Dataset Information

Authentication of a survival nomogram for non-invasive micropapillary breast cancer.

ABSTRACT:

Purpose

We aimed at establishing a nomogram to accurately predict the overall survival (OS) of non-metastatic invasive micropapillary breast carcinoma (IMPC).

Methods

In the training cohort, data from 429 patients with non-metastatic IMPC were obtained through the Surveillance, Epidemiology, and End Results (SEER) database. Other 102 patients were enrolled at the Xijing Hospital as validation cohort. Independent risk factors affecting OS were ascertained using univariate and multivariate Cox regression. A nomogram was established to predict OS at 3, 5 and 8 years. The concordance index (C-index), the area under a receiver operating characteristic (ROC) curve and calibration curves were utilized to assess calibration, discrimination and predictive accuracy. Finally, the nomogram was utilized to stratify the risk. The OS between groups was compared through Kaplan-Meier survival curves.

Results

The multivariate analyses revealed that race (p = 0.047), surgery (p = 0.003), positive lymph nodes (p = 0.027), T stage (p = 0.045) and estrogen receptors (p = 0.019) were independent prognostic risk factors. The C-index was 0.766 (95% CI, 0.682-0.850) in the training cohort and 0.694 (95% CI, 0.527-0.861) in the validation cohort. Furthermore, the predicted OS was consistent with actual observation. The AUCs for OS at 3, 5 and 8 years were 0.786 (95% CI: 0.656-0.916), 0.791 (95% CI: 0.669-0.912), and 0.774 (95% CI: 0.688-0.860) in the training cohort, respectively. The area under the curves (AUCs) for OS at 3, 5 and 8 years were 0.653 (95% CI: 0.498-0.808), 0.683 (95% CI: 0.546-0.820), and 0.716 (95% CI: 0.595-0.836) in the validation cohort, respectively. The Kaplan-Meier survival curves revealed a significant different OS between groups in both cohorts (p<0.001).

Conclusion

Our novel prognostic nomogram for non-metastatic IMPC patients achieved a good level of accuracy in both cohorts and could be used to optimize the treatment based on the individual risk factors.

SUBMITTER: Zhang M

PROVIDER: S-EPMC10369343 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Authentication of a survival nomogram for non-invasive micropapillary breast cancer.

Zhang Mingkun M Qin Yuan Y Hou Niuniu N Ji Fuqing F Zhang Zhihao Z Zhang Juliang J

Frontiers in oncology 20230712

<h4>Purpose</h4>We aimed at establishing a nomogram to accurately predict the overall survival (OS) of non-metastatic invasive micropapillary breast carcinoma (IMPC).<h4>Methods</h4>In the training cohort, data from 429 patients with non-metastatic IMPC were obtained through the Surveillance, Epidemiology, and End Results (SEER) database. Other 102 patients were enrolled at the Xijing Hospital as validation cohort. Independent risk factors affecting OS were ascertained using univariate and multi ...[more]

PMID: 37503326

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Project description:Background: Although it is widely accepted that invasive micropapillary carcinoma (IMPC) presents more aggressive behavior and has a higher aggressive behavior, the prognosis of IMPC compared with invasive ductal carcinoma (IDC) remains controversial. We conducted this study to explore gene expression profiles of IMPC and establish a competing nomogram that predicts the survival outcomes across these two groups of patients. Methods: Data from the Surveillance, Epidemiology, and End Results (SEER) database were reviewed. Propensity score matching (PSM) was used to adjust for potential baseline confounding between IMPC and IDC group. The Kaplan-Meier method was used to calculate the occurrence of overall mortality. The Gray method was used to estimate the rate of breast cancer specific death (BCSD). A competing regression model was used to evaluate factors associated with BCSD. A nomogram based on the competing risk regression model was established to predict individual outcomes. IMPC-specific gene expression profiles were explored using microarrays data from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed. Results: In this study, 330786 (99.62%) patients with IDC 1247 (0.38%) patients with IMPC were included. Patients with IMPC had more lymph node involvement and a larger tumor size compared with those with IDC. After PSM, many distributional differences were eliminated, showing that the IMPC and IDC group were more similar. Patients with IMPC had a favorable prognosis with statistical significance compared with patients with IDC (overall mortality HR = 0.68; 95%CI, 0.53-0.86; P = 0.002). Based on Gray method, patients with IMPC had a favorable prognosis with significant statistical significance compared with patients with IDC (BCSD SHR = 0.64; 95%CI, 0.47-0.88; P = 0.006). Multivariate analysis based on competing risk model demonstrated that IMPC was a favorable independent factor for BCSD. The nomogram could accurately predict BCSD with a high internal and external validated C-index (0.835, 0.818 respectively). A total of 53 upregulated differentially expressed genes (DEGs) and 40 downregulated DEGs of IMPC was identified. The GO analysis results showed that downregulated DEGs were significantly enriched in extracellular structure organization, extracellular matrix, cell-substrate adhesion junction. KEGG analysis of selective gene sets shows that downregulated DEGs significantly enriched for processes related to carbon metabolism, Rap1 signaling pathway. Conclusion: In the current study, IMPC accounted for 0.38% of the entire cohort. IMPC was found to be a favorable independent prognostic factor. The present study identified gene expression profiles and signal pathways of IMPC. The developed nomogram can help the oncologists to predict individual outcomes more accurately.

Project description:ObjectivesThe 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.DesignPrognostic 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.SettingPatient 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.ParticipantsWe ruled out 1893 patients and allowed the incorporation of 1340 patients into the present study.ResultsThe 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).ConclusionsThe 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.

Project description:BackgroundMolecular subtyping of bladder cancer has revealed luminal tumors generally have a more favourable prognosis. However, some aggressive forms of variant histology, including micropapillary, are often classified luminal. In previous work, we found long non-coding RNA (lncRNA) expression profiles could identify a subgroup of luminal bladder tumors with less aggressive biology and better outcomes.ObjectiveIn the present study, we aimed to investigate whether lncRNA expression profiles could identify high-grade T1 micropapillary bladder cancer with differential outcome.Design, setting, and participantsLncRNAs were quantified from RNA-seq data from a HGT1 bladder cancer cohort that was enriched for primary micropapillary cases (15/84). Unsupervised consensus clustering of variant lncRNAs identified a three-cluster solution, which was further characterised using a panel of micropapillary-associated biomarkers, molecular subtypes, gene signatures, and survival analysis. A single-sample genomic signature was trained using lasso-penalized logistic regression to classify micropapillary-like gene-expression, as characterised by lncRNA clustering. The genomic classifier (GC) was tested on luminal tumors derived from the TCGA cohort (N = 202).Outcome measurements and statistical analysisPatient and tumor characteristics were compared between subgroups by using X2 tests and two-sided Wilcoxon rank-sum tests. Primary endpoints were overall, progression-free and high-grade recurrence-free survival, calculated as the date of high-grade T1 disease at TURBT till date of death from any cause, progression, or recurrence, respectively. Survival rates were estimated using weighted Kaplan-Meier (KM) curves.Results and limitationsPrimary micropapillary HGT1 showed decreased FGFR3, SHH, and p53 pathway activity relative to tumors with conventional urothelial carcinoma. Many bladder cancer-associated lncRNAs were downregulated in micropapillary tumors, including UCA1, LINC00152, and MALAT1. Unsupervised consensus clustering resulted in a lncRNA cluster 1 (LC1) with worse prognosis that was enriched for primary micropapillary histology and the Luminal Unstable (LumU) molecular subtype. Interestingly, LC1 appeared to better identify aggressive HGT1 disease, compared to stratifying outcomes using primary histologic characteristics. A signature trained to identify LC1 cases showed good performance in the testing cohort, identifying seven cases with significantly worse survival (p < 0.001). Limitations include the retrospective nature of the study and the lack of a validation cohort.ConclusionsUsing the lncRNA transcriptome we identified a subgroup of aggressive HGT1 bladder cancer that was enriched with micropapillary histology. These data suggest that lncRNAs can facilitate the identification of aggressive micropapillary-like tumors, potentially improving patient management.

Project description:INTRODUCTION:Pure invasive micropapillary carcinoma (IMPC) is a special type of breast carcinoma characterised by clusters of cells presenting polarity abnormalities. The biological alterations underlying this pattern remain unknown. METHODS:Pangenomic analysis (n=39), TP53 (n=43) and PIK3CA (n=41) sequencing in a series of IMPCs were performed. A subset of cases was also analysed with whole-exome sequencing (n=4) and RNA sequencing (n=6). Copy number variation profiles were compared with those of oestrogen receptors and grade-matched invasive ductal carcinomas (IDCs) of no special type. RESULTS:Unsupervised analysis of genomic data distinguished two IMPC subsets: one (Sawtooth/8/16) exhibited a significant increase in 16p gains (71%), and the other (Firestorm/Amplifier) was characterised by a high frequency of 8q (35%), 17q (20% to 46%) and 20q (23% to 30%) amplifications and 17p loss (74%). TP53 mutations (10%) were more frequently identified in the amplifier subset, and PIK3CA mutations (4%) were detected in both subsets. Compared to IDC, IMPC exhibited specific loss of the 6q16-q22 region (45%), which is associated with downregulation of FOXO3 and SEC63 gene expression. SEC63 and FOXO3 missense mutations were identified in one case each (2%). Whole-exome sequencing combined with RNA sequencing of IMPC allowed us to identify somatic mutations in genes involved in polarity, DNAH9 and FMN2 (8% and 2%, respectively) or ciliogenesis, BBS12 and BBS9 (2% each) or genes coding for endoplasmic reticulum protein, HSP90B1 and SPTLC3 (2% each) and cytoskeleton, UBR4 and PTPN21 (2% each), regardless of the genomic subset. The intracellular biological function of the mutated genes identified by gene ontology analysis suggests a driving role in the clinicopathological characteristics of IMPC. CONCLUSION:In our comprehensive molecular analysis of IMPC, we identified numerous genomic alterations without any recurrent fusion genes. Recurrent somatic mutations of genes participating in cellular polarity and shape suggest that they, together with other biological alterations (such as epigenetic modifications and stromal alterations), could contribute to the morphological pattern of IMPC. Though none of the individual abnormalities demonstrated specificity for IMPC, whether their combination in IMPC may have a cumulative effect that drives the abnormal polarity of IMPC needs to be examined further with in vitro experiments.

Dataset Information

Authentication of a survival nomogram for non-invasive micropapillary breast cancer.

Purpose

Methods

Results

Conclusion

Publications

Authentication of a survival nomogram for non-invasive micropapillary breast cancer.

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