Expression Profiling Of Tumors Research Articles

Screening Tumor-Related Genes of Gallbladder Cancer Based on AR-Based Tumor Expression Profile Gene Chip.

The rapid development of molecular biology and gene chip technology has produced a large amount of gene expression profile data. The main research in this article is to screen the tumor-related genes of gallbladder cancer based on AR-based tumor expression profile gene chip. First, convert the chip data into an expression matrix pattern that can be analyzed, and then standardize and normalize all the data. Run ReliefF, GA, and IReliefF-GA on the data set, record the size of the feature subset, and use the tenfold cross-validation method to obtain the classification accuracy, specificity, and sensitivity of each method on the classifier. The target genes used in the chip were amplified by PCR with the universal primers used in cDNA library construction, and the quality of PCR was monitored by agarose gel electrophoresis. The gene chip data of gallbladder cancer was processed with missing values, singular values, and so forth, and 22294 transcripts were obtained. After statistical testing, there were 9483 transcripts with statistically significant differences. The results show that as the number of clusters increases, the network can be better reconstructed through decomposition modeling.

Informative Gene Selection Based on Cost-Sensitive Fast Correlation- Based Filter Feature Selection

Background: Informative gene selection is an essential step in performing tumor classification. However, it is difficult to select informative genes related to tumors from large-scale gene expression profiles because of their characteristics, such as high dimensionality, relatively small samples, and class imbalance, and some genes are superfluous and irrelevant. Objective: Many researchers analyze and process gene expression data to obtain classified gene subsets by using machine learning methods. However, the gene expression profiles of tumors often have massive computational challenges. In addition, when improving feature importance and classification accuracy, cost estimation is often ignored in traditional feature selection algorithms, which makes tumor classification more difficult. Methods: In this study, a novel informative gene selection method based on cost-sensitive fast correlation- based filter (CS-FCBF) feature selection is proposed. Results: First, the symmetric uncertainty index is used to evaluate the correlation between informativeFirst, the symmetric uncertainty index is used to evaluate the correlation between informative genes and class labels, then a large number of irrelevant and redundant genes are quickly filtered according to importance. Thereby, a candidate gene subset is generated. Second, costsensitive learning, which introduces the misclassification cost matrix and support vector machine attribute evaluation, is used to obtain the top-ranked gene subset with minimum misclassification loss. Finally, the candidate gene subset is optimized. genes and class labels, then a large number of irrelevant and redundant genes are quickly filtered according to importance. Thereby, a candidate gene subset is generated. Second, costsensitive learning, which introduces the misclassification cost matrix and support vector machine attribute evaluation, is used to obtain the top-ranked gene subset with minimum misclassification loss. Finally, the candidate gene subset is optimized. Conclusion: This experiment was verified in eight independent tumor datasets. By comparing and analyzing CS-FCBF with another three hybrids of typical gene selection algorithms combined with cost-sensitive learning, we found that the method proposed in this study has a better classification performance with fewer selected genes, which might provide guidance in tumor diagnosis and research.

A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration.

Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model to investigate the dynamics of key cells and cytokines involved in breast cancer development. We used gene expression profiles of tumors to estimate the relative abundance of each immune cell and group patients based on their immune patterns. Dynamical results show the complex interplay between cells and molecules, and sensitivity analysis emphasizes the direct effects of macrophages and adipocytes on cancer cell growth. In addition, we observed the dual effect of IFN- on cancer proliferation, either through direct inhibition of cancer cells or by increasing the cytotoxicity of CD8+ T-cells.

TISMO: syngeneic mouse tumor database to model tumor immunity and immunotherapy response.

Syngeneic mouse models are tumors derived from murine cancer cells engrafted on genetically identical mouse strains. They are widely used tools for studying tumor immunity and immunotherapy response in the context of a fully functional murine immune system. Large volumes of syngeneic mouse tumor expression profiles under different immunotherapy treatments have been generated, although a lack of systematic collection and analysis makes data reuse challenging. We present Tumor Immune Syngeneic MOuse (TISMO), a database with an extensive collection of syngeneic mouse model profiles with interactive visualization features. TISMO contains 605 in vitro RNA-seq samples from 49 syngeneic cancer cell lines across 23 cancer types, of which 195 underwent cytokine treatment. TISMO also includes 1518 in vivo RNA-seq samples from 68 syngeneic mouse tumor models across 19 cancer types, of which 832 were from immune checkpoint blockade (ICB) studies. We manually annotated the sample metadata, such as cell line, mouse strain, transplantation site, treatment, and response status, and uniformly processed and quality-controlled the RNA-seq data. Besides data download, TISMO provides interactive web interfaces to investigate whether specific gene expression, pathway enrichment, or immune infiltration level is associated with differential immunotherapy response. TISMO is available at http://tismo.cistrome.org.

Tumor Expression Profile Analysis Developed and Validated a Prognostic Model Based on Immune-Related Genes in Bladder Cancer.

Background: Bladder cancer (BLCA) ranks 10th in incidence among malignant tumors and 6th in incidence among malignant tumors in males. With the application of immune therapy, the overall survival (OS) rate of BLCA patients has greatly improved, but the 5-year survival rate of BLCA patients is still low. Furthermore, not every BLCA patient benefits from immunotherapy, and there are a limited number of biomarkers for predicting the immunotherapy response. Therefore, novel biomarkers for predicting the immunotherapy response and prognosis of BLCA are urgently needed.Methods: The RNA sequencing (RNA-seq) data, clinical data and gene annotation files for The Cancer Genome Atlas (TCGA) BLCA cohort were extracted from the University of California, Santa Cruz (UCSC) Xena Browser. The BLCA datasets GSE31684 and GSE32894 from the Gene Expression Omnibus (GEO) database were extracted for external validation. Immune-related genes were extracted from InnateDB. Significant differentially expressed genes (DEGs) were identified using the R package “limma,” and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the DEGs were performed using R package “clusterProfiler.” Least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the signature model. The infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The performance of the model was evaluated with receiver operating characteristic (ROC) curves and calibration curves.Results: In total, 1,040 immune-related DEGs were identified, and eight signature genes were selected to construct a model using LASSO regression analysis. The risk score of BLCA patients based on the signature model was negatively correlated with OS and the immunotherapy response. The ROC curve for OS revealed that the model had good accuracy. The calibration curve showed good agreement between the predictions and actual observations.Conclusions: Herein, we constructed an immune-related eight-gene signature that could be a potential biomarker to predict the immunotherapy response and prognosis of BLCA patients.

RNA editing signatures identify melanoma patients who respond to Pembrolizumab or Nivolumab treatment

Immunotherapy has improved the prognosis for many melanoma patients; however, our capacity to predict patient responses and to understand the biological differences between patients who will or will not respond is limited. Gene expression profiling of tumors from patients who respond to immunotherapy has focused on deriving primarily immune-related signatures; however, these have shown limited predictive power. Recent studies have highlighted the role of RNA editing in modulating resistance to immunotherapy. To evaluate the utility of RNA editing activity as a discriminative tool in predicting immunotherapy response, we conducted a retrospective analysis of RNA-sequencing data from melanoma patients treated with Pembrolizumab or Nivolumab. Here, we developed RNA editing signatures that can identify patients who will respond to immunotherapy with very high accuracy and confidence. Our analysis demonstrates that RNA editing is a strong discriminative tool for examining sensitivity of melanoma patients to immunotherapy.

Exploring the role of PDE10 inhibition in ovarian cancer carcinogenesis in the egg-laying hen using RNA sequencing

<h3>Objectives:</h3> Here we investigate a novel phosphodiesterase 10 (PDE10) inhibitor, MCI-030, as a drug candidate for the treatment or prevention of epithelial ovarian cancer (EOC). Prior research showed that MCI-030 decreased cancer incidence in the egg laying hen spontaneous model of EOC by a novel mechanism involving dual suppression of Wnt and MAPK signaling. This study aims to further understand the molecular pathways affected by MCI-030 in preventing EOC development. <h3>Methods:</h3> Hens were treated with MCI-030 or control feed for 6 months. Necropsy was then performed to assess tumor development. Total RNA from ovarian tissue of 8 MCI-030-treated hens (4 tumor, 4 normal) and 8 control hens (4 tumor, 4 normal) was isolated and analyzed for differential gene expression using RNA sequencing (RNAseq). RNAseq was performed by paired-end 75bp sequencing with ~35 million reads coverage using the Illumina NextSeq500 platform. Genes were mapped to the Gallus[gp1] GRCg6 reference genome. Differential gene expression analysis was performed using DESeq2; pathways were investigated in the Molecular Signatures Database of the GSEA (www.gsea-msigdb.org). <h3>Results:</h3> Tumors from MCI-030 treated hens had 1,412 significantly downregulated genes (fold-change≤-2.0; p<0.05) compared to control tumors, including genes in the Wnt and MAPK signaling pathways. The most significant downregulation was in the cytokinecytokine receptor interaction gene pathway (67 genes,p=3.18 e-37). Many pathways downregulated by MCI-030, e.g. PDE10A inhibition, corresponded with pathways upregulated in PDE10A high-expressing ovarian tumors in the TCGA (Figure1). As expected for typical ovarian tumor expression profiling, various immune and inflammatory pathways were upregulated in ovary tumors compared to normal ovaries of control hens. However, these were strikingly absent when comparing tumors vs. normal ovaries of MCI-030 treated hens. The gene expression profiles comparing normal ovaries of treated vs. untreated hens revealed only 22 differentially expressed genes. <h3>Conclusions:</h3> Our data show multiple gene pathways downregulated in tumors treated with MCI-030 compared to untreated controls, including pathways such as Wnt and MAPK believed to be suppressed by PDE10 inhibition. Interestingly, many of the MCI-030 downregulated pathways mirror those observed for genes whose expression was positively correlated PDE10A mRNA in ovarian tumors of The Cancer Genome Atlas (TCGA). Our data also suggest that MCI-030 might have minimum effect in normal ovaries, but in contrast ameliorates inflammation usually associated to the tumor microenvironment.

The Sex Differences in Uveal Melanoma: Potential Roles of EIF1AX, Immune Response and Redox Regulation.

Background: Uveal melanoma (UVM) is a rare cancer that shows sex difference in incidence and survival, with little previous report for the underlying mechanism. Methods: This study used the SEER data (1974–2016) for an age-dependent analysis on sex difference in UVM, and further used the TCGA-UVM genomics dataset for analyzing the differential gene expression profiles in tumors from men and women. Results: Our results demonstrate a sex difference in older age (≥40 years) but not in younger patients, with men exhibiting a higher incidence rate than women. However, younger women have shown a continuous increasing trend since 1974. Examining the 11 major oncogenes and tumor suppressors in UVM revealed that EIF1AX showed a significant sex difference in mRNA accumulation and copy number variation, with female tumors expressing higher levels of EIF1AX and exhibiting more variations in copy numbers. EIF1AX mRNA levels were significantly inversely correlated with EIF1AX copy numbers in female tumors only, but not in male tumors. Differential gene expression analysis at the whole genomic level identified a set of 92 protein-coding and 16 RNA-coding genes which exhibited differential expression in men and women (fold of change cutoff at 1.7, adjusted p value < 0.05, FDR < 0.05). Network analysis showed significant difference in immune response and in disulfide bond formation, with EGR1/EGR2 and PDIA2 genes as regulators for immune response and disulfide bond formation, respectively. The melanocortin pathway which is linked to both melanin synthesis and obesity seems to be altered with unclear significance, as the sex difference in POMC, DCT/TYRP2, and MRAP2 was observed but with no clear direction. Conclusion: This study reveals possible mechanisms for the sex difference in tumorigenesis of UVM which has potentials for better understanding and prevention of UVM.

Abstract 2579: Links between obesity and secreted frizzled-related protein 4 (Sfrp4) in a murine model of colon cancer

Abstract Obesity is a well-established risk factor for colon cancer and the effect of obesity-mediated inflammation is particularly pronounced in colon carcinogenesis. An incomplete understanding of the biology underlying this strong obesity-colon cancer association has hampered efforts to identify effective colon cancer prevention strategies. The current study aims to identify novel colon tumor intrinsic targets that mediate critical inflammatory signals underlying the obesity-colon cancer connection. To induce colon tumors, FVB/N male mice were treated weekly with azoxymethane (10 mg/kg intraperitoneally) for 5 weeks. Mice were then randomized to either continue receiving 10 kcal% fat diet (control) or were switched to a 60 kcal% fat diet to promote diet-induced obesity (DIO) over a 15-week period. DIO mice were then randomized to either receive 0ppm (DIO) or 140ppm sulindac (DIO+Su), a non-steroidal anti-inflammatory drug, for 7 additional weeks. At the end of the 27-week study, colonic tumors were collected for histology and global transcriptomic analysis using Affymetrix Clariom D mouse gene expression microarrays. DIO increased tumor multiplicity and burden in AOM-treated mice. Moreover, long-term administration of dietary sulindac was sufficient to reduce inflammatory signals, tumor multiplicity, and tumor burden in DIO-Su versus DIO mice. Principal component analysis and hierarchical clustering based on the 1,000 most differentially expressed genes revealed distinct gene expression profiles in tumors from control, DIO, and DIO+Su mice. To determine the biological processes most up- or down-regulated in tumors from DIO mice, gene set enrichment analysis was run using the hallmark gene sets. Epithelial-mesenchymal-transition (EMT) was the most upregulated gene set in tumors from DIO mice compared with tumors from control mice (normalized enrichment score 2.00; adjusted p=0.0002) and compared with tumors from DIO+Su mice (normalized enrichment score 1.78; adjusted p=0.009), suggesting that obesity drives EMT via an inflammatory mechanism. Based on a leading-edge analysis, secreted frizzled-related protein 4 (Sfrp4) expression was significantly enriched in the EMT gene set. Sfrp4 is of biological interest given its biphasic modulation of Wnt signaling and association with poor prognosis in aggressive prostate cancer. We confirmed via immunofluorescence that Sfrp4 is produced by AOM-treated colonic intestinal epithelial and submucosal cell populations and observed by qPCR that it is expressed across multiple human colon cancer cell lines. Hence, Sfrp4 may be a novel target to mitigate obesity-induced exacerbation of colon tumorigenesis. Future work will determine the role of Sfrp4 in colon cancer cell-adipose interactions and whether ablation of Sfrp4 is sufficient to impede colon tumor growth. This research was supported by R35CA197627 to S. Hursting. Citation Format: Elaine M. Glenny, Laura W. Bowers, Diana Li, Jatin Roper, Stephen D. Hursting. Links between obesity and secreted frizzled-related protein 4 (Sfrp4) in a murine model of colon cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2579.

Abstract 968: Focal adhesion kinase (FAK) inhibitor APG-2449 sensitizes ovarian tumors to chemotherapy via CD44 downregulation

Abstract Ovarian cancer is one of the deadliest malignancies in women, and up to 70% of patients with epithelial ovarian cancer have FAK overexpression, amplification, or activation. FAK plays an important role in cellular migration, growth factor signaling, cell cycle progression, cellular survival and chemoresistance. This biomarker is also significantly associated with higher tumor stage, metastasis, and shorter overall survival in patients with ovarian cancer. Inhibition of FAK is therefore emerging as a promising treatment target. APG-2449 is a clinical stage FAK/ALK/ROS1 multi-kinase inhibitor. In this study we investigated antitumor activity of APG-2449 combined with standard-of-care chemotherapeutics in ovarian cancer in the preclinical setting. In a mouse xenograft tumor model derived from ovarian cancer cell line OVCAR-3, which was resistant to platinum-based therapies, APG-2449 combined with paclitaxel, and paclitaxel plus carboplatin, synergistically enhanced antitumor activity, whereas the chemotherapeutics showed no activity. Synergistic antitumor activity was also observed in multiple patient-derived xenograft (PDX) models derived from women with chemoinsensitive ovarian cancer, which also frequently expresses high levels of FAK. By comparing gene expression profiles of PDX tumors obtained from responders and nonresponders to the combined therapy, we identified CD44 (a marker for cancer stem cells) as a potentially predictive biomarker. Western blot analysis confirmed higher protein levels of CD44 in pretreated tumors of responders. Interestingly, downregulation of CD44 levels was observed in combination-treated tumors, suggesting that these combinations reduced cancer stem cell populations in ovarian cancer. Accordingly, in ovarian cancer cells exposed to APG-2449 alone or combined with paclitaxel, numbers of cells positive for CD44 or aldehyde dehydrogenase 1 (ALDH1; another marker for cancer stem cells) decreased in a dose-dependent manner. In summary, our data suggest that FAK inhibition by APG-2449 sensitizes ovarian tumors to chemotherapeutics in preclinical tumor models of ovarian cancer. The synergistic antitumor activity was mediated by downregulation of CD44+ or ALDH1+ cancer stem cell populations. These findings encourage clinical development of APG-2449 in combination with chemotherapies for treatment of ovarian cancer. Citation Format: Ran Tao, Douglas D. Fang, Yuanbao Li, Kaixiang Zhang, Chunhua Xu, Xu Fang, Qixin Wang, Dajun Yang, Yifan Zhai. Focal adhesion kinase (FAK) inhibitor APG-2449 sensitizes ovarian tumors to chemotherapy via CD44 downregulation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 968.

Identification of Clinical Relevant Molecular Subtypes of Pheochromocytoma.

Pheochromocytoma (PCC) is a rare neuroendocrine tumor of the adrenal gland with a high rate of mortality if diagnosed at a late stage. Common symptoms of pheochromocytoma include headache, anxiety, palpitation, and diaphoresis. Different treatments are under observation for PCC but there is still no effective treatment option. Recently, the gene expression profiling of various tumors has provided new subtype-specific options for targeted therapies. In this study, using data sets from TCGA and the GSE19422 cohorts, we identified two distinct PCC subtypes with distinct gene expression patterns. Genes enriched in Subtype I PCCs were involved in the dopaminergic synapse, nicotine addiction, and long-term depression pathways, while genes enriched in subtype II PCCs were involved in protein digestion and absorption, vascular smooth muscle contraction, and ECM receptor interaction pathways. We further identified subtype specific genes such as ALK, IGF1R, RET, and RSPO2 for subtype I and EGFR, ESR1, and SMO for subtype II, the overexpression of which led to cell invasion and tumorigenesis. These genes identified in the present research may serve as potential subtype-specific therapeutic targets to understand the underlying mechanisms of tumorigenesis. Our findings may further guide towards the development of targeted therapies and potential molecular biomarkers against PCC.

Integrative Transcriptomic Analysis Reveals Distinctive Molecular Traits and Novel Subtypes of Collecting Duct Carcinoma.

Simple SummaryThe treatment of collecting duct carcinoma (CDC) remains unsatisfactory since this highly aggressive kidney cancer has an unfavorable clinical behavior. Due to the rarity of CDC a complete biological characterization of this disease is still lacking. The aim of our study is to provide new insights into the molecular biology of CDC leveraging newly generated and publicly available gene expression profiles of CDC tumors. We identified unique gene expression programs and pathways that distinguished CDC from other renal malignancies. The CDC-specific expression signature predicted in vitro sensitivity to several small molecule inhibitors screened in cancer cell lines from multiple cancer types. Finally, we proved that CDC is a molecularly heterogeneous disease made up of at least two subtypes distinguished by cell signaling, metabolic and immune-related alterations. Altogether, these findings pave the way for future investigations with meaningful clinical implications aimed at improving the management of CDC patients.Collecting duct carcinoma (CDC) is a rare and highly aggressive kidney cancer subtype with poor prognosis and no standard treatments. To date, only a few studies have examined the transcriptomic portrait of CDC. Through integration of multiple datasets, we compared CDC to normal tissue, upper-tract urothelial carcinomas, and other renal cancers, including clear cell, papillary, and chromophobe histologies. Association between CDC gene expression signatures and in vitro drug sensitivity data was evaluated using the Cancer Therapeutic Response Portal, Genomics of Drug Sensitivity in Cancer datasets, and connectivity map. We identified a CDC-specific gene signature that predicted in vitro sensitivity to different targeted agents and was associated to worse outcome in clear cell renal cell carcinoma. We showed that CDC are transcriptionally related to the principal cells of the collecting ducts providing evidence that this tumor originates from this normal kidney cell type. Finally, we proved that CDC is a molecularly heterogeneous disease composed of at least two subtypes distinguished by cell signaling, metabolic and immune-related alterations. Our findings elucidate the molecular features of CDC providing novel biological and clinical insights. The identification of distinct CDC subtypes and their transcriptomic traits provides the rationale for patient stratification and alternative therapeutic approaches.

Characterizing the molecular and immune landscape of canine bladder cancer.

Transitional cell carcinoma (TCC), also known as urothelial carcinoma, is the most common bladder cancer in humans and dogs. Approximately one-quarter of human TCCs are muscle-invasive and associated with a high risk of death from metastasis. Canine TCC (cTCC) tumours are typically high-grade and muscle-invasive. Shared similarities in risk factors, histopathology, and clinical presentation suggest that cTCC may serve as a model for the assessment of novel therapeutics that may inform therapies for human muscle-invasive TCC. The goal of this study was to characterize cTCC at the molecular level to identify drivers of oncogenesis and druggable targets. We performed whole exome sequencing (WES) of 11 cTCC tumours and three matched normal samples, identifying 583 variants in protein-coding genes. The most common variant was a V-to-E missense mutation in BRAF, identified in 4 out of 11 samples (36%) via WES. Sanger sequencing identified BRAF variants in 8 out of the same 11 cTCC samples, as well as in 22 out of 32 formalin-fixed paraffin embedded (FFPE) cTCC samples, suggesting an overall prevalence of 70%. RNA-Seq was performed to compare the gene expression profiles of cTCC tumours to normal bladder tissue. cTCC tumours exhibited up-regulation of genes involved in the cell cycle, DNA repair, and antiviral immunity. We also analysed the immune landscape of cTCC using immune gene signatures and immunohistochemical analysis. A subset of tumours had characteristics of a hot tumour microenvironment and exhibited high expression of signatures associated with complete response to PD-1/PD-L1 blockade in human bladder cancer.

Comparative Gene Signature of (-)-Oleocanthal Formulation Treatments in Heterogeneous Triple Negative Breast Tumor Models: Oncological Therapeutic Target Insights.

Triple negative breast cancer (TNBC) heterogeneity and limited therapeutic options confer its phenotypic aggressiveness. The discovery of anti-TNBC natural products with valid molecular target(s) and defined pharmacodynamic profile would facilitate their therapeutic nutraceutical use by TNBC patients. The extra-virgin olive oil (EVOO) is a key Mediterranean diet ingredient. S-(−)-Oleocanthal (OC) leads the bioactive anti-tumor EVOO phenolic ingredients. A previous study reported the solid dispersion formulated OC with (+)-xylitol (OC-X) suppressed the in vivo progression and recurrence of the TNBC MDA-MB-231 cells. This study investigates the ability of OC-X formulation to suppress the in vivo heterogeneous BC initiation and progression utilizing advanced preclinical transgenic MMTV-PyVT and TNBC PDX mouse models. Furthermore, the clustering of the gene expression profiles in MMTV-PyVT and PDX mouse tumors treated with OC-X acquired by a Clariom S microarray analysis identified the distinctly affected genes. Several affected novel signature genes identified in response to OC-X treatments and proved overlapped in both mouse and human tumor models, shedding some lights toward understanding the OC anticancer molecular mechanism and assisting in predicting prospective clinical outcomes. This study provides molecular and preclinical evidences of OC-X potential as a nutraceutical suppressing heterogeneous TNBC model and offers preliminary gene-level therapeutic mechanistic insights.

Gene expression profiles of the original tumors influence the generation of PDX models of lung squamous cell carcinoma

Patient-derived xenograft (PDX) murine models are employed for preclinical research on cancers, including non-small cell lung cancers (NSCLCs). Even though lung squamous cell carcinomas (LUSCs) show the highest engraftment rate among NSCLCs, half of them nevertheless show PDX failure in immunodeficient mice. Here, using immunohistochemistry and RNA sequencing, we evaluated the distinct immunohistochemical and gene expression profiles of resected LUSCs that showed successful engraftment. Among various LUSCs, including the basal, classical, secretory, and primitive subtypes, those in the non-engrafting (NEG) group showed gene expression profiles similar to the pure secretory subtype with positivity for CK7, whereas those in the engrafting (EG) group were similar to the mixed secretory subtype with positivity for p63. Pathway analysis of 295 genes that demonstrated significant differences in expression between NEG and EG tumors revealed that the former had enriched expression of genes related to the immune system, whereas the latter had enriched expression of genes related to the cell cycle and DNA replication. Interestingly, NEG tumors showed higher infiltration of B cells (CD19+) and follicular dendritic cells (CD23+) in lymph follicles than EG tumors. Taken together, these findings suggest that the PDX cancer model of LUSC represents only a certain population of LUSCs and that CD19- and CD23-positive tumor-infiltrating immune cells in the original tumors may negatively influence PDX engraftment in immunodeficient mice.

Identification of ZBTB18 as a novel colorectal tumor suppressor gene through genome-wide promoter hypermethylation analysis

BackgroundCancer initiation and progression are driven by genetic and epigenetic changes. Although genome/exome sequencing has significantly contributed to the characterization of the genetic driver alterations, further investigation is required to systematically identify cancer driver genes regulated by promoter hypermethylation.ResultsUsing genome-wide analysis of promoter methylation in 45 colorectal cancer cell lines, we found that higher overall methylation levels were associated with microsatellite instability (MSI), faster proliferation and absence of APC mutations. Because epigenetically silenced genes could represent important oncogenic drivers, we used mRNA expression profiling of colorectal cancer cell lines and primary tumors to identify a subset of 382 (3.9%) genes for which promoter methylation was negatively associated with gene expression. Remarkably, a significant enrichment in zinc finger proteins was observed, including the transcriptional repressor ZBTB18. Re-introduction of ZBTB18 in colon cancer cells significantly reduced proliferation in vitro and in a subcutaneous xenograft mouse model. Moreover, immunohistochemical analysis revealed that ZBTB18 is frequently lost or reduced in colorectal tumors, and reduced ZBTB18 expression was found to be associated with lymph node metastasis and shorter survival of patients with locally advanced colorectal cancer.ConclusionsWe identified a set of 382 genes putatively silenced by promoter methylation in colorectal cancer that could significantly contribute to the oncogenic process. Moreover, as a proof of concept, we demonstrate that the epigenetically silenced gene ZBTB18 has tumor suppressor activity and is a novel prognostic marker for patients with locally advanced colorectal cancer.

Normal tissue adjacent to tumor expression profile analysis developed and validated a prognostic model based on Hippo-related genes in hepatocellular carcinoma.

BackgroundHepatocellular carcinoma (HCC) is the most common malignant disease worldwide. Although the diagnosis and treatment of HCC have greatly improved in the recent years, there is still a lack of accurate methods to predict the prognosis of patients. Evidence has shown that Hippo signaling in tissues adjacent to HCC plays a significant role in HCC development. In the present study, we aimed to construct a model based on the expression of Hippo‐related genes (HRGs) in tissues adjacent to HCC to predict the prognosis of HCC patients.MethodsGene expression data of paired normal tissues adjacent to HCC (PNTAH) and clinical information were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The HRG signature was constructed using four canonical Hippo‐related pathways. Univariate Cox regression analysis was used to screen survival‐related HRGs. LASSO and multivariate Cox regression analyses were used to construct the prognostic model. The true and false positive rates of the model were confirmed using receiver operating characteristic (ROC) analysis.ResultsThe prognostic model was constructed based on the expression levels of five HRGs (NF2, MYC, BIRC3, CSNK1E, and MINK1) in PNTAH. The mortality rate of HCC patients increased as the risk score determined by the model increased. Furthermore, the risk score was found to be an independent risk factor for the survival of patients. ROC analysis showed that the prognostic model had a better predictive value than the other conventional clinical parameters. Moreover, the reliability of the prognostic model was confirmed in TCGA‐LIHC cohort. A nomogram was generated to predict patient survival. An exploration of the predictive value of the model in HCC tissues indicated that the model is PNTAH‐specific.ConclusionsWe developed and validated a prognostic model based on the expression levels of five HRGs in PNTAH, and this model should be helpful in predicting the prognosis of patients with HCC.

Abstract SS1-07: Gene expression profiles of Ghanaian and Ethiopian triple-negative breast tumors

Abstract Background: Triple-negative breast cancer (TNBC) remains the most aggressive molecular subtype of breast cancer, with worse survival outcomes compared to other breast cancer subtypes. TNBC prevalence is highest among women of African descent worldwide, and through our previous work we have established a connection between West African ancestry (WAa) and higher rates of TNBC. Specifically, we have shown that prevalence rates of TNBC among West African and African American women are similar and higher than that of East African and White American women. We have also shown that quantified African ancestry is higher among TNBC cases compared to non-TNBC cases. To determine the influence African ancestry on the TNBC tumor environment, we sought to determine any differences in gene expression profiles of Ghanaian (West African) compared to Ethiopian (East African) women. Methods: RNA was extracted and sequenced from a pilot cohort of archival FFPE tumor tissue among Ghanaian (n = 19) and Ethiopian (n = 20) women. RNAseq reads were aligned, and quality of alignments were assessed, where de-duplicated samples with counts above 10M reads were included in the final analysis. Genetic ancestry was quantified by obtaining SNVs called from the RNAseq alignments, using GATK best practices. Differentially expressed genes lists were determined comparing Ghanaian vs. Ethiopian TNBC tumors, and also by identifying genes that were associated with increasing African ancestry. These gene lists, and log-fold change between comparison groups, were used as input for Ingenuity Pathway Analysis (IPA), to identify canonical pathways and de novo networks that are specific to Ghanaian or Ethiopian TNBC tumors. Results: Using 1KG populations as our reference to quantify genetic ancestry, we show that Ghanaian samples have &amp;gt;94% AFR ancestry, specifically matching population groups representative of WAa. The Ethiopian samples showed between 37-48% AFR ancestry, primarily represented by East African groups. Interestingly, there seems to be a significant proportion of EUR ancestry among the Ethiopians samples (30-49%), primarily represented by Italian ancestry. We have conducted the differential gene expression analysis in two ways. First, we have compared gene expression profiles between Ghanaian and Ethiopian tumors. In our preliminary analysis, we identified &amp;gt;600 genes (p &amp;lt; 0.01) that were differentially expressed between Ghanaian and Ethiopian TNBC tumors. Second, we used AFR ancestry as a continuous variable, where we conducted a linear regression analysis to identify genes associated with AFR ancestry. We identified &amp;gt;900 genes associated with AFR ancestry (p &amp;lt; 0.01), and this gene signature distinguished Ghanaian from Ethiopian tumors in an unsupervised hierarchical clustering. In comparing the differentially expressed gene lists from these two approaches, approximately 200 genes were shared, indicating the distinct value of both analyses. Using these gene lists as input for IPA analysis, we have begun to identify canonical pathways that have been altered by our differentially expressed genes, alongside de novo networks that differ between our Ghanaian and Ethiopian tumors. In our overlapping gene list, we see predicted differences in functions such as quantity of T lymphocytes, where genes downregulated in Ethiopian tumors may indicated reduced presence of these immune cells. Using CIBERSORT and xCell deconvolution methods, validation of these findings are ongoing. Conclusions and Ongoing work: This work highlights how ancestry-specific gene regulation can delineate differences in the tumor microenvironment among a cohort of African tumors. We are currently evaluating distribution of TNBC subtypes and estimation of immune cell populations in these tumors, to determine ancestry-specific differences in tumor heterogeneity and immune response. Citation Format: Rachel Martini, Endale Gebregzabher, Princesca Dorsaint, Timothy Chu, Kanika Arora, Lee Gibbs, Zarko Manojlovic, Nicolas Robine, Andrea Sboner, Olivier Elemento, John Carpten, Lisa Newman, Melissa Davis. Gene expression profiles of Ghanaian and Ethiopian triple-negative breast tumors [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SS1-07.

Abstract PD15-02: Cx3cl1-cx3cr1 axis in liver metastasis of triple negative breast cancer

Abstract Triple negative breast cancer (TNBC) is a breast cancer subtype with increased risk of distant metastasis, especially to visceral organs. However, the detailed molecular mechanism underlying the visceral metastasis of TNBC is unknown. We used three patient-derived xenograft models derived from TNBC tumors with different metastatic capacities. PDX1 and PDX2 model developed distant metastasis in only lung and liver, respectively. In contrast, PDX3 tumor metastasized to both lung and liver. RNA sequencing of the primary tumor and distant metastatic sites of these three PDX models was performed. The gene expression profiles of the primary tumors of the three models showed minimally overlapping genes. However, the microenvironment gene expression profiles, measured by using the sequencing reads aligned to mouse genome, showed distinct difference between the models. Among the differentially expressed genes, we identified Cx3cr1 as a significantly upregulated gene in the liver microenvironment of the PDX models that metastasized to liver. Next, we used 4T1 syngeneic mouse mammary carcinoma model to validate the Cx3cr1 in the mouse liver tissues. Interestingly, the Cx3cr1 up-regulation occurred during the pre-metastatic period, and Cx3cl1, the ligand of the Cx3cr1, was also up-regulated in the liver tissue prior to the development of metastasis suggesting the Cx3cr1 regulates the formation of pre-metastatic niche. Cx3cl1, the ligand of the Cx3cr1, was also up-regulated in the liver tissue prior to the development of metastasis. These data suggest that Cx3cl1 and Cx3cr1-mediated tumor-microenvironment interaction is critical in developing liver metastasis in TNBC. Cx3cl1 increased the invasion and migration of Raw264.7 monocyte/macrophage cells and this effect was abrogated by the Cx3cr1 silencing in Raw264.7 cells or treating Cx3cl1 neutralizing antibody. Pathway analysis of the RNA sequencing data showed that genes involved in extracellular matrix remodeling was significantly dysregulated in the liver tissues including Lysyl Oxidase (Lox). Cx3cl1 treatment in Raw264.7 cells resulted in increased expression of Lox and MMP9 mRNA in three-dimensional culture system. The Raw264.7 cells caused increased invasion of 4T1 cells in vitro. In conclusion, our data suggest that Cx3cl1-Cx3cr1 axis plays critical role during the liver metastasis of TNBC. Citation Format: Woohang Heo, Hye-Youn Son, Ju hee Kim, Kyu Jin Lee, Myeonghee Jeon, Songbin Li, Jeehee Jang, Dong-Young Noh, Wonsik Han, Hyeong-Gon Moon. Cx3cl1-cx3cr1 axis in liver metastasis of triple negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD15-02.

GATA3 somatic mutations are associated with clinicopathological features and expression profile in TCGA breast cancer patients

The effect of somatic mutations and the gene expression profiles on the prognosis is well documented in cancer research. This study was conducted to evaluate the association of GATA3 somatic mutations with tumor features, survival, and expression profiles in breast cancer. Clinicopathological information was compared between TCGA-BRCA patients with GATA3-mutant and non-mutant tumors in all patients as well as in ER-positive subgroup. Cox-regression method was used to evaluate the association of the GATA3 mutation status with overall survival time. Differential gene expression, functional annotation, and protein–protein interaction analyses were performed using edgeR, Metascape, DAVID, STRING and CytoNCA. GATA3-mutant and non-mutant samples had significantly different clinicopathological features (p < 0.05). While GATA3 mutation status was not associated with the overall survival in the entire cohort (padj = 0.52), the GATA3-wild type ER-positive cases had a better prognosis than mutant ones (padj = 0.04). GATA3 expression was higher in tumors than normal tissues. Several pathways were different between mutant and non-mutant groups (p < 0.05). Interleukin-6 was found as the highest scored gene in both comparisons (normal vs. mutant and normal vs. non-mutant groups) in the entire patient and in the ER-positive subgroup, suggesting the association of IL6 with breast tumorigenesis. These findings suggest that GATA3 mutations can be associated with several tumor characteristics and influence the pattern of gene expression. However, GATA3 mutation status seems to be a prognostic factor for the disease only in ER-positive patients.