Browsing Over 79 Presentations
- Guzman Alonso Casal (Barcelona, Spain)
- Guzman Alonso Casal (Barcelona, Spain)
- Susana Aguilar (Barcelona, Spain)
- Francisco Javier Ros Montana (Barcelona, Spain)
- Helena Verdaguer (Barcelona, Spain)
- Ana Callejo Perez (Barcelona, Spain)
- Irene Brana (Barcelona, Spain)
- Iosune Baraibar Argota (Barcelona, Spain)
- Patricia Iranzo Gomez (Barcelona, Spain)
- Omar Saavedra Santa Gadea (Barcelona, Spain)
- Francesc Salva Ballabrera (Barcelona, Ba, Spain)
- Daniel A. Acosta Eyzaguirre (Barcelona, Spain)
- Maria Vieito Villar (Barcelona, La, Spain)
- Esmeralda Garcia Torralba (Murcia, Spain)
- Natassia Ann Wornham (Barcelona, Spain)
- Iris Faull (Barcelona, Spain)
- Josep Tabernero (Barcelona, Spain)
- Enriqueta Felip (Barcelona, Spain)
- Elena Elez (Barcelona, Spain)
- Teresa Macarulla Mercade (Barcelona, Spain)
- Elena Garralda (Barcelona, Spain)
6P - Circulating tumor DNA (ctDNA) next generation sequencing (NGS): Molecular prescreening for tailoring treatment in clinical trials
Abstract
Background
CtDNA NGS analysis has the potential to identify patients (pts) with the appropriate genomic alterations for enrollment in clinical trials (CT), helping overcome the challenge of tissue biopsies.
Methods
Guardant360™ (G360) was performed in patients (pts) with colorectal, cholangiocarcinoma, thyroid, salivary gland, pancreatic cancer and treatment-naïve NSCLC who were candidates for clinical trials at Vall d’Hebron Institute of Oncology. Pts with an available tumor tissue sample of less than 6 months, those with a previously known tier 1 variant according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) or known resistance mutations were excluded. Genomic alteration actionability was classified according to ESCAT. Our main objective was to analyze the targetable genomic alterations detected from all informative G360 tests, and evaluate pts inclusion in CT.
Results
108 patients were included from November 2019 to April 2021. G360 was informative in 96 pts (88.88%), and 36 pts (33.3%) had a previous tissue NGS result. Median Turn Around Time (TAT) for G360 was 8.5 days (7-15). Potentially targetable alterations were identified in 14 pts (14.58%); 5 pts (4.16%) with tier I variants and 9 pts (9.37%) with tier II variants. The main druggable alterations include: ERBB2 amplification (3), KRAS G12C mutation (mut) (3), ERBB2 exon 2 insertion (2), BRAF V600E mut (1), MSI-High (1), EGFR L858R mut (1), EGFR exon 20 indel (1), ERBB2 R678Q (1) and RET M918T mut (1). 5 pts (5.20%) received treatment based on the G360 report. 4/5 pts were treated in a clinical trial, and 3 pts achieved a partial response. We identified 46 tier III variants that could be potential targets in phase I trials. Moreover, 22/52 pts (42,30%) with CRC showed RAS-resistant mutations to anti-EGFR therapies.
Patients’ characteristics All N= 108 Age median (range) 58 (32-83) Sex Male 51 Female 57 Diagnosis New 31 Relapsed 77 Lines of treatment median (range) 2 (0-7) Histology Colorectal 52 Pancreatic 30 NSCLC 17 Salivary gland 4 Cholangiocarcinoma 2 Thyroid 2 Parathyroid 1
Conclusions
G360 has a short turnaround time and is able to identify targetable alterations in patients with unknown genomic drivers. NGS of ctDNA can optimize clinical trial recruitment.
Legal entity responsible for the study
The authors.
Funding
Guardant Health Inc.
Disclosure
H. Verdaguer: Financial Interests, Personal, Other, Honoraria: Amgen; Financial Interests, Personal, Other, Honoraria: Celgene; Financial Interests, Personal, Other, Honoraria: MSD; Financial Interests, Personal, Advisory Board: Ipsen; Financial Interests, Personal, Other, Travel grants: Amgen; Financial Interests, Personal, Other, Travel grants: Celgene; Financial Interests, Personal, Other, Travel grants: Ipsen; Financial Interests, Personal, Other, Travel grants: Servier. A. Callejo Perez: Financial Interests, Personal, Advisory Board: Bristol Myers Squibb; Financial Interests, Personal, Advisory Board: F. Hofmann-La Roche; Financial Interests, Personal, Advisory Board: Pfizer; Financial Interests, Personal, Advisory Board: Boehringer Ingelheim; Financial Interests, Personal, Advisory Board: MSD Oncology; Financial Interests, Personal, Advisory Board: Kyowa Kirin; Financial Interests, Personal, Advisory Board: Celgene; Financial Interests, Personal, Advisory Board: Leo Pharma; Financial Interests, Personal, Advisory Board: Medscape; Financial Interests, Personal, Advisory Board: Kern Pharma. I. Brana: Financial Interests, Personal, Advisory Board: Merck Sharp & Dome; Financial Interests, Personal, Advisory Board: Rakuten Medical; Financial Interests, Personal, Advisory Board: Sanofi; Financial Interests, Personal, Advisory Board: Achilles Therapeutics; Financial Interests, Personal, Advisory Board: eTheRNA Immunotherapies; Financial Interests, Personal, Advisory Board: Cancer Expert Now; Financial Interests, Personal, Research Grant: BMS; Financial Interests, Personal, Research Grant: Merck Serono; Financial Interests, Personal, Research Grant: Roche; Financial Interests, Personal, Research Grant: AstraZeneca; Financial Interests, Personal, Research Grant: BMS; Financial Interests, Personal, Research Grant: Celgene; Financial Interests, Personal, Research Grant: Gliknik; Financial Interests, Personal, Research Grant: GlaxoSmithKline; Financial Interests, Personal, Research Grant: Janssen; Financial Interests, Personal, Research Grant: Kura Oncology; Financial Interests, Personal, Research Grant: Merck Sharp & Dohme; Financial Interests, Personal, Research Grant: Novartis; Financial Interests, Personal, Research Grant: Orion Pharma GmbH; Financial Interests, Personal, Research Grant: Pfizer; Financial Interests, Personal, Research Grant: Roche; Financial Interests, Personal, Research Grant: Shattuck Labs; Financial Interests, Personal, Research Grant: Nanobiotix; Financial Interests, Personal, Other, Travel grants: Seattle Genetics; Financial Interests, Personal, Other, Travel grants: AstraZeneca; Financial Interests, Personal, Other, Travel grants: Merck Serono. I. Baraibar Argota: Financial Interests, Personal, Other, Travel grants: Merck; Financial Interests, Personal, Other, Travel grants: Amgen; Financial Interests, Personal, Other, Travel grants: Sanofi. P. Iranzo Gomez: Financial Interests, Personal, Advisory Board: Bristol Myers Squibb; Financial Interests, Personal, Advisory Board: F. Hofmann-La Roche; Financial Interests, Personal, Advisory Board: Boehringer Ingelheim; Financial Interests, Personal, Advisory Board: Merck Sharp & Dohme; Financial Interests, Personal, Advisory Board: MSD Oncology; Financial Interests, Personal, Advisory Board: Rovi; Financial Interests, Personal, Advisory Board: Kyowa Kirin; Financial Interests, Personal, Advisory Board: Grunenthal Pharma S.A.; Financial Interests, Personal, Advisory Board: Pfizer; Financial Interests, Personal, Advisory Board: Medscape; Financial Interests, Personal, Advisory Board: Kern Pharma. F. Salva Ballabrera: Financial Interests, Personal, Research Grant, Travel grants: F. Hoffman La-Roche; Financial Interests, Personal, Research Grant, Travel grants: Sanofi-Aventis; Financial Interests, Personal, Research Grant, Travel grants: Amgen; Financial Interests, Personal, Research Grant, Travel grants: Merck Serono; Financial Interests, Personal, Research Grant, Travel grants: Servier; Financial Interests, Personal, Research Grant, Travel grants: Bristol Myers Squibb. M. Vieito Villar: Financial Interests, Personal, Advisory Board: Debio; Financial Interests, Personal, Advisory Board: Roche; Financial Interests, Personal, Advisory Board: TFS; Financial Interests, Personal, Other, Travel grants: Merck Serono; Financial Interests, Personal, Other, Travel grants: Roche. I. Faull: Financial Interests, Personal, Full or part-time Employment: Guardant Health Inc. J. Tabernero: Financial Interests, Personal, Advisory Board: Array Biopharma; Financial Interests, Personal, Advisory Board: AstraZeneca; Financial Interests, Personal, Advisory Board: Avvinity; Financial Interests, Personal, Advisory Board: Bayer; Financial Interests, Personal, Advisory Board: Boehringer Ingelheim; Financial Interests, Personal, Advisory Board: Chugai; Financial Interests, Personal, Advisory Board: Daichi Sankyo; Financial Interests, Personal, Advisory Board: F. Hoffmann-La Roche Ltd.; Financial Interests, Personal, Advisory Board: Genentech Inc.; Financial Interests, Personal, Advisory Board: HalloDX SAS; Financial Interests, Personal, Advisory Board: Hutchison MediPharma Internacional; Financial Interests, Personal, Advisory Board: Ikena Oncology; Financial Interests, Personal, Advisory Board: IQVIA; Financial Interests, Personal, Advisory Board: Lilly; Financial Interests, Personal, Advisory Board: Menarini; Financial Interests, Personal, Advisory Board: Merck Serono; Financial Interests, Personal, Advisory Board: Merus; Financial Interests, Personal, Advisory Board: MSD; Financial Interests, Personal, Advisory Board: Mirati; Financial Interests, Personal, Advisory Board: Neophore; Financial Interests, Personal, Advisory Board: Novartis; Financial Interests, Personal, Advisory Board: Orion Biotechnology; Financial Interests, Personal, Advisory Board: Peptomyc; Financial Interests, Personal, Advisory Board: Pfizer; Financial Interests, Personal, Advisory Board: Pierre Fabre; Financial Interests, Personal, Advisory Board: Samsung Bioepis; Financial Interests, Personal, Advisory Board: Sanofi; Financial Interests, Personal, Advisory Board: Seattle Genetics; Financial Interests, Personal, Advisory Board: Servier; Financial Interests, Personal, Advisory Board: Taiho; Financial Interests, Personal, Advisory Board: Tessa Therapeutics; Financial Interests, Personal, Advisory Board: Theramyc; Financial Interests, Personal, Expert Testimony: Imedex; Financial Interests, Personal, Expert Testimony: Medscape Education; Financial Interests, Personal, Expert Testimony: MJH Life Science; Financial Interests, Personal, Expert Testimony: PeerView Institute for Medical Education; Financial Interests, Personal, Expert Testimony: Physicians Education Resource (PER); Financial Interests, Personal, Research Grant: Amgen Inc.; Financial Interests, Personal, Research Grant: Array Biopharma Inc.; Financial Interests, Personal, Research Grant: AstraZeneca Pharmaceuticals LP; Financial Interests, Personal, Research Grant: BeiGene; Financial Interests, Personal, Research Grant: Boehringer Ingelheim; Financial Interests, Personal, Research Grant: Bristol Myers Squibb; Financial Interests, Personal, Research Grant: Celgene; Financial Interests, Personal, Research Grant: Debiopharm International SA; Financial Interests, Personal, Research Grant: F. Hoffmann-La Roche Ltd.; Financial Interests, Personal, Research Grant: Genentech Inc; Financial Interests, Personal, Research Grant: HalioDX SAS; Financial Interests, Personal, Research Grant: Hutchinson MediPharma International; Financial Interests, Personal, Research Grant: Janssen-Cilag SA; Financial Interests, Personal, Research Grant: MedImmune; Financial Interests, Personal, Research Grant: Menarini; Financial Interests, Personal, Research Grant: Merck Health KGaA; Financial Interests, Personal, Research Grant: Merck Sharp & Dohme; Financial Interests, Personal, Research Grant: Merus NV; Financial Interests, Personal, Research Grant: Mirati; Financial Interests, Personal, Research Grant: Novartis Farmaceutica SA; Financial Interests, Personal, Research Grant: Pfizer; Financial Interests, Personal, Research Grant: PharmaMar; Financial Interests, Personal, Research Grant: Sanofi-Aventis Recherche & Développement; Financial Interests, Personal, Research Grant: Servier; Financial Interests, Personal, Research Grant: Taiho Pharma USA Inc; Financial Interests, Personal, Research Grant: Spanish Association Against Cancer Scientific Foundation; Financial Interests, Personal, Research Grant: Cancer Research UK. E. Felip: Financial Interests, Personal, Advisory Board: AbbVie; Financial Interests, Personal, Advisory Board: AstraZeneca; Financial Interests, Personal, Advisory Board: BerGenBio; Financial Interests, Personal, Advisory Board: Beigene; Financial Interests, Personal, Advisory Board: Bayer; Financial Interests, Personal, Advisory Board: Blueprint Medicine; Financial Interests, Personal, Advisory Board: Boehringer Ingelheim; Financial Interests, Personal, Advisory Board: Bristol Meyers Squibb; Financial Interests, Personal, Advisory Board: Celgene; Financial Interests, Personal, Advisory Board: Eli Lilly; Financial Interests, Personal, Advisory Board: GlaxoSmithKline; Financial Interests, Personal, Advisory Board: Guardant Health; Financial Interests, Personal, Advisory Board: Janssen; Financial Interests, Personal, Advisory Board: Medscape; Financial Interests, Personal, Advisory Board: Merck KGaA; Financial Interests, Personal, Advisory Board: Merck Sharp & Dohme; Financial Interests, Personal, Advisory Board: Merck Serono; Financial Interests, Personal, Advisory Board: Novartis; Financial Interests, Personal, Advisory Board: Pfizer; Financial Interests, Personal, Advisory Board: Prime Oncology; Financial Interests, Personal, Advisory Board: Peptomyc; Financial Interests, Personal, Advisory Board: Peervoice; Financial Interests, Personal, Advisory Board: Puma; Financial Interests, Personal, Advisory Board: Regeneron; Financial Interests, Personal, Advisory Board: Sanofi; Financial Interests, Personal, Advisory Board: Syneos Health; Financial Interests, Personal, Advisory Board: Springer; Financial Interests, Personal, Advisory Board: Roche; Financial Interests, Personal, Advisory Board: Samsung; Financial Interests, Personal, Advisory Board: Takeda; Financial Interests, Personal, Advisory Board: Touchtime; Financial Interests, Personal, Advisory Board: Grifols; Financial Interests, Personal, Research Grant: Fundación Merck Salud; Financial Interests, Personal, Research Grant: Oncology Innovation EMD Serono. E. Elez: Financial Interests, Personal, Advisory Board: F. Hoffman La-Roche; Financial Interests, Personal, Advisory Board: Sanofi; Financial Interests, Personal, Advisory Board: Amgen; Financial Interests, Personal, Advisory Board: Merck Serono; Financial Interests, Personal, Advisory Board: Array Biopharma; Financial Interests, Personal, Advisory Board: Bristol Myers Squibb; Financial Interests, Personal, Advisory Board: Servier; Financial Interests, Personal, Advisory Board: Bayer; Financial Interests, Personal, Research Grant: AbbVie; Financial Interests, Personal, Research Grant: Amgen; Financial Interests, Personal, Research Grant: Array Pharmaceuticals; Financial Interests, Personal, Research Grant: AstraZeneca; Financial Interests, Personal, Research Grant: Boehringer Ingelheim; Financial Interests, Personal, Research Grant: Bristol Myers Squibb; Financial Interests, Personal, Research Grant: GlaxoSmithKline; Financial Interests, Personal, Research Grant: F. Hoffman La-Roche; Financial Interests, Personal, Research Grant: MedImmune; Financial Interests, Personal, Research Grant: Merck Serono; Financial Interests, Personal, Research Grant: MSD; Financial Interests, Personal, Research Grant: Novartis; Financial Interests, Personal, Research Grant: Pierre Fabre; Financial Interests, Personal, Research Grant: Sanofi-Aventis. T. Macarulla Mercade: Financial Interests, Personal, Advisory Board: Sanofi-Aventis; Financial Interests, Personal, Advisory Board: Shire; Financial Interests, Personal, Advisory Board: Celgene; Financial Interests, Personal, Advisory Board: Roche; Financial Interests, Personal, Advisory Board: Baxalta; Financial Interests, Personal, Advisory Board: QED Therapeutics; Financial Interests, Personal, Advisory Board: Baxter; Financial Interests, Personal, Advisory Board: Incyte; Financial Interests, Personal, Advisory Board: Servier; Financial Interests, Personal, Advisory Board: Lilly; Financial Interests, Personal, Advisory Board: Ipsen; Financial Interests, Personal, Research Grant: Celgene; Financial Interests, Personal, Research Grant: Agios; Financial Interests, Personal, Research Grant: ASLAN Pharmaceuticals; Financial Interests, Personal, Research Grant: Bayer; Financial Interests, Personal, Research Grant: Roche; Financial Interests, Personal, Research Grant: Genentech; Financial Interests, Personal, Research Grant: AstraZeneca; Financial Interests, Personal, Research Grant: Halozyme; Financial Interests, Personal, Research Grant: Immunomedics; Financial Interests, Personal, Research Grant: Lilly; Financial Interests, Personal, Research Grant: Merrimack; Financial Interests, Personal, Research Grant: Millennium; Financial Interests, Personal, Research Grant: Novartis; Financial Interests, Personal, Research Grant: Novocure; Financial Interests, Personal, Research Grant: Pfizer; Financial Interests, Personal, Research Grant: Pharmacyclics; Financial Interests, Personal, Other, Travel grants: Merck; Financial Interests, Personal, Other, Travel grants: H3 Biomedicine; Financial Interests, Personal, Other, Travel grants: Sanofi; Financial Interests, Personal, Other, Travel grants: Celgene; Financial Interests, Personal, Other, travel Grants: Servier. E. Garralda: Financial Interests, Personal, Advisory Board: F. Hoffman La-Roche; Financial Interests, Personal, Advisory Board: Janssen; Financial Interests, Personal, Advisory Board: Boehringer Ingelheim; Financial Interests, Personal, Advisory Board: Seattle Genetics; Financial Interests, Personal, Advisory Board: Alkermes; Financial Interests, Personal, Advisory Board: Thermo Fisher Scientific; Financial Interests, Personal, Invited Speaker: BMS; Financial Interests, Personal, Advisory Board: TFS; Financial Interests, Personal, Invited Speaker: Roche; Financial Interests, Personal, Research Grant: Novartis; Financial Interests, Personal, Research Grant: Taiho; Financial Interests, Personal, Research Grant: AstraZeneca; Financial Interests, Personal, Research Grant: Roche; Financial Interests, Personal, Research Grant: Thermo Fisher; Financial Interests, Personal, Research Grant: BeiGene. All other authors have declared no conflicts of interest.
- Jyoutishman Saikia (New Delhi, India)
- Jyoutishman Saikia (New Delhi, India)
- Prabhat S. Malik (New Delhi, India)
- Sachin Kumar (New Delhi, India)
- Deepali Jain (New Delhi, India)
- Karan Madan (New Delhi, India)
- Sachidanand J. Bharati (New Delhi, India)
- Suryanarayana Deo (New Delhi, India)
- Sunil Kumar (New Delhi, India)
7P - Predictive and prognostic value of cell-free DNA in plasma and pleural lavage among surgically treated adenocarcinomas of the lung (ADCL)
Abstract
Background
Unlike advanced ADCL, the role of cfDNA in operable ADCL is unclear and this study was aimed to evaluate the feasibility for identification of cfDNA in pleural lavage fluid and its correlation with plasma in resectable ADCL.
Methods
Consecutively resected ADCL within a period of 24 months were evaluated for cfDNA levels in preoperative plasma (Pre-P), intraoperative pleural lavage (IP-L) and postoperative (at 1 month) plasma sample (Post-P). CfDNA was isolated from the stored pleural lavage and plasma using QIAamp DNA Blood Mini Kit (QIAGEN). DNA extracted plasma and pleural lavage DNA were measured quantitatively by qPCR in a TaqMan probe detection approach using the human β-actin gene as the amplifying target.
Results
All of the study patients (n=23) were negative for malignant cells in IP-L cytology. The median cfDNA levels in Pre-P, IP-L and Post-P were 83.1ng/ml, 153.5ng/ml and 88.0ng/ml respectively. A positive correlation was demonstrated between Pre-P and IP-L levels (correlation coefficient r= 0.478, p=0.007). A significant overall survival (OS) and disease-free survival (DFS) was recorded for patients with cfDNA level cut-offs at 125ng/ml, 175ng/ml and 100ng/ml respectively for Pre-P, IP-L and Post-P. The area under the curve (AUC) for IP-L with DFS was found to be at a significant range (AUC=0.901, Standard error rate=0.050). Tumors with stage >T2 produced significantly more cfDNA levels in IP-L (p=0.033). The median OS was 23.7 months. Patients with raised cfDNA in Pre-P (>125ng/ml) and IP-L (>175ng/ml) had a significantly poorer 2-year OS, p=0.026 and p=0.037 respectively. The hazards (OS) were also higher for those with raised cfDNA in IP-L (HR=6.821, 95%CI=0.989-12.796, p=0.050). The median DFS was 16.9 months. A raised IP-L (>175ng/ml) correlated significantly with poorer DFS at 2-years (p=0.003) and a significant increase in hazards of DFS (HR=11.455, 95% CI=1.395-24.434, p=0.023). Multivariate analysis suggested higher IP-L as a poor prognostic factor for both OS and DFS.
Conclusions
Among patients with operable ADCL, cfDNA in pleural lavage can be a reliable biomarker for both recurrence and overall survival, with IP-L cfDNA levels possibly a better indicator than plasma cfDNA levels.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
- Marco Filetti (Rome, Italy)
- Marco Filetti (Rome, Italy)
- Pasquale Lombardi (Rome, Italy)
- Rosa Falcone (Rome, Italy)
- Francesco Paroni Sterbini (Rome, Italy)
- Gennaro Daniele (Rome, Italy)
8P - Clinical trial design in the era of precision oncology: an overview of the last 20 years
Abstract
Background
The recent advent of the “precision oncology” model changed the face of modern drug development. The chance of quickly carrying out extensive molecular profiling and coupling driver mutations to specific selective inhibitors fostered the advent of new methodologies and trial designs. We systematically reviewed the precision oncology trials published in the last 20 years.
Methods
We included all the precision oncology trials published between January 2000 and June 2021. We collected data about screened patients, enrolled patients, overall response rate (ORR), progression-free survival (PFS), overall survival (OS), toxicities, and quality of life (QoL).
Results
In the examined period, 34 papers were published for 27 different trials. Most of the studies (82%) had a basket design, while five studies used an umbrella design, and only one a platform design. Interestingly, most of the studies were non-randomized (81%). In total, 20,790 patients were screened, with an average of 990 (35 - 5,548) patients per study. The average duration of the enrollment phase was approximately 32 (9-88) months. Overall, 3,865 patients were enrolled (18% of screened patients), with an average of 114 (10 - 514) patients per study. An ORR was recorded in 426 patients (11% of enrolled patients, 2% of screened patients) with a mean of 12 patients per single study. Toxicity data were included in 26 publications (76%), while none of the publications had the patient-reported quality of life data. Finally, we found that 23 trials (67%) used ORR as the primary endpoint, 31 publications (91%) reported PFS data, while only 18 publications (52%) reported OS data.
Conclusions
In this analysis, we intended to offer a snapshot of the results produced by precision oncology studies over the past twenty years. In total, these studies enrolled a low percentage of patients, less than 20%. Moreover, we show that most of the trials evaluated ORR as a primary endpoint, and in about half of the publications, no data of OS was reported. In conclusion, despite the vast effort produced in the screening phase, precision oncology trials had modest results and often reported incomplete data regarding OS, toxicity, and QoL.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
- Jose Carlos Benitez Montanez (Villejuif, France)
- Jose Carlos Benitez Montanez (Villejuif, France)
- Arthur Geraud (Villejuif, France)
- Matthieu Texier (Villejuif, France)
- Christophe Massard (Villejuif, France)
- Angelo Paci (Villejuif, France)
- Jean-Charles Soria (Villejuif, CE, France)
- Benjamin Besse (Villejuif, CE, France)
9P - Late phase 1 studies: concepts and outcomes of a new clinical trial design
Abstract
Background
Targeted therapies have become cornerstone treatments for many cancers harboring oncogenic addictions. The emergence of tumor-resistant mechanisms paved the way for next-generation inhibitors. Insufficient concentrations of targeted therapies is a frequent but poorly explored mechanism of treatment failure. We propose a new concept in clinical development, the late phase I trial, to restore drug efficacy at the time of failure at the standard dose.
Methods
The primary goal of these studies is to define a new maximal tolerated dose (MTD) of a drug in chronically-exposed patients (MTDc). Eligible patients (pts) must be still on treatment with the standard dose of the drug, experienced initial benefit and subsequently progressed without an identified resistance alteration. Groups composed of six pts will assess the best MTDc as a new late phase I recommended standard dose. The first group will initially be treated with a ‘dose level 1’, corresponding to the standard approved dose by regulatory agencies plus a predetermined dose increase. If no dose limiting toxicity (DLT) is reported after one DLT assessment window (DAW), these first six pts will move forward to dose level 2, and six new pts will be included at the second dose escalation level moving forward to dose level 3 (dose level 2 dose plus predetermined increase dose) after one DAW without reporting any DLT. Groups of six pts will start the study from sequentially established dose levels until the maximal determined late dose. The highest dose escalation level is defined by the highest administered dose experimental drug with unacceptable toxicity (≥33% of DLT events among 12 patients) and represents the last dose increase level. Unique DLTcs will be described for each subgroup.
Results
Along with the definition of MTDc, these trials will determine a late effective dose (LED) in pts, defining the optimal scheme for a rapid intra-patient dose escalation and hopefully reverse drug resistance.
Conclusions
Late phase I trials could be a new approach to restore the response to a drug by intra-patient dose escalation in cases of relapse without evidence of resistance mutations.
Legal entity responsible for the study
Gustave Roussy Cancer Center.
Funding
Has not received any funding.
Disclosure
C. Massard: Financial Interests, Personal, Advisory Board: AstraZeneca; Financial Interests, Personal, Advisory Board: Amgen; Financial Interests, Personal, Advisory Board: Astellas; Financial Interests, Personal, Advisory Board: Bayer; Financial Interests, Personal, Advisory Board: BMS; Financial Interests, Personal, Advisory Board: Celgene; Financial Interests, Personal, Advisory Board: Janssen; Financial Interests, Personal, Advisory Board: Lilly; Financial Interests, Personal, Advisory Board: Sanofi; Financial Interests, Personal, Advisory Board: Roche; Financial Interests, Personal, Advisory Board: Pfizer. A. Paci: Financial Interests, Personal, Advisory Board: Fresenius; Financial Interests, Personal, Advisory Board: Pierre Fabre; Financial Interests, Personal, Advisory Board: Pfizer; Financial Interests, Personal, Expert Testimony: Servier. J-C. Soria: Financial Interests, Personal, Advisory Board: AstraZeneca; Financial Interests, Personal, Advisory Board: Daiichi Sankyo; Financial Interests, Personal, Funding: Gritstone; Financial Interests, Personal, Advisory Board: Hookipa Pharmaceuticals. B. Besse: Financial Interests, Personal and Institutional, Research Grant: AstraZeneca; Financial Interests, Personal and Institutional, Research Grant: Amgen; Financial Interests, Personal and Institutional, Research Grant: BMS; Financial Interests, Personal and Institutional, Research Grant: MSD. All other authors have declared no conflicts of interest.
- Aram A. Musaelyan (Sochi, Russian Federation)
- Aram A. Musaelyan (Sochi, Russian Federation)
- Sergey Lapin (Saint Petersburg, Russian Federation)
- Vladimir Nazarov (Saint Petersburg, Russian Federation)
- Sergey Vorobyev (Saint Petersburg, Russian Federation)
- Alexander Zakharenko (Saint Petersburg, Russian Federation)
- Sergey V. Orlov (Saint Petersburg, Russian Federation)
10P - Clinical and morphological pattern of malignant tumors with microsatellite instability
Abstract
Background
Solid tumors with microsatellite instability (MSI), regardless of location, are highly susceptible to immune checkpoint inhibitors. The aim of the study was to investigate clinical and morphological features of tumors with MSI.
Methods
The study included 787 tumor samples of the following localizations: 530- colorectal cancer (CRC), 95- endometrial carcinoma (EC), 87- gastric cancer (GC), 20- ovarian cancer, 18- pancreatic cancer, 15- cervical cancer, 15- esophageal cancer, 7- cancers of unknown primary site. The study of MSI was carried out using fragment analysis by determining mononucleotide markers: BAT-25, BAT-26, NR-21, NR-24, NR-27. Data of preoperative level of CEA and CA19-9 were obtained in 185 patients with CRC.
Results
The prevalence of MSI in CRC was 6.8%, in EC- 27.4%, in GC - 6.9%, in ovarian cancer - 5%. MSI was not found in other localizations. The characteristic clinical and morphological features of MSI-positive CRC were younger age (p=0.032), right-sided localization (p<0.0001), presence of multiple primary tumors (p=0.041), absence of distant metastases (p=0.013), presence of carcinoma G3 (p=0.0008), mucinous component (p<0.0001), Crohn-like reaction (p=0.0063) and tumor-infiltrating lymphocytes (p<0.0001). Also, in patients with CRC with MSI, the preoperative level of CEA was lower than in patients with MSS tumors: the median was 2.0 ngml (interquartile range (IQR): 0.7-3.4; n=20) and 3.9 ng/ml (IQR: 1.1-13.1; n=165), respectively (p=0.0061). No differences in smoking status, tumor size and the presence of diseases associated with an increase of CEA were shown between the MSI and MSS CRC. For EC with MSI, there were the following features: endometrioid adenocarcinoma (p=0.017), high grade tumors (p=0.0054), presence of cribriform growth pattern (p=0.0084) and tumor-infiltrating lymphocytes (p=0.0019), as well as a higher level of mitotic activity (p=0.002). MSI-positive GC was more often found in women (p=0.033), was characterized by older age (p=0.001), distal tumor localization (p=0.022), presence of high-grade tumors (p=0.012) and tumor-infiltrating lymphocytes (p=0.009).
Conclusions
Common features for CRC, EC and GC with MSI are the presence of a high-grade tumors and tumor-infiltrating lymphocytes.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
- Sourav K. Mishra (Bhubaneswar, India)
- Sourav K. Mishra (Bhubaneswar, India)
- Sambit K. Mohanty (Bhubaneswar, India)
11P - ROS1-gene rearranged lung adenocarcinomas: Demographic, clinicopathologic, and treatment profile in a cohort of indian patients
Abstract
Background
ROS1 translocations are seen in 1%-2% of non-small cell lung cancer (NSCLC) patients. There is limited data on the clinicopathologic profile of ROS1 translocated NSCLC.
Methods
The study included 409 patients with NSCLC who were referred for molecular testing. Fluorescent in situ hybridisation (FISH) assays were performed to detect ROS1 gene rearrangements on 3-5μm tissue section from formalin-fixed-paraffin embedded (FFPE) tumor tissue. ZytoLight SPEC ROS1 Dual Color Break Apart FISH Probe (ZytoVision, Germany) was used. Clinicopathologic profiles of the FISH-positive patients were documented.
Results
Out of 409 cases of stage IV NSCLC, 18 (4.4%) cases were positive for a ROS1 gene rearrangement. Of the positive cases 11 were females and 7 were males. Smoking history was known for 11 patients of which 2 were smokers (all males) and 9 were non-smokers (7 females and 2 males). The median age was 49 years (range 28 - 65 years). The histopathology was adenocarcinoma in all cases with the solid subtype of adenocarcinoma being the most common histologic subtype (6 cases) followed by solid type with macronuclei (5 cases). Fifteen patients were treated with crizotinib of whom 4 received the drug in the first-line and 11 in the second-line. The overall response rate for crizotinib was 10/15 (66.6%) all of which were partial responses (PR). The disease control rate (PR + stable disease) was 14/15 (93.3%). One patient had disease progression on first-line crizotinib. The median duration of response was 9 months (range 1 to 19 months). After progression on crizotinib; immunotherapy with pembrolizumab was given in 3 patients with PD-L1 IHC of 13%, 65% and 5%. Peripheral edema was the most common toxicity with crizotinib and was reported in 6 (40%) of the patients.
Conclusions
ROS-1 rearranged NSCLC represents 4% of all advanced stage NSCLC patients. Most patients were females, non-smokers and are diagnosed at a younger age (median 49years) compared to NSCLC with other driver mutations. Most patients present in an advanced stage. The response rates to crizotinib (most commonly used drug) is 66.6% with all of them being partial responses. Crizotinib is well tolerated in our cohort of patients.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
- Miriam Dorta Suarez (Madrid, Spain)
- Miriam Dorta Suarez (Madrid, Spain)
- Beatriz Jimenez Munarriz (Madrid, Spain)
- Anabel Del Barrio (Madrid, Spain)
- Gema Garcia Ledo (Madrid, Spain)
- Rocio Blanco Blanco (Madrid, Spain)
- Esther Conde Gallego (Madrid, Spain)
- Susana Hernandez Prieto (Madrid, Spain)
- Fernando Lopez Rios (Madrid, Spain)
- Antonio Cubillo Gracián (Madrid, Spain)
12P - Molecular features of KRAS mutant NSCLC: weaving a future score for immune-check point inhibitors (ICI).
Abstract
Background
KRAS mutation is present in almost 33% of NSCLC patients. Retrospective trials have shown a tendency of higher efficacy of ICI in this subgroup, and prospective trials with KRAS inhibitors are emerging. If KRAS could take part as a biomarker score for ICI or KRAS inhibitors efficacy is still unknown.
Methods
A retrospective analysis was done in our center, from all NSCLC patients with either tissue DNA and/or ctDNA NGS analyses, treated with schemes including ICI. NGS methods included: Oncomine V3.0, Guardant 360, and Foundation liquid.
Results
Two hundred one patients had NGS done with 51(25.4%) with KRAS mutation detected. Median age was 62 years old, and 53% had PDL1 >1%, within 21% with >=50%. High CD8 T Cell infiltration was detected in 18% but was unknown in 51%. KRAS most frequent mutations detected were G12C (43,9%) and G12D (17,1%). TP53 co-mutation was present in 29% (KP group), NF1 in 11.3% and STK11 in 9,7% (KL group). Most KRAS G12C, had PDL1 positive (69%) and 25% had PDL1 >=50%. TILs infitration in 25% with high infiltration KL group had PDL1 positive in 20% (anyone with PDL1 50%) and without CD8 T-cell infiltration. A combination of chemo-immunotherapy (anti-PDL1) was administered in 26% of all, and chemotherapy monotherapy in 53%. Patients KRASmut and PDL1 positive, showed better median OS than PDL1 negative (28 vs 21,9 months, p=0,25), and those with PDL1 >=50% expression reached median survival of 39 months. Patients KRASmut and PDL1 negative, obtained similar low survival rates regardless of treatment (OS 15%). In KP group, PDL1 negative showed mOS of 12 months compared to 21 months if PDL1 positive. Survival was lower in STK11mut respect to STK11wt (17 vs 24,8 months). In KL group, treatment did not affect survival (mOS 10 months). Globally, more than one co-mutation tended to worse survival (14 months).
Conclusions
Our sample represents general NSCLC patients. KP group shows an immune phenotype (high PDL1, CD8 Tcells infiltration) and better survival rates for ICI included therapy. KL group is a challenging group without real ICI efficacy and results from KRAS inhibitors early trials have shown major benefit in this group. Our study shows a potential molecular score to select treatment. A wider sample is expected to support this observation.
Legal entity responsible for the study
HM CIOCC.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
- Maxim Ivanov (Dolgoprudny, Russian Federation)
- Maxim Ivanov (Dolgoprudny, Russian Federation)
- Alexandra Lebedeva (Moscow, Russian Federation)
- Daria Seriak (Moscow, Russian Federation)
- Ekaterina Rozhavskaya (Moscow, Russian Federation)
- Margarita Sharova (Moscow, Russian Federation)
- Divyasphoorthi Vardhan (Fairfax, VA, United States of America)
- Ancha Baranova (Fairfax, United States of America)
- Julia Shaykhutdinova (Moscow, Russian Federation)
- Vladislav Mileyko (Moscow, Russian Federation)
13P - Incidental germline findings from tumor molecular profiling for precision oncology: is it common and how to manage?
Abstract
Background
A fraction of patients referred for tumor-only complex molecular profiling may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Bioinformatic management and reporting of such incidental germline findings are not standardized.
Methods
Data from NGS sequencing of tumor-only samples from patients referred for complex molecular profiling were analyzed in order to identify germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. If possible, variant origin was validated by Sanger sequencing using patients’ normal tissue. Variants’ pathogenicity was assessed according to ACMG/AMP.
Results
NGS data from 183 patients (75 men [41.0%]; mean [SD] age, 57.7 [13.3] years) were obtained. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). We detected 56 sequencing variants (40 patients) in genes associated with HCS. Of them, 17 (14 patients) were predicted to be of germline origin with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV) and 9 as variants of uncertain significance (VUS). Bioinformatics prediction of variant origin was concordant with manual curation for the 41 (97%) missense variants in HCS associated genes. Based on the results of our study we estimate that Sanger sequencing using a patient's normal tissue would be required in ∼1-7% of cases (PV or LPV found in HCS genes) while referring for genetic counseling in ∼2-15% of cases (PV, LPV or VUS found in HCS genes).
Conclusions
Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of variants in genes associated with HCS.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
E. Rozhavskaya, M. Sharova, J. Shaykhutdinova, V. Mileyko: Financial Interests, Personal, Affiliate: Atlas Oncology Diagnostics. A. Baranova: Financial Interests, Institutional, Advisory Board: Atlas Oncology Diagnostics. All other authors have declared no conflicts of interest.
- Jiwei Liu (Dalian City, China)
- Jiwei Liu (Dalian City, China)
- Aman Wang (Dalian city, China)
- Dario Trapani (Rome, Italy)
- Xiuhua Sun (Dalian city, China)
- Xiu Shan (Dalian city, China)
- Hamzah Al-Madani (Beijing, China)
- Mohammed Hussein Omar Safi (Dalian city, China)
14P - Identification of age- associated genes as prognostic factors in non-small cell lung cancer
Abstract
Background
The inevitability of a time-dependent decline in physiological organ performance as we age is a major risk factor for cancer development. As a result, the population is changing, with a growing number of people at risk of acquiring cancer. Cell senescence is one of the hallmarks where cancer and aging are fundamentally different as accumulating DNA damage usually will cause an upregulation of cell cycle inhibitors leading to senescence or apoptosis while malignant cells avoid this by generating additional mutations such as deletion of tumor suppressors.
Methods
Our study reveals new ageing genes model for non-small cell lung cancer NSCLC patients. Researchers from the Genomic Data Commons (GDC, accessible via the portal: https://portal.gdc.cancer.gov/) managed to collect gene expression data from NCLC tissues third level. Transcriptomic analysis from The Cancer Genome Atlas TCGA and matching ageing genes to find new ageing genes signature for both lung squamous cell cancer LUSC and lung adenocarcinoma LUAD.
Results
For LUSC, ANKLE1, and LRRK2, and SMC6, and KRT16 with AUC=96%. For LUAD type TERT, HMGA2, CAV1, KRT16 and CDK1 with AUC=84 %. These signature models consistently showed significance by Cox regression in overall survival for LUSC and LUAD (P=0.003, HR=1.53, CI = 1.15-2.05) and (P=0.008, HR=1.56, CI = 1.12—2.17) respectively. The LUSC gene signature was connected with the biological process of aging, cell aging, cellular senescence, and cell aging regulation, whilst KEGG pathways were largely associated with cellular senescence and cell cycle. Furthermore, LUAD biological activities include enzyme binding, transcription factor binding, and catalytic activity on DNA, whereas the gene signature model is significantly associated with cell cycle and cellular senescence on KEGG pathways.
Conclusions
The novel signature model proposed showed significant effectiveness against several non-small cell lung cancer subgroups. Future research is needed to determine the therapeutic use of biomarkers in personalized NSCLC care with monotherapy or in combination with chemotherapy.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
- Raphael Ari (Tel Aviv, Israel)
- Raphael Ari (Tel Aviv, Israel)
- Elizabeth Dudnik (Petah Tikva, Israel)
- Dov Hershkovitz (Tel Aviv, Israel)
- Suyog S. Jain (Singapore, Singapore)
- Lior Soussan-Gutman (Tel-Aviv, Israel)
- Taly Ben Shitrit (Tel-Aviv, Israel)
- Hovav Nechushtan (Jerusalem, Israel)
- Nir Peled (Jerusalem, Israel)
- Abed Agbarya (Haifa, Israel)
15P - FGFR3-TACC3 fusion (F) as an acquired resistance mechanism following treatment with EGFR TKIs and a suggested novel target in aNSCLC
Abstract
Background
Fusion between FGFR3 and TACC3 represents a rare acquired resistance mechanism following treatment with EGFR TKIs. Data regarding its prevalence and therapeutic implication is limited.
Methods
Guardant Health (GH) clinical electronic database (ED) (11/2016-07/2021) was evaluated for cases of aNSCLC and FGFR2/3 F; prevalence FGFR2/3 F with and without a co-existing EGFR M was assessed (we hypothesized that cases with co-existing FGFR2/3 F and EGFR M reflect the cases of FGFR-driven resistance following EGFR TKIs). ED of Tel-Aviv Sourasky Medical Center (TASMC, a referral center for upfront molecular testing; 161 aNSCLC patients (pts) included in 06/2020-06/2021) was evaluated for cases of aNSCLC and de novo FGFR1/2/3 F; prevalence of de novo FGFR1/2/3 F with or without EGFR M was assessed. Pts with EGFR M aNSCLC progressing on EGFR TKIs that developed an FGFR3-TACC3 F were selected from the ED of Davidoff Cancer Center (DCC) and Oncology Department, Bnei-Zion hospital (BZ) (04/2014-04/2021, n=3). Clinico-pathological pt characteristics, systemic therapies and outcomes were assessed.
Results
In GH database, the prevalence of FGFR2 F and FGFR3 F were 0.02% and 0.24%, respectively. Of FGFR3 F, 99.3% were FGFR3-TACC3 F. Of FGFR3-TACC3 F, EGFR M co-existed in 22.6% (exon 19 del, 64%; L858R, 33%, L861Q, 3%). In TASMC, 1 case of de novo FGFR3-TACC3 F (without EGFR M) was detected (prevalence, 0.62%). Characteristics of the 3 selected pts from DCC and BZ ED are provided in the table. Combination of EGFR TKI + FGFR TKI was initiated in 2 pts: 1st pt achieved a partial response with gefitinib + erdafitinib for 7+ months at the time of the report; 2nd pt recently initiated osimertinib+erdafitinib. No safety signals were seen.
Pt Sex Age Previous therapy EGFR M type FGFR3-TACC3 detection method FGFR3-TACC3 F 1 F 64 Gefitinib, osimertinib L858R Guardant 360 0.3 2 F 64 Gefitinib, osimertinib L747_A750delinsP Guardant 360 0.07 3 M 85 Osimertinib E746_A750del Guardant 360 0.04
Conclusions
Up to 23% of FGFR3-TACC3 F in aNSCLC are associated with acquired resistance following treatment with EGFR TKIs. In this clinical scenario, combination of EGFR TKI and FGFR TKI represents a promising treatment strategy.
Legal entity responsible for the study
Israel Lung Cancer Group; Guardant Health.
Funding
Has not received any funding.
Disclosure
E. Dudnik: Financial Interests, Personal, Invited Speaker: Roche; Financial Interests, Personal, Invited Speaker: BI; Financial Interests, Personal, Research Grant: AZ; Financial Interests, Personal, Invited Speaker: Pfizer; Financial Interests, Personal, Invited Speaker: MSD. S.S. Jain: Financial Interests, Personal, Full or part-time Employment: Guardant Health Pte. Ltd. All other authors have declared no conflicts of interest.
- Izzet Dogan (Istanbul, Turkey)
- Izzet Dogan (Istanbul, Turkey)
- Nijat Khanmamadov (Istanbul, Turkey)
- Nail Paksoy (Istanbul, Turkey)
- Sezai Vatansever (Istanbul, Turkey)
- Pinar Saip (Istanbul, Turkey)
- Adnan Aydiner (Istanbul, Turkey)
16P - Evaluation of the Relationship between Clinicopathological Features at Diagnosis, and Acquisition of T790M Resistance Mutation in Patients with EGFR-mutant Metastatic Lung Cancer
Abstract
Background
Data of the acquisition of T790M resistance mutation in patients with EGFR-mutant metastatic lung cancer is limited. This study aimed to assess the relationship between clinicopathological features at diagnosis, and acquisition of T790M mutation in patients with EGFR-mutant metastatic non-small cell lung cancer.
Methods
We evaluated the EGFR-mutant metastatic lung cancer patients' data who progressed under first-line treatment with tyrosine kinase inhibitors and acquired T790M resistance mutation retrospectively. Survival analyses were assessed with Kaplan-Meier and Cox-regression methods. The relationship between the acquisition of T790M mutation and clinicopathological parameters was evaluated with logistic regression analysis.
Results
Fifty-two patients were included in the study. The median age was 58 (range, 33-78) years. The proportion of female patients was 53.2%. The proportions of exon 19, exon 21, and rare mutations were 68.7%, 23.5%, and 7.8%, respectively. Forty-five (86.5%) patients were de-novo metastatic. The proportion of patients who had one, two, and three or more metastatic sites at diagnosis were 25.5%, 41.3%, and 33.2%, respectively. The proportio of brain, liver and adrenal gland metastasis were 29.4%, 13.7%, and 7.8%, respectively. All patients received tyrosine kinase inhibitors. After the disease progressed, the acquisition of T790M mutation was detected with liquid (75.5%) or standard biopsies (24.5%). T790M mutations were detected in 33 (63.5%) patients. In logistic regression analysis, age, gender, de-novo metastatic disease, number of metastatic sites, primary tumor localization (left or right lung), and type of tyrosine kinase inhibitor was not statistically significant for the acquisition of T790M mutations.
Conclusions
Due to rarity, the data on the acquisition of T790M mutations are limited. In this study, we showed that clinicopathological features were not related to the acquisition of T790M mutations.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
- Ning Jia (Beijing, China)
- Ning Jia (Beijing, China)
- Shanshan Zhang (Beijing, China)
- Yonglei Shi (Beijing, China)
- Xiaohua Shi (Beijing, China)
- Chunmei Bai (Beijing, China)
17P - Genomic profiling of circulating tumour DNA in East Asian head and neck squamous cell carcinoma
Abstract
Background
Novel effective therapy is limited in head and neck squamous cell carcinoma (HNSCC). Next generation sequencing (NGS) with sophisticated bioinformatics allows the distinct identification of tumour-specific DNA mutations in circulating tumor DNA (ctDNA). CtDNA may represent the real-time genomic profile and biology of cancers to be treated. Identification of molecular characterization of ctDNA may potentially provide a way to precisely treat the patients with novel options.
Methods
We performed a retrospective analysis of East Asian patients with HNSCC who underwent molecular profiling of plasma samples utilizing a panel covering 1021-gene next generation sequencing (NGS) platform. Tumour mutation burden (TMB) analysis interrogated single-nucleotide variants (SNVs) and small indels with the variant allele frequency (VAF) ≥ 0.5%. TMB-H was defined as the top quartile of all TMB values.
Results
We identified 45 patients with ctDNA-based genomic profiling, including the primary tumour sites of the oral cavity (n = 15, 33.3%), oropharynx (n= 10, 22.2%), larynx (n = 11, 24.4%), and hypopharynx (n = 9, 20.0%). Median age was 61, 80% were male. Fifty-one plasma samples were collected. Median TMB value was 3.00 mutations/megabase (Mb) [interquartile range (IQR): 2.00–9.00 mutations/Mb] and 9 patients (20.0%) had a TMB ≥ 9.00 mutations/Mb (TMB-H). A total of 190 genetic alterations were identified. The most common altered genes identified by ctDNA analysis were TP53 (n = 24,53.3%), MLL2 (n = 7, 15.6%), and PIK3CA (n = 6, 13.3%). The other genes altered in at least 5% of patients included APC, FAT1, CDK13, MLL3, ARID1A, NCOR1, NOTCH3, PTEN, ATM, BRD2, CDKN2A, CIC, EP300, FANCA, FAT2, FGFR1, LRP1B, MSH3, NBN, PPM1D, RB1, and TERT. Patients with TMB-H had been identified genetic alteration of either MLL3, NOTCH3, BRD2, or FANCA genes.
Conclusions
Analysis of ctDNA may provide novel and clinically relevant insights into precise therapeutic decisions in HNSCC. Some genetic mutation might potentially associate with high TMB status. The potential utility and validity of large-scale ctDNA genomic profiling approaches should be explored in future studies.
Legal entity responsible for the study
Department of Medical Oncology, Peking Union Medical College Hospital.
Funding
CAMS Innovation Fund for Medical Sciences (No. 2016-I2M-1-001).
Disclosure
S. Zhang, Y. Shi: Financial Interests, Personal, Full or part-time Employment: Geneplus-Beijing. All other authors have declared no conflicts of interest.