Genome-wide repeat landscapes in cancer and cell-free DNA

Genetic changes in repetitive sequences are a hallmark of cancer and other diseases, but characterizing these has been challenging using standard sequencing approaches. We developed a de novo kmer finding approach, called ARTEMIS (Analysis of RepeaT EleMents in dISease), to identify repeat elements from whole-genome sequencing. Using this method, we analyzed 1.2 billion kmers in 2837 tissue and plasma samples from 1975 patients, including those with lung, breast, colorectal, ovarian, liver, gastric, head and neck, bladder, cervical, thyroid, or prostate cancer. We identified tumor-specific changes in these patients in 1280 repeat element types from the LINE, SINE, LTR, transposable element, and human satellite families. These included changes to known repeats and 820 elements that were not previously known to be altered in human cancer. Repeat elements were enriched in regions of driver genes, and their representation was altered by structural changes and epigenetic states. Machine learning analyses of genome-wide repeat landscapes and fragmentation profiles in cfDNA detected patients with early-stage lung or liver cancer in cross-validated and externally validated cohorts. In addition, these repeat landscapes could be used to noninvasively identify the tissue of origin of tumors. These analyses reveal widespread changes in repeat landscapes of human cancers and provide an approach for their detection and characterization that could benefit early detection and disease monitoring of patients with cancer.

Detection and characterization of lung cancer using cell-free DNA fragmentomes

Non-invasive approaches for cell-free DNA (cfDNA) assessment provide an opportunity for cancer detection and intervention. Here, we use a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation in a prospective study of 365 individuals at risk for lung cancer. We validate the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 lung cancer patients. Combining fragmentation features, clinical risk factors, and CEA levels, followed by CT imaging, detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites distinguished individuals with small cell lung cancer from those with non-small cell lung cancer with high accuracy (AUC = 0.98). A higher fragmentation score represented an independent prognostic indicator of survival. This approach provides a facile avenue for non-invasive detection of lung cancer.

DNA from tumour cells can be detected in the blood of cancer patients. Here, the authors show that cell free DNA fragmentation patterns can identify lung cancer patients and when this information is further interrogated it can be used to predict lung cancer histological subtype.

Dynamics of Tumor and Immune Responses during Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

Despite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients (N = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels. Patients with initial response followed by acquired resistance to therapy had an initial drop followed by recrudescence in ctDNA levels. Patients without a molecular response had shorter progression-free and overall survival compared with molecular responders [5.2 vs. 14.5 and 8.4 vs. 18.7 months; HR 5.36; 95% confidence interval (CI), 1.57-18.35; P = 0.007 and HR 6.91; 95% CI, 1.37-34.97; P = 0.02, respectively], which was detected on average 8.7 weeks earlier and was more predictive of clinical benefit than CT imaging. Expansion of T cells, measured through increases of T-cell receptor productive frequencies, mirrored ctDNA reduction in response to therapy. We validated this approach in an independent cohort of patients with early-stage non-small cell lung cancer (N = 14), where the therapeutic effect was measured by pathologic assessment of residual tumor after anti-PD1 therapy. Consistent with our initial findings, early ctDNA dynamics predicted pathologic response to immune checkpoint blockade. These analyses provide an approach for rapid determination of therapeutic outcomes for patients treated with immune checkpoint inhibitors and have important implications for the development of personalized immune targeted strategies.Significance: Rapid and sensitive detection of circulating tumor DNA dynamic changes and T-cell expansion can be used to guide immune targeted therapy for patients with lung cancer.See related commentary by Zou and Meyerson, p. 1038.

Abstract 3668: ctDNA and TCR dynamics predict response toimmune checkpoint blockade in non-small cell lung cancer

The dynamic nature of the cancer-immune system crosstalk has rendered single biomarker approaches insufficient to predict outcome from immune-targeted agents. These therapies also pose a challenge to radiographic response assessments that may underestimate the therapeutic benefit. There is therefore an urgent clinical need to develop molecular assays of response and resistance.In order to capture the dynamic nature of the anti-tumor immune response under checkpoint blockade, we devised an integrative non-invasive approach that captures the evolving neoantigen landscape and the associated T-cell receptor (TCR) repertoire. We employed whole exome sequencing to determine the genomic landscape of tumors and identify tumor-derived alterations in subsequent analyses of circulating cell-free tumor DNA (ctDNA), for 14 patients with metastatic NSCLC treated with immune checkpoint blockade. Liquid biopsies were obtained prior to treatment, at week 4-6 and at additional timepoints until disease progression. We used the ultrasensitive targeted error correction sequencing approach to analyze 58 cancer driver genes in the circulation of these patients and assessed the value of longitudinal ctDNA monitoring as a surrogate for response. In parallel, we evaluated dynamics changes in the TCR repertoire by TCR next generation sequencing of serially collected peripheral T cells and tumor infiltrating lymphocytes for each patient. Radiographic response assessments were performed using the RECIST 1.1 criteria. These analyses revealed that ctDNA dynamics predict outcome significantly earlier than imaging. Patients that responded to therapy had a significant drop in ctDNA early during the treatment course whereas non-responders had either limited changes or significant increase in ctDNA. For patients with acquired resistance, ctDNA kinetics revealed clearing of ctDNA at the time of response followed by a new peak at the time of progression. ctDNA detection early during the treatment course was a significant prognostic factor for progression-free and overall survival (log rank p=.004 and .002 respectively) and ctDNA elimination was superior to tumor mutation burden as a predictor of response to therapy. In parallel, we identified changes in the TCR repertoire that are predictive of outcome: peripheral T cell expansion of a subset of intra-tumoral clones was noted at the time of response whereas there was no evidence of T cell expansion in non-responders. Peripheral T cell expansion of a subset of intra-tumoral clones was noted to peak at the time of response and decrease to baseline levels at the time of resistance for patients with acquired resistance. Our findings suggest that a dynamic assay able to capture the tumor-immune system equilibrium would be superior to conventional analyses of static time points. Such an integrated approach would be highly relevant to tailored cancer immunotherapy strategies.

Citation Format: Valsamo Anagnostou, Patrick Forde, Jarushka Naidoo, Kristen Marrone, Vilmos Adleff, James White, Jillian Phallen, Alessandro Leal, Carolyn Hruban, Ashok Sivakumar, Franco Verde, Rachel Karchin, Julie Brahmer, Victor Velculescu. ctDNA and TCR dynamics predict response toimmune checkpoint blockade in non-small cell lung cancer [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 3668.

Direct detection of early-stage cancers using circulating tumor DNA

Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer.

Abstract LB-246: Detection of circulating tumor DNA in early stage cancers

Early detection is a major goal for reducing mortality of human cancer. However, non-invasive detection of early stage tumors has remained a challenge. We have developed an approach called Targeted Error Correction Sequencing (TEC-Seq) for ultra-sensitive analyses of circulating cell-free tumor DNA (ctDNA). This methodology involves in-solution targeted capture of multiple regions of the genome and deep sequencing (~30,000x) of cell-free DNA fragments. Laboratory and bioinformatic methods were optimized to enrich for rare ctDNA molecules and to reduce potential amplification, sequencing, and contamination errors. We have used this approach to examine 58 cancer related genes, and demonstrated a limit of detection of mutant to wild-type DNA of 0.05% and a specificity >99.999% across targeted regions of interest. We applied this method to analyze plasma from healthy individuals as well as over 200 individuals with breast, lung, colorectal and ovarian cancers. Analysis of plasma from 44 healthy individuals revealed no tumor-related somatic mutations and identified alterations in genes related to myelodysplasia in a subset of cases. Among patients with cancer, we detected measurable ctDNA in 56%, 71%, 57%, and 56% of patients with early stage (I and II) breast, colorectal, lung and ovarian cancer. Over three quarters of patients with late stage (III and IV) disease had detectable ctDNA among all cases analyzed. Analyses of mutations in the circulation revealed a high concordance with alterations in the independently analyzed tumors of these patients. These analyses provide a widely applicable, ultra-sensitive, and non-invasive method for detection of ctDNA, and have important implications for detection of early stage disease and management of patients with cancer.

Citation Format: Jillian A. Phallen, Mark Sausen, Vilmos Adleff, Alessandro Leal, Jacob Fiksel, Carolyn Hruban, Savannah Speir, Eniko Papp, Valsamo Anagnostou, Mai-Britt W. Orntoft, Thomas Reinert, Brian D. Woodward, Derek Murphy, Sonya Parpart-Li, David Riley, Monica Nesselbush, Naomi Sengamalay, Andrew Georgiadis, Rob Scharpf, Qing K. Li, Sian Jones, Samuel Angiuoli, Joost Huiskens, Cornelis Punt, Nicole van Grieken, Remond Fijneman, Gerrit Meijer, Hatim Husain, Luis Diaz, Torben Ørntoft, Hans J. Nielsen, Claus L. Anderson, Victor E. Velculescu. Detection of circulating tumor DNA in early stage 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 LB-246. doi:10.1158/1538-7445.AM2017-LB-246

Evolution of Neoantigen Landscape during Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

Immune checkpoint inhibitors have shown significant therapeutic responses against tumors containing increased mutation-associated neoantigen load. We have examined the evolving landscape of tumor neoantigens during the emergence of acquired resistance in patients with non-small cell lung cancer after initial response to immune checkpoint blockade with anti-PD-1 or anti-PD-1/anti-CTLA-4 antibodies. Analyses of matched pretreatment and resistant tumors identified genomic changes resulting in loss of 7 to 18 putative mutation-associated neoantigens in resistant clones. Peptides generated from the eliminated neoantigens elicited clonal T-cell expansion in autologous T-cell cultures, suggesting that they generated functional immune responses. Neoantigen loss occurred through elimination of tumor subclones or through deletion of chromosomal regions containing truncal alterations, and was associated with changes in T-cell receptor clonality. These analyses provide insight into the dynamics of mutational landscapes during immune checkpoint blockade and have implications for the development of immune therapies that target tumor neoantigens.Significance: Acquired resistance to immune checkpoint therapy is being recognized more commonly. This work demonstrates for the first time that acquired resistance to immune checkpoint blockade can arise in association with the evolving landscape of mutations, some of which encode tumor neoantigens recognizable by T cells. These observations imply that widening the breadth of neoantigen reactivity may mitigate the development of acquired resistance. Cancer Discov; 7(3); 264-76. ©2017 AACR.See related commentary by Yang, p. 250This article is highlighted in the In This Issue feature, p. 235.