Significance Of Metastasis Research Articles

Abstract GS3-08: Multiplatform analysis of matched primary and metastatic breast tumors from the AURORA US Network

Abstract Background: It has become increasingly clear that effective treatment of metastatic breast cancer (MBC) requires an in-depth understanding of the molecular differences between primary tumors and metastases. The AURORA US Network was established to collect primary breast cancer-metastasis pairs for multi-platform genomic profiling in order to identify the molecular drivers of metastatic disease. AURORA US has both a retrospective and prospective phase. This is the first report of the retrospective phase. Methods: Archived tissue samples from the primary tumor and at least one distant metastasis were retrospectively collected from 83 MBC patients. Following internal quality assessment, samples from 55 pts, including 105 distinct metastatic lesions, were subject to DNA low pass whole genome and exome sequencing, DNA methylation arrays, and RNA sequencing. Early analyses of these multi-platform data include: DNA methylation, tumor gene expression and microenvironmental signatures, somatic and germline variants, DNA copy number changes, and structural variants between breast primaries and matched metastases. Results: Median age at diagnosis was 49 years (25-76); 32 (58%) were Stage I or II at presentation, 27 (49%) had a family history of breast cancer, and 20 (36%) had a second breast primary. Median disease-free interval before developing MBC was 2 years (range 0-36, 5 patients presented with Stage IV). Median overall survival from initial presentation was 4 years (range 0-37). Median survival after developing MBC was 1 year (range 0-13), with a median of three treatments. Primary tissue samples were banked from 1977-2017 and metastases were banked from 1999-2017. Clinical phenotypes of the primaries included 27 HR+ (49%), 15 triple negative (TNBC, 27%), and 11 HER2+ (20%, 12 missing HER2 status). Intrinsic subtype distribution of the primaries included 17 Basal-like (31%), 17 Luminal A (31%), 7 Normal-like (13%), 5 HER2-enriched (9%), and 1 Luminal B, with 8 pending. All metastases from the Basal-like cases remained Basal-like, while metastases from luminal primaries tended to gain HER2-Enriched subtype features (5/18, p = 0.01). Overall, we identified significant metastasis-enriched alterations in metabolism pathways, an increase in proliferation, and the loss of differentiation signatures and immune infiltrates with progression; the latter being the most pronounced in brain metastases. The most frequent somatic mutations in this cohort were in TP53, NCOR1, and RUNX1. Interestingly, ERBB2, EGFR, and ATM were also mutated in ≥10% of the tumors sequenced. In almost all cases, CpG island hypermethylation was clonally present in the primary tumor and persisted stably in the majority of metastatic lesions. Promoter CpG island hypermethylation was also identified in some metastatic lesions at JAM3, an important cellular adhesion molecule,and this was accompanied by reduced mRNA expression. CONCLUSIONS: Collection of banked primary and metastatic tissue pairs identified a young MBC cohort with a high frequency of breast cancer family history and second breast primaries. Molecular characterization of luminal tumor pairs highlighted acquisition of aggressive traits including increased proliferation and loss of differentiation in the metastases. In contrast, basal-like pairs remained relatively unchanged, except for the loss of immune activation. Ongoing analyses to be presented include clonal heterogeneity and phylogeny, novel metastasis signature discovery, gene fusion, and endogenous retrovirus detection. Citation Format: Tari A King, Minetta C Liu, Marni B McClure, Toshinori Hinoue, Benjamin J Kelly, Chad J Creighton, Jay Bowen, Kristen Leraas, Robyn T Burns, Sara Coppens, Salma Rezk, Amy L Garrett, Justin M Balko, Joel S Parker, Ben H Park, Ian Krop, Carey Anders, Katherine A Hoadley, Julie Gastier-Foster, Mothaffar F Rimawi, Rita Nanda, Nancy U Lin, Claudine Isaacs, P. Kelly Marcom, Anna Maria Storniolo, Fergus J Couch, Elaine R Mardis, Adrian V Lee, Uma Chandran, Peter W Laird, Susan G Hilsenbeck, Larry Norton, Andrea L Richardson, W. Fraser Symmans, Lisa A Carey, Antonio C Wolff, Nancy E Davidson, Charles M Perou, the AURORA US Network. Multiplatform analysis of matched primary and metastatic breast tumors from the AURORA US Network [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr GS3-08.

Abstract P3-01-27: Ectonucleotidase ATP hydrolysis facilitates breast cancer bone metastasis

Abstract Bone is the most common site for breast cancer metastasis. Osteocytes are the most abundant bone cell and can signal nearby cells by releasing ATP through connexin 43 hemichannels. We previously found that this signaling pathway hindered breast cancer growth in bone. In this study, we investigated the role of purinergic signaling on breast cancer bone metastasis in patient samples. Surprisingly, no ATP receptors were differentially expressed in bone metastases compared to other sites. However, enzymes that degrade ATP into adenosine (CD39/ENTPD1 and CD73/NT5E) were upregulated, as was the ADORA3 adenosine receptor (Limma, p=0.037, 0.016, 0.0019, respectively). We next investigated whether this expression signature in primary tumors predicts bone metastasis. In primary ER+ breast cancer, which predominately metastasizes to bone, high expression of these genes is correlated with lower distant metastasis-free survival (HR = 1.97, 1.49, 2.03, logrank p=0.0017, 0.0004, 0.0012). Moreover, this expression pattern is correlated with a bone metastasis signature (Spearman R=0.28, p=1.2 × 10−20). In a pharmacologic screen of 750 cancer cell lines, breast cancer lines and especially ER+ ones, are uniquely sensitive to a pan-adenosine receptor inhibitor (Limma, p=2.9 × 10−5) and ADORA3/2B inhibitor (p=5.4 × 10−5). Our findings suggest that an expression program to convert ATP to adenosine facilitates bone metastasis and begins in the primary tumor. ADORA3 inhibition is proposed as a pharmacologic strategy for preventing or treating bone metastasis. Furthermore, bone metastases should be analyzed in anti-CD39 and CD73 clinical trials. Citation Format: Daniel B Shropshire, Jaime Benavides, Jean X Jiang. Ectonucleotidase ATP hydrolysis facilitates breast cancer bone metastasis [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-01-27.

MiR-431 Promotes Metastasis of Pancreatic Neuroendocrine Tumors by Targeting DAB2 Interacting Protein, a Ras GTPase Activating Protein Tumor Suppressor

The incidence of pancreatic neuroendocrine tumor (PNET) is increasing, and it presents with various clinical manifestations and an unfavorable survival rate. A better understanding of the drivers of PNET tumorigenesis is urgently needed. Distinct miRNA signatures have been identified for different stages of tumorigenesis in both human and mouse PNETs. The functions of these miRNAs are poorly understood. miR-431 is the most up-regulated miRNA in the metastatic signature. However, it is unknown whether miR-431 contributes to metastasis of PNETs. Herein, we show that miR-431 overexpression activates Ras/extracellular signal-regulated kinase (Erk) signaling and promotes epithelial-mesenchymal transition, migration/invasion invitro, and metastasis in both xenograft and spontaneous mouse models of PNET. Treatment of PNET cells with Erk inhibitor or locked nucleic acids sequestering miR-431 inhibits invasion. Four target prediction modules and dual-luciferase reporter assays were used to identify potential mRNA targets of miR-431. A Ras GTPase activating protein tumor suppressor (RasGAP), DAB2 interacting protein (DAB2IP), was discovered as an miR-431 target. Overexpression of DAB2IP's rat homolog, but not its mutant defective in Ras GTPase activating protein activity, reverses miR-431's effect on promoting invasion, Erk phosphorylation, and epithelial-mesenchymal transition of PNETs. Taken together, miR-431 silences DAB2IP to active Ras/Erk and promote metastasis of PNETs. miR-431 may be targeted to manage metastatic PNETs.

Plasma protein-based signature predicts distant metastasis and induction chemotherapy benefit in Nasopharyngeal Carcinoma.

Rationale: Currently, for locoregionally advanced nasopharyngeal carcinoma (LA-NPC), there is no effective blood-based method to predict distant metastasis. We aimed to detect plasma protein profiles to identify biomarkers that could distinguish patients with NPC who are at high risk of posttreatment distant metastasis.Methods: A high-throughput antibody array was initially applied to detect 1000 proteins in pretreatment plasma from 16 matched LA-NPC patients with or without distant metastasis after radical treatment. Differentially expressed proteins were further examined using a low-throughput array to construct a plasma protein-based signature for distant metastasis (PSDM) in a cohort of 226 patients.Results: Fifty circulating proteins were differentially expressed between metastatic and non-metastatic patients and 18 were proven to be strongly correlated with distant metastasis-free survival (DMFS) in NPC. A PSDM signature consisting of five proteins (SLAMF5, ESM-1, MMP-8, INSR, and Serpin A5) was established to assign patients with NPC into a high-risk group and a low-risk group. Patients in the high-risk group had shorter DMFS (P < 0.001), disease-free survival (DFS) (P < 0.001) and overall survival (OS) (P < 0.001). Moreover, the PSDM performed better than N stage and Epstein-Barr virus (EBV) DNA load at effectively identifying patients with NPC at high risk of metastasis. For patients in the high-risk group, induction chemotherapy significantly improved DMFS, DFS, and OS.Conclusions: The PSDM could be a useful liquid biopsy tool to effectively predict distant metastasis and the benefit of induction chemotherapy in patients with LA-NPC.

Label-free whole-colony imaging and metabolic analysis of metastatic pancreatic cancer by an autoregulating flexible optical system

Cancer metastasis is a Gordian knot for tumor diagnosis and therapy. Many studies have demonstrated that metastatic processes are inevitably affected by the tumor microenvironment. Histopathology is used universally as the gold standard for cancer diagnosis despite the lengthy preparation process and invasiveness.Methods: Here, we introduced a supercontinuum and super-wide-tuning integrated multimodal platform, which combines the confocal, nonlinear and fluorescence lifetime microscopy with autoregulations, for label-free evaluation of fresh tissue and pathological sections. Based on various automated tunable lasers, synchronized and self-adjusting components and eight fast switching detection channels, the system features fast, large-field and subcellular-scale imaging of exogenous and endogenous fluorophores, nonlinear coherent scattering and lifetime contrast.Results: With such an integrated multi-dimensional system, we searched the metastatic region by two-photon and three-photon excited autofluorescence, analyzed the cancer invasion by second harmonic generation and revealed the affected cellular metabolism by phasor-lifetime. We demonstrated the flexible measurement of multiple nonlinear modalities at NIR I and II excitation with a pre-compensation for group delay dispersion of ~7,000 fs2 and low power of <40 mW, and of dual autofluorescence lifetime decays for phasor approach to decompose cancer-associated and disassociated components. This significantly revealed the metastatic and metabolic optical signatures of the whole colony of pancreatic cancers.Conclusion: The synergistic effect of the system demonstrates the great potential to translate this technique into routine clinical applications, particularly for large-scale and quantitative studies of metastatic colonization.

Use Large-Scale Samples to Identify Colon-Adenocarcinoma Metastasis-Associated Genetic Signatures and Exploit Potential Targeted Drug Molecules

Aim: Distant metastasis is the main cause of death in patients with colon cancer. Due to the lack of effective molecular markers and treatment, the prognosis of patients with metastatic colon cancer is still rather poor. This research attempts to explore the molecular markers related to colon cancer metastasis and provide potential treatment methods through bioinformatics analysis. Methods: RNASeq data and clinical follow-up information were downloaded from TCGA and GEO, the differentially expressed genes (DEGs) of stage I and stage IV in colon cancer were screened and further verified in GSE41258 dataset. Univariate cox risk regression model is used to analyze the relationship between DEGs and the prognosis of metastatic events. L1000FWD and DGIdb databases are used to mine small molecular substances related to DEGs. Results: Sixteen genes related to metastasis were identified and defined as metastatic related signatures (MRS). Prognostic analysis showed that 14 MRS genes are significantly related to the overall survival. Further functional enrichment analysis showed that MRS gene was significantly related to important biological functions such as cell migration, and apoptosis. Conclusion: This study has screened and identified a group of genes associated with metastasis in patients with colon cancer. Furthermore, the exploration of the potential function and potential drug of MRS gene increases the understanding of the factors affecting the metastasis of colon cancer and provides a potential treatment for metastatic patients. Funding Statement: The authors stated: No funding. Declaration of Interests: The authors declare that there are no conflicts of interest. Ethics Approval Statement: The authors stated: Not applicable.

Deep Learning Signature Based on Staging CT for Preoperative Prediction of Sentinel Lymph Node Metastasis in Breast Cancer

To evaluate the noninvasive predictive performance of deep learning features based on staging CT for sentinel lymph node (SLN) metastasis of breast cancer. A total of 348 breast cancer patients were enrolled in this study, with their SLN metastases pathologically confirmed. All patients received contrast-enhanced CT preoperative examinations and CT images were segmented and analyzed to extract deep features. After the feature selection, deep learning signature was built with the selected key features. The performance of the deep learning signatures was assessed with respect to discrimination, calibration, and clinical usefulness in the primary cohort (184 patients from January 2016 to March 2017) and then validated in the independent validation cohort (164 patients from April 2017 to December 2018). Ten deep learning features were automatically selected in the primary cohort to establish the deep learning signature of SLN metastasis. The deep learning signature shows favorable discriminative ability with an area under curve of 0.801 (95% confidence interval: 0.736-0.867) in primary cohort and 0.817 (95% confidence interval: 0.751-0.884) in validation cohort. To further distinguish the number of metastatic SLNs (1-2 or more than two metastatic SLN), another deep learning signature was constructed and also showed moderate performance (area under curve 0.770). We developed the deep learning signatures for preoperative prediction of SLN metastasis status and numbers (1-2 or more than two metastatic SLN) in patients with breast cancer. The deep learning signature may potentially provide a noninvasive approach to assist clinicians in predicting SLN metastasis in patients with breast cancer.

The Precursor for Nerve Growth Factor (proNGF) in Thyroid Cancer Lymph Node Metastases: Correlation with Primary Tumour and Pathological Variables.

Metastases in thyroid cancer are associated with aggressive disease and increased patient morbidity, but the factors driving metastatic progression are unclear. The precursor for nerve growth factor (proNGF) is increased in primary thyroid cancers, but its expression or significance in metastases is not known. In this study, we analysed the expression of proNGF in a retrospective cohort of thyroid cancer lymph node metastases (n = 56), linked with corresponding primary tumours, by automated immunohistochemistry and digital quantification. Potential associations of proNGF immunostaining with clinical and pathological parameters were investigated. ProNGF staining intensity (defined by the median h-score) was significantly higher in lymph node metastases (h-score 94, interquartile range (IQR) 50–147) than in corresponding primary tumours (57, IQR 42–84) (p = 0.002). There was a correlation between proNGF expression in primary tumours and corresponding metastases, where there was a 0.68 (95% CI 0 to 1.2) increase in metastatic tumour h-score for each unit increase in the primary tumour h-score. However, larger tumours (both primary and metastatic) had lower proNGF expression. In a multivariate model, proNGF expression in nodal metastases was negatively correlated with lateral neck disease and being male. In conclusion, ProNGF is expressed in locoregional metastases of thyroid cancer and is higher in lymph node metastases than in primary tumours, but is not associated with high-risk clinical features.

Comparative\xa0transcriptome analysis of matched primary and distant metastatic ovarian carcinoma

BackgroundHigh grade serous ovarian carcinoma (HGSOC) is the most common subtype of epithelial ovarian cancers (EOC) with poor prognosis. In most cases EOC is widely disseminated at the time of diagnosis. Despite the optimal cytoreductive surgery and chemotherapy most patients develop chemoresistance, and the 5-year overall survival being only 25–35%.MethodsHere we analyzed the gene expression profiles of 10 primary HGSOC tumors and 10 related omental metastases using RNA sequencing and identified 100 differentially expressed genes.ResultsThe differentially expressed genes were associated with decreased embryogenesis and vasculogenesis and increased cellular proliferation and organismal death. Top upstream regulators responsible for this gene signature were NR5A1, GATA4, FOXL2, TP53 and BMP7. A subset of these genes were highly expressed in the ovarian cancer among the cancer transcriptomes of The Cancer Genome Atlas. Importantly, the metastatic gene signature was suggestive of poor survival in TCGA data based on gene enrichment analysis.ConclusionBy comparing the gene expression profiles of primary HGSOC tumors and their matched metastasis, we provide evidence that a signature of 100 genes is able to separate these two sample types and potentially predict patient survival. Our study identifies functional categories of genes and transcription factors that could play important roles in promoting metastases and serve as markers for cancer prognosis.

CD105 Is Expressed in Ovarian Cancer Precursor Lesions and Is Required for Metastasis to the Ovary.

Most high-grade serous ovarian cancers (HGSCs) initiate from the fallopian tube epithelium and then metastasize to the ovary and throughout the abdomen. Genomic analyses suggest that most HGSCs seed the ovary prior to abdominal dissemination. Similarly, animal models support a critical role for the ovary in driving abdominal dissemination. Thus, HGSC cell recruitment to the ovary appears to be a critical component of HGSC cell metastasis. We sought to identify factors driving HGSC recruitment to the ovary. We identified CD105 (endoglin, or ENG, a TGF-β receptor family member) as a mediator of HGSC cell ovarian recruitment. We found that CD105 was expressed on both serous tubal intraepithelial carcinoma (STIC) cells (STICs-HGSC precursors in the fallopian tube epithelium) and HGSC cells. Using data from The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE), we showed that high CD105 expression by HGSC cells correlated with a metastatic signature. Furthermore, intravenous injection of CD105(+) HGSC tumor cells, but not CD105(−), resulted in ovarian-specific metastasis and abdominal dissemination of disease. CD105 knockdown or blockade with a clinically relevant CD105-neutralizing mAb (TRC105), inhibited HGSC metastasis, reduced ascites, and impeded growth of abdominal tumor nodules, thereby improving overall survival in animal models of ovarian cancer. CD105 knockdown was associated with a reduction in TGF-β signaling. Together, our data support CD105 as a critical mediator of ovarian cancer spread to the ovary and implicate it as a potential therapeutic target.

Identification of Prognostic and Metastatic Alternative Splicing Signatures in Kidney Renal Clear Cell Carcinoma.

Background: Kidney renal clear cell carcinoma (KIRC) is the malignancy originated from the renal epithelium, with a high rate of distant metastasis. Aberrant alternative splicing (AS) of pre-mRNA are widely reported to be involved in the tumorigenesis and metastasis of multiple cancers. The aim of this study is to explore the mechanism of alternative splicing events (ASEs) underlying tumorigenesis and metastasis of KIRC.Methods: RNA-seq of 537 KIRC samples downloaded from the TCGA database and ASEs data from the TCGASpliceSeq database were used to identify ASEs in patients with KIRC. The univariate and Lasso regression analysis were used to screen the most significant overall survival-related ASEs (OS-SEs). Based on those, the OS-SEs model was proposed. The interaction network of OS-SEs and splicing factors (SFs) with absolute value of correlation coefficient value >0.750 was constructed by Pearson correlation analysis. The OS-SEs significantly related to distant metastasis and clinical stage were identified by non-parametric test, and those were also integrated into co-expression analysis with prognosis-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways identified by Gene Set Variation Analysis (GSVA). ASEs with significance were selected for multiple online database validation.Results: A total of prognostic 6,081 overall survival-related ASEs (OS-SEs) were identified by univariate Cox regression analysis and a prediction model was constructed based on 5 OS-SEs screened by Lasso regression with the Area Under Curve of 0.788. Its risk score was also illustrated to be an independent predictor, which the good reliability of the model. Among 390 identified candidate SFs, DExD-Box Helicase 39B (DDX39B) was significantly correlated with OS and metastasis. After external database validation, Retained Intron of Ras Homolog Family Member T2 (RHOT2) and T-Cell Immune Regulator 1 (TCIRG1) were identified. In the co-expression analysis, overlapped co-expression signal pathways for RHOT2 and TCIRG1 were sphingolipid metabolism and N-glycan biosynthesis.Conclusions: Based on the results of comprehensive bioinformatic analysis, we proposed that aberrant DDX39B regulated RHOT2-32938-RI and TCIRG1-17288-RI might be associated with the tumorigenesis, metastasis, and poor prognosis of KIRC via sphingolipid metabolism or N-glycan biosynthesis pathway.

BRD4 Promotes Gastric Cancer Progression and Metastasis through Acetylation-Dependent Stabilization of Snail.

Cancer metastasis, a leading cause of death in patients, is associated with aberrant expression of epigenetic modifiers, yet it remains poorly defined how epigenetic readers drive metastatic growth and whether epigenetic readers are targetable to control metastasis. Here, we report that bromodomain-containing protein 4 (BRD4), a histone acetylation reader and emerging anticancer therapeutic target, promotes progression and metastasis of gastric cancer. The abundance of BRD4 in human gastric cancer tissues correlated with shortened metastasis-free gastric cancer patient survival. Consistently, BRD4 maintained invasiveness of cancer cells in vitro and their dissemination at distal organs in vivo. Surprisingly, BRD4 function in this context was independent of its putative transcriptional targets such as MYC or BCL2, but rather through stabilization of Snail at posttranslational levels. In an acetylation-dependent manner, BRD4 recognized acetylated lysine 146 (K146) and K187 on Snail to prevent Snail recognition by its E3 ubiquitin ligases FBXL14 and β-Trcp1, thereby inhibiting Snail polyubiquitination and proteasomal degradation. Accordingly, genome-wide transcriptome analyses identified that BRD4 and Snail regulate a partially shared metastatic gene signature in gastric cancer cells. These findings reveal a noncanonical posttranscriptional regulatory function of BRD4 in maintaining cancer growth and dissemination, with immediate translational implications for treating gastric metastatic malignancies with clinically available bromodomain inhibitors. SIGNIFICANCE: These findings reveal a novel posttranscriptional regulatory function of the epigenetic reader BRD4 in cancer metastasis via stabilizing Snail, with immediate translational implication for treating metastatic malignancies with clinically available bromodomain inhibitors. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/79/19/4869/F1.large.jpg.

Identification of SPP1 as an Extracellular Matrix Signature for Metastatic Castration-Resistant Prostate Cancer.

Resistance to androgen deprivation therapy (ADT) is the main challenge for advanced fatal prostate cancer (PCa), which can gradually develop into metastatic castration-resistant prostate cancer (mCRPC). However, the pathologic mechanisms of mCRPC are still far from clear. Given the high incidence and mortality related to mCRPC, understanding the causes and pathogenesis of this condition as well as identifying potential biomarkers are of great importance. In the research reported here, we integrated several gene expression profiles from hormone sensitive prostate cancer (HSPC) and mCRPC datasets to identify differentially expressed genes (DEGs), key biological pathways, and cellular components. We found that extracellular matrix (ECM) genes were significantly enriched, and further filtered them using Pearson correlation analysis and stepwise regression to find ECM signatures to differentiate between the HSPC and mCRPC phenotypes. Six ECM signatures were input into K-nearest neighbor, logistic regression, naive Bayes, and random forest classifiers models. Random forest algorithm with the six-gene prognostic signatures showed best performance, which had high sensitivity and specificity for HSPC and mCRPC classification and further the six ECM signatures were validated in organoid models. Among the six ECM genes, SPP1 was identified as the key hub signature for PCa metastasis and drug resistance development; we found that both protein and mRNA expression levels of SPP1 were remarkably up-regulated in mCRPC compared with HSPC in organoid models and could regulate the androgen receptor signaling pathway. Therefore, SPP1 is a potential novel biomarker and therapeutic target for mCRPC. Further understanding of the role of SPP1 in mCRPC development may help to explore effectively therapeutic approaches for the prevention and intervention of drug resistance and metastasis.

SRSF1 and RBM4 differentially modulate the oncogenic effect of HIF-1α in lung cancer cells through alternative splicing mechanism

Alternative splicing (AS) constitutes a pivotal mechanism for expanding the transcriptome and proteome diversity in higher eukaryotes. In contrast, misregulated AS events are relevant to carcinogenic signatures, including migration, angiogenesis, immortality, and drug resistance of cancer cells. Using a transcriptome analysis, discriminative splicing profiles of hypoxia-inducible factor (HIF)-1α transcripts were identified in tumorous tissues compared to adjacent normal tissues of lung cancer (LC) patients. In cancerous tissues or LC-derived cells, relatively high levels of HIF-1α-ex14 transcripts encoding the HIF-1αS isoform were noted compared to adjacent normal tissues and non-cancerous cells. The HIF-1αS isoform exhibited a more-prominent effect than that of the HIF-1αL isoform translated from HIF-1α+ex14 transcripts on enhancing promoter activities of the vascular endothelial growth factor receptor 2 (VEGFR2), serine/arginine splicing factor 1 (SRSF1), and c13orf25 genes. An increase in the SRSF1 protein facilitated the generation of HIF-1α-ex14 transcripts, whereas overexpression of RNA-binding motif protein 4 (RBM4) enhanced the expression of HIF-1α+ex14 transcripts in the A549 cells. Results of splicing reporter assays demonstrated the differential impacts of RBM4 and SRSF1 on the utilization of HIF-1α exon 14 in a CU element-dependent manner. In addition to transcriptional regulation, overexpression of the HIF-1αS and HIF-1αL isoforms differentially enhanced the metastatic signatures of A549 cells. Taken together, SRSF1 and RBM4 constitute an antagonistic mechanism on regulating the splicing profiles of HIF-1α gene, which is relevant to the oncogenic signatures of LC cells.

A cross-cancer metastasis signature in the microRNA–mRNA axis of paired tissue samples

In the progression of cancer, cells acquire genetic mutations that cause uncontrolled growth. Over time, the primary tumour may undergo additional mutations that allow for the cancerous cells to spread throughout the body as metastases. Since metastatic development typically results in markedly worse patient outcomes, research into the identity and function of metastasis-associated biomarkers could eventually translate into clinical diagnostics or novel therapeutics. Although the general processes underpinning metastatic progression are understood, no clear cross-cancer biomarker profile has emerged. However, the literature suggests that some microRNAs (miRNAs) may play an important role in the metastatic progression of several cancer types. Using a subset of The Cancer Genome Atlas (TCGA) data, we performed an integrated analysis of mRNA and miRNA expression with paired metastatic and primary tumour samples to interrogate how the miRNA-mRNA regulatory axis influences metastatic progression. From this, we successfully built mRNA- and miRNA-specific classifiers that can discriminate pairs of metastatic and primary samples across 11 cancer types. In addition, we identified a number of miRNAs whose metastasis-associated dysregulation could predict mRNA metastasis-associated dysregulation. Among the most predictive miRNAs, we found several previously implicated in cancer progression, including miR-301b, miR-1296, and miR-423. Taken together, our results suggest that metastatic samples have a common cross-cancer signature when compared with their primary tumour pair, and that these miRNA biomarkers can be used to predict metastatic status as well as mRNA expression.

BSCI-26. COMPARATIVE METHYLATION PROFILING OF EGFR MUTANT LUNG ADENOCARCINOMA AND PAIRED BRAIN METASTASIS

BACKGROUND: Adenocarcinomas (ADC) are the most common lung tumours and EGFR-mutant lesions have a higher risk of brain metastasis development, which confers poorer survival. Genetic and epigenetic signatures of brain metastasis have not been comprehensively identified. The aim of this study is to compare the methylome of EGFR-mutant primary lung tumor and matched brain metastasis to identify mechanisms of brain metastasis and new treatment targets. METHOD: Seven matched primary to brain metastasis tumours were profiled using the Illumina Infinium MethylationEPIC BeadChip array. Hierarchical clustering and principal component analyses (PCA) were performed using most variable CpG sites. Supervised analyses were performed between lung and brain tumour samples. Copy number variation (CNV) plots identified alterations between pairs along with Leukocytes unmethylation for purity (LUMP) score and prediction lymphocyte proportion analyses to measure immune infiltration. RESULTS: Unsupervised clustering showed that the fourteen tumours clustered according to patient with similar methylation profiles between each of seven matched pairs. On the supervised analysis using 83K significant CpG sites, the fourteen samples clustered into two groups based on tumour site being lung or brain. Of these 83K CpG sites, 2.4K were either hypermethylated or hypomethylated in all lung samples. One quarter of these 2.4K CpG sites were located in promoter regions. CNV analyses showed losses of FGFR1, C19MC, CDKN2A, PTCH1, and MYCN genes with higher deep deletions in brain versus lung primary samples. Immune infiltration measures were similar between lung and brain metastasis pairs (LUMP-score=0.64) consistent with high immune cell infiltration. CONCLUSION: In this EGFR-mutant lung adenocarcinomas and matched brain metastases, differentially methylated CpG sites and CNV alterations are identified that distinguish lung from brain samples. Further work with additional matched samples may further elucidate signatures specific to brain metastasis and aid in our understanding of the mechanisms of brain metastasis.

The identification of a TNBC liver metastasis gene signature by sequential CTC-xenograft modeling.

Triple‐negative breast cancer (TNBC) liver metastasis is associated with poor prognosis and low patient survival. It occurs when tumor cells disseminate from primary tumors, circulate in blood/lymph [circulating tumor cells (CTCs)], and acquire distinct characteristics during disease progression toward the metastatic phenotype. The purpose of this study was to decipher the genomic/transcriptomic properties of TNBC liver metastasis and its recurrence for potential therapeutic targeting. We employed a negative depletion strategy to isolate and interrogate CTCs from the blood of patients with TNBC, and to establish sequential generations of CTC‐derived xenografts (CDXs) through injection of patient CTCs in immunodeficient mice. The isolation and validation of CDX‐derived cell populations [analyses of CTCs were paired with bone marrow‐resident cells (BMRTCs) and liver tissue cells obtained from the same animal] were performed by multiparametric flow cytometry, immune phenotyping, and genomic sequencing of putative CTCs. Comprehensive characterization of gene expression arrays from sequentially generated CDX‐derived cell populations, online gene expression arrays, and TCGA databases were employed to discover a CTC‐driven, liver metastasis‐associated TNBC signature. We discovered a distinct transcriptomic signature of TNBC patient‐isolated CTCs from primary TNBCs, which was consistent throughout sequential CDX modeling. We established a novel TNBC liver metastasis‐specific CDX model that selectively recapitulates CTC biology for four sequential generations of mice. The evaluation of online databases and CDX‐derived populations revealed 597 genes specific to the TNBC liver metastasis signatures. Further investigation of the TNBC liver metastasis signature predicted 16 hub genes, 6 biomarkers with clinically available drugs, and 22 survival genes. The sequential interrogation of CDX‐CTCs is an innovative liquid biopsy‐based approach for the discovery of organ metastasis‐specific signatures of CTCs. This represents the first step for mechanistic and analytical validation in their application as prognostic indicators and therapeutic targets. Targeting CTC drug candidate biomarkers along with combination therapy can improve the clinical outcome of TNBC patients in general and recurrence of liver metastasis in particular.

Abstract 1795: MicroRNA sequence analysis reveals signatures of oral cancer lymph node metastasis

Abstract Regional lymph node metastasis (LN+) at the time of diagnosis or during post-treatment follow-up has devastating impact on the decimal survival of oral cancer (OC) patients. Early intervention on at-risk patient may improve survival. The purpose of the study was to identify microRNA (miRNA) signatures that contribute to LN+ using miRNA sequencing in OC surgical samples. The study comprised a Discovery Cohort (n=91) and a Validation Cohort (n=67) of fresh-frozen primary tumors from 158 patients who were surgically treated between 2005 and 2016 with known outcome of LN (LN+, n=76; LN0, n=82). Total RNA was harvested from &amp;gt;70% tumoral areas. MiRNA-seq libraries were constructed from 2µg total RNA per sample followed by adaptor ligation, reverse transcription, PCR, and sequencing on HiSeq 2000 platform. All analyses were performed using R package (v3.4.4) with input matrix of the miRNAs that expressed at a level of at least 10 reads per million (RPM) in at least 10% of samples. A Least Absolute Shrinkage and Selection Operator (LASSO) penalized regression approach was used to identify miRNAs that would best predict nodal-disease free survival (NFS). Random forest classification analysis was used to rank miRNAs for classifying samples as LN0 and LN+. Among the 158 samples, the LN+ group consisted more poorly differentiated tumors and greater depth of invasion (p=0.0001 and 0.002, respectively). To identify miRNAs that contribute to LN+, we used a penalized regression to generate a signature of NFS. The Discovery Cohort was randomly partitioned into training set (n=72; LN+, n=39, LN0, n=33) to generate a predictive model on NFS. This was then tested in the remaining 19 cases (LN+, n=12, LN0, n=7). The model composed of 2 miRNAs (miR-107 and miR-21-5p) which were significantly overexpressed in LN+. When this was tested in the Validation Cohort (n=67; LN+, 25; LN0, 42), the model was significantly associated with NFS (HR=3.4; 95% CI, 1.5-7.6; 5-year NFS, 24.5%, p=0.001). Additionally, we ranked miRNAs for classifying all samples into LN+ and LN0 by using random forest classification analysis and the two miRNAs from the penalized regression analysis remained to be the top two. The classified LN+ group had significant inferior NFS compared to classified LN0 group (HR=3.2; 95% CI, 2.0-5.1; 5-year NFS, 27.8% vs. 66.7%, p&amp;lt;0.0001). We further investigated diagnostic performance of the two miRNAs using receiver operating curve on all samples which had accuracy of 0.88, sensitivity of 0.82, specificity of 0.80, positive predictive value of 0.82, and negative predictive value of 0.80. In conclusion, our data demonstrated noticeable dysregulated miRNAs that may serve as predictive biomarkers for LN+. Note: This abstract was not presented at the meeting. Citation Format: Kelly Yp Liu, Denise Brooks, Reanne Bowlby, Steve Jones, Catherine F. Poh. MicroRNA sequence analysis reveals signatures of oral cancer lymph node metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1795.

Abstract 3689: Tumor-specific gain-of-function tGLI1 transcription factor is a novel mediator of breast cancer stem cells and a novel transcriptional activator of cancer stemness genes

Abstract Breast cancer is the second leading cause of cancer-related mortality in women; metastasis to distant organs results in 90% of deaths for these patients. Cancer stem cells (CSCs) are considered the drivers of metastasis. Despite our current knowledge of breast CSCs, there still remains a significant challenge in managing patients with the metastatic breast cancer, underscoring the need for identifying novel regulators of breast CSCs. The hedgehog pathway is an important mediator of stem cells; however, the effect of truncated glioma-associated oncogene homolog 1 (tGLI1), a nuclear effector of the hedgehog pathway and a gain-of-function GLI1 transcription factor, on breast CSCs has never been investigated. Herein, we investigated whether tGLI1 is implicated in breast CSCs by evaluating tGLI1 expression levels in cells grown as monolayer versus mammospheres, as a representation of the stem cell population, and found tGLI1 to be induced in mammosphere culture. Overexpression of tGLI1 promoted mammosphere-forming ability of breast cancer cells, as well as, increased the breast CSC population defined by CD44high/CD24low expression. Further, tGLI1 overexpression transformed normal mammary epithelial cells resulting in increased mammosphere formation and enhanced anchorage-independent growth of immortalized human mammary epithelial HMLE cells. Functional and biochemical assays further showed that tGLI1 promotes breast CSC self-renewal by transcriptional activation of stemness genes including a novel tGLI1 target gene, OCT4, a recently reported tGLI1 target gene (CD44), and known GLI1 target genes (Nanog and SOX2). Bioinformatic analysis of breast cancer patient datasets revealed that activated tGLI1 is associated with shortened time to develop metastasis to the lung, bone, and brain. Furthermore, tGLI1 activation is enriched in HER2-enriched and triple-negative breast cancers, the subtypes with the highest propensity to metastasize, compared to luminal subtypes. Gene Set Enrichment Analysis showed that high tGLI1 activation is enriched in breast cancer with high gene signatures of breast CSCs, radioresistance, and metastasis. We further validated these results by immunohistochemical staining of paired primary breast tumors with lymph node metastases and found that that expression of tGLI1, but not GLI1, was increased in lymph node metastases and that tGLI1 was expressed at higher levels (84-91%) of lymph node-positive metastatic HER2-enriched and triple-negative breast tumors. Lastly, tGLI1 knockdown resulted in decreased mammosphere formation of breast cancer cells and decreased expression of stemness genes, OCT4, CD44, and Nanog. Taken together, these findings establish a novel role that tGLI1 plays in mediating breast CSCs and implicate tGLI1 in facilitating breast cancer metastasis. Citation Format: Sherona R. Sirkisoon, Richard L. Carpenter, Tadas Rimkus, Daniel Doheny, Dongqin Zhu, Noah R. Aguayo, Marlyn Anguelov, Austin Arrigo, Fei Xing, Michael Chan, Jimmy Ruiz, Linda J. Metheny-Barlow, Roy Strowd, Jiayuh Lin, Boris C. Pasche, Waldemar Debinski, Kounosuke Watabe, Hui-Wen Lo. Tumor-specific gain-of-function tGLI1 transcription factor is a novel mediator of breast cancer stem cells and a novel transcriptional activator of cancer stemness genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3689.

Abstract 4541: Malignant and non-malignant cells from primary tumor and lymph node metastasis ecosystems show different behavior for patient-associated protein signatures in head and neck cancer

Abstract Although lymph node metastasis is the main prognostic factor in patients with head and neck squamous cell carcinoma (HNSCC), the molecular signals involved in this process are poorly characterized and no molecular markers are currently used in clinical practice. Recently, cancer is being viewed as an ecosystem, in which tumor cells cooperate with each other and host cells in their microenvironment. Herein, we mapped the proteome of primary tumor and matched lymph node ecosystems, isolating malignant and non-malignant cells, to better understand the mechanisms underlying lymph node metastasis. For that, we used formalin-fixed paraffin-embedded (FFPE) primary tumors and paired lymph nodes from 27 HNSCC patients positive (N+, n=13) and negative (N0, n=14) for lymph node metastasis using laser microdissection combined with mass spectrometry-based proteomics. An average of 2,266 ± 216 proteins was identified in primary tumor and lymph node ecosystems. A hundred and five differentially abundant proteins from malignant cells in the primary site (N+ vs N0) were mainly involved in RNA stability and metabolism, while inflammation and splicing processes, respectively, were overrepresented in N+ vs N0 non-malignant cells signatures from primary tumor (N=33) and lymph node (N=13) sites (Student's t-test; P-value≤0.05), indicating particular lymph node metastasis signatures for each cell population. Interestingly, the protein pattern of malignant cells from the primary site and matched lymph nodes showed an individual patient-specific metastasis profile through hierarchical clustering analysis; however, the profile of non-malignant cells does not represent patient-specific subpopulations and grouped according to the site of isolation (primary tumor and lymph node microenvironment). Our data reveal potential protein signatures associated with prognosis in HNSCC, as well as a non-specificity of protein patterns from host non-malignant cells that can be related with the immunosurveillance failure. Financial support: FAPESP (Process number 2015/19191-6). Note: This abstract was not presented at the meeting. Citation Format: Ariane F. Busso-Lopes, César Rivera, Barbara P. Mello, Luisa L. Villa, Wilfredo González-Arriagada, Adriana F. Paes Leme. Malignant and non-malignant cells from primary tumor and lymph node metastasis ecosystems show different behavior for patient-associated protein signatures in head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4541.