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Tumor-initiating and metastasis-initiating cells of clear-cell renal cell carcinoma

Abstract

Clear-cell renal cell carcinoma (ccRCC) is the most common subtype of kidney malignancy. ccRCC is considered a major health concern worldwide because its numbers of incidences and deaths continue to rise and are predicted to continue rising in the foreseeable future. Therefore new strategy for early diagnosis and therapeutics for this disease is urgently needed. The discovery of cancer stem cells (CSCs) offers hope for early cancer detection and treatment. However, there has been no definitive identification of these cancer progenitors for ccRCC. A majority of ccRCC is characterized by the loss of the von Hippel-Lindau (VHL) tumor suppressor gene function. Recent advances in genome analyses of ccRCC indicate that in ccRCC, tumor-initiating cells (TICs) and metastasis-initiating cells (MICs) are two distinct groups of progenitors. MICs result from various genetic changes during subclonal evolution, while TICs reside in the stem of the ccRCC phylogenetic tree of clonal development. TICs likely originate from kidney tubule progenitor cells bearing VHL gene inactivation, including chromatin 3p loss. Recent studies also point to the importance of microenvironment reconstituted by the VHL-deficient kidney tubule cells in promoting ccRCC initiation and progression. These understandings should help define the progenitors of ccRCC and facilitate early detection and treatment of this disease.

Background

Clear-cell renal cell carcinoma (ccRCC) constitutes the majority (up to 70%) of primary RCC [1,2,3]. Many ccRCC patients present notable symptoms (hematuria, anemia, cachexia, and flank pain) only in advanced stages [4], making early treatment difficult. The majority (50–60%) of ccRCC cases are diagnosed incidentally via noninvasive imaging, and 30–50% of the cases are diagnosed at metastatic stages [5]. Notably, while the 5-year survival rate of early-stage ccRCC can be up to 90%, that of metastasized ccRCC is only about 12% [5]. These statistics point to the need for early detection and treatment of ccRCC.

The first critical genetic event of sporadic ccRCC is the haploid loss of the short arm of chromosome 3 (3p loss), which is detected in almost 90% of patients [6, 7]. The genomic region of 3p loss encompasses four well-recognized tumor suppressor genes (VHL, PBRM1, BAP1, and SETD2) [8,9,10,11]. Inactivating mutations (loss-of-heterozygosity) or epigenetic changes (mainly promoter hypermethylation) of the tumor suppressor gene VHL in particular are the main drivers of ccRCC, while loss of PBRM1, BAP1 or SETD2 is subordinate to VHL loss [12, 13]. Interestingly, PBRM1, BAP1, and SETD2 are involved in chromatin remodeling, suggesting that widespread epigenetic changes, not specific genetic mutations besides those in VHL, can contribute to ccRCC formation.

Currently, computed tomography and magnetic resonance imaging are the mainstays of ccRCC diagnosis [14, 15]. Yet, these two methods’ clinical application and prediction process are costly and still largely dependent on subjective human interpretation. One obstacle to accessible diagnostic strategy is that there are as yet no proven biomarkers for early-stage ccRCC. Even though various potential markers have been proposed, very few proved useful in clinical settings [16,17,18]. One promising diagnostic strategy may be based on the discovery that early ccRCC shared common serum/urinary inflammatory signatures with chronic kidney disease (CKD). Indeed, mounting evidence has implicated tissue inflammation in the tumorigenesis of ccRCC [19,20,21,22,23], and CKD has proved an important risk factor for ccRCC [24, 25]. However, accessible methods that can differentiate inflammatory kidney disease and early kidney cancer remain elusive. For this purpose, the presence of cancer stem/progenitor cells, combined with kidney inflammatory markers may offer an opportunity for early diagnosis [26,27,28]. The potential inflammatory markers include interleukin-6 (IL-6), a prominent tissue and serum inflammatory cytokine [29, 30]; kidney injury molecule-1 [KIM-1, also known as T-cell Ig and mucin domain-1 (TIM-1)], a serum and urine biomarker for human renal tubule injuries and kidney cancer [31, 32]; neutrophil gelatinase-associated lipocalin [NGAL, also known as lipocalin2 (LCN2)], a tissue and serum marker associated with inflammatory disease and cancer [33, 34]; and fibroblast growth factor 23 (FGF23), a growth factor involved in decreasing reabsorption of phosphate in the kidney and a marker for kidney disease [35, 36].

Cancer stem cells: are they tumor-initiating or metastasis-initiating cells?

The CSC theory originated from the study of teratocarcinoma, in which the cancerous growth contains a mixture of differently differentiated cell types [37]. The theory suggests that there exists a self-renewing primordial cell population that gives rise to the tumor mass containing progenies with different degrees of differentiation, while the progenitor clone can also directly give rise to malignant cancer, hence the term CSC. The theory therefore can also explain the conundrum that in clinical settings, occasionally metastasis can occur before the primary tumor is detected.

Indeed, CSCs have now been identified in a wide range of cancers [38]. However, whether the currently used term CSCs truly indicates the progenitor cells that initiate the growth of a tumor remains unresolved. The debate is also still ongoing as to whether malignant cancer originates from CSCs or is the result of clonal evolution [39], since with the exception of rare fast growing, highly aggressive cancer cases, the development of cancer malignancy is time-dependent and can be correlated with the size of primary tumors. This suggests that the hierarchical clonal evolution model, as opposed to the model of preexisting CSCs, may still be valid. One of the problems likely lies in the interchangeable usage of CSCs to depict TICs and MICs, because of the unspecified distinction between the two populations. In the case of ccRCC, it has been observed that not all VHL-deficient cells develop into metastatic ccRCC [40], and loss of chromosomes 9p and 14q contributes to ccRCC metastasis subsequent to VHL loss [41]. This indicates that VHL loss is necessary for tumor growth but insufficient for metastasis. Therefore such distinction, as will be discussed in this review, is relevant in regard to ccRCC. TICs, or sometimes called cancer cells of origin, are tumorigenic cells exhibiting features of stem cells, whereas MICs, although born from TICs, foster additional attributes such as the spread and recurrence of malignancy [42].

In this review, we will use the term CSC only when the cited literature made no distinction between the origin of primary tumor and the origin of metastatic subclone. When appropriate, we will use TIC and MIC to specify the two events.

The origin of cancer stem cells

Two mechanisms have been proposed to account for the origin of CSCs: either they are mutated adult stem cells (normal stem cells that acquire mutations) or mutated differentiated cells that acquire progenitor features (Fig. 1). The former can be called “mutated stem cell” theory and the latter “dedifferentiated mutant cell” theory.

Fig. 1
figure 1

An alternative model of the origin of ccRCC. Two mechanisms are proposed to explain the origin of CSCs: either they are mutated stem cells (left) or dedifferentiated mutant cells (right). The former suggests that CSCs originate from adult stem cells that accumulate mutations. In the latter theory, cellular changes and microenvironmental factors can transform differentiated cells into malignant, dedifferentiated cells. The development of ccRCC is likely a hybrid model (shaded pathway on the left), in which normal stem cells with 2 hits in the VHL gene, one of which involves chromosome 3p loss, become TICs. The TICs then undergo subclonal evolution to generate metastatic subclone, which constitutes MICs

In the “mutated stem cell” theory, the origin of CSCs is adult stem cells that accumulate pro-tumorigenic mutations. From whole-genome sequencing of adult stem cells (clonal organoid cultures derived from primary multipotent cells) of the small intestine, colon, and liver of human donors with ages ranging from 3 to 87 years, it was revealed that mutations accumulate steadily over time, at a rate of approximately 40 mutations per year [43]. It is therefore conceivable that a “right hit,” or a combination of critical hits, in the adult tissue stem cells can render these stem cells tumorigenic. For example, deletion of Apc in long-lived Lgr5+ intestinal stem cells leads to transformation of the stem cells within days. The transformed stem cells remain at the crypt bottom, forming microadenomas exhibiting unimpeded growth, and become macroscopic adenomas within 3–5 weeks. Importantly, the same Apc deletion fails to drive intestinal adenoma formation when introduced in more differentiated cells [44].

In the “dedifferentiated mutant cell” theory, mutations accumulated in differentiated cells can induce cellular changes such as epithelial-to-mesenchymal transition (EMT) that transforms the benign cells into malignant, dedifferentiated cells. In a landmark study, Mani et al. [45] demonstrated that the transformed human mammary epithelial cells showed transplantable tumor formation and metastasis-initiating ability through activation of EMT (ectopic induction of TGF-β signaling or ectopic expression of either Twist or Snail transcription factors). This study reconciled two seemingly contradictory aspects of cancer initiation: if cancer stem cells exist at the beginning of cancer formation, why the development of malignant cancer is largely time-dependent? The answer therefore lies in the need to accumulate the “right” mutations that induce, in the case of Mani et al. study, EMT, or other oncogenic processes. Besides EMT, differentiated cells can also be reprogrammed to exhibit tumorigenic potential by activation of c-MYC and other “Yamanaka factors” including OCT3/4, SOX2, and KLF4 [46,47,48,49,50]. These findings also explain why in the studies using clonal selection of metastatic cancer cells, multiple and often inconsistent candidates of CSCs have been the result, since there may be more than one genetic pathways that can induce malignancy.

The implication of these studies suggests that TICs and MICs reside in temporally different loci during progression of cancer. The genomic sequencing of a large cohort of ccRCC samples [41, 51], including normal-metastasis pairs, has suggested that an alternative model is likely the case for ccRCC (Fig. 1); that is, mutated stem cells give rise to TICs that form the stem of the phylogenetic tree of primary tumor growth, while dedifferentiated mutant cells initiate the process of subclonal evolution from which the metastatic subclone eventually emerges (Fig. 2). Therefore, the presence of TICs or their molecular signature can serve as early diagnostic markers and treatment targets; while MICs may be the targets for treatment against metastasis of already developed tumor mass. Next, we will discuss the nature of ccRCC stem/progenitor cells.

Fig. 2
figure 2

Adapted from Turajlic et al. [41] and Mitchell et al. [51]

Genomic landscape of ccRCC tumor initiation and metastatic subclonal evolution. Two broadly defined scenarios can account for the initiation and progression of ccRCC. The RSPCs, expressing stem/progenitor cell markers such as Notch or Wnt signaling and CD133 or CD105, first acquire 3p loss (encompassing the VHL tumor suppressor gene), and begin a slow clonal expansion lasting 5–20 years before the appearance of TICs when the second allele of VHL is inactivated, which leads to expression of inflammatory markers such as KIM-1 and HIF targets such as CXCR4. The appearance of TICs initiates subclonal evolution that can last 10–30 years, giving rise to various genetically distinct benign subclones, before the emergence of MICs, which is often accompanied by the 9p21.3 loss. In rare cases, TICs, and hence MICs, can arise from VHL+ cells. These are not included in this general description. Early appearance (i.e., close to or on the phylogenetic stem) of the metastatic subclone characterizes low primary tumor heterogeneity and rapid progression of the disease (left), and late appearance (i.e., after multiple subclonal branching events) of metastatic subclone characterizes high primary tumor heterogeneity and slow progression of the disease (right). RSPC: renal stem/progenitor cell; RSTC*: pre-tumorigenic RSTC; TIC: tumor-initiating cell; P: heterogeneous primary tumor subclones; MIC: metastasis-initiating cell; and M: metastatic subclone.

CSCs of ccRCC—the current status

A number of studies have attempted to identify the CSCs of ccRCC, with varied and sometimes contradictory results. These have been reviewed previously [52,53,54] and are summarized in Table 1. One strategy is to use known stem cell/CSC markers to isolate RCC stem/progenitor cells from clinical samples or established cell lines using fluorescence-activated cell sorting (FACS) or magnetic-activated cell sorting (MACS). The markers often used include the following:

Table 1 Prior studies on CSCs of ccRCC

CD105, also named Endoglin, is a receptor for TGF-β and therefore is presumed to promote EMT in stem cell formation. It is a recognized stem cell marker because of its identification as highly expressed in mesenchymal stem cells (MSCs) [55]. It is subsequently found to be overexpressed in multiple malignant cancers. However, the usefulness of relying on CD105 for identifying CSCs or TICs may be questioned since CD105 MSCs also exist [56] (also see below).

CD133, also named Prominin-1, is a surface marker of hematopoietic stem cells and endothelial cells, and subsequently found to be expressed in multiple CSCs [57]. It can promote self-renewal by activating MAPK, PI3K/AKT, and WNT signaling pathways. It is also highly expressed in metastatic cancer cells. However, not all CSCs express CD133 [58].

CD44 is a receptor for hyaluronan and osteopontin, and is overexpressed in metastatic and stem cells [59]. It is known to promote EMT and can anchor stem cells in the niche. As a CSC marker, it is often combined with the expression of CD24 [60, 61]. However, there seems to be low predictability for cancer stemness since either high or low expression of CD44/CD24 combination can be found in CSCs in different contexts [62, 63].

CD24 is a P-selectin receptor and is a marker found in multiple CSCs. As stated above, it is often used for CSC identification in combination with CD44, although its accuracy in ccRCC progenitor identification is yet to be fully assessed [62, 63].

CXCR4 is a hypoxia- and hypoxia-inducible factor (HIF)-induced receptor for the chemokine CXCL12/stromal cell-derived factor-1 (SDF-1), and is therefore a good marker for VHL mutant tumor cells. It has been implicated in stem cell retention in the stem cell niche as well as in stem cell mobilization, depending on the source of the ligand CXCL12/SDF-1—whether the ligand is expressed by the abutting niche cells or from the target tissue, respectively [64, 65].

These stem cell markers have been used to isolate CSCs of ccRCC (Studies 1–7 in Table 1) [66,67,68,69,70,71,72]. Particularly, CD133 has been suggested as a selective marker for resident progenitor cells in normal adult human kidney [73,74,75], which is an attractive attribute for CSCs. Although the tumorigenic role of CD133+ cells has been postulated in many solid malignancies, the precise function of these progenitor cells in renal carcinogenesis still remains unresolved [76,77,78,79,80]. The CD133-expressing cells were indeed enriched in the side population (SP) in both normal human kidney tissue and human RCC (Study 8 in Table 1) [81]. SP is considered stem cell-like because exclusion of DNA dye is a recognized phenotype of stem cells owing to their elevated efflux activity of ATP-binding cassette (ABC) transporter protein family that excretes dyes absorbed from the culture medium [82, 83]. These cells can be sorted as “side population” because they appear as a small group of cells low in DNA dye staining in FACS analysis. However, in co-transplantation with RCC cells, the tumor-derived CD133+ cells favored vascularization and enhanced tumor growth rather than initiating tumor growth of their own lineage in non-obese diabetic/severe combined immunodeficiency (NOD/SCID) mice [84]. It is probable that CD133+ cells represent a subset of renal progenitor cells or MSCs within the tumor, but not a TIC or MIC population. This is consistent with another study by the same research group, in which the highly tumorigenic human RCC-derived CD105-positive cells lack expression of CD133 (Study 1 in Table 1) [66]. Moreover, the expression of MSC and embryonic renal cell markers in these CD105+ clones suggests that the renal CSCs may not be of CD133+ origin, but rather originate from an undifferentiated CD105+ cell population that retains the MSC phenotype in the adult kidney. However, it is equally possible that CD105+ and CD133+ populations are MIC markers in different metastasis subclones and may be mutually exclusive.

Yet another study using RCC cell line SK-RC-42, which is derived from bone metastasis of unknown VHL status, showed a contradictory result in which CD105 was expressed in almost all monolayer adherent cells but was reduced in sphere-forming cells (Study 9 in Table 1) [85]. Conversely, a subpopulation of Caki-1 RCC cell line of VHL wild-type genotype and notably lacking both CD105 and CD44, displayed high tumorigenic potential when implanted into NOD/SCID mice (Study 5 in Table 1) [72].

Using functional assays such as SP detection and sphere formation may offer less biased criteria for isolating TICs, as opposed to utilizing preconceived stem cell markers. Some SP studies have indeed identified other potential stem cell markers. For example, in the SPs of various RCC cell lines (Study 10 in Table 1), ABCB1 transporter has been identified as a CSC marker of RCC [86], not surprising since the functional assay was based on the ABC activity. The human RCC cell lines ACHN, Caki-1, SMKTR2, SMKTR3, and murine RenCa cells were analyzed for expression of heat shock protein (HSP) 40 family member DnaJ (Hsp40) homolog, subfamily B, member 8 (DNAJB8) in SP (Study 11 in Table 1) [87]. Overexpression of DNAJB8 enhances the expression of stem cell markers and tumorigenicity. RT-PCR analysis of these isolated SP cells showed that DNAJB8 was predominantly coexpressed with Yamanaka factors such as SOX2 and OCT4/POU5F1. Western blotting and immunostaining using SP cells also corresponded with preferential expression of DNAJB8 protein, confirming the stem cell-like phenotypes [87]. In addition, SP from the cell line ACHN has identified Aldehyde dehydrogenase 1 gene (ALDH1) as a potential RCC stem cell marker (Study 12 in Table 1) [88], which has been implicated as a CSC marker for various other cancers possibly by providing increased drug resistance [89]. However, these SP cells from ACHN did not express CD105 or CD133, and the other cell line used in the same study, KRC/Y, although forming SP, did not show increased sphere-forming capacity or increased ALDH1 expression. It is notable that both ACHN and KRC/Y cells are VHL wildtype, but KRY/C is not histologically ccRCC and overexpresses mutant TP53.

Other studies using functional assays such as sphere formation has also identified a number of markers in the putative CSCs in RCC cell lines, including EMT markers CXCR4, SDF-1, ZEBs, TWIST, N-cadherin, and Vimentin, as well as canonical stem cell markers such as OCT4, NANOG, KLF4, CD24, and CD44 (Studies 13 and 14 in Table 1) [90, 91].

Nonetheless, even in these functional assays results could be inconsistent. In one study, SP analysis (exclusion of Hoechst 33342) on different ccRCC cell lines yielded appreciable SP in only one (769-P) of 5 lines (Study 10 in Table 1) [86]. While in this study, ABCB1+ SP was identified in the 769-P cell line, no stem-like cells were isolated from the same cell line in another study using sphere formation as the identification criterion (Study 14 in Table 1) [91]. It is possible that SP and sphere formation are different progenitor phenotypes in different cell lines with different genetic makeups, including VHL and TP53 mutant status (Table 2).

Table 2 Cell lines used in RCC stem/progenitor cell studiesa

Therefore, attempts to identify CSCs from established malignant cell lines may be inherently problematic since these cells have accumulated numerous genetic modifications to adapt to in vitro monoculture conditions. In addition, these commonly used cell lines are derived from renal cancers of different histological features and genetic makeups. The characteristics of the various cell lines used in the above-summarized studies are listed in Table 2. It is quite often that different RCC cell lines are used without consideration for their pathological and genetic features [92, 93]. For example, ACHN is not a ccRCC cell line but a mixed papillary and clear-cell morphology, and does not harbor VHL loss-of-function mutations, and KRC/Y is of granular and clear-cell histology and also VHL wildtype. Their inclusion in the same study (Study 12 in Table 1) yielded opposite results, as discussed above. Caki-1 and Caki-2, although originally isolated from presumed ccRCC patients, are both VHL-positive, and Caki-2 cells and their derived tumors in fact exhibit characteristics of high-grade papillary RCC (pRCC) in their histology and gene expression patterns [94].

Therefore, the results from studies with use of only VHL+ ccRCC cell line (Studies 5 and 12 in Table 1) [72] or mixed use of VHL+ and VHL cell lines (Study 13 in Table 1) [91], or mixed use of ccRCC and pRCC cell lines (Studies 6, 13, and 14 in Table 1) [70, 90], are difficult to extrapolate with relevance to clinical ccRCC [95]. As such, clinical samples should offer a more realistic chance to identify genuine tumor progenitor cells.

Many studies using clinical samples as well as cell lines implicated CXCR4 as a marker for normal human renal progenitor cells and for the tumor progenitor cells in ccRCC (Studies 2, 3, 7, and 14 in Table 1) [68, 69, 71, 91]. The CXCR4+ subpopulation in patient-derived xeno-transplantable ccRCC cells display sphere-forming capacities and are more tumorigenic in comparison with their CXCR4 counterpart. Notably, the expression of CXCR4 and its ligand, CXCL12/SDF-1α, is positively regulated by HIF that is stabilized and activated in VHL-deficient ccRCC cells [96, 97].

Canonically, CXCR4 is the receptor of the chemokine CXCL12/SDF-1 that induces metastasis [98]. HIF2α-induced expression of CXCR4 can also promote sphere formation and self-renewal of ccRCC cell lines [91]. In addition, CXCR4 can also enter the nucleus and interact with nuclear HIF-1α to enhance the expression of HIF target genes and promote ccRCC metastasis [99]. As such, elevated expression of CXCR4 is significantly associated with high-grade and advanced-stage ccRCC, as well as high rates of tumor recurrence [100]. Intriguingly, the significantly elevated CXCR4 mRNA levels were detected in primary ccRCC tumors without metastases, but not in metastasized tumor, and were correlated with short survival time [68]. This suggests that CXCR4 is a predictive marker for tumor aggression and metastasis, perhaps being involved in progenitor cell maintenance, but not contributing to metastasis directly. The notion is consistent with the finding that hypoxia is an important feature of stem/progenitor cell niche [101, 102].

It therefore appears that the best strategy for isolating TICs of ccRCC is to include known VHL-HIF targets in addition to stem cell markers from clinical samples, such as the studies of Addla et al. and Fendler et al. [71, 81], which both identified CXCR4, signaling pathways WNT (β-catenin) and NOTCH1, and stem cell marker CD133 and PAX2, as signature markers (Studies 3 and 8, Table 1).

ccRCC initiation and progression

Sporadic ccRCC tends to be late onset [103, 104]. Modeling of ccRCC progression based on genomic data demonstrates that haploid chromosome 3p loss, likely in the renal stem/progenitor cells (RSPCs), occurs early in childhood or adolescence, representing an initiating genetic event that is followed by slow clonal expansion in the subsequent 5–20 years [41]. The RSPCs with initial loss of chromosome 3p can be regarded as pre-tumorigenic because although they may develop into tumor cells, these RSPCs with 3p loss are not fast-growing as proliferating tumor cells. Indeed, the initial expansion results in only a modest number of progenies (a few hundred cells). The TRAcking renal Cancer Evolution through therapy (Rx) (TRACERx) study suggests that inactivation of the second allele of VHL occurs after 3p loss and before subclonal evolution that leads to metastasis [41, 51]. Therefore, inactivation of the second allele of VHL likely marks the emergence of TICs and sets off tumor growth and subclonal evolution. There is a latency period of 10–30 years between the emergence of TICs and clinical diagnosis (Fig. 2). Hereditary ccRCC, as in the familial VHL disease patients, follows the similar genetic trajectory; but since these patients inherit the first VHL gene inactivation mutations in the germline, the clinical diagnosis of ccRCC is years to decades earlier. Based on this tumor initiation-coupled subclonal evolution model (Fig. 1), one can envisage the difference between tumors with low primary heterogeneity and rapid malignant progression, and those with high primary heterogeneity and attenuated malignant progression (Fig. 2). This model also provides a reasonable explanation for the difference between TICs and MICs; that is, the initial 3p loss combined with loss of the second VHL allele can be viewed as the cause of TIC emergence. Following the appearance of TICs, metastatic subclones can emerge via different genetic and/or epigenetic events. Therefore, if the starting materials for isolating CSCs are malignant tumor mass or established malignant cell lines, it is likely that different “CSC” markers will be identified, reflecting the diverse genetic makeups of different metastatic subclones. On the other hand, TICs can offer a more homogeneous marker set for early diagnosis and treatment targets.

These findings also suggest that the TICs of ccRCC may indeed be the mutated adult RSPCs, since ccRCC appears to originate from a very limited cell population that expands to only a few hundred cells when second hit on the VHL allele occurs. The existence of RSPCs has been suspected since adult kidney is under constant chemical and mechanical assaults, and tubule repair is a well-controlled process [105,106,107,108]. Acute tubular injury can result in extensive tubule epithelial cell death, which is usually followed by a regenerative response characterized by epithelial cell proliferation [109, 110]. Such repair and regeneration processes involve the activation of stem/progenitor cells.

RSPCs are difficult to identify because of the complexity of the kidney structures and the complex developmental process. There are up to 26 cell types in mammalian adult kidney according to one study [111], including 16 different specialized epithelial cell types [112]. Some recent single-cell analyses have even identified 41 cell populations of renal lineage and 32 of non-renal lineage in the adult kidney [113], although whether these renal lineages are all functionally distinct is not clear.

During embryonic development, the nephrons are constructed from existing epithelia (from ureteric buds to form collecting ducts) and from metanephric mesenchyme via the process of mesenchymal-to-epithelial transition (to form distal and proximal tubules, and Bowman’s capsules) [111, 114, 115]. It has been suggested that each distinct segment of the renal tubule system can possess its own adult progenitor cells. Alternatively but not exclusively, a special group of progenitor cells can repopulate other, more distant regions of the nephron via migration, proliferation, and differentiation. Indeed, different adult renal progenitor cells have been identified [116, 117]. A few studies have also identified potential kidney progenitor cells in the interstitial tissue or mesenchyme [118, 119]. These studies are summarized in Table 3. Mostly, these studies employed functional assays such as label (BrdU)-retention (Studies 1 and 2 in Table 3) [120, 121], limiting dilution for proliferative capacity (Studies 3 and 4 in Table 3) [122, 123], serial dilution for in vitro culture (Study 5 in Table 3) [124], outgrowth of cultured kidney tissues (Studies 6–8 in Table 3) [74, 75], and SP isolation (Study 9 in Table 3) [125]. Some other studies used preconceived stem cell markers for isolation (Studies 10 and 11 in Table 3) [73, 126, 127]. More recently, single-cell RNA sequencing (scRNAseq) was used to identify kidney stem cells from urine (Study 12 in Table 3) [128]. These studies largely confirmed the presence of known stem cell markers such as Yamanaka factors, CD133, CD44, CD24, CD106, Sca-1, etc. in the presumptive kidney stem/progenitor cells, which supports using some of these markers for identifying or validating the presence of TICs in RCC.

Table 3 Prior studies on kidney stem/progenitor cells

Therefore, these studies, in aggregate, indicate that RSPCs exist in different segments of the renal tubule systems. They all exhibit canonical stem/progenitor cell activity such as multipotency and clonogenic activity in prolonged culture in vitro, and can repopulate tubule epithelia in kidney injury models. Although they all express a common set of stem/progenitor markers, each subpopulation may exhibit differences in specific marker gene expression. This may explain the clinical and experimental observations that although proximal tubule cells are the main origin of ccRCC, other renal tubule origins such as distal tubule and subregions of collecting duct can also give rise to ccRCC [40, 129]. Many of these RSPCs express NOTCH and/or WNT signaling signatures (Studies 3, 4, 9, 11, and 12 in Table 3). Interestingly, NOTCH and WNT signaling pathways appear to be important factors for specifying cells with tumor-initiating capacity identified from clinical cohorts that mainly include early-stage ccRCC samples [71, 81] (Studies 3 and 8 in Table 1). As such, a rational approach to validate the TICs of ccRCC may be to inactivate VHL specifically in one of these RSPCs, and examine the tumor-initiating property of the resultant mutant progenitor cells.

Loss of VHL and ccRCC initiation

In sporadic ccRCC, the first genetic event is often the haploid 3p loss that generates heterozygous loss of VHL, SETD2, PBRM1, and BAP1. The TICs then emerge after the loss of the second VHL allele, usually as a result of deletion, loss-of-function mutation, or epigenetic inactivation of gene expression. In the hereditary form of ccRCC that occurs in the familial VHL disease, the genetic/epigenetic events are reversed. That is, the patients first inherit VHL inactivating genomic mutations, then acquire loss-of-heterozygosity via 3p loss or epigenetic alterations. Therefore, biallelic loss of VHL appears to be the essential requirement for ccRCC initiation, the rare wild-type VHL ccRCC notwithstanding, and the 3p loss can occur before or coincidental with the second VHL allelic loss. Haploid 3p loss likely serves as an auxiliary oncogenic change that facilitates the subclonal evolution. Indeed, although haploid 3p loss is found in 90% of ccRCC cases, biallelic losses of PBRM1, SETD2, and BAP1 are only found in ~ 30–40%, 11%, and 10% of ccRCC cases, respectively [8, 12]. It is possible that haploid-insufficiency of PBRM1, SETD2, and BAP1 resulting from 3p loss can lead to epigenetic changes and facilitate acquisition of the additional hits that lead to malignancy. Indeed, heterozygous 3p loss is not unique to ccRCC; it is found in a significant number of cases in head and neck, breast, and ovarian cancers [130,131,132]. We suggest that the RSPC with biallelic VHL loss can be considered TIC of ccRCC. The question then is how loss of VHL function can set off the pathogenic process that leads to growth of ccRCC?

VHL is not a typical tumor suppressor gene such as TP53, PTEN, or Rb that directly regulates cell death or proliferation. However, based on previous studies, by acting as a scaffold protein, pVHL does indirectly regulate several key events related to tumor progression. These oncogenic events, when occurring in RSPCs, can induce the formation of TICs.

  1. (1)

    Proliferation. One of the earliest findings concerning the function of VHL is that TGF-α is upregulated in VHL mutant cells [133], which can lead to autocrine activation of the PI3K and ERK signaling pathways, two canonical inducers of cell proliferation. Also important, pVHL can suppress regulatory-associated protein of mTOR (RAPTOR) thus reducing the mTOR signaling [134]. Since mTOR is a major inducer of cell growth and proliferation, loss of VHL function can lead to increased mTOR signaling and tumor growth [6, 8]. Furthermore, the most salient characteristic of the VHL mutant cells is the hypoxic response induced by the stabilization of HIF-α, which results in tumor angiogenesis [via overexpression of vascular endothelial growth factor (VEGF) and Oncostatin M (OSM)] and metabolic switch (via reduced oxidative phosphorylation-based respiration) [23, 135, 136]. Both of these changes are critical for tumor growth. Furthermore, loss of pVHL can suppress cyclin-dependent kinase inhibitor p27kip1 that is involved in cell-cycle arrest [137].

  2. (2)

    Apoptosis. It has been documented that VHL can inhibit apoptosis via Bcl-2 signaling, suggesting that VHL inactivation can lead to increased cell death [138]. Conversely, other studies indicate that VHL deficiency can promote survival and proliferation via activation of HIF-1α and other factors [139, 140]. Such discrepancy may be related to the differential functions of HIF-α isoforms [141, 142]. On the other hand, pVHL can promote apoptosis in a HIF-independent manner by stabilizing p53 via suppressing Mdm2-mediated ubiquitination and nuclear export of p53. In addition, pVHL can increase p53 acetylation, and hence activity, by p300 under genotoxic stress [143]. The net result is the destabilization and decreased activity of p53 in VHL-deficient cells. Therefore it is possible that under stress conditions, VHL loss-of-function does confer cell survival advantages.

  3. (3)

    Genome instability. Genome instability is a distinguishing feature of tumor cells [144], which is important for acquiring necessary mutations that promote the formation of metastatic subclones. ccRCC is not an exception, but its mutational burden is less severe compared with other cancers [145]. Indeed, ccRCC cells do not contain mutations in DNA damage response genes such as BRCA1/2 or mismatch repair genes. These observations indicate that ccRCC may possess a unique mechanism for generating genome instability. One possible mechanism is related to the microtubule-stabilizing activity of pVHL [146, 147]. Thus, loss of VHL function can result in spindle malformation during cytokinesis, leading to chromosome instability [148]. In addition, pVHL can induce DNA damage repair of double-stranded breaks via generation of K63-linked polyubiquitin chains [149] that bind to damaged DNA and recruit repair enzymes [150]. Loss of VHL results in less efficient repair of DNA double-stranded breaks. Interestingly, it has also been reported that loss of PBRM1, another frequently mutated gene in ccRCC, can relieve the severe stress of DNA damages caused by VHL loss [151], thus providing a mechanistic explanation for the frequent coexistence of VHL and PBRM1 losses.

  4. (4)

    Reconstitution of microenvironment. It has been shown that tumor microenvironment plays a critical role in promoting tumor growth and immune evasion [152,153,154]. In particular, many forms of cancer, including ccRCC, have been linked to chronic tissue inflammation [21, 155,156,157]. It has recently been demonstrated that loss of VHL can generate a hypoxic niche for tumor progenitor cell maintenance [102]. Our laboratory has shown that loss of VHL function can also induce inflammatory response via intracellular ER stress [21]. The inflammatory response results in secretion of TNFα family of cytokines including IL-6 and OSM that induce alternatively activated macrophages and inflammation of vascular endothelia, respectively [22, 23]. The activated macrophages and endothelial cells in turn induce immune suppression and tumor cell EMT via the expression of PD-L1 and chemokines such as CCL18. The above notions are further explored in the following section.

Effects of microenvironment

Stem cells are known to require specialized niches for maintenance. CSCs have also been proposed to reside in a specialized niche, consisting of stromal cells such as cancer/carcinoma-associated fibroblasts (CAFs), endothelial cells, immune modulating cells including macrophages and myeloid-derived suppressor cells, reconstituted extracellular matrix, and cytokine-containing extracellular vesicles [158,159,160].

In this sense, VHL deficiency may be a unique self-fulfilling cellular characteristic for generating niches suitable for stem/progenitor cells, since loss of VHL function leads to HIF stabilization, resulting in hypoxic responses that can induce angiogenesis and reconstitute the microenvironment [102, 161]. It has also been known that ccRCC progression is strongly associated with chronic inflammation [162]. Such inflammatory microenvironment can facilitate the growth and malignant transformation of tumor cells [22, 23]. In particular, results from our and other laboratories have shown that hypoxic environment containing VHL-deficient kidney cells can attract monocytes and induce macrophage differentiation via overproduced IL-6, TGF-β, and VEGF [22, 154, 163], which in turn coordinate maintenance and activation of CSCs/TICs [160, 164]. VHL mutant cells also activate endothelial cells that favor inflammatory reactions via overproduced VEGF and OSM [23], which may also serve as the vascular niche that is a widely-recognized component of stem cells and CSC niche [165]. VHL mutant cells also overproduce PDGF-B that activates CAFs in a HIF-independent and Sp1-dependent manner [166]. CAFs produce VEGF, PDGF, TGF-β, EGF, FGF, HGF, CXCL12/SDF-1, and osteopontin that promote EMT and induce angiogenesis important for CSC maintenance. Other less well-studied potential CSC niche components such as mesenchymal stem cells, neurons, lymphatics, etc., require further elucidation.

Besides the cellular components, CXCR4 and CXCL12/SDF-1 expression is also induced by hypoxia in TICs or stromal cells [96, 97], potentially facilitating the mobilization of stem cells. Furthermore, VHL mutant cells are known to overproduce fibronectin and collagens [167,168,169,170] that enrich the extracellular matrix (ECM), lysyl oxidase that crosslinks the collagen fibers [171, 172], and metalloproteases (MMPs; mainly MMP2, MMP9, and MT1-MMP) that remodel the ECM [173,174,175]. Therefore, although it is not yet known whether RSPCs reside in specialized niches, it is entirely possible that the importance of VHL inactivation in initiating ccRCC is that it can create a favorable microenvironment for the emergence of TICs.

As such, crosstalk between TICs of ccRCC and the components of the microenvironment is a critical aspect of TIC development and maintenance [176]. Such interaction is usually mediated through cytokines or growth factors, but recently, metabolites such as methionine have also been shown to promote CSC/TIC maintenance in a paracrine manner [177, 178]. Interestingly, in ccRCC, methionine can be supplied by a subpopulation of pericytes expressing platelet-derived growth factor receptor-beta (PDGFR-β) and G-protein-coupled receptor 91 (GPR91), which are activated by succinate secreted by the TICs and received by GPR91 on pericytes [179].

In the case of ccRCC metastasis, in addition to the contributing stromal components described above, it has been shown that 9p21.3 loss is a common event in metastatic subclones [41]. 9p21.3 encompasses tumor suppressor genes CDKN2A/B and the Type I Interferon (IFN) gene cluster. Interestingly, 9p21.3 loss has been found in 14 different malignant cancer types based on analysis of The Cancer Genome Atlas data [180]. In a syngeneic mouse model of pancreatic cancer, functional genetic study indicates that while loss of the CDKN2A/B genes is important for tumor growth, deletion of the Type 1 IFN locus is specifically needed for metastasis [181]. However, if these cancer cells were injected directly into circulation, deletion of the Type 1 IFN cluster no longer offered advantages in metastasis over the Type 1 IFN-positive counterparts [181]. This suggests that the consequence of Type 1 IFN loss is alteration of the immunogenic response in the microenvironment, thus effecting malignant tumor progression. As such, MICs of ccRCC may be suppressed by reactivating the immune cells induced by Type 1 IFN.

Conclusions and perspectives

In summary, ccRCC initiation is unique in that it requires, at a minimum, only loss of VHL function. This is achievable because pVHL as a scaffold protein can participate in multiple cellular functions involved in different aspects of tumorigenesis [182]. Figure 3 shows the model that explains the origin of TICs of ccRCC and the formation of MIC subclone. Loss of VHL in normal kidney tissue progenitor cells confers TICs the tumor-initiating capacity. These cells can be recognized by the markers of tissue progenitor cells such as NOTCH or WNT signaling components, and progenitor cell marker CD133, PAX2, or CD105, in addition to the VHL-HIF signaling target CXCR4, and urine/serum inflammatory markers such as KIM-1. MICs then emerge after intrinsic genetic changes such as 9p21.3 loss and/or epigenetic changes promoted by haploid loss of PBRM1, SETD2, and BAP1. Extrinsic factors such as cytokines, growth factors, and metabolites emanated from the microenvironment can further induce metastatic transformation.

Fig. 3
figure 3

Model of tumor initiation and metastasis initiation of ccRCC. Renal stem/progenitor cell (RSPC) experiences chromosome 3p loss and begins a slow clonal expansion, followed by loss of the 2nd VHL allele, and becomes tumor-initiating cells (TICs). Loss of VHL function promotes proliferation, survival, genome instability, and reconstitution of the microenvironment, resulting in subclonal evolution, which mainly produces heterogeneous subclones of benign tumor cells. The subclonal evolution may also be aided by epigenetic changes enhanced by the loss of haploid PBRM1, SETD2, and BAP1. Chromosome 9p21.3 loss and other genetic events such as EMT induction then generate metastasis-initiating cells (MICs)

The question remains as to why this unique genetic condition only occurs in ccRCC and a few other cases of benign tumors, but not in other cancers. There are two possibilities. First, the combination of genetic and physiological conditions required for ccRCC formation is only suited for the kidney microenvironment, and even only in certain populations of the kidney epithelial cells [40]. The unique kidney microenvironment may include the unique set of resident macrophages that can be induced by VHL mutant cells [183]. Alternatively but not exclusively, VHL mutant cells may not survive (and therefore no tumor growth) in other tissues. One scenario may be that cells with genome instability resulting from VHL loss can survive better in kidney because these cells have a robust DNA damage response program a priori. Thus the balanced cell survival and accumulation of mutations may be the key to ccRCC development. More detailed analyses of the cellular and molecular characteristics of the TICs of ccRCC should answer this question. Understanding the origin of the TICs and MICs for ccRCC should offer a novel avenue for early detection and prevention of malignant transformation of this deadly disease.

Availability of data and materials

All data analyzed in this review have been published in primary research articles cited as references.

Abbreviations

ABC:

ATP-Binding Cassette

ALDH1A1:

Aldehyde Dehydrogenase 1 Family Member A1

APC:

Adenomatous polyposis coli

AQP2:

Aquaporin 2

BAP1:

Brca1-Associated Protein 1

BMI:

B-Cell Lymphoma Murine Leukemia Virus Integration Site

BNP:

B-Type Natriuretic Peptide

BrdU:

Bromodeoxyuridine/5-bromo-2'-deoxyuridine

CAF:

Cancer/Carcinoma-Associated Fibroblast

c-MYC:

Cellular myelocytomatosis

ccRCC:

Clear-cell renal cell carcinoma

CD:

Cluster of differentiation

CK:

Cytokeratin

CKD:

Chronic kidney disease

CSC:

Cancer stem cell

CXCR4:

C-X-C Chemokine Receptor Type 4

DLL1/4:

Delta-like protein 1/4

ECM:

Extracellular matrix

EGF:

Epithelial growth factor

EMT:

Epithelial-to-mesenchymal transition

FACS:

Fluorescence-activated cell sorting

FGF:

Fibroblast growth factor

FOXD1:

Forkhead Box D1

FU:

Fluorouracil

JAG1/2:

Jagged canonical notch ligand 1/2

GATA4:

GATA binding protein 4

GPR91:

G Protein-Coupled Receptor 91

Gy:

Gray unit of ionizing radiation

HES1:

Hairy and enhancer of split-1

HEY1:

Hairy Ears, Y-Linked 1

HGF:

Hepatocyte growth factor

HIF:

Hypoxia-inducible factor

IFN:

Interferon

IL-6:

Interleukin 6

KIM-1:

Kidney injury molecule-1

KLF4:

Krüppel-like factor 4

LRC:

Label-retaining cell

LGR5:

Leucine Rich Repeat Containing G Protein-Coupled Receptor 5

MDR1:

Multidrug resistance protein 1

MHC-II:

Major histocompatibility complex class II

MIC:

Metastasis-initiating cell

MMC:

Mitomycin C

MMPs:

Matrix metallopeptidases

MSC:

Mesenchymal stem cell

MTX:

Methotrexate

MYST3:

Histone Acetyltransferase (Monocytic Leukemia) 3

NANOG:

Homeobox Transcription Factor Nanog

NGAL:

Neutrophil Gelatinase-Associated Lipocalin

NOD/SCID:

Non-obese Diabetic/Severe Combined Immunodeficiency

NOTCH1/2:

Neurogenic Locus Notch Homolog Protein 1/2

OCT3/4:

Octamer-Binding Transcription Factor 3/4

OSM:

Oncostatin M

PAX2/8:

Paired Box 2/8

PBRM1:

Polybromo 1

PDGF:

Platelet Derived Growth Factor

PDGFR:

Platelet Derived Growth Factor Receptor

PROM1:

Prominin 1

RCC:

Renal Cell Carcinoma

RSPC:

Renal Stem/ Progenitor Cell

RTK:

Receptor Tyrosine Kinase

SALL1:

Spalt Like Transcription Factor 1

SCA1:

Stem Cells Antigen-1

SCF:

Stem Cell Factor

scRNAseq:

Single-Cell RNA Sequencing

SDF-1:

Stromal-Derived Factor-1

SETD2:

SET Domain-Containing 2

SIX2:

Sine Oculis Homeobox Homolog 2

SNAI1:

Snail Family Transcriptional Repressor 1

SOX2/4/9:

SRY-Box Transcription Factor 2/4/9

SP:

Side Population

SSEA-4:

Stage-Specific Embryonic Antigen 4

TGF-α:

Transforming Growth Factor-alpha

TGF-β:

Transforming Growth Factor-beta

TIC:

Tumor-Initiating Cell

TWIST1:

Twist Family bHLH Transcription Factor 1

TLE4:

Transducin-Like Enhancer of Split 4

UMOD:

Uromodulin

VCAM1:

Vascular Cell Adhesion Molecule 1

VEGF:

Vascular Endothelial Growth Factor

VEGFR2:

Vascular Endothelial Growth Factor Receptor 2

VHL:

Von Hippel–Lindau

WNT:

Wingless-Related Integration Site

WT-1:

Wilms Tumor 1

ZEB1/2:

Zinc Finger E-Box Binding Homeobox 1/2

ZO-1:

Zonula Occludens 1

References

  1. Saliby RM, Labaki C, Jammihal TR, Xie W, Sun M, Shah V, et al. Impact of renal cell carcinoma molecular subtypes on immunotherapy and targeted therapy outcomes. Cancer Cell. 2024;42(5):732–5.

    Article  CAS  PubMed  Google Scholar 

  2. Hsieh JJ, Purdue MP, Signoretti S, Swanton C, Albiges L, Schmidinger M, et al. Renal cell carcinoma. Nat Rev Dis Primers. 2017. https://doiorg.publicaciones.saludcastillayleon.es/10.1038/nrdp.2017.9.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Padala SA, Barsouk A, Thandra KC, Saginala K, Mohammed A, Vakiti A, et al. Epidemiology of renal cell carcinoma. World J Oncol. 2020;11(3):79–87.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Sun R, Breau RH, Mallick R, Tanguay S, Pouliot F, Kapoor A, et al. Prognostic impact of paraneoplastic syndromes on patients with non-metastatic renal cell carcinoma undergoing surgery: results from Canadian kidney cancer information system. Can Urol Assoc J. 2021;15(4):132–7.

    PubMed  Google Scholar 

  5. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65(1):5–29.

    Article  PubMed  Google Scholar 

  6. Cancer Genome Atlas Research N. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature. 2013;499(7456):43–9.

    Article  Google Scholar 

  7. Zbar B, Brauch H, Talmadge C, Linehan M. Loss of alleles of loci on the short arm of chromosome 3 in renal cell carcinoma. Nature. 1987;327(6124):721–4.

    Article  CAS  PubMed  Google Scholar 

  8. Sato Y, Yoshizato T, Shiraishi Y, Maekawa S, Okuno Y, Kamura T, et al. Integrated molecular analysis of clear-cell renal cell carcinoma. Nat Genet. 2013;45(8):860–7.

    Article  CAS  PubMed  Google Scholar 

  9. Pena-Llopis S, Vega-Rubin-de-Celis S, Liao A, Leng N, Pavia-Jimenez A, Wang S, et al. BAP1 loss defines a new class of renal cell carcinoma. Nat Genet. 2012;44(7):751–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Dalgliesh GL, Furge K, Greenman C, Chen L, Bignell G, Butler A, et al. Systematic sequencing of renal carcinoma reveals inactivation of histone modifying genes. Nature. 2010;463(7279):360–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Brugarolas J. Molecular genetics of clear-cell renal cell carcinoma. J Clin Oncol. 2014;32(18):1968–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hakimi AA, Ostrovnaya I, Reva B, Schultz N, Chen YB, Gonen M, et al. Adverse outcomes in clear cell renal cell carcinoma with mutations of 3p21 epigenetic regulators BAP1 and SETD2: a report by MSKCC and the KIRC TCGA research network. Clin Cancer Res. 2013;19(12):3259–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kapur P, Pena-Llopis S, Christie A, Zhrebker L, Pavia-Jimenez A, Rathmell WK, et al. Effects on survival of BAP1 and PBRM1 mutations in sporadic clear-cell renal-cell carcinoma: a retrospective analysis with independent validation. Lancet Oncol. 2013;14(2):159–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Vogel C, Ziegelmuller B, Ljungberg B, Bensalah K, Bex A, Canfield S, et al. Imaging in suspected renal-cell carcinoma: systematic review. Clin Genitourin Cancer. 2019;17(2):e345–55.

    Article  PubMed  Google Scholar 

  15. Lopes Vendrami C, Parada Villavicencio C, DeJulio TJ, Chatterjee A, Casalino DD, Horowitz JM, et al. Differentiation of solid renal tumors with multiparametric MR imaging. Radiographics. 2017;37(7):2026–42.

    Article  PubMed  Google Scholar 

  16. Bratu O, Mischianu D, Marcu D, Spinu D, Iorga L, Cherciu A, et al. Renal tumor biomarkers (review). Exp Ther Med. 2021;22(5):1297.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Farber NJ, Kim CJ, Modi PK, Hon JD, Sadimin ET, Singer EA. Renal cell carcinoma: the search for a reliable biomarker. Transl Cancer Res. 2017;6(3):620–32.

    Article  CAS  PubMed  Google Scholar 

  18. Pastore AL, Palleschi G, Silvestri L, Moschese D, Ricci S, Petrozza V, et al. Serum and urine biomarkers for human renal cell carcinoma. Dis Mark. 2015. https://doiorg.publicaciones.saludcastillayleon.es/10.1155/2015/251403.

    Article  CAS  Google Scholar 

  19. Kruk L, Mamtimin M, Braun A, Anders HJ, Andrassy J, Gudermann T, et al. Inflammatory networks in renal cell carcinoma. Cancers. 2023. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/cancers15082212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wolf MM, Madden MZ, Arner EN, Bader JE, Ye X, Vlach L, et al. VHL loss reprograms the immune landscape to promote an inflammatory myeloid microenvironment in renal tumorigenesis. J Clin Invest. 2024. https://doiorg.publicaciones.saludcastillayleon.es/10.1172/JCI173934.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kuo CY, Lin CH, Hsu T. VHL inactivation in precancerous kidney cells induces an inflammatory response via ER stress-activated IRE1alpha signaling. Cancer Res. 2017;77(13):3406–16.

    Article  CAS  PubMed  Google Scholar 

  22. Nguyen TN, Nguyen-Tran HH, Chen CY, Hsu T. IL-6 and CCL18 mediate crosstalk between VHL-deficient kidney cells and macrophages during development of renal cell carcinoma. Cancer Res. 2022;82(15):2716–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Nguyen-Tran HH, Nguyen TN, Chen CY, Hsu T. Endothelial reprogramming stimulated by oncostatin M promotes inflammation and tumorigenesis in VHL-deficient kidney tissue. Cancer Res. 2021;81(19):5060–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Lees JS, Elyan BMP, Herrmann SM, Lang NN, Jones RJ, Mark PB. The “other” big complication: how chronic kidney disease impacts on cancer risks and outcomes. Nephrol Dial Transplant. 2023;38(5):1071–9.

    Article  CAS  PubMed  Google Scholar 

  25. Saly DL, Eswarappa MS, Street SE, Deshpande P. Renal cell cancer and chronic kidney disease. Adv Chronic Kidney Dis. 2021;28(5):460–8.

    Article  PubMed  Google Scholar 

  26. Speer T, Dimmeler S, Schunk SJ, Fliser D, Ridker PM. Targeting innate immunity-driven inflammation in CKD and cardiovascular disease. Nat Rev Nephrol. 2022;18(12):762–78.

    Article  PubMed  Google Scholar 

  27. Sandokji I, Greenberg JH. Plasma and urine biomarkers of CKD: a review of findings in the CKiD study. Semin Nephrol. 2021;41(5):416–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Priyadarshini G, Rajappa M. Predictive markers in chronic kidney disease. Clin Chim Acta. 2022. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.cca.2022.08.018.

    Article  CAS  PubMed  Google Scholar 

  29. Barreto DV, Barreto FC, Liabeuf S, Temmar M, Lemke HD, Tribouilloy C, et al. Plasma interleukin-6 is independently associated with mortality in both hemodialysis and pre-dialysis patients with chronic kidney disease. Kidney Int. 2010;77(6):550–6.

    Article  CAS  PubMed  Google Scholar 

  30. Su H, Lei CT, Zhang C. Interleukin-6 signaling pathway and its role in kidney disease: an update. Front Immunol. 2017. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fimmu.2017.00405.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Bonventre JV. Kidney injury molecule-1 (KIM-1): a urinary biomarker and much more. Nephrol Dial Transplant. 2009;24(11):3265–8.

    Article  CAS  PubMed  Google Scholar 

  32. Scelo G, Muller DC, Riboli E, Johansson M, Cross AJ, Vineis P, et al. KIM-1 as a blood-based marker for early detection of kidney cancer: a prospective nested case-control study. Clin Cancer Res. 2018;24(22):5594–601.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Yi A, Lee CH, Yun YM, Kim H, Moon HW, Hur M. Effectiveness of plasma and urine neutrophil gelatinase-associated lipocalin for predicting acute kidney injury in high-risk patients. Ann Lab Med. 2021;41(1):60–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lippi G, Meschi T, Nouvenne A, Mattiuzzi C, Borghi L. Neutrophil gelatinase-associated lipocalin in cancer. Adv Clin Chem. 2014. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/B978-0-12-800263-6.00004-5.

    Article  PubMed  Google Scholar 

  35. Munoz Mendoza J, Isakova T, Cai X, Bayes LY, Faul C, Scialla JJ, et al. Inflammation and elevated levels of fibroblast growth factor 23 are independent risk factors for death in chronic kidney disease. Kidney Int. 2017;91(3):711–9.

    Article  CAS  PubMed  Google Scholar 

  36. David V, Martin A, Isakova T, Spaulding C, Qi L, Ramirez V, et al. Inflammation and functional iron deficiency regulate fibroblast growth factor 23 production. Kidney Int. 2016;89(1):135–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Sell S. On the stem cell origin of cancer. Am J Pathol. 2010;176(6):2584–3494.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Prager BC, Xie Q, Bao S, Rich JN. Cancer stem cells: the architects of the tumor ecosystem. Cell Stem Cell. 2019;24(1):41–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. van Niekerk G, Davids LM, Hattingh SM, Engelbrecht AM. Cancer stem cells: a product of clonal evolution? Int J Cancer. 2017;140(5):993–9.

    Article  PubMed  Google Scholar 

  40. Mandriota SJ, Turner KJ, Davies DR, Murray PG, Morgan NV, Sowter HM, et al. HIF activation identifies early lesions in VHL kidneys: evidence for site-specific tumor suppressor function in the nephron. Cancer Cell. 2002;1(5):459–68.

    Article  CAS  PubMed  Google Scholar 

  41. Turajlic S, Xu H, Litchfield K, Rowan A, Chambers T, Lopez JI, et al. Tracking cancer evolution reveals constrained routes to metastases: TRACERx renal. Cell. 2018;173(3):581–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Celia-Terrassa T, Kang Y. Distinctive properties of metastasis-initiating cells. Genes Dev. 2016;30(8):892–908.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Blokzijl F, de Ligt J, Jager M, Sasselli V, Roerink S, Sasaki N, et al. Tissue-specific mutation accumulation in human adult stem cells during life. Nature. 2016;538(7624):260–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Barker N, Ridgway RA, van Es JH, van de Wetering M, Begthel H, van den Born M, et al. Crypt stem cells as the cells-of-origin of intestinal cancer. Nature. 2009;457(7229):608–11.

    Article  CAS  PubMed  Google Scholar 

  45. Mani SA, Guo W, Liao MJ, Eaton EN, Ayyanan A, Zhou AY, et al. The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell. 2008;133(4):704–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Muller M, Hermann PC, Liebau S, Weidgang C, Seufferlein T, Kleger A, et al. The role of pluripotency factors to drive stemness in gastrointestinal cancer. Stem Cell Res. 2016;16(2):349–57.

    Article  PubMed  Google Scholar 

  47. Ohnishi K, Semi K, Yamamoto T, Shimizu M, Tanaka A, Mitsunaga K, et al. Premature termination of reprogramming in vivo leads to cancer development through altered epigenetic regulation. Cell. 2014;156(4):663–77.

    Article  CAS  PubMed  Google Scholar 

  48. Sainz B Jr, Alcala S, Garcia E, Sanchez-Ripoll Y, Azevedo MM, Cioffi M, et al. Microenvironmental hCAP-18/LL-37 promotes pancreatic ductal adenocarcinoma by activating its cancer stem cell compartment. Gut. 2015;64(12):1921–35.

    Article  CAS  PubMed  Google Scholar 

  49. Lonardo E, Hermann PC, Mueller MT, Huber S, Balic A, Miranda-Lorenzo I, et al. Nodal/Activin signaling drives self-renewal and tumorigenicity of pancreatic cancer stem cells and provides a target for combined drug therapy. Cell Stem Cell. 2011;9(5):433–46.

    Article  CAS  PubMed  Google Scholar 

  50. Hermann PC, Sancho P, Canamero M, Martinelli P, Madriles F, Michl P, et al. Nicotine promotes initiation and progression of KRAS-induced pancreatic cancer via Gata6-dependent dedifferentiation of acinar cells in mice. Gastroenterology. 2014;147(5):1119–33.

    Article  CAS  PubMed  Google Scholar 

  51. Mitchell TJ, Turajlic S, Rowan A, Nicol D, Farmery JHR, O’Brien T, et al. Timing the landmark events in the evolution of clear cell renal cell cancer: TRACERx renal. Cell. 2018;173(3):611–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Corro C, Moch H. Biomarker discovery for renal cancer stem cells. J Pathol Clin Res. 2018;4(1):3–18.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Yuan ZX, Mo J, Zhao G, Shu G, Fu HL, Zhao W. Targeting strategies for renal cell carcinoma: from renal cancer cells to renal cancer stem cells. Front Pharmacol. 2016. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fphar.2016.00423/full.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Xiong B, Liu W, Liu Y, Chen T, Lin A, Song J, et al. A multi-omics prognostic model capturing tumor stemness and the immune microenvironment in clear cell renal cell carcinoma. Biomedicines. 2024;12(10):2171.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Dominici M, Le Blanc K, Mueller I, Slaper-Cortenbach I, Marini F, Krause D, et al. Minimal criteria for defining multipotent mesenchymal stromal cells. The international society for cellular therapy position statement. Cytotherapy. 2006;8(4):315–7.

    Article  CAS  PubMed  Google Scholar 

  56. Cleary MA, Narcisi R, Focke K, van der Linden R, Brama PA, van Osch GJ. Expression of CD105 on expanded mesenchymal stem cells does not predict their chondrogenic potential. Osteoarthr Cartil. 2016;24(5):868–72.

    Article  CAS  Google Scholar 

  57. Moreno-Londono AP, Robles-Flores M. Functional roles of CD133: more than stemness associated factor regulated by the microenvironment. Stem Cell Rev Rep. 2024;20(1):25–51.

    Article  CAS  PubMed  Google Scholar 

  58. Gisina A, Kim Y, Yarygin K, Lupatov A. Can CD133 be regarded as a prognostic biomarker in oncology: pros and cons. Int J Mol Sci. 2023. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/ijms242417398.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Thapa R, Wilson GD. The importance of CD44 as a stem cell biomarker and therapeutic target in cancer. Stem Cells Int. 2016. https://doiorg.publicaciones.saludcastillayleon.es/10.1155/2016/2087204.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Jaggupilli A, Elkord E. Significance of CD44 and CD24 as cancer stem cell markers: an enduring ambiguity. Clin Dev Immunol. 2012. https://doiorg.publicaciones.saludcastillayleon.es/10.1155/2012/708036.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Li W, Ma H, Zhang J, Zhu L, Wang C, Yang Y. Unraveling the roles of CD44/CD24 and ALDH1 as cancer stem cell markers in tumorigenesis and metastasis. Sci Rep. 2017;7(1):13856.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Mylona E, Giannopoulou I, Fasomytakis E, Nomikos A, Magkou C, Bakarakos P, et al. The clinicopathologic and prognostic significance of CD44+/CD24(-/low) and CD44-/CD24+ tumor cells in invasive breast carcinomas. Hum Pathol. 2008;39(7):1096–102.

    Article  CAS  PubMed  Google Scholar 

  63. Ghuwalewala S, Ghatak D, Das P, Dey S, Sarkar S, Alam N, et al. CD44(high)CD24(low) molecular signature determines the cancer stem cell and EMT phenotype in oral squamous cell carcinoma. Stem Cell Res. 2016;16(2):405–17.

    Article  CAS  PubMed  Google Scholar 

  64. Sugiyama T, Kohara H, Noda M, Nagasawa T. Maintenance of the hematopoietic stem cell pool by CXCL12-CXCR4 chemokine signaling in bone marrow stromal cell niches. Immunity. 2006;25(6):977–88.

    Article  CAS  PubMed  Google Scholar 

  65. Ratajczak MZ, Serwin K, Schneider G. Innate immunity derived factors as external modulators of the CXCL12-CXCR4 axis and their role in stem cell homing and mobilization. Theranostics. 2013;3(1):3–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Bussolati B, Bruno S, Grange C, Ferrando U, Camussi G. Identification of a tumor-initiating stem cell population in human renal carcinomas. Faseb J. 2008;22(10):3696–705.

    Article  CAS  PubMed  Google Scholar 

  67. Galleggiante V, Rutigliano M, Sallustio F, Ribatti D, Ditonno P, Bettocchi C, et al. CTR2 identifies a population of cancer cells with stem cell-like features in patients with clear cell renal cell carcinoma. J Urol. 2014;192(6):1831–41.

    Article  CAS  PubMed  Google Scholar 

  68. Gassenmaier M, Chen D, Buchner A, Henkel L, Schiemann M, Mack B, et al. CXC chemokine receptor 4 is essential for maintenance of renal cell carcinoma-initiating cells and predicts metastasis. Stem Cells. 2013;31(8):1467–76.

    Article  CAS  PubMed  Google Scholar 

  69. Varna M, Gapihan G, Feugeas JP, Ratajczak P, Tan S, Ferreira I, et al. Stem cells increase in numbers in perinecrotic areas in human renal cancer. Clin Cancer Res. 2015;21(4):916–24.

    Article  CAS  PubMed  Google Scholar 

  70. Xiao W, Gao Z, Duan Y, Yuan W, Ke Y. Notch signaling plays a crucial role in cancer stem-like cells maintaining stemness and mediating chemotaxis in renal cell carcinoma. J Exp Clin Cancer Res. 2017;36(1):41.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Fendler A, Bauer D, Busch J, Jung K, Wulf-Goldenberg A, Kunz S, et al. Inhibiting WNT and NOTCH in renal cancer stem cells and the implications for human patients. Nat Commun. 2020;11(1):929.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Fiedorowicz M, Khan MI, Strzemecki D, Orzel J, Welniak-Kaminska M, Sobiborowicz A, et al. Renal carcinoma CD105-/CD44- cells display stem-like properties in vitro and form aggressive tumors in vivo. Sci Rep. 2020;10(1):5379.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Bussolati B, Bruno S, Grange C, Buttiglieri S, Deregibus MC, Cantino D, et al. Isolation of renal progenitor cells from adult human kidney. Am J Pathol. 2005;166(2):545–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Angelotti ML, Ronconi E, Ballerini L, Peired A, Mazzinghi B, Sagrinati C, et al. Characterization of renal progenitors committed toward tubular lineage and their regenerative potential in renal tubular injury. Stem Cells. 2012;30(8):1714–25.

    Article  CAS  PubMed  Google Scholar 

  75. Sagrinati C, Netti GS, Mazzinghi B, Lazzeri E, Liotta F, Frosali F, et al. Isolation and characterization of multipotent progenitor cells from the Bowman’s capsule of adult human kidneys. J Am Soc Nephrol. 2006;17(9):2443–56.

    Article  CAS  PubMed  Google Scholar 

  76. Vander Griend DJ, Karthaus WL, Dalrymple S, Meeker A, DeMarzo AM, Isaacs JT. The role of CD133 in normal human prostate stem cells and malignant cancer-initiating cells. Cancer Res. 2008;68(23):9703–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. O’Brien CA, Pollett A, Gallinger S, Dick JE. A human colon cancer cell capable of initiating tumour growth in immunodeficient mice. Nature. 2007;445(7123):106–10.

    Article  CAS  PubMed  Google Scholar 

  78. Ricci-Vitiani L, Lombardi DG, Pilozzi E, Biffoni M, Todaro M, Peschle C, et al. Identification and expansion of human colon-cancer-initiating cells. Nature. 2007;445(7123):111–5.

    Article  CAS  PubMed  Google Scholar 

  79. Collins AT, Berry PA, Hyde C, Stower MJ, Maitland NJ. Prospective identification of tumorigenic prostate cancer stem cells. Cancer Res. 2005;65(23):10946–51.

    Article  CAS  PubMed  Google Scholar 

  80. Singh SK, Hawkins C, Clarke ID, Squire JA, Bayani J, Hide T, et al. Identification of human brain tumour initiating cells. Nature. 2004;432(7015):396–401.

    Article  CAS  PubMed  Google Scholar 

  81. Addla SK, Brown MD, Hart CA, Ramani VA, Clarke NW. Characterization of the Hoechst 33342 side population from normal and malignant human renal epithelial cells. Am J Physiol Renal Physiol. 2008;295(3):F680–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Challen GA, Little MH. A side order of stem cells: the SP phenotype. Stem Cells. 2006;24(1):3–12.

    Article  PubMed  Google Scholar 

  83. Greve B, Kelsch R, Spaniol K, Eich HT, Gotte M. Flow cytometry in cancer stem cell analysis and separation. Cytometry A. 2012;81(4):284–93.

    Article  PubMed  Google Scholar 

  84. Bruno S, Bussolati B, Grange C, Collino F, Graziano ME, Ferrando U, et al. CD133+ renal progenitor cells contribute to tumor angiogenesis. Am J Pathol. 2006;169(6):2223–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Zhong Y, Guan K, Guo S, Zhou C, Wang D, Ma W, et al. Spheres derived from the human SK-RC-42 renal cell carcinoma cell line are enriched in cancer stem cells. Cancer Lett. 2010;299(2):150–60.

    Article  CAS  PubMed  Google Scholar 

  86. Huang B, Huang YJ, Yao ZJ, Chen X, Guo SJ, Mao XP, et al. Cancer stem cell-like side population cells in clear cell renal cell carcinoma cell line 769P. PLoS ONE. 2013;8(7):e68293.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Nishizawa S, Hirohashi Y, Torigoe T, Takahashi A, Tamura Y, Mori T, et al. HSP DNAJB8 controls tumor-initiating ability in renal cancer stem-like cells. Cancer Res. 2012;72(11):2844–54.

    Article  CAS  PubMed  Google Scholar 

  88. Ueda K, Ogasawara S, Akiba J, Nakayama M, Todoroki K, Ueda K, et al. Aldehyde dehydrogenase 1 identifies cells with cancer stem cell-like properties in a human renal cell carcinoma cell line. PLoS ONE. 2013;8(10):e75463.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Wei Y, Li Y, Chen Y, Liu P, Huang S, Zhang Y, et al. ALDH1: a potential therapeutic target for cancer stem cells in solid tumors. Front Oncol. 2022. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fonc.2022.1026278/full.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Lichner Z, Saleh C, Subramaniam V, Seivwright A, Prud’homme GJ, Yousef GM. miR-17 inhibition enhances the formation of kidney cancer spheres with stem cell/tumor initiating cell properties. Oncotarget. 2015;6(8):5567–81.

    Article  PubMed  Google Scholar 

  91. Micucci C, Matacchione G, Valli D, Orciari S, Catalano A. HIF2alpha is involved in the expansion of CXCR4-positive cancer stem-like cells in renal cell carcinoma. Br J Cancer. 2015;113(8):1178–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Wolf MM, Kimryn Rathmell W, Beckermann KE. Modeling clear cell renal cell carcinoma and therapeutic implications. Oncogene. 2020;39(17):3413–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Brodaczewska KK, Szczylik C, Fiedorowicz M, Porta C, Czarnecka AM. Choosing the right cell line for renal cell cancer research. Mol Cancer. 2016;15(1):83.

    Article  PubMed  PubMed Central  Google Scholar 

  94. Furge KA, Chen J, Koeman J, Swiatek P, Dykema K, Lucin K, et al. Detection of DNA copy number changes and oncogenic signaling abnormalities from gene expression data reveals MYC activation in high-grade papillary renal cell carcinoma. Cancer Res. 2007;67(7):3171–6.

    Article  CAS  PubMed  Google Scholar 

  95. Dong Y, Manley BJ, Becerra MF, Redzematovic A, Casuscelli J, Tennenbaum DM, et al. Tumor xenografts of human clear cell renal cell carcinoma but not corresponding cell lines recapitulate clinical response to sunitinib: feasibility of using biopsy samples. Eur Urol Focus. 2017;3(6):590–8.

    Article  PubMed  Google Scholar 

  96. Zagzag D, Krishnamachary B, Yee H, Okuyama H, Chiriboga L, Ali MA, et al. Stromal cell-derived factor-1alpha and CXCR4 expression in hemangioblastoma and clear cell-renal cell carcinoma: von Hippel-Lindau loss-of-function induces expression of a ligand and its receptor. Cancer Res. 2005;65(14):6178–88.

    Article  CAS  PubMed  Google Scholar 

  97. Staller P, Sulitkova J, Lisztwan J, Moch H, Oakeley EJ, Krek W. Chemokine receptor CXCR4 downregulated by von Hippel-Lindau tumour suppressor pVHL. Nature. 2003;425(6955):307–11.

    Article  CAS  PubMed  Google Scholar 

  98. Pan J, Mestas J, Burdick MD, Phillips RJ, Thomas GV, Reckamp K, et al. Stromal derived factor-1 (SDF-1/CXCL12) and CXCR4 in renal cell carcinoma metastasis. Mol Cancer. 2006. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1476-4598-5-56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Bao Y, Wang Z, Liu B, Lu X, Xiong Y, Shi J, et al. A feed-forward loop between nuclear translocation of CXCR4 and HIF-1alpha promotes renal cell carcinoma metastasis. Oncogene. 2019;38(6):881–95.

    Article  CAS  PubMed  Google Scholar 

  100. Rasti A, Abolhasani M, Zanjani LS, Asgari M, Mehrazma M, Madjd Z. Reduced expression of CXCR4, a novel renal cancer stem cell marker, is associated with high-grade renal cell carcinoma. J Cancer Res Clin Oncol. 2017;143(1):95–104.

    Article  CAS  PubMed  Google Scholar 

  101. Ladikou EE, Chevassut T, Pepper CJ, Pepper AG. Dissecting the role of the CXCL12/CXCR4 axis in acute myeloid leukaemia. Br J Haematol. 2020;189(5):815–25.

    Article  CAS  PubMed  Google Scholar 

  102. Carnero A, Lleonart M. The hypoxic microenvironment: a determinant of cancer stem cell evolution. BioEssays. 2016;38(Suppl 1):S65-74.

    PubMed  Google Scholar 

  103. Jonasch E, Walker CL, Rathmell WK. Clear cell renal cell carcinoma ontogeny and mechanisms of lethality. Nat Rev Nephrol. 2021;17(4):245–61.

    Article  CAS  PubMed  Google Scholar 

  104. Pallikonda HA, Turajlic S. Predicting cancer evolution for patient benefit: renal cell carcinoma paradigm. Biochim Biophys Acta Rev Cancer. 2022;1877(5):188759.

    Article  CAS  PubMed  Google Scholar 

  105. Kumar S, Liu J, McMahon AP. Defining the acute kidney injury and repair transcriptome. Semin Nephrol. 2014;34(4):404–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Maeshima A, Takahashi S, Nakasatomi M, Nojima Y. Diverse cell populations involved in regeneration of renal tubular epithelium following acute kidney injury. Stem Cells Int. 2015. https://doiorg.publicaciones.saludcastillayleon.es/10.1155/2015/964849.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Kumar S. Cellular and molecular pathways of renal repair after acute kidney injury. Kidney Int. 2018;93(1):27–40.

    Article  CAS  PubMed  Google Scholar 

  108. Kirita Y, Chang-Panesso M, Humphreys BD. Recent insights into kidney injury and repair from transcriptomic analyses. Nephron. 2019;143(3):162–5.

    Article  CAS  PubMed  Google Scholar 

  109. Little MH, Kairath P. Does renal repair recapitulate kidney development? J Am Soc Nephrol. 2017;28(1):34–46.

    Article  CAS  PubMed  Google Scholar 

  110. Chang-Panesso M, Humphreys BD. Cellular plasticity in kidney injury and repair. Nat Rev Nephrol. 2017;13(1):39–46.

    Article  CAS  PubMed  Google Scholar 

  111. McMahon AP. Development of the mammalian kidney. Curr Top Dev Biol. 2016. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/bs.ctdb.2015.10.010.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Balzer MS, Rohacs T, Susztak K. How many cell types are in the kidney and what do they do? Annu Rev Physiol. 2022. https://doiorg.publicaciones.saludcastillayleon.es/10.1146/annurev-physiol-052521-121841.

    Article  CAS  PubMed  Google Scholar 

  113. Schumacher A, Rookmaaker MB, Joles JA, Kramann R, Nguyen TQ, van Griensven M, et al. Defining the variety of cell types in developing and adult human kidneys by single-cell RNA sequencing. NPJ Regen Med. 2021;6(1):45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Michos O. Kidney development: from ureteric bud formation to branching morphogenesis. Curr Opin Genet Dev. 2009;19(5):484–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Rock R, Rizzo L, Lienkamp SS. Kidney development: recent insights from technological advances. Physiology. 2022. https://doiorg.publicaciones.saludcastillayleon.es/10.1152/physiol.00041.2021.

    Article  CAS  Google Scholar 

  116. Huang J, Kong Y, Xie C, Zhou L. Stem/progenitor cell in kidney: characteristics, homing, coordination, and maintenance. Stem Cell Res Ther. 2021;12(1):197.

    Article  PubMed  PubMed Central  Google Scholar 

  117. Eymael J, Smeets B. Origin and fate of the regenerating cells of the kidney. Eur J Pharmacol. 2016. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.ejphar.2016.07.030.

    Article  CAS  PubMed  Google Scholar 

  118. Dekel B, Zangi L, Shezen E, Reich-Zeliger S, Eventov-Friedman S, Katchman H, et al. Isolation and characterization of nontubular sca-1+lin- multipotent stem/progenitor cells from adult mouse kidney. J Am Soc Nephrol. 2006;17(12):3300–14.

    Article  PubMed  Google Scholar 

  119. Lee PT, Lin HH, Jiang ST, Lu PJ, Chou KJ, Fang HC, et al. Mouse kidney progenitor cells accelerate renal regeneration and prolong survival after ischemic injury. Stem Cells. 2010;28(3):573–84.

    Article  CAS  PubMed  Google Scholar 

  120. Maeshima A, Yamashita S, Nojima Y. Identification of renal progenitor-like tubular cells that participate in the regeneration processes of the kidney. J Am Soc Nephrol. 2003;14(12):3138–46.

    Article  PubMed  Google Scholar 

  121. Oliver JA, Maarouf O, Cheema FH, Martens TP, Al-Awqati Q. The renal papilla is a niche for adult kidney stem cells. J Clin Invest. 2004;114(6):795–804.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Kang HM, Huang S, Reidy K, Han SH, Chinga F, Susztak K. Sox9-positive progenitor cells play a key role in renal tubule epithelial regeneration in mice. Cell Rep. 2016;14(4):861–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Kitamura S, Yamasaki Y, Kinomura M, Sugaya T, Sugiyama H, Maeshima Y, et al. Establishment and characterization of renal progenitor like cells from S3 segment of nephron in rat adult kidney. FASEB J. 2005;19(13):1789–97.

    Article  CAS  PubMed  Google Scholar 

  124. Gupta S, Verfaillie C, Chmielewski D, Kren S, Eidman K, Connaire J, et al. Isolation and characterization of kidney-derived stem cells. J Am Soc Nephrol. 2006;17(11):3028–40.

    Article  CAS  PubMed  Google Scholar 

  125. Challen GA, Bertoncello I, Deane JA, Ricardo SD, Little MH. Kidney side population reveals multilineage potential and renal functional capacity but also cellular heterogeneity. J Am Soc Nephrol. 2006;17(7):1896–912.

    Article  CAS  PubMed  Google Scholar 

  126. Bussolati B, Dekel B, Azzarone B, Camussi G. Human renal cancer stem cells. Cancer Lett. 2012;338(1):141–6.

    Article  PubMed  Google Scholar 

  127. Li J, Ariunbold U, Suhaimi N, Sunn N, Guo J, McMahon JA, et al. Collecting duct-derived cells display mesenchymal stem cell properties and retain selective in vitro and in vivo epithelial capacity. J Am Soc Nephrol. 2015;26(1):81–94.

    Article  PubMed  Google Scholar 

  128. Wang Y, Zhao Y, Zhao Z, Li D, Nie H, Sun Y, et al. Single-cell RNA-Seq analysis identified kidney progenitor cells from human urine. Protein Cell. 2021;12(4):305–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Hou W, Ji Z. Generation of autochthonous mouse models of clear cell renal cell carcinoma: mouse models of renal cell carcinoma. Exp Mol Med. 2018;50(4):1–10.

    Article  CAS  PubMed  Google Scholar 

  130. Kim HAJ, Shaikh MH, Lee M, Zeng PYF, Sorgini A, Akintola T, et al. 3p arm loss and survival in head and neck cancer: an analysis of TCGA dataset. Cancers. 2021. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/cancers13215313.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Lounis H, Mes-Masson AM, Dion F, Bradley WE, Seymour RJ, Provencher D, et al. Mapping of chromosome 3p deletions in human epithelial ovarian tumors. Oncogene. 1998;17(18):2359–65.

    Article  CAS  PubMed  Google Scholar 

  132. Martinez A, Walker RA, Shaw JA, Dearing SJ, Maher ER, Latif F. Chromosome 3p allele loss in early invasive breast cancer: detailed mapping and association with clinicopathological features. Mol Pathol. 2001;54(5):300–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Knebelmann B, Ananth S, Cohen HT, Sukhatme VP. Transforming growth factor alpha is a target for the von Hippel-Lindau tumor suppressor. Cancer Res. 1998;58(2):226–31.

    CAS  PubMed  Google Scholar 

  134. Ganner A, Gehrke C, Klein M, Thegtmeier L, Matulenski T, Wingendorf L, et al. VHL suppresses RAPTOR and inhibits mTORC1 signaling in clear cell renal cell carcinoma. Sci Rep. 2021;11(1):14827.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Kaelin WG Jr. The VHL tumor suppressor gene: insights into oxygen sensing and cancer. Trans Am Clin Climatol Assoc. 2017;128:298–307.

    PubMed  PubMed Central  Google Scholar 

  136. Semenza GL. Regulation of cancer cell metabolism by hypoxia-inducible factor 1. Semin Cancer Biol. 2009;19(1):12–6.

    Article  CAS  PubMed  Google Scholar 

  137. Kim M, Katayose Y, Li Q, Rakkar AN, Li Z, Hwang SG, et al. Recombinant adenovirus expressing Von Hippel-Lindau-mediated cell cycle arrest is associated with the induction of cyclin-dependent kinase inhibitor p27Kip1. Biochem Biophys Res Commun. 1998;253(3):672–7.

    Article  CAS  PubMed  Google Scholar 

  138. Devarajan P, De Leon M, Talasazan F, Schoenfeld AR, Davidowitz EJ, Burk RD. The von Hippel-Lindau gene product inhibits renal cell apoptosis via Bcl-2-dependent pathways. J Biol Chem. 2001;276(44):40599–605.

    Article  CAS  PubMed  Google Scholar 

  139. Razorenova OV, Castellini L, Colavitti R, Edgington LE, Nicolau M, Huang X, et al. The apoptosis repressor with a CARD domain (ARC) gene is a direct hypoxia-inducible factor 1 target gene and promotes survival and proliferation of VHL-deficient renal cancer cells. Mol Cell Biol. 2014;34(4):739–51.

    Article  PubMed  PubMed Central  Google Scholar 

  140. Zhang J, Zhang Q. VHL and hypoxia signaling: beyond HIF in cancer. Biomedicines. 2018. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/biomedicines6010035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Raval RR, Lau KW, Tran MG, Sowter HM, Mandriota SJ, Li JL, et al. Contrasting properties of hypoxia-inducible factor 1 (HIF-1) and HIF-2 in von Hippel-Lindau-associated renal cell carcinoma. Mol Cell Biol. 2005;25(13):5675–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Hu CJ, Wang LY, Chodosh LA, Keith B, Simon MC. Differential roles of hypoxia-inducible factor 1alpha (HIF-1alpha) and HIF-2alpha in hypoxic gene regulation. Mol Cell Biol. 2003;23(24):9361–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Roe JS, Kim H, Lee SM, Kim ST, Cho EJ, Youn HD. p53 stabilization and transactivation by a von Hippel-Lindau protein. Mol Cell. 2006;22(3):395–405.

    Article  CAS  PubMed  Google Scholar 

  144. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013;500(7463):415–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Davis CF, Ricketts CJ, Wang M, Yang L, Cherniack AD, Shen H, et al. The somatic genomic landscape of chromophobe renal cell carcinoma. Cancer Cell. 2014;26(3):319–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Duchi S, Fagnocchi L, Cavaliere V, Hsouna A, Gargiulo G, Hsu T. Drosophila VHL tumor-suppressor gene regulates epithelial morphogenesis by promoting microtubule and aPKC stability. Development. 2010;137(9):1493–503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Hergovich A, Lisztwan J, Barry R, Ballschmieter P, Krek W. Regulation of microtubule stability by the von Hippel-Lindau tumour suppressor protein pVHL. Nat Cell Biol. 2003;5(1):64–70.

    Article  CAS  PubMed  Google Scholar 

  148. Thoma CR, Toso A, Gutbrodt KL, Reggi SP, Frew IJ, Schraml P, et al. VHL loss causes spindle misorientation and chromosome instability. Nat Cell Biol. 2009;11(8):994–1001.

    Article  CAS  PubMed  Google Scholar 

  149. Metcalf JL, Bradshaw PS, Komosa M, Greer SN, Stephen Meyn M, Ohh M. K63-ubiquitylation of VHL by SOCS1 mediates DNA double-strand break repair. Oncogene. 2014;33(8):1055–65.

    Article  CAS  PubMed  Google Scholar 

  150. Liu P, Gan W, Su S, Hauenstein AV, Fu TM, Brasher B, et al. K63-linked polyubiquitin chains bind to DNA to facilitate DNA damage repair. Sci Signal. 2018. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/scisignal.aar8133.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Espana-Agusti J, Warren A, Chew SK, Adams DJ, Matakidou A. Loss of PBRM1 rescues VHL dependent replication stress to promote renal carcinogenesis. Nat Commun. 2017;8(1):2026.

    Article  PubMed  PubMed Central  Google Scholar 

  152. Li N, Grivennikov SI, Karin M. The unholy trinity: inflammation, cytokines, and STAT3 shape the cancer microenvironment. Cancer Cell. 2011;19(4):429–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Lyssiotis CA, Kimmelman AC. Metabolic interactions in the tumor microenvironment. Trends Cell Biol. 2017;27(11):863–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Vuong L, Kotecha RR, Voss MH, Hakimi AA. Tumor microenvironment dynamics in clear-cell renal cell carcinoma. Cancer Discov. 2019;9(10):1349–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. de Vivar Chevez AR, Finke J, Bukowski R. The role of inflammation in kidney cancer. Adv Exp Med Biol. 2014. https://doiorg.publicaciones.saludcastillayleon.es/10.1007/978-3-0348-0837-8_9.

    Article  CAS  PubMed  Google Scholar 

  156. Pritchett TL, Bader HL, Henderson J, Hsu T. Conditional inactivation of the mouse von Hippel-Lindau tumor suppressor gene results in wide-spread hyperplastic, inflammatory and fibrotic lesions in the kidney. Oncogene. 2015;34(20):2631–9.

    Article  CAS  PubMed  Google Scholar 

  157. Tan W, Hildebrandt MA, Pu X, Huang M, Lin J, Matin SF, et al. Role of inflammatory related gene expression in clear cell renal cell carcinoma development and clinical outcomes. J Urol. 2011;186(5):2071–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Zhao Y, Dong Q, Li J, Zhang K, Qin J, Zhao J, et al. Targeting cancer stem cells and their niche: perspectives for future therapeutic targets and strategies. Semin Cancer Biol. 2018. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.semcancer.2018.08.002.

    Article  CAS  PubMed  Google Scholar 

  159. Ju F, Atyah MM, Horstmann N, Gul S, Vago R, Bruns CJ, et al. Characteristics of the cancer stem cell niche and therapeutic strategies. Stem Cell Res Ther. 2022;13(1):233.

    Article  PubMed  PubMed Central  Google Scholar 

  160. Manneken JD, Currie PD. Macrophage-stem cell crosstalk: regulation of the stem cell niche. Development. 2023. https://doiorg.publicaciones.saludcastillayleon.es/10.1242/dev.201510.

    Article  CAS  PubMed  Google Scholar 

  161. Gilkes DM, Semenza GL, Wirtz D. Hypoxia and the extracellular matrix: drivers of tumour metastasis. Nat Rev Cancer. 2014;14(6):430–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Diaz-Montero CM, Rini BI, Finke JH. The immunology of renal cell carcinoma. Nat Rev Nephrol. 2020;16(12):721–35.

    Article  PubMed  Google Scholar 

  163. Wels J, Kaplan RN, Rafii S, Lyden D. Migratory neighbors and distant invaders: tumor-associated niche cells. Genes Dev. 2008;22(5):559–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Chen P, Hsu WH, Han J, Xia Y, DePinho RA. Cancer stemness meets immunity: from mechanism to therapy. Cell Rep. 2021;34(1):108597.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Ribatti D, Tamma R, Annese T. The role of vascular niche and endothelial cells in organogenesis and regeneration. Exp Cell Res. 2021;398(1):112398.

    Article  CAS  PubMed  Google Scholar 

  166. Rafty LA, Khachigian LM. von Hippel-Lindau tumor suppressor protein represses platelet-derived growth factor B-chain gene expression via the Sp1 binding element in the proximal PDGF-B promoter. J Cell Biochem. 2002;85(3):490–5.

    Article  CAS  PubMed  Google Scholar 

  167. Norman JT, Clark IM, Garcia PL. Hypoxia promotes fibrogenesis in human renal fibroblasts. Kidney Int. 2000;58(6):2351–66.

    Article  CAS  PubMed  Google Scholar 

  168. Berg JT, Breen EC, Fu Z, Mathieu-Costello O, West JB. Alveolar hypoxia increases gene expression of extracellular matrix proteins and platelet-derived growth factor-B in lung parenchyma. Am J Respir Crit Care Med. 1998;158(6):1920–8.

    Article  CAS  PubMed  Google Scholar 

  169. Ohh M, Yauch RL, Lonergan KM, Whaley JM, Stemmer-Rachamimov AO, Louis DN, et al. The von Hippel-Lindau tumor suppressor protein is required for proper assembly of an extracellular fibronectin matrix. Mol Cell. 1998;1(7):959–68.

    Article  CAS  PubMed  Google Scholar 

  170. Bluyssen HA, Lolkema MP, van Beest M, Boone M, Snijckers CM, Los M, et al. Fibronectin is a hypoxia-independent target of the tumor suppressor VHL. FEBS Lett. 2004;556(1–3):137–42.

    Article  CAS  PubMed  Google Scholar 

  171. Erler JT, Bennewith KL, Cox TR, Lang G, Bird D, Koong A, et al. Hypoxia-induced lysyl oxidase is a critical mediator of bone marrow cell recruitment to form the premetastatic niche. Cancer Cell. 2009;15(1):35–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Cox TR, Bird D, Baker AM, Barker HE, Ho MW, Lang G, et al. LOX-mediated collagen crosslinking is responsible for fibrosis-enhanced metastasis. Cancer Res. 2013;73(6):1721–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Munoz-Najar UM, Neurath KM, Vumbaca F, Claffey KP. Hypoxia stimulates breast carcinoma cell invasion through MT1-MMP and MMP-2 activation. Oncogene. 2006;25(16):2379–92.

    Article  CAS  PubMed  Google Scholar 

  174. Choi JY, Jang YS, Min SY, Song JY. Overexpression of MMP-9 and HIF-1alpha in breast cancer cells under hypoxic conditions. J Breast Cancer. 2011;14(2):88–95.

    Article  PubMed  PubMed Central  Google Scholar 

  175. Petrella BL, Lohi J, Brinckerhoff CE. Identification of membrane type-1 matrix metalloproteinase as a target of hypoxia-inducible factor-2 alpha in von Hippel-Lindau renal cell carcinoma. Oncogene. 2005;24(6):1043–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. Lasorsa F, Rutigliano M, Milella M, Ferro M, Pandolfo SD, Crocetto F, et al. Cellular and molecular players in the tumor microenvironment of renal cell carcinoma. J Clin Med. 2023. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/jcm12123888.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Wang Z, Yip LY, Lee JHJ, Wu Z, Chew HY, Chong PKW, et al. Methionine is a metabolic dependency of tumor-initiating cells. Nat Med. 2019;25(5):825–37.

    Article  CAS  PubMed  Google Scholar 

  178. Strekalova E, Malin D, Weisenhorn EMM, Russell JD, Hoelper D, Jain A, et al. S-adenosylmethionine biosynthesis is a targetable metabolic vulnerability of cancer stem cells. Breast Cancer Res Treat. 2019;175(1):39–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Zhang C, Du Z, Gao Y, Lim KS, Zhou W, Huang H, et al. Methionine secreted by tumor-associated pericytes supports cancer stem cells in clear cell renal carcinoma. Cell Metab. 2024;36(4):778–92.

    Article  CAS  PubMed  Google Scholar 

  180. Hoadley KA, Yau C, Hinoue T, Wolf DM, Lazar AJ, Drill E, et al. Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer. Cell. 2018;173(2):291–304.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  181. Barriga FM, Tsanov KM, Ho YJ, Sohail N, Zhang A, Baslan T, et al. MACHETE identifies interferon-encompassing chromosome 9p21.3 deletions as mediators of immune evasion and metastasis. Nat Cancer. 2022;3(11):1367–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Hsu T. Complex cellular functions of the von Hippel-Lindau tumor suppressor gene: insights from model organisms. Oncogene. 2012;31(18):2247–57.

    Article  CAS  PubMed  Google Scholar 

  183. Cheung MD, Erman EN, Moore KH, Lever JM, Li Z, LaFontaine JR, et al. Resident macrophage subpopulations occupy distinct microenvironments in the kidney. JCI Insight. 2022. https://doiorg.publicaciones.saludcastillayleon.es/10.1172/jci.insight.161078.

    Article  PubMed  PubMed Central  Google Scholar 

  184. Bussolati B, Moggio A, Collino F, Aghemo G, D’Armento G, Grange C, et al. Hypoxia modulates the undifferentiated phenotype of human renal inner medullary CD133+ progenitors through Oct4/miR-145 balance. Am J Physiol Renal Physiol. 2012;302(1):F116–28.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank the Hsu laboratory members for stimulating discussion.

Funding

This work is supported by a grant to T.H. from National Science and Technology Council-Taiwan (#NSTC 112–2320-B-039–019) with supplemental funding from the China Medical University-Taiwan (#CMU112-MF-03), and a grant to T.H. from National Health Research Institute-Taiwan (#NHRI-EX111-11101BI). The Hsu lab is also supported by Taiwan Bio-Development Foundation (TBF) Chair Professorship.

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D.-X. P. collected and reviewed the literature, and wrote the original draft of the manuscript. T.H. collected and reviewed the literature, and finalized the manuscript.

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Correspondence to Tien Hsu.

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Pham, DX., Hsu, T. Tumor-initiating and metastasis-initiating cells of clear-cell renal cell carcinoma. J Biomed Sci 32, 17 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12929-024-01111-9

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