Wang, Chen

The accurate detection of point mutations from pathology slides using sequencing data is of great importance in cancer genomics and precision oncology. Formalin-fixation paraffin-embedding (FFPE) is a widely used technique to preserve pathology tissues. The FFPE process introduces artificial C > T mutations in next-generation sequencing, so we set out to develop excerno , a method to score and filter such spurious variants. FFPE mutational artifacts follow a mutational signature. By using the FFPE signature and Bayes' formula, we can calculate the probability of a mutation resulting from the FFPE process and use this probability to filter FFPE variants. We implement this method as the excerno R package. We tested excerno by simulating mutations across all 60-baseline mutational signatures from the Catalog of Somatic Mutations in Cancer (COSMIC) and combining them with mutations following the FFPE mutational signature. The sensitivity and specificity of excerno are adversely affected by the cosine similarity between the baseline and FFPE signatures ( c o s F F P E ). Higher percentages of FFPE mutations ( p c t F F P E ) result in increased sensitivity and reduced specificity. The specificity and sensitivity of excerno can be predicted as linear model with an interaction term using c o s F F P E and p c t F F P E , with an R 2 o f 0 . 8 4 and 0.79, respectively. Finally, we tested excerno using six RNA sequencing cancer samples and observed concordant trends of specificity and sensitivity with respect to our simulated data. The excerno R package can be used to annotate and filter FFPE-induced mutations in cancer genomics. Our method is adversely affected by c o s F F P E and p c t F F P E .

Abstract Motivation Despite the increasing evidence of utility of genomic medicine in clinical practice, systematically integrating genomic medicine information and knowledge into clinical systems with a high-level of consistency, scalability and computability remains challenging. A comprehensive terminology is required for relevant concepts and the associated knowledge model for representing relationships. In this study, we leveraged PharmGKB, a comprehensive pharmacogenomics (PGx) knowledgebase, to formulate a terminology for drug response phenotypes that can represent relationships between genetic variants and treatments. We evaluated coverage of the terminology through manual review of a randomly selected subset of 200 sentences extracted from genetic reports that contained concepts for ‘Genes and Gene Products’ and ‘Treatments’. Results Results showed that our proposed drug response phenotype terminology could cover 96% of the drug response phenotypes in genetic reports. Among 18 653 sentences that contained both ‘Genes and Gene Products’ and ‘Treatments’, 3011 sentences were able to be mapped to a drug response phenotype in our proposed terminology, among which the most discussed drug response phenotypes were response (994), sensitivity (829) and survival (332). In addition, we were able to re-analyze genetic report context incorporating the proposed terminology and enrich our previously proposed PGx knowledge model to reveal relationships between genetic variants and treatments. In conclusion, we proposed a drug response phenotype terminology that enhanced structured knowledge representation of genomic medicine. Supplementary information Supplementary data are available at Bioinformatics online.

Disrupted liver regeneration following hepatectomy represents an “undruggable” clinical challenge associated with poor patient outcomes. Yes-associated protein (YAP), a transcriptional coactivator that is repressed by the Hippo pathway, is instrumental in liver regeneration. We have previously described an alternative, Hippo-independent mechanism of YAP activation mediated by downregulation of protein tyrosine phosphatase nonreceptor type 11 (PTPN11, also known as SHP2) inhibition. Herein, we examined the effects of YAP activation with a selective SHP1/SHP2 inhibitor, NSC-87877, on liver regeneration in murine partial hepatectomy models. In our studies, NSC-87877 led to accelerated hepatocyte proliferation, improved liver regeneration, and decreased markers of injury following partial hepatectomy. The effects of NSC-87877 were lost in mice with hepatocyte-specific Yap/Taz deletion, and this demonstrated dependence on these molecules for the enhanced regenerative response. Furthermore, administration of NSC-87877 to murine models of nonalcoholic steatohepatitis was associated with improved survival and decreased markers of injury after hepatectomy. Evaluation of transcriptomic changes in the context of NSC-87877 administration revealed reduction in fibrotic signaling and augmentation of cell cycle signaling. Cytoprotective changes included downregulation of Nr4a1 , an apoptosis inducer. Collectively, the data suggest that SHP2 inhibition induces a pro-proliferative and cytoprotective enhancement of liver regeneration dependent on YAP.

Abstract Background: Biopsy diagnoses of benign breast disease (BBD) confer a 1.5- to 4-fold increased risk of developing breast cancer (BC) compared with women without BBD. Previously, we reported that decreased numbers of specific immune cell types in lobules of BBD biopsies predicted increased BC risk, suggesting the promise of future tissue biomarker studies to define BC risk markers among BBD patients. Thus, we applied protein-based GeoMx® Digital Spatial Profiling (DSP) to BBD biopsies preceding BC (cases) and to BBD biopsies from cancer-free patients (controls) to identify possible BC risk markers, which we then evaluated in subsequent BC tissues and in surrounding normal lobules of cases. Methods: Archived pathology slides of BBD biopsies were reviewed and used to guide preparation of TMAs containing 1.0-mm diameter FFPE cores of lobules from an age- and cohort-period-matched set of 91 cases and 88 controls from the Mayo Clinic BBD Cohort. For patients who later developed BC, we prepared TMAs of BC tissue and surrounding mapped normal lobules. We applied GeoMx® DSP (immune and canonical signaling proteins) to both sets of TMAs. Following QC and data normalization, associations of case status with log-transformed biomarker expression in lobules of BBD biopsies were carried out using linear mixed modeling approaches, accounting for multiple ROIs per individual. Biomarkers significantly associated with case status (p<0.05) were further examined in BCs and adjacent normal lobules, using similar approaches. Results: The mean age at BBD biopsy was 52 years, and at BC diagnosis of cases, 61.4 years (mean time from BBD to BC was 10.2 years). A family history of BC was more frequent among cases (70% versus 43%; chi-square p=0.002). Of 72 biomarkers tested, 46 (64.4%) were evaluable after QC and normalization and 5 were associated with BC risk after adjustment for family history of BC: BCL2 (p=0.005), STING (p=0.006), CD44 (p=0.02), S100 protein (p=0.03) and pan-AKT (p=0.05); each showed higher levels in lobules of BBD biopsies of controls than cases. Three unique patterns appeared when examining these biomarkers across tissue type within cases: for BCL2 (p=5 x 10-9) and STING (p=2 x 10-19), levels were high in both BC and lobules surrounding BC but low in preceding BBD; for GAPDH (p=4 x 10-53) and pan-AKT (p=2 x 10-33), levels were high in BC, low in preceding BBD, and moderate in lobules surrounding BC; and for CD44 (p=2 x 10-6) and S100B (p=2 x 10-49), levels were low in BC, high in lobules surrounding BC and moderate in preceding BBD. Conclusions: Using a novel TMA of lobules in combination with DSP, we preliminarily identified immune-based and PI3 kinase-related protein biomarkers in BBD biopsies associated with BC risk. In case-only analyses, these markers demonstrated complex differences between lobules in BBD biopsies, subsequent BCs and adjacent normal lobules. Citation Format: Robert Alan Vierkant, Jodi M. Carter, Stacey J. Winham, Chen Wang, Jennifer M. Kachergus, Ji Shi, Raymond M. Moore, Bryan M. McCauley, Laura M. Pacheco-Spann, E A. Thompson, Derek C. Radisky, Amy C. Degnim, Mark E. Sherman. Towards prediction of breast cancer risk in benign biopsies with high-plex GeoMx spatial protein profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2203.

Precision oncology is expected to improve selection of targeted therapies, tailored to individual patients and ultimately improve cancer patients’ outcomes. Several cancer genetics knowledge databases have been successfully developed for such purposes, including CIViC and OncoKB, with active community-based curations and scoring of genetic-treatment evidences. Although many studies were conducted based on each knowledge base respectively, the integrative analysis across both knowledge bases remains largely unexplored. Thus, there exists an urgent need for a heterogeneous precision oncology knowledge resource with computational power to support drug repurposing discovery in a timely manner, especially for life-threatening cancer. In this pilot study, we built a heterogeneous precision oncology knowledge resource (POKR) by integrating CIViC and OncoKB, in order to incorporate unique information contained in each knowledge base and make associations amongst biomedical entities (e.g., gene, drug, disease) computable and measurable via training POKR graph embeddings. All the relevant codes, database dump files, and pre-trained POKR embeddings can be accessed through the following URL: https://github.com/shenfc/POKR.

Abstract BackgroundFormalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data.MethodsWe optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.ResultsSamples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with CPM > 2). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.7 ng/ul and 1.68 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.58 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.803 in predicting QC status (pass/fail) of FFPE samples. ConclusionsWe provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.8 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Prostate‐specific membrane antigen (PSMA) is a validated target for molecular diagnostics and targeted radionuclide therapy. Our purpose was to evaluate PSMA expression in hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), and hepatic adenoma (HCA); investigate the genetic pathways in HCC associated with PSMA expression; and evaluate HCC detection rate with 68Ga‐PSMA‐11 positron emission tomography (PET). In phase 1, PSMA immunohistochemistry (IHC) on HCC (n = 148), CCA (n = 111), and HCA (n = 78) was scored. In a subset (n = 30), messenger RNA (mRNA) data from the Cancer Genome Atlas HCC RNA sequencing were correlated with PSMA expression. In phase 2, 68Ga‐PSMA‐11 PET was prospectively performed in patients with treatment‐naïve HCC on a digital PET scanner using cyclotron‐produced 68Ga. Uptake was graded qualitatively and semi‐quantitatively using standard metrics. On IHC, PSMA expression was significantly higher in HCC compared with CCA and HCA (P < 0.0001); 91% of HCCs (n = 134) expressed PSMA, which principally localized to tumor‐associated neovasculature. Higher tumor grade was associated with PSMA expression (P = 0.012) but there was no association with tumor size (P = 0.14), fibrosis (P = 0.35), cirrhosis (P = 0.74), hepatitis B virus (P = 0.31), or hepatitis C virus (P = 0.15). Overall survival tended to be longer in patients without versus with PSMA expression (median overall survival: 4.2 vs. 1.9 years; P = 0.273). FGF14 (fibroblast growth factor 14) mRNA expression correlated positively (rho = 0.70; P = 1.70 × 10‐5) and MAD1L1 (Mitotic spindle assembly checkpoint protein MAD1) correlated negatively with PSMA expression (rho = −0.753; P = 1.58 × 10‐6). Of the 190 patients who met the eligibility criteria, 31 patients with 39 HCC lesions completed PET; 64% (n = 25) lesions had pronounced 68Ga‐PSMA‐11 standardized uptake value: SUVmax (median [range] 9.2 [4.9‐28.4]), SUVmean 4.7 (2.4‐12.7), and tumor‐to‐liver background ratio 2 (1.1‐11). Conclusion: Ex vivo expression of PSMA in neovasculature of HCC translates to marked tumor avidity on 68Ga‐PSMA‐11 PET, which suggests that PSMA has the potential as a theranostic target in patients with HCC.

Abstract Background: Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC. Methods: We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways. Results: Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P &lt; 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P &lt; 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P &lt; 10−4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P &lt; 10−6). Conclusions: DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways. Impact: This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

Abstract Objective The study sought to test the feasibility of conducting a phenome-wide association study to characterize phenotypic abnormalities associated with individuals at high risk for lung cancer using electronic health records. Materials and Methods We used the beta release of the All of Us Researcher Workbench with clinical and survey data from a population of 225 000 subjects. We identified 3 cohorts of individuals at high risk to develop lung cancer based on (1) the 2013 U.S. Preventive Services Task Force criteria, (2) the long-term quitters of cigarette smoking criteria, and (3) the younger age of onset criteria. We applied the logistic regression analysis to identify the significant associations between individuals’ phenotypes and their risk categories. We validated our findings against a lung cancer cohort from the same population and conducted an expert review to understand whether these associations are known or potentially novel. Results We found a total of 214 statistically significant associations (P &lt; .05 with a Bonferroni correction and odds ratio &gt; 1.5) enriched in the high-risk individuals from 3 cohorts, and 15 enriched in the low-risk individuals. Forty significant associations enriched in the high-risk individuals and 13 enriched in the low-risk individuals were validated in the cancer cohort. Expert review identified 15 potentially new associations enriched in the high-risk individuals. Conclusions It is feasible to conduct a phenome-wide association study to characterize phenotypic abnormalities associated in high-risk individuals developing lung cancer using electronic health records. The All of Us Research Workbench is a promising resource for the research studies to evaluate and optimize lung cancer screening criteria.

Abstract Benign breast disease (BBD) is an established risk factor for development of breast cancer (BC). However, little is known about the prevalence of somatic genetic alterations at the time of BBD diagnosis and relationship to subsequent BC. To characterize DNA variants in BBD and investigate association with BC risk, we isolated DNA from formalin-fixed paraffin-embedded (FFPE) BBD biopsies and assessed mutations using a panel of 93 breast cancer predisposition genes (Qiagen GeneRead). The study set consisted of 120 BBD patients from three age-matched groups defined based on 16 years of BC follow-up: BBD-controls (cancer-free after 16 years), BBD-ER+, or BBD-ER- breast cancer (within 16 years). Bioinformatics quality checks included comparisons of paired fresh-frozen and FFPE replicates to reduce false variant calls induced by FFPE artifacts. Gene-level variant burden differences among study groups were assessed using 12 statistical approaches, adjusted for patient age, year of biopsy, and histology. To investigate possible immune implications of increased variant burden, extent of leukocytes in the BBD biopsies was assessed using CD45 immunohistochemistry. To assess variant profile changes during the progression from BBD to BC, we also performed targeted sequencing of 12 BBD-matched subsequent tumor samples (six ER+ and six ER-) developed within 5 years of BBD diagnosis. Gene-level association results showed consistently skewed distributions suggesting a higher variant burden in BBD controls: among the top 10 genes associated with case-status (p&lt;0.05), all had BC-risk odds ratio estimates less than 1.0. Immune infiltrates, assessed by CD45 H-scores, were positively associated with overall variant burden (r=0.42, p=0.0031), and noticeably higher in cancer-free controls (r=0.50, p=0.005). Comparison of mutation variants in 12 BBD cases that developed cancer within 5 years of diagnosis and their subsequent tumors revealed that more than half of the non-SNP variants were shared between the BBD and the subsequent tumor (54.6%), whereas less than one quarter were unique to the tumor (20.6%) or unique to the BBD (24.9%). Through BBD-BC paired variant analysis, three subjects were found with newly emergent clones uniquely appearing in the tumors and four subjects had loss of clones in the tumor that were present in the BBD. These results show that somatic variant burden is lower in patients with BBD that progress to BC, mutation profiles of BC progression are heterogeneous, and BBD tissues with reduced variant burden also show reduced immune infiltrate. This implicates a potential protective role for immune activation in BBD. Future directions will define the characteristics of the potentially protective immune response and its role in variant heterogeneity in a larger sample set, integrated with paired RNA sequencing to better understand the pathways involved and the relationship to immune infiltration. Citation Format: Stacey J. Winham, Julie M. Cunningham, Yuanhang Liu, Aditya V. Bhagwate, Ethan P. Heinzen, Samantha J. McDonough, Melody L. Stallings-Mann, Robert A. Vierkant, Jodi M. Carter, Mark E. Sherman, Derek C. Radisky, Amy C. Degnim, Chen Wang. Somatic variant burdenin benign breast disease and association with risk of subsequent breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2274.