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The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis

The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the... British Journal of Cancer (2005) 92, 131 – 139 & 2005 Cancer Research UK All rights reserved 0007 – 0920/05 $30.00 www.bjcancer.com The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis ,1,7 1 1 2 1 3 4 5 C Mascaux , N Iannino , B Martin , M Paesmans , T Berghmans , M Dusart , A Haller , P Lothaire , 1,7 1 6 1 A-P Meert , S Noel , J-J Lafitte and J-P Sculier 1 2 Department of Intensive Care and Thoracic Oncology, Institut Jules Bordet, Centre des Tumeurs de l’Universite´ Libre de Bruxelles, Belgium; Data Centre, Institut Jules Bordet, Centre des Tumeurs de l’Universite´ Libre de Bruxelles, Belgium; Department of Nuclear Medicine, Institut Jules Bordet, Centre des ´ ´ Tumeurs de l’Universite Libre de Bruxelles, Belgium; Department of Pathology, Institut Jules Bordet, Centre des Tumeurs de l’Universite Libre de Bruxelles, 5 6 Belgium; Department of Surgery, Institut Jules Bordet, Centre des Tumeurs de l’Universite Libre de Bruxelles, Belgium; Chest Department, CHU Calmette, Lille, France; FNRS (Fonds National de la Recherche Scientifique), Belgium The proto-oncogene RAS, coding for a 21 kDa protein (p21), is mutated in 20% of lung cancer. However, the literature remains controversial on its prognostic significance for survival in lung cancer. We performed a systematic review of the literature with meta- analysis to assess its possible prognostic value on survival. Published studies on lung cancer assessing prognostic value of RAS mutation or p21 overexpression on survival were identified by an electronic search. After a methodological assessment, we estimated individual hazard ratios (HR) estimating RAS protein alteration or RAS mutation effect on survival and combined them using meta- analytic methods. In total, 53 studies were found eligible, with 10 concerning the same cohorts of patients. Among the 43 remaining studies, the revelation method was immunohistochemistry (IHC) in nine and polymerase chain reaction (PCR) in 34. Results in terms of survival were significantly pejorative, significantly favourable, not significant and not conclusive in 9, 1, 31, 2, respectively. In total, 29 studies were evaluable for meta-analysis but we aggregated only the 28 dealing with non-small-cell lung cancer (NSCLC) and not the only one dealing with small-cell-lung cancer (SCLC). The quality scores were not statistically significantly different between studies with or without significant results in terms of survival, allowing us to perform a quantitative aggregation. The combined HR was 1.35 (95% CI: 1.16–1.56), showing a worse survival for NSCLC with KRAS2 mutations or p21 overexpression and, particularly, in adenocarcinomas (ADC) (HR 1.59; 95% CI 1.26–2.02) and in studies using PCR (HR 1.40; 95% CI 1.18–1.65) but not in studies using IHC (HR 1.08; 95% CI 0.86–1.34). RAS appears to be a pejorative prognostic factor in terms of survival in NSCLC globally, in ADC and when it is studied by PCR. British Journal of Cancer (2005) 92, 131–139. doi:10.1038/sj.bjc.6602258 www.bjcancer.com Published online 14 December 2004 & 2005 Cancer Research UK Keywords: RAS; p21; lung cancer; meta-analysis; systematic review; survival; prognostic factor Lung cancer is a major cause of death despite diagnostic and reflecting proliferative state, have already been identified in therapeutic improvements. The overall 5-year survival rate is less patients with lung cancer (Kanters et al, 1995). In order to clarify than 10%. However, the prognosis can be modulated by the prognostic impact of other biological factors in lung cancer, characteristics related to the patient or to the tumour. Some our group has performed systematic reviews of the literature with independent prognostic factors for survival have already been meta-analyses. It allowed us to show that VEGF (Delmotte et al, identified. They include, for small-cell lung cancer (SCLC): disease 2002), microvessel density (Meert et al, 2002b), c-erbB-2 (Meert extent and performance status (PS) (Paesmans et al, 2000); for et al, 2003) and p53 (Steels et al, 2001) have statistically significant non-small cell lung cancer (NSCLC): PS, stage and, with lower worse impact on survival, while Bcl-2 (Martin et al, 2003) has a impact, age, sex and weight loss (Paesmans et al, 1995; Strauss, favourable survival impact. 1997). Oncogenes (RAS, Raf, Myc, Src, Abl/Bcr, c-erbB-2, y) are With the recent progresses in molecular biology, the research on derived from normal genes (the proto-oncogene) coding for prognostic factors could be extended to proteins and genes proteins, which play key roles in physiological cellular processes involved in cancer development. The biological factors implicated such as regulations of gene expression or growth signal transduc- in carcinogenesis should also be considered as potential survival tion. Particularly, RAS oncogene is involved in lung cancer prognostic factors. Some of them, like angiogenesis and factors development. Three human RAS genes (Rodenhuis and Slebos, 1990) have been identified: the HRAS gene (homologous to the oncogene of the Harvey rat sarcoma virus), the KRAS2 gene *Correspondence: Dr C Mascaux, Institut Jules Bordet, rue He´ger- (homologous to the oncogene of the Kirsten rat sarcoma virus) and Bordet, 1 B-1000 Brussels, Belgium; E-mail: celine.mascaux@bordet.be the NRAS gene (first isolated from a human neuroblastoma). Received 18 June 2004; revised 29 September 2004; accepted 18 These genes code for four highly homologous 21 kDa proteins October 2004; published online 14 December 2004 called p21, with a common effector domain within the N-terminal Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al region. To be biologically active, RAS proteins must be localised to (Steels et al, 2001). Each item was assessed using an ordinal scale the inner face of the plasma membrane, where they can effectively (possible values: 2, 1, 0). A consensus was reached in regular interact with their upstream activators and downstream targets. meetings where at least two-thirds of the investigators needed to be The RAS gene proteins can exist in two states: an active state, in present. As the assessed items were objective ones, a consensus which GTP is bound to the molecule and an inactive state, in which was always obtained. the GTP has been hydrolysed to GDP. In physiologic conditions, The overall score evaluated several dimensions of the metho- the active isoform initiates cell proliferation through the RAS- dology, grouped into four main categories: the scientific design, dependent kinase cascade. The RAS proteins possess intrinsic the description of laboratory methods used to identify the presence GTPase activity, which normally leads to their inactivation and the of RAS mutation or p21 expression, the generalisability of the control of cell growth. In tumours, a point mutation resulting in results and the analysis of the study data. Each category had a loss of the intrinsic GTPase activity appears to be associated with maximum score of 10 points, with a maximal theoretical score of transforming activity of the protein, which does not stop anymore 40 points. When an item was not applicable to a study, its value to send the signal stimulating cell proliferation. KRAS2 mutations was not taken into account in the total of the concerned category. are particularly common in pancreatic cancers, colorectal malig- The final scores were expressed as percentages, ranging from 0 to nancies and lung cancer (Rodenhuis, 1992; Minamoto et al, 2000). 100%, higher values reflecting better methodological quality. RAS mutations are detected in 15–20% of NSCLC and, Studies included in the systematic review were called ‘eligible’, particularly, 30–50% of adenocarcinomas (ADC) (Rodenhuis those providing sufficient data for the meta-analysis ‘evaluable’. To et al, 1988). In lung cancer, 90% of the mutations are located in be eligible, studies had to provide univariate analysis. the RAS2 gene and both NRAS mutations and HRAS mutations have occasionally been documented (Rodenhuis and Slebos, 1990). In total, 80% of KRAS2 mutations occur in codon 12. Other Statistical methods mutations are located in codons 13 and 61. The predominant mutation is a G–T transversion (70% of tumours) (Rodenhuis and A study was considered as significant if the P-value for the Slebos, 1990). statistical test comparing survival distributions between the groups The literature remains controversed on the prognostic value of with and without RAS-p21 alteration was o0.05. A study was RAS for survival in patients with lung cancer. In order to clarify called ‘positive’ when a mutation/expression in RAS-p21 proto- this question, we have performed a systematic review of the oncogene was identified as a significant favourable prognostic literature with methodological assessment and meta-analysis. factor for survival. The study was called ‘negative’ if the same characteristic was associated with a significant detrimental impact on survival. Finally, a study was called ‘not significant’ if no statistically significant difference between the two groups was MATERIALS AND METHODS detected and ‘not conclusive’ if any conclusion about significance Publications selection of survival results could be derived from the article. The association between two continuous variables was measured To be eligible for the systematic review, a study had to fulfil the by the Spearman rank correlation coefficient. Nonparametric tests following criteria: to deal only with lung cancer (any stage or were used to compare the distribution of the quality scores histology), to assess the correlation between RAS mutation or p21 according to the value of a discrete variable (Mann–Whitney tests expression and survival, to analyse RAS-p21 in the primary for dichotomic variables or Kruskal–Wallis tests for multiple tumour (not in metastatic tissue or tissue adjacent to the tumour) classes variables). and/or antibodies against p21 in the serum, to have been published For the quantitative aggregation of the survival results, we as a full paper in the English or French language. Abstracts were measured the impact of RAS mutation and/or p21 expression on excluded because they do not provide sufficient data to evaluate survival by hazard ratio (HR) between the two survival distribu- the methodological quality of the trial and/or to perform meta- tions. For each trial, this HR was estimated by a method depending analysis. on the data provided in the publication. The most accurate method Studies were identified by an electronic search on Medline consisted of calculating the estimated HR and its standard error databank and using the following keywords: ‘lung cancer’, ‘lung (s.e.) from the reported results or to calculate them directly using carcinoma’, ‘lung neoplasms’, ‘lung tumour’, ‘lung tumours’, ‘lung two of the following parameters: the O-E statistic (difference tumour’, ‘lung tumours’, ‘lung adenocarcinoma’, ‘lung squamous’, between numbers of observed and expected events), the confidence ‘NSCLC’, ‘non-small cell lung cancer’, ‘non small cell lung cancer’, interval (CI) for the HR, the logrank statistic or its P-value. If these ‘non-small cell lung carcinoma’, ‘non small cell lung carcinoma’, were not available, the total number of events, the number of ‘SCLC’, ‘small cell lung cancer’, ‘small cell lung carcinoma’, ‘ras’, patients at risk in each group and the logrank statistic or its P- ‘K-ras’, ‘Ki-ras’, ‘n-ras’, ‘c-ras’, ‘l-ras’, ‘h-ras’, ‘p21’. The search value were used to allow for an approximation of the HR estimate. ended on July 2003. The bibliographies reported in all the Finally, if the only exploitable data were in form of graphical identified studies were used to complete this search. When the representations of the survival distributions, survival rates at some authors reported results obviously obtained on the same patients specified times were extracted in order to reconstruct the HR population in several publications, only the most recent or the estimate and its variance, with the assumption that the rate of most complete study was included in the analysis, in order to avoid patients censored was constant during the study follow-up overlapping between cohorts. (Parmar et al, 1998). If this last method was used, three independent persons read the curves to reduce inaccuracy in the extracted survival rates. The individual HR estimates were Methodological assessment combined into an overall HR using Peto’s method (Yusuf et al, To assess the quality of the methodology, each study was read 1985), which consisted of using a fixed effect model assuming independently by 12 investigators, including nine physicians and homogeneity of the individual true HRs. This assumption was three scientists. The participation of many readers was a guarantee tested by performing w tests for heterogeneity. If the assumption for the correct interpretation of the articles. The methodological of homogeneity had to be rejected, we used a random-effect model evaluation was scored according to the European Lung Cancer as a second analysis. By convention, an observed HRo1 implied a Working Party (ELCWP) scale. The scoring system used has better survival for the group with mutated RAS or p21 expression. already been described in one of our prior systematic reviews This impact of RAS on survival was considered as statistically British Journal of Cancer (2005) 92(1), 131 – 139 & 2005 Cancer Research UK Meta-analysis: K-RAS in lung cancer C Mascaux et al significant if the 95% confidence interval for the overall HR did not and the lack of repartition of tumours according to RAS mutation/ overlap 1. expression in 1 (Ahrendt et al, 2002). When data about global survival of the entire patients population were available, survival was analysed globally. If Study results report authors only reported the results separately for different sub- groups, those results corresponded to different cohorts of patients Nine of the 43 studies (20.9%) identified proto-oncogene RAS and were treated separately in the meta-analysis. mutations or p21 overexpression as a pejorative prognostic factor for survival (with seven evaluable for the meta-analysis), 31 (72.1%) concluded that RAS was not a prognostic factor for survival (21 evaluable), one (2.3%) reported a better prognosis for RESULTS RAS positivity (evaluable) and two (4.7%) were nonconclusive (both nonevaluable). Study selection and characteristics Overall, the rates of RAS mutations detected by PCR and p21 In total, 53 publications, published between 1990 and 2003, were protein overexpression were, respectively, 18.4% (number of found eligible for the systematic review (Rodenhuis et al, 1988, evaluable tumours (n)¼ 3779) and 44.6% (n¼ 1548) in NSCLC, 1997; Slebos et al, 1990; Mitsudomi et al, 1991; Miyamoto et al, 7.1% (n¼ 141) and 32.3% (n¼ 223) in squamous cell carcinomas 1991; Harada et al, 1992; Sugio et al, 1992; Rosell et al, 1993, 1995b, (SQCC) and 23.1% (n¼ 1847) and 34.7% (n¼ 222) in ADC. The 1996, 1997; Volm et al, 1993, 2002; Westra et al, 1993; Kern et al, rates of positive tumours by molecular biology or IHC were, 1994; Li et al, 1994; Silini et al, 1994; Fujino et al, 1995; Kashii et al, respectively, 21.8% (n¼ 1015) and 54.8% (n¼ 135) in stage I 1995; Keohavong et al, 1996, 1997; Cho et al, 1997; Dosaka-Akita NSCLC, 16.0% (n¼ 399) and 53.5% (n¼ 71) in NSCLC patients et al, 1997; Fukuyama et al, 1997; Komiya et al, 1997; Pifarre´ et al, with stages I and II, 16.2% (n¼ 1263) and 38.5% (n¼ 929) in those 1997; Siegfried et al, 1997; Visscher et al, 1997; De Gregorio et al, with stages I–III. 1998; Greatens et al, 1998; Huang et al, 1998; Kim et al, 1998; Kwiatkowski et al, 1998; Nemunaitis et al, 1998; Wang et al, 1998; Dingemans et al, 1999; Fu et al, 1999; Graziano et al, 1999; Miyake Quality assessment et al, 1999; Nelson et al, 1999; Hommura et al, 2000; Konishi et al, The overall quality score ranged from 31.04 to 78.15% with a 2000; Moldvay et al, 2000; Schneider et al, 2000; Andjelic et al, median of 52.2% (Table 2A). The design subscore had the lowest 2001; Kang et al, 2001; Schiller et al, 2001; Ahrendt et al, 2002; value, with a median of 40%. Broermann et al, 2002; Shoji et al, 2002; Tomizawa et al, 2002; No statistically significant quality difference was shown between Grossi et al, 2003; Ramirez et al, 2003). In all, 10 of these articles significant and nonsignificant studies neither for the global score were excluded because an identical patient cohort had been used in (median: 51.50 vs 53.83%, P¼ 0.90), neither for the four subgroups other selected publications (Rodenhuis et al, 1988; Miyamoto et al, scores. There was also no statistically significant difference 1991; Fujino et al, 1995; Rosell et al, 1995a, b, 1996; Dosaka et al, between evaluable and nonevaluable studies for meta-analysis in 1997; Keohavong et al, 1997; Hommura et al, 2000; Konishi et al, terms of global scores (55.23 vs 44.31%, P¼ 0.10), but the evaluable 2000; Volm et al, 2002). One of the 43 remaining studies (Volm ones had a better score concerning the report of the analysis et al, 1993) assessed separately by immunohistochemistry (IHC) results: 62.5% in comparison to 31.3% for the nonevaluable trials KRAS2, NRAS and HRAS p21. All the other papers concerned (P¼ 0.001). There was a significant correlation between the global KRAS2 only. Therefore, for the meta-analysis, we took into score and the number of patients included (Spearman correlation account only the characteristics and the data concerning KRAS2 coefficient r¼ 0.50, P¼ 0.0006), studies including a higher number p21 expression. of patients showing a better global score. The generalisability of The total number of included patients was 5216, ranging from 21 the results was significantly better in the recent publications to 355 patients per study (median: 103). The main characteristics (r¼ 0.42, P¼ 0.004). There was also a statistically significant of the 43 publications eligible for the systematic review are difference between studies assessing RAS-p21 status by IHC reported in Table 1. In total, 27 were dealing with NSCLC, 11 with (n¼ 9) or by molecular biology (n¼ 34), with global scores of adenocarcinoma only, three with any histological type, one with 58.51 and 49.93%, respectively (P¼ 0.029) and scores assessing the SCLC and one with both ADC and large cell carcinoma. A total of description of the laboratory methodology of 64.3 vs 46%, those 22 studies concerned only nonmetastatic disease, one only stage IV based on IHC being better described than those on molecular disease and 19 all stages (I–IV). One study did not mention the biology (P¼ 0.002). stage of the tumours. In 15 publications, patients were treated by Table 2B reports the analysis of the scores for the 29 studies surgery alone. Surgery was associated with an adjuvant therapy evaluable for meta-analysis. Their overall quality score ranged (radiotherapy and/or chemotherapy) in 26. In one study, SCLC between 34.25 and 78.15%, with a median of 55.24%. The design patients were treated with a combination of radiotherapy and subscore was also the worst reported. Like previously observed chemotherapy (Dingemans et al, 1999). In the last paper, treatment among eligible publications, there was no statistically significant was not described De Gregorio et al, 1998). difference between significant and nonsignificant studies evaluable Nine studies evaluated the accumulation of p21 protein by for the meta-analysis according to the global score (median of IHC. The other 34 identified RAS mutation by molecular biology, 53.04 vs 53.42%, P¼ 0.92). There was also a significant correlation using different polymerase chain reaction (PCR) methodologies, between global score and the number of patients included in the mainly, single-strand conformation polymorphism (SSCP) study (Spearman correlation coefficient r¼ 0.53, P¼ 0.006) and (n¼ 10) and restriction fragment length polymorphism (RFLP) those assessing RAS positivity by IHC obtained a better quality (n¼ 8). scores for the laboratory method subgroup (57.1 vs 50% for Among the 43 studies eligible for the systematic review, 14 were molecular biology, P¼ 0.04), but not for the global score. inevaluable for the meta-analysis due to insufficient data reported in the article. The reasons for noninclusion of a study into the meta-analysis were the lack of available survival results to calculate Meta-analysis HR in 13 (Volm et al, 1993; Westra et al, 1993; Li et al, 1994; Kashii et al, 1995; Pifarre et al, 1997; Visscher et al, 1997; De Gregorio The absence of significant methodological quality difference et al, 1998; Greatens et al, 1998; Fu et al, 1999; Miyake et al, 1999; between significant and nonsignificant studies allowed us to Schneider et al, 2000; Andjelic et al, 2001; Broermann et al, 2002) perform a quantitative aggregation of the survival results. The & 2005 Cancer Research UK British Journal of Cancer (2005) 92(1), 131 – 139 Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al Table 1 Main characteristics and results of the eligible studies First author Year Histology Stage N pts Laboratory method HR estimation Survival results Ahrendt 2002 NSCLC I – IIIA 60 PCR-seq No data NC Andjelic 2001 NSCLC IIIA 21 PCR-SSCP No data Negative Broermann 2002 NSCLC III 28 PCR-RFLP No data NS Cho 1997 NSCLC I – IIIB 58 PCR-SSCP Survival curves Negative De Gregorio 1998 ADC I – IV 184 PCR No data NS Dingemans 1999 SCLC ANY 93 IHC Survival curves NS Fu 1999 NSCLC I – IIIB 158 IHC No data NS Fukuyama 1997 NSCLC I – IV 159 PCR-RFLP Survival curves Negative Graziano 1999 NSCLC I – II 213 PCR Log rank NS Greatens 1998 NSCLC I – IV 101 PCR-SSCP No data NS Grossi 2003 NSCLC I – IIIA 249 PCR HR NS Harada 1992 NSCLC I – IV 94 IHC Survival curves Negative Huang 1998 NSCLC I – IIIB 144 PCR-SSCP Survival curves Negative Kang 2001 NSCLC I – IIIB 61 IHC HR NS Kashii 1995 ALL I – IV 97 PCR-SSCP No data NS Keohavong 1996 NSCLC I – IV 126 PCR-DGGE Log rank NS Kern 1994 ADC I – IV 44 PCR-ASO HR NS Kim 1998 NSCLC I – IV 238 IHC HR NS Komiya 1997 NSCLC I – IIIA 137 IHC Survival curves NS Kwiatkowski 1998 NSCLC I 244 PCR-RFLP Log rank NS Li 1994 ADC I – ? 41 PCR-dot blot No data NS Mitsudomi 1991 ALL I – IV 66 PCR-RFLP Log rank NS Miyake 1999 NSCLC I – IIIB 187 PCR-SSCP No data Negative Moldvay 2000 NSCLC I – IV 227 IHC Log rank NS Nelson 1999 NSCLC I – IV 355 PCR-RFLP Survival curves Negative Nemunaitis 1998 ADC+LC I – IV 103 PCR-RFLP Survival curves NS Pifarre 1997 NSCLC I – IIIA 64 PCR-SSCP No data NC Ramirez 2003 NSCLC I – IV 50 PCR Survival curves NS Rodenhuis 1997 ADC III – IV 62 EPCR Log rank NS Rosell 1997 NSCLC I 35 PCR-SSCP Log rank NS Rosell 1993 NSCLC I – IIIA 66 PCR-RFLP Log rank Negative Schiller 2001 NSCLC II – IIIA 184 PCR-RFLP HR NS Schneider 2000 NSCLC I – IIIA 103 PCR-SSCP No data NS Shoji 2002 NSCLC I – IIIA 233 IHC Survival curves Positive Siegfried 1997 ADC I – IV 181 PCR-DGGE Survival curves NS Silini 1994 ADC I – IV 109 PCR-DGGE Survival curves NS Slebos 1990 ADC I – IIIA 69 PCR-ASO Log rank Negative Sugio 1992 ADC I – IV 115 PCR-dot blot Survival curves NS Tomizawa 2002 ADC I 110 PCR-seq Log rank NS Visscher 1997 ADC I – IV 31 PCR-SSCP No data NS Volm (KRAS2) 1993 NSCLC I – III 206 IHC No data NS Wang 1998 ALL I – IV 53 PCR-seq HR NS Westra 1993 ADC I – III 57 PCR-ASO No data NS N pts¼ number of patients; HR¼ hazard ratio; NSCLC¼ non-small-cell lung cancer; ADC¼ adenocarcinoma; SCLC¼ small-cell lung carcinoma; LC¼ large cell; NC¼ nonconclusive; NS¼ nonsignificative; PCR¼ polymerase chain reaction; SSCP¼ single-strand conformation polymorphism; RFLP¼ restriction fragment length polymorphism; ASO¼ allele-specific oligonucleotide hybridisation; DGGE¼ denaturating gradient gel electrophoresis; seq¼ PCR followed by sequencing of olignucleotide; EPCR¼ mutant-enriched PCR; IHC¼ immunohistochemistry; HR estimation¼ description of the methods used to estimate the individual HR according the three corresponding of the three different methods described in the statistics paragraph. meta-analysis was performed on 28 studies (3620 patients) dealing intervals (CI) 1.20–1.49). The test of heterogeneity was significant with NSCLC. (P¼ 0.01). Nevertheless, we calculated the HR by a random effect The individual HR of the 28 aggregable studies were calculated model that showed also a statistically significant impact on by one of the three methods reported in the Materials and Methods survival with an HR of 1.35 (95% CI: 1.16–1.56). section according to the available data. Only six studies reported In the subgroup analysis (Table 3) according to histology, RAS/ the data needed to directly calculate the estimated HR (HRs and p21 was not a statistically significant prognostic factor for survival 95% confidence intervals). In 10 trials, HR was approximated by in SQCC (H: 1.49, CI 95%: 0.88–2.52), but well in ADC, with the total number of events and the logrank statistic. For the 12 heterogeneity between the trials (heterogeneity test: P¼ 0.02) and a remaining studies, HR had to be extrapolated from the graphical random effect HR of 1.59 (CI 95%: 1.26–2.02). The meta-analysis representation of the survival distributions. of studies into three subgroups according to stages (stage I, stage The NSCLC overall meta-analysis included the 28 aggregable I–III and stage I–IV) did not show any statistically significant studies with a total number of 3620 patients. Two trials (Fukuyama impact of RAS on survival. For the last subgroup (stage I–IV) et al, 1997; Moldvay et al, 2000) gave only subgroup survival there were 11 studies with a large heterogeneity (Po0.001) and the analysis and their data were analysed separately like reported by random effect HR was borderline (1.41, 95% CI: 0.99–1.99). authors, increasing the number of individual cohorts aggregated to Furthermore, we aggregated the studies separately according to 30. The aggregation of the survival data is described in Table 3. the method used to detect RAS/p21 alteration (Table 3). The Overall RAS mutation or p21 expression was associated with a studies were first divided into two main groups according to the worse survival (HR (fixed effect model) 1.30; 95% confidence laboratory method: IHC (Figure 1) or molecular biology (Figure 2), British Journal of Cancer (2005) 92(1), 131 – 139 & 2005 Cancer Research UK Meta-analysis: K-RAS in lung cancer C Mascaux et al Table 2 Results of the methodological assessment of (a) eligible studies by the European Lung Cancer Working Party score and (b) evaluable studies by the European Lung Cancer Working Party score Global score (%) Design (%) Laboratory methodology (%) Generalisability (%) Results analysis (%) (a) All studies (N¼ 43) 52.2 40 50 67 50 Date of publication r Spearman 0.28 0.18 0.26 0.42 0.07 P-value 0.07 0.23 0.09 0.004 0.65 Patient number r Spearman 0.50 0.47 0.14 0.19 0.47 P-value 0.0006 0.001 0.36 0.22 0.002 Significant (n¼ 10) 51.50 40 46 62.5 62.5 Nonsignificant (n¼ 31) 53.83 40 50 66.7 50 P-value 0.9 0.93 0.35 0.39 0.41 Evaluable (n¼ 29) 55.23 40 50 66.7 62.5 Nonevaluable (n¼ 14) 44.31 45 46 62.5 31.3 P-value 0.10 0.67 0.66 0.8 0.001 Method of revelation IHC (n¼ 9) 58.51 50 64.3 66.7 62.5 Molecular biology (n¼ 34) 49.93 40 46 62.5 50 P-value 0.029 0.53 0.002 0.1 0.22 PCR subgroups SSCP (n¼ 10) 48.69 45 42 66.7 50 RFLP (n¼ 8) 52.56 50 46 62.5 75 P-value 0.33 0.39 0.71 0.86 0.16 Calculation of HR HR (n¼ 6) 62.35 50 50 71 75 Log rank (n¼ 10) 52.96 40 46.4 70.8 62.5 Survival curve (n¼ 13) 45.92 40 50 66.7 50 No data (n¼ 14) 44.31 45 46 62.5 31.3 P-value 0.10 0.62 0.62 0.52 0.001 (b) Evaluable studies (n¼ 29) 55.24 40 50 66.7 62.5 Date of publication r Spearman 0.36 0.27 0.25 0.44 0.12 P-value 0.05 0.17 0.19 0.02 0.54 Number of patient r spearman 0.52 0.69 0.05 0.34 0.34 P-value 0.004 0.00003 0.80 0.07 0.07 Significant (n¼ 8) 53.33 40 46 62.5 62.5 Nonsignificant (n¼ 21) 55.42 40 50 66.7 62.5 P-value 0.92 0.82 0.41 0.44 0.65 Method of revelation IHC (n¼ 7) 57.59 50 57 66.7 62.5 Molecular biology (n¼ 22) 51.46 40 50 62.5 62.5 P-value 0.24 0.52 0.04 0.19 0.69 PCR subgroups SSCP (n¼ 3) 53.83 40 42 75 50 RFLP (n¼ 7) 52.08 50 42 58.3 75 P-value 0.73 0.42 0.82 0.73 0.36 Calculation of HR HR (n¼ 6) 62.35 50 50 70.8 75 Log rank (n¼ 10) 52.96 40 46.4 70.8 62.5 Survival curves (n¼ 13) 45.92 40 50 66.7 50 P-value 0.18 0.47 0.43 0.30 0.037 r Spearman¼ correlation coefficient of Spearman; IHC¼ immunohistochemistry; PCR¼ polymerase chain reaction; SSCP¼ single-strand conformation polymorphism; RFLP¼ restriction fragment length polymorphism; HR¼ hazard ratio. The P-values are in bold when the statistical test is significant. & 2005 Cancer Research UK British Journal of Cancer (2005) 92(1), 131 – 139 Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al Table 3 Hazard ratio (HR) value for the NSCLC subgroup according to histology, stage and laboratory technique Nb Patients Fixed effects HR (95% CI) v Heterogeneity test Random effects HR (95% CI) Overall 28 3620 1.30 (1.20 – 1.49) P¼ 0.01 1.35 (1.16–1.56) Histology Squamous 4 280 1.49 (0.88 – 2.52) P¼ 0.48 ADC 15 1436 1.52 (1.30 – 1.78) P¼ 0.02 1.59 (1.26–2.02) Disease stage Stages I 5 562 1.26 (0.94 – 1.69) P¼ 0.43 Stages I – III 7 882 1.20 (0.93 – 1.53) P¼ 0.42 Stages I – IV 11 1553 1.25 (1.04 – 1.50) Po0.001 1.41 (0.99 – 1.99) Laboratory method IHC 7 989 1.08 (0.86 – 1.34) P¼ 0.21 PCR 23 2631 1.39 (1.22 – 1.58) P¼ 0.03 1.40 (1.18–1.65) PCR subgroups RFLP 6 765 1.70 (1.31–2.19) P¼ 0.53 SSCP 3 361 1.32 (0.72 – 1.47) P¼ 0.06 ADC IHC 4 266 1.57 (1.13 – 2.16) P¼ 0.01 1.48 (0.76 – 2.87) PCR 11 1170 1.50 (1.26–1.80) P¼ 0.1 Nb¼ number of studies; ADC¼ adenocarcinomas; IHC¼ immunohistochemistry; PCR¼ polymerase chain reaction; SSCP¼ single-strand conformation polymorphism; RFLP¼ restriction fragment length polymorphism; statistically significant results are in bold. Harada,1992 Cho,1997 Kang, 2001 Fukyama stages l−ll,1997 Fukyama stages lll−lV,1997 Kim,1998 Graziano,1999 Komiya,1997 Grossi, 2003 Moldvay squamous, 2000 Huang,1998 Moldvay adeno, 2000 Keohavong,1996 Shoji, 2002 Kern,1994 Kwiatkowski,1998 Mitsdudomi,1991 0.0 2.5 5.0 7.5 10.0 Nelson,1999 Figure 1 Meta-analysis of studies assessing RAS with IHC in NSCLC. Nemunaitis,1998 Hazard ratio (HR) and 95% confidence interval (CI) of survival in studies Ramirez, 2003 evaluating RAS-p21 status in NSCLC. HR41 implies a survival disadvan- Rodenhuis,1997 tage for the group with p21 expression. The square size is proportional to the number of patients included in the study. The center of the lozenge Rosell,1993 gives the combined HR of the meta-analysis and its extremities the 95% Rosell,1997 confidence interval. HR¼ 1.08; CI 95% 0.86–1.34. Total number of Schiller, 2001 patients: 989. Siegfried,1997 Silini,1994 Slebos,1990 including the different techniques of PCR. The fixed effect HR were Sugio,1992 respectively 1.08 (95% CI: 0.86–1.34) and 1.39 (95% CI: 1.22–1.58) for IHC and molecular biology. For PCR, there was a statistically Tomizawa,2002 significant heterogeneity (P¼ 0.03) and the random effect HR was Wang,1998 1.40 (95% CI: 1.18–1.65). Among the studies with PCR based revelation technique, two methods, PCR-RFLP and PCR-SSCP, were used in respectively six and three studies. Fixed effect HR of 0.0 2.5 5.0 7.5 10.0 1.7 (95% CI: 1.31–2.19) and 1.32 (95% CI: 0.72–1.47) were Figure 2 Meta-analysis of studies assessing RAS mutation with PCR in obtained, respectively, the first one only being statistically NSCLC. Hazard ratio (HR) and 95% confidence interval (CI) of survival in significant. studies evaluating RAS-p21 status in NSCLC. HR41 implies a survival Finally, we decided to perform an analysis in histological disadvantage for the group with RAS mutation. The square size is subgroups separately according to the method of detection. There proportional to the number of patients included in the study. The centre of were only four studies dealing with SQCC and it was a nonsense to the lozenge gives the combined HR of the meta-analysis and its extremities the 95% confidence interval. HR¼ 1.40; CI 95% 1.18 –1.65. Total number make more reduced subgroups analysis. We were able to analyse of patients: 2631. studies including ADC separating those using IHC from those applying PCR. Four studies were using IHC only. The HR (random-effects model, p heterogeneity test¼ 0.01) was 1.48 value of RAS alterations is observed in ADC but not for SQCC and (95% CI 0.76–2.87). The HR (fixed-effects model, p heterogeneity when PCR is used as revelation method but not when IHC is used. test¼ 0.1) for 11 studies assessing RAS mutation by PCR in ADC Our data help so to clarify the message of individual studies, was 1.50 (95% CI 1.26–1.80) (Figure 3). arguing with the hypothesis that RAS is a prognostic factor for lung cancer. This still needs to be confirmed in prospective trials with appropriate multivariate analysis taking into account other clinical or biological prognostic factors. Another meta-analysis DISCUSSION based on a review of the literature on the role of KRAS2 as The present systematic review of the literature with meta-analysis prognostic factor in lung cancer was previously published shows that RAS gene alteration and/or protein p21 overexpression (Huncharek et al, 1999). Only eight trials (Slebos et al, 1990; Kern is a poor prognostic factor for survival of patients with NSCLC in et al, 1994; Silini et al, 1994; Rosell et al, 1995a; Cho et al, 1997; univariate analysis. In subgroup analysis, the negative prognostic Fukuyama et al, 1997; Rodenhuis et al, 1997; Siegfried et al, 1997) British Journal of Cancer (2005) 92(1), 131 – 139 & 2005 Cancer Research UK Meta-analysis: K-RAS in lung cancer C Mascaux et al Some eligible trials had to be excluded from the meta-analysis Fukuyama,1999 because they did not provide sufficient data on survival. Among Huang,1998 the 14 excluded studies, 12 were nonsignificant (86%) while a lower proportion of the studies evaluable for the meta-analysis Kern,1994 were nonsignificant (70%). It is known that negative studies are Nelson,1999 less frequently published or, if they are, with less detailed results, Nemunaitis,1998 making them less assessable. However, the methodological quality of trials, according to the global score, was not significantly Rodenhuis,1997 different between evaluable and nonevaluable studies for the Siegfried,1997 quantitative aggregation of individual survival results. Silini,1994 Some results need comments: we only demonstrated significant impact of RAS alterations in ADC and not in SQCC. This Slebos,1990 observation suggests that the biological signalling pathways Sugio,1992 implicated in carcinogenesis are different for ADC and for SQCC. Tomizawa, 2002 Those information should interpreted carefully because RAS mutations are more frequently observed in ADC as compared with SQCC (23.12 vs 7.09%) Moreover, authors more often assessed ADC rather than SQCC (1436 vs 280 patients in the 0.0 2.5 5.0 7.5 10.0 meta-analysis). For example, Nelson’s trial (Nelson et al, 1999), Figure 3 Meta-analysis of studies assessing RAS mutation by PCR in firstly based on all histological subtypes, did not detect any adenocarcinomas. Hazard ratio (HR) and 95% confidence interval (CI) of mutation in squamous cell carcinoma and thus did not report data survival in studies evaluating RAS-p21 status in NSCLC. HR41 implies a on this histological subtype. Another example arises in Moldvay‘s survival disadvantage for the group with RAS mutation. The square size is study (Moldvay et al, 2000): she assessed overexpression of p21 by proportional to the number of patients included in the study. The centre of IHC in all tumours but only evaluate RAS mutation by PCR in the lozenge gives the combined HR of the meta-analysis and its extremities ADC and not in SQCC. There is a potential bias to evalue the the 95% confidence interval. HR¼ 1.50; CI 95% 1.26–1.80. Total number impact of RAS in squamous cell carcinomas and this should be of patients: 1170. further investigated. The diversity in the techniques used to identify alteration of were included because the selection criteria of the studies were RAS-p21 status can also be a potential source of bias. Firstly, IHC different from ours: the search for studies ended in 1997, only is not comparable among the nine studies. There were six different trials documenting KRAS2 mutation by PCR (and not those with primary antibodies, different revelation protocols and different IHC) were included, other histologies than NSCLC were excluded, level of positivity (from 0 to 50% or only based on intensity). 2-year survival rates had to be described. The authors observed Secondly, there is not a good correlation between DNA mutation that KRAS2 mutations detected by different PCR variants were and protein conformation or level of protein expression and thus poor prognostic factor for NSCLC. These results support the between molecular biology and IHC. Authors (Nelson et al, 1999; validity of ours. No subgroup analyses according to stage or Moldvay et al, 2000) who studied RAS mutation and p21 histology (ADC vs SQCC) were performed, not allowing us to expression on the same tumours did not find any correlation compare with our results. between the two abnormalities. Particularly, Nelson (Nelson et al, RAS gene mutations are involved in oncogenesis of a variety of 1999) did not observe significant impact of p21 expression in human tumours (Rodenhuis and Slebos, 1990). In lung cancer, multivariate analysis (P¼ 0.89), but well for RAS mutation Fisher et al (2001) has demonstrated that RAS mutation is (P¼ 0.04). Moldvay (Moldvay et al, 2000) only found three necessary for induction and maintenance of lung cancer. The same patients among 81 analysed with both RAS IHC staining and KRAS2 point mutation. It could bring some potential explanations author showed that lung tumours arising in the absence of tumour suppressor gene remain dependent on mutant KRAS2 for to the difference between IHC and PCR in our meta-analysis. PCR maintenance of tumour growth and that apoptosis after KRAS2 seems to be a more accurate technique to assess RAS in lung downregulation does not require p53 or Ink4A/Arf. Those points tumours. It is interesting to observe that we previously had never suggest that RAS plays a key role in lung carcinogenesis. Moreover, showed differences between the two techniques for other markers the present demonstration of its prognostic role in lung suggests like p53 (Steels et al, 2001). This suggests the importance to that the detection of RAS alteration would also allow us to stratify determine the best method to assess each marker. There was also a patients with higher risk. It could also determine patients with a difference between RFLP- and SSCP-PCR, only the first one better chance to respond to specific treatment targeting RAS. showing statistically significant impact on survival of patient with To avoid bias due to a more detailed reporting of significant lung cancer. There were only three trials with SSCP-PCR and the trials, we decided to perform a methodological assessment of the results reached to be significant. There is thus need to confirm or publications prior to quantitative aggregation. We have used a infirm those results prospectively with an adequately designed and methodology similar to previous systematic reviews reported by powered trial. The PCR techniques used were thus different our group about biological prognostic factors in lung cancer between the trials and between the specific KRAS2 codon analysed. (Steels et al, 2001; Delmotte et al, 2002; Meert et al, 2002a, b; Whatever, in the other meta-analysis (Huncharek et al, 1999), Martin et al, 2003; Meert et al, 2003). The absence of a statistically pooling all trials with PCR with an heterogeneity detected significant difference in quality score between the significant and the according to different procedure and codon analysed, the results nonsignificant publications allowed us to perform a quantitative reached significance. For clinical application, the best method to aggregation (meta-analysis) of the results of the individual trials. assess KRAS2 still needs to be determined in further studies to However, this approach does not prevent all potential biases. Biases provide reproductible results and standardised evaluation. including publication bias, choice of language, selection of fully In conclusion, our systematic review suggests that RAS mutation published studies only, method of extrapolation of HR, validity of a or p21 expression is of poor prognostic significance for survival in meta-analyses based on systematic review of the literature as patients with non-small-cell lung cancer. The results were based on compared with those based on individual data were already an aggregation of data obtained by univariate analysis in retro- discussed in our previous papers (Steels et al, 2001; Delmotte et al, spective trials. In order to become a useful prognostic factor at the 2002; Meert et al, 2002a, b; Martin et al, 2003; Meert et al, 2003). level of individual patients and in the context of targeted therapy, & 2005 Cancer Research UK British Journal of Cancer (2005) 92(1), 131 – 139 Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al these results need to be confirmed by an adequately designed technique to assess RAS alteration as compared with IHC. It is a prospective study and the exact value of p21 expression needs to priority to confirm those data in order to determine the adequate be determined by an appropriate multivariate analysis taking into method to assess RAS, which would then further allow performing account the classical well-defined prognostic factors for lung prospective studies with adequate design and, particularly, adapted cancer. Moreover, molecular biology arises as a more accurate laboratory methods. 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Oncogene 8: Askin FB, Rodenhuis S, Hruban RH (1993) K-ras oncogene activation in 2407– 2412 lung adenocarcinomas from former smokers. Evidence that K-ras Rosell R, Molina F, Moreno I, Martinez E, Pifarre A, Font A, Li S, Skacel Z, mutations are an early and irreversible event in the development of Gomez-Codina J, Camps C (1995a) Mutated K-ras gene analysis in a adenocarcinoma of the lung. Cancer 72: 432–438 randomized trial of preoperative chemotherapy plus surgery vs surgery Yusuf S, Peto R, Lewis J, Collins R, Sleight P (1985) Blockade during and in stage IIIA non-small cell lung cancer. Lung Cancer 12(Suppl 1): after myocardial infarction: an overview of the randomized trials. Prog S59 –S70 Cardiovasc Dis 27: 335– 371 & 2005 Cancer Research UK British Journal of Cancer (2005) 92(1), 131 – 139 Molecular Diagnostics http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png British Journal of Cancer Springer Journals

The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis

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Springer Journals
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Copyright © 2005 by The Author(s)
Subject
Biomedicine; Biomedicine, general; Cancer Research; Epidemiology; Molecular Medicine; Oncology; Drug Resistance
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0007-0920
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1532-1827
DOI
10.1038/sj.bjc.6602258
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Abstract

British Journal of Cancer (2005) 92, 131 – 139 & 2005 Cancer Research UK All rights reserved 0007 – 0920/05 $30.00 www.bjcancer.com The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis ,1,7 1 1 2 1 3 4 5 C Mascaux , N Iannino , B Martin , M Paesmans , T Berghmans , M Dusart , A Haller , P Lothaire , 1,7 1 6 1 A-P Meert , S Noel , J-J Lafitte and J-P Sculier 1 2 Department of Intensive Care and Thoracic Oncology, Institut Jules Bordet, Centre des Tumeurs de l’Universite´ Libre de Bruxelles, Belgium; Data Centre, Institut Jules Bordet, Centre des Tumeurs de l’Universite´ Libre de Bruxelles, Belgium; Department of Nuclear Medicine, Institut Jules Bordet, Centre des ´ ´ Tumeurs de l’Universite Libre de Bruxelles, Belgium; Department of Pathology, Institut Jules Bordet, Centre des Tumeurs de l’Universite Libre de Bruxelles, 5 6 Belgium; Department of Surgery, Institut Jules Bordet, Centre des Tumeurs de l’Universite Libre de Bruxelles, Belgium; Chest Department, CHU Calmette, Lille, France; FNRS (Fonds National de la Recherche Scientifique), Belgium The proto-oncogene RAS, coding for a 21 kDa protein (p21), is mutated in 20% of lung cancer. However, the literature remains controversial on its prognostic significance for survival in lung cancer. We performed a systematic review of the literature with meta- analysis to assess its possible prognostic value on survival. Published studies on lung cancer assessing prognostic value of RAS mutation or p21 overexpression on survival were identified by an electronic search. After a methodological assessment, we estimated individual hazard ratios (HR) estimating RAS protein alteration or RAS mutation effect on survival and combined them using meta- analytic methods. In total, 53 studies were found eligible, with 10 concerning the same cohorts of patients. Among the 43 remaining studies, the revelation method was immunohistochemistry (IHC) in nine and polymerase chain reaction (PCR) in 34. Results in terms of survival were significantly pejorative, significantly favourable, not significant and not conclusive in 9, 1, 31, 2, respectively. In total, 29 studies were evaluable for meta-analysis but we aggregated only the 28 dealing with non-small-cell lung cancer (NSCLC) and not the only one dealing with small-cell-lung cancer (SCLC). The quality scores were not statistically significantly different between studies with or without significant results in terms of survival, allowing us to perform a quantitative aggregation. The combined HR was 1.35 (95% CI: 1.16–1.56), showing a worse survival for NSCLC with KRAS2 mutations or p21 overexpression and, particularly, in adenocarcinomas (ADC) (HR 1.59; 95% CI 1.26–2.02) and in studies using PCR (HR 1.40; 95% CI 1.18–1.65) but not in studies using IHC (HR 1.08; 95% CI 0.86–1.34). RAS appears to be a pejorative prognostic factor in terms of survival in NSCLC globally, in ADC and when it is studied by PCR. British Journal of Cancer (2005) 92, 131–139. doi:10.1038/sj.bjc.6602258 www.bjcancer.com Published online 14 December 2004 & 2005 Cancer Research UK Keywords: RAS; p21; lung cancer; meta-analysis; systematic review; survival; prognostic factor Lung cancer is a major cause of death despite diagnostic and reflecting proliferative state, have already been identified in therapeutic improvements. The overall 5-year survival rate is less patients with lung cancer (Kanters et al, 1995). In order to clarify than 10%. However, the prognosis can be modulated by the prognostic impact of other biological factors in lung cancer, characteristics related to the patient or to the tumour. Some our group has performed systematic reviews of the literature with independent prognostic factors for survival have already been meta-analyses. It allowed us to show that VEGF (Delmotte et al, identified. They include, for small-cell lung cancer (SCLC): disease 2002), microvessel density (Meert et al, 2002b), c-erbB-2 (Meert extent and performance status (PS) (Paesmans et al, 2000); for et al, 2003) and p53 (Steels et al, 2001) have statistically significant non-small cell lung cancer (NSCLC): PS, stage and, with lower worse impact on survival, while Bcl-2 (Martin et al, 2003) has a impact, age, sex and weight loss (Paesmans et al, 1995; Strauss, favourable survival impact. 1997). Oncogenes (RAS, Raf, Myc, Src, Abl/Bcr, c-erbB-2, y) are With the recent progresses in molecular biology, the research on derived from normal genes (the proto-oncogene) coding for prognostic factors could be extended to proteins and genes proteins, which play key roles in physiological cellular processes involved in cancer development. The biological factors implicated such as regulations of gene expression or growth signal transduc- in carcinogenesis should also be considered as potential survival tion. Particularly, RAS oncogene is involved in lung cancer prognostic factors. Some of them, like angiogenesis and factors development. Three human RAS genes (Rodenhuis and Slebos, 1990) have been identified: the HRAS gene (homologous to the oncogene of the Harvey rat sarcoma virus), the KRAS2 gene *Correspondence: Dr C Mascaux, Institut Jules Bordet, rue He´ger- (homologous to the oncogene of the Kirsten rat sarcoma virus) and Bordet, 1 B-1000 Brussels, Belgium; E-mail: celine.mascaux@bordet.be the NRAS gene (first isolated from a human neuroblastoma). Received 18 June 2004; revised 29 September 2004; accepted 18 These genes code for four highly homologous 21 kDa proteins October 2004; published online 14 December 2004 called p21, with a common effector domain within the N-terminal Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al region. To be biologically active, RAS proteins must be localised to (Steels et al, 2001). Each item was assessed using an ordinal scale the inner face of the plasma membrane, where they can effectively (possible values: 2, 1, 0). A consensus was reached in regular interact with their upstream activators and downstream targets. meetings where at least two-thirds of the investigators needed to be The RAS gene proteins can exist in two states: an active state, in present. As the assessed items were objective ones, a consensus which GTP is bound to the molecule and an inactive state, in which was always obtained. the GTP has been hydrolysed to GDP. In physiologic conditions, The overall score evaluated several dimensions of the metho- the active isoform initiates cell proliferation through the RAS- dology, grouped into four main categories: the scientific design, dependent kinase cascade. The RAS proteins possess intrinsic the description of laboratory methods used to identify the presence GTPase activity, which normally leads to their inactivation and the of RAS mutation or p21 expression, the generalisability of the control of cell growth. In tumours, a point mutation resulting in results and the analysis of the study data. Each category had a loss of the intrinsic GTPase activity appears to be associated with maximum score of 10 points, with a maximal theoretical score of transforming activity of the protein, which does not stop anymore 40 points. When an item was not applicable to a study, its value to send the signal stimulating cell proliferation. KRAS2 mutations was not taken into account in the total of the concerned category. are particularly common in pancreatic cancers, colorectal malig- The final scores were expressed as percentages, ranging from 0 to nancies and lung cancer (Rodenhuis, 1992; Minamoto et al, 2000). 100%, higher values reflecting better methodological quality. RAS mutations are detected in 15–20% of NSCLC and, Studies included in the systematic review were called ‘eligible’, particularly, 30–50% of adenocarcinomas (ADC) (Rodenhuis those providing sufficient data for the meta-analysis ‘evaluable’. To et al, 1988). In lung cancer, 90% of the mutations are located in be eligible, studies had to provide univariate analysis. the RAS2 gene and both NRAS mutations and HRAS mutations have occasionally been documented (Rodenhuis and Slebos, 1990). In total, 80% of KRAS2 mutations occur in codon 12. Other Statistical methods mutations are located in codons 13 and 61. The predominant mutation is a G–T transversion (70% of tumours) (Rodenhuis and A study was considered as significant if the P-value for the Slebos, 1990). statistical test comparing survival distributions between the groups The literature remains controversed on the prognostic value of with and without RAS-p21 alteration was o0.05. A study was RAS for survival in patients with lung cancer. In order to clarify called ‘positive’ when a mutation/expression in RAS-p21 proto- this question, we have performed a systematic review of the oncogene was identified as a significant favourable prognostic literature with methodological assessment and meta-analysis. factor for survival. The study was called ‘negative’ if the same characteristic was associated with a significant detrimental impact on survival. Finally, a study was called ‘not significant’ if no statistically significant difference between the two groups was MATERIALS AND METHODS detected and ‘not conclusive’ if any conclusion about significance Publications selection of survival results could be derived from the article. The association between two continuous variables was measured To be eligible for the systematic review, a study had to fulfil the by the Spearman rank correlation coefficient. Nonparametric tests following criteria: to deal only with lung cancer (any stage or were used to compare the distribution of the quality scores histology), to assess the correlation between RAS mutation or p21 according to the value of a discrete variable (Mann–Whitney tests expression and survival, to analyse RAS-p21 in the primary for dichotomic variables or Kruskal–Wallis tests for multiple tumour (not in metastatic tissue or tissue adjacent to the tumour) classes variables). and/or antibodies against p21 in the serum, to have been published For the quantitative aggregation of the survival results, we as a full paper in the English or French language. Abstracts were measured the impact of RAS mutation and/or p21 expression on excluded because they do not provide sufficient data to evaluate survival by hazard ratio (HR) between the two survival distribu- the methodological quality of the trial and/or to perform meta- tions. For each trial, this HR was estimated by a method depending analysis. on the data provided in the publication. The most accurate method Studies were identified by an electronic search on Medline consisted of calculating the estimated HR and its standard error databank and using the following keywords: ‘lung cancer’, ‘lung (s.e.) from the reported results or to calculate them directly using carcinoma’, ‘lung neoplasms’, ‘lung tumour’, ‘lung tumours’, ‘lung two of the following parameters: the O-E statistic (difference tumour’, ‘lung tumours’, ‘lung adenocarcinoma’, ‘lung squamous’, between numbers of observed and expected events), the confidence ‘NSCLC’, ‘non-small cell lung cancer’, ‘non small cell lung cancer’, interval (CI) for the HR, the logrank statistic or its P-value. If these ‘non-small cell lung carcinoma’, ‘non small cell lung carcinoma’, were not available, the total number of events, the number of ‘SCLC’, ‘small cell lung cancer’, ‘small cell lung carcinoma’, ‘ras’, patients at risk in each group and the logrank statistic or its P- ‘K-ras’, ‘Ki-ras’, ‘n-ras’, ‘c-ras’, ‘l-ras’, ‘h-ras’, ‘p21’. The search value were used to allow for an approximation of the HR estimate. ended on July 2003. The bibliographies reported in all the Finally, if the only exploitable data were in form of graphical identified studies were used to complete this search. When the representations of the survival distributions, survival rates at some authors reported results obviously obtained on the same patients specified times were extracted in order to reconstruct the HR population in several publications, only the most recent or the estimate and its variance, with the assumption that the rate of most complete study was included in the analysis, in order to avoid patients censored was constant during the study follow-up overlapping between cohorts. (Parmar et al, 1998). If this last method was used, three independent persons read the curves to reduce inaccuracy in the extracted survival rates. The individual HR estimates were Methodological assessment combined into an overall HR using Peto’s method (Yusuf et al, To assess the quality of the methodology, each study was read 1985), which consisted of using a fixed effect model assuming independently by 12 investigators, including nine physicians and homogeneity of the individual true HRs. This assumption was three scientists. The participation of many readers was a guarantee tested by performing w tests for heterogeneity. If the assumption for the correct interpretation of the articles. The methodological of homogeneity had to be rejected, we used a random-effect model evaluation was scored according to the European Lung Cancer as a second analysis. By convention, an observed HRo1 implied a Working Party (ELCWP) scale. The scoring system used has better survival for the group with mutated RAS or p21 expression. already been described in one of our prior systematic reviews This impact of RAS on survival was considered as statistically British Journal of Cancer (2005) 92(1), 131 – 139 & 2005 Cancer Research UK Meta-analysis: K-RAS in lung cancer C Mascaux et al significant if the 95% confidence interval for the overall HR did not and the lack of repartition of tumours according to RAS mutation/ overlap 1. expression in 1 (Ahrendt et al, 2002). When data about global survival of the entire patients population were available, survival was analysed globally. If Study results report authors only reported the results separately for different sub- groups, those results corresponded to different cohorts of patients Nine of the 43 studies (20.9%) identified proto-oncogene RAS and were treated separately in the meta-analysis. mutations or p21 overexpression as a pejorative prognostic factor for survival (with seven evaluable for the meta-analysis), 31 (72.1%) concluded that RAS was not a prognostic factor for survival (21 evaluable), one (2.3%) reported a better prognosis for RESULTS RAS positivity (evaluable) and two (4.7%) were nonconclusive (both nonevaluable). Study selection and characteristics Overall, the rates of RAS mutations detected by PCR and p21 In total, 53 publications, published between 1990 and 2003, were protein overexpression were, respectively, 18.4% (number of found eligible for the systematic review (Rodenhuis et al, 1988, evaluable tumours (n)¼ 3779) and 44.6% (n¼ 1548) in NSCLC, 1997; Slebos et al, 1990; Mitsudomi et al, 1991; Miyamoto et al, 7.1% (n¼ 141) and 32.3% (n¼ 223) in squamous cell carcinomas 1991; Harada et al, 1992; Sugio et al, 1992; Rosell et al, 1993, 1995b, (SQCC) and 23.1% (n¼ 1847) and 34.7% (n¼ 222) in ADC. The 1996, 1997; Volm et al, 1993, 2002; Westra et al, 1993; Kern et al, rates of positive tumours by molecular biology or IHC were, 1994; Li et al, 1994; Silini et al, 1994; Fujino et al, 1995; Kashii et al, respectively, 21.8% (n¼ 1015) and 54.8% (n¼ 135) in stage I 1995; Keohavong et al, 1996, 1997; Cho et al, 1997; Dosaka-Akita NSCLC, 16.0% (n¼ 399) and 53.5% (n¼ 71) in NSCLC patients et al, 1997; Fukuyama et al, 1997; Komiya et al, 1997; Pifarre´ et al, with stages I and II, 16.2% (n¼ 1263) and 38.5% (n¼ 929) in those 1997; Siegfried et al, 1997; Visscher et al, 1997; De Gregorio et al, with stages I–III. 1998; Greatens et al, 1998; Huang et al, 1998; Kim et al, 1998; Kwiatkowski et al, 1998; Nemunaitis et al, 1998; Wang et al, 1998; Dingemans et al, 1999; Fu et al, 1999; Graziano et al, 1999; Miyake Quality assessment et al, 1999; Nelson et al, 1999; Hommura et al, 2000; Konishi et al, The overall quality score ranged from 31.04 to 78.15% with a 2000; Moldvay et al, 2000; Schneider et al, 2000; Andjelic et al, median of 52.2% (Table 2A). The design subscore had the lowest 2001; Kang et al, 2001; Schiller et al, 2001; Ahrendt et al, 2002; value, with a median of 40%. Broermann et al, 2002; Shoji et al, 2002; Tomizawa et al, 2002; No statistically significant quality difference was shown between Grossi et al, 2003; Ramirez et al, 2003). In all, 10 of these articles significant and nonsignificant studies neither for the global score were excluded because an identical patient cohort had been used in (median: 51.50 vs 53.83%, P¼ 0.90), neither for the four subgroups other selected publications (Rodenhuis et al, 1988; Miyamoto et al, scores. There was also no statistically significant difference 1991; Fujino et al, 1995; Rosell et al, 1995a, b, 1996; Dosaka et al, between evaluable and nonevaluable studies for meta-analysis in 1997; Keohavong et al, 1997; Hommura et al, 2000; Konishi et al, terms of global scores (55.23 vs 44.31%, P¼ 0.10), but the evaluable 2000; Volm et al, 2002). One of the 43 remaining studies (Volm ones had a better score concerning the report of the analysis et al, 1993) assessed separately by immunohistochemistry (IHC) results: 62.5% in comparison to 31.3% for the nonevaluable trials KRAS2, NRAS and HRAS p21. All the other papers concerned (P¼ 0.001). There was a significant correlation between the global KRAS2 only. Therefore, for the meta-analysis, we took into score and the number of patients included (Spearman correlation account only the characteristics and the data concerning KRAS2 coefficient r¼ 0.50, P¼ 0.0006), studies including a higher number p21 expression. of patients showing a better global score. The generalisability of The total number of included patients was 5216, ranging from 21 the results was significantly better in the recent publications to 355 patients per study (median: 103). The main characteristics (r¼ 0.42, P¼ 0.004). There was also a statistically significant of the 43 publications eligible for the systematic review are difference between studies assessing RAS-p21 status by IHC reported in Table 1. In total, 27 were dealing with NSCLC, 11 with (n¼ 9) or by molecular biology (n¼ 34), with global scores of adenocarcinoma only, three with any histological type, one with 58.51 and 49.93%, respectively (P¼ 0.029) and scores assessing the SCLC and one with both ADC and large cell carcinoma. A total of description of the laboratory methodology of 64.3 vs 46%, those 22 studies concerned only nonmetastatic disease, one only stage IV based on IHC being better described than those on molecular disease and 19 all stages (I–IV). One study did not mention the biology (P¼ 0.002). stage of the tumours. In 15 publications, patients were treated by Table 2B reports the analysis of the scores for the 29 studies surgery alone. Surgery was associated with an adjuvant therapy evaluable for meta-analysis. Their overall quality score ranged (radiotherapy and/or chemotherapy) in 26. In one study, SCLC between 34.25 and 78.15%, with a median of 55.24%. The design patients were treated with a combination of radiotherapy and subscore was also the worst reported. Like previously observed chemotherapy (Dingemans et al, 1999). In the last paper, treatment among eligible publications, there was no statistically significant was not described De Gregorio et al, 1998). difference between significant and nonsignificant studies evaluable Nine studies evaluated the accumulation of p21 protein by for the meta-analysis according to the global score (median of IHC. The other 34 identified RAS mutation by molecular biology, 53.04 vs 53.42%, P¼ 0.92). There was also a significant correlation using different polymerase chain reaction (PCR) methodologies, between global score and the number of patients included in the mainly, single-strand conformation polymorphism (SSCP) study (Spearman correlation coefficient r¼ 0.53, P¼ 0.006) and (n¼ 10) and restriction fragment length polymorphism (RFLP) those assessing RAS positivity by IHC obtained a better quality (n¼ 8). scores for the laboratory method subgroup (57.1 vs 50% for Among the 43 studies eligible for the systematic review, 14 were molecular biology, P¼ 0.04), but not for the global score. inevaluable for the meta-analysis due to insufficient data reported in the article. The reasons for noninclusion of a study into the meta-analysis were the lack of available survival results to calculate Meta-analysis HR in 13 (Volm et al, 1993; Westra et al, 1993; Li et al, 1994; Kashii et al, 1995; Pifarre et al, 1997; Visscher et al, 1997; De Gregorio The absence of significant methodological quality difference et al, 1998; Greatens et al, 1998; Fu et al, 1999; Miyake et al, 1999; between significant and nonsignificant studies allowed us to Schneider et al, 2000; Andjelic et al, 2001; Broermann et al, 2002) perform a quantitative aggregation of the survival results. The & 2005 Cancer Research UK British Journal of Cancer (2005) 92(1), 131 – 139 Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al Table 1 Main characteristics and results of the eligible studies First author Year Histology Stage N pts Laboratory method HR estimation Survival results Ahrendt 2002 NSCLC I – IIIA 60 PCR-seq No data NC Andjelic 2001 NSCLC IIIA 21 PCR-SSCP No data Negative Broermann 2002 NSCLC III 28 PCR-RFLP No data NS Cho 1997 NSCLC I – IIIB 58 PCR-SSCP Survival curves Negative De Gregorio 1998 ADC I – IV 184 PCR No data NS Dingemans 1999 SCLC ANY 93 IHC Survival curves NS Fu 1999 NSCLC I – IIIB 158 IHC No data NS Fukuyama 1997 NSCLC I – IV 159 PCR-RFLP Survival curves Negative Graziano 1999 NSCLC I – II 213 PCR Log rank NS Greatens 1998 NSCLC I – IV 101 PCR-SSCP No data NS Grossi 2003 NSCLC I – IIIA 249 PCR HR NS Harada 1992 NSCLC I – IV 94 IHC Survival curves Negative Huang 1998 NSCLC I – IIIB 144 PCR-SSCP Survival curves Negative Kang 2001 NSCLC I – IIIB 61 IHC HR NS Kashii 1995 ALL I – IV 97 PCR-SSCP No data NS Keohavong 1996 NSCLC I – IV 126 PCR-DGGE Log rank NS Kern 1994 ADC I – IV 44 PCR-ASO HR NS Kim 1998 NSCLC I – IV 238 IHC HR NS Komiya 1997 NSCLC I – IIIA 137 IHC Survival curves NS Kwiatkowski 1998 NSCLC I 244 PCR-RFLP Log rank NS Li 1994 ADC I – ? 41 PCR-dot blot No data NS Mitsudomi 1991 ALL I – IV 66 PCR-RFLP Log rank NS Miyake 1999 NSCLC I – IIIB 187 PCR-SSCP No data Negative Moldvay 2000 NSCLC I – IV 227 IHC Log rank NS Nelson 1999 NSCLC I – IV 355 PCR-RFLP Survival curves Negative Nemunaitis 1998 ADC+LC I – IV 103 PCR-RFLP Survival curves NS Pifarre 1997 NSCLC I – IIIA 64 PCR-SSCP No data NC Ramirez 2003 NSCLC I – IV 50 PCR Survival curves NS Rodenhuis 1997 ADC III – IV 62 EPCR Log rank NS Rosell 1997 NSCLC I 35 PCR-SSCP Log rank NS Rosell 1993 NSCLC I – IIIA 66 PCR-RFLP Log rank Negative Schiller 2001 NSCLC II – IIIA 184 PCR-RFLP HR NS Schneider 2000 NSCLC I – IIIA 103 PCR-SSCP No data NS Shoji 2002 NSCLC I – IIIA 233 IHC Survival curves Positive Siegfried 1997 ADC I – IV 181 PCR-DGGE Survival curves NS Silini 1994 ADC I – IV 109 PCR-DGGE Survival curves NS Slebos 1990 ADC I – IIIA 69 PCR-ASO Log rank Negative Sugio 1992 ADC I – IV 115 PCR-dot blot Survival curves NS Tomizawa 2002 ADC I 110 PCR-seq Log rank NS Visscher 1997 ADC I – IV 31 PCR-SSCP No data NS Volm (KRAS2) 1993 NSCLC I – III 206 IHC No data NS Wang 1998 ALL I – IV 53 PCR-seq HR NS Westra 1993 ADC I – III 57 PCR-ASO No data NS N pts¼ number of patients; HR¼ hazard ratio; NSCLC¼ non-small-cell lung cancer; ADC¼ adenocarcinoma; SCLC¼ small-cell lung carcinoma; LC¼ large cell; NC¼ nonconclusive; NS¼ nonsignificative; PCR¼ polymerase chain reaction; SSCP¼ single-strand conformation polymorphism; RFLP¼ restriction fragment length polymorphism; ASO¼ allele-specific oligonucleotide hybridisation; DGGE¼ denaturating gradient gel electrophoresis; seq¼ PCR followed by sequencing of olignucleotide; EPCR¼ mutant-enriched PCR; IHC¼ immunohistochemistry; HR estimation¼ description of the methods used to estimate the individual HR according the three corresponding of the three different methods described in the statistics paragraph. meta-analysis was performed on 28 studies (3620 patients) dealing intervals (CI) 1.20–1.49). The test of heterogeneity was significant with NSCLC. (P¼ 0.01). Nevertheless, we calculated the HR by a random effect The individual HR of the 28 aggregable studies were calculated model that showed also a statistically significant impact on by one of the three methods reported in the Materials and Methods survival with an HR of 1.35 (95% CI: 1.16–1.56). section according to the available data. Only six studies reported In the subgroup analysis (Table 3) according to histology, RAS/ the data needed to directly calculate the estimated HR (HRs and p21 was not a statistically significant prognostic factor for survival 95% confidence intervals). In 10 trials, HR was approximated by in SQCC (H: 1.49, CI 95%: 0.88–2.52), but well in ADC, with the total number of events and the logrank statistic. For the 12 heterogeneity between the trials (heterogeneity test: P¼ 0.02) and a remaining studies, HR had to be extrapolated from the graphical random effect HR of 1.59 (CI 95%: 1.26–2.02). The meta-analysis representation of the survival distributions. of studies into three subgroups according to stages (stage I, stage The NSCLC overall meta-analysis included the 28 aggregable I–III and stage I–IV) did not show any statistically significant studies with a total number of 3620 patients. Two trials (Fukuyama impact of RAS on survival. For the last subgroup (stage I–IV) et al, 1997; Moldvay et al, 2000) gave only subgroup survival there were 11 studies with a large heterogeneity (Po0.001) and the analysis and their data were analysed separately like reported by random effect HR was borderline (1.41, 95% CI: 0.99–1.99). authors, increasing the number of individual cohorts aggregated to Furthermore, we aggregated the studies separately according to 30. The aggregation of the survival data is described in Table 3. the method used to detect RAS/p21 alteration (Table 3). The Overall RAS mutation or p21 expression was associated with a studies were first divided into two main groups according to the worse survival (HR (fixed effect model) 1.30; 95% confidence laboratory method: IHC (Figure 1) or molecular biology (Figure 2), British Journal of Cancer (2005) 92(1), 131 – 139 & 2005 Cancer Research UK Meta-analysis: K-RAS in lung cancer C Mascaux et al Table 2 Results of the methodological assessment of (a) eligible studies by the European Lung Cancer Working Party score and (b) evaluable studies by the European Lung Cancer Working Party score Global score (%) Design (%) Laboratory methodology (%) Generalisability (%) Results analysis (%) (a) All studies (N¼ 43) 52.2 40 50 67 50 Date of publication r Spearman 0.28 0.18 0.26 0.42 0.07 P-value 0.07 0.23 0.09 0.004 0.65 Patient number r Spearman 0.50 0.47 0.14 0.19 0.47 P-value 0.0006 0.001 0.36 0.22 0.002 Significant (n¼ 10) 51.50 40 46 62.5 62.5 Nonsignificant (n¼ 31) 53.83 40 50 66.7 50 P-value 0.9 0.93 0.35 0.39 0.41 Evaluable (n¼ 29) 55.23 40 50 66.7 62.5 Nonevaluable (n¼ 14) 44.31 45 46 62.5 31.3 P-value 0.10 0.67 0.66 0.8 0.001 Method of revelation IHC (n¼ 9) 58.51 50 64.3 66.7 62.5 Molecular biology (n¼ 34) 49.93 40 46 62.5 50 P-value 0.029 0.53 0.002 0.1 0.22 PCR subgroups SSCP (n¼ 10) 48.69 45 42 66.7 50 RFLP (n¼ 8) 52.56 50 46 62.5 75 P-value 0.33 0.39 0.71 0.86 0.16 Calculation of HR HR (n¼ 6) 62.35 50 50 71 75 Log rank (n¼ 10) 52.96 40 46.4 70.8 62.5 Survival curve (n¼ 13) 45.92 40 50 66.7 50 No data (n¼ 14) 44.31 45 46 62.5 31.3 P-value 0.10 0.62 0.62 0.52 0.001 (b) Evaluable studies (n¼ 29) 55.24 40 50 66.7 62.5 Date of publication r Spearman 0.36 0.27 0.25 0.44 0.12 P-value 0.05 0.17 0.19 0.02 0.54 Number of patient r spearman 0.52 0.69 0.05 0.34 0.34 P-value 0.004 0.00003 0.80 0.07 0.07 Significant (n¼ 8) 53.33 40 46 62.5 62.5 Nonsignificant (n¼ 21) 55.42 40 50 66.7 62.5 P-value 0.92 0.82 0.41 0.44 0.65 Method of revelation IHC (n¼ 7) 57.59 50 57 66.7 62.5 Molecular biology (n¼ 22) 51.46 40 50 62.5 62.5 P-value 0.24 0.52 0.04 0.19 0.69 PCR subgroups SSCP (n¼ 3) 53.83 40 42 75 50 RFLP (n¼ 7) 52.08 50 42 58.3 75 P-value 0.73 0.42 0.82 0.73 0.36 Calculation of HR HR (n¼ 6) 62.35 50 50 70.8 75 Log rank (n¼ 10) 52.96 40 46.4 70.8 62.5 Survival curves (n¼ 13) 45.92 40 50 66.7 50 P-value 0.18 0.47 0.43 0.30 0.037 r Spearman¼ correlation coefficient of Spearman; IHC¼ immunohistochemistry; PCR¼ polymerase chain reaction; SSCP¼ single-strand conformation polymorphism; RFLP¼ restriction fragment length polymorphism; HR¼ hazard ratio. The P-values are in bold when the statistical test is significant. & 2005 Cancer Research UK British Journal of Cancer (2005) 92(1), 131 – 139 Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al Table 3 Hazard ratio (HR) value for the NSCLC subgroup according to histology, stage and laboratory technique Nb Patients Fixed effects HR (95% CI) v Heterogeneity test Random effects HR (95% CI) Overall 28 3620 1.30 (1.20 – 1.49) P¼ 0.01 1.35 (1.16–1.56) Histology Squamous 4 280 1.49 (0.88 – 2.52) P¼ 0.48 ADC 15 1436 1.52 (1.30 – 1.78) P¼ 0.02 1.59 (1.26–2.02) Disease stage Stages I 5 562 1.26 (0.94 – 1.69) P¼ 0.43 Stages I – III 7 882 1.20 (0.93 – 1.53) P¼ 0.42 Stages I – IV 11 1553 1.25 (1.04 – 1.50) Po0.001 1.41 (0.99 – 1.99) Laboratory method IHC 7 989 1.08 (0.86 – 1.34) P¼ 0.21 PCR 23 2631 1.39 (1.22 – 1.58) P¼ 0.03 1.40 (1.18–1.65) PCR subgroups RFLP 6 765 1.70 (1.31–2.19) P¼ 0.53 SSCP 3 361 1.32 (0.72 – 1.47) P¼ 0.06 ADC IHC 4 266 1.57 (1.13 – 2.16) P¼ 0.01 1.48 (0.76 – 2.87) PCR 11 1170 1.50 (1.26–1.80) P¼ 0.1 Nb¼ number of studies; ADC¼ adenocarcinomas; IHC¼ immunohistochemistry; PCR¼ polymerase chain reaction; SSCP¼ single-strand conformation polymorphism; RFLP¼ restriction fragment length polymorphism; statistically significant results are in bold. Harada,1992 Cho,1997 Kang, 2001 Fukyama stages l−ll,1997 Fukyama stages lll−lV,1997 Kim,1998 Graziano,1999 Komiya,1997 Grossi, 2003 Moldvay squamous, 2000 Huang,1998 Moldvay adeno, 2000 Keohavong,1996 Shoji, 2002 Kern,1994 Kwiatkowski,1998 Mitsdudomi,1991 0.0 2.5 5.0 7.5 10.0 Nelson,1999 Figure 1 Meta-analysis of studies assessing RAS with IHC in NSCLC. Nemunaitis,1998 Hazard ratio (HR) and 95% confidence interval (CI) of survival in studies Ramirez, 2003 evaluating RAS-p21 status in NSCLC. HR41 implies a survival disadvan- Rodenhuis,1997 tage for the group with p21 expression. The square size is proportional to the number of patients included in the study. The center of the lozenge Rosell,1993 gives the combined HR of the meta-analysis and its extremities the 95% Rosell,1997 confidence interval. HR¼ 1.08; CI 95% 0.86–1.34. Total number of Schiller, 2001 patients: 989. Siegfried,1997 Silini,1994 Slebos,1990 including the different techniques of PCR. The fixed effect HR were Sugio,1992 respectively 1.08 (95% CI: 0.86–1.34) and 1.39 (95% CI: 1.22–1.58) for IHC and molecular biology. For PCR, there was a statistically Tomizawa,2002 significant heterogeneity (P¼ 0.03) and the random effect HR was Wang,1998 1.40 (95% CI: 1.18–1.65). Among the studies with PCR based revelation technique, two methods, PCR-RFLP and PCR-SSCP, were used in respectively six and three studies. Fixed effect HR of 0.0 2.5 5.0 7.5 10.0 1.7 (95% CI: 1.31–2.19) and 1.32 (95% CI: 0.72–1.47) were Figure 2 Meta-analysis of studies assessing RAS mutation with PCR in obtained, respectively, the first one only being statistically NSCLC. Hazard ratio (HR) and 95% confidence interval (CI) of survival in significant. studies evaluating RAS-p21 status in NSCLC. HR41 implies a survival Finally, we decided to perform an analysis in histological disadvantage for the group with RAS mutation. The square size is subgroups separately according to the method of detection. There proportional to the number of patients included in the study. The centre of were only four studies dealing with SQCC and it was a nonsense to the lozenge gives the combined HR of the meta-analysis and its extremities the 95% confidence interval. HR¼ 1.40; CI 95% 1.18 –1.65. Total number make more reduced subgroups analysis. We were able to analyse of patients: 2631. studies including ADC separating those using IHC from those applying PCR. Four studies were using IHC only. The HR (random-effects model, p heterogeneity test¼ 0.01) was 1.48 value of RAS alterations is observed in ADC but not for SQCC and (95% CI 0.76–2.87). The HR (fixed-effects model, p heterogeneity when PCR is used as revelation method but not when IHC is used. test¼ 0.1) for 11 studies assessing RAS mutation by PCR in ADC Our data help so to clarify the message of individual studies, was 1.50 (95% CI 1.26–1.80) (Figure 3). arguing with the hypothesis that RAS is a prognostic factor for lung cancer. This still needs to be confirmed in prospective trials with appropriate multivariate analysis taking into account other clinical or biological prognostic factors. Another meta-analysis DISCUSSION based on a review of the literature on the role of KRAS2 as The present systematic review of the literature with meta-analysis prognostic factor in lung cancer was previously published shows that RAS gene alteration and/or protein p21 overexpression (Huncharek et al, 1999). Only eight trials (Slebos et al, 1990; Kern is a poor prognostic factor for survival of patients with NSCLC in et al, 1994; Silini et al, 1994; Rosell et al, 1995a; Cho et al, 1997; univariate analysis. In subgroup analysis, the negative prognostic Fukuyama et al, 1997; Rodenhuis et al, 1997; Siegfried et al, 1997) British Journal of Cancer (2005) 92(1), 131 – 139 & 2005 Cancer Research UK Meta-analysis: K-RAS in lung cancer C Mascaux et al Some eligible trials had to be excluded from the meta-analysis Fukuyama,1999 because they did not provide sufficient data on survival. Among Huang,1998 the 14 excluded studies, 12 were nonsignificant (86%) while a lower proportion of the studies evaluable for the meta-analysis Kern,1994 were nonsignificant (70%). It is known that negative studies are Nelson,1999 less frequently published or, if they are, with less detailed results, Nemunaitis,1998 making them less assessable. However, the methodological quality of trials, according to the global score, was not significantly Rodenhuis,1997 different between evaluable and nonevaluable studies for the Siegfried,1997 quantitative aggregation of individual survival results. Silini,1994 Some results need comments: we only demonstrated significant impact of RAS alterations in ADC and not in SQCC. This Slebos,1990 observation suggests that the biological signalling pathways Sugio,1992 implicated in carcinogenesis are different for ADC and for SQCC. Tomizawa, 2002 Those information should interpreted carefully because RAS mutations are more frequently observed in ADC as compared with SQCC (23.12 vs 7.09%) Moreover, authors more often assessed ADC rather than SQCC (1436 vs 280 patients in the 0.0 2.5 5.0 7.5 10.0 meta-analysis). For example, Nelson’s trial (Nelson et al, 1999), Figure 3 Meta-analysis of studies assessing RAS mutation by PCR in firstly based on all histological subtypes, did not detect any adenocarcinomas. Hazard ratio (HR) and 95% confidence interval (CI) of mutation in squamous cell carcinoma and thus did not report data survival in studies evaluating RAS-p21 status in NSCLC. HR41 implies a on this histological subtype. Another example arises in Moldvay‘s survival disadvantage for the group with RAS mutation. The square size is study (Moldvay et al, 2000): she assessed overexpression of p21 by proportional to the number of patients included in the study. The centre of IHC in all tumours but only evaluate RAS mutation by PCR in the lozenge gives the combined HR of the meta-analysis and its extremities ADC and not in SQCC. There is a potential bias to evalue the the 95% confidence interval. HR¼ 1.50; CI 95% 1.26–1.80. Total number impact of RAS in squamous cell carcinomas and this should be of patients: 1170. further investigated. The diversity in the techniques used to identify alteration of were included because the selection criteria of the studies were RAS-p21 status can also be a potential source of bias. Firstly, IHC different from ours: the search for studies ended in 1997, only is not comparable among the nine studies. There were six different trials documenting KRAS2 mutation by PCR (and not those with primary antibodies, different revelation protocols and different IHC) were included, other histologies than NSCLC were excluded, level of positivity (from 0 to 50% or only based on intensity). 2-year survival rates had to be described. The authors observed Secondly, there is not a good correlation between DNA mutation that KRAS2 mutations detected by different PCR variants were and protein conformation or level of protein expression and thus poor prognostic factor for NSCLC. These results support the between molecular biology and IHC. Authors (Nelson et al, 1999; validity of ours. No subgroup analyses according to stage or Moldvay et al, 2000) who studied RAS mutation and p21 histology (ADC vs SQCC) were performed, not allowing us to expression on the same tumours did not find any correlation compare with our results. between the two abnormalities. Particularly, Nelson (Nelson et al, RAS gene mutations are involved in oncogenesis of a variety of 1999) did not observe significant impact of p21 expression in human tumours (Rodenhuis and Slebos, 1990). In lung cancer, multivariate analysis (P¼ 0.89), but well for RAS mutation Fisher et al (2001) has demonstrated that RAS mutation is (P¼ 0.04). Moldvay (Moldvay et al, 2000) only found three necessary for induction and maintenance of lung cancer. The same patients among 81 analysed with both RAS IHC staining and KRAS2 point mutation. It could bring some potential explanations author showed that lung tumours arising in the absence of tumour suppressor gene remain dependent on mutant KRAS2 for to the difference between IHC and PCR in our meta-analysis. PCR maintenance of tumour growth and that apoptosis after KRAS2 seems to be a more accurate technique to assess RAS in lung downregulation does not require p53 or Ink4A/Arf. Those points tumours. It is interesting to observe that we previously had never suggest that RAS plays a key role in lung carcinogenesis. Moreover, showed differences between the two techniques for other markers the present demonstration of its prognostic role in lung suggests like p53 (Steels et al, 2001). This suggests the importance to that the detection of RAS alteration would also allow us to stratify determine the best method to assess each marker. There was also a patients with higher risk. It could also determine patients with a difference between RFLP- and SSCP-PCR, only the first one better chance to respond to specific treatment targeting RAS. showing statistically significant impact on survival of patient with To avoid bias due to a more detailed reporting of significant lung cancer. There were only three trials with SSCP-PCR and the trials, we decided to perform a methodological assessment of the results reached to be significant. There is thus need to confirm or publications prior to quantitative aggregation. We have used a infirm those results prospectively with an adequately designed and methodology similar to previous systematic reviews reported by powered trial. The PCR techniques used were thus different our group about biological prognostic factors in lung cancer between the trials and between the specific KRAS2 codon analysed. (Steels et al, 2001; Delmotte et al, 2002; Meert et al, 2002a, b; Whatever, in the other meta-analysis (Huncharek et al, 1999), Martin et al, 2003; Meert et al, 2003). The absence of a statistically pooling all trials with PCR with an heterogeneity detected significant difference in quality score between the significant and the according to different procedure and codon analysed, the results nonsignificant publications allowed us to perform a quantitative reached significance. For clinical application, the best method to aggregation (meta-analysis) of the results of the individual trials. assess KRAS2 still needs to be determined in further studies to However, this approach does not prevent all potential biases. Biases provide reproductible results and standardised evaluation. including publication bias, choice of language, selection of fully In conclusion, our systematic review suggests that RAS mutation published studies only, method of extrapolation of HR, validity of a or p21 expression is of poor prognostic significance for survival in meta-analyses based on systematic review of the literature as patients with non-small-cell lung cancer. The results were based on compared with those based on individual data were already an aggregation of data obtained by univariate analysis in retro- discussed in our previous papers (Steels et al, 2001; Delmotte et al, spective trials. In order to become a useful prognostic factor at the 2002; Meert et al, 2002a, b; Martin et al, 2003; Meert et al, 2003). level of individual patients and in the context of targeted therapy, & 2005 Cancer Research UK British Journal of Cancer (2005) 92(1), 131 – 139 Molecular Diagnostics Molecular Diagnostics Meta-analysis: K-RAS in lung cancer C Mascaux et al these results need to be confirmed by an adequately designed technique to assess RAS alteration as compared with IHC. It is a prospective study and the exact value of p21 expression needs to priority to confirm those data in order to determine the adequate be determined by an appropriate multivariate analysis taking into method to assess RAS, which would then further allow performing account the classical well-defined prognostic factors for lung prospective studies with adequate design and, particularly, adapted cancer. Moreover, molecular biology arises as a more accurate laboratory methods. 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Published: Dec 14, 2004

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