Abstract
We systematically characterised multifactorial multidrug resistance (MDR) in CEM/ADR5000 cells, a doxorubicin-resistant sub-line derived from drug-sensitive, parental CCRF-CEM cells developed in vitro. RNA sequencing and network analyses (Ingenuity Pathway Analysis) were performed. Chromosomal aberrations were identified by array-comparative genomic hybridisation (aCGH) and multicolour fluorescence in situ hybridisation (mFISH). Fifteen ATP-binding cassette transporters and numerous new genes were overexpressed in CEM/ADR5000 cells. The basic karyotype in CCRF-CEM cells consisted of 47, XX, der(5)t(5;14) (q35.33;q32.3), del(9) (p14.1), +20. CEM/ADR5000 cells acquired additional aberrations, including X-chromosome loss, 4q and 14q deletion, chromosome 7 inversion, balanced and unbalanced two and three way translocations: t(3;10), der(3)t(3;13), der(5)t(18;5;14), t(10;16), der(18)t(7;18), der(18)t(21;18;5), der(21;21;18;5) and der(22)t(9;22). CCRF-CEM consisted of two and CEM/ADR5000 of five major sub-clones, indicating genetic tumor heterogeneity. Loss of 3q27.1 in CEM/ADR5000 caused down-regulation of ABCC5 and ABCF3 expression, Xq28 loss down-regulated ABCD1 expression. ABCB1, the most well-known MDR gene, was 448-fold up-regulated due to 7q21.12 amplification. In addition to well-known drug resistance genes, numerous novel genes and genomic aberrations were identified. Transcriptomics and genetics in CEM/AD5000 cells unravelled a range of MDR mechanisms, which is much more complex than estimated thus far. This may have important implications for future treatment strategies.
Introduction
Leukaemia constitutes a heterogeneous group of haematopoietic malignancies and can be categorised in four main types: acute myeloid leukaemia (AML), acute lymphoblastic leukaemia (ALL), chronic myeloid leukaemia (CML) and chronic lymphocytic leukaemia (CLL)1. ALL is referred as the most common paediatric oncological diagnosis2,3 and overall survival of ALL patients remains relatively poor with 20–40%4. In USA, leukaemia is the sixth leading cause of cancer associated death with incidences of 7.1 per 100,000 people per year and one of the main cause of death worldwide among children5.
Drugs accumulate in cancer cells by various mechanisms, such as diffusion, transport and endocytosis. Each of these mechanisms possesses physiological significance based on detailed uptake studies in drug-resistant mutants6. Main reasons of chemotherapy failure are drug resistance of tumour cells and the high susceptibility of normal tissues to treatment-related toxicity7,8,9. Important multidrug resistance mechanisms in cancer are apoptosis inhibition, DNA repair, drug efflux, altered drug metabolism and others6,10. Some immunotoxin-based anti-cancer drugs enter cells by receptor mediated endocytosis to kill tumour cells11. Vesicle trafficking, including the release of extracellular micro-vesicles, is critical in carcinogenesis, which involves invasion, metastasis, cell cycle regulation, angiogenesis, tumour immune privilege, neoplastic coagulopathy and multidrug resistance (MDR)12. Moreover, one study in eukaryotic cells pointed out that the balance between exocytosis and endocytosis is critical for generating the membrane domains recognized by sterol-targeting antibiotics, determining their efficacy13. Therefore, regulation of endocytosis and exocytosis may be considered as another mechanism of drug resistance.
In order to maximise the therapeutic benefit and minimise treatment-related toxicity, drug resistance phenomena should be better understood and the responsible mechanisms should be identified. For this purpose, gene expression profiling of different kinds of tumours needs to be investigated to unravel the multi-facetted nature of drug resistance in a more comprising manner.
Molecular cytogenetic studies provide an important approach to characterise drug resistance of tumours14. MDR is primarily mediated by P-glycoprotein, which acts as energy-dependent efflux pump to reduce intracellular drug concentrations15,16,17. In addition, random chromosomal rearrangements leading to capture and activation of ABCB1/MDR1 gene have been proposed as mechanism of MDR18.
RNA sequencing represents a powerful and sensitive method for gene expression profiling19,20,21. It has been used in combination with cytogenetic profiling to evaluate differential gene expression profiles and chromosomal aberrations in leukaemia cells22,23,24,25,26. Array-comparative genomic hybridisation (aCGH) and multicolour fluorescence in situ hybridisation (mFISH) techniques are valuable to detect genetic aberrations associated with the acquisition of drug resistance27,28. Such genetic aberrations provide clues about putative drug resistance genes in affected chromosomal regions. However, there is scarce information on the systematic analysis of MDR cells by parallel assessment of transcriptome-wide RNA sequencing and cytogenetic profiling by aCGH and mFISH.
While it is known that drug resistance can be multifactorial in nature, the full complexity of mechanisms and genetic alterations have been rarely addressed as of yet. In this study, we applied RNA sequencing, aCGH and mFISH to analyse drug sensitive parental CCRF-CEM and multidrug-resistant CEM/ADR5000 cells.
Results
Differential gene expression profile of CEM/ADR5000 cell line and downstream pathway analysis
The RNA sequencing data were analysed by considering RPKM (reads per kilobase of exon model per million mapped reads) values. Ratios of overall RPKM values for the expression of each gene in CEM/ADR5000 cells in comparison to that of CCRF-CEM were considered as fold change of gene expression. Firstly, setting a fold change threshold of ±1.5 yielded in 3,186 differentially expressed genes in CEM/ADR5000 cells. A threshold of ±3 resulted in 1,199 and a threshold of ±7 in 509 deregulated genes. Finally, if a fold change threshold of ±10 was applied, 369 deregulated genes were recorded. For further analysis, only the ±7 threshold was taken into account. Deregulated gene lists were used for downstream pathway analysis with Ingenuity Pathway Analysis (IPA) to identify affected pathways and networks in CEM/ADR5000 cells, if compared to CCRF-CEM cells. Downstream pathway and network analyses yielded similar results for ±7 and ±10 fold changes. Here, we show only the results for the ±7 fold change threshold. Three ATP-binding cassette (ABC) transporters (ABCA2, ABCB1 and ABCG2) were among the most up-regulated genes. They were 10.5-, 402.4-fold and 12.2-fold up-regulated, respectively, in CEM/ADR5000 cells in comparison to CCRF-CEM cells. Pathway and network analyses of deregulated genes in CEM/ADR5000 cells revealed connections to drug resistance and carcinogenesis, e.g. “cell death of leukaemia” and “apoptosis” pathways were inhibited, whereas the “transport of cyclosporine” network was predicted to be activated due to up-regulated ABCB1. The networks involving ABCB1 and ABCG2 are summarised in Fig. 1.
Several genes known to be involved in drug resistance were deregulated implying that CEM/ADR5000 cells exerts a multi-factorial resistance phenotype. If a fold change threshold of ±7.0 was applied, 7 out of 101 apoptosis-regulating genes (7%), 34 out of 726 kinases (5%) and 3 out of 48 ABC transporters (6%) were deregulated implying that genes from these gene classes may have an important influence on the MDR phenotype of CEM/ADR5000 cells. These genes are depicted in Table 1. A full list of all deregulated genes involved in resistance mechanisms is given in Supplementary Table 1.
Lipid metabolism, small molecule biochemistry, carbohydrate metabolism, drug metabolism, molecular transport, cancer, haematological disease, cellular development, cellular growth and proliferation, cell death and survival were identified by IPA as biological functions that involve ABCB1. A bar chart for the most affected biological functions and pathways is depicted in Fig. 2A,B.
Three genes involved in DNA repair were up-regulated in CEM/ADR5000 cells, which emphasises the role of DNA repair as important mechanism of drug resistance: NEIL2 was up-regulated by 22.35-fold, TEX15 by 10.52-fold.
Genes playing a role in membrane lipid metabolism via the ceramide pathway were down-regulated in CEM/ADR5000 cells. SMPD3 was down-regulated by 5.71-fold and ACER1 by 3.17-fold.
NQO1, which plays role in reactive oxygen species pathway and apoptosis regulation, is down-regulated by 3.57-fold in CEM/ADR5000 cells.
Functional enrichment analyses using the DAVID software pointed to various resistance related biological functions. “Leukocyte differentiation” (p = 7.4 × 10−5; fold-enrichment: 3.8), “regulation of exocytosis” (p = 2.3 × 10−3; fold-enrichment: 6.3), and “membrane organisation” (p = 2.4 × 10−3; fold-enrichment: 2.1). The results are summarised in Table 2.
The analysis of the drug resistance gene list of SABioscience (http://www.sabiosciences.com/ArrayList.php) revealed 9 down-regulated and 25 up-regulated genes, if fold change thresholds of ±7 were applied. The results are shown in Table 3. DNAJC15 (down-regulated by 499-fold), ABCB1 (up-regulated by 402-fold), PDLIM1 (upregulated by 270-fold), FZD7 (up-regulated by 161-fold) and CCND2 (up-regulated by 101-fold) were the most deregulated genes residing at drug resistance clusters.
Validation of the selected resistance genes were performed at the protein level for FOXO1 and NQO1. As shown in Fig. 3, FOXO1 was up-regulated, whereas NQO1 was down-regulated in CEM/ADR5000 cells, correlating with the RNA sequencing output and validating the RNA expression data at the protein level.
mFISH
CCRF-CEM cells revealed the following karyotype by mFISH: 47, XX, der(5)t(5;14) (q35.33;q32.3), t(8;9) (p12;p24), del(9) (p14.1), +20[85%]/46, X, -X, der(5)t(5;14) (q35.1;q32.3), del(9) (p14.1), +20[15%]. A deletion in the chromosomal region 9p and chromosome 20 trisomy were also confirmed by aCGH analysis.
CEM/ADR5000 cells showed a less stable profile with the following highly complex karyotype in clone 1, which represents about 19% of the cells; 47, X, -X, t(3;10) (q11.2 ~ 12;p14 ~ 15), der(3)t(3;13) (q26.32;q22.3), del(4) (q31.32q34.3), der(5)t(18;5;14) (18qter→18q21.2::5p12→5q35.33::14q32.3→14qter), inv(7) (p21.1q21.1), t(8;9) (p12;p24), del(9) (p14.1), t(10;16) (q23.31;q22 ~ 23), del(14) (q32.3), der(18)t(7;18) (p21;q21.2), der(18) (21qter→21q22.1::18p11.22→18q12.1::5p12→5pter), der(18) (21p?::21q22.3→21q22.1::18p11.22→18q12.1::5p12→5pter), +20, der(22)t(9;22) (q22.33;q13.33). Besides, there were four additional clones with the following genetic aberrations compared to clone 1:
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Clone 1a (20%) with an additional translocation t(6;14) (q26;q32.33);
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Clone 1b (26%) with a translocation between one chromosome 20 and a derivative chromosome der(10)t(3;10);
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Clone 1b1 (30%) with the same additional aberration as clone 1b and an additional translocation between a chromosome 17 and der(18) (21;18;5);
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Clone 1c (5%) with a translocation t(6;20;8) (q24;q11.2 ~ 1;q22.3 ~ 23) and loss of the derivative chromosome der(18) (21qter→21q22.1::18p11.22→18q12.1::5p12→5pter).
Deletion at chromosomal regions 3q and 9p, deletion and amplifications in chromosome 18, chromosome 20 trisomy and loss of one X chromosome were confirmed by aCGH analysis. The results for the mFISH analyses are summarised in Fig. 4.
mFISH analysis of CCRF-CEM and CEM/ADR5000 cells.
Two clones detected in CCRF-CEM are depicted in (A,B). All derivative chromosomes present in clones 1 and 2 are highlighted by light-green arrows. Individual changes for clones 1 and 2 are labelled by arrows in darker green. For derivative chromosome 5, a whole chromosome paint (wcp) and a subtelomeric (st) probe for 5qter were applied. For the derivative chromosome 8, a centromeric probe (D8Z1) and a st probe for 14qter had been used. In (4C) to F, CEM/ADR5000 clones 1, 1a, 1b, 1b1 and 1c are depicted. The per clone acquired alterations are highlighted by coloured arrows as explained in the legend between (4A/B) and C/D. For clear visualisation of the inversion in chromosome 7, MCB 7 was applied as shown in (4C). In (4C), the only additional aberration present in clone 1a is depicted, i.e. a reciprocal translocation between chromosomes 6 and 14.
The clonal evolution of CCRF-CEM and CEM/ADR5000 cells are summarised in Fig. 5 and detailed karyotypes of all subclones detected in this study are listed in Supplementary Table 2.
aCGH of CCRF-CEM cells
One deletion was located between 9p21.1 and 9p24.3 (28,466,044 bp) with 21 deregulated genes, 12 of which were down-regulated as shown by RNA sequencing. An amplification was detected between 20p11.1 and 20p13 (26,126,681 bp) carrying 22 deregulated genes. Of them, 11 were found by RNA sequencing to be up-regulated, including CD93 as highest up-regulated gene (29.9-fold). Another amplification was located between 20q11.21 and 20q13.33 (33,061,715 bp). This region harboured 67 deregulated genes, and 45 of them were found by RNA sequencing to be up-regulated. This amplification contained the MYH7B and C20orf197 genes with 10.8 and 9.7 fold upregulation, respectively. The results are summarised in Fig. 6 and Table 4. Deletions are represented in green and amplifications in red.
aCGH of CEM/ADR5000 cells
CEM/ADR5000 cells possessed considerably more deletions and amplifications than CCRF-CEM cells, indicating high selection pressure during resistance development. The corresponding chromosomal locations with amplifications and deletions were compared with those of the deregulated genes identified by RNA-sequencing. The aCGH results were corroborated by RNA sequencing results, since most deregulated genes were located within the chromosomal loci, which were identified to be amplified or deleted by aCGH. One deletion was detected between 1p36.31 and 1p36.32 (2,005,754 bp), and this region harboured six deregulated genes. Five of them were found by RNA sequencing to be down-regulated. Another deletion was detected between 3q26.32 and 3q29 (21,664,432 bp), and this region carried 72 deregulated genes. Of them, 68 were found by RNA sequencing to be down-regulated. A deletion within 3q27.1 caused down-regulation of ABCC5 and ABCF3 expression. ABCC5 mediates the ATP-dependent transport of various anticancer drugs, including doxorubicin29. Its expression in doxorubicin-resistant human lung cancer cells SBC-3/ADM, AdR MCF-7 and K562/ADM was higher compared to their respective parental cell lines30. Since ABCF3 resides at the same cyto-band with ABCC5, their expression might be regulated in a similar manner. However, ABCF3 is not known as MDR related drug transporter. Therefore, the ABCF3 linkage with doxorubicin resistance should not be over-interpreted.
Another deletion was detected between 4q31.23 and 4q34.3 (29,086,190 bp). This region harboured 33 deregulated genes, 30 of them were found by RNA sequencing to be down-regulated. One amplification was detected between 7p21.1 and 7p22.3 (16,468,962 bp). This region contained 36 deregulated genes, 31 of them were found by RNA sequencing to be up-regulated. Another amplification was located at 7q21.12 (182,792 bp). This region carried two deregulated genes with ABCB1 as the most up-regulated gene (402.4-fold). One deletion was found between 16p12.1 and 16p12.3 (6,639,549 bp) and this region involved 25 deregulated genes, 23 of which were found by RNA sequencing to be down-regulated. One deletion was detected between 18p11.22 and 18p11.32 (8,506,661 bp) and this region harboured 16 deregulated genes. All of them were found by RNA sequencing to be down-regulated. Deletion within Xq28 caused down-regulation of ABCD1 expression. The results are summarised in Fig. 7 and Table 4. Deleted regions are represented in green and amplified regions in red.
A complete list of deregulated genes in ADR/CEM5000 cells in comparison to CCRF-CEM cells is depicted in Supplementary Table 3. The corresponding chromosomal aberrations found by aCGH analyses are depicted in Supplementary Table 4.
Tumor evolution
Previously, we have already investigated the genetic aberrations of CCRF-CEM and CEM/ADR5000 cells by CGH and mFISH31,32,33. The intention of the present study was to directly compare RNA sequencing data with aCGH and mFISH results from cells harvested at the same time. Nevertheless, we were interested to compare the previous results published in the year 2002 with those of the present investigation. We took this as an opportunity to investigate the evolution of tumor cells over a time period of 14 years permanent culturing in vitro.
The present study is more detailed and differs from the previously performed CGH and mFISH analysis by us31,32,33 in terms of aberrations. As shown in Fig. 8, the number of chromosomal aberrations both in CCRF-CEM and CEM/ADR5000 increased compared to those studies performed in 2002. Figure 8A depicts the chromosomal aberrations found in the 2002 studies. Figure 8B depicts the chromosomal aberrations found in the present study. One possible explanation is genetic instability that leads to the tumour evolution phenomenon34,35. Our comparison revealed a considerable number of additional aberrations, which have been acquired over a time period of 14 years of permanent culturing in vitro. In the previous studies, we did not observe an aberration in 7q21, which is the region where the ABCB1 gene resides. In the present study, we could observe an amplification at this region. Chromosomes 7, 14 and 18 involved the majority of the aberrations, chromosome 14 carrying similar number of aberrations for CCRF-CEM and CEM/ADR5000 (three deletions and two amplifications at the former, four deletions and three amplifications at the latter). It can be hypothesised that chromosome 14 might be more prone to genetic instability. Aberrations at this chromosome might be relevant to resist the selection pressure to grow in vitro. It warrants more investigations in the future to explore, whether genes at these aberrant chromosomal loci are associated with tumor progression in patients.
Comparison of chromosomal aberrations analysed in CCRF-CEM and CEM/ADR5000 cells in the year 2002 (A) with the results of the present study (B). Each dot represents an aberration, green: deletion, red: amplification. Some of the deregulated drug resistance linked genes are marked on the plots for the CEM/ADR5000 cells observed in the present study.
Discussion
Leukaemia is among the most frequent tumours worldwide and the survival rates are still low. One reason is the development of drug resistance towards chemotherapy36. P-glycoprotein/ABCB1/MDR1 is an important determinant of MDR37,38,39. Previous functional studies regarding P-glycoprotein performed by us revealed that natural products targeting P-glycoprotein may serve as good candidate to reverse doxorubicin resistance in CEM/ADR5000 cells40. While there is a plethora of reports on single resistance mechanisms, studies focusing on the full complexity of all genetic changes in MDR cells and providing a comprising picture of potential drug resistance mechanisms are still rare.
Gene expression profiling and chromosomal aberration analyses are valuable strategies to identify the genome-wide characteristics of cancer cells. For this purpose, we performed gene expression profiling of multidrug-resistant CEM/ADR5000 and sensitive parental CCRF-CEM leukaemia cells by RNA sequencing and cytogenetic analyses by aCGH and mFISH. Remarkably, CEM/ADR5000 cells showed a less stable chromosomal karyotype with many additional chromosomal aberrations compared to CCRF-CEM cells. Deficiency in MLH1 and MSH2 mismatch repair genes might cause a high background mutation rate in CCRF-CEM cells41. This deficiency leads to telomere shortening as also observed in human fibroblasts42. The background mutation rate was further increased in CEM/ADR5000 cells under drug selection pressure. This led to an increased number of chromosomal aberrations in CEM/ADR5000 cells.
We compared our results with our previous studies in terms of chromosomal aberrations and observed that over a time period of 14 years, those cell lines accumulated additional aberrations. Increased numbers of aberrations on both cell lines might be due to tumour evolution and clonal diversity. One study with acute myeloid leukaemia cells also reported the accumulation of additional aberrations over time34. Pre-existing drug-resistant subclones might be a substantial contributor to therapeutic resistance in oncology43. It has been stated in the literature that sampling the tumour at different time-points might reveal genetic evolution or differences in the clonal composition of the tumour as the disease progresses44,45.
ABCB1/MDR1 was the most up-regulated gene in CEM/ADR5000 cells. It was also mapped to pathways and networks linked with MDR and cancer progression, e.g. “cell death of leukaemia cell lines”, “apoptosis” and “transport of cyclosporine”. Cyclosporine represents a well-known inhibitor of P-glycoprotein/ABCB146,47 and up-regulated P-glycoprotein/ABCB1 expression leads to increased cyclosporine efflux48. ABCB1 influenced a number of other biological functions and pathways, and PXR/RXR activation was among these pathways. This pathway is linked with the transport of xenobiotics and endogenous organic compounds49,50. Downstream pathway and network analyses clearly demonstrated that several drug resistance and cancer progression events were affected in CEM/ADR5000 cells. “Leukocyte differentiation” may be attributed to leukaemia progression, whereas “regulation of exocytosis” and “membrane organisation” may be associated with drug transport.
Several deregulated genes in CEM/ADR5000 are known to be involved in classical resistance mechanisms. DNA topoisomerases, apoptosis-regulating genes, kinases, ABC transporters and autophagy regulating genes were the most frequently influenced resistance mechanisms. Down-regulated DNA topoisomerase 2 has been linked with doxorubicin resistance51. Indeed, DNA topoisomerases 2A (TOP2A) and 2B (TOP2B) were 6.8- and 2.3-fold down-regulated in CEM/ADR5000 cells, respectively. Another study reported that doxorubicin resistant MCF-7 cells showed ABCB1 (24.0-fold), ABCG2 (15.8-fold), RXRA (4.4-fold), IGF1R (3.8-fold) up-regulation and TP53 (5.9-fold), MYC (5.3-fold), GSK3A (3.2-fold) down-regulation52. This is accordance with our results, since we found up-regulation of ABCB1 (402.4-fold), ABCG2 (12.2-fold), RXRA (4.4-fold), IGF1R (14.6 fold) and down-regulated TP53 (1.6-fold), MYC (1.9-fold), GSK3A (2.4-fold) in CEM/ADR5000 cells compared to CCRF-CEM cells.
Glutathione related enzymes represent another class of MDR mediating molecules53. Ten glutathione related genes were also deregulated in CEM/ADR5000 cells. Furthermore, apoptotic pathways caused drug resistance in doxorubicin resistant 8226/Dox6 myeloma cells54. In concordance with these findings, we observed that the pro-apoptotic genes encoding and caspase 8 were down-regulated by 2.5- and 1.6-fold, respectively, whereas the anti-apototic Bcl2L2 was up-regulated by 24.9-fold.
HMOX-1/HO-1 (71.7 fold up-regulated in CEM/ADR5000 cells) has been linked with doxorubicin resistance. HMOX-1 may be involved in drug resistance of breast cancer cells by preventing apoptosis and autophagy, since siRNA knockdown of HMOX-1 enhanced the cytotoxicity of doxorubicin in MDA-MB-231 and BT549 cells55,56. HMOX1 possesses anti-apoptotic activity in imatinib-resistant CML patients57. Inducing its expression via the PKC-β/p38-MAPK (mitogen activated protein kinase) pathway may promote resistance of tumour cells to oxidative stress57.
NQO1 (3.57-fold down-regulated in CEM/ADR5000 cells) plays role in reactive oxygen species pathway and apoptosis regulation. There are various studies pointing out its association with cancer. One study stated that overexpression and genomic gain of NQO1 locus modulated breast cancer cell sensitivity to quinones58. NQO1 protects cells from oxidative stress through inhibition of quinones from entering the one electron reduction to semiquinone free radicals and ROS (reactive oxygen species), therefore NQO1 is considered as an anticancer enzyme59,60. The use of dietary compounds to induce NQO1 expression has emerged as a promising strategy for cancer prevention by increasing efficacy of bioreductive anticancer drugs61,62.
NKX3-1 (2848.9-fold up-regulated in CEM/ADR5000 cells) transcriptionally regulates oxidative damage response and enhances topoisomerase I re-ligation. DNA damage induced by doxorubicin was negatively influenced by NKX3-1 expression63. Another study pointed out that IGF1R (14.6-up-regulated in CEM/ADR5000 cells) enhanced the cytotoxicity of doxorubicin in both sensitive and resistant osteosarcoma cells64.
PRKCA is another gene associated with drug resistance in ovarian cancer cells65,66, colon cancer cells67, and pancreatic cancer cells68. Up-regulation in CEM/ADR5000 cells indicates that this gene also contributes to the MDR phenotype of leukaemia cells. PRKCA (70.9-fold up-regulated in CEM/ADR5000 cells) phosphorylates and modulates the activity of a doxorubicin transporter, RLIP76. Inhibition of PRKCA and RLIP76 resulted in a synergistic increase of doxorubicin sensitivity69.
TRPV6 has been reported as pro-apoptotic gene in small cell lung cancer cells treated with capsaicin70. Its 7.13-fold down-regulation in CEM/ADR5000 cells indicates that it may also contribute to the MDR phenotype of leukaemia.
In total, 37 apoptosis-regulating genes (37% of all apoptosis-regulating genes) were deregulated. Genes involved in other modes of cell death such as autophagy, ferroptosis and necrosis may also contribute to MDR. Twenty-nine percent of autophagy regulating genes were deregulated in CEM/ADR5000 cells, whereas 17% of necrosis or ferroptosis regulating genes were deregulated. This implies that multiple cell death mechanisms may contribute to the MDR phenotype of CEM/ADR5000 cells. Kinases comprise another class of proteins related to drug resistance71,72. A total of 242 kinases (33% of all kinases) were deregulated, implying a role for MDR of CEM/ADR5000 cells.
Using the SABioscience PCR array list of drug resistance genes (http://www.sabiosciences.com/ArrayList.php) we showed that 9 genes were down-regulated and 25 up-regulated in CEM/ADR5000 cells as observed by RNA sequencing. PDLIM1 was 270.42-fold up-regulated in CEM/ADR5000 cells. This gene promotes carcinogenesis73. CYP27B1, which was 13.23-fold up-regulated in CEM/ADR5000 cells, is important for drug metabolism74. BNIP3 plays role in oxidative stress75 and was 10.41-fold up-regulated in our resistant cell line. TCF7 is an anti-apoptotic gene76 and was 17.66-fold down-regulated. SLC2A3 plays a role in carcinogenesis77 and was 13.64-fold up-regulated in CEM/ADR5000 cells.
DNA repair was also associated with the MDR phenotype of CEM/ADR5000 cells. Three DNA repair genes were up-regulated, i.e. NEIL278,79 by 22.35-fold, TEX1580 by 10.52-fold. Membrane lipid metabolism also contributes to drug resistance81,82. Two genes playing a role in this metabolic pathway revealed differential expression in CEM/ADR5000 cells. Ceramide is a lipid second messenger, which is synthesised de novo or generated from the hydrolysis of sphingomyelin by sphingomyelinases. Ceramide triggers signal transduction pathways in response to cytokines or extrinsic cellular stresses, leading to a variety of cellular responses, including growth suppression and apoptosis83. SMPD3 plays role in ceramide pathway. It is down-regulated and mutated in many leukaemia cells84. It was down-regulated by 5.71-fold in CEM/ADR5000 cells, implying a possible role of the ceramide pathway for the MDR phenotype of CEM/ADR5000 cells. Another down-regulated gene of the ceramide pathway was ACER1 (3.17-fold). It has anti-proliferating and pro-differentiating functions by controlling the generation of sphingosine and/or sphingosine-1-phosphate85. Down-regulation of ACER1 implies that CEM/ADR5000 cells may resist the anti-proliferative activity of ACER1 better than CCRF-CEM cells.
By using mFISH, we identified novel chromosomal breakpoints in CEM/ADR5000 cells that were not present in parental CCRF-CEM cells, e.g. 3q11.2 ~ 12, 3q26.32, 4q31.32, 4q34.3, 5p12, 6q26, 7p21.1, 7q21.1, 9q22.33, 10p14 ~ 15, 10q23.31, 13q22.3, 14q32.33, 16q22 ~ 23, 17q22, 18p11.22, 18q12.1, 18q21.2, 20p11.2, 21q22.1, 21q22.3, and 22q13.33.
4q31-32 has been described as chromosomal locus of a tumour suppressor gene in renal cell carcinoma86. The breakpoint at that region may cause loss of this tumour suppressor gene. Amplification of 6q25-27 has been previously associated with platinum resistance in ovarian carcinoma cell lines87. Amplification of 7q21.1 as well as chromosomal breaks at this region cause the over-expression of MDR1/ABCB1. Over-expression of the MDR1 gene product, P-glycoprotein, has been associated with abnormalities of chromosome 7, e.g. monosomy 7 or 7q8 and 7q9 deletions88. Deletion of 10p14-15 has been described in prostate cancer, gliomas and cervical cancer87,89,90. The 10p14-15 break in CEM/ADR5000 cells indicates that this aberration may be critical for leukaemia as well. PTEN deletions identified in human prostate cancer suggest unusual genomic features in 10q23.31, which facilitates DNA rearrangements91. 14q32.33 amplifications have been observed in platinum-resistant patients, and these amplifications might be a predictive marker of treatment outcome92. Loss of 16q was previously correlated with good prognosis in retinoblastoma93, supporting the hypothesis that there genes located at 16q22 ~ 23 may be related to cisplatin resistance94. 16q22.2 has been linked with increased frequency of loss in drug-resistant serous ovarian carcinoma compared to sensitive ones95. The identification of these chromosomal aberrations in our analyses indicates that they are not only relevant for leukaemia too, but also that they may contribute to the MDR phenotype.
By means of aCGH, karyotypic evolution of the cell lines could be detected. The karyotypic subclones of the two cell lines were detected. These subclones were the result of tumour evolution leading to tumour heterogeneity. Genetic alterations in cellular subpopulations allow tumours to better adapt to external selection pressure such as hypoxia, nutritional starvation, and also chemotherapy. Even if chemotherapy would be able to kill the vast majority of tumour cells, few surviving cells of a genetically distinct subclone may repopulate the entire tumour, which ultimately may lead to treatment failure and death of the patient. Therefore, tumour heterogeneity has to be understood as important genetically regulated phenomenon of drug resistance. Our analysis demonstrated that tumour cell heterogeneity is also associated with the MDR phenotype.
Analysing the observed breakpoints, candidate genes may be identified involved in drug resistance, even though point mutations also might play a role–an aspect which cannot be addressed by aGCH and mFISH technologies and which was, therefore, not considered in this study.
In conclusion, the genotypes and gene expression profiles of CCRF-CEM and CEM/ADR5000 leukaemia cell lines were analysed by RNA sequencing, aCGH, and mFISH in a comparative manner. CEM/ADR5000 cells possess an MDR phenotype, which reaches a degree of complexity far higher than estimated in the past for other MDR cell lines. Numerous chromosomal aberrations, deletions, and amplifications associated with the MDR phenotype have been detected. By using RNA sequencing, it was possible to detect gene expression changes with non-precedent preciseness. In addition to known classical drug resistance genes, many new genes were found to be differentially regulated in MDR cells. This study is of high importance for the future development of more specific and promising anti-cancer strategies against leukaemia.
Materials and Methods
Cell culture
CCRF-CEM cells were isolated from peripheral blood of a child with ALL96. Multidrug-resistant, P-glycoprotein over-expressing CEM/ADR5000 cells were derived from CCRF-CEM cells by continuous treatment with doxorubicin up to a concentration of 5,000 ng/mL97. These cells were generously provided by Prof. Axel Sauerbrey (Department of Pediatrics, University of Jena, Jena, Germany). The cell lines were authenticated using Multiplex Cell Authentication (MCA) based on single nucleotide polymorphism profiling by Multiplexion GmbH (Heidelberg, Germany) as recently described98. Those cell lines have been in culture for over a time period of 14 years.
RNA sequencing
CCRF-CEM cells and CEM/ADR5000 cells were used. Total RNA isolation was performed with InviTrap Spin Universal RNA Mini Kit (Stratec, Birkenfeld, Germany). Total RNA quality and quantity were evaluated using an Agilent Bioanalyser 2100 and Qubit Fluorometer (Life Technologies, Darmstadt, Germany). Poly A+ RNA was isolated, fractionated and double-stranded cDNA was synthesised using the TruSeq RNA sample prep v2 protocol (Illumina Inc., San Diego, CA). End-repaired, A-tailed and adaptor-ligated cDNA was PCR-amplified by 10 cycles. The library was sequenced in paired-end mode (2 × 100 bp) using 0.4 lane of an Illumina HiSeq 2000 flowcell. Gene expressions were quantified using the RPKM measure25,99. RPKM values for transcripts and the ratios of transcripts were taken into consideration to calculate the overall RPKM value for each gene. The deregulation of genes in CEM/ADR5000 cells was calculated by dividing overall RPKM values of genes in CEM/ADR5000 cells by those in CCRF-CEM cells. Chromosomal locations of deregulated genes were retrieved from UCSC Table Browser (https://genome.ucsc.edu/cgi-bin/hgTables). Genes involved in classical drug resistance mechanisms (ABC transporters, apoptosis, autophagy, CYP enzymes, DNA repair, ferroptosis, glutathione related enzymes, heat shock proteins, kinases, necroptosis, oxidative stress, receptors, topoisomerases and transcription factors) were retrieved from HUGO database100 and the literature to categorize the deregulated genes in resistance classes.
Pathway and network analysis
Fold change in RNA expression of ±7 were applied for filtering and then subjected to Ingenuity Pathway Analysis (QIAGEN Redwood City, USA, www.qiagen.com/ingenuity) to identify specific networks and pathways in CEM/ADR5000 cells. Functional gene enrichment analyses were performed with the DAVID software101,102,103. SABiosciences PCR array (Qiagen, http://www.sabiosciences.com/ArrayList.php?pline=PCRArray) is another useful tool classifying genes in functional clusters. The genes residing in the following clusters were taken into account: cancer drug resistance, DNA damage signalling pathway, DNA repair, drug metabolism, drug metabolism phase I, drug metabolism phase II, drug transporters, heat shock proteins, oncogenes and tumour suppressors, oxidative stress, stem cell, transcription factors, Wnt signalling pathway.
mFISH
CCRF-CEM and CEM/ADR5000 cells were cytogenetically prepared to obtain metaphase spreads and analysed using molecular cytogenetics as previously reported104. As probes, we used all 24 human whole chromosome paints in one experiment as previously reported105 as well as human multicolour banding106 probes as mentioned in Table 5. Additionally, partial chromosome paint (PCP), centromeric (CEP) or commercially available locus specific (LSI) probes were applied to verify or refine some of the multicolour FISH results, whole chromosome paint (WCP).
aCGH
Whole genomic DNA was extracted from CCRF-CEM and CEM/ADR5000 cells with QIAmp DNA mini kit (QIAGEN GmbH, Hilden, Germany). aCGH was done as previously reported107.
Western blotting
The protein expression levels of selected resistance genes, FOXO1 and NQO1 were evaluated in CCRF-CEM and CEM/ADR5000 cells to validate their deregulation found by RNA sequencing analysis. Protein isolation was performed using mPER protein extraction reagent (Invitrogen, Darmstadt, Germany) supplemented with protease inhibitor cocktail (Roche Diagnostics, Mannheim, Germany) according to the manufacturer’s recommendations. Concentrations of proteins were determined using NanoDrop1000 (PEQLAB, Erlangen, Germany). Overnight incubation at 4 °C with primary antibodies at a dilution of 1:1000 (anti- FOXO1-rabbit, anti-NQO1-mouse) or 1:2000 (anti-β-actin-rabbit) (New England Biolabs, Frankfurt, Germany) and then 2 h incubation at room temperature with HRP-linked secondary anti-rabbit or anti-mouse IgG antibody (1:2000 dilution) was performed. Detection was done with Luminata Classico HRP Western Blot substrate (Merck Millipore, Schwalbach, Germany).
Additional Information
How to cite this article: Kadioglu, O. et al. Genomic and transcriptomic profiling of resistant CEM/ADR-5000 and sensitive CCRF-CEM leukaemia cells for unraveling the full complexity of multi-factorial multidrug resistance. Sci. Rep. 6, 36754; doi: 10.1038/srep36754 (2016).
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Contributions
O.K. and J.C. performed the RNA sequencing data analysis. N.K., K.M. and T.L. performed the mFISH and aCGH analysis. O.K. and J.C. prepared Figures 1 and 2. O.K. prepared Tables 1–4 and Supplementary Tables 1,3,4. N.K., K.M. and T.L. prepared Figures 3–6, Table 5 and Supplementary Table 2. O.K. and T.E. wrote the main manuscript text. T.E. designed and supervised the project. All authors reviewed the manuscript.
Gene networks influenced by ABCB1 and ABCG2 in CEM/ADR5000 cells.
IPA software was used to depict the networks. Genes that are labelled in green were down-regulated and genes that are labelled in red were up-regulated. The lower panel depicts ABCB1 and ABCG2 playing role in “cell death of leukaemia cell lines” and “apoptosis” inhibition as shown by blue dotted lines. ABCB1 up-regulation is predicted to activate “transport of cyclosporine A” as shown by the orange dotted line.
(A) Biological function of differentially expressed genes in CEM/ADR5000 cells in comparison to wild-type CCRF-CEM cells as determined by IPA software. The orange line depicts the statistical significance threshold (p = 0.05). (B) Signaling pathways of differentially expressed genes in CEM/ADR5000 cells in comparison to wild-type CCRF-CEM cells as determined by IPA software. The orange line depicts the statistical significance threshold (p = 0.05) and the orange chart depicts the ratio of deregulated genes in each pathway.
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Kadioglu, O., Cao, J., Kosyakova, N. et al. Genomic and transcriptomic profiling of resistant CEM/ADR-5000 and sensitive CCRF-CEM leukaemia cells for unravelling the full complexity of multi-factorial multidrug resistance. Sci Rep 6, 36754 (2016). https://doi.org/10.1038/srep36754
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DOI: https://doi.org/10.1038/srep36754
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