University Of California Santa Cruz Research Articles

Multi-omic analysis identifies the molecular mechanism of hepatocellular carcinoma with cirrhosis

Hepatocellular carcinoma with cirrhosis promotes the advancement of malignancy and the development of fibrosis in normal liver tissues. Understanding the pathological mechanisms underlying the development of HCC with cirrhosis is important for developing effective therapeutic strategies. Herein, the RNA-sequencing (RNA-seq) data and corresponding clinical features of patients with HCC were extracted from The Cancer Genome Atlas (TCGA) database using the University of California Santa Cruz (UCSC) Xena platform. The enrichment degree of hallmarkers for each TCGA-LIHC cohort was quantified by ssGSEA algorithm. Weighted gene co-expression network analysis (WGCNA) revealed two gene module eigengenes (MEs) associated with cirrhosis, namely, MEbrown and MEgreen. Analysis of these modules using AUCell showed that MEbrown had higher enrichment scores in all immune cells, whereas MEgreen had higher enrichment scores in malignant cells. The CellChat package revealed that both immune and malignant cells contributed to the fibrotic activity of myofibroblasts through diverse signaling pathways. Additionally, spatial transcriptomic data showed that hepatocytes, proliferating hepatocytes, macrophages, and myofibroblasts were located in closer proximity in HCC tissues. These cells may potentially participate in the process of stimulating myofibroblast fibrotic activity, which may be related to the development of liver fibrosis. In summary, we made full use of multi-omics data to explore gene networks and cell types that may be involved in the development and progression of cirrhosis in HCC.

Role of CENPL, DARS2, and PAICS in determining the prognosis of patients with lung adenocarcinoma.

Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancers, and is the leading cause of tumor-related death. Lung adenocarcinoma (LUAD) is the most prevalent subtype of NSCLC. Although significant progress of LUAD treatment has been made under multimodal strategies, the prognosis of advanced LUAD is still poor due to recurrence and metastasis. There is still a lack of reliable markers to evaluate the LUAD prognosis. This study aims to explore novel biomarkers and construct a prognostic model to predict the prognosis of LUAD patients. The Genomic Data Commons-The Cancer Genome Atlas-Lung Adenocarcinoma (GDC-TCGA-LUAD) dataset was downloaded from the University of California, Santa Cruz (UCSC) Xena browser. The GSE72094 and GSE13213 datasets and corresponding clinical information were downloaded from the Gene Expression Omnibus (GEO) database. By analyzing these datasets using DESeq2 R package and Limma R package, differentially expressed genes (DEGs) were found. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to analyze possible enrichment pathways. A protein-protein interaction (PPI) network was constructed to explore possible relationship among DEGs by using the STRING database. A survival analysis was performed to identify reliable prognostic genes using the Kaplan-Meier method. A multi-omics analysis was performed using the Gene Set Cancer Analysis (GSCA). The Tumor Immune Estimation Score (TIMER) database was used to analyze the association between prognostic genes and immune infiltration. A Spearman correlation analysis was conducted to examine the correlation between prognostic genes and drug sensitivity. A multivariate Cox regression was used to identify independent prognostic factors. Next, a nomogram was constructed using the rms R package. Finally, the expressions of aspartyl-tRNA synthetase 2 (DARS2) and phosphoribosyl aminoimidazole carboxylase (PAICS) were detected using immunohistochemistry (IHC). We screened out 30 DEGs prior to functional enrichment and PPI network analysis revealing potential enrichment pathways and interactions of these DEGs. Then survival analysis revealed the CENPL, DARS2, and PAICS expression was negatively correlated with LUAD prognosis. Additionally, multi-omics analysis showed CENPL, DARS2, and PAICS expressions were significantly higher in LUAD tissues than normal tissues. CENPL, DARS2, and PAICS were all up-regulated in late stage and M1 stage. Correlation analysis indicated CENPL, DARS2, and PAICS may not be associated with activation or suppression of immune cells. Drug sensitivity analysis revealed many potentially effective drugs and small molecule compounds. Moreover, we successfully constructed a robust and stable nomogram by combining the DARS2 and PAICS expression with other clinicopathological variables. Finally, IHC results showed DARS2 and PAICS were significantly up-regulated in LUAD. The CENPL, DARS2, and PAICS expression was negatively correlated with LUAD prognosis. A prognostic model, which integrated DARS2, PAICS, and other clinicopathological variables, was able to effectively predict LUAD patients prognosis.

PRNP is a pan-cancer prognostic and immunity-related to EMT in colorectal cancer.

Prion protein gene (PRNP) is widely expressed in a variety of tissues. Although the roles of PRNP in several cancers have been investigated, no pan-cancer analysis has revealed its relationship with tumorigenesis and immunity. Comprehensive analyses were conducted on The Cancer Genome Atlas (TCGA) Pan-Cancer dataset from the University of California Santa Cruz (UCSC) database to determine the expression of PRNP and its potential prognostic implications. Immune infiltration and enrichment analysis methods were used to ascertain correlations between PRNP expression levels, tumor immunity, and immunotherapy. Additionally, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods were employed to examine possible signaling pathways involving PRNP. In vitro experiments using CCK-8 assay, Wound healing assay, and Transwell assay to detect the effect of Cellular prion protein (PrPC) on proliferation, migration, and invasion in colorectal cancer (CRC) cells. The expression levels of epithelial-mesenchymal transition (EMT)-related proteins (N-cadherin, E-cadherin, Vimentin and Snail) were detected by western blot. Among most cancer types, PRNP is expressed at high levels, which is linked to the prognosis of patients. PRNP expression is strongly associated with immune infiltrating cells, immunosuppressive cell infiltration and immune checkpoint molecules. In addition to tumor mutation burden (TMB), substantial correlations are detected between PRNP expression and microsatellite instability (MSI) in several cancers. In vitro cell studies inferred that PrPC enhanced the proliferation, migration, invasion, and EMT of CRC cells. PRNP serves as an immune-related prognostic marker that holds promise for predicting outcomes related to CRC immunotherapy while simultaneously promoting cell proliferation, migration, and invasion activities. Furthermore, it potentially plays a role in governing EMT regulation within CRC.

Signature identification based on immunogenic cell death-related lncRNAs to predict the prognosis and immune activity of patients with endometrial carcinoma.

Endometrial carcinoma (EC) is one of the most prevalent gynecologic malignancies and requires further classification for treatment and prognosis. Long non-coding RNAs (lncRNAs) and immunogenic cell death (ICD) play a critical role in tumor progression. Nevertheless, the role of lncRNAs in ICD in EC remains unclear. This study aimed to explore the role of ICD related-lncRNAs in EC via bioinformatics and establish a prognostic risk model based on the ICD-related lncRNAs. We also explored immune infiltration and immune cell function across prognostic groups and made treatment recommendations. A total of 552 EC samples and clinical data of 548 EC patients were extracted from The Cancer Genome Atlas (TCGA) database and University of California Santa Cruz (UCSC) Xena, respectively. A prognostic-related feature and risk model was developed using the least absolute shrinkage and selection operator (LASSO). Subtypes were classified with consensus cluster analysis and validated with t-Distributed Stochastic Neighbor Embedding (tSNE). Kaplan-Meier analysis was conducted to assess differences in survival. Infiltration by immune cells was estimated by single sample gene set enrichment analysis (ssGSEA), Tumor IMmune Estimation Resource (TIMER) algorithm. Quantitative polymerase chain reaction (qPCR) was used to detect lncRNAs expression in clinical samples and cell lines. A series of studies was conducted in vitro and in vivo to examine the effects of knockdown or overexpression of lncRNAs on ICD. In total, 16 ICD-related lncRNAs with prognostic values were identified. Using SCARNA9, FAM198B-AS1, FKBP14-AS1, FBXO30-DT, LINC01943, and AL161431.1 as risk model, their predictive accuracy and discrimination were assessed. We divided EC patients into high-risk and low-risk groups. The analysis showed that the risk model was an independent prognostic factor. The prognosis of the high- and low-risk groups was different, and the overall survival (OS) of the high-risk group was lower. The low-risk group had higher immune cell infiltration and immune scores. Consensus clustering analysis divided the samples into four subtypes, of which cluster 4 had higher immune cell infiltration and immune scores. A prognostic signature composed of six ICD related-lncRNAs in EC was established, and a risk model based on this signature can be used to predict the prognosis of patients with EC.

Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer

Ovarian cancer (OC) is one of the most prevalent and fatal malignant tumors of the female reproductive system. Our research aimed to develop a prognostic model to assist inclinical treatment decision-making.Utilizing data from The Cancer Genome Atlas (TCGA) and copy number variation (CNV) data from the University of California Santa Cruz (UCSC) database, we conducted analyses of differentially expressed genes (DEGs), gene function, and tumor microenvironment (TME) scores in various clusters of OC samples.Next, we classified participants into low-risk and high-risk groups based on the median risk score, thereby dividing both the training group and the entire group accordingly. Overall survival (OS) was significantly reduced in the high-risk group, and two independent prognostic factors were identified: age and risk score. Additionally, three genes—C-X-C Motif Chemokine Ligand 10 (CXCL10), RELB, and Caspase-3 (CASP3)—emerged as potential candidates for an independent prognostic signature with acceptable prognostic value. In Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, pathways related to immune responses and inflammatory cell chemotaxis were identified. Cellular experiments further validated the reliability and precision of our findings. In conclusion, necroptosis-related genes play critical roles in tumor immunity, and our model introduces a novel strategy for predicting the prognosis of OC patients.

Comprehensive pan-cancer analysis identifies the RNA-binding protein LRPPRC as a novel prognostic and immune biomarker

AimsRNA-binding proteins (RBPs) play pivotal roles in carcinogenesis and immunotherapy. Leucine-rich pentapeptide repeat-containing protein (LRPPRC) is crucial for RNA polyadenylation, transport, and stability. Although recent studies have suggested LRPPRC's potential role in tumor progression, its significance in tumor prognosis, diagnosis, and immunology remains unclear. Main methodsWe comprehensively analyzed LRPPRC expression in tumors using various databases, including Human Transcriptome Cell Atlas (HTCA), University of California Santa Cruz (UCSC), Human Protein Atlas (HPA), Sangerbox, TISIDB, GeneMANIA, GSCALite, and CellMiner. We examined the correlation between LRPPRC expression level and prognosis, immune infiltration, immunotherapy, methylation, biological function, and drug sensitivity. Single-cell analysis was performed using Tumor Immune Single Cell Hub (TISCH) and CancerSEA software. Patients with acute myeloid leukemia (AML) were categorized based on LRPPRC levels for functional and immune infiltration analyses. The role of LRPPRC in cancer was validated using in vitro experiments. Key findingsOur findings revealed that LRPPRC was highly expressed in almost all cancer types, indicating its significant prognostic and diagnostic potential. Notably, LRPPRC was associated with diverse immune features, such as immune cell infiltration, immune checkpoint genes, tumor mutational burden, and microsatellite instability, suggesting its value in guiding immunotherapy strategies. Within AML, the high-expression group had lower levels of immune cells, including CD8+ T cells. In vitro experiments confirmed the inhibitory effects of LRPPRC knockdown on AML cell proliferation. SignificanceThis study highlights LRPPRC as a reliable pan-cancer prognostic and immune biomarker, particularly in AML. It lays the groundwork for future research on LRPPRC-targeted cancer therapies.

The diagnostic, prognostic, drug sensitivity and ceRNA internet of PPP4R1 in liver hepatocellular carcinoma (LIHC).

Recent studies have reported a role of protein phosphatase 4 regulatory subunit 1 (PPP4R1) in cancer development. However, its expression, diagnostic significance, prognostic value and biological function in liver hepatocellular carcinoma (LIHC) are not known. The expression level of PPP4R1 in pan-cancer was evaluated by analyzing publicly accessible data from the University of California Santa Cruz (UCSC) Xena database. The diagnostic value of PPP4R1 for tumors was assessed using receiver operating characteristic (ROC) curves, whereas the impact of PPP4R1 on tumor prognosis was determined using Kaplan-Meier survival curves, and a prognostic model for LIHC was established using cox regression analysis. In addition, analysis of the correlation between PPP4R1 and anti-cancer drugs using Spearman's correlation coefficient was carried out. Four databases, miRWalk (mRNA-miRNA interactions), MicroT-CDS (mRNA-miRNA interactions), LncBase (miRNA-lncRNA interactions) and Encyclopedia of RNA Interactomes (ENCORI), were used to predict the competitive endogenous RNA (ceRNA) regulatory network of PPP4R1. Finally, the expression of PPP4R1 protein levels was verified using experiments. The findings indicated that the PPP4R1 expression level in cancerous tissues was notably greater than in adjacent tissues (P<0.05). PPP4R1 showed diagnostic significance for 14 tumors based on the ROC curves results area under the curve >0.7. Furthermore, the Kaplan-Meier survival plots demonstrated that PPP4R1 exhibited prognostic significance for all five tumors (P<0.05). According to the cox regression analysis, LIHC patients' prognosis was independently influenced by pathological stage, M stage, and PPP4R1 (P<0.05). The drug sensitivity analysis revealed a positive correlation between the expression level of PPP4R1 and the half maximal inhibitory concentration (IC50) of fludarabine. Additionally, the ceRNA network prediction indicated that the FGD5 antisense RNA 1 (FGD5-AS1)-hsa-miR-22-3p-PPP4R1 ceRNA network could potentially contribute to the progression of LIHC. The experimental results showed that the expression level of PPP4R1 protein was higher in cancer tissues than in paracancerous tissues. PPP4R1 has diagnostic value in most cancers, and high expression of PPP4R1 is associated with poor prognosis, drug resistance and natural killer cell-mediated toxicity, particularly in LIHC. Therefore, PPP4R1 may be a prognostic biomarker and a potential target for immunotherapy in LIHC.

Trackplot: a fast and lightweight R script for epigenomic enrichment plots.

BigWig files serve as essential inputs in epigenomic data visualization. However, current R packages for visualizing these files are limited, slow, and burdened by numerous dependencies. We introducetrackplot, a minimal R script designed for the rapid generation of integrative genomics viewer (IGV) style track plots, profile plots, and heatmaps from bigWig files. This script offers speed, owing to its reliance onbwtool, resulting in performance gains ofseveral magnitudescompared to equivalentpackages.The script is lightweight, requiring only thedata.tableandbwtoolpackages as primary dependencies. Notably, the plots are generated in base R graphics,eliminatingthe need for additional packages.trackplotqueries the University of California Santa Cruz (UCSC) genome browser for gene models thereby enhancing the reproducibility of analyses. The script extends its support to general transfer format (GTF) further enhancing its versatility. This tool addresses the gaps in existing bigWig visualization approaches by offering speed, simplicity, and minimal dependencies, thereby presenting a valuable asset to researchers in the fields of epigenomics. trackplot is implemented in R is made available under MIT license at https://github.com/PoisonAlien/trackplot.

FHIP1A-DT is a potential novel diagnostic, prognostic, and therapeutic biomarker of colorectal cancer: A pan-cancer analysis

BackgroundFHIP1A-DT is a long non-coding RNA (lncRNA) obtained by divergent transcription whose mechanism in pan-cancer and colorectal cancer (CRC) is unclear. We elucidated the molecular mechanism of FHIP1A-DT through bioinformatics analysis and in vitro experiments. MethodsPan-cancer and CRC data were downloaded from the University of California, Santa Cruz (UCSC) Genome Browser and the Cancer Genome Atlas (TCGA). We analyzed FHIP1A-DT expression and its relationship with clinical stage, diagnosis, prognosis, and immunity characteristics in pan-cancer. We also analyzed FHIP1A-DT expression in CRC and explored the relationship between FHIP1A-DT and CRC diagnosis and prognosis. Then, we analyzed the correlation between FHIP1A-DT and drug sensitivity, immune cell infiltration, and the biological processes involved in FHIP1A-DT. The competing endogenous RNA (ceRNA) regulatory network associated with FHIP1A-DT was explored. External validation was conducted using external data sets GSE17538 and GSE39582 and in vitro experiments. ResultsFHIP1A-DT expression was different in pan-cancer and had excellent diagnostic and prognostic capability for pan-cancer. FHIP1A-DT was also related to the pan-cancer tumor mutation burden (TMB), microsatellite instability (MSI), and immune cell content. FHIP1A-DT was downregulated in CRC, where patients with CRC with low FHIP1A-DT expression had a worse prognosis. A nomogram combined with FHIP1A-DT expression demonstrated excellent predictive ability for prognosis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that FHIP1A-DT was associated with epigenetic modification and regulated many cancer-related pathways. The ceRNA network demonstrated the potential gene regulation of FHIP1A-DT. FHIP1A-DT was related to many chemotherapeutic drug sensitivities and immune cell infiltration such as CD4 memory resting T cells, monocytes, plasma cells, neutrophils, and M2 macrophages. The FHIP1A-DT expression and prognostic analysis of GSE17538 and GSE39582, and qPCR yielded similar external verification results. ConclusionFHIP1A-DT was a novel CRC-related lncRNA related to CRC diagnosis, prognosis, and treatment sensitivity. It could be used as a significant CRC biomarker in the future.

A prognostic and immune infiltration analysis of ZEB2 in pan-cancer

[Objective] ZEB2 is known to be participated in several cancers, yet there is no comprehensive analysis about its function in pan-cancer. This study aimed to investigate the role ZEB2 plays in pan-cancer. [Methods] The data was downloaded from the University of California Santa Cruz (UCSC) Xena and the Cancer Genome Atlas (TCGA). The mRNA expression status of ZEB2 was studied in the TCGA_GTEx samples, TCGA samples and paired samples in TCGA, respectively, and protein expression status was obtained from the University of Alabama at Birmingham Cancer data analysis Portal (UALCAN). Kaplan-Meier analysis was applied to 33 kinds of tumors in TCGA, then among the cancers that ZEB2 can affect prognosis, clinical correlation analysis and univariate and multivariate Cox regression analysis were performed. Furthermore, to confirm the prognostic value of ZEB2 in cancers, nomogram models were constructed on lung adenocarcinoma (LUAD) and stomach adenocarcinoma (STAD). The relationship between ZEB2 mRNA expression and immune cell infiltrates was determined by tumor immune estimation resource (TIMER2.0). Protein-protein interaction (PPI) networks were constructed by the STRING. Functional enrichment analysis was also performed using the “ClusterProfiler” package. [Results] ZEB2 was expressed in most tumors, either upregulated or downregulated, and correlated with clinical characteristics in a part of tumors. The expression level of ZEB2 was also found to impact the prognosis of tumors. Additionally, ZEB2 expression was significantly related to immune cells infiltration level in tumor microenvironment. [Conclusion] we propose that ZEB2 has the potential to be a prognostic biomarker and a promising target for cancer immunotherapy.

Pan-cancer analysis of G6PD carcinogenesis in human tumors.

Glucose-6-phosphate dehydrogenase (G6PD) is involved in the catalytic pentose phosphate pathway (PPP), which is closely related to energy metabolism. G6PD plays a crucial role in many types of cancer, but the specific molecular mechanisms of G6PD in cancer remain unclear. Therefore, we investigated the potential oncogenic role of G6PD in various tumors based on The Cancer Genome Atlas (TCGA), the cBioPortal datasets, the University of California Santa Cruz (UCSC) Xena browser and the UALCAN-based online tool. G6PD was highly expressed in several cancer tissues (hepatocellular carcinoma, glioma, and breast cancer) compared with normal tissues and was significantly associated with poor prognosis of hepatocellular carcinoma, clear cell renal cell carcinoma, and breast cancer. Promoter methylation levels of G6PD were lower in Bladder Urothelial Carcinoma (BLCA) (P = 2.77e-02), breast invasive carcinoma (BRCA) (P = 1.62e-12), kidney renal clear cell carcinoma (KIRC) (P = 4.23e-02), kidney renal papillary cell carcinoma (KIRP) (P = 2.64e-03), liver hepatocellular carcinoma (LIHC) (P = 1.76e-02), stomach adenocarcinoma (STAD) (P = 3.50e-02), and testicular germ cell tumors (TGCT) (P = 1.62e-12) and higher in prostate adenocarcinoma (PRAD) (P = 1.81e-09) and uterine corpus endometrial carcinoma (UCEC) (P = 2.96e-04) compared with corresponding normal tissue samples. G6PD expression was positively correlated with the infiltration level of immune cells in most tumors, suggesting that G6PD may be involved in tumor immune infiltration. In addition, the functional mechanism of G6PD also involves "Carbon metabolism", "Glycolysis/Gluconeogenesis", "Pentose phosphate pathway", and "Central carbon pathway metabolism in cancer signaling pathway". This pan-cancer study provides a relatively broad understanding of the oncogenic role of G6PD in various tumors and presents a theoretical basis for the development of G6PD inhibitors as therapeutic drugs for multiple cancers.

Family hypercholesterolemia and LDLR mutations in communities of european origin in southern Brazil: a prospective observational cohort study

Familial hypercholesterolemia (FH) is an autosomal dominant disease characterized by high levels of circulating low-density lipoprotein (LDL) and premature coronary heart events. A quarter of the population of Southern Brazil is affected by hypercholesterolemia and the region has the highest mortality rates due to cardiovascular disease in the country. The aim of this study was to describe LDLR mutations in European descendants with FH living in Southern Brazil. Ten mL of venous blood were taken from 40 patients and used for DNA extraction and subsequent Polymerase Chain Reaction (PCR). The DNA fragments were sequenced and analyzed and the data obtained were compared to reference values from the University of California Santa Cruz (UCSC) Genome Browser. A total of 15 mutations were identified in 38 patients (95% of the total samples). These mutations were located in exons 11 (P518L) and 15 (D727G) in Italian, Portuguese and Spanish descendants and the *105T&gt;G mutation, still undescribed, should be critically evaluated by means of mRNA alteration studies. The present study demonstrated for the first time the presence of the P518L mutation located in exon 11 of the LDLR gene in European descendants living in southern Brazil. This mutation has a high potential to be pathogenic since it is located in a domain responsible for LDLR release from the endoplasmic reticulum (ER).

Ag-tech, agroecology, and the politics of alternative farming futures: The challenges of bringing together diverse agricultural epistemologies

Agricultural-technology (ag-tech) and agroecology both promise a better farming future. Ag-tech seeks to improve the food system through the development of high-tech tools such as sensors, digital platforms, and robotic harvesters, with many ag-tech start-ups promising to deliver increased agricultural productivity while also enhancing food system sustainability. Agroecology incorporates diverse cropping systems, low external resource inputs, indigenous and farmer knowledge, and is increasingly associated with political calls for a more just food system. Recently, demand has grown for the potentially groundbreaking benefits of their convergence, with the University of California, Santa Cruz (UCSC) attempting just such a union. Building on its combined expertise in engineering and agroecology, as well as a longstanding reputation as a socially progressive institution, university administrators believe that UCSC could produce a unique, socially just form of ag-tech designed for small, low-resource farmers—a rare contribution given ag-tech’s tendency to cater primarily to large-scale agribusiness. This paper examines the complexities of uniting agroecology and ag-tech through interviews with agroecologists, engineers, and social scientists involved in UCSC’s ag-tech initiative. Within the setting of a historically radical yet neoliberalizing university, I find that significant epistemic and structural barriers exist for agroecology and ag-tech to come together on an even playing field. This case study contributes to broader discussions of the future of food and farming by focusing on the contours and challenges of a widely called-for agricultural collaboration, highlighting its difficulty but also areas of possibility in a particularly rich, contested context.

Pan-cancer analysis of PCAT6 and its effect on oesophageal squamous cell carcinoma cell proliferation and migration

Bioinformatics methods were used to analyze the role of PCAT6 in a variety of tumors and verify its role in oesophageal squamous cell carcinoma (ESCC) EC109 cells. The pan-cancer dataset was downloaded from the University of California Santa Cruz (UCSC) database to analyze the expression of PCAT6 in pan-cancer and its relationship with prognosis, clinical features, and immune infiltration. The expression and prognosis of PCAT6 in ESCC were verified by Gene Expression Omnibus (GEO) and Kaplan-Meier database. CCK8, colony formation, wound healing, Transwell cell invasion (CI), and cell migration (CM) assays were used to detect the effect of PCAT6 knockdown on the ability of ESCC cell proliferation (CP), CI and CM. Gene Set Enrichment Analysis was used to analyze the signaling pathways involved in the regulation of PCAT6. Quantitative real-time PCR and western blotting were used to examine the expression of cancer stem cell-related markers and the activation of JAK/STAT pathway in ESCC after PCAT6 knockdown. PCAT6 is significantly up-regulated in a variety of tumor tissues, and its expression is closely related to prognosis, clinical features and immune infiltration. High expression of PCAT6 leads to poor prognosis in ESCC patients. In ESCC EC109 cells, PCAT6 knockdown inhibited the ability of CP, CI, CM, and stemness, and inhibited the activation of JAK/STAT signaling pathway. PCAT6 expression is elevated in a variety of tumors. PCAT6 plays an oncogene role in ESCC by activating the JAK/STAT signaling pathway.

Systematic pan-cancer analysis of the potential tumor diagnosis and prognosis biomarker P4HA3.

Purpose: Prolyl 4-hydroxylase subunit alpha 3 (P4HA3) is implicated in several cancers' development. However, P4HA3 has not been reported in other cancers, and the exact mechanism of action is currently unknown. Materials and methods: First, the expression profile of P4HA3 was analyzed using a combination of the University of California Santa Cruz (UCSC) database, Cancer Cell Line Encyclopedia (CCLE) database, and Genotype-Tissue Expression (GTEx) database. UniCox and Kaplan-Meier were used to analyze the predictive value of P4HA3. The expression of P4HA3 was analyzed in clinical staging, immune subtypes, and Molecular subtypes. Secondly, the correlation of P4HA3 with immunomodulatory genes, immune checkpoint genes, RNA modification genes, immune cell infiltration, cancer-related functional status, tumor stemness index, DNA mismatch repair (MMR) genes and DNA Methyltransferase was examined. The role of P4HA3 in DNA methylation, copy number variation (CNV), mutational status, tumor mutational burden (TMB), and microsatellite instability (MSI) was also analyzed. In addition, gene set enrichment analysis (GSEA) was used to explore the potential functional mechanisms of P4HA3 in pan-cancer. Finally, P4HA3-related drugs were searched in CellMiner, Genomics of Drug Sensitivity in Cancer (GDSC), and Cancer Therapeutics Response Portal (CTRP) databases. Results: P4HA3 is significantly overexpressed in most cancers and is associated with poor prognosis. P4HA3 is strongly associated with clinical cancer stage, immune subtypes, molecular subtypes, immune regulatory genes, immune checkpoint genes, RNA modifier genes, immune cell infiltration, cancer-related functional status, tumor stemness index, MMR Gene, DNA Methyltransferase, DNA methylation, CNV, mutational status, TMB, and MSI are closely related. Available enrichment analysis revealed that P4HA3 is associated with the epithelial-mesenchymal transition and immune-related pathways. There are currently 20 drugs associated with P4HA3. Conclusion: In human pan-cancer, P4HA3 is associated with poor patient prognosis and multiple immune cells and may be a novel immunotherapeutic target. It may act on tumor progression through the epithelial-mesenchymal transition (EMT) pathway.

Decreased DIO3OS Expression Predicts Poor Prognosis in Hepatocellular Carcinoma and is Associated with Immune Infiltration.

Hepatocellular carcinoma has become one of the most shared cancers in the whole world because of its high morbidity, poor survival rate, and low recovery rate. LncRNA DIO3 opposite strand upstream RNA (DIO3OS) has been reported to be obviously important in several human cancers, while its biological function in hepatocellular carcinoma (HCC) remains unclear. Here, DIO3OS gene expression data and clinical information of HCC patients were extracted from the Cancer Genome Atlas (TCGA) database and the university of California Santa Cruz (UCSC) Xena database. In our study, the Wilcoxon rank sum test was used to compare DIO3OS expression between healthy individuals and HCC patients. It was found that patients with HCC had significantly lower DIO3OS expression than healthy individuals. Furthermore, Kaplan-Meier curves and Cox regression analysis showed that high DIO3OS expression tended to predict better prognosis and higher survival rate in HCC patients. In addition, the gene set enrichment analysis (GSEA) assay was used to annotate the biological function of DIO3OS. It was found that DIO3OS was significantly correlated with immune invasion in HCC. This was also aided by the subsequent ESTIMATE assay. Our study provides a novel biomarker and therapeutic strategy for patients with hepatocellular carcinoma.

An integrative analysis revealing cuproptosis-related lncRNAs signature as a novel prognostic biomarker in hepatocellular carcinoma.

Background: Cuproptosis is a newly defined form of cell death, whether cuproptosis involved in hepatocellular carcinoma (HCC) remains elusive. Method: We obtained patients' RNA expression data and follow-up information from University of California Santa Cruz (UCSC) and The Cancer Genome Atlas (TCGA). We analyzed the mRNA level of Cuproptosis-related genes (CRGs) and performed univariate Cox analysis. Liver hepatocellular carcinoma (LIHC) was chosen for further investigation. Real-Time quantitative PCR (RT-qPCR), Western blotting (WB), Immunohistochemical (IHC), and Transwell assays were used to determine expression patterns and functions of CRGs in LIHC. Next, we identified CRGs-related lncRNAs (CRLs) and differentially expressed CRLs between HCC and normal cases. Univariate Cox analysis, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to construct the prognostic model. Univariate and multivariate Cox analysis was used to assess whether the risk model can act as an independent risk factor of overall survival duration. Different risk groups performed immune correlation analysis, tumor mutation burden (TMB), and Gene Set Enrichment Analysis (GSEA) analysis were performed in different risk groups. Finally, we assessed the performance of the predictive model in drug sensitivity. Results: CRGs expression levels have significant differences between tumor and normal tissues. High expression of Dihydrolipoamide S-Acetyltransferase (DLAT) correlated to metastasis of HCC cells and indicated poor prognosis for HCC patients. Our prognostic model consisted of four cuproptosis-related lncRNA (AC011476.3, AC026412.3, NRAV, MKLN1-AS). The prognostic model performed well in predicting survival rates. The results from Cox regression analysis suggested that risk score can serve as an independent prognostic element for survival durations. Survival analysis revealed that low risk patients have extended survival periods compared with those with high risk. The results of the immune analysis indicated that risk score has a positive correlation with B cell and CD4+ T cell Th2, while has a negative relationship with endothelial cell and hematopoietic cells. Besides, immune checkpoint genes have higher expression folds in the high-risk set than in the low-risk set. The high-risk group had higher rates of genetic mutation than the low-risk set while having a shorter survival time. GSEA revealed the signaling pathways enriched in the high-risk group were mostly immune-related, while metabolic-related pathways were enriched in the low-risk group. Drugs sensitivity analysis indicated that our model has the ability to predict the efficacy of clinical treatment. Conclusion: The Cuproptosis-related lncRNAs prognostic formula is a novel predictor of HCC patients' prognosis and drug sensitivity.

Hsa_circ_0072309 is a prognostic biomarker and is correlated with immune infiltration in gastric cancer

BackgroundHsa_circ_0072309 has been identified as a tumor suppressor in several carcinomas. However, its precise role in gastric cancer (GC) remains largely unknown. This study was aimed to explore the precise role of Hsa_circ_0072309 in GC. MethodsThe transcriptional and clinical data of stomach adenocarcinoma were downloaded using the University of California SantaCruz (UCSC) Xena browser. The circular RNA (circRNA) datasets were obtained from the Gene Expression Omnibus (GEO) database. The expression profile and survival analysis of differentially expressed micro RNAs (DEMIs) and differentially expressed messenger RNAs (DEMs) were performed. Correlations between the expression and immune infiltration of the DEMS were studied. Additionally, the expression of hsa_circ_0072309 in GC tissues and cell lines were validated, and the relationship between its expression and clinical features was investigated. Gain- and loss-of function experiments and molecular interaction experiments were also conducted. ResultsOverall, 7 differentially expressed circRNAs, 13 DEMIs, and 17 DEMs were screened. Two DEMIs (hsa_miR-34a-3p and hsa_miR-326) and five DEMs (C7, MARCKSL1, UBE2T, OLR1, and HOXC11) showed significant differences in the high- and low-risk groups. The most significantly enriched Gene Ontology terms were the circadian regulation of gene expression and protein binding. The most significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways were the PI3K-Akt and Ras signal pathways. Additionally, six genes were significantly correlated with immune infiltration. The real-time quantitative PCR (RT-qPCR) results revealed a significant downregulation of hsa_circ_0072309 in GC tissues related to tumor size, vascular invasion, and lymph node metastasis. A hsa_circ_0072309 overexpression suppressed whereas a hsa_circ_0072309 knockdown promoted GC cells proliferation and migration in vitro; in addition, hsa_circ_0072309 could directly bind to has-miR-34a-3p and has-miR-330-5p. ConclusionsHsa_circ_0072309 is a potential diagnostic biomarker for GC, and complement component 7 may be a tumor suppressor. These may potentially predict the prognosis of patients with GC and may become new therapeutic targets.

EXOC3L1: A Novel Prognostic Biomarker Correlated with Immune Infiltration in Esophageal Squamous Cell Carcinoma.

BACKGROUND Exocyst complex component 3-like 1 (EXOC3L1) is ubiquitously present in multiple organs. However, its role in esophageal squamous cell carcinoma (ESCC) remains unknown. The aim of this study was to explore the relationship between EXOC3L1 and ESCC. MATERIAL AND METHODS A total of 652 normal samples and 82 ESCC samples obtained from the University of California Santa Cruz (UCSC) Xena were applied to detect the expression difference of EXOC3L1. GSE53625 with 179 paired samples and GSE161533 with 28 paired samples were used for validation. The correlation between clinicopathological features and EXOC3L1 expression was calculated. Kaplan-Meier method was employed to assess the prognostic value of EXOC3L1 in ESCC. Univariate and multivariate Cox regression analyses were carried out to screen the factors contributing to the prognosis of ESCC. In addition, functional enrichment analysis, protein-protein interaction (PPI) network analysis, and immune infiltration analysis were conducted to identify the significantly involved functions of EXOC3L1. RESULTS EXOC3L1 was significantly overexpressed in ESCC compared to normal samples. High expression of EXOC3L1 was associated with worse prognosis, and univariate and multivariate Cox regression analysis demonstrated that EXOC3L1 was an independent prognostic predictor of ESCC. Functional enrichment analysis and immune infiltration analysis disclosed that the expression of EXOC3L1 was correlated with the abundance of several types of immune cells. CONCLUSIONS EXOC3L1 plays a crucial role in the prognosis of ESCC, and it may serve as a reliable biomarker for predicting the survival and a potential therapeutic target for ESCC.

Building a Community Archive: Preserving and Uplifting Stories of Filipino Labor and Migration

Abstract: In April 2022, Watsonville Is in the Heart (WIITH), a research initiative based at the University of California, Santa Cruz (UCSC), launched a new digital archive that preserves histories of Filipino American migration, labor, and community in the Pajaro Valley region of California’s Central Coast. This article describes WIITH’s partnership between UCSC, The Tobera Project, and the descendants of the first Filipinos to settle in the Pajaro Valley. It outlines our methods for critical community-engaged archiving. It also shares the multiple ways in which the WIITH Digital Archive has significantly impacted project stakeholders in the university and the community.