Precision Cancer Care Research Articles

Development of a culturally sensitive narrative intervention to promote genetic counseling among African American women at risk for hereditary breast cancer.

African American women with hereditary breast cancer risk are less likely to undergo genetic counseling and testing compared with non-Hispanic White women. Inequities in the use of precision cancer care are likely to exacerbate racial disparities in cancer outcomes. A culturally sensitive multimedia narrative intervention was developed to motivate African American women at risk for hereditary breast cancer to engage in genetic counseling. Development of the intervention was grounded in the Integrative Model of Behavioral Prediction using a phenomenological, deductive approach and employed multiple qualitative methods for data collection, including 1-on-1 interviews and story circles with members of the target audience to identify salient themes and lived experiences. Focus group testing was then conducted with members of the group of focus, primary care providers, and community stakeholders. Six themes that mapped to the theoretical model were identified. Lived experiences were abstracted from story circle data to create a narrative storyline. Educational content and motivational messaging derived from the 6 themes were embedded into the script. Focus group testing with stakeholder groups was used to refine the intervention. Testing of the final multimedia narrative with focus groups indicated that the intervention was culturally sensitive and authentic, and the messaging was effective. Multiple qualitative data collection methods and a robust theoretical framework of health behavior were key elements for this study to develop a culturally sensitive, narrative intervention that reflects lived experiences and motivates underserved African American women with hereditary breast cancer risk to engage in genetic counseling. This strategy can be applied to mitigate racial inequities in the use of other genomic approaches for personalizing cancer care.

HSR21-045: Genetic Counselor Coverage Disparities & Inequities in Access to Precision Cancer Care

HSR21-045: Genetic Counselor Coverage Disparities & Inequities in Access to Precision Cancer Care

Abstract PO-066: Data standardization, integration and meta-analysis of preclinical pharmacogenomics studies for gene expression biomarker discovery

Abstract The sparsity of predictive biomarkers for drug response remains a major impediment to the clinical success of precision oncology. Over the past decade, massive studies combining in-vitro drug screening with high-throughput molecular profiling of cancer cell lines have been published, with the goal of discovering novel predictive biomarkers for drug response. Unfortunately, inconsistencies in the data, as well as a lack of standards in the field, has effectively siloed the findings of these studies away from the clinical researchers working in precision medicine. In our previous work developing the PharmacoGx/PharmacoDB platform, we have reprocessed and curated the 7 largest pharmacogenomic studies released to date. Together, these studies profiled 760 compounds across ~1600 cell lines, in over 650,000 drug dose response experiments. Here, we present an update of this database, and describe our preliminary findings from a statistical meta-analysis of these data for the discovery of gene expression biomarkers. Our meta-analysis looked for markers consistently associated with drug response across 11 tissue types and 70 compounds found in at least 3 studies in the examined dataset. From these data, we find approximately 4338 consistent associations across studies surviving multiple hypothesis correction, in 1946 genes, across 8 tissues and 34 different drugs. The results show evidence of both drug-mechanism specific markers of response, as well as markers of multi-drug resistance phenotypes. Within lung cancer cell lines, we observe an enrichment of TGF-β signalling related genesets among markers of multi-drug sensitivity and resistance. We discuss our approach to validate these markers using organoid, in vivo and clinical datasets. Finally, we detail tools we are building for researchers to explore our database of putative biomarkers and the data supporting them; focusing on exposing our findings to the clinical precision medicine research community. Ultimately, our goal is to extract a database of high confidence preclinical associations from the consensus of published pharmacogenomic studies. This database would be the first step in translating findings from these massive preclinical studies towards novel clinically actionable biomarkers for use in the pursuit of precision cancer care. Citation Format: Petr Smirnov, Benjamin Haibe-Kains. Data standardization, integration and meta-analysis of preclinical pharmacogenomics studies for gene expression biomarker discovery [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-066.

Abstract IA23: The role of the microbiome in response and toxicity to cancer therapy

Abstract We have made tremendous progress in cancer care via the use of immunotherapy; however, not all patients respond and toxicity to therapy may be limiting. It is becoming increasingly clear that responses to therapy are dependent on a number of factors that influence tumor growth and immunity—and that these all are inter-related. There is a growing appreciation of the role of environmental factors, such as the microbiome, on responses to therapy. The microbiome refers to microbes and their genomes within a given host, and there is a significant contribution of microbes to our overall cellular content and to our genomic content. There is now evidence that the gut microbiome may shape immunity and responses to immunotherapy, and efforts are ongoing to modulate the microbiome to enhance therapeutic responses. Additionally, there is evidence that microbes within tumors of patients with cancer may shape responses to therapy. Furthermore, microbes may also influence toxicity to cancer therapy. The use of the microbiome as a biomarker and a therapeutic target will be discussed, as will complexities and recommendations for a path forward to implement microbiome analyses and targeting in precision cancer care and overall precision health. Citation Format: Jennifer A. Wargo. The role of the microbiome in response and toxicity to cancer therapy [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr IA23.

Antibody Pretargeting Based on Bioorthogonal Click Chemistry for Cancer Imaging and Targeted Radionuclide Therapy.

Bioorthogonal click chemistry-employing antibody-conjugated trans-cyclooctenes (TCO) and tetrazine (Tz)-based radioligands able to covalently bind in vivo-appeared recently as a potential alternative to circumvent the hematotoxicity induced by radioimmunotherapy of solid tumors. This Review focuses on the recent advances concerning TCO/Tz pretargeting in both cancer imaging and targeted-radionuclide therapy for prospective clinical transfer. We exhaustively identified 25 PubMed publications reporting preclinical imaging and 5 therapy studies with full mAbs as targeting vectors, since its first application in 2010. The fast, safe, modulable, and specific TCO/Tz pretargeting showed high potential as a theranostic tool to get more personalized and precise cancer care. The recent optimizations reported here highlighted a possible first clinical evaluation of IEDDA pretargeting in the coming years.

Proposal for Value-Based, Tiered Reimbursement for Tumor Biomarker Tests to Promote Innovation and Evidence Generation.

Cancer precision medicine depends on high-quality tumor biomarker tests (TBTs) for treatment selection. TBT reimbursement within the United States in the current regulatory environment is not tied to premarket evidence of clinical utility, resulting in a vicious cycle wherein low-level evidence of utility leads to poor reimbursement, thereby impeding investment in developing new, clinically valuable TBTs supported by high-level evidence. Rational, value-based TBT pricing presents many practical challenges. Precise one-to-one mapping of reimbursement to cost savings or cost effectiveness is precluded by an absence of formal cost-effectiveness analyses for many emerging TBTs, and for more established TBTs, it has become clear that such analyses may yield wildly variable, subjective estimates. To address these challenges, we propose a system of tiered reimbursement that rewards development of high-quality TBTs within specific use contexts, supported by strong evidence of analytic validity and clinical utility. We propose three use contexts of TBTs, each defined by its influence on treatment decisions relative to the current standard of care-Opt-Out, Opt-In, and the use of appropriate, alternative, effective therapies (Opt-Alt). By ensuring minimum levels of reimbursement, this system provides a return on investment to encourage and support the research and development needed to generate high levels of evidence for claims of clinical utility for TBTs by using a robust, objective, and value-based system. We believe our proposed evaluation system will serve as a practical starting point to raise the bar for TBT quality and utility, which has the potential to redirect health care dollars from futile or ineffective treatment to investment in the development of high-quality TBTs needed for safe and effective precision cancer care.

Clinical Molecular Marker Testing Data Capture to Promote Precision Medicine Research Within the Cancer Research Network.

To evaluate health care systems for the availability of population-level data on the frequency of use and results of clinical molecular marker tests to inform precision cancer care. We assessed cancer-related molecular marker test data availability across 12 US health care systems in the Cancer Research Network. Overall, these systems provide care to a diverse population of more than 12 million people in the United States. We performed qualitative analyses of test data availability for five blood-based protein, nine germline, and 14 tissue-based tumor marker tests in each health care system's electronic health record and tumor registry using key informants, test code lists, and manual review of data types and output. We then performed quantitative analyses to estimate the proportion of patients with cancer with test utilization data and results for specific molecular marker tests. Health systems were able to systematically capture population-level data on all five blood protein markers, six of 14 tissue-based tumor markers, and none of the nine germline markers. Successful, systematic data capture was achievable for tests with electronic data feeds for test results (blood protein markers) or through prior manual abstraction by tumor registrars (select tumor-based markers). For test results stored in scanned image files (particularly germline and tumor marker tests), information on which test was performed and test results was not readily accessible in an electronic format. Even in health care systems with sophisticated electronic health records, there were few codified data elements available for evaluating precision cancer medicine test use and results at the population level. Health care organizations should establish standards for electronic reporting of precision medicine tests to expedite cancer research and facilitate the implementation of precision medicine approaches.

Abstract LB-300: The life history of breast cancer in Nigerian women: Evidence for ethnic differences in tumor evolution based on whole-genome sequencing

Abstract Breast cancer is a heterogeneous disease and the incidence to mortality ratio is highest for women of African ancestry. Paucity of data from non-European ancestry groups limits our understanding of the underlying etiological differences or alternative routes to progression that may explain differential outcomes. To examine the contribution of genomic differences, we performed high-depth whole-genome sequencing on 100 breast tumors (90X) and their paired normal samples (30X) from indigenous African women with breast cancer in Southwest Nigeria and performed comparative analysis with 84 TCGA whole genome sequences of breast tumor/normal pairs (46 White, 30 African American and 8 samples representing other ethnicities). High confidence somatic single nucleotide variants (SNVs) were obtained by using MuTect and Strelka. To analyse intra-tumoral heterogeneity (ITH), Battenberg and DPClust were used to call copy number aberrations (CNA) and cluster somatic SNVs based on cancer cell fraction (CCF) respectively. We find that in the HR-/HER2+ subtype, clonal losses of chromosome 14q are highly enriched in Nigerians (41%) but absent in the Whites even though the proportion of this subtype was comparable between the two groups (42% and 33% respectively). This is an interesting observation since not only 14q loss is known to be an event associated with breast cancer aggressiveness, but HR-/HER2+ has also been reported to be enriched within the relatively younger Nigerian patients with breast cancer. This may in part explain inter-ethnic disparity in survival. Also, somatic SNV clustering analysis showed that Nigerian cancers have a higher level of ITH than Whites, which may explain the pronounced aggressiveness of breast cancer in women of African ancestry. In contrast, early drivers (e.g. TP53 and PIK3CA) and whole genome duplication rates were mostly similar between the groups. Our observations suggest differences in the underlying evolutionary trajectories of breast cancer across ethnic backgrounds. These data underscore the need for larger and more in-depth studies of diverse cancer genomes and, if validated, may translate into clinical intervention opportunities tailored to women of African ancestry and accelerate progress in precision cancer care. Note: This abstract was not presented at the meeting. Citation Format: Naser Ansari-Pour, Jason J. Pitt, Stefan Dentro, Dominic Fitzgerald, Yonglan Zheng, Toshio F. Yoshimatsu, Padma Rajagopal, Andreas Gruber, Ayodele Sanni, Olayiwola Oluwasola, Mustapha Ajani, Abayomi Odetunde, Abiodun Popoola, Adeyinka Falusi, Temidayo Ogundiran, John Obafunwa, Oladosu Ojengbede, Nasiru Ibrahim, Kevin P. White, Dezheng Huo, Peter Van Loo, David C. Wedge, Olufunmilayo Olopade. The life history of breast cancer in Nigerian women: Evidence for ethnic differences in tumor evolution based on whole-genome sequencing [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 LB-300.

Meta-Analysis of Genome-Wide Association Studies (GWAS) of Late Toxicity in 3,874 Men Treated with Radiation for Prostate Cancer

Late toxicity following prostate cancer radiotherapy negatively impacts quality of life and can be dose-limiting. Radiosensitivity is a genetic trait, and identification of single nucleotide polymorphisms (SNPs) associated with toxicity could uncover novel radiobiology pathways and contribute to precision cancer care. The largest study to date meta-analyzed data from 1,564 men with prostate cancer and identified two risk SNPs. This expanded study added new cohorts to greatly increase the sample to 3,874 men with the aim of identifying new toxicity risk SNPs and validating previously identified SNPs. A GWAS meta-analysis was performed with six independent cohorts of men treated with radiotherapy for prostate cancer: RAPPER (n=2,010), RADIOGEN (n=658), GenePARE (n=495), UGhent (n=311), CCI-BT (n=252), and CCI-EBRT (n=148). Four toxicities were assessed prospectively from 6 months after radiotherapy and harmonized to a common scale: increased urinary frequency, decreased urine stream, hematuria, and rectal bleeding. Germline DNA was genotyped using genome-wide arrays. Imputation generated a uniform set of ∼7 million SNPs (frequency in Europeans >4%) across cohorts. Cox proportional hazards regression tested association between each SNP and time to first occurrence of grade 2 or worse toxicity within each cohort. Individual cohort results were combined using inverse variance weighted fixed-effects meta-analysis. Novel SNP-toxicity associations were considered significant if they had meta-p-value <5x10-8. Bayesian False Discovery Probability (BFDP) provided an additional measure of confidence. Five new risk loci for late toxicity were identified in 3,874 prostate cancer patients: rs17055178 (HR 1.98; 95%CI 1.60 to 2.44; p=2.4x10-10; BFDP <1%) and rs9644474 (HR 0.47; 95%CI 0.36 to 0.62; p=4.3x10-8; BFDP 10%) associated with rectal bleeding; rs10969913 (HR 3.82; 95%CI 2.50 to 5.83; p=6.2x10-10; BFDP 1.6%) with decreased urine stream; rs11122573 (HR 1.89; 95%CI 1.50 to 2.38; p=2.3x10-8; BFDP 5.7%) and rs139882217 (HR 4.83; 95%CI 2.73 to 8.52; p=2.7x10-8; BFDP 69%) with hematuria. Previously published risk SNPs showed consistent associations in the cohorts not included in prior discovery GWAS: rs1801516 in ATM associated with overall toxicity (ß=0.05; 95%CI 0.01 to 0.09; p=0.016), rs17599026 in KDM3B associated with 2yr prevalence of increased urinary frequency (OR 1.27; 95%CI 0.95 to 1.70; p=0.10), rs7720298 in DNAH5 associated with 2yr prevalence of decreased urine stream (OR 1.26; 95%CI 0.94 to 1.70; p=0.13). A locus in TANC1 showed replication in some, but not all, new cohorts and warrants further investigation. This largest GWAS to date identified novel risk SNPs and replicated previously identified SNPs. Further expansion of cohorts will uncover additional SNPs and allow development of risk models. Such models can be tested in clinical trials aimed at stratification of cancer patients based on toxicity risk profile.

The Role of “Liquid Biopsy” Repositories in Cancer Care in Low to Middle–Income Countries

Background and context: Translation of underlying individual genomic heterogeneity in cancer into precision medicine practice requires annotated cancer biorepositories. The potential for practice of precise medicine is also coupled to saving vital resources in low to middle–income countries. An overview of experience and outcomes from a tertiary level cancer center in a high-income country for liquid biobank established since 2009 is presented. Aim: To understand the challenges of building economically viable biorepositories that can be used for molecular diagnostics while delivering cancer care. Strategy/Tactics: An institutional ethics–approved prospective liquid biorepository was established in September of 2009 for advanced cancer patients. Informed consent–approved collection of 29.5 mL blood/urine was performed serially on enrolled patients and clinical annotation was obtained during follow-up including previous, current and future treatments and their outcomes. All specimens were processed using a uniform protocol in which extraction of germline DNA from buffy coats; serum for proteomics; platelet-poor and platelet-rich plasma (in citrate and EDTA anticoagulants) for microRNA and cell-free DNA extractions; and extraction of PAXgene RNA/DNA from whole blood was performed. Processing was done within 45 minutes of sample acquisition and storage in −80°C freezers with no freeze–thaw cycles. Program/Policy process: Biobanking for cancer care. Outcomes: Between September of 2009 and January of 2015, 535 advanced-stage prostate cancer patients in hormone-sensitive and castrate-resistant stage; 250 advanced kidney cancer patients; 110 testicular cancer patients were enrolled and 1550 collections were performed serially. This generated &gt;60,000 plasma/serum/DNA/RNA aliquots. Nucleic acids (DNA/RNA) from buffy coats and whole blood of 500-1000 ng volume each were also extracted. Cell-free DNA for somatic mutational and copy number analysis; single nucleotide profiling from germline DNA; RNA expression profiling from whole blood and microRNA analysis in plasma has been performed from this cohort along with proteomics using tandem mass spectrometry. By 2017, this has resulted in &gt;35 scientific publications; 5 patents; multiple national and international grant awards and enhanced precision cancer care for patient care. The cost burden for establishing the infrastructure was highly economical. What was learned: In our experience, liquid biopsy repositories can augment clinical cancer globally, but do not find this discussed in low to middle–income nations. Advancing and applying molecular oncology and team science to prospectively collected and retrospectively annotated biobanks can be a cost-efficient resource in a global cancer healthcare delivery system and a useful tool for scientific and economic opportunities and collaborations.

Abstract 418: Highly efficient duplex DNA tagging strategy improves accuracy of detecting ultra-low-frequency mutations through consensus read reconstruction

Abstract Introduction: Molecular diagnostics and precise personalized care continue to increase the sensitivity and specificity requirements for detecting low (~5%) to ultra-low (&amp;lt;1%) frequency actionable mutations by next generation sequencing (NGS). These low-frequency variants often occur below the reliable limit of detection of standard NGS as they are confounded by errors introduced during the NGS workflow. We have developed adapters containing unique molecular identifiers (UMIs) that permit tagging of double-stranded DNA and statistical reconstruction of reads sequenced as duplicates. These novel adapters are compatible with standard library preparation and enrichment methods and reagents, yet provide significantly enhanced error correction. Methods: Libraries were prepared from the 3 most commonly used oncology sample types: genomic, FFPE, or plasma-derived, cell-free DNA, using a standard, commercially available kit combined with standard adapters or the novel duplex UMI adapters. The libraries were enriched with a custom xGen Lockdown Panel targeting a 75 kb polymorphic region, and then deep sequencing and variant calling were performed. A consensus read building tool was developed to collapse PCR duplicates based on molecular barcodes, and the tool was used to evaluate the utility of UMIs in error correction. Results: Compared to standard adapters, the duplex adapters presented comparable or better library yield and mean deduplicated sequencing depth for all sample types and input masses tested. To evaluate variant-calling accuracy, we established mixtures of DNA of known SNP genotype to mimic ultra-low-frequency variant samples. For genomic DNA samples, DNA from NA12878 and NA24385 were mixed to generate minor allele frequency (MAF) down to 0.1%, and variant calls were evaluated against annotations in Genome in a Bottle. Commercial FFPE and cell-free DNA samples were genotyped and mixed to present MAF at 0.5%. When standard adapters were used, variants present at the MAF were detected with 90% sensitivity for all sample types, but only under conditions that also called &amp;gt;4,000 false positives, resulting in a positive predictive value (PPV) of &amp;lt;3%. Using the duplex UMI adapters in conjunction with consensus read construction, &amp;gt;90% detection sensitivity was achieved for genomic and cell-free DNA samples with 0 false positives, resulting in 100% PPV, a &amp;gt;40-fold error suppression. For FFPE DNA samples, the duplex adapters provided &amp;gt;30-fold PPV improvement compared to standard adapters. Conclusions: The duplex UMI adapters eliminate background NGS errors by collapsing duplicated reads using their unique tags. This leads to unprecedented accuracy in detecting true low-frequency variants, regardless of the input DNA source. Such advances are key to refining diagnostics and improving precision cancer care. Citation Format: Jiashi Wang, Kevin Lai, Madelyn Light, Layla Katiraee, Kristina Giorda, Mirna Jarosz, Yun Bao, Criss Walworth, David Kupec, Caifu Chen. Highly efficient duplex DNA tagging strategy improves accuracy of detecting ultra-low-frequency mutations through consensus read reconstruction [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 418.

Opportunities and Challenges in Genomic Sequencing for Precision Cancer Care.

Cancer is defined by diverse somatic and germline alterations that promote aberrant cell growth. Tumor genomic profiling to guide therapy is now part of standard management in several solid tumor t...

Establishment of aliving biobank : Improved guidance of precision cancer care with in vitro and in vivo cancer models

Precision oncology is aclinical approach aimed towards tailoring treatment strategies for patients based on the genetic profile of each patient's cancer. The integration of aliving biobank, consisting of patient-derived tumor organoids and PDXs, with next generation sequencing approaches and high-throughput drug screening help to guide clinical decision-making and clinical trial development. Tumor organoids derived from fresh tumor samples were used for in vitro and in vivo high-throughput drug testing. Over aperiod oftwo years we established 56 in vitro tumor organoids and 19 in vivo xenografts from 18different solid tumor types. Tumor morphology and molecular profiles show good concordance between the in vitro and in vivo models compared to their native tumor. High-throughput drug screening (up to 160 drugs) has been tested on eighttumor organoid lines. Sevenof them underwent an additional combination drug screen. We nominated several targeted small molecules and novel combinations that have been validated in corresponding xenograft models. This precision medicine approach outlines the integration of genomic data with drug screening from personalized preclinical cancer models to guide precision cancer care. It also fuels next generation research and has been implemented for clinical trial development.

Genetics of pancreatic cyst-cancer progression: standing on the shoulders of giants

Pancreatic cancer, despite years of study and some progress, presents with a grim prognosis in almost all cases. In the current review, we have discussed recent studies that have attempted to decipher the genetic makeup of pancreatic ductal adenocarcinoma and preneoplastic pancreatic cystic neoplasms. With the advent of high throughput sequencing, the genetic code of pancreatic cancer is beginning to unravel and this new-found information heralds an era of precision cancer care where treatment will be guided by the genetic code of the neoplasm. Results from these studies have pointed towards the complexity and heterogeneity of the pancreatic cancer genome, provided avenues to "tailor therapy" based as well as shed light on progression of preneoplastic pancreatic neoplasms into full blown invasive pancreatic ductal adenocarcinoma. While this progress has made us closer to the model of precision medicine, significant obstacles need to be overcome to use this new-found information to change the way we manage patients with pancreatic cancer.

The Use of Imaging in the Prediction and Assessment of Cancer Treatment Toxicity.

Multimodal imaging is commonly used in the management of patients with cancer. Imaging plays pivotal roles in the diagnosis, initial staging, treatment response assessment, restaging after treatment and the prognosis of many cancers. Indeed, it is difficult to imagine modern precision cancer care without the use of multimodal molecular imaging, which is advancing at a rapid pace with innovative developments in imaging sciences and an improved understanding of the complex biology of cancer. Cancer therapy often leads to undesirable toxicity, which can range from an asymptomatic subclinical state to severe end organ damage and even death. Imaging is helpful in the portrayal of the unwanted effects of cancer therapy and may assist with optimal clinical decision-making, clinical management, and overall improvements in the outcomes and quality of life for patients.

Cancer of the esophagus and esophagogastric junction-Major changes in the American Joint Committee on Cancer eighth edition cancer staging manual.

Answer questions and earn CME/CNE New to the eighth edition of the American Joint Committee on Cancer (AJCC) Cancer Staging Manual for epithelial cancers of the esophagus and esophagogastric junction are separate, temporally related cancer classifications: 1) before treatment decision (clinical); 2) after esophagectomy alone (pathologic); and 3) after preresection therapy followed by esophagectomy (postneoadjuvant pathologic). The addition of clinical and postneoadjuvant pathologic stage groupings was driven by a lack of correspondence of survival, and thus prognosis, between both clinical and postneoadjuvant pathologic cancer categories (facts about the cancer) and pathologic categories. This was revealed by a machine-learning analysis of 6-continent data from the Worldwide Esophageal Cancer Collaboration, with consensus of the AJCC Upper GI Expert Panel. Survival is markedly affected by histopathologic cell type (squamous cell carcinoma and adenocarcinoma) in clinically and pathologically staged patients, requiring separate stage grouping for each cell type. However, postneoadjuvant pathologic stage groups are identical. For the future, more refined and granular data are needed. This requires: 1) more accurate clinical staging; 2) innovative solutions to pathologic staging challenges in endoscopically resected cancers; 3) integration of genomics into staging; and 4) precision cancer care with targeted therapy. It is the responsibility of the oncology team to accurately determine and record registry data, which requires eliminating both common errors and those related to incompleteness and inconsistency. Despite the new complexity of eighth edition staging of cancers of the esophagus and esophagogastric junction, these key concepts and new directions will facilitate precision cancer care. CA Cancer J Clin 2017;67:304-317. © 2017 American Cancer Society.

Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine.

Precision medicine is an approach that takes into account the influence of individuals' genes, environment, and lifestyle exposures to tailor interventions. Here, we describe the development of a robust precision cancer care platform that integrates whole-exome sequencing with a living biobank that enables high-throughput drug screens on patient-derived tumor organoids. To date, 56 tumor-derived organoid cultures and 19 patient-derived xenograft (PDX) models have been established from the 769 patients enrolled in an Institutional Review Board-approved clinical trial. Because genomics alone was insufficient to identify therapeutic options for the majority of patients with advanced disease, we used high-throughput drug screening to discover effective treatment strategies. Analysis of tumor-derived cells from four cases, two uterine malignancies and two colon cancers, identified effective drugs and drug combinations that were subsequently validated using 3-D cultures and PDX models. This platform thereby promotes the discovery of novel therapeutic approaches that can be assessed in clinical trials and provides personalized therapeutic options for individual patients where standard clinical options have been exhausted.Significance: Integration of genomic data with drug screening from personalized in vitro and in vivo cancer models guides precision cancer care and fuels next-generation research. Cancer Discov; 7(5); 462-77. ©2017 AACR.See related commentary by Picco and Garnett, p. 456This article is highlighted in the In This Issue feature, p. 443.

8th edition AJCC/UICC staging of cancers of the esophagus and esophagogastric junction: application to clinical practice.

The 8th edition of the American Joint Committee on Cancer (AJCC) staging of epithelial cancers of the esophagus and esophagogastric junction (EGJ) presents separate classifications for clinical (cTNM), pathologic (pTNM), and postneoadjuvant (ypTNM) stage groups. Histopathologic cell type markedly affects survival of clinically and pathologically staged patients, requiring separate groupings for each cell type, but ypTNM groupings are identical for both cell types. Clinical categories, typically obtained by imaging with minimal histologic information, are limited by resolution of each method. Strengths and shortcomings of clinical staging methods should be recognized. Complementary cytology or histopathology findings may augment imaging and aid initial treatment decision-making. However, prognostication using clinical stage groups remains coarse and inaccurate compared with pTNM. Pathologic staging is losing its relevance for advanced-stage cancer as neoadjuvant therapy replaces esophagectomy alone. However, it remains relevant for early-stage cancers and as a staging and survival reference point. Although pathologic stage could facilitate decision-making, its use to direct postoperative adjuvant therapy awaits more effective treatment. Prognostication using pathologic stage groups is the most refined of all classifications. Postneoadjuvant staging (ypTNM) is introduced by the AJCC but not adopted by the Union for International Cancer Control (UICC). Drivers of this addition include absence of equivalent pathologic (pTNM) categories for categories peculiar to the postneoadjuvant state (ypT0N0-3M0 and ypTisN0-3M0), dissimilar stage group compositions, and markedly different survival profiles. Thus, prognostication is specific for patients undergoing neoadjuvant therapy. The role of ypTNM classification in additional treatment decision-making is currently limited. Precision cancer care advances are necessary for this information to be clinically useful.

'Omics Approaches in Breast Cancer Research and Clinical Practice.

Our understanding of the natural history of breast cancer has evolved alongside technologies to study its genomic, transcriptomic, proteomic, and metabolomics landscapes. These technologies have helped decipher multiple molecular pathways dysregulated in breast cancer. First-generation 'omics analyses considered each of these dimensions individually, but it is becoming increasingly clear that more holistic, integrative approaches are required to fully understand complex biological systems. The 'omics represent an exciting era of discovery in breast cancer research, although important issues need to be addressed to realize the clinical utility of these data through precision cancer care. How can the data be applied to predict response to molecular-targeted therapies? When should treatment decisions be based on tumor genetics rather than histology? And with the sudden explosion of "big data" from large 'omics consortia and new precision clinical trials, how do we now negotiate evidence-based pathways to clinical translation through this apparent sea of opportunity? The aim of this review is to provide a broad overview of 'omics technologies used in breast cancer research today, the current state-of-play in terms of applying this new knowledge in the clinic, and the practical and ethical issues that will be central to the public discussion on the future of precision cancer care.

Development and validation of a whole-exome sequencing test for simultaneous detection of point mutations, indels and copy-number alterations for precision cancer care.

We describe Exome Cancer Test v1.0 (EXaCT-1), the first New York State-Department of Health-approved whole-exome sequencing (WES)-based test for precision cancer care. EXaCT-1 uses HaloPlex (Agilent) target enrichment followed by next-generation sequencing (Illumina) of tumour and matched constitutional control DNA. We present a detailed clinical development and validation pipeline suitable for simultaneous detection of somatic point/indel mutations and copy-number alterations (CNAs). A computational framework for data analysis, reporting and sign-out is also presented. For the validation, we tested EXaCT-1 on 57 tumours covering five distinct clinically relevant mutations. Results demonstrated elevated and uniform coverage compatible with clinical testing as well as complete concordance in variant quality metrics between formalin-fixed paraffin embedded and fresh-frozen tumours. Extensive sensitivity studies identified limits of detection threshold for point/indel mutations and CNAs. Prospective analysis of 337 cancer cases revealed mutations in clinically relevant genes in 82% of tumours, demonstrating that EXaCT-1 is an accurate and sensitive method for identifying actionable mutations, with reasonable costs and time, greatly expanding its utility for advanced cancer care.