Loibl, Sibylle

Abstract Background: The PALLAS trial (ABCSG-42, AFT-05, BIG-14-03) investigates adjuvant palbociclib plus endocrine therapy (ET) versus ET alone in patients (pts) with HR+/HER2− early breast cancer. While palbociclib improves outcomes in metastatic settings, final analysis from PALLAS did not demonstrate benefit in survival outcomes from the addition of palbociclib to ET. A number of pts discontinued palbociclib before the planned 2 year duration though degree of palbociclib exposure was not associated with clinical outcomes. This analysis explores factors predictive of palbociclib early discontinuation and dose reductions, including baseline characteristics, toxicities, and patient-reported outcomes (PROs). Methods: Using the safety population of 5736 pts (2840 receiving palbociclib + ET), we assessed early palbociclib discontinuation within a competing-risks framework (competing events: progression, death). Cumulative incidence curves (Aalen-Johansen estimates) and cause-specific hazard models were used to explore associations with clinical and demographic factors (age, menopausal status, stage, race, endocrine therapy type), key toxicities (neutropenia, anemia, nausea), and baseline PROs (patient assessed quality of life [QoL], anxiety, fatigue, pain, frailty/ dependency, depression, and low income. financial difficulties). An automated model selection based on the Akaike information criterion (AIC) starting from the cause-specific hazard model incorporating all considered predictors including PROs. Results: Early discontinuation of palbociclib not due to progression or death occurred in 1171 pts (41.3%); an additional 343 pts (12.1%) stopped due to results of a futility analysis. In 108 (3.8%) and 2 (0.1%) pts treatment was discontinued due to progression or death. Median time to early discontinuation was 7.7 months in pts that discontinued treatment (median interquartile range 3.45-13.60). Very early discontinuation (≤3 months) occurred in 261 pts (9.2%). Dose reductions to 100mg and 75mg occurred in 1566 pts (55.2%) and 951 pts (33.6%) of 2840 pts, respectively. In univariable analyses, higher age, lower N-stage, and specific baseline PROs (baseline QoL, fatigue, anxiety, depression, frailty/ dependency and financial difficulties) were linked with increased risk of discontinuation. The best-fitting multivariable model identified age, nodal stage (N-stage), low quality of life (QoL), and low income as key predictors of early treatment discontinuation. Conclusions: In the PALLAS trial, our findings highlight the importance of integrating PROs into risk prediction of early treatment discontinuation. Additionally, when starting pts on oral targeted therapies in the adjuvant setting, symptom control, social work and financial counseling resources may support pts at higher risk of non-adherence. This is in line with findings from the ESMO Breast QoL analysis (Bjelic-Radisic et al.), which emphasized the added value of subjective patient-reported outcomes alongside objective clinical parameters in understanding treatment burden and adherence. Support: AFT, ABCSG, Pfizer, ECOG-ACRIN, NSABP Foundation, GBG, BIG; https://acknowledgments.alliancefound.org; ClinicalTrials.gov Identifier: NCT02513394. Citation Format: M. Vetter, A. Wiencierz, M. Gnant, D. Hlauschek, C. Kurzeder, C. Grasic Kuhar, N. Zdenkowski, E. Shinn, J. Suga, D. Egle, J. Meisel, S. Antolin-Novoa, E. Munzone, T. Haddad, S. Loibl, A. Holynskyj, C. Fesl, A. Dueck, A. DeMichele, E. Mayer, on behalf of the PALLAS groups and investigators (ABCSG, AFT, BIG,PReCOG, GBG, NSABP). Predictors of early discontinuation of adjuvant palbociclib in early HR+/ HER2- breast cancer: final analysis of the PALLAS trial integrating patient-reported outcomes [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-07-14.

Importance The Breast Cancer Index (BCI) previously identified premenopausal patients with tumors in which the ratio of expression of HOXB13 relative to IL17BR (hereafter, BCI [H/I]–low tumors) as likely to derive greatest benefit from ovarian function suppression (OFS)–containing adjuvant therapy in the Suppression of Ovarian Function Trial (SOFT) trial. Objectives To assess BCI as a predictive biomarker of benefit from exemestane plus OFS vs tamoxifen plus OFS and to validate BCI as a prognostic biomarker for premenopausal patients. Design, Setting, and Participants This prognostic study used a prospective-retrospective translational design within the Tamoxifen and Exemestane (TEXT) and SOFT trials (enrolled November 2003 to April 2011). Blinded BCI testing in all available tumor samples was completed in March 2024. Premenopausal women with hormone receptor–positive breast cancer randomized to tamoxifen plus OFS or exemestane plus OFS who had BCI assessed were included. Analysis occurred from March to August 2024. Exposure 5 years of adjuvant tamoxifen plus OFS or exemestane plus OFS. Main Outcomes and Measures The primary outcomes were breast cancer-free interval (BCFI) for predictive analyses and distant recurrence-free interval (DRFI) for prognostic analyses after a median follow-up of 13 years in the TEXT cohort. Secondary objectives examined the predictive performance of BCI (H/I) in the combined TEXT and SOFT cohort overall and in prespecified clinical subgroups. Results Of 1782 patients in the TEXT study, 1034 (58.0%) had BCI (H/I)–low tumors; 915 (51.3%) of patients had N0 disease and 1077 (60.4%) were younger than 45 years. Patients with BCI (H/I)–low tumors had a 6.6% absolute benefit in 12-year BCFI (HR, 0.61; 95% CI, 0.44-0.85) for exemestane plus OFS vs tamoxifen plus OFS, while those with BCI (H/I)–high tumors had a 6.3% absolute benefit (HR, 0.78; 95% CI, 0.57-1.07; P for interaction = .29). Results were consistent in the combined TEXT plus SOFT cohort (2896 patients) and adjusting for clinicopathological variables. Clinical subgroup analyses consistently showed benefit of exemestane plus OFS vs tamoxifen plus OFS for BCI (H/I)–low tumors, and more variable relative treatment effects among BCI (H/I)–high tumors, including by age. Post hoc exploratory time-varying estimates suggested the treatment × BCI associations may differ in years 0 to 5 vs greater than 5 years. BCI and BCI N+ as continuous indices were prognostic for distant recurrence in N0 (HR, 1.27; 95% CI, 1.11-1.44; P < .001) and N1 (HR, 1.58; 95% CI, 1.21-2.05; P < .001) cancers. The 12-year DRFI was 96.3%, 90.3%, and 84.9% for BCI low-, intermediate-, and high-risk N0 cancers, respectively. Conclusions and Relevance In this study of premenopausal women with hormone receptor–positive breast cancer, BCI (H/I) status did not clearly predict greater benefit of adjuvant exemestane plus OFS vs tamoxifen plus OFS for women with BCI (H/I)–low tumors than for those with BCI (H/I)–high tumors; BCI continuous indices were reconfirmed as prognostic for premenopausal women. These findings support prior results of SOFT, which compared tamoxifen-alone vs OFS with either exemestane or tamoxifen, indicating premenopausal patients with BCI (H/I)–low tumors may benefit from more intensive endocrine therapy.

Abstract Purpose :Tamoxifen undergoes bioactivation to its active metabolite (Z)-endoxifen, which blocks estrogen-dependent breast tumor growth at high potency. We tested the feasibility and safety of supplementing standard tamoxifen therapy with low-dose (Z)-endoxifen in patients with breast cancer with compromised tamoxifen bioactivation. Patients and Methods :We conducted a prospective, interventional, three group randomized trial including 235 patients with hormone receptor–positive breast cancer who received standard tamoxifen therapy (20 mg/day). Patients were stratified by CYP2D6 genotype (n = 78), defining poor, intermediate, and normal metabolizers, or by baseline (Z)-endoxifen plasma concentration (n = 78), defining ≤15, 15 to 25, and ≥25 nmol/L. Co-treatment with (Z)-endoxifen 3 and 1.5 mg/day or placebo was performed, respectively. A control group (n = 79) received placebo regardless of metabolizer phenotype. The primary endpoint was the number of patients with (Z)-endoxifen levels >32 nmol/L after 6 weeks of treatment. Adverse events were continuously monitored. Results: A higher proportion of patients in both intervention groups achieved target concentrations >32 nmol/L compared with control (P < 0.0001). At 3 mg (Z)-endoxifen supplementation, 92.3% of CYP2D6 poor metabolizer patients and all patients with baseline (Z)-endoxifen ≤15 nmol/L achieved the target concentration. At 1.5 mg (Z)-endoxifen supplementation, 88% of CYP2D6 intermediate metabolizer patients and 95% of patients with 15 to 25 nmol/L baseline (Z)-endoxifen levels achieved the target concentration. Similar proportions of patients receiving (Z)-endoxifen (6/80, 7.5%) or placebo (8/155, 5.2%) experienced grade 3 adverse events. Conclusions: Adding low-dose (Z)-endoxifen to standard tamoxifen is safe and provides a new approach to personalized antiestrogen treatment for patients with low endoxifen plasma levels.

Abstract Background: Low levels of HER2 expression (HER2-low) have recently emerged as a therapeutic target in patients (pts) with breast cancer (BC). The aim of this study was to evaluate clinical and demographic variables associated with HER2 expression, as well as the value of HER2-low as a prognostic and predictive biomarker for palbociclib benefit in pts enrolled in the PALLAS trial. Methods: The phase III PALLAS trial investigated the addition of palbociclib to adjuvant endocrine therapy (ET) in pts with stage II-III hormone receptor-positive BC. The aims of this analysis are (1) to assess the association between the presence of low levels of HER2 expression with demographic and clinicopathological parameters, (2) to test the prognostic value of HER2-low status on invasive disease-free survival (IDFS), distant relapse-free survival (DRFS), and overall survival (OS) and (3) to assess the value of HER2 expression as a predictive biomarker of response to palbociclib. HER2-low was defined as HER2 immunohistochemistry (IHC) 1+ or IHC 2+ with negative in situ hybridization; all pathologic evaluation was performed locally. Pts with HER2-0 and Her2-low BC were included in this analysis; those with HER2-positive BC or missing HER2 status were excluded. Association of HER2 with other baseline covariates were tested with Chi-squared tests. Prognostic and predictive power of HER2 were assessed with Cox Models. Multivariable models included age, T-stage, N-stage, grade and progesterone receptor (PR) expression. Hazard ratios (HR) and 95% Confidence intervals (CI) are reported. Results: From the original PALLAS intention-to-treat population (N = 5,753), 5304 pts (92.2%) were included in this analysis. Among these, 2,254 pts (42.5%) were classified as HER2 IHC 0 (HER2-0) and 3,050 (57.5%) as HER2-low (1,838 with IHC 1+ and 1,212 with IHC 2+). For this analysis, median follow-up was 59.8 months. Compared to HER2-0, pts with HER2-low tumors had statistically higher estrogen receptor expression levels (mean expression 89.2% vs 88.2%, p = 0.019), lower PR expression levels (65.9% vs 68.2%, p = 0.007). Importantly, HER2-low status varied significantly across 21 participating countries (range 16.7% to 75.6%; p< 0.001) and was more frequent in pts enrolled in North America (63.1%) than in Europe (53.4%) and other regions (53.4%) (p < 0.001). No differences in HER2 expression were observed according to anatomic stage, T-stage, N-stage, histological grade, age, menopausal status, primary surgery type, prior radiation, prior chemotherapy, or baseline performance status. There were no statistically significant differences in IDFS, DRFS or OS according to HER2 status in univariate or multivariable Cox models (prognostic value, HR provided in the Table). There was no significant interaction between the HER2 status and the benefit to palbociclib in IDFS, DRFS or OS (Table). Similar results were obtained when HER2-0 was compared to HER2 1+ and HER2 2+ separately. Conclusions: In this large, prospective and international cohort, no differences were observed in clinical parameters, prognosis, or differential benefit from palbociclib (predictive value) between HER2-0 and HER2-low tumors. Significant geographic variability was observed in the prevalence of HER2-low status, suggesting a high degree of variation in pathologic assessment of HER2 expression without impact on outcomes. Support: AFT, Abbvie Pfizer; Clinicaltrials.gov: NCT02513394 https://acknowledgments.alliancefound.org Citation Format: Guilherme Nader-Marta, Christian F. Singer, Dominik Hlauschek, Angela DeMichele, Paolo Tarantino, Georg Pfeiler, Miguel Martín, Justin Balko, Zbigniew Nowecki, Marija Balic, Adam Brufsky, Arlene Chan, Patrick G. Morris, Tufia Haddad, Sibylle Loibl, Yuan Liu, Lidija Sölkner, Christian Fesl, Erica Mayer, Michael Gnant. Clinical characterization, prognostic and predictive values of HER2-low in early breast cancer in the PALLAS trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-01-13.

Abstract Background. The phase 3 PALLAS trial (NCT02513394) compared two years of the CDK4/6 inhibitor palbociclib with endocrine therapy of provider choice, versus endocrine therapy alone, as adjuvant treatment for patients with Stage II-III hormone receptor-positive HER2-negative (HR+/HER2-) breast cancer. Genomic subtype (PAM50 intrinsic subtype) measured from whole-transcriptome RNA sequencing data was defined in the protocol of the PALLAS trial as the primary biomarker for analysis of prediction and prognosis. Clinical data have been previously presented (Gnant et al, JCO 2022), and the trial now has 5-year median follow-up. Methods. As part of trial eligibility, all participants in PALLAS provided a tumor tissue block prior to randomization (surgical if primary resection, core biopsy if neoadjuvant treatment) for translational analyses (TRANS-PALLAS). The biorepository and laboratory were blinded to identity and processed samples in random order, to minimize bias. Nucleic acids were extracted from samples with sufficient tumor tissue and cellularity (>25 mm2 with ≥20% cancer nuclei). The Genome Sequencing Center at Washington University St. Louis performed whole-transcriptome RNA sequencing. Libraries were prepared from 1 µg DNase-1 treated total RNA, if total RNA DV200 >28 (Agilent Bioanalyzer), using an unbiased library protocol of RNA HyperPrep kit with RiboErase (HMR) (Kapa Biosystems, Wilmington, MA). 100 bp paired-end sequencing was performed on NovaSeq 6000 using S4 Reagent Kit (Illumina, San Diego, CA), with 48 libraries pooled per lane. Intrinsic subtype was determined using Bioclassifier package (Research PAM50 script, Parker et al.) only for the analysis population of primary breast cancer samples that had not been exposed to prior neoadjuvant therapy. Invasive disease-free survival (IDFS) will be visualized using Kaplan-Meier plots, with log-rank test between groups. Cox models of proportional hazards will be developed to evaluate prognosis adjusted for known clinical covariates, or for predictive interactions. The pre-defined level of significance is a two-sided 0.05. Results. From the total study population of 5796 enrolled patients, 4655 tissue blocks had sufficient tumor content to process for RNA, with 3931 yielding sufficient RNA for sequencing, and 2669/4655 (57.3%) submitted tissue blocks had DV200 ≥28 and were successfully sequenced. Clinical unblinding revealed 2370 unique patients (1182 in the palbociclib treatment arm and 1188 in the control arm) with intrinsic subtype defined from their untreated primary tumor: 1555 (65.6%) luminal A, 287 (12.1%) luminal B, 167 (7.0%) HER2-enriched, 310 (13.1%) basal-like, 51 (2.2%) normal-like. We will report the results for association of molecular subtype, proliferation score, and Risk of Recurrence (ROR) scores with invasive disease-free survival (IDFS) by treatment arm at the meeting. Conclusions. The TRANS-PALLAS cohort represents one of the largest biorepositories of HR+/HER2- early breast cancer reflecting contemporary systemic management in the framework of a prospectively randomized global trial. Required tumor block submission in this phase 3 trial yielded data from unbiased whole-transcriptome RNA sequencing of the primary tumor prior to treatment from 41% of the PALLAS participants. The proportion of luminal A cancers was unexpectedly high (66%), indicating a lower-risk distribution of cancers in this population. The planned analyses of prediction and prognosis are ongoing and those results will be presented at the time of the meeting. Support: AFT, ABCSG, Pfizer, ECOG-ACRIN, NSABP Foundation, GBG, BIG; Clinicaltrials.gov Identifier: NCT02513394; https://acknowledgments.alliancefound.org Citation Format: Daniel Stover, Dominik Hlauschek, Erica Mayer, W. Fraser Symmans, Mark Watson, Iros Barozzi, Martin Filipits, Karla Ballman, Meritxell Bellet- Ezquerra, Justin Balko, Gabor Rubovszky, Nicholas Zdenkowski, Adam Brufsky, Guenther Steger, Claudine Isaacs, Sibylle Loibl, Fernando Henao, Meredith Regan, Yuan Liu, Christian Fesl, Patrick O'Brien, Angela DeMichele, Michael Gnant, Otto Metzger. Protocol-defined biomarker analysis in the PALLAS (AFT-05) adjuvant trial: Genomic subtype derived from RNA sequencing of HR+/HER2- early breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr GS03-07.

Abstract Recent advances in the field of immuno‐oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high‐throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi‐marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Abstract Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector‐based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well‐described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

AbstractThe clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

PURPOSE BMI affects breast cancer risk and prognosis. In contrast to cytotoxic chemotherapy, CDK4/6 inhibitors are given at a fixed dose, irrespective of BMI or weight. This preplanned analysis of the global randomized PALLAS trial investigates the impact of BMI on the side-effect profile, treatment adherence, and efficacy of palbociclib. METHODS Patients were categorized at baseline according to WHO BMI categories. Neutropenia rates were assessed with univariable and multivariable logistic regression. Time to early discontinuation of palbociclib was analyzed with Fine and Gray competing risk models. Unstratified Cox models were used to investigate the association between BMI category and time to invasive disease-free survival (iDFS). 95% CIs were derived. RESULTS Of 5,698 patients included in this analysis, 68 (1.2%) were underweight, 2,082 (36.5%) normal weight, 1,818 (31.9%) overweight, and 1,730 (30.4%) obese at baseline. In the palbociclib arm, higher BMI was associated with a significant decrease in neutropenia (unadjusted odds ratio for 1-unit change, 0.93; 95% CI, 0.91 to 0.94; adjusted for age, race ethnicity, region, chemotherapy use, and Eastern Cooperative Oncology Group at baseline, 0.93; 95% CI, 0.92 to 0.95). This translated into a significant decrease in treatment discontinuation rate with higher BMI (adjusted hazard ratio [HR] for 10-unit change, 0.75; 95% CI, 0.67 to 0.83). There was no significant improvement in iDFS with the addition of palbociclib to ET in any weight category (normal weight HR, 0.84; 95% CI, 0.63 to 1.12; overweight HR, 1.10; 95% CI, 0.82 to 1.49; and obese HR, 0.95; 95% CI, 0.69 to 1.30) in this analysis early in follow-up (31 months). CONCLUSION This preplanned analysis of the PALLAS trial demonstrates a significant impact of BMI on side effects, dose reductions, early treatment discontinuation, and relative dose intensity. Additional long-term follow-up will further evaluate whether BMI ultimately affects outcome.