Morphologic and Molecular Features of Breast Ductal Carcinoma in Situ

Sanati, Souzan

doi:10.1016/j.ajpath.2018.07.031

Cited by 27 publications

(23 citation statements)

References 74 publications

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“…One in three women with a HER2‐positive pure DCIS lesion develops a subsequent HER2‐negative invasive breast cancer (Visser et al , 2019), although the clonal relationship between primary and recurrent lesions was not investigated in that study. Taken together, these observations indicate that HER2 overexpression is more likely to play a role as an instigator of tumour cell proliferation, rather than being a crucial driver of cancer cell invasion (Sanati, 2019). The series of pathogenic and likely pathogenic somatic variants that we describe here yields a wide range of potential alternative drivers of cancer cell proliferation and invasion.…”

Section: Discussionmentioning

confidence: 98%

Somatic mutations and copy number variations in breast cancers with heterogeneous HER2 amplification

et al. 2020

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Intratumour heterogeneity fuels carcinogenesis and allows circumventing specific targeted therapies. HER2 gene amplification is associated with poor outcome in invasive breast cancer. Heterogeneous HER2 amplification has been described in 5–41% of breast cancers. Here, we investigated the genetic differences between HER2‐positive and HER2‐negative admixed breast cancer components. We performed an in‐depth analysis to explore the potential heterogeneity in the somatic mutational landscape of each individual tumour component. Formalin‐fixed, paraffin‐embedded breast cancer tissue of ten patients with at least one HER2‐negative and at least one HER2‐positive component was microdissected. Targeted next‐generation sequencing was performed using a customized 53‐gene panel. Somatic mutations and copy number variations were analysed. Overall, the tumours showed a heterogeneous distribution of 12 deletions, 9 insertions, 32 missense variants and 7 nonsense variants in 26 different genes, which are (likely) pathogenic. Three splice site alterations were identified. One patient had an EGFR copy number gain restricted to a HER2‐negative in situ component, resulting in EGFR protein overexpression. Two patients had FGFR1 copy number gains in at least one tumour component. Two patients had an 8q24 gain in at least one tumour component, resulting in a copy number increase in MYC and PVT1. One patient had a CCND1 copy number gain restricted to a HER2‐negative tumour component. No common alternative drivers were identified in the HER2‐negative tumour components. This series of 10 breast cancers with heterogeneous HER2 gene amplification illustrates that HER2 positivity is not an unconditional prerequisite for the maintenance of tumour growth. Many other molecular aberrations are likely to act as alternative or collaborative drivers. This study demonstrates that breast carcinogenesis is a dynamically evolving process characterized by a versatile somatic mutational profile, of which some genetic aberrations will be crucial for cancer progression, and others will be mere ‘passenger’ molecular anomalies.

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Section: Discussionmentioning

confidence: 98%

Somatic mutations and copy number variations in breast cancers with heterogeneous HER2 amplification

et al. 2020

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“…Detection of DCIS is of exceptional value because this lesion is a non-obligate precursor of invasive breast carcinoma (IBC). Diagnosis of DCIS indicates a 10 times higher risk of development of IBC if left untreated 14 .…”

Section: Ductal Carcinoma In Situ (Dcis)mentioning

confidence: 99%

Assessment of Ki-67 proliferation index with deep learning in DCIS (ductal carcinoma in situ)

Fuławka¹,

Błaszczyk

Tabakov

et al. 2021

Preprint

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The proliferation index (PI) is crucial in histopathologic diagnostics, in particular tumors. It is calculated based on Ki-67 protein expression by immunohistochemistry. PI is routinely evaluated by a visual assessment of the sample by a pathologist. However, this approach is far from ideal due to its poor intra- and interobserver variability and time-consuming. These factors force the community to seek out more precise solutions. Virtual pathology as being increasingly popular in diagnostics, armed with artificial intelligence, may potentially address this issue. The proposed solution calculates the Ki-67 proliferation index by utilizing a deep learning model and fuzzy-set interpretations for hot-spots detection. The obtained region-of-interest is then used to segment relevant cells via classical methods of image processing. The index value is approximated by relating the total surface area occupied by immunopositive cells to the total surface area of relevant cells. The achieved results are compared to the manual calculation of the Ki-67 index made by a domain expert. To increase results reliability, we trained several models in a 3-fold manner and compared the impact of different hyper-parameters. Our best-proposed method estimates PI with 0,026 mean absolute error, which gives a significant advantage over the current state-of-the-art solution.

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“…It may therefore be possible to provide stronger evidence for the so-called low-grade and high-grade pathway of breast cancer progression, wherein low-grade DCIS gives rise to less aggressive low-grade invasive carcinoma, and high-grade DCIS gives rise to more aggressive high-grade invasive carcinoma. 50,99 Implementation of this novel research strategy in a combined multicenter international effort could force a major breakthrough in the research on DCIS biology and its natural progression.…”

Section: Practical Implementation Of the Alternative Research Strategymentioning

confidence: 99%

“…Inclusion of a sufficiently large number of patients does not only allow stratification according to type of adjuvant treatment, but it would also allow stratification according to DCIS grade and other clinicopathological parameters. It may therefore be possible to provide stronger evidence for the so‐called low‐grade and high‐grade pathway of breast cancer progression, wherein low‐grade DCIS gives rise to less aggressive low‐grade invasive carcinoma, and high‐grade DCIS gives rise to more aggressive high‐grade invasive carcinoma . Implementation of this novel research strategy in a combined multicenter international effort could force a major breakthrough in the research on DCIS biology and its natural progression.…”

Section: Introductionmentioning

confidence: 99%

A retrospective alternative for active surveillance trials for ductal carcinoma in situ of the breast

Bockstal

Agahozo

Koppert

et al. 2019

Intl Journal of Cancer

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Ductal carcinoma in situ (DCIS) of the breast is a nonobligate precursor of invasive breast cancer, accounting for 20 % of screen‐detected breast cancers. Little is known about the natural progression of DCIS because most patients undergo surgery upon diagnosis. Many DCIS patients are likely being overtreated, as it is believed that only around 50 % of DCIS will progress to invasive carcinoma. Robust prognostic markers for progression to invasive carcinoma are lacking. In the past, studies have investigated women who developed a recurrence after breast‐conserving surgery (BCS) and compared them with those who did not. However, where there is no recurrence, the patient has probably been adequately treated. The present narrative review advocates a new research strategy, wherein only those patients with a recurrence are studied. Approximately half of the recurrences are invasive cancers, and half are DCIS. So‐called “recurrences” are probably most often the result of residual disease. The new approach allows us to ask: why did some residual DCIS evolve to invasive cancers and others not? This novel strategy compares the group of patients that developed in situ recurrence with the group of patients that developed invasive recurrence after BCS. The differences between these groups could then be used to develop a robust risk stratification tool. This tool should estimate the risk of synchronous and metachronous invasive carcinoma when DCIS is diagnosed in a biopsy. Identification of DCIS patients at low risk for developing invasive carcinoma will individualize future therapy and prevent overtreatment.

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Morphologic and Molecular Features of Breast Ductal Carcinoma in Situ

Cited by 27 publications

References 74 publications

Somatic mutations and copy number variations in breast cancers with heterogeneous HER2 amplification

Somatic mutations and copy number variations in breast cancers with heterogeneous HER2 amplification

Assessment of Ki-67 proliferation index with deep learning in DCIS (ductal carcinoma in situ)

A retrospective alternative for active surveillance trials for ductal carcinoma in situ of the breast

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