A Web-based Prediction Model for Early Death in Patients With Metastatic Triple-negative Breast Cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the absence of expression of estrogen receptor, progesterone receptor, or human epidermal growth factor receptor 2. This subtype of breast cancer is known for its high aggressiveness, high metastatic potential, tendency for recurrence, and poor prognosis. Patients with metastatic TNBC (mTNBC) have a poorer prognosis and a higher likelihood of early death (survival time ≤3 months). Therefore, the development of effective individualized survival prediction tools, such as prediction nomograms and web-based survival calculators, is of great importance for predicting the probability of early death in patients with metastatic TNBC.

METHODS

Patients diagnosed with mTNBC in the Surveillance, Epidemiology, and End Results database between 2010 and 2015 were included in the model construction. Univariate and multivariate logistic regression analysis was performed to identify risk factors associated with early death in patients with mTNBC and predictive prognostic nomograms were constructed. The accuracy of the nomograms was verified using receiver operating characteristic curves, and GiViTi Calibration belt plots were used to evaluate the model consistency. The clinical applicability of the nomograms was evaluated using decision curve analysis. On the basis of the predictive prognostic nomograms, a network survival rate calculator was developed for individualized survival prediction in patients with mTNBC.

RESULTS

A total of 2230 patients diagnosed with mTNBC were included in the Surveillance, Epidemiology, and End Results database for this study. After strict exclusion criteria, 1428 patients were found to be eligible for the study. All the patients were randomly divided into a training cohort and a validation cohort in a ratio of 7:3. Independent risk factors for mTNBC, including age, tumor size, brain metastasis, liver metastasis, surgery, and chemotherapy, were identified and integrated to construct the prediction nomogram and survival calculator. Results of receiver operating characteristic curves, calibration curves, and decision curve analysis curves from the training and validation cohort confirmed that the developed nomogram and web-based survival calculator in this study could accurately predict the probability of early death in patients with mTNBC.

CONCLUSIONS

In this study, we developed a reliable prediction nomogram and web-based survival calculator for predicting the probability of early death in patients with mTNBC. These tools can assist clinical physicians in identifying high-risk patients and developing personalized treatment plans as early as possible.

γ-Secretase Inhibitor Potentiates the Activity of Suberoylanilide Hydroxamic Acid by Inhibiting Its Ability to Induce Epithelial to Mesenchymal Transition and Stemness via Notch Pathway Activation in Triple-Negative Breast Cancer Cells

Histone deacetylase inhibitors, such as suberoylanilide hydroxamic acid (SAHA), possess great therapeutic value for triple-negative breast cancer patients. However, their inherent ability to induce epithelial to mesenchymal transition in various malignancies has been of greater concern. Herein, we hypothesize that SAHA facilitates epithelial to mesenchymal transition (EMT) via activation of the Notch pathway. From the literature survey, it is evident that histone deacetylase mediates the formation of the co-repressor complex upon interacting with the DNA binding domain, thereby inhibiting the transcription of the Notch downstream genes. Hence, we hypothesize that the use of SAHA facilitates the transcriptional activation of the Notch target genes, by disrupting the co-repressor complex and recruiting the coactivator complex, thereby facilitating EMT. In this study, we have observed that SAHA upregulates the expression profile of the Notch downstream proteins (such as Notch intracellular domain, Hes-1, c-Myc, etc.) and the Notch ligands (such as Jagged-1 and Jagged-2), thereby aberrantly activating the signaling pathway. Therefore, we have focused on combination therapy using a γ-secretase inhibitor LY411575 that would enhance the efficacy of SAHA by blocking the canonical Notch pathway mediated via its intracellular domain. It was observed that co-treatment significantly mediates apoptosis, generates cellular reactive oxygen species, depolarizes mitochondria, and diminishes the stemness properties. Besides, it also mediates autophagy-independent cell death and diminishes the expression of inflammatory cytokines, along with the downregulation in the expression of the Notch downstream genes and mesenchymal markers. Altogether, our study provides a mechanistic basis for combating EMT potentiated by SAHA, which could be utilized as a rational strategy for the treatment of solid tumors, especially triple-negative breast cancer.

Functional Characterization of lncRNA152 as an Angiogenesis-Inhibiting Tumor Suppressor in Triple-Negative Breast Cancers

Long noncoding RNAs have been implicated in many of the hallmarks of cancer. Herein, we found that the expression of lncRNA152 (lnc152; a.k.a. DRAIC), which we annotated previously, is highly upregulated in luminal breast cancer (LBC) and downregulated in triple-negative breast cancer (TNBC). Knockdown of lnc152 promotes cell migration and invasion in LBC cell lines. In contrast, ectopic expression of lnc152 inhibits growth, migration, invasion, and angiogenesis in TNBC cell lines. In mice, lnc152 inhibited the growth of TNBC cell xenografts, as well as metastasis of TNBC cells in an intracardiac injection model. Transcriptome analysis of the xenografts indicated that lnc152 downregulates genes controlling angiogenesis. Using pull down assays followed by LC/MS-MS, we identified RBM47, a known tumor suppressor in breast cancer, as a lnc152-interacting protein. The effects of lnc152 in TNBC cells are mediated, in part, by regulating the expression of RBM47. Collectively, our results demonstrate that lnc152 is an angiogenesis-inhibiting tumor suppressor that attenuates the aggressive cancer-related phenotypes found in TNBC.

IMPLICATIONS

This study identifies lncRNA152 as an angiogenesis-inhibiting tumor suppressor that attenuates the aggressive cancer-related phenotypes found in TNBC by upregulating the expression of the tumor suppressor RBM47. As such, lncRNA152 may serve as a biomarker to track aggressiveness of breast cancer, as well as therapeutic target for treating TNBC.

Prevalence Study of PD-L1 SP142 Assay in Metastatic Triple-negative Breast Cancer

Metastatic triple-negative breast cancer (mTNBC) is the most aggressive breast cancer subtype. Programmed death ligand 1 (PD-L1) on immune cells (IC) using the VENTANA SP142 assay is linked to improved clinical outcome in atezolizumab plus nab-paclitaxel-treated patients with mTNBC in the IMpassion130 study. The goal of the current study was to evaluate prevalence of VENTANA SP142 PD-L1 assay by anatomic location in 670 histologically confirmed TNBC cases from subjects with metastatic disease screened for the phase 1 study PCD4989g (NCT01375842). PD-L1 immunohistochemistry was centrally tested on tumor cells (TC) and on tumor infiltrating IC, following manufacturer's instructions. At a 1% cutoff, tumor PD-L1 was more prevalent in IC than TC: 46% were PD-L1 IC+/TC-, 3% were PD-L1 IC-/TC+, and 10% were PD-L1 IC+/TC+. PD-L1 IC and TC immunostaining correlated with CD274 RNA expression, as assessed by fluidigm. Analyses of anatomic locations suggest that prevalence of PD-L1 IC+ was highest in lymph nodes (65.0%), lowest in liver metastases (26.9%), while breast tissue was intermediate (57.1%). Matched paired samples from the same subject collected synchronously or asynchronously showed a PD-L1 IC status agreement of 80% (8/10) and 75% (15/20), respectively. Our results suggest that the anatomic location of metastases and time of collection may influence the detection of PD-L1.

A Four-gene Decision Tree Signature Classification of Triple-negative Breast Cancer: Implications for Targeted Therapeutics

The molecular complexity of triple-negative breast cancers (TNBCs) provides a challenge for patient management. We set out to characterize this heterogeneous disease by combining transcriptomics and genomics data, with the aim of revealing convergent pathway dependencies with the potential for treatment intervention. A Bayesian algorithm was used to integrate molecular profiles in two TNBC cohorts, followed by validation using five independent cohorts (n = 1,168), including three clinical trials. A four-gene decision tree signature was identified, which robustly classified TNBCs into six subtypes. All four genes in the signature (EXO1, TP53BP2, FOXM1, and RSU1) are associated with either genomic instability, malignant growth, or treatment response. One of the six subtypes, MC6, encompassed the largest proportion of tumors (∼50%) in early diagnosed TNBCs. In TNBC patients with metastatic disease, the MC6 proportion was reduced to 25%, and was independently associated with a higher response rate to platinum-based chemotherapy. In TNBC cell line data, platinum sensitivity was recapitulated, and a sensitivity to the inhibition of the phosphatase PPM1D was revealed. Molecularly, MC6-TNBCs displayed high levels of telomeric allelic imbalances, enrichment of CD4+ and CD8+ immune signatures, and reduced expression of genes negatively regulating the MAPK signaling pathway. These observations suggest that our integrative classification approach may identify TNBC patients with discernible and theoretically pharmacologically tractable features that merit further studies in prospective trials.