{"paper_id":"af4ab7a8-a53a-4ed7-8c2f-cbb30c114351","body_text":"Orginal Article  | JOGCR. 2026; 11(4): 358-366 \n     Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \n Journal of Obstetrics, Gynecology and Cancer Research | ISSN: 2476-5848 \n \n \nSynergistic Effects of IL-16 and KRAS in Endometriosis with Emphasis on \nOxidative Stress \n \nDeepthi Sudharma1, Natrajan Muninathan2* , Arumugam Suresh2, Mohanalakshmi Parthasarathy3, \nAswathi Ramachandran Krishnakumary 1, Sheeja Mullukalayil Joseph1, Jeena Jose1, Nitha \nNellikuzhimalayil Parameswaran1, Arun Dileep Rajamony Chellammal1, Simi Skariah1,  \nDinesh Roy Divakaran4*  \n \n1. Meenakshi Academy of Higher Education and Research (MAHER - Deemed to be University), West K.K Nagar, \nChennai, Tamil Nadu, India \n2. Central Research Laboratory, Meenakshi Medical College Hospital and Research Institute, Meenakshi Academy of \nHigher Education and Research (Deemed to be University), Kanchipuram, Tamil Nadu, India \n3. Deptartment of Biochemistry, Sri Muthukumaran Medical College Hospital and Research, Chennai, Tamil Nadu, India \n4. Deptartment of Cytogenetics, Genetika Centre for Advanced Genetic Studies, Thiruvananthapuram, Kerala, India \nArticle Info  ABSTRACT \n  \n 10.24200/jogcr.11.4.358 \n \n \n \nBackground & Objective:  Endometriosis is characterized by the growth of \nendometrial-like tissue outside the uterus, leading to inflammation, pain, and infertility. \nIts pathogenesis involves genetic, immunological, and hormonal factors. This study \nexamines the synergistic roles of IL‑16 and KRAS gene expression in endometriosis \nand their interaction with oxidative stress markers to identify potential biomarkers for \ntargeted therapy. \nMaterials & Methods : A case -control study was conducted with 300 subjects, \nincluding 150 cases diagnosed with endometriosis and 150 healthy controls. Gene \nexpression levels of IL‑16 and KRAS were analyzed using real-time PCR. Oxidative \nstress markers, including Superoxide Dismutase (SOD), glutathione peroxidase, and \nvitamin C, along with the inflammatory cytokine IL‑6, were measured. \nResults: IL‑16 and KRAS gene expression levels were significantly elevated in cases \ncompared with controls, with KRAS identified as an independent predictor (P=0.002). \nOxidative stress markers demonstrated a marked reduction in SOD and glutathione \nperoxidase levels, accompanied by decreased vitamin C levels. Elevated IL‑6 levels \n(>5.57 pg/mL, OR=7.91, P=0.032) were associated with increased inflammation and \noxidative stress related cellular damage. \nConclusion: The findings indicate that IL‑16 and KRAS contribute to the progression \nof endometriosis through oxidative stress -mediated genetic alterations and \ninflammatory pathways. The study underscores the combined impact of oxidative \nimbalance, IL‑6 driven inflammation, and KRAS dysregulation in disease pathogenesis. \nUnlike previous research focusing on genetic polymorphisms, this study provides novel \ninsights into gene expression patterns and their clinical implications. Further \ninvestigation into th e mechanistic interactions among IL‑16, KRAS, and oxidative \nstress may aid in the development of targeted therapeutic strategies. \nKeywords: Endometriosis , Genetic expression, IL-16, Inflammatory markers, \nKRAS, Oxidative stress \n \nReceived: 2025/02/08 \nAccepted: 2025/03/18 \nPublished Online: 23 Mar. 2026 \n \n \n \n \n Corresponding Information:  \nNatrajan Muninathan, \nCentral Research Laboratory, Meenakshi \nMedical College Hospital and Research \nInstitute, Meenakshi Academy of Higher \nEducation and Research (Deemed to be \nUniversity), Kanchipuram, Tamil Nadu, India \n \nEmail: muninathanpappaiya@gmail.com \n \nDinesh Roy Divakaran, \nDeptartment of Cytogenetics, Genetika Centre \nfor Advanced Genetic Studies, \nThiruvananthapuram, Kerala, India   \n \nEmail: drdineshroyd@gmail.com \n \n \nCopyright © 2025, This is an original open -access article distributed under the terms of the Creative Commons Attribution-noncommercial \n4.0 International License which permits copy and redistribution of the material just in noncommercial usages with proper citation . \n \n \n1. Introduction\nThe growth of tissue similar to the lining of the uterus \noutside the uterus is known as endometriosis, leading \nto inflammation, pain, and infertility. This condition is \ncommonly attributed to retrograde menstruation  (1). It \naffects approximately 6-10% of women worldwide, of \nwhom 10% are of childbearing age, totaling 247 \nmillion individuals globally and 42 million in India \nalone (2). A variety of factors influence the \ndevelopment of endometriosis, including hormonal \nimbalances, immune system dysfunction, gen etic \npredisposition, surgical scars, and environmental \ntoxins (3). Major contributors to the development and \nprogression of endometriosis include variations in the \nKRAS and IL‑16 genes. \n\n\n359 IL-16, KRAS, and Oxidative Stress in Endometriosise \n      Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \nInterleukins are integral to endometriosis research, as \nthey are key regulators of inflammation, autoimmunity, \nand immune modulation. Prostaglandin E, Tumor \nNecrosis Facto r‑α (TNF‑α), and proinflammatory \ncytokines such as Interleukins (IL‑1, IL‑6, IL‑10, and \nIL‑16) contribute to the development of endometriosis  \n(4). Interleukin‑16 (IL‑16), a lymphocyte \nchemoattractant factor, plays a multifunctional role in \nimmune and inflammatory responses. The \npathogenesis of endometriosis is driven by the \nproduction of key proinflammatory cytokines, such as \nIL‑6, IL‑1β, and TNF‑α , by peripheral blood \nmononuclear cells. These cells are, in turn, stimulated \nby IL‑16  (5). Additionally, recent studies have \nidentified the IL‑16 gene polymorphism rs11556218 as \na potential genetic risk factor for endometriosis, \nsuggesting that this variant may contribute to abnormal \nIL‑16 expression and heightened inflammation (6). \nKRAS (Kirsten rat sarcoma virus) is a critical \noncogenic driver in human cancer and the most \ncommonly mutated gene in the RAS family  (7). It \nencodes a protein that regulates cell‑signaling \npathways involved in cell proliferation, differentiation, \nand survival. KRAS mutations have been observed in \nendometriosis, indicating a possible role in disease \npathogenesis (8). Yachida et al., (2021) confirmed the \nrole of the KRAS p.G12V mutation in the progression \nof ovarian endometriosis and its association with \nelevated inflammation (9). \nOxidative stress is a major factor in the \npathophysiology of endometriosis, as it triggers a \nperitoneal inflammatory response. This stress results \nfrom an imbalance between Reactive Oxygen Species \n(ROS) production and the body’s antioxidant defense \nmechanisms. ROS, which are natural byproducts of \noxygen metabolism, can cause cellular damage, initiate \ninflammation, and support the survival and \nproliferation of endometriotic lesions  (10). Although \nROS are normally neutralized by antioxidant systems \nsuch as superoxide dismutase, glutathione peroxidase, \nand vitamins C and E, an imbalance can lead to \noxidative stress. Additionally, ROS production in the \nperitoneal cavity is enhanced by macrophages, \nerythrocytes, and apoptotic endometrial tissue resulting \nfrom ret rograde menstruation, thereby promoting the \ndevelopment of endometriosis (11). \nBoth IL‑16 and KRAS play critical roles in pathways \nassociated with oxidative stress and inflammation. \nTheir interaction in endometriosis is an emerging area \nof research, and their potential synergistic effects may \ncontribute to disease progression. This s tudy aims to \ninvestigate the combined influence of IL‑16 and KRAS \nin endometriosis, with a particular focus on oxidative \nstress. Understanding these interactions could provide \ndeeper insights into disease pathogenesis and aid in the \ndevelopment of targeted therapeutic strategies.  \n \n2. Materials and Methods \nTo focus on oxidative stress in patients with \nendometriosis, a case -control study was conducted to \nexplore the synergistic effects of the IL‑16 and KRAS \ngenes. The study was approved by the Institutional \nEthics Committee of Genetika (03/2022/IECG), and \ninformed consent was obtained from 300 participants, \nequally divided into 150 cases and 150 healthy controls \nto enhance statistical power. Sample collection was \ncarried out in collaboration with Credence Hospital, \nPran Fertility and Well Woman Centre, PRS Hos pital \nPvt Ltd, Yana Women’s Hospital & Fertility Centre, \nand Genetika, Centre for Advanced Genetic Studies, \nThiruvananthapuram, where the laboratory \ninvestigations were performed.  \nParticipants were aged between 20 and 45 years. \nHealth controls had no history of chronic diseases, \nwere not taking medications that affect oxidative stress \nor gene expression and  provided informed consent. \nEndometriosis cases were diagnosed through clinical \nexamination, laparoscopy, or imaging, had no prior \ntreatment involving KRAS inhibitors or IL‑16 \nmodulators, and provided informed consent. Exclusion \ncriteria included a history  of chronic diseases, current \nuse of medications affecting oxidative stress o r gene \nexpression, pregnancy, recent surgery or significant \nmedical procedures within the last six months, and \ninability to provide informed consent. \nData collection involved demographic, \nphysiological, biochemical, and genetic parameters. \nBlood samples (8-10 mL) were collected and analyzed. \nDemographic and lifestyle information was obtained \nthrough face‑to‑face interviews using a detailed \nquestionnaire. The sample size was calculated using \nthe formula: \nSample size= Z²pq/d², \nWhere Z represents the standard normal deviation, p \ndenotes prevalence, q is 1-p, and d indicates the degree \nof accuracy. The prevalence (p) was derived from \nexisting literature, ensuring a reliable estimate and an \nadequate sample size for the study.  \nGene expression analysis of IL‑16 and KRAS was \nperformed using RT‑PCR techniques with specific \nprimers on the Bio‑Rad CFX Opus 96 Real‑Time PCR \nsystem. For the genetic assessment of the IL‑16 gene, \na 20 μL PCR reaction mixture was prepared, containing \n2× Real‑Time PCR Master Mix, primers, cDNA, and \nnuclease‑free water. Primers for IL‑16 and KRAS were \ndesigned by Eurofins Genomics India Pvt. Ltd. and \nvalidated for specificity. \nThe IL‑16 primers were carefully selected and \nevaluated to ensure specificity. The forward primer \n(TTGGACACAGGGTTCTCGCTCA) was 22 bp in \nlength, with a GC content of 54.55%, a melting \ntemperature ™ of 62.12°C, an annealing temperature \nof 57°C, and a molecular weight of 6.726 g/mol. The \nreverse primer \n(AGCAGGGAGATAACGGACTGAC) was also \n22 bp in length, with a GC content of 54.55%, a melting \n\nDeepthi S, et al. 360 \n      Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \ntemperature of 62.12°C, an annealing temperature of \n57°C, and a molecular weight of 6.842 g/mol. \nThe KRAS primers were designed to ensure \nspecificity and efficiency in real‑time PCR analysis. \nThe forward primer \n(CAGTAGACACAAAACAGGCTCAG) was 23 bp in \nlength, with a GC content of 48%, a melting \ntemperature ™ of 60.65°C, an annealing temperature \nof 53 °C, and a molecular weight of 7059.65 g/mol. \nThe reverse primer \n(TGTCGGATCTCCCTCACCAATG) was 22 bp in \nlength, with a GC content of 55%, a melting \ntemperature of 62.12°C, an annealing temperature of \n57°C, and a molecular weight of 6646.30 g/mol. \nThe PCR steps included denaturation, annealing, and \nextension, followed by melt curve analysis. Gene \nexpression levels were calculated using the 2⁻ΔΔCt \nmethod. Laboratory analyses included sandwich \nenzyme immunoassays for IL‑6, FSH, SOD, \nglutathione peroxi dase, LH, and SDHA, as well as a \ncompetitive inhibition enzyme immunoassay for \nvitamin C. \n \n3. Results \nThis study included 150 individuals diagnosed with \nendometriosis and 150 control subjects to assess the \nclinical, biochemical, hormonal, and genetic alterations \nassociated with the disease. To better understand the \nbackground characteristics of the study p opulation, a \ncomparison was made between the 150 control subjects \nand the 150 cases.  \nAs summarized in Table 1, the two groups did not \nshow any appreciable differences in baseline \nparameters, including age. Oxidative stress markers \nshowed reduced superoxide dismutase and glutathione \nperoxidase levels, while inflammatory markers, \nincluding IL‑6, were elevated. Vita min C levels were \nsignificantly lower in cases (57.3% vs. 20.7%, χ²=42.4, \nP=0.001). SDHA levels were higher in cases \n(44.7%>1.5 ng/mL vs. 28% in controls). Reproductive \nhormone levels varied, with altered FSH and LH levels. \nElevated IL‑16 and KRAS expression suggested a \ngenetic influence on disease progression. \nTable 2 presents a comparative analysis between \ncases and controls across various physiological, \nbiochemical, and genetic parameters. Oxidative stress \nmarkers were notably reduced in cases, with lower \nlevels of superoxide dismutase (2.45±1.82 U/mL vs. \n5.10±2.48 U/mL, P=0.001) and glutathione peroxidase \n(56.2±24.5 ng/mL vs. 67.2 ± 24.9 ng/mL, P=0.001). \nInterleukin‑6, an inflammatory marker, was \nsignificantly elevated in cases (7.74±5.13 pg/mL vs. \n3.18±1.99 pg/mL, P=0.001) \nReproductive hormone analysis indicated that cases \nhad significantly increased FSH levels \n(15.9±5.5 mIU/mL vs. 14.1±5.7 mIU/mL, P=0.004). In \ncontrast, LH levels were lower in cases \n(12.0±5.8 mIU/mL vs. 13.9±3.7 mIU/mL, P=0.001). \nVitamin C levels were significantly reduced in cases \n(1.167±0.716 mg/dL vs. 1.746±0.896 mg/dL, P=0.001). \nGene expression analysis demonstrated that IL‑16 \n(1.483±0.748 vs. 1.006±0.166, P=0.001) and KRAS \n(1.488±0.860 vs. 1.001±0.210, P=0.001) expression \nlevels were significantly higher in cases. Levels of \nsuccinate dehydrogenase complex flavoprotein \nsubunit A were the same between the two groups. \nReceiver Operating Characteristic (ROC) curve \nanalysis of six markers revealed varying degrees of \ndiagnostic performance. Interleukin‑6 demonstrated \nthe most promising results, exhibiting the highest \nsensitivity and specificity among the markers tested. In \ncontrast, FSH was the least informative marker, \nshowing minimal discriminatory power. The IL‑16 and \nKRAS genes displayed reasonably good diagnostic \nperformance. Glutathione peroxidase and LH showed \nintermediate discriminatory power, as shown in \nFigure 1. \n \n \nFigure 1 . ROC curve comparisons of variables for \nidentifying predictors of endometriosis \n \nIL-6 (AUC 0.801, >5.57 pg/mL) and SOD \n(AUC 0.820, ≤3.23 U/mL) demonstrated good diagnostic \npotential. IL-16 (AUC 0.717) and KRAS (AUC 0.681) \nshowed moderate diagnostic value. FSH (AUC 0.595) \nand glutathione (AUC 0.626) exhibited modest sensitivity \nand specifi city. SDHA (AUC 0.536) showed limited \nclinical utility. Vitamin C (AUC 0.697, ≤1.1989 mg/dL) \ndemonstrated moderate predictive value (Table 3). \nThe multivariate binary logistic regression model \n(Table 4) demonstrated strong predictive accuracy \n(86.9%). Significant independent predictors of \nendometriosis included low SOD levels (≤3.23 U/mL, \nOR=112.71, P<0.001), elevated IL‑6 (>5.57 pg/mL, \nOR=7.91, P=0.032), and increased KRAS gene \nexpression (>1.23, OR=13.93, P=0.002). Other \nvariables, including LH, FSH, vitamin C, and IL‑16 \ngene expression, were not statistically significant. \n\n\n361 IL-16, KRAS, and Oxidative Stress in Endometriosise \n      Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \nTable 1. Baseline comparison of demographic and laboratory findings between study groups \n  Control (n=150) Case (n=150) \nχ2 df P \n  n % n % \nAge      1.62 1 0.204 \n ≤35 years 72 48 83 55.3    \n >35 years 78 52 67 44.7    \nSOD      126 1 0.001 \n >3.23 (U/mL) 129 86 32 21.3    \n ≤3.23 (U/mL) 21 14 118 78.7    \nGlutathione \nPeroxidase       15.8 1 0.001 \n >72.2 (ng /mL) 80 53.3 46 30.7    \n ≤72.2 (ng /mL) 70 46.7 104 69.3    \nLH      30.4 1 0.001 \n >12.25 (mIU/mL) 112 74.7 65 43.3    \n ≤12.25 (mIU/mL) 38 25.3 85 56.7    \nFSH      16.1 1 0.001 \n ≤15.86 (mIU/mL) 108 72 74 49.3    \n >15.86 (mIU/mL) 42 28 76 50.7    \nSDHA      9.01 1 0.003 \n ≤1.5 (ng/mL) 108 72 83 55.3    \n >1.5 (ng/mL) 42 28 67 44.7    \nVitamin C      42.4 1 0.001 \n >1.1989 (mg/dL) 119 79.3 64 42.7    \n ≤1.1989 (mg/dL) 31 20.7 86 57.3    \nInterleukin-6      86.9 1 0.001 \n ≤5.57 (pg/mL) 130 86.7 51 34    \n >5.57 (pg/mL) 20 13.3 99 66    \nIl-16 Gene      76 1 0.001 \n ≤1.23 136 90.7 65 43.3    \n >1.23 14 9.3 85 56.7    \nKRAS Gene      62.1 1 0.001 \n ≤1.23 127 84.7 61 40.7    \n >1.23 23 15.3 89 59.3    \nSOD: Superoxide dismutase, LH: Luteinizing hormone, FSH: Follicle-stimulating hormone, SDHA: Succinate dehydrogenase complex \nflavoprotein subunit A, IL-6: Interleukin-6, IL-16: Interleukin-16 gene, KRAS: Kirsten rat sarcoma viral oncogene homolog, χ² - Chi-square test \nvalue, df -Degrees of freedom. The results are expressed as numbers (%). P<0.05 is statistically significant. \n\nDeepthi S, et al. 362 \n      Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \nTable 2. Comparison of Physiological, Biochemical, and Genetic Parameters Between Study Groups \n Control (n=150) Case (n=150) t test \nmeans SD means SD t P \nSuperoxide dismutase (U/mL) 5.10 2.48 2.45 1.82 10.568 0.001 \nGlutathione Peroxidase (ng /mL) 67.2 24.9 56.2 24.5 3.845 0.001 \nInterleukin 6 (pg/mL) 3.18 1.99 7.74 5.13 10.152 0.001 \nFSH (mIU/mL) 14.1 5.7 15.9 5.5 2.921 0.004 \nLH (mIU/mL) 13.9 3.7 12.0 5.8 3.339 0.001 \nSuccinate Dehydrogenase Complex \nFlavoprotein Subunit A (ng/mL) 1.453 0.950 1.599 1.118 1.221 0.223 \nVitamin C (mg/dL) 1.746 0.896 1.167 0.716 6.189 0.001 \nIL-16 gene 1.006 0.166 1.483 0.748 7.616 0.001 \nKRAS gene 1.001 0.210 1.488 0.860 6.733 0.001 \nThe results are expressed as mean±standard deviation (SD). P-values are derived from an independent sample t-test. SDHA: Succinate \nDehydrogenase Complex Subunit A; IL-16: Interleukin-16; KRAS: Kirsten Rat Sarcoma Viral Oncogene Homolog. P<0.05 is statistically significant. \n \n \n \nTable 3. AUC Values for Biomarkers in Endometriosis \nVariable AUC se 95% CI z statistic P Youden \nindex \nOptimu\nm cut off \nSensiti\nvity \nSpecifici\nty +LR -LR PPV NPV \nFSH \n(mIU/mL) 0.595 0.033 0.537 to 0.651 2.888 0.004 0.227 >15.86 50.67 72 1.81 0.69 64.4 59.3 \nGlutathione \nPeroxidase \n(ng /mL) \n0.626 0.032 0.568 to 0.681 3.929 0.001 0.227 ≤72.2 69.33 53.33 1.49 0.58 59.8 63.5 \nIL-16 gene 0.717 0.032 0.663 to 0.768 6.883 0.001 0.473 >1.23 56.67 90.67 6.07 0.48 85.9 67.7 \nInterleukin-6 \n(pg/mL) 0.801 0.026 0.751 to 0.845 11.489 0.001 0.526 >5.57 66 86.58 4.92 0.39 83.2 71.7 \nKRAS gene 0.681 0.033 0.625 to 0.734 5.445 0.001 0.440 >1.23 59.33 84.67 3.87 0.48 79.5 67.6 \nLH \n(mIU/mL) 0.638 0.033 0.580 to 0.692 4.173 0.001 0.313 ≤12.25 56.67 74.67 2.24 0.58 69.1 63.3 \nSDHA \n(ng/mL) 0.536 0.034 0.478 to 0.594 1.08 0.001 0.167 >1.5 44.67 72 1.6 0.77 61.5 56.5 \nSOD (U/mL) 0.82 0.026 0.772 to 0.862 12.298 0.001 0.647 ≤3.23 78.67 86 5.62 0.25 84.9 80.1 \nVitamin C \n(mg/dL) 0.697 0.030 0.642 to 0.749 6.534 0.001 0.367 ≤1.1989 57.33 79.33 2.77 0.54 73.5 65 \nAUC: Area Under the Curve, a measure of diagnostic accuracy, SE: Standard error of AUC, CI: Confidence Interval (95%), +LR: Positive \nLikelihood Ratio, -LR: Negative Likelihood Ratio, PPV: Positive Predictive Value, NPV: Negative Predictive Value, Optimum cutoff values \nwere determined using the Youden index. Higher AUC values indicate better diagnostic performance. \n \n \nTable 4. Logistic Regression Analysis of Predictors for Endometriosis \n B  S.E.  Wald  df  P OR  95% C.I. for OR \nLower Upper \nSOD 4.725 1.193 15.692 1 0.001 112.71 10.88 1167.41 \nGlutathione Peroxidase 1.594 0.882 3.265 1 0.071 4.93 0.87 27.76 \nLH 0.495 0.707 0.49 1 0.484 1.64 0.41 6.56 \nFSH 0.537 0.777 0.479 1 0.489 1.71 0.37 7.84 \nSDHA 0.551 0.76 0.525 1 0.469 1.74 0.39 7.70 \nVitamin C 0.337 0.692 0.237 1 0.627 1.40 0.36 5.44 \nInterleukin-6 2.068 0.965 4.594 1 0.032 7.91 1.19 52.45 \nIL-16 Gene 0.535 0.989 0.293 1 0.588 1.71 0.25 11.86 \nKRAS Gene 2.634 0.834 9.97 1 0.002 13.93 2.72 71.46 \nConstant -12.238 2.611 21.974 1 0.000      \nB: Regression coefficient, indicating the strength and direction of the relationship between the variable and the outcome, S.E.: Standard error of \nthe regression coefficient, Wald: Wald test statistic, assessing the significance of each predictor, df: Degrees of freedom for the Wald test, P: P-\nvalue, indicating statistical significance (p < 0.05 is considered significant), OR: Odds Ratio, representing the likelihood of the outcome \noccurring with each unit increase in the predictor, 95% C.I. for OR (Lower, Upper): Confidence interval, showing the range within which the \ntrue odds ratio is likely to fall, Constant: Intercept of the logistic regression model. \n\n363 IL-16, KRAS, and Oxidative Stress in Endometriosise \n      Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \n4. Discussion \nWe designed this case -control study to investigate \nthe synergistic effects of IL‑16 and KRAS gene \nexpression in endometriosis, with a specific focus on \ntheir interaction with oxidative stress markers. This \nstudy identified that IL‑16 and KRAS gene expression \nlevels were lower in the control group than in the case \ngroup, as shown in Table 1. While previous research \nhas predominantly focused on polymorphic variations, \nthe present findings highlight a potential interaction \nbetween these genes in the pathophysi ology of \nendometriosis. Oxidative stress acts as a disease \npromoter, and the observed gene expression patterns \nsuggest a link between inflammatory pathways and \noxidative damage. Further research is required to \nelucidate the mechanistic roles of IL‑16 and K RAS in \noxidative stress -mediated endometriosis, as indicated \nby these findings. \nRecent studies have highlighted the role of IL‑16 \ngene polymorphisms in disease susceptibility. Notably, \nthe IL‑16 rs4778889 variant has been implicated as a \npotential genetic marker for endometriosis in Nigerian \nand African populations, suggesting ethnic‑ specific \ngenetic predispositions (6). IL‑16 gene polymorphisms \nare associated with the development of endometriosis \nand may be used as predictive risk factors for \nsusceptibility to the disease (12).  \nPrevious studies have primarily focused on the role \nof KRAS in ovarian and other gynecological \nmalignancies, with limited evidence linking it to \nendometriosis. Soliman et al. , (2018) suggested that \nany risk of endometriosis associated with common \nKRAS variations is likely minimal  (13). Additionally, \nSuda et al. , (2018) identified KRAS mutations in \novarian endometriosis, reporting that 42.6% (23/54) of \ncases harbored somatic KRAS mutations  (14). \nHowever, these studies did not establish KRAS as an \nindependent predictor of endometriosis. \nIn contrast, a novel finding of the current study is the \nidentification of KRAS as a significant and \nindependent predictor of endometriosis ( P=0.002), as \nshown in Figure 1. Unlike the diffuse and \nhomogeneous distribution of KRAS p.G12V mutations \nobserved in ovarian cancer, KRAS mutant allele \nexpression was detected in only two endometriosis \ncases, and the mutation signals in endometriosis \nappeared more spatially distinct (8).  \nThe synergistic effect of IL‑16 and KRAS in \nendometriosis has not been explored in previous \nresearch, making this study the first to investigate their \ncombined influence. While KRAS has been implicated \nin ovarian endometriosis and identified as an \nindependent predictor in the current study ( P=0.002), \nno prior studies have examined its potential interaction \nwith IL‑16  (14). The absence of such investigations \nhighlights a critical gap in understanding the molecular \nmechanisms underlying endometriosis. \nOxidative stress can lead to cellular damage, \ninflammation, and fibrosis, thereby exacerbating the \nsymptoms of endometriosis (15). The development and \nprogression of endometriosis were assessed by \nexamining the roles of various enzymatic and \nnon‑enzymatic oxidative stress markers. The \nenzymatic markers included Superoxide Dismutase \n(SOD), glutathione peroxidase, and Succinate \nDehydrogenase (SDHA), while the non‑enzymatic \nmarker assessed was vitamin C. Our aim was to \ndetermine how these oxidative stress markers \ncontribute to genetic defects associated with the \nprogression of endometriosis. \nFindings from this study revealed that SOD levels \nwere significantly higher in the control group \ncompared with the case group, as shown in Table 2. \nReduced SOD activity has been reported in the \nperitoneal fluid of women affected by endometriosis, \nleading to an imbalance in oxidative stress regulation \nand significantly contributing to disease \npathophysiology (16). This reduction suggests \ndysregulated oxidative stress control which, in \ncombination with inflammatory mediators such as \nIL‑16, may enhance cellula r damage and promote \ngenetic instability. \nSimilarly, the present study observed significantly \nhigher glutathione peroxidase levels in the control \ngroup (67.2±24.9 ng/mL, P=0.001) compared with the \ncases (56.2±24.5 ng/mL), as indicated in Table 1. \nThese findings are consistent with previous reports \nsuggesting that SOD and glutathione peroxidase levels \nare lowest in patients with severe‑stage endometriosis  \n(17). Reported SOD and GPx activities in disease and \ncontrol groups were 6.15 and 8.11, and 463.9 and \n472.34 nmol/min/mL, respectively (18). \nFurthermore, different phases of the menstrual cycle \nhave been shown to exhibit varying expression of \noxidative stress markers. Zwahlen et al. , (2024) \nreported that expression was minimal during the early \nproliferative phase, gradually increased, peaked during \nthe early secretory phase, and subsequently declined. \nThis cyclical pattern may indicate hormonal influences \non oxidative stress mechanism s in endometriosis. \nOverall, the observed alterations in oxidative stress \nmarker levels emphasize the critical ro le of oxidative \nimbalance in the progression of endometriosis (19). \nIn the present study, SDHA exhibited limited clinical \nutility (AUC 0.536), as shown in Table 3. The role of \nSDHA in endometriosis remains largely unexplored, as \nmost existing research has predominantly focused on \nits involvement in endometrial and ovarian cancers. \nThe scarcity of studies examining SDHA in the context \nof endometriosis highlights the need for further \ninvestigations to determine its potential significance in \ndisease pathophysiology. Future studies focusing on \nthe impact of SDHA expression on m itochondrial \nfunction and oxidative stress in endometriosis may \nprovide deeper insights into its role in disease \nprogression. \n\nDeepthi S, et al. 364 \n      Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \nIn the current study, vitamin C levels were \nsignificantly reduced in cases (1.167±0.716 mg/dL) \ncompared with controls (1.746± 0.896 mg/dL, \nP=0.001). Additionally, vitamin C demonstrated \nmoderate predictive value for endometriosis \n(AUC 0.697, ≤1.1989 mg/dL), as shown in Table 3. \nThese findings are consistent with previous research \nby Lu et al. , (2018), which reported lower serum and \nFollicular Fluid (FF) levels of vitamin C and SOD in \nindividuals with endometriosis compared with healthy \ncontrols (20). The reduction in vitamin C levels \nsuggests a compromised antioxidant defense system, \nwhich may contribute to increased oxidative stress, \ninflammation, and subsequent disease progression. \nThe current study also highlights the role of IL‑6 in \nthe pathophysiology of endometriosis, demonstrating \nsignificantly elevated levels in affected individuals. \nIncreased IL‑6 levels (>5.57 pg/mL, OR=7.91, \nP=0.032) were identified as a significant predictor of \nthe disease. IL‑6 is a pro‑inflammatory cytokine known \nto enhance immune cell recruitment and inflammatory \nresponses, thereby exacerbating oxidative stress -\ninduced damage in endometrial tissue  (21). The \nobserved increase in IL‑6 levels suggests a stro ng \nassociation between inflammatory responses and \ndisease severity.  \nWhen comparedometriosis literature, previous \nstudies have likewise reported elevated IL‑6 levels in \npatients with endometriosis, correlating with an \nincreased inflammatory burden and impaired immune \ntolerance (22). However, variations in IL‑6 expression \namong different studies may be attributed to \ndifferences in patient populations, disease stage, and \nmethodological approaches. The current study further \nsupports IL‑6 as a potential marker of \ninflammation‑induced ox idative stress, as evidenced \nby its associa tion with reduced antioxidant enzyme \nlevels (SOD, glutathione peroxidase, and vitamin C). \nDespite its statistical significance ( P=0.032, \nOR=7.91), the precise mechanistic link between IL‑6 \nand KRAS/IL‑16 gene dysregulation in endometriosis \nremains unclear and warrants further investigation. \nIL‑6 may contribute to KRAS activation through \ninflammatory signaling pathways, thereby promo ting \naberrant cellular proliferation and fibrosis. In addition, \nIL‑6‑induced oxidative stress may exacerbate \nepigenetic modifications, leading to altered gene \nexpression patterns in endometrial lesions. \nFurthermore, KRAS gene expression (>1.23, \nOR=13.93, P=0.002) was identified as a significant \ngenetic determinant of endometriosis. As a key \nregulator of cell proliferation and survival, KRAS \noverexpression may contribute to uncontrolled cellular \ngrowth and genetic instability, thereby further \npromoting the i mplantation and invasion of ectopic \nendometrial tissue. The present findings suggest that \nvariables such as LH, FSH, vitamin C, and IL‑16 gene \nexpression were not major statistical predictors in the \nmultivariate model, as indicated in Table 4; however, a \npotential synergistic interaction appears to exist \nbetween oxidative stress, IL‑6‑driven inflammation, \nand KRAS‑mediated genetic alterations in the \npathophysiology of endometriosis.  \nAlthough vitamin C plays a role in counteracting \noxidative stress, its independent contribution may be \nlimited due to interactions with other antioxidant and \ninflammatory pathways. Similarly, while IL‑16 has \nbeen implicated in immune modulation, its direct  role \nin driving the progression of endometriosis remains \nunclear. \nThe findings of this study emphasize the synergistic \ninterplay between oxidative stress markers, \nIL‑16‑mediated inflammation, and KRAS‑driven \ngenetic alterations in the pathogenesis of \nendometriosis. The combined effects of oxidative \nstress-induced damage and inflammatory responses \nmay contribute to genetic instability, thereby \naccelerating disease progression. \nThis study has several limitations that should be \nacknowledged. One important confounding factor is \nthe timing of sample collection in relation to the \nmenstrual cycle. Hormonal fluctuations throughout the \ncycle can influence inflammatory markers, oxidative  \nstress levels, and gene expression patterns, potentially \naffecting the observed IL‑6, KRAS, and IL‑16 levels. \nStandardizing sample collection according to specific \nmenstrual phases in future studies would help \nminimize variability and improve biomarker accuracy. \nAdditionally, factors such as the heterogeneity of \nendometriosis cases, including variations in disease \nseverity and lesion location, may have influenced the \nfindings. The study also did not account for potential \nconfounders such as prior hormonal treatmen ts or \nenvironmental exposures, which could affect \ninflammatory and oxidative stress responses. Future \nresearch should explore the mechanistic pathways \nlinking IL‑16 and KRAS gene expression with \noxidative stress and inflammation in endometriosis. \nLarger, multicenter studies involving diverse \npopulations are needed to validate these findings and \nassess their clinical applicability. Furthermore, \ninvestigating potential therapeutic interventions \ntargeting KRAS and oxidative stress markers may offer \nnovel treatment strategies for endometriosis. \n \n5. Conclusion \nThis study highlights the synergistic role of IL‑16 \nand KRAS in endometriosis, linking their \noverexpression to disease progression. KRAS emerged \nas a significant independent predictor. Markers of \noxidative stress, including reduced SOD, glutathione \nperoxidase, and vitamin C, together with elevated IL‑6, \nreflect a state of inflammation, oxidative imbalance, \nand genetic instability. These findings suggest that \noxidative stress, IL‑6‑driven inflammation, and \n\n365 IL-16, KRAS, and Oxidative Stress in Endometriosise \n      Volume 11, April 2026       Journal of Obstetrics, Gynecology and Cancer Research \nKRAS‑mediated genetic alterations collectively \ncontribute to the pathogenesis of endometriosis. \nIn contrast to previous studies focused primarily on \ngenetic polymorphisms, this study provides novel \ninsights based on gene expression analysis. Future \nstudies should validate these findings in larger \npopulations and further explore therapeutic targets \ninvolving KRAS and oxidative stress–related pathways \nin endometriosis. \n \n6. Declarations \nAcknowledgments \nWe sincerely appreciate the support and resources \nprovided by Meenakshi Academy of Higher Education \nand Research, Chennai, Tamil Nadu, India, and \nGenetika, Centre for Advanced Genetic Studies, \nThiruvananthapuram, Kerala, India. \n \nEthical Considerations \nEthical approval (03/2022/IECG) was secured from \nthe Institutional Ethics Committee of Genetika. \n \nAuthors' Contributions \nConceptualization: Deepthi S, N Muninathan, \nDinesh Roy D, Data curation: Deepthi S, Sheeja M J, \nJeena Jose, Nitha N P, Arun Dileep R C, Simi Skariah, \nFormal analysis: Deepthi S, A Suresh, P Mohana \nLakshmi, Investigation: Deepthi S, Sheeja M J, Jeena \nJose, Nitha N P, Arun Dileep R C, Simi Skariah, \nMethodology: Deepthi S, N Muninathan, A Suresh, \nProject administration: Dinesh Roy D, Resources: \nDeepthi S, N Muninathan, Supervision: N Muninathan, \nDinesh Roy D, Validation: P Mohana Lakshmi, A \nSuresh, Visualizati on: Deepthi S, Writing – original \ndraft: Deepthi S, Writing – review and editing: N \nMuninathan, Dinesh Roy D. \n \nConflict of Interest \nAll authors declare that they have no conflicts of \ninterest. \n \nFund or Financial Support \nThere are no funding sources to report. \n \n \n \n \n \n1. 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Immunol Lett. 2018;201:31-7. \n[doi:10.1016/j.imlet.2018.10.011] \n22. Kashanian M, Sariri E, Vahdat M, Ahmari M, \nMoradi Y, Sheikhansari N. Comparison of \nserum IL -6 and CA125 in patients with \nendometriosis and controls. Med J Islam \nRepub Iran. 2015;29:280.  \n \n \n \n How to Cite This Article:  \nDeepthi S, Muninathan  N, Suresh A, Mohana Lakshmi  P, Aswathi R K, Sheeja M J , et al. Synergistic Effects of \nIL-16 and KRAS in Endometriosis with Emphasis on Oxidative Stress : A Randomized Controlled Trial. J Obstet \nGynecol Cancer Res. 2026;11(4):358-366. \nDownload citation:                             RIS | EndNote | Mendeley |BibTeX |","source_license":"CC0","license_restricted":false}