Association of clinicopathological and treatment variables with DFS and DRFS in ER+/HER2- ILC patients with cH/gL risk.

Transcriptomic differences between non-classic and classic ER+/HER2- ILC.

Liver metastases are frequent and challenging to treat owing to the liver's metabolically active and immune-tolerant environment. However, how cancer cells exploit nutrient availability in the liver to evade immune surveillance remains unknown. Here we show that cancer cells use the palmitate availability in the liver to impair the neutrophil antitumour function. Mechanistically, we find that breast and colorectal cancer cells metastasizing to the liver, but not the lung, require the palmitoyltransferase 17 (DHHC17, gene name ZDHHC17) to stabilize laminin-511 enabling its secretion. In turn, neutrophils in the liver metastasis environment respond to laminin-511 by decreasing their cancer cell-killing capacity. Consistently, silencing ZDHHC17 in cancer cells decreases liver metastases only in the presence of neutrophils, while metastasis growth is restored in ZDHHC17-silenced metastases upon injection of laminin-511 or inhibition of neutrophil degranulation. Taken together, we find that liver palmitate not only supports tumour intrinsic processes but also enables immune evasion.

Acetylation is frequently dysregulated in cancer, and both acetyltransferase and deacetylase inhibitors are being evaluated at various stages of preclinical and clinical development. However, how the expression of acetyltransferases and deacetylases is regulated remains often elusive. We focused on the lysine acetyltransferase 2A (KAT2A) as it is important in multiple cancer indications with a clinical inhibitor in development. We discovered that KAT2A expression is regulated by palmitoylation in breast cancer-derived metastases. Specifically, we find that the palmitoyltransferase DHHC20 (gene name ZDHHC20) palmitoylates transmembrane 4L six family member 1 (TM4SF1) promoting its plasma membrane localization. This in turn fosters phosphorylation of the signal transducer and activator of transcription 3 (STAT3), which we identify as a transcriptional regulator of KAT2A. Accordingly, Zdhhc20 and Tm4sf1 silencing as well as expression of a Tm4sf1 double palmitoylation mutant decreases lung metastasis growth, which is rescued by Kat2a expression. We detect evidence of this palmitoylation-induced regulation of KAT2A in lung metastasis samples from patients with breast cancer. Thus, we show that palmitoylation can orchestrate the expression of a global acetylation regulator in lung metastases.

PURPOSE:The risk for estrogen receptor positive/HER2-negative (ER+/HER2-) breast cancer (BC) is transiently augmented in the first years after giving birth especially if the first birth is occurring at a later age. Later in life, high parity and early first full-term pregnancy (1st FTP) appear to be protective for ER+/HER2- BC. The impact of reproductive factors on invasive lobular carcinoma (ILC) is poorly studied. We aimed at retrospectively investigating the association between reproductive factors (parity and age at 1st FTP) and the prevalence and clinicopathological features of ER+/HER2- ILC. METHODS:We considered patients primarily diagnosed with non-metastatic ER+/HER2- BC at University Hospitals Leuven, Belgium, between January 2000 and November 2020. Pure ILC cases were compared in a case-only design to a reference group including all other histological subtypes per parity and age at 1st FTP using linear regression models. RESULTS:7360 patients were included, of which 1121 (15.2%) were diagnosed with pure ER+/HER2- ILC. A parity greater than two children was associated with a higher prevalence of pure ILC compared to uniparous patients (OR 1.28, 95%CI 1.06-1.55, p-value 0.011). No significant association was seen for parity equal to two compared to one or for age at 1st FTP <21 vs. 21-25, 26-30 and ≥30. In patients with pure ER+/HER2- ILC, no significant associations were seen between parity and the clinicopathological features. CONCLUSIONS:Within an ER+/HER2- BC cohort, higher parity seems to be associated with a higher prevalence of pure ILC. No association was found between parity and clinicopathological features of ER+/HER2- pure ILC.

Importance:Molecular analyses of biospecimens collected from study participants are essential for identifying biomarkers that can tailor treatments to specific subsets of patients who are most likely to benefit. Sharing of data and biospecimens from clinical trials enables personalized, patient-centric use of cancer therapies and accelerates the development of new treatments. Objective:To describe obstacles to sharing data and biospecimens and to propose strategies to enhance access and collaboration. Evidence Review:This is a Special Communication authored by 53 academic investigators and patient representatives from the breast cancer community with extensive experience in conducting clinical and translational research. The article also evaluates the impact of biomarker research on specifying responsive subpopulations in the 29 registrational clinical trials that have led to approval of a new drug for treatment of breast cancer between 2017 and 2024. Findings:Clinical trial participants are increasingly asked to provide tissue and/or body fluid biospecimens for biomarker research that is typically controlled by the sponsoring pharmaceutical company, but published biomarker studies are rare. Among 29 breast cancer registrational studies reported in the past 8 years, none resulted in biomarker research that restricted a drug's approved indication. Herein, strategies to maximize the value of clinical data and biospecimens contributed by participants are proposed, thereby supporting the shared goals of the pharmaceutical industry and academia to improve patient care. These strategies include (1) establishing coleadership structures involving academia and patients in clinical trial design and conduct, (2) ensuring that informed consent forms state that data and biospecimens will be shared with academia for future research, (3) requiring the sharing of clinical data as a condition for regulatory approval, and (4) enabling access to biospecimens and translational research data for independent studies on biomarkers that may indicate drug efficacy and toxicity. Conclusions and Relevance:Data and biospecimen sharing from registrational trials has been suboptimal. Improving clinical data, biospecimens, and biospecimens' related data sharing requires concrete actions and a multidimensional stakeholder approach to accelerate the impact of clinical cancer research on the quality of patient care.

Background:Invasive lobular breast cancer (ILC) is the most commonly diagnosed special histological subtype of breast cancer (BC). Metastatic ILC (mILC) is less sensitive to FDG-PET imaging and often metastasizes to unusual sites -peritoneum, gastrointestinal ( GI) tract, ovaries, urinary tract, and orbit-which may go unrecognized after a long disease-free interval. Some metastatic sites cause nonspecific symptoms, like abdominal/epigastric pain, with numerous published case reports of mILC misdiagnosed as gastric cancer. These atypical BC metastatic sites may lead to late and/or misdiagnosis, thereby delaying effective treatments. Objective:We developed a patient survey to investigate the patient-reported prevalence of delayed diagnosis or misdiagnosis of mILC and their potential impact upon treatment outcomes. Methods:A 45-question survey was developed and piloted with breast cancer researchers, clinical oncologists, and patient advocates. This IRB-approved survey was then distributed to patients with ILC. Analyses including data QC and visualization were conducted in R using descriptive statistics. Incomplete or inconsistent responses were excluded, and summary statistics were stratified by four common mILC sites to highlight subgroup differences. Results:525 patient surveys were completed, with 450 patients diagnosed with ILC, and of those 321 diagnosed with mILC. For those with mILC, 33.3% (n=107) were diagnosed with de novo mILC at initial presentation. Of the patients diagnosed with mILC, 32.1% (n=103) presented with other medical conditions at diagnosis. Misdiagnosis was reported by 26.2% (n=84) of patients with mILC, and of these cases, 31% (n=26) had ≥2 misdiagnoses. The top 5 misdiagnoses were bone-related condition (24.7%), benign breast condition (23.4%), another type of BC (7.8%), diagnostic delay (7.8%), and menopause related (5.2%). 44.5% of patients waited ≥1 year for an accurate diagnosis. 49 patients were treated for their misdiagnosis, and 6 received incorrect cancer treatments. The most frequently reported contributors to delayed or misdiagnosis were inconclusive imaging, providers' lack of ILC knowledge, and initial misdiagnosis. Of the 321 patients with mILC, 138 (42.9%) reported symptoms before diagnosis; the most common were back pain (16.5%), fatigue/malaise (14.9%), GI symptoms (11.8%), bloating (8.4%), and weight loss (8.1%). Although 40% of patients reported having a mammogram at the time of their initial misdiagnosis, ILC was detected in only 20.5% (24/116) of these cases, and mammography detected only 5 (25%) of the 20 de novo mILC cases. Patients reported additional diagnostic testing within 1-3 months of their initial mammogram, includingbiopsy, ultrasound (US), and MRI. 47.9% of patients were in active BC surveillance after curative intent therapy at the time of their mILC diagnosis; however, no statistical difference was seen in time to diagnosis versus those patients not under surveillance. Conclusion:Our survey results underscore the urgent need to improve diagnostic strategies for mILC. Addressing delays and diagnostic errors in mILC is critical to optimizing treatment strategies and improving patient outcomes.

Supplementary Figure 1 Surfactant lipids are enriched in the vicinity of lung metastases from patients with breast cancer; Supplementary Figure 2 AT2 cells and surfactant lipids co-localize in the vicinity of metastases from mice; Supplementary Figure 3 Metastases progression increases the enrichment of AT2 cells; Supplementary Figure 4 The metastasis secretome reprograms AT2 cell lipid metabolism by activating SREBP-1; Supplementary Figure 5 Gpam knockdown in cancer cells does not affect 3D spheroid growth in vitro; Supplementary Figure 6 GPAM and FASN inhibition in cancer cells does not affect metastasis formation in vitro and in vivo

While primary invasive lobular carcinoma (ILC) is well characterized, metastatic ILC remains understudied. Within the post-mortem tissue donation programs, UPTIDER (Belgium) and Hope for Others (USA), we first aimed to explore intra-patient heterogeneity of key prognostic and predictive markers (stromal tumor-infiltrating lymphocytes (sTIL), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and KI67). Secondly, we compared detection of the metastases by pathology on autopsy samples versus pre-mortem imaging. In total, 306 metastases from 12 patients were collected at autopsy (median: 27 per patient). Both primary tumors (n = 15) and metastases (n = 232) had low sTIL levels, with a median of 2% (range: 0.67–6.67%) and 0.67% (range: 0–13.33%), respectively. Regression models showed lower ER- and PR-expression in metastases (respectively, n = 265 and n = 64) compared to primary tumors (both p < 0.01). KI67 was significantly higher in metastases (n = 262, p = 0.02). HER2-low metastases were found in all but one patient although in varying proportion of metastases (range: 7.5–100%). Central radiology and pathology review had a median concordance of 78% at organ level (range: 33.33–100%) and 71% at patient level (range: 55.88-85.29%). Our findings suggest that a single metastatic biopsy has great limitations to guide treatment and that more adequate methods are needed to detect and monitor ILC metastases.

PURPOSE:Invasive lobular carcinoma (ILC) is the second most common subtype of breast cancer after invasive breast cancer of no special type (IBC-NST). This retrospective analysis of the MINDACT trial investigated transcriptomic differences between estrogen receptor (ER)-positive/HER2-negative ILC and ER+/HER2- IBC-NST; classic and nonclassic ER+/HER2- ILC; and recurring and nonrecurring ER+/HER2- ILC in patients with a low genomic risk and either a low clinical/low genomic (cL/gL) or high clinical/low genomic (cH/gL) risk. EXPERIMENTAL DESIGN:We analyzed 4,262 ER+/HER2- tumors (63.7%; 464 ILC and 3,798 IBC-NST) with central pathology review. Differential gene expression analysis was adjusted for age and grade, followed by gene set enrichment analysis. Adjusted regression models evaluated associations of transcriptomic profiles with disease-free survival and distant recurrence-free survival. RESULTS:An increased expression of CDH1 (E-cadherin) in IBC-NST compared with ILC was observed. ILC showed more uptake of extracellular lipid sources (LPL, CD36, LEP, and LEPR), whereas IBC-NST favored lipid synthesis (FASN). Decreased ER signaling, increased PI3K/Akt signaling, and differences related to the extracellular matrix were also observed in ILC. Classic and nonclassic ILC differed subtly, notably in cell-cycle regulation. In patients with ER+/HER2- ILC with a cL/gL risk, enrichment of apoptosis, inflammatory response, hypoxia, and oncogenic signaling (PI3K/Akt, Ras, and c-Myc) were associated with worse survival. In contrast, in the cH/gL group, associations between ILC transcriptomic features and survival were more subtle. CONCLUSIONS:This represents the largest transcriptomic dataset for ILC from a clinical trial with central histology review. These findings may provide insights to refine treatment strategies and relapse risk assessment for patients with ILC.

Association of enrichment of molecular hallmarks with DRFS in ER+/HER2- ILC and IBC-NST patients with cH/gL risk.

1079 Background: INAVO (a highly potent and selective PI3Kα inhibitor that also promotes mut p110α degradation) + PALBO + FULV is approved for PIK3CA mut, HR+, HER2–, endocrine-resistant aBC based on statistically significant and clinically meaningful investigator-assessed progression-free survival (PFS) benefit over PBO + PALBO + FULV in INAVO120 (NCT04191499). We report exploratory analyses of treatment (tx) outcomes by lob histology status documented at initial diagnosis. Methods: Baseline characteristics, PFS, overall survival (OS), objective response rate (ORR), and duration of response (DoR) were evaluated for 53 pts with reported lob only and 64 with reported lob only or mixed lob (lob + ≥1 other selected subtype) histology at initial diagnosis. PIK3CA mut distribution, and association of histology and PFS with CDH1 alteration (alt) status, were also assessed. Results: At the clinical data cut-off for the updated PFS and final OS analyses (Nov 15, 2024), 24 and 29 pts with lob only histology, and 29 and 35 pts with mixed lob histology, were randomized to the INAVO and PBO arms, respectively. Baseline characteristics were balanced across tx arms. Median follow-up was 34.2 and 32.3 months (m) in the INAVO and PBO arms, respectively. Pathogenic CDH1 alts were more frequent in the lob only (65.2%) and mixed lob (58.9%) subgroups compared with no lob histology (6.3%). Efficacy by lob status is shown in the Table. PIK3CA mut distribution was similar across histologies. PFS benefit of INAVO over PBO was observed regardless of baseline CDH1 alt status (hazard ratio 0.3 for CDH1 alt and 0.5 for no alt detected). Conclusions: In this INAVO120 exploratory analysis, efficacy was improved with INAVO vs PBO, regardless of lob histology status at initial diagnosis and CDH1 alt status. This further supports the benefit of INAVO + PALBO + FULV in PIK3CA mut, HR+, HER2–, endocrine-resistant aBC. Clinical trial information: NCT04191499 . Lob only: INAVO n = 24 Non-lob: INAVO n = 137 Lob only: PBO n = 29 Non-lob: PBO n = 135 Mixed lob: INAVO n = 29 Non-mixed lob: INAVO n = 132 Mixed lob: PBO n = 35 Non-mixed lob: PBO n = 129 PFS, m (95% CI) 21.7 (9.3–25.8) 17.2 (11.6–24.3) 7.2 (3.7–9.4) 7.4 (5.8–9.7) 21.7 (11.3–27.9) 16.6 (11.2–24.2) 7.2 (3.8–9.4) 7.4 (5.8–9.7) OS, m (95% CI) NR (18.1–NR) 33.0 (27.1–44.8) 24.1 (11.1–NR) 27.0 (22.8–40.7) NR (28.4–NR) 33.0 (27.0–38.0) 24.1 (11.1–NR) 28.0 (22.8–40.7) ORR, n (%; 95% CI) 15 (62.5; 40.6–81.2) 86 (62.8; 54.1–70.9) 6 (20.7; 8.0–39.7) 40 (29.6; 22.1–38.1) 19 (65.5; 45.7–82.1) 82 (62.1; 53.3–70.4) 7 (20.0; 8.4–36.9) 39 (30.2; 22.5–38.9) DoR, m (95% CI) 21.2 (9.3–NR) 18.7 (12.2–28.3) 11.1 (8.5–NR) 10.7 (7.5–20.2) 20.3 (9.6–NR) 18.8 (11.1–28.7) 11.1 (3.1–NR) 11.1 (7.5–20.2) CI, confidence interval; NR, not reached.

BACKGROUND:Higher body mass index (BMI) is a risk factor for breast cancer (BC) development, but the relationship with BC subtypes in pre- and post-menopausal women remains unclear. METHODS:We performed a systematic search from PubMed, Embase and Cochrane databases until 09/24 (CRD42020206108) for cohort and case-control studies assessing the association between BMI and BC subtypes and/or menopausal status. BC risk in overweight (BMI 25-29.9 kg/m2) or obese (BMI≥30 kg/m2) subjects was compared to risk in under/normal weight (BMI<25 kg/m2). BC subtypes were classified as i) ER-positive (regardless HER2-status) ii) ER-negative (regardless HER2-status) iii) HER2-positive (regardless ER-status); iv) triple-negative BC (TNBC). RESULTS:Out of 2841 records screened, 33 studies (9 cohort and 24 case-control) including 2,103,181 women were eligible. Obesity was associated with a modestly increased risk of ER-positive BC (pOR 1.13; 95 % CI 1.03-1.24). In postmenopausal women, obesity was associated with a moderate higher risk of ER-positive BC (pOR 1.29; 95 % CI 1.18-1.41), while overweight was associated with an increased risk of ER-positive (pOR 1.14; 95 % CI 1.06-1.22) and HER2-positive BC (pOR 1.13; 95 % CI 1.05-1.22). In premenopausal women, overweight was linked with reduced risk of ER-positive (pOR 0.80 95 % CI 0.71-0.91) but increased risk of ER-negative BC (pOR 1.15 95 % CI 1.05-1.26) and TNBC (pOR 1.30; 95 % CI 1.15-1.47). CONCLUSIONS:Obesity was associated with a modestly higher risk of ER-positive BC, driven by postmenopausal status. Considering potential confounders, in premenopausal women, higher BMI was associated with lower risk of ER-positive BC, and an increased risk of ER-negative BC.

554 Background: The 21-gene recurrence score (RS) is a foundational tool for risk-stratifying HR+/HER2- early breast cancer (EBC). However, clinical outcomes vary within RS categories. RlapsRisk BC (RR), an AI pathology-based test, integrates features from H&E-stained whole-slide images with clinical data (age, tumor size, nodal status) and was developed using 7 retrospective cohorts totaling 6,039 patients. We evaluated the clinical validity of RR and its histology-only component (RR-H) beyond RS and standard clinicopathologic factors. Methods: The clinical validity of RR was established through a validation program of 4 cohorts and over 8,521 patients across diverse geographic regions and laboratory settings. This included 3 international cohorts (n=933) and a prospective-retrospective analysis of the TAILORx trial, where RR-H was evaluable in 7,585 (97.5% of analyzable patients). The primary endpoint was distant recurrence-free interval (DRFI). In TAILORX, we assessed the additive value of the RR-H score to a base model (composed of age, tumor size, histological grade and RS) using Cox proportional hazards models and C-index comparison. Results: Across international validation cohorts (median follow-up 7.5 years, 9,8% DRFI events), RR successfully stratified patients (HR=4.91; 95% CI: 3.13-7.71; p < 0.00001), and identified a low-risk population with a 97.5% (95% CI: 95.8%-98.5%) 5-year DRFI rate. In the TAILORx population (n=7,584), the RR-H score was a highly significant independent predictor of DRFI. Incorporating RR-H as a continuous variable to the base model (including RS) significantly increased the C-index from 0.6730 to 0.7007 (p < 0.0001). The estimated HR for a 1-point difference in RR-H was 1.108 (95% CI: 1.078-1.138; p < 0.0001). When analyzed by quartiles, patients in the highest risk group (Q4) exhibited a significantly higher risk of distant recurrence compared to the lowest risk group (Q1) HR= 2.656 (95% CI: 2.003-3.522). Concordance analysis revealed that RR-H is independent of stromal TILs (R 2 =0.01). While RR-H correlated with increasing histological grade, substantial distribution overlap confirms intra-grade prognostic granularity. Furthermore, RR-H distributions were consistent across ILC and non-NLC. Conclusions: RR demonstrated robust and reproducible prognostic value across 8520 patients from diverse populations and settings establishing its clinical validity. Additional findings on TAILORx demonstrate that RR-H provides significant, independent prognostic value that complements existing prognostic tools (including genomic assays and clinicopathological factors), suggesting that integrating AI-pathology can refine precision risk assessment, and thus optimize adjuvant treatment in HR+ HER2- EBC.

Short hairpin RNAs (shRNAs) used to generate knockdown cell lines

Invasive lobular breast cancer (ILC), the most common special histologic subtype of breast cancer, may metastasize to atypical sites, including the peritoneum, gastrointestinal tract, ovaries, urinary tract, and orbit. Because metastatic ILC (mILC) is often less FDG-avid and may present after a long disease-free interval with nonspecific symptoms, diagnosis may be delayed or mistaken for other conditions. We developed and piloted a 45-question IRB-approved patient survey with breast cancer researchers, clinical oncologists, and patient advocates to evaluate patient-reported delayed diagnosis or misdiagnosis of mILC. Responses were analyzed in R using descriptive statistics after exclusion of incomplete or inconsistent responses. Among 525 completed surveys, 450 respondents had ILC and 321 had mILC; 107 (33.3%) presented with de novo mILC. Misdiagnosis was reported by 84 patients (26.2%), including 26 (31.0%) with ≥2 misdiagnoses. Nearly half (44.5%) waited ≥1 year for an accurate diagnosis, 49 received treatment for an incorrect diagnosis, and 6 received incorrect cancer-directed therapy. Symptoms before diagnosis were reported by 138 patients (42.9%), most commonly back pain, fatigue/malaise, gastrointestinal symptoms, bloating, and weight loss. These findings highlight the need for improved diagnostic strategies and clinician awareness to reduce diagnostic delays and errors in mILC.

555 Background: Stratipath Breast is an AI-based prognostic medical device for risk stratification of early-stage breast cancer using routine H&E-stained histopathology whole slide images (WSIs). AI-based analyses of histopathology slides offer an alternative to costly and logistically demanding genomic assays. In this study, the prognostic performance of Stratipath Breast was validated in the TAILORx trial (NCT00310180). Methods: WSIs from patients enrolled in TAILORx were analyzed by Stratipath Breast. After histopathology quality control and availability of clinical endpoints and WSIs, 5,519 patients were included. Stratipath Breast binary risk category, multi-level risk group, and continuous risk score were evaluated. The prognostic performance was analyzed by Kaplan-Meier statistic and log rank test, as well as concordance index (C-index). Multivariable Cox Proportional Hazard (PH) model adjusting for age, tumor size, histologic subtype and continuous Oncotype DX recurrence score (RS), both without and with histologic grade, was used to assess independent prognostic value. Recurrence-free interval (RFI) and distant recurrence-free interval (DRFI) were evaluated. Results: 53.9% (2,975/5,519) of patients were classified as Stratipath low risk and 46.1% (2,544/5,519) as high risk. A significant association of Stratipath risk category and group with RFI and DRFI was confirmed (p < 0.05). In multivariable Cox PH analyses, Stratipath high-risk category was an independent prognostic factor associated with worse outcomes (RFI HR = 1.54, 95%CI:1.29-1.84, p < 0.05; DRFI HR = 1.61, 95%CI: 1.30-1.99, p < 0.05). Stratipath risk category remained significant in multivariable analysis when histologic grade was included, whereas grade did not. RS remained prognostic significant in multivariable analyses together with Stratipath Breast, indicating potentially complementary prognostic information. C-index improved with inclusion of Stratipath Breast together with clinical variables and RS, exceeding that of grade. Conclusions: In the TAILORx trial Stratipath Breast was found to provide significant prognostic value. Stratipath Breast also provided independent prognostic value in multivariable analysis adjusting for standard clinicopathologic factors and RS. These findings support the clinical relevance of AI-driven morphology-based biomarkers for breast cancer risk stratification.

Association of clinicopathological and treatment variables with DFS and DRFS in ER+/HER2- IBC-NST patients with cL/gL risk.