Dataset Information

Collagen Alignment as a Predictor of Recurrence after Ductal Carcinoma In Situ.

ABSTRACT: Background: Collagen fibers surrounding breast ducts may influence breast cancer progression. Syndecan-1 interacts with constituents in the extracellular matrix, including collagen fibers, and may contribute to cancer cell migration. Thus, the orientation of collagen fibers surrounding ductal carcinoma in situ (DCIS) lesions and stromal syndecan-1 expression may predict recurrence.Methods: We evaluated collagen fiber alignment and syndecan-1 expression in 227 women diagnosed with DCIS in 1995 to 2006 followed through 2014 (median, 14.5 years; range, 0.7-17.6). Stromal collagen alignment was evaluated from diagnostic tissue slides using second harmonic generation microscopy and fiber analysis software. Univariate analysis was conducted using ?2 tests and ANOVA. The association between collagen alignment z-scores, syndecan-1 staining intensity, and time to recurrence was evaluated using HRs and 95% confidence intervals (CIs).Results: Greater fiber angles surrounding DCIS lesions, but not syndecan-1 staining intensity, were related to positive HER2 (P = 0.002) status, comedo necrosis (P = 0.03), and negative estrogen receptor (P = 0.002) and progesterone receptor (P = 0.02) status. Fiber angle distributions surrounding lesions included more angles closer to 90 degrees than normal ducts (P = 0.06). Collagen alignment z-scores for DCIS lesions were positively related to recurrence (HR = 1.25; 95% CI, 0.84-1.87 for an interquartile range increase in average fiber angles).Conclusions: Although collagen alignment and stromal syndecan-1 expression did not predict recurrence, collagen fibers perpendicular to the duct perimeter were more frequent in DCIS lesions with features typical of poor prognosis.Impact: Follow-up studies are warranted to examine whether additional features of the collagen matrix may more strongly predict patient outcomes. Cancer Epidemiol Biomarkers Prev; 27(2); 138-45. ©2017 AACR.

SUBMITTER: Conklin MW

PROVIDER: S-EPMC5809285 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Collagen Alignment as a Predictor of Recurrence after Ductal Carcinoma In Situ.

Conklin Matthew W MW Gangnon Ronald E RE Sprague Brian L BL Van Gemert Lisa L Hampton John M JM Eliceiri Kevin W KW Bredfeldt Jeremy S JS Liu Yuming Y Surachaicharn Nuntida N Newcomb Polly A PA Friedl Andreas A Keely Patricia J PJ Trentham-Dietz Amy A

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20171115 2

Background: Collagen fibers surrounding breast ducts may influence breast cancer progression. Syndecan-1 interacts with constituents in the extracellular matrix, including collagen fibers, and may contribute to cancer cell migration. Thus, the orientation of collagen fibers surrounding ductal carcinoma in situ (DCIS) lesions and stromal syndecan-1 expression may predict recurrence.Methods: We evaluated collagen fiber alignment and syndecan-1 expression in 227 women diagnosed ...[more]

PMID: 29141852

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Project description:BackgroundBreast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mastectomy or adjuvant radiation can reduce recurrence risk, there are significant concerns regarding patient over-/under-treatment. Current clinicopathological markers are insufficient to accurately assess the recurrence risk. To address this issue, we developed a novel machine learning (ML) pipeline to predict risk of ipsilateral recurrence using digitized whole slide images (WSI) and clinicopathologic long-term outcome data from a retrospectively collected cohort of DCIS patients (n = 344) treated with lumpectomy at Nottingham University Hospital, UK.MethodsThe cohort was split case-wise into training (n = 159, 31 with 10-year recurrence) and validation (n = 185, 26 with 10-year recurrence) sets. The sections from primary tumors were stained with H&E, then digitized and analyzed by the pipeline. In the first step, a classifier trained manually by pathologists was applied to digital slides to annotate the areas of stroma, normal/benign ducts, cancer ducts, dense lymphocyte region, and blood vessels. In the second step, a recurrence risk classifier was trained on eight select architectural and spatial organization tissue features from the annotated areas to predict recurrence risk.ResultsThe recurrence classifier significantly predicted the 10-year recurrence risk in the training [hazard ratio (HR) = 11.6; 95% confidence interval (CI) 5.3-25.3, accuracy (Acc) = 0.87, sensitivity (Sn) = 0.71, and specificity (Sp) = 0.91] and independent validation [HR = 6.39 (95% CI 3.0-13.8), p < 0.0001;Acc = 0.85, Sn = 0.5, Sp = 0.91] cohorts. Despite the limitations of our cohorts, and in some cases inferior sensitivity performance, our tool showed superior accuracy, specificity, positive predictive value, concordance, and hazard ratios relative to tested clinicopathological variables in predicting recurrences (p < 0.0001). Furthermore, it significantly identified patients that might benefit from additional therapy (validation cohort p = 0.0006).ConclusionsOur machine learning-based model fills an unmet clinical need for accurately predicting the recurrence risk for lumpectomy-treated DCIS patients.

Project description:ImportancePathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer strongly correlates with overall survival and has become the standard end point in neoadjuvant trials. However, there is controversy regarding whether the definition of pCR should exclude or permit the presence of residual ductal carcinoma in situ (DCIS).ObjectiveTo examine the association of residual DCIS in surgical specimens after neoadjuvant chemotherapy for breast cancer with survival end points to inform standards for the assessment of pathologic complete response.Design, setting, and participantsThe study team analyzed the association of residual DCIS after NAC with 3-year event-free survival (EFS), distant recurrence-free survival (DRFS), and local-regional recurrence (LRR) in the I-SPY2 trial, an adaptive neoadjuvant platform trial for patients with breast cancer at high risk of recurrence. This is a retrospective analysis of clinical specimens and data from the ongoing I-SPY2 adaptive platform trial of novel therapeutics on a background of standard of care for early breast cancer. I-SPY2 participants are adult women diagnosed with stage II/III breast cancer at high risk of recurrence.InterventionsParticipants were randomized to receive taxane and anthracycline-based neoadjuvant therapy with or without 1 of 10 investigational agents, followed by definitive surgery.Main outcomes and measuresThe presence of DCIS and EFS, DRFS, and LRR.ResultsThe study team identified 933 I-SPY2 participants (aged 24 to 77 years) with complete pathology and follow-up data. Median follow-up time was 3.9 years; 337 participants (36%) had no residual invasive disease (residual cancer burden 0, or pCR). Of the 337 participants with pCR, 70 (21%) had residual DCIS, which varied significantly by tumor-receptor subtype; residual DCIS was present in 8.5% of triple negative tumors, 15.6% of hormone-receptor positive tumors, and 36.6% of ERBB2-positive tumors. Among those participants with pCR, there was no significant difference in EFS, DRFS, or LRR based on presence or absence of residual DCIS.Conclusions and relevanceThe analysis supports the definition of pCR as the absence of invasive disease after NAC regardless of the presence or absence of DCIS.Trial registrationClinicalTrials.gov Identifier NCT01042379.

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Collagen Alignment as a Predictor of Recurrence after Ductal Carcinoma In Situ.

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Collagen Alignment as a Predictor of Recurrence after Ductal Carcinoma <i>In Situ</i>.

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