Supplementary Figure S7. HER2 IHC Concordance In A Subset Of Breast Cancers With ERBB2-Activating Mutations (+) and (-) indicate the results of confirmatory FISH, if performed. ECD, Extracellular Domain; IDC, Invasive Ductal Carcinoma; ILC, Invasive Lobular Carcinoma; KD, Kinase Domain; NOS, Not Otherwise Specified

Circulating tumor DNA (ctDNA) has potential as a prognostic factor for predicting relapse in high-risk breast cancer (BC). This study investigates the utility of ctDNA assessment using a tumor-informed assay, in patients with high-risk BC treated with neoadjuvant chemotherapy (NAC). Thirty newly diagnosed patients with various high-risk BC subtypes participated, providing serial blood samples at multiple time points, including baseline, during NAC, and during follow-up. ctDNA was detected at baseline in 29/29 patients for whom an assay panel could be designed, with detection sensitivity reaching 0.0083% (variant allele frequency). Among patients with detectable baseline ctDNA, 94% showed clearance during treatment, correlating with improved outcomes. Additionally, ctDNA detection post-surgery or during follow-up predicted disease recurrence. These findings suggest that serial ctDNA monitoring throughout NAC and follow-up can effectively identify residual disease in BC and correlate with clinical outcomes.

Supplementary Figure 1: Number of cancer cases and deaths across indications in 2020, Millions

Supplementary Figure S11. Pan-Tumor Landscape Of ERBB2 Activating Alterations Detected In The MSKCC Clinicogenomic Cohort a) Prevalence of ERBB2 activating alterations (known or likely functional significance) across solid tumors in the MSKCC clinicogenomic cohort. ‘Multiple’ includes patients with AMP + MUT, AMP + RE, MUT + RE, AMP + MUT + RE and patients with >1 MUT. b) Cancer type distribution of ERBB2 MUT tumors. AMP, Amplification (CN ≥ 6); MUT, Mutation (SNV, Indel); RE, Rearrangement.

Supplementary Figure S10. HER2-Directed Therapy Response Modifying Alterations In Select Cancers (Related To Figure 4) Co-occurrence of alterations that have been reported to impact response to HER2-directed therapies (mAB, TKI, ADC) in tumors with ERBB2 amplification or ERBB2 activating mutations including TP53 MUT, PIK3CA MUT, CCNE1 AMP, RB1 MUT/DEL, PTEN MUT/DEL, ERBB3 AMP/MUT, EGFR MUT, MET AMP/Ex14 MUT, and IGF1R AMP. Patients with multiple ERBB2 alteration types (e.g., AMP + MUT) were excluded from the analysis. ADC, Antibody-Drug Conjugate; AMP, Amplification; mAB, Monoclonal Antibodies; MUT, Mutation (SNV, Indel); TKI, Tyrosine Kinase Inhibitor.

SUPPLEMENTARY MATERIALS & METHODS Foundation Medicine Comprehensive Genomic Profiling

Supplementary Figure S2. ERBB3 Activating Mutations In Select Cancers Distribution of ERBB3 mutations across key HER3 protein domains a) in the combined cohort of 5 major ERBB3 MUT cancer types and b) in each cancer type. The number of mutations is indicated. c) Lollipop plot mapping ERBB3 mutations across the HER3 protein in select cancer types. The two most frequent codon hotspots for each cancer type are labeled; % represent the proportion of observed mutations at a particular codon in the respective cancer type. AA, Amino Acid; ECD, Extracellular Domain; KD, Kinase Domain; MUT, Mutation (SNV, Indel); TMD, Transmembrane Domain.

Supplementary Table S2. Histology Breakdown Of Top 5 ERBB3 MUT Cancer Types

The co-occurrence of germline and somatic oncogenic alterations is frequently observed in breast cancer, yet their combined influence on tumour evolution and therapy resistance remains poorly defined. Through an integrated clinicogenomic analysis of more than 5,800 patients, we show that germline (g) pathogenic variants dictate the evolutionary trajectory of acquired resistance. We specifically find that gBRCA2-associated tumours are uniquely predisposed to develop acquired RB1 loss-of-function alterations, resulting in poor outcomes on standard-of-care frontline CDK4/6 inhibitor (CDK4/6i) combinations. This vulnerability is driven by a dual mechanism: baseline RB1 hemizygosity (heterozygous loss resulting in a single functional RB1 allele), which lowers the evolutionary barrier to biallelic inactivation, and ongoing homologous recombination deficiency, which promotes acquisition of RB1 loss-of-function alterations under the selective pressure of CDK4/6i. Preclinical models from gBRCA2 carriers showed near-uniform resistance to CDK4/6i, with consistent post-treatment Rb loss. Across multiple independent models and in our clinical data, PARP inhibition consistently outperformed CDK4/6i. Our findings suggest that prioritizing PARP inhibition in gBRCA2 carriers may intercept RB1-loss trajectories and delay resistance. More broadly, we establish a predictive framework for forecasting drug-resistant trajectories based on pre-treatment allelic configuration and mutational signatures.

Supplementary Figure S4. ERBB3 Mutation Landscape Of Select Cancers Shown for each cancer type are (Left) the distribution of mutations across key HER3 protein domains, (Middle) lollipop plot showing the location and incidence of mutations across the HER3 protein (NM_001982) with the 5 most frequently mutated codons labeled, and (Right) plot showing distribution of mutations among the 10 most frequently mutated codons. The number of mutations is indicated. AA, Amino Acid; ECD, Extracellular Domain; KD, Kinase Domain; TMD, Transmembrane Domain.

Supplementary Figure S5. Rare ERBB2 Activating Mutations In Select Cancers a) Distribution of ERBB2 TMD mutations combined across select cancers (Left) and number of TMD mutated tumors in select cancer types (Right). b) Distribution of Ex16Alt in the combined cohort (Left) and number of Ex16Alt tumors in select cancer types (Right). Ex16Alt, Exon 16 Alterations (Ex16 Deletion, Ex16 Splice Site); TMD, Transmembrane Domain.

Supplementary Figure S1. ERBB2/ERBB3 Amplification Pan-Tumor Landscape The distribution of amplification ratios for tumors with a) ERBB2 and b) ERBB3 amplification in tissue biopsies as assessed by FoundationOneCDx is shown. Amplification ratio is equal to the ratio of the modeled gene copy number to sample ploidy. Tumor types representing the highest proportion of ERBB2 or ERBB3 mutated tumors, respectively, which were the subject of focused analysis in this study are highlighted.

Loss-of-function (LOF) alterations in PTCH1 are a hallmark of basal cell carcinoma (BCC) and drive activation of the Hedgehog (Hh) signaling pathway. Hh inhibitors are approved to treat advanced BCC, but little is known about the frequency, biology, and treatment of PTCH1 alterations in other cancers. We analyzed PTCH1 LOF alterations across diverse solid tumors and evaluated outcomes of patients with non-BCC tumors who received Hh inhibitors. Among 121,490 tumor samples, 2064 (1.7%) harbored PTCH1 LOF alterations. Among 13 patients with non-BCC tumors treated with an Hh inhibitor, the response rate was 31%, with responses seen in sebaceous adenocarcinoma, squamous cell lung cancer (SCC), cutaneous SCC and glioblastoma. Median progression-free survival was 4.1 months, and median overall survival was 9.8 months. PTCH1 LOF alterations may identify a tumor-agnostic subset of patients who could derive benefit from Hh inhibitors beyond BCC, supporting further prospective evaluation.

Supplementary Figure S8. Co-Alteration Landscape Of ERBB2 Mutated Tumors In Select Cancers The prevalence of oncogenic co-alterations was compared for ERBB2 MUT (excluding samples w/ ERBB2 co-amplification) versus ERBB2 WT (non-mutated and non-amplified) a) NSCLC, b) Breast, c) CRC, d) Bladder, e) GEC, f) MSS CRC, and g) MSS GEC tumor samples profiled using tissue CGP. Only genes altered in at least 50 tumors and targeted across all tissue CGP assay versions were included. For each gene, mutations (SNVs, Indels), rearrangements, and copy number changes of known or likely functional significance detected using our assay were included. Genes highlighted in the National Comprehensive Cancer Network (NCCN) Guidelines as molecular drivers as well as genes altered at a high prevalence (≥10%) in either cohort are labeled for each volcano plot if a statistically significant difference was observed (p < 0.05, threshold indicated by dashed line). ERBB3, if statistically significant, is also labeled. Fisher’s Exact Test was performed to assess patterns of co-occurrence/mutual exclusivity between ERBB2 and other genes. P values were corrected using the Benjamini-Hochberg FDR method. MSS, Microsatellite Stable.

Supplementary Figure S6. ERBB2 Mutation Clonality Distribution of clonal fraction (VAF/TP) for ERBB2 mutation classes across select cancers. A dashed line at clonal fraction of 0.25 (25%) is shown as an estimated threshold for clonality1,2. ECD, Extracellular Domain; KD, Kinase Domain; TMD, Transmembrane Domain; TP, Computational Tumor Purity; VAF, Variant Allele Frequency. 1Sottoriva A, Graham TA. A pan-cancer signature of neutral tumor evolution. bioRxiv. 2015;014894. 2Bozic I, Gerold JM, Nowak MA. Quantifying Clonal and Subclonal Passenger Mutations in Cancer Evolution. PLoS Comput Biol. 2016;12:e1004731.

Supplementary Figure S3. ERBB2 Mutation Landscape Of Select Cancers Shown for each cancer type are (Left) the distribution of mutations across key HER2 protein domains, (Middle) lollipop plot showing the location and incidence of mutations across the HER2 protein (NM_004448) with the 5 most frequently mutated codons labeled, and (Right) plot showing distribution of mutations among the 10 most frequently mutated codons. The number of mutations is indicated. AA, Amino Acid; ECD, Extracellular Domain; KD, Kinase Domain; TMD, Transmembrane Domain.

Supplementary Figure 2: Number of cancer cases and deaths across geography in 2020, Millions

Supplementary Figure S9. EGFR/ERBB2/ERBB3 TMD Mutation Co-Occurrence In NSCLC The inner circle represents ERBB2 TMD mutations detected in NSCLC tumors (n = 98). The outer circle represents co-occurring EGFR and ERBB3 TMD mutations detected in the same tumors. TMD, Transmembrane Domain.

Supplementary Table 1: Authors and affiliations