Decreased Patient Survival Research Articles

Identifying Survival Subtypes of Esophageal Squamous Cell Carcinoma Patients: An Application of Deep Learning in Gene Expression Data Analysis

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most lethal types of cancer. Late diagnosis significantly decreases patient survival rates. Objectives: The study aimed to identify survival groups for patients with ESCC and find predictive biomarkers of time-to-death from ESCC using state-of-the-art deep learning (DL) and machine learning algorithms. Methods: Expression profiles of 60 ESCC patients, along with their demographic and clinical variables, were downloaded from the GEO dataset. A DL autoencoder model was employed to extract lncRNA features. The univariate Cox proportional hazard (Cox-PH) model was used to select significant extracted features related to patient survival. Hierarchical clustering (HC) identified risk groups, followed by a decision trees algorithm which was used to identify lncRNA profiles. We used Python.3.7 and R.4.0.1 software. Results: Inputs of the autoencoder were 8,900 long noncoding RNAs (lncRNAs), of which 1000 features were extracted. Out of the features, 42 lncRNAs were significantly related to time-to-death using the Cox-PH model and used as input for clustering of patients into high and low-risk groups (P-value of log-rank test = 0.022). These groups were then labeled for supervised HC. The C5.0 algorithm achieved an overall accuracy of 0.929 on the test set and identified four hub lncRNAs associated with time-to-death. Conclusions: Novel discovered lncRNAs lnc-FAM84A-1, LINC01866, lnc-KCNE4-2 and lnc-NUDT12-4 implicated in the pathogenesis of death from ESCC. Our findings represent a significant advancement in understanding the role of lncRNAs on ESCC prognosis. Further research is necessary to confirm the potential and clinical application of these lncRNAs.

Bevacizumab reduces cerebral radiation necrosis due to stereotactic radiotherapy in non-small cell lung cancer patients with brain metastases: an inverse probability of treatment weighting analysis.

Cerebral radiation necrosis (RN), a severe complication of stereotactic radiotherapy (SRT), has been shown to significantly decrease patient survival time and quality of life. The purpose of this study was to analyze whether bevacizumab can prevent or reduce the occurrence of SRT-induced cerebral RN in non-small cell lung cancer (NSCLC) patients with brain metastases. We retrospectively reviewed the clinical records of NSCLC patients with brain metastases from March 2013 to June 2023 who were treated with SRT. Patients were divided into two groups: those in the bevacizumab group received SRT with four cycles of bevacizumab, and patients in the control group received SRT only. Inverse probability of treatment weighting (IPTW) was performed based on a multinomial propensity score model to balance the baseline characteristics. The chi-square test was used. A Cox model was used to evaluate overall survival (OS). A total of 80 patients were enrolled, namely, 28 patients in the bevacizumab group and 52 patients in the control group. The possibility of developing cerebral RN and/or symptomatic edema (RN/SE) was significantly decreased in patients treated with bevacizumab compared to those who did not receive bevacizumab before IPTW (p=0.036) and after IPTW (p=0.015) according to chi-square analysis. The IPTW-adjusted median OS was 47.7 months (95% CI 27.4-80.8) for patients in the bevacizumab group and 44.1 months (95% CI 36.7-68.0) (p=0.364) for patients in the control group. The application of bevacizumab concurrent with SRT may prevent or reduce the occurrence of cerebral RN in NSCLC patients with brain metastases.

Soluble ST2: A Novel Biomarker for Diagnosis and Prognosis of Cardiovascular Disease.

The increasing incidence of cardiovascular disease (CVD) is a significant global health concern, affecting millions of individuals each year. Accurate diagnosis of acute CVD poses a formidable challenge, as misdiagnosis can significantly decrease patient survival rates. Traditional biomarkers have played a vital role in the diagnosis and prognosis of CVDs, but they can be influenced by various factors, such as age, sex, and renal function. Soluble ST2 (sST2) is a novel biomarker that is closely associated with different CVDs. Its low reference change value makes it suitable for continuous measurement, unaffected by age, kidney function, and other confounding factors, facilitating risk stratification of CVDs. Furthermore, the combination of sST2 with other biomarkers can enhance diagnostic accuracy and prognostic value. This review aims to provide a comprehensive overview of sST2, focusing on its diagnostic and prognostic value as a myocardial marker for different types of CVDs and discussing the current limitations of sST2.

Investigating the Association between LncRNA NR2F2-AS1, miR-320b, and BMI1 in Gastric Cancer: Insights into Expression Profiles as Potential Biomarkers for Disease Management.

This study aims to investigate the potential role of lncRNA NR2F2-AS1 in the development of gastric cancer by affecting the levels of miR-320b and BMI1. Gastric cancer is a high-mortality malignancy, and understanding the underlying molecular mechanisms is crucial. Non-coding RNAs play an important role in gene expression, and their dysregulation can lead to tumor initiation and progression. This study aims to determine the pathological role of LncRNA NR2F2-AS1 in gastric cancer progression and its association with the clinicopathological characteristics of patients. Bioinformatics databases were used to predict the expression levels and interactions between the studied factors to achieve this objective. The expression pattern of NR2F2-AS1/miR- 320b/BMI1 in 40 pairs of tumor and adjacent normal tissues was examined using RT-PCR, IHC, and western blot. The correlation, ROC curve, and survival analyses were also conducted for the aforementioned factors. The results showed an increase of more than 2-fold for BMI-1 and lncRNA NR2F2-AS1 in lower stages, and the elevation continued with the increasing stage of the disease. This correlated with significant downregulation of miR-320b and PTEN, indicating their association with gastric cancer progression and decreased patient survival. LncRNA NR2F2-AS1 acts as an oncogene by influencing the level of miR-320b, altering the amount of BMI1. A reduction in the amount of miR-320b against lncRNA NR2F2-AS1 and BMI1 directly correlates with a reduced overall survival rate of patients, especially if this disproportion is more than 3.0. ROC curve analysis indicated that alteration in the lncRNA NR2F2-AS1 level showed more than 98.0% sensitivity and specificity to differentiate the lower from higher stages of GC and predict the early onset of metastasis. In conclusion, these results suggest that NR2F2-AS1/miR-320b/BMI1 has the potential to be a prognostic as well as diagnostic biomarker for gastric cancer.

Potentiating dual-directional immunometabolic regulation with nanomedicine to enhance anti-tumor immunotherapy following incomplete photothermal ablation

Photothermal therapy (PTT) is a promising cancer treatment method due to its ability to induce tumor-specific T cell responses and enhance therapeutic outcomes. However, incomplete PTT can leave residual tumors that often lead to new metastases and decreased patient survival in clinical scenarios. This is primarily due to the release of ATP, a damage-associated molecular pattern that quickly transforms into the immunosuppressive metabolite adenosine by CD39, prevalent in the tumor microenvironment, thus promoting tumor immune evasion. This study presents a photothermal nanomedicine fabricated by electrostatic adsorption among the Fe-doped polydiaminopyridine (Fe-PDAP), indocyanine green (ICG), and CD39 inhibitor sodium polyoxotungstate (POM-1). The constructed Fe-PDAP@ICG@POM-1 (FIP) can induce tumor PTT and immunogenic cell death when exposed to a near-infrared laser. Significantly, it can inhibit the ATP-adenosine pathway by dual-directional immunometabolic regulation, resulting in increased ATP levels and decreased adenosine synthesis, which ultimately reverses the immunosuppressive microenvironment and increases the susceptibility of immune checkpoint blockade (aPD-1) therapy. With the aid of aPD-1, the dual-directional immunometabolic regulation strategy mediated by FIP can effectively suppress/eradicate primary and distant tumors and evoke long-term solid immunological memory. This study presents an immunometabolic control strategy to offer a salvage option for treating residual tumors following incomplete PTT.

MCT4 and CD147 colocalize with MMP14 in invadopodia and support matrix degradation and invasion by breast cancer cells.

Expression levels of the lactate-H+ cotransporter MCT4 (also known as SLC16A3) and its chaperone CD147 (also known as basigin) are upregulated in breast cancers, correlating with decreased patient survival. Here, we test the hypothesis that MCT4 and CD147 favor breast cancer invasion through interdependent effects on extracellular matrix (ECM) degradation. MCT4 and CD147 expression and membrane localization were found to be strongly reciprocally interdependent in MDA-MB-231 breast cancer cells. Overexpression of MCT4 and/or CD147 increased, and their knockdown decreased, migration, invasion and the degradation of fluorescently labeled gelatin. Overexpression of both proteins led to increases in gelatin degradation and appearance of the matrix metalloproteinase (MMP)-generated collagen-I cleavage product reC1M, and these increases were greater than those observed upon overexpression of each protein alone, suggesting a concerted role in ECM degradation. MCT4 and CD147 colocalized with invadopodia markers at the plasma membrane. They also colocalized with MMP14 and the lysosomal marker LAMP1, as well as partially with the autophagosome marker LC3, in F-actin-decorated intracellular vesicles. We conclude that MCT4 and CD147 reciprocally regulate each other and interdependently support migration and invasiveness of MDA-MB-231 breast cancer cells. Mechanistically, this involves MCT4-CD147-dependent stimulation of ECM degradation and specifically of MMP-mediated collagen-I degradation. We suggest that the MCT4-CD147 complex is co-delivered to invadopodia with MMP14.

Beyond Hormones: Investigating the Impact of Progesterone Receptor Membrane Component 1 in Lung Adenocarcinoma.

Progesterone Receptor Membrane Component 1 (PGRMC1) is a candidate oncogene with a prominent involvement in the pathogenesis of diverse cancers (ovarian, thyroid, breast, colon, head, and neck). Our study ascertains the ability of PGRMC1 to influence WNT members in the non-small cell lung cancer subtype-lung adenocarcinoma (LUAD) and participates in augmented cell proliferation and migration. Both computational and in vitro experimental analyses were performed in this study. Gene silencing, in vitro assays, gene expression & and protein expression studies were performed to ascertain the role of PGRMC1 in LUAD cells. The computational analysis, PGRMC1 gene level expression was analysed using the microarray gene expression omnibus datasets (GSE27262; GSE18842) to compare LUAD tumours and normal tissues. Concurrently, the gene expression profiling interactive analysis of PGRMC1 and Kaplan-Meier survival analysis revealed a decreasing patient survival rate with an increasing PGRMC1 gene expression in LUAD tumour samples. Interestingly, the experimental gene silencing studies were conducted in vitro (si-PGRMC1 Vs si-Control) to understand the essential role of PGRMC1 in regulating WNT-associated genes (WNT1, WNT5A, and WNT11). Comparative experimental cell migration and spheroid formation assays (si-PGRMC1 Vs si-Control) in vitro showed a strong association between PGRMC1 and LUAD. In vitro expression analysis using real-time PCR and western blot further confirmed the connecting link between PGRMC1 and WNT5A compared to other WNT member genes (WNT1 and WNT11) in LUAD. The computational and experimental analyses agreed with one another.

Abstract 1495: Lipocalin-2 promotes breast cancer metastasis via tumor cell intrinsic and extrinsic mechanisms

Abstract While metastasis is the primary factor predicting poor outcomes in solid tumors, survival is lowest in patients initially diagnosed with a localized malignancy that then progresses to metastatic disease. Notably, nearly 25% of early-stage breast cancers (BCs) metastasize during treatment or following an initial positive response to therapeutic intervention. To define the molecular and cellular factors that contribute to metastatic progression of BC, we previously developed the Py230-C57Bl/6 syngeneic experimental metastasis model for interrogating mechanisms by which soluble factors condition premetastatic lung tissue to potentiate BC cell seeding/expansion. Using this model and the TCGA, we identified lipocalin-2 (Lcn2) as a molecular candidate that is upregulated in lung-tropic Py230 cells and other human triple-negative breast cancer (TNBC) cells, and that predicts poor outcomes in human BCs. While Lcn2 has been previously reported to mediate BC progression in genetically engineered mouse models, its mechanism(s) of action remain undefined. Here, we demonstrate that Py230 cell-secreted Lcn2 is necessary for optimal reprogramming of the premetastatic lung during metastatic progression. In agreement with these data, we defined a cell intrinsic role for Lcn2 in BC cell organoid assembly/invasion and expression of proinflammatory factors. To define BC cell extrinsic roles for Lcn2 in remodeling the premetastatic lung, we collected global transcriptome and single-cell spatial proteome data for lung tissue from C57Bl/6 mice systemically educated with mock media or media conditioned with Py8119 (Lcn2low) or Py230 (Lcn2hi) BC cells. Mice receiving Py230 conditioned media treatments were further divided between two groups – one receiving an isotype control IgG and the other receiving an Lcn2 immunoneutralizing antibody. Global transcriptome data was used to determine novel gene set enrichment signatures and clinically relevant interactomes – notable candidates predicted to cooperate with Lcn2 in decreasing patient survival were affiliated with cilia biogenesis and function. Single-cell spatial proteome data were analyzed for 28 different cell populations within the premetastatic lung. Interestingly, Py230 cell-derived Lcn2 did not affect the percentage of ciliated epithelial cells indicating that the global transcriptome data referenced above represent a real increase in expression of cilia-related genes and not an increase in cilia-positive cell types. Notably, we identified that Lcn2 increased the percentage of CD45neg/Despos mechanomodulatory cells and proliferating CD45pos/CD3pos/CD4neg/CD8pos cytotoxic T cells in the premetastatic lung. Taken together, these data define new targets around which new therapeutic strategies can be developed to improve BC patient outcomes. Citation Format: Joshua Gamez, Francesca Sanchez, Gabriela Ortiz-Soto, Jane Cox, Amir Gerami, Jonathan A. Kelber. Lipocalin-2 promotes breast cancer metastasis via tumor cell intrinsic and extrinsic mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1495.

Abstract B093: Investigating early events of ovarian cancer transcoelomic metastasis identifies the small Rho-GTPase RHOV as an essential gene for cellular detachment and aggregate formation

Abstract B093: Investigating early events of ovarian cancer transcoelomic metastasis identifies the small Rho-GTPase RHOV as an essential gene for cellular detachment and aggregate formation

Coactosin-Like Protein 1 (COTL1) Could Be an Immunological and Prognostic Biomarker: From Pan-Cancer Analysis to Low-Grade Glioma Validation.

Cancer represents a widespread global health challenge impacting millions of individuals worldwide. Identifying new targets for cancer treatment is a crucial step in developing more effective therapies. Among these potential targets, Coactosin-like protein 1 (COTL1), a cytoskeleton-associated protein with critical roles in cell migration, adhesion, and signaling, has shown involvement in tumor progression. GSCA, TIMER, SangerBox database were used to explore the COTL1 expression across different tumor types. We employed the TCGA Pan-Atlas Cancer Genomics Dataset, which is available through the cBioportal platform, to explore genetic alterations in COTL1. We conduct a comprehensive analysis of COTL1, encompassing gene expression, clinical prognosis, RNA modification, immunotherapy, and cancer stemness through SangerBox database. Clinical samples were validated using immunohistochemistry. Our analysis revealed that COTL1 is highly expressed in most cancers and correlates with decreased survival in Glioma, Glioblastoma multiforme, and pan-kidney cohorts. Furthermore, COTL1 was found to be associated with DNA and RNA stemness in 20 and 22 different tumor types, respectively. Additionally, COTL1 showed positive correlations with immunological checkpoints and immune infiltration cells. It was also linked to tumor mutation burden (TMB), microsatellite instability (MSI), neoantigen (NEO), and programmed death ligand 1 (PD-L1), all of which are potential targets for immunotherapies. Moreover, a favorable relationship was demonstrated between genomic-instability markers such as heterozygosity (LOH), homologous recombination deficiency (HRD), and mutant allele tumor heterogeneity (MATH) with COTL1. Furthermore, our findings confirmed a positive correlation between COTL1 expression, CD8, and PD-L1 in LGG, as well as an association of high COTL1 expression with decreased patient survival in LGG. Based on these compelling findings, COTL1 may hold significant clinical implications for the development of novel cancer therapies and serve as a potential target for tumors associated with immunotherapy in the future.

Essential role of PLD2 in hypoxia-induced stemness and therapy resistance in ovarian tumors.

Hypoxia in solid tumors is an important source of chemoresistance that can determine poor patient prognosis. Such chemoresistance relies on the presence of cancer stem cells (CSCs), and hypoxia promotes their generation through transcriptional activation by HIF transcription factors. We used ovarian cancer (OC) cell lines, xenograft models, OC patient samples, transcriptional databases, induced pluripotent stem cells (iPSCs) and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). Here, we show that hypoxia induces CSC formation and chemoresistance in ovarian cancer through transcriptional activation of the PLD2 gene. Mechanistically, HIF-1α activates PLD2 transcription through hypoxia response elements, and both hypoxia and PLD2 overexpression lead to increased accessibility around stemness genes, detected by ATAC-seq, at sites bound by AP-1 transcription factors. This in turn provokes a rewiring of stemness genes, including the overexpression of SOX2, SOX9 or NOTCH1. PLD2 overexpression also leads to decreased patient survival, enhanced tumor growth and CSC formation, and increased iPSCs reprograming, confirming its role in dedifferentiation to a stem-like phenotype. Importantly, hypoxia-induced stemness is dependent on PLD2 expression, demonstrating that PLD2 is a major determinant of de-differentiation of ovarian cancer cells to stem-like cells in hypoxic conditions. Finally, we demonstrate that high PLD2 expression increases chemoresistance to cisplatin and carboplatin treatments, both in vitro and in vivo, while its pharmacological inhibition restores sensitivity. Altogether, our work highlights the importance of the HIF-1α-PLD2 axis for CSC generation and chemoresistance in OC and proposes an alternative treatment for patients with high PLD2 expression.

Living Donor Whole and Partial Liver Grafts, Deceased Donor Whole Liver and SPLIT: Outcome Comparison

BackgroundCurrently, graft options for pediatric liver transplantation (PLT) include whole (WL) and partial (P) grafts, in the form of either deceased donor transplantation (DD) or living donor liver transplantation (LD). WL transplants from LD are commonly referred to as domino LT. The objective of this manuscript is to compare the outcomes of PLT performed with each of the available graft options. MethodsRetrospective cohort study from Jan. 2010 to Dec. 2022. The variables included data on the recipients’ preoperative clinical status, intraoperative technical aspects, post-operative complications, and survival studies. There were 4 groups: SPLIT (17), DD-WL (55), LD-WL (824), and LD-P (22). ResultsThe median age and BW of the recipients was smaller in SPLIT, LD-P, and LD-WL compared to DDT-WL groups. HVOO (HR 15.87, 95% CI 1.89–133.06, P = 0.01), retransplantation (HR 7.94, 95% CI 2.63–24.02, P < 0.01), and malignancies (HR 3.08, 95% CI 1.29–7.37, P = 0.01) were independently associated with decreased patient survival. HAT (HR 27.54, 95% CI 10.44–72.68, P < 0.01) and malignancies (HR 2.42, 95% CI 1.10–5.34, P = 0.03) increased the risk of graft loss. The overall survival in this series was 91.4% (mean follow-up of 74.3 months). Patient and graft survival were not different among groups. ConclusionHAT and malignancies were associated with reduced graft survival. Whole liver from living donors with MSUD presented 100% patient survival at 120 months. Even without statistical differences in survival among the studied groups, LD-P and LD-WL recipients presented a trend towards better outcomes. Level of EvidenceLEVEL III.

Multidimensional screening of pancreatic cancer spheroids reveals vulnerabilities in mitotic and cell-matrix adhesion signaling that associate with metastatic progression and decreased patient survival

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy, with a median survival of less than 12 months and a 5-year survival of less than 10 %. Here, we have established an image-based screening pipeline for quantifying single PDAC spheroid dynamics in genetically and phenotypically diverse PDAC cell models. Wild-type KRas PDAC cells formed tight/compact spheroids – compaction of these structures was completely blocked by cytoplasmic dynein and focal adhesion kinase (FAK) inhibitors. In contrast, PDAC cells containing mutant KRas formed loosely aggregated spheroids that grew significantly slower following inhibition of polo-like kinase 1 (PLK1) or focal adhesion kinase (FAK). Independent of genetic background, multicellular PDAC-mesenchymal stromal cell (MSC) spheroids self-organized into structures with an MSC-dominant core. The inclusion of MSCs into wild-type KRas PDAC spheroids modestly affected their compaction; however, MSCs significantly increased the compaction and growth of mutant KRas PDAC spheroids. Notably, exogenous collagen 1 potentiated PANC1 spheroid compaction while ITGA1 knockdown in PANC1 cells blocked MSC-induced PANC1 spheroid compaction. In agreement with a role for collagen-based integrin adhesion complexes in stromal cell-induced PDAC phenotypes, we also discovered that MSC-induced PANC1 spheroid growth was completely blocked by the ITGB1 immunoneutralizing antibody mAb13. Finally, multiplexed single-cell immunohistochemical analysis of a 25 patient PDAC tissue microarray revealed a relationship between decreased variance in Spearman r correlation for ITGA1 and PLK1 expression within the tumor cell compartment of PDAC in patients with advanced disease stage, and elevated expression of both ITGA1 and PLK1 in PDAC was found to be associated with decreased patient survival. Taken together, this work uncovers new therapeutic vulnerabilities in PDAC that are relevant to the progression of this stromal cell-rich malignancy and which may reveal strategies for improving patient outcomes.

To study the utility of tumor budding as a histopathological marker in comparison to various histopathological parameters and TNM staging in breast carcinoma

Background Breast cancer is the leading cause of death in Indian females. Detection of breast cancer in later stages leads to poorer prognosis and therefore decreases patient survival. Various new modalities such as mammography and USG guided FNACs are developed and many new markers are available to diagnose breast cancer; however, tumour budding is a cost-effective method which can be helpful in early diagnosis. Tumour buds are found to have a positive correlation with various histopathological prognostic markers in breast cancer. The present study will be conducted to evaluate tumour buds as a prognostic marker in breast cancer. This study aims to compare tumour budding with histopathological prognostic markers, TNM staging and IHC phenotypes. Methods The study will be observational, cross- sectional, and prospective, will include 60 cases and will be conducted at Jawaharlal Nehru Medical College (JNMC) Wardha in the Pathology Department. Results Data will be collected and combined together over a period of two years and will be analysed statistically for tumour budding as a marker and its correlation with breast prognosis.

Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma

Disulfidptosis, a novel form of regulated cell death, occurs due to the aberrant accumulation of intracellular cystine and other disulfides. Moreover, targeting disulfidptosis could identify promising approaches for cancer treatment. Long non-coding RNAs (lncRNAs) are known to be critically implicated in clear cell renal cell carcinoma (ccRCC) development. Currently, the involvement of disulfidptosis-related lncRNAs in ccRCC is yet to be elucidated. This study primarily dealt with identifying and validating a disulfidptosis-related lncRNAs-based signature for predicting the prognosis and immune landscape of individuals with ccRCC. Clinical and RNA sequencing data of ccRCC samples were accessed from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted for the identification of the disulfidptosis-related lncRNAs. Additionally, univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator Cox regression, and stepwise multivariate Cox analysis were executed to develop a novel risk prognostic model. The prognosis-predictive capacity of the model was then assessed using an integrated method. Variation in biological function was noted using GO, KEGG, and GSEA. Additionally, immune cell infiltration, the tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores were calculated to investigate differences in the immune landscape. Finally, the expression of hub disulfidptosis-related lncRNAs was validated using qPCR. We established a novel signature comprised of eight lncRNAs that were associated with disulfidptosis (SPINT1-AS1, AL121944.1, AC131009.3, AC104088.3, AL035071.1, LINC00886, AL035587.2, and AC007743.1). Kaplan–Meier and receiver operating characteristic curves demonstrated the acceptable predictive potency of the model. The nomogram and C-index confirmed the strong correlation between the risk signature and clinical decision-making. Furthermore, immune cell infiltration analysis and ssGSEA revealed significantly different immune statuses among risk groups. TMB analysis revealed the link between the high-risk group and high TMB. It is worth noting that the cumulative effect of the patients belonging to the high-risk group and having elevated TMB led to decreased patient survival times. The high-risk group depicted greater TIDE scores in contrast with the low-risk group, indicating greater potential for immune escape. Finally, qPCR validated the hub disulfidptosis-related lncRNAs in cell lines. The established novel signature holds potential regarding the prognosis prediction of individuals with ccRCC as well as predicting their responses to immunotherapy.

Comprehensive split TEV based protein-protein interaction screening reveals TAOK2 as a key modulator of Hippo signalling to limit growth.

The conserved Hippo signalling pathway plays a crucial role in tumour formation by limiting tissue growth and proliferation. At the core of this pathway are tumour suppressor kinases STK3/4 and LATS1/2, which limit the activity of the oncogene YAP1, the primary downstream effector. Here, we employed a split TEV-based protein-protein interaction screen to assess the physical interactions among 28 key Hippo pathway components and potential upstream modulators. This screen led us to the discovery of TAOK2 as pivotal modulator of Hippo signalling, as it binds to the pathway's core kinases, STK3/4 and LATS1/2, and leads to their phosphorylation. Specifically, our findings revealed that TAOK2 binds to and phosphorylates LATS1, resulting in the reduction of YAP1 phosphorylation and subsequent transcription of oncogenes. Consequently, this decrease led to a decrease in cell proliferation and migration. Interestingly, a correlation was observed between reduced TAOK2 expression and decreased patient survival time in certain types of human cancers, including lung and kidney cancer as well as glioma. Moreover, in cellular models corresponding to these cancer types the downregulation of TAOK2 by CRISPR inhibition led to reduced phosphorylation of LATS1 and increased proliferation rates, supporting TAOK2's role as tumour suppressor gene. By contrast, overexpression of TAOK2 in these cellular models lead to increased phospho-LATS1 but reduced cell proliferation. As TAOK2 is a druggable kinase, targeting TAOK2 could serve as an attractive pharmacological approach to modulate cell growth and potentially offer strategies for combating cancer.

Integrated Gene Expression Data-Driven Identification of Molecular Signatures, Prognostic Biomarkers, and Drug Targets for Glioblastoma.

Glioblastoma (GBM) is a highly prevalent and deadly brain tumor with high mortality rates, especially among adults. Despite extensive research, the underlying mechanisms driving its progression remain poorly understood. Computational analysis offers a powerful approach to explore potential prognostic biomarkers, drug targets, and therapeutic agents for GBM. In this study, we utilized three gene expression datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) associated with GBM progression. Our goal was to uncover key molecular players implicated in GBM pathogenesis and potential avenues for targeted therapy. Analysis of the gene expression datasets revealed a total of 78 common DEGs that are potentially involved in GBM progression. Through further investigation, we identified nine hub DEGs that are highly interconnected in protein-protein interaction (PPI) networks, indicating their central role in GBM biology. Gene Ontology (GO) and pathway enrichment analyses provided insights into the biological processes and immunological pathways influenced by these DEGs. Among the nine identified DEGs, survival analysis demonstrated that increased expression of GMFG correlated with decreased patient survival rates in GBM, suggesting its potential as a prognostic biomarker and preventive target for GBM. Furthermore, molecular docking and ADMET analysis identified two compounds from the NIH clinical collection that showed promising interactions with the GMFG protein. Besides, a 100 nanosecond molecular dynamics (MD) simulation evaluated the conformational changes and the binding strength. Our study highlights the potential of GMFG as both a prognostic biomarker and a therapeutic target for GBM. The identification of GMFG and its associated pathways provides valuable insights into the molecular mechanisms driving GBM progression. Moreover, the identification of candidate compounds with potential interactions with GMFG offers exciting possibilities for targeted therapy development. However, further laboratory experiments are required to validate the role of GMFG in GBM pathogenesis and to assess the efficacy of potential therapeutic agents targeting this molecule.

Evaluation of the accuracy of heart dose prediction by machine learning for selecting patients not requiring deep inspiration breath‑hold radiotherapy after breast cancer surgery.

Increased heart dose during postoperative radiotherapy (RT) for left-sided breast cancer (BC) can cause cardiac injury, which can decrease patient survival. The deep inspiration breath-hold technique (DIBH) is becoming increasingly common for reducing the mean heart dose (MHD) in patients with left-sided BC. However, treatment planning and DIBH for RT are laborious, time-consuming and costly for patients and RT staff. In addition, the proportion of patients with left BC with low MHD is considerably higher among Asian women, mainly due to their smaller breast volume compared with that in Western countries. The present study aimed to determine the optimal machine learning (ML) model for predicting the MHD after RT to pre-select patients with low MHD who will not require DIBH prior to RT planning. In total, 562 patients with BC who received postoperative RT were randomly divided into the trainval (n=449) and external (n=113) test datasets for ML using Python (version 3.8). Imbalanced data were corrected using synthetic minority oversampling with Gaussian noise. Specifically, right-left, tumor site, chest wall thickness, irradiation method, body mass index and separation were the six explanatory variables used for ML, with four supervised ML algorithms used. Using the optimal value of hyperparameter tuning with root mean squared error (RMSE) as an indicator for the internal test data, the model yielding the best F2 score evaluation was selected for final validation using the external test data. The predictive ability of MHD for true MHD after RT was the highest among all algorithms for the deep neural network, with a RMSE of 77.4, F2 score of 0.80 and area under the curve-receiver operating characteristic of 0.88, for a cut-off value of 300 cGy. The present study suggested that ML can be used to pre-select female Asian patients with low MHD who do not require DIBH for the postoperative RT of BC.

Identifying the effectiveness of 3D culture systems to recapitulate breast tumor tissue in situ.

Breast cancer heterogeneity contributes to chemotherapy resistance and decreased patient survival. To improve patient outcomes it is essential to develop a technology that is able to rapidly select the most efficacious therapy that targets the diverse phenotypes present within the tumor. Breast cancer organoid technologies are proposed as an attractive approach for evaluating drug responses prior to patient therapy. However, there remain challenges in evaluating the effectiveness of organoid cultures to recapitulate the heterogeneity present in the patient tumor in situ. Organoids were generated from seven normal breast and nineteen breast cancer tissues diagnosed as estrogen receptor positive or triple negative. The Jensen-Shannon divergence index, a measure of the similarity between distributions, was used to compare and evaluate heterogeneity in starting tissue and their resultant organoids. Heterogeneity was analyzed using cytokeratin 8 and cytokeratin 14, which provided an easily scored readout. In the in vitro culture system HER1 and FGFR were able to drive intra-tumor heterogeneity to generate divergent phenotypes that have different sensitivities to chemotherapies. Our methodology, which focuses on quantifiable cellular phenotypes, provides a tractable system that complements omics approaches to provide an unprecedented view of heterogeneity and will enhance the identification of novel therapies and facilitate personalized medicine.

Neurotransmitter Receptor HTR2B Regulates Lipid Metabolism to Inhibit Ferroptosis in Gastric Cancer.

Nerve cancer cross-talk mediated by HTR2B inhibits lipid peroxidation and ferroptosis in gastric cancer cells and promotes viability under metabolic stress, resulting in increased tumor growth and decreased patient survival.