Prognostic significance of nucleolar assessment in invasive breast cancer

Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review

Advancements in digital pathology and computing resources have made a significant impact in the field of computational pathology for breast cancer diagnosis and treatment. However, access to high-quality labeled histopathological images of breast cancer is a big challenge that limits the development of accurate and robust deep learning models. In this scoping review, we identified the publicly available datasets of breast H&E-stained whole-slide images (WSIs) that can be used to develop deep learning algorithms. We systematically searched 9 scientific literature databases and 9 research data repositories and found 17 publicly available datasets containing 10 385 H&E WSIs of breast cancer. Moreover, we reported image metadata and characteristics for each dataset to assist researchers in selecting proper datasets for specific tasks in breast cancer computational pathology. In addition, we compiled 2 lists of breast H&E patches and private datasets as supplementary resources for researchers. Notably, only 28% of the included articles utilized multiple datasets, and only 14% used an external validation set, suggesting that the performance of other developed models may be susceptible to overestimation. The TCGA-BRCA was used in 52% of the selected studies. This dataset has a considerable selection bias that can impact the robustness and generalizability of the trained algorithms. There is also a lack of consistent metadata reporting of breast WSI datasets that can be an issue in developing accurate deep learning models, indicating the necessity of establishing explicit guidelines for documenting breast WSI dataset characteristics and metadata.

Exploring the multifaceted impact of lanthanides on physiological pathways in human breast cancer cells

Lanthanum (La) and cerium (Ce), rare earth elements with physical properties similar to calcium (Ca), are generally considered non-toxic when used appropriately. However, their ions possess anti-tumor capabilities. This investigation explores the potential applications and mechanisms of LaCl3 or CeCl3 treatment in triple-negative breast cancer (TNBC) cell lines. TNBC, characterized by the absence of estrogen receptor (ERα), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) expression, is prone to early metastasis and resistant to hormone therapy. Our results demonstrate that La/Ce treatment reduces cell growth, and when combined with cisplatin, it synergistically inhibits cell growth and the PI3K/AKT pathway. La and Ce induce oxidative stress by disrupting mitochondrial function, leading to protein oxidation. Additionally, they interfere with protein homeostasis and induce nucleolar stress. Furthermore, disturbance in F-actin web formation impairs cell migration. This study delves into the mechanism by which calcium-like elements La and Ce inhibit breast cancer cell growth, shedding light on their interference in mitochondrial function, protein homeostasis, and cytoskeleton assembly.

Expanding the toolset of fluorescent covalent staining of biological samples by labeling carboxylate and phosphate groups

Recently, fluorescent covalent staining methods have been developed for visualization of anatomical structures in cells and tissues. Coupled with expansion microscopy, these stains revealed various ultrastructural details. However, the covalently stainable chemical groups have been limited to amines, carbohydrates, and thiols. Here, we developed procedures for covalently labeling tissues for carboxylate and phosphate groups, utilizing carbodiimide crosslinker chemistry. In porcine kidney tissues, the carboxylate and phosphate stain provides 1.8-4.8-fold higher signal intensity than those from the three existing stains. In cancer cells, such stain allows 2-8-fold more accurate identification of nucleoli than the amine stain. In expansion microscopy samples, such stain reveals a variety of sub-cellular structures in tissues when combined with the amine stain. Such stain also allows imaging of lipid-based structures in cultured cells. With these advantages, this new covalent staining method further expands the toolset for fluorescent visualization of histology.

Ribosome biosynthesis and Hedgehog activity are cooperative actionable signaling mechanisms in breast cancer following radiotherapy

Hyperactivated ribosome biosynthesis is attributed to a need for elevated protein synthesis that accommodates cell growth and division, and is characterized by nucleomorphometric alterations and increased nucleolar counts. Ribosome biogenesis is challenged when DNA-damaging treatments such as radiotherapy are utilized. Tumor cells that survive radiotherapy form the basis of recurrence, tumor progression, and metastasis. In order to survive and become metabolically revitalized, tumor cells need to reactivate RNA Polymerase I (RNA Pol I) to synthesize ribosomal RNA, an integral component of ribosomes. In this study, we showed that following radiation therapy, tumor cells from breast cancer patients demonstrate activation of a ribosome biosynthesis signature concurrent with enrichment of a signature of Hedgehog (Hh) activity. We hypothesized that GLI1 activates RNA Pol I in response to irradiation and licenses the emergence of a radioresistant tumor population. Our work establishes a novel role for GLI1 in orchestrating RNA Pol I activity in irradiated breast cancer cells. Furthermore, we present evidence that in these irradiated tumor cells, Treacle ribosome biogenesis factor 1 (TCOF1), a nucleolar protein that is important in ribosome biogenesis, facilitates nucleolar translocation of GLI1. Inhibiting Hh activity and RNA Pol I activity disabled the outgrowth of breast cancer cells in the lungs. As such, ribosome biosynthesis and Hh activity present as actionable signaling mechanisms to enhance the effectiveness of radiotherapy.

Krüppel-like factor 7 influences translation and pathways involved in ribosomal biogenesis in breast cancer

Background

Ribosomal biogenesis and ribosomal proteins have attracted attention in the context of tumor biology in recent years. Instead of being mere translational machineries, ribosomes might play an active role in tumor initiation and progression. Despite its importance, regulation of ribosomal biogenesis is still not completely understood.

Methods

Using Gene Set Enrichment Analysis of RNA sequencing and proteomical mass spectrometry data in breast cancer cells expressing Krüppel-like factor 7 (KLF7), we identified processes altered by this transcription factor. In silico analyses of a cohort of breast cancer patients in The Cancer Genome Atlas confirmed our finding. We further verified the role of KLF7 the identified ribosomal processes in in vitro assays of mammary carcinoma cell lines and analyses of breast cancer patients’ tissue slices.

Results

We identified the transcription factor Krüppel-like factor 7 (KLF7) as a regulator of ribosomal biogenesis and translation in breast cancer cells and tissue. Highly significant overlapping processes related to ribosomal biogenesis were identified in proteomics and transcriptomics data and confirmed in patients’ breast cancer RNA Seq data. Further, nucleoli, the sites of ribosomal biogenesis, were morphologically altered and quantitatively increased in KLF7-expressing cells. Pre-rRNA processing was identified as one potential process affected by KLF7. In addition, an increase in global translation independent from proliferation and transcription was observed upon exogenous KLF7 expression in vitro. Importantly, in a cohort of breast cancer patients, KLF7-expression levels correlated with aggressiveness of the intrinsic breast cancer subtype and tumor grading. Moreover, KLF7 correlated with nucleolar characteristics in human breast tumor tissue, indicating a role for KLF7 in ribosomal biogenesis.

Conclusion

In mammary carcinoma, KLF7 is involved in ribosomal biogenesis. Alterations of ribosomal biogenesis has far reaching quantitative and qualitative implications for the proteome of the cancer cells. This might influence the aggressiveness of cancer cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01562-8.

Salivary Gland Polymorphous Adenocarcinoma: Clinicopathological Features and Gene Alterations in 36 Japanese Patients

OBJECTIVES

Polymorphous adenocarcinoma (PAC) is a common intraoral minor salivary gland carcinoma in Western countries but is extremely rare in Japan. The current study aimed to characterize the clinicopathological features and status of molecular alterations of PAC-associated genes, such as (e.g., PRKD1/2/3, ARID1A, and DDX3X) in a large cohort of Japanese patients with PAC.

MATERIALS AND METHODS

We examined the cases of 36 Japanese patients with salivary gland PAC and 26 cases involving histopathological mimics. To detect gene splits, fluorescence in situ hybridization was carried out for PAC-associated genes. Additionally, we applied a SNaPshot multiplex assay to identify PRKD1 hotspot mutations.

RESULTS

This study revealed the indolent clinical course of PAC with a high 10-year overall survival rate (92.9%), accompanied by occasional local recurrences and cervical lymph node metastasis (both 23.3%). Twenty cases (55.6%) of PAC (but none of the mimics) exhibited alterations in at least one PAC-associated gene. Rearrangement of PAC-associated genes and PRKD1 E710D were identified in 17 (47.2%) and 4 (11.1%) cases, respectively; one case showed coexisting PRKD3 split and PRKD1 E710D. In the multivariate analysis, high clinical stage (P=0.0005), the presence of prominent nucleoli (P=0.0003), and ARID1A split positivity (P=0.004) were independent risk factors for disease-free survival.

CONCLUSION

Japanese patients with PAC showed clinicopathological features similar to those reported in Western countries. This study disclosed that PAC-associated genetic alterations were common and specific findings in PACs. The diagnostic role and possible prognostic significance of PAC-associated genetic alterations in PACs were suggested.

Artificial intelligence grading of breast cancer: a promising method to refine prognostic classification for management precision

AIM

Artificial intelligence (AI)-based breast cancer grading may help to overcome perceived limitations of human assessment. Here, the potential value of AI grade was evaluated at the molecular level and in predicting patient outcome.

METHODS AND RESULTS

A supervised convolutional neural network (CNN) model was trained on images of 612 breast cancers from The Cancer Genome Atlas (TCGA). The test set, obtained from the Cooperative Human Tissue Network (CHTN), comprised 1058 cancers with corresponding survival data. Upon reversal, a CNN was trained from images of 1537 CHTN cancers and tested on 397 TCGA cancers. In TCGA, mRNA models were trained using AI grade and Nottingham grade (NG) as labels. Performance of mRNA models in predicting patient outcome was evaluated using data from 1807 cancers from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. In selecting images for training, nucleolar prominence determined high- versus low-grade cancer cells. In CHTN, NG corresponded to significant survival stratification in stages 1, 2 and 3 cancers, while AI grade showed significance in stages 1 and 2 and borderline in stage 3 tumours. In METABRIC, the mRNA model trained from AI grade was not significantly different to the NG-based model. The gene which best described AI grade was TRIP13, a gene involved with mitotic spindle assembly.

CONCLUSION

An AI grade trained from the morphologically distinctive feature of nucleolar prominence could transmit significant patient outcome information across three independent patient cohorts. AI grade shows promise in gene discovery and for second opinions.

Ribosomal RNA Transcription Regulation in Breast Cancer

Ribosome biogenesis is a complex process that is responsible for the formation of ribosomes and ultimately global protein synthesis. The first step in this process is the synthesis of the ribosomal RNA in the nucleolus, transcribed by RNA Polymerase I. Historically, abnormal nucleolar structure is indicative of poor cancer prognoses. In recent years, it has been shown that ribosome biogenesis, and rDNA transcription in particular, is dysregulated in cancer cells. Coupled with advancements in screening technology that allowed for the discovery of novel drugs targeting RNA Polymerase I, this transcriptional machinery is an increasingly viable target for cancer therapies. In this review, we discuss ribosome biogenesis in breast cancer and the different cellular pathways involved. Moreover, we discuss current therapeutics that have been found to affect rDNA transcription and more novel drugs that target rDNA transcription machinery as a promising avenue for breast cancer treatment.

Nucleolar protein 10 (NOP10) predicts poor prognosis in invasive breast cancer

Purpose

Nucleolar protein 10 (NOP10) is required for ribosome biogenesis and telomere maintenance and plays a key role in carcinogenesis. This study aims to evaluate the clinical and prognostic significance of NOP10 in breast cancer (BC).

Methods

NOP10 expression was assessed at mRNA level employing the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (n = 1980) and Cancer Genome Atlas (TCGA) BC cohorts (n = 854). Protein expression was evaluated on tissue microarray of a large BC cohort (n = 1081) using immunohistochemistry. The correlation between NOP10 expression, clinicopathological parameters and patient outcome was assessed.

Results

NOP10 expression was detected in the nucleus and nucleolus of the tumour cells. At the transcriptomic and proteomic levels, NOP10 was significantly associated with aggressive BC features including high tumour grade, high nucleolar score and poor Nottingham Prognostic Index. High NOP10 protein expression was an independent predictor of poor outcome in the whole cohort and in triple-negative BC (TNBC) class (p = 0.002 & p = 0.014, respectively). In chemotherapy- treated patients, high NOP10 protein expression was significantly associated with shorter survival (p = 0.03) and was predictive of higher risk of death (p = 0.028) and development of distant metastasis (p = 0.02) independent of tumour size, nodal stage and tumour grade.

Conclusion

High NOP10 expression is a poor prognostic biomarker in BC and its expression can help in predicting chemotherapy resistance. Functional assessments are necessary to decipher the underlying mechanisms and to reveal its potential therapeutic values in various BC subtypes especially in the aggressive TNBC class.

Electronic supplementary material

The online version of this article (doi:10.1007/s10549-020-05999-3) contains supplementary material, which is available to authorized users.

The nucleolar-related protein Dyskerin pseudouridine synthase 1 (DKC1) predicts poor prognosis in breast cancer

BACKGROUND

Hypertrophy of the nucleolus is a distinctive cytological feature of malignant cells and corresponds to aggressive behaviour. This study aimed to identify the key gene associated with nucleolar prominence (NP) in breast cancer (BC) and determine its prognostic significance.

METHODS

From The Cancer Genome Atlas (TCGA) cohort, digital whole slide images identified cancers having NP served as label and an information theory algorithm was applied to find which mRNA gene best explained NP. Dyskerin Pseudouridine Synthase 1 (DKC1) was identified. DKC1 expression was assessed using mRNA data of Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1980) and TCGA (n = 855). DKC1 protein expression was assessed using immunohistochemistry in Nottingham BC cohort (n = 943).

RESULTS

Nuclear and nucleolar expressions of DKC1 protein were significantly associated with higher tumour grade (p < 0.0001), high nucleolar score (p < 0.001) and poor Nottingham Prognostic Index (p < 0.0001). High DKC1 expression was associated with shorter BC-specific survival (BCSS). In multivariate analysis, DKC1 mRNA and protein expressions were independent risk factors for BCSS (p < 0.01).

CONCLUSION

DKC1 expression is strongly correlated with NP and its overexpression in BC is associated with unfavourable clinicopathological characteristics and poor outcome. This has been a detailed example in the correlation of phenotype with genotype.

Tumor-infiltrating lymphocytes are associated with poor prognosis in invasive lobular breast carcinoma

The prognostic impact of tumor-infiltrating lymphocytes (TILs) within invasive lobular carcinoma (ILC) remains to be better characterized. In estrogen receptor (ER)-negative invasive ductal carcinomas of no special type (IDC-NST), TILs are associated with good prognosis. The aim of this study was to examine TILs in ILC, with particular focus on prognostic and clinicopathologic features. A cohort comprising 459 consecutive ILCs diagnosed in a single institution from 2005 to 2008 met the eligibility criteria for this study. The percentage of tumor area occupied by TILs was quantified by two breast pathologists and categorized into three groups: no TILs, ≤5%, >5%. Clinicopathologic features were tested by Fisher's exact tests or Chi² tests. Overall survival (OS) and invasive disease-free survival (iDFS) were estimated by Kaplan-Meier and Cox proportional hazard statistics. There were 239 TIL-negative cases, 185 cases with ≤5% TILs, and 35 cases with >5% TILs. TILs were associated with younger age, larger tumors, lymph node involvement, poor Nottingham prognostic index, HER2 amplification, multinucleation, and prominent nucleoli (p < 0.05). Poor OS was significantly associated with increasing TILs in the univariate Cox proportional hazards model (p < 0.001) and Kaplan-Meier estimator (p < 0.05, log-rank test). Similar results were observed for iDFS (p = 0.004 for Cox univariate and p = 0.005 for log-rank test). Notably, TILs can identify a subset of ILC patients with poor OS independently of molecular subtype and lymph node metastases (multivariate Cox, p < 0.001, OS hazard ratio (HR) = 4.38 and HR = 6.15, for ≤5% and >5% TILs, respectively, vs. absence of TILs). Prominent nucleoli was the only nuclear feature associated with poor OS (p = 0.05) and iDFS (p = 0.05) in univariate Cox survival analysis. TILs represent a promising new morphologic biomarker associated with poor outcome of ILC, in contrast with that observed in ER-negative IDC-NST.

Visual histological assessment of morphological features reflects the underlying molecular profile in invasive breast cancer: a morphomolecular study

AIMS

Tumour genotype and phenotype are related and can predict outcome. In this study, we hypothesised that the visual assessment of breast cancer (BC) morphological features can provide valuable insight into underlying molecular profiles.

METHODS AND RESULTS

The Cancer Genome Atlas (TCGA) BC cohort was used (n = 743) and morphological features, including Nottingham grade and its components and nucleolar prominence, were assessed utilising whole-slide images (WSIs). Two independent scores were assigned, and discordant cases were utilised to represent cases with intermediate morphological features. Differentially expressed genes (DEGs) were identified for each feature, compared among concordant/discordant cases and tested for specific pathways. Concordant grading was observed in 467 of 743 (63%) of cases. Among concordant case groups, eight common DEGs (UGT8, DDC, RGR, RLBP1, SPRR1B, CXorf49B, PSAPL1 and SPRR2G) were associated with overall tumour grade and its components. These genes are related mainly to cellular proliferation, differentiation and metabolism. The number of DEGs in cases with discordant grading was larger than those identified in concordant cases. The largest number of DEGs was observed in discordant grade 1:3 cases (n = 1185). DEGs were identified for each discordant component. Some DEGs were uniquely associated with well-defined specific morphological features, whereas expression/co-expression of other genes was identified across multiple features and underlined intermediate morphological features.

CONCLUSION

Morphological features are probably related to distinct underlying molecular profiles that drive both morphology and behaviour. This study provides further evidence to support the use of image-based analysis of WSIs, including artificial intelligence algorithms, to predict tumour molecular profiles and outcome.