Adjacent Normal Tissue Samples Research Articles

Expression of nuclear receptor co‑activator 7 protein is associated with poor prognosis of breast cancer.

Nuclear receptor coactivator 7 (NCOA7) is an estrogen receptor binding protein. Its role in breast cancer progression has so far remained elusive. The present study aimed to determine the expression levels of NCOA7 in breast tumor samples and confirmed its potential utility as a breast cancer prognostic biomarker. The expression of NCOA7 was detected by immunohistochemical staining in 241 breast cancer tumor samples and 163 adjacent normal tissue samples. The association of NCOA7 expression with the clinicopathological characteristics and overall survival were statistically analyzed. Cell proliferation was determined by Cell Counting Kit-8 and colony-formation assays. Cell migration was detected using wound-healing and Transwell assays. NCOA7 was positively expressed in 44% of breast tumor tissues. The expression of NCOA7 was positively associated with tumor size (T-stage; P=0.005) and lymph node metastasis (N-stage; P=0.008). Additional statistical analysis indicated that the expression of NCOA7 was associated with patient age, tumor size and lymph node metastasis in patients with triple-negative breast cancer (TNBC) compared with that in patients with non-TNBC. The overall survival of patients with NCOA7-positive breast cancer was significantly lower than that of patients with NCOA7-negative breast cancer (P=0.006). Among the patients with lymph node metastasis, the overall survival was reversely associated with the expression of NCOA7 (P=0.042). Furthermore, knockdown of NCOA7 expression in breast cancer T47D and MCF7 cells significantly inhibited both cell proliferation and migration, suggesting that this protein may exert a role in driving breast cancer progression. Taken together, these results indicate that the expression of NCOA7 is associated with poor prognosis of breast cancer and suggest that this protein may be a driver for metastasis and a potential therapeutic target for advanced breast cancer.

Functional analysis of ESM1 by shRNA-mediated knockdown of its expression in papillary thyroid cancer cells.

Endothelial specific molecule-1 (ESM1) is implicated as an oncogene in multiple human cancers. However, the function of ESM1 in papillary thyroid cancer (PTC) is not well understood. The current study aimed to investigate the effect of ESM1 on the growth, migration, and invasion of PTC to provide a novel perspective for PTC treatment. The expression levels of ESM1 in PTC tissues form 53 tumor tissue samples and 59 matching adjacent normal tissue samples were detected by immunohistochemical analysis. Knockdown of ESM1 expression in TPC-1 and SW579 cell lines was established to investigate its role in PTC. Moreover, cell proliferation, apoptosis, wound healing, and transwell assays were conducted in vitro to assess cell proliferation, migration and invasion. The findings revealed that ESM1 expression was significantly higher in PTC tissues than that found in paraneoplastic tissues (P<0.0001). Knockdown of ESM1 expression inhibited the proliferation, migration, and invasion of TPC-1 and SW579 cells in vitro. Compared with the control group, the mRNA and protein levels of ESM1 in PTC cells were significantly reduced following knockdown of its expression (P<0.01). In addition, ESM1-knockdown cells indicated decreased proliferation and decreased migratory and invasive activities (P<0.01, P<0.01, P<0.001, respectively). ESM1 was identified as a major gene in the occurrence and progression of PTC, which could increase the proliferation, migration, and invasion of PTC cells. It may be a promising diagnostic and therapeutic target gene.

ScRNA-seq characterizing the heterogeneity of fibroblasts in breast cancer reveals a novel subtype SFRP4+ CAF that inhibits migration and predicts prognosis.

Cancer-associated fibroblasts (CAFs) are a diverse group of cells that significantly impact the tumor microenvironment and therapeutic responses in breast cancer (BC). Despite their importance, the comprehensive profile of CAFs in BC remains to be fully elucidated. To address this gap, we utilized single-cell RNA sequencing (scRNA-seq) to delineate the CAF landscape within 14 BC normal-tumor paired samples. We further corroborated our findings by analyzing several public datasets, thereby validating the newly identified CAF subtype. Additionally, we conducted coculture experiments with BC cells to assess the functional implications of this CAF subtype. Our scRNA-seq analysis unveiled eight distinct CAF subtypes across five tumor and six adjacent normal tissue samples. Notably, we discovered a novel subtype, designated as SFRP4+ CAFs, which was predominantly observed in normal tissues. The presence of SFRP4+ CAFs was substantiated by two independent scRNA-seq datasets and a spatial transcriptomics dataset. Functionally, SFRP4+ CAFs were found to impede BC cell migration and the epithelial-mesenchymal transition (EMT) process by secreting SFRP4, thereby modulating the WNT signaling pathway. Furthermore, we established that elevated expression levels of SFRP4+ CAF markers correlate with improved survival outcomes in BC patients, yet paradoxically, they predict a diminished response to neoadjuvant chemotherapy in cases of triple-negative breast cancer. This investigation sheds light on the heterogeneity of CAFs in BC and introduces a novel SFRP4+ CAF subtype that hinders BC cell migration. This discovery holds promise as a potential biomarker for refined prognostic assessment and therapeutic intervention in BC.

Abstract 1694: Using high-throughput screening to identify DNA response elements that sense cancer dysregulated pathways

Abstract Earli is developing a highly sensitive, orthogonal approach that is designed to be delivered via IV injection and uses a genetic construct to usurp dysregulated pathways, and actively forces cancer cells to drive the expression of a detectable ‘synthetic’ biomarker. The key element of our cancer-activated construct that drives specificity and sensitivity of expression is a promoter sequence, synthetically engineered to leverage transcription factors (TFs) activated in cancer pathways. Acting as a molecular sensor for dysregulated TF levels, the DNA construct expresses a measurable biomarker in cancer cells, while remaining transcriptionally silent in normal adjacent tissues and benign lesions. Previously, we described a multiomics factor analysis (MOFA) to interrogate 200 non-small cell lung cancer (NSCLC) and matched normal adjacent tissue samples comprised of RNA-seq based transcriptional profiling, and MS-based proteomics and phospho-proteomics from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset, and generated a list of top TFs dysregulated in NSCLC. In this study, we show the capability to design, engineer, and test cancer specific activity of combinations of response elements using a Massively Parallel Reporter Assay (MPRA) high-throughput pooled screening (HTS) method. More than 2,000 unique sequences of homotypic or heterotypic TF binding sites corresponding to the top 100 TFs were arrayed with diverse spacing and individually barcoded for the high-throughput screens in NSCLC cell lines. To validate our top hits, we individually tested 10 sequences from the top 25% and 8 sequences from the bottom 25%. Nine of the top sequences produced signals 5-10X higher than the background, whereas only one of the eight bottom sequences produced signal higher than the background. We have individually validated 30 different response elements and found that 28 of 30 drove the expected expression, with the majority of response elements (n=20) showing expression 5-10X higher than background. Remarkably, two of the engineered response elements were able to drive expression 20-30X higher in a specific cell line activated by WNT-signaling, suggesting that these response elements can sense specific cancer dysregulated pathways. Our lead response elements are being tested across a broad range of in vitro primary tumor lines with diverse genetic backgrounds and transcriptional profiles prior to in vivo testing using our imaging platform to distinguish malignant lung nodules. In summary, we have established a robust screening platform to identify response elements that can be activated by cancer dysregulated pathways. We are currently expanding this platform to other cancer models and indications, and leveraging this to explore more complex response elements that use combinations of TFs and natural spacing. Citation Format: Elizabeth Stroebele, Yue (Wendy) Zhang, Ishan Podar, Chloe Xia, Ajda Rojc, Dariusz Wodziak, Maggie Louie, David Suhy. Using high-throughput screening to identify DNA response elements that sense cancer dysregulated pathways [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 1694.

Abstract 2268: CREDAC: Copy number-based reference-free expression deconvolution analysis of cancers

Abstract Introduction: Analyses of bulk RNA sequencing data are central to most large-scale tumor sequencing studies. Bulk expression data represent population averages and its interpretation is confounded by both normal cell contamination and somatic copy number alterations. Several computational methods to deconvolve have been developed recently. However, these methods often rely on a set of cell-type-specific reference signatures and ignore the effect of copy number changes. Methods: To address these issues, we have developed a method that formalizes the relationship between allele-specific copy number, expression and sample purity to deconvolve the expression profiles of tumor and normal cells from bulk RNA-seq in an unbiased manner. Our method was applied to sequencing data produced by the TRACERx consortium, a longitudinal study with multi-region whole-exome and RNA-seq of non-small-cell lung cancers. A total of 414 primary tumor regions and 140 adjacent normal tissue samples from 140 patients with matched DNA and RNA-seq data were processed. Results: We were able to directly deconvolve a median of ~2,000 genes per sample and indirectly infer tumor and normal expression profiles of ~10,000 genes using an scaled and weighted mean approach. The accuracy of the deconvolution was validated using (1) in-silico mixtures of patient-derived tumor and normal cells, (2) pseudo-bulk scRNAseq and (3) in regions with loss of heterogeneity (LOH) directly on the bulk sequencing data, where the total fraction of expression attributed to tumor cells can be computed directly using somatic mutations. CREDAC allows for single sample bulk-level tumor-normal differential expression analysis and revealed a strong and constitutive genome-wide overexpression in cancer compared to admixed normal cells, with a more pronounced overexpression in lung squamous cell carcinoma than lung adenocarcinoma (p&amp;lt;0.001). CREDAC adjusts for variations in copy number, thus facilitating the investigation of cancer-specific dosage compensatory responses triggered by aneuploidy. We revealed that a majority of genes (~65%) exhibit proportionality to copy number alterations, while a substantial proportion (~35%) shows anti-scaling or dosage compensation strategies. We show an enrichment of genes involved in cell cycle and expression processes within the dosage compensated group and revealed methylation as a key mechanism driving this compensatory process. Conclusion: Overall, our results suggest that CREDAC is able to accurately disentangle the expression of tumor and normal cells from bulk RNA-seq without any previous knowledge. It has potential applications in many studies that include matched RNA-seq and copy number data and can provide new insights functional characterization, the taxonomy of cancer, and tumor evolution. Citation Format: Carla Castignani, Jonas Demeulemeester, Oriol Pich, Tom Lesluyes, Robert E. Hynds, David R. Pearce, Elizabeth Larose Cadieux, Stefan C. Dentro, TRACERx Consortium, Nnenna Kanu, Charles Swanton, Peter Van Loo. CREDAC: Copy number-based reference-free expression deconvolution analysis of cancers [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 2268.

O266: Transcriptomic signature from spatially inferred histologically benign ancestral clone predicts high risk prostate cancer

Abstract Introduction Prostate cancer (PCa) is a multifocal disease driven by heterogenous spatial and temporal branching evolution of tumour clones. Spatial transcriptomic analysis has revealed, clonally distributed copy number alterations even in histologically benign regions. We aim to evaluate if the genetic signature comprised within these genetically aberrant histologically benign regions, or “ancestral clones” may predict presence of high-risk disease. Methods Fresh-frozen, radical prostatectomy specimen was profiled using the 10x Genomics Visium Spatial Gene Expression platform. Via hierarchical clustering, spatial tumour clonal relations were inferred. Differentially expressed genes (DEGs) between high-grade tumour and histologically benign ancestral clones were identified. DEGs (|log2FC|&amp;gt;0.75) were input into a LASSO regression algorithm with normalised mRNA expression of normal adjacent tissue from the TCGA PCa database to train a genetic risk model to predict presence of high risk PCa (Gleason&amp;gt;8). Derived risk score was validated on an external cohort (GSE21032). Results A total of 683 DEGs were identified. These were enriched for organic acid metabolic pathways. Regression analysis on 57 normal adjacent tissue samples from TCGA PCa dataset was performed to develop a predictive model comprising of 3 genes (SLC22A3, CRIP2, LSAMP). External validation of the genetic risk score on matched histologically benign tissue from 131 patients, had good performance for prediction of high-risk PCa (AUC 0.807; 95% CI 0.693-0.921). Conclusion Our model has good performance for predicting high-risk PCa from matched normal tissue. Developed genetic risk score has translational potential to improve detection of unsampled clinically significant prostate cancer from histologically benign biopsy cores.

Quantitative Pattern of hPTMs by Mass Spectrometry-Based Proteomics with Implications for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is known for its aggressive nature, and TNBC management is currently challenging due to the lack of effective targets. Despite the importance of histone post-translational modifications (hPTMs) in breast cancer, their associations with molecular subtypes of breast cancer, especially TNBC, are poorly understood. In this study, a combination of untargeted and targeted proteomics approaches, supplemented by a derivatization method, was applied to breast cancer cells and tissue samples. Untargeted proteomics of eight breast cancer cell lines belonging to different molecular subtypes revealed 36 modified peptides with 12 lysine modification sites in histone H3, and the most frequently reported top 5 histone H3 methylation and acetylation sites were covered. Then, targeted proteomics was carried out to quantify the total 20 target hPTMs at the covered modification sites (i.e., mono-, di-, trimethylation, and acetylation for each site), indicating the difficulty in distinguishing TNBC cells from normal cells. Subsequently, the analysis in TNBC patients revealed significant expression differences in 4 specific hPTMs (H3K14ac, H3K27me1, H3K36me2, and H3K36me3) between TNBC and adjacent normal tissue samples. These unique hPTM patterns allowed for the differentiation of TNBC from normal cases. This finding provides promising implications for advancing targeted treatment strategies for TNBC in the future.

Prognostic correlation between specialized capillary endothelial cells and lung adenocarcinoma

BackgroundIn-depth analysis of the functional changes occurring in endothelial cells (ECs) involved in capillary formation can help to elucidate the mechanism of tumour vascular growth. MethodsAppropriate datasets were retrieved from the GEO database to obtain single-cell data on LUAD samples and adjacent normal tissue samples. ECs were selected by an automatic annotation program in R and further subdivided based on reported EC marker genes. Functional changes in different types of capillary ECs were then visualized, and the concrete expression was classified by genetic data in the TCGA. Finally, a prognostic model was constructed to predict immunoinfiltration status, survival and drug therapy effects. ResultsThe LUAD data contained in the GSE183219 dataset were suitable for our analysis. After dimensionality reduction analysis and cell annotation, EC general capillary and EC aerocyte subsets as capillary specialized phenotypes showed a series of functional changes in tumour samples, with a total of 108 genes found to undergo functional changes. Use of CellPhoneDB revealed a close interaction of activity between ECs. After integration of TCGA, GSE68465 and GSE11969 datasets, the genes obtained were analysed by cluster analysis and risk model construction, identifying 8 genes. Drug sensitivity, immune cell and molecular differences can be accurately predicted. ConclusionsEC general capillary and EC aerocyte subsets are recognized capillary ECs in the tumour microenvironment, and the functional changes between them are relevant to the prognosis and treatment of LUAD patients and have the potential to be used in target therapy.

Comprehensive RNA-sequencing analysis of colorectal cancer in a Korean cohort

Considering the recent increase in the number of colorectal cancer (CRC) cases in South Korea, we aimed to clarify the molecular characteristics of CRC unique to the Korean population. To gain insights into the complexities of CRC and promote the exchange of critical data, RNA-sequencing (RNA-Seq) analysis was performed to reveal the molecular mechanisms that drive the development and progression of CRC; this analysis is critical for developing effective treatment strategies. We performed RNA-Seq analysis of CRC and adjacent normal tissue samples from 214 Korean participants (comprising a total of 381 including 169 normal and 212 tumor samples) to investigate differential gene expression between the groups. We identified 19,575 genes expressed in CRC and normal tissues, with 3,830 differentially expressed genes (DEGs) between the groups. Functional annotation analysis revealed that the upregulated DEGs were significantly enriched in pathways related to the cell cycle, DNA replication, and IL-17, whereas the downregulated DEGs were enriched in metabolic pathways. We also analyzed the relationship between clinical information and subtypes using the Consensus Molecular Subtype (CMS) classification. Furthermore, we compared groups clustered within our dataset to CMS groups and performed additional analysis of the methylation data between DEGs and CMS groups to provide comprehensive biological insights from various perspectives. Our study provides valuable insights into the molecular mechanisms underlying CRC in Korean patients and serves as a platform for identifying potential target genes for this disease. The raw data and processed results have been deposited in a public repository for further analysis and exploration. Data availability statementThe RNA-Seq data have been deposited in the Korean Nucleotide Archive under the accession number KAP230608 (https://www.kobic.re.kr/kona/search_bioproject?bioproject_id=KAP230608#none). Clinical data, preprocessed gene quantification (RSEM), normalized gene expression data (log2CPM), and downstream analysis results have been deposited in Zenodo (https://doi.org/10.5281/zenodo.8333650). Further information and requests for experimental resources should be directed to and will be fulfilled by the corresponding authors, Kil-yong Lee (cyboryee@hanmail.net), Jin Ok Yang (joy@kribb.re.kr), and Young-Joon Kim (yjkim@yonsei.ac.kr).

Prognostic significance of RKIP, TGM2, and CMTM4 expression in oral squamous cell carcinoma.

The expression of RKIP, TGM2, and CMTM4 in oral squamous cell carcinoma (OSCC) and normal oral tissues was detected and their correlations were analyzed. The relationships between RKIP, TGM2, and CMTM4 and the clinicopathological parameters and prognosis of patients were analyzed. Seventy cancerous and adjacent normal tissue samples were selected, recorded in the pathology department, and embedded in paraffin. Protein expression was detected by immunohistochemistry. Statistical software (SPSS 25.0, IBM Corporation) was used for the statistical analysis. The chi-squared (χ2) test was used to analyze the expression of RKIP, TGM2, and CMTM4 proteins and their clinicopathological features. Differences in RKIP, TGM2, and CMTM4 protein levels between OSCC and normal tissues were compared using a χ2 test. Survival analysis was performed using the Kaplan-Meier method, and differences between survival curves were determined using the log-rank test. The effects of RKIP, TGM2, and CMTM4 expression on patient prognosis were analyzed using a multivariate Cox proportional hazards regression model. P < .05 was considered statistically significant. The expression level of RKIP correlated with age and clinical stage (P < .05). TGM2 was associated with clinical stage and lymph node metastasis (P < .05). The expression of CMTM4 increased with a decrease in cancer differentiation. Kaplan-Meier survival analysis suggested that the positive expression of TGM2 and CMTM4 may predict poor prognosis in patients with OSCC. The multivariate Cox proportional hazards regression model suggested that TGM2 could be an independent prognostic factor for patients with OSCC. Combined expression of TGM2 and CMTM4 can be used as an indicator to evaluate the risk of metastasis and prognosis of OSCC.

Enhanced NK cell activation via eEF2K-mediated potentiation of the cGAS–STING pathway in hepatocellular carcinoma

BackgroundLiver cancer, particularly hepatocellular carcinoma (HCC), is characterized by a high mortality rate, attributed primarily to the establishment of an immunosuppressive microenvironment. Within this context, we aimed to elucidate the pivotal role of eukaryotic elongation factor 2 kinase (eEF2K) in orchestrating the infiltration and activation of natural killer (NK) cells within the HCC tumor microenvironment. By shedding light on the immunomodulatory mechanisms at play, our findings should clarify HCC pathogenesis and help identify potential therapeutic intervention venues. MethodsWe performed a comprehensive bioinformatics analysis to determine the functions of eEF2K in the context of HCC. We initially used paired tumor and adjacent normal tissue samples from patients with HCC to measure eEF2K expression and its correlation with prognosis. Subsequently, we enrolled a cohort of patients with HCC undergoing immunotherapy to examine the ability of eEF2K to predict treatment efficacy. To delve deeper into the mechanistic aspects, we established an eEF2K-knockout cell line using CRISPR/Cas9 gene editing. This step was crucial for verifying activation of the cGAS–STING pathway and the subsequent secretion of cytokines. To further elucidate the role of eEF2K in NK cell function, we applied siRNA-based techniques to effectively suppress eEF2K expression in vitro. For in vivo validation, we developed a tumor-bearing mouse model that enabled us to compare the infiltration and activation of NK cells within the tumor microenvironment following various treatment strategies. ResultsWe detected elevated eEF2K expression within HCC tissues, and this was correlated with an unfavorable prognosis (30.84 vs. 20.99 months, P = 0.033). In addition, co-culturing eEF2K-knockout HepG2 cells with dendritic cells led to activation of the cGAS–STING pathway and a subsequent increase in the secretion of IL-2 and CXCL9. Moreover, inhibiting eEF2K resulted in notable NK cell proliferation along with apoptosis reduction. Remarkably, after combining NH125 and PD-1 treatments, we found a significant increase in NK cell infiltration within HCC tumors in our murine model. Our flow cytometry analysis revealed reduced NKG2A expression and elevated NKG2D expression and secretion of granzyme B, TNF-α, and IFN-γ in NK cells. Immunohistochemical examination confirmed no evidence of damage to vital organs in the mice treated with the combination therapy. Additionally, we noted higher levels of glutathione peroxidase and lipid peroxidation in the peripheral blood serum of the treated mice. ConclusionTargeted eEF2K blockade may result in cGAS–STING pathway activation, leading to enhanced infiltration and activity of NK cells within HCC tumors. The synergistic effect achieved by combining an eEF2K inhibitor with PD-1 antibody therapy represents a novel and promising approach for the treatment of HCC.

The diagnostic potential of miR-196a-1 in colorectal cancer

BackgroundColorectal cancer (CRC) is a common malignancy worldwide. MicroRNAs (miRNAs) are important epigenetic alterations that notably impact various physiological and pathological processes by acting as negative regulators of gene expression. Furthermore, they have a vital function in different types of cancers, including CRC. In this research, we evaluated, for the very first time, the expression levels of miR-196a-1 in the tissue and plasma of patients with CRC and also homeobox D8 (HOXD8) as the target gene.Materials and methodsThis study included a collection of 220 plasma and tissue samples from 55 patients diagnosed with CRC, as well as 55 healthy individuals matched by age and sex. Total RNA was extracted from plasma and tissue samples, and then polyadenylation and cDNA synthesis were performed. The expression levels of miR-196a-1 and HOXD8 as target gene was evaluated by quantitative RT-PCR (qRT-PCR) assay. We compared the diagnostic value of plasma miR-196a-1 with that of the circulating tumor markers CA19-9 and CEA using a Receiver Operating Characteristics (ROC) analysis. The association of miR-196a-1 with clinicopathological characteristics was assessed in tissue and plasma samples from patients with CRC.ResultsOur data demonstrated that the expression levels of miR-196a-1 in the tissue and plasma samples of CRC patients were 11.426- and 11.655-fold higher, respectively than those in adjacent normal tissue and plasma samples from normal subjects (p < 0.001). Through ROC curve analysis, it was identified that the sensitivity and specificity of miR-196a-1 for tissue samples, with an AUC of 0.925, were 89% and 98%, respectively. In addition, the sensitivity and specificity for plasma samples with an AUC of 0.801 were 70% and 98%, respectively. These findings reveal that miR-196a-1 is a useful biomarker for discriminating cases from controls. Furthermore, the expression of HOXD8 was not significantly altered in tumor tissue samples compared to adjacent normal tissues (P > 0.05).ConclusionsThese results show that miR-196a-1 has an oncogenic impact and plays a significant role in CRC development. The results also indicate that miR-196a-1 could serve as a novel noninvasive biomarker for the detection of CRC.

Bioinformatic analysis reveals an association between Metadherin with breast cancer prognosis and tumor immune infiltration

Breast cancer metastasis and invasion are both promoted by the oncoprotein Metadherin (MTDH). However, the the role of Metadherin in breast cancer progression and its role in the immune microenvironment. Are not clear. A bioinformatic analysis was performed to demonstrate the prognostic value of Metadherin in BC. In the present study, we found that Metadherin is overexpressed in BC and is significantly correlated with individual cancer stage, age, subclasses, menopause and nodal metastasis status. Metadherin overexpression was associated with a significant decrease in OS and DSS. Cox multivariate analysis indicated that Metadherin was an independent negative prognostic indicator for OS and DSS. Moreover, Metadherin hypomethylation status was associated with poor prognosis. A negative correlation was also noted between Metadherin overexpression and the number of plasmacytoid dendritic cells, cluster of differentiation 8+ T cells, and natural killer cells. Association patterns varied with different subtypes. Various associations between Metadherin levels and immune cell surface markers were revealed. A total of 40 groups of BC and adjacent normal breast tissue samples were collected. Metadherin mRNA was detected by PCR, and its expression levels in BC tissues were significantly increased compared with those noted in normal tissues. The expression levels of Metadherin were also measured in normal and BC cell lines, respectively, and similar conclusions were obtained. The Metadherin mRNA levels were knocked down in SK-BR3 and MDA-MB-231 cell lines and the cell proliferative and migratory activities were determined using Cell Counting Kit-8 and scratch assays, respectively. The results indicated that the cell proliferative and migratory abilities were reduced following knockdown of Metadherin expression. Therefore, Metadherin may be considered as a novel prognostic biomarker in BC.

Comprehensive Analysis of the Immunosuppressive Function of Regulatory T Cells in Human Hepatocellular Carcinoma Tissues.

Immune-based therapies are commonly employed to combat hepatocellular carcinoma (HCC). However, the presence of immune-regulating elements, especially regulatory T cells (Tregs), can dramatically impact the treatment efficacy. A deeper examination of the immune-regulation mechanisms linked to these inhibitory factors and their impact on HCC patient outcomes is warranted. We employed multicolor fluorescence immunohistochemistry (mIHC) to stain Foxp3, cytokeratin, and nuclei on an HCC tissue microarray (TMA). Leveraging liver cancer transcriptome data from TCGA, we built a prognostic model focused on Treg-associated gene sets and represented it with a nomogram. We then sourced liver cancer single-cell RNA sequencing data (GSE140228) from the GEO database, selectively focusing on Treg subsets, and conducted further analyses, including cell-to-cell communication and pseudo-time trajectory examination. Our mIHC results revealed a more substantial presence of Foxp3+Tregs in HCC samples than in adjacent normal tissue samples (P < .001). An increased presence of Foxp3+Tregs in HCC samples correlated with unfavorable patient outcomes (HR = 1.722, 95% CI:1.023-2.899, P = .041). The multi-factorial prognosis model we built from TCGA liver cancer data highlighted Tregs as a standalone risk determinant for predicting outcomes (HR = 3.84, 95% CI:2.52-5.83, P < .001). Re-analyzing the scRNA-seq dataset (GSE140228) showcased distinctive gene expression patterns in Tregs from varying tissues. Interactions between Tregs and other CD4+T cell types were predominantly governed by the CXCL13/CXCR3 signaling pathway. Communication pathways between Tregs and macrophages primarily involved MIF-CD74/CXCR4, LGALS9/CD45, and PTPRC/MRC1. Additionally, macrophages could influence Tregs via HLA-class II and CD4 interactions. An elevated presence of Tregs in HCC samples correlated with negative patient outcomes. Elucidating the interplay between Tregs and other immune cells in HCC could provide insights into the modulatory role of Tregs within HCC tissues.

The mutation and low expression of ARID1A are predictive of a poor prognosis and high immune infiltration in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) has the poorest prognosis among all breast cancer subtypes. While several tumor types are excepted to have a curative response to immunotherapy through the AT-rich interaction domain 1A (ARID1A) gene, its role in TNBC remains unclear. The expression of the ARID1A gene and immune infiltration in TNBC were analyzed by way and function enrichment analysis. Additionally, 27 gene mutations, including ARID1A mutation, were detected in paraffin-embedded TNBC specimens and normal breast specimens using Next Generation Sequencing (NGS). Immunohistochemical staining was employed to detect the expression of AIRD1A, TP53, Ki67, CD4, CD8, and PD-L1 proteins in TNBC and the adjacent normal tissue samples. The bioinformatics analysis revealed that ARID1A was mutated in TNBC and significantly associated with tumor immune infiltration. NGS analysis showed a high mutation rate of ARID1A (35%) in TNBC, but the mutation status of ARID1A was not associated with age at onset, lymph node metastasis, pathological grade, or Ki67 index. Low expression or loss of AIRD1A was more commonly observed in TNBC tissues (36/108) as compared to normal tissues (3/25). Positive expression of CD8 and PD-L1 was observed in TNBC tissues with low ARID1A expression. ARID1A mutation was associated with low protein expression, and patients with ARID1A mutation or low protein expression had shorter progression-free survival. The ARID1A mutation and low expression are associated with poor prognosis and high immune infiltration in TNBC, and might be biomarkers for TNBC prognosis and immunotherapy efficacy.

Systematic Analysis to Identify the MIR99AHG-has-miR-21-5p-EHD1 CeRNA Regulatory Network as Potential Biomarkers in Lung Cancer.

Lung cancer (LC) remains an extremely lethal disease worldwide, and effective prognostic biomarkers are at top priority. With the rapid development of high-throughput sequencing and bioinformatic analysis methods, the quest to characterize cancer transcriptomes continues to move forward. However, the integrated systematic analysis of lncRNA-miRNA-mRNA regulatory network in LC is lacking. In this study, we collected samples of cancer tissues and adjacent normal tissues from patients with lung cancer and conducted transcriptome and small RNA sequencing to identify differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs). The regulatory roles of miRNAs in LC were explained by functional analysis on DEM-targeted genes. The lncRNA-miRNA pairs, miRNA-mRNA pairs, and lncRNA-mRNA pairs were identified and combined to construct the interplay of lncRNA-miRNA-mRNA. We evaluated the prognostic value of selected lncRNA-miRNA-mRNA by Kaplan-Meier analysis. Finally, we analyzed the expression levels of selected DEM, DELs, and DEGs in lung cancer patients and healthy people to verify our findings. A total of 1492 DEGs, 12 DEMs, and 604 DELs were identified in LC patients. Based on the bioinformatic analysis and the regulatory mechanism of ceRNAs, 3 lncRNAs (GATA2-AS1, LINC00632, MIR99AHG), 1 miRNA (hsa-miR-21-5p) and 5 targeted genes (RECK, TIMP3, EHD1, RASGRP1 and ERG) were figured out first. Through further Kaplan-Meier analysis screening the prognostic value, we finally found the hub subnetwork (MIR99AHG-hsa-miR-21-5p-EHD1) by collating lncRNA-miRNA pairs, miRNA-mRNA pairs and lncRNA-mRNA pairs. As the key of ceRNA regulatory network, the expression of miRNA-21-5p in lung cancer patients was significantly higher than that in healthy people (P < 0.01), and its high expression was significantly associated with poor prognosis (P = 0.0025). Our study successfully constructed a MIR99AHG-hsa-miR-21-5p-EHD1 mutually regulatory network, suggesting the potential efficient biomarkers in LC.

Investigating the Spatial Distribution of Proliferating Cells in Primary Ovarian Cancers.

Ovarian cancer (OC) accounts for about 4% of female cancers globally. While Ki67-immunopositive (Ki67+) cell density is commonly used to assess proliferation in OC, the two-dimensional (2D) distribution pattern of these cells is poorly understood. This study explores the 2D distribution pattern of Ki67+ cells in primary OC tissues and models the proliferation process to improve our understanding of this hallmark of cancer. A total of 100 tissue cores, included in a tissue microarray (TMA) representing 5 clear cell carcinomas, 62 serous carcinomas, 10 mucinous adenocarcinomas, 3 endometrioid adenocarcinomas, 10 lymph node metastases from OC, and 10 samples of adjacent normal ovary tissue, were stained using a standardized immunohistochemical protocol. The computer-aided image analysis system assessed the 2D distribution pattern of Ki67+ proliferating cells, providing the cell number and density, patterns of randomness, and cell-to-cell closeness. Three computer models were created to simulate behavior and responses, aiming to gain insights into the variations in the proliferation process. Significant differences in Ki67+ cell density were found between low- and high-grade serous carcinoma/mucinous adenocarcinomas (p = 0.003 and p = 0.01, respectively). The Nearest Neighbor Index of Ki67+ cells differed significantly between high-grade serous carcinomas and endometrioid adenocarcinomas (p = 0.01), indicating distinct 2D Ki67+ distribution patterns. Proxemics analysis revealed significant differences in Ki67+ cell-to-cell closeness between low- and high-grade serous carcinomas (p = 0.002). Computer models showed varied effects on the overall organization of Ki67+ cells and the ability to preserve the original 2D distribution pattern when altering the location and/or density of Ki67+ cells. Cell proliferation is a hallmark of OCs. This study provides new evidence that investigating the Ki67+ cell density and 2D distribution pattern can assist in understanding the proliferation status of OCs. Moreover, our computer models suggest that changes in Ki67+ cell density and their location are critical for maintaining the 2D distribution pattern.

ZNF471 Interacts with BANP to Reduce Tumour Malignancy by Inactivating PI3K/AKT/mTOR Signalling but is Frequently Silenced by Aberrant Promoter Methylation in Renal Cell Carcinoma.

Background: Renal cell carcinoma (RCC) is one of the most common malignant tumours of the urinary system. However, the aetiology and pathogenesis of RCC remain unclear. The C2H2 zinc finger protein (ZNF) family is the largest transcriptional regulatory factor family found in mammals, and Krüppel-associated box domain-containing zinc finger proteins (KRAB-ZFPs) constitute the largest subfamily of the C2H2 zinc finger protein family and play an important role in the occurrence and development of tumours. The aim of this study was to explore the role of abnormal methylation of ZNF471 in the development of renal carcinoma. Methods: In this study, we first used the TCGA and EWAS Data Hub databases to analyse the expression and methylation levels of ZNF471 in renal carcinoma tissues and adjacent normal tissues. Second, we collected samples of renal cancer and adjacent normal tissues at Peking University First Hospital to investigate the expression and methylation level of ZNF471 in renal cancer tissues and the relationships between these levels and the clinicopathological features and prognosis of patients with renal cancer. Next, we investigated the effects of ZNF471 on the proliferation, metastasis, cell cycle progression, and apoptosis of renal cell carcinoma cells by cell biology experiments. Finally, we elucidated the underlying molecular mechanisms of ZNF471 in renal cell carcinoma by transcriptome sequencing, bioinformatics analysis and molecular biology experiments. Results: The expression of ZNF471 in renal carcinoma tissues and cell lines was significantly lower than that in adjacent normal tissues and cell lines due to abnormal promoter CpG methylation. Furthermore, the expression of ZNF471 in renal carcinoma tissues was negatively correlated with tumour stage and grade in patients with renal carcinoma. The results of the cell biology experiments showed that ZNF471 could significantly inhibit the proliferation, migration and cell cycle progression of renal cell carcinoma cells and promote apoptosis in these cells. In addition, ZNF471 could interact with BANP and suppress the malignant phenotype of RCC by inactivating the PI3K/AKT/mTOR signalling pathway. Conclusions: As an important tumour suppressor, ZNF471 can interact with BANP in renal cancer cells and inhibit the activation of the PI3K/AKT/mTOR signalling pathway, thereby inhibiting the occurrence and development of renal cancer.

CMTM6: A Critical Prognostic Indicator in Non-Small Cell Lung Cancer.

While CKLF-like MARVEL transmembrane domain containing 6 (CMTM6)'s role in stabilizing PD-L1 and immune evasion within tumors is established, its expression in lung cancer tissue and adjacent macrophages remains uncertain. The study aimed to elucidate this ambiguity by investigating CMTM6's role in non-small cell lung cancer (NSCLC) prognosis. Employing immunohistochemical staining on 141 NSCLC and 110 adjacent normal lung tissue samples, CMTM6 expression was evaluated using the HSCORE system. Interestingly, NSCLC exhibited significantly higher CMTM6 levels (161.04±86.60) compared to normal tissues (71.20±45.10) (p < 0.001), detected not only in cancer cells but also in macrophages, lymphocytes, and nearby bronchial epithelial cells. Stratifying patients by CMTM6 levels unveiled a correlation between heightened expression and poorer overall survival (p = 0.003), alongside a link to tumor-infiltrating lymphocytes (TIL) (p = 0.037), especially in cases with increased TIL. Multivariate analysis identified CMTM6 as an independent predictor of overall survival (p = 0.009), implying that elevated CMTM6 expression in NSCLC might signify an adverse prognostic marker for patient outcomes.

MiR-1180 Targets FXYD5 to Regulate Pancreatic Cancer Cells Migration and Invasion.

Pancreatic cancer is a fatal malignancy typically diagnosed in older males and has an aggressive progression. The function of the miR-1180/FXYD5 axis in pancreatic cancer malignant behaviors was investigated. 20 pairs of pancreatic cancer and adjacent normal tissue samples were harvested from pancreatic cancer patients, and qRT-PCR, IHC, and western blot assays were performed, respectively, to detect the mRNA expression and protein levels of miR-1180 or FXYD5. Transwell and scratch assays were conducted to detect the migratory and invasive ability of pancreatic cancer cells; a Dual-luciferase reporter assay was employed to validate miR-1180 targeting FXYD5. miR-1180 targeting FXYD5 to regulate the migratory and invasive ability of pancreatic cancer cells was validated in mouse xenograft tumor models. FXYD5 expression was increased in pancreatic cancer tissue samples than in adjacent normal tissue samples (P < 0.01), and FXYD5 expression exhibited a positive correlation with the migratory and invasive ability of pancreatic cancer cells. miR-1180 targeted FXYD5 and negatively regulated FXYD5. Restoring miR-1180 expression could inhibit the migratory and invasive ability of pancreatic cancer cells (P < 0.01), and this effect could potentially be alleviated by FXYD5 overexpression. The miR-1180/FXYD5 axis positively regulated E-cadherin and negatively regulated MMP2 and MMP9 expression levels. In vivo findings demonstrated that miR-1180 overexpression inhibited tumor growth and lung metastasis (P < 0.05), while FXYD5 overexpression promoted tumor growth and lung metastasis (P < 0.05). In conclusion, the miR-1180 /FXYD5 axis could be involved in pancreatic cancer metastasis through the regulation of EMT and extracellular matrix degradation.