ELMO: An Efficient Logistic Regression-Based Multi-Omic Integrated Analysis Method for Breast Cancer Intrinsic Subtypes

BACKGROUND:Molecular subtyping of breast cancer cells is increasingly being developed as an initial step in selecting therapy and predicting the prognosis of breast cancer patients. During breast cancer, the molecular subtype of cancer cells can change. This study aimed to analyze the relationship between changes in the intrinsic subtype of breast cancer with metastasis and progression-free survival in breast cancer patients.METHODS:This was a retrospective cohort study of patients diagnosed with breast cancer from 2016 to 2021. The molecular subtypes from the immunohistochemical examination results were recorded twice, and metastasis and progression-free survival (PFS) were recorded. The data were analyzed using the chi-square test and SPSS 26.RESULTS:Of the 44 patients, 19 (43.2%) experienced a change in molecular subtype, and 25 (56.8%) did not. No significant relationship existed between changes in molecular subtype and metastasis (p = 0.405). No significant relationship existed between changes in molecular subtype and PFS (p = 0.900). A significant relationship was found between changes in the molecular subtype and PFS in the patients with changes in the molecular subtype (p = 0.022).CONCLUSIONS:Changes in the intrinsic subtype were associated with PFS in breast cancer patients. Patients with an intrinsic subtype that changed to triple-negative showed worse PFS.

Background: Breast cancer (BC) is a heterogeneous disease. It is estimated that 5 to 10% of all BC to have a germline genetic predisposition. A 50-gene assay (PAM50) identifies 5 intrinsic molecular subtypes (IMS): Luminal A, Luminal B, HER2-enriched, Basal-like, and Normal-like. Basal-like breast cancers are enriched for BRCA1/2 germline mutations. Deleterious mutations in BRCA1/2 or other DNA-damage repair (DDR) genes may increase tumor mutational burden (TMB), a biomarker for response to checkpoint inhibition therapy. We sought to determine the spectrum of germline mutations in molecular BC subtypes (IMS), and their relation to somatic TMB. Methods: We performed a retrospective analysis of data from NantHealth database. RNAseq was used to classify breast tumors into IMS. Germline variants within putative driver genes (COSMIC v.76) were detected in analysis of 181 whole-genomes and 89 whole-exomes sequenced using Illumina chemistry. Classification of germline variants into potentially pathogenic variants (pPv) was determined using ClinVar database annotation. Patients were categorized as TMB-high by thresholding on >200 non-synonymous exonic somatic mutations as was previously reported. Results: A total of 270 BC patients with comprehensive omics profiling (germline DNAseq, somatic DNAseq, and somatic RNAseq) were available for this analysis. The mean age (±SD) was 56.4 (± 12.5) years (range 20.8-86.5). Forty-six patients (17.0%) were classified TMB-high. The IMS distribution was 40.7% Luminal A, 31.5% Luminal B, 5.9% HER2-enriched, 21.5% Basal-like, and 0.37% Normal-like. Over 200 unique germline variants were detected of which 98 were pPv according to ClinVar annotation. These pPv spanned 21 genes, 7 of which are directly related to DDR. One hundred and four patients had ≥1 pPv (78 had only 1 pPv, and 26 had >1 pPv). The most common pPv were APC (5.9%), BRCA2 (5.2%), TSC2 (4.4%), BRCA1 (3.7%), SDHB (3.3%), SDHD (3.3%), TSC1 (3.0%), PMS2 (3.0%), MUTYH (2.6%), MSH2 (1.5%) and MSH6 (1.5%). BRCA1 and especially BRCA2 pPv were mostly seen in the basal-like patients. Luminal B had distinctly more germline pPv in PMS2, BRCA1 & BRCA2 than Luminal A. TMB-high patients were not significantly enriched for germline pPv (OR 0.73, p=0.41), even when limited to pPv in DDR genes (OR 0.69, p=0.52). TMB-high patients were present in all 4 major IMS types; Her2-enriched 37.5%, Luminal B 23.5%, Basal-like 17.2%, and Luminal A 9.1%. Conclusion: We identified differential distribution of germline pPv in BC IMS. Of the pPv found, APC was the most commonly detected pPv across subtypes, while BRCA1/2 pPv were clustered in Basal-like subtype, and PMS2 in Luminal B subtype. 17% of all patients had a pPv within at least one DDR gene, that potentially may benefit from targeted therapy. Despite IMS types having distinct germline pPv profiles especially in DDR genes, there was no association with subsequent somatic TMB. This suggests that either 1. somatic events are the primary drivers of TMB, or 2. that germline variants with either unknown or benign significance need to be revisited. Future analysis in a larger demographically well-annotated dataset (commercial data, ExAC, other) or via functional studies should be considered. Citation Format: Obeid E, Reddy SB, Goldstein LJ, Daly MB, Benz SC, Hall MJ, Szeto C. Germline potentially pathogenic variants in breast cancer intrinsic molecular subtypes are not associated with somatic TMB [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-03-03.

Background In metastatic triple negative breast cancer (mTNBC), median progression-free survival (PFS) with chemotherapy alone is approximately 2–4 months1 and improvements with single agent checkpoint inhibitors (CI) are limited by...

Backgrounds: Breast cancer (BC) is a heterogeneous disease and usually divided into 5 subtypes according to clinicopathologic features. These subtypes have concordance with mRNA-based subtypes called as "intrinsic subtypes". Further gene expression analysis categorized triple negative BCs into 7 sub-subtypes which relate to clinical behaviors. DNA methylation is one of the epigenetic systems to regulate gene transcription. DNA methylation in CpG islands (CGIs) associated with the gene promoter region affects gene expression levels. Recently genome-wide analyses suggested that methylation status not only in CGIs, but also in CpG shores (within 2000 bps from CGIs) and CpG shelves (2000-4000 bps from CGIs) contribute to gene silencing. Thus, we hypothesized that intrinsic subtypes may possess specific methylation profiles especially in regions surrounding CGIs (islands, shores and shelves). To date, several reports demonstrated each intrinsic subtype has specific methylation patterns in CGIs. They indicate that DNA methylation is promising markers for cancer detection, prediction of therapeutic response and clinical outcomes. However, there were no report that conducted a genome-wide high-resolution epigenetic analysis for BC. Objectives: This study aims to determine whether specific DNA methylation patterns exist in CGIs, shores and shelves in BC cells, and whether the DNA methylation-based classification correlates with intrinsic subtypes, furthermore, to identify the subtype specific epigenetic markers using high-resolution methylation array. Materials and Methods: DNA was extracted from 31 samples of 28 BC cell lines (8 luminal, 18 basal, 2 unclassified) and 3 samples of 3 non-BC cell lines. We performed genome-wide methylation analysis using Illumina Infinium HumanMethylation450 BeadChip. We did unsupervised hierarchical clustering analysis of cell lines using top 3000 variably methylated (VM) loci among cancer cell lines. We also analyzed top 3000 VM CGI-related loci. Gene functional annotation clustering was performed using DAVID. Results: In top 3000 VM loci, CGIs were most frequently observed (43.0%). According to clustering analysis using top 3000 VM loci, cell lines were roughly classified into 4 clusters. There were trends that cell lines of same subtype fell into the same cluster, but not definitely. In case of clustering using top 3000 VM CGI-related loci, cell lines were clearly divided into 2 clusters, high and low methylated clusters. High methylated cluster contained almost all luminal cell lines and low methylated cluster contained most of basal cell lines and all non-BC cell lines. In low methylated cluster, cell lines of the same sub-subtype, such as Basal-like 1 and 2, were clustered closely. Gene functional annotation clustering suggested that genes related to "transcription" and "differentiation" were more frequently regulated by epigenetics. Conclusions: High-resolution methylation analysis revealed methylation-based clusters were concordant with intrinsic subtypes in BC cells. Transcriptional factors and differentiation-related genes could be differently regulated by epigenetics among different subtypes of BC. Citation Format: Natsue Uehiro, Fumiaki Sato, Sunao Tanaka, Fengling Pu, Junji Itou, Shigehira Saji, Masakazu Toi. DNA methylation-based classification are mostly concordant with intrinsic subtypes of breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-06-05.

Introduction: APOlipoprotein B mRNA Editing enzyme Catalytic peptide-like, APOBEC, is a family of innate immune enzymes that catalyze cytosine to uracil deamination in single-stranded DNA, which lead to mutations in preferred trinucleotide contexts. APOBEC mutagenesis portends a worse prognosis in several breast cancer subtypes and associates with increased tumor mutational burden (TMB). Specific mutations enriched with APOBEC mutation signatures and immune phenotypes are not well described. The purpose of our study was to identify genes enriched for APOBEC mutagenesis and determine their relationship to intrinsic subtypes, TMB, and the immune composition of the transcriptome in breast cancers. Methods: We queried TCGA breast cancer database involving 980 breast cancer samples. We used consensus mutation calls from four somatic mutation callers (MuTect2, VarScan2, MuSE, and SomaticSniper). APOBEC mutagenesis scores were calculated for each tumor using a published method (Nik-Zainal et al. 2012) and a modified version thereof. The score was calculated at the gene-level, to identify genes enriched for APOBEC mutagenesis, and the cancer sample-level to investigate the relationship of APOBEC mutagenesis scores with intrinsic subtypes (using PAM50), APOBEC3A and 3B expression levels, and TMB. We also undertook differential expression analysis of CIBERSORT gene signatures and individual genes from the innate immune system, IFN, TGFB, WNT, and immune checkpoints with respect to common somatic mutations in APOBEC enriched genes. Results: The genes with the strongest statistical evidence for enrichment of APOBEC mutagenesis were PIK3CA, TP53, MUC16, and TTN. Among three common somatic mutations in PIK3CA (E542K, E545K, H1047R), the APOBEC score was only observed to be associated with E542K (q=2.47 × 10−2) and E545K (q=9.81 × 10−6) mutations. APOBEC mutagenesis revealed a high degree of enrichment across all breast cancer intrinsic subtypes, 75% in luminal A, 68% in luminal B, 91% in HER2 enriched, 73% in basal, and 89% in normal-like phenotypes. APOBEC mutagenesis scores were observed to significantly associate with APOBEC3A expression (q=1.1 × 10−9) and as a trend of association with APOBEC3B expression (q=1.62 × 10−1). A strong association was observed between APOBEC mutagenesis score and elevated TMB (p<2 × 10−16). No checkpoint genes (i.e. CTLA-4, PD-1, and PD-L1) were observed to be significantly overexpressed among those tumors with E542K and E545K PIK3CA mutations. The CIBERSORT mast cell gene signature (q=1.32 × 10−2) and the individual genes TGFB3 (q=5 × 10−3), ROR (q=7.91 × 10−3), and WNT5A (q=1.92 × 10-2) were overexpressed in breast tumors with E542K PIK3CA mutations. Conclusion: APOBEC mutagenesis patterns are seemingly prevalent across all breast cancer intrinsic subtypes and associate with elevated TMB and mutations in the PIK3CA helical loop domain and TP53 gene in TCGA breast cancer samples. Cancers with PIK3CA mutations in the helical loop domain did not demonstrate checkpoint gene overexpression, but were associated with other immunosuppressive features (e.g. TGFB3 and WNT5A overexpression). Investigation into innate immune cell signaling, mast cell immune signaling, and immunosuppressive expression profiles in APOBEC mutated breast cancers with and without PIK3CA mutations may help to identify novel immune targets to combine with PI3K inhibitors in breast cancer. Citation Format: Jeremy Force, Xiaodi Qin, Dadong Zhang, P. Kelly Marcom, Jeffrey Marks, Mary Love Taylor, Carey Anders, Kouros Owzar, Jichun Xie. Characterization of gene- and sample-level APOBEC mutagenesis enrichment with respect to intrinsic subtypes, tumor mutational burden, and immune composition in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-06-02.

Background: Tamoxifen and aromatase inhibitors constitute the backbone of treatment for estrogen receptor positive early stage breast cancers based on immunohistochemical (IHC) results. While these therapies significantly reduce the risk of relapse of breast cancer, they have toxicities and add to costs. Gene expression profiling assays are widely used to quantify risk and support targeted therapies for luminal breast cancers treated with adjuvant endocrine therapy. In a prospective-retrospective analysis of the phase III CCTG MA.12 clinical trial (randomizing premenopausal women treated with adjuvant chemotherapy, to either tamoxifen or placebo for 5 years), luminal subtype by PAM50 was significantly predictive for tamoxifen benefit. However, IHC classification (as estrogen receptor positive) could not demonstrate a statistically significant benefit from tamoxifen over placebo. More accurate IHC biomarkers incorporating nestin positivity or loss of inositol polyphosphate-4-phosphate (INPP4B) have recently been optimized to identify the basal-like intrinsic subtype of breast cancer regardless of ER/PR/HER2 status. In this study, we examined the capacity of these basal biomarkers to identify intrinsic subtype and predict benefit from adjuvant tamoxifen vs. placebo in the CCTG MA.12 clinical trial Methods:492 formalin-fixed paraffin embedded blocks of primary tumor from patients randomized in the CCTG MA.12 trial were used to build tissue microarrays. IHC staining for nestin and INPP4B was done according to published methods, and interpretation was performed by pathologists with no access to molecular data. The performance of the nestin and INPP4B panel was assessed against PAM50 gene expression assay as a standard reference. A prespecified statistical plan was executed independently by the Canadian Cancer Trials Group, testing the primary hypothesis that patients with basal breast cancer, when defined as “positive for nestin or negative for INPP4B,” would not benefit from tamoxifen (primary endpoint: disease-free survival).Results: 366 primary tumor samples from the CCTG MA.12 had a full dataset available for IHCbiomarker evaluation, PAM50 subtype and clinical outcomes. Positive staining of nestin or loss of INPP4B was observed in 47 (13%) of the total cases and was significantly associated with poor prognostic factors including high grade, younger age, ER negativity, triple negative and core basal IHC status (p<0.01). “Nestin+ or INPP4B-” status was significantly associated with basal-like PAM50 gene expression subtype, while the other cases (nestin- and INPP4B+) were significantly associated with PAM50 luminal subtype. Patients assigned as basals by “nestin+ or INPP4B-” IHC status did not demonstrate a benefit from adjuvant tamoxifen vs. placebo (HR=1.39, 95%CI [0.37-5.26], p=0.63), whereas “nestin- and INPP4B+” cases displayed a significantly higher benefit from adjuvant tamoxifen vs. placebo (HR=0.67, 95% CI [0.45-0.98], p=0.04), (p-interaction=0.87). While, in this trial, ER clinical status as determined in community hospitals or centrally by single biomarker IHC was not significantly predictive for tamoxifen benefit, patients classified as IHC non-basal “nestin- and INPP4B+” within the ER+ subgroup did benefit from addition of tamoxifen (HR=0.62, 95%CI [0.38-1.01], p=0.05).Conclusions:The nestin/INPP4B IHC panel offers a feasible and inexpensive methodology to accurately identify intrinsic subtype of breast cancer. Patients assigned as IHC basal by this panel did not display a superior survival when treated with tamoxifen vs. placebo in the adjuvant setting. Within the ER+ subgroup, these cases could potentially be spared the side effects of currently recommended endocrine therapies that do not benefit this group of patients. Citation Format: Karama Asleh, Dongxia Gao, Vivien H Bramwell, Dongsheng Tu, Lois E Shepherd, Torsten O Nielsen. Predictive significance of an optimized immunohistochemical panel for basal-like breast cancer on the CCTG MA.12 phase III randomized clinical trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-11-03.

Axillary lymph node status is an important prognostic factor for breast cancer patients and sentinel lymph node biopsy (SLNB) is a less invasive surgical proxy. We examined if consecutively derived molecular subtypes from primary breast cancers provide additional predictive value for SLNB status. 1556 patients with a breast cancer > 10 mm underwent primary surgical procedure including SLNB and tumor specimens were assigned with a transcriptomics-based molecular subtype. 1020 patients had a negative sentinel node (SN) and 536 a positive. A significant association between tumor size and SN status (p < 0.0001) was found across all samples, but no association between size and SN status (p = 0.14) was found for BasL tumors. A BasL subtype was a predictor of an SN-negative status (p = 0.001, OR 0.58, 95% CI 0.38;0.90) and among the BasL, postmenopausal status was a predictor for SN-negative status (p = 0.01). Overall survival was significantly lower (p = 0.02) in patients with BasL tumors and a positive SN. Interestingly, we identified a significant correlation between hormone receptor activity and SN status within the BasL subtype. Taken together, molecular subtypes and hormone receptor activity of breast cancers add predictive value for SLNB status.

Simple SummaryPrimary systemic or neoadjuvant chemotherapy of breast cancer has become a standard therapy option in locally advanced or triple negative or Her2 positive breast cancer. Neoadjuvant chemotherapy can result in complete pathological response without residual tumor cells (tumor bed) or partial response and non-response with different amounts of reactive stroma and residual tumor cells. In this study, we characterized the mutational status of residual breast cancer cells and reactive tumor stroma devoid of residual tumor cells in partial or non-responders using next generation sequencing. Pathogenic driver-mutations are exclusively restricted to residual carcinoma cells and are absent in reactive stroma independently from intrinsic breast cancer subtypes or tumor stage. These data suggest that the absence of pathogenic mutations in a tumor bed without residual tumor cells may have prognostic implications after neoadjuvant chemotherapy. Primary systemic or neoadjuvant chemotherapy of breast cancer has become a standard therapy option in locally advanced or predefined intrinsic subtypes such as triple negative or Her2 positive breast cancer. Neoadjuvant chemotherapy can result in complete pathological response without residual tumor cells (tumor bed) or partial response and non-response with different amounts of reactive stroma and residual tumor cells. The interaction between therapy regimens and tumoral driver mutations have been extensively studied, although the reactive stroma of the tumor bed received less attention. In this study, we characterized the mutational status of residual breast cancer cells and reactive tumor stroma devoid of residual tumor cells in partial or non-responders using next generation sequencing. Twenty-one post-therapeutic breast surgical specimens after neoadjuvant chemotherapy underwent pathogenic driver-mutation screening using microdissected residual breast cancer cells and in reactive stroma adjacent to tumor bed areas. In reactive stroma, no mutations could be validated. In residual breast cancer cells, mutations were detected in sixteen of twenty-one cases (76%). In nine of these twenty-one cases (43%), pathogenic driver mutations (PIK3CA, PTEN, TP53, FN1, PLAG1) were identified. Pathogenic driver-mutations are exclusively restricted to residual carcinoma cells and are absent in reactive stroma independently from intrinsic breast cancer subtypes or tumor stage. These data suggest that the absence of pathogenic mutations in a tumor bed without residual tumor cells may have prognostic implications after neoadjuvant chemotherapy.

Late diagnosis is one of the reasons that head and neck squamous cell carcinoma (HNSCC) patients experience relative five-year survival rates ranging from 40%-66%. The molecular-level differences between early and advanced stage HNSCC may provide insight into therapeutic targets and strategies. Previous bioinformatics studies have shown mixed or limited results in identifying gene and protein markers and in developing models for discriminating between early and advanced stage HNSCC. Thus, we have investigated models for HNSCC stage prediction using RNAseq and reverse phase protein array data from The Cancer Genome Atlas and The Cancer Proteome Atlas. We systematically assessed individual and ensemble binary classifiers, using filter and wrapper feature selection methods, to develop several well-performing models. In particular, integrated models harnessing both data types consistently resulted in better performance. This study identifies informative protein and gene feature sets which may increase understanding of HNSCC progression.

Target spectrum based feature selection (TSFS): A new method based on chain coding for target detection problems

BackgroundUrinary bladder cancer (BLCA) and breast cancer (BRCA) are two cancers which are the most common cause of death. Recent studies have found that BLCA and BRCA shared commonness on many areas, such as biological mechanism, molecular subtypes and clinical stage. Therefore, a mature knowledge of BRCA can help highlight the treatment and prognosis of BLCA.MethodsTo address this issue, we performed a comprehensive integrative analysis to investigate the similarity between both cancers. Firstly, functional enrichment analysis based on differently expressed transcripts was performed. Secondly, PPI network analysis was performed to identify some hub genes in both cancers. Thirdly, the machine learning method was applied to construct cancer predictor. Finally, competing endogenous RNA (ceRNA) networks of both cancers were constructed by applying the integrated method.ResultsThe functional enrichment analysis showed that ECM-receptor interaction, Focal adhesion, PI3K-Akt signaling pathway were significantly pathways shared by BLCA and BRCA. From the PPI networks analysis, we identified some potential biomarkers shared by both cancers, such as CCNB1, CDC20, BUB2 and so on. The mRNA type and lncRNA type cancer predictor with good classifying performance were generated with machine learning approach, and some mRNA and lncRNA that contribute to cancer diagnostic were identified. By construct ceRNA networks, we identified some common cancer-associated ceRNA pairs, which may be helpful to uncover the relationship between two cancers.ConclusionsOur findings enhance the understanding of the various molecular signatures and commonalities shared by BLCA and BRCA, suggesting that BLCA may be particularly responsive to some treatments for BRCA.

ObjectiveTranscriptional profiling of epithelial ovarian cancer has revealed molecular subtypes correlating to biological and clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and investigate similarities with the well-established intrinsic molecular subtypes of breast cancer.MethodsGlobal gene expression profiling using Illumina's HT12 Bead Arrays was applied to 59 fresh-frozen serous ovarian malignant, benign and borderline tumors. Nearest centroid classification was performed applying previously published gene profiles for the ovarian and breast cancer subtypes. Correlations to gene expression modules representing key biological breast cancer features were also sought. Validation was performed using an independent, publicly available dataset.Results5,944 genes were significantly differentially expressed between benign and malignant serous ovarian tumors, with cell cycle processes enriched in the malignant subgroup. Borderline tumors were split between the two clusters. Significant correlations between the malignant serous tumors and the highly aggressive ovarian cancer signatures, and the basal-like breast cancer subtype were found. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer signature derived from borderline tumors. The borderline tumors in the study dataset, in addition, also correlated significantly to the luminal A breast cancer subtype. These findings remained when analyzed in an independent dataset, supporting links between the molecular subtypes of ovarian cancer and breast cancer beyond those recently acknowledged.ConclusionsThese data link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, and suggest that biomarkers and targeted therapies may overlap between these tumor subsets. The link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers.

Factors influencing the development of visceral metastasis of breast cancer: A retrospective multi-center study

Breast cancer is still a public health problem worldwide and is currently the most common tumor in the world. Breast cancer is a life-threatening disease in women and the leading cause of death in the female population. Breast cancer is a heterogeneous disorder with different molecular subtypes and biological characteristics, with different therapeutic functions and clinical outcomes for each molecular subtype. Furthermore, the treatment of BC is complicated by intratumoral complexity. Consequently, breast cancer risk assessment is an important part of public health. Precision medicine for breast cancer is a practice for diagnosis, treatment, screening and prevention of the disease that takes into account the patient's genetic makeup. Therefore, by identifying women who are at high risk of breast cancer, it is possible to make personalized recommendations regarding screening methods, the age at which breast screening should begin, the frequency of completing screenings, and individual counselling.

Breast cancer is the most common malignant tumor and the major cause of death among women worldwide. Molecular subtyping of breast cancer is important to individualize its management, to understand prognosis of disease and avoid overtreatment. The current study aimed at correlating the breast cancer subtypes with their different ultrasound criteria. The ultrasound findings might have an important role in predicting different groups. The current study is a retrospective study. Which was conducted on 40 females patients with breast cancer; during the period from November 2020 till March 2021.The age were 45–65 years old. They were presented to the Radiology Department, ·Ain-Shams University, Faculty of Medicine. The selected cases had been afforded from: the Breast-unit of General Surgery Hospital, El Demerdash University Hospital, Clinical Oncology &amp; Nuclear Medicine Department. When analyzing the main four breast cancer subtypes in the current work we found that the rates of Luminal A was 34%, Luminal B was 40%, HER2 was 15%, and TNBC was 11%. LA subtype was strongly associated with hypoechoic lesions showing irregular shape, speculated margin surrounded by desmoplastic reaction with posterior shadowing. LB subtype was associated with irregular shape and speculated margin with absence of desmoplastic reaction. Human Epidermal Growth Factor (HER2) subtype in the current study was found to be associated with irregular shape, lobulated margin, absent desmoplastic reaction with posterior acoustic mixed shadowing and enhancement. This could be related to suspicious microcalcifications. Triple Negative Breast Cancer (TNBC) lesions in the present work were predominantly oval in shape with• circumscribed margin; the benign looking malignant lesions which carry the worst prognosis. Based on the latter finding, the good radiologist should be aware about ultround features of different molecular subtype in order not to under diagnose a malignant breast lesion. The sonographic features as margin, shape, posterior acoustic features were significantly associated with molecular subtypes. The histopathological grade and hormone receptor status. Being able to predict the molecular subtype. The current study recommend that the radiologist should be aware about different imaging features of different molecular subtypes especially the triple negative breast cancer which had the most benign looking criteria aiming for better lesion characterization and to allow the patient to benefit from earlier non-invasive, cheap diagnosis and the curable on time treatment.