Genetic Determinants of Cisplatin Resistance in Patients With Advanced Germ Cell Tumors

Abstract

Purpose

Owing to its exquisite chemotherapy sensitivity, most patients with metastatic germ cell tumors (GCTs) are cured with cisplatin-based chemotherapy. However, up to 30% of patients with advanced GCT exhibit cisplatin resistance, which requires intensive salvage treatment, and have a 50% risk of cancer-related death. To identify a genetic basis for cisplatin resistance, we performed whole-exome and targeted sequencing of cisplatin-sensitive and cisplatin-resistant GCTs.

Methods

Men with GCT who received a cisplatin-containing chemotherapy regimen and had available tumor tissue were eligible to participate in this study. Whole-exome sequencing or targeted exon-capture–based sequencing was performed on 180 tumors. Patients were categorized as cisplatin sensitive or cisplatin resistant by using a combination of postchemotherapy parameters, including serum tumor marker levels, radiology, and pathology at surgical resection of residual disease.

Results

TP53 alterations were present exclusively in cisplatin-resistant tumors and were particularly prevalent among primary mediastinal nonseminomas (72%). TP53 pathway alterations including MDM2 amplifications were more common among patients with adverse clinical features, categorized as poor risk according to the International Germ Cell Cancer Collaborative Group (IGCCCG) model. Despite this association, TP53 and MDM2 alterations predicted adverse prognosis independent of the IGCCCG model. Actionable alterations, including novel RAC1 mutations, were detected in 55% of cisplatin-resistant GCTs.

Conclusion

In GCT, TP53 and MDM2 alterations were associated with cisplatin resistance and inferior outcomes, independent of the IGCCCG model. The finding of frequent TP53 alterations among mediastinal primary nonseminomas may explain the more frequent chemoresistance observed with this tumor subtype. A substantial portion of cisplatin-resistant GCTs harbor actionable alterations, which might respond to targeted therapies. Genomic profiling of patients with advanced GCT could improve current risk stratification and identify novel therapeutic approaches for patients with cisplatin-resistant disease.

INTRODUCTION

Germ cell tumors (GCTs) are the most common solid tumors diagnosed in men 15 to 40 years old.¹ Most patients with metastatic GCT are cured with cisplatin-based chemotherapy combinations, which is unique among adult solid tumors. However, 20% to 30% of those with advanced disease progress after first-line chemotherapy and require intensive salvage regimens, which include high-dose chemotherapy with autologous stem cell transplantation and desperation surgery. Despite such efforts, nearly half of these patients are destined to die of progressive GCT.² The clinically based International Germ Cell Cancer Collaborative Group (IGCCCG) prognostic model stratifies patients into good-, intermediate-, and poor-risk groups. Understanding the molecular and genetic pathogenesis of the disease, including determinants of cisplatin sensitivity and resistance, could allow for enhanced risk stratification and more accurate identification of high-risk patients most in need of novel therapeutic approaches. Prior investigations have yielded conflicting results regarding the association of genomic alterations with cisplatin resistance in GCT.^3,4 In addition, the utility of prior studies was limited by small patient populations, the inclusion of few patients with cisplatin-resistant disease, and/or the lack of comprehensive sequencing approaches.

With the goal of identifying recurrent genetic alterations associated with cisplatin resistance in GCT, we performed whole-exome sequencing (WES) on a discovery cohort of 19 tumors and validated our findings using selective exon-capture sequencing of an additional 161 GCTs enriched for the cisplatin-resistant phenotype.

PATIENTS AND METHODS

Patient Eligibility

This study was conducted following institutional review board approval. All specimens were obtained from patients evaluated at Memorial Sloan Kettering Cancer Center. Men who received standard first-line cisplatin-based chemotherapy for advanced GCT of any primary site were eligible if they provided informed consent for tumor molecular characterization and had available histologically confirmed fresh or archived tumor tissue containing viable GCT and matching normal DNA. Pure teratoma and pure malignant transformation tumors were excluded. Standard first-line chemotherapy consisted of at least three cycles of a cisplatin-based combination regimen, typically etoposide plus cisplatin (EP), bleomycin plus EP (BEP), or ifosfamide plus EP. First-line treatment with paclitaxel plus ifosfamide plus cisplatin as part of a phase II clinical trial (NCT01873326) was also allowed. Patients who received only adjuvant chemotherapy, carboplatin-based regimens, or fewer than three cycles of cisplatin-based chemotherapy were ineligible. Nonprogressing patients were required to have at least 1 year of clinical follow-up.

Definitions of Response and Cisplatin Sensitivity and Resistance

A complete response (CR) to first-line cisplatin-based chemotherapy (CR chemo) was defined as tumor marker normalization and either complete resolution of all radiographic evidence of tumor masses or complete surgical resection of residual tumor masses revealing necrosis and/or teratoma. When complete surgical resection revealed viable nonteratomatous GCT elements, it was termed a CR to chemotherapy plus surgery (CR chemo + surgery). Patients who achieved marker normalization but did not undergo complete surgical resection of residual disease were considered to have achieved a partial response with negative tumor markers (PR-negative markers). If such patients underwent partial tumor resection, the pathology could consist of only teratoma or necrosis but no viable GCT elements. All other patients were categorized as having an incomplete response (IR).

Cisplatin resistance has a more stringent definition in GCT than other adult solid tumors. In this study, patients with cisplatin resistance had to meet one of the following criteria: (1) IR to first-line cisplatin-based chemotherapy, (2) nonteratomatous tumor progression after first-line cisplatin-based chemotherapy, or (3) viable nonteratomatous GCT identified at postchemotherapy surgery. All other patients were considered cisplatin-sensitive.

Next-Generation Sequencing

High-quality, fresh-frozen tumor tissues were selected for WES analysis from a discovery cohort consisting of 19 specimens. Representative hematoxylin-and-eosin–stained sections were reviewed by a Memorial Sloan Kettering Cancer Center genitourinary pathologist and were confirmed to have > 40% tumor purity. Additional details regarding the WES specimens and sequencing are provided in the methods section of the Appendix (online only).

Targeted, capture-based, next-generation sequencing of more than 300 cancer-related genes to a mean depth of 500- to 1,000-fold coverage was performed using the Memorial Sloan Kettering Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) assay. MSK-IMPACT was performed on the 19 WES tumors to confirm alterations identified by WES and to improve the sensitivity in detecting known cancer-associated genetic alterations.⁵ MSK-IMPACT was also performed on tumors from a prospective validation cohort that comprised 161 additional patients with advanced GCT. Following DNA extraction from tumor- and patient-matched normal samples, barcoded libraries were captured, sequenced, and analyzed through a customized pipeline for somatic mutation calling, copy number alterations, and structural rearrangements, as previously described.³

Functional Assays

Details of the methods used to functionally characterize RAC1 mutations are provided in the Appendix (online only).

Statistical Analysis

We assessed the association between alterations and clinicopathologic features (ie, histology, primary site, IGCCCG risk group, sample location) using Fisher’s exact test. Genes enriched in cisplatin-resistant versus cisplatin-sensitive tumors in the discovery cohort were examined for association with cisplatin-sensitivity in the validation cohort. Given the relative paucity of recurrent mutations, the entire cohort (discovery plus validation; N = 180) was used to assess for associations between genetic alterations and clinicopathologic features.

All clinical data were collected through retrospective chart review. Progression-free survival (PFS) was calculated from start date of chemotherapy to date of progression or death. Cox regression was used to evaluate multivariable associations with PFS.

RESULTS

Table 1 depicts patient and tumor characteristics for the combined cohort (N = 180), including the 19-sample discovery set and the 161-sample validation set. In the discovery cohort, nine tumors were cisplatin sensitive and 10 were resistant. Of the resistant tumors, eight were metastatic lesions and eight were collected after administration of chemotherapy. By definition, we were not able to obtain cisplatin-sensitive tumors after chemotherapy. WES was performed on all 19 samples with mean sample coverage of 116× (range, 93× to 134×) with 90% of target bases covered at greater than 30×. The mean number of somatic mutations per sample was 44 (standard deviation [SD], 50; median, 22; range, 10 to 208) and the mean number of nonsynonymous mutations was 31 (SD, 33; median, 16; range, 7 to 137; Appendix Table A1). The mean rate of 0.9 mutations per megabase with MSK-IMPACT was very low compared with other adult solid tumors.⁶ The median number of total (46 v 21; P = .05) and nonsynonymous (36 v 14; P = .04) mutations was higher among cisplatin-resistant tumors than among cisplatin-sensitive tumors (Fig 1A).

Table 1.

Patient Characteristics (discovery and validation cohorts)

Fig 1.

Differences between cisplatin-sensitive and cisplatin-resistant germ cell tumors (GCTs) in the discovery set. (A) Frequency of nonsynonymous mutations identified on whole-exome sequencing was higher among cisplatin-resistant than cisplatin-sensitive GCTs (36 [range, 8-137] v 14 [range, 7-28]; P = .04). (B) Oncoprint displaying the distribution of alterations in TP53, MDM2, KRAS, and NRAS in patients with cisplatin sensitivity and those with cisplatin resistance, as analyzed by whole-exome sequencing. Each column represents an individual patient or sample. Distribution of 12p gain among the discovery set samples is also shown.

As expected, evidence of 12p gain was noted in most tumors (74%) in the discovery cohort, but few other recurrent alterations were identified (Fig 1B). Notably, among 10 patients with cisplatin-resistant disease, two had TP53 alterations (one mutation [V173M] and one intragenic deletion) and three had focal amplification of MDM2, an E3 ubiquitin-protein ligase that negatively regulates TP53. Thus, five of 10 cisplatin-resistant tumors harbored alterations within the TP53/MDM2 pathway compared with none of the cisplatin-sensitive tumors (P = .033; Fig 1B).

To further explore this finding and mitigate potential bias associated with differences in sample timing relative to chemotherapy (ie, before v after) and sample type (primary v metastatic) between the cisplatin-sensitive and cisplatin-resistant cohorts, we performed MSK-IMPACT sequencing on a prospective cohort of 161 patients with GCT.⁵ In this validation cohort, 102 specimens (63%) were acquired before chemotherapy and 64 (40%) were metastatic lesions. An additional 14 hotspot mutations and one homozygous deletion of TP53 were identified. TP53 alterations were found exclusively in tumors from patients with cisplatin-resistant disease. Seven additional tumors in the validation set harbored MDM2 amplifications. As in other tumor types, amplification of MDM2 was mutually exclusive with TP53 alteration. The majority of patients with MDM2 amplification (five of seven [71.4%]) had cisplatin-resistant disease. Notably, alterations within TP53 and MDM2 were significantly more common in patients with cisplatin-resistant versus cisplatin-sensitive GCT (21.3% v 3%; P = .001).

We used the combined discovery and validation datasets to evaluate for associations between recurrent genetic alterations and clinicopathologic features (Table 1; Fig 2A). In the combined dataset, TP53 mutations/deletions alone and in combination with MDM2 amplifications were significantly more common in resistant versus sensitive tumors (TP53, 17 of 104 [16.3%] v none of 76 [0%], P < .001; TP53/MDM2, 25 of 104 [24.0%] v two of 76 [2.6%], P < .001; Fig 2B). When considered alone, there was a trend toward more frequent MDM2 amplification in resistant tumors (eight of 104 [7.6%] v two of 76 [2.6%]; P = .195). Figure 3A illustrates the distribution of TP53 mutations, which included previously reported recurrent missense mutations and truncations. With a median follow-up of 38.8 months, patients with TP53/MDM2 pathway alterations had significantly shorter PFS than those without these alterations (Fig 4). In addition, TP53/MDM2 alterations were more frequent among patients in the IGCCCG poor-risk group as compared with those in the intermediate- and good-risk groups (32.2% v 7.1% v 6.5%; P < .001). In a multivariable analysis that included the IGCCCG risk model, the presence of a TP53/MDM2 alteration was an independent predictor of disease progression following first-line cisplatin-based chemotherapy (hazard ratio, 1.83; 95% CI, 1.12 to 2.98; P = .016).

Fig 2.

Genomic alterations among 180 germ cell tumor (GCT) samples in the combined discovery and validation cohorts. (A) Oncoprint displaying the most frequently altered and other biologically notable mutations. (B) TP53 alterations and combined MDM2/TP53 alterations were more common among resistant GCT samples than sensitive ones. Indel, insertion/deletion.

Fig 3.

Distribution of gene mutations among 180 germ cell tumor (GCT) samples in the combined cohort. (A) TP53 mutations. (B) KIT mutations. The distribution of KIT mutations in GCT differs from GI stromal tumors. (C) Alignment and number of KRAS and RAC1 mutations at the 12, 34, and 61 positions. Expression of the RAC1 mutations identified in GCT results in increased phosphorylation of PAK1 and ERK. Ig, immunoglobulin.

Fig 4.

Progression-free survival (PFS) by TP53/MDM2 status (wild type v altered) demonstrated superior PFS for patients with wild-type germ cell tumor.

We also identified a strikingly higher rate of TP53 alterations in samples from patients with a mediastinal versus a testicular primary tumor site (13 of 22 [59.1%] v four of 158 [2.5%]; P < .001). When limited to primary mediastinal nonseminoma, which has a distinctly more aggressive biology and unfavorable outcome than primary mediastinal seminoma, the alteration rate was even more pronounced (13 of 18 [72.2%]) because none of the four primary mediastinal seminomas harbored a TP53 mutation.⁷

An intact TP53 pathway that facilitates apoptosis has been postulated to explain the exquisite cisplatin sensitivity characteristic of most GCTs.⁸ We thus used a pathway-based analysis to identify additional recurrent alterations predicted to impact TP53-mediated downstream functions and assessed their association with cisplatin sensitivity. Among TP53-associated genes, MYCN amplifications were identified in five patients (all cisplatin resistant), four of whom had TP53/MDM2 wild-type tumors (Fig 2A). MYCN, which transcriptionally targets both TP53 and MDM2, is a marker of poor prognosis in neuroblastoma, in which TP53 mutations are also rare (< 2%).

We grouped all other somatic mutations into core signal transduction pathways or canonical cell functions with the goal of identifying additional genes predictive of cisplatin resistance and/or potential targets for therapy, using a precision medicine approach. Potentially actionable alterations (n = 75) were identified in 57 of 104 patients (55%) with cisplatin-resistant disease (Appendix Table A2, online only). Within the receptor tyrosine kinase (RTK) pathway, we identified 20 hotspot mutations in KIT among 19 patients. In contrast to GI stromal tumors, most of these were localized to exon 17 and are associated with imatinib resistance (Fig 3B).⁹ KIT mutations were also more common in seminoma than nonseminoma (16 of 54 [29.6%] v five of 126 [4%]; P < .001). Seven additional tumors contained alterations in CBL, a negative regulator of KIT, including one previously identified hotspot mutation (W408R) in the RING finger domain, three X410 splice sites, and one homozygous deletion.^10,11 One activating mutation in GNAQ (Q209P), a common finding in ocular melanoma,¹² was also identified. Four patients had amplifications in KDR and one had an amplification of MET. Potential therapies directed against each of these alterations are provided in Appendix Table A2 (online only).

RAS/ERK pathway mutations were identified in 33 patients (Fig 2A), including 23 hotspot mutations in KRAS in 22 patients (15 at the G12 codon) along with four NRAS mutations (Fig 2A). KRAS mutations were significantly more frequent in seminomas versus nonseminomas (11 of 54 [20%] v 11 of 126 [8.7%]; P = .045). As previously observed,³ the majority of KRAS mutations in nonseminoma (eight of 11 [72.7%]) were present in cisplatin-resistant tumors, as were three of four mutations in NRAS. In contrast, no association between RAS mutation and cisplatin sensitivity was noted for seminoma.³

In keeping with prior work, three hotspot BRAF mutations were also identified⁴ (D594N, D594G, and G466E) and the rate of BRAF mutations within the entire cohort (1.7%) and among patients with cisplatin resistance (2.9%) was low.^3,4 Nine mutations were identified in RAC1 (G12V, n = 3; G12R, n = 2; P34R, Q61R, and Q61K, n = 2; Fig 3C), a member of the Rho family of GTPases, with significant homology to the RAS family, including conserved residues at positions 12, 34, and 61.¹³ The RAC1 mutants identified in the GCT cohort were expressed within HEK293 cells, confirming that each was associated with increased expression of phosphorylated PAK1 and phosphorylated MEK (Fig 3C).

Finally, consistent with prior data, 24 samples (13.3%) had mutually exclusive phosphoinositide 3-kinase (PI3K) pathway mutations, including four PIK3CA E542K mutations, five loss-of-function mutations in PTEN, four missense variants of unknown significance in PTEN (V85F, Q149K, S361N, and Y178 deletion), one AKT1 amplification, two MTOR mutations (T1977K and A1513P), two putative loss of function alterations in TSC1 (F216 frameshift and homozygous deletion), and four novel TSC2 mutations (Fig 2).³ Other notable findings included inactivating mutations or deletions in APC (n = 3); FAT1 (n = 4); AXIN1 (n = 2); EP300, SETD2, and PTPRD (n = 3); and BRCA2 tumor suppressor genes. All mutational and clinical data are available on the cBio Cancer Genomics Portal.¹⁴

DISCUSSION

To our knowledge, ours is the largest series reported to date of advanced GCT analyzed with massively parallel next generation sequencing. We identified TP53 pathway alterations among a significant proportion of patients with cisplatin-resistant disease. In particular, TP53 alterations were present exclusively in patients with cisplatin-resistant tumors (Figs 2A and 2B). In addition, as one might expect for a biomarker of adverse outcome, mutually exclusive TP53/MDM2 alterations were significantly more frequent among patients with unfavorable clinical characteristics, such as categorization in the IGCCCG poor-risk group and having a mediastinal primary tumor site. Although mediastinal origin has no effect on prognosis for seminoma (characterized by chemosensitivity and excellent outcomes), for nonseminoma, it singularly confers poor-risk classification in the IGCCCG model. Furthermore, within the IGCCCG poor-risk group, having a mediastinal primary tumor site is considered the most unfavorable characteristic as it is associated with the lowest rates of PFS and overall survival.⁷ Thus, to our knowledge, the provocative data in this series provide, for the first time, a genetic and biologic basis for the unique and adverse clinical phenotype of these tumors as compared with gonadal nonseminoma and mediastinal seminoma. Furthermore, the association of TP53 pathway alterations with shorter PFS independent of the IGCCCG model supports genomic profiling of advanced GCT, particularly for patients in the IGCCCG intermediate- and poor-risk groups, to enhance risk stratification and facilitate clinical trials of novel treatment strategies.

Potentially actionable alterations were identified in 55% of patients with cisplatin-resistant disease (Appendix Table A2, online only). The most common of these was MDM2 amplification, which has immediate therapeutic implications because seven potent inhibitors of MDM2 are under study in clinical trials with promising results.¹⁵ Furthermore, sensitivity to MDM2 inhibitors is more pronounced in neuroblastoma cell lines that harbor MYCN amplification, an alteration observed in four additional TP53 wild-type but cisplatin-resistant tumors in our cohort.¹⁶ The promise of MDM2 inhibitors in patients with GCT is also supported by in vitro studies of the MDM2 inhibitor nutlin-3, which demonstrated strong antiproliferative and apoptotic activity and synergy with cisplatin in TP53 wild-type, cisplatin-resistant GCT cell lines.^17,18

Potentially targetable alterations were also identified in the PI3K and RAS RTK pathways. Of particular note, nine activating mutations in RAC1 were identified and functionally validated. RAC1 is a Rho family GTPase that shares significant residue homology to RAS and plays a role in cell proliferation, motility, and drug resistance.¹³ RAC1 mutations are rare in human cancers, with only 38 mutations identified in 6,076 samples (0.6%) subjected to WES by The Cancer Genome Atlas. Thus, to our knowledge, the 5% incidence of RAC1 mutations in this cohort makes GCT the cancer type with the highest prevalence of RAC1 mutations reported to date.¹⁴

There are several limitations of this study. Although we identified and validated a genetic basis for cisplatin resistance in a significant proportion of patients with cisplatin-resistant tumors, there remains a large subset of patients for whom cisplatin resistance cannot be explained by the sequencing techniques and methodologies used in this study. We are thus pursuing whole-genome, transcriptome, and epigenome analyses to further define the mechanisms of treatment resistance in such patients. Second, the rate of deaths in the cisplatin-resistant cohort (23.1%) was lower than expected.¹ This probably reflects both the relatively short follow-up after progression to first-line chemotherapy for patients with cisplatin-resistant GCT in our cohort, as well as a high response rate to salvage treatment. In particular, high-dose chemotherapy with stem-cell transplantation has been demonstrated to overcome resistance to standard-dose cisplatin in a sizable proportion of patients with GCT progressing after first-line chemotherapy.^19,20 There were too few recurrent genetic abnormalities to identify associations with response to specific salvage chemotherapy regimens in our cohort, but these associations should be explored in future studies. Third, 49 resistant samples were mixed GCTs that contained teratoma (n = 49), which is known to be cisplatin resistant. Although pure teratomas were excluded from our cohort and we strove to sequence only the nonteratomatous portion of these tumors, we did not perform microdissection. Therefore, a small amount of DNA from the teratoma component could have been sequenced in some cases. However, the finding of TP53 and MDM2 alterations within tumors that did not contain any teratoma makes it unlikely that this had any meaningful effect on our results. Finally, although we identified actionable genomic alterations within tumors from a significant proportion of patients with cisplatin resistance, the frequency of each specific alteration was low, posing a challenge to clinical trial enrollment and targeted drug development in this disease.

Despite these limitations, this series provides, to our knowledge, the first evidence for a genomic basis for cisplatin resistance among a significant proportion of patients with advanced GCT. Our data also provides a potential genomic explanation for the adverse prognosis associated with specific clinical features. In particular, we identified a high rate of TP53 alterations among primary mediastinal nonseminomas, the group of GCT with the highest rates of chemoresistance and poorest outcomes. Furthermore, the prognostic significance of TP53 pathway alterations independent of the current clinically based IGCCCG prognostic model indicates the potential for genomic sequencing to improve upon current risk stratification and provides a rationale for genomic profiling in patients with advanced GCT. Finally, the presence of actionable genomic alterations in nearly half of cisplatin-resistant GCT suggests novel treatment approaches may be of benefit for patients with refractory GCT and indicates a potential advantage of prospective genomic characterization of these tumors.

METHODS

Whole-Exome Sequencing

Of 19 samples, 14 (74%) had ≥ 50% tumor purity. Any sample with evidence of malignant transformation of teratoma was excluded. Matched normal DNA was obtained from peripheral blood in five patients, adjacent nontestis normal parenchyma (eg, lung) in four patients, and adjacent non-neoplastic testis tissue in 10 patients. When adjacent testis tissue was used for comparison against normal, the absence of intratubular germ cell neoplasia was pathologically confirmed. Primary and metastatic lesions were included in this analysis as were both pre- and postchemotherapy specimens. Between 1.5 and 2 μg of genomic DNA was captured by hybridization using the SureSelect XT Human All Exon V4 (Agilent Technologies, Santa Clara, CA). Libraries were prepared according to manufacturer’s instructions. Polymerase chain reaction (PCR) amplification of the libraries was performed, followed by sample barcoding, and all specimens were sequenced on a HiSEquation 2500 in 100 base pair (bp) paired-end runs using the TruSeq SBS Kit V5 (Illumina, San Diego, CA).

Sequence Alignment and Mutation Detection

Sequence alignment and mutation identification were performed as previously described (Johnson BE, et al: Science 343:189-193, 2014). Briefly, paired-end sequencing data from exome-capture libraries were aligned to the reference human genome (hg19) with the Burrows-Wheeler Aligner (Li H, et al: Bioinformatics 25:1754-1760, 2009). Deduplication, base quality recalibration, and multiple-sequence realignment were performed using Picard suite (https://broadinstitute.github.io/picard/) and the Genome Analysis Toolkit (https://software.broadinstitute.org/gatk/) before mutation detection (McKenna A, et al: Genome Res 20:1297-1303, 2010; and DePristo MA, et al: Nat Genet 43:491-498, 2011). BAM files were sorted and analyzed for both point mutations and small insertions and deletions (indels) of less than 50 bp. Single-nucleotide variants were detected using MuTect (https://www.broadinstitute.org/cancer/cga/mutect), a Bayesian framework for the detection of somatic mutations and indels using Pindel (https://github.com/genome/pindel; Cibulskis K, et al: Nat Biotechnol 31:213-219, 2013; and Ye K, et al: Bioinformatics 25:2865-2871, 2009).

RAC1 Experiments

The coding sequences for wild-type RAC1, RAC1^G12R, RAC1^P29S, RAC1^P34R, RAC1^Q61K, and RAC1^Q61R were obtained from Genewiz (South Plainfield, NJ), amplified by PCR to include an N-terminal 3×FLAG epitope tag (Sigma-Aldrich, Saint Louis, Missouri), and subcloned into a pcDNA3 mammalian expression vector (Life Technologies, Grand Island, NY). Expression constructs were transfected into 293T cells using Lipofectamine 2000 (Life Technologies), and cells were collected and lysed in radioimmunoprecipitation assay buffer lysis buffer after 48 hours. GTP-bound Rac1, or active Rac1, was isolated via immunoprecipitation using recombinant p21-binding domain (PBD) of PAK1 (PAK1-PBD; Active Rac1 Detection Kit, catalog no. 8815; Cell Signaling Technology, Danvers, MA), according to the manufacturer’s instructions. Immunoblots were performed using antiRAC1 (antibody no. 4651), antipMEK1/2 (S217/221) (antibody no. 9121), antipPAK1 (T423; (antibody no. 2601), and anti-MEK1/2 (antibody no. 9122) primary antibodies (all from Cell Signaling Technology). Secondary antibodies were then detected using a Fuji LAS-4000 imager (GE Healthcare Life Sciences, Pittsburgh, PA).

Table A1.

Number of Total and Nonsynonymous Mutations in the Discovery Cohort (n = 19)

Table A2.

Potentially Actionable Alterations (n = 75) Among 104 Cisplatin-Resistant Germ Cell Tumors

AUTHOR CONTRIBUTIONS

Conception and design: Aditya Bagrodia, Eugene K. Cha, David B. Solit, Darren R. Feldman

Collection and assembly of data: Aditya Bagrodia, Byron H. Lee, William Lee, Eugene K. Cha, John P. Sfakianos, Gopa Iyer, Eugene J. Pietzak, Sizhi Paul Gao, Samuel D. Kaffenberger, Aijazuddin Syed, Maria E. Arcila, Ritika Kundra, Jana Eng, Joseph Hreiki, Dayna M. Oschwald, Michael F. Berger, Manjit S. Bains, Nikolaus Schultz, Victor E. Reuter, Joel Sheinfeld, George J. Bosl, Hikmat A. Al-Ahmadie, David B. Solit, Darren R. Feldman

Data analysis and interpretation: Aditya Bagrodia, William Lee, Gopa Iyer, Emily C. Zabor, Irina Ostrovnaya, Raju S. Chaganti, Vladimir Vacic, Kanika Arora, Dayna M. Oschwald, Michael F. Berger, Dean F. Bajorin, Nikolaus Schultz, Victor E. Reuter, Joel Sheinfeld, George J. Bosl, Hikmat A. Al-Ahmadie, David B. Solit, Darren R. Feldman

Manuscript writing: All authors

Final approval of manuscript: All authors

Accountable for all aspects of the work: All authors

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

Genetic Determinants of Cisplatin Resistance in Patients With Advanced Germ Cell Tumors

The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or jco.ascopubs.org/site/ifc.

Aditya Bagrodia

No relationship to disclose

Byron H. Lee

No relationship to disclose

William Lee

Employment: Helix OpCo

Leadership: Helix OpCo

Eugene K. Cha

No relationship to disclose

John P. Sfakianos

No relationship to disclose

Gopa Iyer

No relationship to disclose

Eugene J. Pietzak

No relationship to disclose

Sizhi Paul Gao

No relationship to disclose

Emily C. Zabor

No relationship to disclose

Irina Ostrovnaya

No relationship to disclose

Samuel D. Kaffenberger

No relationship to disclose

Aijazuddin Syed

No relationship to disclose

Maria E. Arcila

No relationship to disclose

Raju S. Chaganti

Employment: Cancer Genetics

Leadership: Cancer Genetics

Stock or Other Ownership: Cancer Genetics

Consulting or Advisory Role: Cancer Genetics

Patents, Royalties, Other Intellectual Property: Cancer Genetics

Ritika Kundra

No relationship to disclose

Jana Eng

No relationship to disclose

Joseph Hreiki

Employment: Bristol-Myers Squibb, Interpace Diagnostics

Stock or Other Ownership: Interpace Diagnostics

Travel, Accommodations, Expenses: Bristol-Myers Squibb, Interpace Diagnostics

Vladimir Vacic

Employment: 23andMe

Kanika Arora

No relationship to disclose

Dayna M. Oschwald

No relationship to disclose

Michael F. Berger

Consulting or Advisory Role: Cancer Genetics, Sequenom

Dean F. Bajorin

Consulting or Advisory Role: Bristol-Myers Squibb, Novartis, Roche, Genentech, Merck, Eli Lilly, Fidia Farmaceutici, Eisai, Urogen Pharma

Research Funding: Dendreon (Inst), Novartis (Inst), Amgen (Inst), Genentech (Inst), Merck (Inst), Bristol-Myers Squibb (Inst)

Travel, Accommodations, Expenses: Genentech, Merck

Manjit S. Bains

No relationship to disclose

Nikolaus Schultz

No relationship to disclose

Victor E. Reuter

No relationship to disclose

Joel Sheinfeld

No relationship to disclose

George J. Bosl

No relationship to disclose

Hikmat A. Al-Ahmadie

Consulting or Advisory Role: Genentech

David B. Solit

Honoraria: Novartis, Loxo, Pfizer

Consulting or Advisory Role: Pfizer, Loxo

Darren R. Feldman

Consulting or Advisory Role: Bayer, Gilead Sciences (I), Seattle Genetics

Research Funding: Novartis