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Predictive assays: will they ever have a role in the clinic?
Int. J. Radiation Oncology Biol. Phys., Vol. 49, No. 2, pp. 501–504, 2001 Copyright © 2001 Elsevier Science Inc. Printed in the USA. All rights reserved 0360-3016/01/$–see front matter
PII S0360-3016(00)01469-3
ICTR 2000
Translational Research in the Clinical Setting
PREDICTIVE ASSAYS: WILL THEY EVER HAVE A ROLE IN THE CLINIC? LESTER PETERS, M.D., F.R.A.N.Z.C.R., F.R.C.R., F.A.C.R., AND MICHAEL MCKAY, M.B.B.S. (HONS)., PH.D., F.R.A.N.Z.C.R. Peter MacCallum Cancer Institute, Melbourne, Australia
INTRODUCTION
difficult to sterilize. This is clearly the case when tumors of different histologies are compared. Within a given histology there is also a wide range of cellular radiosensitivity, providing the rationale for testing this parameter as a predictive assay. When radiosensitivity is quantified as the in vitro tumor cell surviving fraction at 2 Gy (SF2), several groups have found a trend toward a higher surviving fraction in tumors that recur after radiotherapy than in those that are controlled. However, in only one series of cervix cancer patients has the difference been significant and sustained in multiple analyses (2). In the case of head and neck cancer, results have generally been inconclusive. The most convincing evidence comes from a recently reported prospective Swedish study (3) that showed a significant effect of SF2 on local control but not survival. Indirect assays of cellular radiosensitivity based on measurements of DNA or chromosomal damage are quicker but no more discriminating than SF2.
The term “predictive assays” refers to laboratory tests designed to predict the response of tumors and/or normal tissues to radiotherapy on the basis of their radiobiological characteristics. These tests need to be distinguished conceptually from clinicopathologic prognostic factors that have been determined empirically such as tumor site, stage, type and grade, and performance status in that predictive assays are mechanistically based and offer the prospect of rational interventions to improve the therapeutic ratio. The reason for seeking reliable predictive assays is that within any clinically defined strata of patients, there is significant variability in outcome with respect to both tumor control probability and normal tissue damage. It is intuitively obvious that knowledge of which patients were destined to respond favorably to radiotherapy and which were not would enable the most appropriate treatment to be selected on an individual basis. This expectation is supported by formal mathematical modeling (1). Although desperately needed, predictive assays must be shown to be reliable, reproducible, and practical to be accepted into routine practice. Despite a great deal of research effort over the past decade, this has not yet been achieved. In this article, we briefly review the current state of predictive assays and some of the hurdles they would need to overcome to enter routine clinical use and focus on some new molecular approaches to predictive assays.
Tumor cell oxygenation The radioprotective effect of hypoxia has long been suspected as a cause for radioresistance, leading to a large number of treatment strategies aimed at countering the presence of hypoxic but viable tumor cells in vivo. These have had only modest success, suggesting that hypoxia is not a universal factor determining treatment outcome. Thus it is logical to think that quantitation of hypoxia in individual tumors might have utility as a predictive assay. Only in recent years has direct measurement of tissue oxygen tensions been possible. Although limited in number and size, studies of tumor cell oxygenation using polarographic probe measurements have consistently shown an adverse effect on both local tumor control and survival in tumors with a low mean level of oxygenation (4). Besides conferring radioresistance directly, it has recently been found that hypoxia selects for cells with defects in apoptosis, such as tumor cells with mutant p53 (5). Interestingly, hypoxia is an adverse prognostic factor even in patients treated surgically
TUMORS Largely because of the accessibility of tumors for obtaining fresh tissue, most predictive assay research has been done on head and neck and cervix cancers. The main types of predictive assays that have been studied to date and a summary of the results are as follows: Tumor cell radiosensitivity It is intuitively obvious that tumors whose clonogenic cells are more inherently radioresistant should be more Reprint requests to: Lester Peters, Peter MacCallum Cancer Institute, St. Andrews Place, East Melbourne Vic 3002, Australia. Tel: ⫹61 3 9656 1111; Fax: ⫹61 3 9656 1424; E-mail: Lpeters@ petermac.unimelb.edu.au
Presented at ICTR 2000, Lugano, Switzerland, March 5– 8, 2000. Accepted for publication 31 August 2000.
501
502
I. J. Radiation Oncology
●
Biology
●
Physics
(6), implying that factors other than radioresistance are involved. Tumor cell number and proliferation kinetics Tumor control probability is closely correlated with tumor volume. A simple explanation is that larger tumors contain more clonogenic cells that must be sterilized to achieve a cure. Because tumor control depends on sterilizing all the clonogenic cells that are present at any time up to the end of treatment, it is obvious that repopulation of cells that survive the early part of a course of treatment may result in failure to achieve tumor control. This is the reason for the importance of overall time of treatment. Measurements of tumor cell proliferation kinetics have therefore been studied as a predictive assay. Preliminary results suggested that tumor cell potential doubling time (Tpot) as an estimate of the regenerative capacity of tumor cells during fractionated radiotherapy might have predictive value. However, more mature data have failed to show any significant correlation of Tpot with tumor control, although simple labeling index (LI) did show a weak correlation (7). Summary of tumor predictive assays and inherent unsolved problems To date, predictive assays for tumor control have had limited success, and none has entered routine practice. Although tumor hypoxia appears to have clinical potential, probe measurements will need to be replaced by noninvasive methods to achieve clinical acceptance. The failure of any one assay to reliably predict for tumor control is not too surprising, since tumor response is almost certainly multifactorial. It is therefore appealing to consider predictive assays based on a test dose of radiation in situ as a surrogate. Morphologic assessments of tumor cell radiosensitivity based on cytological examination of tumor cells during a course of radiotherapy have been correlated with treatment outcome by various authors for more than 50 years. Although proponents of cytologic assays have claimed high predictive value, the subjectivity of these assays probably accounts for their lack of clinical acceptance. More recent approaches include measurement of tumor cell chromosome aberrations (8) and nett tumor cell DNA damage using the comet assay (9). No clinical assessments of the utility of these assays have yet been published. Problems in bringing tumor predictive assays to the clinic include the relative inaccessibility of the majority of tumor types for sampling, patient tolerance of invasive sampling procedures, precise definition of the clonogenic cell population, and the precision and time-to-results for most assays. Normal tissues In clinical radiotherapy, the therapeutic ratio depends on the relative radiosensitivity of the tumor with respect to dose-limiting normal tissues. Usually, the limitation imposed by normal tissue tolerance determines total dose
Volume 49, Number 2, 2001
and/or treatment intensity (10). It follows, therefore, that predictive assays of response of normal tissues could be even more important ultimately in optimizing radiotherapy than assays of tumor response. Most predictive assay research on normal tissues to date has been based on the radiosensitivity of normal lymphocytes and skin fibroblasts. A promising new focus is on genetic determinants of radiosensitivity. Cellular radiosensitivity. Several small series using cultured fibroblasts from individual patients have shown positive but weak correlations between fibroblast radiosensitivity and endpoints such as s.c. fibrosis and telangiectasia. Brock et al. (11) systematically examined the effect of dose rate and immediate vs. delayed plating on the predictive value of fibroblast SF2 and concluded that cellular radiosensitivity could at best explain only part of the interpatient variability observed clinically. More recent larger studies (12) have failed to demonstrate any significant utility for this assay. Part of the problem with fibroblast SF2 assays is the precision achievable with a single measurement, but perhaps more important is that cellular radiosensitivity is only one of several interacting factors determining late normal tissue response. For example cytokines, especially TGF1, which is rapidly induced after cellular exposure to ionizing radiation (13), also play an important role. Another potential contributing factor is the induction by radiation of terminal differentiation or senescence in the fibroblast lineage (14). Only in cases of extreme radiosensitivity syndromes, such as ataxia telangiectasia and related syndromes, are normal cell types uniformly radiosensitive. In the spectrum of “normality” there is little correlation between the interindividual radiosensitivity of different cell types. This would imply that for cellular radiosensitivity to be used as a predictive assay, the critical cell population would have to be identified for each normal tissue of concern—a daunting task. Genetic profiling. Realization that the underlying basis for differences in radiosensitivity of different individuals is most likely genetically determined has led to searches for genetic aberrations that could be used as predictive assays. Two basic approaches are currently under intensive study. The first is an attempt to link mutated candidate genes such as the ataxia telangiectasia gene ATM (15, 16), BRCA1, BRCA2 (17), and other genes involved in DNA doublestrand break repair with the radiosensitive phenotype. Preliminary results from this approach have to date been largely unsuccessful, as might be expected based on the multitude of interacting genes involved. However, it is possible that subgroups of radiosensitive patients might carry mutations or polymorphisms in specific ionizing radiation damage-processing genes. If this turns out to be the case, screening of the radiotherapy population for the particular gene defect before therapy may allow treatment to be individualized for those carrying the gene variant. The second, more ambitious approach is to attempt to define a large-scale genetic “fingerprint” of radiosensi-
Predictive assays and the clinic
●
L. PETERS
AND
M. MCKAY
503
Fig. 1. (Top) Image of the same region of two separate 5,000 gene chips hybridized with pairs of labeled RNA from a radiosensitive individual and a nonradiosensitive control cancer patient. The similar signals across both fields indicate excellent intrachip reproducibility of the hybridizations. (Bottom) Replicates of the 16 genes on a 5K chip that varied greater than twofold between lymphoblastoid cell lines from a control and a radiosensitive individual after 2 Gy ionizing radiation and 4 h RNA harvest. The fold differences indicate absolute differences between control and test cases. Note similarity between values for replicate samples (light and dark bars), demonstrating good intrachip variation (All genes are spotted twice on the one chip). (Lightning) Bone morphogenetic protein 4, a TGF superfamily member (TGF is also a strong early-phase–induced gene in the IR stress response), and placental and bone alkaline phosphatases (arrowheads), both expressed 2.5–5-fold greater in the control, indicating internal consistency in the experiment.
tive individuals using microarray (“DNA Chip”) technology. In this procedure, DNA corresponding to (part of) thousands of gene sequences is coupled to a solid support and interrogated with a mixture of two different labeled RNA pools, corresponding to two different states of interest (e.g., diseased or not). The relative hybridization of each sample to each DNA spot gives a measure of activity (expression) of each individual gene in the two samples. Thus, a profile of gene activity in each sample can be derived. Gene expression profiling with microarrays has already been useful for distinguishing different disease states, including the genetic complexity of cancer (18); thus its application to radiation sensitivity has significant promise. To pursue this line of research, we have established a relational database of patients known to have experienced abnormally severe radiation reactions and have collected blood and skin samples from them. The gene expression profile of these patients has been assessed using a system based on cDNA arraying on glass slides (S. Bassal, M. Chao, and M. McKay, unpublished). We have identified many mRNA expression differences
between radiosensitive patients and controls, including known radiation-responsive genes (Fig. 1). For clinical applications, the analysis of small numbers of cells would seem essential in investigating the cellular basis of radiosensitivity in different organs. In this regard, a recent complementary advance has been the development of quantitative methods for close to proportional amplification of material from very few cells using the polymerase chain reaction. Combining microarray analysis with histologic microdissection of different cell types (19) now enables the derivation of cell-type–specific gene expression profiles. Should profiles of the radiosensitive phenotype be detectable, their combination with fine-needle aspiration would have good potential for their trial in the clinic. Because of the sensitivity and potential scope of such technology—to examine the entire genetic expression profile of an individual simultaneously—the microarray approach seems to be the best prospect yet for predicting human radiosensitivity. In summary, although initial results are emerging (20), it is too early to assess the ultimate value of this new approach.
504
I. J. Radiation Oncology
●
Biology
●
Physics
Normal tissue predictive assays: Inherent unsolved problems As for tumors, the relative inaccessibility of, and inability to clearly define the relevant stem cell population of different tissues limits the utility of normal tissue assays based on cellular radiosensitivity in the clinic. Another hazard is the contribution of factors other than cell survival to the pathogenesis of severe radiation reactions in patients. As for tumor predictive assays, the precision, reproducibility and time-to-results for cellular radiosensitivity assays are also limiting factors, although some surrogate assays for clonogenic survival and microarray analysis give results within the window of time required for clinical decision-making. Will predictive assays ever have a role in the clinic? Unfortunately, this is still unclear at present. It is certainly disappointing that after more than a decade of intensive effort, no predictive assay has yet entered clinical practice. However, the rapid rate of development of new technologies and their integration into predictive assay research are reasons for maintaining an optimistic outlook. In
Volume 49, Number 2, 2001
the case of prediction of tumor response, one possibility is that a combination of imaging and cell-based assays will enable the four most important radiobiological predictive factors (inherent sensitivity, tumor oxygen status, proliferative capacity, and clonogenic cell number) all to be assessed in a practical way. These would then be categorized (e.g., favorable, average, unfavorable), to determine which is most likely to be cure-limiting in a given patient. Whether tumor-specific gene expression profiles will provide recognizable “signatures” for radiocurability is an unanswered question but may render more traditional assays obsolete. Similarly for normal tissue prediction, the best prospects seem to lie in the field of genetic profiling; it is certainly encouraging to note that preliminary results have shown consistent patterns of gene expression in overreacting patients. However the specificity of these patterns and any causal relationship to the radiosensitive phenotype have not been established. The next few years will be critical in determining just how close we are to the “Holy Grail.”
REFERENCES 1. Mackay RI, Hendry JH. The modelled benefits of individualizing radiotherapy patients’ dose using cellular radiosensitivity assays with inherent variability. Radiother Oncol 1999;50: 67–75. 2. West CML. Intrinsic radiosensitivity as a predictor of patient response to radiotherapy. Br J Radiol 1995;68:827– 837. 3. Bjork-Eriksson T, West C, Karlsson E, et al. Tumor radiosensitivity (SF2) is a prognostic factor for local control in head and neck cancers. Int J Radiat Oncol Biol Phys 2000;46:13– 19. 4. Horsman MR. Measurement of tumor oxygenation. Int J Radiat Oncol Biol Phys 1998;42:701–704. 5. Graeber TG, Osmanian C, Jacks T, et al. Hypoxia-mediated selection of cells with diminished apoptotic potential in solid tumors. Nature 1996;379:88 –91. 6. Hockel M, Schlenger K, Aral B, et al. Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix. Cancer Res 1996;56:4509 – 4515. 7. Begg AC, Haustermans K, Hart AAM, et al. The value of pretreatment cell kinetic parameters as predictors for radiotherapy outcome in head and neck cancer: A multicenter analysis. Radiother Oncol 1999;50:13–23. 8. Brown JM, Evans JW, Kovacs MS. Mechanism of chromosome exchange formation in human fibroblasts: Insights from “chromosome painting.” Environ Mol Mutagen 1993;22:218 –224. 9. Aquino-Parsons C, Luo C, Vikse CM, et al. Comparison between the comet assay and the oxygen microelectrode for measurement of tumor hypoxia. Radiother Oncol 1999;51: 179 –185. 10. Peters LJ. Inherent radiosensitivity of tumor and normal tissue cells as a predictor of human tumor response. Radiother Oncol 1990;17:177–190. 11. Brock WA, Tucker SL, Geara FB, et al. Fibroblast sensitivity versus acute and late normal skin responses in patients treated for breast cancer. Int J Radiat Oncol Biol Phys 1995;32:1371–1379.
12. Bentzen SM, Hendry JH. Variability in the radiosensitivity of normal cells and tissues. Report from a workshop organised by the European Society for Therapeutic Radiology and Oncology in Edinburgh UK 19 September 1998. Int J Radiat Biol 1999;75:513–517. 13. Martin M, Vozenin MC, Gault N, et al. Coactivation of AP-1 activity and TGF-beta 1 gene expression in the stress response of normal skin cells to ionizing radiation. Oncogene 1997;15: 981–989. 14. Herskind C, Bentzen SM, Overgaard M, et al. Differentiation state of skin fibroblast cultures versus risk of subcutaneous fibrosis after radiotherapy. Radiother Oncol 1998;47:263–269. 15. Shayeghi M, Seal S, Regan J, et al. Heterozygosity for mutations in the ataxia telangiectasia gene is not a major cause of radiotherapy complications in breast cancer patients. Br J Cancer 1998;78:922–927. 16. Ramsay J, Birrell G, Lavin M. Testing for mutations of the ataxia telangiectasia gene in radiosensitive breast cancer patients. Radiother Oncol 1998;47:125–128. 17. Leong T, Whitty J, Mifsud MS, et al. Mutation analysis of BRCA1 and BRCA2 cancer predisposition genes in radiation hypersensitive cancer patients. Int J Radiat Oncol Biol Phys 2000; In press. 18. Alizadeh AA, Eisen MB, Davis RE, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000;403:503–511. 19. Sgroi DC, Teng S, Robinson G, et al. In vivo gene expression profile analysis of human breast cancer progression. Cancer Res 1999;59:5656 –5661. 20. Amundson SA, Bittner M, Chen Y, et al. Fluorescent cDNA microarray hybridization reveals complexity and heterogeneity of cellular genotoxic stress responses. Oncogene 1999;18: 3666 –3672.
PII S0360-3016(00)01469-3
ICTR 2000
Translational Research in the Clinical Setting
PREDICTIVE ASSAYS: WILL THEY EVER HAVE A ROLE IN THE CLINIC? LESTER PETERS, M.D., F.R.A.N.Z.C.R., F.R.C.R., F.A.C.R., AND MICHAEL MCKAY, M.B.B.S. (HONS)., PH.D., F.R.A.N.Z.C.R. Peter MacCallum Cancer Institute, Melbourne, Australia
INTRODUCTION
difficult to sterilize. This is clearly the case when tumors of different histologies are compared. Within a given histology there is also a wide range of cellular radiosensitivity, providing the rationale for testing this parameter as a predictive assay. When radiosensitivity is quantified as the in vitro tumor cell surviving fraction at 2 Gy (SF2), several groups have found a trend toward a higher surviving fraction in tumors that recur after radiotherapy than in those that are controlled. However, in only one series of cervix cancer patients has the difference been significant and sustained in multiple analyses (2). In the case of head and neck cancer, results have generally been inconclusive. The most convincing evidence comes from a recently reported prospective Swedish study (3) that showed a significant effect of SF2 on local control but not survival. Indirect assays of cellular radiosensitivity based on measurements of DNA or chromosomal damage are quicker but no more discriminating than SF2.
The term “predictive assays” refers to laboratory tests designed to predict the response of tumors and/or normal tissues to radiotherapy on the basis of their radiobiological characteristics. These tests need to be distinguished conceptually from clinicopathologic prognostic factors that have been determined empirically such as tumor site, stage, type and grade, and performance status in that predictive assays are mechanistically based and offer the prospect of rational interventions to improve the therapeutic ratio. The reason for seeking reliable predictive assays is that within any clinically defined strata of patients, there is significant variability in outcome with respect to both tumor control probability and normal tissue damage. It is intuitively obvious that knowledge of which patients were destined to respond favorably to radiotherapy and which were not would enable the most appropriate treatment to be selected on an individual basis. This expectation is supported by formal mathematical modeling (1). Although desperately needed, predictive assays must be shown to be reliable, reproducible, and practical to be accepted into routine practice. Despite a great deal of research effort over the past decade, this has not yet been achieved. In this article, we briefly review the current state of predictive assays and some of the hurdles they would need to overcome to enter routine clinical use and focus on some new molecular approaches to predictive assays.
Tumor cell oxygenation The radioprotective effect of hypoxia has long been suspected as a cause for radioresistance, leading to a large number of treatment strategies aimed at countering the presence of hypoxic but viable tumor cells in vivo. These have had only modest success, suggesting that hypoxia is not a universal factor determining treatment outcome. Thus it is logical to think that quantitation of hypoxia in individual tumors might have utility as a predictive assay. Only in recent years has direct measurement of tissue oxygen tensions been possible. Although limited in number and size, studies of tumor cell oxygenation using polarographic probe measurements have consistently shown an adverse effect on both local tumor control and survival in tumors with a low mean level of oxygenation (4). Besides conferring radioresistance directly, it has recently been found that hypoxia selects for cells with defects in apoptosis, such as tumor cells with mutant p53 (5). Interestingly, hypoxia is an adverse prognostic factor even in patients treated surgically
TUMORS Largely because of the accessibility of tumors for obtaining fresh tissue, most predictive assay research has been done on head and neck and cervix cancers. The main types of predictive assays that have been studied to date and a summary of the results are as follows: Tumor cell radiosensitivity It is intuitively obvious that tumors whose clonogenic cells are more inherently radioresistant should be more Reprint requests to: Lester Peters, Peter MacCallum Cancer Institute, St. Andrews Place, East Melbourne Vic 3002, Australia. Tel: ⫹61 3 9656 1111; Fax: ⫹61 3 9656 1424; E-mail: Lpeters@ petermac.unimelb.edu.au
Presented at ICTR 2000, Lugano, Switzerland, March 5– 8, 2000. Accepted for publication 31 August 2000.
501
502
I. J. Radiation Oncology
●
Biology
●
Physics
(6), implying that factors other than radioresistance are involved. Tumor cell number and proliferation kinetics Tumor control probability is closely correlated with tumor volume. A simple explanation is that larger tumors contain more clonogenic cells that must be sterilized to achieve a cure. Because tumor control depends on sterilizing all the clonogenic cells that are present at any time up to the end of treatment, it is obvious that repopulation of cells that survive the early part of a course of treatment may result in failure to achieve tumor control. This is the reason for the importance of overall time of treatment. Measurements of tumor cell proliferation kinetics have therefore been studied as a predictive assay. Preliminary results suggested that tumor cell potential doubling time (Tpot) as an estimate of the regenerative capacity of tumor cells during fractionated radiotherapy might have predictive value. However, more mature data have failed to show any significant correlation of Tpot with tumor control, although simple labeling index (LI) did show a weak correlation (7). Summary of tumor predictive assays and inherent unsolved problems To date, predictive assays for tumor control have had limited success, and none has entered routine practice. Although tumor hypoxia appears to have clinical potential, probe measurements will need to be replaced by noninvasive methods to achieve clinical acceptance. The failure of any one assay to reliably predict for tumor control is not too surprising, since tumor response is almost certainly multifactorial. It is therefore appealing to consider predictive assays based on a test dose of radiation in situ as a surrogate. Morphologic assessments of tumor cell radiosensitivity based on cytological examination of tumor cells during a course of radiotherapy have been correlated with treatment outcome by various authors for more than 50 years. Although proponents of cytologic assays have claimed high predictive value, the subjectivity of these assays probably accounts for their lack of clinical acceptance. More recent approaches include measurement of tumor cell chromosome aberrations (8) and nett tumor cell DNA damage using the comet assay (9). No clinical assessments of the utility of these assays have yet been published. Problems in bringing tumor predictive assays to the clinic include the relative inaccessibility of the majority of tumor types for sampling, patient tolerance of invasive sampling procedures, precise definition of the clonogenic cell population, and the precision and time-to-results for most assays. Normal tissues In clinical radiotherapy, the therapeutic ratio depends on the relative radiosensitivity of the tumor with respect to dose-limiting normal tissues. Usually, the limitation imposed by normal tissue tolerance determines total dose
Volume 49, Number 2, 2001
and/or treatment intensity (10). It follows, therefore, that predictive assays of response of normal tissues could be even more important ultimately in optimizing radiotherapy than assays of tumor response. Most predictive assay research on normal tissues to date has been based on the radiosensitivity of normal lymphocytes and skin fibroblasts. A promising new focus is on genetic determinants of radiosensitivity. Cellular radiosensitivity. Several small series using cultured fibroblasts from individual patients have shown positive but weak correlations between fibroblast radiosensitivity and endpoints such as s.c. fibrosis and telangiectasia. Brock et al. (11) systematically examined the effect of dose rate and immediate vs. delayed plating on the predictive value of fibroblast SF2 and concluded that cellular radiosensitivity could at best explain only part of the interpatient variability observed clinically. More recent larger studies (12) have failed to demonstrate any significant utility for this assay. Part of the problem with fibroblast SF2 assays is the precision achievable with a single measurement, but perhaps more important is that cellular radiosensitivity is only one of several interacting factors determining late normal tissue response. For example cytokines, especially TGF1, which is rapidly induced after cellular exposure to ionizing radiation (13), also play an important role. Another potential contributing factor is the induction by radiation of terminal differentiation or senescence in the fibroblast lineage (14). Only in cases of extreme radiosensitivity syndromes, such as ataxia telangiectasia and related syndromes, are normal cell types uniformly radiosensitive. In the spectrum of “normality” there is little correlation between the interindividual radiosensitivity of different cell types. This would imply that for cellular radiosensitivity to be used as a predictive assay, the critical cell population would have to be identified for each normal tissue of concern—a daunting task. Genetic profiling. Realization that the underlying basis for differences in radiosensitivity of different individuals is most likely genetically determined has led to searches for genetic aberrations that could be used as predictive assays. Two basic approaches are currently under intensive study. The first is an attempt to link mutated candidate genes such as the ataxia telangiectasia gene ATM (15, 16), BRCA1, BRCA2 (17), and other genes involved in DNA doublestrand break repair with the radiosensitive phenotype. Preliminary results from this approach have to date been largely unsuccessful, as might be expected based on the multitude of interacting genes involved. However, it is possible that subgroups of radiosensitive patients might carry mutations or polymorphisms in specific ionizing radiation damage-processing genes. If this turns out to be the case, screening of the radiotherapy population for the particular gene defect before therapy may allow treatment to be individualized for those carrying the gene variant. The second, more ambitious approach is to attempt to define a large-scale genetic “fingerprint” of radiosensi-
Predictive assays and the clinic
●
L. PETERS
AND
M. MCKAY
503
Fig. 1. (Top) Image of the same region of two separate 5,000 gene chips hybridized with pairs of labeled RNA from a radiosensitive individual and a nonradiosensitive control cancer patient. The similar signals across both fields indicate excellent intrachip reproducibility of the hybridizations. (Bottom) Replicates of the 16 genes on a 5K chip that varied greater than twofold between lymphoblastoid cell lines from a control and a radiosensitive individual after 2 Gy ionizing radiation and 4 h RNA harvest. The fold differences indicate absolute differences between control and test cases. Note similarity between values for replicate samples (light and dark bars), demonstrating good intrachip variation (All genes are spotted twice on the one chip). (Lightning) Bone morphogenetic protein 4, a TGF superfamily member (TGF is also a strong early-phase–induced gene in the IR stress response), and placental and bone alkaline phosphatases (arrowheads), both expressed 2.5–5-fold greater in the control, indicating internal consistency in the experiment.
tive individuals using microarray (“DNA Chip”) technology. In this procedure, DNA corresponding to (part of) thousands of gene sequences is coupled to a solid support and interrogated with a mixture of two different labeled RNA pools, corresponding to two different states of interest (e.g., diseased or not). The relative hybridization of each sample to each DNA spot gives a measure of activity (expression) of each individual gene in the two samples. Thus, a profile of gene activity in each sample can be derived. Gene expression profiling with microarrays has already been useful for distinguishing different disease states, including the genetic complexity of cancer (18); thus its application to radiation sensitivity has significant promise. To pursue this line of research, we have established a relational database of patients known to have experienced abnormally severe radiation reactions and have collected blood and skin samples from them. The gene expression profile of these patients has been assessed using a system based on cDNA arraying on glass slides (S. Bassal, M. Chao, and M. McKay, unpublished). We have identified many mRNA expression differences
between radiosensitive patients and controls, including known radiation-responsive genes (Fig. 1). For clinical applications, the analysis of small numbers of cells would seem essential in investigating the cellular basis of radiosensitivity in different organs. In this regard, a recent complementary advance has been the development of quantitative methods for close to proportional amplification of material from very few cells using the polymerase chain reaction. Combining microarray analysis with histologic microdissection of different cell types (19) now enables the derivation of cell-type–specific gene expression profiles. Should profiles of the radiosensitive phenotype be detectable, their combination with fine-needle aspiration would have good potential for their trial in the clinic. Because of the sensitivity and potential scope of such technology—to examine the entire genetic expression profile of an individual simultaneously—the microarray approach seems to be the best prospect yet for predicting human radiosensitivity. In summary, although initial results are emerging (20), it is too early to assess the ultimate value of this new approach.
504
I. J. Radiation Oncology
●
Biology
●
Physics
Normal tissue predictive assays: Inherent unsolved problems As for tumors, the relative inaccessibility of, and inability to clearly define the relevant stem cell population of different tissues limits the utility of normal tissue assays based on cellular radiosensitivity in the clinic. Another hazard is the contribution of factors other than cell survival to the pathogenesis of severe radiation reactions in patients. As for tumor predictive assays, the precision, reproducibility and time-to-results for cellular radiosensitivity assays are also limiting factors, although some surrogate assays for clonogenic survival and microarray analysis give results within the window of time required for clinical decision-making. Will predictive assays ever have a role in the clinic? Unfortunately, this is still unclear at present. It is certainly disappointing that after more than a decade of intensive effort, no predictive assay has yet entered clinical practice. However, the rapid rate of development of new technologies and their integration into predictive assay research are reasons for maintaining an optimistic outlook. In
Volume 49, Number 2, 2001
the case of prediction of tumor response, one possibility is that a combination of imaging and cell-based assays will enable the four most important radiobiological predictive factors (inherent sensitivity, tumor oxygen status, proliferative capacity, and clonogenic cell number) all to be assessed in a practical way. These would then be categorized (e.g., favorable, average, unfavorable), to determine which is most likely to be cure-limiting in a given patient. Whether tumor-specific gene expression profiles will provide recognizable “signatures” for radiocurability is an unanswered question but may render more traditional assays obsolete. Similarly for normal tissue prediction, the best prospects seem to lie in the field of genetic profiling; it is certainly encouraging to note that preliminary results have shown consistent patterns of gene expression in overreacting patients. However the specificity of these patterns and any causal relationship to the radiosensitive phenotype have not been established. The next few years will be critical in determining just how close we are to the “Holy Grail.”
REFERENCES 1. Mackay RI, Hendry JH. The modelled benefits of individualizing radiotherapy patients’ dose using cellular radiosensitivity assays with inherent variability. Radiother Oncol 1999;50: 67–75. 2. West CML. Intrinsic radiosensitivity as a predictor of patient response to radiotherapy. Br J Radiol 1995;68:827– 837. 3. Bjork-Eriksson T, West C, Karlsson E, et al. Tumor radiosensitivity (SF2) is a prognostic factor for local control in head and neck cancers. Int J Radiat Oncol Biol Phys 2000;46:13– 19. 4. Horsman MR. Measurement of tumor oxygenation. Int J Radiat Oncol Biol Phys 1998;42:701–704. 5. Graeber TG, Osmanian C, Jacks T, et al. Hypoxia-mediated selection of cells with diminished apoptotic potential in solid tumors. Nature 1996;379:88 –91. 6. Hockel M, Schlenger K, Aral B, et al. Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix. Cancer Res 1996;56:4509 – 4515. 7. Begg AC, Haustermans K, Hart AAM, et al. The value of pretreatment cell kinetic parameters as predictors for radiotherapy outcome in head and neck cancer: A multicenter analysis. Radiother Oncol 1999;50:13–23. 8. Brown JM, Evans JW, Kovacs MS. Mechanism of chromosome exchange formation in human fibroblasts: Insights from “chromosome painting.” Environ Mol Mutagen 1993;22:218 –224. 9. Aquino-Parsons C, Luo C, Vikse CM, et al. Comparison between the comet assay and the oxygen microelectrode for measurement of tumor hypoxia. Radiother Oncol 1999;51: 179 –185. 10. Peters LJ. Inherent radiosensitivity of tumor and normal tissue cells as a predictor of human tumor response. Radiother Oncol 1990;17:177–190. 11. Brock WA, Tucker SL, Geara FB, et al. Fibroblast sensitivity versus acute and late normal skin responses in patients treated for breast cancer. Int J Radiat Oncol Biol Phys 1995;32:1371–1379.
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