Potential Prognostic Biomarker Research Articles

Abstract B017: The double-edged sword of cystatin B in luminal-like and triple-negative breast cancers

Abstract The complex protease network of cathepsins and their inhibitors, cystatins, intricately regulates numerous cellular processes, and its dysregulation is frequently implicated in cancer pathogenesis. Abnormal cathepsin activity, subcellular localization, and a disrupted balance between cathepsins and cystatins have been identified in cancer. While diminished cystatin levels typically correlate with more aggressive cancer phenotypes, few findings challenge this paradigm. In this context, our latest study revealed elevated expression of cystatin B (CSTB) in luminal-like breast cancer (BC) patients experiencing relapse within five years post-surgery. Furthermore, computational analysis of publicly available datasets supports our idea of CSTB as a potential negative prognostic biomarker in luminal-like tumors. Intriguingly, a converse relationship is observed in basal-like/triple negative BC patients, where increased CSTB expression seems to be associated with improved prognosis. In addition, the cysteine/cathepsin network intricately intersects with immune functions, adding another layer of complexity. Cathepsins are indeed involved in the induction of an efficient anti-tumor immune response, being key in antigen processing and presentation by antigen-presenting cells and in the cytotoxic activities of NK and T cells. On the other hand, myeloid cells rely on cathepsins for the degradation of ECM proteins that may favor migration and invasion of tumor cells. All these pieces of evidence led to the hypothesis that the functional impact of CSTB may vary depending on the tumor intrinsic characteristics and on its microenvironment and therefore that CSTB might fulfill distinct functional roles in luminal-like and basal-like BC. To start addressing our hypothesis, we silenced CSTB expression in the 4T1 mouse cell line, a TNBC model spontaneously metastasizing to the lungs upon intra-mammary fat pad injection. Preliminary in vivo experiments to investigate the effect on primary tumor growth and metastatic dissemination showed that 4T1 shCSTB lines were indeed characterized by increased tumor growth and metastatic dissemination than the two sh-control lines. Interestingly, expression of stemness- related genes (Nanog, Sox2 and Oct4) were up-modulated upon CTSB silencing, in agreement with a more aggressive phenotype. On the other hand, preliminary in vitro assays with a luminal- like BC cell line support the hypothesis of an opposite effect of CSTB down-modulation in luminal BC subtype. Moreover, CSTB silencing in RAW264.7 macrophagic cell line, impaired M1 in vitro polarization, while it did not appear to affect M2 skewing. Overall, although preliminary, these data suggest that CSTB may affect BC aggressiveness by both interfering with tumor cell-intrinsic features and microenviroment-related traits. Citation Format: Anna Zaccaria, Chiara Ratti, Laura Botti, Sabina Sangaletti, Mario P. Colombo, Claudia Chiodoni. The double-edged sword of cystatin B in luminal-like and triple-negative breast cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B017.

Soluble Urokinase-Type Plasminogen Activator Receptor and Inflammatory Biomarker Response with Prognostic Significance after Acute Neuronal Injury - a Prospective Cohort Study.

Aneurysmal subarachnoid hemorrhage (aSAH), ischemic stroke (IS), and traumatic brain injury (TBI) are severe conditions impacting individuals and society. Identifying reliable prognostic biomarkers for predicting survival or recovery remains a challenge. Soluble urokinase type plasminogen activator receptor (suPAR) has gained attention as a potential prognostic biomarker in acute sepsis. This study evaluates suPAR and related neuroinflammatory biomarkers in serum for brain injury prognosis. This prospective study included 31 aSAH, 30 IS, 13 TBI, and three healthy controls (n = 77). Serum samples were collected on average 5.9days post-injury, analyzing suPAR, IL-1β, cyclophilin A, and TNFα levels using ELISA. Outcomes were assessed 90days post-injury with the modified Rankin Scale (mRS), categorized as favorable (mRS 0-2) or unfavorable (mRS 3-6). Statistical analyses included 2-tailed t-tests, Pearson's correlations, and machine learning linear discriminant analysis (LDA) for biomarker combinations. Elevated suPAR levels were found in brain injury patients compared to controls (p = 0.017). Increased suPAR correlated with unfavorable outcomes (p = 0.0018) and showed prognostic value (AUC = 0.66, p = 0.03). IL-1β levels were higher in the unfavorable group (p = 0.0015). LDA combinatory analysis resulted a fair prognostic accuracy with canonical equation = 0.775[suPAR] + 0.667[IL1-β] (AUC = 0.77, OR 0.296, sensitivity 93.1%, specificity 53.1%, p = 0.0007). No correlation was found between suPAR and CRP or infection status. Elevated suPAR levels in acute brain injury patients were associated with poorer outcomes, highlighting suPAR's potential as a prognostic biomarker across different brain injury types. Combining IL-1β with suPAR improved prognostic accuracy, supporting a multimodal biomarker approach for predicting outcomes.

Potential Prognostic Protein Biomarkers in Tears From Noninfectious Uveitis Patients Under Biologic Treatment as a Prelude to Personalized Medicine.

Adalimumab (ADA) is a systemic biological treatment option approved for the treatment of noninfectious uveitis (NIU); however, up to 40% of patients do not respond to the drug, either in a primary or secondary manner. Here, we evaluated the proteomic profile of patients with NIU who fail to ADA to identify proteins implicated in intraocular inflammation, as well as potential biomarkers for treatment response and novel therapeutic targets. Cross-sectional observational study of patients with NIU under ADA treatment for six or more months. Tears were collected with microcapillary tubes and protein analyzed by data-independent acquisition/sequential window acquisition of all theoretical mass spectra. Differentially expressed proteins (DEPs) were defined based on the fold change between their expression in nonresponders (NR) and responders (R). Protein network and gene ontology analysis were performed. The χ2 test for trend and receiver operating characteristic (ROC) curves were used to evaluate potential biomarkers of treatment response. Twenty-nine DEPs, 14 upregulated and 15 downregulated, were detected in NR. These proteins were mainly related to enhanced neutrophil effector functions and redox imbalance. ROC analysis identified defensin-1,3 (DEF-1,3), biotinidase, and ATP-binding cassette transporter A1 as potential biomarkers for treatment response. This is the first study on a clinical cohort of patients with noninfectious uveitis that identifies tear proteins related to neutrophil hyperactivation as drivers of the persistent intraocular inflammation observed in NR to ADA and provides evidence that targeting interleukin 6, Janus kinases, or the complement cascade could be potential alternative therapeutic strategies in these patients. Our results indicate the potential of high-throughput proteomics to provide insights into the underlying pathological mechanisms of persistent intraocular inflammation observed in patients who do not adequately respond to anti-TNF treatment and the value of tear proteomics as a tool for personalized medicine.

Abstract A020: LncTransformer: Identifying novel prognostic long-noncoding RNA biomarkers for pancreatic cancer using deep learning

Abstract Pancreatic cancer remains a formidable challenge due to high mortality rates and limited therapeutic options due to late detection of the cancer. Recent literature has focused on investigating the potential of long noncoding RNAs (lncRNAs) as biomarkers in several cancers. To identify significantly altered expression of lncRNA in pancreatic cancer, I collected information from the Cancer Genome Atlas (TCGA) and extracted RNA- sequencing (RNA-seq) transcriptomic profiles of pancreatic carcinomas. Out of 60,660 gene transcripts shared between 151 pancreatic cancer patients, 38 lncRNAs were identified to be significantly differentially expressed. To find the lncRNAs related to metastatic progression of pancreatic cancer, different machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest classifier (RFC), and a custom autoencoder model were trained to identify potential prognostic biomarkers. The custom deep learning model predicted metastatic prognostic biomarkers with a 92% accuracy, with the second-best accuracies coming from the SVM and RFC models, having an accuracy of 76%. Using the deep learning model, the following novel lncRNA and gene biomarkers were identified: LINC01300, SERPINB13, AC010789.1, TMPRSS15, DUSP5- DT, AL513128.3, MIR205HG, LINC00486, RF00019, LINC01115, and AC133530.1. Further investigating these results, specifically the identified lncRNA, the LINC01300 was identified to be potentially circulating in the blood. If further analysis proves this hypothesis correct then LINC01300 along with other identified genes could serve as biomarkers in a liquid biopsy. The identified biomarkers would be especially helpful in rural areas with lower accessibility to healthcare as it would allow for an easier, more efficient, and cost-effective method of pancreatic cancer detection. Based on these findings, further investigations of this gene panel in vitro and in vivo will be conducted, as they could be targeted for improved outcomes in pancreatic cancer patients and assist in the diagnosis of metastatic progression based on RNA-seq data of primary pancreatic tumors or the development of a liquid biopsy. Citation Format: Shivali Singh. LncTransformer: Identifying novel prognostic long-noncoding RNA biomarkers for pancreatic cancer using deep learning [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr A020.

MicroRNAome profiling of breast cancer unveils hsa-miR-5683 as a tumor suppressor microRNA predicting favorable clinical outcome.

Breast cancer is a heterogeneous disease with diverse molecular subtypes, underscoring a better understanding of its molecular features and underlying regulatory mechanisms. Therefore, identifying novel prognostic biomarkers and therapeutic targets is crucial for advancing the current standard of care for breast cancer patients. Ninety-six formalin-fixed paraffin-embedded (FFPE) breast cancer samples underwent miRNAome profiling using QIAseq microRNA library kit and sequencing on Illumina platform. Mature miRNA quantification was conducted using CLC Genomics Workbench v21.0.5, while Relapse-free survival (RFS) analysis was conducted using RStudio 2023.09.1. Gain-of-function studies were conducted using miRNA mimics, while the effects of miRNA exogenous expression on cancer hallmark were assessed using 2-dimentional (2D) proliferation assay, three-dimensional (3D) organotypic culture, and live-dead staining. TargetScan database and Ingenuity Pathway Analysis (IPA) were used for miRNA target identification. Hierarchical clustering based on miRNA expression revealed distinct patterns in relation to PAM50 classification and identified miRNAs panels associated with luminal, HER2, and basal subtypes. hsa-miR-5683 emerged as a potential prognostic biomarker, showing a favorable correlation with RFS and suppressing tumorigenicity under 2D and 3D conditions in triple-negative breast cancer (TNBC) models. Findings were further extended to the MCF7 hormone receptor positive (HR+) model. Transcriptomic profiling of hsa-miR-5683 overexpressing TNBC cells revealed its potential role in key oncogenic pathways. Integration of downregulated genes and CRISPR-Cas9 perturbational effects identified ACLY, RACGAP1, AK4, MRPL51, CYB5B, MKRN1, TMEM230, NUP54, ANAPC13, PGAM1, and SOD1 as bona fide gene targets for hsa-miR-5683. Our data provides comprehensive miRNA expression atlas in breast cancer subtypes and underscores the prognostic and therapeutic significance of numerous miRNAs, including hsa-miR-5683 in TNBC. The identified gene targets unravel the intricate regulatory network in TNBC progression, suggesting promising avenues for further research and targeted therapeutic interventions.

Abstract A067: lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models

Abstract Pancreatic cancer remains a formidable challenge due to high mortality rates and limited therapeutic options due to late detection of the cancer. Recent literature has focused on investigating the potential of long noncoding RNAs (lncRNAs) as biomarkers in several cancers. To identify significantly altered expression of lncRNA in pancreatic cancer, I collected information from the Cancer Genome Atlas (TCGA) and extracted RNA-sequencing (RNA-seq) transcriptomic profiles of pancreatic carcinomas. Out of 60,660 gene transcripts shared between 151 pancreatic cancer patients, 38 lncRNAs were identified to be significantly differentially expressed. To find the lncRNAs related to metastatic progression of pancreatic cancer, different machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest classifier (RFC), and a custom autoencoder model were trained to identify potential prognostic biomarkers. The custom deep learning model predicted metastatic prognostic biomarkers with a 92% accuracy, with the second-best accuracies coming from the SVM and RFC models, having an accuracy of 76%. Using the deep learning model, the following novel lncRNA and gene biomarkers were identified: LINC01300, SERPINB13, AC010789.1, TMPRSS15, DUSP5-DT, AL513128.3, MIR205HG, LINC00486, RF00019, LINC01115, and AC133530.1. Further investigating these results, specifically the identified lncRNA, the LINC01300 was identified to be potentially circulating in the blood. If further analysis proves this hypothesis correct then LINC01300 along with other identified genes could serve as a biomarker panel for a liquid biopsy. The identified biomarkers would be especially helpful in rural areas with lower accessibility to healthcare as it would allow for an easier, more efficient, and cost-effective method of pancreatic cancer detection. Based on these findings, further investigations of this gene panel are being conducted, in vitro and in vivo, to create a novel liquid biopsy to assist in the prognostic diagnosis of metastatic progression of pancreatic cancer. Citation Format: Shivali Singh. lncTransformer: Identifying novel prognostic biomarkers for pancreatic cancer using deep learning models [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A067.

Identification of CAPG as a potential prognostic biomarker associated with immune cell infiltration and ferroptosis in uterine corpus endometrial carcinoma

IntroductionCapping actin protein, gelsolin-like (CAPG) is a potential therapeutic target in various cancers. However, the potential immunotherapeutic effects and prognostic value of CAPG in uterine corpus endometrial carcinoma (UCEC) remain unclear.MethodsThe characterization, methylation effects, prognostic value, targeted miRNAs of CAPG, and the correlation of CAPG with immune cell infiltration and ferroptosis in UCEC were investigated using multiple public databases and online tools. Furtherly, we explored the potential physiological function of CAPG using EdU and Transwell migration assays, identified the cell localization and expression of CAPG and GPX4 by immunofluorescence, and detected the intracellular Fe2+ levels using a FerroOrange fluorescent probe in Ishikawa cells. Additionally, the OncoPredict package was used to analyze the potential chemotherapeutic drugs for UCEC.ResultsCAPG showed generally high expression in tumor group. The overall survival rate of the high-risk group was significantly lower than that of the low-risk group. Enrichment analysis indicated that CAPG is involved in immune-related pathways and is closely associated with the tumor microenvironment. CAPG expression levels were affected by abnormal DNA methylation and/or targeted miRNAs, infiltration levels and marker genes of various immune cells, thereby impacting immune response, ferroptosis, and patient prognosis. Ferroptosis analysis indicated that ALOX5 and VLDLR were the top CAPG-related ferroptosis markers; glutathione metabolism levels in tumor group were generally high, and decitabine was a ferroptosis inducer. CAPG-siRNA suppressed the cell proliferation and invasion, and markedly elevated the expression levels of immune-related genes IL8, TNF, TLR4 and the intracellular Fe2+ levels. CAPG co-located with GPX4 in nucleus and co-regulated ferroptosis and metabolism in Ishikawa cells. Moreover, four chemotherapy drugs showed better sensitivity to UCEC patients in the low-risk cohort.ConclusionsCAPG may serve as a potential biomarker of UCEC owing to its role in modulating the immune response and ferroptosis, providing novel perspectives for combined immunotherapy of UCEC.

Complement C1S is a potential prognostic biomarker and associated with M2 macrophage infiltration in gliomas: From bioinformatics to comprehensive experimental validation

Glioma is the most common malignant tumor of the central nervous system, and the ability of traditional clinical treatment to prolong the survival of glioma patients is limited. A substantial body of evidence underscores the pivotal role of the immune system in eradicating malignant cells and impeding tumor metastasis. Consequently, tumor immunotherapy has become a promising avenue to address the clinical conundrum faced by glioma patients. The complement system is a natural immune system that is an important line of defense in the immune response. C1S plays a key role in activating the classical complement system. Nevertheless, few studies have focused on the role of C1S in glioma tumorigenesis and progression. In this study, we demonstrated that C1S was upregulated in GBM (Grade IV) and low-grade gliomas (LGG, Grade II-III) by combining glioma cohorts from multiple public databases with our internal independent cohorts and that increased C1S expression levels predict a poor prognosis for gliomas. Cox regression analysis identified C1S as an important prognostic indicator for glioma patients. In addition, gene functional enrichment analysis demonstrated that C1S was involved in cellular immunity, T-cell activation, macrophage differentiation, and cell proliferation. Further experiments demonstrated that C1S facilitates tumor cell proliferation, cell migration and intracranial tumor growth in nude mice. More importantly, we evaluated the role of C1S in immune infiltration. These results suggested that C1S was closely related to a variety of immune cell types in glioma, especially M2 macrophages. Our findings were further validated via glioma tissue microarray immunohistochemical analysis and an M2 macrophage infiltration assay. Together, these findings revealed the underlying critical role of C1S in glioma tumorigenesis, progression, and the tumor immune microenvironment, contributing to further understanding of glioma pathogenesis and guiding immunotherapy.

RNF19A inhibits bladder cancer progression by regulating ILK ubiquitination and inactivating the AKT/mTOR signalling pathway

BackgroundThe role of the RING finger protein superfamily in carcinogenesis has been widely studied, but one member of this family, RNF19A, has not yet been thoroughly explored in bladder cancer (BCa).MethodsThe expression levels of RNF19A in BCa samples and cell lines were analysed through data mining of public resources and further experiments. BCa cells in which RNF19A was stably overexpressed or knocked down were generated through lentivirus infection. The effects of RNF19A on cell proliferation, migration, and invasion were explored by performing a series of in vitro experiments, including CCK-8, colony formation, wound healing, and Transwell invasion assays. Using bioinformatics methods and multiple experiments, including western blot, qRT‒PCR, immunoprecipitation, cycloheximide, ubiquitination, and rescue assays, the mechanism underlying the effect of RNF19A on the progression of BCa was investigated.ResultsHere, we found that RNF19A expression was reduced in BCa samples and cell lines and that lower RNF19A expression predicted shorter overall survival of BCa patients. Functionally, forced expression of RNF19A suppressed BCa cell proliferation, migration, and invasion by inactivating the AKT/mTOR signalling pathway, whereas silencing RNF19A had the opposite effects. Mechanistically, RNF19A could directly interact with ILK and promote its ubiquitination and degradation. Rescue experiments revealed that forced ILK expression partially rescued the decreased phosphorylation of AKT, mTOR, and S6K1 caused by RNF19A overexpression and that the increased levels of the p-AKT, p-mTOR, and p-S6K1 proteins induced by RNF19A knockdown were eliminated after silencing ILK. Similarly, the effects of RNF19A overexpression or knockdown on the phenotypes of cell proliferation, migration, and invasion could also be restored by forced or decreased ILK expression.ConclusionsRNF19A suppressed the proliferation, migration, and invasion abilities of BCa cells by regulating ILK ubiquitination and inactivating the AKT/mTOR signalling pathway. RNF19A might be a potential prognostic biomarker and promising therapeutic target for BCa.

TPD52 is a Potential Prognostic Biomarker and Correlated with Immune Infiltration: A Pan-cancer Analysis.

Some tumors have a poor prognosis regarding TPD52 (tumor protein D52). This study aims to explore TPD52's role in the cancer process from a pan-cancer perspective. A pan-cancer analysis was conducted to investigate how TPD52 may be involved in cancer as well as its association with prognosis. A variety of human cancers express TPD52 abnormally and correlate with clinical stage. There was a significant association between low expression of TPD52 and poor survival in BRCA, KIRP, LAML, LIHC, UCEC, and UVM. TPD52 alterations were most frequently amplified in pan-cancer. The co-occurrence of 10 genes alterations was found in the TPD52 altered group. There was a significant association between TPD52 expression and MSI in four cancer types and TMB in twelve cancer types. There was a significant correlation between TPD52 expression and immunerelated cell infiltration. A significant correlation was found between TPD52 expression in many tumor types and 8 immune checkpoint genes. There were signaling pathways involved in pan-cancer caused by TPD52, including endocytosis, Fc gamma Rmediated phagocytosis, and so on. TPD52 may be involved in chemotherapy and chemoresistance. The TPD52 gene may be important for human cancer treatment.

Homologous recombination deficiency score is an independent prognostic factor in esophageal squamous cell carcinoma.

Homologous recombination deficiency (HRD) represents an impairment in the homologous recombination repair (HRR) pathway, crucial for repairing DNA double-strand breaks and contributing to genomic instability in cancer. The HRD score may be a more reliable biomarker than HRR-related gene mutations for identifying patients sensitive to poly(ADP-ribose) polymerase inhibitors. Despite its relevance in various cancers, the HRD score remains underexplored in esophageal squamous cell carcinoma (ESCC). We retrospectively analyzed HRD scores in 96 ESCC patients, examining correlations with clinical characteristics and survival outcomes, and validated our findings using the TCGA dataset. Genomic sequencing utilized a custom superHRD next-generation sequencing panel, and HRD scores were calculated from 54,000 single-nucleotide polymorphisms using Kruskal-Wallis rank-sum tests and two cut-off points for analysis. Higher HRD scores correlated with advanced tumor stages, recurrence, and mutations in TP53 and ABCB1, while APC mutations were linked to lower HRD scores. Patients with high HRD scores had significantly shorter disease-free survival (p = 0.013) and a trend toward shorter overall survival (OS) (p = 0.005), particularly those not receiving adjuvant therapy. Conversely, HRD-high patients undergoing adjuvant therapy showed a trend toward longer OS (p = 0.015). Multivariate analysis identified HRD as an independent prognostic factor (hazard ratio = 2.814 for recurrence, p = 0.015). Validation with the TCGA dataset supported these findings. This study highlights the associations between HRD scores, clinical characteristics, and genomic mutations in ESCC, suggesting HRD as a potential prognostic biomarker. HRD assessment may aid in patient stratification and personalized treatment strategies, warranting further investigation to validate the therapeutic implications of HRD scores in ESCC.

Comprehensive Analysis and Experimental Validation of HEPACAM2 as a Potential Prognosis Biomarker and Immunotherapy Target in Colorectal Cancer.

The role of HEPACAM family member 2 (HEPACAM2) is unclear in colorectal cancer (CRC). The objective of this study was to perform an extensive examination of HEPACAM2 and validate it experimentally in CRC. This study investigated the significance of HEPACAM2 in CRC and its potential diagnostic utility utilizing data from the Cancer Genome Atlas (TCGA) database. Additionally, the study examined potential regulatory networks involving HEPACAM2, including its associations with immune infiltration, immune checkpoint genes, tumor mutational burden (TMB), microsatellite instability (MSI), mRNA expression-based stemness index (mRNAsi), and drug sensitivity in CRC. The expression of HEPACAM2 was further validated using the GSE89076 dataset, and quantitative reverse transcription PCR (qRT-PCR) was employed to confirm HEPACAM2 expression levels in six pairs of CRC tissue samples. HEPACAM2 exhibited abnormal expression patterns in various types of cancer, including CRC. A decrease in HEPACAM2 expression levels in CRC was found to be significantly correlated with the T stage (p < 0.001). Reduced HEPACAM2 expression in CRC patients was also linked to poorer overall survival (OS) (p = 0.007). The expression levels of HEPACAM2 in CRC patients were identified as an independent prognostic factor (p = 0.016). Furthermore, HEPACAM2 was associated with TCF-dependent signaling in response to WNT, G2/M checkpoints, and other pathways. The expression of HEPACAM2 in CRC was found to be associated with immune infiltration, immune checkpoint genes, TMB / MSI, and mRNAsi. Additionally, the expression of HEPACAM2 in CRC was significantly and inversely correlated with the drug sensitivities to gw772405x and 6-phenyl-6h-indeno[1,2-c]isoquinoline-5,11-dione. qRT-PCR confirmed that the expression level of HEPACAM2 was found to be lowly expressed in CRC tissues. These findings suggest that HEPACAM2 may serve as a potential prognostic biomarker and immunotherapeutic target for CRC patients.

HOXA7 Expression Is an Independent Prognostic Biomarker in Esophageal Squamous Cell Carcinoma

Background/Objectives: Homeobox (HOX) genes encode conserved transcription factors essential for tissue and organ development and cellular differentiation. In humans, these genes are organized into four clusters: HOXA, HOXB, HOXC, and HOXD. While HOX genes have been extensively studied in cancer biology, their roles in esophageal squamous cell carcinoma (ESCC) remain poorly understood. Given the increasing incidence and high mortality rate of ESCC, exploring the molecular drivers of this tumor is urgent. Methods: Therefore, this study investigated the mutational landscape and expression profiles of HOX genes in ESCC and their differentially expressed targets using ESCC data from The Cancer Genome Atlas (TCGA) and two independent transcriptome datasets. Results: We found that copy number alterations and single nucleotide variations were rare, while seven HOX genes (HOXA2, HOXA7, HOXB13, HOXC9, HOXC10, HOXC13, and HOXD10) were significantly differentially expressed in ESCC compared to paired non-malignant mucosa. Further analysis identified 776 potential HOX target genes differentially expressed in ESCC, many of which are involved in critical cancer pathways such as PI3K-AKT, cell cycle regulation, and epithelial–mesenchymal transition (EMT). The HOXA7 overexpression was associated with poor overall survival rates in ESCC. This finding opens new possibilities for targeted therapies, offering hope for improved patient outcomes. Conclusions: Thus, this study underscored the pivotal role of HOX gene dysregulation in ESCC and classified HOXA7 as a potential prognostic biomarker in this tumor.

CSF Parvalbumin Levels at Multiple Sclerosis Diagnosis Predict Future Worse Cognition, Physical Disability, Fatigue, and Gray Matter Damage.

Cognitive impairment (CI) in multiple sclerosis (MS) is frequent and determined by a complex interplay between inflammatory and neurodegenerative processes. We aimed to investigate whether CSF parvalbumin (PVALB), measured at the time of diagnosis, may have a prognostic role in patients with MS. In this cohort study, CSF analysis of PVALB and Nf-L levels was performed on all patients at diagnosis (T0) and combined with physical, cognitive, and MRI assessment after an average of 4 years of follow-up (T4) from diagnosis. Cognitive performance was evaluated with a comprehensive neuropsychologic battery: both global (cognitively normal, CN, mildly CI, mCI, and severely CI, sCI) and domain cognitive status (normal/impaired in memory, attention/information processing speed, and executive functions) were considered. Cortical thickness and gray matter volume data were acquired using 3T MRI scanner. A total of 72 patients with MS were included. At diagnosis, PVALB levels were higher in those patients who showed a worsening physical disability after 4 years of follow-up (p = 0.011). CSF PVALB levels were higher in sCI patients than in CN (p = 0.033). Moreover, higher PVALB levels significantly correlated with worse global cognitive (p = 0.024) and memory functioning (p = 0.044). A preliminary clinical threshold for PVALB levels at diagnosis was proposed (2.57 ng/mL), which maximizes the risk of showing CI (in particular, sCI) at follow-up, with a sensitivity of 91% (specificity 30%). No significant results were found for these associations with Nf-L. In addition, patients with higher levels of PVALB at diagnosis showed higher cognitive (p = 0.024) and global fatigue (p = 0.043) at follow-up. Finally, higher PVALB levels also correlated significantly with more pronounced CTh/volume at T4 in the inferior frontal gyrus (p = 0.044), postcentral gyrus (p = 0.025), frontal pole (p = 0.042), transverse temporal gyrus (p = 0.008), and cerebellar cortex (p = 0.041) and higher atrophy (change T0-T4) in the right thalamus (p = 0.038), pericalcarine cortex (p = 0.009), lingual gyrus (p = 0.045), and medial frontal gyrus (p = 0.028). The significant association found between parvalbumin levels in the CSF at diagnosis and cognitive, clinical, and neuroradiologic worsening after 4 years of follow-up support the idea that parvalbumin, in addition to Nf-L, might represent a new potential prognostic biomarker, reflecting MS neurodegenerative processes occurring since early disease stages.

Combined Bone Mineral Density (BMD) and Monocyte-to-Lymphocyte Ratio (MLR) Predicts Recurrence and Prognosis in Hepatocellular Carcinoma Patients Following Liver Resection.

Bone mineral density (BMD) and monocyte-to-lymphocyte ratio (MLR) were recently identified as novel risk factors for patients with several malignancies. The objective of this study was to validate the role of preoperative BMD/MLR as a potential prognostic biomarker in patients with hepatocellular carcinoma (HCC) undergoing liver resection. This investigation enrolled 442 adult patients diagnosed with HCC who underwent liver resection. The patients were classified into high- and low-BMD/MLR groups based on the median, and forward stepwise logistic regression was employed to identify independent predictors for early HCC recurrence. To mitigate the impact of confounding factors, a propensity score matching (PSM) analysis was conducted between patients in the high- and low-BMD/MLR groups. The Kaplan-Meier method was employed to assess and compare the disease-free survival (DFS) and overall survival (OS) between the two cohorts. The study categorized patients into high-BMD/MLR and low-BMD/MLR groups. Forward stepwise logistic regression analysis revealed that low BMD/MLR (P < 0.001), tumor size > 50 mm (P < 0.001), and AFP > 200 ug/L (P = 0.001) were significantly associated with the early recurrence of HCC. Moreover, the results suggested that DFS and OS were significantly shorter in the low-BMD/MLR group compared to the high-BMD/MLR group, both before and after PSM (P < 0.05). Preoperative BMD/MLR held promise as a prognostic biomarker for early recurrence and prognosis in patients with HCC who underwent liver resection. Furthermore, the integration of tumor size, AFP level, and BMD/MLR demonstrated a robust predictive capacity for early recurrence within this patient population.

LOXL1 promotes gastric cancer progression by β-catenin-cyclinD mediated proliferation.

Although much progress has been made in chemotherapy or target therapy for advanced gastric cancer, the prognosis is still poor. It is necessary to screen biomarkers for early diagnosis and prognosis prediction. However, the prognostic value of LOX family in gastric cancer and the underlying molecular mechanisms for promoting the progression of gastric cancer remains unclear. Among five members of LOX family, LOXL1 was the unique independent prognostic risk factor. The nomogram established based on the expression of LOXL1 and other clinical parameters could predict the overall survival rate of gastric cancer. Knockdown (KD) of LOXL1 decreased cell proliferation and led to G1 phase arrest in gastric cells. According to GSEA analysis that LOXL1 was positively correlated with the WNT signaling pathway, in vitro experiment proved that LOXL1-KD reduced the phosphorylation level of β-catenin and the expression of the downstream G1 phase checkpoint CCND1.In Conclusion, LOXL1 has been identified as a potential risk prognostic biomarker for gastric cancer by promoting gastric cancer proliferation via WNT/β-catenin/cyclinD1 pathway.

Plasma COL10A1 Level, a Potential Diagnostic and Prognostic Biomarker for Pancreatic Ductal Adenocarcinoma.

COL10A1 expression was up-regulated and could promote tumor development in pancreatic cancer. As a secreted protein, plasma COL10A1 level was proven to have certain diagnostic efficacy in gastric cancer, breast cancer, and colorectal cancer. It is still unknown whether it has a biomarker role for pancreatic cancer. To explore and analyze the diagnostic and prognostic value of plasma COL10A1 level in pancreatic ductal adenocarcinoma (PDAC). The RNA-seq dataset of PDAC from The Cancer Genome Atlas (TCGA) and six expression profiling microarray datasets from Gene Expression Omnibus (GEO) were downloaded to analyze the expression of COL10A1 in tissues. Thirty-six patients with PDAC and eighteen healthy volunteers were enrolled to measure COL10A1 levels in tissues and plasmas, and the relationship between clinical characteristics and the COL10A1 levels was analyzed. The diagnostic and prognostic efficacy of plasma COL10A1 levels were calculated. Aspects of COL10A1 expression level in tissues, COL10A1 expression was significantly higher in PDAC tissue than adjacent normal tissue. The expression of COL10A1 was correlated with T, M, and AJCC stages. Patients with high COL10A1 expression had worse recurrence-free survival (RFS) and overall survival (OS) than those with low expression. Aspects of COL10A1 expression levels in plasma, its diagnostic area under the curve (AUC) for PDAC was 0.926 (95% CI 0.853-0.999), diagnostic sensitivity was 81% (95% CI 64-92%), and specificity was 100% (95% CI 81-100%). The time-dependent AUCs at 1-year and 3-year were 0.71 (95% CI 0.51-0.90) and 0.74 (95% CI 0.48-1.00), respectively. In PDAC, plasma COL10A1 levels showed certain diagnostic and prognostic efficacy. COL10A1 may be a diagnostic and prognostic biomarker for PDAC and play a role in liquid biopsy of this disease.

Comprehensive gene set enrichment and variation analyses identify SUV39H1 as a potential prognostic biomarker for glioblastoma immunorelevance

Glioblastoma (GBM) is the most common intracranial malignancy. SUV39H1 encodes a histone H3 lysine 9 methyltransferase that acts as an oncogene in several cancers; however, its role in GBM remains unknown. We obtained GBM transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database on the UCSC Xena platform to perform differential and enrichment analyses of genes in the SUV39H1 high- and low-expression groups to construct a prognostic risk model. Analysis of SUV39H1 related biological processes in GBM was performed by gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). High- and low-risk subgroup mutation signatures were analyzed using maftools. Immune infiltration was evaluated using IOBR and CIBERSORT algorithms. We analyzed the cell types and intercellular communication networks in glioma stem cells (GSCs) using scRNA-seq. The effects on GBM cells and GSCs after inhibition of SUV39H1 were investigated in vitro. SUV39H1 was significantly overexpressed in GBM and associated with poor prognosis. SUV39H1-related differentially expressed genes were enriched in immune and inflammation related pathways, and GSEA revealed that these genes were significantly enriched in signaling pathways such as IL-18, oxidative phosphorylation, and regulation of TP53 activity. Mutational analysis revealed frequent alterations in TP53 and PTEN expression. In addition, the infiltration abundances of the five immune cell types were significantly different between the high- and low-expression groups. Analysis of cellular communication networks by scRNA-seq revealed a strong interaction between CRYAB-GSC and PTPRZ1-GSC in GSCs. In vitro experiments verified that knockdown of SUV39H1 inhibited the viability and proliferation of U87 and U251 glioblastoma cells and downregulated the expression of stemness markers Nestin and SOX2 in CSC1589 and TS576 GSC lines. Increased SUV39H1 expression is associated with immune cell infiltration and poor prognosis in patients with GBM. Inhibition of SUV39H1 restrains GBM growth and reduces the stem cell properties of GSC. Thus, SUV39H1 might be a prognostic predictor and immunotherapeutic target in patients with GBM.

FABP7: A Potential Diagnostic and Prognostic Biomarker for Clear Cell Renal Cell Carcinoma.

Renal cell carcinoma (RCC) is highly heterogeneous, with distinct patient management between clear cell RCC (ccRCC) and non-ccRCC groups. Previous bioinformatics and machine learning techniques identified fatty acid binding protein 7 (FABP7) as a potential ccRCC biomarker. However, FABP7 expression studies between ccRCC and non-ccRCC were incomplete. This study aimed to assess FABP7 as a biomarker for distinguishing between ccRCC and non-ccRCC tissue samples. FABP7 expression was evaluated via immunohistochemical staining in 58 RCC cases, including 43 ccRCC and 15 non-ccRCC cases. Staining results were interpreted using H-scores; scores above the cut-off were deemed positive. The correlation between FABP7 expression and clinicopathological RCC features was investigated. FABP7 positivity was 48.8% in ccRCC and only 13.3% in non-ccRCC cases, with weak positivity in non-ccRCC tissues. FABP7 expression significantly differed between ccRCC and non-ccRCC (p<0.05). This finding was confirmed in a TCGA dataset. However, FABP7 expression was not correlated with other RCC clinicopathological features in our dataset. TCGA results linked FABP7 expression to tumor stage and disease-free survival in patients with ccRCC. This study preliminarily evaluated FABP7 as a differential diagnostic biomarker in RCC subtyping, showing higher expression in ccRCC than non-ccRCC. FABP7 may serve as a potential diagnostic and prognostic biomarker for ccRCC.

MicroRNA-Targeted Gene Regulation in Salivary Gland Tissue of De Novo Parkinson's Disease Patients.

Although α-synucleinopathy has been confirmed in the submandibular gland (SMG) tissue of Parkinson's disease (PD) patients, in-depth disease-related molecular research, such as tissue-specific transcriptional signals, has not been performed. In the present study, disease-relevant tissue-specific transcriptional signals in SMG tissue from PD patients were investigated to identify potential diagnostic, prognostic, and pathophysiologic biomarkers. Here, seven de novo drug-naïve PD patients and six age- and sex-matched individuals without neurological or psychological diseases were enrolled. Total RNA sequencing (RNA-seq) and total small RNA-seq (smRNA-seq) were performed on SMG tissue and blood samples, with 26 RNA-seq and 26 smRNA-seq samples used for the final analysis. Differentially expressed genes (DEGs) and microRNAs in SMG tissue and blood from PD patients were obtained and their functional integration and interaction network were analyzed. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the DEGs interacted with cytokine-, inflammation-, and immune-related pathways. Synphilin-1 expression was significantly downregulated in SMG tissue of PD patients, and α-synuclein expression did not significantly differ between PD patients and controls in either SMG tissue or blood. Fifteen tissue-specific miRNA signals in SMG tissue were identified that showed better diagnostic ability compared with those in blood samples. The correlation between DEGs and environmental factors appeared altered in PD patients. The results indicated the DEGs and microRNA signatures identified in SMG tissue may be promising diagnostic and prognostic biomarkers. These molecular insights offer potential avenues for the development of novel therapeutic strategies targeting the underlying disease mechanisms in PD patients.