Pyroptosis-related molecular classification and immune microenvironment infiltration in breast cancer: A novel therapeutic target.

The underlying role of pyroptosis in breast cancer (BC) remains unknown. Herein, we investigated the correlations of 33 pyroptosis-related genes (PRGs) with immune checkpoints and immune cell infiltrations in BC patients based on The Cancer Genome Atlas cohort (n = 996) and Gene Expression Omnibus cohort (n = 3,262). Enrichment analysis revealed that these PRGs mainly functioned in pyroptosis, inflammasomes and regulation of autophagy pathway. Four prognostic independent PRGs (CASP9, TIRAP, GSDMC and IL18) were identified. Then, cluster 1/2 was recognized using consensus clustering for these four PRGs. Patients from cluster 1 had a favourable prognosis and diverse immune cell infiltrations. A nomogram was developed based on age, TNM stage, tumour subtype and pyroptosis score. Patients with the high-risk group exhibited worse 5-year OS, and the result was consistent in the external cohort. Additionally, high-risk group patients were associated with downregulated immune checkpoint expression. Further analysis suggested that the high-risk group patients were associated with a higher IC50 of paclitaxel, doxorubicin, cisplatin, methotrexate and vinorelbine. In summarizing, the pyroptosis score-based nomogram might serve as an independent prognostic predictor and could guide medication for chemotherapy. Additionally, it may bring novel insight into the regulation of tumour immune microenvironment in BC and help to achieve precision immunotherapy.

Lymphatic metastasis-associated circRNA‒miRNA‒mRNA network for exploring the pathogenesis and therapeutic target of triple negative breast cancer based on whole-transcriptome sequencing analysis: an experimental verification study.

BACKGROUND: The metastatic mechanisms of axillary lymph nodes (ALNs) in triple-negative breast cancer (TNBC) remain unclear. We aimed to identify the potential circRNA regulatory network in ALN metastasis. METHODS: We performed whole transcriptome sequencing (WTS) to determine the expression profiles of RNAs and screen out differentially expressed messenger RNAs (DEMs), microRNAs (DEMis), and circRNAs (DECs) between ALN-positive and ALN-negative TNBC patients. Functional enrichment analysis and Kaplan-Meier survival analysis were utilized to unearth the potential regulatory mechanisms of the DEMs. A competing endogenous RNA (ceRNA) network was constructed using computational biology. The expression levels of DECs in cell lines were confirmed by real-time polymerase chain reaction (RT‒PCR). RESULTS: Following WTS and differential expression analysis, 739 DEMs, 110 DEMis, and 206 DECs were identified between ALN-positive and ALN-negative TNBC patients. Functional analysis indicated that the DEMs mainly functioned in carcinogenesis and tumor progression-related pathways. ceRNA networks containing eight circRNAs, six miRNAs, and eighteen mRNAs were developed. In the ceRNA network, two mRNAs (RAB3D and EDARADD) that were significantly associated with better overall survival and one mRNA (GSR) that predicted favorable recurrence-free survival in TNBC patients were chosen for further analysis. Then, a survival-related ceRNA network containing two DECs (hsa_circ_0061260 and hsa_circ_0060876), two DEMis (hsa-miR-5000-3p and hsa-miR-4792), and three mRNAs (GSR, RAB3D, and EDARADD) was identified. Then, two candidate DECs were validated by real-time PCR. CONCLUSION: Our research constructed a ceRNA network that provides novel insights into the molecular mechanism of ALN metastasis and potential therapeutic targets in TNBC.

CDKN1C as a prognostic biomarker correlated with immune infiltrates and therapeutic responses in breast cancer patients.

Breast cancer (BC) prognosis and therapeutic sensitivity could not be predicted efficiently. Previous evidence have shown the vital roles of CDKN1C in BC. Therefore, we aimed to construct a CDKN1C-based model to accurately predicting overall survival (OS) and treatment responses in BC patients. In this study, 995 BC patients from The Cancer Genome Atlas database were selected. Kaplan-Meier curve, Gene set enrichment and immune infiltrates analyses were executed. We developed a novel CDKN1C-based nomogram to predict the OS, verified by the time-dependent receiver operating characteristic curve, calibration curve and decision curve. Therapeutic response prediction was followed based on the low- and high-nomogram score groups. Our results indicated that low-CDKN1C expression was associated with shorter OS and lower proportion of naïve B cells, CD8 T cells, activated NK cells. The predictive accuracy of the nomogram for 5-year OS was superior to the tumour-node-metastasis stage (area under the curve: 0.746 vs. 0.634, p < 0.001). The nomogram exhibited excellent predictive performance, calibration ability and clinical utility. Moreover, low-risk patients were identified with stronger sensitivity to therapeutic agents. This tool can improve BC prognosis and therapeutic responses prediction, thus guiding individualized treatment decisions.

Comprehensive analysis of autophagy-related prognostic genes in breast cancer.

Accumulating evidence revealed that autophagy played vital roles in breast cancer (BC) progression. Thus, the aim of this study was to investigate the prognostic value of autophagy-related genes (ARGs) and develop a ARG-based model to evaluate 5-year overall survival (OS) in BC patients. We acquired ARG expression profiling in a large BC cohort (N = 1007) from The Cancer Genome Atlas (TCGA) database. The correlation between ARGs and OS was confirmed by the LASSO and Cox regression analyses. A predictive model was established based on independent prognostic variables. Thus, time-dependent receiver operating curve (ROC), calibration plot, decision curve and subgroup analysis were conducted to determine the predictive performance of ARG-based model. Four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were identified using the LASSO and multivariate Cox regression analyses. A ARG-based model was constructed based on the four ARGs and two clinicopathological risk factors (age and TNM stage), dividing patients into high-risk and low-risk groups. The 5-year OS of patients in the low-risk group was higher than that in the high-risk group (P < 0.0001). Time-dependent ROC at 5 years indicated that the four ARG-based tool had better prognostic accuracy than TNM stage in the training cohort (AUC: 0.731 vs 0.640, P < 0.01) and validation cohort (AUC: 0.804 vs 0.671, P < 0.01). The mutation frequencies of the four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were 0.9%, 2.8%, 8% and 1.3%, respectively. We built and verified a novel four ARG-based nomogram, a credible approach to predict 5-year OS in BC, which can assist oncologists in determining effective therapeutic strategies.

Molecular characterization of breast cancer: a potential novel immune-related lncRNAs signature.

BACKGROUND: Accumulating evidence has demonstrated that immune-related lncRNAs (IRLs) are commonly aberrantly expressed in breast cancer (BC). Thus, we aimed to establish an IRL-based tool to improve prognosis prediction in BC patients. METHODS: We obtained IRL expression profiles in large BC cohorts (N = 911) from The Cancer Genome Atlas (TCGA) database. Then, in light of the correlation between each IRL and recurrence-free survival (RFS), we screened prognostic IRL signatures to construct a novel RFS nomogram via a Cox regression model. Subsequently, the performance of the IRL-based model was evaluated through discrimination, calibration ability, risk stratification ability and decision curve analysis (DCA). RESULTS: A total of 52 IRLs were obtained from TCGA. Based on multivariate Cox regression analyses, four IRLs (A1BG-AS1, AC004477.3, AC004585.1 and AC004854.2) and two risk parameters (tumor subtype and TNM stage) were utilized as independent indicators to develop a novel prognostic model. In terms of predictive accuracy, the IRL-based model was distinctly superior to the TNM staging system (AUC: 0.728 VS 0.673, P = 0.010). DCA indicated that our nomogram had favorable clinical practicability. In addition, risk stratification analysis showed that the IRL-based tool efficiently divided BC patients into high- and low-risk groups (P < 0.001). CONCLUSIONS: A novel IRL-based model was constructed to predict the risk of 5-year RFS in BC. Our model can improve the predictive power of the TNM staging system and identify high-risk patients with tumor recurrence to implement more appropriate treatment strategies.

Development and validation of a nomogram incorporating axillary lymph node ratio to predict survival in node-positive breast cancer patients after neoadjuvant chemotherapy.

OBJECTIVE: Over the past decade, several studies have highlighted that axillary lymph node ratio (ratio of involved over excised axillary lymph nodes) was a superior predictor for survival outcomes compared with ypN staging. Thus, this study aimed to integrate the prognostic value of axillary lymph node ratio to improve individualized prediction of survival in node-positive breast cancer patients after neoadjuvant chemotherapy. METHODS: A clinical data of 339 node-positive breast cancer patients after neoadjuvant chemotherapy from two independent centers were retrospectively reviewed. A nomogram incorporating axillary lymph node ratio was constructed to predict disease-free survival based on Cox proportional hazards model. The discrimination, calibration ability, and clinical usefulness of the axillary lymph node ratio-based model were evaluated using C-index, calibration curve, risk group stratification and decision curve analysis and were compared with the TNM staging system. RESULTS: Independent prognostic factors for disease-free survival were age, pathological T stage, axillary lymph node ratio, histological grade, estrogen receptor status, Ki67 and lymphovascular invasion, which were entered into the nomogram. The C-index of the axillary lymph node ratio-based nomogram was higher than that of the TNM staging system (0.773 vs 0.610). The calibration plot indicated close agreement between model predictions and actual observations. Based on the risk group stratification of the nomogram, Kaplan-Meier curves demonstrated significant differences between the low-risk and high-risk groups (P < 0.0001). CONCLUSIONS: The axillary lymph node ratio-based nomogram provided more accurate individualized risk prediction of disease-free survival in node-positive breast cancer patients after neoadjuvant chemotherapy. This practical tool may assist oncologists in selecting the high-risk patients who are in need of a specific treatment strategy.

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

BACKGROUND: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast cancer (BC). The aim of this study was to construct a radiogenomic multimodal model, based on machine learning and whole-transcriptome sequencing (WTS), to accurately evaluate the risk of ALN metastasis (ALNM), drug therapeutic response and avoid unnecessary axillary surgery in BC patients. METHODS: In this study, conducted a retrospective analysis of 1078 BC patients from The Cancer Genome Atlas (TCGA), The Cancer Imaging Archive (TCIA), and Foshan cohort. These patients were divided into the TCIA cohort ( N =103), TCIA validation cohort ( N =51), Duke cohort ( N =138), Foshan cohort ( N =106), and TCGA cohort ( N =680). Radiological features were extracted from BC radiological images and differentially expressed gene expression was calibrated using technology. A support vector machine model was employed to screen radiological and genetic features, and a multimodal model was established based on radiogenomic and clinical pathological features to predict ALNM. The accuracy of the model predictions was assessed using the area under the curve (AUC) and the clinical benefit was measured using decision curve analysis. Risk stratification analysis of BC patients was performed by gene set enrichment analysis, differential comparison of immune checkpoint gene expression, and drug sensitivity testing. RESULTS: For the prediction of ALNM, rad-score was able to significantly differentiate between ALN- and ALN+ patients in both the Duke and Foshan cohorts ( P <0.05). Similarly, the gene-score was able to significantly differentiate between ALN- and ALN+ patients in the TCGA cohort ( P <0.05). The radiogenomic multimodal nomogram demonstrated satisfactory performance in the TCIA cohort (AUC 0.82, 95% CI: 0.74-0.91) and the TCIA validation cohort (AUC 0.77, 95% CI: 0.63-0.91). In the risk sub-stratification analysis, there were significant differences in gene pathway enrichment between high and low-risk groups ( P <0.05). Additionally, different risk groups may exhibit varying treatment responses ( P <0.05). CONCLUSION: Overall, the radiogenomic multimodal model employs multimodal data, including radiological images, genetic, and clinicopathological typing. The radiogenomic multimodal nomogram can precisely predict ALNM and drug therapeutic response in BC patients.

Circular RNA circTATDN3 promotes the Warburg effect and proliferation in colorectal cancer.

As one of the key metabolic enzymes in the glycolytic pathway, lactate dehydrogenase A (LDHA) might be linked to tumor proliferation by driving the Warburg effect. Circular RNAs (circRNAs) are widely implicated in tumor progression. Here, we report that circTATDN3, a circular RNA that interacts with LDHA, plays a critical role in proliferation and energy metabolism in CRC. We found that circTATDN3 expression was increased in CRC cells and tumor tissues and that high circTATDN3 expression was positively associated with poor postoperative prognosis in CRC patients. Additionally, circTATDN3 promoted the proliferation of CRC cells in vivo and vitro. Mechanistically, circTATDN3 was shown to function as an adaptor molecule that enhances the binding of LDHA to FGFR1, leading to increased LDHA phosphorylation and consequently promoting the Warburg effect. Moreover, circTATDN3 increased the expression of LDHA by sponging miR-511-5p, which synergistically promoted CRC progression and the Warburg effect. In conclusion, circTATDN3 may be a target for the treatment of CRC.

Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: A large-scale pan-cancer cohort, machine learning and experimental study.

BACKGROUND: Lymph node metastasis (LNM) is an independent prognostic factor in numerous types of cancer. Therefore, a LNM-related gene-based nomogram may precisely predict survival and drug sensitivity, and reveal the mechanism underlying LNM. MATERIALS AND METHODS: Gene sequencing profiles of pan-cancer data (33 cancer types) were acquired from The Cancer Genome Atlas UCSC Xena database. Patients were classified into primary (N = 10,071) and testing (N = 5,036) cohorts. The lymph node score (LNscore) was established via single-cell RNA sequencing, whole-transcriptome sequencing, machine learning, and Cox regression analyses. A novel prognosis model, formulated by incorporating the LNscore and clinical characteristics, was evaluated using the concordance index, calibration curve, and decision curve analysis. Moreover, patients were assigned into high- and low-risk groups according to the median LNscore. We investigated these two groups for survival prognosis, functional enrichment, immune infiltration, and drug sensitivity. In addition, we silenced and overexpressed insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2). We also analyzed the behavior of breast cancer (BRCA) cells regarding lymphatic metastasis and lymphangiogenesis in vitro. IGF2BP2 stimulated the proliferation of BRCA cells via 5-Ethynyl-2'-deoxyuridine and Cell Counting Kit-8 experiments. RESULTS: A LNM-related set of 12 genes was identified and utilized to determine the LNscore. The concordance-index of both cohorts in the LNscore-based model was >0.7. The immune landscape revealed that the sensitivity to immunotherapy might be better in the high-risk group versus the low-risk group. In addition, we discovered that IGF2BP2 was overexpressed in BRCA tissues and significantly associated with poor survival. Functional analysis indicated that IGF2BP2 promoted BRCA cell migration and proliferation. Additionally, IGF2BP2 accelerated lymphatic metastasis and lymphangiogenesis in vivo. CONCLUSIONS: A novel LNscore-based model was established via comprehensive analysis of LNM-related genes. This model can accurately predict patient survival and drug sensitivity, and reveal the mechanism of LNM in the pan-cancer setting.

Integrated analysis of cell cycle-related genes in HR+/HER2- breast cancer.

PURPOSE: This study aimed to explore the mutational characteristics and significance of cell cycle-related genes (CCGs) in hormone-receptor positive, human epidermal growth factor receptor 2 negative breast cancer (HR+/HER2- BC). METHODS: A total of 1668 HR+/HER2- BC patients from the Guangdong Provincial People's Hospital (GDPH) cohort (n = 321) and METABRIC cohort (n = 1347) were included. Tumor samples from HR+/HER2- BC patients were collected for a next-generation sequencing assay in GDPH cohort, including 15 key CCGs. The association between CCGs alterations and overall survival were identified via the Cox regression analysis. The functional roles of the CCGs were explored via the Metascape database. RESULTS: Based on multivariate Cox regression analysis, a set of five key CCGs (CDK4, CCND1, CDKN1A, CDKN1C, and CHEK2) were identified as independent prognostic variables in HR+/HER2- BC patients. Besides, the five-CCGs-based risk score was used to effectively classify patients into the low-risk and high-risk groups (P < 0.0001). The potential functional pathways of the CCGs included cell cycle, cyclin D associated events in G1, and regulation of G1/S transition of mitotic cell cycle. CONCLUSION: We performed the integrated analysis of the CCGs in HR+/HER2- BC patients. It has the potential to guide individualized precision oncology therapeutic schemes in HR+/HER2- BC patients.

A Novel Protein Encoded by Exosomal CircATG4B Induces Oxaliplatin Resistance in Colorectal Cancer by Promoting Autophagy.

Oxaliplatin is commonly used in chemotherapeutic regimens for colorectal cancer (CRC) after surgical resection. However, acquired chemoresistance seriously affects the curative effect in CRC patients, and the mechanism is still unclear. Here, a circular RNA, circATG4B is identified, which plays an important role in oxaliplatin resistance in CRC. circATG4B expression is found to be increased in exosomes secreted by oxaliplatin-resistant CRC cells. In addition, the results suggest that circATG4B induces oxaliplatin resistance by promoting autophagy. Further in vivo and in vitro studies indicate that the effect of circATG4B is attributed to its potential to encode a novel protein, circATG4B-222aa. Next, circATG4B-222aa is found to function as a decoy to competitively interact with TMED10 and prevent TMED10 from binding to ATG4B, which leads to increased autophagy followed by induction of chemoresistance. Therefore, this study reveals that exosomal circATG4B participates in the decreased chemosensitivity of CRC cells, providing a new rationale for a potential therapeutic target for oxaliplatin resistance in CRC.

Spectrum of MAP3K1 mutations in breast cancer is luminal subtype-predominant and related to prognosis.

MAP3K1 is a MAPK family serine-threonine kinase that is frequently mutated in human cancer. The association between mutations in the MAP3K1 gene and the clinicopathological characteristics and prognosis of patients with breast cancer remain unclear in the Chinese population. Thus, the aim of the present retrospective study was to investigate the possible role and function of MAP3K1 in breast cancer. Data obtained from 412 consecutive patients with breast cancer were selected from Guangdong Provincial People's Hospital (GDPH) for analysis in the present study. Mutations were assessed using next-generation sequencing. The association between MAP3K1 mutations and clinicopathological features were analyzed and further compared with the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort and data from The Cancer Genome Atlas (TCGA). In the GDPH cohort, a total of 45 mutations MAP3K1 were identified in 8.5% (n=35) of the 412 patients, compared with 9.7% (n=244) in METABRIC and 7.9% (n=88) in TCGA. The majority of the mutations identified in the in three cohorts were truncating mutations, followed by mis-sense mutations. Mutations in MAP3K1 were predominant in patients with the luminal A and B breast cancer subtypes in METABRIC datasets (P<0.001), although no significant differences were observed in the GDPH cohort (P=0.227). In the METABRIC cohort, patients with MAP3K1 mutations experienced a improved overall survival (OS) rate than patients without MAP3K1 mutations (P=0.006). In patient with hormone receptor (HR)+ breast cancer, a more significantly higher OS rate was observed in patients with MAP3K1 mutations (P<0.001). MAP3K1 expression was associated with OS in the HR+ subgroup. Moreover, the MAP3K1 methylation levels were reduced in primary breast cancer tissue, compared with normal tissue. Thus, the present findings identified MAP3K1 mutations in Chinese patients with breast cancer, and compared MAP3K1 mutations between the cohorts from Western and Eastern countries.

Heterogenous and Low Expression of HER2 in Breast Cancer Overcome by DS-8201a in a Heavily Treated Patient: Case Report and Review of the Literature.

Breast cancer is highly heterogenous with temporal and spatial heterogeneity making it necessary for rebiopsy. DS-8201a, a new potential therapy for human epidermal growth factor receptor 2 (HER2) low expression breast cancer, had been proved that it could overcome heterogenous HER2 expression in a preclinical setting. In January 2014, a 23-year-old woman was presented with a lump in the right breast with bone metastasis, diagnosed as infiltrating ductal carcinoma, estrogen receptor (ER)+, progesterone receptor (PR)+, HER2 immunohistochemistry (IHC) 2+, and fluorescence in situ hybridization negative. The patient received a series of therapies including surgery, radiotherapy, endocrine therapy, target therapy, and chemotherapy. The longest progression-free survival was 17 months after surgery. Biopsy of liver metastasis in February 2020 showed triple negative (HER2-, ER-, PR-), which was quite different from the initial diagnosis in 2014, so retesting was performed and the results showed ER-, PR+ by 10%, HER2 IHC score of 1+, indicating heterogeneity of HER2 expression. In May 2020, DS-8201a treatment was initiated and continued for 10 cycles until November 2020. Remarkable relief in symptoms was observed after the first dose. A reduction in the metastatic lesion size (liver and brain) and improved liver function was observed during the therapy. This case indicated the heterogeneity of breast cancer, and impressive efficacy of DS-8201a in a heavily treated patient with HER2-low and HER2 heterogeneity.

Clinicopathologic and Genomic Features in Triple-Negative Breast Cancer Between Special and No-Special Morphologic Pattern.

Background: Triple-negative breast cancer (TNBC) is refractory and heterogeneous, comprising various entities with divergent phenotype, biology, and clinical presentation. As an aggressive subtype, Chinese TNBC patients with special morphologic patterns (STs) were restricted to its incidence of 10-15% in total TNBC population. Methods: We recruited 89 patients with TNBC at Guangdong Provincial People's Hospital (GDPH) from October 2014 to May 2021, comprising 72 cases of invasive ductal carcinoma of no-special type (NSTs) and 17 cases of STs. The clinical data of these patients was collected and statistically analyzed. Formalin-fixed, paraffin-embedded (FFPE) tumor tissues and matched blood samples were collected for targeted next-generation sequencing (NGS) with cancer-related, 520- or 33-gene assay. Immunohistochemical analysis of FFPE tissue sections was performed using anti-programmed cell death-ligand 1(PD-L1) and anti-androgen receptor antibodies. Results: Cases with NSTs presented with higher histologic grade and Ki-67 index rate than ST patients (NSTs to STs: grade I/II/III 1.4%, 16.7%,81.9% vs 0%, 29.4%, 58.8%; p<0.05; Ki-67 ≥30%: 83.3% vs. 58.8%, p<0.05), while androgen receptor (AR) and PD-L1 positive (combined positive score≥10) rates were lower than of STs cases (AR: 11.1% vs. 47.1%; PD-L1: 9.6% vs. 33.3%, p<0.05). The most commonly altered genes were TP53 (88.7%), PIK3CA (26.8%), MYC (18.3%) in NSTs, and TP53 (68.8%), PIK3CA (50%), JAK3 (18.8%), KMT2C (18.8%) in STs respectively. Compared with NSTs, PIK3CA and TP53 mutation frequency showed difference in STs (47.1% vs 19.4%, p=0.039; 64.7% vs 87.5%, p=0.035). Conclusions: In TNBC patients with STs, decrease in histologic grade and ki-67 index, as well as increase in PD-L1 and AR expression were observed when compared to those with NSTs, suggesting that TNBC patients with STs may better benefit from immune checkpoint inhibitors and/or AR inhibitors. Additionally, lower TP53 and higher PIK3CA mutation rates were also found in STs patients, providing genetic evidence for deciphering at least partly potential mechanism of action.

Establishment and Validation of a Preoperative MRI-based Nomogram for Predicting the Risk of Malignancy in Patients with Breast Tumor.

Purpose: To establish a preoperative nomogram incorporating morphological and dynamic contrast-enhanced (DCE) features to individually predict the risk of malignancy in patients with breast tumor. Methods A total of 447 consecutive female patients who were divided into the primary cohort (n=326) and the validation cohort (n=121) were enrolled between March 2015 to January 2018. Univariate and multivariate logistic regression analyses were used to identify the potential independent indicators of malignancy. An MRI-based nomogram integrating morphological features and kinetic curves was developed to achieve individualized risk prediction of malignancy in patients with breast masses. The discrimination, calibration ability and clinical utility of the MRI-based model were assessed using C-index, calibration curve and decision curve analysis. Results: Age, tumor size, margin, internal enhancement characteristics, and kinetic curve were confirmed as the independent predictors of malignancy. The AUC of MRI-based nomogram was 0.940 (95% CI: 0.911-0.970) and 0.894 (95% CI: 0.816-0.974) in the primary cohort and validation cohort, respectively. 447 patients were subdivided into the low-risk group (n=107) and high-risk group (n=340) based on the optimal cut-off value of 21.704. The high-risk patients had a higher likelihood of harboring malignancy. Conclusion: The MRI-based nomogram can be used to achieve an accurate individualized risk prediction of malignancy and reduce unnecessary breast biopsy.

Characterization of Frequently Mutated Cancer Genes and Tumor Mutation Burden in Chinese Breast Cancer.

OBJECTIVES: Various genomic alterations and genomic signatures, including ERBB2 amplification, mutations in PIK3CA, AKT1, and ESR1, and tumor mutational burden (TMB), have become important biomarkers for treatment selection in breast cancer (BC). This study aimed to investigate the mutational features of Chinese early-stage BC patients. METHODS: Tumors and matched blood samples collected from 589 Chinese patients with early-stage BC were sequenced using a commercial gene panel consisting of 520 cancer-related genes to analyze all types of genomic alterations and estimate the TMB status. RESULTS: A total of 18 genes were found to be more frequently mutated (P<0.05) or amplified (P<0.05) in stage T3-4 tumors as compared with T1-2 tumors. A total of 18 genes were found to be differentially mutated (P<0.05) or amplified (P<0.05) in patients with lymph node metastasis than those without lymph node metastasis. Younger patients (≤35 years) were more frequently identified with mutations or gene amplifications in eleven genes (P<0.05). TMB >10mutations/Mb were found in 5.7% of our cohort. Although the TMB was similar for various molecular subtypes between our cohort and the BC cohort of The Cancer Genome Atlas (TCGA) study, the TMB were statistically different for HR+/HER-, HR+/HER2+, and triple-negative subtypes between our cohort and African Americans in the TCGA study. As compared to the TCGA BC cohort, our cohort had a much earlier median age of diagnosis (48 vs. 58 years, P<0.001), and had significantly lower frequency of triple-negative subtype (11.5% vs. 18.4%, P<0.001) and invasive lobular BC (2.4% vs. 19.0%, P<0.001). Further subgroup analyses revealed that mutation rates in various genes including TP53, ERBB2, and PIK3CA were distinct for patients who were younger (≤35 years), had triple-negative or invasive lobular BC in our cohort than in the TCGA cohort. CONCLUSIONS: This study revealed distinct mutational features of various molecular subtypes of early-stage BC among Chinese patients. Moreover, we provide new insights into the differences in early-stage BC between the East and West.

Mutational Landscape of PI3K-AKT-mTOR Pathway in Breast Cancer: Implications for Targeted Therapeutics.

Background: Comprehensive analysis of PI3K-AKT-mTOR pathway gene alterations in breast cancer may be helpful for targeted therapy. Methods: We performed targeted sequencing using a panel of 520 cancer-related genes to investigate gene alterations in the PI3K-AKT-mTOR pathway from 589 consecutive Chinese women diagnosed with stage I-III breast cancer. Analyses of overall survival (OS) were performed using the publicly available clinical and genomic data from METABRIC. Results: PI3K-AKT-mTOR pathway gene alterations were detected in 62.6% (369/589) of our cohort. The most commonly altered genes were PIK3CA (45%), PTEN (7.5%), AKT1 (5.9 %), PIK3R1 (2.7%), and PIK3CG (2%). Four PIK3CA mutations (E545K, H1047R, E542K, and H1047L) were detected in all the breast cancer molecular subtypes. Seven PIK3CA mutations (E545G, E418_L422delinsV, E726K, E110del, G1049R, G118D, and D350G) were only detected in HR+ subtypes. Two PIK3CA mutations (C420R and N345K) were only detected in non-triple-negative subtypes. Most cases with PTEN mutation were HR+/HER2- subtype (77.3%), followed by triple-negative subtype (18.2%). In the METABRIC breast cancer dataset, no significant OS difference was observed between the PIK3CA-mutant and wild-type groups. However, patients with multiple PIK3CA mutations (mOS: 131 vs. 159 months, P= 0.029), or PIK3CA mutations located in the C2 domain had significantly shorter OS (mOS, 130 vs. 154 months, P=0.020) than those without the mutations. Conclusions: Our study reveals the heterogeneity in PI3K-AKT-mTOR pathway among the breast cancer molecular subtypes in our cohort. Moreover, the number and specific sites of PIK3CA mutations have distinct prognostic impact.

Characterization of AKT Somatic Mutations in Chinese Breast Cancer Patients.

PURPOSE: This study aimed to investigate AKT gene mutation status in Chinese breast cancer patients. METHODS: The study included 411 breast cancer patients hospitalized in Guangdong Provincial People's Hospital (GDPH) from June 1, 2017 to September 27, 2018. Mastectomy or breast conserving surgery was performed, and tissue samples were subjected to next-generation sequencing (NGS) to determine AKT gene mutation status. Meanwhile, the expression of human epidermal growth factor receptor 2 (Her2), progesterone receptor (PR), and estrogen receptor (ER) was analyzed by immunohistochemistry staining. The Cancer Genome Atlas (TCGA) database was used for comparative studies. RESULTS: Patients in the GDPH cohort had an older age (P < 0.001), higher postmenopausal rate (P < 0.001), larger tumor size (P < 0.001), higher histologic type of infiltrating duct cancer (P < 0.001), higher metastatic rate (P < 0.001), higher expression of ER (P = 0.015) and HER2 (P < 0.001), and higher percentage of the HR/HER2 subtype (P < 0.001) than those in the TCGA cohort. The GDPH cohort displayed lower rates of overall AKT and AKT3 mutation (P < 0.001), but a higher AKT1 mutation rate (P < 0.0001) compared with the TCGA cohort. Notably, the NGS studies identified missense mutation and copy number amplification as the most common AKT variation type in the GDPH and TCGA cohorts, respectively. Specifically, E17K mutation in AKT1 was predominantly detected in GDPH cohort, while being absent in TCGA cohort. Moreover, in the GDPH cohort, AKT variation was correlated with a number of clinicopathological variables, including age over 50, HER2-, HR+/HER2-, and PR+. CONCLUSION: Patients in the GDPH cohort had lower rates of AKT and AKT3 mutation and higher AKT1 mutation rate than those in the TCGA cohort, while harboring missense mutations detected predominantly as E17K mutation in AKT1. In GDPH cohort, there were correlations between AKT mutation and the clinicopathological characteristics of patients.

Genetic and immune characteristics of sentinel lymph node metastases and multiple lymph node metastases compared to their matched primary breast tumours.

BACKGROUND: Patients with breast cancer presenting with single lymph node metastasis (from a sentinel node) experience prolonged survival compared to patients with multiple lymph node metastases (≥3). However, little information is available on the genetic and immunological characteristics of breast cancer metastases within the regional lymph nodes as they progress from the sentinel lymph node (SLN) downstream to multiple regional lymph nodes (MLNs). METHODS: Genomic profiling was performed using a next-generation sequencing panel covering 520 cancer-related genes in the primary tumour and metastatic lymph nodes of 157 female patients with breast cancer. We included primary tumours, metastatic lymph nodes and adjacent clinically normal lymph nodes (20 patients from the SLN group and 28 patients from the MLNs group) in the whole transcriptome analysis. FINDINGS: The downstream metastatic lymph nodes (P = 0.029) and the primary breast tumours (P = 0.011) had a higher frequency of PIK3CA mutations compared to the SLN metastasis. We identified a distinct group of 14 mutations from single sentinel node metastasis and a different group of 15 mutations from multiple nodal metastases. Only 4 distinct mutations (PIK3CA, CDK4, NFKBIA and CDKN1B) were conserved in metastases from both lymph node settings. The tumour mutational burden (TMB) was significantly lower in single nodal metastasis compared to the paired primary breast cancer (P = 0.0021), while the decline in TMB did not reach statistical significance in the MLNs group (P = 0.083). In the gene set enrichment analysis, we identified 4 upregulated signatures in both primary tumour and nodal metastases from the MLNs group, including 3 Epithelial-mesenchymal transition(EMT) signatures and 1 angiogenesis signature. Both the CD8/Treg ratio and the CD8/EMT ratio were significantly higher in adjacent normal lymph nodes from patients with a single metastasis in the SLN compared with samples from the MLNs group (P = 0.045 and P = 0.023, respectively). This suggests that the immune defence from the MLNs patients might have a less favourable microenvironment, thus permitting multiple lymph nodes metastasis. INTERPRETATION: Single lymph node metastases and multiple lymph node metastases have significant differences in their molecular profiles and immune profiles. The findings are associated with more aggressive tumour characteristics and less favourable immune charactoristics in patients with multiple nodal metastases compared to those with a single metastasis in the sentinel node. FUNDING: This work was supported by funds from High-level Hospital Construction Project (DFJH201921), the National Natural Science Foundation of China (81902828 and 82002928), the Fundamental Research Funds for the Central Universities (y2syD2192230), and the Medical Scientific Research Foundation of Guangdong Province (B2019039).