Whole-exome sequencing identifies somatic mutations and intratumor heterogeneity in inflammatory breast cancer

Differential somatic coding variant landscapes between laser microdissected luminal epithelial cells from canine mammary invasive ductal solid carcinoma and comedocarcinoma

BACKGROUND

Breast cancer (BC) is the most common cancer in women. Likewise, canine mammary tumors (CMT) represent the most common cancer in intact female dogs and develop in the majority spontaneously. Similarities exist in clinical presentation, histopathology, biomarkers, and treatment. However, CMT subtype-specific genomic background is less investigated. Here, we assess the genetic etiology of two histomorphological (HM) subtypes with BC counterparts, the CMT invasive ductal simple solid carcinoma (SC) and comedocarcinoma (CC), and compare the results with BC data.

METHODS

Groups of 11-13 transformed ductal luminal epithelial cells were laser-capture microdissected from snap-frozen invasive mammary SC and CC subtypes of one intact female dog. HM unaffected lobular luminal epithelial cells were controls. Single-cell whole genome libraries were generated using PicoPLEX and sequenced to compare the subtypes' somatic coding variant landscapes with each other and with BC data available in COSMIC-CGC and KEGG. Furthermore, HM and immunohistochemical (IHC) subtype characteristics were compared with the genomic results.

RESULTS

The CC had six times more variants than the SC. The SC showed variants in adherens junction genes and genes of the MAPK, mTOR and NF-kappa-B signaling pathways. In the CC, the extracellular matrix (ECM) receptor interaction, cell adhesion, PI3K-Akt and cGMP-PKG pathways were enriched, reflecting the higher cellular malignancy. Affected pathways in both CMT subtypes overlapped with BC pathways in KEGG. Additionally, we identified ATP6V1C2, GLYATL3, CARMIL3, GATAD2B, OBSCN, SIX2, CPEB3 and ZNF521 as potential new subtype-distinct driver genes. Furthermore, our results revealed biomarker alterations in IHC in the basal/myoepithelial cell layer without respective genetic mutations, suggesting changes to their complex signaling pathways, disturbed regulative feedback loops or other silencing mechanisms.

CONCLUSIONS

This study contributes to understanding the subtype-specific molecular mechanisms in the canine mammary invasive ductal simple SC and CC, and revealed subtype-specific molecular complexity for phenotypically similar characteristics. Several affected genes and signaling pathways overlapped with BC indicating the potential use of CMT as model for BC. Our findings emphasize the need for thorough characterization of cancer specimens with respect to translational cancer research, but also how insight into tumor heterogeneity will be crucial for the development of targeted prognostics and therapeutic interventions.

Genomic and transcriptomic analyses identify distinctive features of triple-negative inflammatory breast cancer

Triple-negative inflammatory breast cancer (TN-IBC) is the most aggressive type of breast cancer, yet its defining genomic, molecular, and immunological features remain largely unknown. In this study, we performed the largest and most comprehensive genomic and transcriptomic analyses of prospectively collected TN-IBC patient samples from a phase II clinical trial (ClinicalTrials.gov, NCT02876107, registered on August 22, 2016) and compared them to similarly analyzed stage III TN-non-IBC patient samples (ClinicalTrials.gov, NCT02276443, registered on October 21, 2014). We found that TN-IBC tumors have distinctive genomic, molecular, and immunological characteristics, including a lower tumor mutation load than TN-non-IBC, and an association of immunosuppressive tumor-infiltrating immune components with an unfavorable response to neoadjuvant chemotherapy. To our knowledge, this is the only study in which TN-IBC and TN-non-IBC samples were collected prospectively. Our analysis improves the understanding of the molecular landscape of the most aggressive subtype of breast cancer. Further studies are needed to discover novel prognostic biomarkers and druggable targets for TN-IBC.

From Genomic Exploration to Personalized Treatment: Next-Generation Sequencing in Oncology

Next-generation sequencing (NGS) has revolutionized personalized oncology care by providing exceptional insights into the complex genomic landscape. NGS offers comprehensive cancer profiling, which enables clinicians and researchers to better understand the molecular basis of cancer and to tailor treatment strategies accordingly. Targeted therapies based on genomic alterations identified through NGS have shown promise in improving patient outcomes across various cancer types, circumventing resistance mechanisms and enhancing treatment efficacy. Moreover, NGS facilitates the identification of predictive biomarkers and prognostic indicators, aiding in patient stratification and personalized treatment approaches. By uncovering driver mutations and actionable alterations, NGS empowers clinicians to make informed decisions regarding treatment selection and patient management. However, the full potential of NGS in personalized oncology can only be realized through bioinformatics analyses. Bioinformatics plays a crucial role in processing raw sequencing data, identifying clinically relevant variants, and interpreting complex genomic landscapes. This comprehensive review investigates the diverse NGS techniques, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and single-cell RNA sequencing (sc-RNA-Seq), elucidating their roles in understanding the complex genomic/transcriptomic landscape of cancer. Furthermore, the review explores the integration of NGS data with bioinformatics tools to facilitate personalized oncology approaches, from understanding tumor heterogeneity to identifying driver mutations and predicting therapeutic responses. Challenges and future directions in NGS-based cancer research are also discussed, underscoring the transformative impact of these technologies on cancer diagnosis, management, and treatment strategies.

Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers

PURPOSE

Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC.

METHODS

Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics.

RESULTS

Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment.

CONCLUSION

We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.

Whole-exome profiles of inflammatory breast cancer and pathological response to neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NACT) became a standard treatment strategy for patients with inflammatory breast cancer (IBC) because of high disease aggressiveness. However, given the heterogeneity of IBC, no molecular feature reliably predicts the response to chemotherapy. Whole-exome sequencing (WES) of clinical tumor samples provides an opportunity to identify genomic alterations associated with chemosensitivity.

METHODS

We retrospectively applied WES to 44 untreated IBC primary tumor samples and matched normal DNA. The pathological response to NACT, assessed on operative specimen, distinguished the patients with versus without pathological complete response (pCR versus no-pCR respectively). We compared the mutational profiles, spectra and signatures, pathway mutations, copy number alterations (CNAs), HRD, and heterogeneity scores between pCR versus no-pCR patients.

RESULTS

The TMB, HRD, and mutational spectra were not different between the complete (N = 13) versus non-complete (N = 31) responders. The two most frequently mutated genes were TP53 and PIK3CA. They were more frequently mutated in the complete responders, but the difference was not significant. Only two genes, NLRP3 and SLC9B1, were significantly more frequently mutated in the complete responders (23% vs. 0%). By contrast, several biological pathways involved in protein translation, PI3K pathway, and signal transduction showed significantly higher mutation frequency in the patients with pCR. We observed a higher abundance of COSMIC signature 7 (due to ultraviolet light exposure) in tumors from complete responders. The comparison of CNAs of the 3808 genes included in the GISTIC regions between both patients' groups identified 234 genes as differentially altered. The CIN signatures were not differentially represented between the complete versus non-complete responders. Based on the H-index, the patients with heterogeneous tumors displayed a lower pCR rate (11%) than those with less heterogeneous tumors (35%).

CONCLUSIONS

This is the first study aiming at identifying correlations between the WES data of IBC samples and the achievement of pCR to NACT. Our results, obtained in this 44-sample series, suggest a few subtle genomic alterations associated with pathological response. Additional investigations are required in larger series.

Validation and Implementation of a Somatic-Only Tumor Exome for Routine Clinical Application

Next-generation sequencing-based genomic testing is standard of care for tumor workflows. However, its application across different institutions continues to be challenging given the diversity of needs and resource availability among different institutions globally. Moreover, the use of a variety of different panels, including those from a few individual genes to those involving hundreds of genes, results in a relatively skewed distribution of care for patients. It is imperative to obtain a higher level of standardization without having to be restricted to specific kits or requiring repeated validations, which are generally expensive. We show the validation and clinical implementation of the DH-CancerSeq assay, a tumor-only whole-exome-based sequencing assay with integrated informatics, while providing similar input requirements, sensitivity, and specificity to a previously validated targeted gene panel and maintaining similar turnaround times for patient care.

PDE4B promotes the progression of gastric cancer via the PI3K/AKT/MYC pathway and immune infiltration

Phosphodiesterase 4B (PDE4B) is a key enzyme involved in regulating intracellular cyclic adenosine monophosphate levels and plays a significant role in the diagnosis, classification, treatment, and prognosis of various cancers. However, the role of PDE4B in gastric cancer (GC) remains unclear. We used the GEPIA2 (Gene Expression Profiling Interactive Analysis 2) database to analyze the differential expression level of PDE4B across tumor samples and verified our findings via qPCR and immunohistochemical analysis. We also analyzed the correlation between PDE4B expression levels and clinical pathological parameters, and prognosis, in the database. The effects of PDE4B on GC proliferation, migration, and invasion were evaluated through in vitro and in vivo experiments. Enrichment analysis was performed using bioinformatic tools, and results were validated by western blot analysis. The correlation between PDE4B expression and immune cell infiltration was investigated using bioinformatics tools. PDE4B is highly expressed in GC and is significantly associated with deep infiltration, distant metastasis, tumor, node, metastasis (TNM) stage, and preoperative CA199 levels. Over-expression of PDE4B promotes proliferation, clonal formation, migration, and invasion of GC cells and is associated with poor prognosis. PDE4B promotes the infiltration of immune cells into the tumor microenvironment (TME) and the phosphorylation of PI3K/AKT pathway, increasing MYC expression. PDE4B can serve as an independent prognostic biomarker for GC. We found that PDE4B can promote immune cell infiltration of the TME and mediate malignancy in gastric cancer through the PI3K/AKT/MYC pathway.

Mutational landscape of inflammatory breast cancer

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Deciphering the molecular biology of inflammatory breast cancer through molecular characterization of patient samples and preclinical models

Inflammatory breast cancer is an aggressive subtype of breast cancer with dismal patient prognosis and a unique clinical presentation. In the past two decades, molecular profiling technologies have been used in order to gain insight into the molecular biology of IBC and to search for possible targets for treatment. Although a gene signature that accurately discriminates between IBC and nIBC patient samples and preclinical models was identified, the overall genomic and transcriptomic differences are small and ambiguous, mainly due to the limited sample sizes of the evaluated patient series and the failure to correct for confounding effects of the molecular subtypes. Nevertheless, data collected over the past 20 years by independent research groups increasingly support the existence of several IBC-specific biological characteristics. In this review, these features are classified as established, emerging and conceptual hallmarks based on the level of evidence reported in the literature. In addition, a synoptic model is proposed that integrates all hallmarks and that can explain how cancer cell intrinsic mechanisms (i.e. NF-κB activation, genomic instability, MYC-addiction, TGF-β resistance, adaptive stress response, chromatin remodeling, epithelial-to-mesenchymal transition) can contribute to the establishment of the dynamic immune microenvironment associated with IBC. It stands to reason that future research projects are needed to further refine (parts of) this model and to investigate its clinical translatability.

Long-Read DNA and RNA Sequencing to Streamline Clinical Genetic Testing and Reduce Barriers to Comprehensive Genetic Testing

BACKGROUND

Obtaining a precise molecular diagnosis through clinical genetic testing provides information about disease prognosis or progression, allows accurate counseling about recurrence risk, and empowers individuals to benefit from precision therapies or take part in N-of-1 trials. Unfortunately, more than half of individuals with a suspected Mendelian condition remain undiagnosed after a comprehensive clinical evaluation, and the results of any individual clinical genetic test ordered during a typical evaluation may take weeks or months to return. Furthermore, commonly used technologies, such as short-read sequencing, are limited in the types of disease-causing variation they can identify. New technologies, such as long-read sequencing (LRS), are poised to solve these problems.

CONTENT

Recent technical advances have improved accuracy, increased throughput, and decreased the costs of commercially available LRS technologies. This has resolved many historical concerns about the use of LRS in the clinical environment and opened the door to widespread clinical adoption of LRS. Here, we review LRS technology, how it has been used in the research setting to clarify complex variants or identify disease-causing variation missed by prior clinical testing, and how it may be used clinically in the near future.

SUMMARY

LRS is unique in that, as a single data source, it has the potential to replace nearly every other clinical genetic test offered today. When analyzed in a stepwise fashion, LRS will simplify laboratory processes, reduce barriers to comprehensive genetic testing, increase the rate of genetic diagnoses, and shorten the amount of time required to make a molecular diagnosis.

AI-powered interpretable imaging phenotypes noninvasively characterize tumor microenvironment associated with diverse molecular signatures and survival in breast cancer

BACKGROUND AND OBJECTIVES

Tumor microenvironment (TME) is a determining factor in decision-making and personalized treatment for breast cancer, which is highly intra-tumor heterogeneous (ITH). However, the noninvasive imaging phenotypes of TME are poorly understood, even invasive genotypes have been largely known in breast cancer.

METHODS

Here, we develop an artificial intelligence (AI)-driven approach for noninvasively characterizing TME by integrating the predictive power of deep learning with the explainability of human-interpretable imaging phenotypes (IMPs) derived from 4D dynamic imaging (DCE-MRI) of 342 breast tumors linked to genomic and clinical data, which connect cancer phenotypes to genotypes. An unsupervised dual-attention deep graph clustering model (DGCLM) is developed to divide bulk tumor into multiple spatially segregated and phenotypically consistent subclusters. The IMPs ranging from spatial heterogeneity to kinetic heterogeneity are leveraged to capture architecture, interaction, and proximity between intratumoral subclusters.

RESULTS

We demonstrate that our IMPs correlate with well-known markers of TME and also can predict distinct molecular signatures, including expression of hormone receptor, epithelial growth factor receptor and immune checkpoint proteins, with the performance of accuracy, reliability and transparency superior to recent state-of-the-art radiomics and 'black-box' deep learning methods. Moreover, prognostic value is confirmed by survival analysis accounting for IMPs.

CONCLUSIONS

Our approach provides an interpretable, quantitative, and comprehensive perspective to characterize TME in a noninvasive and clinically relevant manner.

PTEN in triple-negative breast carcinoma: protein expression and genomic alteration in pretreatment and posttreatment specimens

Background

Recent advances have been made in targeting the phosphoinositide 3-kinase pathway in breast cancer. Phosphatase and tensin homolog (PTEN) is a key component of that pathway.

Objective

To understand the changes in PTEN expression over the course of the disease in patients with triple-negative breast cancer (TNBC) and whether PTEN copy number variation (CNV) by next-generation sequencing (NGS) can serve as an alternative to immunohistochemistry (IHC) to identify PTEN loss.

Methods

We compared PTEN expression by IHC between pretreatment tumors and residual tumors in the breast and lymph nodes after neoadjuvant chemotherapy in 96 patients enrolled in a TNBC clinical trial. A correlative analysis between PTEN protein expression and PTEN CNV by NGS was also performed.

Results

With a stringent cutoff for PTEN IHC scoring, PTEN expression was discordant between pretreatment and posttreatment primary tumors in 5% of patients (n = 96) and between posttreatment primary tumors and lymph node metastases in 9% (n = 33). A less stringent cutoff yielded similar discordance rates. Intratumoral heterogeneity for PTEN loss was observed in 7% of the patients. Among pretreatment tumors, PTEN copy numbers by whole exome sequencing (n = 72) were significantly higher in the PTEN-positive tumors by IHC compared with the IHC PTEN-loss tumors (p < 0.0001). However, PTEN-positive and PTEN-loss tumors by IHC overlapped in copy numbers: 14 of 60 PTEN-positive samples showed decreased copy numbers in the range of those of the PTEN-loss tumors.

Conclusion

Testing various specimens by IHC may generate different PTEN results in a small proportion of patients with TNBC; therefore, the decision of testing one versus multiple specimens in a clinical trial should be defined in the patient inclusion criteria. Although a distinct cutoff by which CNV differentiated PTEN-positive tumors from those with PTEN loss was not identified, higher copy number of PTEN may confer positive PTEN, whereas lower copy number of PTEN would necessitate additional testing by IHC to assess PTEN loss.

Trial registration

NCT02276443.

The mutational landscape of a US Midwestern breast cancer cohort reveals subtype-specific cancer drivers and prognostic markers

BACKGROUND

Female breast cancer remains the second leading cause of cancer-related death in the USA. The heterogeneity in the tumor morphology across the cohort and within patients can lead to unpredictable therapy resistance, metastasis, and clinical outcome. Hence, supplementing classic pathological markers with intrinsic tumor molecular markers can help identify novel molecular subtypes and the discovery of actionable biomarkers.

METHODS

We conducted a large multi-institutional genomic analysis of paired normal and tumor samples from breast cancer patients to profile the complex genomic architecture of breast tumors. Long-term patient follow-up, therapeutic regimens, and treatment response for this cohort are documented using the Breast Cancer Collaborative Registry. The majority of the patients in this study were at tumor stage 1 (51.4%) and stage 2 (36.3%) at the time of diagnosis. Whole-exome sequencing data from 554 patients were used for mutational profiling and identifying cancer drivers.

RESULTS

We identified 54 tumors having at least 1000 mutations and 185 tumors with less than 100 mutations. Tumor mutational burden varied across the classified subtypes, and the top ten mutated genes include MUC4, MUC16, PIK3CA, TTN, TP53, NBPF10, NBPF1, CDC27, AHNAK2, and MUC2. Patients were classified based on seven biological and tumor-specific parameters, including grade, stage, hormone receptor status, histological subtype, Ki67 expression, lymph node status, race, and mutational profiles compared across different subtypes. Mutual exclusion of mutations in PIK3CA and TP53 was pronounced across different tumor grades. Cancer drivers specific to each subtype include TP53, PIK3CA, CDC27, CDH1, STK39, CBFB, MAP3K1, and GATA3, and mutations associated with patient survival were identified in our cohort.

CONCLUSIONS

This extensive study has revealed tumor burden, driver genes, co-occurrence, mutual exclusivity, and survival effects of mutations on a US Midwestern breast cancer cohort, paving the way for developing personalized therapeutic strategies.

Taxifolin Inhibits Breast Cancer Growth by Facilitating CD8+ T Cell Infiltration and Inducing a Novel Set of Genes including Potential Tumor Suppressor Genes in 1q21.3

Taxifolin inhibits breast cancer (BC) via novel mechanisms. In a syngeneic mouse BC model, taxifolin suppressed 4T-1 cell-derived allografts. RNA-seq of 4T-1 tumors identified 36 differentially expressed genes (DEGs) upregulated by taxifolin. Among their human homologues, 19, 7, and 2 genes were downregulated in BCs, high-proliferative BCs, and BCs with high-fatality risks, respectively. Three genes were established as tumor suppressors and eight were novel to BC, including HNRN, KPRP, CRCT1, and FLG2. These four genes exhibit tumor suppressive actions and reside in 1q21.3, a locus amplified in 70% recurrent BCs, revealing a unique vulnerability of primary and recurrent BCs with 1q21.3 amplification with respect to taxifolin. Furthermore, the 36 DEGs formed a multiple gene panel (DEG36) that effectively stratified the fatality risk in luminal, HER2+, and triple-negative (TN) equivalent BCs in two large cohorts: the METABRIC and TCGA datasets. 4T-1 cells model human TNBC cells. The DEG36 most robustly predicted the poor prognosis of TNBCs and associated it with the infiltration of CD8+ T, NK, macrophages, and Th2 cells. Of note, taxifolin increased the CD8+ T cell content in 4T-1 tumors. The DEG36 is a novel and effective prognostic biomarker of BCs, particularly TNBCs, and can be used to assess the BC-associated immunosuppressive microenvironment.

Omics-Based Investigations of Breast Cancer

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

Copy Number Variation in Inflammatory Breast Cancer

Identification of a unique genomic biomarker in de novo inflammatory breast cancer (IBC) may provide an insight into the biology of this aggressive disease. The goal of our study was to elucidate biomarkers associated with IBC. We examined breast biopsies collected from Dana–Farber Cancer Institute patients with IBC prior to initiating preoperative systemic treatment (30 samples were examined, of which 14 were eligible). Patients without available biopsies (n = 1), with insufficient tumor epithelial cells (n = 10), or insufficient DNA yield (n = 5) were excluded from the analysis. Molecular subtype and tumor grade were abstracted from a medical records’ review. Ten IBC tumors were estrogen-receptor-positive (ER+) and human epidermal growth factor receptor 2 (HER2)-negative (n = 10 out of 14). Sufficient RNA and DNA were simultaneously extracted from 14 biopsy specimens using the Qiagen AllPrep Kit. RNA was amplified using the Sensation kit and profiled using the Affymetrix Human Transcriptome Array 2.0. DNA was profiled for genome-wide copy number variation (CNV) using the Affymetrix OncoScan Array and analyzed using the Nexus Chromosome Analysis Suite. Among the 14 eligible samples, we first confirmed biological concordance and quality control metrics using replicates and gene expression data. Second, we examined CNVs and gene expression change by IBC subtype. We identified significant CNVs in IBC patients after adjusting for multiple comparisons. Next, to assess whether the CNVs were unique to IBC, we compared the IBC CNV data to fresh-frozen non-IBC CNV data from The Cancer Genome Atlas (n = 388). On chromosome 7p11.2, we identified significant CN gain located at position 58,019,983-58,025,423 in 8 ER+ IBC samples compared to 338 non-IBC ER+ samples (region length: 5440 bp gain and 69,039 bp, False Discovery Rate (FDR) p-value = 3.12 × 10−10) and at position 57,950,944–58,025,423 in 3 TN-IBC samples compared to 50 non-IBC TN samples (74,479 base pair, gain, FDR p-value = 4.27 × 10−5; near the EGFR gene). We also observed significant CN loss on chromosome 21, located at position 9,648,315–9,764,385 (p-value = 4.27 × 10−5). Secondarily, differential gene expression in IBC patients with 7p11.2 CN gain compared to SUM149 were explored after FDR correction for multiple testing (p-value = 0.0016), but the results should be interpreted with caution due to the small sample size. Finally, the data presented are hypothesis-generating. Validation of CNVs that contribute to the unique presentation and biological features associated with IBC in larger datasets may lead to the optimization of treatment strategies.

Comparison of the genomic alterations present in tumor samples from patients with metastatic inflammatory versus non-inflammatory breast cancer reveals AURKA as a potential treatment target

Inflammatory breast cancer (IBC) is a rare but aggressive subtype of breast cancer, mainly characterized using primary tumor samples. Here, using public datasets, we compared the genomic alterations in primary and metastatic samples from patients with metastatic IBC versus patients with metastatic non-IBC. We observed a higher frequency of AURKA amplification in IBC. We further showed that AURKA amplification was associated with increased AURKA mRNA expression, which we demonstrated was higher in IBC. Finally, higher protein expression of AURKA was associated with worse prognosis in patients with IBC. These findings deserve further investigation given the existence of AURKA-inhibitors.

The regulatory role of PDE4B in the progression of inflammatory function study

Inflammation is a response of the body to external stimuli (eg. chemical irritants, bacteria, viruses, etc.), and when the stimuli are persistent, they tend to trigger chronic inflammation. The presence of chronic inflammation is an important component of the tumor microenvironment produced by a variety of inflammatory cells (eg. macrophages, neutrophils, leukocytes, etc.). The relationship between chronic inflammation and cancer development has been widely accepted, and chronic inflammation has been associated with the development of many cancers, including chronic bronchitis and lung cancer, cystitis inducing bladder cancer. Moreover, chronic colorectitis is more likely to develop into colorectal cancer. Therefore, the specific relationship and cellular mechanisms between inflammation and cancer are a hot topic of research. Recent studies have identified phosphodiesterase 4B (PDE4B), a member of the phosphodiesterase (PDEs) protein family, as a major cyclic AMP (cAMP) metabolizing enzyme in inflammatory cells, and the therapeutic role of PDE4B as chronic inflammation, cancer. In this review, we will present the tumors associated with chronic inflammation, and PDE4B potential clinical application.

Differential expression profile of mRNAs, lncRNAs and circRNAs reveals potential molecular mechanism in breast cancer

In recent years, breast cancer attracts more and more attention because of its high incidence. To explore the molecular functions and mechanisms, we performed RNA sequencing on the tumor tissues and their paired normal tissues from three breast cancer patients. By differential expression analysis, we found 3764 differentially expressed (DE) mRNAs, 5416 DE lncRNAs, and 148 DE circRNAs. Enrichment analysis suggested that the DE lncRNAs and DE circRNAs were enriched in mitochondria and nucleus, which indicated that they may participate in the vital metabolism directly or indirectly, such as fatty acid metabolism. Subsequently, the protein–protein interaction (PPI) network was constructed and we got 8 key proteins, of which the matrix metalloproteinase-9 (MMP9; degree 5) draws our attention. Based on the 38 up-regulated circRNAs and 14 down-regulated circRNAs, we constructed competing endogenous RNA (ceRNA) networks, from which the has-miR-6794-5p has been identified to enriched in the up-regulated network and correlated with the circNFIX directly. At this point, we presented that the circNFIX and MMP9 may play a significant role by regulating fatty acid metabolism in breast cancer.

Genomic Aberrations in Circulating Tumor DNAs from Palbociclib-Treated Metastatic Breast Cancer Patients Reveal a Novel Resistance Mechanism

Previously undescribed molecular mechanisms of resistance will emerge with the increased use of cyclin-dependent kinase 4/6 inhibitors in clinical settings. To identify genomic aberrations in circulating tumor DNA associated with treatment resistance in palbociclib-treated metastatic breast cancer (MBC) patients, we collected 35 pre- and post-treatment blood samples from 16 patients with estrogen receptor-positive (ER⁺) MBC, including 9 with inflammatory breast cancer (IBC). Circulating cell-free DNAs (cfDNAs) were isolated for sequencing using a targeted panel of 91 genes. Our data showed that FBXW7 and CDK6 were more frequently altered in IBC than in non-IBC, whereas conversely, PIK3CA was more frequently altered in non-IBC than in IBC. The cfDNA samples collected at follow-up harbored more mutations than baseline samples. By analyzing paired samples, we observed a higher percentage of patients with mutations in RB1, CCNE1, FBXW7, EZH2, and ARID1A, but a lower proportion of patients with mutated TSC2 at the post-treatment stage when they developed progression. Moreover, acquisition of CCNE1 mutations or loss of TSC2 mutations after treatment initiation conferred an unfavorable prognosis. These data provide insights into the relevance of novel genomic alterations in cfDNA to palbociclib resistance in MBC patients. Future large-scale prospective studies are warranted to confirm our findings.

Clinical and genomic analyses of neuroendocrine neoplasms of the breast

Breast neuroendocrine neoplasms (NENs) constitute a rare histologic subtype that includes both neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs). In this study, we aimed to gain insight into the clinical and molecular characteristics of NENs of the breast. NEN and paired distant normal fresh tissues and clinicopathological data were obtained from 17 patients with NENs, and clinicopathological data were collected from 755 patients with invasive breast carcinomas of no special type (IBCs-NST). We compared the clinicopathological characteristics of NENs and IBCs-NST and performed whole-exome sequencing (WES) of both NEN and paired normal tissues. Compared with the IBC-NST patients, the NEN patients had a higher mean age, lower clinical stage, and lower pathological nodal (pN) stage (P < 0.001, P < 0.001, and P = 0.017, respectively). The most frequently mutated gene in NENs was KMT2C (3/17, 17.6%). NENs had copy number variations (CNVs) of 8q, 11q, and 17q amplification and 17q and 11q deletion and harbored the following specific genes related to tumorigenesis: (i) suppressor genes with loss of heterozygosity (LOH) such as ACE (2/17, 11.8%); (ii) tumor driver genes such as GATA3 (2/17, 11.8%); and (iii) susceptibility genes such as MAP3K4 (17/17, 100%) and PDE4DIP (17/17, 100%). The oncogenic/likely oncogenic mutations of NETs in PI3K pathway genes (50.0%, 18.2%; P < 0.001) and MAPK signaling pathway genes (83.3%, 18.2%; P = 0.035) affected higher proportions than those of NECs. In conclusion, this study provides certain clinical and molecular evidence supporting NENs as a distinct subtype of breast cancer and provides some potential molecular features for distinguishing NETs from NECs.

Multi-Omics Profiling Suggesting Intratumoral Mast Cells as Predictive Index of Breast Cancer Lung Metastasis

Breast cancer lung metastasis has a high mortality rate and lacks effective treatments, for the factors that determine breast cancer lung metastasis are not yet well understood. In this study, data from 1067 primary tumors in four public datasets revealed the distinct microenvironments and immune composition among patients with or without lung metastasis. We used multi-omics data of the TCGA cohort to emphasize the following characteristics that may lead to lung metastasis: more aggressive tumor malignant behaviors, severer genomic instability, higher immunogenicity but showed generalized inhibition of effector functions of immune cells. Furthermore, we found that mast cell fraction can be used as an index for individual lung metastasis status prediction and verified in the 20 human breast cancer samples. The lower mast cell infiltrations correlated with tumors that were more malignant and prone to have lung metastasis. This study is the first comprehensive analysis of the molecular and cellular characteristics and mutation profiles of breast cancer lung metastasis, which may be applicable for prognostic prediction and aid in choosing appropriate medical examinations and therapeutic regimens.

Circulating Tumor Cells as a Tool to Untangle the Breast Cancer Heterogeneity Issue

Breast cancer (BC) is a disease characterized by high degrees of heterogeneity at morphologic, genomic, and genetic levels, even within the same tumor mass or among patients. As a consequence, different subpopulations coexist and less represented clones may have a selective advantage, significantly influencing the outcome of BC patients. Circulating tumor cells (CTCs) represent a rare population of cells with a crucial role in metastatic cascade, and in recent years have represented a fascinating alternative to overcome the heterogeneity issue as a “liquid biopsy”. However, besides the raw enumeration of these cells in advanced epithelial tumors, there are no CTC-based assays applied in the clinical practice to improve personalized medicine. In this review, we report the latest findings in the field of CTCs for intra-tumoral heterogeneity unmasking in BC, supporting the need to deepen their analysis to investigate their role in metastatic process and include the molecular characterization in the clinical practice. In the future, CTCs will be helpful in monitoring patients during treatment, as well as to better address therapeutic strategies.