Abstract P3-08-10: A unique coding and non-coding benign breast transcriptome in post-menopausal ER+ breast cancer

Identification of molecular signatures that allow detection of the transition from normal breast epithelial cells to malignant invasive cells is a critical component in the development of diagnostic, therapeutic, and preventative strategies for human breast cancer. Substantial efforts have been devoted to deciphering breast cancer etiology at the genome level, but only a limited number of studies have appeared at the proteome level. In this work, we compared individual in situ proteome profiles of nonpatient matched nine noncancerous, normal breast epithelial (NBE) samples with nine estrogen receptor (ER)-positive (luminal subtype), invasive malignant breast epithelial (MBE) samples by combining laser capture microdissection (LCM) and quantitative shotgun proteomics. A total of 12,970 unique peptides were identified from the 18 samples, and 1623 proteins were selected for quantitative analysis using spectral index (SpI) as a measure of protein abundance. A total of 298 proteins were differentially expressed between NBE and MBE at 95% confidence level, and this differential expression correlated well with immunohistochemistry (IHC) results reported in the Human Protein Atlas (HPA) database. To assess pathway level patterns in the observed expression changes, we developed protein set enrichment analysis (PSEA), a modification of a well-known approach in gene expression analysis, Gene Set Enrichment Analysis (GSEA). Unlike single gene-based functional term enrichment analyses that only examines pathway overrepresentation of proteins above a given significance threshold, PSEA applies a weighted running sum statistic to the entire expression data to discover significantly enriched protein groups. Application of PSEA to the expression data in this study revealed not only well-known ER-dependent and cellular morphology-dependent protein abundance changes, but also significant alterations of downstream targets for multiple transcription factors (TFs), suggesting a role for specific gene regulatory pathways in breast tumorigenesis. A parallel GOMiner analysis revealed both confirmatory and complementary data to PSEA. The combination of the two annotation approaches yielded extensive biological feature mapping for in depth analysis of the quantitative proteomic data.

Racial/ethnic disparity in cancer refers to the disproportionate incidence of and/or mortality from various cancers among population groups. In addition to differences in social, lifestyle and structural determinants of health, there is accumulating evidence for a biologic contribution to racial/ethnic disparity in cancer. To understand further the biologic mechanisms underlying racial/ethnic disparity in cancer, the analysis of differential aggregate gene expression and mutation among cancer patients of different population groups is important. Our recently published work reported differential RNA splicing as a critical mechanism underlying prostate cancer aggressiveness and drug response in African American (AA) patients. Here, we use R to analyze the Genomic Data Commons for differential aggregate gene expression (2-fold mean change, p < 0.001, Wilcoxon rank sum test) and TCGASpliceSeq to analyze TCGA for differential RNA splicing (20% median change, percent spliced in) between breast (BRCA, 183 AA and 761 white), colon (COAD, 56 AA and 194 white), squamous and adenocarcinoma lung (LUSC and LUAD, 34 and 57 AA and 392 and 444 white, respectively), and prostate (PRAD, 49 AA and 307 white) cancer specimens from AA and white patients. Our analysis identified 698 differentially expressed genes (DEGs) and 114 alternative RNA splicing events (ARSs) in BRCA, 107 DEGs and 57 ARSs in COAD, 25 and 117 DEGs and 115 and 53 ARSs in LUSC and LUAD, respectively, and 25 DEGs and 71 ARSs in PRAD from AA and white patients. Notably, comparing the lists of DEGs or ARSs from each cancer type with each of the other cancer types yields a minority of overlapping DEGs or ARSs among cancer types, indicating that race-related DEGs and ARSs are largely specific to cancer type. Pathway analysis of DEGs and ARSs reveals that the majority of these genes function in pathways relevant to cancer development and progression, such as programmed cell death, DNA repair, signal transduction, gene expression and metabolism. These analyses increase understanding of molecular mechanisms underlying racial/ethnic disparity in cancer. Upon further study of the function of these variants, such DEGs and ARSs have the potential to become candidates for development of new precision medicine interventions. Citation Format: Muthana Al Abo, Daniel J. George, Jennifer A. Freedman, Steven R. Patierno. Identification of differentially expressed and spliced genes between breast, colon, lung, and prostate cancer from African American and white patients [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr B050.

Breast cancer is a common cancer and could result in a substantial mortality. The study aimed to screen gene signatures associated with the development and metastasis of breast cancer and explore their regulation mechanisms. Three datasets of GSE10797, GSE8977 and GSE3744 were downloaded from GEO (Gene Expression Omnibus) database, containing 55 breast cancer samples and 27 normal samples. After data preprocessing using limma software and RMA (robust multi-array average) algorithm, DEGs (differentially expressed genes) between breast tumor and normal tissues in three individual experiments were identified using MADAM package. Function and pathway enrichment analyses were performed for the DEGs. Transcription factors and TAGs (tumor associated genes) among the DEGs were recognized and the PPI (protein-protein-interaction) network for the DEGs was constructed using Cytoscape software. The mRNA expression was analyzed via real-time quantitative PCR and protein expression was measured by western blotting. Totally, 100 DEGs were identified, including 33 up-regulated genes and 67 down-regulated genes. Among them, up-regulated DEGs such as CD80 was enriched in toll-like receptor (TLR) interaction pathway and the TAG, ISG15 was related to RIG-I-like receptor signaling pathway, while CXCL10 was involved in both of the two pathways. Whereas, the down-regulated DEG, CXCL12 was significantly associated with axon guidance pathway. Additionally, these DEGs were also pivotal nodes in the PPI network with high degrees. Besides, CXCL10 and CD80 were both interacted with IFNG. The mRNA expression of ISG15 was obviously enhanced in human breast cancer cells MCF-7, while no significant difference of CXCL10 mRNA level was found between MCF10A and MCF-7 cells. Moreover, the proteins expression levels of CD80 and ISG15 were significantly increased in MCF-7, MDA-MB-468 and MDA-MB-231 breast cancer cells than in normal MCF10A cells. CD80 might be responsible for the breast cancer's progression and metastasis via regulating innate immune system. In addition, ISG15 is identified as a crucial gene signature associated with breast cancer development and metastasis via RIG-I-like receptor signaling pathway.

Breast cancer (BC) is a public health concern in Colombia that presents admixture of indigenous American (IA), European and African American (AA) ancestries. These differences could be affecting prognosis and neoadjuvant chemotherapy (NAC) response. This study aims to identify gene expression profiles associated with non-response to NAC in Colombian women diagnosed with invasive BC, including genetic ancestry as a covariable. An integrative transcriptome analysis was conducted on 87 samples of BC female patients belonging to Colombian NCI population and candidates for NAC. Patients either responded or did not respond to NAC. To estimate genetic ancestry, genotyping of 106 ancestry informative markers was performed from non-tumoral DNA. Molecular intrinsic subtypes were classified into four groups: All luminal, LuminalBHer2+/-, LuminalBHer2+ & HER2 enriched, and TNBC+Her2-enriched. Two analyses were performed: differential gene expression comparing RNA-Seq data from different molecular subtype grouping, and enrichment analysis comparing baseline vs follow-up samples from non-responders, as well as baseline samples from non-responders vs responders. All analyses were performed comparing ancestry as a covariable in differential expression model. Responders and nonresponders showed distinct gene signatures in all categories. Sample distribution shown 8% AA, 59% IA and 32% European ancestry. Subtype grouping with ancestry as a covariable found 4 differential expressed genes (DEG) across nonresponders and baseline analyses for all samples (CPNE9, GTSF1, NORAD, PPP1R35) associated with cell differentiation pathways. 1 luminal DEG (CGB3), 20 DEG for LuminalBHer2+/-, 202 DEGs for LuminalBHer2+ & HER2 enriched, and 7 DEGs for TNBC+Her2-enriched (AKR1E2, CEACAM6, IRS4,LIGO, MICU2, NPAS2 and STATH). Among these groups, enrichment pathways included positive regulation of cell migration, cell-cell adhesion, cellular response to hormone stimulus. We found a notable increase in differential gene expression as the proportion of IA genetic ancestry becomes greater. Genetic ancestry effect might indicate a connection between heterozygosity and genetic variance. We contrasted our results to other studies performed in other Latin American cohorts. Overall, our findings reveal a significant gene signature between responders and non-responders across subtype grouping. Our previous findings identified different sets of genes among this subtype grouping suggesting that genetic ancestry affects the gene signatures and as it's already reported, treatment response. Our results emphasizes the significance of assessing gene expression in heterogeneous populations with diverse ancestral backgrounds like Colombia, as a means to facilitate novel findings and alleviate disparities. Overexpression of these genes provides a potential to predict therapy response, alerting clinicians about patients who may not benefit from NAC. Citation Format: Hedda Michelle Guevara-Nieto, Rafael Santiago Parra-Medina, Juan Carlos Mejia Henao, Jone Garai, Jovanny Zabaleta, Liliana Lopez-Kleine, Alba Lucia Combita. Evaluation of genetic ancestry as a covariable in gene expression analysis for chemotherapy response in Colombian breast cancer women [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR015.

Background: Heterogeneity between different breast cancer tumors plays an important role in patients’ survival outcomes, and such tumor heterogeneity unveiled by transcriptome and proteome are often in disagreement. We hypothesize that alternative splicing of mRNA could explain heterogeneity within intrinsic breast cancer subtypes. Methods: Cases used in this study were drawn from the Clinical Breast Care Project where breast cancer patients were consented using an IRB-approved protocol. Fifty breast tumors were selected and processed by laser microdissection. RNA and protein were extracted from tissues using the Illustra triplePrep kit (GE Healthcare). Paired-end mRNA sequencing was performed using the Illumina HiSeq platform. Paired-end reads were preprocessed using PRINSEQ and splice-aligned to the genome using GSNAP software. Gene counts were measured using HTSeq while Exon counts used the DEXSeq. Differential expression was called at 10% false discovery rate. Proteome Discoverer with Byonic node was used for analyzing the quantitative global proteomics dataset, and we were able to quantitate 8600 proteins. All other analyses were performed using Perl and R. Results: The number of sequencing reads for the 50 cases ranged from 60 million to 410 million reads. After preprocessing, an average of 93% of reads was mapped, and 36,700 genes were identified among 50 tumor samples. PAM50 algorithm was used for intrinsic subtype calls, yielding 16 Basal, 8 Her2+, 19 Luminal A (LA) and 7 Luminal B tumors. Unsupervised clustering of the 8 Her2+ cases using the PAM50 genes and highly varying proteins resulted in different clustering patterns, with the latter clustering 6 of the 8 Her2+ cases with two distinct 3-case sub-clusters. Between these two sub-clusters, there were 10 differentially expressed (DEX) genes and 25 DEX proteins, but none of the 25 proteins were mapped to the 10 DEX genes. This motivated us to investigate the DEX exons, and we found 7,076 DEX exons between the Her2+ sub-clusters, and 9 of the 25 DEX proteins were matched to genes bearing DEX exons. For comparison, we performed the same analyses between similarly clustered Basal and LA sub-clusters. Even though the number of DEX genes between Basal (8) and LA (18) sub-clusters were comparable to that between the Her2+ sub-clusters, DEX exons were much lower for both subtypes (616 & 157), and none of the DEX proteins (3 & 7) mapped to DEX exons or genes for either subtype. Conclusions: Our findings imply that there is more proteomic-level heterogeneity in the Her2+ subtype than in Basal and LA subtypes, which could be due to alternative usage of exons (alternative splicing). If such heterogeneity is associated with patients’ survival outcomes then our results will further stress the importance of alternative splicing in breast cancer. The views expressed in this article are those of the author and do not reflect the official policy of the Department of Defense, or U.S. Government. Citation Format: Praveen Kumar Raj Kumar, Tao Liu, Lori A. Sturtz, Albert Kovatich, Marina A. Gritsenko, Vladislav A. Petyuk, Brenda Deyarmin, Viswanadham Sridhara, James Craig, Jason E. McDermott, Anil K. Shukla, Ronald J. Moore, Matthew E. Monroe, Bobbie-Jo M. Webb-Robertson, Jeffrey A. Hooke, Leigh Fantacone-Campbell, Leonid Kvecher, Jianfang Liu, Jennifer Kane, Jennifer Melley, Stella Somiari, Joji Iida, Stephen C. Benz, Justin Golovato, Shahrooz Rabizadeh, Patrick Soon-Shiong, Richard D. Smith, Richard J. Mural, Karin D. Rodland, Craig D. Shriver, Hai Hu. Differential exon usage in the HER2 subtype of breast cancer identified with RNA-seq and proteomic data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3372. doi:10.1158/1538-7445.AM2017-3372

Background: TP53 alterations have been identified in approximately 20% of breast carcinomas, especially in ER/PR negative high grade carcinomas. It is believed that TP53 alteration is an early event in the carcinogenesis of high grade breast carcinomas. TP53 alteration could even be identified in morphologically "benign" appearing breast tissues. Nevertheless, the precursor lesion of high grade ductal carcinoma in situ and/or invasive carcinoma is not well recognized morphologically. Design: We retrospectively analyzed the TP53 status of 108 cases with high grade (modified Bloom-Richardson grade 3) invasive ductal carcinoma, 51 cases with non-high grade invasive ductal carcinoma, and 50 cases with benign breast from mammoplasty. The high grade carcinomas were all estrogen receptor (ER) and progesterone receptor (PR) negative and 96.3% of them were HER-2 negative. The non-high grade carcinomas were all ER and/or PR positive, 92.2% Her2 negative. Blocks with tumor and/or benign tissue were selected from each case. Immunohistochemical stain for p53 was performed. TP53 gene sequencing was performed on selected tumors with inconclusive p53 staining. Further ER and Ki67 immunohistochemical stains were performed on the blocks with p53 positive benign tissue. Results: Of the 108 high grade carcinomas, 48 (44%) were positive for TP53 alteration. Seventeen of the 48 (35.4%) cases also showed focal p53 staining in the adjacent benign appearing tissue. Only one case was negative for TP53 alteration in tumor but with focal p53 staining in benign tissue. Of the non-high grade carcinomas, 5 (9.8%) were positive for TP53 alteration, one of which had focal p53 staining in adjacent benign breast tissue. No p53 staining positivity was identified in the mammoplasty specimens. The p53 staining positive benign glands were ER negative, and did not show an increase in Ki67 labeling index. The morphology of these cells appeared to be slightly enlarged nuclei, with a mildly increased nuclear/cytoplasm ratio, slightly irregular nuclear contours, open chromatin, and prominent nucleoli, but still within the limits of "benign" glands. Conclusion: TP53 is already altered in "benign" appearing breast glands in patients with high grade breast carcinomas. These glands show the same ER status as their counterpart carcinomas, but remain inactive with low Ki67 labeling index, indicating further genetic changes are needed to trigger the unlimited tumor growth and fully malignant transformation. The special morphology and p53 positivity of the "benign" appearing cells could serve as an indicator for future potential risk of TP53 positive high grade breast carcinoma. Citation Format: Xi Wang, Moritz Stolla, Todd S Laughlin, Paul G Rothberg, Kristin Skinner, David G Hicks. TP53 alteration in morphologically benign breast tissue in patients with ER/PR negative high grade breast carcinomas: Marker for early detection of high risk patients for high grade carcinomas? [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-07-08.

GATA3 mutations are known to play an important role in breast cancer progression. The exact role and mechanisms of these mutations remain controversial as some studies suggest a relation to breast tumor growth, while others suggest a relation to longer survival. GATA3 germline mutations are not well studied in breast cancer. In this study, it was hypothesized that different types of GATA3 mutations could contribute to the breast cancer progression in different ways. GATA3 exon 6, which is important for GATA3 protein functions, was reported to have hotspots, and hence it was selected for study. Intronic GATA3 germline mutations were found to be related to favorable prognosis, while protein coding mutations were found to be related to unfavorable prognosis. Bioinformatics study of large publically available datasets showed that GATA3 mutations lead to dysregulation of pathways related to T-cells activation, inflammation, and breast cancer development.

: Fatty acid binding protein 5 (FABP5) is a small, 14-15 kDa, molecular weight intracellular fatty acid shuttle. FABP5 functions to shuttle long chain fatty acids from the extracellular environment to the nucleus. These fatty acids are then used as ligands for nuclear receptors and activate transcription. FABP5 has been shown to coordinate metabolic and inflammatory responses in adipocytes and may play a role in the development of obesity-mediated breast cancer. Both FABP5 and S100A7 proteins are over-expressed in the inflammatory skin disease, psoriasis. Additionally, there is evidence that these two proteins associate with one another. Previously reported by our lab, S100A7 enhances tumor progression in orthotopic breast cancer mouse models. Taking together the evidence of S100A7 in breast cancer progression and the support that FABP5 is involved in breast cancer development and progression. We have shown overexpression of FABP5 in mammary glands of mice overexpressing mS100a7a15, the mouse homolog of human S100A7. FABP5 was also shown to be expressed higher in S100A7 overexpressing triple negative breast cancer cells compared to vector control. Additionally, FABP5 has higher expression in a highly metastatic breast cancer cell line compared to a low metastatic breast cancer cell line. We determined FABP5 knockout in the host significantly decreases tumor volume in an orthotopic model of breast cancer. We showed that shRNA mediated FABP5 knockdown in triple negative breast cancer cells results in less migration compared to scrambled shRNA. Additional cell lines are being evaluated and used to validate these results. FABP5 expression was examined in a tumor microarray and found that FABP5 expression is correlated with higher tumor grade and triple negative breast cancer. Additionally, high FABP5 protein expression is associated with shorter disease free recurrence.

Long non coding RNAs (lncRNAs) have been identified as regulators of the cell cycle, apoptosis, and DNA damage among other processes that if deregulated, may lead to cancer by acting as proto-oncogenes, tumor suppressor genes, and drivers of metastatic transformation. Using RNA sequencing we have identified 42 differentially expressed lncRNAs from a healthy cohort of parous vs. nulliparous women. After bioinformatics and RT-qPCR analysis, we have focused on a vaguely studied lncRNA called BC200 that is highly expressed in the nulliparous postmenopausal breast tissue. It is known that BC200 lncRNA is overexpressed in invasive and pre-invasive breast cancer; however, its functional role in the initiation and progression of breast cancer is poorly understood. In the present work we provide insight on the role of BC200 in the context of luminal and triple negative breast cancer (TNBC). We have confirmed that BC200 is highly expressed in breast cancer tissue and in widely used breast cancer cell lines such as MCF7, T47D, MDAMB231, and Hs578T. Using a lentiviral system we successfully obtained cell lines which stably express BC200. Overexpression of BC200 increases proliferation, migration, and invasion potential in vitro in the cell lines tested, specifically luminal T47D and TNBC MDAMB231. Xenograft studies performed in the mammary fat pad of female SCID mice confirm the role of BC200 as a tumor promoter. Tumors in mice injected with MDAMB231 cells overexpressing BC200 were 4.5 times bigger than tumors in the control group in only 6 weeks when injecting 1 million cells. Moreover, we have determined, using reverse transcriptase PCR targeting genes less than 200 kb from the start site of BC200, that when BC200 is overexpressed, CALM2 is downregulated in both T47D and MDAMB231 cell lines. CALM2 or Calmodulin is a calcium binding protein that plays a role in signaling pathways, cell cycle progression, proliferation, and apoptosis. Mutations in CALM2 are associated with increased risk of breast cancer. Our positive results on Cis regulation are being expanded using chromatin isolation by RNA immunoprecipitation to determine BC200's genome wide regulation. These results demonstrate the participation of BC200 lncRNA in the progression of breast cancer. Notably, BC200 regulates nearby genes that have an implication in cancer progression. BC200, identified in the normal breast tissue of nulliparous women, not only plays a key role in breast cancer progression but also provides a new insight in the preventive role of pregnancy by the downregulation of the expression of this lncRNA in the normal parous breast. [This work was supported by the NCI (National Cancer Institute) Core Grant CA06927 to Fox Chase Cancer Center and generous support from Christian - Diane Martin, the Flyers Wives, and Joseph - Barbara Breitman to Dr. J. Russo, MD]. Citation Format: Barton M, Santucci-Pereira J, Su Y, Russo J. BC200 lncRNA is involved in the progression of triple negative breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-08-06.

<title>Abstract</title> Objective(s): 1. The common differential genes of breast cancer and thyroid cancer were identified by Gene Express Omnibus database (GEO). The Cancer Genome Atlas (TCGA) database was used to determine the relationship between the screened differential genes and the clinicopathologic features. Gene set enrichment analysis (GSEA) was used to identify the enrichment pathways of the differential genes in breast and thyroid cancers.2. Retrospective studies were conducted to analyze the relationship between the general characteristics, clinicopathological features, and hormone expression levels in patients with dual cancers of breast cancer combined with thyroid cancer and patients with breast cancer and thyroid cancer alone, and to further analyze the KRT19 expression levels in their tissues. analyze the expression of KRT19 protein in their tissues. Method(s): 1. Download the datasets GSE70947 and GSE3467 from the GEO database, analyze the differential genes of breast cancer, thyroid cancer and normal tissues respectively by using R, and take the intersection of the differential genes of the two tissues to continue the next step of the study. 2. Download the mRNA-seq data of the above differential genes of BRCA and THCA from the TCGA database, and identify the differences in expression of differential genes between normal tissues and tumor tissues by using the above differential gene substitution in R. Gene set enrichment analysis (GSEA) identifies the differences in expression of differential genes enriched in breast and thyroid cancer. Differential gene substitution analysis, and identify the differences in differential gene expression between normal and tumor tissues, Gene set enrichment analysis (GSEA) to identify the pathways of enrichment in breast and thyroid cancers, and then screened out the representative differential gene KRT19 (human cytokeratin 19).3. Collect the mRNA-seq data of BRCA and THCA in the database of TCGA, and use the R language in the substitution analysis of the above differential genes, and identify the differences in differential gene expression between normal and tumor tissues. 3. July 2023 in Zhongshan People's Hospital and puncture or surgical treatment of breast cancer combined with thyroid cancer patient data, a total of 92 cases (experimental group), another randomly collected in the past two years in Zhongshan People's Hospital in the simple breast cancer patients 100 cases (control group 1), thyroid cancer patients, 100 cases (control group 2). 4. the experimental group and the control group 1, 2 of the patient pathology data for Pathological data of patients in experimental and control groups 1 and 2 were retrospectively analyzed, and additional surgical bulk or puncture specimens were subjected to immunohistochemical staining (IHC) to examine the expression of KRT19 protein in the tissues, and to explore whether there was a difference in its expression between experimental and control groups. Result(s): 1. KRT19 mRNA levels were significantly overexpressed in breast and thyroid cancer tissues as analyzed by the GEO database, and KRT19 was associated with clinicopathological features of breast and thyroid cancers as analyzed by the TCGA database, and the GSEA showed that both the breast and thyroid cancer-KRT19 overexpression groups were significantly enriched in the estrogen-responsive pathway.2. In the dual-primary cancer group, of which breast cancer preceded In the dual-primary cancer group, breast cancer preceded thyroid cancer in 86 cases and thyroid cancer preceded in 6 cases, i.e., breast cancer preceded thyroid cancer in the vast majority of patients (&gt; 90%). Compared with the breast cancer group, the dual-primary cancer group was younger at the time of diagnosis, more often in the premenopausal state, with a larger tumor size, and more often positively expressed estrogen receptors (ER) and progesterone receptors (PR), with a statistically significant difference (all <italic>P</italic> &lt; 0.050). Compared with the thyroid cancer group, the odds of tumors occurring bilaterally were increased in the double primary cancer group, and the levels of triiodothyronine (T3) and thyroxine (T4) (both <italic>P</italic> &lt; 0.050) were significantly higher. KRT19 was more frequently positively expressed in breast cancer than in breast cancer alone in dual primary cancers ( <italic>P</italic> = 0.069), and in thyroid cancer than in thyroid cancer alone in dual primary cancers ( <italic>P</italic> &lt; 0.050). Conclusion(s): Pathogenesis correlates between breast and thyroid cancers, estrogen receptor expression is associated with dual carcinogenesis, and KRT19 influences dual carcinogenesis through the estrogen response pathway.

BackgroundNormalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to minimize the bias introduced by DEGs in the normalization step. The modified t-test is derived based on asymptotic theory for hypothesis testing that suitably pairs with the proposed robust normalization.ResultsWe first compared super-delta with four commonly used normalization methods: global, median-IQR, quantile, and cyclic loess normalization in simulation studies. Super-delta was shown to have better statistical power with tighter control of type I error rate than its competitors. In many cases, the performance of super-delta is close to that of an oracle test in which datasets without technical noise were used. We then applied all methods to a collection of gene expression datasets on breast cancer patients who received neoadjuvant chemotherapy. While there is a substantial overlap of the DEGs identified by all of them, super-delta were able to identify comparatively more DEGs than its competitors. Downstream gene set enrichment analysis confirmed that all these methods selected largely consistent pathways. Detailed investigations on the relatively small differences showed that pathways identified by super-delta have better connections to breast cancer than other methods.ConclusionsAs a new pipeline, super-delta provides new insights to the area of differential gene expression analysis. Solid theoretical foundation supports its asymptotic unbiasedness and technical noise-free properties. Implementation on real and simulated datasets demonstrates its decent performance compared with state-of-art procedures. It also has the potential of expansion to be incorporated with other data type and/or more general between-group comparison problems.

BackgroundDifferential gene expression analysis using RNA-seq data is a popular approach for discovering specific regulation mechanisms under certain environmental settings. Both gene ontology (GO) and KEGG pathway enrichment analysis are major processes for investigating gene groups that participate in common biological responses or possess related functions. However, traditional approaches based on differentially expressed genes only detect a few significant GO terms and pathways, which are frequently insufficient to explain all-inclusive gene regulation mechanisms.MethodsTranscriptomes of survivin (birc5) gene knock-down experimental and wild-type control zebrafish embryos were sequenced and assembled, and a differential expression (DE) gene list was obtained for traditional functional enrichment analysis. In addition to including DE genes with significant fold-change levels, we considered additional associated genes near or overlapped with differentially expressed long noncoding RNAs (DE lncRNAs), which may directly or indirectly activate or inhibit target genes and play important roles in regulation networks. Both the original DE gene list and the additional DE lncRNA-associated genes were combined to perform a comprehensive overrepresentation analysis.ResultsIn this study, a total of 638 DE genes and 616 DE lncRNA-associated genes (lncGenes) were leveraged simultaneously in searching for significant GO terms and KEGG pathways. Compared to the traditional approach of only using a differential expression gene list, the proposed method of employing DE lncRNA-associated genes identified several additional important GO terms and KEGG pathways. In GO enrichment analysis, 60% more GO terms were obtained, and several neuron development functional terms were retrieved as complete annotations. We also observed that additional important pathways such as the FoxO and MAPK signaling pathways were retrieved, which were shown in previous reports to play important roles in apoptosis and neuron development functions regulated by the survivin gene.ConclusionsWe demonstrated that incorporating genes near or overlapped with DE lncRNAs into the DE gene list outperformed the traditional enrichment analysis method for effective biological functional interpretations. These hidden interactions between lncRNAs and target genes could facilitate more comprehensive analyses.

Breast cancer is a complex and heterogeneous disease that arises from epithelial cells lining the breast ducts and lobules. Correct adhesion between adjacent epithelial cells is important in determining the normal structure and function of epithelial tissues, and there is accumulating evidence that dysregulated cell-cell adhesion is associated with many cancers. This review will focus on one cell-cell adhesion complex, the tight junction (TJ), and summarize recent evidence that TJs may participate in breast cancer development or progression. We will first outline the protein composition of TJs and discuss the functions of the TJ complex. Secondly we will examine how alterations in these functions might facilitate breast cancer initiation or progression; by focussing on the regulatory influence of TJs on cell polarity, cell fate and cell migration. Finally we will outline how pharmacological targeting of TJ proteins may be useful in limiting breast cancer progression. Overall we hope to illustrate that the relationship between TJ alterations and breast cancer is a complex one; but that this area offers promise in uncovering fundamental mechanisms linked to breast cancer progression.

Breast cancer is one of the most common cancers causing a high mortality worldwide. This study aimed to identify differential methylation and expression genes with prognostic value in breast cancer. DNA methylation and gene expression profiles (GSE60185, GSE42568, GSE21653, GSE58812, and GSE52865) were downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) databases. The differentially expressed genes (DEGs) and differential methylation genes were identified between breast cancer samples and normal samples. Functional analysis was performed using DAVID (Database for Annotation, Visualization, and Integrated Discovery) tool. Furthermore, functional epigenetic modules (FEM) were analyzed to identify critical genes with prognostic values. A large amount of DEGs and aberrant methylation genes were identified between breast cancer samples and normal samples. These genes were mainly associated with several GO (Gene Ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, such as neuroactive ligand-receptor interaction, alcoholism, gamma-aminobutyric acid signaling pathway, and G-protein-coupled receptor signaling pathway. Additionally, 10 DEGs with differential methylation levels were significantly correlated with survival outcomes in breast cancer patients. FEM analysis revealed that several DEGs (e.g., GABRA4, GABRG1, and GABRA1) in module GABRA4 were identified as potential biomarkers in breast cancer patients. Several DEGs identified were associated with breast cancer prognosis. These DEGs might act as prognostic and diagnostic markers in breast cancer.

Historically, incidence rates of breast cancer (BC) have been higher among Caucasian (CA) women compared to African-American (AA) women, until convergence of these rates in the mid 2000s. Conversely, when accessing mortality rates among these women, AA women have reported higher rates of mortality from BC since the mid 1980s. Despite a decline in BC mortality over the past 30 years, the mortality rate of disease among AA women remains to be significantly higher than that of their CA counterparts. When molecular subtypes of BC are considered, prevalence of Triple-Negative BC (TNBC), the most aggressive subtype of BC, is found to be higher among AA women. TNBC prevalence on the global scale shows highest levels of TNBC across Africa, and higher rates can also be observed across the African diaspora. To address this, we sought out to identify race-specific differences among TNBC cases. We completed RNA sequencing on a cohort of 75 cases, where 42 of the cases were AA, and 33 were CA. The dataset was dichotomized by if the individuals had received neoadjuvant chemotherapy prior to surgery and specimen collection, where we had 60 treatment naïve cases (31 AAs and 29 CAs) and the remaining 15 had received neoadjuvant chemotherapy (residual tumors; 11 AAs and 4 CAs). We assessed self-reported race, ancestry estimation from matched DNA samples into and TNBC molecular subtyping from matched DNA samples into our DE gene expression analyses. Among treatment naïve tumors, we identified over 1000 genes that were significantly differentially expressed (DE) between race groups (p &amp;lt; 0.05). To further analyze our race-specific gene set, we used Ingenuity Pathway Analysis (IPA) to investigate relevant pathways and regulators specific to our gene set. Using the causal network analysis, we see that biological functions such as cellular organization and assembly show significant enrichment in our gene set, and that the NFkB complex is a top regulator predicted to be activated in our AA treatment naïve cases compared to CAs. For those individuals who had received neoadjuvant chemotherapy, we identified 13 genes that are significantly different between race groups, and these DE genes are distinct from those identified in our treatment naïve analyses. Citation Format: Rachel Martini, Jason White, Akanksha Verma, Olivier Elemento, Lisa Newman, Manne Upender, Clayton Yates, Melissa Davis. Race-specific gene expression patterns in triple-negative breast cancer (TNBC) cases [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr B107.