- © 2006 by American Society of Clinical Oncology
FGFR4 Arg388 Allele Is Associated With Resistance to Adjuvant Therapy in Primary Breast Cancer
- Christoph Thussbas,
- Jorg Nahrig,
- Sylvia Streit,
- Johannes Bange,
- Monika Kriner,
- Ronald Kates,
- Kurt Ulm,
- Marion Kiechle,
- Heinz Hoefler,
- Axel Ullrich and
- Nadia Harbeck
- From the Department of Obstetrics and Gynecology, Institute of Pathology, and Institute for Medical Statistics and Epidemiology, Technical University of Munich, Munich; and the Department of Molecular Biology, Max-Planck-Institute of Biochemistry and U3 Pharma AG, Martinsried, Germany
- Address reprint requests to Nadia Harbeck, MD, Department of Obstetrics and Gynecology, Technical University of Munich, Ismaninger Strasse 22, D-81675 Munich, Germany; e-mail: nadia.harbeck{at}lrz.tum.de
Abstract
Purpose A recent study presented first evidence that a single nucleotide polymorphism (SNP) at codon 388 of fibroblast growth factor receptor 4 (FGFR4) gene, causing a transmembrane domain missense mutation (Gly388Arg), is associated with disease outcome in node-positive breast cancer. This article addresses the clinical relevance of this SNP, FGFR4 genotype, phenotype, and HER2 regarding patient outcome and influence of adjuvant systemic therapy in a substantial primary breast cancer collective (n = 372; median follow-up, 94.5 months).
Methods Polymerase chain reaction restriction fragment length polymorphism analysis of germ-line polymorphism was performed in uninvolved lymph nodes; FGFR4 and HER2 expression were assessed immunohistochemically in tissue microarrays.
Results In 51% of patients, homo- or heterozygous Arg388 allele was present. No correlation existed between FGFR4 genotype and expression or HER2 status. In node-negative patients, FGFR4 genotype was not correlated with disease outcome. In node-positive patients, however, FGFR4 Arg388 was significantly associated with poor disease-free survival (DFS; P = .02) and overall survival (OS; P = .04). Notably, this association seems to be attributable to relatively poor therapy response in Arg388 carriers, reflected in their significantly shorter DFS (P = .02) and OS (P = .045) among patients receiving adjuvant systemic therapy. It is also seen as a significant interaction term in a multivariate proportional hazards model with Arg388 carriers having only about half as much benefit from adjuvant systemic therapy as wild-type carriers.
Conclusion According to this study, FGFR4 Arg388 genotype is a marker for breast cancer progression in patients with adjuvant systemic therapy, particularly chemotherapy, and thus may indicate therapy resistance.
INTRODUCTION
Uncontrolled cellular growth and metastasis are characteristics of malignant tumors. Metastasis requires tumor cells to detach from the primary tumor, cross tissue boundaries, enter and exit the circulatory system, and finally infiltrate distant organs.1 During tumorigenesis, those properties are acquired in a multistep process based on accumulation of innate and acquired genetic defects.2 The genes concerned usually play a decisive role in regulation of cell growth. Hence, protein tyrosine kinases, transducting growth-stimulating signals into cells, are often the decisive points where regulation fails.3 Alterations in receptor tyrosine kinase genes such as specific point mutations or gene amplification induce neoplastic disorders,4,5 as first demonstrated for HER2 oncogenic activation.6
The fibroblast growth factor receptor (FGFR) family with its four closely related human members is also one of the tyrosine kinase receptors. This family, comprising more than 20 known ligands, is critically involved in cell growth, differentiation, migration, angiogenesis, and tumorigenesis,7 and is linked to human diseases: Gly380Arg and Ala391Glu amino acid substitutions in the FGFR3 transmembrane domain cause achondroplasia and Crouzon syndrome.8,9 FGFR2 is required in limb and lung development10; its point mutations lead to Crouzon syndrome.11,12 FGFR3 and FGFR2 somatic mutations have been detected in human bladder, cervical, and colorectal carcinomas.13,14 FGFR1 and FGFR3 gene translocations play a role in development of leukemia and multiple myeloma.15,16 FGFR1 signaling is critical for prostate cancer cell growth.17FGFR4 is decisively involved in differentiation of limb muscles18 and, like FGFR1, it is highly expressed in mammary carcinomas.19,20 High FGFR4 expression was demonstrated in pancreatic21 and renal cell carcinoma.22
In 2002, Bange et al discovered a germ-line polymorphism in the gene encoding for FGFR4.23 The single nucleotide polymorphism (SNP) at codon 388, from G to A, results in a change of the amino acid sequence of the FGFR4 from glycine to arginine (Gly388 to Arg388). The result is a charged amino acid in the highly conserved and normally hydrophobic transmembrane region. Analysis of three geographically separated groups indicated that the germ-line polymorphism occurs in approximately 50% of the human population; FGFR4 Arg388 genotype is not involved in tumor initiation, since FGFR4 alleles are similarly distributed in breast cancer patients and controls. FGFR4 Arg388 was over-represented in node-positive breast cancer patients with early relapse but was not associated with shortened disease-free survival (DFS) in node-negative patients.23 HER2 status was significantly associated with FGFR4 Arg388.23 Recently, Streit et al24 demonstrated that high expression of the FGFR4 Arg388 allele was associated with poor clinical outcome in head and neck squamous cell carcinoma (HNSCC). An impact of Arg388 polymorphism on patient outcome was also reported in lung adenocarcinoma.25 These findings underline the clinical relevance of the FGFR4 Arg388 polymorphism in cancer. It remains an open question whether the observed impact is purely prognostic or involves differential response to therapy. Given the clearly documented impact of adjuvant therapy on DFS,26 primary breast cancer is particularly well suited for distinguishing purely prognostic from predictive impact.
The present study was therefore intended to validate the relevance of FGFR4 Arg388 polymorphism in breast cancer in a substantially larger patient cohort with long follow-up and complete, representative adjuvant therapy. For the first time, FGFR4 expression and HER2 status by immunohistochemistry (IHC) are analyzed next to FGFR4 genotype in breast cancer—of interest in view of the previously reported association between HER2 and FGFR4 Arg388. We focus on the influence of adjuvant systemic therapy on prognostic impact of FGFR4, because follow-up results indicating impact on disease outcome may be confounded by differential therapy response.27
METHODS
Patients and Tissue Samples
Tissue specimens of 372 consecutive primary breast carcinomas were collected by the Pathology Department, Technical University of Munich (TUM; Munich, Germany), all patients diagnosed and treated at the TUM Department of Obstetrics and Gynecology (1987-2001); treatment decisions were based on consensus recommendations at the time. All patients gave informed consent for research use of tissue. After surgery (modified radical mastectomy or breast-conserving therapy), 73 patients, all of them node negative, received no adjuvant systemic therapy. One hundred fourteen patients received adjuvant chemotherapy, 87% cyclophosphamide/methotrexate/fluorouracil (CMF) -based regimens; 164 patients received tamoxifen, 10 patients combined chemoendocrine therapy (10 unknown). One patient had missing nodal status. Follow-up was performed regularly; median follow-up in patients still alive at analysis was 94.5 months (range, 7 to 199 months). Relapse data were available in 357 patients: 128 (36%) experienced disease recurrence; 81% (n = 104) distant relapses; and 140 (38%) death.
Sequence analysis of FGFR4
As described earlier,23 DNA samples were extracted from 10-μm sections of formalin-fixed, paraffin-embedded lymph nodes selected by a pathologist after dissection using light microscopy. Because FGFR4 Arg388 allele is a germ-line mutation, benign lymph node tissue was analyzed in all patients using polymerase chain reaction restriction fragment length ploymorphism (PCR-RFLP). To screen individuals for FGFR4 Arg388 allele, the following primers were applied: 5′-GACCGCAGCAGCGCCGAGGCCAG-3′ and 5′-AGAGGGAAGAGGGAGAGCTTCTG-3′. Primers (2 μmol/L) and 50 ng of genomic DNA were combined in a 25 μL total reaction volume using Ready-to-Go PCR beads (Amersham Pharmacia Biotech, Piscataway, NJ). The 168-bp (base pair) fragment was digested overnight by BstNI (New England BioLabs, Ipswich, MA) according to manufacturer’s instructions. Restriction fragments were resolved on a 12% nondenaturing polyacrylamide gel; DNA was visualized with ethidium bromide. Arg388 allele was characterized by two distinctive fragments (80 bp, 29 bp); a single distinctive band (109 bp) was observed for Gly388 allele.
FGFR4 Semiquantitative IHC
Rabbit polyclonal anti-FGFR4 immunoglobulin G (IgG) antibody (C-16; Santa Cruz Biotechnology Inc, Santa Cruz, CA) was used for FGFR4 expression analysis on tissue microarrays with two peripheral and one central 1-mm2 tumor areas. After dewaxing, endogenous peroxidase was blocked by 1% hydrogen peroxide (10 minutes). Antigen retrieval was performed using pH 6 citrate buffer (12 minutes, microwave, 700 W).24 Standard immunostaining used antibody goat-antirabbit K 4002/4003 for EnVision-method (DAKO, Copenhagen, Denmark) on TechMate Horizon autostainer (DAKO) according to supplier’s recommendations. Primary anti FGFR4 polyclonal IgG was diluted 1:1,000 (antibody dilution and storage buffer, DAKO, F 3022) and incubated (room temperature, 2× 25 minutes). Hematoxylin counterstaining was performed.
FGFR4 Expression Analysis
Cytoplasmatic FGFR4 immunostaining was scored semiquantitatively (four-grade system): negative (0), low (1), intermediate (2), and high expression (3). The grade 0 category was added to the previously described three-grade score because, in contrast to HNSCC,24 we observed invasive breast carcinomas without any FGFR4 immunoreactivity. Polyclonal IgG specificity was determined by Western blot analysis and IHC using breast cancer cell line MDA-MB-231 infected with retrovirus expressing FGFR4. Preincubation with blocking peptide (1:1,000, sc-124p, Santa Cruz Biotechnology Inc) completely abrogated serum binding. Cytoblock preparations of FGFR4-infected and -uninfected MDA-MB-23123 were included in tissue microarrays and used as external controls for FGFR4 expression scoring. In heterogeneity controls, IHC in complete tumor sections of 10 randomly selected breast carcinomas revealed homogeneous staining intensity and patterns, as described for HNSCC.24
HER2 Semiquantitative Immunohistochemistry
HER2 IHC was performed using DAKO HercepTest according to manufacturer’s recommendations. In addition to supplied controls, we included in-house controls on each slide consisting of breast carcinomas of score 3+ (high-level amplification), score 2+ (polysomy) and score 0 (disomy) with known HER2 IHC and HER2–fluorescence in situ hybridization status according to our previous protocol.28 HER2 staining was assessed according to Clinical Trials Assay (CTA) -score recommended in HercepTest.
Statistical Methods
All molecular and immunohistochemical analyses were performed blinded to clinical data. Spearman correlations were analyzed between continuous variables. Associations between continuous and/or categoric variables were analyzed using the Mann-Whitney U test or Pearson χ2 test. Survival curves were plotted according to Kaplan-Meier; DFS was of primary interest, since it best reflects impact of adjuvant systemic therapy. The proportional hazards model was tested graphically; comparison between groups was performed by log-rank test. Forward stepwise Cox regression was used for multivariate survival modeling, with linear terms in first block and interactions in second block. Analyses were performed using SPSS 12.0.1 (SPSS Inc, Chicago, IL).
RESULTS
Distribution of FGFR4 Gly388Arg Polymorphism
In the present primary breast cancer cohort, 156 patients (49%) were homozygous for Gly388 allele, with 136 heterozygous (43%) and 24 homozygous (8%) for Arg388, consistent with Hardy-Weinberg equilibrium for a Gly388 frequency of approximately 70%. This is consistent with previous reports23 of approximately 50% homo- or heterozygous carriers of the Arg388 allele in both the healthy population and in breast and colon cancer patients, independent of ethnic background. No significant association was found between clinical or histopathological tumor characteristics and FGFR4 genotype (Table 1). Borderline significant associations of Arg388 allele presence with higher grade (P = .056) and with larger tumors (P = .058) were seen.
Association Between FGFR4 Alleles and Clinicopathologic Variables
Expression Patterns of FGFR4 and HER2
Seventy percent of invasive breast carcinoma tumors had low (1) to moderate (2), 22% strong (3), and 8% score 0 FGFR4 staining (Fig 1). FGFR4 staining (all scores) showed a diffuse and granular cytoplasmatic pattern; distinct membrane staining was observed in some tumors but never without cytoplasmatic staining. FGFR4 and HER2 scores were not significantly correlated. FGFR4 and HER2 IHC results are summarized in Table 2.
FGFR4 immunohistochemistry in poorly differentiated invasive ductal breast carcinomas. (A) Strong (score 3); (B) moderate (score 2); (C) weak staining (score 1); (D) positive control (strong staining in MDA-MB-231 cells infected with retrovirus expressing FGFR4); (E) negative control (no immunoreactivity in noninfected MDA-MB-231 cells).
Comparison of FGFR4 Expression and HER2 Expression, Ungrouped
FGFR4 Genotype, Expression of FGFR4 and HER2
FGFR4 genotype showed no significant association with FGFR phenotype (IHC; Table 3); this holds between each genotype and each expression pattern separately or grouped (high/low) and for grouped FGFR4 genotype (wild-type [Gly/Gly] v homozygous or heterozygous Arg388 carriers). No significant correlation was seen between FGFR4 genotype and HER2 expression. Interestingly, no HER2 overexpression (ie, score 3+ or even 2+) was found in tumors with absent FGFR4 expression (ie, score 0; Table 2); absence of staining (score 0) in HER2 and in FGFR4 expression were significantly (P = .013) associated.
Comparison of FGFR4 Genotype, FGFR4 Expression, and HER2
FGFR4 Genotype and Disease Progression
Consistent with Bange et al,23 no significant association between FGFR4 genotype and disease progression or patient outcome was seen for the whole cohort (DFS, P = .13; overall survival [OS], P = .09) and for node-negative patients (DFS, P = .51; OS, P = .71). In node-positive patients, however, presence of Arg388 allele was associated with shorter DFS (P = .019) and OS (P = .04; Fig 2). No significant association was found between presence of Arg388 allele and DFS or OS in the small (n = 13) node-positive subgroup with no FGFR4 staining.
FGFR4 Arg388 allele is related to tumor progression. Probability of disease-free survival (DFS) in patients without axillary lymph node involvement (A) and with lymph node metastasis (B) according to their FGFR4 allele status.
FGFR4 Genotype and Adjuvant Systemic Therapy
The relationship between FGFR4 genotype and course of disease depended on administration of adjuvant systemic therapy: No significant survival differences between FGFR4 genotypes were found in patients without adjuvant systemic therapy. However, with adjuvant systemic therapy, the wild-type cohort showed better DFS (P = .025) and OS (P = .045; Fig 3). Separately considering adjuvant therapy types (chemo-/endocrine), no significant survival difference was seen in patients with adjuvant endocrine therapy (Fig 3). In contrast, in patients with adjuvant chemotherapy, significant survival differences were observed favoring FGFR4 wild-type carriers for DFS (P = .023) and OS (P = .08; Fig 3).
Effect of adjuvant systemic therapy (upper panel) and type of adjuvant systemic therapy (lower panel) on prognostic impact of FGFR4 Arg388 allele in primary breast cancer. (A) No adjuvant systemic therapy; (B) adjuvant systemic therapy; (C) adjuvant endocrine therapy; and (D) adjuvant chemothearpy. DFS, disease-free survival; NS, not significant.
FGFR4 Arg388 Allele As a Predictor for Resistance to Systemic Therapy: Interaction Analysis
These results strongly suggest the presence of an interaction. Multivariate analysis was performed in two steps: In the first step, the model included established prognostic factors (affected lymph nodes, tumor stage, hormone receptor status, grading, and age) as well as adjuvant chemotherapy and endocrine therapy; nodal involvement was coded as fractional rank of number of nodes; squared fractional rank was included. The step also included a binary variable FGFR4 genotype (wild-type [Gly/Gly] v homozygous or heterozygous Arg388 carriers). In the second step, interactions between this binary variable FGFR4 genotype and the following factors were included: presence of adjuvant therapy (either or both), chemotherapy, endocrine therapy, nodal status, and ranked nodal involvement (Table 4). The resulting model showed that, next to the hazard associated with lymph node involvement and the substantial benefit from both kinds of adjuvant systemic therapy, the interaction between FGFR4 genotype and adjuvant therapy had the strongest impact on DFS. Specifically, the interaction implies that patients with the Arg388 allele had only about half as much benefit from adjuvant systemic therapy as patients with the wild type (Table 4). No difference between heterozygous and homozygous Arg388 carriers was seen in this regard. An alternative interaction model including the interactions between each separate type of therapy (chemo- and endocrine) and FGFR4 genotype (but not adjuvant therapy as a whole) yields a significant interaction with chemotherapy (hazard ratio [HR] = 2.2; 95% CI, 1.1 to 4.4; P = .03) of similar impact (compare Kaplan-Meier analysis in Fig 3). In addition, neither an impact of FGFR4 expression nor an interaction of FGFR4 expression with therapy was found.
Multivariate Cox Model (disease-free survival) Including Interaction of FGFR4 Genotype With Adjuvant Therapy
FGFR4 and HER2 Expression and Disease Progression
No significant association between FGFR4 and HER2 expression was observed. There was no significant impact of FGFR4 expression or HER2 expression on disease outcome. Moreover, no significant correlation between HER2 status and disease outcome was observed.
DISCUSSION
To validate the role of FGFR4 Arg388 polymorphism in breast cancer as first reported by Bange et al,23 a substantially larger patient cohort with long-term follow-up has now been evaluated, including FGFR4 and HER2 expression as well as FGFR4 genotype. Associations between FGFR4 and disease outcome were analyzed, taking the influence of different adjuvant systemic therapies separately into account.
The allele proportions for Gly388 and Arg388 found here resemble those reported by Bange et al23 in the normal population and in breast and colon cancer patients, independent of ethnic background, and these proportions are consistent with Hardy-Weinberg equilibrium for a Gly388 frequency of approximately 70%. No significant associations were found between FGFR4 genotype and established clinicopathological parameters, in accordance with Jezequel et al,29 although borderline significant associations of Arg388 allele presence with higher grade and with larger tumors were noted.
We have now extended the focus, considering both FGFR4 genotype and phenotype. No significant correlation between FGFR4 genotype and FGFR4 expression was found, in accordance with Streit et al for HNSCC.24 Moreover, no significant association between FGFR4 expression and disease outcome or response to adjuvant therapy was observed. Thus far, FGFR4 genotype provides the clinically more relevant information. Plausible explanations include the following: Arg388 allele might not influence protein expression; or the scoring system might not adequately capture the underlying biology.
In this larger cohort, no significant correlation between FGFR4 geno- or phenotype and HER2 expression was observed. Remarkably, no high HER2 expression (ie, 3+ or even 2+) was observed in those 16 patients scored 0 for FGFR4 expression. Influence of HER2 on disease course reflects a combination of both prognostic and predictive impact.30 Hence, the lack of significant correlation between HER2 status and disease course here could reflect masking of prognostic impact by predictive impact (therapy resistance/response), which sometimes becomes visible when stratifying according to nodal status.30
As previously reported,23 we observed a significant association between FGFR4 genotype and disease outcome in node-positive but not in node-negative patients; FGFR4 Gly388 was associated with favorable DFS and OS. These results support the hypothesis that Arg388 allele accelerates advanced breast cancer progression, as reported for colon23 and soft-tissue carcinomas.31 For HNSCC, this association was demonstrated for tumors with high FGFR4 expression.24
There is evidence that “prognostic” impact of a factor can be confounded by administration of adjuvant systemic therapy.27,32 Consequently, a factor’s influence on tumor aggressiveness is reflected in DFS in patients without adjuvant systemic therapy, whereas a factor’s predictive impact (therapy resistance or response) emerges in DFS of patients with adjuvant systemic therapy. Whereas adjuvant therapy tends to be homogeneous and guideline-oriented, OS results are confounded by individualized heterogeneous therapies following relapse. Because indication for adjuvant systemic therapy was linked to nodal status when our patients were treated, we thus analyzed impact of FGFR4 genotype on survival considering administration and type of adjuvant systemic therapy separately. As suggested by the apparent dependence of prognostic impact of FGFR4 Arg388 genotype on nodal status, a significant survival impact of FGFR4 was indeed found only in patients with adjuvant systemic therapy. Interestingly, this survival difference favoring FGFR4 wild type was more strongly evident in patients with chemotherapy than in patients with endocrine therapy alone.
The molecular mechanism by which FGFR4 Arg388 polymorphism leads to a more aggressive clinical phenotype is not yet fully understood. Similar mutations in the transmembrane domain of HER2 or FGFR3 result in increased tyrosine kinase activity and are associated with cellular transformation and developmental disorders. However, for FGFR4 Arg388, no elevated tyrosine phosphorylation was observed compared with FGFR4 Gly388 in breast and prostate cancer cells.23 This might indicate that changes in kinase activity are too subtle to detect differences reliably. Alternatively, the two polymorphic FGFR4 forms may use different intracellular signal transduction pathways or interact with different cell surface proteins. FGFR4 Arg388 allele may also be in linkage disequilibrium with other genetic changes that contribute to poor prognosis in breast cancer. Yet, cancer cells ectopically expressing FGFR4 Arg388 do possess increased cell motility and invasiveness, both characteristic of an aggressive tumor phenotype.23,33 Moreover, urokinase-receptor (uPAR) expression is increased in prostate epithelial cells expressing the FGFR4 Arg388 allele compared with FGFR4 Gly388 allele–expressing cells.33 uPAR is the cell-surface receptor for the urokinase-type plasminogen activator/plasminogen activator inhibitor type 1 system, playing a key role in breast cancer progression.34 Furthermore, urokinase-type plasminogen activator downregulation sensitizes tumor cells to chemotherapy-induced apoptosis.35 This background is particularly important, because one aspect in chemotherapy failure is tumor cell resistance to induction of apoptosis. Therefore, possible explanations for the impact of FGFR4 Arg388 allele on disease progression in patients with adjuvant chemotherapy include either increased expression of antiapoptotic factors or downregulation of proapoptotic factors in cells expressing FGFR4 Gly388 allele, as observed in previous investigations for promigration factors (J. Bange, unpublished results).
Recent data by Jezequel et al29 show no prognostic impact of FGFR4. These apparently conflicting results may well be attributed to differences in the patient cohorts, particularly regarding systemic therapy. Whereas their node-negative cohort was similar to ours regarding absence of adjuvant systemic therapy, systemic treatment of their node-positive cohort was different. Their chemotherapy consisted solely of anthracycline-based therapy, whereas less than 30% of our patients received anthracyclines. Moreover, our anthracycline-treated patients received a higher weekly dose (≥ 30 mg/m2). Hence, resistance to adjuvant therapy observed in our cohort could be associated with certain adjuvant therapy types, particularly CMF-based chemotherapy. This issue deserves further study.
In conclusion, the initially observed genotype-dependent difference in disease progression in node-positive patients had at first suggested FGFR4 as a pure marker for tumor aggressiveness, subdividing patients with advanced breast cancer into those with good or poor outcome. Our new findings with regard to survival differences dependent on administration and type of adjuvant systemic therapy point toward a much more complex role of FGFR4 in tumor progression. This new understanding could thus impact basic research as well as clinical management, potentially leading to differential strategies in therapy design.
Authors’ Disclosures of Potential Conflicts of Interest
The authors indicated no potential conflicts of interest.
Author Contributions
Conception and design: Christoph Thussbas, Johannes Bange, Monika Kriner, Kurt Ulm, Axel Ullrich, Nadia Harbeck
Financial support: Axel Ullrich
Provision of study materials or patients: Jorg Nahrig, Sylvia Streit, Marion Kiechle, Heinz Hoefler, Nadia Harbeck
Collection and assembly of data: Christoph Thussbas, Jorg Nahrig, Sylvia Streit, Marion Kiechle, Heinz Hoefler, Nadia Harbeck
Data analysis and interpretation: Christoph Thussbas, Jorg Nahrig, Sylvia Streit, Johannes Bange, Monika Kriner, Ronald Kates, Kurt Ulm, Marion Kiechle, Nadia Harbeck
Manuscript writing: Christoph Thussbas, Jorg Nahrig, Johannes Bange, Monika Kriner, Ronald Kates, Kurt Ulm, Nadia Harbeck
Final approval of manuscript: Christoph Thussbas, Jorg Nahrig, Sylvia Streit, Johannes Bange, Monika Kriner, Ronald Kates, Kurt Ulm, Marion Kiechle, Heinz Hoefler, Axel Ullrich, Nadia Harbeck
GLOSSARY
- FGFR4:
- Shows the strong binding to acidic FGF, bFGF, FGF-4, FGF-6, FGF-8, and FGF-9. FGFR3 and FGFR4 have been shown to co-operate in lung development. It is involved in the development of endoderm derivatives and in skeletal muscle formation, and also plays a role in the cascade of molecular events leading to terminal muscle differentiation.
- Germ-line polymorphism:
- Germ-line polymorphism is a difference in DNA sequence among individuals in the germ cells. Unlike somatic cell genetic mutations, these polymorphisms can be transmitted to an organism’s offspring. Genetic polymorphisms may be the result of a chance process or may have been induced by external agents (such as viruses or radiation). Changes in DNA sequence that have been confirmed to be caused by external agents are generally called “mutations” rather than “polymorphisms.”
- Hardy-Weinberg equilibrium:
- A state in which genotype frequencies and ratios remain constant from generation to generation and in which genotype frequencies are a product of allele frequencies. A randomly mating population tends toward a Hardy-Weinberg equilibrium state if there are no mutations, migrations, or environmental factors favoring particular genotypes.
- Linkage disequilibrium:
- Nonrandom association of linked genes. This is the tendency of the alleles of two separate but already linked loci to be found together more frequently than would be expected by chance alone.
- PCR-RFLP analysis (polymerase chain reaction restriction fragment length polymorphism):
- PCR-RFLP analysis is a technique in which organisms may be differentiated by analysis of patterns derived from cleavage of their DNA. If two organisms differ in the distance between sites of cleavage of a particular restriction endonuclease, the length of the fragments produced will differ when the DNA is digested with a restriction enzyme. Isolation of sufficient DNA for RFLP analysis is time consuming and labor intensive. However, PCR can be used to amplify very small amounts of DNA, usually in 2 to 3 hours, to the levels required for RFLP analysis.
- Predictive impact:
- A measurable patient characteristic that is associated with the degree of response to therapy. The predictive impact of a factor refers to that part of its influence on the subsequent course of disease that is attributable to its association with therapy response. The impact of a factor can be prognostic, predictive, or both.
- Prognostic factor:
- A measurable patient characteristic that is associated with the subsequent course of disease (whether or not therapy is administered). The identification of a prognostic factor does not necessarily imply a cause-and-effect relationship. However, within a suitable outcome model, the measurement of a prognostic factor contributes to an estimate of an outcome probability (eg, the probability of disease-free survival within a given time interval).
- Protein tyrosine kinases:
- Generic name for enzymes that phosphorylate tyrosine molecules in proteins.
- SNP (single nucleotide polymorphism):
- Genetic polymorphisms are natural variations in the genomic DNA sequence present in greater than 1% of the population, with SNP representing DNA variations in a single nucleotide. SNPs are being widely used to better understand disease processes, thereby paving the way for genetic-based diagnostics and therapeutics.
- Tissue microarrays:
- Used to analyze the expression of genes of interest simultaneously in multiple tissue samples, tissue microarrays consist of hundreds of individual tissue samples placed on slides ranging from 2 to 3 mm in diameter. Using conventional histochemical and molecular detection techniques, tissue microarrays are powerful tools to evaluate the expression of genes of interest in tissue samples. In cancer research, tissue microarrays are used to analyze the frequency of a molecular alteration in different tumor types, to evaluate prognostic markers, and to test potential diagnostic markers.
Acknowledgments
We thank Anette Haas and Daniela Hellmann for their excellent technical assistance.
Footnotes
-
published online ahead of print at www.jco.org on July 5, 2006.
Supported by grants from Universal Mobile Telecommunications System (# 01GS0105, part 11) to H.H. and A.U., as well as the State of Bavaria (KKF Project # 8756159) and the Wilhelm Sander Foundation (2000.017.2) to N.H.
Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.
Terms in blue are defined in the glossary, found at the end of this article and online at www.jco.org.
- Received December 2, 2005.
- Accepted April 17, 2006.
