Integrating bulk and single-cell RNA sequencing data reveals the relationship between intratumor microbiome signature and host metabolic heterogeneity in breast cancer

Clinical Relevance and Drug Modulation of PPAR Signaling Pathway in Triple-Negative Breast Cancer: A Comprehensive Analysis

Triple-negative breast cancer (TNBC) is highly heterogeneous and poses a significant medical challenge due to limited treatment options and poor outcomes. Peroxisome proliferator-activated receptors (PPARs) play a crucial role in regulating metabolism and cell fate. While the association between PPAR signal and human cancers has been a topic of concern, its specific relationship with TNBC remains unclear. Integrated analysis of large published datasets from clinical cohorts and cell lines through databases has proven to be a powerful and essential approach for understanding cancer and uncovering new molecular targets. Here, we conducted a comprehensive study investigating the clinical relevance and drug modulation of the PPAR signaling pathway in TNBC, using data from The Cancer Genome Atlas (TCGA) for TNBC patients and Genomics of Drug Sensitivity in Cancer (GDSC) for TNBC cell lines, along with drug perturbation information from Connectivity Map (CMap). In the TCGA-TNBC cohort, higher PPAR signaling activity was not associated with clinical stage, prognosis, tumor mutational burden, microsatellite instability, homologous recombination deficiency, stemness, or proliferation status. However, it was linked to older age; an elevated rate of piccolo presynaptic cytomatrix protein (PCLO) mutations; and oncogenic signal transduction involving MAPK, Ras, and PI3K-Akt pathways. Additionally, it influenced biological pathways including fatty acid metabolism, AMPK signaling, and ferroptosis. Strikingly, higher PPAR activity appeared to promote the formation of an antitumor immune and microbial microenvironment. In the GDSC-TNBC cells, nevertheless, it seemed to incur chemoresistance. Furthermore, we identified a batch of potential compounds that can regulate the PPAR signaling pathway. Lastly, our experimental validation demonstrated the ability of the histone deacetylase (HDAC) inhibitor chidamide to activate the PPAR signal in TNBC cells. In conclusion, the PPAR signaling pathway likely has pleiotropic biological effects in TNBC. These preliminary but interesting findings enhance our understanding of the role played by PPAR signal and provide new insights into the heterogeneity driven by it in TNBC.

Guideline for designing microbiome studies in neoplastic diseases

Oncobiosis has emerged as a key contributor to the development, and modulator of the treatment efficacy of cancer. Hereby, we review the modalities through which the oncobiome can support the progression of tumors, and the emerging therapeutic opportunities they present. The review highlights the inherent challenges and limitations faced in sampling and accurately characterizing oncobiome. Additionally, the review underscores the critical need for the standardization of microbial analysis techniques and the consistent reporting of microbiome data. We provide a suggested metadata set that should accompany microbiome datasets from oncological settings so that studies remain comparable and decipherable.

Intratumoral Microbiota as a Target for Advanced Cancer Therapeutics

In recent years, advancements in microbial sequencing technology have sparked an increasing interest in the bacteria residing within solid tumors and its distribution and functions in various tumors. Intratumoral bacteria critically modulate tumor oncogenesis and development through DNA damage induction, chronic inflammation, epigenetic alterations, and metabolic and immune regulation, while also influencing cancer treatment efficacy by affecting drug metabolism. In response to these discoveries, a variety of anti-cancer therapies targeting these microorganisms have emerged. These approaches encompass oncolytic therapy utilizing tumor-associated bacteria, the design of biomaterials based on intratumoral bacteria, the use of intratumoral bacterial components for drug delivery systems, and comprehensive strategies aimed at the eradication of tumor-promoting bacteria. Herein, this review article summarizes the distribution patterns of bacteria in different solid tumors, examines their impact on tumors, and evaluates current therapeutic strategies centered on tumor-associated bacteria. Furthermore, the challenges and prospects for developing drugs that target these bacterial communities are also explored, promising new directions for cancer treatment.

Comprehensive analysis of microbial content in whole-genome sequencing samples from The Cancer Genome Atlas project

In recent years, a growing number of publications have reported the presence of microbial species in human tumors and of mixtures of microbes that appear to be highly specific to different cancer types. Our recent re-analysis of data from three cancer types revealed that technical errors have caused erroneous reports of numerous microbial species found in sequencing data from The Cancer Genome Atlas (TCGA) project. Here we have expanded our analysis to cover all 5,734 whole-genome sequencing (WGS) data sets currently available from TCGA, covering 25 distinct types of cancer. We analyzed the microbial content using updated computational methods and databases, and compared our results to those from two major recent studies that focused on bacteria, viruses, and fungi in cancer. Our results expand upon and reinforce our recent findings, which showed that the presence of microbes is far smaller than had been previously reported, and that many species identified in TCGA data are either not present at all, or are known contaminants rather than microbes residing within tumors. As part of this expanded analysis, and to help others avoid being misled by flawed data, we have released a dataset that contains detailed read counts for bacteria, viruses, archaea, and fungi detected in all 5,734 TCGA samples, which can serve as a public reference for future investigations.

The immunoregulatory role of gut microbiota in the incidence, progression, and therapy of breast cancer

Breast cancer (BrCa) is the most prevalent malignant tumor in women and one of the leading causes of female mortality. Its occurrence and progression are influenced by various factors, including genetics, environment, lifestyle, and hormones. In recent years, the gut microbiota has been identified as a significant factor affecting BrCa. The gut microbiota refers to the collective population of various microorganisms in the human gastrointestinal tract. Gut microbiota is closely associated with human health and disease development, participating in crucial physiological functions such as digestion, metabolism, immune response, and neural regulation. It has been found to influence the occurrence and treatment of BrCa through a variety of mechanisms. This article aims to review the immunomodulatory role of the gut microbiota in the development and treatment of BrCa.

Impact of Equine Ocular Surface Squamous Neoplasia on Interactions between Ocular Transcriptome and Microbiome

Ocular surface squamous neoplasia (OSSN) represents the most common conjunctival tumor in horses and frequently results in vision loss and surgical removal of the affected globe. Multiple etiologic factors have been identified as contributing to OSSN progression, including solar radiation exposure, genetic mutations, and a lack of periocular pigmentation. Response to conventional treatments has been highly variable, though our recent work indicates that these tumors are highly responsive to local immunotherapy. In the present study, we extended our investigation of OSSN in horses to better understand how the ocular transcriptome responds to the presence of the tumor and how the ocular surface microbiome may also be altered by the presence of cancer. Therefore, we collected swabs from the ventral conjunctival fornix from 22 eyes in this study (11 with cytologically or histologically confirmed OSSN and 11 healthy eyes from the same horses) and performed RNA sequencing and 16S microbial sequencing using the same samples. Microbial 16s DNA sequencing and bulk RNA sequencing were both conducted using an Illumina-based platform. In eyes with OSSN, we observed significantly upregulated expression of genes and pathways associated with inflammation, particularly interferon. Microbial diversity was significantly reduced in conjunctival swabs from horses with OSSN. We also performed interactome analysis and found that three bacterial taxa (Actinobacillus, Helcococcus and Parvimona) had significant correlations with more than 100 upregulated genes in samples from animals with OSSN. These findings highlight the inflammatory nature of OSSN in horses and provide important new insights into how the host ocular surface interacts with certain microbial populations. These findings suggest new strategies for the management of OSSN in horses, which may entail immunotherapy in combination with ocular surface probiotics or prebiotics to help normalize ocular cell and microbe interactions.

Multi-omics analysis elucidates the relationship between intratumor microbiome and host immune heterogeneity in breast cancer

Research has indicated that intratumor microbiomes affect the occurrence, progression, and therapeutic response in many cancer types by influencing the immune system. We aim to evaluate the characteristics of immune-related intratumor microbiomes (IRIMs) in breast cancer (BC) and search for potential prognosis prediction factors and treatment targets. The clinical information, microbiome data, transcriptomics data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) patients were obtained from Kraken-TCGA-Raw-Data and TCGA portal. The core tumor-infiltrating immune cell was identified using univariate Cox regression analysis. Based on consensus clustering analysis, BC patients were categorized into two immune subtypes, referred to as immune-enriched and immune-deficient subtypes. The immune-enriched subtype, characterized by higher levels of immune infiltration of CD8+ T and macrophage M1 cells, demonstrated a more favorable prognosis. Furthermore, significant differences in alpha-diversity and beta-diversity were observed between the two immune subtypes, and the least discriminant analysis effect size method identified 33 types of IRIMs. An intratumor microbiome-based prognostic signature consisting of four prognostic IRIMs (Acidibacillus, Succinimonas, Lachnoclostridium, and Pseudogulbenkiania) was constructed using the Cox proportional-hazard model, and it had great prognostic value. The prognostic IRIMs were correlated with immune gene expression and the sensitivity of chemotherapy drugs, specifically tamoxifen and docetaxel. In conclusion, our research has successfully identified two distinct immune subtypes in BC, which exhibit contrasting prognoses and possess unique epigenetic and intratumor microbiomes. The critical IRIMs were correlated with prognosis, tumor-infiltrating immune cell abundance, and immunotherapeutic efficacy in BC. Consequently, this study has identified potential IRIMs as biomarkers, providing a novel therapeutic approach for treating BC.IMPORTANCERecent research has substantiated the presence of the intratumor microbiome in tumor immune microenvironment, which could influence tumor occurrence and progression, as well as provide new opportunities for cancer diagnosis and treatment. This study identified the critical immune-related intratumor microbiome (Acidibacillus, Succinimonas, Lachnoclostridium, and Pseudogulbenkiania), which were correlated with prognosis, tumor-infiltrating immune cell abundance, and immunotherapeutic efficacy in breast cancer and might be the novel target to regulate immunotherapy in BC.

Major data analysis errors invalidate cancer microbiome findings

IMPORTANCE

Recent reports showing that human cancers have a distinctive microbiome have led to a flurry of papers describing microbial signatures of different cancer types. Many of these reports are based on flawed data that, upon re-analysis, completely overturns the original findings. The re-analysis conducted here shows that most of the microbes originally reported as associated with cancer were not present at all in the samples. The original report of a cancer microbiome and more than a dozen follow-up studies are, therefore, likely to be invalid.

Intratumor microbiome: selective colonization in the tumor microenvironment and a vital regulator of tumor biology

The polymorphic microbiome has been proposed as a new hallmark of cancer. Intratumor microbiome has been revealed to play vital roles in regulating tumor initiation and progression, but the regulatory mechanisms have not been fully uncovered. In this review, we illustrated that similar to other components in the tumor microenvironment, the reside and composition of intratumor microbiome are regulated by tumor cells and the surrounding microenvironment. The intratumor hypoxic, immune suppressive, and highly permeable microenvironment may select certain microbiomes, and tumor cells may directly interact with microbiome via molecular binding or secretions. Conversely, the intratumor microbiomes plays vital roles in regulating tumor initiation and progression via regulating the mutational landscape, the function of genes in tumor cells and modulating the tumor microenvironment, including immunity, inflammation, angiogenesis, stem cell niche, etc. Moreover, intratumor microbiome is regulated by anti-cancer therapies and actively influences therapy response, which could be a therapeutic target or engineered to be a therapy weapon in the clinic. This review highlights the intratumor microbiome as a vital component in the tumor microenvironment, uncovers potential mutual regulatory mechanisms between the tumor microenvironment and intratumor microbiome, and points out the ongoing research directions and drawbacks of the research area, which should broaden our view of microbiome and enlighten further investigation directions.

Major data analysis errors invalidate cancer microbiome findings

We re-analyzed the data from a recent large-scale study that reported strong correlations between microbial organisms and 33 different cancer types, and that created machine learning predictors with near-perfect accuracy at distinguishing among cancers. We found at least two fundamental flaws in the reported data and in the methods: (1) errors in the genome database and the associated computational methods led to millions of false positive findings of bacterial reads across all samples, largely because most of the sequences identified as bacteria were instead human; and (2) errors in transformation of the raw data created an artificial signature, even for microbes with no reads detected, tagging each tumor type with a distinct signal that the machine learning programs then used to create an apparently accurate classifier. Each of these problems invalidates the results, leading to the conclusion that the microbiome-based classifiers for identifying cancer presented in the study are entirely wrong. These flaws have subsequently affected more than a dozen additional published studies that used the same data and whose results are likely invalid as well.

From Reductionistic Approach to Systems Immunology Approach for the Understanding of Tumor Microenvironment

The tumor microenvironment (TME) is a complex and dynamic ecosystem that includes a variety of immune cells mutually interacting with tumor cells, structural/stromal cells, and each other. The immune cells in the TME can have dual functions as pro-tumorigenic and anti-tumorigenic. To understand such paradoxical functions, the reductionistic approach classifies the immune cells into pro- and anti-tumor cells and suggests the therapeutic blockade of the pro-tumor and induction of the anti-tumor immune cells. This strategy has proven to be partially effective in prolonging patients' survival only in a fraction of patients without offering a cancer cure. Recent advances in multi-omics allow taking systems immunology approach. This essay discusses how a systems immunology approach could revolutionize our understanding of the TME by suggesting that internetwork interactions of the immune cell types create distinct collective functions independent of the function of each cellular constituent. Such collective function can be understood by the discovery of the immunological patterns in the TME and may be modulated as a therapeutic means for immunotherapy of cancer.