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

Elevated expression of complement factor I in lung cancer cells associates with shorter survival-Potentially via non-canonical mechanism

While numerous membrane-bound complement inhibitors protect the body's cells from innate immunity's autoaggression, soluble inhibitors like complement factor I (FI) are rarely produced outside the liver. Previously, we reported the expression of FI in non-small cell lung cancer (NSCLC) cell lines. Now, we assessed the content of FI in cancer biopsies from lung cancer patients and associated the results with clinicopathological characteristics and clinical outcomes. Immunohistochemical staining intensity did not correlate with age, smoking status, tumor size, stage, differentiation grade, and T cell infiltrates, but was associated with progression-free survival (PFS), overall survival (OS) and disease-specific survival (DSS). Multivariate Cox analysis of low vs. high FI content revealed HR 0.55, 95 % CI 0.32-0.95, p=0.031 for PFS, HR 0.51, 95 % CI 0.25-1.02, p=0.055 for OS, and HR 0.32, 95 % CI 0.12-0.84, p=0.021 for DSS. Unfavorable prognosis might stem from the non-canonical role of FI, as the staining pattern did not correlate with C4d - the product of FI-supported degradation of active complement component C4b. To elucidate that, we engineered three human NSCLC cell lines naturally expressing FI with CRISPR/Cas9 technology, and compared the transcriptome of FI-deficient and FI-sufficient clones in each cell line. RNA sequencing revealed differentially expressed genes engaged in intracellular signaling pathways controlling proliferation, apoptosis, and responsiveness to growth factors. Moreover, in vitro colony-formation assays showed that FI-deficient cells formed smaller foci than FI-sufficient NSCLC cells, but their size increased when purified FI protein was added to the medium. We postulate that a non-canonical activity of FI influences cellular physiology and contributes to the poor prognosis of lung cancer patients.

Secretome analysis of breast cancer cells to identify potential target proteins of Ipomoea turpethum extract-loaded nanoparticles in the tumor microenvironment

Background: Breast cancer is the leading cause of frequent malignancy and morbidity among women across the globe, with an increment of 0.5% incidences every year. The deleterious effects of traditional treatment on off-target surrounding cells make it difficult to win the battle against breast cancer. Hence, an advancement in the therapeutic approach is crucial. Nanotechnology is one of the emerging methods for precise, targeted, and efficient drug delivery in cells. The previous study has demonstrated the cytotoxic effect of Ipomoea turpethum extract on breast cancer cells delivered via NIPAAM-VP-AA nanoparticles (NVA-IT). Manipulating the tumor microenvironment (TME) to inhibit cancer progression, invasion, and metastasis seems to be very insightful for researchers these days. With the help of secretome analysis of breast cancer cells after treatment with NVA-IT, we have tried to find out the possible TME manipulation achieved to favor a better prognosis of the disease. Method: MCF-7 and MDA MB-231 cells were treated with the IC50 value of NVA-IT, and the medium was separated from the cells after 24 h of the treatment. Nano LCMS/MS analysis was performed to identify the secretory proteins in the media. Further bioinformatics tools like GENT2, GSCA, GeneCodis 4, and STRING were used to identify the key proteins and their interactions. Result: From the nano LCMS/MS analysis, 70 differentially expressed secretory proteins in MCF-7 and 191 in MDA MB-231 were identified in the cell's media. Fifteen key target proteins were filtered using bioinformatics analysis, and the interaction of proteins involved in vesicular trafficking, cell cycle checkpoints, and oxidative stress-related proteins was prominent. Conclusion: This study concluded that I. turpethum extract-loaded NIPAAM-VP-AA nanoparticles alter the secretory proteins constituting the TME to cease cancer cell growth and metastasis.

Screening of Exosome-Derived Proteins and Their Potential as Biomarkers in Diagnostic and Prognostic for Pancreatic Cancer

In the oncological area, pancreatic cancer is one of the most lethal diseases, with 5-year survival rising just 10% in high-development countries. This disease is genetically characterized by KRAS as a driven mutation followed by SMAD4, CDKN2, and TP53-associated mutations. In clinical aspects, pancreatic cancer presents unspecific clinical symptoms with the absence of screening and early plasmatic biomarker, being that CA19-9 is the unique plasmatic biomarker having specificity and sensitivity limitations. We analyzed the plasmatic exosome proteomic profile of 23 patients with pancreatic cancer and 10 healthy controls by using Nanoscale liquid chromatography coupled to tandem mass spectrometry (NanoLC-MS/MS). The pancreatic cancer patients were subdivided into IPMN and PDAC. Our findings show 33, 34, and 7 differentially expressed proteins when comparing the IPMN vs. control, PDAC-No treatment vs. control, and PDAC-No treatment vs. IPMN groups, highlighting proteins of the complement system and coagulation, such as C3, APOB, and SERPINA. Additionally, PDAC with no treatment showed 11 differentially expressed proteins when compared to Folfirinox neoadjuvant therapy or Gemcitabine adjuvant therapy. So here, we found plasmatic exosome-derived differentially expressed proteins among cancer patients (IPMN, PDAC) when comparing with healthy controls, which could represent alternative biomarkers for diagnostic and prognostic evaluation, supporting further scientific and clinical studies on pancreatic cancer.

Synthetic Reader-Actuators Targeted to Polycomb-Silenced Genes Block Triple-Negative Breast Cancer Proliferation and Invasion

Scientists have used pharmacological inhibitors of polycomb proteins to restore the expression of tumor suppressor genes and stop cancer proliferation and invasion. A major limitation of this approach is that key transcriptional activators, such as TP53 and BAF SWI/SNF, are often mutated in cancer. Poor clinical results for polycomb-targeting therapies in solid cancers, including triple-negative breast cancer (TNBC), could discourage the further development of epigenetic monotherapies. Here, we performed epigenome actuation with a synthetic reader-actuator (SRA) that binds trimethylated histone H3 lysine 27 in polycomb chromatin and modulates core transcriptional activators. In SRA-expressing TNBC BT-549 cells, 122 genes become upregulated ≥2-fold, including the genes involved in cell death, cell cycle arrest, and migration inhibition. The SRA-expressing spheroids showed reduced size in Matrigel and loss of invasion. Therefore, targeting Mediator-recruiting regulators to silenced chromatin can activate tumor suppressors and stimulate anti-cancer phenotypes, and further development of robust gene regulators might benefit TNBC patients.

The effect of organ-specific tumor microenvironments on response patterns to immunotherapy

Immunotherapy, particularly immune checkpoint inhibitors, have become widely used in various settings across many different cancer types in recent years. Whilst patients are often treated on the basis of the primary cancer type and clinical stage, recent studies have highlighted disparity in response to immune checkpoint inhibitors at different sites of metastasis, and their impact on overall response and survival. Studies exploring the tumor immune microenvironment at different organ sites have provided insights into the immune-related mechanisms behind organ-specific patterns of response to immunotherapy. In this review, we aimed to highlight the key learnings from clinical studies across various cancers including melanoma, lung cancer, renal cell carcinoma, colorectal cancer, breast cancer and others, assessing the association of site of metastasis and response to immune checkpoint inhibitors. We also summarize the key clinical and pre-clinical findings from studies exploring the immune microenvironment of specific sites of metastasis. Ultimately, further characterization of the tumor immune microenvironment at different metastatic sites, and understanding the biological drivers of these differences, may identify organ-specific mechanisms of resistance, which will lead to more personalized treatment approaches for patients with innate or acquired resistance to immunotherapy.

The Innate Immune Microenvironment in Metastatic Breast Cancer

The immune system plays a fundamental role in neoplastic disease. In the era of immunotherapy, the adaptive immune response has been in the spotlight whereas the role of innate immunity in cancer development and progression is less known. The tumor microenvironment influences the terminal differentiation of innate immune cells, which can explicate their pro-tumor or anti-tumor effect. Different cells are able to recognize and eliminate no self and tumor cells: macrophages, natural killer cells, monocytes, dendritic cells, and neutrophils are, together with the elements of the complement system, the principal players of innate immunity in cancer development and evolution. Metastatic breast cancer is a heterogeneous disease from the stromal, immune, and biological point of view and requires deepened exploration to understand different patient outcomes. In this review, we summarize the evidence about the role of innate immunity in breast cancer metastatic sites and the potential targets for optimizing the innate response as a novel treatment opportunity.

Inside-Out of Complement in Cancer

The role of complement in cancer has received increasing attention over the last decade. Recent studies provide compelling evidence that complement accelerates cancer progression. Despite the pivotal role of complement in fighting microbes, complement seems to suppress antitumor immunity via regulation of host cell in the tumor microenvironment. Although most studies link complement in cancer to complement activation in the extracellular space, the discovery of intracellular activation of complement, raises the question: what is the relevance of this process for malignancy? Intracellular activation is pivotal for the survival of immune cells. Therefore, complement can be important for tumor cell survival and growth regardless of the role in immunosuppression. On the other hand, because intracellular complement (the complosome) is indispensable for activation of T cells, these functions will be essential for priming antitumor T cell responses. Here, we review functions of complement in cancer with the consideration of extra and intracellular pathways of complement activation and spatial distribution of complement proteins in tumors and periphery and provide our take on potential significance of complement as biomarker and target for cancer therapy.

Investigating the Prognostic Relevance of Tumor Immune Microenvironment and Immune Gene Assembly in Breast Carcinoma Subtypes

We hypothesized that different BC subtypes are characterized by spatially distinct tumor immune microenvironment (TIME) and that immune gene assembly of metastatic (Met) and non-metastatic (Ctrl) BCs vary across subtypes. Peritumoral, stromal and intratumoral TIL was assessed on 309 BC cases. Hot, cold and immune-excluded groups were defined, and the prognostic role of this classification was assessed. CD4+/CD8+ positivity was analyzed in 75 cases in four systematically predefined tumor regions. Immune gene expression of Met and Ctrl HER2-negative BCs was compared by using NanoString nCounter technology. The amount of TIL infiltration varied greatly within all BC subtypes. Two-third of the cases were cold tumors with no significant survival difference compared to hot tumors. A lower CD4+/CD8+ ratio at the stromal internal tumor region was significantly associated with longer distant metastasis-free survival. The differentially expressed immune genes between Met and Ctrl varied across the studied BC subtypes with TNBC showing distinct features from the luminal subtypes. The TIME is characterized by a considerable heterogeneity; however, low level of TILs does not equate to disease progression. The differences in immune gene expression observed between Met and Ctrl breast carcinomas call attention to the important role of altered immune function in BC progression.

Non-Coding RNAs Are Brokers in Breast Cancer Interactome Networks and Add Discrimination Power between Subtypes

Despite the power of high-throughput genomics, most non-coding RNA (ncRNA) biotypes remain hard to identify, characterize, and validate. This is a clear indication that intensive next-generation sequencing research has led to great efficiency and accuracy in detecting ncRNAs, but not in their functionalization. Computational scientists continue to support the discovery process by spotting significant data features (expression or mutational profiles), elucidating phenotype uncertainty, and delineating complex regulation landscapes for biological pathways and pathophysiological processes. With reference to transcriptome regulation dynamics in cancer, this work introduces a novel network-driven inference approach designed to reveal the potential role of computationally identified ncRNAs in discriminating between breast cancer (BC) subtypes beyond the traditional gene expression signatures. As heterogeneity cast in the subtypes is a characteristic of most cancers, the proposed approach is generalizable beyond BC. Expression profiles of a wide transcriptome spectrum were obtained for a number of BC patients (and controls) listed in TCGA and processed with RNA-Seq. The well-known PAM50 subtype signature was available for the samples and used to move from differentially expressed transcript profiles to subtype-specific biclusters associating gene patterns with patients. Co-expressed gene networks were then generated and annotations were provided, focusing on the biclusters with basal and luminal signatures. These were used to build template maps, i.e., networks in which to embed the ncRNAs and contextually functionalize them based on their interactors. This inference approach is able to assess the influence of ncRNAs at the level of BC subtype. Network topology was considered through the brokerage measure to account for disruptiveness effects induced by the removal of nodes corresponding to ncRNAs. Equivalently, it is shown that ncRNAs can act as brokers of network interactome dynamics, and removing them allows the refinement of subtype-related characteristics previously obtained by gene signatures only. The results of the study elucidate the role of pseudogenes in two major BC subtypes, considering the contextual annotations. Put into a wider perspective, ncRNA brokers may help predictive functionalization studies targeted to new disease phenotypes, for instance those linked to the tumor microenvironment or metabolism, or those specifically involving metastasis. Overall, the approach may represent an in silico prioritization strategy toward the systems identification of new diagnostic and prognostic biomarkers.

Identification of hub genes for early detection of bone metastasis in breast cancer

BACKGROUND

Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers.

METHODS

GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC.

CONCLUSIONS

2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment.