DESCRIPTION METHOD FOR DIAGNOSING PANCREATIC CANCER
PRIORITY INFORMATION
This application claims priority to United States Provisional Application Serial No.60/414,872, filed September 30, 2002, and Serial No.60/450,889, filed February 28, 2003, and which are incorporated herein by reference.
TECHMCAL FIELD
The invention relates to methods of diagnosing pancreatic cancer.
BACKGROUND OF THE INVENTION
Pancreatic cancer has one of the highest mortality rates of any malignancy, and the 5- year-survival rate of patients is 4%. 28000 patients with pancreatic cancer are diagnosed each year, and nearly all patients will die of their disease (1). The poor prognosis of this malignancy is a result of the difficulty of early diagnosis and poor response to current therapeutic methods (1, 2). In particular currently no tumor markers are identified that allow reliable screening at an early, potentially curative stage of the disease.
cDNA microarray technologies have enabled to obtain comprehensive profiles of gene expression in normal and malignant cells, and compare the gene expression in malignant and corresponding normal cells (Okabe et al., Cancer Res 61:2129-37 (2001); Kitahara et al., Cancer Res 61: 3544-9 (2001); Lin et al, Oncogene 21:4120-8 (2002); Hasegawa et al, Cancer Res 62:7012-7 (2002)). This approach enables to disclose the complex nature of cancer cells, and helps to understand the mechanism of carcinogenesis. Identification of genes that are deregulated in tumors can lead to more precise and accurate diagnosis of individual cancers, and to develop novel therapeutic targets (Bienz and Clevers, Cell 103:311- 20 (2000)). To disclose mechanisms underlying tumors from a genome-wide point of view, and discover target molecules for diagnosis and development of novel therapeutic drugs, the present inventors have been analyzing the expression profiles of tumor cells using a cDNA
microarray of 23040 genes (Okabe et al., Cancer Res 61:2129-37 (2001); Kitahara et al., Cancer Res 61:3544-9 (2001); Lin et al., Oncogene 21:4120-8 (2002); Hasegawa et al., Cancer Res 62:7012-7 (2002)).
Studies designed to reveal mechanisms of carcinogenesis have already facilitated identification of molecular targets for anti-tumor agents. For example, inhibitors of farnexyltransferase (FTIs) which were originally developed to inhibit the growth-signaling pathway related to Ras, whose activation depends on posttranslational farnesylation, has been effective in treating Ras-dependent tumors in animal models (He et al., Cell 99:335-45 (1999)). Clinical trials on human using a combination or anti-cancer drugs and anti-HER2 monoclonal antibody, trastuzumab, have been conducted to antagonize the proto-oncogene receptor HER2/ neu; and have been achieving improved clinical response and overall survival of breast-cancer patients (Lin et al., Cancer Res 61:6345-9 (2001)). A tyrosine kinase inhibitor, STI-571, which selectively inactivates bcr-abl fusion proteins, has been developed to treat chronic myelogenous leukemias wherein constitutive activation of bcr-abl tyrosine kinase plays a crucial role in the transformation of leukocytes. Agents of these kinds are designed to suppress oncogenic activity of specific gene products (Fujita et al, Cancer Res 61 -.1122-6 (2001)). Therefore, gene products commonly up-regulated in cancerous cells may serve as potential targets for developing novel anti-cancer agents.
It has been demonstrated that CD8+ cytotoxic T lymphocytes (CTLs) recognize epitope peptides derived from tumor-associated antigens (TAAs) presented on MHC Class I molecule, and lyse tumor cells. Since the discovery of MAGE family as the first example of TAAs, many other TAAs have been discovered using immunological approaches (Boon, Int J Cancer 54: 177-80 (1993); Boon and van der Bruggen, J Exp Med 183: 725-9 (1996); van der Braggen et al., Science 254: 1643-7 (1991); Brichard et al., J Exp Med 178: 489-95 (1993); Kawakami et al., J Exp Med 180: 347-52 (1994)). Some of the discovered TAAs are now in the stage of clinical development as targets of immunotherapy. TAAs discovered so far include MAGE (van der Bruggen et al, Science 254: 1643-7 (1991)), gplOO (Kawakami et al, J Exp Med 180: 347-52 (1994)), SART (Shichijo et al., J Exp Med 187: 277-88 (1998)), and NY-ESO-1 (Chen et al., Proc Natl Acad Sci USA 94: 1914-8 (1997)). On the other hand, gene products which had been demonstrated to be specifically overexpressed in tumor cells, have been shown to be recognized as targets inducing cellular immune responses. Such gene products include p53 (Umano et al., Brit J Cancer 84: 1052-7 (2001)), HER2/ neu (Tanaka et
al., Brit J Cancer 84: 94-9 (2001)), CEA (Nukaya et al., Int J Cancer 80: 92-7 (1999)), and so on.
In spite of significant progress in basic and clinical research concerning TAAs (Rosenbeg et al., Nature Med 4: 321-7 (1998); Mukherji et al., Proc Natl Acad Sci USA 92: 8078-82 (1995); Hu et al., Cancer Res 56: 2479-83 (1996)), only limited number of candidate TAAs for the treatment of adenocarcinomas, including colorectal cancer, are available. TAAs abundantly expressed in cancer cells, and at the same time which expression is restricted to cancer cells would be promising candidates as inimuno therapeutic targets. Further, identification of new TAAs inducing potent and specific antitumor immune responses is expected to encourage clinical use of peptide vaccination strategy in various types of cancer (Boon and can der Bruggen, J Exp Med 183: 725-9 (1996); van der Bruggen et al., Science 254: 1643-7 (1991); Brichard et al., J Exp Med 178: 489-95 (1993); Kawakami et al.,J Exp Med 180: 347-52 (1994); Shichijo et al., J Exp Med 187: 277-88 (1998); Chen et al., Proc Natl Acad Sci USA 94: 1914-8 (1997); Harris, J Natl Cancer Inst 88: 1442-5 (1996); Butterfield et al., Cancer Res 59: 3134-42 (1999); Nissers et al., Cancer Res 59: 5554-9 (1999); van der Burg et al., J Immunol 156: 3308-14 (1996); Tanaka et al., Cancer Res 57: 4465-8 (1997); Fujie et al., Int J Cancer 80: 169-72 (1999); Kikuchi et al., Int J Cancer 81: 459-66 (1999); Oiso et al., it J Cancer 81: 387-94 (1999)).
It has been repeatedly reported that peptide-stimulated peripheral blood mononuclear cells (PBMCs) from certain healthy donors produce significant levels of IFΝ-γ in response to the peptide, but rarely exert cytotoxicity against tumor cells in an HLA-A24 or -A0201 restricted manner in 51Cr-release assays (Kawano et al., Cance Res 60: 3550-8 (2000); Νishizaka et al, Cancer Res 60: 4830-7 (2000); Tamura et al., Jpn J Cancer Res 92: 762-7 (2001)). However, both of HLA-A24 and HLA-A0201 are one of the popular HLA alleles in Japanese, as well as Caucasian (Date et al., Tissue Antigens 47: 93-101 (1996); Kondo et al., J Immunol 155: 4307-12 (1995); Kubo et al., J Immunol 152: 3913-24 (1994); Imanishi et al., Proceeding of the eleventh International Hictocompatibility Workshop and Conference Oxford University Press, Oxford, 1065 (1992); Williams et al., Tissue Antigen 49: 129 (1997)). Thus, antigenic peptides of carcinomas presented by these HLAs may be especially useful for the treatment of carcinomas among Japanese and Caucasian. Further, it is known that the induction of low-affinity CTL in vitro usually results from the use of peptide at a high concentration, generating a high level of specific peptide/MHC complexes on antigen
presenting cells (APCs), which will effectively activate these CTL (Alexander-Miller et al., Proc Natl Acad Sci USA 93: 4102-7 (1996)).
SUMMARY OF THE INVENTION
The invention is based on the discovery of a pattern of gene expression correlated with pancreatic cancer (PNC). The genes that are differentially expressed in pancreatic cancer are collectively referred to herein as "PNC nucleic acids" or "PNC polynucleotides" and the corresponding encoded polypeptides are referred to as "PNC polypeptides" or "PNC proteins." Accordingly, the invention features a method of diagnosing or determining a predisposition to pancreatic cancer in a subject by determining an expression level of a PNC- associated gene in a patient derived biological sample, such as tissue sample. By PNC- associated gene is meant a gene that is characterized by an expression level which differs in a cell obtained from a PNC cell compared to a normal cell. A normal cell is one obtained from pancreas tissue. A PNC-associated gene is one or more of PNC 1-605. An alteration, e.g., increase or decrease of the level of expression of the gene compared to a normal control level of the gene indicates that the subject suffers from or is at risk of developing PNC.
By normal control level is meant a level of gene expression detected in a normal, healthy individual or in a population of individuals known not to be suffering from pancreatic cancer. A control level is a single expression pattern derived from a single reference population or from a plurality of expression patterns. For example, the control level can be a database of expression patterns from previously tested cells. A normal individual is one with no clinical symptoms of pancreatic cancer.
An increase in the level of PNC 1-259 detected in a test sample compared to a normal control level indicates the subject (from which the sample was obtained) suffers from or is at risk of developing PNC. In contrast, a decrease in the level of PNC 260-605 detected in a test sample compared to a normal control level indicates said subject suffers from or is at risk of developing PNC.
Alternatively, expression of a panel of PNC-associated genes in the sample is compared to a PNC control level of the same panel of genes. By PNC control level is meant the expression profile of the PNC-associated genes found in a population suffering from PNC.
Gene expression is increased or decreased 10%, 25%, 50% compared to the control level. Alternately, gene expression is increased or decreased 1, 2, 5 or more fold compared to the control level. Expression is determined by detecting hybridization, e.g. , on an array, of a PNC-associated gene probe to a gene transcript of the patient-derived tissue sample.
The patient derived tissue sample is any tissue from a test subject, e.g., a patient known to or suspected of having PNC. For example, the tissue contains an epithelial cell. For example, the tissue is an epithelial cell from a pancreatic ductal adenocarcinoma.
The invention also provides a PNC reference expression profile of a gene expression level of two or more of PNC 1-605. Alternatively, the invention provides a PNC reference expression profile of the levels of expression two or more of PNC 1-259 or PNC 260-605.
The invention further provides methods of identifmg an agent that inhibits or enhances the expression or activity of a PNC-associated gene, e.g. PNC 1-605 by contacting a test cell expressing a PNC-associated gene with a test agent and determining the expression level of the PNC associated gene. The test cell is a epithelial cell such as an epithelial cell from a pancreatic adenocarcinoma. A decrease of the level compared to a normal control level of the gene indicates that the test agent is an inhibitor of the PNC-associated gene and reduces a symptom of PNC, e.g. PNC 1-259. Alternatively, an increase of the level or activity compared to a normal control level or activity of the gene indicates that said test agent is an enhancer of expression or function of the PNC-associated gene and reduces a symptom of PNC, e.g, PNC 260-605.
The invention also provides a kit with a detection reagent which binds to one or more PNC nucleic acids or which binds to a gene product encoded by the nucleic acid sequences. Also provided is an array of nucleic acids that binds to one or more PNC nucleic acids.
Therapeutic methods include a method of treating or preventing pancreatic cancer in a subject by administering to the subject an antisense composition. The antisense composition reduces the expression of a specific target gene, e.g., the antisense composition contains a nucleotide, which is complementary to a sequence selected from the group consisting of PNC 1-259. Another method includes the steps of administering to a subject an short interfering RNA (siRNA) composition. The siRNA composition reduces the expression of a nucleic acid
selected from the group consisting of PNC 1-259. In yet another method, treatment or prevention of PNC in a subject is carried out by administering to a subject a ribozyme composition. The nucleic acid-specific ribozyme composition reduces the expression of a nucleic acid selected from the group consisting of PNC 1-259. Other therapeutic methods include those in which a subject is administered a compound that increases the expression of PNC 260-605 or activity of a polypeptide encoded by PNC 260-605.
The invention also includes vaccines and vaccination methods. For example, a method of treating or preventing PNC in a subject is carried out by administering to the subject a vaccine containing a polypeptide encoded by a nucleic acid selected from the group consisting of PNC 1-259 or an immunologically active fragment such a polypeptide. An immunologically active fragment is a polypeptide that is shorter in length than the full-length naturally-occurring protein and which induces an immune response. For example, an immunologically active fragment at least 8 residues in length and stimulates an immune cell such as a T cell or a B cell. L-nmune cell stimulation is measured by detecting cell proliferation, elaboration of cytokines (e.g., IL-2), or production of an antibody.
Alternatively, the present invention provides target molecules for treating or preventing malignant pancreatic cancer. According to the present invention, 76 (PNC 606- 681), 168 (PNC 682-849) and 84 (850-933) genes were identified as genes that showed unique altered expression patterns in pancreatic cancer cells with lymph-node metastasis, liver metastasis and early recurrence, respectively. Thus, malignant pancreatic cancer can be treated or prevented via the suppression of the expression or activity of up-regulated genes selected from the group consisting of PNC 606-640 and PNC 682-741. Furthermore, recurrence of pancreatic cancer can be treated or prevented via the suppression of the expression or activity of up-regulated genes selected from the group consisting of PNC 850- 893. Moreover, malignant pancreatic cancer can also be treated or prevented through enhancing the expression or activity of down-regulating genes in cancerous cells.
The present invention also provides methods for predicting recurrence of pancreatic cancer. The method comprises the step of measuring the expression level of marker genes selected from the group consisting of PNC 850-879. The marker genes were identified as genes that show unique altered expression patterns in pancreatic cancer cells of patients with recurrence within 12 month after surgery. Therefore, recurrence of the pancreatic cancer in a subject can be predicted by determining whether the expression level
detected in a sample derived from the subject is closer to the mean expression level of early- recurrent cases or late-recurrent cases in reference samples.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.
One advantage of the methods described herein is that the disease is identified prior to detection of overt clinical symptoms of pancreatic cancer. Other features and advantages of the invention will be apparent from the following detailed description, and from the claims.
BRIEF DESCRIPTION OF THE FIGURES
Figure 1 A is a photograph of a hematoxylin and eosin stained pancreatic cancer
(well-differentiated type) before microdissection.1A1 is the same sections after microdissection. 1 A2 is a photograph of the microdissected cancer cells captured on the collecting cap.
Figure IB is a photograph of a hematoxylin and eosin stained pancreatic cancer (scirrhous type) before microdissection. IB 1 is the same sections after microdissection. 1B2 is a photograph of the microdissected cancer cells captured on the collecting cap.
Figure 1C is a photograph of normal pancreas containing greater than 90% acinar cell.
Figure ID is a photograph of microdissected normall pancreatic ductal epithial cells.
Figure 2 is a photograph of a DNA agarose gel showing expression of representative 12 genes and TUBA examined by semi-quantitative RT-PCR using cDNA prepared from amplified RNA. Lanes 1-12 each show the expression level of the genes in a different PNC patient. Gene symbols are noted for the genes. The last lane shows the expression level of each gene in a normal individual.
Figure 3 Dendrogram of two-dimensional hierarchical clustering analysis using 76 genes selected by a random-permutation test which compared expression profiles of 9 lymph-node positive cases with those of 4 lymph-node negative cases. In the vertical axis, 35 genes were clustered in the upper branch, indicating relatively high levels of expression in lymph-node positive cases.
Figure 4 Dendrogram of two-dimensional hierarchical clustering analysis using 168 genes selected by a random-permutation test which compared expression profiles of 5 liver-metastasis-positive cases with those of 6 negative cases. In the vertical axis, 60 genes were clustered in the upper branch which was more highly expressed in liver-metastasis- positive cases.
Figure 5 (A) Result of a two-dimensional hierarchical clustering analysis using 84 genes selected by a random-permutation test which compared expression profiles of 7 early-recurrent cases (within 12months after surgery) with those of 6 late-recurrent cases (over 12 months after surgery). In the vertical axis, 84 genes were clustered in different branches according to similarity in relative expression ratios. (B) Optimization of the number of discriminating genes. The classification score (CS) was calculated by using the prediction score of early-recurrent case (PSr) and late-recurrent case (PSn) in each gene set, as follows. CS= (μpsr - μpsn) / (σps. + σpsn). A larger value of CS indicates better separation of the two groups by the predictive-scoring system. (C) Different prediction scores appear when the number of discriminating genes is changed. Red diamonds represent early-recurrent cases; blue diamonds denote late-recurrent cases.
DETAILED DESCRIPTION
Generally pancreatic ductal adenocarcinoma has a characteristic of highly desmoplastic stromal reaction, only a low percentage (about 30%) of cancer cells are contained in the tumor mass. Furthermore, normal pancreatic ductal epithelial cells, which recently considered to be the normal counterpart of the pancreatic adenocarcinoma, occupied only less than 5% of the total population of cells composing the organ 'pancreas' (7, 8 ). Hence, the gene-expression analysis of PNC compared to normal pancreas by using whole tissue is distorted by the contamination of needless cells such as fibroblast, inflammatory cells, acinar cells, etc., and results in "noisy data". Therefore Laser capture microdissection (LCM),
or Laser microbeam microdissection (LMM), a method for isolating pure cell populations, was used to obtain specific cancer cells and normal epithelial cells (9,10).
The present invention is based in part on the discovery of changes in expression patterns of multiple nucleic acids in epithelial cells from adenocarcinomas of patients with PNC. The differences in gene expression were identified by using a comprehensive cDNA microarray system.
The gene-expression profiles of cancer cells from 18 PNCs were analyzed using cDNA microarray representing 23,040 genes couples with laser microdissection. By comparing expression patterns between cancer cells from diagnostic PNC patients and normal ductal epithelial cells purely selected with Laser Microdisection, 259 genes were identified as commonly up-regulated in PNC cells, and 346 genes were identified as being commonly down-regulated in PNC cells. In addition, selection was made of candidate molecular markers with the potential of detecting cancer-related proteins in serum or sputum of patients, and discovered some potential targets for development of signal-suppressing strategies in human PNC.
The differentially expressed genes identified herein are used for diagnostic purposes as markers of PNC and as gene targets, the expression of which is altered to treat or alleviate a symptom of PNC.
The genes whose expression levels are modulated (i.e., increased or decreased) in PNC patients are summarized in Tables 3-4 and are collectively referred to herein as " PNC- associated genes " , "PNC nucleic acids" or "PNC polynucleo tides" and the corresponding encoded polypeptides are referred to as "PNC polypeptides" or "PNC proteins." Unless indicated otherwise, "PNC" is meant to refer to any of the sequences disclosed herein, (e.g., PNC 1-605). The genes have been previously described and are presented along with a database accession number.
By measuring expression of the various genes in a sample of cells, PNC is diagnosed. Similarly, measuring the expression of these genes in response to various agents can identify agents for treating PNC.
The invention involves determining (e.g., measuring) the expression of at least one, and up to all the PNC sequences listed in Tables 3-4. Using sequence information provided by the GeneBank™ database entries for the known sequences the PNC-associated genes are detected and measured using techniques well known to one of ordinary skill in the art. For
example, sequences within the sequence database entries corresponding to PNC sequences, are used to construct probes for detecting PNC RNA sequences in, e.g., northern blot hybridization analysis. Probes include at least 10, 20, 50, 100, 200 nucleotides of a reference sequence. As another example, the sequences can be used to construct primers for specifically amplifying the PNC nucleic acid in, e.g, amplification-based detection methods such as reverse-transcription based polymerase chain reaction.
Expression level of one or more of the PNC-associated genes in the test cell population, e.g., a patient derived tissues sample, is then compared to expression levels of the some genes in a reference population. The reference cell population includes one or more cells for which the compared parameter is known, i. e. , pancreatic ductal adenocarcinoma cells or normal pancreatic ductal epithelial cells.
Whether or not a pattern of gene expression levels in the test cell population compared to the reference cell population indicates PNC or predisposition thereto depends upon the composition of the reference cell population. For example, if the reference cell population is composed of non-PNC cells, a similar gene expression pattern in the test cell population and reference cell population indicates the test cell population is non-PNC. Conversely, if the reference cell population is made up of PNC cells, a similar gene expression profile between the test cell population and the reference cell population indicates that the test cell population includes PNC cells. A level of expression of a PNC marker gene in a test cell population is considered altered in levels of expression if its expression level varies from the reference cell population by more than 1.0, 1.5, 2.0, 5.0, 10.0 or more fold from the expression level of the corresponding PNC marker gene in the reference cell population.
Differential gene expression between a test cell population and a reference cell population is normalized to a control nucleic acid, e.g. a housekeeping gene. For example, a control nucleic acid is one which is known not to differ depending on the cancerous or non- cancerous state of the cell. Expression levels of the control nucleic acid in the test and reference nucleic acid can be used to normalize signal levels in the compared populations. Control genes include, e.g. β-actin, glyceraldehyde 3- phosphate dehydrogenase or ribosomal protein PI.
The test cell population is compared to multiple reference cell populations. Each of the multiple reference populations may differ in the known parameter. Thus, a test cell
population may be compared to a second reference cell population known to contain, e.g., PNC cells, as well as a second reference population known to contain, e.g., non-PNC cells (normal cells). The test cell is included in a tissue type or cell sample from a subject known to contain, or to be suspected of containing, PNC cells. The test cell is obtained from a bodily tissue or a bodily fluid, e.g., biological fluid
(such as blood or sputum). For example, the test cell is purified from pancreas tissue. Preferably, the test cell population comprises an epithelial cell. The epithelial cell is from tissue known to be or suspected to be a pancreatic ductal adenocarcinoma.
Cells in the reference cell population are derived from a tissue type as similar to test cell. Optionally, the reference cell population is a cell line, e.g. a PNC cell line (positive control) or a normal non-PNC cell line (negative control). Alternatively, the control cell population is derived from a database of molecular information derived from cells for which the assayed parameter or condition is known.
The subject is preferably a mammal. The mammal can be, e.g., a human, non-human primate, mouse, rat, dog, cat, horse, or cow.
Expression of the genes disclosed herein is determined at the protein or nucleic acid level using methods known in the art. For example, Northern hybridization analysis using probes which specifically recognize one or more of these nucleic acid sequences can be used to determine gene expression. Alternatively, expression is measured using reverse- transcription-based PCR assays, e.g., using primers specific for the differentially expressed gene sequences. Expression is also determined at the protein level, i.e., by measuring the levels of polypeptides encoded by the gene products described herein, or biological activity thereof. Such methods are well known in the art and include, e.g., immunoassays based on antibodies to proteins encoded by the genes. The biological activity of the proteins encoded by the genes are also well known.
Diagnosing pancreatic cancer
PNC is diagnosed by measuring the level of expression of one or more PNC nucleic acid sequences from a test population of cells, (i.e., a patient derived biological sample). Preferably, the test cell population contains an epithelial cell, e.g., a cell obtained from pancreas tissue. Gene expression is also measured from blood or other bodily fluids such as urine. Other biological samples can be used for measuring the protein level. For example,
the protein level in the blood, serum, or pancreatic juice derived from subject to be diagnosed can be measured by immunoassay or biological assay.
Expression of one or more PNC-associated genes, e.g., PNC 1-605 is determined in the test cell or biological sample and compared to the expression of the normal control level. A normal control level is an expression profile of a PNC-associated gene typically found in a population known not to be suffering from PNC. An increase or a decrease of the level of expression in the patient derived tissue sample of the PNC-associated genes indicates that the subject is suffering from or is at risk of developing PNC. For example, an increase in expression of PNC 1-259 in the test population compared to the normal control level indicates that the subject is suffering from or is at risk of developing PNC. Conversely, a decrease in expression of PNC 260-605 in the test population compared to the normal control level indicates that the subject is suffering from or is at risk of developing PNC.
When one or more of the PNC-associated genes are altered in the test population compared to the normal control level indicates that the subject suffers from or is at risk of developing PNC. For example, at least 1%, 5%, 25%, 50%, 60%, 80%, 90% or more of the panel of PNC-associated genes (PNC 1-259, PNC 260-605, or PNC 1-605) are altered.
Predicting prognosis of PNC
The present invention provides a method for predicting prognosis of PNC in a subject, the method comprising the steps of: (a) detecting an expression level of one or more marker genes in a specimen collected from a subject to be predicted, wherein the one or more marker genes are selected from the group consisting of PNC 850-866, 894-906; and (b) comparing the expression level of the one or more marker genes to that of a early recurrence cases and late recurrence cases; and (c) when the expression level of one or marker genes is close to that of the early recurrence case, determining the subject to be at a risk of having recurrence of PNC and when the expression level of one or marker genes is close to that of the late recurrence case, determining the risk of the subject of having recurrence of PNC to be low. In the present invention, marker gene(s) for prediction of prognosis of PNC may be at least one gene selected from the group consisting of PNC 850-933 ; 84 genes shown in Tableδ. The nucleotide sequences of the genes and amino acid sequences encoded thereby are known
in the art. See Table 8 for the Accession Numbers of the genes.
According to the present invention, prediction of prognosis comprises prediction of probability for recurrence of PNC. When recurrence of PNC is observed within 12 month after surgery, the subject is determined to have poor prognosis. In one embodiment, the expression levels of multiple marker genes selected from the group of PNC 850-866, 894-906 can be measured for the prediction. Preferably, the 30 genes consisting of top 17 genes (ARGBP2, CBARAl, EEF1G, LCAT, RPL23A, RPL17, ATP1A1, QARS, BZRP, TUFM, SERPINA4, SCAP, HK1, RPS11, SYNGR2, FLOT2, PSMB4) of up-regulated in late recurrence cases genes and top 13 genes of up-regulated in early recurrence cases genes (MTMR1, HT010, NPD002, YME1L1, CCT6A, HSPD1, TIMM9, GRB14, FLJ10803, LAMP1, MLLT4, CTSB, RALY) of Table 8 are useful for the prediction. In the present method, the specimen is collected from a subject. Preferable specimen include pancreatic tissue derived from patient of pancreatic cancer. Methods for measuring the expression level of marker genes are well-known in the art. For example, DNA array is useful for measuring the expression level of multiple marker genes. According to the present invention, first, the expression level of each marker genes in a specimen is measured and then compared to that of early recurrence cases and late recurrence cases. The expression level of the marker genes of each of the cases can be measured prior to the comparison of the expression level. Then, based on the above comparison, when the expression level of one or marker genes is close to that of the early recurrence case, determining the subject to be at a risk of having recurrence of PNC and when the expression level of one or marker genes is close to that of the late recurrence case, determining the risk of the subject of having recurrence of PNC to be low. In the present invention, the recurrence of PNC can be predicted using prediction score that may be calculated by statistical methods. Methods for calculating prediction score is well- known in the art (T.R. Golub et al., Science 286, 531-7, 1999 ; TJ. MacDonald et al., Nat.
Genet, 29, 143-52, 2001). Furthermore, prediction of recurrence using prediction score in the present invention may be also performed according to the method disclosed in the Example.
Identifying Agents that inhibit or enhance PNC-associated gene expression
An agent that inhibits the expression or activity of a PNC-associated gene is identified by contacting a test cell population expressing a PNC-associated up-regulated gene with a test agent and determining the expression level of the PNC-associated gene. A decrease in expression in the presence of the agent compared to the normal control level (or compared to
the level in the absence of the test agent) indicates the agent is an inhibitor of a PNC- associated up-regulated gene and useful to inhibit PNC.
Alternatively, an agent that enhances the expression or activity of a PNC-associated down-regulated gene is identified by contacting a test cell population expressing a PNC- associated gene with a test agent and determining the expression level or activity of the PNC- associated down-regulated gene. An increase of expression or activity compared to a normal control expression level or activity of the PNC-associated gene indicates that the test agent augments expression or activity of the PNC-associated down-regulated gene.
The test cell population is any cell expressing the PNC-associated genes. For example, the test cell population contains an epithelial cell, such as a cell is or derived from pancreas tissue. For example, the test cell is an immortalized cell line derived from an adenocarcinoma cell. Alternatively, the test cell is a cell, which has been transfec ted with a PNC-associated gene or which has been transfected with a regulatory sequence (e.g. promoter sequence) from a PNC-associated gene operably linked to a reporter gene. Assessing efficacy of treatment of PNC in a subject
The differentially expressed PNC-associated gene identified herein also allow for the course of treatment of PNC to be monitored. In this method, a test cell population is provided from a subject undergoing treatment for PNC. If desired, test cell populations are obtained from the subject at various time points before, during, or after treatment. Expression of one or more of the PNC-associated gene, in the cell population is then determined and compared to a reference cell population which includes cells whose PNC state is known. The reference cells have not been exposed to the treatment.
If the reference cell population contains no PNC cells, a similarity in expression between PNC-associated gene in the test cell population and the reference cell population indicates that the treatment is efficacious. However, a difference in expression between PNC- associated gene in the test population and a normal control reference cell population indicates a less favorable clinical outcome or prognosis.
By "efficacious" is meant that the treatment leads to a reduction in expression of a pathologically up-regulated gene, increase in expression of a pathologically down-regulated gene or a decrease in size, prevalence, or metastatic potential of pancreatic ductal adenocarcinoma in a subject. When treatment is applied prophylac tically, "efficacious" means that the treatment retards or prevents a pancreatic tumor from forming or retards,
prevents, or alleviates a symptom of clinical PNC. Assessment of pancreatic tumors is made using standard clinical protocols.
Efficaciousness is determined in association with any known method for diagnosing or treating PNC. PNC is diagnosed for example, by identifying symptomatic anomalies, e.g., weight loss, abdominal pain, back pain, anorexia, nausea, vomiting and generalized malaise, weakness, and jaundice.
Selecting a therapeutic agent for treating PNC that is appropriate for a particular individual
Differences in the genetic makeup of individuals can result in differences in their relative abilities to metabolize various drugs. An agent that is metabolized in a subject to act as an anti-PNC agent can manifest itself by inducing a change in gene expression pattern in the subject's cells from that characteristic of a cancerous state to a gene expression pattern characteristic of a non-cancerous state. Accordingly, the differentially expressed PNC- associated gene disclosed herein allow for a putative therapeutic or prophylactic inhibitor of PNC to be tested in a test cell population from a selected subject in order to determine if the agent is a suitable inhibitor of PNC in the subject.
To identify an inhibitor of PNC, that is appropriate for a specific subject, a test cell population from the subject is exposed to a therapeutic agent, and the expression of one or more of PNC 1-605 genes is determined.
The test cell population contains a PNC cell expressing a PNC-associated gene. Preferably, the test cell is an epithelial cell. For example a test cell population is incubated in the presence of a candidate agent and the pattern of gene expression of the test sample is measured and compared to one or more reference profiles, e.g., a PNC reference expression profile or a non-PNC reference expression profile.
A decrease in expression of one or more of PNC 1-259 or an increase in expression of one or more of PNC 260-605 in a test cell population relative to a reference cell population containing PNC is indicative that the agent is therapeutic.
The test agent can be any compound or composition. For example, the test agents are immunomodulatory agents.
Screening assays for identifying therapeutic agents The differentially expressed genes disclosed herein can also be used to identify candidate therapeutic agents for treating PNC. The method is based on screening a candidate
therapeutic agent to determine if it converts an expression profile of PNC 1-605 characteristic of a PNC state to a pattern indicative of a non-PNC state.
In the method, a cell is exposed to a test agent or a combination of test agents (sequentially or consequentially) and the expression of one or more PNC 1-605 in the cell is measured. The expression profile of the PNC-associated gene in the test population is compared to expression level of the PNC-associated gene in a reference cell population that is not exposed to the test agent.
An agent effective in stimulating expression of under-expressed genes, or in suppressing expression of over-expressed genes is deemed to lead to a clinical benefit such compounds are further tested for the ability to prevent pancreatic ductal adenocarcmomal growth in animals or test subjects.
In a further embodiment, the present invention provides methods for screening candidate agents which are potential targets in the treatment of PNC. As discussed in detail above, by controlling the expression levels or activities of marker genes, one can control the onset and progression of PNC. Thus, candidate agents, which are potential targets in the treatment of PNC, can be identified through screenings that use the expression levels and activities of marker genes as indices. In the context of the present invention, such screening may comprise, for example, the following steps: a) contacting a test compound with a polypeptide encoded by PNC 1-605; b) detecting the binding activity between the polypeptide and the test compound; and c) selecting a compound that binds to the polypeptide. Alternatively, the screening method of the present invention may comprise the following steps: a) contacting a candidate compound with a cell expressing one or more marker genes, wherein the one or more marker genes is selected from the group consisting of PNC
1-605; and b) selecting a compound that reduces the expression level of one or more marker genes selected from the group consisting of PNC 1-259, or elevates the expression level of one or more marker genes selected from the group consisting of PNC 260-605. Cells expressing a marker gene include, for example, cell lines established from PNC; such cells can be used for the above screening of the present invention.
Alternatively, the screening method of the present invention may comprise the
following steps: a) contacting a test compound with a polypeptide encoded by selected from the group consisting of PNC 1-605; b) detecting the biological activity of the polypeptide of step (a); and c) selecting a compound that suppresses the biological activity of the polypeptide encoded by PNC 1-259 in comparison with the biological activity detected in the absence of the test compound, or enhances the biological activity of the polypeptide encoded by PNC 260-605 in comparison with the biological activity detected in the absence of the test compound. A protein required for the screening can be obtained as a recombinant protein using the nucleotide sequence of the marker gene. Based on the information of the marker gene, one skilled in the art can select any biological activity of the protein as an index for screening and a measurement method based on the selected biological activity.
Alternatively, the screening method of the present invention may comprise the following steps: a) contacting a candidate compound with a cell into which a vector comprising the transcriptional regulatory region of one or more marker genes and a reporter gene that is expressed under the control of the transcriptional regulatory region has been introduced, wherein the one or more marker genes are selected from the group consisting of PNC 1-605 b) measuring the activity of said reporter gene; and c) selecting a compound that reduces the expression level of said reporter gene when said marker gene is an up-regulated marker gene selected from the group consisting of PNC 1-259 or that enhances the expression level of said reporter gene when said marker gene is a down-regulated marker gene selected from the group consisting of
PNC 260-605, as compared to a control. Suitable reporter genes and host cells are well known in the art. The reporter construct required for the screening can be prepared by using the transcriptional regulatory region of a marker gene. When the transcriptional regulatory region of a marker gene has been known to those skilled in the art, a reporter construct can be prepared by using the previous sequence information. When the transcriptional regulatory region of a marker gene remains unidentified, a nucleotide segment containing the transcriptional regulatory region can be
isolated from a genome library based on the nucleotide sequence information of the marker gene.
The compound isolated by the screening is a candidate for drugs that inhibit the activity of the protein encoded by marker genes and can be applied to the treatment or prevention of pancreatic cancer.
Moreover, compound in which a part of the structure of the compound inhibiting the activity of proteins encoded by marker genes is converted by addition, deletion and/or replacement are also included in the compounds obtainable by the screening method of the present invention. When administrating the compound isolated by the method of the invention as a pharmaceutical for humans and other mammals, such as mice, rats, guinea-pigs, rabbits, cats, dogs, sheep, pigs, cattle, monkeys, baboons, and chimpanzees, the isolated compound can be directly administered or can be formulated into a dosage form using known pharmaceutical preparation methods. For example, according to the need, the drugs can be taken orally, as sugar-coated tablets, capsules, elixirs and microcapsules, or non-orally, in the form of injections of sterile solutions or suspensions with water or any other pharmaceutically acceptable liquid. For example, the compounds can be mixed with pharmaceutically acceptable carriers or media, specifically, sterilized water, physiological saline, plant-oils, emulsifiers, suspending agents, surfactants, stabilizers, flavoring agents, excipients, vehicles, preservatives, binders, and such, in a unit dose form required for generally accepted drug implementation. The amount of active ingredients in these preparations makes a suitable dosage within the indicated range acquirable.
Examples of additives that can be mixed to tablets and capsules are, binders such as gelatin, corn starch, tragacanth gum and arabic gum; excipients such as crystalline cellulose; swelling agents such as corn starch, gelatin and alginic acid; lubricants such as magnesium stearate; sweeteners such as sucrose, lactose or saccharin; and flavoring agents such as peppermint, Gaultheria adenothrix oil and cherry. When the unit-dose form is a capsule, a liquid carrier, such as an oil, can also be further included in the above ingredients. Sterile composites for injections can be formulated following normal drug implementations using vehicles such as distilled water used for injections.
Physiological saline, glucose, and other isotonic liquids including adjuvants, such as D-sorbitol, D-mannnose, D-mannitol, and sodium chloride, can be used as aqueous solutions
for injections. These can be used in conjunction with suitable solubilizers, such as alcohol, specifically ethanol, polyalcohols such as propylene glycol and polyethylene glycol, non-ionic surfactants, such as Polysorbate 80 (TM) and HCO-50.
Sesame oil or Soy-bean oil can be used as a oleaginous liquid and may be used in conjunction with benzyl benzoate or benzyl alcohol as a solubilizer and may be formulated with a buffer, such as phosphate buffer and sodium acetate buffer; a pain-killer, such as procaine hydrochloride; a stabilizer, such as benzyl alcohol andphenol; and an anti-oxidant. The prepared injection may be filled into a suitable ampule.
Methods well known to one skilled in the art may be used to administer the pharmaceutical composition of the present inevntion to patients, for example as intraarterial, intravenous, or percutaneous injections and also as intranasal, transbronchial, intramuscular or oral administrations. The dosage and method of administration vary according to the body- weight and age of a patient and the administration method; however, one skilled in the art can routinely select a suitable metod of administration. If said compound is encodable by a DNA, the DNA can be inserted into a vector for gene therapy and the vector administered to a patient to perform the therapy. The dosage and method of administration vary according to the body- weight, age, and symptoms of the patient but one skilled in the art can suitably select them.
For example, although the dose of a compound that binds to the protein of the present invention and regulates its activity depends on the symptoms, the dose is about 0.1 mg to about 100 mg per day, preferably about 1.0 mg to about 50 mg per day and more preferably about 1.0 mg to about 20 mg per day, when administered orally to a normal adult (weight 60 kg).
When administering parenterally, in the form of an injection to a normal adult (weight 60 kg), although there are some differences according to the patient, target organ, symptoms and method of administration, it is convenient to intravenously inject a dose of about 0.01 mg to about 30 mg per day, preferably about 0.1 to about 20 mg per day and more preferably about 0.1 to about 10 mg per day. Also, in the case of other animals too, it is possible to administer an amount converted to 60 kgs of body- weight. Screening assays for identifying therapeutic agents for malignant pancreatic cancer
The present invention provides target molecules for treating or preventing malignant pancreatic cancer. In the present invention, malignant cancer includes cancers having
properties such as follows:
- local invasion;
- aggressive proliferatio ; and
- metastasis. Therefore, according to the present invention, malignant pancreatic cancer includes pancreatic cancer with metastasis. Screening assay for malignant PNC of the present invention can be performed according to the mehtod for PNC described above using marker genes for malignant pancreatic cancer.
In the present invention, marker genes selected from the group consisting of PNC 606- 681, and 682-849 are useful for the screening. 76 genes shown in Table 6 (PNC 606-681) were associated with lymph node metastasis. Among the genes, 35 genes (PNC 606-640) were relatively up-regulated and 41 genes (PNC 641-681) were down-regulated in node- positive tumors (Figure 3). In addition, 168 genes (PNC 682-849) showed unique altered expression patterns in pancreatic cells with liver metastasis (Table 7) wherein 60 of the genes(PNC 682-741) were relatively up-regulated (Figure 4). An agent suppressing the activity or expression of these up-regulated genes obtained by the present invention are useful for treating or preventing malignant pancreatic cancer with lymph-node metastasis or liver metastasis. Alternatively, an agent enhancing the activity or expression of the down- regulated genes obtained by the present invention are also useful for treating or preventing malignant pancreatic cancer.
Furthermore, the present invention provides target molecules for treating or preventing recurrence of pancreatic cancer. Herein, recurrence of pancreatic cancer indicates recurrence of cancer in pancreas after surgery. For example, the recurrence of cancer within 12 month after surgery can be predicted by the invention. According to the present invention, early recurrence includes the recurrence within 12 month after surgery, and when no recurrence can be observed within 12 month after surgery in a case, the case is considered to be a pancreatic cancer with "late recurrence". 84 genes (PNC 850-933) shown in Table 8 are useful as the marker genes for the screening of the present invention. Among them, the genes shown in Figure 5A-1 are up-regulated in early recurrence cases(PNC 894-933), and the genes shown in Figure 5A-2 are up-regulated in late recurrence cases(PNC 850-893). Therefore, an agent suppressing the up-regulated genes in early recurrence cases is useful for treating or
preventing recurrence. Alternatively, an agent enhancing the up-regulated genes in late recurrence cases is also useful for treating or preventing recurrence.
Assessing the prognosis of a subject with pancreatic cancer
Also provided is a method of assessing the prognosis of a subject with PNC by comparing the expression of one or more PNC-associated gene in a test cell population to the expression of the genes in a reference cell population derived from patients over a spectrum of disease stages. By comparing gene expression of one or more PNC-associated gene in the test cell population and the reference cell population(s), or by comparing the pattern of gene expression over time in test cell populations derived from the subject, the prognosis of the subject can be assessed.
A decrease in expression of one or more of PNC 260-605 compared to a normal control or an increase of expression of one or more of PNC 1-259 compared to a normal control indicates less favorable prognosis. A similar expression of one or more of PNC 1-605 indicates a more favorable prognosis compared to nomal control indicates a more favorable prognosis for the subject. Preferably, the prognosis of a subject can be assessed by comparing the expression profile of PNC 1-605. The classification score (CS) may be use for the comparing the expression profile.
Kits
The invention also includes a PNC-detection reagent, e.g., a nucleic acid that specifically binds to or identifies one or more PNC nucleic acids such as oligonucleotide sequences, which are complementary to a portion of a PNC nucleic acid or antibodies which bind to proteins encoded by a PNC nucleic acid. The reagents are packaged together in the form of a kit. The reagents are packaged in separate containers, e.g., a nucleic acid or antibody (either bound to a solid matrix or packaged separately with reagents for binding them to the matrix), a control reagent (positive and/or negative), and/or a detectable label. Instructions (e.g., written, tape, VCR, CD-ROM, etc.) for carrying out the assay are included in the kit. The assay format of the kit is a Northern hybridization or a sandwich ELISA known in the art.
For example, PNC detection reagent is immobilized on a solid matrix such as a porous strip to form at least one PNC detection site. The measurement or detection region of the porous strip may include a plurality of sites containing a nucleic acid. A test strip may also
contain sites for negative and/or positive controls. Alternatively, control sites are located on a separate strip from the test strip. Optionally, the different detection sites may contain different amounts of immobilized nucleic acids, i.e., a higher amount in the first detection site and lesser amounts in subsequent sites. Upon the addition of test sample, the number of sites displaying a detectable signal provides a quantitative indication of the amount of PNC present in the sample. The detection sites may be configured in any suitably detectable shape and are typically in the shape of a bar or dot spanning the width of a teststrip.
Alternatively, the kit contains a nucleic acid substrate array comprising one or more nucleic acids. The nucleic acids on the array specifically identify one or more nucleic acid sequences represented by PNC 1-605. The expression of 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 40 or 50 or more of the nucleic acids represented by PNC 1-605 are identified by virtue of the level of binding to an array test strip or chip. The substrate array can be on, e.g., a. solid substrate, e.g., a "chip" as described in U.S. Patent No.5,744,305.
Arrays and pluralities The invention also includes a nucleic acid substrate array comprising one or more nucleic acids. The nucleic acids on the array specifically correspond to one or more nucleic acid sequences represented by PNC 1-605. The level of expression of 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 40 or 50 or more of the nucleic acids represented by PNC 1-605 are identified by detecting nucleic acid binding to the array. The invention also includes an isolated plurality (i.e., a mixture if two or more nucleic acids) of nucleic acids. The nucleic acids are in a liquid phase or a solid phase, e.g., immobilized on a solid support such as a nitrocellulose membrane. The plurality includes one or more of the nucleic acids represented by PNC 1-605. In various embodiments, the plurality includes 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 40 or 50 or more of the nucleic acids represented by PNC 1 -605.
Methods of inhibiting pancreatic cancer
The invention provides a method for treating or alleviating a symptom of PNC in a subject by decreasing expression or activity of PNC 1-259 or increasing expression or activity of PNC 260-605. Therapeutic compounds are administered prophylactically or therapeutically to subject suffering from or at risk of (or susceptible to) developing PNC.
Such subjects are identified using standard clinical methods or by detecting an aberrant level
of expression or activity of PNC 1-605. Therapeutic agents include inhibitors of cell cycle regulation, cell proliferation, and protein kinase activity.
The therapeutic method includes increasing the expression, or function, or both of one or more gene products of genes whose expression is decreased ("under-expressed genes") in a PNC cell relative to normal cells of the same tissue type from which the PNC cells are derived. In these methods, the subject is treated with an effective amount of a compound, which increases the amount of one or more of the under-expressed genes in the subject. Administration can be systemic or local. Therapeutic compounds include a polypeptide product of an under-expressed gene, or a biologically active fragment thereof a nucleic acid encoding an under-expressed gene and having expression control elements permitting expression in the PNC cells; for example an agent which increases the level of expression of such gene endogenous to the PNC cells (i.e., which up-regulates expression of the under- expressed gene or genes). Administration of such compounds counters the effects of aberrantly-under expressed of the gene or genes in the subject's pancreas cells and improves the clinical condition of the subject.
The method also includes decreasing the expression, or function, or both, of one or more gene products of genes whose expression is aberrantly increased ("over-expressed gene") in pancreas cells. Expression is inhibited in any of several ways known in the art. For example, expression is inhibited by administering to the subject a nucleic acid that inhibits, or antagonizes, the expression of the over-expressed gene or genes, e.g., an antisense oligonucleotide or small interfering RNA which disrupts expression of the over-expressed gene or genes.
As noted above, antisense nucleic acids corresponding to the nucleotide sequence of PNC 1-259 can be used to reduce the expression level of the PNC 1-259. Antisense nucleic acids corresponding to PNC 1-259 that are up-regulated in pancreatic cancer are useful for the treatment of pancreatic cancer. Specifically, the antisense nucleic acids of the present invention may act by binding to the PNC 1-259 or mRNAs corresponding thereto, thereby inhibiting the transcription or translation of the genes, promoting the degradation of the mRNAs, and/or inhibiting the expression of proteins encoded by the PNC 1-259, finally inhibiting the function of the proteins. The term "antisense nucleic acids" as used herein encompasses both nucleotides that are entirely complementary to the target sequence and those having a mismatch of one or more nucleotides, so long as the antisense nucleic acids
can specifically hybridize to the target sequences. For example, the antisense nucleic acids of the present invention include polynucleotides that have a homology of at least 70% or higher, preferably at 80% or higher, more preferably 90% or higher, even more preferably 95% or higher over a span of at least 15 continuous nucleotides. Algorithms known in the art can be used to determine the homology.
The antisense nucleic acid derivatives of the present invention act on cells producing the proteins encoded by marker genes by binding to the DNAs or mRNAs encoding the proteins, inhibiting their transcription or translation, promoting the degradation of the mRNAs, and inhibiting the expression of the proteins, thereby resulting in the inhibition of the protein function.
An antisense nucleic acid derivative of the present invention can be made into an external preparation, such as a liniment or a poultice, by mixing with a suitable base material which is inactive against the derivative.
Also, as needed, the derivatives can be formulated into tablets, powders, granules, capsules, liposome capsules, injections, solutions, nose-drops and freeze-drying agents by adding excipients, iso tonic agents, solubilizers, stabilizers, preservatives, pain-killers, and such. These can be prepared by following known methods.
The antisense nucleic acids derivative is given to the patient by directly applying onto the ailing site or by injecting into a blood vessel so that it will reach the site of ailment. An antisense-mounting medium can also be used to increase durability and membrane- permeability. Examples are, liposomes, poly-L-lysine, lipids, cholesterol, lipofectin or derivatives of these.
The dosage of the antisense nucleic acid derivative of the present invention can be adjusted suitably according to the patient's condition and used in desired amounts. For example, a dose range of 0.1 to 100 mg/kg, preferably 0.1 to 50 mg/kg can be administered. The antisense nucleic acids of the invention inhibit the expression of the protein of the invention and is thereby useful for suppressing the biological activity of a protein of the invention. Also, expression-inhibitors, comprising the antisense nucleic acids of the invention, are useful since they can inhibit the biological activity of a protein of the invention. The antisense nucleic acids of present invention include modified oligonucleotides.
For example, thioated nucleotides may be used to confer nuclease resistance to an oligonucleotide.
Also, a siRNA against marker gene can be used to reduce the expression level of the marker gene. By the term "siRNA" is meant a double stranded RNA molecule which prevents translation of a target mRNA. Standard techniques of introducing siRNA into the cell are used, including those in which DNA is a template from which RNA is transcribed. In the context of the present invention, the siRNA comprises a sense nucleic acid sequence and an anti-sense nucleic acid sequence against an up-regulated marker gene, such as PNC 1-259. The siRNA is constructed such that a single transcript has both the sense and complementary antisense sequences from the target gene, e.g., a hairpin.
The method is used to alter the expression in a cell of an up-regulated, e.g., as a result of malignant transformation of the cells. Binding of the siRNA to a transcript corresponding to one of the PNC 1-259 in the target cell results in a reduction in the protein production by the cell. The length of the oligonucleotide is at least 10 nucleotides and may be as long as the naturally-occurring transcript. Preferably, the oligonucleotide is 19-25 nucleotides in length. Most preferably, the oligonucleotide is less than 75, 50, 25 nucleotides in length. The nucleotide sequence of the siRNAs were designed using an siRNA design computer program available from the Ambion website (http://www.ambion.com techlib/ misc/siRNA_finder.html). The computer program selects nucleotide sequences for siRNA synthesis based on the following protocol. Selection of siRNA Target Sites: 1. Beginning with the AUG start codon of the object transcript, scan downstream for AA dinucleotide sequences. Record the occurrence of each AA and the 3' adjacent 19 nucleotides as potential siRNA target sites. Tuschl, et al. recommend against designing siRNA to the 5* and 3' untranslated regions (UTRs) and regions near the start codon (within 75 bases) as these may be richer in regulatory protein binding sites. UTR-binding proteins and/or translation initiation complexes may interfere with binding of the siRNA endonuclease complex.
2. Compare the potential target sites to the human genome database and eliminate from consideration any target sequences with significant homology to other coding sequences. The homology search can be performed using BLAST, which can be found on the NCBI server at: www.ncbi.nlm.nih.gov/BLAST/
3. Select qualifying target sequences for synthesis. At Ambion, preferably several target sequences can be selected along the length of the gene to evaluate.
The antisense oligonucleotide or siRNA of the invention inhibit the expression of the polypeptide of the invention and is thereby useful for suppressing the biological activity of the polypeptide of the invention. Also, expression-inhibitors, comprising the antisense oligonucleotide or siRNA of the invention, are useful in the point that they can inhibit the biological activity of the polypeptide of the invention. Therefore, a composition comprising the antisense oligonucleotide or siRNA of the present invention is useful in treating a pancreatic cancer.
Alternatively, function of one or more gene products of the over-expressed genes is inhibited by administering a compound that binds to or otherwise inhibits the function of the gene products. For example, the compound is an antibody which binds to the over-expressed gene product or gene products.
The present invention refers to the use of antibodies, particularly antibodies against a protein encoded by an up-regulated marker gene, or a fragment of the antibody. As used herein, the term "antibody" refers to an immunoglobulin molecule having a specific structure, that interacts (i.e., binds) only with the antigen that was used for synthesizing the antibody (i.e., the up-regulated marker gene product) or with an antigen closely related to it. Furthermore, an antibody may be a fragment of an antibody or a modified antibody, so long as it binds to one or more of the proteins encoded by the marker genes. For instance, the antibody fragment may be Fab, F(ab') , Fv, or single chain Fv (scFv), in which Fv fragments from H and L chains are ligated by an appropriate linker (Huston J. S. et al. Proc. Natl. Acad. Sci. U.S.A. 85:5879-5883 (1988)). More specifically, an antibody fragment may be generated by treating an antibody with an enzyme, such as papain or pepsin. Alternatively, a gene encoding the antibody fragment may be constructed, inserted into an expression vector, and expressed in an appropriate host cell (see, for example, Co M. S. et al. J. Immunol. 152:2968- 2976 (1994); Better M. and Horwitz A. H. Methods Enzymol. 178:476-496 (1989); Pluckthun A. and Skerra A. Methods Enzymol. 178:497-515 (1989); La oyi E. Methods Enzymol. 121:652-663 (1986); Rousseaux J. et al. Methods Enzymol. 121:663-669 (1986); Bird R. E. and Walker B. W. Trends Biotechnol. 9:132-137 (1991)).
An antibody may be modified by conjugation with a variety of molecules, such as polyethylene glycol (PEG). The present invention provides such modified antibodies. The modified antibody can be obtained by chemically modifying an antibody. These modification methods are conventional in the field.
Alternatively, an antibody may be obtained as a chimeric antibody, between a variable region derived from a nonhuman antibody and a constant region derived from a human antibody, or as a humanized antibody, comprising the complementarity determining region (CDR) derived from a nonhuman antibody, the frame work region (FR) derived from a human antibody, and the constant region. Such antibodies can be prepared by using known technologies.
Cancer therapies directed at specific molecular alterations that occur in cancer cells have been validated through clinical development and regulatory approval of anti-cancer drugs such as trastuzumab (Herceptin) for the treatment of advanced breast cancer, imatinib methylate (Gleevec) for chronic myeloid leukemia, gefitinib (Iressa) for non-small cell lung cancer (NSCLC), and rituximab (anti-CD20 mAb) for B-cell lymphoma and mantle cell lymphoma (Ciardiello F, Tortora G. A novel approach in the treatment of cancer: targeting the epidermal growth factor receptor. Clin Cancer Res. 2001 Oct;7(10):2958-70. Review.; Slamon DJ, Leyland- Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, Fleming T, Eiermann W, Wolter J, Pegram M, Baselga J, Norton L. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. 2001 Mar 15;344(ll):783-92.; Rehwald U, Schulz H, Reiser M, Sieber M, Staak JO, Morschhauser F, Driessen C, Rudiger T, Muller-Hermelink K, Diehl V, Engert A. Treatment of relapsed CD20+ Hodgkin lymphoma with the monoclonal antibody rituximab is effective and well tolerated: results of a phase 2 trial of the German Hodgkin Lymphoma Study Group. Blood. 2003 Jan 15;101(2):420-424.; Fang G, Kim CN, Perkins CL, Ramadevi N, Winton E, Wittmann S and Bhalla KN. (2000). Blood, 96, 2246-2253.). These drugs are clinically effective and better tolerated than traditional anti-cancer agents because they target only transformed cells. Hence, such drugs not only improve survival and quality of life for cancer patients, but also validate the concept of molecularly targeted cancer therapy. Furthermore, targeted drugs can enhance the efficacy of standard chemotherapy when used in combination with it (Gianni L. (2002). Oncology, 63 Suppl 1, 47-56.; Klejman A, Rushen L, Morrione A, Slupianek A and Skorski T. (2002). Oncogene, 21, 5868-5876.). Therefore, future cancer treatments will probably involve combining conventional drugs with target-specific agents aimed at different characteristics of tumor cells such as angiogenesis and invasiveness.
These modulatory methods are performed ex vivo or in vitro (e.g., by culturing the cell with the agent) or, alternatively, in vivo (e.g., by administering the agent to a subject).
The method involves administering a protein or combination of proteins or a nucleic acid molecule or combination of nucleic acid, molecules as therapy to counteract aberrant expression or activity of the differentially expressed genes.
Diseases and disorders that are characterized by increased (relative to a subject not suffering from the disease or disorder) levels or biological activity of the genes may be treated with therapeutics that antagonize (i.e., reduce or inhibit) activity of the over-expressed gene or genes. Therapeutics that antagonized activity are administered therapeutically or prophylactically.
Therapeutics that may be utilized include, e.g., (i) a polypeptide, or analogs, derivatives, fragments or homologs thereof of the over-expressed or under-expressed gene or genes; (ii) antibodies to the over-expressed or under-expressed gene or genes; (iii) nucleic acids encoding the over-expressed or under-expressed gene or genes; (iv) antisense nucleic acids or nucleic acids that are "dysfunctional" (i.e., due to a heterologous insertion within the nucleic acids of one or more over-expressed or under-expressed gene or genes); (v) small interfering RNA (siRNA); or (vi) modulators (i.e., inhibitors, agonists and antagonists that alter the interaction between an over/under-expressed polypeptide and its binding partner). The dysfunctional antisense molecules are utilized to "knockout" endogenous function of a polypeptide by homologous recombination (see, e.g., Capecchi, Science 244: 1288-1292 1989). 259 Diseases and disorders that are characterized by decreased (relative to a subject not suffering from the disease or disorder) levels or biological activity may be treated with therapeutics that increase (i.e., are agonists to) activity. Therapeutics that up-regulate activity may be administered in a therapeutic or prophylactic manner. Therapeutics that may be utilized include, but are not limited to, a polypeptide (or analogs, derivatives, fragments or homologs thereof) or an agonist that increases bioavailability.
Increased or decreased levels can be readily detected by quantifying peptide and/or RNA, by obtaining a patient tissue sample (e.g., from biopsy tissue) and assaying it in vitro for RNA or peptide levels, structure and/or activity of the expressed peptides (or mRNAs of a gene whose expression is altered). Methods that are well-known within the art include, but are not limited to, immunoassays (e.g., by Western blot analysis, immunoprecipitation followed by sodium dodecyl sulfate (SDS) polyacrylamide gel electrophoresis,
immunocytochemistry, etc.) and/or hybridization assays to detect expression of mRNAs (e.g., Northern assays, dot blots, in situ hybridization, etc.).
Prophylactic administration occurs prior to the manifestation of overt clinical symptoms of disease, such that a disease or disorder is prevented or, alternatively, delayed in its progression.
Therapeutic methods include contacting a cell with an agent that modulates one or more of the activities of the gene products of the differentially expressed genes. An agent that modulates protein activity includes a nucleic acid or a protein, a naturally-occurring cognate ligand of these proteins, a peptide, a peptidomimetic, or other small molecule. For example, the agent stimulates one or more protein activities of one or more of a differentially under- expressed gene.
The present invention also relates to a method of treating or preventing pancreatic cancer in a subject comprising administering to said subject a vaccine comprising a polypeptide encoded by a nucleic acid selected from the group consisting of PNC 1-259 or an immunologically active fragment of said polypeptide, or a polynucleotide encoding the polypeptide or the fragment thereof. An administration of the polypeptide induces an anti- tumor immunity in a subject. To inducing anti-tumor immunity, a polypeptide encoded by a nucleic acid selected from the group consisting of PNC 1-259 or an immunologically active fragment of said polypeptide, or a polynucleotide encoding the polypeptide is administered. The polypeptide or the immunologically active fragments thereof are useful as vaccines against PNC. In some cases the proteins or fragments thereof may be administered in a form bound to the T cell recepor (TCR) or presented by an antigen presenting cell (APC), such as macrophage, dendritic cell (DC), or B-cells. Due to the strong antigen presenting ability of DC, the use of DC is most preferable among the APCs. In the present invention, vaccine against PNC refers to a substance that has the function to induce anti-tumor immunity upon inoculation into animals. According to the present invention, polypeptides encoded by PNC 1-259 or fragments thereof were suggested to be HLA-A24 or HL A- A* 0201 restricted epitopes peptides that may induce potent and specific immune response against PNC cells expressing PNC 1-259. Thus, the present invention also encompasses method of inducing anti-tumor immunity using the polypeptides. In general, anti-tumor immunity includes immune responses such as follows: - induction of cytotoxic lymphocytes against tumors,
- induction of antibodies that recognize tumors, and
- induction of anti-tumor cytokine production.
Therefore, when a certain protein induces any one of these immune responses upon inoculation into an animal, the protein is decided to have anti-tumor immunity inducing effect. The induction of the anti-tumor immunity by a protein can be detected by observing in vivo or in vitro the response of the immune system in the host against the protein.
For example, a method for detecting the induction of cytotoxic T lymphocytes is well known. A foreign substance that enters the living body is presented to T cells and B cells by the action of antigen presenting cells (APCs). T cells that respond to the antigen presented by APC in antigen specific manner differentiate into cytotoxic T cells (or cytotoxic T lymphocytes; CTLs) due to stimulation by the antigen, and then proliferate (this is referred to as activation of T cells). Therefore, CTL induction by a certain peptide can be evaluated by presenting the peptide to T cell by APC, and detecting the induction of CTL. Furthermore, APC has the effect of activating CD4+ T cells, CD8+ T cells, macrophages, eosinophils, and NK cells. Since CD4+ T cells and CD 8+ T cells are also important in anti-tumor immunity, the anti-tumor immunity inducing action of the peptide can be evaluated using the activation effect of these cells as indicators.
A method for evaluating the inducing action of CTL using dendritic cells (DCs) as APC is well known in the art. DC is a representative APC having the strongest CTL inducing action among APCs. In this method, the test polypeptide is initially contacted with DC, and then this DC is contacted with T cells. Detection of T cells having cytotoxic effects against the cells of interest after the contact with DC shows that the test polypeptide has an activity of inducing the cytotoxic T cells. Activity of CTL against tumors can be detected, for example, using the lysis of 51Cr-labeled tumor cells as the indicator. Alternatively, the method of evaluating the degree of tumor cell damage using 3H-thymidine uptake activity or LDH (lactose dehydrogenase)-release as the indicator is also well known.
Apart from DC, peripheral blood mononuclear cells (PBMCs) may also be used as the APC. The induction of CTL is reported that it can be enhanced by culturing PBMC in the presence of GM-CSF and IL-4. Similarly, CTL has been shown to be induced by culturing PBMC in the presence of keyhole limpet hemocyanin (KLH) and IL-7.
The test polypeptides confirmed to possess CTL inducing activity by these methods are polypeptides having DC activation effect and subsequent CTL inducing activity.
Therefore, polypeptides that induce CTL against tumor cells are useful as vaccines against tumors. Furthermore, APC that acquired the ability to induce CTL against tumors by contacting with the polypeptides are useful as vaccines against tumors. Furthermore, CTL that acquired cytotoxicity due to presentation of the polypeptide antigens by APC can be also used as vaccines against tumors. Such therapeutic methods for tumors using anti-tumor immunity due to APC and CTL are referred to as cellular immunotherapy.
Generally, when using a polypeptide for cellular immunotherapy, efficiency of the CTL-induction is known to increase by combining a plurality of polypeptides having different structures and contacting them with DC. Therefore, when stimulating DC with protein fragments, it is advantageous to use a mixture of multiple types of fragments.
Alternatively, the induction of anti-tumor immunity by a polypeptide can be confirmed by observing the induction of antibody production against tumors. For example, when antibodies against a polypeptide are induced in a laboratory animal immunized with the polypeptide, and when growth of tumor cells is suppressed by those antibodies, the polypeptide can be determined to have an ability to induce anti-tumor immunity.
Anti-tumor immunity is induced by administering the vaccine of this invention, and the induction of anti-tumor immunity enables treatment and prevention of PNC. Therapy against cancer or prevention of the onset of cancer includes any of the steps, such as inhibition of the growth of cancerous cells, involution of cancer, and suppression of occurrence of cancer. Decrease in mortality of individuals having cancer, decrease of tumor markers in the blood, alleviation of detectable symptoms accompanying cancer, and such are also included in the therapy or prevention of cancer. Such therapeutic and preventive effects are preferably statistically significant. For example, in observation, at a significance level of 5% or less, wherein the therapeutic or preventive effect of a vaccine against cell proliferative diseases is compared to a control without vaccine administration. For example, Student's t- test, the Mann- Whitney U-test, or ANOVA may be used for statistical analyses.
The above-mentioned protein having immunological activity or a vector encoding the protein may be combined with an adjuvant. An adjuvant refers to a compound that enhances the immune response against the protein when administered together (or successively) with the protein having immunological activity. Examples of adjuvants include cholera toxin, salmonella toxin, alum, and such, but are not limited thereto. Furthermore, the vaccine of this invention may be combined appropriately with a pharmaceutically acceptable
carrier. Examples of such carriers are sterilized water, physiological saline, phosphate buffer, culture fluid, and such. Furthermore, the vaccine may contain as necessary, stabilizers, suspensions, preservatives, surfactants, and such. The vaccine is administered systemically or locally. Vaccine administration may be performed by single administration, or boosted by multiple administrations.
When using APC or CTL as the vaccine of this invention, tumors can be treated or prevented, for example, by the ex vivo method. More specifically, PBMCs of the subject receiving treatment or prevention are collected, the cells are contacted with the polypeptide ex vivo, and following the induction of APC or CTL, the cells may be administered to the subject. APC can be also induced by introducing a vector encoding the polypeptide into PBMCs ex vivo. APC or CTL induced in vitro can be cloned prior to administration. By cloning and growing cells having high activity of damaging target cells, cellular immunotherapy can be performed more effectively. Furthermore, APC and CTL isolated in this manner may be used for cellular immunotherapy not only against individuals from whom the cells are derived, but also against similar types of tumors from other individuals. Furthermore, a pharmaceutical composition for treating or preventing a cell proliferative disease, such as cancer, comprising a pharmaceutically effective amount of the polypeptide of the present invention is provided. The pharmaceutical composition may be used for raising anti tumor immunity.
Methods for inhibiting development or recurrence of malignant pancreatic cancer
The present invention provides a method for treating or preventing malignant pancreatic cancer, or recurrence of pancreatic cancer by increasing or decreasing the expression or activity of marker genes. According to the present invention, the marker genes that can be used for the treatment or prevention of malignant pancreatic cancer are PNC 606- 681 (Table 6) and PNC 682-849 (Table 7). Alternatively, the marker genes for treating or preventing the recurrence are PNC 850-933 (Table 8). 35 genes of the PNC 606-640 (Figure 3) and 60 genes of PNC 682-741 (Figure 4) are up-regulated in the malignant cancer cells and 40 genes of PNC 894-933 are up-regulated in the early recurrence cases. Antisense- nucleotides and siRNAs against any one of the up-regulated marker genes are useful for suppressing the expression of the up-regulated genes. Alternatively, the activity of a protein encoded by any one of the up-regulated marker genes can be inhibited by administering an antibody that binds to the protein. Furthermore, a vaccine against the protein encoded by any
one of the up-regulated marker genes is useful for inducing anti tumor immunity. Moreover, administeration of the down regulated genes or proteins encoded thereby is also effective for treating or preventing malignant pancreatic cancer or the recurrence.
Pharmaceutical compositions for inhibiting PNC, malignant PNC, or recurrence of PNC. Pharmaceutical formulations include those suitable for oral, rectal, nasal, topical
(including buccal and sub-lingual), vaginal or parenteral (including intramuscular, subcutaneous and intravenous) administration, or for administration by inhalation or insufflation. Preferably, administration is intravenous. The formulations are optionally packaged in discrete dosage units. Pharmaceutical formulations suitable for oral administration include capsules, cachets or tablets, each containing a predetermined amount of the active ingredient. Formulations also include powders, granules or solutions, suspensions or emulsions. The active ingredient is optionally administered as a bolus electuary or paste. Tablets and capsules for oral administration may contain conventional excipients such as binding agents, fillers, lubricants, disintegrant or wetting agents. A tablet may be made by compression or molding, optionally with one or more formulational ingredients. Compressed tablets may be prepared by compressing in a suitable machine the active ingredients in a free-flowing form such as a powder or granules, optionally mixed with a binder, lubricant, inert diluent, lubricating, surface active or dispersing agent. Molded tablets may be made by molding in a suitable machine a mixture of the powdered compound moistened with an inert liquid diluent. The tablets may be coated according to methods well known in the art. Oral fluid preparations may be in the form of, for example, aqueous or oily suspensions, solutions, emulsions, syrups or elixirs, or may be presented as a dry product for constitution with water or other suitable vehicle before use. Such liquid preparations may contain conventional additives such as suspending agents, emulsifying agents, non-aqueous vehicles (which may include edible oils), or preservatives. The tablets may optionally be formulated so as to provide slow or controlled release of the active ingredient therein. A package of tablets may contain one tablet to be taken on each of the month.
Formulations for parenteral administration include aqueous and non-aqueous sterile injection solutions which may contain anti-oxidants, buffers, bacteriostats and solutes which render the formulation isotonic with the blood of the intended recipient; and aqueous and non- aqueous sterile suspensions which may include suspending agents and thickening agents. The
formulations may be presented in unit dose or multi-dose containers, for example sealed ampoules and vials, and may be stored in a freeze-dried (lyophilized) condition requiring only the addition of the sterile liquid carrier, for example, saline, water-for-injection, immediately prior to use. Alternatively, the formulations may be presented for continuous infusion. Extemporaneous injection solutions and suspensions may be prepared from sterile powders, granules and tablets of the kind previously described.
Formulations for rectal administration include suppositories with standard carriers such as cocoa butter or polyethylene glycol. Formulations for topical administration in the mouth, for example buccally or sublingually, include lozenges, which contain the active ingredient in a flavored base such as sucrose and acacia or tragacanth, and pastilles comprising the active ingredient in a base such as gelatin and glycerin or sucrose and acacia. For intra-nasal administration the compounds of the invention may be used as a liquid spray or dispersible powder or in the form of drops. Drops may be formulated with an aqueous or non-aqueous base also comprising one or more dispersing agents, solubilizing agents or suspending agents.
For administration by inhalation the compounds are conveniently delivered from an insufflator, nebulizer, pressurized packs or other convenient means of delivering an aerosol spray. Pressurized packs may comprise a suitable propellant such as dichlorodifluoromethane, trichlorofluoromethane, dichioro tefrafluoroethane, carbon dioxide or other suitable gas. In the case of a pressurized aerosol, the dosage unit may be determined by providing a valve to deliver a metered amount.
Alternatively, for administration by inhalation or insufflation, the compounds may take the form of a dry powder composition, for example a powder mix of the compound and a suitable powder base such as lactose or starch. The powder composition may be presented in unit dosage form, in for example, capsules, cartridges, gelatin or blister packs from which the powder may be administered with the aid of an inhalator or insufflators.
Other formulations include implantable devices and adhesive patches; which release a therapeutic agent.
When desired, the above described formulations, adapted to give sustained release of the active ingredient, may be employed. The pharmaceutical compositions may also contain other active ingredients such as antimicrobial agents, immunosuppressants or preservatives.
It should be understood that in addition to the ingredients particularly mentioned above, the formulations of this invention may include other agents conventional in the art having regard to the type of formulation in question, for example, those suitable for oral administration may include flavoring agents. Preferred unit dosage formulations are those containing an effective dose, as recited below, or an appropriate fraction thereof, of the active ingredient.
For each of the aforementioned conditions, the compositions, e.g., polypeptides and organic compounds are administered orally or via injection at a dose of from about 0.1 to about 250 mg/kg per day. The dose range for adult humans is generally from about 5 mg to about 17.5 g/day, preferably about 5 mg to about 10 g/day, and most preferably about 100 mg to about 3 g/day. Tablets or other unit dosage forms of presentation provided in discrete units may conveniently contain an amount which is effective at such dosage or as a multiple of the same, for instance, units containing about 5 mg to about 500 mg, usually from about 100 mg to about 500 mg. The dose employed will depend upon a number of factors, including the age and sex of the subject, the precise disorder being treated, and its severity. Also the route of administration may vary depending upon the condition and its severity.
The invention will be further described in the following examples, which do not limit the scope of the invention described in the claims. The following examples illustrate the identification and characterization of genes differentially expressed in PNC cells.
Genome-wide cDNA Microarray Analysis of Gene-Expression Profiles of Pancreatic Cancer Using Cancer and Normal Ductal Epithelial Cells Purely Selected by Laser Microdissection
Tumor markers and targets for therapeutic intervention were identified by analyzing gene-expression profiles using a cDNA microarray representing 23,040 genes. Pancreatic ductal adenocarcinoma that has a characteristic of highly desmoplastic stromal reaction contained a low proportion of cancer cells in the tumor mass. Furthermore, normal duct epithelial cells from which the pancreatic carcinoma originates correspond to a few percent of the pancreas tissue. Therefore, cancer cells were purified from 18 pancreatic cancers by means of laser microbeam microdissection (LMM). Gene expression profiles were examined and compared with those of normal purified pancreatic ductal epithelial cells. These cell populations had been rendered homogenous (more than 95% purified cells). As a result, 259 genes were identified to be commonly up-regulated in pancreatic cancer cells;
among them, the disease correlation and/or function of 64 (including 30 ESTs) genes were not known prior to the invention. The up-regulated genes included ones that were previously reported to be over-expressed in pancreatic cancer, such as interferon-induced transmembrane protein 1 (IFITM1), plasminogen activator, urokinase (PLAU), prostate stem cell antigen (PSCA), SI 00 calcium binding protein P (SI OOP), and baculoviral LAP repeat-containing 5 (BIRC5). 346 genes were identified as being commonly down-regulated in pancreatic cancer cells. Of them, 211 genes were functionally characterized and included some tumor suppressor genes such as AXINl up-regulated l(AXUDl), deleted in liver cancer 1 (DLC1), growth arrest and DNA-damage-inducible, beta (GADD45B), p53-inducible p53DINPl (p53DINPl).
The present gene expression profile represents a highly accurate cancer reference, because a number of limitations of earlier methods were overcome. First, a microarray analysis using clinical samples has been difficult, because of various cellular components are present in the normal as well as cancer tissues. In particular, pancreatic ductal adenocarcinoma that has a characteristic of highly desmoplastic stromal reaction contained a low proportion of cancer cells in the tumor mass. Furthermore, the normal pancreas is mostly constituted from acinar cells and islets that accounted for more than 95% of whole pancreas, and normal duct epithelial cells from which the pancreatic carcinoma originates correspond to a few % of the pancreas. Therefore, the analysis of gene-expression profiles using bulk pancreatic cancer and normal whole pancreatic tissues is significantly influenced by the proportions of cells mixed in the tissues examined; proportional differences of acinar cells, islet cells, fibroblasts, and inflammatory cells may mask the significant increase or decrease of genes that are involved in pancreatic carcinogenesis. Hence, in this study, LMM systems were used to purify cancer and normal epithelial cells from surgical specimens to a high degree of purity (95% or higher). Because it is possible to microdissect even a single cell with LMM, this technology is critical for an accurate microarray analysis of pancreatic cancer specimens. To evaluate the purifity of micordissected pancreatic cancer and normal ductal cells, the expression profile of AMY1A gene which is known to be expressed specifically in acinar cells were analyzed. As a result, the proportion of contaminating acinar cells in the dissected normal pancreatic ductal epithelial cells was estimated to be smaller than 0.29%. In addition to AMY1A, expression levels of other genes that were highly expressed in acinar cells like elastase 1, trypsin 1, and pancreatic lipase were examined. Similar results were
obtained, indicating that the purifity of cell populations by the LMM technique was as high as 99.2%-99.7%.
Second, the quality of extracted RNA from clinical tissue, particularly from pancreas, is one of the most important factors. Pancreas is known to be RNase-rich organ and degradation of RNA occurs very rapidly. In this study, the quality of the extracted RNA from the specimen was examined by visualization of 28S and 18S ribosomal RNAs using denaturing agarose gel electrophoresis. Following electrophoretic analysis, samples in which bands corresponding to two ribosomal RNAs were clearly observed were selected. For example, 18 cases (32%) were selected from the 56 surgically-ressected cases, i.e., many were not included in the analysis due to the poor quality of RNA.
Careful purification of cancer cells as well as normal epithelial ductal cells, subsequent RNA isolation, and cDNA microarray analysis identified 259 genes whose expression was commonly up-regulated (genes which were able to obtain expression data in more than 50% cancer cases and whose expression ratio(Cy5/Cy3 intensity ratio) was more than 5.0 and the genes which were able to calculate in 33 to 50% cases and which expressed the expression ratio of more than 5.0 in all of that cases were also evaluated)
Over 90% of the gene expression profile of pancreatic cancer was different from previous pancreatic cancer expression profiles, because the expression data was obtained by testing highly purified cell populations obtained from patient tissues using laser dissection techniques.
The profiles obtained and described herein represent an improvement over earlier profiles, because they were obtained by analyzing highly purified populations of cancerous cells (pancreatic ductal adenocarcinoma) and compared to a highly purified population of the most relevant normal control, i.e., normal duct epithelial cells. Earlier methods and profiles were hampered by a high percentage of contaminating cells, which reduced the accuracy and reliability of earlier profiles. This present profile is the first one of precise and genome-wide gene expression profiles in large-scale pancreatic cancer. These data identify molecular targets for therapeutic modulation for the treatment of pancreatic cancer and specific novel tumor markers for early and accurate diagnosis of the cancer or a precancerous condition.
EXAMPLE 1: PREPARATION OF TEST SAMPLES
Tissue obtained from diseased tissue (e.g., epithelial cells from PNC) and normal
tissues was evaluated to identify genes which are differently expressed or a disease state, e.g., PNC. The assays were carried out as follows.
Patients, tissue samples, and laser microdissection Tissue samples of pancreatic cancer (n =18) and normal pancreas (n = 7) were obtained from surgical specimens from patients with informed consent. All pancreatic cancer tissues had his tologically confirmed invasive ductal carcinoma. Clinicopathological features of the patients we used in this study are summarized in Table 1. Since almost all pancreatic ductal cells from corresponding normal tissue blocks showed dysplastic changes mostly because of downstream ductal obstruction, ductal cells for only 4 of the 18 pancreatic cancer tissues were suitable to use as normal controls. Hence, additional control ductal cells were obtained from 3 normal pancreas tissues from patients who were operated by cholangiocarcinoma, duodenal leiomyosarcoma, or ampullary tumor. In each case, the specimens were harvested immediately after surgical resection and were embedded in TissueTek OCT medium (Sakura, Tokyo, Japan) before storage at -80°C. The frozen tissues were cut to 8-μm sections using a cryostat (Sakura, Tokyo, Japan) and then stained with Hematoxylin and Eosin, and check the histological state. Pancreatic carcinoma cells and normal pancreatic ductal epithelial cells were isolated selectively using the EZ cut system with pulsed ultraviolet narrow beam focus laser (SL Microtest GmbH, Germany) in accordance with the manufacturer's protocols. After microdissection, 7 normal cases were mixed to make a "universal control of normal pancreatic ductal epithelial cells ", that was used as a control for all 18 cancer samples.
Clinical stage was judged according to the UICC TNM classification location: Tumor location, ph: pancreas head, pb: pancreas body
All patients were Invasive ductal adenocarcinomas, well: Tubular adenocarcinoma well differentiated type mod: Tubular adenocarcinoma mderately type, por: Tubular adenocarcinoma poorly differentiated type, pap: Papillary adenocarcinoma, adenoscc: Adenosquamous carcinoma
Isolation of pancreatic cancer cells and normal pancreatic ductal epithelial cells by using LMM
To obtain precise expression profiles of pancreatic cancer cells, LMM was used to purify cancer cells and avoid contamination of non-cancerous cells. In addition, since pancreatic cancer originates from pancreatic ductal cells, pancreatic ductal epithelial cells were used as controls. The great majority of cells in pancreas are acinar cells, it was determined that the use of the entire pancreas was inappropriate for screening genes associated with pancreatic carcinogenesis. As shown in Fig. 1, representative cancer cases (Fig. 1A and IB), and normal pancreatic duct (Fig. 1C and ID) were microdissected. Fig. 1A and IB showed a well-differentiated type and a scirrhous type of invasive ductal adenocarcinoma, and the proportion of cancer cell was about 30% and 10%, respectively. After isolation of pancreatic cancer cells by LMM, we estimated that the proportion of pancreatic cancer cells used in this study was at least 95%.
The proportion of acinar cells contaminated was examined in the microdissected normal pancreatic ductal epithelial cells which used as universal control (FiglC and ID). The signal intensity of AMY 1 A gene was examined that is known to be expressed exclusively in normal acinar cells. The signal intensity of whole pancreatic tissue was investigated in which >90% of the cells are acinar cells, the ratio of the average signal intensity of the pancreatic amylase gene to that of ACTB was approximately 96.7, whereas the ratio of that in microdissected normal pancreatic ductal epithelial cells in this study was calculated approximately 0.28. This result showed the proportion of contaminating acinar cells in the microdissected normal pancreatic ductal epithelial cells was estimated to be 0.29% in average (Fig. 1). Furthermore, the extent of contamination of acinar cells was determined in the microdissected normal pancreatic ductal epithelial cells. Pancreatic amylase gene (AMY1 A)
that is expressed exclusively in pancreatic acinar cells was used to evaluate the proportion of the acinar cells in microdissected normal pancreatic ductal epithelial cells. Each intensity was normalized by intensity of β-actin gene (ACTB) as follows;
(Ratio A) the AMY1 A /ACTB intensity ratio in whole pancreas (most of the cells correspond to acinar cells) = 96.74
(Ratio B) the AMY1 A/ACTB intensity ratio in microdissected normal ductal epithelial cells = 0.28 Contamination percentage (%) ;(Ratio B) /(Ratio A) x 100 =0.29%
Extraction of RNA and T7-based RNA amplification
Total RNAs were extracted from each sample of laser-microdissected cells into 350 μl of RLT lysis buffer (QIAGEN, Hilden, Germany). The extracted RNAs were treated for 30 minutes at room temperature with 30 units of DNase I (Roche, Basel, Switzerland) in the presence of 1 unit of RNase inhibitor (TOYOBO, Osaka, Japan) to remove any contaminating genomic DNA. After inactivation at 70° C for 10 min, the RNAs were purified with an RNeasy Mini Kit (QIAGEN) according to the manufacturer's recommendations. All of the DNase I-treated RNAs were subjected to T7-based RNA amplification as described previously. Two rounds of amplification yielded 50-1 OOμg of aRNA from each sample. A 2.5μg aliquot of aRNA from cancer and normal pancreatic duct epithelial cells was labeled with Cy5-dCTP or Cy3-dCTP, respectively, by a protocol described elsewhere. The hybridization, washing, and scanning were carried out according to the methods described previously (11).
Preparation of the cDNA microarray A genome- wide cDNA microarray with 23,040 cDNAs selected from the
UniGene database (build # 131) of the National Center for Biotechnology Information (NCBI) was constructed. Briefly, the cDNAs were amplified by RT-PCR using poly(A)+ RNA isolated from various human organs as templates; the lengths of the amplicons ranged from 200 to 1,100 bp that did not contain repetitive or poly(A) sequences. The cDNA microarray system was constructed essentially as described previously (11).
Acquisition of data
Signal intensities of Cy3 and Cy5 from the 23,040 spots were quantified and analyzed by substituting backgrounds, using ArrayVision software (Imaging Research, Inc., St. Catharines, Ontario, Canada). Subsequently, the fluorescent intensities of Cy5 (tumor) and Cy3 (control) for each target spot were adjusted so that the mean Cy3/Cy5 ratio of the 52 housekeeping genes was equal to one. Because the data derived from low signal intensities are less reliable, a cut-off value for signal intensities was determined on each slide and excluded genes from further analysis when both Cy3 and Cy5 dyes provided signal intensities lower than the cut-off as described previously (12). For other genes we calculated the Cy5/Cy3 ratio using raw data of each sample.
Semi-Quantitative RT-PCR
The 12 highly up-regulated genes were selected and examined their expression levels by applying the semi-quantitative RT-PCR experiments. A 3-μg aliquot of aRNA from each sample was reversely-transcribed for single-stranded cDNAs using random primer (Roche) and Superscript II (Life Technologies, Inc.). Each cDNA mixture was diluted for subsequent PCR amplification with the same primer sets that were prepared for the target DNA or tubulin, alpha-specific reactions. The primer sequences are listed in Table 2. Expression of tubulin- alpha served as an internal control. PCR reactions were optimized for the number of cycles to ensure product intensity within the linear phase of amplification.
Table 2 Primer sequences for semi-quantitative RT-PCR experiments
SE SE
PNC Acce
Sym Q Q
Assign ssion Forward primer ID Reverse primer ID bol ment No. NO NO
AA9 5'- 5'-
No. No.
12 1682 APP CTGCTGGTCTTCAATTACC CTCATCCCCTTATATTGC 1 2
6 AAG-3' CACTT-3'
ARH 5'- 5'-
L206 No. No.
13 GDI CTCCCTCTGATCCTCCATC TCTTGTTCTCTTGTGTCGT 88 3 4
B AG-3" TTACAG-3'
5'- 5'-
L242 ATD No. No.
15 CATTCTCTCTGGCGATGGA ACCAATGGTTTATTCCAA
03 C 5 6
GTG-3' AGGG-3'
5'- 5'-
U514 ATP1 No. No.
16 CAGTGTACAGTCGCCAGA TCCTCACATACAGAACTT
78 B3 7
TAG-3' CTCCAC-3'
5'- 5'-
U752 BIRC No. No.
19 CTCCCTCAGAAAAAGGCA GAAGCTGTAACAATCCA
85 5 9 10
GTG-3' CCCTG-3'
5'-
AF06 BUB No.
AGGGAAAAGTAGAGACA IJ°- 8760 IB AGCTAGGCAATCAAGTCT
CAC-3' 11 AATGGG-3'
ABO
CEL 5'- No.
1153 AAGCAGCTTCCTGGGAGA ACGGAACAATTTACACA *J°- SR3 13
6 TT-3' GACAGG-3'
5'-
X549 CKS No. No
ACTATTCGGACAAATACG CACTGTTTGAATGTGCTG T 41 1 15
ACGAC-3* GTAAC-3'
5'-
X549 CKS No. No
CAAGCAGATCTACTACTCG CAGTAACCTACTTGCAGT XX
42 2 17
GACAA-3' TGCATT-3'
AA5 5'-
CYP No.
7995 CACCCTGATTCTACCAAAT CCTTAAGTCACAAGGAA J°-
2S1 19
9 GC-3' CGTCAG-3' υ
5'-
M91 E2- No. No
TCTGCTCACAGAGATCCAC TTAGAGACAGAGTTGGA Xl' 670 EPF 21
G-3' GGGAGG-3'
5'-
U326 No.
ELF4 AGAAATGTCAGCCACGGA AAAGGCACTTTAATGCC ^°' 45 23
AAC-3' AACTG-3'
5'-
AF01 ENC No.
CGATATAGGCATTTGGTCT TTTCTCTTCATTAGACTT ^°- 0314 1 25
CAC-3' GGCCTCT-3'
5'-
L366 EPH No.
GAAGGCGTGGTCACTAAA CTTTAATTTCAGAGGGCG °R
45 A4 27
TGTAA-3' AAGAC-3'
5'- 5'.
AI62 No.
Evi-1 GCAAGCTTGTGCGATGTTA CTCCTCCCATAGTAATGC ^°' 7919 29
TGT-3' ACTGA-3'
5'-
L167 FOX No.
GATGGATGCAACTGAAGC GTCCACCTTCGCTTTTAT ^°- 83 Ml 31
AGAG-3' TGAGT-3'
AA6 5'-
GW1 No. 5219 GAAAATCTGATGGCAGTG AAGGTTTCCAACTACTGC 1 °" 12 33
7 ACAA-3' ACTGA-3'
5'- 5'-
J045 No.
GYSl TGCCCACTGTGAAACCACT CATCTCATCTCCGGACAC °' 01 35
AG-3' ACT-3'
5'-
D164 HOG No.
TATCCCAGCTGCCTAGATT GAGTCTTCCCAAGCATCC ^- 31 F 37
C-3' TATTT-3'
5'-
M16 HOX No.
GTACCTATAGGAAAGTCT AACACGCGAGTGGTAGG ^°- 937 B7 39
GTC-3' TTTT-3' hPA
AA4 5'-
D- No. 9586 CACTGAGCCAACTACTGTC CTTCCTACCCACAGCTCT ^°" colon 41
ACTG-3' TTCTC-3' ylO
5'-
U637 KNS No.
ACTCTAGGACTTGCATGAT TCCTCTAGGACTCTAGGG ^°. 43 L6 43
TGCC-3' AGACA-3'
5*- 5'.
U703 KPN No.
TCTTGGAGACTATAAGGG TTTTGCTTCTTCACATCC ?°" 22 B2 45 46
AGCC-3' ACTG-3'
5'-
X577 MMP No. 66 GCACTGAAGCAAGGGTGC GACAGGATTGAGGTATG ^°" 11 47
TG-3' TTGCAG-3'
5'-
X132 MYB No. No.
120 TCCTGAGGTGTTGAGGGTG ATCCTAAGCAGGGTCTG 93 L2 49 50
TC-3' AGATG-3'
5'- 5'-
X043 OAS No. No.
125 TTTCAGGATCAGTTAAATC GGCCTGGCTGAATTACCC 71 1 51 52
GCC-3' ATG-3'
5'- 5'-
U657 ORP No. No.
127 GTTCTGCTCCTCCCAGACA GCCCTAGCTCCTGCTACA 85 150 53 54
G-3' GA-3'
5'- 5'-
D385 PCO No. No.
132 GCTCACTGCGTTTGGTTTT CAGCATTCTAGGAGAAA
54 LN3 55
C-3' GGTGAA-3' 56
AA9 5'- 5'-
PPM No. No.
141 3198 CTGTAACGTTTTCCTGAAG TCAGTACAGGGTTGGATC IB 57
1 CTGT-3' AGAGT-3' 58
5'- 5'-
AF04 PRC No. No.
143 GTGCCTACTTTGCCTGAGT CAGGACACGTACTGTAT 4588 1 59 60
TC-3' GAGGTAAA-3'
5'- 5'-
AF04 PSC No. No.
149 GACCATGTATGTTTGCACC AACTCACGTCAACTCTTG 3498 A 61 62
C-3' TCCTC-3'
5'- 5'-
M77 PYC No. No.
152 ATCCCAAGTCCAGCGTGA TCCACTATTCCACCCACA 836 Rl 63 64
AG-3' GTAAC-3'
5'- 5'-
X646 RBM No. No.
155 CTGTCGAGACGTCTAATGA TTACTAAAATAAACCTGT
52 SI 65 66
CC-3' TCGGGGG-3'
AA3 5'- 5'-
REGI No. No.
157 1652 CCAGTAGTGGCTTCTAGCT GAAAAACAAGCAGGAGT V 67 68
5 C-3' TGAGTG-3' AA3 5'- 5'-
S100 No. No.
164 0806 GCATGATCATAGACGTCTT GATGAACTCACTGAAGT P 69 70
2 TTCC-3' CCACCT-3'
5'- 5'-
AF02 No.
169 SFN GAGCGCACCTAACCACTG TGAGTGTCACAGGGGAA No. 9082 GTC-3* 71 72
CTTTAT-3'
AA6 5'- 5'-
SLC1 No. No.
170 3959 AACCGAAGTCTCCATACA GTTCGTGGGAATCATCAG
2A2 CG-3' 73 74
9 AG-3'
5'-
K031 5'-
SLC2 No. No.
173 GTTCGTGGGAATCATCAG 95 AACCGAAGTCTCCATACA Al 75 76
CG-3' AG-3'
5'- 5'-
M32 SRD No. No.
178 TCTGTAACAATAACAAGA CCAGATGAGATGATAAG 313 5A1 CC-3' 77 78
GCAAAG-3'
5'- 5'-
M81 TCE TGTCCCAAGTCTTATTTGC No. No.
180 GCAACAGTGGCCTTTAA 601 Al TGA-3' 79 80
AGTATG-3'
5'- 5'-
K025 No.
184 TKl ATTTCATAAGCTACAGCA No. 81 GTAATTGTGGCTGCACTGG
AT-3' 81 82
GAGGC-3'
5'- 5'-
U733 UBC No.
188 ACACACATGCTGCCGAGC TAATATACAAGGGCTCA No. 79 H10 83 84
TC-3' ACCGAG-3'
AA5 5'- 5'-
WHS No. No.
196 8194 CCTATGAGTGTAGTTGATG CAACTGGCAAGTCTCAA Cl 85 86
0 AC-3' CTCTCT-3' 198 AA7 FLU 5'- No. 5'- No.
0915 0134 TCCAGATGGATTTGTCCTG 87 TAGTAGCAAGCCCAGTA 88 TATC-3' ACCTTG-3'
5'- 5 5''-.
199 « £_ GCTTACCATTGAAACTTAA ^ NJ°"' CTCATTTACAGTAGCCCA ^°-
CCCC-3' GTGGT-3'
5'- 5'-
203 GACTTCCACAATGAACAG ^°" ATTGGAATAAGAGGAAC ^°-
GGTAA-3' AGGAGC-3'
5'-
D146 _______ No 5'- No
208 CCAATTAGCTTTGTTGAAC XT GGCAGCAGTACAACAAT '
57 ø_ ø; AGGC-3' V CTAAGC-3*
5'- 5'-
R397 KIAA
217 CAGTGCTACACCCACTTCT °' ATACCACCAATGGTTCTG ^°" 94 1624
TG-3' CTATG-3'
AA4 5'- 5'-
KIAA
218 3404 CTCATCTTTGAAGCCAGCA ^ GACTCACAGGCAGGAAC ^°" 1808
5 G-3' ATC-3' AA5 5'- 5'-
FLI2
225 2311 GGATAGCTGGGGCATTTGT ^°- TCCATAAAAGAGTTTGGC ^l0' 1504
7 CTAG-3' AGTC-3' AA7 5'- 5'-
VAN
231 8933 GAGTTGTATTATGAAGAG ^°" ATGTCTCAGACTGTAAGC ^ GL1
2 GCCGA-3' GAAGG-3'
5'- 5'-
AI34
234 EST GTAGATGTGGGGACAACA °" TTTAAAGTCACCTTAGGT ^°" 9804
GAGAG-3' TGGGG-3'
AA8 5'- 5'-
No No
239 0611 EST CACCTATCCCTATTACCTG , "" TCTGAGGGTTTACATTGA , ""
4 ACCC-3' CGACT-3' AA4 5'- No 5'- No
242 1956 EST GAGTCCAGGTAAGTGAAT ' "„ ATTTCCACCGAGACCTCT ' "„
8 CTGTCC-3' CATC-3' AA5 5'- 5'-
245 7018 EST GTCTATCTGTGCTGGAACC ^°q GTGTAGGTGAGTGCTTTC °'
6 TGAG-3' TCCA-3' AA8 5'- 5'-
253 3032 EST ACTCCCGAGTAAATCATA ^°" GACTGTTTCTACTCCAGA ^0„
6 GAGCC-3' GGGGT-3'
5'- 5'-
AI24 FXY
254 AAAGCTGATGAGGACAGA ^°' GGCAGAGGCACAATCAT ^°. 0520 D3
CCAG-3' TTTAG-3'
5'- 5'-
AI02
259 EST TGGTGTCTTTCTACCATTC °' AAAAGGCTAGTCCCCTTC ^0' 7791
AAGG-3' TACCT-3'
5'- 5'-
AF14 TUB No No
CTTGGGTCTGTAACAAAGC ' "„ AAGGATTATGAGGAGGT ' 1347 A ATTC-3' TGGTGT-3'
Accession numbers and gene symbols were retrieved from the Unigene Databases (build#131).
EXAMPLE 2: IDENTIFICATION OF PNC - ASSOCIATED GENES
The up- or down-regulated genes were identified common to pancreatic cancer using following criteria; 1) genes which were able to obtain expression data in more than 50%
cancer cases, and 2) genes whose expression ratio was more than 5.0 in pancreatic cancer cells (defined as up-regulated genes) or genes whose expression ratio was under 0.2 (defined as down-regulated genes) in more than 50% of informative cases. Moreover, 3) the genes which were able to calculate in 33 to 50% cases and which expressed the expression ratio of more than 5.0 in all of that cases were also evaluated as up-regulated genes.
IDENTIFICATION OF GENES WITH CLINICALLY RELEVANT EXPRESSION PATTERNS IN PNC CELLS
The expression of approximately 23,000 genes in in 18 pancreatic cancer patients was examined using cDNA microarray. Individual data were excluded when both Cy5 and Cy3 signals were under cut-off values. Two hundred fifty-nine up-regulated genes were identified whose expression ratio was more than 5.0 in PNC cells (see Table 3). 167 of them were expressed greater than 10-fold comparing to the normal ductal cells. Three hundred forty-six down-regulated genes whose expression ratio was less than 0.2 were identified (see Table 4).
Among the up-regulated genes, interferon induced transmembrane protein 1 (IFITM1), plasminogen activator, urokinase (PLAU), prostate stem cell antigen (PSCA), SI 00 calcium binding protein P (SI OOP), RNA binding-motif single-stranded interacting protein 1 (RBMS1), and baculoviral IAP repeat-containing 5 (BIRC5), have been reported to be overexpressed in pancreatic cancer (5, 6). Furthermore, these up-regulated genes included ones encoding proteins involved in the signal transduction pathway, transcriptional factors, cell cycle, and cell adhesion (Table 5).
Significantly overexpressed genes have diagnostic potential, and of them which were critical for tumor growth have also therapeutic potential. Specifically, genes such as regenerating gene type IV (REGIV), ephrin type-A receptor 4 precursor (EphA4), and vang (van gogh, Drosophila)-like 1 (VANGL1), are useful as a potential molecular target for new therapeutic agents.
REGIV was over-expressed in all informative pancreatic cancer cases, and the overexpression was confirmed in 7 of the 12 pancreatic cancer cases by semi-quantitative RT- PCR. Since REGIV protein was thought to be a secreted protein from the amino-acid sequences and in fact its secretion was detected in the culture medium of HT29-5M12 cells (22), it is a candidate as tumor marker.
EphA4 was indicated to be overexpressed in 12 of the 14 informative pancreatic cancer cases in the microarray, and confirmed in 9 of the 12 cases were examined by semi- quantitative RT-PCR. EphA4 is known to be a membrane receptor belonging to the ephrin family, which contains an intracellular tyrosine kinase catalytic domain (23). Involvement of EphA4 in any human cancer has not been reported. However, its nature of the cytoplasmic membrane receptor protein with possible tyrosine kinase activity as well as high level expression in cancer cells suggest that EphA4 is a candidate gene for therapeutic agents.
VANGLl was over-expressed if all of the informative pancreatic cancer cases in the microarray data, and its high expression was also confirmed in 9 of the 12 cases by semi- quantitative RT-PCR. VANGLl , which contained four putative fransmembrane domains, was expressed specifically in testis and ovary among 29 normal tissues examined (4). This gene was also highly and frequency transactivated in hepatocellular carcinoma. Since the enforced reduction of this gene expression in hepatocellular carcinomas induced apoptosis (4), this gene product is a good candidate for development of novel anti-cancer drugs. Among the genes that were functionally highly overexpressed in pancreatic cancer such as the above mentioned genes, those whose products are putative membranous or secreted are of interest for potential as novel anti-cancer drugs or as serological diagnostic markers for early detection.
To confirm the reliability of the expression profiles indicated by microarray analysis, semi-quantitative RT-PCR experiments were performed. Other 55 genes whose cancer/normal ratios were highest among the informative genes, APP, ARHGDIB, ATDC, ATP1B3, BIRC5, BUB1B, CELSR3, CKS1, CKS2, CYP2S1, E2-EPF, ELF4, ENC1, Evi-1, FOXM1, GW112, GYSl, HDGF, HOXB7, hPAD-colonylO, KNSL6, KPNB2, MMP11, MYBL2, OAS1, ORP150, PCOLN3, PPM1B, PRC1, PSCA, PYCR1, RBMS1, S100P, SFN, SLC12A2, SLC2A1, SRD5A1, TCEA1, TKl, UBCH10, WHSC1, FLJ10134, FLJ10540, FLJ20225, KIAA0101, KIAA1624, KIAA1808, FLJ21504, FXYD3, and 6 ESTs (Accession No.AI349804, AA806114, AA419568, AA570186, AA830326, AI027791) were PCR- amplified and compared with the microarray data. As shown in Fig.2, the results of the cDNA microarray werehighly similar to those of the RT-PCR analysis in the great majority of the tested cases.
APP was confirmed whose over-expression in 10 of the 12 cases, ARHGDIB was confirmed whose over-expression in 12 cases,
ATDC was confirmed whose over-expression in 10 of the 12 cases, ATP1B3 was confirmed whose over-expression in 12 cases, BIRC5 was confirmed whose over-expression in 12 cases, BUB IB was confirmed whose over-expression in 12 cases, CELSR3 was confirmed whose over-expression in 9 of the 12 cases,
CKS1 was confirmed whose over-expression in 7 of the 12 cases, CKS2 was confirmed whose over-expression in 11 of the 12 cases, CYP2S1 was confirmed whose over-expression in 8 of the 12 cases, E2-EPF was confirmed whose over-expression in 8 of the 12 cases, ELF4 was confirmed whose over-expression in 11 of the 12 cases,
ENC1 was confirmed whose over-expression in 7 of the 12 cases, Evi-1 was confirmed whose over-expression in 11 of the 12 cases, FOXMl was confirmed whose over-expression in 11 of the 12 cases, GW112 was confirmed whose over-expression in 7 of the 12 cases, GYSl was confirmed whose over-expression in 10 of the 12 cases,
HDGF was confirmed whose over-expression in 10 of the 12 cases, HOXB7 was confirmed whose over-expression in 6 of the 12 cases, hPAD-colonylO was confirmed whose over-expression in 6 of the 12 cases, KNSL6 was confirmed whose over-expression in 12 cases, KPNB2 was confirmed whose over-expression in 10 of the 12 cases,
MMP11 was confirmed whose over-expression in 10 of the 12 cases, MYBL2 was confirmed whose over-expression in 11 of the 12 cases, OAS1 was confirmed whose over-expression in 10 of the 12 cases , ORP150 was confirmed whose over-expression in 8 of the 12 cases, PCOLN3 was confirmed whose over-expression in 4 of the 12 cases,
PPM1B was confirmed whose over-expression in 3 of the 12 cases, PRC1 was confirmed whose over-expression in 12 cases, PSCA was confirmed whose over-expression in 6 of the 12 cases, PYCR1 was confirmed whose over-expression in 9 of the 12 cases, RBMS1 was confirmed whose over-expression in 12 cases,
SI OOP was confirmed whose over-expression in 10 of the 12 cases, SFN was confirmed whose over-expression in 9 of the 12 cases,
SLC12A2 was confirmed whose over-expression in 5 of the 12 cases, SLC2A1 was confirmed whose over-expression in 11 of the 12 cases, SRD5A1 was confirmed whose over-expression in 8 of the 12 cases, TCEA1 was confirmed whose over-expression in 8 of the 12 cases, TKl was confirmed whose over-expression in 10 of the 12 cases,
UBCH10 was confirmed whose over-expression in 10 of the 12 cases, WHSC1 was confirmed whose over-expression in 8 of the 12 cases, FLJ10134 was confirmed whose over-expression in 8 of the 12 cases, FLJ 10540 was confirmed whose over-expression in 11 of the 12 cases, FLJ20225 was confirmed whose over-expression in 5 of the 12 cases,
KIAA0101 was confirmed whose over-expression in 12 cases, KIAA1624 was confirmed whose over-expression in 9 of the 12 cases, KIAA1808 was confirmed whose over-expression in 8 of the 12 cases, FLJ21504 was confirmed whose over-expression in 11 of the 12 cases, FXYD3 was confirmed whose over-expression in 9 of the 12 cases, and
Accession No. AI349804 was confirmed whose over-expression in 11 of the 12 cases, AA806114 was confirmed whose over-expression in 8 of the 12 cases, AA419568 was confirmed whose over-expression in 9 of the 12 cases, AA570186 was confirmed whose over-expression in 6 of the 12 cases, AA830326 was confirmed whose over-expression in 12 cases,
AI027791 was confirmed whose over-expression in 6 of the 12 cases.
These data verified the reliability of our strategy to identify commonly up-regulated genes in PNC cells.
Among the 346 down-regulated genes in pancreatic cancer cells, functions of 211 genes are characterized. These included genes that have been reported to be invoved in growth suppression (24,27,28,29), such as AXINl up-regulated 1(AXUD1), Deleted in liver cancer 1 (DLC1), growth arrest and DNA-damage-inducible, beta (GADD45B), and P53- inducible p53DINPl (p53DINPl).
The down-regulated genes are likely to have a tumor suppressive function. Although the representative tumor suppressor genes for pancreatic cancer such as SMAD4, TP53,
INK4A, and BRCA2 (24, 25) were not observed in down-regulated gene list, other genes that were reported to be involved in tumor suppression or apoptosis, such as, AXINl up-regulated
1(AXUD1), deleted in liver cancer 1 (DLCl), growth arrest and DNA-damage-inducible, beta (GADD45B), p53-inducible p53DINPl (ρ53DINPl) were included in these data.
AXUD1, a nuclear protein, is induced in response to elevation of axin that is a key mediator of the Wnt-signalling pathway and is important in axis formation in early development. Dysfunction or down-regulation of the Wnt-signaling pathway is observed in human tumors, suggesting that this gene product has a tumor suppressor function (26, 27). Hence, these data imply that down-regulation of AXUD1 might lead to down-regulation of this signaling pathway and then lead to pancreatic carcinogenesis. Deleted in liver cancer 1 (DLCl) was suggested to be a candidate tumor suppressor gene for human liver cancer, as well as for prostate, lung, colorectal, and breast cancers. DLCl shares high sequence similarity with the rat pi 22 RhoGap that negatively regulates the Rho GTPases. Hence, down-regulation of DLCl is considered to result in the constitutive activation of the Rho- Rho-kinase pathway and subsequent oncogenic malignant transformation (28, 29).
Table3 . A list of up- regulated genes
PNC
Assign Accession ment No. Symbol Gene Name
1 V00478 ACTB actin, beta
2 D26579 ADAM8 a disintegrin and me talloproteinase domain 8
3 D14874 ADM adrenomedullin
4 H78430 AHSG alpha-2-HS-glycoprotein
5 W92633 AIB3 thyroid hormone receptor binding protein
6 AF024714 AIM2 absent in melanoma 2
7 X60673 AK3 adenylate kinase 3
8 AF047002 ALY transcriptional coactivator
9 AI341261 ANLN anillin (Drosophila Scraps homolog), actin binding protein
10 J03578 ANXA6 annexin A6
11 U81504 AP3B1 adaptor-related protein complex 3, beta 1 subunit amyloid beta (A4) precursor protein (protease nexin-fl, Alzheimer
12 AA916826 APP disease)
13 L20688 ARHGDIB Rho GDP dissociation inhibitor (GDI) beta
14 AF006086 ARPC3 actin related protein 2/3 complex, subunit 3 (21 kD)
15 L24203 ATDC ataxia-telangiectasia group D-associated protein
16 U51478 ATP1B3 ATPase, Na+/K+ transporting, beta 3 polypeptide
17 AA148566 ATP2B4 ATPase, Ca++ transporting, plasma membrane 4
ATPase, H+ transporting, lysosomal (vacuolar proton pump),
W27948 ATP6S1 subunit 1
U75285 BIRC5 baculoviral LAP repeat-containing 5 (survivin)
L13689 BMI1 murine leukemia viral (bmi) oncogene homolog
W91908 BRAG B cell RAG associated protein
AF068760 BUB1B budding uninhibited by benzimidazoles 1 (yeast homolog), beta
AF028824 C190RF3 chromosome 19 open reading frame 3
J04080 CIS complement component 1, s subcomponent
M15082 C2 complement component 2
AA600048 CALD1 caldesmon 1
AA621719 CAP-C chromosome-associated polypeptide C
AA557142 CD2AP CD2-associated protein
CD83 antigen (activated B lymphocytes, immunoglobulin
Z11697 CD83 superfamily)
H52870 CDC 10 CDC 10 (cell division cycle 10, S. cerevisiae, homolog)
AA421724 CDC20 CDC20 (cell division cycle 20, S. cerevisiae, homolog)
X63629 CDH3 cadherin 3, type 1, P-cadherin (placental) cadherin, EGF LAG seven-pass G-type receptor 3, flamingo
AB011536 CELSR3 (Drosophila) homolog
X95404 CFL1 cofilin 1 (non-muscle)
X54941 CKS1 CDC28 protein kinase 1
X54942 CKS2 CDC28 protein kinase 2
AA001074 CNNM4 Cyclin M4
AA977821 COL1A1 collagen, type I, alpha 1
J03464 COL1A2 collagen, type I, alpha 2 collagen, type III, alpha 1 (Ehlers-Danlos syndrome type IN,
X14420 COL3A1 autosomal dominant)
AI140851 COL6A1 collagen, type VI, alpha 1
J04823 COX8 cytochrome c oxidase subunit NIII
AA523543 CRABP1 cellular retinoic acid-binding protein 1 cofactor required for Spl transcriptional activation, subunit 3
AA905901 CRSP3 (130kD)
X16312 CSNK2B casein kinase 2, beta polypeptide
U16306 CSPG2 chondroitin sulfate proteoglycan 2 (versican)
U40763 CYP Clk-associating RS-cyclophilin
AA579959 CYP2S1 cytochrome P540 family member predicted from ESTs
AA863145 DAO D-amino-acid oxidase
AI287670 DDEF1 Development and differentiation enhancing factor 1
All 59886 DDX21 DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 21
U90426 DDXL nuclear RNA helicase, DECD variant of DEAD box family
AA921756 DIA4 diaphorase (NADH/NADPH) (cytochrome b-5 reductase)
M91670 E2-EPF ubiquitin carrier protein
AA457022 E2IG5 hypothetical protein, es tradiol-induced
U32645 ELF4 E74-like factor 4 (ets domain transcription factor)
AF010314 ENC1 ectodermal-neural cortex (with BTB-like domain)
AF027299 EPB41L2 erythrocyte membrane protein band 4.1-like 2
L36645 EPHA4 EphA4
AA983304 ERH enhancer of rudimentary (Drosophila) homolog
AI627919 Evi-1 ecotropic viral integration site 1
X02761 FN1 fibronectin 1
L16783 FOXMl forkhead box Ml
M14333 FYN FYN oncogene related to SRC, FGR, YES
UDP-N-acetyl-alpha-D-galactosamine:polypeptide -
N36998 GALNT2 acetylgalac tosaminyltransferase 2
AA418167 GATA3 GATA-binding protein 3
U78027 GLA galactosidase, alpha
AF040260 GMDS GDP-mannose 4,6-dehydratase guanine nucleotide binding protein (G protein), alpha z
J03260 GNAZ polypeptide
D63997 GOLGA3 golgi autoantigen, golgin subfamily a, 3
X62320 GRN granulin
D87119 GS3955 GS3955 protein
AA652197 GW112 differentially expressed in hematopoietic lineages
J04501 GYSl glycogen synthase 1 (muscle)
M60756 H2BFQ H2B histone family, member Q
AA608605 HCS cytochrome c hepatoma-derived growth factor (high-mobility group protein 1-
D16431 HDGF like)
X63187 HE4 epididymis-specific, whey-acidic protein type, four-disulfide core
AA714394 HMG2 high-mobility group (nonhistone chromosomal) protein 2 high-mobility group (nonhistone chromosomal) protein isoform I-
X92518 HMGIC C
X06985 HMOX1 heme oxygenase (decycling) 1
N92060 HNRPL Heterogeneous nuclear ribonucleopro tein L
M16937 HOXB7 homeo box B7 hPAD-
AA495868 colonylO peptidylarginine deiminase type I
85 AF070616 HPCAL1 hippocalcin-like 1
86 AF064084 ICMT isoprenylcysteine carboxyl methyltransferase
87 AA328385 ICSBP1 in terferon consensus sequence binding protein 1
88 AA573936 IDH2 isoci trate dehydrogenase 2 (NADP+), mitochondrial
89 AI341760 IFI27 interferon, alpha-inducible protein 27
90 AI081175 IFITM1 interferon induced transmembrane protein 1 (9-27)
91 X16302 IGFBP2 insulin-like growth factor binding protein 2 (36kD)
92 M87789 IGHG3 immunoglobulin heavy constant gamma 3 (G3m marker)
93 M87790 Iglλ immunoglobulin lambda locus
94 S74221 IK LK cytokine, down-regulator of HLA II
95 X59770 IL1R2 interleukin 1 receptor, type II
96 J05272 IMPDH1 IMP (inosine monophosphate) dehydrogenase 1
97 AB003184 ISLR immunoglobulin superfamily containing leucine-rich repeat
98 M15395 ITGB2 integrin, beta 2
99 L38961 ITM1 integral membrane protein 1
100 AA574178 KAI1 Kangai 1 potassium voltage-gated channel, shaker-related subfamily,
101 M55513 KCNA5 v member 5
102 U63743 KNSL6 kinesin-like 6 (mitotic centromere-associated kinesin)
103 U70322 KPNB2 karyopherin (importin) beta 2
104 J00269 KRT6A keratin 6A
105 X53305 LAP18 leukemia-associated phosphoprotein pi 8 (stathmin)
106 AA742701 LCP1 lymphocyte cytosolic protein 1 (L-plastin)
107 AA826336 LHFPL2 lipoma HMGIC fusion partner-like 2
108 U24576 LM04 LIM domain only 4
109 AA555023 LOC51191 cyclin-E binding protein 1
110 AI299952 LOC51765 serine/ threonine protein kinase MASK
111 U89942 LOXL2 lysyl oxidase-like 2 mannosyl (alpha,6-)-glycoprotein beta,2-N-
112 U15128 MGAT2 acetylglucosaminyltransferase
113 J03746 MGST1 microsomal glutathione S-transferase 1 myeloid/lymphoid or mixed-lineage leukemia (trithorax
114 AA531437 MLLT4 (Drosophila) homolog); translocated to, 4
115 X57766 MMP11 matrix metalloproteinase 11 (stromelysin 3) matrix metalloproteinase 9 (gelatinase B, 92kD gelatinase, 92kD
116 J05070 MMP9 type IV collagenase) molybdenum cofactor biosynthesis protein A; molybdenum
117 AF034374 MOCS1 cofactor biosynthesis protein C
118 M74905 MPG N-methylpurine-DNA glycosylase
119 AA458825 MTIF2 mitochondrial translational initiation factor 2
120 X13293 MYBL2 v-myb avian myeloblastosis viral oncogene homolog-like 2
121 D32002 NCBP1 nuclear cap binding protein subunit 1, 80kD
122 AA729022 NCOA3 nuclear receptor coactivator 3
NADH dehydrogenase (ubiquinone) Fe-S protein 5 (15kD)
123 AF047434 NDUFS5 (NADH-coenzyme Q reductase)
124 AA602490 NOP5/NOP58 nucleolar protein NOP5/NOP58
25 X04371 OAS1 2',5'-oligoadenylate synthetase 1 (40-46 kD)
126 M23204 OAT ornithine amino transferase (gyrate atrophy)
127 U65785 ORP150 oxygen regulated protein (150kD)
128 AI223298 P125 Sec23-interacting protein pl25 procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline 4-
129 M24486 P4HA1 hydroxylase), alpha polypeptide I
130 M80482 PACE4 paired basic amino acid cleaving system 4
131 LI 1370 PCDH1 protocadherin 1 (cadherin-like 1)
132 D38554 PCOLN3 procollagen (type III) N-endopeptidase
133 AA034069 PDK1 pyruvate dehydrogenase kinase, isoenzyme 1
134 AA586974 PI3 protease inhibitor 3, skin-derived (SKALP)
135 M16750 PIM1 pim oncogene
136 AA234962 PKP3 plakophilin 3
137 X02419 PLAU plasminogen activator, urokinase
138 AA308562 PLEK2 pleckstrin 2 (mouse) homolog
139 U97519 PODXL podocalyxin-like
140 All 85998 PPIC peptidylprolyl isomerase C (cyclophilin C) protein phosphatase IB (formerly 2C), magnesium-dependent,
141 AA931981 PPM1B beta isoform
142 L42373 PPP2R5A protein phosphatase 2, regulatory subunit B (B56), alpha isoform
143 AF044588 PRC1 protein regulator of cytokinesis 1
144 X74496 PREP prolyl endopeptidase
145 M65066 PRKAR1B protein kinase, cAMP-dependent, regulatory, type I, beta
146 AA972414 PR02975 hypothetical protein PR02975
147 D00860 PRPS1 phosphoribosyl pyrophosphate synthetase 1
148 D87258 PRSS11 protease, serine, 11 (IGF binding)
149 AF043498 PSCA prostate stem cell antigen
150 D26598 PSMB3 proteasome (prosome, macropain) subunit, beta type, 3 polypyrimidine tract binding protein (heterogeneous nuclear
151 X62006 PTB ribonucleoprotein I)
M77836 PYCR1 pyrroline-5-carboxylate reductase 1
X12953 RAB2 RAB2, member RAS oncogene family
AA346311 RAJ3 retinoic acid induced 3
X64652 RBMS1 RNA binding motif, single stranded interacting protein 1
S45545 RCV1 recoverin
AA316525 REGIV Regenerating gene type IN
AB008109 RGS5 regulator of G-protein signalling 5
AA778308 RNASE1 ribonuclease, RΝase A family, 1 (pancreatic)
AA811043 RNASE6PL ribonuclease 6 precursor
L05096 RPL39 Homo sapiens ribosomal protein L39 mRΝA, complete cds
X76302 RY1 putative nucleic acid binding protein RY
D38583 S100A11 SI 00 calcium-binding protein Al 1 (calgizzarin)
AA308062 SI OOP SI 00 calcium-binding protein P
AA452018 SCD stearoyl-CoA desaturase (del ta-9-desaturase) succinate dehydrogenase complex, subunit C, integral membrane
D49737 SDHC protein, 15kD
AA579861 SEC23A Sec23 (S. cerevisiae) homolog A
AA430643 SEPW1 selenoprotein W, 1
AF029082 SFN stratifin solute carrier family 12 (sodium/potassium/chloride transporters),
AA639599 SLC12A2 member 2
L20859 SLC20A1 solute carrier family 20 (phosphate transporter), member 1
L02785 SLC26A3 solute carrier family 26, member 3
K03195 SLC2A1 solute carrier family 2 (facilitated glucose transporter), member 1
U09873 SNL singed (Drosophila)-like (sea urchin fascin homolog like)
X13482 SNRPA1 small nuclear ribonucleoprotein polypeptide A'
M37716 SNRPE small nuclear ribonucleoprotein polypeptide E
J03040 SPARC secreted protein, acidic, cysteine-rich (osteonectin)
M32313 SRD5A1 steroid-5-alpha-reductase, alpha polypeptide 1
M95787 TAGLN transgelin
M81601 TCEA1 transcription elongation factor A (SII), 1
AF033095 TEGT testis enhanced gene transcript (BAX inhibitor 1)
L12350 THBS2 thrombospondin 2
M77142 TIA1 TIA1 cytotoxic granule-associated RΝA-binding protein
K02581 TKl thymidine kinase 1, soluble
AA429631 TK2 thymidine kinase 2, mitochondrial
U09087 TMPO thymopoietin
187 AF065388 TSPAN tetraspan 1
188 U73379 UBCH10 ubiquitin carrier protein E2-C ubiquitin-conjugating enzyme E2D 2 (homologous to yeast
189 AA977545 UBE2D2 UBC4/5)
190 U45328 UBE2I ubiquitin-conjugating enzyme E2I (homologous to yeast TJBC9)
191 M57899 UGT1A1 UDP glycosyltransferase 1 family, polypeptide Al
192 AA315189 UQCRB ubiquinol-cytochrome c reductase binding protein
193 AB000450 VRK2 vaccinia related kinase 2
194 AA079060 WFDC2 WAP four-disulfide core domain 2
195 AA043277 WFS1 Wolfram syndrome 1 (wolframin)
196 AA581940 WHSC1 Wolf-Hirschhorn syndrome candidate 1
197 All 85056 ZNF134 zinc finger protein 134 (clone pHZ5)
198 AA709155 FU10134 hypothetical protein FLJ10134
199 AA806630 FIJI 0540 hypothetical protein FLJ10540
200 AA115015 FLJ10633 hypothetical protein FLJ 10633
201 AA394229 FU10637 hypothetical protein FLJ 10637
202 AA633302 FLJ20063 hypothetical protein FLJ20063
203 AA918811 FLJ20225 hypothetical protein
204 R09189 FLJ20281 hypothetical protein FLJ20281
205 AA112198 FLJ20296 hypothetical protein FLJ20296
206 AI033837 FLJ20406 hypothetical protein FLJ20406
207 AA974462 FLJ23053 hypothetical protein FLJ23053
208 D14657 KIAA0101 KIAA0101 gene product
209 D61862 KIAA0332 KIAA0332 protein
210 AB014566 KIAA0666 KIAA0666 protein
211 AB014570 KIAA0670 KIAA0670 protein/acinus
212 AA665890 KIAA0729 KIAA0729 protein
213 W80765 KIAA0731 KIAA0731 protein
214 AF052170 KJAA0750 KIAA0750 gene product
215 D20853 K1AA0776 KIAA0776 protein
216 AA031775 KIAA0990 KIAA0990 protein
217 R39794 KIAA1624 KIAA1624 protein
218 AA434045 KIAA1808 ESTs
219 AI074410 KIAA1863 Homo sapiens cDNA FLJ13996 fis, clone Y79AA1002211
220 AF070638 CGI-57 hypothetical protein
221 N38882 H.sapiens gene from PAC 106H8
222 AI142828 Homo sapiens adlican mRNA, complete cds
223 AA028961 Homo sapiens cDNA FLJ12150 fis, clone MAMMA1000422
224 AA933635 Homo sapiens cDNA FLJ13154 fis, clone NT2RP3003427
225 AA523117 FLJ21504 Homo sapiens cDNA: FLJ21504 fis, clone COL05662
226 AA555187 Homo sapiens cDNA: FLJ22277 fis, clone HRC03740
227 AF035315 Homo sapiens clone 23664 and 23905 mRNA sequence
228 AA968840 Homo sapiens HSPC285 mRNA, partial cds
Homo sapiens mRNA; cDNA DKFZp547K204 (from clone
229 R55322 DKFZp547K204)
Homo sapiens mRNA; cDNA DKFZp586A0424 (from clone
230 W55876 DKFZp586A0424)
231 AA789332 VANGLl ESTs, Moderately similar to KIAA1215 protein [H.sapiens]
ESTs, Weakly similar to A4P_HUMAN INTESTINAL
232 AI310156 MEMBRANE A4 PROTEIN [H.sapiens]
233 C01335 ESTs, Weakly similar to FLDED [H.sapiens]
ESTs, Weakly similar to IQGA_HUMAN RAS GTPASE-
234 AI349804 ACTΓVATING-LIKE PROTEIN IQGAPl
235 AA683373 ESTs
236 H28960 ESTs
237 AA429665 ESTs
238 R17093 ESTs
239 AA806114 ESTs
240 AA707966 ESTs
241 D85376 ESTs
242 AA419568 ESTs
243 AA251355 ESTs
244 W63676 ESTs
245 AA570186 ESTs
246 AI239432 ESTs
247 AI264318 ESTs
248 AA553741 ESTs
249 N70804 ESTs
250 R61891 ESTs
251 WO 1507 ESTs
252 AA587884 ESTs
253 AA830326 ESTs
254 AI240520 ESTs
255 AA453716 ESTs
256 AI199761 ESTs
57 AI271678 ESTs 58 AA242941 ESTs 59 AI027791 ESTs
Table4 A list of down-regulated genes
PNC
Accession
Assign Symbol GeneName No. ment acetyl-Coenzyme A acyltransferase 2 (mitochondrial 3-oxoacyl-
260 D 16294 ACAA2 Coenzyme A thiolase)
261 M12963 ADH1 alcohol dehydrogenase 1 (class I), alpha polypeptide
262 X04299 ADH3 alcohol dehydrogenase 3 (class I), gamma polypeptide
263 L22214 ADORA1 adenosine Al receptor
264 U04241 AES amino-terminal enhancer of split
265 AF044961 AKR1B11 aldo-keto reductase family 1, member Bl 1
266 U05861 AKR1C1 aldo-keto reductase family 1, member Cl
267 D26125 AKR1C4 aldo-keto reductase family 1, member C4
268 AI765873 ALDH10 aldehyde dehydrogenase 10 (fatty aldehyde dehydrogenase)
269 X02747 ALDOB aldolase B, true tose-bisphosphate
270 M18786 AMY1A amylase, alpha 1A; salivary
271 M28443 AMY2A amylase, alpha 2A; pancreatic
272 M22324 ANPEP alanyl (membrane) aminopeptidase
273 Z11502 ANXA13 annexin A13
274 M82809 ANXA4 annexin A4
275 D00097 APCS amyloid P component, serum
276 M30704 AREG amphiregulin (schwannoma-derived growth factor)
277 AB007884 ARHGEF9 Cdc42 guanine exchange factor (GEF) 9
278 AI147612 ARL7 ADP-ribosylation factor-like 7
279 X83573 ARSE arylsulfatase E (chondrodysplasia punctata 1)
280 L19871 ATF3 activating transcription factor 3
281 Y15724 ATP2A3 ATPase, Ca++ transporting, ubiquitous
282 AI091372 AXUD1 AXINl up-regulated
283 X83107 BMX BMX non-receptor tyrosine kinase
284 AA468538 BRPF3 bromodomain and PHD finger containing, 3
285 U03274 BTD biotinidase
286 D31716 BTEB1 basic transcription element binding protein 1
287 W45244 C3 complement component 3
288 J03037 CA2 carbonic anhydrase II
289 U36448 CADPS Ca2+-dependent activator protein for secretion
290 AI085802 CAV2 Caveolin 2
291 J02988 CD28 CD28 antigen (Tp44)
292 M55509 CES1 carboxylesterase 1 (monocyte/ macrophage serine esterase 1)
293 U91543 CHD3 chromodomain helicase DNA binding protein 3
294 AA417345 CHP1 chord domain-containing protein 1
295 U62431 CHRNA2 cholinergic receptor, nicotinic, alpha polypeptide 2 (neuronal)
296 U89916 CLDN10 claudin 10
297 AA885961 CLDN2 Claudin 2
298 J02883 CLPS colipase, pancreatic
299 M64722 CLU clusterin
300 X67318 CPA1 carboxypeptidase Al (pancreatic)
301 U19977 CPA2 carboxypeptidase A2 (pancreatic)
302 AA780301 CTSF cathepsin F
303 T84490 CUGBP2 CUG triplet repeat, RNA-binding protein 2
304 M22865 CYB5 cytochrome b-5 cytochrome P450, subfamily IIC (mephenytoin 4-hydroxylase),
305 Y00498 CYP2C8 polypeptide 8 cytochrome P450, subfamily IIIA (niphedipine oxidase),
306 J04813 CYP3A5 polypeptide 5
307 D00408 CYP3A7 cytochrome P450, subfamily IIIA, polypeptide 7
308 AA316159 DC 11 DC 11 protein
309 AA640753 DDAH1 dimethylarginine dimethylaminohydrolase 1
310 X96484 DGCR6 DiGeorge syndrome critical region gene 6
311 W76197 DLCl Deleted in liver cancer 1
312 X68277 DUSP1 dual specificity phosphatase 1
313 M62829 EGR1 early growth response 1
314 M16652 ELA1 elastase 1, pancreatic
315 AA845162 ELA3 elastase 3, pancreatic (protease E)
316 M81635 EPB72 erythrocyte membrane protein band 7.2 (stomatin)
317 Ml 6967 F5 coagulation factor V (proaccelerin, labile factor)
318 AA573905 FCGBP Fc fragment of IgG binding protein
319 AA033657 FGFR2 fibroblast growth factor receptor 2
320 U20391 FOLR1 folate receptor 1 (adult)
321 U50743 FXYD2 FXYD domain-containing ion transport regulator 2
322 M11321 GC mRNA for group supecific component (GC) glucose-6-phosphatase, transport (glucose-6-phosphate) protein
323 Y15409 G6PT1
1
324 AA279817 GADD45B growth arrest and DNA-damage-inducible, beta
325 L13720 GAS6 growth arrest-specific 6 glycine amidinotransferase (L-arginine:glycine
326 S68805 GATM amidinotransferase)
327 M24903 GGT1 gamma-glutamyltransferase 1
328 AW008481 GLUD1 glutamate dehydrogenase 1
329 T79836 GPS2 G protein pathway suppressor 2
330 D86962 GRB10 growth factor receptor-bound protein 10
331 L76687 GRB14 growth factor receptor-bound protein 14
332 D49742 HABP2 hyaluronan-bin ding protein 2
333 W37916 HCF-2 host cell factor 2
334 U63008 HGD homogentisate 1,2-dioxygenase (homogentisate oxidase)
335 W95267 HIBADH 3 -hydroxy isobutyrate dehydrogenase
336 K01505 HLA-DQA1 DC classll histocompatibility antigen alpha-chain
337 M81141 HLA-DQB1 major histocompatibility complex, class II, DQ beta 1
338 J03048 HPX hemopexin
339 T55714 HS3ST1 heparan sulfate (glucosamine) 3-O-sulfotransferase 1
340 AA206625 HS6ST heparan sulfate 6-O-sulfotransferase
341 U14631 HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2
342 M11717 HSPA1A heat shock 70kD protein 1 A
343 D49547 HSPF1 heat shock 40kD protein 1
344 AA885758 HTATIP HIV Tat interactive protein, 60 kDa
345 M27492 IL1R1 interleukin 1 receptor, type I
346 AF014398 IMPA2 inositol(myo)(or 4)-monophosphatase 2
347 U84400 INPP5D inositol polyphosphate-5-phosphatase, 145kD integrin, alpha 3 (antigen CD49C, alpha 3 subunit of VLA-3
348 AA345854 ITGA3 receptor)
349 AA845511 KCNJ16 potassium inwardly-rectifying channel, subfamily J, member 16
350 AI025297 KLF7 Kruppel-like factor 7 (ubiquitous)
351 X79683 LAMB2 laminin, beta 2 (laminin S)
352 X77196 LAMP2 lysosomal-associated membrane protein 2
353 M87842 LGALS2 lectin, galactoside-binding, soluble, 2 (galectin 2)
354 All 60184 LOC51673 brain specific protein
355 AI093595 LOC55895 22kDa peroxisomal membrane protein-like
356 AA347844 LOC56908 Meis (mouse) homolog 2
357 AK025620 LOC56990 non-kinase Cdc42 effector protein SPEC2
358 AA461526 LRRFIP2 leucine rich repeat (in FLII) interacting protein 2
359 H17536 LSM4 U6 snRNA-associated Sm-like protein
360 AI092885 LSM6 Sm protein F
361 AA157731 MAP1ALC3 Microtubule-associated proteins 1A and IB, light chain 3
362 X69078 MAT1A methionine adenosyltransferase 1 alpha
MADS box transcription enhancer factor 2, polypeptide B
363 X63380 MEF2B (myocyte enhancer factor 2B)
MADS box transcription enhancer factor 2, polypeptide C
364 L08895 MEF2C (myocyte enhancer factor 2C) mel transforming oncogene (derived from cell line NK14)-
365 X56741 MEL RAB8 homolog
366 AI037890 MMP1 matrix metalloproteinase 1 (interstitial collagenase)
367 R59292 MS4A8B Membrane-spanning 4-domains, subfamily A, member 8B
368 AL022315 MSE55 serum constituent protein
369 D49441 MSLN mesothelin
370 M74178 MST1 macrophage stimulating 1
371 TJ35113 MTA1 metastasis associated 1
372 Y09788 MUC5B mucin 5, subtype B, tracheobronchial
373 AI745345 MVP major vault protein
374 X69090 MYOM1 myomesin 1 (skelemin) (185kD)
375 AA497062 NFIC nuclear factor I/C (CCAAT-binding transcription factor)
376 AI309212 NLGN1 neuroligin 1 natriuretic peptide receptor B/guanylate cyclase B
377 AJ005282 NPR2 (atrionatriuretic peptide receptor B)
378 AA340728 NR2F2 nuclear receptor subfamily 2, group F, member 2
379 L13740 NR4A1 nuclear receptor subfamily 4, group A, member 1
380 X75918 NR4A2 nuclear receptor subfamily 4, group A, member 2
381 AB002341 NRCAM neuronal cell adhesion molecule
382 AA435678 P28 dynein, axonemal, light intermediate polypeptide
383 AA576089 p53DINPl P53-inducible p53D_NPl
384 L15533 PAP pancreatitis-associated protein
385 T56982 PDE7A phosphodiesterase 7A
386 C05229 PDK4 pyruvate dehydrogenase kinase, isoenzyme 4
387 N47861 PDF pyruvate dehydrogenase phosphatase
388 AF012281 PDZK1 PDZ domain containing 1
389 AA220941 PHB prohibitin
390 D38616 PHKA2 phosphorylase kinase, alpha 2 (liver)
391 L47738 PIR121 p53 inducible protein
392 X98654 PITPNM phosphatidylinositol transfer protein, membrane-associated
393 W19216 PKIG protein kinase (cAMP-dependent, catalytic) inhibitor gamma
394 AF064594 PLA2G6 phospholipase A2, group VI (cytosolic, calcium-independent)
395 AF038440 PLD2 phospholipase D2
396 D87810 PMM1 phosphomannomutase 1
397 J05125 PNLIP pancreatic lipase
398 Z11898 POU5F1 POU domain, class 5, transcription factor 1
399 AI343963 PP2135 PP2135 protein
400 U57961 13CDNA73 putative gene product
401 AI094447 PP5395 hypothetical protein PP5395
402 S74349 PPARA peroxisome proliferative activated receptor, alpha
403 AB007851 PRPSAP2 phosphoribosyl pyrophosphate synthetase-associated protein 2
404 AA845165 PRSS1 protease, serine, 1 (trypsin 1)
405 D88378 PSMF1 proteasome (prosome, macropain) inhibitor subunit 1 (PI31)
406 U68142 RAB2L RAB2, member RAS oncogene family-like
407 AI277086 RAGB GTP-binding protein ragB
408 AA972852 RBP1 retinol-binding protein 1, cellular
409 X00129 RBP4 retinol-binding protein 4, interstitial
410 AA807607 RDGBB retinal degeneration B beta
411 AA428540 REC8 Rec8p regenerating islet-derived 1 alpha (pancreatic stone protein,
412 Ml 8963 REG1A pancreatic thread protein)
413 AC004003 RIPK2 receptor-interacting serine-threonine kinase 2
414 AI341482 RNB6 RNB6
415 AW510670 RNF3 ring finger protein 3
416 U38894 ROR1 receptor tyrosine kinase-like orphan receptor 1
417 X65463 RXRB retinoid X receptor, beta
418 U72355 SAFB scaffold attachment factor B
419 AI338007 SCDGF-B Spinal cord-derived growth factor-B
420 AA911283 SCMH1 sex comb on midleg homolog 1 small inducible cytokine subfamily D (Cys-X3-Cys), member 1
421 U84487 SCYD1 (fractalkine, neurotactin)
422 W73992 SDCCAG43 serologically defined colon cancer antigen 43 sema domain, immunoglobulin domain (Ig), short basic domain,
423 U28369 SEMA3B secreted, (semaphorin) 3B sema domain, immunoglobulin domain (Ig), short basic domain,
424 U38276 SEMA3F secreted, (semaphorin) 3F
425 AI026695 SENP1 Sentrin SUMO-specific protease
426 Z11793 SEPP1 selenoprotein P, plasma, 1
serine (or cysteine) proteinase inhibitor, clade A (alpha antiproteinase, antitrypsin), member 4 serine (or cysteine) proteinase inhibitor, clade A (alpha
428 J02943 SERPINA6 antiproteinase, antitrypsin), member 6 serine (or cysteine) proteinase inhibitor, clade G (Cl inhibitor),
429 M13690 SERPING1 member 1
430 AF017988 SFRP5 secreted frizzled-related protein 5
431 N56912 SFTPC surfactant, pulmonary-associated protein C
432 Y10032 SGK serum/ lucocorticoid regulated kinase
433 AI198522 SLC11A3 solute carrier family 11, member 3
434 U59299 SLC16A5 solute carrier family 16, member 5
435 AA243675 SLC1A1 solute carrier family 1, member 1
Solute carrier family 25 (mitochondrial carrier; citrate
436 AA435777 SLC25A1 transporter), member 1 solute carrier family 2 (facilitated glucose transporter), member
437 NM 000340 SLC2A2 solute carrier family 3 (cystine, dibasic and neutral amino acid
438 M95548 SLC3A1 transporters, activator of cystine, dibasic and neutral amino acid transport), member 1 solute carrier family 4, sodium bicarbonate cotransporter,
439 AF007216 SLC4A4 member 4
440 M24847 SLC5A1 solute carrier family 5 (sodium/glucose cotransporter), member 1
SWI/SNF related, matrix associated, actin dependent regulator of
441 AA902273 SMARCD3 chromatin, member 3
442 U41303 SNRPN small nuclear ribonucleoprotein polypeptide N
443 AA604446 SPINK5 serine protease inhibitor, Kazal type, 5
444 secreted phosphoprotein 1 (osteopontin, bone sialoprotein I,
J04765 SPP1 early T-lymphocyte activation 1)
445 L14865 SSTR5 somatostatin receptor 5 transforming growth factor beta-activated kinase-binding protein
446 R60028 TAB1
1 transcription factor 2, hepatic; LF-B3; variant hepatic nuclear
447 X58840 TCF2 factor
448 J05068 TCN1 transcobalamin I (vitamin B12 binding protein, R binder family)
449 L15203 TFF3 trefoil factor 3 (intestinal)
450 D29992 TFPI2 tissue factor pathway inhibitor 2
451 AA403273 transducin-like enhancer of split 1, homolog of Drosophila
TLE1
E(spl)
452 U31449 TM4SF4 transmembrane 4 superfamily member 4
453 AA131918 TMEM3 transmembrane protein 3
454 U70321 TNFRSF14 tumor necrosis factor receptor superfamily, member 14 (herpesvirus entry mediator)
455 L21715 TNNI2 troponin I, skeletal, fast
456 AI091425 TONDU TONDU
457 U54831 TOP2B topoisomerase (DNA) II beta (180kD)
458 U44427 TPD52L1 tumor protein D52-like 1
459 M10605 TTR transthyretin (prealbumin, amyloidosis type I)
460 AI090567 TUBB2 tubulin, beta, 2
461 L13852 UBE1L ubiquitin-activating enzyme El -like
462 X63359 UGT2B10 UDP glycosyltransferase 2 family, polypeptide B10
463 J05428 UGT2B7 UDP glycosyltransferase 2 family, polypeptide B7
464 AA446913 USP11 ubiquitin specific protease 11
465 L13288 VIPR1 vasoactive intestinal peptide receptor 1
466 D78298 VLCAD very-long-chain acyl-CoA dehydrogenase
467 AA769424 VNN2 vanin 2
468 AF039022 XPOT exportin, tRNA (nuclear export receptor for tRNAs)
469 D83407 ZAKI4 Down syndrome critical region gene 1-like 1 zinc finger protein 145 (Kruppel-like, expressed in
470 Z19002 ZNF145 promyelocytic leukemia) zinc finger protein 42 (myeloid-specific retinoic acid-
471 M58297 ZNF42 responsive)
472 N24911 C1WRF2 chromosome 11 open reading frame2
473 All 86263 C210RF11 chromosome 21 open reading frame 11
474 Y11392 C210RF2 chromosome 21 open reading frame 2
475 H16793 C80RF4 chromosome 8 open reading frame 4
DKFZp434C
476 AI160590 hypothetical protein DKFZp434G0522
0522 DKFZP434J
477 T65389 DKFZP434J214 protein
214 DKFZP564F
478 H61870 DKFZP564F1123 protein
1123 DKFZP564K
479 AI218000 DKFZP564K1964 protein
1964 DKFZP586A
480 AI306435 DKFZP586A0522 protein
0522 DKFZP586B
481 W05570 DKFZP586B0621 protein
0621
482 N92489 FLJ10103 hypothetical protein FLJ10103
483 AA933772 FIJI 0252 hypothetical protein FLJ10252
484 AA452368 FLJ10582 hypothetical protein FLJ10582
485 AA481246 FU12287 hypothetical protein FLJ12287 similar to semaphorins
486 AI042204 FLJ12895 hypothetical protein FLJ12895
487 AI342612 FU20011 hypothetical protein FLJ20011
488 AA708532 FLJ20041 hypothetical protein FLJ20041
489 AIO 16890 F 20542 hypothetical protein FLJ20542
490 AA593701 FLJ21817 hypothetical protein FLJ21817 similar to Rhoip2
491 NM_022493 F 21988 hypothetical protein FLJ21988 hypothetical protein FLJ22649 similar to signal peptidase
492 N30915 F 22649 SPC22/23
Likely ortholog of mouse tumor necrosis-alpha-induced adipose-
493 AA650281 FU23153 related protein
494 AA522448 FLJ23239 hypothetical protein FLJ23239
495 AA403120 HT014 HT014
496 D31884 KIAA0063 KIAA0063 gene product
497 D87465 KIAA0275 KIAA0275 gene product
498 AI190847 KIAA0397 KIAA0397 gene product
499 AB011115 KIAA0543 KIAA0543 protein
500 AA910738 KIAA0579 KIAA0579 protein
501 AA156717 KIAA0668 KIAA0668 protein
502 W56303 KIAA0802 KIAA0802 protein
503 AA127777 KIAA1071 KIAA1071 protein
504 AI148832 KIAA1209 KIAA1209 protein
505 AA573892 KIAA1359 KIAA1359 protein
506 N54300 KIAA1500 KIAA1500 protein
507 N36929 KIAA1954 KIAA 1954 protein hypothetical protein, clone
508 AA477232 LOC56997 Telethon(Italy_B41)_Strait02270_FL142
509 AF001550 LOC57146 hypothetical protein from clone 24796
510 AA303231 LOC64744 hypothetical protein AL133206
511 AA044186 Homo sapiens cDNA FLJ11410 fis, clone HEMBA1000852
512 D62873 Homo sapiens cDNA FLJ12900 fis, clone NT2RP2004321
513 AA858162 Homo sapiens cDNA FLJ13005 fis, clone NT2RP3000441
514 AA327291 Homo sapiens cDNA FLJ13322 fis, clone OVARC1001713
515 AI096874 Homo sapiens cDNA FLJ14115 fis, clone MAMMA1001760
516 H28758 Homo sapiens cDNA: FLJ20925 fis, clone ADSE00963
517 T04932 Homo sapiens cDNA: FLJ21545 fis, clone COL06195
518 AK025906 Homo sapiens cDNA: FLJ22253 fis, clone HRC02763
519 AI344138 Homo sapiens cDNA: FLJ22288 fis, clone HRC04157
520 AA206578 Homo sapiens cDNA: FLJ22316 fis, clone HRC05262
521 R89624 Homo sapiens cDNA: FLJ22386 fis, clone HRC07619
522 AA404225 Homo sapiens cDNA: FLJ22418 fis, clone HRC08590
523 AI089485 Homo sapiens cDNA: FLJ22479 fis, clone HRC 10831
524 AA505312 Homo sapiens cDNA: FLJ22648 fis, clone HSI07329
525 R72460 Homo sapiens cDNA: FLJ22807 fis, clone KAIA2887
526 AAO 19961 Homo sapiens cDNA: FLJ22811 fis, clone KAIA2944
527 N46856 Homo sapiens cDNA: FLJ23091 fis, clone LNG07220
528 AA321321 Homo sapiens cDNA: FLJ23091 fis, clone LNG07220
529 AI084531 Homo sapiens cDNA: FLJ23093 fis, clone LNG07264
530 AA543086 Homo sapiens cDNA: FLJ23270 fis, clone COL10309
531 AA741042 Homo sapiens cDNA: FLJ23527 fis, clone LNG05966
532 AF009314 Homo sapiens clone TTJA8 Cri-du-chat region mRNA
533 AA293837 Homo sapiens GKAP42 (FKSG21) mRNA, complete cds
534 Homo sapiens mRNA full length insert cDNA clone
AA195740 EUROIMAGE 41832
Homo sapiens mRNA; cDNA DKFZp434M229 (from clone
535 AA829835 DKFZp434M229)
Homo sapiens mRNA; cDNA DKFZp564A026 (from clone
536 AA985007 DKFZp564A026)
Homo sapiens mRNA; cDNA DKFZp564Nl 116 (from clone
537 AA938345 DKFZp564Nl l l6)
Homo sapiens mRNA; cDNA DKFZp761K2024 (from clone
538 AA129758 DKFZp761K2024) I276126 Human DNA sequence from clone RP4-756G23 on chromosome
539 A 22ql3.313.33
ESTs, Highly similar to AF172268 1 Traf2 and NCK interacting
540 AI301241 kinase, splice variant 5
ESTs, Highly similar to AF219140 1 gastric cancer-related
541 AI291118 protein GCYS-20 [H.sapiens]
ESTs, Highly similar to 138945 melanoma ubiquitous mutated
542 AA143060 protein [H.sapiens]
543 AI304351 ESTs, Moderately similar to NFY-C [H.sapiens]
ESTs, Weakly similar to cytokine receptor-like factor 2;
544 AA923049 cytokine receptor CRL2 precusor
545 AA604003 ESTs, Weakly similar to CTL1 protein [H.sapiens]
ESTs, Weakly similar to G786_HUMAN PROTEIN GS3786
546 AA847242 [H.sapiens]
547 AI274179 ESTs, Weakly similar to LJV protein [H.sapiens]
ESTs, Weakly similar to RAB8_HUMAN RAS-RELATED
548 R87741 PROTEIN RAB-8 [Rsapiens]
549 AA465193 ESTs, Weakly similar to unnamed protein product [H.sapiens]
550 AI266124 ESTs, Weakly similar to unnamed protein product [H.sapiens]
551 AA777360 KIAA1002 ESTs
552 AA358397 ESTs
553 AA129817 ESTs
554 F06091 ESTs
555 H42099 ESTs
556 AI090386 ESTs
557 AA449335 ESTs
558 AI243456 ESTs
559 AI355928 ESTs
560 R45502 ESTs
561 AA630642 ESTs
562 AA781393 ESTs
563 AA528243 ESTs
564 AA430699 ESTs
565 AA528190 ESTs
566 AA369905 ESTs
567 AI201894 ESTs
568 AI342469 ESTs
569 AA313152 ESTs
570 AI299327 ESTs
571 AI341332 ESTs
572 N33189 ESTs
573 W37776 ESTs
574 AI023557 ESTs
575 AA418448 ESTs
576 AA458558 ESTs
577 H52704 ESTs
578 AA142875 ESTs
579 AI366443 ESTs
580 H96559 ESTs
581 H98777 ESTs
582 AA989233 ESTs
583 AI032354 ESTs
584 W93000 ESTs
585 AA446184 ESTs
586 AI291207 ESTs
587 AA699359 ESTs
588 AA447217 ESTs
589 AA769604 ESTs
590 AI208970 ESTs
591 N93057 ESTs
592 AI225224 ESTs
593 W67193 ESTs
594 AI022649 ESTs
595 AA625553 ESTs
596 AA446064 ESTs
597 D61466 ESTs
598 H05777 ESTs
599 N30923 ESTs
600 AA135406 ESTs
601 AA661636 ESTs
602 H98796 ESTs
603 AI927063 ESTs
604 AA687594 ESTs
605 AA879280 ESTs
Table 5 Representative up-regulated genes with known function in pancreatic cancers
PNC Accession
Symbol Gene Name
Assignment No. genes involved in signal transduction pathway
12 AA916826 APP amyloid beta (A4) precursor protein (protease nexin-II,
Alzheimer disease)
13 L20688 ARHGDIB Rho GDP dissociation inhibitor (GDI) beta
59 L36645 EPHA4 EphA4
69 J03260 GNAZ guanine nucleotide binding protein (G protein), alpha z polypeptide
100 AA574178 KAI1 Kangai 1
119 AA458825 MTIF2 mitochondrial translational initiation factor 2
130 M80482 PACE4 paired basic amino acid cleaving system 4
135 M16750 PIM1 pim oncogene
151 X62006 PTB polypyrimidine tract binding protein (heterogeneous nuclear ribonucleoprotein I)
154 AA346311 RAI3 retinoic acid induced 3
156 S45545 RCV1 recoverin
163 D38583 S100A11 S100 calcium-binding protein Al 1 (calgizzarin)
164 AA308062 S100P SI 00 calcium-binding protein P
169 AF029082 SFN stratifin
177 J03040 SPARC secreted protein, acidic, cysteine-rich (osteonectin)
transcriptioi lal factors
8 AF047002 ALY transcriptional coactivator
44 AA905901 CRSP3 cofactor required for Spl transcriptional activation, subunit 3
(130kD)
63 L16783 FOXMl forkhead box Ml
66 AA418167 GATA3 GATA-binding protein 3
80 X92518 HMGIC high-mobility group (nonhistone chromosomal) protein isoform I-C
83 Ml 6937 HOXB7 homeo box B7
108 U24576 LM04 LIM domain only 4
120 X13293 MYBL2 v-myb avian myeloblas tosis viral oncogene homolog-like 2
155 X64652 RBMS1 RNA binding motif, single stranded interacting protein 1
180 M81601 TCEA1 transcription elongation factor A (SII), 1
cell adhesion and cytoskeleton
14 AF006086 ARPC3 actin related protein 2/3 complex, subunit 3 (21 kD)
28 AA557142 CD2AP CD2-associated protein
32 X63629 CDH3 cadherin 3, type 1, P-cadherin (placental)
38 AA977821 COL1A1 collagen, type I, alpha 1
39 J03464 COL1A2 collagen, type I, alpha 2
40 X14420 COL3A1 collagen, type III, alpha 1 (Ehlers-Danlos syndrome type IV, autosomal dominant)
41 AI140851 COL6A1 collagen, type VI, alpha 1
46 U16306 CSPG2 chondroitin sulfate proteoglycan 2 (versican)
62 X02761 FN1 fibronectin 1
98 M15395 ITGB2 integrin, beta 2 (antigen GDI 8 (p95), lymphocyte function- associated antigen 1; macrophage antigen 1 (mac) beta subunit)
104 J00269 KRT6A keratin 6A
131 L11370 PCDH1 protocadherin 1 (cadherin-like 1)
136 AA234962 PKP3 plakophilin 3
cell cycle
35 X54941 CKSl CDC28 protein kinase 1
63 L16783 FOXMl forkhead box Ml
102 U63743 KNSL6 kinesin-like 6 (mitotic centromere-associated kinesin)
143 AF044588 PRC1 protein regulator of cytokinesis 1
184 K02581 TKl thymidine kinase 1, soluble
Comparison of clinicopathological parameters with the expression profiles indicated that altered expression of 76 genes was associated with lymph-node metastasis and
fhat of 168 genes with liver metastasis. In addition, expression levels of 84 genes were related to the recurrence of disease. These genome-wide expression profiles should provide useful information for finding candidate genes whose products might serve as specific tumor markers and/or as molecular targets for treatment of patients with pancreatic cancer. Materials and Methods
Ldentification of genes responsible for clinicopathological data
Genes associated with clinicopathological features, such as lymph-node-positive (r) and -negative (n), liver metastasis-positive (r) and -negative (n), and early-recurrence (r) and late-recurrence (n), were chosen according to the these two criteria; (i) signal intensities are higher than the cut-off value in at least 80% of the cases; (ii) | Medr - Medn |>=0.5, where
Med indicates the median derived from log-transformed relative expression ratios in two groups. Genes were selected as candidates when they met the criteria with a permutation p- value of smaller than 0.05 in each clinicopathological status.
First, we applied a random permutation test to identify genes that were expressed differently in following two groups. The mean (μ) and standard deviation (σ) were calculated from the log-transformed relative expression ratios of each gene in node-positive (r) and node-negative (n) cases, liver-metastasis-positive (r) and -negative (n), and early-recurrence (r) and late-recurrence (n), respectively. A discrimination score (DS) for each gene was defined as follows: DS = (μr - μn) / (σr+ σ„)
We carried out permutation tests to estimate the ability of individual genes to distinguish with two groups; samples were randomly permutated between the two classes 10,000 times. Since the DS dataset of each gene showed a normal distribution, we calculated a P value for the user-defined grouping (Golub et al., 1999). For this analysis, we applied the expression data of 13 cases consisting of 4 lymph-node-positive and 9 negative cases, those of 11 cases consisting of 5 liver metastasis-positive and 6 negative cases, and those of 13 cases consisting of 7 early-recurrent cases and 6 late-recurrent cases. For these analyses were performed by using only StagelV cases according to UICC TNM classification.
Calculation of prediction score
We further calculated the prediction score of recurrence according to procedures described previously (Golub et al., 1999). Each gene (g;) votes for either early-recurrent cases or late-recurrent cases depending on whether the expression level (x,) in the sample is closer to the mean expression level of early-recurrent cases or late-recurrent cases in reference samples. The magnitude of the vote (VJ) reflects the deviation of the expression level in the sample from the average of the two classes:
We summed the votes to obtain total votes for the early-recurrent cases (V
r) and late-recurrent cases (V
n), and calculated PS values as follows: PS = ((V, - V
n) / (V
r + V
n)) xl 00 reflecting the margin of victory in the direction of either early-recurrent cases or late-recurrent cases. PS values range from -100 to 100; a higher absolute value of PS reflects a stronger prediction.
Evaluation of classification and leave-one-out test We calculated the classification score (CS) by using the prediction score of early- recurrent (PSr) and late-recurrent cases (PSn) in each gene set, as follows:
CS = (μPsr - μpsn) (^PSr + ^PSn) A larger value of CS indicates better separation of the two groups by the predictive-scoring system. For the leave-one-out test, one sample is withheld, the permutation p- value and mean expression levels are calculated using remaining samples, and the class of the withheld sample is subsequently evaluated by calculating its prediction score. We repeated this procedure for each of the 13 samples.
Results Identification of genes correlated with clinicopathological features Lymph-node metastasis and liver metastasis
In order to investigate relations between gene expression profiles and clinicopathological parameters, we searched genes that were possibly associated with lymph- node metastasis and liver metastasis that are important determining factors of patients' prognosis. We first examined the expression profiles and the status of lymph-node metastasis using nine lymph-node-positive and four node-negative cases, and identified 76 genes that
were associated with lymph node status by a random permutation (p-value <0.05) (Table 6). Of those, 35 genes were relatively up-regulated, and 41 genes were down-regulated in node- positive tumors (Figure 3) comparing with node-negative tumors as control. In addition, we compared expression profiles of 5 cases with predominant recurrence in liver with those of 6 cases with metastasis to other sites (local, peritoneal and chest). We identified 168 genes that showed altered expression patterns uniquely in cases that had liver metastasis (Table 7), and 60 of them were relatively up-regulated in tumors (Figure 4). These genes included some key factors which had been proposed to play crucial roles in tumor cell proliferation, invasion and metastasis: integrin, beta 4 (ITGB4) (Shaw et al., 1997), colony stimulating factor 1 (CSF1) (Chambers et al., 1997), basigin (BSG) (Guo et al., 2000), and kinesin-like 6 (KNSL6)
(Scanlan MJ et al., 2002). Hierarchical clustering analysis using these identified gene sets was also able to clearly classify the groups with regard to lymph node status or those with liver metastasis, respectively (Figure 3, 4).
Prognosis To further investigate genes that might be associated with prognosis, we compared expression profiles of 7 cases who had recurrence within 12 months after surgery (disease free interval <12 months; median 6.4 months) with those of 6 cases who had >12 months of disease free interval (median 17.0 months). As shown in Figure 5 A, we identified 84 genes that were expressed differently between these two groups using a random permutation method (p< 0.05).
In attempt on establishment of a predictive scoring system using gene expression pattern for recurrence after surgery, we rank-ordered above prognostic 84 candidate genes on the basis of the magnitude of their permutation p- values (Table 8) and calculated the prediction score by the leave-one-out test for cross-validation using top 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80 and 84 genes on the rank-ordered list. To determine the number of discriminating genes giving the best separation of the two groups, we calculated a classification score (CS) for each gene set (Figure 5B). As show in Figure 5C, the best separation was obtained when we used 30 genes consisting of top 17 genes of up-regulated in late recurrence cases genes and top 13 genes of up-regulated in early recurrence cases genes in our candidate list for scores calculation.
Discussion
Pancreatic cancer is characterized by very aggressive progression and rapid recurrence after surgical treatment. It has been reported that the cumulative 1-, 3-, and 5- year disease free survival rate were 66%, 7%, and 3% respectively, and median disease-free survival time was the only 8 months (Sperti et al., 1997). Most common recurrent sites are the local region and the liver, and distant metastases appear in the peritoneal cavity.
However, since the relationships between tumor characteristics and the recurrence patterns are still little understood, we compared the expression profiles to lymph-node status or liver metastasis. We identified 76 genes that might be associated with lymph-node status, and 168 genes with liver metastasis. These genes included some key molecules whose possible roles in tumor progression had been reported previously; ITGB4 and BSG were up-regulated in lymph-node positive cases, and KNSL6 and KRT8 were relatively up-regulated in liver metastasis cases. LTGB4 was reported to promote carcinoma invasion through a preferential and localized targeting of phosphoinositide-3 OH kinase activity (Shaw et al., 1997), supporting the possible involvement oϊITGB4 in lymph-node metastasis. KNSL6, a member of the kinesin family of motor proteins, is known to be involved in chromosome segregation during mitosis (Maney T et al., 1998). The transcript of KNSL6 was highly expressed in colon cancer, and was identified as cancer antigens associated with a cancer-related serum IgG response (Scanlan MJ et al., 2002). Thus, this antigen could be a biological marker for diagnosis and for monitoring of recurrence site. In addition, we identified 84 genes possibly associated with tumor recurrence of pancreatic cancers. Expression levels of a subset of 30 genes selected from these 84 genes would be useful for predicting the disease free interval after surgical operation (Figure 5). These results might be useful for selection of patients for active adjuvant therapy although larger-scale study will be required to further evaluate our prediction system.
Tableό A list of 76 Candidate Genes for lymph-node metastasis
PNC GenBank
Assign ™ Symbol Gene Name ment
UP-RE 1GGUULLAATTEEDD GGEENNEESS
606 D 16480 HADHA hydroxyacy dehydrogenase, subunitA
607 AF015767 BRE brain and reproductive organ-expressed (TNFRSF1A modulator)
608 D49742 HABP2 hyaluronan-binding protein 2
609 M37400 GOT1 glu tamic-oxaloacetic transaminase 1
610 Z11502 ANXA13 annexin A13
611 D32050 AARS alanyl-tRNA synthetase
612 U42376 LY6E lymphocyte antigen 6 complex, locus E
613 U68019 MADH3 MAD (mothers against decapentaplegic, Drosophila) homolog 3
614 AI248620 AP3D1 adaptor-related protein complex 3, delta 1 subunit
615 U24183 PFKM phosphofructokinase, muscle
616 AA193416 ESTs
617 AA911109 FLJ20254 hypothetical protein FLJ20254
618 AF070616 HPCAL1 hippocalcin-like 1
619 AI143127 Dynactin 4
620 AA412250 PYGB phosphorylase, glycogen; brain
621 D45131 BSG basigin
622 AB010427 WDR1 WD repeat domain 1
623 H20386 MYG1 MYG1 protein
624 AA371593 GCNILI GCNl (general control of amino-acid synthesis 1, yeast)-like 1
625 L31581 CCR7 chemokine (C-C motif) receptor 7
626 AA922357 DKFZp586A0618
627 U07424 FARSL phenylalanine-tRNA synthetase-like
628 AI248327 FLJ22233
DKFZP727
629 AF055022 DKFZP727M231 protein M231
630 M37435 CSF1 colony stimulating factor 1 (macrophage)
631 U34683 GSS glu tafhione synthetase
632 L41351 PRSS8 protease, serine, 8 (prostasin)
633 X52186 ITGB4 integrin, beta 4
634 R52161 DKFZp434A2410 eukaryotic translation initiation factor 2B, subunit 5 (epsilon,
635 U23028 EIF2B5
82kD)
636 AI336230 RPS8 ribosomal protein S8
637 AI268861 EST
638 U73036 IRF7 interferon regulatory factor 7
639 AI097058 FLJ23538
640 L36151 PIK4CA phosphatidylinositol 4-kinase, catalytic, alpha polypeptide
>OW_> f-REGULATED GENES
641 AA747290 RPS15A ribosomal protein SI 5a
642 AA641744 RPA2 replication protein A2 (32kD)
643 AI188196 USP22 ubiquitin specific protease 22
644 AI222007 ESTs
645 AA192445 TMEPAI transmembrane, prostate androgen induced RNA
646 AW069055 FLJ10773 Likely ortholog of mouse NPC derived proline rich protein 1
647 AI365733 ESTs
648 AF017418 MEIS2 Meis (mouse) homolog 2
649 AF024714 AIM2 absent in melanoma 2
650 AU155489 MMP7 matrix metalloproteinase 7 (matrilysin, uterine)
HUMAGCG
651 AW779142 chromosome 3p21.1 gene sequence B
652 AA487669 GSTM1 glutathione S-transferase Ml
653 AA601564 DLG5 discs, large (Drosophila) homolog 5
654 AI042204 FLJ12895 hypothetical protein FLJ12895
655 D14662 KIAA0106 anti-oxidant protein 2
656 BF059178 NONO non-POU-domain-containing, octamer-binding
657 U70063 ASAH N-acylsphingosine amidohydrolase (acid ceramidase)
658 AA091553 UBE2H ubiquitin-conjugating enzyme E2H (homologous to yeast UBC8)
659 L12350 THBS2 thrombospondin 2
660 AA324335 ERF. Ets2 repressor factor
661 AI626007 NTRK1 neurotrophic tyrosine kinase, receptor, type 1
662 AI261382 SH120 putative G-protein coupled receptor
663 AF046024 UBEIC ubiquitin-activating enzyme EIC (homologous to yeast UBA3) protein phosphatase 3 (formerly 2B), catalytic subunit, alpha
664 AI299911 PPP3CA isoform
665 X07979 ITGB1 integrin, beta 1
666 W45244 C3 complement component 3
667 AI245516 EST
668 AA907519 C30RF4 chromosome 3 open reading frame 4
669 D42041 KIAA0088 KIAA0088 protein
670 AI300002 CCNI cyclin I enhancer of filamentation 1 (cas-like docking; Crk-associated
671 AI338165 HEF1 substrate related)
672 AI312689 HE1 epididymal secretory protein (19.5kD)
NM 00607
673 CBARA1 calcium binding atopy-related autoantigen 1
7
674 AF131847 MRG15 MORF-related gene 15
675 AA676585 NPM1 nucleophosmin (nucleolar phosphoprotein B23, numatrin) transcription factor AP-2 gamma (activating enhancer-binding
676 U85658 TFAP2C protein 2 gamma)
677 ABO 11090 KIAA0518 Max-interacting protein
678 U93867 RPC62 polymerase (RNA) III (DNA directed) (62kD)
679 Z11531 EEF1G eukaryotic translation elongation factor 1 gamma
680 AA676322 MTF1 metal-regulatory transcription factor 1
681 AI339006 DKFZp586L1121
Table7 A list of 168 Candidate Genes for liver metastasis
PNC
GenBank
Assign Symbol Gene Name ID ment
UP-REGULATED GENES
682 U63743 KNSL6 kinesin-like 6 (mitotic centromere-associated kinesin)
683 U12707 WAS Wiskott-Aldrich syndrome (eczema-thrombocytopenia)
684 AA904028 PAPPA pregnancy-associated plasma protein A
685 T69711 EST
Homo sapiens mRNA; cDNA DKFZp566L203 (from clone
686 AI338282 TIGA1
DKFZp566L203) inhibitor of DNA binding 2, dominant negative helix-loop-helix
687 AA843756 ID2 protein
688 AF076483 PGLYRP peptidoglycan recognition protein
689 AA447852 PC326 PC326 protein
690 L13939 AP1B1 adaptor-related protein complex 1, beta 1 subunit
691 AI344213 CCS copper chaperone for superoxide dismutase
692 X74929 KRT8 keratin 8
693 U92459 GRM8 glutamate receptor, metabotropic 8
694 AA078295 ESTs
695 AA084871 YKT6 SNARE protein
696 M26252 PKM2 pyruvate kinase, muscle
697 AI280555 KIAA0860 KIAA0860 protein
698 U09278 FAP fibroblast activation protein, alpha
699 AA989386 EST
700 U01184 FLU flightless I (Drosophila) homolog
NM 0164
701 HSPC138 hypothetical protein 01
AW24510
702 E2IG3 putative nucleotide binding protein, estradiol-induced 1
703 U47025 PYGB phosphorylase, glycogen; brain
704 Z21507 EEF1D eukaryotic translation elongation factor 1 delta
705 U38320 MMP19 matrix metalloproteinase 19
706 AA233644 PPPICC protein phosphatase 1, catalytic subunit, gamma isoform
707 L40401 ZAP128 peroxisomal long-chain acyl-coA thioesterase ; putative protein
708 AI365683 Homo sapiens PAC clone RP4-751H13 from 7q35-qter
709 AF039690 SDCCAG8 serologically defined colon cancer antigen 8
710 L19067 RELA v-rel avian re ticuloendofheliosis viral oncogene homolog A
711 U48734 ACTN4 actinin, alpha 4
712 M22324 ANPEP alanyl (membrane) aminopeptidase
713 AA921921 KIAA0414 KIAA0414 protein
714 X97630 EMK1 ELKL motif kinase
715 AJ002308 SYNGR2 synaptogyrin 2
716 AA447019 MANIBI mannosidase, alpha, class IB, member 1
717 M98252 PLOD procollagen-lysine, 2-oxoglutarate 5-dioxygenase
718 H48649 FGG fibrinogen, gamma polypeptide
719 AI139231 FBL fibrillarin
720 AA249454 ESTs, Weakly similar to KIAA0227 [H.sapiens]
721 U89278 EDR2 early development regulator 2 (homolog of polyhomeotic 2)
722 M24398 PTMS parathymosin
723 L41668 GALE galactose-4-epimerase, UDP-
724 D78298 VLCAD very-long-chain acyl-CoA dehydrogenase
HSRTSBET
725 X89602 rTS beta protein
A
726 M91029 AMPD2 adenosine monophosphate deaminase 2 (isoform L)
727 X73478 PPP2R4 protein phosphatase 2A, regulatory subunit B' (PR 53)
728 All 89477 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial
729 D30612 ZNF282 zinc finger protein 282
730 AA506972 KIAA0668 KIAA0668 protein
731 AA404724 GPRK7 G protein-coupled receptor kinase 7
732 AB001451 SLI neuronal She adaptor homolog
733 AL120683 LASS2 LAG1 longevity assurance homolog 2 (S. cerevisiae)
734 H20386 MYG1 MYG1 protein
735 AA477862 KIAA0974 KIAA0974 protein
736 AF075590 BZRP benzodiazapine receptor (peripheral)
737 AA748421 TFR2 transferrin receptor 2
738 AA639771 MMP12 matrix metalloproteinase 12 (macrophage elastase)
ESTs, Moderately similar to integral inner nuclear membrane
739 AI218495 protein MAN1
DKFZP586
740 N80334 hypothetical protein O0223
741 AA847660 HEXA hexosaminidase A (alpha polypeptide)
>OW f-REGULATED GENES
742 S74678 HNRPK heterogeneous nuclear ribonucleoprotein K
743 D56784 DEK DEK oncogene (DNA binding)
744 U31383 GNG10 guanine nucleotide binding protein 10
745 H06970 STK24 serine/threonine kinase 24 (Ste20, yeast homolog)
ATPase, H+ transporting, lysosomal (vacuolar proton pump),
746 AF038954 ATP6J member J
747 W19984 DREV1 CGI-81 protein
748 AA282650 SAC1 Suppressor of actin 1
749 U16738 RPL14 ribosomal protein L14
750 AA614311 VCP valosin-containing protein
751 AF006088 ARPC5 actin related protein 2/3 complex, subunit 5 (16 kD)
752 AF007871 DYT1 dystonia 1, torsion (autosomal dominant; torsin A)
753 D21090 RAD23B RAD23 (S. cerevisiae) homolog B
754 AA910279 STAU staufen (Drosophila, RNA-binding protein)
755 AA226073 ITM2C integral membrane protein 2C
756 AA583455 RNF7 ring finger protein 7
757 AA731151 KIAA1085 KIAA1085 protein
758 U14575 PPP1R8 protein phosphatase 1, regulatory (inhibitor) subunit 8
759 M81637 GCL grancalcin
760 L37368 RNPS1 RNA-binding protein SI, serine-rich domain
761 AK000403 FLJ20396 hypothetical protein FLJ20396
762 D13315 GLOl glyoxalase I
763 U66818 UBE2I ubiquitin-conjugating enzyme E2I (homologous to yeast UBC9)
764 X56351 ALAS1 aminolevulinate, delta-, synthase 1
765 L08424 ASCL1 achaete-scute complex (Drosophila) homolog-like 1
766 X15187 TRAl tumor rejection antigen (gp96) 1
767 U33286 CSE1L chromosome segregation 1 (yeast homolog)-like
768 AA747290 RPS15A ribosomal protein SI 5a
769 AI148832 KIAA1209 KIAA1209 protein
770 S65738 ADF destrin (actin depolymerizing factor)
771 X53586 ITGA6 integrin, alpha 6
772 U31906 GOLGA4 golgi autoantigen, golgin subfamily a, 4
773 AA664213 DKC1 dyskeratosis congenita 1, dyskerin enhancer of filamentation 1 (cas-like docking; Crk-associated
774 AI338165 HEF1 substrate related)
775 W74416 LOC51126 N-terminal acetyltransferase complex ardl subunit
776 AI125978 SNX2 sorting nexin 2
777 H96478 EST
778 U46570 TTC1 tetratricopeptide repeat domain 1
779 U21242 GTF2A2 general transcription factor IIA, 2 (12kD subunit)
780 W95089 HSPC033 HSPC033 protein
781 D55654 MDH1 malate dehydrogenase 1, NAD (soluble) protein kinase, interferon-inducible double stranded RNA
782 AF072860 PRKRA dependent activator
783 AF042081 SH3BGRL SH3 domain binding glutamic acid-rich protein like
784 D63881 KIAA0160 KIAA0160 protein
Homo sapiens mRNA full length insert cDNA clone
785 AA195740
EUROIMAGE 41832
786 M36341 ARF4 ADP-ribosylation factor 4
787 C06051 JAK1 Janus kinase 1 (a protein tyrosine kinase)
788 D28473 MRS isoleucine-tRNA synthetase
789 R23830 ESTs
790 U51166 TDG thymine-DNA glycosylase
791 AA128470 DSP desmoplakin (DPI, DPII)
792 M77698 YY1 YY1 transcription factor
793 AI272932 BAG5 BCL2-associated athanogene 5
794 U45879 BIRC2 baculoviral IAP repeat-containing 2
795 Z35491 BAG1 BCL2-associated a hanogene
796 AF016507 CTBP2 C-terminal binding protein 2
797 X89478 HRB HTV Rev binding protein
798 X06323 MRPL3 mitochondrial ribosomal protein L3
799 M29065 HNRPA2B1 heterogeneous nuclear ribonucleoprotein A2/B1
800 AA431846 LOC51187 60S ribosomal protein L30 isolog
801 E02628 polypeptide chain elongation factor 1 alpha
802 AI349804 EST
803 X99584 SMT3H1 SMT3 (suppressor of mif two 3, yeast) homolog 1
804 D13630 KIAA0005 KIAA0005 gene product
805 U24223 PCBP1 poly(rC)-binding protein 1
806 AA315729 FLJ23197
DKFZP566
807 AA401318 DKFZP566D193 protein D193
808 AA524350 LOC51719 M025 protein
809 AB004857 SLC11A2 solute carrier family 11, member 2
810 AA379042 PUM2 Pumilio (Drosophila) homolog 2
AW77914 HUMAGCG
811 chromosome 3p21.1 gene sequence 2 B
812 R39044 Homo sapiens clone 25194 mRNA sequence
813 M58458 RPS4X ribosomal protein S4, X-linked
814 H89110 ESTs
815 U47077 PRKDC protein kinase, DNA-activated, catalytic polypeptide
816 AA236252 ASH2L ash2 (absent, small, or homeotic, Drosophila, homolog)-like
817 D50683 TGFBR2 transforming growth factor, beta receptor II (70-80kD)
818 M61199 SSFA2 sperm specific antigen 2
819 U56637 CAPZAl capping protein (actin filament) muscle Z-line, alpha 1
820 AA514818 KIAA0068 KIAA0068 protein
821 N45298 ARHGEF12 Rho guanine exchange factor (GEF) 12
822 X76104 DAPK1 death-associated protein kinase 1
823 D14812 KIAA0026 MORF-related gene X
824 AA357508 Homo sapiens clone 24711 mRNA sequence
825 U96915 SAP18 sin3 -associated polypeptide, 18kD myristoylated alanine-rich protein kinase C substrate (MARCKS,
826 D 10522 MACS
80K-L)
827 N46856 Homo sapiens cDNA: FLJ23091 fis, clone LNG07220
828 D26125 AKR1C4 aldo-keto reductase family 1, member C4
829 AI085802 CAV2 Caveolin 2
830 AI289407 ZNF207 zinc finger protein 207
831 U54831 TOP2B topoisomerase (DNA) II beta (180kD)
832 AA281115 UBQLN1 ubiquilin 1 833 N41902 CLTH Clafhrin assembly lymphoid-myeloid leukemia gene
834 AA432312 TSPYL TSPY-like
835 AF006516 SSH3BP1 spectrin SH3 domain binding protein 1
836 AA706503 EEFIAI eukaryotic translation elongation factor 1 alpha 1
837 N95414 ESTs
838 M20472 CLTA clathrin, light polypeptide (Lea)
839 AI078833 TAXIBPI Taxi (human T-cell leukemia virus type I) binding protein 1
840 U09953 RPL9 ribosomal protein L9
841 U44772 PPT1 palmitoyl-protein thioesterase 1
842 AA973853 Homo sapiens cDNA FLJ20532 fis, clone KAT10877
843 U81504 AP3B1 adaptor-related protein complex 3, beta 1 subunit
844 AA634090 HNRPAI heterogeneous nuclear ribonucleoprotein Al
845 U83463 SDCBP syndecan binding protein (syntenin)
846 AI092703 FBXW1B f-box and WD-40 domain protein IB
847 AF052113 Rabl4 GTPase RabH solute carrier family 4, sodium bicarbonate cotransporter,
848 AF007216 SLC4A4 member 4
849 AA809819 CREG cellular repressor of ElA-stimulated genes
Table8 A list of 84 Candidate Genes for prognosis
PNC
GenBank
Assign Symbol Gene Name ID ment up-regulated in late recurrence cases 850 AF049884 ARGBP2 Arg/Abl-interacting protein ArgBP2 NM 0060
851 CBARAl calcium binding atopy-related autoantigen 1
77
852 Z11531 EEF1G eukaryotic translation elongation factor 1 gamma
AW15720
853 LCAT lecithin-cholesterol acyltransferase 3
854 AI123363 RPL23A ribosomal protein L23a
855 X53777 RPL17 ribosomal protein LI 7
856 U16798 ATP1A1 ATPase, Na+/K+ transporting, alpha 1 polypeptide
857 X76013 QARS glutaminyl-tRNA synthetase
858 AF075590 BZRP benzodiazapine receptor (peripheral)
859 L38995 TUFM Tu translation elongation factor, mitochondrial
860 H89783 SERPINA4 serine (or cysteine) proteinase inhibitor, clade A , member 4
861 D83782 SCAP SREBP CLEAVAGE-ACTIVATING PROTEIN
862 M75126 HK1 hexokinase 1
863 AA936173 RPS11 ribosomal protein SI 1
864 AA488766 SYNGR2 synap togyrin 2
865 M60922 FLOT2 flotillin 2
866 D26600 PSMB4 proteasome (prosome, macropain) subunit, beta type, 4
867 L19711 DAG1 dystroglycan 1 (dystrophin-associated glycoprotein 1)
868 AI148194 Novel human gene mapping to chomosome 22
869 X57398 PM5 pM5 protein
870 M17886 RPLP1 ribosomal protein, large, PI protein phosphatase 3 (formerly 2B), catalytic subunit, alpha
871 L14778 PPP3CA isofoπn (calcineurin A alpha)
872 AA156481 RPL13A ribosomal protein LI 3a
873 AA083406 EIF3S8 eukaryotic translation initiation factor 3, subunit 8 (1 lOkD)
DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide, Y
874 AF000984 DBY chromosome
875 XI 7206 RPS2 ribosomal protein S2
876 W45522 LOC51189 ATPase inhibitor precursor
ATP synthase, H+ transporting, mitochondrial FI complex, O
877 X83218 ATP50 subunit
878 AI246699 CATX-8 CATX-8 protein
879 AA029875 CASP4 caspase 4, apoptosis-related cysteine protease
880 AI366139 MAC30 hypothetical protein
881 U46191 RAGE renal tumor antigen
882 AA487669 GSTM1 glutathione S-transferase Ml
883 AI131289 RPLP2 ribosomal protein, large P2
884 AI299327 ESTs
885 AA922716 PRKACB protein kinase, cAMP-dependent, catalytic, beta
886 AA845165 PRSS1 protease, serine, 1 (trypsin 1)
887 AA877534 GPRC5C G protein-coupled receptor, family C, group 5, member C
888 C01335 ESTs, Weakly similar to FLDED [H.sapiens]
889 Z26876 RPL38 ribosomal protein L38
890 AI080640 AGR2 anterior gradient 2 (Xenepus laevis) homolog
891 X04588 TPM3 2.5kb mRNA for cytoskeletal tropomyosin TM30
Homo sapiens cDNA FLJ12750 fis, clone NT2RP2001168,
892 D30949 weakly similar to VERPROLIN
893 Z11559 ACOl aconitase 1, soluble up-regulated in early recurrence cases
894 AA700379 MTMR1 myotubularin related protein 1
895 AI340331 HT010 uncharacterized hypothalamus protein HT010
896 AA459167 NPD002 NPD002 protein
897 AI014395 YME1L1 YME1 (S.cerevisiae)-like 1
898 M94083 CCT6A chaperonin containing TCP1, subunit 6A (zeta 1)
899 M22382 HSPD1 heat shock 60kD protein 1 (chaperonin)
900 AA150867 TIMM9 translocase of inner mitochondrial membrane 9 (yeast) homolog
901 L76687 GRB14 growth factor receptor-bound protein 14
902 T70782 FLJ10803 hypothetical protein FLJ10803
903 AIO 18632 LAMP1 lysosomal-associated membrane protein 1
904 AA531437 MLLT4 myeloid/ lymphoid or mixed-lineage leukemia translocated to, 4
905 AI075048 CTSB cathepsin B
906 AL031668 RALY RNA-binding protein (autoantigenic)
907 AI357601 RPL37A ribosomal protein L37a
908 U51586 SMHBP1 siah binding protein 1
909 AF004430 TPD52L2 tumor protein D52-like 2
910 AI279562 KIAA0469 KIAA0469 gene product
911 Ml 1717 HSPA1A heat shock 70kD protein 1A brain and reproductive organ-expressed (TNFRSF1A
912 AF015767 BRE modulator)
913 X06323 MRPL3 mitochondrial ribosomal protein L3
914 AI305234 ESTs
915 W24533 GRB10 growth factor receptor-bound protein 10
916 AA504081 CSH2 chorionic somatomammotropin hormone 2
917 AA778572 HSPC164 hypothetical protein
918 D11999 GLS glutaminase
919 D32050 AARS alanyl-tRNA synthetase
920 D63997 GOLGA3 golgi autoantigen, golgin subfamily a, 3
921 R64726 Homo sapiens cDNA: FLJ23591 fis, clone LNG14729
922 M61715 WARS tryptophanyl-tRNA synthetase
923 AI090753 SHMT2 serine hydroxymethyltransferase 2 (mitochondrial)
DKFZP761C
924 AI289991 hypothetical protein DKFZp761C169 169
925 AA345061 KLAA0903 KIAA0903 protein
Human DNA sequence from clone RP3-324017 on
926 AA255699 chromosome 20
927 H73961 ARPC3 actin related protein 2/3 complex, subunit 3 (21 kD)
928 D87666 GPI glucose phosphate isomerase
929 AI075943 SENP2 sentrin-specific protease
930 D87989 UGTREL1 UDP-galactose transporter related
931 D86956 HSP105B heat shock 105kD
932 L13740 NR4A1 nuclear receptor subfamily 4, group A, member 1
933 AA320379 POH1 26S proteasome-associated padl homolog
Industrial Applicability
The gene-expression analysis of pancreatic cancer described herein, obtained through a combination of laser-capture dissection and genome- wide cDNA microarray, has identified specific genes as targets for cancer prevention and therapy. Based on the expression of a subset of these differentially expressed genes, the present invention provides a molecular diagnostic markers for identifying or detecting pancreatic cancer.
The methods described herein are also useful in the identification of additional molecular targets for prevention, diagnosis and treatment of pancreatic cancer. The data reported herein add to a comprehensive understanding of pancreatic cancer, facilitate development of novel diagnostic strategies, and provide clues for identification of molecular targets for therapeutic drugs and preventative agents. Such information contributes to a more profound understanding of pancreatic tumorigenesis, and provide indicators for developing novel strategies for diagnosis, treatment, and ultimately prevention of pancreatic cancer. All patents, patent applications, and publications cited herein are incorporated by reference in their entirety. Furthermore, while the invention has been described in detail and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention.
REFERENCES
1. Greenlee, R. T., Hill-Harmon, M. B., Murray, T., and Thun, M. Cancer statistics, 2001. CA Cancer J Clin, 51: 15-36, 2001. 2. Klinkenbijl, J. H., Jeekel, J., Sahmoud, T., van Pel, R., Couvreur, M. L., Veenhof, C. H., Arnaud, J. P., Gonzalez, D. G., de Wit, L. T., Hennipman, A., and Wils, J. Adjuvant radiotherapy and 5-fluorouracil after curative resection of cancer of the pancreas and periampullary region: phase III trial of the EORTC gastrointestinal tract cancer cooperative group. Ann Surg, 230: 116-182; discussion 782-774, 1999.
3. Ishiguro, H., Shimokawa, T., Tsunoda, T., Tanaka, T., Fujii, Y., Nakamura, Y., and Furukawa, Y. Isolation of HELAD1, a novel human helicase gene up-regulated in colorectal carcinomas. Oncogene, 21: 6387-6394, 2002.
4. Yagyu, R., Hamamoto, R., Furukawa, Y., Okabe, H., Yamamura, T., and Nakamura, Y. Isolation and characterization of a novel human gene, VANGLl, as a therapeutic target for hepatocellular carcinoma. Int J Oncol, 20: 1173-1178, 2002.
5. Iacobuzio-Donahue, C. A., Maitra, A., Shen-Ong, G. L., van Heek, T., Ashfaq, R., Meyer, R., Walter, K., Berg, K., HoUingsworth, M. A., Cameron, J. L., Yeo, C. J., Kern, S. E., Goggins, M., and Hruban, R. H. Discovery of novel tumor markers of PNC using global gene expression technology. Am J Pathol, 160: 1239-1249, 2002.
6. Han, H., Bearss, D. J., Browne, L. W., Calaluce, R., Nagle, R. B., and Von Hoff, D. D. Identification of differentially expressed genes in PNC cells using cDNA microarray. Cancer Res, 62: 2890-2896, 2002.
7. Bockman, D. E., Boydston, W. R., and Parsa, I. Architecture of human pancreas: implications for early changes in pancreatic disease. Gastroenterology, 85: 55-61,
1983.
8. Hruban, R. H., Wilentz, R. E., and Kern, S. E. Genetic progression in the pancreatic ducts. Am J Pathol, 156: 1821-1825, 2000.
9. Kitahara, O., Furukawa, Y., Tanaka, T., Kihara, C, Ono, K., Yanagawa, R., Nita, M. E., Takagi, T., Nakamura, Y., and Tsunoda, T. Alterations of gene expression during colorectal carcinogenesis revealed by cDNA microarrays after laser-capture microdissection of tumor tissues and normal epithelia. Cancer Res, 61: 3544-3549, 2001.
10. Gjerdrum, L. M., Lielpetere, I., Rasmussen, L. M., Bendix, K., and Hamilton-Dutoit, S. Laser-assisted microdissection of membrane-mounted paraffin sections for polymerase chain reaction analysis: identification of cell populations using immunohistochemistry and in situ hybridization. J Mol Diagn, 3: 105-110, 2001.
11. Ono, K., Tanaka, T., Tsunoda, T., Kitahara, O., Kihara, C, Okamoto, A., Ochiai, K., Takagi, T., and Nakamura, Y. Identification by cDNA microarray of genes involved in ovarian carcinogenesis. Cancer Res, 60: 5007-5011, 2000.
12. Saito-Hisaminato, A., Katagiri, T., Kakiuchi, S., Nakamura, T., Tsunoda, T., and Nakamura, Y. Genome- wide profiling of gene expression in 29 normal human tissues
with a cDNA microarray. DNA Res, 9: 35-45, 2002. 13. DiMagno EP, Reber HA, Tempero MA. AGA technical review on the epidemiology, diagnosis, and treatment of pancreatic ductal adenocarcinoma. American Gastroenterological Association. Gastroenterology. 1999 Dec; 117(6): 1464-84. Review. 14. Brentnall TA, Bronner MP, Byrd DR, Haggitt RC, Kimmey MB. Early diagnosis and treatment of pancreatic dysplasia in patients with a family history of pancreatic cancer. Ann Intern Med. 1999 Aug 17;131(4):247-55. 15. Rosenberg L. Pancreatic cancer: a review of emerging therapies. Drugs. 2000 May;59(5):1071-89. Review. 16. Hao D, Rowinsky EK. Inhibiting signal transduction: recent advances in the development of receptor tyrosine kinase and Ras inhibitors. Cancer Invest. 2002;20(3):387-404. Review. 17. Laheru D, Biedrzycki B, Jaffee EM. Immunologic approaches to the management of pancreatic cancer. Cancer J. 2001 J ul-Aug;7(4):324-37. Review. 18. Crnogorac-Jurcevic T, Efthimiou E, Nielsen T, Loader J, Terris B, Stamp G, Baron A, Scarpa A, Lemoine NR. Expression profiling of microdissected pancreatic adenocarcinomas. Oncogene. 2002 Jul 4;21(29):4587-94. 19. Ciardiello F, Tortora G. A novel approach in the treatment of cancer: targeting the epidermal growth factor receptor. Clin Cancer Res. 2001 Oct;7(10):2958-70. Review. 20. Slamon DJ, Leyland- Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, Fleming T, Eiermann W, Wolter J, Pegram M, Baselga J, Norton L. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. 2001 Mar 15;344(ll):783-92.
21. Rehwald U, Schulz H, Reiser M, Sieber M, Staak JO, Morschhauser F, Driessen C, Rudiger T, Muller-Hermelink K, Diehl V, Engert A. Treatment of relapsed CD20+
Hodgkin lymphoma with the monoclonal antibody rituximab is effective and well tolerated: results of a phase 2 trial of the German Hodgkin Lymphoma Study Group. Blood. 2003 Jan 15;101(2):420-424.
22. Violette S, Festor E, Pan drea-Vasile I, Mitchell V, Adida C, Dussaulx E, Lacorte JM, Chambaz J, Lacasa M, Lesuffleur T. Reg IV, a new member of the regenerating gene family, is overexpressed in colorectal carcinomas. Int J Cancer. 2003 Jan 10; 103(2): 185-93.
23. Kullander K, Mather NK, Diella F, Dottori M, Boyd AW, Klein R. Kinase-dependent and kinase-independent functions of EphA4 receptors in major axon tract formation in vivo. Neuron. 2001 Jan;29(l):73-84.
24. Rozenblum E, Schutte M, Goggins M, Hahn SA, Panzer S, Zahurak M, Goodman SN, Sohn TA, Hruban RH, Yeo CJ, Kern SE. Tumor-suppressive pathways in pancreatic carcinoma. Cancer Res. 1997 May l;57(9):1731-4.
25. Goggins M, Hruban RH, Kern SE. BRCA2 is inactivated late in the development of pancreatic intraepithelial neoplasia: evidence and implications. Am J Pathol. 2000 May; 156(5): 1767-71. 26. Ishiguro H, Tsunoda T, Tanaka T, Fujii Y, Nakamura Y, Furukawa Y. Identification of AXUD1, a novel human gene induced by AXINl and its reduced expression in human carcinomas of the lung, liver, colon and kidney. Oncogene. 2001 Aug 16;20(36):5062-6.
27. Satoh S, Daigo Y, Furukawa Y, Kato T, Miwa N, Nishiwaki T, Kawasoe T, Ishiguro H, Fujita M, Tokino T, Sasaki Y, Imaoka S, Murata M, Shimano T, Yamaoka Y,
Nakamura Y. AXINl mutations in hepatocellular carcinomas, and growth suppression in cancer cells by virus-mediated transfer of AXINl. Nat Genet. 2000 Mar;24(3):245- 50.
28. Yuan BZ, Miller MJ, Keck CL, Zimonjic DB, Thorgeirsson SS, Popescu NC. Cloning, characterization, and chromosomal localization of a gene frequently deleted in human liver cancer (DLC-1) homologous to rat RhoGAP. Cancer Res. 1998 May 15;58(10):2196-9.
29. Ng IO, Liang ZD, Cao L, Lee TK. DLC-1 is deleted in primary hepatocellular carcinoma and exerts inhibitory effects on the proliferation of hepatoma cell lines with deleted DLC-1. Cancer Res. 2000 Dec l;60(23):6581-4.
30. Fang G, Kim CN, Perkins CL, Ramadevi N, Winton E, Wittmann S and Bhalla KN. (2000). Blood, 96, 2246-2253.
31. Gianni L. (2002). Oncology, 63 Suppl 1, 47-56.
32. Klejman A, Rushen L, Morrione A, Slupianek A and Skorski T. (2002). Oncogene, 21, 5868-5876.