HER2 intratumoral heterogeneity is independently associated with distal metastasis and overall survival in HER2-positive breast carcinomas

Clinical characteristics and therapeutic direction of HER2 low-expression breast cancer

Human epidermal growth factor receptor 2 (HER2) is one of the oncogenic drivers of breast cancer and is often used as a definitive therapeutic marker for breast cancer. This has led to significant improvements in both targeted therapy and prognosis for HER2-targeted breast cancer. Due to the differences in HER2 gene and protein expression levels, they are clinically classified into HER2 zero-expression breast cancer, low-expression breast cancer and high-expression breast cancer. Among them, HER2 low-expression is considered a special expression state, which is insensitive to conventional anti-HER2 therapy and has a poorer prognosis and thus has received attention from researchers. Some studies demonstrate that patients with HER2 low-expression can benefit from antibody-drug conjugates (ADC). Several studies are currently exploring the efficacy of various ADC drugs in breast cancer with HER2 low-expression, opening up new treatment avenues for patients with HER2 low-expression breast cancer. This review aims to summarize the clinical features of HER2 low-expression breast cancer and the recent advances in its therapeutic agents.

Clinicopathologic Characteristics and Follow-Up Outcomes of Invasive Breast Carcinoma With Different Positive HER2 Fluorescence In Situ Hybridization Patterns: Experience From a Single Academic Institution

Human epidermal growth factor receptor 2 (HER2)-positive breast carcinoma (BC) encompasses a spectrum of molecular subtypes, characterized by varying HER2/CEP17 ratios and HER2 copy numbers, influencing responses to anti-HER2 therapy. This study stratified HER2 fluorescence in situ hybridization (FISH)-positive patients into 3 distinct groups-group 1 with high copy number (G1-HC: ratio ≥2, copy number ≥6), group 1 with low copy number (G1-LC: ratio ≥2, copy number ≥4 and <6), and group 3 (G3: ratio <2.0, copy number ≥6.0)-and evaluated their clinicopathologic features, response to anti-HER2 therapy, and outcomes. In a cohort of 2702 continuous primary BCs, G1-HC BCs accounted for 304 cases (11.3%), G1-LC for 37 cases (1.4%), and G3 for 75 cases (2.8%). G1-HC BCs were associated with younger age, higher tumor grade, and estrogen receptor negativity compared with G1-LC BCs. Furthermore, G1-HC BCs exhibited increased progesterone receptor negativity and HER2 immunohistochemistry 3+ compared with G1-LC and G3 BCs. Analysis of the subgroup of HER2 immunohistochemistry 2+-only cases (n = 166) showed similar results. Notably, G1-HC patients exhibited significantly enhanced responses to anti-HER2 neoadjuvant chemotherapy compared with G1-LC and G3 patients. Conversely, G1-LC patients displayed a lower likelihood of disease-free status compared with G1-HC and G3 patients, albeit with no significant differences in overall survival, distant metastasis, or local recurrence among the groups. These findings offer valuable clinicopathologic insights into different HER2 FISH positive subgroups, potentially informing future criteria for interpreting HER2 FISH results.

Clinicopathologic Features and Digital Imaging Analysis of HER2 Protein in Breast Carcinomas With Different HER2 Fluorescence in Situ Hybridization Patterns

BACKGROUND

HER2-targeted therapies have significantly improved outcomes for patients with HER2-positive breast cancer (BC), which represents 15% to 20% of all BC cases. HER2 status is assessed via immunohistochemistry (IHC) and/or in situ hybridization (ISH), dividing BCs into five groups (G1-G5).

PATIENTS AND METHODS

In a study of 2,702 primary BC cases, comprising 12.7% G1, 0.2% G2, 2.8% G3, 8.5% G4, and 75.9% G5, we analyzed clinicopathologic features and HER2 protein expression digitally for each ISH group.

RESULTS

Notably, G5 cases had a higher proportion of lobular carcinoma (13.9%) compared to other groups. G3 cases showed the highest percentage of grade 3 tumors (56.9%), while G5 cases had the lowest (21.4%). Additionally, G5 cases had the highest rate of estrogen receptor (ER) positivity (84.6%), while G1-HC (high copy number) cases had the lowest (70.4%). Most G1-HC cases were HER2 IHC 3+ (76.1%), while most G5 cases were IHC 0/1+ (75.7%). IHC 2+ was most common in G1-LC (low copy number) and G3 cases (83.8% and 90.7%, respectively), with G4 cases predominantly IHC 2+ (56.3%) and IHC 1+ (30.1%). Discordant HER2 IHC and ISH results were observed in 12 cases (0.4%), including 7 G1-HC (2.3%), 4 G1-LC (10.8%), and 1 G5 case (0.1%). Digital quantification of HER2 IHC levels in all groups except G5 revealed that G1-HC tumors had the highest HER2 protein expression, followed by G3, with G4 showing the lowest.

CONCLUSION

These findings offer valuable insights into the clinicopathologic characteristics and future management for different HER2 ISH groups.

High HER2 Intratumoral Heterogeneity Is a Predictive Factor for Poor Prognosis in Early-Stage and Locally Advanced HER2-Positive Breast Cancer

PURPOSE

Breast cancer tumors frequently have intratumoral heterogeneity (ITH). Tumors with high ITH cause therapeutic resistance and have human epidermal growth factor receptor 2 (HER2) heterogeneity in response to HER2-targeted therapies. This study aimed to investigate whether high HER2 heterogeneity levels were clinically related to a poor prognosis for HER2-targeted adjuvant therapy resistance in primary breast cancers.

METHODS

This study included patients with primary breast cancer (n = 251) treated with adjuvant HER2-targeted therapies. HER2 heterogeneity was manifested by the shape of HER2 fluorescence in situ hybridization amplification (FISH) distributed histograms with the HER2 gene copy number within a tumor sample. Each tumor was classified into a biphasic grade graph (high heterogeneity [HH]) group or a monophasic grade graph (low heterogeneity [LH]) group based on heterogeneity. Both groups were evaluated for disease-free survival (DFS) and overall survival (OS) for a median of ten years of annual follow-up.

RESULTS

Of 251 patients with HER2-positive breast cancer, 46 (18.3%) and 205 (81.7%) were classified into the HH and LH groups, respectively. The HH group had more distant metastases and a poorer prognosis than the LH group (DFS: p < 0.001 (HH:63% vs. LH:91% at 10 years) and for the OS: p = 0.012 (HH:78% vs. LH:95% at 10 years).

CONCLUSIONS

High HER2 heterogeneity is a poor prognostic factor in patients with HER2-positive breast cancer. A novel approach to heterogeneity, which is manifested by the shape of HER2 FISH distributions, might be clinically useful in the prognosis prediction of patients after HER2 adjuvant therapy.

Harnessing the Lysosomal Sorting Signals of the Cation-Independent Mannose-6-Phosphate Receptor for Targeted Degradation of Membrane Proteins

Membrane proteins are a crucial class of therapeutic targets that remain challenging to modulate using traditional occupancy-driven inhibition strategies or current proteolysis-targeting degradation approaches. Here, we report that the inherent endolysosomal sorting machinery can be harnessed for the targeted degradation of membrane proteins. A new degradation technique, termed signal-mediated lysosome-targeting chimeras (SignalTACs), was developed by genetically fusing the signaling motif from the cation-independent mannose-6-phosphate receptor (CI-M6PR) to a membrane protein binder. Antibody-based SignalTACs were constructed with the CI-M6PR signal peptides fused to the C-terminus of both heavy and light chains of IgG. We demonstrated the scope of this platform technology by degrading five pathogenesis-related membrane proteins, including HER2, EGFR, PD-L1, CD20, and CD71. Furthermore, two simplified constructs of SignalTACs, nanobody-based and peptide-based SignalTACs, were created and shown to promote the lysosomal degradation of target membrane proteins. Compared to the parent antibodies, SignalTACs exhibited significantly higher efficiency in inhibiting tumor cell growth both in vitro and in vivo. This work provides a simple, general, and robust strategy for degrading membrane proteins with molecular precision and may represent a powerful platform with broad research and therapeutic applications.

HER2-low metastases of HER2-negative primary tumors: a single institution analysis of intertumoral and internodal heterogeneity in node-positive breast cancer

Objective

HER2 status in breast cancer is an essential parameter in individual therapeutic decision-making and is routinely assessed in primary tumors in accordance with international recommendations. Reports of HER2 heterogeneity raise the question of basing treatment decisions on HER2 status in metastases, if present. We investigated the degree and clinical implications of HER2 heterogeneity in lymph node-positive breast cancer. Because of recent recognition of therapeutic opportunities in this group of tumors, we especially focused on cases involving low-level HER2 expression.

Methods

The HER2 status of primary tumors and of corresponding lymph node metastases was determined in archived material at the protein and gene levels using the gene- protein assay and interpreted in accordance with 2018 ASCO/CAP criteria. HER2-low status was defined as protein expression levels 1+ or 2+ with negative amplification status.

Results

We analyzed a series of 43 cases of primary infiltrating breast cancer, each with at least two axillary nodes harboring macrometastases (>2 mm), in total 206 such nodes. In 7% of cases, we detected intertumoral HER2 heterogeneity. Three of nine HER2-positive primary tumors were associated with HER2-negative metastases. No cases with HER2-negative primary tumors had HER2-positive metastases, but 55% (6/11) of HER2 0 primary tumors had HER2 1+ and/or 2+ metastases, and 19% (3/16) HER2 1+ cases had exclusively HER2 0 metastases. All metastases in HER2 2+ cases showed HER2-low protein expression levels. Internodal HER2 heterogeneity at low protein expression levels (presence of HER2 0, HER2 1+, and/or HER2 2+ metastatic deposits within the same axilla) was seen in 40% (17/43) of cases. We found no statistically significant association between HER2 heterogeneity and other tumor-related parameters. Survival data indicated worse outcomes in the HER2-low group compared with the rest of the cohort.

Conclusion

Our results indicate a substantial instability of HER2 protein expression, leading to considerable intertumoral and internodal HER2 heterogeneity in lymph node-positive breast carcinomas. This heterogeneity is particularly relevant in HER2-low tumors in which the corrective effects of HER2 gene copy number analysis definitionally is absent. Our findings suggest that determining HER2 status in metastatic lymph nodes may generate relevant information for therapeutic decision-making.

Lipidomics-based tissue heterogeneity in specimens of luminal breast cancer revealed by clustering analysis of mass spectrometry imaging: A preliminary study

Cancer tissues reflect a greater number of pathological characteristics of cancer compared to cancer cells, so the evaluation of cancer tissues can be effective in determining cancer treatment strategies. Mass spectrometry imaging (MSI) can evaluate cancer tissues and even identify molecules while preserving spatial information. Cluster analysis of cancer tissues' MSI data is currently used to evaluate the phenotype heterogeneity of the tissues. Interestingly, it has been reported that phenotype heterogeneity does not always coincide with genotype heterogeneity in HER2-positive breast cancer. We thus investigated the phenotype heterogeneity of luminal breast cancer, which is generally known to have few gene mutations. As a result, we identified phenotype heterogeneity based on lipidomics in luminal breast cancer tissues. Clusters were composed of phosphatidylcholine (PC), triglycerides (TG), phosphatidylethanolamine, sphingomyelin, and ceramide. It was found that mainly the proportion of PC and TG correlated with the proportion of cancer and stroma on HE images. Furthermore, the number of carbons in these lipid class varied from cluster to cluster. This was consistent with the fact that enzymes that synthesize long-chain fatty acids are increased through cancer metabolism. It was then thought that clusters containing PCs with high carbon counts might reflect high malignancy. These results indicate that lipidomics-based phenotype heterogeneity could potentially be used to classify cancer for which genetic analysis alone is insufficient for classification.

Centrosome instability: when good centrosomes go bad

The centrosome is a tiny cytoplasmic organelle that organizes and constructs massive molecular machines to coordinate diverse cellular processes. Due to its many roles during both interphase and mitosis, maintaining centrosome homeostasis is essential to normal health and development. Centrosome instability, divergence from normal centrosome number and structure, is a common pathognomonic cellular state tightly associated with cancers and other genetic diseases. As novel connections are investigated linking the centrosome to disease, it is critical to understand the breadth of centrosome functions to inspire discovery. In this review, we provide an introduction to normal centrosome function and highlight recent discoveries that link centrosome instability to specific disease states.

Intra-Tumor Heterogeneity Revealed by Mass Spectrometry Imaging Is Associated with the Prognosis of Breast Cancer

Intra-tumor heterogeneity (ITH) results from the coexistence of genetically distinct cancer cell (sub)populations, their phenotypic plasticity, and the presence of heterotypic components of the tumor microenvironment (TME). Here we addressed the potential association between phenotypic ITH revealed by mass spectrometry imaging (MSI) and the prognosis of breast cancer. Tissue specimens resected from 59 patients treated radically due to the locally advanced HER2-positive invasive ductal carcinoma were included in the study. After the on-tissue trypsin digestion of cellular proteins, peptide maps of all cancer regions (about 380,000 spectra in total) were segmented by an unsupervised approach to reveal their intrinsic heterogeneity. A high degree of similarity between spectra was observed, which indicated the relative homogeneity of cancer regions. However, when the number and diversity of the detected clusters of spectra were analyzed, differences between patient groups were observed. It is noteworthy that a higher degree of heterogeneity was found in tumors from patients who remained disease-free during a 5-year follow-up (n = 38) compared to tumors from patients with progressive disease (distant metastases detected during the follow-up, n = 21). Interestingly, such differences were not observed between patients with a different status of regional lymph nodes, cancer grade, or expression of estrogen receptor at the time of the primary treatment. Subsequently, spectral components with different abundance in cancer regions were detected in patients with different outcomes, and their hypothetical identity was established by assignment to measured masses of tryptic peptides identified in corresponding tissue lysates. Such differentiating components were associated with proteins involved in immune regulation and hemostasis. Further, a positive correlation between the level of tumor-infiltrating lymphocytes and heterogeneity revealed by MSI was observed. We postulate that a higher heterogeneity of tumors with a better prognosis could reflect the presence of heterotypic components including infiltrating immune cells, that facilitated the response to treatment.

Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry-based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.