Heterogeneity of Colorectal Cancer Liver Metastasis: History
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Contributor:
Hao Chen
,
Chongya Zhai
,
Xian Xu
,
Haidong Wang
,
Weidong Han
,
Jiaying Shen

Colorectal cancer (CRC) is a disease with a high incidence and mortality rate. The number of new CRC cases worldwide reached 1.93 million in 2020, ranking third after breast cancer and lung cancer. The number of CRC-related deaths reached 940,000, making it the second most deadly tumor globally. In China, according to the 2016 national cancer statistics published by the National Cancer Center, a total of 4.06 million tumor patients were diagnosed in 2016, with approximately 408,000 being CRC patients. Among these cases, approximately 196,000 CRC patients died, accounting for 8.10% of the total. A comprehensive overview of the spatial heterogeneity of CRLM at different molecular levels is discussed, including genetics, metabolism, and immune levels. 

  • colorectal cancer liver metastasis
  • heterogeneity
  • gene
  • transcriptome
  • protein
  • metabolism
  • immune

1. Genetic Heterogeneity

The adenoma–carcinoma sequence underlies the development of CRC and involves many changes, including tumor suppressor gene inactivation (APC, TP53), oncogene activation (BRAF, PI3KA, and RAS), chromosomal instability (CIN), CpG island methylation phenotype (CIMP), and microsatellite instability (MSI) pathways [1][2]. These alterations result in a highly unstable genome in CRC. However, when exploring the sources of genetic heterogeneity in CRLM, researchers were surprised to find little genetic heterogeneity between primary CRC and CRLM.

1.1. Key Driver Genes

There are five key driver genes, APC, TP53, RAS, BRAF, and PIK3CA, that play a critical role in the adenoma–carcinoma sequence of CRC, and the mutational status of these genes can influence the clinical outcome of CRC patients. Patients with KRAS wild-type tumors had significantly better clinical outcomes than patients with KRAS mutation tumors [3]. Patients with BRAF mutation and PIK3CA mutation tumors also showed poorer clinical outcomes [4][5]. Therefore, researchers summarize the heterogeneity of these five genes among CRLM patients. These genes did not show heterogeneity between the primary tumor and the corresponding liver metastasis [6][7][8][9][10]. Brunsell et al. examined mutation sites in KRAS, BRAF, and PIK3CA in 20 CRLM patients and found the same mutation status in 18 patients with primary tumor and liver metastasis [6]. Hou et al. investigated the heterogeneity of the KRAS pathway in CRC and found that the frequency of KRAS mutations was significantly higher in the lung (62.0%) and brain (56.5%) than in the liver (32.5%). Thus, KRAS mutation could be an independent predictor of lung metastasis but played a less significant role in CRLM [11]. Another study reached a similar conclusion [12]. In addition to the five genes mentioned above, SMAD4 is a key regulator of the TGFβ signaling pathway, which inhibits cell proliferation, promotes apoptosis, and regulates epithelial–mesenchymal transition (EMT) [13]. Itatani et al. found that the knockdown of SMAD4 led to a significant increase in the expression of CCL15, which led to the aggregation of CCR1+ myeloid cells in hepatic metastases and contributed to CRC cells colonizing the liver in the early stages of liver metastasis [14]. Although deletion of the SMAD4 gene is associated with tumor progression, metastasis, and poor prognosis, two other studies concluded that the mutation profiles of SMAD4 are highly concordant in primary CRC and CRLM [9][15].

1.2. Chromosomal Instability (CIN)

CIN is a common feature of solid tumors, including CRC, and causes genomic instability in approximately 70% of CRC patients [1][16]. CIN includes instability of the chromosome number (numerical CIN) and instability of the chromosome structure (structural CIN); numerical CIN refers to the increase or decrease of chromosome copy number; and structural CIN includes deletions, translocations, and derivative chromosomes, among others [17].
Previous studies found that chromosome instability is significantly higher in metastatic breast cancer cells than in primary cells, and it is also a driver of metastasis [18]. In CRC, some studies reached the same conclusion [19][20][21][22]. Mamlouk et al. found through whole-genome sequencing that the CNVs of the MMP9 and CDX2 genes were significantly increased in CRLM [22]. MMP9 belongs to the matrix metalloproteinase family, which can degrade various protein components in the extracellular matrix (ECM) and disrupt the histological barrier that prevents tumor cell invasion, and therefore plays a key role in tumor invasion and metastasis [23]. CDX2 is involved in the proliferation and differentiation of intestinal epithelial cells [24].
Nonetheless, some studies have come to the opposite conclusion. Leonie used a high-resolution array of comparative genomic hybridization to study 62 primary colorectal cancers and 68 matched metastatic lesions (22 liver, 11 lung, 12 ovary, 12 omentum, and 11 distant lymph nodes). They found that patterns of DNA copy number aberrations were highly similar between all primary and metastatic lesions [25]. Through allelic copy number analysis of 33 CRC samples, Shogo identified several chromosomal aberrations common in CRC patients, with gains on 20p13-p12.1 and 20q11.21-q13.33 and loss of heterozygosity (LOH) on 6q14.1-q25.1 more common in CRLM patients. Through genetic analysis of metastatic lesions, they found that allelic imbalances in CRLM were very similar to those in primary CRC and these aberrations on chromosomes 20p, 20q, and 6q were also present in CRLM, which suggests that they may promote CRLM [26]. Previous studies have also shown that only a few mutations are needed to transform highly aggressive tumor cells into metastatic ones [27]. These results indicate that CRC cells maintain relative chromosome stability during metastasis.

1.3. Microsatellite Instability (MSI) Status

Approximately 15% of CRC patients are affected by MSI pathways [28]. MSI is caused by functional defects in genes such as DNA mismatch repair genes (hMSH2, hMLH1, hMSH3, hMSH6, hPMSH1, and hPMSH2). Currently, there are two main methods to detect MSI status as follows: (1) immunohistochemistry (IHC), which detects the expression of four mismatch repair proteins (MLH1, PMS2, MSH2, and MSH6) in the nucleus to detect the presence of mismatch function defects, and (2) molecular testing, which detects the length of microsatellite sequences in tumor tissue to determine whether MSI is present at the site. Through IHC and molecular assays, current studies found a very high similarity of MSI status between primary CRC and CRLM [29][30][31][32]. Among them, He et al. and Jung et al. found partial differences, but the differences were concentrated in peritoneal and ovarian metastasis, and no differences were found in CRLM [29][31].

2. Metabolic Heterogeneity

Metabolic reprogramming is one of the hallmarks of cancer [33]. Compared with normal tissues, tumor cells often require more energy to maintain their growth. Due to the different microenvironments of metastatic organs, tumor cells still need to undergo metabolic reprogramming to obtain energy for growth in different metastatic organs.
Tumor cells are often in a state of aerobic glycolysis, the so-called “Warburg effect”, and even with sufficient oxygen, cells prioritize glycolysis to quickly generate energy rather than through the tricarboxylic acid cycle (TCA cycle). After CRLM, some specific growth factors and enzymes in the liver make this effect more obvious in metastatic lesions. The expression of glucose transporter 3 (GLUT3) and pyruvate kinase muscle isozyme 2 (PKM2) is also significantly higher in CRLM [34]. Increased glucose uptake mediated by GLUT3 can promote the occurrence of various tumors including liver cancer, breast cancer, and lung cancer [35][36][37]. The overexpression of GLUT3 activates Yes-associated protein (YAP), which in turn promotes the expression of GLUT3 and glycolytic genes; conversely, the expression of GLUT3 and glycolytic genes is decreased after YAP is knocked down. Meanwhile, YAP also interacts with PKM2 through the WW domain and collectively enhances the expression of GLUT3. GLUT3 and YAP/PKM2 constitute a positive feedback pathway that enhances glycolysis in CRLM [34]. Some studies have also reported the mechanism of GLUT3 upregulation in CRLM. High mobility group proteins (HMGs) are a class of structural transcription factors that do not have transcriptional activity, but they can regulate the transcription of target genes by binding with their structures. Yang et al. found that HMGA1 can promote the expression of GLUT3 in CRLM and thereby enhance the GLUT3-YAP signaling pathway [38].
Next, the expression of phosphorylated PKM2 is higher in CRLM than in primary CRC, it can act as a transcriptional cofactor for hypoxia-inducing Factor 1 (HIF-1), and it promotes the expression of glycolytic genes including LDHA, PDK1, and SLC2A1 (GLUT1) [39]. In addition to the two proteins PKM2 and GLUT3, Deng et al. also identified another differentially expressed protein, Dickkopf-associated protein 2 (DKK2), which promotes aerobic glycolysis in CRC cells [40]. By comparing the proteomes of primary CRC and CRLM from seven patients, Fahrner et al. found that most of the proteins upregulated in CRLM were involved in glucose metabolism, including pyruvate carboxylase, fructose-bisphosphate aldolase B, and fructose-1,6-bisphosphatase 1 [41]. Finally, according to Bu et al., the expression of aldolase B (ALDOB), an enzyme involved in fructose metabolism, is increased in CRLM, and overexpressed ALDOB enhances fructose metabolism and thereby generates more propanose phosphate [42]. The production of large amounts of propyl phosphate also promotes glycolysis in CRC cells.
In addition, enhanced cholesterol synthesis and upregulated expression of some fatty acids, acylcarnitines, and polyamines have also been found in CRLM [43][44]. As previously described, SREBP2 is a key transcription factor for lipid synthesis. Zhang et al. found that the expression of SREBP2 and its downstream target genes, LDLR and SRB1, were significantly upregulated in CRLM [43]. These authors subsequently knocked down SREBP2 and found that total cholesterol levels in tumor cells were significantly reduced and tumor cell growth was restricted. After screening several liver-rich growth factors, they finally found that hepatocyte growth factor (HGF) in the liver promotes the PI3K/AKT/mTOR pathway, which stimulates SREBP2 and stimulates cholesterol synthesis in CRLM [43]. Finally, Williams et al. found that several phosphatidylcholines, carnitine, bile acids, nucleotides, oxidative compounds (glutathione), and polyamines (putrescine) were expressed significantly higher in CRLM than in primary CRC [44]. Glutathione (GSH) protects cells against oxidative stress and polyamines are important growth factors needed for cell growth.
Overall, researchers show in Table 1 the changes in metabolic reprogramming of CRLM that allow CRC cells to adapt more quickly to the metabolic state of the liver and thereby promote their growth in the liver. From the table, researchers can determine that glycolysis-related heterogeneity is the most obvious, which is probably because glycolysis can generate a large amount of energy, and it provides energy in the process of CRC cell metastasis and colonization in the liver. Furthermore, the other metabolites also upregulate and promote the growth of CRC cells. From the conclusion, researchers identify that CRLM possesses a more active metabolic state to maintain cell growth compared to primary CRC.
Table 1. Summary of metabolic heterogeneity in CRLM (↑: upregulated).
Items Factors Change References
Aerobic glycolysis GLUT3, HMGA1, PKM2, DKK2, Pyruvate carboxylase, Fructose-bisphosphate aldolase B, Fructose-1,6-bisphosphatase 1 ↑ [34][38][39][40][41]
Fructose metabolism ALDOB ↑ [42]
Cholesterol metabolism SREBP2, LDLR, SRB1 ↑ [43]
Fatty acids, acylcarnitines, oxidative compounds, polyamines GSH, putrescine ↑ [44]

3. Immune Heterogeneity

The immune microenvironment of tumors is a complex system, and immune cells in the microenvironment have been shown to influence tumor progression and response to immunotherapy [45][46]. Current research on the heterogeneity of the immune microenvironment is still mainly focused on immune cells. During tumor metastasis, immune cells are dynamically heterogeneous, which means that cell types, numbers, and sizes change [47].

3.1. Macrophages

Tumor-associated macrophages (TAMs) are closely associated with tumor progression and angiogenesis [48]. SPP1+ TAMs are immunosuppressive cells that are reported to be highly expressed in CRC compared to normal tissues, which can promote CRC progression and metastasis, and are also associated with the prognosis and response to immunotherapy in CRC patients [49][50]. Liu et al. found that SPP1+ TAMs are malignancy-associated and are linked to CRLM [51]. The angiogenesis and phagocytosis properties of three types of TAMs, MKI67+ TAMs, SPP1+ TAMs, and C1QC+ TAMs were also compared in the context of CRC. Results revealed that SPP1+ TAMs possessed the strongest angiogenic function, which confirmed their immunosuppressive and protumorigenic functions. Wu et al. used single-cell RNA sequencing and spatial transcriptomics to determine 97 CRC-paired samples and derived a single-cell spatial map of CRLM [52]. Results demonstrated that MRC1+ CCL18+ TAMs, SPP1+ TAMs, and neutrophils were significantly increased in CRLM compared to matched primary CRC. Neutrophils are reported to be potential tumor-promoting cells [53]. Wu et al. focused their research on MRC1+ CCL18+ TAMs. They suggested that MRC1+ CCL18+ TAMs might originate from Kupffer cells in the liver and found that M2 polarization-related genes (APOE, MARCO) were significantly upregulated in MRC1+ CCL18+ TAMs of CRLM, while MRC1+ CCL18+ TAMs of primary CRC showed higher expression of inflammatory cytokines (TNF, IL1B, CCL3, and CCL4). Additionally, they found that the MRC1+ CCL18+ TAMs of CRLM possessed strong metabolic activity, mainly in terms of phenylalanine metabolism, whereas the MRC1+ CCL18+ TAMs of CRC were dominated by oxidative phosphorylation. Moreover, both SPP1+ TAMs and MRC1+ CCL18+ TAMs showed enhanced antigen processing and presentation and complex activity. Tu et al. also found more TAM enrichment in CRLM and dominance of M2 TAMs [54]. This phenomenon was associated with the elevated expression of TCF4 in CRLM. TCF4, a transcription factor involved in the WNT/TCF signaling pathway, recruits TAMs and promotes TAM M2 polarization mainly by promoting the expression of two monocyte chemokines, CCL2 and CCR2.
In addition, earlier studies have shown that macrophages are morphologically heterogeneous. For example, M1-like macrophages are often round or flat, whereas M2-like macrophages are elongated [55][56], and macrophages acquire different geometries in different tissues [57][58]. Therefore, it is conceivable that during CRC metastasis to the liver, macrophages change not only in type and gene expression but also in morphology. Donadon et al. investigated this phenomenon and found a significant increase in the area and circumference of macrophages in CRLM, which they termed large (L-TAMs) macrophages [59]. These L-TAMs have a strong lipid-metabolizing capacity, while inflammation-related pathways (leukocyte extravasation, acute phase response, and NF-κB signaling) are downregulated. Finally, both complement-related pathways and their genes were highly expressed in these L-TAMs, which is a result that is consistent with the findings of Wu [52].

3.2. T Cells

T cells play an important role in tumor progression and metastasis. Cytotoxic T cells can secrete granzyme and perforin to kill tumor cells, while regulatory T cells (Tregs) can suppress the immune response and promote tumor cell development [60]. During tumor progression, large numbers of CD4+ T cells and CD8+ T cells are usually depleted, and studies have demonstrated that during the course of CRLM, the numbers of these two cells are significantly reduced and more CD4+FOXP3+ Tregs are found in liver metastasis [61][62]. Another study found that T helper cell (Th)17 as well as two other Tregs (Treg-IL10 and Treg-CTLA4) are enriched in primary CRC, and furthermore, the proportions of Treg-IL10 and Treg-CTLA4 in primary foci of CRC patients with the presence of liver metastases were significantly higher compared to non-metastatic CRC tumors [51]. Treg-IL10 show high expression of IL10, IL23, and IL1R1. The role of IL10 in tumors is controversial, as on the one hand, it can inhibit the function of antigen-presenting cells and block T-cell killing function against tumors, while on the other hand, it can inhibit angiogenic factors and activate CD8+ T cells [63][64]. The chronic inflammation-associated cytokine IL23 can promote tumor progression [65]. Treg-CTLA4 is highly expressed in Treg activation-related factors, including LAYN, CCR8, and TIGIT [51].

3.3. Dendritic Cells

Dendritic cells (DCs) can be divided into plasmacytoid DCs (pDCs) and conventional DCs (cDCs) in both humans and mice [66]. cDCs can be further divided into two phenotypically and functionally distinct subsets. cDC1s express Toll-like receptors (TLRs) and secrete proinflammatory cytokines, including IL-12p70 and IFN-α, to induce Th1 responses. cDC2 mainly acts as an antigen-presenting cell and activates effector T cells, including Th2 and Th17 cells [66][67]. Presently, there are few studies on the heterogeneity of dendritic cells between primary CRC and CRLM. Liu et al. identified 10 DC subsets in CRLM patients and found great heterogeneity in two types of cDC2s (cDC2-C1QC and cDC2-TIMP1) [51]. Because cDC2-C1QC was highly expressed in C1QA, CD68, CD163, and CD14, similar to the recently identified DC3 population [68][69], it was identified as DC3s. Overall, cDC2-C1QC cells showed a higher proinflammatory profile, whereas cDC2-TIMP1 cells exhibited a high expression of maturation markers (such as CCR7) and angiogenesis-related genes (EREG, CREM, and VEGFA). In addition, cDC2-TIMP1 cells expressed more anti-inflammatory genes than DC3 cells. These results revealed that cDC2-C1QC was enriched in CRC in contrast to cDC2-TIMP1, which was more abundant in CRLM.
Immune cells play a major role in the immune response to tumors, and different types of immune cells either kill tumor cells or promote their immune escape. In Table 2, researchers summarize the types of cells with the most pronounced heterogeneity in CRLM and immunosuppressive cells occupy the majority. Compared to CRC, the accumulation of these immunosuppressive cells in the liver increases the probability of immune escape from the tumor and reduces the response of CRLM to immunotherapy.
Table 2. Summary of immune heterogeneity in CRLM (↑: upregulated, ↓: downregulated).
Items Factors Change References
TAMs MRC1+ CCL18+ TAMs, SPP1+ TAMs ↑ [51][52][54]
T cells CD4+ FOXP3+ Tregs ↑ [61][62]
Th17, CD4+ T cells, CD8+ T cells, Treg-IL10, Treg-CTLA4 ↓ [51][61][62]
DCs cDC2-TIMP1 ↑ [51]
cDC2-C1QC(DC3s) ↓ [51]
Neutrophils   ↑ [52]

This entry is adapted from the peer-reviewed paper 10.3390/cancers16010059

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