Peroxiredoxins: regulatory roles and potential clinical significances in breast cancer

Aim. To investigate the possibility of using radiation diagnostic data to determine various molecular subtypes of breast cancer (BC) using artificial intelligence technologies.Materials and methods. The material for the study was retrospective data of 344 patients treated at the Sverdlovsk Regional Oncology Dispensary in the period from 2021 to 2023. The average age of the study sample was 56.8 ± 10.6 years, ranging from 33 to 82 years. All patients were diagnosed with BC, confirmed histologically. Molecular subtypes of BC were assessed based on trepan biopsy and surgical material. All patients underwent mammographic, ultrasound, and magnetic resonance imaging examinations, and sets of diagnostic features were identified that most accurately correspond to various molecular subtypes of BC. To achieve this goal, the authors identified the following diagnostic features: age, maximum diameter of the formation measured for various methods of radiation diagnostics, morphological features (contours, spatial orientation, shape of the detected formations or areas of reconstruction, heterogeneity of the structure of formations, presence of calcifications, characteristics of blood flow in the tumor) and dynamic parameters of paramagnetic accumulation during magnetic resonance imaging of the mammary gland.Based on the histological examination data, the degree of tumor differentiation (G), proliferative activity index (Ki-67), regional lymph node status (presence or absence of metastases), and molecular-immunohistochemical tumor subtype were assessed. An analysis was conducted to determine whether there was a statistically significant relationship between diagnostic features and molecular subtypes of BC. The analysis was performed by conducting chi-square tests for features and subtypes (classes) of BC, previously converted to binary form. From the arrays of values s elected for the study of diagnostic features, training and test samples were formed, and an algorithm for the classification model of artificial intelligence was determined. The accuracy of BC typing was ensured by using a combination of 7 diagnostic features and 6 classification models: five single-class and one multi-class. The gradient boosting algorithm (GradientBoostingRegressor) was used to train single-class models. The strategy “one (class) versus the rest” was used to train the multi-class model using the OneVsRestClassifier and gradient boosting (GradientBoostingClassifier) algorithms. The quality of the trained model was tested on test data. Statistical data processing, development of classification models, their testing and assessment of the quality of training were performed in the Jupyter Notebook environment v.6.5.2.Results. The training quality indicators of single-class models for recognizing BC subtypes were as follows: sensitivity in determining luminal A subtype (LA) was 67.0 %, luminal B subtype (LB) – 72.7 %, luminal B HER2-positive subtype (LBH) – 81.8 %, non-luminal HER2-positive (HER) and triple negative breast cancer (TNC) – 100 %. The specificity was 90.2 % for LA, 83.0 % for LB, 89.7 % for LBH, 98.3 % and 93.5 % in the cases of HER and TNC, respectively.The area under the ROC curve (AUC) depending on the molecular subtype was determined as follows: for LA – 0.88, for LB – 0.86, for LBH – 0.87, for HER – 0.96, and for TNC – 1.000. The multiclass model also showed low sensitivity values, except for the TNC (100 %) and HER (85.7 %) subtypes, low levels of positive predictive value for all subtypes, except for TNC (91.7 %), and high specificity and negative predictive value for all subtypes. The area under the ROC curve for the multiclass model was for the subtypes: LA – 0.88, LB – 0.86, LBH – 0.86, HER – 0.95 and for TNC – 1.00.Conclusion. The possibility of using certain combinations of diagnostic features obtained as a result of radiation diagnostic methods to determine the probability of a molecular biological subtype of BC was proven. This indicates the presence of prerequisites for the creation of a new diagnostic tool for typing BC using classification models of artificial intelligence. In the future, its implementation will reduce the likelihood of an error in determining the molecular biological subtype of BC, especially in situations where the doctor»s opinion and the results of the immunohistochemical study do not coincide.

Exploring the Potential of Breast Microbiota as Biomarker for Breast Cancer and Therapeutic Response

BMI is an independent prognostic factor for late outcome in patients diagnosed with early breast cancer: A landmark survival analysis

Introduction: Family history of breast cancer has been shown to be a strong risk factor for breast cancer in all populations studied. However, there are limited data related to risk of estrogen receptor negative (ER-) breast cancer in African American women, who have a disproportionately high incidence of ER- and triple negative (ER-, progesterone receptor negative, and HER2 receptor negative; TN) breast cancer. Even less information is available on whether a family history of other cancers also affects risk of ER- and TN breast cancer. Methods: Questionnaire data from the Black Women's Health Study, the Carolina Breast Cancer Study, the Multiethnic Cohort Study, and the Women's Circle of Health Study were pooled as part of the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium. Breast cancer cases were classified as ER+, ER-, and TN based on pathology data from medical records and/or state cancer registries. Participants were asked about first degree relatives with a breast cancer diagnosis and the age at which the relative was diagnosed. Participants were also asked about first degree relatives with prostate, lung, colorectal, ovarian, or cervical cancer or with lymphoma or leukemia. Polytomous logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for various categories of positive family history relative to no first degree relative with breast cancer or no first degree relative with any of the cancers. Multivariable analyses controlled for age, study, time period, and other potential confounders. Results: The analysis included 3,023 African American women with ER+, 1,497 with ER-, and 696 with TN breast cancer and 17,420 controls. First degree family history of breast cancer, regardless of whether first degree relatives had cancers other than breast cancer, was associated with a 70% increased risk of ER+, ER- and TN breast cancer; the ORs were 1.7 (95% CI 1.6-2.0) for ER+, 1.7 (95% CI 1.4-1.9) for ER-, and 1.7 (95% CI 1.4-2.1) for TN breast cancer. The ORs were somewhat higher if the relative was diagnosed before age 50 (2.0 for ER+, 1.9 for ER-, and 1.8 for TN). Among the six other cancer sites examined, only family history of cervical cancer was significantly associated with risk; the ORs were 2.4 (1.4-4.2) for ER- and 2.9 (1.5-5.5) for TN breast cancer and there was no association with ER+ breast cancer. The OR for family history of ovarian cancer in relation to TN breast cancer was 1.6 (0.9-2.7), which is of interest because findings from The Cancer Genome Atlas (TCGA) indicate that serous ovarian cancers and basal-like breast cancers, which are mostly triple negative, have many molecular commonalities. The ORs for a family history of both breast and prostate cancer versus no family history of any of the cancers were 3.4 (2.4-4.7) for ER+ cancer, as compared with 1.6 for breast alone (p-interaction=0.01), and 2.1 (1.2-3.7) for ER- cancer, as compared with 1.5 for breast alone (p-interaction=0.08). The OR for a family history of both breast and lung cancer was 3.3 (1.9-5.9) for TN breast cancer, compared to 1.5 for breast alone (p-interaction=0.10). The ORs for family history of breast plus two other cancers were 2.4 (1.6-3.6) for ER+, 2.8 (1.6-4.7) for ER-, and 2.7 (1.3-5.7) for TN breast cancer. Conclusion: Our results confirm that having a first degree family history of breast cancer is a strong risk factor for ER+, ER-, and TN breast cancer. The findings also suggest that having relatives with other cancers in addition to a relative with breast cancer may further increase risk. Consideration of family history of other cancers may improve risk prediction models. The association observed for family history of cervical cancer and increased risk of ER- and TN breast cancer was unexpected and needs to be replicated by other studies. Citation Format: Traci N. Bethea, Lynn Rosenberg, Nelsy Castro-Webb, Kathryn L. Lunetta, Lara E. Sucheston, Edward A. Ruiz-Narvaez, Marjory Charlot, Song Y. Park, Elisa V. Bandera, Melissa A. Troester, Christine B. Ambrosone, Julie R. Palmer. Relation of family history of cancer to risk of ER+, ER-, and triple-negative breast cancer in African American women. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr C49.

BackgroundWhether tumour-infiltrating lymphocytes (TILs) play different roles in different molecular subtypes of breast cancer remains unknown. Additionally, their prognostic and predictive value in different molecular subtypes of breast cancer is still controversial. The aim of our meta-analysis was to assess the prognostic and predictive value of TILs in different molecular subtypes of breast cancer by summarizing all relevant studies performing multivariate analysis.MethodsPubMed, Embase, EBSCO, ScienceDirect, the Cochrane Database and Web of Science were comprehensively searched (until March 2020). Hazard ratios (HRs), odds ratios (ORs) and their 95% confidence intervals (CIs) were used as effect measures to perform our meta-analysis. A random effect model was used. Stata software, version 15 (2017) (StataCorp, College Station, TX, USA) was used to perform the statistical analysis.ResultsThirty-three studies including 18,170 eligible breast cancer patients were analysed. The meta-analysis showed that high TIL expression was significantly associated with increased pathological complete response (pCR) rates after neoadjuvant chemotherapy in patients with the HER2-enriched molecular subtype (OR = 1.137, 95% CI [1.061 ~ 1.218], p < 0.001) and triple-negative breast cancer (TNBC) subtype (OR = 1.120, 95% CI [1.061 ~ 1.182], p < 0.001). However, high TIL expression was not significantly associated with high pCR rates after neoadjuvant chemotherapy in patients with the luminal molecular subtype of breast cancer (OR = 1.154, 95% CI [0.789 ~ 1.690], p = 0.460). We carried out a meta-analysis on the HRs of overall survival (OS) and disease-free survival (DFS) to assess the prognostic value of TILs in breast cancer with different molecular subtypes more deeply. Our meta-analysis confirmed that high TILs were associated with significantly improved DFS in patients with the HER2-enriched molecular subtype [HR = 0.940, 95% CI (0.903 ~ 0.979), p = 0.003] and TNBC molecular subtype [HR = 0.907, 95% CI (0.862 ~ 0.954), p < 0.001]. However, high TILs were not associated with significantly better DFS in patients with the luminal molecular subtype of breast cancer [HR = 0.998, 95% CI (0.977 ~ 1.019), p = 0.840]. Furthermore, the results confirmed that high TILs were significantly related to better OS in patients with the HER2-enriched molecular subtype [HR = 0.910, 95% CI (0.866 ~ 0.957), p < 0.001] and TNBC molecular subtype [HR = 0.869, 95% CI (0.836 ~ 0.904), p < 0.001]. Conversely, the summarized results indicated that high TILs were significantly associated with poor OS in patients with the luminal molecular subtype of breast cancer [HR = 1.077, 95% CI (1.016 ~ 1.141), p = 0.012].ConclusionsOur meta-analysis confirms that high TILs are associated with favourable survival and predicts pCR in breast cancer patients with the TNBC and HER2-enriched molecular subtypes.

Background: In the US, the number of breast cancer (BC) survivors is expected to increase to 5 million by 2030. Although it is well established that BC survivors are at increased risk of second primary cancer (SPC), little is known about the characteristics of these tumors. Methods: We conducted a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER) 18 database to compare the tumor characteristics of first primary cancer (FPC) to SPC among women diagnosed with BC between 2000-2016. For this analysis, we focused on breast, lung, colorectal, uterine, and cervical cancer. Odds ratio (OR) and 95% confidence interval (CI) for tumor characteristics comparing SPC to FPC were estimated from logistic or multinomial logistic regression, adjusting for race/ethnicity, year of diagnosis, and age at diagnosis. Tumor characteristics included summary tumor stage, T stage, tumor grade, hormone receptor (HR) status of BC, molecular subtype of BC, Oncotype DX score of BC for a subset (N=48,826), and histologic subtype of lung cancer. Results: The study population included 14,392 second and 586,788 first BC, 5,202 second and 246,543 first lung cancers, 3,525 second and 190,640 first colorectal cancers, 2,517 second and 125,818 first uterine cancers, as well as 230 second and 42,601 first cervical cancers. Women with SPC were older than women with FPC. Compared to FPC, SPC were more likely to be diagnosed at local stage for breast (OR: 1.30, 95%CI: 1.25-1.34), lung (OR: 1.57, 95%CI: 1.47-1.68), colorectal (OR: 1.20, 95%CI: 1.12-1.28), and cervical cancer (OR: 1.59, 95%CI: 1.19-2.12), but not for uterine cancer (OR: 1.07, 95%CI: 0.98-1.17). Second breast (OR: 1.26, 95%CI: 1.21-1.31) and uterine (OR: 1.83, 95%CI: 1.65-2.03) cancers were more likely to present at poorly or undifferentiated tumor grade after adjusting for tumor stage. No difference in tumor grade was found for lung, colorectal, and cervical cancer. Second BC were more likely to be of hormone receptor (HR) negative (OR: 1.64, 95%CI: 1.57-1.71), human epidermal growth factor receptor 2 (HER2) enriched (OR:1.30, 95%CI: 1.16-1.45) and triple negative (OR: 1.66, 95%: 1.55-1.77) subtype, and having Oncotype DX score above 26 (OR: 1.73, 95%CI: 1.47-2.04). Second lung cancers were more likely to be of small cell histology compared to first lung cancers (OR =1.15, 95%CI: 1.06-1.25). Conclusion: Screen-detectable second cancers were diagnosed at an earlier stage compared with first cancers. Further, second breast, uterine, and lung cancer had a more aggressive tumor profile compared to women with a similar type of first cancer suggestive of underlying biological differences between the two groups. It is plausible that more intensive screening strategies akin to screening recommendations for women at high risk of BC may be needed for survivors at risk for certain second cancers. Citation Format: Zhengyi Deng, Miranda R. Jones, Kala Visvanathan. Comparison of tumor profiles of second cancers among breast cancer survivors to first cancers in the SEER registries: A nationwide study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 896.

Triple-negative breast cancer (TNBC) patients have the poorest clinical outcomes compared to other molecular subtypes of breast cancer. IL6/JAK/STAT3 signalling is upregulated in breast cancer; however, there is limited evidence for its role in TNBC. This study aimed to assess the expression of IL6/JAK/STAT3 in TNBC as a prognostic biomarker. Tissue microarrays consisting of breast cancer specimens from a retrospective cohort (n = 850) were stained for IL6R, JAK1, JAK2 and STAT3 via immunohistochemistry. Staining intensity was assessed by weighted histoscore and analysed for association with survival/clinical characteristics. In a subset of patients (n = 14) bulk transcriptional profiling was performed using TempO-Seq. Nanostring GeoMx® digital spatial profiling was utilised to establish the differential spatial gene expression in high STAT3 tumours. In TNBC patients, high expression of stromal STAT3 was associated with reduced cancer-specific survival (HR = 2.202, 95% CI: 1.148-4.224, log rank p = 0.018). TNBC patients with high stromal STAT3 had reduced CD4+ T-cell infiltrates within the tumour (p = 0.001) and higher tumour budding (p = 0.003). Gene set enrichment analysis (GSEA) of bulk RNA sequencing showed high stromal STAT3 tumours were characterised by enrichment of IFNγ, upregulation of KRAS signalling and inflammatory signalling Hallmark pathways. GeoMx™ spatial profiling showed high stromal STAT3 samples. Pan cytokeratin (panCK)-negative regions were enriched for CD27 (p < 0.001), CD3 (p < 0.05) and CD8 (p < 0.001). In panCK-positive regions, high stromal STAT3 regions had higher expression of VEGFA (p < 0.05). High expression of IL6/JAK/STAT3 proteins was associated with poor prognosis and characterised by distinct underlying biology in TNBC.

Breast cancer is the second leading cause of cancer mortality in women after lung cancer; however, it is the primary cause of death among Hispanic women. About 10-20% of breast cancers are basal (triple-negative) subtype at the time of diagnosis, and they do not respond well to treatment regimens due to a lack of specific targets. Triple-negative breast cancer is a deadly and very aggressive tumor type associated with poor prognosis compared to other molecular subtypes of breast cancer, especially among Hispanic women. Thus, identifying novel molecules with prognostic and therapeutic value is critical to treat this ever-evolving disease. Numerous studies suggest that genes transcribed from chromosome X (X-linked genes) are implicated in cancers. The expression of these genes is tightly regulated and restricted to immune-privileged organs; however, many of them escape regulation and become aberrantly expressed in tumors.Interestingly, our genomic analysis suggests that several newly annotated X-linked genes are cancer testis-antigens (CT genes) that are highly antigenic and are located at regions previously considered to be gene deserts in the human genome. To date, very minimal is known about their expression and role in triple-negative breast cancer. In this regard, we used an integrated genomic approach to identify testis-tissue-specific genes that are differentially expressed in triple-negative breast cancer. Further, we identified a highly immunogenic cancer-testis gene by incorporating cutting-edge technology-driven (Global Run-On Sequencing) gene expression analysis. Mechanistically, by using cell-, mouse-based, and genomic approaches, we have found that candidate CT gene modulates gene expression, immune response, and tumor growth in triple-negative breast cancer. Hence, it has the potential to change the way triple-negative breast cancer is diagnosed and treated. S.S.G. is supported by a First-time Faculty Recruitment Award from the Cancer Prevention and Research Institute of Texas (CPRIT; RR170020). S.S.G. is also supported by a grant from Lizanell and Colbert Coldwell foundation. Citation Format: Melina J Sedano, Alana L Harrison, Ine le, Shrikanth S Gadad. The role of a cancer testis-antigen in regulating tumor growth and oncogenic pathways in triple-negative breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-12-12.

Background: Apoptosis signalling is controlled by a complex interaction of pro- and anti-apoptotic BCL2 proteins and its dysregulation is believed to be a major contributor to therapy responses and resistance in cancer. We previously demonstrated that inhibition of cell death in cancer cell is associated to poor outcome in colorectal cancer (Lindner et al., Cancer Res, 2012) and to lower cell death in triple negative breast cancer (TNBC) cells in vitro (Lucantoni et al., in review). In ER+ breast cancer, the anti-apoptotic protein BCL2 is commonly overexpressed, but its expression is associated with improved clinical outcome. The aim of this study was to assess whether system modelling of BCL2 protein interactions stratifies low- and high-risk breast cancer patients, and to determine the contribution of apoptosis signalling in different molecular subtypes of breast cancer. Methods: Protein levels of BAK, BAX, BCL2 and BCL(X) were determined in fresh frozen, TNBC samples from the BREAST-PREDICT Irish Cancer Society Collaborative Research Centre cohort, using HeLa cells as standard in which absolute protein levels were previously determined. Clinical, protein level and gene expression datasets of 845 invasive breast carcinoma patients were accessed from The Cancer Genome Atlas project, and BCL2 protein profiles were calculated by linear regression based on the BREAST-PREDICT cohort. In both cohorts, profiles were used to calculate the stress dose required to induce mitochondrial apoptosis (η). Results: In contrast to experiments with TNBC cells in which a high η indicated lower rates of cell death in vitro (Lucantoni et al., in review), we found that in breast cancer patients, η ≤ 0 was associated with lower overall survival (OS) compare to η &amp;gt; 0 (HR 2.1, 95%CI 1.3-3.3, p &amp;lt; 0.01). η &amp;gt; 0 was associated with lower levels of cleaved caspase 7 compared to η ≤ 0 (ANOVA &amp; Tukey post-hoc; p &amp;lt; 0.1). Cleaved caspase 7 levels &amp;gt; mean were associated with improved OS compared to levels ≤ mean (HR 0.4, 95%CI 0.3-0.7, p = 0.001). High values of η were significantly associated with lower proliferation in ER/PR+ cancer (ANOVA &amp; Tukey post-hoc; p &amp;lt; 0.01), but not in HER2+ or TNBC. Next we performed hierarchical cluster analysis (ConsensusClusterPlus; Monti et al, Machine Learning, 2003) with 61 additional mRNAs and proteins which are not implemented in our systems modelling approach. We found a subgroup with high BAD, PUMA, BOK and TRADD mRNA expression levels in ER/PR+ breast cancer patients, independently of the value of η. ER/PR+, but not HER2+ or TNBC, patients with an averaged expression of these 4 mRNA &amp;gt; mean had significant higher OS compared with patients with an averaged expression ≤ mean (HR 0.4, 95%CI 0.2-0.9, p = 0.02). Conclusions: Impairment of apoptosis assessed solely on the levels of BAK, BAX, BCL2 and BCLX(L) proteins were not sufficient as prognostic marker in breast cancer patients. However, our analysis suggest that patients with ER/PR+ cancer cells potentially 'primed' towards apoptosis - via the expression of pro-apoptotic BAD, PUMA, BOK and TRADD - had a more favourable clinical outcome compared to patients with cancer cells lacking this priming. Citation Format: Lindner AU, Lucantoni F, Vareslija D, Resler A, Gallagher WM, Hill A, Young L, Prehn JHM. High expression of BAD, PUMA, BOK and TRADD mRNA is associated with higher overall survival in ER+ and PR+ breast cancer patients [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-10-02.

BackgroundTissue inhibitor of metalloproteinases-1 (TIMP-1) is a multifunctional protein that can directly regulate apoptosis and metastasis. In this study, we investigated the functional and molecular mechanisms by which TIMP-1 influences triple-negative breast cancer (TNBC).MethodsThe expression level of TIMP-1 in breast cancer tissues was analyzed using the ONCOMINE microarray database. The overall survival of patients with distinct molecular subtypes of breast cancer stratified by TIMP-1 expression levels was evaluated using Kaplan–Meier analysis. Bisulfate sequencing PCR (BSP) was used to analyze the methylation status of the TIMP-1 promoter. Real-time-PCR (RT-PCR), Western blot and ELISA assays were used to evaluate gene and protein expression in cell lines and human tissue specimens. In addition, TIMP-1 function was analyzed using a series of in vitro and in vivo assays with cells in which TIMP-1 was inhibited using RNAi or neutralizing antibodies.ResultsWe found that serum TIMP-1 levels were strongly enhanced in patients with TNBC and that elevated TIMP-1 levels were associated with a poor prognosis in TNBC. However, TIMP-1 levels were not significantly associated with overall survival in other subtypes of breast cancer or in the overall population of breast cancer patients. We also report the first evidence that the TIMP-1 promoter is hypomethylated in TNBC cell lines compared with non-TNBC cell lines, suggesting that aberrant TIMP-1 expression in TNBC results from reduced DNA methylation. RNAi-mediated silencing of TIMP-1 in TNBC cells induced cell cycle arrest at the G1 phase and reduced cyclin D1 expression. In addition, mechanistic analyses revealed that the p-Akt and p-NF-κB signaling pathways, but not the GSK-3β and MAPK1/2 pathways, are associated with TIMP-1 overexpression in TNBC cells. Moreover, neutralizing antibodies against TIMP-1 significantly decreased the rate of tumor growth in vivo.ConclusionsOur findings suggest that TIMP-1 is a biomarker indicative of a poor prognosis in TNBC patients and that targeting TIMP-1 may provide an attractive therapeutic intervention specifically for triple-negative breast cancer patients.

Simple SummaryImmunotherapies for breast cancer (BC) are among the most promising treatments for mammary gland malignancies, but their tissue and cellular targets are heterogeneous and controversial. Hence, the effectiveness of immunotherapy varies. Tertiary lymphoid structures (TLSs) are paid the most attention among these therapies due to the favorable prognostic function they have been shown to play for several malignancies, but this has less investigated for BC because they are not at all connected to some BC molecular subtypes and the stromal vascular network. Moreover, research on the TLS’s impact on lymphovascular, perineural, and BC recurrence is inconsistent. In the current investigation, significant variations between TLS positive and TLS negative subgroups within the same BC molecular subtype were observed and had a significant impact on BC recurrence, lymphovascular invasion, and perineural invasion. By promoting quick blood vessel maturation followed by lowering lymphovascular or perineural invasion, and recurrence, BC-associated TLSs seem to have a local protective role against tumor spread.Background: Tertiary lymphoid structures (TLSs) mediate local antitumor immunity, and interest in them significantly increased since cancer immunotherapy was implemented. We examined TLS− tumor stromal blood vessel interplay for each breast cancer (BC) molecular subtype related to recurrence, lymphovascular invasion (LVI), and perineural invasion (PnI). Methods: TLSs were quantified on hematoxylin and eosin stain specimens followed by CD34/smooth muscle actin (SMA) double immunostaining for stromal blood vessel maturation assessment. Statistical analysis linked microscopy to recurrence, LVI, and PnI. Results: TLS negative (TLS−) subgroups in each BC molecular subtype (except to Luminal A) have higher LVI, PnI, and recurrence. A significant rise in LVI and PnI were observed for the HER2+/TLS− subgroup (p < 0.001). The triple negative breast cancer (TNBC)/TLS− subgroup had the highest recurrence and invasion risk which was also significantly related to tumor grade. PnI but not LVI significantly influenced recurrence in the TNBC/TLS+ subgroup (p < 0.001). TLS−stromal blood vessel interrelation was different amongst BC molecular subtypes. Conclusion: BC invasion and recurrence are strongly influenced by TLS presence and stromal blood vessels, especially for HER2 and TNBC BC molecular subtypes.

The role of VEGF in triple-negative breast cancer: where do we go from here?

Background: Breast cancer is a heterogeneous disease. Triple-negative breast cancer (TNBC) as defined by negativity in estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), has a distinct disease course and response to treatment, compared with ER+ breast cancer. Circulating microRNAs (miRNAs) have been suggested as promising diagnostic and early detection biomarkers for cancer, including breast cancer, as miRNAs can be detected in extra-cellular biofluids at stable levels. However, findings from previous studies of circulating miRNA are inconsistent, which may be in part due to the heterogeneity nature of breast cancer. Methods: To characterize the differential expression pattern of circulating miRNAs in TNBC from ER+ breast cancer, we performed a whole miRNome profiling experiment using Exiqon miRCURY microRNA qRT-PCR Human panels which include 752 miRNAs. Total RNA was extracted from 200ul serum of 27 luminal A-like breast cancer patients (ER+/PR+/HER2-), 18 TNBC, and 31 volunteer controls who did not have breast cancer. After global mean normalization, we used linear models and empirical Bayes methods to examine expression differences across the three groups. Benjamini and Hochberg's false discovery rate method was used to correct for multiple testing. Penalized logistic regression was used to build a profile of miRNAs that can distinguish TNBC from luminal A-like breast cancer. Results: The mean age was similar between the three groups (luminal A-like: 51.1, TNBC: 52.5, and controls: 50.6 years old). A total of 226 miRNAs could be detected in more than half of the samples and were included for further analysis. Of them, 20 miRNAs were differently expressed between luminal A-like and control groups, and 12 were different between TNBC and controls. In the contrast between TNBC and luminal A-like breast cancer, we found 34 miRNAs were significantly different, with the most significant miRNA being miR-423 (p = 8.8e-5). The multivariable logistic regression identified a panel of 7 miRNAs which can distinguish TNBC and luminal A-like tumors. ROC analysis found these 7 miRNAs had good discriminatory power (area under ROC curve = 0.865). Conclusion: Our study demonstrates the existence of a set of circulating miRNAs specific to TNBC, which has a clear “fingerprint” to differentiate TNBC from luminal A-like breast cancer. This finding suggests that early detection markers for different breast cancer subtypes may be distinct. It is also interesting to further investigate if different miRNA profiles in circulation between breast cancer subtypes are derived directly from tumors or from other sources in response to tumors. Citation Format: Dezheng Huo, Wendy M. Clayton, Toshio F. Yoshimatsu, Jianjun Chen, Olufunmilayo I. Olopade. Breast cancer molecular subtypes are reflected in circulating microRNA profiles. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3995. doi:10.1158/1538-7445.AM2015-3995

In resource-limited settings, data regarding the impact of molecular/receptor subtypes on breast cancer (BC) are sparse. In this single-center retrospective study from north India, we analyze the outcomes of various molecular subtypes of BC. Females with biopsy-proven BC who were treated at our State Cancer Institute from 2014-2018 were included. Data regarding clinicopathological parameters and follow-up details were evaluated. For data analysis, cancers were categorized into 4 subtypes: HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-. Among 944 patients included, HR+HER2- (49.1%) and HR+HER2+ (13.1%) were the most and least common subtypes, respectively. The receptor subtype significantly impacted overall survival (OS). HR+HER2- cancers had the best outcomes while HR-HER2- cancers fared worst (3-yr OS of 94.3% and 69.1%, respectively). On subgroup analysis, the molecular subtype continued to significantly impact OS in patients with tumor grades II and III, disease stages II and III, and age groups of <40 and 40-60 years, respectively (HR-HER2- cancers had the lowest cumulative survival in each subgroup). In patients with metastatic BC, all molecular subtypes except HR+HER2- had a dismal prognosis. Overall and across various subgroups, patients with triple-negative BC had the poorest outcomes. Ensuring optimal treatment utilization including affordable access to personalized tailored therapy is the need of the hour to improve long-term outcomes in these patients.

To explore the associations between dietary factors and breast cancer (BC) molecular subtypes. The retrospective cases were confirmed by pathological diagnosis with breast cancer were gathered in two major hospitals in Xuzhou city, China, from 2015 to 2016. These cases were classified by the meeting standard of 13th St Gallen: luminal A, luminal B, Her‐2 overexpression, and triple‐negative breast cancer (TNBC) subtypes. A 1:2 paired retrospective case–control study with 210 cases and 420 controls was conducted to evaluate individual dietary intake, by food frequency questionnaire (FFQ) and estimate odds ratios (ORs), by the Cox regression model. For overall breast cancer patients, the more frequency of red meat (OR = 1.002, 95% CI = 1.001–1.004) and salted food (OR = 1.003, 95% CI = 1.001–1.005) were statistically significantly associated with a greater risk of breast cancer. Beans (OR = 0.997, 95% CI = 0.995–0.999), white meat (OR = 0.993, 95% CI = 0.989–0.997), aquatic products (OR = 0.990, 95% CI = 0.984–0.996), vegetables (OR = 0.999, 95% CI = 0.999–0.999), fruit (OR = 0.998, 95% CI = 0.997–0.999), and green tea (OR = 0.997, 95% CI = 0.994–0.999) were significantly associated with a lower risk of breast cancer. For luminal breast cancer patients, beans (OR = 0.997, 95% CI = 0.994–0.999), white meat (OR = 0.992, 95% CI = 0.987–0.997), green tea (OR = 0.995, 95% CI = 0.991–0.999), and milk (OR = 0.998, 95% CI = 0.996–0.999) were protective factors. While for nonluminal breast cancer, red meat was not included in the equation, and beans (OR = 0.989, 95% CI = 0.981–0.997), white meat (OR = 0.989, 95% CI = 0.981–0.998), vegetables (OR = 0.998, 95% CI = 0.997–0.999), and milk (OR = 0.994, 95% CI = 0.989–0.999) still showed a significantly reduced risk of nonluminal breast cancer. Different dietary factors revealed different effects on the etiology of breast cancer. Red meat may be a specific risk factor for luminal‐type breast cancer.