Tumor Content Research Articles

Deciphering resistance mechanisms in cancer: final report of MATCH-R study with a focus on molecular drivers and PDX development

BackgroundUnderstanding the resistance mechanisms of tumor is crucial for advancing cancer therapies. The prospective MATCH-R trial (NCT02517892), led by Gustave Roussy, aimed to characterize resistance mechanisms to cancer treatments through molecular analysis of fresh tumor biopsies. This report presents the genomic data analysis of the MATCH-R study conducted from 2015 to 2022 and focuses on targeted therapies.MethodsThe study included resistant metastatic patients (pts) who accepted an image-guided tumor biopsy. After evaluation of tumor content (TC) in frozen tissue biopsies, targeted NGS (10 < TC < 30%) or Whole Exome Sequencing and RNA sequencing (TC > 30%) were performed before and/or after the anticancer therapy.Patient-derived xenografts (PDX) were established by implanting tumor fragments into NOD scid gamma mice and amplified up to five passages.ResultsA total of 1,120 biopsies were collected from 857 pts with the most frequent tumor types being lung (38.8%), digestive (16.3%) and prostate (14.1%) cancer. Molecular targetable driver were identified in 30.9% (n = 265/857) of the patients, with EGFR (41.5%), FGFR2/3 (15.5%), ALK (11.7%), BRAF (6.8%), and KRAS (5.7%) being the most common altered genes. Furthermore, 66.0% (n = 175/265) had a biopsy at progression on targeted therapy. Among resistant cases, 41.1% (n = 72/175) had no identified molecular mechanism, 32.0% (n = 56/175) showed on-target resistance, and 25.1% (n = 44/175) exhibited a by-pass resistance mechanism. Molecular profiling of the 44 patients with by-pass resistance identified 51 variants, with KRAS (13.7%), PIK3CA (11.8%), PTEN (11.8%), NF2 (7.8%), AKT1 (5.9%), and NF1 (5.9%) being the most altered genes. Treatment was tailored for 45% of the patients with a resistance mechanism identified leading to an 11 months median extension of clinical benefit.A total of 341 biopsies were implanted in mice, successfully establishing 136 PDX models achieving a 39.9% success rate. PDX models are available for EGFR (n = 31), FGFR2/3 (n = 26), KRAS (n = 18), ALK (n = 16), BRAF (n = 6) and NTRK (n = 2) driven cancers. These models closely recapitulate the biology of the original tumors in term of molecular alterations and pharmacological status, and served as valuable models to validate overcoming treatment strategies.ConclusionThe MATCH-R study highlights the feasibility of on purpose image guided tumor biopsies and PDX establishment to characterize resistance mechanisms and guide personalized therapies to improve outcomes in pre-treated metastatic patients.Graphical

2272P Minimal DNA-methylation (DNAm) signatures for non-invasive tumor-agnostic estimation of tumor content (TC) and molecular subtype in patients (pts) with metastatic breast cancer (mBC)

2272P Minimal DNA-methylation (DNAm) signatures for non-invasive tumor-agnostic estimation of tumor content (TC) and molecular subtype in patients (pts) with metastatic breast cancer (mBC)

Abstract 5066: Accurate detection of tumor sequence at low tumor content for MRD

Abstract Background Accurate detection of tumor sequence when the overall tumor content (TC) of the sample is low (&amp;lt;0.01%) is critical for tumor-informed minimal residual disease (MRD) monitoring. Current methodology generally relies on detection of multiple low-VAF (variant allele fraction) co-mutations. At low TC and low DNA input (&amp;lt;30ng, 9,000 genome equivalents), many variant sites are not expected to have any tumor-derived fragments or will be only marginally above background noise. A method that does not rely on the positive identification of mutations would be useful for detecting early disease recurrence. Methods We developed a maximum likelihood (ML) method for inferring the TC of MRD samples, rather than VAF at individual sites. This method considers the frequency of non-reference reads at each variant site along with estimated error rates. To evaluate our method at low TC, we carried out spike-in simulations of MRD samples across a range of sample TC from 0 to 0.1%. For each simulation, we randomly selected a single normal from a pool of sequenced normal samples to serve as background. Using this background, we randomly selected sites and mutations to represent somatic variants, sampled the existing noise at each site, and the number of ctDNA fragments and reads given the tumor content. Intrinsic error rates were modeled as either the mean error of the sample, the per-reference base error, or the mutation error. An additional randomly selected normal sample was used for extrinsic, per-site error estimates. We created contrived tumor-informed MRD samples by serial two-fold dilution of tumor DNA in a normal background (0.2%-0.0125% sample TC), followed by amplicon sequencing and characterization by our ML method. Results In our spike-in simulations, using 32 variants sites, we achieved 99% sensitivity in detecting tumor sequence at a TC of 0.01% (average ~1 tumor fragment per site), 73% sensitivity at 0.005% (average ~0.5 tumor fragments per site), and 99.9% specificity when using extrinsic error from a normal sample. At 16 sites we achieved 95% and 68% sensitivity respectively, and 99.6% specificity. Without the extrinsic error, specificity was greatly reduced to 71% (16 sites) and 77% (32 sites) at .005% TC. This highlights the advantage of extrinsic error in estimating low TC. In our contrived samples, we found that TC estimates from our ML approach correlated well with the expected values (r = 0.99). Conclusions With our approach, we were able to accurately quantify TC in both simulated and contrived samples. In simulated samples, we can detect TC well below 0.01% with high specificity and using only 16 sites. Importantly, the TC estimation does not rely on identifying individual positive sites. While modeling the intrinsic sequencing error rates in a sample does increase our ability to characterize TC, extrinsic, per-site error rates are needed to control false positives introduced by constitutively noisy sites. Citation Format: Andrew Conley, Huazhang Li, Alex V. Kotlar. Accurate detection of tumor sequence at low tumor content for MRD [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5066.

Decrease in tumor content assessed in biopsies is associated with improved treatment outcome response to pembrolizumab in patients with rare tumors

BackgroundDecreased tumor content (TC) in resection specimens after neoadjuvant therapy is used to predict prognosis. We investigated whether TC assessed in biopsy specimens or the shift in TC from baseline...

1886P - Prospective pathological experience with research biopsies in the context of clinical trials at Vall d’Hebron Institute of Oncology

1886P - Prospective pathological experience with research biopsies in the context of clinical trials at Vall d’Hebron Institute of Oncology

Prenatal Diagnosis of a Ranula With 2- and 3-Dimensional Sonography and Sonographically Guided Aspiration

Journal of Ultrasound in MedicineVolume 25, Issue 11 p. 1499-1502 Case Report Prenatal Diagnosis of a Ranula With 2- and 3-Dimensional Sonography and Sonographically Guided Aspiration Pedro Pires MD, PhD, Pedro Pires MD, PhD Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Search for more papers by this authorMayra Pereira MD, PhD, Mayra Pereira MD, PhD Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Search for more papers by this authorLuiz Machado MD, PhD, Luiz Machado MD, PhD Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Search for more papers by this authorFernando Bonilla-Musoles MD, PhD, Corresponding Author Fernando Bonilla-Musoles MD, PhD cegiob@interbook.net Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Address correspondence to Fernando Bonilla-Musoles, MD, PhD, Navarro Reverter 11, 46004 Valencia, Spain.Search for more papers by this author Pedro Pires MD, PhD, Pedro Pires MD, PhD Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Search for more papers by this authorMayra Pereira MD, PhD, Mayra Pereira MD, PhD Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Search for more papers by this authorLuiz Machado MD, PhD, Luiz Machado MD, PhD Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Search for more papers by this authorFernando Bonilla-Musoles MD, PhD, Corresponding Author Fernando Bonilla-Musoles MD, PhD cegiob@interbook.net Serviço de Medicina Fetal, Centro Integrado de Saúde Amaury de Medeiros/Universidade de Pernambuco, Recife, Brazil.Address correspondence to Fernando Bonilla-Musoles, MD, PhD, Navarro Reverter 11, 46004 Valencia, Spain.Search for more papers by this author First published: 01 November 2006 https://doi.org/10.7863/jum.2006.25.11.1499Citations: 10Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume25, Issue11November 2006Pages 1499-1502 RelatedInformation