RSK1 promotes murine breast cancer growth and metastasis

Introduction. Triple-negative breast cancer (TNBC), representing over 15% of all breast cancers, has a poorerprognosis than other subtypes. There is no effective targeted treatment available for the TNBC sufferers. Ribosomal S6 kinases (RSKs) have been previously proposed as drug targets for TNBC based on observations that 85% of these tumors express activated RSKs.Materials and methods. Herein we examined an involvement of RSK1 (p90 ribosomal S6 kinase 1) in a regulation of TNBC growth and metastatic spread in an animal model, which closely imitates human disease. Micewere inoculated into mammary fat pad with 4T1 cells or their RSK1-depleted variant. We examined tumorgrowth and formation of pulmonary metastasis. Boyden chamber, wound healing and soft agarose assays wereperformed to evaluate cells invasion, migration and anchorage-independent growth.Results. We found that RSK1 promoted tumor growth and metastasis in vivo. After 35 days all animals inoculatedwith control cells developed tumors while in the group injected with RSK1-negative cells, there were 75%tumor-bearing mice. Average tumor mass was estimated as 1.16 g and 0.37 g for RSK1-positive vs. -negativesamples, respectively (p < 0.0001). Quantification of the macroscopic pulmonary metastases indicated that micewith RSK1-negative tumors developed approximately 85% less metastatic foci on the lung surface (p < 0.001).This has been supported by in vitro data presenting that RSK1 promoted anchorage-independent cell growthand migration. Moreover, RSK1 knock-down corresponded with decreased expression of cell cycle regulatingproteins, i.e. cyclin D3, CDK6 and CDK4.Conclusions. We provide evidence that RSK1 supports tumor growth and metastatic spread in vivo as well asin vitro migration and survival in non-adherent conditions. Further studies of RSK1 involvement in TNBC progression may substantiate our findings, laying the foundations for development of anti-RSK1-based therapeuticstrategies in the management of patients with TNBC

Reduced expression of innate immunity-related genes in lymph node metastases of luminal breast cancer patients

Immune system plays a dual role in cancer by either targeting or supporting neoplastic cells at various stages of disease, including metastasis. Yet, the exact immune-related transcriptome profiles of primary tumours (PT) and lymph node metastases (LNM) and their evolution during luminal breast cancer (BCa) dissemination remain undiscovered. In order to identify the immune-related transcriptome changes that accompany lymphatic spread, we analysed PT-LNM pairs of luminal BCa using NanoString technology. Decrease in complement C3—one of the top-downregulated genes, in LNM was validated at the protein level using immunohistochemistry. Thirty-three of 360 analysed genes were downregulated (9%), whereas only 3 (0.8%) upregulated in LNM when compared to the corresponding PT. In LNM, reduced expression was observed in genes related to innate immunity, particularly to the complement system (C1QB, C1S, C1R, C4B, CFB, C3, SERPING1 and C3AR1). In validation cohort, complement C3 protein was less frequently expressed in LNM than in PT and it was associated with worse prognosis. To conclude, local expression of the complement system components declines during lymphatic spread of non-metastatic luminal BCa, whilst further reduction of tumoral complement C3 in LNM is indicative for poor survival. This points to context-dependent role of complement C3 in BCa dissemination.publishedVersio

Spectrum of Epithelial-Mesenchymal Transition Phenotypes in Circulating Tumour Cells from Early Breast Cancer Patients

Circulating tumour cells (CTCs) can provide valuable prognostic information in a number of epithelial cancers. However, their detection is hampered due to their molecular heterogeneity, which can be induced by the epithelial-mesenchymal transition (EMT) process. Therefore, current knowledge about CTCs from clinical samples is often limited due to an inability to isolate wide spectrum of CTCs phenotypes. In the current work, we aimed at isolation and molecular characterization of CTCs with different EMT status in order to establish their clinical significance in early breast cancer patients. We have obtained CTCs-enriched blood fraction from 83 breast cancer patients in which we have tested the expression of epithelial, mesenchymal and general breast cancer CTCs markers (MGB1/HER2/CK19/CDH1/CDH2/VIM/PLS3), cancer stem cell markers (CD44, NANOG, ALDH1, OCT-4, CD133) and cluster formation gene (plakoglobin). We have shown that in the CTCs-positive patients, epithelial, epithelial-mesenchymal and mesenchymal CTCs markers were detected at a similar rate (in 28%, 24% and 24%, respectively). Mesenchymal CTCs were characterized by the most aggressive phenotype (significantly higher expression of CXCR4, uPAR, CD44, NANOG, p < 0.05 for all), presence of lymph node metastases (p = 0.043), larger tumour size (p = 0.023) and 7.33 higher risk of death in the multivariate analysis (95% CI 1.06–50.41, p = 0.04). Epithelial-mesenchymal subtype, believed to correspond to highly plastic and aggressive state, did not show significant impact on survival. Gene expression profile of samples with epithelial-mesenchymal CTCs group resembled pure epithelial or pure mesenchymal phenotypes, possibly underlining degree of EMT activation in particular patient’s sample. Molecular profiling of CTCs EMT phenotype provides more detailed and clinically informative results, proving the role of EMT in malignant cancer progression in early breast cancer

Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data

The field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and therapy personalization. This study presents a multiclass approach based on deep learning to analyze and classify diseases based on blood platelet RNA. Its primary objective is to enhance cancer-type diagnosis in clinical settings by leveraging the power of deep learning combined with high-throughput sequencing of liquid biopsy. Ultimately, the study demonstrates the potential of this approach to accurately identify the patient’s type of cancer. Methods: The developed method classifies patients using heatmap images, generated based on gene expression arranged according to the Kyoto Encyclopedia of Genes and Genomes pathways. The images represent samples of patients with ovarian cancer, endometrial cancer, glioblastoma, non-small cell lung cancer, and sarcoma, as well as cancer patients with brain metastasis. Results: Our deep learning-based models reached 66.51% balanced accuracy when distinguishing between those 6 sites of cancer origin and 90.5% balanced accuracy on a location-specific dataset where cancer types from close locations were grouped. The developed models were further investigated with an explainable artificial intelligence-based approach (XAI) - SHAP. They returned a set of 60 genes with the highest impact on the models’ decision-making process. Conclusions: Our results show that deep-learning methods are a promising opportunity for cancer detection and could support clinicians’ decision-making process in finding the solution for the black-box problem. Clinical and Translational Impact Statement— Utilizing TEPs-based liquid biopsies and deep learning, our study offers a novel approach to early cancer detection, highlighting cancer origin. The integration of Explainable AI reinforces trust in predictive outcomes. Category: Early/Pre-Clinical Research

ERα36-High Cancer-Associated Fibroblasts as an Unfavorable Factor in Triple-Negative Breast Cancer

Background: Cancer-associated fibroblasts (CAFs) are the most abundant cell type in the tumor microenvironment (TME). Estrogen receptor alpha 36 (ERα36), the alternatively spliced variant of ERα, is described as an unfavorable factor when expressed in cancer cells. ERα can be expressed also in CAFs; however, the role of ERα36 in CAFs is unknown. Methods: Four CAF cultures were isolated from chemotherapy-naïve BC patients and characterized for ERα36 expression and the NanoString gene expression panel using isolated RNA. Conditioned media from CAF cultures were used to assess the influence of CAFs on triple-negative breast cancer (TNBC) cells using a matrigel 3D culture assay. Results: We found that ERα36high CAFs significantly induced the branching of TNBC cells in vitro (p low CAFs, among which hepatocyte growth factor (HGF) was the main inducer of TNBC cell invasive phenotype in vitro (p high CAFs was correlated with high Ki67 expression (p = 0.041) and tumor-associated macrophages markers (CD68 and CD163, p = 0.041 for both). HGF was found to be an unfavorable prognostic factor in TCGA database analysis (p = 0.03 for DFS and p = 0.04 for OS). Conclusions: Breast cancer-associated fibroblasts represent distinct subtypes based on ERα36 expression. We propose that ERα36high CAFs could account for an unfavorable prognosis for TNBC patients

ERα36-High Cancer-Associated Fibroblasts as an Unfavorable Factor in Triple-Negative Breast Cancer

Background: Cancer-associated fibroblasts (CAFs) are the most abundant cell type in the tumor microenvironment (TME). Estrogen receptor alpha 36 (ERα36), the alternatively spliced variant of ERα, is described as an unfavorable factor when expressed in cancer cells. ERα can be expressed also in CAFs; however, the role of ERα36 in CAFs is unknown. Methods: Four CAF cultures were isolated from chemotherapy-naïve BC patients and characterized for ERα36 expression and the NanoString gene expression panel using isolated RNA. Conditioned media from CAF cultures were used to assess the influence of CAFs on triple-negative breast cancer (TNBC) cells using a matrigel 3D culture assay. Results: We found that ERα36high CAFs significantly induced the branching of TNBC cells in vitro (p < 0.001). They also produced a set of pro-tumorigenic cytokines compared to ERα36low CAFs, among which hepatocyte growth factor (HGF) was the main inducer of TNBC cell invasive phenotype in vitro (p < 0.001). Tumor stroma rich in ERα36high CAFs was correlated with high Ki67 expression (p = 0.041) and tumor-associated macrophages markers (CD68 and CD163, p = 0.041 for both). HGF was found to be an unfavorable prognostic factor in TCGA database analysis (p = 0.03 for DFS and p = 0.04 for OS). Conclusions: Breast cancer-associated fibroblasts represent distinct subtypes based on ERα36 expression. We propose that ERα36high CAFs could account for an unfavorable prognosis for TNBC patients

Heterogeneity of Mesenchymal Markers Expression—Molecular Profiles of Cancer Cells Disseminated by Lymphatic and Hematogenous Routes in Breast Cancer

Breast cancers can metastasize via hematogenous and lymphatic routes, however in some patients only one type of metastases are detected, suggesting a certain proclivity in metastatic patterns. Since epithelial-mesenchymal transition (EMT) plays an important role in cancer dissemination it would be worthwhile to find if a specific profile of EMT gene expression exists that is related to either lymphatic or hematogenous dissemination. Our study aimed at evaluating gene expression profile of EMT-related markers in primary tumors (PT) and correlated them with the pattern of metastatic spread. From 99 early breast cancer patients peripheral blood samples (N = 99), matched PT (N = 47) and lymph node metastases (LNM; N = 22) were collected. Expression of TWIST1, SNAI1, SNAI2 and VIM was analyzed in those samples. Additionally expression of CK19, MGB1 and HER2 was measured in CTCs-enriched blood fractions (CTCs-EBF). Results were correlated with each other and with clinico-pathological data of the patients. Results show that the mesenchymal phenotype of CTCs-EBF correlated with poor clinico-pathological characteristics of the patients. Additionally, PT shared more similarities with LNM than with CTCs-EBF. Nevertheless, LNM showed increased expression of EMT-related markers than PT; and EMT itself in PT did not seem to be necessary for lymphatic dissemination