A Competing Nomogram to Predict Survival Outcomes in Invasive Micropapillary Breast Cancer

Association of molecular subtypes and treatment with survival in invasive micropapillary breast cancer: an analysis of the Surveillance, Epidemiology, and End Results database

BACKGROUND

This study aims to examine the features, treatments, and survival of invasive micropapillary carcinoma (IMPC) according to different molecular subtypes.

METHODS

In this cohort study, data between 2010 and 2018 were retrospectively reviewed from the Surveillance, Epidemiology, and End Results database. Molecular subtypes were categorized into four varieties: hormone receptor (HR)+/HER2- (Luminal A), HR+/HER2+ (Luminal B), HR-/HER2- [triple-negative (TN)], and HR-/HER2+ (HER2 enriched).

RESULTS

In this study, 1,180 IMPC patients were included, with 99 patients (8.39%) of the 1,180 patients having an overall mortality, and 53 patients (53.54%) of the 99 patients having a breast cancer-specific mortality. The follow-up duration was 40.00 (18.50, 61.00) months. TN molecular subtype was associated with worse OS and BCSS in IMPC patients. Treatment of chemotherapy, radiation, and combination therapy were associated with better survival in HR+/HER2+ molecular subtype and HR+/HER2- molecular subtype. However, in HR-/HER2- molecular subtype, treatment of chemotherapy was associated with a poor BCSS, and treatment of radiation was not associated with OS and BCSS. Surgery treatment was not associated with survival in HR+/HER2+ molecular subtype and HR+/HER2- molecular subtype. However, surgery treatment of mastectomy was associated with better OS in HR-/HER2- molecular subtype (P < 0.05).

CONCLUSION

The prognosis of IMPC was significantly influenced by different molecular subtypes. Chemotherapy and radiotherapy are beneficial in HR+/HER2+ and HR+/HER2- patients. However, they should be used with caution in HR-/HER2- (TN) patients.

A web-based novel model for predicting prognostic value in patients with invasive micropapillary carcinoma in breast cancer: a real-world data retrospective cohort study

Invasive micropapillary carcinoma (IMPC) accounts for less than 2% of all invasive breast cancers and usually associates with poor survival, so we investigated the prognostic factors for IMPC using a large population-based database and designed a web-based novel model. Clinicopathological prognostic factors were evaluated using the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate Cox regression analysis was performed to evaluate the prognostic value of variables on the overall survival. A web-based nomogram was finally constructed to predict the survival probability. The model was validated in an external dataset. A web-based model, combined with age, radiation, clinical stage, and hormone receptor (HR) immunochemistry status four prognostic factors, was constructed. The C-index (0.714, 95% CI 0.683-0.741), calibration curves, and decision curves showed that this model was superior in prediction. By determining the cut-off values, high-risk group and low-risk group were divided. The Kaplan-Meier survival curves showed that these two groups had significantly different survival rates (P < 0.0001). The result of C-index, calibration curves, and Kaplan-Meier survival curves were consistent in the validation cohort. The novel nomogram with four risk factors resulted in accurate prognostic prediction for IMPC.

Nomogram predicting overall prognosis for invasive micropapillary carcinoma of the breast: a SEER-based population study

OBJECTIVES

The prognosis of invasive micropapillary carcinoma (IMPC) of the breast is determined by many clinicopathological factors. This study aims to identify prognostic factors and develop reliable nomogram to predict the overall survival (OS) in patients with IMPC.

DESIGN

Log-rank test and Cox proportional hazards analysis were used to identify variables and construct a nomogram based on the training cohort. C-index and calibration curves were performed to evaluate the performance of the model in the training cohort and validation cohorts.

SETTING

We collected the patient data from the Surveillance, Epidemiology and End Results (SEER) database. This database holds data related to the cancer incidence from 18 population-based cancer registries in the USA.

PARTICIPANTS

The SEER database was used to screen 754 eligible patients as the study cohort. The whole cohort was randomly divided into a training cohort (n=377) and a validation cohort (n=377).

RESULTS

Age at diagnosis, hormone receptors, number of positive regional lymph nodes and clinical stage were independent prognostic factors for patients with IMPC. The calibration curves presented excellent consistency between the actual and nomogram-predict survival probabilities in the training and validation cohorts. The C-index values of the nomogram were 0.794 and 0.774 for OS in the training and validation cohorts, respectively.

CONCLUSIONS

The novel nomogram provides new insights of the risk of each prognostic factor and can assist doctors in predicting the 1-year, 3-year and 5-year OS in patients with IMPC.

Development and validation of nomograms to predict survival in patients with invasive micropapillary carcinoma of the breast

OBJECTIVES

The present study aimed to develop and validate nomograms to predict the survival of patients with breast invasive micropapillary carcinoma (IMPC) to aid objective decision-making.

DESIGN

Prognostic factors were identified using Cox proportional hazards regression analyses and used to construct nomograms to predict overall survival (OS) and breast cancer-specific survival (BCSS) at 3 and 5 years. Kaplan-Meier analysis, calibration curves, the area under the curve (AUC) and the concordance index (C-index) evaluated the nomograms' performance. Decision curve analysis (DCA), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used to compare the nomograms with the American Joint Committee on Cancer (AJCC) staging system.

SETTING

Patient data were collected from the Surveillance, Epidemiology, and End Results (SEER) database. This database holds data related to the incidence of cancer acquired from 18 population-based cancer registries in the US.

PARTICIPANTS

We ruled out 1893 patients and allowed the incorporation of 1340 patients into the present study.

RESULTS

The C-index of the AJCC8 stage was lower than that of the OS nomogram (0.670 vs 0.766) and the OS nomograms had higher AUCs than the AJCC8 stage (3 years: 0.839 vs 0.735, 5 years: 0.787 vs 0.658). On calibration plots, the predicted and actual outcomes agreed well, and DCA revealed that the nomograms had better clinical utility compared with the conventional prognosis tool. In the training cohort, the NRI for OS was 0.227, and for BCSS was 0.182, while the IDI for OS was 0.070, and for BCSS was 0.078 (both p<0.001), confirming its accuracy. The Kaplan-Meier curves for nomogram-based risk stratification showed significant differences (p<0.001).

CONCLUSIONS

The nomograms showed excellent discrimination and clinical utility to predict OS and BCSS at 3 and 5 years, and could identify high-risk patients, thus providing IMPC patients with personalised treatment strategies.

Integrated bioinformatics analysis of microarray data from the GEO database to identify the candidate genes linked to poor prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common cancers with high morbidity and mortality and remains a crucial factor endangering human health.

OBJECTIVE

This study aimed to elucidate the potential treatment target and prognostic biomarker in patients with LUAD through a comprehensive bioinformatics analysis.

METHODS

The three public microarray datasets of GSE118370, GSE116959, and GSE43767 were obtained from the GEO data resource. The DEGs were explored between LUAD and non-malignant samples using GEO2R online tool in GEO data resource. GO along with KEGG analysis of DEGs were examined using WebGestalt tool. The STRING web resource was employed to develop the PPI network of DEGs, whereas Cytoscape software was employed to perform module analysis. Finally, the mRNA, protein expression along with survival analysis of hub genes were explored via GEPIA, HPA along with Kaplan-Meier plotter web resource, respectively.

RESULTS

Only 82 upregulated and 105 downregulated DEGs were found among the three datasets. Further, GO analysis illustrated that 187 DEGs were primary enriched in extracellular structure organization, tube development along with cell adhesion. The KEGG enrichments showed that these DEGs were primary linked to leukocyte transendothelial migration, vascular smooth muscle contraction along with ECM-receptor interaction. Among the 187 DEGs, the 10 hub genes (P4HB, SPP1, CP, GOLM1, COL1A1, MMP9, COL10A1, APOA1, COL4A6, and TIMP1) were identified. The mRNA along with protein levels of hub genes in LUAD tissues were further verified by Oncomine, UCSC Xena, GEPIA and HPA databases. Additionally, overall survival curves illustrated that LUAD patients with the higher levels of P4HB, SPP1, COL1A1, and MMP9 were dramatically linked to shorter overall survival.

CONCLUSIONS

The current study identified DEGs candidate genes (P4HB, SPP1, COL1A1, and MMP9) and pathways in LUAD using bioinformatics analysis, which could enhance our understanding of pathogenesis along with underlying molecular events in LUAD, and these hub genes and pathways may help provide candidate treatment targets for LUAD.

Analysis of Prognostic Factors and Construction of Prognostic Models for Invasive Micropapillary Carcinoma of the Breast

OBJECTIVE

To compare and analyze the clinical characteristics of invasive micropapillary carcinoma (IMPC) of the breast (IMPC-B) and invasive ductal carcinoma (IDC) of the breast (IDC-B) and establish a prognostic model of IMPC-B.

METHODS

We retrospectively analyzed data for patients diagnosed with breast cancer in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2018 and screened 581 patients with IMPC and 1325 patients with IDC. We compared age, race, laterality, tumor site, histological grade, type of surgery, radiation, chemotherapy, whether the first primary tumor, T stage, N stage, M stage, and molecular type between IMPC-B and IDC-B and draw survival curves of IMPC-B and IDC-B. The relationship between clinical factors and prognosis was investigated by univariate analysis using the Log-rank test and multivariate analysis of the Cox proportional hazards regression model. A risk scoring model was constructed based on independent risk factors to distinguish high-risk and low-risk patients; in addition, a nomogram was created to predict patient survival.

RESULTS

There were differences between the two groups in the age of onset, race, tumor site, histological grade, type of surgery, N stage, and molecular type (p < 0.05). Overall survival was decreased in IMPC-B compared with IDC-B (p < 0.05). The prognosis of IMPC-B was significantly correlated with histological grade, whether the first primary tumor, type of surgery, radiotherapy, chemotherapy, T stage, and N stage. Based on the relationship between the above factors and overall survival prognosis, the risk score model we constructed can effectively distinguish high-risk and low-risk patients (p < 0.05). The established nomogram had better performance in predicting survival in patients with IMPC-B (C - index = 0.78).

CONCLUSION

IMPC-B has a worse prognosis than IDC-B, with earlier age of onset, higher histological grade, and later N stage, and luminal breast cancer is the main type. The nomogram can well predict the prognosis of patients with IMPC-B, which has a high clinical reference value and provides a scientific basis for clinical treatment.

Nomogram for predicting overall survival in patients with invasive micropapillary carcinoma after breast-conserving surgery: A population-based analysis

Background

Due to the loss of prediction of overall survival (OS) for patients with invasive micropapillary carcinoma (IMPC) after breast-conserving surgery (BCS), this study aimed to construct a nomogram for predicting OS in IMPC patients after BCS.

Methods

In total, 481 eligible cases staged 0-III IMPC from 2000 to 2016 were retrieved from the SEER database. A nomogram was built based on the variables selected by LASSO regression to predict the 3-year and 5-year probabilities of OS.

Results

A total of 336 patients were randomly assigned to the training cohort and 145 cases in the validation cohort. The LASSO regression revealed that six variables (age at diagnosis, AJCC stage, marital status, ER status, PR status, and chemotherapy) were predictive variables of OS, and then a nomogram model and an easy-to-use online tool were constructed. The C-indices 0.771 in the training cohort and 0.715 in the validation cohort suggested the robustness of the model. The AUC values for 3-year and 5-year OS in the training cohort were 0.782, 0.790, and 0.674, and 0.682 in the validation cohort, respectively. Based on the cutoff values of 147.23 and 222.44 scores calculated by X-tile analysis, participants in the low-risk group (≤147.23 scores) had a more favorable OS in comparison with those in the medium (>147.23, but <222.44 scores)- and high-risk groups (≥222.44 scores).

Conclusions

By risk stratification, this model is expected to provide a precise and personalized prediction of the cumulative risk and guide treatment decision-making in improving OS strategies for IMPC patients.

Micropapillary Breast Carcinoma: From Molecular Pathogenesis to Prognosis

Invasive micropapillary carcinoma (IMPC) of the breast is an infrequent type of breast cancer often discussed for its potency for lymphovascular invasion and difficulty in accurate imaging estimation. Micropapillary carcinomas are noted to be present as larger tumors, of higher histological grade and a notably higher percentage of disease-positive lymph nodes. Hormonal and HER-2 positivity in IMPC is also commoner when compared to other NST carcinomas. IMPC occurs either as a pure form or more often as a component of mixed Non-Specific Type (NST) carcinoma. The latest data suggest that despite having comparable survival rates to other histological subtypes of breast carcinoma, effective surgical treatment often requires extended surgical margins and vigilant preoperative axillary staging due to an increased incidence of lymph node invasion, and locoregional recurrence. Moreover, the presence of micropapillary in situ components within tumors also seems to alter tumor aggression and influence the nodal disease stage. In this review, we present an overview of the current literature of micropapillary carcinoma of the breast from biology to prognosis, focusing on biological differences and treatment.

Cell polarity and cell adhesion associated gene expression differences between invasive micropapillary and no special type breast carcinomas and their prognostic significance

Invasive micropapillary carcinoma of the breast (IMPC) has been in the focus of several studies given its specific histology and clinicopathological course. We analysed mRNA expression profiles and the prognostic value of 43 genes involved in cell polarity, cell-adhesion and epithelial-mesenchymal transition (EMT) in IMPC tumors and compared them to invasive breast carcinomas of no special type (IBC-NST). IMPCs (36 cases), IBC-NSTs (36 cases) and mixed IMPC-IBC NSTs (8 cases) were investigated. mRNA expression level of selected genes were analysed using the NanoString nCounter Analysis System. Distant metastases free survival (DMFS) intervals were determined. Statistical analysis was performed using Statistica 13.5 software. Twelve genes showed significantly different expression in the IMPC group. There was no difference in DMFS according to histological type (IBC-NST vs. IMPC). High CLDN3, PALS1 and low PAR6 expression levels in the entire cohort were associated with shorter DMFS, and PALS1 was proven to be grade independent prognostic factor. Positive lymph node status was associated with higher levels of AKT1 expression. Differences in gene expression in IMPC versus IBC-NST may contribute to the unique histological appearance of IMPCs. No marked differences were observed in DMFS of the two groups. Altered gene expression in the mTOR signaling pathway in both tumor subtypes highlights the potential benefit from AKT/mTOR inhibitors in IMPCs similarly to IBC-NSTs.

Construction and Validation of Nomograms Predicting Survival in Triple-Negative Breast Cancer Patients of Childbearing Age

Background

Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer with poorest clinical outcomes. Patients of childbearing age have a higher probability of TNBC diagnosis, with more demands on maintenance and restoration of physical and psychosocial function. This study aimed to design effective and comprehensive nomograms to predict survival in these patients.

Methods

We used the SEER database to identify patients with TNBC aged between 18 and 45 and randomly classified these patients into a training (n=2,296) and a validation (n=2,297) cohort. Nomograms for estimating overall survival (OS) and breast cancer-specific survival (BCSS) were generated based on multivariate Cox proportional hazards models and competing-risk models in the training cohort. The performances of the nomograms were quantified in the validation cohort using calibration curves, time-dependent receiver operating characteristic (ROC) curves and Harrell’s concordance index (C-index).

Results

A total of 4,593 TNBC patients of childbearing age were enrolled. Four prognostic factors for OS and six for BCSS were identified and incorporated to construct nomograms. In the validation cohort, calibration curves showed excellent agreement between nomogram-predicted and actual survival data. The nomograms also achieved relatively high Harrell’s C-indexes and areas under the time-dependent ROC curves for estimating OS and BCSS in both training and validation cohorts.

Conclusions

Independent prognostic factors were identified, and used to develop nomograms to predict OS and BCSS in childbearing-age patients with TNBC. These models could enable individualized risk estimation and risk-adapted treatment for these patients.

HER2 Immunohistochemistry in Invasive Micropapillary Breast Carcinoma: Complete Assessment of an Incomplete Pattern

CONTEXT.—

Invasive micropapillary carcinoma (IMPC) is a rare variant of breast carcinoma, composed of avascular morula-like tumor clusters surrounded by stromal spaces, which can affect the HER2 immunohistochemical (IHC) staining pattern. The 2013 American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) HER2 testing guideline suggests moderate to intense but incomplete (basolateral) staining be considered equivocal.

OBJECTIVES.—

To perform a detailed assessment of HER2 IHC staining patterns in IMPC.

DESIGN.—

Hematoxylin-eosin and HER2 IHC slides were retrospectively reviewed to assess the morphology and HER2 IHC characteristics of IMPC. The 2018 ASCO/CAP guideline was applied.

RESULTS.—

The cohort consisted of 187 IMPCs from 181 patients with median age of 58 years. Homogeneous (≥90%) micropapillary component was found in 40% (75 of 187) of cases. Receptor profile was as follows: 75% (140 of 187) ER+ HER2-, 19% (37 of 187) ER+ HER2+, 4% (7 of 187) ER- HER2+, and 2% (3 of 187) ER- HER2-. Of 26 cases with HER2 IHC 3+, 65% (17 of 26) showed a basolateral staining pattern with strong intensity. HER2 fluorescence in situ hybridization (FISH) showed amplification in 26% (17 of 66) of HER2 IHC equivocal cases: 76% (13 of 17) showed basolateral staining pattern and 24% (4 of 17) complete staining, with weak to moderate (2), moderate (14), or moderate to strong (1) intensity.

CONCLUSIONS.—

The most frequent staining pattern was basolateral, seen in 49% of cases, including 65% HER2 IHC positive and 76% HER2 IHC equivocal/FISH amplified. If a basolateral pattern and weak to moderate staining is observed in IMPC, alternative testing should be performed to confirm the HER2 status.

Clinicopathological characteristics and prognosis of breast cancer with special histological types: A surveillance, epidemiology, and end results database analysis

Objectives

To explore the clinicopathological features and prognosis of breast cancer with special histological types.

Materials and methods

The information of breast cancer patients was obtained from the Surveillance, Epidemiology, and End Results (SEER) database (2010–2016). Comparative analyses were performed to explore the difference in clinicopathological characteristics and propensity score matching (PSM) was used to weaken the effects from clinical profiles. Survival analysis was conducted to investigate the prognostic effects from histological types, and the prognostic factors of this group of patients were identified with the univariate COX proportional model.

Results

A total of 242863 breast cancer patients were eligible, of which 230213 individuals were ductal breast cancer (IDC) and 12650 individuals were special breast lesions, respectively. Comparatively, special breast cancer had a lower histological grade, a smaller tumor size, a lower proportion of nodal involvement and distant metastasis, in addition to a higher proportion of triple-negative subtype. The overall prognosis of special histological breast cancer was comparable to IDC, while the survival of HER2 enriched breast cancer was in favor of special breast cancer. With the PSM performance, the prognosis exhibited an inferior profile in the metaplastic breast cancer and was significantly favorable to apocrine, medullary, micropapillary, and papillary breast cancer.

Conclusion

This study revealed that the special histological breast cancer presented distinct clinicopathological characteristics and great heterogeneity in the prognosis among diverse histological subtypes.

•

Breast cancer is a heterogenous disease with diverse histological subtypes.

•

Special histological breast cancer exhibits distinct clinicopathological profiles.

•

Prognosis of special histological breast cancer is profoundly heterogenous.

•

Histological subtype is an independent prognostic indicator of breast cancer.