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. Author manuscript; available in PMC: 2026 Feb 18.
Published before final editing as: Clin Cancer Res. 2026 Jan 15:10.1158/1078-0432.CCR-25-4382. doi: 10.1158/1078-0432.CCR-25-4382

Landscape of Genomic Mechanisms of Resistance to Selective RET Inhibitors in RET-Altered Solid Tumors: Analysis of the RETgistry Global Consortium

Sarah Waliany 1, Alissa J Cooper 2,3, Stephen V Liu 4, Oliver Gautschi 5,6, Julia K Rotow 7, Katherine Emilie Rhoades Smith 8, Urs M Weber 9, Dae Ho Lee 10, Herbert H F Loong 11, Jyoti D Patel 12, Nathan A Pennell 13, Misako Nagasaka 14, Shetal A Patel 15, Daniel SW Tan 16, Benjamin J Solomon 17, Tae Min Kim 18, Georg Pall 19, Jonathan W Riess 20, Lova Sun 21, Martin Früh 22,23, Natalie F Uy 24, Shirish Gadgeel 25, Jamie Feng 26, Andrew Do 1, Christina Falcon 2,3, Natasha B Leighl 26, Christina S Baik 24, Gillianne GY Lai 16, S Ignatius Ou 14, Kingsley SY Cheung 11, Tejas Patil 9, Aaron S Mansfield 8, Daniela Weiler 5, Beow Y Yeap 1, Lori J Wirth 1, Justin F Gainor 1, Alexander Drilon 2,3,*, Jessica J Lin 1,*
PMCID: PMC12912800  NIHMSID: NIHMS2140953  PMID: 41537704

Abstract

Purpose:

Rearranged during transfection (RET) alterations are oncogenic drivers across solid tumors. Selective RET inhibitors (SRIs) selpercatinib and pralsetinib have transformed outcomes for patients with RET-altered malignancies. Limited knowledge exists on genomic mechanisms of resistance to SRIs.

Experimental Design:

We established ‘RETgistry,’ a global consortium of patients with advanced RET-altered solid tumors who received SRIs and underwent post-progression tissue or plasma biopsies assessed by next-generation sequencing. Frequencies of secondary RET resistance mutations and acquired non-RET gene alterations were determined. Progression-free survival (PFS) and time to treatment discontinuation (TTD) on first SRI were estimated with Kaplan-Meier method.

Results:

RETgistry included 109 patients with RET-altered advanced solid tumors (lung: n=94; thyroid: n=15) who underwent 143 post-SRI progression biopsies (tissue: 91; plasma: 52). Median PFS and TTD were 13.9 months (95% confidence interval [CI] 10.1-16.6) and 17.3 months (95% CI 14.0-20.2), respectively. Secondary RET mutations were detected in 20 (14.0%) biopsies (lung cancer: 15 [12.4%], thyroid carcinoma: 5 [22.7%]). Common acquired off-target alterations involved MET (18.2%; amplification: 15.0%), TP53 (8.2%), APC (7.6%), KRAS (7.1%), KEAP1 (5.9%), and CDKN2A/B (5.3%). MET alterations were enriched in post-SRI versus pre-SRI specimens (full cohort: 17.6% vs 2.0%, p=0.022; lung cancer: 19.1% vs 2.1%, p=0.022).

Conclusions:

Prevalence of secondary RET mutations after SRIs was low, underscoring greater role for off-target resistance. Recurrent acquired alterations involving tumor suppressor genes or upstream regulators of MAPK and PI3K pathways were identified, most commonly MET amplification. Continued efforts to characterize SRI resistance biology are critical to guide development of novel therapeutic strategies.

Keywords: RET alterations, selective RET inhibitors, acquired resistance, MET amplification

Introduction

Rearranged during transfection (RET) alterations are known oncogenic drivers across various tumor types, including non-small cell lung cancer (NSCLC), thyroid carcinoma, and other solid malignancies.1–4 RET rearrangements occur in 1-2% of NSCLC1 and 5-20% of papillary thyroid cancers.2,3 Additionally, somatic or germline RET mutations in kinase or cysteine-rich domains occur in approximately 65% of medullary thyroid carcinomas (MTC).5,6 These oncogenic alterations induce ligand-independent activation of MAPK, PI3K, and JAK-STAT pathways, driving tumor proliferation.6–8

The treatment landscape for patients with advanced RET-altered malignancies has evolved. A historical approach involved repurposing of multikinase inhibitors (MKIs) with activity against RET, including cabozantinib, lenvatinib, vandetanib, and others.9–12 However, these drugs were limited by significant toxicities and low response rates. Guided by the precision medicine paradigm that propelled development of potent, selective, and CNS-penetrant targeted therapies across multiple oncogenic drivers in NSCLC and other malignancies, selpercatinib and pralsetinib were rationally designed as selective RET inhibitors (SRIs), transforming the treatment landscape.13–16 The registrational phase 1/2 LIBRETTO-001 and ARROW trials for selpercatinib and pralsetinib, respectively, resulted in FDA approvals of both drugs for advanced or metastatic RET-rearranged NSCLC and radioiodine-refractory RET-rearranged thyroid carcinoma, with additional approvals of selpercatinib for RET-mutant MTC and RET-rearranged advanced solid tumors.13,15–19 For treatment-naïve patients with advanced RET-rearranged NSCLC, selpercatinib and pralsetinib induce objective response rates (ORRs) of 83% and 72% and median progression-free survival (PFS) of 22.0 and 13.0 months, respectively.13,15,19,20 In patients with previously treated, advanced RET-rearranged thyroid carcinoma, selpercatinib and pralsetinib achieve ORRs of 79% and 91%, respectively.16

Despite initial efficacy, disease resistance to selpercatinib and pralsetinib invariably occurs. Subsequent treatment options are limited with no approved targeted therapies post-SRIs. Few studies with limited size cohorts have investigated resistance to SRIs, identifying cases with on-target RET resistance mutations.21–23 One study assessing 23 post-progression biopsies from 18 patients who received selpercatinib and/or pralsetinib for RET fusion-positive NSCLC identified acquired RET mutations in two (10%) cases.23 Off-target alterations in MET and NTRK have been reported in small cohorts or individual patients.24,25 Knowledge is lacking on whether resistance mechanisms differ by prior MKI exposure. A comprehensive understanding of the frequency and distribution of on- and off-target mechanisms of resistance to SRIs in large cohorts could guide drug development efforts to overcome resistance.

We therefore established ‘RETgistry,’ a global consortium of patients with post-progression biopsies after SRIs for RET altered-solid tumors to determine the landscape of genomic mechanisms of resistance to SRIs.

Patients and Methods

Study Population

Patients with advanced RET altered-solid tumors were identified by medical oncologists from 20 participating institutions, representing a global multicenter cohort. Patients were eligible if they had 1) histologically or cytologically confirmed diagnosis of advanced or metastatic lung cancer, thyroid carcinoma, or other solid tumors, 2) detection of an oncogenic RET fusion or mutation at initial diagnosis through local testing (fluorescence in situ hybridization [FISH] of tissue or next-generation sequencing [NGS] of tumor or circulating tumor DNA), 3) disease progression on pralsetinib and/or selpercatinib per local investigator assessment, and 4) post-progression tissue or plasma biopsy evaluated using NGS.

Systemic therapy before SRIs including chemotherapy, immunotherapy, or RET-targeting MKIs was allowed. Patients were excluded if they had detection of other actionable genomic alterations in SRI-naïve specimens including EGFR mutations, KRAS G12C, BRAF V600E, MET exon 14 skipping, or fusions involving ALK, ROS1, or NTRK1-3. Data cut-off date was August 1, 2023.

Data Collection

Demographic, clinical, and pathologic features were retrieved via chart review by each center. Tumor type and histology (per local histopathologic review), baseline RET alteration, and RET fusion detection method were retrieved. All therapies for advanced/metastatic disease, including MKIs prior to SRIs, were recorded. Clinical outcomes on selpercatinib or pralsetinib, including PFS and time to treatment discontinuation (TTD), were determined by local investigators, with disease progression on SRIs determined per investigator assessment at each participating institution.

All biopsies obtained upon progression on selpercatinib or pralsetinib were reviewed and eligible for inclusion. Biopsy type (tissue or plasma), time interval between start of SRI to post-progression biopsy, genotyping results, and platform used were retrieved. Histology of post-progression tumor samples was reviewed by participating center pathologists to assess for histologic transformation. For patients with prior MKI exposure, data from any biopsies obtained after MKIs and prior to SRIs were extracted.

De-identified data were collected by local investigators under IRB-approved protocols at each center and centrally stored at Mass General Brigham Cancer Institute using password-protected electronic forms in the RETgistry REDCap database.

Statistical Analysis

Descriptive statistics were used to summarize demographic and clinical characteristics and reported as frequencies for categorical variables and as medians and ranges for continuous variables. The proportion of post-progression biopsies with detection of secondary RET resistance mutations (on-target resistance) was determined for the entire biopsy cohort and for subgroups defined by tumor type (lung versus thyroid carcinoma), biopsy type (tissue versus plasma), and prior versus no prior MKI exposure. Differences in the frequency of secondary RET mutations between subgroups were assessed with Fisher’s exact test.

Acquired genomic alterations were delineated in the subgroup of patients with paired pre- and post-SRI progression biopsies (tissue and/or plasma). Pre-SRI biopsies were obtained immediately prior to the SRI and after preceding MKIs, if received. Genomic alterations identified on post-progression biopsies were considered ‘acquired’ if pre-SRI NGS assays sequenced those respective genes and did not identify alterations. The frequency of recurring acquired genomic alterations was reported. Among paired tissue biopsies, genomic alterations enriched in post- versus pre-SRI samples were assessed using McNemar’s test.

PFS and TTD were estimated by Kaplan-Meier method and compared between patients with versus without on-target RET mutations or select off-target alterations using log-rank test. Analyses were performed using SAS 9.4 (SAS, Cary, NC; RRID: SCR_008567) and R-Studio (version 2023.12.1+402; RRID: SCR_000432).

Results

Cohort Characteristics

The RETgistry included 109 patients with advanced or metastatic RET-altered tumors who underwent 143 post-progression biopsies (tissue: 91; plasma: 52) after selpercatinib or pralsetinib (Figure 1, Table 1, Supplementary Data) evaluated by NGS. This cohort included 94 patients (with 121 biopsies) with lung cancer (NSCLC: n=93; mixed small cell/large cell neuroendocrine carcinoma: n=1) and 15 patients (with 22 biopsies) with thyroid carcinoma (medullary: n=12; papillary: n=2; anaplastic: n=1).

Figure 1:

Figure 1:

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CONSORT diagram of patients in the RETgistry consortium with post-progression biopsies after selpercatinib or pralsetinib.

Table 1:

Demographic and clinical characteristics of patient cohort

Characteristic Full cohort (N=109) Subgroup with lung cancer (N=94) Subgroup with thyroid carcinoma (N=15)
Age at diagnosis of advanced disease, median (range) 60 (21-86) 61 (23-86) 51 (21-72)
Sex, n (%)
  Female 61 (56.0%) 54 (57.4%) 7 (46.7%)
  Male 48 (44.0%) 40 (42.6%) 8 (53.3%)
Race/ethnicity, n (%)
  White 78 (71.6%) 64 (68.1%) 14 (93.3%)
  Asian 22 (20.2%) 22 (23.4%) 0 (0%)
  Hispanic/Latino 4 (3.7%) 3 (3.2%) 1 (6.7%)
  Black 3 (2.8%) 3 (3.2%) 0 (0%)
  Other/Unknown 2 (1.8%) 2 (2.1%) 0 (0%)
Smoking status, n (%)
  Never 79 (72.5%) 68 (72.3%) 11 (73.3%)
  Light (<10 pack-years) 18 (16.5%) 15 (16.0%) 3 (20.0%)
  Heavy (10+ pack-years) 10 (9.2%) 9 (9.6%) 1 (6.7%)
  Unknown 2 (1.8%) 2 (2.1%) 0 (0%)
Lung cancer histology, n (%)
  Adenocarcinoma - 83 (88.3%) -
  Adenosquamous - 1 (1.1%) -
  Large cell neuroendocrine carcinoma - 2 (2.1%) -
  Other NSCLC or NSCLC NOS - 7 (7.4%) -
  Mixed small cell/large cell neuroendocrine carcinoma - 1 (1.1%) -
Thyroid carcinoma histology, n (%)
  Medullary thyroid carcinoma - - 12 (80.0%)
  Papillary thyroid carcinoma - - 2 (13.3%)
  Anaplastic thyroid carcinoma - - 1 (6.7%)
RET fusion partner in NSCLC, n (%)
  KIF5B - 71 (75.5%) -
  CCDC6 - 16 (17.0%) -
  Other - 7 (7.4%) -
Primary RET alteration in thyroid carcinoma, n (%)
  M918T - - 7 (46.7%)
  CCDC6::RET fusion - - 1 (6.7%)
  ERC1::RET fusion - - 1 (6.7%)
  NCOA4::RET fusion - - 1 (6.7%)
  Other alterations* - - 5 (33.3%)
SRI immediately preceding biopsy**
  Selpercatinib 95 (87.2%) 84 (89.4%) 11 (73.3%)
  Pralsetinib 17 (15.6%) 13 (13.8%) 4 (26.7%)
Number of any therapies received prior to SRI
  0 32 (29.4%) 29 (30.9%) 3 (20.0%)
  1 47 (43.1%) 40 (42.6%) 7 (46.7%)
  2 13 (11.9%) 11 (11.7%) 2 (13.3%)
  3+ 17 (15.6%) 14 (14.9%) 3 (20.0%)
Number of MKIs received prior to SRI
  0 79 (72.5%) 76 (80.9%) 3 (20.0%)
  1 19 (17.4%) 12 (12.8%) 7 (46.7%)
  2-4 11 (10.1%) 6 (6.4%) 5 (33.3%)
MKIs received prior to biopsy
  Cabozantinib 16 (14.7%) 9 (9.6%) 7 (46.7%)
  Vandetanib 8 (7.3%) 1 (1.1%) 7 (46.7%)
  Lenvatinib 5 (4.6%) 1 (1.1%) 4 (26.7%)
  Alectinib 4 (3.7%) 4 (4.3%) 0 (0%)
  Regorafenib 2 (1.8%) 0 (0%) 2 (13.3%)
  Ponatinib 1 (0.9%) 1 (1.1%) 0 (0%)
  Investigational RET inhibitor 7 (6.4%) 7 (7.4%) 0 (0%)
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*

Includes RET C618S (n=1), D631_L633delinsE (n=1), E632_L633del (n=1), L629_I638delinsCD (n=1), and L633_A639del (n=1)

**

Three patients with NSCLC underwent post-progression biopsies after both pralsetinib and selpercatinib (reflecting the denominator of 112 for full cohort and 97 for lung cancer)

Abbreviations: MKI, multikinase inhibitor; NOS, not otherwise specified; NSCLC, non-small cell lung cancer; SRI, selective RET inhibitor

In the cohort with lung cancer, median age was 61 (range 23-86), 54 (57.4%) patients were female, and 68 (72.3%) had no prior smoking history (Table 1). The most common RET fusion partners were KIF5B (n=71, 75.5%) and CCDC6 (n=16, 17.0%). Of 121 post-progression biopsies (tissue: 76; plasma: 45), 104 were obtained after selpercatinib (n=84 patients) and 17 after pralsetinib (n=13); three patients underwent post-progression biopsies after both pralsetinib and selpercatinib, given sequentially in that order. Most patients (n=79, 72.5%) received selpercatinib or pralsetinib as their first targeted therapy; the remainder had received ≥1 prior MKI. Thirty-two patients (29.4%) received selpercatinib or pralsetinib as their first-line systemic anti-cancer therapy.

In the cohort with thyroid carcinoma, median age was 51 (range 21-72), and seven (46.7%) patients were female (Table 1). The most common oncogenic RET alteration was M918T (n=7, 46.7%), all in patients with MTC. Three patients had RET fusion-positive thyroid carcinoma (fusion partners: CCDC6 [histology: anaplastic], ERC1 [papillary], and NCOA4 [papillary]); the remaining five patients (all with MTC) had mutations in or adjacent to the cysteine-rich domain of RET. Of 22 post-progression biopsies (tissue: 15, plasma: 7), 16 were obtained after selpercatinib (n=11 patients) and 6 after pralsetinib (n=4). Most patients (n=12) had received ≥1 prior MKI.

Treatment outcomes with first SRI received were determined for the full cohort and for the lung cancer subgroup. Median follow-up for treatment duration was 65.3 months (95% confidence interval (CI) 47.8-not estimable (NE)). Median PFS was 13.9 months (95% CI 10.1-16.6), and median TTD was 17.3 months (95% CI 14.0-20.2). In the lung cancer subgroup, median PFS was 13.0 months (95% CI 9.3-15.8), and median TTD was 15.7 months (95% CI 13.0-19.0).

On-Target RET Mutations

Among 143 post-progression biopsies obtained after SRIs in the full cohort, 20 (14.0%) harbored on-target RET resistance mutations (Figure 2).

Figure 2: Secondary RET mutations identified in post-progression biopsies after selective RET inhibitor therapy.

Figure 2:

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Frequency of secondary RET mutations is shown for the post-progression biopsies in the full RETgistry cohort and in subgroups with lung cancer versus thyroid carcinoma tumor types, tissue versus plasma biopsies, and without versus with prior MKI exposure. Abbreviations: delins, deletion-insertion; MKI, multikinase inhibitor.

Among 121 post-progression lung cancer biopsies, 15 (12.4%) harbored secondary RET resistance mutations, including single RET mutations in 13 biopsies and multiple co-occurring RET mutations in two biopsies. Among biopsies with secondary RET resistance mutations, the underlying fusion partners were KIF5B (n=10), CCDC6 (n=4), and EML4 (n=1). Single secondary RET resistance mutations included solvent front missense mutations in the G810 residue (n=11), the V804M gatekeeper mutation (n=1), and an insertion-deletion mutation impacting both V804 and G810 (n=1). Co-occurring secondary RET mutations included presence of both G810S and V804M (n=1) or multiple solvent front mutations involving G810 (n=1).

Among 22 post-progression biopsies for thyroid carcinoma, five (22.7%), all from patients with MTC, harbored secondary RET resistance mutations, including G810X (n=3); A764G (n=1); and co-occurring G810S, V804M, and L881V (n=1) (Figure 2).

We compared the frequency of secondary RET mutations detected by tissue versus plasma NGS. RET mutations were identified in 12.1% (11/91) of post-progression tissue biopsies and 17.3% (9/52) of plasma biopsies (p=0.45; Figure 2). The frequency of secondary RET mutations was similar in patients with (7/46, 15.2%) versus without prior MKI exposure (13/97, 13.4%; p=0.80).

RET Gain

RET copy number gain was identified in three (2.1%) post-progression tissue biopsies, including two (1.7%) biopsies from patients with NSCLC and one (4.5%) from a patient with thyroid carcinoma. All three cases of RET gain were identified by NGS after selpercatinib and were mutually exclusive with secondary RET mutations (Supplementary Table 1).

Landscape of Acquired Genomic Alterations

Among 109 patients in the full cohort, a total of 79 patients underwent 99 paired pre- and post-SRI tissue or liquid biopsies, enabling direct assessments of acquired alterations during therapy (Figure 3A). Pre-SRI biopsies were obtained following any prior MKIs and immediately before initiation of an SRI. Paired pre-/post-SRI sample analysis indicated that 72 (72.7%) post-SRI samples harbored acquired genomic alterations, comprising on-target RET mutations in 2 (2.0%) biopsies, both on-target RET mutations and off-target alterations in 10 (10.1%) biopsies, and off-target alterations alone in 60 (60.6%) biopsies (Figure 3B, Supplementary Table 2). Similar findings were observed in the NSCLC subgroup with paired biopsies (Figure 3B). No acquired genomic alterations were detected in 27 (27.3%) post-SRI biopsies overall and 25 (27.2%) in NSCLC.

Figure 3: Acquired genomic alterations following selective RET inhibitor therapy.

Figure 3:

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(A) Schematic of the RETgistry subgroup with paired pre- and post-SRI biopsies assessed with NGS including tissue or plasma biopsies, allowing the assessment of acquired genomic alterations. Pre-SRI biopsies were obtained after any prior MKIs, if received, and immediately prior to the SRI of interest. (B) Frequencies of on-target and off-target putative genomic mechanisms of resistance identified on post-SRI biopsies. (C) The frequency of acquired non-RET gene alterations is presented for all genes that were evaluated in at least 50% of the 99 paired pre- and post-SRI biopsies. Abbreviations: MKI, multikinase inhibitor; ca, carcinoma; alt, alteration; mut, mutation; NGS, next-generation sequencing; NSCLC, non-small cell lung cancer; SRI, selective RET inhibitor.

The most frequent acquired co-altered genes identified in post-SRI biopsies (Figure 3C and 4) included MET (18.2%; amplification: 15.2%, missense mutation: 2.0%, loss: 1.0%); TP53 (8.1%; missense mutation: 4.0%, truncating mutation: 2.0%, unknown type: 2.0%); APC (7.1%; missense mutation: 6.1%, unknown type: 1.0%); KRAS (7.1%; missense mutation: 4.0%, amplification: 3.0%); KEAP1 (3.0%; missense mutation: 3.0%); and CDKN2A/B (5.1%; loss: 4.0%, truncating mutation: 1.0%). Details on cases of acquired MET amplification including the degree of copy number variation are provided in Supplementary Table 3. Acquired KRAS mutations included oncogenic or likely oncogenic gain-of-function missense mutations (G12V: n=1; Q61H: n=1; V14I: n=1) or alterations of unknown significance (M111V: n=1). Other genes with acquired alterations (Supplementary Table 2) included ERBB2 (4.0%; amplification: 2.0%, truncating mutation of unknown significance: 1.0%; missense mutation of unknown significance: 1.0%), PIK3CA (4.0%; amplification: 1.0%, missense mutation: 1.0%, alterations of unknown significance: 1.0%), EGFR (3.0%; all amplification), and BRAF (2.0%; amplification: 1.0%, V600E: 1.0%). Acquired fusions were identified in ALK (3.1%; EML4::ALK: 2.1%, ALK::EML4, 1.0%) and ROS1 (1.1%; TPD52::ROS1: 1.1%). Of the 60 biopsies with acquired off-target alterations without co-acquired secondary RET mutations, 19 (31.7%) harbored alterations with commercially available targeted therapies (MET amplification, n=15; ALK fusion, n=2; ROS1 fusion, n=1; BRAF V600E, n=1) and 10 (16.7%) had alterations for which investigational therapies were available (KRAS non-G12C, n=4; EGFR amplification, n=3; HRAS Q61L, n=1; SMARCA4 M781V, n=1; HER2 amplification, n=1).

Figure 4: Landscape of acquired genomic alterations identified on post-progression biopsies after selective RET inhibitors.

Figure 4:

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Acquired alterations are presented for genes that were evaluated in at least 50% of the 99 paired pre- and post-SRI biopsies. MSK300 had mixed small cell/large cell neuroendocrine carcinoma at baseline; all other cases with lung cancer had non-small cell histology. Thyroid carcinoma histology included medullary (MGH-067, MGH-078, MGH-079) and anaplastic (MGH-077). RET exon 11 alterations in medullary thyroid carcinoma cases included RET D631_L633delinsE (MGH-078) and E632_L633del (MGH-079). Abbreviations: Ca, carcinoma; SRI, selective RET inhibitor; MKI, multikinase inhibitor; no, number; pt, patient.

As liquid biopsies can be less sensitive than tissue-based biopsies for evaluations of copy number changes, we next focused our analysis on 68 patients with 76 paired pre- and post-SRI tissue biopsies to identify significant differences in gene alterations detected pre-SRI versus post-SRI (Figure 5A). MET alterations were enriched in post-SRI versus pre-SRI tissue biopsies among patients with lung and thyroid cancer collectively (17.6% vs 2.0%, p=0.022, Figure 5B) and in the subgroup with lung cancer (19.1% vs 2.1%, p=0.022, Figure 5C). For other recurrently altered genes, no significant difference was identified post-SRI versus pre-SRI.

Figure 5: Analysis of genomic alterations enriched in post-SRI versus pre-SRI tissue biopsies.

Figure 5:

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(A) Schematic of RETgistry subgroup with paired pre- and post-SRI tissue biopsies, with pre-SRI tissue biopsies obtained after any prior MKIs, if received, and immediately prior to the SRI of interest. (B and C) On McNemar’s test comparing the frequency of genomic alterations identified by paired post- versus pre-SRI tissue biopsies, MET alterations were enriched on post-SRI tissue biopsies in (B) patients both with NSCLC and thyroid cancer and (C) the subgroup with NSCLC. Abbreviations: MKI, multikinase inhibitor; NSCLC, non-small cell lung cancer; SRI, selective RET inhibitor.

Histologic Transformation

The prevalence of histologic transformation in RET-altered solid tumors following SRI therapy has not been well-defined.23 In RETgistry, only one of 75 (1.3%) post-SRI tumor specimens from patients with advanced/metastatic lung cancer had features consistent with transformation from lung adenocarcinoma to small cell lung cancer as assessed by histopathologic review. This biopsy was obtained from a 76-year-old woman with metastatic KIF5B::RET fusion-positive NSCLC treated with first-line selpercatinib; post-selpercatinib tissue NGS also identified acquired alterations in TP53, CCND1, FGF3, FGF4, and PBRM1. No cases of transformation to squamous cell carcinoma were reported.

Among 13 post-progression tissue biopsies from patients with thyroid carcinoma assessed by histopathologic review, no cases of histologic transformation were observed.

Clinical Outcomes According to Molecular Mechanisms of Resistance

Finally, we assessed whether clinical outcomes of patients on their first SRI were associated with distinct mechanisms of resistance. We first evaluated outcomes based on presence versus absence of secondary RET mutations in post-SRI biopsies. In the overall cohort, median PFS was 19.7 months (95% CI 4.5-32.5) in those with versus 13.8 months (95% CI 10.1-15.8) in those without a RET resistance mutation (log-rank: p=0.42). Median TTD was also comparable between those with (20.5 months, 95% CI 6.5-33.5) versus without (16.8 months, 95% CI 14.0-20.0) a RET resistance mutation (log-rank: p=0.61). Within the subgroup with lung cancer, no statistically significant difference was observed in PFS or TTD among patients with versus without on-target resistance.

We similarly compared clinical outcomes with first SRI in patients with versus without MET amplification detected in post-SRI biopsies. Median PFS was 7.8 months (95% CI 4.8-13.0) in those with versus 14.8 months (95% CI 12.4-18.1) in those without MET amplification (p=0.25). Median TTD was significantly shorter in patients with MET amplification at 8.4 months (95% CI 6.3-15.3) versus 19.0 months (95% CI 15.1-23.2) in those without MET amplification (p=0.025).

Discussion

Despite recent advances in the management of patients with advanced RET-altered solid tumors, significant unmet needs remain. Treatment options remain limited after progression on SRIs. In subsets of NSCLC harboring classical EGFR mutations or ALK fusions, which heralded the precision oncology paradigm in lung cancer, knowledge of mechanisms of resistance to existing targeted therapies has proven pivotal in the development of subsequent treatment approaches.26,27 To date, insights into mechanisms of resistance to SRIs have largely been derived from single institution or small cohort series, precluding a comprehensive understanding of the resistance landscape. To address this knowledge gap, we launched the RETgistry consortium, providing an international, multicenter analysis of 143 post-progression biopsies from patients treated with selpercatinib and pralsetinib. To the best of our knowledge, this represents the largest such effort to date.

Previous reports have described on-target RET resistance mutations in case series or small cohorts of patients with progression after SRIs, with preclinical models confirming the role of secondary RET mutations in conferring resistance to SRIs.21–23 However, the frequency and distribution of these mutations have not been previously systematically analyzed in a large cohort. In this study, we identified a low frequency (14.0%) of on-target RET resistance mutations across the overall cohort, implicating a more dominant role of off-target resistance to SRIs in RET-altered tumors. The frequency of on-target resistance was low regardless of prior exposure to MKIs (15.2% vs 13.4%). This low frequency contrasts with the higher prevalence (40-65%) of on-target resistance in EGFR-mutant or ALK-rearranged NSCLC after first- or second-generation tyrosine kinase inhibitors (TKIs).28,29 However, our findings align with the low prevalence of on-target resistance observed after first-line use of third-generation EGFR or ALK TKIs,29–31 likely reflecting the favorable potency and selectivity of SRIs and efforts during drug development to select agents with activity against gatekeeper mutations.

The spectrum of on-target mutations identified was narrow, predominantly converging on G810. RET G810 solvent front mutations have previously been identified as a recurrent mechanism of resistance to SRIs.22,23 To date, no approved drugs harbor activity against RET G810X, representing an unmet therapeutic need. Additionally, gatekeeper mutations involving the V804 residue, known to confer resistance to multikinase inhibitors,3,32 were observed. Although preclinical studies have demonstrated activity of SRIs against RET V804 mutations,33–35 cases of co-occurring RET V804 and G810 mutations have been reported in selpercatinib-resistant biopsies.22 In our analysis of paired pre- and post-SRI biopsies, RET V804M emerged as an acquired alteration in two post-selpercatinib plasma biopsies from patients with lung cancer (one in isolation and the other co-occurring with acquired RET G810S). Notably, additional secondary mutations – A764G (as a single RET mutation) and L881V (co-occurring with RET G810S and V804M) – were identified in patients with thyroid carcinoma. To our knowledge, RET A764G has not been previously reported as a mechanism of resistance to RET inhibitors. Prior reports on RET L881V are sparse and include germline variants in familial medullary thyroid carcinoma.36,37 Although L881V has been implicated in resistance to vandetanib in preclinical models,21 it has not been linked to resistance to SRIs in prior studies. Functional validation studies are needed to assess the potential role of these mutations in mediating resistance to SRIs.

The infrequent occurrence of on-target RET resistance mutations highlights the predominant role of off-target alterations in mediating resistance to SRIs. We identified acquired alterations in a wide range of non-RET genes, without concomitant secondary RET mutations, in 60.6% of cases. MET amplification emerged as a recurrent off-target alteration and was mutually exclusive to secondary RET mutations. Notably, MET amplification represents a common resistance mechanism to next-generation inhibitors across genomic subtypes of NSCLC,31,38–42 and its frequency (15.2%) in SRI-resistant RET-altered malignancies mirrors findings in TKI-refractory EGFR-mutant (7-22%)31,39 and ALK+ NSCLC (12-22%).38,40 Preclinical models have demonstrated that MET amplification is indeed sufficient in mediating resistance to RET inhibitors,24 activating MAPK, STAT, and PI3K/AKT signaling pathways independently of the original oncogenic driver.43,44 In clinical practice, MET amplification detection in post-progression biopsies enables the consideration of therapeutic regimens combining MET inhibitors with targeted therapies against the original oncogenic driver.24 Collectively, these findings underscore MET amplification as a shared resistance driver across actionable tumor subtypes, emphasizing the pivotal role of post-progression biopsies in guiding next-line treatment strategies.

Of note, the emergence of MET amplification in SRI-resistant tumors was associated with shorter TTD on SRI and numerically shorter PFS compared to cases without MET amplification. These results suggest that MET amplification may represent an early resistance driver and that patients with relatively rapid progression on SRIs may be more likely to have tumors with MET-mediated resistance. The findings warrant confirmation in larger cohorts, and further studies are needed to uncover why MET amplification may emerge as an earlier mechanism of resistance to SRIs.

Additional post-SRI acquired alterations were identified in genes regulating MAPK or PI3K signaling pathways, including KRAS, BRAF, EGFR, ERBB2, ALK, ROS1, and PIK3CA, or tumor suppressor genes including TP53, APC, KEAP1, and CDKN2A/B. It remains unclear whether these acquired genomic alterations represent true drivers of resistance versus passenger alterations. Genomic alterations in upstream regulators of MAPK and PI3K pathways have previously been implicated in resistance to targeted therapies for other oncogene-driven cancers, including NSCLC harboring EGFR mutations or KRAS G12C.31,45 Furthermore, baseline alterations in CDKN2A/B, KEAP1, and TP53 have been identified as negative predictors of response to targeted therapies or immunotherapy across multiple molecular subgroups.46,47 Ultimately, functional studies are necessary to investigate the role of these acquired non-RET alterations in mediating resistance to SRIs and their potential as therapeutic targets. Additionally, the absence of any acquired genomic alterations in 27% of this study cohort underscores the importance of further investigations centered on non-genomic mechanisms of resistance to SRIs.

Our findings highlight the need to explore strategies to overcome off-target resistance to SRIs. Currently, chemotherapy remains the standard next-line option after SRIs for NSCLC, with limited therapeutic benefit.48 In one previously reported case, combining selpercatinib with TRK inhibitor larotrectinib achieved disease control in a patient with RET-mutant MTC harboring an acquired NTRK3 fusion after selpercatinib monotherapy.49 Similarly, selpercatinib combined with MEK inhibitor trametinib was effective in a patient with RET fusion-positive NSCLC with an acquired BRAF fusion after selpercatinib.50 While EGFR and RET inhibitor combinations have been implemented as a strategy to overcome resistance to EGFR TKIs mediated by acquired RET fusions in EGFR-mutant NSCLC,51,52 it is unknown whether such combinations would be effective in overcoming resistance to SRIs mediated by EGFR alterations in RET-altered tumors. Further investigation into novel therapeutic strategies, including rational combination therapies, is critical to expand treatment options and improve outcomes for patients with SRI-refractory tumors. Additionally, studies are warranted to investigate approaches to delay or circumvent resistance. A better understanding of the biology of drug-tolerant persister cells and development of advanced disease monitoring technologies may enable early intensification strategies that ablate residual tumor populations before drug-resistant clones evolve.53

Our study had several limitations. This was a retrospective analysis with potential for selection and referral biases. As the RETgistry comprised an international cohort of patients across multiple institutions, the use of variable NGS assays among tissue and plasma samples may have impacted analyses. To mitigate this limitation, we restricted assessments of acquired alterations to cases where both pre- and post-SRI NGS platforms sequenced genes of interest. Analyses of genes enriched in post- versus pre-SRI biopsies were also restricted to patients with paired tissue biopsies. Data were limited on the number of metastatic sites, disease progression patterns on therapy, and whether paired (pre- versus post-treatment) biopsies were obtained from the same versus discordant tumor sites; as a result, the presence of inter-tumoral heterogeneity between distinct sites of disease may have influenced genomic findings. Additionally, the small number of patients with thyroid carcinoma limited the power of subgroup analyses for this tumor type. Similarly, due to limited size cohorts, mechanisms of resistance identified after selpercatinib versus pralsetinib could not be compared. Further studies are needed to define resistance in thyroid carcinoma and other non-NSCLC malignancies. Lastly, clinical outcomes with SRIs were biased relative to those reported in LIBRETTO-001 and ARROW, respectively.13,15,16,19,20 While the PFS in those trials reflected collective outcomes in patients with and without progression during prospective follow-up and who had ECOG performance status 0-1 at baseline, our cohort was defined retrospectively by real-world patients with progression on SRIs, effectively shifting PFS curves towards shorter durations.

In summary, we identified on-target RET resistance mutations in 14.0% of biopsies from patients progressing on SRIs, implicating a predominant role of off-target resistance mechanisms. A broad spectrum of acquired off-target alterations was detected, with MET amplification emerging as a frequent, recurrent mechanism of resistance and an early resistance driver. Continued characterization of the biology underlying resistance to SRIs among RET-altered tumors is critical for advancing drug development efforts to overcome or delay resistance to SRIs and improve outcomes.

Supplementary Material

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Translational Relevance.

Selective RET inhibitors (SRIs) have transformed outcomes for patients with RET-altered solid tumors. Genomic mechanisms of resistance to SRIs are poorly understood. We established a global consortium of patients with RET-altered lung cancer or thyroid carcinoma treated with SRIs (first-line: 72.5%) who underwent post-progression tissue and/or liquid biopsies. Next-generation sequencing of paired pre/post-SRI biopsies revealed that more than half of acquired resistance events were associated with alterations in genes other than RET. On-target RET mutations were uncommon (paired analysis: 12.1%). MET amplification was the most frequent (15.2%) acquired alteration, with others involving upstream regulators of MAPK and PI3K pathways or tumor suppressor genes. Histologic transformation was reported in 1.3% of SRI-resistant lung cancers. Time to SRI discontinuation was shorter in those with versus without emergence of MET amplification, indicating its role as an early resistance driver. These findings highlight predominance of off-target resistance to SRIs and need for novel therapeutic strategies to overcome it.

Funding

This work was supported by The Happy Lungs Project (to J.J.L., A.D., J.F.G.), Career Enhancement Program award from the Dana-Farber/Harvard Cancer Center (DF/HCC) Lung Cancer SPORE National Cancer Institute at the National Institutes of Health P50 CA265826 (to J.J.L.), Biostatistics Core of the DF/HCC SPORE in Lung Cancer P50 CA265826 (to B.Y.Y.), and Targeting a Cure for Lung Cancer Fund of Thoracic Oncology at Massachusetts General Brigham (to J.J.L. and J.F.G.). A.E.D. was supported by the National Cancer Institute/National Institutes of Health P30CA008748, 1R01CA251591001A1, 1R01CA273224-01, 1R01CA226864-01A1 grants. G.P. was supported by the Verein für Tumorforschung, Sanatoriumstraße 43, 6511 Zams, Austria. A.S.M. has been supported by a Mark Foundation ASPIRE Award, Thymic Carcinoma Center Research Award, Department of Defense Concept Award W81XWH-22-1-0021, NCI R21 (CA251923), NCI R33 (CA272271), NCI U24 (CA283479) and NCI UG1 (CA232760).

Conflicts of Interest:

S.W. reports consulting fees from AstraZeneca. A.J.C. has received honoraria from MJH Life Sciences, Ideology Health, Intellisphere LLC, MedStar Health, PeerDirect and CancerGRACE; consulting fees from Gilead Sciences, Inc, Daiichi/Astra Zeneca, Novartis, BI, and Regeneron; and prior research funding to institution from Merck, Monte Rosa, AbbVie, Roche, Daiichi Sankyo, and Amgen (end 08/2025). S.V.L. has served as a compensated consultant for Abbvie, Amgen, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi Sankyo, Genentech/Roche, Gilead, GSK, Guardant Health, Johnson & Johnson, Jazz Pharmaceuticals, Merck, Merus, Natera, Novartis, Nuvalent, OSE Immunotherapeutics, PharmaMar, Pfizer, Regeneron, Revolution Medicines, SystImmune, Takeda, and Yuhan; has received institutional research funds from Abbvie, Alkermes, AstraZeneca, Avenzo, BioNTech, Bristol-Myers Squibb, Cogent Biosciences, Duality, Ellipses, Genentech, Gilead, Medilink, Merck, Merus, Nuvalent, OSE Immunotherapeutics, Puma, Synthekine, SystImmune. O.G. received travel grants from Amgen, AstraZeneca and Roche. J.K.R. reports consulting fees or honoraria from Amgen, AstraZeneca, BioAtla, BMS, Boehringer Ingelheim, Daiichi Sankyo, Genentech, G1 Therapeutics, Guardant Health, Johnson and Johnson, Jazz Pharmaceuticals, Merus, Novocure, Nuvation Bio, Pfizer, Sanofi-Genzyme, Summit Therapeutics, and Takeda; travel from AstraZeneca, BMS, Daiichi-Sankyo, Johnson and Johnson, and Merus; and research funding (institutional) from Altor Bioscience, AstraZeneca, Bicycle Therapeutics, BioAtla, BlossomHill, Blueprint Medicines, Enliven Therapeutics, EpimAb, Black Diamond, Duality, LOXO Oncology, ORIC Pharmaceuticals, AbbVie, RedCloud Bio, Summit, Synthekine, Immunity Bio, and Regeneron. U.M.W. has served as a compensated consultant for Janssen. D.H.L. reports honoraria from AstraZeneca/MedImmune, Boehringer Ingelheim, Bristol Myers Squibb, Lilly, MSD, Novartis, Ono Pharmaceutical, Pfizer, Roche/Genentech, ST Cube, Takeda, AbbVie, Yuhan, and Janssen; and has served in a consulting or advisory Role for ST Cube and Abion. H.H.L. reports consulting fees from Amgen, AstraZeneca, Bohringer-Ingelheim, Celgene, Eli-Lilly, Emerald Clinical Trials Illumina, Guardant Health, MSD, Novartis, Pfizer, Takeda and Zuellig Biopharma. J.D.P. is an employee at Tempus AI, Inc and has served as an advisor for AstraZeneca, AbbVie, BMS, Black Diamond, Gilead, Boehringer Ingelheim, Takeda, Natera, and Guardant. N.A.P. is an employee at Bristol Myers Squibb and has done consulting for NuvationBio, Summit, Genentech, Eli Lilly, Johnson and Johnson, Iovance, and Daiichi Sankyo. M.N. has received honoraria from AstraZeneca, Daiichi Sankyo, Lilly, Pfizer, Genentech, BMS/Mirati, Takeda, Johnson and Johnson, Boehringer Ingelheim, and Regeneron; consulting fees from Caris Life Sciences; and travel support from AnHeart Therapeutics/ Nuvation Bio. S.A.P. has served as a compensated consultant for Astellas and Genentech; and has received institutional research funds from AstraZeneca, Amgen, Bristol Myers Squibb, Black Diamond Therapeutics, Seattle Genetics, Pfizer, Genentech, Eli Lilly, Prelude Therapeutics, ASCO, MediLink Therapeutics, Dracen Pharmaceuticals, Guardant, OncoC4, and Macrogenics. D.S.W.T. has received grants from ACM Biolabs, Amgen, AstraZeneca, Bayer, Pfizer; personal fees from Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, DKSH, GSK, Merck, Novartis, Pfizer, Roche, Takeda, Zymeworks and Armando Santoro; has acted as a consultant or advisor for Bristol-Myers Squibb, Servier, Gilead, Pfizer, Eisai, and Bayer. B.J.S. has served on advisory boards/received honoraria from Eli Lilly, AstraZeneca, Pfizer, Roche, Amgen, Johnson and Johnson, Glaxo Smith Kline, Bristol Myers Squibb, Merck Sharp Dohme, and D3Bio. T.M.K. reports consulting fees from AstraZeneca, BeOne Medicines Ltd, Daiichi-Sankyo, HK inno.N, IMBDx. Inc., Janssen, Merck KGaA, Novartis, Regeneron, Roche/Genentech, Samsung Bioepis, and Chong Kun Dang Pharmaceutical; speakers’ bureau payments from AstraZeneca, Amgen, BeOne Medicines Ltd, Daiichi-Sankyo, Janssen Research & Development, and Takeda; and medical writing support from AbbVie, AstraZeneca, Bayer, BeOne Medicines, Boryung, Incyte, Janssen, Merck & Co. Inc., Regeneron, Roche/Genentech, Takeda. G.P. reports speaker honoraria from Eli-Lilly and has participated in national advisory boards for Eli-Lilly. J.W.R. has received compensated consulting fees from Daiichi Sankyo and Replimmune; compensated advisory board fees from AstraZeneca, Regeneron, Catalyst, Janssen, Nuvalent, Amgen, Boehringer Ingelheim, BMS, Oncohost, ArriVent, Merck, GSK, Roche/Genentech and Pfizer; travel fees from GSK, IO Biotech and Astrazeneca; and institutional research funds from AstraZeneca, Prelude, Merck, Nuvalent, Summit Therapeutics, Janssen, Boehringer Ingelheim, Pfizer, ArriVent, IO Biotech and Blossom Hill. L.S. reports consulting fees from Pfizer, AstraZeneca, GSK, Merus, Guardant, and Flatiron, and institutional research funds from Seagen/Pfizer, Immunocore, Abbvie, ORIC, Merus, Frontier, and Tempus. M.F. reports consulting or advisory roles for BMS, AstraZeneca, MSD, Takeda, Roche, and Lilly; has served on speakers’ bureau for Pfizer; and research funding from Bristol Myers Squibb and AstraZeneca. S.G. has served as a consultant for AbbVie, Amgen, Astellas Pharma, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi Sankyo, Genentech, Gilead Foundation, I-MAB, Johnson and Johnson, Merck, Mirati Therapeutics, Nuvation Bio, Pfizer, Regeneron, and Takeda Oncology; has done data and safety monitoring for AstraZeneca; and has received travel support from Merck and Mirati Therapeutics. J.F. has received speaker’s honoraria from AstraZeneca, Merck, Pfizer, Amgen, Roche, and CPD Network (Oncology Education); has served on advisory boards for Amgen, Merck, Astra Zeneca, and Pfizer; received travel support from DAVA Oncology and Boehringer-Ingelheim; and has served as a principal investigator in sponsored trials for Eli Lilly and Black Diamond Therapeutics. N.B.L. reports grants/research support to her institution from Amgen, AstraZeneca, Boehringer-Ingelheim, Bristol Myers Squibb, GlaxoSmithKline, Eli Lilly, Johnson and Johnson, Merck, Sharp & Dohme, Novartis, Pfizer, Takeda, Guardant Health, Neogenomics; travel support (CME lectures) from AstraZeneca, MSD, Roche, Johnson and Johnson, Sanofi, Guardant Health; and has served on Data Safety Monitoring Board (uncompensated) for Mirati Therapeutics and Daichii Sankyo. C.S.B. has served as a consultant for Daiichi, Nuvalent, Janssen, Lilly, AstraZeneca, Boehringer, Natera, Regeneron, Takeda, BMS, Pfizer, and Genentech; and has received research funding to institution from AstraZeneca, Pfizer, Blueprint, Daiichi, Abbvie, TP Therapeutics, Lilly, Janssen, Nuvalent, Boehringer, BlackDiamond, BMS, and Ellipses. G.G.Y.L. reports grants from Merck, Astra Zeneca, Pfizer, BMS and Roche outside of the submitted work. S.I.O. reports consulting fees from Pfizer, Bayer, and Bristol Myers Squibb; honoraria for lectures or speakers’ bureaus from Pfizer, AstraZeneca, DAVA Oncology, and OncLive; stock ownership in Nuvalent, MBrace Therapeutics, BlossomHill Therapeutics, and Lilly; and stock options with Nuvation Bio. T.P. has served in an advisory role (advisory boards or consultations) for Aadi Biosciences, Astrazeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Caris, Cellworks, Daiichi, Foundation Medicine, Guardant Health, Gilead, Johnson & Johnson, Jazz Pharmaceuticals, Merus, Natera, Nuvation, Pfizer, Regeneron, Rigel, Roche/Genentech, Summit Therapeutics, Takeda; on data safety monitoring board or Scientific Steering Committees for Boehringer Ingelheim, Elevation Oncology, Johnson & Johnson, Foundation Medicine; and has received research funding from Janssen and Gilead. A.S.M reports receiving support from Genentech and Janssen for manuscript publication; receiving honoraria to institution for participation on advisory boards for AbbVie, AstraZeneca, Bristol-Myers Squibb, Genentech, Janssen, RayzeBio and Takeda Oncology; serving as steering committee member for Janssen and Johnson & Johnson Global Services; having speaking engagements from Chugai Pharmaceutical Co., Ltd. (Roche); serving as grant reviewer for Rising Tide; having expert think tank participation in TRIPTYCH Health Partners; serving as a moderator for Ideology Health LLC (formerly Nexus Health Media); having CME presentation for Intellisphere LLC (OncLive Summit Series) and Answers in CME; having presentation for Immunocore; serving on the advisory board for Sanofi Genzyme; receiving honoraria to self for CME presentation for Antoni van Leeuwenhoek Kanker Instituut and MJH Life Sciences (OncLive); having presented to the University of Miami International Mesothelioma Symposium; and serving as nonremunerated director of the Mesothelioma Applied Research Foundation and member of the Friends of Patan Hospital Board of Directors. D.W. has served on advisory boards for MSD and Merck. L.J.W. reports consulting fees from Eisai, Inc, Coherus BioSciences, AbbVie Inc., Bicara Therapeutics, Fore Biotherapeutics, Leo Pharma, Pyxis, Tubulis, Merck, and Novartis; travel support from Novartis; and has served on advisory board or data safety monitoring board for PDS Biotech. J.F.G. has served as a compensated consultant for Amgen, AstraZeneca, Daiichi Sankyo, Pfizer, Novocure, AI Proteins, Novartis, Sanofi, Summit Therapeutics, Bristol Myers Squibb, Genentech, Revolution Medicine, Merck, Moderna Therapeutics, Rigel Therapeutics; has received honorarium from Novartis, Merck, Novartis, and Pfizer, received institutional research funding from Adaptimmune, Alexo Therapeutics, AstraZeneca, Blueprint Medicines, Bristol Myers Squibb, Genentech, Merck, Moderna Therapeutics, Novartis, NextPoint Therapeutics, Palleon Pharmaceuticals; research support from Novartis, Genentech and Takeda, and has equity in AI Proteins; and has an immediate family member who has equity in Ironwood Pharmaceuticals and Alkeus Pharmaceuticals. A.D. reports honoraria from 14ner/Elevation Oncology, Amgen, Abbvie, AnHeart Therapeutics, ArcherDX, AstraZeneca, Beigene, BergenBio, Blueprint Medicines, Bristol Myers Squibb, Boehringer Ingelheim , Chugai Pharmaceutical, EcoR1, EMD Serono, Entos, Exelixis, Helsinn, Hengrui Therapeutics, Ignyta/Genentech/Roche, Janssen, Loxo/Bayer/Lilly, Merus, Monopteros, MonteRosa, Novartis, Nuvalent, Pfizer, Prelude, Regeneron, Repare RX, Springer Healthcare, Takeda/Ariad/Millenium, Treeline Bio, TP Therapeutics, Tyra Biosciences, Verastem, and Zymeworks; has served on advisory boards for Bayer, MonteRosa, Abbvie, EcoR1 Capital, LLC, Amgen, Helsinn, Novartis, Loxo/Lilly, AnHeart Therapeutics, Bristol Myers Squibb, Nuvalent; consulting for MonteRosa, Innocare, Boundless Bio, Treeline Bio, Nuvalent, 14ner/Elevation Oncology, Entos, Prelude, Bayer, Applied Pharmaceutical Science, Bristol Myers Squibb, Enlaza, Pfizer, Roche/Genetech, Nuvalent, Two River, Lilly/Loxo; has received funding to institution from Foundation Medicine, GlaxoSmithKlein, Teva, Taiho, PharmaMar; equity from mBrace and Treeline; has a copyright for selpercatinib-osimertinib (US 18/041,617, pending); royalties from Wolters Kluwer and UpToDate; and has CME Honoraria from Answers in CME, Applied Pharmaceutical Science, Inc, AXIS, Clinical Care Options, Doc Congress, EPG Health, Harborside Nexus, I3 Health, Imedex, Liberum, Medendi, Medscape, Med Learning, MedTalks, MJH Life Sciences, MORE Health, Ology, OncLive, Paradigm, Peerview Institute, PeerVoice, Physicians Education, Projects in Knowledge, Resources, Remedica Ltd, Research to Practice, RV More, Targeted Oncology, TouchIME, WebMD. J.J.L. has served as a compensated consultant for Genentech, C4 Therapeutics, Blueprint Medicines, Nuvalent, Bayer, Elevation Oncology, Novartis, Mirati Therapeutics, AnHeart Therapeutics, Takeda, CLaiM Therapeutics, Ellipses, AstraZeneca, Bristol Myers Squibb, Daiichi Sankyo, Yuhan, Merus, Regeneron, Pfizer, Roche, Gilead, Janssen, Nuvation Bio, Eli Lilly, Gilead, Triana, Nuvectis, and Turning Point Therapeutics; has received institutional research funds from Hengrui Therapeutics, Turning Point Therapeutics, Neon Therapeutics, Relay Therapeutics, Bayer, Elevation Oncology, Roche, Linnaeus Therapeutics, Nuvalent, Bristol Myers Squibb, Pfizer, Eli Lilly, and Novartis; and travel support from Pfizer, Merus, Takeda, and Bristol Myers Squibb.

Data Availability

The human sequencing data generated in this study are not publicly available due to patient privacy restrictions, as the raw sequencing files were not used or shared. For the purposes of this international consortium, the data on the gene alterations identified by the NGS platforms were collected from each participating institution rather than the raw sequencing files and are provided in the Supplementary Data. All other data generated in this study are included within the article and its supplementary files or are available upon request to the corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS2140953-supplement-1.docx (16KB, docx)
2
NIHMS2140953-supplement-2.docx (25.7KB, docx)
3
NIHMS2140953-supplement-3.docx (18.7KB, docx)
4
NIHMS2140953-supplement-4.xlsx (27.3KB, xlsx)

Data Availability Statement

The human sequencing data generated in this study are not publicly available due to patient privacy restrictions, as the raw sequencing files were not used or shared. For the purposes of this international consortium, the data on the gene alterations identified by the NGS platforms were collected from each participating institution rather than the raw sequencing files and are provided in the Supplementary Data. All other data generated in this study are included within the article and its supplementary files or are available upon request to the corresponding author.

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