TACkling Cancer by Targeting Selective Protein Degradation.

Targeted protein degradation has emerged as an alternative therapy against cancer, offering several advantages over traditional inhibitors. The new degrader drugs provide different therapeutic strategies: they could cross the phospholipid bilayer membrane by the addition of specific moieties to extracellular proteins. On the other hand, they could efficiently improve the degradation process by the generation of a ternary complex structure of an E3 ligase. Herein, we review the current trends in the use of TAC-based technologies (TACnologies), such as PROteolysis TArgeting Chimeras (PROTAC), PHOtochemically TArgeting Chimeras (PHOTAC), CLIck-formed Proteolysis TArgeting Chimeras (CLIPTAC), AUtophagy TArgeting Chimeras (AUTAC), AuTophagosome TEthering Compounds (ATTEC), LYsosome-TArgeting Chimeras (LYTAC), and DeUBiquitinase TArgeting Chimeras (DUBTAC), in experimental development and their progress towards clinical applications.

Mapping of Genomic Vulnerabilities in the Post-Translational Ubiquitination, SUMOylation and Neddylation Machinery in Breast Cancer.

The dysregulation of post-translational modifications (PTM) transversally impacts cancer hallmarks and constitutes an appealing vulnerability for drug development. In breast cancer there is growing preclinical evidence of the role of ubiquitin and ubiquitin-like SUMO and Nedd8 peptide conjugation to the proteome in tumorigenesis and drug resistance, particularly through their interplay with estrogen receptor signaling and DNA repair. Herein we explored genomic alterations in these processes using RNA-seq and mutation data from TCGA and METABRIC datasets, and analyzed them using a bioinformatic pipeline in search of those with prognostic and predictive capability which could qualify as subjects of drug research. Amplification of UBE2T, UBE2C, and BIRC5 conferred a worse prognosis in luminal A/B and basal-like tumors, luminal A/B tumors, and luminal A tumors, respectively. Higher UBE2T expression levels were predictive of a lower rate of pathological complete response in triple negative breast cancer patients following neoadjuvant chemotherapy, whereas UBE2C and BIRC5 expression was higher in luminal A patients with tumor relapse within 5 years of endocrine therapy or chemotherapy. The transcriptomic signatures of USP9X and USP7 gene mutations also conferred worse prognosis in luminal A, HER2-enriched, and basal-like tumors, and in luminal A tumors, respectively. In conclusion, we identified and characterized the clinical value of a group of genomic alterations in ubiquitination, SUMOylation, and neddylation enzymes, with potential for drug development in breast cancer.

Transcriptomic Mapping of Non-Small Cell Lung Cancer K-RAS p.G12C Mutated Tumors: Identification of Surfaceome Targets and Immunologic Correlates.

Targeting K-RAS-mutant non-small cell lung cancer (NSCLC) with novel inhibitors has shown promising results with the recent approval of sotorasib in this indication. However, progression to this agent is expected, as it has previously been observed with other inhibitors. Recently, new immune therapeutics, including vectorized compounds with antibodies or modulators of the host immune response, have demonstrated clinical activity. By interrogating massive datasets, including TCGA, we identified genes that code for surface membrane proteins that are selectively expressed in K-RAS mutated NSCLC and that could be used to vectorize novel therapies. Two genes, CLDN10 and TMPRSS6, were selected for their clear differentiation. In addition, we discovered immunologic correlates of outcome that were clearly de-regulated in this particular tumor type and we matched them with immune cell populations. In conclusion, our article describes membrane proteins and immunologic correlates that could be used to better select and optimize current therapies.

Checkpoint Kinase 1 Pharmacological Inhibition Synergizes with DNA-Damaging Agents and Overcomes Platinum Resistance in Basal-Like Breast Cancer.

Basal-like breast cancer is an incurable disease with limited therapeutic options, mainly due to the frequent development of anti-cancer drug resistance. Therefore, identification of druggable targets to improve current therapies and overcome these resistances is a major goal. Targeting DNA repair mechanisms has reached the clinical setting and several strategies, like the inhibition of the CHK1 kinase, are currently in clinical development. Here, using a panel of basal-like cancer cell lines, we explored the synergistic interactions of CHK1 inhibitors (rabusertib and SAR020106) with approved therapies in breast cancer and evaluated their potential to overcome resistance. We identified a synergistic action of these inhibitors with agents that produce DNA damage, like platinum compounds, gemcitabine, and the PARP inhibitor olaparib. Our results demonstrated that the combination of rabusertib with these chemotherapies also has a synergistic impact on tumor initiation, invasion capabilities, and apoptosis in vitro. We also revealed a biochemical effect on DNA damage and caspase-dependent apoptosis pathways through the phosphorylation of H2AX, the degradation of full-length PARP, and the increase of caspases 3 and 8 activity. This agent also demonstrated synergistic activity in a platinum-resistant cell line, inducing an increase in cell death in response to cisplatin only when combined with rabusertib, while no toxic effect was found on non-tumorigenic breast tissue-derived cell lines. Lastly, the combination of CHK1 inhibitor with cisplatin and gemcitabine resulted in more activity than single or double combinations, leading to a higher apoptotic effect. In conclusion, in our study we identify therapeutic options for the clinical development of CHK1 inhibitors, and confirm that the inhibition of this kinase can overcome acquired resistance to cisplatin.

Genomic Signatures of Immune Activation Predict Outcome in Advanced Stages of Ovarian Cancer and Basal-Like Breast Tumors.

There is an unmet need for new therapies in metastatic ovarian cancer and basal-like breast cancer since no curative therapies are currently available. Immunotherapy has shown to be active in several solid tumors, but particularly more in those where a pre-activated immune state does exist. In this work, we aim to identify biomarkers that could distinguish immune-activated tumors and predict response to therapies in ovarian and basal-like breast cancer, as well as their association with the level of tumor immune infiltration. We found that the combined expression of IFNG, CD30, CXCL13, and PRF1 correlated with better overall survival (OS) in advanced stage ovarian cancer. This was confirmed using an independent dataset from TCGA. Interestingly, we observed that this gene combination also predicted for better prognosis in ovarian tumors with low mutational load, which typically respond less to immunotherapy. Expression of IFNG, CD30, CXCL13, and PRF1 was associated with increased level of immune infiltrates (CD8+ T cells, dendritic cells, and neutrophils) within the tumor. Moreover, we found that these gene signature also correlated with an increased OS and with a higher level of tumor immune infiltrates (B cells, CD8+ T cells, CD4+ T cells, neutrophils, and dendritic cells) in basal-like breast cancer. In conclusion, our analysis identifies genes signatures with potential to recognize immune activated ovarian and basal-like breast cancers with favorable prognosis and with a remarkable predictive capacity in tumors with low mutational burden. The presented results led to a hypothesis being formulated, but prospective clinical studies are needed to support a potential clinical application.

Transcriptome evolution from breast epithelial cells to basal-like tumors.

In breast cancer, it is unclear the functional modifications at a transcriptomic level that are associated with the evolution from epithelial cells and ductal carcinoma in situ (DCIS) to basal-like tumors. By applying weighted gene co-expression network analysis (WGCNA), we identified 17 gene co-expression modules in normal, DCIS and basal-like tumor samples. We then correlated the expression pattern of these gene modules with disease progression from normal to basal-like tumours and found eight modules exhibiting a high and statistically significant correlation. M4 included genes mainly related to cell cycle/division and DNA replication like CCNA2 or CDK1. The M7 module included genes linked with the immune response showing top hub genes such as CD86 or PTPRC. M10 was found specifically correlated to DCIS, but not to basal-like tumor samples, and showed enrichment in ubiquitination or ubiquitin-like processes. We observed that genes in some of these modules were associated with clinical outcome and/or represented druggable opportunities, including AURKA, AURKB, PLK1, MCM2, CDK1, YWHAE, HSP90AB1, LCK, or those targeting ubiquitination. In conclusion, we describe relevant gene modules related to biological functions that can influence survival and be targeted pharmacologically.

DNA-damage related genes and clinical outcome in hormone receptor positive breast cancer.

BACKGROUND: Control of DNA damage is frequently deregulated in solid tumors. Upregulation of genes within this process can be indicative of a more aggressive phenotype and linked with worse outcome. In the present article we identify DNA damage related genes associated with worse outcome in breast cancer. RESULTS: 2286 genes were differentially expressed between normal breast tissue and basal-like tumors, and 62 included in the DNA metabolic process function. Expression of RAD51, GINS1, TRIP13 and MCM2 were associated with detrimental relapse free survival (RFS) and overall survival (OS) in luminal tumors. The combined analyses of TRIP13+RAD51+MCM2 showed the worse association for RFS (HR 2.25 (1.51-3.35) log rank p= 4.1e-05) and TRIP13+RAD51 for OS (HR 5.13 (0.6-44.17) log rank p=0.098) in ER+/HER2- tumors. TRIP13 is amplified in 3.1% of breast cancers. METHODS: Transcriptomic analyses using public datasets evaluating expression values between normal breast tissue and TNBC identified upregulated genes. Genes included in the DNA metabolic process were selected and confirmed using data contained at oncomine (www.oncomine.org). Evaluation of the selected genes with RFS and OS was performed using the KM Plotter Online Tool (http://www.kmplot.com). Evaluation of molecular alterations was performed using cBioportal (www.cbioportal.org). CONCLUSIONS: Expression of DNA metabolic related genes RAD51, GINS1, TRIP13 and MCM2 are associated with poor outcome. Combinations of some of these genes are linked to poor RFS or OS in luminal A, B and ER+HER2- tumors. Evaluation of its predictive capacity in prospective studies is required.

Synthetic Lethality Interaction Between Aurora Kinases and CHEK1 Inhibitors in Ovarian Cancer.

Ovarian cancer is characterized by frequent mutations at TP53. These tumors also harbor germline mutations at homologous recombination repair genes, so they rely on DNA-damage checkpoint proteins, like the checkpoint kinase 1 (CHEK1) to induce G2 arrest. In our study, by using an in silico approach, we identified a synthetic lethality interaction between CHEK1 and mitotic aurora kinase A (AURKA) inhibitors. Gene expression analyses were used for the identification of relevant biological functions. OVCAR3, OVCAR8, IGROV1, and SKOV3 were used for proliferation studies. Alisertib was tested as AURKA inhibitor and LY2603618 as CHEK1 inhibitor. Analyses of cell cycle and intracellular mediators were performed by flow cytometry and Western blot analysis. Impact on stem cell properties was evaluated by flow cytometry analysis of surface markers and sphere formation assays. Gene expression analyses followed by functional annotation identified a series of deregulated genes that belonged to cell cycle, including AURKA/B, TTK kinase, and CHEK1. AURKA and CHEK1 were amplified in 8.7% and 3.9% of ovarian cancers, respectively. AURKA and CHEK1 inhibitors showed a synergistic interaction in different cellular models. Combination of alisertib and LY2603618 triggered apoptosis, reduced the stem cell population, and increased the effect of taxanes and platinum compounds. Finally, expression of AURKA and CHEK1 was linked with detrimental outcome in patients. Our data describe a synthetic lethality interaction between CHEK1 and AURKA inhibitors with potential translation to the clinical setting. Mol Cancer Ther; 16(11); 2552-62. ©2017 AACR.

Mitotic read-out genes confer poor outcome in luminal A breast cancer tumors.

Luminal breast tumors have been classified into A and B subgroups, with the luminal A being associated with a more favorable clinical outcome. Unfortunately, luminal A tumors do not have a universally good prognosis. We used transcriptomic analyses using public datasets to evaluate the differential expression between normal breast tissue and breast cancer, focusing on upregulated genes included in cell cycle function. Association of selected genes with relapse free survival (RFS) and overall survival (OS) was performed using the KM Plotter Online Tool (http://www.kmplot.com). Seventy-seven genes were differentially expressed between normal and malignant breast tissue. Only five genes were associated with poor RFS and OS. The mitosis-related genes GTSE1, CDCA3, FAM83D and SMC4 were associated with poor outcome specifically in Luminal A tumors. The combination of FAM83D and CDCA3 for RFS and GTSE1 alone for OS showed the better prediction for clinical outcome. CDCA3 was amplified in 3.4% of the tumors, and FAM83D and SMC4 in 2.3% and 2.2%, respectively. In conclusion, we describe a set of genes that predict detrimental outcome in Luminal A tumors. These genes may have utility for stratification in trials of antimitotic agents or cytotoxic chemotherapy, or as candidates for direct target inhibition.

Targeting basal-like breast tumors with bromodomain and extraterminal domain (BET) and polo-like kinase inhibitors.

Metastatic triple negative breast cancer (TNBC) is an incurable disease with limited therapeutic options, and no targeted therapies available. Triple negative tumors and the basal-like genomic subtype, are both characterized by a high proliferation rate and an increase in cell division. In this context, protein kinases involved in the mitotic formation have a relevant role in this tumor subtype. Recently, Bromodomain and extraterminal domain (BET) inhibitors have shown to be active in this disease by modulating the expression of several transcription factors. In this article, by using an "in silico" approach, we identified genomic functions that can be inhibited pharmacologically in basal-like tumors. Functional annotation analyses identified "cell division" and "regulation of transcription" as upregulated functions. When focus on cell division, we identified the polo-like kinase 1 (PLK) as an upregulated kinase. The PLK inhibitor Volasertib had the strongest anti-proliferative effect compared with other inhibitors against mitotic kinases. Gene expression analyses demonstrated that the BET inhibitor JQ1 reduced the expression of kinases involved in cell division, and synergized with Volasertib in a panel of triple negative cell lines. Combination of both agents augmented cell death. Similarly, combination of both compounds reduced the expression of stem cell markers. Globally, this data demonstrates the synergistic interaction between BET and PLK inhibitors, paving the way for their future clinical development.

In silico analyses identify gene-sets, associated with clinical outcome in ovarian cancer: role of mitotic kinases.

INTRODUCTION: Accurate assessment of prognosis in early stage ovarian cancer is challenging resulting in suboptimal selection of patients for adjuvant therapy. The identification of predictive markers for cytotoxic chemotherapy is therefore highly desirable. Protein kinases are important components in oncogenic transformation and those relating to cell cycle and mitosis control may allow for identification of high-risk early stage ovarian tumors. METHODS: Genes with differential expression in ovarian surface epithelia (OSE) and ovarian cancer epithelial cells (CEPIs) were identified from public datasets and analyzed with dChip software. Progression-free (PFS) and overall survival (OS) associated with these genes in stage I/II and late stage ovarian cancer was explored using the Kaplan Meier Plotter online tool. RESULTS: Of 2925 transcripts associated with modified expression in CEPIs compared to OSE, 66 genes coded for upregulated protein kinases. Expression of 9 of these genes (CDC28, CHK1, NIMA, Aurora kinase A, Aurora kinase B, BUB1, BUB1ßB, CDKN2A and TTK) was associated with worse PFS (HR:3.40, log rank p<0.001). The combined analyses of CHK1, CDKN2A, AURKA, AURKB, TTK and NEK2 showed the highest magnitude of association with PFS (HR:4.62, log rank p<0.001). Expression of AURKB predicted detrimental OS in stage I/II ovarian cancer better than all other combinations Conclusion: Genes linked to cell cycle control are associated with worse outcome in early stage ovarian cancer. Incorporation of these biomarkers in clinical studies may help in the identification of patients at high risk of relapse for whom optimizing adjuvant therapeutic strategies is needed.