Abstract PO017: HBV alters YAP regulation in liver cancer by remodeling PP2A complexes

Viral hepatitis promotes hepatocellular carcinoma (HCC) initiation by inducing inflammation, cellular stress and cell death. However, the cell-intrinsic effects of viral infection in advanced HCC remain unclear. We used affinity purification mass spectrometry to develop a complete map of 145 interactions among Hepatitis B Virus (HBV) and host proteins in the HUH7 HCC tumor cell line, identifying known and novel HBV/host protein-protein interactions. We integrated this map with HCC genomes, identifying 61 proteins with preferential mutation in non-HBV HCC, suggesting that their interaction with HBV plays a role in cancer. Focusing on proteins that directly interact with the HBV oncoprotein X (HBx), we found that HBx rewires the effect of the PP2A phosphatase on HCC signaling. HBx binding excluded striatin-family regulatory subunits from the PP2A complex, causing Hippo kinase activation. This effect creates a requirement for integrin signaling to mTOR complex 2 to maintain expression of the YAP oncoprotein, critical for HCC growth. Thus, HBV rewires HCC signaling and may promote targetable dependencies.

Citation Format: John Gordan, Adriana Pitea, Rigney E Turnham, Manon Eckhardt, Gwendolyn M Jang, Huat Lim, Alex L Choi, Sourav Bandyopadhyay, Danielle Swaney, Kevan Shokat, Trey Ideker, Nevan Krogan. HBV alters YAP regulation in liver cancer by remodeling PP2A complexes [abstract]. In: Proceedings of the AACR Special Conference: Advances in the Pathogenesis and Molecular Therapies of Liver Cancer; 2022 May 5-8; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(17_Suppl):Abstract nr PO017.

A multi-scale map of cell structure fusing protein images and interactions

The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.

Genome-wide 5hmC profiles to enable cancer detection and tissue of origin classification in breast, colorectal, lung, ovarian, and pancreatic cancers

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Background: Epigenomics assays have recently become popular tools for identification of molecular biomarkers, both in tissue and in plasma. In particular 5-hydroxymethyl-cytosine (5hmC) method, has been shown to enable the epigenomic regulation of gene expression and subsequent gene activity, with different patterns, across several tumor and normal tissues types. In this study we show that 5hmC profiles enable discrete classification of tumor and normal tissue for breast, colorectal, lung ovary and pancreas. Such classification was also recapitulated in cfDNA from patient with breast, colorectal, lung, ovarian and pancreatic cancers. Methods: DNA was isolated from 176 fresh frozen tissues from breast, colorectal, lung, ovary and pancreas (44 per tumor per tissue type and up to 11 tumor tissues for each stage (I-IV)) and up to 10 normal tissues per tissue type. cfDNA was isolated from plasma from 783 non-cancer individuals and 569 cancer patients. Plasma-isolated cfDNA and tumor genomic DNA, were enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to a reference genome to construct features sets of 5hmC patterns. Results: 5hmC multinomial logistic regression analysis was employed across tumor and normal tissues and identified a set of specific and discrete tumor and normal tissue gene-based features. This indicates that we can classify samples regardless of source, with a high degree of accuracy, based on tissue of origin and also distinguish between normal and tumor status.Next, we employed a stacked ensemble machine learning algorithm combining multiple logistic regression models across diverse feature sets to the cfDNA dataset composed of 783 non cancers and 569 cancers comprising 67 breast, 118 colorectal, 210 Lung, 71 ovarian and 100 pancreatic cancers. We identified a genomic signature that enable the classification of non-cancer versus cancers with an outer fold cross validation sensitivity of 49% (CI 45%-53%) at 99% specificity. Further, individual cancer outer fold cross validation sensitivity at 99% specificity, was measured as follows: breast 30% (CI 119% -42%); colorectal 41% (CI 32%-50%); lung 49% (CI 42%-56%); ovarian 72% (CI 60-82%); pancreatic 56% (CI 46%-66%). Conclusions: This study demonstrates that 5hmC profiles can distinguish cancer and normal tissues based on their origin. Further, 5hmC changes in cfDNA enables detection of the several cancer types: breast, colorectal, lung, ovarian and pancreatic cancers. Our technology provides a non-invasive tool for cancer detection with low risk sample collection enabling improved compliance than current screening methods. Among other utilities, we believe our technology could be applied to asymptomatic high-risk individuals thus enabling enrichment for those subjects that most need a diagnostic imaging follow up.

Abstract 4891: Hepatitis B virus remodels host protein interaction networks to generate distinct cellular dependencies

Hepatocellular carcinoma (HCC) is the second leading cause of cancer death worldwide. Advanced HCC has proven particularly difficult to treat because of a scarcity of clear genetic drivers of cancer progression; thus, there are currently no predictive markers that guide HCC therapy. HCC arises in the context of co-morbid hepatitis due to hepatitis B virus (HBV), hepatitis C (HCV) or fatty liver disease. We hypothesize that protein-protein interactions (PPIs) between viral proteins and HCC genes may contribute to tumor initiation and maintenance. In order to characterize these PPIs, we performed affinity purification - mass spectrometry (APMS), defining 145 HBV/host PPIs including known and novel interacting partners. We next used a network propagation algorithm to identify host genes and protein complexes that were preferentially mutated in the absence of HBV infection. HBV is a small DNA virus, with 4 genes of which only one has enzymatic activity, raising a question as to how HBV interaction modifies host behavior. Using AP-MS of host proteins, we found that the HBV X protein (HBx) remodels multiple host protein complexes through direct interaction. These physical effects on complex components result in distinct biochemical behavior from the CRL4 E3 ubiquitin ligase complex as well as the phosphatase PP2A, as determined through global phosphoproteomics and ubiquitin analysis. We show that this remodeling driven by HBx substantially changes cellular protein turnover and downstream signaling dynamics. We followed this up with assessments of cellular viability and proliferation in response to pharmacological inhibition or CRISPRi-based knockdown of HBx effectors. Our data support a model where HBV proteins alter the components and behavior of key regulatory protein complexes in the cell, altering tumor behavior and raising the possibility of precision therapeutics for HCC.

Citation Format: John D. Gordan, Adriana Pitea, Manon Eckhardt, Gwendolyn Jang, Rigney E. Turnham, Alex L M. Choi, John Von Dollen, Huat C. Lim, Elizabeth F. Thayer, R. Katie Kelley, Danielle L. Swaney, Wei Zhang, Fabian J. Theis, Trey Ideker, Nevan J. Krogan. Hepatitis B virus remodels host protein interaction networks to generate distinct cellular dependencies [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4891.

A prognostic mRNA expression signature of four 16q24.3 genes in radio(chemo)therapy-treated head and neck squamous cell carcinoma (HNSCC)

Previously, we have shown that copy number gain of the chromosomal band 16q24.3 is associated with impaired clinical outcome of radiotherapy‐treated head and neck squamous cell carcinoma (HNSCC) patients. We set out to identify a prognostic mRNA signature from genes located on 16q24.3 in radio(chemo)therapy‐treated HNSCC patients of the TCGA (The Cancer Genome Atlas, n = 99) cohort. We applied stepwise forward selection using expression data of 41 16q24.3 genes. The resulting optimal Cox‐proportional hazards regression model included the genes APRT, CENPBD1, CHMP1A, and GALNS. Afterward, the prognostic value of the classifier was confirmed in an independent cohort of HNSCC patients treated by adjuvant radio(chemo)therapy (LMU‐KKG cohort). The signature significantly differentiated high‐ and low‐risk patients with regard to overall survival (HR = 2.01, 95% CI 1.10–3.70; P = 0.02125), recurrence‐free survival (HR = 1.84, 95% CI 1.01–3.34; P = 0.04206), and locoregional recurrence‐free survival (HR = 1.87, 95% CI 1.03–3.40; P = 0.03641). The functional impact of the four signature genes was investigated after reconstruction of a gene association network from transcriptome data of the TCGA HNSCC cohort using a partial correlation approach. Subsequent pathway enrichment analysis of the network neighborhood (first and second) of the signature genes suggests involvement of HNSCC‐associated signaling pathways such as apoptosis, cell cycle, cell adhesion, EGFR, JAK‐STAT, and mTOR. Furthermore, a detailed analysis of the first neighborhood revealed a cluster of co‐expressed genes located on chromosome 16q, substantiating the impact of 16q24.3 alterations in poor clinical outcome of HNSCC. The reported gene expression signature represents a prognostic marker in HNSCC patients following postoperative radio(chemo)therapy.

Copy number aberrations from Affymetrix SNP 6.0 genotyping data-how accurate are commonly used prediction approaches?

Copy number aberrations (CNAs) are known to strongly affect oncogenes and tumour suppressor genes. Given the critical role CNAs play in cancer research, it is essential to accurately identify CNAs from tumour genomes. One particular challenge in finding CNAs is the effect of confounding variables. To address this issue, we assessed how commonly used CNA identification algorithms perform on SNP 6.0 genotyping data in the presence of confounding variables. We simulated realistic synthetic data with varying levels of three confounding variables-the tumour purity, the length of a copy number region and the CNA burden (the percentage of CNAs present in a profiled genome)-and evaluated the performance of OncoSNP, ASCAT, GenoCNA, GISTIC and CGHcall. Furthermore, we implemented and assessed CGHcall*, an adjusted version of CGHcall accounting for high CNA burden. Our analysis on synthetic data indicates that tumour purity and the CNA burden strongly influence the performance of all the algorithms. No algorithm can correctly find lost and gained genomic regions across all tumour purities. The length of CNA regions influenced the performance of ASCAT, CGHcall and GISTIC. OncoSNP, GenoCNA and CGHcall* showed little sensitivity. Overall, CGHcall* and OncoSNP showed reasonable performance, particularly in samples with high tumour purity. Our analysis on the HapMap data revealed a good overlap between CGHcall, CGHcall* and GenoCNA results and experimentally validated data. Our exploratory analysis on the TCGA HNSCC data revealed plausible results of CGHcall, CGHcall* and GISTIC in consensus HNSCC CNA regions. Code is available at https://github.com/adspit/PASCAL.

Epigenetically Regulated Chromosome 14q32 miRNA Cluster Induces Metastasis and Predicts Poor Prognosis in Lung Adenocarcinoma Patients

Most lung cancer deaths are related to metastases, which indicates the necessity of detecting and inhibiting tumor cell dissemination. Here, we aimed to identify miRNAs involved in metastasis of lung adenocarcinoma as prognostic biomarkers and therapeutic targets. To that end, lymph node metastasis-associated miRNAs were identified in The Cancer Genome Atlas lung adenocarcinoma patient cohort (sequencing data; n = 449) and subsequently validated by qRT-PCR in an independent clinical cohort (n = 108). Overexpression of miRNAs located on chromosome 14q32 was associated with metastasis in lung adenocarcinoma patients. Importantly, Kaplan-Meier analysis and log-rank test revealed that higher expression levels of individual 14q32 miRNAs (mir-539, mir-323b, and mir-487a) associated with worse disease-free survival of never-smoker patients. Epigenetic analysis including DNA methylation microarray data and bisulfite sequencing validation demonstrated that the induction of 14q32 cluster correlated with genomic hypomethylation of the 14q32 locus. CRISPR activation technology, applied for the first time to functionally study the increase of clustered miRNA levels in a coordinated manner, showed that simultaneous overexpression of 14q32 miRNAs promoted tumor cell migratory and invasive properties. Analysis of individual miRNAs by mimic transfection further illustrated that miR-323b-3p, miR-487a-3p, and miR-539-5p significantly contributed to the invasive phenotype through the indirect regulation of different target genes. In conclusion, overexpression of 14q32 miRNAs, associated with the respective genomic hypomethylation, promotes metastasis and correlates with poor patient prognosis in lung adenocarcinoma.Implications: This study points to chromosome 14q32 miRNAs as promising targets to inhibit tumor cell dissemination and to predict patient prognosis in lung adenocarcinoma. Mol Cancer Res; 16(3); 390-402. ©2018 AACR.

Expression of miRNA-26b-5p and its target TRPS1 is associated with radiation exposure in post-Chernobyl breast cancer

Ionizing radiation is a well-recognized risk factor for the development of breast cancer. However, it is unknown whether radiation-specific molecular oncogenic mechanisms exist. We investigated post-Chernobyl breast cancers from radiation-exposed female clean-up workers and nonexposed controls for molecular changes. Radiation-associated alterations identified in the discovery cohort (n = 38) were subsequently validated in a second cohort (n = 39). Increased expression of hsa-miR-26b-5p was associated with radiation exposure in both of the cohorts. Moreover, downregulation of the TRPS1 protein, which is a transcriptional target of hsa-miR-26b-5p, was associated with radiation exposure. As TRPS1 overexpression is common in sporadic breast cancer, its observed downregulation in radiation-associated breast cancer warrants clarification of the specific functional role of TRPS1 in the radiation context. For this purpose, the impact of TRPS1 on the transcriptome was characterized in two radiation-transformed breast cell culture models after siRNA-knockdown. Deregulated genes upon TRPS1 knockdown were associated with DNA-repair, cell cycle, mitosis, cell migration, angiogenesis and EMT pathways. Furthermore, we identified the interaction partners of TRPS1 from the transcriptomic correlation networks derived from gene expression data on radiation-transformed breast cell culture models and sporadic breast cancer tissues provided by the TCGA database. The genes correlating with TRPS1 in the radiation-transformed breast cell lines were primarily linked to DNA damage response and chromosome segregation, while the transcriptional interaction partners in the sporadic breast cancers were mostly associated with apoptosis. Thus, upregulation of hsa-miR-26b-5p and downregulation of TRPS1 in radiation-associated breast cancer tissue samples suggests these molecules representing radiation markers in breast cancer.

Abstract 1945: Identification of a miRNA/mRNA network driving non-small cell lung cancer (NSCLC) dissemination

Background:

Non-small cell lung cancer (NSCLC) is one of the most aggressive tumor entities and first data indicate that microRNAs (miRNAs) are central regulators of NSCLC dissemination. Since each miRNA is able to modulate the expression of several transcripts, they are promising targets for the development of drugs that cause efficient antitumor effects and low resistance. However, the relevant network of miRNA/mRNA driving NSCLC metastasis has not been identified yet.

Methods:

The differential expression of miRNAs was compared between NSCLC samples from patients with and without lymph node metastasis (N1, N2 and N3 vs. N0) in a cohort of The Cancer Genomic Atlas (TCGA) database (n = 449). The dysregulation of the miRNAs in tumors versus normal lung samples (n = 39) was also analyzed. For validation, fresh-frozen samples from an independent patient cohort (n = 108) were analyzed by qRT-PCR. The role of selected miRNAs in tumor dissemination was assessed by migration and invasion experiments after transfection of respective antagomirs and agomirs in NSCLC cells (time-lapse microscopy). The novel algorithm “miRlastic” was used to identify potential miRNA targets through the integration of miRNA-mRNA expression data by negative multiple linear regression analysis. Moreover, differential methylation of the miRNA genomic locations was studied as a possible mechanism of miRNA dysregulation by analyzing Illumina Infinium 450 k DNA methylation TCGA data (n = 29).

Results:

By using a stringent selection process, we identified 135 miRNAs differentially induced or reduced in NSCLCs with lymph node metastasis (p≤0.05). Interestingly, 22/135 (16.3%) of the selected miRNAs were located in the chromosomal cluster 14q32.31. Elevated expression of miR-323b, miR-487a and miR-539, which are located in 14q32.31, significantly correlated with poor patient survival. Time-resolved and quantitative analysis of lateral migration illustrated that these miRNAs increased tumor migration without affecting cell viability. Moreover, miRlastic identified several metastasis-related genes as potential downstream targets of these miRNAs. The connection between miRNAs encoded in 14q32.31 and candidate targets was confirmed in NSCLC cell lines (e.g. Pumilio RNA-Binding Family Member-2; PUM2). Lastly, hypomethylation of the 14q32.31 cluster in tumor tissues might explain increased expression of these miRNAs.

Conclusions: Our results demonstrate that miRNAs located in the chromosomal cluster 14q32.31 are driving NSCLC dissemination. Therefore, we hypothesize that the coordinated overexpression of these miRNAs is part of a genetic network supporting cancer progression and that they represent promising cancer biomarkers and therapeutic targets.

Citation Format: Margarita González-Vallinas, Marco Albrecht, Adriana Pitea, Manuel Rodríguez-Paredes, Damian Stichel, Steffen Sass, Julian Gutekunst, Jennifer Schmitt, Thomas Muley, Michael Meister, Arne Warth, Peter Schirmacher, Fabian J. Theis, Nikola S. Müller, Franziska Matthäus, Kai Breuhahn. Identification of a miRNA/mRNA network driving non-small cell lung cancer (NSCLC) dissemination. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1945.

Changes in circulating microRNAs after radiochemotherapy in head and neck cancer patients

INTRODUCTION

Circulating microRNAs (miRNAs) are easily accessible and have already proven to be useful as prognostic markers in cancer patients. However, their origin and function in the circulation is still under discussion. In the present study we analyzed changes in the miRNAs in blood plasma of head and neck squamous cell carcinoma (HNSCC) patients in response to radiochemotherapy and compared them to the changes in a cell culture model of primary HNSCC cells undergoing simulated anti-cancer therapy.

MATERIALS AND METHODS

MiRNA-profiles were analyzed by qRT-PCR arrays in paired blood plasma samples of HNSCC patients before therapy and after two days of treatment. Candidate miRNAs were validated by single qRT-PCR assays. An in vitro radiochemotherapy model using primary HNSCC cell cultures was established to test the possible tumor origin of the circulating miRNAs. Microarray analysis was performed on primary HNSCC cell cultures followed by validation of deregulated miRNAs via qRT-PCR.

RESULTS

Unsupervised clustering of the expression profiles using the six most regulated miRNAs (miR-425-5p, miR-21-5p, miR-106b-5p, miR-590-5p, miR-574-3p, miR-885-3p) significantly (p = 0.012) separated plasma samples collected prior to treatment from plasma samples collected after two days of radiochemotherapy. MiRNA profiling of primary HNSCC cell cultures treated in vitro with radiochemotherapy revealed differentially expressed miRNAs that were also observed to be therapy-responsive in blood plasma of the patients (miR-425-5p, miR-21-5p, miR-106b-5p, miR-93-5p) and are therefore likely to stem from the tumor. Of these candidate marker miRNAs we were able to validate by qRT-PCR a deregulation of eight plasma miRNAs as well as miR-425-5p and miR-93-5p in primary HNSCC cultures after radiochemotherapy.

CONCLUSION

Changes in the abundance of circulating miRNAs during radiochemotherapy reflect the therapy response of primary HNSCC cells after an in vitro treatment. Therefore, the responsive miRNAs (miR-425-5p, miR-93-5p) may represent novel biomarkers for therapy monitoring. The prognostic value of this exciting observation requires confirmation using an independent patient cohort that includes clinical follow-up data.