Robert J. Pelham

Whole Transcriptome RNA-Seq Analysis of Breast Cancer Recurrence Risk Using Formalin-Fixed Paraffin-Embedded Tumor Tissue

RNA biomarkers discovered by RT-PCR-based gene expression profiling of archival formalin-fixed paraffin-embedded (FFPE) tissue form the basis for widely used clinical diagnostic tests; however, RT-PCR is practically constrained in the number of transcripts that can be interrogated. We have developed and optimized RNA-Seq library chemistry as well as bioinformatics and biostatistical methods for whole transcriptome profiling from FFPE tissue. The chemistry accommodates low RNA inputs and sample multiplexing. These methods both enable rediscovery of RNA biomarkers for disease recurrence risk that were previously identified by RT-PCR analysis of a cohort of 136 patients, and also identify a high percentage of recurrence risk markers that were previously discovered using DNA microarrays in a separate cohort of patients, evidence that this RNA-Seq technology has sufficient precision and sensitivity for biomarker discovery. More than two thousand RNAs are strongly associated with breast cancer recurrence risk in the 136 patient cohort (FDR <10%). Many of these are intronic RNAs for which corresponding exons are not also associated with disease recurrence. A number of the RNAs associated with recurrence risk belong to novel RNA networks. It will be important to test the validity of these novel associations in whole transcriptome RNA-Seq screens of other breast cancer cohorts.

Detection of ubiquitous and heterogeneous mutations in cell-free DNA from patients with early-stage non-small-cell lung cancer

BACKGROUND The aim of this pilot study was to assess whether both ubiquitous and heterogeneous somatic mutations could be detected in cell-free DNA (cfDNA) from patients with early-stage non-small-cell lung cancer (NSCLC). PATIENTS AND METHODS Three stage I and one stage II primary NSCLC tumors were subjected to multiregion whole-exome sequencing (WES) and validated with AmpliSeq. A subset of ubiquitous and heterogeneous single-nucleotide variants (SNVs) were chosen. Multiplexed PCR using custom-designed primers, coupled with next-generation sequencing (mPCR-NGS), was used to detect these SNVs in both tumor DNA and cfDNA isolated from plasma obtained before surgical resection of the tumors. The limit of detection for each assay was determined using cfDNA from 48 presumed-normal healthy volunteers. RESULTS Tumor DNA and plasma-derived cfDNA was successfully amplified and sequenced for 37/50 (74%) SNVs using the mPCR-NGS method. Twenty-five (68%) were ubiquitous and 12 (32%) were heterogeneous SNVs. Variant detection by mPCR-NGS and WES-AmpliSeq in tumor tissue was well correlated (R(2) = 0.8722, P < 0.0001). Sixteen (43%) out of 37 SNVs were detected in cfDNA. Twelve of these were ubiquitous SNVs with a variant allele frequency (VAF) range of 0.15-23.25%, and four of these were heterogeneous SNVs with a VAF range of 0.28-1.71%. There was a statistically significant linear relationship between the VAFs for tumor and cfDNA (R(2) = 0.5144; P = 0.0018). For all four patients, at least two variants were detected in plasma. The estimated number of copies of variant DNA present in each sample ranged from 5 to 524. The average number of variant copies required for detection (VCRD) was 3.16 (range: 0.2-7.6 copies). CONCLUSIONS The mPCR-NGS method revealed intratumor heterogeneity in early-stage NSCLC tumors, and was able to detect both ubiquitous and heterogeneous SNVs in cfDNA. Further validation of mPCR-NGS in cfDNA is required to define its potential use in clinical practice.

Modulators of Sensitivity and Resistance to Inhibition of PI3K Identified in a Pharmacogenomic Screen of the NCI-60 Human Tumor Cell Line Collection

The phosphoinositide 3-kinase (PI3K) signaling pathway is significantly altered in a wide variety of human cancers, driving cancer cell growth and survival. Consequently, a large number of PI3K inhibitors are now in clinical development. To begin to improve the selection of patients for treatment with PI3K inhibitors and to identify de novo determinants of patient response, we sought to identify and characterize candidate genomic and phosphoproteomic biomarkers predictive of response to the selective PI3K inhibitor, GDC-0941, using the NCI-60 human tumor cell line collection. In this study, sixty diverse tumor cell lines were exposed to GDC-0941 and classified by GI50 value as sensitive or resistant. The most sensitive and resistant cell lines were analyzed for their baseline levels of gene expression and phosphorylation of key signaling nodes. Phosphorylation or activation status of both the PI3K-Akt signaling axis and PARP were correlated with in vitro response to GDC-0941. A gene expression signature associated with in vitro sensitivity to GDC-0941 was also identified. Furthermore, in vitro siRNA-mediated silencing of two genes in this signature, OGT and DDN, validated their role in modulating sensitivity to GDC-0941 in numerous cell lines and begins to provide biological insights into their role as chemosensitizers. These candidate biomarkers will offer useful tools to begin a more thorough understanding of determinants of patient response to PI3K inhibitors and merit exploration in human cancer patients treated with PI3K inhibitors.

Detection of Clonal and Subclonal Copy-Number Variants in Cell-Free DNA from Patients with Breast Cancer Using a Massively Multiplexed PCR Methodology.

We demonstrate proof-of-concept for the use of massively multiplexed PCR and next-generation sequencing (mmPCR-NGS) to identify both clonal and subclonal copy-number variants (CNVs) in circulating tumor DNA. This is the first report of a targeted methodology for detection of CNVs in plasma. Using an in vitro model of cell-free DNA, we show that mmPCR-NGS can accurately detect CNVs with average allelic imbalances as low as 0.5%, an improvement over previously reported whole-genome sequencing approaches. Our method revealed differences in the spectrum of CNVs detected in tumor tissue subsections and matching plasma samples from 11 patients with stage II breast cancer. Moreover, we showed that liquid biopsies are able to detect subclonal mutations that may be missed in tumor tissue biopsies. We anticipate that this mmPCR-NGS methodology will have broad applicability for the characterization, diagnosis, and therapeutic monitoring of CNV-enriched cancers, such as breast, ovarian, and lung cancer.

Identification of prostate cancer-expressed microRNAs associated with clinical recurrence (cR) and prostate cancer-specific survival (PCSS) following radical prostatectomy (RP).

21 Background: We previously identified messenger RNAs (mRNAs) whose expression can distinguish aggressive from indolent prostate cancer. Representing multiple key genomic pathways, these mRNAs are significantly associated with cR and PCSS after RP, providing prognostic information beyond PSA, cT stage and Gleason Score. We evaluated microRNA expression in the same specimens for association with cR and PCSS. METHODS All cT1/cT2 prostate cancer pts treated with RP at Cleveland Clinic from 1987-2004 were identified (n~2,600), of which 127 pts w/ cR and 374 pts w/o cR after RP were randomly selected using cohort sampling. RNA was purified from 2 macrodissected FPE tumor specimens per pt. Expression of 76 test and 5 reference microRNAs was quantified by RT-PCR. Cox regression and control of the false discovery rate (FDR) was used to assess reference-normalized microRNA and mRNA expression for association with cR and PCSS. RESULTS 106 pts with cR and 310 without cR had sufficient RNA and successful microRNA assays. Analysis of primary Gleason pattern tumor tissue for each pt identified 21 microRNAs associated with cR and 13 microRNAs associated with PCSS, with FDR at 10%; 8 microRNAs were associated with both endpoints. Similar analysis of highest Gleason pattern tumor tissue for each pt identified 22 microRNAs associated with cR (17 overlapping with those for the primary Gleason pattern) and 7 microRNAs associated with PCSS, with FDR at 10%; 4 were associated with both endpoints. miR-1, miR-21, miR-93, and miR-106b were associated with both cR and PCSS in primary and highest Gleason pattern specimens. The 76 microRNAs in this study tended to have weaker association with cR and PCSS than the 732 mRNAs. In multivariate analyses, mRNAs and microRNAs provided prognostic information beyond PSA, cT stage, and biopsy Gleason score. MicroRNAs co-express more frequently with each other than with mRNAs, which may indicate distinct biological regulation. CONCLUSIONS Expression of some microRNAs assayed in FPE prostate tumor tissue was associated with cR and PCSS after RP in this study, and may retain prognostic value in the face of tumor heterogeneity.

Abstract P4-02-03: Detection of single nucleotide variations and copy number variations in breast cancer tissue and ctDNA samples using single-nucleotide polymorphism-targeted massively multiplexed PCR

Genomic instability, the hallmark of cancer, presents with a variety of mutation types, most commonly single nucleotide variations (SNVs) and copy number variations (CNVs), which traditionally have required different methods for identification. It has proven challenging to simultaneously achieve sufficient breadth to detect CNVs and depth to detect SNVs on samples of limited input amount. The objective of this study was to validate a new methodology for detection of SNVs and CNVs in a single assay. We used a massively multiplex PCR/NGS approach combining an SNV panel covering 585 point mutation hotspots in breast cancer (Cosmic) and a CNV panel targeting 28,000 SNPs designed to detect copy number at chromosomes 1, 2, 13, 18, 21, and X, and focal regions 4p16, 5p15, 7q11, 15q, 17p, 22q11, and 22q13. We applied these panels to breast cancer cell lines and fresh frozen (FF) breast tumor samples; the presence of CNVs in circulating cell-free tumor DNA (ctDNA) in the plasma of breast cancer patients was also investigated. The CNV assay methodology was validated using genomic DNA isolated from 96 human samples with known karyotype; sensitivity to single region deletions or duplications was 100% (71/71) and specificity was 100% for normal regions in the same samples. Single-molecule sensitivity for the detection of CNVs was established by analyzing isolated single cells. Performance of the mutation assay was demonstrated with the analysis of 5 matched tumor and normal cell lines, with 24 out of 27 SNVs known to be present in these cell lines detected. The 3 undetected SNVs were determined to be a result of assay design failure. Also, multiple somatic CNVs (median: 13) were detected in all 5 tumor cell lines. Analysis of the normal cell lines found no cancer related SNVs or CNVs. In 32 FF tumor samples, 78.1% (25/32) had SNVs detected; of samples with SNVs, 88% (22/25) had SNVs in TP53 or PIK3CA. Of the same 32 FF breast tumor samples, 96.9% (31/32) showed full or partial CNVs in at least 1 and up to 15 regions; of the 31 samples with detected CNVs, 93.5% had a CNV of either 1q or 17p, two of the three most prevalent breast cancer CNVs (the 16q region was not represented in this panel). Overall, a combination of SNV and CNV testing allowed identification of genetic changes in 100% of the breast tumor samples, a significant improvement in diagnostic yield than using SNV detection alone. Of the 12 breast cancer patients with matched tumor tissue and plasma samples, 83.3% (10/12) had CNVs detected in tissue. The CNVs present in each primary tumor sample were identified in corresponding plasma ctDNA samples (1 stage IIa, 7 stage IIb, and 2 stage III). The ctDNA fractions in these samples ranged from 0.58 to 4.33%; detection required as few as 86 heterozygous SNPs per CNV. Analysis of ctDNA for cancer-associated mutations may allow earlier, safer and more accurate profiling and monitoring of breast cancer. Thus, this targeted PCR approach offers the promise of an assay able to detect both cancer-associated SNVs and CNVs in the same sample with good sensitivity and specificity, and improved detection rates compared to assays that only detect SNVs. Citation Format: Robert J Pelham, Bernhard G Zimmermann, Eser Kirkizlar, Ryan K Swenerton, Bin Hoang, Onur Sakarya, Joshua E Babiarz, Nicholas Wayham, Tudor Constantin, Styrmir Sigurjonsson, Matthew Rabinowitz, Matthew Hill. Detection of single nucleotide variations and copy number variations in breast cancer tissue and ctDNA samples using single-nucleotide polymorphism-targeted massively multiplexed PCR [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-02-03.

Abstract 3436: Ameloblastoma driver mutations revealed by next-generation sequencing of formalin-fixed paraffin-embedded specimens

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Rare cancer types are not only understudied, but are typically represented by formalin-fixed paraffin-embedded (FFPE) (rather than freshly-frozen) specimens that are suboptimal for genomic analysis. Ameloblastoma is one such rare tumor type, thought to arise from ameloblasts, the cells that deposit enamel during tooth development. Though typically benign, ameloblastomas are locally destructive to the jaw and face, and new non-surgical interventions are needed. To discover novel driver mutations and therapeutic targets, we optimized methods and performed whole-transcriptome sequencing and/or targeted exon sequencing (TruSeq Cancer Panel) of 8 FFPE cases. Identified mutations were verified, and then evaluated on a larger, independent set of 21 FFPE cases by PCR and Sanger sequencing. From the analysis, we identified recurrent somatic mutations in three key developmental or signaling pathways, including Hedgehog, fibroblast growth factor, and MAP kinase pathways. Functional interrogation of a novel Hedgehog pathway mutation confirmed increased basal pathway activity, and defined the response profile to various pharmacologic Hedgehog inhibitors. Together, our results define new ameloblastoma drivers and nominate new molecularly-directed therapies for this rare but disfiguring disease. More generally, our findings validate a robust approach for discovering driver mutations in rare cancers. Citation Format: Andrew C. McClary, Robert T. Sweeney, Jewison Biscocho, Benjamin R. Myers, Lila Neahring, Kevin A. Kwei, Kunbin Qu, Xue Gong, Tony Ng, Carol D. Jones, Sushama Varma, Justin I. Odegaard, Brian Rubin, Megan L. Troxell, Robert J. Pelham, James L. Zehnder, Philip A. Beachy, Jonathan R. Pollack, Robert B. West. Ameloblastoma driver mutations revealed by next-generation sequencing of formalin-fixed paraffin-embedded specimens. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3436. doi:10.1158/1538-7445.AM2014-3436

Abstract 5456: Functional genomics reveals diverse cellular processes that modulate tumor cell response to oxaliplatin

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Oxaliplatin is widely used to treat colorectal cancer, as both adjuvant therapy for resected disease and palliative treatment of metastatic disease. However, a significant number of patients experience serious side effects from oxaliplatin treatment, including prolonged neurotoxicity, creating an urgent need for biomarkers of oxaliplatin response or resistance to direct therapy to those most likely to benefit. As a first step to improve selection of patients for oxaliplatin-based chemotherapy, we have conducted an in vitro cell-based small interfering RNA (siRNA) screen of 500 genes aimed at identifying genes whose loss of expression alters tumor cell response to oxaliplatin. The siRNA screen identified twenty-seven genes, that when silenced, significantly altered colon tumor cell line sensitivity to oxaliplatin. Silencing of a group of putative resistance genes increased the extent of oxaliplatin-mediated DNA damage and inhibited cell cycle progression in oxaliplatin-treated cells. The activity of several signaling nodes, including AKT1 and MEK1, was also altered. We used cDNA transfection to over-express two genes (LTBR and TMEM30A) that were identified in the siRNA screen as mediators of oxaliplatin sensitivity. In both instances, over-expression conferred resistance to oxaliplatin. In summary, this study identifies numerous putative predictive biomarkers of response to oxaliplatin which should be studied further in patient specimens for potential clinical application. Diverse gene networks appear to influence tumor survival in response to DNA damage by oxaliplatin. Finally, those genes whose loss of expression (or function) is related to oxaliplatin sensitivity may be promising therapeutic targets to increase patient response to oxaliplatin. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5456. doi:10.1158/1538-7445.AM2011-5456