Supplementary Figure S21 shows Venn diagrams of CNV-confirmed cancer cells and their coexpression of DLL3, SEZ6, B7H3 for tumors in Cohort C.
Supplementary Figure S24 shows the distribution of DLL3 positive cells based on cell type for Cohort B and patient 37.
Supplementary Figure S17 shows graphs of CD4+ T cells phenotypic profiles for memory, activation and exhaustion.
Supplementary Figure S5 shows single-cell transcriptional landscape of SCLC tumor biopsies and CNV for Cohort B.
Supplementary Figure S2 shows the CTC-iCHIP workflow and images of staining optimization using control cancer cell lines.
Supplementary Figure S9 shows that the fraction of DLL3-positive tumor cells does not significantly correlate with the distribution of SCLC molecular subtypes in primary tumors across cohorts.
Supplementary Figure S8 shows fraction of DLL3 negative tumor cells based on single-cell RNA-seq “drop out” of rare transcripts.
Supplementary Figure S12 shows isoform characterization of DLL3 including protein structure, expression and isoform profiles for specific patients.
Supplementary Table S1 shows patient demographics and clinical characteristics for Cohort A.
Supplementary Figure S4 shows the size distribution of the CTCs based on their marker expression profiles.
Supplementary Figure S16 shows CD4+ T cells phenotypic profiling for individual markers in control sample HD2.
Markers of T-cell dysfunction in patients with acquired tarlatamab resistance despite persistent DLL3 expression. A, Box plot representing flow cytometric analysis of PBMCs showing the percentage of CD8+ (left) or CD4+ (right) live T cells. Blood specimens analyzed from healthy donors (HD: gray, N = 3), tarlatamab-untreated advanced SCLC (Pre-Tx: orange, N = 5), SCLC cases at the time of tarlatamab response (Resp.: blue, N = 4), and patients with SCLC with acquired resistance to tarlatamab despite persistent DLL3 expression in CTCs (Prog.: red, N = 2, open circles denote two distinct measurements from one case). For A–E and G–I, multiple measurements from a single patient (where available) were averaged for statistical comparison using the Student unpaired t test between Resp. vs. Prog. groups. B, Percentage of central memory (CM) CD8+ T cells (phenotype: CD45RA−CCR7+CD28+) versus effector memory subtype 1 (EM1) CD8+ T cells (phenotype: CD45RA−CCR7−CD28+). C, Percentage of KLRG1+ cells within activated (PD-1+) CD8+ T cells. D, Percentage of GZMB+ cells within activated (PD-1+) CD8+ T cells. E, Percentage of CD39+ cells within activated (PD-1+) CD8+ T cells. F, Percentage of GZMB+ cells within PD-1+CD8+ T cells, with and without CD39 expression, across all SCLC samples. Statistical comparison between CD39+ (dark red) and CD39− (gray) cells was done using the Student paired t test (N = 9 SCLC cases, including Pre-Tx, Resp., and Prog.). Samples with fewer than 50 recorded T cells in either the CD39+ or the CD39− group were excluded. G, Percentage of PD-1+ cells within total CD8+ T cells. H, Percentage of TIM3+ cells within activated (PD-1+) CD8+ T cells. I, Percentage of TOX+ cells within activated (PD-1+) CD8+ T cells.
Supplementary Figure S19 shows Venn diagrams of CNV-confirmed cancer cells and their coexpression of DLL3, SEZ6, B7H3 for tumors in Cohort B.
Differential CTC expression of DLL3 upon acquired resistance to tarlatamab. A, Representative case (patient 1) showing total CTC enumeration and DLL3 staining in a DLL3High patient with initial profound response to tarlatamab, whose CTCs show complete loss of expression of the targeted epitope at the time of acquired resistance and disease progression. CTC counts are normalized to 20 mL, with the percentage DLL3-positive (orange) versus DLL3-negative (green) shown for each time point during the course of treatment (arrowheads: tarlatamab cycles). B, Another representative tarlatamab-responsive DLL3High case (patient 8) in which increasing numbers of CTCs at the time of acquired drug resistance show universally persistent expression of the targeted DLL3 epitope. C, Relative fraction of DLL3Pos patients who initially benefited from tarlatamab (PR or SD), whose CTCs at the time of cancer progression are either above (positive) or below (low) the median 25% cutoff for DLL3 expression (N = 5).
Antibody-drug conjugates (ADCs) target surface proteins on cancer cells, leading to internalization and delivery of a drug payload, thereby enhancing selectivity and minimizing toxicity. ADCs against TROP2 (Sacituzumab govitecan) or HER2 (T-DXd) have demonstrated efficacy in metastatic breast cancer, yet paradoxically, outside of HER2-amplified breast cancers, expression levels of these breast cancer-enriched epitopes in tumor biopsies have not been strongly correlated with clinical response. We undertook serial quantitative imaging of circulating tumor cells (CTCs) in a prospective cohort of 35 patients treated with either of these ADCs. At the single-cell level, expression of TROP2 and HER2 within individual patients is highly heterogeneous in both CTCs and paired tumor biopsies. Measurement of these epitopes on CTCs immediately prior to ADC therapy does not predict depth of clinical response. However, absence of CTCs or >80% reduction in CTC numbers after three weeks of treatment (CTCLow) predicts durable response, compared with CTCHigh cases (TROP2: HR 5.15, P = 0.012; HER2: HR 6.01, P < 0.001). Targeted epitopes are not commonly downregulated on CTCs at the time of acquired clinical resistance, and switching between TROP2- and HER2-targeting ADCs sharing similar payloads infrequently leads to second-line response. Thus, while CTC burden is correlated with response to these ADCs, the level of TROP2 or HER2 expression is poorly predictive. These findings point to sensitivity to the drug payload as a potential driver of clinical response to currently approved ADCs in breast cancer.
Supplementary Figure S13 displays a gallery of CTFs in specific patient samples following the onset of tarlatamab therapy.
Supplementary Figure S16 shows CD4+ T cells phenotypic profiling for individual markers in control sample HD2.