Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data

Impact of neoadjuvant chemotherapy on somatic mutation status in high-grade serous ovarian carcinoma

BACKGROUND

Patients treated with neoadjuvant chemotherapy (NACT) for advanced high-grade serous ovarian carcinoma (HGSC) have a higher rate and shorter time to platinum-resistant recurrence compared to patients treated with primary cytoreductive surgery (PCS) and adjuvant chemotherapy. The purpose of this study is to determine the impact of NACT on somatic mutation status in platinum-sensitive and resistant HGSC. Patients with advanced HGSC who had a documented response to platinum-based NACT, a banked blood sample, and a banked tumor sample before and after NACT were identified. Whole exome and/or targeted deep sequencing was performed in matched normal and pre/post-NACT tumor samples from 3 platinum-resistant and 2 platinum-sensitive patients to identify somatic non-synonymous mutations at each time point.

RESULTS

When comparing exonic non-synonymous mutations in pre-NACT and post-NACT samples from the same patient, an average of 41% (1-68%) of genes were mutated at both time points. There were no trends detected in the mutational burden following exposure to NACT in platinum-resistant vs. platinum-sensitive cases. The majority of mutated genes were unique to each case. We identified several genes that were commonly mutated in pre-NACT samples specific to platinum-resistant (CSPG4, SLC35G5, TUBA3D) or sensitive (CYP2D6, NUTM1, DNAH5) cases. Four mutated genes emerged exclusively in the platinum-resistant cases (ADGRV1, MUC17, MUC20, PAK2) following NACT.

CONCLUSIONS

Patients with advanced HGSC present with significant intra-tumor heterogeneity. NACT significantly impacts the somatic mutation status irrespective of the time to recurrence. The mutated genes detected in chemo-naive pre-NACT tumor samples from either resistant or sensitive cases could potentially have a role in the prediction of chemotherapy response in patients scheduled to receive NACT; larger studies are required to further validate these genes.

Functional Analysis of Non-Genetic Resistance to Platinum in Epithelial Ovarian Cancer Reveals a Role for the MBD3-NuRD Complex in Resistance Development

Simple Summary

Most epithelial ovarian cancer (EOC) patients, although initially responsive to standard treatment with platinum-based chemotherapy, develop platinum resistance over the clinical course and succumb due to drug-resistant metastases. It has long been hypothesized that resistance to platinum develops as a result of epigenetic changes within tumor cells evolving over time. In this study, we investigated epigenomic changes in EOC patient samples, as well as in cell lines, and showed that profound changes at enhancers result in a platinum-resistant phenotype. Through correlation of the epigenomic alterations with changes in the transcriptome, we could identify potential novel prognostic biomarkers for early patient stratification. Furthermore, we applied a combinatorial RNAi screening approach to identify suitable targets that prevent the enhancer remodeling process. Our results advance the molecular understanding of epigenetic mechanisms in EOC and therapy resistance, which will be essential for the further exploration of epigenetic drug targets and combinatorial treatment regimes.

Abstract

Epithelial ovarian cancer (EOC) is the most lethal disease of the female reproductive tract, and although most patients respond to the initial treatment with platinum (cPt)-based compounds, relapse is very common. We investigated the role of epigenetic changes in cPt-sensitive and -resistant EOC cell lines and found distinct differences in their enhancer landscape. Clinical data revealed that two genes (JAK1 and FGF10), which gained large enhancer clusters in resistant EOC cell lines, could provide novel biomarkers for early patient stratification with statistical independence for JAK1. To modulate the enhancer remodeling process and prevent the acquisition of cPt resistance in EOC cells, we performed a chromatin-focused RNAi screen in the presence of cPt. We identified subunits of the Nucleosome Remodeling and Deacetylase (NuRD) complex as critical factors sensitizing the EOC cell line A2780 to platinum treatment. Suppression of the Methyl-CpG Binding Domain Protein 3 (MBD3) sensitized cells and prevented the establishment of resistance under prolonged cPt exposure through alterations of H3K27ac at enhancer regions, which are differentially regulated in cPt-resistant cells, leading to a less aggressive phenotype. Our work establishes JAK1 as an independent prognostic marker and the NuRD complex as a potential target for combinational therapy.

Network analysis with biological data of cancer patients: A scoping review

BACKGROUND & OBJECTIVE

Network Analysis (NA) is a mathematical method that allows exploring relations between units and representing them as a graph. Although NA was initially related to social sciences, the past two decades was introduced in Bioinformatics. The recent growth of the networks' use in biological data analysis reveals the need to further investigate this area. In this work, we attempt to identify the use of NA with biological data, and specifically: (a) what types of data are used and whether they are integrated or not, (b) what is the purpose of this analysis, predictive or descriptive, and (c) the outcome of such analyses, specifically in cancer diseases.

METHODS & MATERIALS

The literature review was conducted on two databases, PubMed & IEEE, and was restricted to journal articles of the last decade (January 2010 - December 2019). At a first level, all articles were screened by title and abstract, and at a second level the screening was conducted by reading the full text article, following the predefined inclusion & exclusion criteria leading to 131 articles of interest. A table was created with the information of interest and was used for the classification of the articles. The articles were initially classified to analysis studies and studies that propose a new algorithm or methodology. Each one of these categories was further screened by the following clustering criteria: (a) data used, (b) study purpose, (c) study outcome. Specifically for the studies proposing a new algorithm, the novelty presented in each one was detected.

RESULTS

& Conclusions: In the past five years researchers are focusing on creating new algorithms and methodologies to enhance this field. The articles' classification revealed that only 25% of the analyses are integrating multi-omics data, although 50% of the new algorithms developed follow this integrative direction. Moreover, only 20% of the analyses and 10% of the newly developed methodologies have a predictive purpose. Regarding the result of the works reviewed, 75% of the studies focus on identifying, prognostic or not, gene signatures. Concluding, this review revealed the need for deploying predictive and multi-omics integrative algorithms and methodologies that can be used to enhance cancer diagnosis, prognosis and treatment.

Collagen XI alpha 1 chain, a potential therapeutic target for cancer

Extracellular matrix (ECM) plays an important role in the progression of cancer. Collagen is the most abundant component in ECM, and it is involved in the biological formation of cancer. Although type XI collagen is a minor fibrillar collagen, collagen XI alpha 1 chain (COL11A1) has been found to be upregulated in a variety of cancers including ovarian cancer, breast cancer, thyroid cancer, pancreatic cancer, non-small-cell lung cancer, and transitional cell carcinoma of the bladder. High levels of COL11A1 usually predict poor prognosis, while COL11A1 is related to angiogenesis, invasion, and drug resistance of cancer. However, little is known about the specific mechanism by which COL11A1 regulates tumor progression. Here, we have organized and summarized the recent developments regarding elucidation of the relationship between COL11A1 and various cancers, as well as the interaction between COL11A1 and intracellular signaling pathways. In addition, we have selected therapeutic agents targeting COL11A1. All these indicate the possibility of using COL11A1 as a target for cancer treatment.

Organotypic Models in Drug Development "Tumor Models and Cancer Systems Biology for the Investigation of Anticancer Drugs and Resistance Development"

The landscape of cancer treatment has improved over the past decades, aiming to reduce systemic toxicity and enhance compatibility with the quality of life of the patient. However, at the therapeutic level, metastatic cancer remains hugely challenging, based on the almost inevitable emergence of therapy resistance. A small subpopulation of cells able to survive drug treatment termed the minimal residual disease may either harbor resistance-associated mutations or be phenotypically resistant, allowing them to regrow and become the dominant population in the therapy-resistant tumor. Characterization of the profile of minimal residual disease represents the key to the identification of resistance drivers that underpin cancer evolution. Therapeutic regimens must, therefore, be dynamic and tailored to take into account the emergence of resistance as tumors evolve within a complex microenvironment in vivo. This requires the adoption of new technologies based on the culture of cancer cells in ways that more accurately reflect the intratumor microenvironment, and their analysis using omics and system-based technologies to enable a new era in the diagnostics, classification, and treatment of many cancer types by applying the concept "from the cell plate to the patient." In this chapter, we will present and discuss 3D model building and use, and provide comprehensive information on new genomic techniques that are increasing our understanding of drug action and the emergence of resistance.

Functional and transcriptomic characterization of carboplatin-resistant A2780 ovarian cancer cell line

Background

Ovarian cancer is a significant cancer-related cause of death in women worldwide. The most used chemotherapeutic regimen is based on carboplatin (CBDCA). However, CBDCA resistance is the main obstacle to a better prognosis. An in vitro drug-resistant cell model would help in the understanding of molecular mechanisms underlying this drug-resistance phenomenon. The aim of this study was to characterize cellular and molecular changes of induced CBDCA-resistant ovarian cancer cell line A2780.

Methods

The cell selection strategy used in this study was a dose-per-pulse method using a concentration of 100 μM for 2 h. Once 20 cycles of exposure to the drug were completed, the cell cultures showed a resistant phenotype. Then, the ovarian cancer cell line A2780 was grown with 100 μM of CBDCA (CBDCA-resistant cells) or without CBDCA (parental cells). After, a drug sensitivity assay, morphological analyses, cell death assays and a RNA-seq analysis were performed in CBDCA-resistant A2780 cells.

Results

Microscopy on both parental and CBDCA-resistant A2780 cells showed similar characteristics in morphology and F-actin distribution within cells. In cell-death assays, parental A2780 cells showed a significant increase in phosphatidylserine translocation and caspase-3/7 cleavage compared to CBDCA-resistant A2780 cells (P < 0.05 and P < 0.005, respectively). Cell viability in parental A2780 cells was significantly decreased compared to CBDCA-resistant A2780 cells (P < 0.0005). The RNA-seq analysis showed 156 differentially expressed genes (DEGs) associated mainly to molecular functions.

Conclusion

CBDCA-resistant A2780 ovarian cancer cells is a reliable model of CBDCA resistance that shows several DEGs involved in molecular functions such as transmembrane activity, protein binding to cell surface receptor and catalytic activity. Also, we found that the Wnt/β-catenin and integrin signaling pathway are the main metabolic pathway dysregulated in CBDCA-resistant A2780 cells.

Electronic supplementary material

The online version of this article (10.1186/s40659-019-0220-0) contains supplementary material, which is available to authorized users.