Decoding the molecular landscape: A novel prognostic signature for uveal melanoma unveiled through programmed cell death-associated genes.

Uveal melanoma (UM) is a rare but aggressive malignant ocular tumor with a high metastatic potential and limited therapeutic options, currently lacking accurate prognostic predictors and effective individualized treatment strategies. Public databases were utilized to analyze the prognostic relevance of programmed cell death-related genes (PCDRGs) in UM transcriptomes and survival data. Consensus clustering and Lasso Cox regression analysis were performed for molecular subtyping and risk feature construction. The PCDRG-derived index (PCDI) was evaluated for its association with clinicopathological features, gene expression, drug sensitivity, and immune infiltration. A total of 369 prognostic PCDRGs were identified, which could cluster UM into 2 molecular subtypes with significant differences in prognosis and clinicopathological characteristics. Furthermore, a risk feature PCDI composed of 11 PCDRGs was constructed, capable of indicating prognosis in UM patients. Additionally, PCDI exhibited correlations with the sensitivity to 25 drugs and the infiltration of various immune cells. Enrichment analysis revealed that PCDI was associated with immune regulation-related biological processes and pathways. Finally, a nomogram for prognostic assessment of UM patients was developed based on PCDI and gender, demonstrating excellent performance. This study elucidated the potential value of PCDRGs in prognostic assessment for UM and developed a corresponding risk feature. However, further basic and clinical studies are warranted to validate the functions and mechanisms of PCDRGs in UM.

Exploring the role of CDCA4 in liver hepatocellular carcinoma using bioinformatics analysis and experiments.

Liver hepatocellular carcinoma (LIHC) encompasses diverse therapeutic approaches, among which targeted therapy has gained significant prominence in recent years. The identification of numerous targets and the increasing clinical application of targeted drugs have greatly improved LIHC treatment. However, the precise role of CDCA4 (Cell Division Cycle Associated 4), as well as its underlying mechanisms and prognostic implications in LIHC, remains unclear. CDCA4 expression levels in LIHC were analyzed using multiple databases including the cancer genome atlas (TCGA), gene expression profiling interactive analysis (GEPIA), and ULCAN, as well as the datasets E_TABM_36, GSE144269, GSE14520, and GSE54236. The prognostic value of CDCA4 was then evaluated. Subsequently, the association between CDCA4 and immune cells was investigated. Enrichment analysis (GSEA) was utilized to investigate the functional roles and pathways linked to CDCA4. Additionally, the methylation patterns and drug sensitivity of CDCA4 were examined. A predictive model incorporating immune genes related to CDCA4 was developed. The TISCH dataset was used to investigate the single-cell expression patterns of CDCA4. Finally, validation of CDCA4 expression levels was conducted through RT-PCR, Western blotting, and immunohistochemistry. CDCA4 exhibited significant overexpression in LIHC and demonstrated significant correlations with clinical features. High expression of CDCA4 is associated with a poorer prognosis. Analysis of immune infiltration and enrichment revealed its association with the immune microenvironment. Furthermore, its expression is correlated with methylation and mutation patterns. CDCA4 is associated with 19 drugs. Prognostic models utilizing CDCA4 demonstrate favorable effectiveness. T cell subtypes were found to be associated with CDCA4 through single-cell analysis. The conclusive experiment provided evidence of significant upregulation of CDCA4 in LIHC. The high expression of CDCA4 in LIHC is associated with prognostic significance and is highly expressed in T cell subtypes, providing a new therapeutic target and potential therapeutic strategy for LIHC.

The emerging roles of miRNA-mediated autophagy in ovarian cancer.

Ovarian cancer is one of the common tumors of the female reproductive organs. It has a high mortality rate, is highly heterogeneous, and early detection and primary prevention are very complex. Autophagy is a cellular process in which cytoplasmic substrates are targeted for degradation in lysosomes through membrane structures called autophagosomes. The periodic elimination of damaged, aged, and redundant cellular molecules or organelles through the sequential translation between amino acids and proteins by two biological processes, protein synthesis, and autophagic protein degradation, helps maintain cellular homeostasis. A growing number of studies have found that autophagy plays a key regulatory role in ovarian cancer. Interestingly, microRNAs regulate gene expression at the posttranscriptional level and thus can regulate the development and progression of ovarian cancer through the regulation of autophagy in ovarian cancer. Certain miRNAs have recently emerged as important regulators of autophagy-related gene expression in cancer cells. Moreover, miRNA analysis studies have now identified a sea of aberrantly expressed miRNAs in ovarian cancer tissues that can affect autophagy in ovarian cancer cells. In addition, miRNAs in plasma and stromal cells in tumor patients can affect the expression of autophagy-related genes and can be used as biomarkers of ovarian cancer progression. This review focuses on the potential significance of miRNA-regulated autophagy in the diagnosis and treatment of ovarian cancer.

Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease.

Periampullary cancers, including pancreatic ductal adenocarcinoma, ampullary-, cholangio-, and duodenal carcinoma, are frequently diagnosed in an advanced stage and are associated with poor overall survival. They are difficult to differentiate from each other and challenging to distinguish from benign periampullary disease preoperatively. To improve the preoperative diagnostics of periampullary neoplasms, clinical or biological markers are warranted.In this study, 28 blood plasma amino acids and derivatives from preoperative patients with benign (N = 45) and malignant (N = 72) periampullary disease were analyzed by LC-MS/MS.Principal component analysis and consensus clustering both separated the patients with cancer and the patients with benign disease. Glutamic acid had significantly higher plasma expression and 15 other metabolites significantly lower plasma expression in patients with malignant disease compared with patients having benign disease. Phenylalanine was the only metabolite associated with improved overall survival (HR = 0.50, CI 0.30-0.83, P < 0.01).Taken together, plasma metabolite profiles from patients with malignant and benign periampullary disease were significantly different and have the potential to distinguish malignant from benign disease preoperatively.

Analyzing the expression and clinical significance of CENPE in gastric cancer.

BACKGROUND: Gastric cancer (GC) is a prevalent type of malignant gastrointestinal tumor. Many studies have shown that CENPE acts as an oncogene in some cancers. However, its expression level and clinical value in GC are not clear. METHODS: Obtaining clinical data information on gastric adenocarcinoma from TCGA and GEO databases. The gene expression profiling interaction analysis (GEPIA) was used to evaluate the relationship between prognosis and CENPE expression in gastric cancer patients. Utilizing the UALCAN platform, the correlation between CENPE expression and clinical parameters was examined. Functions and signaling pathways of CENPE were analyzed using the Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). The association between immunological infiltrating cells and CENPE expression was examined using TIMER2.0. Validation was performed by real-time quantitative PCR (qPT-PCR) and immunohistochemical analysis. RESULTS: According to the analysis of the GEPIA database, the expression of CENPE is increased in gastric cancer tissues compared to normal tissues. It was also found to have an important relationship with the prognosis of the patient (p<0.05). The prognosis was worse and overall survival was lower in individuals with increased expression of CENPE. In line with the findings of the GEPIA, real-time fluorescence quantitative PCR (qPT-PCR) confirmed that CENPE was overexpressed in gastric cancer cells. Furthermore, It was discovered that H. pylori infection status and tumor grade were related to CENPE expression. Enrichment analysis revealed that CENPE expression was linked to multiple biological functions and tumor-associated pathways. CENPE expression also correlated with immune-infiltrating cells in the gastric cancer microenvironment and was positively connected to NK cells and mast cells. According to immunohistochemical examination, paracancerous tissues had minimal expression of CENPE, but gastric cancer showed significant expression of the protein. CONCLUSIONS: According to our findings, CENPE is substantially expressed in GC and may perhaps contribute to its growth. CENPE might be a target for gastric cancer therapy and a predictor of a bad prognosis.

Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma.

BACKGROUND: Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP. METHODS: RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors. RESULTS: In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP. CONCLUSIONS: We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.

Mutation characteristics and molecular evolution of ovarian metastasis from gastric cancer and potential biomarkers for paclitaxel treatment.

Ovarian metastasis is one of the major causes of treatment failure in patients with gastric cancer (GC). However, the genomic characteristics of ovarian metastasis in GC remain poorly understood. In this study, we enroll 74 GC patients with ovarian metastasis, with 64 having matched primary and metastatic samples. Here, we show a characterization of the mutation landscape of this disease, alongside an investigation into the molecular heterogeneity and pathway mutation enrichments between synchronous and metachronous metastasis. We classify patients into distinct clonal evolution patterns based on the distribution of mutations in paired samples. Notably, the parallel evolution group exhibits the most favorable prognosis. Additionally, by analyzing the differential response to chemotherapy, we identify potential biomarkers, including SALL4, CCDC105, and CLDN18, for predicting the efficacy of paclitaxel treatment. Furthermore, we validate that CLDN18 fusion mutations improve tumor response to paclitaxel treatment in GC with ovarian metastasis in vitro and vivo.

Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments.

BACKGROUND: Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. METHODS: Utilizing RNA sequencing data and corresponding clinical information from the TCGA database, and employing Weighted Gene Co-expression Network Analysis (WGCNA) on TNBC mRNAsi sourced from an online database, stemness-related genes (SRGs) and SRlncRNAs were identified. A prognostic model was developed using univariate Cox and LASSO-Cox analysis based on SRlncRNAs. The performance of the model was evaluated using Kaplan-Meier analysis, ROC curves, and ROC-AUC. Additionally, the study delved into the underlying signaling pathways and immune status associated with the divergent prognoses of TNBC patients. RESULTS: The research identified a signature of six SRlncRNAs (AC245100.6, LINC02511, AC092431.1, FRGCA, EMSLR, and MIR193BHG) for TNBC. Risk scores derived from this signature were found to correlate with the abundance of plasma cells. Furthermore, the nominated chemotherapy drugs for TNBC exhibited considerable variability between different risk score groups. RT-qPCR validation confirmed abnormal expression patterns of these SRlncRNAs in TNBC stem cells, affirming the potential of the SRlncRNAs signature as a prognostic biomarker. CONCLUSION: The identified signature not only demonstrates predictive power in terms of patient outcomes but also provides insights into the underlying biology, signaling pathways, and immune status associated with TNBC prognosis. The findings suggest the possibility of guiding personalized treatments, including immune checkpoint gene therapy and chemotherapy strategies, based on the risk scores derived from the SRlncRNA signature. Overall, this research contributes valuable knowledge towards advancing precision medicine in the context of TNBC.

RICTOR amplification is associated with Rictor membrane staining and does not correlate with PD-L1 expression in lung squamous cell carcinoma.

RICTOR gene, which encodes the scaffold protein of mTORC2, can be amplified in various tumor types, including squamous cell carcinoma (SCC) of the lung. RICTOR amplification can lead to hyperactivation of mTORC2 and may serve as a targetable genetic alteration, including in lung SCC patients with no PD-L1 expression who are not expected to benefit from immune checkpoint inhibitor therapy. This study aimed to compare RICTOR amplification detected by fluorescence in situ hybridization (FISH) with Rictor and PD-L1 protein expression detected by immunohistochemistry (IHC) in SCC of the lung. The study was complemented by analysis of the publicly available Lung Squamous Cell Carcinoma (TCGA, Firehose legacy) dataset. RICTOR amplification was observed in 20% of our cases and 16% of the lung SCC cases of the TCGA dataset. Rictor and PD-L1 expression was seen in 74% and 44% of the cases, respectively. Rictor IHC showed two staining patterns: membrane staining (16% of the cases) and cytoplasmic staining (58% of the cases). Rictor membrane staining predicted RICTOR amplification as detected by FISH with high specificity (95%) and sensitivity (70%). We did not find any correlation between RICTOR amplification and PD-L1 expression; RICTOR amplification was detected in 18% and 26% of PD-L1 positive and negative cases, respectively. The TCGA dataset analysis showed similar results; RICTOR copy number correlated with Rictor mRNA and protein expression but showed no association with PD-L1 mRNA and protein expression. In conclusion, the correlation between RICTOR amplification and Rictor membrane staining suggests that the latter can potentially be used as a surrogate marker to identify lung SCC cases with RICTOR amplification. Since a significant proportion of PD-L1 negative SCC cases harbor RICTOR amplification, analyzing PD-L1 negative tumors by RICTOR FISH or Rictor IHC can help select patients who may benefit from mTORC2 inhibitor therapy.

SOX13 is a novel prognostic biomarker and associates with immune infiltration in breast cancer.

Background: The transcription factor, SOX13 is part of the SOX family. SOX proteins are crucial in the progression of many cancers, and some correlate with carcinogenesis. Nonetheless, the biological and clinical implications of SOX13 in human breast cancer (BC) remain rarely known. Methods: We evaluated the survival and expression data of SOX13 in BC patients via the UNLCAL, GEPIA, TIMER, and Kaplan-Meier plotter databases. Immunohistochemistry (IHC) was used to verify clinical specimens. The gene alteration rates of SOX13 were acquired on the online web cBioportal. With the aid of the TCGA data, the association between SOX13 mRNA expression and copy number alterations (CNA) and methylation was determined. LinkedOmics was used to identify the genes that co-expressed with SOX13 and the regulators. Immune infiltration and tumor microenvironment evaluations were assessed by ImmuCellAI and TIMER2.0 databases. SOX13 correlated drug resistance analysis was performed using the GDSC2 database. Results: Higher SOX13 expression was discovered in BC tissues in comparison to normal tissues. Moreover, increased gene mutation and amplification of SOX13 were found in BC. Patients with increased SOX13 expression levels showed worse overall survival (OS). Cox analysis showed that SOX13 independently served as a prognostic indicator for poor survival in BC. Further, the expression of SOX13 was also confirmed to be correlated with tumor microenvironment and diverse infiltration of immune cells. In terms of drug sensitivity analysis, we found higher expression level of SOX13 predicts a high IC50 value for most of 198 drugs which predicts drug resistance. Conclusion: The present findings demonstrated that high expression of SOX13 negatively relates to prognosis and SOX13 plays an important role in cancer immunity. Therefore, SOX13 may potentially be adopted as a biomarker for predicting BC prognosis and infiltration of immune cells.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Significance of NKX2-1 as a biomarker for clinical prognosis, immune infiltration, and drug therapy in lung squamous cell carcinoma.

Background: This study was performed to determine the biological processes in which NKX2-1 is involved and thus its role in the development of lung squamous cell carcinoma (LUSC) toward improving the prognosis and treatment of LUSC. Methods: Raw RNA sequencing (RNA-seq) data of LUSC from The Cancer Genome Atlas (TCGA) were used in bioinformatics analysis to characterize NKX2-1 expression levels in tumor and normal tissues. Survival analysis of Kaplan-Meier curve, the time-dependent receiver operating characteristic (ROC) curve, and a nomogram were used to analyze the prognosis value of NKX2-1 for LUSC in terms of overall survival (OS) and progression-free survival (PFS). Then, differentially expressed genes (DEGs) were identified, and Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were used to clarify the biological mechanisms potentially involved in the development of LUSC. Moreover, the correlation between the NKX2-1 expression level and tumor mutation burden (TMB), tumor microenvironment (TME), and immune cell infiltration revealed that NKX2-1 participates in the development of LUSC. Finally, we studied the effects of NKX2-1 on drug therapy. To validate the protein and gene expression levels of NKX2-1 in LUSC, we employed immunohistochemistry(IHC) datasets, The Gene Expression Omnibus (GEO) database, and qRT-PCR analysis. Results: NKX2-1 expression levels were significantly lower in LUSC than in normal lung tissue. It significantly differed in gender, stage and N classification. The survival analysis revealed that high expression of NKX2-1 had shorter OS and PFS in LUSC. The multivariate Cox regression hazard model showed the NKX2-1 expression as an independent prognostic factor. Then, the nomogram predicted LUSC prognosis. There are 51 upregulated DEGs and 49 downregulated DEGs in the NKX2-1 high-level groups. GO, KEGG and GSEA analysis revealed that DEGs were enriched in cell cycle and DNA replication.The TME results show that NKX2-1 expression was positively associated with mast cells resting, neutrophils, monocytes, T cells CD4 memory resting, and M2 macrophages but negatively associated with M1 macrophages. The TMB correlated negatively with NKX2-1 expression. The pharmacotherapy had great sensitivity in the NKX2-1 low-level group, the immunotherapy is no significant difference in the NKX2-1 low-level and high-level groups. The analysis of GEO data demonstrated concurrence with TCGA results. IHC revealed NKX2-1 protein expression in tumor tissues of both LUAD and LUSC. Meanwhile qRT-PCR analysis indicated a significantly lower NKX2-1 expression level in LUSC compared to LUAD. These qRT-PCR findings were consistent with co-expression analysis of NKX2-1. Conclusion: We conclude that NKX2-1 is a potential biomarker for prognosis and treatment LUSC. A new insights of NKX2-1 in LUSC is still needed further research.

[Earlier detection of lung cancer through analysis of circulating tumor DNA from blood]. / Tidigare upptäckt av lungcancer med analys av tumör-DNA i blod.

To investigate the  clinical use of analyzing circulating tumor DNA in a clinical setting we present a pilot study comprising 93 patients from individuals with suspected lung cancer. The study aimed to evaluate the capability of analyzing circulating tumor DNA at the initial medical visit in order to detect genetic changes and mutations associated with lung cancer in plasma samples. Tumor DNA from plasma was extracted and analyzed with Next Generation Sequencing (NGS) and the result was compared with a matched tumor tissue collected in close connection from the same individual. Cancer-associated genetic mutations could be confirmed in about 60 percent of the plasma samples, and we observed a higher degree of conformance in patients with a more advanced disease. The results from the study provide valuable insights for an early clinical use of analyzing circulating tumor DNA in cases of suspected lung cancer, which could contribute to improving early diagnosis and treatment strategies for patients with lung cancer.

Genomic profiling of pleomorphic rhabdomyosarcoma reveals a genomic signature distinct from that of embryonal rhabdomyosarcoma.

Pleomorphic rhabdomyosarcoma (PRMS) is a rare and highly aggressive sarcoma, occurring mostly in the deep soft tissues of middle-aged adults and showing a variable degree of skeletal muscle differentiation. The diagnosis is challenging as pathologic features overlap with embryonal rhabdomyosarcoma (ERMS), malignant Triton tumor, and other pleomorphic sarcomas. As recurrent genetic alterations underlying PRMS have not been described to date, ancillary molecular diagnostic testing is not useful in subclassification. Herein, we perform genomic profiling of a well-characterized cohort of 14 PRMS, compared to a control group of 23 ERMS and other pleomorphic sarcomas (undifferentiated pleomorphic sarcoma and pleomorphic liposarcoma) using clinically validated DNA-targeted Next generation sequencing (NGS) panels (MSK-IMPACT). The PRMS cohort included eight males and six females, with a median age of 53 years (range 31-76 years). Despite similar tumor mutation burdens, the genomic landscape of PRMS, with a high frequency of TP53 (79%) and RB1 (43%) alterations, stood in stark contrast to ERMS, with 4% and 0%, respectively. CDKN2A deletions were more common in PRMS (43%), compared to ERMS (13%). In contrast, ERMS harbored somatic driver mutations in the RAS pathway and loss of function mutations in BCOR, which were absent in PRMS. Copy number variations in PRMS showed multiple chromosomal arm-level changes, most commonly gains of chr17p and chr22q and loss of chr6q. Notably, gain of chr8, commonly seen in ERMS (61%) was conspicuously absent in PRMS. The genomic profiles of other pleomorphic sarcomas were overall analogous to PRMS, showing shared alterations in TP53, RB1, and CDKN2A. Overall survival and progression-free survival of PRMS were significantly worse (p < 0.0005) than that of ERMS. Our findings revealed that the molecular landscape of PRMS aligns with other adult pleomorphic sarcomas and is distinct from that of ERMS. Thus, NGS assays may be applied in select challenging cases toward a refined classification. Finally, our data corroborate the inclusion of PRMS in the therapeutic bracket of pleomorphic sarcomas, given that their clinical outcomes are comparable.

Genomic Profiling of Rare Undifferentiated Sarcomatoid Subtypes of Pancreatic Carcinomas: In Search of Therapeutic Targets.

PURPOSE: The highly aggressive undifferentiated sarcomatoid carcinoma (USC) subtype of pancreatic ductal adenocarcinoma (PDAC) remains poorly characterized because of its rarity. Previous case reports suggest that immune checkpoint inhibitors could be a promising treatment strategy, but the prevalence of established predictive biomarkers of response is largely unknown. The objective of this study was to leverage comprehensive genomic profiling of USC PDAC tumors to determine the prevalence of biomarkers associated with potential response to targeted therapies. METHODS: USC tumors (n = 20) underwent central pathology review by a board-certified gastrointestinal pathologist to confirm the diagnosis. These samples were compared with non-USC PDAC tumors (N = 5,562). Retrospective analysis of DNA and RNA next-generation sequencing data was performed. RESULTS: USC PDACs were more frequently PD-L1+ by immunohistochemistry than non-USC PDAC (63% v 16%, respectively, P < .001). Furthermore, USC PDAC had an increase in neutrophils (8.99% v 5.55%, P = .005) and dendritic cells (1.08% v 0.00%, q = 0.022) and an increased expression of PDCD1LG2 (4.6% v 1.3%, q = 0.001), PDCD1 (2.0% v 0.8%, q = 0.060), and HAVCR2 (45.9% v 21.7%, q = 0.107) than non-USC PDAC. Similar to non-USC PDAC, KRAS was the most commonly mutated gene (86% v 90%, respectively, P = 1). CONCLUSION: To our knowledge, this work represents the largest molecular analysis of USC tumors to date and showed an increased expression of immune checkpoint genes in USC tumors. These findings provide evidence for further investigation into immune checkpoint inhibitors in USC tumors.

Analysis of the diagnostic performance of PAX1/SOX1 gene methylation in cervical precancerous lesions and its role in triage diagnosis.

Methylation panels, tools for investigating epigenetic changes associated with diseases like cancer, can identify DNA methylation patterns indicative of disease, providing diagnostic or prognostic insights. However, the application of methylation panels focusing on the sex-determining region Y-box 1 (SOX1) and paired box gene 1 (PAX1) genes for diagnosing cervical lesions is under-researched. This study aims to examine the diagnostic performance of PAX1/SOX1 gene methylation as a marker for cervical precancerous lesions and its potential application in triage diagnosis. From September 2022 to April 2023, 181 patients with abnormal HPV-DNA tests or cytological exam results requiring colposcopy were studied at Hubei Maternal and Child Health Hospital, China. Data were collected from colposcopy, cytology, HPV-DNA tests, and PAX1/SOX1 methylation detection. Patients were categorized as control, cervical intraepithelial neoplasia Grade 1 (CIN1), Grade 2 (CIN2), Grade 3 (CIN3), and cervical cancer (CC) groups based on histopathology. We performed HPV testing, liquid-based cytology, and PAX1/SOX1 gene methylation testing. We evaluated the diagnostic value of methylation detection in cervical cancer using DNA methylation positivity rate, sensitivity, specificity, and area under the curve (AUC), and explored its potential for triage diagnosis. PAX1/SOX1 methylation positivity rates were: control 17.1%, CIN1 22.5%, CIN2 100.0%, CIN3 90.0%, and CC 100.0%. The AUC values for PAX1 gene methylation detection in diagnosing CIN1+, CIN2+, and CIN3+ were 0.52 (95% confidence interval [CI]: 0.43-0.62), 0.88 (95% CI: 0.80-0.97), and 0.88 (95% CI: 0.75-1.00), respectively. Corresponding AUC values for SOX1 gene methylation detection were 0.47 (95% CI: 0.40-0.58), 0.80 (95% CI: 0.68-0.93), and 0.92 (95% CI: 0.811-1.00), respectively. In HPV16/18-negative patients, methylation detection showed sensitivity of 32.4% and specificity of 83.7% for CIN1+. For CIN2+ and CIN3+, sensitivity was all 100%, with specificities of 83.0% and 81.1%. Among the patients who underwent colposcopy examination, 166 cases had cytological examination results ≤ASCUS, of which 37 cases were positive for methylation, and the colposcopy referral rate was 22.29%. PAX1/SOX1 gene methylation detection exhibits strong diagnostic efficacy for cervical precancerous lesions and holds significant value in triage diagnosis.

Development of 42 marker panel for in-depth study of cancer associated fibroblast niches in breast cancer using imaging mass cytometry.

Imaging Mass Cytometry (IMC) is a novel, and formidable high multiplexing imaging method emerging as a promising tool for in-depth studying of tissue architecture and intercellular communications. Several studies have reported various IMC antibody panels mainly focused on studying the immunological landscape of the tumor microenvironment (TME). With this paper, we wanted to address cancer associated fibroblasts (CAFs), a component of the TME very often underrepresented and not emphasized enough in present IMC studies. Therefore, we focused on the development of a comprehensive IMC panel that can be used for a thorough description of the CAF composition of breast cancer TME and for an in-depth study of different CAF niches in relation to both immune and breast cancer cell communication. We established and validated a 42 marker panel using a variety of control tissues and rigorous quantification methods. The final panel contained 6 CAF-associated markers (aSMA, FAP, PDGFRa, PDGFRb, YAP1, pSMAD2). Breast cancer tissues (4 cases of luminal, 5 cases of triple negative breast cancer) and a modified CELESTA pipeline were used to demonstrate the utility of our IMC panel for detailed profiling of different CAF, immune and cancer cell phenotypes.

Overweight as a biomarker for concomitant thyroid cancer in patients with Graves' disease.

The incidence of concomitant thyroid cancer in Graves' disease varies and Graves' disease can make the diagnosis and management of thyroid nodules more challenging. Since the majority of Graves' disease patients primarily received non-surgical treatment, identifying biomarkers for concomitant thyroid cancer in patients with Graves' disease may facilitate planning the surgery. The aim of this study is to identify the biomarkers for concurrent thyroid cancer in Graves' disease patients and evaluate the impact of being overweight on cancer risk. This retrospective cohort study analyzed 122 patients with Graves' disease who underwent thyroid surgery at Seoul St. Mary's Hospital (Seoul, Korea) from May 2010 to December 2022. Body mass index (BMI), preoperative thyroid function test, and thyroid stimulating hormone receptor antibody (TR-Ab) were measured. Overweight was defined as a BMI of 25 kg/m² or higher according to the World Health Organization (WHO). Most patients (88.5%) underwent total or near-total thyroidectomy. Multivariate analysis revealed that patients who were overweight had a higher risk of malignancy (Odds ratios, 3.108; 95% confidence intervals, 1.196-8.831; p = 0.021). Lower gland weight and lower preoperative TR-Ab were also biomarkers for malignancy in Graves' disease. Overweight patients with Graves' disease had a higher risk of thyroid cancer than non-overweight patients. A comprehensive assessment of overweight patients with Graves' disease is imperative for identifying concomitant thyroid cancer.

The role of IGFBP-3 in tumor development and progression: enlightenment for diagnosis and treatment.

IGFBP-3 is aberrantly expressed in many tumor types, and its serum and tumor tissue levels provide auxiliary information for assessing the degree of tumor malignancy and patient prognosis, making it a potential therapeutic target for human malignancies and conferring it remarkable clinical value for determining patient prognosis. In this review, we provide a comprehensive overview of the aberrant expression, diverse biological effects, and clinical implications of IGFBP-3 in tumors and its role as a potential prognostic marker and therapeutic target for tumors. In addition, we summarize the signaling pathways through which IGFBP-3 exerts its effects. IGFBP-3 comprises an N-terminal, an intermediate region, and a C-terminal structural domain, each exerting different biological effects in several tumor cell types in an IGF-dependent/non-independent manner. IGFBP-3 shares an intricate relationship with the tumor microenvironment, thereby affecting tumor growth. Overall, IGFBP-3 is an essential regulatory factor that mediates tumor occurrence and progression. Gaining deeper insights into the fundamental characteristics of IGFBP-3 and its role in various tumor types will provide new perspectives and allow for the development of novel strategies for cancer diagnosis, treatment, and prognostic evaluation.

[Auxiliary diagnosis and prognosis evaluation of KIF4A, RAD51AP1 and CDKN3 in esophageal cancer].

To investigate the expression of mRNA in esophageal cancer (ESCA) tissues and its potential and diagnostic and prognostic value by high-throughput sequencing data. Using the Cancer Genome Atlas Program (TCGA) database in USA by integrative bioinformatics analysis methods, the gene expression profiles and clinical data of 173 patients with ECSA were collected. The mRNA expression levels in ESCA tissue and para-cancerous tissue samples were analyzed using DESeq2, edgeR and limma to screen the differentially expressed genes (DEGs). DEGs-related protein network diagrams were drawn. GO and KEGG function enrichment analysis were performed and the hub genes were screened and the survival analysis of hub genes was analyzed. Genes related to the prognosis of ESCA were selected and their prognostic value in ESCA was analyzed. Finally, the receiver operating characteristic curve was drawn to evaluate its diagnostic value. The results showed that using TCGA cancer data, a total of 620 up-regulated DEGs and 668 down-regulated DEGs with significant differential expression between ESCA and para-cancerous tissues were screened. DEGs were mainly involved in receptor complexes, ubiquitin ligase complexes, etc., playing GTPase activity, phospholipid binding, and other molecular functions, and participating in the regulation of intracellular substance transport, small molecule metabolism, and other biological processes. Protein functional enrichment analysis showed that these proteins were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, Epstein-Barr virus infection, neutrophil extracellular trap formation, and other pathways involved in the formation and development process of ESCA. Survival analysis showed that the overall survival rate of ESCA patients with high expression of KIF4A, RAD51AP1, and CDKN3 was significantly shortened, and the difference was statistically significant (P<0.05). Furthermore, the areas under the curve (AUC) of KIF4A, RAD51AP1, and CDKN3 for diagnosing esophageal cancer were 0.956, 0.951 and 0.979, respectively, with sensitivities and specificities both exceeding 80%. Additionally, ROC results of the combined diagnostic model of these three genes showed an AUC of 0.979, with sensitivities and specificities of 0.914 and 1, respectively. This indicates that KIF4A, RAD51AP1 and CDKN3 have individual or combined auxiliary diagnostic value for ESCA. In conclusion, KIF4A, RAD51AP1 and CDKN3 have high diagnostic efficiency for ESCA, and their increased expression is closely related to the prognosis, suggesting that these three genes could be used as auxiliary diagnostic and prognostic factors for ESCA.