Cancer/testis (CT) antigens are immunogenic in cancer patients, exhibit highly tissue-restricted expression, and are considered promising target molecules for cancer vaccines. To date, 44 CT gene families have been identified and their expression studied in numerous cancer types. For example, bladder cancer, non-small cell lung cancer, and melanoma are high CT gene expressors, with 11/20 (55%), 17/33 (51%) and 17/32 (53%) of the CT transcripts examined by RT-PCR detected in 20% or more of the specimens examined, respectively. Breast and prostate cancer can be considered moderate CT gene expressors, with 12/32 (37%) and 6/20 (30%) CT transcripts having an expression frequency >20%, respectively, while renal and colon cancer are low CT gene expressors, with only 3/33 (9%) and 4/25 (16%) CT transcripts having an expression frequency >20%, respectively. In normal tissues, standardized RT-PCR experiments showed that 19/43 CT genes were testis-restricted, 10/43 CT genes were tissue-restricted (mRNA detected in 2 or fewer non-gametogenic tissues), 9/43 CT genes were differentially expressed (mRNA detected in 3-6 non-gametogenic tissues), and 5/43 CT genes were ubiquitously expressed. With the exception of testis-restricted CT transcripts, all remaining CT transcripts were expressed in normal pancreas. In terms of immunogenicity, 14/29 testis/tissue-restricted CT gene families have been shown to induce a cellular and/or humoral immune response in humans. In view of the expanding list of CT genes, a CT gene database was created to standardize CT nomenclature and accumulate relevant data regarding their expression profiles, immunogenicity, function (where known), gene structure and location, and orthologous groups.
This article was published in Cancer Immunity, a Cancer Research Institute journal that ceased publication in 2013 and is now provided online in association with Cancer Immunology Research.
The cancer/testis genes
Continued progress in the development of antigen-specific cancer vaccines depends in part on the identification of a wider spectrum of immunogenic gene products expressed predominately in human cancer. The foundations for our current efforts to define molecular targets for cancer vaccines were laid in the 1970s and 1980s with the establishment of autologous typing as the methodology to identify small subsets of patients with specific humoral or T cell immunity to their own tumor cells (1). This approach set the stage for the molecular definition of tumor antigens recognized by T cells by Boon and his colleagues (2, 3), and those recognized by antibodies by Pfreundschuh and his colleagues (4). The T cell epitope cloning technique developed by Boon et al. in 1991 (5) led to the discovery of the human tumor antigens MAGEA1 (3), BAGE (6), and GAGE1 (7). It was shown that mRNA transcripts encoding these gene products were present exclusively in normal testis and in a fraction of the samples analyzed for various cancer types. In 1995, Pfreundschuh and colleagues introduced the SEREX (serological expression cloning) approach to identify tumor antigens that elicit high-titer IgG antibody responses in cancer patients (4). Among the genes identified during these initial SEREX analyses of human cancer were SSX2 (4), NY-ESO-1 (8), and SYCP-1 (9), which like MAGE, BAGE, and GAGE, are expressed predominantly in normal testis and in cancer. In recognition of this expression profile shared by otherwise unrelated genes, the terms "cancer-testis (CT) antigen" (8) and "cancer-germline gene" (10) have been introduced to incorporate this heterogeneous group of tumor antigens.
The advent of high throughput mRNA expression analysis, including such techniques as representational difference analysis (RDA), differential display, and cDNA microarray analysis, as well as SAGE (serial analysis of gene expression) and EST (expressed sequence tag) sequencing, has prompted the search for additional gene products with mRNA expression profiles restricted to cancer and testis. For example, RDA led to the cloning of several transcripts, including LAGE-1 (11), MAGEE1/CT10 (12), and SAGE (13). Likewise, the CT genes CTp11/SPAN-X-C1 (14) and MMA-1A (15) were identified by differential display and oligonucleotide array analysis, respectively. Most recently, the bioinformatics based analysis of EST databases was used to identify several CT transcripts, including those derived from BRDT/CT9 (16), PAGE5/CT16 (17), LDHC (18), and TPTE (19). There is a clear distinction between CT genes identified by mRNA expression analysis and those identified through immunological methods; the former group has immunogenic potential, while the latter are known to be immunogenic in cancer patients.
As shown in Table 1, 44 distinct CT "gene" or "antigen" families have been reported in the literature. Certain CT gene families contain multiple members (e.g. MAGEA, GAGE1), as well as splice variants (e.g. XAGE1a, XAGE1b), and currently a total of 89 distinct transcripts are known to be encoded by CT genes. With the exception of the related genes in the MAGE-A, -B, -C and -E families, and the GAGE, XAGE, and PAGE families, there is no general evolutionary linkage between CT genes. Furthermore, the protein products of only 19/44 CT gene families (Table 2) have been demonstrated to elicit an immune response in humans. For this reason, it is more appropriate to consider them as a category of genes or gene products connected by a common expression pattern, rather than as a single family of genes or antigens.
The growing list of CT genes compels the field to implement a standard nomenclature. One can envision a situation similar to that of the "cluster of differentiation" or CD antigens, where hundreds of related molecules are defined. The CT classification system should provide a framework for accommodating a larger number of gene products and their relatedness, replacing the current "-AGE" nomenclature (e.g. MAGE, GAGE, BAGE, PAGE, CAGE, XAGE, CSAGE, HAGE, SAGE). A proposed scheme for the CT family has been suggested (20). Due to a general lack of information regarding the function of CT gene products, this nomenclature is based largely on their chronological order of discovery e.g. MAGEA is CT1; BAGE is CT2 etc. In cases were there are multiple family members, individual members are designated numerically e.g. SSX1 is CT5.1; SSX2 is CT5.2; SSX3 is CT5.3, and so on. In cases were there are multiple isoforms, individual splice variants are designated alphabetically, e.g. XAGE-1a is CT12.1a; XAGE-1b is CT12.1b; and XAGE-3a is CT12.3a. Finally, in deference to the original discovery, this nomenclature lists the given gene identifier in addition to the aforementioned nomenclature (e.g. SYCP1/CT8).
In view of the expanding list of CT genes and their significance in relation to antigen-specific cancer vaccines, we have recently created a CT gene database to accumulate relevant data at a single web interface (21). The CT Gene Database focuses on several characteristics of CT genes, including their expression profiles, immunogenicity, function (where known), gene structure and location, and orthologous groups. As an introduction to the database, this review examines the expression and immunogenicity of the current list of 44 CT gene families.
CT gene expression in cancer
A search of the EST (22) and SAGE (23) databases was used to verify CT gene expression in cancer. Of the 44 CT gene families, 34 were found to be represented by at least one EST derived from non-germ cell associated tumors. With the exception of tumor cell lines and germ cell tumors, no homologous ESTs for SAGE/CT14, NA88/CT18, CAGE/CT26, HOM-TES-85/CT28, LDHC/CT32, MORC/CT33, SPO11/CT35, NY-SAR-35/CT37, FTHL17/CT38, and TPTE/CT44 were present in more than 4,000 EST libraries derived from tumor tissue. However, a small number of SAGE tags corresponding to these ten CT transcripts were found in SAGE libraries derived from various non-germ cell related malignant tissues, indicating that these genes have a low expression frequency and/or a low transcript copy number in tumor tissue. Thus, it was possible to verify the expression of all founding members of each CT gene family in cancer using publicly available transcript data.
A survey of publications describing the expression frequencies of CT genes was used to generate an RT-PCR based expression profile for 41 of the 44 founding members of each CT gene family in 16 different cancer types (RT-PCR expression data in cancer was not available for IL13RA/CT19, CSAGE/CT24.1, and BORIS/CT27). As shown in Table 3, the scope of this expression profile varies with tumor type. Bladder cancer, breast cancer, colon cancer, non-small cell lung cancer, prostate cancer, renal cancer, and melanoma have been evaluated for the expression of more than 20 different CT gene families, while esophageal cancer, gastric cancer, head and neck cancer, ovarian cancer, leukemia/lymphoma, hepatocellular carcinoma, and sarcoma have been evaluated for the expression of 10-20 different CT families. On the other hand, brain and pancreatic cancer have been less widely studied, with the expression of fewer than ten CT gene families having been analyzed in these tumor types. It should be noted that the mRNA expression frequencies shown in Table 3 were obtained from numerous sources under non-standardized RT-PCR conditions. Therefore, it would be incorrect to directly compare the level of expression of individual CT genes in cancer using these data. However, they do permit generalized comparisons of CT expression in different tumor types.
Excluding brain and pancreatic cancers, which have been insufficiently studied with regard to CT transcript expression, the tumor types listed in Table 3 can be placed into three groups based on the number of CT genes expressed and their expression frequency: (i) High CT expressors: tumors which express more than 50% of the CT antigens examined at a expression frequency greater than 20% (a frequency of 20% of the specimens is above the average expression frequency of 16.1% for all CT transcripts shown in Table 3, n=305, SD ± 18.2); (ii) Moderate CT expressors: tumors which express between 30-50% of the CT transcripts examined at an expression frequency greater than 20%; and (iii) Low CT expressors: tumors which express less than 30% of the CT transcripts examined at an expression frequency greater than 20%. As mentioned above, seven tumor types (bladder cancer, breast cancer, colon cancer, non-small lung cancer, melanoma, prostate cancer and renal cancer) have been tested for expression of at least 20 CT transcript families. Of these, bladder cancer, non-small cell lung cancer, and melanoma are high expressors, where 11/20 (55%), 17/33 (51%) and 17/32 (53%) of the CT transcripts examined by RT-PCR were detected in 20% or more of the specimens examined, respectively. In turn, breast and prostate cancer can be considered moderate expressors, where 12/32 (37%) and 6/20 (30%) of the CT transcripts examined had an expression frequency of greater than 20% in these tumor types, respectively. On the other hand, renal cancer and colon cancer are low CT expressors, in that only 3/33 (9%) and 4/25 (16%) of the CT genes examined had an expression frequency of greater than 20% in these tumor types, respectively. These variations in the observed incidences of CT expression may, in part, stem from the fact that most colon and renal cancer specimens evaluated were from primary lesions, whereas most melanomas were metastatic lesions. Whether these differences in CT expression have significance with regard to tumor etiology or pathology needs to be explored. The conclusions of this analysis pointing to high CT expression in non-small cell lung cancer and melanoma, as well as infrequent expression in colon cancer and renal cancer, are in agreement with other recent overviews (24). On the other hand, the finding of frequent CT expression in bladder cancer is new. This adds another tumor type to the list of cancers (e.g. melanoma and lung cancer) that might be exceptionally suitable for treatment by immunotherapy with polyvalent CT antigen-based vaccines. Although these data provide a generalized view of the incidence of CT expression in cancer, individual tumor subtypes were not evaluated (e.g. adenocarcinoma vs. squamous cell carcinoma). Such analyses are infrequent (16, 25), though critical to fully understand the phenomenon of CT expression.
Seven tumor types (esophageal cancer, gastric cancer, head and neck cancer, leukemia/lymphoma, hepatocellular carcinoma, ovarian cancer, and sarcoma) have been examined for the expression of 10-20 CT transcript families. Of these seven tumor types, only hepatocellular carcinoma can be considered a high CT expressor. In hepatocellular carcinoma 8/10 CT genes examined were expressed in more than 20% of the specimens examined. Esophageal cancer, head and neck cancer, ovarian cancer, and sarcoma were identified as moderate CT transcript expressors, where 4/12 (33%), 5/15 (33%), 7/16 (43%), and 7/19 (37%) of the CT transcripts examined were detected at a frequency of greater than 20%, respectively. Both gastric cancer and leukemia/lymphoma are low CT transcript expressors, with 2/10 and 3/16 (approximately 20%) of the CT transcripts examined being detected at a frequency of at least 20%, respectively. Since a relatively small number of CT transcripts were examined in these seven tumor types, a more accurate assessment of the degree of CT expression in these cancers will depend upon further RT-PCR analyses involving additional CT transcripts.
It should be emphasized that these data correspond to mRNA expression frequencies, which do not necessarily directly correlate with protein expression frequencies. For example, only 2/14 or 14% of breast cancers were positive for NY-ESO-1/CT6.1 expression as measured by immunohistochemical analyses using the NY-ESO-1/CT6.1 specific monoclonal antibody ES121 (26). This study is in contrast to the NY-ESO-1/CT6.1 mRNA expression frequency of 30% (10/33 specimens) in breast cancer (8). Conversely, 9/11 (81%) invasive ductal carcinomas of the breast were positive for PLU-1/CT31 protein expression as judged by Western blotting using polyclonal antisera specific for PLU-1, which is consistent with its mRNA expression frequency [6/7 or 86% of breast cancer specimens (27)]. Discrepancies between gene and protein expression frequencies may reflect variations in tissue sampling, tumor heterogeneity or different levels of sensitivity of detection. Studies similar to those described by Jungbluth and colleagues (28), in which MAGEA1/CT1.1 transcript expression and MAGEA1/CT1.1 protein expression were directly compared in the same lung cancer specimens, are very useful in distinguishing between these possibilities. Unfortunately, the list of available monoclonal antibodies to CT proteins that can be used in an immunohistochemical or biochemical analysis of protein expression is relatively limited, but includes mAbs E975 and ES121 to NY-ESO-1/CT6.1 (29), mAb MA454 to MAGEA1/CT1.1 (30), and mAb CT7-33 to MAGEC1/CT7.1 (31), as well as mAbs that recognize multiple members of CT antigen families, such as mAb 57B to MAGEA/CT1 (32) and mAb E3AS to SSX/CT5 (33). Thus, monoclonal antibodies are currently available for only four of the protein products encoded by the 44 CT transcript families. The generation of additional monoclonal antibodies specific for CT proteins is essential for defining their tissue and tumor distribution.
CT transcript expression in normal tissues
A standardized, quantitative end-point RT-PCR assay was used to evaluate the expression profile of 44 genes representing founding members of each CT family in a series of normal tissues. End-point RT-PCR, as opposed to real-time PCR, was chosen as the assay system since it is the most widespread method used for analyzing CT transcript expression. In this standardized assay, the PCR primers and annealing temperatures were those described in the corresponding primary publications [see the CT Gene Database (21)]. A total of 35 PCR amplification cycles were performed in all experiments. The cDNA templates consisted of commercially available, normalized cDNA panels (MTC panels I and II, BD Biosciences, Palo Alto CA) encompassing 16 normal tissues (including the three gametogenic tissues ovary, testis and placenta), obtained from multiple (3-500) disease-free individuals. A "hot start" PCR master mix (Platinum PCR Super Mix, Invitrogen, Carlsbad CA), containing recombinant Taq DNA polymerase complexed with Taq antibody (20 U/ml), and deoxyribonucleotide triphosphates (200 µM), and MgCl2 (1.5 mM), was used in all experiments. The resultant PCR products were electrophoresed in 2% agarose/Tris-Acetate-EDTA (TAE) gels and quantified using a standard curve of signal intensities generated from simultaneous electrophoresis of molecular mass markers (Quanti-ladder, OriGene Technologies, Rockville MD). Signal intensities were calculated using digital image capture equipment (Kodak Image Station 440, Eastman Kodak, New Haven CT) and corresponding image analysis software (Kodak ID 3.6). Due to image saturation, the upper limit of quantification was 2.0 µg, while the sensitivity of the assay was limited to 0.01 µg cDNA. Gel images are available at the CT Gene Database (21).
As summarized in Table 4, standardized RT-PCR expression analysis segregated the CT family into four categories on the basis of normal tissue expression: (i) testis-restricted transcripts, (ii) tissue-restricted CT genes expressed in two or fewer of the non-gametogenic tissues tested, (iii) differentially expressed CT genes expressed in three to six of the 13 non-gametogenic tissues tested, and (iv) ubiquitously expressed CT genes. Of the 43 CT transcripts amplified (HCA661/CT30 could not be amplified), 19 were expressed exclusively in normal testis, as judged by this assay, with final levels of cDNA ranging from more than 2 µg to a minimal level of 0.01 µg produced by 35 amplification cycles. A subset of ten CT transcripts was tissue restricted, being expressed in testis (>2.0-0.02 µg cDNA product), ovary (0.01 µg cDNA product), and/or placenta (0.1-0.01 µg cDNA product), plus one or two non-gametogenic tissues. In all nine of these cases, pancreas was one of the two additional non-gametogenic tissues (1.2-0.01 µg cDNA product), while liver (0.19-0.01 µg cDNA product) or spleen (0.01 µg cDNA product) was the other non-gametogenic tissue found to express CT genes in this tissue-restricted category. An additional subset of nine CT transcripts was differentially expressed, with mRNA detected in three to six of 13 non-gametogenic tissues. Again, corresponding mRNA was detected in pancreas for each of these CT genes (0.07-0.01 µg cDNA product). Other tissues that express these differentially expressed CT transcripts include liver, spleen, thymus, kidney, lung, prostate and brain. Overall, with the exceptions of SPANXC/CT11.3 expression in pancreas (1.2 µg cDNA product detected) and XAGE-1a/CT12.1a expression in lung (>2.0 µg cDNA product detected), the expression levels of tissue-restricted and differentially expressed subsets of CT genes in non-gametogenic tissues were quite low, with 0.11-0.01 µg cDNA product detected. It is unclear whether these low-levels of mRNA expression correspond to significant quantities of protein. For example, although MAGEA1/CT1.1 mRNA was detected in pancreas (0.02 µg cDNA product detected), and NY-ESO-1/CT6.1 mRNA was detected in both pancreas (0.02 µg cDNA product detected) and liver (0.11 µg cDNA product detected), no corresponding protein has ever been reported in these tissues by immunohistochemistry (26, 34).
A subset of five CT transcripts, IL13RA/CT19, TSP50/CT20, SPA-17/CT22, OY-TES-1/CT23, and PLU-1/CT31, were ubiquitously expressed, with mRNA being detected in a majority of the non-gametogenic tissues tested. As shown in Figure 1, PLU-1/CT31 mRNA was detected at low levels (0.05 µg cDNA product detected or less) in all tissues except testis (0.2 µg). Thus, it appears that PLU-1/CT31 is universally expressed at low levels in non-gametogenic tissues. With regard to TSP50/CT20, the corresponding mRNA was detected at high levels (>1.0 µg cDNA product detected) in testis, kidney, liver, and pancreas; at a moderate level in thymus (0.11 µg); and at low levels in all other normal tissues (0.05 µg or less). Transcripts encoding IL13RA/CT19, SPA17/CT22, and OY-TES-1/CT23 were detected at high levels in testis (>2.0 µg cDNA product detected), and at moderate to high levels (0.1-2.0 µg cDNA product detected) in 11 of the 13 non-gametogenic tissues examined. Thus in addition to their high level of expression in testis, SPA17/CT22, OY-TES-1/CT23, and IL13RA/CT19 were also expressed at high levels in many non-gametogenic tissues, and therefore on the basis of mRNA expression, their inclusion in the CT gene category is suspect.
The frequent detection of CT transcripts in normal pancreas was unexpected. In order to validate these results, additional pancreatic cDNA was prepared as previously described (17) and subjected to the same RT-PCR analysis for CT gene expression as described above. As shown in Figure 2, 16 of the 24 CT transcripts originally detected in normal pancreas were also detected in this second sample of normal pancreas cDNA. In addition to the universally expressed CT transcripts, SPA17/CT22, OY-TES-1/CT23, and IL13RA/CT19, mRNA expression in normal pancreas was also confirmed for MAGEA1/CT1.1, XAGE-1a/CT12.1a, HAGE/CT13, PAGE-5/CT16A, TSP50/CT20, BORIS/CT27, D40/CT29, PLU-1/CT31, SGY-1/CT34, NY-SAR-35/CT37, NXF2/CT39, TAF7L/CT40, and TDRD1/CT41.1. Conversely, mRNA encoding NY-ESO-1/CT6.1, MAGEC1/CT7.1, SYCP1/CT8, SPANXC/CT11.3, ADAM2/CT15, CAGE/CT26, TEX15/CT42, and FATE/CT43 was not detected in this second cDNA preparation from normal pancreas. These genes, whose expression could not be confirmed in a second source of normal pancreas, do not necessarily correspond to those previously detected in pancreas at exceptionally low levels (<0.05 µg cDNA product detected). For example, MAGEA1/CT1A was detected at low levels in both the first and second pancreatic cDNA preparations (0.02 µg cDNA product detected), while SPANXC/CT11.3 was originally detected in pancreas at a high level (1.2 µg cDNA product detected), but was not detected in the second pancreatic cDNA (Figure 1). It is possible that these differences in CT transcript expression in the pancreas reflect differences in the cellular composition of the tissue used in the different pancreatic RNA preparations and/or differences among tissue donors. Nevertheless, these data indicate that CT transcripts are frequently expressed in the pancreas.
CT transcripts encoding immunogenic proteins
As their name implies, CT antigens are immunogenic gene products. Nineteen of the 44 CT families encode proteins associated with an immune response in humans, and can be considered bona fide CT antigens (Table 2). Immune recognition of the majority of these CT antigens is cancer-related, occurring spontaneously in cancer patients, but not in cancer-free individuals. The exceptions to this are humoral immune responses to MAGEB1/CT3.1 in systemic lupus erythematosus patients (35) and to SPA17/CT22 in vasectomized men (36). The process of CT antigen discovery in cancer, by either T cell epitope cloning or by serological analyses, has separated the cancer-related CT antigens into two groups, those defined by T lymphocyte recognition (MAGEA/CT1, BAGE/CT2, GAGE/CT4, NA88/CT18) and those defined by antibody recognition (SSX/CT5, NY-ESO-1/CT6, MAGEC/CT7, SYCP1/CT8, SPANXB1/CT11B, CTAGE/CT21, OY-TES-1/CT23, CAGE/CT26, HOM-TES-85/28, HCA661/CT30, NY-SAR-35/CT37, FATE/CT43, TPTE/CT44). However, there is increasing evidence of a coordinated immune response to these antigens in cancer patients. Both antibody and T-lymphocyte (CD4 and CD8) responses have been shown for three of these CT families, MAGEA/CT1, SSX/CT5 and NY-ESO-1/CT6 (3, 29, 37, 38, 39). Characterization of the T cell response to other serologically-defined CT antigens is a high priority. This should not only increase the number of vaccine targets, but also provide further evidence of the coordinated nature of the immune response to cancer.
With regard to the tissue expression patterns of CT antigens, 14 of the 19 immunogenic CT gene products have highly tissue-restricted mRNA expression profiles in normal tissues, i.e., they are expressed in two or fewer non-gametogenic tissues. These data emphasize the specificity of the host immune response to cancer and underscore the utility of immunogenic methods of gene discovery. The exceptions to the tissue restriction/immunogenicity paradigm are the differentially expressed genes CAGE/CT26 and FATE/CT43, and the ubiquitously expressed genes SPA17/CT22 and OY-TES-1/CT23 (in the present study HCA661/CT30 could not be amplified by RT-PCR). In these cases, expression in multiple normal tissues does not appear to be tolerogenic, suggesting that these antigens are expressed at an immunologically irrelevant level in normal tissues, and their expression in the context of cancer elicits an immune response.
Based on their immunogenicity and restricted expression, CT antigens are ideal for use in cancer vaccines. To date, approximately 90 CT transcripts have been identified, thus providing a substantial arsenal for active, antigen-specific immunotherapy of cancer. Many of the antigens have been proven to be immunogenic in cancer patients. The fact that cancer patients with spontaneous immune reactivity to CT antigens still present with progressive disease begs the question as to whether naturally immunoreactive antigens are valid targets for cancer vaccines. What we do not know is whether cancer would progress more rapidly in the absence of an immune response. The influence of vaccine-induced immunity on tumor growth without pre-existing immunity to CT antigens is, of course, the way to answer this question. Two features of immunogenic CT gene products (e.g. NY-ESO-1) greatly favor efforts to develop protective vaccines. One, the spontaneous immunogenicity of these antigens in a small subset of patients indicates their potential immunogenicity in a wider spectrum of patients, and two, the analysis of the humoral and cellular immune responses to these antigens in patients with spontaneous immunity has given us useful tools for monitoring the immunogenicity of CT vaccines and for determining the relative immunogenicity of different vaccine constructs.
As opposed to the conventional view that CT genes are expressed only in gametogenic tissues, the present survey shows CT mRNA transcripts to be present in other normal tissues, most notably, pancreas. In most cases, this does not detract from their immunotherapeutic potential, since expression levels in non-gametogenic tissues are exceptionally low and unlikely to result in the presence of immunologically relevant levels of MHC/CT peptide complexes. However, such hypotheses need to be tested, perhaps by direct measurement of the concentrations of MHC/CT peptide complexes in normal tissues (40).
Many questions regarding CT genes remain, including the biological function of their protein products, and the elucidation of the factors that control their expression in normal tissues and cancer. Epigenetic events such as DNA methylation and histone acetylation are known to influence CT gene expression (41, 42). Genome-wide, random hypomethylation in cancer has been viewed as a triggering event for CT gene expression, but hypomethylation itself may be part of a larger gene program characteristic of cancer. More specifically, the appearance of gametic traits in cancer, such as the expression of CT genes, global hypomethylation, cellular immortality, migratory behavior, and ectopic production of gonadotrophins, indicates a strong link between gametogenesis and carcinogenesis, and raises the possibility that cancer has acquired many of its traits by usurping the genetic program directing gametogenesis (43). The testing of such hypotheses awaits the determination of CT gene product function and a detailed analysis of genomic regulatory elements and their methylation status in normal and malignant tissues. Indeed, this gene set is highly unusual in that research into their utility in cancer therapy is far more advanced than that into their function. Nonetheless, this is in the grand tradition of the empirical nature of vaccine development that started with Pasteur and which still pervades the entire field today.
- Copyright © 2004 by Matthew J. Scanlan