Non-tumor Tissues Research Articles

Fecal Microbiota Strongly Correlates with Tissue Microbiota Composition in Colorectal Cancer but Not in Non-Small Cell Lung Cancer

Microbiota could be of interest in the diagnosis of colorectal and non-small cell lung cancer (CRC and NSCLC). However, how the microbial components of tissues and feces reflect each other remains unknown. In this work, our main objective is to discover the degree of correlation between the composition of the tissue microbiota and that of the feces of patients affected by CRC and NSCLC. Specifically, we investigated tumor and non-tumor tissues from 38 recruited patients with CRC and 19 with NSCLC. DNA from samples was submitted for 16S rDNA metagenomic sequencing, followed by data analysis through the QIIME2 pipeline and further statistical processing with STATA IC16. Tumor and non-tumor tissue selected genera were highly correlated in both CRC and NSCLC (100% and 81.25%). Following this, we established tissue–feces correlations, using selected genera from a LEfSe analysis previously published. In CRC, we found a strong correlation between the taxa detected in feces and those from colorectal tissues. However, our data do not demonstrate this correlation in NSCLC. In conclusion, our findings strongly reinforce the utility of fecal microbiota as a non-invasive biomarker for CRC diagnosis, while highlighting critical distinctions for NSCLC. Furthermore, our data demonstrate that the microbiota components of tumor and non-tumor tissues are similar, with only minor differences being detected.

Implication of tumor morphology and MRI characteristics on the accuracy of automated versus human segmentation of GBM areas

An assessment scheme is proposed to evaluate GBM gross tumor core and T2-FLAIR hyper-intensity segmentations on preoperative multicentric MR images as a function of tumor morphology and MRI characteristics. 74 gross tumor core and T2-FLAIR hyper-intensity BraTS-Toolkit and DeepBraTumIA automatic segmentations, and 42 gross tumor core neurosurgeon manual segmentations were accordingly evaluated. Brats-Toolkit and DeepBraTumIA generally provide accurate segmentations, particularly for the most common round-shaped or well-demarked tumors, where: (1) gross tumor segmentation correctly includes necrosis and contrast enhanced tumor in 100% and 97.06% of cases (vs. 73.68% for manual segmentation) and wrongly includes healthy or non-tumor related tissues in 2.94% and 20.59% of cases (vs. 10.53% for manual segmentations); (2) T2-FLAIR hyper-intensity segmentations completely includes edema in 88.24% of cases for both software. MR image quality has little impact on the segmentation performance on these tumors. Conversely, on less common tumors with more complex tissue distribution and infiltrative behavior, manual segmentation works better than BraTS-Toolkit and DeepBraTumIA, and image quality has a larger impact on automatic segmentation performance. BraTS-Toolkit and DeepBraTumIA gross tumor segmentation properly includes necrosis and contrast enhanced areas in 50% and 37.50% of cases (vs. 66.67% for manual segmentation), all corresponding to higher image quality; T2-FLAIR hyper-intensity segmentation wrongly includes necrosis and contrast enhanced areas in 37.50% and 50% of cases.

Dysregulation of genes involved in the long-chain fatty acid transport in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive lethal malignancy with limited options for treatment and a 5-year survival rate of 11% in the United States. As for other types of tumors, such as colorectal cancer, aberrant de novo lipid synthesis and reprogrammed lipid metabolism have been suggested to be associated with PDAC development and progression. To identify the possible involvement of lipid metabolism in PDAC by analyzing in tumoral and non-tumoral tissues the expression level of the most relevant genes involved in the long-chain fatty acid (FA) import into cell. A gene expression analysis of FASN, CD36, SLC27A1, SLC27A2, SLC27A3, SLC27A4, SLC27A5, ACSL1, and ACSL3 was performed by qRT-PCR in 24 tumoral PDAC tissues and 11 samples from non-tumoral pancreatic tissues obtained via fine needle aspiration or via surgical resection. The genes were considered significantly dysregulated between the groups when the p value was < 0.05 and the fold change (FC) was ≤ 0.5 and ≥ 2. We found that three FA transporters and two long-chain acyl-CoA synthetases genes were significantly upregulated in the PDAC tissue compared to the non-tumoral tissue: SLC27A2 (FC = 5.66; P = 0.033), SLC27A3 (FC = 2.68; P = 0.040), SLC27A4 (FC = 3.13; P = 0.033), ACSL1 (FC = 4.10; P < 0.001), and ACSL3 (FC = 2.67; P = 0.012). We further investigated any possible association between the levels of the analyzed mRNAs and the specific characteristics of the tumors, including the anatomic location, the lymph node involvement, and the presence of metastasis. A significant difference in the expression of SLC27A3 (FC = 3.28; P = 0.040) was found comparing patients with and without lymph nodes involvement with an overexpression of this transcript in 17 patients presenting tumoral cells in the lymph nodes. Despite the low number of patients analyzed, these preliminary results seem to be promising. Addressing lipid metabolism through a broad strategy could be a beneficial way to treat this malignancy. Future in vitro and in vivo studies on these genes may offer important insights into the mechanisms linking PDAC with the long-chain FA import pathway.

Assessment of Surgical Margin of Tongue Squamous Cell Carcinoma via Raman Mapping.

This study introduces a novel classification approach that combines convolutional neural network (CNN) and Raman mapping to differentiate between tongue squamous cell carcinoma (TSCC) and non-tumorous tissue, as well as to identify different histological grades of TSCC. In this study, 240 Raman mappings data from 30 tissue samples were collected from 15 patients who had undergone surgical resection for TSCC. A total of 18,000 sub-mappings extracted from Raman mappings were then used to train and test a CNN model, which extracted feature representations that were subsequently processed through a fully connected network to perform classification tasks based on the Raman mapping data. The experimental results indicated that the proposed method achieved competitive classification accuracy above 83%. To further validate the effectiveness of the Raman mapping, its performance was compared with Raman spectroscopy, demonstrating a competitive accuracy rate. The promising outcomes from this application of CNN in Raman mapping suggest that this technique could be a reliable method for intraoperative assessment of surgical margins, potentially leading to shorter detection times.

LncRNA MANCR is downregulated in non-small cell lung cancer and predicts poor survival

BackgroundIt is known that genomic instability contributes to cancer development. Mitotically associated long non-coding RNA (MANCR) has been reported to promote genomic stability, suggesting its involvement in cancers. Therefore, this study was conducted to investigate the role of MANCR in non-small cell lung cancer (NSCLC).MethodsAfter NSCLC (n = 60) and control (healthy subjects, n = 60) plasma samples, as well as NSCLC and paired non-tumor tissues from patients were collected, the levels of MANCR expression in plasma and tissues was detected using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Then the correlations of MANCR expression with clinical stages were confirmed. The diagnostic values of MANCR in both plasma and tissue samples for stage I/II NSCLC were analyzed using Receiver Operating Characteristic (ROC) curves. All NSCLC patients were monitored for 5 years to investigate the role of MANCR in the prediction of patients’ survival.ResultsMANCR expression was downregulated in both NSCLC plasma and tissue of NSCLC patients compared to controls (P < 0.05). Decreased MANCR expression levels from stage I to IV were observed. However, MANCR expression in non-tumor tissue was not significantly different between different stages (P > 0.05). Additionally, stage I/II NSCLC patients were separated from controls using MANCR in plasma and tumor tissues as biomarkers. Lower MANCR levels in plasma and tumor were closely correlated with patients’ higher mortality rate.ConclusionMANCR is down-expressed in NSCLC patients and may serve as a diagnostic and prognostic biomarker for NSCLC.

Migrasome-related prognostic signature TSPAN4 correlates with immune infiltrates and metabolic disturbances in hepatocellular carcinoma.

We aim to comprehensively analyze and validate the prognostic efficacy of tetraspanin 4 (TSPAN4) and several other migrasome-related markers in hepatocellular carcinoma (HCC). The expression, diagnostic, and prognostic efficacy of five migrasome-related genes in HCC were analyzed using several databases. Five pairs of adjacent non-tumor tissues and HCC tissues were used to validate the expression. The prognostic efficacy of TSPAN4 was validated in a HCC cohort. TSPAN4 was knocked down in Huh-7 cells, EdU, and CCK-8, and wound healing assays were conducted to analyze its effects on cell proliferation and migration. In addition, transcriptomic sequencing was used to identify differentially expressed genes. Compared with those in normal tissues, four genes (TSPAN4, PIGK, NDST1, and CPQ) were elevated in liver hepatocellular carcinoma (LIHC), but not TSPAN7. Of these, only elevated TSPAN4 predicted unfavorable prognosis of HCC patients. The expression and prognostic efficacy of TSPAN4 were further confirmed in a HCC cohort (97 patients); and patients in the TSPAN4high group showed unfavorable overall survival (log-rank P = 0.0055). Functional analysis showed that TSPAN4 knockdown significantly suppressed cell migration, but not cell proliferation. Moreover, TSPAN4 knockdown induced disturbances of the metabolic pathways, mainly pentose and glucuronate interconversions. TPSAN4 is a promising prognostic and therapeutic target for HCC treatment and may be involved in the metabolic pathways that affect disease progression.

Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate

Primary aldosteronism (PA), characterized by autonomous aldosterone overproduction, is a major cause of secondary hypertension with significant cardiovascular complications. Current treatments mainly focus on symptom management rather than addressing underlying mechanisms. This study aims to discover novel therapeutic targets for PA using integrated bioinformatics and experimental validation approaches. We employed a systematic approach combining: gene identification through transcriptome-wide association studies (TWAS); causal inference using summary data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) analyses; additional analyses included phenome-wide association analysis, enrichment analysis, protein-protein interaction (PPI) networks, drug repurposing, molecular docking and clinical validation through aldosterone-producing adenomas (APAs) tissue. Through systematic screening and prioritization, we identified 163 PA-associated genes, of which seven emerged as potential drug targets: CEP104, HIP1, TONSL, ZNF100, SHMT1, and two long non-coding RNAs (AC006369.2 and MRPL23-AS1). SHMT1 was identified as the most promising target, showing significantly elevated expression in APAs compared to adjacent non-tumorous tissues. Drug repurposing analysis identified four potential SHMT1-targeting compounds (Mimosine, Pemetrexed, Leucovorin, and Irinotecan), supported by molecular docking studies. The integration of multiple bioinformatics methods and experimental validation successfully identified novel drug targets for hyperaldosteronism. SHMT1, in particular, represents a promising candidate for future therapeutic development. These findings provide new opportunities for developing causative treatments for PA, though further clinical validation is warranted.

Global profiling of alternative splicing in non-small cell lung cancer reveals novel histological and population differences.

Lung cancer is one of the most frequently diagnosed cancers in the US. African-American (AA) men are more likely to develop lung cancer with higher incidence and mortality rates than European-American (EA) men. Herein, we report high-confidence alternative splicing (AS) events from high-throughput, high-depth total RNA sequencing of lung tumors and non-tumor adjacent tissues (NATs) in two independent cohorts of patients with adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). We identified novel AS biomarkers with notable differential percent spliced in (PSI) values between lung tumors and NATs enriched in the AA and EA populations, which were associated with oncogenic signaling pathways. We also uncovered tumor subtype- and population-specific AS events associated with cell surface proteins and cancer driver genes. We highlighted significant AS events in SYNE2 specific to LUAD in both populations, as well as those in CD44 from EAs and TMBIM6 from AAs specific to LUAD. Here, we also present the validation of cancer signatures based on direct high-throughput reverse transcription-PCR. Our large survey of lung tumors presents a rich data resource that may help to understand molecular subtypes of lung tumor between AAs and EAs and reveal new therapeutic vulnerabilities that potentially advance health equity.

Proteomic Characterization of Liver Cancer Cells Treated with Clinical Targeted Drugs for Hepatocellular Carcinoma

Background/Objectives: Hepatocellular carcinoma (HCC) remains a significant global health concern, primarily due to the limited efficacy of targeted therapies, which are often compromised by drug resistance and adverse side effects. Methods: In this study, we utilized a Tandem Mass Tag (TMT)-based quantitative proteomic approach to analyze global protein expression and serine/threonine/tyrosine (S/T/Y) phosphorylation modifications in HepG2 cells following treatment with three clinically relevant hepatocellular carcinoma-targeted agents: apatinib, regorafenib, and lenvatinib. Results: Utilizing KEGG pathway enrichment analysis, biological process enrichment analysis, and protein interaction network analysis, we elucidated the common and specific metabolic pathways, biological processes, and protein interaction regulatory networks influenced by three liver cancer therapeutics. The study additionally proposed potential combinational treatment strategies, highlighting a possible synergistic interaction between HCC-targeted drugs and the DNA methyltransferase inhibitor. Furthermore, through the integration of clinical phosphorylation site data, we identified several phosphorylation sites that exhibited higher abundance in tumor tissues compared to adjacent non-tumor tissues. These sites were associated with poor prognosis and elevated functional scores. Conclusions: In summary, this study conducted an in-depth analysis of the molecular alterations in proteins and phosphorylation modifications induced by clinical HCC-targeted drugs, predicting drug combination strategies and therapeutic targets.

MiR-9-5p/HMMR regulates the tumorigenesis and progression of clear cell renal cell carcinoma through EMT and JAK1/STAT1 signaling pathway

BackgroundThe most common malignant type of kidney cancer is clear cell renal cell carcinoma (ccRCC). The expression levels of hyaluronan-mediated motility receptor (HMMR) in many tumor types are significantly elevated. HMMR is closely associated with tumor-related progression, treatment resistance, and poor prognosis, and has yet to be fully investigated in terms of its expression patterns and molecular mechanisms of action in ccRCC. Further research is imperative to elucidate these aspects.MethodsWe used The Cancer Genome Atlas (TCGA) database to preliminarily investigate HMMR expression and function in ccRCC and the data for 19 samples from the NCBI GEO database (GSE207493) for single-cell analysis. We assessed the differential expression level of HMMR between ccRCC cancerous tissues and their matched non-tumor tissues. Subsequently, a series of in vivo and in vitro experiments were designed to elucidate the biological function of HMMR in ccRCC, including Transwell assays, CCK-8 assays, clone formation assays and subcutaneous xenograft experiments in nude mice. Through bioinformatics analysis, we identified potential microRNAs (miRNAs) that may regulate HMMR, as well as the possible signaling pathways involved. Finally, we conducted a series of cellular functional experiments to validate our hypotheses regarding the HMMR axis.ResultsHMMR expression was significantly up-regulated in tumor tissues of ccRCC patients, and elevated HMMR expression level showed a strong correlation with ccRCC progression and adverse prognoses of patients. Knocking down HMMR inhibited the proliferative and migratory abilities of ccRCC cells, while its overexpression amplified these oncogenic properties. In nude mice model, reduced HMMR expression inhibited ccRCC tumor proliferation in vivo. Furthermore, overexpression of an upstream transcriptional regulator, miR-9-5p, effectively downregulated HMMR expression and thus impeded ccRCC cells proliferation and migration. HMMR might influence ccRCC growth via the Epithelial-Mesenchymal Transition (EMT) pathway and the Janus Kinase 1/Signal Transducer and Activator of Transcription 1 (JAK1/STAT1) pathway.ConclusionsHMMR is overexpressed in ccRCC, and there is a significant link between high HMMR expression and tumor progression, as well as poor patient prognosis. Specifically, HMMR could be targeted and inhibited by miR-9-5p and might modulate the tumorigenesis and progression of ccRCC through both EMT and JAK1/STAT1 signaling pathway.

Comparative Analysis of Transcriptomic and Proteomic Expression between Two Non-Small Cell Lung Cancer Subtypes.

Non-small cell lung cancer (NSCLC) is frequently diagnosed late and has poor survival. The two predominant subtypes of NSCLC, adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), are currently differentially diagnosed using immunohistochemical markers; however, they are increasingly recognized as very different cancer types suggestive of potential for new, more targeted therapies. There are extensive efforts to find more precise and noninvasive differential diagnostic tools. Here, we examined these two NSCLC subtypes for differences that may inform treatment and identify potential novel therapeutic pathways. We presented a comparative analysis of transcriptomic and proteomic expression in tumors from a cohort of 22 NSCLC patients: 8 LUSC and 14 LUAD. Comparing NSCLC subtypes, we found differential gene expression related to cell differentiation for LUSC and cellular structure and immune response regulation for LUAD. Differential protein expression between NSCLC subtypes was related to extracellular structure for LUSC and metabolic processes, including glucose metabolism for LUAD. This direct comparison was more informative about subtype-specific pathways than between each subtype and control (nontumor) tissues. Many of our observations between NSCLC subtypes support and inform existing observations and reveal differences that may aid research seeking to identify and validate novel subtype biomarkers or druggable targets.

Membranous Overexpression of Fibronectin Predicts Microvascular Invasion and Poor Survival Outcomes in Patients with Hepatocellular Carcinoma.

Fibronectin (FN) has recently been identified as being overexpressed in patients with hepatocellular carcinoma (HCC) and deemed a promising biomarker of vascular invasion. The aim of this study was to examine the patterns of FN expression in HCC cells and their clinicopathological significance, such as their association with vascular invasion and angiogenesis patterns. Immunohistochemical analysis of FN was conducted using tissue microarrays from 258 surgically resected HCCs and matched nontumorous liver tissues. Three distinct FN expression patterns were observed: cytoplasmic, membranous, and sinusoidal. Moderate or strong expression was considered FN-positive. Cytoplasmic or sinusoidal FN expression was significantly more common in HCC cells than in the adjacent liver tissue (p<0.001). FN expression was detected in the membranes of HCC cells and absent in nonneoplastic hepatocytes (p<0.001). Overall survival and disease-free survival in patients with HCC cells with membranous FN expression were significantly shorter than those in patients without membranous FN expression. Membranous FN expression in HCC was significantly associated with high serum alpha-fetoprotein (AFP) and protein induced by vitamin K absence-II (PIVKA-II) levels, infiltrative gross type, poor Edmondson-Steiner grade, major vessel invasion, microvascular invasion, macrotrabecular massive subtype, advanced T stage, and vessel-encapsulating tumor cluster pattern. Sinusoidal pattern of FN expression in HCC was significantly associated with high serum AFP and PIVKA-II levels, infiltrative gross type, large tumor size, microvascular invasion, macrotrabecular massive subtype, and vessel-encapsulating tumor cluster patterns. Evaluating FN expression in HCC cells may be useful for identifying aggressive cases of HCC with vascular invasion via biopsy.

Modulating tumor-associated macrophages through CSF1R inhibition: a potential therapeutic strategy for HNSCC

PurposeTumor-associated macrophages (TAMs) are pivotal immune cells within the tumor microenvironment (TME), exhibiting dual roles across various cancer types. Depending on the context, TAMs can either suppress tumor progression and weaken drug sensitivity or facilitate tumor growth and drive therapeutic resistance. This study explores whether targeting TAMs can suppress the progression of head and neck squamous cell carcinoma (HNSCC) and improve the efficacy of chemotherapy.MethodsBioinformatics analyses were performed to evaluate TAMs infiltration levels in HNSCC tumor tissues and examine their associations with patients’ clinicopathological characteristics and prognosis. Flow cytometry was utilized to measure the expression of key macrophage markers and assess apoptosis following treatment with colony stimulating factor 1 receptor (CSF1R) inhibitors (BLZ945, PLX3397). Additionally, immunohistochemistry was employed to detect CD68 and CD8 expression. In vivo, the antitumor efficacy of CSF1R inhibitors was tested in mouse HNSCC tumor model, both as monotherapy and in combination with cisplatin, to evaluate potential synergistic effects.ResultsBioinformatic analysis identified TAMs as the predominant infiltrating immune cells in the TME of HNSCC, with significantly higher infiltration levels in tumor tissues compared to adjacent non-tumor tissues. High TAMs infiltration was associated with poorer overall survival (OS), disease-free survival (DFS), human papillomavirus (HPV) infection status, and advanced disease stages. The TAMs-related genes prediction model demonstrated high prognostic accuracy. CSF1R is primarily expressed in TAMs, where high CSF1R expression may suppress antigen binding and activation. In vitro experiments showed that CSF1R inhibitors induce TAMs apoptosis, enhance their phagocytic activity, and reduce CD206 expression and IL-10 secretion, thereby diminishing their immunosuppressive function. In vivo experiments revealed that while CSF1R inhibitors alone had limited efficacy in suppressing tumor growth, their combination with cisplatin significantly enhanced therapeutic efficacy, as evidenced by increased CD8+ T cells infiltration within the TME.ConclusionTargeting TAMs via CSF1R inhibition enhances the therapeutic efficacy of cisplatin in HNSCC. These findings suggest that CSF1R inhibitors hold promise as a component of combination therapy for HNSCC.Graphical abstract

Identification of a mitophagy-related gene signature for predicting overall survival and response to immunotherapy in rectal cancer.

Rectal cancer is a highly heterogeneous gastrointestinal tumor, and the prognosis for patients with treatment-resistant and metastatic rectal cancer remains poor. Mitophagy, a type of selective autophagy that targets mitochondria, plays a role in promoting or inhibiting tumors; however, the importance of mitophagy-related genes (MRGs) in the prognosis and treatment of rectal cancer is unclear. In this study, we used the differentially expressed genes (DEGs) and MRGs from the TCGA-READ dataset to identify differentially expressed mitophagy-related genes (MRDEGs). The mitophagy scores were then analyzed for differential expression and ROC. Seven module genes were identified using the weighted gene coexpression network analysis (WGCNA) approach and subsequently validated in the merged datasets GSE87211 and GSE90627. The model genes were obtained based on prognostic features, and the subgroups were distinguished by risk score. Gene enrichment, immune infiltration and immunotherapy response were also evaluated. Finally, validation of prognostic gene expression in rectal cancer was carried out using clinical samples, employing Immunohistochemistry (IHC). We demonstrated that 22 MRGs were differentially expressed between normal and rectal cancer tissues. A prognostic model for rectal cancer MRGs was constructed using WGCNA and Cox regression, which exhibited good diagnostic performance. In this study, we identified four molecular markers (MYLK, FLNC, MYH11, and NEXN) as potential prognostic biomarkers for rectal cancer for the first time. Moreover, our findings indicate that the risk scores derived from the four MRGs are associated with tumor immunity. To further validate our findings, IHC analyses suggested that the expression of MYH11 in rectal cancer tissues was lower than in nontumorous rectal tissues. MRGs could predict the prognosis and response to immunotherapy in patients with rectal cancer and might be able to personalize treatment for patients.

IRF1 transcriptionally up-regulates CXCL10 which increases CD8+ T cells infiltration in colorectal cancer.

Tumor-infiltrating CD8+ T cell is a robust predictor of outcome and immunotherapy response in patients with CRC. However, limited introduction of intratumoral CD8+ T cells remains a barrier for treatment of CRC. One of the most effective but difficult therapy for CD8+ T cells entering the tumor is activating chemokine receptors. This study observed a decrease in the expression level of interferon regulator factor 1(IRF1) in CRC tumor tissues compared to matched non-tumor tissues. Furthermore, it found a positive correlation between low IRF1 expression and unfavorable prognosis in CRC patients. The present study also demonstrated that overexpression of IRF1 attenuated tumor growth by promoting the accumulation of facilitating CD8+T cells at the tumor site in mouse models. Additionally, this study identified IRF1 response elements in the promoter region of CXCL10 and show that the binding of IRF1 promoted the transcription of CXCL10. Of note, it was discovered that an increase in CXCL10 was positively associated with improved survival in CRC. These findings strongly suggest that IRF1 serves as a key transcription factor for CXCL10, highlighting its potential as a therapeutic target for CRC.

Potential Regulation of ARID1A by miR-129-5p and miR-3613-3p and Their Prognostic Value in Gastric Cancer.

Gastric cancer (GC) remains the most common malignant tumor of the gastrointestinal tract and one of the leading causes of cancer-related deaths worldwide. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), are involved in the pathogenesis and progression of GC and, therefore, may be potential diagnostic and prognostic biomarkers. Our work was aimed at investigating the predicted regulation of ARID1A by miR-129-5p and miR-3613-3p and the clinical value of their aberrant expression in GC. The study included tumor and adjacent non-tumor tissues from 110 GC patients, 38 sectional normal gastric tissue samples, as well as 65 plasma samples of GC patients and 49 plasma samples of healthy donors. Expression levels of ARID1A and both miRNAs were quantified by reverse transcription-polymerase chain reaction (RT-PCR). We have identified significant associations of their expression with the clinical and pathological characteristics of GC patients both in tissues and plasma. To validate predicted target pairs miR-129-5p/ARID1A and miR-3613-3p/ARID1A, in vitro experiments on cancer cell lines were conducted. The obtained results suggest a complex role of ARID1A, miR-129-5p and miR-3613-3p in GC and potential regulation of ARID1A expression by both miRNAs.

Identification and validation of an immune-related miRNA signature for predicting prognosis of hepatocellular carcinoma.

MicroRNAs play a significant role in the initiation and progression of hepatocellular carcinoma (HCC); however, their roles in immune regulation of HCC remain unclear. Our study aimed to identify an immune-related miRNA signature and explore its impact on the prognosis and tumor immune microenvironment HCC. Initially, we identified 48 differentially expressed immune-related miRNAs. Using the LASSO regression dimensionality reduction method, we constructed an immune-related miRNA signature from 12 of these miRNAs. This signature has emerged as an independent prognostic marker and is associated with the clinical stage of HCC. To elucidate the roles of the twelve-microRNA signature, we predicted their target genes. Enrichment analysis indicated that these target genes were involved in immune cell infiltration. Notably, the target genes regulated by hsa-miR-139-5p, hsa-miR-551a, and hsa-miR-7-5p showed a partial overlap. We further confirmed the differential expression of miR-7, miR-551a, miR-139-5p, and some of their overlapping target genes in tumor and non-tumor tissues derived from patients with HCC using RT-qPCR. Overall, we identified an immune-related miRNA signature that is strongly correlated with the prognosis and immune microenvironment of HCC; and confirmed the differential expression of the three most important microRNAs and their overlapping target genes in tumor and non-tumor tissues derived from HCC patients.

Extensive methylation analysis of circulating tumor DNA in plasma of patients with gastric cancer

DNA methylation is known to be involved in tumor progression. This is the first study to perform an extensive methylation analysis of plasma circulating tumor DNA (ctDNA) using targeted bisulfite sequencing in gastric cancer (GC) patients to evaluate the usefulness of ctDNA methylation as a new biomarker. Sixteen patients who received chemotherapy for recurrent GC were included. After confirmation of the methylation status of 63 genes using the Cancer Genome Atlas (TCGA) dataset, the methylation status in paired tumor and non-tumor tissues and plasma were investigated using targeted bisulfite sequencing in these genes. Forty-four of the 63 genes were significantly hypermethylated in GC patients in the TCGA cohort. Of these 44 genes, hierarchical clustering showed that five (SPG20, FBN1, SDC2, TFPI2, SEPT9) were particularly hypermethylated in tumor compared to non-tumor tissues in our GC cohort. In plasma methylation analysis, patients with high methylation of these genes had significantly worse overall survival than those with low methylation (log-rank P = 0.009). In a patient who underwent blood sampling at multiple points, the methylation levels of these five genes varied closely with clinical tumor status. The plasma ctDNA methylation levels of these five genes could be useful as a noninvasive prognostic biomarker for GC.

Clinical confocal laser endomicroscopy for imaging of autofluorescence signals of human brain tumors and non-tumor brain

PurposeAnalysis of autofluorescence holds promise for brain tumor delineation and diagnosis. Therefore, we investigated the potential of a commercial confocal laser scanning endomicroscopy (CLE) system for clinical imaging of brain tumors.MethodsA clinical CLE system with fiber probe and 488 nm laser excitation was used to acquire images of tissue autofluorescence. Fresh samples were obtained from routine surgeries (glioblastoma n = 6, meningioma n = 6, brain metastases n = 10, pituitary adenoma n = 2, non-tumor from surgery for the treatment of pharmacoresistant epilepsy n = 2). Additionally, in situ intraoperative label-free CLE was performed in three cases. The autofluorescence images were visually inspected for feature identification and quantification. For reference, tissue cryosections were prepared and further analyzed by label-free multiphoton microscopy and HE histology.ResultsLabel-free CLE enabled the acquisition of autofluorescence images for all cases. Autofluorescent structures were assigned to the cytoplasmic compartment of cells, elastin fibers, psammoma bodies and blood vessels by comparison to references. Sparse punctuated autofluorescence was identified in most images across all cases, while dense punctuated autofluorescence was most frequent in glioblastomas. Autofluorescent cells were observed in higher abundancies in images of non-tumor samples. Diffuse autofluorescence, fibers and round fluorescent structures were predominantly found in tumor tissues.ConclusionLabel-free CLE imaging through an approved clinical device was able to visualize the characteristic autofluorescence patterns of human brain tumors and non-tumor brain tissue ex vivo and in situ. Therefore, this approach offers the possibility to obtain intraoperative diagnostic information before resection, importantly independent of any kind of marker or label.

The survival prediction analysis and preliminary study of the biological function of YEATS2 in hepatocellular carcinoma.

Our study aims to develop and validate a novel molecular marker for the prognosis and diagnosis of hepatocellular carcinoma (HCC) MATERIALS & METHODS: We retrospectively analyzed mRNA expression profile and clinicopathological data of HCC patients fetched from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and The International Cancer Genome Consortium (ICGC) datasets. Univariate Cox regression analysis was performed to collect differentially expressed mRNA (DEmRNAs) from HCC and non-tumor tissues, and YEATS2, a prognostic marker, was identified by further analysis. ROC curve, survival analysis and multivariate Cox regression analysis as well as nomograms were used to evaluate the prognosis of this gene. Finally, the biological function of this gene was preliminarily discussed by using single gene Gene Set Enrichment Analysis (GSEA), and the YEATS2 overexpression and knockdown hepatoma cell line was used to verify the results in vitro and in vivo. Based on the clinical information of HCC in TCGA, GEO and ICGC databases, the gene YEATS2 with significant differences from HCC was identified. There was a statistical difference in the survival prognosis between the two databases and the ROC curve showed that the survival of HCC in both TCGA, GSE14520 and ICGC groups had a satisfactory predictive effect. Univariate and multivariate Cox regression analysis showed that YEATS2 was an independent prognostic factor for HCC, and Nomograms, which combined this prognostic feature with significant clinical features, provided an important reference for the clinical prognostic diagnosis of HCC. Next, we constructed overexpression and knockdown YEATS2 cell line in Hep3B and LM3 cells, and further proved that overexpression YEATS2 promote the proliferation and migration of HCC cells by CCK8, colony formation experiment, and transwell assays, and knockdown YEATS2 inhibited the proliferation and migration of HCC cells by CCK8, colony formation experiment, and transwell assays. Finally, the biological function of YEATS2 was preliminarily explored through GSEA analysis of a single gene, and it was found that it was significantly correlated with cell cycle and DNA repair, which provided us with ideas for further analysis. Furthermore, the knockdown of YEATS2 promoted radiation-induced DNA damage, enhanced radiosensitivity, and ultimately inhibited the proliferation of hepatocellular carcinoma cells in vitro and in vivo. Our study identified a promising prognostic marker for hepatocellular carcinoma that is useful for clinical decision-making and individualized treatment.