Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Loss of HIF1A From Pancreatic Cancer Cells Increases Expression of PPP1R1B and Degradation of p53 to Promote Invasion and Metastasis.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinomas (PDACs) are hypovascular, resulting in the up-regulation of hypoxia inducible factor 1 alpha (HIF1A), which promotes the survival of cells under low-oxygen conditions. We studied the roles of HIF1A in the development of pancreatic tumors in mice. METHODS: We performed studies with KrasLSL-G12D/+;Trp53LSL-R172H/+;Pdx1-Cre (KPC) mice, KPC mice with labeled pancreatic epithelial cells (EKPC), and EKPC mice with pancreas-specific depletion of HIF1A. Pancreatic and other tissues were collected and analyzed by histology and immunohistochemistry. Cancer cells were cultured from PDACs from mice and analyzed in cell migration and invasion assays and by immunoblots, real-time polymerase chain reaction, and liquid chromatography-mass spectrometry. We performed studies with the human pancreatic cancer cell lines PATU-8988T, BxPC-3, PANC-1, and MiaPACA-2, which have no or low metastatic activity, and PATU-8988S, AsPC-1, SUIT-2 and Capan-1, which have high metastatic activity. Expression of genes was knocked down in primary cancer cells and pancreatic cancer cell lines by using small hairpin RNAs; cells were injected intravenously into immune-competent and NOD/SCID mice, and lung metastases were quantified. We compared levels of messenger RNAs in pancreatic tumors and normal pancreas in The Cancer Genome Atlas. RESULTS: EKPC mice with pancreas-specific deletion of HIF1A developed more advanced pancreatic neoplasias and PDACs with more invasion and metastasis, and had significantly shorter survival times, than EKPC mice. Pancreatic cancer cells from these tumors had higher invasive and metastatic activity in culture than cells from tumors of EKPC mice. HIF1A-knockout pancreatic cancer cells had increased expression of protein phosphatase 1 regulatory inhibitor subunit 1B (PPP1R1B). There was an inverse correlation between levels of HIF1A and PPP1R1B in human PDAC tumors; higher expression of PPP1R1B correlated with shorter survival times of patients. Metastatic human pancreatic cancer cell lines had increased levels of PPP1R1B and lower levels of HIF1A compared with nonmetastatic cancer cell lines; knockdown of PPP1R1B significantly reduced the ability of pancreatic cancer cells to form lung metastases in mice. PPP1R1B promoted degradation of p53 by stabilizing phosphorylation of MDM2 at Ser166. CONCLUSIONS: HIF1A can act a tumor suppressor by preventing the expression of PPP1R1B and subsequent degradation of the p53 protein in pancreatic cancer cells. Loss of HIF1A from pancreatic cancer cells increases their invasive and metastatic activity.

A Genetically Engineered Primary Human Natural Killer Cell Platform for Cancer Immunotherapy.

Enhancing natural killer (NK) cell cytotoxicity by blocking inhibitory signaling could lead to improved NK-based cancer immunotherapy. Thus, we have developed a highly efficient method for editing the genome of human NK cells using CRISPR/Cas9 to knock out inhibitory signaling molecules. Our method efficiently edits up to 90% of primary peripheral blood NK cells. As a proof-of-principle we demonstrate highly efficient knockout of ADAM17 and PDCD1, genes that have a functional impact on NK cells, and demonstrate that these gene-edited NK cells have significantly improved activity, cytokine production, and cancer cell cytotoxicity. Furthermore, we were able to expand cells to clinically relevant numbers, without loss of activity. We also demonstrate that our CRISPR/Cas9 method can be used for efficient knockin of genes by delivering homologous recombination template DNA using recombinant adeno-associated virus serotype 6 (rAAV6). Our platform represents a feasible method for generating engineered primary NK cells as a universal therapeutic for cancer immunotherapy.

Single-Cell RNA Sequencing of Ovarian Cancer: Promises and Challenges.

Ovarian cancer remains the leading cause of death from gynecologic malignancy in the Western world. Tumors are comprised of heterogeneous populations of various cancer, immune, and stromal cells; it is hypothesized that rare cancer stem cells within these subpopulations lead to disease recurrence and treatment resistance. Technological advances now allow for the analysis of tumor genomes and transcriptomes at the single-cell level, which provides the resolution to potentially identify these rare cancer stem cells within the larger tumor.In this chapter, we review the evolution of next-generation RNA sequencing techniques, the methodology of single-cell isolation and sequencing, sequencing data analysis, and the potential applications in ovarian cancer. We also summarize the current published work using single-cell sequencing in ovarian cancer.By utilizing this novel technique to characterize the gene expression of rare subpopulations, new targets and treatment pathways may be identified in ovarian cancer to change treatment paradigms.

Colorectal cancer mutational profiles correlate with defined microbial communities in the tumor microenvironment.

Variation in the gut microbiome has been linked to colorectal cancer (CRC), as well as to host genetic variation. However, we do not know whether, in addition to baseline host genetics, somatic mutational profiles in CRC tumors interact with the surrounding tumor microbiome, and if so, whether these changes can be used to understand microbe-host interactions with potential functional biological relevance. Here, we characterized the association between CRC microbial communities and tumor mutations using microbiome profiling and whole-exome sequencing in 44 pairs of tumors and matched normal tissues. We found statistically significant associations between loss-of-function mutations in tumor genes and shifts in the abundances of specific sets of bacterial taxa, suggestive of potential functional interaction. This correlation allows us to statistically predict interactions between loss-of-function tumor mutations in cancer-related genes and pathways, including MAPK and Wnt signaling, solely based on the composition of the microbiome. In conclusion, our study shows that CRC microbiomes are correlated with tumor mutational profiles, pointing towards possible mechanisms of molecular interaction.

Meta-analytic framework for modeling genetic coexpression dynamics.

Methods for exploring genetic interactions have been developed in an attempt to move beyond single gene analyses. Because biological molecules frequently participate in different processes under various cellular conditions, investigating the changes in gene coexpression patterns under various biological conditions could reveal important regulatory mechanisms. One of the methods for capturing gene coexpression dynamics, named liquid association (LA), quantifies the relationship where the coexpression between two genes is modulated by a third "coordinator" gene. This LA measure offers a natural framework for studying gene coexpression changes and has been applied increasingly to study regulatory networks among genes. With a wealth of publicly available gene expression data, there is a need to develop a meta-analytic framework for LA analysis. In this paper, we incorporated mixed effects when modeling correlation to account for between-studies heterogeneity. For statistical inference about LA, we developed a Markov chain Monte Carlo (MCMC) estimation procedure through a Bayesian hierarchical framework. We evaluated the proposed methods in a set of simulations and illustrated their use in two collections of experimental data sets. The first data set combined 10 pancreatic ductal adenocarcinoma gene expression studies to determine the role of possible coordinator gene USP9X in the Hippo pathway. The second experimental data set consisted of 907 gene expression microarray Escherichia coli experiments from multiple studies publicly available through the Many Microbe Microarray Database website (http://m3d.bu.edu/) and examined genes that coexpress with serA in the presence of coordinator gene Lrp.

Flap endonuclease overexpression drives genome instability and DNA damage hypersensitivity in a PCNA-dependent manner.

Overexpression of the flap endonuclease FEN1 has been observed in a variety of cancer types and is a marker for poor prognosis. To better understand the cellular consequences of FEN1 overexpression we utilized a model of its Saccharomyces cerevisiae homolog, RAD27. In this system, we discovered that flap endonuclease overexpression impedes replication fork progression and leads to an accumulation of cells in mid-S phase. This was accompanied by increased phosphorylation of the checkpoint kinase Rad53 and histone H2A-S129. RAD27 overexpressing cells were hypersensitive to treatment with DNA damaging agents, and defective in ubiquitinating the replication clamp proliferating cell nuclear antigen (PCNA) at lysine 164. These effects were reversed when the interaction between overexpressed Rad27 and PCNA was ablated, suggesting that the observed phenotypes were linked to problems in DNA replication. RAD27 overexpressing cells also exhibited an unexpected dependence on the SUMO ligases SIZ1 and MMS21 for viability. Importantly, we found that overexpression of FEN1 in human cells also led to phosphorylation of CHK1, CHK2, RPA32 and histone H2AX, all markers of genome instability. Our data indicate that flap endonuclease overexpression is a driver of genome instability in yeast and human cells that impairs DNA replication in a manner dependent on its interaction with PCNA.

Single-cell sequencing in ovarian cancer: a new frontier in precision medicine.

PURPOSE OF REVIEW: This article discusses the advances, applications and challenges of using single-cell RNA sequencing data in guiding treatment decisions for ovarian cancer. RECENT FINDINGS: Genetic heterogeneity is a hallmark of ovarian cancer biology and underlies treatment resistance. Defining the different cell types present within a single ovarian cancer is difficult, but could ultimately lead to improvements in diagnosis and treatment. Next-generation sequencing technologies have rapidly increased our understanding of the molecular landscape of epithelial ovarian cancers, but the majority of these studies are conducted on bulk samples, resulting in data that represents an 'average' of all cells present. Single-cell sequencing provides a means to characterize heterogeneity with a tumor tissue in ovarian cancer patients and opens up opportunity to determine key molecular properties that influence clinical outcomes, including prognosis and treatment response. SUMMARY: Single-cell sequencing provides a powerful tool in improving our understanding of tumor cell heterogeneity for the purpose of informing personalized cancer treatment.

Biological Insights into Chemotherapy Resistance in Ovarian Cancer.

The majority of patients with high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy; however, most will develop chemotherapy resistance. Gene signatures may change with the development of chemotherapy resistance in this population, which is important as it may lead to tailored therapies. The objective of this study was to compare tumor gene expression profiles in patients before and after treatment with neoadjuvant chemotherapy (NACT). Tumor samples were collected from six patients diagnosed with HGSOC before and after administration of NACT. RNA extraction and whole transcriptome sequencing was performed. Differential gene expression, hierarchical clustering, gene set enrichment analysis, and pathway analysis were examined in all of the samples. Tumor samples clustered based on exposure to chemotherapy as opposed to patient source. Pre-NACT samples were enriched for multiple pathways involving cell cycle growth. Post-NACT samples were enriched for drug transport and peroxisome pathways. Molecular subtypes based on the pre-NACT sample (differentiated, mesenchymal, proliferative and immunoreactive) changed in four patients after administration of NACT. Multiple changes in tumor gene expression profiles after exposure to NACT were identified from this pilot study and warrant further attention as they may indicate early changes in the development of chemotherapy resistance.

Recurrent R-spondin fusions in colon cancer.

Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics. Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2, chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3. Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM. Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer.

Transposon mutagenesis identifies candidate genes that cooperate with loss of transforming growth factor-beta signaling in mouse intestinal neoplasms.

Colorectal cancer (CRC) results from the accumulation of gene mutations and epigenetic alterations in colon epithelial cells, which promotes CRC formation through deregulating signaling pathways. One of the most commonly deregulated signaling pathways in CRC is the transforming growth factor ß (TGF-ß) pathway. Importantly, the effects of TGF-ß signaling inactivation in CRC are modified by concurrent mutations in the tumor cell, and these concurrent mutations determine the ultimate biological effects of impaired TGF-ß signaling in the tumor. However, many of the mutations that cooperate with the deregulated TGF-ß signaling pathway in CRC remain unknown. Therefore, we sought to identify candidate driver genes that promote the formation of CRC in the setting of TGF-ß signaling inactivation. We performed a forward genetic screen in mice carrying conditionally inactivated alleles of the TGF-ß receptor, type II (Tgfbr2) using Sleeping Beauty (SB) transposon mediated mutagenesis. We used TAPDANCE and Gene-centric statistical methods to identify common insertion sites (CIS) and, thus, candidate tumor suppressor genes and oncogenes within the tumor genome. CIS analysis of multiple neoplasms from these mice identified many candidate Tgfbr2 cooperating genes and the Wnt/ß-catenin, Hippo and MAPK pathways as the most commonly affected pathways. Importantly, the majority of candidate genes were also found to be mutated in human CRC. The SB transposon system provides an unbiased method to identify Tgfbr2 cooperating genes in mouse CRC that are functionally relevant and that may provide further insight into the pathogenesis of human CRC.

A multiplex platform for the identification of ovarian cancer biomarkers.

BACKGROUND: Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients. METHODS: We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients. RESULTS: Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population. CONCLUSIONS: These data demonstrate that the Proseek® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

Single cell sequencing reveals heterogeneity within ovarian cancer epithelium and cancer associated stromal cells.

OBJECTIVES: The purpose of this study was to determine the level of heterogeneity in high grade serous ovarian cancer (HGSOC) by analyzing RNA expression in single epithelial and cancer associated stromal cells. In addition, we explored the possibility of identifying subgroups based on pathway activation and pre-defined signatures from cancer stem cells and chemo-resistant cells. METHODS: A fresh, HGSOC tumor specimen derived from ovary was enzymatically digested and depleted of immune infiltrating cells. RNA sequencing was performed on 92 single cells and 66 of these single cell datasets passed quality control checks. Sequences were analyzed using multiple bioinformatics tools, including clustering, principle components analysis, and geneset enrichment analysis to identify subgroups and activated pathways. Immunohistochemistry for ovarian cancer, stem cell and stromal markers was performed on adjacent tumor sections. RESULTS: Analysis of the gene expression patterns identified two major subsets of cells characterized by epithelial and stromal gene expression patterns. The epithelial group was characterized by proliferative genes including genes associated with oxidative phosphorylation and MYC activity, while the stromal group was characterized by increased expression of extracellular matrix (ECM) genes and genes associated with epithelial-to-mesenchymal transition (EMT). Neither group expressed a signature correlating with published chemo-resistant gene signatures, but many cells, predominantly in the stromal subgroup, expressed markers associated with cancer stem cells. CONCLUSIONS: Single cell sequencing provides a means of identifying subpopulations of cancer cells within a single patient. Single cell sequence analysis may prove to be critical for understanding the etiology, progression and drug resistance in ovarian cancer.

The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer.

New methods for finding common insertion sites and co-occurring common insertion sites in transposon- and virus-based genetic screens.

Insertional mutagenesis screens in mice are used to identify individual genes that drive tumor formation. In these screens, candidate cancer genes are identified if their genomic location is proximal to a common insertion site (CIS) defined by high rates of transposon or retroviral insertions in a given genomic window. In this article, we describe a new method for defining CISs based on a Poisson distribution, the Poisson Regression Insertion Model, and show that this new method is an improvement over previously described methods. We also describe a modification of the method that can identify pairs and higher orders of co-occurring common insertion sites. We apply these methods to two data sets, one generated in a transposon-based screen for gastrointestinal tract cancer genes and another based on the set of retroviral insertions in the Retroviral Tagged Cancer Gene Database. We show that the new methods identify more relevant candidate genes and candidate gene pairs than found using previous methods. Identification of the biologically relevant set of mutations that occur in a single cell and cause tumor progression will aid in the rational design of single and combinatorial therapies in the upcoming age of personalized cancer therapy.

A Sleeping Beauty transposon-mediated screen identifies murine susceptibility genes for adenomatous polyposis coli (Apc)-dependent intestinal tumorigenesis.

It is proposed that a progressive series of mutations and epigenetic events leads to human colorectal cancer (CRC) and metastasis. Furthermore, data from resequencing of the coding regions of human CRC suggests that a relatively large number of mutations occur in individual human CRC, most at low frequency. The functional role of these low-frequency mutations in CRC, and specifically how they may cooperate with high-frequency mutations, is not well understood. One of the most common rate-limiting mutations in human CRC occurs in the adenomatous polyposis coli (APC) gene. To identify mutations that cooperate with mutant APC, we performed a forward genetic screen in mice carrying a mutant allele of Apc (Apc(Min)) using Sleeping Beauty (SB) transposon-mediated mutagenesis. Apc(Min) SB-mutagenized mice developed three times as many polyps as mice with the Apc(Min) allele alone. Analysis of transposon common insertion sites (CIS) identified the Apc locus as a major target of SB-induced mutagenesis, suggesting that SB insertions provide an efficient route to biallelic Apc inactivation. We also identified an additional 32 CIS genes/loci that may represent modifiers of the Apc(Min) phenotype. Five CIS genes tested for their role in proliferation caused a significant change in cell viability when message levels were reduced in human CRC cells. These findings demonstrate the utility of using transposon mutagenesis to identify low-frequency and cooperating cancer genes; this approach will aid in the development of combinatorial therapies targeting this deadly disease.

Differential landscape of immune evasion in oncogenic RAS-driven primary and metastatic colorectal cancers.

Oncogenic drivers such as KRAS extensively modulate the tumor inflammatory microenvironment (TIME) of colorectal cancer (CRC). The influence of KRAS on modulating immune cell composition remains unclear. The objective of this study was to identify signatures of infiltrative immune cells and distinctive patterns that differ between RAS wild-type (WT) and oncogenic mutant (MT) CRC that explain immune evasion in MT tumors. A total of 7,801 CRC specimens were analyzed using next-generation DNA sequencing, whole-exome sequencing, and/or whole transcriptome sequencing. Deficiency of mismatch repair (dMMR)/microsatellite instability (MSI) and tumor mutation burden (TMB) were also assessed. KRAS mutations were present in 48% of CRC, similarly distributed in patients younger than vs. 50 years and older. In microsatellite stable (MSS) KRAS MT tumors, composition of the TIME included higher neutrophil infiltration and lower infiltration of B cells. MSI-H/dMMR was significantly more prevalent in RAS WT (9.1%) than in KRAS MT (2.9%) CRC. In MSS CRC, TMB-high cases were significantly higher in RAS MT (3.1%) than in RAS WT (2.1%) tumors. KRAS and NRAS mutations are associated with increased neutrophil infiltration, with codon-specific differences. These results demonstrate significant differences in the TIME of RAS mutant CRC that match previous reports of immunoevasive characteristics of such tumors.

Fecal Microbiota Restoration Modulates the Microbiome in Inflammation-Driven Colorectal Cancer.

Chronic inflammation of the colon (colitis) is a known risk factor for inflammatory-driven colorectal cancers (id-CRCs), and intestinal microbiota has been implicated in the etiology of id-CRCs. Manipulation of the microbiome is a clinically viable therapeutic approach to limiting id-CRCs. To understand the microbiome changes that occur over time in id-CRCs, we used a mouse model of id-CRCs with the treatment of azoxymethane (AOM) and dextran sodium sulfate (DSS) and measured the microbiome over time. We included cohorts where the microbiome was restored using cage bedding swapping and where the microbiome was depleted using antibiotics to compare to untreated animals. We identified consistent increases in Akkermansia in mice receiving horizontal microbiome transfer (HMT) via cage bedding swapping, while the control cohort had consistent longitudinal increases in Anaeroplasma and Alistipes. Additionally, fecal lipocalin-2 (Lcn-2), a marker of intestinal inflammation, was elevated in unrestored animals compared to restored and antibiotic-treated counterparts following HMT. These observations suggest a potential role for Akkermansia, Anaeroplasma, and Alistipes in regulating colonic inflammation in id-CRCs.