Mete Hakan Karalök

Patient-derived cancer organoids (PDOs) are increasingly used to investigate tumor biology, treatment response, and precision oncology, yet their correspondence to the tumors from which they originate is often summarized using global terms such as “recapitulation” or “fidelity.” Such terminology obscures the fact that tumor–organoid correspondence may differ across genomic, clonal, cellular, spatial, metabolic, organelle, temporal, and therapeutic dimensions. Here, cancer organoid fidelity is reframed as a reference-specific and dimension-specific property organized across three analytically distinguishable but biologically interdependent domains: composition, state, and function. We examine how spatial sampling, tissue processing, culture establishment, matrix and medium composition, oxygen and nutrient availability, passage, and multicellular reconstruction can preserve selected tumor features while reshaping others. This distinction is particularly important for metabolism, mitochondrial and lysosomal function, autophagy and mitophagy, ferroptosis, treatment adaptation, and acquired resistance, for which similar phenotypes may arise through different upstream mechanisms. We introduce Culture-Induced State Distortion (CISD) to describe reproducible culture-associated states that differ from the parental tumor reference and propose the Organoid Fidelity Mapping Framework (OFMF) to classify dimension-specific evidence and define the limits of biological inference. Applying the framework to published colorectal cancer and glioblastoma organoid studies illustrates how validated features can coexist with unassessed dimensions. We also consider how reference availability, experimental resources, and clinical feasibility constrain the assessment and interpretation of fidelity. This framework supports question-driven selection of the minimum sufficient model rather than equating increasing experimental complexity with increasing biological fidelity.

Background and Objectives: Gestational diabetes mellitus (GDM) is characterized by insulin resistance and metabolic dysregulation, in which adipokines may be involved. We evaluated serum Wnt1-inducible signaling pathway protein-1 (WISP-1/CCN4) and C1q/TNF-related protein-1 (CTRP1) in women with GDM and normal glucose tolerance and assessed their relationships with glucose–insulin homeostasis and cross-sectional discriminatory ability. Materials and Methods: This exploratory cross-sectional biomarker study with prospective obstetric follow-up included 100 pregnant women at 24–28 weeks of gestation (50 GDM and 50 controls). WISP-1, CTRP1, HOMA-IR, and GDM status were assessed during the same gestational period; therefore, the principal biomarker analyses were cross-sectional. GDM was diagnosed using the one-step 75-g oral glucose tolerance test criteria recommended by the American Diabetes Association Standards of Care 2026. WISP-1 and CTRP1 were measured by ELISA. Group comparisons, correlation analyses, ROC analyses, nested logistic regression, and bootstrap internal validation were performed. Results: WISP-1 was higher in GDM than in controls (422.80 [387.10–471.85] vs. 315.00 [288.30–351.55] pg/mL; p < 0.001), as was CTRP1 (34.13 ± 6.74 vs. 26.50 ± 5.65 ng/mL; p < 0.001). WISP-1 showed a higher apparent AUC than CTRP1 in the present cohort (0.908 vs. 0.802; DeLong p = 0.034). In the final model adjusted for maternal age and BMI, both WISP-1 (adjusted OR per 1-SD increase 7.53, 95% CI 2.95–19.21; p < 0.001) and CTRP1 (3.61, 95% CI 1.45–8.99; p = 0.006) remained associated with GDM status after adjustment for these covariates. Within GDM, the age- and BMI-adjusted association between WISP-1 and HOMA-IR remained significant (partial ρ = 0.574; p < 0.001), whereas CTRP1 was not associated with HOMA-IR. Conclusions: WISP-1 and CTRP1 were elevated in GDM, with WISP-1 showing a stronger association with HOMA-IR and a higher internally derived AUC in this cohort. These findings support further investigation of WISP-1 and CTRP1 as exploratory metabolic biomarkers associated with GDM but do not establish diagnostic or predictive utility. Independent external validation is required before any potential clinical application.

In just over a decade, in vitro modeling of the female reproductive tract has advanced from planar monolayers of immortalized cells to self-organizing epithelial organoids and, most recently, to increasingly complex multicellular and multicompartment 3D models, including assembloids that combine organoids with additional organoid modules or specialized cell lineages and demonstrate post-assembly integration and self-organization. This review concentrates deliberately on organoid, assembloid, and related multicellular 3D models rather than on reproductive physiology per se. We first establish a criterion-based framework that distinguishes organoids, assembloids, co-cultures, organ-on-chip systems, and blastoids according to assembly strategy, cellular composition, and evidence of structural and functional integration, and trace the rapid consolidation of the assembloid concept from neuroscience into reproductive biology. We then survey, organ-by-organ and with a critical eye, what these models have demonstrated in the endometrium, the ovary and follicle, the fallopian tube, and the embryo–maternal interface, together with the enabling technologies (including microfluidics, vascularization strategies, biomaterials and bioprinting, and single-cell and spatial benchmarking) and the limitations that still constrain the field. We close with emerging translational opportunities in disease modeling, drug and toxicology screening, and personalized reproductive medicine, while highlighting the requirements for physiological validation, reproducibility, standardization, and appropriate ethical and regulatory oversight.

Organelle-selective autophagy is an important regulator of tumor adaptation, immune signaling, and therapeutic resistance. By directing specific intracellular cargos to lysosomal degradation, selective autophagy pathways determine whether organelle damage is eliminated or remains available to innate immune sensors. In cancer, this is particularly relevant because mitochondrial and nuclear damage can generate immunologically active signals that influence tumor–immune interactions. This review examines mitophagy and nucleophagy-related nuclear quality-control mechanisms as regulators of cancer immunity and immunotherapy response. Mitophagy can limit mitochondrial ROS and mtDNA release while supporting metabolic adaptation, whereas nuclear quality-control mechanisms, including lamin B1 degradation, micronuclear clearance, and cGAS-associated micronucleophagy, may regulate the persistence of nuclear-derived DNA signals. We propose the concept of “intracellular immune-signal editing” to describe how organelle-selective autophagy controls the persistence, accessibility, and duration of mitochondrial and nuclear danger signals. The immunological outcome is highly context- and compartment-dependent because autophagy may protect tumor cells while supporting mitochondrial fitness and effector function in immune cells. We also discuss therapeutic implications, biomarkers, and experimental strategies required to distinguish true organelle-selective autophagic flux from static marker changes.

Background: Anti-Müllerian hormone (AMH) is a key biomarker of ovarian reserve, reflecting the quantity of the remaining follicular pool. While chronological age is the primary determinant of AMH concentrations, emerging evidence suggests that vitamin D, vitamin B12, folate, and iron metabolism parameters may also influence ovarian function through mechanisms involving steroidogenesis, DNA synthesis, and oxidative stress regulation. However, clinical findings regarding these associations remain inconsistent. Objective: The aim of this study was to evaluate the relationships between serum AMH concentrations and biomarkers of vitamin D status, vitamin B12, folate, ferritin, and lipid profile in women of reproductive age, and to compare the strength of these associations with that of chronological age. Methods: This retrospective, observational, cross-sectional study included 264 women who underwent AMH testing at Atlas University Hospital. Demographic and laboratory data including AMH, age, vitamin D, vitamin B12, folic acid, ferritin, and lipid parameters were extracted from electronic medical records. Bivariate correlations were assessed using Pearson’s and Spearman’s coefficients on both untransformed and Box–Cox power-transformed data, and were repeated as first-order partial correlations conditioning on chronological age. Statistical significance was set at p < 0.05. Results: The mean age was 34.61 ± 5.75 years, and median AMH was 0.96 ng/mL (Q1–Q3: 0.34–2.34). Age showed a moderate-to-strong, significant inverse correlation with AMH (Pearson’s r = −0.508, Spearman’s rho = −0.547; p < 0.001), and the linear component of this association strengthened after Box–Cox transformation (Pearson’s r = −0.553; p < 0.001). In contrast, vitamin D, vitamin B12, folic acid, ferritin, and lipid parameters (triglycerides, HDL, LDL, total cholesterol) showed no statistically significant and no clinically meaningful correlation with AMH, with all coefficients remaining below 0.20 regardless of transformation (all p > 0.05). After adjustment for age, every coefficient attenuated further towards the null (all |r_partial| < 0.10; all p ≥ 0.127), the largest being that of 25-hydroxyvitamin D (r_partial = 0.094, 95% CI −0.027 to 0.213). A sensitivity power analysis confirmed 80% power to detect an age-adjusted partial correlation of |r| = 0.172 and 91% power at |r| = 0.200. Conclusions: Age remains the principal determinant of ovarian reserve, while vitamin D, vitamin B12, folic acid, ferritin, and lipid parameters show no statistically significant or clinically meaningful association with AMH. These findings suggest that any biological influence of these micronutrients on ovarian reserve, if present, is markedly overshadowed by age-dependent follicular decline. Prospective studies incorporating longitudinal AMH measurements and standardized nutritional assessment are needed to further clarify these relationships.

Ovarian cancer remains a major cause of gynecological cancer-related mortality, highlighting the need for novel therapeutic strategies capable of enhancing antitumor activity while targeting multiple mechanisms involved in tumor progression. Everolimus, an inhibitor of the mammalian target of rapamycin pathway, and carboplatin are established antineoplastic agents with distinct mechanisms of action, whereas astaxanthin is a bioactive carotenoid with antioxidant, anti-inflammatory, and potential anticancer properties. This study compared the individual and pairwise combination effects of carboplatin, everolimus, and astaxanthin on cell viability, migratory capacity, and inflammatory and tumor-associated biomarkers in SKOV3 ovarian cancer cells. Human SKOV3 ovarian cancer cells were cultured under standard conditions and exposed to different concentrations of carboplatin, everolimus, and astaxanthin, either individually or as pairwise two-drug combinations, for 24–72 h. Cell viability was assessed using the Cell Counting Kit-8 (CCK-8) assay. Cell migration was evaluated using a scratch wound-healing assay. Based on the experimental treatment protocol, 100 nM everolimus, 100 μM carboplatin, and 100 μM astaxanthin, alone and in combination, were further evaluated for their effects on β-defensin 1, β-defensin 2, α-defensin 1, tumor necrosis factor-alpha (TNF-α), and interleukin-1 beta (IL-1β) levels. Biomarker concentrations were determined by ELISA. Experiments were independently performed in triplicate. Everolimus, carboplatin, and astaxanthin produced concentration- and time-dependent alterations in SKOV3 cell viability, with more pronounced cytotoxic effects generally observed following prolonged exposure. The pairwise combination treatments also substantially affected cell viability, particularly at later experimental time points. Assessment of migratory capacity demonstrated significant differences in wound closure among treatment groups at 24, 48, and 72 h (p = 0.0224, p = 0.0155, and p = 0.0028, respectively), indicating a time-dependent inhibitory effect on SKOV3 cell migration. Treatment with carboplatin, everolimus, and astaxanthin, individually or in pairwise combinations, also significantly modulated β-defensin 1, β-defensin 2, α-defensin 1, TNF-α, and IL-1β levels compared with control cells, with the magnitude and direction of these changes varying according to treatment regimen and exposure duration. Everolimus, carboplatin, and astaxanthin exerted significant time- and treatment-dependent effects on the viability and migratory behavior of SKOV3 ovarian cancer cells and markedly modulated defensin and pro-inflammatory cytokine responses. The findings demonstrate distinct treatment- and time-dependent responses to the individual agents and their pairwise combinations in SKOV3 ovarian cancer cells. These observations represent preliminary comparative in vitro effects rather than evidence of pharmacological synergy or therapeutic benefit. Further mechanistic studies using additional ovarian cancer cell lines, formal drug interaction analyses, and in vivo models are required to establish the biological and potential therapeutic relevance of these treatment combinations.

Background: Fibroblast growth factor 23 (FGF23) and α-Klotho are key regulators of mineral metabolism and bone homeostasis; however, their combined diagnostic value in postmenopausal osteoporosis remains incompletely understood. This study investigated the associations of serum FGF23, α-Klotho, and the FGF23/α-Klotho ratio with bone mineral density (BMD), bone turnover markers, and their diagnostic performance for postmenopausal osteoporosis. Methods: This cross-sectional study included 165 women divided into three groups: premenopausal healthy controls (n = 55), postmenopausal non-osteoporotic women (n = 55), and postmenopausal women with osteoporosis (n = 55). Serum FGF23 and α-Klotho concentrations were measured by enzyme-linked immunosorbent assay. Bone mineral density was assessed by dual-energy X-ray absorptiometry. Correlation analyses, age- and BMI-adjusted partial correlations, multivariable linear and logistic regression analyses, receiver operating characteristic (ROC) analyses, and incremental diagnostic models were performed. Diagnostic ROC and incremental model analyses were restricted to postmenopausal women (n = 110). Results: Serum FGF23 concentrations and the FGF23/α-Klotho ratio increased progressively across the study groups, whereas α-Klotho levels decreased (all p < 0.001). FGF23 was inversely correlated with lumbar spine, femoral neck, and total hip BMD and T-scores (all p < 0.001), whereas α-Klotho demonstrated positive correlations with all BMD parameters (all p < 0.001). These associations remained significant after adjustment for age and BMI. In multivariable linear regression analyses, the FGF23/α-Klotho ratio showed the strongest independent association with skeletal T-scores (standardized β = −0.379 to −0.404; all p < 0.001). Multivariable logistic regression identified lower 25-hydroxyvitamin D, higher parathyroid hormone, higher FGF23, and lower α-Klotho as independent factors associated with osteoporosis. In analyses restricted to postmenopausal women, the FGF23/α-Klotho ratio showed the highest numerical discriminative performance for osteoporosis (AUC = 0.832, 95% CI: 0.755–0.901), followed by α-Klotho (AUC = 0.793) and FGF23 (AUC = 0.697). The ratio significantly outperformed FGF23 alone (ΔAUC = 0.135, p = 0.001), whereas its performance did not differ significantly from that of α-Klotho (ΔAUC = 0.038, p = 0.270). Adding FGF23 and α-Klotho to age, BMI, and 25-hydroxyvitamin D increased the AUC from 0.743 to 0.882. Conclusions: Serum FGF23 and α-Klotho are independently associated with bone mineral density and are linked to bone turnover markers in postmenopausal women. The FGF23/α-Klotho ratio showed the highest numerical discriminative performance among the evaluated biomarkers, although its performance was not significantly different from that of α-Klotho alone. The combined assessment of FGF23 and α-Klotho provided additional discriminatory information beyond the measured clinical variables. Given the cross-sectional design and lack of external validation, these findings should be considered exploratory and require validation in prospective independent cohorts.

Objective: Anti-Müllerian hormone (AMH) is the most widely used biochemical marker of ovarian reserve, but its associations with other reproductive hormones are usually examined one hormone at a time and without accounting for values reported at the assay floor. This study examined the associations between serum AMH and age, follicle-stimulating hormone (FSH), luteinising hormone (LH), estradiol, progesterone and prolactin in women attending a tertiary gynaecology clinic. Materials and Methods: In this retrospective, cross-sectional, single-centre study, the records of women who underwent serum AMH testing together with a reproductive hormone panel between 1 January 2020 and 31 December 2025 were reviewed. Women with polycystic ovary syndrome, primary ovarian insufficiency, pregnancy or previous ovarian surgery were excluded. Bivariate associations were assessed with Pearson and Spearman correlation coefficients on raw and Box–Cox-transformed variables. Because 12.82% (n = 15) of AMH results were left-censored at the analytical reporting floor of 0.02 ng/mL, a multivariable Tobit model with the censoring limit specified on the Box–Cox-transformed scale (λ = 0.309, threshold = −2.270) was fitted, with predictors selected a priori on clinical grounds. Sensitivity analyses examined the influence of high AMH values, an alternative transformation of AMH, and flexible modelling of age. Results: The analysis included 117 women aged 18–45 years. Mean AMH was 2.22 ± 2.24 ng/mL [median 1.61 ng/mL (Q1–Q3, 0.36–3.20)]. In bivariate correlation analysis, AMH showed statistically significant inverse associations with age (r = −0.376, p < 0.001) and FSH (r = −0.445, p < 0.001), whereas LH, estradiol, progesterone, and prolactin showed no statistically significant correlations with AMH (all p > 0.10). In the multivariable Tobit model, only age (β = −0.068; 95% CI [−0.117, −0.018]; p = 0.007) and transformed FSH (β = −3.582; 95% CI [−4.846, −2.317]; p < 0.001) remained independently associated with transformed AMH. LH, estradiol, progesterone, and prolactin were not independently associated with AMH in the multivariable model (all p > 0.05). The standardised association was greater for transformed FSH (β* = −0.559) than for age (β* = −0.234). The associations of age and FSH were consistent in direction and magnitude across all sensitivity analyses. Conclusions: In this selected clinical sample, age and FSH were the only variables independently associated with serum AMH after mutual adjustment. LH, estradiol, progesterone, and prolactin showed no statistically significant associations with AMH in either the unadjusted bivariate analyses or the multivariable model. The absence of independent associations for these hormones should be interpreted cautiously because hormone sampling was not standardised to menstrual cycle day, which may have introduced measurement variability. These findings describe associations within the study population and do not establish causal relationships, reference intervals, or a basis for modifying testing strategies. The analysis also highlights the importance of accounting for left-censoring when modelling AMH data containing a substantial proportion of results at the assay reporting floor.

Background/Objectives: Human papillomavirus (HPV) is the leading cause of cervical cancer and anogenital malignancies, yet its clinical presentation, genotype distribution, co-infection patterns, and viral load are poorly characterised in tertiary-care referrals. This study aimed to identify predictors of HPV positivity and describe genotype, co-infection, and relative viral copy number (Cq values) in this setting. Methods: A retrospective case–control study of 234 patients (97 HPV-positive, 137 HPV-negative) used a 37-genotype qPCR platform at a tertiary-care hospital between January-December 2025. Demographic data, clinical diagnosis categories, genotype profiles, co-infection patterns, and cycle quantification (Cq) values were recorded, and multivariable logistic regression identified independent predictors of HPV positivity. Results: HPV positivity was 41.5% (97/234). Only the clinical diagnosis category independently predicted HPV status. Compared with non-specific presentations, patients with anogenital or viral warts (aOR: 4.25; 95% CI: 1.49–12.14; p = 0.007) and vaginal or vulvar inflammation (aOR: 2.08; 95% CI: 1.19–3.63; p = 0.010) had higher odds of positivity. High-risk genotypes were the second most frequently detected category (40.00% of detections), after low-risk genotypes (48.21%), with HPV-16 leading among high-risk types. Co-infection occurred in 44.3% of HPV-positive patients, mostly involving mixed-risk genotypes. Patients with anogenital warts had lower Cq values than those with urinary tract complaints (p = 0.011), reflecting higher relative viral copy numbers per swab. Conclusions: HPV positivity and relative viral copy number (as approximated by Cq values) tracked more closely with clinical presentation than with demographic background. The dominance of low-risk and high-risk genotypes and the prevalence of mixed-risk co-infections were consistent with the symptomatic profile of the cohort. These findings support interpreting HPV results in light of clinical presentation and extended genotyping with relative viral copy number quantification in tertiary settings.

Background: Anti-Müllerian hormone (AMH) is widely used as a marker of ovarian reserve and is strongly influenced by chronological age. Although inflammation has been implicated in ovarian aging and follicular dysfunction, whether routinely measured peripheral inflammatory markers provide additional information regarding AMH concentrations remains unclear. Objective: This study aimed to evaluate the age-adjusted associations of C-reactive protein (CRP) and the neutrophil-to-lymphocyte ratio (NLR) with serum AMH concentrations in reproductive-age women. Methods: This retrospective cross-sectional study included women aged 18–45 years with available AMH, complete blood count, and CRP measurements. After reapplying the prespecified eligibility criteria and excluding confirmed data-entry or analytical errors, 819 women were included in the final analysis. NLR was calculated from absolute neutrophil and lymphocyte counts. Because CRP and NLR showed right-skewed distributions, Box–Cox transformations were applied. Associations with Box–Cox-transformed AMH were evaluated using an age-adjusted left-censored Tobit regression model. Results: The mean age of the participants was 34.07 ± 6.94 years, and the median AMH concentration was 1.07 ng/mL (interquartile range, 0.29–2.50). Chronological age was inversely associated with AMH (β = −0.123, 95% CI: −0.135 to −0.111, p < 0.001). After adjustment for age, neither CRP (β = −0.038, 95% CI: −0.085 to 0.009, p = 0.114) nor NLR (β = −0.012, 95% CI: −0.222 to 0.198, p = 0.912) was independently associated with AMH. Conclusions: In this retrospective outpatient cohort, routine peripheral inflammatory markers did not explain additional variation in AMH beyond chronological age. These results do not exclude a potential role for local ovarian inflammation, which may not be adequately captured by peripheral CRP or NLR measurements.