MRI-guided optimisation of neoadjuvant chemotherapy duration in stage II-III HER2-positive breast cancer (TRAIN-3): a multicentre, single-arm, phase 2 study

BACKGROUND

Patients with stage II-III HER2-positive breast cancer have good outcomes with the combination of neoadjuvant chemotherapy and HER2-targeted agents. Although increasing the number of chemotherapy cycles improves pathological complete response rates, early complete responses are common. We investigated whether the duration of chemotherapy could be tailored on the basis of radiological response.

METHODS

TRAIN-3 is a single-arm, phase 2 study in 43 hospitals in the Netherlands. Patients with stage II-III HER2-positive breast cancer aged 18 years or older and a WHO performance status of 0 or 1 were enrolled. Patients received neoadjuvant chemotherapy consisting of paclitaxel (80 mg/m2 of body surface area on day 1 and 8 of each 21 day cycle), trastuzumab (loading dose on day 1 of cycle 1 of 8 mg/kg bodyweight, and then 6 mg/kg on day 1 on all subsequent cycles), and carboplatin (area under the concentration time curve 6 mg/mL per min on day 1 of each 3 week cycle) and pertuzumab (loading dose on day 1 of cycle 1 of 840 mg, and then 420 mg on day 1 of each subsequent cycle), all given intravenously. The response was monitored by breast MRI every three cycles and lymph node biopsy. Patients underwent surgery when a complete radiological response was observed or after a maximum of nine cycles of treatment. The primary endpoint was event-free survival at 3 years; however, follow-up for the primary endpoint is ongoing. Here, we present the radiological and pathological response rates (secondary endpoints) of all patients who underwent surgery and the toxicity data for all patients who received at least one cycle of treatment. Analyses were done in hormone receptor-positive and hormone receptor-negative patients separately. This trial is registered with ClinicalTrials.gov, number NCT03820063, recruitment is closed, and the follow-up for the primary endpoint is ongoing.

FINDINGS

Between April 1, 2019, and May 12, 2021, 235 patients with hormone receptor-negative cancer and 232 with hormone receptor-positive cancer were enrolled. Median follow-up was 26·4 months (IQR 22·9-32·9) for patients who were hormone receptor-negative and 31·6 months (25·6-35·7) for patients who were hormone receptor-positive. Overall, the median age was 51 years (IQR 43-59). In 233 patients with hormone receptor-negative tumours, radiological complete response was seen in 84 (36%; 95% CI 30-43) patients after one to three cycles, 140 (60%; 53-66) patients after one to six cycles, and 169 (73%; 66-78) patients after one to nine cycles. In 232 patients with hormone receptor-positive tumours, radiological complete response was seen in 68 (29%; 24-36) patients after one to three cycles, 118 (51%; 44-57) patients after one to six cycles, and 138 (59%; 53-66) patients after one to nine cycles. Among patients with a radiological complete response after one to nine cycles, a pathological complete response was seen in 147 (87%; 95% CI 81-92) of 169 patients with hormone receptor-negative tumours and was seen in 73 (53%; 44-61) of 138 patients with hormone receptor-positive tumours. The most common grade 3-4 adverse events were neutropenia (175 [37%] of 467), anaemia (75 [16%]), and diarrhoea (57 [12%]). No treatment-related deaths were reported.

INTERPRETATION

In our study, a third of patients with stage II-III hormone receptor-negative and HER2-positive breast cancer had a complete pathological response after only three cycles of neoadjuvant systemic therapy. A complete response on breast MRI could help identify early complete responders in patients who had hormone receptor negative tumours. An imaging-based strategy might limit the duration of chemotherapy in these patients, reduce side-effects, and maintain quality of life if confirmed by the analysis of the 3-year event-free survival primary endpoint. Better monitoring tools are needed for patients with hormone receptor-positive and HER2-positive breast cancer.

FUNDING

Roche Netherlands.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials

BACKGROUND

Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296-2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA),  L. E. Elshof et al., Eur J Cancer, 51, 1497-510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials.

OBJECTIVE

To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance.

METHODS

In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS.

RESULTS

When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved.

CONCLUSION

For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.

Prognostic value of histopathologic traits independent of stromal tumor-infiltrating lymphocyte levels in chemotherapy-naïve patients with triple-negative breast cancer

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.

The effects of contemporary treatment of DCIS on the risk of developing an ipsilateral invasive Breast cancer (iIBC) in the Dutch population

PURPOSE

To assess the effects of contemporary treatment of ductal carcinoma in situ (DCIS) on the risk of developing an ipsilateral invasive breast cancer (iIBC) in the Dutch female population.

METHODS

Clinical data was obtained from the Netherlands Cancer Registry (NCR), a nationwide registry of all primary malignancies in the Netherlands integrated with the data from PALGA, the Dutch nationwide network and registry of histo- and cytopathology in the Netherlands, on all women in the Netherlands treated for primary DCIS from 2005 to 2015, resulting in a population-based cohort of 14.419 women. Cumulative iIBC incidence was assessed and associations of DCIS treatment type with subsequent iIBC risk were evaluated by multivariable Cox regression analyses.

RESULTS

Ten years after DCIS diagnosis, the cumulative incidence of iIBC was 3.1% (95% CI: 2.6-3.5%) in patients treated by breast conserving surgery (BCS) plus radiotherapy (RT), 7.1% (95% CI: 5.5-9.1) in patients treated by BCS alone, and 1.6% (95% CI: 1.3-2.1) in patients treated by mastectomy. BCS was associated with a significantly higher risk for iIBC compared to BCS + RT during the first 5 years after treatment (HR 2.80, 95% CI: 1.91-4.10%). After 5 years of follow-up, the iIBC risk declined in the BCS alone group but remained higher than the iIBC risk in the BCS + RT group (HR 1.73, 95% CI: 1.15-2.61).

CONCLUSIONS

Although absolute risks of iIBC were low in patients treated for DCIS with either BCS or BCS + RT, risks remained higher in the BCS alone group compared to patients treated with BCS + RT for at least 10 years after DCIS diagnosis.

Causality and functional relevance of BRCA1 and BRCA2 pathogenic variants in non-high-grade serous ovarian carcinomas

The identification of causal BRCA1/2 pathogenic variants (PVs) in epithelial ovarian carcinoma (EOC) aids the selection of patients for genetic counselling and treatment decision-making. Current recommendations therefore stress sequencing of all EOCs, regardless of histotype. Although it is recognised that BRCA1/2 PVs cluster in high-grade serous ovarian carcinomas (HGSOC), this view is largely unsubstantiated by detailed analysis. Here, we aimed to analyse the results of BRCA1/2 tumour sequencing in a centrally revised, consecutive, prospective series including all EOC histotypes. Sequencing of n = 946 EOCs revealed BRCA1/2 PVs in 125 samples (13%), only eight of which were found in non-HGSOC histotypes. Specifically, BRCA1/2 PVs were identified in high-grade endometrioid (3/20; 15%), low-grade endometrioid (1/40; 2.5%), low-grade serous (3/67; 4.5%), and clear cell (1/64; 1.6%) EOCs. No PVs were identified in any mucinous ovarian carcinomas tested. By re-evaluation and using loss of heterozygosity and homologous recombination deficiency analyses, we then assessed: (1) whether the eight 'anomalous' cases were potentially histologically misclassified and (2) whether the identified variants were likely causal in carcinogenesis. The first 'anomalous' non-HGSOC with a BRCA1/2 PV proved to be a misdiagnosed HGSOC. Next, germline BRCA2 variants, found in two p53-abnormal high-grade endometrioid tumours, showed substantial evidence supporting causality. One additional, likely causal variant, found in a p53-wildtype low-grade serous ovarian carcinoma, was of somatic origin. The remaining cases showed retention of the BRCA1/2 wildtype allele, suggestive of non-causal secondary passenger variants. We conclude that likely causal BRCA1/2 variants are present in high-grade endometrioid tumours but are absent from the other EOC histotypes tested. Although the findings require validation, these results seem to justify a transition from universal to histotype-directed sequencing. Furthermore, in-depth functional analysis of tumours harbouring BRCA1/2 variants combined with detailed revision of cancer histotypes can serve as a model in other BRCA1/2-related cancers. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Proteomics on malignant pleural effusions reveals ERα loss in metastatic breast cancer associates with SGK1-NDRG1 deregulation

Breast cancer (BCa) is a highly heterogeneous disease, with hormone receptor status being a key factor in patient prognostication and treatment decision-making. The majority of primary tumours are positive for oestrogen receptor alpha (ERα), which plays a key role in tumorigenesis and disease progression, and represents the major target for treatment of BCa. However, around one-third of patients with ERα-positive BCa relapse and progress into the metastatic stage, with 20% of metastatic cases characterised by loss of ERα expression after endocrine treatment, known as ERα-conversion. It remains unclear whether ERα-converted cancers are biologically similar to bona fide ERα-negative disease and which signalling cascades compensate for ERα loss and drive tumour progression. To better understand the biological changes that occur in metastatic BCa upon ERα loss, we performed (phospho)proteomics analysis of 47 malignant pleural effusions derived from 37 BCa patients, comparing ERα-positive, ERα-converted and ERα-negative cases. Our data revealed that the loss of ERα-dependency in this metastatic site leads to only a partial switch to an ERα-negative molecular phenotype, with preservation of a luminal-like proteomic landscape. Furthermore, we found evidence for decreased activity of several key kinases, including serum/glucocorticoid regulated kinase 1 (SGK1), in ERα-converted metastases. Loss of SGK1 substrate phosphorylation may compensate for the loss of ERα-dependency in advanced disease and exposes a potential therapeutic vulnerability that may be exploited in treating these patients.

Artificial intelligence-based morphometric signature to identify ductal carcinoma in situ with low risk of progression to invasive breast cancer

Ductal carcinoma in situ (DCIS) may progress to ipsilateral invasive breast cancer (iIBC), but often never will. Because DCIS is treated as early breast cancer, many women with harmless DCIS face overtreatment. To identify these women that may forego treatment, we hypothesized that DCIS morphometric features relate to the risk of subsequent iIBC. We developed an artificial intelligence-based DCIS morphometric analysis pipeline (AIDmap) to detect DCIS as a pathologist and measure morphological structures in hematoxylin-eosin-stained (H&E) tissue sections. These were from a case-control study of patients diagnosed with primary DCIS, treated by breast-conserving surgery without radiotherapy. We analyzed 689 WSIs of DCIS of which 226 were diagnosed with subsequent iIBC (cases) and 463 were not (controls). The distribution of 15 duct morphological measurements in each H&E was summarized in 55 morphometric variables. A ridge regression classifier with cross validation predicted 5-years-free of iIBC with an area-under the curve of 0.65 (95% CI 0.55-0.76). A morphometric signature based on the 30 variables most associated with outcome, identified lesions containing small-sized ducts, low number of cells and low DCIS/stroma area ratio. This signature was associated with lower iIBC risk in a multivariate regression model including grade, ER, HER2 and COX-2 expression (HR = 0.56; 95% CI 0.28-0.78). AIDmap has potential to identify harmless DCIS that may not need treatment.

Clinicopathological and prognostic value of calcification morphology descriptors in ductal carcinoma in situ of the breast: a systematic review and meta-analysis

BACKGROUND

Calcifications on mammography can be indicative of breast cancer, but the prognostic value of their appearance remains unclear. This systematic review and meta-analysis aimed to evaluate the association between mammographic calcification morphology descriptors (CMDs) and clinicopathological factors.

METHODS

A comprehensive literature search in Medline via Ovid, Embase.com, and Web of Science was conducted for articles published between 2000 and January 2022 that assessed the relationship between CMDs and clinicopathological factors, excluding case reports and review articles. The risk of bias and overall quality of evidence were evaluated using the QUIPS tool and GRADE. A random-effects model was used to synthesize the extracted data. This systematic review is reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA).

RESULTS

Among the 4715 articles reviewed, 29 met the inclusion criteria, reporting on 17 different clinicopathological factors in relation to CMDs. Heterogeneity between studies was present and the overall risk of bias was high, primarily due to small, inadequately described study populations. Meta-analysis demonstrated significant associations between fine linear calcifications and high-grade DCIS [pooled odds ratio (pOR), 4.92; 95% confidence interval (CI), 2.64-9.17], (comedo)necrosis (pOR, 3.46; 95% CI, 1.29-9.30), (micro)invasion (pOR, 1.53; 95% CI, 1.03-2.27), and a negative association with estrogen receptor positivity (pOR, 0.33; 95% CI, 0.12-0.89).

CONCLUSIONS

CMDs detected on mammography have prognostic value, but there is a high level of bias and variability between current studies. In order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.

CRITICAL RELEVANCE STATEMENT

Mammographic calcification morphology descriptors (CMDs) have prognostic value, but in order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.

SYSTEMATIC REVIEW REGISTRATION

CRD42022341599 KEY POINTS: • Mammographic calcifications can be indicative of breast cancer. • The prognostic value of mammographic calcifications is still unclear. • Specific mammographic calcification morphologies are related to lesion aggressiveness. • Variability between studies necessitates standardization in calcification evaluation to achieve clinical utility.

Impact of the COVID-19 pandemic on breast cancer incidence and tumor stage in the Netherlands and Norway: A population-based study

BACKGROUND

Comparing the impact of the COVID-19 pandemic on the incidence of newly diagnosed breast tumors and their tumor stage between the Netherlands and Norway will help us understand the effect of differences in governmental and social reactions towards the pandemic.

METHODS

Women newly diagnosed with breast cancer in 2017-2021 were selected from the Netherlands Cancer Registry and the Cancer Registry of Norway. The crude breast cancer incidence rate (tumors per 100,000 women) during the first (March-September 2020), second (October 2020-April 2021), and Delta COVID-19 wave (May-December 2021) was compared with the incidence rate in the corresponding periods in 2017, 2018, and 2019. Incidence rates were stratified by age group, method of detection, and clinical tumor stage.

RESULTS

During the first wave breast cancer incidence declined to a larger extent in the Netherlands than in Norway (27.7% vs. 17.2% decrease, respectively). In both countries, incidence decreased in women eligible for screening. In the Netherlands, incidence also decreased in women not eligible for screening. During the second wave an increase in the incidence of stage IV tumors in women aged 50-69 years was seen in the Netherlands. During the Delta wave an increase in overall incidence and incidence of stage I tumors was seen in Norway.

CONCLUSION

Alterations in breast cancer incidence and tumor stage seem related to a combined effect of the suspension of the screening program, health care avoidance due to the severity of the pandemic, and other unknown factors.

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning

BACKGROUND

Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict treatment response before administering the therapy.

METHODS

In this retrospective study, we developed hypothesis-driven interpretable biomarkers based on deep learning, to predict the pathological complete response (pCR, i.e., the absence of tumor cells in the surgical resection specimens) to neoadjuvant chemotherapy solely using digital pathology H&E images of pre-treatment breast biopsies. Our approach consists of two steps: First, we use deep learning to characterize aspects of the tumor micro-environment by detecting mitoses and segmenting tissue into several morphology compartments including tumor, lymphocytes and stroma. Second, we derive computational biomarkers from the segmentation and detection output to encode slide-level relationships of components of the tumor microenvironment, such as tumor and mitoses, stroma, and tumor infiltrating lymphocytes (TILs).

RESULTS

We developed and evaluated our method on slides from n = 721 patients from three European medical centers with triple-negative and Luminal B breast cancers and performed external independent validation on n = 126 patients from a public dataset. We report the predictive value of the investigated biomarkers for predicting pCR with areas under the receiver operating characteristic curve between 0.66 and 0.88 across the tested cohorts.

CONCLUSION

The proposed computational biomarkers predict pCR, but will require more evaluation and finetuning for clinical application. Our results further corroborate the potential role of deep learning to automate TILs quantification, and their predictive value in breast cancer neoadjuvant treatment planning, along with automated mitoses quantification. We made our method publicly available to extract segmentation-based biomarkers for research purposes.

Association of DCIS size and margin status with risk of developing breast cancer post-treatment: multinational, pooled cohort study

OBJECTIVE

To examine the association between size and margin status of ductal carcinoma in situ (DCIS) and risk of developing ipsilateral invasive breast cancer and ipsilateral DCIS after treatment, and stage and subtype of ipsilateral invasive breast cancer.

DESIGN

Multinational, pooled cohort study.

SETTING

Four large international cohorts.

PARTICIPANTS

Patient level data on 47 695 women with a diagnosis of pure, primary DCIS between 1999 and 2017 in the Netherlands, UK, and US who underwent surgery, either breast conserving or mastectomy, often followed by radiotherapy or endocrine treatment, or both.

MAIN OUTCOME MEASURES

The main outcomes were 10 year cumulative incidence of ipsilateral invasive breast cancer and ipsilateral DCIS estimated in relation to DCIS size and margin status, and adjusted hazard ratios and 95% confidence intervals, estimated using multivariable Cox proportional hazards analyses with multiple imputed data RESULTS: The 10 year cumulative incidence of ipsilateral invasive breast cancer was 3.2%. In women who underwent breast conserving surgery with or without radiotherapy, only adjusted risks for ipsilateral DCIS were significantly increased for larger DCIS (20-49 mm) compared with DCIS <20 mm (hazard ratio 1.38, 95% confidence interval 1.11 to 1.72). Risks for both ipsilateral invasive breast cancer and ipsilateral DCIS were significantly higher with involved compared with clear margins (invasive breast cancer 1.40, 1.07 to 1.83; DCIS 1.39, 1.04 to 1.87). Use of adjuvant endocrine treatment was not significantly associated with a lower risk of ipsilateral invasive breast cancer compared to treatment with breast conserving surgery only (0.86, 0.62 to 1.21). In women who received breast conserving treatment with or without radiotherapy, higher DCIS grade was not significantly associated with ipsilateral invasive breast cancer, only with a higher risk of ipsilateral DCIS (grade 1: 1.42, 1.08 to 1.87; grade 3: 2.17, 1.66 to 2.83). Higher age at diagnosis was associated with lower risk (per year) of ipsilateral DCIS (0.98, 0.97 to 0.99) but not ipsilateral invasive breast cancer (1.00, 0.99 to 1.00). Women with large DCIS (≥50 mm) more often developed stage III and IV ipsilateral invasive breast cancer compared to women with DCIS <20 mm. No such association was found between involved margins and higher stage of ipsilateral invasive breast cancer. Associations between larger DCIS and hormone receptor negative and human epidermal growth factor receptor 2 positive ipsilateral invasive breast cancer and involved margins and hormone receptor negative ipsilateral invasive breast cancer were found.

CONCLUSIONS

The association of DCIS size and margin status with ipsilateral invasive breast cancer and ipsilateral DCIS was small. When these two factors were added to other known risk factors in multivariable models, clinicopathological risk factors alone were found to be limited in discriminating between low and high risk DCIS.

Deep (phospho)proteomics profiling of pre- treatment needle biopsies identifies signatures of treatment resistance in HER2+ breast cancer

Patients with early-stage HER2-overexpressing breast cancer struggle with treatment resistance in 20%-40% of cases. More information is needed to predict HER2 therapy response and resistance in vivo. In this study, we perform (phospho)proteomics analysis of pre-treatment HER2+ needle biopsies of early-stage invasive breast cancer to identify molecular signatures predictive of treatment response to trastuzumab, pertuzumab, and chemotherapy. Our data show that accurate quantification of the estrogen receptor (ER) and HER2 biomarkers, combined with the assessment of associated biological features, has the potential to enable better treatment outcome prediction. In addition, we identify cellular mechanisms that potentially precondition tumors to resist therapy. We find proteins with expression changes that correlate with resistance and constitute to a strong predictive signature for treatment success in our patient cohort. Our results highlight the multifactorial nature of drug resistance in vivo and demonstrate the necessity of deep tumor profiling.

Active surveillance versus treatment in low-risk DCIS: Women's preferences in the LORD-trial

BACKGROUND

Ductal carcinoma in situ (DCIS) can progress to invasive breast cancer (IBC), but most DCIS lesions remain indolent. However, guidelines recommend surgery, often supplemented by radiotherapy. This implies overtreatment of indolent DCIS. The non-randomised patient preference LORD-trial tests whether active surveillance (AS) for low-risk DCIS is safe, by giving women with low-risk DCIS a choice between AS and conventional treatment (CT). Here, we aim to describe how participants are distributed among both trial arms, identify their motives for their preference, and assess factors associated with their choice.

METHODS

Data were extracted from baseline questionnaires. Descriptive statistics were used to assess the distribution and characteristics of participants; thematic analyses to extract self-reported reasons for the choice of trial arm, and multivariable logistic regression analyses to investigate associations between patient characteristics and chosen trial arm.

RESULTS

Of 377 women included, 76% chose AS and 24% CT. Most frequently cited reasons for AS were "treatment is not (yet) necessary" (59%) and trust in the AS-plan (39%). Reasons for CT were cancer worry (51%) and perceived certainty (29%). Women opting for AS more often had lower educational levels (OR 0.45; 95% confidence interval [CI], 0.22-0.93) and more often reported experiencing shared decision making (OR 2.71; 95% CI, 1.37-5.37) than women choosing CT.

CONCLUSION

The LORD-trial is the first to offer women with low-risk DCIS a choice between CT and AS. Most women opted for AS and reported high levels of trust in the safety of AS. Their preferences highlight the necessity to establish the safety of AS for low-risk DCIS.

High-dose alkylating chemotherapy in BRCA-altered triple-negative breast cancer: the randomized phase III NeoTN trial

Exploratory analyses of high-dose alkylating chemotherapy trials have suggested that BRCA1 or BRCA2-pathway altered (BRCA-altered) breast cancer might be particularly sensitive to this type of treatment. In this study, patients with BRCA-altered tumors who had received three initial courses of dose-dense doxorubicin and cyclophosphamide (ddAC), were randomized between a fourth ddAC course followed by high-dose carboplatin-thiotepa-cyclophosphamide or conventional chemotherapy (initially ddAC only or ddAC-capecitabine/decetaxel [CD] depending on MRI response, after amendment ddAC-carboplatin/paclitaxel [CP] for everyone). The primary endpoint was the neoadjuvant response index (NRI). Secondary endpoints included recurrence-free survival (RFS) and overall survival (OS). In total, 122 patients were randomized. No difference in NRI-score distribution (p = 0.41) was found. A statistically non-significant RFS difference was found (HR 0.54; 95% CI 0.23-1.25; p = 0.15). Exploratory RFS analyses showed benefit in stage III (n = 35; HR 0.16; 95% CI 0.03-0.75), but not stage II (n = 86; HR 1.00; 95% CI 0.30-3.30) patients. For stage III, 4-year RFS was 46% (95% CI 24-87%), 71% (95% CI 48-100%) and 88% (95% CI 74-100%), for ddAC/ddAC-CD, ddAC-CP and high-dose chemotherapy, respectively. No significant differences were found between high-dose and conventional chemotherapy in stage II-III, triple-negative, BRCA-altered breast cancer patients. Further research is needed to establish if there are patients with stage III, triple negative BRCA-altered breast cancer for whom outcomes can be improved with high-dose alkylating chemotherapy or whether the current standard neoadjuvant therapy including carboplatin and an immune checkpoint inhibitor is sufficient. Trial Registration: NCT01057069.

Archival single-cell genomics reveals persistent subclones during DCIS progression

Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer. Our understanding of its genomic progression to recurrent disease remains poor, partly due to challenges associated with the genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. Here, we developed Arc-well, a high-throughput single-cell DNA-sequencing method that is compatible with FFPE materials. We validated our method by profiling 40,330 single cells from cell lines, a frozen tissue, and 27 FFPE samples from breast, lung, and prostate tumors stored for 3-31 years. Analysis of 10 patients with matched DCIS and cancers that recurred 2-16 years later show that many primary DCIS had already undergone whole-genome doubling and clonal diversification and that they shared genomic lineages with persistent subclones in the recurrences. Evolutionary analysis suggests that most DCIS cases in our cohort underwent an evolutionary bottleneck, and further identified chromosome aberrations in the persistent subclones that were associated with recurrence.

BluePrint molecular subtypes predict response to neoadjuvant pertuzumab in HER2-positive breast cancer

BACKGROUND

The introduction of pertuzumab has greatly improved pathological complete response (pCR) rates in HER2-positive breast cancer, yet effects on long-term survival have been limited and it is uncertain which patients derive most benefit. In this study, we determine the prognostic value of BluePrint subtyping in HER2-positive breast cancer. Additionally, we evaluate its use as a biomarker for predicting response to trastuzumab-containing neoadjuvant chemotherapy with or without pertuzumab.

METHODS

From a cohort of patients with stage II-III HER2-positive breast cancer who were treated with neoadjuvant chemotherapy and trastuzumab with or without pertuzumab, 836 patients were selected for microarray gene expression analysis, followed by readout of BluePrint standard (HER2, Basal and Luminal) and dual subtypes (HER2-single, Basal-single, Luminal-single, HER2-Basal, Luminal-HER2, Luminal-HER2-Basal). The associations between subtypes and pathological complete response (pCR), overall survival (OS) and breast cancer-specific survival (BCSS) were assessed, and pertuzumab benefit was evaluated within the BluePrint subgroups.

RESULTS

BluePrint results were available for 719 patients. In patients with HER2-type tumors, the pCR rate was 71.9% in patients who received pertuzumab versus 43.5% in patients who did not (adjusted Odds Ratio 3.43, 95% CI 2.36-4.96). Additionally, a significantly decreased hazard was observed for both OS (adjusted hazard ratio [aHR] 0.45, 95% CI 0.25-0.80) and BCSS (aHR 0.46, 95% CI 0.24-0.86) with pertuzumab treatment. Findings were similar in the HER2-single subgroup. No significant benefit of pertuzumab was seen in other subtypes.

CONCLUSIONS

In patients with HER2-type or HER2-single-type tumors, pertuzumab significantly improved the pCR rate and decreased the risk of breast cancer mortality, which was not observed in other subtypes. BluePrint subtyping may be valuable in future studies to identify patients that are likely to be highly sensitive to HER2-targeting agents.

Microcalcification crystallography as a potential marker of DCIS recurrence

Ductal carcinoma in-situ (DCIS) accounts for 20-25% of all new breast cancer diagnoses. DCIS has an uncertain risk of progression to invasive breast cancer and a lack of predictive biomarkers may result in relatively high levels (~ 75%) of overtreatment. To identify unique prognostic biomarkers of invasive progression, crystallographic and chemical features of DCIS microcalcifications have been explored. Samples from patients with at least 5-years of follow up and no known recurrence (174 calcifications in 67 patients) or ipsilateral invasive breast cancer recurrence (179 microcalcifications in 57 patients) were studied. Significant differences were noted between the two groups including whitlockite relative mass, hydroxyapatite and whitlockite crystal maturity and, elementally, sodium to calcium ion ratio. A preliminary predictive model for DCIS to invasive cancer progression was developed from these parameters with an AUC of 0.797. These results provide insights into the differing DCIS tissue microenvironments, and how these impact microcalcification formation.

A living biobank of patient-derived ductal carcinoma in situ mouse-intraductal xenografts identifies risk factors for invasive progression

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer (IBC). Due to a lack of biomarkers able to distinguish high- from low-risk cases, DCIS is treated similar to early IBC even though the minority of untreated cases eventually become invasive. Here, we characterized 115 patient-derived mouse-intraductal (MIND) DCIS models reflecting the full spectrum of DCIS observed in patients. Utilizing the possibility to follow the natural progression of DCIS combined with omics and imaging data, we reveal multiple prognostic factors for high-risk DCIS including high grade, HER2 amplification, expansive 3D growth, and high burden of copy number aberrations. In addition, sequential transplantation of xenografts showed minimal phenotypic and genotypic changes over time, indicating that invasive behavior is an intrinsic phenotype of DCIS and supporting a multiclonal evolution model. Moreover, this study provides a collection of 19 distributable DCIS-MIND models spanning all molecular subtypes.

Homologous recombination deficiency derived from whole-genome sequencing predicts platinum response in triple-negative breast cancers

The high frequency of homologous recombination deficiency (HRD) is the main rationale of testing platinum-based chemotherapy in triple-negative breast cancer (TNBC), however, the existing methods to identify HRD are controversial and there is a medical need for predictive biomarkers. We assess the in vivo response to platinum agents in 55 patient-derived xenografts (PDX) of TNBC to identify determinants of response. The HRD status, determined from whole genome sequencing, is highly predictive of platinum response. BRCA1 promoter methylation is not associated with response, in part due to residual BRCA1 gene expression and homologous recombination proficiency in different tumours showing mono-allelic methylation. Finally, in 2 cisplatin sensitive tumours we identify mutations in XRCC3 and ORC1 genes that are functionally validated in vitro. In conclusion, our results demonstrate that the genomic HRD is predictive of platinum response in a large cohort of TNBC PDX and identify alterations in XRCC3 and ORC1 genes driving cisplatin response.

Abstract 125: Archival single cell sequencing reveals persistent subclones over years to decades of DCIS progression

Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer (IBC), yet the genomic progression to recurrent disease remains poorly understood. A main contributor to this gap in knowledge arises from technical challenges with genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. To address this challenge, we developed Arc-well, the first high-throughput method that can perform single cell DNA sequencing of thousands of cells from FFPE materials and frozen tissues. Using Arc-well, we profiled genomic copy number in 27,851 single cells from 26 archival FFPE tissues that were stored for 3-31 years. Analysis of genomic evolution in 10 patients with matched DCIS and recurrent cancers (DCIS or IBC) separated by 2-16 years showed that many primary DCIS lesions had already undergone whole-genome-doubling and had extensive clonal diversity, similar to the paired recurrence. The data from most patients (8/10) suggest an evolutionary bottleneck model of progression, in which a single subclone persisted during the progression to the recurrent disease, revealing copy number aberrations associated with invasion and recurrence.

Citation Format: Kaile Wang, Tapsi Kumar, Junke wang, Darlan Minussi, Emi Sei, Jianzhuo li, Tuan Tran, Aatish Thennavan, Min Hu, Anna Casasent, Zhenna Xiao, Shanshan Bai, Yuehui Zhao, Amado Zurita, Ana Aparicio, Brian Chapin, Jie ye, Jianjun Zhang, Don Gibbons, Andrew Futreal, Lorraine King, Jeffrey Marks, E. Shelley Hwang, Vandna Shah, Ellinor Sawyer, Petra Kristel, Jelle Wesseling, Esther H. Lips, Nicholas Navin. Archival single cell sequencing reveals persistent subclones over years to decades of DCIS progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 125.

Abstract F1-2: Clonal evolution of DCIS to invasion

Clonal evolution of DCIS to invasion

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive breast cancer (IBC). If not treated, at least 3 out of 4 women with DCIS will not develop IBC1-3. This implies many women with non-progressive, low-risk DCIS are likely to carry the burden of overtreatment. To solve this DCIS dilemma, two fundamental questions need to be answered. The first question is, how the subsequent IBC is related to the initial DCIS lesion. The second question is how to distinguish high- from low-risk DCIS at the time of diagnosis. This is essential to take well-informed DCIS management decisions, i.e., surgery, followed by radiotherapy in case of breast conserving treatment with or without subsequent endocrine treatment, or test whether active surveillance for low-risk DCIS is safe.

How is the subsequent IBC related to the initial DCIS?

The high genomic concordance in DNA aberrations between DCIS and IBC suggest that most driver mutations and CNA events are acquired at the earliest stages of DCIS initiation. It has therefore been assumed that most solid tumours arise from a single cell and that the probability of two independent tumours arising from the same tissue is low4-6. However, lineage tracing and genomic studies strongly suggest both direct and independent clonal lineages during the initiation of DCIS and evolution to IBC. In these processes, mammary stem cells have been implicated in DCIS initiation.

Role of mammary stem cells in DCIS initiation

Lineage tracing mouse model experiments have shown the fate of individual cells and lineages that acquire mutations before a tumour is established7-9. This is also relevant for DCIS initiation10,11, as different pools of MaSCs drive the growth and development of the ductal network and are considered the cell of origin for breast cancers9,10. The ductal trees remain quiescent until puberty, during which extension, branching and termination of terminal end buds (TEBs) leads to its expansion throughout the fat pad7,12,13. Any oncogenic mutation that occurs in a fetal MaSC will spread throughout the ductal network to a large part of the ductal tree, leading to sick lobes9. By contrast, oncogenic mutations acquired by a single MaSC during puberty spread to a smaller number of offspring located in small clusters in a part of the ductal network8,14.

Direct lineage models for DCIS progression

Direct lineage models postulate that DCIS has a single cell of origin that acquires mutations and progresses to IBC15-18. This is also supported by the high genomic concordance of CNAs and mutations in synchronous DCIS–IBC regions6,15,17,19-21 and the results of a recent large longitudinal study that profiled pure DCIS and recurrent IBC using multiple sequencing techniques, which estimated direct clonal lineages in approximately ~80% of patients18.

Two distinct direct lineage models have been proposed: the evolutionary bottleneck model and the multiclonal invasion model. In the evolutionary bottleneckmodel, a single clone (or a limited number of clones) with an invasive genotype is selected and breaks through the basement membrane to migrate into surrounding tissues15,16,22, while other clones are unable to escape the ducts21-28. The multiclonal invasion model posits that most or all subclones can escape the basement membrane, establishing invasive disease6,16,17,20. The multiclonal model has not been studied widely in pure DCIS and recurrent IBC samples.

Independent lineage model for DCIS progression

DCIS lesions and IBCs can arise from different initiating cells in the same breast independently5,20,29-32. An analysis of sequential DCIS–IBC pairs in a unique, large-scale, in-depth study of 95 matched pure DCIS and recurrent IBC showed that ~20% of the IBC recurrences were indeed clonally unrelated to the primary DCIS18, as is also supported by some mathematical model studies33.

The potential role of a field effect

IBC can develop in the same breast as an initial DCIS even after treatment, which could be explained by the presence of a field effect34-37. Alternatively, the sick lobe hypothesis proposes that a single lobe harbours first-hit mutations, acquired in utero or during early mammary development37-42. This could also explain the restriction of IBC to the ipsilateral side of the breast39,43,44. Germline mutations may also explain the emergence of independent lineages in DCIS and IBC patients, lowering the threshold for cancer development32,43-46.

Convergent evolution model of DCIS progression

A third model for the emergence of IBC from DCIS is convergent evolution, in which the same mutations and CNA are selected and expanded during tumour growth such that environmental factors fuel competition between distinct clones and push them towards a similar genotype. Ultimately, two independent clonal lineages from different ancestral cells then happen to share multiple genomic aberrations or driver mutations across regions47-49. Although independent lineages are considered uncommon (~20%) in ipsilateral recurrences, they occur at much higher frequencies in contralateral recurrences (&gt;80%), in which single-nucleotide polymorphism and comparative genomic hybridization microarrays show few (or no) genomic alterations shared in tumours from the contralateral breast cancer18,50,51.

How to distinguish high- from low-risk DCIS at the time of diagnosis?

The genomic and transcriptomic profile present at the time of DCIS diagnosis may contain crucial information on the risk of progression of DCIS to IBC. Thus far, it has been unclear whether prognostic gene expression markers can be used to separate indolent DCIS from potentially progressive DCIS. To this end, microarrays and RNA-seq have been applied for the comparison of bulk RNA from microdissected DCIS and IBC tissue. In synchronous DCIS–IBC, a limited number of transcriptional differences have been found and the few events discovered often varied extensively across different tumours52-56. Although these differences were strong, the added value of these studies is uncertain as they are often confounded by small sample size, lack of matched receptor status data, and low sample purity. Despite these limitations, these studies have implicated the epithelial-mesenchymal transition (EMT) and extracellular matrix (ECM) remodelling pathways as potentially relevant for the progression of DCIS to IBC55-62.

We studied two large DCIS cohorts: the Sloane cohort, a prospective breast screening cohort from the UK (median follow-up of 12.5 years), and a Dutch population-based cohort (NKI, median follow-up of 13 years). FFPE tissue specimens from patients with pure primary DCIS after breast-conserving surgery (BCS) +/- RT that did develop a subsequent ipsilateral event (DCIS or invasive) were considered as cases, whereas patients that did not develop any form of recurrence up to the last follow-up or death were considered as controls. We performed copy number analysis (CNA) and RNAseq analysis on 229 cases (149 IBC recurrences and 80 DCIS recurrences) and 344 controls.

We classified DCIS into the PAM50 subtypes using RNAseq data which revealed an enrichment of luminal A phenotype in DCIS that did not recur (P = 0.01, Fisher Exact test). No single copy number aberration was more common in cases compared to controls. RNAseq data did not reveal any genes significantly over/under expressed in cases versus controls after false discovery rate (FDR) correction. However, by limiting the analysis to samples that had not had RT and excluding pure DCIS recurrences we developed a penalized Cox model from RNAseq data. The model was trained on weighted samples (to correct for the biased sampling of the case control dataset) from the NKI series with double loop cross validation. Using this predicted hazard ratio, the samples were split into high, medium and low risk quantiles, with a recurrence risk of 20%, 9% and 2.5%, respectively at 5 years (p&lt;0.001, Wald test). The NKI-trained predictor was independently validated in the Sloane No RT cohort (p = 0.02, Wald test). GSEA analysis revealed proliferation hallmarks enriched in the recurrence predictor (FDR = 0.058). The NKI-RNAseq predictor was more predictive of invasive recurrence than PAM50, clinical features (Grade, Her2 and ER) and the 12-gene Oncotype DCIS score (p &lt; 0.001, permutation test using the Wald statistic) in both the NKI and Sloane series.

In the methylation analysis, 50 controls were compared with 35 cases. We could identify Variably Methylation Regions (VMRs) and Differentially Methylated Regions (DMRs) between cases and controls. Interestingly, VMRs were enriched in cell adhesion pathways

Conclusion

The recently acquired knowledge described above on how often the subsequent IBC is directly related to the initial DCIS and on molecular markers predicting the risk of DCIS progression is essential for accurate DCIS risk assessment. This is essential to aid accurate clinical decision making to personalize DCIS management in the near future.

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Citation Format: Jelle Wesseling. Clonal evolution of DCIS to invasion [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr F1-2.

Abstract P5-14-01: Transcriptomic insights into lobular breast cancer biology: a retrospective analysis of the MINDACT clinical trial

Background: Invasive lobular carcinoma (ILC) represents the second most common subtype of breast cancer after invasive breast cancer of no special type (NST). In this retrospective analysis of the MINDACT trial, we aimed at identifying/refining the transcriptomic differences between: 1) estrogen receptor positive/HER2-negative (ER+/HER2-) ILC versus ER+/HER2- NST, 2) classic and non-classic ER+/HER2- ILC, and, 3) recurring and non-recurring ER+/HER2- ILC in the subgroup of patients with a low clinical and low genomic (cL/gL) risk (as defined by a modified version of Adjuvant Online! and the 70-gene signature). Patients and methods: Central pathology review was performed for histological subtype, grade and Ki67 (G.V.) for 5929/6693 (88.6%) of the patients included in the MINDACT trial (NCT00433589). Analysis of transcriptomic data adjusted for age and grade was performed using the R/Bioconductor package ‘limma’ to identify differentially expressed genes (DEGs). DEGs having absolute log-fold change (logFC)≥ 0.2 and FDR-adjusted p-value (q-value) &lt; 0.05 were considered. Gene set enrichment analyses (GSEA) of MSigDB hallmark gene sets were performed. Adjusted Cox regression models were used to evaluate the association of these hallmarks with disease free survival (DFS) and distant recurrence free survival (DRFS). Results: After central pathological review, 464 patients with ER+/HER2- ILC and 3798 patients with ER+/HER2- NST were identified. Patients with ILC were significantly older at diagnosis, had larger tumors, less axillary nodal involvement, more grade 2 tumors than patients with NST. At the transcriptomic level, we observed a high number of DEGs between these 2 subgroups, confirming their distinct phenotype. CDH1, the gene coding for E-cadherin, was as expected the most highly overexpressed gene in NST versus ILC. We further observed an increased expression of leptin (LEP), leptin receptor (LEPR), lipoprotein lipase (LPL), and the fatty acid transporter CD36 in ILC. This could suggest that ILC relied on increased lipid uptake thanks to the increased contact of ILC tumor cells with the adipocytes. IGF1 was also overexpressed in ILC versus NST, as a potential consequence of high LEP and high LEPR expression. Differences were also evident with regard to the extracellular matrix (ECM), with many collagens, matrix metalloproteinases (MMPs) and other key enzymes (e.g. LOXL1) being differentially expressed. We confirmed a decreased ER-signaling and increased PI3K/Akt signaling in ILC versus NST. Out of the 464 ER+/HER2- ILC tumors, 253 (55%) were classic ILC and 211 (45%) non-classic ILC. There were more grade 3 tumors, more highly proliferative tumors and more nodal involvement in patients with non-classic versus classic ILC. At the transcriptomic level, differences were subtler than the differences seen above. Still, a significant enrichment of the hallmarks related to cell cycle in the non-classic ILC, and of the hallmarks related to epithelial-to-mesenchymal transition, hypoxia, adipogenesis and IL6/JAK/STAT3 signaling in classic ILC was observed. Finally, 216/464 patients with ER+/HER2- ILC (47%) were assigned to the cL/gL risk group and did not receive chemotherapy. 28/216 of these patients (13%) relapsed (DFS, median FU: 8.7 years). Enrichment of hallmarks related to apoptosis, inflammatory response, hypoxia and oncogenic signaling (PI3K/Akt, Ras, c-Myc) was associated with worse survival. Conclusion: This represents, to the best of our knowledge, the largest set of gene expression data for patients with ILC, issued from a clinical trial where histology was reviewed centrally. These results could be used to personalize treatment for patients with ILC. This project is funded by the Breast Cancer Research Foundation.

Citation Format: Christine Desmedt, Ha-Linh Nguyen, François Richard, Sabine Linn, Otto Metzger, Coralie Poncet, Jelle Wesseling, Florentine Hilbers, Kim Aalders, Mauro Delorenzi, Suzette Delaloge, Jean-Yves Pierga, Etienne Brain, Suzan Vrijaldenhoven, Peter A Neijenhuis, Karen Van Baelen, Marion Maetens, Emiel Rutgers, Martine Piccart, Laura Van ’t Veer, Giuseppe Viale, Fatima Cardoso. Transcriptomic insights into lobular breast cancer biology: a retrospective analysis of the MINDACT clinical trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-14-01.

Abstract P4-02-22: Breast microcalcification chemistry predicts DCIS prognosis

Introduction: Microcalcifications are a common feature in mammographic detection of ductal carcinoma in situ (DCIS), and occur in &gt;80% of cases. Known to be present as type I (calcium oxalate-CaO) and type II (carbonated calcium hydroxyapatite-CHAP) microcalcifications, their association with DCIS and their role in the progression of DCIS to invasive breast cancer (IBC) remains unexplored. In an effort to understand the factors involved in DCIS prognosis, it is hypothesized that changes in the chemical composition of calcifications, in tandem with molecular changes in the surrounding soft tissue, will define patients with DCIS who will progress to develop IBC from those who remain with a stable DCIS phenotype. To this end, a novel label-free approach of hyperspectral imaging using mid-infrared (mid-IR) and Raman spectroscopy was used to probe calcification chemistry and molecular composition of the surrounding ductal and stromal soft tissue. The main aim of the work is to identify biomarkers for DCIS prognosis, based on chemical and molecular compositional changes of calcifications and the surrounding soft tissue. It is anticipated that the spectral biomarkers will provide patients and clinicians an informed risk assessment whether to undertake treatment for DCIS or to be placed under active surveillance. Methods: Tissue samples from 422 patient have been obtained and include (i) ‘pure DCIS’ (DCIS without recurrence) (n=193), (ii) ‘DCIS with invasive recurrence’ (DCIS from patients who subsequently were known to develop invasive disease) (n=123), (iii) ‘DCIS plus contemporaneous invasive cancer’ (n=44) and ‘benign’ (n=62) samples. Serial tissue sections were measured using mid-IR and Raman hyperspectral imaging approaches targeting the same calcification and soft tissue regions from specific DCIS ducts. Hyperspectral imaging data was initially pre-processed to digitally remove paraffin and unintended spectral interferences. The pre-processed data was subjected to cluster analysis followed by unsupervised and supervised machine learning classification models to identify spectral features associated with DCIS and its progression to IBC. Results: Cluster analysis based segmentation of hyperspectral images revealed histopathological features including calcifications, epithelium, necrotic areas, connective tissue and stroma. Spectra were extracted from each of the histopathological features using image coordinates, and biomodelling analysis was performed. Initial analysis of 314 calcification images from 170 patients with (i) ‘pure DCIS’ (n=118) and (ii) ‘DCIS with invasive recurrence’ (n=52) showed an area under the receiver operating characteristic (AUROC) mean value of 85% in distinguishing pure DCIS from DCIS that later recurred as IBC. The calcification features appeared to indicate pathology specific changes in phosphate and carbonate content as well as changes in magnesium whitlockite content. Similar analysis of the surrounding soft tissue spectral features showed an AUROC mean value of 85% (necrotic regions surrounding calcifications) and 76% (epithelium) respectively. The epithelial features showed changes in protein secondary structure and content, which together with the calcification changes indicate structural remodelling in DCIS that progresses to IBC, from those that do not. Perspectives: In the ongoing analyses of imaging data from 422 patients, it is anticipated that molecular/structural features from calcification and soft tissue imaging data will provide important cues in understanding DCIS prognosis and could be a promising way forward in determining management of DCIS risk and treatment underpinned by the identification of specific discriminatory spectral markers. Acknowledgments: This work was supported by Cancer Research UK and by KWF Kankerbestrijding (ref. C38317/A24043).

Citation Format: Jayakrupakar Nallala, Doriana Calabrese, Sarah Gosling, Esther Lips, Rachel Factor, Allison Hall, Sarah E. Pinder, Ihssane Bouybayoune, Lorraine King, Jeffrey Marks, Thomas Lynch, Donna Pinto, Jelle Wesseling, E Shelley Hwang, Keith Rogers, Nick Stone. Breast microcalcification chemistry predicts DCIS prognosis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-02-22.

Abstract PD18-06: Image-guided optimization of neoadjuvant chemotherapy duration in stage II and III HER2-positive breast cancer: radiologic and pathologic complete response (pCR) rates in the multicenter phase 2 TRAIN-3 study (BOOG 2018-01)

Background pCR rates in stage II – III HER2-positive breast cancer have greatly improved since the addition of HER2 targeted agents to neoadjuvant chemotherapy and are associated with excellent long-term survival. While longer treatment regimens increase pCR rate, early complete responses are also common. We evaluated an image-guided approach to tailor chemotherapy duration based on the identification of early complete responders.

Methods 45 hospitals across the Netherlands participated in the phase 2 TRAIN-3 trial. Patients received neoadjuvant systemic treatment consisting of paclitaxel, trastuzumab, carboplatin and pertuzumab (PTC-Ptz). Response to treatment was monitored every three cycles and patients were referred for surgery in case of a radiologic complete response (rCR) or after a maximum of 9 cycles. RCR was defined as the absence of pathological enhancement on MRI breast plus negative vacuum assisted core biopsies in case of hormone-receptor positive (HR+) tumors. In addition, negative fine needle aspiration or lymph node biopsy was required in patients with nodal involvement at baseline. The primary endpoint was 3-year event-free survival (EFS). Here, we report locally assessed rCR and pCR rates after 3, 6 and 9 cycles, the negative predictive value of rCR assessment and the incidence of adverse events (AEs). Analyses are stratified by HR-status.

Results We included 467 patients between April 2019 and May 2021. Median age was 51 years, 69% had stage II disease and 232 had HR+ tumors. 33.6% of HR- patients and 15.5% of HR+ patients achieved pCR after 3 cycles of PTC-Ptz (see table). The NPV was higher in HR- patients and independent of the number of cycles. AE evaluation is currently ongoing.

Conclusion Three cycles of PTC-Ptz induce an early pCR in one in three HR- and one in six HR+ tumors in patients with stage II-III HER2+ breast cancer. Dynamic contrast enhanced MRI-based response evaluation identifies these patients with ±87% certainty in HR- disease and ±58% in HR+ disease. Continuation of PTC-Ptz after 6 cycles further improves pCR rates and can be considered to reduce the need for adjuvant T-DM1. Efficacy and safety of this image-guided approach to tailor treatment duration need to be confirmed with follow-up in EFS and OS analyses.

Table 1: Cumulative rCR & pCR according to HR-status *Including patients who underwent surgery for other reasons than rCR

Citation Format: Anna van der Voort, Mette S. van Ramshorst, Rob Kessels, Ingrid A. Mandjes, Inge Kemper, Mariëtte J. Agterof, Wim A. van der Steeg, Joan B. Heijns, Marlies L. van Bekkum, Ester J. Siemerink, Philomeen M. Kuijer, Astrid Scholten, Jelle Wesseling, Marie-Jeanne T.F.D. Vrancken Peeters, Ritse M. Mann, Gabe S. Sonke. Image-guided optimization of neoadjuvant chemotherapy duration in stage II and III HER2-positive breast cancer: radiologic and pathologic complete response (pCR) rates in the multicenter phase 2 TRAIN-3 study (BOOG 2018-01) [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD18-06.

Abstract P6-05-11: Active surveillance versus conventional treatment in low-risk DCIS; women’s preferences in the LORD trial

Background: Ductal carcinoma in situ (DCIS) is a potential precursor to breast cancer. Its incidence has increased multifold with the introduction of breast cancer screening and makes for 20% of all malignant breast lesions in women. DCIS has the potential to progress into invasive breast cancer. However, the majority of DCIS lesions are indolent and will never progress during the patient’s lifetime. Consequently, there is a growing concern of overdiagnosis and overtreatment for women with DCIS. The LORD trial is a non-randomized, patient preference trial comparing active surveillance to conventional treatment (i.e., breast conserving surgery with or without radiotherapy or mastectomy). The primary outcome of this trial is the percentage of women without an occurrence of ipsilateral invasive breast cancer after 10 years of follow up. Within the patient preference design, women are free to opt for either treatment arm. In addition to active surveillance of the DCIS, quality of life (QOL) of women included in the LORD trial is also actively monitored. The aims of this study were to: a) describe the distribution of participants within the treatment arms, b) identify women’s motives to opt for their preferred treatment arm, and c) assess factors associated with a preference for either treatment arm. Methods: Data from the baseline patient QOL questionnaire was collected. This questionnaire was completed after the women’s diagnosis and first consultation with their physician. Descriptive statistics were used to assess the distribution in both treatment arms. Thematic analyses were used to describe self-reported reasons for treatment selection derived from the open-ended question about treatment preference. Multivariable logistic regression analyses were used to assess associations between the patient characteristics and their preferred treatment arm. Results: In total 384 women completed the baseline questionnaire, of which 376 entered their final treatment decision. Of these women, 287 (76%) opted for active surveillance and 89 (24%) for conventional treatment. Most frequently cited reason for opting for active surveillance was that treatment was not yet necessary (55%). Also, patients’ reasons for preferring active surveillance alluded to a high level of trust in the active surveillance plan (24%) and that disease progression could be picked up and treated in a timely manner (14%). Furthermore, 11% of patients cited the advice of their healthcare professional as a reason for opting for active surveillance and 8% cited reasons relating to altruism. Most reported reasons for opting for the conventional treatment arm were avoiding unnecessary risks (26%), avoiding cancer worry (18%), the notion that what doesn’t belong, should be removed from the body (18%) and a need for closure (13%). In multivariable logistic regression analyses, high level of education (OR 2.17; 95%CI 1.09-4.38) and higher knowledge score (OR 1.8; 95%CI 1.07-3.02) were associated with a preference for conventional treatment. Furthermore, women opting for active surveillance more often reported the decision to be a shared decision between them and their healthcare professional (OR 2.30; 95%CI 1.18-4.47) compared to women who chose conventional treatment, who more often reported decision-making to be patient-driven. Age and tolerance of uncertainty were not significantly associated with treatment preference. Conclusion: The LORD trial is the first to actively offer women with low-risk DCIS a choice between conventional treatment and active surveillance. Within this trial, most women opt for active surveillance, even though clinical guidelines still recommend treatment for all women with DCIS. Women with low-risk DCIS report high levels of trust in their physicians and the safety of active surveillance. Their preferences also highlight the necessity to proof that de-escalating treatment of low-risk DCIS is safe.

Citation Format: Renée S. Schmitz, Ellen G. Engelhardt, Miranda A. Gerritsma, Carine M. Sondermeijer, Sena Alaeikhanehshir, Ellen Verschuur, Marja van Oirsouw, Julia Houtzager, Rosalie Griffioen, Nina Bijker, Ritse M. Mann, Frederieke van Duijnhoven, Jelle Wesseling, Eveline Bleiker. Active surveillance versus conventional treatment in low-risk DCIS; women’s preferences in the LORD trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-05-11.

Tumour-educated platelets for breast cancer detection: biological and technical insights

BACKGROUND

Studies have shown that blood platelets contain tumour-specific mRNA profiles tumour-educated platelets (TEPs). Here, we aim to train a TEP-based breast cancer detection classifier.

METHODS

Platelet mRNA was sequenced from 266 women with stage I-IV breast cancer and 212 female controls from 6 hospitals. A particle swarm optimised support vector machine (PSO-SVM) and an elastic net-based classifier (EN) were trained on 71% of the study population. Classifier performance was evaluated in the remainder (29%) of the population, followed by validation in an independent set (37 cases and 36 controls). Potential confounding was assessed in post hoc analyses.

RESULTS

Both classifiers reached an area under the curve (AUC) of 0.85 upon internal validation. Reproducibility in the independent validation set was poor with an AUC of 0.55 and 0.54 for the PSO-SVM and EN classifier, respectively. Post hoc analyses indicated that 19% of the variance in gene expression was associated with hospital. Genes related to platelet activity were differentially expressed between hospitals.

CONCLUSIONS

We could not validate two TEP-based breast cancer classifiers in an independent validation cohort. The TEP protocol is sensitive to within-protocol variation and revision might be necessary before TEPs can be reconsidered for breast cancer detection.

Abstract PR003: Pioneering genetic rat models of Ductal Carcinoma in situ (DCIS)

DCIS has been virtually unknown before the introduction of breast cancer screening programs in the 1980s. Since then, its incidence has been rising steeply and it now accounts for about 25% of all newly diagnosed ‘breast cancer’ cases. Despite the increase in occurrence, the molecular underpinnings regulating DCIS initiation and progression remain elusive. In addition, almost all DCIS cases are hormone dependent, a characteristic which remains one of the biggest challenges to recapitulate in breast cancer research. We could successfully establish models for DCIS as well as estrogen receptor positive disease subtypes by somatically engineering the rat mammary gland via intraductal injection of lentiviral vectors encoding for the most commonly mutated genes (Ccnd1, Myc, Pik3ca and p53) in (pre-) breast cancer. Models with one perturbed gene remained mostly mammary tumor-free after an observation period of 18 months. However, when perturbed in two loci, animals showed mammary lesion formation within 5 and after up to 40 weeks. Histopathological analysis of these lesions characterized a broad spectrum of tumor types including ductal and lobular carcinomas, with both in situ and invasive phenotypes. Among these tumor types, DCIS lesions as well as invasive ductal carcinoma showed estrogen receptor positivity after immunohistochemical staining. Two distinct growth patterns were observed: a flat growing tumor, shaped by, and replacing the host rat mammary duct, and a round growing lesion, disregarding ductal structures. Interestingly, the flat growing tumor pattern evolved mostly in models expressing luminal drivers (Ccnd1 and Pik3ca) and strongly correlated with in situ growth. To increase luminal subtypes and to narrow down the broad tumor spectrum observed in these models, we generated a luminal cell type-specific promoter expressing our genes of interest. Pathological analysis of the arisen tumors indeed revealed a more homogeneous tumor subtype for all models, with an average tumor latency of 28 to 40 weeks. These genetically engineered models for DCIS and estrogen receptor positive breast cancer may aid in an improved treatment stratification by distinguishment between indolent and aggressive DCIS, a persisting challenge as of today. Additionally, these models broaden the scope of available hormone dependent breast cancer models, benefitting the search for novel treatment regiments for patients suffering from this breast cancer subtype.

Citation Format: Catrin Lutz, Madelon Badoux, Timo Eijkman, Bim de Klein, Ji-Ying Song, Linda Henneman, Colinda Scheele, Jelle Wesseling, Jos Jonkers. Pioneering genetic rat models of Ductal Carcinoma in situ (DCIS) [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr PR003.

Abstract IA012: Mammary epithelial architecture modulates field cancerization

The architecture of the human breast undergoes extensive remodeling throughout puberty, the menstrual cycle, pregnancy and involution with a risk of accumulating genetic alterations and tissue changes. Cells that have acquired mutations in driver genes are found to be abundant in tissues of healthy individuals, but they rarely develop into tumors. Yet, the underlying protection mechanisms that prevent tumor formation are largely unknown. Here, we utilized tissue clearing and imaged 15 normal human breasts and DCIS resections with cellular resolution to unravel the 3D architecture of thousands of mammary ducts. Surprisingly, our analysis revealed that disease-free breasts carry a high burden of microscopic tissue lesions. Distinct trees from the same breast differ in the kind and frequency of lesions, which coevolve scattered along the ductal routes. Interestingly, combining tissue clearing of FFPE archival material with spatial CNV-seq reveals that in half of the cases disease-free ductal segments neighboring DCIS lesions contain molecular alterations. To resolve the mechanisms that restrain and permit mutation spread, we compare the clonal fate behavior of cells that acquire oncogenic mutations with those bearing neutral mutations in the mouse mammary gland epithelium. From the quantitative analysis of the clonal dynamics, we find that local tissue remodeling during the estrous cycle leads to the stochastic elimination of the majority of mutant clones, while massively accelerating the expansion of a minority of clones that, by chance, survive. Thereby, oncogenic mutations can be spread along entire ducts before signs of transformation become visible. Together this data provides quantitative understanding of the earliest stages of epithelial evolution preceding disease.

Citation Format: Hendrik Messal, Colinda Scheele, Esther Lips, Catrin Lutz, Stefan Hutten, Petra Kristel, Carmen Vlahu, Jos Jonkers, Jelle Wesseling, Jacco van Rheenen. Mammary epithelial architecture modulates field cancerization [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA012.

Abstract PR002: Genomic predictor can discriminate between high- and low-risk DCIS

Introduction: Ductal carcinoma in situ (DCIS) is considered a non-obligate precursor of invasive ductal carcinoma. With the aim of preventing a subsequent invasive cancer, all DCIS lesions are currently treated with surgical excision often supplemented with radiotherapy (RT). To prevent DCIS over- or undertreatment, a reliable marker of DCIS invasiveness risk is urgently needed. Methods: We studied two large DCIS cohorts: the Sloane cohort, a prospective breast screening cohort from the UK (median follow-up of 11 years), and a Dutch population-based cohort (NKI, median follow-up of 13 years). FFPE tissue specimens from patients with pure primary DCIS after breast-conserving surgery (BCS) +/- RT that did develop a subsequent ipsilateral event (DCIS or invasive) were considered as cases, whereas patients that did not develop any form of recurrence up to the last follow-up or death were considered as controls. We performed copy number analysis (CNA) and RNAseq analysis on 229 cases (80 DCIS only recurrences) and 344 controls. Results: DCIS was classified into the PAM50 subtypes using RNAseq data which revealed an enrichment of luminal A phenotype in DCIS that did not recur (P = 0.01, Fisher Exact test). No single copy number aberration was more common in cases compared to controls. RNAseq data did not reveal any genes significantly over/under-expressed in cases versus controls after FDR correction. However, by limiting the analysis to samples that had not had RT and excluding pure DCIS recurrences, we could develop a penalized Cox model from RNAseq data. The model was trained on weighted samples (to correct for the biased sampling of the case-control dataset) from the NKI series with double loop cross-validation. The genes were selected using the Elastic net framework of penalization. Using this predicted hazard ratio, the samples were split into high, medium, and low-risk quantiles, with a recurrence risk of 23%, 7% and 2%, respectively at 5 years (p = 10-10, Wald test). The NKI-trained predictor was independently validated in the Sloane No RT no DCIS recurrence cohort (p = 0.02, Wald test). GSEA analysis revealed proliferation hallmarks enriched in the recurrence predictor (FDR = 0.058). The RNAseq predictor was more predictive of recurrence than PAM50, clinical features (Grade, Her2 and ER) and the 12-gene Oncotype DCIS score (p &lt; 0.001, permutation test using the Wald statistic) in both the NKI and Sloane series. Conclusion: Genomic profiling of two independent series of DCIS with outcome data did not reveal any clear associations with recurrence until analysis was limited to a set of samples who had not had radiotherapy and DCIS recurrences were excluded. We then identified an RNAseq-based classifier that could differentiate primary DCIS in low-, medium-, and high-risk groups, and validated it in an independent cohort. This classifier, if validated in other datasets, will allow us to identify women who do not need intensive treatment for their DCIS.

Citation Format: Maria Roman Escorza, Michael Sheinman, Tycho Bismeijer, Ahmed A. Ahmed, Vandna Shah, Jeffrey R. Marks, Lorraine M. King, Anargyros Megalios, Lindy L. Visser, Marlous Hoogstrat, Helen R. Davies, Tapsi Kumar, Deborah Collyar, Hilary Stobart, Sarah Pinder, Nicholas N. Navin, Andrew Futreal, Serena Nik-Zainal, E. Shelley Hwang, Esther H. Lips, Alastair Thompson, Lodewyk F.A. Wessels, Jelle Wesseling, Elinor J. Sawyer. Genomic predictor can discriminate between high- and low-risk DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr PR002.

Learning to distinguish progressive and non-progressive ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) is a non-invasive breast neoplasia that accounts for 25% of all screen-detected breast cancers diagnosed annually. Neoplastic cells in DCIS are confined to the ductal system of the breast, although they can escape and progress to invasive breast cancer in a subset of patients. A key concern of DCIS is overtreatment, as most patients screened for DCIS and in whom DCIS is diagnosed will not go on to exhibit symptoms or die of breast cancer, even if left untreated. However, differentiating low-risk, indolent DCIS from potentially progressive DCIS remains challenging. In this Review, we summarize our current knowledge of DCIS and explore open questions about the basic biology of DCIS, including those regarding how genomic events in neoplastic cells and the surrounding microenvironment contribute to the progression of DCIS to invasive breast cancer. Further, we discuss what information will be needed to prevent overtreatment of indolent DCIS lesions without compromising adequate treatment for high-risk patients.

Abstract PR006: A living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts identifies multiple risk factors of invasive progression

Ductal Carcinoma in Situ (DCIS) is a non-invasive non-obligate precursor of invasive breast cancer (IBC). DCIS is usually treated by surgery combined with radiotherapy, which can have a large impact on the life of patients. However, many of these DCIS lesions would never progress into IBC. To reduce the overtreatment of DCIS, but assure proper treatment for high risk DCIS, it is crucial to understand the biology underlying DCIS. To study the biology of DCIS we established Mouse INtraDuctal (MIND) patient-derived xenograft (PDX) models by intraductally injecting patient DCIS material into the mammary ducts of female immunocompromised mice. We engrafted 130 samples, which have been incubated in vivo for a period of 12 months. We obtain a take rate of 88% with 46% of our models showing invasive progression. Histology and molecular subtyping by PAM50 classification are well preserved in the MIND models compared to the primary counterpart, ensuring that our MIND models represent the patient disease well. For 102 primary samples we obtained RNAseq profiles as well as for 64 matched MIND-PDX models. In addition whole exome-/panel sequencing data is generated from the same primary DCIS samples together with 12 matched MIND-PDX WES profiles as well as 60 matched Copy Number Variation (CNV) MIND-PDX profiles. Together these data revealed multiple biomarkers related to invasive progression, including factors such as high grade, solid growth, a high copy number aberrations burden, HER2, PTK6 & MYC amplifications and a high Ki67. On top of this we used whole mount imaging of the injected mammary glands extracted from our MIND-PDX models, showing two distinct growth patterns correlated with invasion. And as this is all done in the context of the PRECISION consortium this allows us to confirm and validate our findings in larger sequencing and imaging efforts of human samples. We have also successfully passaged 42 MIND-PDX models which showed minimal changes in pheno- and genotype over time indicating invasive behavior is an intrinsic phenotype of DCIS with minimal evolution, supporting a multiclonal evolution model. Moreover, this provided a collection of 19 stable sequentially transplantable DCIS MIND models including Luminal A, Luminal B, ER+/HER2+ and ER-/HER2+ models. Ultimately these models can be used to validate the biomarkers found to be related to invasive progression, as an example we proved the direct role of HER2 overexpression in invasive progression by inhibiting the HER2 receptor or by overexpressing HER2. In conclusion all this data together enabled us to create a well-characterized biobank of DCIS models with the unique opportunity to follow the natural progression, sequentially transplant 42 models, find genomic and transcriptomic profiles related to high risk DCIS and manipulate gene expression to validate the role of genes in DCIS progression.

Citation Format: Stefan J. Hutten, Roebi de Bruijn, Catrin Lutz, Madelon Badoux, Timo Eijkman, Xue Chao, Marta Ciwinska, Andrea Herencia-Ropero, Petra Kristel, Lennart Mulder, Joyce Sanders, Mathilde Almekinders, Alba Llop-Gueverra, Helen R. Davies, Fariba Behbod, Serena Nik-Zainal, Violeta Serra, Jacco van Rheenen, Esther H. Lips, Lodewyk F.A. Wessels, Jelle Wesseling, Colinda Scheele, Jos Jonkers. A living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts identifies multiple risk factors of invasive progression [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr PR006.

Abstract A016: Identification of methylated regions in ductal carcinoma in situ and association with disease progression

Background: The advent of breast screening has led to a 4-fold increase in the diagnosis of ductal carcinoma in situ (DCIS). Studies following the clinical outcomes of patients show variable progression free survival rates, with only up to 35% of patients progressing to invasive disease without treatment. This highlights the need to find a biomarker to accurately predict which DCIS lesions will recur as invasive tumors. Epigenetics changes are events which occur early in tumorigenesis, this makes DNA methylation a potential biomarker of DCIS progression. However, a lack of DCIS methylation profiling with long term follow-up data exists. This study investigates genome-wide methylation profiles in women with primary DCIS and associates the data with their overall recurrence free survival. Methods: DCIS was macrodissected from 89 formalin-fixed paraffin embedded (FFPE) to extract tumor enriched DNA from patients with DCIS and long term follow up. 39 women had developed an ipsilateral invasive recurrence (classified as cases) and 50 had no evidence of recurrent disease (classified as controls). Genome wide methylation was assessed using the human methylation EPIC BeadChip which, interrogates over 850,000 methylation sites. Data was assessed for quality both at the sample and probe level by the wateRmelon. Further analysis was performed in ChAMP to identify differentially methylated regions (DMR) and by DMRcate packages in R to identify variably methylated regions (VMR). Genes annotated in the most significant VMRs were analysed through Metascape, a web-based tool to perform functional gene set enrichment analysis (GSEA). A cox proportional hazards model was used to calculate the association between the methylation of the VMRs and recurrence free survival. This model was adjusted for DCIS receptor status and grade. Results: 59 samples passed data quality assessment (35 controls and 24 cases). 10 differentially methylated regions were identified. The most significant of which, was a hypomethylated region on chromosome 4, containing CDKL2 (p = 0.001), known to promote the epithelial-mesenchymal transition in breast cancer progression. 5813 VMRs were identified across the genome, (P-value range between 0 and 10-321). 82% of the VMRs aligned to the body of the gene or the surrounding regulatory features. GSEA revealed that VMRs were predominantly involved in pathways involved in cell adhesion (GO:0007156) Assessment of the significant VMRs by COX proportional hazards model showed that a VMR on chromosome 6p was associated with the development of invasive disease after adjusting for oestrogen receptor, human epidermal growth factor 2 status and grade (p=0.001). Conclusions: This preliminary study shows altered sites of methylation could be observed across the genome, in DCIS. The function of the VMRs is currently being investigated to understand how methylation in this region predisposes to invasive recurrence of DCIS. Correlation of methylation status and RNA expression data will be used to understand the biological relevance.

Citation Format: Vandna Shah, Maria Roman-Escorza, Karen Clements Clements, Lennart Mulder, Esther H. Lips, Jelle Wesseling, Sarah Pinder, Alastair M. Thompson, Elinor J. Sawyer. Identification of methylated regions in ductal carcinoma in situ and association with disease progression [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr A016.

Abstract IA013: A single-cell and spatial investigation of tumor and TME for DCIS

Ductal carcinoma in situ (DCIS) is early-stage non-malignant breast cancer that tumor cells are confined to the lumens of ducts. Over 50,000 DCIS patients are diagnosed each year in the United States, however, less than half of DCIS will develop into invasive breast cancer (IBC), suggesting a risk of overtreatment for some DCIS patients. A comprehensive investigation of the molecular mechanisms of DCIS initiation and progression is urgently needed that can facilitate us stratifying the risk of DCIS invasion and design better intervention approaches. In this study, we conducted single-cell RNA-seq and spatial transcriptomics (ST) on DCIS and IBC samples (most estrogen receptor positive). We first inferred copy number aberrations (CNA) in these samples and found that DCIS and IBC shared the most copy number events while only marginal differences were identified. Tumor CNA subclones colocalized in different ductal regions from the ST data. Further, we applied a sample-wise non-negative matrix factorization (NMF) to identify robust gene expression metaprograms across tumor samples. On the ST data, we found these metaprograms also displayed distinct spatial patterns. For non-tumor cells in the TME, we sub-clustering them into cell states and identified that some cell states showed a gradual change along breast cancer initiation and progression. To recapitulate the tumor ecosystems, we also conducted an ecotype analysis in DCIS samples and identified that some ecotypes showed an increasing/decreasing trend in IBC patients. Further, tumor and TME ecotypes also showed spatially colocalizations based on our ST data. In summary, these results demonstrated that genomic signatures could hardly predict the DCIS progression while tumor metaprograms and TME ecotypes might serve as a potential risk stratification approach for DCIS patients.

Citation Format: Runmin Wei, Siyuan He, Shanshan Bai, Emi Sei, Min Hu, Chandandeep Nagi, Brian Menegaz, Huma Javaid, Jelle Wesseling, Andrew Futreal, Alastair Thompson, Savitri Krishnamurthy, Nicholas Navin. A single-cell and spatial investigation of tumor and TME for DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA013.

Dynamic Changes in the NK-, Neutrophil-, and B-cell Immunophenotypes Relevant in High Metastatic Risk Post Neoadjuvant Chemotherapy-Resistant Early Breast Cancers

PURPOSE

To identify potential immune targets in post-neoadjuvant chemotherapy (NAC)-resistant triple-negative breast cancer (TNBC) and ER+HER2- breast cancer disease.

EXPERIMENTAL DESIGN

Following pathology review, 153 patients were identified as having residual cancer burden (RCB) II/III disease (TNBC n = 80; ER+HER2-n = 73). Baseline pre-NAC samples were available for evaluation for 32 of 80 TNBC and 36 of 73 ER+HER2- cases. Bright-field hematoxylin and eosin assessment allowed for tumor-infiltrating lymphocyte (TIL) evaluation in all cases. Multiplexed immunofluorescence was used to identify the abundance and distribution of immune cell subsets. Levels of checkpoints including PD-1/PD-L1 expression were also quantified. Findings were then validated using expression profiling of cancer and immune-related genes. Cytometry by time-of-flight characterized the dynamic changes in circulating immune cells with NAC.

RESULTS

RCB II/III TNBC and ER+HER2- breast cancer were immunologically "cold" at baseline and end of NAC. Although the distribution of immune cell subsets across subtypes was similar, the mRNA expression profiles were both subtype- and chemotherapy-specific. TNBC RCB II/III disease was enriched with genes related to neutrophil degranulation, and displayed strong interplay across immune and cancer pathways. We observed similarities in the dynamic changes in B-cell biology following NAC irrespective of subtype. However, NAC induced changes in the local and circulating tumor immune microenvironment (TIME) that varied by subtype and response. Specifically, in TNBC residual disease, we observed downregulation of stimulatory (CD40/OX40L) and inhibitory (PD-L1/PD-1) receptor expression and an increase in NK cell populations (especially non-cytolytic, exhausted CD56dimCD16-) within both the local TIME and peripheral white cell populations.

CONCLUSIONS

This study identifies several potential immunologic pathways in residual disease, which may be targeted to benefit high-risk patients.

Efficacy of neoadjuvant treatment with or without pertuzumab in patients with stage II and III HER2-positive breast cancer: a nationwide cohort analysis of pathologic response and 5-year survival

Background

Methods

Results

Conclusion

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The benefit of adding pertuzumab to the (neo)adjuvant treatment of lymph node negative and HR+/HER2+ patients remains unclear.

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Pertuzumab increases pCR rate from 41% to 65% in stage II-III HER2+ breast cancer.

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5-year BCSS is 95% and 98% in patients treated without and with pertuzumab, respectively.

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Patients <50 years benefit most from the addition of pertuzumab.

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Survival benefit of pertuzumab is more evident in patients with higher stage, but independent of HR-status.

De-escalation of radiotherapy after primary chemotherapy in cT1-2N1 breast cancer (RAPCHEM; BOOG 2010-03): 5-year follow-up results of a Dutch, prospective, registry study

BACKGROUND

Primary chemotherapy in breast cancer poses a dilemma with regard to adjuvant locoregional radiotherapy, as guidelines for locoregional radiotherapy were originally based on pathology results of primary surgery. We aimed to evaluate the oncological safety of de-escalated locoregional radiotherapy in patients with cT1-2N1 breast cancer treated with primary chemotherapy, according to a predefined, consensus-based study guideline.

METHODS

In this prospective registry study (RAPCHEM, BOOG 2010-03), patients referred to one of 17 participating radiation oncology centres in the Netherlands between Jan 1, 2011, and Jan 1, 2015, with cT1-2N1 breast cancer (one to three suspicious nodes on imaging before primary chemotherapy, of which at least one had been pathologically confirmed), and who were treated with primary chemotherapy and surgery of the breast and axilla were included in the study. The study guideline comprised three risk groups for locoregional recurrence, with corresponding locoregional radiotherapy recommendations: no chest wall radiotherapy and no regional radiotherapy in the low-risk group, only local radiotherapy in the intermediate-risk group, and locoregional radiotherapy in the high-risk group. Radiotherapy consisted of a biologically equivalent dose of 25 fractions of 2 Gy, with or without a boost. During the study period, the generally applied radiotherapy technique in the Netherlands was forward-planned or inverse-planned intensity modulated radiotherapy. 5-year follow-up was assessed, taking into account adherence to the study guideline, with locoregional recurrence rate as primary endpoint. We hypothesised that 5-year locoregional recurrence rate would be less than 4% (upper-limit 95% CI 7·8%). This study was registered at ClinicalTrials.gov, NCT01279304, and is completed.

FINDINGS

838 patients were eligible for 5-year follow-up analyses: 291 in the low-risk group, 370 in the intermediate-risk group, and 177 in the high-risk group. The 5-year locoregional recurrence rate in all patients was 2·2% (95% CI 1·4-3·4). The 5-year locoregional recurrence rate was 2·1% (0·9-4·3) in the low-risk group, 2·2% (1·0-4·1) in the intermediate-risk group, and 2·3% (0·8-5·5) in the high-risk group. If the study guideline was followed, the locoregional recurrence rate was 2·3% (0·8-5·3) for the low-risk group, 1·0% (0·2-3·4) for the intermediate-risk group, and 1·4% (0·3-4·5) for the high-risk group.

INTERPRETATION

In this study, the 5-year locoregional recurrence rate was less than 4%, which supports our hypothesis that it is oncologically safe to de-escalate locoregional radiotherapy based on locoregional recurrence risk, in selected patients with cT1-2N1 breast cancer treated with primary chemotherapy, according to this predefined, consensus-based study guideline.

FUNDING

Dutch Cancer Society.

TRANSLATION

For the Dutch translation of the abstract see Supplementary Materials section.

Validation of the 70-gene signature test (MammaPrint) to identify patients with breast cancer aged ≥ 70 years with ultralow risk of distant recurrence: A population-based cohort study

INTRODUCTION

When risk estimation in older patients with hormone receptor positive breast cancer (HR + BC) is based on the same factors as in younger patients, age-related factors regarding recurrence risk and other-cause mortality are not considered. Genomic risk assessment could help identify patients with ultralow risk BC who can forgo adjuvant treatment. However, assessment tools should be validated specifically for older patients. This study aims to determine whether the 70-gene signature test (MammaPrint) can identify patients with HR + BC aged ≥70 years with ultralow risk for distant recurrence.

MATERIALS AND METHODS

Inclusion criteria: ≥70 years; invasive HR + BC; T1-2N0-3M0.

EXCLUSION CRITERIA

HER2 + BC; neoadjuvant therapy. MammaPrint assays were performed following standardized protocols. Clinical risk was determined with St. Gallen risk classification. Primary endpoint was 10-year cumulative incidence rate of distant recurrence in relation to genomic risk. Subdistribution hazard ratios (sHR) were estimated from Fine and Gray analyses. Multivariate analyses were adjusted for adjuvant endocrine therapy and clinical risk.

RESULTS

This study included 418 patients, median age 78 years (interquartile range [IQR] 73-83). Sixty percent of patients were treated with endocrine therapy. MammaPrint classified 50 patients as MammaPrint-ultralow, 224 patients as MammaPrint-low, and 144 patients as MammaPrint-high risk. Regarding clinical risk, 50 patients were classified low, 237 intermediate, and 131 high. Discordance was observed between clinical and genomic risk in 14 MammaPrint-ultralow risk patients who were high clinical risk, and 84 patients who were MammaPrint-high risk, but low or intermediate clinical risk. Median follow-up was 9.2 years (IQR 7.9-10.5). The 10-year distant recurrence rate was 17% (95% confidence interval [CI] 11-23) in MammaPrint-high risk patients, 8% (4-12) in MammaPrint-low (HR 0.46; 95%CI 0.25-0.84), and 2% (0-6) in MammaPrint-ultralow risk patients (HR 0.11; 95%CI 0.02-0.81). After adjustment for clinical risk and endocrine therapy, MammaPrint-high risk patients still had significantly higher 10-year distant recurrence rate than MammaPrint-low (sHR 0.49; 95%CI 0.26-0.90) and MammaPrint-ultralow patients (sHR 0.12; 95%CI 0.02-0.85). Of the 14 MammaPrint-ultralow, high clinical risk patients none developed a distant recurrence.

DISCUSSION

These data add to the evidence validating MammaPrint's ultralow risk threshold. Even in high clinical risk patients, MammaPrint-ultralow risk patients remained recurrence-free ten years after diagnosis. These findings justify future studies into using MammaPrint to individualize adjuvant treatment in older patients.

Prediction Models and Decision Aids for Women with Ductal Carcinoma In Situ: A Systematic Literature Review

Simple Summary

Ductal carcinoma in situ (DCIS) is a potential precursor to invasive breast cancer (IBC). Although in many women DCIS will never become breast cancer, almost all women diagnosed with DCIS undergo surgery with/without radiotherapy. Several studies are ongoing to de-escalate treatment for DCIS. Multiple decision support tools have been developed to aid women with DCIS in selecting the best treatment option for their specific goals. The aim of this study was to identify these decision support tools and evaluate their quality and clinical utility. Thirty-three studies were reviewed, in which four decision aids and six prediction models were described. While some of these models might be promising, most lacked important qualities such as tools to help women discuss their options or good quality validation studies. Therefore, the need for good quality, well validated decision support tools remains unmet.

Abstract

Even though Ductal Carcinoma in Situ (DCIS) can potentially be an invasive breast cancer (IBC) precursor, most DCIS lesions never will progress to IBC if left untreated. Because we cannot predict yet which DCIS lesions will and which will not progress, almost all women with DCIS are treated by breast-conserving surgery +/− radiotherapy, or even mastectomy. As a consequence, many women with non-progressive DCIS carry the burden of intensive treatment without any benefit. Multiple decision support tools have been developed to optimize DCIS management, aiming to find the balance between over- and undertreatment. In this systematic review, we evaluated the quality and added value of such tools. A systematic literature search was performed in Medline(ovid), Embase(ovid), Scopus and TRIP. Following the PRISMA guidelines, publications were selected. The CHARMS (prediction models) or IPDAS (decision aids) checklist were used to evaluate the tools’ methodological quality. Thirty-three publications describing four decision aids and six prediction models were included. The decision aids met at least 50% of the IPDAS criteria. However, most lacked tools to facilitate discussion of the information with healthcare providers. Five prediction models quantify the risk of an ipsilateral breast event after a primary DCIS, one estimates the risk of contralateral breast cancer, and none included active surveillance. Good quality and external validations were lacking for all prediction models. There remains an unmet clinical need for well-validated, good-quality DCIS risk prediction models and decision aids in which active surveillance is included as a management option for low-risk DCIS.

Comprehensive multiplexed immune profiling of the ductal carcinoma in situ immune microenvironment regarding subsequent ipsilateral invasive breast cancer risk

Background

Ductal carcinoma in situ (DCIS) is treated to prevent subsequent ipsilateral invasive breast cancer (iIBC). However, many DCIS lesions will never become invasive. To prevent overtreatment, we need to distinguish harmless from potentially hazardous DCIS. We investigated whether the immune microenvironment (IME) in DCIS correlates with transition to iIBC.

Methods

Patients were derived from a Dutch population-based cohort of 10,090 women with pure DCIS with a median follow-up time of 12 years. Density, composition and proximity to the closest DCIS cell of CD20⁺ B-cells, CD3⁺CD8⁺ T-cells, CD3⁺CD8⁻ T-cells, CD3⁺FOXP3⁺ regulatory T-cells, CD68⁺ cells, and CD8⁺Ki67⁺ T-cells was assessed with multiplex immunofluorescence (mIF) with digital whole-slide analysis and compared between primary DCIS lesions of 77 women with subsequent iIBC (cases) and 64 without (controls).

Results

Higher stromal density of analysed immune cell subsets was significantly associated with higher grade, ER negativity, HER-2 positivity, Ki67 ≥ 14%, periductal fibrosis and comedonecrosis (P < 0.05). Density, composition and proximity to the closest DCIS cell of all analysed immune cell subsets did not differ between cases and controls.

Conclusion

IME features analysed by mIF in 141 patients from a well-annotated cohort of pure DCIS with long-term follow-up are no predictors of subsequent iIBC, but do correlate with other factors (grade, ER, HER2 status, Ki-67) known to be associated with invasive recurrences.

Abstract 686: Subsequent invasive breast cancer risk after DCIS treatment in multinational PRECISION consortium cohorts comprising 48,576 patients

Background: Although DCIS is a precursor of invasive breast cancer (IBC), most DCIS lesions never will progress. As we cannot distinguish reliably progressive from harmless DCIS yet, almost all women with DCIS are treated extensively with surgery and often adjuvant radiotherapy or endocrine treatment, implying overtreatment of many thousands of women with harmless DCIS. PRECISION aims to reduce such overtreatment by identifying factors associated with subsequent ipsilateral IBC. Many factors have been implicated in subsequent DCIS and IBC risk, but most studies relied on small series with limited prognostic power. To overcome this, we conducted pooled analyses of four large cohorts with DCIS from three different countries.

Methods: Cohorts were pooled with data of 48,804 women with DCIS: a population-based cohort (NL, n=18,996), prospective, a population-based, screening cohort (Sloane, UK, n=8,462), a single center cohort (MDACC, USA, n=2,363), and a representative DCIS patient series from the National Cancer Database Special Study (USA, n=18,983). Patients with missing data on treatment and follow-up or follow-up shorter than six months were excluded from analyses. Risk of a subsequent ipsilateral invasive breast cancer (iIBC) was assessed in three DCIS lesion size groups (&lt;20mm, 20-50mm and ≥50mm) and in patients who had clear surgical margins (&lt;2mm) after final breast conserving surgery (BCS) versus patients who did not. Cox proportional hazards models were used to assess differences in risk of IBC, with a focus on DCIS size and margin status.

Results: In final analyses, 48,576 patients, diagnosed between 1999 and 2017, were included. Median follow-up was 7.6 years (range 0.5-21.1). In multivariable analyses, patients with smaller size of DCIS (&lt;20mm) had a decreased risk of iIBC compared with women with larger lesion size (HR 0.81; 95% CI 0.68-0.97). In 33,091 BCS treated patients, patients with clear surgical margins had a decreased risk of iIBC (HR 0.68; 95% CI 0.52-0.90).

Conclusion: In our quest to reduce overtreatment for women with DCIS, we have identified free surgical margins and smaller lesion size as independent factors reducing the risk of subsequent ipsilateral invasive breast cancer, irrespective of the treatment received. Knowledge of these, and additional, factors could aid in selecting patients suitable for less invasive management strategies such as active surveillance or omitting radiotherapy. This work was supported by Cancer Research UK and by KWF Dutch Cancer Society (ref.C38317/A24043); Web site: https://cancergrandchallenges.org/teams/precision

Citation Format: Renee S. Schmitz, Alexandra W. van den Belt-Dusebout, Karen Clements, Yi Ren, Chiara Cresta, Jasmine Timbres, Yat-Hee Liu, Danalyn Byng, Thomas Lynch, Brian Menegaz, Deborah Collyar, Terry Hyslop, Michael Schaapveld, Elinor Sawyer, Shelley E. Hwang, Alastair Thompson, Marc D. Ryser, Jelle Wesseling, Esther H. Lips, Marjanka K. Schmidt, Grand Challenge PRECISION Consortium. Subsequent invasive breast cancer risk after DCIS treatment in multinational PRECISION consortium cohorts comprising 48,576 patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 686.

Abstract 5108: Copy number analysis of pure DCIS and association with recurrence

With the widespread adoption of breast cancer screening the incidence of pure ductal carcinoma in situ (DCIS) has increased. As DCIS is considered a non-obligate precursor of invasive ductal carcinoma most women with pure DCIS are treated with breast conserving surgery (BCS) +/- radiotherapy. However, for many this is likely to be overtreatment as only a minority will develop a subsequent ipsilateral recurrence. Studies also show that only ~60% of these ipsilateral recurrences are invasive disease with the remainder being pure DCIS. To predict which women are most likely to benefit from interventions, there is a need to identify biomarkers that are associated with invasive recurrence. Our aim was to assess whether copy number aberrations (CNAs) could be used to identify DCIS that was likely to recur as invasive disease or remain recurrence-free during long-time follow up.

We performed somatic copy number profiling on 309 pure DCIS samples that had not developed an ipsilateral event (controls), 198 that had developed subsequent ipsilateral invasive disease (INV-cases) and 58 that had developed subsequent ipsilateral pure DCIS (DCIS-cases). The samples were obtained from two large nation-wide cohorts: the Sloane cohort, a prospective breast screening cohort from the UK with a median follow up of 12.5 years and a Dutch population based cohort, with a median follow up of 13 years. CNAs were assessed using the CytoSNP array or low pass whole genome sequencing and analyzed using GISTIC.

Integrative cluster (IntClust) subtyping revealed that only 5 subtypes were well represented in DCIS compared to 10 in invasive disease and the distribution of clusters between INV-cases and controls was similar with the exception of IntClust 4, which was significantly more common in controls (P= 0.025, Fishers exact test). IntClust 4 is characterized to have low levels of genomic instability and a CNA-devoid. INV-cases were globally more aberrant than controls (P = 0.006, Wilcoxon test) as assessed by the chromosomal instability index (CIN) score. GISTIC identified 17 recurrent amplifications, 21 recurrent gains and 22 recurrent losses in the whole cohort. Six of these regions were more common in INV-cases compared to controls: amplifications at 17q24.1 and 8p11.23, losses at 1p36.13 and 11q23.2 ​and gains at 17q21.33​ and 16p (Nominal P &lt; 0.05 and FDR &lt; 0.1, Fishers exact test). Subgroup analysis of ER+, Her2- INV-cases versus controls revealed an additional differential CNA, amplification at 11q13.3 more common in cases.

DCIS-cases had similar CNAs to INV-cases and were more aberrant than controls in terms of CIN score (P &lt; 0.037, Wilcoxon test) but not as aberrant as INV-cases.

In conclusion, we have identified potential CNAs that are associated with invasive recurrence. Further analysis will integrate gene expression with copy number data to identify which genes are being targeted by these CNAs in order to identify pathways important in progression of DCIS.

Citation Format: Ahmed A. Ahmed, Maria Roman-Escorza, Tycho Bismeijer, Michael Sheinman, Vandna Shah, Rana Shami, Jeffrey R. Marks, Lorraine M. King, Anargyros Megalios, Lindy L. Visser, Marlous Hoogstraat, Helen R. Davies, Tapsi Kumar, Deborah Collyar, Hilary Stobart, Sarah Pinder, Nicholas N. Navin, Andrew Futreal, Serena Nik-Zainal, E. Shelley Hwang, Lodewyk F. Wessels, Esther H. Lips, Alastair Thompson, Jelle Wesseling, Elinor J. Sawyer. Copy number analysis of pure DCIS and association with recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5108.

Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.

Beyond the snapshot: optimizing prognostication and prediction by moving from fixed to functional multidimensional cancer pathology

The role of pathology in patient management has evolved over time from the retrospective review of cells, tissue, and disease (‘what happened’) to a prospective outlook (‘what will happen’). Examination of a static, two‐dimensional hematoxylin and eosin (H&E)‐stained tissue slide has traditionally been the pathologist's primary task, but novel ancillary techniques enabled by technological breakthroughs have supported pathologists in their increasing ability to predict disease status and behaviour. Nevertheless, the informational limits of 2D, fixed tissue are now being reached and technological innovation is urgently needed to ensure that our understanding of disease entities continues to support improved individualized treatment options. Here we review pioneering work currently underway in the field of cancer pathology that has the potential to capture information beyond the current basic snapshot. A selection of exciting new technologies is discussed that promise to facilitate integration of the functional and multidimensional (space and time) information needed to optimize the prognostic and predictive value of cancer pathology. Learning how to analyse, interpret, and apply the wealth of data acquired by these new approaches will challenge the knowledge and skills of the pathology community. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Prognostic Value of Stromal Tumor-Infiltrating Lymphocytes in Young, Node-Negative, Triple-Negative Breast Cancer Patients Who Did Not Receive (neo)Adjuvant Systemic Therapy

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 (χ² = 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.

Young cancer patients with TNBC and high sTILs have an excellent outcome, even without systemic treatment

Differential Survival and Therapy Benefit of Patients with Breast Cancer Are Characterized by Distinct Epithelial and Immune Cell Microenvironments

PURPOSE

Extensive work in preclinical models has shown that microenvironmental cells influence many aspects of cancer cell behavior, including metastatic potential and their sensitivity to therapeutics. In the human setting, this behavior is mainly correlated with the presence of immune cells. Here, in addition to T cells, B cells, macrophages, and mast cells, we identified the relevance of nonimmune cell types for breast cancer survival and therapy benefit, including fibroblasts, myoepithelial cells, muscle cells, endothelial cells, and seven distinct epithelial cell types.

EXPERIMENTAL DESIGN

Using single-cell sequencing data, we generated reference profiles for all these cell types. We used these reference profiles in deconvolution algorithms to optimally detangle the cellular composition of more than 3,500 primary breast tumors of patients that were enrolled in the SCAN-B and MATADOR clinical trials, and for which bulk mRNA sequencing data were available.

RESULTS

This large data set enables us to identify and subsequently validate the cellular composition of microenvironments that distinguish differential survival and treatment benefit for different treatment regimens in patients with primary breast cancer. In addition to immune cells, we have identified that survival and therapy benefit are characterized by various contributions of distinct epithelial cell types.

CONCLUSIONS

From our study, we conclude that differential survival and therapy benefit of patients with breast cancer are characterized by distinct microenvironments that include specific populations of immune and epithelial cells.