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

BACKGROUND: Understanding 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. METHODS: The 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. RESULTS: A 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. CONCLUSION: The 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.

Understanding and Overcoming Resistance to Selective FGFR inhibitors Across FGFR2-Driven Malignancies.

PURPOSE: Understanding resistance to selective FGFR inhibitors is crucial to improve the clinical outcomes of patients with FGFR2-driven malignancies. EXPERIMENTAL DESIGN: We analyzed sequential ctDNA, +/- WES or targeted NGS on tissue biopsies from patients with tumors harboring activating FGFR2 alterations progressing on pan-FGFR-selective inhibitors, collected in the prospective UNLOCK program. FGFR2::BICC1 Ba/F3 and patient-derived xenografts (PDX) models were used for functional studies. RESULTS: Thirty-six patients were included. In cholangiocarcinoma, at resistance to both reversible inhibitors (e.g. pemigatinib, erdafitinib) and the irreversible inhibitor futibatinib, polyclonal FGFR2 kinase domain mutations were frequent (14/27 patients). Tumors other than cholangiocarcinoma shared the same mutated FGFR2 residues, but polyclonality was rare (1/9 patients). At resistance to reversible inhibitors, 14 residues in the FGFR2 kinase domain were mutated; after futibatinib, only the molecular brake N550 and the gatekeeper V565. Off-target alterations in PI3K/mTOR and MAPK pathways were found in 11 patients, often together with on-target mutations. At progression to a first FGFR inhibitor, 12 patients received futibatinib or lirafugratinib (irreversible inhibitors), with variable clinical outcomes depending on previous resistance mechanisms. Two patients with TSC1 or PIK3CA mutations benefitted from everolimus. In cell viability assays on Ba/F3 and in pharmacologic studies on PDX, irreversible inhibitors retained better activity against FGFR2 kinase domain mutations, with lirafugratinib active against the recalcitrant V565L/F/Y. CONCLUSIONS: At progression to FGFR inhibitors, FGFR2-driven malignancies are characterized by high intra- and inter-patient molecular heterogeneity, particularly in cholangiocarcinoma. Resistance to FGFR inhibitors can be overcome by sequential, molecularly-oriented treatment strategies across FGFR2-driven tumors.

NVL-655 Is a Selective and Brain-Penetrant Inhibitor of Diverse ALK-Mutant Oncoproteins, Including Lorlatinib-Resistant Compound Mutations.

Three generations of tyrosine kinase inhibitors (TKI) have been approved for anaplastic lymphoma kinase (ALK) fusion-positive non-small cell lung cancer. However, none address the combined need for broad resistance coverage, brain activity, and avoidance of clinically dose-limiting TRK inhibition. NVL-655 is a rationally designed TKI with >50-fold selectivity for ALK over 96% of the kinome tested. In vitro, NVL-655 inhibits diverse ALK fusions, activating alterations, and resistance mutations, showing ≥100-fold improved potency against ALKG1202R single and compound mutations over approved ALK TKIs. In vivo, it induces regression across 12 tumor models, including intracranial and patient-derived xenografts. NVL-655 inhibits ALK over TRK with 22-fold to >874-fold selectivity. These preclinical findings are supported by three case studies from an ongoing first-in-human phase I/II trial of NVL-655 which demonstrate preliminary proof-of-concept clinical activity in heavily pretreated patients with ALK fusion-positive non-small cell lung cancer, including in patients with brain metastases and single or compound ALK resistance mutations. Significance: By combining broad activity against single and compound ALK resistance mutations, brain penetrance, and selectivity, NVL-655 addresses key limitations of currently approved ALK inhibitors and has the potential to represent a distinct advancement as a fourth-generation inhibitor for patients with ALK-driven cancers.

Development of Novel Models of Aggressive Variants of Castration-resistant Prostate Cancer.

BACKGROUND: Genomic studies have identified new subsets of aggressive prostate cancer (PCa) with poor prognosis (eg, neuroendocrine prostate cancer [NEPC], PCa with DNA damage response [DDR] alterations, or PCa resistant to androgen receptor pathway inhibitors [ARPIs]). Development of novel therapies relies on the availability of relevant preclinical models. OBJECTIVE: To develop new preclinical models (patient-derived xenograft [PDX], PDX-derived organoid [PDXO], and patient-derived organoid [PDO]) representative of the most aggressive variants of PCa and to develop a new drug evaluation strategy. DESIGN, SETTING, AND PARTICIPANTS: NEPC (n = 5), DDR (n = 7), and microsatellite instability (MSI)-high (n = 1) PDXs were established from 51 patients with metastatic PCa; PDXOs (n = 16) and PDOs (n = 6) were developed to perform drug screening. Histopathology and treatment response were characterized. Molecular profiling was performed by whole-exome sequencing (WES; n = 13), RNA sequencing (RNA-seq; n = 13), and single-cell RNA-seq (n = 14). WES and RNA-seq data from patient tumors were compared with the models. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Relationships with outcome were analyzed using the multivariable chi-square test and the tumor growth inhibition test. RESULTS AND LIMITATIONS: Our PDXs captured both common and rare molecular phenotypes and their molecular drivers, including alterations of BRCA2, CDK12, MSI-high status, and NEPC. RNA-seq profiling demonstrated broad representation of PCa subtypes. Single-cell RNA-seq indicates that PDXs reproduce cellular and molecular intratumor heterogeneity. WES of matched patient tumors showed preservation of most genetic driver alterations. PDXOs and PDOs preserve drug sensitivity of the matched tissue and can be used to determine drug sensitivity. CONCLUSIONS: Our models reproduce the phenotypic and genomic features of both common and aggressive PCa variants and capture their molecular heterogeneity. Successfully developed aggressive-variant PCa preclinical models provide an important tool for predicting tumor response to anticancer therapy and studying resistance mechanisms. PATIENT SUMMARY: In this report, we looked at the outcomes of preclinical models from patients with metastatic prostate cancer enrolled in the MATCH-R trial (NCT02517892).