December 2013, Vol 2, No 8

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Predicting Response to EGFR-Targeting mAbs in Colorectal Cancer – Is the KRAS Mutation Test Sufficient?

Niklas K. Finnberg, PhD

Colorectal Cancer

Dr Finnberg is an Assistant Professor at Penn State Hershey Cancer Institute. He received his PhD degree from Karolinska Institutet in Stockholm, Sweden, and has worked extensively to characterize the role of apoptosis in tissue toxicity to conventional and targeted cancer therapeutics. Dr Finnberg’s current research focuses on understanding tissue responses to DNA damage inflicted by cancer therapy, addressing molecular pathways activated following radio/chemotherapy to modulate toxicity of treatment, and developing biomarkers that can predict toxicity to therapy.

Dr Lim is a clinical fellow in the Division of Hematology/Oncology, Penn State Hershey Cancer Institute. She received her MD from the Ewha Womans University, Seoul, South Korea, and later joined the laboratory of Dr Marcia S. Brose at the Hospital of the University of Pennsylvania where she studied Rap1 and Rap1-GAP as clinical outcome markers in breast cancer. Dr Lim has a special interest in the molecular biology of triple-negative breast cancer (TNBC) and identifying new biomarkers and strategies employing targeted therapeutics to treat TNBC and other cancers. Dr Lim is an active preclinical scientist and a coinvestigator on clinical trials conducted at Penn State Hershey Cancer Institute.

Although metastatic colorectal cancer (mCRC) has a poor overall prognosis, the introduction of monoclonal antibodies (mAbs) that antagonize signaling from the epidermal growth factor receptor (EGFR) has led to improvements in response rate and survival.1,2 There are currently 2 FDA-approved antagonist mAbs (cetuximab [Erbitux] and panitumumab [Vectibix]) targeting EGFR for the treatment of mCRC. EGFR is a protein tyrosine kinase aberrantly expressed in many cancers.3,4 The EGFR ligand EGF activates 2 well-characterized signal transduction pathways of RAS-RAF-MEK-ERK and PI3K-AKT-mTOR signaling5 (Figure 1). KRAS functions as an essential molecular switch for both normal cell and tissue homeostasis. Once turned on, KRAS promotes the propagation of signals from, for example, growth factors such as RAF and PI3K (Figure 1). KRAS activity is tightly regulated in a rheostat-like manner in normal cells. A single nucleotide substitution is responsible for oncogenic KRAS mutations that are frequent in cancers such as leukemia, colon cancer, pancreatic cancer, and lung cancer. Mutation of the KRAS gene results in a constitutively active GTP-bound form and produces a constitutive “switch-on” state. This triggers aberrant activity of the downstream signaling cascade, thus allowing cell growth independent of extracellular stimuli.6

Aberrant constitutive activation of these pathways leads to cellular proliferation and invasive behavior of cancer cells. It is estimated that EGFR is overexpressed in 65% to 70% of CRCs, and EGFR overexpression tends to be associated with advanced disease stage.7 However, only subsets of patients show clinical benefit to treatment using cetuximab and panitumumab, and expression of EGFR alone is not predictive for response to EGFR-targeting mAbs. This is in part explained by the fact that 40% to 50% of mCRC patients have the gain-of-function KRAS mutation in codons 12 or 13, a genetic lesion that bypasses the requirement of upstream EGFR stimuli8 (Figure 1). The American Society of Clinical Oncology provisional opinion and the National Comprehensive Cancer Network recommend testing patients with mCRC for KRAS mutations. The KRAS mutation in codons 12 and 13 exclude EGFR-targeting mAbs as a treatment option.9,10 Thus, patients with mCRC and these specific KRAS gene mutations are not treated with cetuximab or panitumumab. KRAS mutation analysis is carried out in Clinical Laboratory Improvement Amendments (CLIA)-certified laboratories. DNA is isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissue and sequenced to identify KRAS mutations in codons 12 and 13. The use of the KRAS mutation as a negatively predictive biomarker for response to EGFR-targeting mAbs is associated with several technical obstacles, as well as hurdles related to tumor biology and histology. A recent case report may have exemplarily illustrated the symptoms of said hurdles. Lamparella et al11 reported that KRAS mutation analysis by 2 independent CLIA-certified laboratories resulted in conflicting information regarding 1 patient’s CRC mutation status. The discordant reports complicated the decision with respect to the inclusion of EGFR-targeting mAbs as part of personalized therapy. The patient was subjected to FOLFIRI (leucovorin, 5-fluorouracil, and irinotecan) and cetuximab as the second test indicated that the original tumor was KRAS wild-type. This treatment seemed to yield a short-lived response to the treatment (commonly seen in “responders” to EGFR targeting) as evidenced by a reduction of the serum tumor markers CA19-9 and CEA, suggesting that the tumor indeed might have been KRAS wild-type. Herein we discuss the limitations associated with the use of KRAS as a single “negative” biomarker for response to EGFR-targeting mAbs and emerging methodology that is likely to improve the prediction of response to EGFR targeting.

Determinants of Response to EGFR Targeting
Despite the value of the KRAS mutations as an exclusionary biomarker for response to EGFR targeting, the presence of wild-type KRAS does not guarantee a favorable response to EGFR-targeting mAbs. In fact, KRAS mutations may only account for 30% to 40% of patients who do not respond to cetuximab.12 Thus, it is clear that there are additional molecular mechanisms that dictate the response to EGFR-targeting mAbs. Preclinical data have indicated that mutations of the RAF oncogene might confer resistance to EGFR targeting (Figure 1). It is estimated that 5% to 10% of CRCs carry a mutation in the BRAF V600E allele. However, the CRYSTAL and OPUS trials suggest that BRAF mutations are poor prognostic markers regardless of treatment types, and they lack the predictive value for cetuximab treatment.13

Figure 1

PI3K belongs to a family of intracellular lipid kinases that phosphorylate the 3?-hydroxyl group of phosphatidylinositol and phosphoinositides (Figure 1). PI3K is activated by EGFR and RAS signaling and is responsible for the activation of AKT (protein kinase B) through an intermediate step. PI3K-AKT signaling regulates proliferation of intestinal epithelia, malignant transformation, and propagation of CRC cells.14-17 The PI3K gene (PIK3CA) is mutated in approximately 15% of all CRCs.18 PI3K mutations result in the upregulation of AKT in the absence of upstream signals via gain of enzymatic function in the p110? subunit of PI3K, and those mutations have been proposed to predict for patients who are
less likely to respond to the mAbs against EGFR.18

PI3K signaling is inhibited by the phosphate and tensin homologue deleted on chromosome ten (PTEN) (Figure 1). Preclinical data indicate that cell lines lacking PTEN are more resistant to cetuximab.19 PTEN mutations occur in approximately 30% of sporadic CRCs, and inactivating mutations of PTEN may be associated with an impaired response to cetuximab.20-22 Taken together, additional mutations downstream of EGFR could influence the response to mAbs targeting the receptor, and subsequently such alterations might need to be considered to better predict responses to cetuximab and panitumumab. Patients who seem to benefit the most from EGFR targeting are those who have the combination of wild-type BRAF, KRAS, PI3K-intact PTEN expression (Figure 1). However, an assessment of all of these factors is not routinely included in predicting response to cetuximab or panitumu­mab and may explain why some patients with wild-type KRAS do not respond to treatment with EGFR-targeting mAbs. Moreover, recent clinical data also indicate that mutations in the NRAS gene have to be considered in addition to mutations in the KRAS gene to predict response to panitumumab and FOLFOX4 (leucovorin, 5-fluorouracil, and oxaliplatin).23

Antibody-Dependent Cell-Mediated Cytotoxicity
The value of mutated KRAS as a biomarker has come into question since occasionally patients with mutation of the KRAS gene respond to treatment that includes cetuximab. Cetuximab and panitumumab are considered antagonist mAbs that inhibit the interaction between EGFR and its ligand through targeting of the extracellular domain. Rare responses to cetuximab in KRAS-mutant CRC may be explained by antibody-dependent cell-mediated cytotoxicity (ADCC) (Figure 2). ADCC results from the effector cells of the immune system targeting the cells that have antibodies bound to membrane surface antigens.24 The primary purpose of ADCC in the human body is to limit the spread of infected cells. Typically this mechanism involves the activity of natural killer (NK) cells, macrophages, neutrophils, and eosinophils. ADCC can be modulated by specific sequences of the Fc domain of mAbs. NK cells express CD16/Fc?RIII, which functions as a receptor for the Fc domain. Interaction between CD16 and the Fc domain triggers the release of cytokines such as interferon-gamma. ADCC is one of the important mechanisms of response to mAbs. Thus, ADCC could potentially enable patients with mutated KRAS to respond to EGFR-targeting mAbs. Polymorphisms in the Fc?RIII gene can negatively impact ADCC following treatment with mAbs that target cell surface receptors. The high-affinity Fc?RIIIa-158-
valine (V) polymorphism is associated with more potent ADCC response compared with the low-affinity
Fc?RIIIa-158-phenylalanine (F) polymorphism. Approximately 45% of all patients are homozygous for Fc?RIIIa-158-phen­ylalanine (F/F) and subsequently impaired in their ability to generate an ADCC. In order to increase the likelihood of an ADCC response, novel EGFR-targeting mAbs have been developed that interacts with the Fc?R with higher affinity.25 Preclinical data suggest that KRAS mutation status does not affect ADCC, but KRAS status and Fc?RIII polymorphisms as covariants have not been studied. In conclusion, it is likely that ADCC will be an important cofactor of the EGFR-targeted therapy response (Figure 2).

New Diagnostic Methodology Will Pave the Way for Personalized Medicine in the Treatment of CRC
Typically, analyses of KRAS mutations are based on polymerase chain reaction (PCR)-based genotyping in which DNA is isolated from FFPE tumor tissue. Blocks are identified by an expert pathologist for the content of tumor tissues. Unfortunately, despite appearing trivial, sequencing tumor tissue can present technical challenges, including the analysis of a heterogeneous tumor cell population and contamination by normal tissue. Also, part of the challenge consists of the isolation of macromolecules from FFPE material, a procedure that involves cutting sufficiently large tissue slides from the FFPE blocks followed by a dewaxing procedure. The captured tissues are then subjected to proteinase K digestion in order to extract a sufficient amount of DNA that can be used for PCR amplification of exon 1 and 2 of the KRAS gene and subsequent sequencing. Findings should be repeated in at least 2 experiments. DNA that is isolated by such procedures is often degraded, and the remnants from the fixation can interfere with the analysis. Successful analysis of DNA from an FFPE block ranges from 70% to 88% when dewaxing is used in combination with proteinase K digestion.26,27 More recently, novel methodologies that omit the use of xylene for dewaxing and proteinase K for digestion of the tissues have been developed that are automated in function and remove some of the variables from the procedures. Nevertheless, despite being routinely used for diagnostic purposes, isolation of DNA from FFPE tissue remains suboptimal compared with the use of fresh tumor tissue.

Routine Sanger sequencing currently used for diagnostic purposes is unlikely to detect mutations that are present in less than 10% of the CRC cell population. Therefore, rare tumor populations are unlikely to be detected by current diagnostic tools. Next genome sequencing (NGS) broadly describes those technologies that share the ability to massively parallel sequence millions of DNA templates.28 NGS may address some of the issues with Sanger sequencing since such approaches provide higher sensitivity and the ability to sample rare mutant alleles present in a background that are predominant wild-type ones.29 Furthermore, NGS may offer increased speed, enhanced sensitivity in mutation detection, and lower cost compared with Sanger sequencing.30 Recent data suggest that NGS is equal or superior when sequencing DNA from FFPE CRC specimens with respect to sensitivity and specificity.31,32 One additional advantage of massive parallel sequencing is the lack of dependency on an a priori selection of mutation “hot spots” compared with Sanger sequencing. Enhanced analytical sensitivity may be required to accurately identify patients who are most likely to benefit from the inclusion of targeted therapeutics. A comparison between Sanger sequencing and massively parallel sequencing on EGFR-mutant non–small cell lung cancer (NSCLC) specimens revealed that only massively parallel sequencing was able to detect all the relevant EGFR mutations present in responders to EGFR inhibition.33 In contrast, Sanger sequencing misdiagnosed 25% (6/24) of the tumor samples. Furthermore, the authors found a low correlation between tumor cell content and the frequency of mutant alleles, indicating that routine survey of histopathological sections cannot be relied on to accurately estimate the degree of bystander cells that carry wild-type alleles in NSCLC. Therefore, microdissection may be the only method to improve the sensitivity of Sanger sequencing. Despite the development of different techniques to geno­type CRCs, a thorough clinical validation of NGS methodologies has yet to be completed.

Figure 2

The advent of NGS will result in an increased demand to assess tumor purity in the samples analyzed in order to accurately estimate the tumor heterogeneity. Tumor purity has traditionally been assessed by a pathologist or by image analysis. However, tumor heterogeneity is not being addressed by such methods. The clonal theory of cancer progression states that cancerous cells in a tumor are descendents of a single founder cell.34 Descendents have acquired mutations that promote tumorigeneses that are distinct from each other. Thus subpopulations of tumor cells may harbor distinct somatic mutations. Tumor heterogeneity has a role in resistance to EGFR-targeting therapy. Patients with wild-type KRAS mCRC who are subjected to treatment with EGFR-targeting mAbs typically show short-lived responses. Recent data indicate that the mechanism of acquired resistance frequently involves the expansion of CRC clones with KRAS mutations that reside within the primary tumor (de novo).35,36 Subsequently, treatment with EGFR-targeting mAbs may shift the population dynamics of wild-type KRAS and mutant KRAS CRC cell clones within the primary tumor by selective pressure. Recent data underline tumor heterogeneity as one of the important mechanisms to acquired resistance to EGFR targeting. Thus, it will be important to develop diagnostic techniques that are sufficiently sensitive to detect a rare population of “resistance DNA” in the analyzed tissue. NGS offers the opportunity to assess tumor heterogeneity through the analysis of copy number and mutational heterogeneity.37 Recent methodologies couple high-throughput DNA sequencing with computational methods to make an assessment of the presence of distinct tumor clones within a tumor. Such methods may help the oncologist design a proper therapeutic targeting strategy to avoid recurrence or secondary resistance development. Unfortunately, this knowledge comes at an increased cost due to the requirement of increased sequencing “depth.” Part of the challenge will be to make such methodology affordable.

Circulating Tumor DNA and Cells
The development of novel diagnostic methods that are inexpensive, allowing for early detection and/or continuous assessment of the molecular profile of the (relapsed) tumor is highly desirable. Circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are good examples of novel biomarkers that can be identified in the blood of CRC patients and allow for the assessment of tumor burden and molecular profiling. These biomarkers are present in the majority of patients with metastatic disease.38-41 CTCs have been validated as an independent prognostic factor in cancer patients and a predictive biomarker for treatment efficacy, whereas ctDNA is just beginning to be recognized as a putative biomarker.42 CTC and ctDNA analysis are considered as real-time “liquid biopsy” due to easy sampling by obtaining blood rather than invasive tissue biopsy in cancer patients.43 The presence of CTCs in the blood of patients with mCRC has been known for some time. An overall reduced survival was seen in patients with advanced CRC and high levels of CTCs who were treated with cetuximab.44 The concentration of ctDNA is high in cancer patients since apoptotic and necrotic cells of the primary tumor release DNA into the bloodstream, where it tends to exist in the form of nucleosomes. CTCs and ctDNA can be studied as a surrogate to primary tumor tissue that allow for an assessment of genetic/epigenetic alterations present in the primary tumor.45 CTCs and ctDNA may complement each other in that they tend to predict the presence of one another in the blood.

In order to analyze CTCs they need to be enriched and detected through different strategies since they occur at a very low frequency of 1 CTC per million blood cells. A number of innovative technologies have been developed recently, including CRC microchips, filtration devices, quantitative reverse transcriptase-PCR assays, and automated microscopic systems that facilitate detection and analysis.43 Negative selection strategies based on the depletion of the leukocytes surrounding CTCs or high-speed scanning of all nucleated blood cells might be feasible approaches for an unbiased selection strategy of tumor cells, including those subsets of disseminating cells that may lack epithelial markers and cannot be selectively enriched for. However, the current gold standard for the detection of CTCs is the FDA-approved CellSearch system (Veridex), which provides prognostic value in metastatic breast cancer, prostate cancer, and CRC.41 Changes in the CTC count after therapy was correlated with response in CRC and in the neoadjuvant setting of breast cancer.44,46 Profiling of CTCs also provided a “drug resistance profile” of the primary tumor in a recent study.47 This suggests that responses of CTCs may provide additional prognostic/predictive information following cancer therapy.

The analysis of ctDNA is one step closer as a tool with which to study the molecular profile of tumors. Efforts have been made to develop a high-throughput assay for detection of KRAS mutations in the blood for patients treated with FOLFOX and FOLFIRI.48,49 A strong correlation was observed between the lack of response to cetuximab and the detection of mutated KRAS DNA in the blood. Thus, the presence of disseminated tumor cells and DNA in the cancer patient’s blood may serve as an important predictive biomarker for targeted therapy. Another methodology to assess the presence of oncogene mutations in plasma involves the use of picodroplet multiplex digital PCR (dPCR) that can facilitate simultaneous detection of multiple mutations in circulating DNA obtained from blood.50 Of 19 patients with known KRAS mutations, 14 were detected to have KRAS mutations in blood plasma by screening for the 7 most common mutations of codons 12 and 13 of the KRAS gene, using the multiplex dPCR technique. KRAS mutations were also identified in blood plasma from patients with primary tumors that had been genotyped as wild-type KRAS. Furthermore, exciting new technology has been developed that allows for NGS to be performed on a single CTC.51

The Future of EGFR Targeting in CRC
It is likely that EGFR will continue to be an impor­tant target for the treatment of CRC. Several novel EGFR-targeting mAbs are being evaluated for the treatment of CRC. Preclinical data suggest that targeting EGFR with a mixture of mAbs is superior at inhibiting the growth of cancer cells compared with cetuximab and panitumumab as single agents.52,53 One such mixture of 2 mAbs to EGFR, Sym004, is being subjected to a clinical trial in mCRC with wild-type KRAS. Improved methodology that allows for sensitive detection of KRAS-mutant CRC and the development of novel biomarkers that predict response to EGFR-targeting therapeutics are in great need. As such, NGS is a promising candidate methodology that can improve sensitivity with reduced cost compared with the currently used sequencing methodology. Furthermore, mutations of target genes outside of conventional “hot spots” may be detected with better sensitivity by NGS. The clinical relevance of such genetic aberrations has yet to be established, but such knowledge can help refine current inclusion criteria for EGFR targeting. It is clear that bioinformatics/computational software have to be codeveloped to help in identifying the presence of DNA in surrounding tissue and establish tumor heterogeneity. However, one potential problem is that the NGS concept encompasses numerous sequencing methodologies, while a single platform is preferable in clinical use. Thus, an appropriate methodology from the NGS cluster remains to be identified and thoroughly evaluated for clinical application.
Targeted therapy of today tends to focus on a single molecule. It is likely that future targeted therapies will become increasingly complex to improve treatment efficacy. Primary tumor heterogeneity, clonal selection, and acquired mutations are likely the causes of tumor resistance to such therapeutics. Subsequently, it is likely that continuous monitoring of disease response to therapy on the molecular level will be required. Methodology that allows for the detection of de novo or secondary mutations will be a prerequisite for successful therapy. As such, ctDNA and CTCs may offer additional (noninvasive) means to assess CRC and help prognosticate the response to EGFR-targeting and future targeted therapeutics.

The development of novel diagnostic tools that allow for the molecular profiling of CRC will help eliminate the chance of receiving contradictory diagnostic test results. Blood-based biomarkers can help in providing a direct real-time correlative between molecular events and response parameters. Further development of biomarkers that would predict a favorable response to EGFR targeting would benefit patients with CRC.

1. Jonker DJ, O’Callaghan CJ, Karapetis CS, et al. Cetuximab for the treatment of colorectal cancer. N Engl J Med. 2007;357:2040-2048.
2. Van Cutsem E, Peeters M, Siena S, et al. Open-label phase III trial of panitumumab plus best supportive care compared with best supportive care alone in patients with chemotherapy-refractory metastatic colorectal cancer. J Clin Oncol. 2007;25:1658-1664.
3. Mammano E, Belluco C, Sciro M. Epidermal growth factor receptor (EGFR): mutational and protein expression analysis in gastric cancer. Anticancer Res. 2006;26:3547-3550.
4. Nicholson RI, Gee JM, Harper ME. EGFR and cancer prognosis. Eur J Cancer. 2001;37(suppl 4):9S-15S.
5. Merla A, Goel S. Novel drugs targeting the epidermal growth factor receptor and its downstream pathways in the treatment of colorectal cancer: a systematic review. Chemother Res Pract. 2012;2012:387172.
6. Velho S, Moutinho C, Cirnes L, et al. BRAF, KRAS and PIK3CA mutations in colorectal serrated polyps and cancer: primary or secondary genetic events in colorectal carcinogenesis? BMC Cancer. 2008;8:255.
7. Beaven AW, Goldberg RM. Adjuvant therapy for colorectal cancer: yesterday, today, and tomorrow. Oncology (Williston Park). 2006;20:461-469.
8. Lievre A, Bachet JB, Boige V, et al. KRAS mutations as an independent prognostic factor in patients with advanced colorectal cancer treated with cetuximab. J Clin Oncol. 2008;26:374-379.
9. Allegra CJ, Jessup JM, Somerfield MR, et al. American Society of Clinical Oncology provisional clinical opinion: testing for KRAS gene mutations in patients with metastatic colorectal carcinoma to predict response to anti-epidermal growth factor receptor monoclonal antibody therapy. J Clin Oncol. 2009;27:2091-2096.
10. Engstrom PF, Arnoletti JP, Benson AB III, et al. NCCN Clinical Practice Guidelines in Oncology: colon cancer. J Natl Compr Canc Netw. 2009;7:778-831.
11. Lamparella NE, Saroya BS, Yang Z, et al. Contradictory KRAS mutation test results in a patient with metastatic colon cancer: a clinical dilemma in the era of personalized medicine. Cancer Biol Ther. 2013;14:699-702.
12. Qiu LX, Mao C, Zhang J, et al. Predictive and prognostic value of KRAS mutations in metastatic colorectal cancer patients treated with cetuximab: a meta-analysis of 22 studies. Eur J Cancer. 2010;46:2781-2787.
13. Bokemeyer C, Van Cutsem E, Rougier P, et al. Addition of cetuximab to chemotherapy as first-line treatment for KRAS wild-type metastatic colorectal cancer: pooled analysis of the CRYSTAL and OPUS randomised clinical trials. Eur J Cancer. 2012;48:1466-1475.
14. Sheng H, Shao J, Townsend CM Jr, et al. Phosphatidylinositol 3-kinase mediates proliferative signals in intestinal epithelial cells. Gut. 2003;52:1472-1478.
15. Philp AJ, Campbell IG, Leet C, et al. The phosphatidylinositol 3’-kinase p85­alpha gene is an oncogene in human ovarian and colon tumors. Cancer Res. 2001;61:7426-7429.
16. Khaleghpour K, Li Y, Banville D, et al. Involvement of the PI 3-kinase signaling pathway in progression of colon adenocarcinoma. Carcinogenesis. 2004;25:241-248.
17. Leystra AA, Deming DA, Zahm CD, et al. Mice expressing activated PI3K rapidly develop advanced colon cancer. Cancer Res. 2012;72:2931-2936.
18. Zhang J, Roberts TM, Shivdasani RA. Targeting PI3K signaling as a therapeutic approach for colorectal cancer. Gastroenterology. 2011;141:50-61.
19. Jhawer M, Goel S, Wilson AJ, et al. PIK3CA mutation/PTEN expression status predicts response of colon cancer cells to the epidermal growth factor receptor inhibitor cetuximab. Cancer Res. 2008;68:1953-1961.
20. Frattini M, Saletti P, Romagnani E, et al. PTEN loss of expression predicts cetuximab efficacy in metastatic colorectal cancer patients. Br J Cancer. 2007;97:1139-1145.
21. Shen Y, Yang J, Xu Z, et al. Phosphatase and tensin homolog expression related to cetuximab effects in colorectal cancer patients: a meta-analysis. World J Gastroenterol. 2012;18:2712-2718.
22. Tural D, Batur S, Erdamar S, et al. Analysis of PTEN, BRAF and PI3K status for determination of benefit from cetuximab therapy in metastatic colorectal cancer patients refractory to chemotherapy with wild-type KRAS [published online September 1, 2013]. Tumour Biol.
23. Douillard JY, Oliner KS, Siena S, et al. Panitumumab-FOLFOX4 treatment and RAS mutations in colorectal cancer. N Engl J Med. 2013;369:1023-1034.
24. Adams GP, Weiner LM. Monoclonal antibody therapy of cancer. Nat Biotechnol. 2005;23:1147-1157.
25. Jain A, Poonia B, So EC, et al. Tumour antigen targeted monoclonal antibodies incorporating a novel multimerisation domain significantly enhance antibody dependent cellular cytotoxicity against colon cancer. Eur J Cancer. 2013;49:3344-3352.
26. Ritter JH, Wick MR, Adesokan PN, et al. Assessment of clonality in cutaneous lymphoid infiltrates by polymerase chain reaction analysis of immunoglobulin heavy chain gene rearrangement. Am J Clin Pathol. 1997;108:60-68.
27. Inghirami G, Szabolcs MJ, Yee HT, et al. Detection of immunoglobulin gene rearrangement of B cell non-Hodgkin’s lymphomas and leukemias in fresh, unfixed and formalin-fixed, paraffin-embedded tissue by polymerase chain reaction. Lab Invest. 1993;68:746-757.
28. Meldrum C, Doyle MA, Tothill RW. Next-generation sequencing for cancer diagnostics: a practical perspective. Clin Biochem Rev. 2011;32:177-195.
29. Do H, Krypuy M, Mitchell PL, et al. High resolution melting analysis for rapid and sensitive EGFR and KRAS mutation detection in formalin fixed paraffin embedded biopsies. BMC Cancer. 2008;8:142.
30. Martinez DA, Nelson MA. The next generation becomes the now generation. PLoS Genet. 2010;6:e1000906.
31. Altimari A, de Biase D, De Maglio G, et al. 454 next generation-sequencing outperforms allele-specific PCR, Sanger sequencing, and pyrosequencing for routine KRAS mutation analysis of formalin-fixed, paraffin-embedded samples. Onco Targets Ther. 2013;6:1057-1064.
32. McCourt CM, McArt DG, Mills K, et al. Validation of next generation sequencing technologies in comparison to current diagnostic gold standards for BRAF, EGFR and KRAS mutational analysis. PloS One. 2013;8:e69604.
33. Querings S, Altmüller J, Ansén S, et al. Benchmarking of mutation diagnostics in clinical lung cancer specimens. PloS One. 2011;6:e19601.
34. Nowell PC. The clonal evolution of tumor cell populations. Science. 1976;194:23-28.
35. Misale S, Yaeger R, Hobor S, et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature. 2012;486:532-536.
36. Diaz LA Jr, Williams RT, Wu J, et al. The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature. 2012;486:537-540.
37. Ding L, Raphael BJ, Chen F, et al. Advances for studying clonal evolution in cancer. Cancer Lett. 2013;340:212-219.
38. Diehl F, Schmidt K, Durkee KH, et al. Analysis of mutations in DNA isolated from plasma and stool of colorectal cancer patients. Gastroenterology. 2008;135:489-498.
39. Diehl F, Schmidt K, Choti MA, et al. Circulating mutant DNA to assess tumor dynamics. Nat Med. 2008;14:985-990.
40. Holdhoff M, Schmidt K, Donehower R, et al. Analysis of circulating tumor DNA to confirm somatic KRAS mutations. J Natl Cancer Inst. 2009;101:1284-1285.
41. Allen JE, El-Deiry WS. Circulating tumor cells and colorectal cancer. Curr Co­lorectal Cancer Rep. 2010;6:212-220.
42. Dawson SJ, Tsui DW, Murtaza M, et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med. 2013;368:1199-1209.
43. A lix-Panabieres C, Schwarzenbach H, Pantel K. Circulating tumor cells and circulating tumor DNA. Annu Rev Med. 2012;63:199-215.
44. Kuboki Y, Matsusaka S, Minowa S, et al. Circulating tumor cell (CTC) count and epithelial growth factor receptor expression on CTCs as biomarkers for cetuximab efficacy in advanced colorectal cancer. Anticancer Res. 2013;33:3905-3910.
45. Schwarzenbach H, Hoon DS, Pantel K. Cell-free nucleic acids as biomarkers in cancer patients. Nat Rev Cancer. 2011;11:426-437.
46. Hou JM, Krebs MG, Lancashire L, et al. Clinical significance and molecular characteristics of circulating tumor cells and circulating tumor microemboli in patients with small-cell lung cancer. J Clin Oncol. 2012;30:525-532.
47. Gazzaniga P, Naso G, Gradilone A, et al. Chemosensitivity profile assay of circulating cancer cells: prognostic and predictive value in epithelial tumors. Int J Cancer. 2010;126:2437-2447.
48. Chen YF, Wang JY, Wu CH, et al. Detection of circulating cancer cells with K-ras oncogene using membrane array. Cancer Lett. 2005;229:115-122.
49. Yen LC, Yeh YS, Chen CW, et al. Detection of KRAS oncogene in peripheral blood as a predictor of the response to cetuximab plus chemotherapy in patients with metastatic colorectal cancer. Clin Cancer Res. 2009;15:4508-4513.
50. Taly V, Pekin D, Benhaim L, et al. Multiplex picodroplet digital PCR to detect KRAS mutations in circulating DNA from the plasma of colorectal cancer patients. Clin Chem. 2013;59:1722-1731.
51. Zhao L, Lu YT, Li F, et al. High-purity prostate circulating tumor cell isolation by a polymer nanofiber-embedded microchip for whole exome sequencing [published online March 26, 2013]. Adv Mater.
52. Pedersen MW, Jacobsen HJ, Koefoed K, et al. Sym004: a novel synergistic anti-epidermal growth factor receptor antibody mixture with superior anticancer efficacy. Cancer Res. 2010;70:588-597.
53. Koefoed K, Steinaa L, Søderberg JN, et al. Rational identification of an optimal antibody mixture for targeting the epidermal growth factor receptor. mAbs. 2011;3:584-595.

Uncategorized - January 3, 2014

Happy Holidays From the PMO Editorial Board

Dear Colleague, As we close out another year, we would like to thank you, our Personalized Medicine in Oncology reading community, for your support, encouragement, and loyal readership. We have relied on your guidance throughout our 2-year tenure to put forth the best possible journal addressing personalized medicine in all [ Read More ]

Editorial - January 3, 2014

Case Study: Lower-Risk Myelodysplastic Syndromes

At the 2013 conference of the Global Biomarkers Consortium, which took place October 4-6, 2013, in Boston, Massachusetts, Rami Komrokji, MD, from the H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, discussed the use of personalizing therapy in the management of myelodysplastic syndromes. Myelodysplastic syndromes (MDS) are a [ Read More ]