To compare the progression-free survival (PFS) using a treatment regimen selected by molecular profiling (MP) of a patient's tumor with the PFS for the most recent regimen on which the patient had experienced progression (ie, patient as his own control).

Patients with refractory metastatic cancer had tissue samples submitted for MP in two formats including formalin-fixed tissue for immunohistochemistry and fluorescent in situ hybridization assays and immediately frozen tissue for oligonucleotide microarray (MA) gene expression assays (all performed in a Clinical Laboratory Improvement Amendments [CLIA] –certified laboratory). The MP approach was deemed of clinical benefit for the individual patient who had a PFS ratio (PFS on MP-selected therapy/PFS on prior therapy) of ≥ 1.3.

In 86 patients who had MP attempted, there was a molecular target detected in 84 (98%). Sixty-six of the 84 patients were treated according to MP results. Eighteen (27%) of 66 patients had a PFS ratio of ≥ 1.3 (95% CI, 17% to 38%; one-sided, one-sample P = .007). Therefore, the null hypothesis (that ≤ 15% of this patient population would have a PFS ratio of ≥ 1.3) was rejected.

It is possible to identify molecular targets in patients' tumors from nine different centers across the United States. In 27% of patients, the MP approach resulted in a longer PFS on an MP-suggested regimen than on the regimen on which the patient had just experienced progression. Issues to be considered in interpretation of this study include limited prior experience with patients as their own controls as a study end point and overall patient attrition.

Eventually, most patients with metastatic cancer run out of treatment options. With the increasing ability of standard and molecular techniques to measure potential targets in patients' tumors, for which we already have available noninvestigational agents (eg, estrogen receptor by immunohistochemistry [IHC], HER2/neu by fluorescent in situ hybridization [FISH]), one question involves how often such targets are actually present in patients' refractory malignancies.

In a 2006 feasibility study,1 we examined tumors for potential targets from patients who had experienced progression on multiple standard therapies. That work in 186 patients demonstrated that using IHC and oligonucleotide microarray (MA), one can consistently receive and process high-quality specimens. In addition, it was surprising to consistently find a target for which there is a potential standard therapeutic agent in patients' tumors, even though the patients had experienced progression on multiple prior therapies. Of course, simply finding a potential target present in a patient's tumor does not imply that the patient would respond to a therapeutic agent against that target. Therefore, the current prospective multicenter study was designed.

Study Objectives

Figure 1 details the Consolidated Standards of Reporting Trials (CONSORT) diagram demonstrating the flow of the 106 patients who consented and were evaluated for the study in nine different sites. The primary objective for the study was to compare the progression-free survival (PFS) using therapy selected by molecular profiling (MP) of a patient's tumor (period B) with the PFS for the most recent therapy on which the patient had just experienced progression (period A; Fig 2A). If the PFS of period B/PFS of period A ratio was ≥ 1.3, then MP-selected therapy was defined as having benefit for the patient.

Secondary objectives included determining the frequency with which MP by IHC/FISH and MA yielded a target against which there is a commercially available therapeutic agent and determining the response rate (Response Evaluation Criteria in Solid Tumors [RECIST]) and percentage of patients without progression or death at 4 months.

Study Design

The hypothesis for this study was that using treatment suggested by an MP approach would favorably change the clinical course for an individual patient. This multicenter, prospective, single-arm trial was conducted in patients with refractory metastatic cancer to compare the PFS using a treatment regimen selected by MP with the PFS (really time to tumor progression because death is excluded as an event)2 for the most recent regimen on which the patient had experienced progression (ie, using patients as their own control2,3). Patients were enrolled at nine sites throughout the United States. The study was conducted in accordance with the Declaration of Helsinki and was approved by institutional review boards.

Figure 2B outlines the mechanics of the study. Patients provided consented and were screened, and eligibility was verified by one of two oncologist physician monitors (E.W. or C.F.). Importantly, those physicians confirmed that the patients had experienced progression on their prior therapy, and PFS (time to progression) in days was documented. A tumor biopsy was then performed. The tumor was assayed using IHC/FISH and MA analyses.

The results of the IHC/FISH and MA analyses were reviewed by two study physicians (D.D.V.H. and E.W.). The results were considered in the context of the patient's prior treatment history and comorbidities, and the identified targets were ranked according to the protocol-specified algorithm as follows: first priority, IHC/FISH and MA indicated same target; next priority, IHC-positive result alone; and last priority, MA-positive result alone.

On the basis of this algorithm and the possible therapy suggested by the target present (Appendix Table A1, online only, which was generated through an extensive review of the literature and our prior experience in a retrospective feasibility study1), the specific therapy was suggested to the treating investigator, and the patient was treated according to the package insert recommendations. If two targets were identified that were known to be a well-tolerated combination (based on a literature-based documented regimen contained in an appendix in the protocol), that combination was suggested to the treating investigator. Disease status by tumor imaging was scheduled and was assessed every 8 weeks, and clinical assessments and laboratory studies were planned before each cycle. Adverse effects were graded according to the National Cancer Institute Common Terminology Criteria of Adverse Events (version 3.0).

Patient Eligibility

Eligibility criteria included the following: informed consent and Health Insurance Portability and Accountability Act authorization; any histologic type of metastatic cancer; progression by RECIST criteria on at least two prior regimens for advanced disease (or progression by prostate-specific antigen according to Prostate-Specific Antigen Working Group or by CA-125 according to Gynecologic Cancer Intergroup Response Criteria); ability to undergo a biopsy or surgical procedure to obtain tumor; age ≥ 18 years; life expectancy of more than 3 months; Eastern Cooperative Oncology Group performance status of 0 to 1; measurable or evaluable disease; refractory to last line of therapy (documented disease progression under last treatment; received ≥ 6 weeks of last treatment; discontinued last treatment for progression); adequate organ and bone marrow function; adequate methods of birth control; and adequately controlled CNS metastases, if present. Importantly, before MP was performed, the treating investigator had to designate the chemotherapeutic agent(s) that he or she would treat the patient with if no MP results were available (Appendix Tables A2 and A3, online only).

MP of Patient Samples

Biopsies were performed at local investigators' sites through a heterogeneous group of different surgical techniques including incisional biopsies, excisional biopsies, and needle biopsies. For needle biopsies, two to three 18-gauge needle core biopsies were performed. For DNA MA analysis, tissue was immediately frozen and shipped on dry ice to a central Clinical Laboratory Improvement Amendments–certified laboratory (Caris Life Sciences, Phoenix, AZ). For IHC, paraffin blocks were shipped on cold packs. For IHC studies, the formalin-fixed paraffin-embedded tumor samples had sections submitted and processed for standard IHC or FISH testing for 11 proteins (Appendix Table A1 and Appendix, online only).

All slides were evaluated semiquantitatively on a scale of 0 (no staining) to 4+ and by the percentage of the tumor cells showing the reactivity by a single pathologist (R.P.) who confirmed the original diagnosis and interpreted each of the immunohistochemical stains. The methodology for performing the MA and the cut points are detailed in the Appendix. The arrays contain probes for 51 genes for which there is a therapeutic agent that could potentially interact with that gene. Those 51 genes are listed in Appendix Table A1.

The chips were hybridized for 16 to 18 hours at 60°C, washed to remove nonstringently hybridized probe, and scanned on an Agilent Microarray Scanner (Agilent, Santa Clara, CA). Fluorescence intensity data were extracted, normalized, and analyzed using Agilent Feature Extraction Software. A gene's expression was judged as different from its reference based on the significance of the extent of change at the level of P ≤ .001.

Statistical Considerations and Methods

The protocol called for a planned 92 enrolled patients, of whom an estimated 64 would be treated with therapy assigned by MP. The other 28 patients were projected to not have MP results available because of inability to biopsy, no target identified by the MP, or deteriorating performance status.

A sample size of 64 patients was required to reject the hypothesis that the PFS ratio was greater than 1.3 in 15% of patients receiving MP treatment, with an α risk of 5% and a power of 90%, under the assumption that the true rate of MP response is 30%. Time-to-event data were summarized using the Kaplan-Meier method and compared using the log-rank test; continuous data were compared using the nonparametric Mann-Whitney U test; categorical data were compared using the χ2 or Fisher's exact test, as appropriate. No imputation of missing data or adjustment for multiplicity of comparisons of clinical data was performed. All of the reported significance levels are two-sided, and P < .05 was considered to represent a significant correlation. Because of the small sample size, a multivariable analysis adjusting for heterogeneity of disease type, disease history, and prognostic factors was not considered.

Patient Distribution

Of the 106 patients who consented and were evaluated, 20 did not proceed with MP for the reasons outlined in Figure 1 (mainly worsening condition or withdrawing their consent because they did not want any additional therapy). Eighteen patients were not treated after MP (again mainly because of worsening condition or withdrawing consent because of not wanting any additional therapy). Of the 68 patients treated, 66 were treated according to MP results, and two were treated not according to MP results (one patient was treated with another agent because the clinician caring for the patient felt a sense of urgency to treat, and the other patient was treated with another agent because the insurance company would not cover the MP-suggested treatment).

Patient Characteristics

Table 1 lists the characteristics of the 66 patients who had MP performed on their tumors and who received treatment according to the MP results. The majority of patients were female, with a median age of 60 years (range, 27 to 75 years) and an Eastern Cooperative Oncology Group performance status of 1. Of note, 20 patients experienced progression on prior phase I therapies.


Table 1. Patient Demographics and Clinical Characteristics

Table 1. Patient Demographics and Clinical Characteristics

Characteristic No. of Patients(N = 66) %
    Female 43 65
    Male 23 35
Age, years
    Median 60
    Range 27-75
No. of prior treatment regimens
    2-4* 35 53
    5-13 25 38
    0 18 27
    1 48 73
Tumor type
    Breast 18 27
    Colorectal 11 17
    Ovarian 5 8
    Miscellaneous 32 48
        Prostate 4 6
        Lung 3 5
        Melanoma 2 3
        Small cell (esophageal/retroperitoneal) 2 3
        Cholangiocarcinoma 1 1.5
        Mesothelioma 2 3
        Head and neck 2 3
        Pancreas 2 3
        Pancreas neuroendocrine 1 1.5
        Unknown primary (SCC) 1 1.5
        Gastric 1 1.5
        Duodenal 1 1.5
        Peritoneal pseudomyxoma 1 1.5
        Anal canal (SCC) 1 1.5
        Vagina (SCC) 1 1.5
        Cervix 1 1.5
        Renal 1 1.5
        Eccrine sweat adenocarcinoma 1 1.5
        Salivary gland adenocarcinoma 1 1.5
        Soft tissue sarcoma (uterine) 1 1.5
        GIST (gastric) 1 1.5
        Thyroid anaplastic 1 1.5

Abbreviations: ECOG PS, Eastern Cooperative Oncology Group performance status; SCC, squamous cell carcinoma; GIST, GI stromal tumor.

*Six patients (9%) had only one prior regimen because there was no approved active second-line therapy available.

Tumor types included breast (n = 18, 27%), colorectal (n = 11, 17%), and ovarian (n = 5, 8%); 32 patients (48%) were in the miscellaneous category with many rare types of cancer. The cohort of patients with breast cancer was particularly heavily pretreated, with a median of five prior lines of systemic treatment.

Regarding the primary end point of the study (PFS ratio of ≥ 1.3), in the 66 patients treated according to MP results, 18 patients (27%; 95% CI, 17% to 38%; one-sided, one-sample nonparametric test, P = .007) had a PFS ratio of ≥ 1.3. The null hypothesis was that ≤ 15% of this patient population would have a PFS ratio of ≥ 1.3. Therefore, the null hypothesis is rejected, and our conclusion is that the MP approach is promising.

Critical to ascertainment of the PFS ratio is the determination of the time to progression interval before any patient's entry onto the study. Details on these ascertainments are provided in the Appendix. Tumor assessment by imaging was schedule every 8 weeks, and clinical assessment and laboratory tests were planned before each cycle.

Figure 3 details the actual comparison of PFS on MP therapy versus PFS (time to progression) on the patient's last prior therapy for the 18 patients with a PFS ratio of ≥ 1.3. The median PFS ratio is 2.9 (range, 1.3 to 8.15).

By tumor type, a PFS ratio of ≥ 1.3 was achieved in eight (44%) of 18 patients with breast cancer, four (36%) of 11 patients with colorectal cancer, one (20%) of five patients with ovarian cancer, and five (16%) of 32 patients with miscellaneous tumor types (miscellaneous tumor types with PFS ratio ≥ 1.3 included one of three patients with non–small-cell lung cancer, one of three patients with cholangiocarcinoma, one of two patients with peritoneal mesothelioma, one of one patient with eccrine sweat gland tumor, and one of one patient with GI stromal tumor [gastric]).

Table 2 lists the treatments that the 18 patients with PFS ≥ 1.3 received based on MP. Overall, 14 patients were treated with suggested combinations, and four patients were treated with single agents. The reader is cautioned that in some cases, these treatments might represent off-label uses for these standard agents.


Table 2. Treatment Received by 18 Patients With PFS ≥ 1.3(based on molecular profiling)

Table 2. Treatment Received by 18 Patients With PFS ≥ 1.3(based on molecular profiling)

Tumor Type Therapy Received
Breast Diethylstilbestrol
Breast NAB paclitaxel + trastuzumab
Breast NAB paclitaxel + gemcitabine
Breast Letrozole + capecitabine
Breast Oxaliplatin + fluorouracil + trastuzumab
Breast Gemcitabine + pemetrexed
Breast Doxorubicin
Breast Exemestane
Colorectal Irinotecan + sorafenib
Colorectal Temozolomide + bevacizumab
Colorectal Sunitinib + mitomycin
Colorectal Temozolomide + sorafenib
Ovarian Lapatinib + tamoxifen
NSCLC Cetuximab + irinotecan
Cholangiocarcinoma Cetuximab + irinotecan
Mesothelioma Gemcitabine + etoposide
Eccrine sweat gland Sunitinib
GIST Cetuximab + gemcitabine

Abbreviations: PFS, progression-free survival; NAB, nanoparticle albumin bound; NSCLC, non–small-cell lung cancer; GIST, GI stromal tumor.

Regarding the secondary end points, MP of a patient's tumor yielded a target in 84 (98%) of 86 patients in whom MP was attempted. Broken down by methodology, 83 (97%) of 86 patients yielded a target by IHC/FISH, and 81 (94%) of 86 patients yielded a target by MA. Of note, RNA was tested for integrity by assessing the ratio of 28S to 18S ribosomal RNA on an Agilent BioAnalyzer. Eighty-three (97%) of 86 specimens had ratios of ≥ 1 and gave high intrachip reproducibility ratios. This demonstrates that one can have good collection and shipment of patients' specimens throughout the United States and obtain excellent technical results.

Responses by RECIST criteria in 66 patients included one complete response (breast cancer) and five partial responses (breast cancer, n = 2; ovarian cancer, n = 1; rectal cancer, n = 1; non–small-cell lung cancer, n = 1), for an overall response rate of 10%. Fourteen (21%) of 66 patients were without progression at 4 months.

In an exploratory analysis, we created a waterfall plot for all patients for maximum percent change in the summed diameters of target lesions with respect to baseline diameters. Demonstrated in Figure 4 are the patients who experienced progression and the patients who had some shrinkage of their tumor sometime during their course. As can be seen, there is some shrinkage of tumors in more than 47% of patients (in whom two or more evaluations were completed).

A second exploratory analysis of the overall survival for the 18 patients with a PFS ratio of ≥ 1.3 versus the overall survival of all 66 patients was performed. This was performed to help determine whether, in this pilot trial, the PFS ratio had some other possible clinical relevance. The overall survival for the 18 patients with a PFS ratio of ≥ 1.3 was 9.7 months, compared with 5 months for all 66 patients (Mantel-Cox log-rank, P = .026). This exploratory analysis indicated that the PFS ratio correlates with the clinical parameter of survival.

We also examined the relationship between what therapy the clinician would have selected to treat the patient and what the MP results suggested. There was no relationship between the two. More specifically, no complete matches for the 18 patients with a PFS ratio ≥ 1.3 were noted (Appendix Table A2).


There were no treatment-related deaths, but nine treatment-related serious adverse events occurred, including anemia (n = 2), neutropenia (n = 2), dehydration (n = 1), pancreatitis (n = 1), nausea (n = 1), vomiting (n = 1), and febrile neutropenia (n = 1). Only one patient (1.5%) was discontinued at the patient's request as a result of a treatment-related adverse event (grade 2 fatigue).

The conclusions from this prospective multicenter pilot study include that it is possible to measure molecular targets in patients' tumors from nine different centers across the United States with good quality and sufficient tumor collection and to suggest a treatment regimen based on those results and that this MP approach resulted in a longer PFS for patients on an MP-suggested regimen than on the regimen the patients had just experienced progression on for 27% of the patients (95% CI, 17% to 38%; P = .007). The results also alert us to the fact that often, patients with refractory cancers can commonly have simple targets (such as estrogen receptor) for which we have therapies that may provide benefit.

There are some important issues that need to be considered in the interpretation of this study. First, not a lot of experience exists with PFS ratio (patients as their own controls) as a clinical trial end point.2,3 There can be ascertainment bias, with the PFS ratio influenced by frequency of tumor evaluation in the control and evaluation periods. For our analysis of times of evaluation for period A versus period B, we had no evidence that there was an ascertainment bias.

Second, the trial was not randomized. We did not feel that the trial should be randomized in this multitumor type pilot setting. A future randomized trial testing MP versus a physician's choice would most appropriately be done in patients with one histologic type of cancer. Third, we worry about patient attrition, with 106 patients who consented and were evaluated for the study but only 66 actually being treated based on MP results. Overall, of the 40 patients lost, 30 (75%) were lost as a result of worsening condition or withdrawal. Exploring this MP approach earlier in the disease process would be of interest.

Another potential issue with the trial is that the selection of a commercially available agent to suggest for treatment against a particular target was based on an extensive literature review and prior experience in a feasibility study. Obviously, using studies from the literature often relies on retrospective review of information, and this is challenging, as demonstrated by the recent work with mutated ras defining the possibility of response to EGFR interactive monoclonal antibodies for patients with colorectal cancer. There is a tremendous need for additional prospective evaluation of these biomarkers to determine response or lack of response.

Future directions for this work should include initiating disease-specific trials and introducing new MP methodologies with additional credentialed tests such as K-Ras and B-RAF sequencing, comparative genomic hybridization (CGH), NextGen sequencing, and other techniques. In the last few months, there has been a substantial increase in new targeted agents being introduced,46 giving us more agents to match targets that can be found in patients' tumors. In addition, there are even more uses for agents we already have against specific targets (eg, use of trastuzumab for HER2/neu-positive advanced gastric cancers).7

The current trial used fairly simplistic IHC/FISH plus MA approaches looking for individual targets in a patient's tumor (not signatures) to try to prospectively select treatments for patients with refractory cancers. Of course, IHC and FISH have been used for years to select patients for hormonal and other therapies (eg, trastuzumab). For MA, excellent reviews and commentary have been written on the subject of gene expression arrays and their potential and actual use in predicting clinical response to chemotherapy.810 Currently, the majority of trials have been retrospective correlations of gene signatures in responders versus nonresponders.1115 Other studies using MA have begun reporting clinical correlations with expression of one or a few drug targets. In addition, there are some excellent prospective clinical trials already reported and others under way.1618

The present study and the previously mentioned and other studies have demonstrated that one can molecularly profile patients' tumors from many centers with excellent quality control. As more targets are discovered and more targeted agents become available, it is likely that the chances of finding something that will have activity in changing the clinical outcome for an individual patient will be increased.

© 2010 by American Society of Clinical Oncology

See accompanying editorial on page 4869

Written on behalf of the Bisgrove Study Group.

Supported by a grant from the Stardust Foundation, Scottsdale, AZ, and by the Scottsdale Healthcare Foundation, Scottsdale, AZ.

Presented in part at the 100th Annual Meeting of the American Association for Cancer Research, April 18-22, 2009, Denver, CO.

Terms in blue are defined in the glossary, found at the end of this article and online at

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

Clinical trial information can be found for the following: NCT00530192.

Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a “U” are those for which no compensation was received; those relationships marked with a “C” were compensated. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.

Employment or Leadership Position: David M. Loesch, Caris Life Sciences (C); William Sutherland, AAIPharma (C); Arlet Alarcon, Caris Life Sciences (C); David Mallery, Caris Life Sciences (C); Robert Penny, Caris Life Sciences (C) Consultant or Advisory Role: Daniel D. Von Hoff, Caris Life Sciences (C); Joseph J. Stephenson Jr, Caris Life Sciences (C); Peter Rosen, Caris Life Sciences (C); Stephen Anthony, Caris Life Sciences (C); Nina Cantafio, Caris Life Sciences (C); Robert Penny, Caris Life Sciences (C) Stock Ownership: Daniel D. Von Hoff, Caris Life Sciences; Arlet Alarcon, Caris Life Sciences; David Mallery, Caris Life Sciences; Robert Penny, Caris Life Sciences, Mid America Clinical Laboratories Honoraria: Stephen Anthony, Caris Life Sciences Research Funding: None Expert Testimony: None Other Remuneration: None

Conception and design: Daniel D. Von Hoff, David M. Loesch, Mitesh J. Borad, Michael Bittner, Arlet Alarcon, David Mallery, Robert Penny

Administrative support: Susan Brown, Nina Cantafio

Provision of study materials or patients: Daniel D. Von Hoff, Joseph J. Stephenson Jr, Peter Rosen, David M. Loesch, Mitesh J. Borad, Stephen Anthony, Gayle Jameson, Susan Brown, Donald A. Richards, Tom R. Fitch, Ernesto Wasserman

Collection and assembly of data: Daniel D. Von Hoff, Joseph J. Stephenson Jr, David M. Loesch, Stephen Anthony, Nina Cantafio, Tom R. Fitch, Ernesto Wasserman, Cristian Fernandez, Arlet Alarcon

Data analysis and interpretation: Daniel D. Von Hoff, Joseph J. Stephenson Jr, David M. Loesch, Stephen Anthony, Tom R. Fitch, Ernesto Wasserman, Cristian Fernandez, Sylvan Green, William Sutherland, Robert Penny

Manuscript writing: Daniel D. Von Hoff, Joseph J. Stephenson Jr, Nina Cantafio, William Sutherland

Final approval of manuscript: Daniel D. Von Hoff, Joseph J. Stephenson Jr, Peter Rosen, David M. Loesch, Mitesh J. Borad, Stephen Anthony, Gayle Jameson, Susan Brown, Nina Cantafio, Donald A. Richards, Tom R. Fitch, Ernesto Wasserman, Cristian Fernandez, William Sutherland, Michael Bittner, Arlet Alarcon, David Mallery, Robert Penny

Glossary Terms

Raf proteins (Raf-1, A-Raf, B-Raf) are intermediate to Ras and MAPK in the cellular proliferative pathway. Raf proteins are typically activated by Ras via phosphorylation, and activated Raf proteins in turn activate MAPK via phosphorylation. However, Raf proteins may also be independently activated by other kinases.

CGH (comparative genomic hybridization):

A molecular cytogenetic method of screening tumor samples for genetic changes showing characteristic patterns for copy number changes (mutations cannot be detected by CGH) at chromosomal and subchromosomal levels. Alterations in patterns are classified as DNA gains and losses. The method consists of isolating DNA from tumors and healthy tissues (reference) and labeling each with a different “color” or fluor. The two samples are then mixed and hybridized to normal metaphase chromosomes. In the case of array or matrix CGH, the hybridization mixing is done on a slide with thousands of DNA probes. The detection system is varied, but basically determines the color ratio along the chromosomes to determine DNA regions that might be gained or lost in tumor samples.

CLIA certified:

Clinical Laboratory Improvement Amendments put in place by Congress in 1988 to establish quality standards in laboratory testing.

FISH (fluorescent in situ hybridization):

In situ hybridization is a sensitive method that is generally used to detect specific gene sequences in tissue sections or cell preparations by hybridizing the complementary strand of a nucleotide probe to the sequence of interest. FISH uses a fluorescent probe to increase the sensitivity of in situ hybridization.


The application of antigen-antibody interactions to histochemical techniques. Typically, a tissue section is mounted on a slide and is incubated with antibodies (polyclonal or monoclonal) specific to the antigen (primary reaction). The antigen-antibody signal is then amplified using a second antibody conjugated to a complex of peroxidase-antiperoxidase (PAP), avidin-biotin-peroxidase (ABC) or avidin-biotin alkaline phosphatase. In the presence of substrate and chromogen, the enzyme forms a colored deposit at the sites of antibody-antigen binding. Immunofluorescence is an alternate approach to visualize antigens. In this technique, the primary antigen-antibody signal is amplified using a second antibody conjugated to a fluorochrome. On UV light absorption, the fluorochrome emits its own light at a longer wavelength (fluorescence), thus allowing localization of antibody-antigen complexes.


The Ras gene family consists of H-Ras, N-Ras, and K-Ras. The Ras proteins are typically small triphosphate-binding proteins, and are the common upstream molecule of several signaling pathways that play a key role in signal transduction, which results in cellular proliferation and transformation.

NextGen Sequencing:

The first methodologic papers describing relatively rapid DNA sequencing were produced by Sanger et al (1977). NextGen sequencing is a subsequently developed non-Sanger method that can be done with greater speed.

Null hypothesis:

The statistical hypothesis that the observed difference is due to chance alone.

Oligonucleotide microarray (MA) gene expression assays:

Also known as biochip, DNA chip, or gene array, cDNA microarray technology allows for identification of gene expression levels in a biologic sample. cDNAs or oligonucleotides, each representing a given gene, are immobilized on a small chip or nylon membrane, tagged, and serve as probes that will indicate whether they are expressed in biologic samples of interest. Thus, the simultaneous expression of thousands of genes can be monitored simultaneously.

1. DD Von Hoff, R Penny, S Shack , etal : Frequency of potential therapeutic targets identified by immunohistochemistry (IHC) and DNA microarray (DMA) in tumors from patients who have progressed on multiple therapeutic agents J Clin Oncol 24: 138s,2006 suppl abstr 3071 Google Scholar
2. N Dhani, D Tu, DJ Sargent , etal : Alternate endpoints for screening phase II studies Clin Cancer Res 15: 18731882,2009 Crossref, MedlineGoogle Scholar
3. DD Von Hoff : There are no bad anticancer agents, only bad clinical trial designs: Twenty-first Richard and Hinda Rosenthal Foundation Award Lecture Clin Cancer Res 4: 10791086,1998 MedlineGoogle Scholar
4. J O'Shaughnessy, C Osborne, J Pippen , etal : Efficacy of BSI-201, a poly (ADP-ribose) polymerase-1 (PARP1) inhibitor, in combination with gemcitabine/carboplatin (G/C) in patients with metastatic triple-negative breast cancer (TNBC): Results of a randomized phase II trial J Clin Oncol 27: 6s,2009 suppl abstr 3 LinkGoogle Scholar
5. I Puzanov, KL Nathanson, PB Chapman , etal : PLX4032, a highly selective V600EBRAF kinase inhibitor: Clinical correlation of activity with pharmacokinetic and pharmacodynamic parameters in a phase I trial J Clin Oncol 27: 466s,2009 suppl abstr 9021 Google Scholar
6. DD Von Hoff, PM LoRusso, CM Rudin , etal : Inhibition of the hedgehog pathway in advanced basal-cell carcinoma N Engl J Med 361: 11641172,2009 Crossref, MedlineGoogle Scholar
7. E Van Cutsem, Y Kang, H Chung , etal : Efficacy results from the ToGA trial: A phase III study of trastuzumab added to standard chemotherapy (CT) in first-line human epidermal growth factor receptor 2 (HER2)-positive advanced gastric cancer (GC) J Clin Oncol 27: 798s,2009 suppl abstr LBA4509 LinkGoogle Scholar
8. JD Minna, L Girard, Y Xie : Tumor mRNA expression profiles predict responses to chemotherapy J Clin Oncol 25: 43294336,2007 LinkGoogle Scholar
9. F Andre, C Mazouni, GN Hortobagyi , etal : DNA arrays as predictors of efficacy of adjuvant/neoadjuvant chemotherapy in breast cancer patients: Current data and issues on study design Biochim Biophys Acta 1766: 197204,2006 MedlineGoogle Scholar
10. T Sørlie, CM Perou, C Fan , etal : Gene expression profiles do not consistently predict the clinical treatment response in locally advanced breast cancer Mol Cancer Ther 5: 29142918,2006 Crossref, MedlineGoogle Scholar
11. JC Chang, A Makris, MC Gutierrez , etal : Gene expression patterns in formalin-fixed, paraffin-embedded core biopsies predict docetaxel chemosensitivity in breast cancer patients Breast Cancer Res Treat 108: 233240,2008 Crossref, MedlineGoogle Scholar
12. HK Dressman, A Berchuck, G Chan , etal : An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer J Clin Oncol 25: 517525,2007 LinkGoogle Scholar
13. C Kihara, T Tsunoda, T Tanaka , etal : Prediction of sensitivity of esophageal tumors to adjuvant chemotherapy by cDNA microarray analysis of gene-expression profiles Cancer Res 61: 64746479,2001 MedlineGoogle Scholar
14. M Del Rio, F Molina, C Bascoul-Mollevi , etal : Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan J Clin Oncol 25: 773780,2007 LinkGoogle Scholar
15. S Smith, D Su, IA Rigault de la Longrais , etal : ERCC1 genotype and phenotype in epithelial ovarian cancer identify patients likely to benefit from paclitaxel treatment in additional to platinum-based therapy J Clin Oncol 25: 51725179,2007 LinkGoogle Scholar
16. K Iwao-Koizumi, R Matoba, N Ueno , etal : Prediction of docetaxel response in human breast cancer by gene expression profiling J Clin Oncol 23: 422431,2005 LinkGoogle Scholar
17. M Cobo, D Isla, B Massuti , etal : Customizing cisplatin based on quantitative excision repair cross-complementing 1 mRNA expression: A phase III trial in non–small-cell lung cancer J Clin Oncol 25: 27472754,2007 LinkGoogle Scholar
18. ES Kim, RS Herbst, JJ Lee , etal : Phase II randomized study of biomarker-directed treatment for non-small cell lung cancer (NSCL): The BATTLE (Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination) clinical trial program J Clin Oncol 27: 412s,2009 suppl abstr 8024 Google Scholar


We thank our patients and their families for their participation and for their trust. This work is dedicated to the memory of Sylvan Green, MD, a valued friend and biostatistician colleague who passed away during the conduct of this study, and Deborah Bisgrove, a brave and compassionate woman who fought hard to stay with family and friends.

The following colleagues worked hard to make this study possible: Translational Genomics Research Institute (TGen) Clinical Research Service: Stephen P. Anthony, DO; Mitesh J. Borad, MD; Ramesh K. Ramanathan, MD; Raoul K. Tibes, MD, PhD; Glen Weiss, MD; Gayle S. Jameson, MSN, ACNP-BC, AOCN; Terri J. Stone, MSN, FNP-BC, AOCNP; Katy Schroeder, RN, BSN, OCN; Christian Lawson, RN; Patricia Hopper, RN; Erica White; and Ranay Yarian; Cancer Centers of the Carolinas: Joe Stephenson, MD; William J. Edenfield, MD; W. Larry Gluck, MD; Julie C. Martin, RN, FNP; Lisa Johnson, RN; Lauren Baber; and Brandy Corley; Mayo Clinic Arizona: Tom Fitch, MD; Donald W. Northfelt, MD; Michael K. Gornet, MD; Stacey Jones, BS, RN; and Debbie Gallagher; Tower Cancer Research: Peter Rosen, MD; Robert W. Decker, MD; Julie A. Dunhill, MD; Leland M. Green, MD; Solomon I. Hamburg, MD, PhD; David M.J. Hoffman, MD; Philomena F. McAndrew, MD; Dorothy J. Park, MD; Barry E. Rosenbloom, MD; Fred P. Rosenfelt, MD; Wendy Batista, RN, BSN; Barbara Newman, RN; and Elizabeth Tran; South Texas Oncology Hematology: Lon Smith, MD; Ronald L. Drengler, MD; Lisa M. Fichtel, MD; Allison M. Garner, MD; Steven P. Kalter, MD; Amy S. Lang, MD; Gladys I. Rodriguez, MD; Luis C. Rodriguez, MD; Scott C. Ulmer, MD; Muralidhar Beeram, MD; Annelies Burnley, BSN, RN, OCN; Katherine S. DeLeom, BSN, RN; and Pam Sparks; Central Indiana Cancer Center: David Loesch, MD; Magaral S. Murali, MD; Andrew R. Greenspan, MD; James K. Hwang, MD; Hillary H. Wu, MD; Jennifer K. Morgan, MD; Keith W. Logie, MD; Thomas L. Whittaker, MD; Elsayed Aly, MD; Sead Beganovic, MD; Melody Sands, NP; Lynn Robbin, NP; Yvonne Lafary, Clinical RN; LeaEtta Hyer, RN; Vicki Yaggi, RN; Katrina Yaggi; and Ahran Lee; Clearview Cancer Institute: Jeremy Hon, MD; Marshall Schreeder, MD; John Waples, MD; Philip McGee, MD; Brian Matthews, MD; Manh Dang, MD; Surrinder Dang, MD; Frank Kelly, MD; Sammy Becdach, MD; Purvi Shah, MD; Kelly Herndon, RN, BSN; and Leslie Smoot; Louis-Warshaw Prostate Cancer Center: David Agus, MD; Mahul Amin, MD; Mitchell Gross, MD; Daniel Luthringer, MD; Ronald Natale, MD; Sonya Sakowsky; Tina Tolbert; and Koo Nguyen; Texas Oncology at Tyler: Don Richards, MD; William J. Hyman, MD; Svetislava J. Vukelja, MD; Thomas Gregory, MD; Aparna R. Chacko, MD; Frank T. Ward, MD; Linda Dunklin; and Susan Kerr.

Details on Ascertainment of the Time to Progression to Document the Progression-Free Survival Ratio

Time to progression under the last line of treatment was documented by imaging in 58 patients (88%). Among these 58 patients, documentation by imaging alone occurred in 49 patients (74%), and documentation by imaging with tumor markers occurred in nine patients (14%; ovarian cancer, n = 3; colorectal, n = 1; pancreas, n = 1; prostate, n = 3; breast, n = 1). Patients with clinical proof of progression were accepted when the investigator reported the assessment of palpable and measurable lesions (ie, inflammatory breast cancer, skin/subcutaneous nodules, or lymph nodes), which occurred in six patients (9%). One patient (2%) with prostate cancer was included with progression by tumor marker. In one patient (2%) with breast cancer, the progression was documented by increase of tumor marker and worsening of bone pain.

The time to progression achieved with a treatment based on molecular profiling was documented by imaging in 44 patients (67%) and by clinical events detected between two scheduled tumor assessments in 20 patients. These clinical events were reported as serious adverse events related to disease progression (eg, death, bleeding, bowel obstruction, hospitalization), and the dates of reporting were censored as progression of disease. The remaining two patients were censored at the date of last follow-up.

Immunohistochemistry/Fluorescent In Situ Hybridization Methods and Cut Points

Immunohistochemistry (IHC) was considered positive for target if staining was ≥ 2+ in ≥ 30% of cells. For IHC, rather than just look for a simple positive, we wanted to raise the stringency of the cut point such that it would be a significant or more demonstrative positive. The hypothesis was that if the mechanism of the target was functioning in a significant proportion of the tumor, then a higher positive would be more likely to be associated with a therapy that would affect the time to progression. We determined the cut point to be 2+ reactivity from a scale of 0 to 4+, and 2+ or greater reactivity had to be present in at least 30% of the tumor cells. This is similar to some of the cut points used in breast cancer for HER2/neu. When IHC cut points were compared with evidence from the tissue of origin of the cancer, our cut points were equal to or higher (more stringent) than the evidence cut points.

Human epidermal growth factor receptor 2 (HER2) and epidermal growth factor receptor (EGFR) were stained as specified by the vendor (DAKO, Copenhagen, Denmark). All other antibodies were purchased from commercial sources and visualized with a DAB biotin-free polymer detection kit. Appropriate positive control tissue was used for each antibody. Negative control slides were stained by replacing the primary antibody with an appropriately matched isotype-negative control reagent. All slides were counterstained with hematoxylin as the final step and cover slipped. Tissue sections were analyzed by fluorescent in situ hybridization (FISH) for EGFR and HER2/neu copy number, as per the manufacturer's instructions. FISH for HER2/neu was performed with the PathVysion HER2 DNA Probe Kit (Abbott Molecular, Abbott Park, IL). FISH for EGFR was performed with the LSI EGFR/CEP 7 Probe (Abbott Molecular).

Microarray Method and Cut Points

The frozen tumor fragments for microarray (MA) were placed in a glass tube on 0.5 mL of frozen 0.5 M guanidine isothiocyanate solution and thawed and homogenized with a Covaris S2 (Covari, Woburn, MA). TriZol (0.5 mL) was added and mixed, and the solution was heated to 65°C for 5 minutes and then cooled on ice and phase separated by adding chloroform and centrifugation. An equal volume of 70% ethanol was added to the aqueous phase, which was chromatographed on a Qiagen Rneasy column (Qiagen, Germantown, MD). RNA was bound and then eluted. RNA was tested for integrity by assessing the ratio of 28S to 18S ribosomal RNA on an Agilent BioAnalyzer (Agilent, Santa Clara, CA). Tumor RNA (2 to 5 μg) and RNA from a sample of a normal tissue representative of the tumor's tissue of origin (2 to 5 μg) were converted to cDNA and labeled during T7 polymerase amplification with contrasting fluor tagged (Cy3, Cy5) cytidine triphosphate . The labeled tumor and its tissue of origin reference were hybridized to an Agilent H1Av2 60-mer oligo array chip with 17,085 unique probes.

The MA was considered positive for a target if the difference in expression for a gene between tumor and control organ tissue was at a significance level of P ≤ .001. Our hypothesis was that if we made the cut points rigorous enough such that a meaningful number of cancer cells would have the target or mechanism in place, then the study could make some meaningful inferences on whether the therapy had an effect on these mechanisms based on time to progression versus the earlier standard of care time to progression. Cut points were chosen for gene expression of the cancer based on stringent P values (P < .001) compared with the normal mRNA expression levels. It was decided that using the mRNA level from the tissue of the organ of tumor origin would be the most informative comparison. To provide stringent quality control, these MA studies were performed in a Clinical Laboratory Improvement Amendments–certified environment.


Table A1. Pairings of Targets and Drugs

Table A1. Pairings of Targets and Drugs

Potential Target Agents Suggested as Interacting With the Target
    EGFR* Cetuximab, erlotinib, gefitinib
    SPARC Nanoparticle albumin-bound paclitaxel
    c-KIT Imatinib, sunitinib, sorafenib
    ER Tamoxifen, aromatase inhibitors, toremifene, progestational agent
    PR Progestational agents, tamoxifen, aromatase inhibitor, goserelin
    Androgen receptor Flutamide, abarelix, bicalutamide, leuprolide, goserelin
    PGP Avoid natural products, doxorubicin, etoposide, docetaxel, vinorelbine
    HER2/NEU* Trastuzumab
    PDGFR Sunitinib, imatinib, sorafenib
    CD52 Alemtuzumab
    CD25 Denileukin diftitox
    HSP90 Geldanamycin, CNF2024
    TOP2A Doxorubicin, epirubicin, etoposide
    ADA Pentostatin, cytarabine
    AR Flutamide, abarelix, bicalutamide, leuprolide, goserelin
    ASNA Asparaginase
    BCL2 Oblimersen sodium
    BRCA2 Mitomycin
    CD33 Gemtuzumab ozogamicin
    CDW52 Alemtuzumab
    CES-2 Irinotecan
    DCK Gemcitabine
    DNMT1 Azacitidine, decitabine
    EGFR Cetuximab, erlotinib, gefitinib
    ERBB2 Trastuzumab
    ERCC1 Cisplatin, carboplatin, oxaliplatin
    ESR1 Tamoxifen, aromatase inhibitors, toremifene, progestational agent
    FOLR2 Methotrexate, pemetrexed
    GART Pemetrexed
    GSTP1 Platinum
    HDAC1 Vorinostat
    HIF1α Bevacizumab, sunitinib, sorafenib
    HSPCA Geldanamycin, CNF2024
    IL2RA Aldesleukin
    KIT Imatinib, sunitinib, sorafenib
    MLH-1 Gemcitabine, oxaliplatin
    MSH1 Gemcitabine
    MSH2 Gemcitabine, oxaliplatin
    NFKB2 Bortezomib
    NFKB1 Bortezomib
    OGFR Opioid growth factor
    PDGFC Sunitinib, imatinib, sorafenib
    PDGFRA Sunitinib, imatinib, sorafenib
    PDGFRB Sunitinib, imatinib, sorafenib
    PGR Progestational agents, tamoxifen, aromatase inhibitors, goserelin
    POLA Cytarabine
    PTEN Rapamycin (if low)
    PTGS2 Celecoxib
    RAF1 Sorafenib
    RARA Bexarotene, all-trans-retinoic acid
    RXRB Bexarotene
    SPARC Nanoparticle albumin-bound paclitaxel
    SSTR1 Octreotide
    TK1 Capecitabine
    TNF Infliximab
    TOP1 Irinotecan, topotecan
    TOP2A Doxorubicin, etoposide, mitoxantrone
    TOP2B Doxorubicin, etoposide, mitoxantrone
    TXNRD1 Px12
    TYMS Fluorouracil, capecitabine
    VDR Calcitriol
    VEGF Bevacizumab, sunitinib, sorafenib
    VHL Bevacizumab, sunitinib, sorafenib
    ZAP70 Geldanamycin, CNF2024

Abbreviation: IHC, immunohistochemistry.

*Fluorescent in situ hybridization was also performed for these potential targets; see Patients and Methods.

†Although not commercially available agents, the new agents were at recommended phase II doses at the time of this study.


Table A2. Targets Noted in Patients' Tumors, Treatment Suggested on the Basis of These Results, and Treatment Investigator Would Use if No Target Was Identified (in patients with PFS ratio ≥ 1.3)

Table A2. Targets Noted in Patients' Tumors, Treatment Suggested on the Basis of These Results, and Treatment Investigator Would Use if No Target Was Identified (in patients with PFS ratio ≥ 1.3)

Patient No. PFS Ratio Response Location of Primary Tumor Targets Used to Suggest Treatment and Method Used Treatment Suggested on Basis of Patient's Tumor Molecular Profiling Treatment the Investigator Would Have Used if No Results From Molecular Profiling
01-07 Y Breast ESR1:I; ESR1: M DES 5 mg TID Investigational
01-12 Y Cholangiocarcinoma EGFR: I; TOP1: M CPT-11 350 mg/m2 every 3 weeks; cetuximab 400 mg/m2 day 1, 250 mg/m2 every week Investigational
02-13 Y Breast SPARC: I; SPARC, ERBB2: M NAB paclitaxel 260 mg/m2 every 3 weeks; trastuzumab 6 mg/kg every 3 weeks Docetaxel, trastuzumab
01-14 Y Other eccrine sweat gland right forearm c-KIT: I; c-KIT:M Sunitinib 50 mg/d, 4 weeks on/2 weeks off Best supportive care
04-31 Y Ovary HER2/NEU, ER: I; HER2/NEU: M Lapatinib 1,250 mg PO days 1-21; tamoxifen 20 mg PO Bevacizumab
05-36 Y Colon/rectum PDGFR, c-KIT: I I; PDGFR, TOP1: M CPT-11 70 mg/m2 weekly for 4 weeks on/2 weeks off; sorafenib 400 mg BID Cetuximab
01-41 Y Breast SPARC: I; DCK: M NAB paclitaxel 90 mg/m2 every 3 weeks; gemcitabine 750 mg/m2 days 1, 8, 15, every 3 weeks Mitomycin
02-55 Y Breast ER: I; ER, TYMS: M Letrozole 2.5 mg daily; capecitabine 1,250 mg/m2 BID, 2 weeks on/1 week off Capecitabine
08-56 Y Malignant mesothelioma MLH1, MLH2: I; RRM2B, RRM1, RRM2, TOP2B: M Gemcitabine 1,000 mg/m2 days 1 and 8, every 3 weeks; etoposide 50 mg/m2 3 days every 3 weeks Gemcitabine
01-58 Y Breast MSH2, HER2/NEU: I; MSH2: M Oxaliplatin 85 mg/m2 every 2 weeks; fluorouracil 1,200 mg/m2 days 1 and 2, every 2 weeks; trastuzumab 4 mg/kg day 1, 2 mg/kg every week Investigational
09-75 Y Non–small-cell lung cancer EGFR: I; EGFR, TOP1: M Cetuximab 400 mg/m2 day 1, 250 mg/m2 every week; CPT-11 125 mg/m2 weekly for 4 weeks on/2 weeks off Vinorelbine
01-83 Y Colon/rectum MGMT, VEGFA: M Temozolomide 150 mg/m2 for 5 days every 4 weeks; bevacizumab 5 mg/kg every 2 weeks Capecitabine
01-86 Y Colon/rectum PDGFR, c-KIT: I; PDGFR: KDR, HIF1A, BRCA2: M Mitomycin 10 mg once every 4-6 weeks; sunitinib 37.5 mg/d, 4 weeks on/2 weeks off Capecitabine
02-94 Y Breast DCK, DHFR: M Gemcitabine 1,000 mg/m2 days 1 and 8 every 3 weeks; pemetrexed 500 mg/m2 days 1 and 8, every 3 weeks Best supportive care
06-98 Y Breast TOP2A: I; TOP2A: M Doxorubicin 50 mg/m2 every 3 weeks Vinorelbine
06-99 Y Colon/rectum MGMT, VEGFA, HIF1A: M Temozolomide 150 mg/m2 for 5 days every 4 weeks; sorafenib 400 mg BID Panitumumab
03-100 Y Breast ESR1, PR: I; ESR1, PR: M Exemestane 25 mg every day Doxorubicin liposomal
01-106 Y GIST (stomach) EGFR: I; EGFR, RRM2: M Gemcitabine 1,000 mg/m2 days 1, 8, and 15 every 4 weeks; cetuximab 400 mg/m2 day 1, 250 mg/m2 every week None

Abbreviations: PFS, progression-free survival; Y, yes; I, immunohistochemistry; M, microarray; DES, diethylstilbestrol; CPT-11, irinotecan; TID, three times a day; NAB, nanoparticle albumin bound; PO, orally; BID, twice a day; GIST, GI stromal tumor.


Table A3 Targets Noted in Patients' Tumors, Treatment Suggested on the Basis of These Results, and Treatment Investigator Would Use if No Target Was Identified (in patients with PFS ratio < 1.3).

Table A3 Targets Noted in Patients' Tumors, Treatment Suggested on the Basis of These Results, and Treatment Investigator Would Use if No Target Was Identified (in patients with PFS ratio < 1.3).

Patient No. PFS Ratio Response Location of Primary Tumor Targets Used to Suggest Treatment and Method Used Treatment Suggested on Basis of Patient's Tumor Molecular Profiling Treatment the Investigator Would Have Used if No Results From Molecular Profiling
01-01 N Breast EGFR: I; EGFR, TOP1, CES2: M Cetuximab, CPT-11 Investigational
01-03 N Thyroid, anaplastic carcinoma PDGFR: I; PDGFR: M Sunitinib Investigational
01-04 N Colon/rectum PDGFR, c-KIT: I; PDGFR, VEGF: M Sunitinib Investigational
01-08 N Head and neck (SCC) PDGFR, c-KIT: I; PDGFR: M Imatinib Investigational
01-09 N Choroidal melanoma SPARC: I; SPARC:M NAB paclitaxel Sorafenib
02-10 N Breast HER2/NEU: I; HER2/NEU, HIF1A: M Sorafenib, trastuzumab Investigational
02-11 N NSCLC SPARC: I NAB paclitaxel Gemcitabine, irinotecan
01-15 N Ovary PDGFR: I; VEGF: M Sunitinib, carboplatin
01-16 N Parotid-salivary gland adenocarcinoma TOP2A, TOP2B: M Doxorubicin liposomal Fluorouracil
01-17 N Ovary PDGFR: I; VEGF: M Sunitinib Capecitabine
02-19 N Other mucinous cystadenoma appendix c-KIT: I; PDGFR, HIF1A, GART, TYMS: M Sunitinib, pemetrexed Best supportive care
02-20 N Pancreas PDGFR, EGFR: I; PDGFR, HIF1A: M Sunitinib, erlotinib Bevacizumab
01-22 N Pancreas c-KIT, PDGFR: I; c-KIT, PDGFR: M Sunitinib Capecitabine
02-23 N Colon/rectum PDGFR: I; VEGF: M Sunitinib Best supportive care
01-24 N Ovary HER2/NEU: I; HER2/NEU: M Trastuzumab Gemcitabine
04-25 N Pancreas EGFR: I; TOP1, CES2: M Cetuximab, CPT-11 Temozolomide
01-26 N NSCLC EGFR: I; EGFR, TOP1, CES2: M Cetuximab, CPT-11 Docetaxel, cisplatin
04-27 N Anal carcinoma (SCC) EGFR: I; EGFR, VEGF, HIF1A: M Bevacizumab, erlotinib Capecitabine, cetuximab, RT
01-28 N Prostate AR: I; AR: M Bicalutamide Taxotere
01-29 N Vagina (SCC) PDGFR: I; HIF1A, VEGF: M Sunitinib Investigational
03-32 N Breast HER2/NEU: I Trastuzumab Vinorelbine
01-34 N Stomach PDGFR, c-KIT: I; PDGFR: M Sunitinib Fluorouracil
06-35 N Kidney SPARC: I; SPARC: M Paclitaxel Interferon
01-38 N Cervix PDGFR, c-KIT, EGFR: I Sunitinib, erlotinib Erlotinib
01-39 N Breast PDGFR: I Sunitinib Mitomycin
03-40 N Breast PDGFR: I; PDGFR, TOP2A: M Doxorubicin liposomal, sorafenib Doxorubicin liposomal
06-43 N Breast PDGFR, c-KIT: I; KDR: M Sunitinib Docetaxel
01-48 N Duodenal adenocarcinoma (ampulla) EGFR: I; EGFR, TOP1: M Cetuximab, CPT-11 Capecitabine
01-51 N Prostate SPARC: I; SPARC: M NAB paclitaxel Ketoconazole
06-52 N Esophagus (small cell) c-KIT, PDGFR: I; DCK, RRM2B: M Gemcitabine, sunitinib
01-53 N Breast c-KIT, PDGFR: I; c-KIT M; Sunitinib
06-57 N Colon/rectum EGFR: I; TOP1: M CPT-11/panitumumab Panitumumab
06-61 N Neuroendocrine mass/retroperitoneal HER2/NEU, MSH2: I; HER2/NEU, DCK, RRM2B: M Gemcitabine, oxaliplatin, lapatinib Investigational
08-62 N Ovary TOP2A: I; TOP2A , TOP2B: M Etoposide Topotecan
08-66 N Unknown primary carcinoma (SCC) HER2/NEU, MSH2: I; HER2/NEU:M Gemcitabine, oxaliplatin, lapatinib Carboplatin, gemcitabine
06-67 N Breast HER2/NEU: I; TYMS: M Capecitabine, lapatinib Mitomycin
01-69 N Prostate c-KIT, PDGFR: I Sorafenib Investigational
06-72 N Breast HER2/NEU: I; DHFR, TYMS: M Pemetrexed, trastuzumab Docetaxel
02-74 N Head/neck right oropharyngeal carcinoma TOP2A: I ; TOP2A, TOP2B: M Doxorubicin liposomal Carboplatin, fluorouracil
06-78 N Skin melanoma SPARC: I; SPARC: M NAB paclitaxel Dacarbazine
02-79 N Colon/rectum DNMT3B, DNMT3A, DNMT1: M Azacitidine Capecitabine, bevacizumab
01-84 N Colon/rectum BRCA2: M Capecitabine, mitomycin Capecitabine
01-92 N Breast MLH1, DCK: M Gemcitabine, oxaliplatin Cisplatin
08-93 N Prostate TOP2A: I; TOP2A: TOP2B: M Doxorubicin liposomal Carboplatin
01-95 N Mesothelioma peritoneal PDGFR: I; PDGFR, FLT1, VEGFA: M Sunitinib Investigational
09-96 N Colon/rectum TOP2A: I Doxorubicin Best supportive care
02-103 N Colon/rectum VEGFA, MSH2, RRM2B, RRM1, RRM2: M Gemcitabine/bevacizumab Best supportive care
01-105 N Soft tissue sarcoma (uterine) MGMT: M Temozolomide Investigational

Abbreviations: PFS, progression-free survival; N, no; I, immunohistochemistry; M, microarray; CPT-11, irinotecan; SCC, squamous cell carcinoma; NAB, nanoparticle albumin bound; NSCLC, non–small-cell lung cancer; RT, radiotherapy.

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DOI: 10.1200/JCO.2009.26.5983 Journal of Clinical Oncology 28, no. 33 (November 20, 2010) 4877-4883.

Published online October 04, 2010.

PMID: 20921468

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