This article has Open Peer Review reports available.
Primary effect of chemotherapy on the transcription profile of AIDS-related Kaposi's sarcoma
© van der Kuyl et al; licensee BioMed Central Ltd. 2002
Received: 18 June 2002
Accepted: 2 September 2002
Published: 2 September 2002
Drugs & used in anticancer chemotherapy have severe effects upon the cellular transcription and replication machinery. From in vitro studies it has become clear that these drugs can affect specific genes, as well as have an effect upon the total transcriptome.
Total mRNA from two skin lesions from a single AIDS-KS patient was analyzed with the SAGE (Serial Analysis of Gene Expression) technique to assess changes in the transcriptome induced by chemotherapy. SAGE libraries were constructed from material obtained 24 (KS-24) and 48 (KS-48) hrs after combination therapy with bleomycin, doxorubicin and vincristine. KS-24 and KS-48 were compared to SAGE libraries of untreated AIDS-KS, and to libraries generated from normal skin and from isolated CD4+ T-cells, using the programs USAGE and HTM. SAGE libraries were also compared with the SAGEmap database.
In order to assess the primary response of AIDS-related Kaposi's sarcoma (AIDS-KS) to chemotherapy in vivo, we analyzed the transcriptome of AIDS-KS skin lesions from a HIV-1 seropositive patient at two time points after therapy. The mRNA profile was found to have changed dramatically within 24 hours after drug treatment. There was an almost complete absence of transcripts highly expressed in AIDS-KS, probably due to a transcription block. Analysis of KS-24 suggested that mRNA pool used in its construction originated from poly(A) binding protein (PABP) mRNP complexes, which are probably located in nuclear structures known as interchromatin granule clusters (IGCs). IGCs are known to fuse after transcription inhibition, probably affecting poly(A)+RNA distribution.
Forty-eight hours after chemotherapy, mRNA isolated from the lesion was largely derived from infiltrating lymphocytes, confirming the transcriptional block in the AIDS-KS tissue.
These in vivo findings indicate that the effect of anti-cancer drugs is likely to be more global than up- or downregulation of specific genes, at least in this single patient with AIDS-KS. The SAGE results obtained 24 hrs after chemotherapy can be most plausibly explained by the isolation of a fraction of more stable poly(A)+RNA.
Existing anti-cancer drugs are generally seen as non-specific anti-mitotic agents, inducing apoptosis in all rapidly dividing cells by interfering with DNA replication and the cell cycle. Distinct combinations of chemotherapeutic agents have been found empirically to be beneficial treating different types of cancer. E.g. bleomycin is used to treat squamous cell carcinoma, lymphomas, and testicular tumors, while doxorubicin (Adriamycin™) is used to combat acute lymphoblastic and myeloblastic leukemia, Wilms' tumor, soft tissue and osteogenic sarcomas, neuroblastoma, cancer of the breast, ovaries, lungs, bladder, and thyroid, lymphomas, bronchogenic and gastric carcinoma, and Kaposi's sarcoma. Vinca alkaloids (vinblastine, vincristine and vindesine) are used in the treatment a wide variety of tumors including lymphomas, breast cancer, Kaposi's sarcoma, testicular cancer, leukemia and neuroblastoma. To treat AIDS-KS, a cocktail of doxorubicin, bleomycin and vincristine is at present a widely used chemotherapy.
Anti-cancer drugs have been shown to inhibit cell cycle progression by interfering with microtubule formation and DNA replication, and to induce apoptosis probably through DNA damage. In vitro studies have elucidated some aspects of how this is achieved. Micro-array analysis has indicated that anticancer drugs could be clustered according to the specific gene expression pattern they induced in cultured cells, with drugs with a same known mode of action generating a similar change in mRNA levels . Vinca alkaloids are known to interfere with microtubule formation at the protein level, resulting in G2/M phase arrest, inhibition of cell proliferation and apoptosis . Doxorubicin also induces cell-cycle arrest at the G2/M checkpoint  and induces apoptosis, probably by directly intercalating into double-stranded DNA , or by forming drug-DNA adducts, which also prevents DNA replication . Doxorubicin can effectively chelate Fe3+, and subsequently cleave DNA through the production of hydroxyl radicals [6–9]. It was also shown that doxorubicin can inhibit RNA polymerase II , and the helicase activity of the RNA helicase II/Gu-protein complex, probably by binding to its RNA substrates . However, all these effects were seen in vitro at relatively high concentrations of the drug. At plasma concentrations, the main action of doxorubicin is probably inhibition of topoisomerase II , although helicase inhibition could also be achieved with clinically relevant concentrations. Gene expression profiling clustered doxorubicin with the topoisomerase II inhibitors . Bleomycin has been shown to induce G2 block , inhibit DNA  and RNA synthesis , and induce apoptosis . In addition, bleomycin mediates the degradation of DNA [17, 18], especially of active chromatin , and of all classes of cellular mRNAs . In vitro, bleomycin upregulates alpha 1 (I) collagen, fibronectin and decorin mRNAs  and connective tissue growth factor mRNA , in line with its capability to induce pulmonary fibrosis as a side-effect.
Analysis of the complete transcriptome (all mRNAs present in a cell) has been shown to be a powerful way of detecting genes specifically expressed, or up/down-regulated under certain conditions. The most widely used methods used for large-scale gene expression analysis today are micro-arrays and SAGE . One important difference between these methods is that on micro-arrays internal fragments of a transcript are essential for positive identification, while with SAGE only 3' ends of transcripts are captured, and a transcript is identified by a 14 nucleotide stretch at its 3' end. Both methods have been used already on a large variety of tissues, cells, and cell cultures. Cancer tissue from patients was used in several SAGE studies (see e.g. [24–26]), but the short-term effect of chemotherapy on overall gene expression has not been studied to date.
To examine the effect of chemotherapy on gene expression profiles in vivo, we performed SAGE on two AIDS-KS tissue samples taken from a single patient, 24 and 48 hrs after treatment with a cocktail of doxorubicin, bleomycin, and vincristine. These two SAGE libraries were compared with SAGE libraries derived from tumor tissue from two untreated AIDS-KS patients, a SAGE library generated from normal skin, and with a SAGE library from isolated CD45+CD4+ T-cells.
Kaposi's sarcoma (KS), a relatively rare disease, is now encountered more often in HIV-infected homosexual men. Characteristic for KS are proliferating spindle-shaped cells, inflammatory cell infiltration, and profound angiogenesis. Two viruses play a role in AIDS-KS: human immunodeficiency virus (HIV), and human herpesvirus 8 (HHV8, also known as Kaposi's Sarcoma-associated Herpes Virus, KSHV). Immune suppression by HIV could be a mechanism facilitating HHV8 replication, with the HHV8 genome containing many genes able to deregulate the cell cycle such as chemokines, growth factors, a G-coupled receptor, cyclins and anti-apoptotic genes (for a review see: ). HHV8 can infect a variety of cells, including B cells, vascular endothelial cells, keratinocytes, monocytes, and macrophages [28–31]. It also is involved in two other types of cancer: primary effusion lymphoma (a B-cell lymphoma) , and multicentric Castleman's disease .
SAGE library characteristics
Two SAGE libraries were constructed from treated AIDS-KS tissue. A total of 47,298 tags were sequenced from the SAGE library obtained 24 hrs after the start of the first course of chemotherapy (library KS-24), while 46,671 tags were sequenced from the SAGE library derived from a tumor biopsy taken 48 hrs after treatment (KS-48). Library characteristics are summarized in Table 1. Characteristics for the control libraries from untreated AIDS-KS (KSa and KSb), normal skin (NS), and CD4+ T cells (CD4) are also presented in Table 1. Tag frequencies are very similar for all six SAGE libraries, but the libraries KS-24 and KS-48 generated from the drug-treated material show a higher number of tags that appear only once. Also, the amount of unique tags is higher in KS-24, KS-48 and CD4 compared to KSa, KSb and NS. More tags are differentially expressed tags between library KS-24 and the other three AIDS-KS libraries (Table 2). Statistical correlation analysis was performed using all six SAGE libraries in pair-wise comparisons. Pearson correlation coefficients were calculated for each comparison (Table 3). The two untreated KS libraries have a correlation coefficient of 0.83, indicating a high level of similarity. Surprisingly, the SAGE library obtained 48 hrs after chemotherapy, KS-48, shows a high correlation coefficient of 0.92 with SAGE library CD4, suggesting that mRNA isolated from this biopsy is mainly derived from infiltrating T-cells. Histological analysis of the paraffin embedded tissue of KS-24 and KS-48 with anti-CD3 antibodies showed at least a two-fold increase of the amount of T-cells in KS-48 compared with KS-24 (result not shown). Library KS-24 has the lowest correlation coefficients observed with both untreated AIDS-KS libraries (0.38 and 0.37, respectively), suggesting that the RNA pool isolated after chemotherapy is significantly different from that in untreated AIDS-KS. Hierarchical clustering performed with the program Cluster using the Average Linkage Clustering option, and all tag counts that appear at least twice in at least one of the SAGE libraries, confirmed that the expression pattern of KS-24 is greatly different from that of the other libraries (Fig. 2). KS-48 clusters with library CD4 in this tree, in line with the high correlation coefficient of the two libraries.
Frequency distribution of tag counts in the four KS and control SAGE libraries
= 25 – 75
= 5 – 24
= 2 – 4
Transcripts differentially expressed between the four KS SAGE a
Pearson correlation coefficients obtained from variation analysis of the six SAGE libraries
Highest tag counts in KS-24
Twenty-five most frequent tags from SAGE library KS-24
Mt 16S rRNA
Mt 16S rRNA
Mt NADH-dehydrogenase subunit 4L
Mt ATP-synthase 6 and 8
Tumor protein, translationally controlled 1
Peptidylprolyl isomerase A (Cyclophilin A)
RP large P2
Tubulin, alpha, ubiquitous
Mt 16S rRNA
Effect of chemotherapy after 24 hrs: disappearance of KS tags
Transcription profile of untreated AIDS-KS compared with KS-24 and normal skin (NS) a
Collagen, type IV, α1
MHC, class I C
Heme oxygenase (decyling) 1
Complement component 1q subcomponent α peptide
Tissue inhibitor of metalloproteinase, collagenase inhibitor (TIMP)
Lysosomal-associated multispanning membrane protein 5
Cartilage oligomeric matrix protein
Cytochrome b-245, α polypeptide
ATX1 (antioxidant protein1)
H2A histone family member
Ribosomal protein L15
Interferon induced transmembrane protein 2 (1-8D)
Heat shock 90 kD protein1, beta
Phospholipid transfer protein
Thy-1 cell surface antigen
Glutamate-ammonia ligase, glutamine synthase
S100 calcium binding protein A7 (Psoriasin)
Collagen type VI α3
S100 calcium binding protein A9 (Calgranulin)
16,7 Kd protein
No reliable matches
Endothelial differentiation-related factor 1
Thioredoxin interacting protein
Lysyl oxidase-like 2
In general, classes of genes whose expression was absent or significantly decreased in KS-24 included cytokines, chemokines, collagens, keratins, S100 calcium-binding proteins, MHC components, and integrins (not shown). Elevated tag counts (> 3-fold increase) include those for seven ribosomal proteins (S25, large P1, L7, S29, L37, S27a, L23), glutaminyl tRNA-synthetase, transcription factors, translation initiation/elongation factors (including cyclin T), poly(A) binding proteins, cyclins (B1, B2, D3), and four tags representing parts of the T-cell receptor (β chain, CD3D antigen delta polypeptide, CD3G antigen gamma peptide, CD3Z antigen zeta polypeptide). No tags were detected for the α-chain of the T-cell receptor. In the CD4 library, tags for the α-chain were found, but not for the β chain, or any other component of the CD3 antigen.
Effect of chemotherapy: decrease of nuclear rRNA but not mitochondrial rRNA tags
Tag counts derived from ribosomal RNAs in the six SAGE libraries a
Mt 12S (3 tags)
Mt 16S (4 tags)
1378 (2.91 %)
18S (8 tags)
28S (8 tags)
Total nuclear b
Increase in tags containing poly(A) sequences in KS-24
Frequency of tags ending with multiple A-nucleotides in the AIDS-KS and control SAGE libraries a
Poly(A) binding protein tags in the AIDS-KS and control SAGE libraries a
Poly(A) binding protein,
nuclear 1 (PABP2) Hs 117176
Poly(A) binding protein,
cytoplasmic 1 (PABP1) Hs 172182
SAGE is a widely used technique to analyze the transcriptome of cells and tissues. Here, we have studied mRNA populations expressed in AIDS-KS tissue of a single patient, 24 and 48 hrs after chemotherapy with a cocktail of doxorubicin, bleomycin and vincristine (libraries KS-24 and KS-48, respectively), and compared them with SAGE libraries generated from similar tissue of two untreated patients (libraries KSa and KSb). Resistance to the chemotherapy was not observed, as the patient already improved upon the first treatment, and all KS lesions finally resolved after five courses. All three anti-cancer drugs are able to induce cell cycle arrest and apoptosis in proliferating cells through damage of the DNA. Inhibition of DNA replication and RNA transcription are other common effects. In vitro investigations show that the drugs are capable of up/down regulating specific genes [21, 34, 36–38].
The tag counts of the four libraries ranged from 46,671 – 49,335 tags. Libraries KS-24 and KS-48 had slightly higher unique tag counts than KSa and KSb (~20,000 versus ~16,500). Tag frequencies were similar between the four libraries, albeit that KS-24 and KS-48 contained more single tags than the other two libraries (~15,500 versus ~11,500). So, from the general characteristics of the SAGE libraries, chemotherapy does not seem to create significant problems when constructing a SAGE library. Comparing relationships based on gene expression profiles, libraries KS-48, KSa, and KSb were more closely related to each other than to KS-24. However, correlation analysis showed that library KS-48 was almost identical to a library generated from CD4 T-cells, suggesting that the RNA extracted from the KS-48 tissue is derived from tumor infiltrating T-cells, possibly because the AIDS-KS cells are still suffering from cell cycle arrest at this time-point. In paclitaxel-treated breast cancer patients, the attraction of tumor infiltrating lymphocytes (TILs) after treatment, probably resulting from drug-induced apoptosis, was found to be an indicator of favorable outcome . In the patient described in this paper, a good response to chemotherapy and a complete recovery from AIDS-KS was observed, suggesting that the development of TILs after chemotherapy is also a predictor of clinical response in AIDS-KS. Most likely, these infiltrating lymphocytes are CD8+ T-cells, allowing for the slight discrepancy between the KS-48 and CD4 SAGE libraries (Pearson correlation coefficient = 0.92).
The significant divergence of library KS-24 suggests a major impact of chemotherapy on the cellular transcriptome, in line with earlier experiments . In summary, the main results from SAGE analysis of anti-cancer drug-treated tissue were: 1. Transcripts found to be highly and specifically expressed in AIDS-KS were lacking or low, 2. Nuclear ribosomal RNA levels have declined, and 3. mRNAs with long(er) poly(A)-tails were abundant. Results 1 and 2 are likely to be due to inhibition of transcription, and subsequent degradation of RNA. Lam et al., analyzing the transcriptional effect of several anti-cancer drugs on micro-arrays, found that transcriptionally inducible genes often have short half-lives of less than 4 hrs. The major classes of unstable transcripts include those encoding cytokines, chemokines, and apoptosis- and cell cycle regulators. Thus, 24 hrs after drug-treatment, resulting in repression of de novo transcription, most unstable transcripts likely have disappeared from the cells. Doxorubicin treatment of cells in vitro results in a complete shut down of transcription, possibly because doxorubicin inhibits the activity of RNA polymerase II . Topoisomerase II inhibition by doxorubicin could explain the severe effects of this drug on RNA polymerase I and -III promoters . Most likely, the transcripts found to be highly expressed in AIDS-KS, which include collagens, keratins, S100 calcium-binding proteins, MHC components, and integrins, have relatively short half-lives, and are thus no longer present in KS-24.
Another factor likely to distort the mRNA profile after anti-cancer drug-treatment is the ability of chemotherapeutic agents to inhibit cell cycle progression at a certain point. Analyzing the pattern of gene expression during the cell cycle, oscillation of many mRNAs, including genes known to be involved in cell cycle control, was detected . Earlier reports indicated that the three drugs administered to the patient analyzed here all block cells in late G2, just before start of mitosis. Genes expressed at high levels during G2 in the mouse include cyclin B1, and cdc20 (see also ), both of which are elevated in KS-24. In line with this, doxorubicin was found to induce cyclin B1 accumulation in cell cultures [49, 50]. Cyclin B1 tags are approximately 5-fold induced in KS-24, tags for cdc20 are absent from all libraries except KS-24, which contains 9 tags /50.000. Increased tags for cyclin B2 (4 tags/50.000 in KS-24, none in the other libraries) also point at inhibition at the G2/M boundary in KS-24. Cyclin D3 tags are elevated in KS-24, but cyclin D3 is not cell cycle regulated and its concentration depends upon the growth rate of the cell. During mitosis there is no significant transcription, resulting in a reduction of poly(A)+ RNA and protein synthesis. It is possible that a large number of mRNAs, including those for the PABP's themselves, are before this stage assembled into complexes, to have them ready for translation at the next phase of the cell cycle. If this is true, the observation of an increase in PABP-bound mRNAs in KS-24 could be directly associated to cancer cells being blocked at the G2/M transition. Poly(A) polymerase (PAP) activity is cell cycle regulated, with enzyme activity being low during mitosis .
Analysis of gene expression patterns in vivo after anticancer drug treatment in AIDS-KS suggest that the RNA profile is dramatically influenced by the extraction of subsets of mRNA present in mRNP complexes, as well as by a block in transcription, resulting in differences in stability of individual mRNAs becoming highly important. Cell cycle effects are also likely to be important, as the expression of many genes fluctuates with the phase of the cell cycle. The findings reported here oppose the common idea that the main effect of chemotherapy is found in the specific up- or downregulation of gene expression, whereby the genes found to be affected play an important role in the reaction of the cell upon the anti-cancer drug. This could be an effect at low concentrations, but is unlikely to be the main effect of chemotherapeutic agents at effective plasma levels.
Analysis of gene expression patterns in vivo after anticancer drug treatment in AIDS-KS suggest that the RNA profile is dramatically influenced by the extraction of subsets of mRNA present in mRNP complexes, as well as by a block in transcription, resulting in differences in stability of individual mRNAs becoming highly important. Cell cycle effects are also likely to be important, as the expression of many genes fluctuates with the phase of the cell cycle. The findings reported here, although be it in a single patient, oppose the common idea that the main effect of chemotherapy is found in the specific up- or downregulation of gene expression, whereby the genes found to be affected play an important role in the reaction of the cell upon the anti-cancer drug. This could be a possible effect at low concentrations, but is unlikely to be the main effect of chemotherapeutic agents at effective plasma levels.
A 31-year old man was demonstrated to be HIV-1 seropositive in February 1997. The initial CD4 cell count was 25 × 106/ l. The patient presented within two months a mucocutaneous Herpes simplex infection and an extrapulmonary Cryptococcosis for which specific medication was given. The HIV-1 RNA load at presentation was 15,000 copies/ml and increased to 33,000 copies/ml in three months. Then antiretroviral therapy was started with zidovudine, lamivudine and indinavir. After 4 weeks of treatment his plasma HIV-1 copy number had declined to below the assay detection limit (1000 copies/ml). Six months later the patient presented with gradual appearance of an increasing number of violaceous skin lesions in the perianal region and on the face that clinically resembled KS. The diagnosis was confirmed by histological examination of one of the lesions. A serum sample taken earlier was found to be positive for HHV8 antibody. In view of the rapidly progressive and extensive nature of the disease, systemic chemotherapy with bleomycin (15 mg), vincristine (2 mg) and doxorubicin (10 mg/m2) was started. At this time KS had progressed to about 150 cutaneous lesions. Antiretroviral therapy was continued unchanged. The interval between the courses of chemotherapy was three weeks, and five courses were given. Following the first course of chemotherapy no new KS lesions appeared during the first month and about two thirds of the existing lesions had disappeared. Complete remission was gradually reached after one year. During chemotherapy several biopsies were taken. The first biopsy was obtained 24 hours after the start of the chemotherapy (named KS-24) and the second biopsy was taken after 48 hours (named KS-48). Two biopsies were flash-frozen in liquid nitrogen immediately after neurosurgical removal and stored at -80°C. Another biopsy taken from the same lesion was used for histological analysis. Diagnosis of AIDS-KS was confirmed histopathologically (Fig. 1a, 1b). About 30–40% of the biopsies consisted of tumor specific spindle cells.
SAGE libraries KSa and KSb were made from frozen material taken at autopsy from two untreated AIDS-KS patients, both of which died in 1986 (Cornelissen et al., manuscript submitted). Additionally, a control SAGE libraries of 39,492 tags was generated from the pooled normal skin samples of three patients undergoing reduction mammoplasty (library NS), and another control library of 51,886 tags was made from isolated CD45+CD4+ T-cells from a healthy blood donor (library CD4). Control libraries KSa, KSb and NS have been described elsewhere (Cornelissen et al., manuscript submitted).
SAGE library construction
CD4+ T-cells were depleted from peripheral blood mononuclear cells from a single healthy donor by the use of CD4-coated immunomagnetic beads (miniMACS, CLB, The Netherlands). Total RNA was isolated from the two AIDS-KS biopsies and from 1.9 × 107 CD4+ T-cells using Trizol reagent (Life Technologies, San Diego CA, USA). Poly(A)+ RNA was further isolated using the Micro-FastTrack 2.0 messenger RNA (mRNA) purification kit (Invitrogen, Carlsbad CA, USA) according to the manufacturer's protocol. SAGE was performed as described previously [23, 52]. In short: synthesis of cDNA was performed using Superscript II RNAse H-reverse transcriptase (Life Technologies, San Diego CA, USA) and a primer biotin-5'-T18-3'. The cDNA was then cleaved with NlaIII, and the 3' restriction fragments were isolated with magnetic streptavidin-coated beads (Dynabeads M280 from Dynal, Oslo, Norway). Oligonucleotides containing BsmF1 recognition sites were ligated to the fragments bound to the beads, and tags were released from the beads by BsmF1 digestion. Tags were ligated to create ditags, and amplified by 26–28 PCR cycles. NlaIII digested, amplified ditags were subsequently concatenated and cloned using the Zero Background cloning kit from Invitrogen (Carlsbad CA, USA). Colonies were screened by PCR using M13 reverse or (-) 21M13 primers, and inserts were sequenced with the Bigdye Terminator Cycle Sequencing kit (ABI, Foster City CA, USA) and analyzed with an ABI 377 automated sequencer (ABI, Foster City CA, USA), following the manufacturer's protocols.
Analysis of SAGE libraries
Primary analysis of the SAGE libraries was performed with the program USAGE version2 . This program is able to do initial analyses on raw sequence data, e.g. ditag and tag extraction, tag counting, and tag identification. Tags are identified with the tag-to-gene mapping of the SAGEmap database and a tag-to-gene mapping database established as part of the Human Transcriptome Map . In this latter identification, the SAGEmap database from NCBI http://www.ncbi.nlm.nih.gov/SAGE has been corrected for common errors, mostly due to sequencing errors in publicly available sequences.
Secondly, the USAGE program was used to compare SAGE libraries, and to do statistical analyses on tag count differences. For this, USAGE implements the method proposed by Kal et al.
We thank Dr. T. Halaby for access to the patient samples, W.van Est for generating the computer version of figure 3, and Dr. B. Berkhout for helpful comments on the manuscript.
- Scherf U, Ross DT, Waltham M, Smith LH, Lee JK, Tanabe L, Kohn KW, Reinhold WC, Myers TG, Andrews DT, et al: A gene expression database for the molecular pharmacology of cancer. Nat Genet. 2000, 24: 236-244. 10.1038/73439.View ArticlePubMedGoogle Scholar
- Jordan MA, Thrower D, Wilson L: Mechanism of inhibition of cell proliferation by Vinca alkaloids. Cancer Res. 1991, 51: 2212-2222.PubMedGoogle Scholar
- Barlogie B, Drewinko B, Johnston DA, Freireich EJ: The effect of adriamycin on the cell cycle traverse of a human lymphoid cell line. Cancer Res. 1976, 36: 1975-1979.PubMedGoogle Scholar
- Mimnaugh EG, Trush MA, Bhatnagar M, Gram TE: Enhancement of reactive oxygen-dependent mitochondrial membrane lipid peroxidation by the anticancer drug adriamycin. Biochem Pharmacol. 1985, 34: 847-856. 10.1016/0006-2952(85)90766-X.View ArticlePubMedGoogle Scholar
- Cullinane C, Cutts SM, Panousis C, Phillips DR: Interstrand cross-linking by adriamycin in nuclear and mitochondrial DNA of MCF-7 cells. Nucleic Acids Res. 2000, 28: 1019-1025. 10.1093/nar/28.4.1019.View ArticlePubMedPubMed CentralGoogle Scholar
- Eliot H, Gianni L, Myers C: Oxidative destruction of DNA by the adriamycin-iron complex. Biochemistry. 1984, 23: 928-936.View ArticlePubMedGoogle Scholar
- Muindi J, Sinha BK, Gianni L, Myers C: Thiol-dependent DNA damage produced by anthracycline-iron complexes. The structure-activity relationships and molecular mechanisms. Mol Pharmacol. 1985, 27: 356-365.PubMedGoogle Scholar
- Muindi JR, Sinha BK, Gianni L, Myers CE: Hydroxyl radical production and DNA damage induced by anthracycline-iron complex. FEBS Lett. 1984, 172: 226-230. 10.1016/0014-5793(84)81130-8.View ArticlePubMedGoogle Scholar
- Myers C, Gianni L, Zweier J, Muindi J, Sinha BK, Eliot H: Role of iron in adriamycin biochemistry. Fed Proc. 1986, 45: 2792-2797.PubMedGoogle Scholar
- Maniglia CA, Wilson RG: Two types of adriamycin inhibition of a homologous RNA synthesizing system from L1210 cells. Chem Biol Interact. 1981, 33: 319-327. 10.1016/0009-2797(81)90050-8.View ArticlePubMedGoogle Scholar
- Zhu K, Henning D, Iwakuma T, Valdez BC, Busch H: Adriamycin inhibits human RH II/Gu RNA helicase activity by binding to its substrate. Biochem Biophys Res Commun. 1999, 266: 361-365. 10.1006/bbrc.1999.1815.View ArticlePubMedGoogle Scholar
- Gewirtz DA: A critical evaluation of the mechanisms of action proposed for the antitumor effects of the anthracycline antibiotics adriamycin and daunorubicin. Biochem Pharmacol. 1999, 57: 727-741. 10.1016/S0006-2952(98)00307-4.View ArticlePubMedGoogle Scholar
- Barlogie B, Drewinko B, Schumann J, Freireich EJ: Pulse cytophotometric analysis of cell cycle perturbation with bleomycin in vitro. Cancer Res. 1976, 36: 1182-1187.PubMedGoogle Scholar
- Noda A: Gene expression in ataxia telangiectasia cells as perturbed by bleomycin treatment. Somat Cell Mol Genet. 1992, 18: 113-122.View ArticlePubMedGoogle Scholar
- Kuo MT, Auger LT, Saunders GF, Haidle CW: Effect of bleomycin on the synthesis and function of RNA. Cancer Res. 1977, 37: 1345-1348.PubMedGoogle Scholar
- Vernole P, Tedeschi B, Caporossi D, Maccarrone M, Melino G, Annicchiarico-Petruzzelli M: Induction of apoptosis by bleomycin in resting and cycling human lymphocytes. Mutagenesis. 1998, 13: 209-215.View ArticlePubMedGoogle Scholar
- Iqbal ZM, Kohn KW, Ewig RA, Fornace AJ: Single-strand scission and repair of DNA in mammalian cells by bleomycin. Cancer Res. 1976, 36: 3834-3838.PubMedGoogle Scholar
- D'Andrea AD, Haseltine WA: Sequence specific cleavage of DNA by the antitumor antibiotics neocarzinostatin and bleomycin. Proc Natl Acad Sci U S A. 1978, 75: 3608-3612.View ArticlePubMedPubMed CentralGoogle Scholar
- Kuo MT: Preferential damage of active chromatin by bleomycin. Cancer Res. 1981, 41: 2439-2443.PubMedGoogle Scholar
- Hecht SM: Bleomycin: new perspectives on the mechanism of action. J Nat Prod. 2000, 63: 158-168. 10.1021/np990549f.View ArticlePubMedGoogle Scholar
- Yamamoto T, Eckes B, Krieg T: Bleomycin increases steady-state levels of type I collagen, fibronectin and decorin mRNAs in human skin fibroblasts. Arch Dermatol Res. 2000, 292: 556-561. 10.1007/s004030000180.View ArticlePubMedGoogle Scholar
- Lasky JA, Ortiz LA, Tonthat B, Hoyle GW, Corti M, Athas G, Lungarella G, Brody A, Friedman M: Connective tissue growth factor mRNA expression is upregulated in bleomycin-induced lung fibrosis. Am J Physiol. 1998, 275: L365-L371.PubMedGoogle Scholar
- Velculescu VE, Zhang L, Vogelstein B, Kinzler KW: Serial analysis of gene expression. Science. 1995, 270: 484-487.View ArticlePubMedGoogle Scholar
- Hough CD, Sherman-Baust CA, Pizer ES, Montz FJ, Im DD, Rosenshein NB, Cho KR, Riggins GJ, Morin PJ: Large-scale serial analysis of gene expression reveals genes differentially expressed in ovarian cancer. Cancer Res. 2000, 60: 6281-6287.PubMedGoogle Scholar
- Waghray A, Schober M, Feroze F, Yao F, Virgin J, Chen YQ: Identification of differentially expressed genes by serial analysis of gene expression in human prostate cancer. Cancer Res. 2001, 61: 4283-4286.PubMedGoogle Scholar
- Ryu B, Jones J, Hollingsworth MA, Hruban RH, Kern SE: Invasion-specific genes in malignancy: serial analysis of gene expression comparisons of primary and passaged cancers. Cancer Res. 2001, 61: 1833-1838.PubMedGoogle Scholar
- Moore PS, Chang Y: Antiviral activity of tumor-suppressor pathways: Clues from molecular piracy by KSHV. Trends in Genetics. 1998, 14: 144-150. 10.1016/S0168-9525(98)01408-5.View ArticlePubMedGoogle Scholar
- Blasig C, Zietz C, Haar B, Neipel F, Esser S, Brockmeyer NH, Tschachler E, Colombini S, Ensoli B, Sturzl M: Monocytes in Kaposi's sarcoma lesions are productively infected by human herpesvirus 8. Journal of Virology. 1997, 71: 7963-7968.PubMedPubMed CentralGoogle Scholar
- Cerimele F, Curreli F, Ely S, Friedman-Kien AE, Cesarman E, Flore O: Kaposi's sarcoma-associated herpesvirus can productively infect primary human keratinocytes and alter their growth properties. J Virol. 2001, 75: 2435-2443. 10.1128/JVI.75.5.2435-2443.2001.View ArticlePubMedPubMed CentralGoogle Scholar
- Moses AV, Fish KN, Ruhl R, Smith PP, Strussenberg JG, Zhu L, Chandran B, Nelson JA: Long-term infection and transformation of dermal microvascular endothelial cells by human herpesvirus 8. J Virol. 1999, 73: 6892-6902.PubMedPubMed CentralGoogle Scholar
- Mesri EA, Cesarman E, Arvanitakis L, Rafii S, Moore MA, Posnett DN, Knowles DM, Asch AS: Human herpesvirus-8/Kaposi's sarcoma-associated herpesvirus is a new transmissible virus that infects B cells. J Exp Med. 1996, 183: 2385-2390.View ArticlePubMedGoogle Scholar
- Cesarman E, Chang Y, Moore PS, Said JW, Knowles DM: Kaposi's sarcoma-associated herpesvirus-like DNA sequences in AIDS-related body-cavity-based lymphomas. New England Journal of Medicine. 1995, 332: 1186-1191. 10.1056/NEJM199505043321802.View ArticlePubMedGoogle Scholar
- Soulier J, Grollet L, Oksenhendler E, Cacoub P, Cazals-Hatem D, Babinet P, D'Agay M-F, Clauvel J-P, Raphael M, Degos L, et al: Kaposi's sarcoma-associated herpesvirus-like DNA sequences in multicentric Castleman's disease. Blood. 1995, 86: 1276-1280.PubMedGoogle Scholar
- Khanna N, Reddy VG, Tuteja N, Singh N: Differential gene expression in apoptosis: identification of ribosomal protein S29 as an apoptotic inducer. Biochem Biophys Res Commun. 2000, 277: 476-486. 10.1006/bbrc.2000.3688.View ArticlePubMedGoogle Scholar
- Collins I, Weber A, Levens D: Transcriptional consequences of topoisomerase inhibition. Mol Cell Biol. 2001, 21: 8437-8451. 10.1128/MCB.21.24.8437-8451.2001.View ArticlePubMedPubMed CentralGoogle Scholar
- Kaminski N, Allard JD, Pittet JF, Zuo F, Griffiths MJ, Morris D, Huang X, Sheppard D, Heller RA: Global analysis of gene expression in pulmonary fibrosis reveals distinct programs regulating lung inflammation and fibrosis. Proc Natl Acad Sci U S A. 2000, 97: 1778-1783. 10.1073/pnas.97.4.1778.View ArticlePubMedPubMed CentralGoogle Scholar
- Kudoh K, Ramanna M, Ravatn R, Elkahloun AG, Bittner ML, Meltzer PS, Trent JM, Dalton WS, Chin KV: Monitoring the expression profiles of doxorubicin-induced and doxorubicin-resistant cancer cells by cDNA microarray. Cancer Res. 2000, 60: 4161-4166.PubMedGoogle Scholar
- Dan S, Yamori T: Repression of cyclin B1 expression after treatment with adriamycin, but not cisplatin in human lung cancer A549 cells. Biochem Biophys Res Commun. 2001, 280: 861-867. 10.1006/bbrc.2000.4231.View ArticlePubMedGoogle Scholar
- Demaria S, Volm MD, Shapiro RL, Yee HT, Oratz R, Formenti SC, Muggia F, Symmans WF: Development of tumor-infiltrating lymphocytes in breast cancer after neoadjuvant paclitaxel chemotherapy. Clin Cancer Res. 2001, 7: 3025-3030.PubMedGoogle Scholar
- Lam LT, Pickeral OK, Peng AC, Rosenwald A, Hurt EM, Giltnane JM, Averett LM, Zhao H, Davis RE, Sathyamoorthy M, et al: Genomic-scale measurement of mRNA turnover and the mechanisms of action of the anti-cancer drug flavopiridol. Genome Biol. 2001, 2: RESEARCH0041-10.1186/gb-2001-2-10-research0041.View ArticlePubMedPubMed CentralGoogle Scholar
- Guhaniyogi J, Brewer G: Regulation of mRNA stability in mammalian cells. Gene. 2001, 265: 11-23. 10.1016/S0378-1119(01)00350-X.View ArticlePubMedGoogle Scholar
- Hendrickson S, Johnson LF: Evidence for highly stable nuclear poly(A) in cultured mammalian cells. Biochim Biophys Acta. 1978, 517: 287-295. 10.1016/0005-2787(78)90195-8.View ArticlePubMedGoogle Scholar
- Spector DL: Macromolecular domains within the cell nucleus. Annu Rev Cell Biol. 1993, 9: 265-315. 10.1146/annurev.cellbio.9.1.265.View ArticlePubMedGoogle Scholar
- Huang S, Deerinck TJ, Ellisman MH, Spector DL: The perinucleolar compartment and transcription. J Cell Biol. 1998, 143: 35-47. 10.1083/jcb.143.1.35.View ArticlePubMedPubMed CentralGoogle Scholar
- Brawerman G, Diez J: Metabolism of the polyadenylate sequence of nuclear RNA and messenger RNA in mammalian cells. Cell. 1975, 5: 271-280.View ArticlePubMedGoogle Scholar
- Mintz PJ, Patterson SD, Neuwald AF, Spahr CS, Spector DL: Purification and biochemical characterization of interchromatin granule clusters. EMBO J. 1999, 18: 4308-4320. 10.1093/emboj/18.15.4308.View ArticlePubMedPubMed CentralGoogle Scholar
- Tenenbaum SA, Carson CC, Lager PJ, Keene JD: Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proc Natl Acad Sci U S A. 2000, 97: 14085-14090. 10.1073/pnas.97.26.14085.View ArticlePubMedPubMed CentralGoogle Scholar
- Ishida S, Huang E, Zuzan H, Spang R, Leone G, West M, Nevins JR: Role for E2F in control of both DNA replication and mitotic functions as revealed from DNA microarray analysis. Mol Cell Biol. 2001, 21: 4684-4699. 10.1128/MCB.21.14.4684-4699.2001.View ArticlePubMedPubMed CentralGoogle Scholar
- Ling YH, el Naggar AK, Priebe W, Perez-Soler R: Cell cycle-dependent cytotoxicity, G2/M phase arrest, and disruption of p34cdc2/cyclin B1 activity induced by doxorubicin in synchronized P388 cells. Mol Pharmacol. 1996, 49: 832-841.PubMedGoogle Scholar
- Aytac U, Claret FX, Ho L, Sato K, Ohnuma K, Mills GB, Cabanillas F, Morimoto C, Dang NH: Expression of CD26 and its associated dipeptidyl peptidase IV enzyme activity enhances sensitivity to doxorubicin-induced cell cycle arrest at the G(2)/M checkpoint. Cancer Res. 2001, 61: 7204-7210.PubMedGoogle Scholar
- Colgan DF, Murthy KG, Prives C, Manley JL: Cell-cycle related regulation of poly(A) polymerase by phosphorylation. Nature. 1996, 384: 282-285. 10.1038/384282a0.View ArticlePubMedGoogle Scholar
- Zhang L, Zhou W, Velculescu VE, Kern SE, Hruban RH, Hamilton SR, Vogelstein B, Kinzler KW: Gene expression profiles in normal and cancer cells. Science. 1997, 276: 1268-1272. 10.1126/science.276.5316.1268.View ArticlePubMedGoogle Scholar
- van Kampen AH, van Schaik BD, Pauws E, Michiels EM, Ruijter JM, Caron HN, Versteeg R, Heisterkamp SH, Leunissen JA, Baas F, et al: USAGE: a web-based approach towards the analysis of SAGE data. Bioinformatics. 2000, 16: 899-905. 10.1093/bioinformatics/16.10.899.View ArticlePubMedGoogle Scholar
- Caron H, van Schaik B, van der Mee M, Baas F, Riggins G, van Sluis P, Hermus MC, van Asperen R, Boon K, Voute PA, et al: The human transcriptome map: clustering of highly expressed genes in chromosomal domains. Science. 2001, 291: 1289-1292. 10.1126/science.1056794.View ArticlePubMedGoogle Scholar
- Kal AJ, van Zonneveld AJ, Benes V, van den Berg M, Koerkamp MG, Albermann K, Strack N, Ruijter JM, Richter A, Dujon B, et al: Dynamics of gene expression revealed by comparison of serial analysis of gene expression transcript profiles from yeast grown on two different carbon sources. Mol Biol Cell. 1999, 10: 1859-1872.View ArticlePubMedPubMed CentralGoogle Scholar
- Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci S U A. 1998, 95: 14863-14868. 10.1073/pnas.95.25.14863.View ArticleGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/2/21/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.