The microbiota and renal cell carcinoma

Abstract

Renal cell carcinoma (RCC) accounts for about 2% of cancer diagnoses and deaths worldwide. Recent studies emphasized the critical involvement of microbial populations in RCC from oncogenesis, tumor growth, and response to anticancer therapy. Microorganisms have been shown to be involved in various renal physiological and pathological processes by influencing the immune system function, metabolism of the host and pharmaceutical reactions. These findings have extended our understanding and provided more possibilities for the diagnostic or therapeutic development of microbiota, which could function as screening, prognostic, and predictive biomarkers, or be manipulated to prevent RCC progression, boost anticancer drug efficacy and lessen the side effects of therapy. This review aims to present an overview of the roles of microbiota in RCC, including pertinent mechanisms in microbiota-related carcinogenesis, the potential use of the microbiota as RCC biomarkers, and the possibility of modifying the microbiota for RCC prevention or treatment. According to these scientific findings, the clinical translation of microbiota is expected to improve the diagnosis and treatment of RCC.

Introduction

Renal cell carcinoma (RCC) is one of the most frequent cancers with a rising prevalence, accounting for about 400,000 newly diagnosed cases and around 180,000 deaths globally each year [1]. Nearly 30% of patients are identified at an advanced or metastatic stage, with an estimated 10% 5-year survival probability [2]. Despite the fact that the discovery of targeted medicines and immune checkpoint inhibitors (ICIs) has resulted in significant therapeutic gains for patients over the past few decades, a deeper knowledge of the RCC etiology is required to further lower morbidity and mortality [3]. Microbiota, which consists of microorganisms and their genomes, affects the metabolic, immunologic, hormonal, and homeostatic processes of the host. In recent years, mounting data suggests that microbiota may potentially play a significant role in the onset and progression of RCC [4]. Antibiotic-treated patients with advanced RCC showed less sensitivity to immunotherapies and had shorter progression-free survival (PFS) and overall survival (OS) than non-antibiotic-treated patients [5–7]. In addition, for RCC patients without a history of antibiotic exposure, an overabundance of Akkermansia muciniphila, Bacteroides salyersiae, and Eubacterium siraeum in the stomach may increase the efficacy of nivolumab [8]. However, direct evidence for the engagement of microbiota in RCC tissues is still lacking, and more exhaustive research is needed.

As early as 1976, a landmark trial credited to Morales, where recurrent non-muscle invasive bladder cancer (NMIBC) was treated with Bacillus Calmette–Guérin (BCG) vaccination, brought the administration of attenuated Mycobacterium tuberculosis and linked the urinary system with exogenous microbiota [9]. Generally, the urinary tract (UT) was considered to be sterile. In 2008, the Human Microbiome Project (HMP) was established to provide a thorough characterization of the microbiome and analysis of its function in human health and illness, whereas the urinary system was not included in this study [10]. Nevertheless, the microbiome of UT was found using sophisticated molecular biology techniques and culturomics [11, 12]. The identification and function of a particular microbiome in UT were characterized in various urinary disorders [13]. Patients with urologic disorders such as urinary incontinence (UI), bladder and prostate cancer, neurogenic bladder dysfunction (NBD), interstitial cystitis (IC), sexually transmitted infections (STIs), and chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) were observed to have altered urinary microbiota in some studies [14]. Urinary cancer is no exception. Alterations in the microbiome community of bladder cancer patients relative to healthy persons revealed an increase in Streptococcus in their urine [15–17]. Thus, exploring the role of the microbiome in RCC is in the ascendant.

In this review, we will provide an overview of the relationships and potential mechanisms between the microbiome and the origin and development of RCC. In addition, possible applications for microbiome-based diagnostic and therapeutic tools, as well as ongoing clinical studies, will be highlighted.

The landscape of the RCC microbiota

Clinical microbiology laboratories have long held that a healthy person’s urinary system is sterile. Expanded culture methods and bacterial nucleic acid sequencing, including next-generation sequencing of the 16S ribosomal RNA gene (rRNA) and metagenomics whole-genome shotgun sequencing, have made it possible to identify the bacteria in urinary tract [18–20]. The development of more advanced technologies allowed for the taxonomic resolution of bacterial communities down to the level of individual species and strains. Recent studies indicated that a great number of microorganisms existed in the urinary tract [21] and changed in patients with type 2 diabetes mellitus [22], overactive bladder syndrome [23, 24], UI [25], IC [26], neuropathic bladder [27, 28], STIs [29], and CP/CPPS [30, 31]. More evidence revealed that endogenous and exogenous factors, such as food, environment, infections, medications, hospital personnel, hormonal status, stress, infections, personal habits, vaccination, and age are all implicated in the establishment of renal microbiota [32–35]. Therefore, numerous microbiological mechanisms could act in controlling the urine microbial composition (Fig. 1).

Fig. 1.

Detection, sources and influencing factors of microbiota in RCC. Advanced sequencing technologies have made it possible to identify the bacteria in urinary tract. The composition and functions of renal microbiota can be affected by lots of external and internal factors. The ever-changing sources of flora in the kidney include translocation from the circulatory system, migration from the gut and ascension from the lower urinary tract (UT). This figure was created with Adobe Illustrator

The source of flora in the kidney is ever-changing. Some pathological microorganisms from the bloodstream and lower urinary tract migrate to the kidney [36, 37]. Clinically, the presence of bacteria with inflammatory cells is diagnostic evidence of urinary tract infection (UTI) [38]. Asymptomatic bacteriuria is also commonly observed in the clinic. In the absence of estrogen, residual urine and decreased urine flow hinder mechanical clearance of bacteria and facilitate pathogen colonization [39]. Microbes can be derived from either renal pelvis urine or kidney stones [40–43]. As the urinary tract communicates with the outside environment via urethra, a retrograde flow of urine from the lower urinary tract is more likely to influence the renal microbiomes [44]. These findings explain variations in the microbiota of commensal urine (Fig. 1). Therefore, whether in patients with urinary disorders or healthy persons, the renal microbiome, bladder microbiome, and urine microbiome do exist and are analogical in general.

To date, multiple studies have examined the microbiome of RCC tissue, disclosing differences between the microbiomes of malignant and benign tissues [45–48]. A population-based case-control study suggested a positive correlation between a history of UTI with RCC development even after adjustment of other known and suspected risk factors [49]. It is well-accepted that Escherichia coli (E. coli), the vast majority (70–80%) of bacteria colonized in kidney during UTIs [50], which have been identified as a potential risk factor for several cancers [51]. The oncogenic properties of E. coli strain from the B2 family have been proven according to a recent accumulation of observations [52]. The study released in 2019 showed that 2,060,224 microorganisms stayed in malignant tissue and 528,795 microorganisms in healthy renal tissue [47]. The existence of a specific microbiome in the kidney was further validated by subsequent studies, which also revealed that the microbiome differed in terms of both composition and function [45, 46, 48]. Interestingly, the microbiome of the RCC is less diverse than that of the adjacent normal renal tissues [46, 48, 53]. However, among individuals with thrombus, the microbial diversity within the tumors is higher than that of the neighboring normal tissues and the thrombus [45]. The phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) analysis uncovered significant differences in 9 KEGG pathways between RCC tissues and para-carcinoma tissues, based on the predictive functional profiles of microbial communities that were identified [48]. These investigations consistently used 16S rRNA gene sequencing to identify, categorize, and quantify bacteria, and they concluded that Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria were the most ubiquitous phyla in both tumor and benign renal tissues [45–48]. Likewise, these bacterial phyla are also predominant in the gut [54]. Comparative metagenomic or metataxonomic approaches have typically been used in human studies to examine the involvement of the gut microbiota in RCC. It was demonstrated that gut microbiota associated with RCC differed from that in the control population with higher species richness, decreased abundance of possibly beneficial taxa (like Roseburia), and increased abundance of cancer-causing taxa (such as Bacteroides, Escherichia, Fusobacterium, and Porphyromonas) [55]. These findings highlight a potential core group of microbes that may be carcinogenic and show the functional significance of the microbial ecosystem.

In addition to bacteria, the microbiome also includes fungi and viruses. Peyton Rous et al. reported a transmissible oncogenic virus in chickens in 1911, which represented a major step forward for the viral theory of cancer that had previously received little attention [56]. Following decades of research, the association between RCC and viruses has been gradually established [57]. The Epstein-Barr virus (EBV) was soon found to have infected all RCC and nephroblastomas, regardless of their histological or clinical stages [58–60]. Furthermore, EBV expression increases in RCC with higher grades [58]. These findings imply that EBV plays a critical role in the pathophysiology of RCC and nephroblastoma. RCC was subsequently shown to relate to the DNA of several viruses, including human papillomavirus (HPV), hepatitis C virus (HCV), and polyomaviruses (BKV and JCV) [61, 62]. It was previously believed that the presence of fungus in the kidney was caused by an infection; however, the significance of a microbiome in RCC is still largely unrecognized at this time. In RCC patients, potential fungal infections, such as candida (1.3%), aspergillosis (0.4%), and others (0.2%), as well as viral infections, like herpes (1.1%) and hepatitis (0.2%), and parasitic infections (0.2%) due to mammalian target of rapamycin (mTOR) inhibitors were reported in studies [63]. Thus, immediate detection and appropriate treatment of infections caused by these factors are essential for optimal patient outcomes [63]. On the basis of existing findings, a few dozen microorganisms are directly linked to RCC. These investigations also raised numerous questions regarding microorganisms and RCC that require additional exploration.

Microorganisms in carcinogenesis and tumor progression

The relationship between microbes and carcinogenesis is intricate. Several studies have viewed the microbiome as a potential modulator of oncogenesis, tumor progression, and response to anticancer therapy by altering the balance of cell proliferation and cell death, influencing immune system function and the metabolism activity of the host, and affecting the response to pharmaceuticals [64–66]. Gut microbiota can regulate many functions of the tumor-bearing meta-organism, typically through immunomodulation, and putative intratumoral microbes may also be important (Fig. 2).

Fig. 2.

Microbial drivers of various cancers and their underlying mechanisms. ①. Breast cancer: The gut microbial community regulates estrogens through secretion of b-glucuronidase, thus increasing the breast cancer risk. ②. Gastric cancer: Direct and indirect actions of Helicobacter pylori (H. pylori) on gastric epithelial cells during gastric carcinogenesis. ③. Colorectal cancer: Many bacteria have been investigated to affect tumor development and growth. ④. Prostate cancer: IGF1 production stimulated from gut microbes influences the growth of prostate cancer via activating local prostate MAPK and PI3K signaling. ⑤. RCC: (a) Products from the bacteria metabolism play a role in the repression of inflammation and cancer. (b) Some microorganisms influence RCC genesis through oxidative/nitrosative stress and inflammatory processes. (c) HPV and EBV appear to exert a complex role in the progression of RCC. This figure was created with Adobe Illustrator. (d) Toxins from pathogenic bacteria may cause malignant transformation of target cells

The gut microbiome, consisting of microorganisms, plays a crucial role in the initiation and progression of various cancers. Gastrointestinal (GI) cancer is thought to be more impacted by the gut microbiome than other tumors due to the direct effect of gut microbiome alterations in the GI tract. Dysbiosis of gut microbiota can alter metabolism, cause inflammation, induce DNA damage, and affect signaling pathways, contributing to the promotion or progression of colorectal cancer (CRC). For example, F. nucleatum can increase cell proliferation in CRC cells through two mechanisms: binding FadA to E-cadherin and activating Toll-like receptor 4 (TLR4) [67]. Pathogenic bacteria-related molecular patterns and metabolites, such as deoxycholic acid (DCA) and lipopolysaccharide (LPS), can promote liver inflammation, fibrosis, and genotoxicity, activate antiapoptotic signaling pathways, and trigger immune responses that support the development of hepatocellular carcinoma (HCC) [68]. Colonization of the human gastric mucosa by H. pylori affects the plasticity and homeostasis of gastric epithelial cells and increases the carcinogenesis of gastric cancer [69].

In recent years, it has become evident that gut microbiota also affects several non-gastrointestinal cancers which exist in distant organs from the gut. For example, it has been reported that gut microbiota influences the development of breast cancer through the modulation of the immune system, the release of bacterial metabolites, and the modulation of estrogen levels [67]. Additionally, insulin-like growth factor-1 (IGF1) production stimulated by SCFAs from gut microbes influences the growth of prostate cancer via activating local prostate MAPK and PI3K signaling [68]. This finding indicated the presence of a gut microbiota-IGF1-prostate axis at the same time.

Despite the fact that the majority of studies have concentrated on the gut microbiome, accumulating evidence indicates that intratumoral microbes have multiple effects on the biological behavior of tumors. The resident lower airway bacterial flora may influence the carcinogenesis of lung cancer by inducing the host’s inflammatory response, producing bacterial toxins that impair the stability of the host’s genome, and releasing microbial metabolites that promote cancer [69]. Microbiome in the pancreatic cancer can facilitate tumorigenesis by inducing innate and adaptive immune suppression [70]. In addition to bacteria, pancreatic cancer fungi can promote the host complement cascade by binding mannose-binding lectin (MBL), thus promoting pancreatic ductal adenocarcinoma (PDAC) [71]. The intratumoral microbiome can accelerate the peogression of breast cancer by activating estrogen signaling, regulating the metabolism of cancer cells, promoting the development of local inflammatory responses and reducing the number of lymphocytes [72]. In addition to these aforementioned tumors, intratumoral bacteria have also been found in other types of cancer [73]. However, mechanisms between intratumoral microbiomes and development of these tumors are not well known.

The development of RCC is a complex process influenced by hereditary and environmental variables with distinct etiological processes. There is a close connection between the microbiota and these mechanisms with regard to the metabolism of food components, inflammation, immunological modulation, and the formation of genotoxin. Here we will highlight microbiota-related factors in RCC carcinogenesis and progression that may be modified and applied in the clinic (Table 1).

Table 1.

Important studies exploring the effects of microbiota on the development of RCC and mechanisms of action.

Study	Associated microbiota	Main findings	Potential mechanism	Reference
Routy et al., 2018	Gut microbiota, especially Bifidobacterium spp., Akkermansia muciniphila and Alistipes indistinctus	Oral supplementation with A. muciniphila could increase the recruitment of CCR9 + CXCR3 + CD4 + T lymphocytes into mouse RCC tissues	The abundance of certain bacteria in the gut microbiota (e.g. Bifidobacterium spp., Akkermanisa uciniphila, and Enterococci) influence the development of RCC by affecting anti-tumor specific immunity	[142]
Nyberg et al., 2020	Hepatitis C virus	Participants with HCV infection had a significantly higher risk of RCC (RR = 1.71)	Although the mechanism by which HCV increased the risk of RCC is not completely understood, the most important explanation is that HCV-associated chronic kidney disease (CKD) might play an important role	[107]
Liss et al., 2020	Oral microbiota in RCC	All 3 of those subjects with oral microbiome aggregates located within the RCC were noted to have high PD-L1 expression within the tumor thrombus (p = 0.05)	Microbiota can inhibit immune cell function to create an environment conducive to intravascular propagation of renal cancer.	[45]
Dai et al., 2021	Gut microbiota associated with tryptophan metabolite, including Agathobacter, Escherichia-Shigella, Romboutsia, and Akkermansia	AhR expression was up-regulated in RCC tissues. The proportion of Kyn was increased in RCC. After being treated with Kyn, the migration, invasion, and proliferation ability of human RCC 786-O cells were decreased	Gut microbiota could activate AhR through its tryptophan metabolite Kyn to mediate RCC metastasis.	[78]
Kovaleva et al., 2022	Total bacterial load in RCC	The group of RCCs with high content of PU.1 + cells(p = 0.013) and CD66b + cells(p = 0.007) in the stroma was characterized by a lower bacterial load In the tumors with high bacterial burden, the number of PU.1 + cells and CD66b + was associated with a poor prognosis(p = 0.037)	Tumor microbiome influence RCC progression by affecting the number and function of immune cells	[46]
Chen et al., 2022	“Five-genera” of gut microbiota: Blautia, Streptococcus, [Ruminococcus]_torques_group, Romboutsia, and [Eubacterium]_hallii_group	Blautia, Streptococcus, [Ruminococcus]_torques_group, Romboutsia, and [Eubacterium]_hallii_group were dominant and positively associated with ccRCC	Streptococcus lutetiensis promotes in vitro ccRCC proliferation, migration, and invasion via the TGF-signaling pathway	[126]

AhR, aromatic hydrocarbon receptor; HCV, hepatitis C virus; Kyn, Kynurenine; RCC, renal cell carcinoma; TGF, transforming growth factor

Metabolism of dietary components

Gut microbiota can affect RCC by influencing the levels of various metabolites such as dietary amino acids and short-chain fatty acids (SCFAs). RCC is sometimes referred to as a “metabolic disease” because of changes and disruptions in numerous metabolic pathways. Reprogramming of the tricarboxylic acid (TCA) cycle, glucose, and fatty acid metabolism is a common feature of all forms of RCCs [74]. Glutamine, tryptophan, and arginine metabolism are also altered to promote RCC oncogenesis and progression [74]. For instance, the gut microbiome mediates RCC metastasis through tryptophan metabolite kynurenine, which affects cell proliferation, migration, apoptosis, adhesion, and differentiation [75]. The effect of products from the bacteria metabolism on kidneys reflects the concept of “gut-kidney axis”. Some species of gut bacteria produce renal toxins, whereas protective gut microbiota produces SCFAs. The three most common SCFAs are acetate, butyrate, and propionate, which play a role in the repression of inflammation and cancer by altering cell metabolism, immune cell activation, and cell death in the intestine and other organs, including kidneys [76, 77] (Fig. 2a).

Trimethylamine oxide (TMAO), a renal toxin derived from microbial metabolites, accelerates renal tubular-interstitial fibrosis and kidney dysfunction [78]. A fecal microbiota transplantation study showed that mice receiving Eggerthella lenta (E. lenta) and F. nucleatum exhibited more severe renal fibrosis, glomerulosclerosis, and oxidative stress, and increased serum levels of uremic toxins, including p-cresol sulfate, phenylacetylglycine, phenyl sulfate, and indoxyl sulfate, while Bifidobacterium decreased the abundance of the aforementioned species and relieved renal impairment severity [79]. Gut bacteria harboring p-cresol- and indole-forming enzymes are overgrown in patients with kidney diseases, where they could promote fermentation of tyrosine and tryptophan with a consequent increase in circulatory levels of indoxyl sulfate, p-cresol, and p-cresyl sulfate [80]. Healthy renal tubules drain these uremic toxins via organic anion transporters (OATs) localized at the basolateral and apical cell membranes. Once uremic toxins such as indoxyl sulfate and p-cresol enter the renal tubular cells via OATs, they can stimulate the production of TGF-β1, chemokines, and free radicals, which can induce oxidative stress and inflammation in both tubular and glomerular compartments, leading to interstitial fibrosis and sclerosis, when in high concentrations [77]. Another study confirmed that oxalate-degrading bacterial taxa, including E. lenta, decreased in children who had kidney stones [81] (Fig. 2a). Moreover, patients with urolithiasis showed a large increase in proteolytic bacteria such as Clostridium which could increase the concentration of biogenic amines, indoles, ammonia, and cresol, adding up to the inflammatory pattern [82].

The reduction of butyrate levels in the intestinal, which results in an inflammatory pattern and functional instability in the urothelium (butyrate contributes to the trophism of the epithelium), contributes to RCC genesis and development [83]. It has been proven that butyrate metabolism also affects ccRCC TME. Tang et al. developed a predictive signature involving six butyrate-metabolism-related genes (Bu-Meta-GPS) to compute risk scores. In comparison to patients with low-risk scores, those with high-risk scores were characterized by a higher immunoscore, increased immuno-oncological targets (PD1, PD-L1, CTLA4, and CD19), and unique immune-cell infiltration, exhibiting a worse prognosis as a result [84]. Several bacteria have been identified as potential butyrate producers, like Fecalibacterium, Oscillospira, Ruminococcaceae, Eubacterium, and Coriobacteriaceae, which are deficient in gut microbiome of mRCC patients with worse prognosis [85]. Fecalibacterium prausnitzii is the largest producer of butyrate and the largest consumer of acetate [86]. In calcium oxalate lithiasis patients, Fecalibacterium prausnitzii depletes along with the reduction of Bifidobacterium promotes acetate production and then leads to a reduction in the energetic yield as well as in the availability of substrates to form other SCFAs, including butyrate [82].

Owing to the functional repertoire of the metagenome, the microbiota was found to be able to produce numerous other metabolites important for our physiology. The respective roles of some of these RCC-related metabolites have been reviewed elsewhere [74, 77, 87]. Importantly, these metabolites could be modulated independently or through manipulation of the microbiota to influence the risk and development of RCC.

Inflammation and immune regulation

Inflammation is the immune response to harmful stimuli like pathogens, poisonous substances, damaged cells, or radiation, which has the dual purpose of eliminating harmful stimuli and starting the healing process. Carcinogenesis in infected tissues is known to be accelerated by the inflammatory responses that accompany bacterial infections. Numerous chronic inflammatory situations cause vulnerable cells to undergo malignant transformation [88]. Long-term Helicobacter pylori (H. pylori) infection, for example, will cause gastric malignancies by inflammation-induced oxidative stress and DNA injury in some people. Similarly, enterotoxigenic Bacteroides fragilis (B. fragilis) causes colitis, stimulates the production of reactive oxygen and nitrogen species (ROS and RNS), raises levels of oxidative DNA lesions, and thus induces colonic tumors [89, 90]. Certain microorganisms promote RCC genesis via oxidative/nitrosative stress, implying that inflammatory processes may lead to DNA alterations and thus result in the inhibition or activation of transcription, the activation of signal transduction pathways, replication mistakes, and genomic instability [88, 91] (Fig. 2b). In addition, metastatic RCC (mRCC) has long been regarded as an “immunogenic malignancy” amenable to several immunotherapies, indicating that inflammation and immunological modulation are strongly associated with RCC.

Urinary microbiota might influence RCC in inflammatory illnesses like urolithiasis due to their intimate interaction with the immune system. A meta-analysis revealed an association between a history of kidney stones and an elevated risk of RCC in males [92]. A cohort study from the Netherlands also indicated that kidney stones were related to a higher risk of papillary renal cell carcinoma (pRCC) but not clear-cell RCC (ccRCC) [93]. Chronic inflammation and infection, which change the proliferation of urothelial cells and bring in the resulting tumor formation, have been determined to be the fundamental reasons for the association between RCC and kidney stones [93, 94]. Inflammation is a hallmark and a known risk factor for RCC, according to epidemiologic research since those with UTI are more likely than the general population to acquire the malignancy [49]. In a recent study, it was determined that 18% of RCC patients had recurrent UTIs in the 12 months before diagnosis and that 73% of RCC patients had presented with at least one relevant symptom [95]. In cases of severe UTIs, it is common to find multiple types of pathogens, whereas E. coli is the most common kind of pathogen in uncomplicated UTIs [96]. The microbial composition of kidney stone sufferers was significantly different from that of healthy participants, with the former exhibiting a dramatic reduction in microbial diversity [97]. In individuals with kidney stones, pro-inflammatory bacteria were prevalent while anti-inflammatory bacteria were scarce [97]. Several studies have also attempted to assess the effect of the renal microbiome on the advancement of RCC with the existence of kidney stones [40–43]. Compared to mice with calcium oxalate deposits or pyelonephritis alone, animals infected with glyoxalate and uropathogenic E. coli (UPEC) had greater bacterial loads, increased kidney calcium oxalate deposits, and a greater kidney innate immune response [40]. Furthermore, the inflammatory processes provide an important interface for crosstalk between the urinary microbiota and the tumor microenvironment (TME).

TME consists of all structures recruited to the organ, including vascular vessels, immunological infiltrates, fibroblasts, and extracellular matrix. Emerging evidence has concluded that the local microbiota plays a crucial role in the development of TME in a wide variety of cancer types [98]. In RCC, the predominant immune infiltrating cells are macrophages, T-cells, and neutrophils [99]. Kovaleva et al. found an inverse connection between the level of bacterial load and the tumor stroma phenotype for PU.1 macrophages and CD66b neutrophils [46]. The phenotypes and activities of macrophages associated with tumors were affected by malfunctioning and oxidatively stressed mitochondrial DNA (mtDNA), which may partially explain the mechanism underlying the effect of bacteria on the phenotypes of RCC-related immune cells [100]. In addition, some microbes contribute to tumor growth by creating an immunosuppressive microenvironment [101, 102]. A positive link existed between renal cancer thrombus and PD-L1 expression in primary renal malignancies with discordant oral microbiome [45]. Fusobacterium nucleatum (F. nucleatum), a member of the oral commensal flora, has been found to inhibit human T-cell responses and contains immunosuppressive properties [101]. Based on microbiome analysis and PD-L1 expression test in ccRCC with tumor thrombus, Liss et al. explained that F. nucleatum is more prevalent in RCC tumor tissue than in normal surrounding tissues and tumor thrombus. Besides, they observed that a single tumor sample with high levels of F. nucleatum also included the greatest levels of PD-L1 expression within the tumor thrombus [45].

Viruses oncogenesis

Protein post-translational modifications (PTMs) are adaptable tools utilized by both prokaryotic and eukaryotic cells to modulate essential protein function. PTMs include the addition of simple chemical groups (like phosphate, acetyl, methyl, or hydroxyl groups), more complex groups (like adenosine monophosphate, adenosine diphosphate-ribose, sugars, or lipids), and small polypeptides (like ubiquitin or ubiquitin-like proteins), as well as modifications to specific amino acid side chains. PTMs are increasingly recognized as key strategies for many viruses to modulate host proteins critical for their infection [103]. The best-known example is p53 and Rb inactivation by HPV E6/E7, which are thought to have a role in carcinogenesis for high-risk HPVs (HPV-16, -18, and − 31) [57]. In a case-control study, HPV-16 and HPV-18 were found to be associated with RCC [61]. E6 binds and degrades p53 through an E3 ubiquitin protein ligase called cellular E6-associated protein (E6-AP) [57] (Fig. 2c). E6 and E7 also stimulate the phosphorylation of Rb in different approaches, promoting cell cycle progression [57]. Participants with HCV infection had a significantly higher risk of RCC [104].Tracking for the HCV- and RCC-related protein with further detection of common protein, only NY-REN-54 was found, which may explain the cause-outcome relationship between HCV virus infection and RCC via disruption of autophagic response caused by ubiquitin-protein ligase [105].

EBV seems to exert a rather complex role in RCC. Shimakage et al. examined the EBV expression by indirect immunofluorescence staining, revealing strong signals of Latent membrane protein 1 (LMP-1) and Epstein–Barr virus nuclear antigen 2 (EBNA-2) in RCC and nephroblastoma cells, which suggested an oncogenic and tumor-promoting role of EBV in RCC and nephroblastoma [58]. The signal region of LMP-1 contains three sites: carboxy-terminal activating region 1 (CTAR1), CTAR2, and CTAR3 that directly interact with some cell factors and activate NF-κB, JNK (c-Jun N-terminal kinase), p38 MAPK, JAK/ STAT, and PI3K/Akt signal pathways which are involved in cell cycle progression [106]. Studies have characterized the ability of LMP-1 to recruit TRAFs (TRAF-1, -2, -3, and − 5) to CTAR1 [107]. CTAR1 has the unique ability to induce the expression of epidermal growth factor receptor (EGFR) and TRAF-1 [108]. It can deregulate molecules involved in G1/S cell cycle progression, such as an inhibitor of differentiation or DNA binding 1 (Id1), the CDK inhibitor p27Kip1, CDK2, and Rb [109]. LMP-1 regulates telomerase activity through the p16INK4A/Rb/E2F1, PI3K-AKT, and JNK signaling pathways to promote cell immortalization [110]. Hömig-Hölzel et al. found that B cell-specific expression of LMP-1/CD40 activated the MAPKs/JNK/ERK and the noncanonical NF-κB pathway (Fig. 2c). The concerted action of these signaling pathways ultimately leads to B cell lymphomagenesis [111]. Also, LMP-1 can induce invasiveness and metastasis factors, for instance, matrix metalloproteinase 9, which disrupts the basement membrane [57]. EBNA-2 is a nuclear protein that has a critical role in lymphocyte immortalization. The P3HRI variant of EBV has a deletion encompassing EBNA-2, which is not immortalizing and fails to induce these types of changes in cellular gene expression [57]. LMP-1 and c-Myc are directly activated by EBNA-2, which is an important step in the process of EBV-induced proliferation and immortalization [109].

Production of genotoxins

Although a favorable host cell environment will be created to resist the toxin-mediated assault strategies from pathogenic bacteria, their toxins, likely as a side effect of their mode of action, can also contribute to carcinogenesis. Mechanistic insights have been provided for various bacterial genotoxins, including cytolethal distending toxins (CDT) synthesized by gram-negative bacteria, colibactin synthesized by B2 phylogroup Escherichia coli, and typhoid toxin synthesized by Salmonella enterica serovars, which can induce DNA damage and may result in irreversible cell cycle arrest or death of the target cells, therefore causing malignant transformation [52, 112, 113] (Fig. 2d).

CDT is secreted by various Gram-negative bacteria that belong to the Gamma and Epsilon class of Proteobacteria, including S. Typhi, E. coli, Shigella dysenteriae, and Campylobacter jejuni. CDT is comprised of three subunits, CdtA, CdtB and CdtC. CdtA and CdtC ensure the uptake and cellular delivery of CdtB, which harbors the catalytic activity of CDT and causes double‐strand DNA breaks (DSBs) in host cells. After the host cell is bound and internalized by subunits CdtA and CdtC, CdtB undergoes retrograde transport via the endosomes and Golgi to the endoplasmic reticulum (ER), where it undergoes ER‐associated protein degradation‐mediated translocation into the cytosol. The CtdB subunit is then imported into the nucleus and leads to DSBs [114]. These DSBs result in DNA damage responses (DDR) that cause G1‐S cell cycle arrest in endothelial and epithelial cells, both G1‐S and G2‐M cell cycle arrest in fibroblasts and apoptosis in haematopoietic cells that are particularly sensitive to these toxins. As a result, this toxin can locally eliminate immune cells and therefore provide an obvious advantage for the bacteria. Prolonged exposure to sublethal doses of CDT can impair DDR sensor functionality, resulting in impaired detection of DNA damage and the accumulation of mutations. At the same time, mitogen‐activated protein kinase (MAPK) activity is upregulated by activation of the neuroepithelial cell‐transforming gene 1 protein (NET1) and the GTPase RhoA, which supports the survival of the toxin‐exposed cells [115]. Consequently, these cells can propagate with DNA mutations and deletions that arise during the repair process, thus inducing genomic errors that underlie cancer formation.

Aside from the CDT toxins, the DNA-interacting colibactin toxin has also been associated with the formation of DSBs and the introduction of genomic instability. Colibactin is secreted by E. coli strains of the phylogenetic group B2 that harbors the polyketide synthetase (PKS) island [116]. Bacteria that harbor the PKS genomic island can induce DSBs in eukaryotic cells and then activate the DNA damage checkpoint pathways ATM, CHK1, and CHK2. This results in CDC25 and cyclin-dependent kinase 1 (CDK1)‐mediated G2‐ to M-phase cell cycle arrest and finally in apoptotic cell death [117–119]. As a side effect of their mode of action, colibactin-producing bacteria also induce incomplete DNA repair, chromosomal instability, and anchorage-dependent colony formation, phenotypes that can promote cancer formation [120, 121]. Genotoxin colibactin is produced by PKS + E. coli alkylates DNA, resulting in DNA adducts in colonic epithelial cells [122]. It is assumed that the ability of PKS + E. coli to generate DNA adducts and the involvement of colibactin in cancer development or progression may also contribute to RCC development.

The bacteria also contribute to cancer development by directly modulating intracellular signaling pathways [49]. An intuitive proof is that Streptococcus lutetiensis isolated from fecal samples of ccRCC patients was able to promote ccRCC proliferation, migration, and invasion via the TGF-β signaling pathway in vitro [123]. Unlike toxins that contribute to carcinogenesis by introducing DSBs and genomic instability, several toxins work by inducing resistance to cell death signaling and by promoting proliferative signaling. These toxins are generally secreted by pathogenic bacteria that favor cell life as part of their infectious cycle and thus directly benefit from host cell survival. An example of such a toxin is the B. fragilis toxin (BFT) which binds to intestinal epithelial cell receptors and stimulates cell proliferation by cleavage of the tumor suppressor protein E-cadherin [124, 125]. E-cadherin is involved in the formation of intercellular adhesion junctions in the intestinal epithelium and in cellular signaling, proliferation, and differentiation via activation of the β‐catenin/Wnt and NF‐κβ signaling pathways [126–128]. F. nucleatum, abundant in RCC tissue, also promotes intestinal tumorigenesis through binding to E-cadherin and stimulating the β-catenin signaling via its FadA adhesin [129]. Likewise, bacteria may render the host susceptible to oncogenic transformation in the kidney through the Wnt/ß-catenin pathway. Increased ß-catenin induces several pro-inflammatory and tumor-promoting genes, including cyclooxygenase-2 (Cox-2). Cox-2 is the rate-limiting enzyme in the biosynthesis of prostaglandins. It has gained recent interest because it is overexpressed in many human cancers and has been linked to increased tumor invasiveness via overexpression of the cellular oncoprotein Bcl-2 and suppression of apoptosis [130, 131]. Data from animal and human studies also suggest that a portion of RCCs overexpress Cox-2 [130, 132]. Many E. coli species produce a toxin known as a cytotoxic necrotizing factor (CNF), which has been shown to induce elevated expression levels of Cox-2 in murine fibroblasts [133].

Potential translational applications of microbiota

Currently, the diagnostic sensitivity of upper urinary tract urothelium carcinoma is highest in the FISH examination, followed by a CT scan and urine cytologic examination [134]. The microbiome is a predictor of disease severity and therapy results and can be modifiable for cancer treatment [113]. The genetic heterogeneity of microbes provides an opportunity to diagnose and locate disease, using renal microbiota and gut microbiota as diagnostic biomarkers. Furthermore, the associations between bacterial markers and treatment efficacies or clinical outcomes increase the potential of utilizing these markers for treatment prediction and prognostication [8, 123, 135–137]. Modulation of the renal microbiota may also represent a novel and important adjunct to current cancer therapeutic modalities. The microbiome is personalized and can be analyzed to provide individualized management for each patient with consideration of the molecular peculiarities of the tumor (Fig. 3).

Fig. 3.

Clinical applications of microbes in RCC care. Some potential clinical applications for harnessing the microbiota in RCC are depicted and include the development of screening, prognostic and predictive biomarkers, and microbiota modulation for RCC prevention and treatment. This figure was created with Adobe Illustrator

The microbiome has shown great significance in diagnosis and predicting prognosis. The microbiota difference between renal malignancy and healthy kidney individuals is a potential diagnostic signature for RCC [45–48]. Several species appear in RCC tissue only, such as Cyanophora paradoxa, Spirosoma Navajo, Phaeocystis Antarctica, Euglena mutabilis, and Mycoplasma vulturii [47]. In adjacent renal tissues, Comamonadaceae is a notably more prevalent bacterial family [47, 48, 53]. In a study conducted in China, Chen et al. found significant differences in the gut microbiota distribution between the ccRCC patients and the healthy control group. They used five genera positively associated with ccRCC: Blautia, Streptococcus, [Ruminococcus]_torques_group, Romboutsia, and [Eubacterium]_hallii_group to diagnose ccRCC (AUC = 93.3%) [123]. Except for the differences with benign tissues, the taxonomic composition of the microbiome in different RCC histotypes varies as well. For example, bacteria of the Tenericutes phylum were present in ccRCC and papillary RCC (pRCC) and were absent in normal tissue and chromophobe tumors. For ccRCC, the most represented genera were Cutibacterium, Sphingomonas, Roseomonas, Staphylococcus, Mesomycoplasma, Massilia, Escherichia Shigella, and Photobacterium [46]. Additionally, there was a trend of decreasing microbiota richness of RCC tissue with increasing tumor grade [48]. The relative abundance of Rhodoplanes was significantly higher in grade I RCC tissue than that in grade II tumor tissue, indicating that the relative abundance of Rhodoplanes had a correlation with the tumor grade [48]. However, basic questions remain about the functional impacts of this intratumoral microbiota and whether they are parasitic, symbiotic, or passive passengers, and a biopsy specimen is required for analysis, limiting its diagnostic utility [138].

Recent evidence also provided an interesting insight into the microbiome in predicting the prognosis of RCC. Tumor microbiome composition in combination with macrophage phenotype offers a new approach to predicting RCC patients’ survival. Kovaleva et al. demonstrated that the number of PU.1 + cells and CD66b + cells had prognostic significance in tumors with a high bacterial load, where they were associated with a poor prognosis (HR = 4.046; p = 0.037) [46]. Renal and gut microbiomes provide potential biomarkers to predict the prognosis of systematic therapy and immunotherapy of RCC. It has been identified that incongruous oral microbiota within primary RCCs had an association with PD-L1 expression in the propagated intravascular component of RCC, which implied that those microbiomes might serve as a biomarker for predicting the efficacy of immunotherapy (p = 0.05) [45]. Several clinical studies have attempted to characterise associations between the microbiome and RCC (Table 2). In the gut microbiome, Akkermansia muciniphila were found to increase in relative abundance in patients receiving anti-PD-1 ICIs and was associated with positive clinical outcomes in three study cohorts [8, 135, 139].

Table 2.

Summary of microbiota intervention clinical trials in RCC patients

Study	Patients(n)	Study design	Cancer therapy	Microbiota intervention(s)	Primary outcome measures	Findings or results	Clinical identifier	Reference
Derosa et al., 2020	69	Phase II randomized clinical trial	Immune checkpoint blockade	Antibiotics (ATB)	Objective response rate	Recent ATB use reduced objective response rates (from 28–9%, p < 0.03)	NCT03013335	[8]
Ianiro et al., 2020	20	Randomized Controlled Trial	Tyrosine kinase inhibitors	Fecal microbiota transplantation (FMT)	Resolution of diarrhoea	Donor FMT was more effective than placebo FMT in treating TKI-induced diarrhoea (70% vs 0%)	NCT04040712	[139]
Dizman et al., 2021	20	Randomized Controlled Trial	Tyrosine kinase inhibitors	Probiotic	Clinical benefit rate	Clinical benefit rate was similar in probiotic-supplemented versus probiotic-restricted arms (70% vs. 80%, p = 0.606)	NCT02944617	[140]
Dizman et al., 2022	30	Phase I randomized clinical trial	Anti-PD1 plus anti-CTLA4	CBM588	Relative abundance of Bifidobacterium spp.	No significant differences in the relative abundance of Bifidobacterium spp. associated with the addition of CBM588 to nivolumab-ipilimumab were detected(p > 0.05) PFS was significantly longer in patients receiving nivolumab-ipilimumab with CBM588 than without (12.7 months versus 2.5 months, HR = 0.15, p = 0.001)	NCT03829111	[150]
Ninkov et al., 2023	10	Phase I randomized clinical trial	Anti-PD1 plus anti-CTLA4	Fecal microbiota transplantation (FMT)	Peripheral MAIT cell frequencies and functions	MAIT cells maintained their frequencies and improved their functions in RCC patients after FMT	NCT04163289	[146]

ATB, Antibiotics; CBM588, Clostridium butyricum CBM 588 probiotic capsules; MAIT, mucosa-associated invariant T; RCC, renal cell carcinoma; CTLA4, cytotoxic T lymphocyte associated antigen 4; FMT, fecal microbiota transplantation

In patients receiving vascular endothelial growth factor–tyrosine kinase inhibitors (VEGF-TKIs) with clinical benefit (vs. no clinical benefit), the presence of excessive amounts of Barnesiella intestinihominis and Akkermansia muciniphila was confirmed to improve the drug efficacy (p < 0.001 and p = 0.0056, respectively) [137]. VEGF-TKI alters the composition of the microbiota, and the efficacy of VEGT-TKIs is also influenced by gut microbiota at the same time. Antibiotics and probiotics combined with VEGF-TKI greatly impact the prognosis of RCC patients. Hahn et al. declared that targeting stool Bacteroides spp. with antibiotics improved PFS in mRCC patients receiving first-line VEGF-TKIs in a duration-dependent manner (HR = 0.92; p = 0.04), while targeting non-Bacteroides species did not affect PFS in patients receiving VEGF-TKIs (HR = 0.90; p = 0.67) [140]. Further studies are in progress in which fecal bacteria from patients responding to VEGF-TKIs treatment will be transferred to non-responding patients. Hypothetically, changing the microbiome profile into healthy individuals or patients with good prognoses would enable patients better respond to VEGF-TKIs therapy. As VEGF-TKIs are wide-used drugs for the treatment of RCC, the degree of tolerance to TKI is an important factor affecting the medical strategy. Additionally, because almost half of the patients with mRCC taking VEGF-TKIs have diarrhea, it is important to emphasize the link between the gut flora and VEGF-TKI-induced diarrhea [141]. In mRCC patients receiving VEGF-TKIs, higher levels of Bacteroides spp. and lower levels of Prevotella spp. were found in stool samples of patients with diarrhea, compared with those without diarrhea [142]. Another study also discovered that the abundance of Actinobacteria was decreased in mRCC patients receiving sunitinib (one of VEGF-TKI approved for treatment in patients with mRCC) with severe diarrhea [85]. A randomized clinical trial involving mRCC patients with TKI-related diarrhea showed that fecal material from healthy donors greatly relieved their symptoms (70% vs. 0%, p = 0.003), while A. muciniphila was shared between healthy donors and patients with improved outcomes after receiving feces from healthy donors [136].

Growing evidence has connected the gut microbiome to immunotherapy response as our understanding of the microbiota and RCC develops. In patients with mRCC, peripheral blood mucosa-associated invariant T (MAIT) cells maintained their frequencies and improved their functions after receiving fecal microbiota transplantation (FMT) [143]. In other words, FMT could improve MAIT cell functions and enhance anti-tumor immunity. Given the function of the gut microbiota in modulating host immunity, it is fairly intuitive that it could significantly impact response and toxicity to immunotherapy. Based on several retrospective studies, antibiotic therapy before ICI treatment in patients with RCC received worse outcomes [5, 144]. Yu et al. found that antibiotics compromised the efficacy of ICIs, presumably because antibiotics altered the taxonomic beta diversity and composition of intestinal microbiota [145]. However, in other cases, changes might be therapeutic; for example, TKIs induced a significant and prototypic microbiota shift including immunostimulatory commensals like Alistipes senegalensis and A. muciniphila that could be harnessed to improve the efficacy of ICIs in RCC patients [8]. Previous research has demonstrated that CBM588, a bifidogenic live bacterial product, could significantly increase the abundance of Bifidobacterium spp. in the intestine [146], which might enhance the effectiveness of immunotherapy in RCC. Dizman et al. suggested that CBM588 appeared to extend the progression-free survival in patients with mRCC treated with nivolumab-ipilimumab (12.7 months vs. 2.5 months, HR = 0.15, p < 0.001) [147]. These studies provided preliminary evidence that microbiota alterations affect the therapy of RCC. More in-depth mechanistic studies of modulation approaches and better clinical understandings are needed before applying FMT, prebiotics, probiotics, postbiotics, and antibiotics for a favorable outcome in response to therapies.

Outlook

There is an extensive diversity of gut microbiomes in individuals depending on host genetics, diet, age, geographic location, toxin/carcinogen exposure, hormones, mode of birth, and antibiotics [138, 148, 149]. Adding to that complexity, microbes interact with the host and the tumor in a diverse and context-specific manner. It has been shown that gut microorganisms have a distinct effect on RCC by regulating metabolism and immunology. Even though research on gut microorganisms is currently popular, the renal microbiome appears to be more closely linked to RCC. Now, several studies with limited sample sizes have offered preliminary insights into renal bacteria, large-scale investigations are required to shed light on the close connection between RCC and the renal microbiome. However, many challenges exist in renal microbiome detection. The sensitivity and specificity of technology, low biomass relative to the host, and disturbance from reagents or environmental contaminants should be taken into account. Further, understanding the interactions between microbiome, hosts, and tumors for the risk of RCC would help to build a unique screening system and improve RCC prevention and treatment based on individual characteristics.

Challenges

Currently, the enhanced culture technique (EQUC) and 16S rRNA sequencing are used for urinary microbiome detection. Each technique possesses distinct advantages and disadvantages. Deep 16S rRNA sequencing is a high-throughput technology that facilitates rapid screening at great depth, permitting researchers to obtain a broad and deep overview of the microbiota without the need to cultivate it. However, the advantage provided by the speed and depth of the high-throughput technology is balanced by the inability to reliably identify bacteria below the genus level [44]. In addition, for samples with low microbial abundance, it is necessary to prevent cross-amplification of the host’s mitochondrial DNA which has some sequence similarities to the 16S rRNA bacterial gene. Although current experiments are detecting kidney microbes by 16S rRNA sequencing, it may be possible to implicate EQUC, which has been utilized to detect urine microbes [43]. Unlike 16S rRNA sequencing, EQUC can capture the bacterium, but only if it can be cultivated. EQUC procedures could also be used to determine if the sequences identified in the urine samples represent living bacteria.

Sampling for renal microbiota analysis is a problem as well. An intravascular portion of the renal tumor is not typically biopsied and would be invasive, which is why studies focused on the intratumor microbiota profile [45]. The microbiota obtained from a kidney biopsy obviously cannot be used for screening. Taking urine and analyzing its microorganisms may be useful for screening in the future. Addedly, proper sampling to obtain adequate amounts of microorganisms and avoid contamination is also a concern in the sampling process. On the one hand, the skin microbiome can be a risk factor for bacterial contamination of samples in laparoscopic surgery. On the other hand, surgical instruments are all sterile but not DNA-free, so background DNA noise is almost inevitable and environmental control is important [44]. Moreover, there is always a concern regarding contamination during fixation and embedding of the tissue during germ identification [47].

Future directions

Administration of bacterial consortia or “designer probiotics” could provide a more feasible method of microbial manipulation in the clinical setting. Implementing regimens that supply beneficial gut bacteria or renal microbiome through probiotics/prebiotics may lessen the risk of RCC. The associations between microbiota and the activity of systemic lymphoid tissues have stimulated interest in microbial modulation as a powerful immunotherapeutic modality. There is a prospective randomized study sought to assess if a Bifidobacterium-containing yogurt product could modulate the gut microbiome and clinical outcome from VEGF-TKIs. Although the clinical benefit rate was similar in probiotic-supplemented versus probiotic-restricted arms, probiotic supplementation successfully increased the Bifidobacterium spp. levels [137]. Microbiota-modulating strategies such as probiotics, antibiotics, “urinary microbiota transplantation”-referring to the already known fecal microbiota transplantation, and a synthetic urinary microbiota for transplantation might lead to an effective treatment for RCC patients. However, many questions about their specificity, prevalence, and stability during cancer treatment or utility during antibiotic administration remain to be answered and must be addressed before clinical deployment [138].

Precision medicine, also called personalized medicine sometimes, has been defined as an approach that uses a person’s genetics, biomarker, or psychosocial characteristics, to meet the needs of the individual patient and determine the most effective treatment and prevention methods [150]. Microbiome-based treatment methods for precision medicine are gaining momentum where individual host-microbiome patterns can be integrated with other personal health-related information for evaluation of suitable therapy [151]. Significant heterogeneity of gut and urinary microbiota among individuals provides a new theoretical basis for the application of precision medicine in RCC. The microbiome is not only a target but also a possible biomarker for identifying therapy choices in precision medicine. The resulting progress in precision medicine offers new insight into tumor interventions including narrow-spectrum antibiotics, probiotics, and microbiota transplantation.

Authors’ contributions

The idea for the article is from KW, XM, ZL and JZ. ZY, ZZ, and FS designed the outline of this review. KW and YL collected and analyzed the related publications and wrote the main manuscript text. KM and WZ assisted in the writing of the manuscript. YL, KM, WZ critically revised the manuscript. KW, YL, KM and WZ prepared Figs. 1, 2 and 3. All authors reviewd and approved the final manuscript.

Funding

This work was financially supported by the National Nature Science Foundation of China (Project Nos. 81972393).

Data Availability

Not applicable.

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval

Not applicable.