Citations

569 Background: Several studies established the prognostic role of both the amount and locations of tumor-infiltrating lymphocytes (TILs) in TNBC. Three distinct immunotypes were described based on the amount and locations of TILs: immune enriched (IN), immune excluded, and immune desert. Using single-cell spatial transcriptomic analysis in the Mayo Clinic TNBC cohort, our previous studies showed the central role of interferon (IFN) signaling in IN phenotype. Herein, we evaluated the association between IFN and outcomes in TNBC in 3 independent datasets. Methods: NanoString IO360 was performed in 114 samples from FinXX (NCT00114816) to generate 22-gene IFNα and 33-gene IFNγ signatures. RNA sequencing was performed in 388 samples from CALGB 40603 (NCT00861705). 3038 TNBC samples were tested by WTS (NovaSeq; Caris Life Sciences, Phoenix, AZ). Median values were used as cut-offs for high vs low IFNγ RNA expression and 18-gene IFNγ signature scores. Caris Life Science CODEai was used to evaluate real-world overall survival (OS) obtained from insurance claims and calculated from tissue collection to last contact using Kaplan-Meier estimates. Chi-square, Mann-Whitney U, ANOVA, and Cox regression were used. Results: A high 22-gene IFNα signature score was associated with significantly improved recurrence-free survival (RFS) in FinXX (hazard ratio [HR] 0.32, 95% confidence interval [CI] 0.14-0.74, p 0.007) and OS (HR 0.28, 95%CI 0.12-0.66, p 0.003). Similar findings were observed with 33-gene IFNγ signature with significant improvement in RFS (HR 0.21, 95%CI 0.09-0.51, p < 0.001) and OS (HR 0.18, 95%CI 0.08-0.44, p < 0.001). Furthermore, in CALGB 40603, both IFNα and IFNγ scores were positively associated with pathologic complete response (pCR: IFNα p 0.019 and IFNγ p 0.007) and residual cancer burden (RCB: IFNα p 0.044 and IFNγ p 0.013). Using the Caris data platform to further validate, we identified 2899 TNBC patients (pts) with genomic and clinical outcome data. High IFNγ expression was associated with significant improvement in OS (25.95 vs 17.43 months; HR 0.65, 95% CI 0.59 – 0.72, p < 0.001). Similarly, pts with high IFNγ signature scores had significant improvement in median OS (25.79 vs 16.22 months; HR 0.66, 95% CI 0.6 – 0.73, p < 0.001). Conclusions: This study underscores the pivotal role of IFN signaling in TNBC. High IFNα and IFNγ signatures were consistently associated with improved RFS, OS, higher pCR rates, and lower RCB across clinical trial cohorts and real-world data. These findings signify IFN signaling as a potential key biomarker and therapeutic target in TNBC. Support: U10CA180821, U10CA180882, U24CA196171; Breast Cancer Research Foundation, Mayo Clinic Breast Cancer SPORE (P50CA116201-17), Bankhead Coley, W81XWH-15-1-0292, P50CA015083, R35CA253187; https://acknowledgments.alliancefound.org . Genentech. Clinical trial information: NCT00114816 and NCT00861705 .

548 Background: TNBC is associated with higher risk of recurrence and poorer survival rates than other breast cancer subtypes. For node-positive TNBC or tumors larger than 0.5 cm, chemotherapy is generally recommended. For stage I TNBC, the benefit from chemotherapy, the optimal regimen, and whether to administer it in the neoadjuvant versus adjuvant setting remain controversial. Here, we report the treatment patterns and clinical outcomes of patients with stage I TNBC treated at Mayo Clinic. Methods: Using the Mayo Clinic Tumor Registry data, we identified patients with stage I TNBC treated between 2010 and 2021. We used the pathologic tumor (T) category for patients treated with upfront surgery and the clinical T category for patients receiving neoadjuvant chemotherapy. We used the Kaplan-Meier method and log-rank test to compare recurrence-free survival (RFS) according to treatment groups, measured from the day of surgery. RFS was reported at a median follow-up of 3.9, 6.2, and 7.3 years for patients who received chemotherapy neoadjuvantly, adjuvantly, and surgery alone with no chemotherapy, respectively. Results: A total of 602 patients with Stage I TNBC were included, with a median age of 62 years. 290 (48%) underwent upfront surgery followed by adjuvant chemotherapy (pT1a: 2%, pT1b: 25%, pT1c: 74%), 127 (21%) received neoadjuvant chemotherapy followed by surgery (cT1a: 2%, cT1b: 11%, cT1c: 87%), and 185 (31%) underwent primary surgery without any chemotherapy (pT1mi/T1a: 33%, pT1b: 32%, pT1c: 35%). Most patients treated with neoadjuvant therapy received anthracycline/cyclophosphamide + taxane (70%), while most patients treated in the adjuvant setting received a non-anthracycline containing regimen (60%). The 5-year RFS was 96% (95% CI: 93-100%) for patients who received chemotherapy neoadjuvantly, 95% (95% CI: 92-98%) for those who received chemotherapy adjuvantly, and 85% (95% CI: 80-91%) for those treated with surgery alone and no chemotherapy ( P < 0.0001). 71 (56%) of the 127 patients who received neoadjuvant therapy achieved a pCR, with only 1 RFS event (at 14 months) in that group, compared to 4 RFS events among those not achieving pCR (at 12, 20, 28 and 75 months, respectively). Among patients not receiving chemotherapy (either adjuvantly or neoadjuvantly), the 5-year RFS rates were 94% for pT1mi/T1a, 92% for pT1b and 72% for pT1c (T1mi/a/b vs T1c, P = 0.009). Conclusions: In this large cohort of stage I TNBC, patients who received chemotherapy (adjuvantly or neoadjuvantly) had better 5-year RFS compared with those treated with locoregional therapy only. Among patients receiving chemotherapy, 5-year RFS was nearly identical regardless of whether chemotherapy was administered before or after surgery. Interestingly, patients undergoing upfront surgery were more likely to receive an anthracycline-sparing chemotherapy regimen.

9503 Background: Neoadjuvant ± adjuvant immunotherapy improves event-free survival relative to adjuvant immunotherapy alone for patients with high-risk resectable stage III melanoma. However, the optimal regimen balancing efficacy and tolerability is not known. T-cell immunoglobulin and ITIM domain (TIGIT) is a promising immune checkpoint but its therapeutic potential in stage III melanoma is underexplored. Methods: In this phase II trial, patients with resectable, macroscopic stage III melanoma received four 21-day neoadjuvant cycles of 1200mg IV atezolizumab (atezo, anti-PD-L1) + 600mg IV tiragolumab (tira, anti-TIGIT), followed by therapeutic lymph node dissection (TLND) and eight 21-day adjuvant cycles of 1200mg IV atezo. Primary endpoints were pathologic response (of all patients initiating neoadjuvant therapy) and recurrence-free survival (RFS) from the time of TLND in patients who were operated on per protocol and received adjuvant therapy. Secondary endpoint was adverse events (AEs); exploratory endpoints included event-free survival (EFS) and distant metastasis-free survival (DMFS). Results: Thirty-four patients, median age 59 years, were accrued and initiated neoadjuvant atezo/tira. 76.5% had >1 metastatic lymph node involved at baseline and 73.5% presented with Stage IIIC disease. All 34 patients were evaluable for AEs, pathologic response and EFS. Four patients were diagnosed with metastatic disease during neoadjuvant treatment, while 30 had TLND per protocol and 28 received adjuvant treatment and were evaluable for RFS and DMFS. Major pathologic responses (MPR, ≤10% viable tumor) were observed in 16/34 patients (47.1%, Table). With 19.9 months median follow-up from registration, 12-month EFS was 72.0% (95% CI 57.9 to 89.5%). With 16 months median follow-up from operation, 12-month RFS was 73.3% (n=28, 95% CI 56.9 to 94.5%), while 12-month DMFS was 86.0% (n=28, 95% CI 72.2 to 100%). In the 16 patients with an MPR, 2 did not receive adjuvant treatment and were followed for 33.3 and 10.8 months without recurrence/death. In the remaining 14 patients, 12-month RFS and 12-month DMFS were both 91.7% (95% CI 77.3 to 100%). 5 patients (14.7%) experienced any grade 3+ AE with 2 (5.9%) at least possibly related to the neoadjuvant regimen. Conclusions: Among patients with high-risk resectable stage III melanoma, neoadjuvant atezo/tira was a promising regimen with a favorable safety profile and warrants further study. Identification of predictive biomarkers will allow for optimization of neoadjuvant therapy for individual patients. Clinical trial information: NCT03554083 . Pathologic response. N=34 Major Pathologic Response 16 (47.1%) Pathologic complete response (no viable tumor) 13 (38.2%) Near-pathologic complete response (0.1−10% viable tumor) 3 (8.8%) Pathologic partial response (>10.0−50% viable tumor) 2 (5.9%) Pathologic non-response (>50% viable tumor) 12 (35.3%) No per protocol operation 4 (11.8%)

The National Comprehensive Cancer Network (NCCN) recommended surveillance imaging intervals for uveal melanoma (UM) based on the risk of distant metastasis. The objective of this research is to evaluate if patients, treated at our tertiary cancer center, who had scans consistent with these guidelines, had improved overall survival (OS). This was a single-center, retrospective study of UM patients, who developed metastatic disease. Patients were grouped into risk-of-metastasis cohorts (low, medium, and high-risk) based on the UM NCCN guidelines v1.2023. The frequency of scans was reported within annual intervals for 5 years within the low-risk cohort and for 10 years within the medium-risk cohort, and within 6-month intervals for the first 5 years and then annually in years 6–10 within the high-risk cohort. Conditional landmark analyses were used to evaluate the relationship between OS and consistency with guidelines. Scan frequency was evaluated against socioeconomic status. Of the 740 UM patients identified (1997–2020), 110 experienced metastasis and comprised our analysis population (20 low-risk; 67 medium-risk; and 23 high-risk). The median time to death (95% confidence interval) from diagnosis of metastasis was similar between the low, medium, and high-risk cohorts at 1.2 (1.0, 2.0), 2.0 (1.7, 2.6), and 1.6 (1.3, 2.3) years, respectively. For each cohort, the OS results were similar between those who followed guidelines vs. not at each annual landmark time. Living in disadvantaged areas did not impact imaging frequency (all P > 0.05). Imaging at intervals outlined by the NCCN guidelines v1.2023 did not impact OS for patients who developed metastatic UM.

Abstract Purpose: While an addition of immune checkpoint inhibitor (ICI), pembrolizumab, has improved outcomes of patients with TNBC, early-stage TNBC patients with residual cancer burden (RCB) II/III after neoadjuvant chemotherapy in combination with pembrolizumab (NAP) still have poor outcomes. Previously, we demonstrated that intratumoral HLA-DRA expression and interferon-alpha (IFNα) responses were associated with immune-inflamed phenotype and better outcomes in TNBC patients receiving chemotherapy. This study utilized the CosMx™ SMI to investigate in early-stage TNBC treated with NAP. Methods: Of 151 samples from TNBC patients treated with NAP at Mayo Clinic, 8 pre-treatment biopsy samples (5 pCR and 3 RCB II/III were analyzed using the CosMx™ SMI platform. Linear mixed models to assess differential expression (DE), adjusting for hierarchical data structures. DE analyses were expressed as log2-fold changes (logFC), with the Benjamini-Yekutieli method. GSEA and IPA for signaling pathway exploration. Results: 1.7 million cells were identified across 8 samples after stringent quality control. Immune cell profiling revealed higher B cells, plasma cells, plasmablasts, and T cells (CD4 and CD8) in responders, whereas fibroblasts and myeloid cells were enriched in non-responders. DE analysis showed significantly elevated expression of HLA-DRA (logFC 1.955, p&lt;0.001), other MHC class I and II components, and IFNα in responders. Tumor cells in responders exhibited the highest IFNα expression across cell types. GSEA and IPA analysis revealed enrichment in interferon signaling, antigen presentation, and the cGAS-STING pathway, which drives IFNα production. Spatial analysis categorized cells by their proximity to tumor cells: within 50 µm, 50-100 µm, and over 100 µm. T cells, particularly CD8 T cells, showed a distance-dependent distribution, with a higher abundance near tumor cells in responders. CD8 T cell activation scores declined with increasing distance from IFNα-positive tumor cells but remained consistently low near IFNα-negative tumor cells. IFNγ-positive CD8 T cells exhibited higher activation compared to IFNγ-negative cells, with activation levels influenced by proximity to tumor cells. Lastly, MHC expression in tumor cells was examined relative to CD8 T cell proximity. HLA-DRA and CIITA expression decreased as tumor cells were farther from CD8 T cells. Conclusions: This spatially resolved single-cell analysis highlights the pivotal role of tumor-immune interactions in response to pembrolizumab in TNBC. Our data suggest that tumor cells secrete IFNα through the activation of the cGAS-STING pathway, which activates T cells within close proximity, highlighting the potential role of cGAS-STING agonist as well as IFNα signaling and antigen presentation in augmenting TNBC responses to ICIs. Citation Format: Yi Liu, Saranya Chumsri, Yaohua Ma, Jodi M. Carter, Aziza Nassar, Edith Perez, Roberto A. Leon-Ferre, David Zahrieh, David W. Hillman, Judy C. Boughey, James Ingle, Krishna R. Kalari, Fergus J. Couch, Matthew P. Goetz, Keith L. Knutson, E. Aubrey Thompson. Spatially resolved single-cell analysis reveals cGAS-STING-mediated tumor-immune interactions via IFNα as determinants of pembrolizumab sensitivity in triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7130.

Background Neoadjuvant treatment has become standard for patients with high-risk operable stage III melanoma, but the optimal regimen is unknown. Targeted therapy approaches yield high pathological response rates, while immunotherapy regimens show favorable recurrence-free survival (RFS). NeoACTIVATE was designed to address whether a neoadjuvant combination of both targeted therapy and immunotherapy might leverage the benefits of each. Methods We tested neoadjuvant treatment with 12 weeks of vemurafenib, cobimetinib, and atezolizumab for patients with BRAF-mutated (BRAFm) melanoma (cohort A) and cobimetinib and atezolizumab for patients with BRAF-wild-type (BRAFwt) melanoma (cohort B), regimens which we have shown generate a substantial major pathological response. After therapeutic lymph node dissection, patients received 24 weeks of adjuvant atezolizumab. Here, we report survival outcomes and their association with biomarkers assayed among the gut microbiome and peripheral blood immune subsets. Results With 49 months median follow-up, the median RFS was not reached for cohort A and was 40.8 months for cohort B. At 24 months after operation, 2 of 14 cohort A patients and 4 of 13 cohort B patients had experienced distant relapse. Key findings from correlative analyses included diversity, taxonomic and functional metagenomic gut microbiome signals associated with distant metastasis-free survival at 2 years. Notably, we observed a strong correlation between low microbial arginine biosynthesis (required for T-cell activation and effector function) and early distant recurrence (p=0.0005), which correlated with taxonomic differential abundance findings. Peripheral blood immune monitoring revealed increased double-positive (CD4+CD8+) T cells in patients with early recurrence. Conclusions Neoadjuvant treatment with cobimetinib and atezolizumab±vemurafenib was associated with a low rate of distant metastasis in patients with high-risk stage III melanoma. Freedom from early distant metastasis was highly associated with taxonomic differences in gut microbiome structure and with functional pathway alterations known to modulate T cell immunity. Identification of predictive biomarkers will permit optimization of neoadjuvant therapy regimens for individual patients. Trial registration number NCT03554083.

Abstract The intracluster correlation coefficient (ICC) measures the correlation of observations within clusters and is a key parameter for power and sample size calculations for cluster randomized trials (CRTs). To facilitate the design of future CRTs within the National Cancer Institute Community Oncology Research Program (NCORP), all studies from the NCORP website were reviewed to identify completed CRTs. ICCs for primary and secondary outcomes (when available) were ascertained from these trials and summarized in this article as a resource for future trial development. Although ICCs are relatively small for many outcome cluster combinations, that is not always the case, so consideration should always be given to the specific outcome of interest, trial design, and type of cluster when estimating an ICC to facilitate trial development.

Abstract Cancer care delivery research trials conducted within the National Cancer Institute (NCI) Community Oncology Research Program (NCORP) routinely implement interventions at the practice or provider level, necessitating the use of cluster randomized controlled trials (cRCTs). The intervention delivery requires cluster-level randomization instead of participant-level, affecting sample size calculation and statistical analyses to incorporate correlation between participants within a practice. Practical challenges exist in the conduct of these cRCTs due to unique trial network infrastructures, including the possibility of unequal participant accrual totals and rates and staggered study initiation by clusters, potentially with differences between randomized arms. Execution of cRCT designs can be complex, ie, if some clusters do not accrue participants, unintended cluster-level crossover occurs, how best to identify appropriate cluster-level stratification, timing of randomization, and multilevel eligibility criteria considerations. This article shares lessons learned with potential mitigation strategies from 3 NCORP cRCTs.

Abstract Background: Previous studies demonstrated that obesity is associated with poor outcomes and significantly worse pathological complete response (pCR) in triple-negative breast cancer (TNBC) treated with conventional chemotherapy. Emerging studies described a phenomenon termed the obesity paradox, which referred to improved outcomes observed in obese patients treated with immune checkpoint inhibitors (ICIs). Our study aimed to determine distinct immune features in TNBC across body mass index (BMI). Methods: Characteristics and outcomes of TNBC patients treated with neoadjuvant pembrolizumab-based chemotherapy at Mayo Clinic were collected. Normal BMI was defined as 18-25 kg/m2, overweight 25-30, and obese BMI ≥ 30. NanoString CosMx, a spatial multi-omics single-cell imaging (SMI), was performed in 75 samples from the Mayo Clinic TNBC cohort (Leon-Ferre BCRT 2018). Differential expression as log 2-fold change (FC) was estimated from the linear mixed model with significance defined as two-sided p&lt; 0.05. Results: Between 2021-2023, there were 108 TNBC patients treated with neoadjuvant pembrolizumab. 25.9% were obese, 32.4% were overweight, and 41.7% had normal BMI. In contrast to previous studies with conventional chemotherapy, obese patients numerically had a higher pCR rate of 71.4% with pembrolizumab-based chemotherapy compared to 55.6% in normal and 62.9% in overweight patients. However, this difference did not reach statistical significance (obese vs. normal weight, OR 2.26, 95%CI 0.89-6.06, p 0.094). We further evaluated spatially-resolved immune features associated with obesity using CosMx SMI in 75 samples from the MC TNBC cohort. Obese patients had significantly higher intratumoral B cells (log2FC 1.88, p 0.017), stromal B cells (log2FC 2.79, p 0.001), stromal plasmablasts (log2FC 1.94, p 0.047), and stromal macrophages (log2FC 1.80, p 0.017) compared to patients with normal BMI. Obese patients also had significantly lower intratumoral myeloid dendritic cells (mDC) (log2FC -1.27, p 0.037). Similar trends were observed after standardizing cell counts per 100 tumor or stromal cells, including higher intratumoral B cells (log2FC 3.00, p 0.001), intratumoral plasmablasts (log2FC 2.00, p 0.006), intratumoral natural killer (NK) cells (log2FC 1.66, p 0.044), and stromal B cells (log2FC 1.50, p 0.008). Differential gene analyses for intratumoral B cells revealed that genes (CD74, HLA-C, HLA-DRB1, HLA-DRA, HLA-DRB) associated with the positive regulation of type 2 immune or chemokine response were upregulated. Conclusions: Using in-depth analysis with spatially defined context, our study showed that obese TNBC patients had significantly higher B cell infiltration, which is associated with improved outcomes with ICIs. Future research on how obesity alters the immune microenvironment is needed to identify potential pathways to improve outcomes with ICIs in TNBC. Citation Format: Songhan Pang, Yi Liu, Yaohua Ma, Zhuo Li, Roberto A. Leon-Ferre, David Zahrieh, David W. Hillman, Judy C. Boughey, James N. Ingle, Krishna R. Kalari, Fergus J. Couch, Matthew P. Goetz, Keith L. Knutson, Saranya Chumsri, E. Aubrey Thompson. Tumor-immune microenvironment associated with obesity in triple-negative breast cancer in the Mayo Clinic cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1162.

Background: Knowing the predictive factors of the variation in a center-level continuous outcome of interest is valuable in the design and analysis of parallel-arm cluster randomized trials. The symbolic two-step method for sample size planning that we present incorporates this knowledge while simultaneously accounting for patient-level characteristics. Our approach is illustrated through application to cluster randomized trials in cancer care delivery research. The required number of centers (clusters) depends on the between- and within-center variance; the within-center variance is a function of estimates obtained by regressing the log within-center variance on predictive factors. Obtaining accurate estimates of the components needed to characterize the within-center variation is challenging. Methods: Using our previously derived sample size formula, our objective in the current research is to directly account for the imprecision in these estimates, using a Bayesian approach, to safeguard against designing an underpowered study when using the symbolic two-step method. Using estimates of the required components, including the number of centers that contribute to those estimates, we make formal allowance for the imprecision in these estimates on which a sample size will be based. Results: The mean of the distribution for power is consistently smaller than the single point estimate that the sample size formula yields. The reduction in power is more pronounced in the presence of increased uncertainty about the estimates with the reduction becoming more attenuated with increased numbers of centers that contribute to the estimates. Conclusions: Accounting for imprecision in the estimates of the components required for sample size estimation using the symbolic two-step method in the design of a cluster randomized trial yields conservative estimates of power.