Bartkevičienė, Arenida

Introduction Gastric cancer is an aggressive malignancy and in 2023 was the third leading cause of cancerrelated death in Lithuania. Among gastrointestinal tumors, it most frequently leads to peritoneal dissemination. Tumor cells spread within the peritoneal cavity through direct contact, and surgical manipulation may further contribute to their dissemination. Moreover, gastric cancer often shows limited sensitivity to systemic chemotherapy due to poor drug penetration [1]. Hyperthermic intraperitoneal chemotherapy (HIPEC) is a localized treatment based on circulatory perfusion of a heated chemotherapy solution in the abdominal cavity. HIPEC is usually combined with cytoreductive surgery (CRS), which enhances drug absorption and elimination of metastasized cancer cells [2]. Some studies report improved survival rate among patients with metastatic gastric cancer who received HIPEC [3]. Aim To evaluate the effects of CRS and HIPEC on gene expression and protein levels in peripheral blood of gastric cancer patients. Methods Peripheral blood mononuclear cells (PBMCs) were obtained from 6 patients with confirmed gastric cancer undergoing CRS and HIPEC, as well as from 23 healthy controls without any surgery and cancer history. PBMCs were isolated from venous blood using Ficoll–Paque density gradient centrifugation. Blood samples were collected at three points: before surgery, on postoperative days 2–3, and on days 4–8 after surgery. Gene expression levels were evaluated by qRT-PCR. Soluble cytokines concentrations in serum were measured using a multiplex ELISA. Results Gene expression analysis revealed that AHR (77%), ELAVL1 (49%), IL12A (18%), IL12B (23%) and PD1 (30%) were downregulated in patients a few days after surgery compared to healthy controls. IL12A and IL12B expression remained low before HIPEC and during the early posttreatment period. Analysis of cytokine concentrations in serum, IL-6 levels were elevated in patients before (48,5 pg/ml) compared to healthy controls (35,5 pg/ml), reflecting tumourassociated and perioperative inflammatory activation [4]. After HIPEC, IL-6 concentrations gradually decreased over time, approaching control levels. IL-12/IL-23 p40 subunit concentration increased four days after HIPEC (140,5 pg/ml while before surgery was 98 pg/ml), which reflects total p40 secretion. The rise in p40 could be a non-specific inflammatory response rather than a specific activation of IL-12 signaling. Conclusions The findings indicate that CRS and HIPEC modulate immune-related pathways at both gene and protein levels in gastric cancer patients. Further studies incorporating comparison between CRS with HIPEC and CRS-only groups are needed to clarify the independent immunomodulatory impact of HIPEC and its relevance to postoperative recovery and therapeutic outcomes.

Pancreatic ductal adenocarcinoma (PDAC) remains largely unresponsive to immunotherapy because of its highly immunosuppressive tumor microenvironment. Aryl hydrocarbon receptor (AHR), a ligand-dependent transcription factor, has emerged as a key regulator of immune homeostasis and inflammation. However, its systemic immunomodulatory role in PDAC, particularly outside the tumor microenvironment, remains poorly understood.

Aryl hydrocarbon receptor (AHR) is a transcription factor that’s commonly upregulated in pancreatic ductal adenocarcinoma (PDAC). There are evidence that upregulated AHR increases PDAC aggressiveness, invasiveness, migration and decreases survival rates. This can be linked to epithelial-mesenchymal transition, when cells acquire a migratory mesenchymal phenotype. AHR expression levels have been shown to influence epithelial or mesenchymal phenotype in some cancer types, however little is known how targeting AHR would affect cell migration and invasiveness in pancreatic cancer. The aim of this study was to investigate how targeting AHR would affect cell migration and invasiveness in pancreatic cancer cells. Two PDAC cell were used for the study (BxPC-3 and Su.86.86). AHR was silenced by lipofectamine mediated siRNA transfection, inhibited by AHR inhibitor (BAY compound) or knocked-out by using CRISPR-CAS system. After silencing, inhibiting or knocking-out AHR, scratch assay was performed to asses the effect on cell migration in 2D system. AHR protein inhibition influence on cell invasiveness and migration was also assessed in 3D system by growing them in low-adherence plates until they formed spheroids. The spheroids were then moved into adherence allowing plates to asses migration. Alternatively the spheroids were put into an extracellular matrix to asses invasion. The results showed that targeting AHR decreases PDAC cells migration and invasiveness. 2D Scratch assay showed that the migration was decreased by silencing AHR (BxPC-3 by 73 %; Su.86.86 by 54 %), inhibiting (BxPC-3 by 36 %; Su.86.86 – no change) and knocking-out (BxPC-3 by 51 %; Su.86.86 – KO not tested). 3D spheroid assays revealed similar trends of reducing cell migration (by 33-41 % depending on cell line) and invasiveness (by 20-43 % depending on cell line) after inhibiting AHR with BAY compound. Targeting AHR could prove to be a viable strategy in slowing PDAC progression by reduce cell invasiveness and migratory capabilities, however differences between cell lines suggest that such strategy should be pursued as a personalized treatment with other molecular mechanisms in mind.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, partly because the cancer cells can evade the immune system, also the pancreatic cancer cells are highly heterogeneous, and this tumor has a late onset of symptoms, which become visible only in advanced stages. For this study, we wanted to investigate the role of the aryl hydrocarbon receptor (AhR), a potential regulator of immune response and inflammatory pathways in PDAC. Using patient-derived peripheral blood mononuclear cells (PBMCs), we sought to determine how modulation of AhR activity affects the expression and production of immune checkpoint molecules and inflammatory mediators. To reflect the subtle effects of AhR activity on immunity, we divided PBMCs from 22 PDAC patients into four groups: unmodulated control, AhR stimulated by carbidopa, AhR stimulated by tapinarof, and AhR suppressed by bay. After 24 hours of modulation, the PBMCs were frozen for gene expression analysis using RT-PCR. The culture supernatants were also frozen for target protein analysis using ELISA. After experimental analysis all patient results were separated into two parts based on the AhR expression level of the unmodulated group: low AhR and high AhR. The Mann-Whitney test was used to determine the statistical significance in GraphPad software. Our study demonstrated different patterns of gene regulation in response to AhR modulation. In the high AhR expression group, carbidopa significantly downregulated AhR expression (p < 0.05), while in the low AhR expression group, tapinarof induced a significant upregulation of AhR (p < 0.05). Regardless of baseline AhR levels, tapinarof stimulation consistently increased CYP1A1 transcription (p < 0.05) across both groups. Conversely, AhR inhibition with bay resulted in a decreasing trend of CYP1A1 expression in both AhR groups. Interestingly, PTGS2 (encoding COX-2) remained downregulated in AhR-stimulated groups, but no reliable changes were observed. AhR modulation also affected immune checkpoint gene expression. Tapinarof treatment showed an upregulating trend in CD274 (PD-L1) transcription, independent of the initial AhR levels, while CD279 (PD-1) expression remained relatively stable across all conditions. At the protein level, carbidopa treatment was associated with a decreasing trend in soluble PD-L1 concentrations across both AhR expression groups. In contrast, soluble PD-1 levels remained elevated following AhR stimulation with carbidopa and tapinarof. Notably, soluble PGE2 levels showed a decreasing trend in the low AhR group after suppression with bay. These findings suggest the unique immunological role of AhR primary expression, functional activity, and different modulators in PDAC patients' blood. AhR activation enhances CYP1A1 expression, slightly reduces PD-L1 protein production with carbidopa, and affects inflammation-related genes in a context-dependent manner. AhR inhibition attenuates these responses, particularly in patients with low baseline AhR expression. However, these results suggest that AhR may be one of the main targets as a key regulator of immune responses in PDAC, and present new strategies for improving the efficacy of immunotherapeutic interventions.

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related deaths, with a five-year survival rate below 10%. Its aggressiveness and chemotherapy resistance are linked to epithelial-mesenchymal transition (EMT), a process enabling epithelial cells to gain mesenchymal properties, enhancing migration and metastasis. EMT is driven by transcription factors such as SNAIL, SLUG, ZEB1/2, and TWIST. SNAI1 plays a key role in metastasis, while high ZEB1 expression correlates with poor survival. This process is tightly regulated by signalling networks, including ELAVL1, which encodes HuR, a protein that stabilizes mRNAs by binding to AU-rich elements (AREs) in their 3′ untranslated regions (3′UTRs), enhancing translation. Tumor tissues from 65 PDAC patients undergoing surgical resection were analyzed. Total RNA was extracted and converted into cDNA for qRT-PCR. BxPC-3, MiaPaCa-2, and Su.86.86 cell lines were cultured in RPMI medium with 10% fetal bovine serum and 1% antibiotics at 37°C in a 5% CO2 humidified environment. For immunoprecipitation, 1–2 × 107 cells were lysed using a manufacturer-provided protocol. Mouse monoclonal anti-HuR (ELAVL1) antibody was used for protein binding, with normal mouse IgG as a control. Samples were analyzed via qRT-PCR. Binding sites were annotated using the CISBP-RNA database, considering only RNAdirect-confirmed 3′UTR motifs. Target gene 3′UTR sequences were retrieved from GENCODE V47 (GRCh38). Statistical analysis was performed using GraphPad Prism, applying the Kruskal-Wallis test with Dunn’s multiple comparisons and Spearman’s correlation. Data were presented as median with ± interquartile range, with significance at p<0.05. A strong positive correlation was identified between ELAVL1 and the transcription factors ZEB1, SNAI1, and SNAI2 (r = 0.74, 0.76, and 0.76, respectively). Expression levels of EMT-TFs and ELAVL1 were classified as high and low. Elevated ELAVL1 expression was associated with a 71.65-fold increase in ZEB1, whereas high ZEB1 levels corresponded to a 96.1% reduction in ELAVL1 expression. Similarly, high ELAVL1 levels resulted in a substantial upregulation of SNAI1 (312.35-fold), while even low ELAVL1 expression maintained elevated SNAI1 levels (8.45-fold). However, when SNAI1 expression was high, ELAVL1 levels declined by 90%, whereas simultaneous high expression of both factors led to a moderate 3.71-fold increase in ELAVL1. High SNAI2 expression was associated with a 93% reduction in ELAVL1, whereas low SNAI2 levels corresponded to a striking 198.11-fold increase in ELAVL1. Structural analysis identified multiple ELAVL1 binding sites: 34 in ZEB1, 1 in SNAI1, and 9 in SNAI2. Immunoprecipitation analysis confirmed that ELAVL1 can potentially bind to ZEB1, SNAI1, and SNAI2 in MiaPaCa-2 and Su.86.86 cell lines. In conclusion, our findings highlight a significant regulatory interplay between ELAVL1 and key EMT transcription factors in PDAC. The strong positive correlation between ELAVL1 and these genes, along with their observed expression patterns, suggests that ELAVL1 plays a crucial role in EMT regulation. Furthermore, structural mapping identified multiple ELAVL1 binding sites within these genes, reinforcing its post-transcriptional regulatory function. These insights lay the groundwork for further investigations into ELAVL1 as a potential therapeutic target in EMT-driven pancreatic cancer progression.

Introduction: Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest solid tumors, largely due to late diagnosis and limited molecular stratification strategies. In our previous work, we analyzed transcriptomic profiles of PDAC tissue and PBMCs to characterize immune and oncogenic pathway activity (AHR, PD1/PDL1). To complement this, we performed targeted pathogenic mutation analysis, aiming to distinguish germline and somatic events in matched samples from PDAC patients. Aims & Methods: Targeted sequencing data from six PDAC patients were analyzed using RStudio. Each patient provided matched PDAC tissue and PBMC samples. Mutations were filtered to include only pathogenic or likely pathogenic variants, which were then plotted across genes and individuals. Sample-type–specific differences and recurrence patterns were visualized using a bubble plot format. Results: Mutations were detected in several high-impact genes, including ATM, BRCA1/2, TP53, MSH2, MSH6, PALB2, and APC. PBMCs showed elevated mutation frequency in ATM and BRCA1, suggesting possible germline background or systemic genomic instability. Tumor-specific mutations, such as in TP53 and MUC16, were mostly restricted to PDAC tissue. Some genes (e.g., PALB2, MSH6) appeared across both compartments but varied per patient. This individual variability may reflect clonal hematopoiesis or subclonal tumor heterogeneity. Conclusion: Pathogenic mutation profiles differ significantly between PBMC and PDAC compartments, with certain genes showing tissue specificity. These findings build on our transcriptomic analysis and highlight the value of integrating DNA- and RNA-level data to understand patient-specific molecular features. Combined profiling may support bio-marker development, improve patient stratification, and guide personalized treatment decisions.

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related deaths, with a five-year survival rate un-der 10% [1]. Its lethality stems from its aggressive progression and strong chemotherapy resistance, both closely linked to epithelial-mesenchymal transition (EMT). EMT enables epithelial cells to gain migratory mesenchymal traits and is regulated by transcription factors such as SNAIL, SLUG,ZEB1/2, and TWIST [2].Among these, SNAIL plays a major role in metastasis [3], while ZEB1 is as-sociated with poor prognosis [4]. EMT is tightly modulated by networks including ELAVL1, which encodes the RNA-binding protein HuR. HuR stabilizes mRNAs by binding AU-rich elements (AREs) in their 3′ untranslated regions (3′UTRs), promoting their expression [5].Aims & Methods: This study aimed to identify post-transcriptional interactions between ELAVL1 and EMT-related genes and assess their prognostic value in PDAC. mRNA was extracted from cancerous and adjacent normal tissues (n=65), converted to cDNA, and analyzed by RT-PCR.BxPC-3, MiaPaCa-2, and Su.86.86 cell lines were cultured under standard conditions. Immunoprecipitation was performed on 1–2×10⁷ cells using a mouse monoclonal anti-HuR antibody, with IgG as control. qRT-PCR assessed mRNA enrichment. Binding sites were annotated using CISBP-RNA, considering only RNA direct-confirmed 3′UTR motifs. Target 3′UTRsequences were retrieved from GENCODE V47. Statistical analysis was performed using GraphPad Prism, applying the Wilcoxon signed-rank test, Kruskal-Wallis test with Dunn’s correction, and Spearman correlation. Data were presented as median ± interquartile range, with p<0.05considered significant. Results: Expression levels of EMT-related genes and ELAVL1 varied according to survival outcomes. In short-term survivors (1–12 months), SNAIL and SLUG were significantly upregulated (2.19- and 1.92-fold), while ZEB2was downregulated (0.65-fold). Medium-term survivors (13–35 months)showed reduced ZEB1 (0.53), SNAIL (0.30), SLUG (0.35), and TWIST (0.68).Long-term survivors (36–125 months) had the lowest levels of ZEB1 (0.24),ZEB2 (0.50), SLUG (0.24), TWIST (0.35), and ELAVL1 (0.72). ELAVL1 showed strong positive correlations with ZEB1, SNAIL, and SLUG (r = 0.74–0.76),whereas overall survival was weakly negatively correlated with the ex -pression of ZEB1, SNAIL, SLUG, and TWIST (r = -0.25 to -0.32).Although ZEB1, SNAIL, and TWIST did not show significant survival differences individually, low SLUG predicted better early survival (36 vs. 15months, p = 0.0278). ELAVL1 expression was stratified as high and low. High ELAVL1 corresponded to a 71.65-fold increase in ZEB1, whereas highZEB1 reduced ELAVL1 by 96.1%. High ELAVL1 also led to a 312.35-fold in-crease in SNAIL, while low ELAVL1 still supported elevated SNAIL expression (8.45-fold). High SNAIL expression reduced ELAVL1 by 90%, though simultaneous high expression of both resulted in a 3.71-fold ELAVL1 in-crease. High SLUG reduced ELAVL1 by 93%, whereas low SLUG led to a198.11-fold increase. Binding site analysis revealed ELAVL1 targets within3′UTRs: 34 in ZEB1, 1 in SNAIL, and 9 in SLUG. Conclusion: ELAVL1 (HuR) likely plays a central role in regulating EMT in PDAC through stabilization of key transcription factor mRNAs. High levels of ELAVL1, SNAIL, SLUG, and ZEB1 were associated with worse outcomes, particularly in short-term survivors. Conversely, low expression of SLUG was linked to improved survival. The strong correlations and validated binding sites suggest ELAVL1 as a promising prognostic biomarker and potential therapeutic target in PDAC.

Kasos vėžys yra vienas iš mirtiniausių onkologinių susirgimų pasaulyje, dažniausiai diagnozuojamas vėlyvose stadijose dėl besimptomės eigos ankstyvuoju laikotarpiu ir specifinių diagnostinių žymenų stokos. Prognozuojama, kad ateityje šis vėžys gali tapti antru pagal mirtingumą po plaučių vėžio [1]. Viena iš ligos progresavimo priežasčių yra naviko mikroaplinkos sukelta imunosupresija, mažinanti priešvėžinių imuninių ląstelių (citotoksinių T limfocitų, NK ląstelių, dendritinių ląstelių) aktyvumą ir sukelianti imuninės sistemos disfunkciją [2]. Siekiant geriau suprasti molekulinius mechanizmus, susijusius su imuninio atsako reguliacija, atliekami imunotranskriptominiai tyrimai, analizuojant periferinio kraujo vienbranduolių ląstelių (PKVL) ir kasos navikinio audinio mėginius. Tokia analizė gali padėti nustatyti naujus diagnostinius biožymenis bei potencialius taikinius personalizuotam gydymui. Lietuvos mokslo tarybos (LMT) vasaros praktikos metu studentė prisidėjo prie kasos vėžio tyrimų, įgyvendinamų Chirurginės gastroenterologijos laboratorijoje. Šios praktikos temos įgyvendinimui buvo naudojami pacientų kraujo mėginiai bei kasos navikiniai audiniai. Praktikos pradžioje iš periferinio kraujo mėginių buvo išskirtos PKVL tankio gradiento metodu naudojant “Ficol” reagentą ir išskirtos ląstelės buvo krioprezervuojamos tolimesniems žingsniams. RNR išskyrimas iš PKVL vykdomas naudojant “Purelink RNA Mini” rinkinį, kurio eigoje jos yra lizuojamos, o supernatantas su išlaisvinta RNR yra perkeliamas į kitą mėgintuvėlį ir sumaišomas su 70% etanoliu. Visas mėginio tūris yra perkeliamas į kolonėles ir po centrifugavimo RNR fiksuojasi filtre, o supernatantas pašalinamas. Po RNR plovimo keliais etapais, buvo atliktas RNR tirpinimas - eliucija, kad išplautume RNR iš filtro su be nukleazių vandeniu. RNR skyrimas iš paciento audinio buvo atliekamas su „ZYMO Direct-zol RNA Mini prep “ rinkiniu, naudojant TRI reagentą su keraminiais lizavimo rutuliukais bei homogenizatorių „Roshe MagNa Lyser“. Po RNR izoliavimo spektrofotometriškai buvo matuojama RNR koncentracija ir švarumas „NanoDrop 2000“ prietaisu bei fluorometriškai RNR integralumas su „Qubit4“, taip pat RNR kokybė tikrinta su „2100 Bioanalyzer Agilent RNA 6000 Nano“ rinkiniu. Sekantis etapas atrinktų pakankamai kokybiškų mėginių (RIN >8, koncentracija >100 ng/µl, 260/280 ir 260/230 santykiai ~2) bibliotekų ruošimas, kai išskirtą RNR konvertavome į cDNR panaudojant “Collibri Stranded RNA library preparation” rinkinį. Šiame etape buvo atlikta RNR fragmentacija, hibridizacija, ligacija bei RNR konvertavimas atvirkštinės tranksriptazės pagalba į cDNR, kuri vėliau buvo amplifikuota. Vėliau gauta cDNR buvo kiekybiškai ir kokybiškai vertinama naudojant „ 2100 Bioanalyzer Agilent High Sensitivity DNA“ rinkinį. Gautos cDNR bibliotekos įvertintos kiekybiškai ir kokybiškai bei suvienodintos iki 1 nM koncentracijos sekoskaitai. Praktikos tikslas buvo paruošti bent keturių pacientų (8 mėginių) kokybiškas kasos audinio ir PKVL transkriptomo bibliotekas. Rezultatai pranoko lūkesčius – buvo paruoštas pakankamai kokybiškas šešių pacientų mėginių bibliotekų rinkinys (12 bibliotekų). Tai sudaro pagrindą tolimesnei sekoskaitai, leisiančiai tirti molekulinius imuninio atsako reguliacijos pokyčius ir identifikuoti galimus personalizuoto gydymo taikinius. Praktikos metu studentė taip pat įgijo praktinių molekulinės biologijos įgūdžių, susipažino su geros laboratorinės praktikos principais ir laboratorijoje vykdomais tyrimais.

Introduction Pancreatic ductal adenocarcinoma (PDAC) accounts for approximately 7% of cancer-related deaths [1]. Despite advancements in cancer research, the five-year survival rate remains at 9%, primarily due to late diagnosis and limited treatment options [2,3]. Investigating differential gene expression between tumor tissue and peripheral blood mononuclear cells (PBMCs) may uncover potential biomarkers and therapeutic targets for early diagnosis and personalized treatment [4,5]. A key target in this pilot study was the aryl hydrocarbon receptor (AHR) and its pathways, implicated in immune suppression, oxidative stress, inflammation, angiogenesis, and tumor progression [6–9]. Aim To analyze transcriptional differences between PBMCs and PDAC tissues, focusing on the AHR signaling and related genes to understand their roles in disease progression. Methods PDAC tissue and PBMC samples were collected from six patients on the day of surgery, including one postneoadjuvant treatment. RNA sequencing libraries were prepared using the ILMN Stranded Total RNA Library with Ribo-Zero PLUS and sequenced on the NextSeq550 platform. Data were processed with the Nextflow RNA-seq workflow, using STAR for sequence alignment and RSEM for transcript quantification. Differential gene expression analyses were performed in RStudio, focusing on AHR signaling and related genes. Results PBMC samples exhibited similar immune gene expression profiles, while PDAC tissues demonstrated greater variability due to tumor heterogeneity and mutations. The principal component analysis identified two outliers: one reflecting the impact of neoadjuvant therapy, showing unique expression patterns, and another linked to a poor prognosis characterized by lymph node involvement and vascular invasion. Targeted gene analysis revealed that IL-4 expression was higher in tumor tissues compared to PBMCs, while AHRR, CYP1A1, IL-6, and IL-10 were more highly expressed in PBMCs than in tumor tissues, indicating immune modulation. Further studies should be done to validate these findings in larger cohorts and explore the impact of neoadjuvant treatments on gene expression to predict patient outcomes and therapeutic responses. Conclusions This study reveals significant transcriptional differences between PBMCs and PDAC tissues, reflecting tumor heterogeneity and variation in immune responses. IL-4 expression was higher in tumor tissues, suggesting its role in tumor progression and immune evasion, while AHRR, CYP1A1, IL-6, and IL-10 were more highly expressed in PBMCs.

Pancreatic cancer (PC) presents a significant challenge in treatment efficacy due to late-stage diagnosis and chemoresistance. The effects of the combination of a selective small-molecule AHR inhibitor and gemcitabine treatmenteffectiveness in PC cells has been a focus of research. This study utilized the PC cell lines BxPC-3 and Su.86.86 to investigate the impact of AHR activity modulation on gene and protein expression related to the gemcitabine response. Assays including viability measurement, combinational index calculation, qRT-PCR, Western blot analysis, immunocytofluorescence, and clonogenic assays, were employed. Additionally, patient tissue samples were analysed for AHR, ELAVL1, and DCK levels. The results show that AHR activity modulation influenced ELAVL1 localization, DCK expression, and gemcitabine response. Inhibition of AHR activity caused synergistic effects with gemcitabine, whereas activation had an antagonistic effect. Regarding colony formation, inhibition of AHR increased gemcitabine effectiveness by 30-41%, whereas activation decreased the response by 11-28%. Patient tissue analysis revealed correlations between AHR, ELAVL1, and DCK mRNA levels and showed increased levels of AHR protein (2.2-fold) and decreased DCK protein levels (36% decrease) in tumor tissue compared to next-to-cancer tissue. These findings demonstrate the potential of AHR modulation to improve gemcitabine treatment outcomes. This study highlights the significance of AHR modulation in influencing the gemcitabine response in PC cells. By inhibiting AHR activity, cells exhibited improved gemcitabine response, offering a promising avenue for enhancing treatment efficacy. These findings suggest that AHR could serve as a target for optimizing gemcitabine treatment and potentially reducing cancer aggressiveness.