Ductal carcinoma in situ: challenges, opportunities, and uncharted waters

Analysis of tumour-infiltrating lymphocytes reveals two new biologically different subgroups of breast ductal carcinoma in situ

Background

Tumour-infiltrating lymphocytes (TILs) have been demonstrated to significantly influence prognosis and response to therapy of invasive breast cancer (IBC). Thus, it has been suggested that TIL density or/and immunophenotype could serve as biomarkers for selection of IBC patients for immunotherapy. However, much less is known about significance of TILs in breast ductal carcinoma in situ (DCIS).

Methods

We retrospectively investigated TIL density and immunophenotype in 96 pure DCIS and 35 microinvasive carcinomas (miCa). TIL density was assessed on H&E-stained breast biopsy sections as the percentage of tumour stromal area occupied by TILs, and classified into 4 grades: 0 (0%–9%), 1 (10–29%), 2 (30–49%) and 3 (50%–100%). TIL immunophenotype was assessed by immunohistochemistry for CD8, CD4, FoxP3, CD38 or CD20.

Results

Compared to pure DCIS, miCa contained significantly more cases with TIL density grade 3 (p = 0.028). Concordantly, CD8+, CD4+ and CD38+ cells were more numerous in miCa than in pure DCIS. In the pure DCIS subgroup with TIL density grades 2 and 3, all TIL subpopulations were more numerous than in the pure DCIS with TIL density grades 0 and 1, however the ratio between T-lymphocytes (CD8+ and CD4+) and B-lymphocytes (CD20+) was significantly lower (p = 0.029). On the other side, this ratio was significantly higher in miCa, in comparison with pure DCIS having TIL density grades 2 and 3 (p = 0.017). By cluster analysis of tumour cell pathobiological features we demonstrated similarity between miCa and the pure DCIS with TIL density grades 2 and 3. The only significant difference between those two categories was in the ratio of T- to B-TILs, higher in miCa.

Conclusion

Results indicate that TIL density level can distinguish 2 biologically different DCIS subgroups, one of which (DCIS with ≥30% TILs, the TIL-rich DCIS) is like miCa. Similarity of TIL-rich pure DCIS and miCa as well as the role of B-lymphocytes in DCIS invasiveness are worth further investigating with regards to the potential development of immunotherapy-based prevention of DCIS progression.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4013-6) contains supplementary material, which is available to authorized users.

A model of immunohistochemical differences between invasive breast cancers and DCIS lesions tested on a consecutive case series of 1248 patients

BACKGROUND

A previous theoretic model (Tumour Biol 2013;34:1-7.) that breast tumor types differ in the relative rate of tissue invasion was elaborated and developed on a consecutive case series.

METHOD

Histologic data of 68 ductal breast cancer in situ (DCIS) and 1180 invasive ductal cancer (IDC) patients were collected and analyzed.

RESULTS

ER+PgR- phenotype was more common in Luminal B2 than among the pooled Luminal A&B1 (p = 0.0002), and more frequent in Luminal B1 than in Luminal A (p = 0.0167). The same phenotype was associated with the age older than 54 years in Luminal B1 and in B2 patients. HER2 type cancers were more frequent in older patients (p = 0.0038).Tumor progression from DCIS to IDC was found 39% faster than the average in Luminal B1 tumors, supporting the clinical importance of this tumor type. A rare combination of low Ki-67 in HER2 type cancers (only 14% of HER2 type cancers) showed very slow transition to IDC (occurring at only 53.55% of average progression rate), while triple-negative cancers progressed faster than the average, despite Ki-67 value (104.63% for low and 114.27% for high Ki-67 tumors).In three tumor types with positive steroid receptors the ER+PgR- phenotype showed slower IDC transition than the ER+PgR+ phenotype of the same tumor type (difference in progression rate was 38% for Luminal A, 46% for Luminal B1 and 67% for Luminal B2 with Ki67 > 14%).Triple-negative tumors in younger patients exceeded the expected average progression rate by 24%, while in HER2 type tumors, the rate of tissue invasion was in younger patients 20% lower than the expected value.

CONCLUSIONS

The relative rate of tissue invasion differed substantialy among our patients. Differences depended on tumor types, steroid expression phenotypes and age. The dysfunctional ERs in the ER+PgR- phenotype showed slower rates of tissue invasion, suggesting that ligand binding to functional breast tumor ERs, beside promoting the PgR expression, possibly also promotes tumor transition to the invasive phase.In triple-negative tumors, an age dependent premenopausal mechanism possibly acted as an accelerator of tissue invasion, while faster tissue invasion by HER2-overexpressed tumors in older patients possibly depended on an unidentified mechanism that takes more time to be acquired, so it was less present in premenopausal patients.

In search of triple-negative DCIS: tumor-type dependent model of breast cancer progression from DCIS to the invasive cancer

This paper is based on the idea that ductal breast cancer in situ (DCIS) precedes the invasive breast cancer (invBC), although the triple-negative invBCs almost lack their DCIS precursor. Reported incidences of breast tumor types in DCIS and in invasive BCs suggest that probabilities of tumor progression might differ among tumor types, and these differences can have some impact on our patients. Reported data from several papers on incidences of the four breast tumor types-luminal A, luminal B, HER2, and triple negative-are used to compare tumor-type incidences for DCIS and for the invasive BC. The pooled distributions differed (Χ (2) = 97.05, p < 0.0001), suggesting a strong selection pressure that reduces the number of triple-negative DCIS lesions at the time of breast tumor diagnosis. Reported shares of DCIS in all newly diagnosed breast cancers range in large screening trials from 9 to 26 %, so in making a population model, three values are arbitrarily chosen: one DCIS out of ten breast cancers (the 10 % share), one DCIS out of seven breast cancers (one seventh or the 14.3 % share), and one out of five (the 20 % share). By using these shares and the pooled data of tumor-type incidences, values are calculated that would be expected from a hypothetical population in which types of DCIS and invasive BC are distributed accordingly to the reported incidences. The model predicts that the shares of breast cancer tumor types in the modeled population (DCIS plus invasive BCs) are 39 % for luminal A, 20 % for luminal B, 11 % for HER2 positive, and 30 % for the triple-negative cancers. Some 59 % of all breast tumors are expected to be hormone receptor positive, and HER2 to be overexpressed in 31 %. Simulated probabilities of tumor progression were used to calculate the number of tumor progression t(1/2) that has passed before the time of diagnosis. Calculated relative t(1/2) durations in the modeled population suggest that the triple-negative DCIS cases were fastest in tumor progression, three times faster than the HER2-positive tumors and near twice as fast as luminal A. Luminal A is the model slower than luminal B DCIS, suggesting that although their progression depends on estrogen exposure, HER2 overexpression in luminal B tumors adds some speed in tumor progression. The model results suggest that quick tumor progression might be the main feature of the triple-negative breast tumors, leading to seldom triple-negative DCIS at the time of breast cancer diagnosis. Applying approach of the presented model to the real data from a well-defined population seems warranted.