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Background: In the absence of prognostic biomarkers, most patients with early-stage triple-negative breast cancer (eTNBC) are treated with combination chemotherapy. The identification of biomarkers to select patients for whom treatment de-escalation or escalation could be considered remains an unmet need. We evaluated the prognostic value of histopathologic traits in a unique cohort of young, (neo)adjuvant chemotherapy-naïve patients with early-stage (stage I or II), node-negative TNBC and long-term follow-up, in relation to stromal tumor-infiltrating lymphocytes (sTILs) for which the prognostic value was recently reported., Materials and Methods: We studied all 485 patients with node-negative eTNBC from the population-based PARADIGM cohort which selected women aged <40 years diagnosed between 1989 and 2000. None of the patients had received (neo)adjuvant chemotherapy according to standard practice at the time. Associations between histopathologic traits and breast cancer-specific survival (BCSS) were analyzed with Cox proportional hazard models., Results: With a median follow-up of 20.0 years, an independent prognostic value for BCSS was observed for lymphovascular invasion (LVI) [adjusted (adj.) hazard ratio (HR) 2.35, 95% confidence interval (CI) 1.49-3.69], fibrotic focus (adj. HR 1.61, 95% CI 1.09-2.37) and sTILs (per 10% increment adj. HR 0.75, 95% CI 0.69-0.82). In the sTILs <30% subgroup, the presence of LVI resulted in a higher cumulative incidence of breast cancer death (at 20 years, 58%; 95% CI 41% to 72%) compared with when LVI was absent (at 20 years, 32%; 95% CI 26% to 39%). In the ≥75% sTILs subgroup, the presence of LVI might be associated with poor survival (HR 11.45, 95% CI 0.71-182.36, two deaths). We confirm the lack of prognostic value of androgen receptor expression and human epidermal growth factor receptor 2 -low status., Conclusions: sTILs, LVI and fibrotic focus provide independent prognostic information in young women with node-negative eTNBC. Our results are of importance for the selection of patients for de-escalation and escalation trials., Competing Interests: Disclosure PJvD has advisory relationships with Paige, Pantarei and Samantree, paid to the institution, and research grants paid to the institute from Pfizer. NS received institutional research funding from Pfizer. ZV has a consulting role for Roche. CHMvD received institutional research funding from AstraZeneca/Daiichi Sankyo. SMW has a consulting role for Roche, and received institutional research funding from Roche, Pfizer, Bayer, MSD, AstraZeneca/Merck and Amgen. SMW has a consulting role for IDDI, Sensorion, Biophytis, Servier, Yuhan, Amaris Consulting and Roche. JW received institutional research funding from Cancer Research UK and KWF Dutch Cancer Society. AR has a consulting role for MSD Oncology, Amgen, Roche, AstraZeneca/Daiichi Sankyo and Bristol Myers Squibb/Pfizer. SCL reports grants from ZonMw and A Sister’s Hope during the conduct of the study; has been an advisory board member for AstraZeneca, Cergentis, IBM, Novartis, Pfizer, Sanofi and Roche; and received institutional research grants from Agendia, AstraZeneca, Eurocept-pharmaceuticals and Merck and Pfizer. In addition, SCL received institutional research grants and institutional non-financial support from Agendia, Genentech, Novartis, Roche, Tesaro and Immunomedics and other institutional support from AstraZeneca, Pfizer, Cergentis, Daiichi Sankyo, IBM and Bayer outside the submitted work. MK is an advisory board member and/or received speakers’ fee for/from Alderaan, Bristol Myers Squibb (BMS), Domain Therapeutics, Gilead, Roche, Medscape, MSD and AZ/Daiichi and received institutional research support from AstraZeneca/Daiichi, BMS and Roche outside the submitted work. RS reports non-financial support from Merck and BMS, research support from Merck, Puma Biotechnology and Roche, and personal fees from Roche, BMS and Exact Sciences for advisory boards. IRK received research grants from Novartis and Gilead. RHTK is an advisory board member for Amgen, AstraZeneca, Bayer, BMS, MSD, Novartis, Pfizer, Pierre Fabre Sante, Sanofi and Servier. All other authors have declared no conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Due to the abundant usage of chemotherapy in young triple-negative breast cancer (TNBC) patients, the unbiased prognostic value of BRCA1-related biomarkers in this population remains unclear. In addition, whether BRCA1-related biomarkers modify the well-established prognostic value of stromal tumor-infiltrating lymphocytes (sTILs) is unknown. This study aimed to compare the outcomes of young, node-negative, chemotherapy-naïve TNBC patients according to BRCA1 status, taking sTILs into account., Methods: We included 485 Dutch women diagnosed with node-negative TNBC under age 40 between 1989 and 2000. During this period, these women were considered low-risk and did not receive chemotherapy. BRCA1 status, including pathogenic germline BRCA1 mutation (gBRCA1m), somatic BRCA1 mutation (sBRCA1m), and tumor BRCA1 promoter methylation (BRCA1-PM), was assessed using DNA from formalin-fixed paraffin-embedded tissue. sTILs were assessed according to the international guideline. Patients' outcomes were compared using Cox regression and competing risk models., Results: Among the 399 patients with BRCA1 status, 26.3% had a gBRCA1m, 5.3% had a sBRCA1m, 36.6% had tumor BRCA1-PM, and 31.8% had BRCA1-non-altered tumors. Compared to BRCA1-non-alteration, gBRCA1m was associated with worse overall survival (OS) from the fourth year after diagnosis (adjusted HR, 2.11; 95% CI, 1.18-3.75), and this association attenuated after adjustment for second primary tumors. Every 10% sTIL increment was associated with 16% higher OS (adjusted HR, 0.84; 95% CI, 0.78-0.90) in gBRCA1m, sBRCA1m, or BRCA1-non-altered patients and 31% higher OS in tumor BRCA1-PM patients. Among the 66 patients with tumor BRCA1-PM and ≥ 50% sTILs, we observed excellent 15-year OS (97.0%; 95% CI, 92.9-100%). Conversely, among the 61 patients with gBRCA1m and < 50% sTILs, we observed poor 15-year OS (50.8%; 95% CI, 39.7-65.0%). Furthermore, gBRCA1m was associated with higher (adjusted subdistribution HR, 4.04; 95% CI, 2.29-7.13) and tumor BRCA1-PM with lower (adjusted subdistribution HR, 0.42; 95% CI, 0.19-0.95) incidence of second primary tumors, compared to BRCA1-non-alteration., Conclusions: Although both gBRCA1m and tumor BRCA1-PM alter BRCA1 gene transcription, they are associated with different outcomes in young, node-negative, chemotherapy-naïve TNBC patients. By combining sTILs and BRCA1 status for risk classification, we were able to identify potential subgroups in this population to intensify and optimize adjuvant treatment., (© 2023. The Author(s).)

Background: The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment., Methods: We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds., Results: A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22-1.43). Model discrimination was moderate overall (AUC 10-year :0.65, 95%CI:0.62-0.68), and poor for women with ER-negative tumors (AUC 10-year :0.56, 95%CI:0.51-0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors., Conclusions: PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset., Competing Interests: Declaration of Competing Interest Sabine C. Linn has been an advisory board member for AstraZeneca, Cergentis, IBM, Novartis, Pfizer, Roche and Sanofi, and has received unrestricted institutional research support or unrestricted educational funding from Agendia, Amgen, AstraZeneca, Bayer, Daiichi Sankyo, Eurocept Pharmaceuticals, Genentech, Immunomedics (now Gilead), Merck, Roche, Sanofi and TESARO (now GSK), and has a pending patent application for a BRCA-like ovarian cancer classifier. Paul J. van Diest has a pending patent application for DDX3 as a biomarker for cancer and its related methods. Gabe Sonke has received institutional research support from Agendia, AstraZeneca, Merck, Novartis, Roche and Seagen. Other authors claim no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Breast cancer tumor grade is strongly associated with patient survival. In current clinical practice, pathologists assign tumor grade after visual analysis of tissue specimens. However, different studies show significant inter-observer variation in breast cancer grading. Computer-based breast cancer grading methods have been proposed but only work on specifically selected tissue areas and/or require labor-intensive annotations to be applied to new datasets. In this study, we trained and evaluated a deep learning-based breast cancer grading model that works on whole-slide histopathology images. The model was developed using whole-slide images from 706 young (&lt; 40 years) invasive breast cancer patients with corresponding tumor grade (low/intermediate vs. high), and its constituents nuclear grade, tubule formation and mitotic rate. The performance of the model was evaluated using Cohen's kappa on an independent test set of 686 patients using annotations by expert pathologists as ground truth. The predicted low/intermediate (n = 327) and high (n = 359) grade groups were used to perform survival analysis. The deep learning system distinguished low/intermediate versus high tumor grade with a Cohen's Kappa of 0.59 (80% accuracy) compared to expert pathologists. In subsequent survival analysis the two groups predicted by the system were found to have a significantly different overall survival (OS) and disease/recurrence-free survival (DRFS/RFS) (p &lt; 0.05). Univariate Cox hazard regression analysis showed statistically significant hazard ratios (p &lt; 0.05). After adjusting for clinicopathologic features and stratifying for molecular subtype the hazard ratios showed a trend but lost statistical significance for all endpoints. In conclusion, we developed a deep learning-based model for automated grading of breast cancer on whole-slide images. The model distinguishes between low/intermediate and high grade tumors and finds a trend in the survival of the two predicted groups., (© 2022. The Author(s).)

Purpose: Triple-negative breast cancer (TNBC) is considered aggressive, and therefore, virtually all young patients with TNBC receive (neo)adjuvant chemotherapy. Increased stromal tumor-infiltrating lymphocytes (sTILs) have been associated with a favorable prognosis in TNBC. However, whether this association holds for patients who are node-negative (N0), young (< 40 years), and chemotherapy-naïve, and thus can be used for chemotherapy de-escalation strategies, is unknown., Methods: We selected all patients with N0 TNBC diagnosed between 1989 and 2000 from a Dutch population-based registry. Patients were age < 40 years at diagnosis and had not received (neo)adjuvant systemic therapy, as was standard practice at the time. Formalin-fixed paraffin-embedded blocks were retrieved (PALGA: Dutch Pathology Registry), and a pathology review including sTILs was performed. Patients were categorized according to sTILs (< 30%, 30%-75%, and ≥ 75%). Multivariable Cox regression was performed for overall survival, with or without sTILs as a covariate. Cumulative incidence of distant metastasis or death was analyzed in a competing risk model, with second primary tumors as competing risk., Results: sTILs were scored for 441 patients. High sTILs (≥ 75%; 21%) translated into an excellent prognosis with a 15-year cumulative incidence of a distant metastasis or death of only 2.1% (95% CI, 0 to 5.0), whereas low sTILs (< 30%; 52%) had an unfavorable prognosis with a 15-year cumulative incidence of a distant metastasis or death of 38.4% (32.1 to 44.6). In addition, every 10% increment of sTILs decreased the risk of death by 19% (adjusted hazard ratio: 0.81; 95% CI, 0.76 to 0.87), which are an independent predictor adding prognostic information to standard clinicopathologic variables (χ 2 = 46.7, P < .001)., Conclusion: Chemotherapy-naïve, young patients with N0 TNBC with high sTILs (≥ 75%) have an excellent long-term prognosis. Therefore, sTILs should be considered for prospective clinical trials investigating (neo)adjuvant chemotherapy de-escalation strategies.

Background: The benefit of adjuvant aromatase inhibitors (AI) vs tamoxifen has been investigated in randomized clinical trials for premenopausal and postmenopausal patients with early, estrogen receptor-positive (ER+) breast cancer. The optimal endocrine treatment for chemotherapy-treated perimenopausal women, who generally develop chemotherapy-induced amenorrhea, is uncertain., Methods: All Dutch women who received adjuvant chemotherapy and endocrine treatment for stage I-III, ER+ (>10% positive cells), invasive breast cancer diagnosed between 2004 and 2007 were identified through the Netherlands Cancer Registry. Included women were considered perimenopausal based on an age at diagnosis of 45 to 50 years (n = 2295). For each patient, AI treatment duration relative to total endocrine treatment duration was calculated. Predominantly tamoxifen-treated patients (AI < 25%) were compared with those receiving AI and tamoxifen for a similar duration (AI 25%-75%) and those mostly using AI (AI > 75%). Adjusted hazard ratios (HRs) for recurrence-free survival (RFS) and overall survival were calculated using time-dependent Cox regression., Results: After an average follow-up of 7.6 years, 377 RFS events occurred. Women mostly receiving AI (AI > 75%) had the best RFS (adjusted HR = 0.63, 95% confidence interval = 0.46 to 0.86) followed by those receiving AI 25% to 75% (adjusted HR = 0.85, 95% confidence interval = 0.65 to 1.12) compared with predominantly tamoxifen-treated women. Trend analyses showed that every 10% increase in AI-endocrine treatment ratio reduced RFS event risk by 5% (2-sided Ptrend = .002). In total, 236 deaths occurred; hazard ratios for overall survival showed similar trends., Conclusions: These results suggest that the best adjuvant endocrine treatment for chemotherapy-treated, ER+ breast cancer patients diagnosed aged 45-50 years consists of mainly AI followed by a switch strategy and mainly tamoxifen., (© The Author(s) 2021. Published by Oxford University Press.)

Preclinical studies have shown synergistic effects when combining PARP1/2 inhibitors and platinum drugs in BRCA1/2 mutated cancer cell models. After a formulation change of olaparib from capsules to tablets, we initiated a dose finding study of olaparib tablets bidaily (BID) continuously with carboplatin to prepare comparative studies in this patient group. Patients were included in a 3 + 3 dose-escalation schedule: olaparib 25 mg BID and carboplatin area under the curve (AUC) 3 mg*min/mL d1/d22, olaparib 25 mg BID and carboplatin AUC 4 mg*min/mL d1/d22, followed by increasing dose-levels of olaparib from 50 mg BID, 75 mg BID, to 100 mg BID with carboplatin at AUC 4 mg*min/mL d1/d22. After two cycles, patients continued olaparib 300 mg BID as monotherapy. Primary objective was to assess the maximum tolerable dose (MTD). Twenty-four patients with a confirmed diagnosis of advanced cancer were included. Most common adverse events were nausea (46%), fatigue (33%) and platelet count decrease (33%). Dose-level 3 (olaparib 75 mg BID and carboplatin AUC 4 mg*min/mL; n = 6) was defined as MTD. Fourteen out of 24 patients (56%) had a partial response as best response (RECIST 1.1). Systemic exposure of the olaparib tablet formulation appeared comparable to the previous capsule formulation with olaparib tablet AUC 0-12 of 16.3 μg/mL*h at MTD. Polymers of ADP-ribose levels in peripheral blood mononuclear cells were reduced by 98.7% ± 0.14% at Day 8 compared to Day 1 for dose-level 3. Olaparib tablets 75 mg BID and carboplatin AUC 4 mg*min/mL for two cycles preceding olaparib monotherapy 300 mg is a feasible and tolerable treatment schedule for patients with advanced cancer., (© 2021 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Purpose: The addition of trastuzumab to adjuvant chemotherapy has improved the outcome of human epidermal growth-factor receptor 2 (HER2)-positive breast cancer. Uncertainty remains about the optimal timing of trastuzumab treatment. Therefore, we compared long-term outcome after concurrent versus sequential treatment, in a population-based setting, using data from the nationwide Netherlands Cancer Registry., Methods: We identified 1843 women diagnosed in The Netherlands from January 1st 2005 until January 1st 2008 with primary, HER2-positive, T 1-4 N any M 0 breast cancer who received adjuvant chemotherapy and trastuzumab. Kaplan-Meier survival estimates and Cox regression were used to compare recurrence-free survival (RFS) and overall survival (OS) between women who received trastuzumab concurrently with versus sequentially after chemotherapy. Hazard ratios (HR) were adjusted for age, year of diagnosis, grade, pathological T-stage, number of positive lymph nodes, ER-status, PR-status, socio-economic status, radiotherapy, hormonal therapy, ovarian ablation, and type of chemotherapy., Results: After a median follow-up of 8.2 years, RFS events had occurred in 224 out of 1235 (18.1%) concurrently treated women and 129 out of 608 (21.2%) sequentially treated women (adjusted-HR 0.91; 95% confidence interval (CI) 0.67-1.24; P = 0.580). Deaths occurred in 182/1235 (14.7%) concurrently treated women and 104/608 (17.1%) sequentially treated women (adjusted-HR 0.92; 95% CI 0.65-1.29; P = 0.635)., Conclusions: The results of this population-based study are consistent with earlier randomized trials, demonstrating a non-significant difference in outcome for concurrently treated women compared to those who were treated sequentially, suggesting both options are justified.

Background: Prior randomised controlled trials on adjuvant hormonal therapy included HER2 any patients; however, a differential effect of aromatase inhibitors (AIs) versus tamoxifen (TAM) may have been missed in ER+/HER2+ patients that comprise 7-15% of all breast cancer patients. In addition, a woman's hormonal microenvironment may influence sensitivity to TAM and AIs in the adjuvant setting, which changes during menopausal transition, a process that takes years. We studied the efficacy of AIs versus TAM in ER+/HER2+ breast cancer patients grouped by age at diagnosis as a proxy for menopausal status using treatment and outcome data from the nationwide population-based Netherlands Cancer Registry (NCR)., Patients and Methods: All women diagnosed between 2005 and 2007 with endocrine-treated, T any N any M 0 , ER+/HER2+ breast cancer were identified through the NCR (n = 1155). Patients were divided by age at diagnosis: premenopausal (≤45 years; n = 326), perimenopausal (4555 years; n = 525). A time-dependent variable, indicating whether AI or TAM was received for >50% of endocrine treatment duration, was applied to subdivide groups by predominant treatment received. Recurrence-free survival (RFS) and overall survival (OS) were assessed using Kaplan-Meier survival estimation and Cox regression. Hazard ratios (HRs) were adjusted for chemotherapy, trastuzumab, age at diagnosis, N-status, grade, pT-stage and ovarian ablation., Results: During follow-up, 237 recurrences and 182 deaths occurred. Perimenopausal women derived significant RFS and OS benefit from AI compared with TAM, HR 0.47 (95% CI 0.25-0.91; P = 0.03) and HR 0.37 (95% CI 0.18-0.79; P = 0.01), respectively, whereas premenopausal women derived no benefit from AI compared with TAM. Treatment effects differed significantly between these age groups (interaction P = 0.03 and P = 0.02, respectively). Among postmenopausal women a small but non-significant AI benefit was observed., Conclusion: AI treatment, preferably without any TAM treatment, was associated with the best RFS and OS outcome in ER+/HER2+ perimenopausal breast cancer patients., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)