Molecular profiling of microinvasive breast cancer microenvironment progression

Redox and metabolic reprogramming in breast cancer and cancer-associated adipose tissue

Redox and metabolic processes are tightly coupled in both physiological and pathological conditions. In cancer, their integration occurs at multiple levels and is characterized by synchronized reprogramming both in the tumor tissue and its specific but heterogeneous microenvironment. In breast cancer, the principal microenvironment is the cancer-associated adipose tissue (CAAT). Understanding how the redox-metabolic reprogramming becomes coordinated in human breast cancer is imperative both for cancer prevention and for the establishment of new therapeutic approaches. This review aims to provide an overview of the current knowledge of the redox profiles and regulation of intermediary metabolism in breast cancer while considering the tumor and CAAT of breast cancer as a unique Warburg's pseudo-organ. As cancer is now recognized as a systemic metabolic disease, we have paid particular attention to the cell-specific redox-metabolic reprogramming and the roles of estrogen receptors and circadian rhythms, as well as their crosstalk in the development, growth, progression, and prognosis of breast cancer.

A real-world multi-center RNA-seq benchmarking study using the Quartet and MAQC reference materials

Translating RNA-seq into clinical diagnostics requires ensuring the reliability and cross-laboratory consistency of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. As part of the Quartet project, we present an RNA-seq benchmarking study across 45 laboratories using the Quartet and MAQC reference samples spiked with ERCC controls. Based on multiple types of 'ground truth', we systematically assess the real-world RNA-seq performance and investigate the influencing factors involved in 26 experimental processes and 140 bioinformatics pipelines. Here we show greater inter-laboratory variations in detecting subtle differential expressions among the Quartet samples. Experimental factors including mRNA enrichment and strandedness, and each bioinformatics step, emerge as primary sources of variations in gene expression. We underscore the profound influence of experimental execution, and provide best practice recommendations for experimental designs, strategies for filtering low-expression genes, and the optimal gene annotation and analysis pipelines. In summary, this study lays the foundation for developing and quality control of RNA-seq for clinical diagnostic purposes.

Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E-stained and multiphoton microscopy images

Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E-stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E-stained sections. The intensity of two-photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second-harmonic generation (SHG), respectively. By fusing the nuclei in H&E-stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).

Spatial transcriptomics and the anatomical pathologist: Molecular meets morphology

In recent years anatomical pathology has been revolutionised by the incorporation of molecular findings into routine diagnostic practice, and in some diseases the presence of specific molecular alterations are now essential for diagnosis. Spatial transcriptomics describes a group of technologies that provide up to transcriptome-wide expression profiling while preserving the spatial origin of the data, with many of these technologies able to provide these data using a single tissue section. Spatial transcriptomics allows expression profiling of highly specific areas within a tissue section potentially to subcellular resolution, and allows correlation of expression data with morphology, tissue type and location relative to other structures. While largely still research laboratory-based, several spatial transcriptomics methods have now achieved compatibility with formalin-fixed paraffin-embedded tissue (FFPE), allowing their use in diagnostic tissue samples, and with further development potentially leading to their incorporation in routine anatomical pathology practice. This mini review provides an overview of spatial transcriptomics methods, with an emphasis on platforms compatible with FFPE tissue, approaches to assess the data and potential applications in anatomical pathology practice.

T-cell infiltration and its regulatory mechanisms in cancers: insights at single-cell resolution

Tumor-infiltrating T cells recognize, attack, and clear tumor cells, playing a central role in antitumor immune response. However, certain immune cells can impair this response and help tumor immune escape. Therefore, exploring the factors that influence T-cell infiltration is crucial to understand tumor immunity and improve therapeutic effect of cancer immunotherapy. The use of single-cell RNA sequencing (scRNA-seq) allows the high-resolution analysis of the precise composition of immune cells with different phenotypes and other microenvironmental factors, including non-immune stromal cells and the related molecules in the tumor microenvironment of various cancer types. In this review, we summarized the research progress on T-cell infiltration and the crosstalk of other stromal cells and cytokines during T-cell infiltration using scRNA-seq to provide insights into the mechanisms regulating T-cell infiltration and contribute new perspectives on tumor immunotherapy.

Single-cell RNA sequencing reveals a pro-metastatic subpopulation and the driver transcription factor NFE2L1 in ovarian cancer cells

BACKGROUND

Although cytoreductive surgery followed by adjuvant chemotherapy is effective as a standard treatment for early-stage ovarian cancer, the majority of ovarian cancer cases are diagnosed at the advanced stages with dissemination to the peritoneal cavity, leading to a poor prognosis. Therefore, it is crucial to understand the cellular and molecular mechanisms underlying metastasis and identify novel therapeutic targets.

OBJECTIVE

In this study, we aimed to elucidate the mechanisms underlying gene expression alterations during the acquisition of metastatic potential and characterize the metastatic subpopulations within ovarian cancer cells.

METHODS

We conducted single-cell RNA sequencing of two human ovarian cancer cell lines: SKOV-3 and SKOV-3-13, a highly metastatic subclone of SKOV-3. Suppression of NFE2L1 expression was performed through siRNA-mediated knockdown and CRISPR-Cas9-mediated knockout.

RESULTS

Clustering and pseudotime trajectory analysis revealed pro-metastatic subpopulation within these cells. Furthermore, gene set enrichment analysis and prognosis analysis indicated that NFE2L1 could be a key transcription factor in the acquisition of metastasis potential. Inhibition of NFE2L1 significantly reduced migration and viability of both cells. In addition, NFE2L1 knockout cells exhibited significantly reduced tumor growth in a mouse xenograft model, recapitulating in silico and in vitro results.

CONCLUSION

The results presented in this study deepen our understanding of the molecular pathogenesis of ovarian cancer metastasis with the ultimate goal of developing treatments targeting pro-metastatic subclones prior to metastasis.

Assessing Tumor-Infiltrating Lymphocytes in Breast Cancer: A Proposal for Combining Immunohistochemistry and Gene Expression Analysis to Refine Scoring

Scoring of tumor-infiltrating lymphocytes (TILs) in breast cancer specimens has gained increasing attention, as TILs have prognostic and predictive value in HER2+ and triple-negative breast cancer. We evaluated the intra- and interrater variability when scoring TILs by visual inspection of hematoxylin and eosin-stained tissue sections. We further addressed whether immunohistochemical staining of these sections for immune cell surface markers CD45, CD3, CD4, and CD8 and combination with nanoString nCounter® gene expression analysis could refine TIL scoring. Formalin-fixed paraffin-embedded and fresh-frozen core needle biopsies of 12 female and treatment-naive breast cancer patients were included. Scoring of TILs was performed twice by three independent pathologists with a washout period of 3 days. Increasing intra- and interrater variability was observed with higher TIL numbers. The highest reproducibility was observed on tissue sections stained for CD3 and CD8. The latter TIL scores correlated well with the TIL scores obtained through nanoString nCounter® gene expression analysis. Gene expression analysis also revealed 104 and 62 genes that are positively and negatively related to both TIL scores. In conclusion, integration of immunohistochemistry and gene expression analysis is a valuable strategy to refine TIL scoring in breast tumors.

Markers of Angiogenesis, Lymphangiogenesis, and Epithelial-Mesenchymal Transition (Plasticity) in CIN and Early Invasive Carcinoma of the Cervix: Exploring Putative Molecular Mechanisms Involved in Early Tumor Invasion

The establishment of a proangiogenic phenotype and epithelial-to-mesenchymal transition (EMT) are considered as critical events that promote the induction of invasive growth in epithelial tumors, and stimulation of lymphangiogenesis is believed to confer the capacity for early dissemination to cancer cells. Recent research has revealed substantial interdependence between these processes at the molecular level as they rely on common signaling networks. Of great interest are the molecular mechanisms of (lymph-)angiogenesis and EMT associated with the earliest stages of transition from intraepithelial development to invasive growth, as they could provide the source of potentially valuable tools for targeting tumor metastasis. However, in the case of early-stage cervical cancer, the players of (lymph-)angiogenesis and EMT processes still remain substantially uncharacterized. In this study, we used RNA sequencing to compare transcriptomes of HPV(+) preinvasive neoplastic lesions and early-stage invasive carcinoma of the cervix and to identify (lymph-)angiogenesis- and EMT-related genes and pathways that may underlie early acquisition of invasive phenotype and metastatic properties by cervical cancer cells. Second, we applied flow cytometric analysis to evaluate the expression of three key lymphangiogenesis/EMT markers (VEGFR3, MET, and SLUG) in epithelial cells derived from enzymatically treated tissue specimens. Overall, among 201 differentially expressed genes, a considerable number of (lymph-)angiogenesis and EMT regulatory factors were identified, including genes encoding cytokines, growth factor receptors, transcription factors, and adhesion molecules. Pathway analysis confirmed enrichment for angiogenesis, epithelial differentiation, and cell guidance pathways at transition from intraepithelial neoplasia to invasive carcinoma and suggested immune-regulatory/inflammatory pathways to be implicated in initiation of invasive growth of cervical cancer. Flow cytometry showed cell phenotype-specific expression pattern for VEGFR3, MET, and SLUG and revealed correlation with the amount of tumor-infiltrating lymphocytes at the early stages of cervical cancer progression. Taken together, these results extend our understanding of driving forces of angiogenesis and metastasis in HPV-associated cervical cancer and may be useful for developing new treatments.

Molecular natural history of breast cancer: Leveraging transcriptomics to predict breast cancer progression and aggressiveness

BACKGROUND

Characterizing breast cancer progression and aggressiveness relies on categorical descriptions of tumor stage and grade. Interpreting these categorical descriptions is challenging because stage convolutes the size and spread of the tumor and no consensus exists to define high/low grade tumors.

METHODS

We address this challenge of heterogeneity in patient-specific cancer samples by adapting and applying several tools originally created for understanding heterogeneity and phenotype development in single cells (specifically, single-cell topological data analysis and Wanderlust) to create a continuous metric describing breast cancer progression using bulk RNA-seq samples from individual patient tumors. We also created a linear regression-based method to predict tumor aggressiveness in vivo from bulk RNA-seq data.

RESULTS

We found that breast cancer proceeds along three convergent phenotype trajectories: luminal, HER2-enriched, and basal-like. Furthermore, 31 296 genes (for luminal cancers), 17 827 genes (for HER2-enriched), and 18 505 genes (for basal-like) are dynamically differentially expressed during breast cancer progression. Across progression trajectories, our results show that expression of genes related to ADP-ribosylation decreased as tumors progressed (while PARP1 and PARP2 increased or remained stable), suggesting the potential for a differential response to PARP inhibitors based on cancer progression. Additionally, we developed a 132-gene expression regression equation to predict mitotic index and a 23-gene expression regression equation to predict growth rate from a single breast cancer biopsy.

CONCLUSION

Our results suggest that breast cancer dynamically changes during disease progression, and growth rate of the cancer cells is associated with distinct transcriptional profiles.

Recent Advances in Cancer Plasticity: Cellular Mechanisms, Surveillance Strategies, and Therapeutic Optimization

The processes of recurrence and metastasis, through which cancer relapses locally or spreads to distant sites in the body, accounts for more than 90% of cancer-related deaths. At present there are very few treatment options for patients at this stage of their disease. The main obstacle to successfully treat advanced cancer is the cells' ability to change in ways that make them resistant to treatment. Understanding the cellular mechanisms that mediate this cancer cell plasticity may lead to improved patient survival. Epigenetic reprogramming, together with tumor microenvironment, drives such dynamic mechanisms favoring tumor heterogeneity, and cancer cell plasticity. In addition, the development of new approaches that can report on cancer plasticity in their native environment have profound implications for studying cancer biology and monitoring tumor progression. We herein provide an overview of recent advancements in understanding the mechanisms regulating cell plasticity and current strategies for their monitoring and therapy management.