Search

Purpose: Not all patients with metastatic castration-resistant prostate cancer (mCRPC) have sufficient tumor tissue available for multigene molecular testing. Furthermore, samples may fail because of difficulties within the testing procedure. Optimization of screening techniques may reduce failure rates; however, a need remains for additional testing methods to detect cancers with alterations in homologous recombination repair genes. We evaluated the utility of plasma-derived circulating tumor DNA (ctDNA) in identifying deleterious BRCA1, BRCA2 (BRCA), and ATM alterations in screened patients with mCRPC from the phase III PROfound study. Patients and Methods: Tumor tissue samples were sequenced prospectively at Foundation Medicine, Inc. (FMI) using an investigational next-generation sequencing (NGS) assay based on FoundationOne®CDx to inform trial eligibility. Matched ctDNA samples were retrospectively sequenced at FMI, using an investigational assay based on FoundationOne®Liquid CDx. Results: 81% (503/619) of ctDNA samples yielded an NGS result, of which 491 had a tumor tissue result. BRCA and ATM status in tissue compared with ctDNA showed 81% positive percentage agreement and 92% negative percentage agreement, using tissue as reference. At variant-subtype level, using tissue as reference, concordance was high for nonsense (93%), splice (87%), and frameshift (86%) alterations but lower for large rearrangements (63%) and homozygous deletions (27%), with low ctDNA fraction being a limiting factor. Conclusions: We demonstrate that ctDNA can greatly complement tissue testing in identifying patients with mCRPC and BRCA or ATM alterations who are potentially suitable for receiving targeted PARP inhibitor treatments, particularly patients with no or insufficient tissue for genomic analyses.

Marker genes for the monocyte-macrophage-DC subpopulations identified in Supplementary Figure 5H. Only genes with adjusted p-value < 0.01 and average log fold-change > 0.3 were included. gene, gene name; p_val, p-value calculated based on Wilcoxon test; avg_logFC, log fold-change of the average expression between the given cluster and all other clusters; pct.1, fraction of gene-expressing cells in the given cluster; pct.2, fraction of gene-expressing cells in all other clusters; pct.diff, Difference between the percentage of gene-expressing cells in the given cluster and all other clusters; p_val_adj, Bonferroni adjusted p-value; cluster, cluster annotation based on the gene markers identified; resolution, clustering resolution parameter used in Seurat.

Figure S6

Pharmacodynamics of STAT3 ASO in CT26 STK11 KO model. (A) Percentage of CD45+ immune cells among live cells from untreated or drug-treated STK11 KO CT26 tumors as indicated. (B) Percentage of Ly6G+ granulocytic cells among live CD45+ cells. (C) Percentage of intratumoral CD103+ cDC1 dendritic cells among CD45+ immune cells. (D) CD86 MFI of CD103+ cDC1s. (E) Percentage of migratory DC among CD45+ cells in TDLN of tumor engrafted mice. (F) CD86 MFI of these migratory DC in TDLNs. (G) Flow cytometry plots of CD86 levels on TDLN migratory DC. (H) Percentage of CD64+ CD11b+ myeloid cells among live intratumoral CD45+ cells. (I) Flow cytometry plots of CD86 on these CD64+ CD11b+ myeloid cells. (J) Percentages of MHCII+ CD206+ intratumoral myeloid cells. (K) Percentage of MHCII+ CD163+ intratumoral myeloid cells.

Table S3

The utility of circulating tumor DNA (ctDNA) as a biomarker in patients with advanced cancers receiving immunotherapy is uncertain. We therefore analyzed pretreatment (n = 978) and on-treatment (n = 171) ctDNA samples across 16 advanced-stage tumor types from three phase I/II trials of durvalumab (± the anti-CTLA4 therapy tremelimumab). Higher pretreatment variant allele frequencies (VAF) were associated with poorer overall survival (OS) and other known prognostic factors, but not objective response, suggesting a prognostic role for patient outcomes. On-treatment reductions in VAF and lower on-treatment VAF were independently associated with longer progression-free survival and OS and increased objective response rate, but not prognostic variables, suggesting that on-treatment ctDNA dynamics are predictive of benefit from immune checkpoint blockade. Accordingly, we propose a concept of “molecular response” using ctDNA, incorporating both pretreatment and on-treatment VAF, that predicted long-term survival similarly to initial radiologic response while also permitting early differentiation of responders among patients with initially radiologically stable disease.Significance:In a pan-cancer analysis of immune checkpoint blockade, pretreatment ctDNA levels appeared prognostic and on-treatment dynamics predictive. A “molecular response” metric identified long-term responders and adjudicated benefit among patients with initially radiologically stable disease. Changes in ctDNA may be more dynamic than radiographic changes and could complement existing trial endpoints.This article is highlighted in the In This Issue feature, p. 1775

Supplementary Appendix

Mutations in the STK11 (LKB1) gene regulate resistance to PD-1/PD-L1 blockade. This study evaluated this association in patients with nonsquamous non–small cell lung cancer (NSCLC) enrolled in three phase I/II trials. STK11 mutations were associated with resistance to the anti–PD-L1 antibody durvalumab (alone/with the anti-CTLA4 antibody tremelimumab) independently of KRAS mutational status, highlighting STK11 as a potential driver of resistance to checkpoint blockade. Retrospective assessments of tumor tissue, whole blood, and serum revealed a unique immune phenotype in patients with STK11 mutations, with increased expression of markers associated with neutrophils (i.e., CXCL2, IL6), Th17 contexture (i.e., IL17A), and immune checkpoints. Associated changes were observed in the periphery. Reduction of STAT3 in the tumor microenvironment using an antisense oligonucleotide reversed immunotherapy resistance in preclinical STK11 knockout models. These results suggest that STK11 mutations may hinder response to checkpoint blockade through mechanisms including suppressive myeloid cell biology, which could be reversed by STAT3-targeted therapy.Significance:Patients with nonsquamous STK11-mutant (STK11mut) NSCLC are less likely than STK11 wild-type (STK11wt) patients to respond to anti–PD-L1 ± anti-CTLA4 immunotherapies, and their tumors show increased expression of genes and cytokines that activate STAT3 signaling. Preclinically, STAT3 modulation reverses this resistance, suggesting STAT3-targeted agents as potential combination partners for immunotherapies in STK11mut NSCLC.This article is highlighted in the In This Issue feature, p. 2659

Supplementary Data from Identification of a Molecularly-Defined Subset of Breast and Ovarian Cancer Models that Respond to WEE1 or ATR Inhibition, Overcoming PARP Inhibitor Resistance

Supplementary Figure from Detection of BRCA1, BRCA2, and ATM Alterations in Matched Tumor Tissue and Circulating Tumor DNA in Patients with Prostate Cancer Screened in PROfound

Supplementary Data from Detection of BRCA1, BRCA2, and ATM Alterations in Matched Tumor Tissue and Circulating Tumor DNA in Patients with Prostate Cancer Screened in PROfound

Purpose:Not all patients with metastatic castration-resistant prostate cancer (mCRPC) have sufficient tumor tissue available for multigene molecular testing. Furthermore, samples may fail because of difficulties within the testing procedure. Optimization of screening techniques may reduce failure rates; however, a need remains for additional testing methods to detect cancers with alterations in homologous recombination repair genes. We evaluated the utility of plasma-derived circulating tumor DNA (ctDNA) in identifying deleterious BRCA1, BRCA2 (BRCA), and ATM alterations in screened patients with mCRPC from the phase III PROfound study.Patients and Methods:Tumor tissue samples were sequenced prospectively at Foundation Medicine, Inc. (FMI) using an investigational next-generation sequencing (NGS) assay based on FoundationOne®CDx to inform trial eligibility. Matched ctDNA samples were retrospectively sequenced at FMI, using an investigational assay based on FoundationOne®Liquid CDx.Results:81% (503/619) of ctDNA samples yielded an NGS result, of which 491 had a tumor tissue result. BRCA and ATM status in tissue compared with ctDNA showed 81% positive percentage agreement and 92% negative percentage agreement, using tissue as reference. At variant-subtype level, using tissue as reference, concordance was high for nonsense (93%), splice (87%), and frameshift (86%) alterations but lower for large rearrangements (63%) and homozygous deletions (27%), with low ctDNA fraction being a limiting factor.Conclusions:We demonstrate that ctDNA can greatly complement tissue testing in identifying patients with mCRPC and BRCA or ATM alterations who are potentially suitable for receiving targeted PARP inhibitor treatments, particularly patients with no or insufficient tissue for genomic analyses.

Purpose:PARP inhibitors (PARPi) induce synthetic lethality in homologous recombination repair (HRR)-deficient tumors and are used to treat breast, ovarian, pancreatic, and prostate cancers. Multiple PARPi resistance mechanisms exist, most resulting in restoration of HRR and protection of stalled replication forks. ATR inhibition was highlighted as a unique approach to reverse both aspects of resistance. Recently, however, a PARPi/WEE1 inhibitor (WEE1i) combination demonstrated enhanced antitumor activity associated with the induction of replication stress, suggesting another approach to tackling PARPi resistance.Experimental Design:We analyzed breast and ovarian patient-derived xenoimplant models resistant to PARPi to quantify WEE1i and ATR inhibitor (ATRi) responses as single agents and in combination with PARPi. Biomarker analysis was conducted at the genetic and protein level. Metabolite analysis by mass spectrometry and nucleoside rescue experiments ex vivo were also conducted in patient-derived models.Results:Although WEE1i response was linked to markers of replication stress, including STK11/RB1 and phospho-RPA, ATRi response associated with ATM mutation. When combined with olaparib, WEE1i could be differentiated from the ATRi/olaparib combination, providing distinct therapeutic strategies to overcome PARPi resistance by targeting the replication stress response. Mechanistically, WEE1i sensitivity was associated with shortage of the dNTP pool and a concomitant increase in replication stress.Conclusions:Targeting the replication stress response is a valid therapeutic option to overcome PARPi resistance including tumors without an underlying HRR deficiency. These preclinical insights are now being tested in several clinical trials where the PARPi is administered with either the WEE1i or the ATRi.

Purpose: Maintenance therapy with olaparib has improved progression-free survival in women with high-grade serous ovarian cancer (HGSOC), particularly those harboring BRCA1/2 mutations. The objective of this study was to characterize long-term (LT) versus short-term (ST) responders to olaparib.Experimental Design: A comparative molecular analysis of Study 19 (NCT00753545), a randomized phase II trial assessing olaparib maintenance after response to platinum-based chemotherapy in HGSOC, was conducted. LT response was defined as response to olaparib/placebo >2 years, ST as BRCA1/2 status, three-biomarker homologous recombination deficiency (HRD) score, BRCA1 methylation, and mutational profiling. Another olaparib maintenance study (Study 41; NCT01081951) was used as an additional cohort.Results: Thirty-seven LT (32 olaparib) and 61 ST (21 olaparib) patients were identified. Treatment was significantly associated with outcome (P < 0.0001), with more LT patients on olaparib (60.4%) than placebo (11.1%). LT sensitivity to olaparib correlated with complete response to chemotherapy (P < 0.05). In the olaparib LT group, 244 genetic alterations were detected, with TP53, BRCA1, and BRCA2 mutations being most common (90%, 25%, and 35%, respectively). BRCA2 mutations were enriched among the LT responders. BRCA methylation was not associated with response duration. High myriad HRD score (>42) and/or BRCA1/2 mutation was associated with LT response to olaparib. Study 41 confirmed the correlation of LT response with olaparib and BRCA1/2 mutation.Conclusions: Findings show that LT response to olaparib may be multifactorial and related to homologous recombination repair deficiency, particularly BRCA1/2 defects. The type of BRCA1/2 mutation warrants further investigation. Clin Cancer Res; 23(15); 4086–94. ©2017 AACR.

SV loads in non-BRCA1/2 HR genes per sample by SV type

Purpose: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with distinct molecular subtypes. The most established subtyping approach, the “Cell of Origin” (COO) algorithm, categorizes DLBCL into activated B-cell (ABC) and germinal center B-cell (GCB)-like subgroups through gene expression profiling. Recently developed immunohistochemical (IHC) techniques and other established methodologies can deliver discordant results and have various technical limitations. We evaluated the NanoString nCounter gene expression system to address issues with current platforms.Experimental Design: We devised a scoring system using 145 genes from published datasets to categorize DLBCL samples. After cell line validation, clinical tissue segmentation was tested using commercially available diagnostic DLBCL samples. Finally, we profiled biopsies from patients with relapsed/refractory DLBCL enrolled in the fostamatinib phase IIb clinical trial using three independent RNA expression platforms: NanoString, Affymetrix, and qNPA.Results: Diagnostic samples showed a typical spread of subtypes with consistent gene expression profiles across matched fresh, frozen, and formalin-fixed paraffin-embedded tissues. Results from biopsy samples across platforms were remarkably consistent, in contrast to published IHC data. Interestingly, COO segmentation of longitudinal fostamatinib biopsies taken at initial diagnosis and then again at primary relapse showed 88% concordance (15/17), suggesting that COO designation remains stable over the course of disease progression.Conclusions: DLBCL segmentation of patient tumor samples is possible using a number of expression platforms. However, we found that NanoString offers the most flexibility and fewest limitations in regards to robust clinical tissue subtype characterization. These subtype distinctions should help guide disease prognosis and treatment options within DLBCL clinical practice. Clin Cancer Res; 21(10); 2367–78. ©2014 AACR.See related commentary by Rimsza, p. 2204

Syngeneic mouse tumor efficacy, STAT3, and gene expression changes

Purpose: To characterize the gene expression profiles of endometrioid endometrial cancers associated with lymph node metastasis in an effort to identify genes associated with metastatic spread.Experimental Design: Tumors from 41 patients with endometrioid endometrial cancer grossly confined to the uterine cavity were evaluated. Positive lymph nodes were noted in 12 of 41 patients. RNA was analyzed for gene expression using the Affymetrix HG133A and HG133B GeneChip set, representing 45,000 array features covering >28,000 UniGene clusters. Data analysis was done using multidimensional scaling, binary comparison, and hierarchical clustering. Gene expression for several differentially expressed genes was examined using quantitative PCR.Results: Gene expression data was obtained from 30,964 genes that were detected in at least 5% of the cases. Supervised analysis of node-positive versus node-negative cases indicated that 450 genes were significantly differentially expressed between the two classes at P < 0.005, 81 of which were differentially expressed by at least 2-fold at P < 0.005. Overexpressed genes included two cell cycle checkpoint genes, CDC2 and MAD2L1, which have previously been described in association with lymph node metastasis in other cancer types. The ZIC2 zinc finger gene was overexpressed in endometrial cancers with positive nodes versus those with negative nodes.Conclusion: Gene expression profiling of the primary tumors in patients with endometrioid endometrial cancers seems promising for identifying genes associated with lymph node metastasis. Future studies should address whether the status of nodal metastasis can be determined from the expression profiles of preoperative tissue specimens.

Supplementary Figures S1-S4 from Accelerated Preclinical Testing Using Transplanted Tumors from Genetically Engineered Mouse Breast Cancer Models

Supplementary Data from Multiomic Characterization of High-Grade Serous Ovarian Carcinoma Enables High-Resolution Patient Stratification

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Purpose: Cancer/testis (CT) genes predominantly expressed in the testis (germ cells) and generally not in other normal tissues are aberrantly expressed in human cancers. This highly restricted expression provides a unique opportunity to use these CT genes for diagnostics, immunotherapeutic, or other targeted therapies. The purpose of this study was to identify those CT genes with the greatest incidence of expression in uterine cancers.Experimental Design: We queried the expression of known and putative CT gene transcripts (representing 79 gene loci) using whole genome gene expression arrays. Specifically, the global gene expressions of uterine cancers (n = 122) and normal uteri (n = 10) were determined using expression data from the Affymetrix HG-U133A and HG-U133B chips. Additionally, we also examined the brother of the regulator of imprinted sites (BORIS) transcript by reverse transcription-PCR and quantitative PCR because its transcript was not represented on the array.Results: Global microarray analysis detected many CT genes expressed in various uterine cancers; however, no individual CT gene was expressed in more than 25% of all cancers. The expression of the two most commonly expressed CT genes on the arrays, MAGEA9 (24 of 122 cancers and 0 of 10 normal tissues) and Down syndrome critical region 8 (DSCR8)/MMA1 (16 if 122 cancers and 0 of 10 normal tissues), was confirmed by reverse transcription-PCR methods, validating the array screening approach. In contrast to the relatively low incidence of expression of the other CT genes, BORIS expression was detected in 73 of 95 (77%) endometrial cancers and 24 of 31 (77%) uterine mixed mesodermal tumors.Conclusions: These data provide the first extensive survey of multiple CT genes in uterine cancers. Importantly, we detected a high frequency of BORIS expression in uterine cancers, suggesting its potential as an immunologic or diagnostic target for these cancers. Given the high incidence of BORIS expression and its possible regulatory role, an examination of BORIS function in the etiology of these cancers is warranted.

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Class comparison data

Supplementary Figures: Supplementary Figure 1. Summary of duration on AZD9496 therapy, previous therapies, and circulating biomarkers status at baseline for each patient ranked by ascending dose; Supplementary Figure 2. Tumor pharmacodynamics. Supplementary Tables: Supplementary Table 1. Study Plan showing time-points of collection of biosamples for exploratory research; Supplementary Table 2. ddPCR primers and probes;Supplementary Table 3. Antibodies and conditions for IHC analysis Antibodies for IHC analysis; Supplementary Table 4. Patients with {greater than or equal to}1 CTC/7.5 mL WB within 120 days of fulvestrant wash-out period prior C1D1.

Patient STAT reductions and reproducibility of replicates

Purpose: The goal of this study was to determine whether distinct gene expression profiles are associated with intrinsic and/or acquired chemoresistance in epithelial ovarian carcinoma.Experimental Design: Gene expression profiles were generated from 21 primary chemosensitive tumors and 24 primary chemoresistant tumors using cDNA-based microarrays. Gene expression profiles of both groups of primary tumors were then compared with those of 15 ovarian carcinomas obtained following platinum-based chemotherapy (“postchemotherapy” tumors). A theme discovery tool was used to identify functional categories of genes involved in drug resistance.Results: Comparison of primary chemosensitive and chemoresistant tumors revealed differential expression of 85 genes (P < 0.001). Comparison of gene expression profiles of primary chemosensitive tumors and postchemotherapy tumors revealed more robust differences with 760 genes differentiating the two groups (P < 0.001). In contrast, only 230 genes were differentially expressed between primary chemoresistant and postchemotherapy groups (P < 0.001). Common to both gene lists were 178 genes representing transcripts differentially expressed between postchemotherapy tumors and all primary tumors irrespective of intrinsic chemosensitivity. The gene expression profile of postchemotherapy tumors compared with that of primary tumors revealed statistically significant overrepresentation of genes encoding extracellular matrix–related proteins.Conclusions: These data show that gene expression profiling can discriminate primary chemoresistant from primary chemosensitive ovarian cancers. Gene expression profiles were also identified that correlate with states of intrinsic and acquired chemoresistance and that represent targets for future investigation and potential therapeutic interventions.

Supplemental Figure 3. COO correlations across platforms

Patient sample details

Supplementary Figure S1 from Gene Expression Profiles Associated with Response to Chemotherapy in Epithelial Ovarian Cancers

Purpose:Common resistance mechanisms to endocrine therapy (ET) in estrogen receptor (ER)–positive metastatic breast cancers include, among others, ER loss and acquired activating mutations in the ligand-binding domain of the ER gene (ESR1LBDm). ESR1 mutational mediated resistance may be overcome by selective ER degraders (SERD). During the first-in-human study of oral SERD AZD9496, early changes in circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) were explored as potential noninvasive tools, alongside paired tumor biopsies, to assess pharmacodynamics and early efficacy.Experimental Design:CTC were enumerated/phenotyped for ER and Ki67 using CellSearch in serial blood draws. ctDNA was assessed for the most common ESR1LBDm by droplet digital PCR (BioRad).Results:Before starting AZD9496, 11 of 43 (25%) patients had ≥5 CTC/7.5 mL whole blood (WB), none of whom underwent reduction to +, two of whom had CTC-ER+ reduction. CTC-Ki67 status did not change appreciably. Patients with ≥5 CTC/7.5 mL WB before treatment had worse progression-free survival (PFS) than patients with P = 0.0003). Fourteen of 45 (31%) patients had ESR1LBDm+ ctDNA at baseline, five of whom had ≥2 unique mutations. Baseline ESR1LBDm status was not prognostic. Patients with persistently elevated CTC and/or ESR1LBDm+ ctDNA at C1D15 had worse PFS than patients who did not (P = 0.0007).Conclusions:Elevated CTC at baseline was a strong prognostic factor in this cohort. Early on-treatment changes were observed in CTC-ER+ and ESR1LBDm+ ctDNA, but not in overall CTC number. Integrating multiple biomarkers in prospective trials may improve outcome prediction and ET resistance mechanisms' identification over a single biomarker.

Purpose: To develop a clinically viable gene expression assay to measure RAS/RAF/MEK/ERK (RAS–ERK) pathway output suitable for hypothesis testing in non–small cell lung cancer (NSCLC) clinical studies.Experimental Design: A published MEK functional activation signature (MEK signature) that measures RAS–ERK functional output was optimized for NSCLC in silico. NanoString assays were developed for the NSCLC optimized MEK signature and the 147-gene RAS signature. First, platform transfer from Affymetrix to NanoString, and signature modulation following treatment with KRAS siRNA and MEK inhibitor, were investigated in cell lines. Second, the association of the signatures with KRAS mutation status, dynamic range, technical reproducibility, and spatial and temporal variation was investigated in NSCLC formalin-fixed paraffin-embedded tissue (FFPET) samples.Results: We observed a strong cross-platform correlation and modulation of signatures in vitro. Technical and biological replicates showed consistent signature scores that were robust to variation in input total RNA; conservation of scores between primary and metastatic tumor was statistically significant. There were statistically significant associations between high MEK (P = 0.028) and RAS (P = 0.003) signature scores and KRAS mutation in 50 NSCLC samples. The signatures identify overlapping but distinct candidate patient populations from each other and from KRAS mutation testing.Conclusions: We developed a technically and biologically robust NanoString gene expression assay of MEK pathway output, compatible with the quantities of FFPET routinely available. The gene signatures identified a different patient population for MEK inhibitor treatment compared with KRAS mutation testing. The predictive power of the MEK signature should be studied further in clinical trials. Clin Cancer Res; 23(6); 1471–80. ©2016 AACR.See related commentary by Xue and Lito, p. 1365

Patient tumor gene expression data