Cell-free Circulating Tumor DNA Variant Allele Frequency Associates with Survival in Metastatic Cancer.

PURPOSE: Physicians are expected to assess prognosis both for patient counseling and for determining suitability for clinical trials. Increasingly, cell-free circulating tumor DNA (cfDNA) sequencing is being performed for clinical decision making. We sought to determine whether variant allele frequency (VAF) in cfDNA is associated with prognosis. EXPERIMENTAL DESIGN: We performed a retrospective analysis of 298 patients with metastatic disease who underwent clinical comprehensive cfDNA analysis and assessed association between VAF and overall survival. RESULTS: cfDNA mutations were detected in 240 patients (80.5%). Median overall survival (OS) was 11.5 months. cfDNA mutation detection and number of nonsynonymous mutations (NSM) significantly differed between tumor types, being lowest in appendiceal cancer and highest in colon cancer. Having more than one NSM detected was associated with significantly worse OS (HR = 2.3; P < 0.0001). VAF was classified by quartiles, Q1 lowest, Q4 highest VAF. Higher VAF levels were associated with a significantly worse overall survival (VAF Q3 HR 2.3, P = 0.0069; VAF Q4 HR = 3.8, P < 0.0001) on univariate analysis. On multivariate analysis, VAF Q4, male sex, albumin level <3.5 g/dL, number of nonvisceral metastatic sites >0 and number of prior therapies >4 were independent predictors of worse OS. CONCLUSIONS: Higher levels of cfDNA VAF and a higher number of NSMs were associated with worse OS in patients with metastatic disease. Further study is needed to determine optimal VAF thresholds for clinical decision making and the utility of cfDNA VAF as a prognostic marker in different tumor types.

A Deep Learning Framework for Predicting Response to Therapy in Cancer.

A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep neural networks for prediction of drug response and assessed their performance on multiple clinical cohorts. We demonstrate that deep neural networks outperform the current state in machine learning frameworks. We provide a proof of concept for the use of deep neural network-based frameworks to aid precision oncology strategies.

Molecular Profiling of Hepatocellular Carcinoma Using Circulating Cell-Free DNA.

PURPOSE: Molecular profiling has been used to select patients for targeted therapy and determine prognosis. Noninvasive strategies are critical to hepatocellular carcinoma (HCC) given the challenge of obtaining liver tissue biopsies. EXPERIMENTAL DESIGN: We analyzed blood samples from 206 patients with HCC using comprehensive genomic testing (Guardant Health) of circulating tumor DNA (ctDNA). RESULTS: A total of 153/206 (74.3%) were men; median age, 62 years (range, 18-91 years). A total of 181/206 patients had ≥1 alteration. The total number of alterations was 680 (nonunique); median number of alterations/patient was three (range, 1-13); median mutant allele frequency (% cfDNA), 0.49% (range, 0.06%-55.03%). TP53 was the common altered gene [>120 alterations (non-unique)] followed by EGFR, MET, ARID1A, MYC, NF1, BRAF, and ERBB2 [20-38 alterations (nonunique)/gene]. Of the patients with alterations, 56.9% (103/181) had ≥1 actionable alterations, most commonly in MYC, EGFR, ERBB2, BRAF, CCNE1, MET, PIK3CA, ARID1A, CDK6, and KRAS. In these genes, amplifications occurred more frequently than mutations. Hepatitis B (HBV)-positive patients were more likely to have ERBB2 alterations, 35.7% (5/14) versus 8.8% HBV-negative (P = 0.04). CONCLUSIONS: This study represents the first large-scale analysis of blood-derived ctDNA in HCC in United States. The genomic distinction based on HCC risk factors and the high percentage of potentially actionable genomic alterations suggests potential clinical utility for this technology.

OCTANE: Oncology Clinical Trial Annotation Engine.

PURPOSE: Many targeted therapies are currently available only via clinical trials. Therefore, routine precision oncology using biomarker-based assignment to drug depends on matching patients to clinical trials. A comprehensive and up-to-date trial database is necessary for optimal patient-trial matching. METHODS: We describe processes for establishing and maintaining a clinical trial database, focusing on genomically informed trials. Furthermore, we present OCTANE (Oncology Clinical Trial Annotation Engine), an informatics framework supporting these processes in a scalable fashion. To illustrate how the framework can be applied at an institution, we describe how we implemented an instance of OCTANE at a large cancer center. OCTANE consists of three modules. The data aggregation module automates retrieval, aggregation, and update of trial information. The annotation module establishes the database schema, implements data integration necessary for automation, and provides an annotation interface. The update module monitors trial change logs, identifies critical change events, and alerts the annotators when manual intervention may be needed. RESULTS: Using OCTANE, we annotated 5,439 oncology clinical trials (4,438 genomically informed trials) that collectively were associated with 1,453 drugs, 779 genes, and 252 cancer types. To date, we have used the database to screen 4,220 patients for trial eligibility. We compared the update module with expert review, and the module achieved 98.5% accuracy, 0% false-negative rate, and 2.3% false-positive rate. CONCLUSION: OCTANE is a general informatics framework that can be helpful for establishing and maintaining a comprehensive database necessary for automating patient-trial matching, which facilitates the successful delivery of personalized cancer care on a routine basis. Several OCTANE components are publically available and may be useful to other precision oncology programs.

Use of a Targeted Exome Next-Generation Sequencing Panel Offers Therapeutic Opportunity and Clinical Benefit in a Subset of Patients With Advanced Cancers.

PURPOSE: Smaller hotspot-based next-generation sequencing (NGS) panels have emerged to support standard of care therapy for patients with cancer. When standard treatments fail, it is unknown whether additional testing using an expanded panel of genes provides any benefit. The purpose of this study was to determine if larger sequencing panels that capture additional actionable genes, coupled with decision support, translates into treatment with matched therapy after frontline therapy has failed. PATIENTS AND METHODS: A prospective protocol accrued 521 patients with a wide variety of refractory cancers. NGS testing using a 46- or 50-gene hotspot assay, then a 409-gene whole-exome assay, was sequentially performed in a Clinical Laboratory Improvement Amendments-certified clinical laboratory. A decision-support team annotated somatic alterations in clinically actionable genes for function and facilitated therapeutic matching. Survival and the impact of matched therapy use were determined by Kaplan-Meier estimate, log-rank test, and Cox proportional hazards regression. RESULTS: The larger NGS panel identified at least one alteration in an actionable gene not previously identified in the smaller sequencing panel in 214 (41%) of 521 of enrolled patients. After the application of decision support, 41% of the alterations in actionable genes were considered to affect the function of the gene and were deemed actionable. Forty patients (40 of 214 [19%]) were subsequently treated with matched therapy. Treatment with matched therapy was associated with significantly improved overall survival compared with treatment with nonmatched therapy (P = .017). CONCLUSION: Combining decision support with larger NGS panels that incorporate genes beyond those recommended in current treatment guidelines helped to identify patients who were eligible for matched therapy while improving overall treatment selection and survival. This survival benefit was restricted to a small subset of patients.

Identification of Actionable Genomic Alterations Using Circulating Cell-Free DNA.

PURPOSE: Cell-free DNA (cfDNA) next-generation sequencing is a noninvasive approach for genomic testing. We report the frequency of identifying alterations and their clinical actionability in patients with advanced/metastatic cancer. PATIENTS AND METHODS: Prospectively consented patients had cfDNA testing performed. Alterations were assessed for therapeutic implications. RESULTS: We enrolled 575 patients with 37 tumor types. Of these patients, 438 (76.2%) had at least one alteration detected, and 205 (35.7%) had one or more alterations of high potential for clinical action. In diseases with 10 or more patients enrolled, 50% or more had at least one alteration deemed of high potential for clinical action. Trials were identified in 80% of patients (286 of 357) with any alteration and in 92% of patients (188 of 205) with one or more alterations of high potential for clinical action of whom 57.6% (118 of 205) had 6 or more months of follow-up available. Of these patients, 10% (12 of 118) had received genomically matched therapy through enrollment in clinical trials (n = 8), off-label drug use (n = 3), or standard of care (n = 1). Although 88.6% of all patients had a performance status of 0 or 1 upon enrollment, the primary reason for not acting on alterations was poor performance status at next treatment change (28.1%; 27 of 96). CONCLUSION: cfDNA testing represents a readily accessible method for genomic testing and allows for detection of genomic alterations in most patients with advanced disease. Utility may be higher in patients interested in investigational therapeutics with adequate performance status. Additional study is needed to determine whether utility is enhanced by testing earlier in the treatment course.

Survival Outcomes by TP53 Mutation Status in Metastatic Breast Cancer.

PURPOSE: We sought to determine the significant genomic alterations in patients with metastatic breast cancer (MBC), and survival outcomes in common genotypes. PATIENTS AND METHODS: High-depth next generation sequencing was performed for 202 genes in tumor and normal DNA from 257 patients with MBC, including 165 patients with ER/PR+ HER2- (hormone receptor positive, HR+ positive), 32 patients with HER2+ and 60 patients with triple negative (ER/PR/HER2-) cancer. Kaplan Meier survival analysis was performed in our discovery set, in breast cancer patients analyzed in The Cancer Genome Atlas, and in a separate cohort of 98 patients with MBC who underwent clinical genomic testing. RESULTS: Significantly mutated genes (SMGs) varied by histology and tumor subtype, but TP53 was a SMG in all three subtypes. The most SMGs in HR+ patients included PIK3CA (32%), TP53 (29%), GATA3 (15%), CDH1 (8%), MAP3K1 (8%), PTEN (5%), TGFBR2 (4%), AKT1 (4%), and MAP2K4 (4%). TP53 mutations were associated with shorter recurrence-free survival (P=0.004), progression-free survival (P=0.00057) and overall survival (P=0.003). Further, TP53 status was prognostic among HR+ patients with PIK3CA mutations. TP53 mutations were also associated with poorer overall survival in the 442 HR+ breast cancer patients in the TCGA (P=0.042) and in an independent set of 96 HR+ MBC who underwent clinical sequencing (P=0.0004). CONCLUSIONS: SMGs differ by tumor subtype but TP53 is significantly mutated in all three breast cancer subtypes. TP53 mutations are associated with poor prognosis in HR+ breast cancer. TP53 mutations should be considered in the design and interpretation of precision oncology trials.

Targeted next generation sequencing of well-differentiated/dedifferentiated liposarcoma reveals novel gene amplifications and mutations.

Well-differentiated/dedifferentiated liposarcoma is a common soft tissue sarcoma with approximately 1500 new cases per year. Surgery is the mainstay of treatment but recurrences are frequent and systemic options are limited. 'Tumor genotyping' is becoming more common in clinical practice as it offers the hope of personalized targeted therapy. We wanted to evaluate the results and the clinical utility of available next-generation sequencing panels in WD/DD liposarcoma. Patients who had their tumor sequenced by either FoundationOne (n = 13) or the institutional T200/T200.1 panels (n = 7) were included in this study. Significant copy number alterations were identified, but mutations were infrequent. Out of the 27 mutations detected in 7 samples, 8 (CTNNB1, MECOM, ZNF536, EGFR, EML4, CSMD3, PBRM1, PPP1R3A) were identified as deleterious (on Condel, PolyPhen and SIFT) and a truncating mutation was found in NF2. Of these, EGFR and NF2 are potential driver mutations and have not been reported previously in liposarcoma. MDM2 and CDK4 amplification was universally present in all the tested samples and multiple other recurrent genes with high amplification or high deletion were detected. Many of these targets are potentially actionable. Eight patients went on to receive an MDM2 inhibitor with a median time to progression of 23 months (95% CI: 10-83 months).

Physician interpretation of genomic test results and treatment selection.

BACKGROUND: Genomic testing is increasingly performed in oncology, but concerns remain regarding the clinician's ability to interpret results. In the current study, the authors sought to determine the agreement between physicians and genomic annotators from the Precision Oncology Decision Support (PODS) team at The University of Texas MD Anderson Cancer Center in Houston regarding actionability and the clinical use of test results. METHODS: On a prospective protocol, patients underwent clinical genomic testing for hotspot mutations in 46 or 50 genes. Six months after sequencing, physicians received questionnaires for patients who demonstrated a variant in an actionable gene, investigating their perceptions regarding the actionability of alterations and clinical use of these findings. Genomic annotators independently classified these variants as actionable, potentially actionable, unknown, or not actionable. RESULTS: Physicians completed 250 of 288 questionnaires (87% response rate). Physicians considered 168 of 250 patients (67%) as having an actionable alteration; of these, 165 patients (98%) were considered to have an actionable alteration by the PODS team and 3 were of unknown significance. Physicians were aware of genotype-matched therapy available for 119 patients (71%) and 48 of these 119 patients (40%) received matched therapy. Approximately 46% of patients in whom physicians regarded alterations as not actionable (36 of 79 patients) were classified as having an actionable/potentially actionable mutation by the PODS team. However, many of these were only theoretically actionable due to limited trials and/or therapies (eg, KRAS). CONCLUSIONS: Physicians are aware of recurrent mutations in actionable genes on "hotspot" panels. As larger genomic panels are used, there may be a growing need for annotation of actionability. Decision support to increase awareness of genomically relevant trials and novel treatment options for recurrent mutations (eg, KRAS) also are needed. Cancer 2018;124:966-72. © 2017 American Cancer Society.

Characteristics of percutaneous core biopsies adequate for next generation genomic sequencing.

PURPOSE: Determine the characteristics of percutaneous core biopsies that are adequate for a next generation sequencing (NGS) genomic panel. MATERIALS AND METHODS: All patients undergoing percutaneous core biopsies in interventional radiology (IR) with samples evaluated for a 46-gene NGS panel during 1-year were included in this retrospective study. Patient and procedure variables were collected. An imaging-based likelihood of adequacy score incorporating targeting and sampling factors was assigned to each biopsied lesion. Univariate and multivariate logistic regression was performed. RESULTS: 153 patients were included (58.2% female, average age 59.5 years). The most common malignancy was lung cancer (40.5%), most common biopsied site was lung (36%), and average size of biopsied lesions was 3.8 cm (+/- 2.7). Adequacy for NGS was 69.9%. Univariate analysis showed higher likelihood of adequacy score (p = 0.004), primary malignancy type (p = 0.03), and absence of prior systemic therapy (p = 0.018) were associated with adequacy for NGS. Multivariate analysis showed higher adequacy for lesions with likelihood of adequacy scored 3 (high) versus lesions scored 1 (low) (OR, 7.82; p = 0.002). Melanoma lesions had higher adequacy for NGS versus breast cancer lesions (OR 9.5; p = 0.01). Absence of prior systemic therapy (OR, 6.1; p = 0.02) and systemic therapy 3 months before biopsy yielded greater adequacy for NGS. Lesions <3 cm had greater adequacy for NGS than larger lesions (OR 2.72, p = 0.02). CONCLUSION: As targeted therapy becomes standard for more cancers, percutaneous biopsy specimens adequate for NGS genomic testing will be needed. An imaging-based likelihood of adequacy score assigned by IR physicians and other pre-procedure variables can help predict the likelihood of biopsy adequacy for NGS.

Precision oncology: neither a silver bullet nor a dream.

Precision oncology is not an illusion, nor is it the magic bullet that will eradicate all cancers. Precision oncology is simply another weapon in our growing armament against cancer. Rather than honing in on the failures of a relatively young field, one should advocate for integrating its successes into widespread clinical practice, especially for indications, such as: ABL, ALK, BRAF, BRCA1, BRCA2, EGFR, KIT, KRAS, PDGFRA, PDGFRB, ROS1, BCR-ABL, FLT3 and ROS1, where aberrations have been shown to alter responses to US FDA approved drugs - that is, level 1 data. Moreover, to truly assess the promise of precision oncology, we must first begin by defining our expectations for this field. Importantly, we must recognize that the conception of precision oncology arose as an antithesis of the 'one-size fits all' cancer therapeutics approach. Consequently, tools used for evaluating these conventional, large-scale trials, are not directly transferable for assessing nonconventional, smaller-scale trials needed for evaluating precision oncology. Hence, a thorough vetting of precision oncology as another tool of the trade, must first begin by reassessing our expectations for this field, as well as current clinical trial designs and end point measurements. Importantly, we must recognize that most targeted therapy approaches are in their infancy, with only monotherapy approaches being assessed and combination therapies likely being necessary to fulfill the promise of precision oncology.

A feasibility study of returning clinically actionable somatic genomic alterations identified in a research laboratory.

PURPOSE: Molecular profiling performed in the research setting usually does not benefit the patients that donate their tissues. Through a prospective protocol, we sought to determine the feasibility and utility of performing broad genomic testing in the research laboratory for discovery, and the utility of giving treating physicians access to research data, with the option of validating actionable alterations in the CLIA environment. EXPERIMENTAL DESIGN: 1200 patients with advanced cancer underwent characterization of their tumors with high depth hybrid capture sequencing of 201 genes in the research setting. Tumors were also tested in the CLIA laboratory, with a standardized hotspot mutation analysis on an 11, 46 or 50 gene platform. RESULTS: 527 patients (44%) had at least one likely somatic mutation detected in an actionable gene using hotspot testing. With the 201 gene panel, 945 patients (79%) had at least one alteration in a potentially actionable gene that was undetected with the more limited CLIA panel testing. Sixty-four genomic alterations identified on the research panel were subsequently tested using an orthogonal CLIA assay. Of 16 mutations tested in the CLIA environment, 12 (75%) were confirmed. Twenty-five (52%) of 48 copy number alterations were confirmed. Nine (26.5%) of 34 patients with confirmed results received genotype-matched therapy. Seven of these patients were enrolled onto genotype-matched targeted therapy trials. CONCLUSION: Expanded cancer gene sequencing identifies more actionable genomic alterations. The option of CLIA validating research results can provide alternative targets for personalized cancer therapy.

Targeting TRK family proteins in cancer.

The tropomyosin receptor kinase (TRK) family includes TRKA, TRKB, and TRKC proteins, which are encoded by NTRK1, NTRK2 and NTRK3 genes, respectively. Binding of neurotrophins to TRK proteins induces receptor dimerization, phosphorylation, and activation of the downstream signaling cascades via PI3K, RAS/MAPK/ERK, and PLC-gamma. TRK pathway aberrations, including gene fusions, protein overexpression, and single nucleotide alterations, have been implicated in the pathogenesis of many cancer types, with NTRK gene fusions being the most well validated oncogenic events to date. Although the NTRK gene fusions are infrequent in most cancer types, certain rare tumor types are predominately driven by these events. Conversely, in more common histologies, such as lung and colorectal cancers, prevalence of the NTRK fusions is well below 5%. Selective inhibition of TRK signaling may therefore be beneficial among patients whose tumors vary in histologies, but share underlying oncogenic NTRK gene alterations. Currently, several TRK-targeting compounds are in clinical development. The ongoing Phase 2 trials with entrectinib and LOXO-101, two of the leading TRK inhibitors, are designed as 'basket trials', inclusive of patients whose tumors harbor NTRK gene fusions, independent of histology. Additional Phase 1 studies of other TRK inhibitors, including MGCD516, PLX7486, DS-6051b, and TSR-011, are underway. Interim data examining NTRK-rearranged tumors treated with entrectinib or LOXO-101 demonstrate encouraging activity, with patients achieving rapid and durable responses. Consequently, both drugs have achieved orphan designation from regulatory agencies, and efforts are underway to further expedite their development.

Clinical Use of Precision Oncology Decision Support.

PURPOSE: Precision oncology is hindered by the lack of decision support for determining the functional and therapeutic significance of genomic alterations in tumors and relevant clinically available options. To bridge this knowledge gap, we established a Precision Oncology Decision Support (PODS) team that provides annotations at the alteration-level and subsequently determined if clinical decision-making was influenced. METHODS: Genomic alterations were annotated to determine actionability based on a variant's known or potential functional and/or therapeutic significance. The medical records of a subset of patients annotated in 2015 were manually reviewed to assess trial enrollment. A web-based survey was implemented to capture the reasons why genotype-matched therapies were not pursued. RESULTS: PODS processed 1,669 requests for annotation of 4,084 alterations (2,254 unique) across 49 tumor types for 1,197 patients. 2,444 annotations for 669 patients included an actionable variant call: 32.5% actionable, 9.4% potentially, 29.7% unknown, 28.4% non-actionable. 66% of patients had at least one actionable/potentially actionable alteration. 20.6% (110/535) patients annotated enrolled on a genotype-matched trial. Trial enrolment was significantly higher for patients with actionable/potentially actionable alterations (92/333, 27.6%) than those with unknown (16/136, 11.8%) and non-actionable (2/66, 3%) alterations (p=0.00004). Actionable alterations in PTEN, PIK3CA, and ERBB2 most frequently led to enrollment on genotype-matched trials. Clinicians cited a variety of reasons why patients with actionable alterations did not enroll on trials. CONCLUSION: Over half of alterations annotated were of unknown significance or non-actionable. Physicians were more likely to enroll a patient on a genotype-matched trial when an annotation supported actionability. Future studies are needed to demonstrate the impact of decision support on trial enrollment and oncologic outcomes.

Next-Generation Sequencing and Result Interpretation in Clinical Oncology: Challenges of Personalized Cancer Therapy.

The tools of next-generation sequencing (NGS) technology, such as targeted sequencing of candidate cancer genes and whole-exome and -genome sequencing, coupled with encouraging clinical results based on the use of targeted therapeutics and biomarker-guided clinical trials, are fueling further technological advancements of NGS technology. However, NGS data interpretation is associated with challenges that must be overcome to promote the techniques' effective integration into clinical oncology practice. Specifically, sequencing of a patient's tumor often yields 30-65 somatic variants, but most of these variants are "passenger" mutations that are phenotypically neutral and thus not targetable. Therefore, NGS data must be interpreted by multidisciplinary decision-support teams to determine mutation actionability and identify potential "drivers," so that the treating physician can prioritize what clinical decisions can be pursued in order to provide cancer therapy that is personalized to the patient and his or her unique genome.

Healthy choices through family history: a community approach to family history awareness.

BACKGROUND: The importance of family health history data in health care is widely acknowledged. Few individuals report having collected this information from their own family. METHODS: This project implemented a community-based approach to design and pilot a linguistically and culturally appropriate family health history collection toolkit for two minority populations in Harrisburg, Pa. RESULTS: The toolkit relied on oral traditions and family stories as a way to successfully introduce genetics education and family health history to these populations. Participants not only found the tool engaging and culturally appropriate, they were also able to obtain information that they were likely to share with their physician. CONCLUSION: While limited in scope, this project provides a model to other communities for the design, pilot testing, and implementation of a community-based public health initiative regarding family health histories.

Essay contest reveals misconceptions of high school students in genetics content.

National educational organizations have called upon scientists to become involved in K-12 education reform. From sporadic interaction with students to more sustained partnerships with teachers, the engagement of scientists takes many forms. In this case, scientists from the American Society of Human Genetics (ASHG), the Genetics Society of America (GSA), and the National Society of Genetic Counselors (NSGC) have partnered to organize an essay contest for high school students as part of the activities surrounding National DNA Day. We describe a systematic analysis of 500 of 2443 total essays submitted in response to this contest over 2 years. Our analysis reveals the nature of student misconceptions in genetics, the possible sources of these misconceptions, and potential ways to galvanize genetics education.