A seven-gene signature can predict distant recurrence in patients with triple-negative breast cancers who receive adjuvant chemotherapy following surgery

Exploring the prognostic value of S100A11 and its association with immune infiltration in breast cancer

Breast cancer (BC) is a severe danger to women's lives and health globally. S100A11 is aberrantly expressed in many carcinomas and serves a crucial function in cancer development. However, the role of S100A11 in BC is unclear. In this study, we utilized multiple databases and online tools, including the TCGA database, cBioPortal, and STRING, to evaluate the significance of S100A11 in BC prognosis and immune infiltration. We found that S100A11 was considerably more abundant in BC tissues. Survival analysis indicated that individuals with S100A11 high expression of BC had shorter overall survival. Multivariate Cox regression analysis revealed that high S100A11 expression independently influenced the poor outcome of patients with BC (HR = 1.738, 95%CI 1.197-2.524). Our nomogram incorporating five factors, including S100A11, age, clinical stage, N, and M, was developed to anticipate the survival probability in BC prognosis. The model demonstrated good consistency and accuracy. Furthermore, the mutation rete of S100A11 was 14%. Survival analysis suggested that breast cancer patients with S100A11 mutation had a worse prognosis. KEGG pathway enrichment analysis revealed that S100A11 may be mainly involved in the IL-17 signaling pathway. Finally, we discovered a correlation between S100A11 expression and immune cell infiltration on BC. S100A11 expression was positively associated with 17 immune checkpoint-related genes. In conclusion, this study indicates that S100A11 may contribute to a worse prognosis for BC and potentially has a significant impact through its influence on immune cell infiltration and the IL-17 signaling pathway.

Identification and panoramic analysis of drug response-related genes in triple negative breast cancer using as an example NVP-BEZ235

Taking NVP-BEZ235 (BEZ235) as an example to screen drug response-related genes (DRRGs) and explore their potential value in triple-negative breast cancer (TNBC). Through high-throughput technique, multidimensional transcriptome expression data (mRNA, miRNA and lncRNA) of BEZ235-treated and -untreated MDA-MB-468 cell lines were obtained. Combined with transcriptome data of the MDA-MB-468 cells and TCGA-TNBC tissues, differential gene expression analysis and WGCNA were performed to identify DRRGs associated with tumor trait by simulating the drug response microenvironment (DRM) of BEZ235-treated patients. Based on DRRGs, we constructed a ceRNA network and verified the expression levels of three key molecules by RT-qPCR, which not only demonstrated the successful construction of a BEZ235-treated cell line model but also explained the antitumor mechanism of BEZ235. Four molecular subtypes related to the DRM with survival difference were proposed using cluster analysis, namely glycolysis subtype, proliferation depression subtype, immune-suppressed subtype, and immune-activated subtype. A novel prognostic signature consisting of four DRRGs was established by Lasso-Cox analysis, which exhibited outstanding performance in predicting overall survival compared with several excellent reported signatures. The high- and low-risk groups were characterized by enrichment of metabolism-related pathways and immune-related pathways, respectively. Of note, the low-risk group had a better response to immune checkpoint blockade. Besides, pRRophetic analysis found that patients in the low-risk group were more sensitive to methotrexate and cisplation, whereas more resistant to BEZ235, docetaxel and paclitaxel. In conclusion, the DRRGs exemplified by BEZ235 are potential biomarkers for TNBC molecular typing, prognosis prediction and targeted therapy. The novel DRRGs-guided strategy for predicting the subtype, survival and therapy efficacy, might be also applied to more cancers and drugs other than TNBC and BEZ235.

Advancement of prognostic models in breast cancer: a narrative review

Objective

To provide a reference for clinical work and guide the decision-making of healthcare providers and end-users, we systematically reviewed the development, validation and classification of classical prognostic models for breast cancer.

Background

Patients suffering from breast cancer have different prognosis for its high heterogeneity. Accurate prognosis prediction and risk stratification for breast cancer are crucial for individualized treatment. There is a lack of systematic summary of breast cancer prognostic models.

Methods

We conducted a PubMed search with keywords "breast neoplasm", "prognostic model", "recurrence" and "metastasis", and screened the retrieved publications at three levels: title, abstract and full text. We identified the articles presented the development and/or validation of models based on clinicopathological factors, genomics, and machine learning (ML) methods to predict survival and/or benefits of adjuvant therapy in female breast cancer patients.

Conclusions

Combining prognostic-related variables with long-term clinical outcomes, researchers have developed a series of prognostic models based on clinicopathological parameters, genomic assays, and medical figures. The discrimination, calibration, overall performance, and clinical usefulness were validated by internal and/or external verifications. Clinicopathological models integrated the clinical parameters, including tumor size, histological grade, lymph node status, hormone receptor status to provide prognostic information for patients and doctors. Gene-expression assays deeply revealed the molecular heterogeneity of breast cancer, some of which have been cited by AJCC and National Comprehensive Cancer Network (NCCN) guidelines. In addition, the models based on the ML methods provided more detailed information for prognosis prediction by increasing the data dimension. Combined models incorporating clinical variables and genomics information are still required to be developed as the focus of further researches.

A Novel Seven Gene Signature-Based Prognostic Model to Predict Distant Metastasis of Lymph Node-Negative Triple-Negative Breast Cancer

Background

The prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment.

Methods

We analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model.

Results

A clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size.

Conclusions

The proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.

Targeting c-Met in triple negative breast cancer: preclinical studies using the c-Met inhibitor, Cpd A

Introduction Triple negative breast cancer (TNBC) represents a heterogeneous subtype of breast cancer that carries a poorer prognosis. There remains a need to identify novel drivers of TNBC, which may represent targets to treat the disease. c-Met overexpression is linked with decreased survival and is associated with the basal subtype of breast cancer. Cpd A, a kinase inhibitor selective/specific for Met kinase has demonstrated preclinical anti-cancer efficacy in TNBC. We aimed to assess the anti-cancer efficacy of Cpd A when combined with Src kinase, ErbB-family or hepatocyte growth factor (HGF) inhibitors in TNBC cell lines. Methods We determined the anti-proliferative effects of Cpd A, rilotumumab, neratinib and saracatinib tested alone and in combination in a panel of TNBC cells by acid phosphatase assays. We performed reverse phase protein array analysis of c-Met and IGF1Rβ expression and phosphorylation of c-Met (Y1234/1235) in TNBC cells and correlated their expression/phosphorylation with Cpd A sensitivity. We examined the impact of Cpd A, neratinib and saracatinib tested alone and in combination on invasive potential and colony formation.Results TNBC cells are not inherently sensitive to Cpd A, and neither c-Met expression nor phosphorylation are biomarkers of sensitivity to Cpd A. Cpd A enhanced the anti-proliferative effects of neratinib in vitro; however, this effect was limited to cell lines with innate sensitivity to Cpd A. Cpd A had limited anti-invasive effects but it reduced colony formation in the TNBC cell line panel.Conclusions Despite Cpd A having a potential role in reducing cancer cell metastasis, identification of strong predictive biomarkers of c-Met sensitivity would be essential to the development of a c-Met targeted treatment for an appropriately selected cohort of TNBC patients.

CLCA2 expression is associated with survival among African American women with triple negative breast cancer

Purpose

Black/African American (AA) women are twice as likely to be diagnosed with triple negative breast cancer (TNBC) compared to whites, an aggressive breast cancer subtype associated with poor prognosis. There are no routinely used targeted clinical therapies for TNBC; thus there is a clear need to identify prognostic markers and potential therapeutic targets.

Methods

We evaluated expression of 27,016 genes in 155 treatment-naïve TN tumors from AA women in Detroit. Associations with survival were evaluated using Cox proportional hazards models adjusting for stage and age at diagnosis, and p-values were corrected using a false discovery rate. Our validation sample consisted of 494 TN tumors using four publically available data sets. Meta-analyses were performed using summary statistics from the four validation results.

Results

In the Detroit AA cohort, CLCA2 [Hazard ratio (HR) = 1.56, 95% confidence interval (CI) 1.31–1.86, nominal p = 5.1x10-7, FDR p = 0.014], SPIC [HR = 1.47, 95%CI 1.26–1.73, nominal p = 1.8x10-6, FDR p = 0.022], and MIR4311 [HR = 1.57, 95% CI 1.31–1.92, nominal p = 2.5x10-5, FDR p = 0.022] expression were associated with overall survival. Further adjustment for treatment and breast cancer specific survival analysis did not substantially alter effect estimates. CLCA2 was also associated with increased risk of death in the validation cohorts [HR = 1.14, 95% CI 1.05–1.24, p = 0.038, p-heterogeneity = 0.88].

Conclusions

We identified CLCA2 as a potential prognostic marker for TNBC in AA women.

Anti-tumour effects of Keratin 6A in lung adenocarcinoma

BACKGROUND

To examine the effects of Keratin 6A (KRT6A) protein on the proliferation, migration and invasion abilities of lung adenocarcinoma cells, and to analyse the relationship between the expression level of KRT6A protein and the survival prognosis of lung adenocarcinoma patients.

METHODS

Western Blot was used to detect the expression of KRT6A protein in lung adenocarcinoma cell lines. CCK-8 experiment and colony formation assays were performed to detect the proliferation ability. Wound healing assay and transwell migration assay were conducted to detect the migration ability. Transwell invasion assay was conducted to detect the invasion ability. Immunohistochemistry was used to detect the expression of KRT6A protein in lung adenocarcinoma tissues.

RESULTS

We first found that the expression of KRT6A protein in lung adenocarcinoma cell lines was low. After overexpressed KRT6A protein in lung adenocarcinoma cells, we then found that KRT6A protein could not only inhibit the proliferation ability of lung adenocarcinoma cells but also inhibit them migration and invasion abilities. In addition, we also found that there had obvious difference in the expression of KRT6A protein in between patients. And through further analysis, we finally discovered that high expression of KRT6A protein was related to favourable prognosis in lung adenocarcinoma patients.

CONCLUSIONS

KRT6A protein inhibits the proliferation, migration and invasion abilities of lung adenocarcinoma cells, and high expression of KRT6A protein is a predictor of good prognosis in patients with lung adenocarcinoma.

Profiling molecular regulators of recurrence in chemorefractory triple-negative breast cancers

Background

Approximately two thirds of patients with localized triple-negative breast cancer (TNBC) harbor residual disease (RD) after neoadjuvant chemotherapy (NAC) and have a high risk-of-recurrence. Targeted therapeutic development for TNBC is of primary significance as no targeted therapies are clinically indicated for this aggressive subset. In view of this, we conducted a comprehensive molecular analysis and correlated molecular features of chemorefractory RD tumors with recurrence for the purpose of guiding downstream therapeutic development.

Methods

We assembled DNA and RNA sequencing data from RD tumors as well as pre-operative biopsies, lymphocytic infiltrate, and survival data as part of a molecular correlative to a phase II post-neoadjuvant clinical trial. Matched somatic mutation, gene expression, and lymphocytic infiltrate were assessed before and after chemotherapy to understand how tumors evolve during chemotherapy. Kaplan-Meier survival analyses were conducted categorizing cancers with TP53 mutations by the degree of loss as well as by the copy number of a locus of 18q corresponding to the SMAD2, SMAD4, and SMAD7 genes.

Results

Analysis of matched somatic genomes pre-/post-NAC revealed chaotic acquisition of copy gains and losses including amplification of prominent oncogenes. In contrast, significant gains in deleterious point mutations and insertion/deletions were not observed. No trends between clonal evolution and recurrence were identified. Gene expression data from paired biopsies revealed enrichment of actionable regulators of stem cell-like behavior and depletion of immune signaling, which was corroborated by total lymphocytic infiltrate, but was not associated with recurrence. Novel characterization of TP53 mutation revealed prognostically relevant subgroups, which were linked to MYC-driven transcriptional amplification. Finally, somatic gains in 18q were associated with poor prognosis, likely driven by putative upregulation of TGFß signaling through the signal transducer SMAD2.

Conclusions

We conclude TNBCs are dynamic during chemotherapy, demonstrating complex plasticity in subclonal diversity, stem-like qualities, and immune depletion, but somatic alterations of TP53/MYC and TGFß signaling in RD samples are prominent drivers of recurrence, representing high-yield targets for additional interrogation.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1171-7) contains supplementary material, which is available to authorized users.

Gene expression in triple-negative breast cancer in relation to survival

PURPOSE

The identification of biomarkers related to the prognosis of triple-negative breast cancer (TNBC) is critically important for improved understanding of the biology that drives TNBC progression.

METHODS

We evaluated gene expression in total RNA isolated from formalin-fixed paraffin-embedded tumor samples using the NanoString nCounter assay for 469 TNBC cases from the Shanghai Breast Cancer Survival Study. We used Cox regression to quantify Hazard Ratios (HR) and corresponding confidence intervals (CI) for overall survival (OS) and disease-free survival (DFS) in models that included adjustment for breast cancer intrinsic subtype. Of 302 genes in our discovery analysis, 22 were further evaluated in relation to OS among 134 TNBC cases from the Nashville Breast Health Study and the Southern Community Cohort Study; 16 genes were further evaluated in relation to DFS in 335 TNBC cases from four gene expression omnibus datasets. Fixed-effect meta-analysis was used to combine results across data sources.

RESULTS

Twofold higher expression of EOMES (HR 0.90, 95% CI 0.83-0.97), RASGRP1 (HR 0.89, 95% CI 0.82-0.97), and SOD2 (HR 0.80, 95% CI 0.66-0.96) was associated with better OS. Twofold higher expression of EOMES (HR 0.89, 95% CI 0.81-0.97) and RASGRP1 (HR 0.87, 95% CI 0.81-0.95) was also associated with better DFS. On the contrary, a doubling of FA2H (HR 1.14, 95% CI 1.06-1.22) and GSPT1 (HR 1.33, 95% CI 1.14-1.55) expression was associated with shorter DFS.

CONCLUSIONS

We identified five genes (EOMES, FA2H, GSPT1, RASGRP1, and SOD2) that may serve as potential prognostic biomarkers and/or therapeutic targets for TNBC.

Genome wide copy number analyses of superficial esophageal squamous cell carcinoma with and without metastasis

Superficial esophageal squamous cell carcinoma (ESCC) is generally considered a subtype of less invasive ESCC. Yet a subset of these superficial ESCC would have metastasis after esophagostomy or endoscopic resection and lead to poor prognosis. The objective of this study is to determine biomarkers that can identify such subset of superficial ESCC that would have metastasis after surgery using genome wide copy number alteration (CNA) analyses. The CNAs of 38 cases of superficial ESCCs originated from radical surgery, including 19 without metastasis and 19 with metastasis within 5 years’ post-surgery, were analyzed using Affymetrix OncoScan™ FFPE Assay. A 39-gene signature was identified which characterized the subset of superficial ESCC with high risk of metastasis after surgery. In addition, recurrent CNAs of superficial ESCC were also investigated in the study. Amplification of 11q13.3 (FGF4) and deletion of 9p21.3 (CDKN2A) were found to be recurrent in all 38 superficial ESCCs analyzed. Notably amplifications of 3p26.33 (SOX2OT), 8q24.21 (MYC), 14q21.1 (FOXA1) and deletion of 3p12.1 (GBE1) were only found to be recurrent in metastaic superficial ESCCs. In conclusion, using CNAs analyses, we identify a 39-gene signature which characterizes the high risk metastatic superficial ESCCs and discover several recurrent CNAs that might be the driver alterations in metastasis among superficial ESCCs.

The Prognostic Value of HRAS mRNA Expression in Cutaneous Melanoma

This study aimed to investigate the prognostic value of HRAS mRNA expression in cutaneous melanoma. Cutaneous melanoma is an aggressive cancer with an increasing incidence. Few studies have focused on the transcriptional level of RAS isoforms (KRAS, NRAS, and HRAS) in cutaneous melanoma. To gain further insight into RAS isoforms at transcriptional level, we obtained the cutaneous melanoma data from cBioPortal and investigated the RAS mRNA expression levels in different stages of melanoma and evaluated their correlation with clinical characteristics and patients' survival. Furthermore, we retrieved and analyzed the coexpression data and performed pathway enrichment analysis. Totally, 452 cutaneous melanoma cases were included in this study. We found that lower HRAS expression level was associated with longer patient survival. 206 genes that negatively correlated with HRAS expression were positively correlated with KRAS and NRAS expression. In contrast, no gene that positively correlated with HRAS expression was positively correlated with KRAS and NRAS expression. In conclusion, our data showed that transcriptional regulation was different for the three RAS isoforms in cutaneous melanoma. This study highlighted the prognostic value of HRAS mRNA expression and revealed that HRAS greatly differs from KRAS and NRAS at the transcriptional level.

Statins affect ETS1-overexpressing triple-negative breast cancer cells by restoring DUSP4 deficiency

We investigated the molecular mechanisms underlying statin-induced growth suppression of triple-negative breast cancer (TNBC) that overexpress the transcription factor ets proto-oncogene 1(ets-1) and downregulate dual specific protein phosphatase 4(dusp4) expression. We examined the gene expression of BC cell lines using the nCounter expression assay, MTT viability assay, cell proliferation assay and Western blot to evaluate the effects of simvastatin. Finally, we performed cell viability testing in TNBC cell line-transfected DUSP4. We demonstrated that ETS1 mRNA and protein were overexpressed in TNBC cells compared with other BC cell lines (P = <0.001) and DUSP4 mRNA was downregulated (P = <0.001). MTT viability assay showed that simvastatin had significant antitumor activity (P = 0.002 in 0.1 μM). In addition, simvastatin could restore dusp4 deficiency and suppress ets-1 expression in TNBC. Lastly, we found that si-DUSP4 RNA transfection overcame the antitumor activity of statins. MAPK pathway inhibitor, U0126 and PI3KCA inhibitor LY294002 also decreased levels of ets-1, phosphor-ERK and phosphor-AKT on Western blot assay. Accordingly, our study indicates that simvastatin potentially affects the activity of transcriptional factors such as ets-1 and dusp4 through the MAPK pathway. In conclusion, statins might be potential candidates for TNBC therapy reducing ets-1 expression via overexpression of dusp4.

The relationship between nuclear factor (NF)-κB family gene expression and prognosis in triple-negative breast cancer (TNBC) patients receiving adjuvant doxorubicin treatment

We investigated gene expression profiles of the NF-κB pathway in patients with triple-negative breast cancer (TNBC) receiving adjuvant chemotherapy to determine the prognostic value of NF-κB pathway genes according to chemotherapeutic regimen. We used the nCounter expression assay to measure expression of 11 genes (NFKB1, NFKB2, RELA, RELB, REL, TP53, FOXC1, TBP, SP1, STAT3 and IRF1 genes) belonging to the NF-κB pathway using mRNA extracted from paraffin-embedded tumor tissues from 203 patients diagnosed with TNBC. Of the 203 patients, 116 were treated with a chemotherapeutic regimen containing doxorubicin. As revealed by the expression profiles of the 11 genes, increased expression of SP1 was associated with poor prognosis in TNBC patients treated with adjuvant doxorubicin chemotherapy (5-year distant recurrence-free survival [5Y DRFS], low vs. high expression [cut-off: median]: 92.3% vs. 71.6%, P = 0.001). In a multivariate Cox regression model, SP1 expression was a useful marker for predicting long-term prognosis in TNBC patients receiving doxorubicin treatment, and we thus suggest that SP1 expression could serve as a prognostic marker in these patients.

Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics

Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

Association between Mutation and Expression of TP53 as a Potential Prognostic Marker of Triple-Negative Breast Cancer

Purpose

TP53, the most frequently mutated gene in breast cancer, is more frequently altered in HER2-enriched and basal-like breast cancer. However, no studies have clarified the role of TP53 status as a prognostic and predictive marker of triple-negative breast cancer (TNBC).

Materials and Methods

We performed p53 immunohistochemistry (IHC), nCounter mRNA expression assay, and DNA sequencing to determine the relationship between TP53 alteration and clinical outcomes of TNBC patients.

Results

Seventy-seven of 174 TNBC patients were found to harbor a TP53 mutation. Patients with missense mutations showed high protein expression in contrast to patients with deletion mutations (positivity of IHC: wild type vs. missense vs. deletion mutation, 53.6% vs. 89.8% vs. 25.0%, respectively; p < 0.001). TP53 mRNA expression was influenced by mutation status (mRNA expression [median]: wild type vs. missense vs. deletion mutation, 207.36± 132.73 vs. 339.61±143.21 vs. 99.53±99.57, respectively; p < 0.001). According to survival analysis, neither class of mutation nor protein or mRNA expression status had any impact on patient prognosis. In subgroup analysis, low mRNA expression was associated with poor prognosis in patients with a TP53 missense mutation (5-year distant recurrence-free survival [5Y DRFS]: low vs. high, 50.0% vs. 87.8%; p=0.009), while high mRNA expression with a TP53 deletion mutation indicated poor prognosis (5Y DRFS: low vs. high, 91.7% vs. 75.0%; p=0.316).

Conclusion

Association between TP53 mutation and expression indicates a potential prognostic marker of TNBC; hence both DNA sequencing and mRNA expression analysis may be required to predict the prognosis of TNBC patients.