Gene expression profiling of 49 human tumor xenografts from in vitro culture through multiple in vivo passages--strategies for data mining in support of therapeutic studies

DNA damage, demethylation and anticancer activity of DNA methyltransferase (DNMT) inhibitors

Role of DNA damage and demethylation on anticancer activity of DNA methyltransferase inhibitors (DNMTi) remains undefined. We report the effects of DNMT1 gene deletion/disruption (DNMT1^-/-) on anticancer activity of a class of DNMTi in vitro, in vivo and in human cancers. The gene deletion markedly attenuated cytotoxicity and growth inhibition mediated by decitabine, azacitidine and 5-aza-4'-thio-2'-deoxycytidine (aza-T-dCyd) in colon and breast cancer cells. The drugs induced DNA damage that concurred with DNMT1 inhibition, subsequent G₂/M cell-cycle arrest and apoptosis, and upregulated p21 in DNMT1^+/+ versus DNMT1^-/- status, with aza-T-dCyd the most potent. Tumor growth and DNMT1 were significantly inhibited, and p21 was upmodulated in mice bearing HCT116 DNMT1^+/+ xenograft and bladder PDX tumors. DNMT1 gene deletion occurred in ~ 9% human colon cancers and other cancer types at varying degrees. Decitabine and azacitidine demethylated CDKN2A/CDKN2B genes in DNMT1^+/+ and DNMT1^-/- conditions and increased histone-H3 acetylation with re-expression of p16^INK4A/p15^INK4B in DNMT1^-/- state. Thus, DNMT1 deletion confers resistance to DNMTi, and their anti-cancer activity is determined by DNA damage effects. Patients with DNMT1 gene deletions may not respond to DNMTi treatment.

ROADMAPS: An Online Database of Response Data, Dosing Regimens, and Toxicities of Approved Oncology Drugs as Single Agents to Guide Preclinical In Vivo Studies

Preclinical studies provide valuable data in the early development of novel drugs for patients with cancer. Many cancer treatment regimens now utilize multiple agents with different targets to delay the emergence of drug-resistant tumor cells, and experimental agents are often evaluated in combination with FDA-approved drugs. The Biological Testing Branch (BTB) of the U.S. NCI has evaluated more than 70 FDA-approved oncology drugs to date in human xenograft models. Here, we report the first release of a publicly available, downloadable spreadsheet, ROADMAPS (Responses to Oncology Agents and Dosing in Models to Aid Preclinical Studies, dtp.cancer.gov/databases_tools/roadmaps.htm), that provides data filterable by agent, dose, dosing schedule, route of administration, tumor models tested, responses, host mouse strain, maximum weight loss, drug-related deaths, and vehicle formulation for preclinical experiments conducted by the BTB. Data from 70 different single targeted and cytotoxic agents and 140 different xenograft models were included. Multiple xenograft models were tested in immunocompromised mice for many cancer histologies, with lung cancer as the most broadly tested (24 models). Many of the dose levels and schedules used in these experiments were comparable with those tolerated in humans. Targeted and cytotoxic single agents were included. The online spreadsheet will be updated periodically as additional agent/dose/model combinations are evaluated. ROADMAPS is intended to serve as a publicly available resource for the research community to inform the design of clinically relevant, tolerable single and combinatorial regimens in preclinical mouse models.

SIGNIFICANCE

ROADMAPS includes data that can be used to identify tolerable dosing regimens with activity against a variety of human tumors in different mouse strains, providing a resource for planning preclinical studies.

Reinspection of a Clinical Proteomics Tumor Analysis Consortium (CPTAC) Dataset with Cloud Computing Reveals Abundant Post-Translational Modifications and Protein Sequence Variants

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has provided some of the most in-depth analyses of the phenotypes of human tumors ever constructed. Today, the majority of proteomic data analysis is still performed using software housed on desktop computers which limits the number of sequence variants and post-translational modifications that can be considered. The original CPTAC studies limited the search for PTMs to only samples that were chemically enriched for those modified peptides. Similarly, the only sequence variants considered were those with strong evidence at the exon or transcript level. In this multi-institutional collaborative reanalysis, we utilized unbiased protein databases containing millions of human sequence variants in conjunction with hundreds of common post-translational modifications. Using these tools, we identified tens of thousands of high-confidence PTMs and sequence variants. We identified 4132 phosphorylated peptides in nonenriched samples, 93% of which were confirmed in the samples which were chemically enriched for phosphopeptides. In addition, our results also cover 90% of the high-confidence variants reported by the original proteogenomics study, without the need for sample specific next-generation sequencing. Finally, we report fivefold more somatic and germline variants that have an independent evidence at the peptide level, including mutations in ERRB2 and BCAS1. In this reanalysis of CPTAC proteomic data with cloud computing, we present an openly available and searchable web resource of the highest-coverage proteomic profiling of human tumors described to date.

YKL-40 protein expression in human tumor samples and human tumor cell line xenografts: implications for its use in tumor models

BACKGROUND

YKL-40, also known as non-enzymatic chitinase-3 like-protein-1 (CHI3L1), is a glycoprotein expressed and secreted mainly by inflammatory cells and tumor cells. Accordingly, several studies demonstrated elevated YKL-40 serum levels in cancer patients and found YKL-40 to be correlated with a poor prognosis and disease severity in some tumor entities. YKL-40 was suggested to be involved in angiogenesis and extracellular matrix remodeling. As yet, however, its precise biological function remains elusive.

METHODS

As YKL-40 protein expression has only been investigated in few malignancies, we employed immunohistochemical detection in a large multi-tumor tissue microarray consisting of 2,310 samples from 72 different tumor entities. In addition, YKL-40 protein expression was determined in primary mouse xenograft tumors derived from human cancer cell lines.

RESULTS

YKL-40 could be detected in almost all cancer entities and was differently expressed depending on tumor stage and subtype (e.g., thyroid cancer, colorectal cancer, gastric cancer and ovarian cancer). While YKL-40 was absent in in vitro grown human cancer cell lines, YKL-40 expression was upregulated in xenograft tumor tissues in vivo.

CONCLUSIONS

These data provide new insights into YKL-40 expression at the protein level in various tumor entities and its regulation in tumor models. Our data suggest that upregulation of YKL-40 expression is a common feature in vivo and is finely regulated by tumor cell-microenvironment interactions.

Drug discovery oncology in a mouse: concepts, models and limitations

The utilization of suitable mouse models is a critical step in the drug discovery oncology workflow as their generation and use are important for target identification and validation as well as toxicity and efficacy assessments. Current murine models have been instrumental in furthering insights into the mode of action of drugs before transitioning into the clinic. Recent advancements in genome editing with the development of the CRISPR/Cas9 system and the possibility of applying such technology directly in vivo have expanded the toolkit of preclinical models available. In this review, a brief presentation of the current models used in drug discovery will be provided with a particular emphasis on the novel CRISPR/Cas9 models.

TET2 and DNMT3A mutations and exceptional response to 4'-thio-2'-deoxycytidine in human solid tumor models

Background

Challenges remain on the selection of patients who potentially respond to a class of drugs that target epigenetics for cancer treatment. This study aims to investigate TET2/DNMT3A mutations and antitumor activity of a novel epigenetic agent in multiple human cancer cell lines and animal models.

Methods

Seventeen cancer cell lines and multiple xenograft models bearing representative human solid tumors were subjected to 4′-thio-2′-deoxycytidine (T-dCyd) or control treatment. Gene mutations in cell lines were examined by whole exome and/or Sanger sequencing. Specific gene expression was measured in cells and xenograft tumor samples by Western blotting and immunohistochemistry. TET2/DNMT3A mutation status in 47,571 human tumor samples was analyzed at cBioPortal for Cancer Genomics.

Results

Cell survival was significantly inhibited by T-dCyd in breast BT549, lung NCI-H23, melanoma SKMEL5 and renal ACHN cancer lines harboring deleterious TET2 and nonsynonymous DNMT3A mutations compared to 13 lines without such mutation pattern (P = 0.007). The treatment upregulated p21 and induced cell cycle arrest in NCI-H23 cells, and dramatically inhibited their xenograft tumor growth versus wildtype models. T-dCyd administrations led to a significant p21 increase and near eradication of tumor cells in the double-mutant xenografts by histological evaluation. TET2/DNMT3A was co-mutated in human lung, breast, skin and kidney cancers and frequently in angioimmunoblastic and peripheral T cell lymphomas and several types of leukemia.

Conclusions

Cell and animal models with concurrent mutations in TET2 and DNMT3A were sensitive to T-dCyd treatment. The mutations were detectable in human solid tumors and frequently occur in some hematological malignancies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13045-021-01091-5.

F-aza-T-dCyd (NSC801845), a Novel Cytidine Analog, in Comparative Cell Culture and Xenograft Studies with the Clinical Candidates T-dCyd, F-T-dCyd, and Aza-T-dCyd

In this article, 5-aza-4'-thio-2'-β-fluoro-2'-deoxycytidine (F-aza-T-dCyd, NSC801845), a novel cytidine analog, is first disclosed and compared with T-dCyd, F-T-dCyd, and aza-T-dCyd in cell culture and mouse xenograft studies in HCT-116 human colon carcinoma, OVCAR3 human ovarian carcinoma, NCI-H23 human NSCLC carcinoma, HL-60 human leukemia, and the PDX BL0382 bladder carcinoma. In three of five xenograft lines (HCT-116, HL-60, and BL-0382), F-aza-T-dCyd was more efficacious than aza-T-dCyd. Comparable activity was observed for these two agents against the NCI-H23 and OVCAR3 xenografts. In the HCT-116 study, F-aza-T-dCyd [10 mg/kg intraperitoneal (i.p.), QDx5 for four cycles], produced complete regression of the tumors in all mice with a response that proved durable beyond postimplant day 150 (129 days after the last dose). Similarly, complete tumor regression was observed in the HL-60 leukemia xenograft when mice were dosed with F-aza-T-dCyd (10 mg/kg i.p., QDx5 for three cycles). In the PDX BL-0382 bladder study, both oral and i.p. dosing of F-aza-T-dCyd (8 mg/kg QDx5 for three cycles) produced regressions that showed tumor regrowth beginning 13 days after dosing. These findings indicate that further development of F-aza-T-dCyd (NSC801845) is warranted. GRAPHICAL ABSTRACT: http://mct.aacrjournals.org/content/molcanther/20/4/625/F1.large.jpg.

Computational Drug Repositioning and Experimental Validation of Ivermectin in Treatment of Gastric Cancer

Objective: The aim of the present study was repositioning of ivermectin in treatment of gastric cancer (GC) by computational prediction based on gene expression profiles of human and mouse model of GC and validations with in silico, in vitro and in vivo approaches.

Methods: Computational drug repositioning was performed using connectivity map (cMap) and data/pathway mining with the Ingenuity Knowledge Base. Tissue samples of GC were collected from 16 patients and 57 mice for gene expression profiling. Additional seven independent datasets of gene expression of human GC from the TCGA database were used for validation. In silico testing was performed by constructing interaction networks of ivermectin and the downstream effects in targeted signaling pathways. In vitro testing was carried out in human GC cell lines (MKN74 and KATO-III). In vivo testing was performed in a transgenic mouse model of GC (INS-GAS mice).

Results: GC gene expression “signature” and data/pathway mining but not cMAP revealed nine molecular targets of ivermectin in both human and mouse GC associated with WNT/β-catenin signaling as well as cell proliferation pathways. In silico inhibition of the targets of ivermectin and concomitant activation of ivermectin led to the inhibition of WNT/β-catenin signaling pathway in “dose-depended” manner. In vitro, ivermectin inhibited cell proliferation in time- and concentration-depended manners, and cells were arrested in the G₁ phase at IC₅₀ and shifted to S phase arrest at >IC₅₀. In vivo, ivermectin reduced the tumor size which was associated with inactivation of WNT/β-catenin signaling and cell proliferation pathways and activation of cell death signaling pathways.

Conclusion: Ivermectin could be recognized as a repositioning candidate in treatment of gastric cancer.

Proteome Discoverer-A Community Enhanced Data Processing Suite for Protein Informatics

Proteomics researchers today face an interesting challenge: how to choose among the dozens of data processing and analysis pipelines available for converting tandem mass spectrometry files to protein identifications. Due to the dominance of Orbitrap technology in proteomics in recent history, many researchers have defaulted to the vendor software Proteome Discoverer. Over the fourteen years since the initial release of the software, it has evolved in parallel with the increasingly complex demands faced by proteomics researchers. Today, Proteome Discoverer exists in two distinct forms with both powerful commercial versions and fully functional free versions in use in many labs today. Throughout the 11 main versions released to date, a central theme of the software has always been the ability to easily view and verify the spectra from which identifications are made. This ability is, even today, a key differentiator from other data analysis solutions. In this review I will attempt to summarize the history and evolution of Proteome Discoverer from its first launch to the versions in use today.

PDXGEM: patient-derived tumor xenograft-based gene expression model for predicting clinical response to anticancer therapy in cancer patients

Background

Cancer is a highly heterogeneous disease with varying responses to anti-cancer drugs. Although several attempts have been made to predict the anti-cancer therapeutic responses, there remains a great need to develop highly accurate prediction models of response to the anti-cancer drugs for clinical applications toward a personalized medicine. Patient derived xenografts (PDXs) are preclinical cancer models in which the tissue or cells from a patient’s tumor are implanted into an immunodeficient or humanized mouse. In the present study, we develop a bioinformatics analysis pipeline to build a predictive gene expression model (GEM) for cancer patients’ drug responses based on gene expression and drug activity data from PDX models.

Results

Drug sensitivity biomarkers were identified by performing an association analysis between gene expression levels and post-treatment tumor volume changes in PDX models. We built a drug response prediction model (called PDXGEM) in a random-forest algorithm by using a subset of the drug sensitvity biomarkers with concordant co-expression patterns between the PDXs and pretreatment cancer patient tumors. We applied the PDXGEM to several cytotoxic chemotherapies as well as targeted therapy agents that are used to treat breast cancer, pancreatic cancer, colorectal cancer, or non-small cell lung cancer. Significantly accurate predictions of PDXGEM for pathological response or survival outcomes were observed in extensive independent validations on multiple cancer patient datasets obtained from retrospective observational studies and prospective clinical trials.

Conclusion

Our results demonstrated the strong potential of using molecular profiles and drug activity data of PDX tumors in developing a clinically translatable predictive cancer biomarkers for cancer patients. The PDXGEM web application is publicly available at http://pdxgem.moffitt.org.

CCLA: an accurate method and web server for cancer cell line authentication using gene expression profiles

Cancer cell lines (CCLs) as important model systems play critical roles in cancer research. The misidentification and contamination of CCLs are serious problems, leading to unreliable results and waste of resources. Current methods for CCL authentication are mainly based on the CCL-specific genetic polymorphism, whereas no method is available for CCL authentication using gene expression profiles. Here, we developed a novel method and homonymic web server (CCLA, Cancer Cell Line Authentication, http://bioinfo.life.hust.edu.cn/web/CCLA/) to authenticate 1291 human CCLs of 28 tissues using gene expression profiles. CCLA showed an excellent speed advantage and high accuracy for CCL authentication, a top 1 accuracy of 96.58 or 92.15% (top 3 accuracy of 100 or 95.11%) for microarray or RNA-Seq validation data (719 samples, 461 CCLs), respectively. To the best of our knowledge, CCLA is the first approach to authenticate CCLs using gene expression data. Users can freely and conveniently authenticate CCLs using gene expression profiles or NCBI GEO accession on CCLA website.

TET1 promotes growth of T-cell acute lymphoblastic leukemia and can be antagonized via PARP inhibition

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological cancer characterized by skewed epigenetic patterns, raising the possibility of therapeutically targeting epigenetic factors in this disease. Here we report that among different cancer types, epigenetic factor TET1 is highly expressed in T-ALL and is crucial for human T-ALL cell growth in vivo. Knockout of TET1 in mice and knockdown in human T cell did not perturb normal T-cell proliferation, indicating that TET1 expression is dispensable for normal T-cell growth. The promotion of leukemic growth by TET1 was dependent on its catalytic property to maintain global 5-hydroxymethylcytosine (5hmC) marks, thereby regulate cell cycle, DNA repair genes, and T-ALL associated oncogenes. Furthermore, overexpression of the Tet1-catalytic domain was sufficient to augment global 5hmC levels and leukemic growth of T-ALL cells in vivo. We demonstrate that PARP enzymes, which are highly expressed in T-ALL patients, participate in establishing H3K4me3 marks at the TET1 promoter and that PARP1 interacts with the TET1 protein. Importantly, the growth related role of TET1 in T-ALL could be antagonized by the clinically approved PARP inhibitor Olaparib, which abrogated TET1 expression, induced loss of 5hmC marks, and antagonized leukemic growth of T-ALL cells, opening a therapeutic avenue for this disease.

Immuno-imaging of ICAM-1 in tumours by SPECT

PURPOSE

Molecular imaging of cancer cells' reaction to radiation damage can provide a non-invasive measure of tumour response to treatment. The cell surface glycoprotein ICAM-1 (CD54) was identified as a potential radiation response marker. SPECT imaging using an 111In-radiolabelled anti-ICAM-1 antibody was explored.

METHODS

PSN-1 cells were irradiated (10 Gy), and protein expression changes were investigated using an antibody array on cell lysates 24 h later. Results were confirmed by western blot, flow cytometry and immunofluorescence. We confirmed the affinity of an 111In-labelled anti-ICAM-1 antibody in vitro, and in vivo, in PSN-1-xenograft bearing mice. The xenografts were irradiated (0 or 10 Gy), and [111In]In-anti-ICAM-1 SPECT/CT images were acquired 24, 48 and 72 h after intravenous administration.

RESULTS

ICAM-1 was identified as a potential marker of radiation treatment using an antibody array in PSN-1 cell lysates following irradiation, showing a significant increase in ICAM-1 signal compared to non-irradiated cells. Western blot and immunohistochemistry confirmed this upregulation, with an up to 20-fold increase in ICAM-1 signal. Radiolabelled anti-ICAM-1 bound to ICAM-1 expressing cells with good affinity (Kd = 24.0 ± 4.0 nM). [111In]In-anti-ICAM-1 uptake in tumours at 72 h post injection was approximately 3-fold higher than non-specific isotype-matched [111In]In-mIgG2a control (19.3 ± 2.5%ID/g versus 6.3 ± 2.2%ID/g, P = 0.0002). However, ICAM1 levels, and [111In]In-anti-ICAM-1 uptake in tumours was no different after irradiation (uptake 9.2%ID/g versus 14.8%ID/g). Western blots of the xenograft lysates showed no significant differences, confirming these results.

CONCLUSION

Imaging of ICAM-1 is feasible in mouse models of pancreatic cancer. Although ICAM-1 is upregulated post-irradiation in in vitro models of pancreatic cancer, it shows little change in expression in an in vivo mouse xenograft model.

Murine xenograft bioreactors for human immunopeptidome discovery

The study of peptides presented by MHC class I and class II molecules is limited by the need for relatively large cell numbers, especially when studying post-translationally modified or otherwise rare peptide species. To overcome this problem, we pose the hypothesis that human cells grown as xenografts in immunodeficient mice should produce equivalent immunopeptidomes as cultured cells. Comparing human cell lines grown either in vitro or as murine xenografts, we show that the immunopeptidome is substantially preserved. Numerous features are shared across both sample types, including peptides and proteins featured, length distributions, and HLA-binding motifs. Peptides well-represented in both groups were from more abundant proteins, or those with stronger predicted HLA binding affinities. Samples grown in vivo also recapitulated a similar phospho-immunopeptidome, with common sequences being those found at high copy number on the cell surface. These data indicate that xenografts are indeed a viable methodology for the production of cells for immunopeptidomic discovery.

Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models

Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients.

BRAF and AXL oncogenes drive RIPK3 expression loss in cancer

Necroptosis is a lytic programmed cell death mediated by the RIPK1-RIPK3-MLKL pathway. The loss of Receptor-interacting serine/threonine-protein kinase 3 (RIPK3) expression and necroptotic potential have been previously reported in several cancer cell lines; however, the extent of this loss across cancer types, as well as its mutational drivers, were unknown. Here, we show that RIPK3 expression loss occurs progressively during tumor growth both in patient tumor biopsies and tumor xenograft models. Using a cell-based necroptosis sensitivity screen of 941 cancer cell lines, we find that escape from necroptosis is prevalent across cancer types, with an incidence rate of 83%. Genome-wide bioinformatics analysis of this differential necroptosis sensitivity data in the context of differential gene expression and mutation data across the cell lines identified various factors that correlate with resistance to necroptosis and loss of RIPK3 expression, including oncogenes BRAF and AXL. Inhibition of these oncogenes can rescue the RIPK3 expression loss and regain of necroptosis sensitivity. This genome-wide analysis also identifies that the loss of RIPK3 expression is the primary factor correlating with escape from necroptosis. Thus, we conclude that necroptosis resistance of cancer cells is common and is oncogene driven, suggesting that escape from necroptosis could be a potential hallmark of cancer, similar to escape from apoptosis.

Human tissue models in cancer research: looking beyond the mouse

Mouse models, including patient-derived xenograft mice, are widely used to address questions in cancer research. However, there are documented flaws in these models that can result in the misrepresentation of human tumour biology and limit the suitability of the model for translational research. A coordinated effort to promote the more widespread development and use of ‘non-animal human tissue’ models could provide a clinically relevant platform for many cancer studies, maximising the opportunities presented by human tissue resources such as biobanks. A number of key factors limit the wide adoption of non-animal human tissue models in cancer research, including deficiencies in the infrastructure and the technical tools required to collect, transport, store and maintain human tissue for lab use. Another obstacle is the long-standing cultural reliance on animal models, which can make researchers resistant to change, often because of concerns about historical data compatibility and losing ground in a competitive environment while new approaches are embedded in lab practice. There are a wide range of initiatives that aim to address these issues by facilitating data sharing and promoting collaborations between organisations and researchers who work with human tissue. The importance of coordinating biobanks and introducing quality standards is gaining momentum. There is an exciting opportunity to transform cancer drug discovery by optimising the use of human tissue and reducing the reliance on potentially less predictive animal models.

Summary: Samuel Jackson and Gareth Thomas discuss the limitations of patient-derived xenograft mouse models and highlight initiatives to maximise the use of human tissue in cancer research, with the goal of improving translation and reducing animal experimentation.

Collagen type IV alpha 1 (COL4A1) and collagen type XIII alpha 1 (COL13A1) produced in cancer cells promote tumor budding at the invasion front in human urothelial carcinoma of the bladder

Current knowledge of the molecular mechanism driving tumor budding is limited. Here, we focused on elucidating the detailed mechanism underlying tumor budding in urothelial cancer of the bladder. Invasive urothelial cancer was pathologically classified into three groups as follows: nodular, trabecular, and infiltrative (tumor budding). Pathohistological analysis of the orthotopic tumor model revealed that human urothelial cancer cell lines MGH-U3, UM-UC-14, and UM-UC-3 displayed typical nodular, trabecular, and infiltrative patterns, respectively. Based on the results of comprehensive gene expression analysis using microarray (25 K Human Oligo chip), we identified two collagens, COL4A1 and COL13A1, which may contribute to the formation of the infiltrative pattern. Visualization of protein interaction networks revealed that proteins associated with connective tissue disorders, epithelial-mesenchymal transition, growth hormone, and estrogen were pivotal factors in tumor cells. To evaluate the invasion pattern of tumor cells in vitro, 3-D collective cell invasion assay using Matrigel was performed. Invadopodial formation was evaluated using Gelatin Invadopodia Assay. Knockdown of collagens with siRNA led to dramatic changes in invasion patterns and a decrease in invasion capability through decreased invadopodia. The in vivo orthotopic experimental model of bladder tumors showed that intravesical treatment with siRNA targeting COL4A1 and COL13A1 inhibited the formation of the infiltrative pattern. COL4A1 and COL13A1 production by cancer cells plays a pivotal role in tumor invasion through the induction of tumor budding. Blocking of these collagens may be an attractive therapeutic approach for treatment of human urothelial cancer of the bladder.

Alteration of Epigenetic Regulation by Long Noncoding RNAs in Cancer

Long noncoding RNAs (lncRNAs) are important regulators of the epigenetic status of the human genome. Besides their participation to normal physiology, lncRNA expression and function have been already associated to many diseases, including cancer. By interacting with epigenetic regulators and by controlling chromatin topology, their misregulation may result in an aberrant regulation of gene expression that may contribute to tumorigenesis. Here, we review the functional role and mechanisms of action of lncRNAs implicated in the aberrant epigenetic regulation that has characterized cancer development and progression.

The human lncRNA LINC-PINT inhibits tumor cell invasion through a highly conserved sequence element

Background

It is now obvious that the majority of cellular transcripts do not code for proteins, and a significant subset of them are long non-coding RNAs (lncRNAs). Many lncRNAs show aberrant expression in cancer, and some of them have been linked to cell transformation. However, the underlying mechanisms remain poorly understood and it is unknown how the sequences of lncRNA dictate their function.

Results

Here we characterize the function of the p53-regulated human lncRNA LINC-PINT in cancer. We find that LINC-PINT is downregulated in multiple types of cancer and acts as a tumor suppressor lncRNA by reducing the invasive phenotype of cancer cells. A cross-species analysis identifies a highly conserved sequence element in LINC-PINT that is essential for its function. This sequence mediates a specific interaction with PRC2, necessary for the LINC-PINT-dependent repression of a pro-invasion signature of genes regulated by the transcription factor EGR1.

Conclusions

Our findings support a conserved functional co-dependence between LINC-PINT and PRC2 and lead us to propose a new mechanism where the lncRNA regulates the availability of free PRC2 at the proximity of co-regulated genomic loci.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1331-y) contains supplementary material, which is available to authorized users.

Patient-derived xenografts undergo mouse-specific tumor evolution

Patient-derived xenografts (PDXs) have become a prominent cancer model system, as they are presumed to faithfully represent the genomic features of primary tumors. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We observed rapid accumulation of CNAs during PDX passaging, often due to selection of pre-existing minor clones. CNA acquisition in PDXs was correlated with the tissue-specific levels of aneuploidy and genetic heterogeneity observed in primary tumors. However, the particular CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients. Several CNAs recurrently observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Importantly, the genomic stability of PDXs was associated with their response to chemotherapy and targeted drugs. These findings have important implications for PDX-based modeling of human cancer.

3D Models of the NCI60 Cell Lines for Screening Oncology Compounds

The NCI60 cell line panel screen includes 60 human tumor cell lines derived from nine tumor types that has been used over the past 20+ years to screen small molecules, biologics, and natural products for activity. Cells in monolayer culture in 96-well plates are exposed to compounds for 48 h, and Sulforhodamine B is used to determine cell viability. Data analysis tools such as COMPARE allow classification of compounds based on the pattern of cell line response. However, many compounds highly active in monolayer cell culture fail to show efficacy in vivo. Therefore, we explored 3D culture of the NCI60 panel as a strategy to improve the predictive accuracy of the screen. 3D cultures more closely resemble tumors than monolayer cultures with tighter cell-cell contact and nutrient and oxygen gradients between the periphery and the center. We optimized the NCI60 cell line panel for generating 3D spheroids of a prespecified diameter (300-500 µm) in ultra-low attachment (ULA) plates. Spheroids were classified into four categories based on imaging, and concentration response of select agents in 2D and 3D models is presented.

CASTIN: a system for comprehensive analysis of cancer-stromal interactome

BACKGROUND

Cancer microenvironment plays a vital role in cancer development and progression, and cancer-stromal interactions have been recognized as important targets for cancer therapy. However, identifying relevant and druggable cancer-stromal interactions is challenging due to the lack of quantitative methods to analyze whole cancer-stromal interactome.

RESULTS

We present CASTIN (CAncer-STromal INteractome analysis), a novel framework for the evaluation of cancer-stromal interactome from RNA-Seq data using cancer xenograft models. For each ligand-receptor interaction which is derived from curated protein-protein interaction database, CASTIN summarizes gene expression profiles of cancer and stroma into three evaluation indices. These indices provide quantitative evaluation and comprehensive visualization of interactome, and thus enable to identify critical cancer-microenvironment interactions, which would be potential drug targets. We applied CASTIN to the dataset of pancreas ductal adenocarcinoma, and successfully characterized the individual cancer in terms of cancer-stromal relationships, and identified both well-known and less-characterized druggable interactions.

CONCLUSIONS

CASTIN provides comprehensive view of cancer-stromal interactome and is useful to identify critical interactions which may serve as potential drug targets in cancer-microenvironment. CASTIN is available at: http://github.com/tmd-gpat/CASTIN .

Heterotypic mouse models of canine osteosarcoma recapitulate tumor heterogeneity and biological behavior

Osteosarcoma (OS) is a heterogeneous and rare disease with a disproportionate impact because it mainly affects children and adolescents. Lamentably, more than half of patients with OS succumb to metastatic disease. Clarification of the etiology of the disease, development of better strategies to manage progression, and methods to guide personalized treatments are among the unmet health needs for OS patients. Progress in managing the disease has been hindered by the extreme heterogeneity of OS; thus, better models that accurately recapitulate the natural heterogeneity of the disease are needed. For this study, we used cell lines derived from two spontaneous canine OS tumors with distinctly different biological behavior (OS-1 and OS-2) for heterotypic in vivo modeling that recapitulates the heterogeneous biology and behavior of this disease. Both cell lines demonstrated stability of the transcriptome when grown as orthotopic xenografts in athymic nude mice. Consistent with the behavior of the original tumors, OS-2 xenografts grew more rapidly at the primary site and had greater propensity to disseminate to lung and establish microscopic metastasis. Moreover, OS-2 promoted formation of a different tumor-associated stromal environment than OS-1 xenografts. OS-2-derived tumors comprised a larger percentage of the xenograft tumors than OS-1-derived tumors. In addition, a robust pro-inflammatory population dominated the stromal cell infiltrates in OS-2 xenografts, whereas a mesenchymal population with a gene signature reflecting myogenic signaling dominated those in the OS-1 xenografts. Our studies show that canine OS cell lines maintain intrinsic features of the tumors from which they were derived and recapitulate the heterogeneous biology and behavior of bone cancer in mouse models. This system provides a resource to understand essential interactions between tumor cells and the stromal environment that drive the progression and metastatic propensity of OS.

Editors' choice: We developed a system that recapitulates the heterogeneous biological behavior of bone cancer in mouse models and describe novel methods to study tumor–stromal interactions in these models.

Stromal contribution to the colorectal cancer transcriptome

Recent studies identified a poor-prognosis stem/serrated/mesenchymal (SSM) transcriptional subtype of colorectal cancer (CRC). We noted that genes upregulated in this subtype are also prominently expressed by stromal cells, suggesting that SSM transcripts could derive from stromal rather than epithelial cancer cells. To test this hypothesis, we analyzed CRC expression data from patient-derived xenografts, where mouse stroma supports human cancer cells. Species-specific expression analysis showed that the mRNA levels of SSM genes were mostly due to stromal expression. Transcriptional signatures built to specifically report the abundance of cancer-associated fibroblasts (CAFs), leukocytes or endothelial cells all had significantly higher expression in human CRC samples of the SSM subtype. High expression of the CAF signature was associated with poor prognosis in untreated CRC, and joint high expression of the stromal signatures predicted resistance to radiotherapy in rectal cancer. These data show that the distinctive transcriptional and clinical features of the SSM subtype can be ascribed to its particularly abundant stromal component.

Genomic Analysis as the First Step toward Personalized Treatment in Renal Cell Carcinoma

Drug resistance mechanisms in renal cell carcinoma (RCC) still remain elusive. Although most patients initially respond to targeted therapy, acquired resistance can still develop eventually. Most of the patients suffer from intrinsic (genetic) resistance as well, suggesting that there is substantial need to broaden our knowledge in the field of RCC genetics. As molecular abnormalities occur for various reasons, ranging from single nucleotide polymorphisms to large chromosomal defects, conducting whole-genome association studies using high-throughput techniques seems inevitable. In principle, data obtained via genome-wide research should be continued and performed on a large scale for the purposes of drug development and identification of biological pathways underlying cancerogenesis. Genetic alterations are mostly unique for each histological RCC subtype. According to recently published data, RCC is a highly heterogeneous tumor. In this paper, the authors discuss the following: (1) current state-of-the-art knowledge on the potential biomarkers of RCC subtypes; (2) significant obstacles encountered in the translational research on RCC; and (3) recent molecular findings that may have a crucial impact on future therapeutic approaches.