":""},{"id":602374592,"identity":"55586702-28dc-4455-8d5c-0f9fe4a64597","order_by":1,"name":"Heidi Annuk","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Heidi","middleName":"","lastName":"Annuk","suffix":""},{"id":602374593,"identity":"a6dd3cbe-6e11-40ca-9882-ecb01340c4b8","order_by":2,"name":"Nicola Miller","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Nicola","middleName":"","lastName":"Miller","suffix":""},{"id":602374594,"identity":"45980b10-e281-4ee6-b39e-a7abecb498dd","order_by":3,"name":"Kerin Michael","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Kerin","middleName":"","lastName":"Michael","suffix":""},{"id":602374595,"identity":"12e8e451-4929-4724-80a3-bb84ff6dd09a","order_by":4,"name":"Sanjeev Gupta","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Sanjeev","middleName":"","lastName":"Gupta","suffix":""},{"id":602374596,"identity":"a7be3f8e-2637-462e-8703-be0d5bb78172","order_by":5,"name":"Sai Zhang","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Sai","middleName":"","lastName":"Zhang","suffix":""},{"id":602374597,"identity":"8b706def-362e-4337-98af-dce547939b5e","order_by":6,"name":"Ananya Gupta","email":"data:image/png;base64,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","orcid":"","institution":"University of Galway","correspondingAuthor":true,"prefix":"","firstName":"Ananya","middleName":"","lastName":"Gupta","suffix":""}],"badges":[],"createdAt":"2026-03-05 11:10:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9039383/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9039383/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105017697,"identity":"5c7a1cfa-f82f-4b24-8e28-e1c212a19867","added_by":"auto","created_at":"2026-03-20 01:21:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":203890,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression of selected miRNA in different cancer subtypes\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039383/v1/4d74617e147799e40df2ae67.jpg"},{"id":105035577,"identity":"95045d37-83f8-4f95-8d93-6acbab80f78b","added_by":"auto","created_at":"2026-03-20 07:26:17","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":259568,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression of selected miRNAs in surgery (A), chemotherapy (B, C), endocrine (D) and combined therapy (E)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(A) paired surgery group: 5 pre-treated vs 5 post-treated; (B) paired chemotherapy group: 8 vs 8, and (C)non-paired chemotherapy group (15 vs 19); (D) endocrine therapy:15 vs 4; (E) combined therapy: 15 vs 5 (one paired), and the paired samples in this group were regarded as independent samples. Paired t-test or Wilcoxon signed-rank test was performed for paired samples, Student’s t-test or Mann-Whitney U \u0026nbsp;test was performed for non-paired samples. *represents p\u0026lt;0.05; **represents p\u0026lt;0.01; ***represents p\u0026lt;0.001.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039383/v1/4931f6d325b804e3e759c383.jpg"},{"id":105017701,"identity":"7fb2173a-2562-41ef-9da4-c7f7bd2e4a3d","added_by":"auto","created_at":"2026-03-20 01:21:05","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":259305,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression of selected miRNA in pre-treated, and post-treated groups in Luminal A (A, B), Luminal B (C), HER2+ (D), and Basal-like (E) breast cancer.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(A) paired Luminal A: 10 vs 10; (B) non-paired Luminal A: 5 vs 15; (C)Luminal B: 5 vs 6 (one paired); (D) HER2+: 5 vs 5 (two paired); (E) Basal-like: 4 vs 6 (1 paired). Due to the small number of paired samples, the paired samples in these groups were regarded as independent samples. Paired t-test or Wilcoxon signed-rank test was performed for paired samples, Student’s t-test or Mann-Whitney U test was performed for non-paired samples. *represents p\u0026lt;0.05; **represents p\u0026lt;0.01; ***represents p\u0026lt;0.001.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039383/v1/91e9d43907f82e38aff8709d.jpg"},{"id":105035587,"identity":"f344a2c7-9d7d-44b0-82d1-c9e0cafd7aa7","added_by":"auto","created_at":"2026-03-20 07:26:17","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":127985,"visible":true,"origin":"","legend":"\u003cp\u003eThe impact of treatment duration on miRNA change\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe bracket represents the p value from ANOVA or the Kruskal-Wallis test; the solid line represents the p value from within groups comparison, and significance values have been adjusted by the Bonferroni correction. *represents p\u0026lt;0.05; **represents p\u0026lt;0.01; ***represents p\u0026lt;0.001.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039383/v1/96c8510f1e07e651c49dd4bf.jpg"},{"id":105017699,"identity":"7203d36c-d361-45aa-a5a4-5765816676e4","added_by":"auto","created_at":"2026-03-20 01:21:05","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":116274,"visible":true,"origin":"","legend":"\u003cp\u003emiRNA expression in different age groups\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudent t-test or Mann-Whitney U test was performed. *represents p\u0026lt;0.05; **represents p\u0026lt;0.01; ***represents p\u0026lt;0.001.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9039383/v1/44ea2bf801a3a1c9558892fd.jpg"},{"id":105036841,"identity":"7fe7b9ed-5006-4365-b950-6cc0da5f1cbd","added_by":"auto","created_at":"2026-03-20 07:36:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2117073,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9039383/v1/ffa4dd1d-4b85-4081-b75b-ea961db70b38.pdf"},{"id":105017703,"identity":"09c94f1d-d7f7-4574-9113-b22674b48dd8","added_by":"auto","created_at":"2026-03-20 01:21:06","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":61619,"visible":true,"origin":"","legend":"","description":"","filename":"03Supplementaryfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-9039383/v1/e5f63ddfbd32f8fa1f8f34ee.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Circulating muscle- and inflammation-related microRNAs in breast cancer survivorship: associations with treatment, timing, and age","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn 2022, breast cancer has surpassed lung cancer as the most frequently diagnosed malignancy in female, with more than 2.3\u0026nbsp;million cancer cases. The advances in multimodal therapy have given rise to an increased chance of cure in 70\u0026ndash;80% of patients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, cancer- and cancer treatment-induced complications can exert negative effects on treatment efficacy, and even significantly increase morbidity and mortality. Sarcopenia refers to the loss of muscle mass and strength, and is one of the severe complications that breast cancer survivors face during and after treatment. Research has shown that the prevalence of sarcopenia ranges from 30% to 55% in breast cancer patients, and it is linked to a higher chance of chemotoxicity, functional decline, and poorer quality of survivorship [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Sarcopenic survivors have a 2.86-fold greater all-cause mortality compared to their non-sarcopenic counterparts [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The mechanisms for cancer- and cancer treatment-induced sarcopenia are complex, and one of these mechanisms may be involved in inflammation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Inflammation can over-stimulate the immune system, which fuels energy expenditure, thus leading to a shortage of stored reserves and affecting general metabolism. Such a dynamic shift may result in skeletal homeostasis toward muscle loss [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicroRNAs (miRNAs) are a group of short, non-coding RNAs, with 20\u0026ndash;22 nucleotides, and evidence has demonstrated miRNAs play an important role in modulating the pathway of skeletal muscle turnover and inflammation[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. For example, Narasimhan et al [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] found eight upregulated miRNAs in cachectic cancer patients compared to their non-cachectic counterparts by next-generation sequencing. Ingenuity pathway analysis showed that the targets of these miRNAs were known to engage in myogenesis, inflammation, and immune response. These results indicated that miRNA may directly or indirectly be involved in muscle development and function and the abnormal expression of miRNAs may imply muscle loss and dysfunction during cancer survivorship. While research has shown that exercise can restore muscle loss and strength by improving systemic inflammation and this process is accompanied by the alterations of miRNAs. In our previous work, we reviewed the role of miRNA in both cancer- or cancer treatment-induced muscle loss and exercise. Generally, cancer itself and cancer treatment can cause muscle damage and inflammation, thus leading to physical inability and poor quality of life, while exercise can trigger adaptive responses and facilitate organ recovery, reflected by altered miRNA expression in damaged organs. This indicates that muscle- and inflammation-related miRNAs may be potential molecular biomarkers to monitor the progress of exercise-based cancer rehabilitation during cancer survivorship [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, given the heterogeneity of breast cancer biology and its treatment, initial exploratory studies are needed to determine the association between miRNAs expression profiles and specific cancer subtypes or cancer treatment. Therefore, based on our previous work, we selected a panel of muscle-specific (miR-1, miR-133, miR-208, miR-486, miR-499) and inflammation-related (miR-21, miR-126, miR-146, and miR-155) miRNAs to conduct exploratory research on their associations with breast cancer subtypes, treatment, timing, and age during cancer survivorship.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Ethics approval and plasma sample information\u003c/h2\u003e \u003cp\u003e This study was performed in line with the principles of the Declaration of Helsinki and the Clinical Research Ethics Committee of the University Hospital of Galway approved the use of archived human plasma samples (ethical approval number: Ref: C.A. 2828). The commercial healthy plasma pool was purchased from Amsbio company, characterized by one African American and one Hispanic American, with an average age of 52. All archived plasma samples were obtained from the Cancer Biobank, Discipline of Surgery, University of Galway: 5 healthy archived samples were from healthy controls, with a median age of 52.2 (ranging from 51 to 55 years old). The archived samples from breast cancer patients were included when their donors met the following criteria: 1) aged over 18 years old and 2) diagnosed with breast cancer. However, samples were excluded if their donors had: 1) breast cancer with rare subtypes or 2) confirmed to have other cancer history in addition to breast cancer. A total of 71 archived samples from breast cancer patients were obtained. These samples came from breast cancer patients aged from 24 to 88 years old, with a median age of 59. Among these 71 plasma samples, there were 29 pre-treated samples (from patients who did not receive any treatment when the samples were collected) and 42 post-treated samples (from patients who received cancer treatment when the samples were collected). Among these samples, there were 14 paired samples where pre-treated and post-treated samples were obtained from the same patients. There were also 15 pre-treated samples and 28 post-treated samples obtained from different patients, classified as non-paired samples. Patients\u0026rsquo; characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatients\u0026rsquo; characteristics of included samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePre-treatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePost-treatment\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Samples (N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;=50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSubtypes (N)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLuminal A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLuminal B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHER2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasal-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTreatment received\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndocrine therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHER2+: human epidermal growth factor receptor 2 positive\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 RNA isolation\u003c/h2\u003e \u003cp\u003eArchived plasma samples were stored at -80℃, and thawed at 37℃ water bathing before RNA isolation. Plasma miRNA was isolated using plasma/serum miReasy Kit (Qiagen, Germany) according to the manufacturer\u0026rsquo;s instructions. The plasma aliquot was transferred to a new microcentrifuge tube with five times a Qiazol mixture without spike-ins as RNU6B was used as a reference miRNA in quantitative reverse transcription polymerase chain reaction (qRT-PCR). RNA concentration was measured by NanoDrop spectrophotometry (NanoDrop ND-100 Technologies Inc., DE USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Quantification of miRNA expression by qRT-PCR\u003c/h2\u003e \u003cp\u003eThe reverse transcription (RT) was performed by using the TaqMan microRNA reverse transcription kit (applied biosystem) with 50 nanograms of miRNA in a 15\u0026micro;L reaction system (RNA: 5\u0026micro;L, RT master mix: 7\u0026micro;L, primer: 3\u0026micro;L) according to the manufacturer\u0026rsquo;s instruction. The reaction conditions in the thermal cycler for miRNA-specific RT reaction were as follows: 16℃ for 30 min, 42℃ for 30 min, 85℃ for 5 min, and 4℃ for hold. All primers\u0026rsquo; information was shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. qRT-PCR was then performed on MicroAmp\u0026reg; Fast 96-Well Reaction Plate (applied biosystem) with a condition of holding at 50℃ for 2 min, further holding at 95℃ for 10 min, and then running 40 cycles for 0.15 min followed by holding at 60℃ for 1 min. All assays were conducted in triplicates. A comparative cycle (Ct) threshold was used to calculate the miRNA expression level, and the relative expression level of selected miRNAs in each plasma was normalized to that of RNU6B, and calculated as (2^\u003csup\u003e\u0026minus;ΔCt\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed by using SPSS 25.0 and GraphPad Prism 8.0. Considering the characteristics of relative miRNA expression levels, miRNA data were log10-transformed (Log10) for analysis. The expression of miRNA data was presented with Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). The student\u0026rsquo;s t-test or ANOVA were performed when data were normally distributed; the Mann-Whitney U test or Kruskal-Wallis test was performed when data were not normally distributed. For multiple groups\u0026rsquo; comparison, significance values have been adjusted by the Bonferroni correction. Paired t-test or Wilcoxon signed-rank test was performed for paired sample analysis. All p values were two-sided and the significance level is 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Circulating miRNA profiles in healthy controls and pre-treated breast cancer patients\u003c/h2\u003e \u003cp\u003eWe first measured circulating levels of selected muscle-specific and inflammation-related miRNAs in healthy controls (including a healthy plasma pool and five healthy plasma samples) and pre-treated breast cancer patients. Muscle-related miRNAs such as miR-1, miR-133, miR-486, and miR-499 were found at low levels in healthy individuals (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), while miR-208 was not detected in most samples (data not shown). Comparison of pre-treated breast cancer patients (n\u0026thinsp;=\u0026thinsp;29) with healthy controls (n\u0026thinsp;=\u0026thinsp;6) revealed no statistically significant differences in the expression of any selected miRNAs, despite trends toward increased miR-21 and miR-499, and decreased miR-133, miR-486, and miR-155 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results indicate that, at the group level, breast cancer alone was not associated with substantial alterations in circulating muscle- or inflammation-related miRNAs prior to treatment. In this study, miR-451 was included as the biomarker monitoring hemolysis in plasma samples based on literature [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although we used clear and transparent plasma samples, miR-451 showed some significance in our results. This may be in part explained by that miR-451 can be influenced by cancer and cancer therapy [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and may not be a reliable biomarker for hemolysis in this context. Therefore, the results of miR-451 were presented in the following Tables and Figures without interpretation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Association between breast cancer subtype and circulating miRNA expression\u003c/h2\u003e \u003cp\u003eBecause breast cancer is biologically diverse, we examined circulating miRNA levels across different molecular subtypes using only pre-treated samples. Luminal A breast cancer was associated with lower circulating levels of muscle-related miRNAs compared to healthy controls, particularly miR-486 (0.68-fold, p\u0026thinsp;=\u0026thinsp;0.047, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table S2). MiR-133 (0.06-fold, p\u0026thinsp;=\u0026thinsp;0.081) was also lower in Luminal A patients, though this was not quite significant. In Luminal B breast cancer, inflammation-related miRNAs were more affected. MiR-21 (19.32-fold, p\u0026thinsp;=\u0026thinsp;0.008), miR-126 (1.27-fold, p\u0026thinsp;=\u0026thinsp;0.062), and miR-146 (1.31-fold, p\u0026thinsp;=\u0026thinsp;0.065) were increased in Luminal B patients. In human epidermal growth factor receptor 2 positive (HER2+) subtype, miR-21 (14.10-fold, p\u0026thinsp;=\u0026thinsp;0.042) was significantly increased, but this trend was not seen in other inflammation-related miRNAs. No significant differences were observed for the Basal-like subtype. These findings indicate that muscle- and inflammation-related circulating miRNAs may display subtype-specific expression patterns prior to treatment. However, since the healthy controls used in this study is mixed sources and sample sizes in controls and each subtype are relatively small, these results are more descriptive rather than definitive, and should be interpreted cautiously.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Student\u0026rsquo;s t-test or Mann-Whitney U test was performed to compare different cancer subtypes to healthy controls. ANOVA or Kruskal-Wallis test was performed to compare the expression levels of selected miRNAs among different cancer subtypes, p values for within-group comparisons have been adjusted by the Bonferroni correction. *represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe expression of selected miRNAs in plasma samples from healthy controls and breast cancer patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003emiRNAs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHealthy vs pre-treated\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003ePaired samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eNon-paired samples\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy plasma samples (N\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePre-treated plasma samples (N\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFold change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePre-treated samples (N\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePost-treated samples (N\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFold change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePre-treated samples (N\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePost-treated samples (N\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eFold change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.05 (0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.25 (1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.24(1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.07(1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.21(1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.66(1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.37 (0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35 (0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.31(0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.12(0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.46(0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.53(0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.05 (0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51 (0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.30(0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.03(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.20(0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.14(0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.79 (0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.10 (0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.21(0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.76(0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.59(1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.17(0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60 (1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.40(1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.26(0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.97(0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.81(1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.61 (0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.70 (1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.21(1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.53(1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.36(0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.27(0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.41 (0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.51(1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.02(0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.64(0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.71(0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.25 (0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.80 (1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.35(1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.61(1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.70(1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.51(1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiR-499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.66(0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.19(0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.50(1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.91(0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.27(0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.07(0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eFor paired samples, paired t-test or Wilcoxon signed-rank test was applied. For unpaired comparisons, Student\u0026rsquo;s t-test or Mann\u0026ndash;Whitney U test was applied.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Impact of cancer treatment on circulating miRNA expression\u003c/h2\u003e \u003cp\u003eTo assess how cancer treatment affects circulating miRNA levels, we compared post-treated and pre-treated samples using both unpaired and paired analyses. In unpaired analyses, post-treated patients had significantly higher levels of miR-486 than pre-treated patients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Paired analyses showed similar results of miR-486. Besides, paired analyses also found significant increases in miR-21 and miR-126 after treatment, which were not seen in unpaired comparisons. Other miRNAs, such as miR-133 and miR-146, showed similar trends toward change after treatment but were not statistically significant. These results suggest that changes in circulating miRNA profiles are mainly linked to cancer treatment, not just the diagnosis itself.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Treatment modality\u0026ndash;specific miRNA responses\u003c/h2\u003e \u003cp\u003eWe then looked at how different treatment types affected circulating miRNAs. Both surgery and chemotherapy led to significant increases in miR-21 and miR-486 when comparing samples before and after treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). These trends were seen in both paired and unpaired analyses, but were more often significant in paired comparisons. Endocrine therapy was not associated with significant changes in any of the examined miRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). In patients receiving combined therapy, which most commonly included surgery and chemotherapy, miR-486 again demonstrated a significant increase compared with pre-treated samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Across treatment modalities, miR-21 exhibited a consistent tendency toward increased expression following treatment exposure, supporting its sensitivity to treatment-related physiological changes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Subtype-specific treatment-associated miRNA changes\u003c/h2\u003e \u003cp\u003eWe also looked at treatment-related miRNA changes within each breast cancer subtype. In Luminal A, treatment led to significant increases in miR-486 and miR-21 in paired analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), and an increase in miR-133 in unpaired analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Although there were some differences between paired and unpaired results, the overall pattern was similar. In Luminal B breast cancer, inflammation-related miRNAs miR-146 and miR-155 demonstrated significant decreases following treatment, despite modest elevations in pre-treated patients relative to healthy controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). In HER2\u0026thinsp;+\u0026thinsp;breast cancer, treatment exposure was associated with increased circulating miR-133 and miR-155 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). No statistically significant treatment-associated changes were observed in the Basal-like subtype (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). These results show that the way circulating miRNAs respond to cancer treatment depends on the breast cancer subtype, likely due to differences in tumor biology and treatment approaches.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(A) paired surgery group: 5 pre-treated vs 5 post-treated; (B) paired chemotherapy group: 8 vs 8, and (C)non-paired chemotherapy group (15 vs 19); (D) endocrine therapy:15 vs 4; (E) combined therapy: 15 vs 5 (one paired), and the paired samples in this group were regarded as independent samples. Paired t-test or Wilcoxon signed-rank test was performed for paired samples, Student\u0026rsquo;s t-test or Mann-Whitney U test was performed for non-paired samples. *represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e(A) paired Luminal A: 10 vs 10; (B) non-paired Luminal A: 5 vs 15; (C)Luminal B: 5 vs 6 (one paired); (D) HER2+: 5 vs 5 (two paired); (E) Basal-like: 4 vs 6 (1 paired). Due to the small number of paired samples, the paired samples in these groups were regarded as independent samples. Paired t-test or Wilcoxon signed-rank test was performed for paired samples, Student\u0026rsquo;s t-test or Mann-Whitney U test was performed for non-paired samples. *represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Association between treatment duration and circulating miRNA expression\u003c/h2\u003e \u003cp\u003eTo examine temporal patterns, post-treated samples were stratified by time from diagnosis to blood collection (Table S3). Circulating miRNA changes were most pronounced within the first 91 days following diagnosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). During this early period, miR-133, and miR-486 were significantly elevated compared to pre-treated samples. After 91 days, circulating miRNA levels mostly returned to pre-treatment values, and there were no significant differences at later time points. Most samples from the first 91 days came from patients having surgery or neoadjuvant chemotherapy, showing that the early treatment phase is a time of greater physiological change.\u003c/p\u003e \u003cp\u003eWe also looked at miRNA levels by age group (age distribution in Table S4). In patients 50 years or younger, there were no significant differences between pre-treated and treated groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In patients over 50, treatment led to significant increases in miR-133 and miR-486. These results suggest that age affects how circulating miRNAs respond to cancer treatment, especially for muscle-related miRNAs that are important for physical function and recovery.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eThe bracket represents the p value from ANOVA or the Kruskal-Wallis test; the solid line represents the p value from within groups comparison, and significance values have been adjusted by the Bonferroni correction. *represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eStudent t-test or Mann-Whitney U test was performed. *represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***represents p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Muscle- and inflammation-related miRNAs have different expression patterns among breast cancer subtypes\u003c/h2\u003e \u003cp\u003eThe expression of miRNA was influenced by multiple factors. Research has demonstrated that the miRNAs expression profile in tumor tissue is different from that in circulation, and some of the differentially expressed circulating miRNAs are novel, denoting that miRNAs may be selectively released into circulation, and this may be one of the factors affecting miRNA expression in circulation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Similarly, our results showed that muscle-enriched miRNAs such as miR-1, miR-133, miR-486, and miR-499 had a low expression in the plasma of healthy controls, and this may support their property of selective release into circulation. Blenkiron et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] profiled miRNA expression in 93 breast cancer patients, and identified 133 differentially expressed miRNAs between healthy breast tissue and breast cancer tissue. Furthermore, a body of miRNAs was differentially expressed among these cancer subtypes, and certain miRNAs were implicated in clinicopathological factors, indicating that the cancer subtype may influence miRNA expression in breast cancer. Nevertheless, whether the selected inflammation- and muscle-related miRNAs are affected by cancer subtypes remains to be unclear. In this exploratory study, comparisons of healthy controls and pre-treated samples showed that none of these select miRNAs were significantly different. However, this changed when stratified analyses were performed across cancer subtypes: muscle-related miRNA miR-486 (p\u0026thinsp;=\u0026thinsp;0.047) and miR-133 (p\u0026thinsp;=\u0026thinsp;0.081, close to significance level) was decreased in Luminal A; inflammation-related miR-21 (p\u0026thinsp;=\u0026thinsp;0.008) in Luminal B was 19-fold greater than that in healthy controls, miR-126 (p\u0026thinsp;=\u0026thinsp;0.062) and miR-146 (p\u0026thinsp;=\u0026thinsp;0.065) increased by about 30% in cancer patients, and it almost reached the statistical significance. These results revealed that Luminal A may have a greater impact on changes in muscle-related miRNAs, while Luminal B may have a greater impact on inflammation-related miRNAs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2 miRNAs have different responses to cancer treatment in breast cancer\u003c/h2\u003e \u003cp\u003eSince miRNA signature was different among breast cancer subtypes and each subtype might have different treatment strategies, it is therefore assumed that miRNA signature may have different responses to different cancer treatments [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Research has shown that miR-30a-3p, miR-30c, and miR-182 can predict the clinical benefit of tamoxifen in estrogen receptor positive breast cancer; miR-21, miR-125b, and miR-331, may be associated with the response to HER2-targeted therapy or the modulation of HER2 expression [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In our study, cancer treatment changed the expression of muscle- and inflammation-related miRNAs. Compared to pre-treated samples, miR-486 significantly increased following treatment; however, miR-486 had decreased expression in post-treated samples when compared to healthy controls. This may be explained that treatment rescued the damage caused by cancer itself. MiR-21 and miR-126 significantly increased after cancer treatment in paired samples analysis, indicating their potential role as biomarkers monitoring cancer treatment-induced inflammation. In addition, miR-21 and miR-486 showed significant sensitivity to surgery and chemotherapy. In Luminal A breast cancer, miR-21, miR-133, and miR-486 significantly responded to treatment; miR-146 and miR-155 responded to treatment in Luminal B and HER2\u0026thinsp;+\u0026thinsp;breast cancer, but their tendency to treatment was opposite in these two cancer subtypes. These results may imply that the changes of miRNAs were likely to be treatment modality-specific or subtype-specific. However, given the small sample size in each subgroup, the interpretation should be cautious and confirmatory studies with larger sample size are needed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.3 The implication of miR-486, miR-133, and miR-21 during cancer survivorship\u003c/h2\u003e \u003cp\u003eMiR-486 and miR-133 are muscle-enriched miRNAs, and play an important role in muscle development and function. Studies showed mice with Duchenne muscular dystrophy had a lower expression of miR-486 in muscle compared to their healthy counterparts; miR-486 knockout mice were likely to develop dysfunctional muscular structure in skeletal muscle, including disrupted myofiber architecture and decreased myofiber size, thus leading to exacerbated locomotor activity and metabolic defects, indicating its crucial role in maintaining muscle function [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In a recently published research, Wang et al[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] investigated the role of miR-486 in muscle function in breast cancer mouse models and found that miR-486 significantly prevented a cancer-induced reduction in muscle contraction force, grip strength, and rotarod performance. Besides, overexpression of miR-486 could reverse cancer-induced muscle change by modulating the miR-486-PTEN-AKT signaling axis. Our research showed that except for a slight increase in Luminal B, plasma miR-486 generally decreased in breast cancer patients compared to its healthy controls despite a significant difference only in Luminal A, and this is in line with previous reports both in patients and mouse models [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, the expression of miR-486 was linked to cancers and cancer treatment. Research has shown that circulating miR-486 in non-small lung cancer and cervical cancer was higher in cancer patients than in healthy controls [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Besides, plasma miR-486 in small lung cancer significantly increased after surgical resection, and such an increase could persist up to one year after surgery [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In our results, miR-486 significantly increased after treatment regardless of surgery and chemotherapy, and such an increase is more prominent in Luminal A and Luminal B. Normally, muscle-related miRNAs have a very low expression in circulation in healthy people, which was also confirmed in our study [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]; in this case, the high expression of circulating miR-486 is likely to be a stress response to treatment, which is contradictory to the aforementioned findings that overexpressed miR-486 in muscle tissue improve muscle function. One of possible explanation for this contradiction is that muscle cells were damaged, died, or even broken down following treatment, thus releasing miR-486 into the circulating system. In the context of exercise, research has shown that circulating miR-486 significantly decreases regardless of acute or chronic exercise, and the changes of miR-486 are negatively associated with maximal oxygen consumption [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These results suggested that miR-486 may be a promising candidate biomarker for exercise-based cancer rehabilitation, but further prospective studies are needed.\u003c/p\u003e \u003cp\u003eNie et al [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] demonstrated that miR-133 deficient mice had a low maximal exercise capacity, and such a compromised exercise capacity was impaired via depressing the transcription of mitochondrial biogenesis regulators. In addition, instead of in miR-133a-deficient mice, endurance exercise only elevated the transcriptional level of miR-133a as well as mitochondrial biogenesis in wild-type mice. In a case-control study, high expression of serum miR-133 was reported in breast cancer patients with doxorubicin-induced cardiotoxicity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These results suggest that miR-133 may be a potential biomarker for cardiovascular function during treatment. However, miR-133 is not as sensitive to cancer and cancer treatment as miR-486 was in our research. This may be explained by their different roles in muscle: miR-486 is more engaged in maintaining muscle function, while miR-1 and miR-133 are more involved in muscle cell proliferation and differentiation, which are not commonly seen in adult patients [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In addition, we observed that miR-133 did not change between pre-treated and post-treated samples in non-paired analysis but almost reached statistical significance in paired samples analysis, implying that the sample variability and small sample size in subgroups may be attributed to such insensitivity. In the time course analysis, miR-133 and miR-486 were significantly increased in the 0\u0026ndash;91 days group and remained at a high level despite being insignificant onwards. This indicated that muscle damage may be most susceptible in the first three months of cancer treatment. Of note, four out of these seven samples in the 0\u0026ndash;91 days group were from patients who received surgery and the other were from patients who received neoadjuvant chemotherapy, and this again emphasized the huge impact of surgery and chemotherapy on muscle-related miRNA. Besides, higher expression of miR-486 and miR-133 in the older post-treated group may suggest the effect of age on muscle.\u003c/p\u003e \u003cp\u003eMiR-21 was implicated in multiple activities in breast cancer. Research has shown that the high expression of miR-21 was not only involved in promotion and invasion but also mediated drug resistance as well as poor cancer prognosis [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Inflammation-related miR-21 plays a negative role in breast cancer patients. Muller et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] reported a higher expression level of serum miR-21 in HER2\u0026thinsp;+\u0026thinsp;breast cancer compared to healthy controls, and miR-21 increased further after chemotherapy combined with either trastuzumab or lapatinib. In our work, miR-21 was significantly higher in breast cancer patients, especially in Luminal B and HER2+, than that of healthy controls, and increased further after surgery and chemotherapy. Such an increasing trend was consistent with the findings of Muller et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. While Khalighfard et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] found that plasma miR-21 was significantly increased in Luminal A breast cancer patients, but it was significantly down-regulated after surgery, chemotherapy, and radiotherapy compared to pre-treatment. These results again underscored miR-21 was treatment modality- and subtype-specific.\u003c/p\u003e \u003cp\u003eTaken together, in this exploratory study, miR-486, miR-133, and miR-21 showed different responses to subtypes, treatment, timing, or age. These properties should be taken into consideration when exploring their potential as biomarkers to monitor exercise progress in cancer rehabilitation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis exploratory study describes how selected muscle-specific and inflammation-related miRNAs are expressed in breast cancer patients, taking into account cancer subtype, treatment type, treatment duration, and age. While breast cancer itself did not cause major changes in these miRNAs overall, we found differences based on subtype and treatment. Of the miRNAs studied, miR-21 and miR-486 consistently changed in response to surgery and chemotherapy, especially early in treatment. miR-133 was more sensitive to treatment in older patients. These results show that circulating miRNAs reflect changes in the body during cancer treatment, rather than just the presence of disease.\u003c/p\u003e \u003cp\u003eThis study has some limitations, including its retrospective design and small subgroup sizes. However, our results suggest that circulating miR-21, miR-133, and miR-486 could be useful biomarkers for tracking inflammation and muscle changes related to cancer treatment. Future studies should follow patients over time and include measures of physical function and recovery to see if these miRNAs can help monitor adaptation and guide exercise-based rehabilitation in breast cancer survivors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003e \u003cb\u003eEthical approval and consent to participate\u003c/b\u003e \u003c/h2\u003e \u003cp\u003eEthics approval for the current study was obtained from the Clinical Research Ethics committee of University hospital Galway \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hseresearch.ie/research-ethics/research-ethics-committees-cho-based-research/galwayuniversity-hospital-research-ethics-committee/\u003c/span\u003e\u003cspan address=\"https://hseresearch.ie/research-ethics/research-ethics-committees-cho-based-research/galwayuniversity-hospital-research-ethics-committee/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Ref: C.A. 2828 \u0026ndash; Identification and characterisation of biomarkers that determine the quality of life of cancer survivors). The Clinical Research Ethics Committee at the University of Galway operates in accordance with the World Medical Association Declaration of Helsinki, which provides the core ethical principles for medical research involving human subjects. The committee reviews applications to ensure they meet the Declaration of Helsinki, EU Directives, and national legislation regarding ethical research conduct. All experiments were conducted in line with the approved ethics and were carried out in accordance with clinical research ethics committee guidelines. All experimental protocols were approved by the clinical research ethics committee prior to the start of the study. A written informed consent was obtained from all participants ensuring participants voluntarily agree, are fully informed, and can withdraw at any time. All data was collected, stored and managed adhering to GDPR 2016 and Data Protection Act 2018 for data processing.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Clinical Research Ethics Committee of the University Hospital of Galway (ethical approval number: Ref: C.A. 2828).\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was supported by a joint grant from the China Scholarship Council and the University of Galway. Financial Support for the Cancer Biobank was provided by the National Breast Cancer Research Institute under grant number FY23001.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYanping Jiang conducted the experiment and drafted the manuscript; Heidi Annuk. provided archived plasma samples and sample information; Nicola Miller and Kerin Michael provided technical support; Sai Zhang provided statistical instruction, Sanjeev Gupta and Ananya Gupta supervised this experiment. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to express our great thanks to Cancer Biobank, Discipline of Surgery, University Hospital of Galway for providing their precious archived plasma samples.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData supporting the findings of this study are available in supplementary files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHarbeck N et al (2019) Breast cancer, \u003cem\u003eNature Reviews Disease Primers\u003c/em\u003e vol. 5, no. 1, pp. 1\u0026ndash;31, Sep. 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41572-019-0111-2\u003c/span\u003e\u003cspan address=\"10.1038/s41572-019-0111-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBray Bsc F et al (May 2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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In this study, we measured levels of selected muscle- (miR-1, miR-133, miR-208, miR-486, miR-499) and inflammation-related (miR-21, miR-126, miR-146, miR-155) miRNAs in breast cancer patients, and aimed to explore, using a stratifies analysis, how their levels relate to cancer subtype, treatment type, treatment duration, and age.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe collected 77 plasma samples from pre-treated and post-treated breast cancer patients, and healthy controls. Circulating miRNA levels were measured using quantitative RT-PCR. We compared miRNA levels across different breast cancer subtypes, treatment types, treatment duration, and age groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePre-treated breast cancer patients did not show significant changes in the selected miRNAs compared to healthy controls. However, different breast cancer subtypes showed distinct patterns: Luminal A predominantly affected muscle-related miRNAs, and Luminal B inflammation-related miRNAs. Cancer treatment, especially surgery and chemotherapy, led to significant changes in miR-21 and miR-486, mainly within the first 91 days after diagnosis. Increases in miR-133 and miR-486 after treatment were mostly seen in patients over 50 years old.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eCirculating muscle- and inflammation-related miRNAs display distinct expression patterns associated with breast cancer subtype and treatment. Specifically, miR-21, miR-133, and miR-486 demonstrate sensitivity to cancer treatment exposure, timing, and patient age.\u003c/p\u003e\u003ch2\u003eImplications for cancer survivors:\u003c/h2\u003e \u003cp\u003eOur findings support further investigation of these miRNAs as candidate biomarkers in prospective studies, including their potential use for monitoring physiological responses during exercise-based cancer rehabilitation.\u003c/p\u003e","manuscriptTitle":"Circulating muscle- and inflammation-related microRNAs in breast cancer survivorship: associations with treatment, timing, and age","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-20 01:21:01","doi":"10.21203/rs.3.rs-9039383/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-07T15:13:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-06T17:23:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-06T17:23:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Biology Reports","date":"2026-03-05T10:50:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b69a8c60-39b8-48c2-a9a9-d2314880b40a","owner":[],"postedDate":"March 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T01:21:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-20 01:21:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9039383","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9039383","identity":"rs-9039383","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}