Nongenetic adaptive resistance to chemotherapy, driven by transcriptional rewiring, is emerging as a significant mechanism in tumor survival. In this study we combined longitudinal transcriptomics with temporal pattern analysis to investigate patient-specific mechanisms underlying acquired resistance in breast cancer. Matched tumor biopsies (pretreatment, posttreatment, and adjacent normal) were collected from breast cancer patients who received neoadjuvant chemotherapy. Transcriptomes were analyzed by longitudinal gene-pattern classification to track patient-specific gene expression alterations that occur during treatment. Our findings reveal that resistance-associated genes were already dysregulated in primary tumors, suggesting the presence of a preexisting drug-tolerant state. While each patient displayed unique resistance-associated gene rewiring, these alterations converged into a limited number of dysregulated functional modules. Notably, patients receiving the same treatment exhibited distinct rewiring of genes and pathways, revealing parallel, individualized routes to resistance. In conclusion, we propose that tumor cells survive chemotherapy by sustaining or amplifying a preexisting drug-tolerant state that circumvents drug action. We suggest that individualized "chemoresistome maps" could identify cancer vulnerabilities and inform personalized therapeutic strategies to overcome or prevent resistance.

Humanized tumor mice (HTM) allow for preclinical cancer treatment studies of breast cancer (BC) under human-like conditions. This study utilized HTM for the first time to investigate potential miRNA biomarker candidates for treatment response in sera and extracellular vesicles (EVs), following X-irradiation and atezolizumab (anti-PD-L1) treatment. We identified the changes of human-specific miRNAs (miR-23b-3p and miR-155-5p) after irradiation and anti-PD-L1 treatment in HTMs with human epidermal growth factor receptor 2 positive (HER2+ BC) and triple-negative breast cancer (TNBC). The high degree of conserved, circulating free miRNA in mice and men represents a challenge of our assay; however, miRNAs with ≥2 nucleotide mismatches can be employed for human-specific analysis, and even conserved miRNAs may be utilized under clearly defined conditions of human tumor growth in HTM. A comparative analysis of extracellular vesicle miRNA cargo and free-circulating serum miRNAs revealed several exosome-specific miRNAs (miR-29b-3p, miR-34c-5p, miR-203a-3p, miR-378g, and miR-382-5p) in HTMs, which are known to play roles in BC. Our findings demonstrate that HTMs are a suitable model to identify treatment-induced changes in free-circulating and exosomal miRNAs that influence tumor progression and immunological tumor defense, both locally and at distant sites. This study presents a proof-of-principle approach to analyzing cell-free nucleotides and exosomes in a human-like, preclinical in vivo setting. Further refinements are necessary to enhance the sensitivity and the specificity of the HTM-based approach.

Mixed invasive ductal and lobular breast carcinoma (IDLC) is a rare and understudied subtype of breast cancer with unique prognostic characteristics.

This study analyzed data from the SEER database and the METABRIC database. Survival outcomes of IDLC were compared with those of IDC and ILC using Kaplan-Meier survival curves and Cox regression analyses. Based on these findings, a prognostic model tailored for IDLC patients was developed using the SEER cohort, which was divided into a training set (70%) and an internal validation set (30%). The model incorporated clinical and molecular features and was externally validated using the METABRIC cohort. Its performance was assessed via C-index, AUC, calibration curves, and decision curve analysis (DCA).

A total of 26,138 early-stage IDLC patients were included, along with 391,888 IDC and 47,571 ILC patients. In unadjusted analyses, IDLC showed better overall survival (OS) and breast cancer-specific survival (BCSS) compared to both IDC and ILC. However, after multivariate adjustment, the differences in survival outcomes varied. IDLC demonstrated better OS than IDC and better BCSS than ILC. Additionally, a prognostic model for early-stage IDLC that incorporates clinical and molecular features was developed.

This study found that early-stage IDLC had superior BCSS and OS in unadjusted analyses. However, after multivariate adjustment, there was no difference in BCSS between IDLC and IDC, and no difference in OS between IDLC and ILC. A prognostic model was developed and validated, offering precise predictions of OS and BCSS.

We aimed to answer the following question: How effective is the addition of AKT inhibitors to the treatment of advanced or metastatic breast cancer?

We searched PubMed, Embase and Cochrane for randomized controlled trials (RCTs) that investigated AKT inhibitors for advanced or metastatic BC. We computed hazard-ratios (HRs) for binary endpoints.

A total of 5 RCTs were included in the meta-analysis, comprising 1,334 patients with BC. The use of AKT inhibitors demonstrated a significant improvement in OS (HR 0.70; 95% CI, 0.58-0.85; P < .001) and PFS (HR 0.6797; 95% CI, 0.5499-0.8403; P < .001) in the overall population. Within the PIK3CA/AKT1/PTEN-altered subgroup (n = 645), the OS rate also significantly favored AKT inhibitors over the control group (HR 0.62; 95% CI, 0.42-0.92; P = .019), as well as PFS (HR 0.5224; 95% CI, 0.3366-0.8105; P = .004).

Our findings suggest that the incorporation of AKT inhibitors holds promise for treating patients with advanced or metastatic PIK3CA/AKT1/PTEN-altered BC.

Major advances have been achieved in the characterization of primary breast cancer genomic profiles. Limited information is available on the genomic profile of tumors originating from different metastatic locations in recurrent/metastatic (R/M) breast cancer, especially in Asian patients. This study aims to decipher the mutational profiles of primary and R/M breast cancer in Chinese patients using next-generation sequencing.

A total of 563 breast cancer patients were enrolled, and 590 tumor tissues and matched peripheral blood samples were collected and subjected to targeted sequencing with a panel of 1,021 cancer-related genes. The mutation spectrum, DNA damage response (DDR) genes, commonly altered signal pathways, and immunotherapy-related markers were compared between primary and R/M breast cancer. The molecular differences between our cohort and the Memorial Sloan Kettering Cancer Center (MSKCC) dataset were also explored.

A total of 361 samples from primary and 229 samples from R/M breast cancer were analyzed. BRCA2, ATRX, and ATM were more frequently observed in R/M lesions among the 36 DDR genes. An ESR1 mutation and PD-L1 and PD-L2 amplification were enriched in R/M breast cancer (all p<0.05). Compared with the MSKCC dataset, we recruited more patients diagnosed at age 50 or younger and more patients with triple-negative breast cancer (TNBC) subtypes. The TNBC patients in our dataset had a higher percentage of PD-L1 amplification in metastasis tumors (p<0.05).

This study revealed the distinctive mutational features of primary and R/M tumors in Chinese breast cancer patients, which are different from those from Western countries. The enrichment of PD-L1 amplification in metastatic TNBC indicates the necessity to re-biopsy metastatic tumors for immunotherapy.

Approximately 70% of breast cancer (BC) cases are luminal-type (estrogen receptor-positive, ER+), suitable for endocrine therapy with tamoxifen as the most commonly used drug. However, about 30% of these patients develop tamoxifen resistance due to various mechanisms, primarily involving PI3K pathway activation through mutations or unknown pathways. Here, we discover, via bioinformatics analysis and clinical samples, that N6 adenine-specific DNA methyltransferase 1 (N6AMT1) is highly expressed in luminal breast cancer but downregulated in tamoxifen-resistant (TamR) BC cells. ChIP-qPCR and luciferase reporter assays showed that FOXA1 binds to the N6AMT1 promoter and enhances its transcription. In TamR models, FOXA1 and N6AMT1 are downregulated, increasing p110α protein levels (but not mRNA), phospho-AKT levels, and tamoxifen resistance. In vivo, N6AMT1 overexpression enhanced tamoxifen sensitivity, while knockdown reduced it; this sensitivity could be restored with the p110α inhibitor A66. Clinically, decreased N6AMT1 expression correlates with poor prognosis in luminal BC patients. In TamR BC organoids, combining tamoxifen with A66 further reduced growth compared to either treatment alone. Mechanistically, increased p110α levels result from inhibited degradation by E3 ubiquitin ligase NEDD4L. These findings suggest N6AMT1 as a potential luminal breast cancer biomarker and highlight the N6AMT1-p110α pathway as a therapeutic target to sensitize cells to tamoxifen.

Diagnosis and treatment decisions of hormonal breast cancers (BC) are now guided by genomic mutations determination, combined into mutational signatures, and provide insight into the patients' genomic landscape. This work aims to compare genomic data and signatures extracted from tissue samples collected in the CICLADES study to existing cohorts. Ultimately, the goal is to prove the accuracy of smaller cohorts and provide new relevant data.

DNA from patients of the CICLADES cohort was extracted, sequenced, and custom filtering was applied to the resulting files. Genomic data was pulled from 6 BC cohorts available on cBioPortal.com. In total, 2303 samples were analyzed. Mutational signatures were extracted and matched to known signatures of the Catalogue of Somatic Mutations in Cancer (COSMIC). Tumor Mutation Burden (TMB) and hypermutation were estimated and compared between samples.

PIK3CA and TP53 represented the two genes highly mutated across all cohorts. TMB was similar between the CICLADES and CBSM groups, however the MSKCC population showed a significantly higher TMB than both. Nine signatures were extracted, with recurring Single Base Substitutions (SBS) signatures like SBS1, SBS2 and SBS5. The presence of APOBEC-specific signatures was concordant with cohorts presenting APOBEC enrichment. The mean number of mutations was significantly higher in enriched samples for each analyzed cohort.

The use of comprehensive genomic profiling provided accurate evaluation of the TMB and extraction of signatures consistent with published literature. The genomic analysis of the tissue samples of the CICLADES cohort brings new and relevant data, comparable to results found in bigger cohorts.

RNF114, a member of the E3 ubiquitin ligase family, was first identified as a zinc-binding protein that exhibits frequent genomic amplification across various cancers. Previous studies have shown that inhibition of RNF114 E3 ligase activity by Nimbolide treatment can result in trapping of PARP1 and synthetic lethality in BRCA-mutated cancers, suggesting its E3 ligase role in tumor progress. However, it's important to reveal novel functions and interacting molecules of RNF114. Here, we first described that RNF114 promotes tumor proliferation and autophagy by interacting with EWSR1 and regulating VEGFR2 expression in HER2-positive breast cancer (BC). Our results also showed that RNF114 is significantly overexpressed in BC and is associated with TNM stage and poor prognosis in BC patients. And knockdown of RNF114 suppresses proliferation, migration, invasion, and autophagy of HER2-positive BC cells. Our findings highlight the transcriptional regulatory function of RNF114 in BC, offering new insights into its oncogenic role and contribution to HER2-positive BC progression.

Ferroptosis is a recently studied form of programmed cell death characterized by lipid peroxides accumulation in the cells. This process occurs when a cell's antioxidant capacity is disturbed resulting in the inability of the cell to detoxify the toxic peroxides. Two major components that regulate ferroptosis are cysteine and iron.

This study aimed to determine the effect of cysteine deficiency and iron chelation on triple-negative breast cancer (TNBC) ferroptosis in a lipid-enriched microenvironment.

The study has a laboratory-based experimental design. This study used the MDA-MB-231 cell line in various in vitro cell culture systems to investigate the research question.

For the first part of the study, we subjected MDA-MB-231 cells to grow in cysteine-absent adipocyte-conditioned media. In the second half, we treated MDA-MB-231 cells with iron chelator, deferoxamine. BODIPY imaging and western blot were carried out to observe ferroptosis in the cells under the 2 conditions.

The results showed that cysteine absence in the conditioned media was able to reduce the formation of lipid droplets, which increased the greater access to free fatty acids to undergo oxidation, therefore inducing ferroptosis. On the contrary, cells when treated with deferoxamine along with erastin (ferroptosis-inducing drug), showed an increase in cell iron content was observed, later inducing ferroptosis.

Our results show an alternative function of cysteine and deferoxamine, one regulating lipid droplets and the other inducing ferroptosis, although an inhibitor of the same, respectively.

Breast cancer (BC) is the world's largest tumor species in which hormone receptor-positive patients have relatively good prognosis. However, majority of patients will develop late resistance, one of the important factors is due to the loss of the original estrogen receptor (ER) expression.

We conducted this study in 115 patients with BC who experienced second biopsy at Jiangsu Province Hospital (JSPH) and divided patients into two subgroups ER + to - and ER + to + . First, clinicopathological characteristics between two groups were evaluated. Second, we explored candidate genes related to BC ER intratumor heterogeneity by applying next-generation sequencing (NGS) in 42 patients. Multi-omics integrative analysis of tumor transcriptomic, cancer-related pathway, diagnostic and prognostic value and immune profile were conducted. Besides, preliminary assay were also used to evaluate the correlation between KMT2C and ERα (ESR1) expression. The CCK-8, 5-Ethynyl-2'-deoxyuridine (EdU) assays, Transwell assays and the wound scratch tests were applied to explore the cellular interactions between KMT2C and BC.

We find the histological type (p = 0.008) and disease-free survival (DFS) (p = 0.004) were significantly different in two subgroups. In Cox survival analysis, metastasis (Hazard ratio (HR) > 1, p = 0.007) and neo-adjuvant (HR < 1, p < 0.001) are independent prognostic factors of DFS. Besides, by analyzing NGS results, we found four genes KMT2C, FGFR19, FGF1 and FGF4 were highly mutated genes in ER + to - subgroup. Furthermore, the gene KMT2C displayed significant diagnostic value and prognostic value in BC and pan-cancer. In addition, a positive correlation between KMT2C expression and immune infiltrating levels of T cell CD4 + , macrophage and neutrophil was found. In the end, Western blot and RT-qPCR assay were used and found KMT2C and ERα (ESR1) expressions are strongly positive correlated in mRNA and protein level. Inhibition of KMT2C significantly reduced proliferation, invasion, and migration of MCF7 cells.

People in two cohorts from JSPH presented different clinical characteristics and prognosis. The gene KMT2C may affect the progression of BC by regulating the molecular, epigenetic activity and immune infiltration. It may also serve as a novel prognostic biomarker for BC patients who underwent ER status converted from positive to negative.

Breast cancer (BC) is a profoundly heterogenous disease, with diverse molecular, histological, and clinical variations. The intricate molecular landscape of BC is evident even at early stages, illustrated by the complexity of the evolution from precursor lesions to invasive carcinoma. The key for therapeutic decision-making is the dynamic assessment of BC receptor status and clinical subtyping. Hereditary BC adds an additional layer of complexity to the disease, given that different cancer susceptibility genes contribute to distinct phenotypes and genomic features. Furthermore, the various BC subtypes display distinct metabolic demands and immune microenvironments. Finally, genotypic-phenotypic correlations in special histologic subtypes of BC inform diagnostic and therapeutic approaches, highlighting the significance of thoroughly comprehending BC heterogeneity.

Massively parallel sequencing technologies have been a boon to many fields of biological science, including oncology. Cancer is an umbrella term for many diseases featuring abnormal cellular growth due to genetic and epigenetic aberrations. Advances in sequencing technology allow for interrogation of the DNA and RNA of cancer cells and other cells in the tumor microenvironment down to a single-base resolution. However, these strides come after a rich history of ground-breaking biological assays, like the discovery of the Philadelphia chromosome in the context of leukemia. Many specific genetic and epigenetic modifications have been implicated in oncogenesis, cancer progression, and response to treatment. Sequencing technologies have also helped to associate populations of bacteria in the microbiome to cancer development and prognosis. However, all this new information, especially when procured via high-throughput methods, comes at the cost of being more computationally and staff-resource intensive. There is also more risk to the privacy of the individuals with sequenced genomes. Notwithstanding, the overall benefit of sequencing technologies can greatly outweigh the risks with careful advancements and continued focus on the goal: helping those affected by cancer via precision medicine. Cancer biology has been and will continue to be elucidated by sequencing innovations in ways unimaginable without it.

Conventional approaches to predict protein involvement in cancer often rely on defining either aberrant mutations at the single-gene level or correlating/anti-correlating transcript levels with patient survival. These approaches are typically conducted independently and focus on one protein at a time, overlooking nucleotide substitutions outside of coding regions or mutational co-occurrences in genes within the same interaction network. Here, we present CancerHubs, a method that integrates unbiased mutational data, clinical outcome predictions and interactomics to define novel cancer-related protein hubs. Through this approach, we identified TGOLN2 as a putative novel broad cancer tumour suppressor and EFTUD2 as a putative novel multiple myeloma oncogene.

Breast cancer is the most common cancer in women and the 2nd most common cancer worldwide, yearly impacting over 2 million females and causing 650 thousand deaths. It has been widely studied, but its epigenetic variation is not entirely unveiled. We aimed to identify epigenetic mechanisms impacting the expression of breast cancer related genes to detect new potential biomarkers and therapeutic targets. We considered The Cancer Genome Atlas database with over 800 samples and several omics datasets such as mRNA, miRNA, DNA methylation, which we used to select 2701 features that were statistically significant to differ between cancer and control samples using the Monte Carlo Feature Selection and Interdependency Discovery algorithm, from an initial total of 417,486. Their biological impact on cancerogenesis was confirmed using: statistical analysis, natural language processing, linear and machine learning models as well as: transcription factors identification, drugs and 3D chromatin structure analyses. Classification of cancer vs control samples on the selected features returned high classification weighted Accuracy from 0.91 to 0.98 depending on feature-type: mRNA, miRNA, DNA methylation, and classification algorithm. In general, cancer samples showed lower expression of differentially expressed genes and increased β-values of differentially methylated sites. We identified mRNAs whose expression is well explained by miRNA expression and differentially methylated sites β-values. We recognized differentially methylated sites possibly affecting NRF1 and MXI1 transcription factors binding, causing a disturbance in NKAPL and PITX1 expression, respectively. Our 3D models showed more loosely packed chromatin in cancer. This study successfully points out numerous possible regulatory dependencies.

Breast cancer (BC) is the most commonly diagnosed cancer and the predominant cause of death in women. BC is a complex disorder, and the exploration of several types of BC omic data, highlighting genes, perturbations, signaling and cellular mechanisms, is needed. We collected mutational data from 9,555 BC samples using cBioPortal. We classified 1174 BC genes (mutated ≥ 40 samples) into five tiers (BCtier_I-V) and subjected them to pathway and protein‒protein network analyses using EnrichR and STRING 11, respectively. BCtier_I possesses 12 BC genes with mutational frequencies > 5%, with only 5 genes possessing > 10% frequencies, namely, PIK3CA (35.7%), TP53 (34.3%), GATA3 (11.5%), CDH1 (11.4%) and MUC16 (11%), and the next seven BC genes are KMT2C (8.8%), TTN (8%), MAP3K1 (8%), SYNE1 (7.2%), AHNAK2 (7%), USH2A (5.5%), and RYR2 (5.4%). Our pathway analyses revealed that the five top BC pathways were the PI3K-AKT, TP53, NOTCH, HIPPO, and RAS pathways. We found that BC panels share only seven genes. These findings show that BC arises from genetic disruptions evident in BC signaling and protein networks.

Breast cancer treatments are based on prognostic clinicopathologic features that form the basis for therapeutic guidelines. Although the utilization of these guidelines has decreased breast cancer-associated mortality rates over the past three decades, they are not adequate for individualized therapy. Radiation therapy (RT) is the backbone of breast cancer treatment. Although a highly successful therapeutic modality clinically, from a biological perspective, preclinical studies have shown RT to have the potential to alter tumor cell phenotype, immunogenicity, and the surrounding microenvironment, potentially changing the behavior of cancer cells and resulting in a significant variation in RT response. This review presents the recent advances in revealing the complex molecular changes induced by RT in the treatment of breast cancer and highlights the complexities of translating this information into clinically relevant tools for improved prognostic insights and the revelation of novel approaches for optimizing RT.

Current literature was reviewed with a focus on recent advances made in the elucidation of tumor-associated radiation-induced molecular changes across molecular, genetic, and proteomic bases. This review was structured with the aim of providing an up-to-date overview over the very broad and complex subject matter of radiation-induced molecular changes and radioresistance, familiarizing the reader with the broader issue at hand.

The subject of radiation-induced molecular changes in breast cancer has been broached from various physiological focal points including that of the immune system, immunogenicity and the abscopal effect, tumor hypoxia, breast cancer classification and subtyping, molecular heterogeneity, and molecular plasticity. It is becoming increasingly apparent that breast cancer clinical subtyping alone does not adequately account for variation in RT response or radioresistance. Multiple components of the tumor microenvironment and immune system, delivered RT dose and fractionation schedules, radiation-induced bystander effects, and intrinsic tumor physiology and heterogeneity all contribute to the resultant RT outcome.

Despite recent advances and improvements in anticancer therapies, tumor resistance remains a significant challenge. As new analytical techniques and technologies continue to provide crucial insight into the complex molecular mechanisms of breast cancer and its treatment responses, it is becoming more evident that personalized anticancer treatment regimens may be vital in overcoming radioresistance.

Drug resistance in tumors is the primary contributor to clinical treatment failures, and aberrant expression of small RNA molecules, specifically microRNAs (miRNAs), in tumor tissues is intricately associated with drug resistance. The aim of this study is to investigate the targets and mechanisms through which exosomal miRNAs from triple-negative breast cancer (TNBC) regulate chemotherapy resistance in tumor cells. Utilizing high-throughput sequencing technology, we conducted exosomal miRNA sequencing on serum samples obtained from TNBC patients who were either sensitive or resistant to AC-sequential T chemotherapy. Subsequently, we identified and screened differentially expressed miRNAs. The observed differences in miRNA expression were further validated through quantitative reverse transcription-polymerase chain reaction. In comparison to TNBC patients who exhibited sensitivity to the AC-sequential T regimen chemotherapy, we identified significant differences in the expression of 85 miRNAs within serum exosomes of patients displaying chemotherapy resistance. Furthermore, we observed a substantial difference in the expression of hsa-miR-6831-5p between TNBC patients who were responsive to chemotherapy and those who were drug-resistant and underwent treatment with the AC-sequential T regimen. hsa-miR-6831-5p holds the potential to serve as a diagnostic marker for assessing the chemosensitivity of the AC-sequential T regimen in TNBC.

Breast cancer is the most common cause of death from cancer in women. Here, we present the case of a 43-year-old woman, who received a diagnosis of claudin-low luminal B breast cancer. The lesion revealed to be a poorly differentiated high-grade infiltrating ductal carcinoma, which was strongly estrogen receptor (ER)/progesterone receptor (PR) positive and human epidermal growth factor receptor (HER2) negative. Her tumor underwent in-depth chromosomal, mutational and gene expression analyses. We found a pathogenic protein truncating mutation in the TP53 gene, which is predicted to disrupt its transcriptional activity. The patient also harbors germline mutations in some mismatch repair (MMR) genes, and her tumor displays the presence of immune infiltrates, high tumor mutational burden (TMB) status and the apolipoprotein B mRNA editing enzyme catalytic polypeptide 3 (APOBEC3) associated signatures, which, overall, are predictive for the use of immunotherapy. Here, we propose promising prognostic indicators as well as potential therapeutic strategies based on the molecular characterization of the tumor.

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. A genome-wide association study was conducted in 2,850 women of European ancestry with breast cancer using TP53 and PIK3CA mutation status (positive or negative) as well as specific functional categories [e.g., TP53 gain-of-function (GOF) and loss-of-function, PIK3CA activating] as phenotypes. Germline variants showing evidence of association were selected for validation analyses and tested in multiple independent datasets. Discovery association analyses found five variants associated with TP53 mutation status with P values <1 × 10-6 and 33 variants with P values <1 × 10-5. Forty-four variants were associated with PIK3CA mutation status with P values <1 × 10-5. In validation analyses, only variants at the ESR1 locus were associated with TP53 mutation status after multiple comparisons corrections. Combined analyses in European and Malaysian populations found ESR1 locus variants rs9383938 and rs9479090 associated with the presence of TP53 mutations overall (P values 2 × 10-11 and 4.6 × 10-10, respectively). rs9383938 also showed association with TP53 GOF mutations (P value 6.1 × 10-7). rs9479090 showed suggestive evidence (P value 0.02) for association with TP53 mutation status in African ancestry populations. No other variants were significantly associated with TP53 or PIK3CA mutation status. Larger studies are needed to confirm these findings and determine if additional variants contribute to ancestry-specific differences in mutation frequency.

Emerging data show ancestry-specific differences in TP53 and PIK3CA mutation frequency in breast tumors suggesting that germline variants may influence somatic mutational processes. This study identified variants near ESR1 associated with TP53 mutation status and identified additional loci with suggestive association which may provide biological insight into observed differences.

Breast cancer is a heterogeneous disease categorized based on molecular characteristics, including hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression levels. The emergence of profiling technology has revealed multiple driver genomic alterations within each breast cancer subtype, serving as biomarkers to predict treatment outcomes. This study aimed to explore the genomic landscape of breast cancer in the Taiwanese population through comprehensive genomic profiling (CGP) and identify diagnostic and predictive biomarkers.

Targeted next-generation sequencing-based CGP was performed on 116 archived Taiwanese breast cancer specimens, assessing genomic alterations (GAs), including single nucleotide variants, copy number variants, fusion genes, tumor mutation burden (TMB), and microsatellite instability (MSI) status. Predictive variants for FDA-approved therapies were evaluated within each subtype.

In the cohort, frequent mutations included PIK3CA (39.7%), TP53 (36.2%), KMT2C (9.5%), GATA3 (8.6%), and SF3B1 (6.9%). All subtypes had low TMB, with no MSI-H tumors. Among HR + HER2- patients, 42% (27/65) harbored activating PIK3CA mutations, implying potential sensitivity to PI3K inhibitors and resistance to endocrine therapies. HR + HER2- patients exhibited intrinsic hormonal resistance via FGFR1 gene gain/amplification (15%), exclusive of PI3K/AKT pathway alterations. Aberrations in the PI3K/AKT/mTOR and FGFR pathways were implicated in chemoresistance, with a 52.9% involvement in triple-negative breast cancer. In HER2+ tumors, 50% harbored GAs potentially conferring resistance to anti-HER2 therapies, including PIK3CA mutations (32%), MAP3K1 (2.9%), NF1 (2.9%), and copy number gain/amplification of FGFR1 (18%), FGFR3 (2.9%), EGFR (2.9%), and AKT2 (2.9%).

This study presents CGP findings for treatment-naïve Taiwanese breast cancer, emphasizing its value in routine breast cancer management, disease classification, and treatment selection.

Breast cancer is the most common malignancy in women around the world. Intratumor and intertumoral heterogeneity persist in mammary tumors. Therefore, the identification of biomarkers is essential for the treatment of this malignancy. This study analyzed 28,143 genes expressed in 49 breast cancer cell lines using a Weighted Gene Co-expression Network Analysis to determine specific target proteins for Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes. Sixty-five modules were identified, of which five were characterized as having a high correlation with breast cancer subtypes. Genes overexpressed in the tumor were found to participate in the following mechanisms: regulation of the apoptotic process, transcriptional regulation, angiogenesis, signaling, and cellular survival. In particular, we identified the following genes, considered as hubs: IFIT3, an inhibitor of viral and cellular processes; ETS1, a transcription factor involved in cell death and tumorigenesis; ENSG00000259723 lncRNA, expressed in cancers; AL033519.3, a hypothetical gene; and TMEM86A, important for regulating keratinocyte membrane properties, considered as a key in Basal A, Basal B, Luminal A, Luminal B, and HER2 ampl breast cancer subtypes, respectively. The modules and genes identified in this work can be used to identify possible biomarkers or therapeutic targets in different breast cancer subtypes.

Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors.

We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers.

We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors.

This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Inflammatory breast cancer (IBC) is the most pro-metastatic form of BC. Better understanding of its enigmatic pathophysiology is crucial. We report here the largest whole-exome sequencing (WES) study of clinical IBC samples.

We retrospectively applied WES to 54 untreated IBC primary tumor samples and matched normal DNA. The comparator samples were 102 stage-matched non-IBC samples from TCGA. We compared the somatic mutational profiles, spectra and signatures, copy number alterations (CNAs), HRD and heterogeneity scores, and frequencies of actionable genomic alterations (AGAs) between IBCs and non-IBCs. The comparisons were adjusted for the molecular subtypes.

The number of somatic mutations, TMB, and mutational spectra were not different between IBCs and non-IBCs, and no gene was differentially mutated or showed differential frequency of CNAs. Among the COSMIC signatures, only the age-related signature was more frequent in non-IBCs than in IBCs. We also identified in IBCs two new mutational signatures not associated with any environmental exposure, one of them having been previously related to HIF pathway activation. Overall, the HRD score was not different between both groups, but was higher in TN IBCs than TN non-IBCs. IBCs were less frequently classified as heterogeneous according to heterogeneity H-index than non-IBCs (21% vs 33%), and clonal mutations were more frequent and subclonal mutations less frequent in IBCs. More than 50% of patients with IBC harbored at least one high-level of evidence (LOE) AGA (OncoKB LOE 1-2, ESCAT LOE I-II), similarly to patients with non-IBC.

We provide the largest mutational landscape of IBC. Only a few subtle differences were identified with non-IBCs. The most clinically relevant one was the higher HRD score in TN IBCs than in TN non-IBCs, whereas the most intriguing one was the smaller intratumor heterogeneity of IBCs.

Cancer is a complex and evolutionary disease mainly driven by the accumulation of genetic variations in genes. Identifying cancer driver genes is important. However, most related studies have focused on the population level. Cancer is a disease with high heterogeneity. Thus, the discovery of driver genes at the individual level is becoming more valuable but is a great challenge. Although there have been some computational methods proposed to tackle this challenge, few can cover all patient samples well, and there is still room for performance improvement. In this study, to identify individual-level driver genes more efficiently, we propose the PDGCN method. PDGCN integrates multiple types of data features, including mutation, expression, methylation, copy number data, and system-level gene features, along with network structural features extracted using Node2vec in order to construct a sample-gene interaction network. Prediction is performed using a graphical convolutional neural network model with a conditional random field layer, which is able to better combine the network structural features with biological attribute features. Experiments on the ACC (Adrenocortical Cancer) and KICH (Kidney Chromophobe) datasets from TCGA (The Cancer Genome Atlas) demonstrated that the method performs better compared to other similar methods. It can identify not only frequently mutated driver genes, but also rare candidate driver genes and novel biomarker genes. The results of the survival and enrichment analyses of these detected genes demonstrate that the method can identify important driver genes at the individual level.

The evolutionary trajectory of glioblastoma (GBM) is a multifaceted biological process that extends beyond genetic alterations alone. Here, we perform an integrative proteogenomic analysis of 123 longitudinal glioblastoma pairs and identify a highly proliferative cellular state at diagnosis and replacement by activation of neuronal transition and synaptogenic pathways in recurrent tumors. Proteomic and phosphoproteomic analyses reveal that the molecular transition to neuronal state at recurrence is marked by post-translational activation of the wingless-related integration site (WNT)/ planar cell polarity (PCP) signaling pathway and BRAF protein kinase. Consistently, multi-omic analysis of patient-derived xenograft (PDX) models mirror similar patterns of evolutionary trajectory. Inhibition of B-raf proto-oncogene (BRAF) kinase impairs both neuronal transition and migration capability of recurrent tumor cells, phenotypic hallmarks of post-therapy progression. Combinatorial treatment of temozolomide (TMZ) with BRAF inhibitor, vemurafenib, significantly extends the survival of PDX models. This study provides comprehensive insights into the biological mechanisms of glioblastoma evolution and treatment resistance, highlighting promising therapeutic strategies for clinical intervention.

Breast acinic cell carcinoma (ACC) is a rare subtype of breast cancer. Accurate diagnosis of ACC using core needle biopsy (CNB) is pivotal for the use of effective treatments and patient prognosis. In the present study, a detailed analysis of the morphological, immunohistochemical and gene mutation features of 2 cases of ACC was performed. CNB was performed prior to surgical excision. The breast ACC in the present cases exhibited overt burrowing labyrinthine networks or 'hand-holding-hand' features. The tumor cells in both of the present cases expressed cytokeratin (CK)7, S100 and CK5/6, but were negative for p63, estrogen receptor and progesterone receptor. GATA binding protein 3 was positive in case 1 but negative in case 2. Fluorescence in situ hybridization indicated no ETS variant transcription factor 6 break-apart probe detection. Next-generation sequencing results revealed the same mutation and a similar abundance in exon 27 (NM_005120.2; c.3817G>T; p.A1273S) of the mediator of RNA polymerase II transcription, subunit 12 homolog (MED12) gene in both patients. To conclude, the findings of the present study suggested that recognition of this rare 'hand-holding-hand' structure could potentially be beneficial for avoiding patient misdiagnosis. In addition, it could be suggested that a mutation in the MED12 exon 27 was associated with the formation of a burrowing labyrinthine network or 'hand-holding-hand' feature.

Despite advances in screening, therapy and surveillance, breast cancer remains threatening to women. Worst, patients suffer from side effects of treatments and cancer cells become resistant. The emergence of RUNX1 in breast cancer has put it in a spotlight due to its roles in the disease progression. It also plays important roles in normal mammary glands such as for cell growth, proliferation, migration and stemness. However, mutations in the RUNX1 gene have changed the regulation of these phenotypes and the full spectrum of its implications in breast cancer patients is unknown. In this study therefore, the pattern of RUNX1 mutations in breast cancer patients was examined to understand its fundamental impacts on the disease. The perturbation of RUNX1 and its mutations in breast cancer was elucidated through different studies reported in cBioPortal in the past ten years. From our analyses, the majority of RUNX1 mutations were found in the primary breast cancer, with women constituted most of the mutations, especially on the left side of the breast. Similarly, increased number of mutations was observed in ER-positive breast cancer patients and this was also the case at the early stage of the disease development. The level of RUNX1 mutations also increased gradually as patients got older and the peak was highest in the patients of 60-70 years old. Altogether, these data indicated that the mutated RUNX1 gene contributed to the progression of breast cancer and understanding of its regulatory mechanisms is crucial to therapeutically target this gene in the future.

The aim of this study was to investigate genetic alterations within breast cancer in the setting of recurrent or de novo stage IV disease.

This study included 22 patients with recurrent breast cancer (n = 19) and inoperable de novo stage IV breast cancer (n = 3). For next generation sequencing, FoundationOneCDx (F1CDx) (Foundation Medicine Inc., Cambridge, MA, USA) was performed in 21 patients and FoundationOneLiquid CDx was performed in 1 patient.

Median age was 62.9 years (range, 33.4-82.1). Pathological diagnoses of specimens included invasive ductal carcinoma (n = 19), invasive lobular carcinoma (n = 2), and invasive micropapillary carcinoma (n = 1). F1CDx detected a median of 4.5 variants (range, 1-11). The most commonly altered gene were PIK3CA (n = 9), followed by TP53 (n = 7), MYC (n = 4), PTEN (n = 3), and CDH1 (n = 3). For hormone receptor-positive patients with PIK3CA mutations, hormonal treatment plus a phosphoinositide 3-kinase inhibitor was recommended as the treatment of choice. Patients in the hormone receptor-negative and no human epidermal growth factor receptor 2 expression group had significantly higher tumor mutational burden than patients in the hormone receptor-positive group. A BRCA2 reversion mutation was revealed by F1CDx in a patient with a deleterious germline BRCA2 mutation during poly ADP ribose polymerase inhibitor treatment.

Guidance on tailored precision therapy with consideration of genomic mutations was possible for some patients with information provided by F1CDx. Clinicians should consider using F1CDx at turning points in the course of the disease.

Breast cancer is heterogeneous and differs substantially across different tumors (intertumor heterogeneity) and even within an individual tumor (intratumor heterogeneity). Gene-expression profiling has considerably impacted our understanding of breast cancer biology. Four main "intrinsic subtypes" of breast cancer (i.e., luminal A, luminal B, HER2-enriched, and basal-like) have been consistently identified by gene expression, showing significant prognostic and predictive value in multiple clinical scenarios. Thanks to the molecular profiling of breast tumors, breast cancer is a paradigm of treatment personalization. Several standardized prognostic gene-expression assays are presently being used in the clinic to guide treatment decisions. Moreover, the development of single-cell-level resolution molecular profiling has allowed us to appreciate that breast cancer is also heterogeneous within a single tumor. There is an evident functional heterogeneity within the neoplastic and tumor microenvironment cells. Finally, emerging insights from these studies suggest a substantial cellular organization of neoplastic and tumor microenvironment cells, thus defining breast cancer ecosystems and highlighting the importance of spatial localizations.

Breast cancer remains to be the second leading cause of cancer deaths worldwide thereby highlighting the critical need to find superior treatment strategies for this disease. In the current era of cancer treatment, personalized medicine is garnering much attention as this type of treatment is more selective thereby minimizing harmful side effects. Personalized medicine is dependent upon knowing the underlying genetic landscape of the initial tumor. In our study, we focused our efforts on a specific subset of breast cancer that harbors genetic alterations in the Mediator subunit 12 (MED12). Our results show that loss of MED12 leads to enhanced cellular proliferation and colony formation of breast cancer cells through a mechanism that involves activation of GLI3-dependent SHH signaling, a pathway that is central to breast development and homeostasis. To find a personalized treatment option for this subset of breast cancer, we employed a natural compound screening strategy which uncovered a total of ten compounds that selectively target MED12 knockdown breast cancer cells. Our results show that two of these ten compounds, solasonine and alisol B23-acetate, block GLI3-dependent SHH signaling which leads to a reversal of enhanced cellular proliferation and colony formation ability. Thus, our findings provide promising insight into a novel personalized treatment strategy for patients suffering from MED12-altered breast cancer.

High temperature requirement A1 (HTRA1), a member of the HTRA family, is a serine peptidase involved in many crucial bioprocesses such as proliferation, mitochondrial homeostasis, apoptosis, and protein quality control. It also plays an important role in the development of various tumors. However, the potential role and mechanisms of action of HTRA1 in breast cancer (BRCA) remain unclear. We conducted a bioinformatics-based study to investigate HTRA1 expression in BRCA alongside its associations with immune-cell infiltrates and survival outcomes.

The expression of HTRA1 in BRCA samples was analyzed using RNAseq datasets from The Cancer Genome Atlas and Gene Expression Omnibus. R software was employed to assess the relationship between HTRA1 expression and clinicopathological characteristics, tumor-infiltrating immune cells, and immunity-associated biomarkers in BRCA. MethSurv and cBioPortal database were utilized to evaluate DNA methylation and genovariation within the HTRA1 DNA. Receiver operating characteristic curves, Kaplan-Meier analysis, and Cox regression were performed to estimate the impact of HTRA1 on diagnosis, prognosis, and response to chemotherapy in BRCA.

HTRA1 expression was significantly downregulated in BRCA tissues compared to adjacent normal breast tissue controls. Differentially expressed genes associated with HTRA1 expression primarily enriched in cell proliferation pathways. Furthermore, altered HTRA1 expression significantly correlated with patient age, tumor histological type, T stage, progesterone receptor/estrogen receptor status, and PAM50 subtype of BRCA. Both positive and negative associations were observed between HTRA1 levels and the abundance of different types of immune cells, as well as immune biomarkers, including resting mast cells, follicular helper T cells, PD-L1, p53, and Ki67. Low HTRA1 expression was related with pathological complete response in luminal B BRCA patients undergoing chemotherapy. Additionally, lower HTRA1 expression in BRCA was associated with inferior overall survival and relapse-free survival.

HTRA1 expression is associated with immune-cell infiltration, response to chemotherapy, and survival outcomes in BRCA. HTRA1 has the potential to serve as a promising biomarker and therapeutic target moving forward.

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors.

A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.

The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.

We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

The estrogen receptor-positive (ER+) breast cancers constitute more than 50 % of breast cancers, seriously threatening the health of women. Unfortunately, the detection and targeted therapy of ER+ breast cancers remain a challenge. Here, a novel nucleic acid aptamer S1-4 was developed to specifically target ER+ breast cancer MCF-7 cells by using Cell-SELEX and nucleic acid truncation strategies. The affinity dissociation constant of the binding of aptamer S1-4 to MCF-7 cells was 97.6 ± 7.5 nM in vitro. Compared with HER2+ breast cells SK-BR-3 and triple-negative breast cancer cells MDA-MB-231, MCF-7 cells were selectively recognized and targeted by aptamer S1-4. Fluorescence tracing in vivo results also indicated that aptamer S1-4 selectively targeted the cell membrane of tumor tissues in MCF-7- but not in SK-BR3 or MDB-MA-231-bearing mice. This selectively developed novel aptamer probe S1-4 with high affinity could be used for the diagnosis and treatment of ER+ breast cancers.

Breast cancer (BC) and prostate cancer (PC) are at the top of the list when it comes to the most common types of cancers worldwide. The phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway is important, in that it strongly influences the development and progression of these tumors. Previous studies have emphasized the key role of inhibitors of the PIK3/AKT/mTOR signaling pathway in the treatment of BC and PC, and it remains to be a crucial method of treatment. In this review, the inhibitors of these signaling pathways are compared, as well as their effectiveness in therapy and potential as therapeutic agents. The use of these inhibitors as polytherapy is evaluated, especially with the use of hormonal therapy, which has shown promising results.