Transit Signal Research Articles

NSUN2 Promotes Head and Neck Squamous Cell Carcinoma Progression by Targeting EMT-Related Gene LAMC2 in an m5C-YBX1-Dependent Manner

Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) is a prevalent and aggressive cancer with high rates of metastasis and poor prognosis. Recent research highlights the role of 5-methylcytosine (m5C) in cancer progression. NSUN2, an m5C methyltransferase, has been implicated in various cancers, but its role in HNSCC remains elusive. Methods: NSUN2 expression and its impact on HNSCC were analyzed by using clinical samples and bioinformatic analysis. m5C-Bis-Seq was used to assess changes in mRNA m5C modification and identify downstream targets. Both in vitro and vivo studies were performed to evaluate the impact of NSUN2 manipulation on tumor growth and metastasis. Results: Results indicated that NSUN2 was significantly upregulated in HNSCC tissues compared to normal tissues and was associated with poor prognosis. NSUN2 knockdown led to decreased cell proliferation, migration, and invasion in vitro and reduced tumorigenicity and lymph node metastasis in vivo. m5C-Bis-Seq revealed altered m5C-modification patterns upon NSUN2 knockdown, with LAMC2 identified as a key downstream target. Conclusions: NSUN2-mediated m5C-modification enhanced LAMC2 stability, promoting epithelial–mesenchymal transition (EMT) signaling pathways. These findings demonstrate that NSUN2 promotes the initiation and progression of HNSCC by stabilizing the LAMC2 transcript through m5C-dependent mechanisms, offering a promising epitranscriptomic-targeted therapeutic approach for HNSCC.

Spermine Synthase : A Potential Prognostic Marker for Lower-Grade Gliomas.

The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

Enhanced cancer cell proliferation and aggressive phenotype counterbalance in breast cancer with high BRCA1 gene expression.

While comprehensive research exists on the mutation of the DNA repair gene BRCA1, limited information is available regarding the clinical significance of BRCA1 gene expression. Given that cancer cell proliferation is aggrevated by DNA repair, we hypothesized that high BRCA1 gene expression breast cancer (BC) might be linked with aggressive tumor biology and poor clinical outcomes. The cohorts: The Cancer Genome Atlas (TCGA, n = 1069), METABRIC (n = 1903), and SCAN-B (n = 3273) were utilzed to obtain data of 6245 BC patients. BC patients without BRCA1 mutation exhibited higher BRCA1 expression, which was associated with DNA repair functionality. However, no such correlation was observed with BRCA2 expression. The association of high BRCA1 expression with cancer cell proliferation was evidenced by significant enrichment of cell proliferation-related gene sets, higher histological grade, and proliferation score. Furthermore, increased levels of homologous recombination deficiency, intratumoral heterogeneity, and altered fractions were associated with high BRCA1 expression. Moreover, BC with high BRCA1 expression exhibited reduced infiltration of dendritic cells and CD8 T-cells, while showing increased infiltration of Th1 cells. Surprisingly, BRCA1 expression was not associated with the survival of BC irrespective of the subtypes. Conversely, BC with low BRCA1 expression enriched cancer aggravating pathway gene sets, such as Cancer Stem Cell-related signaling (NOTCH and HEDGEHOG), Angiogenesis, Epithelial-Mesenchymal Transition, Inflammatory Response, and TGF-beta signaling. Despite being linked to heightened proliferation of cancer cells and unassertive phenotype, BRCA1 expression did not show any association with survival in BC.

MLLT3 knockdown suppresses proliferation and cell mobility in human lung adenocarcinoma.

Lung cancer is emerging as one of the most frequently encountered malignancies around the world that carries high morbidity and mortality. Lung adenocarcinoma (LUAD) has become the most common subtype of lung cancer. MLLT3 or named AF9 was first characterized in acute myeloid leukemia and can downregulate the expression of several critical genes. The aim of this study was to explore the function of MLLT3 in the progression of LUAD and related molecular mechanisms. Immunohistochemistry was employed to assess MLLT3 expression in LUAD tissues, while quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were utilized to detect MLLT3 expression levels in lung adenocarcinoma cell lines. These results revealed a significant overexpression of MLLT3 in LUAD cell lines and tissues. We further uncovered an association between MLLT3 expression profiles in LUAD tissues and metastasis, as well as TNM stage. Survival analysis showed that elevated MLLT3 correlated with a poorer survival rate. We also found that MLLT3 knockdown repressed LUAD cells invasion, migration, and proliferation in vitro, while inducing cell cycle arrest and apoptosis of LUAD cells. Moreover, knocking down MLLT3 inhibited tumor growth in vivo. Specific markers of apoptosis, cell cycle, epithelial-mesenchymal transition (EMT), and MLLT3-induced signaling were examined by Western blot. We demonstrated that MLLT3 knockdown inhibited the activity of the EGFR-MAPK/ERK signaling pathway, and MLLT3 might be a novel diagnostic biomarker and therapeutic target in lung adenocarcinomas.

Detecting and sizing the Earth with PLATO: A feasibility study based on solar data

The PLAnetary Transits and Oscillations of stars (PLATO) mission will observe the same area of the sky continuously for at least two years in an effort to detect transit signals of an Earth-like planet orbiting a solar-like star. We aim to study how short-term solar-like variability caused by oscillations and granulation would affect PLATO's ability to detect and size Earth if PLATO were to observe the Solar System itself. We also compare different approaches to mitigate noise caused by short-term solar-like variability and perform realistic transit fitting of transit signals in PLATO-like light curves. We injected Earth-like transit signals onto real solar data taken by the Helioseismic and Magnetic Imager (HMI) instrument on board the Solar Dynamics Observatory (SDO). We isolated short-term stellar variability in the HMI observations by removing any variability with characteristic timescales longer than five hours using a smooth Savitzky-Golay filter. We then added a noise model for a variety of different stellar magnitudes computed by assuming an observation by all 24 normal cameras. We first compared four different commonly used treatments of correlated noise in the time domain by employing them in a transit fitting scheme. We then tried to recover pairs of transit signals using an algorithm similar to the transit least squares algorithm. Finally, we performed transit fits using realistic priors on planetary and stellar parameters and assessed how accurately the pair of two injected transits was recovered. We find that short-term solar-like variability affects the correct retrieval of Earth-like transit signals in PLATO data. Variability models accounting for variations with typical timescales at the order of one hour are sufficient to mitigate these effects. We find that when the limb-darkening coefficients of the host star are properly constrained, the impact parameter does not negatively affect the detectability of a transit signal or the retrieved transit parameters, except for high values ($b > 0.8$). For bright targets (8.5 - 10.5 mag), the transit signal of an Earth analogue can reliably be detected in PLATO data. For faint targets a detection is still likely, though the results of transit search algorithms have to be verified by transit-fitting algorithms to avoid false positive detections being flagged. For bright targets (V-mag leq 9.5), the radius of an Earth-like planet orbiting a solar-like star can be correctly determined at a precision of 3<!PCT!> or less, assuming that at least two transit events are observed and the characteristics of the host star are well understood.

Cell Fate Dynamics Reconstruction Identifies TPT1 and PTPRZ1 Feedback Loops as Master Regulators of Differentiation in Pediatric Glioblastoma-Immune Cell Networks.

Pediatric glioblastoma is a complex dynamical disease that is difficult to treat due to its multiple adaptive behaviors driven largely by phenotypic plasticity. Integrated data science and network theory pipelines offer novel approaches to studying glioblastoma cell fate dynamics, particularly phenotypic transitions over time. Here we used various single-cell trajectory inference algorithms to infer signaling dynamics regulating pediatric glioblastoma-immune cell networks. We identified GATA2, PTPRZ1, TPT1, MTRNR2L1/2, OLIG1/2, SOX11, FXYD6, SEZ6L, PDGFRA, EGFR, S100B, WNT, TNF , and NF-kB as critical transition genes or signals regulating glioblastoma-immune network dynamics, revealing potential clinically relevant targets. Further, we reconstructed glioblastoma cell fate attractors and found complex bifurcation dynamics within glioblastoma phenotypic transitions, suggesting that a causal pattern may be driving glioblastoma evolution and cell fate decision-making. Together, our findings have implications for developing targeted therapies against glioblastoma, and the continued integration of quantitative approaches and artificial intelligence (AI) to understand pediatric glioblastoma tumor-immune interactions.

Targeting the Galectin-1/Ras Interaction for Treating Malignant Peripheral Nerve Sheath Tumors.

Background: Neurofibromatosis type 1 (NF1) is a common inherited neurological disorder that can lead to the development of malignant peripheral nerve sheath tumors (MPNSTs), a highly aggressive form of sarcoma. Current treatment options for MPNSTs are limited, with poor prognosis and high recurrence rates. This study aims to explore the potential of targeting the Galectin-1 (Gal-1) and Ras interaction as a novel therapeutic strategy for MPNSTs. Methods: Molecular docking simulations were conducted to identify specific residues involved in the Gal-1 and H-Ras(G12V) interaction. LLS30, a compound designed to target the Ras binding pocket on Gal-1, was developed and tested. The efficacy of LLS30 was evaluated through in vitro assays, including cell viability, apoptosis, and co-immunoprecipitation studies, as well as in vivo assays using orthotopic MPNST xenograft and experimental lung metastasis models. Transcriptome sequencing was performed to analyze the impact of LLS30 on gene expression and signaling pathways. Results: Molecular docking revealed key residues involved in the Gal-1/Ras interaction, and LLS30 was shown to bind to these residues, disrupting the interaction. LLS30 treatment resulted in Ras delocalization from the plasma membrane and suppression of the Ras/Erk signaling pathway. In vitro, LLS30 significantly reduced MPNST cell proliferation and induced apoptosis. In vivo, LLS30 demonstrated potent anti-tumor activity, reducing tumor burden and metastasis while improving survival in animal models. Transcriptome analysis showed that LLS30 downregulates critical pathways, including KRAS signaling and epithelial-mesenchymal transition (EMT). Conclusions: Interference with the Gal-1/Ras interaction could lead to suppression of the Ras signaling pathway. LLS30 effectively disrupts the Gal-1/Ras interaction, resulting in significant anti-tumor and anti-metastatic effects in MPNST models. These findings indicated that targeting Gal-1 with LLS30 offers a promising therapeutic approach for treating MPNSTs and may also be applicable to other malignancies where Gal-1 and Ras are key oncogenic drivers.

Development and Validation of a Comprehensive Prognostic and Depression Risk Index for Gastric Adenocarcinoma

Depressive disorder contributes to the initiation and prognosis of patients with cancer, but the interaction between cancer and depressive disorder remains unclear. We generated a gastric adenocarcinoma patient-derived xenograft mice model, treated with chronic unpredictable mild stimulation. Based on the RNA-sequence from the mouse model, patient data from TCGA, and MDD-related (major depressive disorder) genes from the GEO database, 56 hub genes were identified by the intersection of differential expression genes from the three datasets. Molecular subtypes and a prognostic signature were generated based on the 56 genes. A depressive mouse model was constructed to test the key changes in the signatures. The signature was constructed based on the NDUFA4L2, ANKRD45, and AQP3 genes. Patients with high risk-score had a worse overall survival than the patients with low scores, consistent with the results from the two GEO cohorts. The comprehensive results showed that a higher risk-score was correlated with higher levels of tumor immune exclusion, higher infiltration of M0 macrophages, M2 macrophages, and neutrophils, higher angiogenetic activities, and more enriched epithelial–mesenchymal transition signaling pathways. A higher risk score was correlated to a higher MDD score, elevated MDD-related cytokines, and the dysfunction of neurogenesis-related genes, and parts of these changes showed similar trends in the animal model. With the Genomics of Drug Sensitivity in Cancer database, we found that the gastric adenocarcinoma patients with high risk-score may be sensitive to Pazopanib, XMD8.85, Midostaurin, HG.6.64.1, Elesclomol, Linifanib, AP.24534, Roscovitine, Cytarabine, and Axitinib. The gene signature consisting of the NDUFA4L2, ANKRD45, and AQP3 genes is a promising biomarker to distinguish the prognosis, the molecular and immune characteristics, the depressive risk, and the therapy candidates for gastric adenocarcinoma patients.

Reinforcement Learning for Transit Signal Priority with Priority Factor

Public transportation has been identified as a viable solution to mitigate traffic congestion. Transit signal priority (TSP) control, which is widely used at signalized intersections, has been recognized as a practical strategy to improve the efficiency and reliability of bus operations. However, traditional TSP control may fall short of efficiency and is facing several challenges of negative externalities for non-transit users and the need to handle conflicting priority requests. Recent studies have proposed the use of reinforcement learning (RL) methods to identify efficient traffic signal control (TSC). Some of these studies on RL-based TSC have incorporated the concept of max-pressure (MP), which is a maximal weight-matching algorithm to minimize queue sizes. Nevertheless, the existing RL-based TSC methods focus on private vehicles and cannot adequately distinguish between buses and private vehicles. In prior research, RL-based control has been implemented within the context of bus rapid transit (BRT) systems. This study proposes a novel RL-based TSC strategy that leverages the MP concept and extends it to incorporate TSP control. This is the first implementation of RL-based TSP control within the mixed-traffic road network. A significant innovation of this research is the introduction of the priority factor (PF), which is designed to prioritize bus movements at signalized intersections. The proposed RL-based TSP with PF control seeks to balance the competing objectives of enhancing bus operations while mitigating adverse impacts on non-transit users. To evaluate the performance of the proposed TSP method with the PF mechanism, simulations were conducted on an arterial and a grid network under dynamic traffic conditions. The simulation results demonstrated that the proposed TSP with PF not only reduces bus travel times and resolves conflicts between priority requests but also does not make a significant negative impact on passenger car operations. Furthermore, the PF can be dynamically assigned according to the number of passengers on each bus, suggesting the potential for the proposed approach to be applied in various traffic management scenarios.

Dissecting the Significance of Acid Phosphatase 1 Gene Alterations in Prostate Cancer.

The acid phosphatase 1 (ACP1) gene encodes low-molecular-weight protein tyrosine phosphatase, which is overexpressed in prostate cancer (PC) and a potential therapeutic target. We analyzed ACP1 expression in primary/metastatic PC and its association with molecular profiles and clinical outcomes. NextGen sequencing of DNA (592-gene/whole-exome sequencing)/RNA(whole-transcriptome sequencing) was performed for 5,028 specimens. ACP1-High/ACP1-Low expression was defined as quartile (Q4/1) of RNA transcripts per million (TPM). DNA mutational profiles were analyzed for ACP1-quartile-stratified samples. Gene set enrichment analysis was used for Hallmark collection of pathways. PD-L1+(≥2+, ≥5%; SP142) was tested by immunohistochemistry. Tumor microenvironment's (TME) immune cell fractions were estimated by RNA deconvolution/quanTIseq. Overall survival (OS) was assessed from initial diagnosis/treatment initiation to death/last follow-up. We included 3,058 (60.8%) samples from the prostate, 634 (12.6%) from lymph node metastases (LNMs), and 1,307 (26.0%) from distant metastases (DMs). ACP1 expression was higher in LNM/DM than prostate (49.8/47.9 v 44.1 TPM; P < .0001). TP53 mutations were enriched in ACP1-Q4 (37.9%[Q4] v 27.0%[Q1]; P < .001) among prostate samples. Pathways associated with cell cycle regulation and oxidative phosphorylation were enriched in ACP1-Q4, whereas epithelial-mesenchymal transition and tumor necrosis factor-alpha signaling via nuclear factor kappa-light-chain-enhancer of activated B-cell pathways were enriched in ACP1-Q1. Neuroendocrine and androgen receptor signaling was increased in ACP1-Q4. M2 macrophages and natural killer cell fractions were increased, whereas T cells and M1 macrophages were decreased in ACP1-Q4. While OS differences between ACP1-Q1/Q4 were not statistically significant, there was a trend for worse OS among ACP1-Q4 prostate samples (Q4 v Q1: hazard ratio [HR], 1.19 [95% CI, 0.99 to 1.42]; P = .06) and DM (HR, 1.12 [95% CI, 0.93 to 1.36]; P = .22) but not LNM (HR, 0.98 [95% CI, 0.74 to 1.29]; P = .87). ACP1-High tumors exhibit a distinct molecular profile and cold TME, highlighting ACP1's potential role in PC pathogenesis and novel therapeutic targeting.

Early recurrence as a pivotal event in nasopharyngeal carcinoma: identifying predictors and key molecular signals for survivors

PurposeThe duration of response to treatment is a significant prognostic indicator, with early recurrence (ER) often predicting poorer survival outcomes in nasopharyngeal carcinoma (NPC) survivors. This study seeks to elucidate the factors contributing to the onset of ER following radiotherapy in NPC survivors.MethodsThis investigation encompassed 2,789 newly diagnosed NPC patients who underwent radical intensity-modulated radiotherapy. Ordinal logistic regression analysis was employed to evaluate the independent predictors of earlier recurrence. A machine learning-based prediction model of NPC recurrence patterns was developed. Tumorous RNA-sequencing (in-house cohort: N = 192) and biological tipping point analysis were utilized to infer potential molecular mechanisms associated with ER.ResultsOur results demonstrated that ER within 24 months post-initial treatment was the optimal time frame for identifying early malignant progression in NPC survivors. The ER cohort (150 of 2,789, 5.38%) exhibited a notably short median overall survival of 48.6 months. Multivariate analyses revealed that male gender, T4 stage, local or regional residual disease, detectable pre- and post-radiotherapy EBV DNA, and the absence of induction chemotherapy were significant predictors of earlier recurrence. The machine learning-based predictive model further underscored the importance of tumor-related factors in NPC recurrence. Moreover, ER emerged as a pivotal stage in NPC progression, with 15 critical transition signals identified potentially associated with the negative modulation of the immune response.ConclusionsOur comprehensive analysis of NPC recurrence patterns has unveiled insights into the key factors driving ER and provided novel insights into potential early warning biomarkers and the mechanisms underlying NPC progression.

LncRNAs orchestration of gastric cancer - particular emphasis on the etiology, diagnosis, and treatment resistance.

Gastric cancer (GC) remains a major public health challenge worldwide. Long non-coding RNAs (lncRNAs) play important roles in the development, progression, and resistance to the treatment of GC, as shown by recent developments in molecular characterization. Still, an in-depth investigation of the lncRNA landscape in GC is absent. However, The objective of this systematic review is to evaluate our present understanding of the role that lncRNA dysregulation plays in the etiology of GC and treatment resistance, with a focus on the underlying mechanisms and clinical implications. Research that described the functions of lncRNA in angiogenesis, stemness, epigenetics, metastasis, apoptosis, development, and resistance to key treatments was given priority. In GC, it has been discovered that a large number of lncRNAs, including MALAT1, HOTAIR, H19, and ANRIL, are aberrantly expressed and are connected with disease-related outcomes. Through various methods such as chromatin remodeling, signal transduction pathways, and microRNA sponging, they modulate hallmark cancer capabilities. Through the activation of stemness programs, epithelial-mesenchymal transition (EMT), and survival signaling, LncRNAs also control resistance to immunotherapy, chemotherapy, and targeted therapies. By clarifying their molecular roles further, we may be able to identify new treatment targets and ways to overcome resistance. This article aims to explore the interplay between lncRNAs, and GC. Specifically, the focus is on understanding how lncRNAs contribute to the etiology of GC and influence treatment resistance in patients with this disease.

Identifying Key Genes as Progression Indicators of Prostate Cancer with Castration Resistance Based on Dynamic Network Biomarker Algorithm and Weighted Gene Correlation Network Analysis.

Background: Androgen deprivation therapy (ADT) is the mainstay of treatment for prostate cancer, yet dynamic molecular changes from hormone-sensitive to castration-resistant states in patients treated with ADT remain unclear. Methods: In this study, we combined the dynamic network biomarker (DNB) method and the weighted gene co-expression network analysis (WGCNA) to identify key genes associated with the progression to a castration-resistant state in prostate cancer via the integration of single-cell and bulk RNA sequencing data. Based on the gene expression profiles of CRPC in the GEO dataset, the DNB method was used to clarify the condition of epithelial cells and find out the most significant transition signal DNB modules and genes included. Then, we calculated gene modules associated with the clinical phenotype stage based on the WGCNA. IHC was conducted to validate the expression of the key genes in CRPC and primary PCa patients Results:Nomograms, calibration plots, and ROC curves were applied to evaluate the good prognostic accuracy of the risk prediction model. Results: By combining single-cell RNA sequence data and bulk RNA sequence data, we identified a set of DNBs, whose roles involved in androgen-associated activities indicated the signals of a prostate cancer cell transition from an androgen-dependent state to a castration-resistant state. In addition, a risk prediction model including the risk score of four key genes (SCD, NARS2, ALDH1A1, and NFXL1) and other clinical-pathological characteristics was constructed and verified to be able to reasonably predict the prognosis of patients receiving ADT. Conclusions: In summary, four key genes from DNBs were identified as potential diagnostic markers for patients treated with ADT and a risk score-based nomogram will facilitate precise prognosis prediction and individualized therapeutic interventions of CRPC.

Abstract C070: Keratin 17 and GATA6 correlate with diffusely infiltrative versus gland-forming components of PDAC: Uncovering the transitional state in pancreatic ductal adenocarcinoma

Abstract Purpose: Optimization of pancreatic ductal adenocarcinoma (PDAC) patient survival will depend on advancing our understanding of the mechanisms governing tumor cell plasticity and effectively mitigating their invasive and metastatic capabilities. This study aims to investigate the correlation of cancer biomarkers crucial to these processes by integrating molecular signatures with histopathological characteristics using single-cell RNA sequencing (scRNA-seq) and multiplexed IHC/IF. Methods: Single-cell RNA sequencing (scRNA-seq) data from a comprehensive dataset of over 53,000 PDAC cells and validation of lead targets through 14-plex immunofluorescence, using a customized MICS platform (Miltenyi Biotec) and dual color IHC were employed to assess protein expression of defining biomarkers of basal and classical subtypes of PDAC including Keratin 17 (K17) and GATA6. Results: scRNAseq analysis revealed distinct patterns of K17 and GATA6 expression, highlighting intratumoral heterogeneity among PDAC tumors. Specifically, populations of cells expressing K17+/GATA6+ and K17+/GATA6- exhibited significant enrichment in pathways associated with invasion and cell migration, including PI3K/Akt/mTOR, TGF-β, and epithelial-mesenchymal transition (EMT) signaling. Conversely, GATA6-/K17- cells demonstrated enrichment in biosynthetic and metabolic pathways that govern cell cycle regulation. Additionally, mIF data assessment revealed correlations between histomorphological patterns and dynamic shifts in K17 and GATA6 expression within PDAC tumors. Diffusely infiltrative tumor cells (DITCs) uniformly expressed K17, contrasting with the gland-forming components (GFCs) of PDAC, which showed enrichment in GATA6 and sporadic expression of K17. E-cadherin, a key adhesion marker, exhibited the highest expression levels in the glandular and solid components of PDAC, underscoring their epithelial characteristics. Conversely, vimentin, a marker typically associated with epithelial-to-mesenchymal transition (EMT), was significantly expressed in DITCs, suggesting a mesenchymal-like phenotype in these infiltrative cells. Dual color IHC further validated these findings, reinforcing the correlation between morphologic plasticity and the expression patterns of K17 and GATA6, emphasizing their potential to distinguish distinct tumor cell populations within PDAC. Conclusions: These insights suggest that the interaction between these markers may indicate a distinct biological state characterized by altered cellular metabolism and potentially different therapeutic vulnerabilities. The robust association between K17 expression and diffusely infiltrative tumor cells underscores its potential as a marker for the most aggressive forms of this disease. Our results highlight the heterogeneous nature of PDAC and emphasize the critical importance of understanding these molecular distinctions in histopathological contexts to develop targeted therapies aimed at improving patient survival. Citation Format: Lyanne A Delgado- Coka, Brian Nelson, Michael Horowitz, Shayan Sarkar, Natalia Marchenko, Scott Powers, Luisa F Escobar-Hoyos, Kenneth Shroyer. Keratin 17 and GATA6 correlate with diffusely infiltrative versus gland-forming components of PDAC: Uncovering the transitional state in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C070.

Final Overall Survival Analysis of S1500: A Randomized, Phase II Study Comparing Sunitinib With Cabozantinib, Crizotinib, and Savolitinib in Advanced Papillary Renal Cell Carcinoma.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.Mesenchymal-epithelial transition (MET) signaling pathway plays a role in the pathogenesis of selected patients with papillary renal cell carcinoma (PRCC). In the phase II PAPMET trial (ClinicalTrials.gov identifier: NCT02761057), cabozantinib significantly prolonged progression-free survival and improved objective response rate compared with sunitinib in patients with advanced PRCC. Here, we present the final overall survival (OS) analysis. In this multicenter, randomized phase II, open-label trial, 147 patients with advanced PRCC who have received up to one previous therapy (excluding vascular endothelial growth factor-directed agents) were assigned to sunitinib, cabozantinib, crizotinib, or savolitinib. Ultimately, savolitinib and crizotinib arms were closed because of futility. With a median follow-up of 17.5 months, the median OS was 21.5 months (95% CI, 12.0 to 28.1) with cabozantinib and 17.3 months (95% CI, 12.8 to 21.8) with sunitinib (hazard ratio, 0.83; 95% CI, 0.51 to 1.36; P = .46). The OS landmark estimates for cabozantinib and sunitinib were 50% versus 39% at 24 months and 32% versus 28% at 36 months. In conclusion, we observed no significant difference in OS across treatment arms. Although cabozantinib represents a well-supported option for advanced PRCC, the lack of survival benefit underscores the need to develop novel therapies for this disease.

A patient-derived cell model for malignant transformation in IDH-mutant glioma

Malignant transformation (MT) is commonly seen in IDH-mutant gliomas. There has been a growing research interest in revealing its underlying mechanisms and intervening prior to MT at the early stages of the transforming process. Here we established a unique pair of matched 3D cell models: 403L, derived from a low-grade glioma (LGG), and 403H, derived from a high-grade glioma (HGG), by utilizing IDH-mutant astrocytoma samples from the same patient when the tumor was diagnosed as WHO grade 2 (tumor mutational burden (TMB) of 3.96/Mb) and later as grade 4 (TMB of 70.07/Mb), respectively. Both cell models were authenticated to a patient’s sample retaining endogenous expression of IDH1 R132H. DNA methylation profiles of the parental tumors referred to LGG and HGG IDH-mutant glioma clusters. The immunopositivity of SOX2, NESTIN, GFAP, OLIG2, and beta 3-Tubulin suggested the multilineage potential of both models. 403H was more prompt to cell invasion and developed infiltrative HGG in vivo. The differentially expressed genes (DEGs) from the RNA sequencing analysis revealed the tumor invasion and aggressiveness related genes exclusively upregulated in the 403H model. Pathway analysis showcased an enrichment of genes associated with epithelial-mesenchymal transition (EMT) and Notch signaling pathways in 403H and 403L, respectively. Mass spectrometry-based targeted metabolomics and hyperpolarized (HP) 1-13C pyruvate in-cell NMR analyses demonstrated significant alterations in the TCA cycle and fatty acid metabolism. Citrate, glutamine, and 2-HG levels were significantly higher in 403H. To our knowledge, this is the first report describing the development of a matched pair of 3D patient-derived cell models representative of MT and temozolomide (TMZ)-induced hypermutator phenotype (HMP) in IDH-mutant glioma, providing insights into genetic and metabolic changes during MT/HMP. This novel in vitro model allows further investigation of the mechanisms of MT at the cellular level.Graphic

Detection of transiting exoplanets and phase-folding their host star’s light curves from K2 data with 1D-CNN

Abstract In this research, we present two 1D Convolutional Neural Network (CNN) models that were trained, validated and tested using simulated light curves designed to mimic those expected from the Kepler Space Telescope during its extended mission (K2). We also tested them on real K2 data. Our light curve simulator considers different stellar variability phenomena, such as rotations, pulsations and flares, which along with the stellar noise expected for K2 data, hinders the transit signal detection, as in real data. The first model effectively identifies transit-like signals in light curves, classifying them based on the presence or absence of such signals. Furthermore, the second model not only phase-folds the light curves but also eliminates stellar noise, a crucial step when fitting transits to the Mandel and Agol theoretical transit shape. The obtained results include an accuracy of $\sim 99\%$ when classifying the light curves based on the presence or absence of transit-like signals, and $MAPE\sim 6\%$ regarding to the transits’ depth and duration when phase folding the light curves, showing the great capabilities of 1D-CNN for automatizing the transit search in light curves, both on simulated and real data.

Curcumin blunts epithelial-mesenchymal transition to alleviate invasion and metastasis of prostate cancer through the JARID1D demethylation

Prostate cancer (PCa) is one of the most common and prevalent cancers in men worldwide. The majority of PCa-related deaths result from metastasis rather than primary tumors. Several studies have focused on the relationship between male-specific genes encoded on the Y chromosome and PCa metastasis; however, the relationship between the male specific protein encoded on the Y chromosome and tumor suppression has not been fully clarified. Here, we report a male specific protein of this type, the histone H3 lysine 4 (H3K4) demethylase JARID1D, which has the ability to inhibit the gene expression program related to cell invasion, and can thus form a phenotype that inhibits the invasion of PCa cells. However, JARID1D exhibits low expression level in advanced PCa, and which is related to rapid invasion and metastasis in patients with PCa. Curcumin, as a multi-target drug, can enhance the expression and demethylation activity of JARID1D, affect the androgen receptor (AR) and epithelial-mesenchymal transition (EMT) signaling cascade, and inhibit the metastatic potential of castration resistant cancer (CRPC). These findings suggest that using curcumin to increase the expression and demethylation activity of JARID1D may be a feasible strategy to inhibit PCa metastasis by regulating EMT and AR.

Quercetin inhibits truncated isoform of dopamine- and cAMP-regulated phosphoprotein as adjuvant treatment for trastuzumab therapy resistance in HER2-positive breast cancer

Trastuzumab resistance is one of the causes of poor prognosis in patients with human epidermal growth factor receptor 2 (HER2)-positive (HER2+) breast cancer (BC). The truncated isoform of dopamine- and cAMP-regulated phosphoprotein (t-DARPP) has been reported to be involved in trastuzumab therapy resistance and promoting tumor progression. To evaluate the t-DARPP expression in BC, paired tumors and surrounding normal tissues were analyzed by real-time polymerase chain reaction and confirmed higher DARPP-32 kDa family mRNA expression in HER2+ BC tumor tissues. We established 2 patient-derived xenografts (PDX) mice models to test the efficacy of trastuzumab, named model 1 (non-responder) and model 2 (responder). t-DARPP and p95-HER2 protein-protein interactions were detected in PDX tumor tissue from non-responders using Förster resonance energy transfer assays. Instead, there is no response from the responder. Furthermore, mechanistic studies using transwell and Western blot assays demonstrated that t-DARPP could upregulate epithelial-mesenchymal transition signaling proteins, enhance p95-HER2 expression and promote cell migration. We found that quercetin effectively reduced t-DARPP expression in HER2+ BC cells. In t-DARPP ShRNA-suppressed cells, quercetin synergistically enhanced trastuzumab-induced apoptotic cell death and G2/M phase arrest. In conclusion, the combination of quercetin and trastuzumab treatment by targeting t-DARPP in HER2+ BC patients has the potential as a biomarker for mitigating drug resistance.

Distinct clinical outcomes and biological features of specific KRAS mutants in human pancreatic cancer

KRAS mutations in pancreatic ductal adenocarcinoma (PDAC) are suggested to vary in oncogenicity but the implications for human patients have not been explored in depth. We examined 1,360 consecutive PDAC patients undergoing surgical resection and find that KRASG12R mutations are enriched in early-stage (stage I) disease, owing not to smaller tumor size but increased node-negativity. KRASG12R tumors are associated with decreased distant recurrence and improved survival as compared to KRASG12D. To understand the biological underpinnings, we performed spatial profiling of 20 patients and bulk RNA-sequencing of 100 tumors, finding enhanced oncogenic signaling and epithelial-mesenchymal transition (EMT) in KRASG12D and increased nuclear factor κB (NF-κB) signaling in KRASG12R tumors. Orthogonal studies of mouse KrasG12R PDAC organoids show decreased migration and improved survival in orthotopic models. KRAS alterations in PDAC are thus associated with distinct presentation, clinical outcomes, and biological behavior, highlighting the prognostic value of mutational analysis and the importance of articulating mutation-specific PDAC biology.