Prostate cancer, a predominant cause of illness and death among men, originates in the prostate a gland the size of a walnut that generates seminal fluid to sustain and convey sperm. Early detection through screening improves treatment success [1], but advanced metastatic castration- resistant prostate cancer (mCRPC) often necessitates systemic therapies like chemotherapy [2]. Docetaxel, a cornerstone treatment for prostate cancer, exerts its anticancer effects by binding to microtubules, stabilizing them, and preventing their disassembly, which halts cancer cell division during mitosis [3]. However, this mechanism also disrupts rapidly dividing normal cells, such as bone marrow precursors, leading to myelosuppression characterized by neutropenia and increased susceptibility to infections which can exacerbate systemic inflammation [4]. This dynamic is especially important in type 2 diabetes (T2D), a common comorbidity with hyperglycemia, insulin resistance, and chronic low-grade inflammation [5]. T2D may affect prostate cancer prognosis due to overlapping inflammatory pathways and altered androgen signaling [6]. Increased pro-inflammatory cytokines, such as TNF-α and IL-6, impair insulin signaling in T2D by phosphorylating insulin receptor substrate-1 (IRS-1) at serine residues, causing oxidative stress and ROS [7]. This metabolic abnormality may worsen cancer inflammation and therapy responses. Prostate-specific antigen (PSA), a serine protease and key biomarker, is elevated in both malignancy and non-cancerous conditions like bacterial prostatitis [8]. Chronic bacterial infections, often caused by
Participants ranged in age from 50 to 75 and were sourced from specialized hospitals in Baghdad. The study was designed to be cross-sectional. Table 1 shows the four groups of participants classified by their health status and chemotherapy exposure.
| Group | Description | Number of Participants | Age Range | Chemotherapy Details | Dose of Chemotherapy |
| Group 1 | Patients with type 2 diabetes (T2D) but without cancer | 40 | 50-75 years | None | None |
| Group 2 | Patients with type 2 diabetes (T2D) and prostate cancer (pre-chemotherapy) | 40 | 50-75 years | None | None |
| Group 3 | Patients from Group 2 with T2D and prostate cancer who underwent two cycles of chemotherapy | 40(subset of Group 2) | 50-75 years | 2 cycles of Docetaxel (3 weeks apart) | 75 mg/m²per cycle |
| Group 4 | Patients from Group 2 with T2D and prostate cancerwho underwent five cycles of chemotherapy | 40(subset of Group 2) | 50-75 years | 5 cycles of Docetaxel (3 weeks apart) | 75 mg/m²per cycle |
Ten milliliters of blood were put into tubes free of anticoagulants following venipuncture. After 30 minutes of coagulation at room temperature, the samples were spun at 3000 rpm for 10 minutes in a centrifuge. Preserved at-80°C until analysis, portions of the serum supernatant were transferred to labeled tubes. The midstream clean-catch approach was used to collect urine samples following genital cleaning with antiseptic wipes. In order to prevent the growth of bacteria, samples were placed in sterile, airtight containers that could not leak. A patient’s ID, date, and time were written on the labels. If the samples were not processed within two hours, they were refrigerated at 4°C.
Urine specimens from Groups 2 and 4 (n=40 each) were examined for
In accordance with the Clinical and Laboratory Standards Institute, as outlined in CLSI M100TM (2024) [14], the antibiotic susceptibility of
Serum levels of procalcitonin (PCT), interleukin-6 (IL-6), prostate-specific antigen (PSA), and fasting insulin were quantified using the Cobas e411 analyzer (Roche, Germany) with electrochemiluminescence immunoassays (ECLIA). Tumor necrosis factor-α (TNF-α) was measured using a Human TNF-α ELISA Kit, Invitrogen- Thermo Fisher Scientific - US, with colorimetric detection.
Fasting glucose was determined on the Cobas c311 analyzer (Roche, Germany) using a photometric method at 550 nm,. All assays were performed in duplicate, with intra-assay coefficients of variation <5%.
The Homeostasis Model Assessment (HOMA-IR) used the following calculation to measure insulin resistance:
Interpreting HOMA-IR Values:
• < 1.0 → Highly insulin sensitive (ideal)
• 1.0 – 1.9 → Normal insulin sensitivity
• 2.0 – 2.9 → Early insulin resistance
• ≥ 3.0 → Significant insulin resistance (risk for metabolic disorders like type 2 diabetes)
The statistical analysis was done using Prism 10.4 from GraphPad Software (San Diego, CA, USA). For continuous variables, the data are presented as the mean with the standard deviation shown as plus or minus. We employed one-way ANOVA and Tukey’s post hoc test for multiple pairwise comparisons among the four groups. In all two-tailed statistical tests, a p-value less than 0.05 was deemed significant. The groups exhibit substantial differences when the significance threshold is elevated (p < 0.0001).
This study evaluated differences in inflammatory markers (procalcitonin [PCT], interleukin-6 [IL-6], tumor necrosis factor-α [TNF-α]), metabolic parameters (fasting glucose, fasting insulin, HOMA-IR), prostate-specific antigen (PSA) and
| Parameters | Group 1 | Group 2 | Group 3 | Group 4 | P value |
| Mean ± SD | Mean ± SD | Mean ± SD | Mean ± SD | ||
| PCT (less than 0.05 ng/ml) | 0.03 ± 0.01 | 0.47± 0.3 | 1.15 ± 0.51 | 49.15 ± 5.8 | <0.0001 |
| IL-6 (less than 7 pg/ml) | 3.62 ± 1.4 | 9.63 ± 1.63 | 27.88 ± 9.5 | 131.5 ± 37.3 | <0.0001 |
| TN-F (less than 8.1 pg/ml) | 5.38 ± 1.7 | 2.3 ± 0.36 | 19.2 ± 3 | 37.3 ± 5.9 | <0.0001 |
| Fasting glucose (70-99 md/dl) | 63.07 ± 9.9 | 55.9 ± 8.8 | 88.1 ± 13.9 | 123.2 ± 19.5 | <0.0001 |
| Fasting insulin (2–20 μIU/ml) | 28.18 ± 5.9 | 33.25 ± 6.2 | 38.5 ± 5.1 | 48.75 ± 9.4 | <0.0001 |
| HOMA-IR ≥ 3.0 → Significant insulin resistance | 11.83 ± 5.4 | 19.10 ± 5.7 | 28.7 ± 10.4 | 40.26 ± 15.7 | <0.0001 |
| Prostate-Specific Antigen (PSA) | 3.8 ± 0.85 | 12.96 ± 3.5 | 10.67 ± 2.4 | 9.48 ± 1.8 | <0.0001 |
| Parameter | Group 2 (Pre-Chemotherapy) | Group 4 (Post-Chemotherapy) | Change (%) | P-Value |
| E. coli isolation rate | 67.5% (27/40) | 80% (32/40) | 12.5 | 0.2 |
| TMP-SMX Resistance | 80% (32/40) | 85% (34/40) | 5 | 0.54 |
| Ciprofloxacin Resistance | 87.5% (35/40) | 90% (36/40) | 2.5 | 0.72 |
| Ceftriaxone Resistance | 57.5% (23/40) | 62.5% (25/40) | 5 | 0.66 |
| Cefotaxime Resistance | 52.5% (21/40) | 55% (22/40) | 2.5 | 0.82 |
| Nitrofurantoin Resistance | 25% (10/40) | 30% (12/40) | 5 | 0.61 |
| Amoxicillin-Clavulanate Resistance | 72.5% (29/40) | 72.5% (29/40) | 0 | 1 |
| Amikacin Resistance | 17.5% (7/40) | 35% (14/40) | 17.5 | 0.08 |
| MDR Rate | 55% (22/40) | 57.5% (23/40) | 2.5 | 0.82 |
| XDR Rate | 20% (8/40) | 25% (10/40) | 5 | 0.6 |
The levels of PCT, IL-6, and TNF-α exhibited substantial variation among the groups (P≤0.01 for all comparisons, Table 2). Group 4 exhibited the highest concentrations of these markers, with substantially elevated levels compared to Groups 1, 2, and 3 (P≤0.01; Figure 1). Group 3 showed a substantial increase in PCT, IL-6, and TNF-α relative to Groups 1 and 2 (P≤0.01) but a modest reduction compared to Group 4 (P≤0.01). In contrast, Group 2 displayed a marked elevation in inflammatory markers compared to Group 1 (P≤0.01), though levels were significantly lower than in Groups 3 and 4 (P≤0.01). Group 1 consistently demonstrated the lowest levels of PCT, IL-6, and TNF-α among all groups (P≤0.01 vs. Groups 2–4). These findings suggest a progressive increase in systemic inflammation with cancer presence and chemotherapy duration (Figure 1).
Fasting glucose, fasting insulin, and HOMA-IR values also varied significantly across groups (P≤0.01, Table 2). Group 4 exhibited the highest levels of these parameters, with substantial increases compared to Groups 1, 2, and 3 (P≤0.01). Group 3 showed a significant rise in fasting glucose, fasting insulin, and HOMA-IR relative to Groups 1 and 2 (P≤0.01), but a slight decline compared to Group 4 (P≤0.01). Notably, No notable variations were detected between Groups 1 and 2 for any metabolic parameter (P>0.05), while Group 2 values were significantly lower than those in Groups 3 and 4 (P≤0.01). These results indicate that chemotherapy, particularly with extended cycles, exacerbates insulin resistance and glycemic dysregulation in diabetic patients with cancer (Figure 2).
PSA levels were significantly elevated in Groups 2, 3, and 4 compared to Group 1 (P≤0.01, Table 2; Figure 3), reflecting the presence of cancer in these cohorts. However, no notable differences in PSA were observed among Groups 2, 3, and 4 (P>0.05), suggesting that Docetaxel chemotherapy, regardless of cycle number, does not significantly alter PSA concentrations in this population. Group 1 maintained the lowest PSA levels (P≤0.01 vs. Groups 2–4), consistent with the absence of cancer.
This study elucidates the multifaceted effects of Docetaxel chemotherapy in type 2 diabetes (T2D) patients with prostate cancer. It demonstrates a dose-dependent escalation of systemic inflammation, metabolic dysregulation, and
The notable increase in inflammatory markers (PCT, IL- 6, TNF-α) across Groups 1–4 (P≤0.01), peaking in Group 4 post-five Docetaxel cycles, underscores chemotherapy’s role in amplifying systemic inflammation. This aligns with prior evidence that taxanes induce cytokine release via cytotoxicity and immune activation [15]. The concurrent rise in PCT, a biomarker of bacterial infection, with IL-6 and TNF-α in Group 4 (Table 2, Figure 1) suggests a synergistic interaction between chemotherapy-induced immunosuppression and infection-driven inflammation [16]. Neutropenia, a common sequela of Docetaxel due to bone marrow suppression [17], likely contributes by impairing neutrophil-mediated bacterial clearance, as evidenced by the increased
The dose-dependent rise in fasting glucose, insulin, and HOMA-IR value from Group 2 to Group 4 (P≤0.01), with no substantial variation between Groups 1 and 2 (P>0.05), indicates that chemotherapy, rather than prostate cancer alone, drives metabolic deterioration in T2D patients (Table 2, Figure 2). This mirrors findings linking chemotherapy to insulin resistance via oxidative stress and pro-inflammatory cytokines [19]. TNF-α, elevated across cancer groups, disrupts insulin signaling by promoting lipolysis and impairing receptor function, while IL-6 inhibits glucose uptake in skeletal muscle [20]. The peak HOMA-IR in Group 4 reflects a vicious cycle where inflammation and metabolic stress reinforce each other, potentially fueling cancer progression by providing glucose to tumor cells [21]. These metabolic shifts underscore the need for glycemic control during chemotherapy to mitigate adverse outcomes [22].
The elevated PSA levels in Groups 2–4 compared to Group 1 (P≤0.01), absent notable disparities among the cancer groups (P>0.05; Figure 3), deviate from the expected PSA decline with effective chemotherapy [23]. This stability may reflect Docetaxel resistance, a known challenge in advanced prostate cancer [24], or interference from infection-induced inflammation. The 12.5% increase in
The trend toward increased
Inflammation, metabolic dysfunction, PSA stability, and bacterial resistance reflect a complicated pathophysiological network. ROS and cytokines (TNF-α, IL-6) from chemotherapy might generate oxidative inflammatory conditions that impair insulin signaling and immune function [29]. Hypoxic tumor regions prevent Docetaxel penetration, and CAFs or P-glycoproteins may promote tumor resistance [10]. Immunosuppression increases the risk of prostatitis and PSA levels from
This suggests using anti-inflammatory medications (IL-6 inhibitors), tight glycemic management, and preventive bacterial prophylaxis to decrease chemotherapy adverse effects in clinical practice. The recurring PSA and resistance patterns emphasize the need for personalized treatment regimens, which may involve resistance testing or alternative treatments if Docetaxel fails.
The study’s limitations include small sample size (n=40/group), reducing statistical power, a cross-sectional design limiting temporal insights, single-center recruitment affecting generalizability, and the absence of microbiome data restricting mechanistic understanding of bacterial resistance. Future studies with larger sample sizes, longitudinal methodologies, and metagenomic investigations can provide a better understanding of the metabolic effects of microbial changes. Analyzing tumor microenvironment alterations with clinical results may help type 2 diabetic patients understand chemotherapy’s efficacy and side effects.
In conclusion, in type 2 diabetes (T2D) prostate cancer patients, Docetaxel, systemic inflammation, metabolic dysregulation, and bacterial resistance interact in complex ways. The data show that chemotherapy promotes insulin resistance, chronic inflammation, and
Mustansiriyah University and Ibn Sina University of Medical and Pharmaceutical Sciences in Baghdad, Iraq, were much appreciated by the authors for their assistance with this endeavor.
The authors report no conflicts of interest.
Study conception & design: (Anwer Jaber Faisa, Baraa Ahmed Saeed). Literature search: (Anwer Jaber Faisal, Baraa Ahmed Saeed, Rabiah Muayad Sabri, Noor Kareem Kadhim, and Bassam Shaker Mahmood). Data acquisition: (Baraa Ahmed Saeed). Data analysis & interpretation: (Anwer Jaber Faisa, Baraa Ahmed Saeed, and Abbas A Mohammed). Manuscript preparation: (Anwer Jaber Faisal, Baraa Ahmed Saeed, Abbas A Mohammed, and Bassam Shaker Mahmood). Manuscript editing & review: (Baraa Ahmed Saeed and Anwer Jaber Faisal).
All data were included in this investigation.