Duygu Aygunes Jafari

Background/Objectives: A fixed splice-junction panel for hepatocellular carcinoma (HCC) requires junctions recurring across patients and absent from normal tissue; absence is inferred from non-detection in finite references. Methods: Across 300 secreted, membrane-protein and HCC-associated genes, 1,263,305 junctions were screened for recurrence (≥30%) in 374 TCGA-LIHC tumours and absence in 50 matched normals and 251 GTEx liver samples. Results: No junction met the pre-specified criteria. Widely recurring junctions occurred in normal tissue; of 981 canonical junctions meeting both absence criteria, 740 were seen in one tumour. Post hoc, 8 of the 981 exceeded 11.63%, the prevalence below which non-detection in 50 normals does not demonstrate absence. None reached 30%; they reflect TERT expression, UGT1A first-exon choice, and a UGT2B readthrough of unresolved origin also present in normal breast. Twenty such junctions covered 63.9% of held-out tumours (post hoc), with absence assumed for most. Positive controls from other cancers were recovered. Genome-wide (post hoc), 18 junctions met all criteria, 17 at loci silent in normal liver. Conclusions: No panel junction was both recurrent and demonstrably absent from normal liver; genome-wide, such junctions mostly reflected expression of these silent loci, not tumour-specific splicing. Reporting the prevalence above which absence is demonstrable is recommended.

Background/aim: Astaxanthin, a marine carotenoid, shows antiproliferative activity across cancer models, but its reported mechanisms vary widely by cell type and comparative studies with a common protocol are scarce. This study compared MCF-7 breast (estrogen/ progesterone receptor-positive; wild-type TP53) and OVCAR-3 ovarian carcinoma (high-grade serous; homozygous TP53 R248Q) cells after astaxanthin treatment at cell-line-specific IC50 concentrations. Materials and methods: Cytotoxicity was measured by WST-1, apoptosis by annexin V/propidium iodide flow cytometry, and 43 cancer-associated genes by a pathway-focused RT-qPCR array (n = 3). Relative expression was calculated by comparative ΔΔCt method with ACTB as the reference gene. Results: At 72 h, the IC50 values were 27 μM (MCF-7) and 43 μM (OVCAR-3). Annexin V positivity rose by 7–8 percentage points in both lines, dominated by late apoptotic cells. The shared response comprised downregulation of PTEN and BIRC5 and upregulation of MGMT, with the extreme MCF-7 PTEN signal read cautiously. BRCA1 showed a possible concordant decrease but was low-confidence in MCF-7. The lines otherwise diverged: OVCAR-3 induced apoptosis-associated and checkpoint genes (BAX, BAD, APAF1, SFN), whereas MCF-7 altered PI3K/AKT regulators (PTEN, AKT1), with AKT1 moving in opposite directions. Conclusion: Under one matched protocol, astaxanthin produced a defined transcriptional response in both carcinomas: a narrow shared core alongside larger cell-type-specific programs, namely PI3K/AKT-associated regulators in MCF-7 and a coordinated apoptosis and checkpoint program in OVCAR-3. This side-by-side design clarifies which effects are conserved and which are cell-of-origin-specific, establishing that the response is strongly context-dependent. The dissociation between the modest annexin V positivity and the larger WST-1 viability loss further indicates that apoptosis is not the sole effector, with cytostatic or metabolic mechanisms likely contributing. Profiling astaxanthin in OVCAR-3, not previously reported, alongside MCF-7, this study delineates shared and divergent candidates (PTEN, MGMT, mutant TP53, and the OVCAR-3 apoptosis axis) for protein-level validation.

Background/Objectives: Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease, and cellular senescence is a tractable therapeutic target; yet prioritizing credible repurposing candidates is difficult because bulk-tissue senescence signals are weak, single-dataset analyses are unstable, and transcriptome-reversal screens overstate novelty. The objective was to build a senescence-anchored, multi-evidence computational prioritization of repurposing candidates for DKD entirely from open data. Methods: Per-sample senescence activity was quantified by single-sample gene set enrichment across three DKD kidney cohorts, and consensus signatures were reversed against 45,956 LINCS L1000 signatures. Candidates were ranked by reversal strength, mechanism, ChEMBL stage, and ClinicalTrials.gov novelty, then assessed for robustness by senotherapeutic enrichment, an external senolytic benchmark, leave-one-cohort-out analysis, drug–target Mendelian randomization, and single-nucleus profiling. Results: Senescence activity was consistently elevated in DKD across all three cohorts, with moderate-to-large effect sizes (rank-biserial 0.32–0.78). Reversal recovered established senotherapeutic classes and nominated the approved JAK inhibitor fedratinib (within the same class, baricitinib reduced albuminuria in a Phase 2 DKD trial); curated senolytics were modestly separated from negatives (AUROC 0.62, 95% CI 0.52–0.72). Filtering yielded 867 mechanism-annotated compounds robust to cohort removal. Drug–target Mendelian randomization was inconclusive, and single-nucleus profiling highlighted endothelial activation rather than a stable senescent compartment. Conclusions: The result is an externally benchmarked, novelty-annotated senotherapeutic candidate map, offered as convergent confirmation of repurposable mechanisms rather than a claim of new drug classes.

Major depressive disorder (MDD) continues to be diagnosed using subjective clinical assessment, without validated biological tests to confirm the diagnosis, predict its course, or match patients to effective treatments. This chapter reviews the molecular pathways most consistently implicated in MDD (monoaminergic and glutamatergic–GABAergic signalling, neuroinflammation, impaired neuroplasticity, hypothalamic–pituitary–adrenal axis dysfunction, and the microbiota–gut–brain axis), and evaluates how genomics, transcriptomics, proteomics, and metabolomics are being used to identify diagnostic, prognostic, and treatment-predictive biomarkers. Candidate markers, machine-learning approaches, sex-related heterogeneity, and biomarkers shared with common comorbidities are examined, together with the barriers that keep such markers from clinical use. The evidence indicates that no single molecule is likely to capture a disorder as heterogeneous as MDD, and that integrative, multimodal panels validated in large cohorts offer a more realistic route toward precision psychiatry.

Objective: Triple-Negative Breast Cancer (TNBC) is characterized by aggressive behavior and reliance on taxanes like Docetaxel. Although hyperinsulinemia is linked to poor prognosis, the transcriptional mechanisms by which physiological versus supra-physiological insulin levels modulate taxane-induced stress remain poorly defined.Materials and Methods: MDA-MB-231 cells were treated with Docetaxel (5nM) alone or combined with physiological (5 ng/mL) and supra-physiological (19 ng/mL) insulin. Expression of survival (AKT1, MAPK1), apoptotic (CASP8, CASP9) and cell cycle (CDKN1A, CDKN1C) markers was analyzed using quantitative Real-Time PCR.Results: Docetaxel monotherapy triggered transcriptional changes consistent with mitotic arrest and apoptosis, as indicated by the upregulation of CDKN1A, CDKN1C and executioner caspases. Insulin co-treatment significantly attenuated this cytotoxic response. Notably, a non-linear dose response emerged: while MAPK1 signaling increased linearly with insulin concentration, the suppression of apoptotic and cell cycle arrest markers was most potent at physiological levels. Reduced suppression at supra-physiological doses suggests the activation of negative feedback loops.Conclusion: Insulin co-treatment induces a transcriptional profile consistent with reduced docetaxel sensitivity, characterized by sustained proliferative signaling and attenuation of apoptotic and cell cycle arrest responses at the transcriptional level. Importantly, even low-dose insulin was sufficient to attenuate pro-apoptotic transcriptional responses, suggesting that the tumor microenvironment may modulate chemotherapy efficacy independent of systemic metabolic syndrome. These findings suggest the insulin signaling axis as a potential modulator of chemotherapy response in TNBC.

Aim: Ovarian cancer is a highly lethal gynecologic malignancy, accounting for more deaths than any other female reproductive cancer. Standard chemotherapy often fails over time due to chemoresistance and toxic side effects, resulting in poor five-year survival rates under 40%. There exists an increasing scholarly interest in phytochemicals as potential anticancer agents, attributable to their multifaceted mechanisms of action and comparatively reduced toxicity profiles. Pimenta dioica (allspice) berries are rich in antioxidants and contain bioactive compounds such as eugenol and gallic acid with reported antiproliferative properties. However, their effects in ovarian cancer remain underexplored. Materials and Methods: P. dioica extract was evaluated on human ovarian adenocarcinoma OVCAR-3 cells. Cytotoxicity was assessed by WST-1 viability assays across a 12.5-200 µg/mL dose range (48-72 h exposure) to determine IC₅₀ values. Apoptosis induction was analyzed by Annexin V-FITC /PI via flow cytometry. Expression of apoptosis related genes (BAX, BCL-2, CASP3, CASP9 and TP53) was quantified by qRT-PCR. Results: P. dioica extract inhibited OVCAR-3 cell viability in dose and time dependent manner (p

Objective: Reduced cerebral glucose metabolism is a defining feature of Alzheimer's disease (AD), and brain insulin resistance is widely invoked but defined at the level of receptor signaling, not transcript abundance. Whether the donor-level transcriptional signature of that axis rises, falls, or is unchanged in AD was examined using a cross-cohort, cell-type-resolved design with a pre-specified external test. Material and Methods: Four a-priori metabolic gene signatures (glucose delivery, astrocytic support, neuronal utilization, and insulin signaling; 123 genes fixed before any expression data were examined) were scored per nucleus within their own cell-type compartment and averaged to one value per donor in four single-nucleus RNA-seq cohorts (57 donor-level units). Effects were pooled by random-effects meta-analysis of Hedges' g (AD versus control) with the modified Hartung–K-napp estimator, complemented by a donor-label permutation test; pathway specificity was tested against 1000 size- and expression-matched random gene sets, and direction was examined at single-gene resolution and in one pre-specified external cohort. Results: The insulin signature showed a positive effect estimate in all four cohorts (per-cohort Hedges' g +1.11, +0.92, +0.29, +0.56). The primary few-studies estimator gave pooled g = +0.73 (95% CI −0.10 to +1.56, p = .067); the donor-label permutation p, a secondary inference, was .006, and the direction was unchanged in every leave-one-cohort-out analysis. The signature exceeded matched-random gene sets in the largest discovery cohort (empirical p = .001) and in the second-largest cohort (p = .019), but not in the two smallest (p = .55 and .28; Fisher combined p = .001). The external cohort reproduced the direction but not specificity. Neuronal utilization showed a negative estimate in all four cohorts (g = −0.49, 95% CI −1.29 to +0.32, p = .15), led by Complex I subunits. Conclusion: Across four cohorts the neuronal insulin-signaling transcriptional program shows a directionally consistent positive trend rather than the suppression a transcript-level reading of brain insulin resistance might assume. The trend is not statistically established under the primary estimator and is hypothesis-generating; because transcript abundance does not report phosphorylation, it is compatible with compensatory transcriptional feedback and marks a target for proteomic follow-up.

Gene polymorphisms involved in cardiac development are increasingly recognized as key contributors to congenital heart disease (CHD), often co-occurring with neonatal anomalies and malignancy risk. Disruptions in developmental pathways such as RAS/MAPK, Notch, and Wnt not only affect cardiac morphogenesis but also exert pleiotropic effects across multiple organ systems. Syndromic CHDs, including Noonan, Alagille, and 22q11.2 deletion syndromes, demonstrate well-established links between specific genetic variants, structural anomalies, and elevated cancer susceptibility. Non-syndromic CHD genes, such as NKX2-5, GATA4, and TBX20, typically lead to isolated cardiac defects, though emerging evidence suggests subtle associations with oncogenic processes. Polygenic risk, copy number variations, and gene–environment interactions further complicate the genetic landscape. Understanding these interrelated mechanisms supports the integration of genomic data into early diagnosis, clinical management, and personalized surveillance strategies for both cardiac and oncologic outcomes.

Breast cancer remains one of the most prevalent malignancies worldwide, with chemotherapy serving as a cornerstone of treatment despite its substantial toxicity risks. Carboxylesterase 1 (CES1), a critical drug-metabolizing enzyme, plays a central role in the activation and clearance of various chemotherapeutic agents, including capecitabine. Genetic polymorphisms in CES1, together with environmental exposures such as pollutants, diet, and lifestyle factors, contribute to the interindividual variability in chemotherapy metabolism and toxicity profiles. This chapter examines the complex gene–environment interplay influencing treatment outcomes in breast cancer and highlights emerging strategies for integrating genetic and environmental assessments. A deeper understanding of these interactions paves the way for precision oncology approaches that personalize therapy, improve tolerability, and ultimately enhance patient outcomes in breast cancer care.

Introduction: Hypertension is a systemic disease characterized by high blood pressure and an important threat for the population, as it is common and can cause serious complications. Genetic and environmental factors are involved in its development like the recently defined genetic risk factor ARHGAP42 that encodes the Rho GTPase activating protein 42. In the study, the intronic rs604723 (C/T) gene polymorphism of ARHGAP42 was investigated in relation to arterial stiffness. Methods: Peripheral blood samples, taken from 63 study group subjects with hypertension and 100 healthy subject as control, were analyzed for the presence of the ARHGAP42 rs604723 gene polymorphism by a real-time PCR method following DNA isolation. Demographic data of the study group subjects were recorded and blood pressure, ambulatory blood pressure and arterial stiffness values were measured. Results: The heterozygous polymorphic CT (~2-fold) and homozygous polymorphic TT (~1.6-fold) genotypes were found to be higher in study group subjects when compared to the control group subjects, whereby the increase of the CT genotype was statistically significant (p = 0.006). Similarly, the frequency of the polymorphic T allele was found to be higher (~1.9-fold) and statistically significant (p = 0.003) in the study group subjects. In addition, the heterozygous polymorphic CT and homozygous polymorphic TT genotypes were found to be associated with carotid-femoral pulse velocity, which is a measure of arterial stiffness (p = 0.025). Conclusion: In this study, the ARHGAP42 rs604723 (C/T) gene polymorphism was found to be associated with pulse wave speed in subjects with hypertension. It will be of interest, to investigate its association with any specific drug or drugs commonly used in anti-hypertensive therapy. Thus, it would be possible to select the appropriate drug or drugs according to the hypertensive subjects’ genotype to carry out personalized medicine in future.