Comparison of clinical outcomes between luminal invasive ductal carcinoma and luminal invasive lobular carcinoma

Adachi, Yayoi; Ishiguro, Junko; Kotani, Hirokazu; Hisada, Tomoka; Ichikawa, Mari; Gondo, Naomi; Yoshimura, Akinobu; Kondo, Naoto; Hattori, Masao; Sawaki, Masataka; Fujita, Takashi; Kikumori, Toyone; Yatabe, Yasushi; Kodera, Yasuhiro; Iwata, Hiroji

doi:10.1186/s12885-016-2275-4

Cited by 91 publications

(71 citation statements)

References 18 publications

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“…Loibl et al observed that patients with ILC had a low chance of obtaining a pCR although it was not well correlated with further outcome [20]. In another study focusing on the ER+/HER2- subgroup, patients with ILC had shorter disease-free survival and overall survival than patients with IDC [21], in congruence with our data.…”

Section: Discussionsupporting

confidence: 86%

18FDG-PET/CT for predicting the outcome in ER+/HER2- breast cancer patients: comparison of clinicopathological parameters and PET image-derived indices including tumor texture analysis

et al. 2017

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BackgroundThis study investigated the value of some clinicopathological parameters and 18 F-fluorodeoxyglucose-positron emission tomography/computed tomography (18FDG-PET/CT) indices, including textural features, to predict event-free survival (EFS) in estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) locally advanced breast cancer (BC) patients.MethodsFDG-PET/CT indices and clinicopathological parameters were assessed before neoadjuvant chemotherapy (NAC). After completion of chemotherapy, all patients had breast surgery with axillary lymph node dissection, followed by radiation therapy and endocrine therapy for 5 years. EFS was estimated using the Kaplan-Meier method. A Cox proportional hazard regression model was used for multivariate analysis.ResultsOne hundred forty-three consecutive patients with stage II–III ER+/HER2- BC and without distant metastases at baseline PET were included. High standardized uptake values (SUVs), were associated with shorter EFS (HR = 3.51, P < 0.01 for SUVmax; HR = 2.76, P = 0.02 for SUVmean; and HR = 4.40 P < 0.01 for SUVpeak). Metabolically active tumor volume (MATV, HR = 3.47, P < 0.01) and total lesion glycolysis (TLG, HR = 3.10, P < 0.01) were also predictive of EFS. Homogeneity was not predictive (HR = 2.27, P = 0.07) and entropy had weak prediction (HR = 2.89, P = 0.02). Among clinicopathological parameters, EFS was shorter in progesterone receptor (PR)-negative tumor (vs. PR-positive tumor; HR = 3.25, P < 0.01); histology was predictive of EFS (lobular vs. ductal invasive carcinoma; HR = 3.74, P = 0.01) but not tumor grade (grade 3 vs. grade 1–2; HR = 1.64, P = 0.32). Pathological complete response after NAC was not correlated to the risk of relapse. Three parameters remained significantly associated with EFS in multivariate analysis. MATV (HR = 1.01, P < 0.01), progesterone receptor expression (HR = 2.90, P = 0.03) and tumor histology (HR = 3.80, P = 0.02).ConclusionsBaseline PET parameters measured before neoadjuvant treatment have prognostic values in ER+/HER2- locally advanced breast cancer patients. After multivariate analysis, metabolically active tumor volume remains significant while textural analysis of PET images is not of added value. Considering histopathological parameters, our study shows that patients with PR-negative or lobular invasive tumor have poorer prognosis than patients with PR-positive or ductal carcinoma, respectively.

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Section: Discussionsupporting

confidence: 86%

18FDG-PET/CT for predicting the outcome in ER+/HER2- breast cancer patients: comparison of clinicopathological parameters and PET image-derived indices including tumor texture analysis

et al. 2017

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“…This is consistent with the observation that ductal tumors tend to be more aggressive and are predictive of poorer outcome19, although significance was lost when adjusted for stage, ER status, or both, which may also be consistent with other studies that have shown that lobular tumors can have similar or even worse prognosis than ductal tumors when lobular subtypes are assessed51. The 46 selected genes for the final model included E-cadherin (CDH1), which has long been recognized to be differentially expressed between lobular and ductal tumors.…”

Section: Discussionsupporting

confidence: 91%

Molecular Classification of Lobular Carcinoma of the Breast

Zuo

Huang

et al. 2017

Sci Rep

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The morphology of breast tumors is complicated and diagnosis can be difficult. We present here a novel diagnostic model which we validate on both array-based and RNA sequencing platforms which reliably distinguishes this tumor type across multiple cohorts. We also examine how this molecular classification predicts sensitivity to common chemotherapeutics in cell-line based assays. A total of 1845 invasive breast cancer cases in six cohorts were collected, split into discovery and validation cohorts, and a classifier was created and compared to pathological diagnosis, grade and survival. In the validation cohorts the concordance of predicted diagnosis with a pathological diagnosis was 92%, and 97% when inconclusively classified cases were excluded. Tumor-derived cell lines were classified with the model as having predominantly ductal or lobular-like molecular physiologies, and sensitivity of these lines to relevant compounds was analyzed. A diagnostic tool can be created that reliably distinguishes lobular from ductal carcinoma and allows the classification of cell lines on the basis of molecular profiles associated with these tumor types. This tool may assist in improved diagnosis and aid in explorations of the response of lobular type breast tumor models to different compounds.

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“…Therefore, we intended to investigate the relationship between the molecular subtypes proposed by the St. Gallen consensus meeting 2013 and SUVmax of primary breast cancer lesion. Because the pathological and clinical features and FDG avidity of IDC differ from those of invasive lobular carcinoma (ILC) [15], our study specifically enrolled patients with IDC to perform investigations in a homogeneous patients' group.…”

Section: Introductionmentioning

confidence: 99%

Correlation of Molecular Subtypes of Invasive Ductal Carcinoma of Breast with Glucose Metabolism in FDG PET/CT: Based on the Recommendations of the St. Gallen Consensus Meeting 2013

Lee

Bae

Park³

et al. 2016

Nucl Med Mol Imaging

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Purpose This study aimed to investigate the relationship between the SUVmax of primary breast cancer lesions and the molecular subtypes based on the recommendations of the St. Gallen consensus meeting 2013. Methods Clinical records of patients who underwent F-18 FDG PET/CT for initial staging of invasive ductal carcinoma (IDC) of the breast were reviewed. A total of 183 patients were included. SUVmax was correlated with the molecular subtypes defined by the St. Gallen Consensus Meeting 2013, i.e., luminal A-like (LA), luminal B-like HER2 negative (LBHER2-), luminal Blike HER2 positive (LBHER2+), HER2 positive (HER2+), and triple negative (TN), and with the clinicohistopathologic characteristics. Results The molecular subtype was LA in 38 patients, LBHER2-in 72, LBHER2+ in 21, HER2+ in 30, and TN in 22. The mean SUVmax in the LA, LBHER2-, LBHER2+, HER2+, and TN groups were 4.5 ± 2.3, 7.2 ± 4.9, 7.2 ± 4.3, 10.2 ± 5.5, and 8.8 ± 7.1, respectively. Although SUVmax differed significantly among these subtypes (p < 0.001), the values showed a wide overlap. Optimal cut-off SUVmax to differentiate LA from LBHER2-, LBHER2+, HER2+ and TN were 5.9, 5.8, 7.5, and 10.2 respectively, with area under curve (AUC) of 0.648, 0.709, 0.833, and 0.697 respectively. The cut-off value of 5.9 yielded the highest accuracy for differentiation between the LA and non-LA subtypes, with sensitivity, specificity, and AUC of 79.4 %, 57.9 %, and 0.704 respectively. Conclusion The SUVmax showed a significant correlation with the molecular subtype. Although SUVmax measurements could be used along with immunohistochemical analysis for differentiating between molecular subtypes, its application to individual patients may be limited due to the wide overlaps in SUVmax.

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Comparison of clinical outcomes between luminal invasive ductal carcinoma and luminal invasive lobular carcinoma

Cited by 91 publications

References 18 publications

18FDG-PET/CT for predicting the outcome in ER+/HER2- breast cancer patients: comparison of clinicopathological parameters and PET image-derived indices including tumor texture analysis

18FDG-PET/CT for predicting the outcome in ER+/HER2- breast cancer patients: comparison of clinicopathological parameters and PET image-derived indices including tumor texture analysis

Molecular Classification of Lobular Carcinoma of the Breast

Correlation of Molecular Subtypes of Invasive Ductal Carcinoma of Breast with Glucose Metabolism in FDG PET/CT: Based on the Recommendations of the St. Gallen Consensus Meeting 2013

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