All times are listed in CEST (Central European Summer Time)
- Sarah-Jane Dawson (Melbourne, Australia)
- Marleen Kok (Amsterdam, Netherlands)
- John Stagg (Montreal, Canada)
LBA72 - Unraveling the mechanism of action and resistance to trastuzumab deruxtecan (T-DXd): Biomarker analyses from patients from DAISY trial
- Maria Fernanda Mosele (Villejuif, France)
Abstract
Background
T-DXd is an anti-HER2 antibody-drug conjugate that demonstrated high efficacy in patients with HER2-overexpressing and HER2-low metastatic breast cancer (mBC). We aimed to explore the mechanism of action and resistance to T-DXd in patients from DAISY trial.
Methods
DAISY is a phase II, multicenter, open-label trial (NCT04132960) that assessed T-DXd efficacy in three cohorts of patients with mBC according to HER2 expression and performed biomarker analyses. Efficacy and biomarker results have been reported previously (Dieras et al, SABCS 2021; Mosele et al, ESMO BREAST 2022). To further explore the mechanism of action of T-DXd, we assessed the spatial genomic response according to HER2 expression by GeoMx in biopsies at D2-4 after cycle 1 of T-DXd (
Results
Serotonin receptor pathways in HER2-overexpressing and interferon alpha pathways in HER2-negative area were activated after T-DXd administration. No association between
Conclusions
T-DXd could trigger anti-tumor immune response in HER2-negative mBC. No recurrent drivers were identified at resistance.
Clinical trial identification
NCT04132960.
Legal entity responsible for the study
Gustave Roussy and Unicancer.
Funding
Daiichi Sankyo.
Disclosure
M.F. Mosele: Personal and Institutional, Pegascy. V.C. Dieras: Financial Interests, Personal, Advisory Board, National advisory board: Pierre Fabre Oncologie; Financial Interests, Personal, Advisory Board, Steering comittee, consultant, Symposium, travel expenses: Roche Genentech; Financial Interests, Personal, Advisory Board, + Symposia and travel expenses: Novartis; Financial Interests, Personal, Advisory Board, Advisory boards, symposia, travel expenses: Pfizer; Financial Interests, Personal, Advisory Board, Symposia, travel expenses: Lilly, AstraZeneca, MSD; Financial Interests, Personal, Advisory Board, Symposia,travel expenses: Daiichi Sankyo; Financial Interests, Personal, Advisory Board, symposia,travel expenses: Seagen, Gilead; Financial Interests, Personal, Advisory Board, Steering comitte: AbbVie; Financial Interests, Personal, Advisory Board: EISAI; Financial Interests, Personal, Other, IDMC: Sanofi; Financial Interests, Personal and Institutional, Other, IDMC: Sanofi; Financial Interests, Institutional, Invited Speaker: ROCHE Genentech, Astra Zeneca; Financial Interests, Institutional, Invited Speaker, Steering comittee: Lilly; Financial Interests, Institutional, Invited Speaker, IDMC: Daiichi Sankyo; Financial Interests, Institutional, Invited Speaker, PI: Seagen. E. Deluche: Financial Interests, Personal, Advisory Board: Novartis, Pfizer, Fresenius-Kabi, Lilly; Financial Interests, Personal, Invited Speaker: MSD; Financial Interests, Personal, Other, scientific events: Lilly, GSK; Financial Interests, Personal, funding for conference travel: AstraZeneca, Daiichi, Roche, Amgen. B. Pistilli: Financial Interests, Institutional, Advisory Role: AstraZeneca, Myriad, Pierre Fabre, Pfizer; Financial Interests, Institutional, Speaker’s Bureau: Daiichi Sankyo, Novartis, Puma; Financial Interests, Personal, Training: AstraZeneca, Pierre Fabre, MSD; Financial Interests, Institutional, Advisory Board: Novartis, AstraZeneca, Daiichi Sankyo. T. Bachelot: Financial Interests, Personal, Advisory Board: Roche, Novartis, AstraZeneca, Pfizer, SeaGen; Financial Interests, Institutional, Research Grant: Novartis, Roche, AstraZeneca, SeaGen, Pfizer; Financial Interests, Personal, Invited Speaker: Roche. M. Kobayashi: Personal, Employee of Daiichi Sankyo RD Novare, which belongs to Daiichi Sankyo Group. Daiichi Sankyo Group is developing T-DXd: Daiichi Sankyo RD Novare. T. Kakewaga: Personal, Employee of Daiichi Sankyo RD Novare, which belongs to Daiichi Sankyo Group. Daiichi Sankyo Group is developing T-DXd: Daiichi Sankyo RD Novare. M. Lacroix-Triki: Financial Interests, Personal and Institutional, Invited Speaker: Daiichi Sankyo RD Novare; Financial Interests, Personal and Institutional, Training: AstraZeneca. F. André: Financial Interests, Institutional, Research Grant: AstraZeneca, Lilly, Novartis, Pfizer, Roche, Daiichi; Founder: Pegacsy. All other authors have declared no conflicts of interest.
904MO - Anthracycline-related cardiotoxicity in breast cancer patients carrying mutational signature of homologous recombination deficiency (HRD)
- Lorena Incorvaia (Palermo, Italy)
Abstract
Background
The BRCA proteins play a key role in the homologous recombination (HR) pathway. Beyond
Methods
This is a multi-institutional retrospective/prospective study to investigate the risk of heart failure from anthracyclines on adjuvant setting in BC patients carrying germline pathogenic or likely pathogenic variant (PV) in
Results
Five hundred and three (503) BC patients, aging 21 to 82, were included in the study; 201 patients were carriers of germline PV in HRR pathway genes: 77 in
Conclusions
Our data suggest that PVs in HRR pathway genes can increase sensitivity of cardiac cells to DNA damaging anthracycline in BC patients. In these patients other measurements, such as the global longitudinal strain, could be proposed to optimize cardiovascular risk-management and to improve long-term survival.
Legal entity responsible for the study
University of Palermo.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
68MO - Generalization of a deep learning model for HER2 status predictions on H&E-stained whole slide images derived from 3 neoadjuvant clinical studies
- Miriam Hägele (Berlin, Germany)
Abstract
Background
Due to its decisive role to select targeted treatment options in breast cancer, we investigated if machine learning (ML) models could identify HER2-positive tumours from routinely obtained haematoxylin and eosin (H&E)-stained whole slide images.
Methods
We trained a machine learning model to predict the HER2 status on 844 patients from the GeparSixto and GeparSepto studies and validated it on 1567 independent patients from GeparSixto, GeparSepto and GeparOcto. The challenge of a single label per gigapixel image without additional, granular domain-expert annotations, is addressed by aggregating learned features per patient. We trained a network with a gated attention head and patch filtering on previously segmented tumour regions. Final predictions are made by an ensemble from a 5-fold outer cross-validation. Additionally, we use selective prediction analysis to choose a subset of patients for which the model is highly certain.
Results
Our model was evaluated on 1488 patients of the validation set (excluding 5% due to automatic quality control). With respect to the centrally assessed clinical HER2 status it achieves an area under the receiver-operator curve (AUROC) of 0.81 (95% CI 0.79-0.83) and a balanced accuracy (BA) of 73.1%. In the held-out GeparOcto subcohort, we observe AUROC=0.80 (95% CI 0.77-0.83) and BA=70.4%. Taking the model's confidence into account, we show that for a subset of 13% and another set of 32% of selected cases the BA increases to 84.7% and 81.5%, respectively. Considering different thresholds illustrates the trade-off between coverage and performance.
Conclusions
The trained ML model predicts HER2 status with state-of-the-art performance. We extend on that by demonstrating the generalization of performance on a held-out clinical study (GeparOcto). In addition, our approach demonstrates that substantial performance increases can be achieved for subsets of patients based on the model's confidence. Both, the generalization to a held-out clinical study as well as the subset analysis of the most confident predictions, demonstrate the robustness of our approach.
Legal entity responsible for the study
GBG Forschungs GmbH and BIFOLD.
Funding
German Ministry for Education and Research as BIFOLD - Berlin Institute for the Foundations of Learning and Data (ref. 01IS18025A and ref 01IS18037A) and as BBDC (KS 89715122).
Disclosure
M. Hägele: Financial Interests, Institutional, Research Grant: German Ministry for Education and Research as BIFOLD -Berlin Institute for the Foundations of Learning and Data. C. Denkert: Other, Institutional, Research Grant: Myriad, Roche; Financial Interests, Personal and Institutional, Royalties: VmScope Digital Pathology Software; Financial Interests, Personal and Institutional, Advisory Role, Consulting fees: MSD Oncology, Daiichi Sankyo, Merck, Roche, Lilly, Molecular Health; Financial Interests, Personal and Institutional, Speaker’s Bureau, Consulting fees: AstraZeneca; Financial Interests, Personal and Institutional, Other, Paten for Therapy response: WO2015114146A1, WO2010076322A1; Financial Interests, Personal and Institutional, Other, Patent for Cancer Immunotherapy: WO2020109570A1; Non-Financial Interests, Personal, Ownership Interest, cofounder and shareholder until 2016: Sividon Diagnostics. A. Schneeweiss: Other, Institutional, Research Grant: BMS (Celgene), Roche, AbbVie; Financial Interests, Personal, Other, Honoraria, Travel expenses: Pfizer; Financial Interests, Personal, Other, Honoraria: AstraZeneca, Novartis, MSD, Tesaro, Lilly, Seagen, Gilead, GSK, Bayer, Amgen, Pierre Fabre; Financial Interests, Personal, Other, Travel expenses, Honoraria: BMS (Celgene), Roche. M. Untch: Non-Financial Interests, Personal and Institutional, Other: Amgen GmbH, AstraZeneca, Celgene GmbH, Daiichi Sankyo, Eisai, Lilly Int., MSD Merck, Myriad Genetics, Pfizer GmbH, Roche Pharma AG, Sanofi Aventis Deutschland GmbH, Novartis, Clovis Oncology; Financial Interests, Personal and Institutional, Other: Lilly Deutschland, Pierre Fabre, Seattle Genetics, Seagen, GSK, Gilead. P.A. Fasching: Financial Interests, Personal, Advisory Board: Roche, Novartis, Pfizer, Daiichi Sankyo, Eisai, Merck Sharp & Dohme, AstraZeneca, Hecal, Lilly, Pierre Fabre, Seagen, Agendia; Financial Interests, Personal, Invited Speaker: Novartis, Daiichi Sankyo, Eisai, Merck Sharp & Dohme, AstraZeneca, Lilly, Seagen; Financial Interests, Personal, Other, Medical Writing Support: Roche; Financial Interests, Institutional, Invited Speaker: BionTech, Cepheid; Non-Financial Interests, Member: ASCO, Arbeitsgemeinschaft für Gynäkologische Onkologie e.V., Translational Research in Oncology, Deutsche Gesellschaft für Senologie e.v. V. Mueller: Financial Interests, Personal, Other, Speaker and Consultancy Honoraria: Amgen, Daiichi Sankyo, Eisai, MSD, GSK, Gilead; Financial Interests, Personal, Other, Consultancy Honoraria: Genomic Health, Hexal, Pierre Fabre, ClinSol, Lilly; Financial Interests, Institutional, Other, institutional research support: Novartis, Roche, Seagen, Genentech; Financial Interests, Personal, Other, speaker honoraria: AstraZeneca, Pfizer, Teva; Financial Interests, Personal and Institutional, Other, speaker and consultancy honoraria, Institutional research support: Novartis, Roche; Financial Interests, Personal and Institutional, Other, speaker honoraria, Institutional research support: Seagen; Financial Interests, Institutional, Other, institutional research support: Genentech. S. Loibl: Financial Interests, Institutional, Research Grant, honorarium for Ad Boards, paid to institute: AbbVie, Celgene; Financial Interests, Institutional, Other, honorarium for Ad Boards, paid to institute: Amgen, BMS, Eirgenix, GSK, Lilly, Merck; Financial Interests, Institutional, Research Grant, honorarium for Ad Boards & Lectures, paid to institute: AstraZeneca; Non-Financial Interests, Institutional, Research Grant, honorarium for Ad Boards & Lectures, paid to institute / Medical Writing: Gilead, Novartis, Pfizer, Daiichi Sankyo, Roche; Financial Interests, Institutional, Other, honorarium for Ad Board & Lecture, paid to institute: Pierre Fabre; Non-Financial Interests, Institutional, Other, honorarium for Ad Boards & Lectures, paid to institute / Medical Writing: Seagen; Financial Interests, Institutional, Other, honorarium for Ad Board, paid to institute: Sanofi; Financial Interests, Institutional, Other, Patent for Immunsignature in TNBC, paid to institute: EP14153692.0; Financial Interests, Institutional, Other, Patent for Signature for CDK 4/6 Inhibitor, paid to institute: EP21152186.9; Financial Interests, Institutional, Other, Paten for Predicting response to an Anti-HER2 containing therapy, paid to institute: EP15702464.7; Financial Interests, Institutional, Other, Patent for GeparNuevo, paid to institute: EP19808852.8; Financial Interests, Institutional, Royalties, VM Scope GmbH, paid to institute: Digital Ki67 Evaluator. All other authors have declared no conflicts of interest.
1661MO - Genomic somatic copy number alterations drive adaptive tumor immune suppression and primary resistance to anti-PD1 + anti-angiogenics in pleural mesothelioma
- François-Xavier DANLOS (Villejuif, France)
Abstract
Background
In patients with advanced pleural malignant mesothelioma (MM), Pembrolizumab [P] in combination with Nintedanib [N] synergize with a response rate of 24% (PEMBIB trial initial results reported at ESMO Congress 2021), superior to [P] alone (8% in MM in the KN158 trial). Here we report new data from the biomarker analysis performed in this trial (NCT02856425).
Methods
30 MM patients were treated with [N] (150mg bid) & [P] (200mg IV Q3W). Fresh tumor biopsies were collected in media and immediately processed at baseline and at C2D1 for measuring proteins released in the biopsy supernatant and immune cell infiltrates (by Flow Cytometry). Frozen and fixed tumor biopsies were also analyzed by WES, FISH, RNAseq and IHC. Circulating cytokines & immune cells were measured on plasma and fresh whole blood at baseline and on-treatment. At 6 months, patients remaining in stable disease or objective tumor response per RECIST1.1 were categorized as having Durable Clinical Benefit (DCB). All differences reported here are statistically significant with a p value at least <0,05.
Results
Higher PD-L1 on tumor cells, higher tumor CD45+, CD3+ & CD8+ T-cells characterized the DCB group at baseline. Unexpectedly, active recruitment of CD8+ T-cells, with higher gene expression of EOMES, T-BET, IFNg, & GzmB, occurred in No DCB tumors upon treatment. At C2D1, same levels of tumor infiltrating CD8+ T-cells were found in DCB & No DCB tumors. This tumor T-cell recruitment occurred in a context of high blood and tumor CXCL9 increases upon [N]+[P] treatment. However, No DCB patients presented more IL6, VEGF, IL8, in their blood & tumor secretome and they increased their tumor content in CD4+ CD25+ Tregs compared to DCB patients upon treatment. Tumor somatic copy number alterations (SCNA) were higher in tumors with no DCB and correlated with higher plasmatic IL-6 rate levels in MM patients.
Conclusions
MM primary resistance to anti-PD1+antiangiogenics is not due to a lack of CD8+ T-cell tumor response but to an adaptive secretion of IL6 by tumors, driven by genomic SCNA, leading to VEGF and IL8 secretion, and recruitment of tumor infiltrating Tregs.
Clinical trial identification
NCT02856425.
Legal entity responsible for the study
Gustave Roussy.
Funding
Funding: Boehringer Ingelheim; Drug supply: Boehringer Ingelheim & MSD;Sponsor: Gustave Roussy.
Disclosure
C. Baldini: Financial Interests, Institutional, Advisory Board: BMS; Financial Interests, Institutional, Expert Testimony: MSD; Financial Interests, Personal, Invited Speaker: AstraZeneca; Financial Interests, Institutional, Research Grant: BMS; Financial Interests, Institutional, Invited Speaker: iTeos, AZ, Janssen, Amgen, Bicycle Therapeutics, MSD, Seattle Genetics, Tahio; Non-Financial Interests, Member: ASCO, SIOG, SOFOG, AACR. N. Chaput-Gras: Financial Interests, Personal, Advisory Board, Strong-Iopredi Scientific Advisory Board: AstraZeneca; Financial Interests, Institutional, Invited Speaker, Educational Session On Immune Cell Death: Servier; Financial Interests, Institutional, Expert Testimony, Expertise On Immune Cell Death Biomarkers: Servier; Financial Interests, Personal, Invited Speaker: Cytune Pharma; Financial Interests, Institutional, Research Grant, Research grant to identify immune biomarkers associated to clinical response in patients treated with agonistic mAbs: GSK; Financial Interests, Institutional, Research Grant, Preclinical studies in mice: GSK; Financial Interests, Institutional, Research Grant, Immune profiling of Head & Neck tumors: Sanofi. C. Massard: Non-Financial Interests, Personal, Advisory Board: Amgen, Astellas Pharma, AstraZeneca, Bayer, BeiGene, BMS, Celgene, Debiopharm Group, Genentech/Roche, Ipsen, Janssen, Lilly, MSD, Novartis, Pfizer, Sanofi, Orion, Taiho Pharmaceuticals, Blueprint Medicines, Innate Pharma, PharmaMar, Faron Pharmaceuticals. J. Soria: Financial Interests, Personal, Full or part-time Employment, From Sept 2017 to Dec 2019: AstraZeneca; Financial Interests, Personal, Invited Speaker, 2019-2021: Hookipa Pharmaceuticals; Financial Interests, Personal, Full or part-time Employment, SVP Amgen since August 2021: Amgen; Financial Interests, Personal, Stocks/Shares: Gritstone, Hookipa Pharmaceuticals. G. Zalcman: Financial Interests, Personal, Invited Speaker, outside the submitted work: BMS, MSD, AstraZeneca, Boehringer Ingelheim; Non-Financial Interests, Personal, Advisory Board, outside the submitted work: Roche, Takeda, AstraZeneca. A. Marabelle: Financial Interests, Personal, Invited Speaker: Roche/Genentech, BMS, Merck Serono, AstraZeneca, Amgen, Sanofi, Servier; Financial Interests, Personal, Stocks/Shares: Pegascy SAS, Centessa Pharmaceuticals, HiFiBio, Shattuck Labs; Financial Interests, Institutional, Research Grant: Merus, BMS, Boehringer Ingelheim, Transgene, Foundation MSD Avenir, Sanofi. All other authors have declared no conflicts of interest.
Invited Discussant LBA72, 904MO, 68MO and 1661MO
- Marleen Kok (Amsterdam, Netherlands)
1662MO - Longitudinal analysis of circulating immune cell subsets in melanoma patients (pts) treated with neo-adjuvant ipilimumab (ipi) & nivolumab (nivo)
- Rebecca C. Simpson (Wollstonecraft, Australia)
Abstract
Background
Immune checkpoint inhibition (ICI) has improved outcomes for pts with stage II-IV melanoma, although drug resistance and/or immune-related adverse events (irAEs) impact the majority of pts. Here we present a longitudinal analysis of immune cell subsets and correlation with pathological response and irAEs in pts on the neoadjuvant OpACIN-neo & PRADO trials (NCT02977052).
Methods
All pts with resectable stage III melanoma received combination neoadjuvant therapy with ipi and nivo for 6 weeks followed by surgical resection of the involved lymph node basin or index node. Paired pre (baseline) and post (wk 6) treatment PBMCs were comprehensively profiled using mass cytometry (CyTOF).
Results
Of 71 pts included, 53 (75%) had a pathological response (pCR, near-pCR and pPR) and 60 (85%) experienced at least one irAE; 16 (23%) Gd 3 or higher. Irrespective of clinical outcome, treatment was associated with a decreased frequency (% total CD45+) of both CD4+ and CD8+ naive T cells (CD45RA+CCR7+) (P< 0.0001, P= 0.0006) and an increased frequency of effector memory T cell (Tem) populations (CD45RA- CCR7-) (P=0.0165, P=0.0096). Significantly, gut homing CD8+ Tem (IntegrinB7+ CCR9+) increased with treatment (P< 0.0001). Pathological response was associated with increased Th1 (P=0.0055) and decreased Th2 (P=0.0037) populations, as well as a decreased frequency of circulating CD25+ FoxP3+ regulatory T cells (Tregs) (P= 0.0016). Pts that developed Gd 3 or higher irAEs had a significant reduction in both the frequency of Tregs (P=0.0293) and the ratio of Tregs to CD8+ Tem (P=0.0290) at week 6, however 75% (12/16) received immunosuppressants before/at wk 6.
Conclusions
Neoadjuvant treatment with ipilimumab and nivolumab promotes the systemic expansion of effector T cell populations including gut homing subsets. In particular, response is associated with an increase in circulating type 1 T cell subsets and a reduction in Tregs. Understanding systemic immune dynamics during treatment could inform the development of therapeutic strategies and interventions that increase treatment efficacy, reduce irAE occurrence, and allow for more targeted treatment of irAEs.
Clinical trial identification
NCT02977052.
Legal entity responsible for the study
Melanoma Institute Australia & The Netherlands Cancer Institute.
Funding
Melanoma Institute Australia, The University of Sydney.
Disclosure
A.M. Menzies: Financial Interests, Personal, Advisory Board, advisory board: BMS, MSD, Novartis, Roche, Pierre Fabre, QBiotics. R.P.M. Saw: Financial Interests, Personal, Invited Speaker: Bristol Myers Squib, Novartis; Financial Interests, Personal, Advisory Board: Novartis, MSD, Qbiotics; Financial Interests, Personal, Other, On Faculty, support of University of Sydney salary: Melanoma Institute Australia. C.U. Blank: Financial Interests, Institutional, Advisory Board: BMS, MSD, Roche, Novartis, GSK, AZ, Pfizer, Lilly, GenMab, Pierre Fabre; Financial Interests, Personal, Expert Testimony: Third Rock Ventures; Financial Interests, Personal, Stocks/Shares: Uniti Cars, co-founder Immagene BV; Financial Interests, Institutional, Invited Speaker: BMS, Novartis, NanoString, 4SC. R.A. Scolyer: Financial Interests, Personal, Advisory Role, fees for professional services: Evaxion, Provectus Biopharmaceuticals Australia, F. Hoffmann-La Roche Ltd., Qbiotics, Novartis, Merck Sharp & Dohme, NeraCare, Amgen Inc., Bristol Myers Squibb, Myriad Genetics, GlaxoSmithKline. G.V. Long: Financial Interests, Personal, Other, Consultant Advisor: Agenus Inc., Amgen Inc., Array Biopharma Inc., Boehringer Ingelheim International GmbH, Bristol Myers Squibb, Evaxion Biotech A/S, Hexal AG (Sandoz Company), Merck Sharpe & Dohme (Australia) Pty Limited, Novartis Pharma AG, OncoSec Medical Australia, Pierre Fabre, Provectus Australia, Qbiotics Group Limited, Regeneron Pharmaceuticals Inc.; Financial Interests, Personal, Advisory Board, Consultant Advisor: Highlight Therapeutics S.L. All other authors have declared no conflicts of interest.
1663MO - DAV132 prevents antibiotic-induced intestinal microbiota dysbiosis and maintains anti-PD-1 efficacy: A proof-of-concept in tumor-bearing mice transplanted with human feces
- Meriem Messaoudene (Montreal, Canada)
Abstract
Background
Antibiotics (ABX) prior to immune checkpoint inhibitors (ICI) induce intestinal dysbiosis and decrease ICI efficacy. DAV132 is a colon-targeted ABX adsorbent designed to prevent ABX-related dysbiosis. We investigated whether DAV132 could protect microbiota diversity and composition post ABX, and determined anti-PD-1 efficacy through fecal microbiota transplantation (FMT) in germ-free (GF) mice.
Methods
Twenty-four human healthy volunteers (HV) were randomized to receive either ceftazidime-avibactam (CZA, 2g/0.5g q8h IV for 5 days) or CZA + DAV132 (12g PO tid for 7 days). CZA plasmatic and fecal levels were measured, and microbiome was profiled with 16S metagenomics. FMT in GF mice was performed using samples from 3 HV in each group before CZA +/- DAV132 or at D6, thereafter mice were inoculated with MCA-205 tumor and treated with anti-PD-1, 4 times every 3 days.
Results
DAV132 did not impact plasmatic CZA concentrations, but significantly reduced ceftazidime concentration in feces compared to HV treated with CZA alone. Moreover, DAV132 significantly prevented the reduction in microbiota alpha- and beta-diversities. Mice transplanted with feces collected prior to CZA +/- DAV132 exhibited a significant reduction in tumor size when treated with anti-PD-1 antibodies. This anti-tumor response was inhibited in mice transplanted with D6 feces from any of the 3 CZA-treated HV. Conversely, the anti-tumor response was maintained in mice transplanted with D6 feces from any of the 3 HV treated with CZA + DAV132.
Conclusions
DAV132 strongly reduced CZA-induced dysbiosis in HV without effect on CZA plasmatic concentrations. In a murine model, FMT from HV treated with CZA + DAV132 was able to preserve anti-PD-1 efficacy. These results provide rationale to launch clinical trials combining DAV132 with ABX on patients amenable to ICI.
Legal entity responsible for the study
Da Volterra SA, Paris, France & University of Montreal Hospital Research Centre (CRCHUM), Montreal, Quebec, QC, Canada.
Funding
Da Volterra.
Disclosure
N. Saint-Lu: Financial Interests, Personal, Full or part-time Employment: Da Volterra. F. Sablier-Gallis: Financial Interests, Personal, Full or part-time Employment: Da Volterra; Financial Interests, Personal, Stocks/Shares: Da Volterra. S. Ferreira: Financial Interests, Personal, Full or part-time Employment: Da Volterra. C. Le Bescop: Financial Interests, Personal, Full or part-time Employment: Da Volterra; Financial Interests, Personal, Stocks/Shares: Da Volterra. C. Féger: Financial Interests, Personal, Advisory Role: Da Volterra. A. Andremont: Financial Interests, Personal, Advisory Role: Da Volterra; Financial Interests, Personal, Stocks/Shares: Da Volterra. J. de Gunzburg: Financial Interests, Personal, Stocks/Shares: Da Volterra; Financial Interests, Personal, Member of the Board of Directors: Da Volterra; Financial Interests, Personal, Advisory Role: Da Volterra. B. Routy: Financial Interests, Personal, Research Grant: Da Volterra. All other authors have declared no conflicts of interest.
Invited Discussant 1662MO and 1663MO
- John Stagg (Montreal, Canada)
905MO - Synergistic combination of clinical, imaging and DNA methylation biomarkers improves the classification of pulmonary nodules
- Wenhua Liang (Guangzhou, China)
Abstract
Background
Clinical unmet needs still abound for an accurate noninvasive test to facilitate early detection of lung cancer. Here, we describe a novel combination of clinical, imaging and DNA methylation biomarkers to improve the classification of pulmonary nodules.
Methods
We conducted a prospective collection and retrospective blinded evaluation trial comprising 1,380 subjects in 24 sites. We developed a 10-feature combined clinical and imaging biomarkers model (CIBM) for the classification of malignant and benign pulmonary nodules in a cohort (n=839) and validated it in 2 cohorts (n1=258, n2=283). Then we integrated CIBM model with our previously established ctDNA methylation model (PulmoSeek) to create a new combined model (n=258), PulmoSeek Plus, and verified it independently (n=283). Meanwhile, a 12-feature imaging biomarker model for invasiveness differentiation (IBMI) of lung adenocarcinoma were established (n=624) and validated (n1=202, n2=193). Clinical utility of the models was evaluated using a decision curve analysis.
Results
The CIBM model achieved improved AUCs (0.85 [95% CI 0.80-0.89]; 0.85 [0.81-0.89]) over Mayo model (0.60 [0.52-0.68]; 0.57 [0.50-0.64]) and Brock model (0.70 [0.63-0.77]; 0.67 [0.60-0.73]) in the two validation cohorts, respectively. PulmoSeek Plus had AUC of 0.90 [0.88-0.93] in the combined set (n=541), significantly outperforming both CIBM (0.85 [0.82-0.88]) and PulmoSeek (0.85 [0.82-0.88]). The overall sensitivity was 98.0% [0.97-1.00] at a fixed specificity of 50.0% for rule out. High sensitivity of 98.0% [0.96-0.99] was maintained in early-stage lung cancer (0-I, n=390) and 99.2% [0.96-1.00] in 5-10 mm nodules (n=123). The IBMI model had AUCs of 0.87 [0.82-0.92], 0.89 [0.84-0.93] and 0.89 [0.85-0.92] in the two validation sets and the combined set. At a risk score of 0.54, PulmoSeek Plus improved net benefit by 60.8%, equivalent to detecting additional 82.4% of lung cancers. Using two cut-offs of PulmoSeek Plus scores to reclassify would have reduced 46.0% unnecessary surgeries and reduced 73.2% delayed treatment.
Conclusions
PulmoSeek Plus model improves the early detection and classification of pulmonary nodules, potentially worth using in clinical decision-making.
Legal entity responsible for the study
Anchordx Medical Co., Ltd., Guangzhou, China.
Funding
Anchordx Medical Co., Ltd., Guangzhou, China.
Disclosure
All authors have declared no conflicts of interest.
1664MO - Tumor-naïve methylomes and fragmentomes during pembrolizumab (P) in metastatic cancer patients
- Eric Y. Zhao (Toronto, Canada)
Abstract
Background
Decrease in circulating tumour DNA (ctDNA) by cycle 3 (C3) of P predicts favorable response. However, matched tissue sequencing is often needed to measure ctDNA mutation concentration (MC). ctDNA demonstrates cancer-specific methylation (CSM) and higher short fragment fraction (SFF). We report the first joint analysis of tumour-naïve cell-free methylomes and fragmentomes in a P-treated cohort.
Methods
In INSPIRE (NCT02644369), we measured CSM and SFF from tumour-naïve cell-free methylated DNA immunoprecipitation & sequencing (cfMeDIP-seq) at baseline (B) and C3 during P immunotherapy. SFF was defined as fraction of fragments shorter than mononucleosome median (146 bp). We independently trained a pan-cancer methylation signature on PanCanAtlas 450K arrays, then further filtered out leukocyte-methylated regions, yielding 298 CpGs. Methylation probabilities were inferred from coverage in 300 bp bins. CSM was the sum of probabilities across the 298 CpG signature. MC was measured with bespoke 16-mutation ctDNA panels (Signatera), guided by tissue exomes. Cox model adjusted hazard ratios (aHR) and p-values were corrected for cohort.
Results
51 patients were included, median follow-up: 18.2 months. Cohorts included head & neck n=12, breast n=10, ovary n=10, melanoma n=8, and others n=11. CSM was strongly correlated with MC (r=0.85, p<0.001). SFF was moderately correlated with CSM and MC (both r>0.55, p<0.001). Table shows associations of B-to-C3 ΔMC, ΔSFF, and ΔCSM with overall survival (OS) and progression-free survival (PFS). Decrease in any ctDNA metric was correlated with longer OS and PFS, with ΔMC and ΔCSM being statistically significant. To combine ΔCSM and ΔSFF, we devised a joint prognostic score, which yielded superior association with OS and PFS.
Outcome Predictor aHR Cohort-adjusted p-value Group # Events /# Patients (%) Median survival (months) OS ΔMC 0.45 0.016 * ↑ 23 / 25 (92%) 6.5 ΔCSM 0.35 0.0039 ** ↑ 25 / 28 (89%) 7.35 ΔSFF 0.50 0.055 ↑ 25 / 26 (96%) 7.35 Joint score 0.18 0.0009 *** 0 17 / 17 (100%) 6.3 PFS ΔMC 0.44 0.013 * ↑ 21 / 24 (88%) 0.5 ΔCSM 0.45 0.019 * ↑ 24 / 28 (86%) 0.5 ΔSFF 0.50 0.1 ↑ 20 / 25 (80%) 0.6 Joint score 0.20 0.004 ** 0 15 / 17 (88%) 0.5
Conclusions
CSM is an accurate tumour-naïve metric of ctDNA, using bespoke ctDNA as a gold standard. ΔCSM predicts OS and PFS comparably to ΔMC. Combining ΔCSM and ΔSFF from the same assay yields superior OS and PFS prediction.
Clinical trial identification
NCT02644369.
Legal entity responsible for the study
University Health Network.
Funding
Major funding support for the project was made possible by the Princess Margaret Cancer Foundation, Ontario Institute for Cancer Research and Terry Fox Research Institute. Merck did not provide direct funding for the study but contributed the study drug in kind.
Disclosure
A. Abdul Razak: Financial Interests, Personal, Advisory Role: Adaptimmune, Bayer, GlaxoSmithKline, Medison, Inhibrx; Financial Interests, Personal, Expert Testimony: Medison; Financial Interests, Institutional, Funding: Deciphera, Karyopharm Therapeutics, Pfizer, Roche/Genentech, Bristol Myers Squibb, MedImmune, Amgen, GlaxoSmithKline, Blueprint Medicines, Merck, AbbVie, Adaptimmune, Iterion Therapeutics, Neoleukin Therapeutics, Daiichi Sankyo, Symphonogen, Rain Therapeutics. A. Spreafico: Financial Interests, Personal, Other, Honoraria: Bristol Myers Squibb, Janssen Oncology; Financial Interests, Institutional, Advisory Role: Bristol Myers Squibb, Merck, Novartis, Oncorus, Medison & Immunocore; Financial Interests, Institutional, Funding: Alkermes, Array BioPharma, AstraZeneca/MedImmune, Bayer, Bristol Myers Squibb, GlaxoSmithKline, Janssen Oncology, Merck, Northern Biologics, Novartis, Replimune, Roche, Surface Oncology, Symphogen, Amgen, Treadwell Therapeutics; Financial Interests, Institutional, Other, Travel Expenses: Bayer, Bristol Myers Squibb, Idera, Janssen Oncology, Merck, Roche. P.L. Bedard: Financial Interests, Institutional, Invited Speaker: AstraZeneca, Bicara, BMS, Amgen, Novartis, Genentech/Roche, Sanofi, Merck, Pfizer, Zymeworks, Nektar Therapeutics, Lilly, Seagen; Financial Interests, Institutional, Research Grant: Pfizer; Financial Interests, Institutional, Funding: Servier; Non-Financial Interests, Invited Speaker, Executive Board Member: Breast International Group; Non-Financial Interests, Leadership Role, Chair: AACR Project GENIE; Non-Financial Interests, Leadership Role, Past Chair IND Committee Member, Breast Site Steering Committee: Canadian Clinical Trials Group; Non-Financial Interests, Advisory Role: Seagen, Lilly, Amgen, Merck, BMS, Pfizer, Gilead. A.R. Hansen: Financial Interests, Institutional, Advisory Role: AstraZeneca, Bristol Myers Squibb, Eisai, GlaxoSmithKline, Merck, Novartis; Financial Interests, Institutional, Research Grant: Astellas Pharma, AstraZeneca/MedImmune, BioNTech, Boehringer Ingelheim, Bristol Myers Squibb, GlaxoSmithKline, Janssen, Karyopharm Therapeutics, Merck, Neoleukin Therapeutics, Pfizer/EMD Serono, Roche/Genentech. S. Lheureux: Financial Interests, Personal, Advisory Role: AstraZeneca, Merck, GlaxoSmithKline, Eisai, Novocure, Shattuck Labs, Novartis; Financial Interests, Personal, Other, Honoraria: AstraZeneca, Eisai, Merck, GlaxoSmithKline; Financial Interests, Institutional, Funding: Tesaro, AstraZeneca, Roche/Genentech, Regeneron, Merck, GlaxoSmithKline, Repare Therapeutics. D. Torti: Financial Interests, Personal, Full or part-time Employment: Ezra AI; Financial Interests, Personal, Stocks/Shares: Ezra AI. T.J. Pugh: Financial Interests, Personal, Advisory Role: Chrysalis Biomedical Advisors, Axiom Healthcare Strategies; Financial Interests, Personal and Institutional, Proprietary Information: Hybrid-Capture Sequencing for Determining Immune Cell Clonality; Financial Interests, Personal, Other, Honoraria: Merck; Financial Interests, Institutional, Funding: Roche. L.L. Siu: Financial Interests, Personal, Advisory Board: Merck, Pfizer, AstraZeneca, Morphosys, Roche, GeneSeeq, Loxo, Oncorus, Symphogen, Seattle Genetics, Voronoi, Treadwell Therapeutics, Arvinas, Tessa, Navire, Relay Therapeutics, Rubius, Janpix; Financial Interests, Personal, Other, Spouse is co-founder: Treadwell Therapeutics; Financial Interests, Personal, Stocks/Shares, Spouse has stock ownership: Agios; Financial Interests, Institutional, Invited Speaker: Novartis, Bristol Myers Squibb, Pfizer, Boehringer Ingelheim, GlaxoSmithKline, Roche/Genentech, AstraZeneca, Merck, Astellas, Bayer, Amgen, Symphogen, Intensity Therapeutics, Mirati, Shattucks, Avid. All other authors have declared no conflicts of interest.
69MO - 5-Hydroxymethycytosine analysis reveals stable epigenetic changes in tumor tissue that enable cfDNA cancer predictions
- Felix Feng (San Francisco, United States of America)
Abstract
Background
5-Hydroxymethylcytosines (5hmCs) are stable epigenetic marks in the regions of active gene expression and regulation that underlie development and tumorigenesis. To investigate 5hmC patterns in tumor tissues, we characterized a collection of 267 fresh frozen tumor and non-tumor tissue samples using Bluestar Genomics’ genome-wide 5hmC profiling technology. The tumor samples represent five tissue types at various stages of cancer: breast, colon, lung, ovary, and pancreas.
Methods
Fresh-frozen samples of five tissue types were obtained by autopsy or surgery from individual subjects, 217 are tumor and 50 are non-tumor; cfDNA samples were obtained from 1009 cancer subjects and 1678 non-cancer subjects. Genomic or cfDNA were extracted, then enriched for 5hmC containing fragments. Whole genome and 5hmC-enriched libraries were generated and sequenced.
Results
Differential analysis found that up to 50% of all genes are hyper- or hypo- hydroxymethylated between tumor and normal samples and a global decrease of 5hmC in tumors across all tissue types. The 5hmC landscape reveals both a common theme across tissues as well as tissue-specific changes during tumorigenesis--changes that appear to be stable during cancer progression. We constructed a multinomial model that incorporates both non-tumor and tumor tissue 5hmC data. The model predicts Tissue of Tumor Origin (TOTO) and cancer status with 88% overall accuracy. There is a significant overlap of tumor-differentiating signatures between tissue and cfDNA, with highest concordance in colon, ovarian and pancreatic cancers, and weaker concordance in lung and breast; the strength of concordance trends with plasma cfDNA concentration. Further, we found the top tumor-differentiating 5hmC genes (DhMR) increase cancer prediction sensitivity over non-DhMR genes for cfDNA samples.
Conclusions
Our results suggest that the majority of 5hmC changes occur during the early onset of tumorigenesis and remain stable over cancer stage and therefore can be used to improve cancer and TOTO predictions for both early- and late-stage tumors as well as cfDNA from patients.
Editorial acknowledgement
Dr. Elizabeth Stewart for her assistance in the writing of the abstract.
Legal entity responsible for the study
Bluestar Genomics.
Funding
Bluestar Genomics.
Disclosure
F. Feng: Stocks/Shares, Financial Interests, Personal: Bluestar Genomics. Y. Ning, Y. Xue, V. Friedl, D. Hann, B. Gibb, A. Bergamaschi, G. Guler, K. Hazen, A. Scott, T. Phillips, E. McCarthy, C. Ellison, R. Malta, A. Nguyen, V. Lopez, R. Cavet, S. Chowdhury, W. Volkmuth, S. Levy: Other, Institutional, Full or part-time Employment, employee only authors: Bluestar Genomics.
Invited Discussant 905MO, 1664MO and 69MO
- Sarah-Jane Dawson (Melbourne, Australia)