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CDK4/6 inhibitors such as palbociclib in combination with endocrine therapy (ET) have remarkablyimproved the outcome of patients with ER+/HER2- metastatic breast cancer (MBC). However, manypatients are intrinsically resistant to CDK4/6i therapy, and those who respond eventually acquireresistance. Although high baseline CCNE1 expression and rare alterations in RB1 and FAT1 geneshave been shown to be associated with CDK4/6i resistance, the molecular mechanisms of CDK4/6iresistance are complex and remain poorly understood. To better understand and overcome CDK4/6iresistance, we performed multi-omics profiling of paired tumor biopsies from ER+/HER2- MBCpatients treated with palbociclib combined with ET. Tumor biopsies taken at pre-treatment, on-treatment, and progressive disease (PD) from 71 patients were profiled using whole-exomesequencing (WES), whole-transcriptome sequencing (RNA-Seq) and IHC analysis. Ourcomprehensive analysis identified several tumor intrinsic molecular markers associated with worsePFS, including the Luminal B subtype (p=0.012, HR=2.593), BRCA1/2 pathogenic mutation (p=0.012,HR=2.67) and mutation signatures linked to APOBEC enzymatic activity (p=0.002, HR=3.19).Conversely, the estrogen response signature (p=0.006, HR=0.43) was associated with favorableprognosis. Unsupervised analysis revealed a cluster of tumors enriched in homologousrecombination deficiency (HRD) linked genomic scars that was associated with poor prognosis(p=0.005, HR=2.49). Of note, these HRD-high tumors responded even more poorly to treatment whenco-occurring with TP53 somatic mutations. Integrative analysis further identified three poorprognosis clusters (IC2-4) enriched in Luminal B, proliferative and HRD features when compared tothe favorable prognosis cluster (IC1).Comparing baseline vs. PD samples, we observed a pattern of post-treatment enrichment for the poorprognosis markers. In addition, breast cancer-associated genes such as BRCA1/2, TP53 and PTENharbored a higher prevalence of genomic alterations including somatic mutation, amplification,. deletion and gene fusion at PD. Cell cycle gene expression and signatures also markedly increased atPD compared to baseline whereas estrogen response signatures decreased. Upon diseaseprogression, tumors had frequently switched to molecular subtypes with aggressive and estrogenindependent characteristics, demonstrating high plasticity in response to CDK4/6i and ET treatment.These patterns of acquired resistance were validated by IHC analysis of cyclins E1 and E2, Ki67 andpRb. To investigate the genomic alterations responsible for acquired resistance, we compared 21paired baseline and PD samples. We observed that PD-specific RB1 loss-of-function events occurredwith higher prevalence than previously reported, underscoring a major role of cell cycle de-regulation in conferring resistance to CDK4/6 inhibition. In this prospective longitudinal multi-omicsstudy, we identified novel candidate biomarkers that can be used to improve prediction of responseto CDK4/6i. In addition, we derived new insights into the molecular mechanisms of drug resistanceto palbociclib plus ET that will help guide therapeutic strategies and drug development inHR+/HER2− MBC. Citation Format: Zhengyan Kan, Seock-Ah Im, Kyunghee Park, Ji Wen, Kyung-Hun Lee, Yoon-La Choi, Won-Chul Lee, Ahrum Min, Vinicius Bonato, Seri Park, Sripad Ram, Dae-Won Lee, Ji-Yeon Kim, Su Kyeong Lee, Won-Woo Lee, Jisook Lee, Miso Kim, Scott L. Weinrich, Han Suk Ryu, Tae Yong Kim, Stephen Dann, Diane Fernandez, Jiwon Koh, Song Yi Park, Shibing Deng, Eric Powell, Rupesh Kanchi Ravi, Jadwiga Bienkowska, Paul A. Rejto, Woong-Yang Park, Yeon Hee Park. Serial genomic profiling reveals molecular mechanisms of breast cancer resistance to palbociclib [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD2-08.

Extra domain B splice variant of fibronectin (EDB+FN) is an extracellular matrix protein (ECM) deposited by tumor-associated fibroblasts, and is associated with tumor growth, angiogenesis, and invasion. We hypothesized that EDB+FN is a safe and abundant target for therapeutic intervention with an antibody-drug conjugate (ADC). We describe the generation, pharmacology, mechanism of action, and safety profile of an ADC specific for EDB+FN (EDB-ADC). EDB+FN is broadly expressed in the stroma of pancreatic, non-small cell lung (NSCLC), breast, ovarian, head and neck cancers, whereas restricted in normal tissues. In patient -derived xenograft (PDX), cell-line xenograft (CLX), and mouse syngeneic tumor models, EDB-ADC, conjugated to auristatin Aur0101 through site-specific technology, demonstrated potent antitumor growth inhibition. Increased phospho-histone H3, a pharmacodynamic biomarker of response, was observed intumor cells distal to the target site of tumor ECM after EDB-ADC treatment. EDB-ADC potentiated infiltration of immune cells, including CD3+ T lymphocytes into the tumor, providing rationale for the combination of EDB-ADC with immune check-point therapy. EDB-ADC and anti-PD-L1 combination in a syngeneic breast tumor model led to enhanced antitumor activity with sustained tumor regressions. In nonclinical safety studies in nonhuman primates, EDB-ADC had a well-tolerated safety profile without signs of either on-target toxicity or the off -target effects typically observed with ADCs that are conjugated through conventional conjugation methods. These data highlight the potential for EDB-ADC to specifically target the tumor microenvironment, provide robust therapeutic benefits against multiple tumor types, and enhance activity antitumor in com-bination with checkpoint blockade., Molecular Cancer Therapeutics, 21 (9), ISSN:1535-7163, ISSN:1538-8514

Understanding how standard-of-care drug treatments affect tumor intrinsic biology and microenvironment is critical for elucidating drug resistance mechanisms and developing better combination therapies as well as new therapies. To characterize the effects of neoadjuvant chemotherapy (NAC) on the genome, transcriptome and tumor infiltrating leukocytes (TILs), we have conducted whole exome and whole transcriptome sequencing of a large longitudinal breast cancer cohort consisting of 146 cases and 281 paired tumor samples. In total, 52 (38%) patients achieved pathologic complete response (pCR) while 85 patients (62%) had residual disease with standard chemotherapy regimen. Tumor biopsies were collected for each patient at three time points – pre-treatment, three weeks after the first cycle of anthracycline and cyclophosphamide (AC) and at the time of surgery after 3 more cycles of AC followed by 4 cycles of taxane or taxane plus Herceptin in case of HER2+ subtype. We detected 5,955 protein-altering somatic mutations affecting 4,414 genes in pretreatment samples and 502 acquired mutations in surgery samples affecting 477 genes including 19recurrently mutated genes such as TP53 and NOTCH1. Across all subtypes, 4,346 genes were differentially expressed (DE) following NAC treatment and significantly enriched in pathways such as cell cycle, ER signaling, PI3K/mTOR, immune and metabolism. Expression-based virtual microdissection analysis indicated that NAC treatment induced an increase in the fractions of stromal and adjacent normal tissue compartment, consistent with observed reduction in tumor cellularity. To assess the NAC induced changes in the molecular landscape of these tumors, we compared molecular features including gene expression signatures, mutation prevalence and copy number alteration between three time points while adjusting for confounding effects of molecular subtype and tumor cellularity. We found that NAC induced dynamic changes in gene expression signatures associated with proliferation and immunomodulatory treatment response. We further validated the observed pattern of change in TILs through histopathology and digital imaging analyses. In pretreatment tumors, 116 genes were DE between patients with pCR vs. those with residual disease with significant enrichment in immune/inflammatory pathways. Further, pre-treatment TIL levels were found to be significantly associated with pCR, echoing previous reports in breast cancers that implicated anti-tumor immunity in mediating the efficacy of chemotherapies. Our analyses also revealed associations between NAC response and baseline genomic attributes such as genomic alterations that affect DNA damage repair pathways. Taken together, these results suggest that NAC induced a multitude of changes on the genomic landscape and immune microenvironment of breast cancers, some of which point to combination strategies with immunomodulatory therapies and therapies that target DNA damage repair. Citation Format: Kan Z, Lal S, Ding Y, Lee JE, Lee S-H, Lee SK, Yu JH, Choi Y-l, Kim SW, Nam SJ, Kim J-Y, Ram S, Powell E, Ching K, Cho SY, Bonato V, Deng S, Park W-Y, Rejto P, Bienkowska J, Park Y-H. Neoadjuvant chemotherapy alters the genomic landscape and immune microenvironment of breast cancers [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD5-08.

To elucidate the effects of neoadjuvant chemotherapy (NAC), we conduct whole transcriptome profiling coupled with histopathology analyses of a longitudinal breast cancer cohort of 146 patients including 110 pairs of serial tumor biopsies collected before treatment, after the first cycle of treatment and at the time of surgery. Here, we show that cytotoxic chemotherapies induce dynamic changes in the tumor immune microenvironment that vary by subtype and pathologic response. Just one cycle of treatment induces an immune stimulatory microenvironment harboring more tumor infiltrating lymphocytes (TILs) and up-regulation of inflammatory signatures predictive of response to anti-PD1 therapies while residual tumors are immune suppressed at end-of-treatment compared to the baseline. Increases in TILs and CD8+ T cell proportions in response to NAC are independently associated with pathologic complete response. Further, on-treatment immune response is more predictive of treatment outcome than immune features in paired baseline samples although these are strongly correlated., Neoadjuvant chemotherapy is a therapeutic option for the treatment of breast cancer. Here, the authors characterize changes in the gene expression profiles and immune microenvironment in serial breast cancer biopsies taken before, during and after neoadjuvant chemotherapy.

The advent of immuno-oncology (IO) therapies has made it an imperative to characterize intratumoral immune microenvironment in addition to oncogenic alterations through molecular profiling of the tumor. To elucidate the baseline profiles of tumor infiltrating leukocytes (TILs) in breast cancer (BC) in the context of molecular subtypes and oncogenic alterations, we performed whole-exome sequencing (WES) and RNA-Seq of an Asian BC cohort (SMC) consisting of 178 treatment naïve primary tumors. A subset of 120 tumors was further analyzed by H&E and IHC using a panel of 8 TIL markers (CD45, CD4, CD8, CD163, PD1, PD-L1, IDO1 and FOXP3). Using expression signatures representing distinct immune cell types, we classified an expression compendium of 2,781 tumor samples, including SMC and multiple cancers from TCGA, into three immune subtypes with high, medium and low levels of TILs. Basal and HER2 subtypes show higher levels of TILs than Luminal subtypes, consistent with observed clinical responses to checkpoint blockade in clinical trials. Moreover, Asian BCs were significantly enriched in TIL-high subtype (35.3%) compared to the primarily Caucasian TCGA BC cohort (20.2%) while 50.6% of the highly immunogenic Lung adenocarcinoma was TIL-high. We then applied machine learning methods to detect and quantify TILs from H&E images of 120 SMC and 349 TCGA BC tumors. The expression signature analysis results were concordant with independently derived histology based TIL data. Taken together, our findings suggest that IO therapies may be more effective in HR negative BC subtypes and Asian BCs. Leukocyte exclusion (LE), an immunophenotype where TILs concentrate at the tumor periphery, has been linked to worse prognosis and resistance to IO therapies. Visual assessment of whole tumor IHC images identified LE patterns in 25% of SMC cases. We observed differential distribution of LE by molecular subtype and evidence for selective exclusion of immune cell subsets. Covariate analyses with clinical and molecular data while controlling for subtype as a confounder identified significant associations with tumor proliferation index, percent tumor purity and TP53 mutations. LE is also significantly associated with expression signatures of chemokine signaling, macrophages, angiogenesis and hypoxia, indicating that marked distinctions exist in both tumor intrinsic and microenvironment characteristics between TIL excluded and TIL infiltrated tumors. To validate these findings, we independently identified LE for 200 cases of TCGA BCs based on patterns of TILs extracted from H&E images and saw significant concordance of covariate relationships identified between TCGA and SMC. Our study provided a rare comprehensive resource for studying tumor associated immunity in breast cancers by generating the integrated multi-omics and IO profiles for a large cohort of primary tumors. Comparative analyses revealed that TIL activities are highly variable across different intrinsic subtypes and geographic origins of BC, with potential implications for IO therapeutic application. Correlative analyses of immunophenotypes with molecular data further yielded insights into LE's role in immune escape and identified hallmark signatures for LE indicative of causal molecular mechanisms. Citation Format: Kan Z, Powell E, Ram S, Ching K, Ding Y, Vizcarra P, Nichols T, Hardwick J, Lee S-H, Cho SY, Choi Y-L, Yu J-H, Park YH. Integrative analyses of immunophenotypes and multi-omics profiles in breast cancers [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-07-01.

Summary The CDK4/6 inhibitor, palbociclib (PAL), significantly improves progression-free survival in HR+/HER2− breast cancer when combined with anti-hormonals. We sought to discover PAL resistance mechanisms in preclinical models and through analysis of clinical transcriptome specimens, which coalesced on induction of MYC oncogene and Cyclin E/CDK2 activity. We propose that targeting the G1 kinases CDK2, CDK4, and CDK6 with a small-molecule overcomes resistance to CDK4/6 inhibition. We describe the pharmacodynamics and efficacy of PF-06873600 (PF3600), a pyridopyrimidine with potent inhibition of CDK2/4/6 activity and efficacy in multiple in vivo tumor models. Together with the clinical analysis, MYC activity predicts (PF3600) efficacy across multiple cell lineages. Finally, we find that CDK2/4/6 inhibition does not compromise tumor-specific immune checkpoint blockade responses in syngeneic models. We anticipate that (PF3600), currently in phase 1 clinical trials, offers a therapeutic option to cancer patients in whom CDK4/6 inhibition is insufficient to alter disease progression.

1013 Background: The development of CDK4/6 inhibitors represents a significant advance in the treatment of metastatic breast cancer (MBC). To better understand the impact of treatment and drug resistance at the molecular level, we performed multi-omics profiling of matched pre-treatment, on-treatment, and post-progression tumor biopsies from patients treated with palbociclib combined with endocrine blockades (AIs and fulvestrant). The purpose of the study was to identify biomarkers of palbociclib resistance as well as to assess molecular changes during treatment, and those appearing at disease progression. Methods: Patients with Hormone Receptor positive (HR+)/HER2- MBC treated with palbociclib in combination with endocrine therapies were prospectively enrolled from July 2017 to June 2020. Of the 89 patients enrolled, we obtained tumor biopsies and matched blood samples, taken at pre-treatment, on-treatment (6 weeks or 12 weeks) and progressive disease (PD) from 71 patients (first line: 55, second line or later: 16 pts.) who had agreed to informed consent form. Tumor biopsies were profiled using whole-exome sequencing (WES) and whole-transcriptome sequencing (RNA-Seq). Results: Median follow-up duration was 20 (3-48) months and median age of the patients was 45 (range 30-71) years. The median progression free survival (PFS) of 71 patients was 15 (0.7-39.8) months. The Luminal B subtype is associated with shorter PFS compared to Luminal A (8.6 m vs 19.3 m, p=0.03, HR=1.96). The Luminal B subtype along with multiple cell cycle regulatory genes such as CCNE1 (8.3 m, p=0.015, HR=2.07), CCNE2 (8.5 m, p=8.5e-3, HR=2.2), CDK2 (8.45 m, p=0.05, HR=1.79) are associated with shorter PFS while estrogen response signatures (20.9 m, p=4.6e-3, HR=0.43) and PGR gene expression (20.2 m, p=6.2e-2, HR=0.56) are associated with more favorable prognosis. A Cox-regression multivariate model (p=5.17e-5, C-Index=0.72) was developed and revealed that PFS is independently associated with BRCA1/2 (HR=1.44; CI=[0.49, 4.29]), TP53 mutation statuses (HR=3.58; CI=[1.58, 8.13]), the HRD mutation signature (HR=1.40; CI=[1.09, 1.81]) and the proliferative index (HR=1.53; CI=[1.00, 2.34]), an expression signature of cell proliferation. Tumors classified as Luminal A at baseline frequently switched into Luminal B or Her2-enriched subtypes at PD, along with up-regulation of cell cycle markers and proliferation signatures. Further, tumor mutation burden (TMB) and HRD index, a DNA-based measure of genomic instability, significantly increased from baseline to PD in patients with TP53 and BRCA1/2 wild-type tumors. Conclusions: Our longitudinal multi-omics study identified prognostic biomarkers as well as post-treatment enrichment of HRD related genomic scars and frequent switching into molecular subtypes with aggressive and estrogen independence characteristics. Clinical trial information: NCT03401359 .

557 Background: To precisely predict neoadjuvant chemotherapy (NAC) response and long-term prognosis, we developed prediction model with clinical and genomic characteristics of breast cancer (BC). Methods: We included early and locally advanced BC that would be scheduled to receive standard NAC (four cycles of anthracycline and cyclophosphamide and four cycles of docetaxel or docetaxel plus trastuzumab for HER2+ BC) followed by curative surgery. For each patient, tumor tissue and matched blood were prospectively collected three times: at diagnosis (T1), three weeks after the first cycle of chemotherapy (T2), and curative surgery (T3). Whole exome sequencing (WES) was performed to detect somatic mutation, mutational signature and tumor mutational burden (TMB) while RNASeq with PAM50 prediction was to classify intrinsic subtype. In terms of clinical variables, clinical stage and IHC subtype at diagnosis, residual cancer burden (RCB) class and distant recurrence free survival (DRFS) were used. Logistic regression was used for predicting RCB class with clinical and genomic variables at T1. Univariate and multivariate Cox regression were performed to identify prognostic factors for DRFS. Results: In total, 210 patients were enrolled and treated with NAC as scheduled. We successfully conducted WES in 231 BC tissues (T1:117, T2:101 and T3:13) from 117 patients. In NAC response, 13 patients were in RCB class 3, 39 in class 2, 14 in class 1 and 46 in class 0. Median follow up duration was 44months and distant recurrence was observed in 13 patients. TP53 mutation (68%) was the most commonly detected genetic alteration. ARID1A, CDH1, CSMD3, LRP1B, PIK3CA, RUNX1 and TP53 were significantly mutated genes in driver gene analysis. Median TMB was 87 (range, 14-570) and signature 3 was most frequently observed. Among genetic characteristics, high TMB was significantly associated with better NAC response compared with low TMB (hazard ratio[HR] for RCB class III: 0.11, 95% confident interval[CI]: 0.01, 0.74, p = 0.05). In prediction model, combination of seven variables: intrinsic subtype, TMB, LRRK1, OPLAH, and PIK3CA hotspot mutation, ERBB2 amplification, and clinical stage had 0.83 in area under curve (AUC) and 0.75 in accuracy. High clinical stage, PTEN and PIK3CA hotspot mutation negatively affected to DRFS while high TMB had protective effect (all ps < 0.05). Prediction model made with five variables: intrinsic subtype, TMB, PTEN mutation, PIK3CA hotspot mutation and clinical stage had 0.88 in c-index (95% CI: 0.81, 0.95). Conclusions: TMB, PIK3CA hotspot mutation and clinical stage showed predictive roles on NAC response and distant recurrence of BC in NAC setting. In prediction model, intrinsic subtype, TMB, LRRK1, OPLAH, and PIK3CA hotspot mutation, ERBB2 amplification, and clinical stage affected to RCB class while intrinsic subtype, TMB, PTEN, PIK3CA hotspot mutation and clinical stage did to DRFS. Clinical trial information: NCT02591966.

Breast cancers (BC) in younger, premenopausal patients (YBC) tend to be more aggressive with worse prognosis, higher chance of relapse and poorer response to endocrine therapies compared to breast cancers in older patients. The proportion of YBC (age ≤ 40) among BC in East Asia is estimated to be 16-32%, significantly higher than the 7% reported in Western countries. To characterize the molecular bases of Asian YBC, we have performed whole-exome sequencing (WES) and whole-transcriptome sequencing (WTS) on tumor and matched normal samples from 134 Korean BC patients consisting of 74 YBC cases (age ≤ 40) and 60 OBC cases (age > 40). We then performed comparison analyses and integrative analyses with the TCGA BC cohort consisting of 1,116 tumors from primarily Caucasian patients, also grouped by age into YBC (age ≤ 40), IBC (40 < age ≤ 60) and OBC (age > 60). Somatic mutation prevalence analysis identified 7 significantly mutated genes and the same top three genes – TP53, GATA3 and PIK3CA – were reported by the TCGA BC study. To identify differentially expressed (DE) genes and pathways in YBCs vs. OBCs, we performed logistic regression analyses while controlling for the confounding effects of tumor purity and stage. We were surprised to see a significant overlap in DE pathways between a comparison of adjacent normal tissues in younger vs. older TCGA cohorts and a comparison of YBC vs. OBC tumors, indicating that normal tissue compartment could contribute to observed differences between bulk tumors. To separately examine molecular signatures from tumor, stroma and normal compartments, we used non-negative matrix factorization (NMF) analyses to virtually dissect bulk tumor expression data and identified 14 factors including 3 factors associated with normal tissues, 1 factor associated with stroma and 1 factor associated with tumor infiltrating lymphocytes (TIL). Integrative analyses of tumor associated factors and DE pathways revealed that estrogen response, endocrine therapy resistance, and oxidative phosphorylation pathways are up-regulated in YBCs compared to OBCs while cell cycle and proliferation pathways are up-regulated in Asian OBCs. Interestingly, many immune and inflammation pathways correlated with the TIL factor were significantly upregulated in OBCs vs. YBCs. Using gene expression signatures representing distinct immune cell types, we classified our cohort into four subtypes of varying TIL activities and observed significant enrichment of the TIL-high subtype in OBCs compared to YBCs. These observations were confirmed by IHC analyses of four TIL markers (CD45, CD4, CD8 and CD163) in 120 tumors. To our knowledge, this is the first large-scale multi-omics study of Asian breast cancer and would significantly contribute to the compendium of molecular data available for studying young breast cancers. The major landmarks in the molecular landscape looked similar across BCs of different ethnicities and ages, however, we have identified a number of distinguishing molecular characteristics associated with Asian YBC. The sources for some signatures were further traced to non-tumor intrinsic compartments, indicating that tumor microenvironment may play potentially important roles in driving the carcinogenesis of young breast cancers. Citation Format: Kan Z, Ding Y, Cho S, Lee S-H, Powell E, Jung HH, Chung W, Deng S, Choi Y-l, Kim J, Park W-Y, Vizcarra P, Fernandez-Banet J, Nichols T, Ram S, Lee SK, Kim SW, Lee JE, Ching KA, Kim J-Y, Ahn JS, Im Y-H, Nam SJ, Park YH. Multi-omics and immuno-oncology profiling reveal distinct molecular signatures of young Asian breast cancers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-05-15.

Additional file 1: Figure S1. Schematic representation of the strategy for the quantification of TILs in H&E stained images. Figure S2. Expression levels of immune-related genes in the three luminal immune subtypes and non-luminal (HER2-enriched and basal-like) tumors in HKBC. Figure S3. MCP-counter scores and CIBERSORT relative fractions of a subset of immune cell subpopulations in the three luminal immune subtypes and non-luminal (HER2-enriched and basal-like, separately) tumors in HKBC. Figure S4. MCP-counter scores of eight immune cell subpopulations in the three luminal immune subtypes and non-luminal (HER2-enriched and basal-like) tumors with the adjustment of tumor purity in HKBC. Figure S5. Replication of luminal immune subtypes in TCGA and KBC datasets: a) MCP-counter scores for eight immune cell subpopulations; b) Relative fractions of immune cell subpopulations by CIBERSORT (cell populations with extremely low fractions were not shown); c) High-TIL tumors showed upregulation of genes in immune activation and regulation activities than tumors in the other two luminal immune subtypes; d) High-ISG tumors expressed higher levels of ISG genes than tumors in the other two luminal immune subtypes. Figure S6. Genomic features associated with luminal immune subtypes in HKBC (HER2-enriched and basal-like, separately): a) ESR1/ESR2 ratios; b) number of mutations. Figure S7. Replication of genomic features associated with luminal immune subtypes in TCGA and KBC datasets: a) ESR1/ESR2 ratios; b) age at diagnosis; c) 10-year overall survival. Figure S8. Expression of APOBEC3B in normal and tumor tissue in relation to the polymorphic germline APOBEC3B deletion represented by rs12628403-C allele in HKBC. Figure S9. MCP-counter scores of eight immune cell subpopulations in adjacent normal breast tissue in the three luminal immune subgroups and non-luminal (HER2-enriched and basal-like) patients of HKBC.

Background And Aims The pattern of genetic alterations in cancer driver genes in patients with hepatocellular carcinoma (HCC) is highly diverse, which partially explains the low efficacy of available therapies. In spite of this, the existing mouse models only recapitulate a small portion of HCC inter-tumor heterogeneity, limiting the understanding of the disease and the nomination of personalized therapies. Here, we aimed at establishing a novel collection of HCC mouse models that captured human HCC diversity. Methods By performing hydrodynamic tail-vein injections, we tested the impact of altering a well-established HCC oncogene (either MYC or β-catenin) in combination with an additional alteration in one of eleven other genes frequently mutated in HCC. Of the 23 unique pairs of genetic alterations that we interrogated, 9 were able to induce HCC. The established HCC mouse models were characterized at histopathological, immune, and transcriptomic level to identify the unique features of each model. Murine HCC cell lines were generated from each tumor model, characterized transcriptionally, and used to identify specific therapies that were validated in vivo. Results Cooperation between pairs of driver genes produced HCCs with diverse histopathology, immune microenvironments, transcriptomes, and drug responses. Interestingly, MYC expression levels strongly influenced β-catenin activity, indicating that inter-tumor heterogeneity emerges not only from specific combinations of genetic alterations but also from the acquisition of expression-dependent phenotypes. Conclusions This novel collection of murine HCC models and corresponding cell lines establishes the role of driver genes in diverse contexts and enables mechanistic and translational studies.

Patient-Derived Xenograft (PDX) provides important preclinical model for pharmacological testing of oncology drug candidates. Molecular profiling of PDX tumors contributes to many areas of drug discovery from target discovery to development of clinical biomarker hypotheses and clinical trial design. We established a work flow to perform genomic and histopathology analyses of large numbers of PDX tumor models being made available for Pfizer internal research. To date we have generated whole-genome sequencing (WGS), whole-exome sequencing (WES) and whole transcriptome sequencing (RNA-Seq) data on PDX models spanning six cancer types including colon, pancreatic and breast cancers. Bioinformatics pipelines were developed to quantify gene expression and detect genetic alterations including mutation, copy number variations and gene fusions. A controlled evaluation study demonstrated that in silico classification of NGS reads into human/mouse origins is more effective than laboratory-based methods for removing mouse tissue contamination. Comparative analyses of molecular profiles from PDX and primary tumors of the same cancer origins suggest that important patterns of gene expression are retained by PDX models. An integrative genomic classifier was developed using the random forest algorithm, trained on primary tumor data, and shown to identify PDX cancer subtypes with high accuracy. Citation Format: Zhengyan Kan, Edward Rosfjord, James Hardwick, Ying Ding, Xianxian Zheng, Julio Fernandez, Stephanie Shi, Mark Ozeck, Hui Wang, Gabriel Troche, Eric Upeslacis, Amy Jackson-Fisher, Keith Ching, Shibing Deng, Xie Tao, John Chionis, Maruja Lira, Xiaorong Li, Konstantinos Tsaparikos, Patrick Lappin, Pamela Vizcarra, David Shields, Judy Lucas, Paul Rejto. Molecular profiling of patient-derived xenograft models across cancers. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-33.

As the impact of genetics, genomics, and bioinformatics on drug discovery has been increasingly recognized, this session of the 2018 Pacific Symposium on Biocomputing (PSB) aims to facilitate scientific discussions between academia and pharmaceutical industry on how to best apply genetics, genomics and bioinformatics to enable drug discovery. The selected papers focus on developing and applying computational approaches to understand drug mechanisms of action and develop drug combination strategies, to enable in silico drug screening, and to further delineate disease pathways for target identification and validation.

Single-cell transcriptome profiling of tumour tissue isolates allows the characterization of heterogeneous tumour cells along with neighbouring stromal and immune cells. Here we adopt this powerful approach to breast cancer and analyse 515 cells from 11 patients. Inferred copy number variations from the single-cell RNA-seq data separate carcinoma cells from non-cancer cells. At a single-cell resolution, carcinoma cells display common signatures within the tumour as well as intratumoral heterogeneity regarding breast cancer subtype and crucial cancer-related pathways. Most of the non-cancer cells are immune cells, with three distinct clusters of T lymphocytes, B lymphocytes and macrophages. T lymphocytes and macrophages both display immunosuppressive characteristics: T cells with a regulatory or an exhausted phenotype and macrophages with an M2 phenotype. These results illustrate that the breast cancer transcriptome has a wide range of intratumoral heterogeneity, which is shaped by the tumour cells and immune cells in the surrounding microenvironment., Genetic heterogeneity in breast cancer has been demonstrated at a single-cell resolution with high levels of genome coverage. Here, the authors perform transcriptome analysis of 515 single cells from 11 patients and define core gene expression signatures for subtype-specific single breast cancer cells and tumour-infiltrating immune cells.

The molecular bases underlying neoadjuvant chemotherapy (NAC) response are poorly understood. To elucidate the effects of NAC on breast tumor biology and its association with clinical outcome, we have conducted WES and RNA-Seq profiling of a longitudinal breast cancer (BC) cohort consisting of 146 cases (281 tumors, 109 pairs), including 55 (38%) that achieved pathologic complete responses (pCR) and 91 (62%) that harbored residual diseases at time of surgery. Tumor biopsies were collected for each patient at three time points - pre-treatment, three weeks after the first cycle of anthracycline and cyclophosphamide (AC) and at the time of surgery, after 3 more cycles of AC followed by 4 cycles of taxane. In addition to somatic mutations and copy number alterations, we also derived a comprehensive set of genomic and molecular features for each tumor including chromosomal instability, loss-of-heterozygosity, mutation burden, mutation signatures and expression signatures for oncogenic signaling pathways and immune cell subsets. Virtual microdissection analysis inferred 14 factors that represent distinct tissue compartment including a tumor infiltrating lymphocyte (TIL) factor and revealed that initial NAC treatment increased stromal and adjacent normal tissue fractions while reducing tumor cellularity. NAC also induced dynamic changes in immune gene expressions over time, a pattern that was validated through detecting and quantifying the density of TILs from H&E images. To investigate NAC induced changes in tumor intrinsic biology we classified tumors into five oncogenic cellular states on a reference Onco-GPS map defined by transcriptional signatures from breast cancer cell lines. We observed that, as a result of NAC treatment, tumors often change from one oncogenic state to another, transiently upregulating an EMT program that appears to mediate drug resistance and increase the likelihood of residual disease. Multiple regression and multivariate analyses were performed to identify predictive biomarkers of pCR status while adjusting for BC subtypes and tumor purity. We found that ER+ subtype and estrogen response signature but not Ki-67 were independently associated with NAC response. Within TNBC, the immunomodulatory subtype was enriched in responders while the basal-like subtype had the poorest response. Pretreatment TIL and changes in TIL level over time were independently associated with NAC response, implicating anti-tumor immunity in mediating the efficacy of chemotherapies. Through multi-omics characterization of longitudinally paired tumor biopsies, we have revealed dynamic changes in the tumor molecular states in BC patients undergoing NAC treatment, identified molecular markers of treatment outcome and derived insights into the mechanism of action as well as resistance to an important class of therapy. Citation Format: Samir Lal, Ying Ding, Jeong Eon Lee, Soo-Hyeon Lee, Se Kyung Lee, Jae-Yong Nam, Jong Han Yu, Yoon-la Choi, Seok Won Kim, Seok Jin Nam, Ji-Yeon Kim, Sripad Ram, Eric Powell, Keith A. Ching, Pablo Tamayo, William Kim, Huwate Yeerna, Soo Youn Cho, Vinicius Bonato, Shibing Deng, Jinho Kim, Hyuntae Shin, Woong-Yang Park, Paul A. Rejto, Jadwiga Bienkowska, Yeon-Hee Park, Zhengyan Kan. Multi-omics profiling of breast cancers during neoadjuvant chemotherapy identified distinct molecular changes and biomarkers associated with clinical response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1684.

Gastric cancer is a heterogeneous disease with multiple environmental etiologies and alternative pathways of carcinogenesis. Beyond mutations in TP53, alterations in other genes or pathways account for only small subsets of the disease. We performed exome sequencing of 22 gastric cancer samples and identified previously unreported mutated genes and pathway alterations; in particular, we found genes involved in chromatin modification to be commonly mutated. A downstream validation study confirmed frequent inactivating mutations or protein deficiency of ARID1A, which encodes a member of the SWI-SNF chromatin remodeling family, in 83% of gastric cancers with microsatellite instability (MSI), 73% of those with Epstein-Barr virus (EBV) infection and 11% of those that were not infected with EBV and microsatellite stable (MSS). The mutation spectrum for ARID1A differs between molecular subtypes of gastric cancer, and mutation prevalence is negatively associated with mutations in TP53. Clinically, ARID1A alterations were associated with better prognosis in a stage-independent manner. These results reveal the genomic landscape, and highlight the importance of chromatin remodeling, in the molecular taxonomy of gastric cancer.

Cancer is a heterogeneous disease that is classified by its tissue of origin or molecular characteristics such as genetic alterations that drive tumorigenesis. Large-scale efforts using loss-of-function genetic screens to systematically identify genes essential for the proliferation and survival of cancer cells provide a powerful approach for studying cancer biology and discovering drug targets. However, cancer cell lines from different lineages or molecular background vary in their dependencies on specific genes or pathways. Functional ablation of a gene may be only lethal in one segment of cancer cell lines harboring certain molecular deficiencies or activation of a specific oncogenic signaling pathway, a phenomenon called synthetic lethality. A key challenge here would be to identify the true synthetic lethal interactions from a combinatorially large number of possible interactions between molecular aberrations and gene-level sensitivity to functional perturbation. With recent advances in large-scale studies such as CCLE and Achilles, genome-wide functional genomics screens using CRISPR-Cas9 or shRNA technologies as well as comprehensive molecular profiles have become available for a large number of cancer cell lines. Here we present the Variant Interpretation Portal (VIP), a system biology tool designed to enable integrative analysis of molecular and functional genomics data in cell lines for identifying synthetic lethal interactions. VIP consists of a command-line pipeline and a web-based user interface. The VIP pipeline rigorously filters out germline events and classifies genomic variants into multiple functional tiers. The VIP web portal provides users with a graphic interface to perform exploratory visual analyses of associations between two variables or multiple variables, where a variable could be a genetic alteration or a gene-level sensitivity profile. VIP also enables systematic search for significant association between one variable, such as the sensitivity profile, vs. a database of variables such as histology or molecular attributes. VIP is optimized to perform real-time analytics and enables the incorporation and analysis of user-provided data. The code can be accessed from https://github.com/juferban/vip. Citation Format: Julio Fernandez, Ying Ding, Zhengyan Kan. VIP: A system biology platform for cell line centric integrative analysis of molecular and functional genomics data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2282.

The Cell Index Database, (CELLX) (http://cellx.sourceforge.net) provides a computational framework for integrating expression, copy number variation, mutation, compound activity, and meta data from cancer cells. CELLX provides the computational biologist a quick way to perform routine analyses as well as the means to rapidly integrate data for offline analysis. Data is accessible through a web interface which utilizes R to generate plots and perform clustering, correlations, and statistical tests for associations within and between data types for ~20,000 samples from TCGA, CCLE, Sanger, GSK, GEO, GTEx, and other public sources. We show how CELLX supports precision oncology through indications discovery, biomarker evaluation, and cell line screening analysis.

International audience; The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Molecular medicine requires the precise definition of drug targets, and tools are now in place to provide genome-wide information on the expression and alternative splicing patterns of any known gene. DNA microarrays were used to monitor transcript levels of the nine well-characterized alpha-subunit sodium channel genes across a broad range of tissues from cynomolgus monkey, a non-human primate model. Alternative splicing of human transcripts for a subset of the genes that are expressed in dorsal root ganglia, SCN8A (Na(v)1.6), SCN9A (Na(v)1.7), and SCN11A (Na(v)1.9) was characterized in detail. Genomic sequence analysis among gene family paralogs and between cross-species orthologs suggested specific alternative splicing events within transcripts of these genes, all of which were experimentally confirmed in human tissues. Quantitative PCR revealed that certain alternative splice events are uniquely expressed in dorsal root ganglia. In addition to characterization of human transcripts, alternatively spliced sodium channel transcripts were monitored in a rat model for neuropathic pain. Consistent down-regulation of all transcripts was observed, as well as significant changes in the splicing patterns of SCN8A and SCN9A.

Alternative pre–messenger RNA (pre-mRNA) splicing plays important roles in development, physiology, and disease, and more than half of human genes are alternatively spliced. To understand the biological roles and regulation of alternative splicing across different tissues and stages of development, systematic methods are needed. Here, we demonstrate the use of microarrays to monitor splicing at every exon-exon junction in more than 10,000 multi-exon human genes in 52 tissues and cell lines. These genome-wide data provide experimental evidence and tissue distributions for thousands of known and novel alternative splicing events. Adding to previous studies, the results indicate that at least 74% of human multi-exon genes are alternatively spliced.

The expressed sequence tag (EST) collection in dbEST provides an extensive resource for detecting alternative splicing on a genomic scale. Using genomically aligned ESTs, a computational tool (TAP) was used to identify alternative splice patterns for 6400 known human genes from the RefSeq database. With sufficient EST coverage, one or more alternatively spliced forms could be detected for nearly all genes examined. To identify high (>95%) confidence observations of alternative splicing, splice variants were clustered on the basis of having mutually exclusive structures, and sample statistics were then applied. Through this selection, alternative splices expected at a frequency of >5% within their respective clusters were seen for only 17%–28% of genes. Although intron retention events (potentially unspliced messages) had been seen for 36% of the genes overall, the same statistical selection yielded reliable cases of intron retention for

Breast cancers (BC) in younger, premenopausal patients (YBC) tend to be more aggressive with worse prognosis, higher chance of relapse and poorer response to endocrine therapies compared to breast cancers in older patients. The proportion of YBC (age ≤ 40) among BC in East Asia is estimated to be 16-32%, significantly higher than the 7% reported in Western countries. In addition, approximately half of the Asian BC patients were premenopausal compared to 15-30% in the West. To characterize the molecular bases of Asian YBC, we have performed whole-exome sequencing (WES) and whole-transcriptome sequencing (WTS) on tumor and matched normal samples from 168 Korean BC patients consisting of 106 YBC cases (age ≤ 40) and 62 OBC cases (age > 40). We then performed comparison analyses with the TCGA BC cohort consisting of 1,116 tumors from primarily Caucasian patients, also grouped by age into YBC (age ≤ 40), IBC (40 < age ≤ 60) and OBC (age > 60). We performed logistic regression analyses to identify differentially expressed (DE) genes and pathways among age-based cohorts while controlling for the confounding effects of molecular subtype, tumor purity and stage. Within the Asian cohort, we found that estrogen response, endocrine therapy resistance, and various metabolism pathways are up-regulated in YBCs while cell cycle, proliferation and inflammatory pathways are up-regulated in OBCs. To separately examine molecular signatures from tumor, stroma and normal compartments, we used non-negative matrix factorization (NMF) analyses to virtually dissect bulk tumor expression data and identified 14 factors including 3 factors associated with normal tissues, 1 factor associated with stroma and 1 factor associated with tumor infiltrating leukocytes (TILs). By examining the correlation between pathway gene expression and NMF factors, we inferred that DE pathways such as fatty acid metabolism, bile acid biosynthesis, and epithelial-to-mesenchymal transition (EMT) were mainly active in stromal and normal tissue compartments. The TIL factor was significantly enriched in Asian BCs relative to Caucasian BCs with the highest TIL factor weight observed in Asian OBCs. Using gene expression signatures representing distinct types of TILs, we classified the combined cohort into three subtypes of varying TIL activities. Consistent with results from the NMF analysis, the TIL-high subtype is also significantly enriched in Asian BCs relative to Caucasian BCs. To our knowledge, this is the first large-scale multi-omics study of Asian breast cancer. Comparative analyses of multi-omics profiles from Asian and primarily Caucasian BC cohorts identified distinguishing molecular signatures associated with Asian BCs. Further, many signatures appeared to be specific to non-tumor compartments within bulk tumor, indicating that young Asian BCs may harbor distinctive tumor microenvironment. Citation Format: Yeon Hee Park, Ying Ding, Soo-Hyeon Lee, Hae Hyun Jung, Woosung Chung, Soonweng Cho, Jin-Ho Kim, Shibing Deng, Yoon-la Choi, Julio Fernandez, Se Kyung Lee, Seok Won Kim, Jeong Eon Lee, Ji-Yeon Kim, Jin Seok Ahn, Young-Hyuck Im, Seok Jin Nam, Woong-Yang Park, Zhengyan Kan. Comparative analyses of multi-omics profiles reveal distinctive molecular signatures of young Asian breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3370. doi:10.1158/1538-7445.AM2017-3370

With the availability of a nearly complete sequence of the human genome, aligning expressed sequence tags (EST) to the genomic sequence has become a practical and powerful strategy for gene prediction. Elucidating gene structure is a complex problem requiring the identification of splice junctions, gene boundaries, and alternative splicing variants. We have developed a software tool, Transcript Assembly Program (TAP), to delineate gene structures using genomically aligned EST sequences. TAP assembles the joint gene structure of the entire genomic region from individual splice junction pairs, using a novel algorithm that uses the EST-encoded connectivity and redundancy information to sort out the complex alternative splicing patterns. A method called polyadenylation site scan (PASS) has been developed to detect poly-A sites in the genome.TAP uses these predictions to identify gene boundaries by segmenting the joint gene structure at polyadenylated terminal exons. Reconstructing 1007 known transcripts, TAP scored a sensitivity (Sn) of 60% and a specificity (Sp) of 92% at the exon level. The gene boundary identification process was found to be accurate 78% of the time. TAP also reports alternative splicing patterns in EST alignments. An analysis of alternative splicing in 1124 genic regions suggested that more than half of human genes undergo alternative splicing. Surprisingly, we saw an absolute majority of the detected alternative splicing events affect the coding region. Furthermore, the evolutionary conservation of alternative splicing between human and mouse was analyzed using an EST-based approach. (See http://stl.wustl.edu/∼zkan/TAP/)

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.

Breast cancers (BC) in younger, premenopausal patients (YBC) tend to be more aggressive with worse prognosis, higher chance of relapse and poorer response to endocrine therapies compared to breast cancers in older patients (OBC). The proportion of YBC (age ? 40) among BC in East Asia is estimated to be 16-32%, significantly higher than the 7% reported in Western countries. Genomic and molecular characterizations have deepened our understanding of breast cancer biology in areas ranging from intrinsic subtypes to treatment responses, however, the molecular bases of Asian YBC remains poorly characterized. We have performed whole-exome sequencing (WES), whole-transcriptome sequencing (WTS) and high coverage targeted sequencing on tumor and matched normal samples from 133 Korean BC patients consisting of 74 YBC cases (age ? 40). We further performed immunohistochemistry (IHC) analyses to characterize tumor-infiltrating lymphocytes (TILs) in 46 tumors using four markers (CD45, CD4, CD8 and CD163). We found that BRCA1/2 germline deleterious mutations are enriched in YBC and the ER+/HER2- subtype, indicating that Asian ER+ YBC has a significant germline contribution. MutSig analysis4 identified ARID1A as a significantly mutated gene, implicating chromatin modeling as a cancer driver in Asian BC. Differential expression analyses suggested that Asian YBC differ in energy metabolism and are more active in protein synthesis than OBC tumors, whereas OBC is more proliferative than YBC. Using gene expression signatures representing distinct immune cell types and immunohistochemistry, we classified our cohort into four subtypes of varying TIL activities: high, medium, low and quiet. The majority of immunogenic cases with high TIL levels lie in ER+ or HER2+ subtypes although higher proportion is seen in TNBC. Moreover, YBC tumors appear to harbor lower levels of TIL activities than OBC, suggesting that younger patients may be less likely to benefit from immunomodulatory therapies than older patients. To our knowledge, this is the first large-scale multi-omics study of Asian breast cancer and would significantly contribute to the compendium of molecular data available for young, premenopausal breast cancer. While the major landmarks in the molecular and immune landscape of Asian BC look similar to that of the predominantly Caucasian BC cohorts, we have identified a number of distinguishing characteristics pointing to distinctive oncogenic mechanisms underlying Asian BC. Citation Format: Yeon Hee Park, Ying Ding, Soonweng Cho, Soo-Hyeon Lee, Hae Hyun Jung, Woosung Chung, Jinho Kim, Woong-Yang Park, Eric Powell, Pamela Vizcarra, Shibing Deng, Se Kyung Lee, Seok Won Kim, Jeong Eon Lee, Ji-Yeon Kim, Jin Seok Ahn, Young-Hyuck Im, Seok Jin Nam, Zhengyan Kan. Multi-omics and immuno-oncology profiling of an Asian breast cancer cohort enriched in young and premenopausal patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-325.

To survey hepatitis B virus (HBV) integration in liver cancer genomes, we conducted massively parallel sequencing of 81 HBV-positive and 7 HBV-negative hepatocellular carcinomas (HCCs) and adjacent normal tissues. We found that HBV integration is observed more frequently in the tumors (86.4%) than in adjacent liver tissues (30.7%). Copy-number variations (CNVs) were significantly increased at HBV breakpoint locations where chromosomal instability was likely induced. Approximately 40% of HBV breakpoints within the HBV genome were located within a 1,800-bp region where the viral enhancer, X gene and core gene are located. We also identified recurrent HBV integration events (in ≥ 4 HCCs) that were validated by RNA sequencing (RNA-seq) and Sanger sequencing at the known and putative cancer-related TERT, MLL4 and CCNE1 genes, which showed upregulated gene expression in tumor versus normal tissue. We also report evidence that suggests that the number of HBV integrations is associated with patient survival.

Background Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and expression levels of TICs in individual samples across the genome. Methods We performed single-end RNA-Seq on three human prostate adenocarcinoma samples and their corresponding normal tissues, as well as brain and universal reference samples. We developed two bioinformatics methods to specifically identify TIC events: a targeted alignment method using artificial exon-exon junctions within 200,000 bp from adjacent genes, and genomic alignment allowing splicing within individual reads. We performed further experimental verification and characterization of selected TIC and fusion events using quantitative RT-PCR and comparative genomic hybridization microarrays. Results Targeted alignment against artificial exon-exon junctions yielded 339 distinct TIC events, including 32 gene pairs with multiple isoforms. The false discovery rate was estimated to be 1.5%. Spliced alignment to the genome was less sensitive, finding only 18% of those found by targeted alignment in 33-nt reads and 59% of those in 50-nt reads. However, spliced alignment revealed 30 cases of TICs with intervening exons, in addition to distant inversions, scrambled genes, and translocations. Our findings increase the catalog of observed TIC gene pairs by 66%. We verified 6 of 6 predicted TICs in all prostate samples, and 2 of 5 predicted novel distant gene fusions, both private events among 54 prostate tumor samples tested. Expression of TICs correlates with that of the upstream gene, which can explain the prostate-specific pattern of some TIC events and the restriction of the SLC45A3-ELK4 e4-e2 TIC to ERG-negative prostate samples, as confirmed in 20 matched prostate tumor and normal samples and 9 lung cancer cell lines. Conclusions Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as MSMB-NCOA4, may play functional roles in cancer.

A Smooth(ened) Path to Drug Resistance The Hedgehog (Hh) signaling pathway has emerged as a key contributor to the growth of medulloblastoma, an aggressive brain tumor. GDC-0449, a drug that ramps down this signaling pathway by binding to the Hh pathway component Smoothened, was recently shown to induce rapid and dramatic tumor regression in a patient with metastatic medulloblastoma, but the tumor eventually developed resistance to the drug. Yauch et al. (p. 572 , published online 3 September) show that resistance arose because the tumor acquired a mutation in Smoothened that disrupts binding of the drug. Identification of this resistance mechanism may facilitate the design of next-generation drugs for this type of cancer.

Although genomewide association studies have successfully identified associations of many common single-nucleotide polymorphisms (SNPs) with common diseases, the SNPs implicated so far account for only a small proportion of the genetic variability of tested diseases. It has been suggested that common diseases may often be caused by rare alleles missed by genomewide association studies. To identify these rare alleles we need high-throughput, high-accuracy resequencing technologies. Although array-based genotyping has allowed genomewide association studies of common SNPs in tens of thousands of samples, array-based resequencing has been limited for 2 main reasons: the lack of a fully multiplexed pipeline for high-throughput sample processing, and failure to achieve sufficient performance. We have recently solved both of these problems and created a fully multiplexed high-throughput pipeline that results in high-quality data. The pipeline consists of target amplification from genomic DNA, followed by allele enrichment to generate pools of purified variant (or nonvariant) DNA and ends with interrogation of purified DNA on resequencing arrays. We have used this pipeline to resequence approximately 5 Mb of DNA (on 3 arrays) corresponding to the exons of 1,500 genes in >473 samples; in total >2,350 Mb were sequenced. In the context of this large-scale study we obtained a false positive rate of approximately 1 in 500,000 bp and a false negative rate of approximately 10%.

There was an error in the title of the article, which omitted the word "in." The correct title should read: ACC2 Is Expressed at High Levels in Human White Adipose and Has an Isoform with a Novel N-Terminus. This also affects the article's citation.

An important level at which the expression of programmed cell death (PCD) genes is regulated is alternative splicing. Our previous work identified an intronic splicing regulatory element in caspase-2 (casp-2) gene. This 100-nucleotide intronic element, In100, consists of an upstream region containing a decoy 3' splice site and a downstream region containing binding sites for splicing repressor PTB. Based on the signal of In100 element in casp-2, we have detected the In100-like sequences as a family of sequence elements associated with alternative splicing in the human genome by using computational and experimental approaches. A survey of human genome reveals the presence of more than four thousand In100-like elements in 2757 genes. These In100-like elements tend to locate more frequent in intronic regions than exonic regions. EST analyses indicate that the presence of In100-like elements correlates with the skipping of their immediate upstream exons, with 526 genes showing exon skipping in such a manner. In addition, In100-like elements are found in several human caspase genes near exons encoding the caspase active domain. RT-PCR experiments show that these caspase genes indeed undergo alternative splicing in a pattern predicted to affect their functional activity. Together, these results suggest that the In100-like elements represent a family of intronic signals for alternative splicing in the human genome.

The discovery of somatic mutations in cancer tissue is extremely laborious, time-consuming and costly. In an evaluation comparing mismatch repair detection (MRD) against Sanger sequencing for somatic-mutation detection, we found that MRD had a specificity of 96% and a sensitivity of 92%. Our results showed that MRD is a robust and cost-effective alternative to Sanger sequencing for identifying somatic mutations in human tumors.

Clinical development of cancer therapies is associated with attrition rates as high as 80-95%. This high attrition suggests that standard preclinical pharmacology models do not accurately reflect clinical responses. The development of more predictive preclinical models requires several considerations; the relevance of the in vivo model, the administration of test agent, and the interpretation of efficacy data. PDX are cancer models developed from the direct transfer of patient tumor tissue into immunocompromised mice. A collection of PDX models, by retaining the genetic and histologic characteristics of the patients from which they were derived, represents the complexity and heterogeneity of human cancer. To minimize the clinical attrition rates of oncology compounds, we are developing hundreds of PDX models in seven major cancer indications. The collection is being molecularly profiled by RNAseq, WES, and proteomics. Profiling has identified models with robust expression of target proteins or mutant oncogenes that are likely to respond in preclinical efficacy tests. Conversely, the PDX models may provide an understanding of resistance, for example evaluating models with good target expression that fail to respond to therapy. Patient and tumor information, if known, has been collected for each PDX model including age, sex, cancer stage and grade, diagnosis, primary or metastatic site, and prior treatments. In addition to the improvements provided by the PDX models, a preclinical paradigm shift away from treatment with maximally tolerated dose towards clinically relevant dose (CRD), taking into consideration such aspects as exposure, formulation, route and schedule, is critical when attempting to predict clinical outcome from preclinical data. Also essential is the incorporation of clinically meaningful endpoints (regression) when assessing preclinical activity. We have initiated studies on cohorts of non small cell lung and breast PDX models to predict the likely clinical efficacy of candidate compounds for clinical development and to determine the CRD for standard of care (SOC) regimens required to define the most promising Phase II/III combination therapies. Anti-tumor activities were characterized using RECIST criteria of progressive disease (PD), stable disease (SD), partial response (PR), and complete response (CR). Target expression was evaluated by RNA, proteomics and immunohistochemistry. Preliminary results demonstrate a spectrum of responses against experimental therapeutics, including Phase I ADCs and are defining the CRD required for combination treatments with SOC. Identification of the most critical parameters of PDX models predicting clinical outcome will help in validating the utility of ‘n of 1′ studies with the PDX collection, inform patient enrollment strategies, guide combination therapies, and provide insight for identifying new tumor indications. Citation Format: Edward Rosfjord, Xin Han, Danielle Leahy, Erik Upeslacis, Justin Lucas, Jonathon Golas, Andrea Hooper, Fred Immermann, Bingwen Lu, Jeremy Myers, Zhengyan Kan, James Hardwick, Eric Powell, Puja Sapra, Paul Rejto, Hans-Peter Gerber, Judy Lucas. Patient derived xenograft (PDX) models: improving predictability of experimental cancer therapies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1469. doi:10.1158/1538-7445.AM2015-1469

Advances in cancer research and sequencing technologies have contributed to the proliferation of large-scale cancer omics data sets from both public consortia and privately funded collaborations. There are increasing demands for broadly accessible tools that enable scientists to perform ad hoc analyses of cancer omics data. Here we present OASIS (http://oasis.pfizer.com), an open-access web portal that enables complex analytical queries across somatic mutations, copy number changes (CNV) and gene expression data from public domain and Pfizer funded omics studies. OASIS was designed to perform multidimensional data integration, allowing users to analyze correlations among multiple data types, as well as visualize and compare alterations across different cancers. Users can browse alteration summary reports at the gene and sample level and perform analyses using interactive visualizations. These include the Pan-Cancer Report, a unique tool that provides a high-level overview of genetic variation across multiple cancer types. Through the use of the interactive visualizations researchers can explore differentially expressed genes, identify tumor samples for over expression, investigate the correlation between CNV and expression or survey alteration patterns for a list of genes. Users can explore molecular profiles from the Cancer Cell Line Encyclopedia (CCLE) and the Catalog of Somatic Mutations in Cancer (COSMIC), to identify cell line models of interest. Researchers can also construct complex queries through a user-friendly web interface supported by the Biomart query engine. Programmatic access is also available through web services. OASIS is a powerful tool that enables cancer researchers to perform integrative analyses of large-scale cancer omics data sets, thereby facilitating key steps in oncology drug discovery ranging from target identification to model selection. Citation Format: Julio Fernandez-Banet, Anthony Esposito, Scott Coffin, Sabine Schefzick, Ying Ding, Keith Ching, Istvan Horvath, Peter Roberts, Paul Rejto, Zhengyan Kan. OASIS: A centralized portal for cancer omics data analysis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4874. doi:10.1158/1538-7445.AM2015-4874