Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer

Expression of PD-L1 in breast invasive lobular carcinoma

PURPOSE

The purpose of this study was to investigate the expression of PD-L1 in invasive lobular carcinoma (ILC) and to determine its implications.

METHODS

Tissue microarrays were constructed for 101 cases of ILC, and immunohistochemical staining for PD-L1 (using 22C3, SP142, and SP263 antibodies) was performed to examine the correlation between staining results and clinicopathologic parameters.

RESULTS

The positive cut-off values were defined as tumor cell (TC)≥1%, immune cell (IC)>0%, and IC≥1%. The range of PD-L1 TC positivity was 0.0-2.0%, with PD-L1 SP263 TC showing the highest positivity of 2.0%. The range of PD-L1 IC positivity was 0-21.8% for IC ≥ 1%, with PD-L1 22C3 IC showing the highest positivity. When PD-L1 IC was positive (IC≥1%), the highest antibody agreement was observed between SP263 and SP142 (OA = 93.1%), while the lowest agreement was observed between 22C3 and SP263 (OA = 73.3%, κ = 0.040). PD-L1 22C3 IC positivity (≥1%) was associated with high nuclear grade (p = 0.002), HER-2 positivity (p = 0.019), and pleomorphic type (p = 0.002).

CONCLUSION

PD-L1 expression in ILC shows a low TC positivity rate (0-2%) with various antibody clones and a variable IC positivity rate (0-21.8%). Pleomorphic type ILC exhibits higher PD-L1 IC positivity.

Synergizing Immunotherapy and Antibody-Drug Conjugates: New Horizons in Breast Cancer Therapy

The advent of immunotherapy and antibody-drug conjugates (ADCs) have revolutionized breast cancer treatment, offering new hope to patients. However, challenges, such as resistance and limited efficacy in certain cases, remain. Recently, the combination of these therapies has emerged as a promising approach to address these challenges. ADCs play a crucial role by delivering cytotoxic agents directly to breast cancer cells, minimizing damage to healthy tissue and enhancing the tumor-killing effect. Concurrently, immunotherapies harness the body's immune system to recognize and eliminate cancer cells. This integration offers potential to overcome resistance mechanisms and significantly improve therapeutic outcomes. This review explores the rationale behind combining immunotherapies with ADCs, recent advances in this field, and the potential implications for breast cancer treatment.

Immune Infiltration Correlates with Transcriptomic Subtypes in Primary ER+ Invasive Lobular Breast Cancer

Understanding interplay of breast cancer and microenvironment is critical. Here, we identified two transcriptomic subtypes and five immune infiltration patterns from RNA-seq and multiplex immunohistochemistry from 21 ER+/HER2- invasive lobular breast cancers. The proliferative subtype associated with increased immune infiltration especially by immunosuppressive regulatory T-cells and macrophages. We also defined a TAM-Low signature, which associated with lower infiltration of proliferative, pro-inflammatory TAM, and improved outcome in patients with ER+ tumors.

ELF4 was a prognostic biomarker and related to immune infiltrates in glioma

ELF4 (E74-like factor 4) is a transcription factor, dysregulation of which has been associated with carcinogenesis and cancer development. Nevertheless, the precise role of ELF4 in glioma pathology and its impact on clinical outcomes remains to be investigated. In the present research, comprehensive analyses demonstrated that elevated expression of ELF4 in glioma tissues correlates with malignant phenotypes and adverse clinical outcomes. Multivariate Cox regression analysis determined that ELF4 expression could serve as a reliable predictor of glioma outcomes. (CGGA, hazard ratio [HR]: 1.21, 95% confidence interval [CI]: 1.09-1.34, p<0.001; TCGA, HR: 1.19, 95%CI: 1.01-1.41, p=0.043; and Gravendeel, HR: 1.44, 95%CI: 1.15-1.80, p=0.002). Knockdown of ELF4 reduced the cell viability and migration capacity of glioma cells in vitro. In addition to the tumor invasive role, enrichment analysis revealed the overexpressed ELF4 was involved in the immune regulation, characterized by the elevated activity of Il6/Jak/Stat3 signaling, interferon alpha (IFN-α) response, and IL2/Stat5 signaling. Single-cell RNA sequencing (scRNA)-seq and spatial transcriptome (ST)-seq analyses revealed that ELF4 could induce reprogramming of tumor-associated monocytes/macrophages (TAMMs). Molecular docking analysis revealed ELF4 might be targeted by drugs/compounds, including Veliparib (ABT-888), Motesanib (AMG 706), and EHT 1864. Genomic analysis revealed that, in LGG, in the low ELF4 expression subgroup, IDH1 demonstrated a higher mutation rate, and TP53 and ATRX Chromatin Remodeler (ATRX) displayed the lower mutation rates, than the high ELF4 expression group. Conclusion: Our research suggests that ELF4 may contribute to the prognostic assessment of glioma and personalized medicine.

Spatial molecular profiling of mixed invasive ductal and lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and mutations

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity - e.g., MDLC with triple-negative breast cancer (TNBC) or basal ductal and estrogen receptor positive (ER+) luminal lobular regions, distinct enrichment of cell cycle arrest/senescence and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular but not ductal regions, and single-cell ductal and lobular subpopulations with unique oncogenic signatures further highlighting intraregional heterogeneity. Altogether, we demonstrated that the intratumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma.

E-Cadherin Mutational Landscape and Outcomes in Breast Invasive Lobular Carcinoma

Invasive lobular carcinomas (ILC) are characterized by the loss of E-cadherin expression and CDH1 gene inactivation. Diagnostic reproducibility for this tumor type is currently suboptimal and could be improved by a better understanding of its histomolecular and clinical heterogeneity. We have analyzed the relationship between the presence, type, or position of CDH1 mutations, E-cadherin expression, and clinicopathological features (including outcome) in a retrospective series of 251 primary ILC with a long follow-up (median: 9.5 years). The mutational status of E-cadherin gene (CDH1) was determined by RNA sequencing from frozen tumor samples. E-cadherin immunohistochemistry (IHC) was performed with antibodies directed against the intracellular domain (clone 4A2C7) and the extracellular domain (clone NCH38). IHC expression of p120 and β-catenin was also assessed in E-cadherin diffusely positive cases. Three major patterns of E-cadherin membrane expression were identified by IHC, with good agreement between the 2 clones (overall concordance: 83.8%, Kappa 0.67): null/focal expression (≤10%) (72.8% of cases for 4A2C7 and 83.8% for NCH38), heterogeneous expression (11%-89%) (19.2% of cases for 4A2C7 and 6.9% for NCH38), and diffuse expression (≥90%) (8% of cases for 4A2C7 and 9.3% for NCH38). E-cadherin membranous expression, when present, was abnormal (incomplete labeling and/or reduced intensity). ILC with diffuse E-cadherin expression showed abnormal β-catenin or p120-catenin staining in 21% of cases. Interestingly, these cases with diffusely expressed E-cadherin had a CDH1 mutation rate as high as the E-cadherin null/focal cases (∼70%) but were enriched in nontruncating mutations. Regarding CDH1 mutation location, intracytoplasmic domain mutations correlated with a divergent E-cadherin IHC phenotype between the 2 antibodies (4A2C7 ≤ 10%/NCH38 ≥ 10%). Clinico-pathological correlation analyses found that stromal amount (inversely correlated with tumor cellularity) and tumor-infiltrating lymphocytes were less abundant in ILC with E-cadherin null/focal cases. In addition, CDH1 truncating mutations were associated with radiohistologic size discordance and were identified in multivariate survival analysis as an independent poor prognosis factor in terms of metastasis risk and breast cancer-related mortality. Overall, our study highlights the importance of the precise mutational status of CDH1 in the clinical, radiological, histologic, and phenotypic expression of lobular carcinomas. These findings should be taken into account in future attempts to improve diagnostic criteria or methods for ILC, as well as for clinicobiological studies dedicated to this tumor type.

B Cell Lymphocytes as a Potential Source of Breast Carcinoma Marker Candidates

Despite advances in the genomic classification of breast cancer, current clinical tests and treatment decisions are commonly based on protein-level information. Nowadays breast cancer clinical treatment selection is based on the immunohistochemical (IHC) determination of four protein biomarkers: Estrogen Receptor 1 (ESR1), Progesterone Receptor (PGR), Human Epidermal Growth Factor Receptor 2 (HER2), and proliferation marker Ki-67. The prognostic correlation of tumor-infiltrating T cells has been widely studied in breast cancer, but tumor-infiltrating B cells have not received so much attention. We aimed to find a correlation between immunohistochemical results and a proteomic approach in measuring the expression of proteins isolated from B-cell lymphocytes in peripheral blood samples. Shotgun proteomic analysis was chosen for its key advantage over other proteomic methods, which is its comprehensive and untargeted approach to analyzing proteins. This approach facilitates better characterization of disease-associated changes at the protein level. We identified 18 proteins in B cell lymphocytes with a significant fold change of more than 2, which have promising potential to serve as breast cancer biomarkers in the future.

Spatial molecular profiling of mixed invasive ductal-lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and mutations

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially-resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity (e.g., MDLC with TNBC/basal ductal and ER+/luminal lobular regions), distinct enrichment of senescence/dormancy and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular, but not ductal regions, and single-cell ductal and lobular sub-populations with unique oncogenic signatures further highlighting intra-regional heterogeneity. Altogether, we demonstrated that the intra-tumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma.

Significance

MDLC displays both ductal and lobular tumor regions. Our multi-omic profiling approach revealed that these morphologically distinct tumor regions harbor distinct intrinsic subtypes and oncogenic features that may cause prognostic uncertainty and therapeutic dilemma. Thus histopathological/molecular profiling of individual tumor regions may guide clinical decision making and benefit patients with MDLC, particularly in the advanced setting where there is increased reliance on next generation sequencing.

Pathway-based signatures predict patient outcome, chemotherapy benefit and synthetic lethal dependencies in invasive lobular breast cancer

BACKGROUND

Invasive Lobular Carcinoma (ILC) is a morphologically distinct breast cancer subtype that represents up to 15% of all breast cancers. Compared to Invasive Breast Carcinoma of No Special Type (IBC-NST), ILCs exhibit poorer long-term outcome and a unique pattern of metastasis. Despite these differences, the systematic discovery of robust prognostic biomarkers and therapeutically actionable molecular pathways in ILC remains limited.

METHODS

Pathway-centric multivariable models using statistical machine learning were developed and tested in seven retrospective clinico-genomic cohorts (n = 996). Further external validation was performed using a new RNA-Seq clinical cohort of aggressive ILCs (n = 48).

RESULTS AND CONCLUSIONS

mRNA dysregulation scores of 25 pathways were strongly prognostic in ILC (FDR-adjusted P < 0.05). Of these, three pathways including Cell-cell communication, Innate immune system and Smooth muscle contraction were also independent predictors of chemotherapy response. To aggregate these findings, a multivariable machine learning predictor called PSILC was developed and successfully validated for predicting overall and metastasis-free survival in ILC. Integration of PSILC with CRISPR-Cas9 screening data from breast cancer cell lines revealed 16 candidate therapeutic targets that were synthetic lethal with high-risk ILCs. This study provides interpretable prognostic and predictive biomarkers of ILC which could serve as the starting points for targeted drug discovery for this disease.

Plasma-based analysis of ERBB2 mutational status by multiplex digital PCR in a large series of patients with metastatic breast cancer

Erb-b2 receptor tyrosine kinase 2 (ERBB2)-activating mutations are therapeutically actionable alterations found in various cancers, including metastatic breast cancer (MBC). We developed multiplex digital PCR assays to detect and quantify ERBB2 mutations in circulating tumor DNA from liquid biopsies. We studied the plasma from 272 patients with hormone-receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) MBC to detect 17 ERBB2 mutations using a screening assay. The assay was developed on the three-color Crystal dPCR™ naica® platform with a two-step strategy for precise mutation identification. We found that nine patients (3.3%) harbored at least one ERBB2 mutation. The mutation rate was higher in patients with lobular histology (5.9%) compared to invasive breast carcinoma of no special type (2.6%). A total of 12 mutations were found with the following frequencies: L755S (25.00%), V777L (25.00%), S310Y (16.67%), L869R (16.67%), S310F (8.33%), and D769H (8.33%). Matched tumor samples from six patients identified the same mutations with an 83% concordance rate. In summary, our highly sensitive multiplex digital PCR assays are well suited for plasma-based monitoring of ERBB2 mutational status in patients with MBC.

WNT4 Regulates Cellular Metabolism via Intracellular Activity at the Mitochondria in Breast and Gynecologic Cancers

Wnt ligand WNT4 is critical in female reproductive tissue development, with WNT4 dysregulation linked to related pathologies including breast cancer (invasive lobular carcinoma, ILC) and gynecologic cancers. WNT4 signaling in these contexts is distinct from canonical Wnt signaling yet inadequately understood. We previously identified atypical intracellular activity of WNT4 (independent of Wnt secretion) regulating mitochondrial function, and herein examine intracellular functions of WNT4. We further examine how convergent mechanisms of WNT4 dysregulation impact cancer metabolism. In ILC, WNT4 is co-opted by estrogen receptor α (ER) via genomic binding in WNT4 intron 1, while in gynecologic cancers, a common genetic polymorphism (rs3820282) at this ER binding site alters WNT4 regulation. Using proximity biotinylation (BioID), we show canonical Wnt ligand WNT3A is trafficked for secretion, but WNT4 is localized to the cytosol and mitochondria. We identified DHRS2, mTOR, and STAT1 as putative WNT4 cytosolic/mitochondrial signaling partners. Whole metabolite profiling, and integrated transcriptomic data, support that WNT4 mediates metabolic reprogramming via fatty acid and amino acid metabolism. Furthermore, ovarian cancer cell lines with rs3820282 variant genotype are WNT4 dependent and have active WNT4 metabolic signaling. In protein array analyses of a cohort of 103 human gynecologic tumors enriched for patient diversity, germline rs3820282 genotype is associated with metabolic remodeling. Variant genotype tumors show increased AMPK activation and downstream signaling, with the highest AMPK signaling activity in variant genotype tumors from non-White patients. Taken together, atypical intracellular WNT4 signaling, in part via genetic dysregulation, regulates the distinct metabolic phenotypes of ILC and gynecologic cancers.

SIGNIFICANCE

WNT4 regulates breast and gynecologic cancer metabolism via a previously unappreciated intracellular signaling mechanism at the mitochondria, with WNT4 mediating metabolic remodeling. Understanding WNT4 dysregulation by estrogen and genetic polymorphism offers new opportunities for defining tumor biology, precision therapeutics, and personalized cancer risk assessment.

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.

Systems approach for congruence and selection of cancer models towards precision medicine

Cancer models are instrumental as a substitute for human studies and to expedite basic, translational, and clinical cancer research. For a given cancer type, a wide selection of models, such as cell lines, patient-derived xenografts, organoids and genetically modified murine models, are often available to researchers. However, how to quantify their congruence to human tumors and to select the most appropriate cancer model is a largely unsolved issue. Here, we present Congruence Analysis and Selection of CAncer Models (CASCAM), a statistical and machine learning framework for authenticating and selecting the most representative cancer models in a pathway-specific manner using transcriptomic data. CASCAM provides harmonization between human tumor and cancer model omics data, systematic congruence quantification, and pathway-based topological visualization to determine the most appropriate cancer model selection. The systems approach is presented using invasive lobular breast carcinoma (ILC) subtype and suggesting CAMA1 followed by UACC3133 as the most representative cell lines for ILC research. Two additional case studies for triple negative breast cancer (TNBC) and patient-derived xenograft/organoid (PDX/PDO) are further investigated. CASCAM is generalizable to any cancer subtype and will authenticate cancer models for faithful non-human preclinical research towards precision medicine.

Construction of immune score and its prognostic value in invasive lobular carcinoma of the breast using computational pathology analysis

BACKGROUND

Previous studies have shown that high level of TILs in invasive lobular carcinoma (ILC) is associated with poor prognosis, contrary to that in TNBC and HER2-positive breast cancer.

METHODS

The densities of six immune cell markers and three immune checkpoints in the ILC microenvironment were detected by computational pathology analysis. Then, the LASSO cox regression model was used to construct an immune score (IS) and further evaluate its prognostic value.

RESULTS

In our ILC cohort, the low density of CD4, CD8, CD20, CD56, CD68, FOXP3, PD-1, and PD-L1 had significantly longer disease-free survival (DFS) and overall survival (OS); however, the low density of CTLA-4 was associated with shorter DFS and OS. Based on this, an IS was constructed, and patients with low-IS had significantly prolonged DFS (p < 0.0001) and OS (p < 0.0001). Multivariate analysis revealed that IS was an independent prognostic indicator for DFS and OS. Further analysis showed that IS may increase the prognostic value of TNM stage. We further explored the prognostic role of CD68 and FOXP3 in the transcriptional level and the corresponding ISm in the METABRIC dataset, and found that low proportion of CD68 and FOXP3 and their ISm were associated with longer OS, and ISm was also an independent prognostic factor for OS.

CONCLUSION

IS was a promising biomarker to distinguish the prognosis in ILC patients.

Multiomics insights on the onset, progression, and metastatic evolution of breast cancer

Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.

Multi-omic characterization of ILC and ILC-like cell lines as part of ILC cell line encyclopedia (ICLE) defines new models to study potential biomarkers and explore therapeutic opportunities

Invasive lobular carcinoma (ILC), the most common histological "special type", accounts for ∼10-15% of all BC diagnoses, is characterized by unique features such as E-cadherin loss/deficiency, lower grade, hormone receptor positivity, larger diffuse tumors, and specific metastatic patterns. Despite ILC being acknowledged as a disease with distinct biology that necessitates specialized and precision medicine treatments, the further exploration of its molecular alterations with the goal of discovering new treatments has been hindered due to the scarcity of well-characterized cell line models for studying this disease. To address this, we generated the ILC Cell Line Encyclopedia (ICLE), providing a comprehensive multi-omic characterization of ILC and ILC-like cell lines. Using consensus multi-omic subtyping, we confirmed luminal status of previously established ILC cell lines and uncovered additional ILC/ILC-like cell lines with luminal features for modeling ILC disease. Furthermore, most of these luminal ILC/ILC-like cell lines also showed RNA and copy number similarity to ILC patient tumors. Similarly, ILC/ILC-like cell lines also retained molecular alterations in key ILC genes at similar frequency to both primary and metastatic ILC tumors. Importantly, ILC/ILC-like cell lines recapitulated the CDH1 alteration landscape of ILC patient tumors including enrichment of truncating mutations in and biallelic inactivation of CDH1 gene. Using whole-genome optical mapping, we uncovered novel genomic-rearrangements including novel structural variations in CDH1 and functional gene fusions and characterized breast cancer specific patterns of chromothripsis in chromosomes 8, 11 and 17. In addition, we systematically analyzed aberrant DNAm events and integrative analysis with RNA expression revealed epigenetic activation of TFAP2B - an emerging biomarker of lobular disease that is preferentially expressed in lobular disease. Finally, towards the goal of identifying novel druggable vulnerabilities in ILC, we analyzed publicly available RNAi loss of function breast cancer cell line datasets and revealed numerous putative vulnerabilities cytoskeletal components, focal adhesion and PI3K/AKT pathway in ILC/ILC-like vs NST cell lines. In summary, we addressed the lack of suitable models to study E-cadherin deficient breast cancers by first collecting both established and putative ILC models, then characterizing them comprehensively to show their molecular similarity to patient tumors along with uncovering their novel multi-omic features as well as highlighting putative novel druggable vulnerabilities. Not only we expand the array of suitable E-cadherin deficient cell lines available for modelling human-ILC disease but also employ them for studying epigenetic activation of a putative lobular biomarker as well as identifying potential druggable vulnerabilities for this disease towards enabling precision medicine research for human-ILC.

Canonical Kaiso target genes define a functional signature that associates with breast cancer survival and the invasive lobular carcinoma histological type

Invasive lobular carcinoma (ILC) is a low- to intermediate-grade histological breast cancer type caused by mutational inactivation of E-cadherin function, resulting in the acquisition of anchorage independence (anoikis resistance). Most ILC cases express estrogen receptors, but options are limited in relapsed endocrine-refractory disease as ILC tends to be less responsive to standard chemotherapy. Moreover, ILC can relapse after >15 years, an event that currently cannot be predicted. E-cadherin inactivation leads to p120-catenin-dependent relief of the transcriptional repressor Kaiso (ZBTB33) and activation of canonical Kaiso target genes. Here, we examined whether an anchorage-independent and ILC-specific transcriptional program correlated with clinical parameters in breast cancer. Based on the presence of a canonical Kaiso-binding consensus sequence (cKBS) in the promoters of genes that are upregulated under anchorage-independent conditions, we defined an ILC-specific anoikis resistance transcriptome (ART). Converting the ART genes into human orthologs and adding published Kaiso target genes resulted in the Kaiso-specific ART (KART) 33-gene signature, used subsequently to study correlations with histological and clinical variables in primary breast cancer. Using publicly available data for ERPOS Her2NEG breast cancer, we found that expression of KART was positively associated with the histological ILC breast cancer type (p < 2.7E-07). KART expression associated with younger patients in all invasive breast cancers and smaller tumors in invasive ductal carcinoma of no special type (IDC-NST) (<2 cm, p < 6.3E-10). We observed associations with favorable long-term prognosis in both ILC (hazard ratio [HR] = 0.51, 95% CI = 0.29-0.91, p < 3.4E-02) and IDC-NST (HR = 0.79, 95% CI = 0.66-0.93, p < 1.2E-04). Our analysis thus defines a new mRNA expression signature for human breast cancer based on canonical Kaiso target genes that are upregulated in E-cadherin deficient ILC. The KART signature may enable a deeper understanding of ILC biology and etiology. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Lobular Carcinoma of the Breast: A Comprehensive Review with Translational Insights

The second most common breast carcinoma, invasive lobular carcinoma, accounts for approximately 15% of tumors of breast origin. Its incidence has increased in recent times due in part to hormone replacement therapy and improvement in diagnostic modalities. Although believed to arise from the same cell type as their ductal counterpart, invasive lobular carcinomas (ILCs) are a distinct entity with different regulating genetic pathways, characteristic histologies, and different biology. The features most unique to lobular carcinomas include loss of E-Cadherin leading to discohesion and formation of a characteristic single file pattern on histology. Because most of these tumors exhibit estrogen receptor positivity and Her2 neu negativity, endocrine therapy has predominated to treat these tumors. However novel treatments like CDK4/6 inhibitors have shown importance and antibody drug conjugates may be instrumental considering newer categories of Her 2 Low breast tumors. In this narrative review, we explore multiple pathological aspects and translational features of this unique entity. In addition, due to advancement in technologies like spatial transcriptomics and other hi-plex technologies, we have tried to enlist upon the characteristics of the tumor microenvironment and the latest associated findings to better understand the new prospective therapeutic options in the current era of personalized treatment.

MYC is a clinically significant driver of mTOR inhibitor resistance in breast cancer

Targeting the PI3K-AKT-mTOR pathway is a promising therapeutic strategy for breast cancer treatment. However, low response rates and development of resistance to PI3K-AKT-mTOR inhibitors remain major clinical challenges. Here, we show that MYC activation drives resistance to mTOR inhibitors (mTORi) in breast cancer. Multiomic profiling of mouse invasive lobular carcinoma (ILC) tumors revealed recurrent Myc amplifications in tumors that acquired resistance to the mTORi AZD8055. MYC activation was associated with biological processes linked to mTORi response and counteracted mTORi-induced translation inhibition by promoting translation of ribosomal proteins. In vitro and in vivo induction of MYC conferred mTORi resistance in mouse and human breast cancer models. Conversely, AZD8055-resistant ILC cells depended on MYC, as demonstrated by the synergistic effects of mTORi and MYCi combination treatment. Notably, MYC status was significantly associated with poor response to everolimus therapy in metastatic breast cancer patients. Thus, MYC is a clinically relevant driver of mTORi resistance that may stratify breast cancer patients for mTOR-targeted therapies.

Quantifying hormone receptor status in lobular breast cancer in an institutional series: the relationship between estrogen and progesterone receptor status and outcomes

PURPOSE

Recent guidelines defined a new reporting category of ER-low-positive breast cancer based on immunohistochemistry (IHC). While low positivity of either hormone receptor is uncommon in invasive lobular carcinoma (ILC), we sought to investigate whether relatively low hormone receptor positivity was associated with tumor characteristics and patient outcomes in a single institutional cohort.

METHODS

We searched an institutional database for cases of stage I-III ILC with available IHC reports. Based on prior published categories in ILC, ER was classified as low, medium, or high as defined by ER staining of 10-69%, 70-89%, and ≥ 90% respectively. PR low and high tumors were defined by < 20%, or ≥ 20% staining respectively. We used chi-squared tests, t-tests, and Cox proportional hazards models to evaluate associations between ER/PR categories and tumor characteristics or disease-free survival (DFS).

RESULTS

The cohort consisted of 707 ILC cases, with 11% of cases categorized as ER low, 15.1% as medium, and 73.8% as high. The majority (67.6%) were PR high. Patients with ER low/medium expression were significantly younger, and more likely to also have PR low and/or HER2 positive tumors compared to those that were ER high. In a Cox proportional hazards model adjusting for age, stage, grade, pleomorphic histology, and treatment, ER category was not prognostic for DFS, but PR negative and PR low status each had significantly worse DFS compared to PR high status (HR 3.5, 95% CI 1.8-6.7, p < 0.001; and HR 2.0, 95% CI 1.1-3.5, p = 0.015, respectively).

CONCLUSION

These findings highlight the relevance of quantifying ER and PR within ILC.

Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration

Multiomics data including imaging radiomics and various types of molecular biomarkers have been increasingly investigated for better diagnosis and therapy in the era of precision oncology. Artificial intelligence (AI) including machine learning (ML) and deep learning (DL) techniques combined with the exponential growth of multiomics data may have great potential to revolutionize cancer subtyping, risk stratification, prognostication, prediction and clinical decision-making. In this article, we first present different categories of multiomics data and their roles in diagnosis and therapy. Second, AI-based data fusion methods and modeling methods as well as different validation schemes are illustrated. Third, the applications and examples of multiomics research in oncology are demonstrated. Finally, the challenges regarding the heterogeneity data set, availability of omics data, and validation of the research are discussed. The transition of multiomics research to real clinics still requires consistent efforts in standardizing omics data collection and analysis, building computational infrastructure for data sharing and storing, developing advanced methods to improve data fusion and interpretability, and ultimately, conducting large-scale prospective clinical trials to fill the gap between study findings and clinical benefits.

Riluzole Suppresses Growth and Enhances Response to Endocrine Therapy in ER+ Breast Cancer

Background

Resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer remains a significant clinical problem. Riluzole is FDA-approved for the treatment of amyotrophic lateral sclerosis. A benzothiazole-based glutamate release inhibitor with several context-dependent mechanism(s) of action, riluzole has shown antitumor activity in multiple malignancies, including melanoma, glioblastoma, and breast cancer. We previously reported that the acquisition of tamoxifen resistance in a cellular model of invasive lobular breast cancer is accompanied by the upregulation of GRM mRNA expression and growth inhibition by riluzole.

Methods

We tested the ability of riluzole to reduce cell growth, alone and in combination with endocrine therapy, in a diverse set of ER+ invasive ductal and lobular breast cancer-derived cell lines, primary breast tumor explant cultures, and the estrogen-independent, ESR1-mutated invasive lobular breast cancer patient-derived xenograft model HCI-013EI.

Results

Single-agent riluzole suppressed the growth of ER+ invasive ductal and lobular breast cancer cell lines in vitro, inducing a histologic subtype-associated cell cycle arrest (G0-G1 for ductal, G2-M for lobular). Riluzole induced apoptosis and ferroptosis and reduced phosphorylation of multiple prosurvival signaling molecules, including Akt/mTOR, CREB, and Fak/Src family kinases. Riluzole, in combination with either fulvestrant or 4-hydroxytamoxifen, additively suppressed ER+ breast cancer cell growth in vitro. Single-agent riluzole significantly inhibited HCI-013EI patient-derived xenograft growth in vivo, and the combination of riluzole plus fulvestrant significantly reduced proliferation in ex vivo primary breast tumor explant cultures.

Conclusion

Riluzole may offer therapeutic benefits in diverse ER+ breast cancers, including lobular breast cancer.

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.

Immune landscape in invasive ductal and lobular breast cancer reveals a divergent macrophage-driven microenvironment

T cell-centric immunotherapies have shown modest clinical benefit thus far for estrogen receptor-positive (ER+) breast cancer. Despite accounting for 70% of all breast cancers, relatively little is known about the immunobiology of ER+ breast cancer in women with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC). To investigate this, we performed phenotypic, transcriptional and functional analyses for a cohort of treatment-naive IDC (n = 94) and ILC (n = 87) tumors. We show that macrophages, and not T cells, are the predominant immune cells infiltrating the tumor bed and the most transcriptionally diverse cell subset between IDC and ILC. Analysis of cellular neighborhoods revealed an interplay between macrophages and T cells associated with longer disease-free survival in IDC but not ILC. Our datasets provide a rich resource for further interrogation into immune cell dynamics in ER+ IDC and ILC and highlight macrophages as a potential target for ER+ breast cancer.

PD-L1 blockade in combination with carboplatin as immune induction in metastatic lobular breast cancer: the GELATO trial

Invasive lobular breast cancer (ILC) is the second most common histological breast cancer subtype, but ILC-specific trials are lacking. Translational research revealed an immune-related ILC subset, and in mouse ILC models, synergy between immune checkpoint blockade and platinum was observed. In the phase II GELATO trial ( NCT03147040 ), patients with metastatic ILC were treated with weekly carboplatin (area under the curve 1.5 mg ml-1 min-1) as immune induction for 12 weeks and atezolizumab (PD-L1 blockade; triweekly) from the third week until progression. Four of 23 evaluable patients had a partial response (17%), and 2 had stable disease, resulting in a clinical benefit rate of 26%. From these six patients, four had triple-negative ILC (TN-ILC). We observed higher CD8+ T cell infiltration, immune checkpoint expression and exhausted T cells after treatment. With this GELATO trial, we show that ILC-specific clinical trials are feasible and demonstrate promising antitumor activity of atezolizumab with carboplatin, particularly for TN-ILC, and provide insights for the design of highly needed ILC-specific trials.

Acquired radioresistance in EMT6 mouse mammary carcinoma cell line is mediated by CTLA-4 and PD-1 through JAK/STAT/PI3K pathway

Cancer recurrence is often associated with the acquisition of radioresistance by cancer tissues due to failure in radiotherapy. The underlying mechanism leading to the development of acquired radioresistance in the EMT6 mouse mammary carcinoma cell line and the potential pathway involved was investigated by comparing differential gene expressions between parental and acquired radioresistance cells. EMT6 cell line was exposed to 2 Gy/per cycle of gamma-ray and the survival fraction between EMT6-treated and parental cells was compared. EMT6RR_MJI (acquired radioresistance) cells was developed after 8 cycles of fractionated irradiation. The development of EMT6RR_MJI cells was confirmed with further irradiation at different doses of gamma-ray, and both the survival fraction and migration rates were measured. Higher survival fraction and migration rates were obtained in EMT6RR_MJI cells after exposure to 4 Gy and 8 Gy gamma-ray irradiations compared to their parental cells. Gene expression between EMT6RR_MJI and parental cells was compared, and 16 genes identified to possess more than tenfold changes were selected and validated using RT-PCR. Out of these genes, 5 were significantly up-regulated i.e., IL-6, PDL-1, AXL, GAS6 and APCDD1. Based on pathway analysis software, the development of acquired radioresistance in EMT6RR_MJI was hypothesized through JAK/STAT/PI3K pathway. Presently, CTLA-4 and PD-1 were determined to be associated with JAK/STAT/PI3K pathway, where both their expressions were significantly increased in EMT6RR_MJI compared to parental cells in the 1st, 4th and 8th cycle of radiation. As a conclusion, the current findings provided a mechanistic platform for the development of acquired radioresistance in EMT6RR_MJI through overexpression of CTLA-4 and PD-1, and novel knowledge on therapeutic targets for recurrent radioresistant cancers.

Evolving treatment landscape of immunotherapy in breast cancer: current issues and future perspectives

Immune checkpoint inhibitors (ICIs) deeply changed the treatment landscape of breast cancer (BC). In particular, anti-programmed-death (ligand) 1 antibodies were approved for the treatment of triple-negative breast cancer (TNBC), both in first line for metastatic disease and in neoadjuvant setting, on the basis of a demonstrated improvement of the survival outcomes. In light of these results, current clinical trials aim at improving this benefit investigating novel combinations and strategies, at exploring the role of ICIs beyond TNBC, and at better selecting the patients in order to spare non-responders from avoidable toxicities. This narrative review aims at summarizing and discussing the evolving landscape of immunotherapeutic treatments for BC, highlighting the current challenges and the future perspectives.

The Great Immune Escape: Understanding the Divergent Immune Response in Breast Cancer Subtypes

Breast cancer, the most common type of cancer affecting women, encompasses a collection of histologic (mainly ductal and lobular) and molecular subtypes exhibiting diverse clinical presentation, disease trajectories, treatment options, and outcomes. Immunotherapy has revolutionized treatment for some solid tumors but has shown limited promise for breast cancers. In this review, we summarize recent advances in our understanding of the complex interactions between tumor and immune cells in subtypes of breast cancer at the cellular and microenvironmental levels. We aim to provide a perspective on opportunities for future immunotherapy agents tailored to specific features of each subtype of breast cancer.

SIGNIFICANCE

Although there are currently over 200 ongoing clinical trials testing immunotherapeutics, such as immune-checkpoint blockade agents, these are largely restricted to the triple-negative and HER2+ subtypes and primarily focus on T cells. With the rapid expansion of new in vitro, in vivo, and clinical data, it is critical to identify and highlight the challenges and opportunities unique for each breast cancer subtype to drive the next generation of treatments that harness the immune system.

Computed cancer interactome explains the effects of somatic mutations in cancers

Protein-protein interactions (PPIs) are involved in almost all essential cellular processes. Perturbation of PPI networks plays critical roles in tumorigenesis, cancer progression, and metastasis. While numerous high-throughput experiments have produced a vast amount of data for PPIs, these data sets suffer from high false positive rates and exhibit a high degree of discrepancy. Coevolution of amino acid positions between protein pairs has proven to be useful in identifying interacting proteins and providing structural details of the interaction interfaces with the help of deep learning methods like AlphaFold (AF). In this study, we applied AF to investigate the cancer protein-protein interactome. We predicted 1,798 PPIs for cancer driver proteins involved in diverse cellular processes such as transcription regulation, signal transduction, DNA repair, and cell cycle. We modeled the spatial structures for the predicted binary protein complexes, 1,087 of which lacked previous 3D structure information. Our predictions offer novel structural insight into many cancer-related processes such as the MAP kinase cascade and Fanconi anemia pathway. We further investigated the cancer mutation landscape by mapping somatic missense mutations (SMMs) in cancer to the predicted PPI interfaces and performing enrichment and depletion analyses. Interfaces enriched or depleted with SMMs exhibit different preferences for functional categories. Interfaces enriched in mutations tend to function in pathways that are deregulated in cancers and they may help explain the molecular mechanisms of cancers in patients; interfaces lacking mutations appear to be essential for the survival of cancer cells and thus may be future targets for PPI modulating drugs.

Loss of E-cadherin Induces IGF1R Activation and Reveals a Targetable Pathway in Invasive Lobular Breast Carcinoma

No special-type breast cancer [NST; commonly known as invasive ductal carcinoma (IDC)] and invasive lobular carcinoma (ILC) are the two major histological subtypes of breast cancer with significant differences in clinicopathological and molecular characteristics. The defining pathognomonic feature of ILC is loss of cellular adhesion protein, E-cadherin (CDH1). We have previously shown that E-cadherin functions as a negative regulator of the IGF1R and propose that E-cadherin loss in ILC sensitizes cells to growth factor signaling that thus alters their sensitivity to growth factor-signaling inhibitors and their downstream activators. To investigate this potential therapeutic vulnerability, we generated CRISPR-mediated CDH1 knockout (CDH1 KO) IDC cell lines (MCF7, T47D, and ZR75.1) to uncover the mechanism by which loss of E-cadherin results in IGF pathway activation. CDH1 KO cells demonstrated enhanced invasion and migration that was further elevated in response to IGF1, serum and collagen I. CDH1 KO cells exhibited increased sensitivity to IGF resulting in elevated downstream signaling. Despite minimal differences in membranous IGF1R levels between wild-type (WT) and CDH1 KO cells, significantly higher ligand-receptor interaction was observed in the CDH1 KO cells, potentially conferring enhanced downstream signaling activation. Critically, increased sensitivity to IGF1R, PI3K, Akt, and MEK inhibitors was observed in CDH1 KO cells and ILC patient-derived organoids.

IMPLICATIONS

Overall, this suggests that these targets require further exploration in ILC treatment and that CDH1 loss may be exploited as a biomarker of response for patient stratification.

Current and future diagnostic and treatment strategies for patients with invasive lobular breast cancer

BACKGROUND

Invasive lobular breast cancer (ILC) is the second most common type of breast cancer after invasive breast cancer of no special type (NST), representing up to 15% of all breast cancers.

DESIGN

Latest data on ILC are presented, focusing on diagnosis, molecular make-up according to the European Society for Medical Oncology Scale for Clinical Actionability of molecular Targets (ESCAT) guidelines, treatment in the early and metastatic setting and ILC-focused clinical trials.

RESULTS

At the imaging level, magnetic resonance imaging-based and novel positron emission tomography/computed tomography-based techniques can overcome the limitations of currently used imaging techniques for diagnosing ILC. At the pathology level, E-cadherin immunohistochemistry could help improving inter-pathologist agreement. The majority of patients with ILC do not seem to benefit as much from (neo-)adjuvant chemotherapy as patients with NST, although chemotherapy might be required in a subset of high-risk patients. No differences in treatment efficacy are seen for anti-human epidermal growth factor receptor 2 (HER2) therapies in the adjuvant setting and cyclin-dependent kinases 4 and 6 inhibitors in the metastatic setting. The clinical utility of the commercially available prognostic gene expression-based tests is unclear for patients with ILC. Several ESCAT alterations differ in frequency between ILC and NST. Germline BRCA1 and PALB2 alterations are less frequent in patients with ILC, while germline CDH1 (gene coding for E-cadherin) alterations are more frequent in patients with ILC. Somatic HER2 mutations are more frequent in ILC, especially in metastases (15% ILC versus 5% NST). A high tumour mutational burden, relevant for immune checkpoint inhibition, is more frequent in ILC metastases (16%) than in NST metastases (5%). Tumours with somatic inactivating CDH1 mutations may be vulnerable for treatment with ROS1 inhibitors, a concept currently investigated in early and metastatic ILC.

CONCLUSION

ILC is a unique malignancy based on its pathological and biological features leading to differences in diagnosis as well as in treatment response, resistance and targets as compared to NST.

Loss of E-cadherin leads to Id2-dependent inhibition of cell cycle progression in metastatic lobular breast cancer

Invasive lobular breast carcinoma (ILC) is characterized by proliferative indolence and long-term latency relapses. This study aimed to identify how disseminating ILC cells control the balance between quiescence and cell cycle re-entry. In the absence of anchorage, ILC cells undergo a sustained cell cycle arrest in G0/G1 while maintaining viability. From the genes that are upregulated in anchorage independent ILC cells, we selected Inhibitor of DNA binding 2 (Id2), a mediator of cell cycle progression. Using loss-of-function experiments, we demonstrate that Id2 is essential for anchorage independent survival (anoikis resistance) in vitro and lung colonization in mice. Importantly, we find that under anchorage independent conditions, E-cadherin loss promotes expression of Id2 in multiple mouse and (organotypic) human models of ILC, an event that is caused by a direct p120-catenin/Kaiso-dependent transcriptional de-repression of the canonical Kaiso binding sequence TCCTGCNA. Conversely, stable inducible restoration of E-cadherin expression in the ILC cell line SUM44PE inhibits Id2 expression and anoikis resistance. We show evidence that Id2 accumulates in the cytosol, where it induces a sustained and CDK4/6-dependent G0/G1 cell cycle arrest through interaction with hypo-phosphorylated Rb. Finally, we find that Id2 is indeed enriched in ILC when compared to other breast cancers, and confirm cytosolic Id2 protein expression in primary ILC samples. In sum, we have linked mutational inactivation of E-cadherin to direct inhibition of cell cycle progression. Our work indicates that loss of E-cadherin and subsequent expression of Id2 drive indolence and dissemination of ILC. As such, E-cadherin and Id2 are promising candidates to stratify low and intermediate grade invasive breast cancers for the use of clinical cell cycle intervention drugs.

Unlocking the Mysteries of Lobular Breast Cancer Biology Needs the Right Combination of Preclinical Models

Preclinical model systems are essential research tools that help us understand the biology of invasive lobular carcinoma of the breast (ILC). The number of well-established ILC models are increasing but remain limited. Lower incidence of ILC, under-representation of ILC patients in clinical trials, and intrinsic ILC tumor characteristics all contribute to this challenge. Hence, there is significant need to continually develop better model systems to recapitulate the essential characteristics of ILC biology, genetics, and histology, and empower preclinical therapeutic studies to be translated back into the clinic. In this Perspective, we highlight recent advances in in vivo experimental models, which recapitulate key features of ILC biology and disease progression and potentially reshape the future of ILC translational research. We assert that all existing in vitro and in vivo ILC preclinical models have their strengths and weaknesses, and that it is necessary to bridge key deficiencies in each model context as we move forward with ILC research. Thus, unlocking the mysteries of ILC will be best achieved by choosing the right combination of preclinical model systems.

Impact of lobular versus ductal histology on overall survival in metastatic breast cancer: a French retrospective multicentre cohort study

BACKGROUND

The impact of the histological lobular subtype on overall survival (OS) in metastatic breast cancer (MBC) is still under debate, with very few data available.

PATIENTS AND METHODS

Using the French national multicentre Epidemiological Strategy and Medico Economics [ESME]) data platform, the primary objective was to compare the OS of patients with invasive lobular carcinoma (ILC) versus invasive ductal carcinoma (IDC) MBC, with adjustment on the main prognostic factors using two approaches: multivariable analysis and matching with a propensity score. Secondary objectives were to compare first-line progression-free survival (PFS1) and describe patients and tumour characteristics.

RESULTS

Of the 16,703 patients with MBC in the ESME database, 13,111 met all inclusion criteria for the present analysis. One-thousand eight-hundred and four (13.8%) patients had ILC and 11.307 (86.2%) IDC. In the multivariable analysis, patients with ILC had a worse OS [hazard ratio (HR): 1.31; 95%CI 1.20-1.42; p < 0.0001] and a worse PFS1 (HR: 1.15; 95%CI 1.07-1.22; p < 0.0001) as compared with those with IDC, independently of hormone receptor and HER2 status. Interestingly, OS was better (HR 0.79; 95% confidence interval [CI] 0.64-0.98; p = 0.0302), worse (HR: 1.17; 95%CI 1.08-1.27; p = 0.0001) or similar (HR: 0.88; 95%CI 0.67-1.15; p = 0.3455) in patients with ILC with triple-negative, hormone receptor-positive/HER2-negative and HER2-positive MBC, respectively, compared with patients with IDC.

CONCLUSION

Lobular histology is an independent adverse prognostic factor among women with MBC. ILC MBC could be considered a specific entity. Dedicated prospective studies are needed to tailor the management of these patients.

Exploring the effects of genetic variation on gene regulation in cancer in the context of 3D genome structure

Background

Numerous genome-wide association studies (GWAS) conducted to date revealed genetic variants associated with various diseases, including breast and prostate cancers. Despite the availability of these large-scale data, relatively few variants have been functionally characterized, mainly because the majority of single-nucleotide polymorphisms (SNPs) map to the non-coding regions of the human genome. The functional characterization of these non-coding variants and the identification of their target genes remain challenging.

Results

In this communication, we explore the potential functional mechanisms of non-coding SNPs by integrating GWAS with the high-resolution chromosome conformation capture (Hi-C) data for breast and prostate cancers. We show that more genetic variants map to regulatory elements through the 3D genome structure than the 1D linear genome lacking physical chromatin interactions. Importantly, the association of enhancers, transcription factors, and their target genes with breast and prostate cancers tends to be higher when these regulatory elements are mapped to high-risk SNPs through spatial interactions compared to simply using a linear proximity. Finally, we demonstrate that topologically associating domains (TADs) carrying high-risk SNPs also contain gene regulatory elements whose association with cancer is generally higher than those belonging to control TADs containing no high-risk variants.

Conclusions

Our results suggest that many SNPs may contribute to the cancer development by affecting the expression of certain tumor-related genes through long-range chromatin interactions with gene regulatory elements. Integrating large-scale genetic datasets with the 3D genome structure offers an attractive and unique approach to systematically investigate the functional mechanisms of genetic variants in disease risk and progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01021-x.

Characterisation of the Stromal Microenvironment in Lobular Breast Cancer

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer, and it exhibits a number of clinico-pathological characteristics distinct from the more common invasive ductal carcinoma (IDC). We set out to identify alterations in the tumor microenvironment (TME) of ILC. We used laser-capture microdissection to separate tumor epithelium from stroma in 23 ER+ ILC primary tumors. Gene expression analysis identified 45 genes involved in regulation of the extracellular matrix (ECM) that were enriched in the non-immune stroma of ILC, but not in non-immune stroma from ER+ IDC or normal breast. Of these, 10 were expressed in cancer-associated fibroblasts (CAFs) and were increased in ILC compared to IDC in bulk gene expression datasets, with PAPPA and TIMP2 being associated with better survival in ILC but not IDC. PAPPA, a gene involved in IGF-1 signaling, was the most enriched in the stroma compared to the tumor epithelial compartment in ILC. Analysis of PAPPA- and IGF1-associated genes identified a paracrine signaling pathway, and active PAPP-A was shown to be secreted from primary CAFs. This is the first study to demonstrate molecular differences in the TME between ILC and IDC identifying differences in matrix organization and growth factor signaling pathways.

Clinical outcomes in patients with triple negative or HER2 positive lobular breast cancer: a single institution experience

PURPOSE

Invasive lobular carcinomas (ILC) are characterised by loss of the cell adhesion molecule E-cadherin. Approximately 15% of ILC are ER negative at the time of breast cancer diagnosis, or at relapse due to loss of ER expression. Less than 5% of classical ILC but up to 35% of pleomorphic ILC are HER2 positive (HER2+).

METHODS

Retrospective analysis of clinic-pathological data from patients with Triple negative (TN) or HER2+ ILC diagnosed 2004-2014 at the Royal Marsden Hospital. The primary endpoint was median overall survival (OS) in patients with metastatic disease. Secondary endpoints included response rate to neo-adjuvant chemotherapy (NAC), median disease-free interval (DFI) and OS for patients with early disease.

RESULTS

Three of 16 patients with early TN ILC and 7/33 with early HER2+ ILC received NAC with pCR rates of 0/3 and 3/5 patients who underwent surgery, respectively. Median DFI was 28.5 months [95% Confidence interval (95%CI) 15-78.8] for TN ILC and not reached (NR) (111.2-NR) for HER2+ early ILC. Five-year OS was 52% (95%CI 23-74%) and 77% (95%CI 58-88%), respectively. Twenty-three patients with advanced TN ILC and 14 patients with advanced HER2+ ILC were identified. Median OS was 18.3 months (95%CI 13.0-32.8 months) and 30.4 months (95%CI 8.8-NR), respectively.

CONCLUSIONS

In our institution we report a high relapse rate after treatment for early TN ILC, but median OS from metastatic disease is similar to that expected from TN IDC. Outcomes for patients with advanced HER2+ ILC were less favourable than those expected for IDC, possibly reflecting incomplete exposure to anti-HER2 therapies.

CLINICAL TRIAL REGISTRATION

ROLo (ClinicalTrials.gov Identifier: NCT03620643), ROSALINE (ClinicalTrials.gov Identifier: NCT04551495).

Atlas of Lobular Breast Cancer Models: Challenges and Strategic Directions

Invasive lobular carcinoma (ILC) accounts for up to 15% of all breast cancer (BC) cases and responds well to endocrine treatment when estrogen receptor α-positive (ER+) yet differs in many biological aspects from other ER+ BC subtypes. Up to 30% of patients with ILC will develop late-onset metastatic disease up to ten years after initial tumor diagnosis and may experience failure of systemic therapy. Unfortunately, preclinical models to study ILC progression and predict the efficacy of novel therapeutics are scarce. Here, we review the current advances in ILC modeling, including cell lines and organotypic models, genetically engineered mouse models, and patient-derived xenografts. We also underscore four critical challenges that can be addressed using ILC models: drug resistance, lobular tumor microenvironment, tumor dormancy, and metastasis. Finally, we highlight the advantages of shared experimental ILC resources and provide essential considerations from the perspective of the European Lobular Breast Cancer Consortium (ELBCC), which is devoted to better understanding and translating the molecular cues that underpin ILC to clinical diagnosis and intervention. This review will guide investigators who are considering the implementation of ILC models in their research programs.

Survival analysis in breast cancer using proteomic data from four independent datasets

Breast cancer clinical treatment selection is based on the immunohistochemical determination of four protein biomarkers: ESR1, PGR, HER2, and MKI67. Our aim was to correlate immunohistochemical results to proteome-level technologies in measuring the expression of these markers. We also aimed to integrate available proteome-level breast cancer datasets to identify and validate new prognostic biomarker candidates. We searched studies involving breast cancer patient cohorts with published survival and proteomic information. Immunohistochemistry and proteomic technologies were compared using the Mann-Whitney test. Receiver operating characteristics (ROC) curves were generated to validate discriminative power. Cox regression and Kaplan-Meier survival analysis were calculated to assess prognostic power. False Discovery Rate was computed to correct for multiple hypothesis testing. We established a database integrating protein expression data and survival information from four independent cohorts for 1229 breast cancer patients. In all four studies combined, a total of 7342 unique proteins were identified, and 1417 of these were identified in at least three datasets. ESR1, PGR, and HER2 protein expression levels determined by RPPA or LC-MS/MS methods showed a significant correlation with the levels determined by immunohistochemistry (p < 0.0001). PGR and ESR1 levels showed a moderate correlation (correlation coefficient = 0.17, p = 0.0399). An additional panel of candidate proteins, including apoptosis-related proteins (BCL2,), adhesion markers (CDH1, CLDN3, CLDN7) and basal markers (cytokeratins), were validated as prognostic biomarkers. Finally, we expanded our previously established web tool designed to validate survival-associated biomarkers by including the proteomic datasets analyzed in this study ( https://kmplot.com/ ). In summary, large proteomic studies now provide sufficient data enabling the validation and ranking of potential protein biomarkers.

The Genomic Landscape of Lobular Breast Cancer

Invasive lobular carcinoma (ILC) is the second most common breast cancer histologic subtype, accounting for approximately 15% of all breast cancers. It is only recently that its unique biology has been assessed in high resolution. Here, we present a meta-analysis of ILC sequencing datasets, to provide a long-awaited ILC-specific resource, and to confirm the prognostic value and strength of association between a number of clinico-pathology features and genomics in this special tumour type. We consider panel (n = 684), whole exome (n = 215) and whole genome sequencing data (n = 48), and review histology of The Cancer Genome Atlas cases to assign grades and determine whether the ILC is of classic type or a variant, such as pleomorphic, prior to performing statistical analyses. We demonstrate evidence of considerable genomic heterogeneity underlying a broadly homogeneous tumour type (typically grade 2, estrogen receptor (ER)-positive); with genomes exhibiting few somatic mutations or structural alterations, genomes with a hypermutator phenotype, and tumours with highly rearranged genomes. We show that while CDH1 (E-cadherin) and PIK3CA mutations do not significantly impact survival, overall survival is significantly poorer for patients with a higher tumour mutation burden; this is also true for grade 3 tumours, and those carrying a somatic TP53 mutation (and these cases were more likely to be ER-negative). Taken together, we have compiled a meta-dataset of ILC with molecular profiling, and our analyses show that the genomic landscape significantly impacts the tumour's variable natural history and overall survival of ILC patients.

Invasive Lobular Carcinoma of the Breast: Ongoing Trials, Challenges, and Future Directions

Purpose of Review

Invasive lobular carcinoma (ILC) is increasingly recognized as a distinct subtype of breast cancer with unique management challenges. We reviewed currently available clinical trials for patients with ILC.

Recent Findings

We describe the rationale for and study design of clinical trials for patients with both early stage and metastatic ILC. Molecular alterations specific to or enriched in ILC may serve as treatment targets.

Summary

ILC has specific features that may be treatment targets. Clinical trials for ILC are available and being developed.

Aberrations of Chromosomes 1 and 16 in Breast Cancer: A Framework for Cooperation of Transcriptionally Dysregulated Genes

Derivative chromosome der(1;16), isochromosome 1q, and deleted 16q-producing arm-level 1q-gain and/or 16q-loss-are recurrent cytogenetic abnormalities in breast cancer, but their exact role in determining the malignant phenotype is still largely unknown. We exploited The Cancer Genome Atlas (TCGA) data to generate and analyze groups of breast invasive carcinomas, called 1,16-chromogroups, that are characterized by a pattern of arm-level somatic copy number aberrations congruent with known cytogenetic aberrations of chromosome 1 and 16. Substantial differences were found among 1,16-chromogroups in terms of other chromosomal aberrations, aneuploidy scores, transcriptomic data, single-point mutations, histotypes, and molecular subtypes. Breast cancers with a co-occurrence of 1q-gain and 16q-loss can be distinguished in a "low aneuploidy score" group, congruent to der(1;16), and a "high aneuploidy score" group, congruent to the co-occurrence of isochromosome 1q and deleted 16q. Another three groups are formed by cancers showing separately 1q-gain or 16q-loss or no aberrations of 1q and 16q. Transcriptome comparisons among the 1,16-chromogroups, integrated with functional pathway analysis, suggested the cooperation of overexpressed 1q genes and underexpressed 16q genes in the genesis of both ductal and lobular carcinomas, thus highlighting the putative role of genes encoding gamma-secretase subunits (APH1A, PSEN2, and NCSTN) and Wnt enhanceosome components (BCL9 and PYGO2) in 1q, and the glycoprotein E-cadherin (CDH1), the E3 ubiquitin-protein ligase WWP2, the deubiquitinating enzyme CYLD, and the transcription factor CBFB in 16q. The analysis of 1,16-chromogroups is a strategy with far-reaching implications for the selection of cancer cell models and novel experimental therapies.

Comprehensive Review of Molecular Mechanisms and Clinical Features of Invasive Lobular Cancer

Invasive lobular carcinoma (ILC) accounts for 10% to 15% of breast cancers in the United States, 80% of which are estrogen receptor (ER)-positive, with an unusual metastatic pattern of spread to sites such as the serosa, meninges, and ovaries, among others. Lobular cancer presents significant challenges in detection and clinical management given its multifocality and multicentricity at presentation. Despite the unique features of ILC, it is often lumped with hormone receptor-positive invasive ductal cancers (IDC); consequently, ILC screening, treatment, and follow-up strategies are largely based on data from IDC. Despite both being treated as ER-positive breast cancer, querying the Cancer Genome Atlas database shows distinctive molecular aberrations in ILC compared with IDC, such as E-cadherin loss (66% vs. 3%), FOXA1 mutations (7% vs. 2%), and GATA3 mutations (5% vs. 20%). Moreover, compared with patients with IDC, patients with ILC are less likely to undergo breast-conserving surgery, with lower rates of complete response following therapy as these tumors are less chemosensitive. Taken together, this suggests that ILC is biologically distinct, which may influence tumorigenesis and therapeutic strategies. Long-term survival and clinical outcomes in patients with ILC are worse than in stage- and grade-matched patients with IDC; therefore, nuanced criteria are needed to better define treatment goals and protocols tailored to ILC's unique biology. This comprehensive review highlights the histologic and clinicopathologic features that distinguish ILC from IDC, with an in-depth discussion of ILC's molecular alterations and biomarkers, clinical trials and treatment strategies, and future targets for therapy. IMPLICATIONS FOR PRACTICE: The majority of invasive lobular breast cancers (ILCs) are hormone receptor (HR)-positive and low grade. Clinically, ILC is treated similar to HR-positive invasive ductal cancer (IDC). However, ILC differs distinctly from IDC in its clinicopathologic characteristics and molecular alterations. ILC also differs in response to systemic therapy, with studies showing ILC as less sensitive to chemotherapy. Patients with ILC have worse clinical outcomes with late recurrences. Despite these differences, clinical trials treat HR-positive breast cancers as a single disease, and there is an unmet need for studies addressing the unique challenges faced by patients diagnosed with ILC.

Invasive pleomorphic lobular carcinoma of the breast with multiple metastases: A case report

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Invasive Pleomorphic Lobular Carcinoma(IPLC) accounts for less than 1% of breast cancer.

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This paper reports a case of IPLC with multiple metastases and gives review literature.

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The patient’s general condition improved after our specific treatment options, which has a certain reference for the treatment of this kind of patients in the future.

Introduction and importance

IPLC (Invasive Pleomorphic Lobular Carcinoma) accounts for less than 1% of breast cancer. To the best of our knowledge, this is one of the few reported cases in the IPLC with multiple metastases. The patient's general condition got improved after our treatment, which has a certain reference for the treatment of this kind of patient in the future.

Case presentation

A 42-year-old female with IPLC and multiple metastases. The IPLC malignant cells were positive for p120 (cytoplasmic) and human epidermal growth factor receptor 2, negative for estrogen receptor, progesterone receptor, and E-cadherin. There were nodular enhancement foci in the liver, which are considered the metastatic lesions of the breast, and the liver function was abnormal. Multiple metastatic lesions of the vertebral body, appendage of the whole spine, and sternum. And C7, T1, and T9 vertebrae showed compression fractures.

Clinical discussion

IPLC has systemic metastasis which molecular typing by immunohistochemistry is HER-2 overexpression can choose chemotherapy combined with targeted therapy to prolong the survival time and improve the quality of life of patients. The patient was followed up.

Conclusions

This paper reports a case of IPLC with multiple metastases and gives review literature. Our treatment of the patient can be a reference for other clinicians.

Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis

While cost-effective high-throughput technologies provide an increasing amount of data, the analyses of single layers of data seldom provide causal relations. Multi-omics data integration strategies across different cellular function levels, including genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes offer unparalleled opportunities to understand the underlying biology of complex diseases, such as cancer. We review some of the most frequently used data integration methods and outline research areas where multi-omics significantly benefit our understanding of the process and outcome of the malignant transformation. We discuss algorithmic frameworks developed to reveal cancer subtypes, disease mechanisms, and methods for identifying driver genomic alterations and consider the significance of multi-omics in tumor classifications, diagnostics, and prognostications. We provide a comprehensive summary of each omics strategy's most recent advances within the clinical context and discuss the main challenges facing their clinical implementations. Despite its unparalleled advantages, multi-omics data integration is slow to enter everyday clinics. One major obstacle is the uneven maturity of different omics approaches and the growing gap between generating large volumes of data compared to data processing capacity. Progressive initiatives to enforce the standardization of sample processing and analytical pipelines, multidisciplinary training of experts for data analysis and interpretation are vital to facilitate the translatability of theoretical findings.

Invasive lobular carcinoma of the breast: the increasing importance of this special subtype

Invasive lobular carcinoma (ILC) is the most common of the breast cancer special types, accounting for up to 15% of all breast cancer cases. ILCs are noted for their lack of E-cadherin function, which underpins their characteristic discohesive growth pattern, with cells arranged in single file and dispersed throughout the stroma. Typically, tumours are luminal in molecular subtype, being oestrogen and progesterone receptor positive, and HER2 negative. Since last reviewing the lobular literature (McCart Reed et al., Breast Cancer Res 17:12, 2015), there has been a considerable increase in research output focused on this tumour type, including studies into the pathology and management of disease, a high-resolution definition of the genomic landscape of tumours as well as the evolution of several potential therapeutic avenues. There abounds a huge amount of new data, which we will review herein.

Progesterone Receptor Signaling in the Breast Tumor Microenvironment

The tumor microenvironment (TME) is a complex infrastructure composed of stromal, epithelial, and immune cells embedded in a vasculature ECM. The microenvironment surrounding mammary epithelium plays a critical role during the development and differentiation of the mammary gland, enabling the coordination of the complex multihormones and growth factor signaling processes. Progesterone/progesterone receptor paracrine signaling interactions in the microenvironment play vital roles in stem/progenitor cell function during normal breast development. In breast cancer, the female sex hormones, estrogen and progesterone, and growth factor signals are altered in the TME. Progesterone signaling modulates not only breast tumors but also the breast TME, leading to the activation of a series of cross-communications that are implicated in the genesis of breast cancers. This chapter reviews the evidence that progesterone and PR signaling modulates not only breast epitheliums but also the breast TME. Furthermore, crosstalk between estrogen and progesterone signaling affecting different cell types within the TME is discussed. A better understanding of how PR and progesterone affect the TME of breast cancer may lead to novel drugs or a therapeutic approach for the treatment of breast cancer shortly.