Open Access

A rational two-step approach to KRAS mutation testing in colorectal cancer using high resolution melting analysis and pyrosequencing

  • Elisabeth Mack1,
  • Kathleen Stabla1,
  • Jorge Riera-Knorrenschild1,
  • Roland Moll2,
  • Andreas Neubauer1 and
  • Cornelia Brendel1Email author
BMC Cancer201616:585

https://doi.org/10.1186/s12885-016-2589-2

Received: 7 July 2016

Accepted: 20 July 2016

Published: 2 August 2016

Abstract

Background

KRAS mutation testing is mandatory in the management of metastatic colorectal cancer prior to treatment with anti-EGFR antibodies as patients whose tumors express mutant KRAS do not benefit from these agents. Although the U.S. Food and Drug Administration has recently approved two in-vitro diagnostics kits for determination of KRAS status, there is generally no consensus on the preferred method and new tests are continuously being developed. Most of these techniques focus on the hotspot mutations at codons 12 and 13 of the KRAS gene.

Methods

We describe a two-step approach to KRAS codon 12/13 mutation testing involving high resolution melting analysis (HRM) followed by pyrosequencing using the Therascreen KRAS Pyro kit (Qiagen) of only those samples that are not clearly identified as KRAS wildtype or mutant by HRM. First, we determined KRAS status in a panel of 61 colorectal cancer samples using both methods to compare technical performance and concordance of results. Subsequently, we evaluated practicability and costs of our concept in an independent set of 120 colorectal cancer samples in a routine diagnostic setting.

Results

HRM and pyrosequencing appeared to be equally sensitive, allowing for clear detection of mutant alleles at a mutant allele frequency ≥12.5 %. Pyrosequencing yielded more exploitable results due to lower input requirements and a lower rate of analysis failures. KRAS codon 12/13 status was called concordantly for 98.2 % (56/57) of all samples that could be successfully analysed by both methods and 100 % (19/19) of samples that were identified mutant by HRM. Reviewing the actual effort and expenses for KRAS mutation testing in our laboratory revealed, that the selective use of pyrosequencing for only those samples that could not be analysed by HRM increased the fraction of valid results from 87.5 % for HRM alone to 99.2 % (119/120) while allowing for a net reduction of operational costs of >75 % compared to pyrosequencing alone.

Conclusions

Combination of HRM and pyrosequencing in a two-step diagnostic procedure constitutes a reliable and economic analysis platform for KRAS mutation testing in colorectal cancer in a clinical setting.

Keywords

KRAS mutation Colorectal cancer High resolution melting analysis Pyrosequencing

Background

The anti EGFR-antibodies cetuximab and panitumumab represent well-established treatments for metastatic colorectal cancer (CRC), the third most prevalent cancer entity and fourth most common cause of cancer-related death around the world [1, 2]. Several studies have shown KRAS status to predict outcome under these anti-EGFR targeting agents, with beneficial effects being seen only in patients whose tumors express wildtype (WT) KRAS [38]. Thus, testing for KRAS mutations, which are found in approximately 40 % of colorectal cancers, has become routine in the management of metastatic CRC (mCRC) prior to cetuximab or panitumumab treatment [9, 10] and is even required by the responsible regulatory agencies. Notably, current standards regarding oncogenic Ras mutation analysis in mCRC issued by the U.S Food and Drug Administration (FDA) require determination of KRAS status by an FDA-approved test, while the European Medical Agency (EMA) just states application of validated methods by an experienced laboratory [1115]. Currently available FDA-approved companion diagnostic devices for cetuximab (Erbitux) and panitumumab (Vectibix) comprise the Cobas KRAS Mutation Test (Roche) and Therascreen KRAS RGQ PCR Kit (Qiagen) [16]. Besides these and other commercially available kits, the spectrum of methods for KRAS mutation testing encompasses multiple PCR-derived and sequencing-based techniques. Of note, most of the previously established assays for KRAS mutation detection focus on the hotspot mutations involving codons 12 and 13, which account for >95 % of Ras mutations in CRC [10]. The advantages and limitations of selected methods have been repeatedly evaluated comparatively [1722], however, beyond the FDA-guideline, there is no consensus on the preferred approach to investigate KRAS status in routine molecular pathological diagnostics [23]. Given the high incidence of CRC resulting in high demand for KRAS mutation testing, an ideal diagnostic assay for this purpose not only needs to be sufficiently sensitive and specific, but, for socio-economic reasons, also should be time- and cost-effective. Therefore, we developed a two-step procedure for KRAS mutation testing including high resolution melting analysis (HRM) followed by pyrosequencing of only those samples that are not clearly identified as KRAS WT or mutant by HRM. HRM is a one-tube qPCR-based technique for DNA-variant detection. The method utilizes alterations in the melting behavior of double-stranded DNA fragments that are conferred by nucleotide exchanges. Melting of qPCR amplicons is monitored in real time using a suitable qPCR instrument capable of time-dense data aquisition and a saturating DNA-intercalating fluorescent dye that does not redistribute during the melting step [24]. Pyrosequencing is a sequencing-by-synthesis approach that involves sequential addition of dNTPs and recording incorporation of a nucleotide based on a light signal that is generated by sulfurylase-catalyzed conversion of the released pyrophosphate to ATP and a subsequent luciferase reaction [25]. Here, we applied a previously described HRM-assay [20] and the Therascreen KRAS Pyro kit (Qiagen) for detection of KRAS codon 12/13 mutations. First we comparatively analysed KRAS status in a panel of 61 colon cancer samples to determine sensitivity, specificity, technical performance and concordance of results of the two methods. Subsequently, we evaluated our two-step approach in the routine setting of our molecular diagnostics laboratory. In summary, we present a reliable, time- and cost-effective operational concept for KRAS mutation testing prior to anti-EGFR antibody treatment in mCRC.

Methods

Tumor samples, control cell lines and DNA isolation

The colorectal cancer samples reported on in this study were obtained from patients with metastatic colorectal cancer (UICC IV) at the University Hospital Marburg, Germany and analysed in a routine diagnostic setting. Tissue samples were fixed, paraffin-embedded, sectioned, hematoxylin-eosin stained and deparaffinated using standard procedures. Tissue sections were reviewed by an experienced pathologist (RM) to establish the diagnosis and to mark regions for microdissections. Microdissection of tumor cells was performed from deparaffinated sections using a scalpel. DNA was isolated from microdissected samples using the QiaAmp DNA Mini kit (Qiagen) as recommended by the manufacturer. KRAS mutant cell lines PL45 (pancreatic adenocarcinoma) and RPMI 8226 (multiple myeloma) were obtained from ATCC and cultured according to standard cell culture methods. Positive control DNA for HRM analyses was isolated from these cell lines using the QiaAmp DNA Mini kit. WT control DNA was extracted from peripheral blood of healthy donors from whom informed consent had been obtained (WT control) with the QiaAmp DNA Mini kit. DNA concentrations were measured using a Nanodrop 1000 spectrophotometer (Peqlab).

High resolution melting analysis

For HRM analysis, a 92 bp amplicon spanning exons 2 and 3 of the KRAS gene was amplified from 60 ng (or less) of sample DNA using the primers KRAS-92_F 5′-ttataaggcctgctgaaaatgactgaa-3′ and KRAS-92_R 5′-tgaattagctgtatcgtcaaggcact-3′ [20], the DNA-intercalating dye SYTO 9 (Thermo) in a final concentration of 5 μM and Platinum Taq polymerase (Thermo). Amplification and melting analysis was performed on a Rotor Gene 6000 instrument (Corbett Life Sciences) under the following temperature conditions: one cycle 95 °C/2 min, 40 cycles 95 °C/15 sec – 67.5 °C/15 sec - 72 °C/15 sec, one cycle 95 °C/1 sec, pre-melt conditioning at 72 °C/90 sec, HRM-ramp from 72 °C to 95 °C rising at 0.2 °C per step/wait 2 sec each step. Controls in each HRM run included a no-template-control, a WT control (gDNA from healthy donor) and two mutation controls (gDNA from the cell lines RPMI 8226, KRAS codon 12 GGT → GCT/heterozygous, corresponding to G12A and PL45, KRAS codon 12 GGT → GAT/heterozygous, corresponding to G12D). All HRM assays were performed in quadruplicate.

Pyrosequencing

Pyrosequencing of the KRAS codon 12/13 region was performed using the Therascreen KRAS Pyro Kit (Qiagen) as recommended by the manufacturer. 2 ng of DNA were used per analysis. PCR amplification of the target region was performed on a T-100 thermocycler (Biorad). For the pyrosequencing reaction on the PyroMark Q24 platform (Qiagen), amplicons were immobilized to the wells of a PyroMark Q24 plate using streptavidin high performance beads (GE Healthcare). Pyrosequencing results were analysed using the PyroMark Q24 software version 2.0 with the Therascreen KRAS Pyro-plugin report, which already incorporated the thresholds for mutation calls (detection limit for the mutation (LOD) + 3 %).

Statistical analysis

HRM and pyrosequencing results were compared by contingency table analysis test using GraphPad Prism 5 software (GraphPad). Technical performance (1st run success vs. 1st run failure) was evaluated by two-sided Fisher’s exact test at a significance level of 5 %. The agreement between HRM and pyrosequencing results was quantified by kappa using the appropriate Graphpad Prism online calculator (http://graphpad.com/quickcalcs/kappa2).

Results

Sensitivity of HRM and pyrosequencing

In order to test whether pyrosequencing allows for KRAS mutation detection with at least equal sensitivity compared to HRM, we analysed serial dilutions of DNA from a KRAS mutant cell line (PL45, codon 12 GGT → GAT heterozygous mutation) in WT DNA by both HRM and pyrosequencing. For HRM, we found, that the presence of KRAS mutant DNA in the sample was clearly reflected by a shifted or skewed melting curve for a fraction of PL45-DNA exceeding 25 %, which corresponded to a mutant allele frequency of 12.5 % (Fig. 1). Similarly, pyrosequencing definitely yielded a mutation if the sample contained ≥25 % PL45-DNA. On the other hand, samples with 5–10 % cell line DNA were indicated to exhibit a potential low level mutation as the mutant allele frequency was quantified below the threshold for accurate WT/mutant discrimination for the G12D mutation (LOD + 3 %; LOD = 2,2 %) for both the 5 and 10 % samples (Fig. 2). Thus, HRM and pyrosequencing appeared to be equally sensitive methods for the detection of KRAS codon 12/13 mutations.
Fig. 1

Sensitivity of HRM. Dilutions of genomic DNA from the KRAS mutant cell line PL45 (codon 12 GGT → GAT, heterozygous mutation) in WT genomic DNA was analysed by HRM. Normalised fluorescence and difference graphs are indicated. Clear discrimination of WT and mutant amplicons is possible using either graph if the fraction of PL45-DNA in the sample exceeds 25 %, corresponding to a mutant allele frequency of 12.5 %

Fig. 2

Sensitivity of pyrosequencing. Dilutions of genomic DNA from the KRAS mutant cell line PL45 (codon 12 GGT → GAT, heterozygous mutation) in WT genomic DNA was analysed by pyrosequencing on the Pyromark Q24 platform. The WT sequence and the sequence to analyse including wobble bases at the potentially mutant positions in the region of interest (codons 12 and 13) are indicated in the top panel. Lower panels: KRAS codon 12/13 pyrograms for different dilutions of PL45-DNA in WT DNA. Clear mutation calls are obtained for samples containing ≥25 % of PL45-DNA, corresponding to 12.5 % mutant alleles. For lower concentrations, yielding signals below the LOD of the mutation (2.2 %) + 3 %, presence of a potential low level mutation is suggested, which requires technical and/or biological replication of the analysis

Technical reliability of HRM and pyrosequencing

To further assess the suitability of pyrosequencing to serve as a backup-assay allowing for accurate diagnosis of KRAS mutation status in case of failed HRM analysis, we investigated KRAS status of 61 colorectal cancer samples by both HRM and pyrosequencing and compared the two methods with regard to their technical performance and concordance of results. In a first run of HRM analysis, 11/61 samples (18.0 %) could not be analysed due to PCR-failures or ambiguous melting curves (Table 1). Repetition of the assay for seven samples, which most likely had been compromised technically, allowed for assigning KRAS mutation status in all cases. The remaining four samples were directly subjected to pyrosequencing without a second round of HRM analysis. Indeed, KRAS status could each be determined, although one sample yielded a potential low level mutation. Of the 57 samples that could be definitely classified as KRAS WT or mutant by HRM, 26 WT samples (45.6 % of all samples/68.4 % of WT samples) yielded skewed HRM curves, which, however, did not prevent establishment of a diagnosis (Tables 1 and 2). Moreover, we noted that low DNA content of the samples below the detection limit of the Nanodrop spectrophotometer not necessarily prevented successful HRM analysis. In contrast to HRM, the pyrosequencing assay had to be repeated for only one sample (Table 1). Thus, the failure rate of a first analysis run as a consequence of technical and/or sample-issues was significantly higher for HRM analysis than for pyrosequencing (p = 0.0042). Together, pyrosequencing is technically more reliable than HRM due to lower input requirements and a lower incidence of invalid results.
Table 1

KRAS codon 12/13 status by HRM and pyrosequencing in 61 CRC samples

  

HRM

Pyrosequencing

    

Run 1

Run 2

 

Sample

cDNA [ng/μl]

Run 1

Run 2

Result

% mut. Alleles

Result

% mut. Alleles

Final result

1

11

failed

WT a

WT

   

WT

2

31

WT a

 

WT

   

WT

3

10

WT a

 

G12C

13.4

  

mut

4

93

WT a

 

WT

   

WT

5

26

WT a

 

WT

   

WT

6

27

WT a

 

WT

   

WT

7

10

WT a

 

WT

   

WT

8

43

mut

 

G13D

73.9

  

mut

9

85

failed

WT

WT

   

WT

10

N/A

mut

 

G13D

44.3

  

mut

11

N/A

failed

 

G12V

2.6

  

WT b

12

N/A

WT

 

WT

   

WT

13

N/A

mut

 

G12V

41.9

  

mut

14

126

mut

 

failed

 

G12D

65.7

mut

15

133

mut

 

G12D

74.1

  

mut

16

97

mut

 

G13D

52.8

  

mut

17

47

failed

WT

WT

   

WT

18

14

failed

WT

WT

   

WT

19

44

WT a

 

WT

   

WT

20

20

failed

WT a

WT

   

WT

21

N/A

failed

 

WT

   

WT

22

138

mut

 

G12V

12.9

  

mut

23

325

mut

 

G12D

56.1

  

mut

24

140

WT a

 

WT

   

WT

25

7

mut

 

G12C

61.2

  

mut

26

4

WT a

 

WT

   

WT

27

27

WT a

 

WT

   

WT

28

13

WT a

 

WT

   

WT

29

207

mut

 

G12D

54.5

  

mut

30

10

failed

WT

G12V

1.5

  

WT b

31

54

WT a

 

WT

   

WT

32

120

mut

 

G12V

29.2

  

mut

33

33

failed

mut

G12C

33.5

  

mut

34

N/A

mut

 

G12C

71.4

  

mut

35

N/A

WT

 

WT

   

WT

36

N/A

failed

 

WT

   

WT

37

67

WT a

 

WT

   

WT

38

137

mut

 

G12C

76.7

  

mut

39

63

mut

 

G12A

56

  

mut

40

13

WT a

 

WT

   

WT

41

113

WT a

 

WT

   

WT

42

82

mut

 

G12C

75.4

  

mut

43

39

WT

 

WT

   

WT

44

7

WT a

 

G12S

2

  

WT b

45

23

WT a

 

WT

   

WT

46

24

faileda

 

G13D

3.5

  

WT b

47

9

WT a

 

WT

   

WT

48

34

WT a

 

G12S

2

  

WT b

49

25

WT a

 

WT

   

WT

50

17

WT

 

WT

   

WT

51

5

WT a

 

WT

   

WT

52

29

WT a

 

WT

   

WT

53

31

mut

 

G12D

71.3

  

mut

54

68

WT

 

WT

   

WT

55

93

mut

 

G12D

74.2

  

mut

56

221

WT

 

WT

   

WT

57

83

WT

 

WT

   

WT

58

N/A

WT a

 

G12V

1.2

  

WT b

59

35

mut

 

G12D

83.3

  

mut

60

N/A

WT

 

WT

   

WT

61

37

WT a

 

WT

   

WT

aSkewed HRM curve

bLOD/threshold for potential low level mutation (cf. Therascreen KRAS Pyro Kit handbook version 1, July 2011): G12D 2.2 %/5.2 %, G12V 1.0 %/4.0 %, G12C 2.1 %/5.1 %, G12S 1.9 %/4.9 %, G13D 1.9 %/4.9 %

Table 2

Comparison of HRM and pyrosequencing results in 61 CRC samples

 

Run 1

Run 2

Summary

Summary of Results

HRM

n

%

n

%

n

%

 Number of samples

61

100.0

7

100.0 (11.5)

61

100.0

 Analysis passed

50

82.0

7

100.0

57

93.4

  WT (total)

32

64.0

6

85.7

38

66.7

  WT (skewed HRM curve)

24

75.0

2

33.3

26

68.4

  Mutant (total)

18

36.0

1

14.3

19

33.3

  Mutant (skewed HRM curve)

0

 

0

 

0

 

 Analysis failed

11

18.0

0

   

Pyrosequencing

n

%

n

%

n

%

 Number of samples

61

100.0

1

100.0 (1.6)

61

100.0

 Analysis passed

60

98.4

1

100.0

61

100.0

  WT (total)

41

68.3

0

 

41

67.2

  WT (call: WT)

35

58.3

  

35

 

  WT (call: potential low level mutation)

6

10.0

0

 

6

 

  Mutant

19

31.7

1

100.0

20

32.8

 Analysis failed

1

1.6

0

   

Concordance of Results

HRM

Pyrosequencing

 

n

%

n

%

 Number of samples

57

100

57

100

 WT (total)

38

66.7

37

64.9

  WT (call: WT)

  

33

57.9

  WT (call: potential low level mutation)

  

4

7.0

 Mutant

19

33.3

20

35.1

 Concordant

56

98.2

  

 Discordant

1

1.8

  

 Correctly classified WT

37

97.4

  

 Incorrectly classified WT

1

2.6

  

 Correctly classified mutant

19

100

  

 Incorrectly classified mutant

0

0

  

Concordance of HRM and pyrosequencing results

In order to evaluate the diagnostic validity of HRM analysis as a basic test for KRAS mutation detection, we compared the results from this assay to pyrosequencing in the 57 samples that could be successfully analysed by both methods. KRAS status was assigned concordantly for 56 samples (98.2 %; kappa = 0.961), while the result for one sample with a low mutant allele frequency of 13.4 % (#3, Table 1) was inconsistent between HRM and pyrosequencing (Tables 1 and 2). Importantly, pyrosequencing indicated the presence of potential low level mutations (mutant allele frequency < 4.0–5.2 %, cf. Table 1) in four samples that were called WT by HRM. Given that this output is generated due to low signal strength for the potential mutation near the technical detection limit of the pyrosequencing method we finally classified these samples as WT. Conversely, all 19 samples that were clearly identified as mutant by HRM were classified identically by pyrosequencing. Therefore, defining pyrosequencing as the reference method, the specificity of HRM for detection of mutant KRAS alleles was 100 %. On the other hand, the specificity for the detection of WT alleles was slightly reduced (97.4 %) due to erroneous interpretation of the HRM curve for the one sample mentioned (#3, Table 1) with a mutant allele frequency only slightly above the sensitivity threshold of the method. When we applied a different HRM assay for the detection of NRAS codon 61 mutations on an independent set of 19 CRC samples, we found a 100 % concordance of results with reports from a reference laboratory (Additional file 1: Table S1). Of note, sensitivity of the NRAS HRM assay was comparable to the KRAS assay and allowed for reliable identification of mutations at a mutant sample fraction of 20 % (Additional file 2: Figure S1). Taken together, these findings indicate that HRM represents a very reliable basic method for KRAS mutation testing.

Two-step KRAS mutation testing in routine diagnostics

To evaluate the actual effectiveness of our two-step analysis platform (Fig. 3) in a routine diagnostic setting, we reviewed effort and outcome of KRAS codon 12/13 mutation testing in 120 independent colorectal cancer samples that were examined consecutively in our laboratory according to this concept (Table 3). We found, that KRAS status could be determined for 87.5 % of samples by HRM and for 99.2 % of samples in total, when pyrosequencing was applied to samples that could not be successfully analysed by HRM (Table 4). However, for both HRM and pyrosequencing, the failure rate was slightly higher than anticipated based on the observations from our initial 61 sample set (Tables 2 and 4). Also of note, the number of samples that were subjected to pyrosequencing in routine diagnostics exceeded the previously estimated need of this analysis (19/120 = 15.5 % vs. 4/61 = 6.6 %) because 15 samples were directly analysed by pyrosequencing after the first failed HRM run in order to utilize otherwise wasted capacities. Yet, in summary, these data strongly support the rationale of our two-step approach to KRAS codon 12/13 mutation analysis, confirming the accuracy of our diagnostic platform.
Fig. 3

Outline of the two-step procedure for KRAS codon 12/13 mutation analysis. Genomic DNA from microdissected colorectal cancer cells from FFPE samples is subjected to HRM of a PCR amplicon spanning the mutation-bearing region of interest. For samples that are clearly identified as KRAS mutant or, respectively, WT, the HRM result is incorporated in the final diagnostic report. Samples for which HRM analysis fails technically or which yield ambiguous HRM curves are further evaluated by a second round of HRM and, if results are still invalid, to pyrosequencing. Note that samples for which a WT result is obtained by the diagnostic procedure outlined here require further examination for additional KRAS and NRAS mutations

Table 3

Detailed results of KRAS codon 12/13 mutation testing in 120 CRC samples

  

HRM

Pyrosequencing

    

Run 1

Run 2

 

Sample

cDNA [ng/μl]

Run 1

Run 2

Result

% mut. Alleles

Result

% mut. Alleles

Final result

62

541

WT a

 

WT

   

WT

63

29

WT a

 

WT

   

WT

64

378

WT

     

WT

65

342

WT a

WT

    

WT

66

176

failed

WT a

G12V

3.2

G12V

5.2

WT

67

139

mut

     

mut

68

520

WT

     

WT

69

42

WT

     

WT

70

202

WT

     

WT

71

157

mut

     

mut

72

259

mut

     

mut

73

145

WT

     

WT

74

21

failed

failed

WT

   

WT

75

22

failed

 

WT

   

WT

76

66

mut

     

mut

77

55

mut

     

mut

78

199

mut

     

mut

79

197

WT

     

WT

80

171

WT

     

WT

81

55

failed

 

G12V

41.1

  

mut

82

231

failed

 

WT

   

WT

83

250

failed

 

WT

   

WT

84

57

failed

WT a

    

WT

85

21

mut

     

mut

86

248

WT

     

WT

87

258

WT

     

WT

88

83

failed

 

failed

 

failed

 

N/A

89

38

failed

 

WT

   

WT

90

279

WT

     

WT

91

122

failed

 

WT

   

WT

92

129

failed

 

Low Mut.

5.2

Low Mut.

8.2

mut

93

58

WT

     

WT

94

129

WT

     

WT

95

254

WT

     

WT

96

373

WT

     

WT

97

158

WT

     

WT

98

96

mut

     

mut

99

22

WT

     

WT

100

30

mut

     

mut

101

26

muta

muta

G13D

7.3

  

mut

102

49

WT

     

WT

103

47

WT

     

WT

104

43

WT

     

WT

105

54

WT

     

WT

106

363

failed

mut

    

mut

107

521

failed

WT

    

WT

108

199

mut

     

mut

109

260

WT

     

WT

110

67

WT

     

WT

111

103

WT

     

WT

112

24

mut

     

mut

113

150

WT

     

WT

114

5

WT

     

WT

115

25

WT

     

WT

116

33

WT

     

WT

117

26

mut

     

mut

118

72

WT

     

WT

119

16

failed

 

G12V

12.8

  

mut

120

33

failed

 

WT

   

WT

121

48

WT

     

WT

122

74

WT

     

WT

123

474

mut

     

mut

124

431

mut

     

mut

125

66

mut

     

mut

126

143

mut

     

mut

127

49

failed

WT

    

WT

128

143

WT

     

WT

129

122

mut

     

mut

130

139

WT

     

WT

131

21

failed

 

WT

   

WT

132

39

failed

 

WT

   

WT

133

128

failed

 

G12D

26.7

  

mut

134

60

mut

     

mut

135

330

failed

mut

    

mut

136

165

mut

     

mut

137

213

mut

     

mut

138

31

failed

mut

    

mut

139

156

mut

     

mut

140

59

WT

     

WT

141

68

WT

     

WT

142

164

WT

     

WT

143

238

mut

     

mut

144

12

mut

     

mut

145

33

failed

WT

    

WT

146

81

WT

     

WT

147

11

WT

     

WT

148

13

mut

     

mut

149

71

WT

     

WT

150

11

mut

     

mut

151

40

failed

WT

    

WT

152

50

WT

     

WT

153

128

mut

     

mut

154

146

WT

     

WT

155

69

WT

     

WT

156

182

WT

     

WT

157

32

failed

WT

    

WT

158

142

WT

     

WT

159

53

WT

     

WT

160

91

failed

WT

    

WT

161

334

WT

     

WT

162

86

failed

WT

    

WT

163

61

WT

     

WT

164

64

WT

     

WT

165

141

WT

     

WT

166

271

WT

     

WT

167

40

WT

     

WT

168

34

failed

WT

    

WT

169

29

failed

failed

WT

   

WT

170

354

WT

     

WT

171

66

WT

     

WT

172

43

failed

WT

    

WT

173

114

WT

     

WT

174

268

WT

     

WT

175

107

WT

     

WT

176

170

mut

     

mut

177

65

failed

mut

    

mut

178

31

failed

mut

    

mut

179

61

WT

     

WT

180

659

mut

     

mut

181

34

WT

     

WT

aSkewed HRM curve

Table 4

Operational analysis of two-step KRAS mutation testing of 120 CRC samples

 

Run 1

Run 2

Summary

HRM

n

%

n

%

n

%

 Number of samples

120

100.0

20

100.0 (16.7)

120

100.0

 Analysis passed

89

74.2

18

90.0

105

87.5

  WT (total)

60

67.4

12

66.7

71

67.6

  WT (skewed HRM curve)

3

5.0

2

16.7

4

5.6

  Mutant (total)

29

32.6

6

33.3

34

32.4

  Mutant (skewed HRM curve)

1

3.4

1

16.7

1

2.9

 Analysis failed

31

25.8

2

10.0

  

Pyrosequencing

n

%

n

%

n

%

 Number of samples

19

100.0 (15.8)

3

100.0 (2.5)

19

100.0

 Analysis passed

18

94.7

2

66.7

18

94.7

  WT

12

66.7

0

0.0

13

72.2

  Potential low level mutation

2

11.1

1

50.0

0

0.0

  Mutant

4

22.2

1

50.0

5

27.8

 Analysis failed

1

5.3

1

33.3

1

 

Combined HRM + Pyrosequencing

    

n

%

 Number of samples

    

120

100.0

 Number of HRM runs

    

140

116.7

 Number of pyrosequencing runs

    

22

18.3

 Analysis passed

    

119

99.2

 WT

    

81

68.1

 Mutant

    

38

31.9

 Analysis failed

    

1

0.8

Assay costs

In order to estimate the economic benefits of our two-step approach to KRAS mutation testing, we compared analysis costs in our routine setting to a pyrosequencing-only platform. Based on current list prices for reagents and consumables, we estimated the assay costs for HRM analysis and pyrosequencing at approximately € 7.50 and € 100, respectively (Table 5). The costs for the essential technical devices for both methods have not been converted to per-sample costs because operation expenses are highly dependent on sample throughput, including not only the KRAS mutation assay but also other applications. Moreover, investments for technical equipment are in the same range for pyrosequencing and HRM. Considering the failure rates of each assay in our set of 120 routine samples (23.6 % for HRM and 9.1 % for pyrosequencing), leading to repeated testing of some samples, our two-step approach allows for net reduction of operational costs of approximately 75 % compared to pyrosequencing alone. Moreover, according to our experience, hands-on time for processing the maximum number of samples for one HRM-run (14 + 4 controls) is only half of the time required to prepare and perform a pyrosequencing run at full capacity (22 + 2 controls) (Table 5). Therefore, our concept to maintain two sequential assays for KRAS codon 12/13 mutation testing represents cost- and time-effective approach for routine diagnostics.
Table 5

Per-sample costs and hands-on time for HRM and pyrosequencing analyses

 

HRM

Pyrosequencing

Costs (Euro)

 Reagents

3.40

90.00

 Consumables

2.40

3.50

 Controls

1.70

8.50

 Total

7.50

102.00

Time (minutes)

 14 samples + 4 controls

60

 

 22 samples + 2 controls

 

120

Costs for the controls were estimated based on the maximum number of samples that can be processed in one HRM- or pyrosequencing run, respectively. Costs for HRM controls also include DNA isolation from KRAS WT and mutant cell lines. Hands-on time is indicated for full capacity runs

Discussion

Here we present a two-step approach to KRAS codon 12/13 mutation testing for mCRC employing HRM analysis and pyrosequencing using the Therascreeen KRAS Pyro Kit. Comparing the performance of the two methods in a panel of 61 samples, we observed a 98.2 % concordance of results with a 100 % specificity of HRM for the detection of mutant alleles. Thus, HRM analysis needs methodically independent confirmation of results by pyrosequencing only in exceptional cases and therefore can serve as a filter assay to exclude clearly WT or mutant samples from the more expensive and more laborious pyrosequencing analysis. Specifically, based on our observations reported here, this approach can reduce throughput of the pyrosequencing assay by >85 %, resulting in a >75 % cost reduction compared to using pyrosequencing only. We emphasize, that our comparison of the two methods in the first place aimed on diagnostic accuracy for sequential application in order to establish a reliable and economized platform for KRAS mutation testing. Of note, we reached this goal in spite we were able to detect mutant KRAS alleles only at a frequency >12.5 % instead of 5 % as reported in the literature [20, 26].

With respect to technical performance, although we successfully applied HRM to very low input samples, we state a clear advantage for the pyrosequencing assay due to lower input requirements and an apparently relatively high susceptibility of HRM to artifacts. More precisely, previous authors have pointed out, that especially WT HRM curves show a certain degree of variation resulting from poor quality of FFPE-derived template DNA, differing salt- or inhibitor concentrations or unspecific amplification [20, 27], that may complicate correct determination of KRAS status. Consistent with this notion, 6 of the 7 samples in our 61-sample validation set that were subjected to a second round of HRM analysis due to poor interpretability of first round results were eventually called WT by this method. Conversely, we did not obtain false positive results by HRM, i.e., none of our samples that had been identified as mutant by HRM was found to be WT according to pyrosequencing. Yet, we state that the mutation frequency of KRAS codon 12/13 observed in our study was slightly lower than reported in the literature [9, 10], which may be explained by our homogenous patient population from a single center (Marburg, Germany).

Concerning diagnostic value of results from our sequential KRAS mutation analysis procedure, it is important to point out that pyrosequencing results include information on the site, type and frequency of the nucleotide exchange, while HRM only allows for categorical discrimination of WT and mutant tumors. According to current standards, such a dual output is actually sufficient to establish the indication for anti-EGFR treatment, although certain authors have suggested that not all KRAS mutations are equal regarding outcome in mCRC patients treated with cetuximab [3]. Consequently, as clinical routine testing at present in principle does not require sequence-based analysis, the more differentiated output of the pyrosequencing assay does not warrant the higher costs for this analysis. Therefore, the two-step procedure for KRAS mutation testing presented here represents a reasonable diagnostic approach not only from a technical-practical and economical, but also from a clinical perspective. More specifically, using our diagnostic platform focused on KRAS codon 12/13 mutation testing, even small diagnostic laboratories can provide accurate and clinically meaningful results within a short processing time for the most relevant genetic alteration that determines a treatment decision for mCRC patients. Consequently, only a small fraction of patient samples has to be sent to an external reference laboratory for further molecular studies in accordance with the current EMA standards and recommendations by the American Society of Clinical Oncology, which state that Ras mutation testing prior to initiation of treatment with cetuximab and panitumumab has to include analysis of both KRAS and NRAS exons 2, 3 and 4 (codons 12, 13, 59, 61, 117 and 146). Also of note, besides KRAS and NRAS mutations, alterations in several other genes such as BRAF and PIK3CA have been proposed to predict outcome with EGFR antibody treatment [2830]. Thus, identification of patients eligible for cetuximab or panitumumab treatment in fact requires either a broad panel of single mutation tests or a multiplex approach. Optimized methods for DNA melting analysis of short PCR amplicons have been suggested to allow for comprehensive hot spot mutation testing in a clinical setting as they require only standard qPCR equipment. However, each assay requires careful optimization, implying considerable efforts for a diagnostic laboratory to set up all tests on site [31]. Alternatively, next generation sequencing (NGS) with a targeted resequencing approach appears to be a suitable technology for extensive clinically relevant mutation testing in the future, which has already been evaluated for the molecular diagnostics of colorectal cancer [32, 33]. Given the high frequency of KRAS codon 12/13 mutations compared to other KRAS- or NRAS mutations and the fact that these mutations occur mutually exclusive [10], it still seems reasonable, to filter the samples that actually need advanced testing method as proposed here. Thus, a two-step approach including HRM analysis of KRAS codon 12/13 mutations followed by next generation targeted resequencing might be the most attractive implementation for routine KRAS mutation diagnostics in the future.

Conclusion

We present a diagnostically reliable and cost-effective two-step approach to KRAS codon 12/13 mutation testing of CRC samples prior to initiation of treatment with anti-EGFR antibodies. The platform appears to be especially attractive for small to medium diagnostic laboratories that don’t have the capacities to maintain an extensive spectrum of rare mutation tests according to regulatory standards for diagnostic laboratories [34] or to adopt NGS-technology with its complex associated infrastructure including bioinformatics.

Abbreviations

CRC, colorectal cancer; EMA. European medical agency; FDA, U.S. food and drug administration; HRM, high resolution melting analysis; LOD, limit of detection; mCRC, metastatic colorectal cancer; NGS, next generation sequencing; PCR, polymerase chain reaction; qPCR, quantitative polymerase chain reaction; WT, wildtype; UICC, Union internationale contre le cancer.

Declarations

Acknowledgements

We like to thank Viktoria Wischmann, Department of Pathology, University Hospital Marburg for microdissection of CRC specimens. Petra Ross, Lisa-Marie Koch and the staff of the Molecular Biology Laboratory, Department of Hematology and Oncology are acknowledged for excellent technical assistance and helpful discussion.

Funding

This work was supported by DFG Klinische Forschergruppe KFO210 (AN, CB) and the José Carreras Leukemia Foundation (AH06-01, to AN).

Availability of data and materials

The dataset supporting the conclusions of this article is included within the article and its supplementary material.

Authors’ contributions

CB, EM and RM conceived and designed the study. RM reviewed tissue sections. KS established the method and performed KRAS mutation analysis. KS, CB and EM analysed data. AN and JRK contributed to the analysis and interpretation of the data. EM wrote the manuscript, which was critically revised by CB, AN, RM and JRK. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

This study was conducted in a routine diagnostic setting for internal quality control purposes and did not require formal ethics approval according to the guidelines of the local ethics comitee. Verbal informed consent to perform routine pathological examinations on their samples as needed was obtained from all patients.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Klinik für Hämatologie, Onkologie und Immunologie, Universitätsklinikum Gießen und Marburg, Standort Marburg, Philipps-Universität Marburg, Baldingerstraße
(2)
Institut für Pathologie, Universitätsklinikum Gießen und Marburg, Standort Marburg, Philipps-Universität Marburg, Baldingerstraße

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Copyright

© The Author(s). 2016