The Cancer Genome Atlas RNA-seq Data Research Articles

Layer Analysis Based on RNA-Seq Reveals Molecular Complexity of Gastric Cancer.

Gastric adenocarcinoma (GA) is a significant global health issue with poor prognosis, despite advancements in treatment. Although molecular classifications, such as The Cancer Genome Atlas (TCGA), provide valuable insights, their clinical utility remains limited. We performed a multi-layered functional analysis using TCGA RNA sequencing data to better define molecular subtypes and explore therapeutic implications. We reanalyzed TCGA RNA-seq data from 142 GA patients with localized disease who received adjuvant chemotherapy. Our approach included probabilistic graphical models and recurrent sparse k-means/consensus cluster algorithms for layer-based analysis. Our findings revealed survival differences among TCGA groups, with the GS subtype showing the poorest prognosis. We identified twelve functional nodes and seven biological layers, each with distinct functions. The combined molecular layer (CML) classification identified three prognostic groups that align with TCGA subtypes. CML2 (GS-like) displayed gene expression related to lipid metabolism, correlating with worse survival. Transcriptomic heterogeneity within the CIN subtype revealed clusters tied to proteolysis and lipid metabolism. We identified a subset of CIN tumors with profiles similar to MSI, termed CIN-MSI-like. Claudin-18, a key gene in proteolysis, was overexpressed across TCGA subtypes, suggesting it is a potential therapeutic target. Our study advances GA biology, enabling refined stratification and personalized treatment. Further studies are needed to translate these findings into clinical practice.

Keratin 17 and A2ML1 are negative prognostic biomarkers in non-small cell lung cancer

Although the overall prognosis for patients with non-small cell lung cancer (NSCLC) has improved over the past several decades, there are still survival differences that are not accurately defined by clinicopathological factors. Thus, there is an unmet clinical need to develop novel approaches to enhance prognostic accuracy for these patients. Keratin 17 (K17) is a negative prognostic biomarker in a wide range of cancer types, including pancreatic ductal adenocarcinoma, head and neck squamous cell carcinoma, and pulmonary adenocarcinoma (LUAD), but has yet to be investigated as a prognostic biomarker in primary lung squamous cell carcinoma (LSCC). Based on TCGA RNA-seq data, alpha-2-macroglobulin like 1 (A2ML1), a protease inhibitor, is highly correlated with K17 in other solid tumors, including pancreatic ductal adenocarcinoma and is also a prognostic biomarker for LSCC, although the prognostic accuracy of A2ML1 for LUAD has not been tested. Thus, we hypothesized that A2ML1 expression correlates with K17 expression and that K17/A2ML1 co-testing could provide complementary prognostic data for NSCLC. The aims of this study were to explore K17 and A2ML1 as dual prognostic biomarkers, using publicly available gene expression databases [The Cancer Genome Atlas (TCGA)] LSCC (n=266), LUAD (n=271)] and multiplexed immunohistochemistry (mIHC) on representative sections of LSCC (n=104) and LUAD (n=107) from two major academic medical centers. Our results suggest that using either mRNA or mIHC-based methods, combined K17 and A2ML1 testing provides information, independent of other clinicopathologic variables, that could impact treatment decisions for patients with NSCLC.

Abstract 3034: Krüppel-like factors in regulation of gastric cancer progression

Abstract Introduction: Gastric cancer (GC) is the third leading cause of cancer-associated mortality and the fifth most frequently diagnosed cancer worldwide. The development and progression of GC is a complicated multistage process subjected to dynamic changes in gene regulation. Investigating the effects of these changes is therefore critical for improving our knowledge about GC initiation and progression. Krüppel-like factors (KLFs) are evolutionarily conserved zinc finger-containing transcription factors with altered expressions and diverse regulatory functions in GC. We previously reported that there is loss of KLF4 in GC. Here we report that KLF4 is a crucial regulator of KLF5 expression and vice versa and together they regulate GC cell behavior. Methods: The Cancer Genome Atlas (TCGA) and pan cancer data of differential expressions of KLFs in GC was analyzed. TCGA RNAseq and clinical data for the differential expression status of KLF genes in normal and cancerous tissues and the clinicopathological association was accessed from the UALCAN web portal. The expressions of KLF4 and KLF5 in human normal stomach and GC and orthotopic xenografts were detected by immunohistochemistry (IHC). KLF4, KLF5 cross regulation was evaluated by gene manipulation of each gene individually and checking the expression of the other factor in GC cells. The effect of KLFs on GC cell proliferation, migration, and invasion was determined by Ki67 staining of tissues, PrestoBlue cell viability assay, scratch wound and transwell cell invasion assays. Results and Conclusion: Our results indicated that not only KLF4 and KLF5 have contrasting expressions and effects in GC but also these two factors cross regulate each other. While lower expressions of KLF4 was found in human GC and orthotopic xenografts, increased expression of KLF5 was found in both human GC tissue and orthotopic xenografts. KLF4 silencing and CRISPR/Cas9 knockdown in human GC cells resulted in increased expression of KLF5 which was associated with increased GC cell proliferation and invasiveness. Interestingly, KLF5 knockdown by CRISPR/Cas9 in human GC cells on the other hand resulted in increased expression of KLF4, which was associated with decreased GC cell growth. Our data therefore suggests that the differential expressions of KLF4 and KLF5 might serve as valuable prognostic markers in GC. Citation Format: Sooraj Kakkat, Prabhat Suman, Sandeep Goswami, Sujit Basu, Martin J. Heslin, Elba A. Turbat-Herrera, Veronica Ramirez Alcantara, Chandrani Sarkar, Debanjan Chakroborty. Krüppel-like factors in regulation of gastric cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3034.

LRRC59 promotes the progression of oral squamous cell carcinoma by interacting with SRP pathway components and enhancing the secretion of CKAP4-containing exosomes

BackgroundAs a ribosome receptor, LRRC59 was thought to regulate mRNA translation on the ER membrane. Evidence suggests that LRRC59 is overexpressed in a number of human malignancies and is associated with poor prognoses, but its primary biological function in the development of oral squamous cell carcinoma (OSCC) remains obscure. ObjectiveThe purpose of this study is to investigate at the expression changes and functional role of LRRC59 in OSCC. MethodsLRRC59 gene expression and correlation with prognosis of OSCC patients were first examined using the data from The Cancer Genome Atlas (TCGA) databases. Following that, a series of functional experiments, including cell counting kit-8, cell cycle analysis, wound healing assays, and transwell assays, were carried out to analyze the biological roles of LRRC59 in tumor cells. Mechanistically, we employed Tandem Affinity Purification-Mass Spectrometry (TAP-MS) approach to isolate and identify protein complexes of LRRC59. Downstream regulatory proteins of LRRC59 were verified through immunoprecipitation and immunofluorescence experiments. Furthermore, we isolated exosomes from OSCC cell supernatant and conducted co-culture experiments to examine the effect of LRRC59 knockdown on OSCC cells. ResultsIn samples from OSCC patients, LRRC59 was highly expressed and correlated with poor prognoses. Moreover, the gene sets analysis based on TCGA RNA-seq data indicated that LRRC59 seemed to be strongly related with protein secretory and OSCC migration. Upregulated levels of LRRC59 are more prone to lymph node metastasis in OSCC patients. LRRC59 knockdown impaired the ability of OSCC cell proliferation, migration, and invasion invitro. Mechanistically, our TAP-MS data situate LRRC59 in a functional nexus for mRNA translation regulation via interactions with SRP pathway components, translational initiation factors, CRD-mediated mRNA stabilization factors. More importantly, we found that LRRC59 interacted with cytoskeleton-associated protein 4 (CKAP4) and promoted the formation of CKAP4-containing exosomes. We also revealed that the LRRC59-CKAP4 axis was a crucial regulator of CKAP4-containing exosome secretion in OSCC cells for migration and invasion. ConclusionsTherefore, based on our findings, LRRC59 may serve as a potential biomarker for OSCC patients, and LRRC59-induced exosome secretion via the CKAP4 axis may serve as a potential therapeutic target for OSCC.

Abstract PO-011: Analysis of nuclear receptor expression in head and neck cancer

Abstract Background: The nuclear receptor (NR) superfamily contains a wide array of transcription factors responsible for cellular metabolism, inflammation, differentiation, and hormonal functions. For 45 years these receptors have been of interest in head and neck squamous cell carcinoma (HNSCC) treatment and prevention, especially retinoic acid receptor (RAR), peroxisome proliferator-activated receptor (PPAR), and vitamin D receptor (VDR) families. In the current study we examined expression patterns of these receptors in The Cancer Genome Atlas (TCGA). Methods: TCGA RNA-Seq data within the cBioportal platform comparing HNSCC samples (n=515 patients/samples) to normal tissue (n=82 patients/samples) was interrogated for significant differences in nuclear receptor expression. Genes with a z-score relative to normal samples (log RNA-Seq V2 RSEM normalized) greater than +2 or less than -2 in ≥50% of cases were considered significant. Unpaired, two-tailed t-tests were used to analyze comparisons in nuclear receptor genes’ z-scores across multiple clinical and pathologic parameters, p<0.05 was deemed significant. Statistical stringency for differential gene expression conformed to cBioportal and the University of Alabama at Birmingham’s Cancer Data Analysis Portal (UALCAN). Results: Of the 46 NR genes and 19 NR cofactors examined, ninety nine percent of tumor samples in the TCGA had some form of NR gene ‘alteration’ compared to normal tissue. These alterations predominantly encompass expression up- or down-regulation. NR genes Peroxisome Proliferator Activated Receptor Gamma (PPARγ) and Retinoic Acid Receptor Related Orphan Receptor C (RORC) (both in the thyroid hormone receptor-like family), and the NR cofactor, Nuclear Receptor Coactivator 1 (NCOA1), were differentially expressed and downregulated in tumors compared to normal tissue. Differences in specific NR expression varied significantly with HPV status (30 NRs), organ site (oral cavity vs hypopharynx & larynx; 20 NRs), tumor size (T1/2 vs. T3/4; 21 NRs), gender (male vs. female; 7 NRs); tumor staging (stage I/II vs. stage III/IV; 6 NRs); lymph node status (N0 vs. N+; 5 NRs), smoking history (smokers vs. non-smokers; 3 NRs), and patient race (White vs. Black/African American; 2 NRs). Conclusions: In prior studies of nuclear receptors in aerodigestive cancer, the retinoid receptor axis was downregulated, and a subsequent goal was stimulation and restoration of activity with natural or synthetic retinoids as a rationale for treatment. Presently, we have discovered significant decreases in PPARγ expression and are targeting this receptor with thiazolidinediones in a series of preclinical and human trials in a similar rationale to promote restoration of normal signaling and events like maturation. Here, we observed significant differences in a variety of parameters of several receptors associated with risk factors, stage, race, and gender that are observed and may become the focus of interest in future targeting efforts. Citation Format: Lindsey Mortensen, Beverly R. Wuertz, Frank G. Ondrey. Analysis of nuclear receptor expression in head and neck cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-011.

Y-Chromosome-Linked Genes Are Associated With Sex-Related Head-Neck Squamous Cell Carcinoma Survival.

To define novel gene biomarkers for prognosis of head and neck squamous cell carcinoma (HNSCC) patients' survival. Retrospective study. The Cancer Genome Atlas (TCGA) HNSCC RNA-Seq dataset. Coexpressed gene clusters were extracted from TCGA RNA-seq data using our previously published method (EPIG). Kaplan-Meier estimator was then used for overall survival-relevant analysis, with patients partitioned into 3 groups based on gene expression levels: female, male_low, and male_high. Male had better overall survival than female and male with higher expression level of Y-chromosome-linked (Y-linked) genes had significantly better survival than those with lower expression levels. In addition, male with a higher expression level of Y-linked genes showed even better survival when they have a higher level of coexpressed cluster of genes related to B or T cell immune response. Other clinical conditions related to immune responses also consistently showed favorable effects on the Y-linked genes for survival estimation. Male patients with higher expression level of Y-linked genes also have significantly higher tumor/normal tissue (T/N) ratio of those genes and higher level of several immune responses related clinical measurements (eg, lymphocyte and TCR related). Male patients with lower expression level of Y-linked genes benefited from radiation-only treatment. The favorable role of a cluster of coexpressed Y-linked genes in HNSCC patients' survival is potentially associated with elevated level of immune responses. These Y-linked genes could serve as useful prognostic biomarkers for HNSCC patients' survival estimation and treatment.

TCGA RNA-Seq and Tumor-Infiltrating Lymphocyte Imaging Data Reveal Cold Tumor Signatures of Invasive Ductal Carcinomas and Estrogen Receptor-Positive Human Breast Tumors.

Comparative studies of immune-active hot and immune-deserted cold tumors are critical for identifying therapeutic targets and strategies to improve immunotherapy outcomes in cancer patients. Tumors with high tumor-infiltrating lymphocytes (TILs) are likely to respond to immunotherapy. We used the human breast cancer RNA-seq data from the cancer genome atlas (TCGA) and classified them into hot and cold tumors based on their lymphocyte infiltration scores. We compared the immune profiles of hot and cold tumors, their corresponding normal tissue adjacent to the tumor (NAT), and normal breast tissues from healthy individuals from the Genotype-Tissue Expression (GTEx) database. Cold tumors showed a significantly lower effector T cells, lower levels of antigen presentation, higher pro-tumorigenic M2 macrophages, and higher expression of extracellular matrix (ECM) stiffness-associated genes. Hot/cold dichotomy was further tested using TIL maps and H&E whole-slide pathology images from the cancer imaging archive (TCIA). Analysis of both datasets revealed that infiltrating ductal carcinoma and estrogen receptor ER-positive tumors were significantly associated with cold features. However, only TIL map analysis indicated lobular carcinomas as cold tumors and triple-negative breast cancers (TNBC) as hot tumors. Thus, RNA-seq data may be clinically relevant to tumor immune signatures when the results are supported by pathological evidence.

Excavation of diagnostic biomarkers and construction of prognostic model for clear cell renal cell carcinoma based on urine proteomics.

Clear cell renal cell carcinoma (ccRCC) is the most common pathology type in kidney cancer. However, the prognosis of advanced ccRCC is unsatisfactory. Thus, early diagnosis becomes one of the most important research priorities of ccRCC. However, currently available studies about ccRCC lack urine-related further studies. In this study, we applied proteomics to search urinary biomarkers to assist early diagnosis of ccRCC. In addition, we constructed a prognostic model to assist judge patients' prognosis. Urine which was used to perform 4D label-free quantitative proteomics was collected from 12 ccRCC patients and 11 non-tumor patients with no urinary system diseases. The urine of 12 patients with ccRCC confirmed by pathological examination after surgery was collected before operatoin. Bioinformatics analysis was used to describe the urinary proteomics landscape of these patients with ccRCC. The top ten proteins with the highest expression content were selected as the basis for subsequent validation. Urine from 46 ccRCC patients and 45 control patients were collected to use for verification by enzyme linked immunosorbent assay (ELISA). In order to assess the prognostic value of urine proteomics, a prognostic model was constructed by COX regression analysis on the intersection of RNA-sequencing data in The Cancer Genome Atlas (TCGA) database and our urine proteomic data. 133 proteins differentially expressed in the urinary samples were found and 85 proteins (Fold Change, FC>1.5) were identified up-regulated while 48 down-regulated (FC<0.5). Top 10 proteins including S100A14, PKHD1L1, FABP4, ITIH2, C3, C8G, C2, ATF6, ANGPTL6, F13B were performed ELISA to verify. The results showed that PKHD1L1, ANGPTL6, FABP4 and C3 were statistically significant (P<0.05). We performed multivariate logistic regression analysis and plotted a nomogram. Receiver operating characteristic (ROC) curve indicted that the diagnostic efficiency of combined indicators is satisfactory (Aare under curve, AUC=0.835). Furthermore, the prognostic value of the urine proteomics was explored through the intersection between urine proteomics and TCGA RNA-seq data. Thus, COX regression analysis showed that VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 were statistically significant (P<0.05). Our study indicated that the application of urine proteomics to explore diagnostic biomarkers and to construct prognostic models of renal clear cell carcinoma is of certain clinical value. PKHD1L1, ANGPTL6, FABP4 and C3 can assist to diagnose ccRCC. The prognostic model constituted of VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 can significantly predict the prognosis of ccRCC patients, but this still needs more clinical trials to verify.

Abstract 2107: Development a customized panel with clinical application potential for transcriptome analyses in selected cancer types using FFPE specimens

Abstract Purpose: HTG EdgeSeq is a Next Generation Sequencing (NGS) based RNA Sequencing (RNA Seq) platform using a quantitative nuclease protection chemistry that enables extraction-free quantitation of mRNA/miRNAs with significantly reduces FFPE sample requirements compared to standard RNA-Seq, which makes it a feasible option for potential clinical applications. A customized gene panel was designed and developed for detection gene signatures. Procedure: The customized gene panel consists of 1327 genes, including 900 genes in signaling pathways in oncology &amp; immuno-oncology, which including Nature Kill (NK) cells, neutrophils, Plasmacytoid dendritic cells (pDCs), DCs, monocytes, Tregs, B cells, tumor associated macrophages (TAMs), TGFβ, EMT, interferon-γ signature, IL-17, β-catenin etc. and 15 house-keeping genes. The validation included in silico probe design, feasibility testing, data comparison with The Cancer Genome Atlas (TCGA) and precision studies in six cancer indications including: Non-Small-Cell Lung Cancer (NSCLC), Head and Neck Squamous Cell Carcinoma (HNSCC), Hepatocellular Carcinoma (HCC), Colorectal Cancer (CRC), gastric cancer (OC), ovarian cancer (GC). Data Summary: After the In-silico probe design for all genes the custom probe pool for quality control test in biological samples was performed by evaluating directional and expected expression of 1327 selected genes in 59 FFPE samples from six indications. All probes performed as expected according to specification; gene expression signatures data were consistent with the different cancer indication tested. Expected differential expression of the selected genes was based on RNA-Seq data as reported in TCGA. In addition, principal component analysis (PCA) performed on the entire data et, showed a distinct clustering of samples by indication, demonstrating that the custom panel was able to reliably identify each indication. For the validation, precision studies including inter-well, inter-day, inter-processor, inter-sequencer and site-to-site comparisons were performed using FFPE tissue lysate pools prepared from each of the 6 indications. Predefined acceptance criteria are ≥ 90% of all Lin`s Concordance Correlation Coefficients (LCCC) comparisons to be greater than 0.90. The results showed that the predefined acceptance criteria were met, which are 95.9% of LCCC &amp;gt; 0.90 for inter-well repeatability, and 100% of LCCC &amp;gt;0.90 for inter-day, inter-processor, inter-sequencer and inter-site comparisons. Conclusions: The designed panel met all the predefined quality and analytical acceptance criteria, also, the reported results is corrected with TCGA RNA-Seq data, and the precision studies confirmed its performance. Customized gene panel can be possibly utilized for potential predictive and prognostic biomarkers identification to inform new cancer therapies development. Citation Format: Vittorio D'Urso, Dorothee Foernzler, Dennis O’Rourke, Danyi Wang, Jorge F Sanchez-Garcia, Heidi Giese, Thomas Clarke IV, XiaoZhe (Janet) Wang, Andreas Machl, Ti Cai, Juergen Scheuenpflug, Zheng Feng. Development a customized panel with clinical application potential for transcriptome analyses in selected cancer types using FFPE specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2107.

Abstract 641: VirMAP for cancer: Characterization of the intratumoral virome in virally-associated cancers and a resource for investigators

Abstract Background: A major barrier to understanding the role of viruses in cancer progression has been the lack of sensitivity of current tools to identify and assemble viral genomes in an untargeted way. Here, we utilize our novel VirMAP algorithm to identify eukaryotic and prokaryotic viruses associated with cancers, using RNA sequencing data from The Cancer Genome Atlas (TCGA). Methods: VirMAP was used to analyze TCGA RNA-Seq data derived from primary tumor tissues, with a focus on cancers with known viral associations (cervical, ovarian, head and neck, liver, stomach and esophagus). Previously published survival data were matched with viral signatures for exploratory analysis. Ancom-BC, a differential abundance pipeline, was utilized to screen for viruses which drive outcome. Overall survival (OS) was assessed using the Kaplan-Meier method, and p-values were calculated using log-rank test. Multivariate analysis (MVA) was done using the Cox proportional hazards model to control for age, sex, stage, and histology. Results: Viral sequence recovery (among 723 billion sequencing reads from 2090 patients) was at least equal to previously published algorithms such as Kraken, but with higher taxonomic resolution. Cancers with high viral loads such as cervical cancer demonstrated high recovery rates (0.012% of all sequencing reads mapped to viral taxa, followed by 0.004% for liver, 0.0018% for head and neck squamous cell, 0.0016% for stomach, 0.0009% for esophageal, and 0.0002% for ovarian). There was a wide range of viral signature richness, with cervical cancer showing the highest viral read count predominated by HPV serotypes; in contrast, stomach cancer had lower abundance but contained over 300 unique viral taxa. Exploratory clinical analysis revealed novel correlations between viral signatures and OS. In cervical cancer, presence of HPV45 predicted worse survival (median OS 837 days vs 4086, p=0.0043); MVA demonstrated hazard ratio (HR) of 5.7 [2.6-11.4, p&amp;lt;0.0001]. In stomach cancer, patients often had more than one viral taxon present (mean 3.7, range 0-18); presence of 7 or more unique taxa predicted worse OS (median OS 403 days vs 1153, p=0.0001). MVA showed HR 1.1 for every additional taxon (p=0.0004). Conclusions: VirMAP performs deep characterization of the tumor-associated virome in both high and low abundance settings, with generation of partial genome reconstructions and strain level taxonomic classification. Utilizing publicly available platforms such as TCGA, clinical and correlative published data can be leveraged to better understand the nuanced pleotropic effects of the tumor virome on cancer progression. Citation Format: Yongwoo D. Seo, Neal Bhutiani, Matthew C. Wong, Ashish V. Damania, Golnaz Morad, Matthew Lastrapes, Alexander J. Lazar, Jennifer A. Wargo, Nadim J. Ajami. VirMAP for cancer: Characterization of the intratumoral virome in virally-associated cancers and a resource for investigators [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 641.

The EBV Gastric Cancer Resource (EBV-GCR): A Suite of Tools for Investigating EBV-Associated Human Gastric Carcinogenesis.

Epstein-Barr virus (EBV) causes lifelong infection in over 90% of the world's population. EBV infection leads to several types of B cell and epithelial cancers due to the viral reprogramming of host-cell growth and gene expression. EBV is associated with 10% of stomach/gastric adenocarcinomas (EBVaGCs), which have distinct molecular, pathological, and immunological characteristics compared to EBV-negative gastric adenocarcinomas (EBVnGCs). Publicly available datasets, such as The Cancer Genome Atlas (TCGA), contain comprehensive transcriptomic, genomic, and epigenomic data for thousands of primary human cancer samples, including EBVaGCs. Additionally, single-cell RNA-sequencing data are becoming available for EBVaGCs. These resources provide a unique opportunity to explore the role of EBV in human carcinogenesis, as well as differences between EBVaGCs and their EBVnGC counterparts. We have constructed a suite of web-based tools called the EBV Gastric Cancer Resource (EBV-GCR), which utilizes TCGA and single-cell RNA-seq data and can be used for research related to EBVaGCs. These web-based tools allow investigators to gain in-depth biological and clinical insights by exploring the effects of EBV on cellular gene expression, associations with patient outcomes, immune landscape features, and differential gene methylation, featuring both whole-tissue and single-cell analyses.

Stromal Interaction Molecule 1 (STIM1) is a Potential Prognostic Biomarker and Correlates with Immune Infiltrates in Solid Tumors.

Increasing evidence has shown that stromal interaction molecule 1 (STIM1), a key subunit of store-operated Ca2+ entry (SOCE), is closely associated with tumor growth, development, and metastasis. However, there is no report of a comprehensive assessment of STIM1 in pan-cancer. This study aimed to perform a general analysis of STIM1 in human tumors, including its molecular characteristics, functional mechanisms, clinical significance, and immune infiltrates correlation based on pan-cancer data from The Cancer Genome Atlas (TCGA). Gene expression analysis was investigated using TCGA RNA-seq data, the Tumor Immune Estimation Resource (TIMER). Phosphorylation analysis was undertaken using the Clinical Proteomic Tumor Analysis Consortium (CP-TAC) and the PhosphoNET database. Genetic alterations of STIM1 were analyzed using cBioPortal. Prognostic analysis was via the R package "survival" function and the Kaplan-Meier plotter. Functional enrichment analysis was via by the R package "cluster Profiler" function. The association between STIM1 and tumor-infiltrating immune cells and immune markers was by the R package "GSVA" function and TIMER. STIM1 was differentially expressed and associated with distinct clinical stages in multiple tumors. The phosphorylation of STIM1 at S673 is highly expressed in clear cell renal carcinoma and lung adenocarcinoma tumors compared to normal tissues. STIM1 genetic alterations correlate with poor prognosis in several tumors, including ovarian cancer and lung squamous cell carcinomas. High STIM1 expression is associated with good or poor prognosis across diverse tumors. Overall survival (OS) analysis indicated that STIM1 is a favorable prognostic factor for patients with BRCA, KIRC, LIHC, LUAD, OV, SARC, and UCEC, and is a risk prognostic factor for BLCA, KIRP, STAD, and UVM. There is a close correlation between STIM1 expression and immune cell infiltration, immune-regulated genes, chemokines, and immune checkpoints in a variety of tumors. STIM1 functions differently in diverse tumors, playing an oncogenic or antitumor role. Moreover, It may serve as a prognostic biomarker and an immunotherapy target across multiple tumors.

Analysis of aberrant miRNA-mRNA interaction networks in prostate cancer to conjecture its molecular mechanisms.

MicroRNAs (miRNAs) capable of post-transcriptionally regulating mRNA expression are essential to tumor occurrence and progression. This study aims to find negatively regulatory miRNA-mRNA pairs in prostate adenocarcinoma (PRAD). Combining The Cancer Genome Atlas (TCGA) RNA-Seq data with Gene Expression Omnibus (GEO) mRNA/miRNA expression profiles, differently expressed miRNA/mRNA (DE-miRNAs/DE-mRNAs) were identified. MiRNA-mRNA pairs were screened by miRTarBase and TarBase, databases collecting experimentally confirmed miRNA-mRNA pairs, and verified in 30 paired prostate specimens by real-time reverse transcription polymerase chain reaction (RT-qPCR). The diagnostic values of miRNA-mRNA pairs were measured by receiver operation characteristic (ROC) curve and Decision Curve Analysis (DCA). DAVID-mirPath database and Connectivity Map were employed in GO/KEGG analysis and compounds research. Interactions between miRNA-mRNA pairs and phenotypic features were analyzed with correlation heatmap in hiplot. Based on TCGA RNA-Seq data, 22 miRNA and 14 mRNA GEO datasets, 67 (20 down and 47 up) miRNAs and 351 (139 up and 212 down) mRNAs were selected. After screening from 2 databases, 8 miRNA (up)-mRNA (down) and 7 miRNA (down)-mRNA (up) pairs were identified with Pearson's correlation in TCGA. By external validation, miR-221-3p (down)/GALNT3 (up) and miR-20a-5p (up)/FRMD6 (down) were chosen. The model combing 4 signatures possessed better diagnostic value. These two miRNA-mRNA pairs were significantly connected with immune cells fraction and tumor immune microenvironment. The diagnostic model containing 2 negatively regulatory miRNA-mRNA pairs was established to distinguish PRADs from normal controls.

Establishment and Validation of a Tumor Microenvironment Prognostic Model for Predicting Bladder Cancer Survival Status Based on Integrated Bioinformatics Analyses.

This study was designed to analyze the characteristics of bladder cancer-related genes and establish a prognostic model of bladder cancer. The model passed an independent external validation set test. Differentially expressed genes (DEGs) related to bladder cancer were obtained from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx) databases. WGCNA was used to fit the GSE188715, TCGA, and GTEx RNA-Seq data. Fusing the module genes with the high significance in tumor development extracted from WGCNA and DEGs screened from multiple databases. 709 common prognostic-related genes were obtained. The 709 genes were enriched in the Gene Ontology database. Univariate Cox and LASSO regression analyses were used to screen out 21 prognostic-related genes and further multivariate Cox regression established a bladder cancer prognostic model consisting of 8 genes. After the eight-gene prognostic model was established, the Human Protein Atlas (HPA) database, GEPIA 2, and quantitative real-time PCR (qRT-PCR) verified the differential expression of these genes. Gene Set Enrichment Analysis and immune infiltration analysis found biologically enrichment pathways and cellular immune infiltration related to this bladder cancer prognostic model. Then, we selected bladder cancer patients in the TCGA database to evaluate the predictive ability of the model on the training set and validation set. The overall survival status of the two TCGA patient groups in the training and the test sets was obtained by Kaplan–Meier survival analysis. Three-year survival rates in the training and test sets were 37.163% and 25.009% for the low-risk groups and 70.000% and 62.235% for the high-risk groups, respectively. Receiver operating characteristic curve (ROC) analysis showed that the areas under the curve (AUCs) for the training and test sets were above 0.7. In an external independent validation database GSE13507, Kaplan–Meier survival analysis showed that the three-year survival rates of the high-risk and the low-risk groups in this database were 56.719% and 76.734%, respectively. The AUCs of the ROC drawn in the external validation set were both above 0.65. Here, we constructed a prognostic model of bladder cancer based on data from the GEO, TCGA, and GTEx databases. This model has potential prognostic and clinical auxiliary diagnostic value.

Removing unwanted variation from large-scale RNA sequencing data with PRPS

Accurate identification and effective removal of unwanted variation is essential to derive meaningful biological results from RNA sequencing (RNA-seq) data, especially when the data come from large and complex studies. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we examined several sources of unwanted variation and demonstrate here how these can significantly compromise various downstream analyses, including cancer subtype identification, association between gene expression and survival outcomes and gene co-expression analysis. We propose a strategy, called pseudo-replicates of pseudo-samples (PRPS), for deploying our recently developed normalization method, called removing unwanted variation III (RUV-III), to remove the variation caused by library size, tumor purity and batch effects in TCGA RNA-seq data. We illustrate the value of our approach by comparing it to the standard TCGA normalizations on several TCGA RNA-seq datasets. RUV-III with PRPS can be used to integrate and normalize other large transcriptomic datasets coming from multiple laboratories or platforms.

Overexpression of B7-H3 Is Associated With Poor Prognosis in Laryngeal Cancer.

The immune checkpoint molecule, B7-H3, which belongs to the B7 family, has been shown to be overexpressed in various cancers. Its role in tumors is not well defined, and many studies suggest that it is associated with poor clinical outcomes. The effect of B7-H3 on laryngeal cancer has not been reported. This study investigated the expression of B7-H3 in laryngeal squamous cell carcinoma (LSCC), and its relationship with clinicopathological factors and prognosis of LSCC patients. The gene expression quantification data and clinical data of LSCC retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were analyzed to determine the diagnostic and prognostic roles of B7-H3. Quantitative real-time polymerase chain reaction (qRT-PCR) was then performed to determine the gene expression level of B7-H3 between LSCC tissues and paired normal adjacent tissues. In addition, TCGA RNA-seq data was analyzed to evaluate the expression level of B7 family genes. Next, the protein expression of B7-H3 and CD8 in LSCC was determined using immunohistochemistry and immunofluorescence. qRT-PCR results showed that the expression level of B7-H3 mRNA was significantly higher in LSCC tissues than in adjacent normal tissues. Similar results were obtained from the TCGA analysis. The expression of B7-H3 was significantly associated with T stage, lymph node metastasis, and pathological tumor node metastasis (TNM) stage, and it was also an independent factor influencing the overall survival time (OS) of patients with LSCC. In addition, B7-H3 was negatively correlated with CD8+T cells. These results show that B7-H3 is upregulated in LSCC. Therefore, B7-H3 may serve as a biomarker of poor prognosis and a promising therapeutic target in LSCC.

O26: SIGMA RECEPTORS IN BREAST CANCER – EXAMINING THEIR LIGAND MEDIATED MECHANISMS OF CANCER CELL DEATH AND POTENTIAL FOR CLINICAL DIAGNOSTICS

Abstract Introduction Sigma receptors (SRs) are regularly overexpressed in cancer however their functions remain unknown. Certain Sigma1-receptor (Sig1R) ligands trigger death in breast cancer (BCa) cells but not in non-cancerous breast cells (NCB). In stressed cells, Sig1R is vital to the pro-survival unfolded protein response (UPR). Cancer cells depend on UPR signalling for survival, investigating Sig1R mediated mechanisms in BCa vs. NCB might uncover novel and targetable weaknesses in cancer. Method UPR activation by Sig1R antagonist IPAG was examined in BCa cells by Western blotting. Sig1R and UPR marker localizations were examined by immunofluorescence. SR gene expression between 141 matched breast tumour tissue and tumour adjacent normal samples was compared using RNAseq data from The Cancer Genome Atlas (TCGA). Merged microarray datasets were used to compare SR expression in 399 primary breast tumours with relapse (BCaR) vs. 352 without relapse (BCaNR). Result Relative to non-cancerous human mammary epithelial cells, Sig1R expression was lowest in MCF7s and highest in MDA-MB-468s. IPAG induced differential temporal activation of all three branches of the UPR in MCF7 and tamoxifen-resistant, low Sig1R expressing cell line LY2. TCGA RNAseq data highlighted SR overexpression in BCa particularly in the basal subtype. Microarray data showed both oestrogen receptor (ER)+ and ER- BCaR primaries had elevated SIGMAR1 compared to BCaNR primaries of the same respective ER status. Conclusion BCa cells are dependent on Sig1R mediated signalling. Sig1R expression might indicate the propensity of breast tumours to relapse. Thus, Sig1R represents a potential target in BCa, particularly for aggressive subtypes. Take-home message The Sigma-1 receptor (Sig1R) has a vital but unknown pro-survival function in cancer; Sig1R ligands cause death in cancer cells while sparing non-cancerous ones. Characterizing Sig1R mediated signalling may reveal novel, selective therapeutic targets in cancer.

Re-Evaluate Fusion Genes in Prostate Cancer.

Background:Thousands of gene fusions have been reported in prostate cancer, but their authenticity, incidence, and tumor specificity have not been thoroughly evaluated, nor have their genomic characteristics been carefully explored.Methods:We developed FusionVet to dedicatedly validate known fusion genes using RNA-seq alignments. Using FusionVet, we re-assessed 2727 gene fusions reported from 36 studies using the RNA-seq data generated by The Cancer Genome Atlas (TCGA). We also explored their genomic characteristics and interrogated the transcriptomic and DNA methylomic consequences of the E26 transformation-specific (ETS) fusions.Results:We found that nearly two-thirds of reported fusions are intra-chromosomal, and 80% of them were formed between 2 protein-coding genes. Although most (76%) genes were fused to only 1 partner, we observed many fusion hub genes that have multiple fusion partners, including ETS family genes, androgen receptor signaling pathway genes, tumor suppressor genes, and proto-oncogenes. More than 90% of the reported fusions cannot be validated by TCGA RNA-seq data. For those fusions that can be validated, 5% were detected from tumor and normal samples with similar frequencies, and only 4% (120 fusions) were tumor-specific. The occurrences of ERG, ETV1, and ETV4 fusions were mutually exclusive, and their fusion statuses were tightly associated with overexpressions. Besides, we found ERG fusions were significantly co-occurred with PTEN deletion but mutually exclusive with common genomic alterations such as SPOP mutation and FOXA1 mutation.Conclusions:Most of the reported fusion genes cannot be validated by TCGA samples. The ETS family and androgen response genes were significantly enriched in prostate cancer–specific fusion genes. Transcription activity was significantly repressed, and the DNA methylation was significantly increased in samples carrying ERG fusion.

Abstract 5880: Pan-cancer gene expression analysis of tissue microarray using EdgeSeq Oncology Biomarker Panel and a cross-comparison with ERBB3 immunohistochemical analysis

Abstract Background: Antibody-drug conjugate (ADC) is one of the recent break-through approaches of targeting tumors, in which chemotherapeutic agents are attached via linkers to antibodies recognizing membrane proteins on tumor cells and the agents are delivered directly into tumor cells. In ADC drug development, it is important to determine the antibody-target gene expression levels in tumor cells as well as normal tissues. Methods: We characterized an established pan-cancer tissue microarray set by gene expression analysis using HTG EdgeSeq Oncology Biomarker Panel (2,867 genes for 2,376 samples including 17 solid cancer types and 25 normal tissues) and compared it with immunohistochemistry (IHC) result of ERBB3, which is a target of anti-ERBB3 ADC, U3-1402, being investigated in clinical trials. Furthermore, these data were compared with RNA-seq and Reverse-Phase Protein Array (RPPA) publicly available data sets from The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE). Results: Gene signature analyses indicated a similarity of cancer type characteristics between the tissue microarray cohort and TCGA data, such as richness of cancer-associated fibroblast and immune cell infiltrate. As expected, ERBB3 mRNA expression results by EdgeSeq were similar to TCGA RNA-seq data, suggesting an epithelial-biased expression pattern. The result of IHC for ERBB3 showed overall correlation with EdgeSeq mRNA data, such as high IHC scores in melanoma. Interestingly several cancer types and subtypes showed low IHC signals relatively to EdgeSeq data, such as low IHC signals in hepatocellular carcinoma despite of a certain mRNA expression levels. RNA-seq and RPPA data of CCLE did not show such discordance between mRNA and protein levels, which could be a result of the regulation due to in vivo environmental factors. In breast cancer, ERBB3 IHC score levels were generally lower in triple negative breast cancer (TNBC), while TNBC-Mesenchymal subtype showed relatively high IHC score levels comparable to non-TNBC tumor types. In stomach cancer, intestinal subtype showed higher IHC score levels than diffuse subtype despite similar mRNA expression levels. These subtype-specific protein-level regulations were also observed in TCGA RNA-seq and RPPA data comparison. Conclusion: These results suggested a unique protein-level regulation of ERBB3 in tumor cells. It would be important to investigate the significance of protein-level antibody-target expressions on tumor samples, such as IHC on tissue microarray, for antibody-based drug development. Citation Format: Koichiro Inaki, Naoyuki Maeda, Tomoko Shibutani, Serenella Eppenberger-Castori, Stefan Nicolet, Kumiko Koyama, Yui Tanaka, Yuki Kaneda, Kenichi Wakita, Yoshinobu Shiose, Masato Murakami. Pan-cancer gene expression analysis of tissue microarray using EdgeSeq Oncology Biomarker Panel and a cross-comparison with ERBB3 immunohistochemical analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5880.

Prognostic significance of age related genes in patients with lower grade glioma.

Objective: To analyze the prognostic effects of age in different tumor types and determine the prognostic significance of age related genes in patients with lower grade glioma (LGG).Methods: The relationships between age and tumor overall survival were determined by Kaplan-Meier survival analysis using The Cancer Genome Atlas (TCGA) dataset. The age related genes were identified using TCGA RNA-seq data. Univariate and multivariate cox regression were used to determine the prognostic significance of age related genes. The results derived from TCGA dataset were further validated using Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA) datasets.Results: Age at initial pathologic diagnosis was most associated with the overall survival of LGG patients than other types of tumor patients. Age related genes EMP3, IGFBP2, TIMP1 and SERPINE1 were highly expressed in old LGG patients. The hypo-methylations of EMP3 and SERPINE1 were contributing to the high expressions of EMP3 and SERPINE1 in old LGG patients. Also, EMP3, IGFBP2, TIMP1 and SERPINE1 were highly expressed in LGG tumor tissues, compared with normal brain tissues. Moreover, high expressions of IGFBP2, EMP3, TIMP1 and SERPINE1 were associated with the worse prognosis of LGG patients. Furthermore, we demonstrated that EMP3 and SERPINE1 were connected with each other and the combination of EMP3 and SERPINE1 had better prognostic effects in glioma patients.Conclusions: Age related genes IGFBP2, EMP3, TIMP1 and SERPINE1 have significant prognostic effects in LGG patients.