Abstract P4-09-19: Comprehensive multiplatform molecular profiling identifies potentially targetable biomarkers in malignant phyllodes tumors of the breast

Introduction: Malignant phyllodes tumors are rare breast malignancies (0.1% of all breast tumors) with limited effective treatment options for recurrent and metastatic disease. Recent trials indicated a potential for anti-angiogenic therapy in soft tissue sarcomas, which led us to investigate these pathways.

Materials and Methods: Thirty-five malignant phyllodes tumors (including two cases with matched primary and metastatic tumors) were profiled using gene sequencing (Next-generation and Sanger), gene copy number analysis (in-situ hybridization), whole genome RNA expression, and protein expression (immunohistochemical assay).

Results: RNA microarray assay showed consistent over-expression of genes involved in angiogenesis including VEGFA, Angiopoietin2, VCAM1, PDGFRA, PTTG1, and CYP3A5 in all cases analyzed (n=5). No mutations in KDR (VEGFR2) were detected (0/26). EGFR protein overexpression was observed in 25/26 (96%) of cases with amplification of the EGFR gene in 8 cases (33%). EGFR gene mutations were identified in 2 cases (8%) including one case with presumed pathogenic V774M mutation and one case with EGFRvIII mutation. The most common mutations included those of TP53 (50%) and PIK3CA (15%) while other mutations (BRCA1, BRCA2, RET, CDH1, MLH1, ATM) were rare affecting single phyllodes cases. Two cases with matched primary and metastatic cancers harbored the same mutations in both sites (PIK3CA/KRAS and RB1 gene mutations, respectively).

Conclusions: Comprehensive multiplatform profiling approach to phyllodes tumors identifies various molecular alterations of which some are potentially actionable. Our data suggests that anti-angiogenic therapy may also be effective in patients with malignant phyllodes tumor. Evaluation of EGFR pathway discovered consistent protein over-expression but rare activating mutations, which necessitates refinement in patient selection targeting these pathways.

Citation Format: Gatalica Z, Vranic S, Ghazalpour A, Xiu J, Ocal I, McGill J, Bender R, Discianno E, Sanati S, Reddy S, Pockaj B. Comprehensive multiplatform molecular profiling identifies potentially targetable biomarkers in malignant phyllodes tumors of the breast. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-09-19.

Comprehensive tumor profiling identifies numerous biomarkers of drug response in cancers of unknown primary site: analysis of 1806 cases

Background

Cancer of unknown primary (CUP) accounts for approximately 3% of all malignancies. Despite extensive laboratory and imaging efforts, the primary site usually cannot be unequivocally confirmed, and the treatment for the most part remains empirical. Recently, identification of common cancer pathway alterations in diverse cancer lineages has offered an opportunity to provide targeted therapies for patients with CUP, irrespective of the primary site.

Patients and Methods

1806 cancers of unknown primary were identified among more than 63,000 cases profiled at Caris Life Sciences. Multiplatform profiling of the tumor samples included immunohistochemistry, gene sequencing and in situ hybridization methods in an effort to identify changes in biomarkers that are predictive of drug responses.

Results

Biomarkers associated with a potential drug benefit were identified in 96% of cases. Biomarkers identified included those associated with potential benefit in nearly all classes of approved cancer drugs (cytotoxic, hormonal, targeted biological drugs). Additionally, biomarkers associated with a potential lack of benefit were identified in numerous cases, which could further refine the management of patients with CUP.

Conclusion

Comprehensive biomarker profiling of CUP may provide additional choices in treatment of patients with these difficult to treat malignancies.

Abstract LB-171: Concordance between protein expression and mRNA expression in the large cohort of cancer patients

Introduction: Immunohistochemical (IHC) analysis of protein expression in clinical specimens has been invaluable in diagnosing, monitoring and guiding treatment in cancer patients. This approach, however, has its limitations including the difficulty to obtain robust and reliable antibodies, the semi quantitative nature of the assay, subjectivity of intensity call, and the lack of specificity to detect clinically relevant isoform expression in tumor specimen. In light of these limitations, RNA expression may be a useful replacement or a complementary approach to IHC in clinical settings. In this study, we compared the concordance between IHC and mRNA expression levels as measured by microarray using a large cohort of cancer patients spanning multiple lineages.

Methods: 10246 patient samples that included 40 tumor types were utilized in this study. Transcript and protein expression levels were measured for ESR1, AR, KIT, ERBB2 (Her2), RRM1, and ERCC1. Transcript levels were measured by Illumina's HumanHT-12 microarray (v4), and IHC was performed using the following antibodies: SP1 (ESR1), AR27 (AR), 4B5 (Her2), 8F1 (ERCC1), anti-CD117 polyclonal (KIT), and 10526-1-AP (RRM1).

Results: We observed a significant correlation between ERBB2, ESR1, and KIT with IHC data. Of the 3 probes on the microarray measuring ERBB2, only one probe mapping to the 3’ end of the two ERBB2 isoforms showed significant association with IHC data. For KIT, IHC and mRNA expression correlated well across, thymic carcinomas, poorly differentiated neuroendocrine tumors, melanoma, GIST, and head and neck cancer. For ESR1, significant correlations were observed for uterine sarcoma, endometrial carcinoma, and breast adenocarcinoma. Cervical cancers and ovarian surface epithelial carcinomas showed diminished association, and there was a lack of association in NSCLC and neuroendocrine carcinoid tumors. For AR, we observed strong correlation only in prostate tumors. ERCC1 and RRM1 mRNA expressions did not correlate well with protein expression in any of the tumor lineages examined.

Conclusion: These observations suggest that measuring mRNA via microarray has the potential to serve as a surrogate for IHC in clinical setting. The mixed associations observed for some of the genes exhibited lineage specificity suggesting that the relation between microarray results and IHC may be driven by the tissue-specific expression of isoforms, differential expression of genes in the stromal cells, and the technical limitations of each platform including the specificity of either the probes used to measure mRNA or antibodies used to measure protein expression. As such, combining the two platforms in the clinical setting may provide a more complete assessment of gene expression in tumor samples.

Citation Format: Anatole Ghazalpour, Wangjuh Sting Chen, Wenhsiang Wen, Zoran Gatalica, Ryan Bender. Concordance between protein expression and mRNA expression in the large cohort of cancer patients. [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 LB-171. doi:10.1158/1538-7445.AM2014-LB-171

Molecular profiling of infiltrating urothelial carcinoma of bladder and nonbladder origin

BACKGROUND

Infiltrating UC represents the second most common genitourinary malignancy. Advanced UC has a poor prognosis and new treatments are needed. Molecular profiling of UC might identify biomarkers associated with targeted therapies or chemotherapeutics, providing physicians with new treatment options.

MATERIALS AND METHODS

Five hundred thirty-seven cases of locally advanced or metastatic UC of the bladder, 74 nonbladder, and 55 nonurothelial bladder cancers were profiled using mutation analysis, in situ hybridization, and immunohistochemistry assays for biomarkers predictive of therapy response.

RESULTS

Molecular profiling of UC showed high overexpression of topoisomerase 2α, common phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha and/or phosophatase and tensin homolog (PTEN) alterations in nonbladder (27%) and bladder UC (21%), and rare gene mutations across subtypes. Compared with nonbladder, bladder UC consistently exhibited more frequent abnormal protein expression, including HER2 (10% vs. 3%; P = .04), tyrosine protein c-Kit receptor kinases (11% vs. 5%), c-Met proto-oncogene, receptor tyrosine kinases (25% vs. 8%), androgen receptor (16% vs. 6%), O(6)-methylguanine-methyltransferase (63% vs. 43%), ribonucleotide reductase M1 (32% vs. 11%), Serum protein acidic and rich in cysteine (SPARC) (69% vs. 33%), and topoisomerase 1 (63% vs. 39%). Bladder UC also exhibited increased amplification of HER2 (12% vs. 2%; P = .06).

CONCLUSION

Comprehensive molecular profiling of UC identified a large number of biomarkers aberrations that might direct treatment in conventional chemotherapies and targeted therapies, not currently recommended in this population. As a group, bladder UC exhibited higher levels of actionable biomarkers, suggesting that UC from different primary sites and non-UC are driven by different molecular pathways. These differences could have clinical implications resulting in different treatment regimens depending on the site of origin of UC.

Molecular profiling of infiltrating urothelial carcinoma of the bladder

311

Background: Infiltrating urothelial carcinoma (UC) is the most common variant of urinary bladder cancer. The prognosis for muscle infiltrating or metastatic UC of the bladder is poor with no major advances made in the last 20 years. We investigated a large cohort of such patients for specific genetic/biomarker alterations and compared them to other, less common urothelial malignancies. Methods: We reviewed 602 cases; 518 cases (86%) were locally advanced or metastatic UCs of the bladder and the remaining 84 cases (14%) were non-bladder UCs. Multiple methodologies for optimal assessment of biomarker expression (Caris Molecular Intelligence, Caris Life Sciences, Phoenix, AZ) were employed: Mutation analysis (Next-generation sequencing, Sanger, pyrosequencing, qPCR, RFLP), in-situ hybridization (fluorescent and chromogenic), immunohistochemistry, and RNA fragment analysis. Results: Bladder UC showed slightly higher rates of HER2/neu gene amplification (12% in bladder vs. 6% non-bladder, p=0.32) and EGFR gene amplification (22% vs. 12%, p=0.25). HER2/neu and EGFR protein expressions were more common in the bladder than in non-bladder sites (10% vs. 1%, p=0.03, and 77% vs. 60%, p=0.5, respectively). Pathogenic mutations in HER2/neu and EGFR were rare. Although c-Kit and c-Met receptor kinases were more frequently overexpressed in bladder than in non-bladder cancers (10% vs. 6% and 25% vs. 8%, respectively), activating mutations were also rare. PIK3CA and/or PTEN mutations were more frequently observed in non-bladder (27%) than in bladder UCs (21%). Non-bladder UC harbored high FGFR3 gene mutation (33%), which was not observed in any of the UC of the bladder (p=0.02). TP53 gene mutations were frequently identified in both bladder and in non-bladder cancers (49% vs. 27%, respectively, p=0.15), while KRAS was frequently mutated in the bladder adenocarcinomas (56%, p<0.001). Other therapeutically targetable biomarkers over-expressed in bladder UC compared to non-bladder UC included androgen receptor (16% vs. 8%, p=0.07) and MGMT (63% vs. 47%). Conclusions: Comprehensive molecular profiling of urothelial carcinoma identifies a number of potentially actionable targets, which can be managed by the novel treatment modalities.

Molecular profiling of advanced refractory prostate cancer

107

Background: Prostate cancer is the second leading cause of cancer-related death among men in the U.S. Forty percent of men diagnosed will develop metastatic disease, which has few treatment options. We aim to describe the molecular profile of prostate cancer tumors and potential for novel therapeutic options. Methods: We reviewed profiling data of over 330 patients from a large referral laboratory (Caris Life Sciences, Phoenix, AZ) for biomarkers of drug response. Multiple methodologies were employed: sequencing (NGS, Sanger, pyrosequencing), in-situ hybridization (fluorescent and chromogenic), and immunohistochemistry. Results: High expression was observed for AR, MRP1, TOPO1, TLE3 and EGFR, with positivity rates of 89%, 87%, 63%, 48%, and 47%, respectively. Low expression was observed for TS, PGP, TUBB3, RRM1, PTEN and MGMT, with negativity rates of 94%, 87%, 75%, 69%, 54%, and 45%, respectively. Gene copy number increases for EGFR and cMYC were observed in 13% of patients. Sequencing data showed a 48% mutation rate for TP53, 18% for PTEN, 9% for CTNNB1, 8% for PIK3CA, 5% for RB1, ATM, and cMET, and approximately 2% for K/HRAS, ERBB4, ALK, BRAF, and cKIT. Targeted therapy options include imatinib for patients with high cKIT or PDGFRA (9 to 10%) and cetuximab for patients with EGFR positivity (13 to 47%). Promising agents may be considered, including cabozantinib, based on 4% of cohort with cMET aberrations or PAM pathway inhibitors (BEZ234, everolimus) based on approximately 30% of cohort with PIK3CA pathway activation. Lastly, HDAC inhibitors have recently been linked to cMYC driven cancers (13% amplified). 5-FU, gemcitabine, and temozolomide chemotherapies may be options, as approximately 70% of cohort with low TS, RRM1, or MGMT. Biomarker guidance for common prostate cancer drugs such as cabazitaxel is also provided, based on approximately 70% of cohort with low TUBB3 or PGP, or high TLE3. Also, continued dependence on androgen signaling is exhibited by 89% of cohort with high AR, indicating potential utility of anti-androgen agents like enzalutamide. Conclusions: Tumor profiling identified small subsets of patients that may benefit from targeted agents approved for other solid tumors (imatinib, cetuximab), promising therapies in clinical trials (cabozantinib) or agents not routinely used for prostate cancer (gemcitabine).

Neurophysiological correlates of motor and working memory performance following subthalamic nucleus stimulation

Subthalamic nucleus (STN) deep brain stimulation (DBS) has become an accepted treatment for the motor manifestations of Parkinson disease (PD). The beneficial motor effects of STN DBS are likely due to modulation of BG output to frontal cortical regions associated with motor control, but the underlying neurophysiology of STN DBS effects, especially at the level of the cortex, is not well understood. In this study, we examined the effects of STN DBS on motor disability and visual working memory, a cognitive process supported by pFC. We tested 10 PD participants off medications, ON and OFF stimulation, along with 20 normal controls on a visual working memory task while simultaneously recording cortical EEG. In the OFF state, PD patients had poor motor function, were slower and less accurate in performing the working memory task, and had greater amplitudes and shorter latencies of the N200 ERP response. DBS improved clinical motor function, reduced N200 amplitudes, and increased N200 latencies but had little effect on working memory performance. We conclude that STN DBS normalizes neurophysiological activity in fronto striatal circuits and this may independently affect motor and cognitive function.

Frequency distribution of SPARC in triple-negative breast cancer patients

37

Background: SPARC (secreted protein acid rich in cysteine) belongs to a group of extracellular matrix proteins and promotes adhesion of cells from the matrix. It plays an important role in tumor development in breast cancer and has a significant bearing on patient prognosis and long term survival. It is also known to predict response to nab-paclitaxel in certain tumor types including breast cancer. In 2005, FDA approved a solvent free formulation of paclitaxel for the treatment of metastatic breast cancer that utilizes albumin bound (nab) technology (nab-paclitaxel). Clinical studies have shown that nab-paclitaxel is significantly more effective than paclitaxel. Our study evaluated the frequency distribution of SPARC among triple negative breast cancer patients in which identification of a novel therapeutic target is warranted.

Methods: In a total of 951 breast cancer patients, we analyzed tumor SPARC expression by immunohistochemistry (IHC) using a monoclonal (R&D Systems) and a polyclonal antibody (Exalpha Biologicals). Immunoreactivity was assessed by scoring the percentage of cells stained in each field and by the intensity of staining. A cutoff point of 2+ and >30% stained tumor cells were considered as positive.

Results: From our analysis of 951 breast cancer patients profiled, a total of 165 patients (17%) were triple negative for ER, PR and HER2. Within this pathologic subtype, 29% patients stained positive with SPARC monoclonal antibody and 21% stained positive with SPARC polyclonal antibody. The correlation of SPARC tumor staining with hormone receptor status will be presented in detail.

Conclusions: We conclude that SPARC over-expression is a functionally important feature of a subset of triple negative breast cancer patients. The triple negative subset of tumors generally has a more aggressive clinical course and does not benefit from conventional targeted therapies. Our study suggests that nab-paclitaxel may serve as a therapeutic agent for the subset of triple negative patients that over-express SPARC. To the best of our knowledge, this is the first study involving a large patient pool in which SPARC has been investigated in a single clinical laboratory using standardized IHC with two different SPARC antibodies.

Supermassive black holes do not correlate with galaxy disks or pseudobulges

The masses of supermassive black holes are known to correlate with the properties of the bulge components of their host galaxies. In contrast, they seem not to correlate with galaxy disks. Disk-grown 'pseudobulges' are intermediate in properties between bulges and disks; it has been unclear whether they do or do not correlate with black holes in the same way that bulges do. At stake in this issue are conclusions about which parts of galaxies coevolve with black holes, possibly by being regulated by energy feedback from black holes. Here we report pseudobulge classifications for galaxies with dynamically detected black holes and combine them with recent measurements of velocity dispersions in the biggest bulgeless galaxies. These data confirm that black holes do not correlate with disks and show that they correlate little or not at all with pseudobulges. We suggest that there are two different modes of black-hole feeding. Black holes in bulges grow rapidly to high masses when mergers drive gas infall that feeds quasar-like events. In contrast, small black holes in bulgeless galaxies and in galaxies with pseudobulges grow as low-level Seyfert galaxies. Growth of the former is driven by global processes, so the biggest black holes coevolve with bulges, but growth of the latter is driven locally and stochastically, and they do not coevolve with disks and pseudobulges.

Estimating adjusted risk difference (RD) and number needed to treat (NNT) measures in the Cox regression model

In medical research, risk difference (RD) and number needed to treat (NNT) measures for survival times have been mainly proposed without consideration of covariates. In this paper, we develop adjusted RD and NNT measures for use in observational studies with survival time outcomes within the framework of the Cox proportional hazards regression model taking the distribution of confounders into account. We consider the typical situation of a cohort study in which the effect of an exposure on a survival time outcome is investigated and important covariates have to be taken into account. The exposure effect described by means of the RD and NNT measures in dependence on whether the effect of allocating an exposure to unexposed persons (number needed to be exposed) or that of removing an exposure from exposed persons (exposure impact number) is considered. Estimation of these adjusted RD and NNT measures is performed by using the average RD approach recently developed for logistic regression. To determine standard errors and confidence intervals for these estimators we use two approaches, the delta method with respect to the regression coefficients of the Cox model and bootstrapping and compare each other. The performance of these estimators is assessed by performing Monte Carlo simulations demonstrating clear advantages of the bootstrap method. The proposed method for point and interval estimation of adjusted RD and NNT measures in the Cox model is illustrated by means of data of the Düsseldorf Obesity Mortality Study (DOMS).