Gene expression profiles of breast cancer metastasis according to organ site

Machine learning-driven prediction of brain metastasis in lung adenocarcinoma using miRNA profile and target gene pathway analysis of an mRNA dataset

BACKGROUND

Brain metastasis (BM) is common in lung adenocarcinoma (LUAD) and has a poor prognosis, necessitating predictive biomarkers. MicroRNAs (MiRNAs) promote cancer cell growth, infiltration, and metastasis. However, the relationship between the miRNA expression profiles and BM occurrence in patients with LUAD remains unclear.

METHODS

We conducted an analysis to identify miRNAs in tissue samples that exhibited different expression levels between patients with and without BM. Using a machine learning approach, we confirmed whether the miRNA profile could be a predictive tool for BM. We performed pathway analysis of miRNA target genes using a matched mRNA dataset.

RESULTS

We selected 25 miRNAs that consistently exhibited differential expression between the two groups of 32 samples. The 25-miRNA profile demonstrated a strong predictive potential for BM in both Group 1 and Group 2 and the entire dataset (area under the curve [AUC] = 0.918, accuracy = 0.875 in Group 1; AUC = 0.867, accuracy = 0.781 in Group 2; and AUC = 0.908, accuracy = 0.875 in the entire group). Patients predicted to have BM, based on the 25-miRNA profile, had lower survival rates. Target gene analysis of miRNAs suggested that BM could be induced through the ErbB signaling pathway, proteoglycans in cancer, and the focal adhesion pathway. Furthermore, patients predicted to have BM based on the 25-miRNA profile exhibited higher expression of the epithelial-mesenchymal transition signature, TWIST, and vimentin than those not predicted to have BM. Specifically, there was a correlation between EGFR mRNA levels and BM.

CONCLUSIONS

This 25-miRNA profile may serve as a biomarker for predicting BM in patients with LUAD.

6th and 7th International consensus guidelines for the management of advanced breast cancer (ABC guidelines 6 and 7)

This manuscript describes the Advanced Breast Cancer (ABC) international consensus guidelines updated at the last two ABC international consensus conferences (ABC 6 in 2021, virtual, and ABC 7 in 2023, in Lisbon, Portugal), organized by the ABC Global Alliance. It provides the main recommendations on how to best manage patients with advanced breast cancer (inoperable locally advanced or metastatic), of all breast cancer subtypes, as well as palliative and supportive care. These guidelines are based on available evidence or on expert opinion when a higher level of evidence is lacking. Each guideline is accompanied by the level of evidence (LoE), grade of recommendation (GoR) and percentage of consensus reached at the consensus conferences. Updated diagnostic and treatment algorithms are also provided. The guidelines represent the best management options for patients living with ABC globally, assuming accessibility to all available therapies. Their adaptation (i.e. resource-stratified guidelines) is often needed in settings where access to care is limited.

Molecular alterations and prognosis of breast cancer with cutaneous metastasis

PURPOSE

Cutaneous metastasis (CM) accounts for 5-30% of patients with breast cancer (BC) and presents unfavorable response to treatment and poor prognosis. A better understanding of the molecular alterations involved in metastasis is essential, which would help identify diagnostic and efficacy biomarkers for CM.

MATERIALS

We retrospectively reviewed a total of 13 patients with histological or cytological diagnosis of breast cancer and CM. Clinical information was extracted from the medical records. The mutational landscape of matched primary tumors with their lymph nodes or CM tissues were analyzed using next-generation sequencing (NGS) of 425 cancer-relevant genes. All tissues were also analyzed by immunohistochemistry (IHC). The association of prognosis with various clinical and molecular factors was also evaluated.

RESULTS

More than half of the patients were Ki67 low (< 50%, 53.7%). Most patients (12, 92.3%) had other metastasis sites other than skin. The median time from diagnosis to the presentation of CM (T1) was 15 months (range: 0-94 months) and the median time from CM to death (T2) was 13 months (range 1-78). The most frequently altered genes across the three types of tissues were TP53 (69.6%, 16/23), PIK3CA (34.8%, 8/23), and MYC (26.1%). The number of alterations in CM tends to be higher than in primary tumors (median 8 vs. 6, P = 0.077). Copy number loss in STK11, copy number gain in FGFR4, TERT, AR, FLT4 and VEGFA and mutations in ATRX, SRC, AMER1 and RAD51C were significantly enriched in CM (all P < 0.05). Ki67 high group (> 50%) showed significantly shorter T1 than the Ki67 low group (≤ 50%) (median 12.5 vs. 50.0 months, P = 0.036). TP53, PIK3CA mutations, and TERT amplification group were associated with inferior T2 (median 11 vs. 36 months, P = 0.065; 8 vs. 36 months, P = 0.013, 7 vs. 36 months, P = 0.003, respectively). All p values were not adjusted.

CONCLUSION

We compared the genomic features of primary breast cancer tissues with their corresponding CM tissues and discussed potential genes and pathways that may contribute to the skin metastasis of advanced breast cancers patients. TP53, PIK3CA mutant, and TERT amplification may serve as biomarkers for poor prognosis for CM patients.

Unraveling the clinicopathological and molecular changes induced by neoadjuvant chemotherapy and endocrine therapy in hormone receptor-positive/HER2-low and HER2-0 breast cancer

BACKGROUND

The characterization and comparison of gene expression and intrinsic subtype (IS) changes induced by neoadjuvant chemotherapy (NACT) and endocrine therapy in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2 (HER2)-low versus HR+/HER2-0 breast cancer (BC) has not been conducted so far. Most evidence on the association of HER2 status with pathologic responses and prognosis in HR+/HER2-negative BC is controversial and restricted to NACT-treated disease. Similarly, a temporal heterogeneity in HER2 status has been described only with NACT.

METHODS

We retrospectively recruited a consecutive cohort of 186 patients with stage I-IIIB HR+/HER2-negative BC treated with neoadjuvant therapy (NAT). Available diagnostic biopsies and surgical samples were characterized for main pathological features, PAM50 IS and ROR-P score, and gene expression. Associations with pathologic complete response, residual cancer burden-0/I, event-free survival (EFS) and overall survival (OS) based on HER2 status were assessed. Pre/post pathologic/molecular changes were analyzed in matched samples.

RESULTS

The HER2-low (62.9%) and HER2-0 (37.1%) cohorts did not differ significantly in main baseline features, treatments administered, breast-conserving surgery, pathologic complete response and residual cancer burden-0/I rates, EFS, and OS. NAT induced, regardless of HER2 status, a significant reduction of estrogen receptor/progesterone receptor and Ki67 levels, a down-regulation of PAM50 proliferation- and luminal-related genes/signatures, an up-regulation of selected immune genes, and a shift towards less aggressive IS and lower ROR-P. Moreover, 25% of HER2-0 changed to HER2-low and 34% HER2-low became HER2-0. HER2 shifts were significant after NACT (P < 0.001), not neoadjuvant endocrine therapy (P = 0.063), with consistent ERBB2 mRNA level dynamics. HER2 changes were not associated with EFS/OS.

CONCLUSIONS

HER2-low and HER2-0 status change after NAT in ∼30% of cases, mostly after NACT. Targeted adjuvant strategies should be investigated accordingly. Molecular downstaging with current chemo/endocrine agents and immunotherapy should not rely on HER2 immunohistochemical levels in HR+/HER2-negative BC. Instead, HER2-low-targeted approaches should be explored to pursue more effective and/or less toxic dimensional downstaging.

Identification of Genes Crucial for Biological Processes in Breast Cancer Liver Metastasis Relapse

Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, we aimed to shed light on the diversities of this process. This research investigated breast cancer liver metastasis relapse by employing a comprehensive approach that integrated data filtering, gene ontology and KEGG pathway analysis, overall survival analysis, identification of the alteration in the DEGs, visualization of the protein-protein interaction network, Signor 2.0, identification of positively correlated genes, immune cell infiltration analysis, genetic alternation analysis, copy number variant analysis, gene-to-mRNA interaction, transcription factor analysis, molecular docking, and identification of potential treatment targets. This study's integrative approach unveiled metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.

Association of molecular subtypes and treatment with survival in invasive micropapillary breast cancer: an analysis of the Surveillance, Epidemiology, and End Results database

BACKGROUND

This study aims to examine the features, treatments, and survival of invasive micropapillary carcinoma (IMPC) according to different molecular subtypes.

METHODS

In this cohort study, data between 2010 and 2018 were retrospectively reviewed from the Surveillance, Epidemiology, and End Results database. Molecular subtypes were categorized into four varieties: hormone receptor (HR)+/HER2- (Luminal A), HR+/HER2+ (Luminal B), HR-/HER2- [triple-negative (TN)], and HR-/HER2+ (HER2 enriched).

RESULTS

In this study, 1,180 IMPC patients were included, with 99 patients (8.39%) of the 1,180 patients having an overall mortality, and 53 patients (53.54%) of the 99 patients having a breast cancer-specific mortality. The follow-up duration was 40.00 (18.50, 61.00) months. TN molecular subtype was associated with worse OS and BCSS in IMPC patients. Treatment of chemotherapy, radiation, and combination therapy were associated with better survival in HR+/HER2+ molecular subtype and HR+/HER2- molecular subtype. However, in HR-/HER2- molecular subtype, treatment of chemotherapy was associated with a poor BCSS, and treatment of radiation was not associated with OS and BCSS. Surgery treatment was not associated with survival in HR+/HER2+ molecular subtype and HR+/HER2- molecular subtype. However, surgery treatment of mastectomy was associated with better OS in HR-/HER2- molecular subtype (P < 0.05).

CONCLUSION

The prognosis of IMPC was significantly influenced by different molecular subtypes. Chemotherapy and radiotherapy are beneficial in HR+/HER2+ and HR+/HER2- patients. However, they should be used with caution in HR-/HER2- (TN) patients.

Gene expression in metastatic breast cancer-patterns in primary tumors and metastatic tissue with prognostic potential

Background: Metastatic breast cancer (MBC) is the main cause of breast cancer-related death. The outcome of MBC varies, and there is a lack of biomarkers to aid in prognostication. The primary aim of this study was to evaluate the prognostic value of gene expression (GEX) signatures in the primary tumor (PT) and distant metastasis (DM) for progression-free survival (PFS) and overall survival (OS). The secondary aim was to describe GEX changes through MBC evolution and to identify MBC subtypes. Methods: RNA was extracted from the PT, lymph node metastasis (LNM), and DM from MBC patients in a prospective observational study (n = 142; CTC-MBC NCT01322893) and was subjected to GEX analysis retrospectively using the NanoString Breast Cancer 360™ panel. 31 continuous GEX variables in DMs and PTs were analyzed for PFS and OS by Cox regression analysis and Kaplan-Meier estimates. Multivariable Cox regressions were adjusted for number of DM sites and CTCs, visceral metastasis, ECOG status, age at MBC diagnosis and, in additional analyses, PAM50 subtype. Differential GEX analyses and Euclidean distances were used to describe subgroup differences and visualize within-patient heterogeneity. Results: Compared to DM GEX, GEX of the PT was at least equally useful for predicting MBC outcome. The strongest marker for a favorable PFS, both when expressed in the PT and the DM was AR, even after adjustment for prognostic markers including PAM50. GEX signatures related to hormone responsiveness, including ESR1, FOXA1, PGR, and AR were favorable prognostic markers, and the p53 signature was unfavorable for PFS when expressed in PT or DM. The previously published PAM50MET signature was prognostic for both PFS and OS. We established five distinct DM GEX profiles where two associated with liver and bone metastases, respectively. Finally, we identified four DM GEX profiles able to identify MBCs with poor OS in this cohort. Conclusion: GEX of both DM and PT are useful in MBC prognostication. GEX of AR adds prognostic information for MBC. Our descriptive analyses illuminate the biological differences between MBCs in relation to outcome and metastatic site.

High B7-H3 expression with low PD-L1 expression identifies armored-cold tumors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is generally regarded as the most aggressive subtype among breast cancers, but exhibits higher chemotherapeutic and immunotherapeutic responses due to its unique immunogenicity. Thus, appropriate discrimination of subtypes is critical for guiding therapeutic options in clinical practice. In this research, using multiple in-house and public cohorts, we investigated the expression features and immuno-correlations of B7-H3 in breast cancer and checked the anti-tumor effect of the B7-H3 monoclonal antibody in a mouse model. We also developed a novel classifier combining B7-H3 and PD-L1 expression in TNBC. B7-H3 was revealed to be related to immuno-cold features and accumulated collagen in TNBC. In addition, targeting B7-H3 using the monoclonal antibody significantly suppressed mouse TNBC growth, reversed the armored-cold phenotype, and also boosted anti-PD-1 immunotherapy. In addition, patients with B7-H3 high and PD-L1 low expression showed the lowest anti-tumor immune infiltration, the highest collagen level, and the lowest therapeutic responses to multiple therapies, which mostly belong to armored-cold tumors. Overall, this research provides a novel subtyping strategy based on the combination of B7-H3/PD-L1 expression, which leads to a novel approach for the management of TNBC.

HER2-low breast cancer: evolution of HER2 expression from primary tumor to distant metastases

BACKGROUND

Breast cancer (BC) with low human epidermal growth factor receptor 2 (HER2) expression is attracting much attention due to the breakthrough progress of novel anti-HER2 antibody-drug conjugates. HER2 expression is examined in patients with HER2-low BC and their distant metastases in this study, so as to further clarify the dynamic characteristics of HER2 low status in the process of disease progression.

METHODS

Patients diagnosed with HER2 low breast cancer (defined as IHC1+ or IHC2+/ISH-) between 2012 and 2021 were included in this study. We evaluated HER2 expression of primary sites and metastatic sites, compared the impact of different clinicopathological parameters on HER2 status of metastases and compared the overall survival and disease-free survival of patients with different HER2 status in metastases.

RESULTS

Ninety-eight patients were included. All HER2 IHC scores were confirmed and the consistent rate with the original pathological report was 81.1%. 27.6% of the patients showed different HER2 status in metastases. The HER2 discordance rate differed among different metastatic sites (p = 0.040). The higher the T stage of the primary BC, the higher the rate of HER2 discordance was observed (p = 0.042). For the specimen type of metastasis, HER2 discordant rate was higher in surgical specimen than biopsy (p = 0.050). No difference of HER2 discordance rate was found between HER2-1+ and HER2-2+ patients. But comparing HER2 IHC score, HER2-2+ patients were less likely to have consistent metastatic HER2 levels than HER2-1+ patients (p = 0.006). No difference in survival outcomes was observed between patients with different HER2 status in metastases.

CONCLUSIONS

There is a possibility of HER2 expression alteration in the metastases of HER2-low breast cancer. And the rate of altered HER2 low expression was different among different metastatic sites, different T stages of primary BC and specimen type of metastasis. No prognostic significance was observed.

Molecular signaling network and therapeutic developments in breast cancer brain metastasis

Breast cancer (BC) is one of the most frequently diagnosed cancers in women worldwide. It has surpassed lung cancer as the leading cause of cancer-related death. Breast cancer brain metastasis (BCBM) is becoming a major clinical concern that is commonly associated with ER-ve and HER2+ve subtypes of BC patients. Metastatic lesions in the brain originate when the cancer cells detach from a primary breast tumor and establish metastatic lesions and infiltrate near and distant organs via systemic blood circulation by traversing the BBB. The colonization of BC cells in the brain involves a complex interplay in the tumor microenvironment (TME), metastatic cells, and brain cells like endothelial cells, microglia, and astrocytes. BCBM is a significant cause of morbidity and mortality and presents a challenge to developing successful cancer therapy. In this review, we discuss the molecular mechanism of BCBM and novel therapeutic strategies for patients with brain metastatic BC.

Biology of breast cancer brain metastases and novel therapies targeting the blood brain barrier: an updated review

Brain metastasis (BM) is a critical cause of morbidity and mortality in patients with breast cancer (BC). Compared with other cancer cells, BC cells (BCs) exhibit special features in the metastatic process. However, the underlying mechanisms are still unclear, especially the crosstalk between tumour cells and the microenvironment. To date, novel therapies for BM, including targeted therapy and antibody‒drug conjugates, have been developed. Due to an improved understanding of the blood‒brain barrier (BBB) and blood-tumour barrier (BTB), the development and testing of therapeutic agents in clinical phases have substantially increased. However, these therapies face a major challenge due to the low penetration of the BBB or BTB. As a result, researchers have increasingly focused on finding ways to promote drug penetration through these barriers. This review provides an updated overview of breast cancer brain metastases (BCBM) and summarizes the newly developed therapies for BCBM, especially drugs targeting the BBB or BTB.

Prognostic value of intrinsic subtypes in hormone-receptor-positive metastatic breast cancer: systematic review and meta-analysis

BACKGROUND

In hormone receptor-positive (HoR+) breast cancer (BC), gene expression analysis identifies luminal A (LumA), luminal B (LumB), human epidermal growth factor receptor 2 (HER2)-enriched (HER2-E), basal-like (BL) intrinsic subtypes and a normal-like group. This classification has an established prognostic value in early-stage HoR+ BC. Here, we carried out a trial-level meta-analysis to determine the prognostic ability of subtypes in metastatic BC (MBC).

MATERIALS AND METHODS

We systematically reviewed all the available prospective phase II/III trials in HoR+ MBC where subtype was assessed. The primary endpoint was progression-free survival (PFS)/time to progression (TTP) of the LumA subtype compared to non-LumA. Secondary endpoints were PFS/TTP of each individual subtype, according to treatment, menopausal and HER2 status and overall survival (OS). The random-effect model was applied, and heterogeneity assessed through Cochran's Q and I². Threshold for significance was set at P < 0.05. The study was registered in PROSPERO (ID: CRD42021255769).

RESULTS

Seven studies were included (2536 patients). Non-LumA represented 55.2% and was associated with worse PFS/TTP than LumA [hazard ratio (HR) 1.77, P < 0.001, I² = 61%], independently of clinical HER2 status [P_{subgroup difference} (P_sub) = 0.16], systemic treatment (P_sub = 0.96) and menopausal status (P_sub = 0.12). Non-LumA tumors also showed worse OS (HR 2.00, P < 0.001, I² = 65%), with significantly different outcomes for LumB (PFS/TTP HR 1.46; OS HR 1.41), HER2-E (PFS/TTP HR 2.39; OS HR 2.08) and BL (PFS/TTP HR 2.67; OS HR 3.26), separately (PFS/TTP P_sub = 0.01; OS P_sub = 0.005). Sensitivity analyses supported the main result. No publication bias was observed.

CONCLUSIONS

In HoR+ MBC, non-LumA disease is associated with poorer PFS/TTP and OS than LumA, independently of HER2, treatment and menopausal status. Future trials in HoR+ MBC should consider this clinically relevant biological classification.

Eta polycaprolactone (ε-PCL) implants appear to cause a partial differentiation of breast cancer lung metastasis in a murine model

BACKGROUND

Cells in every epithelium can be roughly divided in three compartments: stem cell (SC) compartment, transient amplifying cell (TA) compartment and terminally differentiated (TD) compartment. Maturation of stem cells is characterized by epithelial stromal interaction and sequential maturational movement of stem cell's progeny through those compartments. In this work we hypothesize that providing an artificial stroma, which murine breast cancer metastatic cells can infiltrate, will induce their differentiation.

METHODS

BALB/c female mice were injected with 106 isogenic 4T1 breast cancer cells labeled with GFP. After 20 days primary tumors were removed, and artificial ε-PCL implants were implanted on the contralateral side. After 10 more days mice were sacrificed and implants along with lung tissue were harvested. Mice were divided in four groups: tumor removal with sham implantation surgery (n = 5), tumor removal with ε-PCL implant (n = 5), tumor removal with VEGF enriched ε-PCL implant (n = 7) and mice without tumor with VEGF enriched ε-PCL implant (n = 3). Differentiational status of GFP + cells was assessed by Ki67 and activated caspase 3 expression, thus dividing the population in SC like cells (Ki67+/dim aCasp3-), TA like cells (Ki67+/dim aCasp3+/dim) and TD like cells (Ki67- aCasp3+/dim) on flow cytometry.

RESULTS

Lung metastatic load was reduced by 33% in mice with simple ε-PCL implant when compared to tumor bearing group with no implant. Mice with VEGF enriched implants had 108% increase in lung metastatic load in comparison to tumor bearing mice with no implants. Likewise, amount of GFP + cells was higher in simple ε-PCL implant in comparison to VEGF enriched implants. Differentiation-wise, process of metastasizing to lungs reduces the average fraction of SC like cells when compared to primary tumor. This effect is made more uniform by both kinds of ε-PCL implants. The opposite process is mirrored in TA like cells compartment when it comes to averages. Effects of both types of implants on TD like cells were negligible. Furthermore, if gene expression signatures that mimic tissue compartments are analyzed in human breast cancer metastases, it turns out that TA signature is associated with increased survival probability.

CONCLUSION

ε-PCL implants without VEGF can reduce metastatic loads in lungs, after primary tumor removal. Both types of implants cause lung metastasis differentiation by shifting cancer cells from SC to TA compartment, leaving the TD compartment unaffected.

Genomics of Breast Cancer Brain Metastases: A Meta-Analysis and Therapeutic Implications

Breast cancer brain metastases are a challenging daily practice, and the biological link between gene mutations and metastatic spread to the brain remains to be determined. Here, we performed a meta-analysis on genomic data obtained from primary tumors, extracerebral metastases and brain metastases, to identify gene alterations associated with metastatic processes in the brain. Articles with relevant findings were selected using Medline via PubMed, from January 1999 up to February 2022. A critical review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement (PRISMA). Fifty-seven publications were selected for this meta-analysis, including 37,218 patients in all, 11,906 primary tumor samples, 5541 extracerebral metastasis samples, and 1485 brain metastasis samples. We report the overall and sub-group prevalence of gene mutations, including comparisons between primary tumors, extracerebral metastases and brain metastases. In particular, we identified six genes with a higher mutation prevalence in brain metastases than in extracerebral metastases, with a potential role in metastatic processes in the brain: ESR1, ERBB2, EGFR, PTEN, BRCA2 and NOTCH1. We discuss here the therapeutic implications. Our results underline the added value of obtaining biopsies from brain metastases to fully explore their biology, in order to develop personalized treatments.

Deep learning radiomics model based on breast ultrasound video to predict HER2 expression status

Purpose

The detection of human epidermal growth factor receptor 2 (HER2) expression status is essential to determining the chemotherapy regimen for breast cancer patients and to improving their prognosis. We developed a deep learning radiomics (DLR) model combining time-frequency domain features of ultrasound (US) video of breast lesions with clinical parameters for predicting HER2 expression status.

Patients and Methods

Data for this research was obtained from 807 breast cancer patients who visited from February 2019 to July 2020. Ultimately, 445 patients were included in the study. Pre-operative breast ultrasound examination videos were collected and split into a training set and a test set. Building a training set of DLR models combining time-frequency domain features and clinical features of ultrasound video of breast lesions based on the training set data to predict HER2 expression status. Test the performance of the model using test set data. The final models integrated with different classifiers are compared, and the best performing model is finally selected.

Results

The best diagnostic performance in predicting HER2 expression status is provided by an Extreme Gradient Boosting (XGBoost)-based time-frequency domain feature classifier combined with a logistic regression (LR)-based clinical parameter classifier of clinical parameters combined DLR, particularly with a high specificity of 0.917. The area under the receiver operating characteristic curve (AUC) for the test cohort was 0.810.

Conclusion

Our study provides a non-invasive imaging biomarker to predict HER2 expression status in breast cancer patients.

Clinical implications of the intrinsic molecular subtypes in hormone receptor-positive and HER2-negative metastatic breast cancer

Traditionally, the classification of breast cancer relies on the expression of immunohistochemical (IHC) biomarkers readily available in clinical practice. Using highly standardized and reproducible assays across patient cohorts, intrinsic molecular subtypes of breast cancer - also called "intrinsic subtypes" (IS) - have been identified based on the expression of 50 genes. Although IHC-based subgroups and IS moderately correlate to each other, they are not superimposable. In fact, non-luminal biology has been detected in a substantial proportion (5-20%) of hormone receptor-positive (HoR+) tumors, has prognostic value, and identifies reduced and increased sensitivity to endocrine therapy and chemotherapy, respectively. During tumor progression, a shift toward a non-luminal estrogen-independent and more aggressive phenotype has been demonstrated. Intrinsic genomic instability and cell plasticity, alone or combined with external constraints deriving from treatment selective pressure or interplay with the tumor microenvironment, may represent the determinants of such biological diversity between primary and metastatic disease, and during metastatic tumor evolution. In this review, we describe the distribution and the clinical behavior of IS as the disease progresses, focusing on HoR+/HER2-negative advanced breast cancer. In addition, we provide an overview of the ongoing clinical trials aiming to validate the predictive and prognostic value of IS towards their incorporation into routine care.

Potential of chimeric antigen receptor (CAR)-redirected immune cells in breast cancer therapies: Recent advances

Despite substantial developments in conventional treatments such as surgery, chemotherapy, radiotherapy, endocrine therapy, and molecular-targeted therapy, breast cancer remains the leading cause of cancer mortality in women. Currently, chimeric antigen receptor (CAR)-redirected immune cell therapy has emerged as an innovative immunotherapeutic approach to ameliorate survival rates of breast cancer patients by eliciting cytotoxic activity against cognate tumour-associated antigens expressing tumour cells. As a crucial component of adaptive immunity, T cells and NK cells, as the central innate immune cells, are two types of pivotal candidates for CAR engineering in treating solid malignancies. However, the biological distinctions between NK cells- and T cells lead to differences in cancer immunotherapy outcomes. Likewise, optimal breast cancer removal via CAR-redirected immune cells requires detecting safe target antigens, improving CAR structure for ideal immune cell functions, promoting CAR-redirected immune cells filtration to the tumour microenvironment (TME), and increasing the ability of these engineered cells to persist and retain within the immunosuppressive TME. This review provides a concise overview of breast cancer pathogenesis and its hostile TME. We focus on the CAR-T and CAR-NK cells and discuss their significant differences. Finally, we deliver a summary based on recent advancements in the therapeutic capability of CAR-T and CAR-NK cells in treating breast cancer.

Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors-Dependencies and Novel Pitfalls

Personalized oncology is a rapidly evolving area and offers cancer patients therapy options that are more specific than ever. However, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP)) on three datasets of metastases (n = 682 samples) with three different data transformations (unprocessed, log10 as well as log10 + 1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n = 616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between the site of resection and cluster formation outcome could be demonstrated, or for datasets consisting of solely metastasis or mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in the interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results highlight the need for a more thorough examination of parameters used in the analysis of clusters.

Role of germline variants in the metastasis of breast carcinomas

Most cancer-related deaths in breast cancer patients are associated with metastasis, a multistep, intricate process that requires the cooperation of tumour cells, tumour microenvironment and metastasis target tissues. It is accepted that metastasis does not depend on the tumour characteristics but the host’s genetic makeup. However, there has been limited success in determining the germline genetic variants that influence metastasis development, mainly because of the limitations of traditional genome-wide association studies to detect the relevant genetic polymorphisms underlying complex phenotypes. In this work, we leveraged the extreme discordant phenotypes approach and the epistasis networks to analyse the genotypes of 97 breast cancer patients. We found that the host’s genetic makeup facilitates metastases by the dysregulation of gene expression that can promote the dispersion of metastatic seeds and help establish the metastatic niche—providing a congenial soil for the metastatic seeds.

Breast Cancer Genomics: Primary and Most Common Metastases

Specific genomic alterations have been found in primary breast cancer involving driver mutations that result in tumorigenesis. Metastatic breast cancer, which is uncommon at the time of disease onset, variably impacts patients throughout the course of their disease. Both the molecular profiles and diverse genomic pathways vary in the development and progression of metastatic breast cancer. From the most common metastatic site (bone), to the rare sites such as orbital, gynecologic, or pancreatic metastases, different levels of gene expression indicate the potential involvement of numerous genes in the development and spread of breast cancer. Knowledge of these alterations can, not only help predict future disease, but also lead to advancement in breast cancer treatments. This review discusses the somatic landscape of breast primary and metastatic tumors.

Impact of HER2 Status on Pathological Response after Neoadjuvant Chemotherapy in Early Triple-Negative Breast Cancer

PURPOSE

Investigates the link between HER2 status and histological response after neoadjuvant chemotherapy in patients with early TNBC.

METHODS

We retrieved clinical and anatomopathological data retrospectively from 449 patients treated for the first time with standard neoadjuvant chemotherapy for early unilateral BC between 2005 and 2020. The primary endpoint was pathological complete response (pCR, i.e., ypT0 ypN0), according to HER2 status. Secondary endpoints included invasive disease-free survival (I-DFS) and overall survival (OS).

RESULTS

437 patients were included, and 121 (27.7%) patients had HER2-low tumours. The pCR rate was not significantly different between the HER2-low group vs. the HER2-0 group (35.7% versus 41.8%, p = 0.284) in either univariate analysis or multivariate analysis adjusted for TNM classification and grade (odds ratio [OR] = 0.70, confidence interval [CI] 95% 0.45-1.08). With a median follow-up of 72.9 months, no significant survival differences were observed between patients with HER2-low tumours vs. patients with HER2-0 tumours in terms of I-DFS (p = 0.487) and OS (p = 0.329).

CONCLUSIONS

In our cohort, HER2 status was not significantly associated with pCR in a manner consistent with data published recently on TNBC. However, the prognostic impact of HER2-low expression among TNBC patients warrants further evaluation.

Biomarkers of immunotherapy response in breast cancer beyond PD-L1

Immune checkpoint inhibitors have modified the treatment algorithm in a variety of cancer types, including breast cancer. Nevertheless, optimal selection of ideal candidates to these drugs remains an unmet need. Although PD-L1 expression by immunohistochemistry seems to be the most promising biomarker to date, its predictive ability is far from ideal. Thus, the development of new predictive biomarkers is essential for a better selection of patients. Here, we discuss potential biomarkers beyond PD-L1 that could play an important role in precision cancer immunotherapy.

Dissecting the biological heterogeneity of HER2-positive breast cancer

HER2-positive (HER2+) breast cancer (BC) is a heterogenous and multifaceted disease, with interesting therapeutic implications. First, all intrinsic molecular subtypes can be identified in HER2+ tumors, with the HER2-enriched being the most frequent. Such subtypes do not differ much from their counterparts in HER2-negative disease, apart for the high expression of genes in/near the HER2 amplicon on chromosome 17. Intrinsic subtyping, along with the quantification of ERBB2 mRNA levels, is associated with higher rates of pathologic complete response across neoadjuvant trials of dual HER2 blockade and might help select patients for de-escalation and escalation treatment strategies. Secondly, HER2+ tumors have a broad range of DNA alterations. ERBB2 mutations and alterations in the PI3K/Akt/mTOR pathway are among the most frequent and might predict benefit from potent pan-HER, PI3K and mTOR inhibitors. Moreover, HER2+ tumors are usually infiltrated by lymphocytes. These tumor infiltrating-lymphocytes (TILs) predict response to neoadjuvant anti-HER2-based treatment and exert a prognostic role. PD-L1, detected in ∼42 % of HER2+ BC, might also be useful to define patients responding to novel anti-PD1/PD-L1 immunotherapies. New multiparametric clinicopathologic and genomic tools accounting for this complexity, such as HER2DX, are under development to define more tailored treatment approaches. Finally, HER2-targeted antibody-drug conjugates (ADC) such as trastuzumab deruxtecan might be active in tumors with low expression of HER2. Overall, there is a need to molecularly characterize and develop novel targeted therapies for HER2+ disease.

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Almost 50 % of HER2+ breast cancer (BC) are molecularly HER2-Enriched (HER2-E).

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Most relevant mutations are found in ERBB2 (∼4 %) and PI3K/AKT/mTOR pathway (>30 %).

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Tumor infiltrating lymphocytes are frequent, predictive and prognostic in HER2+ BC.

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HER2 heterogeneity and HER2 low status are gaining therapeutic relevance.

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New treatments need to consider HER2+ molecular and microenvironmental complexity.