Cancer Outcomes in DCIS Patients Without Locoregional Treatment

Invasive recurrence after breast conserving treatment of ductal carcinoma in situ of the breast in the Netherlands: time trends and the association with tumour grade

BACKGROUND

The first aim of this study was to examine trends in the risk of ipsilateral invasive breast cancer (iIBC) after breast-conserving surgery (BCS) of ductal carcinoma in situ (DCIS). A second aim was to analyse the association between DCIS grade and the risk of iIBC following BCS.

PATIENTS AND METHODS

In this population-based, retrospective cohort study, the Netherlands Cancer Registry collected information on 25,719 women with DCIS diagnosed in the period 1989-2021 who underwent BCS. Of these 19,034 received adjuvant radiotherapy (RT). Kaplan-Meier analyses and Cox regression models were used.

RESULTS

A total of 1135 patients experienced iIBC. Ten-year cumulative incidence rates of iIBC for patients diagnosed in the periods 1989-1998, 1999-2008 and 2009-2021 undergoing BCS without RT, were 12.6%, 9.0% and 5.0% (P < 0.001), respectively. For those undergoing BCS with RT these figures were 5.7%, 3.7% and 2.2%, respectively (P < 0.001). In the multivariable analyses, DCIS grade was not associated with the risk of iIBC.

CONCLUSION

Since 1989 the risk of iIBC has decreased substantially and has become even lower than the risk of invasive contralateral breast cancer. No significant association of DCIS grade with iIBC was found, stressing the need for more powerful prognostic factors to guide the treatment of DCIS.

DCIS knowledge of women choosing between active surveillance and surgery for low-risk DCIS

BACKGROUND

Ductal carcinoma in situ (DCIS) can progress to invasive breast cancer (IBC), but often never will. As we cannot predict accurately which DCIS-lesions will or will not progress to IBC, almost all women with DCIS undergo breast-conserving surgery supplemented with radiotherapy, or even mastectomy. In some countries, endocrine treatment is prescribed as well. This implies many women with non-progressive DCIS undergo overtreatment. To reduce this, the LORD patient preference trial (LORD-PPT) tests whether mammographic active surveillance (AS) is safe by giving women with low-risk DCIS a choice between treatment and AS. For this, sufficient knowledge about DCIS is crucial. Therefore, we assessed women's DCIS knowledge in association with socio-demographic and clinical characteristics.

METHODS

LORD-PPT participants (N = 376) completed a questionnaire assessing socio-demographic and clinical characteristics, risk perception, treatment choice and DCIS knowledge after being informed about their diagnosis and treatment options.

RESULTS

66 % of participants had poor knowledge (i.e., answered ≤3 out of 7 knowledge items correctly). Most incorrect answers involved overestimating the safety of AS and misunderstanding of DCIS prognostic risks. Overall, women with higher DCIS knowledge score perceived their risk of developing IBC as being somewhat higher than women with poorer knowledge (p = 0.049). Women with better DCIS knowledge more often chose surgery whilst most women with poorer knowledge chose active surveillance (p = 0.049).

DISCUSSION

Our findings show that there is room for improvement of information provision to patients. Decision support tools for patients and clinicians could help to stimulate effective shared decision-making about DCIS management.

Ductal carcinoma in situ of the breast: finding the balance between overtreatment and undertreatment

Ductal carcinoma in situ (DCIS) accounts for 15-25% of all breast cancer diagnoses. Its prognosis is excellent overall, the main risk being the occurrence of local breast events, as most cases of DCIS do not progress to invasive cancer. Systematic screening has greatly increased the incidence of this non-obligate precursor of invasion, lending urgency to the need to identify DCIS that is prone to invasive progression and distinguish it from non-invasion-prone DCIS, as the latter can be overdiagnosed and therefore overtreated. Treatment strategies, including surgery, radiotherapy, and optional endocrine therapy, decrease the risk of local events, but have no effect on survival outcomes. Active surveillance is being evaluated as a possible new option for low-risk DCIS. Considerable efforts to decipher the biology of DCIS have led to a better understanding of the factors that determine its variable natural history. Given this variability, shared decision making regarding optimal, personalised treatment strategies is the most appropriate course of action. Well designed, risk-based de-escalation studies remain a major need in this field.

Update on Management of Ductal Carcinoma in Situ

Ductal carcinoma in situ (DCIS) represents 18% to 25% of all diagnosed breast cancers, and is a noninvasive, nonobligate precursor lesion to invasive cancer. The diagnosis of DCIS represents a wide range of disease, including lesions with both low and high risk of progression to invasive cancer and recurrence. Over the past decade, research on the topic of DCIS has focused on the possibility of tailoring treatment for patients according to their risk for progression and recurrence, which is based on clinicopathologic, biomolecular and genetic factors. These efforts are ongoing, with recently completed and continuing clinical trials spanning the continuum of cancer care. We conducted a review to identify recent advances on the topic of diagnosis, risk stratification and management of DCIS. While novel imaging techniques have increased the rate of DCIS diagnosis, questions persist regarding the optimal management of lesions that would not be identified with conventional methods. Additionally, among trials investigating the potential for omission of surgery and use of active surveillance, 2 trials have completed accrual and 2 clinical trials are continuing to enroll patients. Identification of novel genetic patterns is expanding our potential for risk stratification and aiding our ability to de-escalate radiation and systemic therapies for DCIS. These advances provide hope for tailoring of DCIS treatment in the near future.

Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer

PURPOSE

The progression of ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) in humans is highly variable. To better understand the relationship between them, we performed a multi-omic characterization of co-occurring DCIS and IBC lesions in a cohort of individuals.

METHODS

Formalin-fixed paraffin-embedded tissue samples from 50 patients with co-occurring DCIS and IBC lesions were subjected to DNA-seq and whole transcriptome RNA-seq. Paired DCIS and IBC multi-omics profiles were then interrogated for DNA mutations, gene expression profiles and pathway analysis.

RESULTS

Most small variants and copy number variations were shared between co-occurring DCIS and IBC lesions, with IBC exhibiting on average a higher degree of additional mutations. However, 36% of co-occurring lesions shared no common mutations and 49% shared no common copy number variations. The most frequent genomic variants in both DCIS and IBC were PIK3CA, TP53, KMT2C, MAP3K1, GATA3 and SF3B1, with KMT2C being more frequent in DCIS and TP53 and MAP3K1 more frequent in IBC, though the numbers are too small for definitive conclusions. The most frequent copy number variations were seen in MCL1, CKSB1 and ERBB2. ERBB2 changes were not seen in IBC unless present in the corresponding DCIS. Transcriptional profiles were highly distinct between DCIS and IBC, with DCIS exhibiting upregulation of immune-related signatures, while IBC showed significant overexpression in genes and pathways associated with cell division and proliferation. Interestingly, DCIS and IBC exhibited significant differential expression of different components of extracellular matrix (ECM) formation and regulation, with DCIS showing overexpression of ECM-membrane interaction components while IBC showed upregulation of genes associated with fibronectin and invadopodia.

CONCLUSION

While most co-occurring DCIS and IBC were mutationally similar and suggestive of a common clonal progenitor, transcriptionally the lesions are highly distinct, with IBC expressing key pathways that facilitate invasion and proliferation. These results are suggestive of additional levels of regulation, epigenetic or other, that facilitate the acquisition of invasive properties during tumor evolution.

Second Primary Breast Cancer in Young Breast Cancer Survivors

Importance

Among women diagnosed with primary breast cancer (BC) at or younger than age 40 years, prior data suggest that their risk of a second primary BC (SPBC) is higher than that of women who are older when they develop a first primary BC.

Objective

To estimate cumulative incidence and characterize risk factors of SPBC among young patients with BC.

Design, Setting, and Participants

Participants were enrolled in the Young Women's Breast Cancer Study, a prospective study of 1297 women aged 40 years or younger who were diagnosed with stage 0 to III BC from August 2006 to June 2015. Demographic, genetic testing, treatment, and outcome data were collected by patient surveys and medical record review. A time-to-event analysis was used to account for competing risks when determining cumulative incidence of SPBC, and Fine-Gray subdistribution hazard models were used to evaluate associations between clinical factors and SPBC risk. Data were analyzed from January to May 2023.

Main Outcomes and Measures

The 5- and 10- year cumulative incidence of SPBC.

Results

In all, 685 women with stage 0 to III BC (mean [SD] age at primary BC diagnosis, 36 [4] years) who underwent unilateral mastectomy or lumpectomy as the primary surgery for BC were included in the analysis. Over a median (IQR) follow-up of 10.0 (7.4-12.1) years, 17 patients (2.5%) developed an SPBC; 2 of these patients had cancer in the ipsilateral breast after lumpectomy. The median (IQR) time from primary BC diagnosis to SPBC was 4.2 (3.3-5.6) years. Among 577 women who underwent genetic testing, the 10-year risk of SPBC was 2.2% for women who did not carry a pathogenic variant (12 of 544) and 8.9% for carriers of a pathogenic variant (3 of 33). In multivariate analyses, the risk of SPBC was higher among PV carriers vs noncarriers (subdistribution hazard ratio [sHR], 5.27; 95% CI, 1.43-19.43) and women with primary in situ BC vs invasive BC (sHR, 5.61; 95% CI, 1.52-20.70).

Conclusions

Findings of this cohort study suggest that young BC survivors without a germline pathogenic variant have a low risk of developing a SPBC in the first 10 years after diagnosis. Findings from germline genetic testing may inform treatment decision-making and follow-up care considerations in this population.

Use of beta-blockers in patients with ductal carcinoma in situ and risk of invasive breast cancer recurrence: a Swedish retrospective cohort study

BACKGROUND

Retrospective observational studies suggest a potential role of beta-blockers as a protective strategy against progression and metastasis in invasive breast cancer. In this context, we investigated the impact of beta-blocker exposure on risk for progression to invasive breast cancer after diagnosis of ductal cancer in situ (DCIS).

METHODS

The retrospective study population included 2535 women diagnosed with pure DCIS between 2006 and2012 in three healthcare regions in SwedenExposure to beta-blocker was quantified using a time-varying percentage of days with medication available. The absolute risk was quantified using cumulative incidence functions and cox models were applied to quantify the association between beta-blocker exposure and time from DCIS diagnosis to invasive breast cancer, accounting for delayed effects, competing risks and pre-specified confounders.

RESULTS

The median follow-up was 8.7 years. One third of the patients in our cohort were exposed to beta-blockers post DCIS diagnosis. During the study period, 48 patients experienced an invasive recurrence, giving a cumulative incidence of invasive breast cancer progression of 1.8% at five years. The cumulative exposure to beta-blocker was associated with a reduced risk in a dose-dependent manner, though the effect was not statistically significant.

CONCLUSION

Our observational study is suggestive of a protective effect of beta-blockers against invasive breast cancer after primary DCIS diagnosis. These results provide rationales for experimental and clinical follow-up studies in carefully selected DCIS groups.

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.

Development of a Multi-Parametric ultrasonography nomogram for prediction of invasiveness in ductal carcinoma in situ

OBJECTIVE

To investigate the independent risk variables associated with the potential invasiveness of ductal carcinoma in situ (DCIS) on multi-parametric ultrasonography, and further construct a nomogram for risk assessment.

METHODS

Consecutive patients from January 2017 to December 2022 who were suspected of having ductal carcinoma in situ (DCIS) based on magnetic resonance imaging or mammography were prospectively enrolled. Histopathological findings after surgical resection served as the gold standard. Grayscale ultrasound, Doppler ultrasound, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS) examinations were preoperative performed. Binary logistic regression was used for multifactorial analysis to identify independent risk factors from multi-parametric ultrasonography. The correlation between independent risk factors and pathological prognostic markers was analyzed. The predictive efficacy of DCIS associated with invasiveness was assessed by logistic analysis, and a nomogram was established.

RESULTS

A total of 250 DCIS lesions were enrolled from 249 patients, comprising 85 pure DCIS and 165 DCIS with invasion (DCIS-IDC), of which 41 exhibited micro-invasion. The multivariate analysis identified independent risk factors for DCIS with invasion on multi-parametric ultrasonography, including image size (>2cm), Doppler ultrasound RI (≥0.72), SWE's Emax (≥66.4 kPa), hyper-enhancement, centripetal enhancement, increased surrounding vessel, and no contrast agent retention on CEUS. These factors correlated with histological grade, Ki-67, and human epidermal growth factor receptor 2 (HER2) (P < 0.1). The multi-parametric ultrasound approach demonstrated good predictive performance (sensitivity 89.7 %, specificity 73.8 %, AUC 0.903), surpassing single US modality or combinations with SWE or CEUS modalities. Utilizing these factors, a predictive nomogram achieved a respectable performance (AUC of 0.889) for predicting DCIS with invasion. Additionally, a separate nomogram for predicting DCIS with micro-invasion, incorporating independent risk factors such as RI (≥0.72), SWE's Emax (≥65.2 kPa), and centripetal enhancement, demonstrated an AUC of 0.867.

CONCLUSION

Multi-parametric ultrasonography demonstrates good discriminatory ability in predicting both DCIS with invasion and micro-invasion through the analysis of lesion morphology, stiffness, neovascular architecture, and perfusion. The use of a nomogram based on ultrasonographic images offers an intuitive and effective method for assessing the risk of invasion in DCIS. Although the nomogram is not currently considered a clinically applicable diagnostic tool due to its AUC being below the threshold of 0.9, further research and development are anticipated to yield positive outcomes and enhance its viability for clinical utilization.

Evolving Treatment Paradigms for Low-Risk Ductal Carcinoma In Situ: Imaging Needs

Ductal carcinoma in situ (DCIS) is a nonobligate precursor to invasive cancer that classically presents as asymptomatic calcifications on screening mammography. The increase in DCIS diagnoses with organized screening programs has raised concerns about overdiagnosis, while a patientcentric push for more personalized care has increased awareness about DCIS overtreatment. The standard of care for most new DCIS diagnoses is surgical excision, but nonsurgical management via active monitoring is gaining attention, and multiple clinical trials are ongoing. Imaging, along with demographic and pathologic information, is a critical component of active monitoring efforts. Commonly used imaging modalities including mammography, ultrasound, and MRI, as well as newer modalities such as contrast-enhanced mammography and dedicated breast PET, can provide prognostic information to risk stratify patients for DCIS active monitoring eligibility. Furthermore, radiologists will be responsible for closely surveilling patients on active monitoring and identifying if invasive progression occurs. Active monitoring is a paradigm shift for DCIS care, but the success or failure will rely heavily on the interpretations and guidance of radiologists.

Classification performance bias between training and test sets in a limited mammography dataset

OBJECTIVES

To assess the performance bias caused by sampling data into training and test sets in a mammography radiomics study.

METHODS

Mammograms from 700 women were used to study upstaging of ductal carcinoma in situ. The dataset was repeatedly shuffled and split into training (n = 400) and test cases (n = 300) forty times. For each split, cross-validation was used for training, followed by an assessment of the test set. Logistic regression with regularization and support vector machine were used as the machine learning classifiers. For each split and classifier type, multiple models were created based on radiomics and/or clinical features.

RESULTS

Area under the curve (AUC) performances varied considerably across the different data splits (e.g., radiomics regression model: train 0.58-0.70, test 0.59-0.73). Performances for regression models showed a tradeoff where better training led to worse testing and vice versa. Cross-validation over all cases reduced this variability, but required samples of 500+ cases to yield representative estimates of performance.

CONCLUSIONS

In medical imaging, clinical datasets are often limited to relatively small size. Models built from different training sets may not be representative of the whole dataset. Depending on the selected data split and model, performance bias could lead to inappropriate conclusions that might influence the clinical significance of the findings.

ADVANCES IN KNOWLEDGE

Performance bias can result from model testing when using limited datasets. Optimal strategies for test set selection should be developed to ensure study conclusions are appropriate.

Duration of Endocrine Treatment for DCIS impacts second events: Insights from a large cohort of cases at two academic medical centers

Ductal carcinoma in situ (DCIS) incidence has risen rapidly with the introduction of screening mammography, yet it is unclear who benefits from both the amount and type of adjuvant treatment (radiation therapy, (RT), endocrine therapy (ET)) versus what constitutes over-treatment. Our goal was to identify the effects of adjuvant RT, or ET+/- RT versus breast conservation surgery (BCS) alone in a large multi-center registry of retrospective DCIS cases (N = 1,916) with median follow up of 8.2 years. We show that patients with DCIS who took less than 2 years of adjuvant ET alone have a similar second event rate as BCS. However, patients who took more than 2 years of ET show a significantly reduced second event rate, similar to those who received either RT or combined ET+RT, which was independent of age, tumor size, grade, or period of diagnosis. This highlights the importance of ET duration for risk reduction.

Imaging Changes and Outcomes of Patients Undergoing Active Monitoring for Ductal Carcinoma In Situ: Seven-Year Follow-up Study

RATIONALE AND OBJECTIVES

To determine the imaging changes and their associated positive predictive value (PPV) for invasive breast cancer in women undergoing active monitoring for ductal carcinoma in situ (DCIS).

MATERIALS AND METHODS

In this seven-year follow-up retrospective IRB-exempted cohort study, we reviewed patients diagnosed with DCIS who elected active monitoring between 2003 and 2022 at a single academic institution. Imaging characteristics, histopathology at initial diagnosis, and subsequent follow-up were recorded. Low-risk DCIS was defined as low or intermediate grade and hormone receptor (HR) positive (estrogen and/or progesterone receptor positive) disease diagnosed in women at least 40 years of age. Progression was defined as subsequent ipsilateral invasive breast cancer diagnosis.

RESULTS

There were 39 patients with a median age of 58.4 years (IQR: 51.1-69.6 years) and a median follow-up of 4.3 years (range: 0.6-16.4 years). Nearly two thirds of patients (64%, 25/39) had stable imaging (range: 0.6-16.4 years) and remained progression-free during active monitoring. Among the remaining 14 patients (36%), there were 24 imaging findings which prompted 22 subsequent core needle biopsies (range: 1-3 biopsies per patient) and two surgical biopsies. The PPV of invasive cancer was 29% (7/24) overall and 38% (3/8) for masses, 33% (3/9) for calcifications, 17% (1/6) for non-mass enhancement, and 0% (0/1) for architectural distortion.

CONCLUSION

Of the radiographic changes prompting an additional biopsy, development of a new mass (38%) and new calcifications (33%) had the highest PPV for invasive progression. Close imaging follow-up should be a critical component for patients undergoing monitoring for DCIS.

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.

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.

Growth Dynamics of Ductal Carcinoma in Situ Recapitulate Normal Breast Development

Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations. The somatic mutation topographies revealed that DCIS is multiclonal and consists of spatially discontinuous subclonal lesions. Here we show that this pattern of spread is consistent with a new 'Comet' model of DCIS tumorigenesis, whereby multiple subclones arise early and nucleate the buds of the growing tumor. The discontinuous, multiclonal growth of the Comet model is analogous to the branching morphogenesis of normal breast development that governs the rapid expansion of the mammary epithelium during puberty. The branching morphogenesis-like dynamics of the proposed Comet model diverges from the canonical model of clonal evolution, and better explains observed genomic spatial data. Importantly, the Comet model allows for the clinically relevant scenario of extensive DCIS spread, without being subjected to the selective pressures of subclone competition that promote the emergence of increasingly invasive phenotypes. As such, the normal cell movement inferred during DCIS growth provides a new explanation for the limited risk of progression in DCIS and adds biologic rationale for ongoing clinical efforts to reduce DCIS overtreatment.

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.

SGLT1 as an adverse prognostic factor in invasive ductal carcinoma of the breast

PURPOSE

Sodium/glucose cotransporter (SGLT) 1 and 2 expression in carcinoma cells was recently examined, but their association with the clinicopathological factors of the patients and their biological effects on breast carcinoma cells have remained remain virtually unknown. Therefore, in this study, we explored the expression status of SGLT1 and SGLT2 in breast cancer patients and examined the effects of SGLT1 inhibitors on breast carcinoma cells in vitro.

METHODS

SGLT1 and SGLT2 were immunolocalized and we first correlated the findings with clinicopathological factors of the patients. We then administered mizagliflozin and KGA-2727, SGLT1 specific inhibitors to MCF-7 and MDA-MB-468 breast carcinoma cell lines, and their growth-inhibitory effects were examined. Protein arrays were then used to further explore their effects on the growth factors.

RESULTS

The SGLT1 high group had significantly worse clinical outcome including both overall survival and disease-free survival than low group. SGLT2 status was not significantly correlated with clinical outcome of the patients. Both mizagliflozin and KGA-2727 inhibited the growth of breast cancer cell lines. Of particular interest, mizagliflozin inhibited the proliferation of MCF-7 cells, even under very low glucose conditions. Mizagliflozin downregulated vascular endothelial growth factor receptor 2 phosphorylation.

CONCLUSION

High SGLT1 expression turned out as an adverse clinical prognostic factor in breast cancer patient. This is the first study demonstrating that SGLT1 inhibitors suppressed breast carcinoma cell proliferation. These results indicated that SGLT1 inhibitors could be used as therapeutic agents for breast cancer patients with aggressive biological behaviors.

Breast cancers as ecosystems: a metabolic perspective

Breast cancer (BC) is the most frequently diagnosed cancer and one of the major causes of cancer death. Despite enormous progress in its management, both from the therapeutic and early diagnosis viewpoints, still around 700,000 patients succumb to the disease each year, worldwide. Late recurrency is the major problem in BC, with many patients developing distant metastases several years after the successful eradication of the primary tumor. This is linked to the phenomenon of metastatic dormancy, a still mysterious trait of the natural history of BC, and of several other types of cancer, by which metastatic cells remain dormant for long periods of time before becoming reactivated to initiate the clinical metastatic disease. In recent years, it has become clear that cancers are best understood if studied as ecosystems in which the impact of non-cancer-cell-autonomous events-dependent on complex interaction between the cancer and its environment, both local and systemic-plays a paramount role, probably as significant as the cell-autonomous alterations occurring in the cancer cell. In adopting this perspective, a metabolic vision of the cancer ecosystem is bound to improve our understanding of the natural history of cancer, across space and time. In BC, many metabolic pathways are coopted into the cancer ecosystem, to serve the anabolic and energy demands of the cancer. Their study is shedding new light on the most critical aspect of BC management, of metastatic dissemination, and that of the related phenomenon of dormancy and fostering the application of the knowledge to the development of metabolic therapies.

Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering

While technologies for multiplexed imaging have provided an unprecedented understanding of tissue composition in health and disease, interpreting this data remains a significant computational challenge. To understand the spatial organization of tissue and how it relates to disease processes, imaging studies typically focus on cell-level phenotypes. However, images can capture biologically important objects that are outside of cells, such as the extracellular matrix. Here, we describe a pipeline, Pixie, that achieves robust and quantitative annotation of pixel-level features using unsupervised clustering and show its application across a variety of biological contexts and multiplexed imaging platforms. Furthermore, current cell phenotyping strategies that rely on unsupervised clustering can be labor intensive and require large amounts of manual cluster adjustments. We demonstrate how pixel clusters that lie within cells can be used to improve cell annotations. We comprehensively evaluate pre-processing steps and parameter choices to optimize clustering performance and quantify the reproducibility of our method. Importantly, Pixie is open source and easily customizable through a user-friendly interface.

Women's views about current and future management of Ductal Carcinoma in Situ (DCIS): A mixed-methods study

Management of low-risk ductal carcinoma in situ (DCIS) is controversial, with clinical trials currently assessing the safety of active monitoring amidst concern about overtreatment. Little is known about general community views regarding DCIS and its management. We aimed to explore women's understanding and views about low-risk DCIS and current and potential future management options. This mixed-method study involved qualitative focus groups and brief quantitative questionnaires. Participants were screening-aged (50-74 years) women, with diverse socioeconomic backgrounds and no personal history of breast cancer/DCIS, recruited from across metropolitan Sydney, Australia. Sessions incorporated an informative presentation interspersed with group discussions which were audio-recorded, transcribed and analysed thematically. Fifty-six women took part in six age-stratified focus groups. Prior awareness of DCIS was limited, however women developed reasonable understanding of DCIS and the relevant issues. Overall, women expressed substantial support for active monitoring being offered as a management approach for low-risk DCIS, and many were interested in participating in a hypothetical clinical trial. Although some women expressed concern that current management may sometimes represent overtreatment, there were mixed views about personally accepting monitoring. Women noted a number of important questions and considerations that would factor into their decision making. Our findings about women's perceptions of active monitoring for DCIS are timely while results of ongoing clinical trials of monitoring are awaited, and may inform clinicians and investigators designing future, similar trials. Exploration of offering well-informed patients the choice of non-surgical management of low-risk DCIS, even outside a clinical trial setting, may be warranted.

Tissue fluidification promotes a cGAS-STING cytosolic DNA response in invasive breast cancer

The process in which locally confined epithelial malignancies progressively evolve into invasive cancers is often promoted by unjamming, a phase transition from a solid-like to a liquid-like state, which occurs in various tissues. Whether this tissue-level mechanical transition impacts phenotypes during carcinoma progression remains unclear. Here we report that the large fluctuations in cell density that accompany unjamming result in repeated mechanical deformations of cells and nuclei. This triggers a cellular mechano-protective mechanism involving an increase in nuclear size and rigidity, heterochromatin redistribution and remodelling of the perinuclear actin architecture into actin rings. The chronic strains and stresses associated with unjamming together with the reduction of Lamin B1 levels eventually result in DNA damage and nuclear envelope ruptures, with the release of cytosolic DNA that activates a cGAS-STING (cyclic GMP-AMP synthase-signalling adaptor stimulator of interferon genes)-dependent cytosolic DNA response gene program. This mechanically driven transcriptional rewiring ultimately alters the cell state, with the emergence of malignant traits, including epithelial-to-mesenchymal plasticity phenotypes and chemoresistance in invasive breast carcinoma.

Should low-risk DCIS lose the cancer label? An evidence review

BACKGROUND

Population mammographic screening for breast cancer has led to large increases in the diagnosis and treatment of ductal carcinoma in situ (DCIS). Active surveillance has been proposed as a management strategy for low-risk DCIS to mitigate against potential overdiagnosis and overtreatment. However, clinicians and patients remain reluctant to choose active surveillance, even within a trial setting. Re-calibration of the diagnostic threshold for low-risk DCIS and/or use of a label that does not include the word 'cancer' might encourage the uptake of active surveillance and other conservative treatment options. We aimed to identify and collate relevant epidemiological evidence to inform further discussion on these ideas.

METHODS

We searched PubMed and EMBASE databases for low-risk DCIS studies in four categories: (1) natural history; (2) subclinical cancer found at autopsy; (3) diagnostic reproducibility (two or more pathologist interpretations at a single time point); and (4) diagnostic drift (two or more pathologist interpretations at different time points). Where we identified a pre-existing systematic review, the search was restricted to studies published after the inclusion period of the review. Two authors screened records, extracted data, and performed risk of bias assessment. We undertook a narrative synthesis of the included evidence within each category.

RESULTS

Natural History (n = 11): one systematic review and nine primary studies were included, but only five provided evidence on the prognosis of women with low-risk DCIS. These studies reported that women with low-risk DCIS had comparable outcomes whether or not they had surgery. The risk of invasive breast cancer in patients with low-risk DCIS ranged from 6.5% (7.5 years) to 10.8% (10 years). The risk of dying from breast cancer in patients with low-risk DCIS ranged from 1.2 to 2.2% (10 years). Subclinical cancer at autopsy (n = 1): one systematic review of 13 studies estimated the mean prevalence of subclinical in situ breast cancer to be 8.9%. Diagnostic reproducibility (n = 13): two systematic reviews and 11 primary studies found at most moderate agreement in differentiating low-grade DCIS from other diagnoses. Diagnostic drift: no studies found.

CONCLUSION

Epidemiological evidence supports consideration of relabelling and/or recalibrating diagnostic thresholds for low-risk DCIS. Such diagnostic changes would need agreement on the definition of low-risk DCIS and improved diagnostic reproducibility.

The Landmark Series-Ductal Carcinoma in Situ: The Evolution of Treatment

The evolution of ductal carcinoma in situ (DCIS) management has been driven by a parallel evolution in our understanding of its natural history. Early trials established the benefit of adjuvant therapies in all patients with DCIS. In contrast, subsequent studies have stratified patients to determine their eligibility for progressively less invasive and less intensive therapies. Large, randomized trials and meta-analyses have supported this shift away from treating DCIS as an homogenous disease treated with similar intensity to invasive breast cancer. This review describes the landmark studies on which current DCIS management is based.

DCIS: When is accelerated partial breast irradiation an option? A meta-analysis on outcomes and eligibility

BACKGROUND

The natural history of DCIS may not be progression to invasive breast cancer (IBC). Accelerated partial breast irradiation (APBI) has emerged as an alternative to whole breast radiotherapy (WBRT). The purpose of this study was to assess the impact of APBI on DCIS patients.

MATERIALS AND METHODS

Eligible studies from 2012 to 2022 were identified in PubMed, Cochrane Library, ClinicalTrials, and ICTRP. A meta-analysis was done comparing recurrence rates, breast-related mortality rates, and adverse events of APBI versus WBRT. A subgroup analysis of 2017 ASTRO Guidelines "Suitable" and "Unsuitable" groups was performed. Forest plots and quantitative analysis were done.

RESULTS

Six studies were eligible (3 on APBI versus WBRT, 3 on APBI suitability). All had a low risk of bias and publication bias. The cumulative incidence was the following for APBI and WBRT respectively: IBTR was 5.7% and 6.3% with odds ratio of 1.09, 95% CI [0.84, 1.42], mortality rate was 4.9% and 5.05%, and adverse events was 48.87% and 69.63%. All had no statistical significance between groups. Adverse events were found to favor the APBI arm. Recurrence rate was significantly less in the Suitable group with an odds ratio 2.69, 95% CI [1.56, 4.67], favoring it over the Unsuitable group.

CONCLUSION

APBI was comparable to WBRT in terms of recurrence rate, breast cancer-related mortality rate, and adverse events. APBI was not inferior to WBRT and showed better safety in terms of skin toxicity. Patients classified as suitable for APBI had significantly lesser recurrence rate.

Molecular Signatures in Ductal Carcinoma In Situ (DCIS): A Systematic Review and Meta-Analysis

CONTEXT

Adjuvant radiotherapy (RT) after breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS) is debated as benefits are inconstant. Molecular signatures for DCIS have been developed to stratify the risk of local recurrence (LR) and therefore guide the decision of RT.

OBJECTIVE

To evaluate, in women with DCIS treated by BCS, the impact of adjuvant RT on LR according to the molecular signature risk stratification.

METHODOLOGY

We conducted a systematic review and meta-analysis of five articles including women with DCIS treated by BCS and with a molecular assay performed to stratify the risk, comparing the effect of BCS and RT versus BCS alone on LR including ipsilateral invasive (InvBE) and total breast events (TotBE).

RESULTS

The meta-analysis included 3478 women and evaluated two molecular signatures: Oncotype Dx DCIS (prognostic of LR), and DCISionRT (prognostic of LR and predictive of RT benefit). For DCISionRT, in the high-risk group, the pooled hazard ratio of BCS + RT versus BCS was 0.39 (95%CI 0.20-0.77) for InvBE and 0.34 (95%CI 0.22-0.52) for TotBE. In the low-risk group, the pooled hazard ratio of BCS + RT versus BCS was significant for TotBE at 0.62 (95%CI 0.39-0.99); however, it was not significant for InvBE (HR = 0.58 (95%CI 0.25-1.32)), Discussion: Molecular signatures are able to discriminate high- and low-risk women, high-risk ones having a significant benefit of RT in the reduction of invasive and in situ local recurrences, while in low-risk ones RT did not have a benefit for preventing invasive breast recurrence. The risk prediction of molecular signatures is independent of other risk stratification tools developed in DCIS, and have a tendency toward RT de-escalation. Further studies are needed to assess the impact on mortality.

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.

De-Escalating the Management of In Situ and Invasive Breast Cancer

Simple Summary

De-escalation of breast cancer treatment reduces morbidity and toxicity for patients. De-escalation is safe if cancer outcomes, such as recurrence and survival, remain unaffected compared to more radical regimens. This review provides an overview on treatment de-escalation for ductal carcinoma in situ (DCIS), local treatment of breast cancer, and surgery after neoadjuvant systemic therapy. Improvements in understanding the natural history and biology of breast cancer, imaging modalities, and adjuvant treatments have facilitated de-escalation of treatment over time.

Abstract

It is necessary to identify appropriate areas of de-escalation in breast cancer treatment to minimize morbidity and maximize patients’ quality of life. Less radical treatment modalities, or even no treatment, have been reconsidered if they offer the same oncologic outcomes as standard therapies. Identifying which patients benefit from de-escalation requires particular care, as standard therapies will continue to offer adequate cancer outcomes. We provide an overview of the literature on the de-escalation of treatment of ductal carcinoma in situ (DCIS), local treatment of breast cancer, and surgery after neoadjuvant systemic therapy. De-escalation of breast cancer treatment is a key area of investigation that will continue to remain a priority. Improvements in understanding the natural history and biology of breast cancer, imaging modalities, and adjuvant treatments will expand this even further. Future efforts will continue to challenge us to consider the true role of various treatment modalities.

Single-Cell Transcriptome Profiling Reveals Intratumoral Heterogeneity and Molecular Features of Ductal Carcinoma In Situ

Ductal carcinoma in situ (DCIS) is a precursor to invasive breast cancer. The frequency of DCIS is increasing because of routine mammography; however, the biological features and intratumoral heterogeneity of DCIS remain obscure. To address this deficiency, we performed single-cell transcriptomic profiling of DCIS and invasive ductal carcinoma (IDC). DCIS was found to be composed of several transcriptionally distinct subpopulations of cancer cells with specific functions. Several transcripts, including long noncoding RNAs, were highly expressed in IDC compared to DCIS and might be related to the invasive phenotype. Closeness centrality analysis revealed extensive heterogeneity in DCIS, and the prediction model for cell-to-cell interactions implied that the interaction network among luminal cells and immune cells in DCIS was comparable to that in IDC. Additionally, transcriptomic profiling of HER2+ luminal DCIS indicated HER2 genomic amplification at the DCIS stage. These data provide novel insight into the intratumoral heterogeneity and molecular features of DCIS, which exhibit properties similar to IDC.

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.

Is loss of p53 a driver of ductal carcinoma in situ progression?

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive carcinoma. Multiple studies have shown that DCIS lesions typically possess a driver mutation associated with cancer development. Mutation in the TP53 tumour suppressor gene is present in 15-30% of pure DCIS lesions and in ~30% of invasive breast cancers. Mutations in TP53 are significantly associated with high-grade DCIS, the most likely form of DCIS to progress to invasive carcinoma. In this review, we summarise published evidence on the prevalence of mutant TP53 in DCIS (including all DCIS subtypes), discuss the availability of mouse models for the study of DCIS and highlight the need for functional studies of the role of TP53 in the development of DCIS and progression from DCIS to invasive disease.

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.

Cancer Modeling as Learning Experience

Cancer modeling has become an accepted method for generating evidence about comparative effectiveness and cost-effectiveness of candidate cancer control policies across the continuum of care. Models of early detection policies require inputs concerning disease natural history and screening test performance, which are often subject to considerable uncertainty. Model validation against an external data source can increase confidence in the reliability of assumed or calibrated inputs. When a model fails to validate, this presents an opportunity to revise these inputs, thereby learning new information about disease natural history or diagnostic performance that could both enhance the model results and inform real-world practices. We discuss the conditions necessary for validly drawing conclusions about specific inputs such as diagnostic performance from model validation studies. Doing so requires being able to faithfully replicate the validation study in terms of its design and implementation and being alert to the problem of non-identifiability, which could lead to explanations for failure to validate other than those identified. See related article by Rutter et al., p. 775.

Estimation of Breast Cancer Overdiagnosis in a U.S. Breast Screening Cohort

BACKGROUND

Mammography screening can lead to overdiagnosis-that is, screen-detected breast cancer that would not have caused symptoms or signs in the remaining lifetime. There is no consensus about the frequency of breast cancer overdiagnosis.

OBJECTIVE

To estimate the rate of breast cancer overdiagnosis in contemporary mammography practice accounting for the detection of nonprogressive cancer.

DESIGN

Bayesian inference of the natural history of breast cancer using individual screening and diagnosis records, allowing for nonprogressive preclinical cancer. Combination of fitted natural history model with life-table data to predict the rate of overdiagnosis among screen-detected cancer under biennial screening.

SETTING

Breast Cancer Surveillance Consortium (BCSC) facilities.

PARTICIPANTS

Women aged 50 to 74 years at first mammography screen between 2000 and 2018.

MEASUREMENTS

Screening mammograms and screen-detected or interval breast cancer.

RESULTS

The cohort included 35 986 women, 82 677 mammograms, and 718 breast cancer diagnoses. Among all preclinical cancer cases, 4.5% (95% uncertainty interval [UI], 0.1% to 14.8%) were estimated to be nonprogressive. In a program of biennial screening from age 50 to 74 years, 15.4% (UI, 9.4% to 26.5%) of screen-detected cancer cases were estimated to be overdiagnosed, with 6.1% (UI, 0.2% to 20.1%) due to detecting indolent preclinical cancer and 9.3% (UI, 5.5% to 13.5%) due to detecting progressive preclinical cancer in women who would have died of an unrelated cause before clinical diagnosis.

LIMITATIONS

Exclusion of women with first mammography screen outside BCSC.

CONCLUSION

On the basis of an authoritative U.S. population data set, the analysis projected that among biennially screened women aged 50 to 74 years, about 1 in 7 cases of screen-detected cancer is overdiagnosed. This information clarifies the risk for breast cancer overdiagnosis in contemporary screening practice and should facilitate shared and informed decision making about mammography screening.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Ductal Carcinoma in Situ: Molecular Changes Accompanying Disease Progression

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive ductal carcinoma (IDC), whereby if left untreated, approximately 12% of patients develop invasive disease. The current standard of care is surgical removal of the lesion, to prevent potential progression, and radiotherapy to reduce risk of recurrence. There is substantial overtreatment of DCIS patients, considering not all DCIS lesions progress to invasive disease. Hence, there is a critical imperative to better predict which DCIS lesions are destined for poor outcome and which are not, allowing for tailored treatment. Active surveillance is currently being trialed as an alternative management practice, but this approach relies on accurately identifying cases that are at low risk of progression to invasive disease. Two DCIS-specific genomic profiling assays that attempt to distinguish low and high-risk patients have emerged, but imperfections in risk stratification coupled with a high price tag warrant the continued search for more robust and accessible prognostic biomarkers. This search has largely turned researchers toward the tumor microenvironment. Recent evidence suggests that a spectrum of cell types within the DCIS microenvironment are genetically and phenotypically altered compared to normal tissue and play critical roles in disease progression. Uncovering the molecular mechanisms contributing to DCIS progression has provided optimism for the search for well-validated prognostic biomarkers that can accurately predict the risk for a patient developing IDC. The discovery of such markers would modernize DCIS management and allow tailored treatment plans. This review will summarize the current literature regarding DCIS diagnosis, treatment, and pathology.

A web-based personalized decision support tool for patients diagnosed with ductal carcinoma in situ: development, content evaluation, and usability testing

PURPOSE

Patients diagnosed with ductal carcinoma in situ (DCIS) face trade-offs when deciding among different treatments, including surgery, radiation, and endocrine therapy. A less chosen option is active monitoring. While evidence from clinical trials is not yet available, observational studies show comparable results for active monitoring and immediate treatment on cancer outcomes in select subgroups of patients. We developed and tested a web-based decision support tool (DST) to help patients explore current knowledge about DCIS and make an informed choice.

METHODS

The DST, an interactive web application, was informed by literature reviews and formative work with patients, breast surgeons, and health communication experts. We conducted iterative interviews to evaluate the DST content among women with and without a history of breast cancer, as well as breast cancer experts. For usability testing, we conducted an online survey among women with and without a history of breast cancer.

RESULTS

For content evaluation, 5 women with and 10 women without a history of DCIS were interviewed. The sample included 11 White and 4 non-White women, with a mean age of 64 years. The expert sample consisted of 5 attendings and a physician assistant. The feedback was used to add, clarify, or reorganize information in the DST. For usability testing, 22 participants with a mean age of 61 years were recruited including 15 White and 7 Black women and 6 women with a history of DCIS. The mean usability score was 3.7 out of 5. Most participants (86%) found that the DST provided unbiased information about treatments. To improve usability, we reduced the per-page content and added navigation cues.

CONCLUSION

Content and usability evaluation showed that the DST helps patients explore trade-offs of active monitoring and immediate treatment. By adopting a personalized approach, the tool will enable informed decisions aligned with patients' values and expectations.

Unresected screen-detected ductal carcinoma in situ: Outcomes of 311 women in the Forget-Me-Not 2 study

BACKGROUND AND AIM

The natural history of ductal carcinoma in situ (DCIS) is poorly understood. The aim of this cohort study was to determine the outcomes of women who had no surgery for screen-detected DCIS in the 6 months following diagnosis.

METHODS

English breast screening databases were retrospectively searched for women diagnosed with DCIS without invasive cancer at screening and who had no record of surgery within 6 months of diagnosis. These were cross-referenced with cancer registry data. Details of the potentially eligible women were sent to the relevant breast screening units for verification and for completion of data forms detailing clinical, radiological and pathological findings, non-surgical treatment and subsequent clinical course.

RESULTS

Data for 311 eligible women (median age 62 years) were available. 60 women developed invasive cancer, 56 ipsilateral and 4 contralateral. Ipsilateral invasion risk increased approximately linearly with time for at least 10 years. The 10-year cumulative risk of ipsilateral invasion was 9% (95% CI 4-21%), 39% (24-58%) and 36% (24-50%) for low, intermediate and high grade DCIS respectively and was higher in younger women, in those with larger DCIS lesions and in those with microinvasion. Most invasive cancers that developed were grade 2 or 3.

CONCLUSION

The findings suggest that active surveillance may be a reasonable alternative to surgery in patients with low grade DCIS but that women with intermediate or high grade disease should continue to be offered surgery. This highlights the importance of reproducible grading of DCIS to ensure patients receive appropriate treatment.

Preneoplastic Low-Risk Mammary Ductal Lesions (Atypical Ductal Hyperplasia and Ductal Carcinoma In Situ Spectrum): Current Status and Future Directions

Intraepithelial mammary ductal neoplasia is a spectrum of disease that varies from atypical ductal hyperplasia (ADH), low-grade (LG), intermediate-grade (IG), to high-grade (HG) ductal carcinoma in situ (DCIS). While ADH has the lowest prognostic significance, HG-DCIS carries the highest risk. Due to widely used screening mammography, the number of intraepithelial mammary ductal neoplastic lesions has increased. The consequence of this practice is the increase in the number of patients who are overdiagnosed and, therefore, overtreated. The active surveillance (AS) trials are initiated to separate lesions that require active treatment from those that can be safely monitored and only be treated when they develop a change in the clinical/radiologic characteristics. At the same time, the natural history of these lesions can be evaluated. This review aims to evaluate ADH/DCIS as a spectrum of intraductal neoplastic disease (risk and histomorphology); examine the controversies of distinguishing ADH vs. DCIS and the grading of DCIS; review the upgrading for both ADH and DCIS with emphasis on the variation of methods of detection and the definitions of upgrading; and evaluate the impact of all these variables on the AS trials.

Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma

Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand the changes in the tumor microenvironment (TME) accompanying transition to IBC, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to interrogate 79 clinically annotated surgical resections using machine learning tools for cell segmentation, pixel-based clustering, and object morphometrics. Comparison of normal breast with patient-matched DCIS and IBC revealed coordinated transitions between four TME states that were delineated based on the location and function of myoepithelium, fibroblasts, and immune cells. Surprisingly, myoepithelial disruption was more advanced in DCIS patients that did not develop IBC, suggesting this process could be protective against recurrence. Taken together, this HTAN Breast PreCancer Atlas study offers insight into drivers of IBC relapse and emphasizes the importance of the TME in regulating these processes.

Prediction of Upstaging in Ductal Carcinoma in Situ Based on Mammographic Radiomic Features

Background Improving diagnosis of ductal carcinoma in situ (DCIS) before surgery is important in choosing optimal patient management strategies. However, patients may harbor occult invasive disease not detected until definitive surgery. Purpose To assess the performance and clinical utility of mammographic radiomic features in the prediction of occult invasive cancer among women diagnosed with DCIS on the basis of core biopsy findings. Materials and Methods In this Health Insurance Portability and Accountability Act-compliant retrospective study, digital magnification mammographic images were collected from women who underwent breast core-needle biopsy for calcifications that was performed at a single institution between September 2008 and April 2017 and yielded a diagnosis of DCIS. The database query was directed at asymptomatic women with calcifications without a mass, architectural distortion, asymmetric density, or palpable disease. Logistic regression with regularization was used. Differences across training and internal test set by upstaging rate, age, lesion size, and estrogen and progesterone receptor status were assessed by using the Kruskal-Wallis or χ² test. Results The study consisted of 700 women with DCIS (age range, 40-89 years; mean age, 59 years ± 10 [standard deviation]), including 114 with lesions (16.3%) upstaged to invasive cancer at subsequent surgery. The sample was split randomly into 400 women for the training set and 300 for the testing set (mean ages: training set, 59 years ± 10; test set, 59 years ± 10; P = .85). A total of 109 radiomic and four clinical features were extracted. The best model on the test set by using all radiomic and clinical features helped predict upstaging with an area under the receiver operating characteristic curve of 0.71 (95% CI: 0.62, 0.79). For a fixed high sensitivity (90%), the model yielded a specificity of 22%, a negative predictive value of 92%, and an odds ratio of 2.4 (95% CI: 1.8, 3.2). High specificity (90%) corresponded to a sensitivity of 37%, positive predictive value of 41%, and odds ratio of 5.0 (95% CI: 2.8, 9.0). Conclusion Machine learning models that use radiomic features applied to mammographic calcifications may help predict upstaging of ductal carcinoma in situ, which can refine clinical decision making and treatment planning. © RSNA, 2022.

Ductal Carcinoma in Situ: State-of-the-Art Review

Ductal carcinoma in situ (DCIS) is a nonobligate precursor of invasive cancer, and its detection, diagnosis, and management are controversial. DCIS incidence grew with the expansion of screening mammography programs in the 1980s and 1990s, and DCIS is viewed as a major driver of overdiagnosis and overtreatment. For pathologists, the diagnosis and classification of DCIS is challenging due to undersampling and interobserver variability. Understanding the progression from normal breast tissue to DCIS and, ultimately, to invasive cancer is limited by a paucity of natural history data with multiple proposed evolutionary models of DCIS initiation and progression. Although radiologists are familiar with the classic presentation of DCIS as asymptomatic calcifications at mammography, the expanded pool of modalities, advanced imaging techniques, and image analytics have identified multiple potential biomarkers of histopathologic characteristics and prognosis. Finally, there is growing interest in the nonsurgical management of DCIS, including active surveillance, to reduce overtreatment and provide patients with more personalized management options. However, current biomarkers are not adept at enabling identification of occult invasive disease at biopsy or accurately predicting the risk of progression to invasive disease. Several active surveillance trials are ongoing and are expected to better identify women with low-risk DCIS who may avoid surgery.

Multiplexed Ion Beam Imaging: Insights into Pathobiology

Next-generation tools for multiplexed imaging have driven a new wave of innovation in understanding how single-cell function and tissue structure are interrelated. In previous work, we developed multiplexed ion beam imaging by time of flight, a highly multiplexed platform that uses secondary ion mass spectrometry to image dozens of antibodies tagged with metal reporters. As instrument throughput has increased, the breadth and depth of imaging data have increased as well. To extract meaningful information from these data, we have developed tools for cell identification, cell classification, and spatial analysis. In this review, we discuss these tools and provide examples of their application in various contexts, including ductal carcinoma in situ, tuberculosis, and Alzheimer's disease. We hope the synergy between multiplexed imaging and automated image analysis will drive a new era in anatomic pathology and personalized medicine wherein quantitative spatial signatures are used routinely for more accurate diagnosis, prognosis, and therapeutic selection. Expected final online publication date for the Annual Review of Pathology: Mechanisms of Disease, Volume 17 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.