Analytical validation of NeXT Personal®, an ultra-sensitive personalized circulating tumor DNA assay.

We describe the analytical validation of NeXT Personal®, an ultra-sensitive, tumor-informed circulating tumor DNA (ctDNA) assay for detecting residual disease, monitoring therapy response, and detecting recurrence in patients diagnosed with solid tumor cancers. NeXT Personal uses whole genome sequencing of tumor and matched normal samples combined with advanced analytics to accurately identify up to ~1,800 somatic variants specific to the patient's tumor. A personalized panel is created, targeting these variants and then used to sequence cell-free DNA extracted from patient plasma samples for ultra-sensitive detection of ctDNA. The NeXT Personal analytical validation is based on panels designed from tumor and matched normal samples from two cell lines, and from 123 patients across nine cancer types. Analytical measurements demonstrated a detection threshold of 1.67 parts per million (PPM) with a limit of detection at 95% (LOD95) of 3.45 PPM. NeXT Personal showed linearity over a range of 0.8 to 300,000 PPM (Pearson correlation coefficient = 0.9998). Precision varied from a coefficient of variation of 12.8% to 3.6% over a range of 25 to 25,000 PPM. The assay targets 99.9% specificity, with this validation study measuring 100% specificity and in silico methods giving us a confidence interval of 99.92 to 100%. In summary, this study demonstrates NeXT Personal as an ultra-sensitive, highly quantitative and robust ctDNA assay that can be used to detect residual disease, monitor treatment response, and detect recurrence in patients.

Sotigalimab and/or nivolumab with chemotherapy in first-line metastatic pancreatic cancer: clinical and immunologic analyses from the randomized phase 2 PRINCE trial.

Chemotherapy combined with immunotherapy has improved the treatment of certain solid tumors, but effective regimens remain elusive for pancreatic ductal adenocarcinoma (PDAC). We conducted a randomized phase 2 trial evaluating the efficacy of nivolumab (nivo; anti-PD-1) and/or sotigalimab (sotiga; CD40 agonistic antibody) with gemcitabine/nab-paclitaxel (chemotherapy) in patients with first-line metastatic PDAC ( NCT03214250 ). In 105 patients analyzed for efficacy, the primary endpoint of 1-year overall survival (OS) was met for nivo/chemo (57.7%, P = 0.006 compared to historical 1-year OS of 35%, n = 34) but was not met for sotiga/chemo (48.1%, P = 0.062, n = 36) or sotiga/nivo/chemo (41.3%, P = 0.223, n = 35). Secondary endpoints were progression-free survival, objective response rate, disease control rate, duration of response and safety. Treatment-related adverse event rates were similar across arms. Multi-omic circulating and tumor biomarker analyses identified distinct immune signatures associated with survival for nivo/chemo and sotiga/chemo. Survival after nivo/chemo correlated with a less suppressive tumor microenvironment and higher numbers of activated, antigen-experienced circulating T cells at baseline. Survival after sotiga/chemo correlated with greater intratumoral CD4 T cell infiltration and circulating differentiated CD4 T cells and antigen-presenting cells. A patient subset benefitting from sotiga/nivo/chemo was not identified. Collectively, these analyses suggest potential treatment-specific correlates of efficacy and may enable biomarker-selected patient populations in subsequent PDAC chemoimmunotherapy trials.

A machine learning algorithm with subclonal sensitivity reveals widespread pan-cancer human leukocyte antigen loss of heterozygosity.

Human leukocyte antigen loss of heterozygosity (HLA LOH) allows cancer cells to escape immune recognition by deleting HLA alleles, causing the suppressed presentation of tumor neoantigens. Despite its importance in immunotherapy response, few methods exist to detect HLA LOH, and their accuracy is not well understood. Here, we develop DASH (Deletion of Allele-Specific HLAs), a machine learning-based algorithm to detect HLA LOH from paired tumor-normal sequencing data. With cell line mixtures, we demonstrate increased sensitivity compared to previously published tools. Moreover, our patient-specific digital PCR validation approach provides a sensitive, robust orthogonal approach that could be used for clinical validation. Using DASH on 610 patients across 15 tumor types, we find that 18% of patients have HLA LOH. Moreover, we show inflated HLA LOH rates compared to genome-wide LOH and correlations between CD274 (encodes PD-L1) expression and microsatellite instability status, suggesting the HLA LOH is a key immune resistance strategy.

Ipilimumab alone or in combination with nivolumab in patients with advanced melanoma who have progressed or relapsed on PD-1 blockade: clinical outcomes and translational biomarker analyses.

BACKGROUND: There are no validated biomarkers that can aid clinicians in selecting who would best benefit from anticytotoxic T lymphocyte-associated antigen 4 monotherapy versus combination checkpoint blockade in patients with advanced melanoma who have progressive disease after programmed death 1 (PD-1) blockade. METHODS: We conducted a randomized multicenter phase II trial in patients with advanced melanoma. Patients were randomly assigned to receive either 1 mg/kg of nivolumab plus 3 mg/kg of ipilimumab or 3 mg/kg of ipilimumab every 3 weeks for up to four doses. Patients were stratified by histological subtype and prior response to PD-1 therapy. The primary clinical objective was overall response rate by week 18. Translational biomarker analyses were conducted in patients with blood and tissue samples. RESULTS: Objective responses were seen in 5 of 9 patients in the ipilimumab arm and 2 of 10 patients in the ipilimumab+nivolumab arm; disease control rates (DCRs) (66.7% vs 60.0%) and rates of grade 3-4 adverse events (56% vs 50%) were comparable between arms. In a pooled analysis, patients with clinical benefit (CB), defined as Response Evaluation Criteria in Solid Tumors response or progression-free for 6 months, showed increased circulating CD4+ T cells with higher polyfunctionality and interferon gamma production following treatment. Tumor profiling revealed enrichment of NRAS mutations and activation of transcriptional programs associated with innate and adaptive immunity in patients with CB. CONCLUSIONS: In patients with advanced melanoma that previously progressed on PD-1 blockade, objective responses were seen in both arms, with comparable DCRs. Findings from biomarker analyses provided hypothesis-generating signals for validation in future studies of larger patient cohorts. TRIAL REGISTRATION NUMBER: NCT02731729.

CD40 agonistic monoclonal antibody APX005M (sotigalimab) and chemotherapy, with or without nivolumab, for the treatment of metastatic pancreatic adenocarcinoma: an open-label, multicentre, phase 1b study.

BACKGROUND: Standard chemotherapy remains inadequate in metastatic pancreatic adenocarcinoma. Combining an agonistic CD40 monoclonal antibody with chemotherapy induces T-cell-dependent tumour regression in mice and improves survival. In this study, we aimed to evaluate the safety of combining APX005M (sotigalimab) with gemcitabine plus nab-paclitaxel, with and without nivolumab, in patients with pancreatic adenocarcinoma to establish the recommended phase 2 dose. METHODS: This non-randomised, open-label, multicentre, four-cohort, phase 1b study was done at seven academic hospitals in the USA. Eligible patients were adults aged 18 years and older with untreated metastatic pancreatic adenocarcinoma, Eastern Cooperative Oncology Group performance status score of 0-1, and measurable disease by Response Evaluation Criteria in Solid Tumors version 1.1. All patients were treated with 1000 mg/m2 intravenous gemcitabine and 125 mg/m2 intravenous nab-paclitaxel. Patients received 0·1 mg/kg intravenous APX005M in cohorts B1 and C1 and 0·3 mg/kg in cohorts B2 and C2. In cohorts C1 and C2, patients also received 240 mg intravenous nivolumab. Primary endpoints comprised incidence of adverse events in all patients who received at least one dose of any study drug, incidence of dose-limiting toxicities (DLTs) in all patients who had a DLT or received at least two doses of gemcitabine plus nab-paclitaxel and one dose of APX005M during cycle 1, and establishing the recommended phase 2 dose of intravenous APX005M. Objective response rate in the DLT-evaluable population was a key secondary endpoint. This trial (PRINCE, PICI0002) is registered with ClinicalTrials.gov, NCT03214250 and is ongoing. FINDINGS: Between Aug 22, 2017, and July 10, 2018, of 42 patients screened, 30 patients were enrolled and received at least one dose of any study drug; 24 were DLT-evaluable with median follow-up 17·8 months (IQR 16·0-19·4; cohort B1 22·0 months [21·4-22·7], cohort B2 18·2 months [17·0-18·9], cohort C1 17·9 months [14·3-19·7], cohort C2 15·9 months [12·7-16·1]). Two DLTs, both febrile neutropenia, were observed, occurring in one patient each for cohorts B2 (grade 3) and C1 (grade 4). The most common grade 3-4 treatment-related adverse events were lymphocyte count decreased (20 [67%]; five in B1, seven in B2, four in C1, four in C2), anaemia (11 [37%]; two in B1, four in B2, four in C1, one in C2), and neutrophil count decreased (nine [30%]; three in B1, three in B2, one in C1, two in C2). 14 (47%) of 30 patients (four each in B1, B2, C1; two in C2) had a treatment-related serious adverse event. The most common serious adverse event was pyrexia (six [20%] of 30; one in B2, three in C1, two in C2). There were two chemotherapy-related deaths due to adverse events: one sepsis in B1 and one septic shock in C1. The recommended phase 2 dose of APX005M was 0·3 mg/kg. Responses were observed in 14 (58%) of 24 DLT-evaluable patients (four each in B1, C1, C2; two in B2). INTERPRETATION: APX005M and gemcitabine plus nab-paclitaxel, with or without nivolumab, is tolerable in metastatic pancreatic adenocarcinoma and shows clinical activity. If confirmed in later phase trials, this treatment regimen could replace chemotherapy-only standard of care in this population. FUNDING: Parker Institute for Cancer Immunotherapy, Cancer Research Institute, and Bristol Myers Squibb.

Transcriptome sequencing in Sezary syndrome identifies Sezary cell and mycosis fungoides-associated lncRNAs and novel transcripts.

Sézary syndrome (SS) is an aggressive cutaneous T-cell lymphoma (CTCL) of unknown etiology in which malignant cells circulate in the peripheral blood. To identify viral elements, gene fusions, and gene expression patterns associated with this lymphoma, flow cytometry was used to obtain matched pure populations of malignant Sézary cells (SCs) versus nonmalignant CD4(+) T cells from 3 patients for whole transcriptome, paired-end sequencing with an average depth of 112 million reads per sample. Pathway analysis of differentially expressed genes identified mis-regulation of PI3K/Akt, TGFß, and NF-κB pathways as well as T-cell receptor signaling. Bioinformatic analysis did not detect either nonhuman transcripts to support a viral etiology of SS or recurrently expressed gene fusions, but it did identify 21 SC-associated annotated long noncoding RNAs (lncRNAs). Transcriptome assembly by multiple algorithms identified 13 differentially expressed unannotated transcripts termed Sézary cell-associated transcripts (SeCATs) that include 12 predicted lncRNAs and a novel transcript with coding potential. High-throughput sequencing targeting the 3' end of polyadenylated transcripts in archived tumors from 24 additional patients with tumor-stage CTCL confirmed the differential expression of SC-associated lncRNAs and SeCATs in CTCL. Our findings characterize the SS transcriptome and support recent reports that implicate lncRNA dysregulation in human malignancies.

A network-based analysis of systemic inflammation in humans.

Oligonucleotide and complementary DNA microarrays are being used to subclassify histologically similar tumours, monitor disease progress, and individualize treatment regimens. However, extracting new biological insight from high-throughput genomic studies of human diseases is a challenge, limited by difficulties in recognizing and evaluating relevant biological processes from huge quantities of experimental data. Here we present a structured network knowledge-base approach to analyse genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes. This approach was used to analyse changes in blood leukocyte gene expression patterns in human subjects receiving an inflammatory stimulus (bacterial endotoxin). We explore the known genome-wide interaction network to identify significant functional modules perturbed in response to this stimulus. Our analysis reveals that the human blood leukocyte response to acute systemic inflammation includes the transient dysregulation of leukocyte bioenergetics and modulation of translational machinery. These findings provide insight into the regulation of global leukocyte activities as they relate to innate immune system tolerance and increased susceptibility to infection in humans.

Computational knowledge integration in biopharmaceutical research.

An initiative to increase biopharmaceutical research productivity by capturing, sharing and computationally integrating proprietary scientific discoveries with public knowledge is described. This initiative involves both organisational process change and multiple interoperating software systems. The software components rely on mutually supporting integration techniques. These include a richly structured ontology, statistical analysis of experimental data against stored conclusions, natural language processing of public literature, secure document repositories with lightweight metadata, web services integration, enterprise web portals and relational databases. This approach has already begun to increase scientific productivity in our enterprise by creating an organisational memory (OM) of internal research findings, accessible on the web. Through bringing together these components it has also been possible to construct a very large and expanding repository of biological pathway information linked to this repository of findings which is extremely useful in analysis of DNA microarray data. This repository, in turn, enables our research paradigm to be shifted towards more comprehensive systems-based understandings of drug action.