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Partridge, Ann H.

Mayo Clinic

Dana-Farber Cancer Institute

Citations 4

Long-term safety outcomes of pregnancy among young breast cancer survivors: Results from a prospective, multicenter cohort study.
Zheng, Yue, Niman, Samuel M. , Dibble, Kate, Rosenberg, Shoshana M., Ruddy, Kathryn Jean, Gelber, Shari , Tamimi, Rulla, Peppercorn, Jeffrey , Schapira, Lidia, Come, Steven E. , Warner, Ellen, Lambertini, Matteo, Ginsburg, E, Partridge, Ann H., Sorouri, Kimia , Dibble, Kate E. , Rosenberg, Shoshana M. , Kirkner, Gregory J. , Ruddy, Kathryn J. , Tamimi, Rulla, Schapira, Lidia , Borges, Virginia F. , Warner, Ellen , Lambertini, Matteo , Ginsburg, Elizabeth S. , Partridge, Ann H.

Journal of Clinical Oncology | May 27, 2026 | Volume: 44 | Issue: 16_suppl | Pages: 632-632

10.1200/jco.2026.44.16_suppl.632 Get It

632 Background: Prospective data on the risk of breast cancer (BC) recurrence among young BC survivors who have a subsequent pregnancy are limited. We sought to evaluate the long-term impact of pregnancy and live birth on BC outcomes in the Young Women’s Breast Cancer Study (NCT01468246), a prospective multicenter study of women aged ≤40 years at BC diagnosis. Methods: Women with stage 0-III BC without prior hysterectomy were included. The primary endpoint was breast cancer-free interval (BCFI) between patients with and without a (a) pregnancy and (b) live birth after BC. Secondary endpoints were distant recurrence-free interval (DRFI) and overall survival (OS). A time-varying Cox proportional hazards model was performed by estrogen receptor (ER) status, controlling for age at diagnosis, tumor stage, HER2 status, tumor grade, parity at diagnosis, and germline pathogenic variant status. Results: Among 1,016 BC survivors at a median follow-up of 12 (range, 0.5-18.5) years, 198 reported ≥1 pregnancy and 165 reported ≥1 live birth post-diagnosis. Among survivors who reported a post-diagnosis pregnancy, median age at diagnosis was 32 (range, 17-40) years; most had stage I (35%) or II (40%) BC, with 72% hormone receptor (HR)-positive and 25% HER2+; 42% were nulligravid and 60% were nulliparous at diagnosis. Among BC survivors who did not become pregnant post-diagnosis, median age at diagnosis was 37 (range, 21-40) years; most had stage I (35%) or II (43%) BC, with 75% HR-positive and 28% HER2+; 25% were nulligravid and 29% were nulliparous at diagnosis. Among BC survivors with ER-positive tumors (n = 737), pregnancy after BC was not associated with a difference in BCFI (adjusted hazard ratio [HR] 0.60, 95% CI 0.31-1.16, P = 0.130), DRFI (HR 0.73, 95% CI 0.35-1.55, P = 0.416), or OS (HR 0.58, 95% CI 0.24-1.40, P = 0.227). Similarly, live birth after BC did not impact BCFI (HR 0.83, 95% CI 0.45-1.55, P = 0.560), DRFI (HR 1.04, 95% CI 0.52-2.06, P = 0.923), or OS (HR 0.77, 95% CI 0.34-1.76, P = 0.541). Outcomes among BC survivors with ER-negative tumors (n = 278) were also not affected by post-diagnosis pregnancy (BCFI [HR 1.48, 95% CI 0.70-3.14, P = 0.304], DRFI [HR 1.59, 95% CI 0.68-3.75, P = 0.287], OS [HR 0.99, 95% CI 0.39-2.49, P = 0.975]) or live birth (BCFI [HR 1.02, 95% CI 0.41-2.53, P = 0.974], DRFI [HR 0.80, 95% CI 0.24-2.69, P = 0.722], OS [HR 0.39, 95% CI 0.09-1.69, P = 0.208]). Conclusions: In this multicenter, prospective study with 12 years of median follow-up, pregnancy and live birth after BC did not impact BC events or overall survival, irrespective of ER status. These long-term data from a modern cohort provide reassurance for young BC patients interested in future fertility. Clinical trial information: NCT01468246 .
Shared and distinct molecular signatures of resistance to different endocrine therapies (Alliance A011106).
Holloway, Kimberly, Williams, Laterrica, Kim, Beom Jun, Sanati, Souzan , Fernandez-Martinez, Aranzazu, Fan, C C, Korchina, Viktoriya , Gibbs, Richard, Watson, Mark A., Partridge, Ann H., Zhang, B, Ellis, Matthew James, Carey, L, Perou, Charles, Ma, C X, Anurag, Meenakshi , Dou, Yongchao , Hoog, Jeremy , Holloway, Kimberly R. , Williams, Laterrica C. , Vij, Kiran R , Fernández-Martínez, Aranzazu , Suman, Vera J. , Partridge, Ann H. , Ellis, Matthew J. , Carey, Lisa A.

Journal of Clinical Oncology | May 27, 2026 | Volume: 44 | Issue: 16_suppl | Pages: 566-566

10.1200/jco.2026.44.16_suppl.566 Get It

566 Background: Endocrine therapy (ET) resistance (ETR) remains a primary challenge in ER+ breast cancer. Analyzing pretreatment tumor transcriptomes across trials with early response endpoints can reveal shared and specific ETR signatures. This study utilizes baseline RNA data from the Phase III ALTERNATE trial (Alliance A011106, NCT01953588; Anastrozole [A], Fulvestrant [F], or AF) and the ACOSOG Z1031B trial (NCT00824941) to identify predictors of early Ki67 response in postmenopausal ER+/HER2– patients. Methods: ETR was defined as week-4 on-treatment Ki67 >10%. Baseline gene expression from ALTERNATE was analyzed to identify differentially expressed (DE) genes (Wilcoxon test, P<0.05) and Hallmark pathways associated with ETR, both across and within individual treatment arms. Feature selection was performed using mixOmics. A Pan-Endocrine Therapy Signature (PETS) was developed by uniting DE genes identified across all three ALTERNATE arms and Z1031B. All statistical analyses were conducted in R (P<0.05). Results: Overall ETR rate in the ALTERNATE RNA-seq cohort (n=733) was 26%. ETR was associated with high Risk of Recurrence (ROR), Oncotype RS, and Mammaprint scores (calculated from RNA-seq data in research setting). In luminal tumors (n=649), ETR was linked to chr 3q13.33, 8q24.13, and 20q13.12 cytoband upregulation and 17q21, 18q23, 3p21.1, and 10q24.32 cytoband downregulation. ETR tumors showed T-cell, E2F target, and interferon-γ enrichment; sensitive tumors favored early estrogen response and muscle differentiation. At individual gene level, high MYBL2 , PIF1 , TROAP and with low HJURP predicted ETR across all samples (AUC>0.70). A deep learning model using all protein-coding genes achieved AUC 0.82 (training) and 0.79 (test) in predicting ETR. Cross-trial integration identified ETR-associated PETS, enriched for genomic instability. PETS performed comparably to established signatures and strongly correlated with MYBL2 signature (r=0.93). Top ETR predictors were MYBL2 , AURKB , and EME1 for Arm A and IL4I1 , TNFAIP6 , and ANLN for Arm AF. AF-resistant tumors were enriched for systemic lupus and RIG-I–like receptor signaling; sensitive tumors favored PI3K–AKT, EGFR TKI resistance, AMPK, and insulin signaling. Conclusions: Baseline transcriptomics identify shared and therapy-specific ETR markers. The 15-gene PETS defines a convergent resistance signature, performing similar to established signatures in predicting ETR and correlating with MYBL2. Enrichment of cell-cycle and immune pathways in resistant tumors may suggest patient stratification approach for alternative or combinatorial strategies to overcome early ETR in ER+ breast cancer. Acknowledgement: https://acknowledgments.alliancefound.org. Support: U10CA180821, U10CA180882, U24CA1. Clinical trial information: NCT01953588 .
EA1181: Accuracy of pre-surgery MRI to predict pathologic complete response after taxane, trastuzumab, and pertuzumab (THP) in HER2-positive breast cancer.
Tung, NM, Zhao, Fengmin, Partridge, Savannah C., Wright, Jean, Recht, Abram, Weiss, Anna, Tjoe, Judy A., Feldman, Sheldon M. , Smith, Mary Lou , O'Sullivan, Ciara Catherine, Sardesai, Sagar D., Winer, Eric P., Partridge, Ann H., Carey, L, DeMichele, Angela, Tung, Nadine , Zhao, Fengmin , Partridge, Savannah C , Recht, Abram , Weiss, Anna, Tjoe, Judy A., Rocque, Gabrielle B. , O’Sullivan, Ciara C. , Sardesai, Sagar , Badve, Sunil , Winer, Eric P. , Miller, Kathy D. , Partridge, Ann H. , Carey, Lisa A. , Rahbar, Habib , DeMichele, Angela , Wolff, Antonio C.

Journal of Clinical Oncology | May 27, 2026 | Volume: 44 | Issue: 16_suppl | Pages: 603-603

10.1200/jco.2026.44.16_suppl.603 Get It

603 Background: Accurate prediction of pathologic complete response (pCR) after preoperative therapy for HER2-positive (HER2+) breast cancer can help triage patients to immediate surgery vs additional preoperative therapy. Pre-surgery (i.e., after neoadjuvant therapy) imaging studies may help estimate the likelihood of pCR. In EA1181, patients (pts) with stage II-IIIA HER2+ breast cancer received four cycles of preoperative taxane, trastuzumab, and pertuzumab (THP×4). Pre-surgery imaging was required, though the specific imaging modality was not mandated. Here, we report the accuracy of pre-surgery breast MRI to predict pCR (ypT0/Tis, ypN0). Methods: Among 2,141 pts treated with THPx4, 1,378 had pre-surgery breast MRI and were representative of the overall cohort, although T3 tumors were more common (16% vs 9%). MRI reports were available for 1,351 pts; all reports were centrally reviewed and classified as radiologic complete response (rCR; no residual tumor enhancement and normalization of lymph nodes, if applicable) or radiologic residual disease (rRD). Reports with indeterminate radiologic response were independently reviewed by two study radiologists blinded to pathology outcomes. Among pts with rCR who had pathologic residual disease (pRD), we also assessed the extent of residual disease by residual cancer burden (RCB) score. Among pts with rRD who had a pCR, we determined the proportion who only had residual ductal carcinoma in situ (DCIS). Results: See Table. Conclusions: After neoadjuvant therapy, preoperative MRI accurately predicted pCR in 86% of patients with HER2+/ER− disease and may help identify patients who can proceed directly to surgery. MRI is insufficient to predict pCR for pts with HER2+/ER+ disease, as only 55% with complete response on MRI had a pCR at surgery. A pre-surgery MRI that indicated residual disease was accurate in 80% of pts with HER2+/ER+ disease, but in only 45% of pts with HER2+/ER- cancer. Accurately predicting residual disease after THPx4 allows for consideration of additional therapy that may increase the chance of pCR. Combining imaging like MRI with other biomarkers, such as tissue-based markers or circulating tumor DNA, may improve prediction of pCR and facilitate personalization of treatment decisions in HER2+ breast cancer. All pts with pre-surgery MRI (n=1351)pCR rate overall in this cohort = 47% MRI result Pathology pCR pRD rCR 70.6% (341/483) 29.4%(142/483) 78% had RCB1 rRD 34%(295/868) 21% of 295 had DCIS only 66.01% (573/868) ER- (n=589)*Overall pCR rate in ER- subset = 68% MRI result Pathology pCR pRD rCR 86.1% (205/238) 13.9% (33/238) 85% had RCB1 rRD 55.3% (194/351) 19% of 194 had only DCIS 44.7% (157/351) ER+ (n= 762)*Overall pCR rate in ER+ subset = 31% MRI result Pathology pCR pRD rCR 55.5% (136/245) 44.5% (109/245) 76% had RCB1 rRD 19.5% (101/517) 26% of 101 had only DCIS 80.5% (416/517)
Effect of a weight loss intervention (WLI) on quality of life (QOL) and symptoms in women with breast cancer: Results from the Breast Cancer Weight Loss (BWEL) trial.
Ligibel, Jennifer A. , Hershman, Dawn L., Dueck, A. C. , McCall, Linda, Ginos, Brenda, Weiss, Anna, Hahn, Olwen, Spears, Patricia, Paskett, Electra D., Hopkins, Judith O. , Frank, Elizabeth S., Bernstein, Vanessa , Stearns, Vered, White, Julia R., Wadden, Thomas, Winer, Eric P., Carey, L, Partridge, Ann H., Hershman, Dawn L. , Goodwin, Pamela J. , Paskett, Electra D. , Mayer, Erica L. , Stearns, Vered , White, Julia , Wadden, Thomas A., Winer, Eric P. , Carey, Lisa A. , Partridge, Ann H.

Journal of Clinical Oncology | May 27, 2026 | Volume: 44 | Issue: 16_suppl | Pages: 12010-12010

10.1200/jco.2026.44.16_suppl.12010 Get It

12010 Background: BWEL (Alliance A011401; NCT02750826) is a Phase III trial that randomizes patients (pts) with stage II-III breast cancer and body mass index (BMI) ≥27 kg/m 2 1:1 to a 24-month (mo) lifestyle-based WLI + health education (HE) or HE alone. Here we report prespecified secondary outcomes of the impact of the WLI on patient-reported QOL and symptoms. Methods: The first 540 BWEL pts (randomized between 9/2016 and 7/2017) were included in this substudy that collected PROMIS 29 Profile 2.0 and Global Health scores at enrollment, 6 and 24 mos. Adjusting for baseline scores, mean physical function (predefined substudy primary outcome), global physical and mental health, fatigue and other scores were compared at 6 and 24 mos using analysis of covariance (ANCOVA). P-values <0.05 were considered significant. Positive differences in positive attributes (e.g., physical function) and negative differences in negative attributes (e.g., anxiety) represented better outcomes in the WLI arm. Results: At baseline, median BMI was 32.9 kg/m 2 (26.5 – 69.1), median age was 53 (25 - 78) years; 83.9% of pts were non-Hispanic White, 10.7% were Black and 5.9% were Hispanic. At 6 mos, the WLI (vs HE) arm had significantly better physical function (ANCOVA-based mean difference between arms 1.9 [95% CI 0.8, 3.0]; p<0.001), global physical health (2.0 [95% CI 0.9, 3.0]; p<0.001), global mental health (1.30 [95% CI 0.2, 2.4], p=0.03), social roles and activities (2.3 [95% CI 1.1, 3.6]; p<0.001), and fatigue (-1.7 [95% CI -3.1, -0.4], p=0.01) (Table). Improvements were generally maintained at 24 mos. Similar findings were seen in analyses using longitudinal mixed modeling. Conclusions: The BWEL WLI demonstrated QOL benefits for patients with breast cancer, resulting in significantly better physical function, global physical and mental health, and symptoms. Future analyses will evaluate which populations experienced the most benefit, as well as the relationships among QOL, symptoms, and weight loss. Support: U10CA180821, U10CA180882, UG1CA189823; U10CA180820; U10CA180868; U10CA180863, CCS 707213; U10CA180888; UG1CA189858; https://acknowledgments.alliancefound.org. Clinical trial information: NCT02750826 . Analysis of covariance-adjusted least squares means values at 6-mos adjusted for baseline scores. QOL/Symptom Attributes HE WLI Between arm difference (95% CI)* P value Physical Function 47.1 49.0 1.9 (0.8, 3.0) <0.001 Global Physical Health 46.2 48.1 2.0 (0.9, 3.0) <0.001 Global Mental Health 48.6 49.9 1.3 (0.2, 2.4) 0.03 Social Roles and Activities 52.7 55.0 2.3 (1.1, 3.6) <0.001 Anxiety 50.2 50.0 -0.2 (-1.6, 1.2) 0.77 Depression 47.5 47.5 -0.0 (11.2, 1.2) 0.96 Fatigue 50.6 48.9 -1.7 (-3.1, -0.4) 0.01 Sleep Disturbance 51.0 51.1 0.1 (-0.6, 0.8) 0.80 Pain Interference 51.3 50.3 -1.0 (-2.4, 0.4) 0.15 *Positive differences in positive attributes and negative differences in negative attributes favor WLI arm.