The original MCF7 (RRID: CVCL_0031), T47D (RRID: CVCL_0553), and ZR-75-1 (RRID: CVCL_0588) cells were received from the Breast Cancer Task Force Cell Culture Bank, Mason Research Institute. The MCF-7-derived cell lines MF-R and MPF-R were developed by extended treatment with fulvestrant (100 nM) alone or combined with CDK4/6i (palbociclib, 150-200 nM), respectively. Cells grew in Dulbecco’s Modified Eagle Medium phenol red-free (DMEM/F12; Gibco) with 1% glutamine (Gibco), 1% heat-inactivated fetal bovine serum (FBS; Sigma-Aldrich), and 6 ng/mL insulin (Sigma-Aldrich) supplemented with 100 nM of fulvestrant and 200 nM CDK4/6i. MCF-7 cells grown in parallel with MPF-R cells without treatment in the media were designated M-S and remained sensitive to drug treatment. T47D cells were maintained in the Roswell Park Memorial Institute (RPMI) 1640 medium (Gibco) without phenol red, supplemented with 1% glutamine, 5% heat-inactivated FBS, and 8 µg/mL insulin. The T47D-derived fulvestrant- and combined CDK4/6i- and fulvestrant-resistant cell lines, TF-R and TPF-R, respectively, were established by long-term treatment with 100 nM fulvestrant alone or combined with 150-200 nM of CDK4/6i. T47D-sensitive cells grown in parallel with TPF-R were designated T-S and were maintained in the same medium as TPF-R cells without treatment. ZR-75-1 cells resistant to combined fulvestrant and palbociclib (ZPF-R) were established from fulvestrant-resistant cells (37) by long-term treatment (2 months) with 100 nM fulvestrant and increasing concentrations of palbociclib (weekly 2-fold increase, from 10 nM to 160 nM). Cells were cultured at 37°C in 5% CO₂ and tested regularly for mycoplasma with a MycoAlert detection kit (Lonza), and all experiments were performed with mycoplasma-free cells. Cells underwent authentication by short tandem repeat (STR) analysis in the past three years. Fulvestrant (ICI 182,780, Tocris) was dissolved in 96% ethanol, CDK4/6i palbociclib isothiocyanate (HY-A0065, MedChemExpress) was dissolved in water, RET inhibitor selpercatinib (also known as LOXO-292, HY-114370, MedChemExpress) was dissolved in DMSO (Sigma-Aldrich). The concentrations of CDK4/6i and RET inhibitor used for in vitro experiments were determined based on the IC50 for each cell line model.

Organoids were established from ER+ primary tumors as previously described [15]. Briefly, tumors were mechanically dissociated in a gentleMACS dissociator (Miltenyi Biotec) and enzymatically digested with 1 mg/mL collagenase (Thermofisher) for 1 hour at 37°C. After dissociation, cells were embedded in cultrex (Bio-techne) and plated in 15 µL domes in six-well cell culture plates. Plates were incubated for 30 minutes at 37°C for solidification of the matrix and then, organoid medium consisting of advanced DMEM/F12 (ThermoFisher) supplemented with 10 mM HEPES (Gibco), 1× Glutamax (Gibco), 1% penicillin/streptomycin (ThermoFisher), 2% Rspo3-Fc fusion protein conditioned medium (Ipatherapeutics), 1% Noggin-Fc Fusion Protein Conditioned Medium (Ipatherapeutics), 1x B27 Supplement (ThermoFisher), 5 mM Nicotinamide (Sigma Aldrich), 1.25 mM N-acetyl-ʟ-cysteine (Sigma Aldrich), 100 µg/mL Primocin (Invivogen), 5nM Heregulin β1 (PeproTech), 5 ng/mL FGF-7 (PeproTech), 10 ng/mL heat-stable FGF-10 (ThermoFisher), 0.5 µM A83-01 (Tocris Bioscience), 10 ng/mL EGF (PeproTech), 0.5 µM SB202190 (Sigma Aldrich) and 5µM Y-27632 dihydrochloride (AbMole Bioscience) was added. Media were renewed every 3 to 4 days. Organoids were dissociated using TrypleExpress (ThermoFisher) for 15 minutes. Before the described experiments, established organoids were tested for mycoplasma (MycoAlert, Lonza).

For drug testing, organoids were plated in 96-well plates at a concentration of 200 organoids/µL in cultrex (50 µL/well), followed by treatment with serially diluted CDK4/6i palbociclib, RETi selpercatinib or both, at different concentrations for 7 days. Cell viability was evaluated with RealTime-Glo™ MT cell viability assay (Promega) according to the manufacturer’s instructions. A Paradigm microplate reader (Beckman Coulter) and SoftMax pro 7.0.2 software were used to measure luminescence. Dose-effect curves were generated using GraphPad Prism software (version 9.0). Data was inputted into SynergyFinder (38) to calculate the Bliss synergy score.

Whole-cell extracts were obtained using RIPA buffer (50 mM Tris HCl (pH 8), 150 mM NaCl (pH 8), 1% IgePAL 630, 0.5% sodium deoxycholate, 0.1% SDS) with protease and phosphatase inhibitors (Thermo Scientific). Pierce BCA Protein Assay kit (Thermo Scientific) was used to determine protein concentration at 562 nm in the Paradigm microplate reader (Beckman Coulter). Protein (10-45 µg) was loaded on a 4-20% SDS-PAGE gel (Bio-Rad) under reducing conditions and electroblotted onto a PVDF transfer membrane (Bio-Rad). Tris-buffered Saline (TBS) with 0.1% Tween-20 (Sigma-Aldrich) and 5% non-fat dry milk powder (Sigma-Aldrich) was used to block membranes for one hour at room temperature. The following antibodies were used: Anti-RET (3223S, 1:250-1:1000), anti-phospho-Rb Ser780 (3590, 1:1000), anti-Rb (9309, 1:1000), anti-cyclin D1 (2978, 1:1000), anti-phospho-CDK2 Thr160 (2561, 1:500), anti-cyclin E2 (4132, 1:1000), anti-CDK2 (2546, 1:2000), anti-cyclin D3 (3223, 1:2000) and anti-cyclin A (4656, 1:2000) from Cell Signaling Technologies; anti-cyclin A2 (ab38, 1:500) and anti-CDK6 (ab12482, 1:5000) from Abcam; anti-cyclin E1 (sc-247, 1:100), anti-CDK4 (sc-23896), and anti-GAPDH (sc-32233, 1:20000) from Santa Cruz Biotechnology. Horseradish peroxidase (HRP)-conjugated goat anti-mouse (P0447, Dako, 1:5000) and HRP-conjugated goat anti-rabbit (P0448, Dako, 1:5000) antibodies were incubated in blocking buffer for one hour at room temperature. Membranes were developed with SuperSignal™ West Pico PLUS chemiluminescent Substrate (Thermo Scientific) and visualized on a ChemiDoc MP imaging system (Bio-Rad).

RET gene knockdown was performed using two different RET-specific siRNAs (RET_15, SI04950554 and RET_17, SI05089756), both from Qiagen and a nontargeting scrambled (control) siRNA used as the universal negative control (SIC001, Sigma-Aldrich). Chemical transfection was performed in M-S, MPF-R, T-S, and TPF-R cell lines with Lipofectamine 3000 transfection reagent (15282465, ThermoFisher Scientific) in Opti-MEM medium (Gibco) according to the manufacturer’s instructions. Efficiency was evaluated at the mRNA level 48 hours after transfection by quantitative real-time PCR (RT-qPCR) and at the protein level 96 hours after transfection with Western blotting. The effect of siRNA-mediated knockdown of RET on cell growth was evaluated with crystal violet assay at 24, 48, 96, and 144 hours after transfection.

TRI reagent^® (Sigma Aldrich) was used for total RNA extraction, and cDNA synthesis was performed with random deoxynucleic acid hexamers and reverse transcriptase (Fermentas). RT-qPCR with SYBR Green PCR Mastermix (Applied Biosystems) was performed according to the manufacturer’s instructions. The following primers (Qiagen) were used: RET (QT00047985, transcript ID: ENST00000355710, amplicon length 120), CDK6 (QT00019985, transcript ID: ENST00000265734, amplicon length 82), CDK4 (QT00016107, transcript ID: ENST00000257904, amplicon length 60) and cyclin D1 (QT00495285, transcript ID: ENST00000227507, amplicon length 96), and PUM1 (QT00029421, transcript ID: ENST00000257075, amplicon length 73) was used as a reference gene. The RT-qPCR reactions were performed using a StepOnePlus system (Applied Biosystems), and data were analyzed with StepOne Software. Reactions were conducted in triplicates, and data were analyzed with the delta-delta CT method (39).

Gene expression analysis was performed on RNA purified from three biological replicates of the combined CDK4/6i- and fulvestrant-resistant cell lines MPF-R and TPF-R treated with control or RET siRNAs using Human Transcriptome Arrays 2.0 (HTA). Cells were grown to reach 70-80% confluency, and RNA was purified using TRI reagent® according to the manufacturer’s instructions. Transcriptome Analysis Console (TAC) software (ThermoFisher) was used for data analysis. Genes from the dataset that exhibited a two-fold or greater alteration in expression with a false discovery rate (FDR) < 0.05 cut-off and p < 0.05 with one-way ANOVA were considered significantly regulated. Gene Set Enrichment Analysis (GSEA 4.3.2) was performed to identify the gene sets enriched in the resistant cells. Microarray gene expression data from the tumor biopsies in the NeoPalAna trial (40) was used to investigate RET expression (GSE93204). Normalized RET expression data from baseline samples from CDK4/6i-sensitive or -resistant patients were used for the analysis.

Exon-spanning primers were designed to perform RNA sequencing (primer sequences are available upon request). RNA from three independent experiments were prepared for sequencing on the Illumina NovaSeq 6000 platform using the NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and the NEBNext Ultra II DNA Library Prep Kit for Illumina (New England Biolabs) with unique dual indexes according to the manufacturer’s instructions. FASTQC (Babraham Bioinformatics) was used to assess the quality of raw sequencing reads, and adaptor sequences were removed using the FASTX toolkit. Trimmed Reads were aligned to the human genome (hg38) using the Spliced Transcripts Alignment to a Reference (STAR) software with default parameters (41). Tags in exons were counted using iRNA-seq (42), and differential expression (FDR-adjusted p < 0.05) between three independent replicates of sensitive cell line and double-resistant cell line samples was determined using DESeq2 (43). Genes with FDR ≤ 0.05 and a log2 fold change > 1.0 in either direction were defined as statistically significant. GSEA and gene ontology (GO) enrichment analysis with ShinyGO (v0.80) were used to identify the gene sets enriched in cells resistant to combined CDK4/6i and fulvestrant versus fulvestrant alone. To identify candidate fusion transcripts from the sequence data, fusion calling was performed on the fastq files using FusionCatcher version 1.33 (44), STAR-fusion version 1.11.0 (45), and Arriba version 2.3.0 (46), with default settings. The GRCh38/hg38 build was used as the human reference genome.

Cells were seeded at 20,000-50,000 cells/well in 96-well plates, and drugs or vehicles were added after 24 hours. Cell growth was evaluated using a crystal violet-based colorimetric assay wherein cells were incubated with a crystal violet solution for 5 minutes, followed by three washes in ddH2O and overnight drying. Cellular crystal violet was extracted by incubation with a 0.1 M citrate buffer (29.41 g sodium citrate dissolved in 50% water and 50% ethanol, pH=6) for 30 minutes on a shaker at room temperature. Reading measurements were performed in a Paradigm microplate reader at 570 nm and data were analyzed with SoftMax pro 7.0.2 software.

The web tool Kaplan-Meier (KM) plotter (47) was used to generate survival curves for ER+ breast cancer patients based on mRNA expression (gene chip) of RET. All datasets available in the KM plotter were included in the analysis. The inclusion criteria were ER status positive by IHC, HER2 status negative by array, and previous treatment with endocrine therapy. These criteria were independent of pathological characteristics such as grade, lymph node status, and previous chemotherapy. The JetSet optimal probe was selected for RET (probe ID 211,421). The ‘auto select best cutoff’ option was used to evaluate all possible cutoff values between the lower and upper quartiles, and the best performing threshold was selected as a cutoff ( Supplementary Table S1 , selected cutoff highlighted). The endpoints were relapse-free survival (RFS) and overall survival (OS).

Formalin-fixed, paraffin-embedded (FFPE) ER+ metastatic tumor lesions from patients treated with combined CDK4/6i and endocrine therapy were obtained from Odense University Hospital (OUH) (N = 115). Inclusion criteria were patients with ER+ advanced breast cancer treated with combined CDK4/6i and endocrine therapy in the metastatic setting who had undergone surgery or biopsy at OUH. Tumor sections with ER expression ≥ 1% were considered ER+. Exclusion criteria were insufficient tumor material and no metastatic biopsy before starting treatment with combined CDK4/6i (palbociclib or ribociclib) and endocrine therapy (letrozole or fulvestrant). These criteria yielded N = 83 patients. Progression-free survival (PFS) was described as the time from starting treatment with combined CDK4/6i and endocrine therapy until disease progression or death.

FFPE blocks of patient metastatic lesions were sectioned at 4 µm with a microtome and mounted on ChemMateTM Capillary GAP slides (Dako). Sections were dried at 60°C, deparaffinized, hydrated, and endogenous activity was blocked. Unmasking of epitopes was achieved by boiling sections in a T-EG solution. The following primary antibody was used: anti-RET antibody (ab134100, 1:50). Primary antibody binding for anti-RET was detected with Optiview-DAB (8–8), EnV, FLEX/HRB+ Rabbit LINK 15-30. An experienced breast pathologist evaluated the clinical samples in a blinded setup. RET protein was primarily expressed in the cytoplasm. The staining intensity was recorded on a semi-quantitative scale of 0-3, with 0 meaning absolutely no reaction and 3 as the most intense staining. The cut-off value for positive versus negative was set as intensity ≥ 1 versus intensity = 0 and determined based on the survival significance.

GraphPad Prism v.9.4.0 software was used for statistical analyses. One-way analysis of variance (ANOVA) and two-tailed t-test were performed to determine statistical significance among data for the in vitro studies (as indicated in the figure legends). Kaplan-Meier estimates generated survival curves for the clinical data, and the log-rank test was used to test the correlation between the expression levels of RET and the PFS. p-values were defined as follows: *p<0.05, **p<0.01, *** p<0.001, and **** p<0.0001.

To investigate the resistance mechanisms to combined CDK4/6i and fulvestrant, we utilized two ER+ breast cancer cell line models resistant to combined CDK4/6i and fulvestrant derived from MCF7 and T47D cells (MPF-R and TPF-R, respectively), which have been previously described (37, 48). To identify the resistance mechanism associated specifically with combined CDK4/6i and fulvestrant rather than fulvestrant alone, we evaluated gene expression alterations in MPF-R and TPF-R cells compared to the respective cell lines resistant to fulvestrant alone (MF-R and TF-R). We focused on this comparison instead of comparison with drug-sensitive cells (M-S and T-S) since we aimed to identify gene alterations uniquely associated with resistance to the combination therapy and distinct from those caused by endocrine therapy alone. Using RNA-sequencing, we identified a total of 1103 genes (523 upregulated and 580 downregulated) that exhibited significantly altered expression in MPF-R versus MF-R, and 1041 genes (600 upregulated and 441 downregulated) that exhibited significantly altered expression in TPF-R versus TF-R cells (fold-change ≥ 2, FDR < 0.05, Wald significance test p < 0.05). Gene set enrichment analysis (GSEA) was performed to identify the most altered pathways in combined CDK4/6i and fulvestrant-resistant vs. fulvestrant-resistant cells. The enrichment analysis revealed that the top hallmark pathways altered in both MPF-R vs. MFR and TPF-R vs. TFR included “estrogen response early” and “estrogen response late” ( Figures 1A, B ). Although RET ranked 34^th and 15^th in the list of genes enriched in the gene set “estrogen response” in MPF-R and TPF-R cells, respectively ( Figure 1C ), only a few genes were shared between the two models, with RET consistently being in the top 5 of the common genes. Notably, neither model showed an alteration of the RET ligand GDNF between resistant and sensitive cells. These findings, together with the established role of RET in ER+ breast cancer, prompted us to further investigate RET in the context of resistance to combined CDK4/6i and endocrine therapy. Increased expression of RET was also observed in MPF-R and TPF-R compared to M-S and T-S cells, respectively ( Figure 1D ). Notably, RET expression levels were significantly higher in the MCF7-derived cells than in the T47D-derived cells, as previously reported (16), which suggests a more critical role for RET in MCF-7 cells. Next, we investigated whether RET-fusions could be identified in our RNA sequencing data of MPF-R, TPF-R, MF-R, TF-R, M-S, and T-S cells. However, no fusion transcripts involving the RET gene were identified in any of the ER+ breast cancer cell lines using three fusion callers (Fusioncatcher, STAR-fusion, and Arriba). Notably, combined fulvestrant and CDK4/6i-resistant cells do not exhibit RET mutations or alterations associated with known/putative mechanisms of resistance towards CDK4/6i, such as ESR1 mutations or CDK4 or CDK6 amplifications (48). To further validate the overexpression of RET in combined CDK4/6i- and fulvestrant-resistant cells, qPCR and Western blotting were performed. Overexpression of RET at the mRNA and protein levels in resistant cells was confirmed ( Figures 1E, F ). Importantly, while RET expression is elevated in fulvestrant-resistant cells compared to sensitive cells, the highest expression levels are observed in combined CDK4/6i- and fulvestrant-resistant cells ( Figure 1F ). Because of the higher levels of RET in the MCF7 model, the amount of protein from T47D-derived cells loaded to detect RET expression was five times that from MPF-R cells ( Figure 1F ). Our findings support a significant upregulation of RET in both cell line models resistant to combined CDK4/6i and fulvestrant.

To investigate RET’s role in the resistance mechanism to combined CDK4/6i and fulvestrant, we performed gene knockdown by using two specific siRNAs targeting RET (RET15 and RET17) and a scrambled siRNA (control). RET was efficiently silenced in both MCF-7- and T47D-derived sensitive and resistant cell lines when using the individual and pooled RET-siRNAs compared with the control siRNA, as determined by RT-qPCR and Western blotting ( Figures 2A, B ). It was not possible to visualize the RET knockdown in T-S cells by Western blotting due to the extremely low levels of RET in these cells. Silencing of RET significantly reduced the growth of M-S and MPF-R cells compared to the control siRNA ( Figure 2C ), indicating that these cells depend on the expression of RET for proliferation and growth. The same effect on cell growth upon RET siRNA-mediated knockdown was not observed in T-S and TPF-R cells, which may be due to the significantly lower level of RET in these cells.

To identify pathways altered following RET silencing, we performed gene expression analysis on MPF-R and TPF-R cells transfected with RET-siRNA (pooled RET15 and RET17) compared to cells transfected with control siRNA (scrambled). Remarkably, alterations in regulators of the cell cycle, particularly regulators of the G2-M phase and E2F targets, were identified as the most significantly enriched gene datasets by GSEA in control-siRNA compared to RET-siRNA treated MPF-R and TPF-R cells ( Figures 3A, B , respectively). In both MCF7- and T47D-derived resistant cells, RET knockdown significantly correlated with reduced gene expression of regulators of late cell cycle phases. These findings were validated by Western blotting, showing that levels of cyclin B1, the primary regulator of early events of mitosis, together with E2F2 and, to a lesser extent, cyclin D1/2, were lower in MPF-R treated with RET-siRNA compared to cells treated with control-siRNA ( Figure 3C ). Conversely, multiple regulators of G1-S phase transition, such as CDK4/6, cyclin D3, p-Rb, CDK2, and cyclin E, were found upregulated, likely to compensate for the cell division inhibition induced by RET knockdown. Together, our data suggest that RET is a driver of cell cycle progression at the G2-M phase of the cell cycle in combined CDK4/6i- and fulvestrant-resistant ER+ breast cancer cells.

To evaluate whether we could pharmacologically overcome resistance to combined CDK4/6i and fulvestrant, we examined the effect of the RET-selective inhibitor, selpercatinib, alone or in combination with CDK4/6i and/or fulvestrant, on the growth of MPF-R and TPF-R cells resistant to CDK4/6i and fulvestrant. Although the concentration of selpercatinib selected based on the IC50 calculation was high (5 µM), it remains within the maximum serum concentration observed in patients (mean steady-state Cmax 2980 ng/mL or 5.67 µM) (49). Treatment with selpercatinib resensitized resistant MPF-R and TPF-R cells to combined CDK4/6i and fulvestrant ( Figures 4A, B ). Indeed, incubation with the triple combination consisting of fulvestrant, CDK4/6i, and RETi significantly reduced the growth of MPF-R cells compared to combined CDK4/6i and fulvestrant. Furthermore, the triple combination more efficiently inhibited the growth of TPF-R cells compared to dual therapy with fulvestrant and RETi, although the difference did not reach statistical significance. Interestingly, the dual combination with RETi and either fulvestrant or CDK4/6i reduced MPF-R and TPF-R cells growth more efficiently than combined CDK4/6i and fulvestrant ( Figures 4A, B ). These data further indicate that ER+ breast cancer cells utilize RET upregulation to acquire resistance to combined CDK4/6i and endocrine therapy.

To validate these findings, we tested the efficacy of RETi in combination with fulvestrant with or without CDK4/6i in another combined CDK4/6i- and fulvestrant-resistant ER+ cell model derived from ZR-75-1 cells ( Supplementary Figures S1A, B ). Consistently with the findings in the other two models, we observed that all treatments significantly inhibited the growth of sensitive Z-S cells in comparison to the vehicle, while the growth of combined CDK4/6i- and fulvestrant-resistant ZPF-R cells was only significantly inhibited by the triple combination with fulvestrant, CDK4/6i and RETi ( Supplementary Figure S1B ). Furthermore, we investigated changes in cell cycle regulators upon treatment with the RETi selpercatinib in the three ER+ cell line models ( Figure 4C ; Supplementary Figure 1C ). Treatment with selpercatinib induced marked reductions in cyclin B1 levels, a key regulator of early mitotic events, particularly when combined with a CDK4/6i. These findings parallel the trends observed following RET siRNA-mediated knockdown ( Figure 3C ). However, contrary to the upregulation of multiple modulators facilitating G1-S phase transition observed after RET knockdown, treatment with selpercatinib led to more efficient inhibition of these regulators, including CDK4, CDK6, cyclin D, and Rb, while leaving others unchanged ( Figure 4C ; Supplementary Figure 1C ). Notably, the CDK inhibitor p21 showed a substantial increase following treatment with RETi. Collectively, these data underscore a blockade of both early and late cell cycle phase progression by RET inhibition with selpercatinib, thereby suggesting a more profound suppression of cell cycle activity.

Next, we evaluated the efficacy of RETi selpercatinib and CDK4/6i palbociclib, alone or combined, in ER+ patient-derived breast cancer organoids (PDO-P48) that exhibited high IC50 towards CDK4/6i, and thus primary resistance to this treatment ( Figure 5 ). This model exhibited increased CDK4, CDK6, and CCND1 expression upon treatment with CDK4/6i ( Figure 5A ). Importantly, combined CDK4/6i and RETi markedly impaired PDO viability at lower concentrations (10 µM) compared to either CDK4/6i or RETi alone (50 and 100 µM, Figure 5B ). Notably, the IC50 of combined CDK4/6i and RETi was lower than that of CDK4/6i alone in PDO-P48 ( Figure 5C ). Treatment of the organoids with 10 µM of CDK4/6i and RETi, combined or as single agents, showed that the combined treatment reduced cell viability relative to controls (untreated organoids), while CDK4/6i or RETi alone did not impair the organoid’s viability ( Figures 5D, E ). The combination of CDK4/6i and RETi demonstrated significant synergy within the concentration range 0.001-10 µM of RETi and 0.0001-1µM of CDK4/6i, as assessed using the Bliss model ( Supplementary Figure S2 ; Mean synergy score: 22.85, p=3.91e-51). These data support the efficacy of combined CDK4/6i and RETi in tumors with poor response to CDK4/6i, such as PDO-P48.

Finally, we evaluated the clinical relevance of RET by assessing the correlation between RET expression and clinical outcomes in ER+ breast cancer patients. We first used the web-based tool Kaplan-Meier plotter (50) to assess the correlation between RET mRNA expression and overall survival (OS) and relapse-free survival (RFS) in a cohort of ER+ breast cancer patients receiving endocrine treatment in the primary setting. High RET mRNA expression significantly correlated with shorter OS (n=189, p=0.05, HR=1.92; Figure 6A ) in ER+, HER2- breast cancer patients treated with endocrine therapy. The estimated 10-year survival was 70% for patients with high RET expression and 85% for patients with low RET expression ( Figure 6A ). High RET expression was also associated with shorter RFS (n=1201, p=0.054, HR=1.3; Figure 6B ). The median time to relapse was 15 years (180 months) in the high-RET group, whereas the median time to progression in the low-RET group was 16 years (200 months) ( Figure 6B ). Multivariate analysis including RET, MKi67, and ESR1 expression levels revealed that MKi67 and RET expression are independent prognostic factors for RFS (HR 1.52, p = 0.0017; HR 1.34, p = 0.034, respectively) but not for OS (HR 1.14, p = 0.73; HR 1.89, p = 0.061, respectively; Supplementary Table S2 ).

Next, we evaluated the clinical relevance of RET as a biomarker of response/resistance to combined CDK4/6i and endocrine therapy in a cohort of ER+ advanced breast cancer patients that has been previously described (37, 48). The protein expression levels of RET were evaluated in whole sections of metastatic lesions before treatment initiation with combined CDK4/6i and endocrine therapy. RET score was determined on a semi-quantitative scale of 0-3, with 0 meaning no staining and 3 as the most intense staining ( Figure 6C ). Although the survival analysis indicated shorter median survival in the RET-positive (intensity ≥1) compared to RET-negative (intensity = 0) groups (11.83 and 21.87 months, respectively), differences in progression-free survival (PFS) between the two groups were not statistically significant (p=0.92, Figure 6D ). Finally, we observed a higher mean of RET relative expression at baseline in the CDK4/6i-resistant compared to the -sensitive samples (1.08 and 0.93, respectively) in the neoadjuvant NeoPalAna trial ( Supplementary Figure S3 ), which assessed the antiproliferative activity of the CDK4/6i palbociclib in breast cancer neoadjuvant setting (40).