TP53 tumor-suppressor gene mutations are among the most frequent abnormalities in cancer, affecting approximately 40% of patients. Yet, there is no accepted way to target these alterations in the clinic. At the same time, antagonists of VEGFR or its ligand are best-selling oncology drugs, with multiple, expensive compounds approved. Although only a subset of patients benefit from these antiangiogenesis agents, no relevant biomarker has been identified. Interestingly, TP53 mutations upregulate VEGF-A and VEGFR2. We prospectively enrolled 500 patients, to be interrogated by comprehensive genomic profiling (CGP) (next-generation sequencing, 236 genes), and to be matched, whenever possible, with targeted agents. Herein, we analyze outcomes based on VEGF/VEGFR inhibitor treatment and presence of TP53 mutations. Of the 500 patients, 188 (37.6%; with ≥1 alteration) were treated; 106 (56% of 188) had tumors that harbored TP53 mutations. VEGF/VEGFR inhibitor therapy was independently associated with improvement in all outcome parameters [rate of stable disease (SD) ≥6 months/partial and complete remission (PR/CR); (31% versus 7%; TP53-mutant patients (who received no other molecular-matched agents) treated with versus without VEGF/VEGFR inhibitors), time-to-treatment failure, and overall survival (multivariate analysis: all P ≤ 0.01)] for the patients harboring TP53-mutant cancers, but improvement was not seen in any of these parameters for patients with TP53 wild-type neoplasms. We conclude that TP53 mutations predict sensitivity to VEGF/VEGFR inhibitors in the clinic. TP53 alterations may therefore be a ready biomarker for treatment with antiangiogenesis agents, a finding of seminal importance across the cancer field. Mol Cancer Ther; 15(10); 2475–85. ©2016 AACR.
Angiogenesis fuels the proliferation and spread of cancer (1). VEGF is probably the most commonly involved proangiogenic factor. FDA-approved drugs now include antibodies against VEGF, as well as numerous small-molecule tyrosine kinase inhibitors (TKI) that target a VEGF receptor (VEGFR). Indeed, bevacizumab, an antibody targeting the VEGF-A ligand, has previously been proclaimed one of the best-selling drugs in oncology. However, for most malignancies in which it is deployed, including colon, lung, and kidney cancer, as well as glioblastoma multiforme, bevacizumab increases survival by only a few weeks. Small-molecule VEGFR inhibitors produce comparable results. Indeed, the FDA revoked its approval of bevacizumab in breast cancer because of the absence of evidence demonstrating a survival advantage, despite prior activity signals (2). It seems plausible that, in relevant neoplasms, a subgroup of patients across tumor types may be responsive to bevacizumab and/or small-molecule VEGFR inhibitors; however, biomarkers to identify and select these subsets remain elusive (3).
TP53 mutations are the most common molecular alterations across cancers, with about 40% of diverse tumors harboring this type of abnormality. Yet, there is no approved therapy that targets p53 (4, 5). We previously reported results of a retrospective study of patients with diverse cancers demonstrating that bevacizumab-containing regimens predicted for longer progression-free survival (PFS) in TP53-mutant tumors (multivariate analysis; P < 0.001; PFS = 11 vs. 5.0 months; mutant vs. wild-type TP53; ref. 6). The mechanism by which this correlation might occur remains uncertain; however, there is evidence to suggest that TP53 is implicated in angiogenesis. For instance, a multiple regression analysis of the transcriptome in non–small cell lung cancer (NSCLC) revealed that high VEGF-A expression correlated independently with TP53 mutational status (7). Though early data failed to find a clear association between VEGF expression and outcome after bevacizumab administration, recent observations using improved technology indicate that circulating levels of the short isoform of VEGF-A is a strong biomarker candidate for predicting benefits (3).
Herein, we report results of a sub-analysis of a prospective study evaluating comprehensive genomic profiling (CGP) using a 236 gene next-generation sequencing (NGS) platform for matching patients (n = 188) to drugs. These data demonstrate that patients whose tumors harbored the TP53-mutant, but not TP53–wild-type, gene had improved outcomes when treated with VEGF or VEGFR antagonists. Our current observations provide important support for the concept that TP53 mutations represent a biomarker that predicts salutary effects of anti-angiogenic agents.
Materials and Methods
Patient population and study design
The parent study enrolled 500 patients with refractory or progressive cancers. Its primary objective was to analyze the outcome of patients with diverse cancers prospectively matched to targeted therapy on the basis of CGP. An analysis of these data has been published (8). The current study represents a complete sub-analysis of the clinical correlates of TP53 status in all 188 patients exhibiting at least one molecular abnormality who were treated on study (Fig. 1). The purpose of this analysis was determining whether the presence of TP53 mutations was associated with a better outcome when antiangiogenesis agents were administered. The antiangiogenesis agents administered are shown in Supplementary Table S1, and included antibodies and small-molecule TKIs, which targeted either VEGF or VEGFR (at low IC50s). Supplementary multivariate analyses are shown in Supplementary Table S2. The study included 17 tumor types (Supplementary Table S3).
Study eligibility criteria included ECOG performance status ≤1 (9), tumor (archived or fresh) likely available for CGP, a life expectancy of ≥3 months, and likely able to qualify for therapy. The study was designed as a navigation trial, where the physician could use the CGP diagnostic, in the context of the patient's other medical conditions and laboratory tests, to choose a therapy, such as an approved medication used on- or off-label or a clinical trial. This protocol (NCT02437617) was approved by the MD Anderson Internal Review Board, and all patients gave informed consent.
CGP using a broad, hybrid capture–based NGS assay
Base substitutions, insertions, deletions, copy-number alterations, and selected gene fusions were detected [Foundation Medicine (Cambridge, MA; clinical laboratory improvements amendment (CLIA) laboratory; ref. 10]. DNA was isolated from 40 μm of formalin-fixed paraffin-embedded tissue (for specimens with ≥20% tumor cells) using the Maxwell 16 FFPE Plus LEV DNA Purification kit (Promega) and quantified using a standardized PicoGreen fluorescence assay (Invitrogen). Library construction was performed with the use of a 50 to 200 ng of DNA sheared by sonication to about 100 to 400 bp before end-repair, dA addition and ligation of indexed, Illumina sequencing adaptors. Enrichment of target sequences (all coding exons of 236 cancer-related genes (3,769 exons) plus 47 introns from 19 genes often rearranged or altered in malignancy (Supplementary Table S4) was achieved by solution-based hybrid capture with custom biotinylated oligonucleotide bases. Enriched libraries were sequenced to an average median depth of >500X with 99% of bases covered >100X (IlluminaHiSeq 2000 platform using 49 × 49 paired-end reads) and mapped to the reference human genome (hg19) using the Burrows–Wheeler Aligner and the publicly available SAM tools, Picard, and Genome Analysis Toolkit. Point mutations were identified by a Bayesian algorithm; short insertions and deletions, determined by local assembly; gene copy-number alterations (amplifications), by comparison with process matched normal controls; and gene fusions/rearrangements, by clustering chimeric reads mapped to targeted introns.
Amplifications were called for ≥6 copies (>7 for triploid, >8 for tetraploid samples) except for ErbB2 (≥5 copies). Aberrations, mutations or other alterations in kinases that were presumed to be non-functional based on wet lab experiments or structural modeling, or lack of data were not included.
Antiangiogenic treatments included antibodies and small-molecule kinase inhibitors (Supplementary Table S1). These treatments could be given as single agents or in combination with other drugs. Antibodies are usually specific for angiogenic molecules, whereas small-molecule inhibitors often had targets in addition to VEGFRs.
Patients who were lost to follow-up or came off early (before restaging) for payor reasons were considered inevaluable for stable disease (SD) ≥6 months/partial and complete remission (PR/CR); patients who came off early for side effects were considered progressors. Patients who had not been restaged at the date of data cutoff (6 months after the date of the last enrollment; August 4, 2014) were considered inevaluable for SD ≥6 months/PR/CR (unless they had already achieved a CR or PR). SD, PR, or CR was determined per the assessment by the treating doctor. Time-to-treatment failure (TTF) and overall survival (OS) were assessed by the method of Kaplan and Meier, and the survival function between groups was compared using a two-sided log-rank test. TTF was the interval from the treatment start date to documentation of disease progression, death, or removal from study for any reason (mostly side effects), whichever occurred first. Patients who had not reached any of those endpoints at the date of data cutoff were censored on that date. If they had not reached the endpoints at the time of being lost to follow-up, they were censored at the date of last contact. OS was measured from the time of study enrollment. Patients still alive (for OS) at the date of data cut off, or the date of last contact for patients lost to follow-up, were censored on that date.
The treatment assessed was the first trial/therapy after receiving the CGP result. Local therapy (hepatic arterial infusion, for example) and transplant was considered inevaluable. If the therapy immediately before the on-study treatment was immunotherapy, that patient was inevaluable for all outcome parameters (SD ≥6 moths/PR/CR, TTF, OS) because of the potential for delayed responses.
Statistical analysis was verified by our statistician J.J. Lee. Patient characteristics were summarized using descriptive statistics. The χ2 test or Fisher's exact test, as appropriate was used to evaluate the associations between categorical variables and SD ≥6 months/PR/CR. The Mann–Whitney U test was applied to compare number of molecular alterations per person between groups (11).
The main endpoints of the study were SD ≥6 months/PR/CR as well as TTF, and OS. Kaplan–Meier estimates were computed for the time-to-event data (12). Log-rank test was applied for comparing the survival curves between groups. The multivariable Cox proportional hazards regression model (13) was used to examine risk factors related to TTF and OS, after adjusting for other factors, in particular TP53 mutation status. Covariates included in the stepwise multivariate analysis were those with a P value of <0.2 in univariate analysis. Only variables with P ≤ 0.10 in the multivariate analysis (and treatment with VEGF/VEGFR inhibitors) were included in the final model. Bootstrapping was performed using random sampling with replacement. The bootstrap method may be superior to approaches relying on the asymptotic distribution of the tests that assume the data come from a normal distribution.
All statistical tests were two-sided, and P ≤ 0.05 was considered statistically significant. Statistical analyses were carried out using SPSS (version 22.0; SPSS).
Of the 500 individuals enrolled, 188 patients (37.6%) with at least one molecular alteration were treated (Fig. 1). One hundred and eighty-two treated patients (97%) were evaluable for assessment of SD ≥6 months/PR/CR, and all 188 were evaluable for TTF and OS. Of patients who were not treated or not evaluable for treatment, the most frequent reasons were insufficient tissue, progressive cancer or succumbing to disease. One hundred and six patients (56% of 188) had tumors that harbored TP53 mutations.
Of 188 treated patients, 55% were 60 years old or younger, and 65% were women. Gastrointestinal malignancies were present in 18% of patients (Table 1). The median number of molecular alterations was five per person (range, 1–14). Patients were heavily pretreated. The median number of prior therapies in the metastatic setting was 4 (range, 0–17). The median OS for all 188 patients was 8.0 months (range, 0.3–23.6 months). There was a trend for participants with TP53 wild-type tumors to survive longer than the TP53-mutant tumor-bearing patients, but this did not reach statistical significance (9.2 vs. 7.6 months; P = 0.132)
Patient characteristics in the TP53–wild-type and -mutant groups were generally well balanced (Table 1; refs. 14–16), except that TP53 mutant versus wild-type individuals generally had a greater number of molecular alterations (median = 5 versus 3, P < 0.00001) and received combination therapies more often (P = 0.005), variables generally associated with worse and better outcomes, respectively (17, 18). Overall, TP53 mutant and wild-type groups were equivalent for both canonical composite prognostic scores–the Royal Marsden Hospital Score (RMH) score [based on levels of albumin, and lactate dehydrogenase (LDH), and number of metastatic sites] and the MD Anderson Cancer Center (MDACC) score (based on RMH with tumor type and ECOG performance status as additional variables; Table 1; refs. 14–16).
Univariate analysis of factors associated with outcome
TP53-mutant tumors (n = 106).
The only factor associated with a higher rate of SD ≥6 months/PR/CR was treatment with VEGF/VEGFR inhibitors (P = 0.020; Supplementary Table S1 for drugs used; Table 2 for univariate analysis).
Lower LDH, higher albumin, lower MDACC prognostic score and treatment with VEGF/VEGFR targeting agents were associated with longer TTF (all P ≤ 0.05).
Lower number of metastatic sites, low LDH, higher albumin, absence of PI3K pathway aberrations, and lower RMH or MDACC prognostic score were associated with better OS. Treatment with VEGF/VEGFR targeting agents showed a trend toward association with longer survival (P = 0.163).
TP53–wild-type tumors (n = 82).
No factors were associated with a higher rate of SD ≥6 months/PR/CR. In contrast with the TP53-mutant patients, in whom the VEGF/VEGFR inhibitors were significantly associated with a higher rate of SD ≥6 months/PR/CR (P = 0.02), for the TP53 wild-type tumors, the p value was 0.456 (Table 2).
Only better ECOG performance status and lower platelet counts correlated with better TTF. In contrast with the TP53-mutant patients, where VEGF/VEGFR inhibitors were significantly associated with longer TTF (P = 0.021), for the TP53 wild-type tumors, the P value was 0.804 (and median TTF was actually numerically shorter for the VEGF/VEGFR inhibitor-exposed patients).
For OS, younger age, better ECOG performance status, few number of prior therapies, lower LDH, higher albumin and better RMH or MDACC prognostic scores were correlated with a better outcome (all P ≤ 0.05). In contrast with the TP53-mutant patients, where VEGF/VEGFR inhibitors were associated with a trend toward a longer OS (P = 0.163), for the TP53 wild-type tumors, the P value was 0.818 (and median OS was actually numerically shorter for the VEGF/VEGFR inhibitor-exposed patients).
Additional alterations in VEGFR/VEGF family genes
Only two patients with a TP53 mutation also carried an additional alteration in a VEGF/VEGFR-related gene. These patients both had a KDR (VEGFR2) amplification. One achieved SD ≥6 months/PR/CR and the other did not; therefore, the improved response rate for VEGF/VEGFR inhibitors in TP53-mutant patients could not be attributed to the presence of another VEGF/VEGFR-related alteration.
Multivariate analysis of factors associated with outcome
The multivariate analysis was performed first by including all variables with a p value of <0.2 in the univariate analyses, and then selecting the variables with a P value of <0.1 and repeating the analysis (Supplementary Table S2). Using this methodology, treatment with VEGF/VEGFR inhibitors was independently associated with improvement in all outcome parameters [rate of SD ≥6 months/PR/CR, length of TTF and OS (all P ≤ 0.01)] for the patients harboring TP53-mutant cancers, but improvement was not seen in any of these parameters for the group of patients with TP53 wild-type neoplasms (Fig. 2A and B, TTF for TP53-mutant versus wild type). (In general, the number of patients with each tumor type was too small to sub-analyze. We did examine gastrointestinal versus other tumors. The rate of SD ≥ 6 months/PR/CR for TP53-mutant gastrointestinal tumors treated with VEGF/VEGFR inhibitors was 29% (2/7 patients) versus 29% (9/31) for p53-mutant other tumors (P = 1.000).
A second analysis was performed similarly, except that the variable of interest—treatment with VEGF/VEGFR inhibitors—was included in the analysis; even if the P value for this variable was greater than 0.2 in the univariate analysis. Under these conditions, treatment with VEGF/VEGFR inhibitors was again independently associated with improvement in all outcome parameters (SD ≥6 months/PR/CR, TTF and OS) in the TP53-mutant group (all P values ≤0.012)] (Table 3). For the TP53 wild-type group, when VEGF/VEGFR treatment was forced into the multivariate analysis despite its insignificance in univariate analysis, it was associated with an improved rate of SD ≥6 months/PR/CR (univariate P value = 0.456; multivariate P value = 0.038; bootstrapping method) but the impact on TTF and OS remained insignificant. Patients often received combination regimens and may have been given matched therapy (concomitant with VEGF/VEGFR inhibitors); indeed, 65% of the VEGF/VEGFR-treated wild-type patients received another match whereas only 38% of the TP53-mutant patients treated with VEGF/VEGFR inhibitors had other matches (P = 0.0039). We therefore analyzed the subgroup of patients whose regimens included no matches to their genomic anomalies (other than VEGF/VEGFR matched to TP53 alterations; Table 4). Comparing patients who had VEGF/VEGFR inhibitors as part of their regimens versus those who did not, in individuals with TP53 mutations and no other matches, the rate of SD ≥6 months/PR/CR was 31% versus 7% (P = 0.04); in contrast, for the patients whose tumors harbored wild-type TP53, the P value was 0.49, indicating no difference in response rate between VEGF/VEGFR inhibitor treatment or not (in the absence of other matches). Similarly, in the absence of other matches, TTF was longer for the TP53-mutant individuals who were treated with VEGF/VEGFR inhibitors versus those who were not [P = 0.005; TP53-mutant patients (VEGF/VEGFR inhibitors yes vs. no)], but not for TP53 wild-type patients (P = 0.543; TP53 wild-type patients treated with VEGF/VEGFR inhibitors, yes versus no; with the TP53 wild-type patients actually showing numerically shorter TTF in the VEGF/VEGFR–treated patients). Similarly, in the absence of other matches, OS showed a trend toward improvement in the TP53-mutant patients who received VEGF/VEGFR inhibitors versus those who did not [9.6 vs. 5.2 months (P = 0.07)], whereas this was not seen in the patients whose tumors were wild-type TP53 (P = 0.607). These data confirm that, in the absence of other concomitant matched agents, VEGF/VEGFR inhibitors are associated with improvement in all outcome parameters in TP53-mutant, but not in TP53 wild-type, malignancies.
We have previously described, in a retrospective study, a clinical association between TP53 mutations and better PFS after bevacizumab treatment (6). Furthermore, a comprehensive transcriptomic analysis in NSCLC demonstrated that, in multivariate analysis, TP53 mutations were an independent predictor of high expression of VEGF-A (7), the primary target of bevacizumab, and the ligand for VEGFR-1 (Flt-1) and VEGFR-2 (KDR/Flk-1). The mechanism underlying the association between TP53 mutations and angiogenesis through VEGF-A is complicated, but may be in part related to the fact that wild-type TP53 indirectly represses VEGF expression by interaction with, and inhibition of, transcription factors such as SP1 and E2F (reviewed in ref. 19). Our current study was a prospective navigation trial and provides validation for the concept that TP53 mutations are a biomarker predicting beneficial effects when VEGF/VEGFR inhibitors are used in the clinic.
In recent years, molecular interrogation of tumors and deployment of matched therapies has shown remarkable responses in a variety of refractory malignancies (4). Aberrant TP53 has, however, proven to be difficult to target, though several approaches are being attempted. For instance, Mdm2 inhibitor molecules demonstrate preclinical promise in a wide variety of tumors with wild-type TP53 (20). In addition, AZD-1775, a potent and selective small-molecule inhibitor of Wee-1 kinase (a tyrosine kinase that is involved in G2 checkpoint signaling) selectively sensitizes tumors to DNA damaging agents, probably because TP53 is a key regulator in the G1 checkpoint, and TP53-deficient tumors depend on the G2 checkpoint after DNA damage (21). More recent work has demonstrated that the p53 protein requires the binding of a single zinc ion for proper folding, and impairing zinc binding is a major mechanism for loss of function in missense mutant p53. A new class of drugs termed zinc metallochaperones may reactivate wild-type p53 structure and function by restoring zinc binding in p53-mutant tumors (22). Overall, however, even though TP53 mutations are among the most common in cancer, there is a dearth of strategies in the clinic to target this frequently altered tumor suppressor. Our current multivariate analysis demonstrates that the administration of VEGF/VEGFR inhibitors is an independent variable significantly associated with improvement in all outcome parameters in patients with TP53-mutant, but not TP53 wild-type, malignancies (Tables 2, 3, and 4, Supplementary Table S2, and Fig. 2).
Other mechanisms, in addition to upregulation of the VEGF-A ligand, may also be operative in the relationship between TP53 and angiogenesis. Indeed, the role of TP53 is broad and reaches far beyond its most commonly studied effects on apoptosis (5, 23–27). TP53 leads to activation of target genes that regulate “healthy” biological processes, including cell-cycle arrest, apoptosis, senescence, energy metabolism, and antioxidant defense to prevent tumorigenesis. In addition to losing tumor suppressive functions of wild-type TP53, proteins associated with mutant TP53 also gain new oncogenic functions, including tumor cell proliferation, antiapoptosis, angiogenesis, metastasis-promotion, and metabolic changes defined as mutant TP53 gain-of-function. A role for TP53 in immune response has also been defined, and here angiogenesis also plays a key role. Importantly, VEGF suppresses the maturation of dendritic cells from hematopoietic progenitors (28). In turn, inadequate function of dendritic cells is one mechanism of tumor escape from “normal” immune system control. Indeed, decreased dendritic cells in tissue result in a dramatically reduced ability of these cells to stimulate allogeneic T cells and antigen-specific primary T-cell response. In a preclinical model, treatment of pulsed dendritic cells in combination with an anti-VEGF antibody led to tumor shrinkage and was associated with significant anti–p53 T-cell response (29). Hence, TP53 mutations may lead to attenuation of immune responses, which can be recovered, at least in some models, with dendritic cell treatment together with antiangiogenesis agents.
Expression analyses have demonstrated that VEGFR2 upregulation may be another mechanism by which mutant p53 controls angiogenesis (30). VEGFR2 is a receptor tyrosine kinase activated by binding of the VEGF-A ligand, and it is the main receptor mediating endothelial cell neovascularization. Mutant p53 binds near the VEGFR2 promoter transcriptional initiation site and plays a role in preserving an open conformation at that location. Relatedly, mutant p53 cooperates with the SWI/SNF complex, which is essential for remodeling the VEGFR2 promoter. Given that wild-type TP53 is a canonical repressor of the VEGF pathway through multiple mechanisms, including transcriptional repression of VEGF-A (7, 19, 31, 32), loss of wild-type p53 function/presence of mutant p53 has several mechanisms by which to turn on the angiogenic “switch.” These mechanisms are compatible with increased susceptibility of TP53-mutant tumors to the effects of VEGF or VEGFR antagonists (5, 33) as confirmed in the current investigation.
There are several limitations to this study. First, there were insufficient numbers of patients to determine whether specific alterations in TP53 are more important than others. Preclinical work has also not clarified which of the TP53 mutations may function to upregulate VEGF-A or VEGFR2, or participate in the immune response. Furthermore, because this study was conducted across tumor types, it remains unclear whether or not there would be differences in significance in specific histologies. Of note, however, in this regard, our patients were well balanced in the number of gastrointestinal versus other tumors (Table 1), and the fact that the study was histology agnostic may suggest generalizability. Another limitation was that a variety of VEGF/VEGFR inhibitors were given. The strength of correlation with benefit by agent could not be analyzed based on the sample size. Still, previous data have suggested that TP53 mutations may correlate with better outcome after either VEGF antibody (6) or VEGFR small-molecule inhibitor treatment (33), and this concept is further supported by the observation that TP53 mutations are associated with increased levels of VEGF-A transcripts (7), which in turn interact with VEGFR1 and VEGFR2. Finally, our study sample size was small. Further prospective studies with larger numbers of treated patients are needed.
In summary, there are at least 12 VEGF/VEGFR inhibitors that are approved, and many more in clinical trials; none have a biomarker for patient selection (34–44). Yet, it is known that most of these agents improve survival by only a few weeks, most likely because a subset of patients respond, whereas others do not benefit or may even be harmed by these drugs. The importance of this problem is further underscored by the immense costs of antiangiogenesis agents, which often runs at thousands of dollars per month. At the same time, TP53 is a tumor-suppressor gene that affects a wealth of cancer-related pathways, and is the most common alteration across diverse tumor types. Yet, to date, this gene has not proven susceptible to targeted agents in the clinic. Our current data support the concept that TP53 status may represent a ready biomarker for response to anti-angiogenesis agents, with multivariate analysis demonstrating significant improvement in all outcome parameters when individuals with TP53-mutant, but not TP53 wild-type, advanced neoplasms were treated with anti-angiogenesis agents. Recently, TP53 mutational status was also shown to be predictive of response to the VEGFR inhibitor pazopanib in advanced sarcomas (45). The underlying mechanism of response may relate to TP53 mutations being associated with upregulation of VEGF-A and VEGFR2 expression (7, 30–32). Of interest in this regard, other tumor suppressors that are not directly druggable may also be actionable based on the upregulation of affected pathways when the suppressor gene is mutated (46). For example, PTEN alterations are not directly targeted; rather they result in upregulation of the PI3K–Akt–mTor pathway, which is actionable (47). In addition, it seems likely that the magnitude of potential benefit in patients with TP53-mutant tumors versus TP53–wild-type is increased because of a distinct role of anti-VEGF in modulating T-cell response. Treatment of TP53-mutant tumors with VEGF/VEGFR inhibitors likely increases dendritic cells, thus promoting innate T-cell response and antitumor activity (29). Overall, our observations indicate that mutant TP53 may be a pharmacologically tractable alteration that can be prosecuted by VEGF/VEGFR inhibitors. This concept requires validation by prospective randomized trials.
Disclosure of Potential Conflicts of Interest
Y. Li ownership interest (including patents) in Foundation Medicine. A.M. Tsimberidou reports receiving a commercial research grant Foundation Medicine. V. Miller is CMO of and has ownership interest (including patents) in Foundation Medicine. R. Yelensky is VP Biomarkers and CDx and has ownership interest (including patents) in Foundation Medicine. R. Kurzrock is employed by and has ownership interest (including patents) in Novena, Inc. and Curematch, Inc.; reports receiving a commercial research grants from Genentech, Merck Serono, Pfizer, Sequenom, Foundation Medicine, and Guardant; and is a consultant/advisory board member for Sequenom, Actuate Therapeutics, and Xbioetch. No potential conflicts of interest were disclosed by the other authors.
Conception and design: J.J. Wheler, A. Naing, S. Fu, A.M. Tsimberidou, R. Yelensky, J.J. Lee, D. Hong
Development of methodology: J.J. Wheler, A.M. Tsimberidou, R. Yelensky
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J.J. Wheler, F. Janku, A. Naing, R. Zinner, V. Subbiah, S. Fu, D. Karp, G.S. Falchook, A.M. Tsimberidou, S. Piha-Paul, D. Ke, V. Miller, D. Hong
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J.J. Wheler, B. Stephen, V. Subbiah, S. Fu, R. Yelensky, J.J. Lee, D. Hong, R. Kurzrock
Writing, review, and/or revision of the manuscript: J.J. Wheler, F. Janku, A. Naing, V. Subbiah, S. Fu, D. Karp, G.S. Falchook, A.M. Tsimberidou, S. Piha-Paul, V. Miller, J.J. Lee, R. Kurzrock
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): J.J. Wheler, F. Janku, Y. Li, B. Stephen, V. Subbiah, A.M. Tsimberidou, R. Anderson
Study supervision: J.J. Wheler, D. Karp, R. Anderson, R. Kurzrock
This study was supported in part by a research grant from Foundation Medicine, Inc. (to J. J. Wheler).
We thank the patients and their families. The authors thank Hemwattie Ramnauth, Nilza Marie Biaggie Labiosa, and, Thomas Vu in the Department of Investigational Cancer Therapeutics at MD Anderson Cancer Center for their role in patient enrollment, regulatory work, and data collection.
Note: Supplementary data for this article are available at Molecular Cancer Therapeutics Online (http://mct.aacrjournals.org/).
- Received April 5, 2016.
- Revision received June 29, 2016.
- Accepted July 10, 2016.
- ©2016 American Association for Cancer Research.